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Forecasting the recovery period of air passenger transportation by using vector error correction model

International Social Science Journal 2022年第245期72卷 813-828页

作者： İNAN, Tüzün Tolga GÖKMEN İNAN, Neslihan Department Ph.D. Area: Civil Aviation Management Bahcesehir University School of Applied Disciplines Pilotage Department Yildiz Ciragan Street Besiktas Istanbul 34349 Turkey Instructor Ph.D. Area: Statistics Koc University Engineering Faculty Computer Engineering Department Rumelifeneri Sariyer Rumeli Feneri Road Sariyer Istanbul 34450 Turkey

The COVId-19 pandemic has had a significantly negative impact on all transportation modules, especially air passengers. The authors aimed to forecast the air passenger load factor using time series modelling for the affecting variables. After providing general information about this pandemic, the forecasting results regarding getting back into the recovery period were presented by time series modelling. The last five years (2016–2020) and the first eight months of 2021 were examined with the following variables: available seat kilometre, revenue passenger kilometre, passenger load factor, gross domestic product, and domestic and international passenger numbers. The forecast results reveal that the recovery period started in June of 2021 and continues with a robust growth trend until September 2021 due to the vaccination process and the starting of the summer season. This trend changed between September to November 2021 slightly negative, from November 2021 to January 2022 slightly positive, and from January 2022 to March 2022 mildly negative. Correspondingly, passenger load factor (PLF) is affected by itself and domestic transportation in the short-term period. This effect seems short-term in domestic and international transport. This research reveals that minimising the economic damage by benefiting from the increasing trend of air passenger numbers increases the recovery period. © 2022 John Wiley & Sons Ltd.

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Meal Image Recognition and Healthy Meal Combination Recommendation System Integrated with Generative Artificial Intelligence 6

Meal Image Recognition and Healthy Meal Combination Recommen...

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6th IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2024

作者： Chang, Chin-Chih Wei, Chi-Hung Hsiao, Sean Yang, Chyuan-Huei Thomas Chung Hua University Department of Computer Science and Information Engineering Hsinchu Taiwan Chung Hua University Ph.D. Program in Engineering Science Hsinchu Taiwan Chung Hua University Program in Applied Foreign Language and Smart Commerce Hsinchu Taiwan School of Information Engineering Shandong Vocational and Technical University of International Studies Shandong China

ISBN: (纸本)9798350396133

People increasingly prioritize a balanced diet to enhance well-being, yet making informed dietary choices remains challenging amidst the abundance of options. To address this, we developed a meal image recognition and healthy meal combination recommender system, integrating generative artificial intelligence (AI). Convolutional neural networks were used for precise meal image recognition to identify diverse food items. The generative AI-augmented recommendation engine offers personalized meal suggestions aligned with nutritional goals and dietary preferences, utilizing a nutrition knowledge base to ensure overall well-being. The system's feasibility was validated, illustrating its excellence in meal recognition accuracy, recommendation diversity, and user engagement. By integrating generative AI, the system shows its potential to enhance dietary recommendations and public health. © 2024 IEEE.

关键词： Generative adversarial networks

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A Fitness Movement Evaluation System Using deep Learning 15

A Fitness Movement Evaluation System Using Deep Learning

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15th International Conference on Knowledge and Systems Engineering, KSE 2023

作者： Chang, Chin-Chih Wei, Chi-Hung Wu, Hao-Wei Hsiao, Sean Chung Hua University Department of Computer Science and Information Engineering Hsinchu City Taiwan Ph.D. Program in Engineering Science Chung Hua University Hsinchu City Taiwan Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu City Taiwan

ISBN: (纸本)9798350329742

This paper proposes a fitness movement evaluation system using deep learning. The system uses a deep convolutional neural network (CNN) to extract features from pictures of fitness movements. The features are then used to classify the movements into different categories. The system is evaluated on a dataset of pictures of fitness movements. The results show that the system can accurately classify the movements into different categories. The system is designed to provide feedback to users on their fitness movements. The proposed system is a valuable tool for fitness enthusiasts. The main contribution of this paper is to propose a way to give users a score for their fitness movement. It can help users improve their fitness and track their progress over time. The system is also a valuable tool for fitness professionals. It can help professionals develop new fitness programs and provide feedback to their clients. © 2023 IEEE.

关键词： Convolutional neural networks

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An Application-Aware Clustering Strategy in Vehicular Ad Hoc Network 6

An Application-Aware Clustering Strategy in Vehicular Ad Hoc...

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6th International Conference on Computing, Electronics and Communications Engineering, iCCECE 2023

作者： Wei, Chi-Hung Chang, Chin-Chih Chu, Chien-Hao Hsiao, Sean Chung Hua University Ph.D. Program in Engineering Science Hsinchu City Taiwan Chung Hua University Department of Computer Science and Information Engineering Hsinchu City Taiwan Chung Hua University Bachelor Program in Applied Foreign Language and Smart Commerce Hsinchu City Taiwan

ISBN: (纸本)9798350340921

VANET (Vehicular Ad Hoc Network) was developed to address the unique challenges of communication in a mobile vehicular environment. This technology can enhance driving safety and traffic control. Moreover, similar principles can be applied to unmanned aerial vehicles and robotics. When transmitting data in moving vehicles, it is challenging as access points and base stations keep changing, requiring handovers between different access points and base stations. Clustering is a popular approach used to address this challenge. Common clustering strategies are based on the proximity, communication range, the density, the application requirements of the moving vehicles, or hybrid of them. In this paper, we propose a clustering strategy based on the application sublayer in the vehicle communication protocol. If two computing devices on the move run the same application, they can be grouped together. The contribution of this research is to develop a clustering mechanism based on the application with very low overhead. We also validate the proposed method through simulations. The simulation results indicate that the proposed method is feasible. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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Teachers’ voice behavior—Principal leadership-driven or teacher self-driven? Evidence from Taiwan

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Psychology in the Schools 2024年第5期61卷 2077-2099页

作者： Hsieh, Chuan-Chung Gunawan, Imam Li, Hui-Chieh Liang, Jyun-Kai Department of Education and Learning Technology National Tsing Hua University Hsinchu Taiwan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu Taiwan Department of Educational Administration Universitas Negeri Malang Malang Indonesia Department of Business Administration National Taipei University of Business Taipei Taiwan Department of Applied Psychology Hsuan Chuang University Hsinchu Taiwan

This study aims to explore whether teachers’ voice behavior is triggered by the leadership of the principal or the teachers themselves. Two conceptual frameworks are proposed to guide this research. In addition, the current study analyzes separately two dimensions of teachers’ voice behavior, namely, promotive voice and prohibitive voice. data collected from 884 teachers in Taiwan were analyzed to test the moderated mediation model. Results of the first conceptual framework revealed that under identity leadership, teacher agency moderated significantly the relationship of psychological empowerment with prohibitive voice, but not significantly with promotive voice. Findings of the second conceptual framework confirmed that under teacher agency, identity leadership did not significantly moderate the relationships of psychological empowerment with promotive voice and prohibitive voice. Most important, this study discovered that teacher agency is the main trigger for teachers exhibiting promotive and prohibitive voice behaviors. Finally, implications and limitations of this study are presented. © 2024 Wiley Periodicals LLC.

关键词： identity leadership psychological empowerment Taiwan teacher agency teacher voice behavior

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Cuisine Image Recognition and Recommender System using Convolutional Neural Network 5

Cuisine Image Recognition and Recommender System using Convo...

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5th IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2023

作者： Chang, Chin-Chih Wei, Chi-Hung Wu, Kuan-Yun Kao, Hao-Xiang Hsiao, Sean Chung Hua University Department of Computer Science and Information Engineering Hsinchu Taiwan Chung Hua University Ph.D. Program in Engineering Science Hsinchu Taiwan National Kaohsiung University of Science and Technology Department of Computer Science and Information Engineering Kaohsiung Taiwan Chung Hua University Program of Applied Foreign Language and Smart Commerce Hsinchu Taiwan

ISBN: (纸本)9798350314694

The fusion of technology and culinary exploration has allowed for the emergence of advanced online customer service systems. We developed a novel approach to enhance the dining experience. We used a Cuisine Image Recognition and Recommender System (CIRRS) powered by Convolutional Neural Network (CNN) to identify and suggest diverse cuisines based on visual inputs. CIRRS swiftly identified diverse cuisines from user-captured images, offering information on origin, ingredients, and variations by crawling websites. The system enhanced dining experiences by suggesting personalized menus based on individual preferences and past selections. Extensively tested across various culinary genres, CIRRS consistently demonstrated accuracy and adaptability. User feedback validated its potential to simplify dining choices and elevate satisfaction. This innovative system enriched dining experiences as a valuable tool for culinary enthusiasts, chefs, and restaurateurs, bridging the gap between technology and gastronomy, It also offers a unique way to explore Taiwanese cuisines. © 2023 IEEE.

关键词： convolutional neural network (CNN) deep learning image recognition recommender system web crawler

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Symbolic-numeric algorithm for parameter estimation in discrete-time models with exp

arXiv

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arXiv 2024年

作者： Berman, Yosef Forrest, Joshua Grote, Matthew Ovchinnikov, Alexey Rueda, Sonia Ph.D. Program in Mathematics CUNY Graduate Center New York United States Ph.D. Program in Computer Science CUNY Graduate Center New York United States Department of Mathematics CUNY Queens College Queens United States Departamento de Matemática Aplicada E.T.S. Arquitectura Universidad Politécnica de Madrid Spain School of Mathematics and Statistics University of Melbourne VIC Australia

determining unknown parameter values in dynamic models is crucial for accurate analysis of the dynamics across the different scientific disciplines. discrete-time dynamic models are widely used to model biological processes, but it is often difficult to determine these parameters. In this paper, we propose a robust symbolic-numeric approach for parameter estimation in discrete-time models that involve non-algebraic functions such as exp. We illustrate the performance (precision) of our approach by applying our approach to the flour beetle (LPA) model, an archetypal discrete-time model in biology. Unlike optimization-based methods, our algorithm guarantees to find all solutions of the parameter values given time-series data for the measured *** Codes 92B05, 68W30, 14Q20, 39A60, 13P15 © 2024, CC BY-NC-SA.

关键词： Parameter estimation

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An Adaptive and Robust Method for Multi-trait Analysis of Genome-wide Association Studies Using Summary statistics

arXiv

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arXiv 2022年

作者： deng, Qiaolan Song, Chi Lin, Shili Interdisciplinary Ph.D. Program in Biostatistics Division of Biostatistics College of Public Health Department of Statistics The Ohio State University ColumbusOH United States

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with human traits or diseases in the past decade. Nevertheless, much of the heritability of many traits is still unaccounted for. Commonly used single-trait analysis methods are conservative, while multi-trait methods improve statistical power by integrating association evidence across multiple traits. In contrast to individual-level data, GWAS summary statistics are usually publicly available, and thus methods using only summary statistics have greater usage. Although many methods have been developed for joint analysis of multiple traits using summary statistics, there are many issues, including inconsistent performance, computational inefficiency, and numerical problems when considering lots of traits. To address these challenges, we propose a multi-trait adaptive Fisher method for summary statistics (MTAFS), a computationally efficient method with robust power performance. We applied MTAFS to two sets of brain imaging derived phenotypes (IdPs) from the UK Biobank, including a set of 58 Volumetric IdPs and a set of 212 Area IdPs. Together with results from a simulation study, MTAFS shows its advantage over existing multi-trait methods, with robust performance across a range of underlying settings. It controls type 1 error well, and can efficiently handle a large number of traits. © 2022, CC BY.

关键词： Numerical methods

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discrete null field equation methods for solving Laplace's equation: Boundary layer computations

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Numerical Methods for Partial differential Equations 2024年第4期40卷 e23092-e23092页

作者： Zhang, Li-Ping Li, Zi-Cai Lee, Ming-Gong Huang, Hung-Tsai School of Mathematical Sciences Qufu Normal University Shandong Qufu China Department of Applied Mathematics National Sun Yat-sen University Kaohsiung Taiwan Department of Tourism and Leisure/Ph.D. Program in Engineering Science Chung Hua University Hsinchu Taiwan Department of Data Science and Analytics I-Shou University Kaohsiung Taiwan

Consider dirichlet problems of Laplace's equation in a bounded simply-connected domain (Formula presented.), and use the null field equation (NFE) of Green's representation formulation, where the source nodes (Formula presented.) are located on a pseudo-boundary (Formula presented.) outside (Formula presented.) but not close to its boundary (Formula presented.). Simple algorithms are proposed in this article by using the central rule for the NFE, and the normal derivatives (Formula presented.) of the solutions on the boundary (Formula presented.) can be easily obtained. These algorithms are called the discrete null field equation method (dNFEM) because the collocation equations are, indeed, the direct discrete form of the NFE. The bounds of the condition number are like those by the method of fundamental solutions (MFS) yielding the exponential growth as the number of unknowns increases. One trouble of the dNFEM is the near singularity of integrations for the solutions in boundary layers in Green's representation formulation. The traditional BEM also suffers from the same trouble. To deal with the near singularity, quadrature by expansions and the sinh transformation are often used. To handle this trouble, however, we develop two kinds of new techniques: (I) the interpolation techniques by Taylor's formulas with piecewise (Formula presented.) -degree polynomials and the Fourier series, and (II) the mini-rules of integrals, such as the mini-Simpson's and the mini-Gaussian rules. Error analysis is made for technique I to achieve optimal convergence rates. Numerical experiments are carried out for disk domains to support the theoretical analysis made. The numerical performance of the dNFEM is excellent for disk domains to compete with the MFS. The errors with (Formula presented.) can be obtained by combination algorithms, which are satisfactory for most engineering problems. In summary, the new simple dNFEM is based on the NFE, which is different from the boundary elem

关键词： Fourier series

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An Application-Aware Clustering Strategy in Vehicular Ad Hoc Network

An Application-Aware Clustering Strategy in Vehicular Ad Hoc...

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International Conference on Computing, Electronics & Communications Engineering (iCCECE)

作者： Chi-Hung Wei Chin-Chih Chang Chien-Hao Chu Sean Hsiao Ph.D. Program in Engineering Science Chung Hua University Hsinchu City Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu City Taiwan Bachelor Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu City Taiwan

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