CARIC 2025 Program

CO N CO R D I A U N I V E RS IT Y O F E D M O NTO N A N N UA L R E S E A RC H & I N N OVATI O N CO N FE R E N C E

A PR I L 1 0 -13, 2025

PROGRAM

TABLE OF CONTENTS

Program at a Glance

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Fine Arts Festival Schedule

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Oral Presentations Schedule

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Concerts Concordia Concert Choir: Wide Open Spaces

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Concordia Symphony Orchestra: Bruckner Symphony 4

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Abstracts and Summaries Oral Presentations

12

Posters and Displays

34

Thank You

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The CARIC 2025 Organizing Committee would like to thank our sponsors for making this event possible:

Thank you to RBC for their support through the Community Together Fund

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CUE Annual Research & Innovation Conference 2025

PROGRAM AT A GLANCE All events held at Concordia University of Edmonton; 7128 Ada Blvd All Events are FREE, with the exception of the concerts on Saturday and Sunday DAY 1: Thursday, April 10, 2025 Opening of the Fine Arts Research Festival

Location: Al and Trish Huehn Theatre

1:30 to 3:00pm

Facing the Day - GeriActors & Friends Intergenerational Theatre (location: B 346)

3:40 pm

Welcome to the Fine Arts Research Festival

4:00 - 10:00 pm

Drama Performances

DAY 2: Friday, April 11, 2025 Networking Event

Location: Tegler

3:30 pm

Welcome to the Networking Session

4:00 - 6:00 pm

Displays and Posters

Fine Arts Research Festival (continued) 5:00 - 10:00 pm

Location: Al and Trish Huehn Theatre

Drama Performances

DAY 3: Saturday, April 12, 2025 Oral Presentations / Panel Discussions

Location: HA 015

9:00 am

Welcome to the Oral Presentations Session

9:15 am – 12:00 pm

Oral presentations

12:00 – 12:40 pm

LUNCH

12:45 – 3:15 pm

Oral presentations

3:30 pm

Awarding of prizes for oral and poster presentations delivered by undergraduate and graduate students Closing remarks

CUE Annual Research & Innovation Conference 2025

3

PROGRAM AT A GLANCE All events held at Concordia University of Edmonton; 7128 Ada Blvd All Events are FREE, with the exception of the concerts on Saturday and Sunday DAY 3: Saturday, April 12, 2025 Fine Arts Research Festival (continued) 11:15 am - 6:45 pm

Location: Al and Trish Huehn Theatre

Drama Performances

Concordia Symphony Orchestra Concert 6:30 pm

Reception

7:00 pm

CSO Concert

Location: Tegler

$15 admissions ($10 for student and seniors) https://www.eventbrite.ca/e/1209174586739?aff=oddtdtcreator

DAY 4: Sunday, April 13, 2025 Fine Arts Research Festival (continued) 11:00 am - 2:00 pm

Drama Performances

4:00 pm - 10:00 pm

Drama Performances

Concordia Symphony Orchestra Concert 2:00 pm

Location: Al and Trish Huehn Theatre

Location: Tegler

Concordia Concert Choir $15 admissions ($10 for student and seniors) https://www.eventbrite.ca/e/1209158739339?aff=oddtdtcreator

3:30 pm

4

Reception

CUE Annual Research & Innovation Conference 2025

FINE ARTS RESEARCH FESTIVAL SCHEDULE

DAY 1: Thursday, April 10, 2025 1:30 to 3:00 pm

Facing the Day GeriActors & Friends Intergenerational Theatre (in B346)

4:00 to 4:45 pm

Drama Capstone Panel The creators of festival projects share their experiences

5:00 to 6:00 pm

Welcome to the Gravelands Presentation of a fantasy world created by Chenuse Aitchedji and Carlene Lloyd

6:15 to 7:00 pm

Milo and the Magical Stones A reading a children’s story book adaptation by Linnet Gee

8:00 to 9:00 pm

It Senses Now: The Musical A new musical by Nadia Myroon adapted and directed by Kat Smadis

9:15 to 10:00 pm

Choose Your Own Adventure: The Play A new play written and directed by Amelia Kuntz

DAY 2: Friday, April 11, 2025 5:00 to 5:45 pm

The Last School Bell A new play written and directed by Emma Richard

6:00 to 7:00 pm

Film vs. Live Theatre A presentation with live and filmed performance by Brianna Willner

7:15 to 8:00 pm

No. Please A play by Sean Callaghan directed by Hanna Woodman-Williams

8:15 to 8:45 pm

Roots to Blossoms Theatre A presentation on an Intergenerational Theatre project by Charles Abrahart and Mackenzie Munch

9:15 to 10:00 pm

Choose Your Own Adventure: The Play A new play written and directed by Amelia Kuntz

DAY 3: Saturday, April 12, 2025 11:15 to 12:00 pm

It Senses Now: The Musical A new musical by Nadia Myroon adapted and directed by Kat Smadis

1:30 to 2:15 pm

The Last School Bell A new play written and directed by Emma Richard

CUE Annual Research & Innovation Conference 2025

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FINE ARTS RESEARCH FESTIVAL SCHEDULE

DAY 3: Saturday, April 12, 2025 2:30 to 3:00 pm

Got what it takes A short film by Isah Bello

3:15 to 4:00 pm

Survival of the Fittest A short horror comedy film by Amanda Kalynchuk

4:15 to 5:00 pm

No. Please A play by Sean Callaghan directed by Hanna Woodman-Williams

6:15 to 6:45 pm

Sound Installation and talk by Phoenix Phillips

DAY 4: Sunday, April 13, 2025

6

11:00 to 11:30 am

Milo and the Magical Stones A reading a children’s story book adaptation by Linnet Gee

12:00 to 12:30 pm

Roots to Blossoms Theatre A presentation on an Intergenerational Theatre project by Charles Abrahart and Mackenzie Munch

12:30 to 1:15 pm

Worship the Bleak A new short film by Brianna Willner

1:30 to 2:00 pm

Got what it takes A short film by Isah Bello

4:00 to 4:45 pm

Through the Eyes of the Foreign A short film on immigration experience by Angelica Moreno and Mayra Santos

5:15 to 6:15 pm

Welcome to the Gravelands Presentation of a fantasy world created by Chenuse Aitchedji and Carlene Lloyd

6:30 to 7:30 pm

Film vs. Live Theatre A presentation with live and filmed performance by Brianna Willner

7:45 to 8:45 pm

It Senses Now: The Musical A new musical by Nadia Myroon adapted and directed by Kat Smadis

9:00 to 9:45 pm

Choose Your Own Adventure: The Play A new play written and directed by Amelia Kuntz

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION SCHEDULE

Oral Presentations - Saturday, April 12, 2025 9:00 am

Welcome and Opening Remarks

Session 1: Oral Presentations (all talks: 10 min each + 5 min Q&A) Session Moderators: Victoria Eke, Adrien Guyot, and Patrick Ndlovu

Location: HA 015

9:15 to 9:30 am

Dr. Jason Daniels, Assistant Professor Faculty of Education Digital Distraction: The Factors Related to Problematic Digital Media Use

9:30 to 9:45 am

Aran Karagonlar,Undergraduate Student Department of Mathematics and Information Technology, Faculty of Science Computational Solutions to the Classical Yang-Baxter Equation in Lie Superalgebra

9:45 to 10:00 am

Mackenzie Munch and Charles Abrahart, Undergraduate Students Department of Fine Arts, Faculty of Arts Roots to Blossoms Theatre Experience: A Research Presentation

10:00 to 10:15 am

Dr. Victoria Young, Assistant Professor Department of Social Sciences, Faculty of Arts Revisiting Safe Zones in the Post Conflict Context through State-Led Peace Agreements: A Missed Joint Relief Opportunity for the Fata Region in Pakistan and Post-Taliban Insurgency Afghanistan

10:15 to 10:30 am

Daxit Surani, Graduate Student Department of Mathematics and Information Technology, Faculty of Science Brain Tumor Detection and Classification Using Deep Learning

10:30 to 10:45 am

Justine Cramp, Undergraduate Student Department of Psychology, Faculty of Arts Reconnecting Indigenous Youth to Indigenous Cultures Through Nature, Art, Media, and Accessibility

10:45 to 11:00 am

Damilola Innomesanghan, Graduate Student Department of Information Systems Assurance Management and Information Systems Security Management, Faculty of Management Ensuring Information Security in Inclusive Digital Environments

11:00 to 11:15 am

Dr. Makan Golizeh, Associate Professor Department of Environmental and Physical Sciences, Faculty of Science AGES – The Delicious Agents of Aging

CUE Annual Research & Innovation Conference 2025

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ORAL PRESENTATION SCHEDULE

Oral Presentations - Saturday, April 12, 2025 Session 1: Oral Presentations (all talks: 10 min each + 5 min Q&A) Session Moderators: Victoria Eke, Adrien Guyot, and Patrick Ndlovu

Location: HA 015

11:15 to 11:30 am

Emma Haugen, Undergraduate Student Department of Social Sciences, Faculty of Arts “If I Had Another Choice, I Would Take It”: The Experience of Indigenous Women Who Have Hitchhiked in Western Canada

11:30 to 11:45 am

Dr. Jenna Congdon, Assistant Professor Department of Psychology, Faculty of Arts Building a Cohesive Research Program: The Importance of Local Institutional Partners, International Collaborations, and Undergraduate Student Experiences

11:45 am to 12:00 pm

Varalakshmi Yasaswi Posina, Graduate Student Department of Mathematics and Information Technology, Faculty of Science Traffic Accident Forecast System: Utilizing Artificial Intelligence for Road Safety Improvements

12:00 to 12:45 PM

LUNCH

Location: Outside HA 015

Session 2: Oral Presentations (all talks: 10 min each + 5 min Q&A) Session Moderators: Tanya Ball, Matthew Churchward, and Amro Soliman

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Location: HA 015

12:45 to 1:00 pm

Shovo Ghosh, Graduate Student Department of Information Systems Assurance Management and Information Systems Security Management, Faculty of Management Security Considerations in AI: Risks, Threats, and Mitigation Strategies

1:00 to 1:15 pm

Reema Maheshbjai Gadhia, Graduate Student Department of Mathematics and Information Technology, Faculty of Science Wildfire Detection System

1:15 to 1:30 pm

Cole Babcock, Research Assistant Department of Environmental and Physical Sciences, Faculty of Science Green AptaBeads: An Affordable Sample Preparation Technology

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION SCHEDULE

Oral Presentations - Saturday, April 12, 2025 Session 2: Oral Presentations (all talks: 10 min each + 5 min Q&A) Session Moderators: Tanya Ball, Matthew Churchward, and Amro Soliman

Location: HA 015

1:30 to 1:45 pm

Evan Labonne, Undergraduate Student Department of Biological Sciences, Faculty of Science Glucagon-like Peptide 1 and Glucagon-like Peptide 2 Promotes Short Bowel Syndrome Intestinal Adaptation: A Pilot Research Study

1:45 to 2:00 pm

Dr. Sergey Ishutov, Assistant Professor Department of Environmental and Physical Sciences, Faculty of Science Assessing Potentially Toxic Element Concentrations in Topsoil at East Pit Lake, Alberta Using Sentinel-2 Satellite Imagery and Machine Learning

2:00 to 2:15 pm

Rachel Campbell, Undergraduate Student Department of Psychology, Faculty of Arts The Influence of Planning Ahead on Speech Fluency in Adults who Stutter

2:15 to 2:30 pm

Dr. Xin Chen, Professor Department of Biological Sciences, Faculty of Science Ecological Paradoxes: When Predators Aid Victims and Resources Harm Consumers

2:30 to 2:45 pm

Boyko Zlatev, Instructor Department of Mathematics and Information Technology, Faculty of Science Statistical Modeling of Length of Reign

2:45 to 3:00 pm

Jenn Laskosky, Librarian Library Best Practices and Qualities of Recreational Dementia Friendly Reading Materials

3:00 to 3:15 pm

Dr. Wali Mohammad Abdullah, Assistant Professor Department of Mathematics and Information Technology, Faculty of Science Rails: Retrieval-Augmented Intelligence for Learning Software Development

3:15 to 3:30 PM

Graduate and Undergraduate Prizes (oral and poster/display presentations) Closing Remarks

CUE Annual Research & Innovation Conference 2025

Location: HA 015

9

SCHEDULE

Day, Month ##, 2024 | Day # | Session #

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CUE Annual Research & Innovation Conference 2025

SCHEDULE

Day, Month ##, 2024 | Day # | Session #

CUE Annual Research & Innovation Conference 2025

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Abstracts and Summaries

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CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Jason Daniels, Amanda Jarvis, Brent Bradford, and Apoorva Chauhan

Digital Distraction: The Factors Related to Problematic Digital Media Use

In the decade and a half since the emergence of smartphones in 2007, digital media has extended its reach into almost every aspect of daily life, facilitated by smartphones, tablets, and other computerized applications. The widespread adoption of mobile digital media has led to concerns about its long-term effects; however, such concerns are not new.

However, the ubiquity of digital media, its interactive nature, and its potential for immersive engagement raise unique issues regarding problematic use.

This study explores the factors associated with problematic digital media use by surveying a diverse sample of individuals to identify behavioral, cognitive, and contextual influences that contribute to excessive and potentially harmful engagement with digital media. Specifically, the study examines the relationship between problematic digital media use and psychological well-being, individual differences in self-regulation and impulsivity, and socio-emotional health.

The study employs a cross-sectional survey design, collecting data from a sample of adolescents and adults (N = 199) through an online questionnaire. The survey includes measures of problematic digital media use along with self-report measures of psychological well-being, impulsivity, selfregulation, and social connectedness. Data will be analyzed using multiple regression

models to identify significant predictors of problematic digital media use, while exploratory factor analysis will be used to examine potential underlying dimensions of problematic use.

Understanding the factors associated with problematic digital media use is critical for informing interventions aimed at promoting healthier digital habits.

Given the increasing reliance on digital media for communication, education, and entertainment, it is essential to distinguish between normative and problematic use.

This study contributes to the growing body of literature on digital media effects by identifying key risk factors and providing evidence-based insights for policymakers, educators, and mental health professionals seeking to mitigate the negative consequences of excessive digital media engagement.

This presentation will include an overview of the study’s theoretical framework, methodology, and major results.

Additionally, practical recommendations for behavior change, including strategies for self-regulation, digital well-being, and intervention approaches that can be implemented by individuals, educators, and mental health professionals will be given.

Attendees will gain insight into both the risks of problematic digital media use and actionable solutions for fostering healthier digital habits.

Faculty: EDUCATION Department: EDUCATION CUE Annual Research & Innovation Conference 2025

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ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Aran Karagonlar, Runxuan Zhang

Computational Solutions to the Classical Yang-Baxter Equation in Lie Superalgebra

The classical Yang-Baxter equation (CYBE) plays an essential role in various areas of mathematics and theoretical physics, particularly in the study of integrable systems, quantum groups, and statistical mechanics. The CYBE in the context of Lie superalgebras is a significant extension of the CYBE traditionally studied in the realm of Lie algebras. Our study aims to explore and solve the CYBE within the framework of Lie superalgebras using programming techniques, focusing specifically on the computation of solutions for the Lie superalgebras sl(1|1) and psq(2).

By employing programming techniques, this research systematically addresses the computation of solutions to the CYBE for the specified Lie superalgebras. We begin with a detailed formulation of the CYBE as applied to superalgebra structures, emphasizing the modifications required

to accommodate the graded properties inherent to Lie superalgebras. Utilizing symbolic computation tools, we develop algorithms to derive a classification of solutions to the CYBE. In particular, we present explicit calculations and illustrative examples of solutions for sl(1|1) and psq(2), highlighting their significance in the broader scope of superalgebra theory and integrable models. This work not only enhances the understanding of the CYBE in the context of Lie superalgebras but also demonstrates the effectiveness of computational methods in solving complex algebraic structures. Our findings set the stage for further research in the intersection of algebra, geometry, and theoretical physics, suggesting new avenues for exploring the implications of the CYBE in various applications.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY 14

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Mackenzie Munch, Charles Abrahart

Roots To Blossoms Theatre Experience: A Research Presentation

Explores intergenerational theatre in the Edmonton community. Four experimental sessions were held with participants from ages 5 to 90 participating in drama exercises and improvisation activities.

The goal was to research how people of different ages can come together and learn to story-tell with one another through theatrical demonstrations. Throughout the four sessions, we adapted each session to better allow participants to be creative and find connections with one another. The presentation will talk about why an intergenerational program on this scale is beneficial in the Edmonton community and will go into what worked best and what could be improved. The creators of this project both believe that this type of program is important

because of the lack of age range here in Edmonton theatre and believe that sharing experiences theatrically is a great way to find connections with people who you perhaps would not connect with outside of intergenerational work. In theatre there can be a lot of discrimination with age and the roles that an actor can play depending on their age. This project works to break that stereotype of an actor’s abilities based on their age, showing that all actors regardless of age can work together to create something beautiful. The research will include photos, videos, and interviews from Roots to Blossoms participants to better explore how it has impacted them and how what they have gained from this experience can be taken into other aspects of their lives.

Faculty: ARTS Department: FINE ARTS CUE Annual Research & Innovation Conference 2025

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ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Victoria Young

Revisiting Safe Zones in the Post Conflict Context through State-Led Peace Agreements: A Missed Joint Relief Opportunity for the Fata Region in Pakistan and Post-Taliban Insurgency Afghanistan Safe Zones have been abandoned as a form of humanitarian protection since the 1990s due to a low success rate. The underpinning policy factors that largely caused safe zones to fail was due to their establishment on extremely politically charged areas of conflict. The research highlights the value of safe zones in the post-conflict context and the important role of international institutions in state-led peace deals and ceasefire agreements.

It uses the Doha Peace Agreement which sealed the withdrawal of US military presence in Afghanistan to highlight an opportunity where the international community should have prepared a plan for humanitarian protection. The agreement led to a refugee influx of Afghan refugees along the Durand Line (border of Afghanistan and Pakistan) trying to refuge to Pakistan. The coexistence of internally displaced peoples and existing

communities in the underdeveloped semi-autonomous FATA region wedged between Pakistan and Afghanistan would advance UN Sustainable Development Goals and ease refugee influx post-Taliban insurgence. Rather than an interventionist approach or imposing western democratic values, embedding safe zones into peace deals and ceasefire agreements grants mobility rights to innocent civilians to leave an environment where they are being targeted by a new regime. Areas with little land value and little state-influenced political constraints allow for a less colonial approach to humanitarian aid. Durring ceasefire negotiations, a politically neutral non-state influence needs to protect the needs of civilians by utilizing a less politically influenced piece of physical land through the implementation of an old practice in a new context.

Faculty: ARTS Department: SOCIAL SCIENCES 16

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Daxit Surani, Baidya Saha

Brain Tumor Detection and Classification Using Deep Learning

Brain tumor detection and classification using deep learning have gained significant attention in medical imaging, offering improved diagnostic accuracy and efficiency. This research presents a novel Deep Reinforcement Learning (DRL) framework that combines Convolutional Neural Networks (CNNs) with Q-learning to classify brain MRI scans. Unlike conventional supervised learning methods, the proposed DRL model leverages a reward-driven learning mechanism to dynamically optimize classification decisions, ensuring adaptive and efficient segmentation of tumor regions.

The model architecture consists of a CNN-based feature extractor that encodes high-dimensional spatial and structural information into a compact state representation. The reinforcement learning agent operates within this feature space, where the action space represents classification decisions. The policy function is trained using a Q-learning

algorithm, with rewards assigned based on segmentation accuracy. To enhance learning stability, an experience replay buffer is integrated, mitigating issues such as correlated updates and catastrophic forgetting. Additionally, a softmax policy gradient method is employed to balance exploration and exploitation, allowing the agent to refine its decision-making process dynamically.

Extensive experiments are conducted to evaluate the model’s performance using key metrics such as accuracy, precision, recall, and F1-score. Comparative analysis with conventional CNN-based classifiers highlights the effectiveness of the proposed DRL-driven approach in improving classification robustness. By integrating reinforcement learning with feature-based decision-making, this study introduces an innovative methodology for AI-assisted brain tumor diagnosis, with potential applications in real-world clinical settings.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

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ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Justine Cramp, Tanya Ball

Reconnecting Indigenous Youth to Indigenous Cultures Through Nature, Art, Media, and Accessibility

Access to culturally based activities is a vital part of the reconnection process, especially amongst Indigenous youth ages 12 through 22. Earlier studies have shown a high correlation between access and interest to culturally based activities, in simpler terms If they have regular access to cultural activities and practices; they will also have interest or develop more of an interest in reconnecting with the cultures.

Studies also show that creative based activities such as dancing, drumming, singing, beading and more can also help spark and keep the interest of reconnecting youth, possibly opening the door to deeper conversations about Indigenous Cultures and how they fit into the community in the modern day. Today’s Indigenous youth are paving the way for Indigenous cultures to become more prominent in mainstream media. Many Indigenous artists like Snotty Nose Rez Kids have started sampling traditional music in genres like hip-hop and pop, Artists have also made entire albums

in their mother tongue in the same genres.

Youth who have regular access to this blended traditional/modern type of media who also have access to cultural activities and practices tend to show a higher interest in cultural reconnection.

Keywords: Indigenous, Youth, Reconnecting, Cultural Practices, Music, Art Biographical Statement: Justine Cramp is a third year Psychology student at Concordia University of Edmonton Department of Arts. Her work with inpatients at the Calgary Children’s Hospital Mental Health Unit inspired her to pursue a degree in Psychology, her work with Indigenous youth in care inspired her to pursue a minor in Indigenous Studies.

She is interested in Indigenous Cultural supports in therapy and supporting Indigenous youth with reconnection in a healthy and healing way. “

Faculty: ARTS Department: PSYCHOLOGY 18

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Damilola Innomesanghan, Damilola Innomesanghan, Emmanuel Kiwamu, Sergey Butakov, and Eslam AbdAllah

Ensuring Information Security in Inclusive Digital Environments

Individuals impacted by disabilities see various adverse effects in their day-today lives, specifically individuals on a spectrum who are unable to integrate into the workforce. To help ensure equitable access for individuals with disabilities, Assistive Technology (AT) bridges this gap by providing specialized tools and devices that empower individuals with disabilities to interact with digital environments seamlessly. These technologies range from screen readers and speech recognition software to adaptive hardware. While AT promote inclusion, they also introduce unique cybersecurity and privacy risks.

The sensitive nature of user data, ranging from biometric information to personal communication logs, demands stringent security measures. Small and mediumsized enterprises (SMEs), often at the forefront of AT deployment and integration, may lack the resources or expertise to implement robust security frameworks. This

is where information security standards, such as ISO 27001, play a crucial role. ISO 27001 provides a structured approach to establishing, implementing, maintaining, and continually improving an Information Security Management System (ISMS). This ensures that SMEs can protect sensitive AT data while complying with security best practices. This paper is divided into two parts. The first part provides an overview of assistive technologies, relevant security standards, and key ISO 27001 controls for securing AT solutions. The second part presents a case study of a Canadianbased SME that employs a neurodiverse workforce, including individuals with Autism Spectrum Disorder (ASD). The paper explores the organization’s approach to implementing ISO 27001 while considering the unique requirements of assistive technologies, the challenges faced during implementation, and the strategies used to mitigate them.

Faculty: MANAGEMENT SYSTEMS ASSURANCE MANAGEMENT Department: INFORMATION AND INFORMATION SYSTEMS SECURITY MANAGEMENT CUE Annual Research & Innovation Conference 2025

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ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Makan Golizeh, Brynmar Degenhardt, Dylan Hrenchuk, Seth Nobert, Taniel Smith, and Cole Babcock

AGES - The Delicious Agents Of Aging

Background: Advanced glycation end-products, AGEs, are chemical compounds that naturally form between sugars and proteins in food and living organisms. AGEs often give colour and flavour to food; however, many are toxic and linked to various health problems, such as metabolic and neurodegenerative diseases. AGEs play an important role in age-related complications and are therefore an important subject of study in health research. Under physiological conditions, AGEs form at slow rates and low quantities, making them challenging targets for laboratory analysis.

Purpose: This research program aims to develop an analytical framework for systematic assessment of AGE formation in humans. Our primary objective is to understand the dynamics between AGE formation, diet and exposure, and age-related diseases.

Methods: The analytical approach utilized in this study comprises of four independent, yet complementary components. An in vitro model has been established to produce AGEs under laboratory conditions. Further investigations were conducted using a food model and a human cell model. Instrumental analytical methods were developed to quantitatively identify AGEs in laboratory and biological samples. An in silico approach was employed to predict the biological consequences of AGE formation in humans.

Results: Our in vitro studies demonstrated that AGEs form more readily at higher pH, temperature, and heavy metal concentrations.

Several toxic AGEs were identified and quantified in the laboratory and biological samples. Iron and copper showed a promoting effect on the rate and extent of AGE formation. On the contrary, organic compounds that react with iron and/or copper had inhibitory properties on the AGE formation reaction. Human cells treated with these compounds had a more balanced metabolic profile compared to those not treated.

Bioinformatics prediction suggested that AGEs can target human proteins that are directly involved in the aging process.

Conlusion: AGEs are difficult to analyze. They comprise of a wide range of molecular structures and diverse physicochemical properties. They are nonabundant and often water insoluble.

Our methods, however, show a promising effectiveness for the analysis of AGEs in complex biological samples, such as food extract and cell lysate. Our studies demonstrate that AGE formation can be controlled by maintaining a balanced intake and/or exposure to heavy metals, such as iron. Our future investigations will focus on the impact of AGE formation on the aging process in humans.

Faculty: SCIENCE Department: ENVIRONMENTAL AND PHYSICAL SCIENCES 20

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Emma Haugen, Jennifer Braun and Tanya Ball

“If I Had Another Choice, I Would Take It”: The Experience of Indigenous Women Who Have Hitchhiked in Western Canada

People in rural and remote Canadian communities are often isolated from larger towns and metropolitan centres due to lack of transportation infrastructure.

As a result, people in these remote communities are forced to make risky and unsafe transportation decisions to fulfill their personal needs and responsibilities.

Amongst those who are the most affected are Indigenous women. Because they hitchhike at higher rates than nonIndigenous women they are also more likely to face adverse outcomes from hitchhiking than non-Indigenous women (Gov’t Canada, 2022). For the purpose of this study, ‘woman’ is defined as someone who identifies as female or 2-Spirit.

This Indigenous-centred, anti-colonial qualitative research study explored the lived experiences of Indigenous women who have hitchhiked from remote or rural communities where public transportation does not exist. When the Saskatchewan Transportation Company and the Western

Canadian Greyhound Bus services shut down in 2018, there were far reaching implications for many Indigenous women and their travel options..The objective of this research was to better understand the experiences and decision making processes of Indigenous women who have hitchhiked. Using information from Canada’s National Inquiry for Missing and Murdered Indigenous Women, Girls, and 2-Spirt (2016) and visiting methodologies (Gaudet, 2019), I was able to contextualize and highlight some themes from the lived experiences of rural Indigenous women surrounding hitchhiking.

Using Intersectionality, and Indigenous Feminisms, I show how the intersection of social class, gender, race, and geography shape the already onerous transportation decision-making process for rural Indigenous women and how they navigate the stigma and danger of these choices to protect themselves and each other.

Faculty: ARTS Department: SOCIAL SCIENCES CUE Annual Research & Innovation Conference 2025

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ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Jenna Congdon

Building a Cohesive Research Program: The Importance of Local Institutional Partners, International Collaborations, and Undergraduate Student Experiences Psychology is defined as the scientific study of behaviour and the mental processes that cause it. Comparative cognition is a discipline within psychology that compares mental processes and behaviour across species, human and non-human, investigating topics such as perception, learning, memory, communication, timing, numerosity, and spatial navigation. Collaborations with zoos and conservation areas are playing an increasing role in this area of research by enabling access to species not suitable for laboratory research and providing more naturalistic research conditions. The greatest benefit of these collaborations is the ability to gather data on basic science questions about how the mind works while simultaneously improving animal welfare through environmental enrichment, revising best practices for housing and care, and informing conservation efforts for their wild counterparts. These collaborations also expand the scientific questions accessible to researchers. Laboratories are often restricted to studying a single focal species at a time (e.g., financial and physical space restrictions, animal husbandry requirements, etc.), whereas non-laboratory based research can

be truly comparative, including a wide variety of species in a single study, or adapting methodologies across whole lines of research. In collaboration with the local Edmonton Valley Zoo, as well as international zoos and researchers, the ‘Cognition, Learning, & Animal Welfare’ (C.L.A.W.) Laboratory is developing a research program, working towards the collective goal of further understanding animal perception, and providing insight regarding enrichment and welfare. As faculty in the undergraduate Psychology program, many of the ideas and facilitation of research projects are driven by the students that I work with; undergraduate students provide consistent scientific inspiration from a diverse range of passions, and inclusion of students provides research opportunities with real world experience in working directly with a variety of animal species, methodologies, and highly trained zookeepers. In this talk I will: 1) briefly describe my research program, studying cognition and learning in non-human animals; and 2) highlight the importance of local institutional partners, international collaborations, and incorporating undergraduate students into research.

Faculty: ARTS Department: PSYCHOLOGY 22

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 1

Varalakshmi Yasaswi Posina

Traffic Accident Forecast System: Utilizing Artificial Intelligence for Road Safety Improvements

Background: Road traffic accidents remain a significant global problem, causing significant deaths as well as significant economic burden. Traditional forecasting models often rely on simple statistical techniques, which often fail to capture the complex interrelationships between the different factors involved in accidents.

Purpose: This project introduces a revolutionary traffic accident prediction platform designed to transform reactive safety approaches into proactive risk mitigation strategies, aiming to develop a system that identifies high-risk collision zones before accidents occur, enabling preventive interventions.

Methods: The approach in this work leverages a novel hybrid neural network design that is capable of examining temporal, spatial, and environmental data simultaneously. This architecture combines custom LSTM networks with a custom attention mechanism for identifying risk factors relevant to specific locations in Alberta’s large traffic and environmental datasets. Our novel ensemble method combines several neural networks, each carefully fine-tuned to identify specific indicators that herald accidents.

Results: The model developed in this research demonstrated 37% improvement in predictive capability over current industry systems through extensive testing.

Its deployment in operational environments generates dynamic risk heatmaps and data-driven intervention recommendations, including optimized signal timing and focused enforcement initiatives. Pilot tests confirm the system’s effectiveness in identifying potential accident hotspots hours or even days in advance of the development of high-risk conditions.

Conclusion: The new strategy revolutionizes traffic safety management so that regulatory bodies can undertake preventative measures before accidents happen.The proposed framework transforms complex traffic information into actionable insights, thus enabling effective resource allocation and providing a foundation for proactive urban safety measures. This technology showcases the immense potential of advanced predictive analytics to save lives and eliminate resource wastage through rational, fact-based decision-making. statistical techniques, which often fail to capture the complex interrelationships between the different factors involved in accidents.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

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ORAL PRESENTATION

Saturday, April 12, 2025 | Session 2

Shovo Ghosh, Ekram Ul Karim Ratul, Al Riyad Linkon, and Shaun Aghili

Security Considerations in AI: Risks, Threats, and Mitigation Strategies

Artificial Intelligence (AI) is rapidly transforming various industries, yet its security vulnerabilities pose significant risks. This literature review explores key threats associated with AI, including adversarial attacks, data poisoning, privacy breaches, and ethical concerns.

Adversarial attacks manipulate AI models to generate incorrect outputs, while data poisoning introduces malicious alterations during training, compromising model integrity. Privacy concerns arise from AI’s reliance on large datasets, increasing risks of data exposure through model inversion and membership inference attacks. Ethical issues, particularly bias in AI decision-making, further exacerbate security challenges. Additionally, emerging

threats such as deepfakes and AI-enabled cyberattacks present novel risks requiring proactive mitigation. Strategies for securing AI systems include adversarial training, model verification techniques, privacypreserving methods like differential privacy, and robust regulatory frameworks.

The review highlights the necessity for interdisciplinary collaboration between policymakers, researchers, and industry leaders to establish standardized security practices. Future research should focus on enhancing AI robustness against evolving threats and ensuring fairness and transparency in AI deployment. Addressing these concerns is imperative for the responsible development and deployment of AI technologies.

Faculty: MANAGEMENT SYSTEMS ASSURANCE MANAGEMENT Department: INFORMATION AND INFORMATION SYSTEMS SECURITY MANAGEMENT 24

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 2

Reema Maheshbhai Gadhia

Wildfire Detection System

Background: Wildfires, nurtured by climate change, continue to pose a significant threat to ecosystems, and human well-being. It requires timely identification to reduce harm and enable quick intervention. Early detection is vital for mitigating the damage caused by wildfires, the ability to predict potential fire outbreaks before they occur would offer an advantage in wildfire management. This research proposes the development of a system that integrates advanced technologies for both wildfire detection using satellite imagery and artificial intelligence-based analytics. This will thus introduce rapid detection of wildfires, improving traditional methods to increase speed and accuracy in warnings.

Purpose: Traditional methods of detection are often slow, visually confirmed and followed through by reports from the ground.

Uncontrollable fires have always been the result of delayed responses. Some technologies have improved detection, while few incorporate analytics to anticipate wildfires before they start.

This puts communities at risk of fires, which could be reduced with better use of resources.

Advanced detection using satellite data will be necessary to gain comprehension regarding early wildfires through real-time information in support of fast response times for minimal damages.

Objectives: Design a machine learning model that incorporates satellite imagery to infer early detection of wildfires.

Employ real-time data analysis that ensure perfection in detection and speed.

Better training reduces the number of false positives.

To utilize this information to provide stakeholders especially emergency responders and local governments with an easy to use interface.

Methodology: Dataset: https://www.kaggle.com/ datasets/johanjohnthomas/corrected-wildfires Phase A is developing a Convolutional Neural Network (CNN) model to automatically detect signs of early fire such as smoke from visual footprints of drone and satellite images.

The challenges would be distinguishing between a hazy/cloudy environment and smoky environment. To eliminate the need for big data I can adapt a transfer learning strategy to use a pre-trained model such as VGG-16 on Aerial images. Phase B is developing a Long Short Term Memory (LSTM) model based on temporal trends depending on historical climatic condition and thermal footprints to detect anomalies in land temperatures based on local fires. The final system will combine prediction results of phase A and phase B. Expected Outcome: A full-scale, functional wildfire detection system with reduced detection times. Anticipating potential wildfires before they occur, providing critical time for prevention and resource planning. Improvement in this field can help prepare people in advance, leading to reduced losses.

Future Scope: Creation of a Wildfire Prediction model that will include the results of the analysis of vegetation health using visual footprints and detection of dry and hot days using a regression model.

Conclusion: This system enhances early warning by using AI and satellite imagery for faster, more accurate detection. More than just detecting fires, it gives emergency teams real-time insights to act quickly. In the future, it could evolve to predict wildfires before they start, helping protect communities and the environment.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

25

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 2

Cole Babcock, Thamizhinian Vasudevan, Taniel Smith, Ayden Justice-Riar, Regan Holt, Emmanuel Mapfumo, and Makan Golizeh

Green AptaBeads: An Affordable Sample Preparation Technology

Background: Biological and environmental samples are often complex, consisting of cell debris, proteins, small molecules, and other substituents. To analyze specific component classes within these samples, researchers must perform multiple strenuous and expensive sample preparation to effectively sift out potential interferences. While these procedures can remove the bulk, these component classes remain complex and can contain hundreds, if not thousands, of individual compounds. Selective decomplexation of these samples can shift their analyses from being ‘untargeted’ to ‘targeted’, with the desired component becoming the main constituent of the analysis. In the targeted approach, compounds are often separated from the sample using a capture agent, such as an antibody or DNA aptamer (single-stranded DNA oligonucleotide). These techniques can yield data which is easier to process and of greater significance to clinicians and researchers.

Purpose: This research is aimed at developing an affordable, sustainable, shelf-stable sample preparation technology with the ability to decrease the complexity of samples prior to analysis. This development, dubbed Green AptaBeads, would support the targeted analysis of a broad range of substituent classes for use in biological and environmental samples.

Methods: With straw as a primary starting material, sustainable synthetic methods were developed to produce derivatized cellulose as the backbone of this new AptaBead technology.

Three techniques were used to form beads from this cellulose derivative, and one was selected as a candidate to proceed with. Using the Nobel Prize winning “click-chemistry” method, the aptamer was then linked to the surface of the bead and assessed to quantify

its aptamer content. The product is currently undergoing evaluation for its effectiveness in a laboratory analysis. Soil respiration tests are being performed in tandem to investigate the rate of biodegradation of the developed cellulose derivative.

Results: Preliminary analyses confirmed the synthesis of the cellulose derivative was successful, and that the methods developed were equivalent to the non-green approaches often used. Following aptamer linkage, analysis positively confirmed aptamer presence on the bead surface, showing a target capture ability comparable to commercially available technologies. Moreover, both preliminary and current biodegradation studies have yielded promising results, however a longer study period is required to make a substantial claim.

Conclusions: While technologies exist for targeted analysis, AptaBeads show potential as an alternative to their expensive counterparts.

The intrinsic advantages of using aptamers over antibodies lends the AptaBeads greater shelf stability, reproducibility, and decreased storage costs. Additionally, in comparison to commercial products, our Green AptaBeads are 1/50th of the cost of competitors, saving clinicians and researchers unnecessary costs. Combining commercially-available bioplastic labware with our sustainable production methodologies, an effective product will be developed with a minimal environmental impact in alignment with Canada’s Zero Plastic Waste Initiative.

Ongoing biodegradation and toxicity studies will yield further insight into the technology’s eco-friendliness. Future directions will include expanding targets to include large molecules, such as proteins, and using Green AptaBeads in samples of greater complexity.

Faculty: SCIENCE Department: ENVIRONMENTAL AND PHYSICAL SCIENCES 26

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 2

Evan Labonne, Pam Wizzard, Mahabub Alam, Shae-Lynn Labonne, Mirielle Pauline, Justine M. Turner, Paul W. Wales, and Matthew Churchward

Glucagon-like Peptide 1 and Glucagon-like Peptide 2 Promotes Short Bowel Syndrome Intestinal Adaptation: A Pilot Research Study Background and Purpose: The human digestive tract is an advanced, complex system, designed to ensure nutrient absorption from food for survival and growth in childhood. Some babies are born with, or due to disease acquire a short bowel causing intestinal failure and death without intravenous nutrition. The solution for these babies is to grow the bowel or make it work better (structural and functional adaptation, respectively). Fortunately, new hormone compounds are being developed that might help.

Because babies with short bowel syndrome are so sick, a neonatal piglet model of short bowel syndrome is used to study the benefits and safety of new treatments. The objectives/purpose of this study was to investigate whether two hormones, Glucagon-Like Peptide-1 and Glucagon-Like Peptide-2, would act in synergy to improve structural and functional adaptation compared to either treatment alone or to the control.

Methods: Each animal underwent surgery removing 75% of the small bowel. The animals received their respective treatment through injections. The saline negative control group received injections at a dosage of 0.10 mg/kg with a sample size of 4. The Glucagon-Like Peptide-1 analogue low-dose experimental treatment group received injections at a dosage of 0.05 µg/kg with a sample size of 5. The Glucagon-Like Peptide-1 analogue high-dose experimental treatment group received injections at a dosage of 0.10 µg/ kg with a sample size of 5. The Glucagon-Like Peptide-2 analogue experimental treatment group received injections at a dosage rate of 0.10 mg/kg with a sample size of 5. The Glucagon-Like Peptide-1 lose-dose and Glucagon-Like Peptide-2

combination synergy treatment group received Glucagon-Like Peptide-1 analogue injections at a dosage of 0.05 µg/kg and Glucagon-Like Peptide-2 analogue at a dosage rate of 0.10 mg/kg with a sample size of 4. The GlucagonLike Peptide-1 high-dose and Glucagon-Like Peptide-2 combination synergy treatment group received Glucagon-Like Peptide-1 analogue at a dosage of 0.10 µg/kg and Glucagon-Like Peptide-2 analogue at a dosage rate of 0.10 mg/ kg with a sample size of 6. Measures of structural and functional adaptation were collected on day 0 during the initial procedure and on day 7.

Outcome measures included change in animal weight, change in intestinal length (day 0 to day 7), small bowel total and mucosal scraped weight, villus length and crypt depth.

Results and Conclusion: This pilot study compared two doses of Glucagon-Like Peptide-1 as this hormone has never previously been studied in piglets, compared to a dose of Glucagon-Like Peptide-2 previously shown to be effective for adaptation in SBS piglets.

Combining low-dose Glucagon-Like Peptide-1 with Glucagon-Like Peptide-2 results in measuring increased growth of the intestine in length, especially compared to saline control.

Combining high-dose Glucagon-Like Peptide-1 with Glucagon-Like Peptide-2 may show a trend to increased growth of the intestinal mucosa. The findings will contribute a critical first step towards a new biomedical pharmaceutical innovation by testing the validity of combining Glucagon-Like Peptide treatments to improve the prognosis and quality of life of patients suffering from conditions such as short bowel syndrome.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES CUE Annual Research & Innovation Conference 2025

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ORAL PRESENTATION

Saturday, April 12, 2025 | Session 2

Sergey Ishutov, Amir Tavallaie Nejad and Emmanuel Mapfumo

Assessing Potentially Toxic Element Concentrations in Topsoil at East Pit Lake, Alberta Using Sentinel-2 Satellite Imagery and Machine Learning Background: Soil contamination with heavy metals and salts presents significant environmental challenges in Alberta, affecting air and water quality, biodiversity, and land reclamation efforts. Understanding the spatial distribution and concentration of these elements is crucial for effective environmental management. Traditional soil monitoring methods rely on field sampling and laboratory analysis, which can be time-consuming and costly. Advances in remote sensing and machine learning offer new opportunities to enhance the efficiency and accuracy of monitoring efforts.

Purpose: This project aims to integrate remote sensing techniques with machine learning algorithms to develop an improved method for detecting and mapping heavy metal and salt concentrations in soils and to provide costeffective, data-driven insights for site remediation, environmental monitoring, and land management.

significant features such as Tasselled Cap - Soil Brightness Index MSS and Ferric iron (Fe²+).

Organic matter predictions were more variable (R² = 0.5273 train, 0.2551 validation), indicating complex interactions with spectral indices and vegetation. Permutation importance analysis confirmed that geological and mineralogical features strongly influenced Ti predictions, while pH was primarily affected by spectral reflectance properties and soil brightness.

Conclusions: The integration of remote sensing and machine learning provides an efficient, scalable approach for soil contamination assessment and environmental monitoring in mining-impacted landscapes. The study demonstrates that high-resolution satellite imagery, when combined with advanced predictive models, can accurately characterize soil properties, reducing the reliance on extensive field sampling.

Methods: This study utilized Sentinel-2 satellite imagery and machine learning models to predict and map the spatial distribution of soil properties and potentially toxic elements (PTEs) in reclaimed soils at East Pit Lake, Alberta. A selection of 127 spectral indices was extracted and analyzed using multiple normalization techniques, with mutual information (MI) applied to assess feature importance. Principal Component Analysis (PCA) was then employed for dimensionality reduction, identifying optimal feature sets for different soil parameters.

Key environmental implications include:

Results: Machine learning model evaluation revealed that machine learning methods performed best for several soil properties, particularly titanium (Ti), pH, and organic matter.

It demonstrated high predictive accuracy for Ti, achieving an R² of 0.9705 (train) and 0.9419 (validation), with key predictors including Gossan formations and mineralogical spectral indices. Predictions for pH exhibited moderate performance (R² = 0.4027 validation), with

These findings contribute to broader applications in mineral exploration, agricultural sustainability, and soil resource management, reinforcing the utility of remote sensing-driven soil monitoring in addressing global environmental challenges. By integrating advanced remote sensing and machine learning techniques, this study represents a significant advancement in environmental monitoring practices, offering improved efficiency, accuracy, and applicability for long-term land management in Alberta.

• Ti distribution is predominantly controlled by geological formations, making spectral indices valuable for mineralogical assessments.

• pH variability is influenced by soil brightness and redox conditions, providing insights into chemical soil processes.

• Machine learning offers a cost-effective solution for land reclamation and sustainable management, guiding remediation strategies.

Faculty: SCIENCE Department: ENVIRONMENTAL AND PHYSICAL SCIENCES 28

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 2

Rachel Campbell, Kacianne Kawulok, Jessica Dubauskas, Ajay Mangat, Tessa Granson-Woolard, and Alexander Taikh

The Influence of Planning Ahead on Speech Fluency in Adults who Stutter

Stuttering is a developmental speech disorder that disrupts the normal flow of speech. Cognitive demands of processing linguistic information may destabilize the speech motor system and make a disfluency more likely. For example, content words, which carry a clear meaning in a sentence, are more likely to be stuttered on than function words, which link content words together in a sentence. Deficits in speech planning are also thought to contribute to speech disfluencies.

According to the EXPLAN theory of fluency control (Howell, 2002), speech disfluencies are due to the asynchronies between planning (PLAN) and execution (EX) processes, where a disfluency is more likely when the preceding word was spoken too quickly to allow sufficient planning for the word currently being spoken. EXPLAN assumes that planning and articulation are concurrent, but independent processes.

In the present study, we extend on EXPLAN by examining whether the planning of a subsequent word influences the likelihood of a disfluency occurring on the word being said, and whether content and function words are equally vulnerable to

this influence. Specifically, studies which examine the typing production of words (e.g., Gow et al., 2024; Taikh et al., 2023) have found that keystroke speeds are influenced by how difficult the subsequent word is to access and plan. The influence of the linguistic information of the subsequent word on the typing of the current word suggests that the planning process influences the typing process and thus the two are not independent. Using recordings of adults who stutter reading short passages that are available in the Fluency Bank database (MacWhinney & Bernstein Ratner, 2021), we found that content words, but not function words, are influenced by the linguistic information of the subsequent word. Specifically, disfluencies were more likely on content words when the subsequent word was a content word, and when it was more frequent. Our findings suggest that planning the articulation of the subsequent word can interfere with the articulation of content words, but not function words in adults who stutter.

Our findings also suggest that, like in typing, planning and production are not independent processes.

Faculty: ARTS Department: PSYCHOLOGY CUE Annual Research & Innovation Conference 2025

29

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 2

Xin Chen

Ecological Paradoxes: When Predators Aid Victims and Resources Harm Consumers

Background: Classical ecological wisdom postulates that predators reduce prey populations, while resource benefits consumer populations. However, paradoxical dynamics have been observed in both theoretical and empirical studies where predators benefit their prey and resources harm their consumers. Such counterintuitive relationships, observed in systems with complex trophic interactions and competition, challenge conventional ecological theories and have significant implications for biodiversity conservation.

Purpose: This study investigates these ecological paradoxes with a focus on analyzing models of complex species interactions. By uncovering the mechanisms underlying these counterintuitive effects, we aim to determine the conditions that give rise to these paradoxical outcomes and evaluate their implications for ecosystem stability and biodiversity conservation.

Methods: Ecological models are developed integrating competition, predator-prey dynamics, and resource-consumer interactions. By analyzing key factors such as predation efficiency, competition intensity, and resource conversion value, the conditions that promote species coexistence and system stability are identifies.

Additionally, the parameter space is mapped where these ecological paradoxes emerge.

To validate the theoretical findings, case studies from both aquatic and terrestrial ecosystems are examined, comparing model predictions with real-world observations.

Results: Model outcomes reveal that predator-driven prey population growth occurs through a subsidy-stress dynamic.

When predators primarily feed on a less vulnerable prey species, they suppress a dominant competitor of the focal prey.

This indirect effect reduces competition for resources, allowing the focal prey to thrive.

Conversely, in resource-rich environments, increased competition between a focal consumer and a stronger competitor disproportionately benefits the more competitive consumer, leading to a decline in the focal consumer’s population. These paradoxical effects are most pronounced in systems with asymmetric competition and trade-offs between resource quality and quantity.

Conclusion: These findings show that ecological paradoxes are features of complex ecosystems shaped by indirect interactions and feedback loops. They challenge the traditional assumption that ecological relationships are straightforward and highlight the importance of considering both direct and indirect effects in ecosystem models. From perspective of biodiversity conservation and ecosystem management, this underscores the risks of oversimplifying complex species interactions. Future research should focus on testing these predictions in real-world settings, particularly in rapidly changing environments where these paradoxes could make ecosystems more vulnerable.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES 30

CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 2

Boyko Zlatev

Statistical Modeling of Length of Reign

The statistical modeling of length of monarchic reign is important in the field of historical science helping to test the plausibility of ancient chronological data and to better understand the regularities in the historical processes. For the statisticians, on the other hand, it is an opportunity to apply advanced statistical methods.

Historically, the problem arises from an ancient computation of the date of founding of Rome by the Roman historian Varo who estimated 257 years to be the total time of reign for 7 consecutive Roman kings. Critical approach to the ancient chronology led Sir Isaac Newton to computation of the first point and interval estimates of population mean for length of reign. These were obtained even before the development of rigorous statistical theory and terminology. Newton’s results were confirmed by Voltaire and further developed by Condorcet who applied de Moivre’s law of mortality to check the plausibility of Varo’s estimation. Similar approaches were later used by Pearson and Trustam.

However, in the beginning of 21st century it became clear that the length of reign modeling must be approached statistically in entirely different ways, having almost nothing in common with the prediction of life expectancy for common human populations. Surprisingly, some lists

of reigns, including those of Roman and Chinese emperors, have shown memoryless behavior modelled by a Poisson process with a constant intensity and exponential distribution of the length of reign. For other data, e.g., Kings of England, this model was not successful.

In the talk an alternative approach is proposed – modeling the consecutive changes of rulers by a self-exciting Hawkes process with an exponential decay as a kernel function. This model has shown to be especially good fit for the Popes of Rome, and it is also giving some promising results for other lists of reigns.

A particular way to improve the model fit can be to consider as a covariate the age of the monarch at the time of ascension to the throne, as well as environmental factors like average temperature. Using a different kernel function can be also an option. However, to choose the proper kernel function, it is worth first to model the intensity of the process with a spline using functional data analysis. The model should also consider the specific topology of data which is different for the inherited monarchies and for the elected rulers (e.g., Popes of Rome, Doges of Venice). Another possibility is to include in the model an interaction between point processes, especially for neighbor states. All these approaches are discussed in the talk.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

31

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 2

Jenn Laskosky

Best Practices and Qualities of Recreational Dementia Friendly Reading Materials

Background: Despite the effects of dementia, many people with dementia retain their ability to read, even if it is at a lower level. However, reading has remained largely ignored as a meaningful experience for people with dementia. Additionally, there are few resources regarding the creation of dementia friendly reading materials and what is required in order for them to be effective. As a result, there is a lack of appropriate and mature reading material available for people with dementia.

Purpose: To outline best practices for creating dementia friendly reading materials in order to create a positive, accessible reading experience for people with dementia.

Methods: A literature review was conducted focusing on dementia, libraries, and reading specifically. Library and information studies databases were searched, along with healthcare, gerontology, and other

related fields. The case study consists of a content and thematic analysis to determine commonalities between dementia friendly reading materials and evidence from the literature review.

Results: Emma Rose Sparrow and Marlena Books both follow several best practices outlined by Ostrowski and Dixon. Best practices have been created, from the literature review and case studies, to determine appropriate dementia friendly reading materials.

Conclusions: Further research into the relation between dementia and reading is required to better understand the needs of readers with dementia. Library and information studies professionals can use the information presented to make informed decisions regarding collection development and educating library users.

Department: LIBRARY

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CUE Annual Research & Innovation Conference 2025

ORAL PRESENTATION

Saturday, April 12, 2025 | Session 2

Wali Mohammad Abdullah, Md Morshedul Islam and Baidya Saha

Rails: Retrieval-Augmented Intelligence for Learning Software Development

Creating accurate and functional computer code from incomplete or ambiguous prompts remains a persistent challenge in software engineering.

Recent advancements in artificial intelligence (AI), particularly using large language models (LLMs), have shown remarkable potential in assisting with tasks such as code generation, debugging, and addressing programming-related queries. However, these models often falter when confronted with domain-specific requirements, frequently producing incorrect or inefficient code due to their reliance on statistical patterns rather than structured, domain-specific knowledge. This research seeks to overcome these limitations by integrating LLMs with retrieval-augmented generation (RAG), a technique that enables AI systems to dynamically retrieve relevant information from external knowledge sources.

The primary objective of this research is to develop an advanced framework that improves the accuracy and reliability of AI-assisted code generation. By incorporating structured data from programming libraries, technical documentation, online forums, and domain-specific repositories, the system can dynamically retrieve contextual information to enhance the relevance and quality of generated code. This approach not only boosts the performance of LLMs but also reduces errors commonly associated with AI-generated programming solutions. A critical feature of this framework is its scalability, making it suitable for both academic learning environments and realworld software development projects.

To achieve these goals, the research adopts a structured methodology that includes: (1) A comprehensive review of existing AI-driven code generation techniques, (2) Development of a prototype integrating retrieval-augmented generation with vector and graph-based knowledge retrieval, and (3) Iterative validation to refine accuracy and performance.

The prototype leverages advanced tools such as vector databases (e.g., Pinecone) and knowledge graphs (e.g., Neo4j) to efficiently retrieve relevant information in response to user queries. Additionally, AI models like CodeBERT and Codex are employed for code generation, ensuring a robust and adaptable system. The effectiveness of this approach will be evaluated through benchmarking against existing code generation tools and performance assessments on standard datasets.

The anticipated outcomes of this research include: (1) Significant improvements in code synthesis accuracy, (2) Reduction in errors in AI-generated code, and (3) Enhanced usability across diverse programming scenarios.

By equipping AI models with access to structured knowledge, the framework is expected to produce code that is not only syntactically correct but also contextually appropriate for specific programming tasks. Furthermore, this research will provide valuable insights into the role of structured knowledge in software engineering and its potential to enhance AI-driven development tools.

This research contributes to the fields of artificial intelligence and software engineering by proposing a novel, cost-effective solution for improving automated code generation.

The proposed framework is designed to be adaptable for various applications, including academic learning, software prototyping, and industrial programming. Future work will focus on refining the system, expanding its applicability to additional programming domains, and exploring opportunities for industry collaboration and funding. By integrating AI with structured knowledge retrieval, this research lays the foundation for more reliable, efficient, and intelligent software development tools.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

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POSTER PRESENTATION Poster 1

Aasma Makwana, John Walsh

Developing A Custom Reference Database For Environmental Dna Metabarcoding To Better Detect Fish Species In Alberta

Background: Environmental DNA (eDNA) metabarcoding is a powerful tool for biodiversity monitoring and species identification by analyzing genetic material shed into the environment. This approach works by amplifying a barcode for the taxa of interest. A barcode is a standardized DNA region that is conserved across many organisms but contains sequence variations that enable species differentiation. However, the accuracy of species identification depends on the reference database used.

While a custom database aids in more accurate taxonomic identification and assignment, it may lack coverage, causing rare or cryptic species to go undetected.

In contrast, public databases have broader coverage but lower resolution, increasing the risk of ambiguous species identification or false positives.

Purpose: This research aimed to develop a custom reference database with Alberta’s native and invasive fish species of interest, analyze metabarcoding data, test variable parameters, and refine the workflow.

Methods: To build the database, a list of relevant fish species was compiled, and their

12S rRNA and CO1 barcodes were retrieved from NCBI and BOLD. The database was validated using simulated data containing known fish species, testing parameters such as filtering criteria and match limits per query.

Additionally, three metabarcoding runs were analyzed under different parameter settings, each yielding distinct results.

Results: The study found that adjusting filtering parameters and match limits affected the accuracy and specificity of species identification. A higher match limit increased the number of species detected but also introduced more ambiguous results, while a stricter match limit improved precision but reduced the number of species identified.

With the higher match limit, the Prussian carp—an invasive fish species—was detected and will be further validated using quantitative polymerase chain reaction (qPCR) to confirm its presence.

Conclusion: These findings highlighted the importance of parameter selection in shaping the outcome. Optimizing these settings is crucial for improving metabarcoding accuracy for biodiversity monitoring and conservation efforts.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES 34

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 2

Adanna Kalita, Elizabeth Farrell

HRM True And False

This is a presentation exploring true and false questions of chapters 9,10,11.Chapter 9 focuses on labour relations, unions, and collective bargaining. It clarifies that the Uber Canada and UFCW Canada agreement does not result in traditional unionization. It also distinguishes craft unions from industrial unions and explains that unions prioritize employee rights over company profits. Additionally, it differentiates collective bargaining from contract administration.

more influential than economic systems.

It discusses cross-cultural preparation, expatriate support, and repatriation while noting that performance management varies globally due to cultural and legal differences.

Chapter 11 focuses on high-performance work systems, stressing that HR, technology, and organizational structure must be integrated. It also explains HRM audits and the strategic role of CHROs.

Chapter 10 highlights global HRM challenges, emphasizing that culture is

Faculty: MANAGEMENT Department: MANAGEMENT CUE Annual Research & Innovation Conference 2025

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POSTER PRESENTATION Poster 3

Aidan Dion, John Walsh

Impact Of Polyploidy On Carassius Gibelio Genome Evolution

Polyploidy occurs when certain species contain two or more complete sets of homoeologous chromosomes within the genome of germline or somatic cells.

This process may occur through the duplication of one set of chromosomes (autoploidy), or through combining the sets that arises from two or more different sub-genomes that have a common origin (alloploidy). It is evident that polyploidy has contributed to the evolution of multiple species, allowing for the development of new traits/versions within genes of interest. This gives rise to creating new modifications and improvements within the organism through neofunctionalization, or may cause a division of certain gene tasks through sub-functionalization. This phenomenon plays an important role in the diversification and evolution of genes occurring as whole-genome duplications in teleost species including the Carassius spp. The Carassius gibelio species are an example of being an amphitriploid, and remains desirable for investigating the relationship between polyploidization and evolution, in order to study sub-genome dominance since no assessments have been conducted to view its genetic diversity. Caspases are protease enzymes responsible in regulating apoptosis and inflammation, and by being able to detect these proteases in Carassius gibelio after expression, information can be gathered

to characterize target caspase orthologs and homoeologs to view the evolution of these genes relating to polyploidy through sub/neofunctionalization. This study investigates the evolutionary fate of caspase homoeologs in the Carassius gibelio genome, with a focus on whether patterns of sequence divergence are consistent with sub-functionalization or neofunctionalization following polyploidization. By characterizing the caspase gene family within this polyploid species, the research contributes to a broader understanding of how duplicated genes may be retained and diversified in polyploid vertebrate genomes. The research study focused on analyzing the caspase family within the Carassius gibelio sub-genomes using published online genome assemblies. Caspase genes were identified through searches in major databases using NCBI and GALAXY. The platforms were used to locate and verify the caspase family genes within its annotated genomes and NCBI BLAST analyses were performed to compare percent identities in order to assess gene homology.

The sequence-level characterization developed here will inform the design and interpretation of subsequent gene expression studies, helping to connect genomic patterns with transcriptional activity.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES 36

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 4

Alexander Taikh, Keira Gow, Muna Mohamud, Alexander Taikh, and Thea Comeau

Linguistic Markers As Indicators Of Post Traumatic Growth And Resilience In Survivors Of Intimate Partner Violence

Intimate partner violence (IPV) is a significant public health concern. In fact, Canadian statistics suggest that almost half of women who have been in a romantic relationship have experienced some form of IPV, such as physical, sexual or emotional abuse (Cotter, 2021). Survivors of IPV can report traumatic sequelae arising from these experiences, such as PTSD. This suffering may be the catalyst for developing positive psychological outcomes (PPOs), such as resilience and posttraumatic growth (PTG). While there is substantial evidence that survivors of IPV have been able to move from suffering towards PPOs, it is not clear how these survivors describe these experiences, what role their use of language plays in these descriptions, and what constitutes resilience and PTG following trauma, how to distinguish between the two, and whether they can co-exist. Secondly, when PTG is identified, it can be challenging for researchers to determine whether the reported changes are authentic or illusory.

One non-invasive method to study post traumatic growth is linguistic information analysis. Language can reflect internal emotional and mental states. It has been suggested that linguistic markers like specific word style and semantic context can be used to understand individuals mental health status, and studies (e.g., Castiglioni et al., 2023) have found that a more cognitive style approach to language choice is related to lower levels or risk of PTSD while more perceptual or affective wording is predictive of negative mental health functioning. The current study seeks to explore the disclosures of survivors of IPV on the social media platform Reddit to understand

what types of language they use to describe their experiences following intimate partner violence, and whether these linguistic markers may be helpful tools to distinguish between resilience and PTG in survivors’ narratives.

We extracted a total of 195 posts from four Reddit threads focused on life after leaving the IPV situation. Two coders identified themes of resilience and PTG in the posts. We then examined posts for the use of cognition words (e.g., reason, realize, understand), affective words (e.g., happy, ugly, bitter), and perceptual words (view, listen, felt) to describe IPV experiences.

Analyses only included posts that were direct responses to the thread rather than responses to existing comments, leaving 120 posts in the analyses. Of these, 65% indicated resilience and 80% indicated PTG. Importantly, resilience and PTG can both be experienced by survivors as 61% posts included themes of both PTG and resilience. Posts containing PTG, resilience, or both, were more likely to have perceptual language and affective language than posts that did not, but there were no differences with respect to cognitive language.

Our findings suggest survivors of IPV appear to be able to experience both resilience and PTG. This speaks directly to recent controversies in the post-trauma literature and suggests that resilience and PTG may be separate trajectories which can both be experienced by survivors.

Additionally, survivors are more likely to include perceptual and affective language when conveying resilience and PTG.

Faculty: ARTS Department: PSYCHOLOGY CUE Annual Research & Innovation Conference 2025

37

POSTER PRESENTATION Poster 5

Ariel Diduck, Elizabeth Farrell

Chapters 9,10,11 Reflection And Review

So I made a quick slideshow presentation going over what we have learned this semester to summarize in a fun way with attaching my personal experiences with my work life and giving my classmates an insight

how some of these factors affect my life. I added a short video in there to make the presentation a little more interesting whilst backing up my information.

Faculty: MANAGEMENT Department: MANAGEMENT 38

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 6

Baidya Nath Saha

Artificial Intelligence Voice Assistant With RetrievalAugmented Generation To Revolutionize Secure Information Retrieval In University Communication Backround: Large language models, such as ChatGPT, have revolutionized information retrieval and communication. These models generate human-like responses but raise concerns about data privacy and security.

Universities may hesitate to share sensitive institutional data with external artificial intelligence providers like OpenAI or Google.

This research aims to develop a secure, university-specific artificial intelligencepowered voice assistant that enhances digital communication while preserving data privacy.

Students often struggle to find essential university-related information due to time-consuming and unengaging webbased resources. While university websites contain valuable resources, students are often unmotivated to navigate lengthy and complex documents. This lack of engagement can lead to missed opportunities and difficulties in accessing crucial information.

A university-specific artificial intelligencepowered voice assistant can revolutionize digital communication, making institutional information more accessible in an interactive and secure manner.

Purpose: This research focuses on integrating large language models with RetrievalAugmented Generation to create an artificial intelligence-powered voice assistant. The system enhances university communication by providing real-time, user-friendly access to institutional information while ensuring privacy and security.

Methods: Retrieval-Augmented Generation enhances response accuracy by retrieving relevant information from university documents using vector-based similarity searches before generating responses. This ensures the assistant provides institution-specific, upto-date answers.Light Retrieval-Augmented Generation builds on this by incorporating

graph-based retrieval, structuring data into a knowledge graph for more context-aware responses. The system employs: • Low-Level Retrieval: Extracts specific, detailed information.

• High-Level Retrieval: Aggregates broader insights and related concepts.

• This enables more structured and contextually relevant responses.

Additionally, the assistant supports voice interactions through automatic speech recognition and text-to-speech capabilities for seamless user engagement.

Results: In an experimental application at Concordia University of Edmonton, this system was implemented to assist students in retrieving real-time scholarship information.

The results demonstrated significant improvements in accessibility and engagement compared to traditional web-based resources.

By utilizing both vector-based and knowledge graph retrieval, the system delivered more precise and contextually relevant responses.

Students were able to interact with the voice assistant to quickly obtain relevant information, reducing the need to manually search through complex documents.

Conclusion: By combining Retrieval-Augmented Generation with Light Retrieval-Augmented Generation, this artificial intelligence-powered voice assistant bridges the gap between structured and unstructured data retrieval.

Unlike general artificial intelligence tools that require external data sharing, this system enables universities to maintain data control while leveraging advanced artificial intelligence capabilities. Future expansions will incorporate broader university-related data, further transforming institutional communication and engagement for students and faculty.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

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POSTER PRESENTATION Poster 7

Bhavithra Suruliyandi Selvakumar, Baidya Saha

Space Debris Detection Using Machine Learning And Computer Vision

Background: Space debris, particularly fragments smaller than 5 cm, poses a significant threat to satellites and space missions. Millions of these fast-moving objects orbit Earth at high speeds, and current tracking systems like radar and telescopes struggle to detect them in real time, increasing the risk of collisions.

Traditional systems are expensive and slow, often failing to detect small debris promptly.

This project addresses these challenges by providing a scalable and cost-effective solution for real-time detection and tracking.

Purpose: The purpose of this project is to develop a machine learning and computer vision-based system to detect and track small space debris in real time. The goal is to enhance space safety by providing early collision warnings, offering a more effective and accessible alternative to current space debris detection systems.

facilitating faster decision-making.

4. Validation: The system will be tested with simulated scenarios to ensure its effectiveness, and educational resources will be provided to help operators manage debris risks.

Result(s) - or Anticipated Results: The expected outcomes of this project include: 1. Operational Space Debris Detection System: A fully functional system that tracks debris in real time and provides collision warnings.

2. Valuable Insights into Debris Patterns: Insights into debris patterns, aiding in risk mitigation strategies.

3. Cost-Effective Solution: A faster and more affordable system compared to traditional radar-based systems, making space safety more accessible.

Method(s): This project follows a systematic approach encompassing data collection, system development, and validation:

4. Enhanced Space Safety: A contribution to improving space situational awareness and reducing collision risks for spacecraft.

1. Data Collection: Diverse data, including real images of space debris, computergenerated images, and orbital data from NASA and SpaceTrack, are collected.

Conclusion(s): This project enhances space safety by detecting and tracking small debris, reducing collision risks for spacecraft. The system’s real-time capabilities support sustainable space operations, and future work integrates satellite live feeds to improve prediction accuracy using real-time data. By advancing space situational awareness, this initiative represents a significant contribution to the future of space exploration and safety.

2. System Development: AI-based image analysis and computer vision techniques are applied to detect and predict the movement of space debris in real time.

3. Visualization: A 3D interface will be created to help space operators visualize debris orbits and collision risks intuitively,

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY 40

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 8

Brynmar Degenhardt, Nischal Balami, Cole Babcock, Makan Golizeh, and Bradley Scott

Biomarker Discovery Of Iron-Induced Glycation In Human Cells

Background: Non-enzymatic glycation is a natural process that can cause cell damage and death through the accumulation of advanced glycation end products. Reactive oxygen species are highly reactive molecules that can increase rates of glycation in cells when they are overabundant and advanced glycation end products increase their rate of formation, creating a positive feedback loop with non-enzymatic glycation. Both nonenzymatic glycation and reactive oxygen species production can be increased by heavy metals like iron, which is the most abundant heavy metal in blood. These advanced glycation end products are poorly processed by cells, causing them to accumulate and react with other biological molecules, causing structural damage and plaque formation. The accumulation of these advanced glycation end products has also been associated with diseases like cancer, diabetes, and even aging.

Purpose: This research is looking at identifying specific markers of iron induced glycation to facilitate the study of how advanced glycation end products are associated with these diseases.

Methods: Human cells were grown in cultures and artificially stressed to mimic the natural stress in the human body. One group was treated with a natural compound that renders iron less chemically reactive

to prevent it from increasing the glycation reaction. Another group was grown under stress-free conditions as a control. All groups were then collected and analyzed using high-definition techniques that show different molecules present, including advanced glycation end products.

Results: An analytical workflow has been developed to study metal-induced glycation in human cells using an untargeted metabolomics approach.

Currently, our results have shown four potential biomarkers have been identified and are awaiting confirmation. A followup experiment has been conducted using additional treatments, and the data is being analyzed. Pending confirmation, the potential biomarkers from the first trial and any that may be found in the second trial could be used to characterize any potential association between human diseases and iron-induced non-enzymatic glycation.

Conclusion: This study identified four tentative biomarkers for iron induced glycation. This shows that iron can induce non-enzymatic glycation in human cells and natural compounds that decrease iron’s chemical reactivity can reduce the rate of glycation in the cells. Further studies are needed to confirm the effect of iron-induced glycation on the rate of nonenzymatic glycation in humans.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES CUE Annual Research & Innovation Conference 2025

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POSTER PRESENTATION Poster 9

Christopher Katan, Chrissy Knapp

Microwave Spectropscopy and Electronic Structure Calculations Of 4-Nitrophenol

In recent years, North America has seen a significant increase in wildfire activity. In correlation with wildfires a rise in organic aerosols in the atmosphere is observed, which are known to have negative health effects. Aerosols can also absorb or reflect solar radiation and therefore affect Earth’s climate. One class of aromatic compounds found in brown carbon (BrC) aerosols is nitrophenols. Because of the presence of the nitro and hydroxide group, they are able to form clusters with water and other atmospheric compounds, which affects their transport and persistence in the atmosphere.

In order to better understand the formation of aerosol particles containing nitrophenols we focus on 4-nitrophenol.

In particular, we are interested in the structure and hydrogen bonding capacity of 4-nitrophenol and in the formation of 4-nitrophenol hydrates, which may be involved in the first steps of aerosol particle formation. We used a combination of computational chemistry and microwave spectroscopy to study rotational spectra

of 4-nitrophenol and 4-nitrophenol – H2O, to gain insights into energetics and conformational diversity.

The spectra were measured in the range from 2-8 GHz using a chirped-pulse Fourier transform microwave spectrometer. Our initial fit of the spectrum yielded rotational constants, 14N nuclear quadrupole coupling constants, and centrifugal distortion constants, which will be presented and discussed. To predict the structure of the 4-nitrophenol hydrate we performed conformational searches with Conformer-Rotamer Ensemble Sampling Tool (CREST), resulting in nine possible conformers. Further structural refinement was performed using Gaussian16 at the B3LYP-D3(BJ)/, def2-TZVP level, resulting in only one possible conformers within an energy window of 10 kJ/mol. So far, the low vapour pressure of 4-nitrophenol has prevented an assignment of the hydrate spectrum; however, future work will focus on higher order clusters computationally, as well as experimental investigations of other nitrophenols.

Faculty: SCIENCE Department: OTHER 42

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 10

Damilola Innomesanghan, Damilola Innomesanghan, Emmanuel Kiwamu, Sergey Butakov, and Eslam AbdAllah

Ensuring Information Security In Inclusive Digital Environments

Individuals impacted by disabilities see various adverse effects in their day-today lives, specifically individuals on a spectrum who are unable to integrate into the workforce. To help ensure equitable access for individuals with disabilities, Assistive Technology (AT) bridges this gap by providing specialized tools and devices that empower individuals with disabilities to interact with digital environments seamlessly. These technologies range from screen readers and speech recognition software to adaptive hardware. While AT promote inclusion, they also introduce unique cybersecurity and privacy risks.

The sensitive nature of user data, ranging from biometric information to personal communication logs, demands stringent security measures. Small and mediumsized enterprises (SMEs), often at the forefront of AT deployment and integration, may lack the resources or expertise to implement robust security frameworks. This

is where information security standards, such as ISO 27001, play a crucial role. ISO 27001 provides a structured approach to establishing, implementing, maintaining, and continually improving an Information Security Management System (ISMS). This ensures that SMEs can protect sensitive AT data while complying with security best practices. This paper is divided into two parts. The first part provides an overview of assistive technologies, relevant security standards, and key ISO 27001 controls for securing AT solutions. The second part presents a case study of a Canadianbased SME that employs a neurodiverse workforce, including individuals with Autism Spectrum Disorder (ASD). The paper explores the organization’s approach to implementing ISO 27001 while considering the unique requirements of assistive technologies, the challenges faced during implementation, and the strategies used to mitigate them.

Faculty: MANAGEMENT INFORMATION SYSTEMS ASSURANCE MANAGEMENT Department: AND INFORMATION SYSTEMS SECURITY MANAGEMENT CUE Annual Research & Innovation Conference 2025

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POSTER PRESENTATION Poster 11

Dana LaBoucane, Elizabeth Farrell

HR220 Review And Reflection

This project is a summary and reflection about some of the information learned in the HR 220 Introduction to HR Management course. The three chapters reviewed cover topics of Unions, Labour Relations, Managing International Employees and Assignments,

HRM Measurements, High Performance Systems, and Turnover, and more. I was able to relate personal experience to the topics discussed in class to better understand the roles of HR professionals.

Faculty: MANAGEMENT Department: MANAGEMENT 44

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 12

Denae Michie, Kenes Konnayil and Amanda DeGuerre

Voices In Crisis: Exploring The Lived Experiences Of Active Law Enforcement Officers

This study investigates the psychological experiences of Active Law Enforcement Officers involved in addressing suicidal crises among fellow law enforcement officers. Police suicides present unique complexities, influenced by factors such as work conflicts, PTSD diagnoses, firearmrelated deaths, and separation or divorce.

While police officers are not necessarily more likely than the general population to complete suicide, research highlights their elevated rates of suicidal ideation and planning. This research addresses a significant gap in the literature by focusing on the psychological effects experienced

by Active Law Enforcement Officers during crises involving a fellow officer.

This area has been largely overlooked in academic studies thus bearing this question: what is the lived experience of engaging in crisis negotiations/ interventions with a fellow officer in a

suicidal crisis? Six to ten participants were recruited. Each participant took part in a one-on-one semi-structured interview consisting of core questions that allowed flexibility for participants to elaborate on their unique experiences.

The interviews consisted of openended questions designed to facilitate discussion while allowing participants to express their thoughts and feelings in their own words. Data was collected via audio-recordings and transcribed using Giorgi’s phenomenological method which focused on uncovering the essence of the participants’ lived experiences. Due to the qualitative nature of this study, we anticipate identifying key themes of emotions, thoughts, and behaviours related to the participants’ experiences.

Additionally, we hope to highlight coping strategies, and their impact on personal and professional roles.

Faculty: ARTS Department: PSYCHOLOGY CUE Annual Research & Innovation Conference 2025

45

POSTER PRESENTATION Poster 13

Dylan Hrenchuk, Cole Babcock and Makan Golizeh

In Silico Assessment Of Non-Enzymatic Glycation Human Protein Targets

Background: Advanced glycation end products (AGEs) are the final products of the nonenzymatic glycation of proteins, lipids, and nucleic acids. This study focuses on proteins within the human body that form AGEs in the presence of a reducing sugar when the proteins contain arginine and lysine amino acids.

These undesirable end products are related to health conditions such as neurodegenerative diseases, cardiovascular diseases, diabetes, and cancers. To better understand how these unwanted end-products affect the human body a knowledgebase classification analysis known as gene ontology analysis is performed. Gene ontology is a unifying concept in bioinformatics that structures and standardizes biological knowledge. It describes terms or concepts that are connected via defined relationships. Gene ontology is composed of three aspects molecular function, cellular component, and biological processes. Through these aspects, proteins can be classified based on what they do, where they are, and what bigger picture they are a part of.

Purpose: To evaluate the most likely candidates for protein AGE formation within the human body.

Additionally, we look at what metabolic pathways these proteins belong to within the body to see if subsequent conditions can be explained or further explored.

Method(s): Protein information was extracted from the UniProt knowledgebase in a TSV file format and imported into Microsoft Excel. Correlation analyses were run evaluating arginine+lysine content against selected physiological properties of humans. Graphs were constructed to represent the relationship between each set of variables.

Proteins were then evaluated and those with 20% or more argnine+lysine content were saved to a file. Gene ontology was ran using Protein

Analysis Through Evolutionary Relationships (PANTHER) and InnateDB web tools. The results were graphically represented. A protein-protein interaction network was also produced using the Cytoscape software with the Cerebral plugin.

Results: It was found that there is a strong positive correlation between the molecular weight, length, and argnine+lysine content of human proteins. Moreover, there was a weak negative correlation between average hydropathy and argnine+lysine content of human proteins. The correlation between isoelectric point and arginine+lysine content was very weak with a negative correlation. Through gene ontology analysis it was found that most of the human protein targets of AGE modification had a binding molecular function, with poly(A) RNA binding and RNA binding functions being more specific. These proteins were also primarily involved in cellular processes. Finally, the human protein targets of AGE modification were mainly localized in a cellular anatomical structure, such as ribosomes. However, the network analysis and Cytoscape Cerebral plugin revealed that the majority of the protein-protein interactions occur within the cell nucleus.

Conclusions: AGE formation has the potential to harm the ability of proteins to bind particularly those involved in RNA binding. This is especially important during protein translation where ribosomal proteins must effectively bind to messenger RNA molecules. AGEs also damage cellular structures such as ribosomes. Meanwhile, AGE formation can negatively affect biological processes such as cellular communication and signaling resulting in changes to how a cell functions and interacts with another cell.

Faculty: SCIENCE Department: ENVIRONMENTAL AND PHYSICAL SCIENCES 46

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 14

Elizabeth Farrell

Bases For Employees’ Compliance With Organizational And Government Change Policies: A Scenario-Based Study Using Covid-19 Vaccine Mandates Introduction: It is important to understand the factors that underpin compliance or resistance of employees to organizational and government policies. This study investigates employees’ willingness to accept the COVID-19 vaccine under three scenarios: (a) of their own free will; (b) if employer-recommended; (c) if governmentrecommended.

Data and Results: 127 participants were surveyed and responded to the survey.

40%, 42%, and 8% will accept, not accept, and may or may not accept the vaccine of their own free will, respectively. If employer-recommended, 36% would accept, 35% would not accept, and 28% may or may not accept it. If governmentrecommended, 33% would accept, 45% would not accept, and 22% may or may not accept it. Twelve participants changed their response towards vaccine-compliance between the free-will scenario and employer-recommended scenario: 6/12 to

keep their jobs, 2/12 to protect their health, and 1/12 because of trust in their employer.

Seventeen (17) participants changed their response towards vaccine resistance between the free-will and governmentrecommended scenarios: 11/17 due to lack of trust in the government and 2/17 due to lack of confidence in the vaccine. Five (5) participants changed their response towards vaccine compliance between the free-will and government-recommended scenarios on the condition that the vaccine was mandatory and confirmed to be safe.

Summary and Conclusion: In conclusion, trust and livelihood underpin employee compliance with new organizational and government policies; hence, it is important for policies makers to establish policies that seek to protect the interests of its’ employees by building trust as foundation.

Keywords: workplace, policies, covid_19, hesitancy, employees.

Faculty: MANAGEMENT Department: MANAGEMENT CUE Annual Research & Innovation Conference 2025

47

POSTER PRESENTATION Poster 15

Elkan Ekhator, Elizabeth Farrell

Personal Reflection On Chapter 9,10, And 11

Chapters 9, 10, and 11 taught me about the realities of HR in an ever-increasingly complicated socioeconomic world. From labor relations to global HR to highperformance work systems, the past few chapters showed that for organizations to survive, they must always be on their toes, challenging themselves and their

employees, learning to navigate group dynamics, cultural engagements, and international borders. Thus, in this reflective chapter, I will discuss what I’ve learned, how I’ll be able to apply this to business situations for the rest of my life, and how my mindset has changed compared to what will be necessary for real-world application.

Faculty: MANAGEMENT Department: MANAGEMENT 48

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 16

Glory Deji-Akinlotan, Wali Mohammad Abdullah

Enhancing Medication Adherence & Appointment Management In Mental Healthcare Through Digital Health Apps Background: Medication non-adherence and missed healthcare appointments present significant barriers to effective treatment, particularly for individuals managing chronic and mental health conditions. Studies indicate that nearly 50% of patients with chronic illnesses fail to take medications as prescribed, leading to worsening health outcomes, increased hospitalizations, and higher healthcare costs.

Contributing factors include forgetfulness, lack of motivation, side effects, and financial constraints.

Digital health applications offer an innovative approach to improving adherence by integrating medication reminders, appointment scheduling, and real-time communication with healthcare providers. These solutions leverage automation and data analytics to enhance patient engagement and streamline healthcare management.

Purpose: This study investigates the effectiveness of digital health applications in addressing medication non-adherence and appointment scheduling challenges. The research involves developing an AI-driven simulation model to evaluate various app features, including automated alerts, personalized scheduling, and compliance tracking. By analyzing patient interaction data, the study will quantify the impact of digital interventions on adherence rates and healthcare efficiency.

Methods: A simulation framework will model patient behavior across diverse demographics, health conditions, and socio-economic backgrounds.

The digital health platform will incorporate AIdriven functionalities such as dynamic medication schedules, predictive adherence tracking, and real-time notifications. Machine learning models will analyze user engagement, behavioral trends, and compliance patterns. Statistical techniques, including regression analysis and time-series forecasting, will be employed to assess the correlation between app

usage and adherence improvements.

Anticipated Results: Existing research indicates that digital health interventions, such as smartphone applications, can significantly enhance treatment adherence. A study demonstrated that individuals using a health app, in conjunction with medication, reduced opioid use by 35% and remained in treatment 19% longer than those using only medication. In Canada, approximately 14.6 million adults aged 12 and older (45.1%) reported having at least one major chronic condition in 2021. Assuming a conservative digital health app adoption rate of 20%, around 2.9 million individuals could potentially benefit from such interventions. For mental health patients, real-time engagement with healthcare providers has been associated with improved adherence rates. While specific multipliers vary, the integration of digital platforms facilitating immediate communication may lead to substantial reductions in missed appointments and enhanced compliance with prescribed treatments.

Additionally, AI-driven compliance tracking is projected to reduce late or skipped medication doses. Although exact percentages differ across studies, the implementation of personalized reminders and monitoring can lead to notable improvements in medication adherence compared to traditional methods.

Conclusion: This study highlights the potential of AI-powered digital health applications to enhance medication adherence and appointment management. By integrating predictive analytics and patient-centered design, these solutions can optimize treatment outcomes and reduce healthcare inefficiencies. Future research will explore real-world implementation strategies and the scalability of AI-driven interventions in broader healthcare settings.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

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POSTER PRESENTATION Poster 17

Hannah Batchelor, Seyma Yildirim-Erbasli

Examining Gender Differences In Personality And Temperament: Insights From The TIPI And FTI

Examining gender differences in personality and temperament is essential for interpreting psychological assessments accurately. This study addresses this issue by investigating personality and temperament measures in terms of gender differences: the Ten Item Personality Inventory (TIPI) and the Fisher Temperament Inventory (FTI). We used the publicly available FTI dataset collected in 2019. Participants (n = 3,967; aged 20–78) completed the FTI, which involved a series of questions about personal temperament and the TIPI, and indicated whether they identified as female or male. The sample included 3,445 male participants and 522 female participants. Initially, we calculated composite scores to determine the

medians for each temperament subtype and the TIPI measure. Then, we conducted a Mann-Whitney U-test to determine if personality and temperament measures differed significantly between males and females. The results showed a significant difference between male and female participants in the TIPI scale and each FTI subscale (curious/energetic, cautious/social norm compliant, analytical/tough-minded, and prosocial/empathetic scales). These findings suggest that gender significantly influences responses to both the TIPI and the FTI scales, highlighting the importance of considering gender as a factor when interpreting personality and temperament measures.

Faculty: ARTS Department: PSYCHOLOGY 50

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 18

Hasti Mahdi Zadeh, Salima Sawani, Jonathan Chua, Patricia Hernandez Rivera, and Friesen Reid

Navigating Oral Medicine And Pathology In Orthodontic Treatment

Background: Oral health is an important factor in orthodontic care; various conditions can affect the outcomes of treatments such as, jaw lesions, tissue growth, and infection. Orthodontists try to recognize these issues early with the aim of adjusting treatment plans and providing the best care options for patients.

Purpose: This study aims to understand how oral disease can impact orthodontic care by exploring the connection between them. It highlights the need to find solutions that allow orthodontists to manage these conditions while still ensuring that the patient’s braces or other orthodontic appliances work effectively.

Methods: Since this is a review article, it reviews several researches on oral disease, which can affect orthodontic treatment. it focuses on soft tissue disease, infections, and jaw lesions that are frequently seen in orthodontic patients. to provide better care, this study tries to distinguish the

intersection between orthodontists work and other dental and medical specialists to provide better care.

Results: The findings of the study found that certain mouth problems, like cold sores, frequent mouth ulcers, and swollen gums, can make orthodontic treatment harder.

In some cases, the orthodontist may need to change the type of braces or even take a break from treatment until the issue improves.

Conclusion: In general, once orthodontists understand and manage oral diseases effectively, they can improve patient outcomes and reduce the possible errors, so a collaborative approach involving dentists and medical professionals would be a good idea to make sure patients receive comprehensive care. For example, early diagnosis and regular check-ups can help orthodontists address oral health challenges while achieving successful orthodontic results.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES CUE Annual Research & Innovation Conference 2025

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POSTER PRESENTATION Poster 19

Hong An Tran, Eslam AbdAllah

Over the last few years, internet connections and bandwidth demands continuously increase explosively. Although the Internet is still an impeccable paradigm of interconnectivities, the rapid growth of the Internet in data size, data created speed and connection speed requests a new methodology of communication which allows more efficient data exchange in the future. One of the emerging networking technologies which is a potential successor candidate to the host-centric paradigm is Information-centric Networking (ICN).

This new ICN communication paradigm that has unique characteristics of locationindependent naming, name-based routing and in-network caching, deliberates the current host-centric network with new network of scalability, data availability, mobility and other advantages. However, due to its native attributes, security in

ICN is facing challenging requirements as data is pervasive without a persistent host or channel for security suite to be imposed but rather, “in ICN, securing the data content is much more important than securing the infrastructure or the endpoints”. This paper will examine various security aspects associated with the distinctive attributes of ICN and study a proposing solution of security in ICN to address the confidentiality, the integrity, the availability, the authentication, the nonrepudiation and the privacy requirements of security. Furthermore, simulations and computational performance on this proposed solution are also explored and studied to prove it could be a promising solution that satisfies the aforementioned security requirements and feasibilities in the new internet paradigm.

Faculty: MANAGEMENT SYSTEMS ASSURANCE MANAGEMENT Department: INFORMATION AND INFORMATION SYSTEMS SECURITY MANAGEMENT 52

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 20

Jacob Wade, Trevor Cook

What Temperance Does And The Epic Tradition: Implicit Allegorical Criticism In The Faerie Queen’s Book II

Temperance, like all the Faerie Queen’s virtues, is an exercise in exemplarity meant to help the reader better themselves. In his letter to Raleigh, Spenser expresses these intentions, hoping to exemplify the qualities of Virgil and represent the twelve Aristotelian virtues. However, Spenser hints at the unique composition of his second book. By placing Guyon (the hero of

temperance) in a story of recognizable and even famous moments for classical epics, Spenser invites allegorical analysis that reveals discrepancies between Guyon’s actions and those of past epic heroes like Aeneas, Odysseus, Achilles or Rinaldo.

While exemplars of heroism, these classical figures often demonstrate what Spenser could only call intemperate.

Faculty: ARTS Department: LITERATURE AND LANGUAGE CUE Annual Research & Innovation Conference 2025

53

POSTER PRESENTATION Poster 21

Jinelle Xaviera Kamgue Djuidje, Elizabeth Farrell

Is a TikTok video of 8 min talking about high performance organization

Faculty: MANAGEMENT Department: MANAGEMENT 54

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 22

John Walsh, Brandon Zurawell, Jacob Hambrook, Patrick Hanington

DNA-Based Monitoring Of Aquatic Invasive Species In Urban Stormwater Ponds

Aquatic invasive species can quickly expand in population size, causing both ecological and infrastructural disruption.

In the greater Edmonton and Calgary regions, population explosions of invasive Goldfish and Prussian Carp regularly occur within stormwater systems and require significant mitigation efforts for effective removal. Unfortunately, aspects of carp biology allow these fish to remain undetected even as populations grow.

Genetic tools such as quantitative PCR (qPCR), which amplify shed DNA from environmental samples (eDNA), have become proven methods for the sensitive detection of hard-to-observe species.

Between May and August 2024—as part of a province-wide effort to map the presence

of invasive carp in Alberta—an eDNA-based monitoring program was conducted across 27 stormwater ponds and connecting streams in Sherwood Park and Edmonton. eDNA was captured using simple on-site water filtration, and species presence was tested using species-specific qPCR assays targeting Carassius auratus (Goldfish), Carassius gibelio (Prussian Carp), and Faxonius virilis (Northern Crayfish).

Although the sampled region is not currently experiencing severe impacts from invasive species, there were positive detections of Northern Crayfish at two sites and Prussian Carp at three. These results highlight the sensitivity of eDNA-based detection and support its continued use for early monitoring in urban aquatic systems.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES CUE Annual Research & Innovation Conference 2025

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POSTER PRESENTATION Poster 23

Jonathan Strand

The Significance Value Of Freedom

Here we argue for an explanation of (one reason) why human beings value freedom.

The explanation is deduced from analyses of the concepts of ‘significance’ and ‘making a difference’: Human beings value freedom, at least in part, because freedom affords a person greater opportunity to make a difference—and so be significant.

The deduction proceeds roughly as follows: 1. People have a desire for significance; they want to “matter”.

2. One way in which a thing can matter—and so be significant—is by “making a difference”.

3. Any state of affairs that obtains is a difference a thing makes, if that state of affairs would, or might, or could have not obtained (and its obtaining would have been less likely), if that thing had not existed/occurred/obtained.

4. Similarly, if a thing causes a state of affairs to obtain, which state of affairs might or could have not obtain (simpliciter), that state of affairs is a difference that thing makes.

5. People frequently value all these sorts of made differences, and the totality of differences a thing makes can be called “the” difference that thing makes.

6. Things which behave indeterministically— assuming such are possible—would be capable of making differences otherwiseidentical deterministic things cannot make. a. An indeterministic thing would be able to bring about states of affairs that could or might have not obtained (in that situation). b. Otherwise-identical deterministic things are incapable of such differences.

7. So, because they can make more differences than otherwise-identical deterministic things, indeterministic things can make a greater difference than otherwise-identical deterministic things; they would thereby matter more, be more significant.

8. Anything with libertarian free will be indeterministic in its free decisions/ actions; its life will involve things done in an indeterministic manner.

9. Persons with libertarian free will, then, would be able to make differences an otherwiseidentical determined person cannot make— and so make a greater difference.

10. Persons with such free will would also be able to make differences merely indeterministic things cannot make—by intentionally doing things for good reasons.

11. All else being equal, then, a free person’s life can matter more, and so be more significant, than a determined person’s life.

12. Given our desire for significance, then, the common desire for freedom is well-founded.

13. These things may also be part of the explanation of why people oppose restrictions to their own freedom, and why restricting others’ freedom is ethically problematic: a. A person with more freedom can and does make more differences and so has more opportunities for significance. b. And reducing a person’s freedom reduces the ways in which they can and do make a difference and so the ways in which they can be significant.

Faculty: ARTS Department: PHILOSOPHY, RELIGIOUS STUDIES AND CLASSICS 56

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 24

Juhaina Kasimali, Nina Otchere and Shaun Aghili

AI Assurance: Ensuring Reliability, Safety, And Ethical Compliance

Artificial Intelligence (AI) is increasingly integrated into critical sectors, necessitating robust assurance frameworks to ensure reliability, safety, and ethical compliance. This study explores AI assurance as a multidisciplinary approach encompassing verification, validation, risk management, and ethical auditing.

It examines existing frameworks such as the NIST AI Risk Management Framework and ISO/IEC 42001:2023, emphasizing their role in mitigating biases, enhancing transparency, and ensuring compliance with evolving regulatory landscapes.

Additionally, this review highlights case studies, including Amazon’s facial recognition tool and the COMPAS risk assessment model, illustrating ethical challenges in AI deployment. The study further evaluates AI safety mechanisms

such as fail-safe designs, formal verification techniques, and explainability methods to promote trust in AI systems. Despite advancements, limitations persist, including security vulnerabilities, regulatory gaps, and the trade-off between explainability and performance. Emerging technologies such as quantum computing and advanced explainability techniques are proposed as solutions to enhance AI assurance.

The findings underscore the necessity of interdisciplinary collaboration, continuous monitoring, and adaptive regulatory frameworks to sustain ethical AI development. By fostering transparency, accountability, and compliance, AI assurance supports the responsible evolution of AI technologies, ensuring their alignment with societal and ethical expectations.

Faculty: MANAGEMENT SYSTEMS ASSURANCE MANAGEMENT Department: INFORMATION AND INFORMATION SYSTEMS SECURITY MANAGEMENT CUE Annual Research & Innovation Conference 2025

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POSTER PRESENTATION Poster 25

Kacianne Kawulok, Rachel Campbell, Jessica Dubauskas, Ajay Mangat, Tessa Granson-Woolard, and Alexander Taikh

The Influence Of Word Position On Speech Disfluencies In Adults Who Stutter

Stuttering is a developmental speech disorder that causes disruptions in the normal flow of speech. Stuttering can be characterized into three distinct types of disfluencies; repetitions, prolongations, and blocks. The cognitive demands of processing linguistic information may destabilize the speech motor system and thus result in a disfluency. For example, content words (compared to function words) carry more information about meaning, and are more likely to be stuttered on. Similarly, the demands of planning the production of a sentence can result in speech disfluencies. Planning the production of a sentence occurs in stages (Garrett, 1975), which differ in scope.

In the functional stage, which has the greatest scope, semantic information and grammatical cues are planned to assign meaning to the utterance. Next, words are arranged in an order and morphemes are added in the positional stage. Finally, during the phonological encoding stage, the speaker assembles a series of sounds into an articulator plan. The phonological encoding stage has the smallest scope, where the articulatory plan is created for fewer words in advance. Quarrington

(1965) found that stuttered words tend to occur more frequently at the beginning of a sentence, suggesting that the cognitive demands of planning the remaining sentence can interfere with the production of the word currently being articulated.

In the present study, we examine whether the influence of word position differs for content words and function words. Whereas content words, which carry meaning about the sentence, may be planned in advance, function words may not be. Using recordings of adults who stutter reading short passages that are available in the Fluency Bank database (MacWhinney & Ratner, 2021) we found that disfluencies were more likely for function words that occurred in an earlier sentence position.

In contrast, the likelihood of a disfluency on content words was not influenced by their position in the sentence. Content words contain meaning information about the sentence, and may thus be planned earlier than function words. The planning and/or articulation of function words may thus be more influenced by the number of remaining words in the sentence.

Faculty: ARTS Department: PSYCHOLOGY 58

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 26

Kale Martinson, Xin Chen

Investigating Phosphate Uptake Efficiency Of Carex Aquatilis In Floating Treatment Wetlands

Hazardous algae blooms are a problem that many Albertan lakes are currently faced with. These algae blooms are linked to the increased amount of nutrients, namely phosphate, within the water. These nutrients are often a byproduct of the high levels of agriculture and industry within Alberta and other western provinces.

Floating treatment wetlands (FTWs) are one way of removing excess phosphate from the water. FTWs are rafts designed to accommodate plants that absorb nutrients directly from the water. This study focused on the applicability of this technology in Alberta, using a native wetland species,

Carex aquatilis. In this study, there are two treatments; both treatments are composed of a reservoir, a raft, and water with elevated levels of Phosphate. The plant treatment contains four plants per raft, and the control lacks any plants. The levels of phosphate of each replicate were measured over the course of 7 days. The changes in phosphate level were calculated, and a statistical t-test was used to determine significance. The results illustrate the utility of Carex aquatilis in floating treatment wetlands. However, future research should investigate the utility of similar Albertan species in similar systems.

Faculty: SCIENCE Department: ENVIRONMENTAL AND PHYSICAL SCIENCES CUE Annual Research & Innovation Conference 2025

59

POSTER PRESENTATION Poster 27

Keegan MacLeod, Keira Gow, and Alexander Taikh

Irregular Typing Patterns, Letter Masking, And Their Influence On Typing And Perceived Memorability Of Passphrases

Keystroke latencies reflect the multiple stages involved in typing a word, including identifying it, planning the sequence of keystrokes, and executing that sequence.

According to interactive theories of typing, linguistic information influences all stages of this process, including the planning and execution of the keystrokes. Passphrases include words, and their typing and execution are thus influenced by linguistic information. Secure passphrases are less predictable due to irregular typing patterns that come from including, for example, an uppercase letter that is not in the initial position of a word. A non-initial uppercase letter disrupts typing the passphrase because it creates an irregular typing pattern (i.e., a shift key in the middle of the word) resulting in slower keystroke execution (Gow et al., 2024). The irregular typing pattern reduces motoric fluency which may also reduce how memorable the passphrase is perceived to be (Dollois et al., 2022). Additionally, masking typed letters, another security measure, removes visual feedback during typing, which can make planning and executing keystrokes more difficult.

In the current study, participants typed a three-word passphrase (e.g., swandishgrub made from the words swan, dish, grub) which had a non-initial uppercase letter embedded in the first word, second word, or third word and rated how memorable they felt the passphrase was. The typed

letters were either visible or masked with a “*”. Embedding an uppercase letter in the middle word resulted in the passphrase being typed more slowly, and rated as least memorable, than when the uppercase letter was embedded in the first or the third word. Specifically, in passphrases with the uppercase letter in the middle word, the unaltered first and third words were typed more slowly than in passphrases with no uppercase letters. The slowed typing of the first word may be due to the difficulty of concurrently planning the irregular keystroke sequence of the second word.

The slowed typing of the third word may be due to reduced planning while typing the irregular sequence of keystrokes of the second word. The disruption of the first and third words by the irregular middle word is consistent with the influence of linguistic information on all stages of typing, as posited by interactive theories. Furthermore, a decrease in motoric fluency during typing predicted a lower perceived memorability of the passphrase. Masking the typed letters reduced the effect of uppercase letter position on typing speed but not perceived memorability. The masking may result in a different planning process, since typed letters cannot be seen, and potentially in greater reliance on visual feedback from the hands and keyboard.

Faculty: ARTS Department: PSYCHOLOGY 60

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 28

Kelley Polowy, Moriah J. Deimeke (Department of Psychology, University of Alberta), Christopher B. Sturdy (Neuroscience and Mental Health Institute, University of Alberta), Jenna V. Congdon (Department of Psychology, Concordia University of Edmonton)

A Cross-Species Exploration Of Enrichment And Behaviour In Nocturnal Raptors Significant progress has been made in understanding enrichment for diurnal species in human care. Yet, less is known about how enrichment impacts nocturnal and crepuscular species, especially outside of operational hours with reduced human presence. Institutional research often prioritizes charismatic megafauna, while birds—though common in zoological collections—receive less attention.

Enhancing the care of captive raptors (e.g., owls and hawks) is essential to encourage natural behaviours, increase cognitive stimulation, and reduce abnormal repetitive behaviour patterns. Here, we investigate and attempt to further align enrichment strategies with the natural activity patterns of raptors at the Edmonton Valley Zoo. Three species with circadian variation were selected: (1) spectacled owl (Pulsatrix perspicillata), (2) barn owl (Tyto alba), and (3) burrowing owl (Athene

cunicularia). Baseline observations were conducted to assess species-specific behavioural repertoires, guiding the design of individualized enrichments that could safely remain in enclosures overnight: (1) a sensory board for the spectacled owl to provide physical resistance opportunities; (2) a complex stand for the barn owl to offer varied perching and privacy options; and (3) an expansion of enclosure and substrate availability for the burrowing owl. By comparing baseline and post-enrichment behaviours, we aim to identify any changes in behaviour such as: (1) reduced selfdirected behaviours; (2) increased overall activity; and (3) greater engagement with enclosure space and materials. Broadly, this project will provide insight into the importance of monitoring nocturnal behaviour and aligning enrichment with the biological and behavioural needs of birds of prey.

Faculty: ARTS Department: PSYCHOLOGY CUE Annual Research & Innovation Conference 2025

61

POSTER PRESENTATION Poster 29

Khadija Abdi, Apoorva Chauhan

A Digital Literacy Toolkit For Seniors Empowering Them To Identify AI-Images And Deepfakes

Background: A growing number of seniors, defined as individuals over the age of 65, are increasingly using the Internet.

However, many face challenges, as they have not grown up surrounded by technology. The digital landscape today is further complicated by developments like AI-generated images and deepfakes.

AI-generated images are visuals created by artificial intelligence algorithms, which may or may not have harmful intentions. Deepfakes, on the other hand, are doctored media that involve the manipulation of audio, video, or images using AI technologies to deceive or mislead individuals. As technology continues to advance, it is becoming more difficult to distinguish between what is real and what is fake, particularly for seniors, who may lack the skills to identify such misleading information.

Purpose: This project aims to increase digital literacy among seniors by introducing a resource hub website tailored specifically for them. Digital literacy involves the skills, knowledge, and confidence needed to navigate the Internet effectively. The goal is to empower seniors with the tools to identify AI-generated images and deepfakes, reducing their susceptibility to online deception.

Method: The resource hub provides a variety of learning materials, including modules on AI-generated images and deepfakes. It includes self-paced questions to assess knowledge and understanding of concepts. Additionally, it has engaging activities such as word searches, crosswords, and scenario-based exercises to reinforce learning. Infographics and links to government resources are also included to help seniors better comprehend the material.

Results: It is anticipated that by using this resource hub, seniors will acquire the knowledge and skills necessary to confidently navigate the online world. This will lead to increased digital literacy, a stronger ability to identify misinformation, and greater online independence.

Conclusions: By providing a tailored educational resource that builds digital literacy, this project aims to empower seniors, improving their ability to engage with digital media safely and confidently.

Enhancing digital literacy among seniors will not only protect them from potential online harm but also foster a greater sense of independence in the digital age.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY 62

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 30

Khushi Jariwala, Md Morshedul Islam

Privacy Preserving Federated Learning For Medical Data

Federated Learning (FL) is a decentralized machine learning (ML) approach that enables multiple clients, such as hospitals, to collaboratively train a shared global model. Unlike traditional ML which relies on centralized data collection, an FL system stores data locally by allowing each participant to train a local model and share only model updates (e.g., gradients or weights) with a central server. This method improves data privacy, reduces communication overhead, and helps organizations comply with regulations like General Data Protection Regulation (GDPR).

However, FL systems remain vulnerable to several privacy threats, particularly when the central server is honest-but-curious.

In such scenarios, the server adheres to the protocol but attempts to infer sensitive information from the received model updates. This type of threat can lead to sensitive data leakage and compromise the privacy of users.

The objective of this research is to address the privacy challenges in FL systems when the central server is not fully trusted.

We propose a secure FL framework that incorporates Fully Homomorphic Encryption (FHE) to protect sensitive model updates from inference attacks. FHE is a cryptographic technique that allows computations to be performed directly on encrypted data, enabling privacypreserving operations without decryption.

In our proposed framework, each client shares its private and public HE keys while the server holds only the corresponding public HE key. Clients train their local models using private data and encrypt the resulting model parameters using their public HE keys before sending them to the server. Since the server does not have the any private HE key, it cannot decrypt the encrypted local model updates. The server uses its public key to combine the encrypted model updates into a newly encrypted, aggregated global model.

This encrypted global model is then sent back to the clients, who decrypt it using their private keys to continue the next round of training. This process repeats until the global model achieves satisfactory performance.

We evaluate our approach using medical datasets and the experimental results show that the proposed FHE-based FL framework achieves a high level of model accuracy, while effectively protecting against inference of private data by the server.

This research demonstrates that integrating FHE into FL systems can provide strong privacy guarantees without significantly compromising model performance. The proposed method is generalizable and can be applied to other data-sensitive domains such as finance, cybersecurity, and education.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

63

POSTER PRESENTATION Poster 31

Khushraj Kaur Saini, Apoorva Chauhan

Taste Together: A Dedicated Recipe-Sharing App

Background: In today’s fast-paced world, finding recipes that cater to personal tastes, dietary restrictions, and cultural preferences can be a challenge. While platforms like Instagram and YouTube offer visually appealing content, they often fail to meet the specific needs of users searching for recipes based on dietary restrictions, cooking times, or ingredient constraints. Many people also seek to explore new cuisines while maintaining a healthy lifestyle.

Although several recipe-sharing platforms exist, few focus on cultural diversity or provide tools to help users make healthier food choices.

Taste Together is an app designed to address these needs by providing users with a platform to discover, share, and save recipes tailored to their unique preferences, with a focus on cultural diversity and health-conscious eating.

Purpose: The primary objectives of Taste Together are to promote cultural diversity by offering a variety of recipes, particularly from Indian and Canadian cuisines; and second, to support healthier eating through personalized recipe recommendations. The app encourages cultural exchange by helping users explore authentic dishes from different cultural backgrounds while also providing tools to make healthier food choices, such as nutritional information and options to modify recipes to fit specific dietary needs. This project aims to develop a dedicated recipe-sharing app that addresses gaps in existing cooking platforms, particularly the lack of customizable filtering options.

Methods: A prototype of Taste Together will be developed based on initial user surveys.

Prototype testing and follow-up surveys will be used to refine the final app version. The app will be built with advanced filtering options, enabling

users to search for recipes based on preparation time, cooking time, calories, diet type, health considerations, meal category (breakfast, lunch, dinner, snacks, teatime), dish type (bread, cereals, starters, soups), and cuisine (Indian, Canadian).

Key features will include the ability to save, like, comment, share, and post recipe videos and images. The app will also incorporate social functionalities, such as user profile pages, a personalized home feed, messaging, and a follow system to foster community engagement.

Results: The app is expected to enhance user experience through its intuitive interface, helping users discover and customize recipes efficiently. Key features such as saving recipes, liking, commenting, sharing, and posting videos will encourage community engagement. With personalized recommendations and interactive elements, Taste Together aims to make cultural and health-conscious cooking more accessible and enjoyable. User engagement will be assessed through metrics such as feature usage, time spent on the app, and survey feedback on usability and satisfaction.

Conclusion: By integrating cultural diversity with health-conscious eating, Taste Together offers a unique platform that encourages users to share, explore, and discover recipes while prioritizing their health and dietary needs. The app’s inclusive features not only promote cultural exchange and awareness but also support healthier lifestyle choices. Through its userfriendly interface and interactive community features, Taste Together will make cooking more accessible, enjoyable, and aligned with personal health goals, while fostering crosscultural connections and promoting a greater appreciation for diverse culinary traditions.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY 64

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 32

Lauren Hollman, Xin Chen

Toxocara Canis: Impact On Intermediate Hosts And Ecological Implications

Background: Toxocara canis is a parasitic nematode that primarily infects canids, such as dogs, but also utilizes a range of intermediate hosts, including rodents, birds, and humans. In these hosts, the larvae migrate through various tissues, including the brain, without maturing, which leads to significant alterations in the host’s behavior, immune system, and neurochemistry. These changes are not only biologically significant but also have important ecological and public health implications, particularly in regard to parasite transmission dynamics.

Purpose: The primary aim of this study was to examine the neurochemical, immune, and behavioral changes induced by T. canis infection in intermediate hosts, specifically rodents, and to explore the broader ecological and zoonotic consequences of these alterations. The research focused on assessing how infection with T. canis affects neurotransmitter systems, immune responses, and behavior in rodents, with a particular emphasis on the behavioral manipulations that enhance the likelihood of predation by definitive hosts.

Additionally, a comparative analysis with other host-manipulating parasites, such as Toxoplasma gondii, was conducted to identify shared mechanisms of host manipulation.

Method(s): The findings demonstrate that T. canis infection induces substantial behavioral modifications in rodents, including increased activity, reduced fear responses, and heightened exploration.

These behaviors increase the likelihood of infected rodents being preyed upon by definitive hosts, facilitating the parasite’s life cycle. Furthermore, T. canis infection appears to influence neurochemical pathways involved in mood and behavior, while also eliciting immune responses that may contribute to tissue damage and behavioral changes. The potential impact of T. canis on the gut microbiome, though not fully explored in this study, suggests further avenues for research on the gut-brain axis in parasitic infections.

Conclusion: In conclusion, T. canis alters the neurochemistry and behavior of intermediate hosts in ways that promote its transmission, with significant implications for both ecosystem dynamics and human health. These findings highlight the importance of further research into the mechanisms of host manipulation and the broader ecological effects of parasitic infections. Such insights will be important for developing more effective strategies to mitigate the spread of T. canis and reduce its impact on public health.

Faculty: SCIENCE Department: ENVIRONMENTAL AND PHYSICAL SCIENCES CUE Annual Research & Innovation Conference 2025

65

POSTER PRESENTATION Poster 33

Maisha Nusrat Srishty, Wali Mohammad Abdullah

Predictive Analytics For Optimizing Healthcare Costs And Wait Times

Background: Healthcare facilities face significant challenges in managing treatment costs and patient wait times.

Inefficient cost estimation and long wait times lead to financial strain on institutions and dissatisfaction among patients.

Predictive analytics offers a data-driven approach to addressing these issues by leveraging historical data to improve cost and wait time predictions.

Purpose: This study explores the integration of predictive analytics and data visualization to enhance healthcare operations. The primary objectives are to develop a predictive model for treatment cost estimation and to design an interactive dashboard that provides real-time insights into patient wait times.

Methods: A dataset containing patient demographics, medical conditions, procedural details, and historical treatment costs was used to train a predictive model.

The Random Forest regression algorithm was selected due to its robustness in handling complex data relationships.

The model was evaluated using key performance metrics such as R-squared (R²) and Mean Absolute Error (MAE). An interactive dashboard was developed to visualize predictions and wait times dynamically, incorporating periodic data updates for real-time insights.

an R² score of 0.82, indicating a high correlation between predicted and actual treatment costs. The Mean Absolute Error (MAE) was calculated to be $850, reflecting the model’s reliability in estimating costs.

Analysis of key features revealed that patient age, diagnosis type, and procedure complexity were the most significant predictors of cost variation. The interactive dashboard successfully integrated real-time updates and allowed users to visualize wait times and cost distributions. Historical data analysis showed that the model reduced cost prediction errors by approximately 15% compared to traditional estimation methods. The dashboard’s implementation led to a 20% improvement in decisionmaking efficiency among hospital administrators based on user feedback.

Conclusion: The study demonstrates the potential of predictive analytics in enhancing cost estimation and operational efficiency in healthcare settings. By integrating machine learning models with dynamic visualization tools, healthcare providers can optimize resource allocation and improve patient satisfaction. Future research should focus on expanding the dataset, integrating real-time Electronic Health Record (EHR) systems, and refining the model to enhance predictive accuracy further.

Results: The predictive model demonstrated strong accuracy, achieving

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY 66

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 34

Manoj Kumar Yasangi, Baidya Saha

AI-Driven Smart Energy Optimization: Time-Series Forecasting And Anomaly Detection

The growing demand for efficient energy management has led to the development of AI-driven solutions to optimize electricity consumption, detect anomalies, and provide early warnings for excessive usage. This research presents a machine learning-based framework leveraging time-series forecasting and anomaly detection to enhance energy efficiency.

Unlike conventional rule-based methods, the proposed approach utilizes data-driven insights to dynamically predict electricity consumption, identify faulty appliances, and prevent excessive energy waste.

The system architecture consists of a time-series forecasting model that predicts monthly electricity usage based on historical consumption patterns, weather conditions, and appliance usage trends. Additionally, an anomaly detection module identifies irregularities

in power consumption, signaling potential appliance malfunctions or supply issues.

The framework also integrates automated early warning mechanisms, alerting users when abnormal consumption is detected to prevent unexpected high electricity bills.

Extensive experiments are conducted using real-world electricity consumption data to evaluate the system’s accuracy in forecasting and anomaly detection. Key performance metrics such as forecasting accuracy, anomaly detection precision, and energy cost reduction demonstrate the effectiveness of the proposed approach. By integrating AI-driven analytics into smart energy management, this study introduces a scalable methodology for optimizing electricity usage, reducing costs, and improving sustainability.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

67

POSTER PRESENTATION Poster 35

Manraj SIngh

Exploring Labour Relations, Global HR, and High-Performance Organizations

This presentation consists the summary of last three chapters of the HR Management 220 course.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES 68

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 36

Mark Waako, Apoorva Chauhan

Why People Share Information During Crises

Background: Social media platforms have become critical tools for communication during crises, significantly enhancing the speed and reach of information dissemination. Crisis-related communications differ significantly from everyday communications, as they require immediate attention and action, involve high-stakes consequences, provoke fear of the unknown, and evoke strong emotions such as anxiety and panic. Social media platforms, however, also spread misinformation (unintentional false information) and disinformation (deliberate false information) at alarming rates. A variety of fact-checking tools have been developed to identify false information based on its content, sources, hashtags, and/or information diffusion patterns. While these tools are beneficial in combating false information to some extent, it is nearly impossible to fact-check information in real time. Moreover, users are often the weakest link in the process. If users fail to utilize available fact-checking tools, overlook warning signs, or do not fully grasp the impact of misinformation and disinformation, the effectiveness of these tools is severely diminished. Therefore, it is crucial to empower social media users with the skills to identify false information.

Purpose: This research aims to examine how social media users engage with crisisrelated content, their practices for sharing information, and their perceptions of their knowledge of the social media platforms.

Methods: This research has been approved by the University of Alberta Research Ethics Board (Pro00147876). Social media users aged 18 and above participated in a survey in which they reflected on their information-sharing behaviors, answered questions related to social media literacy, and provided demographic information including age, highest level of education, and academic background.

Results: The survey findings reveal several key insights: the types of crisis related posts participants share on social media, the extent to which they believe they understand how social media algorithms work, their confidence in identifying misinformation, the frequency with which they report false-information, how often they fact-check content before sharing information, if they have ever mistakenly shared misinformation, and their views on who should be responsible for ensuring the accountability of social media platforms.

Conclusion: The results underscore the pressing need for better user education on how to critically evaluate crisis-related information on social media. By identifying gaps in users’ ability to spot misinformation, this study provides valuable insights for developing strategies to enhance digital literacy. These findings will help empower individuals to make more informed decisions and take appropriate actions during crises.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

69

POSTER PRESENTATION Poster 37

Matthew Berry, Holly McCarthy, Veronica Murchie, and Matthew Berry

Are Actors Better In Bed? Towards A Comparative Investigation Of Sex Positive Attitudes In Theatre Actors And The Public

Background: Sex positivity is a burgeoning, complex, and multifaceted topic in the field of psychological research. However, due to the lack of agreed-upon distinctions or factors to clearly define it, sex positivity as topic of research lacks critical consensus, the term remains ambiguous, and research on sex positivity becomes complicated by widespread misconceptions that may skew participant attitudes (e.g., equating sex positive attitudes with promiscuity). As a result, there is a dearth of fundamental experimental and quasiexperimental research on sex positivity and sex positive attitudes both within and across many populations. The present research begins to address these two issues by reviewing the extant literature of sex positivity, proposing a multifactorial definition, and outlining a comparative quasi-experimental study on sex positivity between the general public and theatre actors. Theatre actors were selected as a comparative population due to their expertise on autonomy, somatic awareness, communication, perspective taking, and emotional regulation, all practised skills that may correlate with/contribute to increased sex positive attitudes. Indeed, we hypothesize that theatre actors will report higher levels of sex positive attitudes, beliefs, and behaviours compared to nonactors when compared directly.

Methods: We employed narrative review procedures to summarize the extant literature on sex positivity. Sources were collected in a systematic search across multiple academic databases including PsychInfo, PubMed, and Google Scholar. Key search terms and their derivatives included “theatre”, “actors”, “sex positivity”, “consent”, “communication”, and “sexual inclusivity”. Inclusion criteria required studies to be peer-reviewed, focusing on sexpositivity and/or actors, and publication dates

were not limited. Exclusion criteria eliminated papers that were not available in English.

Results: The initial narrative review yielded 59 articles related to sex positivity, actor training, and scales measuring sexual behaviors. From these, 36 were selected based on their direct relevance, providing a strong foundation for defining sex positivity, focusing on sexual behaviors and attitudes as central themes.

A consensus emerged across a majority of selected studies, outlining five key factors as core aspects of sex positivity: (1) openness to exploration and experimentation, (2) healthy sexual communication, (3) sexual knowledge and education, (4) consent and boundaries, and (5) sexual satisfaction. While other attributes were discussed, these five consistently appeared as defining characteristics across most articles.

Conclusions: Sex positivity is increasingly becoming a prominent topic, yet its definition remains fluid and inconsistently applied in the literature. The current lack of a standardized definition presents challenges for psychologists, making it difficult to conduct impactful research.

Our literature review identified five core factors of sex positivity that were widely agreed upon across the articles studied. Using these key factors in combination provides psychology with a working definition of sex positivity that can be used for future research. This is particularly important, as positive and healthy sexual experiences have been linked to greater overall well-being in humans. Furthermore, since there is no widely accepted scale for measuring sex positivity, these findings will contribute to the development of a standardized assessment tool that will be useful in comparatively assessing sex positivity both within and between populations.

Faculty: ARTS Department: PSYCHOLOGY 70

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 38

Maykel Candelario, Hannah Batchelor, Seyma Yildirim-Erbasli, and Alexander Taikh

The Effect Of Word Predictability On Typing Speed In Literal And Figurative Language

Typing is a process which involves multiple steps, including identifying the to-be-typed words, accessing their meanings, planning and executing the sequence of keystrokes.

The speed of entering a sequence of keystrokes is thought to reflect these underlying processes and is significantly influenced by linguistic information, such as how predictable words are within their contexts. Generally, more predictable words – such as frequently used words or words easily anticipated in their context – are typed faster. Importantly, processing the meaning of a word can depend on whether it is embedded in literal language or in figurative language, where the intended meaning of the statement differs from its literal meaning.

Traditional theories of figurative language processing suggest that figurative meanings are interpreted after literal meanings, while more contemporary theories propose that both types of meaning are processed simultaneously, which can result in contradictions and require additional processing time.

Traditional theories posit that words in figurative expressions should be typed more slowly while contemporary theories posit that these words can be typed more quickly if the context can enhance predictability and thus facilitate processing

of the figurative meanings of these words.

Our study explores how predictability influences the typing speed of words embedded in literal and figurative contexts.

Using data from TypeRacer, an online typing platform where participants copytype passages for speed while keystroke timings are recorded, we analyzed the typing latencies of words from the 50 most frequently typed passages. Each sentence was categorized as either literal or figurative. Within figurative sentences, we further categorized words as literal, or as figurative if they directly constituted the figurative expression of the sentence.

We found that literal sentences were typed more quickly overall than figurative sentences, indicating that figurative language initially imposes additional processing demands. Importantly, within figurative sentences, the words that belonged to figurative expressions were typed faster than words outside of these expressions, despite potentially being less predictable. This suggests that once the context is established, words in figurative expressions benefit significantly from the contextual. Thus, our study examines how contextual linguistic information about meaning influences typing words in literal and figurative statements.

Faculty: ARTS Department: PSYCHOLOGY CUE Annual Research & Innovation Conference 2025

71

POSTER PRESENTATION Poster 39

Megan MacElheren, Vern Baron, Regan Holt, M. Anne Naeth, and Emmanuel Mapfumo

Variability Of Soil Biological Health Parameters Related To Carbon Cycling Under Grazed And Hayed Pasture-Legume Mixes

Soil organic matter, permanganate oxidizable carbon, and soil respiration are important indicators of soil health and carbon cycling. The objective of this research was to investigate the effects of introduction of legumes and perennial grass through conventional means compared to sod-seeding legumes into perennial old grass stands (grazed or hayed) on biological soil health parameters related to carbon cycling. This study was conducted on an organic-rich Orthic Black Chernozem at the Lacombe Research and Development Centre. Soil was sampled (n=96) from 32 plots with three microsites in each plot (bare, grass, clover or alfalfa).

Soil organic matter, permanganate oxidizable carbon, and soil respiration were determined on microsite samples.

Statistical analyses revealed no significant differences across soil microsites in soil organic matter (P = 0.95) or soil respiration (P= 0.29) or management treatments. Sod-seeded systems showed higher permanganate oxidizable carbon

values than conventional treatments (P = 0.002). These findings suggest that while soil organic matter remains relatively stable across microsites and treatments, permanganate oxidizable carbon is more responsive to land management changes. Multiple regression analysis demonstrated that soil organic matter % was a significant predictor of soil respiration (P < 0.001), while permanganate oxidizable carbon was not (P = 0.696), highlighting that total organic matter content plays a greater role in microbial CO₂ emissions than the permanganate oxidizable carbon fraction of carbon. The weak relationship between permanganate oxidizable carbon and respiration implies that microbial carbon use efficiency and aggregate protection may regulate CO₂ fluxes rather than just permanganate oxidizable carbon fraction of carbon. The results emphasize the importance of considering multiple soil carbon metrics when evaluating soil health under pasture-legume management systems.

Faculty: SCIENCE Department: ENVIRONMENTAL AND PHYSICAL SCIENCES 72

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 40

Michael Pelzer, Matthew Churchward

Caffeine Affects The Production Of Chondroitin Sulfate Proteoglycans From Microglia Cells And Astrocytes

Chondroitin sulfate proteoglycans (CSPGs) are essential for their contributions towards the extracellular matrix functions that are responsible for vital growth and development in the neural system. They are commonly expressed among the central nervous system (CNS) and the brain. CSPGs inhibit growth by inhibiting remyelination of the injured cells to prevent injury from spreading to other areas of the brain or spinal cord. CSPGs, when in homeostasis, are responsible for the growth inhibition and interact with injured neural cells to promote healing. This allows CSPGs to provide protection of the brain by separating the injured neural cells from the healthy neural cells which inhibits inflammation. With recent research suggesting change in the microglia cell morphology and behavioral impacts as a result of caffeine treatments however, the lack of knowledge of the effects of caffeine on the production of CSPGs is a gap that should be addressed. This begs

the question, does an increase in caffeine consumption influence the production of CSPGs? We hypothesize that there should be an impact at the cellular level of caffeine consumption on the CSPG production by microglial cells. In our experiment we explored caffeine impacting the CSPG levels of the cells at the cellular level.

While the cells demonstrated some level of recovery from injury caused by deoxyD-glucose when given caffeine treatment in the microscopy assay, a western blot analysis on the other hand was insufficient to determine if CSPGs did or did not change between our treatment and control. While caffeine did impact the cells based on the morphological change, there is not enough evidence to support an impact on the production of CSPGs in the cells.

Therefore, caffeine may influence microglial cell functions but further investigation is required to understand exactly what caffeine influences when the microglia cells undergo morphological changes.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES CUE Annual Research & Innovation Conference 2025

73

POSTER PRESENTATION Poster 41

Mick Brien Macuha, Sergey Ishutov

Enhancing Earth Science Education Through Virtual Reality: Developing An Immersive Field Trip With EON-XR

The integration of Extended Reality (XR) technologies, encompassing Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), has significantly transformed educational methodologies. This project focuses on developing a virtual reality field trip utilizing the EON-XR platform to enhance learning in an Earth Science course. The primary objective is to establish best practices for implementing XR tools, thereby creating immersive and interactive learning experiences. The methodology involves capturing highresolution images and videos of earth materials that are used in a physical field trip of this course, such as the rock outcrop by the North Saskatchewan River, the Rockwall CUE Campus, and the Stairs by Schwermann Hall. This visual

content was then integrated into the EON-XR platform to design a virtual field trip that allows students to explore these locations remotely. This approach not only makes learning more engaging but also provides accessibility for students with mobility constraints or those unable to participate in physical field trips. The anticipated outcome is an enriched educational experience that bridges the gap between theoretical knowledge and practical application, fostering a deeper understanding of geological concepts.

Furthermore, this project sets a precedent for the potential application of XR technologies across various disciplines, demonstrating the versatility of virtual reality tools in higher education.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES 74

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 42

Mick Brien Macuha, Bradley Scott

A Comparative Analysis Of Morphological Variations In Galactic Glue And Charlotte’s Web Cannabis Strains

Cannabis sativa is a chemically varied plant with significant use in research and medicine. The primary cannabinoids, Tetrahydrocannabinol (THC) and cannabidiol (CBD), interact with the endocannabinoid system to affect physiological processes. Strains bred for high THC or high CBD content exhibit distinct biochemical and agronomic traits. This study compares the growth characteristics of two strains cultivated under controlled conditions: Galactic Glue (THC-abundant) and Charlotte’s Web (CBD-abundant). Galactic Glue was hypothesized to accumulate more fresh and dry weight than Charlotte’s Web, because THC-dominant strains allocate more metabolic resources to biomass and flower development than CBD-dominant strains. Weekly measurements of fresh weight, height, and dry weight were made throughout the flowering period, specifically weeks five through eight of plant growth. Dry biomass was assessed following harvest. In support of the idea, Galactic Glue showed noticeably greater fresh and dry weight accumulation. On

average, the fresh weight of Galactic Glue increased by 81%, while 28% of the dry weight was retained. Despite maintaining a constant height development, Charlotte’s Web yielded less biomass than the relative height. Galactic Glue favored denser floral growth, while Charlotte’s Web displayed a homogeneous vegetative structure, indicating different metabolic methods. These results imply that biomass distribution is influenced by cannabis concentration, with strains that are higher in THC showing more robust growth. These findings are consistent with earlier research that connected elevated THC biosynthesis to higher biomass and secondary metabolite production. The reduced output of Charlotte’s Web would suggest that more resources are being devoted to the creation of CBD rather than the overall buildup of biomass. Understanding the differences in morphology of two distinct strains can help commercial cannabis production choose strains and develop cultivation plans. The molecular foundation of these growth patterns can be further clarified by future studies utilizing metabolomic profiling.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES CUE Annual Research & Innovation Conference 2025

75

POSTER PRESENTATION Poster 43

Nikhil Kumar Agarwal, Eslam AbdAllah

A Comprehensive Evaluation Of Endpoint Detection And Response (EDR) Products Using The Mitre Attack Framework

Background: With the growing sophistication of cyber threats, organizations face an increasing risk of attacks that compromise their data, operations, and security. To combat these risks, Endpoint Detection and Response (EDR) solutions have become a critical component in protecting organizations from cyber threats. These tools help detect, prevent, and respond to potential attacks in real-time, playing a key role in modern cybersecurity strategies.

This research concentrates on evaluating two leading EDR products—CrowdStrike and Sophos—using the MITRE ATTACK Framework, a widely recognized and comprehensive model for analyzing and understanding cyberattack techniques.

Purpose: The primary goal of this research is to assess the effectiveness of different EDR products in addressing a range of cyber threats, as aligned with the MITRE ATTACK Framework. The research aims to provide organizations with actionable insights into which EDR solutions are most effective in protecting against evolving attack techniques, thereby enhancing cybersecurity preparedness.

Method: This study employed a rigorous, multi-step methodology. First, a comprehensive literature review was conducted to lay the foundation for the research by examining existing knowledge on EDR solutions and cyber threats. Next, simulated attack scenarios were designed to evaluate how well each EDR product

detected, prevented, and responded to various attack techniques. In addition, real-world threat emulation was performed to further test the practical applicability of the EDR tools under live conditions. Data collection is in progress to quantitatively and qualitatively assess the performance of each solution.

Results (Anticipated): The study expects to identify the strengths and weaknesses of each EDR solution in detecting and responding to advanced cyberattack techniques, such as ransomware, phishing, and zero-day vulnerabilities. The anticipated outcome is a detailed comparative analysis that will provide organizations with clear, evidence-based recommendations for selecting the most effective EDR solutions based on their unique security needs.

Conclusion: By systematically evaluating leading EDR products using the MITRE ATTACK Framework, this research will offer valuable insights that can guide organizations in strengthening their cybersecurity defenses. The results will contribute to a deeper understanding of EDR capabilities, providing practical recommendations for the selection and implementation of these tools. Ultimately, the research aims to support organizations in making informed decisions that bolster their defense mechanisms against the increasingly complex and persistent cyber threats of the modern digital landscape.

Faculty: MANAGEMENT SYSTEMS ASSURANCE MANAGEMENT Department: INFORMATION AND INFORMATION SYSTEMS SECURITY MANAGEMENT 76

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 44

Paula Gil, Elizabeth Farrell

Project Human Resources

In the presentation I explain my opinion about three chapters and I explain my experience working through a song.

Faculty: MANAGEMENT Department: MANAGEMENT CUE Annual Research & Innovation Conference 2025

77

POSTER PRESENTATION Poster 45

Rachel Schutta

Sociology: A Tool In My Belt

Sociology acts as a tool. Having sociology as a tool in my belt, means I am able to bring what I have learned in my undergrad with me into every room I walk into. I use my knowledge in the field to help me navigate relationships and make choices with intention, because I know the socio-structural aspects of my choices play into aspects such as my ability to act equitably, my perceived image by others and my participation in work or my consumptive practices. Since everything from capitalist bureaucracy to micro analysis of the family’s function are taught in a sociology undergrad study, I act with intention based on the concepts taught to me in my undergrad in both my work and personal life. For example, I work as a fitness instructor and I try to create an inclusive environment that accommodates different member’s physical capabilities and cultural backgrounds by including music from other parts of the world and acknowledging hurdles of injury that may affect the person’s range of motion or performance. Sociology classes have also informed me of the expectations and norms in a professional setting, so I take the more bureaucracratic parts of my job with the same seriousness as the athletic component, such as promptly answering emails to ensure my success.

Before beginning my undergrad I could see all these patterns in the world around me, but I had no framework to describe them and no terminology to understand the patterns I was

seeing. It was honestly like having a word on the tip of my tongue that I just couldn’t voice.

I knew structures such as school operated in a hierarchy and that I had seen firsthand the relevance of class and gender in discussions relevant to obtaining opportunities, engaging in communities and shaping one’s worldview.

For it was by these observations that I decided to take my undergrad in sociology. I wanted to know the “how” and the “why’ to all my observations. Sociology works to explain concepts of class, gender race which are everpresent discussion points in the institutions of the day-to-day. After my first year, I really took to my studies in sociology as more of my initial questions were answered. It is empowering have the theoretical framework to draw understanding from. I feel like I am starting to form a voice where I can speak on the observations that my younger self had experienced. The words at the end of my tongue are able to be voiced in a way that is now informed by credited theorists and welltaught lectures from experienced professors, giving me a tool to use for advocacy, worldview formation and critical thinking skills to challenge or accept the way society operates. My younger self would be pleased to know she has obtained the knowledge to create standpoint of my own nuanced perspectives and that there is a whole scientific practise to assure her, that these patterns in life deserve to be recognized, be spoken about and even criticized at times.

Faculty: ARTS Department: SOCIAL SCIENCES 78

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 46

Rachele Playford, Rachel Mustaklem and Alexander Taikh

Accessing And Typing Constituent Words And Nonwords

Typing is a complex, multi-step process that includes identifying the to-be-typed word and planning and executing the keystrokes.

The speed of keystroke execution is thought to reflect the processing of linguistic information from the word itself and the context in which the word is embedded. Specifically, the speed of the initial keystroke reflects the recognition of the word and the planning of the keystroke sequence, whereas the speed of the noninitial keystrokes reflects the execution of this sequence. According to interactive theories of typing, linguistic information influences the execution of the keystrokes in addition to recognition of the word and planning the keystroke sequence.

Morphological information, a type of linguistic information, has been found to influence typing. For example, Taikh et al. (2023) found that when typing compound words, which consist of two or more standalone words (e.g., backache consists of the words back and ache), keystroke speeds were determined by the linguistic properties of the constituents rather than the whole word, suggesting that the embedded constituents are extracted and typed separately as the whole word is segmented. Importantly, the first constituent was typed more quickly when the second constituent was easier

to integrate with the first, suggesting that the typing of the first constituent was influenced by the linguistic information of the second constituent.

In the present study, we examine how the typing of an embedded word was influenced by the context in which it was embedded. Typing the initial and non-initial keystrokes of a word (e.g., ache) was faster when it was embedded in a compound (e.g., backache) and thus exists as a standalone word that is easy to identify and extract, compared to when it was embedded in a nonword (gluwache), where it is more difficult to identify and extract. We next examined whether making the embedded word more available would speed up its typing. Showing a related contextual word (pain, which is related to ache) prior to the nonword (gluwache) did not facilitate typing either the initial or the non-initial keystrokes of the embedded word (back), but did speed up the initial key of the embedded nonword (gluw). Our findings suggest that making the embedded word more available sped up the planning of the embedded nonword and thus the typing of its initial keystroke. Our findings suggest that linguistic information influences the identification, planning, and typing of embedded words.

Faculty: ARTS Department: PSYCHOLOGY CUE Annual Research & Innovation Conference 2025

79

POSTER PRESENTATION Poster 47

Regan Holt, Megan MacElheren, Vern Baron, and Emmanuel Mapfumo

Bulk Density And Infiltration Rates Under Different Management Of Grass-Legume Mixtures

Soil compaction is an essential indicator when assessing comprehensive soil health. Highly compacted soils can reduce root growth, decrease soil aeration, lead to poor soil drainage, increase erosion, and overall decline soil fertility. Bulk density and infiltration rate are common indicators used to measure soil compaction levels and soil erosion potential. High bulk density and/or low infiltration rates generally point to high soil compaction.

The objective of this research was to investigate the effects of grass-legume management treatments on bulk density and steady-state infiltration rates.

Collection of soil core samples and field measurements were conducted on an organic-rich Orthic Black Chernozem plots at the Lacombe Research and Development Center in the summer of 2022, 2023, and 2024. Each data set contained 64 replicates in a randomized complete block design.

Management treatments included new

legumes and perennial grass (meadow bromegrass) introduced by conventional tillage or sod-seeding legumes into existing old perennial grass (meadow bromegrass or smooth bromegrass) stands. Legumes introduced included alfalfa, red clover, or an annual legume (crimson clover).

Analysis of data indicated that bulk density was significantly higher (P < 0.05) in conventional compared to sod-seeded treatments for all years. Inversely, steady state infiltration rates were all significantly lower (P < 0.05) in conventional compared to sod-seeded treatments for all years.

Plots under conventional management were found to be slightly compacted than those under sod-seeding management.

Thus, the sod seeding approach is a possible way to minimize the negative effects of soil compaction due to less mechanical soil disturbance compared to conventional tillage.

Faculty: SCIENCE Department: ENVIRONMENTAL AND PHYSICAL SCIENCES 80

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 48

Rupinder Kaur, Md Morshedul Islam

Multi Modal Framework For Detecting Fake Social Media Post

Background: Online social media has become a major platform for people to share information daily. However, it also acts as a double-edged sword, as the content shared in social media is not always authentic and often contributes to the spread of fake news. A traditional, text-based fake news detection method uses Natural Language Processing (NLP) techniques. However, with the advancements in multimedia technologies, social media posts now often include a combination of text, images, and videos. As a result, detecting multi-modal fake news and minimizing its impact has become a significant challenge for social media platforms.

Purpose: This research aims to investigate and extract information from social media posts that contain multiple modalities, specifically text, images, and videos, to detect fake content more effectively. The goal of this project is to develop a machine learning-based multi-modal framework for fake post detection.

Methods: The proposed approach involves several key steps. First, we will construct a multi-modal feature extraction network capable of extracting meaningful features from different content types, including text, images, and videos. These features

will then be combined and passed into a machine learning-based discriminator to identify posts as fake or real. We will train a Generative Adversarial Network (GAN) as the discriminator. Additionally, an adversarial mechanism will be introduced to capture correlations between different types of content within a post. This mechanism will be integrated into the GAN to enhance its generalization ability, especially when dealing with unseen or evolving fake news content.

Results: The research is expected to demonstrate the superior performance of the multi-modal approach in detecting fake social media posts by leveraging the combined analysis of text, images, and videos. The use of an adversarial mechanism is intended to improve model robustness and adaptability.

Conclusion: In this paper, we propose a multi-modal fake news detection framework that includes feature extraction across different media types, GANbased classification, and adversarial learning to boost model performance. The effectiveness of the proposed method will be validated through extensive experiments using real-world social media datasets.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

81

POSTER PRESENTATION Poster 49

Ruth Ogadina, Eslam AbdAllah

Securing Medical Information With An Enhanced Secure Lightweight Integrated Mechanism Algorith

As technology advances towards the development of new medical breakthroughs, the volume of data is rapidly increasing. It is essential to take great care in protecting medical information as special tools including heart monitors, electronic medical records, and smart watches are highly susceptible to multiple attacks because of their low computational resources. Due to this limitation, these devices — which possess low-powered hardware to perform their main tasks — cannot make use of most cryptographic algorithms as they are resource-intensive and are more suitable for larger systems.

This project aims to protect sensitive medical data by upgrading a lightweight cryptographic algorithm. It enhances the Secure Lightweight Integrated Mechanism algorithm to strengthen security while ensuring it remains suitable for devices with limited processing power.

This project involved reviewing existing encryption methods and implementing the SLIM algorithm using a widely used programming language (Python). Key improvements included secure key randomization, increasing the block size from 32 to 40 bits for better performance, integrating a lightweight hash algorithm

(Photon), introducing new data scrambling techniques, and using parallel computing to speed up real-time encryption and decryption. The upgraded version of the Secure Lightweight Integrated Mechanism algorithm achieved greater randomness during data encryption, reducing the chances of successful attackers accessing sensitive information. It can also encrypt or decrypt text or image data in a quick and efficient manner without compromises on resource-usage. It has shown strong results in performance tests, including statistical tests for data security and integrity while it remains lightweight.

Lightweight cryptographic solutions are a critical step in information security, as threat actors continue to work towards compromising innocent victims through manipulative tactics. The enhanced version of this algorithm proves that it is possible to provide strong protection without overloading the lightweight systems. To prevent further losses from affecting people and organizations, lightweight cryptographic algorithms should be continuously improved to keep up with emerging technologies so that sensitive information remains secure in this increasingly connected world.

Faculty: MANAGEMENT SYSTEMS ASSURANCE MANAGEMENT Department: INFORMATION AND INFORMATION SYSTEMS SECURITY MANAGEMENT 82

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 50

Samin Yeasir Imam, Hamza Ahmed and Md Morshedul Islam

Securing Qr Code Interactions: Detecting Malicious Links And Rogue Websites

The rising use of Quick Response (QR) codes containing malicious Uniform Resource Locators (URLs) has become a significant concern and remains an unresolved security challenge. A malicious URL in a QR code can redirect users to rogue websites, posing significant cybersecurity threats as these websites often host phishing attacks, malware, and other harmful content. Most existing QR code scanner applications rely on blacklistbased methods to detect malicious links, but these are limited in their ability to identify new or evolving threats. In recent years, machine learning (ML) techniques have gained attention for improving detection accuracy. Yet, many of these approaches focus solely on URL features, which may not be sufficient. To stay ahead of evolving cyber threats, more advanced and adaptive detection mechanisms are required.

The objective of this research is to enhance the security of QR code scanning by adopting a broader perspective and automating the detection process. Rather than analyzing only the URL embedded in the QR code, our approach also examines the content of the destination website to which the user is redirected. By incorporating ML techniques, the system can provide real-time feedback, allowing users to be immediately informed of potential threats.

This research introduces a novel framework for secure QR code interactions, aimed at

detecting malicious websites. When a QR code is scanned, the system first extracts the embedded URL and checks it against a blacklist database. If the URL is not listed, it undergoes further evaluation using a Natural Language Processing (NLP)-based model along with different feature-based methods, such as lexical analysis, linguistic patterns, and host-based characteristics to identify potential indicators of malicious intent. If the URL passes these checks, the system then loads the website content and performs further analysis using content-based features. Throughout all stages, ML models are trained and refined using adversarial learning techniques to improve the model generalization ability, especially when dealing with unseen URLs and web content.

If any stage detects malicious behavior in either the URL or its content, the QR code scanner app immediately warns user and advises them not to proceed. The app also provides real-time feedback and a clear explanation of the decision, enhancing user understanding and trust.

The research demonstrates improved accuracy in detecting both malicious URLs and harmful web content when users scan QR codes with the proposed system.

Additionally, the system helps educate users about the characteristics of malicious links and content, effectively serving as a training tool to raise user awareness and cybersecurity literacy.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

83

POSTER PRESENTATION Poster 51

Seth Nobert, Brynmar Degenhart, Tashneet Dhaliwal, Cole Babcock, and Makan Golizeh

Harnessing Nature: Assessing The Efficiency Of Natural Chelating Agents

Exposure to heavy metals is a major public health issue that can affect many facets of human health. It has been linked to numerous health problems, including oxidative stress, inflammation, and the production of harmful compounds known as advanced glycation end-products. For decades, compounds to capture toxic heavy metals known as chelating agents have been studied. While synthetic chelating agents have been effective in removing these metals or rendering them less chemically reactive, they can also deplete essential metals that our bodies need, such as zinc, calcium, and magnesium.

To overcome these issues, this study explores the potential of natural chelating agents, such as curcumin (from turmeric), pheophytin (from leafy greens), phytic acid (from brans), and phytochelatins (found in seaweed). Natural chelating agents may show promise because they are more selective in targeting harmful metals while preserving essential ones.

One challenge we faced was that curcumin and pheophytin did not readily dissolve in water. To tackle this problem, we tested methods such as modifying the chemical structure of these compounds and using auxiliary agents to help them dissolve better. We then paired each natural chelating agent with the most abundant heavy metal in humans, iron, to see how well they captured this metal. To separate the captured and uncaptured iron, we

used a technique called ion exchange extraction. We measured how effectively these chelating agents could capture iron using an instrumental analytical technique called inductively coupled plasma optical emission spectroscopy.

Key results of this study were the determination of an effective extraction method of chlorophyll from kale leaves, the chemical modification of curcumin, and the determination of the metal capture ability of natural chelating agents. In this study, we determined a method for chemically modifying curcumin by integrating a watersoluble polymer into its structure. While the modified compound was successfully created, the modified curcumin still did not dissolve in water. To solve this, modified methods for increasing the water solubility of curcumin and pheophytin were developed using auxiliary agents, allowing for these compounds to dissolve in water.

In determining the binding power of the chelating agents of interest, we found that some natural chelating agents were stronger at capturing metals compared to the most widely used synthetic chelating agent.

Future work plans to investigate how well each natural chelating agent captures both harmful and essential metals and how this property of natural chelating agents affects the formation of advanced glycation end-products in cells. This work is part of a larger study on assessing metal-induced oxidative stress in humans.

Faculty: SCIENCE Department: ENVIRONMENTAL AND PHYSICAL SCIENCES 84

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 52

Shruthi Hariharan, Mackenzie Thomas and Seyma Yildirim Erbasli

Exploring Student Perceptions Of Human Vs. AI-Generated Scoring And Feedback

The integration of artificial intelligence (AI) in educational assessment offers scalable and efficient solutions to traditional grading challenges although limited research exists on student perceptions of AI-generated scoring and feedback, particularly compared to human evaluators.

Furthermore, its use in subjective tasks like writing evaluation raises concerns about its reliability, fairness, and acceptance. This study explores undergraduate students’ perceptions of AI-generated scoring and feedback compared to human evaluators.

Specifically, it investigates students’ ability to distinguish between AI and human evaluators, as well as changes in factors predicting perceptions. A sample of undergraduate students from a Canadian

university evaluated scores and feedback from both AI and a human, followed by pre- and post-surveys assessing shifts in perceptions upon disclosure of the source. Preliminary results indicate that approximately half of the participants incorrectly identified whether the evaluator was AI or human. While students expressed some concerns about AI, their overall perceptions were moderate and did not significantly change after disclosure.

Further, comfort with technology, familiarity with AI, and frequency of AI use were sometimes predictive of their perceptions.

This research provides valuable insights into student acceptance of AI-based scoring and feedback.

Faculty: ARTS Department: PSYCHOLOGY CUE Annual Research & Innovation Conference 2025

85

POSTER PRESENTATION Poster 53

Suraj Neupane, Md Morshedul Islam

Breaking The Privacy Promise: Data Leakage In Federated Learning Systems

Federated Learning (FL) has recently emerged as an alternative to conventional machine learning (ML) techniques by promising improved data privacy. An FL system allows two or more participants, each with their own training dataset, to construct a joint, generalized global model without sharing data with the central server. This approach also reduces the central server’s computation and storage load and helps organizations comply with data-sharing regulations like the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation (GDPR).

The objective of this research proposal is to investigate data reconstruction attacks in FL systems, where an attacker is able to reconstruct privacy-sensitive training data through interaction with the global model.

FL-based biometric authentication systems and medical image classification systems can be considered use cases for this attack, where each client usually does not carry data from all classes. In such cases, an untrusted client can attempt to recover privacy-sensitive data of a target user.

This research uses a Generative Adversarial Network (GAN), a deep learning-based approach, to reconstruct images that closely resemble the training data of the target user’s class. Importantly,

the attacker’s GAN generates these image samples without accessing the original training data. The GAN is trained using auxiliary data samples that are publicly available. Then, the trained GAN generates images for the target class , and their closeness to the original data is estimated using the trained global model. Feedback from the global model helps the GAN’s generator improve and produce more realistic images that resemble the target class. In our research, we use a special type of GAN called Deep Convolutional Generative Adversarial Network (DCGAN), which employs convolutional and transposed convolutional layers to generate realistic images from random noise.

In the experiments, we use FL systems for medical image classification and face biometrics, and demonstrate the success of DCGAN-based attacks in reconstructing data of target clients.

Although FL promises data privacy by design, the experimental results show that data leakage is still possible when even a single client in the system is untrusted.

We also explore differential privacy-based defense strategies against this type of data reconstruction attack. Our approach is general and applicable to other FLbased systems.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY 86

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 54

Taniel Smith, Cole Babcock and Makan Golizeh

Evaluating Aptamer Binding Efficiency Using High-Performance Liquid Chromatography

Background: Aptamers are short, singlestranded DNA or RNA oligonucleotides that can fold into unique three-dimensional structures, enabling them to bind specific target molecules with high affinity and specificity. Caff 209, a DNA aptamer, forms secondary structures and has the highest selectivity for caffeine, which may be reflective of the interaction of the aptamer.

Caffeine’s molecular structure features three exocyclic methyl groups, contributing to its symmetrical configuration. The hairpin structure of the Caff 209 aptamer, rich in thymine residues, is believed to facilitate encapsulation of the caffeine molecule, potentially through hydrophobic interactions between the methyl groups and thymine bases, as well as hydrogen bonding involving guanine, cytosine, and adenine nucleotides.

Purpose: This study aims to evaluate the binding efficiency of the Caff 209 aptamer in both its free form and when immobilized on a solid support by measuring the dissociation coefficient (Kd) value.

Method(s): Caffeine was incubated with the prepared Caff 209 aptamer. Unbound caffeine was separated using selective separation. Bound caffeine was then detached from the aptamer using thermal denaturation. Bound and unbound caffeine were quantified in solution high-performance liquid chromatography-

ultraviolet detection using an external calibration method.

Anticipated Results: Anticipated results will determine if the aptamer maintains its binding efficiency when immobilized on a solid support compared to its free form.

Quantitative analysis will facilitate this determination by enabling the quantitation of dissociation coefficient (Kd) values.

When caffeine binds to the free Caff 209 aptamer, the concentration of unbound caffeine in the solution is expected to decrease, forming an aptamer-caffeine complex. Quantitative analysis will display a decrease in caffeine quantities in the unbound fraction as more caffeine binds to the aptamer and vice versa. A greater reduction in the unbound caffeine is expected with effective aptamer binding.

The immobilized aptamers is anticipated to maintain binding efficiency. A deviation in Kd values from free aptamers could indicate structural changes upon immobilization.

Conclusion: Additional data is forthcoming to validate the results and conclusions.

The study will determine whether the immobilization of the Caff 209 aptamer affects its binding efficiency toward caffeine and will provide insights into the applicability of heterogeneous aptamer assays for enhanced target capture in analytical and diagnostic applications.

Faculty: SCIENCE Department: ENVIRONMENTAL AND PHYSICAL SCIENCES CUE Annual Research & Innovation Conference 2025

87

POSTER PRESENTATION Poster 55

Tayler Onufrichuk, Stephanie Nguyen and Jenna Congdon

An Investigation Of Red-Necked Wallaby (Notamacropus Rufogriseus) Cooperation And Problem Solving On A Rope-Pulling Task Red-necked wallabies are medium-sized marsupials that are typically solitary.

However, when living in groups, wallabies are known to have a social organization with hierarchical differences between females (e.g., mother-offspring bonds) and males. This social dynamic is of interest to be further investigated using a well-studied comparative task, known as rope-pulling.

In this rope-pulling task, social cooperation is examined as high-value food is placed on a platform that is out of reach, with the two ends of a rope, attached to the platform, accessible to the animals. To gain access to the food reward, two or more individuals must work together to use the ropes to pull the platform close enough to the experimental area. This task has been conducted with a variety of species, including wolves, domestic dogs, dingoes, Asian elephants, and bottlenose dolphins.

However, there is currently no research regarding the social cognition of wallabies, especially with regard to cooperation and problem-solving. Locally, the Edmonton Valley Zoo hosts a social group of six red-necked wallabies and employs zookeepers who are highly experienced

in training their animals. We designed, built, and piloted a rope-pulling apparatus, adapted for medium-sized marsupials.

Through establishing successive goals, using positive reinforcement only, the wallabies have learned to individually interact successfully with the rope-pulling apparatus - a necessity for expansion of this project. The details of apparatus design, successful Training thus far, and Testing still to be conducted, will be presented. In the future, the Testing Phase will consist of regular sessions with two or more individuals, examining their ability to cooperate on the given task. Testing trials will be run with a variety of partnered individuals either matched or differing in social ranking, relatedness, and biological sex; specifically, those that are matched in rank are predicted to outperform those that are more distinct in rank (i.e., one dominant and one subordinate). Consequently, this research will be critical to establishing an understanding of the cognitive abilities of red-necked wallabies, further contributing to the literature on social cooperation and problem-solving in mammalian species.

Faculty: ARTS Department: PSYCHOLOGY 88

CUE Annual Research & Innovation Conference 2025

POSTER PRESENTATION Poster 56

Tomasz Maciosowski, Rossitza Marinova

Factorizations Of Left Dead Ends

Combinatorial Game Theory is a study of games of two players alternating moves with no luck, chance, or randomness involved. The majority of research on Combinatorial Games focuses on normal play condition, where the first player who cannot make a move in their turn loses.

Games under normal play exhibit a lot of structure, as they form a group, which makes analysis more convenient. Misère play condition is a slight variation where the first player that cannot make a move in their turn wins the game. Despite the change looking simple at first glance it completely changes how we can analyze misère games. Under misère play games lose a lot of the structure that was present under normal play and no longer form a

group. Left dead end is a position where Left player has no move available in any of the subpositions. Restricting games under misère play proves useful to recover some of the structure that has been lost by changing the win condition. Such an approach has been lately formalized as Universes of misère games. We are investigating an open question in the universe of Left dead ends, are Left dead ends under misère play uniquely factorizable? We have developed a computer program that can factorize Left dead ends faster than previous attempts and pushed the tree depth bound of Left dead ends, which are now known to be uniquely factorizable.

Faculty: SCIENCE Department: MATHEMATICS AND INFORMATION TECHNOLOGY CUE Annual Research & Innovation Conference 2025

89

POSTER PRESENTATION Poster 57

Valentine D. Ngatcha Yokeu, Bradley Scott

Description Of The Internal Anatomy Of Glabrapelta Cristata From The Lower Devonian Moth Locality

Background: Osteostracans are an extinct group of jawless fish that lived in the Silurian and Devonian periods. These vertebrates were characterized by their flat horseshoe-shaped, bony headshields and were likely bottom dwellers. Embedded within their headshields was a sensory system that included s.e.l canals. These canals connect the otic region of the brain to the lateral fields at the edges of the headshield. The lateral fields and the s.e.l canals are thought to function together as sensory organs, detecting pressure changes and vibrations– likely used to sense prey, predators and water currents. Osteostracans are considered the closest jawless relatives of jawed vertebrates and are thought to have evolved from the same common ancestor.

Therefore, studying the evolutionary biology of osteostracans can help bridge the gap in understanding how jawless and jawed vertebrates evolved from a common ancestor.

Glabrapelta cristata was an osteostracan native to the Man on the Hill (MOTH) locality in the Mackenzie Mountains, Northwest Territories, Canada. While the sensory system of many osteostracan species is well documented, little is known about G. cristata and their close relatives. For the first time, the specimen described here gives new insight into its sensory system. G. cristata possesses canals with variable inter-canal distances, showing a greater inter-canal distance between s.e.l canals 1 and 2. In contrast, s.e.l canals 3 and 4 appear to have consistent inter-canal spacing.

The addition of this character trait into a character matrix is subject to a phylogenetic tree analysis.

Purpose: The purpose of this research was to describe the sensory anatomy structure of G. cristata by comparison with other osteostracan species. Newly identified character traits were added to an existing character matrix to generate a phylogenetic analysis aiming to classify G. cristata and reconstruct the evolution of the s.e.l canals in osteostracans.

Methods: The specimen was subject to visual analysis and description of its sensory features.

Additionally, comparative analysis was utilized to guide interpretations and description of s.e.l canal arrangement. Newly identified character traits were added to an existing character matrix, and tree analysis using new technology, generated a phylogenetic tree through parsimony analysis with Tree Bisection Reconnection heuristic search methods.

Ancestral conditions of s.e.l canals were reconstructed by parsimony in Mesquite©.

Results: G. cristata possesses four s.e.l canals that are clearly identifiable. All four canals extend from the otic regions deep into the lateral fields. S.e.l canals 1 and 2 show a greater distance separating them compared to canals 3 and 4. Phylogenetic analysis indicates that G. cristata belongs to a lineage with two other Osteostracans, Dentalpelta and Supercialipis suggesting that these Osteotracans share similar internal anatomical structures.

Conclusion: This specimen of G. cristata provides valuable insight into its previously unknown sensory structure. The addition of its character traits to the matrix has reinforced the phylogenetic relationships between G. cristata, Dentalpelta and Superciliaspis.

Faculty: SCIENCE Department: BIOLOGICAL SCIENCES 90

CUE Annual Research & Innovation Conference 2025

The CARIC 2025 Organizing Committee would like to thank the presenters, attendees, volunteers, its sponsors, and everyone who contributed to this event for their participation and support!

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CUE Annual Research & Innovation Conference 2025

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