Mobile computing and sustainable informatics : proceedings of ICMCSI 2022 / / edited by Subarna Shakya, Klimis Ntalianis, Khaled A. Kamel

• Record Nr.: UNINA9910584482603321
• Pubbl/distr/stampa: Singapore : , : Springer, , [2022]; ©2022
• ISBN: 981-19-2069-9
• Descrizione fisica: 1 online resource (939 pages)
• Collana: Lecture Notes on Data Engineering and Communications Technologies ; ; v.126
• Disciplina: 004
• Soggetti: Computational intelligence
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- Preface -- Acknowledgments -- Contents -- About the Editors -- XGBoost Design by Multi-verse Optimiser: An Application for Network Intrusion Detection -- 1 Introduction -- 2 Background and Related Work -- 2.1 On the Problem of Intrusion Detection -- 2.2 Machine Learning-Supported Intrusion Detection Systems -- 2.3 Swarm Intelligence -- 3 Methodology -- 3.1 The Multi-verse Optimisation Algorithm -- 3.2 The XGBoost Optimiser -- 3.3 Proposed MVO-XGBoost Framework -- 4 Experimental Setup, Analysis, and Discussion -- 4.1 Experimental Setup -- 4.2 Comparative Analysis and Discussion -- 5 Conclusion -- References -- Gateway-Based Congestion Avoidance Using Two-Hop Node in Wireless Sensor Networks -- 1 Introduction -- 2 Related Work -- 3 Problem Statement -- 4 Proposed Work -- 4.1 Network Model -- 4.2 Gateway-Based Congestion Avoidance (GCA) Mechanism -- 4.3 Congestion Notification -- 4.4 Congestion Avoidance -- 5 Results and Discussion -- 5.1 Performance Metrics -- 6 Conclusion -- References -- Stroke Prediction System Using Machine Learning Algorithm -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Preparation -- 3.2 Data Preprocessing -- 3.3 Feature Selection and Visualization -- 3.4 Model Architecture -- 4 Experimental Results -- 5 Conclusion -- References -- A Comprehensive Survey on Multilingual Opinion Mining -- 1 Introduction -- 2 Opinion Mining of Code-Mix Languages -- 3 Opinion ; Mining Process -- 3.1 Data Extraction -- 3.2 Annotation -- 3.3 Pre-processing -- 3.4 Data Vectorization -- 4 Classification Techniques -- 4.1 Machine Learning Approach -- 4.2 Deep Learning-Based Approach -- 4.3 Lexicon-Based Approach -- 4.4 Hybrid Approach -- 5 Evaluation Parameters -- 6 Conclusion -- References -- Development Features and Principles of Blockchain Technologies and Real Options as the Main Components of the Digital Economy.; 1 Introduction -- 2 Analysis of Recent Research and Publications -- 3 Statement of the Main Research Material -- 3.1 Main Mechanisms for the Blockchain Technology Implementation -- 4 Blockchain Technology and Problems of its Implementation -- 5 System Analysis of Blockchain Technology Contradictions -- 6 Analysis of Real Options as the Most Flexible Financial Tool of Digital Economy -- 7 Classification of Option Contracts -- 8 Option Pricing Analysis -- 9 Conclusions -- References -- Technical Efficiency Analysis of China's Telecommunication Infrastructure: A Copula-Based Meta-Stochastic Frontier Model -- 1 Introduction -- 2 The Conceptual Framework and Methodology -- 2.1 The Conceptual Framework -- 2.2 Copulas and Dependence -- 2.3 Copula-Based Meta-Stochastic Frontier Model (CMSFM) for Technical Efficiency Computational -- 3 The Empirical Study and Simulation Study -- 3.1 Descriptive Statistics for All Variables in the Copula-Based Meta-Stochastic Frontier Model (CMSFM) -- 3.2 Copula-Based Stochastic Frontier Model (CSFM) -- 3.3 Copula-Based Meta-Stochastic Frontier Model (CMSFM) -- 4 Conclusion and Recommendation -- Appendix A.1: (The Simulation Study of the Copulas Model for the Copula-Based Meta-Stochastic Frontier Model (CSFM)) -- Appendix A.2 (The Figure of Simulation Study for Uit and Vit Using in the Copula-Based Meta-Stochastic Frontier Model (CSFM))) -- References -- ATM Security Using Iris Recognition -- 1 Introduction -- 2 Related Works -- 3 Existing System -- 4 Proposed System -- 4.1 Block Diagram -- 4.2 Arduino UNO -- 4.3 LCD Display -- 4.4 Arduino Ide -- 4.5 Embedded C -- 4.6 MATLAB -- 5 Results and Discussion -- 5.1 Experimental Setup -- 6 Conclusion and Future Enhancements -- References -- Reliable Data Acquisition by Master-Slave Approach in Marine-IoT Environment for Logistics -- 1 Introduction -- 2 Literature Survey.; 3 Proposed Methodology -- 3.1 Simulation Parameters-Packet Delivery Ratio -- 3.2 Automatic Identification System (AIS) -- 3.3 Dynamic Information -- 3.4 Maritime Mobile Service Identity Number (MMSI) -- 3.5 Static and Voyage-Related Information -- 3.6 K-Means Clustering -- 4 Result and Discussions -- 5 Conclusion -- References -- Mobile Technology Acceptance of University Students: A Consolidated Approach -- 1 Introduction -- 2 Theoretical and Conceptual Frameworks -- 2.1 Uses and Gratifications Theory -- 2.2 Technology Acceptance Model -- 2.3 The Study Framework -- 3 Methodology -- 4 Findings -- 4.1 Technological and Socio-Situational Factors -- 4.2 Independent and Moderator Roles of Individual Variables -- 5 Discussion -- 6 Conclusion -- References -- Multistage Intrusion Detection System using Machine Learning Algorithm -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Pre-processing -- 3.2 Feature Selection using Decision Tree Classifier -- 3.3 Hyperparameter Optimization -- 3.4 Predict GRU -- 4 Results and Analysis -- 4.1 Pre-processing -- 4.2 Feature Selection -- 4.3 Hyperparameter Optimization -- 4.4 Prediction -- 4.5 Performance Metrics -- 5 Conclusion and Future Work -- References -- Modeling Global Solar Radiation Using Machine Learning with Model Selection Approach: A Case Study in Tanzania -- 1 Introduction -- 2 Related Research -- 3 Dataset and Methods -- 3.1 Solar Radiation Data -- 3.2 ; Machine Learning-Assisted Prediction Model -- 3.3 Computational Framework -- 4 Computational Experiments, Analysis and Discussion -- 5 Conclusion -- References -- Plant Disease Detection Using Transfer Learning with DL Model -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Data Collection -- 3.2 Data Collection -- 3.3 Training Dataset -- 3.4 Applied Model -- 4 Result -- 4.1 10 Fold Cross-Validation Analysis.; 4.2 Confusion Matrix Analysis -- 5 Conclusion -- References -- Tagging Fake Profiles in Twitter Using Machine Learning Approach -- 1 Introduction -- 1.1 Motivation -- 1.2 Twitter's Viewpoint on Fake Profiles -- 2 Literature Survey -- 3 Problem Formulation -- 3.1 Gaps in the Existing Literature -- 3.2 Problem Statement -- 4 Proposed Solution -- 4.1 Data Collection -- 4.2 Feature Selection -- 4.3 Classification of Twitter Users -- 5 Results and Analysis -- 5.1 Results -- 5.2 Validation of the Proposed Approach -- 6 Conclusion -- References -- A Machine Learning System to Classify Cybercrime -- 1 Introduction -- 2 Proposed System Design and Methodology -- 2.1 System Design -- 2.2 Module Description -- 3 System Implementation -- 3.1 Python -- 3.2 Django -- 4 Experimental Results and Discussion -- 5 Conclusion and Future Work -- References -- Analyses of Non-linear Effects with DCS and HOA Performance for 4 X 4 WDM/DWDM System -- 1 Introduction -- 1.1 Optical Amplifiers -- 1.2 Single-mode Fiber (SMF) -- 2 Results and Discussion -- 3 Conclusion and Further Study -- References -- User Profiling and Influence Maximization -- 1 Introduction -- 2 Influence Maximization -- 3 IM Approaches Evolution -- 4 IM Over Big Data Era -- 5 Problem Formulation -- 6 Profiling Influencers Application -- 7 Conclusion -- References -- An Efficient IoT-Based Novel Design for Home Automation Using Node MCU Controller -- 1 Introduction -- 2 Existing Systems -- 2.1 Sensor Basically Primarily House Automation and Safety System -- 2.2 I-Learning IoT -- 2.3 Java-Based Dwelling Automation System -- 2.4 Zigbee-Based Residence Automation Manner Utilizing Cell Phones -- 3 Literature Survey -- 4 Architecture Block Diagram -- 5 Software Tools -- 5.1 IFTTT (Google Assistant) -- 5.2 MQTT (AdaFruit) -- 6 Flow Chart of Proposed System -- 7 Circuit Diagram -- 8 Hardware Implementation.; 9 Results and Discussions -- 10 Conclusion -- References -- A Supervised Machine Learning Approach for Analysis and Prediction of Water Quality -- 1 Introduction -- 1.1 Water Quality Index -- 2 Study Area -- 3 Related Work -- 4 Methodology -- 4.1 Data Preprocessing -- 4.2 Calculation of Water Quality Index -- 4.3 Water Quality Class (WQC) Classification -- 4.4 Machine Learning -- 5 Results and Discussions -- 5.1 Classification -- 5.2 Regression -- 6 Conclusion -- References -- Artificial Neural Network Established Hexagonal Ring- MPA Intended for Wideband Application -- 1 Introduction -- 2 Design of Presented Antenna and Data Generation -- 3 Design Procedure of ANN Modeling for HRMPA -- 4 Results and Discussions -- 5 Conclusion -- References -- EEGs Signals Artifact Rejection Algorithm by Signal Statistics and Independent Components Modification -- 1 Introduction -- 2 Related Works -- 3 Methods and Background on EEG Signals and Artifacts -- 3.1 Ocular Artifact -- 3.2 Muscle Artifacts -- 3.3 Cardiac Artifact -- 3.4 Other Artifacts and Artifact Handling -- 3.5 Independent Component Analysis (ICA) -- 4 The Proposed Algorithm -- 4.1 Using Average Reference Montage -- 4.2 EEG Signal Filtering -- 4.3 Applying ICA to EEG Signal -- 4.4 Artifact Identification and Cancelation -- 4.5 Restoring EEG Signal from ICA Components -- 5 Results -- 6 Conclusion -- References -- IoT-Based Air Quality Monitoring System Using SIM900 -- 1 ; Introduction -- 2 Review of Literature -- 3 Design Process -- 3.1 NodeMCU -- 3.2 DTH11 Sensor -- 3.3 MQ 135 Sensor -- 3.4 GSM SİM900A -- 3.5 Blynk Application -- 4 System Architecture and Implementation -- 5 Results and Conclusions -- References -- Predictive Modeling for Risk Identification in Share Market Trading-A Multiphase Approach -- 1 Introduction -- 1.1 Challenges in Predictive Analytics -- 2 Predictive Analytics.; 2.1 Data Mining Versus Predictive Analytics.