E-Book, Englisch, Band 5, 931 Seiten, eBook
Reihe: Lecture Notes on Data Engineering and Communications Technologies
Saeed / Gazem / Patnaik Recent Trends in Information and Communication Technology
1. Auflage 2018
ISBN: 978-3-319-59427-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Proceedings of the 2nd International Conference of Reliable Information and Communication Technology (IRICT 2017)
E-Book, Englisch, Band 5, 931 Seiten, eBook
Reihe: Lecture Notes on Data Engineering and Communications Technologies
ISBN: 978-3-319-59427-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
1;Preface;6
2;IRICT-2017 Organizing Committee;8
2.1;Patron;8
2.2;Honorary Chair;8
2.3;International Advisory Board;8
2.4;Conference Chair;9
2.5;Program Committee Co-chairs;9
2.6;Secretariat;9
2.7;Publicity Committee;9
2.8;Publications Committee;9
2.9;IT Committee;10
2.10;Logistic Committee;10
2.11;Treasure Committee;10
2.12;Registration Committee;10
2.13;Sponsorship;11
2.14;International Technical Committee;11
3;Contents;12
4;Big Data Analysis Techniques and Applications;22
5;Prediction of Financial Distress for Electricity Sectors Using Data Mining;23
5.1;Abstract;23
5.2;1 Introduction;23
5.3;2 Methodology;24
5.3.1;2.1 Models for Predicting Financial Distress and Forecasting Probability of Default;24
5.3.2;2.2 Financial Indicators;25
5.4;3 Results and Discussion;26
5.4.1;3.1 Prediction Performance of Data Mining Techniques;26
5.4.2;3.2 Importance of Financial Indicators;29
5.5;4 Conclusion;30
5.6;References;30
6;Predictive Modeling for Dengue Patient’s Length of Stay (LoS) Using Big Data Analytics (BDA);32
6.1;Abstract;32
6.2;1 Introduction;32
6.3;2 Background;33
6.3.1;2.1 Big Data;33
6.3.2;2.2 Big Data Analytics in Healthcare;33
6.3.3;2.3 Electronic Medical Records (EMR) System;34
6.3.4;2.4 Hospital Length of Stay (LoS);34
6.3.5;2.5 Dengue Disease;35
6.3.6;2.6 Related Work;35
6.4;3 Methodology;36
6.4.1;3.1 Data Description;36
6.4.2;3.2 Predictive Modeling;37
6.4.2.1;3.2.1 Regression Analysis;37
6.5;4 Results;37
6.5.1;4.1 Statistics and Descriptive Analyses;37
6.6;5 Conclusions and Future Works;38
6.7;Acknowledgments;39
6.8;References;39
7;Experimental Performance Analysis of B+-Trees with Big Data Indexing Potentials;40
7.1;Abstract;40
7.2;1 Introduction;40
7.3;2 Methodology;42
7.3.1;2.1 Experimental Metrics;42
7.3.2;2.2 Experimental Setup;43
7.3.3;2.3 Querying the B+-Tree;43
7.4;3 Experimental Results and Discussions;43
7.4.1;3.1 Results Presentations;43
7.4.2;3.2 Discussions;47
7.5;4 Conclusion;48
7.6;References;48
8;A Proposed Methodology for Integrating Oil and Gas Data Using Semantic Big Data Technology;50
8.1;Abstract;50
8.2;1 Introduction;50
8.3;2 Related Works;51
8.3.1;2.1 Big Data and the Semantic Web;52
8.4;3 Proposed Framework;53
8.5;4 Result;54
8.6;5 Conclusion;56
8.7;References;56
9;Molecular Similarity Searching with Different Similarity Coefficients and Different Molecular Descriptors;59
9.1;Abstract;59
9.2;1 Introduction;59
9.3;2 State of the Art;60
9.4;3 Concept and Method;61
9.4.1;3.1 Similarity Measure;62
9.5;4 Experimental Design;63
9.6;5 Results;64
9.7;6 Conclusion;65
9.8;Acknowledgments;65
9.9;References;66
10;Classification of Arabic Writer Based on Clustering Techniques;68
10.1;Abstract;68
10.2;1 Introduction;68
10.3;2 Related Work;69
10.4;3 Dataset;70
10.5;4 Methodology;71
10.5.1;4.1 Pre-processing;71
10.5.2;4.2 Connected-Components;71
10.5.3;4.3 Feature Extraction;71
10.5.4;4.4 Feature Combination;72
10.5.5;4.5 Clustering (Classification);73
10.6;5 Results and Discussion;74
10.7;6 Conclusions;76
10.8;References;76
11;Data Pre-processing Techniques for Publication Performance Analysis;79
11.1;Abstract;79
11.2;1 Introduction;79
11.3;2 Related Studies;80
11.3.1;2.1 Research Performance Measurement;80
11.3.2;2.2 Data Pre-processing;82
11.4;3 Materials and Methods;82
11.4.1;3.1 Datasets;82
11.4.2;3.2 Data Pre-processing Approach;83
11.5;4 Results and Discussions;84
11.6;5 Conclusion;85
11.7;Acknowledgement;85
11.8;References;85
12;Data Mining Techniques: A Systematic Mapping Review;86
12.1;Abstract;86
12.2;1 Introduction;86
12.3;2 Background;87
12.4;3 Methodology;88
12.4.1;3.1 Research Questions;88
12.4.2;3.2 Literature Search;88
12.4.3;3.3 Study Selection;89
12.4.4;3.4 Data Extraction;90
12.4.5;3.5 Validity;90
12.5;4 Results;90
12.5.1;4.1 RQ-1: What Are the Major Methods for Conducting Web Data Mining?;90
12.5.2;4.2 RQ-2: Which Topics in Web Data Mining Are Covered?;91
12.5.3;4.3 RQ-3: When and Where Were the Studies Published?;92
12.5.4;4.4 RQ-4: How Were Studies Performed in Terms of Visualization of the Results?;93
12.6;5 Discussion;94
12.6.1;5.1 Data Warehousing;94
12.6.2;5.2 Hyperlinks;94
12.6.3;5.3 Web Mining;95
12.7;6 Conclusion and Recommendations;96
12.8;References;96
13;A Comprehensive Study on Opinion Mining Features and Their Applications;98
13.1;Abstract;98
13.2;1 Introduction;98
13.2.1;1.1 Opinion Mining and Sentiment Analysis;99
13.3;2 Features of Reviews, Reviewers, Group of Reviewers and Target;99
13.4;3 Linguistic Features;101
13.5;4 Structural Features;103
13.6;5 Conclusion;106
13.7;Acknowledgments;106
13.8;References;106
14;Mobile Networks, Applications and Usability;110
15;Adaptive Hybrid Geo-casting Routing Protocol for Mobile Ad hoc Networks;111
15.1;Abstract;111
15.2;1 Introduction;111
15.3;2 Related Work;112
15.4;3 Methodology;112
15.5;4 Performance Evaluation;114
15.5.1;4.1 Simulation Overview;114
15.5.2;4.2 Simulation Result;115
15.5.2.1;4.2.1 Effect of Moving Speed;115
15.5.2.2;4.2.2 Effect of Data Traffic Loads;116
15.6;5 Conclusions;117
15.7;References;117
16;What Makes Older People Want to Use Mobile Devices?;118
16.1;Abstract;118
16.2;1 Introduction;118
16.3;2 Older People;119
16.4;3 Mobile Devices and Factors of Usages;119
16.5;4 Methodology;121
16.5.1;4.1 Interview Questions;121
16.5.2;4.2 Data Analysis;121
16.5.3;4.3 Demographic of Participants;121
16.6;5 Findings and Discussions;122
16.6.1;5.1 Mobile Device Design;122
16.6.2;5.2 Mobile Device Functions;122
16.6.3;5.3 Social Inspiration;123
16.6.4;5.4 Economical;124
16.7;6 Conclusions;124
16.8;Acknowledgments;124
16.9;References;124
17;Mobile Augmented Reality Tourism Application Framework;126
17.1;Abstract;126
17.2;1 Introduction;126
17.3;2 Literature Review;127
17.3.1;2.1 Requirements Pyramid Model;127
17.3.2;2.2 User Requirements;128
17.3.3;2.3 Functional Requirements;128
17.4;3 Methodology;129
17.4.1;3.1 Awareness of Problem;129
17.4.2;3.2 Suggestion;129
17.4.3;3.3 Evaluation;129
17.4.4;3.4 Development;130
17.5;4 Findings;130
17.6;5 Mobile Augmented Reality Tourism Application Framework;131
17.7;6 Conclusion;131
17.8;References;132
18;Motion Artifact Reduction Algorithm Using Sequential Adaptive Noise Filters and Estimation Methods for Mobile ECG;134
18.1;Abstract;134
18.2;1 Introduction;134
18.3;2 The Proposed Algorithm;136
18.4;3 Experimental Results and Discussions;138
18.5;4 Conclusion;139
18.6;Acknowledgment;139
18.7;References;140
19;Concerning Matters of Mobile Device Usage Among Older People;142
19.1;Abstract;142
19.2;1 Introduction;142
19.3;2 Older People;143
19.4;3 Mobile Devices and Older People;143
19.4.1;3.1 Concerning Matters (Effects);144
19.5;4 Methodology;145
19.6;5 Findings and Discussions;145
19.6.1;5.1 Addictions;146
19.6.2;5.2 Relationship Between Human;147
19.6.3;5.3 Misuse;147
19.6.4;5.4 Learning Tool;148
19.7;6 Conclusions;148
19.8;Acknowledgments;148
19.9;References;148
20;Adaptive Memory Size Based Fuzzy Control for Mobile Pedestrian Navigation;150
20.1;Abstract;150
20.2;1 Introduction;150
20.3;2 Concept of Single Distribution Resampling;151
20.4;3 Adaptive Memory Size-Based Fuzzy Control;152
20.5;4 Experiment Result;153
20.6;5 Conclusions and Recommendations for Future Research;157
20.7;References;158
21;Extraction of Common Concepts for the Mobile Forensics Domain;159
21.1;Abstract;159
21.2;1 Introduction;159
21.3;2 Background;160
21.4;3 Method;161
21.4.1;3.1 Models Collection;161
21.4.2;3.2 Concepts Extraction;161
21.4.3;3.3 Common Concepts Selection;169
21.4.4;3.4 Designation of Common Concepts;169
21.5;4 Conclusion;170
21.6;Acknowledgment;170
21.7;References;171
22;Revisiting the Usability of Smartphone User Interface for Elderly Users;173
22.1;Abstract;173
22.2;1 Introduction;173
22.3;2 Literature Review;174
22.4;3 The Preliminary Study;175
22.4.1;3.1 Study Objective;175
22.4.2;3.2 Method;175
22.5;4 Results and Discussions;176
22.5.1;4.1 Usability Issues;176
22.5.2;4.2 Beyond Usability Metrics;177
22.5.2.1;4.2.1 Different Users’ Trends When Using Smartphone;177
22.5.2.2;4.2.2 User Experience with the Smartphone;177
22.5.3;4.3 Implications of the Study’s Findings;178
22.6;5 Conclusion and Future Work;179
22.7;References;179
23;Taguchi Methods for Ad Hoc on Demand Distance Vector Routing Protocol Performances Improvement in VANETs;181
23.1;Abstract;181
23.2;1 Introduction;181
23.3;2 Related Works;183
23.4;3 Taguchi Method;183
23.5;4 Results and Discussion;186
23.6;5 Conclusion;187
23.7;References;187
24;Two Stage Integration of GPS, Kinematic Information, and Cooperative Awareness Messages Using Cascaded Kalman Filters;189
24.1;Abstract;189
24.2;1 Introduction;189
24.3;2 The Proposed Algorithm (GPS/DR/V2V);191
24.3.1;2.1 GPS/DR Fusion Algorithm;191
24.3.2;2.2 GPS/DR/V2V Fusion Algorithm;193
24.4;3 Results and Discussions;194
24.5;4 Conclusion;196
24.6;Acknowledgments;196
24.7;References;196
25;Modeling of GPS Ionospheric Scintillation Using Nonlinear Regression Technique;198
25.1;Abstract;198
25.2;1 Introduction;198
25.3;2 Experimental Setup;199
25.4;3 Method;200
25.5;4 Mathematical Model of S4;202
25.6;5 Investigation of the Mathematical Model;203
25.7;6 Conclusions;205
25.8;Acknowledgments;205
25.9;References;205
26;Hybrid LTE-VANETs Based Optimal Radio Access Selection;207
26.1;Abstract;207
26.2;1 Introduction;208
26.3;2 Related Work;209
26.3.1;2.1 Infrastructure Vehicular Connectivity;209
26.3.2;2.2 Multi-channel Access;209
26.3.3;2.3 DSRC/IEEE 802.11p;210
26.4;3 Proposed Method;212
26.5;4 Performance Evaluations;214
26.6;5 Conclusion;217
26.7;Acknowledgment;217
26.8;References;217
27;Reliable Communication Systems;219
28;Optimization of B-MAC Protocol for Multi-scenario WSN by Differential Evolution Algorithm;220
28.1;Abstract;220
28.2;1 Introduction;220
28.3;2 Related Works;221
28.4;3 Differential Evolution Algorithm;222
28.5;4 Proposed Framework;223
28.6;5 Result and Discussion;225
28.7;6 Conclusion;226
28.8;References;226
29;Power Consumption Optimization Based on B-MAC Protocol for Multi-Scenario WSN by Taguchi Method;227
29.1;Abstract;227
29.2;1 Introduction;227
29.3;2 Related Works;228
29.4;3 Taguchi Method;229
29.4.1;3.1 Planning Phase;230
29.4.2;3.2 Experimental Phase;230
29.4.3;3.3 Analysis Phase;232
29.4.4;3.4 Validation Experiments;233
29.5;4 Conclusion;233
29.6;References;233
30;Modelling and Control of a Non-linear Inverted Pendulum Using an Adaptive Neuro-Fuzzy Controller;235
30.1;Abstract;235
30.2;1 Introduction;235
30.3;2 Mathematical Model;236
30.4;3 ANFIS Controller;238
30.5;4 Simulation Results;238
30.6;5 Comparison with Sugeno FIS;240
30.7;6 Conclusion;241
30.8;References;241
31;Adapted WLAN Fingerprint Indoor Positioning System (IPS) Based on User Orientations;243
31.1;Abstract;243
31.2;1 Introduction;243
31.3;2 Background;244
31.4;3 Related Works;246
31.5;4 Methodology;247
31.6;5 Experiments;248
31.7;6 Result and Discussion;249
31.8;7 Conclusion and Future Work;251
31.9;Acknowledgment;252
31.10;References;252
32;Performance Analysis of the Impact of Design Parameters to Network-on-Chip (NoC) Architecture;254
32.1;Abstract;254
32.2;1 Introduction;254
32.3;2 Related Works;255
32.4;3 Parameters Affected Network-on-Chip (NoC) Performance;256
32.5;4 Routing Algorithm;257
32.6;5 Performance Evaluation;258
32.7;6 Conclusion;262
32.8;References;262
33;A Comparative Review of Adaptive Routing Approach for Network-on-Chip Router Architecture;264
33.1;Abstract;264
33.2;1 Introduction;264
33.3;2 Adaptive Routers;265
33.3.1;2.1 DyAD;266
33.3.2;2.2 SPIN;268
33.3.3;2.3 XGFT;269
33.3.4;2.4 Nostrum;269
33.4;3 Conclusion;270
33.5;References;270
34;Intelligent Routing Algorithm Using Genetic Algorithm (IRAGA);272
34.1;Abstract;272
34.2;1 Introduction;272
34.3;2 Genetic Algorithm;273
34.4;3 GA-Based-Routing Algorithm;273
34.4.1;3.1 GLBR;274
34.4.2;3.2 ARGAQ;274
34.4.3;3.3 MURUGA;275
34.5;4 Proposed Method;276
34.5.1;4.1 Initialization;276
34.5.2;4.2 Fitness Function Calculation;276
34.5.3;4.3 New Population Generation;276
34.5.4;4.4 Crossover Refining Operation;277
34.6;5 Simulation and Analysis;277
34.7;6 Conclusion;279
34.8;References;279
35;Double Curved Tracks Simulation of FSO Link for Ground-to-Train Communications in Tropical Weather;281
35.1;Abstract;281
35.2;1 Introduction;281
35.3;2 FSO Ground-to-Train Communication System Model;282
35.3.1;2.1 Geometrical Model;283
35.3.2;2.2 FSO Link Mathematical Model;285
35.4;3 Simulation Results and Discussion;286
35.4.1;3.1 Rain and Fog Attenuation;286
35.4.2;3.2 FSO G2T Link Simulation Results and Performance Evaluation;288
35.5;4 Conclusions;291
35.6;Acknowledgments;291
35.7;References;291
36;Performance Evaluation of AODV, DSDV, and DSR Routing Protocols in MANET Using NS-2 Simulator;293
36.1;Abstract;293
36.2;1 Introduction;293
36.3;2 Classification of Routing Protocols in MANET;294
36.4;3 Ad-Hoc Routing Protocols;294
36.4.1;3.1 Proactive Routing;295
36.4.2;3.2 Reactive Routing;296
36.5;4 Simulation Setup;297
36.6;5 Performance Metrics and Results;298
36.6.1;5.1 Throughput;298
36.6.2;5.2 Average End-to-End Delay;298
36.6.3;5.3 Packet Loss Rate;299
36.7;6 Conclusions;300
36.8;Acknowledgement;300
36.9;References;301
37;Planning and Optimization of LTE Radio Access Network for Urban Area at Taiz City, Yemen;302
37.1;Abstract;302
37.2;1 Introduction;302
37.3;2 Architecture of LTE Network;303
37.4;3 LTE Network Planning and Optimization;304
37.5;4 Results and Discussions;307
37.6;5 Conclusions;309
37.7;References;310
38;Advances on Computer Vision;311
39;Arabic Sign Language Recognition Using Optical Flow-Based Features and HMM;312
39.1;Abstract;312
39.2;1 Introduction;312
39.3;2 Literature Review;313
39.4;3 Proposed System;315
39.4.1;3.1 Video Segmentation;315
39.4.2;3.2 Arabic Sign Language Recognition;316
39.5;4 Experimental Work;317
39.6;5 Conclusions;319
39.7;Acknowledgments;319
39.8;References;319
40;On the Design of Video on Demand Server-Based Hybrid Storage System;321
40.1;Abstract;321
40.2;1 Introduction;321
40.3;2 Related Work;322
40.4;3 Hybrid Storage System;323
40.4.1;3.1 MMS;324
40.4.2;3.2 DSC Scheme;325
40.5;4 Simulation of the VOD HSS Server;326
40.6;5 Performance Evaluation;327
40.6.1;5.1 Comparison of VOD HSS Architecture with VOD FLARE Architecture;328
40.7;6 Conclusions;329
40.8;References;329
41;An Adaptive Threshold Based on Multiple Resolution Levels for Canny Edge Detection;331
41.1;Abstract;331
41.2;1 Introduction;331
41.3;2 An Adaptive Threshold Based on Multiple Resolution Levels for Canny Edge Detection;333
41.4;3 Experiment and Results;334
41.5;4 Conclusion;337
41.6;Acknowledgements;338
41.7;References;338
42;The Design of an Adaptive Media Playout Technique Based on Fuzzy Logic Control for Video Streaming Over IP Networks;339
42.1;Abstract;339
42.2;1 Introduction;339
42.3;2 Design of FLAMP Technique;340
42.3.1;2.1 Architecture of FLAMP Technique;340
42.3.2;2.2 FLAMP Framework;341
42.3.2.1;2.2.1 Fuzzy Sets of FLAMP Technique;341
42.3.2.2;2.2.2 The Rule Base of FLAMP Technique;342
42.3.2.3;2.2.3 Fuzzy Inference Process of FL342
42.4;3 Performance Metrics and Simulation Results;344
42.4.1;3.1 Performance Metrics;344
42.4.1.1;3.1.1 Buffer Underflow;344
42.4.1.2;3.1.2 Average Buffer Overflow;344
42.4.1.3;3.1.3 Variance of Distortion of Playout (VDoP);344
42.4.2;3.2 Simulation Setting;344
42.4.3;3.3 Simulation Results;345
42.4.3.1;3.3.1 The Count of Buffer Underflow;345
42.4.3.2;3.3.2 The Probability of Buffer Overflow;346
42.4.3.3;3.3.3 The Variation of Distortion of Playout (VDoP);346
42.4.3.4;3.3.3 The Variation of Distortion of Playout (VDoP);346
42.5;4 Conclusion;348
42.6;References;348
43;A Preliminary Study on the Effect of Audio Feedback to Support Comprehension of Web Content Among Non-visual Internet Users;350
43.1;Abstract;350
43.2;1 Introduction;350
43.3;2 Literature Review;352
43.3.1;2.1 Assistive Technology for the Visually Impaired Computer Users;352
43.3.2;2.2 Role of Audio;353
43.3.3;2.3 Language Matters in Transferring Knowledge;353
43.3.4;2.4 Accessibility of the Web Content;354
43.4;3 Methodology;354
43.5;4 Results and Discussion;355
43.6;5 Conclusion;356
43.7;References;357
44;Recognition of Holy Quran Recitation Rules Using Phoneme Duration;358
44.1;Abstract;358
44.2;1 Introduction;358
44.3;2 Literature Review;359
44.3.1;2.1 Related Studies on Phoneme Duration;359
44.3.2;2.2 Affecting Factors on the Phoneme Duration in Quran Recitation;359
44.3.2.1;2.2.1 Levels of Recitation;359
44.3.2.2;2.2.2 Arabic Diacritics (Al-Tashkeel);360
44.3.2.3;2.2.3 The Characteristics of the Letters;361
44.3.2.4;2.2.4 The Ranks of the Nasalization (Ghunnah);362
44.3.2.5;2.2.5 The Medd (Lengthenings);363
44.4;3 Methodology;363
44.4.1;3.1 Data Collection Phase;364
44.4.2;3.2 Preprocessing Phase;364
44.4.3;3.3 Segmentation Phase;364
44.4.4;3.4 Phoneme Duration Modeling;364
44.5;4 Experimental Results and Discussion;364
44.6;5 Conclusion;366
44.7;Acknowledgments;366
44.8;References;366
45;Realistic Rendering Colored Light Shafts Using Light Texture;368
45.1;Abstract;368
45.2;1 Introduction;368
45.3;2 Related Works;369
45.4;3 Method;370
45.4.1;3.1 Light Scattering Model;370
45.4.2;3.2 Colored Light Scattering;371
45.4.3;3.3 Algorithm;372
45.5;4 Results and Discussion;372
45.6;5 Conclusion and Future Work;374
45.7;Acknowledgments;374
45.8;References;375
46;Evaluation of Digital Image Watermarking Techniques;376
46.1;Abstract;376
46.2;1 Introduction;376
46.2.1;1.1 Digital Watermarking;376
46.3;2 Watermarking Classification According to Domain;377
46.3.1;2.1 Spatial Domain Techniques;377
46.3.1.1;2.1.1 Least Significant Bits (LSB);377
46.3.1.2;2.1.2 SSM Modulation Based Techniques;378
46.3.2;2.2 Transform Domain Techniques;379
46.3.2.1;2.2.1 Discrete Fourier Transform (DFT);379
46.3.2.2;2.2.2 Discrete Cosine Transform (DCT);380
46.3.2.3;2.2.3 Discrete Wavelet Transform (DWT);380
46.3.2.4;2.2.4 Singular Value Decomposition (SVD);381
46.4;3 Conclusion and Future Work;382
46.5;References;382
47;An Enhanced Quadratic Angular Feature Extraction Model for Arabic Handwritten Literal Amount Recognition;384
47.1;Abstract;384
47.2;1 Introduction;384
47.3;2 Related Works;385
47.4;3 The Proposed Quadratic Angular Feature Extraction Model;386
47.4.1;3.1 Angular Method;387
47.4.2;3.2 Quadratic Angular Method;388
47.5;4 Result and Discussion;388
47.6;5 Conclusion;390
47.7;Acknowledgments;391
47.8;References;391
48;Semi-automatic Methods in Video Forgery Detection Based on Multi-view Dimension;393
48.1;Abstract;393
48.2;1 Introduction;393
48.3;2 Related Work;394
48.4;3 Processing Method;395
48.4.1;3.1 A New Dimension of Multi-view Frames in Video;396
48.4.2;3.2 Dimension Top View of Video;397
48.4.3;3.3 Dimension Side View of Video;398
48.5;4 Results and Discussions;399
48.6;5 Conclusions;402
48.7;References;402
49;Neuronal Approach for Emotion Recognition Based on Features Motion Estimation;404
49.1;Abstract;404
49.2;1 Introduction;404
49.3;2 Related Works;405
49.4;3 Our Approach;405
49.4.1;3.1 Face Detection;406
49.4.2;3.2 Extraction of Strategic Points;407
49.4.3;3.3 Motion Estimation Features;408
49.4.4;3.4 Description of the Action Units (FACS System);409
49.4.5;3.5 Classification;410
49.5;4 Test;412
49.5.1;4.1 Test Data;412
49.5.2;4.2 Results;413
49.6;5 Conclusion;413
49.7;References;413
50;Segmentation and Enhancement of Fingerprint Images Based on Automatic Threshold Calculations;415
50.1;Abstract;415
50.2;1 Introduction;415
50.3;2 Methodology;416
50.3.1;2.1 Segmentation Features;417
50.3.1.1;2.1.1 Distribution of Image Mean, Variance and Coherence;418
50.3.2;2.2 Foreground Extraction;420
50.3.3;2.3 Filling in the Gaps in a Fingerprint Image;421
50.4;3 Results and Discussion;422
50.5;4 Conclusion;425
50.6;References;425
51;Capturing Haptic Experience Through Users’ Visual Sketches;427
51.1;Abstract;427
51.2;1 Introduction;427
51.3;2 The Usability Studies;430
51.3.1;2.1 Usability Study I;430
51.3.2;2.2 Usability Study II;432
51.4;3 General Discussion;433
51.5;4 Conclusion;434
51.6;References;434
52;A Comparative Study of a New Hand Recognition Model Based on Line of Features and Other Techniques;435
52.1;Abstract;435
52.2;1 Introduction;435
52.3;2 Hand Gesture Recognition Technology;436
52.4;3 Captured Image;436
52.5;4 Segmentation Image;436
52.6;5 Feature Extractions;437
52.7;6 The Classification Process;437
52.8;7 Review of Hand Gesture Recognition;438
52.8.1;7.1 Likelihood Based Classification;438
52.8.2;7.2 Gaussian Mixture Model and Distance Metric;439
52.8.3;7.3 Multi Class Support Vector Machine SVM;439
52.8.4;7.4 Navigation of Image Browsing;440
52.8.5;7.5 SD and Average;440
52.8.6;7.6 Constrained Generative Model CGM Neural Network;441
52.8.7;7.7 Contour and Centroidal Profile;441
52.8.8;7.8 Feed Forward Artificial Neural Networks ANN;442
52.9;8 Summary of the Research;443
52.10;9 Conclusion;444
52.11;References;445
53;Novel FPGA Implementation of EPZS Motion Estimation in H.264 AVC;448
53.1;Abstract;448
53.2;1 Introduction;448
53.3;2 Enhanced Predictive Zonal Search Motion Estimation;450
53.3.1;2.1 Predictor Selection;450
53.3.2;2.2 Adaptive Early Termination;451
53.3.3;2.3 Motion Vector Refinement;452
53.4;3 Hardware Design and Implementation of EPZS;452
53.4.1;3.1 CF and RF Memory Modules;453
53.4.2;3.2 Address Control Unit;453
53.4.3;3.3 SAD Module;454
53.4.4;3.4 ME Module;454
53.4.5;3.5 MC Module;456
53.5;4 Simulation Results;456
53.6;5 Conclusion;459
53.7;References;459
54;Advances on Artificial Intelligence and Soft Computing;461
55;Comparison of Drought Forecasting Using ARIMA and Empirical Wavelet Transform-ARIMA;462
55.1;Abstract;462
55.2;1 Introduction;462
55.3;2 Background Information on Methods;463
55.3.1;2.1 Arima;463
55.3.2;2.2 Empirical Wavelet Transform (EWT);464
55.3.3;2.3 Ewt Arima;465
55.3.4;2.4 Performance Measures;465
55.3.5;2.5 Study Area;466
55.4;3 Results and Discussions;466
55.4.1;3.1 Model Development Result;466
55.4.2;3.2 Model Evaluation;467
55.5;4 Conclusions;470
55.6;Acknowledgments;470
55.7;References;470
56;Real Time Electrocardiogram Identification with Multi-modal Machine Learning Algorithms;472
56.1;Abstract;472
56.2;1 Introduction;472
56.3;2 Background of the Study;474
56.4;3 Methodology;475
56.5;4 Classification and Results;476
56.6;5 Conclusion and Future Work;478
56.7;References;478
57;An Analysis of Rough Set-Based Application Tools in the Decision-Making Process;480
57.1;Abstract;480
57.2;1 Introduction;480
57.3;2 Related Works;481
57.3.1;2.1 Rough Set Theory in Brief;481
57.3.2;2.2 Existing Researches Related to the Rough Set Theory;482
57.4;3 Experimental Work;483
57.5;4 Discussion of Results;484
57.6;5 Conclusion;486
57.7;Acknowledgments;486
57.8;References;487
58;Differential Evolution Based Special Protection and Control Scheme for Contingency Monitoring of Transmission Line Overloading;488
58.1;Abstract;488
58.2;1 Introduction;488
58.3;2 Background of Study;489
58.3.1;2.1 Generation Rescheduling;489
58.4;3 Methodology;490
58.4.1;3.1 Mathematical Formulation of the DE-Based SPCS Scheme;490
58.4.2;3.2 Objective Function;491
58.4.3;3.3 Severity Index (SI);491
58.5;4 Overview of Differential Evolution in SPCS Perspective;493
58.5.1;4.1 Initialization;493
58.5.2;4.2 Mutation;494
58.5.3;4.3 Crossover;494
58.5.4;4.4 Selection;495
58.6;5 Results and Analysis;495
58.6.1;5.1 System Contingency Analysis;495
58.6.2;5.2 The Proposed DE Based Algorithm;496
58.7;6 Conclusion;499
58.8;Acknowledgement;499
58.9;References;499
59;An Implementation of Metaheuristic Algorithms in Business Intelligence Focusing on Higher Education Case Study;501
59.1;Abstract;501
59.2;1 Introduction;501
59.3;2 Proposed Business Intelligence Process;502
59.4;3 Higher Education Case Study;503
59.5;4 Metaheuristic Algorithm;504
59.5.1;4.1 Genetic Algorithm;504
59.5.2;4.2 Particle Swarm Optimization (PSO);505
59.5.3;4.3 Ant Colony Optimization (ACO);505
59.6;5 Implementation of Metaheuristic Algorithms and Results;506
59.7;6 Conclusion;507
59.8;Acknowledgments;507
59.9;References;508
60;Design and Control of Online Battery Energy Storage System Using Programmable Logic Controller;509
60.1;Abstract;509
60.2;1 Introduction;509
60.3;2 Methodology of Controller Design;511
60.3.1;2.1 The Online Battery Energy Storage System Design;511
60.3.1.1;2.1.1 Determining the Battery Pack Capacity;511
60.3.1.2;2.1.2 Selection of Inverter, Rectifier and Sensors;512
60.3.2;2.2 PLC Programming;513
60.3.3;2.3 Measurement Data and Acquisition Systems;513
60.4;3 Monitoring and Simulation of the Online BESS;514
60.4.1;3.1 BESS Under Safe Operating Conditions;514
60.4.2;3.2 BESS Under Unsafe Operating Conditions;516
60.5;4 Conclusion;517
60.6;References;517
61;Test Cases Minimization Strategy Based on Flower Pollination Algorithm;518
61.1;Abstract;518
61.2;1 Introduction;518
61.3;2 Test Cases Generation Based on Flower Pollination Algorithm (TGFP);519
61.4;3 Experiments and Evaluation;520
61.5;4 Conclusion;523
61.6;Acknowledgments;523
61.7;References;524
62;Predicting Global Solar Radiation in Nigeria Using Adaptive Neuro-Fuzzy Approach;526
62.1;Abstract;526
62.2;1 Introduction;526
62.3;2 Materials and Method;527
62.3.1;2.1 Study Location;527
62.3.2;2.2 Neuro Fuzzy Computing;528
62.3.2.1;2.2.1 Adaptive Neuro-Fuzzy Inference System (ANFIS);528
62.4;3 Model Performance Evaluation;530
62.5;4 Results and Discussion;530
62.5.1;4.1 Model Analysis;530
62.5.2;4.2 Model Validation;532
62.6;5 Conclusion;533
62.7;Acknowledgement;533
62.8;References;533
63;A Novel Hybrid Bird Mating Optimizer with Differential Evolution for Engineering Design Optimization Problems;535
63.1;Abstract;535
63.2;1 Introduction;535
63.3;2 Bird Mating Optimizer BMO;536
63.4;3 Differential Evolution DE;538
63.5;4 Bird Mating Optimizer with Differential Evolution BMO-dE;540
63.6;5 Constraints Handling;540
63.7;6 Engineering Design Optimization Problems;541
63.7.1;6.1 Design of Pressure Vessel;541
63.7.2;6.2 Design of Tension/Compression Spring;542
63.8;7 Experimental Results and Discussion;543
63.9;8 Conclusions and Recommendations for Future Works;545
63.9.1;8.1 Conclusions;545
63.9.2;8.2 Recommendations for Future Works;546
63.10;References;546
64;Forecasting Crude Oil Prices Using Wavelet ARIMA Model Approach;548
64.1;Abstract;548
64.2;1 Introduction;548
64.3;2 Methodology;550
64.3.1;2.1 Crude Oil Spot Prices Dataset;550
64.3.2;2.2 Autoregressive Integrated Moving Average;550
64.3.3;2.3 Wavelet Transform;551
64.3.4;2.4 Wavelet ARIMA Combination Approach;552
64.3.5;2.5 Effectiveness Evaluation;552
64.4;3 Result and Discussion;553
64.4.1;3.1 ARIMA Model Construction;553
64.4.2;3.2 Wavelet ARIMA Combination Implementation;555
64.4.3;3.3 Effectiveness Evaluation Result;555
64.5;4 Conclusion;556
64.6;Acknowledgments;556
64.7;References;556
65;The Classification of Urban Growth Pattern Using Topological Relation Border Length Algorithm: An Experimental Study;558
65.1;Abstract;558
65.2;1 Introduction;558
65.3;2 Materials and Methods;560
65.3.1;2.1 Data Collection;560
65.3.2;2.2 Image Pre-processing;560
65.3.3;2.3 Urban Growth Pattern Classification Using Existing Topological Relation Border Length Algorithm;561
65.3.4;2.4 Urban Growth Pattern Classification Using Improved Topological Relation Border Length Algorithm;561
65.4;3 Results and Discussion;564
65.5;4 Conclusion;565
65.6;References;565
66;CMARPGA: Classification Based on Multiple Association Rules Using Parallel Genetic Algorithm Pruned Decision Tree;567
66.1;Abstract;567
66.2;1 Introduction;567
66.3;2 General Ideas of AC;568
66.4;3 The Proposed Technique;569
66.5;4 Experimental Setting;570
66.6;5 Experimental Results and Performance Analysis;570
66.7;6 Conclusion;572
66.8;References;573
67;Modified Cuckoo Search Algorithm for Solving Global Optimization Problems;574
67.1;Abstract;574
67.2;1 Introduction;574
67.3;2 Cuckoo Search Algorithm;576
67.3.1;2.1 The Procedure of Basic Cuckoo Search Algorithm;577
67.3.2;2.2 Tournament Selection Schemes;578
67.3.3;2.3 Modified Cuckoo Search Algorithm;579
67.4;3 Experiments;579
67.4.1;3.1 Benchmark Functions;579
67.4.2;3.2 Experimental Results and Algorithms Settings;580
67.5;4 Conclusion and Future Works;582
67.6;References;582
68;A New Hybrid K-Means Evolving Spiking Neural Network Model Based on Differential Evolution;584
68.1;Abstract;584
68.2;1 Introduction;584
68.3;2 Related Work;585
68.3.1;2.1 K-Means;585
68.3.2;2.2 ESNN;586
68.3.3;2.3 Differential Evolution;588
68.4;3 The Proposed Method K-DESNN;589
68.5;4 Experimental Results and Discussion;592
68.6;5 Conclusion;593
68.7;References;593
69;Reliable Health Informatics;597
70;Local Search Based Enhanced Multi-objective Genetic Algorithm of Training Backpropagation Neural Network for Breast Cancer Diagnosis;598
70.1;Abstract;598
70.2;1 Introduction;598
70.3;2 The Proposed Method;600
70.4;3 Dataset;600
70.5;4 Experimental Study;601
70.5.1;4.1 Experimental Settings;601
70.6;5 Results and Discussion;602
70.7;6 Conclusion;604
70.8;References;604
71;Optimization Health Care Resources in Sensor Network Using Fuzzy Logic Controller;606
71.1;Abstract;606
71.2;1 Introduction;606
71.3;2 Health Care System;607
71.4;3 Proposed Method;609
71.5;4 Test System;610
71.5.1;4.1 Network Topology;610
71.5.2;4.2 IEEE 802.15.6 Protocol Stack;610
71.6;5 Simulation Results;611
71.7;6 Conclusion;614
71.8;Acknowledgements;614
71.9;References;614
72;Towards Improving the Healthcare Services in Least Developed Countries: A Case of Health Needs Assessment for Telehealth in Yemen;616
72.1;Abstract;616
72.2;1 Introduction;616
72.3;2 Literature Review;618
72.4;3 Methodology;619
72.4.1;3.1 Document;619
72.4.2;3.2 Observation;619
72.5;4 Analysis and Findings;620
72.5.1;4.1 Document Analysis and Finding;621
72.5.2;4.2 Observation Analysis and Finding;621
72.6;5 Discussion;623
72.7;6 Conclusion;624
72.8;References;625
73;User Requirements for Prediabetes Self-care Application: A Healthcare Professional Perspective;627
73.1;Abstract;627
73.2;1 Introduction;627
73.2.1;1.1 Background;628
73.2.2;1.2 Research Problem Statement and Contributions;628
73.3;2 Methodology;629
73.4;3 Results;630
73.4.1;3.1 Lifestyle and Self-monitoring;631
73.4.2;3.2 Education and Awareness;631
73.4.3;3.3 Motivation and Commitment;632
73.4.4;3.4 Attitude;632
73.4.5;3.5 Social Support and Coaching;633
73.4.6;3.6 Technology;633
73.5;4 Discussion;634
73.6;5 Conclusion and Future Work;635
73.7;Acknowledgements;636
73.8;References;636
74;Understanding Health Professionals’ Intention to Use Telehealth in Yemen: Using the DeLone and McLean IS Success Model;638
74.1;Abstract;638
74.2;1 Introduction;638
74.3;2 Literatures Review;639
74.3.1;2.1 DeLone and McLean IS Success Model;640
74.4;3 The Research Model;641
74.4.1;3.1 The Dimensions of the Research Model and Hypotheses;641
74.5;4 Methodology;643
74.6;5 Analysis and Findings;643
74.6.1;5.1 Response Rate;643
74.6.2;5.2 Data Screening;643
74.6.3;5.3 Normality and Reliability;643
74.6.4;5.4 Descriptive Analysis for Respondents;644
74.6.5;5.5 Pearson Correlation Result;645
74.7;6 Discussion;646
74.8;7 Conclusion;646
74.9;References;647
75;Reliable Cloud Computing Environment;650
76;Quality of Service (QoS) Task Scheduling Algorithm with Taguchi Orthogonal Approach for Cloud Computing Environment;651
76.1;Abstract;651
76.2;1 Introduction;651
76.3;2 Related Works;652
76.4;3 Problem Formulation and QoS Scheduling Model;653
76.5;4 The Multi-objective Task Scheduling Algorithm;654
76.5.1;4.1 The Proposed Dynamic Multi-Objective Orthogonal Taguchi Cat Algorithm (DMOOTC);654
76.6;5 Simulation and Results;656
76.7;6 Discussion;657
76.8;7 Conclusion;658
76.9;References;658
77;A Fuzzy Logic Based Risk Assessment Approach for Evaluating and Prioritizing Risks in Cloud Computing Environment;660
77.1;Abstract;660
77.2;1 Introduction;660
77.3;2 Related Work;661
77.4;3 Research Method;662
77.5;4 Assessing Risk;662
77.6;5 Fuzzy Logic;663
77.6.1;5.1 Constructing Membership Functions;663
77.6.2;5.2 Designing Inference Based on the Set of Rules;665
77.6.3;5.3 Fuzzy Set Operation;665
77.6.4;5.4 Obtaining the Final Result by Defuzzification;666
77.7;6 Result and Discussion;667
77.8;7 Conclusion;668
77.9;References;668
78;Resolve Resource Contention for Multi-tier Cloud Service Using Butterfly Optimization Algorithm in Cloud Environment;670
78.1;Abstract;670
78.2;1 Introduction;670
78.3;2 Problem Statement;671
78.4;3 Related Work;671
78.5;4 The Resource Optimization and Provisioning Framework;672
78.5.1;4.1 Overview of ROP Framework;672
78.5.2;4.2 Design of RO Module;673
78.6;5 Experimental Setup;674
78.7;6 Results and Discussion;675
78.7.1;6.1 Best Service’s Configurations;675
78.7.2;6.2 Convergence Rate;676
78.8;7 Conclusion;677
78.9;References;677
79;Digital Forensic Challenges in the Cloud Computing Environment;679
79.1;Abstract;679
79.2;1 Introduction;679
79.3;2 Cloud Computing Forensics Challenges;680
79.4;3 Conclusions;685
79.5;Acknowledgments;685
79.6;References;685
80;E-Learning Acceptance Models;687
81;Acceptance Model of Social Media for Informal Learning;688
81.1;Abstract;688
81.2;1 Introduction;688
81.3;2 Theoretical Background;689
81.4;3 Development of Theoretical Model;689
81.4.1;3.1 Perceived Usefulness (PU);690
81.4.2;3.2 Perceived Ease of Use (PEOU);691
81.4.3;3.3 Students Engagement;691
81.4.4;3.4 Collaborative Learning;691
81.4.5;3.5 Interactivity;691
81.4.6;3.6 Experience;692
81.4.7;3.7 Culture;692
81.4.8;3.8 Subjective Norm;692
81.4.9;3.9 Image;693
81.4.10;3.10 Self-efficacy;693
81.4.11;3.11 Perceived Enjoyment;693
81.4.12;3.12 Intention;693
81.5;4 Discussion and Conclusion;694
81.6;References;694
82;Critical Factors to Learning Management System Acceptance and Satisfaction in a Blended Learning Environment;697
82.1;Abstract;697
82.2;1 Introduction;697
82.3;2 Conceptual Model and Research Hypotheses Development;698
82.3.1;2.1 Technology Experiences;699
82.3.2;2.2 System Quality;699
82.3.3;2.3 Information Quality;700
82.3.4;2.4 Service Quality;700
82.3.5;2.5 Students’ Acceptance;700
82.3.6;2.6 Students’ Satisfaction;701
82.4;3 Methodology;701
82.5;4 Data Analysis and Results;701
82.5.1;4.1 Structural Equation Modeling (SEM);701
82.5.1.1;4.1.1 Assessment of the Measurement Model;702
82.5.1.2;4.1.2 Assessment of the Structural Model;704
82.6;5 Discussion and Conclusion;705
82.7;References;706
83;End-User Perspectives on Effectiveness of Learning Performance Through Massive Open Online Course (MOOCs);708
83.1;Abstract;708
83.2;1 Introduction;708
83.3;2 Literature Review;709
83.4;3 Research Model and Hypotheses;709
83.4.1;3.1 Readiness (RE);710
83.4.2;3.2 Perceived Ease of Use (PEU);710
83.4.3;3.3 Perceived Usefulness (PU);710
83.4.4;3.4 Perceived Enjoyment (PE);710
83.4.5;3.5 Attitude (AT);710
83.4.6;3.6 Continuance of use of MOOCs (CI);711
83.4.7;3.7 Student Satisfaction and Effectiveness;711
83.5;4 Research Method;711
83.5.1;4.1 Data Collection;711
83.5.2;4.2 Data Analysis;711
83.6;5 Measurement Model Analysis;712
83.7;6 Conclusion;715
83.8;References;715
84;A Reflective Practice of Using Digital Storytelling During Teaching Practicum;717
84.1;Abstract;717
84.2;1 Introduction;717
84.3;2 Literature Review;717
84.4;3 Research Question;719
84.5;4 Methodology;719
84.6;5 Research Participants;719
84.7;6 Research Procedure;719
84.8;7 Findings and Discussions;721
84.8.1;7.1 Enhanced Understanding of Pedagogical Content Knowledge;721
84.8.2;7.2 Improved Teaching Practice;722
84.8.3;7.3 Professional Development;723
84.9;8 Conclusion;723
84.10;References;723
85;Recent Trends on Knowledge Management;725
86;The Role of Knowledge Sharing in Business Incubators Performance;726
86.1;Abstract;726
86.2;1 Introduction;726
86.3;2 Knowledge, Start-Ups and BIs;727
86.3.1;2.1 Networks as Channels;728
86.3.2;2.2 Knowledge Sharing and Performance;728
86.4;3 Method and Data;729
86.4.1;3.1 Measurement Model Results;729
86.4.2;3.2 Structural Model Results;730
86.5;4 Discussion;731
86.6;5 Conclusion;731
86.7;References;732
87;Knowledge Creation Process Within Group Problem Solving Among Students in Academic Institutions;735
87.1;Abstract;735
87.2;1 Introduction;735
87.3;2 Literature Review;736
87.4;3 Methodology;737
87.4.1;3.1 Data Analysis;738
87.4.2;3.2 Research Findings;739
87.5;4 Conclusion;742
87.6;Acknowledgment;742
87.7;References;742
88;Security in the Cyber World;744
89;Blockchain Security Hole: Issues and Solutions;745
89.1;Abstract;745
89.2;1 Introduction;745
89.3;2 Current Applications;746
89.3.1;2.1 Digital Payments (Cryptocurrencies);746
89.3.2;2.2 Smart Contracts;747
89.3.3;2.3 Database and Record Management;747
89.3.4;2.4 Content Distribution;748
89.4;3 Security Issues and Challenges;749
89.4.1;3.1 Security Issues;749
89.4.2;3.2 Other Challenges;749
89.5;4 Solutions;750
89.5.1;4.1 Current Solutions;750
89.6;5 Conclusions;751
89.7;Acknowledgement;751
89.8;References;752
90;A Robust DCT Based Technique for Image Watermarking Against Cropping Attacks;753
90.1;Abstract;753
90.2;1 Introduction;753
90.3;2 Review of DCT;754
90.4;3 Proposed Watermarking Scheme;755
90.4.1;3.1 Embedding Process;755
90.4.2;3.2 Extracting Process;759
90.5;4 Experiment Result;760
90.6;5 Performance Comparison with Other Methods;762
90.7;6 Conclusion;763
90.8;References;763
91;A 0-Day Aware Crypto-Ransomware Early Behavioral Detection Framework;764
91.1;Abstract;764
91.2;1 Introduction;764
91.3;2 Related Work;766
91.4;3 The Methods;766
91.5;4 The Proposed Framework;767
91.6;5 Results and Discussion;768
91.6.1;5.1 Pre-processing Module;768
91.6.2;5.2 Features Engineering Module;768
91.6.3;5.3 Detection Module;770
91.7;6 Conclusion and Future Work;770
91.8;References;770
92;SBRT: API Signature Behaviour Based Representation Technique for Improving Metamorphic Malware Detection;773
92.1;Abstract;773
92.2;1 Introduction;773
92.3;2 Related Works;774
92.3.1;2.1 Research Techniques for a Malware Detection System;774
92.4;3 Proposed Research’s Framework and Methodology;777
92.4.1;3.1 General Structure of Two Phases of the Proposed Research Framework;777
92.4.2;3.2 Phases Representing the Flow of the Whole Process;779
92.5;4 Analyses of Experimental Results;780
92.6;5 Conclusions;781
92.7;References;781
93;Society and Information Technology;784
94;Dimensions for Productive Ageing;785
94.1;Abstract;785
94.2;1 Introduction;785
94.3;2 Methodology;786
94.4;3 Findings on Productive Ageing Dimensions;787
94.4.1;3.1 Activities of Dimensions for Productive Ageing;790
94.5;4 Conclusion;791
94.6;References;791
95;Digital Games Acceptance in Malaysia;793
95.1;Abstract;793
95.2;1 Introduction;793
95.3;2 Literature Review;794
95.4;3 Research Methodology;795
95.4.1;3.1 The Sample and Administering the Survey;795
95.4.2;3.2 Data Analysis Procedures;797
95.5;4 Results and Discussions;797
95.6;5 Conclusions;798
95.7;References;799
96;Rising Ageing Population: A Preliminary Study of Malaysian Older People Expectations in Information and Communication Technology;800
96.1;Abstract;800
96.2;1 Introduction;800
96.3;2 Method;801
96.3.1;2.1 Discussion;802
96.3.2;2.2 Survey;802
96.4;3 ICT Importance and Challenges to Older People;802
96.5;4 Mobile Device Usage;804
96.6;5 Conclusion;806
96.7;Acknowledgments;807
96.8;References;807
97;Online Shopping Inventory Issues and Its Impact on Shopping Behavior: Customer View;808
97.1;Abstract;808
97.2;1 Introduction;808
97.3;2 Methodology;810
97.3.1;2.1 Survey Objective;810
97.4;3 Results Analysis and Discussions;811
97.4.1;3.1 Correlation Analysis;812
97.4.2;3.2 Comments Analysis;813
97.5;4 Conclusion;813
97.6;A Appendix;814
97.7;References;815
98;The DeLone–McLean Information System Success Model for Electronic Records Management System Adoption in Higher Professional Education Institutions of Yemen;816
98.1;Abstract;816
98.2;1 Introduction;816
98.3;2 Previous Works on Electronic Records Management System Technical Factors;817
98.3.1;2.1 System Quality;818
98.3.2;2.2 Information Quality;818
98.3.3;2.3 Service Quality;819
98.3.4;2.4 Behavioral Intention/Intention to Adopt ERMS;819
98.3.5;2.5 Decision Making Process;820
98.4;3 ERMS Adoption Model for Supporting Decision Making Process;820
98.5;4 Methodology;821
98.6;5 Findings and Discussions;822
98.7;6 Conclusion and Recommendations;824
98.8;References;825
99;Users’ Verification of Information System Curriculum Design Model;828
99.1;Abstract;828
99.2;1 Introduction;828
99.2.1;1.1 Information Systems Model;829
99.2.2;1.2 Definition of Curriculum Design;829
99.3;2 Methodology;831
99.4;3 Results and Discussion;831
99.4.1;3.1 The Results;831
99.4.2;3.2 Discussion;834
99.5;4 Conclusions;834
99.6;References;835
100;Understanding NUI Among Children: A Usability Study on Touch-Form and Free-Form Gesture-Based Interaction;836
100.1;Abstract;836
100.2;1 Introduction;836
100.3;2 Related Work;837
100.4;3 User Study;838
100.4.1;3.1 Method and Materials;838
100.4.2;3.2 Tasks;839
100.4.3;3.3 Preliminary State and Training Session;840
100.4.4;3.4 Data Collection;841
100.5;4 Result;841
100.6;5 Discussion and Recommendation;843
100.7;References;844
101;Influence Maximization Towards Target Users on Social Networks for Information Diffusion;846
101.1;Abstract;846
101.2;1 Introduction;846
101.3;2 Related Works;847
101.4;3 Problem Formulation;848
101.5;4 Methodology;849
101.6;5 Algorithms;849
101.7;6 Experiment;850
101.8;7 Result and Discussion;851
101.9;8 Conclusion;853
101.10;References;854
102;Exploring Elements and Factors in Social Content Management for ICT Service Innovation;855
102.1;Abstract;855
102.2;1 Introduction;855
102.3;2 Background;856
102.3.1;2.1 Evolution of Social Content Management;856
102.3.2;2.2 Elements Affecting Social Content Management;856
102.4;3 Method;857
102.5;4 Finding and Analysis;857
102.5.1;4.1 Strategy;858
102.5.2;4.2 People;858
102.5.3;4.3 Content Lifecycle;858
102.5.4;4.4 Technology;859
102.5.5;4.5 Governance;859
102.5.6;4.6 Strategic Managerial Aspect;859
102.6;5 Conclusion;860
102.7;Acknowledgement;860
102.8;References;860
103;Recent Trends on Software Engineering;864
104;Situational Requirement Engineering in Global Software Development;865
104.1;Abstract;865
104.2;1 Introduction;865
104.3;2 Literature Review;866
104.3.1;2.1 Background of the Research;866
104.3.2;2.2 Review of Related Research;867
104.3.3;2.3 Review of the Methodologies;870
104.3.4;2.4 Review of Situational Context;871
104.4;3 Discussion;872
104.4.1;3.1 Research Directions;872
104.5;4 Conclusion;874
104.6;References;874
105;Intellectual Property Challenges in the Crowdsourced Software Engineering: An Analysis of Crowdsourcing Platforms;877
105.1;Abstract;877
105.2;1 Introduction;877
105.3;2 Related Work;878
105.4;3 Methods;879
105.5;4 Results and Discussion;880
105.5.1;4.1 CSE Platforms;880
105.5.2;4.2 Challenges of IP Ownership Rights in CSE Platforms;880
105.6;5 Conclusion and Future Work;883
105.7;References;883
106;A Review of Advances in Extreme Learning Machine Techniques and Its Applications;887
106.1;Abstract;887
106.2;1 Introduction;887
106.3;2 Classical Extreme Learning Machines;888
106.4;3 Research Method;889
106.4.1;3.1 Research Questions;889
106.4.2;3.2 Research Strategy;889
106.4.3;3.3 Search Based on Strings and Scopes;890
106.4.4;3.4 Analysis of Search Result;891
106.5;4 Results and Discussion;893
106.5.1;4.1 ELM Techniques;893
106.5.2;4.2 Major Applications of ELM;893
106.5.3;4.3 Strength and Weaknesses of ELM;894
106.6;5 Conclusion;895
106.7;Acknowledgements;895
106.8;References;895
107;A Review on Meta-Heuristic Search Techniques for Automated Test Data Generation: Applicability Towards Improving Automatic Programming Assessment;898
107.1;Abstract;898
107.2;1 Introduction;899
107.3;2 Methodology;900
107.3.1;2.1 Planning the Review;900
107.3.2;2.2 Conducting the Review;900
107.3.3;2.3 Reporting the Review;901
107.4;3 Analysis and Results;902
107.4.1;3.1 Analysis of Primary Study;902
107.4.2;3.2 Publication Year;902
107.5;4 Conclusion and Future Work;906
107.6;Acknowledgements;907
107.7;References;907
108;Predicting Software Reliability with a Novel Neural Network Approach;909
108.1;Abstract;909
108.2;1 Introduction;909
108.3;2 Software Reliability Concepts;911
108.4;3 ICA-MLP Software Reliability Prediction Model;912
108.4.1;3.1 ICA-MLP Software Reliability Prediction Model;913
108.4.2;3.2 ICA-MLP Experimental Results;913
108.4.2.1;3.2.1 Experimental Results of Comparison;915
108.5;4 Conclusion;917
108.6;Acknowledgments;917
108.7;References;917
109;Performance Analysis of OpenMP Scheduling Type on Embarrassingly Parallel Matrix Multiplication Algorithm;919
109.1;Abstract;919
109.2;1 Introduction;919
109.3;2 Related Work;920
109.4;3 Methodology;921
109.4.1;3.1 Parallelizing Matrix Multiplication Algorithm;922
109.4.2;3.2 Measuring Execution Time;922
109.4.3;3.3 Experimental Platform;923
109.4.4;3.4 Parallel Performance Metrics;923
109.5;4 Results and Discussion;924
109.6;5 Conclusions and Future Work;926
109.7;Acknowledgments;926
109.8;References;927
110;Author Index;928
