12558nam 22007695 450 991087898040332120240803130436.09789819735235(electronic bk.)978981973522810.1007/978-981-97-3523-5(MiAaPQ)EBC31579742(Au-PeEL)EBL31579742(CKB)33645673300041(DE-He213)978-981-97-3523-5(EXLCZ)993364567330004120240803d2024 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierAdvances in Distributed Computing and Machine Learning Proceedings of ICADCML 2024, Volume 2 /edited by Umakanta Nanda, Asis Kumar Tripathy, Jyoti Prakash Sahoo, Mahasweta Sarkar, Kuan-Ching Li1st ed. 2024.Singapore :Springer Nature Singapore :Imprint: Springer,2024.1 online resource (482 pages)Lecture Notes in Networks and Systems,2367-3389 ;1015Print version: Nanda, Umakanta Advances in Distributed Computing and Machine Learning Singapore : Springer,c2024 9789819735228 Intro -- Preface -- Contents -- Editors and Contributors -- OSNR Monitoring for QPSK and QAM in Fiber-Optic Networks Using Machine Learning -- 1 Introduction -- 2 Proposed Method -- 3 Support Vector Machine Algorithms -- 4 Simulation Results and Discussion -- 5 Conclusion and Future Research -- References -- Classification of Star and Galaxy Objects Utilizing Machine Learning Techniques and Deep Neural Networks -- 1 Introduction -- 2 Dataset -- 2.1 Processing Data -- 3 Machine Learning Approach for Star Versus Galaxy Classification -- 4 Convolutional Neural Networks-(CNN) -- 4.1 Convolutional Layers -- 4.2 Implementation Details -- 5 Result and Analysis -- 6 Conclusion -- References -- Probabilistic Forecasting Analysis on Electric Load Systems -- 1 Introduction -- 2 Review of Literature -- 3 Description of the Model -- 4 Sources of Data Generation -- 5 Computational Analysis and Results -- 5.1 Representation of ELG Units -- 5.2 Correlation Analysis -- 5.3 Bivariate Normal Distribution -- 5.4 Linear Regression and ARIMA Models -- 5.5 Electricity Consumption Charges -- 6 Conclusion -- References -- Smart City Survey on AIoT Using Machine Learning, Deep Learning, and Its Computing Tools -- 1 Introduction -- 2 IoT-Oriented Perspective -- 2.1 Smart Infrastructure -- 2.2 Air Management -- 2.3 Traffic Management -- 2.4 Waste Management -- 3 ML-Orient Perspective -- 3.1 Infrastructure -- 3.2 Air Management -- 3.3 Traffic Analysis -- 3.4 Waste Management -- 4 Deep Learning-Oriented Perspective -- 4.1 Supervised Learning -- 4.2 Unsupervised Learning -- 4.3 Reinforcement Learning -- 5 Computing Tools for Smart City -- 5.1 Cloud Computing -- 5.2 Fog Computing -- 5.3 Edge Computing -- 6 Conclusion -- References -- Energy Harvesting Integrated Sensor Node Architecture for Sustainable IoT Networks -- 1 Introduction -- 1.1 Contributions Made in This Research.2 Literature Study on Energy Harvesting -- 3 System Architecture -- 3.1 Hardware Requirements -- 3.2 Circuit Implementation -- 3.3 Energy Source: The PV Cell -- 3.4 Energy Storage Structures -- 3.5 Power Management Protocols -- 4 Lifetime Evaluation with Solar Energy Harvester -- 4.1 System Implementation and Analysis -- 5 Conclusion -- References -- Enhancing Real Estate Price Prediction in Smart Cities: A Comparative Analysis of Machine Learning Techniques -- 1 Introduction -- 2 Related Work -- 3 Limitation -- 4 Methodology -- 4.1 Feature Engineering -- 4.2 Model Description and Predicting the Value -- 5 Results -- 6 Conclusion -- 7 Future Work -- References -- Real-Time AI-Based Face-Mask Detection -- 1 Introduction -- 2 Proposed Design Approach -- 2.1 Custom Dataset Gathering -- 2.2 Data Augmentation for Best Results -- 2.3 Training Model -- 3 Methodology -- 3.1 YOLO Algorithm -- 3.2 MobileNetV2 -- 4 Results and Discussion -- 5 Conclusion -- References -- A Logical Model for Multiple People Activity Recognition Using Non-intrusive Sensors for Geriatric Care -- 1 Introduction -- 2 Related Work -- 3 Problem Scenario -- 4 Logical FHMM for Multiple People Activity Recognition -- 4.1 Solution Overview -- 5 Experiments -- 5.1 Experimental Setup -- 6 Conclusion -- References -- From Sea to Table: A Blockchain-Enabled Framework for Transparent and Sustainable Seafood Supply Chains -- 1 Introduction -- 2 Related Work -- 3 Seafood Supply Chain and Blockchain -- 4 Conceptual Blueprint -- 4.1 The Flow of Code Implementation -- 5 Result -- 6 Discussion -- 7 Conclusion and Future Scope -- References -- Distributed State Estimation for GPS Navigation: The Correntropy Extended Kalman Filter Approach -- 1 Introduction -- 2 Literature Study -- 3 Correntropy Extended Kalman Filter -- 4 Results and Discussion -- 5 Conclusion -- References.Nayantara: Crime Analysis from CCTV Footage Using MobileNet-V2 and Transfer Learning -- 1 Introduction -- 2 Related Works -- 3 Proposed Methodology -- 3.1 System Architecture -- 3.2 Detection Model -- 3.3 Web Application -- 4 Experiments and Results -- 4.1 Dataset -- 4.2 Data Preprocessing -- 4.3 Working of the Detection Algorithm -- 4.4 CNN Model -- 4.5 Results -- 5 Conclusion -- References -- Bird Detection in Microlight Aircraft Strip Using YOLOv8for Adventure Tourism -- 1 Introduction -- 2 Bigdata Analytics Unlocks for Tourism Industry -- 2.1 Why is Microlight Aircraft Safety Important? -- 3 Literature Review -- 4 Implementation and Discussion -- 4.1 Methodology Used -- 4.2 Dataset Used -- 5 Performance Analysis and Results -- 6 Conclusion -- References -- A Graphical Tuning Method-Based Robust PID Controller for Twin-Rotor MIMO System with Loop Shaping Technique -- 1 Introduction -- 2 Preliminaries -- 2.1 Description of Twin-Rotor MIMO System -- 2.2 Design of Decouplers -- 2.3 FOPDT Model -- 3 upper H Subscript normal infinityHinfty Controller -- 4 Results an Discussions -- 5 Conclusion -- References -- Signature Verification Using Deep Learning: An Empirical Study -- 1 Introduction -- 2 Proposed Method -- 2.1 Data Acquisition -- 2.2 Pre-processing -- 2.3 Feature Extraction -- 2.4 Model and Algorithm Hyperparameters -- 2.5 Optimizing Algorithm -- 2.6 Batch Normalization and Dropout -- 3 Results -- 3.1 Performance Stats -- 3.2 Evaluation Metrics -- 4 Discussion -- 5 Conclusion -- References -- An Intelligent and Automated Machine Learning-Based Approach for Heart Disease Prediction and Personalized Care -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset Description -- 3.2 Data Pre-processing -- 3.3 Handling Imbalanced Classes -- 3.4 Data Normalization -- 3.5 Feature Relevance Analysis -- 4 Results and Discussion.4.1 Comparative Analysis -- 5 Conclusion -- References -- Parkinson's Disease Diagnosis Through Deep Learning: A Novel LSTM-Based Approach for Freezing of Gait Detection -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Data Pre-processing -- 3.3 LSTM Architecture -- 4 Results and Discussion -- 4.1 Comparative Analysis -- 5 Conclusion -- References -- Polarity Detection of Online News Articles Using Deep Learning Techniques -- 1 Introduction -- 1.1 Deep Learning and Polarity Detection -- 2 Literature Survey -- 2.1 RNN with GRU -- 2.2 RNN with LSTM -- 2.3 Bidirectional RNN -- 2.4 CNN -- 2.5 Dynamic Dictionaries -- 3 Proposed Method -- 4 Experiment and Result Discussion -- 5 Conclusion and Future Work -- References -- Harnessing ResNet50 and EfficientNetB5 for Detection of Diabetic Retinopathy Using Explainable AI -- 1 Introduction -- 2 Literature Survey -- 3 Methodology -- 4 Results -- 4.1 Model Performance -- 4.2 Interpretation of Result -- 4.3 Model Explainability -- 5 Conclusion -- References -- A Grey Wolf and Rough Set Hybrid Approach for the Detection of Chronic Kidney Disease -- 1 Introduction -- 2 Schematic Representation of Proposed Research -- 3 Experimental Research on Chronic Kidney Disease -- 4 Result Analysis -- 4.1 Proposed GWRSO Data Analysis -- 5 Conclusion -- References -- Efficient Rice Disease Classification Using Intelligent Techniques -- 1 Introduction -- 2 Methodology -- 3 Data Description -- 3.1 Bacterial Leaf Blight -- 3.2 Brown Spot -- 3.3 Blast -- 3.4 Tungro -- 4 Experimental Setup and Performance Analysis -- 5 Conclusion -- References -- Maize Crop Yield Prediction Using Machine Learning Regression Approach -- 1 Introduction -- 2 Methodology -- 2.1 Dataset -- 2.2 Data Preprocessing -- 2.3 Feature Selection -- 2.4 Data Transformation -- 2.5 Model Building Algorithms -- 2.6 Evaluation Metrics.3 Experiment and Results -- 3.1 Model Building, Training, and Testing -- 3.2 Dimension Reduction Using Principal Component Analysis (PCA) -- 3.3 Comparison of the Results -- 3.4 Identification of Main Features -- 3.5 Discussion of the Findings -- 4 Conclusion -- References -- Mode Division Multiplexing-Based Passive Optical Networks for High-Capacity Data Rate via Radio Over Fiber Technology -- 1 Introduction -- 2 Proposed Mode Division Multiplexing Passive Optical Network -- 3 Mode Division Multiplexing Layout Simulation by Using OptiSystemV20 -- 4 Simulation Design of MDM with QAM and DSPK -- 5 Simulation Design of MDM for Noise Removal Systems -- 6 Result and Discussion -- 7 Conclusion -- References -- Enhancing Urban Connectivity: Free Space Optics as a Resilient Backup Link for Fiber Networks in Urban Environments -- 1 Introduction -- 2 Proposed Block Diagram of FSO-NRZ System Model -- 3 Result and Discussion -- 4 Conclusion -- References -- Integrating ANSYS Simulation and Machine Learning Techniques for Thermo-Mechanical Analysis of PCBs -- 1 Introduction -- 2 Problem Statement and Methodology -- 3 Results and Discussions -- 4 Conclusions -- References -- Automation of Quality Assessment Procedures in School Education -- 1 Introduction -- 2 Software Tool for Quality Evaluation: Design and Software Prototype Development -- 3 Experiments -- 4 Conclusions -- References -- The FGSM Attack on Image Classification Models and Distillation as Its Defense -- 1 Introduction -- 2 Related Work -- 3 Theoretical Background -- 4 Results of the FGSM Attack -- 4.1 The Classification Results in the Absence of the FGSM Attack -- 4.2 The Classification Results in the Presence of the FGSM Attack -- 5 Distillation for Defense Against the FGSM Attack -- 6 Conclusion -- References -- An Experimentation of Firefly Algorithm Using a Different Set of Objective Functions.1 Introduction.This book is a collection of peer-reviewed best selected research papers presented at the Fifth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2024), organized by School of Electronics and Engineering, VIT-AP University, Amaravati, Andhra Pradesh, India, during 5–6 January 2024. This book presents recent innovations in the field of scalable distributed systems in addition to cutting edge research in the field of Internet of Things (IoT) and blockchain in distributed environments.Lecture Notes in Networks and Systems,2367-3389 ;1015Computational intelligenceArtificial intelligenceMachine learningBlockchains (Databases)Internet of thingsComputational IntelligenceArtificial IntelligenceMachine LearningBlockchainInternet of ThingsComputational intelligence.Artificial intelligence.Machine learning.Blockchains (Databases).Internet of things.Computational Intelligence.Artificial Intelligence.Machine Learning.Blockchain.Internet of Things.004.36Nanda Umakanta1742711Tripathy Asis Kumar1372576Sahoo Jyoti Prakash1372577Sarkar Mahasweta1742712Li Kuan-Ching1078909MiAaPQMiAaPQMiAaPQ9910878980403321Advances in Distributed Computing and Machine Learning4169410UNINA05391nam 2201369z- 450 991055769920332120220111(CKB)5400000000044565(oapen)https://directory.doabooks.org/handle/20.500.12854/77036(oapen)doab77036(EXLCZ)99540000000004456520202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierEvolutionary Computation 2020Basel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online resource (442 p.)3-0365-2394-4 3-0365-2395-2 Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms.Technology: general issuesbicssc0-1 knapsack problemant colony optimizationassortative matingbinary whale optimization algorithmbug detectionbWOA-SbWOA-Vcitationclassificationcoevolutionconstrained optimizationcuckoo search algorithmdecomposition-based multi-objective optimisationdifferential evolutiondimensionality reductiondiscrete artificial bee colony algorithmdiversity preservationdominancedynamic learningelephant herding optimizationengineering optimizationevolutionary algorithmevolutionary algorithms (EAs)evolutionary computationfeature selectionfuzzingfuzzy hybrid flow shop schedulinggame featuregame simulationgame treesgeoelectric modelglobal optimizationgreen shop schedulinggrey wolf optimizerh-indexiterated local searchknapsack problemknowledge transferkrill herdmagnetotelluricmany-objective optimizationmemetic algorithmmenu planning problemmetaheuristicminimize makespanminimize total energy consumptionmulti-indicatorsmulti-metricmulti-objective optimizationmulti-resourcesmulti-task evolutionary computationmulti-task optimizationmutationone-dimensional inversionsopposite pathopposition-based learningoptimization problemPareto optimalityPareto-frontparticle swarm optimizationpath discoveryperformance indicatorsplaytestingplaytesting metricpremature convergenceQ-learningquantumquantum computingrankingseed scheduleself-adaptive step sizesimulated annealingsingle objective optimizationsingle-objective optimizationsuccess-historyswarm intelligencetraveling salesman problemstravelling salesman problemturning-based mutationunified search spaceuniversities rankingvalidationwhale optimization algorithmWOATechnology: general issuesWang Gai-Geedt1322388Alavi AmiredtWang Gai-GeothAlavi AmirothBOOK9910557699203321Evolutionary Computation 20203034943UNINA