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Dry-season sources of riverine sediment from the tropical mixed urban-agricultural watershed of the Mun River Basin in northeastern Thailand

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International Journal of Sediment Research 2023年第2期38卷 240-252页

作者： Arika Bridhikitti Thayukorn Prabamroong Gaohuan Liu Environmental Engineering and Disaster Management Program School of Interdisciplinary Studies Mahidol University Kanchanaburi Campus Earth Science Research Center Mahidol University Kanchanaburi Campus Faculty of Environment and Resource Studies Mahasarakham University State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences

Northeastern(NE) Thailand is well recognized as the land for rice cropping and consequently, it is potentially contaminated with chemicals from soil fertilization, pest/weed control, and urban *** Mun River basin in NE Thailand principally is comprised of rice paddies and sedimentation in the river has been pronounced, but the studies on sediment source identification are limited. The current study aims to identify sediment sources in the Mun River basin and discuss possible impacts on ecosystems attributed to exposure to polluted sediment. The assessment relies upon physicochemical properties and heavy metal contents(iron(Fe), manganese(Mn), copper(Cu), chromium(Cr), nickel(Ni),and Zinc(Zn)) in the fine-grained sediment(<63 μm) taken from the Mun River basin and the Chi River in the dry season of 2020-2021. The findings revealed that the heavy metals in the sediment had not accumulated to levels of concern. Most sediment was from natural sources, including Fe-and Mn-rich sediment, Cr-dominant sediment, and Ni-and Cu-rich sediment. Fe-and Zn-rich sediment was, however, found in the urban watershed of Lam Ta Klong, and it could originate from mixed urban sources. Ferich sediment was predominant in the Mun River basin, which and could be a significant sink and source of toxic elements from agricultural and urban discharges. It is suggested that the toxic compounds in the sediment should be consistently monitored, whereas ecological and health risk assessment should be focused on the mobile forms.

关键词： Sediment Heavy metals Mun River Lower Mekong River Agriculture

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A Hybrid Learning Approach for Automatic Data Labelling and Anomaly Detection in IoT Networks 3

A Hybrid Learning Approach for Automatic Data Labelling and ...

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3rd IEEE International Conference on Artificial Intelligence, ICAI 2023

作者： Kanwal, Rimsha Noor, Umara Rashid, Zahid International Islamic University Faculty of Computing and Information Technology Department of Computer Science Islamabad Pakistan College of Engineering Technology Management Economics and Policy Program Seoul National University Seoul Korea Republic of

ISBN: (纸本)9798350322125

Internet of Things (IoT) is an environment in which digital equipment is augmented with sensors to share and receive data through network. When devices share data it can be effected by anomalies or any attack due to corrupted data or by any other uncertainty and ambiguity in data. The data can also be corrupted through a damage in device. These attacks or anomalies damage the working of the IoT networks. The anomalous data can be detected through detection techniques however most anomaly detection techniques depend upon labelled data but for IoT datasets, usually class labels are not available. Labeling is performed by a manual process which is time consuming and also costly. As data in IoT increases day by day so there is a need to label and classify data for future unseen data. In this paper a hybrid algorithm is proposed in which both clustering and classification techniques are applied for automatic labeling and classifying on IoT dataset. The model contains two function. In the first phase k-means clustering is employed for labelling dataset instances as normal or anomalous. In the second phase labelled dataset is used to train Random Forest model to detect anomalies in IoT networks. The results show that the proposed model is detecting anomalies in IoT networks with an accuracy 98%, precision 98 %, recall 98%, and F-meausre 0.98%. © 2023 IEEE.

关键词： Classification (of information)

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Awareness of Disaster Risk and Preparedness: Insights from a Survey of Children and Adults in Thailand 23

Awareness of Disaster Risk and Preparedness: Insights from a...

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23rd International Symposium on Communications and information Technologies, ISCIT 2024

作者： Laosunthara, Ampan Leelawat, Natt Ohashi, Takumi Sararit, Titaya Srivichai, Mongkonkorn Tang, Jing School of Environment and Society Tokyo Institute of Technology Tokyo Japan Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Chulalongkorn University Disaster and Risk Management Information Systems Research Unit Bangkok Thailand Graduate School of System Design and Management Keio University Kanagawa Japan Tokyo Institute of Technology Department of Transdisciplinary Science and Engineering Tokyo Japan Chiangmai University Faculty of Architecture Chiangmai Thailand Rajamangala University of Technology Lanna Faculty of Engineering Department of Civil Engineering Chiangrai Thailand International School of Engineering Chulakongkorn University Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9798350353952

Enhancing disaster awareness and preparedness is crucial for building resilient societies. This study comprehensively assessed the levels of disaster awareness and preparedness among children and adults in Thailand through qualitative and quantitative surveys. Children strongly emphasized the importance of disaster education in school curricula, leveraging multimedia channels for risk communication, and implementing early warning systems. In contrast, adults exhibited a greater understanding of the significance of business continuity and disaster management technologies. These findings revealed disparities in disaster awareness across age groups. The insights from this study suggest age-specific engineering system approaches to information dissemination, contributing to the development of inclusive disaster preparedness strategies that incorporate diverse stakeholder perspectives. Children highlighted the need for practical training on survival skills, accessible disaster communication through SMS alerts, and monitoring systems for timely information dissemination. Adults, on the other hand, placed greater importance on business continuity planning and recognized the usefulness of technologies like satellite imagery for disaster management. By identifying these gaps and areas for improvement, this research provides valuable guidance for tailoring interventions, fostering a culture of preparedness, and harnessing technological solutions that resonate with the needs and concerns of different age cohorts within Thai society. © 2024 IEEE.

关键词： Satellite imagery

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Revolutionizing Pharmaceutical Cold Chain Competency Framework with Reference Process Model and Reference Architecture

HighTech and Innovation Journal

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HighTech and Innovation Journal 2023年第2期4卷 387-401页

作者： Latha, Divya Sasi Samanchuen, Taweesak Technology of Information System Management Division Faculty of Engineering Mahidol University Nakhon Pathom73170 Thailand

The utilization of the reference process model (RPM) and reference architecture (RA) as disruptive information and communication technologies (ICT) in the pharmaceutical cold chain (PCC) industry has enabled the management of tasks through a model-architecture-based approach. This research presents an innovative method for competency development in the cold chain sector, leveraging RPM and RA. By introducing a comprehensive conceptual framework encompassing RPM and RA design and workflow into cold chain competency development, this study outlines the key areas for incorporating RPM and RA into the PCC field. The framework elucidates the functioning of RPM and RA concerning occupational standards (OS) and units of competencies (UOC) within the industry. The study generates a research framework for the PCC industry by systematically implementing RPM and RA using a proposed method. The primary outcomes and empirical evidence are UOC and OS derived from RPM and RA implementation and integration, substantiating the conceptual framework's validity. The research highlights the evolutionary aspects and the significance of the conceptual framework in guiding the research framework and proposes a method for competency development. Furthermore, recommendations are provided for future research endeavors. © Authors retain all copyrights.

关键词： information management

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Potential Classification Prediction of Solar and Wind Energy in Indonesia using Machine Learning with Random Forest Algorithm 5

Potential Classification Prediction of Solar and Wind Energy...

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5th IEEE International Conference on Computer and Informatics engineering, IC2IE 2022

作者： Ardiansyah, Deden Mantoro, Teddy Syafei, Wahyul Amien System School of Postgraduate Diponegoro University Doctoral Program of Information Bogor Indonesia Sampoerna University Faculty of Engineering and Technology Jakarta Indonesia Diponegoro University Faculty of Engineering Semarang Indonesia

ISBN: (数字)9781665453387

ISBN: (纸本)9781665453387

The realization of the mass use of renewable energy needs to be supported by various parties, including Indonesia, which is a country that has great potential in the use of renewable energy. The community, government, and private parties who become developers in this regard need to realize the main potential of regions in Indonesia. This study aims to determine the prediction results of renewable energy in Indonesia, especially the potential for solar and wind energy. The method used in this research is machine learning with a random forest algorithm. Random forest classification prediction modeling was carried out using R software. The data samples used were data on maximum temperature, minimum temperature, average temperature, average humidity, duration of sunshine, and average wind speed from 34 provinces in Indonesia. Based on the prediction results with random forest, the average accuracy of the random forest classification model ranges from 81-92%. So, it can be said that the model can provide reasonable predictions. Based on random forest predictions, the classification of the largest level of solar energy potential is in 3 main areas, namely the provinces of East N usa Tenggara, Bali, and West Nusa Tenggara. While the areas with the greatest wind energy potential are in 3 provinces, namely Kep. Bangka Belitung, East Nusa Tenggara, and East Java. The province of East Nusa Tenggara has a high potential for solar and wind energy. The potential duration of solar radiation reaches 10.6 hours per day, while the average wind speed reaches 4 m/s per day. The results of this study are expected to be input for parties who play a role in developing renewable energy in Indonesia to support the renewable energy mix target of 23 % by 2025. © 2022 IEEE.

关键词： Forecasting

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Realizing Global Citizen Solutions for Sustainable Development Goals: A Collaborative engineering Course Between Thai and Japanese Students 23

Realizing Global Citizen Solutions for Sustainable Developme...

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23rd International Symposium on Communications and information Technologies, ISCIT 2024

作者： Sae-Jia, Thanachot Leelawat, Natt Tang, Jing Murakami, Rie Taoka, Yuki Ota, Eri Punyabukkana, Proadpran Chulalonkorn University Faculty of Engineering Department of Environmental Engineering Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Chulalongkorn University Disaster and Risk Management Information Systems Research Unit Bangkok Thailand Graduate School of System Design and Management Keio University Yokohama Japan International School of Engineering Chulakongkorn University Faculty of Engineering Bangkok Thailand Global Education Section Center for Entrepreneurship Education Tokyo Institute of Technology Tokyo Japan School of Environment and Society Tokyo Institute of Technology Tokyo Japan Chulalongkorn University Faculty of Engineering Department of Computer Engineering Bangkok Thailand

ISBN: (纸本)9798350353952

One of the problems faced by engineering and science students is focusing solely on technical knowledge while needing more cultural context. In today's interconnected world, addressing global challenges necessitates collaborative efforts from individuals across nations. Accordingly, a joint course between Chulalongkorn University in Thailand and the Tokyo Institute of technology in Japan has been established. The recent theme of the course, 'Gamification towards Sustainable Development Goals (SDGs),' aimed to foster global citizenship and address SDGs through multicultural collaboration. This study examines the similarities and differences in problem identification between Thai and Japanese student groups participating in the course. Data was collected from discussions, presentations, and group assignments throughout the course. The findings indicate that while both groups share common concerns, such as waste management, language barriers, and transportation issues, their perspectives and proposed solutions are influenced by cultural characteristics. Thai students emphasized infrastructural inadequacies and local traditions, whereas Japanese students focused on efficiency and the impacts of tourism. The study highlights the importance of understanding cultural nuances in collaborative international projects to achieve effective and innovative solutions to global challenges. © 2024 IEEE.

关键词： Sustainable development goals

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Extended NNs-Based Adaptive Event-Triggered Asymptotic Control for Nonlinear systems Against Actuator Faults 7

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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7th International Symposium on Autonomous systems, ISAS 2024

作者： Liu, Shanlin Zhang, Yingwei Zhao, Xudong Wang, Hesheng Northeastern University College of Information Science and Engineering Shenyang China Northeastern University State Laboratory of Synthesis Automation of Process Industry Shenyang China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350363173

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent. © 2024 IEEE.

关键词： Approximation algorithms

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Relation of Determinant Factors and Their Effect on Improving the Online Learning : A systematic literature review 5

Relation of Determinant Factors and Their Effect on Improvin...

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5th International Conference on Advancement in Data Science, E-Learning and information systems, ICADEIS 2023

作者： Widiartha, Ida Bagus Ketut Hwang, Junseok Nugraha, Ryan Adhitya University of Mataram Dept. of Informatics Engineering Mataram Indonesia Seoul National University Technology Management Economic Policy Program Seoul Korea Republic of Telkom University Dept. of Information System Bandung Indonesia

ISBN: (纸本)9798350303414

This study introduces the Harmony Model, which examines factors influencing the success of online learning and the workload of lecturers. Drawing upon the Theory of Action Reason, it explores the impact of student satisfaction and lecturers' willingness to prepare course materials. The model emphasizes the challenge faced by lecturers in creating high-quality content and highlights the importance of balancing supporting factors and alleviating the associated burden. Strategies to enhance online learning effectiveness should address both lecturers' motivation and student satisfaction. Identifying determinant factors and analyzing their impact on material development can increase lecturers' willingness to provide appropriate course materials. Knowledge extraction processes and satisfaction-related factors play crucial roles. This study offers insights to enhance the online learning experience, optimize learning outcomes, and improve overall effectiveness. © 2023 IEEE.

关键词： Curricula

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CUDA Parallelization of Teacher-Learner Optimization Algorithm 1

CUDA Parallelization of Teacher-Learner Optimization Algorit...

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1st International engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2022

作者： Abbasi, Mahdi Alghanim, Mohammed Sabri, Mohammad Khosravi, Mohammad R. Bu Ali Sina University Engineering Faculty Department of Computer Engineering Hamedan Iran Zarqa University Faculty of Information Technology Jordan Zarqa University Department of Management Information System Jordan Weifang University of Science and Technology Weifang Shandong China

ISBN: (纸本)9798350332742

Evolutionary algorithms are effective methods for solving optimization problems that do not require any special assumptions to find optimal solutions. Optimization based on teaching and learning has been parallelized using CUDA parallelization technology. The results show that the proposed parallel version of the algorithm is fast and efficient in teaching and learning phases. © 2022 IEEE.

关键词： Evolutionary algorithms

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A new adoption model for quality of experience assessed by radiologists using AI medical imaging technology

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Journal of Open Innovation: technology, Market, and Complexity 2024年第3期10卷

作者： Nirapai, Anuchit Leelasantitham, Adisorn Technology of Information System Management Division Faculty of Engineering Mahidol University Nakhon Pathom Thailand

This study introduces a new adoption model for assessing the quality of experience (QoE) of radiologists using AI-based medical imaging technology. While AI has increasingly been used by radiologists for screening, diagnosis, and classification of medical images, previous investigations have primarily focused on metrics such as effectiveness, efficiency, and satisfaction. This research expands the evaluation criteria to include user experience and user interface (UX/UI) factors, integrating them within the broader QoE. QoE is conceptualized as a multifaceted construct influenced by both human and system factors, which affect cognitive perception, including hedonic and pragmatic aspects. Data were collected from 159 hospital radiologists with prior experience in using AI technology in medical imaging systems through a structured questionnaire. The data were then analyzed using structural equation modeling principles. The findings suggest that contextual content, human factors, and system characteristics significantly influence cognitive perception, which in turn affects the adoption and utilization of AI in medical imaging. This adoption model captures the radiologists' integration of AI throughout various stages of radiological procedures, including scheduling, scanning, acquisition, interpretation, reporting, and communication. The study also highlights the importance of data collection, storage, and sharing practices in compliance with privacy policies. © 2024 The Authors

关键词： Artificial intelligence Medical imaging Quality of experience technology adoption

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