Patnaik / Popentiu-Vladicescu Recent Developments in Intelligent Computing, Communication and Devices

Proceedings of ICCD 2016
1. Auflage 2017
ISBN: 978-981-10-3779-5
Verlag: Springer Nature Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 555, 172 Seiten

Reihe: Advances in Intelligent Systems and Computing

The book presents high quality papers presented at 2nd International Conference on Intelligent Computing, Communication & Devices (ICCD 2016) organized by Interscience Institute of Management and Technology (IIMT), Bhubaneswar, Odisha, India, during 13 and 14 August, 2016. The book covers all dimensions of intelligent sciences in its three tracks, namely, intelligent computing, intelligent communication and intelligent devices. intelligent computing track covers areas such as intelligent and distributed computing, intelligent grid and cloud computing, internet of things, soft computing and engineering applications, data mining and knowledge discovery, semantic and web technology, hybrid systems, agent computing, bioinformatics, and recommendation systems.Intelligent communication covers communication and network technologies, including mobile broadband and all optical networks that are the key to groundbreaking inventions of intelligent communication technologies. This covers communication hardware, software and networked intelligence, mobile technologies, machine-to-machine communication networks, speech and natural language processing, routing techniques and network analytics, wireless ad hoc and sensor networks, communications and information security, signal, image and video processing, network management, and traffic engineering. And finally, the third track intelligent device deals with any equipment, instrument, or machine that has its own computing capability. As computing technology becomes more advanced and less expensive, it can be built into an increasing number of devices of all kinds. The intelligent device covers areas such as embedded systems, RFID, RF MEMS, VLSI design and electronic devices, analog and mixed-signal IC design and testing, MEMS and microsystems, solar cells and photonics, nanodevices, single electron and spintronics devices, space electronics, and intelligent robotics.

Dr. Srikanta Patnaik is a Professor in the Department of Computer Science and Engineering, Faculty of Engineering and Technology, SOA University, Bhubaneswar, India. He has received his Ph.D. (Engineering) on Computational Intelligence from Jadavpur University, India in 1999 and supervised 12 Ph.D. theses and more than 30 M. Tech theses in the area of Computational Intelligence, Soft Computing Applications and Re-Engineering. Dr. Patnaik has published around 60 research papers in international journals and conference proceedings. He is author of 2 text books and edited 12 books and few invited book chapters, published by leading international publishers like Springer-Verlag, Kluwer Academic, etc. Dr. Patnaik was the Principal Investigator of AICTE sponsored TAPTEC project 'Building Cognition for Intelligent Robot' and UGC sponsored Major Research Project 'Machine Learning and Perception using Cognition Methods'. He is the Editor-in-Chief of International Journal of Information and Communication Technology and International Journal of Computational Vision and Robotics published from Inderscience Publishing House, England and also Series Editor of Book Series on 'Modeling and Optimization in Science and Technology' published from Springer, Germany.Dr. Florin POPENTIU VLÃDICESCU is at present an associated Professor of Software Engineering at UNESCO Department University, City University, London. Dr. Florin POPENTIU has been a Visiting Professor at various universities such as Telecom Paris, ENST, Ecole Nationale Superieure des Mines Paris, ENSMP, Ecole Nationale Superieure de Techniques Avancees, ENSTA, ETH - Zurich, Université Pierre et Marie Curie Paris, UPMC, Delft University of Technology, University of Twente Enschede and Technical University of Denmark Lyngby. Prof. Florin POPENTIU VLÃDICESCU is currently Visiting Professor at 'ParisTech' which includes the 'Grandes Ecoles', The ATHENS Programme, where he teaches courses on Software Reliability. He also lectures on Software Reliability at International Master of Science in Computer Systems Engineering, Technical University of Denmark. Prof. Florin POPENTIU VLÃDICESCU has published over 100 papers in International Journals and Conference Proceedings and is author of one book and co-author of 3 books. He has worked for many years on problems associated with software reliability and has been Co-Director of two NATO research projects involving collaboration with partner institutions throughout Europe. He is on advisory board of several international journals; Reliability: Theory & Applications Journal of Systemics, Cybernetics and Informatics (JSCI) and Microelectronics Reliability. He is reviewer for ACM Computing Reviews, IJCSIS, and Associated Editor to IJICT.

Autoren/Hrsg.

Patnaik, Srikanta

Popentiu-Vladicescu, Florin

Inhaltsverzeichnis

1;Preface;6
2;Acknowledgements;9
3;About the Book;10
4;Contents;11
5;About the Editors;14
6;1 Research on SaaS-Based Mine Emergency Rescue Preplan and Case Management System;16
6.1;Abstract;16
6.2;1 Introduction;16
6.3;2 SaaS and Service-Oriented Architecture;17
6.4;3 The Architecture of System;18
6.5;4 The Components of System;19
6.6;5 System Implementation and Testing;20
6.7;6 Conclusion;22
6.8;Acknowledgements;22
6.9;References;23
7;2 An Investigation of Matching Approaches in Fingerprints Identification;24
7.1;Abstract;24
7.2;1 Introduction;25
7.3;2 Research Method;25
7.3.1;2.1 Research Questions;26
7.3.2;2.2 Research Strategies;26
7.4;3 Fingerprints Matching Approaches;26
7.4.1;3.1 Taxonomy of the Study;26
7.4.2;3.2 Generic Process of Three Main Types of Fingerprints Matching;27
7.5;4 Current Issues of the Matching Approaches;28
7.6;Acknowledgements;29
7.7;References;29
8;3 Figure Plagiarism Detection Using Content-Based Features;31
8.1;Abstract;31
8.2;1 Introduction;31
8.3;2 Content-Based Feature Extraction;32
8.4;3 Similarity Detection;33
8.5;4 Result and Evaluation;33
8.6;5 Conclusions;34
8.7;Acknowledgements;34
8.8;References;34
9;4 An Efficient Content-Based Image Retrieval (CBIR) Using GLCM for Feature Extraction;35
9.1;Abstract;35
9.2;1 Introduction;36
9.3;2 Proposed System;37
9.3.1;2.1 Preprocessing Phase;37
9.3.2;2.2 Feature Extraction Phase;38
9.4;3 Methodology;38
9.5;4 Similarity Feature Extraction;39
9.6;5 Algorithm for GLCM;40
9.7;6 Results and Discussion;41
9.8;7 Comparative Analysis;43
9.9;8 Conclusions;43
9.10;References;43
10;5 Emotion Recognition System Based on Facial Expressions Using SVM;45
10.1;Abstract;45
10.2;1 Introduction;45
10.3;2 Related Works;46
10.4;3 Emotion Recognition;47
10.4.1;3.1 Image Preprocessing;47
10.4.2;3.2 Feature Extraction;47
10.4.3;3.3 Feature Selection;48
10.4.4;3.4 Expression Recognition;48
10.4.5;3.5 Experiments Results;48
10.5;4 Conclusion;49
10.6;References;49
11;6 An AES–CHAOS-Based Hybrid Approach to Encrypt Multiple Images;50
11.1;Abstract;50
11.2;1 Introduction;50
11.2.1;1.1 Fast Chaotic Algorithm;51
11.2.2;1.2 AES Image Encryption;51
11.2.3;1.3 Cramer’s Rule;51
11.3;2 Literature Review;52
11.4;3 Proposed Algorithm;53
11.5;4 Results;54
11.6;5 Conclusion;56
11.7;References;56
12;7 Automatic Text Summarization of Video Lectures Using Subtitles;57
12.1;Abstract;57
12.2;1 Introduction;57
12.3;2 Proposed System;59
12.3.1;2.1 Proposed Architecture;59
12.3.1.1;2.1.1 Data Preprocessing;59
12.3.1.2;2.1.2 Feature Selection for Summarization;59
12.3.1.3;2.1.3 Processing After Feature Selection for Summarization;60
12.4;3 Conclusion;64
12.5;References;64
13;8 Classification of EMG Signals Using ANFIS for the Detection of Neuromuscular Disorders;65
13.1;Abstract;65
13.2;1 Introduction;66
13.3;2 Proposed Model;66
13.3.1;2.1 Preprocessing of the EMG Signal;67
13.3.2;2.2 Processing or Feature Extraction of EMG Signal;68
13.3.3;2.3 Classification of EMG Signal;68
13.4;3 Results and Analysis;70
13.5;4 Conclusion;71
13.6;References;71
14;9 Evaluating Similarity of Websites Using Genetic Algorithm for Web Design Reorganisation;73
14.1;Abstract;73
14.2;1 Introduction;73
14.3;2 Web Mining—A Background;74
14.3.1;2.1 Web Mining Taxonomy;74
14.3.2;2.2 Web Mining Tasks;76
14.4;3 Literature Survey;76
14.5;4 Proposed Methodology;77
14.6;5 Experimental Evaluation;81
14.6.1;5.1 Proposed Genetic Algorithm;81
14.6.2;5.2 Computation of Similarity;82
14.7;6 Conclusion;83
14.8;References;83
15;10 Fusion of Misuse Detection with Anomaly Detection Technique for Novel Hybrid Network Intrusion Detection System;85
15.1;Abstract;85
15.2;1 Introduction;86
15.3;2 Proposed Hybrid Intrusion Detection Methodology;87
15.3.1;2.1 Feature Preparation Module;88
15.3.2;2.2 Misuse Analyzer Module;89
15.3.3;2.3 Anomaly Analyzer Module;90
15.4;3 Simulation Results;91
15.5;4 Conclusion;97
15.6;References;98
16;11 Analysis of Reconfigurable Fabric Architecture with Cryptographic Application Using Hashing Techniques;100
16.1;Abstract;100
16.2;1 Introduction;100
16.3;2 Methodology;101
16.4;3 Implementation of Reconfigurable Fabric;102
16.5;4 Interconnect Topologies;103
16.6;5 Operation;104
16.7;6 Results;105
16.7.1;6.1 Hashing Function;105
16.8;7 Conclusion;106
16.9;References;107
17;12 Privacy Preservation of Infrequent Itemsets Mining Using GA Approach;108
17.1;Abstract;108
17.2;1 Introduction;108
17.3;2 Literature Survey;109
17.4;3 Problem Definition;109
17.5;4 Proposed Framework;109
17.6;5 Proposed Algorithm;110
17.6.1;5.1 Illustrated Example;111
17.7;6 Result Analysis;112
17.8;7 Conclusion;114
17.9;References;114
18;13 A Quinphone-Based Context-Dependent Acoustic Modeling for LVCSR;116
18.1;Abstract;116
18.2;1 Introduction;116
18.3;2 Working of ASR;117
18.4;3 Phonetic Representation of Speech Signals;118
18.4.1;3.1 Modeling Using Monophones;118
18.4.2;3.2 Modeling Using Triphones;119
18.4.3;3.3 Modeling Using Quinphones;119
18.5;4 Implementation;119
18.5.1;4.1 Speech Data Preparation;120
18.5.2;4.2 Training;120
18.5.3;4.3 ASR Performance Analysis;120
18.6;5 Experiments;121
18.6.1;5.1 Testing with Varying Vocabulary Sizes;121
18.6.2;5.2 Testing with Varying Gaussian Mixtures;121
18.7;6 Conclusion;122
18.8;References;122
19;14 Slot-Loaded Microstrip Antenna: A Possible Solution for Wide Banding and Attaining Low Cross-Polarization;123
19.1;Abstract;123
19.2;1 Introduction;123
19.3;2 Theoretical Background;124
19.4;3 Proposed Structure;126
19.5;4 Results and Discussions;126
19.6;5 Conclusions;128
19.7;Acknowledgements;128
19.8;References;128
20;15 Fractal PKC-Based Key Management Scheme for Wireless Sensor Networks;130
20.1;Abstract;130
20.2;1 Introduction;130
20.3;2 Related Work;131
20.4;3 Preliminaries;132
20.4.1;3.1 System Model;132
20.4.2;3.2 Fractal-based Key Pair Generation and Key Exchange;132
20.5;4 Fractal PKC-based Key Management Scheme: FPKM;133
20.5.1;4.1 Set-up Phase;133
20.5.2;4.2 Clustering Phase;133
20.5.3;4.3 Rekeying Phase;135
20.6;5 The Performance Evaluation of Proposed Scheme;135
20.7;6 Conclusion;136
20.8;References;137
21;16 Histogram-Based Human Segmentation Technique for Infrared Images;138
21.1;Abstract;138
21.2;1 Introduction;138
21.3;2 The Proposed Method;139
21.3.1;2.1 Selection of ROIs;139
21.3.2;2.2 Human Candidates Segmentation;140
21.4;3 Experiment Results;140
21.5;4 Conclusion;141
21.6;References;141
22;17 Medical Image Segmentation Based on Beta Mixture Distribution for Effective Identification of Lesions;142
22.1;Abstract;142
22.2;1 Introduction;142
22.3;2 Probability Distribution Functions of Beta Mixture Model Using the EM Algorithm;143
22.4;3 Clustering Algorithm Based on Fuzzy c-Means;144
22.5;4 Dataset;145
22.6;5 Segmentation Algorithm;145
22.6.1;5.1 Experimentation;146
22.7;6 Results Derived and Performance Analysis;146
22.8;7 Conclusion;148
22.9;References;148
23;18 Toward Segmentation of Images Based on Non-Normal Mixture Models Based on Bivariate Skew Distribution;150
23.1;Abstract;150
23.2;1 Introduction;150
23.3;2 Bivariate Skew Gaussian Mixture Model;151
23.4;3 k-Means Algorithm;152
23.5;4 Data Set Considered;152
23.6;5 Feature Selection;152
23.7;6 Experiment Result and Performance Evolution;155
23.8;7 Conclusion;156
23.9;References;156
24;19 Development of Video Surveillance System in All-Black Environment Based on Infrared Laser Light;158
24.1;Abstract;158
24.2;1 Introduction;159
24.3;2 Design of Video Capture System;159
24.3.1;2.1 IR Laser Aiding Light Module;160
24.3.2;2.2 Photoelectric Sensor Module;160
24.3.3;2.3 Central Control Module;161
24.4;3 System Testing;162
24.5;4 Conclusion;163
24.6;Acknowledgements;163
24.7;References;163
25;20 Data Preprocessing Techniques for Research Performance Analysis;165
25.1;Abstract;165
25.2;1 Introduction;165
25.3;2 Literature Review;166
25.3.1;2.1 Business Intelligence;166
25.3.2;2.2 Data Preprocessing;167
25.4;3 Research Performance Analysis;167
25.4.1;3.1 Data Preprocessing Approach;168
25.5;4 Conclusion;169
25.6;Acknowledgements;169
25.7;References;169
26;Author Index;171