Key Digital Trends Shaping the Future of Information and Management Science

Name: Key Digital Trends Shaping the Future of Information and Management Science | Proceedings of 5th International Conference on Information Systems and Management Science (ISMS) 2022
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Proceedings of 5th International Conference on Information Systems and Management Science (ISMS) 2022

Lalit Garg Dilip Singh Sisodia Nishtha Kesswani Joseph G. Vella Imene Brigui Sanjay Misra Deepak Singh(Herausgeber*in)

Springer (Verlag)

Erschienen am 15. Mai 2023

XIII, 628 Seiten

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978-3-031-31153-6 (ISBN)

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Inhalt

Intro
Preface
Organization
Contents
Improvisation of Predictive Modeling Using Different Classifiers for Predicting Thyroid Disease in Patients
1 Introduction
1.1 Data Analytics
1.2 Prediction and Predictive Analysis
2 Literature Review
3 Exploratory Data Analysis
4 Proposed Model
4.1 k-NN Classifier
4.2 Random Forest Classifier
4.3 XGBoost Classifier
4.4 CatBoost Classifier
5 Results
6 Conclusion
References
Application of IoT for Proximity Analysis and Alert Generation for Maintaining Social Distancing
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Methodology and Block Diagram of System
4 Experimental Setup
5 Mathematical Modeling
6 Theoretical Results
7 Device Simulation and Result
8 Conclusions and Future Scope
References
Analysis and Optimization of Fault - Tolerant Behaviour of Motors in Electric Vehicular Systems
1 Introduction
2 Overview of Motors in Electric Vehicular Systems
3 EV Modelling
4 Exploratory Data Analysis of PMSM Characteristics Using Real - Time Data
4.1 About Dataset
4.2 Key Points About the Dataset
4.3 Determining Correlations
4.4 Generating Heatmap
4.5 Observations
5 Modelling of the Dynamics of Electric Vehicle
6 Fault Analysis
6.1 Normal Operation
6.2 Abnormal Operation
6.3 Observation Table
7 Optimization Technique of PMSM for Electric Vehicular Application
7.1 Normal Operation
7.2 Abnormal Operation
7.3 Observation Table
8 Conclusion
References
Transfer Learning of Mammogram Images Using Morphological Bilateral Subtraction and Enhancement Filter
1 Introduction
2 Contrast Enhancement
3 Histogram Equalization (HE)
4 Contrast Limited Adaptive Histogram Equalization (CLAHE)
4.1 Histogram Modified - Local Contrast Enhancement (HM-LCE)
5 Related Works
6 Image Segmentation
6.1 Mathematical Morphological Operations
7 Proposed Contrast Enhancement Using Modified Bi-level Histogram with Homomorphic Filter (MBH-HF)
7.1 Modified Bi-level Histogram
8 Experimental Analysis
8.1 Dataset Used
8.2 Experimental Result Analysis
9 Conclusion
References
Deep Learning Based Bengali Image Caption Generation
1 Introduction
2 Related Works
3 Proposed Methodology
3.1 Processing of Dataset
3.2 Extraction of Feature
3.3 Embedding
3.4 Encoder
3.5 Decoder
4 Experimental Setup
4.1 Output Generation
4.2 Result Analysis
5 Comparison
6 Future Scope and Conclusion
References
Analyzing Deep Neural Network Algorithms for Recognition of Emotions Using Textual Data
1 Introduction
2 Related Work
3 Research Methodology
3.1 Collection of Dataset
3.2 Data Pre-processing
3.3 Feature Extraction
3.4 Emotion Detection Using Deep Learning Models
4 Result and Analysis
5 Conclusion and Future Work
References
Smart Energy Saver
1 Introduction
2 Related Works
3 Proposed Methodology
4 Implementation
5 Result and Analysis
6 Conclusion and Future Work
References
Agile Helmet-A Smart Secure System for Motorbike
1 Introduction
2 Literature Survey
3 Proposed System
3.1 Helmet Module
3.2 Vehicle Module
4 Implementation
5 Results
5.1 Outputs
5.2 Performance Analysis
6 Conclusion and Future Work
References
Decentralized Digital Identity: A New Form of Secured Identity Using Blockchain Technology
1 Introduction
2 The Concept of Personal Identity
2.1 The model of Digital Identity Using Blockchain Technology
3 Materials and Methods
4 Result and Analysis
4.1 Biomedical Blockchain
4.2 Transport Blockchain
5 Conclusions
References
Object Detection with YOLO Version 3 for Big Data
1 Introduction
2 Literature Review
2.1 Artificial Neural Networks
2.2 Convolutional Neural Networks
2.3 Residual Network
2.4 Some Related Object Detection Techniques
3 Proposed Method: You Only Look Once (YOLO)
3.1 Prediction of Each Grid Cell
3.2 Necessity of Anchor-Boxes
3.3 Prediction of Anchor Boxes in YOLOv2 and Later
3.4 The Total Number of Bounding Box that YOLOv3 Can Predict
4 Implementation
4.1 Model Advancement
4.2 API Advancement
5 Conclusions and Future Work
References
Efficient Approach for Virtual Machine and Resource Allocation in Cloud Computing
1 Introduction
2 System Model
2.1 Actors in the Model
2.2 Mathematical Model for Resource Allocation and Profit Maximization
2.3 Mapping Strategy
3 Implementation
4 Result Analysis
5 Conclusions and Future Work
References
A Novel Approach for Service Selection and Ranking in Federated Cloud
1 Introduction
2 Related Work
3 Preliminaries
3.1 Ordered Weighted Averaging Method
4 VIKOR Method
5 Federated Cloud Service Broker (FCSB) Model
6 Service Selection Problem Scenario
7 User Preference Based Brokerage (UPB) Method
8 Simulation and Result Analysis
9 Conclusions and Future Work
References
A Review on IoT Based Wireless Sensor Network and Security
1 Introduction
2 Related Method
3 Wireless Sensor Network (WSN)
4 Data Aggregation
5 Conclusion and References
References
Automated Spoken Language Identification Using Convolutional Neural Networks & Spectrograms
1 Introduction
2 Related Work
3 Methodology
3.1 Data and Pre-processing
3.2 Design and Training
3.3 Evaluation of the Model
4 Results and Discussions
5 Conclusion
References
A Software Quality Characteristics Optimization Model to Reduce Evaluation Overhead
1 Introduction
2 Related Study
3 Proposed Work
3.1 Attribute Categorization
3.2 Software Quality Attribute Optimization
4 Results Analysis
5 Conclusion and Future Work
References
Smart Home Using Internet of Things
1 Introduction
2 Cisco Packet Tracer Software
3 Literature Review
4 Methodology
5 Safe Home Implementation
6 Discussion and Result
7 Conclusion
References
ADAPT- Automated Defence TrAining PlaTform in a Cyber Range
1 Introduction
2 Research Background and Related Work
3 Research Methodology
4 Proposed System
4.1 Profile-Based Training Design
4.2 System Design
4.3 System Implementation
5 System Evaluation
6 Conclusion and Future Work
A Sample Exercise Questions
References
An Improved Recommender System for Dealing with Data Sparsity Using Autoencoders and Neural Collaborative Filtering
1 Introduction
2 The Proposed Method
2.1 Recomendation System Frameworks
2.2 Autoencoder Based Feature Extraction
2.3 Embedding
2.4 Matrix Factorization
2.5 Generalized Matrix Factorization
2.6 Multilayer Perceptron
2.7 Neural Matrix Factorization
3 Dataset
4 Results and Discussions
4.1 Metrics for Evaluation
4.2 Experiment 1: Training of Models and Comparison of Performance
4.3 Experiment 2: Influence of the Sampling Ratio in the Dataset
4.4 Experiment 3: The Number of Predictive Factors
4.5 Experiment 4: The Factor K in the Evaluation
4.6 Experiment 5: Architecture of the Neural Network in MLP
4.7 Comparison with Existing Methods
5 Conclusion and Future Enhancements
References
Neural Network Based Algorithm to Estimate the Axial Capacity of Corroded RC Columns
1 Introduction
2 Research Significance
3 Methodology
3.1 Data Bank
3.2 Preparation of Dataset
3.3 Performance Criteria
4 Artificial Neural Network
4.1 Development of ANN Model
5 Results and Discussion
6 Conclusion
References
ML-Based Computational Model to Estimate the Compressive Strength of Sustainable Concrete Integrating Silica Fume and Steel Fibers
1 Introduction
2 Research Significance
3 Methodology
3.1 Data Bank
3.2 Preparation of Data
4 ANN
4.1 Development of ANN Model
5 Results and Discussion
6 Formulation
7 Conclusion
References
Indian Sign Language Digit Translation Using CNN with Swish Activation Function
1 Introduction
2 Related Works
3 Methodology
3.1 Dataset
3.2 Preprocessing
3.3 Proposed CNN Architecture
3.4 Experimental Setup
4 Results and Discussion
4.1 Performance
4.2 Comparison with Other Models
5 Conclusion and Future Scope
References
Prognosis of Viral Transmission in Naturally Ventilated Office Rooms Using ML
1 Introduction
2 Existing Literature
3 Channelization of Data
3.1 Collection of Data
3.2 Criteria for Evaluation
3.3 Data Normalization
4 Machine Learning (ML) Algorithms
4.1 Support Vector Machine (SVM)
4.2 Ensemble Learning (EL)
4.3 Gaussian Process Regression (GPR)
5 Results and Discussion
5.1 Application of ML Algorithms
5.2 Results of Machine Learning Models
5.3 Discussion
6 Conclusion
References
Impact of Organization Justice on Organizational Citizenship Behavior and Employee Retention
1 Introduction
2 Organizational Justice and Employee Retention
3 Organizational Justice and Organisational Citizenship Behavior
4 Organisational Citizenship Behavior and Employee Retention
5 Organizational Justice, Organizational Citizenship Behaviour and Employee Retention: Mediation Analysis
6 Research Methodology
7 Results
8 Structural Model and Hypotheses Testing
9 Theoretical Implication
10 Managerial Implication
11 Conclusion
References
Adopting Metaverse as a Pedagogy in Problem-Based Learning
1 Introduction
2 Literature Review
2.1 Characteristics and Scope of Metaverse
3 Metaverse and Its Role in Education
3.1 Metaverse Pioneers in Higher Education
4 Benefits of Metaverse
5 Metaverse as an Effective Pedagogy in Higher Education
6 Challenges
7 Conclusion
References
Design of Fuzzy Based Controller for Temperature Process in Fire Tube Boiler
1 Introduction
2 Process Description
3 Fire Tube Boiler
4 Fuzzy Logic Controller
4.1 Data Base
4.2 Rule Base
5 Fuzzy Logic Tool Box
6 Results and Discussion
7 Conclusion
References
Accelerating the Prediction of Anti-cancer Peptides Using Integrated Feature Descriptors and XGBoost
1 Introduction
2 Related Work
3 Methodology
3.1 Feature Extraction
3.2 Detailed Methodology
4 Experimental Setup and Result Discussions
4.1 Experimental Setup
4.2 Result Discussion
5 Conclusion
References
Intelligent Door Locking System
1 Introduction
2 Related Works
3 Proposed Methodology
4 Implementation
5 Result and Analysis
6 Conclusion and Future Work
References
Automated Generation of Multi-tenant Database Systems Based upon System Design Diagrams
1 Introduction
2 Literature Review
2.1 Database Design Diagrams
2.2 Multi-tenancy
2.3 Security Implementation in Database Design
2.4 Access Control Mechanisms
2.5 Software Development of Multi-tenant Database Systems
3 CASE Tool Development
3.1 Reading of System Design Diagrams
3.2 Conversion of System Diagrams to a Data Dictionary
3.3 Incorporation of Access Control Mechanisms
3.4 Automated Generation of SQL Constructs
4 Conclusions
References
Multivariate and Univariate Anomaly Detection in Machine Learning: A Bibliometric Analysis
1 Introduction
2 Research Methodology
3 Bibliometric Analysis
3.1 Document by Type
3.2 Distribution of Publications
3.3 Most Relevant Sources
3.4 Subject Area
3.5 Authors
3.6 Authors Keywords
3.7 Citation Output
3.8 Country
3.9 Country of Articles
3.10 Country of Publication
3.11 Country Collaboration Map
3.12 Total Country Citations
3.13 Network
3.14 Country Collaboration Network
4 Conclusion
References
A Multi Objective Hybrid Collision-Free Near-Optimal Dynamic Path Planner for Autonomous Robots in Dynamic Environments
1 Introduction
2 Related Work
3 Proposed System
3.1 The Proposed Approach MOHC-NODPP'S Working-Principle
3.2 Multi-criteria Optimization
3.3 The Heuristic Function
3.4 The Proposed System
4 Experimental Results
4.1 Casestudy-1
4.2 Case-Study 2
4.3 Case-Study-3
5 Performance Evaluation
6 Conclusion and Future Scope
References
How Does Background Music at Stores Impact Impulse Buying Behavior of Young Customers in Vietnam?
1 Introduction
2 Literature Review
3 Hypotheses Development and Research Model
3.1 Hypotheses Developement
3.2 Proposed Research Model
3.3 Sample Description
3.4 Data Collection Method
3.5 Research Instruments
4 Results
4.1 Exploratory Factor Analysis
4.2 Confirmatory Factor Analysis (CFA)
4.3 Structural Equation Modelling
5 Conclusion
References
A Deep Convolutional Neural Network for Remote Life Activities Detection Using FMCW Radar Under Realistic Environments
1 Introduction
2 Background Study
2.1 Radar Signal Representation
2.2 Deep Convolutional Neural Networks
2.3 Dataset Information
3 proposed work
3.1 Preprocessing of Radar Signals
3.2 Proposed CNN Architecture
4 Results
4.1 Experimental Results
4.2 Training Hyperparameters Results
4.3 Statistical Analysis
4.4 Classification Results Based on Individual Category
5 Discussions and Future
5.1 Classification Accuracy with the Test Data
5.2 Model Time Consumption Analysis
6 Conclusion
References
A Tool to Aid Households in Investments Decision
1 Introduction
2 Literature Review
2.1 How Do Households Make Investment Decisions?
2.2 Why Are Investment Decisions Important?
2.3 What is the Importance of Investment Tools in Making Financial Decisions?
2.4 What Investment Tools Are Available for Households?
3 Design
4 Implementation
5 Results and Evaluations
6 Conclusions and Future Scope
References
Cloud Computing in Upstream Oil and Gas Industry: Aspirations, Trends and Limitations
1 Introduction
1.1 Scope
2 Related Work
3 Problem Statement
4 Analysis and Design
4.1 Respondents Demography
4.2 Methodology
5 Results and Evaluations
5.1 Demography
5.2 Current State of Cloud Computing
5.3 Benefits and Obstacles of Cloud Computing
6 Conclusion
References
Plant Disease Detection Using Deep Learning Techniques
1 Introduction
2 Literature Work
3 Research Methodology
4 Results
5 Conclusion
References
Sentiment Analysis for Depression Detection and Suicide Prevention Using Machine Learning Models
1 Introduction
2 Proposed Methodology and Algorithm Design
2.1 Recurrent Neural Network (RNN)
2.2 Naive Bayes Classifier
2.3 Long Short-term Memory (LSTM)
2.4 Algorithm Design for Depression Analysis
3 Results and Discussion
4 Conclusion
References
Actor Model Frameworks: An Empirical Performance Analysis
1 Introduction
1.1 Problem Definition
2 Literature Review
2.1 Virtual Actor Model
2.2 Actor Model Implementations
3 Implementation
3.1 Actor Benchmark
3.2 Database Access Benchmark
3.3 Packaging and Deployment
3.4 Benchmark Procedure
4 Results
5 Discussion
6 Conclusions
References
Electric Sports Bicycle Motor Testing in a Laboratory Jig Using Cloud Computing and Internet of Things
1 Introduction
2 Objectives of the Invention
3 Features of Research
4 Details of Research
5 Steps for Development of a Hunting Electric Bicycle
6 Parts and Description of Figures
7 Advantages
8 Outcome of Research
9 Conclusions
References
MLTPDFS: Design of Machine Learning Model for Temporal Analysis of Progressive Diseases via Facial Scans
1 Introduction
2 Literature Review
3 Proposed Machine Learning Model for Temporal Analysis of Progressive Diseases via Facial Scans
3.1 Multiple Deep Learning Layer Design Based on Different CNN Models
3.2 Genetic Optimization for Tuning of Hyperparameters
3.3 Machine Learning Model with Incremental Performance Optimizations
4 Result Analysis and Comparison
5 Conclusion
References
CNN with Transfer Learning for Skin Lesion Identification Using Tasmanian Devil Optimization Algorithm
1 Introduction
2 Literature Survey
3 Proposed Methodology of CNN Transfer Learning + TDO for Skin Lesion Identification
3.1 Image Acquisition
3.2 Image Pre-processing Using Gaussian Filter
3.3 Skin Lesion Segmentation
3.4 Feature Extraction
3.5 Skin Lesion Identification Using Shuffle Net with CNN
4 Results and Discussion
4.1 Dataset Description
4.2 Evaluation Measures
4.3 Comparative Analysis
5 Conclusion
References
A Comprehensive Study of Crop Disease Detection Using Machine Learning Classification Techniques
1 Introduction
2 Crop Disease Detection Method
3 Literature Survey
3.1 SVM Classification
3.2 FFNN (Feed Forward Neural Network)
3.3 Naïve Bayes
3.4 KNN
3.5 Logistic Regression
3.6 CNN
4 Conclusion
References
Hybrid ANT Colony Optimization Routing Algorithm for AODV Protocol Improvement in FANET
1 Introduction
2 Literature Survey
3 Proposed Methodology
3.1 AODV Protocol
3.2 Proposed System
3.3 OMNeT++: Simulation Tool
4 Result Analysis
4.1 Simulation Model
4.2 Result File Observation
5 Conclusions and Future Work
References
Estimation of Implied Volatility for Ethereum Options Using Numerical Approximation Methods
1 Introduction
2 Literature Review
3 Methodology
3.1 Numerical Approximation Techniques
4 Results and Discussion
4.1 Dataset Description
4.2 Volatility Estimation
4.3 Performance Assessment
5 Conclusion
References
Semi Supervised Approach with Entity Embeddings for Heart Disease Prediction
1 Introduction
2 Background and Related Work
3 Methodology
3.1 Data Collection and Data Analysis
3.2 Data Preprocessing
3.3 Machine Learning Techniques Random Forest
3.4 Deep Learning Models for the Structured Data Using Semi-supervised Learning
4 Results and Discussion
5 Conclusion and Future Work
References
Machine Learning Model to Predict Mortality Due to Cardiovascular Diseases
1 Introduction
2 Machine Learning Models
3 Related Works
4 Methodology
4.1 Data Acquisition
4.2 Pre-processing Data and Analysis
4.3 Train-Test Data Split
4.4 Models Implementation
4.5 Results
5 Results and Discussion
5.1 Hardware and Software Specifications
5.2 Experimental Observations
5.3 Comparison with Existing Works
6 Conclusion
References
A Novel PCA-Logistic Regression for Intrusion Detection System
1 Introduction
2 Literature Review
3 Materials and Methods
3.1 Dataset
3.2 Principal Component Analysis (PCA)
3.3 The Proposed Approach
3.4 Logistic Regression
3.5 Gaussian Naïve Bayes (GNB)
4 Results and Discussion
4.1 Experimental Results
4.2 Performance Measures
4.3 Results of Proposed System Analysis
5 Discussion
5.1 Comparative Analysis with State-of-the-arts
6 Conclusion
References
Diagnosis Expert System on Breast Cancer Using Fuzzy Logic and Clustering Technique
1 Introduction
1.1 Motivation
2 Materials and Methods
2.1 Fuzzy Knowledge Representation
2.2 Fuzzy C-Means Clustering
3 Results and Discussion
3.1 The Proposed Model Evaluation
4 Conclusion and Future Direction
References
Effective Teaching Aids for People with Dyslexia
1 Introduction
2 Related Works
3 Methodology
3.1 Explanation of the Visual Aid Method:
3.2 Explanation of the Auditory Aid Method
4 Results
5 Conclusion
References
The Numerical Estimation of Spectral Energy Density in Electroencephalogram (EEG)
1 Introduction
2 Materials and Methods
2.1 Data Acquisition
2.2 Discrete Wavelet Transform
2.3 Newton-Gregory Interpolation
2.4 Simpson's Rule of Integral Approximation
2.5 Proposed Feature Extraction
3 Result and Discussion
4 Conclusion
References
Correction to: Key Digital Trends Shaping the Future of Information and Management Science
Correction to: L. Garg et al. (Eds.): Key Digital Trends Shaping the Future of Information and Management Science, LNNS 671, https://doi.org/10.1007/978-3-031-31153-6
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