توضیحاتی در مورد کتاب Proceedings of Data Analytics and Management: ICDAM 2021, Volume 1
نام کتاب : Proceedings of Data Analytics and Management: ICDAM 2021, Volume 1
ویرایش : 1st ed. 2022
عنوان ترجمه شده به فارسی : مجموعه مقالات تجزیه و تحلیل داده ها و مدیریت: ICDAM 2021، جلد 1
سری : Lecture Notes on Data Engineering and Communications Technologies, 90; 90
نویسندگان : Deepak Gupta (editor), Zdzislaw Polkowski (editor), Ashish Khanna (editor), Siddhartha Bhattacharyya (editor), Oscar Castillo (editor)
ناشر : Springer
سال نشر : 2022
تعداد صفحات : 849
[821]
ISBN (شابک) : 9811662886 , 9789811662881
زبان کتاب : English
فرمت کتاب : pdf
حجم کتاب : 18 Mb
بعد از تکمیل فرایند پرداخت لینک دانلود کتاب ارائه خواهد شد. درصورت ثبت نام و ورود به حساب کاربری خود قادر خواهید بود لیست کتاب های خریداری شده را مشاهده فرمایید.
توضیحاتی در مورد کتاب :
این کتاب شامل مشارکتهای منتشر نشده اصلی است که در کنفرانس بینالمللی تجزیه و تحلیل دادهها و مدیریت (ICDAM 2021)، که در دانشگاه یان ویزیکوفسکی، لهستان، در ژوئن 2021 برگزار شد، ارائه شده است. این کتاب موضوعاتی در تجزیه و تحلیل داده، مدیریت داده، دادههای بزرگ را پوشش میدهد. ، هوش محاسباتی و شبکه های ارتباطی. این کتاب کار نوآورانهای توسط دانشگاهیان، محققان و کارشناسان برجسته صنعت ارائه میکند که برای محققان و دانشجویان جوان مفید است.
فهرست مطالب :
ICDAM 2021 Steering Committee Members
Advisory Committee
Preface
Contents
About the Editors
Psychological Stress and Mental Health Among Seafarers
1 Introduction
2 Methods
3 Results
4 Discussion
5 Conclusions
6 Recommendations
References
Real-Time Face Mask Detection and Analysis System
1 Introduction
2 Description of Tools
2.1 OpenCV
2.2 TensorFlow
3 Related Work
4 Proposed Work
5 Methodology
5.1 Model Architecture
5.2 Approach
5.3 Result Analysis and Discussion
6 Conclusion
References
Performance Evaluation of Brahmagupta-Bhaskara Equation Based Algorithm Using OpenMP
1 Introduction
2 Related Works
3 Evaluation of Speed-up Factor and Efficiency
4 Cost and Effort Evaluation Using COCOMO
5 Conclusion
References
Gait Recognition Biometric System
1 Introduction
1.1 Overview
1.2 Gait Biometric Recognition
2 Literature Review
2.1 Gait over Other Biometrics
2.2 Gait over Other Biometrics
2.3 Related Work Done in Gait Analysis Techniques
3 Proposed Model
3.1 Project Requirements
3.2 Standard Terminology
3.3 Approach
4 Scope of the Proposed Model
5 Result
6 Conclusion
References
A New MCDM Approach to Solve a Laptop Selection Problem
1 Introduction
2 Materials and Methods
2.1 Step-Wise Weight Assessment Ratio Analysis (SWARA)
2.2 Simple Multi Attribute Rating Technique (SMART)
2.3 Complex Proportional Assessment (COPRAS)
2.4 Additive Ratio Assessment (ARAS)
3 Result and Discussion
4 Conclusion
References
Fighting Media Hyper-partisanship with Modern Language Representation Models
1 Introduction
2 Related Work
3 Training Data
4 Methodology
4.1 Data Preprocessing
4.2 Sentence Embeddings
4.3 Binary Classification Model
5 Results
6 Discussion
7 Conclusion
References
Hyperparameter Tune for Neural Network to Improve Accuracy of Stock Market Prediction
1 Introduction
2 Data Processing
3 Experimental Study
4 Artificial Neural Network
5 Methodology
6 Result Discussion and Conclusion
References
ANN-Based Handwritten Digit Recognition and Equation Solver
1 Introduction
2 Literature Survey
3 Proposed Work
3.1 Data Set Description
3.2 Methodology
4 Results and Discussion
5 Conclusion and Future Work
References
Intrusion Detection Protocol Using Independent Outlier Ensembles
1 Introduction
2 Related Works
2.1 Independent Outlier Ensembles
2.2 Network Intrusion Detection Using Outlier Detection Techniques
3 Data and Methods
3.1 Dataset
3.2 Methodology
4 Experimental Results
5 Conclusion
References
Hybrid Context-Based Recommendation for Media
1 Introduction
2 Related Work
3 Methods Involved
3.1 Content-Based Recommendation
3.2 Collaborative Filtering
3.3 Pre-Contextual Filtering
4 Proposed Hybrid Recommendation Engine
4.1 Proposed Approach
4.2 Evaluation Metrics
5 Experimental Results
6 Conclusion and Future Scope
References
Hyperspectral Imaging in Document Forgery
1 Introduction
2 Framework
3 Writer Detection
4 Ink Detection
4.1 Unsupervised Techniques
4.2 Supervised Techniques
5 Miscellaneous Methods
6 Comparison Between Various Works
7 Conclusion and Future Work
References
A Review: Trust Management Techniques Used for Cloud Computing
1 Introduction
2 Cloud Computing Landscape
2.1 Service Delivery Model
2.2 Cloud Building Deployment Model
2.3 Cloud Entities
2.4 Issues with Cloud Computing
3 Trust Management System
3.1 Nature of Trust [5, 13, 14]
3.2 Principles of Trust for effective Trust Management System [15]
3.3 Trust Management Techniques
3.4 Comparison of Trust Management Techniques [17]
3.5 QoS(Quality Of Service) For TMS
3.6 Challenges for TMS
4 Survey of Existing Trust Management Model
5 Conclusion
References
Optimized Usability Features of Academic Websites Using Chicken Swarm and Cat Swarm Optimization Algorithm
1 Introduction
2 Related Work
3 Methodology
3.1 Preprocessing
3.2 Chicken Swarm Optimization
3.3 Cat Swarm Optimization
4 Implementation
4.1 Input Parameters
4.2 Dataset Description
5 Results and Discussion
6 Conclusion and Future Work
References
Traffic Signal Control Methods: Current Status, Challenges, and Emerging Trends
1 Introduction
2 Overview of Traffic Light Control Technology
3 Existing Algorithms for Traffic Signal Control
3.1 Traditional Approach
3.2 Sensor Based Approach
3.3 Vision Based Approach
3.4 Evolutionary Algorithm and Swarm Optimization Based Approach
3.5 Connected Vehicle Based Approach
3.6 Fuzzy Logic Based Approach
3.7 Learning Based Approach
4 Networking of Traffic Lights: Where Are We Now?
5 Discussion and Open Issues
6 Conclusion
References
Study and Development of Self Sanitizing Smart Elevator
1 Introduction
2 Literature Review
3 Feature Extraction
3.1 Hardware Requirements for Different Processes
3.2 Methodology
3.3 Our Contribution on the Subject
4 Proposed System Overview
4.1 Calling the Elevator
4.2 Sanitizing the Elevator
4.3 Entering the Floor Number
4.4 Facial Recognition and Body Temperature Measurement
4.5 Notifying the User
5 Results
6 Conclusion
References
Predict COVID-19 with Chest X-ray
1 Introduction
2 Literature Review
3 Proposed System Overview
4 Feature Extraction
4.1 Methodology
4.2 Model Formulation
4.3 Inception Net V3
4.4 XCeption Net
4.5 ResNeXt
5 Experimental Result
6 Advantages
7 Conclusion
References
A Systematic Approach to mHealth in COVID-19: Patient Generated Health Data on Opportunities and Barriers for Transforming Healthcare
1 Introduction
2 Generation of PGHD
3 Capacity of PGHD
4 Methodology
5 Challenges to PGHD
6 Result
7 Discussion
8 Conclusion
References
Handwritten Offline Devanagari Compound Character Recognition Using CNN
1 Introduction
2 Literature Review
3 Devanagari Script
4 Proposed Methodology
5 Experimental Results
6 Results and Discussion
7 Conclusion
References
GA–JAYA: A Novel Hybridization Technique to Solving Job Scheduling Problems
1 Introduction
2 Related Work
3 Identify the Problem
4 JAYA Algorithm
5 Proposed Method
6 Result and Discussion
7 Conclusion
References
Image Segmentation Techniques: A Survey
1 Introduction
2 Related Work
2.1 Edge-Based Image Segmentation Technique
2.2 Region-Based Image Segmentation Technique
2.3 Clustering-Based Image Segmentation Technique
2.4 Threshold-Based Image Segmentation Technique
2.5 Soft Computing-Based Image Segmentation Techniques
3 Application and Limitation of Methods
4 Conclusion and Future Scope
References
Low-Cost IoT Framework for Indian Agriculture Sector: A Compressive Review to Meet Future Expectation
1 Introduction
2 Literature Review
2.1 Automatic Recognition of Soybean Leaf Diseases Using UAV Images and Deep Convolutional Neural Networks
2.2 An IoT-Based Smart Solution for Leaf Disease Detection
2.3 A Low-Power Wide-Area Network Information Monitoring System by Combining NB-IoT and LoRa
2.4 Internet of Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk
2.5 A Low-Power IoT Network for Smart Agriculture
2.6 Internet of Things in Agriculture, Recent Advances, and Future Challenges
2.7 An Automated Approach for Classification of Plant Diseases Toward Development of Futuristic Decision Support System in Indian Perspective
2.8 Thorough Study of LoRaWAN Performance Under Different Parameter Settings
2.9 Analysis of Latency and MAC-Layer Performance for Class A LoRaWAN
2.10 On the Use of LoRaWAN for Indoor Industrial IoT Applications
2.11 Identification of Plant Diseases Using Convolutional Neural Networks
2.12 Disease Detection in Crops Using Remote Sensing Images
2.13 Low-Cost Green Power Predictive Farming Using IOT and Cloud Computing
2.14 Wheat Disease Detection Using Image Processing
2.15 Smart Farming: Pomegranate Disease Detection Using Image Processing
3 Discussion and Inference on Literature Survey
4 Inference on Literature Survey
5 Conclusion
References
Machine Learning-Based Breeding Values Prediction System (ML-BVPS)
1 Introduction
2 Problem Statement
3 Proposed Model
4 Results Discussion and Comparative Analysis
5 Conclusion
References
Machine Learning Based Supraventricular Tachycardia Detection Model of ECG Signal
1 Introduction
1.1 Electrocardiogram Signals
1.2 Supraventricular Tachycardia Arrhythmias
1.3 Related Works
1.4 Our Contributions
2 Method
3 Result and Discussion
3.1 Material
3.2 Simulation Results
4 Conclusion
References
Quantum-Inspired Support Vector Machines for Human Activity Recognition in Industry 4.0
1 Introduction
2 Literature Review
3 Description of Quantum-Inspired Support Vector Machine (QSVM)
4 Experiment and Results
5 Conclusions
References
A Master Data Management Solution for Building Frameworks: A Constructive Way to Pilot the Implementation
1 Introduction
2 MDM Catalog
2.1 MDM Components
2.2 Hype Cycle
3 Research Methodology
4 Key Parameters for MDM Implementation
5 Study of Recent Hype Cycles
6 Proposed Strategic Solution for Implementing MDM
6.1 Framework for MDM
6.2 Roadmap for Implementing MDM
6.3 Data Flow Diagram
7 Conclusion
References
A Heuristic Approach to Extract Knowledge from the Text Considering Explicit and Implicit Features Both
1 Introduction
2 Proposed Method
3 Framework for Knowledge Extraction
4 Experiment and Result
5 Conclusion
References
Hybrid System Based on Genetic Algorithm and Neuro-Fuzzy Approach for Neurodegenerative Disease Forecasting
1 Introduction
2 Related Work
3 Proposed Hybrid Model
3.1 Genetic Algorithm
3.2 Adaptive Neuro-Fuzzy Inference System (ANFIS)
4 Methodology
5 Results and Discussion
6 Conclusion and Future Scope
References
Envisaging Industrial Perspective Demand Response Using Machine Learning
1 Introduction
2 Related Work
3 Industry 4.0
3.1 Predictive Maintenance in Machine Learning
3.2 Predictive Analysis Using Machine Learning
4 Industry 4.0 Environment Case Study
4.1 Data Description
4.2 Data Pre-processing
5 Results
6 Conclusion and Future Work
References
K-Prototype Algorithm for Clustering Large Data Sets with Categorical Values to Established Product Segmentation
1 Introduction
2 Methodology
3 Experimental Setup
3.1 Data Set
3.2 Tools Used
4 Analysis of Data Set
4.1 Simple Statistical Analysis
4.2 Distribution of Sales in Each Region
4.3 Developing Clusters
5 Conclusion
References
Decentralized Library Management System Using Blockchain Technology
1 Introduction
2 Blockchain
2.1 Applications
3 Related Work
4 Proposed System
4.1 Framework
4.2 Implementation and Result
5 Comparison Between Existing and Proposed System
6 Conclusion
References
Latent Dirichlet Allocation (LDA) Based on Automated Bug Severity Prediction Model
1 Introduction
2 Literature Survey
3 Methodology
3.1 Data Description
3.2 Pre-Processing of Data
3.3 Topic Modelling
3.4 Classification Techniques
3.5 Performance Measure
4 Performance Analysis
5 Conclusion
6 Future Scope
References
A Novel Approach of Transfer Learning for Satellite Image Classification
1 Introduction
2 Literature Review
3 Methodology
3.1 Datasets
3.2 The Architecture of the Pre-trained Model
3.3 The Architecture of the VGG16 Network
3.4 Architecture of ResNet50
3.5 The Architecture of Xception Network
4 Results
5 Conclusion and Future Scope
References
Damage Identification in High-Rise Buildings Using Deep Learning Techniques
1 Introduction
2 Methodology
3 Deep Learning Algorithms
4 Results and Discussion
5 Conclusion
References
AI-Driven Fraud Detection and Mitigation in e-Commerce Transactions
1 Introduction
2 Fraud Detection Techniques
2.1 Rule-Based Versus Machine Learning Systems in Fraud Detection
2.2 Big Data and AI Techniques for Fraud Detection
2.3 Fraud Detection in e-Commerce Transactions
3 Types of e-Fraud
3.1 Identity Theft
3.2 Phishing
3.3 Website Cloning (Spoofing)
3.4 Virtual Casinos (Internet Gambling)
3.5 Electronic Cheque Frauds
3.6 Lottery Frauds
3.7 Automated Clearing House (ACH) Frauds
3.8 Nigerian Advance Fee Fraud (419 Fraud)
4 Security of e-Payment
4.1 Secure Socket Layer (SSL)
4.2 Secure Communication Tunnel for Secure e-Payment System
4.3 Server Firewalls (Software or Hardware Firewalls)
5 Fraud Mitigation and Control Strategies
6 Conclusion
References
COVID-19 Vaccination Monitoring Using IoT and Machine Learning
1 Introduction
2 Related Work
3 Intelligent IoT in COVID-19
4 Data Analysis
4.1 Datasets
4.2 Vaccines Analysis
4.3 Prediction Using Regression
4.4 Continentwise Daily Vaccination
4.5 Country Wise Vaccination
4.6 Vaccination in India
5 Conclusion
References
An Efficient Feature Extraction Technique for Brain Tumor Detection Using GUI
1 Introduction
1.1 Problem Statement
2 Related Work
3 Proposed Algorithm
4 Experimental Results
4.1 Evaluation Matrix
5 Conclusion and Future Direction
References
Content-Based Image Retrieval Using Deep Learning
1 Introduction
1.1 Problem Statement
2 Related Work
3 Proposed Algorithm
3.1 Feature Extraction Technique
4 Experimental Results
4.1 Evaluation Matrix
4.2 Performance Analysis
5 Conclusion and Future Direction
References
Diagnosis and Detection of Plant Diseases Using Data Mining Techniques
1 Introduction
2 Literature Review
3 Related Works
4 Plant Disease Detection Process
4.1 Image Acquisition
4.2 Image Segmentation
4.3 Feature Extraction Process and Classification
5 Proposed Model
6 Discussion
7 Conclusion
References
Artificial Intelligence in Healthcare: Diabetic Retinopathy
1 Introduction
2 Information Processing
3 Prediction and Diagnosis of Diseases
4 Diabetic Retinopathy and Artificial Intelligence
4.1 Diabetic Retinopathy
4.2 Problem and Solution
4.3 Algorithm
4.4 Result
5 Challenges and Conclusion
5.1 Challenges
5.2 Conclusion
References
Prediction of Heart Disease and Chronic Kidney Disease Based on Internet of Things Using RNN Algorithm
1 Introduction
2 Related Works
3 Proposed Methodology
3.1 Neural Network Model
3.2 K-Nearest Neighbours for Feature Extraction
3.3 Recurrent Neural Network (RNN)
3.4 Data Set
3.5 Data Transformation for CKD
4 Evaluation Parameters
4.1 Precision and Recall
4.2 Accuracy
4.3 Confusion Matrix
5 Conclusion and Future Work
References
Using Big Data Analytics to Analyze Pre- and Post-launch Emotions: A Study of Apple’s iPhone 12
1 Introduction
2 Related Work
3 Methodology
3.1 Data Collection
3.2 Data Preprocessing
3.3 Data Analysis
4 Results and Discussions
4.1 Pre-launch
4.2 Post-launch
5 Conclusion
References
A Deep Learning-Based Feature Extraction Model for Classification Brain Tumor
1 Introduction
2 Literature Review
3 Problem Identification
4 Dataset
5 Proposed Model
6 Results and Discussion
7 Conclusion
References
Normalized Feature Plane Alteration for Dental Caries Recognition
1 Introduction
2 Motivation and Related Work
3 Methodology
4 Preprocessing Results
5 Results
6 Conclusion
References
Performance Analysis of Smart System with Algorithmic Optimization for Cavities Detection
1 Introduction
1.1 Related Works
2 Materials and Methods
2.1 Pre-processing
2.2 Feature Extraction via MPCA
2.3 Classification
2.4 Computation of Distance Measure
2.5 Nonlinear Programming Optimization
2.6 Theory/Calculation
3 Results
3.1 Performance Analysis
4 Discussion
5 Conclusion
References
Image Classification in Python Using Keras
1 Introduction
2 Related Work
3 Literature Review
4 Implemented Method
5 Dataset
6 Neural Networks
7 Layers of Convolutional Neural Networks
8 Preparing Database
9 Explanation of the Model
10 Optimizing Model with SGD
11 Training Model
12 Result and Interpretation
13 Conclusion
References
Predictive Analytics on E-commerce Annual Sales
1 Introduction
2 Literature Review
3 Research Methodology
4 ARIMA (Auto Regressive Integrated Moving Average)
4.1 Stationary Test (Augmented Dickey-Fuller (ADF) Test)
5 Forecasting
6 Conclusion
References
Proposed Method to Identify Oil Seed Leaf Diseases by Deep Learning Techniques
1 Introduction
2 Related Work
3 Proposed Work and Methodology
4 Tools and Technology Used
5 Expected Outcome
6 Conclusion
References
Heart Disease Detection Using Feature Selection Based KNN Classifier
1 Introduction
2 Related Work
3 Subject Datasets
4 Implementation Mechanism
4.1 Data Preprocessing
4.2 Application of KNN
4.3 Application of LASSO
5 Results and Findings
6 Conclusion
References
Clustering-Based Hybrid Approach for Wind Speed Forecasting
1 Introduction
2 Time Series Data Clustering
3 Statistical Models for Wind Speed Forecasting
3.1 Autoregressive Integrated Moving Average Model (ARIMA)
3.2 Seasonal Autoregressive Integrated Moving Average (SARIMA)
4 Proposed Hybrid Methodology
5 Research Design and Analysis
5.1 Dataset
5.2 Performance Measuring Criteria
5.3 Result Analysis
6 Conclusion
References
Data Analytics and Visualization to Aid Mental Health Care
1 Introduction
2 Material and Methods
2.1 Study Design
2.2 Evaluation of Dataset/Survey
2.3 Ethical Consideration
3 Result and Discussion
3.1 General Data Statistics
3.2 Mental Health Disorder Distribution
3.3 COVID-19 Impact on Mental Health
3.4 Mental Illness Versus Marital Status
3.5 Illness Family History Versus Willingness to Discuss It with Other
3.6 Occupation Versus Mental Illness
3.7 Mental Health Versus Physical Health
4 Conclusion
References
Baseline Evaluation of COVID-19 Impact on Developing Countries Workforce by Machine Learning
1 Introduction
2 Related Works
3 Dataset Description
3.1 Dataset Collection
3.2 Features Description
3.3 Targets Description
4 Feature Selection
5 Methodology
5.1 Dataset Preparation
5.2 Classification and Regression
5.3 Proposed Model
6 Experimental Result and Analysis
6.1 Experimental Environment
6.2 Statistical Data Analysis
6.3 Machine Learning Results and Analysis
7 Summary of the Findings
8 Conclusion
References
A Survey on Deep Learning Methods in Image Analytics
1 Introduction
2 Deep Learning Applications in Image Analytics
2.1 Use of Deep Learning in Feature Extraction and Image Segmentation
2.2 Image Classification Using Deep Neural Networks
3 Deep Learning Historical Analysis
4 Methods
4.1 Unsupervised Learning
4.2 Web-Based Learning
4.3 Optimization Approaches
4.4 Usage of Distributed Systems in Deep Learning
4.5 Frameworks
5 Dataset in Deep Learning
6 Key Challenges in Deep Learning
7 Future Scope
8 Conclusion
References
An Estimation of PCA Feature Extraction in EEG-based Emotion Prediction with Support Vector Machines
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Existing Method
3.2 Proposed Method
3.3 Preprocessing
3.4 Feature Extraction Using Principal Component Analysis
4 Discussion
4.1 Support Vector Machine
4.2 Multiclass Support Vector Machine
4.3 Performance Analysis
5 Conclusion
References
Real-Time Anomaly Detection Surveillance System
1 Introduction
2 Literature Survey
2.1 Research Gaps
3 Research Methodology
3.1 Data Set
3.2 Alarm System
3.3 Future Scope
4 Results and Discussions
5 Conclusion
References
Design of an iOS App Architecture for Cotton Plant Disease Detection Using Artificial Intelligence and Machine Learning Techniques
1 Introduction
2 Related Work
3 Methodology of Proposed Architecture
3.1 System Architecture—Overview
3.2 Architecture Principles
3.3 Design Pattern
3.4 Dependency Injection
3.5 Database—Core Data
3.6 Programming
4 Performance Analysis
4.1 Static Code Analyzer
4.2 Instruments
5 Results
6 Conclusion
References
Unknown Attack Detection in Cloud Based on Correlation Analysis
1 Introduction
2 Proposed Unknown Attack Detection Scheme for Cloud
2.1 Data Pre-processing
2.2 Correlation Coefficient Computation
2.3 Correlation to Euclidean Distance Conversion
2.4 Hierarchical Clustering
3 Results and Discussion
4 Summary
References
Song/Music Recommendation Using Convolutional Neural Network and Keylogger
1 Introduction
1.1 Targeting Milestones
1.2 Literature Review
2 Facial Emotion Detector
2.1 Typing Speed Detector (Keylogger)
2.2 Song/Music Generation
3 Results and Discussions
4 Conclusion
References
Journey of Letters to Vectors Through Neural Networks
1 Introduction
2 Preliminary Exertion
3 Model Analysis Involving Deep Learning Techniques
4 Conclusion
References
A Dynamic Approach of Eye Disease Classification Using Deep Learning and Machine Learning Model
1 Introduction
1.1 Motivation
1.2 Contribution
1.3 Uniqueness of the Paper
1.4 Organization
2 Related Works
3 Proposed Approach
3.1 Dataset Description
3.2 Scaling of Images
3.3 Label Encoding of Columns
3.4 Splitting the Dataset into Training Set and Testing Set
3.5 Building of Convolution Neural Network Model
3.6 Configuring of CNN Model
3.7 CNN Training and Evaluation of Accuracy
3.8 SVM
4 Performance Evaluation
4.1 Discussion on Results
5 Conclusion
References
Feature and Decision Fusion for Breast Cancer Detection
1 Introduction
2 Literature Review
3 Materials and Methods
3.1 Datasets
3.2 Preprocessing
3.3 Feature Extraction, Selection, and Feature Fusion
3.4 Classification and Decision Fusion
4 Results
5 Conclusion
References
Hybridization of Harmony and Cuckoo Search for Managing the Task Scheduling in Cloud Environment
1 Introduction
2 Related Work
3 Background Work
4 Problem Formulation and Proposed Framework
5 Experimental Result Evaluation
6 Conclusion and Future Scope
References
Accident Risk Prediction and Location Tracking of a Vehicle Using Real-Time Data Acquisition from Vehicle Sensors
1 Introduction
2 Motivation
3 Related Work
4 Methodology
4.1 Location Tracking
4.2 Accident Risk Prediction
5 Proposed Architecture
5.1 Overview of the Location Tracking Web App-DTU Shuttle
5.2 Real-Time Accident Risk Prediction Using Web IoT Platform
5.3 Model Implementation
6 Model Evaluation
6.1 Accuracy
6.2 Recall
6.3 F1 Score
6.4 ROC
7 Discussion
7.1 Comparative Analysis
8 Conclusion
9 Future Scope
References
An Hybrid Approach Based on Clustering and Synthetic Sample Generation for Imbalance Data Classification: ClustSyn
1 Introduction
2 Literature Review
2.1 Generative Data Sampling Methods
2.2 Ensemble Methods
3 ClustSyn: An Hybrid Approach Based on Clustering and Synthetic Sample Generation for Imbalance Data Classification—Methodology
3.1 Clustering Phase
3.2 Synthetic Data Generation Phase
3.3 Ensemble Learning
4 Experimental Results
4.1 Evaluation Parameters and Tools Used
4.2 Performance Measure
4.3 Results
5 Conclusion
References
Multimodal Drowsiness Detection Using HM-LSTM Network
1 Introduction
2 Related Works
2.1 Datasets
2.2 Methods
3 The Real-Life Drowsiness Detection Dataset
4 Methodology
4.1 Blink Detection and Blink Feature Extraction
4.2 Yawn Detection and Yawn Feature Extraction
4.3 Preprocessing Features
4.4 The Model
5 Results
6 Discussion and Comparative Analysis
7 Conclusion
References
Data Augmentation and Fine-Tuning the Radiography Images to Detect COVID-19 Patients with Pre-trained Network of Transfer Learning
1 Introduction
2 Literature Review
3 Methodology
4 Dataset
4.1 VGG-16
5 Results
6 Discussion
7 Conclusion
References
Index Optimization Using Wavelet Tree and Compression
1 Introduction
2 Contribution of Wavelet Tree in Indexing
2.1 Indexing in Wavelet Tree
2.2 Indexing Using Parallel Wavelet Tree
2.3 Indexing in Healthcare and Bioinformatics
3 Proposed Methodology
4 Conclusion and Discussion
References
Author Index
توضیحاتی در مورد کتاب به زبان اصلی :
This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2021), held at Jan Wyzykowski University, Poland, during June 2021. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students.