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IEEE International Conference on Systems, Man and Cybernetics

作者： Tao Peng Jing Zhao Yidong Gu Gongye Di Lei Zhang Jing Cai School of Future Science and Engineering Soochow University Suzhou China Department of Radiation Oncology UT Southwestern Medical Center Dallas TX USA Department of Ultrasound Tsinghua University Affiliated Beijing Tsinghua Changgung Hospital Beijing China Department of Medical Ultrasound Suzhou Municipal Hospital The Affiliated Suzhou Hospital of Nanjing Medical University Suzhou Jiangsu China Department of Ultrasonic The Affiliated Taizhou People's Hospital of Nanjing Medical University Taizhou China Graduate Program of Medical Physics and Data Science Research Center Duke Kunshan University Kunshan Jiangsu China Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong China

Ultrasound image segmentation is crucial for early disease detection and treatment planning but remains a challenging task due to the low contrast of organ boundaries and varying image quality. Current methods often require manual intervention or have limited accuracy. In this paper, we propose a novel hybrid framework that combines an automatic option polygon segment (AOPS) algorithm and a distributed- and memory-based evolution (DME) algorithm for precise ultrasound organ segmentation. Our pipeline consists of two cascaded stages: (1) a coarse segmentation step using the AOPS algorithm, which determines the number of vertices/clusters without human intervention, and (2) a refinement step using the DME algorithm to hunt for the optimal neural network, which is then used to represent a smooth, explainable mathematical expression of the organ boundary. We employ the fractional backpropagation learning network with L2 regularization (FBLN) for training and use the scaled exponential linear unit (SELU) activation function to address the vanishing gradient problem. This is a new attempt such a hybrid framework is applied to ultrasound organ segmentation tasks, and it demonstrates significant contributions in terms of accuracy, smoothness, and computational efficiency.

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Comparison Analysis of Simple Additive Weighting (SAW) and Weigthed Product (WP) in Decision Support Systems 2

Comparison Analysis of Simple Additive Weighting (SAW) and W...

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2nd International Conference on Technology, Innovation, Society and Science-to-Business, ICTIS 2018

作者： Wira Trise Putra, Dede Agustian Punggara, Adrian Institut Teknologi Padang Informatics Engineering Study Program Padang Indonesia

Decision support system is a way to help decision maker to choose the best decision from several available alternatives. In the process of decision support system required criteria and weights to be used in the calculation process. Simple additive weighting (SAW) and Weigthed product (WP) are methods in decision support systems that have a search method taking into account the weights held by the criteria. comparison analysis is performed to look at between the WP and SAW methods, methods that have a higher level of accuracy and are in accordance with the conditions. The SAW method uses a weighted weaning system whereas the WP method uses multiplication in calculating the attribute rating. From the weight of each criteria there will be used in the calculation to produce several alternatives. The object of the case study in this study is the determination of people's business credit in the banking world using seven criteria. the criteria used are personal character, credit status, business condition, income, guarantee, guarantee condition and installment. Results of testing using SAW method and WP method, it can help compare the best alternative level results by using the same data and criteria, so both methods can be used as consideration in decision making. WP method gives clear cost and benefit value compared to SAW, but in SAW result gives more clear result because it is based on predetermined value and weight. © The Authors, published by EDP Sciences, 2018.

关键词： Decision support systems

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Comparison of case-based reasoning and dempster shafer on expert system of cassava disease identification 2

Comparison of case-based reasoning and dempster shafer on ex...

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2nd International Conference on Technology, Innovation, Society and Science-to-Business, ICTIS 2018

作者： Minarni Warman, Indra Yuhendra Handayani, Wenda Institut Teknologi Padang Informatics Engineering Study Program Padang Indonesia

This study aims to develop a web-based expert system that can identify cassava disease using Case-Based Reasoning Method and Shafer Dempster Method, and to know the performance comparison of both based on the accuracy of identification. Case-Based Reasoning (CBR) is a computer-generated system that uses old knowledge to solve new problems. CBR provides solutions to new cases by looking at the oldest cases that are closest to new cases. The identification process is done by entering new cases containing the symptoms to be identified into the system, then perform the process of calculating the value of similarity between the new case and the base case using the nearest neighbor method. Dempster Shafer based on two ideas is the idea of obtaining degrees of confidence of subjective possibilities and the rule of dempster safer itself to combine degrees of confidence based on the evidence obtained. This expert system is built using PHP programming language and MySQL data base. The output of the system is the percentage of identification result of both methods. Testing and analysis results show that Case-Based Reasoning provides better identification accuracy than Dempster Shafer. © The Authors, published by EDP Sciences, 2018.

关键词： Case based reasoning

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Contour Detection from Ultrasound Kidney Images with A Coarse-to-Fine Approach

Contour Detection from Ultrasound Kidney Images with A Coars...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Tao Peng Yidong Gu Yanqing Xu Caishan Wang Lei Zhang Jing Cai School of Future Science and Engineering Soochow University Suzhou China Department of Radiation Oncology UT Southwestern Medical Center Dallas TX USA Department of Medical Ultrasound the Affiliated Suzhou Hospital of Nanjing Medical University Suzhou Municipal Hospital Suzhou Jiangsu China McDermott Center for Human Growth and Development University of Texas Southwestern Medical Center Dallas Texas USA Department of Ultrasound the Second Affiliated Hospital of Soochow University Suzhou China Graduate Program of Medical Physics and Data Science Research Center Duke Kunshan University Kunshan Jiangsu China Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong China

Ultrasound kidney image segmentation presents significant challenges due to missing or ambiguous boundaries. In this study, we introduce a coarse-to-refinement approach incorporating four novel aspects. Firstly, we leverage the properties of a principal curve (PC) to automatically fine-tune the curve shape and employ a neural network's learning ability to reduce model error. Secondly, a deep fusion learning network is utilized for the coarse segmentation step, incorporating a parallel architecture to enhance deep-learning performance. Thirdly, addressing the limitation of standard PC-based methods in determining the number of vertices automatically, we propose an automatic searching polygon tracking method using a mean shift clustering-based approach to replace the projection and vertex extension step in standard PC-based methods. Lastly, we develop an explainable mathematical map function for the kidney contour, as denoted by the neural network output (i.e., optimized vertices), which aligns well with the ground truth contour. We conducted various experiments to evaluate our method's performance, demonstrating its effectiveness in ultrasound kidney image segmentation.

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Utilization of the gesture library for learning Java characters interactively 12

Utilization of the gesture library for learning Java charact...

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12th International Conference on Telecommunication Systems, Services, and Applications, TSSA 2018

作者： Dyah Puji Astuti, Nur Rochmah Arfiani, Ika Laksono, Doni Nur Informatics Engineering Study Program Ahmad Dahlan University Yogyakarta Indonesia

ISBN: (纸本)9781538669402

Javanese characters is a priceless cultural heritage. The form of the characters and the art of making it become a legacy that deserves to be preserved. The difficulty that is often experienced by the community is in terms of remembering the form, pronunciation, and errors in placing Javanese characters pairs and the lack of available references. Coupled with the elimination of curricula regarding regional languages at the SMA / SMK level. This encourages writers to conduct research and build mobile learning applications for Java characters learning. With the aim of producing a Mobile Learning application that can Assist learning and writing Javanese characters to be more interactive so as to motivate the community to learn Javanese *** use of the Gesture API technology that functions when the user starts touching the screen and performs the movements that have been determined by the system and understood by the system itself. The steps taken are analyzing the problem regarding the making of this Java characters mobile learning application through observation, interviews and literature studies to be further identified to obtain data from the general public. Then do the system needs analysis, user needs analysis, while the results will be tested using Black Box and Post Study analysis to determine the extent of the usability system to the problems in the communityThe results of the application built in the form of the introduction of Javanese characters with a gesture board, Javanese characters pronunciation in the form of audio visual and Javanese characters quiz writing so that it was more effective and interactive. With the results of testing the black box test, the application built has been running according to its use and function and based on post study testing obtained the average rating of respondents with the results stated that community categories are acceptable, acceptable and acceptable students. © 2018 IEEE.

关键词： Android (operating system)

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Optical character recognition and long short-term memory neural network approach for book classification by librarians

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Journal of Physics: Conference Series 2020年第3期1567卷

作者： YD Rosita YN Sukmaningtyas Study Program of Informatics Engineering Universitas Islam Majapahit

The book is classified by librarians that use Decimal Dewey Classification (DDS) System. It is used for cataloging and indexing books. DDC has three divisions, a ten, a hundred, and a thousand. The book subject is reflected in each division. Commonly, to know the book content, librarians read the book title. Then, they identify the book index in DDC system. Nevertheless, it requires more time. To read the book title, Optical Character Recognition (OCR) aids them to get the book title efficiently that convert the image of the book cover into the text-editable. Librarians use a web camera to scan the book cover, especially the book title area. There are three steps for pre-processing, the lowercase changing, the useless word removing, and tokenizing. To detect the book categories, Long Short-Term Memory Neural Network is good implemented in this research. It is almost used for text classification. In this research, It gives high performance that achieves more than 92% accurately.

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Analysis of Server Virtualization Service Performance Using Citrix Xenserver

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Journal of Physics: Conference Series 2020年第1期1500卷

作者： Surahmat Alfred Tenggono Informatics Engineering Study Program STMIK PalComTech Indonesia

Virtualization technology is a technology that allows making things into a virtual form. Server virtualization itself is a software technology that can enable physical servers to run many operating systems on a physical server. In this study, the service performance testing of Citrix Xenserver was conducted to determine the service performance of this server virtualization. The research method in this study used action research by testing the CPU load and Memory Usage, Benchmark, Network Traffic, and then the response of users by using the technology acceptance model approach. The results obtained from this study were that Citrix XenServer is able to run a virtual operating system well and also get a good user response which can be seen from the questionnaire data.

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On the Parameter Combinations that Matter and on Those that do Not

arXiv

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arXiv 2021年

作者： Evangelou, Nikolaos Wichrowski, Noah J. Kevrekidis, George A. Dietrich, Felix Kooshkbaghi, Mahdi McFann, Sarah Kevrekidis, Ioannis G. Department of Chemical and Biomolecular Engineering Johns Hopkins University United States Department of Applied Mathematics and Statistics Johns Hopkins University United States Department of Mathematics and Statistics University of Massachusetts Amherst United States Department of Informatics Technical University of Munich Germany The Program in Applied and Computational Mathematics Princeton University United States Department of Chemical and Biological Engineering Princeton University United States Lewis-Sigler Institute for Integrative Genomics Princeton University United States

We present a data-driven approach to characterizing nonidentifiability of a model’s parameters and illustrate it through dynamic as well as steady kinetic models. By employing Diffusion Maps and their extensions, we discover the minimal combinations of parameters required to characterize the output behavior of a chemical system: a set of effective parameters for the model. Furthermore, we introduce and use a Conformal Autoencoder Neural Network technique, as well as a kernel-based Jointly Smooth Function technique, to disentangle the redundant parameter combinations that do not affect the output behavior from the ones that do. We discuss the interpretability of our data-driven effective parameters, and demonstrate the utility of the approach both for behavior prediction and parameter estimation. In the latter task, it becomes important to describe level sets in parameter space that are consistent with a particular output behavior. We validate our approach on a model of multisite phosphorylation, where a reduced set of effective parameters (nonlinear combinations of the physical ones) has previously been established *** Codes 37E99 (Primary), 68T07 (Secondary) Copyright © 2021, The Authors. All rights reserved.

关键词： Parameter estimation

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A review of face expression recognition system recommendation for psychiatric disease

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AIP Conference Proceedings 2023年第1期2683卷

作者： Ahmad Ilham Suryono Suryono Catur Edi Widodo Doctoral Program of Information System School of Postgraduate Studies Diponegoro University 50241 Semarang-Central Java Indonesia Department of Informatics Faculty of Engineering Universitas Muhammadiyah Semarang 50273 Semarang-Central Java Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University 50275 Semarang – Central Java Indonesia

Research on human mental disorders has started exploring the relationship between human facial expression recognition (FER) and symptoms of mental disorders because cases in FER are similar to symptoms in psychiatric disease. With the tremendous success of machine learning and deep learning, various models and architecture of these techniques are being leveraged to achieve better performance. The purpose of this work is to undertake a review of the most recent work on automatic facial emotion recognition (FER) using deep learning. We emphasize these contributions from the deep learning architecture and facial databases and the researchers’ progress by comparing the recommended technique with the findings produced. The study found that facial expression recognition based on cognitive internet of things (CIoT) in psychiatry disease did not yet exist, so it became a big opportunity to develop this research in the future. It can be concluded that this research can assist scholars by examining previous works and providing insights to improve this field and can be used as recommendations for psychiatric disease.

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Survey on How to Select and Develop Learning Media Conducted by Teacher Professional Education Participants

Survey on How to Select and Develop Learning Media Conducted...

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International Conference on Electrical, Electronic, informatics and Vocational Education 2018, ICE-ELINVO 2018

作者： Marpanaji, E. Mahali, M.I. Putra, R.A.S. Electronic and Informatics Engineering Education Faculty of Engineering Yogyakarta State University Indonesia Electronic Engineering and Informatics Education Postgraduate Program Yogyakarta State University Indonesia

This paper discusses the selection and development of instructional media of participants of Teacher Professional Education held in the Department of Electronic engineering Education, Faculty of engineering, Universitas Negeri Yogyakarta in the 2018. Teacher Professional Education Participants were middle school and elementary school teachers from Java and Sumatra, Indonesia. The total respondents were 82 teachers. Based on the results of the survey, it was found that most of the teachers had carried out the task of selecting and developing the media even though it was not based on Anderson's theory in selecting and developing media. Most teachers (53.66%) always used learning media when carrying out the learning process. Most of the teachers made their own learning media (78.05%) using computers (84.15%) in the form of Microsoft Power Point presentations (100%). Finally, most teachers did not understand Anderson's theory about the selection and development of learning media (72.20%). © Published under licence by IOP Publishing Ltd.

关键词： Surveys

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