
Modelling and Implementation of Complex Systems
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This proceedings book gives a new vision and real progress towards more difficult problems resolution. In trying to solve the problems we face every day in the complex world we are living, we are constantly developing artificial systems and increasingly complex middleware. Indeed, the research works contained in this book address a large spread of nowadays topics like IoT architectures, communication and routing protocols, smart systems, software defined networks (SDNs), natural language processing (NLP), social media, health systems, machine intelligence and data science, soft computing and optimization, and software technology. This book, which is a selective collection of research papers accepted by the international program committee of the 6th International Symposium on Modelling and Implementation of Complex Systems (MISC 2020), considers intelligence (CI) more as a way of thinking about problems. It includes a mix of old efficient (Fuzzy, NN, GA) and modern AI techniques (deep learning and CNN). The whole complex systems research community finds in this book an appropriate way to approach problems that have no algorithmic solution and finds many well-formulated technical challenges.
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Content
- Intro
- Preface
- Organization
- Honorary Chairs
- General Chairs
- Steering Committee
- Organizing Committee Chairs
- Organizing Committee
- Publication Chairs
- Publicity and Sponsor Chairs
- Program Committee Chairs
- Program Committee
- Co-editors
- Additional Reviewers
- Contents
- Cloud Computing, Networking and IoT
- Dynamic Replication Based on a Data Classification Model in Cloud Computing
- 1 Introduction
- 2 Related Work
- 3 The Proposed Replication Strategy
- 3.1 Creation
- 3.2 Classification
- 3.3 Viral Data Checking Module
- 3.4 Liberation
- 4 Implementation and Experimentation
- 4.1 Experimental Study
- 4.2 Simulation Parameters
- 4.3 Experimental Results and Analysis
- 5 Conclusion
- References
- EECORONA: Energy Efficiency Coordinate and Routing System for Nanonetworks
- 1 Introduction
- 2 Application Context and System Model
- 2.1 Application Context
- 2.2 Terahertz Band
- 2.3 Energy Harvesting Model
- 2.4 Energy Consumption Model
- 3 Assigning of Addresses and Routing System
- 3.1 Coordinate Geolocation Address System
- 3.2 Routing Phase
- 4 Performance Evaluation
- 4.1 Evaluating Metrics and Performance Scenarios
- 4.2 Simulation Setup and Assumptions
- 4.3 Results and Analysis
- 5 Conclusion
- References
- Communication-Flow Privacy-Preservation in 6LoWPANs-Based IoT Networks
- 1 Introduction
- 2 IPv6 Low Power Wireless Personal Area Network (6LoWPAN)
- 3 Communication Privacy
- 3.1 Privacy Definitions
- 3.2 Communication Privacy Preservation Techniques (CPPT)
- 3.3 Anonymous Communication in the IoT
- 4 Main Contributions
- 5 Summary of Main Contributions
- 6 Conclusion
- References
- Workflow Security Scheduling Strategy in Cloud Computing
- 1 Introduction
- 2 Related Work
- 3 System Model and Assumptions
- 4 Proposed System
- 4.1 Pre-scheduler
- 4.2 Security Enhancement Module
- 4.3 Post-Scheduler
- 5 Performance Evaluation and Results
- 5.1 Impact of the Security Level on the Cost
- 5.2 Impact of the Security Level on the Deadline
- 6 Conclusion
- References
- An Optimized Energy-Efficient Mission-Based Routing Protocol for Unmanned Aerial Vehicles
- 1 Introduction
- 2 Related Works
- 3 Proposed Protocol
- 3.1 Mathematical Modeling of PDR and EC Performances Using RSM Methodology
- 3.2 Modelling of Thello as a Function of Vmax, N, and Tx
- 4 Experimental Evaluation and Discussion of Results
- 4.1 Metrics
- 4.2 Experimental Parameter Settings
- 4.3 Results and Discussion
- 5 Conclusions
- References
- Dynamic Clustering Based Energy Optimization for IoT Network
- 1 Introduction
- 2 Related Works
- 2.1 Single-hop Approaches
- 2.2 Muti-hop Approaches
- 3 Network Modelling and Rechargeable Battery Degradation Model
- 3.1 Calendar Aging
- 3.2 Cycle Aging
- 4 Proposed Approach
- 4.1 Neighbors Discovery
- 4.2 Clusters Formation
- 4.3 Maintenance Phase
- 5 Simulation
- 5.1 Experimental Results
- 6 Conclusion
- References
- Machine Intelligence and Data Science
- Comparative Analysis of Machine Learning Algorithms for Early Prediction of Diabetes Mellitus in Women
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 Dataset
- 3.2 Preprocessing
- 3.3 Machine Learning Algorithms for Prediction
- 4 Experimental Results and Discussion
- 5 Conclusion
- References
- Sentiment Analysis in Google Play Store: Algerian Reviews Case
- 1 Introduction
- 2 Related Work
- 3 Proposition: Sentiment Analysis of Algerian App Store Reviews
- 3.1 Language Detection
- 3.2 Machine Learning Approach
- 3.3 Lexicon-Based Approach
- 4 Experiments
- 4.1 Data Collection
- 4.2 Machine Leaning Approach
- 4.3 Lexicon-Based Approach
- 5 Conclusion
- References
- Meta-learning to Select the Best Metaheuristic for the MaxSAT Problem
- 1 Introduction
- 2 Algorithm Selection Problem
- 3 Meta-features for MaxSAT
- 4 Experimental Framework
- 4.1 Set of Metaheuristics
- 4.2 Set of Instances
- 4.3 Meta-learning Process
- 5 Tests and Results
- 5.1 Metaheuristics' Parameters
- 5.2 Data Acquisition and Preparation
- 5.3 Evaluation of the Recommendation Algorithm
- 6 Conclusion
- References
- Ontological Relation Classification Using WordNet, Word Embeddings and Deep Neural Networks
- 1 Introduction
- 2 Related Work
- 3 Proposed Approach
- 3.1 Building the Dataset
- 3.2 Learning Model
- 4 Experiments and Results
- 4.1 Experiment 1: Full Unbalanced Dataset
- 4.2 Experiment 2: Hypernymy, Part Holonymy, Antonymy and Synonymy Classes
- 4.3 Experiment 3: Binary Classification - Hypernymy or Non-hypernymy Class
- 5 Discussion
- 6 Conclusion
- References
- Gender Identification from Arabic Speech Using Machine Learning
- 1 Introduction
- 2 Acoustic Features
- 2.1 Intensity
- 2.2 Zero-Crossing Rate
- 2.3 Fundamental Frequency
- 2.4 Mel Frequency Cepstral Coefficients (MFCC)
- 2.5 Probability of Voicing
- 2.6 Line Spectral Frequency (LSP)
- 3 Related Works
- 4 Arabic Natural Audio Dataset (ANAD)
- 4.1 Dataset Description
- 4.2 Modified Version
- 5 Methodology
- 6 Experiments Results
- 6.1 Stage One
- 6.2 Stage Two
- 6.3 Stage Three
- 7 Conclusion and Future Work
- References
- Face Recognition Based on Harris Detector and Convolutional Neural Networks
- 1 Introduction
- 2 Related Work
- 3 Proposed Method
- 4 Experiments and Results
- 5 Conclusion
- References
- Softcomputing and Optimization
- Quality Preserved Color Image Compression Using Particle Swarm Optimization Algorithm
- 1 Introduction
- 2 Related Work
- 3 Proposed Method
- 3.1 Color Space Design
- 3.2 Discrete Wavelet Transform (DWT)
- 3.3 Thresholds Optimization
- 3.4 Quantization
- 3.5 Lossless Encoder
- 3.6 Performance Criteria
- 4 Results and Performance Comparison
- 5 Conclusion
- References
- A Simple Yet Effective Convolutional Neural Network Model to Classify Facial Expressions
- 1 Introduction
- 2 Related Works
- 3 Facial Expression Recognition System
- 3.1 Convolutional Neural Network
- 3.2 Data Collection
- 3.3 Image Pre-Processing
- 4 Experiments and Discussions
- 5 Conclusion and Future Work
- References
- Materialized View Selection Using Discrete Quantum Based Differential Evolution Algorithm
- 1 Introduction
- 2 Related Work
- 3 Background
- 3.1 Lattice Framework
- 3.2 Space-Constrained MVS Problem
- 3.3 Quantum Inspired Evolutionary Algorithm Overview
- 3.4 Differential Evolution
- 4 QDE Algorithm
- 4.1 Solution Representation
- 4.2 Q-Bit Representation
- 4.3 Quantum Interference Application
- 4.4 Discrete Vs Continuous Search Space
- 4.5 Dealing with Unfeasible Solutions
- 4.6 The ``Reset'' Operator
- 5 Experimental Results
- 6 Conclusion
- References
- Context-Aware Based Evolutionary Collaborative Filtering Algorithm
- 1 Introduction
- 2 Related Work
- 3 Methodology
- 3.1 GA-Based Meta-heuristic to Learn Optimal Weight Vector
- 3.2 Genetic Representation
- 3.3 Fitness Functions
- 3.4 Genetic Operators
- 3.5 Termination Condition
- 4 System Description
- 5 Results and Discussion
- 5.1 Dataset
- 5.2 Evaluation Metrics
- 5.3 Experiment 1: Impact of the Population Size
- 5.4 Experiment 2: Impact of the Crossover Probability
- 5.5 Experiment 3: Impact of the Mutation Probability
- 5.6 Experiment 3: Evaluation of the Proposed Weighting Function
- 6 Conclusion
- References
- A Rule Based Human Skin Detection Method in CMYK Color Space
- 1 Introduction
- 2 Related Works
- 3 The Proposed Method
- 4 Experimental Results
- 5 Conclusion
- References
- Improved NSGA-II for Minimum Weight Minimum Connected Dominating Set Problem
- 1 Introduction
- 2 Related Work
- 3 The Minimum Weight Minimum Connected Dominating Set Problem
- 4 NSGA-II Algorithm
- 4.1 Offspring Production
- 4.2 New Population Selection
- 5 Greedy Heuristics for the MWMCDS Problem
- 6 The Proposed Algorithm I-NSGA-II
- 6.1 Initial Solution
- 6.2 Local Search Method
- 6.3 Progress of I-NSGA-II Algorithm
- 7 Experiments and Results
- 7.1 Experiments
- 7.2 Results
- 8 Conclusion
- References
- Ontology Matching Using Neural Networks: Evaluation for OAEI Tracks
- 1 Introduction
- 2 Related Work
- 3 Overview of the Approach
- 4 Experiments
- 4.1 Experimental Design
- 4.2 Experimental Results
- 4.3 Experimental Summary
- 5 Conclusion
- References
- Software Technology and Model Transformations
- Transforming UML Diagrams to YAWL Models for Business Processes Analysis
- 1 Introduction
- 2 Related Works
- 3 Background
- 3.1 UML Activity Diagram
- 3.2 YAWL
- 3.3 Meta-modeling and Graph Transformation in AToM3
- 4 The Proposed Approach
- 4.1 Activity Diagrams Meta-model
- 4.2 Meta-model of YAWL Models
- 4.3 Transformation Rules
- 4.4 The First Graph Grammar, UML-AD to YAWL
- 4.5 The Second Proposed Graph Grammar, YAWL to Text
- 5 Example
- 6 Conclusion
- References
- Configuration-Dependent Stochastic Reward Nets
- 1 Introduction
- 2 Stochastic Reward Nets
- 3 Configuration-Dependent Stochastic Reward Nets
- 4 Transformation of CD-SRNs into Basic SRNs
- 5 Proofs
- 6 Illustrative Example
- 7 Conclusion
- References
- Author Index
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