Intelligent Computing and Networking: Proceedings of IC-ICN 2021 (Lecture Notes in Networks and Systems, 301)

✍ Scribed by Valentina Emilia Balas (editor), Vijay Bhaskar Semwal (editor), Anand Khandare (editor)

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 287
• Category: Library

✦ Synopsis

This book gathers high-quality peer-reviewed research papers presented at the International Conference on Intelligent Computing and Networking (IC-ICN 2021), organized by the Computer Department, Thakur College of Engineering and Technology, in Mumbai, Maharashtra, India, on February 26–27, 2021. The book includes innovative and novel papers in the areas of intelligent computing, artificial intelligence, machine learning, deep learning, fuzzy logic, natural language processing, human–machine interaction, big data mining, data science and mining, applications of intelligent systems in health ,care, finance, agriculture and manufacturing, high-performance computing, computer networking, sensor and wireless networks, Internet of Things (IoT), software-defined networks, cryptography, mobile computing, digital forensics, and blockchain technology.

✦ Table of Contents

Preface
Contents
Editors and Contributors
Performance Evaluation of an IoT Edge-Based Computer Vision Scheme for Agglomerations Detection Covid-19 Scenarios
1 Introduction
2 Related Work
2.1 IoT and Egde Applications
2.2 Algorithm of Computer Vision to Detect Objects
3 Proposed Edge Architecture
4 Computer Vision Based on Difference of Frame in Single Shot Detection Algorithm
4.1 Evaluation of Frames Based on Difference of Frame
4.2 SSD Algorithm
5 Middleware Connectivity
6 Performance Evaluation and Results Analysis
7 Conclusion and Future Works
References
Comparative Analysis of Classification and Detection of Breast Cancer from Histopathology Images Using Deep Neural Network
1 Introduction
1.1 Symptoms of Breast Cancers Include
1.2 Stages of Breast Cancer
2 Related Work
3 Literature Survey
4 Conclusion
References
Determining Key Performance Indicators for a Doctoral School
1 Introduction
2 Indicators Study for Evaluating a DS Performance: State of the Art
2.1 Concept of Performance Indicator and Research Methods
2.2 Presentation of Criteria for Evaluating a Doctoral School Performance
3 Survey Procedures and Analysis of Results
3.1 Data Collection
3.2 Results Analysis
4 Determination of Performance Indicators for a Doctoral School
4.1 Doctoral School Governance
4.2 Satisfaction with Material and Immaterial Infrastructures
4.3 Results of the Defenses and Prospects of a Doctoral School
5 Discussion
6 Conclusion and Future Works
References
Cloud Attacks and Defence Mechanism for SaaS: A Survey
1 Introduction
2 Cloud Issues Attack and Defence Mechanism
2.1 SaaS Security Issues
2.2 Cloud Attacks and Defence Mechanism for SaaS
3 Conclusion and Future Work
References
“Palisade”—A Student Friendly Social Media Website
1 Introduction
2 Related Study
2.1 Security in Social Media
2.2 Disadvantages of Existing System
2.3 Proposed Model
2.4 Objectives
3 The Architecture of the Project
3.1 Methods of Implementation
3.2 Test Cases and Scenarios
3.3 How to Run MERN Application and Use It:
4 Results and Discussion
5 Conclusion and Future Scope
References
Comparative Review of Content Based Image Retrieval Using Deep Learning
1 Introduction
2 Research Background
3 Comparison of Existing Methods
4 Experimentation
4.1 Decision Tree
4.2 Feed Forward Neural Network
4.3 Convolutional Neural Network
5 Results and Evaluation
6 Conclusion
References
Fuzzy-Logic Approach for Traffic Light Control Based on IoT Technology
1 Introduction
2 Related Work
3 Proposed Approach
3.1 Design of Fuzzy Inference System
3.2 Fuzzy Inference Engine
4 Implementation and Initial Results
5 Conclusion
References
Data Clustering Algorithms: Experimentation and Comparison
1 Introduction
1.1 Working of Data Mining Algorithm
2 What is Clustering?
3 Clustering Algorithms
3.1 Partition Based Method
3.2 Hierarchical-Based Method
3.3 Density-Based Method:
3.4 Grid-Based Method
3.5 Model-Based Method
4 Algorithms
4.1 K-Means Algorithm
4.2 Agglomerative Clustering Algorithm
5 About the Dataset
5.1 First Dataset
5.2 Second Dataset
6 Validity Measures
7 Result And Discussion
7.1 K-Means Algorithm
References
Design and Development of Clustering Algorithm for Wireless Sensor Network
1 Introduction
1.1 Enhancement of an Algorithm for WSN
2 Ease of Use
2.1 K-means Generalization Benefits
2.2 Modified K-means (Initialization Method)
2.3 Clustering in WSN
3 Abbreviations and Acronyms
3.1 Equations
3.2 Complexity
4 Proposed Methodology
4.1 Dataset
4.2 Implementation
4.3 Result and Discussion
5 Conclusion
References
Mitigate the Side Channel Attack Using Random Generation with Reconfigurable Architecture
1 Introduction
2 Cryptography
3 Chaotic Circuit
4 Results and Comparison Analysis
5 Conclusion
References
A Statistical Review on Covid-19 Pandemic and Outbreak
1 Introduction
1.1 The Novel Coronavirus or COVID-19
1.2 Formation of COVID 19
1.3 Symptoms
1.4 Treatment for outbreak of virus COVID-19
2 Literature Survey
3 Statistical Analysis
4 Results and Discussion
References
Performance Evaluation of Secure Web Usage Mining Technique to Predict Consumer Behaviour (SWUM-PCB)
1 Introduction
2 Literature Review
3 Apriori Algorithm
4 Proposed Architecture
5 Proposed Algorithm
6 Experimental Results and Discussion
7 Conclusion
References
Quantum Computing and Machine Learning: In Future to Dominate Classical Machine Learning Methods with Enhanced Feature Space for Better Accuracy on Results
1 Introduction
1.1 Quantum Computing and Concepts
2 Quantum Enhanced ML
3 Quantum ML Research Domains
3.1 Survey on Quantum Literature
3.2 Comparison of Classical and Quantum Models
3.3 Motivation of Quantum Computing in ML
3.4 Platform Used for Proposed Implementation
4 Dataset Selection and Implementation
5 Conclusion
References
Design and Develop Data Analysis and Forecasting of the Sales Using Machine Learning
1 Introduction
2 Problem Statement
3 Proposed Methodology
3.1 Exploratory Data Analysis (EDA)
3.2 RFM (Recency, Frequency, Monetary) Model
3.3 Market Basket Analysis (MBA)
3.4 Time Series Forecasting
3.5 SARIMA (Seasonal Autoregressive Integrated Moving Average)
4 Proposed Algorithm
5 Conclusion
References
Prediction of Depression Using Machine Learning and NLP Approach
1 Introduction
2 Related Work
3 Problem Statement
4 Proposed System
5 Proposed Methodology Architecture
6 Results
7 Conclusion
References
Detection and Performance Evaluation of Online-Fraud Using Deep Learning Algorithms
1 Introduction
2 Literature Survey
3 Problem Statement
4 Data Collection and Visualization
5 Proposed System
6 Model Evaluation and Result
7 Conclusion
References
Data Compression and Transmission Techniques in Wireless Adhoc Networks: A Review
1 Introduction
2 Review on Recent Works for Lossless Compression
3 Conclusion
References
Message Propagation in Vehicular Ad Hoc Networks: A Review
1 Introduction
2 Survey on Recent Works for Vehicular Adhoc Networks
3 Conclusion
References
A Comparative Study of Clustering Algorithm
1 Introduction
2 Related Work
3 Proposed Work
3.1 Technology and Tools
3.2 Dataset
3.3 Clustering
3.4 Cluster Formation Methods
3.5 Clustering Algorithms:
3.6 Different Comparison Metrics
3.7 Comparing the Clustering Quality Measure
4 Implementation
4.1 K-means Algorithm
4.2 Hierarchical Clustering
4.3 DBSCAN Algorithm
5 Result
6 Future Scope
7 Conclusion
References
Refactoring Faces Under Bounding Box Using Instance Segmentation Algorithms in Deep Learning for Replacement of Editing Tools
1 Introduction
2 Methodology
3 Implementation
4 Conclusion
References
Motion Detection and Alert System
1 Introduction
2 Related Study
2.1 Advantages
2.2 Disadvantages
3 Proposed Model
3.1 Proposed Model Objectives
3.2 Proposed Model Outcomes
3.3 Proposed Model Advantages
4 Experimental Setup
4.1 Sensors from Which Data is Taken
4.2 Taking Video Input
4.3 Motion Detection
4.4 Sending Mails
4.5 Local Storage
5 Proposed Algorithm
6 Experimental Procedure
6.1 Pre-processing
6.2 Simple Thresholding
6.3 Smoothing
6.4 Finding Contour
6.5 Contour Approximation
6.6 Contour Area
6.7 Drawing Square Shapes and Output
6.8 Sending Mails
6.9 Experimental Data Used
6.10 Control Data
7 Results and Discussions
7.1 Existing System Outcomes
7.2 Proposed System Outcomes
8 Future Scope
9 Conclusion
References
Feasibility Study for Local Hyperthermia of Breast Tumors: A 2D Modeling Approach
1 Introduction
2 Mathematical Modeling and Analysis for Hyperthermia
2.1 Equations for Effective Temperature Distribution
2.2 Equations for Computational Optimization
2.3 Heat Flow Modeling for Breast Tumor
3 Results and Discussion
4 Conclusion
References
Author Index