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

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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Solving Quadratic Assignment Problem with Fixed Assignment (QAPFA) using Branch and Bound Approach

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IOP Conference Series: Materials science and Engineering 2018年第1期300卷

作者： Sharifah Shuthairah Syed-Abdullah Syariza Abdul-Rahman Aida Mauziah Benjamin Antoni Wibowo Ku-Ruhana Ku-Mahamud School of Quantitative Sciences (SQS Computer Science Department-Binus Graduate Program Bina Nusantara University Anggrek Campus Jl. Kebon Jeruk Raya No. 27 Kebon Jeruk West Jakarta 11530 Indonesia School of Computing (SOC) College of Arts and Sciences Universiti Utara Malaysia 06010 Sintok Kedah Malaysia

Quadratic Assignment Problem (QAP) has been a very popular problem to be solved among researchers due to its practical applications. Several variants of QAP have been proposed by researchers in the past in order to reflect the real situations of QAP. One of the real problems of QAP is related with facilities which are required to be assigned to certain locations due to its function. In solving this problem, a fixed assignment has to be made thus allowing for the complexity of the problem to be reduced. Hence, this study introduces Quadratic Assignment Problem with Fixed Assignment (QAPFA) with the objective to minimize the assignment cost between the facility and location. This assignment takes into account the flow and distance between facility and location. QAPFA represents the real-world situation of the problem especially in dealing with specific requirement of some facilities to specific locations. Dataset of QAPFA is introduced and is solved using branch and bound approach. As for validation, the results of QAPFA are compared with QAP in terms of objective function and running time. The computational results show that the solution quality of QAPFA is lower when compared with the QAP, while the running time for QAPFA is lower than the QAP. Since the complexity of the problem is reduced by fixing the assignment, thus there is possibility that QAPFA has lower quality than QAP due to the fixed assignment. Nevertheless, in terms of running time QAPFA is better than QAP. It can be concluded that this problem reflect the real problem and practical to be used.

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Model of developing key performance indicator to increase the quality of education during the Covid-19 pandemic

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Journal of Physics: Conference Series 2021年第1期1832卷

作者： E Selviyanti W Sardjono M Mukhlis M Tohir M Maswar A Fariz Health Department Politeknik Negeri Jember Jember Jawa Timur Indonesia 68124 Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Faculty of Teacher Training and Education Islamic State Institute of Jember Jawa Timur INDONESIA Universitas Ibrahimy Situbondo Indonesia Computer Network Engineering SMK 3 Perguruan 'Cikini' Jakarta Indonesia 12640

Indonesia is one of the countries whose people are most affected by the 2019 corona virus (COVID-19). When the corona virus spreads faster, the Indonesian government imposed large-scale social restrictions in big cities to villages in Indonesia. With the changing situation in carrying out work activities during this pandemic, it will certainly affect the quality of organization in companies and the quality of education in schools and colleges. In order to identify all processes in teaching and learning activities that are running well or not, schools need to monitor and measure employee performance. Key performance indicators (KPIs) are generally used as benchmarks to determine how well a company's performance can be represented by employee performance. In this study, the key performance indicator preparation process was carried out through the stages of designing a questionnaire, distributing questionnaires to employees in educational institutions, conducting factor analysis and then developing a KPI model. The output is in the form of a KPI model that can be used as a reference in the formation of KPIs in educational institutions, namely Y = 5,360 + 1,380 X1-1, 068 X3.

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A Vehicle Forensics framework with Post-Quantum Cryptography and Blockchain

A Vehicle Forensics framework with Post-Quantum Cryptography...

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IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Chien-Lung Hsu Yi-Cheih Hsu Yu-Jen Shih Cheng-Wei Wu Fu-Hau Hsu Graduate Institute of Management Chang Gung University Taiwan Taoyuan R.O.C Department of Information Management Chang Gung University Taiwan Taoyuan R.O.C Healthy Aging Research Center Chang Gung University Taiwan Taoyuan R.O.C Department of Visual Communication Design Ming-Chi University of Technology Taiwan Taoyuan R.O.C Chang-Gung Memorial Hospital Taiwan Taoyuan R.O.C Department of Master of Science Degree Program in Innovation for Smart Medicine Chang Gung University Taiwan Taoyuan R.O.C Computer Science& Information Engineering National Central University Taiwan Taoyuan R.O.C Information Management Chang Gung University Taiwan Taoyuan R.O.C

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

With the recent rapid development of the Internet of Vehicles and autonomous driving technology, the demand for digital vehicle identification has also increased. Coupled with the gradual maturity of quantum technology, the Internet of Vehicles, which mainly uses wireless communication technology for data transmission, will face the threat of quantum computing and privacy issues. This research proposes the Vehicle Forensics Cloud System (VFCS), a framework combining post-quantum cryptography and blockchain technology to address these issues and provide a comprehensive solution for vehicle digital forensics.

关键词： Wireless communication Quantum computing Digital forensics Insurance Signal processing Blockchains Safety Autonomous vehicles Interoperability Internet of Vehicles

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FIELD SAMPLING OF RESIDUAL AVIATION GASOLINE IN SANDY SOIL

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GROUND WATER MONITORING AND REMEDIATION 1991年第2期11卷 107-120页

作者： OSTENDORF, DW LEACH, LE HINLEIN, ES XIE, YF 1 David W. Ostendorf is an associate professor in the Environmental Engineering Program of the Civil Engineering Department at the University of Massachusetts (Civil Engineering Department University of Massachusetts Amherst MA 01003). His research interests include unconfined aquifer contamination hazardous waste site remediation and analytical modeling of problems in environmental fluid mechanics. Dr. Ostendorf is a registered professional engineer in Massachusetts and a member of the American Geophysical Union American Society of Civil Engineers Soil Science Society of America Water Pollution Control Federation and Association of Environmental Engineering Professors as well as the National Water Well Association.2 Lowell E. Leach is an environmental engineer with the Robert S. Kerr Environmental Research Laboratory of the U.S. Environmental Protection Agency (RS Kerr Environmental Research Laboratory U.S. EPA P.O. Box 1198 Ada OK74820). Leach received his B.S. ingeological engineering at the University of Oklahoma in 1959 and has been a registered professional engineer in Oklahoma since 1966. With 29 years of experience in field applications of geological engineering he is responsible for developing methodology for sampling ground water and subsurface materials for the Robert S. Kerr Environmental Research Laboratory.3 Erich S. Hinlein is a research assistant in the Environmental Engineering Program of the Civil Engineering Department at the University of Massachusetts (Civil Engineering Department University of Massachusetts Amherst MA 01003). His research interests include ground water pollution hazardous waste site investigation and transport processes in unconfined aquifers. Hinlein graduated with a B.S. in electrical and computer engineering from the University of Massachusetts at Amherst in May 1985 and entered the Environmental Engineering Master's Degree Program in January 1989.4 Yuefeng Xie is a postdoctoral research associate in the Environmental Engineering Program of the Civil E

Two complementary field sampling methods for the determination of residual aviation gasoline content in the contaminated capillary fringe of a fine, uniform, sandy soil were investigated. The first method featured field extrusion of core barrels into pint-size Mason jars, while the second consisted of laboratory partitioning of intact stainless steel core sleeves. The barrel extrusion procedure involved jar headspace sampling in a nitrogen-filled glove box, which delineated the 0.7m thick residually contaminated interval for subsequent core sleeve withdrawal from adjacent boreholes. Soil samples removed from the Mason jars (in the field) and sleeve segments (in the laboratory) were subjected to methylene chloride extraction and gas chromatographic analysis to compare their aviation gasoline content. The barrel extrusion sampling method yielded a vertical profile with 0.10m resolution over an essentially continuous 5.0m interval from the ground surface to the water table. The sleeve segment alternative yielded a more resolved 0.03m vertical profile over a shorter 0.8m interval through the capillary fringe. The two methods delivered precise estimates of the vertically integrated mass of aviation gasoline at a given horizontal location, and a consistent view of the vertical profile as well. In the latter regard, a 0.2m thick lens of maximum contamination was found in the center of the capillary fringe, where moisture filled all voids smaller than the mean pore size. The maximum peak was resolved by the core sleeve data, but was partially obscured by the barrel extrusion observations, so that replicate barrels or a half-pint Mason jar size should be considered for data supporting vertical transport analyses in the absence of sleeve partitions.

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A computer-MODEL FOR SHIPBOARD ENERGY ANALYSIS

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NAVAL ENGINEERS JOURNAL 1984年第5期96卷 33-45页

作者： DETOLLA, JP FLEMING, JR Joseph DeTolla:is a ship systems engineer in the Ship Systems Engineering Division SEA 56D5 at the Naval Sea Systems Command. His career with the Navy started in 1965 at the Philadelphia Naval Shipyard Design Division. In 1971 he transferred to the Naval Ship Engineering Center. He has held positions as a fluid systems design engineer and auxiliary systems design integration engineer. Mr. DeTolla has worked extensively in the synthesis and analysis of total energy systems notably the design development of the FFG-7 class waste heat recovery system. He is NA VSEA's machinery group computer supported design project coordinator and is managing the development of a machinery systems data base load forecasting algorithms and design analysis computer programs. Mr. DeTolla has a bachelor of science degree in mechanical engineering from Drexel University and a master of engineering administration degree from George Washington University. He is a registered professional engineer in the District of Columbia and has written several technical papers on waste heat recovery and energy conservation. Jeffrey Fleming:is a senior project engineer in the Energy R&D Office at the David Taylor Naval Ship R&D Center. In his current position as group leader for the future fleet energy conservation portion of the Navy's energy R&D program he is responsible for the identification and development of advanced components and subsystems which will lead to reductions in the fossil fuel consumption of future ships. Over the past several years he has also directed the development and application of total energy computer analysis techniques for the assessment of conventional and advanced shipboard machinery concepts. Mr. Fleming is a 1971 graduate electrical engineer of Virginia Polytechnic Institute and received his MS in electrical engineering from Johns Hopkins University in 1975. Mr. Fleming has authored various technical publications and was the recipient of the Severn Technical Society's “Best Technical Paper of the Year” award in 1

In support of the Navy's efforts to improve the energy usage of future ships and thereby to reduce fleet operating costs, a large scale computer model has been developed by the David Taylor Naval Ship Research and Development Center (DTNSRDC) to analyze the performance of shipboard energy systems for applications other than nuclear or oil-fired steam propulsion plants. This paper discusses the applications and utility of this computer program as a performance analysis tool for design of ship machinery systems. The program is a simulation model that performs a complete thermodynamic analysis of a user-specified energy system. It offers considerable flexibility in analyzing a variety of propulsion, electrical, and auxiliary plant configurations through a component building block structure. Component subroutines that model the performance of shipboard equipment such as engines, boilers, generators, and compressors are available from the program library. Component subroutines are selected and linked in the program to model the desired machinery plant functional configurations. The operation of the defined shipboard energy system may then be simulated over a user-specified scenario of temperature, time, and load profiles. The program output furnishes information on component operating characteristics and fuel demands, which allows evaluation of the total system performance.

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Correction: Advancements in additive manufacturing for video laryngoscopes: a comprehensive scoping and technological review

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Systematic reviews 2024年第1期13卷 31页

作者： Ana Cristina Beitia Kraemer Moraes Chiara das Dores do Nascimento Everton Granemann Souza Mauricio Beitia Kraemer Mauricio Moraes Neftali Lenin Villarreal Carreno Evandro Piva Rafael Guerra Lund Pelotas Dental School Graduate Program in Dentistry Federal University of Pelotas Pelotas RS 96010‑560 Brazil. Master's Degree in Electronic and Computer Engineering Center for Social and Technological Sciences Catholic University of Pelotas Pelotas RS 96015‑560 Brazil. Faculty of Medicine São Francisco University Bragança Paulista SP 12916‑900 Brazil. Faculty of Medicine Federal University of Pelotas Pelotas RS 96010‑560 Brazil. Graduate Program in Materials Science and Engineering Technological Development Center Federal University of Pelotas Pelotas RS 96010‑610 Brazil. Pelotas Dental School Graduate Program in Dentistry Federal University of Pelotas Pelotas RS 96010‑560 Brazil. rafael.lund@***. Graduate Program in Materials Science and Engineering Technological Development Center Federal University of Pelotas Pelotas RS 96010‑610 Brazil. rafael.lund@***.

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The implementation of computer based instruction model on Gost Algorithm Cryptography Learning

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IOP Conference Series: Materials science and Engineering 2018年第1期420卷

作者： Tonni Limbong Janner Simarmata ARS Tambunan Parulian Siagian Joel Panjaitan Lestina Siagian Erbin Sitorus Marvin Frans Sakti Hutabarat Abba Suganda Girsang Katen Lumbanbatu Universitas Katolik Santo Thomas Jalan Setia Budi No. 479 F Tanjung Sari Tj. Sari Medan Selayang 20132 Medan - Indonesia Universitas Negeri Medan Jalan Willem Iskandar Pasar V Medan 20221 Medan - Indonesia Universitas HKBP Nommensen Jalan Sutomo No.4A Perintis Medan Timur 20235 Medan - Indonesia Akademi Teknik Deli Serdang Jl. Sultan Hasanuddin Tj. Garbus Satu Lubuk Pakam 20518 Deli Serdang – Indonesia Institut Sains dan Teknologi TD Pardede Jl. Dokter TD Pardede No. 21 Medan Baru 20152 Medan – Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia STMIK Kaputama Jl. Veteran No. 4A - 9A Tangsi 20714 Binjai - Indonesia

The objective of this study is to develop learning media by using the computer Based Instruction (CBI) model for GOST algorithm cryptographic material (Gosudarstvennyi Standard). Besides, the study serves to present learning using computer media, especially in the Informatics Engineering study program. The method used in this study uses the Research and Development (R & D) method. The results of this development research are learning media products in the form of tutorial CDs with the contents of the material: GOST Cryptographic Theory, Encryption Process and Decryption process using alphabet text data. Based on the results of the application and testing of the program, it can be concluded that this application is easy to use. Learning the Gost algorithm in the encoding method utilizing the computer Based Instructions (CBI) method helps to understand the material and facilitate the learning process.

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Identification of gene expression signatures for psoriasis classification using machine learning techniques

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Medicine in Omics 2021年 1卷

作者： Nguyen Quoc Khanh Le Duyen Thi Do Trinh-Trung-Duong Nguyen Ngan Thi Kim Nguyen Truong Nguyen Khanh Hung Nguyen Thi Thu Trang Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei City 106 Taiwan Research Center for Artificial Intelligence in Medicine Taipei Medical University Taipei City 106 Taiwan Graduate Institute of Biomedical Informatics Taipei Medical University Taipei City 106 Taiwan Department of Computer Science and Engineering Yuan Ze University Chung-Li 32003 Taiwan School of Nutrition and Health Sciences Taipei Medical University Taipei City 110 Taiwan International Master/Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei City 110 Taiwan Orthopedic and Trauma Department Cho Ray Hospital Ho Chi Minh City Viet Nam International PhD Program for Cell Therapy and Regeneration Medicine College of Medicine Taipei Medical University Taipei City 110 Taiwan

Psoriasis classification requires the accurate identification of the lesional types for the early and effective diagnosis and it is worth interesting that the normal and psoriasis cell tissues exhibit different gene expression. Therefore, gene expression data is an effective source for psoriasis classification and there is a challenge regarding the selection of suitable gene signatures for its purpose. In this present study, the gene expression-based microarray data were used and 35 expression features linked with psoriasis were utilized to feed into our machine learning model. Overall, the performance of our model based on 35 mentioned-above features surpassed that of other state-of-the-art classifiers with an average accuracy of 98.3%, recall of 98.6%, and precision of 98% in 5-fold cross-validation tests. We also validate our model on two different sets of psoriasis and the performance results are significant. These results have suggested that our 35 expression signatures have been identified as key features for classifying samples between lesion and non-lesion. More specifically, the expression levels of few genes i.e., FABP5 , TGM1 , or BCAR3 are discovered as newly potential biomarkers for psoriasis classification and treatment with high confidence. This study, therefore, could shed light on developing the prediction models for psoriasis classification and treatment using gene expression profiles.

关键词： Psoriasis classification Random forest Gene expression Feature selection Machine learning FABP5 Dermatology

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Mitigating errors in mobile-based dietary assessments: Effects of a data modification process on the validity of an image-assisted food and nutrition app

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Nutrition 2023年 116卷 112212-112212页

作者： Ho, Dang Khanh Ngan Chiu, Wan-Chun Kao, Jing-Wen Tseng, Hsiang-Tung Yao, Chih-Yuan Su, Hsiu-Yueh Wei, Pin-Hui Le, Nguyen Quoc Khanh Nguyen, Hung Trong Chang, Jung-Su School of Nutrition and Health Sciences College of Nutrition Taipei Medical University Taipei Taiwan Department of Nutrition Wan Fang Hospital Taipei Medical University Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Dietetics Taipei Medical University Hospital Taipei Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Research Center for Artificial Intelligence in Medicine Taipei Medical University Taipei Taiwan Translational Imaging Research Center Taipei Medical University Hospital Taipei Taiwan Department of Adult Nutrition Counselling National Institute of Nutrition Hanoi Viet Nam Department of Clinical Nutrition and Dietetics National Hospital of Endocrinology Hanoi Viet Nam Graduate Institute of Metabolism and Obesity Sciences College of Nutrition Taipei Medical University Taipei Taiwan Nutrition Research Center Taipei Medical University Hospital Taipei Taiwan Chinese Taipei Society for the Study of Obesity (CTSSO) Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

Objective: Mobile nutrition applications (apps) provide a simple way for individuals to record their diet, but the validity and inherent errors need to be carefully evaluated. The aim of this study was to assess the validity and clarify the sources of measurement errors of image-assisted mobile nutrition apps. Methods: This was a cross-sectional study with 98 students recruited from School of Nutrition and Health sciences, Taipei Medical University. A 3-d nutrient intake record by Formosa Food and Nutrient Recording App (FoodApp) was compared with a 24-h dietary recall (24-HDR). A two-stage data modification process, manual data cleaning, and reanalyzing of prepackaged foods were employed to address inherent errors. Nutrient intake levels obtained by the two methods were compared with the recommended daily intake (DRI), Taiwan. Paired t test, Spearman's correlation coefficients, and Bland–Altman plots were used to assess agreement between the FoodApp and 24-HDR. Results: Manual data cleaning identified 166 food coding errors (12%;stage 1), and 426 food codes with missing micronutrients (32%) were reanalyzed (stage 2). Positive linear trends were observed for total energy and micronutrient intake (all P_trend < 0.05) after the two stages of data modification, but not for dietary fat, carbohydrates, or vitamin D. There were no statistical differences in mean energy and macronutrient intake between the FoodApp and 24-HDR, and this agreement was confirmed by Bland–Altman plots. Spearman's correlation analyses showed strong to moderate correlations (r = 0.834 ∼ 0.386) between the two methods. Participants’ nutrient intake tended to be lower than the DRI, but no differences in proportions of adequacy/inadequacy for DRI values were observed between the two methods. Conclusions: Mitigating errors significantly improved the accuracy of the Formosa FoodApp, indicating its validity and reliability as a self-reporting mobile-based dietary assessment tool. Dietitians a

关键词： Food records Mobile application Mobile health Smartphone application

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