Bhattacharyya / Gandhi / Sharma Advanced Computational and Communication Paradigms

Proceedings of International Conference on ICACCP 2017, Volume 1
1. Auflage 2018
ISBN: 978-981-10-8240-5
Verlag: Springer Nature Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 475, 608 Seiten

Reihe: Lecture Notes in Electrical Engineering

The book titled Advanced Computational and Communication Paradigms: Proceedings of International Conference on ICACCP 2017, Volume 1 presents refereed high-quality papers of the First International Conference on Advanced Computational and Communication Paradigms (ICACCP 2017) organized by the Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology, held from 8- 10 September 2017. ICACCP 2017 covers an advanced computational paradigms and communications technique which provides failsafe and robust solutions to the emerging problems faced by mankind. Technologists, scientists, industry professionals and research scholars from regional, national and international levels are invited to present their original unpublished work in this conference. There were about 550 technical paper submitted. Finally after peer review, 142 high-quality papers have been accepted and registered for oral presentation which held across 09 general sessions and 05 special sessions along with 04 keynote address and 06 invited talks. This volume comprises 65 accepted papers of ICACCP 2017.

Dr. Siddhartha Bhattacharyya [FIETE, SMIEEE, SMACM, SMIETI, LMCSI, LMOSI, LMISTE, MIET (UK), MIAENG, MIRSS, MIAASSE, MCSTA, MIDES, MIISIP] did his Bachelors in Physics, Bachelors in Optics and Optoelectronics and Masters in Optics and Optoelectronics from University of Calcutta, India in 1995, 1998 and 2000 respectively. He completed PhD in Computer Science and Engineering from Jadavpur University, India in 2008. He is the recipient of the University Gold Medal from the University of Calcutta for his Masters. He is the recipient of the coveted Adarsh Vidya Saraswati Rashtriya Puraskar in 2016, Distinguished HoD and Distinguished Professor wards conferred by Computer Society of India, Mumbai Chapter, India in 2017 and Bhartiya Shiksha Ratan Award conferred by Economic Growth Foundation, New Delhi in 2017.  He received the NACF-SCRA, India award for Best Faculty for Research in 2017. He received Honorary Doctorate Award (D. Litt.) from The University of South America in 2017. He is also the recipient of the South East Asia Regional Computing Confederation (SEARCC) International Digital Award ICT Educator of the Year at Colombo, Sri Lanka in 2017. He is currently the Principal of RCC Institute of Information Technology, Kolkata, India. In addition, he is also serving as the Dean (Research and Development and Academic Affairs) of the institute. He is a co-author of 4 books and the co-editor of 8 books and has more than 170 research publications in international journals and conference proceedings to his credit. He has got a patent on intelligent colorimeter technology. Dr. Tapan K Gandhi is currently working as Assistant Professor in the Department of Electrical Engineering, IIT Delhi and also research affiliate to MIT, USA. He received his Ph.D. fellowship from PROJECT Prakash (MIT, USA) and obtained his Ph.D. from IIT Delhi in Biomedical Engineering. Following his Ph.D., he has spent 3+ years as postdoctoral research scientist at MIT, USA. Dr. Gandhi was also awarded an INSPIRE Faculty in the engineering & technology category of the Department of Science & Technology, Govt. of India. His research expertise spans from computational neuroscience, brain imaging, assistive technology, bio-medical instrumentation, machine learning, cognitive computing to artificial intelligence. He has published papers in top ranking journals like Nature, PNAS, Current Biology, PloS Biology. He has more than 60 publications in International journals and conference proceedings. He is PI & Co-PI of projects from industry as well as Govt. of India organizations. Dr. Kalpana Sharma is currently Professor and Head of Computer Science and Engineering Department at Sikkim Manipal Institute of Technology, Sikkim Manipal University. She has pursued her B.E. from National Institute of Technology, Silchar, M.Tech from Indian Institute of Technology, Khargpur and Ph.D. from Sikkim Manipal University. She has over 19 years of experience in academics. She is currently guiding two research scholars in the allied fields. She has 29 research publications in various national and international journals and conferences. Her area of interest includes security in wireless sensor networks (WSN) and real time systems. She has authored a book in WSN. She has executed many funded projects in the fields related to security in WSN and real time task scheduling. Dr. Paramartha Dutta, born 1966, is B.Stat (Hons.) (ISI, Calcutta), M. Stat (ISI, Calcutta), M. Tech (Computer Science; ISI, Calcutta) and Ph.D. (Engineering; IIEST, Shibpur), SMIEEE, SMACM, SMIACSIT, FIETE, FIE, FOSI, LMISTE, LMIUPRAI, LMISCA having academic experience of about 23 years. He is presently a Professor in the Department of Computer and System Sciences, Visva Bharati University. He has co-authored eight books and has also seven edited book to his credit. He has published more than 200 papers in various journals and conference proceedings, both international and national as well as several book chapters in edited volumes of reputed international publishing house like Elsevier, Springer-Verlag, CRC Press, John Wiley, etc. Dr. Dutta has guided four scholars and is guiding six for their Ph.D. Dr. Dutta has served as guest editor of special volumes of international journals published by publishers such as Elsevier, Springer, etc.    

Autoren/Hrsg.

Bhattacharyya, Siddhartha

Gandhi, Tapan

Sharma, Kalpana

Dutta, Paramartha

Inhaltsverzeichnis

1;Preface;7
2;Contents;9
3;About the Editors;15
4;Design of Low-Noise Amplifier with High CMRR for Sensor Application;17
4.1;1 Introduction;17
4.2;2 Available Topologies for Low-Noise Amplifier;17
4.2.1;2.1 OLN Topology;18
4.2.2;2.2 CFN Topology;18
4.2.3;2.3 MIFN Topology;19
4.3;3 Noise Efficiency Factor (NEF);20
4.4;4 Differential Difference Amplifier (DDA);20
4.4.1;4.1 Reported Works on DDA;21
4.5;5 Simulation Result;22
4.5.1;5.1 AC Response;22
4.5.2;5.2 CMRR and Noise Analysis;23
4.6;6 Conclusion;24
4.7;References;25
5;Performance Improvement of WiMAX (IEEE 802.16d) Using Combined RS–CC Forward Error Channel Coding Technique;27
5.1;1 Introduction;27
5.2;2 Simulation Model Implemented;28
5.3;3 Results and Discussion;28
5.4;4 Conclusion and Future Directions;33
5.5;References;34
6;A Hybrid Control Algorithm for Extraction of Voltage Harmonics to Mitigate Power Quality Problems Using UPQC;35
6.1;1 Introduction;35
6.2;2 Mathematical Model of Control Techniques for UPQC;36
6.2.1;2.1 An Algorithm to Generate Pulses of Series Converter;36
6.2.1.1;2.1.1 Under Normal Steady State Condition;37
6.2.1.2;2.1.2 Under Voltage Sag Condition of the AC Mains;38
6.2.1.3;2.1.3 Under Voltage Swell Condition of the AC Mains;39
6.2.2;2.2 An Algorithm to Generate Pulses of Shunt Converter;39
6.3;3 Real Results and Discussion;41
6.3.1;3.1 Performance of Hybrid Control Algorithm for Series Converter of UPQC Under Various Conditions of AC Mains;41
6.3.2;3.2 Performance of Shunt Control Algorithm Under Various Conditions of AC Mains;42
6.3.3;3.3 Performance Analysis of Harmonics Spectrum;42
6.3.4;3.4 Active and Reactive Power Sharing;43
6.4;4 Conclusion;45
6.5;References;46
7;Comparative Performance of the Various Control Techniques to Mitigate the Power Quality Events Using UPQC;47
7.1;1 Introduction;47
7.2;2 IGBT Gate Firing Techniques of UPQC;48
7.2.1;2.1 Techniques to Fire the Gate of IGBT-Based Series Converters of UPQC;48
7.2.1.1;2.1.1 Power Angle Control Technique;48
7.2.1.2;2.1.2 Quadrature Angle Technique;49
7.2.1.3;2.1.3 Zero and 180° Angle Techniques;49
7.2.2;2.2 Technique to Fire the Gate of IGBT-Based Shunt Converters of UPQC;50
7.2.2.1;2.2.1 Control Theory for IGBT Shunt Converter;50
7.3;3 Results and Discussions;52
7.4;4 Conclusion;55
7.5;References;55
8;A Mobile Health Intervention to Support TB Eradication Programme for Adherence to Treatment and a Novel QR Code Based Technique to Monitor Patient–DOTS Provider Interaction;57
8.1;1 Introduction;57
8.2;2 Literature Survey;57
8.3;3 Methodology;58
8.4;4 TB Track Application;59
8.4.1;4.1 TB Patient Mobile App;59
8.4.2;4.2 TB Track DOTS Provider Mobile App;64
8.4.3;4.3 TB Track Web Application;66
8.4.4;4.4 TB Track Database;67
8.4.5;4.5 TB Track SMS Communication;68
8.5;5 Pilot Testing and Discussion;68
8.5.1;5.1 Outcome;68
8.6;6 Conclusion;69
8.7;Acknowledgements;69
8.8;References;69
9;Modeling and Behavioral Simulation of PID-Controlled Phase-Locked Loop;71
9.1;1 Introduction;71
9.1.1;1.1 Brief Overview of PLL;71
9.2;2 Related Works;72
9.3;3 Objective and Methodology;73
9.4;4 Theoretical Estimation for the PLL Components;73
9.4.1;4.1 Estimation for PFD;73
9.4.2;4.2 Estimation for VCO;74
9.4.3;4.3 Estimation for LF;74
9.4.4;4.4 Estimation for FD;75
9.4.5;4.5 Estimation for PID Controller;75
9.4.6;4.6 The System TF of the Model;75
9.4.6.1;4.6.1 System TF with LF;75
9.4.6.2;4.6.2 System TF with PID Controller;76
9.5;5 Simulations;76
9.5.1;5.1 Simulation for Settling Time;76
9.5.2;5.2 Simulation for PM and System BW;78
9.6;6 Results and Discussion;78
9.7;7 Conclusion;81
9.8;Acknowledgements;81
9.9;References;81
10;Deviant Calcium Channels: Role in Ventricular Arrhythmias—A Computational Study on Human Ventricular Tissue;83
10.1;1 Introduction;83
10.2;2 Methods and Materials;85
10.2.1;2.1 General;85
10.2.2;2.2 2D Array of Ventricular Cell with Gap Junction;85
10.2.3;2.3 Preparation of Failure Calcium Channels;86
10.3;3 Results and Discussions;87
10.4;4 Conclusions;91
10.5;References;92
11;Modeling and Simulation of 1/f Noise During Threshold Switching for Phase Change Memory;93
11.1;1 Introduction;93
11.2;2 Modeling and Simulation of 1/F Noise in Threshold Switching;94
11.3;3 PCM Transient Simulation with 1/f Noise Fluctuations;96
11.4;4 Effect of PCM Device Scaling on Threshold Switching Considering 1/f Noise;97
11.5;5 Conclusion;99
11.6;References;99
12;Pilot Subcarrier Based Channel Estimation in OFDM System;100
12.1;1 Introduction;100
12.2;2 Related Work;100
12.3;3 Pilot Patterns;101
12.4;4 Pilot Symbol M-ary Modulation;102
12.4.1;4.1 Proposed Algorithm;103
12.5;5 Simulation Results;104
12.6;6 Conclusion;106
12.7;References;106
13;Spectrum Allocation in Cognitive Radio Networks—A Centralized Approach;108
13.1;1 Introduction;108
13.2;2 Related Works;109
13.3;3 Spectrum Sharing Mechanism for CRN;109
13.3.1;3.1 System Model;109
13.3.2;3.2 Sharing Mechanism;110
13.4;4 Performance Evaluation;111
13.5;5 Conclusion;116
13.6;References;116
14;Mixing Test Set Generation for Bridging and Stuck-at Faults in Reversible Circuit;117
14.1;1 Introduction;117
14.2;2 Background;118
14.2.1;2.1 Reversible Logic Circuits;118
14.2.2;2.2 Fault Models in Reversible Circuit;118
14.3;3 Proposed Method;120
14.3.1;3.1 Fault Description List;120
14.3.2;3.2 Test Set Generation Algorithm for Single-Input Bridging Fault;120
14.3.3;3.3 Test Set Generation Algorithm for Single-Input Stuck-at Fault;122
14.4;4 Experimental Results;123
14.5;5 Conclusion;125
14.6;References;125
15;A Comparative Study of Biopotentials Acquired from Left and Right Hands of Human Subjects;126
15.1;1 Introduction;126
15.2;2 Acquisition of Biopotentials;127
15.3;3 Analysis of Acquired Potentials;128
15.3.1;3.1 Raw Biopotential Signals;128
15.3.2;3.2 Bias of the Biopotential Signals;130
15.3.3;3.3 Differential Bias (diff);131
15.4;4 Conclusions;132
15.5;5 Declaration;133
15.6;References;133
16;Real-Time Bottle Detection Using Histogram of Oriented Gradients;134
16.1;1 Introduction;134
16.2;2 Problem Statement;135
16.3;3 System Overview;135
16.3.1;3.1 Database;135
16.3.2;3.2 Preprocessing;136
16.3.3;3.3 HOG Feature Extraction;136
16.3.4;3.4 Sliding Window;138
16.4;4 Experimental Results;139
16.5;5 Conclusions;140
16.6;References;140
17;Global Scenario of Solar Photovoltaic (SPV) Materials;142
17.1;1 Introduction;142
17.2;2 Classification;142
17.3;3 Conventionally Used Material Technologies;143
17.3.1;3.1 Crystalline Material;143
17.3.1.1;3.1.1 Monocrystalline Silicon;143
17.3.1.2;3.1.2 Polycrystalline Silicon;143
17.3.1.3;3.1.2 Polycrystalline Silicon;143
17.3.1.4;3.1.3 Gallium Arsenide (GaAs);144
17.3.2;3.2 Thin-Film Material;145
17.3.2.1;3.2.1 Amorphous Silicon;145
17.3.2.2;3.2.2 Cadmium telluride (CdTe or CdS/CdTe);145
17.3.2.3;3.2.3 Copper Indium Gallium Diselenide (CIS/CGS/CIGS);146
17.4;4 Emerging PV Technologies;146
17.4.1;4.1 Organic/Polymer Material;146
17.4.2;4.2 Hybrid Technology;147
17.4.3;4.3 Quantum Dots;147
17.5;5 Conclusion;147
17.6;References;148
18;A 50 MHz–4 GHz Low-Noise Amplifier for Wideband Applications;150
18.1;1 Introduction;150
18.2;2 LNA Topologies;151
18.3;3 Proposed Circuit;153
18.4;4 Simulation Results;154
18.5;5 Conclusions;155
18.6;Acknowledgements;156
18.7;References;156
19;DEM Reconstruction for Mizoram Area Using CARTOSAT Data and Preserving it by Cloud Computing Method;157
19.1;1 Introduction;157
19.2;2 Objective of the Study;158
19.3;3 Terrain Characteristics of the Mizoram;158
19.4;4 Methodology;159
19.4.1;4.1 DEM Generation Using OPTICAL Data;159
19.4.2;4.2 DEM Generation Using Field GCP;159
19.4.3;4.3 Mosaic;160
19.4.4;4.4 DEM Generation Using RADARSAT 1 Data;160
19.4.5;4.5 Data Fusion or Merging;160
19.5;5 Architecture of the New Application;161
19.6;6 Flow Diagram for the Application;162
19.7;7 Result and Discussion;162
19.8;8 Conclusions;163
19.9;Acknowledgements;164
19.10;References;164
20;Statistical Viability Analysis and Optimization Through Gate Sizing;165
20.1;1 Introduction;165
20.2;2 False Path Detection;166
20.2.1;2.1 False Path;166
20.2.2;2.2 Static Sensitization;166
20.2.3;2.3 Dynamic Sensitization;167
20.2.4;2.4 Viability Analysis;167
20.3;3 Gate Sizing;169
20.4;4 Results;169
20.5;5 Conclusion;171
20.6;References;171
21;A Decision Support System in Healthcare Prediction;172
21.1;1 Introduction;172
21.2;2 Background Study of Decision Support System (DSS) in Healthcare Prediction;174
21.2.1;2.1 Information Gain;175
21.2.2;2.2 Area Under the ROC Curve (AUC ROC);175
21.3;3 Proposed Healthcare Decision Support System;177
21.3.1;3.1 Experimental Setup of Proposed DSS;179
21.3.2;3.2 Implementation of Decision Support System;179
21.3.3;3.3 Comparative Analysis;181
21.4;4 Conclusion and Future Direction of Work;182
21.5;References;182
22;Random Forests in the Classification of Diabetic Retinopathy Retinal Images;184
22.1;1 Introduction;184
22.2;2 Related Work;185
22.3;3 Proposed Methodology;185
22.3.1;3.1 Feature Selection;186
22.3.2;3.2 Random Forest Classifier;188
22.3.3;3.3 Algorithm of Random Forest Classifier;188
22.4;4 Results and Analysis;189
22.5;5 Conclusion;191
22.6;References;191
23;Performance Evaluation of M2M and H2H Communication Coexistence in Shared LTE: A DLMS/COSEM-Based AMI Network Scenario;193
23.1;1 Introduction;193
23.2;2 Related Work;194
23.3;3 AMI Component Models in NS-3;195
23.4;4 Experiments and Evaluation;196
23.4.1;4.1 The Simulation Scenario in NS-3;196
23.4.2;4.2 Simulation Results and Analysis;197
23.5;5 Conclusions;200
23.5.1;5.1 Future Work;201
23.6;References;201
24;Smart Device for Ensuring Women Safety Using Android App;202
24.1;1 Introduction;202
24.2;2 Literature Review;202
24.2.1;2.1 Problems in Existing System;203
24.2.2;2.2 Motivation;203
24.2.3;2.3 Objectives;204
24.3;3 Materials and Methods;204
24.4;4 Results and Discussion;205
24.5;5 Conclusion;212
24.6;Acknowledgements;212
24.7;References;212
25;Characteristics Analysis of Si0.5Ge0.5 Doping-Less PNPN TFET;214
25.1;0 1 Introduction;214
25.2;0 2 Device Structure and Simulation Parameters;215
25.3;0 3 Results and Discussion;216
25.4;0 4 Conclusion;218
25.5;References;219
26;Logical Implication to Reduce Run Time Memory Requirement and Searches During LZW Decompression;220
26.1;1 Introduction;220
26.2;2 Notation and Propositions;221
26.2.1;2.1 Complement Operation;221
26.2.2;2.2 Logical Implication for Encoding and Decoding Patterns;222
26.3;3 The MSED Technique;223
26.3.1;3.1 Modified Dictionary of LZW Compressor;223
26.3.2;3.2 Modified Dictionary of LZW Decompressor;223
26.3.3;3.3 Example of MSED Technique;224
26.4;4 Improvements in Standard LZW Algorithm;226
26.5;5 Conclusion;227
26.6;Acknowledgements;227
26.7;References;227
27;Detection of Schizophrenia Disorder from Ventricle Region in MR Brain Images via Hu Moment Invariants Using Random Forest;229
27.1;1 Introduction;229
27.2;2 Database;230
27.2.1;2.1 Image Database;230
27.3;3 Segmentation;230
27.3.1;3.1 Multiplicative Intrinsic Component Optimization (MICO);230
27.4;4 Validation Measures;231
27.5;5 Hu Moment Invariants;231
27.6;6 Random Forest Classifier;232
27.7;7 Results and Discussion;232
27.8;8 Conclusions;237
27.9;Informed consent;237
27.10;References;238
28;Non-invasive Anaemia Detection by Analysis of Conjunctival Pallor;240
28.1;1 Introduction;240
28.2;2 Related Work;240
28.3;3 Objective;242
28.4;4 Proposed Solution;242
28.5;5 Research Methodology;243
28.5.1;5.1 Research Design;243
28.5.2;5.2 Conjunctival Sample Collection;243
28.5.3;5.3 Image Processing;243
28.5.4;5.4 Laboratory Haemoglobin Measurement;244
28.6;6 Results;244
28.7;7 Limitations;245
28.8;8 Conclusion and Future Scope;246
28.9;References;246
29;Design and Implementation of Portable and Compact Human Heartbeat Rate Monitoring System;248
29.1;1 Introduction;248
29.2;2 Related Works;249
29.3;3 Proposed Methodology;250
29.4;4 Circuit Implementation;251
29.4.1;4.1 The Sensor Circuit;251
29.4.2;4.2 The Filter and Amplifier Circuit;251
29.4.3;4.3 The Comparator Circuit;252
29.4.4;4.4 Interfacing and Processing;252
29.5;5 System Calibration;253
29.6;6 Result and Discussion;254
29.7;7 Conclusion;255
29.8;Acknowledgements;255
29.9;References;255
30;Implementation of a Secure and Efficient Routing Algorithm for Vehicular Ad Hoc Networks;257
30.1;1 Introduction;257
30.1.1;1.1 Vehicular Ad Hoc Networks;257
30.1.2;1.2 Basic Characteristics;257
30.2;2 Related Work;258
30.3;3 Proposed Algorithm;259
30.4;4 Simulation Environment;261
30.4.1;4.1 Simulation Results;262
30.5;5 Conclusion;264
30.6;References;264
31;Design and Analysis of Optimized Hybrid Active Power Filter for Electric Arc Furnace Load;266
31.1;1 Introduction;266
31.2;2 System Modeling;267
31.2.1;2.1 Modeling of Electric Arc Furnace;267
31.2.2;2.2 Vigorous Nature of Electric Arcs;267
31.2.3;2.3 Design of Hybrid Filter;268
31.2.4;2.4 Controller Design;269
31.2.5;2.5 Objective Function;269
31.3;3 Optimization Technique;270
31.3.1;3.1 Genetic Algorithm;270
31.3.2;3.2 Particle Swarm Optimization;270
31.3.3;3.3 Harmony Search Algorithm;270
31.4;4 Results and Discussion;271
31.4.1;4.1 Simulation Result of Shunt Hybrid Active Filter;271
31.5;5 Conclusion;273
31.6;References;273
32;To Detect the Influencers in a Dynamic Co-authorship Network Using Heat-Diffusion Model;275
32.1;1 Introduction;275
32.2;2 The Problem Statement;276
32.3;3 The Proposed Method;276
32.3.1;3.1 Heat Diffusion in Initial Static Graph;277
32.3.2;3.2 Heat Diffusion in Dynamic Evolving Graph;278
32.4;4 The Experimental Results;280
32.4.1;4.1 Dataset;280
32.4.2;4.2 Experimental Evaluation;280
32.5;5 Conclusion and Scope for Further Work;282
32.6;Acknowledgements;283
32.7;References;283
33;Efficient Word2Vec Vectors for Sentiment Analysis to Improve Commercial Movie Success;285
33.1;1 Introduction;285
33.2;2 Related Work;286
33.3;3 Proposed Model for Gross Prediction;286
33.3.1;3.1 Data Collection and Preprocessing;286
33.3.2;3.2 Modeling;288
33.4;4 &!emsp;Proposed Review Model;288
33.4.1;4.1 Data Collection and Preparation;290
33.4.2;4.2 Vectorization;290
33.5;5 Conclusion and Future Work;295
33.6;References;295
34;Improving the Utilization of Licensed Spectrum in Cognitive Radio;296
34.1;1 Introduction;296
34.2;2 Analysis of CDR, CFAR Principles, and CDR–OSA Scheme;297
34.3;3 The Proposed Approach;299
34.4;4 Results and Analysis;302
34.5;5 Conclusion;303
34.6;References;303
35;SmarThings: An Utility Service for Wireless Home Automation, Health Monitoring, and Surveillance System;304
35.1;1 Introduction;304
35.2;2 Related Work;305
35.3;3 Proposed Framework;306
35.4;4 Implementation;309
35.5;5 Result and Performance Analysis;310
35.6;6 Conclusion and Future Work;311
35.6.1;6.1 Conclusion;311
35.6.2;6.2 Future Work;311
35.7;References;312
36;Speech Background Noise Removal Using Different Linear Filtering Techniques;313
36.1;1 Introduction;313
36.2;2 Adaptive Filtering;313
36.2.1;2.1 Least Mean Square Algorithm (LMS);314
36.2.2;2.2 Normalized Least Mean Square Algorithm (NLMS);315
36.3;3 Kalman Filter;315
36.4;4 Experimental Details;316
36.5;5 Comparison;318
36.6;6 Conclusion;322
36.7;References;322
37;Neural Network Classification of EEG Signal for Detection of Brain Abnormalities;324
37.1;1 Introduction;324
37.2;2 Related Work;325
37.3;3 Proposed System;325
37.3.1;3.1 Signal Acquisition;326
37.3.2;3.2 Preprocessing and Segmentation;326
37.3.3;3.3 Feature Extraction;326
37.3.4;3.4 Classification;326
37.4;4 Simulation Results;327
37.5;5 Conclusion;331
37.6;Acknowledgements;332
37.7;References;332
38;Measurement of Walking Speed from EMG Signal using Kurtosis of Approximate Coefficients;333
38.1;1 Introduction;333
38.2;2 EMG Signal Acquisition of VM, TA, GnL;334
38.3;3 Assessment of Walking Speeds using EMG Signal in Time Domain;336
38.4;4 Assessment of Speeds using Kurtosis of Approximate Coefficient from EMG Signal;336
38.4.1;4.1 Determination of Kurtosis of Approximate Coefficients (KA);337
38.4.2;4.2 Optimization of Level of Decomposition for Speed Measurement;337
38.5;5 Algorithm;339
38.6;6 Validation of Algorithm based on Optimized Level;339
38.7;7 Conclusions;340
38.8;Acknowledgements;340
38.9;References;340
39;GAE: A Novel Approach for Software Workflow Improvement by Unhidding Hidden Transactions;342
39.1;1 Introduction;342
39.1.1;1.1 The Event Log as Main Focus of Analysis;342
39.2;2 Literature Review;344
39.3;3 Proposed Algorithm with Procedure with a Sample Case Study;345
39.4;4 Comparison Analysis;347
39.5;5 Results and Outcomes;350
39.6;6 Conclusion and Future Work;350
40;Lung Cancer Detection in CT Scans of Patients Using Image Processing and Machine Learning Technique;352
40.1;1 Introduction;352
40.2;2 Materials and Methods;353
40.2.1;2.1 Image Preprocessing;353
40.2.1.1;2.1.1 DICOM and Hounsfield Units Conversion of Input Pixel Data;353
40.2.1.2;2.1.2 Resampling of HU-Converted Values;354
40.2.1.3;2.1.3 Segmentation of Resampled Pixel Data;355
40.2.1.4;2.1.4 Resizing of Images;356
40.2.1.5;2.1.5 Standardization;357
40.3;3 Machine Learning;357
40.4;4 Experimental Results and Discussions;358
40.5;5 Future Scope;359
40.6;6 Conclusion;359
40.7;Acknowledgments;360
40.8;References;360
41;Implementation of Lifting Scheme Discrete Wavelet Transform Using Modified Multiplier;361
41.1;1 Introduction;361
41.2;2 Lifting Scheme;361
41.3;3 Proposed Multiplier;363
41.4;4 ASIC Implementation Results;365
41.5;5 Conclusion;365
41.6;References;366
42;Evolutionary Algorithms to Minimize Interaction Energy Between Drug Molecule and Target Protein in Streptococcus;367
42.1;1 Introduction;367
42.2;2 Bacteria Protein;367
42.3;3 Proposed Algorithms;368
42.3.1;3.1 For Docking Energy Minimization with Evolutionary Algorithm—GA;368
42.3.2;3.2 For Docking Energy Minimization with Evolutionary Algorithm—PSO;369
42.4;4 Ligand Tree Structure;369
42.4.1;4.1 Necessary Setup;370
42.4.2;4.2 Experiment;372
42.4.3;4.3 Result;374
42.5;5 Conclusion;374
42.6;References;374
43;Assessment of the Fetal Health Using NI-aECG;376
43.1;1 Introduction;376
43.1.1;1.1 Noninvasive Fetal ECG Extraction Techniques;377
43.2;2 Method I: Extraction of FQRS Using Independent Component Analysis;378
43.3;3 Proposed Method II: Synthesized QRS Template;378
43.3.1;3.1 Generation of the Synthesized QRS Waveforms;379
43.4;4 Results and Discussions;380
43.4.1;4.1 ICA Method Results;380
43.4.2;4.2 Results of the Proposed Synthesized QRS Template and Pulse Matching;381
43.5;5 Conclusion;382
43.6;References;383
44;Cost-Effective Vertical Handoff Strategies in Heterogeneous Vehicular Networks;385
44.1;1 Introduction;385
44.2;2 VHO Decision with Inter-distance APs;386
44.2.1;2.1 Cost Minimization Approach;386
44.2.2;2.2 Transmit Time Minimization Approach;387
44.3;3 VHO Decision Based on Statistical Inter-distance APs;387
44.4;4 VHO Decision Including V2V Mode;388
44.4.1;4.1 Ad hoc Network Delay;388
44.4.2;4.2 Wi-Fi and Ad hoc Network;389
44.4.3;4.3 Combination of Cellular, Wi-Fi, and Ad hoc Network;389
44.5;5 Performance Evolution;390
44.5.1;5.1 VHO Decision with Fixed Inter-AP Distance;390
44.5.2;5.2 VHO Decision with Statistical Inter-AP Distance;391
44.5.3;5.3 VHO Decision Including V2V Mode;391
44.6;6 Conclusions;392
44.7;References;392
45;Energy-Efficient Optimum Design for Massive MIMO;394
45.1;1 Introduction;394
45.2;2 System Model;395
45.3;3 Generic Modal of Energy Efficiency (EE);395
45.3.1;3.1 Circuit Power Consumption Model;396
45.3.2;3.2 Energy Efficiency Optimization with ZF Processing;397
45.4;4 Numerical Results;399
45.5;5 Conclusion;401
45.6;References;401
46;Reckoning of Music Rhythm Density and Complexity through Mathematical Measures;403
46.1;1 Introduction;403
46.2;2 Related Works;404
46.3;3 Proposed Work;404
46.4;4 Result Set Analysis;406
46.5;5 Conclusion;409
46.6;References;409
47;Medical Diagnostic Models an Implementation of Machine Learning Techniques for Diagnosis in Breast Cancer Patients;411
47.1;1 Introduction;411
47.1.1;1.1 General Overview;411
47.1.2;1.2 Literature Survey;411
47.2;2 Design Strategy;413
47.2.1;2.1 Elicitation of Outcomes and Findings from Patient Data;413
47.2.2;2.2 Workflow;414
47.3;3 Implementation Details;414
47.3.1;3.1 Attribute Correlation Analysis;414
47.3.2;3.2 Preliminary Tasks Prior to Training;414
47.4;4 Results and Discussion;417
47.4.1;4.1 Comparison of Accuracies of Individual Models;419
47.4.2;4.2 Comparison with Existing Results;419
47.5;5 Conclusion;420
47.6;References;420
48;Breast Blood Perfusion (BBP) Model and Its Application in Differentiation of Malignant and Benign Breast;422
48.1;1 Introduction;422
48.2;2 Proposed System;423
48.2.1;2.1 Preprocessing;423
48.2.2;2.2 Breast Blood Perfusion (BBP) Image Generation;424
48.2.3;2.3 Feature Extraction;426
48.3;3 Experimental Results;427
48.4;4 Conclusion;428
48.5;Acknowledgements;429
48.6;References;429
49;Development and Feasibility Studies of a Device for Early Prediction of Asthma Attack;430
49.1;1 Introduction;430
49.2;2 Theoretical Background;431
49.3;3 Materials;432
49.4;4 Methodology;432
49.4.1;4.1 Overview of the Method;432
49.4.2;4.2 Principle;433
49.4.3;4.3 Procedural Steps;433
49.4.4;4.4 Program Algorithm;434
49.5;5 Results and Discussion;434
49.5.1;5.1 Calibration of Temperature Sensor Along with Signal Conditioning Unit;434
49.5.2;5.2 Performance Study of the Device;435
49.6;6 Conclusion;436
49.7;References;437
50;Game Theory for Vertical Handoff Decisions in Heterogeneous Wireless Networks: A Tutorial;438
50.1;1 Introduction;438
50.2;2 Game Theory: An Overview;439
50.3;3 Game Formulation for VHO;442
50.3.1;3.1 Game Between Mobile Users;442
50.3.2;3.2 Game Between Wireless Networks;443
50.3.3;3.3 Game Between Mobile Users and Wireless Networks;443
50.4;4 Game Solution Using NASH Equilibrium;444
50.4.1;4.1 Performance Measures of a Game;444
50.5;5 Conclusion;445
50.6;References;445
51;Downlink Spectral Efficiency of ZF Precoding Based Multi-user MIMO System Over Weibull Fading Channel;447
51.1;1 Introduction;447
51.2;2 System and Channel Model;448
51.3;3 Simulation Results and Discussion;449
51.4;4 Conclusion;452
51.5;References;452
52;Product Recommendation System Using Support Vector Machine;454
52.1;1 1 Introduction;454
52.2;2 2 Literature Survey;454
52.3;3 3 System Design: Proposed System;456
52.3.1;3.1 Detailed Architecture;456
52.4;4 4 Implementation and Results;460
52.4.1;4.1 Review Aggregation;461
52.5;5 5 Conclusion;461
52.6;6 6 Future Work;462
52.7;References;462
53;A Master Map: An Alternative Approach to Explore Human’s Eye Fixation for Generating Ground Truth Based on Various State-of-the-Art Techniques;463
53.1;1 Introduction;463
53.2;2 Requirement of Combined Saliency Map;464
53.3;3 Various State-of-the-Art Methods to Compute Saliency Map;464
53.3.1;3.1 Frequency-Tuned Salient Region Detection;464
53.3.2;3.2 Minimum Barrier Salient Object Detection Methods;465
53.3.3;3.3 Context-Aware Saliency;465
53.4;4 Proposed Saliency Map for Generating Ground Truth;466
53.4.1;4.1 Saliency Map Generation Using Various Methods and Resizing;466
53.4.2;4.2 Proposed “Master Map” Through “Saliency Maps” Fusion;467
53.5;5 Experiment Validation and More Results;467
53.6;6 Conclusion;468
53.7;References;468
54;Application of Fuzzy Clustering for Selection of Coating Materials for MEMS Sensor Array;470
54.1;1 Introduction;470
54.2;2 Fish Spoilage Markers and Polymer Selection;472
54.3;3 MEMS Sensor Model;473
54.4;4 Data Generation;475
54.5;5 Results and Discussion;476
54.6;6 Conclusion and Future Work;478
54.7;Acknowledgments;478
54.8;References;478
55;Design of H Infinity \left( {H_{\infty } } \right) Controller for Twin Rotor MIMO System (TRMS) Based on Linear Matrix Inequalities;481
55.1;1 Introduction;481
55.2;2 Mathematical Modeling;482
55.3;3 Design of Decoupler;484
55.4;4 Design of H Infinity Controller;484
55.5;5 Simulation Results;486
55.5.1;5.1 Time Response Analysis;486
55.5.2;5.2 Robustness Analysis: Plots for Nominal Model with 50% Increment and Decrement in Moment of Inertia of Main and Tail Rotor;487
55.6;6 Conclusion;488
55.7;Appendix;488
55.8;References;489
56;Development of a Prototype Skin Color Monitor for Noninvasive Estimation of Blood Bilirubin;490
56.1;1 Introduction;490
56.2;2 Theoretical Backgrounds;490
56.3;3 Materials and Methods;491
56.3.1;3.1 Components;491
56.3.2;3.2 System Overview;491
56.3.3;3.3 Program Algorithm;493
56.3.4;3.4 Calibrating the Device;493
56.3.5;3.5 Statistics of Subjects;493
56.4;4 Results;494
56.4.1;4.1 Selecting the Measuring Sites;494
56.4.2;4.2 Performance Study;494
56.5;5 Discussion;495
56.6;6 Conclusion and Future Scope;495
56.7;References;496
57;Noise Removing Filters and Its Implementation on FPGA;497
57.1;1 Introduction;497
57.2;2 Filtering Algorithm;497
57.2.1;2.1 Convolution Operation;497
57.2.2;2.2 Gaussian Filter;497
57.2.3;2.3 Mean Filter;498
57.2.4;2.4 Median Filter;498
57.3;3 Implementation;499
57.3.1;3.1 Implementation Steps for Gaussian and Average Filters on Xilinx ISE;499
57.3.2;3.2 Median Filter Implementation;500
57.4;4 Results;501
57.4.1;4.1 Resource Utilization;501
57.4.2;4.2 Resultant Filtered Images;502
57.5;5 Conclusion;504
57.6;References;504
58;A Novel Unsupervised Framework for Retinal Vasculature Segmentation;506
58.1;1 Introduction;506
58.2;2 Related Work;507
58.3;3 Proposed Method;508
58.3.1;3.1 Preprocessing;508
58.3.2;3.2 Image Enhancement;509
58.3.3;3.3 Vessel Segmentation;510
58.4;4 Experimental Evaluation;512
58.4.1;4.1 Performance Evaluation;512
58.4.2;4.2 Vessel Segmentation Result and Analysis;512
58.5;5 Conclusion;512
58.6;References;512
59;Stochastic Resonance in Bagley-Torvik Equation;514
59.1;1 Introduction;514
59.2;2 Bagley-Torvik Equation with Frequency Noise;515
59.3;3 Solution;515
59.4;4 Results and Discussion;518
59.5;5 Conclusion;520
59.6;Acknowledgements;520
59.7;References;520
60;Classification of Brain MRIs Forming Superpixels;522
60.1;1 Introduction;522
60.2;2 Previous Works;522
60.3;3 Methodology;524
60.3.1;3.1 Dataset Acquisition;524
60.3.2;3.2 Segmentation;525
60.3.3;3.3 Feature Extraction and Classification;526
60.4;4 Results and Discussion;527
60.4.1;4.1 Classification Rates and Performance Validation;527
60.4.2;4.2 Comparison with the Other CAD Systems;528
60.5;5 Conclusion;529
60.6;Acknowledgements;529
60.7;References;529
61;Damping Noise Induced Stochastic Resonance Improves Q-Factor of M/NEMS Resonators;531
61.1;0 1 Introduction;531
61.2;0 2 Cantilever Dynamics and Damping Fluctuations;532
61.3;0 3 Numerical Results and Discussion;535
61.4;0 4 Conclusion;538
61.5;Acknowledgements;538
61.6;References;538
62;Finding the Association of mRNA and miRNA Using Next Generation Sequencing Data of Kidney Renal Cell Carcinoma;540
62.1;1 Introduction;540
62.2;2 Proposed Method;541
62.3;3 Experimental Results;542
62.3.1;3.1 Datasets;542
62.3.2;3.2 Results;542
62.3.3;3.3 Biological Significance;544
62.4;4 Conclusion;548
62.5;References;549
63;Investigations on Failure and Reliability Aspects of Service Oriented Computing Based on Different Deployment Techniques;551
63.1;1 Introduction;551
63.2;2 Related Work;551
63.3;3 Key Objectives and Methodology;552
63.3.1;3.1 Algorithm and Time Complexity of BL Method;553
63.4;4 Testing and Analysis;554
63.4.1;4.1 Reliability Aspects;557
63.5;5 Results and Discussion;557
63.6;6 Conclusion;557
63.7;References;558
64;Data Fusion by Truncation in Wireless Sensor Network;560
64.1;1 Introduction;560
64.1.1;1.1 Wireless Sensor Network;560
64.1.2;1.2 Data Fusion in Wireless Sensor Network;560
64.2;2 Literature Survey;561
64.3;3 Proposed Solution Strategy;562
64.4;4 Inferences;563
64.5;5 Conclusion;566
64.6;6 Future Scope;567
64.7;References;567
65;Optimized Coordinated Economic Load Dispatch and Automatic Generation Control for an Interlinked Power System;568
65.1;1 Introduction;568
65.2;2 Problem Identification;569
65.3;3 Mathematical Modeling;569
65.4;4 Optimization Techniques;571
65.4.1;4.1 Genetic Algorithm;572
65.4.2;4.2 Ant Colony Optimization;572
65.4.3;4.3 Firefly Algorithm;572
65.4.4;4.4 Harmony Search Algorithm;573
65.5;5 Results and Discussions;573
65.6;6 Conclusion;575
65.7;References;575
66;Selection of Colour Correction Algorithms for Calibrating Optical Chronic Ulcer Images;577
66.1;1 Introduction;577
66.2;2 Materials and Methods;578
66.2.1;2.1 Notations;578
66.2.2;2.2 Chronic Wound Sample Image Database Development;578
66.2.3;2.3 Colour Constancy;578
66.3;3 Results and Discussion;584
66.4;4 Conclusion;584
66.5;References;585
67;Designing a Scalable Socio-Technical Method for Evaluating Large e-Governance Systems;587
67.1;1 Introduction;587
67.2;2 Related Work;588
67.3;3 Proposed Evaluation Process;590
67.3.1;3.1 Requirements Gathering;591
67.3.2;3.2 Identification of Quality Attributes;591
67.3.3;3.3 Evaluation of the Quality Attributes and Prioritization;591
67.4;4 Experiments;592
67.5;5 Conclusion;595
67.6;References;595
68;A Low-Noise Low-Cost EEG Amplifier for Neural Recording Applications;597
68.1;1 1 Introduction;597
68.2;2 2 Methodology;598
68.2.1;2.1 System Design;598
68.2.2;2.2 Circuit Description;599
68.3;3 3 Experimental Results and Discussion;601
68.4;4 4 Conclusion;604
68.5;References;604
69;Author Index;606