Advances on smart and soft computing : proceedings of ICACIn 2021 / / Faisal Saeed [and three others]

• Record Nr.: UNINA9910743257903321
• Pubbl/distr/stampa: Singapore : , : Springer, , [2021]; ©2021
• ISBN: 981-16-5559-6; 981-16-5558-8
• Descrizione fisica: 1 online resource (526 pages)
• Collana: Advances in Intelligent Systems and Computing ; ; v.1399
• Disciplina: 006.3
• Soggetti: Artificial intelligence - Safety measures; Artificial intelligence - Methodology
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- ICACIN'21 Organizing Committee -- Preface -- Contents -- About the Editors -- Artificial Intelligence I -- Adaptive Learning Content Based on Learning Styles in Learning Management System -- 1 Introduction -- 2 Literature Review -- 2.1 Adaptive Content -- 2.2 Learning Style -- 2.3 Existing Personalization Taxonomy -- 2.4 Personalization Learning -- 3 Research Methodology -- 4 Results and Discussion -- 5 Conclusion -- References -- A Model-Based Approach for COVID-19 Propagation -- 1 Introduction -- 1.1 The Time-Dependent SIR Model -- 1.2 Differential Equation of Time-Dependent SIR Model -- 1.3 Estimation of β(t) and γ(t) Using L2 Regularization -- 1.4 Estimating the Model Parameters, (t) and (t) -- 1.5 The Basic Reproduction Number -- 2 Dataset -- 3 COVID-19 Exploratory Analysis -- 3.1 COVID-19 Cases in Morocco -- 4 Time Evolution of the Time-Dependent SIR Model -- 5 Conclusion and Future Work -- References -- Numerical Modeling of the Mechanical Behavior of Recycled Flexible PVC Loaded with Different Percentages of Chicken Feathers -- 1 Introduction -- 2 Numerical Study -- 2.1 Mesh and Geometry -- 3 Rho and Gamma Indicators -- 3.1 Mechanical Characteristics -- 4 Results and Discussion -- 5 Conclusion -- References -- Covid-19 Detection from Pneumonia Image Classification Using Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Methods ; -- 3.1 Covid-19 Dataset -- 3.2 Image Data Augmentation with Keras ImageDataGenerator -- 3.3 The Architectures Used for Transfer Learning: DenseNet121 and VGG16 -- 4 Experimental Results -- 5 Conclusion -- References -- Toward the Prediction of the Elasticity of Bio Loaded Polypropylene Using Artificial Neural Networks -- 1 Introduction -- 2 Materials and Methods -- 2.1 Materials -- 2.2 Methods -- 2.3 Smart Methods -- 3 Results and Discussion -- 4 Conclusion -- References.; Post-COVID-19: Deep Image Processing AI to Analyze Social Distancing in a Human Community -- 1 Introduction -- 2 Related Works -- 3 Proposed Approach -- 3.1 Human Detection Step -- 4 Faster R-CNN Design -- 5 Results and Discussion -- 5.1 Phase I-Person Detection Step -- 5.2 Phase II-Distance Computation Step -- 6 Conclusion -- References -- Design and Implementation of ImALeG Serious Game: Behavior of Non-playable Characters (NPC) -- 1 Introduction -- 2 Related Works -- 3 Design and Implementation -- 3.1 ImALeG Virtual Reality Game -- 3.2 Fuzzy Finite-state Machine Design -- 4 Emotional Impact -- 5 Conclusion -- References -- Detection of Personality Traits Through Handwriting Analysis Using Machine Learning Approach -- 1 Introduction -- 2 Literature Review -- 3 Research Methodology -- 3.1 Scanning -- 3.2 Preprocessing -- 3.3 Line Segmentation -- 3.4 Feature Extraction -- 3.5 Classification and Analysis -- 4 Results and Discussion -- 4.1 Preprocessing -- 4.2 Line Segmentation -- 4.3 Feature Extraction -- 4.4 Classification and Analysis -- 4.5 Handwriting Analysis Application -- 5 Conclusion and Future Work -- References -- Data Science -- Hybrid Students' Academic Performance and Dropout Prediction Models Using Recursive Feature Elimination Technique -- 1 Introduction -- 2 Related Works -- 2.1 Naïve Bayes -- 2.2 Support Vector Machine -- 2.3 Recursive Feature Elimination (RFE) Technique -- 3 Methodology -- 4 Results and Discussion -- 4.1 Results of the Autoclassifier Detection Stage -- 4.2 Results of the Feature Selection Layer -- 4.3 Results of the Classification Layer -- 4.4 Results of the Model Evaluation Layer -- 5 Conclusion -- References -- Stage Classification of Alzheimer's Disease Using Transfer Learning -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Set -- 3.2 Proposed Models -- 4 Results and Discussion.; 4.1 Evaluation -- 4.2 Results -- 5 Conclusion -- References -- Predicting the e-Signing Likelihood of Loan Using Machine Learning Models Combining Clustering with Supervised Learning -- 1 Introduction -- 2 Related Work -- 3 Background -- 4 Approach Methodology -- 4.1 Dataset Description -- 4.2 Proposed Pipeline -- 5 Results and Discussion -- 5.1 Classical Approach-Logistic Regression -- 5.2 Machine Learning Approach -- 5.3 A Hybrid Approach Using a Pre-clustering Step to Enhance Performance Using Self-organizing Map Clustering -- 6 Conclusion and Future Work -- References -- Designing an Arabic Google Play Store User Review Dataset for Detecting App Requirement Issues -- 1 Introduction -- 2 Related Works -- 3 Dataset Design -- 3.1 Data Collection Phase -- 3.2 Feature Engineering Phase -- 4 Enabling Research -- 4.1 Sentiment Analysis -- 4.2 Dialect Identification -- 4.3 App Review -- 4.4 Gender Detection -- 4.5 Software Issue Detection -- 5 Conclusion and Future Work -- References -- A Survey of Machine Learning and Deep Learning Applications in Genome Editing -- 1 Introduction -- 2 Genomics -- 3 Genome Editing -- 3.1 Application of Machine Learning in Genome Editing -- 4 Summary and Discussion -- 5 Conclusion -- References -- Educational Data Mining Techniques for Detecting Undesirable Students' Behaviors and Predicting Students' Performance: A Comparative Study -- 1 Introduction -- 2 Educational Data Mining ; Tasks -- 2.1 Detecting Undesirable Students' Behaviors -- 2.2 Detecting Students' Performance -- 3 Discussion and Future work -- References -- COVID-19: Analysis and Measurement of the Influence of the Tweets to Help the Public Health Sector to Fight Coronavirus -- 1 Introduction -- 2 Coronaviruses (COVID-19) -- 3 Twitter -- 4 Influence: An Overview for Our Case -- 5 Related Work -- 5.1 TunkRank Algorithm.; 5.2 Twitter Ratio (Followers and Following) -- 6 Method and Algorithm -- 6.1 Our Method -- 6.2 Influence Score Algorithm Inf(X, TempD) -- 7 Experiments Results and Discussion -- 7.1 The Influential Tweeted not About COVID-19 (Other Tweets) -- 7.2 The Influential Tweeted About COVID-19 -- 8 Conclusion -- References -- Data Analytics Model for Home Improvement Store -- 1 Introduction -- 2 Related Work -- 2.1 Introduction to a Home Improvement Store -- 2.2 Importance of Applying Data Analytics Model to Retail Business -- 2.3 Study on Existing Data Analytics Model -- 2.4 Research Methodology -- 3 Data Quality of Dataset -- 3.1 Issues in Current Dataset -- 3.2 Handling Data Quality Issues -- 3.3 Missing Data -- 3.4 Noisy Data -- 3.5 Output of Descriptive Analytics Model -- 3.6 Output of Predictive Analytics Model -- 4 Techniques and Tools Used -- 5 Result -- 6 Conclusion -- References -- Intelligent Models for Mining Social Media Data -- 1 Introduction -- 2 Research Methods -- 2.1 Dataset -- 2.2 Pre-processing Approach -- 2.3 Learning Algorithms -- 2.4 Evaluation Metrics -- 3 Model Implementation and Results -- 4 Related Work -- 5 Conclusion -- References -- Cloud Computing and Networking -- Routing and Charging of Electric Vehicles: Survey -- 1 Introduction -- 2 Electric Vehicles Routing Problems -- 2.1 Related Works -- 3 Charging of Electric Vehicles -- 4 Conclusion and Future Work -- References -- A Parallel Genetic Algorithm for Solving the Vehicle Routing Problem with Drone Medication Delivery -- 1 Introduction -- 2 Related Literature -- 3 Problem Formulation -- 4 Proposed Approach -- 5 Experiments and Results -- 6 Conclusion and Perspectives -- References -- Review on Blockchain and Access Control Systems -- 1 Introduction -- 2 Methodology -- 3 Preliminaries -- 3.1 Blockchain -- 3.2 Blockchain Layers -- 3.3 Access Control Systems (ACS).; 4 Related Works -- 5 Discussion -- 6 Conclusion -- References -- Adoption of Docker Containers as an Infrastructure for Deploying Software Applications: A Review -- 1 Introduction -- 2 Motivation -- 2.1 Usage of Docker in the Practitioner -- 3 Research Method -- 3.1 Different Solutions/Observations and Studies for Docker -- 4 Docker Containers -- 4.1 Introduction to Docker Containers -- 4.2 Docker Container Architecture -- 4.3 Advantages of Docker Containers -- 4.4 Limitations of Docker Containers -- 4.5 Strategic Approaches to Overcome Docker Limitations -- 5 Docker and Other Corresponding Approaches -- 6 Docker Integration with Container Orchestration -- 7 Conclusion -- References -- Study of the Impact of the Profoundness of Tunnel in the Context of Transition from IPv4 to IPv6 at the Local, Regional, and National Levels -- 1 Introduction -- 2 Overview of Transition Methods -- 3 Related Works -- 4 Context of Study -- 5 Results and Analysis -- 5.1 End-to-End Delay -- 5.2 Variation in Delay -- 5.3 HTTP Response Time -- 6 Conclusion and Future Work -- References -- Artificial Intelligence II -- A Face-Mask Detection System Based on Deep Learning Convolutional Neural Networks -- 1 Introduction -- 2 Related Work -- 3 Proposed Approach -- 3.1 Face Detection and Localization Step -- 3.2 Applying Face-Mask Classifier -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Architectural Details -- 5 Results and Discussion -- 5.1 Results for the "Uni-FaceMask" Model -- 5.2 Results for the "Multi-FaceMask" Model -- 6 Conclusion -- ; References -- Deep Learning for COVID-19 Cases-Based XCR and Chest CT Images -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Research Questions -- 3.2 Dataset -- 3.3 Classification -- 4 Computational Results and Discussion -- 4.1 Experimental Settings -- 4.2 Experimental Datasets -- 4.3 Experimental Results.; 4.4 Results and Discussions.