Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    UID:
    edoccha_9961128713802883
    Format: 1 online resource (221 pages)
    Edition: 1st ed. 2023.
    ISBN: 3-031-30474-8
    Series Statement: Lecture Notes in Networks and Systems, 679
    Content: This book gathers the high-quality papers presented at the 19th International Conference on Computing and Information Technology (IC2IT2023), held on May 18–19, 2023, in Bangkok, Thailand. The book presents an original research work for both academic and industry domains, which is aiming to show valuable knowledge, skills and experiences in the field of computing and information technology. The topics covered in the book include natural language processing, image processing, intelligent systems and algorithms, as well as machine learning. These lead to the major research directions for innovating computational methods and applications of information technology. .
    Note: 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.
    Additional Edition: ISBN 9783031304736
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages