Proceedings of the 19th International Conference on Computing and Information Technology (IC2IT 2023)

Name: Proceedings of the 19th International Conference on Computing and Information Technology (IC2IT 2023)
Brand: Springer
Price: 171.19 EUR
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Phayung Meesad Sunantha Sodsee Watchareewan Jitsakul Sakchai Tangwannawit(Herausgeber*in)

Springer (Verlag)

Erschienen am 23. Mai 2023

X, 222 Seiten

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978-3-031-30474-3 (ISBN)

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Beschreibung

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Inhalt

Intro
Preface
Organization
Contents
A Robust Cursor Activity Control (RCAC) with Iris Gesture and Blink Detection Technique
1 Introduction
2 Literature Review
3 Algorithms and System Implementation
3.1 Frame Processing
3.2 Algorithms
4 Result Analysis
4.1 Accuracy of Blinks in Terms of Distance
4.2 Comparison with Existing System
5 Conclusion
References
Lesion Detection Based BT Type Classification Model Using SVT-KLD-FCM and VCR-50
1 Introduction
1.1 Problem Statement
2 Related Works
3 Research Methodology
3.1 Pre-processing
3.2 Patch Generation
3.3 Segmentation
3.4 Feature Extraction
3.5 Classification
4 Result and Discussion
4.1 Dataset Description
4.2 Performance Analysis of Classification
4.3 Performance Analysis for Segmentation
4.4 Performance Analysis of Edge Enhancement
4.5 Comparative Analysis
5 Conclusion
References
Abnormal Corner of Mouth Fall Detection of Stroke Patient Using Camera
1 Introduction
2 Related Works
3 Methodology
3.1 Data Collection
3.2 Data Preparation
3.3 Model Building for Abnormality Detection of Corner of Mouth Fall in Stroke Patient
3.4 Notification
4 Results and Discussion
4.1 Result of Performance Measurement of Model
4.2 Case Study
5 Conclusions
References
Federated Machine Learning for Self-driving Car and Minimizing Data Heterogeneity Effect
1 Introduction
2 Related Work
3 Methodology
3.1 System Model
3.2 Training Locally
4 Implementations, Results and Analysis
5 Conclusion and Future Works
References
Predicting Foot and Mouth Disease in Thailand's Nakhon Ratchasima Province Through Machine Learning
1 Introduction
2 Literature Review
3 The Method
3.1 Research Method
3.2 Model Construction
3.3 Model Evaluation
4 Experiments and Results
5 Conclusion
References
Inspection of Injection Molding Process Improvement Using Simulation Techniques: A Case Study
1 Introduction
2 Background
3 Objective
4 Input Data Collection and Data Fitting
4.1 Processing Time Includes Inspection and Recording Time
4.2 Transportation Time
4.3 Input Distribution
5 Simulation Model
6 Bottleneck Identification
7 Experimental Design
7.1 Model A: Current Machine Layout and 2 Inspection Stations
7.2 Model B: Rearranged Machine Layout and 2 Inspection Stations
8 Model Validation
9 Results and Conclusion
References
An End-to-end Framework to Harness Knowledge Graphs for Building Better Models from Data
1 Introduction
2 Semantic Feature Selection
3 Model Building Framework
4 DBpedia Implementation
4.1 Inverse Operationalization
4.2 Inference Engine
5 Evaluation
6 Related Work
7 Conclusion
References
Study of Feature Selection for Gold Prices Forecasting Using Machine Learning Approach
1 Introduction
2 Data and Variables
3 Feature Selection Methods
4 Gold Price Forecasting Models
5 Experiment and Discussion
6 Conclusion
References
Airbnb Occupancy Rate Influential Detection Based on Hosting Descriptions with LDA
1 Introduction
2 Literature Review
3 Method
3.1 Data Collection
3.2 Language Detection
3.3 Text Processing
3.4 Latent Dirichlet Allocation
3.5 Consolidate Data
4 Result
5 Discussion
6 Discussion Limitation and Future Research
References
Projectile Launch Point Prediction via Multiple LSTM Networks
1 Introduction
2 Methodology
2.1 Proposed Method
2.2 Dataset
2.3 LSTM Networks and Training
3 Experimental Results
4 Conclusion
References
Accommodation Descriptions that Influence Airbnb Occupancy Rate Using Ontology
1 Introduction
2 Literature Review
3 Method
3.1 Data Collection
3.2 Language Detection
3.3 NLP Ontology Creation
3.4 Consolidate Data to Well-Formed
4 Result and Discussion
5 Conclusion
References
Comparison of Data Augmentation Techniques for Thai Text Sentiment Analysis
1 Introduction
2 Literature Review
2.1 Problems of Text Corpora
2.2 Text Sentiment Analysis
3 Research Methods
3.1 Thai Text Corpus Preprocessing
3.2 Thai Text Tokenization
3.3 Synthetic Texts Generation by Data Augmentation
4 Text Sentiment Classification
5 Analysis of Experimental Results
6 Conclusion
References
Jok Mae Jaem Woven Fabric Motif Recognition Using Convolutional Neural Network
1 Introduction
2 Related Work
3 Dataset and Methodology
3.1 Dataset
3.2 Convolutional Neural Networks Architecture
3.3 Model Training and Evaluation
4 Experimental Results and Discussion
5 Conclusion
References
Project Management Tools Selection Using BWM TOPSIS
1 Introduction
2 Related Work
2.1 Project Management Knowledge Areas
2.2 Multi-criteria Decision-Making (MCDM)
2.3 Best-Worst Method (BWM)
2.4 Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)
2.5 Analytical Hierarchical Process (AHP)
3 Methodology
3.1 Determine Decision Criteria
3.2 Determine the Preference of the Criteria
3.3 Compute the Optimal Weights
3.4 Compute the Optimal Weights of the Alternatives for Each Criterion
3.5 Construct the Weighted Normalized Decision Matrix
3.6 Determine Ideal and Negative-Ideal Solutions
3.7 Compute the Separation Measure
3.8 Compute the Relative Closeness to the Ideal Solution
3.9 Rank the Alternatives
3.10 Evaluate by Measuring Computational Complexity and Consistency
4 Experimental Result
4.1 Criteria for Project Management Tool Selection
4.2 The Best Project Management Tool
4.3 Computational Complexity
4.4 Consistency
5 Conclusion
References
Holistic Evaluation Framework for VR Industrial Training
1 Introduction
2 Theories and Related Works
2.1 Pedagogical Approach
2.2 Applied Training Model Approach
2.3 Biometric Measurement Approach
3 Conceptual Approach
3.1 Approach Overview
3.2 Pretest/Posttest Analysis
3.3 Activity Data Log
4 Results and Discussion
4.1 Phase I: Development
4.2 Phase II Evaluation
4.3 Phase III Framework Development
5 Conclusion
References
Rice Diseases Recognition Using Transfer Learning from Pre-trained CNN Model
1 Introduction
2 Background Knowledge
2.1 InceptionV3
2.2 Xception
2.3 ResNetV2
2.4 InceptionResNetV2
2.5 DenseNet
2.6 Transfer Learning
2.7 Image Data Augmentation Technique
3 Experiment
3.1 Dataset Preparation
3.2 CNN Model and Their Setting
3.3 Experimental Result of the Original Dataset
3.4 Performance Improvement
4 Results and Discussion
5 Conclusion
6 Future Work
References
Machine Learning-Based Methods for Identifying Bug Severity Level from Bug Reports
1 Background
2 Datasets
3 Analysis Method for Bug Severity Identification
3.1 Pre-processing Bug Reports
3.2 Representation of Bug Reports and Term Weighting
3.3 Modeling of Bug Severity Analyzer
4 The Results
5 Conclusion and Future Work
References
Sliding-Window Technique for Enhancing Prediction of Forex Rates
1 Introduction
2 Literature Review
3 Methodology
3.1 Overview
3.2 Input Data
3.3 Data Manipulation
3.4 Modeling
3.5 Output Data
4 Results
5 Conclusion
References
Author Index

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