
The 8th International Conference on Advanced Machine Learning and Technologies and Applications (AMLTA2022)
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This book constitutes the refereed proceedings of the 8th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2022, held in Cairo, Egypt, during May 5-7, 2022. The 8th edition of AMLTA will be organized by the Scientific Research Group in Egypt (SRGE), Egypt, collaborating with Port Said University, Egypt, and VSB-Technical University of Ostrava, Czech Republic. AMLTA series aims to become the premier international conference for an in-depth discussion on the most up-to-date and innovative ideas, research projects, and practices in the field of machine learning technologies and their applications. The book covers current research on advanced machine learning technology, including deep learning technology, sentiment analysis, cyber-physical system, IoT, and smart cities informatics and AI against COVID-19, data mining, power and control systems, business intelligence, social media, digital transformation, and smart systems.
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Content
- Intro
- Preface
- Organization
- Honorary Chair
- General Chairs
- Co-chairs
- International Advisory Board
- Publication Chair
- Program Chairs
- Publicity Chairs
- Technical Program Committee
- Local Arrangement Chairs
- Contents
- Deep Learning and Applications
- Plant Leaf Diseases Detection and Identification Using Deep Learning Model
- 1 Introduction
- 2 Related Works
- 3 Proposed Method
- 4 Experimental Results
- 5 Conclusions
- References
- Reinforcement Learning for Developing an Intelligent Warehouse Environment
- 1 Introduction
- 2 Machine Learning Techniques
- 3 Results and Discussion
- 4 Conclusion and Future Research
- References
- A Low-Cost Multi-sensor Deep Learning System for Pavement Distress Detection and Severity Classification
- 1 Introduction
- 2 Related Work
- 3 Proposed Methodology
- 3.1 Overall System Architecture
- 3.2 Deep Learning Distress Detection
- 3.3 Dataset and Training Information
- 3.4 Projection onto the Depth 3D Point Cloud and ROI Filtering
- 4 Case Study: Pothole Severity Classification
- 5 Experimental Results
- 5.1 Results for the Distress Detection
- 5.2 Results for Pothole Severity Classification
- 6 Conclusion
- References
- An Intrusion Detection Model Based on Deep Learning and Multi-layer Perceptron in the Internet of Things (IoT) Network
- 1 Introduction
- 2 Related Work
- 2.1 Multi Agent Systems for IDS
- 2.2 Fuzzy Systems for IDS
- 2.3 Game Theory Models for IDS
- 3 Architecture of the Proposed Intrusion Detection System
- 3.1 Pre-processing and Feature Engineering
- 3.2 Deep Learning Layer
- 3.3 Evaluation Layer
- 4 The Experimental Results
- 5 Comparison Between Proposed Models and the Others
- 6 Conclusion
- References
- Transfer Learning and Recurrent Neural Networks for Automatic Arabic Sign Language Recognition
- 1 Introduction
- 2 Related Work
- 3 Arabic Sign Language Dataset
- 4 Methodology
- 4.1 Prepare the Dataset
- 4.2 Extract the Spatial Features
- 4.3 Extract the Temporal Features
- 4.4 Video Augmentation
- 5 Experimental and Results
- 5.1 Experiment Settings
- 5.2 Models Results
- 6 Conclusion and Future Works
- References
- Robust Face Mask Detection Using Local Binary Pattern and Deep Learning
- 1 Introduction
- 2 Related Works
- 3 Proposed Method
- 4 Experimental Results
- 5 Conclusion
- References
- Steganography Adaptation Model for Data Security Enhancement in Ad-Hoc Cloud Based V-BOINC Through Deep Learning
- 1 Introduction
- 1.1 Ad-Hoc Cloud Computing
- 1.2 Deep Steganography
- 1.3 Contribution
- 1.4 Paper Organization
- 2 Literature Review
- 3 Proposed Solution
- 4 Experiment
- 5 Discussion and Analysis
- 6 Conclusion
- References
- Performance of Different Deep Learning Models for COVID-19 Detection
- 1 Introduction
- 2 Deep Learning (DL)
- 2.1 The DL-Algorithms Steps in COVID-19 Diagnosis
- 2.2 DL-Models for COVID-19 Detection
- 3 Discussion
- 4 Conclusion
- References
- Deep Learning-Based Apple Leaves Disease Identification Approach with Imbalanced Data
- 1 Introduction
- 2 Basics and Background
- 2.1 Data Imbalance
- 2.2 Convolutional Neural Networks
- 2.3 Transfer Learning
- 3 The Proposed Approach
- 3.1 Dataset Description
- 3.2 Data Preprocessing Phase
- 3.3 Training Phase
- 3.4 Evaluation Phase
- 4 Experimental Results and Analysis
- 4.1 Data Imbalance Problem
- 4.2 Data Augmentation
- 4.3 Setup of the Experiment
- 4.4 Evaluation of the Model
- 5 Conclusion and Future Work
- References
- Commodity Image Retrieval Based on Image and Text Data
- 1 Introduction
- 2 Related Work
- 3 Method
- 3.1 Image and Text Feature Fusion
- 3.2 Target Function
- 4 Experiment
- 4.1 Evaluation Metrics
- 4.2 Datasets
- 4.3 Experimental Details
- 4.4 Experimental Results and Analysis
- 5 Conclusion
- References
- Machine Learning Technologies
- Artificial Intelligence Based Solutions to Smart Warehouse Development: A Conceptual Framework
- 1 Introduction
- 2 SWOT Analysis
- 2.1 Strengths
- 2.2 Weaknesses
- 2.3 Opportunities
- 2.4 Threats
- 3 Proposed Solutions and Current Approaches
- 3.1 WO Strategy (Improve): Testbed as a Trial for Investment Decision
- 3.2 WO Strategy (Improve): AI-Powered Solutions
- 3.3 SO Strategy (Attack): AI Resource Development
- 4 Conclusions and Future Research
- References
- Long-Short Term Memory Model with Univariate Input for Forecasting Individual Household Electricity Consumption
- 1 Introduction
- 2 Related Works
- 3 Deep Learning Models for Load Forecasting
- 3.1 LSTM and LSTM-ED Neural Networks
- 3.2 CNN-LSTM Neural Networks
- 3.3 GRU Neural Networks
- 3.4 BiLSTM Neural Networks
- 3.5 ConvLSTM Neural Networks
- 4 Results and Discussion
- 4.1 Dataset Description
- 4.2 Evaluation Metrics
- 4.3 Prediction Results of ConvLSTM
- 4.4 Discussion of the Forecasting Models
- 5 Conclusion and Future Work
- References
- DNA-Binding-Proteins Identification Based on Hybrid Features Extraction from Hidden Markov Model
- 1 Introduction
- 2 Materials and Methods
- 2.1 Datasets
- 2.2 Encoding
- 2.3 Framing
- 2.4 Hybrid Visual HMM Structure
- 2.5 Features Extraction
- 2.6 Classifier
- 3 Results and Discussions
- 4 Conclusions
- References
- Machine Learning Based Mobile Applications for Cardiovascular Diseases (CVDs)
- 1 Introduction
- 2 ML Based m-Health for CVDs
- 3 Characteristics of the Commercially Available CVDs Mobile Applications
- 4 Future Requirements
- 5 Conclusion
- References
- Regression Analysis for Remaining Useful Life Prediction of Aircraft Engines
- 1 Introduction
- 2 Related Work
- 3 Aircraft Engine System
- 4 Proposed Model for Predicting the RUL
- 5 Experimental Results and Discussion
- 6 Conclusion and Future Work
- References
- Applying Machine Learning Technology to Perform Automatic Provisioning of the Optical Transport Network
- 1 Introduction
- 2 The Challenges in the Current Model of the Supervision of the OTN
- 3 Proposed Model for the Automatic Provision of the OTN
- 4 Results and Discussion
- 5 Conclusion and Future Work
- References
- Robo-Nurse Healthcare Complete System Using Artificial Intelligence
- 1 Introduction
- 1.1 Related Work
- 2 Research Method
- 2.1 Software Implementation
- 2.2 Hardware Implementation
- 2.3 External Design Implementation
- 3 Results and Discussions
- 4 Conclusion
- References
- Resolving Context Inconsistency Approach Based on Random Forest Tree
- 1 Introduction
- 2 Related Work
- 3 Proposed Approach
- 3.1 IoT Data Collection Phase
- 3.2 Context Inconsistency Validator
- 3.3 Best Resolution Selection
- 3.4 Random Forest Tree
- 4 Experimental Results and Evaluations
- 5 Conclusion and Future Directions
- References
- Arduino Line Follower Using Fuzzy Logic Control
- 1 Introduction
- 2 Methodology
- 2.1 Lab Simulation
- 2.2 The ATmega328p Microcontroller
- 2.3 Voltage Regulator
- 2.4 Circuit Diagram Explanation
- 2.5 Microcontroller-Motor Driver IC Interface
- 2.6 Microcontroller-IR Sensor Module Interface
- 2.7 Microcontroller-Variable Resistor Interface
- 2.8 Arduino IDE Interface with Microcontroller
- 3 Summary of Methodology
- 4 Physical Modeling
- 4.1 Block Diagram
- 4.2 Flow Chart
- 4.3 Working Principle
- 5 Result and Analysis
- 6 Conclusion
- References
- Evaluating Adaptive Facade Performance in Early Building Design Stage: An Integrated Daylighting Simulation and Machine Learning
- 1 Introduction
- 2 Related Works
- 3 Building as a Machine and Machine Learning in Architecture
- 4 Adaptive Facade
- 5 Methodology
- 5.1 Data Collection: Available Forms of Kinetic Façade Systems
- 5.2 Data Preparation: Applying System Possibility Scores
- 5.3 Data Exploration and Case Study Setup
- 5.4 Prediction Stage: Applying the KNN Algorithm as a Selective Filter
- 6 Systems Modeling and Simulation
- 7 Results and Discussion
- 8 Conclusion
- References
- LTE Downlink Scheduling with Soft Policy Gradient Learning
- 1 Introduction
- 2 Downlink Resource Allocation in LTE
- 3 Related Work
- 4 DSPG Scheduler: The Proposed Scheduling Algorithm
- 4.1 Problem Statement
- 4.2 Model Design
- 5 Simulation Implementation and Results
- 6 Conclusions
- References
- Predicting the Road Accidents Severity Using Artificial Neural Network
- 1 Introduction
- 2 Literature Review
- 3 Dataset
- 4 The Proposed Methodology
- 5 Results and Discussions
- 5.1 Attributes vs Accident Severity
- 5.2 Accident Severity Prediction Results
- 6 Conclusion
- References
- Predicting the Intention to Use Audi and Video Teaching Styles: An Empirical Study with PLS-SEM and Machine Learning Models
- 1 Introduction
- 2 Theoretical Framework
- 2.1 Technology Acceptance Model (TAM)
- 2.2 Flow Theory
- 2.3 Virtual Reality Attributes
- 3 Research Methodology
- 3.1 Data Collection
- 3.2 Personal/Demographic Information
- 3.3 Study Instrument
- 3.4 Survey Structure
- 4 Findings and Discussion
- 4.1 Data Analysis
- 4.2 Convergent Validity
- 4.3 Discriminant Validity
- 4.4 Hypotheses Testing Using PLS-SEM
- 4.5 Hypothesis Testing Using Machine Learning Algorithms
- 5 Discussion of Results
- References
- Intellgenet Systems and Applications
- Immunity of Signals Transmission Using Secured Unequal Error Protection Scheme with Various Packet Format
- 1 Introduction
- 2 Related Work Overview
- 3 The Proposed Model of Immune Audio Signals Transmission
- 4 Computer Simulation Experiments
- 4.1 Slow Mobility with Different Transmission Scenarios
- 4.2 Higher Mobility with Different Transmission Scenarios
- 5 Conclusion
- References
- Overlapping Cell Segmentation with Depth Information
- 1 Introduction
- 2 Cell Segmentation with Depth Information
- 2.1 Contour Point Attributes with Depth Information
- 2.2 Contour Segment Attributes with Depth Information
- 3 Experimental Results and Discussion
- 3.1 Collection and Evaluation Method
- 3.2 Results
- 3.3 Comparison and Analysis of Cell Segmentation Algorithms
- 4 Conclusion
- References
- Analysis of the China-Eurasian Economic Union Trade Potential Based on Trade Gravity Model
- 1 Preface
- 2 Trade Status Between China and the Five Countries of the EEU
- 2.1 General Situation
- 2.2 Sino-Russian Trade Situation
- 2.3 Sino- Kazakhstan Trade Situation
- 2.4 Trade Between China and Other Three Countries
- 3 Empirical Analysis of China-Eurasian Economic Union's Trade Potential
- 3.1 Construction of Trade Gravity Model
- 3.2 Measurement of Trade Potential Between China and the Five Countries of the EEU
- 4 Conclusion
- References
- Skip Truncation for Sentiment Analysis of Long Review Information Based on Grammatical Structures
- 1 Introduction
- 2 Related Works
- 3 Materials and Method
- 3.1 Raw Data
- 3.2 Sentiment on Grammatical Components
- 3.3 Skip Truncation
- 3.4 Sentiment Perceptron
- 4 Experimental Results
- 4.1 Model Settings
- 4.2 Baselines
- 4.3 Results on Binary Sentiment Polarity
- 4.4 Results on Multiple Sentiment Polarity
- 5 Conclusion
- References
- Improving the Power Quality of the Distribution System Based on the Dynamic Voltage Restorer
- 1 Introduction
- 2 DVR Operation Process
- 3 DVR Control System
- 3.1 Controlling the DVR Using the Battery Energy Storage System
- 3.2 Self-supporting DVR Control (Has a Support Capacitor)
- 4 Simulation and Modeling Results
- 5 DVR System Performance Evaluation
- 6 Conclusion
- References
- Ecosystem of Health Care Software Engineering in 2050
- 1 Introduction
- 2 Current Health Care Eco System
- 3 Emerging Technologies in Health Care Industry
- 3.1 Mixed Reality
- 3.2 Robotics
- 3.3 Artificial Intelligence (AI)
- 3.4 Internet of Things (IoT)
- 3.5 Blockchain
- 4 Literature Review
- 4.1 Solution to MR Challenges
- 4.2 Solution to Robotics Challenges
- 4.3 Solution to AI Challenges
- 4.4 Solution to IoT Challenges
- 4.5 Solution to Blockchain Challenges
- 5 Conclusion
- References
- Precision Education Approaches to Education Data Mining and Analytics: A Review
- 1 Introduction
- 2 Literature Review
- 2.1 Background
- 2.2 Theoretical Framework
- 2.3 Related Work
- 3 Method
- 3.1 Identifying the Purpose
- 3.2 Selection Criteria
- 3.3 Data Sources and Search Strategies
- 3.4 Quality Assessment
- 3.5 Data Analysis and Coding Framework
- 4 Results
- 4.1 RQ1. What are the Trends of the Articles Published on Precision Education in the EDM Context?
- 4.2 RQ2. What are the Main Research Purposes Related to Precision Education in the Context of EDM?
- 4.3 RQ3. What are the Main EDM Tasks that are Used in Precision Education?
- 4.4 RQ4. What Data Mining Tool Have Been Used in Precision Education?
- 4.5 RQ5. What is the Application of Data Mining in Precise Education?
- 4.6 RQ6. What are Some of the Challenges Faced by Precision Educations?
- 4.7 RQ7. What are Possible Future Directions for Research on Precision Education Using EDM?
- 5 Discussion
- 5.1 Limitations
- 6 Conclusion
- References
- The Impact of Strategic Orientation in Enhancing the Role of Social Responsibility Through Organizational Ambidexterity in Jordan: Machine Learning Method
- 1 Introduction
- 2 Literature Review
- 3 Theoretical Framework
- 4 Research Methodology
- 5 Data Analysis
- 6 Discussions
- 7 Conclusions
- References
- Three Mars Missions from Three Countries: Multilingual Sentiment Analysis Using VADER
- 1 Introduction
- 2 Literature Review
- 2.1 Background
- 2.2 Related Work
- 3 Methodology
- 3.1 Design of Experiments
- 4 Results
- 4.1 Mars Sentiment Analysis
- 4.2 The Impact of MSA on Mars Missions' Tweets
- 5 Discussion
- 6 Conclusion
- References
- Applying the Uses and Gratifications Theory to College Major Choice Using Social Networks Online Video
- 1 Introduction
- 2 Literature Review
- 2.1 Uses and Gratifications of Student to Major Academic Choices by Online Video
- 2.2 Motivations of Student to Major Academic Choices, by Online Video
- 2.3 Video Content with Uses and Gratifications
- 3 Discussion
- 4 Conclusion and Recommendations
- References
- Determinants of Unemployment in the MENA Region: New Evidence Using Dynamic Heterogeneous Panel Analysis
- 1 Introduction
- 2 Literature Review
- 3 Methodology and Data Used
- 3.1 Data Descriptions
- 4 Empirical Findings
- 5 Conclusions
- References
- The Relationship Between Digital Transformation and Quality of UAE Government Services Through Machine Learning
- 1 Introduction
- 2 Literature Review
- 3 Digital Transformation of Governments
- 4 Digital Transformation in Government Services in the UAE
- 5 Quality of Service for Customers in Government Institutions
- 6 Discussion
- 7 Conclusion
- References
- Key Factors Determining the Expected Benefit of Customers When Using Artificial Intelligence
- 1 Introduction
- 2 Reasons for Using Artificial Intelligence in E-commerce
- 2.1 Reduce Cart Abandonment
- 2.2 Facilitate Voice Search
- 2.3 Enhance Your Targeting of a More Specific Audience
- 2.4 Improve Search Results
- 3 Artificial Intelligence in 2020
- 4 Benefits of Using Artificial Intelligence Techniques in E-commerce
- 4.1 It Saves Time and Energy
- 4.2 Improves Customer Satisfaction
- 4.3 Software can Make Business Owners Better Serve Their Customers in the Following Ways
- 4.4 Optimizing Operations and Business Intelligence
- 4.5 Reduces the Error
- 4.6 Improves Marketing
- 5 How Will AI Change E-commerce?
- 6 Conclusion
- References
- Examining Factors Affecting Job Employment in Egyptian Market
- 1 Introduction
- 2 Literature Review
- 3 Research Methodology
- 3.1 Hypothesis Formulation
- 3.2 Data Collection
- 4 Discussion of Results
- 4.1 Descriptive Statistics
- 4.2 Reliability Analysis
- 4.3 Exploratory Factor Analysis (EFA)
- 4.4 Conformity Factor Analysis (CFA)
- 5 Conclusion and Future Work
- References
- Intrinsic Interference Reduction: A Channel Estimation Approach for FBMC-OQAM Systems
- 1 Introduction
- 2 FBMC-OQAM System
- 3 Scattered Pilots Channel Estimation Techniques
- 3.1 AP Method
- 3.2 Coding Method
- 4 Proposed Method
- 5 Simulation Results
- 6 Conclusion
- References
- Impact of Using Different Color Spaces on the Image Segmentation
- 1 Introduction
- 2 Related Work
- 3 Color Spaces
- 3.1 RGB
- 3.2 HSV
- 3.3 YCbCr
- 3.4 XYZ
- 4 Segmentation Techniques
- 4.1 K-Means Clustering Segmentation
- 4.2 Fuzzy C-Means Clustering Segmentation
- 4.3 Region Growing Segmentation
- 4.4 Graph Cut Segmentation
- 5 Experimental Results
- 5.1 Dataset
- 5.2 Accuracy Criteria
- 5.3 Results
- 6 Conclusion
- References
- The Relationship Between Functional Empowerment and Creative Behavior of Workers During the COVID-19 Pandemic in the UAE
- 1 Introduction
- 2 Literature Review
- 2.1 The Importance of Empowering Employees
- 2.2 Employees Empowerment with Creative Behavior
- 2.3 The Effect of Decentralization of Authority on the Creative Behavior
- 3 Factors of Creative Behavior of Employees in UAE
- 4 Creative Behavior of Workers During the Covid-19 in UAE
- 5 Discussion
- 6 Conclusion and Future Work
- References
- The Role of Strategic Leadership to Achieving Institutional Excellence for Emirati Federal Institutions
- 1 Introduction
- 2 Development of Conceptual Model
- 2.1 Strategic Leadership and Institutional Excellence
- 2.2 Role of Development Strategies and Organizational Processes in Achieving Institutional Excellence
- 2.3 Role of Leading and Developing People in Achieving Institutional Excellence
- 2.4 Role of Developing Culture and Value System in Achieving Institutional Excellence
- 2.5 Role of Developing Distinct Organizational Competencies in Achieving Institutional Excellence
- 2.6 Role of Developing Effective Networking Competencies in Achieving Institutional Excellence
- 3 Research Methodology
- 3.1 Convergent Validity
- 3.2 Discriminant Validity of Research Model
- 4 Data Analysis and Findings
- 4.1 Sampling and Demographics of Participants
- 4.2 Coefficients of Determination R2
- 4.3 Hypotheses Testing: Path Analysis, Regression, and Mediation Analysis
- 5 Conclusion
- References
- An Extended Modeling Approach for Marine/Deep-Sea Observatory
- 1 Introduction
- 2 Related Work
- 3 Marine Observatories
- 4 Model-Driven Engineering (MDE) and Domain-Specific Modeling Languages (DSML)
- 5 Contribution
- 6 Object Localization Case Study
- 6.1 Design Model
- 6.2 Compilation and Simulation
- 7 Conclusion and Future Work
- References
- Internet of Things and Smart Cities
- Internet of Vehicles and Intelligent Routing: A Survey-Based Study
- 1 Introduction
- 2 Motivation from VANETs to IoV: Architecture and Characteristics
- 2.1 Architecture of IoV
- 2.2 Characteristics of IoV
- 3 Routing Protocols in IoV
- 3.1 Topology-Based Routing
- 3.2 Position-Based Routing
- 3.3 Multicast Routing Protocols
- 3.4 Broadcast Routing
- 4 Heuristic Bio-inspired Routing Protocols Literature
- 4.1 Evolutionary Algorithms
- 4.2 Swarm Intelligence
- 4.3 Other Bio-inspired Approaches
- 4.4 Hybrid Approaches
- 5 Conclusion
- References
- Location Privacy-Preserving of Vehicular Ad-Hoc Network in Smart Cities
- 1 Introduction
- 2 Related Work
- 3 Preliminaries
- 3.1 Advanced Encryption Standard (AES)
- 3.2 Homomorphic Cryptography
- 3.3 Fully Homomorphic Over Advanced Encryption Standard (FHE Over AES)
- 4 Research Scheme
- 4.1 System Design
- 4.2 System Processing
- 5 Performance Evaluation
- 5.1 Simulation Tools
- 5.2 Performance Metrics
- 6 Conclusion
- References
- Post-pandemic Education Strategy: Framework for Artificial Intelligence-Empowered Education in Engineering (AIEd-Eng) for Lifelong Learning
- 1 Introduction
- 2 Background of AI
- 3 Evolution in AIEd-Eng Research
- 3.1 AIEd-Eng Models: From Learning to Management
- 4 AIEd-Eng Strategy, Main Processes, and Applications
- 4.1 Teaching Process
- 4.2 Learning Process
- 4.3 Decision-Making Process
- 5 Prospective Trends and Challenges
- 6 Conclusions
- References
- An Intelligent Algorithmic Approach for Data Collection in a Smart Warehouse Testbed
- 1 Introduction
- 2 Introduction
- 2.1 Basic Requirements
- 2.2 Solution Approaches
- 3 System Design
- 3.1 Description of the System
- 3.2 Description of the Operation of the System
- 4 Analysis of the Smart Warehouse Testbed
- 4.1 Simulation Model for Searching (Tseparator, Vconveyor, and Tstoring)
- 4.2 Details of the Simulation Model
- 5 Results and Discussion
- 6 Conclusion and Future Work
- References
- Fog, Edge, and Cloud Computing
- Mobility-Aware Task Offloading Enhancement in Fog Computing Networks
- 1 Introduction
- 2 Computing Paradigms
- 2.1 Mobile Edge Computing (MEC)
- 2.2 Vehicular Edge Computing (VEC)
- 3 Related Work
- 4 Proposed Model
- 4.1 Fog Computing Architecture
- 4.2 Local Computing Model
- 4.3 Fog Computing Model
- 4.4 Fog Computing Model with Mobility
- 5 Problem Formulation
- 6 Conclusion
- References
- Comprehensive Study on Machine Learning-Based Container Scheduling in Cloud
- 1 Introduction
- 2 Background
- 2.1 Containers and Virtual Machines
- 2.2 Container Engine
- 2.3 Container Cluster and Orchestration Architecture
- 2.4 Machine Learning Types
- 3 Related Machine Learning for Container Orchestration
- 4 Conclusion
- References
- Mobile Computation Offloading in Mobile Edge Computing Based on Artificial Intelligence Approach: A Review and Future Directions
- 1 Introduction
- 2 Background
- 2.1 Multi-tier Computing Paradigm
- 2.2 Mobile Computation Offloading
- 2.3 Machine Learning
- 2.4 Meta-learning
- 3 Related Work
- 3.1 Machine Learning in MCO
- 3.2 Meta-learning in MCO
- 4 Conclusion
- References
- Assessment of Driving Behavior on Edge Devices Using Machine Learning and Sensor Data
- 1 Introduction
- 2 Related Works
- 2.1 Methods
- 2.2 Existing Applications
- 3 Materials and Methods
- 3.1 System Components
- 3.2 Dataset
- 3.3 Sensor Data
- 3.4 Secondary Task Identification
- 3.5 Drowsiness Detection
- 3.6 Forward Gap Estimation
- 3.7 Lane Drifting
- 3.8 Implementation in TensorRT
- 3.9 Overall System Design
- 4 Results and Discussion
- 4.1 Drowsiness Detection
- 4.2 Secondary Task Classification
- 4.3 Car Distance Estimation
- 4.4 Lane Drifting
- 4.5 Implementation in Jetson Nano
- 5 Conclusions
- References
- Advanced Deep Reinforcement Learning Protocol to Improve Task Offloading for Edge and Cloud Computing
- 1 Introduction
- 2 Related Work
- 2.1 Supervised Learning-Based Offloading Mechanisms
- 2.2 Unsupervised Learning-Based Offloading Mechanisms
- 2.3 Reinforcement Learning-Based Offloading Mechanisms
- 3 System Model and Problem Formulation
- 3.1 System Model
- 3.2 Problem Formulation
- 4 ADRL Algorithm
- 4.1 Offloading Action Generation
- 4.2 Training
- 4.3 Testing
- 5 Simulation Results
- 5.1 The Effect of Learning Rate on the Gain Ratio
- 5.2 Gain Ratio Comparison Analysis
- 5.3 Computation Time and Comparison Analysis
- 6 Conclusion and Future Work
- References
- Intelligent Optimization
- Early Classification COVID-19 Based on Particle Swarm Optimization Algorithm Using CT-Images
- 1 Introduction
- 2 Related Works
- 3 Materials and Methods
- 3.1 Methodology
- 3.2 Dataset
- 3.3 Feature Selection (FS)
- 3.4 Feature Selection Approaches
- 3.5 Particle Swarm Optimization Algorithm (PSO)
- 3.6 Classification Methods
- 4 The Proposed PSO-FS Model
- 5 Experimental Results
- 5.1 Performance Metrics
- 5.2 The Evaluation Model
- 6 Conclusion
- References
- MARL-FWC: Optimal Coordination of Freeway Traffic Control Measures
- 1 Introduction
- 2 Single and Multi-agent Algorithms
- 3 MARL-FWC Architecture
- 3.1 MARL-FWC with Single Ramp and RLCA
- 3.2 MARL-FWC Based on Cooperative Q-learning
- 3.3 MARL-FWC for Adaptive Ramp Metering Plus DSLs
- 4 Performance Evaluation
- 5 Conclusions
- References
- Can Digital Finance Contribute to the Optimization of Industrial Structures: Empirical Evidence from Chinese 260 Cities
- 1 Introduction
- 2 Literature Review
- 3 Models and Data
- 3.1 Model Setting
- 3.2 Data and Data Resources
- 4 Empirical Results
- 4.1 The Effect of Digital Finance on the Optimization of Industrial Structures
- 4.2 The Impact of Different Dimensions of Digital Finance on the Optimization of Industrial Structure
- 4.3 Robustness Tests
- 5 Conclusions and Recommendations
- References
- Optimization of Artificial Potential Field Parameters based on Enhanced Butterfly Algorithm
- 1 Introduction
- 2 Original Butterfly Algorithm
- 3 Enhanced Butterfly Algorithm
- 4 Numerical Simulation
- 5 APF Parameters Optimization Problem
- 6 Conclusion
- References
- A Discrete Grey Wolf Optimization Algorithm for Minimizing Penalties on a Single Machine Scheduling Problem
- 1 Introduction
- 2 Related Works
- 3 The Proposed Algorithm
- 3.1 The Standard Grey Wolf Optimization Algorithm (GWO)
- 3.2 The Proposed DGWO
- 4 Experimental Results
- 4.1 Parameter Setting
- 4.2 Performance of DGWO
- 5 Conclusion
- References
- Chaos-Based Applications of Computing Dynamical Systems at Finite Resolution
- 1 Introduction
- 2 Related Work
- 3 Proposed Method
- 3.1 Finite Combinatorial Representation
- 3.2 Combinatorial Pseudo Random Number Generator
- 4 Experimental Results
- 4.1 Steady State Probability of the Logistic Map
- 4.2 Combinatorial Pseudo Random Number Generator
- 5 Conclusions and Future Works
- References
- Author Index
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