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

فهرست مطالب :

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