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Key factors affecting people's willingness to participate in water resource protection in the agricultural Ba River Basin – in the highlands of Vietnam

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Journal of Water and Climate Change 2025年第4期16卷 1225-1237页

作者： Anh, Nguyen Tuan Can, Le Duy Schmalz, Britta Luu, Tran Le Doctoral Training Program in Sustainable Urban Development Vietnamese-German University Vanh Dai 4 Quarter 4Binh Duong Province Ben Cat Viet Nam Nong Lam University of Ho Chi Minh City Gia Lai Campus Gia Lai Viet Nam Department of Mechatronics and Sensor Systems Technology Vietnamese-German University Vanh Dai 4 Quarter 4 Thoi Hoa Ward Binh Duong Province Ben Cat Viet Nam Engineering Hydrology and Water Management Technical University of Darmstadt Darmstadt Germany Master Program in Water Technology Reuse and Management Vietnamese-German University Vanh Dai 4 Quarter 4 Thoi Hoa Ward Binh Duong Province Ben Cat Viet Nam

Willingness to participate (WP) in community-based management depends on various factors such as a sense of community, perceptions, beliefs, and demographic characteristics. This study first evaluates the WP of locals (n = 100) in water management in the Ba River Basin – Highlands of Vietnam, where ethnic minority groups are living and working in the agricultural sector. The multivariable linear regression model is applied to explain WP through the factors including the sense of community (SC), dependance on river water (DW), perceptions of current water resource management (PW), level of income (IN), gender (GE), education levels (ED), and place of residence (PR). The results showed that the final regression model explains 67.9% of the variation in WP levels (R2 = 0.679, p 0.05) in this model. Sense of community and perceptions greatly influence community participation. To boost willingness, periodic training and campaigns are needed. Additionally, improving legal frameworks can encourage greater community involvement in water management programs. © 2025 The Authors.

关键词： Multiple linear regression

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Determinant factors for consumers?? intention in choosing an e-commerce Platform (online shop): An extended Theory of Planned Behavior (TPB) approach 24

Determinant factors for consumers?? intention in choosing an...

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Proceedings of the 10th International Conference on Industrial and Business engineering

作者： Ramon Francisco I. Jorge Maela Madel L. Cahigas Ierenne Novendah Reny Nadlifatin Rachkanok Sukhavalli Yogi Tri Prasetyo School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Department of Industrial Engineering and Management Yuan Ze University Taoyuan Taiwan China Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia International Bachelor Program in Engineering Yuan Ze University Taoyuan Taiwan China

ISBN: (纸本)9798400710742

This study investigates the determinant factors influencing consumers' intention to choose an e-commerce platform (online shop) through the lens of an extended Theory of Planned Behavior (TPB) approach. By examining key elements such as service quality, user interface design, customer support, transparency, personalization, and security measures, the research provides a comprehensive understanding of how these factors contribute to consumer behavior in the online shopping environment. The findings underscore the critical role of service quality in shaping consumer intentions, highlighting the need for online shopping platforms to prioritize and continuously enhance their service offerings. Additionally, the study emphasizes the importance of a user-friendly interface, responsive customer support, transparency in communication, personalized experiences, and robust security measures in fostering consumer trust and satisfaction. These insights offer practical recommendations for e-commerce platforms to improve their service quality, ultimately leading to increased consumer engagement and loyalty. The research concludes that a focus on delivering exceptional service quality, coupled with informed consumer decision-making, can significantly enhance the overall online shopping experience, benefiting both consumers and platform providers.

关键词： e-commerce

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Millennials' social media-driven online entrepreneurship: Assessing their aspirations for multi-level marketing jobs 24

Millennials' social media-driven online entrepreneurship: As...

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Proceedings of the 10th International Conference on Industrial and Business engineering

作者： Ahmad Sattam Alhawamdeh Ierenne Novendah Yogi Tri Prasetyo Reny Nadlifatin Maela Madel L. Cahigas Department of Industrial Engineering and Management Yuan Ze University Taoyuan Taiwan China International Bachelor Program in Engineering Yuan Ze University Taoyuan Taiwan China Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia School of Industrial Engineering and Engineering Management Mapua University Manila Philippines

ISBN: (纸本)9798400710742

Abstract: With the development of Internet technology and the popularization of mobile devices and so on, e-commerce has entered a period of high-speed development, consumers are faced with a wealth of channel choices, and the competition for traffic in different channels is becoming more and more intense, which poses a great challenge to enterprises. From the perspective of PPM theoretical model to study the consumers' migration intention of different online channels, using SPSS software and Amos to construct structural equations for the influencing factors of consumers' migration intention of different online channels, the results show that the push force and pull force positively affect the consumers' migration intention, and the push force has the greatest influence on the consumers' migration intention. It provides a basis for the live e-commerce platform to propose measures to enhance user channel stickiness.

关键词： Consumers

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Hybrid IT Project management Methodology Based on Best Practices of Project management and Critical Success Factors Influencing IT Project management 8th

Hybrid IT Project Management Methodology Based on Best Pract...

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8th International Conference on Intelligent Technologies, ICIT 2023

作者： Hayashida-Marchinares, Augusto Herrera, Jose Rivera, Luis Rodriguez, Ciro Rodriguez Krupa, Miroslav Ph. D. Program of the Faculty of Systems Engineering and Informatics Universidad Nacional Mayor de San Marcos Lima Peru Laboratory of Mathematical Sciences Center of Sciences and Technologies Universidade Estadual Do Norte Fluminense-UENF Rio de Janeiro Brazil Department of Management Faculty of Business Administration Prague University of Economics and Business Prague Czech Republic

ISBN: (纸本)9789819738588

Information Technology (IT) project management is important for the growth of organizations. It involves planning and executing projects to achieve strategic objectives. This paper reviews IT project management methodologies and critical success factors to identify best practices for project success. This paper uses a literature review and analysis of the current state of the art of IT project management methodologies. A total of 39 articles were selected and reviewed. The results of the review include a comparison of the main IT project management methodologies and the critical success factors for project success. The conclusion of the paper is that Hybrid Project management Models are a promising approach for IT project management. This approach combines the foundations and best practices of traditional and agile project management methodologies, making it well-suited for the complex and dynamic nature of IT projects. Additionally, the paper identifies the following critical success factors for IT project success: Clear and well-defined project objectives, Effective communication and collaboration between stakeholders, Appropriate risk management and contingency planning, Strong leadership and project management skills and Adequate resources and support. By understanding and addressing these critical success factors, organizations can increase their chances of success in IT projects. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Project management

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Mental Status Identification for Infertile Patients Using Artificial Intelligence Models 14th

Mental Status Identification for Infertile Patients Using Ar...

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14th International Conference on Frontier Computing, FC 2024

作者： Hsu, Hao-Siang Wang, Jong-Yi Chiou, Hai-Chi Wu, Fu-Hsing Lin, Chuen-Horng Chan, Yung‑Kuan Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung404336 Taiwan Department of Health Services Administration China Medical University Taichung406040 Taiwan Bachelor Degree Program of Artificial Intelligence National Taichung University of Science and Technology Taichung404336 Taiwan Department of Management Information Systems National Chung-Hsing University Taichung402202 Taiwan

ISBN: (纸本)9789819623945

Infertile patients may be a high-risk group of mental disorder. The precise identification of the mental status of infertile patients can provide decision support to healthcare professionals and may be helpful in providing preventive measures accordingly. Rare studies focused on the mental status identification using artificial intelligence (AI) models for infertile people. This study aimed to precisely identify the mental status (anxiety and depression) of infertile patients using three AI models, the XGBoost, decision tree, and stacking models. The dataset, retrieved from a structured questionnaire survey in 2011, which included 400 infertility outpatients seeking reproductive treatments at three teaching hospitals in Taiwan was adopted for training and testing AI models. Aforementioned AI models were designed and reached identification performances of accuracy, precision, recall and area under ROC curve (AUC) equaling 0.75–0.82, 0.70–0.80, 0.64–0.72, and 0.64–0.72, respectively. The XGBoost model (accuracy = 0.82, precision = 0.80, recall = 0.72, and AUC = 0.72) outperformed or equaled the decision tree and stacking models in terms of accuracy, precision, recall, and AUC values. Designed AI models for mental status identification can be integrated into the clinical decision support system (CDSS) to provide the anxiety and depression group automatically. Accordingly, the worsening of infertility-related anxiety and depression can be prevented. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： artificial intelligence infertile patients Mental status identification stacking model XGBoost

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The Centrifugal Nuclear Thermal Rocket: Foundations, Challenges, and Progress

The Centrifugal Nuclear Thermal Rocket: Foundations, Challen...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Thomas, Dale Houts, Michael Wang, Dean Hollingsworth, Keith Frederick, Robert Cassibry, Jason Department of Industrial & Systems Engineering and Engineering Management The University of Alabama in Huntsville HuntsvilleAL35899 United States Space Nuclear Propulsion Program Office NASA Marshall Space Flight Center HuntsvilleAL35812 United States Department of Mechanical & Aerospace Engineering The Ohio State University ColumbusOH43210 United States Department of Mechanical & Aerospace Engineering and Interim Dean of the Honors College The University of Alabama in Huntsville HuntsvilleAL35899 United States Department of Mechanical & Aerospace Engineering Propulsion Research Center The University of Alabama in Huntsville HuntsvilleAL35899 United States Department of Mechanical & Aerospace Engineering The University of Alabama in Huntsville HuntsvilleAL35899 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

The Centrifugal Nuclear Thermal Rocket (CNTR) is a Nuclear Thermal Propulsion (NTP) concept designed to heat propellant directly by the reactor fuel. The primary difference between the CNTR concept and traditional NTP systems is that rather than using traditional solid fuel elements, the CNTR uses liquid fuel with the liquid contained in rotating cylinders by centrifugal force. If the concept can be successfully realized, the CNTR would have a high specific impulse (up to 1800 s) at high thrust, which may enable (i) viable near-term human Mars exploration by reducing round-trip times to 420 days and (ii) direct injection orbits for scientific rendezvous missions to the Solar System outer planets and Kuiper Belt objects. Research is presently underway to determine resolutions for the significant engineering challenges that the CNTR concept presents. These challenges, the study plans to address them, and progress have been described previously;this paper provides an update on progress to date for the overall research effort, including strategies and key results on revision of a reference configuration, definition of key parameters which allows integration of the results of various analyses, and reviews strategies to mitigate the problem of Uranium vapor saturating the propellant exhaust and significantly impacting the CNTR’s specific impulse. Analyses and experiments, both underway and planned, to update estimates of engine key performance parameters including specific impulse, thrust and thrust to weight ratio along with the identification of selected design margins within the engine itself are described – all toward the goal of enabling plans for a laboratory demonstration of a single Centrifugal Fuel Element. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Rockets

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LARGE-SCALE OPTIMIZATION MODELING AT THE UNITED-STATES-TREASURY-DEPARTMENT - AN UPDATE

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INTERFACES 1985年第2期15卷 46-49页

作者： MULVEY, JM Princeton Univ Program in Engineering-Management Systems Princeton NJ USA Princeton Univ Program in Engineering-Management Systems Princeton NJ USA

The US Treasury Department (Office of Tax Analysis) estimates the impact of proposed changes to the US tax code. Their forecasted distribution of potential benefits and losses on various subpopulations plays a significant role in Congressional tax policy debate. Three large-scale optimization models are essential in estimating revenue; one—optimal cluster analysis—was described in a previous Interfaces article, October 1980, and is brought up to date here.

关键词： programing: integer simulation: application

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An explainable non-invasive hybrid machine learning framework for accurate prediction of thyroid-stimulating hormone levels

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Computers in Biology and Medicine 2025年 189卷 109974-109974页

作者： Mohammed, Areej Alshraideh, Hussam Abu-Helalah, Munir Shamayleh, Abdulrahim Department of Industrial Engineering Engineering Systems Management Program American University of Sharjah SharjahP.O. Box 26666 United Arab Emirates Department of Industrial Engineering American University of Sharjah SharjahP.O. Box 26666 United Arab Emirates Industrial Engineering Department Jordan University of Science and Technology Irbid Jordan Department of Family and Community Medicine School of Medicine University of Jordan Public Health Institute Amman Jordan

Machine learning models, including thyroid biomarkers, are increasingly utilized in healthcare for biomarker prediction. These models offer the potential to enhance disease diagnosis through data-driven approaches relying on non-invasive techniques. However, no studies have explored the application of fully non-invasive methods for predicting thyroid-stimulating hormone (TSH) levels. Consequently, this study introduces a novel, fully non-invasive framework for predicting TSH levels by developing an innovative hybrid machine learning model that balances performance, complexity, and interpretability. Seven ML models were evaluated, and the best-performing models were integrated into a hybrid approach to balance performance, complexity, and interpretability. A dataset of 6190 instances from Jordan was used for model development. Four-dimensional non-invasive factors, including demographics, symptoms, family history, and newly engineered symptom scores, were incorporated into the model. The hybrid model achieved an R2 of 94.2 % and RMSE of 0.015, demonstrating superior predictive performance. Model interpretability was ensured using LIME and SHAP explainers, confirming aggregated symptom scores' critical role in enhancing prediction accuracy. A robust feature selection technique was implemented, reducing model complexity and enhancing performance. Among the top ten features for predicting TSH levels were hypothyroidism and hyperthyroidism symptom scores, family history, cold intolerance, itchy-dry skin, sweating, hand tremors, and palpitations. The model can be employed to develop cost-effective diagnostic tools for thyroid disorders. It also offers a robust framework that can be generalized to predict other biomarkers and applied in diverse contexts. © 2025 Elsevier Ltd

关键词： Prediction models

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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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Complementary strengths of water footprint and life cycle assessments in analyzing global freshwater appropriation and its local impacts – Recommendations from an Interdisciplinary discussion series

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Ecological Indicators 2025年 174卷

作者： Berger, Markus Gerbens-Leenes, Winnie Karandish, Fatemeh Aldaya, Maite M. Boulay, Anne-Marie Hogeboom, Rick J. Link, Andreas Manzardo, Alessandro Mialyk, Oleksandr Motoshita, Masaharu Nuñez, Montserrat Pfister, Stephan Rosenbaum, Ralph K. Scherer, Laura Su, Han Wöhler, Lara University of Twente Chair of Multidisciplinary Water Management Enschede Netherlands Groningen Netherlands Earth Systems and Global Change Group Wageningen University and Research Wageningen Netherlands Pamplona Spain Pamplona Spain CIRAIG Polytechnique Montréal Montréal Canada Water Footprint Network Enschede Netherlands Technical University of Berlin Chair of Sustainable Engineering Berlin Germany Padova Italy Japan Sustainability in Biosystems Research Program Caldes de Montbui Barcelona Spain Institute of Environmental Engineering Ecological Systems Design Department of Civil Environmental and Geomatic Engineering ETH Zurich Switzerland Leiden University Leiden Netherlands

Considering globally increasing water challenges, the analysis of water use along supply chains is of great relevance and can be tackled by mainly two methodological approaches: Water Footprint Assessment (WFA) and Life Cycle Assessment (LCA). While sharing the same goal of promoting sustainable water use, both methods developed in different contexts and scientific communities. This has led to heated debates on methodological presuppositions that at times has become unconstructive. To build mutual understanding and enable a fruitful cooperation, researchers from both communities have exchanged over the course of two years. This paper summarizes the outcomes of this discussion series by providing i) a description of the development of both approaches and their ways of assessing freshwater consumption and pollution, ii) an application in a case study, and iii) an analysis of strengths and weaknesses in relation to questions decision-makers may have. Our analysis revealed that WFA's strength lies in its ability to measure freshwater appropriation, water-use efficiency, water scarcity and total pollution levels. This makes WFA particularly useful for crop selection as well as agricultural and river basin water management. With its focus on assessing impacts, LCA is strong in quantifying potential consequences of water use for humans and ecosystems. This makes it particularly useful for assessing complex supply chains and for analysing water-related impacts in combination with other environmental aspects. Rather than being in competition with each other, we emphasize the individual and complementary strengths of both approaches and their joint efforts in addressing the world's pressing water challenges. © 2025 The Authors

关键词： Life cycle assessment

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