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Promotion Classification Using DecisionTree and Principal Component Analysis 7

Promotion Classification Using DecisionTree and Principal Co...

引用

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： Kaewwiset, Theeramet 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)9781665495103

The goal of human resource management is to support the employee to higher position promotion and improve their work performance. The key process for performance evaluation is promotion classification. This paper proposes the machine learning based promotion classification using decision tree and principle Component Analysis (PCA). This paper uses Human Resource Analysis Case Study dataset from Kaggle for comparing the promotion classification. The comparison of classification performance for all features, personal features, and performance features are conducted. The classification results show that the classification with PCA provides the highest accuracy at 91.25%. © 2022 IEEE.

关键词： Classification (of information)

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Knowledge Management System by applying Knowledge Creating Company: Transforming Tacit to Explicit Knowledge 7

Knowledge Management System by applying Knowledge Creating C...

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作者： Nupap, Soontarin Mae Fah Luang University Computer and Communication Engineering for Capacity Building Research Center School of Information Technology Chiang Rai Thailand

ISBN: (纸本)9781665495103

In this era, knowledge management system (KMS) has been accredited as a knowledge repository for utilisation in order to sustain knowledge sharing, capturing, and institutionalising from organisational stakeholders as well as to maintain long-term competitive advantage and sustainable development. Relied on my preceding study that indicated an appropriate KM framework for quality assurance (QA) in management for education, this study endeavour to advocate a framework of KMS implementation based on knowledge creating company notation for a case study which is a group of research team within a university department in Thailand confronting the problems of failing to meet with a national QA standard, topic namely, 'research', by developing a KMS based on the prepared IC system from the preceding study including;knowledge creating company theory, software development life cycle(SDLC), and joint application development(JAD) in order to transform tacit knowledge to explicit knowledge and organise the explicit knowledge to a knowledge repository as a KMS. The initial findings disclose the suggested methodology wherein the KMS primarily applied for resolving problem in QA in management for education was appropriate to sustenance knowledge sharing and learning atmosphere for long-term competitive advantage and sustainable development. © 2022 IEEE.

关键词： Quality assurance

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Adaptive of New Technology for Agriculture Online Learning by Metaverse: A Case Study in Faculty of Agriculture, National University of Laos 7

Adaptive of New Technology for Agriculture Online Learning b...

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作者： Khansulivong, Chithtisack Wicha, Santichai 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)9781665495103

These papers investigated the adaption of the new technology for online learning in the COVID-19 situation, giving one more choice of online applications or programs for getting new experiences with online learning and creating ideas to resolve some of the current problems from online learning in some subjects. This study focuses to utilize the appropriate and new tools to motivate an online learning system during the Covid-19 pandemic in Lao PDR. This method had more functions of 3D for simulation the places and works by using smart mobile devices, computers, and other smart tools connecting to simulate real learning in the parts of technical and visiting were used on data collected from sample size audients from faculty of agriculture, National University of Lao, Ministry of technology and communication. The user satisfaction resulted and success rate of learning show that the positive result for technology adoption with the online learning system. © 2022 IEEE.

关键词： Agriculture

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Multi-Class Classification of Metabolic Syndrome Group Using Gradient Boosting 8

Multi-Class Classification of Metabolic Syndrome Group Using...

引用

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

ISBN: (纸本)9798350396546

Currently, metabolic syndrome, the leading cause of most of non-communicable diseases, has been overlooked because it is common and does not cause illness at the early stage. The purpose of this study was to classify the group of metabolic syndromes including diabetes, cardiovascular disease, and high blood pressure using machine learning based method. The data was collected from three sub-districts in the province of Chiang Rai: Mae Khao Tom, Nang Lae, and Tha Sud totally 1,605 records. The Gradient Boosting is proposed for the multi-class classification model. From the comparison results with other existing methods, including Random Forest, Extra Trees, K-nearest Neighbor, Support Vector Machines, and Decision Trees, Gradient Boosting outperforms other existing methods having 95.27% accuracy, 95.24% precision, 95.26% recall, and 95.24% F1 score, respectively. © 2023 IEEE.

关键词： Decision trees

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Sequential Frequency Estimation Using Auxiliary Particle Filter 6

Sequential Frequency Estimation Using Auxiliary Particle Fil...

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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

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). © 2022 IEEE.

关键词： Frequency estimation

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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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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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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 ...

引用

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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