Universal Threats in Expert Applications and Solutions

Name: Universal Threats in Expert Applications and Solutions | Proceedings of 3rd UNI-TEAS 2024, Volume 1
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Proceedings of 3rd UNI-TEAS 2024, Volume 1

Vijay Singh Rathore Joao Manuel R. S. Tavares B. Surendiran Anil Yadav(Herausgeber*in)

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Erschienen am 3. August 2024

XXII, 507 Seiten

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Prof. (Dr.) Vijay Singh Rathore presently working as Professor-CSE, Jaipur Engineering College & Research Centre, Jaipur (India), and in addition, he is also Chairman, Shree KKarni Universe College, Jaipur, and Membership Chair, ACM Jaipur Chapter, and Past Chairman, CSI Jaipur Chapter. His core research areas include Internet Security, Cloud Computing, Big Data, and IoT. He has organized and participated 25+ National & International Conferences of repute. His foreign visits for various academic activities (Delegate/Invited/Keynote Speaker/Session Chair/Guest) include USA, UK, Canada, France, Netherlands, Singapore, Egypt, Thailand, Vietnam, Nepal, etc. He had been Member of Indian Higher Education Delegation and visited 20+ leading universities at Canada (May, 2019), UK (July, 2017), and USA (Aug, 2018) supported by AICTE and GR foundation. He is Active Academician and always welcoming and forming innovative ideas in the various dimensions of education and research for the better development of the society.

João Manuel R. S. Tavares graduated in Mechanical Engineering at the Universidade do Porto, Portugal in 1992. He also earned his M.Sc. degree and Ph.D. degree in Electrical and Computer Engineering from the Universidade do Porto in 1995 and 2001, and attained his Habilitation in Mechanical Engineering in 2015. He is Senior Researcher at the Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial (INEGI) and Full Professor at the Department of Mechanical Engineering (DEMec) of the Faculdade de Engenharia da Universidade do Porto (FEUP). He is Co-editor of more than 80 books, Co-author of more than 55 book chapters, 650 articles in international and national journals and conferences, and 3 international and 3 national patents. His main research areas include computational vision, medical imaging, computational mechanics, scientific visualization, human-computer interaction, and new product development.

Dr. B. Surendiran is working as Associate Professor, Dept. of CSE, NIT Puducherry, Karaikal. He has more than 16 years of teaching and research experience. He had completed his Ph.D. in the year 2012 from NIT Trichy. His research interests are medical image processing, machine learning, dimensionality reduction, etc. He had 50+ International Journal and Conference Publications to his credit. He has delivered 85+ lectures, reviewed 500+ research papers, and guided 12 Ph.D. scholars. He has received Best Reviewer Award in 2019 by publons.com, Web of Science, and also Outstanding Reviewer Award by Biomedical and Pharmacology Journal in the year 2020. He is Active Reviewer for IEEE sensors, IET image processing, and various SCI/Scopus journals.

Dr. Anil Singh Yadav is Professor in the Department of Mechanical Engineering at IES College of Technology, Bhopal, MP, India. He received his Bachelor's Degree in Mechanical Engineering from Madhav Institute of Technology & Science, Gwalior, MP, India, in 2001. He received his Master's Degree in Thermal Engineering in 2004 and Ph.D. in 2014 from Maulana Azad National Institute of Technology, Bhopal, MP, India. He has more than 22 years of vast teaching experience. His area of research includes CFD modelling and simulation, heat transfer enhancement, solar thermal system and renewable energy conversion. He has published/presented more than 100 research papers to his credit in reputed peer-reviewed national and international journals/conferences. He has also published more than 50 research papers in SCI/SCOPUS indexed journals. He has been granted eleven Indian design patents. His three Indian utility patents have also been published. He authored six books.

Inhalt

Intro
Preface
Acknowledgements
About This Book
Contents
Editors and Contributors
An Advanced Algorithm and Utility for Identifying Critical Web Vulnerabilities with Exceptional Performance
1 Introduction
1.1 Automated Testing Mechanisms
1.2 Use of Machine Learning Techniques
1.3 Techniques for Reducing Input Data Space
1.4 Scanning Tool Development
2 Considered Website Vulnerability
2.1 SQL Injection
2.2 Cross-Site Scripting
3 Related Study
4 Proposed and Improved Algorithms
5 Algorithm for Detecting XSS
6 Enhancing Vulnerability Detection through the Application of Machine Learning
7 Scanning Tool
8 Systematic Flow of GKD Website Scanner
9 Conclusion
References
Potential Impacts of Online-Based Learning 2.0 and Certification on Employability
1 Introduction
1.1 Background
1.2 Statement of the Problem
1.3 Study Rationale
1.4 Purpose of This Work
1.5 Limitations and Scope of the Work
1.6 Research Hypothesis
2 Research Methodology
2.1 The Sample Size of the Work
2.2 Data Collection
3 Data Analysis, Results, and Discussions
3.1 Average Age
3.2 Education Background
3.3 Employment
3.4 Online Certification
3.5 Online-Based Certification Availability
3.6 Online-Based Certification Acceptance
3.7 Online Certification Improves Skill Development
3.8 Online-Based Certification Increases Employability
3.9 Online Learning Fosters the Development of Reflective and Critical Thinking
3.10 Online Education is Useful for a Wide Range of Professions in Many Industries
3.11 Online-Based Learning Provides Knowledge as Required
3.12 Online Learning is Advantageous for Career Development and Ongoing Education
4 Conclusion
References
An Intelligent Self-Driving Car's Design and Development, Including Lane Detection Using ROS and Machine Vision Algorithms
1 Existing Work
2 Proposed System
2.1 Mechanical
2.2 Electrical
2.3 Algorithm and Machine Vision
3 Implementation
3.1 Canny Edge Detection
3.2 Region of Interest
3.3 Hough Transform
3.4 Average Slope Intercept
3.5 Curvature Calculation
3.6 Sliding Window Approach
4 Results and Discussion
5 Conclusion
References
Text Summarization for Kannada Text Documents: A Review
1 Introduction
2 Review of Literature
3 Datasets
3.1 Kannada Treebank
3.2 Kannada-MNIST: A New Handwritten Digit Dataset for the Kannada Language
3.3 Samanantar: Parallel Corpora Collection for 11 Indic Languages
3.4 MLe2e
3.5 IndicCorp
4 Evaluation Measures
5 Conclusion and Future Works
References
Solar Panel Tracking with Battery-Assisted and Battery Charging Modes
1 Introduction
2 Literature Review
3 Methods and Materials
3.1 Implementation Using MATLAB
3.2 Charging Mode
3.3 Discharging Mode
4 Results and Discussion
4.1 Hardware Implementation
5 Conclusion
References
Elevator-Based Earth Tremor Sentinel Technique with MQTT Protocol
1 Introduction
2 Related Work
2.1 Perseverance of Artificial Neural Networks (ANN) in Elevators
2.2 Purpose of Accelerometer in Elevators
2.3 Precedence of MQTT
3 Methodology
3.1 The Layout of the Proposed Model
3.2 Machine Learning Models for Earthquake Detection
3.3 Programming an AI Neural Network
4 Discussion
5 Conclusion
References
An Efficient System Model for Identification of Drug Addiction
1 Introduction
2 Related Work
3 Prpopsed Methodology
3.1 Attribute Selection
3.2 ID3 Algorithm
4 Results and Discussion
5 Conclusion and Future Scope
References
Design and Analysis of a Multipath Routing Protocol to Enhance QoS in MANET
1 Introduction
2 Literature Survey
3 Proposed Work
3.1 Proposed Algorithm
4 Results Analysis
4.1 Simulation Parameters
4.2 Packet Sents
4.3 Packet Receives
4.4 Percentage of Data Receives (PDR)
4.5 Normal Routing Load (NRL)
5 Conclusion
References
Tagging of Uterine Cervix Cases at Cell and Slide Level Through Transfer Learning
1 Introduction
1.1 Deep Neural Network
1.2 Transfer Learning
1.3 ResNet50
1.4 Cervical Cancer
2 Literature Review
3 Material and Method
3.1 Data
3.2 Methodology
4 Result and Analysis
References
Estimation of Medical Expenses Using Machine Learning
1 Introduction
2 Methodology Applied
2.1 Dataset
2.2 Feature Engineering
2.3 Feature Importance Analysis
3 Used Models and Algorithms
4 Experiment Results
5 Conclusion
Challenges in Making OCR of Gujarati Newspaper
1 Introduction
2 Review of Literature
2.1 Review on Segmentation
2.2 Review on Recognition Text
3 Problem in Gujrati Language Newspaper
3.1 Scanner Image Quality
3.2 Background Noise
3.3 Font and Style Variation
3.4 Text Size Variation
3.5 Complex Ligatures in the Script
3.6 Limited Trained Data
4 Observation
5 Conclusion
References
A Hybrid Methodology for Software Development and IT Team Analysis in Manufacturing
1 Introduction
2 Methods
2.1 A Comparison of Project Durations Before and After Model Release
2.2 Before and After the Model's Release on DRE
2.3 A Comparison of the Costs of Development and Maintenance
2.4 Criticality-Based Development to Maintenance Ratio of a Project
2.5 A Maintenance Ratio Determined by the Number of Lines of Code
3 Conclusion
References
AI Enabled Convolutional Neural Networks to Detect Brain Tumors
1 Introduction
2 Literature Review
3 Problem Statement
4 Proposed Methodology
4.1 Image Database
4.2 Data Augmentation with Pre-Processing
4.3 Data Split
5 Results
6 Analysis
7 Conclusion
References
Increasing Productivity in Software Development Through the Use of Docker Technology
1 Introduction of Dockers
1.1 Docker
1.2 Docker File
1.3 Docker Image
2 Experiment
2.1 Docker Java Image File
2.2 Python-Enabled Docker Image File
2.3 Comparative Results
3 Conclusion
4 Future Scope
References
Multimodal Fusion-Based Hybrid CRNN Model for Emotion Prediction in Music
1 Introduction
1.1 Key Contribution
2 Article Organization
3 Related Work
4 Methodology
4.1 Data Description
4.2 Pre-Processing
4.3 Feature Extraction
5 Proposed Model
5.1 Multimodel Fusion
6 Result and Discussion
6.1 Experimental Setup for the Proposed System
6.2 Implementation Details
7 Conclusion
References
Multimodal Analysis of Induction Motor Signals for Power Quality Abnormality Detection Using Wavelet-RBF Approach
1 Introduction
2 Research Contribution
3 Proposed Methodology
3.1 Wavelet Transform
3.2 RBF Neural Networks
4 Result Analysis and Discussion
4.1 Vibration Analysis Using Sensor and Current Transformer
5 Conclusion
References
Smart Electronic Speaking Glove for Physically Challenged Person
1 Introduction
1.1 Research Contribution
2 Proposed Methodology
3 Implementation and Execution
3.1 Hardware Description
3.2 Implemented in Proteus Simulation
4 Result and Discussion
5 Conclusion
References
COVID-19 Detection Using Fourier-Bessel Series Expansion-Based Dyadic Decomposition and Custom CNN
1 Introduction
1.1 Author Contribution
2 Article Organisation
3 Related Work
4 Methodology
4.1 Data Description
4.2 Image Preprocessing
4.3 FBD Methodology
5 Proposed Model
5.1 SMOTETomek
5.2 Keras Tunner
6 Result and Discussion
6.1 Experimental Configuration for the Suggested System
7 Conclusion
References
Instantaneous Interpretation into Sign Language for the Hearing Impaired
1 Introduction
1.1 Feature Extraction
1.2 NLP
1.3 CNN
2 Literature Survey
2.1 Improvement of Speech
2.2 Translation from Speech to Sign Language
2.3 Converter from Speech to Sign Language
3 Proposed Methodology
3.1 Deaf People's Model
3.2 Mute People Model
4 Analysis by Comparison to the Current Model
5 Conclusion
6 Future Scope
References
A Review of Anomaly Based Multiple Intrusion Detection Methods Using a Feature Based Deep Learning Approach
1 Introduction
2 Literature Review
3 Methodology
4 Results and Discussions
5 Conclusion
References
Correlation of Traditional Technique and ML-Based Technique for Efficient Effort Estimation: In Agile Frameworks
1 Introduction
2 Related Work
2.1 Non-Algorithmic Technique-Based Effort Estimation in Agile
2.2 Algorithmic Technique-Based Effort Estimation in Agile
2.3 Machine Learning-Based Effort Estimation in Agile
3 Research Objective
3.1 Research Question
3.2 Question Objective
4 Research Methodology
4.1 (RQ1) What Are the Various Traditional Techniques for Effort Estimation in an Agile Context?
4.2 (RQ2) What Are the Different ML Techniques for Effort Estimation in an Agile Context?
4.3 (RQ3) Which ML Algorithm Outperformed Among Themselves and What Are the Different Metrics Used to Determine the Accuracy of ML Techniques?
5 Results
6 Conclusion and Discussion
References
NLP-Based Processing of Gujarati Compound Word Sandhi's Generation and Segmentation
1 Introduction
1.1 Sandhi in Gujarati
1.2 Gujarati & NLP
2 Implementation
2.1 Execution
2.2 Sandhi Processing
3 Conclusion
References
Building Robust Fraud Detection Model for Insurance Claims Using SMOTE
1 Introduction
2 Literature Review
3 Methodology
3.1 Data Collection
3.2 Data Visualization
3.3 Data Cleaning and Transformation
3.4 Applying SMOTE Algorithms
3.5 Model Training and Testing
3.6 Model Evaluation
4 Result Analysis
4.1 ROC Curve
5 Conclusion
References
Wireless Sensor Network Energy Optimization by Frog Leaping Genetic Algorithm
1 Introduction
2 Related Work
3 Proposed Mehodology
3.1 Environment Development
3.2 Clustering
3.3 Crossover
3.4 Cluster Nodes
4 Experiment and Result
5 Conclusion
References
House Price Prediction Using the Concept of Machine Learning
1 Introduction
2 Literature Review
3 Attribute
4 Proposed System Design
5 Methodology
6 Results and Discussions
References
Smart Anesthesia Level Monitor During Surgery in the Intensive Care Unit
1 Introduction
1.1 Need to Measure Body Temperature with Anaesthesia
1.2 Problem Statement
2 Implementation
2.1 Hardware Implementation
2.2 Software Implementation
3 Results and Discussion
4 Conclusion
References
Plant Classification Using Conv Neural Network
1 Introduction
2 Literature Review
3 Proposed Methodology
4 Conclusion
References
Emergency Evacuation Information System Using IoT
1 Introduction
2 IoT and Its Applications in Emergencies
3 Components of the Evacuation Information System
3.1 Sensors and Devices for Real-Time Data Collection
3.2 Communication Infrastructure to Relay Data and Information
3.3 Centralized Data Processing and Analytics for Decision-Making
4 Information Dissemination and User Interface
5 Integration with Emergency Services
5.1 Collaborative Efforts with Emergency Services for Seamless Coordination
5.2 Interoperability Standards to Ensure Smooth Communication with Existing Emergency Systems
6 Conclusion
References
Genetic Algorithm & Decision Table Base Intrusion Detection
1 Introduction
2 Data Reduction Techniques
2.1 Genetic Algorithm
2.2 GA Working Principle
3 Classifiers
3.1 Decision Tree Classifier
3.2 Decision Tree as Intrusion Detection Model
3.3 More Classifiers
4 Programming Tools
5 Litreture Review
6 Proposed Work
7 Simulation and Result
8 Conclusion
References
Detection and Classification of Periapical Dental X-Ray Images Using Machine Learning
1 Introduction
2 RelatedWork
3 Proposed Method
3.1 RGB Color Image
3.2 Grayscale Image
3.3 Morphological Operations
3.4 Region Segmentation
3.5 Classification
4 Module Description
4.1 Input Image
4.2 Pre-processing
4.3 Segmentation
4.4 Colour Space Conversions
4.5 Morphological Operations
4.6 Feature Extraction
4.7 Classification
5 Results and Discussions
6 Conclusion
References
A Comprehensive Analysis of NOMA in 5G Futuristic Mobile Communications
1 Introduction
2 A Basic Concept Behind NOMA
3 Major Advantages of NOMA Systems
4 NOMA-Uplink and Downlink Transmission
5 Compatibility of Noma with Other Systems
6 Simulation Results
7 Conclusion
References
The Impact of Cloud Computing on Plant Health Monitoring
1 Introduction
2 Need of Cloud-Based Plant Health Monitoring System
2.1 Plant Leaf Disease Detection
2.2 Plant Growth Monitoring
2.3 Temperature and Irrigation Management
2.4 Soil-State Monitoring
2.5 Air-State Monitoring in the Greenhouse
2.6 Pest-Control Monitoring
3 Overview of Cloud, FoG and EDGE Computing
3.1 Cloud Computing
3.2 Fog Computing
3.3 Edge Computing
4 Comparison of Cloud, Fog and Edge Computing
5 Conclusion
References
Smart Digital Urometer for Monitoring Urine Volume and Specific Gravity in Critical Care Unit
1 Introduction
1.1 Low-Urine Output
1.2 Automation and Its Benefits
1.3 Urine Specific Gravity Significance
2 Proposed Device Design and Methodology
2.1 Methodology
2.2 Specific Gravity Calculation
2.3 Volume and Specific Gravity Display
2.4 Discarding Unit
3 Results and Discussions
4 Conclusion
References
Chaos-Based Cryptography for Digital Image Security Using Parrondo's Paradox
1 Introduction
2 Preliminaries
2.1 Alternate System
2.2 Logistic Map
2.3 Piecewise Logistic Map
3 Methodology of Proposed Work
4 Simulated Outcome and Security Analysis
4.1 Encrypted/Decrypted Images
4.2 Key Space Analysis
4.3 Analysis of Information Entropy
4.4 Correlation Coefficient Analysis
5 Conclusion
References
Classification of Venomous and Non-venomous Snakes Using Transfer Learning with MobileNetV2
1 Introduction
2 Related Works
3 Materials and Methods
3.1 Problem Identification
3.2 Existing System Issue
3.3 Proposed System Design
3.4 Algorithms
3.5 UML Diagram
4 Results and Discussions
4.1 Comparative Study
5 Conclusions and Future Work
References
Utilizing Machine Learning-Based Algorithms to Predict Student's Future
1 Introduction
2 Literature Review
3 Methodology
4 Results and Discussions
5 Conclusions
References
IoT-Based Fault Monitoring of Industrial Drives Using Multimodal Sensor Signals
1 Introduction
2 Methodology
3 Results and Discussion
4 Conclusion
References
Investigating the Relationships Between Smoking, Anxiety, and Psychological Distress via SPSS Analysis
1 Introduction
2 Data Description
3 Methodology
4 Results
4.1 Perceptions Between Gender and the Health Hazards Associated with Smoking
4.2 Understanding of the Relationship Between Smoking Patterns and Mental Stress
4.3 Understanding of the Relationship Between Smoking Patterns and Anxiety
4.4 Understanding of the Relationship Between Smoking Patterns and Depression
5 Conclusion
Video Noise Analysis Using Frequency Domain Algorithm
1 Introduction
2 Related Work
3 Methodology
3.1 Short-Time Fourier Transformation
3.2 Sparse Fast Fourier Transformation
3.3 Gaussian Noise Algorithm
3.4 PYIN Algorithm
3.5 Flow Chart
4 Experiment Results
5 Conclusion
References
Ensemble Machine Learning One-Versus-Rest Multilevel Grade Classification and Prediction
1 Introduction
1.1 Method and Materials
1.2 Data Preprocessing and Model Development
2 One-Versus-Rest
2.1 Decision Tree Classifier
2.2 Random Forest Classifiers
2.3 Support Vector Classifiers
2.4 AdaBoosting Classifiers
2.5 XGB Classifiers
2.6 Gradient Boosting Classifiers
2.7 K-Nearest Classifiers
2.8 Logistic Regression Classifiers
2.9 Bagging Classifiers
3 Conclusion
References

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