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28th International Meshing Roundtable, IMR 2019

作者： Stees, Mike Dotzel, Myra Shontz, Suzanne M. Department of Electrical Engineering and Computer Science Information and Telecommunication Technology Center University of Kansas 1520 W. 15th Street LawrenceKS66045 United States Department of Electrical Engineering and Computer Science Department of Mathematics Information and Telecommunication Technology Center University of Kansas 1520 W. 15th Street LawrenceKS66045 United States Department of Electrical Engineering and Computer Science Bioengineering Program Information and Telecommunication Technology Center University of Kansas 1520 W. 15th Street LawrenceKS66045 United States

ISBN: (纸本)9781733489003

One challenge in the generation of high-order meshes is that mesh tangling can occur as a consequence of moving the new boundary nodes to the true curved boundary. In this paper, we propose a new optimization-based method that uses signed angles to untangle invalid second- and third-order triangular meshes. Our proposed method consists of two passes. In the first pass, we loop over each high-order interior edge node and minimize an objective function based on the signed angles of the pair of triangles that share the node. In the second pass, we loop over face nodes and move them to the mean of the high-order nodes of the triangle to which the face node belongs. We present several numerical examples in two dimensions with second- and third-order elements that demonstrate the capabilities of our method for untangling invalid meshes. © 2019 Proceedings of the 28th International Meshing Roundtable, IMR 2019. All rights reserved.

关键词： Numerical methods

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Optimization and Computing Model of Fish Resource Supply Chain Distribution Network

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Journal of Physics: Conference Series 2021年第1期1898卷

作者： Nurdin M Zarlis Tulus S Efendi Graduate Program of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia. Department of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia. Department of Mathematics Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Sumatera Utara Medan Indonesia.

Aceh is a province that is rich in fishery resource potential. Fish resources become one of the leading commodities, therefore we need a supply chain optimization model. Optimization is one of the technologies widely used in supply chain network management. Fish resource supply chain becomes very important because it is caused by several factors, including the diversity of types of products from fish resources and their short expiry. The steps used in this research is literature review, determine parameters and decision variables, formulate the objective function and constraint function, modeling and model implementation. The purpose of this research is to get an optimization model in planning and managing the fish resource supply chain by using mixed integer linear programming, so that the resulting model can solve problems in the limitations of fish resources in certain areas, can distribute all consumer demand quickly. This new model can minimize transportation costs to suppliers, minimize transportation costs from suppliers to distribution centers and minimize transportation costs from distribution centers to consumers, and minimize product inventory costs to suppliers and to distribution centers.

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GAME ON! A PROTOTYPE OF A VIRTUAL CLINICAL RADIOTHERAPY LEARNING APPLICATION

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Journal of Medical Imaging and Radiation Sciences 2023年第3期54卷 S34-S34页

作者： Aniza, Azmi Nor Afiqah, Mohd Sukri Nur Zuan, Lee Xi Chit, Som Khid AL Som Azmie, Yahya Noorazrul Noraini, Ahmad Wahid Izzuan, Hussin Saiful Liyana, Shuib Diagnostic Imaging and Radiotherapy Program Faculty of Health Sciences Universiti Kebangsaan Malaysia 50300 Kuala Lumpur Malaysia National University Hospital Singapore 5 Lower Kent Ridge Road Singapore Diagnostic Radiology Singapore General Hospital Outram Rd Singapore Department of Mathematical Sciences Faculty of Science and Technology Universiti Kebangsaan Malaysia 43600 Selangor Darul Ehsan Malaysia Department of Information Systems Faculty of Computer Science and Information Technology University of Malaya 50603 Kuala Lumpur Malaysia

OBJECTIVE"Game On" is a prototype of a Virtual Clinical Radiotherapy Learning Application (VRLA) designed to provide an immersive pre-clinical learning experience for undergraduates in the Diagnostic Imaging and Radiotherapy (PDR) program at UKM. The VRLA aims to prepare students for their clinical attachments in radiotherapy departments by focusing on patient positioning and immobilization device placement, aligned with the learning outcomes of the Radiotherapy Treatment Planning course. MATERIALS & METHODSThis pilot study involved the development using Unity and Blender software; the VRLA offers a virtual environment where students can engage in interactive gameplay related to radiotherapy procedures. The initial phase of the game model emphasizes key areas such as the lung, breast, and male reproductive regions. The VRLA aims to enhance students' understanding and skills in radiotherapy techniques by employing realistic simulations and game mechanics. A pilot study was conducted with 22 participants, including academicians and PDR students, to assess the effectiveness of the VRLA. Additionally, a BETA test was conducted through an online survey to evaluate user acceptance and engagement. RESULTSThe findings indicate generally positive levels of user acceptance, particularly among the student group. However, the academic group displayed a relatively neutral response regarding user engagement. While the VRLA demonstrates promising effectiveness for pre-clinical learning, further enhancements are necessary to improve user engagement. Recommendations include refining the game's story flow, incorporating additional game elements, and addressing the specific needs of different user groups. CONCLUSIONThis research contributes to advancing virtual clinical learning applications in radiotherapy education. The findings provide insights for developing innovative and engaging tools that can augment traditional educational approaches and enhance the learning experience for ra

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Question-Answering System Extracts information on Injection Drug Use from Clinical Notes

arXiv

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arXiv 2023年

作者： Mahbub, Maria Goethert, Ian Danciu, Ioana Knight, Kathryn Srinivasan, Sudarshan Tamang, Suzanne Rozenberg-Ben-Dror, Karine Solares, Hugo Martins, Susana Trafton, Jodie Begoli, Edmon Peterson, Gregory D. Cyber Resilience and Intelligence Division Oak Ridge National Laboratory Oak RidgeTN United States Information Technology Services Division Oak Ridge National Laboratory Oak RidgeTN United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN United States Department of Biomedical Informatics Vanderbilt University NashvilleTN United States Program Evaluation and Resource Center Office of Mental Health and Suicide Prevention Department of Veterans Affairs United States Department of Medicine Stanford University School of Medicine StanfordCA United States Veterans Affairs Great Lakes Health Care System WestchesterIL United States Department of Electrical Engineering and Computer Science University of Tennessee Knoxville KnoxvilleTN United States

Background: Injection drug use (IDU) is a dangerous health behavior that increases mortality and morbidity. Identifying IDU early and initiating harm reduction interventions can benefit individuals at risk. However, extracting IDU behaviors from patients’ electronic health records (EHR) is difficult because there is no International Classification of Disease (ICD) code and the only place IDU information can be indicated is unstructured free-text clinical notes. Although natural language processing can efficiently extract this information from unstructured data, there are no validated tools. Methods: To address this gap in clinical information, we design and demonstrate a question-answering (QA) framework to extract information on IDU from clinical notes. Our framework involves two main steps: (1) generating a gold-standard QA dataset and (2) developing and testing the QA model. We utilize 2323 clinical notes of 1145 patients sourced from the VA Corporate Data Warehouse to construct the gold-standard dataset for developing and evaluating the QA model. We also demonstrate the QA model’s ability to extract IDU-related information on temporally out-of-distribution data. Results: Here we show that for a strict match between gold-standard and predicted answers, the QA model achieves 51.65% F1 score. For a relaxed match between the gold-standard and predicted answers, the QA model obtains 78.03% F1 score, along with 85.38% Precision and 79.02% Recall scores. Moreover, the QA model demonstrates consistent performance when subjected to temporally out-of-distribution data. Conclusions: Our study introduces a QA framework designed to extract IDU information from clinical notes, aiming to enhance the accurate and efficient detection of people who inject drugs, extract relevant information, and ultimately facilitate informed patient care. © 2023, CC BY-NC-ND.

关键词： Data warehouses

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Silica nanocone array as a template for fabricating a plasmon induced hot electron photodetector

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Photonics Research 2019年第3期7卷 294-299页

作者： ZHIQIANG YANG KANG DU FANFAN LU YANG PANG SHIJIA HUA XUETAO GAN WENDING ZHANG SOO JIN CHUA TING MEI Key Laboratory of Space Applied Physics and Chemistry Ministry of Education and Shaanxi Key Laboratory of Optical Information TechnologySchool of Science Northwestern Polytechnical University Department of Electrical and Computer Engineering National University of Singapore LEES Program Singapore-MIT Alliance for Research & Technology (SMART)

Plasmon induced hot electrons have attracted a great deal of interest as a novel route for photodetection and lightenergy harvesting. Herein, we report a hot electron photodetector in which a large array of nanocones deposited sequentially with aluminum, titanium dioxide, and gold films can be integrated functionally with nanophotonics and microelectronics. The device exhibits a strong photoelectric response at around 620 nm with a responsivity of 180 μA/W under short-circuit conditions with a significant increase under 1 V reverse bias to 360 μA/W. The increase in responsivity and a red shift in the peak value with increasing bias voltage indicate that the bias causes an increase in the hot electron tunneling effect. Our approach will be advantageous for the implementation of the proposed architecture on a vast variety of integrated optoelectronic devices.

关键词： Silica nanocone array plasmon induced hot electron photodetector

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Bulk-plasmon-mediated free-electron radiation beyond the conventional formation time

arXiv

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arXiv 2022年

作者： Tay, Fuyang Lin, Xiao Shi, Xihang Chen, Hongsheng Kaminer, Ido Zhang, Baile Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJUHangzhou Global Science and Technology Innovation Center College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley–Curl Institute Rice University HoustonTX77005 United States International Joint Innovation Center The Electromagnetics Academy Zhejiang University Zhejiang University Haining314400 China Department of Electrical Engineering Technion-Israel Institute of Technology Haifa32000 Israel Jinhua Institute of Zhejiang University Zhejiang University Jinhua321099 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Centre for Disruptive Photonic Technologies Nanyang Technological University 637371 Singapore

Free-electron radiation is a fundamental photon emission process that is induced by fast-moving electrons interacting with optical media. Historically, it has been understood that, just like any other photon emission process, free-electron radiation must be constrained within a finite time interval known as the "formation time", whose concept is applicable to both Cherenkov radiation and transition radiation, the two basic mechanisms describing radiation from a bulk medium and from an interface, respectively. Here we reveal an alternative mechanism of free-electron radiation far beyond the previously defined formation time. It occurs when a fast electron crosses the interface between vacuum and a plasmonic medium supporting bulk plasmons. While emitted continuously from the crossing point on the interface — thus consistent with the features of transition radiation — the extra radiation beyond the conventional formation time is supported by a long tail of bulk plasmons following the electron’s trajectory deep into the plasmonic medium. Such a plasmonic tail mixes surface and bulk effects, and provides a sustained channel for electron-interface interaction. These results also settle the historical debate in Ferrell radiation, regarding whether it is a surface or bulk effect, from transition radiation or plasmonic oscillation. Copyright © 2022, The Authors. All rights reserved.

关键词： Plasmonics

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The Effect of Several Kernel Functions to Financial Transaction Anomaly Detection Performance using One-Class SVM

The Effect of Several Kernel Functions to Financial Transact...

引用

International Congress on Applied information technology

作者： Yaya Heryadi Dandalina Doctor of Computer Science Program Bina Nusantara University Jakarta Indonesia Master of Information and Technology Program Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728158624

ISBN: (纸本)9781728158631

Anomalies in data become ubiquitous and often unavoidable. Despite it might be caused by various errors during the data collection or transportation, some anomalies potentially give important information such as indication of a new underlying process. The aim of anomaly detection task is to determine all such instances in the input dataset in a data-driven fashion. In the past decade, the proliferation of anomaly data in many domains have raised research interest resulted in a plethora of anomaly detection methods A vast number of previous study reports suggested that there is no single model will achieve the best performance for every dataset. This paper presents empiric results on the effect of several kernel functions to performance of One-Class Support Vector Machine (OC-SVM) as an anomaly detector model. The proposed model is tested using financial transactions of microfinance service dataset from an Indonesian Bank. The empiric results showed that OC-SVM model with Sigmoid and RBF kernels achieve the best statistically significant value of training, validation, and testing accuracies than the OC-SVM model with no-kernel, linear kernel and polynomial (degree 3,4,5,6) kernels.

关键词： Kernel Anomaly detection Training Testing Support vector machines Task analysis Feature extraction

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Evaluative Study Of Integration Of Clinic Management information System With Pcare BPJS of health Using COBIT 4.1 Approach

Evaluative Study Of Integration Of Clinic Management Informa...

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International Conference on computer Science, information technology, and Electrical Engineering

作者： Ely Mulyadi Kadek Yota Ernanda Aryanto I Made Candiasa Department of Information Technology Politeknik Negeri Jember Department of Computer Science of Postgraduate Program Universitas Pendidikan Ganesha

ISBN: (纸本)9781728134376

The aim purposed of this research is to evaluate clinical management information system called (E-CLINIC) which is integrated with the Primary Care (Pcare) application provided by Indonesia sosial healt insurance organization called BPJS Kesehatan to first level of health cares facility called as FKTP. This evaluation is intended to measure the maturity level on used of two integrated applications using COBIT 4.1 framework. The integration of the Clinic's management information system with PCare is considered to be the main resource that has strategic value to be able to manage information effectively and efficiently for the achievement of organizational goals. The results achieved have been running in accordance with the organization's business objectives, this can be seen from the level of maturity that reaches level 3 (Defined), which is a condition in which the organization has formal and written standard procedures that have been socialized to all levels of management and employees to be obeyed and run in daily activities.

关键词： E-Clinic MIS PCare BPJS COBIT Maturity Management information Systems Maturity maturity level DNA Integration integration health level health clinic Daily Activities

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Analysis of Application of the SAW, WP and TOPSIS Methods in Decision Support System Determining Scholarship Recipients at University

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Journal of Physics: Conference Series 2021年第1期1830卷

作者： Murni Marbun Muhammad Zarlis Zulkifli Nasution Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Teknik Informatika STMIK Pelita Nusantara Medan Indonesia

This research is an analysis of the application of the SAW, WP and TOPSIS methods to the support system for decision making at university. The types of scholarships provided are PPA education scholarships given by the Kementerian Riset, Teknologi dan Pendidikan Tinggi. The research variables are the attributes or criteria specified by the Directorate General of Learning and Student Affairs as contained in the 2018 Academic Achievement Improvement (PPA) guidebook. Decision Support Systems apply the classic FMADM method SAW, WP and TOPSIS. The results of this study are the application of the both methods of SAW and WP produce the same ranking and TOPSIS giving different rankings.

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, computer Retrospective Study

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