Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0 : Proceedings of the 5th International Conference on Artificial Intelligence and Applied Mathematics in Engineering ICAIAME 2023, Volume 1 / edited by D. Jude Hemanth, Utku Kose, Bogdan Patrut, Mevlut Ersoy.

Format:

Book

Contributor:

Hemanth, D. Jude, editor.

Series:

Engineering Cyber-Physical Systems and Critical Infrastructures, 2731-5010 ; 9

Language:

English

Subjects (All):

Computational intelligence.

Artificial intelligence.

Engineering--Data processing.

Engineering.

Computational Intelligence.

Artificial Intelligence.

Data Engineering.

Local Subjects:

Computational Intelligence.

Artificial Intelligence.

Data Engineering.

Physical Description:

1 online resource (291 pages)

Edition:

1st ed. 2024.

Place of Publication:

Cham : Springer Nature Switzerland : Imprint: Springer, 2024.

Summary:

This book provides a wide collection of the recent studies triggering innovative ways to advance computer science and computational applications. The collection enables readers to understand more about technological conditions advancing industrial perspectives towards Industry 5.0. The research studies included in the book were accepted and presented in the 5th International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2023), which was held in Belek, Antalya, Turkey (on 3–4–5 November 2023). By covering the scientific scope of the conference, the book informs the readers about the cutting-edge data-driven solution aspects, intelligent algorithms, and mathematical background applied for solving different kinds of engineering problems. The book is used as a reference source by the wide readership including international researchers, professionals, practitioners from industry, degree students, and experts from all engineering disciplines. .

Contents:

Intro

Foreword

Preface

Contents

A Brief Survey on Exploring the Application Areas and Scope of ChatGPT

1 Introduction

2 About ChatGPT

3 Usage Areas

3.1 ChatGPT as an Add-On to Already Existing Software

3.2 ChatGPT Usage in Daily Life

4 Potential Risks of ChatGPT and Concerns

4.1 Educational Problems

4.2 Academic Problems

4.3 Social and Being Biased Problems

4.4 Cyber Problems

5 Papers

5.1 Highlights

6 ChatGPT Future Work and Expectations

7 Conclusions

References

Academic Performance Classification: Use of Supervised Learning Approach in Educational Data Mining

2 Method

3 Findings and Discussion

3.1 Findings for Research Question 1

3.2 Findings for Research Question 2

3.3 Findings for Research Question 3

3.4 Findings for Research Question 4

4 Conclusions and Future Work

Artificial Intelligence-Based Engineering Applications a Comprehensive Review of Application Areas, Impacts and Challenges

2 Common AI Techniques

3 AI Engineering Applications

4 Impacts of AI

5 Challenges of AI

6 Conclusions and Future Work

Artificial Intelligence Based Estimation of Individuals' Daily Energy Requirements with Anthropometric Measurements and Demographic Information

1.1 Literature Review

2 Material and Method

2.1 Data Collection

2.2 Feature Selection

2.3 Regression Machine Learning

2.4 Performance Evaluation Criteria

3 Results

4 Discussion

5 Conclusions

6 Future Work

Calculating Bus Occupancy by Deep Learning Algorithms

2 Proposed Approach

2.1 Person Detection

2.2 Tracking

2.3 Counting

2.4 Calculating Bus Occupancy

3 Custom Dataset

3.1 People Counting Dataset

3.2 Overhead View Dataset.

4 Experiments

4.1 Results

Classification of Elective Courses According to Kolb Learning Style Inventory by Using Machine Learning Methods

2 Material and Methods

2.1 Machine Learning Methods

2.2 Dataset

2.3 Performance Measurement Metrics

3 Results and Discussion

4 Conclusion

Investigation of the Best AP Method for Predicting Compressive Strength in RAC

2 Immune Plasma Programming and Versions

2.1 Immune Plasma Programming (IPP)

2.2 Single Dose IPP Algorithm (sdIPP)

2.3 Quick IPP Algorithm (qIPP)

3 Experimental Design

3.1 Dataset and Features

3.2 Parameters

3.3 Performance Evaluation Criteria

4 Simulation Results

Classification of Facial Images and Moods Using Image-Based Algorithms

2 Related Works

3 Proposed Model

"Clip" Thinking in Artificial Intelligence as the Tool of Agile Projects Management

2 Research Methodology

3 The Clip Thinking Principles

4 Conceptual Model of Clip Thinking in Agile Project Management

5 Conclusions and Future Work

Computational Modeling of Trailing Operations by Autonomous Boat

2 Boat Dynamics Model

3 Autonomous Control Model

4 Modeling Results

Deep Learning-Based Hyperparameter Tuning and Performance Comparison

3 Method and Material

4 Experimental Results

5 Discussion and Conclusion

Detection of Faults in High Voltage Power Transmission Lines Using Unmanned Aerial Vehicle with Artificial Intelligence Methods

2 Materials and Methods

2.1 Materials

2.2 Method

3 Findings

4 Results.

References

Developing a Comprehensive Emotion Lexicon for Turkish

3 Methodology

3.1 Creating the Emotion Vectors

3.2 Calculating TF-IDF for Emotions

3.3 Preparing Data for Testing

3.4 Calculating the Distance

3.5 Creating a Test GUI

4 Discussion and Results

5 Conclusion

Appendix

A Hyper-Heuristic Approach to Solving Vehicle Routing Problem in Military Logistics Distribution

3.1 Overview of Deep Learning and YoloV8

3.2 Overview of Hyper-Heuristic Algorithms

3.3 Problem Definition and Solution

3.4 The Proposed Hyper-Heuristic Algorithm

Electricity Price Forecasting Using Automatic Programming Methods

2 Automatic Programming Methods

3.1 Dataset and Analysis

3.3 Evaluation Criteria

4.1 Analysis of RMSE Values with T-Test

Ethical Considerations and Challenges of AI Adoption in Project Management

1 Ethics Re-emerging in the Digital World

2 Implementation of Ethics in the Organizational Context

3 Ethics in Projects

4 Survey on Ethical Considerations and Challenges of AI Adoption in Project Management

4.1 Methods Used

4.2 Statistics and Analysis

Feature Processing on Artificial Graph Node Features for Classification with Graph Neural Networks

3.1 Overview of Graph Neural Networks

3.2 Featureless Graph Datasets and Feature Initialization Methods

3.3 Feature Initialization Based on Graph Measures and Clustering.

3.4 Feature Initialization and GNN Model Integration

4 Experiments

4.1 Datasets

4.2 Experimental Setup

4.3 Graph Classification Experiments

5 Discussion

Analyzing Bias in Machine Learning Models: Insights from the AlexNet Architecture on Balanced and Imbalanced Data

2 Related Work

3.1 Research Hypothesis

3.2 Research Design

3.3 MNIST Dataset

3.4 EMNIST Digits Dataset

4 Testing

5 Results

5.1 MNIST Dataset

5.2 EMNIST Dataset

6 Discussion

6.1 Bias and Data Content

6.2 Accuracy and F1 Score Analysis

6.3 Special Case of Class 7

7 Conclusion

Ghost-Free High Dynamic Range Imaging Based on Two-Stage Dense Image Alignment

2.1 Traditional Alignment Based Methods

2.2 CNN Alignment Based Methods

3 Proposed Method

3.1 Alignment Network

3.2 Merging Network

4 Experiment

Log Anomaly Detection in Application Servers Using Deep Learning

2 RNN Based Log Anomaly Detection

3 Dataset

3.1 Log Collection

3.2 Parsing Log Files

4 Feature Extraction from Log Files

5 Experimental Results and Discussions

6 Conclusions

Modelling Autonomous Vehicle Safety in Road Scenarios Considering User Behaviour

2 Literature Review

2.1 Autonomous Vehicle

2.2 Advanced Driving Assistance System (ADAS)

3 Method

4 Analysis and Discussion

4.1 Driver's Individual Perspective

4.2 The Vehicle (t)

4.3 The Road (r)

4.4 Pedestrian Behaviour (b)

5 Recommendations

6 Conclusion

Author Index.

Notes:

Includes bibliographical references and index.

ISBN:

3-031-56310-7