Recent Trends in Information and Communication Technology

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