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Forecasting inflation rates be extreme gradient boosting with the genetic algorithm

Journal of Ambient Intelligence and Humanized Computing 2023年第3期14卷 2211-2220页

作者： Li, Yu-Shan Pai, Ping-Feng Lin, Ying-Lei Department of Information Management National Chi Nan University Puli Nantou Taiwan PhD Program in Strategy and Development of Emerging Industries National Chi Nan University Puli Nantou Taiwan

One of the most important objectives of monetary institutions is to maintain price stability in countries or regions. Hyperinflation and deflation have adverse influences on economic development and potentially easily lead to a negative economic cycle or a sharp recession. Therefore, accurate inflation rate forecasting is essential in formulating a monetary policy. The Extreme Gradient Boosting (XGBoost) technique has recently become a popular and powerful tool in machine learning, which integrates weak learners and uses the regularization method to decrease overfitting. However, the use of XGBoost in forecasting inflations has not been broadly investigated. Thus, this study aims to utilize the XGBoost approach with the genetic algorithm to forecast inflations for three forecast horizons. The other six forecasting models—random forest (RF), least square support vector regression (LSSVR), backpropagation neural networks (BPNN), general regression neural networks (GRNN), deep belief networks (DBN), and long short-term memory (LSTM)—were employed to predict inflations with the same datasets. The numerical results indicate that the XGBoost models outperformed the other six forecasting models in all forecast horizons. Therefore, the XGBoost technique is a feasible and promising alternative for forecasting inflations. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Forecasting

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How and when job passion promotes customer-oriented organizational citizenship behavior: A moderated mediation model

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International Journal of Hospitality Management 2024年 122卷

作者： Teng, Hsiu-Yu Tsai, Cheng-Hsien Hung, Chia-Wen Department of Leisure and Recreation Management National Taichung University of Science and Technology PhD Program in Strategy and Development of Emerging Industries National Chi Nan University

Customer-oriented organizational citizenship behavior (OCBC) is a crucial topic in the restaurant industry, yet few studies have explored how and when an employee's passion toward their job affects OCBC. This study examined the relationship between the job passion of restaurant employees, employee resilience, and OCBC. The mediation effect of employee resilience and the moderating effect of employee mindfulness were also investigated. A questionnaire survey was administered to 471 frontline restaurant employees in Taiwan. The results demonstrated that harmonious passion and obsessive passion positively influence employee resilience, which positively influences OCBC. Employee resilience mediates the influences of harmonious and obsessive passion on OCBC. Furthermore, employee mindfulness strengthens the positive relationship between job passion and employee resilience, thereby facilitating OCBC. These findings supplement previous studies by elaborating the association between job passion and OCBC. Restaurant managers can apply these findings to human resource practices and service management. © 2024 Elsevier Ltd

关键词： Citizenship behavior Mindfulness Passion Resilience Restaurant

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Exploring the influence of past memories on homeland visiting: enhancing destination brand equity and extension through Myanmar immigrants’ place attachment

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Current Issues in Tourism 2024年第22期27卷 3676-3696页

作者： Dai, You-De Yeh, Shih-Shuo Zin, Eain Chuu Lin, Htet Htet Huan, Tzung-Cheng Department of Tourism Leisure and Hospitality Management National Chi Nan University Puli Township Taiwan Department of Business Administration National Cheng Kung University Tainan City Taiwan Ph.D. Program in Strategy and Development of Emerging Industries National Chi Nan University Puli Township Taiwan Department of Marketing and Tourism Management National Chiayi University Chiayi City Taiwan

This research examines the impact of immigrants’ past memories on destination brand equity and destination brand extension for homeland visiting. Based on the perspective of Myanmar immigrants, this study aims to explore whether travel motivation moderates the influence of past memories on place attachment. Additionally, it investigates whether place attachment positively affects destination brand equity and destination brand extension. The questionnaire involved Myanmar immigrants living in Taiwan for over a year, using convenience sampling. A total of 500 questionnaires were distributed, with 385 questionnaires considered effective, resulting in a response rate of 77%. The findings of this study indicate that (1) past memories have a positive effect on place attachment;(2) place attachment positively influences destination brand equity and destination brand extension;(3) travel motivation moderates the impact of past memories on place attachment. Finally, the implications for managerial practice, research limitations, and future research directions are discussed. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： destination brand homeland visiting Past memory place attachment travel motivation

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Machine Learning Models with Synthetic Minority Oversampling in Predicting Substrate Warpage (IMPACT 2024)

Machine Learning Models with Synthetic Minority Oversampling...

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International Microsystems, Packaging, Assembly and Circuits Technology (IMPACT)

作者： Jung-Pin Lai Wan-Lu Hsu Jerry Wang Chih-Sheng Lin Chih-Yuan Shih Yu-Po Wang Ping-Feng Pai Department of Multimedia Game Development and Application Hungkuang University Taiwan R.O.C. PhD Program in Strategy and Development of Emerging Industries National Chi Nan University Taiwan R.O.C. Siliconware Precision Industries Co. Ltd Taiwan R.O.C. Department of Information Management National Chi Nan University Taiwan R.O.C.

ISBN: (数字)9798331532246

ISBN: (纸本)9798331532253

The performance of semiconductors is improved through advanced packaging design, and it is necessary to accurately calculate the specific values of the thermal and mechanical properties of semiconductor packages. For packaging structures, uneven warping often occurs on the packaging surface when the temperature changes. Packaging warpage is typically obtained through measurement characterization. Therefore, the impact of the volume and design of each material in the package on thermal effects becomes critical. This study employs machine learning (ML) models, namely Support Vector Regression, LightGBM, Random Forest and eXtreme Gradient Boosting, to forecast substrate warpage at both room temperature and high temperature. The input data include design parameters such as substrate thickness, die size, die thickness, core thickness, package size, and heat sink thickness. In addition, the synthetic minority oversampling technique (SMOTE) is used to deal with imbalanced data in this study. The mean absolute percentage error (MAPE) is used as a measurement for evaluating performances of machine learning models. Numerical results reveal that four machine learning models can obtain satisfied forecasting results and the eXtreme Gradient Boosting model generates the most accurate outcomes. Thus, machine learning models are feasible and promising alternative in forecasting substrate warpage.

关键词： Temperature measurement Support vector machines Semiconductor device measurement Accuracy Predictive models Packaging Numerical models Microelectronics Substrates Random forests

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Machine Learning Models with Synthetic Minority Oversampling in Predicting Substrate Warpage (IMPACT 2024) 19

Machine Learning Models with Synthetic Minority Oversampling...

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19th International Microsystems, Packaging, Assembly and Circuits Technology Conference, IMPACT 2024

作者： Lai, Jung-Pin Hsu, Wan-Lu Wang, Jerry Lin, Chih-Sheng Shih, Chih-Yuan Wang, Yu-Po Pai, Ping-Feng Hungkuang University Department of Multimedia Game Development and Application No. 1018 Sec. 6 Taiwan Boulevard Shalu District Taichung City433304 Taiwan National Chi Nan University Program in Strategy and Development of Emerging Industries No. 1 University Road Puli Township Nantou County545301 Taiwan Siliconware Precision Industries Co. Ltd No. 123 Sec. 3 Da Fong Rd. Tantzu Taichung42749 Taiwan National Chi Nan University Department of Information Management No. 1 University Road Puli Township Nantou County545301 Taiwan

ISBN: (纸本)9798331532246

关键词： Chip scale packages

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Machine Learning in Integrated Circuit Substrate Electrical Test (IMPACT 2023) 18

Machine Learning in Integrated Circuit Substrate Electrical ...

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18th International Microsystems, Packaging, Assembly and Circuits Technology Conference, IMPACT 2023

作者： Lai, Jung-Pin Lin, Ying-Lei Liu, Yu-Hui Lin, Ho-Chuan Shih, Chih-Yuan Wang, Yu-Po Pai, Ping-Feng HungKuang University Department of Multimedia Game Development and Application No. 1018 Sec. 6 Taiwan Boulevard Shalu District 433 Taichung City433304 Taiwan National Chi Nan University PhD Program in Strategy and Development of Emerging Industries No. 1 University Road Puli Township Nantou County 545 545301 Taiwan Siliconware Precision Industries Co. Ltd. No. 1 University Road Puli Township Taichung City 427 42749 Taiwan National Chi Nan University Department of Information Management No. 123 Sec. 3 Dafeng Rd. Dafeng Vil. Tanzi Dist Nantou County 545 545301 Taiwan

ISBN: (纸本)9798350384123

Due to the rapid development of information technology both in hardware and software, machine learning has been a very powerful and thus popular tool in dealing with problems in many fields. Based on the data-driven way, complicated mathematical models are not required to derive in employing machine learning techniques for solving problems. Instead, only input-output data are necessary to collect for training machine learning models. Thus, this study aims to collect and analyze literature on using machine learning in integrated circuit substrate electrical tests. Then, cases of applying machine learning in integrated circuit substrate electrical tests are introduced. Finally, potential directions of future study are provided. © 2023 IEEE.

关键词： Integrated circuits

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Machine Learning in Integrated Circuit Substrate Electrical Test (IMPACT 2023)

Machine Learning in Integrated Circuit Substrate Electrical ...

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International Microsystems, Packaging, Assembly and Circuits Technology (IMPACT)

作者： Jung-Pin Lai Ying-Lei Lin Yu-Hui Liu Ho-Chuan Lin Chih-Yuan Shih Yu-Po Wang Ping-Feng Pai Department of Multimedia Game Development and Application HungKuang University Taichung City 433 Taiwan (R.O.C.) PhD Program in Strategy and Development of Emerging Industries National Chi Nan University Nantou County 545 Taiwan (R.O.C.) Siliconware Precision Industries Co. Ltd. Taichung City 427 Taiwan (R.O.C.) Department of Information Management National Chi Nan University Nantou County 545 Taiwan (R.O.C.)

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A Study on Concepts development of "Locavore" for Restaurant Managers in Taiwan

A Study on Concepts Development of "Locavore" for Restaurant...

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AHFE International Conference on Human Factors, Business Management and Society, and the AHFE International Conference on Human Factors in Management and Leadership, 2019

作者： Lin, Shao-Chieh Cheng, Jen-Son Chen, Shieh-Liang Liu, Peng-Jyun Department of Business Administration Asia University 500 Lioufeng Road Wufeng Taichung Taiwan41354 Taiwan Doctoral Program in Strategy and Development of Emerging Industries National Chi Nan University University Road Puli TaiwanNantou Hsien54561 Taiwan Department of Creative Product Design Asia University 500 Lioufeng Road Wufeng Taichung Taiwan41354 Taiwan Institute of Applied Arts National Chiao Tung University 1001 University Road Hsinchu Taiwan30010 Taiwan

ISBN: (纸本)9783030201531

The issues of the food safety, the increasing globalization of food production, and the perceived food risks have raised consumer’s doubt about the industrial food system and changed consumer’s purchasing habits. That is resulting in the emerging food system that food produced and consumed locally. The short supply food chain and transparent procedure could enhance food quality. The basis of the local food system is the face-to-face relationship between producers and consumers. However, there are many different concepts in the literature that explain the local food system. The purpose of this study is the concept of local food systems and ‘Local Consumption of Locally Produced, LCLP’ from the restaurant manager’s perspective. This study will conduct a review of literature related to the local food system and the ‘Locavore’, and through personal interviewing, focus groups, to understand ‘LCLP’, as well as conceptualize comprise production, consumption, and management dimensions. Findings provide the local food system and the specific approach by the ‘Locavore’ in restaurant operations strategy as a future reference for the management plan. © 2020, Springer Nature Switzerland AG.

关键词： Managers

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