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10th International Conference on Digital Arts, Media and Technology and 8th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2025

作者： Yahoui, Hamed Chaisricharoen, Roungsan Srimaharaj, Wanus University of Claude Bernard Lyon 1 Department of Mechanics France Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center School of Applied Digital Technology Chiang Rai57100 Thailand Payap University The International College Chiang Mai50000 Thailand

ISBN: (纸本)9798331543273

This paper presents the comprehensive design and implementation of a Power Hardware-in-the-Loop (PHIL) educational benchmark system for smart grid scenarios. The system features an advanced electrical cabinet incorporating multiple bidirectional DC-DC converter legs with a common 100kW grid connection interface, a back-to-back front-end grid-side converter with galvanic isolation, and an internal DC link. The hardware-in-the-loop (HIL) architecture enables real-time control and monitoring through MATLAB-Simulink integration, supported by a real-time target system. The benchmark demonstrates various DC microgrid configurations through four operational scenarios: independent converter control, microDC network emulation, battery-to-battery energy transfer, and renewable energy integration. Operating at high efficiency (>95%), the system serves as a power electronics educational platform at the University of Lyon 1, providing hands-on experience with smart grid technologies. The design emphasizes energy-efficient operation through regenerative capabilities between DC legs, while maintaining robust safety protocols for both equipment and users. This educational benchmark system bridges the gap between theoretical power electronics education and practical smart grid implementation, offering a versatile platform for studying real-time control strategies and renewable energy integration. © 2025 IEEE.

关键词： Electric power transmission networks

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Sequential Frequency Estimation Using Auxiliary Particle Filter

Sequential Frequency Estimation Using Auxiliary Particle Fil...

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International Conference on Information Technology (INCIT)

作者： Chanin Kuptametee Nattapol Aunsri School of Information Technology Mae Fah Luang University Chiang Rai Thailand Computer and Communication Engineering for Capacity Building Research Center Chiang Rai Thailand

Frequency estimation is an important and challenging task in signal processing and related applications. However, the measurement signals are contaminated with undesired noise sources in practice, and the true frequencies, hence, cannot be extracted directly. Particle filtering (PF) is a sequential Monte Carlo (SMC) method that is proved efficient and effective in estimating the frequencies from the timefrequency representations (TFRs). There are many techniques proposed to enhance estimation performance of PF. This work conducts a study on the performance in estimating frequencies from the spectrogram of the signal (computed using shorttime Fourier transform (STFT) using sequential importance resampling (SIR) PF and auxiliary PF (APF). APF is proved to providing superior performance in frequency estimation at low signal to noise ratios (SNRs).

关键词： Time-frequency analysis Atmospheric measurements Estimation Particle measurements Frequency estimation Particle filters Frequency diversity

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A Study of Generative Large Language Model for Healthcare

A Study of Generative Large Language Model for Healthcare

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International Conference on Information Technology (INCIT)

作者： Seong-Gyeol Park Ahtae Kim Taewoong Yoon Chayapol Kamyod Cheong Ghil Kim Dept of Computer Scicence Namseoul University Choongnam Korea Excellence Center of Industry 4.0 textitComputer and Communication Engineering for Capacity Building Research Center School of Information Technology Mae Fah Luang University Chiang Rai Thailand

The expansion of the 4th Industrial Revolution is making it easier to collect and analyze big data through cloud technology. In addition, advances in semiconductor design and manufacturing technology are accelerating the development of artificial intelligence due to improvements in computer processing speed and performance. These developments in artificial intelligence technology are expected to be applied to the healthcare industry and create new value. Recently, ChatGPT, which has evolved one step further, has emerged, bringing about the development of a new technology called ‘Generative AI’. Research is being actively conducted on how AI can replace fields that were considered the exclusive domain of humans with specialized knowledge, such as medicine and law. In this study, we aim to take the opportunity to identify trends in the healthcare field of generative AI.

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Particle Filtering with Adaptive Diversifying Scheme for Abruptly Changing Hidden States Estimation

Particle Filtering with Adaptive Diversifying Scheme for Abr...

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International Conference on Information Technology (INCIT)

Particle filtering (PF) is a powerful sequential Monte Carlo (SMC) method used to estimate hidden states of parameters of interest from noisy measurements obtained from dynamic systems. The particles are randomly drawn samples of all possible hidden states according to previous knowledge or prior information, if any. Degeneracy occurs when only a few particles locate in high-probability regions (or have significant weights), while the others locate in low-probability regions. Resampling is a simple and straight forward way to tackle degeneracy but introduces another problem called particle impoverishment that destroys particle diversity. Conseqeuntly, the particles are not able to find the high-likelihood state values in the next step, that may suddenly vary from the current values. This paper proposes a scheme to ensure that the particles remain adequately diverse to cover high-likelihood values during the prediction stage. When noisy measurement becomes available, particles are herded to form a better approximation of the posterior probability density function (PDF) of the hidden state that can then be estimated or inferred with high accuracy.

关键词： Monte Carlo methods Atmospheric measurements Density measurement Probability density function Particle measurements Information filters Noise measurement

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Design and Deployment of Online PBL Model for High School Students Promoting Collaborative Learning 6

Design and Deployment of Online PBL Model for High School St...

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Joint 6th International Conference on Digital Arts, Media and Technology with 4th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunication engineering, ECTI DAMT and NCON 2021

作者： Gasonpan, Natticha Temdee, Punnarumol Mae Fah Luang University School of Information Technology Chiang Rai Thailand Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Chiang Rai Thailand

ISBN: (纸本)9781665415699

Problem (Project) Based Learning has been applied successfully in many fields in many higher educational institutions worldwide to develop learning efficiency though idea exchanging, debating and interacting. Students learn how to analyze the given problems, develop thinking s and self-study skills from learning activities in the classroom. Recently, COVID-19 is a major factor contributing to the digital transformation for learning. From offline to online learning, all students are required to adapt their preference of normal learning including high school students. This paper presents the design and the deployment of online Problem (Project) Based Learning for high school students so that enhance their learning efficiency and develop collaborative learning skill required for the future employment. © 2021 IEEE.

关键词： Students

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Preparation of an Excellence Center in Industry 4.0 based on computer engineering Paradigm 14

Preparation of an Excellence Center in Industry 4.0 based on...

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14th International Conference on Software, Knowledge, Information Management and Applications, SKIMA 2022

作者： Chaisricharoen, Roungsan Temdee, Punnarumol Kamyod, Chayapol Wicha, Santichai Thiriet, Jean-Marc Yahoui, Hamed Excellence Center in Industry 4.0 Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Mae Fah Luang University Chiang Rai Thailand Univ. Grenoble Alpes Gipsa-Lab Grenoble France Dépt Mécanique Univ. Claude Bernard Lyon 1 Lyon France

ISBN: (纸本)9781665493345

The presence of Industry 4.0 has altered the requirements of industrial workforces. Previously, the personnel in charge of information systems and plant operations were divided and worked in different concepts and methods. Nevertheless, the convergence of Industry 4.0 has encouraged the development of maintenance workforces capable of both information processing and machine maintenance. In response, an excellence center in Industry 4.0 in as aspect of computer engineering discipline is to be established to support the paradigm change in industry. The Asean Factori 4.0 project, an ERASMUS+ project funded by the European Union, is assisting with the process. The preparation of the excellence center is divided into two parts: the hardware and software definitions, and the staff preparations. The design and delivery of hardware and software is progressed according to the schedule, and the staff are being prepared as intended in the form of seminar and training. The feedback and evaluation strongly state that the audiences and the trainees are well satisfied and educated. © 2022 IEEE.

关键词： Industry 4.0

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Gold-Price Forecasting Method Using Long Short-Term Memory and the Association Rule

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Journal of Mobile Multimedia 2023年第1期19卷 165-186页

作者： Boongasame, Laor Viriyaphol, Piboonlit Tassanavipas, Kriangkrai Temdee, Punnarumol Department of Mathematics Faculty of Science King Mongkut’s Institute of Technology Ladkrabang Bangkok 10520 Thailand Business Innovation and Investment Laboratory: B2I-Lab Faculty of Science King Mongkut’s Institute of Technology Ladkrabang Bangkok 10520 Thailand Gold Research Center Gold Traders Association Bangkok Thailand Faculty of Engineering and Technology Panyapiwat Institute of Management Nonthaburi 11120 Thailand Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Mae Fah Luang University Chiang Rai 57100 Thailand

Since gold prices influence international economic and monetary systems, numerous studies have been conducted to forecast gold prices. Nonetheless, studies employing the linear relationship method usually fail to explain the change in the pattern of the gold price. This study introduces a new paradigm that incorporates association rules and long short-term memory (LSTM) as a nonlinear-based method. For simulation, the proposed method was analyzed with data from Yahoo Finance from January 2010 to December 2020. The association rule was used to choose features relevant to the gold spot (GS) in the US Dollar Index (DXY). The LSTM forecast the gold price with a range of hyperparameter settings. The simulation results showed that the proposed method—the LSTM with GS and DXY, or LSTM-GS-DXY—resulted in low mean absolute percentage error (MAPE) metrics. In addition, the proposed LSTM-GS-DXY system outperformed the simple moving average (SMA), weight moving average (WMA), exponential moving average (EMA), and auto-regressive integrated moving average (ARIMA). © 2022 River Publishers.

关键词： artificial neural network association rule gold forecasting LSTM

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EEG Age Prediction via Elastic Net Linear Regression

EEG Age Prediction via Elastic Net Linear Regression

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International Conference on Information Technology (INCIT)

作者： Sane Yu Wanus Srimaharaj Roungsan Chaisricharoen School of Applied Digital Technology Mae Fah Luang University Chiang Rai Thailand The International College Payap University Chiang Mai Thailand Computer and Communication Engineering for Capacity Building Research Center School of Applied Digital Technology Mae Fah Luang University Chiang Rai Thailand

ISBN: (数字)9798350366303

ISBN: (纸本)9798350366310

Accurate prediction of human age based on EEG signals presents a significant challenge due to the complex changes in brain function associated with aging. This study addresses these issues by proposing an advanced Elastic Net Linear Regression model to enhance prediction accuracy and model reliability. The proposed approach was evaluated on a EEG dataset of 109 samples, each representing 1000 milliseconds of brain activity. Comprehensive preprocessing techniques, including missing value imputation, feature scaling, and feature selection, were employed to prepare the data for the Elastic Net Regression model. The experimental results demonstrate the effectiveness of the Elastic Net Regression model, achieving a mean absolute error of 4.73 years and an R-squared score of 0.7626 on the test set. On the training set, the model’s performance was exceptional, with an MAE of 2.42 years and an R-squared of 0.9404, showcasing its ability to capture the complex relationship between brain activity and age. The model’s predictions were well-calibrated, with a mean of 45.49 years and a standard deviation of 15.80 years, indicating its reliability in representing the age distribution of the samples. The results contribute valuable insights into brain aging mechanisms and offer potential avenues for enhancing cognitive health interventions to support healthy cognitive aging and early intervention in age-related neurological disorders.

关键词： Neurological diseases Training Accuracy Linear regression Predictive models Aging Brain modeling Electroencephalography Data models Reliability

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CIA Analysis for LoraWAN communication Model

CIA Analysis for LoraWAN Communication Model

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International ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering (ECTI-NCON)

作者： Chayapol Kamyod School of Information Technology Computer and Communication Engineering for Capacity Building Research Unit Chiang Rai Thailand

ISBN: (纸本)9781665446914

IoT technologies have helped to advance numerous industries and innovations. Agriculture is one of the key industries in Thailand that is crucial for the country's economic growth. Therefore, many IoT devices and applications for agricultural industries have been created. LoraWan is one of the IoT communication protocols that was applied to various smart farm applications. As a result, IoT deployments can create complex and vulnerable systems. This paper analyzes the security factors of the LoRaWan system based on the Cybersecurity Cube, which is a three-pronged framework for computer security and information protection. The study offers important security details for agricultural IoT communications.

关键词： Economics Technological innovation Protocols Digital art computer architecture Media Environmental factors

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The Integration of Traditional Rural Solar Dryer with LoRa and IoT Technology

The Integration of Traditional Rural Solar Dryer with LoRa a...

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International ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering (ECTI-NCON)

作者： Thongchai Yooyativong Chayapol Kamyod Chong Ghil Kim School of Information Technology Mae Fah Luang University Chiang Rai Thailand Excellence Center of Industry 4.0 Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Mae Fah Luang University Chiang Rai Thailand Dept. of Computer Science Namseoul University Choongnam Korea

Traditional or rural dryers or Thai farmers' dryers have some drawbacks when compared to modern or commercial dryers on the market. Despite the fact that the dryer is vital and may be utilized as postharvest technology to preserve or produce some agricultural products, the farmer chose to build the traditional structure because of his limited income and resources. This research examined the needs of rural farmers and developed an integration of typical rural solar dryers or dryers using IoT technologies. The integrated design will preserve the structure's materials while increasing the system's capacity and efficiency to reduce costs. Farmers may now manage the temperature inside the dryer using the newly created mechanism. Remote monitoring and management are also made possible by the technology, minimizing the need for physical intervention. This leads to increased efficiency, lower costs, and a more sustainable energy source.

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