This book discusses automated computing systems which are mostly powered by intelligent technologies like artificial intelligence, machine learning, image recognition, speech processing, cloud computing, etc., to perform complex automated tasks which are not possible by traditional computing systems. The chapters are extended version of research works presented at second PhD Research Symposium in various advanced technologies used in the field of computer science. This book provides an opportunity for the researchers to get ideas regarding the ongoing works that help them in formulating problems of their interest. The academicians can also be benefited to know about the current research trends that smooth the way to guide their students to carry out research work in the proper direction. The industry people will be also facilitated to know about the current advances in research work and materialize the research work into industrial applications.
Author(s): Satya Ranjan Dash, Himansu Das, Kuan-Ching Li, Esau Villatoro Tello
Series: Studies in Computational Intelligence
Publisher: Springer
Year: 2023
Language: English
Pages: 260
Preface
Contents
Editors and Contributors
Clinical Decision Support System for Diagnosis and Treatment of COPD Using Ensemble Methods
1 Introduction
1.1 COPD Symptoms
1.2 Clinical Decision Support System (CDSS)
2 Problem Statement
3 Literature Survey
4 Objectives of the Proposed Research
5 Methodology Followed
5.1 Architecture for Constructing CDSS for COPD
6 Outcome of the Proposed Research
6.1 Objective 1
6.2 Experimental Results of Objective 1
6.3 Objective 2
6.4 Experimental Results of Objective 2
6.5 Objective 3
6.6 Experimental Results of Objective 3
6.7 Objective 4
6.8 Experimental Results of Objective 4
6.9 Objective 5
7 Conclusion
References
Designing of Fault-Tolerant Models for Wireless Sensor Network-Assisted Smart City Applications
1 Introduction
1.1 Chapter Background
2 Overview
2.1 Fault in WSN
3 Chapter-wise Work
3.1 Energy Balanced Cluster Formation for Uniform Load Distribution
3.2 Partitioned-Based Energy-Efficient LEACH
3.3 Uniform Energy Clustering and Population-Based Clustering
3.4 Applications of Smart Cities: Case Study
4 Conclusion
References
Test Scenarios Generation and Optimization of Object-Oriented Models Using Meta-Heuristic Algorithms
1 Introduction
2 Literature Review
3 Generation of Test Scenarios Using Combined Object-Oriented Models
3.1 Process of Test Scenarios Generation
3.2 Results and Discussions
4 Test Scenarios Optimization Using Fractional-SMO in Object-Oriented Systems
4.1 Proposed Approach
4.2 Results and Relative Study
4.3 Comparative Assessment Using User Login System Case Study
5 SMPSO: Spider Monkey Particle Swarm Optimization for Optimal Test Case Generation in Object-Oriented System
5.1 Proposed Approach (SMPSO)
5.2 Proposed SMPSO
5.3 Results and Comparative Analysis
5.4 Competing Techniques
5.5 Analysis Based on the Case Study of the Online-Trading System
5.6 Comparative Discussion
6 Conclusion and Future Work
6.1 Generation of Test Scenarios Using Combined Object-Oriented Models
6.2 Test Scenarios Optimization Using Fractional-SMO in Object-Oriented Systems
6.3 Spider Monkey Particle Swarm Optimization for Optimal Test Case Generation in OO System
6.4 Future Scope
References
Logical Interpretation of Omissive Implicature
1 Introduction
1.1 Problem Statement and Hypothesis
2 Theoretical Basis
2.1 Implicature
2.2 Answer Set Programming
3 Definitions and Methodology
3.1 Definitions
3.2 Methodology
4 Experimental Environments
4.1 The Testimonials of Logical-Linguistic Puzzles
4.2 Dialogical Interactions
5 Results
6 Conclusions
7 Derived Publications
8 Code for Criminal Puzzle (Clingo 4.5.4)
9 Prototype for Program Update in Logic (Python 3.7)
References
Loss Allocation Techniques in Active Power Distribution Systems
1 Introduction
2 Loss Allocation Analysis with Method-1 With/Without DGs
2.1 Methodology
3 Analysis of Loss Allocation with Respect to Load/DG Power Factor Variation
4 Analysis of Loss Allocation with Different Load Modeling
5 Analysis of Loss Allocation with Network Reconfiguration
6 Conclusion and Future Scope
References
Detection of Brain Abnormalities from Spontaneous Electroencephalography Using Spiking Neural Network
1 Introduction
2 Epileptic Seizure Detection Using Traditional ML and Convolution Neural Network Methods
2.1 Dataset
2.2 Approaches
2.3 Implementation and Result of Traditional and Deep Machine Learning Approaches to Classify EEG Signals
3 Schizophrenia Detection from EEG Signals Using Probability Spiking Neural Network
3.1 Data Set
3.2 Approach
3.3 Result of Implementation of Probability Spiking Neural Network on EEG Signals of Schizophrenia Patients
4 Depression Psychosis Detection from EEG Signals Using Fuzzy-Based NeuCube Spiking Neural Network
4.1 Dataset
4.2 Approach
4.3 Result from Analysis and Discussion on the Implementation of NeuCube Spiking Neural Network on Depression Dataset
5 Comparative Analysis of Three Experiments
6 Summary and Future Scope
References
QOS Enhanced Energy Aware Task Scheduling Models in Cloud Computing
1 Introduction
2 Literature Review
3 Problem Statement
4 Objectives
5 Methodology
5.1 Energy Aware Multi-objective Genetic Algorithm for Task Scheduling in Cloud Computing
5.2 Optimized Resource Scheduling Using the Meta-Heuristic Algorithm in Cloud Computing
5.3 An Optimized Resource Allocation Model Using Ant Colony Auction-Based Method for Cloud Computing
5.4 Multi-objective Dynamic Resource Scheduling Model for User Tasks in the Cloud Computing
6 Results and Discussion
7 Conclusion
References
Power Quality Improvement Using Hybrid Filters Based on Artificial Intelligent Techniques
1 Introduction
2 Power Quality Improvement Using Hybrid Filters in PV Integrated Power System
2.1 Case Study: PQ Improvement in Three Phase System Using PV Integrated Conventional VSI Based Series HAPF Designed by Robust Extended Complex Kalman Filter (RECKF) and Perturb and Observe Fuzzy (PO-F)
2.2 System Configuration and Modelling
2.3 Control Strategies for PV Integrated HAPF
2.4 Results Analysis of the Case Study
3 Artificial Intelligent Methods for PQ Improvement in DC Microgrid Integrated Power System
3.1 Case Study: PQ Improvement in Three Phase System Using PV Integrated Conventional VSI Based Series HAPF Designed by Robust Extended Complex Kalman Filter (RECKF) and Perturb and Observe Fuzzy (PO-F)
3.2 System Configuration and Modelling
3.3 Control Strategies for PV Integrated HAPF
3.4 Results and Discussions
4 Artificial Intelligent Methods for PQ Improvement in Hybrid Microgrid System
4.1 System Configuration and Modelling
4.2 Control Strategies for HMG Integrated with HAPF
4.3 Results and Discussions
5 Conclusion
References
Predictive Analytics for Advance Healthcare Cardio Systems
1 Introduction
1.1 Artificial Intelligence Playing a Major Role in Health Sector
1.2 Role of Deep Learning in Preventive Care
2 Literature Review
2.1 Review of Classification Methods for Heart Disease
2.2 Review of Lifestyle Factors Affecting Heart Disease
3 Comparison of Various Classifiers for Identification of the Disease
3.1 Data Set Description
3.2 Results
3.3 Summary
4 Role of Feature Selection in Prediction of Heart Disease
4.1 Dataset Description
4.2 Results
4.3 Summary
5 Enhancing the Performance of Extreme Learning Machines Using FS with GA for Identification of Heart Disease of Fetus
5.1 Dataset
5.2 Genetic Algorithm (GA)
5.3 ELM as a Classifier
5.4 Results
5.5 Summary
6 COPD and Cardiovascular Diseases: Are They Interrelated?
6.1 Dataset
6.2 Results
6.3 Summary
7 Conclusion and Future Work
References
Performance Optimization Strategies for Big Data Applications in Distributed Framework
1 Performance Improvements in Big Data and SDN
1.1 Introduction
1.2 Open Issues
1.3 Counter Based Reducer Placement
1.4 Intelligent Data Compression Policy
1.5 Resource Aware Task Speculation
1.6 Results-Counter Based Reducer Placement
1.7 Results-Intelligent Compression
1.8 Results-Resource Aware Task Speculation
2 Topology Discovery in Hybrid SDN
2.1 Introduction
2.2 Open Issues
2.3 Indirect Link Discovery (ILD)
2.4 Broadcast Based Link Discovery (BBLD)
2.5 Indirect Controller Legacy Forwarding (ICLF)
2.6 Extended Indirect Controller Legacy Forwarding (E-ICLF)
2.7 Evaluation Platform
2.8 Result Analysis-ILD
2.9 Result-Analysis-BBLD
2.10 Result Analysis-ICLF
2.11 Result Analysis-E-ICLF
3 Traffic Classification and Energy Minimization in SDN
3.1 Introduction
3.2 Open Issues
3.3 Traffic Classification Using Intelligent SDNs
3.4 Clonal Selection Based Energy Minimization
3.5 Dataset Description and Experimental Analysis
3.6 Result Analysis Traffic Classification
3.7 Simulation Setup
3.8 Results Energy Minimization
4 Traffic Engineering in SDN
4.1 Introduction
4.2 Open Issues
4.3 Intelligent Node Placement (INP)
4.4 Simulation Platform
4.5 Result Analysis
5 Conclusions and Future Work
References
