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The Logo Detection in an Illegitimate Web Page

The Logo Detection in an Illegitimate Web Page

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International Conference on Information Technology (INCIT)

作者： Kanokporn Pakhamwang Narathip Sriherun Noppason Waikawee Promchat Jaijith Suppakarn Chansareewittaya Mahamah Sebakor School of Information Technology Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center Mae Fah Luang University

The growth of the online market is rapid. On the other hand, the fraud of brand products are significant serious issue. To mitigate these issues we proposed an intelligent system called The logo detection on an illegitimate web page. we use Convolutional Neural Networks(CNN) for detecting online fake logos on unauthorized web pages. moreover, the evaluation of our performance is presented. Finally, we apply our method to the real world through an online search of the Mae Fah Luang University’s logo on the illegitimate web page. The result outstanding shows us that our proposed is useful for the fake logos detection.

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LoRaWAN GPS Tracker

LoRaWAN GPS Tracker

引用

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

作者： Nattaphit Jengsriwong Suppakarn Chansareewittaya School of Information Technology Mae Fah Luang University Chiang Rai Thailand Computer and Communication Engineering for Capacity Building Research Center Thailand

In this paper, the real practical tests of applied LoRaWAN are presented. The esp32 with LoRaWAN is used as the mainboard. The used RSSI signal strength unit is dB. The cases of testing include indoor and outdoor. Moreover, indoor testing combines both single-stair and multi-stair. The horizontal and diagonal directions are included, too. After that, the GPS module is attached to this mainboard for sending the location of the testing board via LoRaWan. The final testing shows the long distance. The longest distance signal testing is 5.67 km. The benefit of this testing is to develop for more distance and apply to any application. The final product of the developed GPS tracker can be used in various applications such as tracking lost children of the lost vehicle in the future.

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Lifestyle Classification for Recommendation of Excessive Sugar Consumption in Thai Teenagers 6

Lifestyle Classification for Recommendation of Excessive Sug...

引用

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

ISBN: (纸本)9781665415699

Healthy food consumption is one of the most important aspects of life. Consuming adequate nutrition may not only keep healthy but also prevent many diseases. The consumption of sugar should be given the same attention, as many foods, especially in Thailand, are prepared with sugar as the main ingredient. In addition, the personal health and behavior of consuming excessive amounts of sugar per day are neglected by ordinary consumers as well as teenagers and they are not properly recommended by experts. This study aims to create an automated, accurate, and suitable lifestyle classification of a recommendation system for Thai teenagers with different lifestyles and health conditions. A model of the decision tree was proposed in this study along with the optimized metric. The data is collected from 349 teenagers. The results show that the decision tree with Information Gain provides the highest accuracy of 95.90%. © 2021 IEEE.

关键词： Decision trees

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Proposing ChatGPT as a Transformative Tool for Enhancing ESL Speaking and Listening Skills: Bridging research Gaps in Thai Education 10

Proposing ChatGPT as a Transformative Tool for Enhancing ESL...

引用

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： Dawilai, Sirikanya Yooyativong, Thongchai Kamyod, Chayapol Chiang Rai Rajabhat University Faculty of Humanities and Social Sciences Chiang Rai Thailand Mae Fah Luang University Center of Excellence in Artificial Intelligennce and Emerging Technology School of Applied Digital Technology Chiang Rai Thailand Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center School of Applied Digital Technology Chiang Rai Thailand

ISBN: (纸本)9798331543273

The development of speaking and listening skills remains a significant challenge in English as a Second Language (ESL) education, particularly in non-native English-speaking contexts such as Thailand. Traditional tools and methods often fail to provide personalized, real-time conversational practice, leaving gaps in learners' communicative competence. This paper explores ChatGPT, a conversational AI, as a potential solution to these challenges. By conducting a comprehensive review of existing tools and identifying research gaps, this study proposes a conceptual framework for integrating ChatGPT into ESL education, particularly for Thai students at Chiang Rai Rajabhat University (CRRU). This framework highlights how ChatGPT's interactive capabilities can address cultural and linguistic barriers, enhance learner engagement, and provide scalable solutions for improving speaking and listening skills. The paper concludes with recommendations for future research and practical implications for educators. © 2025 IEEE.

关键词： Students

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Deep Learning for Cognitive Detection based on P300 Event-Related Potential 7

Deep Learning for Cognitive Detection based on P300 Event-Re...

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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： Chaisricharoen, Roungsan Temdee, Punnarumol Srimaharaj, Wanus Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Chiang Rai57100 Thailand Payap University The International College Department of Information Technology Chiang Mai50000 Thailand

ISBN: (纸本)9781665495103

Due to the mechanical demands on real-time operations of brain signal reflection, manual parsing, and detection of the Event-Related Potential waveform, especially P300 evoked potential is impropriate and too slow. In addition, traditional methods require specialized knowledge and experience as well as experts to operate. Therefore, a faster and easier method is essential. The application of machine learning is a very reliable and popular method for classifying large and complex data in a short time. Therefore, this study presents a method to classify P300 in ERP waveforms using a deep learning algorithm which provides accurate and reliable results. It allows common and advanced users to detect the P300 evoked potential without specific skill and quickly deploy it to the BCI cases. © 2022 IEEE.

关键词： Deep learning

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Industrial requirements analysis for Excellence Center setting-up and curriculum design in Industry 4.0 context 8

Industrial requirements analysis for Excellence Center setti...

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Joint 8th International Conference on Digital Arts, Media and Technology and 6th ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2023

作者： Wicha, Santichai Temdee, Punnarumol Kamyod, Chayapol Chaisricharoen, Roungsan 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 France

ISBN: (纸本)9798350396546

The needs of industrial workforces have changed in the Industry 4.0 era. The knowledge worker in charge of information systems and internal operations was divided into different roles, and they each used different working methods and concepts. Despite this, Industry 4.0's consolidation has promoted the growth of servicing workforce with both computational complexity and equipment maintenance skills. An industrial requirements analysis is conducted in this paper to identify the key skills and competencies needed for setting up and designing an Excellence Center in the context of Industry 4.0. A diverse group of industry experts are surveyed to gather their insights on the most important areas of focus for such a center. The findings indicate that the key competencies needed for success in an Industry 4.0 setting include digital literacy, data analysis, and the ability to work with advanced technologies such as artificial intelligence and the Internet of Things. Based on these findings, a curriculum for the Excellence Center is proposed that prioritizes these competencies and includes hands-on training and practical experience. Overall, this paper contributes to the understanding of the requirements for Industry 4.0 and provides a roadmap for setting up and designing an Excellence Center to meet these requirements. © 2023 IEEE.

关键词： Industry 4.0

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The Practical IoT System Designed for a Melon Farm: A Case Study for Farmer Development in Northern Thailand Region 7

The Practical IoT System Designed for a Melon Farm: A Case S...

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作者： Kamyod, Chayapol Yooyatiwong, Thongchai Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Chiang Rai57100 Thailand Mae Fah Luang University School of Information Technology Chiang Rai57100 Thailand

ISBN: (纸本)9781665495103

Chiang rai is the northern Thai province with the most melon farms and the greatest potential for farmer profit. Premium melon cultivation, on the other hand, needs more preparations than a standard melon farm, such as irrigation and fertilization from seeding through harvesting. Melon requires varied watering and fertilizer for each cultivation phase to achieve excellent product output and quality per crop. Furthermore, there are other obstacles and issues along the process, such as pests and plant disease. Furthermore, owing to the change in humidity between day and night in the greenhouse throughout the winter and rainy season, numerous melon diseases may be easily detected. This can lead to illness and the breaking of the entire melon plant. If the melon is not properly cared for at the beginning of planting. Currently, all processes are carried out by humans. As a result, a large number of melon farms require a significant number of human resources and money. Furthermore, employees may make errors in measuring the amount of fertilizer solution as well as preparing the needed fertilizer solution and water for each planting phase. This can also have an impact on and damage the entire melon plant. Moreover, most of the melon farms are small and medium size farms owned by low-middle income farmers who are incapable of high investment on smart equipment. As a result, the focus of this research, sponsored by the National Broadcasting and Telecommunication Commission (NBTC), is on the design and implementation of affordable IoT solutions for the small-medium melon farms. There are two proposed systems: fertilization-irrigation system and an environmental control system. The proposed approach has been proven to be effective for small and medium-sized farms. Furthermore, the resulting technology is affordable and may be further improved for application in greenhouse cultivation of other plants. © 2022 IEEE.

关键词： Internet of things

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A Comparative Study of Image Enhancement Methods for Human Skin Image 7

A Comparative Study of Image Enhancement Methods for Human S...

引用

作者： Saiwaeo, Sirawit Mungmai, Lapatrada Preedalikit, Weeraya Arwatchananukul, Sujitra Aunsri, Nattapol Mae Fah Luang University School of Information Technology Thailand University of Phayao Division of Cosmetic Science School of Pharmaceutical Sciences Thailand Computer and Communication Engineering for Capacity Building Research Center Mae Fah Luang University Thailand

ISBN: (纸本)9781665495103

A person's skin serves as a primary line of protection against harmful chemical exposure. During the Covid 19 out-break, customer-provider interactions on social media increased, leading to improvements of the intelligent system for accurate skin type analysis. However, optimizing image quality before further analysis is an important step for training and testing data. As a result, image enhancement technologies contribute to the improvement of image quality. In this paper, we presets a study of four image enhancement techniques for improving the image contrast and detail of facial skin images required for further skincare analysis and treatment. The techniques of image enhancement include Histogram Equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Brightness Preserving Dynamic Fuzzy Histogram Equalization (BPDFHE), and Min-Max Contrast Stretching. The experimental results demonstrate that the CLAHE technique delivers the highest quality of clarity and also facilitates further image processing. © 2022 IEEE.

关键词： Image enhancement

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Real Estate Management System of Personal Seekers for Investment Decision 7

Real Estate Management System of Personal Seekers for Invest...

引用

作者： Chongdarakul, Waralak Rongbutsri, Nikorn Temdee, Punnarumol Mae Fah Luang University School of Information Technology Chiang Rai57100 Thailand Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Chiang Rai57100 Thailand

ISBN: (纸本)9781665495103

Real estate for residence consists of various types such as houses, town houses, condominiums, and vacant land. The residence for sale can be found by the buyer who searches for their preferred information through websites, social media, visiting the real places and more. To find candidate properties has been so complicated and time-consuming since they are large amount of data and many factors to be considered. The residence seeker and investors also have problems of storing plenty of real estate and organizing their property information. The complicated property information causes the seeker difficult to compare many property lists and select the best choice for investment. Many existing websites offer the real estate markets for people who looking for property investment or residence and support real estate agencies and owners to advertise their properties to the right target audiences. However, these websites do not support for personally collecting the buyers' preferred estates found from various sources *** for sale at the real location, or from other web sites. As this motivation, this paper introduces the real estate management system for buyers to personally collect their property information related to the investment decision making. The mobile based application is proposed for collecting house and land data with geographical position at the real place. Meanwhile, the web application is created to handle the backend services, and provides all functions of the property management. Unlike other real estate applications, the proposed system offers features of the property information sharing as the personal group formed by investors. The evaluation of user satisfaction shows that our proposed system is practically used and satisfied. © 2022 IEEE.

关键词： Websites

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Intelligent Genetic Crossover Algorithm for Improving State Estimation in Particle Filtering

Intelligent Genetic Crossover Algorithm for Improving State ...

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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

Particle filtering (PF) is a Monte Carlo (MC) method widely employed to sequentially approximate the time-varying posterior PDF of states or values of variables of interest conditional to noisy observation data from non-linear/non-Gaussian dynamic systems. In many applications, we also infer (or estimate) the hidden state from the obtained approximated posterior PDF. Particles are randomly drawn samples of state vectors that form the approximation of the posterior PDF. However, representation of the approximated posterior PDF may not always be good because sometimes there can be only a few particles with low likelihoods (or importance weights), while there can be many particles with near-zero (or negligible) weights. New state vectors with high weights then should be introduced to the swarm in order to reshape the approximated posterior PDF. This paper introduces an intelligent genetic crossover algorithm (IGCA) that assists PF by applying crossover schemes employed in genetic algorithms (GAs) to reshape the approximated posterior PDF. Experimental results shown that the proposed algorithm improved the accuracy and performance in nonlinear state estimation.

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