Research Overview 2011
Prof. Dr. Habil. Antanas Verikas, Senior Researcher Marija Bačauskienė, Assoc. Prof. Dr. Antanas Stasiūnas, Assoc. Prof. Dr. Adas Gelžinis, M. Sc., PhD student Evaldas Vaičiukynas antanas.verikas@ktu.lt Department of Electrical & Control Equipment
Computational Intelligence Systems
Computational Intelligence represents one of the most vigorously investigated fields of scientific research in Informatics and Engineering. The methods of Computational Intelligence include artificial neural networks, fuzzy logic, and evolutionary computing. Artificial immune systems and swarm intelligencebased calculations inspired by biology and wildlife are becoming increasingly widespread. Intelligent equipment with Computational Intelligence should be adaptive, capable of learning and accommodating themselves to new situations, generalizing, abstracting, and making associations.
International Cooperation The Computational Intelligence research group of the Faculty of Electrical and Control Engineering at Kaunas University of Technology enjoys over 30 years of scientific research experience in such fields as machine learning, decision making, classification, fuzzy logic, artificial neural networks, data mining, image and signal analysis and identification, and speech analysis. The group’s members include from 2 to 4 doctoral students. The group enjoys close cooperation with Halmstad, Chalmers, and Linköping Universities in Sweden, Darmstadt University in Germany, IBM Haifa Research Lab in Israel and others. The results of scientific research have been implemented in Lithuanian and Swedish industries, Swedish and UK banks.
Research and Projects Voice Pathology Detection The research has initially been started in cooperation with the Department of Otolaryngology, Lithuanian University of Health Sciences and led to the research project “Voice Pathology Detection Project – HC3” carried out jointly by KTU, the Speech Technologies group at IBM Haifa Research Lab and Lithuanian University of Health Sciences. The goal of the project is to create decision support tools for diagnosing different voice pathologies. The following user cases will be supported: 1. Patient screening by a general practice physician at a community health care centre.
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2. Patient screening by paramedics at remote locations and third-world countries. 3. Web-based self-screening. 4. Screening of employees that work in risk environments or under risk conditions. 5. Collecting and exploring databases aiming to support trend analysis and treatment policy planning (for ENT experts and voice therapy experts). Advanced Voice Function Assessment The research is being performed under the framework of COST Action IC2103 Advanced Voice Function Assessment. This action aims