Advances in Data-Driven Computing and Intelligent Systems

Name: Advances in Data-Driven Computing and Intelligent Systems | Selected Papers from ADCIS 2022, Volume 1
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Selected Papers from ADCIS 2022, Volume 1

Swagatam Das Snehanshu Saha Carlos A. Coello Coello Jagdish Chand Bansal(Editor)

Springer (Publisher)

Published on 3. August 2023

XXVI, 887 pages

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Swagatam Das received the B. E. Tel. E., M. E. Tel. E (Control Engineering specialization) and Ph. D. degrees, all from Jadavpur University, India, in 2003, 2005, and 2009 respectively. Swagatam Das is currently serving as an associate professor and Head of the Electronics and Communication Sciences Unit of the Indian Statistical Institute, Kolkata, India. His research interests include evolutionary computing and machine learning. Dr. Das has published more than 300 research articles in peer-reviewed journals and international conferences. He is the founding co-editor-in-chief of Swarm and Evolutionary Computation, an international journal from Elsevier. He has also served as or is serving as the associate editors of the IEEE Transactions on Cybernetics, Pattern Recognition (Elsevier), Neurocomputing (Elsevier), Information Sciences (Elsevier), IEEE Trans. on Systems, Man, and Cybernetics: Systems, and so on. He is an editorial board member of Information Fusion (Elsevier), Progress inArtificial Intelligence (Springer), Applied Soft Computing (Elsevier), Engineering Applications of Artificial Intelligence (Elsevier), and Artificial Intelligence Review (Springer). Dr. Das has 25,000+ Google Scholar citations and an H-index of 76 till date. He has been associated with the international program committees and organizing committees of several reputed international conferences including NeurIPS, AAAI, AISTATS, ACM Multimedia, BMVC, IEEE CEC, GECCO, etc. He has acted as guest editors for special issues in journals like IEEE Transactions on Evolutionary Computation and IEEE Transactions on SMC, Part C. He is the recipient of the 2012 Young Engineer Award from the Indian National Academy of Engineering (INAE). He is also the recipient of the 2015 Thomson Reuters Research Excellence India Citation Award as the highest cited researcher from India in Engineering and Computer Science category between 2010 to 2014.
Snehanshu Saha holds Master's Degree in Mathematical and Computational Sciences at Clemson University, USA and Ph.D. from the Department of Applied Mathematics at the University of Texas at Arlington in 2008. He was the recipient of the prestigious Dean's Fellowship during PhD and Summa Cum Laude for being in the top of the class. After working briefly at his Alma matter, Snehanshu moved to the University of Texas El Paso as a regular full-time faculty in the Department of Mathematical Sciences, University of Texas El Paso. Currently, He is a professor of Computer Science and Engineering at PES University since 2011 and heads the Center for AstroInformatis, Modeling and Simulation. He is also a visiting Professor at the department of Statistics, University of Georgia, USA and BTS Pilani, India. He has published 90 peer-reviewed articles in top-tier international journals and conferences and authored three text books on Differential Equations, Machine Learning and System Sciences respectively. Dr. Saha is an IEEE Senior member, ACM Senior Member, Vice Chair-International Astrostatistics Association and Chair, IEEE Computer Society Bangalore Chapter and Fellow of IETE. He's Editor of the Journal of Scientometric Research. Dr Saha is the recipient of PEACE Award for his foundational contributions in Machine Learning and AstroInformatics. Dr. Saha's current and future research interests lie in Data Science, Astronomy and theory of Machine Learning.
Carlos A. Coello Coello (Fellow, IEEE) received the Ph.D. degree in computer science from Tulane University, New Orleans, LA, USA, in 1996. He is currently a Professor with Distinction (CINVESTAV-3F Researcher), Computer Science Department, CINVESTAV-IPN, Mexico City, Mexico. He has authored and coauthored over 500 technical papers and book chapters. He has also co-authored the book Evolutionary Algorithms for Solving Multiobjective Problems (2nd ed., Springer, 2007) and has edited 3 more books with publishers such as World Scientific and Springer. His publications currently report over 60000 citations in Google Scholar (his H-index is 96). His major research interests are evolutionary multiobjective optimization and constraint-handling techniques for evolutionary algorithms. He has received several awards, including the National Research Award (in 2007) from the Mexican Academy of Science (in the area of exact sciences), the 2009 Medal to the Scientific Merit from Mexico City's congress, the Ciudad Capital: Heberto Castillo 2011 Award for scientists under the age of 45, in Basic Science, the 2012 Scopus Award (Mexico's edition) for being the most highly cited scientist in engineering in the 5 years previous to the award and the 2012 National Medal of Science in Physics, Mathematics and Natural Sciences from Mexico's presidency (this is the most important award that a scientist can receive in Mexico). He also received the Luis Elizondo Award from the Tecnológico de Monterrey in 2019. Additionally, he is the recipient of the2013 IEEE Kiyo Tomiyasu Award, "for pioneering contributions to single- and multiobjective optimization techniques using bioinspired metaheuristics", of the 2016 The World Academy of Sciences (TWAS) Award in "Engineering Sciences", and of the 2021 IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award. Since January 2011, he is an IEEE Fellow. He is currently the Editor-in-Chief of the IEEE Transactions on Evolutionary Computation.
Dr. Jagdish Chand Bansal is an Associate Professor at South Asian University New Delhi and Visiting Faculty at Maths and Computer Science, Liverpool Hope University UK. Dr. Bansal has obtained his Ph.D. in Mathematics from IIT Roorkee. Before joining SAU New Delhi he has worked as an Assistant Professor at ABV- Indian Institute of Information Technology and Management Gwalior and BITS Pilani. His Primary area of interest is Swarm Intelligence and Nature Inspired Optimization Techniques. Recently, he proposed afission-fusion social structure-based optimization algorithm, Spider Monkey Optimization (SMO), which is being applied to various problems from engineering domain. He has published more than 70 research papers in various international journals/conferences. He is the editor in chief of the journal MethodsX published by Elsevier. He is the series editor of the book series Algorithms for Intelligent Systems (AIS) and Studies in Autonomic, Data-driven and Industrial Computing (SADIC) published by Springer. He is the editor in chief of International Journal of Swarm Intelligence (IJSI) published by Inderscience. He is also the Associate Editor of Engineering Applications of Artificial Intelligence (EAAI) and ARRAY published by Elsevier. He is the general secretary of Soft Computing Research Society (SCRS). He has also received Gold Medal at UG and PG level.

Content

Intro
Preface
Contents
Editors and Contibutors
Adaptive Volterra Noise Cancellation Using Equilibrium Optimizer Algorithm
1 Introduction
2 Problem Formulation
3 Proposed Equilibrium Optimizer Algorithm-Based Adaptive Volterra Noise Cancellation
3.1 Gbest
3.2 Exploration Stage (F)
3.3 Exploitation Stage (Rate of Generation G)
4 Simulation Outcomes
4.1 Qualitative Performance Analysis
4.2 Quantitative Performance Analysis
5 Conclusion and Scope
References
SHLPM: Sentiment Analysis on Code-Mixed Data Using Summation of Hidden Layers of Pre-trained Model
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 BERT
3.2 RoBERTa
3.3 SHLPM
4 Implementation Details
4.1 Dataset and Pre-processing
4.2 SHLPM-BERT
4.3 SHLPM-XLM-RoBERTa
5 Results and Discussion
6 Conclusion
References
Comprehensive Analysis of Online Social Network Frauds
1 Introduction
1.1 Statistics of Online Social Network Frauds
2 Interrelationship between OSN Frauds, Social Network Threats, and Cybercrime
3 Types of Frauds in OSN
3.1 Social Engineering Frauds (SEF)
3.2 Human-Targeted Frauds (Child/Adults)
3.3 False Identity
3.4 Misinformation
3.5 E-commerce Fraud (Consumer Frauds)
3.6 Case Study for Facebook Security Fraud
4 OSN Frauds Detection Using Machine Learning
4.1 Pros and Cons
5 Conclusion
References
Electric Vehicle Control Scheme for V2G and G2V Mode of Operation Using PI/Fuzzy-Based Controller
1 Introduction
2 Motivation
3 System Description
4 Mathematical Model Equipments Used
4.1 Bidirectional AC-DC Converter
4.2 Bidirectional Buck-Boost Converter
4.3 Battery Modeling
4.4 Control of 1-Ø-Based Bidirectional AC-DC Converter Strategy
5 Fuzzy Logic Controller
6 Control Strategy
6.1 Constant Voltage Strategy
6.2 Constant Current Strategy
7 Results and Discussion
7.1 PI Controller
7.2 Fuzzy Logic Controller
7.3 Comparison of Harmonic Profile
8 Conclusion
References
Experimental Analysis of Skip Connections for SAR Image Denoising
1 Introduction
2 Related Works
2.1 Residual Network
2.2 Existing ResNet-Based Denoising Works
3 Implementation of the Different Patterns of Skip Connections
3.1 Datasets and Pre-processing
3.2 Loss Function
4 Results and Discussions
4.1 Denoising Results on Synthetic Images
4.2 Denoising Results on Real SAR Images
5 Conclusion
References
A Proficient and Economical Approach for IoT-Based Smart Doorbell System
1 Introduction
2 Literature Review
3 System Design and Implementation
3.1 System Design
3.2 Implementation
4 Results and Discussion
4.1 Performance Results
4.2 Comparison with an Existing System
4.3 Cost Analysis
5 Limitations
6 Conclusion
References
Predicting Word Importance Using a Support Vector Regression Model for Multi-document Text Summarization
1 Introduction
2 Related Work
3 Description of Dataset
4 Proposed Methodology
4.1 Preprocessing
4.2 Word Importance Prediction Using Support Vector Regression Model
4.3 Sentence Scoring
4.4 Summary Generation
5 Evaluation, Experiment, and Results
5.1 Evaluation
5.2 Experiment
5.3 Results
6 Conclusion and Future Works
References
A Comprehensive Survey on Deep Learning-Based Pulmonary Nodule Identification on CT Images
1 Introduction
2 Datasets and Experimental Setup
2.1 LIDC/IDRI Dataset
2.2 LUNA16 Dataset
2.3 NLST Dataset
2.4 KAGGLE DATA SCIENCE BOWL (KDSB) Dataset
2.5 VIA/I-ELCAP
2.6 NELSON
2.7 Others
3 CAD System Structure
3.1 Data Acquisition
3.2 Preprocessing
3.3 Lung Segmentation
3.4 Candidate Nodule Detection
3.5 False Positive Reduction
3.6 Nodule Categorization
4 CNN
4.1 Overview
4.2 CNN Architectures for Medical Imaging
4.3 Unique Characteristics of CNNs
4.4 CNN Software and Hardware Equipment
4.5 CNNs versus Conventional Models
5 Discussion
5.1 Research Trends
5.2 Challenges and Future Directions
6 Conclusion
References
Comparative Study on Various CNNs for Classification and Identification of Biotic Stress of Paddy Leaf
1 Introduction
2 Materials and Methods
2.1 Dataset
2.2 Proposed Methods
3 Experimental Results
3.1 Hardware Setup
3.2 Time Analysis with respect to GPU and CPU
3.3 Performance Analysis for Keras and PyTorch
3.4 Performance Analysis of CNN Models
3.5 Comparison of the Proposed CNN with Other State-of-the-Art Works
4 Conclusion
References
Studies on Machine Learning Techniques for Multivariate Forecasting of Delhi Air Quality Index
1 Introduction
2 Materials and Methodology
2.1 Delhi AQI Multivariate Data
2.2 Methodology
3 Experimental Setup and Simulation Results
4 Contrast Analysis Considering Dimensionality Reduction
5 Conclusions
References
Fine-Grained Voice Discrimination for Low-Resource Datasets Using Scalogram Images
1 Introduction
2 Related Works
3 Proposed Methodology
3.1 Collection of Voice Dataset
3.2 Preprocessing of Available Dataset to Increase the Trainable Samples
3.3 Classification of Phonemes Using Deep Convolutional Neural Network (DCNN)-Based Image Classifiers
4 Implementation Result and Analysis
5 Conclusion and Future Work
References
Sign Language Recognition for Indian Sign Language
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset
3.2 Data Preprocessing
3.3 Data Splitting
3.4 Data Augmentation
3.5 Model Compilation
3.6 Model Training and Testing
4 Results
5 Novelty and Future Work
6 Conclusion
References
Buffering Performance of Optical Packet Switch Consisting of Hybrid Buffer
1 Introduction
2 Literature Survey
3 Description of the Optical Packet Switch
4 Simulation Results
4.1 Bernoulli Process
4.2 Results
5 Conclusions
References
Load Balancing using Probability Distribution in Software Defined Network
1 Introduction
2 Related Work
3 Grouping of Controllers in SDN
4 Load Balancing in SDN
4.1 Simulation and Evaluation Result
5 Conclusion
References
COVID Prediction Using Different Modality of Medical Imaging
1 Introduction
2 Principles of Support Vector Machine (SVM)
2.1 Linear Case
2.2 Nonlinear Case
3 Material and Methods
3.1 CT Image Dataset
3.2 X-Ray Image Dataset
3.3 Ultrasound Image Dataset
4 The Proposed Model
5 Experimental Result
6 Conclusion
References
Optimizing Super-Resolution Generative Adversarial Networks
1 Introduction
2 Related Work
3 Dataset
3.1 Training Dataset
3.2 Test Dataset
4 Proposed Methodology
5 Performance Metrics
5.1 Peak Signal-to-Noise Ratio (PSNR)
5.2 Structural Similarity Index (SSIM)
6 Results and Discussion
7 Conclusion
References
Prediction of Hydrodynamic Coefficients of Stratified Porous Structure Using Artificial Neural Network (ANN)
1 Introduction
2 Stratified Porous Structure
3 Experimental Setup
4 Artificial Neural Network
4.1 Dataset Used for ANN
4.2 ANN Model
5 Results and Discussions
6 Conclusions
References
Performance Analysis of Machine Learning Algorithms for Landslide Prediction
1 Introduction
2 Literature Survey
3 Methodology of the Performance Analysis Work
3.1 Data Acquisition Layer
3.2 Fog Layer
3.3 Cloud Layer
4 Performance Analysis and Results
5 Conclusion
References
Brain Hemorrhage Classification Using Leaky ReLU-Based Transfer Learning Approach
1 Introduction
2 Related Works
3 Materials and Method
3.1 Dataset
3.2 Transfer Learning
3.3 ResNet50
4 Proposed Methodology
4.1 Input Dataset
4.2 Pre-processing
4.3 Network Training
4.4 Transfer Learning-Based Feature Extraction
5 Results
6 Conclusion
References
Factors Affecting Learning the First Programming Language of University Students
1 Introduction
2 Literature Review
3 Methodology
3.1 Data Collection
3.2 Experimental Design
3.3 Data Analysis
4 Result
4.1 Findings
5 Decision and Conclusion
References
Nature-Inspired Hybrid Virtual Machine Placement Approach in Cloud
1 Introduction
2 Related Work
3 Problem Formulation
4 Proposed Framework
4.1 Intelligent Water Drops (IWD) Algorithm
4.2 Water Cycle Algorithm (WCA)
4.3 Intelligent Water Drop Cycle Algorithm (IWDCA)
5 Result
5.1 Experiment Setup
5.2 Simulation Analysis of IWDCA
6 Conclusion
References
Segmented e-Greedy for Solving a Redesigned Multi-arm Bandit Environment
1 Introduction
2 Previous Works
3 Methodology
4 Results
5 Conclusion and Future Work
References
Data-Based Time Series Modelling of Industrial Grinding Circuits
1 Introduction
2 Formulation
2.1 Grinding Circuit
2.2 Least Square Support Vector Regression
2.3 Proposed Algorithm
3 Results and Discussions
3.1 Results of Proposed Algorithm
3.2 LS-SVR Model Performance
3.3 Comparison with Arbitrarily Selected Model
4 Conclusions
References
Computational Models for Prognosis of Medication for Cardiovascular Diseases
1 Introduction
2 Literature Review
3 Methodology
4 Results
5 Conclusion
References
Develop a Marathi Lemmatizer for Common Nouns and Simple Tenses of Verbs
1 Introduction
2 Related Work
3 Proposed Methodology
4 Conclusion
References
Machine Learning Approach in Prediction of Asthmatic Attacks and Analysis
1 Introduction
1.1 Machine Learning in Healthcare System
1.2 Role of ML in Asthma Prediction
1.3 Predictive Modeling
2 Literature Review
2.1 Search Strategy
2.2 Data Extraction
3 Conclusions
References
Efficient Fir Filter Based on Improved Booth Multiplier and Spanning Tree Adder
1 Introduction
2 Schematic Design and Simulation Results
2.1 Schematic Design of Spanning Tree Adder
2.2 Schematic Design of Booth Multiplier
2.3 Schematic Design of FIR Filter
3 Comparative Analysis
3.1 Comparison of Booth Multiplier
3.2 Comparison of FIR Filter Design with the Conventional One
4 Conclusion
References
Survey on Natural Language Interfaces to Databases
1 Introduction
2 Literature Survey
3 Comparative Analysis
4 Discussion
5 Conclusion
References
A Multiple Linear Regression-Based Model for Determining State-Wise Pregnancy Care Status for Urban and Rural Areas
1 Introduction
2 Dataset Consideration
3 Multiple Linear Regression Model-Pregnancy Care Score (MLRM-PCS)
3.1 Factors Affecting MLRM-PCS
3.2 Progression of MLRM-PCS
3.3 Development of MLRM-PCS
4 Results and Analysis
4.1 Urban Analysis
4.2 Rural Analysis
5 Conclusion
References
Performance Evaluation of Yoga Pose Classification Model Based on Maximum and Minimum Feature Extraction
1 Introduction
2 Related Work
3 Dataset Preparation
4 Proposed Approach
4.1 Feature Extraction Model using MediaPipe Library
4.2 Yoga Pose Classification Model
5 Experimental Setup and Test Results Discussions
6 Conclusion
References
On Regenerative and Discriminative Learning from Digital Heritages: A Fractal Dimension Based Approach
1 Introduction
2 Related Works
3 Methodology
3.1 Preprocessing of the Spires
3.2 Fractal Dimension
3.3 Proposed Method
4 Experiments and Results
4.1 Datasets
4.2 Qualitative and Quantitative Results
5 Conclusion and Future Works
References
Identifying Vital Features for the Estimation of Fish Toxicity Lethal Concentration
1 Introduction
2 Literature Review
3 Proposed Methodology
3.1 Feature Selection
3.2 Toxicity Estimation
4 Experimental Results
4.1 Dataset
4.2 Model Performance
5 Conclusion
References
High-Impedance Fault Localization Analysis Employing a Wavelet-Fuzzy Logic Approach
1 Introduction
2 Previous and Related Work
2.1 Wavelet-Based Signal Analysis
2.2 Fuzzy Logic Technique
2.3 HIF Diagnosis
3 Single Line Diagram of IEEE-15 Bus System
3.1 Equations Considered
4 Flowchart of Proposed Method
5 Implemented FIS
6 Results Obtained
7 Conclusion
References
A Conceptual Framework of Generalizable Automatic Speaker Recognition System Under Varying Speech Conditions
1 Motivation
2 Introduction
3 Related Work
4 Generalizability Problem
5 ASR Implementation
5.1 Generalizability Measurements
6 Conclusion
References
A Review for Detecting Keratoconus Using Different Techniques
1 Introduction
2 Methodology
2.1 Image Acquisition
2.2 Image Enhancement
2.3 Preprocessing
2.4 Mathematical Model for Feature Extraction
2.5 Feature Selection
2.6 Classification
3 Conclusion
References
An Efficient ECG Signal Compression Approach with Arrhythmia Detection
1 Introduction
2 Related Work
3 Methodology
3.1 Dataset
3.2 Preprocessing
3.3 Segmentation
3.4 Feature Extraction
3.5 Proposed SCAE Model
3.6 Arrhythmia Detection
3.7 Evaluation Metrics
4 Results
5 Conclusion
References
A Chronological Survey of Vehicle License Plate Detection, Recognition, and Restoration
1 Introduction
2 License Plate Detection Techniques
2.1 Edge-Based Approaches
2.2 Color-Based Approaches
2.3 Texture-Based Approaches
2.4 Character-Based Approaches
2.5 Hybrid Approaches
3 License Plate Segmentation Techniques
3.1 Segmentation-Based Approach for License Plate Image Recognition
3.2 Segmentation-Free Approach for License Plate Image Recognition
4 License Plate Recognition
5 Image Restoration
6 Result and Analysis
7 Conclusion
References
Correlation-Based Data Fusion Model for Data Minimization and Event Detection in Periodic WSN
1 Introduction
2 Related Work
3 Two-Level Data Fusion Model for Data Minimization and Event Detection (DMED)
4 Implementation
4.1 Simulation Parameters and Metrics for Evaluation of DMED Model
5 Result
5.1 Data Minimization at the Normal State (S1)
5.2 Event Detection at S2, S3, and S4 States
6 Conclusion
References
Short-term Load Forecasting: A Recurrent Dynamic Neural Network Approach Using NARX
1 Introduction
2 Short-Term Load Forecasting
2.1 Introduction
2.2 Soft Computing Techniques
2.3 Independent Factors
2.4 Historical Data
2.5 Load Data
2.6 Preprocessing of Input Data
2.7 STLF Approach
2.8 Nonlinear Autoregressive with Exogenous Input Neural Network (NARX-NN)
2.9 Methodology of NARX-NN
3 Results and Discussion
4 Conclusion
References
Performance Estimation of the Tunnel Boring Machine in the Deccan Traps of India Using ANN and Statistical Approach
1 Introduction
2 Project Description
3 Geology of the Project Area
4 TBM Performance and Prediction Model Based on RMR
5 Multiple Linear Regression Analysis (MLR)
6 Multiple Non-linear Regression Analysis (MNR)
7 Artificial Neural Network
8 Conclusion
References
Abnormality Detection in Breast Thermograms Using Modern Feature Extraction Technique
1 Introduction
2 Literature Review
3 Methodology
3.1 Dataset
3.2 Preprocessing of Thermal Images
3.3 GLCM Method
3.4 Maximum Red Area Method
3.5 Anomalous Area Detection Using k-Means
3.6 Graphical User Interface (GUI)
4 Result
5 Conclusion
References
Anomaly Detection Using Machine Learning Techniques: A Systematic Review
1 Introduction
2 Background and Literature Review
3 Methodology
3.1 Research Questions
3.2 Search Methodology
3.3 Study Selection Criteria
3.4 Quality Assessment Check
3.5 Data Extraction Strategy
3.6 Data Synthesis
4 Results and Discussion
4.1 Machine Learning Techniques Used for Anomaly Detection
4.2 Machine Learning Algorithm Mostly Used in Various Applications
4.3 Main Research Work Done in Anomaly Detection
5 Conclusion
References
A Comparative Analysis on Computational and Security Aspects in IoT Domain
1 Introduction
2 Background
3 Approach-Based Analysis
4 Problem Statement
5 Proposed Framework for Data Preprocessing and Categorization
6 Discussion and Findings
7 Conclusion
References
Attack Detection in SDN Using RNN
1 Introduction
2 Methodology
2.1 Dataset
3 Experimental Setup and Results
4 Conclusion and Future Work
References
Vehicle Detection in Indian Traffic Using an Anchor-Free Object Detector
1 Introduction
2 Dataset Collection
3 Methodology
3.1 Backbone
3.2 FPN
3.3 VDH
4 Experimental Results
4.1 Platform Configuration and Training
4.2 Evaluation of Model
5 Conclusion
References
GuardianOpt: Energy Efficient with Secure and Optimized Path Election Protocol in MANETs
1 Introduction
2 Related Work
3 Proposed Work
3.1 Computing Factors
3.2 Data Structure
3.3 Guardian Protocol Behaviors
4 Simulation and Result Analysis
4.1 Packet Delivery Ratio
4.2 Throughput
4.3 Delay
5 Conclusion and Future Scope
References
Texture Metric-Driven Brain Tumor Detection Using CAD System
1 Introduction
2 Related Works
2.1 Active Contour Model
3 GLCM Texture Bound Model
4 Texture Analyzes
4.1 PCA-Driven Feature Selection
4.2 Comparison with Other Transformation Methods
5 Experimental Results
6 Conclusion
6.1 Limitations
6.2 Future Scope
References
Comparative Analysis of Current Sense Amplifier Architectures for SRAM at 45 nm Technology Node
1 Introduction
2 Schematic Diversity in Current Sense Amplifiers
3 Performance Analysis of the Current Sense Amplifiers
4 Conclusion
References
Iterative Dichotomiser 3 (ID3) for Detecting Firmware Attacks on Gadgets (ID3-DFA)
1 Introduction
2 Related Work
3 Theoretical Background
3.1 Delineation of Firmware Attack Detection on Gadgets Using Iterative Dichotomiser 3 (ID3)
4 Experimental Results and Comparison
5 Conclusion and Future Work
References
Comparative Performance Analysis of Heuristics with Bicriterion Optimization for Flow Shop Scheduling
1 Introduction
2 Problem Formulation
2.1 Two-Machine Flow Shop Scheduling Problem Having Random Processing Times
2.2 Two-Machine Specially Structured Flow Shop Scheduling Problem
2.3 Assumptions
3 Theorems and Proposed Heuristic
4 Computational Experiments and Results
5 Conclusion
References
Burrows-Wheeler Transform for Enhancement of Lossless Document Image Compression Algorithms
1 Introduction
2 Problem Statement and Motivation
3 Proposed Methodology
3.1 Linearization of Data
3.2 Numeric Burrows-Wheeler Transform
3.3 Modified Run Length Encoding Algorithm
3.4 Huffman Encoding
3.5 Dictionary-Based Method
4 Experimentation and Result Discussion
4.1 Compression Ratio
5 Conclusions
References
Building a Product Recommender System Using Knowledge Graph Embedding and Graph Completion
1 Introduction
2 Literature Survey
3 System Design
3.1 Knowledge Graph Construction
3.2 Knowledge Graph Embedding
3.3 Knowledge Graph Completion and Recommendation
4 Experiments and Results
4.1 Description of Dataset
4.2 Tools Used
5 System Evaluation
5.1 Evaluation Measures
5.2 System Performance
5.3 Real-Time Recommendations
6 Conclusion and Future Work
References
A Survey on Risks Involved in Wearable Devices
1 Introduction
2 Related Works
2.1 A Review on Intelligent Wearables: Uses and Risks
2.2 Are Bluetooth Headphones Safe?
2.3 The Health Impacts of Wearable Technology
2.4 The Negative Effects of Wearable Technology
2.5 Risks of Wearable Technology for Directors and Officers
3 Wearable Devices
3.1 Privacy Risks
3.2 Security Risks
3.3 Social Risks
3.4 Psychological and Biological Risks
3.5 The Likeliness of Effects of Risks Identified Among Different Aged Groups
4 Survey and Its Results
5 Conclusion
References
A Systematic Comparative Study of Handwritten Digit Recognition Techniques Based on CNN and Other Deep Networks
1 Introduction
2 CNN-Based Handwritten Digit Classifiers
3 Other Deep Networks-Based Handwritten Digit Classifiers
4 Implementation and Result Analysis
5 Conclusion
References
Estimating the Tensile Strength of Strain-Hardening Fiber-Reinforced Concrete Using Artificial Neural Network
1 Introduction
2 Artificial Neural Network Model
2.1 Artificial Neural Network Method
2.2 Experimental Database
2.3 K-fold Cross-Validation Approach
2.4 Statistical Metrics
3 Performance of Model
3.1 Performance of the ANN Model Through the 5-folds Cross-Validation
3.2 Performance of the Proposed Model via the Testing Data Set
3.3 Sensitivity Analysis
4 Conclusion
References
Change Detection Using Multispectral Images for Agricultural Application
1 Introduction
1.1 Study Area
2 Proposed Work
2.1 System Architecture
2.2 System Architecture
2.3 Stacking
3 Description of Algorithms
3.1 K-Means Clustering
4 Results and Observations
5 Conclusion
References
Detection of Bicep Form Using Myoware and Machine Learning
1 Introduction
2 Literature Review
3 Methodology
3.1 Data Acquisition
3.2 Feature Extraction and Data Preprocessing
3.3 Machine Learning Model Classification
3.4 Monitoring the Exercise through MIT App Inventor
3.5 Experimental Setup
4 Dataset
5 Results and Discussion
6 Conclusion
References
Improved Adaptive Multi-resolution Algorithm for Fast Simulation of Power Electronic Converters
1 Introduction
2 Revisiting Basic Control Theory
3 Improved AMRS Framework
4 Numerical Examples
4.1 Example 1: Class E Amplifier
4.2 Example 2: Buck-Boost Converter
5 Conclusion
References
Fast and Accurate K-means Clustering Based on Density Peaks
1 Introduction
1.1 K-means Clustering
1.2 Random Swap Clustering
1.3 Density Peaks Clustering
1.4 Paper Contribution
2 Proposed Method
2.1 Cutoff Prediction
2.2 Density Calculation
2.3 Centroids Selection
2.4 K-means Operation
3 Clustering Accuracy Indexes
3.1 Normalized SSE
3.2 Centroid Index (CI)
3.3 Generalized Centroid Index (GCI)
4 Benchmark Datasets
5 Experimental Results
6 Conclusions
References
Improving Accuracy of Recommendation Systems with Deep Learning Models
1 Introduction
1.1 Background of the Study
1.2 Current Challenges
1.3 Problem Statement
2 Recommendation Systems
2.1 Overview of Recommendation Systems
3 MLP-Based Models for Recommendation Systems
4 CNN for Recommendation Systems
5 Conclusion
References
Calibration of Optimal Trigonometric Probability for Asynchronous Differential Evolution
1 Introduction
2 Asynchronous Differential Evolution and Trigonometric Mutation Operation
3 Parameter Settings and Performance Metrics
3.1 Parameter Settings
3.2 Metrics for Evaluating Performance
4 Simulated Results and Analyses
5 Performance Analyses
6 Conclusion and Future Work
References
Person Monitoring by Full Body Tracking in Uniform Crowd Environment
1 Introduction
2 Related Work
2.1 Siamese Trackers
2.2 Spatio-Temporal Transformer Network for Visual Tracking (STARK)
3 Methodology
3.1 Collection of Data
3.2 Annotation of Generated Data
3.3 Splitting of Dataset
3.4 Training Process
4 Results and Discussion
5 Conclusion
References
Malicious Web Robots Detection Based on Deep Learning
1 Introduction
2 Literature Review
3 Proposed Method
3.1 Session Identification
3.2 Feature Extraction
3.3 Deep Feature Representation Learning
3.4 Classification
4 Experimental Results
4.1 Dataset Preparation
4.2 Evaluation Criteria
4.3 Evaluation Results and Discussion
5 Conclusion
References
A Secured MANET Using Trust Embedded AODV for Optimised Routing Against Black-Hole Attacks
1 Introduction
2 Literature Review
3 Problem Statement
4 Objectives of the Study
5 Methodology
5.1 Simulator
5.2 Stimulation Parameters
5.3 Attacks Related to Recommendation Management in Trust and Reputation Frameworks
5.4 Performance Metrics
6 Implementation and Result
6.1 Recording Readings for AODV, DSR and Results for TOADV
6.2 Results with DSR
7 Results with TAODV
7.1 TAODV Without Attacks
7.2 TAODV with Attacks
8 Conclusion and Future Work
References
Recognition of Offline Handwritten Gujarati Consonants Having Loop Feature Using GHCIRS
1 Introduction
2 Gujarati Handwritten Character Identification and Recognition System
3 Results and Outcome
4 Performance Analysis of the GHCIR System
5 Conclusion
References
User-Centric Adaptive Clustering Approach to Address Long-Tail Problem in Music Recommendation System
1 Introduction
2 Related Work
3 Proposed System
3.1 Ada-UCC
3.2 Ada-UCC-KNN
3.3 Ada-UCC-W-KNN
4 Experimentation Results
5 Conclusion and Future Scope
References
Author Index

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Advances in Data-Driven Computing and Intelligent Systems

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