13th International Conference on Information Systems and Advanced Technologies "ICISAT 2023"
Description
This book covers the Proceedings of the 13th International Conference on Information Systems and Advanced Technologies "ICISAT'2023." One of the evocative and valuable dimensions of this conference is the way it brings together researchers, scientists, academics, and engineers in the field from different countries and enables discussions and debate of relevant issues, challenges, opportunities, and research findings.
The ICISAT'2023 conference provided a forum for research and developments in the field of information systems and advanced technologies and new trends in developing information systems organizational aspects of their development and intelligent aspects of the final product.
The aim of the ICISAT'2023 is to report progress and development of methodologies, technologies, planning and implementation, tools, and standards in information systems, technologies, and sciences.
ICISAT'2023 aims at addressing issues related to the intelligent information, data science, and decision support system, from multidisciplinary perspectives and to discuss the research, teaching, and professional practice in the field.
The book of ICISAT'2023 includes selected papers from the 13th International Conference on Information Systems and Advanced Technologies "ICISAT'2023," organized during December 29-30, 2023.
In this book, researchers, professional software, and systems engineers from around the world addressed intelligent information, data science, and decision support system for the conference. The ideas and practical solutions described in the book are the outcome of dedicated research by academics and practitioners aiming to advance theory and practice in this research domain.
The list of topics is in all the areas of modern intelligent information systems and technologies such as neural networks, evolutionary computing, adaptive systems, pervasive system, ubiquitous system, E-learning and teaching, knowledge-based paradigms, learning paradigms, intelligent data analysis, intelligent decision making and support system, intelligent network security, web intelligence, deep learning, natural language processing, image processing, general machine learning, and unsupervised learning.
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Content
- Intro
- Contents
- Perspectives of TinyML-Based Self-management in IoT-Based Systems
- 1 Introduction
- 2 Background Information
- 2.1 Self-management
- 2.2 IoT-Based Systems
- 3 Self-management Issues in IoT-Based Systems
- 3.1 Increasing Complexity of IoT Software Systems
- 3.2 Challenges Specific to Self-management of IoT-Based Systems
- 4 Needs and Requirements for an Effective Self-management Solution
- 5 TinyML
- 5.1 Definition
- 5.2 Fundamental Principles of TinyML
- 6 TinyML-Based Self-management for IoT-Based Systems
- 6.1 Motivations
- 6.2 Current Limitations
- 7 Future Prospects and Opportunities
- 7.1 Evolution of TinyML and Related Techniques
- 7.2 Integrating TinyML into Existing IoT Management Architectures
- 7.3 Practical Implications and Potential Applications
- 8 Conclusion
- References
- Blockchain Technology for Absence Tracking
- 1 Introduction and Related Works
- 2 Preliminaries
- 2.1 Principale of Blockchain Technology
- 2.2 Smart Contracts
- 2.3 Transaction
- 2.4 Wallet
- 3 Our Approach
- 3.1 Global Architecture of Our System
- 4 Experimentation
- 5 Discussion
- 6 Conclusion
- References
- Deep Neural Network Binary Classification for Malware Detection: A Parametric Study
- 1 Introduction
- 2 Malware Detection Techniques
- 3 State of the Art
- 4 Datasets
- 5 Used Deep Learning Architecture
- 6 Results and Discussion
- 7 Conclusion and Perspectives
- References
- An Overview of Formal Verification of Network-on-Chip (NoC) Methods
- 1 Introduction
- 2 Network on Chip Architecture
- 3 Network on Chip and Formal Verification
- 4 Related Works
- 5 Conclusion
- References
- Image Classification Using a Deep Convolutional Neural Network
- 1 Introduction
- 2 Related Work
- 3 Proposed System
- 4 Experimental Results
- 5 Conclusion
- References
- Handwriting Recognition Using HOG and Gabor Features
- 1 Introduction
- 2 Related Works
- 3 Proposed Methods
- 4 Experimental Results
- 5 Conclusions
- References
- Application of Faster-RCNN with Detectron2 for Effective Breast Tumor Detection in Mammography
- 1 Introduction
- 2 Related Works
- 3 Method
- 3.1 Data Preparation and Augmentation
- 3.2 Detection Model
- 4 Experiment and Results
- 4.1 Dataset
- 4.2 Dataset Preprocessing
- 4.3 Evaluation and Performance
- 4.4 Our Model
- 4.5 Results and Discussion
- 5 Conclusion
- References
- Explaining Machine Learning Based Speed Anomaly Detection System Using eXplainable Artificial Intelligence
- 1 Introduction
- 2 Related Literature Review
- 3 The Proposed Method
- 3.1 The System Model
- 3.2 Dataset Description
- 3.3 The Methodology
- 4 Results and Discussion
- 4.1 Comparisons Between Classifiers
- 4.2 Comparison with Recent Works in the Literature
- 4.3 Explanation
- 5 Conclusion and Future Work
- References
- Enhanced CNN Architecture with Comprehensive Performance Metrics for Emotion Recognition
- 1 Introduction
- 2 Literature Survey
- 2.1 CNN Approach for Emotion Recognition via EEG
- 2.2 Real-Time Evaluation Algorithm for Noncontact Heart Rate Variability Monitoring
- 2.3 System of Emotion Recognition and Judgment and Its Application in Adaptive Interactive Game
- 2.4 Dual-Branch Dynamic Graph Convolution Based Adaptive Transformer Feature Fusion Network for EEG Emotion Recognition
- 2.5 Adaptive Gamification in Science Education
- 3 Problem Statement
- 4 Proposed Methodology
- 5 Result
- 6 Conclusion
- References
- Pelican Search Optimization for MANETs Routing
- 1 Introduction
- 2 Related Works
- 3 Proposed Approach AODVPE
- 3.1 Source of Inspiration
- 4 Implementation and Experimental Results
- 4.1 Implementation Details
- 4.2 Results and Discussion
- 5 Discussion
- 6 Conclusion
- References
- Detection of Obstructive Sleep Apnea Based on Deep Learning Models from ECG Signals: A Review
- 1 Introduction
- 2 Methodology
- 2.1 Datasets
- 2.2 Preprocessing and Segmentation
- 2.3 Deep Learning Architectures
- 2.4 Performance Metrics
- 3 Deep Learning Techniques for OSA Detection
- 4 Discussion
- 5 Conclusion
- References
- MPPT Controller Based on Adaptive Pid Based on Programmed Gains for Maximum Power Point Tracking in a Photovoltaic Power Plant with a Battery Load
- 1 Introduction
- 2 General Diagram of the PV System
- 3 General Diagram of the PV System
- 3.1 Mathematical Model
- 4 Simulink Library Model
- 4.1 Design of DC/DC Step-Down Converter (Buck)
- 4.2 Adaptive PID Controller with Programmed Gains
- 5 Controller Performance Indexes
- 5.1 PV Module Validation
- 6 Results
- 7 Conclusions
- References
- Optimal Reconfiguration of Electric Power Distribution Networks
- 1 Introduction
- 2 Methodology
- 2.1 Distribution Network Reconfiguration Model
- 2.2 Methodology for Optimal Distribution Network Reconfiguration
- 2.3 Final Model
- 3 Results
- 3.1 Discussion Analysis
- 4 Conclusions
- References
- QFANet: A New Communication Model Base on Tree Architecture for Flying Ad Hoc Networks
- 1 Introduction
- 2 Related Work
- 2.1 Centralized Architecture
- 2.2 Satellite Architecture
- 2.3 Cellular Architecture
- 2.4 Single Group Ad Hoc Architecture
- 2.5 Multi-group UAVs Ad Hoc Architecture
- 2.6 Multi Layers UAVs Ad Hoc Architecture
- 3 The Proposed Communication Model QFANet
- 4 Simulation
- 5 Conclusion
- References
- VAAD: A VAE Based Anomaly Detection Approach for Smart Grids
- 1 Introduction
- 2 Literature Review
- 2.1 Traditional Approaches
- 2.2 Machine Learning in Anomaly Detection
- 2.3 Variational Autoencoders (VAEs)
- 2.4 Context-Aware Anomaly Detection
- 3 Proposed VAAD Approach
- 3.1 Data Preprocessing
- 3.2 Variational Autoencoder Architecture
- 3.3 Contextual and Temporal Integration
- 3.4 Noise-Tolerant Concept Drift Detection
- 3.5 Anomaly Identification
- 4 Case Study
- 4.1 Dataset Description
- 4.2 Results
- 4.3 Discussion
- 5 Conclusion
- References
- DNA Data Encoding and Compression Using Image Compression Algorithms
- 1 Introduction
- 2 Literature Review
- 2.1 DNA Compression
- 2.2 Applications of DNA Compression
- 2.3 DNA Sequencing
- 3 Image-Based DNA Encoding
- 4 Conclusion
- References
- Generalized Multistage Feature for Deep Age Estimation from a Human Face Image
- 1 Introduction
- 2 State of the Art
- 3 Proposed System
- 3.1 Preprocessing
- 3.2 Face Features Extraction
- 3.3 Dimensionality Reduction
- 3.4 Robust Regression Step
- 4 Experimental Framework
- 4.1 Databases
- 4.2 Evaluation Protocol
- 4.3 Experımental Results
- 5 Conclusion
- References
- Enhancing Intrusion Detection Systems Through Simultaneous Feature Selection and Hyperparameter Tuning
- 1 Introduction
- 2 Related Works
- 3 Proposed Approach
- 3.1 Representation of Individuals/population
- 3.2 Fitness Evaluation
- 4 Experiments and Results
- 4.1 Dataset
- 4.2 Experiments
- 4.3 Evaluation Metrics
- 4.4 Experimental Results
- 5 Conclusion
- References
- A Hybrid Genetic Algorithm for Hierarchical Routing in Wireless Sensor Networks
- 1 Introduction
- 2 Literature Review
- 3 Proposed Approach
- 3.1 General Description and Objectives of the GF Scheme
- 4 Experimental Analysis
- 4.1 Simulation Step
- 4.2 Results and Discussion
- 5 Conclusion
- References
- Energy-Aware LEACH: A Weighted Metric Approach for Dynamic Cluster Head Selection in WSN
- 1 Introduction
- 1.1 LEACH Protocol Overview
- 1.2 Contributions to This Paper
- 1.3 Energy Model
- 1.4 Assumptions
- 2 Related Works
- 3 Proposed Work
- 3.1 Cluster Head Selection Approach
- 4 Implementation and Experimental Results
- 4.1 Performance Metrics
- 5 Conclusion
- References
- Author Index
