Computational Science and Its Applications - ICCSA 2016, part 4

Preface......Page 6
Organization......Page 7
Contents – Part IV......Page 23
 1 Introduction......Page 28
  2.1 Toponymy and Street Names......Page 29
  3.1 Toponym Retrieval......Page 30
  3.3 Entity Ranking......Page 31
 4 Evaluation......Page 32
 5 Results and Discussion......Page 34
 6 Crowd Sourcing Local Knowledge......Page 35
  6.3 Software Architecture......Page 36
 References......Page 38
 1 Introduction......Page 40
 2 Case Study......Page 41
  3.1 Urban Perspective: The Redevelopment of the Borgo S. Antonio Quarter......Page 43
  3.3 PPP – Public Private Partnership......Page 44
  3.4 Italian Real Estate Investment Funds......Page 45
  3.5 Jessica......Page 46
  3.6 Risk Approach......Page 47
  4.1 Generating Strategies: Urban Equalization and Regeneration......Page 49
  4.3 Real Estate Finance: Scenario Analyses......Page 50
 5 Conclusions......Page 54
 References......Page 55
 1 Introduction......Page 56
 2 Materials and Methods......Page 57
 3 Data Analysis and Results......Page 59
  3.1 USPED Method Application......Page 62
   3.1.3 Slope-Length Factor......Page 63
   3.1.5 Model Application and Validation......Page 64
 4 Discussion and Final Remarks......Page 69
 References......Page 71
 1 Introduction......Page 73
 2 Materials......Page 75
  3.1 Equalization and Compensation Pattern......Page 76
  3.2 Housing Affordability......Page 79
 4 Application of the Equalization Pattern......Page 84
 5 Discussion. Compensation Scenarios for Social Housing......Page 85
 6 Conclusions......Page 87
 References......Page 88
 1 Introduction......Page 90
 2 Materials. Noto Real Estate......Page 91
  3.1 General Issues......Page 95
  3.2 Procedure......Page 96
  4.1 Clustering Analysis......Page 97
  4.2 Costs Calculation......Page 100
  4.3 Ordinary and Extra-Ordinary Incomes......Page 101
  4.4 Capitalization Rates......Page 102
 Acknowledgements......Page 104
 References......Page 105
 1 Introduction......Page 106
 2 Materials......Page 108
  3.1 Objectives, Data Sources, Information......Page 109
  3.2 The MAVT Approach to Select and Allocate the Enterprises in a Sustainable Way......Page 111
  3.3 Equalization and Compensation......Page 113
  4.1 The Allocation of the Areas to the Firms......Page 114
  4.2 Results of the Equalization and Compensation Process......Page 116
 5 Discussions and Conclusions......Page 118
 References......Page 120
 1 Introduction......Page 122
 2 Related Work......Page 124
 3 The Proposed Methodology......Page 125
  3.1 Prediction Model at Geographic Neighborhood-Level......Page 126
  3.3 Generalities of the Prediction Model for Environmental Noise......Page 127
 4 The Case Study......Page 128
 5 Experimental Results......Page 129
  5.1 Prediction Model Based on Support Vector Machine......Page 131
   5.1.1 Performance of the Artificial Neural Networks......Page 132
   5.1.3 Performance Comparison Between ANN and SVM......Page 133
  5.2 Visualization of Environmental Noise Maps......Page 134
 6 Conclusion and Future Work......Page 135
 References......Page 136
 1 Introduction......Page 138
 2 A Spatial Decision-Making Process for the Landscape Evaluation. A Literature Review......Page 139
 3 The Methodological Steps of the Knowledge-Based Approach......Page 140
  4.1 The Representation and the Process Models......Page 142
  4.2 Outcome: Two Evaluation Scenario for the Tourism Development Through WLC Method......Page 147
 References......Page 150
 1 Introduction......Page 152
 2 Background......Page 153
 3 Experimental Design......Page 156
 4 Results......Page 158
 5 Conclusion......Page 162
 References......Page 163
 1 Introduction......Page 165
 2 Background and Related Research......Page 166
 3 The Evaluation Model......Page 168
  4.1 Study Area......Page 169
  4.2 Data and Evaluation Criteria......Page 170
  4.3 The Evaluation Procedure......Page 171
 5 Discussion of Results......Page 173
 6 Conclusions and Future Work......Page 174
 References......Page 175
 1 Introduction......Page 177
 2 Background......Page 178
  3.1 Exploratory Data Analysis of Interviews and Tourists Profiling......Page 179
  3.2 Tourists’ Spatial Behaviour......Page 182
  3.3 Time Use by Tourist Profiles......Page 184
 4 Conclusions......Page 186
 References......Page 187
 1 Introduction: Actionable Knowledge About Urban Sprawl......Page 188
 2 Conceptual Background: Open Spatial Indicators and Urban Sprawl in a European Perspective......Page 189
  3.1 Research Approach and Process......Page 191
  3.2 Data and Analytical Methods......Page 192
  3.3 Research Context......Page 193
  4.1 Classifying Urban Forms Based on Landscape Metrics......Page 194
  4.2 Land Use Matters: Sorting Out Sprawl Patterns According to Urban Functions......Page 195
  4.4 Sprawling in Time: Tracking Urban Change to Understand Land Taking Processes......Page 199
 5 Concluding Remarks and Future Developments......Page 201
 References......Page 202
 1 Introduction......Page 204
  2.1 The Context......Page 205
  2.2 Calculation of Likelihood Function of NPV......Page 206
 3 Probabilistic Analysis of the Re-Use Revenue for Determining the Expected Value......Page 207
 4 The Gaming Among DM......Page 210
  5.1 The Intersection Between Expected Utility and Likelihood......Page 213
 Acknowledgements......Page 216
 References......Page 217
 1 Introduction......Page 218
  2.1 Map Algebra......Page 220
  3.1 The Study Area......Page 221
  3.3 The Archaeological Sensibility Evaluation (ASE) Model......Page 222
 4 Results......Page 226
 5 Final Discussion......Page 227
 References......Page 229
 1 Introduction......Page 231
  2.1 General Aims and Particular Focus......Page 232
  2.2 Assessment Approach and Perimeter of Investigation......Page 233
  3.1 Decisions and Repercussions Regarding the Procedures for Identifying the Structures and Determin .........Page 235
  3.2 Decisions and Repercussions Tied to the Procedures for the Planning, Design and Execution of the .........Page 238
 4 Considerations and Strategies of Action to Be Followed (in Advance) for the Development of Future  .........Page 241
 5 Conclusions......Page 243
 References......Page 244
 1 Introduction......Page 246
 2 Related Work......Page 247
  4.2 The IaaS Cloud Service Ontology......Page 248
  5.1 Similarity Computation......Page 251
  5.2 Clustering Results......Page 252
  6.2 The Clustering Procedure......Page 253
  6.5 Experiment Results......Page 254
 References......Page 258
 1 Introduction......Page 259
 2 Stochastic Gradient Variational Bayes......Page 261
  3.1 Lower Bound Estimation......Page 262
  3.2 Maximization of Lower Bound......Page 265
  3.3 Estimation Without Sampling......Page 267
  4.2 Evaluation Method......Page 268
  4.4 Evaluation Results......Page 269
 5 Conclusion......Page 271
 References......Page 272
 1 Introduction......Page 273
  2.2 Directed Acyclic Graph......Page 275
  3.1 VSEncoding......Page 277
  3.2 Optimized Partitioning Strategy......Page 278
  4.1 Experimental Setup......Page 280
  4.2 Indexing Performance......Page 281
  4.3 Decompression Performance......Page 283
 5 Conclusion and Future Work......Page 285
 References......Page 286
 1 Introduction......Page 288
 2 The Function of Property in Ontology Evolution......Page 289
  3.1 Semantic Relationships......Page 291
  3.2 Quantization for the Strength of Semantic Relationship......Page 292
  3.3 Construction of SRG Graph Model......Page 293
  4.1 Ontology Matrix......Page 295
  4.2 Quantitative Analysis of the Ripple-Effect of Ontology Evolution......Page 296
 5 Experiments and Evaluation......Page 297
 References......Page 302
 1 Introduction......Page 304
 2 Background Study......Page 305
 3 Problem Proposing......Page 308
  4.1 Analysis on Complete History......Page 310
 5 Conclusion and Future Work......Page 314
 References......Page 315
 1 Introduction......Page 316
 2 Previous Works......Page 317
 3 Proposed Scheme......Page 318
  3.2 Authentication and Session Key Establishment Phases......Page 319
  3.3 Renewal Phase......Page 323
 4 Security Analysis......Page 324
 References......Page 326
 1 Introduction......Page 329
 2 Related Work......Page 331
  3.1 Identifying Candidate Books......Page 333
  3.2 The Content-Based Filtering Method......Page 334
  3.3 The Collaborative Filtering (CF) Approaches......Page 337
  4.2 Performance Evaluation of CBRec......Page 340
 5 Conclusions and Future Work......Page 342
 References......Page 343
 1 Introduction......Page 345
 2 Related Work......Page 346
  3.1 Delphi Method......Page 348
  3.2 Modified Delphi Method......Page 349
 4 Ontology Evaluation......Page 351
  4.1 Internal Evaluation......Page 352
   4.2.1 Field Testing......Page 353
   4.2.3 Question Answering......Page 357
 5 Generalizing the Approaches and Conclusions......Page 358
 References......Page 359
 1 Introduction......Page 361
 2 Related Works......Page 362
  3.2 A Updating Activities......Page 364
  3.4 C Object Oriented Paradigm......Page 365
 4 Formula for Effort Estimation......Page 366
  4.1 A Fundamental Metrics......Page 367
 6 Conclusion......Page 368
 References......Page 371
 1 Introduction......Page 373
  2.1 Spreading Activation Model......Page 374
  3.1 Genetic Algorithm for the Influence Maximization Problem......Page 376
  3.2 Dataset......Page 378
  3.3 Results......Page 379
 4 Conclusions and Future Works......Page 382
 References......Page 383
 1 Introduction......Page 385
  1.1 The HyperFlex Approach and Toolchain......Page 386
  2.1 MDE for Software Variability Management......Page 389
  2.3 Variability Modeling Approaches in Robotics......Page 390
 3 Variability Composition and Abstraction with HyperFlex......Page 391
  3.1 Bottom-Up Functionality Composition......Page 392
  3.2 Top-Down Specification Refinement......Page 393
  3.3 Refinement Model......Page 394
  3.4 Refinement Language......Page 397
 References......Page 399
 1 Introduction......Page 401
 2 Related Work......Page 402
  3.2 Introduction to Fuzzy Set Theory (FST)......Page 404
 4 A Framework to Identify ToD from User Requirements......Page 406
  5.1 Identifying ToDs from Users’ Requirements......Page 409
 6 Comparative Analysis......Page 411
 References......Page 416
 1 Introduction......Page 419
 2 Related Work......Page 421
 3 Research Methodology......Page 422
 4 Metrics and Analysis Implementation......Page 423
 6 Results......Page 425
 7 Threats to Validity......Page 428
 8 Analysis......Page 430
 10 Future Work......Page 431
 References......Page 432
 1 Introduction......Page 434
 3 Literature Study......Page 437
 4 Proposed Architecture......Page 440
  5.1 Scalable Measurement......Page 442
 6 Attestation Protocol for Scalable Dynamic Behavior......Page 443
 7 Results and Discussion......Page 445
 8 Conclusion......Page 446
 References......Page 447
 1 Introduction......Page 449
 2 Metadata Definition......Page 450
  2.2 Code Annotations Practices......Page 451
  2.3 Motivating Example......Page 452
 3 The Metadata Validation Approach......Page 453
  4.1 General View......Page 455
  4.2 Domain Specific Language of the Meta-framework......Page 456
  4.4 Location Strategies......Page 457
 5 Evaluation......Page 458
  5.2 Functional Evaluation......Page 459
  5.3 Modularity Analysis......Page 460
  5.4 General Analysis......Page 462
 6 Related Works......Page 463
 References......Page 464
 1 Introduction......Page 466
  1.1 Requirements Engineering......Page 467
  1.2 Risk Management for Information Systems......Page 468
 2 Advanced Model......Page 470
 3 Applying the Model for Health Care Risks......Page 471
 4 Results......Page 473
 5 Interdisciplinary Discussion......Page 475
 References......Page 477
 1 Introduction......Page 480
 2 Motivating Examples......Page 482
  3.1 Web Service Clustering......Page 485
  3.2 Web Service Composition and Verification......Page 486
  4.3 Logic-Based Web Service Similarity......Page 487
  4.4 Logic-Based Web Service Clustering......Page 490
 5 Experimentation......Page 492
 6 Conclusion......Page 493
 References......Page 494
 1 Introduction......Page 496
  2.1 Agile Modelling......Page 497
  2.2 Mind Maps......Page 498
  3.1 The Model Transformation Process......Page 499
  3.2 Mind Domain Architecture......Page 500
 4 Case Study......Page 501
 5 Related Works......Page 503
 References......Page 505
 1 Introduction......Page 507
 2 Related Work......Page 508
  3.1 The HMI-Excel Program......Page 509
  3.2 The iFloW Project......Page 510
 4 Using Scrum with UML Models......Page 512
  4.1 Initialization Phase......Page 513
  4.2 Implementation Phase......Page 515
  5.2 Disadvantages......Page 519
 Acknowledgements......Page 520
 References......Page 521
 1 Introduction......Page 523
 2 Geological and Geomorphological Framework of the Study Area......Page 524
 4 Historical-Cultural Importance of the Site “Belvedere Delle Chiese Rupestri”......Page 526
 5 Rockfall Analysis and Simulation......Page 527
 6 Simulation of the Trajectory in the Study Area......Page 528
  6.1 Profile AA’ Near “Madonna Degli Angeli” Church Located in the Archaeological Park of the Rupestr .........Page 529
  6.2 Rockfall Analysis and Simulation......Page 530
  6.3 Profile BB’ in Proximity of the “Madonna Degli Angeli” Church Located in Archaeological Park of  .........Page 531
  6.4 Profile DD’......Page 532
  6.5 Profile FF’ Near GPS Location Number 3 (Fig. 3)......Page 533
 7 Environmental Impacts and Possible Preventive Measures......Page 534
  7.2 Profile CC’ Passing Through the “Madonna Di Monteverde” Church......Page 535
 8 Analysis of Results and Conclusions......Page 537
 References......Page 538
 1 Introduction......Page 539
 2 Related Work......Page 540
 3 Design......Page 542
 4 Implementation......Page 544
 5 Modules......Page 547
 6 Data Mining......Page 551
  6.1 The Measurable Scope......Page 552
  6.3 Visualization of Analytics......Page 553
 8 Conclusions......Page 554
 References......Page 555
 1 Introduction......Page 557
 2 Related Works......Page 558
 3 Algorithm Design......Page 559
 4 Analysis of the Experiments and Discussions......Page 563
 References......Page 568
 1 Introduction......Page 570
  2.2 Genetic Algorithms (GAs)......Page 571
 3 Combining SA and GA with the Multilevel Paradigm......Page 572
  4.1 Experimental Setup......Page 574
  4.2 Analysis of Results......Page 575
 References......Page 578
 1 Introduction......Page 581
 2 Preliminary Bases......Page 582
 3 Related Works......Page 584
  4.1 Steps of the Interruption Caused by the New Task......Page 585
  4.2 Instrumental Environment of Processing the New Task......Page 588
  4.3 Precedent Oriented Modeling of the New Task......Page 589
  5.1 An Initial Statement of a New Task......Page 590
  5.2 Stepwise Refinement in Processing the New Task......Page 591
  5.3 Figuratively-Semantic Support in Interactions with Textual Units......Page 592
 6 Conclusion......Page 594
 References......Page 595
 1 Introduction......Page 597
 2 Related Work......Page 598
 3 Investigating CQA History......Page 600
  4.1 Methodology......Page 602
  4.3 Discussion......Page 603
  4.4 Threats to Validity......Page 605
 References......Page 606
 1 Introduction......Page 608
 2 The Features of the Proposed Approach to Teaching Physics and Concepts of Modern Natural Science f .........Page 610
 4 Teaching Physics to Medical Students......Page 611
 5 The Use of Learning Management Systems......Page 612
 6 The Basis of Special Educational Environment for Teaching Physics......Page 615
 References......Page 617
 1 Introduction......Page 622
  2.1 Problem Features......Page 624
  2.3 Measures......Page 625
  2.4 RBF Interpolation Models......Page 627
 3 Results......Page 630
 4 Discussion and Conclusions......Page 632
 References......Page 634
 1 Introduction......Page 637
 2 Related Work......Page 639
 3 Approach......Page 640
  3.1 Dataset Construction......Page 641
  4.1 The Maintainability of Refactored Methods......Page 643
  4.2 The Effect of Refactorings on Method-Level Source Code Metrics......Page 645
 5 Threats to Validity, Limitations......Page 647
 6 Conclusions and Future Work......Page 648
 References......Page 649
 1 Introduction......Page 652
 2 Related Work......Page 653
 3 Approach......Page 655
 4 Chosen Projects and the Created Databases......Page 656
 5 Evaluation......Page 658
 6 Conclusion and Future Work......Page 663
 References......Page 664
 1 Introduction......Page 666
  2.2 Complaints......Page 667
  3.1 Data Analysis......Page 668
  3.2 Knime Analysis......Page 669
   3.3.1 Application to the Group of All Complaints......Page 670
   3.3.2 Application of the Model to Different Groups of Classification......Page 671
   3.4.1 Study of the Most Frequent Words on Complaints......Page 672
   3.4.4 Study of Frequency by Classification......Page 673
 4 Discussion......Page 674
 Acknowledgments......Page 675
 References......Page 676
 1 Natural Hazards, Disasters, Risks......Page 677
 2 Strategic Approaches to Reduce Risk......Page 678
  2.1 Mitigation Actions to Reduce Exposure......Page 679
  3.1 Scenario Planning......Page 681
  3.2 Evaluation Process......Page 682
 4 Methodology......Page 683
  4.1 Ideal City Modeling......Page 684
  4.2 Criteria Definition......Page 685
 5 Results and Discussion......Page 688
 6 Conclusion......Page 689
 References......Page 690
 1 Introduction......Page 692
  2.2 Dimensionality Reduction......Page 693
  2.4 Classifiers for Water Quality Detection......Page 695
  3.1 Automatic Selection of Principal Components (ASPC)......Page 696
  3.2 Instances Reduction (IR-E)......Page 697
  3.3 Automatic Optimal Synthetic Data Selection (AOSDS)......Page 698
  4.1 Attributes Reduction......Page 699
  4.2 Instance Reduction......Page 701
  4.3 Attributes and Instances Reduction......Page 702
  4.4 Average Classifiers Training Time......Page 703
  4.5 Class Balance......Page 704
  4.6 Classification Module......Page 706
 5 Conclusions and Future Works......Page 707
 References......Page 708
 1 Introduction......Page 711
  2.1 Early Warning Systems......Page 712
 3 State of the Art......Page 713
 4 Proposal......Page 714
  4.1 Application Scenario......Page 715
  4.2 System Design......Page 717
  4.3 Experimental Prototype......Page 720
 5 Results and Discussion......Page 723
 6 Conclusion and Future Works......Page 724
 References......Page 725
Author Index......Page 727