ITNG 2023 20th International Conference on Information Technology-New Generations

Description

This volume represents the 20th International Conference on Information Technology - New Generations (ITNG), 2023. ITNG is an annual event focusing on state of the art technologies pertaining to digital information and communications. The applications of advanced information technology to such domains as astronomy, biology, education, geosciences, security, and health care are the among topics of relevance to ITNG. Visionary ideas, theoretical and experimental results, as well as prototypes, designs, and tools that help the information readily flow to the user are of special interest. Machine Learning, Robotics, High Performance Computing, and Innovative Methods of Computing are examples of related topics. The conference features keynote speakers, a best student award, poster award, service award, a technical open panel, and workshops/exhibits from industry, government and academia. This publication is unique as it captures modern trends in IT with a balance of theoretical and experimental work. Most other work focus either on theoretical or experimental, but not both.  Accordingly, we do not know of any competitive literature. Contents Chair Message ITNG 2023 Reviewers Part I Machine Learning 1 Loop Closure Detection in Visual SLAM Based on Convolutional Neural Network 1.1 Introduction 1.2 Related Works 1.3 Proposed System 1.3.1 Capture the Image 1.3.2 Train the CNN 1.3.3 Loop Closure Detection 1.4 Simulation Results 1.4.1 Scenario 1.4.2 Performance Metrics 1.5 Conclusions and Future Works References 2 Getting Local and Personal: Toward Building a Predictive Model for COVID in Three United States Cities 2.1 Introduction 2.2 Data Sources 2.3 Correlations for Select US Cities 2.3.1 Methodology 2.3.2 Results 2.3.2.1 Pearson Correlation Coefficient 2.3.2.2 Granger Causality 2.3.2.3 Predictive Model 2.4 Conclusions References 3 Integrating LSTM and EEMD Methods to Improve Significant Wave Height Prediction 3.1 Introduction 3.2 Related Work 3.3 Methodology and Implementation 3.4 Comparisons and Results 3.5 Conclusions and Future Work References 4 A Deep Learning Approach for Sentiment and Emotional Analysis of Lebanese Arabizi Twitter Data 4.1 Introduction 4.2 Arabizi 4.3 Related Work 4.4 Dataset Generation 4.5 Classification System 4.5.1 Text Pre-processing 4.5.2 Feature Extraction 4.6 Sentiment and Emotion Classification 4.6.1 Text Vectorization Using Fasttext 4.6.2 Machine Learning Approaches 4.7 Deep Learning Model 4.8 Experimental Results 4.9 Conclusion References 5 A Two-Step Approach to Boost Neural Network Generalizability in Predicting Defective Software 5.1 Introduction 5.2 Related Studies 5.3 Materials and Methods 5.3.1 Dataset 5.3.2 Machine Learning Approach and Experimental Protocol 5.3.3 Evaluation Metrics 5.4 Results and Discussion 5.5 Conclusion References 6 A Principal Component Analysis-Based Scoring Mechanism to Quantify Crime Hot Spots in a City 6.1 Introduction 6.2 Related Work 6.3 Methodology 6.3.1 Data Description 6.3.2 Data Segmentation 6.3.3 Principal Component Analysis (PCA) 6.3.4 Quantifying the Crime Hot Spots 6.3.5 Example 6.4 Results 6.5 Conclusions and Future Work References 7 Tuning Neural Networks for Superior Accuracy on Resource-Constrained Edge Microcontrollers 7.1 Introduction 7.2 Related Work 7.3 Methods and Materials 7.4 Experimental Results 7.5 Conclusions References 8 A Deep Learning Approach for the Intersection Congestion Prediction Problem 8.1 Introduction 8.1.1 Related Work 8.2 Problem Description 8.3 Problem Formulation 8.3.1 Data Collection, Cleansing, and Processing 8.4 Solution Approach 8.5 Experimental Results 8.5.1 Machine Learning Models 8.5.2 LSTM 8.6 Conclusion References 9 A Detection Method for Stained Asbestos Based on Dyadic Wavelet Packet Transform and a Locally Adaptive Method of Edge Extraction 9.1 Introduction 9.2 2D Dyadic Wavelet Packet Transform 9.2.1 2D Dyadic Wavelet Transform 9.2.2 2D Dyadic Wavelet Packet Transform 9.2.3 Locally Adaptive Edge Extraction 9.3 Proposed Method 9.4 Experiment 9.4.1 Experimental Procedure 9.4.2 Experimental Result 9.5 Conclusion References 10 Machine Learning: Fake Product Prediction System 10.1 Introduction 10.2 Current System Analysis 10.3 Opinion Mining 10.4 Data Mining 10.5 Sentiment Analysis 10.6 Problem Statement 10.7 Purpose Statement 10.8 Architecture Functional Requirements 10.9 Data Cleaning 10.10 Exploratory Analysis 10.11 Corpus 10.12 Feature Engineering 10.13 Tokenization 10.14 Stop Word Elimination 10.15 Stemming 10.16 Feature Engineering 10.17 Result 10.18 Conclusion References Part II Cybersecurity and Blockchain 11 Ontology of Vulnerabilities and Attacks on VLAN 11.1 Introduction 11.2 Literature Review and Related Work 11.3 The Building Process of OVAV.owl 11.3.1 Technological Vulnerability 11.3.2 Technological Attack 11.3.3 Security Properties Affected by Attacks 11.3.4 Attack Impact 11.4 Application of OVAV in Attack Prevention 11.5 Discussion and Final Remarks References 12 Verifying X.509 Certificate Extensions 12.1 Introduction 12.2 Previous Works 12.2.1 Covert Channels 12.2.2 X.509 Covert Channel 12.2.3 The X.509 Standard 12.2.4 Intrusion Detection and Prevention Systems 12.3 Research Question 12.4 Suricata Rules 12.4.1 Subject Key Identifier 12.4.2 Authority Key Identifier 12.4.3 Key Usage Identifier 12.4.4 Rule Limitations 12.4.5 Lua Scripting in Suricata 12.4.6 Protocol Matches 12.5 Experimentation 12.5.1 Environment 12.5.2 Network Traffic 12.6 Results 12.7 Conclusion References 13 Detecting Malicious Browser Extensions by Combining Machine Learning and Feature Engineering 13.1 Introduction 13.2 Methodology 13.2.1 Collection of Browser Extensions 13.2.2 Feature Engineering and Dataset Creation 13.2.3 Machine Learning Model Training and Testing 13.3 Performance Evaluation Results 13.3.1 Performance Comparison 13.3.2 FPR and FNR of Algorithms 13.4 Conclusion References 14 A Lightweight Mutual Authentication and Key Generation Scheme in IoV Ecosystem 14.1 Introduction 14.1.1 Our Contribution 14.1.2 Physical Unclonable Function 14.1.3 Related Work 14.2 Chained Hash PUF Authentication Technique 14.3 Network Model, Security Goals, and Assumptions 14.3.1 Network Model 14.3.2 Assumptions 14.3.3 Security Goals 14.4 Authentication and Key Generation Scheme 14.4.1 Enrollment Phase 14.4.2 Registration Phase 14.4.3 Mutual Authentication Phase 14.5 Evaluation Process 14.5.1 Formal Security Verification Using AVISPA 14.5.2 Informal Security Analysis 14.5.3 Performance Analysis 14.6 Conclusion References 15 To Reject or Not Reject: That Is the Question. The Case of BIKE Post Quantum KEM 15.1 Introduction 15.2 Preliminaries and Notation 15.2.1 Isochronous and CT Implementations 15.3 Mitigating the Timing Attack of ches-attack 15.4 The Sampling Method of sendrier 15.5 BIKE v5.0 Spec bike5 Problem and the Responsible Disclosure 15.6 Summary Appendix: Rejection Sampling Success Probability References 16 IoT Forensics: Machine to Machine Embedded with SIM Card 16.1 Introduction 16.1.1 Characteristics 16.1.2 Aim of This Paper 16.1.3 The Structure of the Paper 16.2 Related Work 16.3 Basic Architecture 16.3.1 M2M Architecture 16.3.2 eSIM Architecture 16.4 Security of the eSIM 16.5 Challenges and Solutions 16.5.1 Accessing the Profile 16.5.2 Disable or Deleting the Profile 16.5.3 eUICC Memory Reset 16.5.4 Chip-Off Acquisition 16.5.5 Ability to Attack 16.6 Framework 16.7 Limitation 16.8 Conclusion and Future Work References 17 Streaming Platforms Based on Blockchain Technology: A Business Model Impact Analysis 17.1 Introduction 17.2 Background 17.3 Methodology 17.4 An Analysis of the State of the Art 17.5 Discussion 17.6 Final Considerations References 18 Digital Forensic Investigation Framework for Dashcam 18.1 Introduction 18.2 Related Work 18.3 Methodology and Implementation 18.4 Conclusion References Part III Software Engineering 19 Conflicts Between UX Designers, Front-End and Back-End Software Developers: Good or Bad for Productivity? 19.1 Introduction 19.2 Research Methodology 19.2.1 Research Questions 19.2.2 Respondents Selection 19.2.3 Survey Definition 19.2.4 Data Collection, Analysis and Synthesis 19.3 Threats to Validity 19.4 Results 19.4.1 Which Kinds of Conflict Arise Among UX Designers, Front- and Back-End Developers? (RQ1) 19.4.2 Do Socio-Cultural Factors Such as Gender and Age Favour the Rising of Conflicts? (RQ1.1) 19.4.3 Does the Geographic Distribution of the Team Members Favours the Rising of Conflicts? (RQ1.2) 19.4.4 Do the Identified Conflicts Affect the Success of a Software Project? (RQ2) 19.5 Additional Findings 19.6 Related Work 19.7 Conclusion and Future Work References 20 Generalized EEG Data Acquisition and Processing System 20.1 Introduction 20.2 Background and Related Work 20.2.1 Infrastructure for EEG-Based Studies 20.2.2 Lab Streaming Layer 20.3 Software Design 20.4 Software Prototype 20.4.1 Frontend 20.4.2 Backend 20.4.3 Analytical Module 20.5 Discussion 20.6 Conclusions and Future Work References 21 Supporting Technical Adaptation and Implementation of Digital Twins in Manufacturing 21.1 Introduction 21.2 Background 21.2.1 Digital Twin 21.2.2 ISO 23247 21.3 Research Methodology 21.4 Technical Adaptation and Implementation of Digital Twins 21.5 Related Work 21.6 Conclusion and Future Work Primary Studies References 22 Towards Specifying and Evaluating the Trustworthiness of an AI-enabled System 22.1 Introduction 22.2 Related Work 22.3 Trustworthiness Scenarios 22.4 Trustworthiness Tactics 22.4.1 Reduce Bias 22.4.2 Support User Understanding 22.4.3 Align Behavior 22.4.4 Robustness Against Attacks 22.5 Trustworthiness Analysis 22.6 Conclusions and Future Work References 23 Description and Consistency Checking of Distributed Algorithms in UML Models Using Composite Structure and State Machine Diagrams 23.1 Introduction 23.2 Proposal for PROMELA Description Using UML Diagrams 23.2.1 Instance Definitions 23.2.2 Variable and Type Definitions 23.2.3 Definition of Communication Channels 23.2.4 Description of Communication Channel 23.2.5 Process Behavior 23.3 Model Description of Leader Finding Algorithms Using UML 23.3.1 Overview of Leader Finding Algorithms 23.3.2 Description Using Composite Structure Diagrams 23.3.3 Description Using State Machine Diagrams 23.4 Consistency Check of Composite Structure Diagrams and State Machine Diagrams 23.5 Implementation of Inspectors with astah* Plug-ins 23.6 Summary and Future Work References 24 Simulation and Comparison of Different Scenarios of a Workflow Net Using Process Mining 24.1 Introduction 24.2 Theoretical Background 24.2.1 Process Mining 24.2.2 Workflow Net 24.3 Related Works 24.4 Model Implementation and Variations 24.5 Evaluation 24.6 Conclusion References 25 Making Sense of Failure Logs in an Industrial DevOps Environment 25.1 Introduction 25.2 Related Work 25.3 LogGrouper: Approach 25.3.1 Pre-processing: 25.3.2 Feature Vectors Extraction 25.4 Evaluation 25.4.1 Context and Research Questions 25.4.2 Data Collection 25.4.3 Metrics 25.4.4 Procedure 25.5 Results and Discussion 25.5.1 Quantitative Results (RQ1) 25.5.2 Qualitative Results (RQ2) 25.6 Validity Threats 25.7 Conclusion and Future Directions References Part IV Data Science 26 Analysis of News Article Various Countries on a Specific Event Using Semantic Network Analysis 26.1 Introduction 26.2 Related Work 26.2.1 Natural Language Processing (NLP) 26.2.2 Latent Dirichlet Allocation (LDA) 26.2.3 Semantic Network Analysis 26.3 System Architecture 26.3.1 Dataset 26.3.2 English Translator 26.3.3 Latent Dirichlet Allocation (LDA) Modeling 26.3.4 Coherence Score 26.3.5 Betweenness Centrality Score 26.3.6 Sentiment Analysis 26.4 Experiment Result 26.5 Conclusion References 27 An Approach to Assist Ophthalmologists in Glaucoma Detection Using Deep Learning 27.1 Background 27.2 Methodology 27.2.1 Database Construction 27.2.2 Preprocessing of Images 27.2.2.1 Malachite Filter 27.2.3 Network Model Development 27.2.4 Training 27.2.5 Testing and Validation 27.3 Results Analysis 27.3.1 Analysis of Results with 50 Seasons 27.3.2 Analysis of Results with 30 Seasons 27.3.3 Final Results 27.4 Conclusion References 28 Multtestlib: A Parallel Approach to Unit Testing in Python 28.1 Introduction 28.1.1 Software Testing 28.1.2 Parallel Processing 28.1.3 Python 28.2 Development 28.2.1 Specifications of the New Package 28.2.2 Multiprocessing 28.2.3 Faster than Unittest 28.2.4 Syntax and Application 28.2.5 Flexibility 28.2.6 Results on Screen 28.2.7 Log Files 28.2.8 Easy to Install 28.3 Architecture 28.4 Conclusion 28.5 Future Works References 29 DEFD: Adapted Decision Tree Ensemble for Financial Fraud Detection 29.1 Introduction 29.2 Related Work 29.3 DEFD: Adapted Decision Tree Ensemble for Financial Fraud Detection 29.3.1 Features Extraction 29.3.2 Decision Trees Ensemble 29.3.3 Fraudulent Score Calculation 29.4 Experimentation 29.4.1 Subset of Features and Decision Trees Bagging 29.4.2 Fraudulent Score and Vote System 29.4.3 The Fraudulent Transactions 29.4.4 Results and Discussion 29.5 Conclusion References 30 Prediction of Bike Sharing Activities Using Machine Learning and Data Analytics 30.1 Introduction 30.2 Dataset 30.3 Pre-processing with Data 30.4 Machine Learning Modelling 30.5 Conclusions References Part V E-Learning 31 ICT: Attendance and Contact Tracing During a Pandemic 31.1 Introduction 31.2 Background of the Study 31.3 Related Work 31.4 InClass.Today 31.4.1 Creating a Meeting 31.4.2 Attending a Meeting 31.4.3 Reporting 31.4.4 Contact Tracing 31.5 Platform Utilization 31.6 Conclusion References 32 Towards Cloud Teaching and Learning: A COVID-19 Era in South Africa 32.1 Introduction 32.2 Literature Review 32.2.1 The Theory Underpinning the Research 32.3 Methodology 32.4 Findings 32.4.1 Theme 1: Online Teaching and Learning System Accessibility 32.4.2 Theme 2: Cloud's Teaching and Learning Platform Layout 32.4.3 Theme 3: Resources to Access to Internet and Network 32.4.4 Theme 4: Isolation 32.4.5 Theme 5: Home Environment 32.5 Discussion 32.6 Conclusions and Recommendation References 33 Learning Object as a Mediator in the User/Learner's Zone of Proximal Development 33.1 Introduction 33.2 Zone of Proximal Development 33.3 Learning Object 33.4 Methodology 33.5 LO-ZPD Development 33.6 Final Considerations References 34 Quality Assessment of Open Educational Resources Based on Data Provenance 34.1 Introduction 34.2 Theoretical Background 34.3 Related Work 34.4 ProvOER Model 34.5 QualiProvOER Approach 34.5.1 Quality Assessment of an OER Created “From Scratch” (Qfs) 34.5.2 Assessment of the Quality of a Source OER (Qs) 34.5.3 Quality Assessment of an OER Created Through Revise and/or Remix Activities (Qrr) 34.6 Conclusion and Future Work References 35 Quality Assessment of Open Educational Resources: A Systematic Review 35.1 Introduction 35.2 Theoretical Foundation 35.3 Related Work 35.4 Systematic Review 35.5 Studies to Assess the Quality of OER 35.5.1 Strategy for Quality Evaluation 35.5.2 Quality Dimension 35.5.3 Quality Indicators 35.5.4 Responsible for the Quality Evaluation 35.5.5 Types of Evaluation 35.6 Discussion 35.7 Conclusion and Future Work References Part VI Health 36 Predicting COVID-19 Occurrences from MDL-based Segmented Comorbidities and Logistic Regression 36.1 Introduction 36.2 Background 36.3 Methodology 36.4 An Analysis of the State of the Art 36.5 Discussion 36.6 Final Considerations References 37 Internet of Things Applications for Cold Chain Vaccine Tracking: A Systematic Literature Review 37.1 Introduction 37.2 Method 37.2.1 Planning the Review 37.2.2 Conducting the Review 37.2.3 Reporting the Review 37.3 Results 37.3.1 Time-Spreading of Selected Studies 37.3.2 Technologies of Selected Studies 37.3.2.1 IoT Devices 37.3.2.2 Communication 37.3.2.3 Cloud 37.3.3 Places of Selected Studies 37.4 Discussion 37.4.1 RQ1: What Are the Main IoT Technologies Used in Cold Chain Vaccine Logistics? 37.4.2 RQ2: Which of these Technologies Are Applied in Remote Areas? 37.5 Conclusion References 38 GDPR and FAIR Compliant Decision Support System Design for Triage and Disease Detection 38.1 Introduction 38.1.1 Contributions 38.2 Background and Related Work 38.3 Research Methodology 38.3.1 Data Collection 38.3.2 Data Transformation 38.3.3 Data Anonymization and FAIRification 38.3.4 Creation and Integration of Ontologies 38.3.5 Recording Patients' Data to the Triplestore and Cloud 38.3.6 Prediction Module 38.4 Limitations 38.5 Discussion 38.6 Conclusion and Future Work References Part VII Potpourri I 39 Truckfier: A Multiclass Vehicle Detection and Counting Tool for Real-World Highway Scenarios 39.1 Introduction 39.2 Related Work 39.3 Truckfier Description 39.3.1 Methodology 39.3.1.1 Data Gathering 39.3.1.2 Data Processing 39.3.1.3 Data Analysis 39.3.2 User Interface 39.3.3 Video Summarizing Algorithm 39.3.4 Vehicle Detection 39.4 Experimental Results 39.5 Final Considerations References 40 Explaining Multimodal Image Retrieval Using A Vision and Language Task Model 40.1 Introduction 40.2 System Architecture (Fig. 40Fig240.2) 40.3 Method 40.3.1 Feature Extraction & Transformer Model 40.3.2 Feature Fusion Layer 40.3.3 Model Training 40.4 Explaining BERT Sentence Through SHAP 40.4.1 Shapely Value Analysis 40.4.2 How Does SHAP Work? 40.5 Experimental Result 40.6 Conclusion References 41 Machine Vision Inspection of Steel Surface Using Combined Global and Local Features 41.1 Introduction 41.2 NEU Framework Architecture 41.3 Image Module 41.3.1 Image Enhancement 41.3.2 Global and Local Feature Extraction 41.3.3 Features Combination 41.3.4 Feature Reduction 41.4 Image Classification Module 41.5 Experimental Work, Evaluation and Results 41.5.1 PCA Feature Reduction (Experiment-1) 41.5.2 Feature Set Considerations (Experiment-2) 41.5.3 Defects Classification (Experiment-3) 41.6 Comparing with Other Works 41.7 Conclusion References 42 A Process to Support Heuristic Evaluation and Tree Testing from a UX Integrated Perspective 42.1 Introduction 42.2 Context 42.2.1 Conceptual Framework 42.2.1.1 Heuristic Evaluation 42.2.1.2 Tree Testing 42.2.1.3 BPMN (Business Process Model and Notation) 42.2.2 A Formal Heuristic Evaluation Process 42.2.3 A Process to Support Remote Tree Testing Technique 42.3 Methodology 42.3.1 AS-IS Survey 42.3.2 Virtual Workshop 42.3.2.1 Planning 42.3.2.2 Execution 42.3.2.3 Results 42.3.3 TO-BE Proposal 42.3.4 Proposal Validation 42.4 The Proposed Formal Process 42.5 Conclusions and Future Works References 43 Description and Verification of Systolic Array Parallel Computation Model in Synchronous Circuit Using LOTOS 43.1 Introduction 43.2 Related Work 43.3 Parallel Computation Model Systolic Array 43.4 Proposed Method 43.4.1 Synchronous Circuit 43.4.2 Adder in LOTOS 43.4.3 Multiplier in LOTOS 43.4.4 Register in LOTOS 43.4.5 The Cell in LOTOS 43.4.6 Generator in LOTOS 43.5 Model Analysis 43.5.1 Behavior Property 43.5.2 Adder and Multiplier Delays 43.6 Conclusions and Future Work References 44 A Virtual Reality Mining Training Simulator for Proximity Detection 44.1 Introduction 44.2 Background and Related Work 44.2.1 LIDAR 44.2.2 Software and Hardware 44.2.2.1 Unity and MuVR 44.2.2.2 Hardware Overview 44.2.3 Existing Systems 44.3 Design and Implementation 44.3.1 Multiuser Virtual Reality 44.3.2 Virtual Environment 44.3.3 Collision and Proximity Detection 44.4 Feature Comparison 44.5 Conclusions and Future Work References 45 A Performance Analysis of Different MongoDB Consistency Levels 45.1 Introduction 45.2 Background 45.2.1 MongoDB 45.2.1.1 Data Replication Process 45.2.1.2 MongoDB Consistency Levels 45.2.1.3 Write Concern and Journal 45.2.1.4 Read Concern 45.2.1.5 Read Preference 45.2.2 YCSB 45.2.3 YCSB+T 45.3 Experimental Results 45.3.1 Workload A (50% Read and 50% Update) 45.3.2 Workload B (Read Heavy): 95% Read and 5% Update 45.3.3 Workload D (Read Latest): 95% Read and 5% Inserts 45.4 Future Works References Part VIII Potpourri II 46 Information Extraction and Ontology Population Using Car Insurance Reports 46.1 Introduction 46.2 Related Work 46.2.1 Information Extraction 46.2.1.1 The Named Entity Recognition Methods 46.2.2 Ontology for Damage Modeling 46.3 Ontology Construction 46.3.1 Concepts 46.3.2 Data Properties 46.3.3 Object Properties 46.4 Methodology 46.4.1 The Pre-processing Module 46.4.2 NLP Module 46.4.3 The Information Extraction Module 46.4.4 Ontology Population 46.5 Experiments and Results 46.6 Conclusion and Perspectives References 47 Description of Restricted Object Reservation System Using Specification and Description Language VDM++ 47.1 Introduction 47.2 Upstream Processes and Formal Methods 47.2.1 Upstream Process 47.2.2 Formal Methods 47.3 Higher Level Design Example 47.3.1 System Overview 47.3.2 Requirement Specification 47.3.3 Cyber-Physical System(CPS) 47.3.4 UML Diagram 47.4 VDM++ Description of Each Function and Object 47.4.1 VDM++ Description and Each Function and Object 47.4.2 Example of VDM++ Description 47.5 Conclusion and Future Issues References 48 Applying Scrum in Interdisciplinary Case Study Projects for Literacy in Fluency Analysis 48.1 Introduction 48.2 The Architecture Overview 48.3 Background 48.3.1 The Disciplines 48.3.2 The Framework SCRUM 48.4 The Product Owner Project Vision 48.5 The Project Development 48.5.1 Sprint 0 48.5.2 Sprint 1 48.5.3 Sprint 2 48.5.4 Sprint 3 48.6 Results 48.7 Conclusion 48.7.1 Specific Conclusions 48.7.2 General Conclusions 48.7.3 Recommendations 48.7.4 Future Works References 49 A Demographic Model to Predict Arrests by Race: An Exploratory Approach 49.1 Introduction 49.2 Literary Background 49.3 Methods and Materials 49.3.1 Data Description 49.3.2 Data Generating Process 49.3.3 Bias Check 49.4 Simulation Results and Analyses 49.5 Conclusion and Future Works References 50 An Efficient Approach to Wireless Firmware Update Based on Erasure Correction Coding 50.1 Introduction 50.2 Firmware Update Solutions 50.2.1 The Existing Approach 50.2.2 The Proposed Approach 50.2.3 Theoretical Comparison 50.3 Implementation and Testing 50.3.1 Operational Time 50.3.2 Experimental Results 50.4 Conclusions References 51 Complex Network Analysis of the US Marine Highway Network 51.1 Introduction 51.2 Centrality Metrics and Centrality Tuple 51.3 Community Detection and K-Core Decomposition 51.4 Comparison of MHN and the Related Transportation Networks 51.5 Conclusions and Future Work References 52 Directed Acyclic Networks and Turn Constraint Paths 52.1 Introduction 52.2 Review of Turn Constrained Paths Algorithms 52.2.1 Boroujerdi-Uhlmann Algorithm 52.2.2 Variation of Bellman-Ford Algorithm 52.2.3 Turn-Constrained Disjoint Paths 52.3 Connectivity and Turn Constraint Paths 52.3.1 Turn-Constrained Shortest Path 52.3.1.1 Connectivity of Turn Constraint Shortest Paths Problem (TCSP) 52.4 Discussions References Index