检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Ren, Yingying Li, Qiuli Guo, Yangyang Pedrycz, Witold Xing, Lining Liu, Anfeng Song, Yanjie School of Computer Electronics and Information Guangxi University Nanning China Guangxi Key Laboratory of Multimedia Communications and Network Technology China Key Laboratory of Parallel Distributed and Intelligent Computing Guangxi University China School of Systems Science Beijing Jiaotong University Beijing China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Systems Research Institute Polish Academy of Sciences Poland Faculty of Engineering and Natural Sciences Department of Computer Engineering Sariyer Istanbul Turkey School of Electronic Engineering Xidian University Xian China School of Electronic Engineering Central South University Changsha China National Engineering Research Center of Maritime Navigation System Dalian Maritime University Dalian China

With the rapid development of the satellite industry, the information transmission network based on communication satellites has gradually become a major and important part of the future satellite ground integration network. However, the low transmission efficiency of the satellite data relay back mission has become a problem that is currently constraining the construction of the system and needs to be solved urgently. Effectively planning the task of satellite ground networking by reasonably scheduling resources is crucial for the efficient transmission of task data. In this paper, we hope to provide a task execution scheme that maximizes the profit of the networking task for satellite ground network planning considering feeding mode (SGNPFM). To solve the SGNPFM problem, a mixed-integer planning model with the objective of maximizing the gain of the link-building task is constructed, which considers various constraints of the satellite in the feed-switching mode. Based on the problem characteristics, we propose a distance similarity-based genetic optimization algorithm (DSGA), which considers the state characteristics between the tasks and introduces a weighted Euclidean distance method to determine the similarity between the tasks. To obtain more high-quality solutions, different similarity evaluation methods are designed to assist the algorithm in intelligently screening individuals. The DSGAalso uses an adaptive crossover strategy based on similarity mechanism, which guides the algorithm to achieve efficient population search. In addition, a task scheduling algorithm considering the feed-switching mode is designed for decoding the algorithm to generate a highquality scheme. The results of simulation experiments show that the DSGA can effectively solve the SGNPFM problem. Compared to other algorithms, the proposed algorithm not only obtains higher quality planning schemes but also has faster algorithm convergence speed. The proposed algorithm improves data trans

关键词： Profitability

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Foundational Competencies and Responsibilities of a Research Software Engineer

arXiv

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arXiv 2023年

作者： Goth, Florian Alves, Renato Braun, Matthias Castro, Leyla Jael Chourdakis, Gerasimos Christ, Simon Cohen, Jeremy Druskat, Stephan Erxleben, Fredo Grad, Jean-Noël Hagdorn, Magnus Hodges, Toby Juckeland, Guido Kempf, Dominic Lamprecht, Anna-Lena Linxweiler, Jan Löffler, Frank Martone, Michele Schwarzmeier, Moritz Seibold, Heidi Thiele, Jan Philipp Waldow, Harald von Wittke, Samantha Institute for Theoretical Physics and Astrophysics University of Würzburg Germany European Molecular Biology Laboratory Heidelberg Germany Cluster of Excellence IntCDC University of Stuttgart Germany ZB MED Information Centre for Life Sciences Cologne Germany School of Computation Information and Technology Technical University of Munich Garching Germany Institute for Parallel and Distributed Systems University of Stuttgart Stuttgart Germany Leibniz University Hannover Department of Cell Biology and Biophysics Computational Biology Germany Imperial College London London United Kingdom Institute for Software Technology Berlin Germany Humboldt-Universität zu Berlin Department of Computer Science Berlin Germany Helmholtz-Zentrum Dresden-Rossendorf Germany Institute for Computational Physics University of Stuttgart Germany Geschäftsbereich IT Charité Universitätsmedizin Berlin Germany The Carpentries United States Heidelberg University Scientific Software Center Germany Institute of Computer Science University of Potsdam Germany Technische Universität Braunschweig Germany Michael Stifel Center Jena Friedrich Schiller University Jena Germany Leibniz Supercomputing Centre Garching Germany Mathematical Modeling and Analysis TU Darmstadt Germany IGDORE Munich Germany Weierstrass Institute Berlin Germany Leibniz University Hannover Institute of Applied Mathematics Scientific Computing Hannover Germany Johann Heinrich von Thünen Institute Centre for Information Management Germany

The term Research Software Engineer, or RSE, emerged a little over 10 years ago as a way to represent individuals working in the research community but focusing on software development. The term has been widely adopted and there are a number of high-level definitions of what an RSE is. However, the roles of RSEs vary depending on the institutional context they work in. At one end of the spectrum, RSE roles may look similar to a traditional research role. At the other extreme, they resemble that of a software engineer in industry. Most RSE roles inhabit the space between these two extremes. Therefore, providing a straightforward, comprehensive definition of what an RSE does and what experience, skills and competencies are required to become one is challenging. In this community paper we define the broad notion of what an RSE is, explore the different types of work they undertake, and define a list of foundational competencies as well as values that outline the general profile of an RSE. Further research and training can build upon this foundation of skills and focus on various aspects in greater detail. We expect that graduates and practitioners will have a larger and more diverse set of skills than outlined here. On this basis, we elaborate on the progression of these skills along different dimensions. We look at specific types of RSE roles, propose recommendations for organisations, and give examples of future specialisations. An appendix details how existing curricula fit into this framework. © 2023, CC BY.

关键词： Computer aided software engineering

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QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge

arXiv

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arXiv 2024年

作者： Li, Hongwei Bran Navarro, Fernando Ezhov, Ivan Bayat, Amirhossein Das, Dhritiman Kofler, Florian Shit, Suprosanna Waldmannstetter, Diana Paetzold, Johannes C. Hu, Xiaobin Wiestler, Benedikt Zimmer, Lucas Amiranashvili, Tamaz Prabhakar, Chinmay Berger, Christoph Weidner, Jonas Alonso-Basanta, Michelle Rashid, Arif Baid, Ujjwal Adel, Wesam Alis, Deniz Baheti, Bhakti Bai, Yingbin Bhat, Ishaan Cetindag, Sabri Can Chen, Wenting Cheng, Li Dutande, Prasad Dular, Lara Elattar, Mustafa A. Feng, Ming Gao, Shengbo Huisman, Henkjan Hu, Weifeng Innani, Shubham Ji, Wei Karimi, Davood Kuijf, Hugo J. Kwak, Jin Tae Le, Hoang Long Li, Xiang Lin, Huiyan Liu, Tongliang Ma, Jun Ma, Kai Ma, Ting Oksuz, Ilkay Holland, Robbie Oliveira, Arlindo L. Pal, Jimut Bahan Pei, Xuan Qiao, Maoying Saha, Anindo Selvan, Raghavendra Shen, Linlin Silva, Joao Lourenco Spiclin, Ziga Talbar, Sanjay Wang, Dadong Wang, Wei Wang, Xiong Wang, Yin Xi, Ruiling Xu, Kele Yang, Yanwu Yergin, Mert Yu, Shuang Zeng, Lingxi Zhang, YingLin Zhao, Jiachen Zheng, Yefeng Zukovec, Martin Do, Richard Becker, Anton Simpson, Amber Konukoglu, Ender Jakab, Andras Bakas, Spyridon Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School United States Department of Quantitative Biomedicine University of Zurich Switzerland University Children’s Hospital Zurich University of Zurich Switzerland Department of Radioncology and Radiation Theraphy Klinikum rechts der Isar Technical University of Munich Germany Department of Information Technology and Electrical Engineering ETH-Zurich Switzerland Department of Radiology Memorial Sloan Kettering Cancer Center New York City United States Department of Biomedical and Molecular Sciences Queen’s University Canada TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany McGovern Institute Massachusetts Institute of Technology United States Institute for Diagnostic and Interventional Radiology Unveristy Zurich Hospital Switzerland BioMedIA Imperial College London United Kingdom Department of Radiation Oncology University of Pennsylvania PA United States University of Pennsylvania PA United States Department of Radiation Oncology Winship Cancer Institute of Emory University Georgia United States Nile University Cairo Egypt Department of Medical Sciences Acibadem University Istanbul Turkey Shri Guru Gobind Singhji Institute of Engineering and Technology Maharashtra Nanded India Trustworthy Machine Learning Lab University of Sydney Australia Image Sciences Institute University Medical Center Utrecht Netherlands Computer Engineering Department Istanbul Technical University Istanbul Turkey School of Computer Science Shenzhen University Shenzhen China University of Alberta United States University of Ljubljana Faculty of Electrical Engineering Ljubljana Slovenia Tongji University Shanghai China OPPO Research Institute Shanghai China School of Biological and Medical Engineering Beihang University Beijing China Harvard Medical School Boston

Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a significant challenge in achieving consistent and reliable image segmentation. This variability not only reflects the inherent complexity and subjective nature of medical image interpretation but also directly impacts the development and evaluation of automated segmentation algorithms. Accurately modeling and quantifying this variability is essential for enhancing the robustness and clinical applicability of these algorithms. We report the set-up and summarize the benchmark results of the Quantification of Uncertainties in Biomedical Image Quantification Challenge (QUBIQ), which was organized in conjunction with International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2020 and 2021. The challenge focuses on the uncertainty quantification of medical image segmentation which considers the omnipresence of inter-rater variability in imaging datasets. The large collection of images with multi-rater annotations features various modalities such as MRI and CT;various organs such as the brain, prostate, kidney, and pancreas;and different image dimensions 2D-vs-3D. A total of 24 teams submitted different solutions to the problem, combining various baseline models, Bayesian neural networks, and ensemble model techniques. The obtained results indicate the importance of the ensemble models, as well as the need for further research to develop efficient 3D methods for uncertainty quantification methods in 3D segmentation tasks. © 2024, CC BY-NC-ND.

关键词： Image segmentation

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parallel AND distributed TLM COMPUTATION WITH SIGNAL-processing FOR ELECTROMAGNETIC-FIELD MODELING

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INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 1995年第3-4期8卷 169-185页

作者： SO, PPM ESWARAPPA, C HOEFER, WJR NSERC/MPR Teltech Research Chair in RF Engineering Department of Electrical and Computer Engineering University of Victoria Victoria British Columbia V8W 3P6 Canada Poman So received his B.Sc. degree in computer science and physics from the University of Toronto Toronto Onatario Canada in 1985. He obtained his B.A. Sc. and M.A.Sc. degrees in electrical engineering (summa cum laude) from the University of Ottawa Ottawa Ontario Canada in 1987 and 1989 respectively. Mr So was a research engineer in the University of Ottawa from January 1989 to October 1991 his research interests included CAD techniques of microwave circuits and numerical methods for electromagnetic wave modelling. He specialized in the development of electromagnetic engineering CAD software and successfully implemented a number of electromagnetic wave simulators based on the two-dimensional and three-dimensional transmission-line matrix methods. From August 1990 to February 1991 he accompanied Professor W. J. R. Hoefer to Rome Italy and Sophia Antiopolas France. During that time he implemented a parallel version of the 3D-TLM simulator for the CM-2 Connection Machine using C-Star and X Windows Library. He is a research engineer and a Ph.D. student at the University of Victoria Victoria British Columbia Canada. He ported the 2D- and 3D-TLM simulators to DECmpp 1200 massively parallel computer using MPL C and C++. He also combined OSA90/hope a commercially available microwave CAD program with a 2D-TLM simulation module for geometry optimization using the Datapipe technique of OSA90/hope. Recently he has developed a distributed client-server computing technique for the TLM method this technique could accelerate the TLM simulation by more than an order of magnitude. Channabasappa Eswarappa received the M.Tech. degree in electrical engineering from the Indian Institute of Technology Kanpur India in 1983 and Ph. D. degree from the University of Ottawa Canada in 1990. He worked as an Assistant Executive Engineer and later as

This paper describes the implementation of transmission-line matrix (TLM) method algorithms on a massively parallel computer (DECmpp 12000), the technique of distributed computing in the UNIX environment, and the combination of TLM analysis with Prony's method as well as with autoregressive moving average (ARMA) digital signal processing for electromagnetic field modelling. By combining these advanced computation techniques, typical electromagnetic field modelling of microwave structures by TLM analysis can be accelerated by a few orders of magnitude.

关键词： Mathematical models

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Multiagent fault‐diagnosis expert system in power systems

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European Transactions on Electrical Power 1995年第5期5卷 341-347页

作者： Wang, J.P. Trécat, J. Dr. Jianping Wang is a doctor fellow in the Faculte Polytechnique de Mons in Belgium. His current research field is parallel processing applications in power systems. Dr. Wang obtained his BS degree from Southwest Jiaotong University in P.R. Chinain 1982. From 1982 to 1990 he was appointed as an assistant lecturer. lecturer and associate professor respectively in the electrical engineering department of Southwest Jiaotong University. He obtained his Ph.D in the FacultC Polytechnique de Mons in July of 1993. (BD Dolez 3 1 FPMS B-7000 Mons Belgium T +32-65/37 41 87 Fax +32-65/37 43 00) Professor J. Trécat is a director in the power system laboratory in the Faculty Polytechnique de Mons. He obtained his Ph.D in the University of Manchester Institute of Science and Technology(UM1ST) in U.K. in 1970. He has been working in the fields of power system automation artificial intelligence application and computer vision in the Facult6 Polytechnique de Mons since 1970. He is a senior member of IEEE and he has made much contribution both in electrical engineering education and research. (BD Dolez 3 I FPMS B-7000 Mons T +32-651374185. Fax +32-6513743 00)

In order to solve the speed problem and shallow reasoning problem met in current research in fault diagnosis expert system, this paper presents a model based parallel fault diagnosis expert system for energy management systems (EMS). The Petri net model, which corresponds to the relationship between power system components and their protection systems, has been used for the inference in fault diagnosis. A multiagent parallel processing expert system, which is based on five transputers in Sun workstation, has been built for fault diagnosis purposes. The test results show that this expert system is not only fast but also has better performances. Copyright © 1995 John Wiley & Sons, Ltd.

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The Hi-GAL compact source catalogue. I : The physical properties of the clumps in the inner Galaxy (−71.0◦ 67.0◦)

arXiv

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arXiv 2017年

作者： Elia, Davide Molinari, S. Schisano, E. Pestalozzi, M. Pezzuto, S. Merello, M. Noriega-Crespo, A. Moore, T.J.T. Russeil, D. Mottram, J.C. Paladini, R. Strafella, F. Benedettini, M. Bernard, J.P. Di Giorgio, A. Eden, D.J. Fukui, Y. Plume, R. Bally, J. Martin, P.G. Ragan, S.E. Jaffa, S.E. Motte, F. Olmi, L. Schneider, N. Testi, L. Wyrowski, F. Zavagno, A. Calzoletti, L. Faustini, F. Natoli, P. Palmerim, P. Piacentini, F. Piazzo, L. Pilbratt, G.L. Polychroni, D. Baldeschi, A. Beltrán, M.T. Billot, N. Cambrésy, L. Cesaroni, R. García-Lario, P. Hoare, M.G. Huang, M. Joncas, G. Liu, S.J. Maiolo, B.M.T. Marsh, K.A. Maruccia, Y. Mège, P. Peretto, N. Rygl, K.L.J. Schilke, P. Thompson, M.A. Traficante, A. Umana, G. Veneziani, M. Ward-Thompson, D. Whitworth, A.P. Arab, H. Bandieramonte, M. Becciani, U. Brescia, M. Buemi, C. Bufano, F. Butora, R. Cavuoti, S. Costa, A. Fiorellino, E. Hajnal, A. Hayakawa, T. Kacsuk, P. Leto, P. Li Causi, G. Marchili, N. Martinavarro-Armengol, S. Mercurio, A. Molinaro, M. Riccio, G. Sano, H. Sciacca, E. Tachihara, K. Torii, K. Trigilio, C. Vitello, F. Yamamoto, H. INAF-IAPS via del Fosso del Cavaliere 100 Roma00133 Italy Space Telescope Science Institute 3700 San Martin Dr. BaltimoreMD21218 United States Astrophysics Research Institute Liverpool John Moores University Liverpool Science Park Ic2 146 Brownlow Hill LiverpoolL3 5RF United Kingdom Aix Marseille Univ. CNRS LAM Laboratoire d’Astrophysique de Marseille Marseille France Max-Planck Institute for Astronomy Königstuhl 17 HeidelbergD-69117 Germany Infrared Processing Analysis Center California Institute of Technology 770 South Wilson Ave. PasadenaCA91125 United States Dipartimento di Matematica e Fisica Università del Salento Lecce73100 Italy CNRS IRAP 9 Av. colonel Roche BP 44346 Toulouse cedex 4F-31028 France Université de Toulouse UPS-OMP IRAP Toulouse cedex 4F-31028 France Department of Physics Nagoya University Chikusa-ku Nagoya Aichi464-8601 Japan Department of Physics & Astronomy University of Calgary ABT2N 1N4 Canada Center for Astrophysics and Space Astronomy University of Colorado BoulderCO80309 United States Canadian Institute for Theoretical Astrophysics University of Toronto McLennan Physical Laboratories 60 St. George Street TorontoON Canada School of Physics and Astronomy University of Leeds LeedsLS2 9JT United Kingdom School of Physics and Astronomy Cardiff University Cardiff WalesCF24 3AA United Kingdom IPAG University Grenoble Alpes Grenoble38000 France AIM Paris-Saclay CEA/IRFU - CNRS INSU - Univ. Paris Diderot Service d’Astrophysique CEA-Saclay Gif-surYvette Cedex91191 France INAF Osservatorio Astrofisico di Arcetri Largo E. Fermi 5 Firenze50125 Italy I. Physik. Institut University of Cologne Zülpicher Strasse Köln50937 Germany European Southern Observatory Karl Schwarzschild str. 2 Garching85748 Germany Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 Bonn53121 Germany ASI Science Data centre 00044 Frascati Roma Italy ESA/ESAC PO Box 78 Villanueva de la Cañada Madrid28691 Spain

Hi-GAL is a large-scale survey of the Galactic plane, performed with Herschel in five infrared continuum bands between 70 and 500 µm. We present a band-merged catalogue of spatially matched sources and their properties derived from fits to the spectral energy distributions (SEDs) and heliocentric distances, based on the photometric catalogs presented in Molinari et al. (2016a), covering the portion of Galactic plane −71.0◦ 67.0◦. The band-merged catalogue contains 100922 sources with a regular SED, 24584 of which show a 70 µm counterpart and are thus considered proto-stellar, while the remainder are considered starless. Thanks to this huge number of sources, we are able to carry out a preliminary analysis of early stages of star formation, identifying the conditions that characterise different evolutionary phases on a statistically significant basis. We calculate surface densities to investigate the gravitational stability of clumps and their potential to form massive stars. We also explore evolutionary status metrics such as the dust temperature, luminosity and bolometric temperature, finding that these are higher in proto-stellar sources compared to pre-stellar ones. The surface density of sources follows an increasing trend as they evolve from pre-stellar to proto-stellar, but then it is found to decrease again in the majority of the most evolved clumps. Finally, we study the physical parameters of sources with respect to Galactic longitude and the association with spiral arms, finding only minor or no differences between the average evolutionary status of sources in the fourth and first Galactic quadrants, or between "on-arm" and "inter-arm" positions. Copyright © 2017, The Authors. All rights reserved.

关键词： Galaxies

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