Machine Learning, Image Processing, Network Security and Data Sciences: Select Proceedings of 3rd International Conference on MIND 2021

Preface
Acknowledgements
Contents
About the Editors
Machine and Deep Learning
Beta Artificial Bee Colony Algorithm for EMG Feature Selection
	1 Introduction
	2 Methods and Implementation
		2.1 EMG Data
		2.2 Feature Extraction Using DWT Method
		2.3 Background
	3 Proposed Methodology
		3.1 Beta Artificial Bee Colony (BetaABC)
	4 Proposed Binary BetaABC for EMG Feature Selection
	5 Experimental Analysis
	6 Conclusion
	References
Distributed Deep Learning for Content-Based Image Retrieval
	1 Introduction
	2 Methodology
	3 Results and Discussion
	4 Conclusions and Future Scope
	References
Automated Detection of Type 2 Diabetes with Imbalanced and Machine Learning Methods
	1 Introduction
	2 Related Works
	3 Materials and Methods
		3.1 Dataset Description
		3.2 Feature Engineering
		3.3 Experimental Setup
	4 Experimental Results and Discussions
		4.1 Category 1: Experiments with Traditional Machine Learning Methods
		4.2 Category 2: Experiments with Ensemble Machine Learning Methods
		4.3 Category 3: Experiments with Imbalanced Data Pre-processing and Traditional Machine  Learning Methods
		4.4 Comparison with Previous Studies
	5 Conclusion and Future Directions
	References
Deep Transfer Learning and Intelligent Item Packing in Retail Management
	1 Introduction
	2 Methodology
	3 Architecture CNN
	4 Recognition
	5 Transfer Learning
	6 Result and Discussion
		6.1 Performance Evaluation
		6.2 Classify Before Packaging Service
	7 Conclusion
	References
Prediction of Polycystic Ovarian Syndrome Using Machine Learning Techniques
	1 Introduction
	2 Literature Survey
	3 Proposed Methodology
		3.1 Dataset Description and Feature Selection
		3.2 Normalization
		3.3 Results and Discussion
	4 Conclusion and Future Work
	References
Medical Image Fusion for Diagnosis of Alzheimer Using Rolling Guidance Filter and Parameter Adaptive PCNN
	1 Introduction
	2 Related Work
		2.1 Rolling Guidance Filter (RGF)
		2.2 Parameter Adaptive PCNN (PA-PCNN)
	3 Proposed Method
	4 Experimental Results
	5 Conclusion
	References
Effectiveness of Ensemble Classifier Over State-Of-Art Machine Learning Classifiers for Predicting Software Faults in Software Modules
	1 Introduction
	2 Related Works
	3 Methodology
		3.1 State-Of-Art Classifiers
		3.2 Ensemble Learning Technique
		3.3 Boosting and Boosting Algorithms
	4 Results and Discussion
		4.1 Datasets
		4.2 Evaluation Parameters
		4.3 Results and Analysis
	5 Conclusion and Future Scope
	References
A Machine Learning Approach for Detection of Breast Cancer in Women Using Advanced GLCM
	1 Introduction
	2 Related Work
	3 Proposed Methodology
		3.1 Image Acquisition
		3.2 Advanced Gray-Level Co-occurrence Matrix
		3.3 Classification
	4 Experimental Results and Discussion
	5 Conclusion
	References
Sales Prediction Using ARIMA, Facebook’s Prophet and XGBoost Model of Machine Learning
	1 Introduction
	2 Literature Review
		2.1 Sales Forecasting Newspaper with ARIMA: A Case Study
		2.2 Forecasting of Demand Using ARIMA Model
		2.3 Application of Facebook’s Prophet Algorithm for Successful Sales Forecasting Based on Real-World Data
		2.4 An Advanced Sales Forecasting System XGBoost Algorithm
		2.5 Retail Store Predictions
	3 Proposed Methodology
		3.1 ARIMA Model
		3.2 Prophet Model
		3.3 XGBoost Model
	4 Results
	5 Conclusion and Future Scope
	References
Modeling Concept Drift Detection as Machine Learning Model Using Overlapping Window and Kolmogorov–Smirnov Test
	1 Introduction
	2 Related Works
	3 Proposed Methodology
		3.1 Windowing Module
		3.2 Kolmogorov–Smirnov Test
		3.3 Machine Learning Model for Concept Drift Detection
	4 Results Analysis
		4.1 Dataset
		4.2 Logistic Regression
		4.3 Support Vector Machine
		4.4 K-Nearest Neighbors
		4.5 Naïve Bayes Classifier
		4.6 Decision Tree
		4.7 Random Forest
	5 Conclusion
	References
Wearable Sensor-Based Framework for the Detection of Daily Living Activities Utilizing In-Depth Features
	1 Introduction
	2 Related Work
		2.1 Machine Learning Approaches
		2.2 Deep Learning Approach
	3 Proposed Methodology
	4 Data Preprocessing
		4.1 Principle Component Analysis
		4.2 Standard Scaling (Standardization)
		4.3 Data Balancing
		4.4 Sliding Window Technique
	5 Results
		5.1 Random Forest Classifier
		5.2 Support Vector Machine (SVM)
		5.3 Naïve Bayes Classifier
		5.4 Decision Tree Classifier
		5.5 Convolutional Neural Network
		5.6 Extraction of CNN Features for the Training of Machine Learning Models
	6 Discussion
	7 Conclusion
	References
Implementing Robotic Path Planning After Object Detection in Deterministic Environments Using Deep Learning Techniques
	1 Introduction
	2 Related Study
	3 Proposed Methodology
		3.1 Object Detection
		3.2 Path Generation
	4 Implementation and Analyses
	5 Comparative Analysis
	6 Conclusion and Future Directions
	References
SDDSCNet: Siamese-Based Dilated Depthwise Separable Convolution Neural Network with Wavelet Fusion for Change Detection
	1 Introduction
	2 Dataset Description
	3 Proposed Method
		3.1 UNet Structure with Original Convolution
		3.2 DWconv-Depthwise Separable Convolution
		3.3 Dilated Convolution Operation
		3.4 SDDSCNet with Dilated-Based Depthwise Separable Convolution for Change Detection
		3.5 Details of Training Parameter
		3.6 UDWT-Undecimated Discrete Wavelet Transform Fusion
	4 Results
	5 Conclusion
	References
Evaluation of Customer Care Executives Using Speech Emotion Recognition
	1 Introduction
	2 Related Work
	3 Implementation
		3.1 Dataset Description
		3.2 Pre-processing and Feature Extraction
		3.3 Classification
	4 Results
	5 Conclusion
	6 Future Work
	References
Deep Convolutional Neural Network Approach for Tomato Leaf Disease Classification
	1 Introduction
	2 Literature Review
	3 Method and Materials
		3.1 Deep Learning-Based Image Classifiers Applied for Process
		3.2 Work Flow
		3.3 Data Collection
	4 Experimentation and Results
	5 Conclusion
	References
Cognitive Load Classification During Arithmetic Task Using Single Convolution Layer-Based 2D-CNN Model
	1 Introduction
	2 Methodology
		2.1 Dataset and Pre-processing
		2.2 Architecture of CNN
		2.3 Performance Measures
	3 Results and Analysis
	4 Conclusion and Future Scope
	References
Plant Leaf Diseases Detection Using Deep Learning Algorithms
	1 Introduction
	2 Literature Review
	3 Materials and Methods
		3.1 Datasets
		3.2 Deep Learning Models
	4 Experiments and Results
		4.1 Software Environment
		4.2 Hardware Requirements
		4.3 Metrics Used
		4.4 Parameters Setup
		4.5 Calculation of Results
	5 Conclusion and Future Scope
		5.1 Conclusion
		5.2 Future Work
	References
Performance Comparison of the Classifiers for Betel Vine Disease Prediction
	1 Introduction
	2 Literature Review
	3 Proposed Work
		3.1 Dataset
		3.2 Image Pre-processing
		3.3 Feature Selection
		3.4 Classifier Construction
		3.5 Performance Evaluation
	4 Results and Discussions
	5 Conclusions and Future Work
	References
Enhanced Object Detection in Floor Plan Through Super-Resolution
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Preliminary Step
		3.2 Wall/Room Detection
		3.3 Post-processing
	4 Results and Discussion
		4.1 Inference Latency
		4.2 Results
	5 Conclusion and Future Work
	References
Attention-Based Bitemporal Image Deep Feature-Level Change Detection for High Resolution Imagery
	1 Introduction
	2 Methodology
		2.1 Outline
		2.2 Feature Extractor
		2.3 Difference Evaluation Network
	3 Experiments and Results
		3.1 Dataset
		3.2 Implementation Details
		3.3 Comparison and Evaluation of the Dataset
	4 Conclusion
	References
Prostate Cancer Grading Using Multistage Deep Neural Networks
	1 Introduction
	2 Grading
		2.1 Gleason Score
		2.2 ISUP Grading
	3 Literature Survey
	4 Methodology
		4.1 Segmentation
		4.2 Overlay
		4.3 Classification and Explainable AI
	5 Experiments and Results
		5.1 Dataset
		5.2 AI Training Pipeline
		5.3 Parameters and Metrics
		5.4 Performance Comparison
		5.5 Explainable AI: GradCam Visualization
	6 Conclusion
	References
Analyzing Wearable Data for Diagnosing COVID-19 Using Machine Learning Model
	1 Introduction
	2 Related Studies
	3 Research Problem
	4 Dataset Used
		4.1 Characteristic Physiological Features
	5 Limitations of This Study
	6 Conclusion
	References
Comparative Analysis of Classification Methods to Predict Diabetes Mellitus on Noisy Data
	1 Introduction
	2 Related Work
	3 Exploratory Data Analysis
	4 Methodology
		4.1 Modeling
	5 Results
	6 Conclusion and Future Work
	References
A Robust Secure Access Entrance Method Based on Multi Model Biometric Credentials Iris and Finger Print
	1 Introduction
	2 Type of Biometric System
		2.1 Single Modal Bio System
		2.2 Multi Modal Biometric System
		2.3 Fingerprint Recognition
		2.4 Iris Recognition
	3 Proposed Method
		3.1 Training and Data Set Creation
		3.2 Biometric Finger Print and Iris Matching Proposed Algorithm
	4 Simulation and Result
	5 Conclusion
	References
Region Classification for Air Quality Estimation Using Deep Learning and Machine Learning Approach
	1 Introduction
	2 Literature Review
	3 Proposed Work
		3.1 Proposed Region Classification Model Using Deep Neural Network
		3.2 Transfer Learning in Region Classification
		3.3 AQI Estimation Using Ensemble Approach
	4 Experimental Setup
		4.1 Data Set Collection—Urban and Rural Regions
		4.2 Application of Deep Learning Models for Region Classification
		4.3 Application of Machine Learning Models for Air Pollution Level Estimation
	5 Conclusion and Future Work
	References
Neuroevolution-Based Earthquake Intensity Classification for Onsite Earthquake Early Warning
	1 Introduction
		1.1 Evolutionary Computing Approach
	2 Methodology
		2.1 Neuroevolution
		2.2 Data
	3 Results and Discussion
	4 Conclusion
	References
Detection of Credit Card Fraud by Applying Genetic Algorithm and Particle Swarm Optimization
	1 Introduction
	2 Literature Survey
	3 Artificial Neural Network Application
	4 Genetic Algorithm
	5 Particle Swarm Optimization
		5.1 Personal Best (p-best)
		5.2 Global Best (g-best)
	6 Result and Performance Analysis
		6.1 Dataset Used for Experiment
		6.2 Experimental Setup
		6.3 Confusion Matrix
		6.4 Performance Parameters
	7 Conclusion
	References
Traditional Indian Textile Designs Classification Using Transfer Learning
	1 Introduction
	2 Prior Art
	3 Methodology
		3.1 Dataset
	4 Results and Discussion
	5 Conclusions and Future Directions
	References
Classification of Electrocardiogram Signal Using Hybrid Deep Learning Techniques
	1 Introduction
	2 Related Work
	3 Material and Method
		3.1 ECG MIT-BIH Arrhythmia Database
		3.2 Heartbeat Detection
		3.3 Classification Model
		3.4 Working of the Proposed Deep CNN-LSTM Model
	4 Experimental Results
		4.1 Experiment 1 (Patient Independent for Multiclass Classification)
		4.2 Experiment 2 (Patient Specific for Multiclass Classification)
	5 Discussion
	6 Conclusion
	References
Fault Diagnosis in Wind Turbine Blades Using Machine Learning Techniques
	1 Introduction
	2 Experimental Setup
	3 Experimental Procedure
	4 Feature Extraction
	5 Implementation of Machine Learning Techniques
	6 Results
		6.1 The Results Were Displayed with the Help of a Confusion Matrix
	7 Conclusion
	References
Real-Time Detection of Vehicles on South Asian Roads
	1 Introduction
	2 Related Work
	3 Dataset
		3.1 Sub Setting the COCO and IDD Dataset
		3.2 Frames from Surveillance Videos
		3.3 Web Scraping
	4 Methodology
	5 Experimentation and Results
	6 Conclusion
	References
Stock Market Prediction Using Ensemble Learning and Sentimental Analysis
	1 Introduction
	2 Literature Review
	3 Dataset
		3.1 Historical Features
		3.2 Technical Indicators
		3.3 Sentimental Features
	4 Methodology
		4.1 Proposed Methodology
	5 Results and Discussion
	6 Conclusions and Future Work
	References
Multiple Feature-Based Tomato Plant Leaf Disease Classification Using SVM Classifier
	1 Introduction
	2 Related Works
	3 Preliminaries
		3.1 K-Means Algorithm
		3.2 Feature Extraction
	4 Proposed Method
	5 Simulation Results
	6 Conclusion and Future Scope
	References
A Methodological Review of Time Series Forecasting with Deep Learning Model: A Case Study on Electricity Load and Price Prediction
	1 Introduction
	2 Review Methodology
	3 Literature Review
		3.1 Electrical Load Forecasting
		3.2 Electrical Price Forecasting
	4 Methodology for Dataset Generation and Data Preprocessing
		4.1 U.S. Energy Information Administration and TMY3—Multivariate Time Series Data
		4.2 Univariate Time Series Data
	5 Result Discussion and Analysis
		5.1 Multivariate Time Series
		5.2 Univariate Time Series
	6 Conclusion and Future Work
	References
Unexpected Alliance of Cardiovascular Diseases and Artificial Intelligence in Health Care
	1 Introduction
	2 Literature Review
	3 Proposed Work
		3.1 Architecture of Proposed Work and Implementation
		3.2 Machine and Deep Learning Models
		3.3 Dataset
	4 Results
	5 Conclusion and Future Scope
	References
A Novel Smartphone-Based Human Activity Recognition Using Deep Learning in Health care
	1 Introduction
		1.1 Our Contribution
	2 Previous Work
	3 Dataset Description
		3.1 WISDM
		3.2 UCI-HAR
	4 Proposed Methodology
		4.1 Data Preprocessing
		4.2 Proposed Architecture
	5 Experiments and Results
		5.1 Model Implementation
		5.2 Performance Measure
		5.3 Conclusion
	References
An Enhanced Deep Learning Approach for Smartphone-Based Human Activity Recognition in IoHT
	1 Introduction
		1.1 Our Contribution
	2 Literature Review
	3 Dataset Description
		3.1 UCI-HAR Dataset
		3.2 WISDM Dataset
	4 Data Preprocessing
		4.1 Linear Interpolation
		4.2 Scaling and Normalization
		4.3 Segmentation
	5 Proposed Methodology
		5.1 Bidirectional Gated Recurrent Unit
		5.2 Convolutional and Max Pooling Layers
	6 Experiments and Results
		6.1 Model Implementation
		6.2 Performance Measure
		6.3 Evaluation of Two Datasets
		6.4 Conclusion
	References
Classification of Indoor–Outdoor Scene Using Deep Learning Techniques
	1 Introduction
	2 Literature Review
	3 Research Methodology
	4 Results and Discussion
	5 Conclusion
	6 Future Work
	References
Prediction of the Reference Evapotranspiration Data from Raipur Weather Station in Chhattisgarh using Decision Tree-Based Machine Learning Techniques
	1 Introduction
	2 Study Site and Dataset
		2.1 Study Site
		2.2 Dataset
	3 Methods
		3.1 Preprocessing
		3.2 Input Variables Selection
		3.3 Decision Tree-Based Machine Learning Techniques
		3.4 Performance Evaluation Criteria
	4 Results and Discussions
	5 Conclusion
	References
Application of 1-D Convolutional Neural Network for Cutting Tool Condition Monitoring: A Classification Approach
	1 Introduction
	2 Machining and Data Collection
	3 Data Augmentation
	4 2-D Convolution Neural Networks
		4.1 Layers in CNN
		4.2 Activation and Loss Functions
	5 1-D Convolution Neural Network
	6 Hyper Parameter Tuning
	7 Results and Discussion
	8 Conclusion and Futuristic Directions
	References
Image Processing and Computer Vision
Wireless Surveillance Robot for Industrial Application
	1 Introduction
	2 Related Work
	3 Proposed Design
	4 System Description
		4.1 Surveillance
		4.2 Object Detection and Tracking
		4.3 Object Chasing and Obstacle Handling
	5 Experiment
		5.1 Activation of VNC Server
		5.2 Live Streaming
		5.3 Image Processing
		5.4 Object Detection and Tracking
	6 Performance
	7 Results
	8 Conclusion
	9 Future Scope
	References
An Iterative Posterior Regularized NMF-Based Adaptive Wiener Filter for Speech Enhancement
	1 Introduction
	2 Regularized NMF and Adaptive Wiener Filtering
		2.1 Adaptive Wiener
	3 Iterative Posterior Regularized NMF-Based Adaptive Wiener Filter Method
	4 Experimental Results
	5 Conclusion
	References
ADASemSeg: An Active Learning Based Data Adaptation Strategy for Improving Cross Dataset Breast Tumor Segmentation
	1 Introduction
	2 Background
		2.1 Semantic Segmentation
		2.2 Active Learning
	3 Data and Methods
		3.1 Dataset Description
		3.2 Proposed Methodology
	4 Experimental Setup
	5 Results and Discussion
	6 Conclusion
	References
Dense Disparity Map Generation for Images Captured by Lunar Rover Navigation Camera
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Camera Calibration
		3.2 Image Rectification
		3.3 Stereo Anaglyph
		3.4 Disparity Estimation
	4 Results
		4.1 Quantitative Analysis on the Standard Dataset
		4.2 Qualitative Analysis
		4.3 Occlusion Handling for a Wide-Baseline Stereo Camera (Modified-SGM)
	5 Conclusion and Future Directions
	References
Threat Detection in Self-Driving Vehicles Using Computer Vision
	1 Introduction
	2 Background and Related Work
	3 Methodology
		3.1 System Overview
		3.2 System Architecture
	4 Observations and Results
		4.1 Region of Interest
		4.2 Depth Estimation
	5 Conclusion and Future Scope
	References
Natural Language Processing
KDC: New Dataset for Kannada Document Categorization
	1 Introduction
		1.1 Previous Work on Other Kannada Datasets
	2 A Dataset for Kannada Document Classification
		2.1 Main Challenges in Creating the Dataset
	3 Methodology Used to Validate the New Dataset
		3.1 Tokenization
		3.2 Unicode Encoding
		3.3 Vector Space Model
		3.4 Classifiers
	4 Experiments and Results
		4.1 K-Nearest Neighbor Classifier
		4.2 Support Vector Machine
		4.3 Multinomial Naïve Bayes Classifier
		4.4 Decision Tree
		4.5 Multilayer Perceptron
	5 Conclusion
	References
The Ties that Matter: From the Perspective of Similarity Measure in Online Social Networks
	1 Introduction
	2 Problem Definition
	3 Related Work
	4 Proposed Approach
		4.1 Preliminaries
		4.2 Neighborhood Density-Based Edge Similarity
		4.3 Time Complexity
	5 Experimental Analysis
		5.1 Result Analysis
	6 Conclusion
	References
Comparative Study of Abstractive Summarizers (Sequence2Sequence Models)
	1 Introduction
	2 Literature Review
	3 Methodology
		3.1 Text Preprocessing
		3.2 Word Embeddings
		3.3 Extractive Summarizer
		3.4 Abstractive Summarizer
	4 Implementations
		4.1 Datasets
		4.2 Training
	5 Results
	6 Comparative Analysis
	7 Future Improvements
	8 Conclusion
	References
Comparative Analysis of Lexicon-Based Emotion Recognition of Text
	1 Introduction
	2 Related Work
		2.1 Machine Learning Approach
		2.2 Lexicon-Based Approach
	3 Automatic Emotion Classification
		3.1 Data Source
	4 Evaluation
	5 Conclusion
	References
A Comprehensive Understanding of Text Region Identification and Localization in Scene Imagery Using DL Practices
	1 Introduction
		1.1 Problem Overview
	2 Previous Work
		2.1 Before Deep Learning Era
		2.2 DL-Based Methodologies
	3 Feature Extraction Model
	4 Prediction Model
	5 Benchmark Datasets
	6 Conclusions and Future Perspective
	References
TCRKDS: Towards Integration of Semantic Intelligence for Course Recommendation in Support of a Knowledge Driven Strategy
	1 Introduction
	2 Related Works
	3 Proposed System Architecture
	4 Implementation
	5 Results and Performance Evaluation
	6 Conclusions
	References
Network Security and IoT
Developing MCDM-Based Technique to Calculate Trustworthiness of Advertised QoE Parameters in Fog Computing Environment
	1 Introduction
	2 Related Work
	3 Proposed Framework
	4 Performance Analysis
	5 Conclusion
	References
Data Clustering Approach on the Basis of Data Sensitivity for Implementation of Secure Cloud Computing Environment
	1 Introduction
	2 Related Work
	3 Method
	4 Results and Discussion
	5 Conclusion
	References
An Approach for Energy-Efficient Resource Allocation Through Early Planning of Virtual Machines to Servers in Cloud Server Farms
	1 Introduction
	2 Related Work
	3 Proposed Work
		3.1 Early Planning
		3.2 Algorithm
	4 Results and Discussion
	5 Conclusion
	References
negSPUC: Trees-Based Single-Phase High-Utility Itemset Mining Algorithm with Negative Profit Values
	1 Introduction
	2 Background
		2.1 Related Work
	3 Methodology
		3.1 Utility Count Tree and String Utility Tree
		3.2 negSPUC Algorithm
		3.3 Experimental Evaluation
	4 Conclusion
	References
LoRa-Based IoT Architecture Using Ant Colony Optimization for Intelligent Traffic System
	1 Introduction
	2 Related Work
	3 Proposed System Architecture
	4 Simulation Results and Discussion
	5 Conclusion and Future Work
	References
Energy Saving Techniques for Cloud Data Centres: An Empirical Research Analysis
	1 Introduction
	2 Background
		2.1 Motivation
	3 Literature Review
		3.1 Node Management
		3.2 Virtualisation and Consolidation
		3.3 Task Scheduling
		3.4 Data Placement
		3.5 Infrastructure Change
	4 Experiment
		4.1 Set-up
		4.2 Findings and Interpretation
	5 Discussion
	6 Possible Directions for Future Research
	7 Conclusion
	References
Preliminary Conceptions of a Remote Incoercible E-Voting Scheme
	1 Introduction
	2 Related Works
	3 Cryptographic Tools
		3.1 Confirmation Numbers (CNs)
		3.2 CR-SVRM
		3.3 Check Codes and Encrypted Unknown Integer Pairs
		3.4 Secret Key Anonymous Tag Based Credentials
	4 SK-CRVS
		4.1 Preparation Stage
		4.2 Registration Stage
		4.3 Voting Stage
		4.4 Tallying Stage
		4.5 Vote Correction Stage
	5 Preliminary Evaluation
		5.1 Satisfied Requirements
		5.2 Computation Volumes and Comparisons
	6 Conclusions
	References
Evaluating Data Migrations with Respect to Interoperability in Hybrid Cloud
	1 Introduction
	2 Background
	3 Related Work
	4 Research Aim
	5 Existing Methodologies
	6 Simulation of Data Migration in Hybrid Cloud
	7 Results and Discussion
	8 Conclusions
	References
Secure Management of Digital Academic Certificates Using Blockchain Technology
	1 Introduction
	2 Related Works
	3 Preliminaries
	4 Proposed Method
		4.1 Our Proposed Genesis Block Structure
		4.2 Our Proposed General Block Structure
		4.3 Our Proposed Method and Discussions
	5 Conclusion
	References
Tracking of Fall Detection Using IMU Sensor: An IoHT Application
	1 Introduction
		1.1 Overview
		1.2 Our Contribution
	2 Literature Review of Related Works
		2.1 Related Works
	3 Preliminaries
	4 Proposed Methodology
		4.1 Dataset Acquisition
		4.2 Dataset Preprocessing
		4.3 Data Presentation
		4.4 Proposed Architecture
		4.5 Proposed Algorithm
	5 Results and Discussions
		5.1 Observation from Data
		5.2 Performance Measurement Analysis
	6 Conclusion, Limitation and Future Research Direction
		6.1 Conclusions
		6.2 Limitation and Future Research Direction
	References
Avenues of Graph Theoretic Approach of Analysing the LIDAR Data for Point-To-Point Floor Exploration by Indoor AGV
	1 Introduction
	2 Related Work
	3 Methodology
	4 Analysis of Algorithms
		4.1 YOLOv4 for Object Detection
		4.2 Analysis of Path Planning Techniques
	5 Experimental Analysis
	6 Conclusion
	References
Combined Cryptography and Text Steganography for Enhanced Security Based on Number System
	1 Introduction
	2 Previous Work
		2.1 Hide in a Text
		2.2 Based on Format
		2.3 Word Shift Coding
		2.4 Line Shift Coding
		2.5 Random and Statistical Generation Methods
		2.6 Linguistics Method
		2.7 Feature Coding
		2.8 Other Methods
	3 Proposed Method
	4 Technological and Hypothetical Background
		4.1 Encryption Process
		4.2 Decryption Process
	5 Conclusion
	6 Future Scope
	References
Analysis of Mirai Malware and Its Components
	1 Introduction
	2 Background
	3 Mirai Malware
		3.1 Mirai Requirements
		3.2 Mirai Implementations
		3.3 Existing Solutions for Mitigating Mirai
	4 Related Work
		4.1 Downloader File
		4.2 Mirai File
		4.3 HTTP Server
		4.4 DNS Server
		4.5 Loader Server
		4.6 Scanlisten Server
		4.7 C&C Server
		4.8 Bot Device
	5 Conclusion and Future Work
	References
Realization of 5G NR Primary Synchronization Signal Detector Using Systolic FIR Filter
	1 Introduction
	2 Systolic FIR Filter
		2.1 Proposed Algorithm for Systolic FIR Filter
	3 Design of High-Speed MAC Units
		3.1 Design of 16-Bit Carry Select Adder
		3.2 Design of 8-bit Vedic Multiplier
	4 5G NR Cell ID Detection Using Proposed Systolic FIR Filter
	5 Simulation Results
	6 Conclusion
	References
Composition of Static and Dynamic Analysis for Algorithmic-Level Code Semantic Optimization
	1 Introduction
	2 Literature Survey
		2.1 Dynamic Versus Static Optimization Techniques for Object-Oriented Languages [2]
		2.2 Predicting Execution Time of Computer Programs Using Sparse Polynomial Regression [3]
		2.3 Automatic Algorithmic Complexity Determination Using Dynamic Program Analysis [4]
		2.4 Cisco EIGRP Metric [5]
	3 System Architecture
	4 Dataset
	5 Dynamically Calculated Metrics
		5.1 Architecture
		5.2 Input Generator
		5.3 Polynomial Regression
		5.4 Time and Memory Metric Value Calculation
	6 Statically Calculated Metrics
		6.1 Cyclomatic Complexity
		6.2 Halstead Difficulty Metric
		6.3 Composition of Metrics
	7 Results
	8 Future Work
	9 Conclusion
	References
A Framework for DDoS Attack Detection in SDN-Based IoT Using Hybrid Classifier
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Classifiers Used
		3.2 Dataset Used
	4 Implementation Environment
	5 Experiments and Discussion
	6 Conclusion and Future Work
	References
Modeling Solar Photo-Voltaic Power Generation System with MPPT Controller
	1 Introduction
	2 Modeling of Photo-Voltaic System
		2.1 Modeling of PV Module
		2.2 Modeling of MPPT Controllers
	3 Step Down Converter
	4 Simulation Result of the Solar PV System Without MPPT Controller and DC–DC Buck Converter
		4.1 Simulation Result with MPPT and Buck Converter
	5 Conclusion
	References