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Understanding Human Balance Strategies Through Clustering of Motion Analysis Data 10

Understanding Human Balance Strategies Through Clustering of...

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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： Lapawong, Werapat Uttama, Surapong Rueangsirarak, Worasak Temdee, Punnarumol Hu, Shanfeng Aslam, Nauman Mae Fah Luang University Digital Transformation Technology School of Applied Digital Technology Chiang Rai Thailand Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center Chiang Rai Thailand Northumbria University Department of Computer and Information Sciences Newcastle upon Tyne United Kingdom

ISBN: (纸本)9798331543273

Balance is the result of complex interactions among individuals, tasks, and the environment. It plays a crucial role in daily activities, relying on sensory systems and joint movement strategies to maintain postural stability. Effective balance not only improves movement and physical activities but also enhances overall quality of life. Balance strategies, such as ankle, hip, knee, and stepping strategies, are essential for maintaining stability in various situations and environments. This study focuses on utilizing public data from the Clinical Test of Sensory Interaction on Balance (CTSIB) to assess balance strategies. Traditional methods rely on subjective observations, limiting the identification of nuanced strategy combinations. To overcome this, motion capture (mocap) data and unsupervised machine learning techniques, clustering and dimensionality. reduction using Agglomerative, Gaussian Mixture, and K-Means and classify balance strategies. The results demonstrate the potential of this approach to identify distinct clusters of balance strategies, offering a more detailed, objective, and comprehensive understanding of postural stability. Among the clustering algorithms applied, K-Means proved to be particularly effective, achieving reliable groupings with consistent results. The Silhouette Scores indicated that k=3, identified as the optimal number of clusters from the elbow test, provided the best balance between cohesion and separation for K-Means. This suggests that K-Means delivers interpretable clusters of balance strategies. The three possible outcomes are good balance, A slight unbalance and a poor balance. This innovative methodology advances the field of balance assessment by providing a clear and systematic approach to classifying balance strategies, allowing for better understanding and targeted interventions. © 2025 IEEE.

关键词： K-means clustering

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Pedagogical Benchmark for Smart Grid Scenarios 10

Pedagogical Benchmark for Smart Grid Scenarios

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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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Development of MFU WIFI MAP 6

Development of MFU WIFI MAP

引用

6th International Conference on Information Technology, InCIT 2022

作者： Chansareewittaya, Suppakarn Santithanmanan, Korrawit Bannasak, Chawarat Goythong, Anavil Sebakor, Mahamah Mae Fah Luang University School of Information Technology Thailand Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center Thailand

ISBN: (纸本)9781665489126

In the enterprise wireless network, It is a significant challenge to discover unstable access points. Many thousands of APs may be difficult for network administrators to search the failure APs. To address this issue, we proposed an application called WiFi MAP which is a web application that is extremely helpful for monitoring AP's status in the campus network and being able to track the location of each AP through a web *** this work, our development enables the network administrator to capture the real-time AP condition. In addition, we use the Simple Network Management Protocol (SNMP) to communicate between access points and our application. Then we show the performance and evaluation of our application in terms of real-world use. Moreover, we also apply our application to Mea Fah Luang University (MFU) and the Medical center hospital (MCH) of MFU. © 2022 IEEE.

关键词： Internet protocols

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Developing 21st Century Skills with Project-Based Learning: An Experience Report in the Introductory Course of Software engineering 7

Developing 21st Century Skills with Project-Based Learning: ...

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7th International Conference on Digital Arts, Media and Technology, DAMT 2022 and 5th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering, NCON 2022

作者： Arwatchananukul, Sujitra Singpant, Pattariya Chondamrongkul, Nacha Aunsri, Nattapol Mae Fah Luang University School of Information Technology Thailand Computer and Communication Engineering for Capacity Building Research Center Mae Fah Luang University Thailand

ISBN: (纸本)9781665495103

In a Project-Based Learning (PBL) environment, students are assigned to work on challenging and complicated projects. This environment suites the setting of teaching software engineering courses. Since software engineering not only requires students to gain practical knowledge but they also need to develop soft skills. These soft skills such as communicating, collaborating, being creative, and critically thinking, are essential in the 21st-century working environment. However, these skills are hard to develop during the pandemic of Covid-19 due to social distancing measurement. This paper presents an experience report of using PBL in an online classroom. We have conducted the self-assessment, in which the student's feedbacks have been summarized into positive, negative, and suggestive responses. These responses indicate that students can gain fundamental knowledge and experience in using soft skills when they learn in the PBL environment. Among various soft skills, we have found that collaboration skill can be improved the most. © 2022 IEEE.

关键词： Students

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Development of Smart Light Detection and Monitoring System with Machine Learning 7

Development of Smart Light Detection and Monitoring System w...

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作者： Chansareewittaya, Suppakarn Intan, Korawit Pramoonjakko, Nattapon Sripenbenja, Theerametha Kemavuthanon, Kemachart Laohapensaeng, Teeravisit Sebakor, Mahamah Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center Thailand Mae Fah Luang University School of Information Technology Thailand

ISBN: (纸本)9781665495103

In this paper, the smart light detection and monitoring system is presented. The light sensors are used to detect the light temperature value in the room. The Arduino UNO and ESP32 are used as the main embedded systems. The ZigBee transmitters are used as the main transmitter. MySQL is set as the database. Moreover, Machine Learning is used to classify the light temperature value to natural light or fluorescent light. Test result shows that the cross-validation accuracy of KNN is 0.996. This accuracy of KNN is greater than other algorithms. Moreover, this system can be used to examine the status of the light in the room that can solve the problem of forgetting to turn off the light and can analyze data of using light as well. © 2022 IEEE.

关键词： Zigbee

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An EMD with Masked WVDs for Cross-terms Reduction in Non-stationary Signals 7

An EMD with Masked WVDs for Cross-terms Reduction in Non-sta...

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

ISBN: (纸本)9781665495103

Signals commonly found in real-world applications are non-linear, multi-component, and non-stationary. For simplicity, they are analyzed and processed in time-frequency (TF) domain. Wigner-Ville distribution (WVD) is a method that provides time-frequency representation (TFR) of a signal with high-sharpness resolutions. However, its bilinear nature causes false frequency components called 'cross-terms' to occur between the real components of the multi-component signal. WVDs of mono-component but non-linear signals also suffer from cross-terms problem. Empirical mode decomposition (EMD) is a data-driven algorithm used to decompose a multi-component signal into subcomponents called intrinsic mode functions (IMFs). This paper applies WVD masking for each extracted signal components obtained from EMD to ensure that the cross-terms will be suppressed, especially if there are non-linear IMFs. Also, masked WVDs using different linear TF methods are also investigated to obtain the comparative results. The results revealed that by using the masked WVDs to EMD, the cross-terms were satisfactory removed. © 2022 IEEE.

关键词： Empirical mode decomposition

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Particle Filtering with Adaptive Diversifying Scheme for Abruptly Changing Hidden States Estimation 6

Particle Filtering with Adaptive Diversifying Scheme for Abr...

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6th International Conference on Information Technology, InCIT 2022

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

ISBN: (纸本)9781665489126

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. © 2022 IEEE.

关键词： Probability density function

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Classification Model of Dementia and Heart Failure in Older Adults Using Extra Trees and Oversampling-Based Technique

Classification Model of Dementia and Heart Failure in Older ...

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

作者： Pornthep Phanbua Sujitra Arwatchananukul Punnarumol Temdee Computer and Communication Engineering for Capacity Building Research Center School of Applied Digital Technology Mae Fah Luang University Chiang Rai Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

Dementia (DM) and heart failure (HF) are prevalent and concerning medical conditions among older adults. Several studies indicate that individuals with HF have more risk of developing DM, underscoring the significant correlation between these two conditions. This proposed classification model employed Extra Trees (ETs) to develop a classification model for dementia and heart failure from electronic health records from Chiangrai Prachanukroh Hospital in Chiang Rai Province, Thailand, totally 4,297 records. The imbalanced data was addressed by using Synthetic Minority Oversampling Technique for Nominal and Continuous (SMOTENC). Its performance was evaluated against other methods, including Decision Trees (DT), K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Random Forest (RF), Gradient Boosting (GB), and Adaptive Boosting (AB). The findings indicated that the proposed ET model surpasses alternative methods in accuracy (89.11%), precision (94.92%), recall (92.50%), F-measure (93.70%), and receiver operating characteristic area under the curve (ROC AUC) score (78.88%).

关键词： Support vector machines Radio frequency Measurement Hospitals Nearest neighbor methods Data models Cardiovascular diseases Older adults Random forests Dementia

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Machine Learning Based Pose Identification System with Force-Sensitive Resistors for Four-Step Balance Testing

Machine Learning Based Pose Identification System with Force...

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

作者： Thanapat Sanongyat Chayapol Kamyod Punnarumol Temdee Computer and Communication Engineering for Capacity Building Research Center School of Applied Digital Technology Mae Fah Luang University Chiang Rai Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

This study proposes a system to identify poses based on the 4-stage balance test for fall risk assessment using custom-developed, pressure-sensitive footwear equipped with force-sensitive resistors (FSRs) and machine learning (ML) models. The system captures and analyzes pressure distribution data during balance tests to predict types of poses. Data was collected from 30 healthy participants aged 18-25 years performing standard balance tests. Preprocessing steps included data cleaning, normalization, and feature extraction. Three ML models—Long Short-Term Memory (LSTM), Random Forest (RF), and Gradient Boosting (GB)—were evaluated. The LSTM model achieved the highest performance in terms of accuracy, precision, recall, and F1-scores, demonstrating its capability in handling sequential data. The system shows promise as a cost-effective tool for pose identification to aid fall risk assessment, though further research is needed to expand the dataset diversity and refine the algorithms. This study provides a foundation for developing scalable tools to assess and mitigate fall risks, particularly among vulnerable populations.

关键词： Resistors Accuracy Footwear Predictive models Risk management Long short term memory Wearable sensors Standards Random forests Testing

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Developing a RAG Agent for Personalized Fitness and Dietary Guidance

Developing a RAG Agent for Personalized Fitness and Dietary ...

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

作者： Min Swan Pyae Sai Sithu Phyo Saw Thomas Maung Maung Kyaw Thet Swe Lin Nacha Chondamrongkul Computer and Communication Engineering for Capacity Building Research Center School of Applied Digital Technology Mae Fah Lunag University Chiang Rai Thailand

ISBN: (数字)9798331543273

ISBN: (纸本)9798331543280

This paper focuses on implementing and evaluating a Retrieval-Augmented Generation (RAG) system that provides personalized fitness and dietary guidance by combining real-time data from wearable devices with curated knowledge sources. While the current implementation depends on a carefully selected set of PDF files as a source of knowledge base, extracting relevant information in order to frame the answer to a question by the user, the planned integration of a curated, well-structured database aims to enhance the system’s reliability and scope. The paper presents an overview of RAG-based system-related literature, describes the process of implementing the RAG component, and discusses the effectiveness in generating relevant and accurate answers. This implementation demonstrates the capability of RAG technology to develop interactive and effective solutions for dietary and fitness applications and sets a foundation for further system improvements.

关键词： Technological innovation Accuracy Databases Retrieval augmented generation Transforms Text to speech Reliability Time factors Wearable devices Usability

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