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UK: Managing Editor International Journal of Innovative Technology and Creative Engineering 1a park lane, Cranford London TW59WA UK E-Mail: Phone: +44-773-043-0249 USA: Editor International Journal of Innovative Technology and Creative Engineering Dr. Arumugam Department of Chemistry University of Georgia GA-30602, USA. Phone: 001-706-206-0812 Fax:001-706-542-2626 India: Editor International Journal of Innovative Technology & Creative Engineering Dr. Arthanariee. A. M Finance Tracking Center India 261 Mel quarters Labor colony, Guindy, Chennai -600032. Mobile: 91-7598208700





From Editor's Desk

Dear Researcher, Greetings! This issue of Topics highlights some of the new trends in solar inverter, safe centum plants, Robot locomotion, Non-linear equations that impact thinking professionals. Measuring success in technology practice, experiments, and outcomes of various practice projects are featured. Wind energy is the fastest growing energy source in the world, with capacity doubling every three years. The global wind energy market is growing at more than 25%. This extraordinary growth is driven by declining natural resources, environmental concerns, and political pressure. By 2012, the wind energy sector will employ more than 1 million people, and by 2013 the revenue generated by wind turbine technology is expected to more than $100 billion. This issue is dedicated to the people of Japan and the Pacific zone who are affected by Earthquakes and Tsunamis. An underwater earthquake triggered off Japan's northeast coast has caused vast amount of destruction and loss of lives. This underwater earthquake also sent huge walls of water across the Pacific Ocean towards Hawaii, Australia, and the North and South American coastlines. It has been an absolute pleasure to present you articles that you wish to read. We look forward to many more new technology-related research articles from you and your friends. We are anxiously awaiting the rich and thorough research papers that have been prepared by our authors for the next issue.

Thanks, Editorial Team IJITCE


Editorial Members Dr. Chee Kyun Ng Ph.D Department of Computer and Communication Systems, Faculty of Engineering, Universiti Putra Malaysia,UPM Serdang, 43400 Selangor,Malaysia. Dr. Simon SEE Ph.D Chief Technologist and Technical Director at Oracle Corporation, Associate Professor (Adjunct) at Nanyang Technological University Professor (Adjunct) at Shangai Jiaotong University, 27 West Coast Rise #08-12,Singapore 127470 Dr. sc.agr. Horst Juergen SCHWARTZ Ph.D, Humboldt-University of Berlin, Faculty of Agriculture and Horticulture, Asternplatz 2a, D-12203 Berlin, Germany Dr. Marco L. Bianchini Ph.D Italian National Research Council; IBAF-CNR, Via Salaria km 29.300, 00015 Monterotondo Scalo (RM), Italy

Dr. Nijad Kabbara Ph.D Marine Research Centre / Remote Sensing Centre/ National Council for Scientific Research, P. O. Box: 189 Jounieh, Lebanon Dr. Aaron Solomon Ph.D Department of Computer Science, National Chi Nan University, No. 303, University Road, Puli Town, Nantou County 54561, Taiwan Dr. Arthanariee. A. M M.Sc.,M.Phil.,M.S.,Ph.D Director - Bharathidasan School of Computer Applications, Ellispettai, Erode, Tamil Nadu,India Dr. Takaharu KAMEOKA, Ph.D Professor, Laboratory of Food, Environmental & Cultural Informatics Division of Sustainable Resource Sciences, Graduate School of Bioresources, Mie University, 1577 Kurimamachiya-cho, Tsu, Mie, 514-8507, Japan Mr. M. Sivakumar M.C.A.,ITIL.,PRINCE2.,ISTQB.,OCP.,ICP Project Manager - Software, Applied Materials, 1a park lane, cranford, UK Dr. Bulent Acma Ph.D Anadolu University, Department of Economics, Unit of Southeastern Anatolia Project(GAP), 26470 Eskisehir, TURKEY Dr. Selvanathan Arumugam Ph.D Research Scientist, Department of Chemistry, University of Georgia, GA-30602, USA.

Review Board Members Dr. T. Christopher, Ph.D., Assistant Professor & Head,Department of Computer Science,Government Arts College(Autonomous),Udumalpet, India. Dr. T. DEVI Ph.D. Engg. (Warwick, UK), Head,Department of Computer Applications,Bharathiar University,Coimbatore-641 046, India. Dr. Giuseppe Baldacchini ENEA - Frascati Research Center, Via Enrico Fermi 45 - P.O. Box 65,00044 Frascati, Roma, ITALY. Dr. Renato J. orsato Professor at FGV-EAESP,Getulio Vargas Foundation,S찾o Paulo Business School,Rua Itapeva, 474 (8째 andar) ,01332-000, S찾o Paulo (SP), Brazil Visiting Scholar at INSEAD,INSEAD Social Innovation Centre,Boulevard de Constance,77305 Fontainebleau - France Y. Benal Yurtlu Assist. Prof. Ondokuz Mayis University Dr. Paul Koltun Senior Research ScientistLCA and Industrial Ecology Group,Metallic & Ceramic Materials,CSIRO Process Science & Engineering Private Bag 33, Clayton South MDC 3169,Gate 5 Normanby Rd., Clayton Vic. 3168

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 Dr.Sumeer Gul Assistant Professor,Department of Library and Information Science,University of Kashmir,India Chutima Boonthum-Denecke, Ph.D Department of Computer Science,Science & Technology Bldg., Rm 120,Hampton University,Hampton, VA 23688 Dr. Renato J. Orsato Professor at FGV-EAESP,Getulio Vargas Foundation,São Paulo Business SchoolRua Itapeva, 474 (8° andar), 01332-000, São Paulo (SP), Brazil Lucy M. Brown, Ph.D. Texas State University,601 University Drive,School of Journalism and Mass Communication,OM330B,San Marcos, TX 78666 Javad Robati Crop Production Departement,University of Maragheh,Golshahr,Maragheh,Iran Vinesh Sukumar (PhD, MBA) Product Engineering Segment Manager, Imaging Products, Aptina Imaging Inc. doc. Ing. Rostislav Choteborský, Ph.D. Katedra materiálu a strojírenské technologie Technická fakulta,Ceská zemedelská univerzita v Praze,Kamýcká 129, Praha 6, 165 21 Dr. Binod Kumar,M.C.A.,M.Phil.,ph.d, HOD & Associate Professor, Lakshmi Narayan College of Tech.(LNCT), Kolua, Bhopal (MP) , India. Dr. Paul Koltun Senior Research ScientistLCA and Industrial Ecology Group,Metallic & Ceramic Materials,CSIRO Process Science & Engineering Private Bag 33, Clayton South MDC 3169,Gate 5 Normanby Rd., Clayton Vic. 3168 DR.Chutima Boonthum-Denecke, Ph.D Department of Computer Science,Science & Technology Bldg.,Hampton University,Hampton, VA 23688 Dr.Sumeer Gul Assistant Professor in the Department of Computer Science & Applications, at Dronacharya Institute of Management and Technology, Kurukshetra. (India). Dr. Abhishek Taneja,M.B.E,M.C.A.,M.Phil.,ph.d, Assistant Professor-Department of Library and Information Science,University of Kashmir,India doc. Ing. Rostislav Chotěborský,ph.d, Katedra materiálu a strojírenské technologie, Technická fakulta,Česká zemědělská univerzita v Praze,Kamýcká 129, Praha 6, 165 21 Dr. Amala VijayaSelvi Rajan,,Ph.d, Faculty – Information Technology Dubai Women’s College – Higher Colleges of Technology,P.O. Box – 16062, Dubai, UAE Naik Nitin Ashokrao,M.Sc Lecturer in Yeshwant Mahavidyalaya Nanded University Dr.A.Kathirvell, B.E, M.E, Ph.D,MISTE, MIACSIT, MENGG Professor - Department of Computer Science and Engineering,Tagore Engineering College, Chennai Dr. H. S. Fadewar,,M.Phil.,ph.d,PGDBM,B.Ed. Associate Professor - Sinhgad Institute of Management & Computer Application, Mumbai-Banglore Westernly Express Way Narhe, Pune - 41 Dr. David Batten Leader, Algal Pre-Feasibility Study,Transport Technologies and Sustainable Fuels,CSIRO Energy Transformed Flagship Private Bag 1,Aspendale, Vic. 3195,AUSTRALIA Dr R C Panda (MTech & PhD(IITM);Ex-Faculty (Curtin Univ Tech, Perth, Australia))Scientist CLRI (CSIR), Adyar, Chennai - 600 020,India Miss Jing He PH.D. Candidate of Georgia State University,1450 Willow Lake Dr. NE,Atlanta, GA, 30329 Dr. Wael M. G. Ibrahim Department Head-Electronics Engineering Technology Dept.School of Engineering Technology ECPI College of Technology 5501 Greenwich Road - Suite 100,Virginia Beach, VA 23462 Dr. Messaoud Jake Bahoura Associate Professor-Engineering Department and Center for Materials Research Norfolk State University,700 Park avenue,Norfolk, VA 23504

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 Dr. V. P. Eswaramurthy M.C.A., M.Phil., Ph.D., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 007, India. Dr. P. Kamakkannan,M.C.A., Ph.D ., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 007, India. Dr. V. Karthikeyani Ph.D., Assistant Professor of Computer Science, Government Arts College(Autonomous), Salem-636 008, India. Dr. K. Thangadurai Ph.D., Assistant Professor, Department of Computer Science, Government Arts College ( Autonomous ), Karur - 639 005,India. Dr. N. Maheswari Ph.D., Assistant Professor, Department of MCA, Faculty of Engineering and Technology, SRM University, Kattangulathur, Kanchipiram Dt - 603 203, India. Mr. Md. Musfique Anwar B.Sc(Engg.) Lecturer, Computer Science & Engineering Department, Jahangirnagar University, Savar, Dhaka, Bangladesh. Mrs. Smitha Ramachandran M.Sc(CS)., SAP Analyst, Akzonobel, Slough, United Kingdom. Dr. V. Vallimayil Ph.D., Director, Department of MCA, Vivekanandha Business School For Women, Elayampalayam, Tiruchengode - 637 205, India. Mr. M. Rajasenathipathi M.C.A., M.Phil Assistant professor, Department of Computer Science, Nallamuthu Gounder Mahalingam College, India. Mr. M. Moorthi M.C.A., M.Phil., Assistant Professor, Department of computer Applications, Kongu Arts and Science College, India Prema Selvaraj Bsc,M.C.A,M.Phil Assistant Professor,Department of Computer Science,KSR College of Arts and Science, Tiruchengode Mr. V. Prabakaran M.C.A., M.Phil Head of the Department, Department of Computer Science, Adharsh Vidhyalaya Arts And Science College For Women, India. Mrs. S. Niraimathi. M.C.A., M.Phil Lecturer, Department of Computer Science, Nallamuthu Gounder Mahalingam College, Pollachi, India. Mr. G. Rajendran M.C.A., M.Phil., N.E.T., PGDBM., PGDBF., Assistant Professor, Department of Computer Science, Government Arts College, Salem, India. Mr. R. Vijayamadheswaran, M.C.A.,M.Phil Lecturer, K.S.R College of Ars & Science, India. Ms.S.Sasikala,M.Sc.,M.Phil.,M.C.A.,PGDPM & IR., Assistant Professor,Department of Computer Science,KSR College of Arts & Science,Tiruchengode - 637215 Mr. V. Pradeep B.E., M.Tech Asst. Professor, Department of Computer Science and Engineering, Tejaa Shakthi Institute of Technology for Women, Coimbatore, India.

Dr. Pradeep H Pendse B.E.,M.M.S.,Ph.d Dean - IT,Welingkar Institute of Management Development and Research, Mumbai, India Mr. K. Saravanakumar M.C.A.,M.Phil., M.B.A, M.Tech, PGDBA, PGDPM & IR Asst. Professor, PG Department of Computer Applications, Alliance Business Academy, Bangalore, India. Muhammad Javed Centre for Next Generation Localisation, School of Computing, Dublin City University, Dublin 9, Ireland Dr. G. GOBI Assistant Professor-Department of Physics,Government Arts College,Salem - 636 007 Dr.S.Senthilkumar Research Fellow,Department of Mathematics,National Institute of Technology (REC),Tiruchirappli-620 015, Tamilnadu, India.


Contents 1. Cent Percent Safe Centum Plants For Antiobesity……….[1] 2. EMID: Maximizing Lifetime of Wireless Sensor Network by Using Energy Efficient Middleware Service……….[20]

3. Adaptive Hysteresis Current Control of Inverter For Solar Photovoltaic Applications …..[25] 4. Plan Design Implement Framework Tool For Nce…[34] 5. Lag Based Hermite Interpolation Method For Solving A Root Of Nonlinear Equations…[40] 6. A Novel Approach for Combating Spamdexing in Web using UCINET and SVM Light Tool ……[47]

7. Efficient Wavelet based Image Compression Technique for Wireless Communication….[53] 8. Serpentine Robot Locomotion: Implementation through Simulation………….[60]


CENT PERCENT SAFE CENTUM PLANTS FOR ANTIOBESITY Dr. Philomena George* and O.S.Nimmi Department of Biotechnology, Karunya University, Coimbatore, Tamil Nadu, India 641114 Abstract:This paper is an over view of 100 medicinal plants commonly used as dietary supplements for obesity found in Asian countries particularly in India, China, Taiwan, Korea and Africa. Synthetic drugs are effective but have potential harmful side effects. Nutraceuticals and herbal supplements are used by people worldwide to promote health, wellness, maintain weight and fight diseases. Our project is to formulate a nutraceutical product having antiobesity prepared in the form of fancy food items like estruded products , biscuits, noodles, etc and the PolyHerbal Formulation ( PHF) product is combined with base materials such as cereals, millets, pulses, and fibre rich products. The product evaluation can be done in animal models such as mice , rat, rabbits,chicks and human volunteers.Some of the phyto constituents such as inulin , pectin , flavonoids , saponins , tannins , dietary fibres , phytosterols/stanols , dietary carotenoids , polyphenols ,plant indoles , have potential hypolipidemic properties by different mechanisms such as reducing atherosclerosis by inhibiting platelet aggregation, increasing fibrinolysis , enhancing antioxidant activity, reducing serum lipids in general to lower cholesterol levels, controlling appetite, fat metabolism, adipocyte differentiation, fat absorption, energy metabolism, etc.The present study is to find out the antiobesity effects of few herbals such as Allium sativum ,Coriandrum sativum , Mentha arvensis, Camellia sinensis ,Foeniculum vulgare, Commiphora mukul, Zingiber officinale ,Nelumbo nucifera

etiology of obesity [19] Obesity can result from increased energy intake, decreased energy expenditure ,or a combination of the two. While all causes are considered, major attention is given to behavioural and societal changes that have increased the energy density of diets, overwhelmed sophisticated regulatory systems that control appetite and maintain energy balance, and reduced physical activity[43]. It is found that intra abdominal and abdominal subcutaneous fat have more significance than subcutaneous fat present in buttocks and lower extremities .This distinction is most easily made clinically by determining the waste-tohip ratio and the ratio >0.9 in women and >1.0 in men is considered as abnormal .Many of the most complication of obesity, such as insulin resistance, diabetes, hypertension , hyperlipidemia and hyperandrogenism in women ,are linked most strongly to intraabdominal and/or upper body fat than to overall fat adiposity .The vast majority of obese persons have an increased leptin levels. A BMI between 25 and 30 should be viewed as medically significant and worthy of therapeutic intervention, especially in the presence of risk factors that are influenced by adiposity such as hypertension and glucose in tolerance. There is an urgent need for safe and efficient remedies for obesity. Herbal medicine is a major component in all traditional medicine systems, and a common element in siddha, ayurvedic, homeopathic, naturopathic, traditional chinese medicine, and Native American medicine.

Keywords: Herbal supplements, hypolipidemic, antiobesity, anthropometric, metabolic syndrome, nutraceutical product.

Metabolic syndrome (also known as insulin Resistance syndrome and Syndrome X, Reaven's syndrome) is a common disorder arising as a result of obesity. Metabolic syndrome is a combination of medical disorders that increase the risk of developing cardiovascular disease and diabetes. It affects one in five people; prevalence increases with age and can affect anyone at any age. It is most frequently seen in those who are significantly overweight with most of their excess fat in the abdominal area - and inactive All of the factors associated with metabolic syndrome are interrelated. Obesity and lack of exercise tend to lead to insulin resistance. Insulin resistance has a negative effect on lipid production, increasing VLDL (very

INTRODUCTION Obesity is one of the greatest health threats which has become a global issue of this century. It is a state of excess adipose (lipid storing adipose cell) tissue mass. It has an important impact on lifestyle-related diseases such as coronary heart disease, dyslipidemia, glucose intolerance, diabetics, hypertension and some cancers [25]. Several factors such as lack of exercise, sedentary lifestyle, consumption of energy rich diets etc, are contributory to the


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 • approximately 1.6 billion adults (age 15+) were overweight;

low-density lipoprotein), LDL (low-density lipoprotein – the "bad" cholesterol), and triglyceride levels in the bloodstream of

and decreasing HDL (high-density lipoprotein – the "good" cholesterol)[37] .

at least 400 million adults were obese.

WHO further projects that by 2015, approximately 2.3 billion adults will be overweight and more than 700 million will be obese.At least 20 million children under the age of 5 years are overweight globally in 2005. INDIAN SCENARIO Statistics point to an increase in overweight or obese citizens by 20% between 1998 and 2005. Presently, one in 6 women and one in 5 men are overweight in India. Obesity figures are bulging dangerously at a staggering 70 million in India .Another study published in the Lancet, has revealed that “by 2030, non communicable disease will account for nearly 70% of all global deaths and 80% of these deaths will occur in developing countries like India”[6] The latest obesity statistics shows that 75 percent of Indian women and 58 percent of Indian men are obese. Estimated prevalence (%) of Overweight & Obesity (BMI ≥ 25 kg/m²) females and males (Aged 15+) is 18 and 20.1 respectively [60]. FACTORS AFFECTING OBESITY[42] 1. Genetic & environmental factors : Studies indicate that from 40% to as much as 80% of the variance of BMI can be attributed to genetic factors. It is estimated that heritability is as high as 30-40% for factors relevant to energy balance such as body fat distribution, resting metabolic rate, energy expenditure after overeating, lipoprotein lipase activity and basal rates of lipolysis. Over 250 genetic markers have been described in association with obesity-related variables in humans (e.g., BMI, skin-fold thickness, waist-to-hip ratio, fat mass, and percent fat mass). 2. Endocrine & metabolic Factors : Both metabolic and endocrine factors rarely cause obesity and complex interactions between the endocrine and metabolic systems are found to be contributing factors to obesity. 3. Psychological Factors :


Few causative personality characteristics such as e.g.,externality, depression, orality are seen related to obesity and research evidence strongly suggests that obesity is not a unitary syndrome (i.e.,obesity appears to be the end result of a complex interaction within and between both physical and psychological factors).

The World Health Organisation (2000:14) estimated for the first time in human history that the number of overweight people is higher than the number of starving or undernourished people of the world as shown in the figure 1. WHO’s latest projections indicate that globally in 2005:



Some patients eat more during periods of heavy exercise or during pregnancy and are unable to get back to their former eating habits. The increase in obesity can usually be related to the type of food consumed (i.e. food containing sugar and fat).

The Food and Drug Administration has approved several prescription medications for the treatment of obesity . These medications fall into two categories: (a) centrally acting drugs, which suppress appetite, (b) and peripherally acting drugs, which reduce fat

5. Control of appetite :

absorption. For example, phentermine and sibutramine act centrally, reducing appetite by promoting the release of norepinephrine from presynaptic terminals (phentermine) and inhibiting the uptake of both norepinephrine and serotonin (sibutramine) in central nuclei. Orlistat acts peripherally, inhibiting the action of lipases in the brush border of the intestine and thereby reducing lipid absorption. Such drugs could aim to suppress food intake, increase energy expenditure or increase lipolysis. At present, only two drugs have been shown to reduce the body weight of obese individuals like orlistat (which decreases fat absorption by preventing the breakdown of dietary fat in the gastrointestinal tract) and sibutramine (which is mainly an inhibitor at the CNS sites that stimulate food intake)[42].Under the guidelines of the US Food and Drug Administration, botanical drugs can be developed faster and cheaper than conventional single-entity pharmaceuticals. Many botanicals may provide safe, natural, and costeffective alternatives to synthetic drugs.

Appetite is the desire to eat and this usually initiates food intake. Following a meal, cholecystokinin (CCK), bombesin, glucagons-like peptide 1 (GLP1), enterostatin, and somatostatin are released from the small intestine, and glucagons and insulin from the pancreas. All of these hormones have been implicated in the control of satiety.

6. Energy expenditure & thermogenesis : Basal metabolic rate (BMR) in obese subjects is higher than in lean subjects, which is not surprising since obesity is associated with an increase in lean body mass. Obese patients tend to expend more energy during physical activity as they have a larger mass to move. On the other hand, many obese patients decrease their amount of physical activity. The energy expended on walking at 3 miles per hour is only 15.5 kJ/min (3.7 kcal/min) and therefore increasing exercise plays only a small part in losing weight.


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 TABLE- 1 : Indian plants with known anti obesity properties

S. N o 1.



Allium sativum.L

Antimicrobial, hypolipidemic , antioxidant , antineoplastic , antithrombotic ,antiatherogenic effects.



Citrus aurantium .L


( Bitterorange) Cissus quadrangularis Linn ( Hadjora)


Allicin.allin [55]

0.4 to 1.2 g of dried powder;

Stimulates the action the Fruit:60-120 mg central nervous system , assistance in weight loss. Anti-inflammatory, anti Stem:100 -500 obesity , analgesic, mg antibiotic, anthelmintic , antimicrobial, hypoglycemic.

Synephrine ,an alkaloid [ 3] Phytosterols and fibre [1, 16,26 ,44]


Coleus forskohlii (Willd.) Treating disorders such as glaucoma, heart Briq. (Coleus) failure, bronchial asthma

Root: 50-300 mg

Labdane diterpene forskolin [39]


Commiphora mukul Engl. Hypolipidemic, antiinflammatory, antitumor. (Indian Belellium Tree)

Resin: 50-100 mg

Z-guggalsterone, a ketosteroid [38, 58]


Coriandrum sativum L. ( Coriander)

Hypotensive, hyperglycemia,hyperlipid emia

Leaf:5 mg

Essential oil containing linalool as well as furanocoumarins (coriandrine, dihydrocoriandrine)[14


Costus igneus.Nak

Diuretic, hypotensive, hypoglycaemic.

Leaf:5000 mg

Saponins [9]


(Fiery spiral ginger) Cyperus Rotundus L.

Ant-inflammatory, antidiabetic,


Alkaloids [16, 58]






Foeniculum vulgare .Mill (Fennel seeds)

10 .

Garcinia Cambogia ( Malabar Tamarind)

11 .

Glycyrrhiza glabra Linne ( Licorice)

12 .

Gymnema sylvestre Ex schult ( Gurmar)

13 .

Nelumbo nucifera.Gaertn ( Indian Lotus)

Antispasmodic, secretolytic, secretomotor , antibacterial, galactagogue , anti-inflammatory.


Essential oil contains anethole, camphene, cuminic, limonene

Antiobesity, antiinflammatory, antiulcer, antimicrobial.

Fruits:200 to 500mg

(-) Hydroxy citric acid (HCA) [51,56 ]

Anti-allergic, antiinflammatory, antistress, antidepressive, antiulcer, antidiabetic, antidepressant effects.

Root:2-4 g.

Licorice flavonoid oil (LFO [ 28]

mythyl chavicol, dipentene, [20 ]

Leaves :75-150 mg Antidiabetic ,anti inflammatory activities, anti-obesity, antimicrobial , antihypercholesterolemic , hepatoprotective . Antidiabetic, antipyretic, anti-inflammatory, anticancerous, antiviral antimicrobial, and

Gymnemic acids [46 ,45, 10]

Sees:6-15g Leaf :3-6 g

anti-obesity properties .

Alkaloids(liensinine, neferine, nuciferine, remrefidine and isoliensinine) and flavonoids ((+)-1(R)coclaurine, (-)-1(S)norcoclaurine and quercetin 3-O-b-Dglucuronide) [11]

14 Piper nigrum.L . (Black pepper)

anti-inflammatory, antioxidant, analgesic effects, Aromatic, stimulant, carminative ,febrifuge,cholagogue, emmenagogue

Seeds: 2-5g

Crystalline alkaloids piperine, [ 2]

15 .

Immunomodulatory, antiasthamatic, antioxidant,

Seeds: 500mg-1g

Alkaloids piperine and piperlongumine

Piper longum.L ( Long papper, Pipali)



hypocholestremic , antiinflammmatory, negative chronotropic and negative inotropic activities.

16 .

Phyllanthus emblica.L ( Amla)

17 .

Souropus androgynusL.Merr.

18 .

( Sweet leaf bush) Vitis vinifera L. ( Grape)

19 .

Zingiber officinale Roscoe

[ 31, 2, 58]

Anabolic, antibacterial, antipyretic, antiviral, antioxidative, antihepatic, immunomodulator .

Seeds:3 to 6g

Ascorbic acid, fiber, pectin, zinc [48]


Leaves: 18 mg

Saponin, alkaloids and tannin [53]

Antioxidant, antithrombotic, cardioprotective effects, antiobesity properties .

Skin Extract 50 mg

Resveratrol (trans-3, 40, 5-trihydroxystilbene) , a phytopolyphenol [19,59]

Antioxidant, antihypolipidaemic.

Rhizome: 10mg

Seed Extract 100 mg-350 mg

Gingerols, 6-shogaol and galanolactone

[ 49]

( Ginger) 20 .

Lagerstroemia speciosa.L (Queen’s flower , Banaba , Pride of India)


Antidiabetic, antiadipogenic.


triterpenoid , corosolic acid and the ellagitannins like lagerstroemin, flosin B, and reginin A. [21]

TABLE 2:Chinese herbs with known antiobesity properties[12,6, 27,40,62]


Scientific name

Plant part



Achyranthes bidentata Bl.




Alisma oriental (Sam.) Juzep




Angelica sinensis (Oliv.) Diels.






Astrag alus membranaceus (Fisch.) Bunge




Atractylodes macrocephala Koidz.




Bupleurum chinense DC.




Camellia sinensis (L.) O. Kuntze




Carthamus tinctorius L.




Citrus aurantium L.

Young fruit



Coptis chinensis




Cornus officinalis Sieb. Et Zucc.




Dioscorea opposita Thunb.




Eclipta prostrata L.

Whole grass



Ephedra sinica Stapf

Herbaceous stem



Epimedium brevicornum Maxim.

Aerial part



Forsythia suspensa (Thunb.) Vahl




Grifola frondosa (Dickson ex Fr.) S. F. Gray

Fruit body



Grataegus pinnatifida Bunge




Leonurus japonicus Houtt.




Ligusticum chuanxiong Hort.




L igustrum lucidum Ait.




Lycium chinenseMill




Millettia reticuiata Benth.




Morus alba L.




Paeonia lactiflora Pall.






Panax notoginseng (Burk.) F.H.Chen




Phragmites communis Trin.




Pinellia ternata (Thunb.) Breit.




Plantago asiatica Linn.

Whole grass



Polygonum cuspidatum Sieb. et Zucc

Root and rhizome



Polygonum multiflorum Thunb.




Poria cocos (Schw.) Wolf

Fruit body



Portulaca oleracea Linn.

Aerial part



Prunella vulgaris L.




Pueraria lobata (Willd.) Ohwi




Radix Angelica Sinensis




Raphanus sativus L.




Rheum palmatum L.

Root and rhizome



Rubus suavissimus S.K.Lee




Salvia miltiorrhiza Bge.

Root and rhizome



Saposhnikovia divaricata (Turcz.) Schischk.




Sophora tonkinensis Gapnep.

Root and rhizome



Trigonella foenum-graecum Linn.

Seed and Leaf



Taxillus chinensis (DC.) Danser

Aerial part



Uncaria macrophylla Wall.

Aerial part



Medicago sativa

Leaves and Tender





TABLE -3: Korean medicinal plants used for the management of obesity [61]



Fraxinus rhynchophylla Hance ( Chimese ash)


Eleutherococcus sessiliflorus (Rupr. et Maxim.) S.Y.Hu(Acanthopanax)



Plant Name


Lipoxygenase inhibition, HMGCo A reductase inhibition activities [22]


Anti-inflammatory and antioedemic , adaptogenic, lipid lowering [63]

Crataegus pinnatifida Bunge (Hawthorn, Thorn apple )


Hypotensive,cholesterol level lowering activities , platelet aggregation inhibition [24]

Angelica dahurica (Fisch.) Benth. et Hook.f.


Akebia quinata Decne.





Lipolysis and lipogenesis [35, 36]

Diuretic, anti-inflammatory, lowers serum cholesterollevel , antiulcer [ 34] Spasmolytic, sedative, hypocholesterolaemic



Acorus gramineus Sol.


andcholelytiasic [47]


Antibacterial , sedative , spasmolytic , hypocholesterolaemic [47]


Hypercholesteraemia,haemate mesis [52 ]


Acorus calamus var. angustatus Besser


Typha orientalis J.Presl


Choleretic , arteriosclerotic , hyperlipaemia lowering activities [54]


Antihypercholesterolaemic [64]


Antibacterial, antitussive, expectorant, antiasthmatic ,hypolipidaemic [59]


Scutellaria baicalensis Georgi


Rosa rugosa Thunb.


Pyrrosia lingua (Thunb.) Farw.


Pinus koraiensis Siebold et Zucc. Pinaceae


Hypolipidaemic, , analgesic, anti-inflammatory , antibacterial [13 ,33]



Panax ginseng C.A.Mey.


Antioxidant, antifatigue , immunostimulating ,increasing HDL cholesterol,stimulation of ADH , hypoglycaemic [ 15]

HMG Co-A reductase inhibition , antitumour activity [22] Morus stylosa var. ovalifolia Ser. (pro parte)



TABLE -4: South African medicinal plants used for the management of obesity [4] S. Local Part Plant name Family Purpose of use used No /English name 1. Agathosma apiculata G.Mey


Used to reduce body weight and fluid retention

A mixture of powdered root, vinegar and camphor is taken ½ glass cup twice daily.


Used for weight loss, stomach pain and wound healing

The powder root is soaked in water and infusion taken orally twice daily

Leave s

Used for weight loss and as antidiabetic. It enhances body healthiness, and treats arthritis and constipation

The liquid from the boiled leaves is taken ½ glass cup daily

Ibuchu Rutaceae / Buchu


Preparation/administrati on

Igwili Alepidea amatymbica Eckl. & Zeyh

/ Umvuthuza/ Apiaceae Larger tinsel flower


Aloe ferox Mill


Ikhalalasekoloni /Bitter aloe



Used to reduce body weight, to increase urination and to treat diabetes

The leaves are crushed and soaked in water. ½ glass cup of the extract is taken twice daily


Used for weight loss, as antihypertensive, treats heart problems, and skin burns

2 litres of boiled root infusion is taken ½ glass cup twice daily for 2weeks

Leave s

It is used for weight loss, as psychoactive and stimulates energy.

Fresh leaves are crushed, soaked in water and extract is mixed with vinegar.

Leave s

Used for body weight loss and to treat diabetics

Infusion from boiled leaves is usually taken ½ glass cup twice daily for 2weeks.

Whole plant

Used for body weight loss and wound healing

Cold Infusion of whole plant is taken ½ glass cup three times daily


Used for weight loss, stimulates body energy and arrests stomach aches.

2 litres of mixture called “isiwasho” is made from crushed root and vinegar, rooi pepper,cayane salt and methylated spirit. It is taken ½ glass cup daily or two spoonfuls twice daily.


Used to reduce body weight, as antidiabetic, antihypertensive and to treat stomach ailments

Powered root is boiled in water and taken ½ glass cup for a start and two spoonfuls twice ½ daily for a period of 1 weeks

Umthunzi/ Asparagus africana Lam

Asaparagace ae

Climbing asparagus

5. Bulbine alooides(L.) Willd

Asphodelace ae


6. Isangu Cannabis sativa L.

Cannabaceae /Marijuana


Epinkie/ Catharanthus roseus L G.Don.


Cucumis africanus L.f.

Curcubitacea e


Madagascar periwinkle Ithangazana/ Scaret guord


Cissampelos capensis L.f.

Menispermac eae

Umayisake /David root



Umlahleniselefil e

Curtisia dentata (Burm.f.) C.A.Sm


Exomis microphylla (Thunb.) Aellen

Chenopodiac ae

/Capelancewoo d

Umvawenyathi /Sugarbeet


Leave s

Used for body weight loss, as anti-diabetic and for wound

Decoction is taken ½ glass cup three times daily. Healing


Uthuvishe Kedrostis africana L.Cogn

Cucurbitacea e



Used for body weight loss

Decoction from crushed fresh bulb is taken twice daily

Whole plant

Used for body weight loss, as anti-diabetic and for wound healing

A fresh plant is crushed, boiled in water and infusion is taken ½ glass cup twice daily.

Whole plant

Used for body weight loss, and to treat stomach ache

A fresh plant is crushed, boiled in water and infusion is taken ½ glass cup twice daily.


Used for body weight loss, and to treat stomach ache

It is crushed and soaked in water. Infusion is taken twice daily.

Leave s

Used for body weight loss and as purgative

A mixture is made from boiled leaves and vinegar which is taken ½ glass three times

Leave s

Used for weight loss, reduces body fluid, as digestive, and antihypertensive. It is also used for flavor

Decoction is made from boiled fresh leaves and taken severally


Used to reduce body weight, treat stomachache and body weakness

The infusion is made from root decoction and taken ½ glass cup twice daily

/Baboons cucumber 13. Leonotis leonurus L.R.Br


Leonotis ocymifolia Burm.f Iwarsson

Umunyamunya/ Lamiaceae Wild dagga

Umuncwane Lamiaceae /wild dagga

15. Mimosops obovata Nees ex Sond.

Umntunzi/ Sapotaceae Red milkwood


Idolo l Phytolacca L.


Phytolaccace ae

enkonyane /Phytolacca


Rosmarinus officinalis L


Roosmaryn /Rosemary

18. Rubia D.C


Impendulo Rubiaceae /madder




Used for body weight loss, as anti-diabetic and antihypertensi ve. Used in the treatment of chest pain and arthritis

The bark is crushed to power and 2 spoonfuls of infusion is taken orally twice daily for 2weeks

Whole plant

Used for weight loss, as antihypertensive, and removes body liquid

Decoction from ground fresh plan is taken ½ glass cup twice daily

Umaphipa Schotia Jacq



/Forest bean


20. Vernonia mesphilifolia Less

Uhlunguhlungu Asteraceae /Iron weed


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 Human Subjects (test volunteers ) covering a wide range of adiposity such as overweight (mean body mass index , 2 approximately 32 kg/m , and a waist circumference 2 >85.5cm) , obese (at most 38 kg/m ) and also normal weight but otherwise healthy adults 18 to 65 years can be selected based on their willingness to participate . Subjects are asked to give a written consent form before their participation and the proceedings should be fully explained.



Assessment of obesity and overweight involves using the key measures[7]: i. Body Mass Index (BMI) Although not a direct measure of adiposity, the most widely used method to gauge obesity is the body mass index which is equal to weight/Height 2 (kg/m2) (Underweightbelow 18.5,Normal-18.5 to 24.9 ,Overweight- 25.0 to 29.9 ,Obesity- 30.0 and above ) ii. Waist- to- Hip Ratio (WHR) WHR is the ratio of a person's waist circumference to their hip circumference, and is also used to determine risk for weight-related illnesses. A WHR greater than 1.0 in men or greater than 0.8 in women is considered obese. iii. Waist Circumference Measuring waist circumference is a good indicator of abdominal fat, which is another predictor of your risk for developing risk factors for heart disease and other diseases. This risk increases with a waist measurement of over 40 inches in men and over 35 inches in women. iv. Skin fold thickness Using a skin fold caliper to measure percent body fat is another way to determine obesity. Generally, men with more than 25% body fat and women with more than 30% are considered obese. The caliper takes measurements of fat lying just below the skin from several parts of the body (such as the triceps, or back of upper arm) to estimate percentage of body fat.

Subjects who are pregnant ,have any clinically significant medical condition, are taking prescription medications or appetite suppressants on a regular basis, have a history of alcohol or other drug abuse, or allergic to any of the study products or have dieted with weight loss in the past 6 months are to be exempted for the study. 3.

Experimental diets for animals are prepared and the feed intake has to be measured daily and at the same time the amount of food left over has to be calculated by subtracting from the measured amount of food in each cage barrier for each mice provided the previous day (gm/day/mice) and body weight should be recorded weekly. The animals are grouped into normal control and treatment groups with six in each group (n=6) .The treatment groups are induced to become obese (about 30 days) prior to the experiment.The treatment groups can be with the polyherbal formulation product and synthetic treatment. The dosage of administration of the PHF and the synthetic drug is calculated after the toxicity studies (L50). Human test volunteers are grouped randomly into obese and overweight and normal groups which are divided into placebo- controlled and treatment groups [26 ].The treatment groups can either be formulation with diet or without diet. Experimental period is to be carried out for 3 months.

Other methods for measuring body fat include using electronic impulses densitometry (under water weighing), CT or MRI and electrical impedance, measurements that use modern imaging such as magnetic resonance, X-ray and computerized tomography are proven to be the best and the most accurate. 2.

Study Design


Experimental Models

Weight Measurements

The weight of the experimental animals has to be noted before and after the experiment and also on a weekly basis using an electronics balance to have clear information about the effect of the anti-obesity effect of PolyHerbal Formulation product (PHF).

Different animal models can be used such as Adult Balb/c albino mice (15± 5 g ) , Ob/Ob mice, White male albino rats( 80-90gm, 60 day old)[29], Male Wistar albino rats ( 150-170g,90 days old) [41], Male Sprague –Dawley (307±30g) , male ICR mice (20±2g), female ICR mice ( 8weeks old), C57BL/6J mice ( 4 weeks old) [57], Albino rats of porter strain of either sex[38] Male albino Wistar rats ( 150-200g).

The net weight loss can be calculated as: Net weight loss = Initial weight (W0) – New weight (W1)

Rabbits ( 6-9 months old, 1.3-2.7kg ) [ 18]

% of weight loss= Total Weight loss x 100 / Initial weight Birds such as Broiler Chicken (21 days old) [53]. 5. Biochemical Parameters:



Liver Function Test (LFT)

SGOT-Serum glutamic oxaloacetic transaminse, SGPTserum glutamic pyruvic transaminase, ALPAlkaline phosphatase, Serum bilirubin, Total protein

Kidney function

Urea, creatinine, uric acid

Heart biomarkers

CK-MB (Creatine kinase myocardial type), CK- NAC (N- acetylcysteine) and LDH (lactate dehydrogenase activity),lipoprotein A

The blood has to be collected from the animals initially and terminally to the experiments by the following techniques mentioned in Table 5:

TABLE -5: Techniques of Blood Collection S.No 1.

Techniques Blood collection not requiring anesthesia

Site of Collection Saphenous vein,Dorsal pedal vein


Blood collection requiring anesthesia

Tail vein ,Orbital sinus, Jugular vein


Terminal procedures

Cardiac puncture ,Posterior vena cava, Axillary vessels,Orbital sinus

Oxidative stress markers

Malonyldialdehyde (MDA), Glutathione S-transferase (GST), Reduced glutathione (GSH) Superoxide dismutase (SOD), Catalase.

5.2. Tissue Samples Animals have to be sacrificed and separation of spleen, kidneys, fat pads (hepatic, perirenal, and visceral adipose tissues) has to be done. They are to be blotted on filter paper and weighed (g). The liver should be immediately excised and weighed (g) and is homogenized for GSH (reduced glutathione) and MDA ( Malondialdehyde) catalase measurements.

On day 42 ,blood can be collected after sacrificing them either by cardiac puncture /retro-orbital sinus. Blood samples collected are to be centrifuged at 3500 rpm for 15 mins at room temperature for separation of serum. The clear, non-haemolysed supernatant sera will be separated using clean dry disposable plastic syringes and stored at 20â—ŚC for subsequent biochemical measurements shown in Table 6

5.3. Human Studies considering the anti-obesity effects of PHF

TABLE-6: Biochemical Measurements and Hormonal parameters

Blood analysis 1. Blood analysis(Complete Haemogram)2.

Hormonal Assay

Lipid profile

Change in anthropometric measures such as body weight and waist – hip circumference, body fat (weight or mass of visceral adipose tissue, fat mass or percent),triceps skin fold thickness , appetite or amount of food intake has to be noted. Blood sampling and clinical analysis has to be done at baseline and after the treatment period.

Glucose RBC, WBC (TC/DC) , ESR, Blood platelet , Haemoglobin , Haematocrit , MCV(Mean Corpuscular Haemoglobin) , MCH( Mean Corpuscular Volume) , MCHC( Mean Corpuscular Haemoglobin Concentration Insulin concentration Leptin concentration


Some herbs act on digestion, metabolism, or appetite to impact weight loss. Certain substances can increase thermogenesis (generation of heat), or metabolism, which may lead to weight loss .Herbal weight loss products are a great safe option for the people who want to lose weight naturally.


Total cholesterol. LDL, HDL, VLDL, total triglycerides


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 Various herbal supplements have proved to be effective against obesity and its related diseases. Allicin , the major component of garlic is mainly responsible for the hypolipidemic [5,55] activity. Garlic reduces atherosclerosis by inhibiting platelet aggregation, increasing fibrinolysis , enhancing antioxidant activity, and reducing serum lipids in general to lower cholesterol levels and other significant risk factors for CAD (coronary artery disease). Steroids like Z-Guggulusteron and EGuggulusterone found in Commiphora mukul [38,58] possesses lipid lowering activity. Fibre extracts of Cissus quadrangularis have been shown to have anti-lipase properties that reduce absorption of dietary fats and enhance satiation [1,16,26,44]. The major constituents alkaloids (liensinine , neferine , nuciferine , remrefidine and isoliensinine) and flavonoids (+)-1(R)-coclaurine , (-)-1(S)norcoclaurine and quercetin 3-O-b-D- glucuronide) of Nelumbo nucifera have cholesterol-lowering and anti obesity effects [11]. The active ingredient around 20- 30% of (-) hydroxy citric acid (HCA) in Garcinia cambogia, works by ATP citrate lyase converts, excess calories from food into fat for storage [51,56]. Anti obesity properties of Phyllanthus emblica are due to ascorbic acid, fiber, pectin and zinc [50] . Panax ginseng proved for antihyperglycemia , insulin sensitization , islet protection, antiobesity and anti-oxidation in many model systems. Energy expenditure is enhanced by ginseng through thermogenesis. Ginseng-specific saponins (ginsenosides) are considered as the major bioactive compounds for the metabolic activities of ginseng [23].Vitis vinifera (oligomeric proanthocyanidins (OPCs) or procyanidins from grape seed are theorized to be beneficial to prevent and treat cardiovascular and circulatory conditions due to antioxidant and potential antilipoperoxidant activity [17,57] .Citrus aurantium (Synephrine) stimulates peripheral tissue thermogenesis [3] ,Grifola frondosa (fibers) helped in lowering VLDL and serum cholesterol[43] , Cyperus rotundus (tertiary sesquiterpine alcohol, isocyperol ) suresha[16,58] , exhibits lipolytic action. Irvingia gabonensis ( polyphenols such as epigallocatechin gallate [26] favourably impacts adipogenesis through a variety of critical metabolic pathways.


Achal Thakur, Vandana Jain, L Hingorani, KS Laddha, Phytochemical Studies on Cissus quadrangularis Linn 2009;1(4) : 213-215. 2. Acharya.D and Shrivastava. A, Indigenous Herbal Medicines: Tribal Formulations and Traditional Herbal Practices. Aavishkar Publishers Distributors, Jaipur. 2008 ISBN 978-81-7910-2527. 3. Adriane Fugh-Berman and Adam Myers ,Citrus aurantium, an Ingredient of Dietary Supplements Marketed for Weight Loss: Current Status of Clinical and Basic Research, Exp Biol Med (Maywood). 2004;229(8):695-7. 4. Afolayan A J and Mbaebie B O, Ethnobotanical study of medicinal plants used as anti-obesity remedies in Nkonkobe Municipality of South Africa, Pharmacognosy Journal,Research Article 2010; 2(11): 368-373. 5. Amagase H, Petesch BL, Matsuura H, Kasuga S and Itakura Y , Intake of garlic and its bioactive components ,Journal of Nutrition, 2001 ; 131(3s):955S-62S. 6. Anti-Obesity Day 2010 - The Big Fat Problem Plaguing India 7. Anthropometric Measurements - nutrition, body, fat, weight 8. Ava Jiangyang Guo , Roy Chi-yan Choi , Anna Wing-han Cheung , Jun Li , Ivy Xiaoying Chen , Tina Tingxia Dong , Karl Wah-keung Tsim and Brad Wing-chuen Lau,Stimulation of Apolipoprotein A-IV expression in Caco-2/TC7 enterocytes and reduction of triglyceride formation in 3T3-L1 adipocytes by potential antiobesity Chinese herbal medicines ,Chinese Medicine 2009, 4:5 9. Bhat Vishnu, Asuti Naveen, Kamat Akshay, Sikarwar Mukesh. S., Patil M. B. Vishnu Bhat et al , Antidiabetic activity of insulin plant (Costus igneus) leaf extract in diabetic rats, Journal of Pharmacy Research 2010 ;3(3):608-611. 10. Bishayee, A. and Chatterjee, M. ,Hypolipidaemic and antiatherosclerotic effects of oral Gymnema sylvestre R. Br. Leaf extract in albino rats fed on a high fat diet, Phytotherapy Research (1994);8:118–120. 11. Brindha.D, D.Arthi, Antimicrobial Activity of White and Pink Nelumbo nucifera Gaertn flowers , Journal of Pharmaceutical Research and Health Care ,2010 ;2(2):147-155. 12. Cheng-Dong Zheng,Ya-Qing Duan1, Jin-Ming Gao, Zhi-Gang Ruan , Screening for Anti-lipase Properties of 37 Traditional Chinese Medicinal Herbs, J Chin Med Assoc

This paper is an overview of plants screened globally for antiobesity and ours is an attempt to develop a neutraceutical product for antiobesity. In our study different combinations of herbal supplements for antiobesity are chosen from Table 1 for the preparation of a polyherbal formulation (PHF) product. Ingredients for Poly Herbal formulation product (PHF) and the calorific value of PHF were calculated . Fine tuning of various food formulations such as extruded products , biscuits , noodles, foodles etc is in progress . Studies on animal models and human volunteers are in progress. REFERENCES:


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Total Cholesterol and Triglyceride Lowering Activities of Phyllanthus Emblica L. ( Euphorbiaceace ) Fruits in Rats Advances in natural and Applied Sciences 2010; 4 ( 2): 168170. Rihana kamal and Shagufta Aleem,Clinical evaluation of the efficacy of a combination of Zanjabeel( Zingiber officinale) and amla( Emblica officinalis) in Hyperlipidaemia , Journal of Traditional knowledge 2009;8 (3): 413-416. Ritu, Mathur, Arti Sharma, V. P. Dixit and Mira Verma Title: Hypolipidemic effect of fruit juice of Emblica officinalis in cholesterol-fed rabbits , Journal of Ethnopharmacology 1996 ;50, 2 :6168. Saito M, High dose of Garcinia cambogia is effective in suppressing fat accumulation in developing male Zucker obese rats, but highly toxic to the testis. Food Chem Toxicol. 2005;43(3):411-9. *Sakurai, Tetrahedron (1983) ;39, 883. Cited from WHO Western Pacific Region - Publications and documents Series No21- Medicinal plants in the Republic of Korea 1998, 316 pages. Santoso.U , Kusussiyah and Y. Fenita, The effect of Souropus androgynous Extract and Lemuru oil on Fat deposition and fatty acid Composition of Meat in Broiler Chickens , J. Indonesian Trop. Anim. Agric .2010 ;35( 1). *Shin, K.H.,Kor. J. Pharmacog. (1994) ; 25, 41, Cited from WHO Western Pacific Region Publications and documents Series No21Medicinal plants in the Republic of Korea 1998, 316 pages. Soon Ah Kang, Ho Jung Shin , Ki-Hyo Jang, Sung Eun Choi, Kyung Ah Yoon, Jin Sook Kim, Hye Kyung Chun and Yoongho Lim, Effect of Garlic on Serum Lipids Profiles and Leptin in Rats Fed High Diet, J Food Sci Nutr ( 2006) ;Vol II :4853. Steven B. Heymsfield, MD; David B. Allison, PhD; Joseph R. Vasselli, PhD; Angelo Pietrobelli, MD; Debra Greenfield, MS, RD; Christopher Nunez, MEd , Garcinia cambogia (Hydroxycitric Acid) as a Potential Antiobesity Agent ,A Randomized Controlled Trial ,JAMA. 1998;280:1596-1600. Su-Hui, Park, Tae-Sun, Park,andYoun-Soo, Cha Grape seed extract (Vitis vinifera) partially reverses high fat diet-induced obesity in C57BL/6J mice Nutrition Research and Practice (2008), 2(4), 227-233. Suresha .B., M. G. Hariprasad, R. Rema & U. Imran : Antiobesity effect of Lipovedic formulation in rats fed on atherogenic diet. The Internet Journal of Nutrition and Wellness. 2009; Vol 8 No 2.


EMID: Maximizing Lifetime of Wireless Sensor Network by Using Energy Efficient Middleware Service Chandrakant N1, Tejas J1, Harsha D1 Dept. Computer Science and Engineering,University Visvesvaraya College of Engineering,Bangalore, India 1 1 2 P Deepa Shenoy , Venugopal K R , L M Patnaik 2 Vice Chancellor,Defense Institute of Advanced Technology,Pune, India

Abstract:This paper introduces the processing of raw data from sensor nodes located at different places within the vicinity of header node. The middleware service of header node evaluates the assignment and requirement of each node that comes under its vicinity. Based on header node instructions each sensor node is in one of two modes: Active mode or Sleep mode. We have developed a software program to compute the essence of each node based on the raw information provided by each sensor node. If raw data of current sensor node is static at certain time interval or if the raw data of current sensor node is equal to the raw data of other sensor node, then the current node will be treated as qualified node to go to sleep for the time period of maxSleepTime. The proposed algorithm is well suited for military application or monitoring unmanned area.

WSN is limited in energy and has individual resources (such as CPU and memory). These tiny devices could be deployed in hundreds or even thousands in harsh and hostile environments. In many cases physical contact for gathering data is impossible. In such cases wireless media is the only way for remote accessibility. Hence, middleware should provide mechanisms for efficient computation and memory use while enabling lower-power communication. A sensor node should accomplish its three basic operations: sensing, data processing, and communication without exhausting resources such as energy. The development of middleware for sensor networks, however, places new challenges to middleware developers due to the low availability of resources like energy and processing capacity of the sensor nodes. A middleware layer should act as a broker between applications and the WSN, translating application requirements into WSN configuration parameters. Due to the dynamism of WSN environments, applications should have some degree of power awareness to best reach their network lifetime requirements. The middleware should supply mechanisms that allow the application to monitor the network state through a high level interface. EMID (Energy efficient MIDdleware service) paper proposes a service-oriented middleware for WSNs. We address the problem of energy efficiency in wireless sensor applications. Considering raw data, the proposed algorithm is used to decide which node has to go for sleep and which node has to wake up.

Keywords-EMID, WSN, SleepWake Cycle I.


Wireless Sensor Networks (WSN) is a set of sensor nodes that collects the information from environment and sends to base station (Header node or Central Node).Basically, WSN are application specific and all design considerations are different for each application. The requirements of WSNs are very specific, especially when it comes to military application. Middleware is a software infrastructure that binds together the applications, network hardware, operating systems and network stacks. The main services of middleware are to provide standardized system services to diverse applications. It provides a runtime environment that can support and coordinate multiple applications. However the important mechanism of middleware is to achieve adaptive and efficient utilization of resources.



The power related problem has been studied extensively in the context of power aware


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 communication mechanisms. The Aura project [4] and related work on SenSay: A Context-Aware Mobile Phone [9] investigates how a small set of sensors, may relieve the user from being constantly aware of and having to manage the telephones state. The Solar system [1] is a prototype implementation of a graph-based abstraction for context collecting, aggregation, and dissemination of (sensor) generated events passing one or more operators and is finally delivered to a subscribing application. The Context Toolkit [2] supports the development of context-aware applications using context widgets with different responsibilities that provide context information to applications. The lowest level interfaces to a physical sensor. The middle layer is concerned with abstracting and combining data. The highest level coordinates the underlying components and provides the callback interface to applications.

ability of the WSN is suitably harnessed, it is visualized that WSNs can reduce or eliminate the need for human involvement in information gathering in certain civilian and military applications. The lifetime of wireless sensor network is limited due to lack of battery power. In some cases physical contact for replacement and maintenance is impossible. In such situations we require a efficient service to overcome this problem. The objective of EMID algorithm is to increase the network lifetime by applying Optimal Sleep-Wake Policies for Wireless Sensor Network. The sleep mode is a power saving mode in which the sensor only harvests energy and performs no other functions so that the energy consumption is negligible [6]. IV.

WSN middleware is a software infrastructure that glues together the network hardware, operating systems, network stacks, and applications as given in the Fig 2. A complete middleware solution should include a runtime environment that supports and manages multiple applications, and standardized system services such as data aggregation, control and management policies adapting to target applications, and mechanisms to achieve adaptive and efficient system resources used to prolong the sensor networks life. The EMID will be introduced at the resource management layer to manage the resources based on the raw data provided by each node. The resource management layer also coordinates the resource sharing based on application needs, passed through the upper layers. Services provided by upper layers may need some resource sharing support, which is encapsulated in the communication layer.

The Web Architectures for Service Platforms (WASP) [5]was designed to support context-aware applications specifically in the 3G environment using Web Services technologies and WASP Subscription Language (WSL) to communicate with the platform that connects context-aware applications with context providers (sensors) and third party service providers. The project ”Context Recognition by User Situation Data Analysis (Context)” [7] studies characterization and analysis of information about users’ context and use it in adaptation. Mires [10] propose an adaptation of a message oriented middleware for traditional fixed distributed systems. Mires provide an asynchronous communication model that is suitable for WSN applications, which are event driven in most cases, and has more advantages over the traditional requestreply model. It adopts a component-based programming model using active messages to implement its publish-subscribe-based communication infrastructure. This paper is organized as follows; Section III briefs the problem definition. Section IV gives details about middleware architecture for wireless sensor network. In Section V, we have proposed an algorithm to achieve maximum network life time. Finally Section VI gives our conclusion.




One of the key tasks of WSN is their ability to bridge the gap between the physical and logical worlds, by gathering certain useful information from the physical world and communicating that information to more powerful logical devices that can process it. If the

Figure 1. Structure of Wireless Sensor Network.


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 node. Header node will extract the raw data. If the raw data of current node is equal to its previous owned raw data that has been taken at dataAtSampleTime or if the raw data of current node is equal to the raw data of other node, then SendSleepSignal function will be executed which sends current node to the sleep mode.

TABLE I. Figure 2. EMID overall architecture.


As an application uses such a service, the corresponding layer asks for the communication layer to manage the access control of the required resources. Indeed, the resource management layer commands the allocation and adaptation of resources, such that the QoS requirements specified by the applications can be met.




Maximum sleep Time


Sample Time

Psleep PCS Et1 Ed1



A key assumption in EMID is that, header node will act as central node for all sensor nodes that comes under his vicinity. A central node will have an additional or constant power supply for computation and management of nodes. Middleware is placed in central node or header node as it has constant or additional power supply. Also, each sensor is preloaded with certain power to sense the environment. Since all sensor nodes are homogeneous in nature, their transmission ranges are assumed to be the same. Table 1 enlists all variables used to implement this paper. This section discusses the algorithm and variables used in the implementation. Central node manages the set of sensor nodes. Hence all children nodes should report to the header node. Each sensor node will transmit the raw data detected at the environment to the header

600ÂľW 15mW 1mW 1mW 30 and 500 500X500 m2 10W


Number of nodes considered


Area of network




Initial power of each node Time required to send the wakeup signal Power when receiving


Power when transmitting



Power when in wakeup mode Frequency of the wakeup signal Frequency of sending message Time needed for sending a msg+ACK Time needed for sending just a header



Fwu Fmsg Tmsg Thdr


Power dissipated during Sleep Mode Power dissipated when Processing Power dissipated for sending 1 bit of data Power for transmission over a distance d

Value 5 Seconds 1 second


862Hz Variable 21 ms 7 ms


Begin Signal ← Wakeup if (currentData= previousData) Each node can stay in sleep mode for maximum of maxSleepTime only. After completion of this period, the middleware service will send a message called sendWakeUpSignal to wake up the sensor node for regular service. This work has been carried out in MATLAB, and file details are as follows.

Signal ← Sleep return Signal end if count← N

node: We define a class which specifies the properties and initial conditions of a sensor node. create: This program creates nodes and sets timer object. We can set sample time using the timer object and specify the functions (or file) to be executed. We have taken sample time of 1 second for testing purpose. emid: Our algorithm (EMID) is implemented in this file. Here base node processes the raw data received from each node as per the algorithm and sets the flag to each node. Depending on the value of flag base node sends wakeup/sleep signal to the node. This function (file) executes for every sample time and calculations are done. graph: This will plot the graph of energy v/s time for a random node and total energy of system v/s time. Energy level without our algorithm is also plotted for comparison purpose. efficiency: Executing this file will calculate the increase in efficiency.

while(count != 0) if(buff_rawData[count--] = previousData) Signal ← Sleep break end if end while return Signal

Algorithm 1 and 2 demonstrates the above said logic. The energy spent in transmission of a single bit [8] is given by (1)

t ← currentTime;

where et1 is the energy dissipated per bit in the n is the energy transmitter circuitry and ed1xd dissipated for transmission of a single bit over a distance d, n being the path loss exponent (usually 2.0 < n < 4.0). The latency of a (one-hop) message transfer consists of the time needed to send the wakeup signal (Ttone), and the actual transfer time over the primary radio (Tmsg)[3]. This transfer time includes waking up the radio, receiving the message (including headers), and sending back an acknowledge frame. For simplicity, transmission errors and collisions are not considered. Hence retransmissions are not modeled.

if (s[i].t == maxSleepTime) sendWakeUpSignal (s[i] ) break; end if currentData ←s[i]. curData previousData ← unknownValue 23


(2) (3) (4) The average power consumed by a node depends on the frequency at which messages are sent through the network, denoted by Tmsg. Each message transfer adds energy to the basic costs of the wakeup circuitry (Pwu). Receiving the message also takes Tmsg time. We have started experimenting by taking 30 and 500 nodes in each network. We have calculated the time and energy usage by each network as shown in Fig 3 and Fig 4 respectively. The graph shows the statistics of the network by using EMID technique and without using EMID technique. EMID certainly increases the network lifetime by applying sleep and wakeup strategies. In Fig 5, we have randomly selected a node in the network to check the energy level v/s time. By analysing Fig 3, Fig 4 and Fig 5, we have increased the network life time about 5.63% in the network of 30 nodes and 7.19% in the network of 500 nodes , hence EMID is well suited for big size network and/or crowded network.

VI. CONCLUSIONS In this paper, we propose EMID, an energy efficient middleware service for wireless sensor network. The proposed algorithm increases the network lifetime by computing the essence of each node based on the raw information provided by each sensor node in the network. The average percentage energy saved per network is found to be around 5-7%. Thus there is an enhancement of energy management in EMID by applying wakeup and sleep strategies. As a future work, the application layer can also be included by means of the application metrics. REFERENCES

Figure 3. Energy v/s Time for 30 nodes. [1]





[6] Figure 4. Energy v/s Time for 500 nodes [7]



Figure 5. Energy v/s Time for randomly selected node


G. Chen and D. Kotz. Solar: A pervasive-computing infrastructure for context-aware mobile applications. Technical report, Department of Computer Science, Dartmouth College, Hanover, NH, USA, 2002. A. K. Dey, D. Salber, and G. D. Abowd. A conceptual framework and a toolkit for supporting the rapid prototyping of contextaware applications. Human-Computer Interaction, 16:97–166, 2001. B. V. D. Doorn, W. Kavelaars, and K. Langendoen. A prototype low-cost wakeup radio for the 868mhz band. International Journal of Sensor Networks, 5:22– 32, 2009. D. Garlan. Aura: Distraction-free ubiquitous computing. In IFIP International Conference on Engineering for Human-Computer Interaction, pages 1–2, 2001. B. Han, W. Jia, J. Shen, and M.-C. Yuen. Contextawareness in mobile web services. Parallel and Distributed Processing and Applications, 3358:519–528, 2005. V. Joseph, V. Sharma, and U. Mukherji. Optimal sleepwake policies for an energy harvesting sensor node. In IEEE International Conference on Communications, pages 1–6, 2009. J. Mantyjarvi, J. Himberg, P. Kangas, U. Tuomela, and P. Huuskonen. Sensor signal data set for exploring context recognition of mobile devices. In International conference on Pervasive Computing, pages 1–6, 2004. A. Seetharam, A. Acharya, A. Bhattacharyya, and M. K. Naskar. An energy efficient data gathering protocol for wireless sensor networks. Journal of Applied Computer Science, 1:30– 34, 2008 E. Souto, G. Guimar˜aes, G. Vasconcelos, M. Vieira, N. Rosa, and C. Ferraz. A message-oriented middleware for sensor networks. In Workshop on Middleware for pervasive and adhoc computing, pages 127–134, 2004





K.Punitha , Dr. D. Devaraj , Dr. S. Sakthivel Senior Lecturer in EEE Department, Kalasalingam University, 2 Senior Professor in EEE and DEAN/R&D, Kalasalingam University,Tamilnadu, India, Asia. 3 Principal, PSNA college of Engineering and Technology, Dindigul, Tamilnadu, India, Asia. 1

provides sustainable electricity. However, the solar energy produces the dc power, and hence power electronics and control equipment are required to convert DC to AC power. The performance of the power inverter depends on the control strategy

Abstract – Power inverters are used to convert the D.C power produced by the solar photovoltaic cell into AC. This paper presents a novel Adaptive Hysteresis Current Controller to control the inverter, used in the solar photovoltaic cell. The proposed controller is capable of reducing the total harmonic distortion and to provide constant switching frequency. The mathematical model of Photovoltaic array is developed using the Newton’s method using the parameter obtained from a commercial photovoltaic data sheet under variable weather conditions, in which the effect of irradiance and temperature are considered. The modeled Photovoltaic array is interfaced with DC-DC boost converter, AC-DC inverter and load. A DC-DC boost converter is used to step up the input DC voltage of the Photovoltaic array while the DC-AC single-phase inverter converts the input DC comes from boost converter into AC. The performance of the proposed controller of inverter is evaluated through MATLAB-Simulation. The results obtained with the proposed algorithm are compared with those obtained when using conventional fixed hysteresis current controller for single-phase photovoltaic inverter in terms of THD and switching frequency.

adopted to generate the gate pulses. To control the inverters, current control methods are normally used. There are several current control strategies proposed, namely, PI control [11], Average Current Mode Control (ACMC), Sliding Mode Control (SMC) [13] and hysteresis control [3]. Among the various current control techniques, hysteresis control is the most popular one for voltage source inverter [2]. As the photovoltaic arrays are good approximation to a current source, most of photovoltaic inverters are voltage-source inverters. The conventional fixed hysteresis band is very simple, has robust current control performance with good stability; very fast response, an inherent ability to control peak current and easy to implement. But this technique has the disadvantage that the switching

Frequency varies within a band because peak to – peak current ripple is required to be controlled at all points of the fundamental frequency wave [3]. Variable switching frequency has been recognized as solution for motor drive systems to minimize mechanical noise [9], but it is not recommended for power system applications due to generation of sub harmonics and low order harmonics which affect the quality of the power system. In order to solve this problem, in this paper an adaptive hysteresis band controller is proposed. An adaptive hysteresis band controller changes the hysteresis bandwidth as a function of reference compensator current variation to optimize switching frequency and THD of supply current.

Keywords: - Photovoltaic cell, Adaptive hysteresis controller, Boost converter, Inverter.



Many renewable energy technologies today are well developed, reliable and cost competitive with the conventional fuel generators. Among various renewable energy technologies, the solar energy has several advantages like clean, power, unlimited, and 25

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 MATLAB simulations are carried out for modeling solar photovoltaic array based on its mathematical equation and that model is used to interconnect DC to DC converter, proposed Adaptive hysteresis current controlled DC to AC converter and load. The performance of the proposed controller are evaluated by comparing with the results obtained when using conventional fixed hysteresis current

switching frequency.

controller at the point of THD and switching requency.

This paper is organized as follows. Section II, introduces the model of photovoltaic system description, Section III describes the proposed adaptive hysteresis controller. Simulation results and conclusions are presented in the last section. The appendix is devoted to the mathematical modeling technique and basic characteristics simulation results for the photovoltaic cell.


Figure1. Structure of Photovoltaic System III.

Proposed Adaptive Hysteresis Current Controller Design

The inverters used for photovoltaic energy generators are classified as voltage-source inverter (VSI) and current-source inverter (CSI). Each type of the inverters can be subdivided based on the control schemes; which are voltage-control inverter (VCI) and current-control inverter (CCI). In the voltage-source inverters, a capacitor is connected in parallel with the dc input. In the current source inverters, on the contrary, an inductor is connected in series with the dc input. Photovoltaic arrays are fairy good approximation to a current source. However, most of photovoltaic inverters are voltage-source inverters. The performance of inverter mainly depends on the control strategy adopted to generate the gate pulses. The dynamic responses of the system are controlled by the current controllers. Among the various current control techniques, hysteresis control is the most popular one for voltage source inverter. The basic structure of single phase inverter with hysteresis controller is shown in Figure 2.

Photovoltaic System Description

Figure 1 shows the block diagram of a photovoltaic system, which includes solar photovoltaic panel with DC to DC converter, Single phase inverter and load. The solar photovoltaic panel produces electricity when the photons of the sun light strike on the photovoltaic cell array. The output of the photovoltaic panel is directly connected to the DC to DC boost converter to step up the DC output of photovoltaic panel. Then it is fed to an inverter which converts DC into AC power at the desired voltage and frequency. A current controller is normally preferred due to its advantages like flexibility-modify easily through of software, simplicity-possible implementation in fixed point computation etc. The main task of the control systems in current controlled inverters is to force the current of single phase load according to a reference signal. There are many current control techniques in the literature as mentioned in the Introduction. The simplest current control technique is hysteresis current control technique. The actual value of the output current is controlled in order to remain in a defined area. This method is fast and simple and provides good results. The only problem is the variable switching frequency of the semiconductor switches that is a direct consequence of this control strategy. An adaptive hysteresis current controller is proposed in this paper for the control of inverter to obtain the better result in terms of less total harmonic distortion and constant 26


Fig. 3 Traditional Hysteresis current Controller

The fixed hysteresis band technique is very Figure 2 Single phase inverter

simple, has robust current control performance with good stability; very fast response, inherent ability to control peak current and easy to implement. The

The principle of hysteresis current control is very simple. The purpose of the current controller is to control the load current by forcing it to follow a reference one. It is achieved by the switching action of the inverter by forcing it to follow a reference one. It is achieved by the switching action of the inverter to keep the current within the hysteresis band. The load currents are sensed and compared with respective command currents by hysteresis comparators having a hysteresis band “HB”. The output signal of the comparator is used to activate the inverter power switches. The switching logic for an inverter is given below:

technique does not need any information about system parameters. But, this method has the drawbacks of variable switching frequency, heavy interference, harmonic content around switching side band and irregularity of the modulation pulse position [7]. These drawbacks result in high current ripples and acoustic noise. To overcome these undesirable drawbacks,






hysteresis band control [3, 5]. The proposed adaptive hysteresis band controller adjust the hysteresis band width, according to the load current. The concept of adaptive hysteresis controller is shown in figure 4

If IL < (IL –HB), the switch Ta+ and Tb- are turned OFF (Ta- and Tb+ are turned ON). If IL > (IL + HB), the switch Ta- and Tb+ are turned OFF (Ta+ and Tbare turned ON).The switching function can be seen in Figure 3 below,

where derivative of the load current and the reference current determines the switching time and frequency.

Figure4a. Adaptive Hysteresis Current Controller concept


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 During the current in increasing and decreasing state of the inverter in fig. 4b the following equations can be established.The equation (17) defines the hysteresis band that depends on the system parameters. By substituting the switching frequency we can get the hysteresis band value. Adaptive hysteresis band method allows operating at nearly constant frequencyand is usually performed by software using the system parameters.



Table I – Electrical characteristics of solar photovoltaic module

Simulation Result

Maximum Power

Computer simulation of Photovoltaic system has been carried out using Matlab/Simulink. The performance measurement includes total harmonic distortion (THD) level of load currents and switching frequency. The system consists of solar photovoltaic module, DC-DC converter, DC-AC inverter and RL load. The photovoltaic module generates the DC voltage from solar temperature and irradiation.

A photovoltaic array has been modeled. It consists of 32x1 monocrystalline silicon solar cells each one, connected in series and parallel. Each module can produce DC electrical power. To let the interaction between a DC/DC converter and photovoltaic array, a simulation model for a photovoltaic array has been developed, with the provision of variable irradiance and temperature input. The model was implemented in simulink, helped by the SimPowerSystem block set based on its equivalent circuit (Figure 5) and the electrical characteristics of the photovoltaic module given by datasheet are shown in Table I [1].

40 W

Maximum Voltage

17.3 V

Maximum current

3.31 A

Short-circuit current

3.54 A

Open-circuit voltage

21.8 V

Temperature coefficient


Figures 6(a) and 6(b) show the voltage- current and voltage- power output characteristics of a photovoltaic array model for different solar isolation with 0 temperature of 25 C.



Figure 6a.Current Vs Voltage at Irradiant G= 1 W/m , 2 2 2 2 0.8W/m , 0.6W/m ,0.4W/m ,.2W/m

Figure 5. Equivalent circuit of a photovoltaic cell


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 used in experiment using Matlab/simulink . The results in table III shows that the average switching frequncy and the percentage THD values of load current for different techniques which shows the switching frequency is minimum and THD has decreased for the proposed technique compared with other techniques.

Figure 6b .Power Vs Voltage at Irradiant G= 2 2 2 2 1W/m,0.8W/m ,0.6W/m ,0.4W/m , .2W/m

Processing the energy obtained from the solar photovoltaic module is coming to the fore. The energy supplied by the module does not have constant values, but fluctuates according to the surrounding condition such as intensity of solar rays and temperature shown in the characteristics curves in fig. 6a and 6b. These supplies are therefore supplemented by additional converters. Here the solar photovoltaic system composed of a DC to DC converter and an inverter. The DC to DC boost converter is used to step up the solar photovoltaic module output and the proposed adaptive hysteresis current controlled inverter is used to produce the output in such a way that the current has low total harmonic distortion and it is in constant switching frequency. For comparison the inverter was controlled using sinusoidal PWM and fixed hysteresis current control techniques. The load current wave forms, its harmonic spectrum and it switching frequency using general sinusoidal pulse width modulation are shown in fig. 7. The total harmonic distortion (THD) in this case is 4.5%. It can be seen in fig7b, the switching frequency is variable over a wide frequency range. Figures.8 shows that the source harmonic current in the case of fixed hysteresis band. Here the THD has decreased from 4.5% to shown in fig. 8b.

Figure 7a. Input Voltage,Current, Output Voltage and Current of photovoltaic inverter Sinusoidal PWM

Figure 7b. Switching frequncy of photovoltaic inverter Sinusoidal PWM

The system was connected with an adaptive hysteresis band current controller. The figure 9 shows the performance of the system with the adaptive control scheme. The performance of the proposed control algorithm is found to be excellent. The THD in this case is 3.29% as shown in fig. 9b. In this case modulation frequency is maintained constant at 10KHz.

Figure 7c. Switching frequncy of photovoltaic inverter Sinusoidal PWM

The table II shows the system parameters 30


Figure 8a. Output Current of photovoltaic inverter with fixed hysteresis controller

Figure 9a. Output Current of photovoltaic inverter with Adaptive hysteresis controller

Figure 8b. THD level of Fixed Hysteresis controller of photovoltaic inverter Figure 9b. THD level of Adaptive ysteresis controller of photovoltaic inverter

Figure 8c. Switching Frequency of Fixed Hysteresis controller of photovoltaic inverter Figure 9c. Switching Frequency of Adaptive Hysteresis controller of photovoltaic inverter



Load Resistance

Load Inductance

Conclusion An adaptive hysteresis current control technique for single phase photovoltaic inverter has been presented in this paper. The adaptive hysteresis current controller has fast response and it keeps the switching frequency nearly constant with the harmonic content of the load within the limit. The effectiveness of the proposed adaptive hysteresis current controller has been demonstrated through the results of the simulation in MATLAB/Simulink. Simulation was also conducted with fixed hysteresis controller and their performance and THD of load current has been shown. Based on the simulation results it can be concluded that the adaptive hysteresis current controller results in constant switching frequency and limited harmonic content and is suitable for Photovoltaic system.


Reference current

10 sin (2π50)

Fixed band width HB


Dc link capacitors

5 X 10 F



9 X 10 F V. Table II – System Parameter

TH D %

Current control

Adaptive Hysteresis

1] Paquin, J.-N. and Turcotte, D., “PV Inverter Modelling for Power Quality Studies”, # CETC 2007-202 (TR), CANMET Energy Technology Centre – Varennes, Natural Resources Canada, November 2007, pp.76. 2] Anushuman Shukla, Arindam Ghosh and Ainash Joshi,” Hysteresis current control operation of Flying Capacitor Multilevel Inverter and its Application in Shunt Compensation of Distribution System” IEEE Trans on Power Delivery, Vol 22, No.1, Jan 2007, pp. 396-405.

Average switching frequency

Technique 3.29




3] P. Rathika and Dr. D. Devaraj,” Fuzzy Logic – Based Approach for Adaptive Hysteresis Band and DC Voltage Control in Shunt Active Filter”, International Journal of Comuter and Electrical Engineering, Vol. 2, No. 3, June 2010, pp. 1793-8163.


Fixed Hysteresis

4] M.P.Kazmierkowaski, L.Malesani: “PWM Current Control Techniques of voltage source converters-A Survey” IEEE. Trans. On Industrial Electronics, Vol.45, No.5, Oct.1998, pp.691-703.


Sinusoidal PWM



5] Bimal K. Bose. “An adaptive hysteresis-band current control technique of a voltage-fed PWM inverter for machine drives system.” IEEE Trans. on Industrial Electronics, Vol.37,No.5, October 1990, pp. 402-408.


6] S.R.Bowes, S.Grewal, D.Holliday, “Novel adaptive hysteresis band modulation strategy for three-phase inverters” IEE Proc. Power Application., Vol. 148, No. 1, January 2001, pp. 51-61.

Table III - Results of Various Techniques

7] Yu Quin, Shanshan Du. “A novel adaptive hysteresis band current control using a DSP for a power factor corrected on-line UPS.” IEEE Trans. On Industrial Electronics, pp. 208-212. 8] T.G.Habetler and D.M.Divan, "Acoustic noise reduction in sinusoidal PWM drives using a randomly modulated 32

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 carrier, "IEEE Trans. on Power Electronics,Vol.6, May 1991 pp. 356-363. 9] Zare, Firuz and Zabihi, Sasan and Ledwich, Gerard F., “An adaptive hysteresis current control for a multilevel inverter used in an active power filter”. In Proceedings of European Conference on Power Electronics and Applications, Aalborg, Denmark, Sept. 2007, pp. 1-8. 10] M.Azizur Rahman, Ali M. Osheiba. “Analysis of current controllers for voltage-source inverter” IEEE Transaction on industrial electronics, Vol.44, no.4, Aug-1997, pp.477485. 11] Hongbin Wu, Xiaofeng Tao. “Three Phase Photovoltaic Gird-Connected Generation Technology with MPPT Function and Voltage Control” in Proceedings of International Conference on Power Electronics and Drive Systems PEDC 2009, Nov. 2009, pp. 1295-1300. 12] Gerardo Vazquez, Pedro Rodriguez, Rafael Ordones Tamas Kerekes and Remus Teodorescu, “Adaptive Hysteresis Band Current Control for Transformerless st Single-Phase pv Inverter”, in proceeding of 31 Annual Conference on Industrial Electronics IECON 2009, Nov. 2009, pp. 173-177. 13] Shih-Liang Jung, Ying-Yu Tzou, “Discrete Sliding –mode control of a PWM inverter forsinusoidal output waveform synthesis with optimal sliding curve”, IEEE Transaction on Power Electronics, Vol. 11, No. 4, july 1996, pp. 567-577. 14] S. Buso, L. Malesani, P. Mattavelli, "Comparison of Current Control Techniques for Active Filter Applications", IEEE Transaction on Industrial Electronics, Vol. 45, No.5, October 1998., pp.722-729. 15]

M. Kazmierkowsi, L.Malesani, “Current Control Techniques for Three Phase Voltage Source PWM converters: A survey”, IEEE Trans on Industrial Electronics, vol.45, no.5, pp.691- 703, October 1998.

16] Malesani, L., Tenti, P., “A novel hysteresis control method for current-controlled voltage-source PWM inverters with constant modulation frequency”, IEEE Transaction on Industry Application, Vol. 26, No. 1, Jan/ Feb 1990, pp. 88-92.






Chandrashekhar P K , Shanta Rangaswamy , Ashwin Srigiri #1 M.Tech, CSE, RVCE , Bangalore, India Assistant Professor, RVCE , Bangalore, India Software Engineer, Cisco Systems , Bangalore,India Abstractâ&#x20AC;&#x201D;Every project delivery involves significant amount of repeatable and replicable work, for example Customer Requirement Document(CRD), High Level Design(HLD), Low Level Design(LLD), Network Implementation Plan(NIP) and Network Ready For Use(NRFU) documentation. Repeatable work constitutes over 20% of the total transactional project efforts. Depending on the Service Contract the individual Network Consulting Engineer (NCE) may be responsible for network Prepare, Planning, Design, Implementation, Operation and Optimization (PPDIOO) [1]. This may include remote or onsite: infrastructure design, implementation planning, proofof-concept testing, network auditing/sizing, preconfiguration, deployment planning and acceptance of product in execution or advisory/assistance or support models. For this there is a large potential for automating the low intellect works and to provide more bandwidth for NCE for high value work [2]. Since NCE works in all the phases of the project documentation there is a need for end to end flow of huge amount of information without any errors. There is a need to automate the generation of dynamic contents and to replicate the contents in all phase documents. The main intention is to reduce NCE hours for an organizational benefit. The aim of this paper is to introduce an innovative Plan Design Implement tool. The tool uses the business intelligence to auto generate the dynamic contents in the CRD, HLD, LLD and NIP documents.

for the document generation and so much of the work is being replicated and the information collected in one phase is not being reused in the next phase. The existing systems are template dependent. Plan Design Implement Tool is the complete framework that covers all the phases of project lifecycle. The look and feel of the Plan Design Implement Tool is better than the existing systems. Currently the customer requirement collection, High level design and Network planning are being done manually by the network consulting engineer which consumes 20% of the overall project efforts. Plan Design Implement (PDI) Tool creates rule-based logic to auto-generate dynamic content in these documents. There is a large potential for automating such tasks resulting in significant benefits to an organization. PDI Tool is envisaged as a tool which will allow NCE to create all these documents in 30% to 50% less time than current thresholds [2]. The PDI tool mainly targets at productivity savings such as reduction in NCE hours, potential annual cost savings and margin improvement. PDI Automation eliminates the possibility of manual errors while working on voluminous information. It relieves NCE of de-motivating tedious and low-intellect work and provides more bandwidth to NCE to focus on highvalue work like design, consultancy and advisory and technical development. Templates are the place holders for the contents collected by the tool. These are used as base templates for all the deliverables. NCEs of any grades are expected to generate standard project documents using the templates and develop comprehensive test plans. NCEs will execute all phases of project delivery.

Keywords-customer requirement document; intellect; template; Implementation plan; network ready for use;

INTRODUCTION The primary goal of the PDI Tool is to automate the creation of dynamic content in Customer Requirement Document, High Level Design document, Low Level Design document and other documents and to automate the replication of content across multiple documents. It is also aimed to create rule-based logic to auto-generate dynamic content in all the documents. Currently there are applications for low level design tool for specific domain which generate the low level design document but not cover any other phases like customer requirements, high level design and network implementation [4]. The current state challenge is different teams will be using different templates


Cisco uses a methodology known as PPDIOO as part of designing networks. PPDIOO is an acronym that describes some of the major elements in a network design process, namely: prepare, plan, design, implement, operate, optimize. As shown in the fig 1, the PPDIOO lifecycle phases are separate, yet closely related [1]. Following are the six phases of project lifecycle which the tool is considering:


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 The Fig 1 depicts the organizational PPDIOO lifecycle. The cycle starts with prepare phase and ends with optimize phase. All the projects follow the same life cycle.

Prepare Phase: Business agility starts with preparation: anticipating the broad vision, requirements, and technologies needed to build and sustain a competitive advantage. Plan Phase: Successful technology deployment depends on an accurate assessment of companyâ&#x20AC;&#x2122;s current network, security state, and overall readiness to support the proposed solution. The company then develops a detailed project plan to identify resources, potential difficulties[5], individual responsibilities, and critical tasks necessary to deliver the final project on time and on budget. Design Phase: Developing a detailed design is essential to reducing risk, delays, and the total cost of network deployments. The design phase can also guide and accelerate successful implementation with a plan to stage, configure, test, and validate network operations. Implement Phase: A network is essential to any successful organization, and it must deliver vital services without disruption. In the implement phase, a company works to integrate devices and new capabilities in accordance with the design without compromising network availability or performance [6]. After identifying and resolving potential problems, the company attempts to speed return on investment with an efficient migration and successful implementation including installing, configuring, integrating, testing, and commissioning all systems.

Operate Phase: Network operations represent a significant portion of IT budgets, so it is important to be able to reduce operating expenses while continually enhancing performance. Throughout the operate phase, a company proactively monitors the health and vital signs of the network to improve service quality; reduce disruptions; mitigate outages; and maintain high availability, reliability, and security. By providing an efficient framework and operational tools to respond to problems, a company can avoid costly downtime and business interruption. Expert operations also allow an organization to accommodate upgrades, moves, additions, and changes while effectively reducing operating costs. Optimize Phase: A good business never stops looking for a competitive advantage. As an organization looks to optimize its network and prepares to adapt to changing needs, the lifecycle begins a new continually evolving the network and improving results.

CURRENT CHALLENGES Studies on networks have shown that misconfigurations are common and can significantly affect the correct operations of networks. Manual configuration changes, while time-consuming and error-prone, is extremely common. This suffers from various disadvantages. So the networking projects should have proper documentation. This documentation should maintain consistency throughout the project lifecycle. This documentation will be voluminous in large organizations. Currently there are no tools to help the NCE in this regard. Following are the major challenges on which the to be developed tool targets:   

Template independence Requirement traceability Individual template upload

The tool should provide the flexibility for an individual to upload his own template. It also should maintain the data consistency throughout the project lifecycle like CRD, HLD, LLD, NIP and NRFU [2]. Template independence is the main focus since different NCE uses different templates for documentation of different projects. Fig 2 shows the NCE roles. Following are the roles and responsibilities of an NCE:

Fig. 1 PPDIOO life cycle



and customer interest. This level produces the xml or world document which contains all the information collected by the customer. This Planning and Design Questionnaire is used to collect information from the customer for a network project. The information in this document is required for the planning, design and implementation of the project and will be also used by the organization as the input to the project Low Level Design (LLD). It should be noted that every project is different, even if based on the same solution. This document should be modified for each customer as appropriate and information may need to be added or removed. This document may also need to be modified during the low level design phase as new requirements are brought to light during the design process.

Performs analysis, design and diagnosis of most complex networking problems. Acts as the technical specialist for the most complex deployments. Identifies skills and business shortfalls and establishes programs to address them. Collaborates proactively with other NCEs to ensure optimal use of resources to meet customer needs. Produce reusable Intellectual collateral, share and re-use stored collateral and leading practices documentation.

High Level Design Tool

The HLD phase tool takes the input from the Card’s output. The input can also be given directly. The purpose of this phase is to identify the detailed requirements needed to develop a High Level Design. The output of HLD is the world document or xml document. This document is intended for organizations Engineers who are responsible for the design and implementation of a new solution. The information requested in this document should be obtained from the customer during the discovery & analysis phase of the engagement. The document focuses on the overall topology and features/services provided by the solution. The document starts by describing the various design requirements for the network project infrastructure at customer site. The document then provides an overview of the design, including the logical topology and traffic flows.

Fig. 2 Poles and Responsibilites of NCE


Low Level Design The Solution for the current state challenges is to develop a Plan Design Implement Tool. The Plan Design Implement Tool targets at the above mentioned challenges. The PDI Tool concentrates on template independent document generation which adds the innovative idea. Thus the Plan Design Implement Tool relieves this burden of NCEs and provides impressive and interactive look and feel user interface to the user. The tool provides interesting options based on the requirements. The tool requires CEC authentication to use it.

Input to LLD phase Tool is Held’s output. The input can also be given directly if the user wishes to add. The document has separate sections on the network architecture – physical and logical topology, device naming, etc. and on Network Services running on the Network. This document will provide configuration templates that can be used to derive actual configurations for use in the forthcoming deployment/ migration phases of the deployment. The output of LLD is the world document or xml document. The output of HLD is given as the input to the NIP. This document aims to cover all areas necessary to build and deploy the network infrastructure. The document begins by providing a brief overview of the project, including the scope and high-level project schedule. The scalability and limitations of the proposed design are described next, focusing on both network and application Services components of the solution. Considerations for future services and features are also discussed in this section. Finally, software recommendations for the relevant network components (specific to transparent interception) and application Services software are provided. These recommendations serve as the minimum software versions required to successfully deploy the proposed solution. The information in this document is based on data collected through meetings, interviews, documentation, and other

PDI TOOL PHASES Each phase of the PDI tool itself is a tool which performs the phase specific tasks. There are five phases of PDI tool. Customer Requirement Document Tool

The CRD is the planning phase tool that collects the information from the customer by providing great flexibility to them. To collect information the domain specific questions can be triggered based on the specific domain


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 information provided by customer. Manual entry of this huge data is difficult. PDI tool automates the data collection and report generation. The following Fig 3 shows an example of LLD.

Fig. 4 Example for Network Implementation Plan

Fig. 3 Example for Low Level Design Network Implementation Plan

The purpose of the Standard Tests in this document is to assess the overall functionality of the network as a single entity and of the implemented services that will be operational at the time of hand-over. The primary aim of these tests is to show the reliability and resilience of the network and thereby deeming the network ready to carry live traffic.

The NIP phase tool takes the input from the output of the LLD and generates the configuration that can be applied on the real machine. NIP is the implementation phase document. This document is intended for use by projects design, implementation and support teams, partner implementation and support teams as well as the organizations design and implementation teams [2]. This document describes the Network Implementation Plan of the deliverable. Fig 4 shows an example for NIP.



It very important for any Organization to monitor analysis, design, implementation configuration and NRFU test result documentation. The documents must be Policy compliant and follow a template. Regularly retaining the compliance of the documentation even after changes have been made can effectively reduce the issues raised by the customers. The template compliance can be achieved by uploading required templates. In order to maintain the accuracy and consistency effectively the following functions must be met by the PDItool:

Network Ready For Use

The purpose of this document is to define and record the specific actions that are necessary to test the Customer network and to declare that it is ready for use. The Network Ready For Use (NRFU) tests will demonstrate that the network equipment has been correctly configured and that the network will operate in a manner that will enable customer to accept it as a working system and proceed with the process of adding production connectivity and traffic. The network ready for use is very important phase of the project life cycle since it checks all the requirements. If all the test cases are passes then the network is ready to use. The documentation contains test numbers, description and the test results.



The PDI Tool shall be able to consider all the domains of organization. It shall generate detailed report on dynamic contents after each stage of the tool. Shall support all the NCEs and provide good performance. The PDI Tool provides the function of template compliance jobs.





This project would follow Water Fall Approach since requirements will not change during the development and requirements are well understood. This would enable the product to be built using water fall approach. The most important aspect of the waterfall model is that none of the stages can be started off with before the preceding stage is completed. The software life cycle has to follow the sequence - Specification of Requirements, Design, Construction, Integration, Testing and Debugging, Installation and Maintenance. There are five phases in this project CRD, HLD, LLD, NIP and NRFU. The output of previous phase is given as input to the next phase. This is the heart of PDI framework. That is, for example, the output of the CRD is given as input to the HLD and the output of the HLD is given as input to the LLD. Fig 5 shows the overall framework [2]. In each phase the details are added. This process continues throughout the development.

Fig. 5 Overall PDI Framework The application is developed using Spring Framework. The Spring Framework is an open source application framework for the Java platform. The core features of the Spring Framework can be used by any Java application, but there are extensions for building web applications on top of the Java EE platform. Although the Spring Framework does not impose any specific programming model, it has become popular in the Java community as an alternative to, replacement for, or even addition to the Enterprise JavaBeans (EJB) model. Central to the Spring Framework is its Inversion of Control container, which provides a consistent means of configuring and managing Java objects using callbacks. Decoupling or loose coupling between the classes is another important feature of Spring MVC [3]. Fig 6 shows the single user interface for complete PDI framework so that user can jump to any phase directly [2].

Customer Requirement Document

Interview Q&A Readiness Assessment







“What are routing requirements?”


High Level Design

Fig. 6 Common User Interface for PDI Tool Infrastructure and topology design


“Single area OSPF design”

The PDI Framework can be modularized into following modules. These module appears in almost all five phases of the PDI tool. The user logs on to the system using the credentials and user can perform the functionalities for which he is entitled for. Admin users will have the authorization to register the users to the system and give appropriate access rights to the registered user. The Fig 7 shows the complete low level design of the PDI Tool.

Low Level Design

Technology deep-dive, sizing, best practices

“OSPF detailed explaination, area ID, recommendations”

Capture: The Capture component in the PDI will provide UI to the user to create a new document by giving project title and selecting the template type and giving values for metadata. This will provide Rich Text Editor to the user. System validates the various inputs

……………………………………………………………… Acceptance test casesImplementation “Site specific test cases” Network Plan Detailed implementation steps and configs per site

“Site specific OSPF design and configs”

Network Ready For Use


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 Design Implement tool reduces 30% of the NCE hours on the project. The tool also provides requirement traceability which performs the replication of contents across the multiple documents automatically. Hence this great flexibility and advanced features of the PDI tool makes the PDI tool as the NCEs basic need in the future.

like project title, type, content, recommendation, NCE type etc., for the successful creation of document. It provides the user a flexible way to upload, add/edit data. The captured requirement can be saved, edited and sent to next phase of development.

ACKNOWLEDGEMENT Student’s work is incomplete until they thank the almighty & his teachers. I sincerely believe in this and would like to thank Dr. N. K. Srinath, Head of the Department, Computer Science & Engineering, RVCE, Bangalore for his encouragement and motivation to write this paper. Also I am grateful to Dr. G. Shobha, Dean, PG-Studies (CSE-ISE), RVCE, Bangalore for guiding me in writing this paper. I also thank my manager Robin Jose, Cisco Systems for providing resources and constant support to accomplish this paper.

Fig. 7 System Architecture Search: The Search component of PDI framework will search the previously generate documents based on the user name or project name provided by the user and lists the fetched documents. User can use this search option to find the required document. View: The View component of PDI framework will be invoked by the results page of Search component of the PDI Download: The download component of PDI framework will be invoked by the results page of Search component of the PDI framework, which will allow the user to download the full reports. Admin: Allows the admin to manage the hierarchical questionnaire. The Admin can add the questions at any level. The questionnaire should propagate throughout the framework.

REFERENCES [1] “Creating Business Value And Operational Excellence With the Cisco Systems Lifecycle Services Approach”, white paper [2] Gaurav Garg, Robin Jose “Business Case Review” [3] By Ken Williamson “Starting Spring MVC Tutorial Part 1 of Tutorial Set, [4] “Wide Area Application Service for sizing the network”, Version 1.2, October 8, 2010, [5] “Cisco Advanced Services for the PACE Solution”

CONCLUSION PDI tool reduces the NCEs effort in the voluminous document creation. Errors and redundant data can be eliminated. The NCE can concentrate on the high value work with more bandwidth without worrying about the low intellect work. The tool also provides template independence flexibility feature to the NCE thus any category NCE can use the tool independent of the tool. Plan


Fabio Semperboni , “ The PPDIOO Network Life

Cycle” hitePaper.pdf






Vijaya Lakshmi V, Nadimpalli and Raghavendra Rao,Chillarige * ACRHEM and Department of Computer and Information Sciences University of Hyderabad, Hyderabad 500 046

Abstract- In this paper we propose a learning based

Secant method uses a succession of roots of secant lines to better approximate a root of a function f(x). The Secant method does not require that the root remain bracketed like the Bisection method, and hence it does not always converge but reduces computational time.

iterative numerical method for computing a root ξ of a non-linear equation of the form f(x) = 0 in the interval [a,b]. Lag based method through Hermite interpolation modeled root discovery approach is developed and demonstrated in this paper. The new method has been tested for a series of functions considered by several researchers. The numerical experiments show that the new method is effective and converges faster to a root with lesser number of iterations and lesser number of function evaluations.

The classical Regula falsi method finds a simple root of the nonlinear equation f(x)=0 by repeated linear interpolation between the two current bracketing estimates. Regula falsi method combines features from the Bisection method and the Secant method, here sign as well as magnitude is used. If the initial end points a and b are chosen such that f(a) and f(b) are of opposite signs, then this assumption guarantees the existence of a zero of f(x) in the interval [a,b]. This means that the Regula falsi method always converges. In Regula falsi method, at every iteration one point is dropped, the information available at points which are dropped recently can be used for approximating the function with better accuracy. This enhances the knowledge in the current support about the function.

Keywords- Bisection; Secant; Regula falsi; Newton; Steffensen’s; nonlinear equations; root finding; order of convergence; Hermite interpolation; iteration method

1. Introduction

Intelligent searching strategies will enhance the performance and efficiency of an iterative numerical method for solving a nonlinear equation f(x)=0.

Alefeld and Potra [1,2] proposed three efficient methods for enclosing a simple zero ξ of a

If f is a continuous function on the interval [a,b], the Bisection method converges to a root of f, which repeatedly bisects an interval, then selects a subinterval in which a root must lie for further processing. This is called a bracket of a root and this method is not constrained by any other parameter other than sign. So, this method is relatively slow.

continuous function f(x) in the interval [a,b], provided that f(a) f(b)< 0. Starting with the initial enclosing interval [a1,b1] = [a,b], this method fits a quadratic polynomial to produce a sequence of intervals such ∞

that {(bn − an )}n=1 ξ ∈ [a n+1 ,bn+1 ] ⊆ [a n ,b n ] ⊆ .... ⊆ [a1 , b1 ] ⊆ [a, b] . lim(bn − an ) = 0 n →∞


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 In a subsequent study by Frontini [6], a numerically comparable method through fitting a Hermite interpolating polynomial was suggested. Here in this method, by taking x0 = a and x1 =b as the starting points, with f(x0)f(x1)< 0, then xi+1 is taken as the root of Hermite polynomial P2[f,xi−1,xi](x) which belongs to (xi−1,xi). Use of the dichotomy condition f(xi-1)f(xi) < 0 ensures the existence of at least one root of P2[f, xi−1, xi](x) belonging to (xi−1,xi) because of the continuity of P2[f, xi−1, xi](x). The author further suggested in a similar manner fitting a cubic Hermite polynomial P3[f, xi−1, xi](x) and a generalized method satisfying the interpolation conditions: P2 n −1 [ f , a , b]( a ) = f

(k )

(k )

(a )

(k ) P2 n −1 [

(k )

(b )

f , a , b](b ) = f

distinct points, their function values and the values of their corresponding first derivatives. Hermite Interpolating Polynomial: The Hermite interpolating polynomial interpolates not only the function f(x), but also first order derivatives at a given set of data points ( xi , f ( xi ), f '( xi )) , i=0,1,2,…n. The Hermite interpolating polynomial is given by n 2 ' H 2 n+1 ( x ) = ∑ 1 − 2( x − xi )li ( xi ) li ( x )  f ( xi )  i =0  n + ∑ ( x − xi )[li ( x )]2 f ' ( xi ) i =0


Where k =1,2...n −1→(1)

By considering xn+1 as the root

li ( x ) =

ξ of Hermite

interpolating polynomial P2n-1[f, xn−1, xn](x) belonging to (xi−1,xi), the order of convergence of the iterative method obtained in [6] is given as

( x − x0 )( x − x1 )...( x − xi −1 )( x − xi +1 )...( x − xn ) ( xi − x0 )( xi − x1 )...( xi − xi −1 )( xi − xi +1 )...( xi − xn )

We now consider fifth degree Hermite interpolating polynomial passing through the points ( xi , f ( xi ), f '( xi )) , i=0,1,2 by putting n=2 in (2).



n + n + 4n

. Frontini [6] proposed that his 2 method works effectively only for fitting a cubic Hermite polynomial.


f _ hermite( xi , f ( xi ), f '( xi )) xi = [ a , c, b ]

Based on the earlier methods which emphasize as memory based learning [1,2] and with reinforced learning by making use of derivative through Hermite interpolation as lag based learning [6], in this paper we attempt to propose an iterative method as follows.

f ( xi ) = [ f ( a ), f (c ), f (b)] f '( xi ) = [ f '( a ), f '( c), f '(b )] xr =root of H5(x)

2. The new method

Algorithm 1. Set a=lower bound for search, b=upper bound for search such that f(a)f (b) < 0,find a point c such that a < c < b . Obtain corresponding f '( a ), f '(b ), f '( c ) .

Hermite interpolation is an extension of basic polynomial interpolation that not only matches discrete information at a set of points, but also matches the slope (or rate of change) at those points.

2. Call f _ hermite( xi , f ( xi ), f '( xi )) which returns five roots of fifth degree Hermite polynomial.

We consider x0 = a and x1 =b as the starting points, with f(x0)f (x1) < 0, a point c is taken as a<c<b. A fifth degree Hermite polynomial is fit for these three


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 3. From the above five roots select the root (say xr) which lies in the interval [a,b] and for which function value f(xr) is minimum.

Then by constructing a function F(x) such that

F ( x ) = f ( x ) − φn ( x ) − Lπ n +1 ( x ) and the constant L can be determined so that

4. Obtain f(xr) if f ( xr ) <∈ , then display root= xr

L =

5. Compute f '( xr )

(ξ )

( n + 1) !

H en ce



E ( x) = f ( x) − φn ( x)

6. If f ( a ) f ( xr ) < 0 , then


π n +1 ( x ) f

( n + 1)

( ξ ), x 0 < ξ < x n

c = b , f ( c ) = f (b ), f '( c ) = f '(b )


a = a, b = xr , f (b ) = f ( xr ), f '(b ) = f '( xr )

Now, we consider Hermite interpolating polynomial

( n + 1) !

H2n+1(x), then error E ( x ) = f ( x ) − H 2 n +1 ( x ) can be

f (b ) f ( xr ) < 0 , then


( n + 1)


obtained. Here we notice that both E(x) and

c = a , f ( c ) = f ( a ), f '( c ) = f '( a )

[π n +1 ( x )] vanish together with the first derivatives at

a = xr , b = b, f ( a ) = f ( xr ), f '( a ) = f '( xr )

each of (n+1) points. We then form a linear combination of these functions


Repeat step 2 until | f ( x) |<∈ .

F ( x) = f ( x ) − H 2 n +1 ( x ) − L[π n +1 ( x )]


In each iteration, the information about the point to be dropped is stored and used as lag, (always third point in new method is lag) to fit fifth degree Hermite interpolating polynomial, hence we need only two function evaluations at each iteration which improves the efficiency of the method.



E(x) = f (x) − H2n+1(x) =

(2n + 2)!



(ξ) →(3)

Where f(x) is assumed to have continuous derivatives of order (2n+2) and ξ = ξ ( x ) is in the interval determined by the points x,x0,…,xn . 6

Theorem: Let f ∈ C , at least in a neighborhood of α,

3. The order of convergence

with f (α) = 0. Let {xn} be the sequence defined as

xn +1 = ξ , where ξ is the root of fifth degree Hermite Let the function f(x) defined by (n+1) points (xi,f(xi)), i=0,1,2,…n, be continuous and differentiable (n+1) times and let f(x) be approximated by a

polynomial enhanced by the dichotomy procedure so

polynomial φn ( x ) of degree not exceeding n such that

error of the nth iterate. Then, ∈n +1 |~ M |∈n |

that it converges to α with n. Let ∈n = xn − α be the where

M is a positive constant. Proof

φn ( xi ) = f ( xi ) , i=0,1,2...n, then error is given by

Without loss of generality we assume

that xn − 2 < xn −1 < xn .

E ( x ) = f ( x ) − φn ( x )

There exists η ∈] xn − 2, xn [ such that

= π n +1 ( x ) f [ x0, x1 , .. xn ] = π n +1 ( x ) L where


π n +1 ( x ) = ( x − x0 ) ( x − x1 )...( x − xn )


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 E(α ) = f (α ) − H5[ f , xn−2, xn−1, xn ](α ) (α − xn−2 ) (α − xn−1) (α − xn ) 2




This asymptotic equation is satisfied if p is the positive root of f



is zero of


2 2 p = + 2 + 2p p

3 2 p − 2p − 2p − 2 = 0

p = 2.9196


(η) → (4)

H 5 [ f , xn − 2 , xn −1 , xn ]( xn +1 ) in

] xn − 2 , xn [ , then then, ∈n +1 |~ M |∈n |2..9196 for a suitable constant M.

H 5 [ f , xn − 2, xn −1, xn ]( xn +1 ) = 0 = f (α ) By replacing f (α ) with

It is proved in the above theorem that the new method converges to a root of f(x) with rate of convergence 2.9196. Given three distinct points we obtain their function values and the values of first derivatives corresponding to these three points before starting the first iteration. Consecutively we need only two function evaluations at each iteration as lag based intelligent searching strategy is used which improves the Efficiency Index, given by

H 5 [ f , xn − 2 , xn −1 , xn ]( xn +1 ) in

(4), we get H 5 [ f , xn− 2 , xn−1 , xn ]( xn +1 ) − H 5 [ f , xn− 2 , xn−1 , xn ](α ) =

(α − xn− 2 )2 (α − xn−1 ) 2 (α − xn )2 (6) f (η ) 6!

By Lagrange’s theorem, there exists ξ ∈]α , xn +1[ such


EI = (2.9196) 2


= H5[ f , xn−2,xn−1,xn](xn+1) − H5[ f , xn−2,xn−1, xn](α) →(5)





(α − xn +1 ) = K (α − xn − 2 ) (α − xn −1 ) (α − xn ) 2





( 6)

(η )


6! H 5 [ f , xn − 2 , xn −1 , xn ](ξ )


Table I: Comparison of EI of various methods is shown in Table I.




ξ ∈]α , xn +1[ ,

η ∈] xn − 2 , xn [ Assuming ∈n+1 is asymptotic to c ∈n , p > 1 , p

(α − xn+1 ) = K (α − xn−2 ) (α − xn−1 ) (α − xn ) 2













Regula Falsi










New method




∈n−1 =


EI = p







∈n+1 = K ∈n−2∈n−1∈n c



Expressing this in terms of ∈n−1 , we get 2

.This EI is better than

secant method, Newton method, method suggested by Costabile [3,4] and method proposed by Frontini [6].

' (α − xn+1)H5 [ f , xn−2,xn−1,xn](ξ)


= 1.708684


2 2 2p p K ∈n−1∈n−1∈n−1

The results of numerical experiments are shown in the tables II, III and IV.




The computed results of Examples 1-4 by new method with tolerance= 1×10 are given in Table II. Here NI stands for number of iterations and NFE stands for number of function evaluations. Table III- displays results obtained by Exponential regulafalsi, Regulafalsi, Steffensen’s and Newton methods(see[7]) TABLE II

Interval for

|f( ξ )|






















Function f (x)






x+ 1 - e sinx


[1, 4]

11x11-1 3

xe-x -0.1


Algorithm 2 (EXRF) NI


Algorithm 1 (regula falsi)

|f( ξ )|




|f( ξ )||



|f( ξ )|

Newton NI



















Not convergent









7 8.04133e01











|f( ξ )|



given by Jinhai Chen, and Weiguo Li [7]

TABLE IV: In this Table IV we present results through new method for some examples considered by several researchers with -15

tolerance= 1×10

Function f (x)

Interval for Search


|f( ξ )|




x2(x2/3+ 2 sinx)- 3 /18


































































2xe-n + 1 - 2e-nx 2

[0,1] n=5,10,20

x2 - (1 - x)n 3

[0,1] n=5,10,20

e-nx(x-1) +xn 4

[0,1] n=5,10,20

x2+sin(x/n)-1/4 [0,1]

5 n=5,10,20

(nx-1)/((n-1)x) 6

[0.01,1] n=5,10,20























INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 [4] F.Costabile, M. I. Gualtieri and S.Serra, “An iterative method for the computation of the solutions of nonlinear equation”, Calcolo vol.36, pp 17–34, 1999.

5. CONCLUSION As learning based intelligent searching technique, we propose a method of fitting a fifth degree Hermite polynomial (for three distinct points, their respective function values and values of their corresponding first derivatives). The present method, using lag based −15 searching technique with tolerance= 1×10 has a rate of convergence 2.9196 and better Efficiency Index of 1.708684. The EI obtained by the present method is better than the EI of Secant method, Newton method, as well as the method suggested by Costabile [3,4] and the method proposed by Frontini [6]. Numerical experiments presented in the paper show that this method gives better performance and it is fast approaching to a root of given non linear equation f(x) = 0 with lesser number of iterations and lesser function evaluations and comparable to well known methods.

[5] W. Gautschi, Numerical analysis. An introduction. Boston: Birkhäuser Boston 1997. [6] M.Frontini, “Hermite interpolation and a new iterative method for the computation of the roots of non-linear equations”, Calcolo vol.40, pp 109 – 119, 2003. [7] Jinhai Chen, and Weiguo Li, “ An improved exponential regula falsi methods with quadratic convergence of both diameter and point for solving nonlinear equations”, Applied Numerical Mathematics vol. 57 pp 80–88, 2007.


The authors thank ACRHEM, UoH for financial support. First author thanks Professor. S.P.Tewari, Director, ACRHEM,UoH and Professor. M. Sitaramaiah, emeritus Professor, MCIS, UoH, for the encouragement and valuable suggestions.

REFERENCES [1] G. E. Alefeld and F. A. Potra, “Some efficient methods for enclosing simple zeros of nonlinear equations”, BIT vol. 32, pp 334–344, 1992. [2] Alefeld G, F .A. Potra, Shi Y.X, “On enclosing simple roots of nonlinear equation”, Math. Comput. Vol. 61, pp 733744 (1993) [3] F.Costabile, M. I.Gualtieri and R. Luceri, “New iterative method for the computation of the solutions of nonlinear equations”, Numer. Algorithms vol. 28, pp 87–100, 2001.



A Novel Approach for Combating Spamdexing in Web using UCINET and SVM Light Tool Ms. D. Saraswathi*,Dr. A. Vijaya Kathiravan #,Ms.S. Anita* *Asst. Professor in Computer Science, K.S.R. College of Arts & Science, Tiruchengode-637209, Namakkal, TN, INDIA. # Professor, MCA Dept., Nandha Engineering College, Perundurai, Erode, TN, INDIA

ABSTRACT-Search Engine spam is a web page or a portion of a web page which has been created with the intention of increasing its ranking in search engines. Web spamming refers to actions intended to mislead search engines and give some pages higher ranking than they deserve. Anyone who uses a search engine frequently has most likely encountered a high ranking page that consists of nothing more than a bunch of query keywords. These pages detract both from the user experience and from the quality of the search engine. Search engine spam is a webpage that has been designed to artificially inflating its search engine ranking. Recently this search engine spam has been increased dramatically and creates problem to the search engine and the web surfer. It degrades the search engineâ&#x20AC;&#x2122;s results, occupies more memory and consumes more time for creating indexes, and frustrates the user by giving irrelevant results. Search engines have tried many techniques to filter out these spam pages before they can appear on the query results page. In this paper, various ways of creating spam pages, a collectionof current methods that are being used to detect spam, and a new approach to build a tool for spam detection that uses machine learning as a means for detecting spam. This new approach uses UCINET software and a series of content combined with a Support Vector Machine (SVM) Binary classifier to determine if a given webpage is spam. The link farm can identify based on degree, betweenness and Eigen vector value of link. The spam classifier makes use of the Wordnet word database and SVMLight tool to classify web documents as either spam or not spam. These features are not only related to quantitative data extracted from the Web pages, but also to qualitative properties, mainly of the page links.

Search Engines consist of three major components: spider, index, and search engine program. The spider or crawler starts with an initial set of URLs called seed URLs, retrieves the Web pages of the seed URLs, and follows the links to other sites from those pages. Keywords found on a Web page are added to the index or catalog of the search engine. The searchengine program finds the relevant pages, from the millions of pages recorded in its index, which match a query and returns them to the user after ranking them in order of relevance. A PageRank is determined for all Web pages in the links database and this PageRank is used to evaluate the relevance of a result. Search Engines are entryways to the web. The objective of a search engine is to provide high quality results by correctly identifying all web pages that are relevant for a query, and presenting the user with the most important of those relevant pages. Relevancy is the search engineâ&#x20AC;&#x2122;s measure of how well a particular Web page matches a search. It refers the textual similarity between the query and a page. Pages can be given a query specific, numeric relevance score; the higher the number, the more relevant the page is to the query. Relevancy is measured by using On the Page Criteria and Off the page Criteria factors. The former determines the keyword density by dividing the Keyword count and the total no of keywords in a page. The "off the page" criteria are Number of links, Relevance of links, Click through rates which refers how many people click on a particular link. This is often the quickest route to get a listing and can provide a boost to ranking also. Importance refers to the global popularity of a page, as often inferred from the link structure (e.g., pages with many in-links are more

Keywords: Search engine, PageRank, Spam, Content Spam, Link Farm, Classification I.



INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 important), or perhaps other indicators. In practice, search engines usually combine relevance and importance, computing a combined rank score that is used to order query results presented to the user. The term spamming or spamdexing refers any deliberate human action that is meant to trigger an unsustainably favourable relevance or importance for some web page, considering the page’s true value.


Although both email and search engine spamdexing are attempts to gain the attention of Internet users, they do not have much in common. Search engine spamdexing is a largely technical task in that spammers are trying to get their results placed as highly as possible and it is called as Spamdexing. Thus, filters that foil an email spammer may not be sufficient to stop a more technical search engine spammer. Classifying search engine spam in this manner is more difficult since many non-spam web pages exist for commercial purposes and contain many of the same keywords as the spam pages.


A. Link Analysis More complex ranking methods are also vulnerable to spam. For example, the cosine similarity method used in latent semantic indexing will always rank a document that is an exact match to the query higher than any other document. The popular search engine Google uses a system called PageRank to determine the order in which it returns results [4]. This ranking method orders pages based on the inbound links to each page. Essentially, when one page links to another it is casting a vote that the target of the link is valuable. Although users have found Google resistant to spam, PageRank can be manipulated by artificially altering the link structure of the web. While Page et al. note that this could be done by web authors paying others for inbound links, though they thought it would be financially infeasible [6]. It seems that their predictions were incorrect as atleast one company is in the business of brokering these link sales [7]. Another problem with PageRank is that it only works on interlinked collections of documents. There are many valuable document repositories that do not have links such as newsgroup postings and archived emails. In addition, running PageRank on a small subset of the Web (e.g., the website), will not produce as useful results since links from outside documents can not be considered. Although PageRank has been successful at keeping spammers from manipulating results, it is not impenetrable and link analysis is not applicable in certain instances.

title and description elements with keywords, search engines will usually only look at a finite number of characters in these fields [12]. Additionally, search engines also look for attempts to hide keywords by putting them at the bottom of a page, in a small font, or in a font whose color closely matches the background color [8]. While these methods can detect many spam pages, others remain unnoticed by having spam text appear in the web page, masking itself as normal text. Search engines will also look for “doorway” pages that are setup to rank highly on common searches and then send the user to a different page which would not have ranked as highly [11]. However, many doorway pages are difficult to detect since they use complicated JavaScript code rather than a simple redirect tag. C. Human Experts, Yahoo!, and the Open Directory Project all provide directories of pages on frequently requested topics. These directories have been edited and thus manually screened for spam. However, these listings will reflect the biases of their editors. While this may not bother some users, those searching for information on controversial topics may be more comfortable with search results that have not been filtered by a human. Finally, these directories may not be as up-to-date as other search engines since it is difficult for a human editor to keep up with the fast-changing web. A system designed by Bharat and Mihalia [3] uses existing directories of sites on a particular topic to rank search results for that topic. It scours the web for pages that link to a wide variety of sites that are on the same topic but from different sources and stores these pages as “expert pages.” It then ranks pages based on the number of “experts” that link to them. While this

B. HTML Analysis

All search engines do some analysis of the HTML elements on a web page in order to determine its ranking. In order to keep authors from simply filling the 48

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 of their contents. This research attempt to derive intent based on the link structure and content of the document. Many of these pages are used to create link farms. A link farm is a densely connected set of pages, created explicitly with the purpose of deceiving a link-based ranking algorithm. A link farm may have a high in-degree and statically differ from non-spam pages. This is done by using UCINET Software[13], measure Eigen vector, centrality of degree and betweenness in network. A network that possesses just a few or perhaps even one node with high centrality is a centralized network. In this type of network, all nodes are directly connected to each other. Subordinate nodes direct information to the central node and the central node distributes it to all other nodes. Centralized networks are susceptible to disruption because they have few central nodes and damage to a central node could be devastating to

system appeared very promising in tests, if it were deployed in an actual search engine, it would be subject to phony expert pages. Since the criteria for an “expert page” is based entirely on the content of the page itself, a spammer could create a number of pages that are designed to be recognized as “expert pages” and use them to manipulate the search engine. D. Text Classification

Androutsopoulos et al. tested a Bayesian classifier (developed by Sahami et al.) that determines spam [1]. They note that “it seems that the language of current spam constitutes a distinctive genre” and using natural classification to distinguish between spam and legitimate page thus makes sense. This classification scheme treats each word as a token and analyzes pages based on the frequency of the words they contain. Another spam classifier is Spam Assassin [7]. This classifier tests the presence of key phrases (e.g., pornographic text) and other properties (e.g., an invalid date in the headers). It assigns each of these phrases and properties a numeric value and adds the values for a particular email together. If the sum of these values is above a certain threshold, it marks the message as spam. Quek developed a system to classify web pages into categories using a Bayesian classifier [6]. In addition to using only the textual components of pages, he tried using a couple webspecific classification schemes. One of these was to use only the text contained within header and title tags, as this text is assumed to be representative of the page’s contents. The other was to use the hyperlink structure and the text in the hyperlinks to derive relationships between webpages. III.

the entire network. Decentralized networks are those that do not possess one central hub; but rather possess several important hubs. Each node is indirectly tied to all others and therefore the network has more elasticity. Consequently, candidate’s profile networks choose this type of structure whenever possible. Social network analysts use the term degrees in reference to the number of direct connections that a node enjoys. The node that possesses the largest number of connections is the hub of the network. The term betweenness refers to the number of groups that a node is indirectly tied to through the direct links that it possesses. Therefore, nodes with high a degree of betweenness act as liaisons or bridges to other nodes in the structure. These nodes are known as “brokers” because of the power that they wield. However, these “brokers” represent a single point of failure because if their communication flow is disrupted than they will be cut off to the nodes that it connects. The sum of degree, betweenness and Eigen vector values will get a threshold value. The non links spam can identify based on threshold value and this parameter value pass to SVM Light tool to identify the content of the document.


In order to properly classify spam, we first have to define precisely what constitutes a link farm and spam document. This definition is complex because spam in one context may not be spam in another. A webpage is spam if it or a portion of it was created with the purpose of increasing its ranking through use of link and content that does not add to the user experience. Unfortunately, it is not always possible to detect spam by content analysis, as some spam pages only differ from normal pages because of their links, not because

The motivation behind the content analyzers lies in the fact that written English has certain consistent statistical properties. These include sentence length analyzer, stop word analyzer and part of speech analyzer. From TREC data [9], it has been found that 49



Web Crawler


third analyzer uses WordNet database [12] to ascertain part of speech information for all the words in a document with the intention of collecting frequencies of noun, verb, adjective, and adverb usage. This analyzer can be useful

Not Spam

the average sentence length is 18 words. Stop words are the set of the most frequently occurring words in a collection of documents. Collecting information about stop word frequency in a document can help detect spam pages because an author trying to create spam may not include stop words in their spam efforts. The


Web Page Repository

Spam Detector

UCINET Software


URLs Link Server PageRank


SVM Light Tool




Search Query Client Query Interface

Index Server Query Results

Lexicon Sorter

Fig 1. Proposed Architecture for Combating Spamdexing

classifier, the indexer is slightly modified to write statistics about each document to a file.

because spam pages often have more nouns than non-spam pages because most query terms involve nouns. While all three analyzers report parameters

A. Development on the documents, there is still the problem of using these collected parameters to determine if a given webpage is spam. This is solved by using Vipnikâ&#x20AC;&#x2122;s SVMLight tool [10] to implement Support Vector Machine binary classifier, which fed parameters as feature vectors from the three analyzers to classify documents as either spam or not spam. Fig 1 gives an overview of this architecture.

In order to load TREC data files into our local repository, a Java program has been developed that separates each TREC data file into separate files each composed of one article. By separating these files into articles, the TREC data more closely matches the nature of data on the World Wide Web. To load web pages into the repository, a Java crawler has been developed to download all those documents to the local file system. The indexing engine is based on a flexible architecture that allows us to crawl a directory tree on the local file system and process each file encountered. There are three stages of processing a file:

IV. IMPLEMENTATION PLAN Software has been developed to load documents into a local file repository, index, and query those documents. Under normal operation, the indexer runs the classifier to determine if a file is spam and only indexes it if it is not. For purposes of training the

1. Pre-process. This includes reading the file from 50

INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 disk and extracting the natural language portions from any markup language. 2. Combating Spamdexing Determine the threshold value for link and classify the document in the form of feature vector. Use the UCINET software and SVM based binary classifier model to classify the link and document as either spam or non-spam.

Fig 2: Web Graph for Link Structure

3. Indexing. Add the document to an index file if it is classified as non-spam. In order to use a SVM classifier, it is necessary to first train the model on sample data. This is accomplished by running the indexing process in a mode where it wrote the parameters from the semantic analyzers for each document to a file. Each document is manually classified in the collection indicating whether or not it was spam. Finally, this data file is fed into SVMLight to create and train the Binary Support Vector Machine (SVM) classifier. A query interface is provided to allow users to test this system. The spam and non-spam pages were found by performing five queries on AltaVista and manually classifying the top one hundred results of each. We selected five queries that we thought were likely to result in a large number of spam documents: “MP3”, “breast”, “college girl”, “Apple IBM Dell Gateway”, and “ford chevy nissan toyota honda”. Of the five hundred AltaVista results, 337 were non-spam, eighty were spam, and the remaining eighty-three were not in English. Even using the most powerful open-source Support Vector Machine Binary Classifier implemented by SVMLight, the classifier could not split documents into spam and non-spam. More promising was the fact that many of the web pages classified as TREC contained proportionally large amounts of natural language data. V.

Table 3: Sample Test Results for Content


Total Pages



NonSpam Pages

Spam Pages

Search Time Sec(s)

















































RESULTS AND DISCUSSION An input values are given manually in Table 1, the centrality of the each node by performing Degree Centrality and Betweenness Centrality in Table 2 and corresponding Web Graph in Fig 2.A sample test result for combating spamdexing has been given in Table 3. A search engine downloads web pages one by one starting from the root node, using focused crawler. These documents are stored in web repository, then preceded by tokenization, HTML tags removal, stop words removal, stemming and lexicon formation. Then it is followed by forward indexing, inverse indexing with the help of an

Table 1: Sample Input values for UCINET

Table 2: Degree Centrality & Betweenness Measures


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 able to classify spam vs. one that only looks at plain text.

indexer, and dumping into file barrels for accessed by the client query interface. In this research, the most complicating factor is data collection. Even though several web pages have been collected by this search engine, all the web pages do not contain relevant information. Again the resulted relevant pages may be bounced with dead pointers sometimes. The hyperlinks are not properly bound during crawling process. Another aspect of this search engine is to use storage efficiently. Due to the dynamic storage of forward indexing, a huge amount of memory size is reduced comparing with the conventional search engines. Furthermore, most queries can be answered using just the inverted index. The current version of search engine with spamdexing filter answers most keys in between 1 and 10 seconds. Its accuracy and precision are found to be satisfactory. To improve this in future, plans are made to design a separate spamdexing tool for combating spasm in any search engine results. From the above results, it has been understood that the average relevancy, precision and recall values of this tool is also fine by combating spamdexing. From the following Fig 3, the processing time for initial query and repeated query has been identified evidently.


Due to the similarities between spam and non-spam the original semantic analyzers are not an effective method to classify spam content. Since spam and non-spam documents are so similar, it is sometimes very difficult for a human to differentiate between the two. Because of these similarities, it is unlikely that any natural language analysis method will be successful in differentiating between spam and nonspam. However, using semantic analyzers to determine the usefulness of information on a webpage had much more promising results. REFERENCES [1]


8 7 Time


Larry Page, Sergey Brin, Rajeev Motwani, and Terry Winograd. “The PageRank Citation Ranking: Bringing Order to the Web.” 1999. Technical Report, Stanford University. http:// dbpubs. stanford. edu/ pub/ 1999-66. Alan Perkins. The classification of search engine spam. http://www. whitepapers/ spamclassification/.

Hard disk



5 4 3

Krishna Bharat and George A. Mihala. “When Experts Agree: Using Non-Affiliated Experts to Rank Popular Topics.” ACM Transactions on Information Systems (January 2002). 47-58.




Search Engine








Choon Yang Quek. “Classification of World Wide Web Documents.” 1997. Senior Honors Thesis, Carnegie Mellon University. ttp:// afs/ project/theo11/www/ wwkb/choon-thesis.html.


Spam Assassin. (Software.) http:// www. spamassassin. org.

0 Initial Query

Androutsopoulos, John Koutsias, Konstantinos V. Chandrinos, and Constantine D. Spyropoulos. “An Experimental Comparison of Naive Bayesian and KeywordBased Anti-Spam Filtering with Personal Email Messages.” In Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval (July 2000). Zolt´an Gy¨ongyi, Hector Garcia Molina, and Jan Pedersen. Combating web spam with TrustRank. Technical report, Stanford University, 2004.





Repeated Query


Danny Sullivan, ed. “Search Engine Placement Tips.” Last updated October 14, 2002. http:// searchenginewatch. com / webmasters/ tips.html. [9] S. Brin and L. Page. The anatomy of a large-scale hypertextual web search engine. In WWW Conference, volume 7, 1998. 1.htm [10] Zolt´an Gy¨ongyi, Hector Garcia Molina. Web Spam Taxonomy, March, 2004. [11]

Fig 3: Processing Time for combating Spamdexing Assuming the user is more interested in finding a quick answer to their query, a page with more textual information should have a higher rank. The analyzers could help to determine this rank. In order to better classify web documents it is a belief that it is necessary to take advantage of the meta information that is included in the html as well as the link structure. With this extra information at hand, a spam analyzer will have a better chance of being

[12] Andrew Westbrook, Russell Greene. “Using Semantic Analysis to classify Search Engine Spam” Stanford University, 2005. [13]



Efficient Wavelet based Image Compression Technique for Wireless Communication P. Santha devi M.C.A., M.Phil., Assistant Professor, P.G Department of Computer Science, Kongu Arts and Science College, Erode - 7. DR. ARTHANARIEE A.M. M.SC., M.PHIL., PH.D, PGDCA., M.S., DIRECTOR, BHARATHIDHASAN SCHOOL OF COMPUTER APPLICATIONS, ELLISPETTAI, ERODE. Mr.M.Sivakumar , Doctoral Research Scholar, Anna University of Technology, Coimbatore

Abstract: With phenomenal growth in wireless multimedia image communication, the issues need to handle are resource consumption and the quality of the image being transmitted in wireless channels. The resource consumptions indicated in most literatures are bandwidth and energy consumption. The strict constrains of wireless sensor networks (WSN) on individual sensor node’s resource brings great challenges to the information processing, especially in image capture sensor network. A Simple Wavelet Compression (SWC) processing of image coding is proposed to maximize compression and minimize energy cost in WSN. Most of the current work, utilize lossy image compression techniques to minimize the resource consumption. The lossy image compression technique reduces the size of the image to a great extent, however the quality of the image being reproduced needs appreciation. The proposed work presented, an improved polyomines lossless compression technique and efficient wavelet compression, both increases the quality of image at receiving end of the wireless communication by reducing the Peak to Signal Noise ratio and mean square error. Experimental simulation are carried out using JPEG images for evaluating the performance of the improved polyomines lossless compression compared to that of lossy image compression, which shows nearly 20% improvement in quality of image being reproduced on transmitted decompression. The simulation results showed that these approaches achieved significant energy savings without sacrificing the quality of the image reconstruction. Results show up to 80% reduction in the energy consumption achieved by our efficient wavelet compared to a nonenergy-aware one, with the guarantee for the image quality to be lower-bounded.

multimedia data requires a large amount of information, leading to high bandwidth, computation energy (energy consumed in processing information to be transmitted), and communication energy (energy consumed in wirelessly transmitting information) requirements for mobile multimedia communication. The large requirements for bandwidth and energy consumption are significant bottlenecks to wireless multimedia communication. The characteristic of wireless multimedia communication which can be used to overcome the bandwidth and energy bottlenecks is that the conditions and requirements for mobile communication vary. Variations in wireless channel conditions may be due to user mobility, changing terrain, etc. For example, in [1], the Signal to Interference Ratio (SIR) for cellular phones was found to vary by as much as 100dB for different distances from the base-station. Moreover, the Quality of Service (QoS) – such as transmission latency or bit error rate (BER) – and Quality of Multimedia Data (QoMD) – including image/video quality – required during multimedia communication changes depending on the current multimedia service. For example, the QoS (latency) and QoMD requirements of transmitted data are different between video telephony and web browsing. One way to design a multimedia capable radio signal which accounts for varying communication conditions and requirements is to assume the worst-case. However, by designing a radio signal, which adapts to current communication conditions and requirements, it is possible to help overcome the bandwidth and energy bottlenecks to wireless multimedia communication. For example, in [2], the authors adapt the channel coding parameters used to match current channel conditions, thereby increasing the average bandwidth available. An algorithm to modify the broadcast power of a power amplifier to meet QoMD requirements, thereby lowering energy consumption is proposed in [3]. In [4], the authors change channel coder and power amplifier settings according to current conditions in order to lower

Keywords: Wireless communication, Image compression, image quality 1. INTRODUCTION Wireless sensor networks are being developed for a variety of applications such as environmental monitoring, marine biology and video-surveillance. Several energy efficient protocols of image compression are proposed for wireless applications. The growth of 3G wireless communication systems in line with internet popularity, made wireless multimedia image communication an important research topic in current network communication field. However, representing


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 energy consumption. While previous research has studied the effects of adapting the channel coder and power amplifier to current communication conditions and requirements, the effects of modifying the source coder have not been previously studied. The proposed work, presented an improved lossless image compression technique to have an efficient wireless multimedia image compression which utilize the polymonies technique by integrating Huffman code to the noisy transmission channels.

the correlated information resulting in savings in communication energy. In parallel distributed computing theory [10], a problem (or task) is divided into multiple sub-problems (or sub-tasks) of smaller size (in terms of resource requirements). Every node solves each sub problem by running the same local algorithm, and the solution to the original problem is obtained by combining the outputs from the different nodes. Our approach to the design of distributed image compression is similar in concept, in that we distribute the task of image encoding/compression to multiple smaller image encoding/compression sub-tasks. However, a key difference is that distributed computation theory typically focuses on maximizing the speed of execution of the task while our primarily concern here is reducing the total energy consumption subject to a required image quality. Thus, our proposed approach of image compression intersects with the literature on lossy and lossless compression, which primarily focuses on polyomino technique.

Advances in visual sensors [12], [13] and wireless communication have enabled the development of low-cost, low-power visual multihop wireless networks, which have recently emerged for a variety of applications, including environmental and habitat monitoring, target tracking and surveillance [3], [4]. However, representing visual data requires a large amount of information, leading to high data rates, which in turn requires high computation and communication energy.

R. S. Wagner [14] uses the down sampling from each camera node that have the common image. Thus low resolution image is sent from each node that causes the energy consumption. Min Wu et al. [15] sent only the changes from each node that has the common image. This also have overhead of communication from each node and also considered that background is stationary.

2. RELATED WORKS The proposed work has been inspired by a variety of research efforts in image compression and wireless multimedia communication separately to present an image compression technique which suits the wireless image communication with minimal resource consumption and better quality image at the receiver end. First describe some basic concepts that relates to current research in the area of sensor network applications. The early research efforts in wireless sensor networks did not investigate the issues of node collaboration, focusing more on issues in the design and packaging of small, wireless devices [5], more recent efforts (e.g. [6], [7]) have considered node collaboration issues such as data “aggregation” or “fusion”. Our approach of distributed image compression falls within the domain of techniques that apply the concept of innetwork processing, i.e. processing in the network by computing over the data as it flows through the nodes. It is worth noting that current aggregation functions (e.g., “maximum” and “average” [7]) are limited to scalar data. Our approach can be viewed as an extension to vector data aggregation.





POLYOMINO There are two types of image compression: lossless and lossy. After decompression the original image is recovered. The steps shown in the diagram are invertable, hence they are lossless except for the quantize step to take place. Quantizing refers to a reduction of the precision of the floating point values of the wavelet transform, which are typically either 32-bit or 64-bit floating point numbers. To use less bits in the compressed transform which is necessary if compression of 10 bpp or 14 bpp images is to be achieved these transform values must be expressed with less bits for each value. This leads to rounding error. These approximate, quantized, wavelet transforms will produce approximations to the images then an inverse transform is performed. Thus creating the error inherent in lossy compression.

Previous distributed signal processing/compression problems (e.g. [8], [9]) exploit correlations between data at close-by sensors in order to jointly compress or fuse



Compressing an image is significantly different than compressing raw binary data. The general purpose compression is used to compress images, but the result is less than optimal. This is because images have certain statistical properties which can be exploited by encoders specifically designed for them. This also means that lossy compression techniques can be used in this area.

Inverse Wavelet Transform




+ MN


MSE = 1 / MN Σ Σ [ I (x,y) – I’ (x,y) ] + MN y = 1 to M ; x = 1 to N


Entropy Decoding


Two of the error metrics used to compare the various image compression techniques are the Mean Square Error (MSE) and the Peak Signal to Noise Ratio (PSNR). The MSE is the cumulative squared error between the compressed and the original image, whereas PSNR is a measure of the peak error. The mathematical formulae for the two are

An integer-to-integer wavelet transform produces an integer-valued transform from the greyscale, integer-valued image [11]. Since n loops in Bitplane encoding reduces the quantization error to less than T0/2n, it follows that once 2n is greater than T0, there will be zero error. In other words, the bit-plane encoded transform will be exactly the same as the original wavelet transform, hence lossless encoding is achieved . Lossless compression involves with compressing data which, when decompressed, will be an exact replica of the original data.This is the case when binary data such as executables, documents etc. are compressed. They need to be exactly reproduced when decompressed. On the other hand, images (and music too) need not be Reproduced ‘exactly’.

Wavelet Transform


PSNR = 20 * log10 (255 / sqrt(MSE))

Quantization where I(x,y) is the original image, I'(x,y) is the decompressed image and M,N represents dimensions of the images. A lower value for MSE means lesser error, and as seen from the inverse relation between the MSE and PSNR, this translates to a high value of PSNR. Logically, a higher value of PSNR is good because it means that the ratio of Signal to Noise is higher. The signal is the original image, and the noise is the error in reconstruction. It is highly required to evaluate a compression scheme having a lower MSE (and a high PSNR).

Entropy Coding


Fig 1 A typical Wavelet Compression (a) Encoder (b) Decoder.



3.2 Compression Algorithm There are numerous ways to compare between two compression algorithms. The metrics are different for lossless and lossy compression schemes. For lossless compression scheme, the first parameter to be compared is the compression ratios. Second, we check the time complexity and the memory requirements. Any lossless compression scheme, which yields higher compression ratio, lesser time complexity and requires lesser memory, is accepted to be a better lossless

A typical wavelet based image compression system is shown in Fig. 1. It consists of three closely connected components namely Forward/ Reverse transformer, Quantizer / Dequantizer and Entropy encoder/decoder. In terms of energy dissipation of JPEG2000 compression/decompression, wavelet transform is the dominant part.


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 compression algorithm.The quality of the decompressed image is measured in terms of PSNR (Peak Signal to Noise Ratio) value. The decompressed image having the higher PSNR value is assumed to have retained better image quality of the original image. It is inversely proportional to the mean square error (MSE). The more the error, the less will be the PSNR value and vice versa. PSNR value is infinite for lossless image compression because the MSE value is zero in lossless compression. Hence, any lossy compression scheme, which gives more PSNR value and more compression ratio, is accepted to be the better compression algorithm.

components using low filters. The filter components are reduced their size by half either by rejecting the even or odd samples thereby the total size of the original signal is preserved. The low pass filter component retains almost all distinguishable features of the original signal. And the high pass filter component has little or no resemblance of the original signal. The low pass component is again decomposed into two components.

The decomposition process can be continued up to the last possible level or up to a certain desired level. As the high pass filter components have less information discernible to the original signal, we can eliminate the information contents of the high pass filters partially or significantly at each level of decomposition during the reconstruction process. It is this possibility of elimination of the information contents of the high pass filter components that gives higher compression ratio in the case of wavelet based image compression.

3.3 Wavelet Image Compression Lossy JPEG compression introduces blocky artifacts in the decompressed image, which are not desirable and pleasing to the eyes. Lapped Orthogonal Transforms (LOT) [7] was proposed to solve this problem by using smoothing the overlapping blocks. LOT could reduce the blocking effects but its computational complexity is very high and hence LOT is not preferred to use over JPEG. On the other hand, wavelet based image compression introduces no blocky artifacts in the decompressed image. The decompressed image is much smoother and pleasant to eyes. We can also achieve much higher compression ratios regardless of the amount of compression achieved. By adding more and more detail information we can improve the quality. This feature is attractive for what is known as progressive transmission of images.


The experimental evaluation is carried out with the original image given as the input. The image is compressed at the rate of 50 %. Image compression is done for lossless compression, lossy compression and wavelet compression. The quality rate applied for all the compression technique is 50% carried out with the JPEG image golf.jpg. In the filtering phase the wavelet based image compression does not reduce the dimension of the image , height or width to compress but it transforms it values in order to obtain a more compressible set of data. The filtering phase comprises of standard filtering, color filtering and remapping.Just to show how wavelet based image compression is performed, a simple image compression example is given here. Fig-1, is the original image. It is decomposed up to two levels using 9/7 biorthogonal filters.

Another lossy compression scheme developed for image compression is the fractal base image compression scheme [1]. However the fractal based image compression beginning to loss ground because it is very complex and time consuming.Wavelet signifies small wave. It was first used in approximating a function by linear combination of various waveforms obtained by translating and scaling the wavelet at various position and scales. It was very old from the time of Alfred Haars. But it was not so popular then because it found no application area. It becomes popular only when Ingrid Daubechies [5] shows that QMF (Quadrature Mirror Filter) filters [6] used in filterbank for subband coding can be generated from the wavelet by using the perfect reconstruction relation of the filter bank. So, what we obtain from the wavelet is a set of QMF filter banks that can be used for subband coding. In a QMF filter bank a signal is first decomposed into low pass and high pass

Original Image



Fig 4. Wavelet Compression applied to the original image. There are one low pass components and six high pass components. The low pass component is also most often referred to as approximation component as it basically represents the approximation of the original signal or image. The high pass components are often referred to as details. So, in figure- 2, the top leftmost corner, the rest are the details. We see that the approximation component represents fairly the original signal even it has been reduced four times in size. Figure-3 gives the decompressed image from the 16 times compressed data. And figure 4-d shows the decompressed image from the 32 times compressed data. However, we see that these decompressed image are visually similar to the original image. However, they are very different numerically. This is how the lossy compression works. Using wavelet based image compression we can compress an image up to 128 times, still we would get distinguishable approximation of the image. From the table above it is clear that the wavelet image based compression proves to be highly preferable when compared to the lossless compression and lossy compression.

Fig 1. Original Image

Lossless Compression: At quality rate 50%


Fig 2. Lossless Compression applied to the original image Lossy




There are a wide variety of wavelet-based image compression algorithms besides the one that we focused on here. Some of the most promising are algorithms that minimize the amount of energy which the encoder and/or decoder must use. A new algorithm which is embedded and which minimizes energy is described . Many other algorithms are cited in the review article [1]. In evaluating the performance of any new image compression algorithm, one must take into account not only wavelet values, but also consider the following factors: (1) perceptual quality of the images (edge correlation values can be helpful here), (2) whether the algorithm allows for progressive transmission, (3) the complexity of the algorithm (including memory usage), and (4) whether the algorithm has ROI capability.


Fig 3. Lossy Compression applied to the original image Wavelet Compression : At quality rate 50%

In this section, we perform two sets of simulations that compare our proposed wavelet compression with the centralized algorithm based on


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 two performance metrics : energy consumption and system lifetime. Our simulations are compared with the lossless compression and lossy compression. Results show that though the size of the bytes has been reduced considerably the result after the compression algorithm has not been changed. The image is same as to the original image. From the table we can conclude that as the value of the quality increases in lossless compression we obtain 117331 bytes, in lossy compression we attained 97744 bytes and in wavelet compression we gained 105422 bytes. Compared to the three compression techniques, wavelet compression results with the reduction of bytes without changing the original image. As though we compress the image and then transmit considerable amount of energy is utilized. This energy consumption is also reduced to the maximum possible and then the image after being compressed is transmitted.


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In the proposed scheme we have selected two parameters of the efficient wavelet image compression algorithm to vary, and presented the results of modifying the parameters on quality of image, computation and communication efficiency with respect to energy utilization. We are planning to extend the proposed work to improve on the line of evaluating the performance of the image compression technique to latency and data loss occurrence during the image transmission on the wireless communication channel. The impact of this scheme on image signal quality is presented in the final. The simulation results showed that these approaches achieved significant energy savings without sacrificing the quality of the image reconstruction.




The proposed work presented an improved wavelet based inductive methods for lossless image compression ,lossy image compression and the wavelet image compression which can be effectively deployed in the transmission of wireless communication. The experimental simulation conducted for the standard JPEG images, by applying the three compression techniques in the wireless channel, shows better quality of image on decompression (nearly 25%) compared to that of any other technique. By adapting the source code of a multimedia capable radio to current communication conditions and constraints, it is possible to overcome the bandwidth and energy bottlenecks to wireless multimedia communication.

Source Image: Golf.jpg








INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 Computational Harmonic Analysis, Vol. 5, No. 3, pp. 332-369, 1998.

REFERENCES [12]Digital pixel sensor,. 2004. [Online]. Available: http://www-isl. [1] F. Hendessi, A. U. Sheikh, and R. M. Hafez, “Co-Channel and Adjacent Channel Interference in Wireless Cellular Communications”, Wireless Personal Communications, vol. 12, pp. 239–253, March 2000.

[13] A. E. Gamal,. Trends in CMOS image sensor technology and design,. in Proceedings of IEEE International Electron Devices Meeting, San Francisco, CA, December 2002. [14] R. Wagner, R. Nowak, and R. Baraniuk. Distributed image compression for sensor networks using correspondence analysis and super-resolution. In Proceedings of IEEE International Conference on Image Processing (ICIP’03), volume 1, pages 597–600, Barcelona, Spain, September 2003.

[2] S. Kallel, S. Bakhtiyari, and R. Link, “An Adaptive Hybrid ARQ Scheme”, Wireless Personal Communications, vol. 12, pp. 297–311, March 2000. [3] P. Cherriman and L. Hanzo, “Error-rate Based Powercontrolled Multimode H.263-Assisted Video Telephony”, IEEE Transactions on Vehicular Technology, vol. 48, pp. 1726–38, September 1999.

[15] Min Wu and Chang Wen Chen. Collaborative image coding and transmission over wireless sensor netowrks. EURASIP Journal on Advances in Signal Processing, 2007. Article ID 70481.

[4] M. Goel, S. Appadwedula, N. R. Shanbhag, K. Ramchandran, and D. L. Jones, “A Low-power Multimedia Communication System for Indoor Wireless Applications”, in 1999 IEEE Workshop on Signal Processing Systems. SiPS 99, pp. 473–82, October 1999. [5] G. Zaruba and S. Das, Off-the-shelf enablers of ad hoc networks. New York: IEEE Press Wiley, 2003. [6] C. Intanagonwiwat, R. Govindan, and D. Estrin, “Directed diffusion: a scalable and robust communication paradigm for sensor networks,” in Proceedings of the sixth annual international conference on Mobile computing and networking. ACM Press, 2000, pp. 56–67. [7] W. Zhang, Z. Deng, G. Wang, L. Wittenburg, and Z. Xing, “Distributed problem solving in sensor networks,” in Proceedings of the first international joint conference on Autonomous agents and multiagent systems. ACM Press, 2002, pp. 988–989. [8] A. Wang and A. Chandrakasan, “Energy efficient system partitioning for distributed wireless sensor networks,” in Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP-2001), Salt Lake City, Utah, May 7–11 2001. [9] S. S. Pradhan, J. Kusuma, and K. Ramchandran, “Distributed compression in a dense microsensor network,” IEEE Signal Processing Magazine, vol. 19, no. 2, pp. 51 –60, March 2002. [10] D. P. Bertsekas and J. N. Tsitsiklis, Parallel and distributed computation: numerical methods. Prentice-Hall, Inc., 1989. [11] A.R. Calderbank, I. Daubechies, W. Sweldens, B.-L. Yeo, Wavelet transforms that map integers to integers. Applied and



Serpentine Robot Locomotion: Implementation through Simulation Atanu Maity 1,2


, S. Majumder



, S. Ghosh

Central Mechanical Engineering Research Institute (CSIR), Durgapur, India 3 National Institute of Technology, Durgapur, India

Abstract—Machine locomotion using wheels, tracks or legs is common where as generating locomotion in a limbless, wheelless system is more challenging. Wheeled locomotion and legged locomotion have already been studied by many researchers in detail. On the contrary the limbless locomotion has drawn very limited degree of interest. In limbless locomotion (of a serpent) the cyclic changes in the body shape allow it to locomote. This paper considers the development of a hyper redundant un-tethered serpentine robot for implementation of various serpentine and non serpentine gaits. A highly optimized 3D model of the robot was prepared and exported to CAE environment for kinematic and dynamic analysis. Parameters so obtained through simulation were implemented on the robot for demonstration of serpentine locomotion.

CSERP-X is an experimental serpentine robot developed at CMERI (CSIR) for experimentation with serpentine gaits and locomotion [6].

Keywords: Serpentine Robot Locomotion, Hyper redundant, Mobile Robot. I.


Fig. 1. Experimental serpentine robot CSERP-X [6]

The first qualitative research on biologically inspired serpentine robot was done by Hirose [1]. Early works of Burdick and Chirikjian on hyper redundant robot are worth mentioning [2]. Since then many multi segmented articulated serpentine robots have been attempted by researchers for implementation of crawling gaits. Design of a serpentine robot is principally guided by gait implementation philosophy. Some of them use wheels, tracks, legs or other means for locomotion while others rely solely on body undulation. In most of the cases the segments are connected with revolute joints, but prismatic joints [3] are also employed. These joints may be active or passive. In general, revolute joints were considered for yaw and pitch, however a few models were also developed using roll DOF [4][5].

There are six body segments, one head and one tail. Body segments are identical in shape and size. Head and tail segment are slightly different. Head segment houses some sensors and the tail houses a few other components, for example, battery charging point and

Locomotion of a serpent is due to cyclic changes in the body shapes (gaits). These body shapes most often can be simulated by two body waves on two orthogonal planes passing through snake’s body. Again these body waves are functions of joint orientations in case of an articulated serpentine robot. Mathematical models of the joint orientations were verified in simulation environment before implementing them into the physical prototype. Moreover, the parameters of the mathematical model were fine tuned in simulation for optimal gait performance. II.

Overall length

807 mm

Number of Segments


Number of joint actuators

7 R/C servos

Joint actuator torque

9 kg-cm

Joint to joint

96 mm

Segment cross section

70 mm x 70 mm

Overall weight (Including battery)

1.26 kg

Obstacle detection

IR based

On board micro controller

PIC 16F84A

Power source:



Servo actuators


μ-controller and other electronics


Camera, video transmitter & light



experimental system. To reduce computational load the simulation model was made much simpler as compared to the actual design of the serpentine robot which is further depicted in Fig. 2. While doing so, special attention was given to the overall shape and size and other critical dimensions. As the ACIS geometries were needed for the simulation environment, it converts curves and curved geometries with a set of polygons or planar surfaces (faceting). Optimized geometry was carefully prepared to get better simulation performance without sacrificing realistic simulation results.

TABLE I: A BRIEF SPECIFICATION OF CSERP-X Overall system has 7 DOF with seven joints actuated by seven R/C servo actuators. The adjacent actuators of the robot are perpendicular to each other and each joint has angular freedom of ±90°. Joint pitch on any plane is 192 mm. Four of the joints actuators have horizontal axes and three have vertical axes. Some gaits utilize all four sides of body segments. The segment cross section was chosen as squire so that the robot shows uniformity in all state of its gait. Variation in dorsal and ventral shape would lead to anomalous behaviour in various stages of those gaits which utilize all the four faces of the body segment such as lateral roll. The overall weight of the system includes servos, battery, electronics, cabling and weight of the body segments. If the robot is 3

sleeved with a skin, total volume is about 3675 cm and 3

the overall robot density 0.34 g/cm . I.

Fig. 2. The head segment of the experimental serpentine robot (a) as designed, (b) as built, and (c) as prepared for simulation environment and the body segment of the snake robot (d) as designed, (e) as built, and (f) as prepared for simulation environment.


The design process is iterative in nature and involves simulation in CAE environment [7]. If a design does not work in simulation, most likely it will fail on implementation. A highly optimized 3D model of the robot was prepared and exported to CAE environment for kinematic and dynamic analysis. The study of animal locomotion is typically considered to be a sub-field of biomechanics. Gray used pegs to measure serpentine reaction forces [8][9]. Hirose used strain gauges and supports to measure force in snake locomotion [1]. Biomechanics of scale and muscle in rectilinear mode of snake locomotion was studied in [10].

C. Friction Friction plays a very important role in locomotion simulation. To achieve meaningful locomotion sometimes directional friction helps to a great extent. A biological snake enjoys certain advantages as far as directional friction is concerned.

A. Integration Technique CAE solvers use numerical methods to solve dynamic simulation problems. The solution of the motion of mechanical systems is governed by differential equations arising from mechanics principles and the solution is carried out by numerical integration. While many numerical integration methods exist, the KuttaMerson integration technique [11], which is considered to be fairly accurate, was used. At each integration step, the solver checks its computation results to see if the model satisfies the error bounds. Reducing time step substantially reduces error. Maximum time step for all our simulations was chosen to be 0.001s; however, the solver was allowed to refine it on the run to remain within error bounds.

Fig. 3. Sawtooth corrugation on the head and tail segment of the experimental serpentine robot

This is also termed as frictional anisotropy. Particular orientation and overlap of serpentine scales contributes to achieve directional friction and by virtue of this a snake can easily slide forward than sidewise. On a serpentine robot it can be achieved in many ways. Many serpentine robots use wheels to utilize this directional property. For example, Snakey [2], SR-2 [12] and ACM series robots [13][14][15] use wheels to achieve low forward friction and high lateral friction. However, in simulation environment it has to be modeled. For example in case of Inchworm locomotion the dynamic coefficient of friction (μ) was modeled as:

B. Geometry

IF (velocity of Tail w.r.t. Surface is negative) THEN μ = 0.8 ELSE μ = 0.5 IF (velocity of Head w.r.t. Surface is negative) THEN μ = 0.8 ELSE μ = 0.5

The simulation model of the serpentine robot was made using basic 3D model data used for the design of the


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 In general a value of 0.5 was considered for all other purpose. To impart directional friction sawtooth corrugation on the bottom surface of the Head and Tail segment of the experimental serpentine robot was provided (Fig. 3b).

These two orthogonal sinusoids are parametric to joint position and time dependent. They are made structurally similar for easy deployment and they are deployed in piecewise manner and termed as Joint Orientation Functions or JOFs.

D. Kinematic Model Here D, A and T are offset, amplitude and period of joint Fig. 4 may be referred for better understanding of kinematic structure of the robot. Drawing similarity with ISO8855 convention the axes were defined, which dictates that X-axis pointing straight forward, the Y-axis to the left and the Z-axis pointing upwards. The rotational degrees of freedom with respect to the axes are denoted with φ (roll), θ (pitch) and ψ (yaw) respectively. The body segments are named as: Head – B1 – B2 – B3 – B4 – B5 – B6 – Tail. Each segment (link) is joined with the adjacent one with the help of a revolute joint. There are seven revolute joints altogether for the eight links. The H-Plane (for yaw) and V-Plane (for pitch) are the same as dextro-sinistral and dorso-ventral planes of a biological serpent respectively.

oscillation respectively. The suffix θ and ψ denotes parameters of horizontal and vertical joints respectively. Vertical sinusoid contributes to the lift and proper ground interaction which is essential for this robot to propel. The parameters α0 and δα are initial phase (epoch) and phase lag of H-Plane JOFs. Similarly β0 and δβ represents the same for the V-Plane JOFs. ‘i’ and ‘ j’ are the joint positions numbered from the head side on their respective planes. All the seven revolute joints are constrained with JOFs and considering spatial orientation of the robot, four of which have axes on the horizontal plane (viz. H1, H2, H3 and H4) and three of them have axes on vertical plane (V1, V2, and V3) as shown in the Fig. 4. E. CAE Environment Various studies were carried out to make the serpentine model locomote in simulation environment.

Fig. 4. Kinematic model of the experimental serpentine robot showing coordinate system and naming convention of segments and joint constraints (green)

Each revolute joint has a play of 0° to 180° and in straight configuration they are at 90°. For a biological snake the range of movement between each joint is limited to between 10° and 20° for rotation from side to side (yaw), and to a few degrees of rotation when moving up and down (pitch) [16]. A large total bend of snake body is still possible because of the high number of vertebrae. A very small rotation (roll) is also possible around the direction along the snake’s body. The experimental serpentine robot does not have any roll freedom as it does not contribute significantly in gait generation.

Fig. 5. Experimentation with gaits in simulation environment. The joint constraints are actuated with joint orientation functions to produce desired locomotion. Contact, friction and restitution were modelled between the surface and the simulation geometry

Locomotion of the serpentine robot was achieved with the generation of body waves by the sinusoidal actuation of joints. Two separate sets of sinusoidal actuators were used to simulate waves on both horizontal and vertical plane:

ψ i = DΨ + AΨ sin(2π t / Tψ + α 0 − ( i − 1).δα); i =1 to 3

There is one-is-to-one correspondence between the experimental serpentine robot and the simulation model of the robot as the model geometry was prepared in line with actual robot. In the Fig. 5 the joint locations shown in green are constrained with the mathematical model of the robot kinematics. As such all the joint constraints are made responsive to corresponding joint orientation functions and mathematical model used for gait implementation was verified in simulation environment prior to deployment on the robot.


Pitch, θ j = Dθ + Aθ sin(2π t / Tθ + β 0 − ( j −1).δβ); j = 1 to 4





I. LOCOMOTION Various serpentine and non serpentine locomotion gaits as categorised in Fig. 6 were simulated and implemented. These gaits were not only inspired by snakes but can also be extended to mimic other interesting gaits such as caterpillar, inchworm and tail flapping of fish for example.


θ - Functions

ψ - Functions

For all locomotion types the basic joint orientation function remains same while their parameter changes. These parameters are genetic imprints that determine what gait the robot performs. The value of the parameters as presented in this paper are optimal and can be further adjusted or fine tuned depending upon serpentine robot design, actuator characteristics and environmental parameters.












A slight undulation on the V-Plane (±4°) is provided to simulate proper ground reaction which will help it to propel forward. This undulation can be used to simulate ‘sinus lift‘, a term coined by Hirose [1] where the lateral extremities of the serpentine body get lifted above the ground at high speed of locomotion. For straight heading the offset parameter (Dψ) is set at 90°.

Fig. 6. Various serpentine robot locomotion types simulated and implemented.

These issues have been critically examined through experimental serpentine robot specially designed and extensively used to compare various gaits generated through simulation. Due to space constraint only Lateral Undulation and Caterpillar locomotion are presented here as cases of study. However, [17] may be referred for locomotion videos related to the project.

Fig. 7. Simulation of gaits for lateral undulation locomotion

A. Lateral Undulation It is a continuous sliding motion achieved by swinging the body segments sidewise i.e. on HPlane. For values of δα∈(0,180) the body wave travels from rear to front as in the case of caterpillar locomotion. For values of 0 and 180° the body wave is stationary. On the H-Plane undulation a phase difference of 240° suggest that the body wave moves from front to rear. It may be noted that V-Plane undulation is a stationary wave with δβ =180° which creates two alternating pairs of ground support points.

Fig. 8. JOF Plots for H-Plane undulation (top) and that of V-Plane undulation (bottom)



Fig. 9. Sequence showing gaits of lateral undulation locomotion at different times

B. Caterpillar In this mode of locomotion pure sinusoidal wave travels through the length of the body on the VPlane. The direction of motion of this wave is from rear to front while the robot moves forward.

Fig. 13. Sequence showing caterpillar locomotion of the robot

JOF parameters were further adjusted on implementation wherever felt necessary. For the sake of performance comparison all the gaits were simulated with a period of 4 seconds. Again simulation time and real time are different. In simulation environment it takes much longer time to simulate this 4 seconds activity depending upon many factors, for example, simulation time step, computational power. JOF plots are drawn from 1s to 5s. In the first 1s the plots are distorted due to gait transition.



ψ - Functions Aψ



α -

θ - Functions δα




β0 0

δβ 90°

The serpent moves without sliding any one of the segments on the ground. Vertical servos are not actuated however, their offset values (Dψ) can be adjusted to steer the serpentine robot left or right.



This paper thus presents an approach to gait implementation technique through simulation. Experimentation with serpentine gaits becomes easy and versatile in simulation environment. We can concentrate on a few JOF parameters while experimenting with gaits. JOFs can easily be programmed into a robot’s microcontroller having its parameters known through simulation. Moreover it provides with a good insight into the techniques of gait implementation. However, what conclusion we can draw out of the simulation? How far are they valid? To what extent are they similar to that of a real situation? – are some questions that need to be answered. Simulation results can only be validated through implementation on a physical system. The gait parameters generated through simulation have been successfully tested on the experimental serpentine robot. Due to existence of one-is-to-one correspondence between the simulation model and the experimental serpentine robot, gait

Fig. 10. Simulation of Gaits for Caterpillar locomotion


INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY & CREATIVE ENGINEERING (ISSN:2045-8711) VOL.1 NO.3 MARCH 2011 Experimental Biology 23, 101-120, Published by Company of Biologists, 1946. [10] Gray, J., Lissmann, H.W., “The kinetics of locomotion of the grass-snake,” Journal of Experimental Biology 26, 354-367, Published by Company of Biologists, 1950. [11] Aubin, R., Blazevic, P., Clement, B., Guyvarch, J.P., “Simulation and Design of a Snake-Like Robot Based on a Bio-Inspired Mechanism,” The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, BioRob2006. February 20-22, 2006 Page(s):220- 225.

experimentation becomes straightforward. Also this approach allows us to implement varieties of gaits on a single design. Any snake robot must have the capability to move within a confined area and traverse all terrains that is not possible by conventional wheeled or walking robots. Though serpentine locomotion has its inherent limitations, snake like robots can have tremendous application potential in surveillance, inspection of pipe lines, search and rescue operation after natural disaster and in many more similar situations.

[12] Fox, L., "Numerical Solutions of Ordinary and Partial Differential Equations," Palo Alto: Addison-Wesley, 1962, pp.24-25. [13] Wiriyacharoensonthorn, P., Laowattana, S., “Analysis and Design of A Multi-Link Mobile Robot (Serpentine),” IEEE IClT’02, Bangkok, THAILAND. [14] HIROSE, S., MORI, M., "Biologically Inspired Snake-like Robots," Proceedings of the 2004 IEEE International Conference on Robotics and Biomimetics, August 22 - 26, 2004, Shenyang, China.

Although there are several research efforts in this particular field, very few serpentine robots have been successfully demonstrated beyond experimental stage and none of them has any commercial viability till date. This indicates the need for further research in this direction and there is ample scope of improvement in the field of locomotion and control of highly articulated mechanisms.

[15] Yamada, H., Mori, M., Hirose, S., “Stabilization of the head of an undulating snake-like robot,” Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems San Diego, CA, USA, Oct 29 - Nov 2, 2007.


[16] Yu, S., Ma, S., Li, B., Wang, Y., “An Amphibious Snake-like Robot: Design and Motion Experiments on Ground and in Water,” Proceedings of the 2009 IEEE International Conference on Information and Automation June 22 -25, 2009, Zhuhai/ Macau, China. [17] Buchot, R., Ed, Snakes: A Natural History, Sterling Publishing, New York, ISBN 0-8069-0654-5, 224 pp, 1994. [18] Serpentine Robot, Central Mechanical Engineering Research Institute.

Authors gratefully acknowledge the contribution of all the involved researchers of Central Mechanical Engineering Research Institute (CSIR), Durgapur. The project was funded by Council of Scientific & Industrial th Research, New Delhi under XI Plan Projects. REFERENCES

[1] Hirose, S., “Biologically Inspired Robots: Snake-Like Locomotors and Manipulators,” Oxford, U.K.: Oxford Univ. Press, 1993. [2] Burdick, J. W., "Robots That Crawl, Walk, and Slither," Engineering & Science, Summer 1992. [3] Kimura, H., Hirose, S., “Development of Genbu: Active wheel passive joint articulated mobile robot,” Proceedings of the 2002 IEEE/RSJ Intl Conference on Intelligent Robots and Systems EPFL, Lausanne, Switzerland. October 2002. [4] Ye, C., Ma, S., Li, B., Liu, H., Wang, H., "Development of a 3D Snake-like Robot: Perambulator-II," Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation, August 5 - 8, 2007, Harbin, China. [5] Kamegawa, T., Yamasaki, T., Igarashi, H., Matsuno, F., “Development of The Snake-like Rescue Robot "KOHGA"," Proceedings of the 2004 IEEE International Conference on Robotics & Automation, New Orleans, LA April 2004. [6] Maity, A., Mazumder, S., Ghosh, S., "An Experimental Hyper Redundant Serpentine Robot," 2010 IEEE International Conference on Systems, Man and Cybernetics (SMC-2010), PP. 3180-3185, Oct 10-13, 2010, Istanbul. [7] MSC.visualNastran 4D 2004, Copyright © 1996-2004. MSC Software, [8] Gray, J., “The mechanism of locomotion in snakes,” Journal of




IJITCE March 2011  

International Journal of Innovative Technology and Creative Engineering March 2011 Issue No.1 Vol.3

IJITCE March 2011  

International Journal of Innovative Technology and Creative Engineering March 2011 Issue No.1 Vol.3