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science 2022年第6615期378卷 22-22页

作者： Sills, Jennifer Division of Life Sciences and Medicine University of Science and Technology of China Hefei Anhui 230027 China. Department of Surgery Harvard University Brigham and Women’s Hospital Boston MA 02115 USA. Faculty of Applied Science Macao Polytechnic University Macao SR China. School of Liberal Education Chengdu Jincheng College Chengdu Sichuan 611731 China. Translational Health Science and Technology Institute Faridabad Haryana 121001 India. Department of Chemical Engineering University of Washington Seattle WA 98105 USA. Johns Hopkins University Baltimore MD 21218 USA. The Affiliated Hospital Guizhou Medical University Guiyang Guizhou 550004 China. Department of Infectious Disease Epidemiology Imperial College London London W2 1PG UK. Manchester Fungal Infection Group University of Manchester Manchester UK. Philadelphia PA USA. Harrisburg PA 17102 USA. Department of Chemistry University of Pennsylvania Philadelphia PA 19104 USA. University of Kansas Lawrence KS 66045 USA. Mott MacDonald Noida UP 201010 India. Trudeau Institute Saranac Lake NY 12983 USA. US Department of Agriculture Parlier CA 93648 USA. Vagelos Molecular Life Sciences Program University of Pennsylvania Philadelphia PA 19104 USA. School of Information Systems and Technology Management University of New South Wales Sydney NSW 2052 Australia.

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Quality Analysis the E-PASTI System to Determine the Condition of the System and information Quality

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Journal of Physics: Conference Series 2021年第1期1807卷

作者： Bayu Nugraha Finki Dona Marleny Sfenrianto Sfenrianto Cinthya Edwina Information System Program Faculty of Science and Technology Sari Mulia University Banjarmasin South Kalimantan Indonesia Information Systems Management Department BINUS Graduate Program–Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480

The purpose of this study is to evaluate the quality of secretarial, financial and staffing information systems at the Directorate General of AHU, known as the E-PASTI system. There are two variables analysed, namely system quality and information quality. Data collection using questionnaires that distributed to 123 employees who used the E-PASTI system but returned 93 questionnaires. Data quality analyst uses descriptive quantitative method. The results of the study are several conditions related to the system and information quality of E-PASTI. The quality can be a reference for the AHU Directorate General to improve the quality of E-PASTI that suits the needs of employees.

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A novel evolution-based recommendation system 12

A novel evolution-based recommendation system

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12th International Conference on Ubi-Media Computing, Ubi-Media 2019

作者： Chen, Yi-Cheng Chu, Yen-Lung Hui, Lin Chen, Sheng-Chih Thaipisutikul, Tipajin Weng, Kai-Ze Department of Information Management National Central University Taiwan Department of Computer Science and Information Engineering Tamkang University Taiwan Department of Innovative Information and Technology Tamkang University Taiwan Master's Program of Digital Content and Technologies College of Communication National ChengChi University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan

ISBN: (纸本)9781728128207

Matrix factorization (MF) technique has been widely utilized in recommendation systems due to the precise prediction of users' interests. Prior MF-based methods adapt the overall rating to make the recommendation by extracting latent factors from users and items. However, in real applications, people's preferences usually vary with time;the traditional MF-based methods could not properly capture the change of users' interests. In this paper, by incorporating the recurrent neural network (RNN) into MF, we develop a novel recommendation system, M-RNN-F, to effectively describe the preference evolution of users over time. A learning model is proposed to capture the evolution pattern and predict the user preference in the future. The experimental results show that M-RNN-F performs better than other state-of-the-art recommendation algorithms. In addition, we conduct the experiments on real world dataset to demonstrate the practicability. © 2019 IEEE.

关键词： Recommender systems

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The matter of deep reinforcement learning towards practical ai applications 12

The matter of deep reinforcement learning towards practical ...

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12th International Conference on Ubi-Media Computing, Ubi-Media 2019

作者： Thaipisutikul, Tipajin Chen, Yi-Cheng Hui, Lin Chen, Sheng-Chih Mongkolwat, Pattanasak Shih, Timothy K. Department of Computer Science and Information Engineering National Central University Taiwan Department of Information Management National Central University Taiwan Department of Innovative Information and Technology Tamkang University Taiwan Master's Program of Digital Content and Technologies College of Communication National ChengChi University Taiwan Faculty of Information and Communication Technology Mahidol University Thailand

ISBN: (纸本)9781728128207

Reinforcement Learning (RL) is an extraordinarily paradigm that aims to solve a complex problem. This technique leverages the traditional feedforward networks with temporal-difference learning to overcome supervised and unsupervised real-world problems. However, RL is one of state-of-the-art topic due to the opaque aspects in design and implementation. Also, in which situation we will get performance gain from RL is still unclear. Therefore, This study firstly examines the impact of Experience Replay in Deep Q-Learning agent with Self-Driving Car application. Secondly, The impact of Eligibility Trace in RNN A3C agents with Breakout AI game application is studied. Our results indicated that these two techniques enhance RL performance by more than 20 percent as compared with traditional RL methods. © 2019 IEEE.

关键词： Reinforcement learning

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Citizen science in environmental and ecological sciences

NATURE REVIEWS METHODS PRIMERS

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NATURE REVIEWS METHODS PRIMERS 2022年第1期2卷 1-20页

作者： Morneau, Dominique Novel Data Ecosystems for Sustainability Research Group Advancing Systems Analysis Program International Institute for Applied Systems Analysis (IIASA) Laxenburg Austria Centre d’écologie et des sciences de la conservation Muséum national d’Histoire naturelle Paris France Faculté de droit Université de Namur Namur Belgium Citizen Science Lab Leiden University Leiden Netherlands Department of Mechanical Engineering University of Bath Bath UK Nordic Foundation for Development and Ecology (NORDECO) Copenhagen Denmark Department of Biology Brandeis University Waltham MA USA Ornamental Plant Pathology Department of Plant Pathology Puyallup Research and Extension Center Washington State University Puyallup WA USA Environmental and Sustainability Participatory Information Systems Group Institute of Marine Sciences (ICM-CSIC) Barcelona Spain Electron Microscopy Science Technology Platform The Francis Crick Institute London UK Departamento de Biologia Marina Facultad Ciencias del Mar Universidad Católica del Norte Coquimbo Chile Millennium Nucleus Ecology and Sustainable Management of Oceanic Island (ESMOI) Coquimbo Chile Centro de Estudios Avanzados en Zonas Áridas (CEAZA) Coquimbo Chile Department of Geography University College London (UCL) London UK

This PrimeView highlights the utility of citizen science across a range of ecological and environmental science research.

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Sport science Model to Support the Professional Sports Organization Decision Making

Sport Science Model to Support the Professional Sports Organ...

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International Conference on information management and technology (ICIMTech)

作者： Tanty Oktavia Ford Lumban Gaol Takaaki Hosoda Arsyan Syahir School of Information Systems Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

The role of information technology in sports organizations is important to analyze all aspects including how to win in the competition based on various internal and external factors. The approach that used to enhance the sports organizations is sports science, which is a concept that contributes to the development of athletes by collaborating in many fields and studies, such as anatomy, physiology, psychology, engineering, chemistry, etc. The approach of Sport science articulates the technology that blended on all of the approached. Currently, the use of sports technology or science in Indonesia is also very low in all sports categories. Usually, the management and coaches look at player statistics based on manual data or reports to view player statistics periodically. There is still a lack of exploration to use player statistics to be used by coaches to improve the ability of the players and the organization. This research will propose how to develop sports science with a business intelligence approach that used the Kimball data mart approach as decision support in the field of sports so that management and coaches can apply the correct approach to improve the capacity of players and organizational development. The result of this study will provide the model of sports science that can be implemented for a professional sports organization in Indonesia.

关键词： Business intelligence Decision making Tools Companies

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Transformative Sport science Using Social Media as a Collaboration Tool

Transformative Sport Science Using Social Media as a Collabo...

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International Conference on ICT For Smart Society (ICISS)

作者： Tanty Oktavia Ford Lumban Gaol Takaaki Hosoda Arsyan Syahir School of Information Systems Bina Nusantara University Jakarta Indonesia Binus Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781665404228

ISBN: (纸本)9781665404235

Sports science can have a significant and positive impact on coaches and athletes, as well as for the professional sports organization. According to this situation, more and more organizations are competing to implement sports science as the monitoring systems. Along with the development of technology, it becomes easier for humans to carry out their activities, including communication with each other. Advances in the field of communication technologies have led to the use of social networks to support all activity. With social media, all kinds of information that people want to search for can be found easily. Social networks have their uniqueness in their characteristics. Like LINE has free calling and video calling features, while Instagram has features like Instagram Story, where users can document their activities in the form of photos or recordings. By all the characteristics of social networks, it will support the activity of sports science. The methodology of this research focused on quantitative research based on the T-test approach. The result shows that social media involvement can significantly support collaboration in sports science, so it can increase people's motivation to interact with other participants in sport organizations.

关键词： Sports Social networking (online) Media Reliability Organizations Tools information systems

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The Impact of Learning Motivation on Character-Nurturing and Competitive Game-Based Item Bank Practicing System 10

The Impact of Learning Motivation on Character-Nurturing and...

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10th IEEE International Conference on technology for Education, T4E 2019

作者： Peng, Jui-Chi Lai, Yu-Ling Hwang, Gwo-Haur Health and Hospitality Cardinal Tien Junior College of Healthcare and Management Yilan County Taiwan Information Management Ling Tung University Taichung City Taiwan Bachelor Program in Interdisciplinary Studies National Yunlin University of Science and Technology Yunlin County Taiwan

ISBN: (纸本)9781728142272

In Taiwan, the traditional approach in English learning can be experienced as dull and boring. As a result, it leads to a decline in learning motivation and learning effectiveness. Some scholars have pointed out that adding games into learning could enhance the learner's motivation. However, different game strategies may have different effects on learners' learning motivation. Therefore, this study explored how different types of systems (a character-nurturing game, a competitive game and traditional practice without games) impacted learners' motivation when blending those systems into learning. In order to study this issue, the researchers first developed three systems which were a character-nurturing game-based item bank practicing system, a competitive game-based item bank practicing system and an item bank practicing system without games. Then the researchers invited 125 first-graders from a junior college in northern Taiwan taking an English course, and conducted a nine-week teaching experiment. The results showed that the learners of the competitive-game group had significantly lower confidence and satisfaction than the learners of the character-nurturing-game group. © 2019 IEEE.

关键词： Blending

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A Proposed Model for Consumer-Based Brand Equity Analysis on Social Media Using Data Mining and Social Network Analysis

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Journal of Relationship Marketing 2018年第2期17卷 95-117页

作者： Nogueira, Eduardo Tsunoda, Denise F. Program of Science Management and Information Technology Federal University of Parana Curitiba Parana Brazil

Online social networks have expanded their “virtual borders,” making the Internet more like an environment of social interaction than a business tool. However, even before the emergence and expansion of social media, marketing professionals were interested in identifying consumers' perceptions about brands. Thus, operational models have been proposed to facilitate such a task. Those models, however, can be expensive and inconvenient, since the models use questionnaires for data collection. To help overcome this problem, this article proposes a model for brand equity analysis from the consumer perspective expressed in social networks using opinion mining techniques and social network analysis. The application of the proposed model on data collected from Twitter made it possible to analyze five brand equity dimensions: brand awareness, brand loyalty, perceived sentiment, perceived quality, and brand associations. The results reached by the application of the model show that brand equity can be analyzed from data retrieved from virtual social networks, disclosing how consumers perceive brands in such an environment, without using questionnaires, enabling different brands in different contexts. Those data can be analyzed under both objective and replicable criteria for each of the brand equity elements that make up the model. © 2018 Taylor & Francis Group, LLC.

关键词： brand equity consumer-based brand equity data mining knowledge discovery online social network social media social network analysis

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Left ventricular hypertrophy detection using electrocardiographic signal

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Scientific reports 2023年第1期13卷 2556页

作者： Cheng-Wei Liu Fu-Hsing Wu Yu-Lun Hu Ren-Hao Pan Chuen-Horng Lin Yung-Fu Chen Guo-Shiang Tseng Yung-Kuan Chan Ching-Lin Wang Division of Cardiology Department of Internal Medicine Tri-Service General Hospital Songshan Branch National Defense Medical Center Taipei Taiwan. Bachelor Degree Program of Artificial Intelligence National Taichung University of Science and Technology Taichung Taiwan. Department of Management Information Systems National Chung-Hsing University Taichung Taiwan. La Vida Tec. Co. Ltd. Taichung Taiwan. Preventive Medicine Center National Yang Ming Chiao Tung University Taipei Taiwan. Department of Information Management Tunghai University Taichung Taiwan. Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taichung Taiwan. Department of Dental Technology and Materials Science Central Taiwan University of Science and Technology Taichung Taiwan. Division of Cardiology Department of Internal Medicine Taoyuan Armed Force General Hospital Hsinchu Branch Hsinchu Taiwan. Department of Management Information Systems National Chung-Hsing University Taichung Taiwan. ykchan@nchu.edu.tw. Department of Information Management National Chin-Yi University of Technology Taichung Taiwan. clwang@ncut.edu.tw.

Left ventricular hypertrophy (LVH) indicates subclinical organ damage, associating with the incidence of cardiovascular diseases. From the medical perspective, electrocardiogram (ECG) is a low-cost, non-invasive, and easily reproducible tool that is often used as a preliminary diagnosis for the detection of heart disease. Nowadays, there are many criteria for assessing LVH by ECG. These criteria usually include that voltage combination of RS peaks in multi-lead ECG must be greater than one or more thresholds for diagnosis. We developed a system for detecting LVH using ECG signals by two steps: firstly, the R-peak and S-valley amplitudes of the 12-lead ECG were extracted to automatically obtain a total of 24 features and ECG beats of each case (LVH or non-LVH) were segmented; secondly, a back propagation neural network (BPN) was trained using a dataset with these features. Echocardiography (ECHO) was used as the gold standard for diagnosing LVH. The number of LVH cases (of a Taiwanese population) identified was 173. As each ECG sequence generally included 8 to 13 cycles (heartbeats) due to differences in heart rate, etc., we identified 1466 ECG cycles of LVH patients after beat segmentation. Results showed that our BPN model for detecting LVH reached the testing accuracy, precision, sensitivity, and specificity of 0.961, 0.958, 0.966 and 0.956, respectively. Detection performances of our BPN model, on the whole, outperform 7 methods using ECG criteria and many ECG-based artificial intelligence (AI) models reported previously for detecting LVH.

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