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Decentralized Learning with Virtual Patients for Medical Diagnosis of Diabetes

sN Computer science 2021年第4期2卷 239页

作者： Takahashi, Yuta Chang, Han-ten Nakai, Akie Kagawa, Rina Ando, Hiroyasu Imakura, Akira Okada, Yukihiko Tsurushima, Hideo suzuki, Kenji sakurai, Tetsuya Faculty of Engineering Information and Systems University of Tsukuba Tsukuba Japan Center for Artificial Intelligence Research University of Tsukuba Tsukuba Japan Master’s Program in Service Engineering University of Tsukuba Tsukuba Japan Faculty of Medicine University of Tsukuba Tsukuba Japan Advanced Institute for Materials Research Tohoku University Sendai Japan

Machine learning, applied to medical data, can uncover new knowledge and support medical practices. However, analyzing medical data by machine learning methods presents a trade-off between accuracy and privacy. To overcome the trade-off, we apply the data collaboration analysis method to medical data. This method using artificial dummy data enables analysis to compare distributed information without using the original data. The purpose of our experiment is to identify patients diagnosed with diabetes mellitus (DM), using 29,802 instances of real data obtained from the University of Tsukuba Hospital between 01/03/2013 and 30/09/2018. The whole data is divided into a number of datasets to simulate different hospitals. We propose the following improvements for the data collaboration analysis. (1) Making the dummy data which has a reality and (2) using non-linear reconverting functions into the comparable space. Both can be realized using the generative adversarial network (GAN) and Node2Vec, respectively. The improvement effects of dummy data with GAN scores more than 10% over the effects of dummy data with random numbers. Furthermore, the improvement effect of the re-conversion by Node2Vec with GAN anchor data scores about 20% higher than the linear method with random dummy data. Our results reveal that the data collaboration method with appropriate modifications, depending on data type, improves analysis performance. © 2021, The Author(s).

关键词： Data collaboration Generative adversarial network Machine learning Medical data

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Overview of Bearing Fault Diagnosis Based on Deep Learning 3

Overview of Bearing Fault Diagnosis Based on Deep Learning

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3rd IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2023

作者： Zou, Xue-Ling Han, Kai-Xu Chien, Wei Gan, Xin-Yan shi, Liu-Yue School of Electric and Information Engineering Beibu Gulf University Qinzhou China School of Information Management and Master's Program Lunghwa University of Science and Technology Taoyuan City Taiwan Guangxi University of Chinese Medicine Nanning China

ISBN: (纸本)9798350333862

Deep learning has excellent learning and feature classification abilities, extracting features in massive, multi-source, and high-dimensional measurement data. It also diagnoses and generalizes models without relying on manual intervention. Thus, it is widely used in equipment fault diagnosis. We introduce the common models of deep learning: deep confidence network, convolutional neural network, and automatic encoder. Using deep learning, the fault diagnosis of rolling bearings is executed, and the result provides the basis for future development. © 2023 IEEE.

关键词： Failure analysis

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Even-sized clustering with noise clustering method

Even-sized clustering with noise clustering method

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International symposium on Advanced Intelligent systems

作者： Kei Kitajima Yasunori Endo Master’s Program in Risk Engineering University of Tsukuba Ibaraki Japan Faculty of Engineering Information and Systems University of Tsukuba Ibaraki Japan

ISBN: (纸本)9781538626344;9781538626337

Clustering is a method of data analysis without the use of supervised data. Clustering method focusing on cluster size is expected to be useful for task distribution problems and several methods have been proposed. We proposed Fuzzy Even-sized Clustering Based on Optimization (FECBO) and COntrolled-sized Clustering Based on Optimization as a method focusing on cluster size. However, these methods have the problem that they are susceptible to noise. It is believed that this issue can be overcome by applying noise clustering method. Noise clustering is a method that it classify noise into noise clusters. In this study, we extend FECBO and COCBO with noise clustering and verify its effectiveness through numerical examples.

关键词： Clustering Machine learning Even-sized Noise clustering

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Creating Mathematical Models to Help Formulate Company strategies for Knowledge Management system Implementation 9

Creating Mathematical Models to Help Formulate Company Strat...

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9th International Conference on information Management and Technology, ICIMTech 2024

作者： sardjono, Wahyu Perdana, Widhilaga Gia Pranata, Dewi sagita BINUS Graduate Program Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia Post Graduate Program of Management Science State University of Jakarta Jakarta13220 Indonesia King's College London Cyber Security Studi Program Faculty of Natural Mathematical & Engineering Sciences Department of Informatics Strands West MinsterWC2R 2LS United Kingdom

ISBN: (纸本)9798350390025

This research aims to build a mathematical model to formulate the problems of implementing knowledge management systems in companies that often face obstacles in achieving the desired objectives and goals. With increasing competition in the business sector, organizations or organizations realize the importance of utilizing the knowledge assets that reside in each individual and organization. If this knowledge can be managed optimally, it can become a competitive advantage for the company due to the emergence of innovative ideas by the concepts of knowledge management theory. By implementing optimal knowledge management (KM), companies can design innovative solutions to improve business operations and increase overall revenue. The factor analysis method will be used to find the determining factors for the success of the implementation of knowledge management systems (KMs) and the regression analysis method will also be used to form a mathematical model of several new factors which are formed as independent variables with the current level of community understanding of KMs as the dependent variable. The research results provide insight into strategies to improve success factors to successfully facilitate KMs implementation. This study contributes to existing knowledge management by providing insight into dynamics that go beyond the technical aspects of KMs, ultimately developing strategies for more effective and efficient utilization of knowledge and organizational growth and supporting competitive advantage for companies. © 2024 IEEE.

关键词： Knowledge organization system (KOs)

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Robot Tele-Operation / Teaching system using VR Device

Robot Tele-Operation / Teaching System using VR Device

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IEEE Conference on Cybernetics and Intelligent systems

作者： Minami Ohsato Yasumichi Aiyama Master’s Program in Systems and Information Engineering University of Tsukuba (Alumna) Tsukuba Japan Inst. of Systemsand Information Engineering University of Tsukuba Tsukuba Japan

This paper proposes a "robot tele-teaching system using a VR device" as a new robot teaching method to replace the conventional robot teaching method. Currently we still need teach-pendant to teach industrial robots. It is very inconvenient method. Our novel method consists of two robots and a VR device. One robot is on site instead of the operator. A stereo camera is attached to its end of the robot, which realizes a 3D positionand posture obtained from HMD. The operator can then view the images through the HMD as if he/she are on site. The other manipulating robot is equipped with a gripper and can follow the position and orientation of the gripper-like input device held by the operator. This system is equipped with a correction and auto-teaching function that uses the geometric characteristics of the work object. This significantly reduces the time required for operation. In addition, the teaching points obtained by this system have been successfully used for playback in a real environment.

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Factors that Influence E-satisfaction and Their Impact on Online Purchase Intention of Telemedicine Applications 9

Factors that Influence E-Satisfaction and Their Impact on On...

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9th IEEE International Conference on Computing, engineering and Design, ICCED 2023

作者： Gui, Anderes so, Idris Gautama Novantia, Dea Princes, Elfindah sianipar, Nesti Fronika Haron, Hasnah Bina Nusantara University Information System Program School of Information Systems Jakarta Indonesia Bina Nusantara University Binus Business School Management Department Jakarta Indonesia Bina Nusantara University Binus Graduate Program-Master of Information Systems Management Information Systems Management Department Jakarta Indonesia Bina Nusantara University Faculty of Engineering Food Technology Department Jakarta Indonesia Universiti Sains Islam Malaysia Faculty of Economics and Muamalat Nilai Malaysia

ISBN: (纸本)9798350370126

This study embarked on a rigorous examination of the factors driving user satisfaction and usage behavior in the context of telehealth applications. Utilizing a well- structured Google Form survey, distributed through an array of social media platforms, including WhatsApp, Discord, Instagram, and Line, the research gathered 251 responses. The purposive sampling technique was employed to ensure that the data captured the experiences of individuals who had actively engaged with telehealth services. One hypothesis, relating to the influence of Online Reviews, was found to be unsupported. This surprising result suggests that, contrary to expectations, the opinions and reviews shared online do not significantly affect users' satisfaction or their behavioral decisions in the context of telehealth applications. This finding highlights the need for a more nuanced understanding of the factors influencing user preferences and choices in this rapidly evolving sector. Conversely, other hypotheses examining factors such as social Influence, Facilitating Conditions, Perceived Reliability, Price Value, and Purchase Intention were substantiated. The positive influence of these factors on customer usage behavior underscores their significance in shaping user experiences and satisfaction within the telehealth ecosystem. Furthermore, the study posits that facilitating conditions should be closely aligned with technological advancements, as this alignment is conducive to the development of enhanced application features. This insight suggests that telehealth providers should continuously innovate and integrate advanced technologies to ensure that the facilitating conditions meet the ever-evolving needs and expectations of users. © 2023 IEEE.

关键词： sales

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Time and motion study for operation improvement in Ryokans

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Journal of Japan Industrial Management Association 2015年第4E期66卷 448-459页

作者： Akada, Yosuke T. Awamura, Hironobu K. Master's Program in Business Administration and Public Policy University of Tsukuba Japan Information and Systems University of Tsukuba Japan

The turnover rate in the accommodation industry is higher than that of any other industry in Japan. The long business hours in ryokans make it difficult for employees to work there. To achieve a work-life balance, it is necessary for ryokans to improve operations. Furthermore, service industries are expected to earn considerable benefits by using time and motion study. In this paper, we apply time and motion study to the operation of cleaning up after banquets in ryokans. First, the problems encountered during operations are identified by time and motion study. second, the proposed operation intended to solve these problems is developed. Third, the proposed operation is evaluated from the total operation time calculated by the methods-time measurement system. Finally, the usefulness of the proposed operation is evaluated in terms of its practical application. Consequently, it is found that the proposed operation is useful from the perspective of the total operation time and workload.

关键词： Flowcharting

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Decision support system in Determining the Achievement of Widyaiswara Value Using WAsPAs and TOPsIs Algorithm 1

Decision Support System in Determining the Achievement of Wi...

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1st International Conference on Technology Innovation and Its Applications, ICTIIA 2022

作者： Pratama, Yudhistira Adhitya Iswara, Bagus Ajie Nababan, Adli Abdillah Information System Studies Program Pelita Harapan University Medan Campus Faculty Of Computer Science Medan Indonesia Master's Study Program Informatics Engineering Universitas Sumatera Utara Faculty Of Computer Science And Information Technology Medan Indonesia Digital Business Study Program Stmik Pelita Nusantara Medan Indonesia

ISBN: (数字)9781665488266

ISBN: (纸本)9781665488266

Widyaiswara is required to show the best performance to fulfill his duties and obligations. Therefore, it is very important to measure the performance of the Widyaiswara, so that it can be used as evaluation material by the BPsDM PROVsU. However, the assessment process that occurs is still not precise and time-consuming. Therefore, to minimize this, a decision support system is needed that can minimize time errors and data processing in decision-making so that the assessment runs well and accurately. This system was built by applying the WAsPAs method and the TOPsIs method. Based on the results of tests carried out five times, the results of the WAsPAs method processing time resulted in an average processing time of 0.00029791 ms and an average memory usage value of 2.836.44 kb, while the results of the TOPsIs method processing time test resulted in an average processing time - an average of 0.000296428 ms and an average memory usage value of 2.862.34 kb. © 2022 IEEE.

关键词： Decision support systems

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Construction of a metadata space for a specific field of knowledge from an index of a document

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systems and Computers in Japan 2007年第5期38卷 30-42页

作者： Nakanishi, Takafumi Kishimoto, sadaya sakurai, Tetsuya Kitagawa, Takashi Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba 305-8577 Japan Master's Program in Science and Engineering University of Tsukuba Tsukuba 305-8577 Japan

In this paper, we propose a method for generating a metadata space of associations between words from an index of a book dealing with a specific field of interest. In order to implement a search mechanism using a mathematical model of meaning that deals with a specific field of interest, it is necessary to generate a search space called a metadata space dealing with the field of interest. In the past, the metadata space has been generated by using a terminology dictionary and a highly specialized knowledge base. Also, it is difficult to generate the metadata space if there is no terminology dictionary that deals with the field of interest. The proposed method does not require a terminology dictionary, and it allows the generation of the metadata space without a highly specialized knowledge base. Further, by applying this metadata space generation method to a mathematical model of meaning, a search mechanism based on the associations between words in the search target data, such as documents and media data, in the specific field of interest can be implemented. In this paper, taking examples from the IT field, the effectiveness of the method is verified by comparing the use of a metadata space generated from a terminology dictionary and the use of a metadata space generated from an index to search graphic media data. © 2007 Wiley Periodicals, Inc.

关键词： Metadata

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Effectiveness of human evaluation and human load in acquisition of intelligible fuzzy rules

Effectiveness of human evaluation and human load in acquisit...

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sICE 2003 Annual Conference, sICE 2003

作者： Onisawa, Takehisa Fujihara, Yoshitaka Institute of Engineering Mechanics and Systems University of Tsukuba 1-1-1 Tennodai Tsukuba305-8573 Japan Master's Program in Science and Engineering Onisawa Lab. Institute of Engineering Mechanics and Systems University of Tsukuba 1-1-1 Tennodai Tsukuba305-8573 Japan

ISBN: (纸本)0780383524

Ths pap r discusses the effectiveness of hu an evaluation in the acquisition of fuzzy rules that are proper for situations and intelligible to human. Interactive Genetic Algorithm (Interactive GA) is used for the rules acquisition. Taking car control for running through cran-typed courses as an example, acquired fuzzy rules with human evaluation ad those without human evaluation are eompared with eaeh other. This paper also discusses human load in the evaluation of acquired fuzzy rules. © 2003 sICE.

关键词： Fuzzy rules

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