Recent Trends in Communication and Intelligent Systems: Proceedings of ICRTCIS 2023 (Algorithms for Intelligent Systems)

Conference Program Committee
Preface
Contents
Performance Analysis of UAV Routing Protocol Based on Mobility Models
	1 Introduction
	2 Mobility Model and Routing Protocol
	3 Methodology and Experimental Evaluation
	4 Results and Discussions
	5 Conclusion and Future Enhancements
	References
Evaluation of Lubricant Film Thickness in Helical Gear on Contact Line at Critical Points by Using Elastohydrodynamic Model and It’s Comparison with Kisssoft Result
	1 Introduction
		1.1 Contact Zone
		1.2 Determination of Important Point of Contact Line
		1.3 Contact Geometry
		1.4 Literature Review
		1.5 Problem Definition
		1.6 Software Packages in Use
		1.7 Elastohydrodynamic Lubrication (EHL) Model Development
		1.8 Surface Elastic Deflection-Evaluation
		1.9 Formation of Deformation Equation
		1.10 Results and Discussions
		1.11 Conclusion and Future Scope
	References
ABC Algorithm for Evaluating the Performance of the SVC and Optimal Power Flow
	1 Introduction
	2 The Formulation of the OPF\'s Problems
	3 The Artificial Bee Colony Algorithm Description
	4 Test Results
	5 Conclusions
	References
ELPDI: A Novel Ensemble Learning Approach for Pulmonary Disease Identification
	1 Introduction
	2 Related Works
		2.1 VGG-16
		2.2 Inception-V4
		2.3 ResNet-50
	3 Ensemble Learning for Identification of Pulmonary Disease
		3.1 Converting Audio Files into Spectrograms
		3.2 Classification of Generated Spectrograms
	4 Results
		4.1 Dataset Description
	5 Conclusion
	References
JAYA-Based Task Scheduling Algorithm in Fog-Cloud Environment
	1 Introduction
	2 Related Work
		2.1 JAYA
	3 Task Scheduling Using I-JAYA
		3.1 I-JAYA Algorithm
	4 Performance Evaluation
		4.1 Simulation Study
	5 Conclusion and Future Work
	References
BLOCK-FEMF: Efficient Forensic Evidence Management Framework Using Blockchain Technology
	1 Introduction
	2 Related Work
	3 Proposed Methodology
	4 Implementation
		4.1 Adding Users to the Blockchain Network
		4.2 Transfer Ownership
		4.3 Adding Evidence to the Case
		4.4 Retrieving of Evidence from Case File
	5 Results and Discussions
		5.1 Gas Value Consumption
		5.2 Time Consumption
		5.3 Comparative Study Analysis
	6 Conclusion
	References
Bacterial Spot Classification in Bell Pepper Plants Based on Convolutional Neural Network Architecture
	1 Introduction
	2 Literature Review
	3 Transfer Learning
	4 Google Net and ResNet Architecture
		4.1 Google Net
		4.2 ResNet
	5 Methodology of the Work
		5.1 Aim of the Project
		5.2 Procedure of the Work
		5.3 Result Generated
	6 Conclusion
	References
Prediction of Bone Mineral Density Using AI to Detect Osteoporosis
	1 Introduction
	2 Methodology for Collection of Data
		2.1 Data Description
		2.2 Machine Learning Algorithms
		2.3 Tableau
	3 Result
	4 Conclusions
	References
On the Depth of Convolutional Neural Networks for Image Classification Problems
	1 Introduction
	2 Related Works and Motivation
	3 Network Models
		3.1 Depth Level 1 (Model 1)
		3.2 Depth Level 2 (Model 2)
		3.3 Depth Level 3 (Model 3)
		3.4 Depth Level 4 (Model 4)
	4 Experiments and Observation
		4.1 Datasets Description
		4.2 Prediction Performance
		4.3 Comparative Study and Discussion
	5 Conclusion
	References
A Modified Tilt Integral Derivative (MTID) Controller Design Using Direct Synthesis Approach
	1 Introduction
		1.1 DOF Control Schemes
		1.2 DOF Control Schemes on Fractional Order Framework
	2 Methodology
		2.1 Direct Synthesis Method
		2.2 Controller Design for Processes 1
		2.3 Controller Design for Processes 2
		2.4 Controller Structure
		2.5 Selection of Controller Parameter αcl
	3 Results and Discussions
		3.1 Case Study-1
		3.2 Case Study-2
	4 Conclusions
	References
A Novel Modified Semicircular Patch Antenna for Next Generation Communication
	1 Introduction
	2 Antenna Design
	3 Results and Discussions
	4 Comparison Between Previously Designed Antennas and Proposed Antenna
	5 Conclusion
	References
Panoptic Driving Perception Using Deep Learning Techniques
	1 Introduction
	2 Literature Survey
	3 Proposed Methodology
		3.1 Encoder
		3.2 Decoders
		3.3 Loss Function
		3.4 Distance Computation
		3.5 Experimental Setup
	4 Results
		4.1 Lane and Line Detection
	5 Conclusion
	References
Schistosomiasis Prevention Undermined by Water Point Forecasting: An Approach Based on Data Fusion Model
	1 Introduction
	2 Background on Evidence Theory
		2.1 Modeling
		2.2 Estimation
		2.3 Combination
		2.4 Decision
	3 Proposed Data Fusion Architecture
	4 Implementation of Evidence Theory
		4.1 Mass Modeling and Estimation
		4.2 Combination of Mass Functions
	5 Evaluation
		5.1 Experimental Setup
	6 Results
		6.1 Infestation States Observed for Each Scenario
		6.2 Overall Performance of the FuMalMMO Model
	7 Conclusion
	References
A Comparative Study of Classification Algorithms for the Prediction of Communication Effectiveness
	1 Introduction
	2 Related Works
	3 Proposed Model
	4 Results and Discussion
	5 Conclusion and Future Work
	References
A Dynamic Threshold-Based Cognitive Radio Energy Detection Algorithm for Multi-carrier Waveforms
	1 Introduction
	2 System Model
	3 Simulation Results
	4 Conclusion
	References
Comparison of Different Alphabetically Shaped Microstrip Patch Antennas in the S-Band Using HFSS
	1 Introduction
	2 Proposed Antenna Designs
		2.1 E-Shaped Antenna
		2.2 H Shaped Antenna
		2.3 U Shaped Antenna
	3 Simulation Results
		3.1 E Shaped Antenna
		3.2 H Shaped Antenna
		3.3 U Shaped Antenna
	4 Conclusion
	References
Using MNIST Dataset for De-Pois Attack and Defence
	1 Introduction
	2 Literature Review
	3 Business and Data Understanding
	4 Data Preparation and Data Modelling
	5 Deployment, Analysis and Results
	References
Direction Detection of Select Stocks with Machine Learning
	1 Introduction
	2 Literature Review
		2.1 Fundamental and Technical Analysis
		2.2 Algorithmic Trading
		2.3 Supervised and Unsupervised Learning
		2.4 Classification Machine Learning Techniques
		2.5 Confusion Matrix for Classification Models
	3 Methodology
		3.1 Data Collection
		3.2 Data Exploration
		3.3 Data Pre-processing
		3.4 Data Modeling
	4 Implementation and Results
		4.1 Model Evaluation Using Logistic Regression Classifier for Go Long Direction Prediction
		4.2 Model Evaluation Using Random Forest Classifier for Go Long Direction Prediction
		4.3 Model Evaluation Using Extreme Gradient Boost Classifier for Go Long Direction Prediction
		4.4 Direction Detection and Go Long Direction Prediction Using the Best Classifier Model
		4.5 Utility from the Business Perspectives
		4.6 Risk Adjusted Returns
	5 Conclusion and Future Scope
	References
Prediction of Fatal Accidents in the Petrochemical Industry with Machine Learning
	1 Introduction
	2 Literature Review
	3 Material and Methods
	4 Proposed Model
	5 Data Understanding
		5.1 Incident Proportion by Employment Type
		5.2 Incident Proportion by Incident Type
		5.3 Incident Proportion by Month
		5.4 Incident Proportion by Gender
		5.5 Incident Proportion by Causing Effect
		5.6 Incident Proportion by Plant
		5.7 Incident Proportion by Location
		5.8 Incident Proportion by Injury Illness Type
	6 Implementation
		6.1 Structured Data
		6.2 Combined Data
	7 Conclusion
	References
Author Index