Intelligent and Cloud Computing: Proceedings of ICICC 2021 (Smart Innovation, Systems and Technologies, 286)

✍ Scribed by Debahuti Mishra (editor), Rajkumar Buyya (editor), Prasant Mohapatra (editor), Srikanta Patnaik (editor)

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 626
• Category: Library

✦ Synopsis

This book features a collection of high-quality research papers presented at the International Conference on Intelligent and Cloud Computing (ICICC 2021), held at Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India, during October 22–23, 2021. The book includes contributions on system and network design that can support existing and future applications and services. It covers topics such as cloud computing system and network design, optimization for cloud computing, networking, and applications, green cloud system design, cloud storage design and networking, storage security, cloud system models, big data storage, intra-cloud computing, mobile cloud system design, real-time resource reporting and monitoring for cloud management, machine learning, data mining for cloud computing, data-driven methodology and architecture, and networking for machine learning systems.

✦ Table of Contents

Committees
Chief Patron
Patrons
Finance Chair
General Chair
International Advisory Committee
Program Chair
Program Committee
Organizing Chair
Organizing Co-chair
Conference Coordinator
Convener
Co-convenor
Technical Program Committee Chairs
Preface
Contents
About the Editors
Part I Cloud Computing, Image Processing, and Software
1 An Intelligent Online Attendance Tracking System Through Facial Recognition Technique Using Edge Computing
1.1 Introduction
1.1.1 Motivation and Contribution
1.1.2 Organization of the Paper
1.2 Related Works
1.2.1 In the Year 2017
1.2.2 In the Year 2018
1.2.3 In the Year 2019
1.2.4 In the Year 2020
1.3 Significance of Edge Computing for Online Attendance Tracking System
1.4 Methodology
1.4.1 Student Registration
1.4.2 Faculty Registration
1.4.3 Image Capture
1.4.4 Face Detection
1.4.5 Extraction of Face Encodings
1.4.6 Face Recognition
1.4.7 Attendance Updation
1.5 Practical Implementation
1.6 Results and Discussion
1.7 Conclusion and Future Work
References
2 Cloud Analytics: An Outline of Tools and Practices
2.1 Introduction
2.2 Related Work
2.3 Exploring the Ideology in Cloud-Based Analytics
2.4 Cloud Analytics Platforms
2.4.1 Qlik Sense Enterprise
2.4.2 Tableau
2.4.3 IBM Watson Analytics
2.4.4 Microsoft Power BI
2.4.5 TIBCO Spotfire X
2.4.6 SAS Business Analytics
2.5 Discussions
2.5.1 Benefits to Cloud-Based Analytics
2.5.2 Overview of Emerging Trends
2.6 Conclusion
References
3 An Enhanced Fault-Tolerant Load Balancing Process for a Distributed System
3.1 Introduction
3.2 Background
3.2.1 Related Work
3.3 Proposed Enhanced Load Balancing Scheme with Resource Failure Rate Consideration
3.4 Simulated Results
3.4.1 Results
3.5 Conclusion
References
4 HeartFog: Fog Computing Enabled Ensemble Deep Learning Framework for Automatic Heart Disease Diagnosis
4.1 Introduction
4.2 Related Works
4.3 HeartFog Architecture
4.3.1 Technology Used
4.3.2 Hardware Components Used
4.3.3 Software Components Used
4.4 HeartFog Design
4.4.1 Dataset
4.4.2 Heart Patient Data Pre-processing
4.4.3 Ensemble DL Application
4.4.4 Android Interface and Communication
4.4.5 Experimental Set-Up
4.4.6 Implementation
4.5 Results and a Discussion
4.6 Conclusion and Future Scope
References
5 A Cloud Native SOS Alert System Model Using Distributed Data Grid and Distributed Messaging Platform
5.1 Introduction
5.2 Related Work
5.3 Preliminaries
5.3.1 ZooKeeper as Cluster Coordinator
5.3.2 Kafka as a Data Streaming Platform
5.3.3 Ignite as the In-Memory Data Grid
5.4 Proposed Architecture
5.5 Implementation
5.6 Conclusion
References
6 Efficient Peer-to-Peer Content Dispersal by Spontaneously Newly Combined Fingerprints
6.1 Introduction
6.2 Literature Review
6.3 Proposed Work
6.3.1 Overview
6.3.2 Framework Architecture
6.3.3 Content Uploading and Splitting
6.3.4 Fingerprint Detection
6.3.5 Content Distribution
6.3.6 Anonymous Communication Protocol
6.3.7 Identification of Illegal Distribution
6.4 Experimental Results
6.4.1 Content Uploading and Splitting
6.4.2 Fingerprint Generation
6.4.3 Content Distribution
6.4.4 Identifying and Preventing Illegal Redistribution
6.5 Conclusion
References
7 An Integrated Facemask Detection with Face Recognition and Alert System Using MobileNetV2
7.1 Introduction
7.2 Related Works
7.3 Methodology
7.3.1 Facemask Detection Model
7.3.2 The Face-Recognition Model
7.3.3 Database
7.3.4 Web Application
7.4 Results
7.5 Conclusion
References
8 Test Case Generation Using Metamorphic Relationship
8.1 Introduction
8.2 Usability of Successful Test Cases
8.3 The Formalization and Insight of Metamorphic Testing
8.4 Conclusion
References
Part II IoT/Network
9 IRHMP: IoT-Based Remote Health Monitoring and Prescriber System
9.1 Introduction
9.2 Previous Work
9.2.1 Architecture
9.2.2 Communication Protocol
9.3 IRHMP—IoT-Based Remote Health Monitoring and Prescriber System
9.3.1 Architecture
9.3.2 Functionalities Doctor
9.3.3 Implementation Working
9.4 Conclusion
References
10 On Boundary-Effects at Cellular Automata-Based Road-Traffic Model Towards Uses in Smart City
10.1 Introduction
10.2 Review of the State-of-the-Art Available Works
10.3 Proposed Empirical Investigation
10.3.1 Search for More ECA Rules Toward Uses in Road-Traffic Simulation
10.3.2 Investigations on ECA Dynamics Toward Road-Traffic Simulation at Various Fixed-Boundary Situations
10.4 Detailed Discussions
10.5 Conclusive Remarks
References
11 An Optimized Planning Model for Management of Distributed Microgrid Systems
11.1 Introduction
11.1.1 Components of a Micro Grid
11.1.2 Type of Micro Grid
11.2 Literature Survey
11.3 Proposed Model
11.3.1 Methodology
11.4 Results and Discussion
11.4.1 For PV System
11.4.2 For Wind System
11.4.3 For Fuel Cells Power Generating Systems
11.5 Conclusions
References
12 Hard and Soft Fault Detection Using Cloud Based VANET
12.1 Introduction
12.2 Literature Study
12.3 Proposed Approach
12.3.1 Hard Permanent Fault Detection
12.3.2 Soft Fault Diagnosis
12.3.3 Fault Status Transmission Through Vehicular Cloud
12.4 Simulation Experiments and Discussions
12.5 Conclusion
References
13 A Novel Intelligent Street Light Control System Using IoT
13.1 Introduction
13.2 Related Works
13.3 State of Art
13.3.1 Node MCU
13.3.2 PIR Sensor
13.3.3 Channel Relay
13.3.4 LDR
13.4 Proposed System
13.5 Features of Smart Street Light System
13.6 Results and Discussion
13.7 Conclusion and Future Scope
References
14 Enhancing QoS of Wireless Edge Video Distribution using Friend-Nodes
14.1 Introduction
14.2 System Model
14.3 Video Dissemination Architecture
14.4 Simulation and Results
14.5 Conclusion
References
15 Groundwater Monitoring and Irrigation Scheduling Using WSN
15.1 Introduction
15.2 Materials and Method
15.2.1 System Design
15.2.2 Data Collection
15.2.3 Hardware
15.2.4 Software and Database
15.2.5 Groundwater Level Measurement and Pumping Time
15.2.6 Crop Water Demand
15.2.7 Irrigation Water Requirements
15.2.8 Energy Consumption
15.2.9 Process Flow Diagram
15.2.10 Dashboard
15.3 Results
15.3.1 Discharge and Recharge of Groundwater
15.3.2 Electricity Consumption
15.3.3 Crop Water Demand
15.4 Conclusion
References
16 A Soft Coalition Algorithm for Interference Alignment Under Massive MIMO
16.1 Introduction
16.2 System Model
16.3 Proposed Model
16.4 Experiment Results
16.5 Conclusion
References
Part III Optimization and Nature Inspired Methods
17 Improved Grasshopper Optimization Algorithm Using Crazy Factor
17.1 Introduction
17.2 Grasshopper Optimization Algorithms
17.2.1 Basic Grasshopper Optimization Algorithm (GOA)
17.2.2 Improved GOA with Crazy Factor (Crazy-GOA)
17.3 Result Analysis
17.4 Conclusion
References
18 Reliability Estimation Using Fuzzy Failure Rate
18.1 Introduction
18.2 Reliability Using Fuzzy System
18.3 Discussion
18.4 Illustration
18.5 Conclusion
References
19 A Sine Cosine Learning Algorithm for Performance Improvement of a CPNN Based CCFD Model
19.1 Introduction
19.2 Proposed SCA-CPNN-Based CCFD Model
19.2.1 Evaluation Criteria
19.3 Experimental Result Discussion
19.4 Conclusion
References
20 Quality Control Pipeline for Next Generation Sequencing Data Analysis
20.1 Introduction
20.2 Background and Related Work
20.3 Datasets
20.4 Methods and Material
20.4.1 Duplicate Removal and Trimming
20.4.2 NGS Dataset
20.4.3 NULL Value Removal
20.4.4 Normalization
20.4.5 Dimensionality Reduction
20.5 Result Discussion
20.5.1 The Differentially Expressed Genes and Outlier Detection Visualization
20.5.2 The Differentially Expressed Gene Selection Using Dimension Reduction
20.6 Conclusion and Future Work
References
21 Fittest Secret Key Selection Using Genetic Algorithm in Modern Cryptosystem
21.1 Introduction
21.1.1 Background
21.1.2 Motivation
21.1.3 Contribution
21.2 Preliminaries
21.2.1 Illustration of AVK
21.2.2 Genetic Algorithm
21.3 Proposed Work
21.4 Experiment Examples
21.5 Experiment Results
21.6 Performance Analysis
21.7 Randomness Verification
21.8 Conclusion
21.9 Future Work
References
22 Variable Step Size Firefly Algorithm for Automatic Data Clustering
22.1 Introduction
22.2 Related Work
22.3 Variable Step Size Firefly Algorithm
22.4 Result Analysis
22.5 Conclusion
References
23 GWO Based Test Sequence Generation and Prioritization
23.1 Introduction
23.1.1 Motivation
23.2 Basic Concept
23.2.1 GWO Algorithm
23.2.2 Adjacency Matrix
23.2.3 Objective Function/Fitness Function
23.3 Proposed Approach
23.3.1 Overview
23.3.2 Generation of Control Flow Graph
23.4 Implementation
23.4.1 Experimental Result
23.4.2 Prioritization
23.5 Comparison with Related Work
23.6 Conclusion and Future Work
References
Part IV Intelligent Computing
24 Artificial Intelligent Approach to Predict the Student Behavior and Performance
24.1 Introduction
24.2 Related Work
24.3 Existing System
24.4 Proposed System
24.5 Module Description
24.5.1 Feature Extraction
24.5.2 Emotion Expression Classification
24.5.3 Current Emotion Detection System
24.5.4 Facial Expression Recognition
24.6 Conclusion
References
25 Graph Based Automatic Keyword Extraction from Odia Text Document
25.1 Introduction
25.2 Literature Survey
25.3 Unsupervised Techniques for Ranking and Keyword Extraction
25.3.1 Graph Based Text-Rank Model
25.3.2 TF-IDF
25.4 Implementation and Experimental Results
25.5 Result Analysis
25.6 Conclusion
References
26 An Attempt for Wordnet Construction for Odia Language
26.1 Introduction
26.2 Related Work
26.3 Methods for Wordnet Construction and Procedure for Odia Wordnet Construction
26.4 Experimental Setup
26.5 Advantages and Disadvantages of Expansion Approach
26.6 Application
26.7 Conclusion and Future Works
References
27 A Deep Learning Approach for Face Mask Detection
27.1 Introduction
27.2 Related Works
27.3 Framework Used
27.4 Proposed Methodology
27.5 Results and Discussion
27.6 Conclusions and Future Scope
References
28 A Computational Intelligence Approach Using SMOTE and Deep Neural Network (DNN)
28.1 Introduction
28.2 Methodology Used
28.2.1 Dataset
28.2.2 Over-Sampling
28.2.3 DNN
28.2.4 Performance Metrics
28.3 Proposed Model
28.4 Experiments
28.5 Conclusion
References
29 Face Mask Detection in Public Places Using Small CNN Models
29.1 Introduction
29.2 Related Work
29.3 Small CNN Architectures: MobileNetv2 and ShuffleNet
29.3.1 MobileNetv2
29.3.2 ShuffleNet
29.4 Materials and Methodology
29.4.1 Dataset Description
29.4.2 Methodology
29.5 Result and Discussion
29.6 Conclusion
References
30 LSTM-RNN-Based Automatic Music Generation Algorithm
30.1 Introduction
30.2 Related Work
30.2.1 Melody-RNN
30.2.2 Biaxial-RNN
30.2.3 WaveNet
30.3 System Architecture
30.3.1 LSTM
30.3.2 LSTM with Attention
30.3.3 Encoder-Decoder
30.3.4 Encoder-Decoder with Attention
30.4 IV Implementation
30.5 Performance Evaluation
30.6 Conclusion
References
31 A KNN-PNN Decisioning Approach for Fault Detection in Photovoltaic Systems
31.1 Introduction
31.1.1 Types of PV Systems
31.1.2 Effect of Weather on PV Power Generation
31.1.3 Faults in PV Modules
31.2 Literature Survey
31.3 Proposed Model
31.3.1 Dataset Used
31.3.2 Working
31.4 Results and Discussion
31.4.1 Performance Evaluation for Dataset A
31.4.2 Performance Evaluation for Dataset B
31.5 Conclusions
References
32 Detecting Phishing Websites Using Machine Learning
32.1 Introduction
32.2 Literature Survey
32.3 Methodology
32.4 Results and Discussion
32.5 Conclusion and Future Work
References
33 Designing of Financial Time Series Forecasting Model Using Stochastic Algorithm Based Extreme Learning Machine
33.1 Introduction
33.2 Methodology
33.2.1 SLFN with ELM
33.2.2 SCA Algorithm
33.2.3 ELM-SCA Model
33.3 Experimental Study
33.4 Conclusion
References
34 Twin Support Vector Machines Classifier Based on Intuitionistic Fuzzy Number
34.1 Introduction
34.2 Background Review
34.2.1 Intuitionistic Fuzzy Membership Calculation
34.2.2 IFTSVM
34.3 Proposed Twin Support Vector Machines Classifier Based on Intuitionistic Fuzzy Number
34.4 Numerical Experiment
34.5 Conclusion
References
35 Automatic Detection of Epileptic Seizure Based on Differential Entropy, E-LS-TSVM, and AB-LS-SVM
35.1 Introduction
35.2 Materials and Methods
35.2.1 Clinical Dataset
35.2.2 Preprocessing
35.2.3 Feature Extraction
35.2.4 Performance Computation
35.3 Classifiers
35.4 Results and Discussion
35.5 Conclusion
References
36 Classification of Arrhythmia ECG Signal Using EMD and Rule-Based Classifiers
36.1 Introduction
36.2 Proposed Method
36.2.1 Clinical Dataset
36.2.2 Feature Extraction
36.2.3 Classifiers Used
36.2.4 Performance Measurements
36.3 Results and Discussion
36.4 Comparative Analysis
36.5 Conclusion
References
37 A Comparative Analysis of Data Standardization Methods on Stock Movement
37.1 Introduction
37.2 Related Work
37.3 Methods and Materials
37.3.1 Data Sets
37.3.2 Normalization
37.3.3 Technical Indicators
37.3.4 Support Vector Machines
37.3.5 Artificial Neural Network
37.3.6 K Nearest Neighbor
37.4 Proposed Methodology
37.5 Results and Discussion
37.6 Conclusion and Future Work
References
38 Implementation of Data Warehouse: An Improved Data-Driven Decision-Making Approach
38.1 Motivation of the Work
38.2 Introduction
38.3 Literature Review
38.4 State of the Art
38.5 Experimental Analysis
38.6 Conclusion and Future Scope
References
39 An Empirical Comparison of TOPSIS and VIKOR for Ranking Decision-Making Models
39.1 Introduction
39.2 MCDM Process
39.2.1 A Brief Overview of TOPSIS
39.2.2 A Brief Overview of VIKOR
39.2.3 Comparative Study of TOPSIS and VIKOR
39.3 Simulation
39.4 Conclusion
References
40 An Efficient Learning Model Selection for Dengue Detection
40.1 Introduction
40.2 Related Works
40.3 Proposed Work
40.3.1 Symptoms
40.3.2 Datasets Resources
40.3.3 Criteria for Percentage Selection of Trained and Tested Data
40.3.4 Proposed Algorithm for Evolution of Best ML Technique
40.3.5 Process Flow Chart
40.3.6 ML Algorithms Used
40.4 Results and Discussion
40.5 Conclusion
References
41 A Modified Convolution Neural Network for Covid-19 Detection
41.1 Introduction
41.2 Modified CNN Model for Covid-19 Detection from Chest X-Ray Images
41.2.1 Performance Matrices
41.3 Experimental Result Discussion
41.4 Conclusion
References
42 Bi-directional Long Short-Term Memory Network for Fake News Detection from Social Media
42.1 Introduction
42.2 Related Work
42.3 Methodology
42.4 Results
42.5 Conclusion
References
43 Effect of Class Imbalanceness in Credit Card Fraud
43.1 Introduction
43.2 Preliminary Work
43.3 Proposed Credit Card Fraud Detection Model
43.3.1 Proposed SMOTEMLCFDS Model
43.4 Results and Discussions
43.4.1 Experimental Setup
43.4.2 Description of the Dataset
43.4.3 Performance Metrics
43.4.4 Result Analysis
43.5 Conclusions
References
44 Effect of Feature Selection on Software Fault Prediction
44.1 Introduction
44.2 Literature Survey
44.3 Methodology
44.3.1 Datasets
44.3.2 Classification Techniques
44.3.3 Evaluation Criteria
44.4 Results and Discussions
44.5 Conclusion and Future Work
References
45 Deep Learning-Based Cell Outage Detection in Next Generation Networks
45.1 Introduction
45.1.1 Motivations
45.1.2 Contributions
45.2 Our Proposal
45.3 Performance Analysis
45.4 Conclusion
References
46 Image Processing and ArcSoft Based Data Acquisition and Extraction System
46.1 Introduction
46.2 System Analysis
46.2.1 System Function Structure
46.2.2 System Hardware Requirements
46.3 System Design
46.3.1 Process Design
46.3.2 Data Extraction Design
46.4 Implementation
46.4.1 Environment Deployment
46.4.2 Function Realization of Monitoring Terminal
46.4.3 Function Realization of Data Extraction
46.5 Conclusion
References
Part V Intelligent Computing (eHealth)
47 Machine Learning Model for Breast Cancer Tumor Risk Prediction
47.1 Introduction
47.2 Literature Review
47.3 Experimental Setup
47.4 Result Analysis
47.5 Conclusion
References
48 Comparative Analysis of State-Of-the-Art Classifier with CNN for Cancer Microarray Data Classification
48.1 Introduction
48.2 Related Work
48.3 Materials and Methodology
48.3.1 Dataset Description
48.3.2 Convolutional Neural Network
48.4 Proposed Work
48.5 Result and Analysis
48.6 Conclusion
References
49 Comparative Study of Machine Learning Algorithms for Breast Cancer Classification
49.1 Introduction
49.2 Related Work
49.3 Overview of Machine Learning Models
49.4 Dataset Description
49.5 Proposed Model
49.5.1 Exploratory Data Analysis and Data Preprocessing
49.5.2 Model Evaluation and Results
49.6 Conclusion
References
50 miRNAs as Biomarkers for Breast Cancer Classification Using Machine Learning Techniques
50.1 Introduction
50.2 Dataset Used
50.3 Proposed Model
50.3.1 Data Preparation
50.3.2 Feature Selection
50.3.3 Classifier Models
50.3.4 Evaluation Parameters
50.4 Results
50.4.1 Biological Relevance Analysis
50.5 Conclusion
References
51 A Computational Intelligence Approach for Cancer Detection Using Artificial Neural Network
51.1 Introduction
51.2 Literature Survey
51.3 Proposed Model
51.4 Result Analysis
51.4.1 Neural Network Model for Proposed Work
51.4.2 Dataset Description and Result Analysis
51.5 Conclusion
References
52 Brain MRI Classification for Detection of Brain Tumors Using Hybrid Feature Extraction and SVM
52.1 Introduction
52.2 Proposed Model
52.3 Experimental Study
52.4 Result Analysis
52.5 Conclusion
References
53 Enhancing the Prediction of Breast Cancer Using Machine Learning and Deep Learning Techniques
53.1 Introduction
53.2 Related Works
53.2.1 Machine Learning Techniques
53.2.2 Deep Learning Techniques
53.3 Proposed System
53.4 Experimental Results
53.4.1 Machine Learning
53.4.2 Deep Learning
53.5 Conclusion
References
54 Performance Analysis of Deep Learning Algorithms Toward Disease Detection: Tomato and Potato Plant as Use-Cases
54.1 Introduction
54.1.1 Contributions
54.2 Performance Analysis of Deep Learning Algorithms
54.2.1 Dataset
54.2.2 Data Augmentation
54.2.3 Transfer Learning
54.3 Experimental Settings
54.4 Results and Discussion
54.5 Conclusions
References
55 Classification of Human Facial Portrait Using EEG Signal Processing and Deep Learning Algorithms
55.1 Introduction and Related Studies
55.2 Methodology
55.3 Performance Analysis and Results
55.4 Conclusion and Future Works
References
56 A Semantic-Based Input Model for Patient Symptoms Elicitation for Breast Cancer Expert System
56.1 Introduction
56.2 Review of Literature
56.3 Materials and Method
56.4 Result and Discussion
56.4.1 Evaluation Metrics
56.4.2 Comparative Analysis of Symptoms Count
56.4.3 Comparative Analysis of Precision of Symptoms Generated on the Existing and Proposed Models
56.4.4 Comparative Analysis of Precision and Accuracy of Diagnosis Using Modified ST Algorithm
56.5 Conclusion
References
Appendix
Author Index