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Advances in Computer Science and Ubiquitous Computing

E-BookPDF1 - PDF WatermarkE-Book
918 Seiten
Englisch
Springer Nature Singaporeerschienen am17.12.20151st ed. 2015
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Produkt

Inhalt/Kritik

Inhaltsverzeichnis
1;Message from the CSA 2015 General Chair;6
2;Message from the CSA 2015 Program Chairs;8
3;Organization;10
4;Message from the CUTE 2015 General Chairs;14
5;Message from the CUTE 2015 Program Chairs;16
6;Organization;18
7;Contents;21
8;Cryptanalysis of Enhanced Biometric-Based Authentication Scheme for Telecare Medicine Information Systems Using Elliptic Curve Cryptosystem;32
8.1;1 Introduction;33
8.2;2 Review in Lu et al.´s Scheme;33
8.2.1;2.1 Registration Phase;34
8.2.2;2.2 Login and Authentication;34
8.2.3;2.3 Password Change;35
8.3;3 Security Flaws in Lu et al.´s Scheme;35
8.3.1;3.1 Outsider Attack;35
8.3.2;3.2 User Impersonation Attack;35
8.3.3;3.3 Server Impersonation Attack;36
8.3.4;3.4 Smart Card Stolen Attack;36
8.4;4 Conclusion;37
8.5;References;37
9;Cryptanalysis on Symmetric Key Techniques Based Authentication Scheme for Wireless Sensor Networks;38
9.1;1 Introduction;38
9.2;2 Review of Chen et al.´s Authentication Scheme;39
9.3;3 Cryptanalysis of Chen et al.´s Authentication Scheme;41
9.3.1;3.1 No Perfect Forward Secrecy;41
9.3.2;3.2 Session Key Exposure by GW node;42
9.3.3;3.3 Lack of Anonymity;42
9.3.4;3.4 Lack of Password Check;43
9.4;4 Conclusion;44
9.5;References;44
10;Proving Sufficient Completeness of Constructor-Based Algebraic Specifications;45
10.1;1 Introduction;45
10.2;2 Preliminaries;46
10.3;3 A Sufficient Condition of Sufficient Completeness;48
10.4;4 Proving Sufficient Completeness by Term Rewriting;49
10.5;5 Conclusion;50
10.6;References;51
11;Effect of Zooming Speed and Pattern on Using IPTV by Zoomable User Interface;52
11.1;1 Introduction;52
11.2;2 Background;53
11.2.1;2.1 Zooming Speed;53
11.2.2;2.2 Zooming Pattern;53
11.2.3;2.3 Speed and Patterns;54
11.3;3 Method;55
11.4;4 Results;57
11.4.1;4.1 Results of the 1st Experiment;57
11.4.2;4.2 Comprehensive Analysis of the Speed and the Pattern;57
11.5;5 Conclusions;57
11.6;References;58
12;Malware Similarity Analysis Based on Graph Similarity Flooding Algorithm;59
12.1;1 Introduction;59
12.2;2 Related Work;61
12.3;3 The Overall of Framework;61
12.3.1;3.1 Function-Call Graph;61
12.3.2;3.2 Similarity Flooding Algorithm;62
12.4;4 Performance Analysis;64
12.5;5 Summary and Future Work;64
12.6;References;65
13;The Effect of Information Quality on User Loyalty Towards Smartphone Applications;66
13.1;1 Introduction;67
13.2;2 Research Methodology, Data Analysis, and Results;68
13.3;3 Discussion and d Conclusion;70
13.4;References;70
13.5;Appendix;71
14;Cryptanalysis of Dynamic ID-Based User Authentication Scheme Using Smartcards Without Verifier Tables;72
14.1;1 Introduction;72
14.2;2 Review of Lee´s Scheme;73
14.2.1;2.1 Registration Phase;74
14.2.2;2.2 Authentication Phase;74
14.2.3;2.3 Password Change Phase;75
14.3;3 Cryptanalysis of Lee´s Scheme;75
14.3.1;3.1 Failure to Preserve User Anonymity;76
14.3.2;3.2 Off-line Password Guessing Attack;76
14.3.3;3.3 User Impersonation Attack;76
14.4;4 Conclusions;77
14.5;References;77
15;The Effects of Information Quality on Mental Model and Interactivity in a Smartphone Context;79
15.1;1 Introduction;79
15.2;2 Research Methodology, Data Analysis, and Results;81
15.3;3 Discussion and d Conclusion;83
15.4;References;84
15.5;Appendix;84
16;Immersive Dissection Simulator Using Multiple Volume Rendering;85
16.1;1 Introduction;85
16.2;2 Immersive Virtual Dissection System;86
16.3;3 Experimental Result;88
16.4;4 Conclusion;89
16.5;References;90
17;Business Informatics Management Model;91
17.1;1 Introduction;91
17.2;2 Research Method;92
17.3;3 Business Informatics Management Model;92
17.3.1;3.1 Problem Identification and Motivation;92
17.3.2;3.2 Solution Objectives;93
17.3.3;3.3 MBI Model Design and Development;93
17.3.4;3.4 Demonstration , Evaluation and Communication;94
17.4;4 Conclusion;96
17.5;References;97
18;Group Awareness in Task Context-Aware E-mail Platform;98
18.1;1 Introduction;98
18.2;2 Related Work;99
18.3;3 Task Context-Aware E-mail Platform;100
18.3.1;3.1 System Overview;100
18.3.2;3.2 Task Context Model;101
18.3.3;3.3 E-mail Form Composition Service;101
18.3.4;3.4 Data Extraction Service;102
18.3.5;3.5 Group Awareness;102
18.4;4 Discussion;102
18.5;5 Conclusions and Future Works;103
18.6;References;103
19;An Android-Based Feed Behavior Monitoring System for Early Disease Detection in Livestock;104
19.1;1 Introduction;104
19.2;2 Related Works;105
19.3;3 Livestock Feed d Monitoring System;106
19.3.1;3.1 Workflow of th he Feed Monitoring System;107
19.4;4 Mobile Applica ation;107
19.5;5 Conclusion;108
19.6;References;109
20;Location-Aware WBAN Data Monitoring System Based on NoSQL;110
20.1;1 Introduction;110
20.2;2 Location-Aware WBAN Monitoring System;111
20.3;3 Experimental Results;114
20.4;4 Conclusions;115
20.5;References;115
21;Optimization of a Hybrid Renewable Energy System with HOMER;117
21.1;1 Introduction;117
21.2;2 Literature Review;118
21.3;3 Three Principal Tasks of HOMER;118
21.3.1;3.1 Simulation;118
21.3.2;3.2 Optimization;119
21.3.3;3.3 Sensitivity;119
21.4;4 Modeling System Components;119
21.4.1;4.1 Electrical Load Profile;119
21.4.2;4.2 PV Panel;119
21.4.3;4.3 Turbine;120
21.5;5 Hybrid System Development;120
21.6;6 Conclusion;122
21.7;References;123
22;Efficient Character Input Scheme Based on Gyro-Accelerometer Sensor for NUI;124
22.1;1 Introduction;124
22.2;2 Related Works;125
22.3;3 VGA Input Scheme;126
22.4;4 Design of VGA;127
22.5;5 Implementation of VGA;128
22.6;6 Conclusions;128
22.7;References;129
23;Ubiquitous Bluetooth Mobile Based Remote Controller for Home Entertainment Centre;131
23.1;1 Introduction;132
23.2;2 System Architecture;132
23.3;3 Android Motion Control Design and Implementation;135
23.4;4 Concluding Remark;136
23.5;References;137
24;Robust Feature Design for Object Detection;138
24.1;1 Introduction;138
24.2;2 Proposed Algorithm: Oriented Angular Keypoints;139
24.2.1;2.1 Preprocessing (Outline Detection);140
24.2.2;2.2 Extract Principal Outline;140
24.2.3;2.3 Constitute Block Region;141
24.2.4;2.4 Computation of Angle and Direction;141
24.2.5;2.5 Object Matching;142
24.3;3 Experimental Results;142
24.4;4 Conclusion;143
24.5;References;144
25;An Efficient Key Management Scheme for Advanced Metering Infrastructure*;145
25.1;1 Introduction;145
25.2;2 Related Work;146
25.3;3 Identity-Based Hierarchical Key Management;147
25.3.1;3.1 Network Model;147
25.3.2;3.2 Key Establishment Overview;147
25.3.3;3.3 Key Generation;147
25.3.4;3.4 Key Management;147
25.4;4 Experimental R Results;148
25.5;5 Conclusion;149
25.6;References;149
26;Levenshtein Distance-Based Posture Comparison Method for Cardiopulmonary Resuscitation Education;151
26.1;1 Introduction;151
26.2;2 Posture Comparison Processes;152
26.3;3 Experiments;153
26.4;4 Conclusion;155
26.5;References;156
27;HMM Based Duration Control for Singing TTS;157
27.1;1 Introduction;157
27.2;2 HMM Based Singing TTS;158
27.3;3 Duration Control;159
27.3.1;3.1 Maximum Likelihood Based Duration Control Method;159
27.3.2;3.2 State Level Analysis Based Duration Control;160
27.3.3;3.3 Syllable Analysis Based Duration Control Method;161
27.4;4 Experimental Results and Conclusion;161
27.5;5 Conclusion;162
27.6;References;162
28;Data Analysis of Automated Monitoring System Based on Target Features;164
28.1;1 Introduction;164
28.2;2 System Scheme Design;165
28.3;3 Motion Detection System;166
28.4;4 Distance Calculation Using Ultrasonic Signal;167
28.5;5 Experiments and Performance Assessment;168
28.6;6 Conclusions;170
28.7;References;170
29;A Persistent Web Data Architecture with Named Data Networking;172
29.1;1 Introduction;172
29.2;2 System Design;173
29.2.1;2.1 Design Considerations;173
29.2.2;2.2 Architecture;174
29.3;3 Conclusion;177
29.4;References;177
30;Load Shedding for Window Queries Over Continuous Data Streams;178
30.1;1 Introduction;178
30.2;2 Preliminaries;179
30.2.1;2.1 Time-Based Windows;179
30.2.2;2.2 Disorder Control;180
30.3;3 Proposed Method;181
30.4;4 Conclusion and Future Work;183
30.5;References;183
31;Improved Location Estimation Method of Trilateration in Ubiquitous Computing Indoor Environment;184
31.1;1 Introduction;184
31.2;2 Trilateration-Based Beacon Location Estimation Method;185
31.3;3 Experiment;187
31.4;4 Conclusions;188
31.5;References;188
32;Performance Comparison of Relational Databases and Columnar Databases Using Bitmap Index for Fast Search of 10Gbps Network Flows;189
32.1;1 Introduction;189
32.2;2 Network Flows;190
32.3;3 Queries;190
32.4;4 Loading Time;191
32.5;5 Search Time;192
32.6;6 Conclusion;193
32.7;References;193
33;Group ID Issuing Model Using Temporal Explicit Movement in Social Life Logging;194
33.1;1 Introduction;195
33.2;2 Method;195
33.2.1;2.1 Experimental Method;195
33.2.2;2.2 Signal Analysis;196
33.2.3;2.3 Identifying Group;197
33.3;3 Result;198
33.4;4 Discussion;199
33.5;References;200
34;An Analysis of Infographic Design for Life-Logging Application;201
34.1;1 Introduction;201
34.2;2 Life-Logging;202
34.2.1;2.1 Concept and Features of Life-Logging;202
34.2.2;2.2 Life-Logging Information;202
34.3;3 Analysis of Life-Logging Applications;202
34.3.1;3.1 Method and Scope of Life-Logging Application Analysis;202
34.3.2;3.2 Results of Life-Logging Infographic Design Analysis;203
34.4;4 Conclusion;207
34.5;References;207
35;Cardiovascular Synchrony for Determining Significant Group in Social Life Logging;208
35.1;1 Introduction;208
35.2;2 Materials and Methods;209
35.2.1;2.1 Participants;209
35.2.2;2.2 Task Procedures and Experimental Task;209
35.2.3;2.3 Analysis Metho od;210
35.3;3 Result;211
35.4;4 Conclusion and Discussion;212
35.5;References;213
36;Correlation Between Heart Rate and Image Components;215
36.1;1 Introduction;215
36.2;2 Proposed Method;216
36.2.1;2.1 Heart Rate Measurement;216
36.2.2;2.2 Image Components;217
36.3;3 Experiments and Results;218
36.3.1;3.1 Configuration;218
36.3.2;3.2 Results;219
36.4;4 Conclusion;220
36.5;References;220
37;Experimental Verification of Gender Differences in Facial Movement According to Emotion;222
37.1;1 Introduction;222
37.2;2 Method of Facial Feature Extraction;224
37.3;3 Experimental Results;225
37.4;4 Conclusion;226
37.5;References;227
38;Heart Rate Synchronization with Spatial Frequency of Visual Stimuli;229
38.1;1 Introduction;229
38.2;2 Experimental Method;230
38.2.1;2.1 Visual Stimuli;230
38.2.2;2.2 Heart Rate Measurement;231
38.2.3;2.3 Experimental Procedure;232
38.3;3 Results;233
38.4;4 Conclusion;233
38.5;References;234
39;Effective Similarity Measurement for Key-Point Matching in Images;235
39.1;1 Introduction;235
39.2;2 Similarity Measures Between Images with Key-Points;236
39.2.1;2.1 Related Works;236
39.2.2;2.2 Proposed Simil larity Measure;237
39.3;3 Experiments a and Results;238
39.4;4 Conclusion;239
39.5;References;240
40;Vocabulary Modeling of Social Emotion Based on Social Life Logging;241
40.1;1 Introduction;241
40.2;2 Method;242
40.2.1;2.1 Sampling of Vocabularies;242
40.2.2;2.2 Analysis of Morpheme;243
40.3;3 Analysis;244
40.3.1;3.1 Frequency Analysis;244
40.3.2;3.2 Similarity Evaluation;244
40.3.3;3.3 Multi-dimensional Scaling;245
40.3.4;3.4 Card Sorting;245
40.4;4 Results;246
40.5;5 Discussion;248
40.6;References;248
41;LIDAR Simulation Method for Low-Cost Repetitive Validation;249
41.1;1 Introduction;249
41.2;2 Related Work;250
41.3;3 LIDAR Simulation System Structure;250
41.3.1;3.1 LIDAR Sensing Module;251
41.3.2;3.2 Binary File Generation Module;252
41.4;4 Experiment and Analysis;252
41.5;5 Conclusion;254
41.6;References;254
42;Posture Recognition Using Sensing Blocks;255
42.1;1 Introduction;255
42.2;2 Related Work;256
42.3;3 Posture Recognition;256
42.4;4 Recognition Ex xperiment;258
42.5;5 Conclusions;258
42.6;References;259
43;Design of Secure Protocol for Session Key Exchange in Vehicular Cloud Computing;260
43.1;1 Introduction;260
43.2;2 VANET and Vehicular Cloud Architecture;261
43.2.1;2.1 VANET;261
43.2.2;2.2 Vehicular Cloud Architecture;261
43.3;3 Secure Protocol for Session Key Exchange;262
43.4;4 Security Analysis;264
43.4.1;4.1 Replay Attack;264
43.4.2;4.2 Eavesdropping and Brute Force Attack;264
43.4.3;4.3 Mutual Authentication;265
43.5;5 Conclusion;265
43.6;References;265
44;Zero-Knowledge Authentication for Secure Multi-cloud Computing Environments;266
44.1;1 Introduction;266
44.2;2 Multi-cloud Computing;267
44.2.1;2.1 Multi-cloud;267
44.2.2;2.2 Cloud Type;267
44.3;3 Zero-Knowledge Authentication Protocol;268
44.4;4 Security Analysis;270
44.4.1;4.1 Replay Attack and Relay Attack;270
44.4.2;4.2 Anonymity and Eavesdropping;270
44.4.3;4.3 Forward Security and Error Detection;271
44.5;5 Conclusion;271
44.6;References;271
45;PUF-Based Privacy Protection Method in VANET Environment;273
45.1;1 Introduction;273
45.2;2 Vehicular Ad-hoc Network (VANET);274
45.3;3 Physical Unclonable Functions(PUF);275
45.4;4 Proposed Protocol;275
45.4.1;4.1 OBU Mutual Authentication Phase;275
45.4.2;4.2 OBU Handover r Phase;276
45.5;5 Security Evalu uation;277
45.5.1;5.1 g Eavesdropping Attacks;277
45.5.2;5.2 Masquerading Attacks;277
45.5.3;5.3 Replay Attacks;278
45.5.4;5.4 Vehicle Anonymity;278
45.6;6 Conclusion;278
45.7;References;278
46;Design of Authentication Protocol Based on Distance-Bounding and Zero-Knowledge for Anonymity in VANET;279
46.1;1 Introduction;279
46.2;2 VANET (Vehicular ad hoc networks);280
46.2.1;2.1 VANET Overview;280
46.2.2;2.2 VANET Authentication Security Considerations;280
46.3;3 Zero-Knowledge Authentication;281
46.3.1;3.1 Zero-Knowledge Authentication Properties;281
46.4;4 Distance-Bounding Protocol;281
46.4.1;4.1 Distance-Bounding Overview;281
46.5;5 Proposal;281
46.5.1;5.1 Protocol Process;283
46.6;6 Security Analysis;283
46.6.1;6.1 Resistance to Relay Attack;283
46.6.2;6.2 Ensures Anonymity;283
46.6.3;6.3 Forward Security and Error Detection;284
46.7;7 Conclusion;284
46.8;References;284
47;Design of Exploitable Automatic Verification System for Secure Open Source Software;285
47.1;1 Introduction;285
47.2;2 Preliminaries;286
47.2.1;2.1 Open Source Software(OSS);286
47.2.2;2.2 Web Crawling;286
47.2.3;2.3 Software Testing Methodologies;287
47.2.4;2.4 Information Related to Global Vulnerabilities;287
47.3;3 Design of Exploitable Automatic Verification System;288
47.3.1;3.1 Pre-Execution Procedure;288
47.3.2;3.2 Exploitable Verification Part;289
47.4;4 Conclusion;290
47.5;References;290
48;User Authentication Method Design Based on Biometrics in a Multi-cloud Environment;292
48.1;1 Introduction;292
48.2;2 Learning System;293
48.2.1;2.1 Multi Cloud;293
48.2.2;2.2 Biometric Authentication;293
48.3;3 Proposed Protocol;294
48.4;4 Security Analysis;296
48.4.1;4.1 Replay Attack;296
48.4.2;4.2 Brute Force Attack;296
48.4.3;4.3 Eavesdropping Attacks;296
48.5;5 Conclusion;297
48.6;References;297
49;A Study on Framework for Developing Secure IoT Service;298
49.1;1 Introduction;298
49.2;2 Related Works;298
49.3;3 Proposal for IoT Security Framework;299
49.3.1;3.1 IoT Security Principles;300
49.3.2;3.2 Protection for Key Value of Key Management and Authentication;301
49.4;4 Conclusions;302
49.5;References;302
50;Device Dedication in Virtualized Embedded Systems;304
50.1;1 Introduction;304
50.2;2 IO Virtualization in Embedded Systems;305
50.3;3 Implementatio on;306
50.4;4 Conclusion;307
50.5;References;308
51;An Estimation Filtering for Packet Loss Probability Using Finite Memory Structure Strategy;309
51.1;1 Introduction;309
51.2;2 PLP Estimation Filter with Finite Memory Structure Strategy;310
51.3;3 Computer Simulations;313
51.4;4 Concluding Remarks;314
51.5;References;315
52;Cryptanalysis of User Authentication Scheme Preserving Anonymity for Ubiquitous Devices;316
52.1;1 Introduction;316
52.2;2 Review in Djellali et al.´s Scheme;317
52.2.1;2.1 Setup Phase;317
52.2.2;2.2 Registration Phase;318
52.2.3;2.3 Login and Authentication Phase;318
52.2.4;2.4 Password Change Phase;319
52.3;3 Security Analysis of Djellali´s Scheme;319
52.3.1;3.1 Insider Attack;319
52.3.2;3.2 Smart Card Stolen and Offline-Password Guessing Attack;319
52.3.3;3.3 Impersonation Attack;320
52.3.4;3.4 Replay Attack;320
52.4;4 Conclusion;321
52.5;References;321
53;Feasibility and Reliability of a Mobile Application for Assessing Unilateral Neglect;323
53.1;1 Introduction;323
53.2;2 Methods;324
53.2.1;2.1 The Proposed Digital Testing Methods;325
53.3;3 Results;327
53.4;4 Conclusion;328
53.5;References;328
54;A Context-Aware Framework for Mobile Computing Environment;330
54.1;1 Introduction;331
54.2;2 Related Works;331
54.3;3 Design of Framework for Context Aware System;332
54.4;4 Applying the Framework for Monitoring System;333
54.5;5 Conclusion;335
54.6;References;335
55;The Design of Log Analysis Mechanism in SDN Quarantined Network System;336
55.1;1 Introduction;336
55.2;2 Security Threats Detectable Through Log Analysis;338
55.3;3 Features of NoSQL and Map-Reduce Technology;338
55.4;4 Log Analysis Mechanism;339
55.5;5 Conclusion;340
55.6;References;341
56;A Study on the Defense MITM with Message Authentication in WLAN Environments;342
56.1;1 Introduction;342
56.2;2 MITM Attack Scenario;343
56.2.1;2.1 Environment C Construction;343
56.2.2;2.2 Attack Process;344
56.2.3;2.3 Riskiness Analy lysis of Application;344
56.3;3 Foundation Te echnique;345
56.3.1;3.1 Message Authe entication Code;345
56.3.2;3.2 Security Comm munication Model Based on MAC;346
56.4;4 Proposed Mod del;346
56.5;5 Evaluation on the Proposed Model;347
56.6;6 Conclusion;348
56.7;References;349
57;Interactive Activity Recognition Using Articulated-Pose Features on Spatio-Temporal Relation;350
57.1;1 Introduction;350
57.2;2 Methodology;352
57.2.1;2.1 Joint Detection;352
57.2.2;2.2 Feature Extraction;352
57.3;3 Experiment;354
57.4;4 Conclusion;355
57.5;References;356
58;Development of Learner-Centric Teaching-Learning Application Model for Ubiquitous Learning;357
58.1;1 Introduction;357
58.2;2 Theoretical Background;358
58.2.1;2.1 Ubiquitous Learning;358
58.2.2;2.2 App Inventor;359
58.3;3 Development of Learner-Centric Teaching-Learning Application Based on Ubiquitous Learning;360
58.4;4 Application to Education Field;361
58.4.1;4.1 Study Method and Research Tool;361
58.4.2;4.2 Study Findings;362
58.5;5 Conclusion;362
58.6;References;363
59;EAP: Energy-Awareness Predictor in Multicore CPU;364
59.1;1 Introduction;364
59.2;2 Proposed Method;365
59.2.1;2.1 Target Process;365
59.2.2;2.2 Prediction Model;366
59.3;3 Performance Evaluation;367
59.3.1;3.1 Experiments;367
59.3.2;3.2 Results;368
59.4;4 Conclusion;368
59.5;References;369
60;Design and Implementation of LMS for Sharing Learning Resources in e-Learning;370
60.1;1 Introduction;370
60.2;2 Design and Implementation;371
60.3;3 Suitability Review;374
60.4;4 Conclusion and Suggestions;375
60.5;References;375
61;A Zero-Watermarking Scheme Based on Spread Spectrum and Holography;377
61.1;1 Introduction;377
61.2;2 Related Work;378
61.2.1;2.1 Spread Spectrum;378
61.2.2;2.2 Holography;379
61.2.3;2.3 Visual Cryptography;379
61.3;3 Zero Watermark Scheme;380
61.3.1;3.1 Zero Watermark Embedding;380
61.3.2;3.2 Zero Watermar rk Extraction;381
61.4;4 Experimental Re esults and Analysis;381
61.5;5 Conclusions;383
61.6;References;383
62;A Novel Seamless Redundancy Protocol for Ethernet;384
62.1;1 Introduction;384
62.2;2 The Proposed RPE;385
62.2.1;2.1 RPE Concepts;385
62.2.2;2.2 RPE Frame Structure;386
62.2.3;2.3 RPE Operations;387
62.3;3 Redundancy Performance;388
62.4;4 Simulations;389
62.5;5 Conclusion;390
62.6;References;390
63;Mutual Authentication Scheme Based on GSM for NFC Mobile Payment Environments;391
63.1;1 Introduction;391
63.2;2 Related Work;392
63.3;3 Security Requirements;392
63.4;4 Proposed Scheme;393
63.4.1;4.1 System Parameters;393
63.4.2;4.2 Mutual Authentication Phase (Key Agreement);393
63.5;5 Conclusion;394
63.6;References;395
64;Necessity of Incentive System for the First Uploader in Client-Side Deduplication;396
64.1;1 Introduction;396
64.2;2 Brief Review of Client-Side Deduplication;397
64.3;3 Disadvantage for the First Uploader in Client-Side Dedup;398
64.3.1;3.1 Privacy Leakage;399
64.3.2;3.2 Expensive Service for Devoted Behavior;399
64.4;4 Incentive System in Client-Side Deduplication;400
64.5;5 Conclusion;400
64.6;References;401
65;Design and Implementation of Disaster Information Alert System Using Python in Ubiquitous Environment;402
65.1;1 Introduction*;402
65.2;2 Research of Disaster Based Ubiquitous;403
65.3;3 Disaster Information Alert System;405
65.3.1;3.1 Implementation n of DI Alert System;406
65.4;4 Conclusions;407
65.5;References;408
66;A Study on the Development of Real-Time Analysis Monitoring System and Its Application of Medical Ins;409
66.1;1 Introduction;409
66.2;2 Related Research;410
66.2.1;2.1 Hadoop;410
66.2.2;2.2 Complex Event Processing;410
66.2.3;2.3 Hadoop and EP CE for Big Data Approach;411
66.3;3 System Compo ositions and Implementation;411
66.4;4 Conclusion;414
66.5;References;414
67;Green Treatment Plan Selection Based on Three Dimensional Fuzzy Evaluation Model;415
67.1;1 Introduction;415
67.2;2 Three Dimensional Evaluation Model;416
67.3;3 Green Medical Treatment Plan Selection Strategy Based on Three Dimension Fuzzy Evaluation Model;417
67.3.1;3.1 Establishing the Membership Functions;417
67.3.2;3.2 Degree of Membership Aggregation;418
67.3.3;3.3 Ranking the Treatment Plans;419
67.4;4 An Illustrative Example;419
67.5;5 Conclusions;420
67.6;References;420
68;Performance Analysis of Format-Preserving Encryption Based on Unbalanced-Feistel Structure;422
68.1;1 Introduction;422
68.2;2 Format-Preserving Encryption with Feistel Structure;423
68.3;3 Implementation of Unbalanced-Feistel FPE;424
68.3.1;3.1 FFX[radix] with Unbalanced-Feistel Structure;424
68.3.2;3.2 VAES3 and BPS with Unbalanced-Feistel Structure;425
68.4;4 Performance Analysis;426
68.5;5 Conclusion;426
68.6;References;427
69;Energy Consumption Reduction Technique on Smart Devices for Communication-Intensive Applications;428
69.1;1 Introduction;428
69.2;2 Related and Previous Works;429
69.3;3 An Energy Consumption Reduction Technique;430
69.4;4 Conclusions;431
69.5;References;432
70;Framework of Service Accountability and Policy Representation for Trustworthy Cloud Services;433
70.1;1 Introduction;433
70.2;2 Related Studies;434
70.3;3 Framework for Service Accountability Between Cloud Services;435
70.3.1;3.1 Data Accountability vs. Service Accountability;435
70.3.2;3.2 Framework of the Service Accountability for the Cloud;435
70.3.3;3.3 Representational Scheme of Service Accountability Policy;436
70.4;4 Comparison;438
70.5;5 Conclusion;438
70.6;References;439
71;A New Visual Pet Activities Monitoring System Design;440
71.1;1 Introduction;440
71.2;2 System Design;441
71.2.1;2.1 Motion Detection;441
71.2.2;2.2 Object Recognition;441
71.3;3 System Structure;443
71.4;4 Conclusion;445
71.5;References;445
72;A Study of Security Level in Cloud Computing;446
72.1;1 An Overview on Cloud Computing;446
72.2;2 Literature Survey;447
72.3;3 Some of Security Metrics of Cloud Computing;447
72.4;4 Security Issues and Solutions;448
72.4.1;4.1 Security Challenges;448
72.4.2;4.2 Some Solutions on Security Issues;449
72.4.3;4.3 Security Level Analysis;450
72.5;5 Conclusion and Future Work;451
72.6;References;451
73;The Dynamic Unequal Clustering Routing Protocol Based on Efficiency Energy in Wireless Sensor Network;452
73.1;1 Introduction;453
73.2;2 Related Works;453
73.3;3 The System Model and Assumption;453
73.3.1;3.1 The System Model;453
73.3.2;3.2 The Energy Model;454
73.4;4 Dynamic Unequal Clustering Routing Protocol Based on Efficiency Energy in Wireless Sensor Network;455
73.4.1;4.1 Set-up Phase;455
73.4.2;4.2 Steady-Set Phase;455
73.4.3;4.3 Reconstruction Phase;455
73.5;5 Analysis and Simulation Result;456
73.6;6 Conclusion;458
73.7;References;458
74;A Study on the Localization Algorithm Using RSSI and Directional Antennas Between Sensor Nodes for the DV-HOP Algorithm;459
74.1;1 Introduction&;459
74.2;2 Localization Algorithm Model;460
74.3;3 Simulation and Analysis;461
74.4;4 Conclusion;463
74.5;References;464
75;Estimation of Human Social Relation Based on Device Connectivity;465
75.1;1 Introduction&;465
75.2;2 Related Works;466
75.3;3 Human Sociality Based on Device Connectivity;467
75.4;4 Experimental Results R;468
75.5;5 Conclusion;469
75.6;References;470
76;Secure Framework for Software Defined Based Internet of Things;471
76.1;1 Introduction&;471
76.2;2 Software-Defined Internet of Things;472
76.3;3 SDIoT Secure Framework Requirements;473
76.4;4 SDIoT Secure Frameworks;474
76.4.1;4.1 Infrastructure;474
76.4.2;4.2 Control Layer;474
76.4.3;4.3 Application Layer;475
76.5;5 Conclusion;476
76.6;References;476
77;Secure Data Access Control Scheme for Smart Home;477
77.1;1 Introduction&;477
77.2;2 Analysis of Security Requirements;478
77.2.1;2.1 Data Confidentiality;478
77.2.2;2.2 Device Authentication;478
77.2.3;2.3 Access Control;478
77.3;3 Proposed Scheme;479
77.3.1;3.1 Proposed Scheme Component;479
77.3.2;3.2 Data Access Control;480
77.4;4 Security Analysis of the Proposed Scheme;481
77.4.1;4.1 Data Confidentiality;481
77.4.2;4.2 Authentication;481
77.4.3;4.3 Access Control;482
77.5;5 Conclusion;482
77.6;References;482
78;A Combination of PSO-Based Feature Selection and Tree-Based Classifiers Ensemble for Intrusion Detection Systems;483
78.1;1 Introduction;483
78.2;2 Related Work;484
78.2.1;2.1 PSO and Correlation-Based Feature Selection;484
78.2.2;2.2 Fusion of Tree-Based Classifiers;485
78.3;3 Experimental Setup;485
78.4;4 Result and Discussion;487
78.5;5 Conclusion;488
78.6;References;488
79;Secure Traffic Data Transmission Protocol for Vehicular Cloud;490
79.1;1 Introduction;490
79.2;2 System Architecture;491
79.3;3 Protocol Description;492
79.4;4 Security Analysis and Performance;494
79.5;5 Conclusion;495
79.6;References;495
80;A Short-Range Tracking System Based on Bluetooth Radio Identification: An Algorithm and Its Implementation;497
80.1;1 Introduction;497
80.2;2 The Proposed Approach;498
80.3;3 Implementatio on;499
80.3.1;3.1 BT Transmitter;499
80.3.2;3.2 BT Receiver;500
80.4;4 Detection Analyses;501
80.5;5 Conclusions;503
80.6;References;504
81;Design and Implementation of a Collaboration Messenger System Based on MQTT Protocol;505
81.1;1 Introduction;505
81.2;2 Related Research;506
81.2.1;2.1 Message Transmission Protocol;506
81.2.2;2.2 MQTT Protocol;506
81.3;3 Design of MQTT Based Collaboration Messenger;507
81.3.1;3.1 Reliable Messages Delivery Technique;507
81.3.2;3.2 Design of MQTT Based Collaboration Messenger Protocol;508
81.3.3;3.3 Collaboration Messenger System Configuration;509
81.4;4 Experiment;510
81.4.1;4.1 Experiment Environment;510
81.4.2;4.2 Result of Experiment;510
81.5;5 Conclusion;510
81.6;References;511
82;Financial Security Protocol and Service Model for Joint Account Banking Transaction;512
82.1;1 Introduction;512
82.2;2 Study on the Diffie-Hellman and Station-to-Station Protocols;513
82.2.1;2.1 Diffie-Hellman Protocol and the Features;513
82.2.2;2.2 Station-to-Station Protocol;514
82.3;3 Financial Security Protocol Design for Joint Accounts;514
82.3.1;3.1 The Proposing Security Protocol;514
82.3.2;3.2 Safety Verification of Financial Security Protocol;515
82.4;4 The Financial Security Service Model of Joint Account;516
82.5;5 Conclusion;517
82.6;References;518
83;Development of a Cursor for Persons with Low Vision;519
83.1;1 Introduction&;519
83.2;2 Design of a Cursor for Persons with Low Vision;520
83.2.1;2.1 Basic Functions;521
83.2.2;2.2 Advanced Functions;521
83.3;3 Performance Evaluation;522
83.3.1;3.1 Experimental Design;522
83.3.2;3.2 Experimental Result;522
83.4;4 Conclusion;524
83.5;References;524
84;Implementation of Unified Gesture Library for Multiple-Devices Environments;525
84.1;1 Introduction;526
84.2;2 Related Works;527
84.3;3 UGesture Platform;527
84.4;4 Applications Using the UGesture Platform;528
84.5;5 Conclusion;530
84.6;References;530
85;Design of the Real-Time Mobile Push System for Implementation of the Shipboard Smart Working*;531
85.1;1 Introduction;532
85.2;2 Related Research;533
85.2.1;2.1 Push System;533
85.3;3 Design of the Real-time Mobile Push System for Satellite Communication to Implement Smart Work on the Ship;534
85.4;4 Conclusion and Future Work;536
85.5;References;537
86;A Shipboard Secret Ballot System for the ICT-Isolated Ocean Crews;539
86.1;1 Introduction&;539
86.2;2 Related Research;540
86.2.1;2.1 Data Flow Diagram of the On-board Secret Ballot System;540
86.2.2;2.2 VMS / e-NOAD;541
86.2.3;2.3 e-NOA/D (Electronic Notification of Arrival / Departure) System;541
86.3;3 Shipboard Secret Ballot Algorithm;541
86.3.1;3.1 1st Step: Confirmation of On-Board Crews Eligible for the Ballot (D-30 days);542
86.3.2;3.2 2nd Step: Installation And tests of the Voting Machines (D-15 days);542
86.3.3;3.3 3rd Step: Updating the Ballot-Eligible Crew List (2nd) (D-7 days);543
86.3.4;3.4 4th Step: Commencement of the Ballot (D-day);543
86.3.5;3.5 5th Step: Vote Counting Method;543
86.3.6;3.6 6th Step: Transmitting the Vote Count Results (ship´s DID);544
86.4;4 Shipboard Secret Ballot System;544
86.5;5 Conclusion;546
86.6;References;546
87;Secure Deletion for Flash-Based Self-Encrypting Drives;548
87.1;1 Introduction;548
87.2;2 Background;549
87.2.1;2.1 Self-Encrypting Drive;549
87.2.2;2.2 Phase-Change Memory;550
87.3;3 Secure Deletion for Self-Encrypting Flash Memory;550
87.4;4 Performance;553
87.5;5 Conclusion;554
87.6;References;555
88;A Distributed Mobility Support in SDN-Based LTE/EPC Architecture;556
88.1;1 Introduction;556
88.2;2 SDN-Based Distributed Mobility Support;558
88.2.1;2.1 SDN-Based DMM Architecture;558
88.2.2;2.2 SDN-Based DMM (SDMM);559
88.3;3 Performance Evaluation;560
88.4;4 Conclusions;562
88.5;References;562
89;Implementation of Wireless Communication- Based Video Control System for Media Façade;563
89.1;1 Introduction;563
89.2;2 Backgrounds;564
89.2.1;2.1 Technology of Realizing Media Façade;564
89.2.2;2.2 Multi Image Display;565
89.3;3 Wireless Video Control System that Uses RF Communication;566
89.3.1;3.1 RF Communication;566
89.3.2;3.2 Wireless Video Control System;566
89.4;4 Conclusion;568
89.5;References;569
90;Adaptive Clustering of Merchandise Code for Recommender System with an Immediate Effect;570
90.1;1 Introduction;570
90.2;2 Related Works;571
90.2.1;2.1 RFM Model;571
90.2.2;2.2 Clustering;572
90.2.3;2.3 BN(Bayesian Network);573
90.3;3 Our Proposal for a Recommender System with an Immediate Effect;574
90.3.1;3.1 Adaptive Clustering of Merchandise Code;574
90.4;4 The Environment of Implementation and Experiment and Evaluation;576
90.4.1;4.1 Experimental Data for Evaluation;576
90.4.2;4.2 Experiment and Evaluation;577
90.5;5 Conclusions;578
90.6;References;579
91;Bayesian Probability-Based Motion Estimation Method in Ubiquitous Computing Environments;580
91.1;1 Introduction;580
91.2;2 Motion Estimation Processes;581
91.3;3 Experiment;582
91.4;4 Conclusion;585
91.5;References;585
92;Occlusion Detection Using Multi-mode Mean-shift Tracking;586
92.1;1 Introduction;586
92.2;2 Mean-shift Tracking Using Multi-mode Kernel;588
92.2.1;2.1 Partitioning the Target Region;588
92.2.2;2.2 Target Model Using Multi-mode Global Kernel Weight;588
92.2.3;2.3 Target Candidate Using Multi-mode Global Kernel Weight;589
92.2.4;2.4 Mean-shift Tracking;589
92.3;3 Occlusion Detection Using Coefficient Variation of Bhattachryya Coefficient;590
92.4;4 Experimental Results;590
92.4.1;4.1 Tracking Errors;591
92.4.2;4.2 Occlusion Detection Results;592
92.5;5 Conclusions;592
92.6;References;593
93;OCSP Modification for Supporting Anonymity and High-Speed Processing in Vehicle Communication System;594
93.1;1 Introduction;594
93.2;2 Traditional Message Transmission Method Using Certificate;595
93.2.1;2.1 Message Format;595
93.2.2;2.2 Operations;596
93.3;3 Message Transmission Method Using Proposed OCSP Response;596
93.3.1;3.1 Proposed OCSP Response Format;597
93.3.2;3.2 Message Format;597
93.3.3;3.3 Operations;598
93.4;4 Conclusions;599
93.5;References;599
94;A Study on the New Ethernet Communication Method Using Virtual MAC Address;600
94.1;1 Introduction;600
94.2;2 Designs;601
94.2.1;2.1 Frame Format;601
94.2.2;2.2 VARP;602
94.3;3 Operations;603
94.4;4 Conclusions;605
94.5;References;605
95;A Hybrid Prediction Model Integrating FCM Clustering Algorithm with Supervised Learning;606
95.1;1 Introduction;606
95.2;2 Related Work;607
95.2.1;2.1 FCM (Fuzzy C-Means) Clustering Algorithm;607
95.2.2;2.2 Numerical Prediction Using the FCM Clustering Algorithm;608
95.3;3 Design of A Hybrid Prediction Model;609
95.3.1;3.1 Process of the Proposed Prediction Model;609
95.3.2;3.2 Algorithm of the Proposed Model and its Verification;610
95.4;4 Implementation and Evaluation;611
95.4.1;4.1 Results Predicted by Using Back-Propagation Algorithm;612
95.4.2;4.2 Hybrid Fuzzy C C-Means (FCM) Clustering;613
95.4.3;4.3 Analysis of the Function of the Proposed Model;615
95.5;5 Conclusion;615
95.6;References;616
96;Environmental Monitoring Over Wide Area in Internet of Things;617
96.1;1 Introduction;617
96.2;2 EMoMC;618
96.2.1;2.1 Components in System;618
96.2.2;2.2 Local Storage Management Algorithm;619
96.2.3;2.3 MC;620
96.2.4;2.3 MC´s Data Collecting Algorithm;620
96.3;3 Simulation Works;621
96.3.1;3.1 Local Storage Management Algorithm;621
96.4;4 Conclusion;622
96.5;References;622
97;Speech-to-Text-Based Life Log System for Smartphones;623
97.1;1 Introduction;623
97.2;2 Proposed System Overview;624
97.3;3 Experimental Results;626
97.4;4 Conclusion and Future Works;628
97.5;References;628
98;The Packet Filtering Method with Packet Delay Distribution Forecasting for Stability and Synchronization in a Heterogeneous Network;629
98.1;1 Introduction;629
98.2;2 Applications of Packet Filtering Method;631
98.2.1;2.1 Packet Filtering Method(PFM);631
98.2.2;2.2 Numerical Sim mulation;632
98.3;3 Conclusion;634
98.4;References;634
99;An Automatic Feedback System Based on Confidence Deviations of Prediction and Detection Models for English Phrase Break;635
99.1;1 Introduction;635
99.2;2 Material;636
99.2.1;2.1 A Corpus for Phrase Break Models;636
99.2.2;2.2 Preprocessing the BU Corpus;636
99.3;3 Methods;637
99.3.1;3.1 Prediction Mod del;637
99.3.2;3.2 Detection Model;638
99.3.3;3.3 Feedback Provision;638
99.4;4 Results;639
99.4.1;4.1 Validation of the Prediction and Detection Models;639
99.4.2;4.2 Validation of the Feedback Provision Model;640
99.5;5 Conclusion;640
99.6;References;640
100;Conceptual Design of a Network-Based Personalized Research Environment;642
100.1;1 Introduction;642
100.2;2 Related Works;643
100.2.1;2.1 Research Support Environments;643
100.2.2;2.2 Changes in Information Service Environment;644
100.3;3 Design of a Personalized Research Environment;645
100.4;4 Conclusion;647
100.5;References;647
101;Design and Implementation of the Basic Technology for Realtime Smart Metering System Using Power Line Communication for Smart Grid;648
101.1;1 Introduction;649
101.2;2 Related Research;649
101.2.1;2.1 PLC between Electronic Ammeter and Main Server;649
101.2.2;2.2 Connection System Diagram;650
101.3;3 Basic Technology for Realtime Smart Metering System;650
101.3.1;3.1 Relationship Diagram of the Power System Control Programs Using PLC;650
101.3.2;3.2 RS232-Based Protocol Design;652
101.4;4 Conclusion;652
101.5;References;653
102;Parallel Balanced Team Formation Clustering Based on MapReduce;655
102.1;1 Introduction;656
102.2;2 Parallel Balanced Team Formation Algorithm;656
102.2.1;2.1 Balanced Team Formation Algorithm;656
102.2.2;2.2 Parallel Balanced Team Formation Algorithm;657
102.3;3 Conclusion;659
102.4;References;659
103;2D Barcode Localization Using Multiple Features Mixture Model;660
103.1;1 Introduction;660
103.2;2 2D Barcode Detection System in Our Approach;661
103.2.1;2.1 2D Barcode Localization;662
103.2.2;2.2 Corner Features for 2D Barcode Localization;662
103.2.3;2.3 Variance-Frequency Distribution Model;662
103.2.4;2.4 Estimation of Final QR Code Region;663
103.3;3 Experiments;663
103.4;4 Conclusions;664
103.5;References;665
104;LPLB: A Novel Approach for Loop Prevention and Load Balancing in Ethernet Ring Networks;666
104.1;1 Introduction;666
104.2;2 LPLB Approach;667
104.2.1;2.1 LPLB Concept and Setup Procedure;667
104.2.2;2.2 Monitoring and Recovery Procedure;670
104.3;3 LPLB Performa ance Analysis;672
104.4;4 Conclusions;674
104.5;References;674
105;Design & Implementation for Emergency Broadcasting Using Agencies´ Disaster Information;675
105.1;1 Introduction&;675
105.2;2 Disaster Broadcasting in Korea;676
105.3;3 Disaster Information Contents Analysis;677
105.4;4 Implementatio on of Disaster Situation Dashboard;678
105.5;5 Conclusion;679
105.6;References;679
106;Application and Development of Service Integration Platform for Agricultural Products;680
106.1;1 Introduction;680
106.2;2 Agricultural Product´s ICT Convergence;681
106.2.1;2.1 ICT Convergence Strategy for Agricultural Products;681
106.2.2;2.2 Agricultural Products ICT Convergence Ecosystem;681
106.3;3 Agricultural Products Mobile Service Integration Platform;682
106.3.1;3.1 Mobile Service Integration Platform;682
106.3.2;3.2 Mobile Service Integration Platform Connection;683
106.4;4 Conclusion;684
106.5;References;684
107;Implementation of Kegel Exercises for Prevention of Urinary Incontinence and Treatment Thereof;685
107.1;1 Introduction;685
107.2;2 Relevant Studies;686
107.2.1;2.1 Insertable Exercise Equipment;686
107.2.2;2.2 Extracorporeal l Exercise Equipment;687
107.3;3 System Design and Main Functions;688
107.3.1;3.1 Structure of Pressure Sensors and Arduino Board System;688
107.3.2;3.2 Structure of Communication System;688
107.3.3;3.3 Construction of a Combined Server;689
107.3.4;3.4 Diagram of Program;690
107.4;4 Conclusion;690
107.5;References;691
108;A Functional Relationship Based Attestation Scheme for Detecting Compromised Nodes in Large IoT Networks;692
108.1;1 Background;692
108.2;2 Proposed Attestation Scheme;694
108.2.1;2.1 Neighbor Discovery and Verifier Election;694
108.2.2;2.2 Path Establishment and Function Assessment;695
108.2.3;2.3 Path Integration and Consistency Analysis;696
108.3;3 Analysis and Discussion;697
108.4;4 Performance Evaluation;698
108.5;5 Conclusion and Future Work;699
108.6;References;700
109;Multiple Service Robot Synchronization and Control with Surveillance System Assistance for Confined Indoor Area Applications;701
109.1;1 Introduction;702
109.2;2 Navigation and Synchronization Strategy;703
109.2.1;2.1 Grid Based Concurrent Navigation;703
109.2.2;2.2 Extension to Multi-Cell Environments;704
109.2.3;2.3 Role of Surveillance Network;704
109.3;3 Environment Adaptations;705
109.3.1;3.1 Dynamic Obstacle Management;705
109.3.2;3.2 Virtual Grid Adaptation for Fine Grain Navigation;705
109.3.3;3.3 Speed Control with Node-Ordering;706
109.4;4 Evaluations;706
109.5;5 Conclusions;708
109.6;References;708
110;Author Identification and Analysis for Papers, Reports and Patents;709
110.1;1 Introduction;709
110.2;2 Author Control Strategy;711
110.3;3 Analysis of Author Identification Results;711
110.4;4 Conclusions and Future Research;712
110.5;References;713
111;Resource-Aware Job Scheduling and Management System for Semiconductor Application;714
111.1;1 Introduction;714
111.1.1;1.1 Job Scheduling;716
111.1.2;1.2 Resource Management;716
111.2;2 Resource-Awa are Scheduling System;717
111.3;3 Dynamic Reso urce Management;719
111.4;4 Result;720
111.5;5 Conclusion;721
111.6;References;721
112;Live Mobile Learning System with Enhanced User Interaction;722
112.1;1 Introduction;722
112.2;2 Live Mobile Learning System with Enhanced user Interaction;723
112.3;3 Conclusion;726
112.4;References;727
113;Implementation of Autonomous Navigation Using a Mobile Robot Indoor;728
113.1;1 Introduction;728
113.2;2 Element Technology for Navigation;729
113.2.1;2.1 Map Building;729
113.2.2;2.2 Localization;729
113.2.3;2.3 Path Planning and Obstacle Avoidance;730
113.2.4;2.4 Integration of the Algorithm Components;731
113.3;3 Experiments;732
113.4;4 Conclusion;733
113.5;References;733
114;Convergence Modeling of Heterogeneous Medical Information for Acute Myocardial Infarction;734
114.1;1 Introduction;734
114.2;2 Analysis of AMI-related Data;735
114.3;3 Data Convergence Modeling for AMI;736
114.4;4 Conclusion;739
114.5;References;740
115;HiL Test Based Fault Localization Method Using Memory Update Frequency;741
115.1;1 Introduction;741
115.2;2 Related Work;743
115.3;3 Finding the Fault Candidates Using Memory Update Frequency;744
115.3.1;3.1 Problem Definition;744
115.3.2;3.2 Fault Localization Process;744
115.4;4 Experimental Result;747
115.5;5 Conclusion;748
115.6;References;748
116;Data Cascading Method for the Large Automotive Data Acquisition Beyond the CAN Bandwidth in HiL Testing;749
116.1;1 Introduction;749
116.2;2 Related Work;751
116.3;3 Data Cascading Method;751
116.3.1;3.1 Slicing Data into Segments;752
116.3.2;3.2 Defining Message Protocol by Reusing CAN Data Field;753
116.3.3;3.3 Data Cascading Algorithm;753
116.4;4 Experimental Result;754
116.4.1;4.1 Experiments;754
116.4.2;4.2 Evaluation;755
116.5;5 Conclusion;755
116.6;References;756
117;Classification Framework for Electropulsegraph Waves;757
117.1;1 Introduction;757
117.2;2 Classifications of Electropulsegraphy Waves Based on Logistic Regression;758
117.2.1;2.1 Regularized Logistic Regression;758
117.2.2;2.2 One-vs-all Mul lticlass Classification;759
117.3;3 Estimation Res sults;759
117.4;4 Conclusions;762
117.5;References;763
118;Optimization of LSPL Algorithm for Data Transfer in Sensor Networks Based on LEACH;764
118.1;1 Introduction;764
118.2;2 Relevant Studies;765
118.2.1;2.1 LEACH Protocol;765
118.2.2;2.2 LSPL Algorithm;765
118.3;3 Optimization of LSPL Algorithm;766
118.4;4 Simulation and Analysis;767
118.4.1;4.1 Experimental Environment;767
118.4.2;4.2 Evaluation of L LSPL Algorithm Performance;768
118.5;5 Conclusion;770
118.6;References;770
119;In-Memory Processing for Nearest User-Specified Group Search;772
119.1;1 Introduction;772
119.2;2 Problem Formulation;773
119.3;3 In-Memory NUG Query Processing;774
119.4;4 Experimental Results;776
119.5;5 Conclusion;777
119.6;References;778
120;Choreography Retrieval from the Korean POP Dance Motion Capture Database with Low-Cost Depth Cameras;779
120.1;1 Introduction;779
120.2;2 Choreography Retrieval System;780
120.3;3 Experimental Results;783
120.4;4 Conclusion and Future Work;784
120.5;References;784
121;Enhancing PIN Input for Preventing Eavesdropping in BLE Legacy Pairing;786
121.1;1 Introduction;786
121.2;2 Bluetooth;787
121.2.1;2.1 Architecture;787
121.2.2;2.2 Security s Issues;788
121.3;3 Increasing Bluetooth PIN´s Entropy;789
121.4;4 Computational Entropy Comparison;789
121.5;5 Conclusion;790
121.6;References;790
122;Erasure Codes Encoding Performance Enhancing Techniques Using GPGPU Based Non-sparse Coding Vector in Storage Systems;791
122.1;1 Introduction;791
122.2;2 Erasure Codes;792
122.3;3 GPU Based Erasure Codes Encoding Using Non-sparse Coding Matrix;793
122.4;4 Experimental Results;794
122.5;5 Conclusion;795
122.6;References;796
123;FAIR-Based Loss Measurement Model for Enterprise Personal Information Breach;797
123.1;1 Introduction;797
123.2;2 Previous Research;798
123.2.1;2.1 South Korea;798
123.2.2;2.2 The World;798
123.2.3;2.3 FAIR (Factor Analysis of Information Risk) Methodology;799
123.3;3 Loss Measurement Model;800
123.3.1;3.1 Limitations of Previous Research and Contribution of the Current Research;800
123.3.2;3.2 Probability Interval Model for Enterprise Environment;801
123.3.3;3.3 Loss Measurement Model Where Timing Issue Is Considered;802
123.3.4;3.4 Improved FAIR Methodology Process;802
123.4;4 Conclusion;803
123.4.1;4.1 Case Study and Application of the Proposed Model;803
123.4.2;4.2 Conclusion;804
123.5;References;804
124;Variational Bayesian Inference for Multinomial Dirichlet Gaussian Process Classification Model;806
124.1;1 Introduction;806
124.2;2 Multinomial Dirichlet Gaussian Process Classification Model;807
124.3;3 Variantial Bay yesian Inference;808
124.3.1;3.1 Variational App proximate Posterior Distribution;808
124.3.2;3.2 Predictive Classification Method for New Sample;810
124.4;4 Experimental Results;811
124.5;5 Conclusion;812
124.6;References;812
125;A Log Regression Seasonality Based Approach for Time Series Decomposition Prediction in System Resources;814
125.1;1 Introduction;814
125.2;2 Related Work;815
125.2.1;2.1 Time Series Decomposition;815
125.2.2;2.2 Seasonality;816
125.3;3 Detecting Trend and Seasonality, Forecasting;816
125.3.1;3.1 Detecting Trend and Seasonality;816
125.3.2;3.2 Log Regression Seasonality;816
125.4;4 Experiment;817
125.4.1;4.1 The Prediction Accuracy: TSD vs. LRTSD vs. Simple Linear Regression TSD (SLRTSD);818
125.5;5 Conclusions;819
125.6;References;819
126;A Study on the Algorithm Design for Improving the Accuracy of Decision Tree;821
126.1;1 Introduction;821
126.2;2 Related Study;822
126.2.1;2.1 Decision Tree;822
126.2.2;2.2 IoT Data Processing;822
126.3;3 Improved Decision Tree;823
126.3.1;3.1 Algorithm Process;824
126.3.2;3.2 Error Correction;824
126.3.3;3.3 Processing of the Limit Value;825
126.4;4 Test and Evaluation;825
126.4.1;4.1 Experimental Results and Analysis;826
126.5;5 Conclusions and Future Challenges;828
126.6;References;828
127;Design of a Smartphone-Based Driving Habit Monitoring System;830
127.1;1 Introduction;830
127.2;2 Related Work;831
127.2.1;2.1 OBD-II;831
127.2.2;2.2 Wearable Devices;832
127.2.3;2.3 Driver Monitoring System;832
127.3;3 System Design;832
127.3.1;3.1 System Architecture;832
127.3.2;3.2 Monitoring Service;833
127.4;4 Conclusion;834
127.5;References;834
128;Analysis of Medical Data Using the Big Data and R;836
128.1;1 Introduction;836
128.2;2 ECG-ViEW Database;837
128.2.1;2.1 Overall Structure of Tables;837
128.2.2;2.2 Explanation of Table;838
128.3;3 ECG-ViEW Data Analysis;838
128.3.1;3.1 Association Analysis with ECG-ViEW Database;838
128.3.2;3.2 Outlier Diagnosis of ECG-ViEW Data;839
128.3.3;3.3 Simple Regression Analysis of ECG-ViEW Data;840
128.4;4 Conclusion;841
128.5;References;842
129;Homography-Based Motion Detection in Screen Content;843
129.1;1 Introduction;843
129.2;2 The Characteristic of Motion in Screen Contents;845
129.3;3 Motion Detection;845
129.3.1;3.1 The Proposed Screen Content Scheme;845
129.3.2;3.2 Motion Detection;846
129.4;4 Experimental results;848
129.5;5 Conclusions;848
129.6;References;849
130;A Reference Architecture Framework for Orchestration of Participants Systems in IT Ecosystems;850
130.1;1 Introduction;850
130.2;2 Meta-model for IT Ecosystem;851
130.3;3 Architecture of IT Ecosystems for Orchestration;852
130.4;4 Conclusion;856
130.5;References;856
131;Contents Based Traceability Between Research Artifact and Process for R&D Projects;857
131.1;1 Introduction;857
131.2;Traceability in the General Software Industry;858
131.3;3 Content Based Traceability Between Research Artifact and Process for R&D Projects;859
131.3.1;3.1 Research Descriptor Traceability;859
131.3.2;3.2 Research Descriptor Based Traceability Information Model;859
131.3.3;3.3 Definition of Relation Type for Research Descriptor;860
131.3.4;3.4 Example of Research Descriptor Based Traceability;862
131.4;4 Conclusion and Further Works;863
131.5;References;864
132;Design and Implementation of Panoramic Vision System Based on MPEG-V;865
132.1;1 Introduction;865
132.2;2 Usage Scenarios;866
132.2.1;2.1 Virtual Panoramic IVI (In-Vehicle Information System);866
132.2.2;2.2 Virtual Panora amic Black Box;867
132.3;3 Extension of M MPEG-V Metadata Schema for Panoramic Vision;867
132.3.1;3.1 RADAR Sensor r Type;867
132.3.2;3.2 Array Camera Sensor Type;868
132.4;4 Implementatio on of Panoramic Vision and Metadata Generation;869
132.5;5 Conculusion;870
132.6;References;870
133;Computational Fluid Dynamics Analysis of the Air Damping for an Electromechanical Converter;872
133.1;1 Introduction;872
133.2;2 Numerical Simulation;873
133.3;3 Results and Discussion;875
133.4;4 Conclusions;878
133.5;References;879
134;Author Index;880mehr

Autor

Professor Doo-SoonPark received hisPhD in Computer Science from Korea University in 1988. Currently, he is aprofessor in the Department of Computer Software Engineering at SoonchunhyangUniversity, South Korea. He is President of KIPS(Korea Information ProcessingSociety) and Director of Central Library at Soonchunhyang University andDirector of Wellness Service Coaching Center at Soonchunhyang University. Hewas editor in chief of JIPS(Journal of Information Processing Systems) at KIPSfrom 2009 to 2012. He was Dean of the Engineering College at SoonchunhyangUniversity from 2002 to 2003, and was the Director of the u-Healthcare ResearchCenter at Soonchunhyang University from 2006 to 2007. He has served as anorganizing committee member of international conferences including CUTE 2014,CSA 2014, EMC-14, FutureTech 2014, and MUE 2014. His research interests includedata mining, big data processing and parallel processing. He is a member ofIEEE, ACM, KIPS, KMS, and KIISE. Contact him at parkds@sch.ac.kr.

ProfessorHamid R. Arabnia received a Ph.D.degree in Computer Science from the University of Kent (Canterbury, England) in1987. Arabnia is currently a Professor of Computer Science at University ofGeorgia (Georgia, USA), where he has been since October 1987. His researchinterests include Parallel and distributed processing techniques andalgorithms, supercomputing, Big Data Analytics and applications in medicalimaging, knowledge engineering, security and surveillance systems and othercomputational intensive problems. Most recently, he has been studying ways topromote legislation that would prevent cyber-stalking, cyber-harassment, andcyber-bullying. Dr. Arabnia is Editor-in-Chief of The Journal of Supercomputing(one of the oldest journals in Computer Science) published by Springer and hasbeen Associate Editor of IEEE Transactions on Information Technology in Biomedicine(2008-2011). He is also on the editorial and advisory boards of 32 otherjournals. He is the book series editor-in-chief of "Transactions ofComputational Science and Computational Intelligence" (Springer) andeditor-in-chief of the book series entitled "Emerging Trends in ComputerScience and Applied Computing" (Elsevier). Dr. Arabnia has received anumber of awards; most recently (2007), he received an "OutstandingAchievement Award in Recognition of His Leadership and Outstanding Research Contributionsto the Field of Supercomputing". This award was presented to him atHarvard University Medical School (signatories: Lawrence O. Hall, President ofIEEE/SMC; Zhi-Pei Liang, Vice President of IEEE/EMB; Jack. Y. Yang, GeneralChair of IEEE BIBE and Harvard University; Mary Qu Yang, Chair of SteeringCommittee, IEEE BIBE and NIH); Distinguished Leadership and Visionary Award.Presented by FTRA (Future Technology Research Association), presented bySteering Committee of CSA-13 International Conference; Distinguished ResearchAward for his Outstanding Contributions to Adaptable Communication Systems,presented by ACM SIGAPP IMCOM Co-Chairs, 2014. Dr. Arabnia is an electedFellow, International Society of Intelligent Biological Medicine (ISIBM); hehas served on the Advisory Board of IEEE Technical Committee on ScalableComputing (TCSC, 2006-2012).

ProfessorYoung-Sik Jeong is a professor inthe Department of Multimedia Engineering at Dongguk University in Korea. Hisresearch interests include multimedia cloud computing, information security ofcloud computing, mobile computing, IoT(Internet of Things), and wireless sensornetwork applications. He received his B.S. degree in Mathematics and his M.S.and Ph.D. degrees in Computer Science and Engineering from Korea University inSeoul, Korea in 1987, 1989, and 1993, respectively. He was a professor in theDepartment of Computer Engineering at Wonkwang University in Korea from 1993 to2012. He worked and researched to Michigan State University and Wayne StateUniversity as visiting professor in 1997 and 2004 respectively. Since 2002, hehas been serving as an IEC/TC 100 Korean Technical Committee member, as theIEC/TC 108 Chairman of Korean Technical Committee, and as an ISO/IEC JTC1 SC25Korean Technical Committee member. Also He is an EiC(Editor-in-Chief) ofJournal of Information Processing Systems, an associate editor of JoS(Journalof Supercomputing), IJCS(international Journal of Communication Systems) and aneditor of JIT(Journal of Internet Technology), finally an associate editor ofJournal of Human-centric Computing(HCIS) and so on. He is also is a member ofthe IEEE.

ProfessorJames J. (Jong Hyuk) Park received his Ph.D. degree in Graduate School of Information Security from KoreaUniversity, Korea. From December, 2002 to July, 2007, Dr. Park had been aresearch scientist of R&D Institute, Hanwha S&C Co., Ltd., Korea. FromSeptember, 2007 to August, 2009, He had been a professor at the Department ofComputer Science and Engineering, Kyungnam University, Korea. He is now aprofessor at the Department of Computer Science and Engineering, Seoul NationalUniversity of Science and Technology (SeoulTech), Korea. Dr. Park has publishedabout 100 research papers in international journals and conferences. He hasbeen serving as chairs, program committee, or organizing committee chair formany international conferences and workshops. He is a president of the FutureTechnology Research Association International (FTRA) and Korea InformationTechnology Convergence Society (KITCS). He is editor-in-chief of Human-centricComputing and Information Sciences(HCIS) by Springer, International Journal ofInformation Technology, Communications and Convergence (IJITCC) byInderScience, and Journal of Convergence (JoC) by FTRA Publishing. He isAssociate Editor / Editor of 14 international journals including 8 journalsindexed by SCI(E). In addition, he has been serving as a Guest Editor forinternational journals by some publishers: Springer, Elsevier, John Wiley,Oxford Univ. press, Hindawi, Emerald, Inderscience. His research interestsinclude security and digital forensics, Human-centric ubiquitous computing,context awareness, multimedia services, etc. He got the best paper awards fromISA-08 and ITCS-11 conferences and the outstanding leadership awards from IEEEHPCC-09, ICA3PP-10, IEE ISPA-11, and PDCAT-11. Dr. Park' s research interestsinclude Digital Forensics, Security, Ubiquitous and Pervasive Computing,Context Awareness, Multimedia Service, etc. He is a member of the IEEE, IEEEComputer Society, KIPS, KICS, KIISC, KMMS, KDFS and KIIT.