Innovative Methods in Computer Science and Computational Applications in the Era of Industry 5.0

Name: 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
Brand: Springer
Price: 223.63 EUR
Availability: OnlineOnly

Proceedings of the 5th International Conference on Artificial Intelligence and Applied Mathematics in Engineering ICAIAME 2023, Volume 1

D. Jude Hemanth Utku Kose Bogdan Patrut Mevlut Ersoy(Herausgeber*in)

Springer (Verlag)

1. Auflage

Erschienen am 5. April 2024

X, 280 Seiten

E-Book

PDF mit Wasserzeichen-DRM

Systemvoraussetzungen

978-3-031-56310-2 (ISBN)

223,63 €inkl. 7% MwSt.

Systemvoraussetzungen

für PDF mit Wasserzeichen-DRM

E-Book Einzellizenz

Als Download verfügbar

Beschreibung

Weitere Details

Weitere Ausgaben

Inhalt

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
1 Introduction
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
References
Artificial Intelligence-Based Engineering Applications a Comprehensive Review of Application Areas, Impacts and Challenges
1 Introduction
2 Common AI Techniques
3 AI Engineering Applications
4 Impacts of AI
5 Challenges of AI
6 Conclusions and Future Work
References
Artificial Intelligence Based Estimation of Individuals' Daily Energy Requirements with Anthropometric Measurements and Demographic Information
1 Introduction
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
References
Calculating Bus Occupancy by Deep Learning Algorithms
1 Introduction
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
5 Conclusions
References
Classification of Elective Courses According to Kolb Learning Style Inventory by Using Machine Learning Methods
1 Introduction
2 Material and Methods
2.1 Machine Learning Methods
2.2 Dataset
2.3 Performance Measurement Metrics
3 Results and Discussion
4 Conclusion
References
Investigation of the Best AP Method for Predicting Compressive Strength in RAC
1 Introduction
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
5 Conclusions
References
Classification of Facial Images and Moods Using Image-Based Algorithms
1 Introduction
2 Related Works
3 Proposed Model
4 Discussion
5 Conclusions
References
"Clip" Thinking in Artificial Intelligence as the Tool of Agile Projects Management
1 Introduction
2 Research Methodology
3 The Clip Thinking Principles
4 Conceptual Model of Clip Thinking in Agile Project Management
5 Conclusions and Future Work
References
Computational Modeling of Trailing Operations by Autonomous Boat
1 Introduction
2 Boat Dynamics Model
3 Autonomous Control Model
4 Modeling Results
5 Conclusions
References
Deep Learning-Based Hyperparameter Tuning and Performance Comparison
1 Introduction
2 Related Works
3 Method and Material
4 Experimental Results
5 Discussion and Conclusion
References
Detection of Faults in High Voltage Power Transmission Lines Using Unmanned Aerial Vehicle with Artificial Intelligence Methods
1 Introduction
2 Materials and Methods
2.1 Materials
2.2 Method
3 Findings
4 Results
References
Developing a Comprehensive Emotion Lexicon for Turkish
1 Introduction
2 Related Works
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
References
A Hyper-Heuristic Approach to Solving Vehicle Routing Problem in Military Logistics Distribution
1 Introduction
2 Related Works
3 Method and Material
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
4 Discussion and Results
5 Conclusions and Future Work
References
Electricity Price Forecasting Using Automatic Programming Methods
1 Introduction
2 Automatic Programming Methods
3 Experimental Design
3.1 Dataset and Analysis
3.2 Parameters
3.3 Evaluation Criteria
4 Simulation Results
4.1 Analysis of RMSE Values with T-Test
5 Conclusion
References
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
5 Conclusions and Future Work
References
Feature Processing on Artificial Graph Node Features for Classification with Graph Neural Networks
1 Introduction
2 Related Works
3 Method and Material
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
6 Conclusions and Future Work
References
Analyzing Bias in Machine Learning Models: Insights from the AlexNet Architecture on Balanced and Imbalanced Data
1 Introduction
2 Related Work
3 Method and Material
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
References
Ghost-Free High Dynamic Range Imaging Based on Two-Stage Dense Image Alignment
1 Introduction
2 Related Works
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
5 Conclusion
References
Log Anomaly Detection in Application Servers Using Deep Learning
1 Introduction
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
References
Modelling Autonomous Vehicle Safety in Road Scenarios Considering User Behaviour
1 Introduction
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
References
Author Index

Systemvoraussetzungen

Als PDF speichern Als Link merken