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OPTIMAL control FOR TWO-DIMENSIONAL LINEAR systemS WITH VARIABLE COEFFICIENTS

Asian Journal of control 2008年第4期1卷

作者： Jimshone Li Jason Sheng-Hong Tsai Leang-San Shieh Control System Laboratory Department of Electrical Engineering National Cheng Kung University Tainan 701 Taiwan R.O.C. Jim-Shone Li was born in Taiwan R. O.C. on April 20 1967. He received B.S. and M.S. degrees in Electrical Engineering from the Chung-Cheng Institute of Technology Taoyuan Taiwan R.O.C. in 1989 and 1993 respectively. He is currently a Ph.D. student at National Cheng-Kung University Tainan Taiwan R.O.C. His research interests include analysis and design of multidimensional systems and nonlinear system control. Department of Electrical and Computer Engineering University of Houston Houston TX 77004-4793 U.S.A.

An optimal control method for two-dimensional (2-D) linear systems with variable coefficients and free boundary conditions in Roesser's model is proposed in this paper. Based on Roesser's model, an equivalent general 1-D model of the 2-D system is presented, and the problem of minimizing a 2-D linear quadratic (LQ) cost function is solved for the case where complete state information is available. The solution is obtained by using the proposed dynamic programming in 1-D descriptor form to solve the Riccati equation and then arriving at the optimal control law and minimum cost. The proposed control methodology can be applied to discrete-time models of systems described by partial differential equations and can also be used in the field of signal processing.

关键词： Two-dimensional system optimal control Roesser's model Riccati equation

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An approach to the direct analysis of transient stability

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European Transactions on Electrical Power 1993年第3期3卷 241-248页

作者： Djukanovic, M.B. Sobajic, D.J. Pao, Y.‐H. Miodrag B. Djukanovic (1959) received his B.S. M.Sc. and Ph.D. degrees in Electrical Engineering from the University of Belgrade/Yugoslavia in 1982 1985 and 1992 respectively specializing in electric power systems. In 1984 he joined the Electrical Engineering Institute “Nikola Tesla” in Belgrade where he was working on the scientific studies in the field of power systems planning operation and control. In 1985 and 1990 he was appointed as a research scholar at the Royal Institute of Technology Stockholm and Case Western Reserve University Cleveland Ohio. His major in- terests are in the area of power system analysis steady-state and dynamic security and application of neural networks in electric power systems. (Electrical Engineering Institute “Nicola Tesla” ul. Koste Glavinica 8A YU-11000 Belgrad T +3811/2351-619 Fax + 3811/2351-823) Dejan J. Sobajic (1949) received the B.S.E.E. and the M.S.E.E. degrees from the University of Belgrade/Yugoslavia in 1972 and 1976 respectively and the Ph.D. degree from Case Western Reserve University Cleveland Ohio in 1988. At present he is with the Department of Electrical Engineering and Applied Physics Case Western Reserve University Cleveland. He is also the Engineering Manager of A1 WARE Inc. Cleveland. His current research interests include power system operation and control neuralnet systems and adaptive control. He is a member of the IEEE Task Force on Neural-Network Applications in Power Systems and of the IEEE Intelligent Controls Committee. He is the Chairman of the International Neural-Networks Society Special Interest Group on Power Engineering. (Case Western Reserve University Department of Electrial Engineering and Computer Sciences Glennan Building Ohio 44 106 USA T + 1216/421-2380 Fax +1216/368-8776) Yoh-Han Pao (1922) has been a Professor of Electrical Engineering and Computer Science at Case Westem Reserve University (CWRU) Cleveland Ohio since 1967. He has served as chairman of the University's Electrical Engineering Department

The Transient Energy Function (TEF) method has been intensely investigated over the last decade as a reliable and accurate tool for transient stability assessment of multimachine power systems. In this paper we propose the Potential Energy Boundary Surface (PEBS) based method for direct analysis of transient stability. The critical value of transient energy and the Critical Clearing Time (T_CCT) are evaluated without the need for successive calculation and memorization of the system kinetic and potential energy values along the sustained fault trajectory. The method is used for determination of output features in the training phase of the neural‐net based transient security assessment. The proposed approach is tested on the well‐known ten‐generator New England test system demonstrating the validity and accuracy of obtained results. Copyright © 1993 John Wiley & Sons, Ltd.

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Elements realization of software-algorithmic system optimization of technological processes based on adaptive methods

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IOP Conference Series: Materials Science and engineering 2020年第1期791卷

作者： A L Rutskov E V Sidorenko V L Burkovsky Ya P Fedorov Forecasting department of electricity balance power and loss analysis branch office OJSC «IDGC Centre» - «Voronezhenergo» Arzamaskaya 2 Voronezh 394033 Russia Novovoronezh representation of NR Corporation SA ESKM Moskovsky prospect 179 office building 3 Voronezh 394066 Russia Department of electric drive automation and control in an engineering system Vornezh State Technical University Moscow prospect 179 Voronezh 394066 Russia Corporate finance department and corporate management of the Financial University under the Government of the Russian Federation Leningradsky prospect 49 Mocow 125993 Russia

The paper examines a possibility to optimize complex technological processes of energy resources transfer and consumption. Notes the importance of unidentified and weakly formalized factors consideration, which influence quality of the described object classes functioning. Suggests use of fuzzy neural networks and controllers on their basis for implementation of technological processes optimization of energy resources transfer and consumption at the expense of its dynamic accuracy forecast improvement. Presents algorithmic realization, that later on configured in the MATLAB simulated environment. Quantitative and qualitative parameters, which characterize fuzzy neural controller's usage quality, were received. Later, software environment elements are being described, which constructed on the basis of the suggested adaptive approach for complex technological processes optimization. Points out a possibility to conduct comparative study, and also simulation modeling implementation by way of presented solutions.

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ASYNCHRONOUS TRANSFER MODE (ATM) OPERATION VIA SATELLITE - ISSUES, CHALLENGES AND RESOLUTIONS

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INTERNATIONAL JOURNAL OF SATELLITE COMMUNICATIONS 1994年第3期12卷 211-222页

作者： CHITRE, DM GOKHALE, DS HENDERSON, T LUNSFORD, JL MATHEWS, N COMSAT Laboratories 22300 Comsat Drive Clarksburg MD 20871 USA. Received his B.Sc. from the University of Bombay India an M.A. in mathematics from the University of Cambridge U.K. and a Ph.D. in physics from the University of Maryland. He is currently an Associate Executive Director of the Network Technology Division at COMSAT Laboratories. He has been involved in research and development activities in ISDN VSAT networks data communications and network systems and architectures. Prior to his current positions Dr. Chitre was a Principal Scientist in the Network Technology Division at COMSAT Laboratories. Dr. Chitre joined COMSAT Laboratories in 1980. He has made major contributions to the analysis and architecture of data communication ISDN and BISDN via satellite. Dr. Chitre directs and participates in the international and national standards activities in ISDN BISDN and data communication as they apply to satellite communication. He was Chairman of the Working Group on Protocols and Network Timing Function of the CCIR/CCITT Joint Ad Hoc Group on ISDN-Satellite Matters during 1990–1992. Currently he is the Chairman of the Working Group on New Technologies in the ITU Intersector Coordinating Group (ICG) on Satellite Matters. Dr. Chitre was a programme manager during 1990 and 1991 on a contract from INTELSAT on systems studies on satellite communications systems architectures for ISDN and broadband ISDN systems. Currently he is the technical manager of the DoD Contract on ATM via satellite demonstration and the programme manager for the INTELSAT contract on analysis and top-level specification of INTELSAT ISDN subnetworks and SDH compatible transport network. Department manager for ISDN/Data Communications in the Network Technology Division of COMSAT Laboratories. His responsibilities include managing the implementation of next generation telecommunication systems for fixed and mobile satellite systems. Current projects include the development of a high data rate gateway switch that provides for the

Key issues regarding the operation of the broadband integrated services digital network (BISDN) via satellite are presented herein. The specific issues, challenges, and their resolutions are detailed. In particular, the impact of error characteristics and propagation delay on the operation of BISDN via satellite is discussed. Solutions are presented for removing adverse effects and providing high-quality service to users of BISDN via satellite.

关键词： ATM BISDN

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TEST AND EVALUATION STATISTICAL PLANNING, EXECUTION, AND analysis

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NAVAL ENGINEERS JOURNAL 1974年第4期86卷 41-50页

作者： ORLEANS, BS HIGDON, HE The author holds a BA degree in Mathematics and Statistics from Hunter College and a MA degree in Statistics from the Columbia University Gaduate School of Business. She has also completed graduate courses at Columbia George Washington and American Universities. Prior to her present position she was employed by the International Statistical Bureau as an Economic Statistician the Educational Testing Service as a Research Assistant the U.S. Air Force Human Resources Research Laboratory as an Aviation Psychologist and Head of the Statistics Section and CNO Aviation Plans and Programs as a Mathematical Statistician. At present she is Head Statistical Engineering Branch Naval Ship Systems Command covering areas of Quality Control Reliability and Design and Analysis of Experiments. In addition she has taught a number of sessions of a course in “Introduction of Statistical Inference” for the Navy the Laboratories and the Army. The author received his BS degree in Statistics and Mathematics from the University of Alabama and has completed graduate courses at the University of Alabama and Florida State University. He was employed out of college as a Statistician at the Naval Coastal System Laboratory (formerly the Navy Mine Defense Laboratory). His present position at the Laboratory is that of Head Statistical Design and Analysis Section in the Technical Support Department. Work experience in his position has covered a variety of problems in Diving and Salvage Swimmer Defense Mine Countermeasures and Acoustic Warfare. In addition he has served as Assistant Technical Test Director for two CNO projects and as Technical Test Director for another.

The first part of the paper deals with the need for statistical planning of a test. The general approach to such planning, starting with the dialogue between the subject matter (Test Director) and the Statistician before any data are collected, is discussed. Various specific principles which are inherent in such test planning are defined and explained, and the type of analyses inherent in various plans are discussed. The second half of the paper provides the details on specific test plans which have been used for actual technical evaluations. The application of statistical designs in three separate tests are described, explaining the reasons for the specific designs, including a discussion of the analysis, if a completed test, or the proposed analysis. These three evaluations are Underwater Communication Equipment; Swimmer Hand-Held Sonar Equipment; and the Submarine Acoustic Warfare system (SAWS). The particular designs used in the foregoing tests which are discussed are Randomized Blocks and Sequential Testing.

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Simple robust adaptive control of static VAR compensator

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European Transactions on Electrical Power 1993年第6期3卷 429-435页

作者： Machowski, J. Nelles, D. Jan Machowski (1950) received the M.Sc. degree in Electrical Faculty of Warsaw University of Technology in 1974. For two years he was employed in the Power Dispatching Centre in Warsaw/Poland. Later after gaining some field experience in several power plants he did a postgraduate study at Warsaw University of Technology where he received his Ph.D. degree in 1979. In the same year he joined the Electrical Faculty of Warsaw University of Technology where he is presently employed as a professor and head of the power system protection and control group. His areas of interest are power systems analysis protection and control. Since October 1989 he has been with Kaiserslautem University/Germany. (Univ. Kaiserslautern FB Elektrotechnik. P.O. Box 30 49 67618 Kaiserslautem T +4963/205-3431 Fax +49631/205-21 68) Dieter Nelles (1939). VDE received the Dipl.-Ing. degree in electrical engineering in 1966 from the Technical University in Darmstadt/Germany and the Dr.-Ing. degree in 1973 from the Technical University of Berlird/Germany. Since 1966 he has been with the Technical and Science Department of AEG-Telefunken (Frankfurt/M Germany) as a research engineer and since 1972 as the head of this department. In 1982 he joined the Electical Faculty of Kaiserslautem University where he presently is il professor of eletrical engineering and head of the Electrical Energy Supply Group. His special areas of interest are powersystem stability. power system protection and power system control. He is a member of VDE and serves as the chairman of Synchronous Machines Regulation and Excitation Systems Committee. (Univ. Kaisers-lautem FB Elektrotechnik. P.O. Box 304967618 Kaiserslautem T +49631/205-28 46 Fax +49631/205-21 68)

A study of power system transient stability enhancement through effective use of static VAR compensator is presented. It is shown that optimal state‐variable control can be approximately realized as a simple closed‐loop control based on locally measurable electric quantities. In order to make this regulation more effective and insensitive to the changes of the network parameters and loading condition it is proposed to use simple adaptive control with dynamic gain tuned by additional control loops. Tests done for two‐machine and multi‐machine systems have confirmed the validity and robustness of the proposed control method. Copyright © 1993 John Wiley & Sons, Ltd.

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

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The Lancet 2023年第10397期402卷 203-234页

作者： Ong, Kanyin Liane Stafford, Lauryn K. McLaughlin, Susan A. Boyko, Edward J. Vollset, Stein Emil Smith, Amanda E. Dalton, Bronte E. Duprey, Joe Cruz, Jessica A. Hagins, Hailey Lindstedt, Paulina A. Aali, Amirali Abate, Yohannes Habtegiorgis Abate, Melsew Dagne Abbasian, Mohammadreza Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Mohsen ElHafeez, Samar Abd Abd-Rabu, Rami Abdulah, Deldar Morad Abdullah, Abu Yousuf Md Abedi, Vida Abidi, Hassan Aboagye, Richard Gyan Abolhassani, Hassan Abu-Gharbieh, Eman Abu-Zaid, Ahmed Adane, Tigist Demssew Adane, Denberu Eshetie Addo, Isaac Yeboah Adegboye, Oyelola A. Adekanmbi, Victor Adepoju, Abiola Victor Adnani, Qorinah Estiningtyas Sakilah Afolabi, Rotimi Felix Agarwal, Gina Aghdam, Zahra Babaei Agudelo-Botero, Marcela Arriagada, Constanza Elizabeth Aguilera Agyemang-Duah, Williams Ahinkorah, Bright Opoku Ahmad, Danish Ahmad, Rizwan Ahmad, Sajjad Ahmad, Aqeel Ahmadi, Ali Ahmadi, Keivan Ahmed, Ali Ahmed, Luai A. Ahmed, Syed Anees Ajami, Marjan Akinyemi, Rufus Olusola Al Hamad, Hanadi Al Hasan, Syed Mahfuz AL-Ahdal, Tareq Mohammed Ali Alalwan, Tariq A. Al-Aly, Ziyad AlBataineh, Mohammad T. Alcalde-Rabanal, Jacqueline Elizabeth Alemi, Sharifullah Ali, Hassam Alinia, Tahereh Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Amare, Firehiwot Ameyaw, Edward Kwabena Amiri, Sohrab Amusa, Ganiyu Adeniyi Andrei, Catalina Liliana Anjana, Ranjit Mohan Ansar, Adnan Ansari, Golnoosh Ansari-Moghaddam, Alireza Anyasodor, Anayochukwu Edward Arabloo, Jalal Aravkin, Aleksandr Y. Areda, Demelash Arifin, Hidayat Arkew, Mesay Armocida, Benedetta Arnlov, Johan Artamonov, Anton A. Arulappan, Judie Aruleba, Raphael Taiwo Arumugam, Ashokan Aryan, Zahra Asemu, Mulu Tiruneh Asghari-Jafarabadi, Mohammad Askari, Elaheh Asmelash, Daniel Astell-Burt, Thomas Athar, Mohammad Athari, Seyyed Shamsadin Atout, Maha Moh'd Wahbi Avila-Burgos, Leticia Awaisu, Ahmed Azadnajafabad, Sina Darshan, B.B. Babamohamadi, Hassan Badar, Muhammad Badawi, Alaa Badiye, Ashish D. Baghcheghi, Nayereh Baghe Institute for Health Metrics and Evaluation School of Medicine General Medicine Service Department of Veterans Affairs Seattle WA United States Department of Health Metrics Sciences School of Medicine Faculty of Medicine France Department of Clinical Governance and Quality Improvement Aleta Wondo Hospital Aleta Wondo Ethiopia Department of Nursing Woldia University Woldia Ethiopia Department of Nursing Department of Orthopedic Surgery Orthopaedic Surgery Social Determinants of Health Research Center Non-communicable Diseases Research Center Epidemiology Department Evidence-Based Practice Center Community and Maternity Nursing Unit University of Duhok Duhok Iraq School of Planning Faculty of Environment Department of Public Health Sciences Penn State College of Medicine Pennsylvania State University Hershey PA United States Biocomplexity Institute Virginia Tech Blacksburg VA United States College of Medicine Department of Public Health Laboratory Technology Sciences Department Department of Family and Community Health University of Health and Allied Sciences Ho Ghana Research Center for Immunodeficiencies Department of Biosciences and Nutrition Karolinska University Hospital Huddinge Sweden Clinical Sciences Department Department of Surgery Department of Surgery Department of Obstetrics & Gynecology College of Graduate Health Sciences University of Tennessee Memphis TN United States Department of Obstetrics & Gynecology Department of Clinical and Psychosocial Epidemiology Department of Anesthesia and Critical Care Centre for Social Research in Health Quality and Systems Performance Unit Cancer Institute NSW Sydney NSW Australia Department of Public Health and Tropical Medicine HIV and Infectious Diseases Department Jhpiego Abuja Nigeria Adolescent Research and Care Department Adolescent Friendly Research Initiative and Care Ado Ekiti Nigeria Department of Epidemiology Department of Epidemiology and Medical Statistics Department of Family Medicine McMaster University

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined;these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs;defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims;type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative r

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Developing a prototype concurrent design tool for composite topside structures

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NAVAL ENGINEERS JOURNAL 1997年第3期109卷 279-290页

作者： Dirlik, S Hambric, S Azarm, S Marquardt, M Hellman, A Bartlett, S Castelli, V Steve Dirlik:began his career at the Naval Surface Warfare Center Carderock Division in 1981 as an aerospace engineer co-op student. He completed his bachelor of science degree in aeropace and ocean engineering from Virginia Polytechnic Institute and State University in 1985 and his master of science degree in aerospace engineering from the University of Maryland in 1990. Mr. Dirlik recently completed a master of science program in applied physics at The Johns Hopins University and currently works in the Radar Cross Section and Target Physics Branch of the Signatures Directorate at the Naval Surface Warfare Center Corderoke Division. He has worked on Navy low observable programs since 1990. Stephen Hambric:is a research associate at the Applied Research Laboratory at The Pennsylvania State University. He received his B. S. and M.S. degree in mechanical engineering from Virginia Polytechnic Institute and State University and his D. Sc. in mechnical engineering from the George Washington University. He has worked on several computer aided multidiscikplinary design and optimization projects over the years including an automated propeller design system and a structural acoustic optimization capability. Dr. Shpour Azarm:is currently working as an associate professor with the Design and Manufacturing Group of the Department of Mechanical Engineering at the University of maryland at College Park. Dr Azarm's expertise is in the areas of optimization-based designed and concurrent design and optimization of multidisciplinary systems. He was a consultant at Black & Decker Corporation (summer 1996) and worked as a Navy senior summer faculty fellow (summer 1995) and a NASA summer faculty fellow (summer 1994). He was a visiting scientist at NASA Langley Research Center for Multidisciplinary Analysis and Applied Structural Optimzatiom at the University of Siegen in Germany (spring 1992) and the Design Institute of the Technical University of Denmark (summer 1990). Dr Azarm was an associate technical editor of the ASME Jour

A prototype concurrent engineering tool has been developed for the preliminary design of composite topside structures for modern navy warships. This tool, named GELS for the Concurrent engineering of Layered Structures, provides designers with an immediate assessment of the impacts of their decisions on several disciplines which are important to the performance of a modern naval topside structure, including electromagnetic interference effects (EMI), radar cross section (RCS), structural integrity, cost, and weight. Preliminary analysis modules in each of these disciplines are integrated to operate from a common set of design variables and a common materials database. Performance in each discipline and an overall fitness function for the concept are then evaluated. A graphical user interface (GUI) is used to define requirements and to display the results from the technical analysis modules. Optimization techniques, including feasible sequential quadratic programming (FSQP) and exhaustive search are used to modify the design variables to satisfy all requirements simultaneously. The development of this tool, the technical modules, and their integration are discussed noting the decisions and compromises required to develop and integrate the modules into a prototype conceptual design tool.

关键词： Warships

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