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Rainfall frequency analysis using event-maximum rainfalls – An event-based mixture distribution modeling approach

Weather and Climate Extremes 2024年 43卷

作者： Cheng, Ke-Sheng Chen, Bo-Yu Lin, Teng-Wei Nakamura, Kimihito Ruangrassamee, Piyatida Chikamori, Hidetaka Department of Bioenvironmental Systems Engineering National Taiwan University Taipei Taiwan Master Program in Statistics National Taiwan University Taipei Taiwan Graduate School of Agriculture Kyoto University Kyoto Japan Department of Water Resources Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Environmental Management Engineering Okayama University Okayama Japan

Rainfall frequency analysis, an essential work for water resources management, is often conducted by using the annual maximum rainfall series. For rainfall stations with short record lengths and outliers presence, the use of annual maximum series for rainfall frequency analysis may yield design rainfall estimates of higher uncertainties. Moreover, for regions with cyclostationary climate patterns, the annual maximum rainfalls may be caused by different prevalent storm types, which differ in terms of their occurrence frequency and storm rainfall characteristics. In this study, we propose a novel event-maximum-rainfall-based mixture distribution modeling approach for rainfall frequency analysis. By considering the event-maximum rainfalls of individual storm events, the sample size for parameter estimation increases, and the uncertainty of design rainfall estimates reduces. Mixture distribution modeling enables a thorough investigation of the contributing probabilities of different storm types to the annual maximum rainfall. Through rigorous stochastic simulation, we demonstrated the superiority of the proposed approach over the conventional annual maximum rainfall approach. The proposed approach was applied to four representative rainfall stations in Taiwan, and the results revealed that the proposed approach is more robust than the conventional annual maximum rainfall approach. The results provide insights into the contributions of individual storm types to the annual maximum rainfall. © 2023 The Authors

关键词： Annual maxima Event-maximum rainfalls Frequency analysis Mixture distribution Negative binomial distribution Poisson distribution

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Strategic legislation for the promotion of university–industry collaborations: a case study of Taiwan

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Journal of Technology Transfer 2025年第1期50卷 304-344页

作者： Truong, Thanh Hue Lin, Bou-Wen Tung, Ching-Pin International Degree Program in Climate Change and Sustainable Development National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei106 Taiwan Research Center for Future Earth National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei106 Taiwan Graduate Institute of Business Administration College of Management National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei106 Taiwan National Applied Research Laboratories No. 106 Sec. 2 Heping E. Rd. Da’an Dist. Taipei City106214 Taiwan Department of Bioenvironmental Systems Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei106 Taiwan

The strategic utilization of technology to enhance industrial competitiveness and product quality is pivotal for economic growth. As universities own more inventions, collaborative efforts between industry and academia become essential for regional competitiveness and overall economic advancement. This study explores Taiwan’s systematic approach to upgrading its infrastructure, emphasizing the significance of University–Industry Collaborations (UIC) in realizing Industry 4.0. Government strategies and policy decisions emerge as key drivers in fostering successful collaborative projects between industry and university teams. The relaxation of restrictions, particularly related to part-time teachers and technology transfer, along with the promotion of corporate programs, effective use of public funding, and the development of an innovative digital platform system for UIC, collectively contribute to establishing a robust university–industry cooperation mechanism. This mechanism has contributed to Taiwan’s move towards new digital advances in innovation and entrepreneurship, fostering industrial leadership and efficient governance. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Technology transfer

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A Multi-phase Deep Learning Approach for Predicting HCC Response to TACE using Complete Computed Tomography

A Multi-phase Deep Learning Approach for Predicting HCC Resp...

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Data Science and engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Shun Cheng Chang Chien Fu Liu Marta Misztal Yi Hsien Hsieh Che Lin Graduate Institute of Communication Engineering National Taiwan University (NTU) Taiwan School of Electronic Engineering and Computer Science Queen Mary University of London UK Department of Electrical Engineering NTU Taiwan Center for Computational and Systems Biology and Center for Biotechnology NTU Taiwan Smart Medicine and Health Informatics Program NTU Taiwan

In this research study, we compare the predictive performance of two advanced deep learning-based models in order to provide a solution to TACE (Transarterial Chemoembolization) response prediction in HCC (Hepatocellular Carcinoma) patients. Using entire abdominal CT scans enabled a broader perspective available for the model, eliminating the need for segmentation during the preprocessing. Making use of both single-phase and multi-phase CT imaging, we have used DenseNet121 and have obtained an accuracy of 80% for the multi-phase *** Relevance: The ability to predict the effectiveness of TACE treatment prior to its administration makes it possible to provide a better decision-making aid for physicians and patients.

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Rainfall Frequency Analysis Using Event-Maximum Rainfalls – an Event-Based Mixture Distribution Modeling Approach

SSRN

引用

SSRN 2023年

作者： Cheng, Ke-Sheng Chen, Bo-Yu Lin, Teng-Wei Nakamura, Kimihito Ruangrasamee, Piyatida Chikamori, Hidetaka Department of Bioenvironmental Systems Engineering National Taiwan University Taipei Taiwan Master Program in Statistics National Taiwan University Taipei Taiwan Graduate School of Agriculture Kyoto University Kyoto Japan Department of Water Resources Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Environmental Management Engineering Okayama University Okayama Japan

Rainfall frequency analysis, an essential work for water resources management, is often conducted by using the annual maximum rainfall series. For rainfall stations with short record lengths and outliers presence, the use of annual maximum series for rainfall frequency analysis may yield design rainfall estimates of higher uncertainties. Moreover, for regions with cyclostationary climate patterns, the annual maximum rainfalls may be caused by different prevalent storm types, which differ in terms of their occurrence frequency and storm rainfall characteristics. In this study, we propose an event-maximum-rainfall-based mixture distribution modeling approach for rainfall frequency analysis. By considering the event-maximum rainfalls of individual storm events, the sample size for parameter estimation increases, and the uncertainty of design rainfall estimates reduces. Mixture distribution modeling enables a thorough investigation of the contributing probabilities of different storm types to the annual maximum rainfall. Through rigorous stochastic simulation, we demonstrated the superiority of the proposed approach over the conventional annual-maximum-rainfall approach. The proposed approach was applied to four representative rainfall stations in Taiwan, and the results revealed that the proposed approach is more robust than the conventional annual-maximum-rainfall approach. The results provide insights into the contributions of individual storm types to the annual maximum rainfall. © 2023, The Authors. All rights reserved.

关键词： Poisson distribution

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Analysis of Non-fatal Occupational Accidents in a Ready-mixed Concrete Company

Analysis of Non-fatal Occupational Accidents in a Ready-mixe...

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2022 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2022

作者： Prasetyo, Yogi Tri Sario, Maria Cristina Chuenyindee, Thanatorn Nadlifatin, Reny Persada, Satria Fadil Sittiwatethanasiri, Thaninrat Mapúa University School of Industrial Engineering and Engineering Management Manila Philippines Yuan Ze University Department of Industrial Engineering and Management Chung-Li Taiwan Mapúa University School of Graduate Studies Manila Philippines Navaminda Kasatriyadhiraj Royal Air Force Academy Department of Industrial Engineering and Aviation Management Bangkok Thailand Institut Teknologi Sepuluh Nopember Department of Information Systems Surabaya Indonesia Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta Indonesia

ISBN: (数字)9781665486873

ISBN: (纸本)9781665486873

The production and delivery of ready-mixed concrete consist of several activities which expose employees to considerable safety hazards that lead to occupational accidents. The study aimed to determine the significant factors contributing to non-fatal occupational accidents in the ready-mixed concrete industry in Qatar. A total of 84 non-fatal occupational accidents were collected from a ready-mixed concrete company in Qatar. A coding scheme was developed based on available literature and the company's existing classification to analyze each accident in terms of employee, injury, and accident characteristics. Cross-tabulation analysis was used to determine the associations between categorical factors. Frequency distribution showed that regular employees aged between 25 and 44 years old were mostly involved in accidents, with hand/arm and leg/foot being mostly injured. The most common accident types were struck by an object (44%), slip, trip or fall on the same level (23.8%), and caught in between objects (17.9%). The majority of work-related accidents (71%) could be attributed to unsafe behavior, particularly due to improper use of PPE. Strong significant associations were observed between activity type and accident root cause, as well as injured body type and accident root cause. The significant factors contributing to non-fatal occupational accidents were determined through the study. The insights obtained from this study could be used by the company in designing a comprehensive safety management program with the goal of driving occupational injuries to a lower level. © 2022 IEEE.

关键词： Accidents

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The Impact of COVID-19 Pandemic on Airport: An Empirical Study of Service Quality, Customer Satisfaction, and Travel Intention for Sustainable Airport Operations

The Impact of COVID-19 Pandemic on Airport: An Empirical Stu...

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2022 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2022

作者： Prasetyo, Yogi Tri Fuente, Darlene Gayle D. Dela Chuenyindee, Thanatorn Nadlifatin, Reny Persada, Satria Fadil Mapúa University School of Industrial Engineering and Engineering Management Manila Philippines Yuan Ze University Department of Industrial Engineering and Management Chung-Li Taiwan Mapúa University School of Graduate Studies Manila Philippines Navaminda Kasatriyadhiraj Royal Air Force Academy Department of Industrial Engineering and Aviation Management Bangkok Thailand Institut Teknologi Sepuluh Nopember Department of Information Systems Surabaya Indonesia Bina Nusantara University Entrepreneurship Department Binus Business School Undergraduate Program Jakarta Indonesia

ISBN: (数字)9781665486873

ISBN: (纸本)9781665486873

Delivering a high service quality under the safety protocol of COVID-19 is very essential for the sustainable airport operations. The study was intended to determine the impact of COVID-19 on Airport Service Quality (ASQ), customer satisfaction, and travel intention by utilizing a structural equation modeling (SEM) approach. A total of 517 Filipinos voluntarily answered an online questionnaire that consists of 92 questions. SEM indicated that the security check, terminal facilities, and services had significant effects on perceived value which subsequently led to customer satisfaction. In addition, travel safety measures had direct effects on Filipinos' travel intention and customer satisfaction. Interestingly, service innovations had no significant impact on customer satisfaction but directly affected travel intention. By understanding the relationship between these factors, airport management could have better decision-making while efficiently and effectively utilizing the resources in these times of uncertainty. © 2022 IEEE.

关键词： COVID-19

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The Impact of the COVID-19 Pandemic on the Organizational Commitment in Semiconductor Industry: The Mediator Effect of the Job Satisfaction

The Impact of the COVID-19 Pandemic on the Organizational Co...

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2022 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2022

作者： Prasetyo, Yogi Tri Ong, Ardvin Kester S. Cagubcob, Alaissa Marie A. Chuenyindee, Thanatorn Nadlifatin, Reny Persada, Satria Fadil Mapúa University School of Industrial Engineering and Engineering Management Manila Philippines Yuan Ze University Department of Industrial Engineering and Management Chung-Li Taiwan Mapúa University School of Graduate Studies Manila Philippines Navaminda Kasatriyadhiraj Royal Air Force Academy Department of Industrial Engineering and Aviation Management Bangkok Thailand Institut Teknologi Sepuluh Nopember Department of Information Systems Surabaya Indonesia Bina Nusantara University Binus Business School Undergraduate Program Entrepreneurship Department Jakarta Indonesia

ISBN: (数字)9781665486873

ISBN: (纸本)9781665486873

Due to the COVID-19 pandemic, employees are required to respond to changes and conform to stringent safety laws and regulations. This study aimed to analyze the impact of the COVID-19 pandemic on the organizational commitment among employees in the semiconductor industry. A total of 272 employees working in the semiconductor industry answered a self-administered questionnaire that considered 51 questions, distributed online. Utilizing Structural equation modeling (SEM), the results showed that the COVID-19 was found to have a significant direct effect on employees' perceived job outcomes (PO) and a negative direct effect on job demands (JD). Moreover, PO had a positive effect on job motivation (JM) and job satisfaction (JS). Subsequently, JM presented a significant positive direct effect on JS, while JD showed a negative effect on JS. Lastly, JS showed a significant positive direct effect on organizational commitment (OC). Intriguingly, an indirect effect of PO on JS was seen. This study is one of the first studies that analyzed the organization commitment among semiconductor workers during the COVID-19 pandemic. This paper could be utilized as a foundation to enhance organizational commitment, particularly in the semiconductor industry worldwide. © 2022 IEEE.

关键词： COVID-19

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CLINICAL DETERIORATION PREDICTION IN BRAZILIAN HOSPITALS BASED ON ARTIFICIAL NEURAL NETWORKS AND TREE DECISION MODELS

arXiv

引用

arXiv 2022年

作者： Yazdanpanah, Hamed Silva, Augusto C.M. Guedes, Murilo Morales, Hugo M.P. Coelho, Leandro dos S. Moro, Fernando G. Department of Research Robô Laura PR Curitiba Brazil Department of Computer Science University of São Paulo SP São Paulo Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana PR Curitiba Brazil Electrical Engineering Graduate Program Federal University of Parana PR Curitiba Brazil

Early recognition of clinical deterioration (CD) has vital importance in patients' survival from exacerbation or death. Electronic health records (EHRs) data have been widely employed in Early Warning Scores (EWS) to measure CD risk in hospitalized patients. Recently, EHRs data have been utilized in Machine Learning (ML) models to predict mortality and CD. The ML models have shown superior performance in CD prediction compared to EWS. Since EHRs data are structured and tabular, conventional ML models are generally applied to them, and less effort is put into evaluating the artificial neural network's performance on EHRs data. Thus, in this article, an extremely boosted neural network (XBNet) is used to predict CD, and its performance is compared to eXtreme Gradient Boosting (XGBoost) and random forest (RF) models. For this purpose, 103,105 samples from thirteen Brazilian hospitals are used to generate the models. Moreover, the principal component analysis (PCA) is employed to verify whether it can improve the adopted models' performance. The performance of ML models and Modified Early Warning Score (MEWS), an EWS candidate, are evaluated in CD prediction regarding the accuracy, precision, recall, F1-score, and geometric mean (G-mean) metrics in a 10-fold cross-validation approach. According to the experiments, the XGBoost model obtained the best results in predicting CD among Brazilian hospitals' data. © 2022, CC BY-NC-SA.

关键词： Machine learning

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Assistive technology with device for self-inflating bag in neonatology

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Research on Biomedical engineering 2025年第2期41卷

作者： Marcelino, Ana Carolina Rodovanski, Giovana Pascoali Bonetti, Karoline Panes, Caio Rabinovich de Almeida Martins, Fernando Moran, Cristiane Aparecida Araranguá Brazil Graduate Program in Neurosciences and Behavior Department of Experimental Psychology of the Institute of Psychology-University of São Paulo Sao Paulo Brazil Araranguá Brazil Computer Engineering Instituto Mauá de Tecnologia São Caetano do Sul Brazil Electronic Engineering and Computing with Emphasis on Electronic Devices and Systems at Instituto Tecnológico de Aeronáutica–ITA São Caetano do Sul Brazil Department of Physiotheraphy and at the Postgraduate Program in Rehabilitation Science of the Federal University of Santa Catarina-UFCS Ararangua Brazil

Purpose: The objectives of this study were to create a device with technological development of the self-inflating bag (SIB) equipment to measure the variables tidal volume, peak inspiratory pressure, and inspiratory flow and to evaluate the knowledge of undergraduate students in handling the SIB. To reduce the risks of mortality, length of hospital stay, and infections, SIB is a resource used to ventilate the patient through the inflation of the device, but it is not capable of measuring the ventilatory parameters. Excess ventilation and incorrect handling of the bag can cause lung injury in newborns. Therefore, measuring these parameters can prevent lung injury resulting from inadequate ventilation. Method: This is a cross-sectional and experimental study, with the development of a device SIB that allows the evaluation of variables of neonatal respiratory mechanics that were tested with an artificial lung. It was approved by the Research Ethics Committee and the research was developed in three stages: the first represents the search for scientific articles for the consensus of neonatal ventilatory variables for the construction of the SIB parameters;the second stage depicts the technological development of a device capable of monitoring such variables through the SIB. In the third stage, the content validation of the device with the handling of the SIB was carried out by students of medicine and physiotherapy courses of Brazil. Results: In this work, a device that analyzes the values of the main ventilatory parameters in neonatology was developed and to generate a safety range for the use of the device, curves with a tolerance of 10% up and down were created. All electronic components were coupled to the equipment, with a display that transmits the parameter values. The web page can be used on a cell phone, tablet, computer, or SmartTv, as long as it is connected to the "RespiratorIoT_AP" network. Among the 29 participants in the study, 8 said they were familiar w

关键词： Students

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Determining ergonomics-based sustainability for public utility vehicles: integrating higher-order structural equation modelling and random forest classifier

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Ergonomics 2025年 1-24页

作者： Yogi Tri Prasetyo Zachariah John A Belmonte Ardvin Kester S Ong Ken Joshua U Rebosura Lanndon Ocampo Reny Nadlifatin International Bachelor Program in Engineering Yuan Ze University Chung-Li ROC. Department of Industrial Engineering and Management Yuan Ze University Chung-Li ROC. Mechanical Engineering and Allied Department Technological University of the Philippines Taguig Philippines. School of Graduate Studies Mapúa University Manila Philippines. School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines. Center for Applied Mathematics and Operations Research Cebu Technological University Cebu City Philippines. Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya Indonesia.

Ergonomics-based sustainability (EBS) in public utility vehicles (PUVs) requires an integrated approach that balances environmental, social and economic factors while enhancing commuter and driver well-being. This study develops an EBS framework for PUVs in the Philippines by integrating higher-order structural equation modelling (H-SEM) and the random forest classifier (RFC). Analysing 350 survey responses, results indicated that environmental sustainability, particularly pollution reduction and energy efficiency, had the greatest influence on overall sustainability. Social dimensions, such as driver well-being and vehicle safety, were also critical, while economic factors like affordability and investment played a supporting role. The RFC model highlighted immediate operational concerns, emphasising safety and usability, which complement SEM's long-term sustainability insights. This study provides a data-driven framework for policymakers and transport planners to improve PUV ergonomics, enhance commuter satisfaction and promote sustainable mobility, with adaptability for global applications in EBS.

关键词： Macroergonomics sustainable ergonomics sustainable mobility user-centred design

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