Advanced soft computing techniques in data science, IoT and cloud computing

This book plays a significant role in improvising human life to a great extent. The new applications of soft computing can be regarded as an emerging field in computer science, automatic control engineering, medicine, biology application, natural environmental engineering, and pattern recognition. N...

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Bibliographic Details
Main Authors Dash, Sujata, Pani, Subhendu Kumar, Abraham, Ajith, Liang, Yulan
Format eBook Book
LanguageEnglish
Published Cham Springer 2021
Springer International Publishing AG
Springer International Publishing
Edition1
SeriesStudies in Big Data
Subjects
Big Data
Cloud computing
Computational Intelligence
Computer Science
Cyber-physical systems, IoT
Data Engineering
Engineering
Engineering > Data processing
Information technology
Internet of things
Soft computing
Online AccessGet full text
ISBN9783030756567
3030756564
ISSN2197-6503
2197-6511
DOI10.1007/978-3-030-75657-4

Cover

Table of Contents:
  • Intro -- Preface -- Acknowledgements -- Contents -- Editors and Contributors -- Abbreviations -- Soft Computing Techniques for IoT Devices -- A Wearable Assistive Device for Safe Travel Using Transfer Learning and IoT for Visually Impaired People -- 1 Introduction -- 2 Review of Literature -- 3 Overview of Proposed System -- 4 Proposed Methodology -- 4.1 Bus Board Detection for Route Information Extraction -- 4.2 Route Recognition -- 4.3 Text to Speech Conversion for Route Identification -- 4.4 An IOT Based Railway Platform Detection -- 4.5 Assistive Device for Visual Mobility and Safe Travel -- 5 Implementation and Results -- 6 Conclusion and Future Work -- References -- Soft Computing Techniques for Physical Layer Security of IoT Devices -- 1 Introduction -- 2 Machine Learning Algorithms for PLS in IoT -- 2.1 PLS Schemes Using K-Nearest Neighbor Algorithm -- 2.2 PLS Scheme Using Support Vector Machine -- 3 Deep Learning Algorithms for PLS in IoT -- 3.1 PLS Scheme Using Deep Neural Network Models -- 3.2 PLS Scheme Using Convolutional Neural Network Models -- 3.3 PLS Scheme Using Long Short-Term Memory Networks -- 3.4 PLS Schemes Based on Recurrent Neural Networks -- 4 Fuzzy Systems for Physical Layer Security for IoT -- 5 Genetic Algorithm for Physical Layer Security for IoT -- 6 Conclusions -- References -- Linear Congruence Generator and Chaos Based Encryption Key Generation for Medical Data Security in IoT Based Health Care System -- 1 Introduction -- 2 Literature Survey -- 3 Problem Domain -- 4 Our Contributions -- 5 Proposed Work -- 5.1 Session Key Generation -- 5.2 Intermediate Key Generation -- 5.3 Encryption Process -- 5.4 Generation of Authentication Code and Transmission File -- 5.5 Decryption Phase -- 6 Result and Discussion -- 6.1 Randomness Analysis of Key
  • 6.1 BMRI Image Segmentation Process -- 6.2 Feature Extraction -- 6.3 Feature Normalization -- 6.4 Data Distribution -- 6.5 Classification Result -- 6.6 Result Analysis -- 7 Conclusion and Future Scope -- References -- Automatic Localization of Optic Disc in Retinal Fundus Image Based on Unsupervised Learning -- 1 Introduction -- 2 Related Work -- 3 Clustering Methods -- 3.1 Agglomerative Clustering -- 3.2 K-Means Clustering -- 3.3 Fuzzy C Mean Clustering -- 3.4 DBSCAN Clustering -- 4 Methodology -- 4.1 Retinal Image Pre-processing -- 5 Results and Discussion -- 5.1 Dataset Description -- 5.2 Result Analysis -- 5.3 Optic Disc Detection -- 5.4 Performance Evaluation -- 5.5 Discussion -- 6 Conclusion -- References -- Soft Computing Techniques in Data Science -- Performance Evaluation of Hybrid Machine Learning Algorithms for Medical Image Classification -- 1 Introduction -- 2 Methodologies -- 2.1 Efficiency of SVM-RBF Kernels for Medical Image Classification -- 2.2 Feature Reduction using PCA -- 2.3 Hybrid Algorithm Based on PSO, GA with Local Search -- 2.4 Deep Learning -- 3 Discussion of Experimental Results -- 4 Conclusion -- References -- Computing Truth Values of Modus Ponens and Modus Tollens Rule for Linguistic Truth-Valued Propositions and Its Application in Taking Decisions in Health Care -- 1 Introduction -- 2 Basic Concepts -- 3 Reasoning with Linguistic Truth-Valued Propositions -- 3.1 Computation of Truth Values of Modus Ponens and Modus Tollens rules for LTVP -- 3.2 Computation of Truth Values of Modus Ponens and Modus Tollens rules for QLTVP -- 4 Output and Results -- 4.1 Examples -- 5 Conclusion -- References -- Analysis of Customers' Reviews Using Soft Computing Classification Algorithms: A Case Study of Amazon -- 1 Introduction -- 2 Literature Survey -- 3 Data Collection and Methodology -- 3.1 Data Collection and Preprocessing
  • 4.3 Dynamic Spatial RBAC Algorithm -- 5 Experimental Results -- 6 Summary -- References -- Analysis of Long Short Term Memory (LSTM) Networks in the Stateful and Stateless Mode for COVID-19 Impact Prediction -- 1 Introduction -- 2 Recurrent Neural Networks -- 2.1 From RNN to LSTM -- 3 LSTM Architecture -- 3.1 Various Gates in the LSTM Architecture -- 3.2 Stateful and Stateless LSTM -- 4 LSTM Research -- 5 COVID19-Prediction Problem -- 6 Defining Models in Keras -- 6.1 Five Step Lifecycle -- 7 LSTM State Management -- 8 Results and Conclusion -- 8.1 A Vanilla RNN -- 8.2 Stateful LSTM -- 8.3 Stateless LSTM Without Shuffling -- 8.4 Stateless with Shuffling -- References -- Soft Computing Techniques for Energy Consumption and Resource Aware Allocation on Cloud: A Progress and Systematic Review -- 1 Introduction -- 2 Motivation -- 3 Background -- 3.1 Framework for Energy Consumption and Resource Aware Allocation -- 3.2 Types of Soft Computing Techniques -- 3.3 Importance of Soft Computing Techniques for Energy Consumption -- 3.4 Research Challenges or Issues -- 3.5 Application Areas -- 4 Reported Work -- 4.1 Soft Computing Techniques for Energy Consumption -- 4.2 Resource Allocation -- 5 Comparative Analysis of Soft Computing Techniques for Energy Consumption and Resource Aware Allocations -- 6 Conclusion -- References -- Automatic Segmentation and Classification of Brain Tumor from MR Images Using DWT-RBFNN -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Magnetic Resonance Imaging (MRI) -- 3.2 MRI Database -- 3.3 Wavelet Transform (WT) -- 3.4 DWT Image Filtering -- 4 Preprocessing of MRI Data -- 4.1 Resizing of MRI Images -- 4.2 Image Denoising Using MRDWT-ICA -- 4.3 Tumor Segmentation -- 4.4 Otsu's Thresholding -- 5 RBFNN Classifier -- 5.1 Performance Evaluation Assessment Metrics (PEAM) -- 6 Experimental Result and Discussion
  • 6.2 Comparative Analysis Between Modified Logistic Map and Standard Logistic Map -- 6.3 Statistical Analysis -- 6.4 Key Sensitivity Analysis -- 6.5 Security Analysis -- 6.6 Functionality Analysis of Encryption Technique -- 6.7 Significance of Authentication in Our Proposed Scheme -- 7 Conclusion -- References -- Content Based Video Retrieval-Methods, Techniques and Applications -- 1 Introduction -- 2 State-of-the-Art Techniques -- 3 Content Based Video Retrieval (CBVR) -- 3.1 Keyframe Extraction -- 3.2 Feature Vectors for CBVR -- 3.3 The Proposed Method -- 3.4 Performance Analysis -- 4 Applications -- 5 Conclusion -- References -- Building the World of Internet of Things -- 1 Introduction: The Information Revolution -- 2 Sensors -- 3 Networks -- 4 Augmented Intelligence -- 5 Augmented Behavior -- 6 Standards -- 7 Conclusion -- References -- Applicability of Machine Learning Algorithms for Intelligent Farming -- 1 Introduction -- 2 Literature Review -- 3 Data Analysis and Its Techniques Used in Machine Learning -- 3.1 Feature Selection -- 4 Background Statistics of ML Algorithms -- 4.1 Chi-Square Statistics -- 4.2 Euclidean Distance -- 5 Classification Algorithms Used -- 5.1 K-Nearest Neighbor's -- 5.2 Support-Vector Machine (SVM) -- 5.3 Logistic Regression -- 5.4 Decision Trees -- 6 Implementation -- 6.1 Gathering Data -- 6.2 Analyzing Gathered Data -- 6.3 Results -- 6.4 Integrating IoT and ML for Intelligent Farming-A Future Approach -- 7 Conclusion and Future Scope -- References -- Soft Computing Techniques in Cloud Computing and Computer Networking -- Hybrid Cloud Data Protection Using Machine Learning Approach -- 1 Introduction -- 2 Problem Statement -- 3 De-duplication -- 4 Cloud Security Protection Framework with Machine Learning Modules -- 4.1 Cloud Client Classification Using Enhanced C4.5 Algorithm -- 4.2 De-duplication Processing Algorithm
  • Role of Artificial Intelligence in COVID-19 Pandemic
  • 3.2 Data Representation -- 3.3 Classifications -- 4 Experimental Results and Discussions -- 5 Conclusions -- References -- Pattern Mining-FTISPAM Using Hybrid Genetic Algorithm -- 1 Introduction -- 2 Fuzzy Time-Interval Sequential Patterns Using Hybrid Genetic Algorithm -- 3 Overview of the FTISPAM-HGA -- 4 Fuzzy Time Interval Sequential Pattern Mining -- 5 Hybrid Genetic Algorithm -- 6 Fuzzy Time Interval Sequential Pattern Mining Using HGA Algorithm -- 7 Patterns Matching Using SCI -- 8 Significant Pattern Evaluation -- 9 Experimental Results and Discussion -- 10 Conclusion -- References -- Soft Computing Techniques for Medical Diagnosis, Prognosis and Treatment -- 1 Introduction -- 1.1 Healthcare Data -- 1.2 Types of AI in Healthcare -- 2 Intelligent Systems for Healthcare Decisions -- 2.1 Virtual Assistants in Drug Development -- 2.2 Intelligent Medical Devices -- 2.3 Ambient Healthcare Monitoring System -- 3 Use Cases of Soft Computing in Basic Sciences and Diagnostics -- 3.1 Soft Computing in Basic Sciences -- 3.2 Soft Computing in Medical Diagnosis -- 4 Soft Computing Techniques in Healthcare Decision Systems -- 4.1 Artificial Neural Networks -- 4.2 Fuzzy Logic -- 4.3 Genetic Algorithms -- 5 Further Applications of Soft Computing in Healthcare Decision Making -- 5.1 Fuzzy Logic in Remote Healthcare Monitoring -- 5.2 Risk Assessment of Cervical Cancer in Women-Based on Convolutional Neural Network -- 5.3 Diagnosis of Depression Using Neuro-fuzzy Model of Soft Computing -- 6 Hybrid Techniques Used in Healthcare -- 6.1 Hybrid Solution for Skin Cancer Detection -- 7 Soft Computing in Clinical Applications -- 7.1 Soft Computing in Cardiology -- 7.2 Soft Computing in Neurology -- 7.3 Soft Computing in Medicine and Rehabilitation -- 7.4 Soft Computing in Other Clinical Areas -- 8 Conclusion -- References