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Correction to: High-speed tracking based on multi-CF filters and attention mechanism

Signal, Image and Video Processing 2020年第3期14卷 637-637页

作者： Fan, Songyuan Wang, Rui Wu, Zhihao Rho, Seungmin Liu, Shaohui Xiong, Jiaxin Fu, Sen Jiang, Feng School of Computer Science Harbin Institute of Technology Harbin China School of Architecture Harbin Institute of Technology Harbin China College of Software and Convergence Technology Sejong University Seoul Republic of Korea Beijing Institute of Technology Beijing China Shanghai Radio Equipment Research Institute Shanghai China

Unfortunately, the Acknowledgement section has been published as blinded version.

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Adaptive, HHybrid FFeature Selection (AHFS)

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Pattern Recognition 2021年 116卷 107932-107932页

作者： Viharos, Zsolt János Kis, Krisztián Balázs Fodor, Ádám Büki, Máté István Institute for Computer Science and Control Fraunhofer Project Centre for Production Management and Informatics Budapest Kende u. 13–17. H-1111 Hungary Faculty of Economics and Business Department of Economics and Law John von Neumann University Kecskemét Izsáki u. 10. H-1117 Hungary Department of Software Technology and Methodology Eötvös Loránd University Budapest H-1117 Pázmány P. sny 1/C. Hungary

This paper deals with the problem of integrating the most suitable feature selection methods for a given problem in order to achieve the best feature order. A new, adaptive and hybrid feature selection approach is proposed, which combines and utilizes multiple individual methods in order to achieve a more generalized solution. Various state-of-the-art feature selection methods are presented in detail with examples of their applications and an exhaustive evaluation is conducted to measure and compare the their performance with the proposed approach. Results prove that while the individual feature selection methods may perform with high variety on the test cases, the combined algorithm steadily provides noticeably better solution. © 2021 The Authors

关键词： Information theory

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Improved meet-in-the-middle attacks on 7-round AES-192 and 8-round AES-256

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Tongxin Xuebao/Journal on Communications 2010年第9 A期31卷 197-201页

作者： Dong, Xiao-Li Hu, Yu-Pu Chen, Jie Li, Shun-Bo Yang, Yang Key Laboratory of Computer Networks and Information Security of Ministry of Education Xidian University Xi'an 710071 China State Key Laboratory of Information Security Institute of Software Chinese Academy of Sciences Beijing 100049 China School of Science Xi'an University of Architecture and Technology Xi'an 710055 China

A new variant of 5-round distinguisher of meet-in-the-middle attack on AES was constructed by exploiting the properties of the round transform of AES. Based on the variant of distinguisher, meet-in-the-middle attacks on 7-round AES-192 and 8-round AES-256 were presented by using the time-memory tradeoff approach. It is shown that the new results are better than the cryptanalytic results presented at FSE2008 on reduced AES in terms of the time complexity and the memory complexity.

关键词： Cryptography

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Verification of a numerical model of the offshore wind turbine from the alpha ventus wind farm within OC5 phase III 37

Verification of a numerical model of the offshore wind turbi...

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ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering, OMAE 2018

作者： Popko, Wojciech Huhn, Matthias L. Robertson, Amy Jonkman, Jason Wendt, Fabian Muller, Kolja Kretschmer, Matthias Vorpahl, Fabian Hagen, Torbjørn Ruud Galinos, Christos Dreff, Jean-Baptiste Le Gilbert, Philippe Auriac, Bertrand Villora, Francisco Navarro Schunemann, Paul Bayati, Ilmas Belloli, Marco Oh, Sho Totsuka, Yoshitaka Qvist, Jacob Bachynski, Erin Sørum, Stian Høegh Thomassen, Paul E. Shin, Hyunkyoung Vittori, Felipe Galvan, Josean Molins, Climent Bonnet, Paul Van Der Zee, Tjeerd Bergua, Roger Wang, Kai Fu, Pengcheng Cai, Jifeng Fraunhofer Institute for Wind Energy Systems IWES Division Wind Turbine and System Technology Bremerhaven27572 Germany National Renewable Energy Laboratory GoldenCO United States University of Stuttgart Stuttgart Wind Energy Stuttgart Germany Senvion Osnabruck Germany OWEC Tower AS Oslo Norway Technical University of Denmark Department of Wind Energy Roskilde Denmark Electricite de France Recherche et Developpement Palaiseau France IFP Energies Nouvelles Solaize France Principia La Ciotat France Siemens Gamesa Renewable Energy Hamburg Germany University of Rostock Endowed Department of Wind Energy Technology Rostock Germany Politecnico di Milano Department of Mechanical Engineering Milan Italy Tokyo Japan Wind Energy Institute of Tokyo Inc. Tokyo Japan Subsea Hvalstad Norway Norwegian University of Science and Technology Department of Marine Technology Trondheim Norway Simis AS Trondheim Norway University of Ulsan School of Naval Architecture and Ocean Engineering Ulsan Korea Republic of Sarriguren Spain TECNALIA Derio Spain Polytechnic University of Catalonia Barcelona Spain Siemens Industry Software Cornella de Llobregat Spain Knowledge Centre WMC Wieringerwerf Netherlands Envision Energy Limited Shanghai China China General Certification Center Beijing China

ISBN: (纸本)9780791851319

The main objective of the Offshore Code Comparison Collaboration Continuation, with Correlation (OC5) project, is validation of aero-hydro-servo-elastic simulation tools for offshore wind turbines (OWTs) through comparison of simulated results to the response data of physical systems. Phase III of the OC5 project analyzes the Senvion 5M wind turbine supported by the OWEC Quattropod from the alpha ventus offshore wind farm. This paper shows results of the verification of the OWT models (code-to-code comparison). A subsequent publication will focus on their validation (comparison of simulated results to measured physical system response data). Based on the available data, the participants of Phase III set up numerical models of the OWT in their simulation tools. It was necessary to verify and to tune these models. The verification and tuning were performed against an OWT model available at the University of Stuttgart - Stuttgart Wind Energy (SWE) and documentation provided by Senvion and OWEC Tower. A very good match was achieved between the results from the reference SWE model and models set up by OC5 Phase III participants. © Copyright 2018 ASME.

关键词： Numerical models

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Package of the vector math library based on the sunway processor

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Ruan Jian Xue Bao/Journal of software 2014年 25卷 70-79页

作者： Xie, Qing-Chun Zhang, Yun-Quan Li, Yan Pang, Ren-Bo Wu, Zai-Long Lu, Yong-Quan Gao, Peng-Dong High Performance Computing Center Communication University of China Beijing100024 China Laboratory of Parallel Computing Institute of Software The Chinese Academy of Sciences Beijing100190 China State Key Laboratory of Computer Architecture Institute of Computing Technology The Chinese Academy of Sciences Beijing100190 China Department of Computer and Network National Marine Environmental Forecasting Center Beijing100081 China School of Information Sceience and Technology The Ocean University of China Qingdao266100 China

This paper first introduces the SIMD (single instruction multiple data) extension technology and presents three ways to use SIMD instructions. It is considered that calling the third party library, which is optimized for the target platform by using those instructions, is the best way to benefit the developers. Next, it introduces the China-developed SW-1600 CPU, and a software package called SW-VML, which consists of many mathematical functions, by using the SIMD extension technology. In order to solve the additional overhead caused by unaligned address access and transformation between vector and scalar array, the paper provides some performance optimized methods, such as aligned address access, simplifying vector condition branch and loop unrolling. An upgrade to SW-VML is also offered to support multi-thread with OpenMP. Finally, functions in the package are tested using arrays of different sizes on SW-1600, and the test results show that high performance is achieved with the technology of the SIMD vectorization. Compared with the traditional methods of the scalar calculation, the average speedup is up to 2.06. The performance speedup of package using 4 threads is up to 2.26 compared to using a single thread. SW-VML is a common vector function package for domestic Sunway processor series, and it can be used as a basic toolkit which is beneficial to high performance computing on Sunway platform. ©2014 ISCAS.

关键词： Vectors

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Analysis and Design of Mobile Model for DTN

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电子学报(英文版) 2009年第4期

作者： LIN Zhiting LIN Zhiting QU Yugui QU Yugui JI Yusheng JI Yusheng ZHAO Baohua ZHAO Baohua Department of Computer Science University of Science and Technology of China Hefei 230027 China Department of Computer Science University of Science and Technology of China Hefei 230027 China Province Key Laboratory of Software in Computing and Communication Hcfei 230027 China Province Key Laboratory of Software in Computing and Communication Hcfei 230027 China Information Systems Architecture Science Research Division National Institute of Info~natics Tokyo Japan) Information Systems Architecture Science Research Division National Institute of Info~natics Tokyo Japan)

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NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results

arXiv

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arXiv 2024年

作者： Liu, Xiaoning Wu, Zongwei Li, Ao Vasluianu, Florin Zhang, Yulun Gu, Shuhang Zhang, Le Zhu, Ce Timofte, Radu Jin, Zhi Wu, Hongjun Wang, Chenxi Ling, Haitao Cai, Yuanhao Bian, Hao Zheng, Yuxin Lin, Jing Yuille, Alan Shao, Ben Guo, Jin Liu, Tianli Wu, Mohao Feng, Yixu Hou, Shuo Lin, Haotian Zhu, Yu Wu, Peng Dong, Wei Sun, Jinqiu Zhang, Yanning Yan, Qingsen Zou, Wenbin Yang, Weipeng Li, Yunxiang Wei, Qiaomu Ye, Tian Chen, Sixiang Zhang, Zhao Zhao, Suiyi Wang, Bo Luo, Yan Zuo, Zhichao Wang, Mingshen Wang, Junhu Wei, Yanyan Sun, Xiaopeng Gao, Yu Huang, Jiancheng Chen, Hongming Chen, Xiang Tang, Hui Chen, Yuanbin Zhou, Yuanbo Dai, Xinwei Qiu, Xintao Deng, Wei Gao, Qinquan Tong, Tong Li, Mingjia Hu, Jin He, Xinyu Guo, Xiaojie Sabarinathan Uma, K. Sasithradevi, A. Sathya Bama, B. Mohamed Mansoor Roomi, S. Srivatsav, V. Wang, Jinjuan Sun, Long Chen, Qiuying Shao, Jiahong Zhang, Yizhi Conde, Marcos V. Feijoo, Daniel Benito, Juan C. García, Alvaro Lee, Jaeho Kim, Seongwan Sharif, S.M.A. Khujaev, Nodirkhuja Tsoy, Roman Murtaza, Ali Khairuddin, Uswah Faudzi, Ahmad'Athif Mohd Malagi, Sampada Joshi, Amogh Akalwadi, Nikhil Desai, Chaitra Tabib, Ramesh Ashok Mudenagudi, Uma Lian, Wenyi Lian, Wenjing Kalyanshetti, Jagadeesh Aralikatti, Vijayalaxmi Ashok Yashaswini, Palani Upasi, Nitish Hegde, Dikshit Patil, Ujwala Sujata, C. Yan, Xingzhuo Hao, Wei Fu, Minghan Choksy, Pooja Sarvaiya, Anjali Upla, Kishor Raja, Kiran Yan, Hailong Zhang, Yunkai Li, Baiang Zhang, Jingyi Zheng, Huan University of Electronic Science and Technology of China China Computer Vision Lab University of Würzburg Germany Shanghai Jiao Tong University China Computer Vision Lab ETH Zurich Switzerland School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen Campus Guangdong Shenzhen518107 China Guangdong Provincial Key Laboratory of Fire Science and Technology Guangzhou510006 China Johns Hopkins University United States Tsinghua University China Zhejiang Dahua Technology Co. Ltd. China School of Computer Science Northwestern Polytechnical University China School of Software Northwestern Polytechnical University China School of Computer Science Xi'an University of Architecture and Technology China South China University of Technology China Fuzhou University China Chengdu University of Information Technology China Hong Kong University of Science and Technology Guangzhou China Hefei University of Technology China Individual Researcher Shenyang Aerospace University China Nanjing University of Science and Technology China Fuzhou University Fuzhou China Imperial Vision Technology Fuzhou China Tianjin University China Couger Inc Japan Sasi Institute of Technology & Engineering India Vellore Institute of Technology India Thiagarajar college of engineering India Coventry University United Kingdom Cidaut AI CVLab University of Wuerzburg Germany Opt-AI University Teknologi Malaysia Kuala Lumpur Malaysia Universiti Teknologi Malaysia Kuala Lumpur Malaysia KLE Technological University Karnataka Hubballi India School of Electronics and Communication Engineering KLE Technological University Karnataka Hubballi India School of Computer Science and Engineering KLE Technological University Karnataka Hubballi India Uppsala University Sweden Northeastern University United States Bosch Investment Ltd. China Fortinet Inc. University of Saskatchewan Canada Sardar Vallabhbhai National Institute of Technology India Norwegian University of Science and Technolog

This paper reviews the NTIRE 2024 low light image enhancement challenge, highlighting the proposed solutions and results. The aim of this challenge is to discover an effective network design or solution capable of generating brighter, clearer, and visually appealing results when dealing with a variety of conditions, including ultra-high resolution (4K and beyond), non-uniform illumination, backlighting, extreme darkness, and night scenes. A notable total of 428 participants registered for the challenge, with 22 teams ultimately making valid submissions. This paper meticulously evaluates the state-of-the-art advancements in enhancing low-light images, reflecting the significant progress and creativity in this field. © 2024, CC BY.

关键词： Image enhancement

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Cognitive and learning difficulties and how they affect access to IT systems

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Universal Access in the Information Society 2007年第4期5卷 329-339页

作者： Keates, Simeon Adams, Ray Bodine, Cathy Czaja, Sara Gordon, Wayne Gregor, Peter Hacker, Emily Hanson, Vicki Kemp, John Laff, Mark Lewis, Clayton Pieper, Michael Richards, John Rose, David Savidis, Anthony Schultz, Greg Snayd, Paul Trewin, Shari Varker, Philip ITA Software Cambridge USA Collaborative International Research Centre for Universal Access (CIRCUA) School of Computing Science Middlesex University Hendon UK Assistive Technology Partners Department of Rehabilitation Medicine University of Colorado Health Sciences Center Denver USA Department of Psychiatry and Behavioral Sciences University of Miami School of Medicine Miami USA Department of Rehabilitation Medicine Mt Sinai School of Medicine One Gustave L. Levy Place New York USA Applied Computing University of Dundee Dundee Scotland Division of Employment Training Education & Youth Services F.E.G.S. New York USA IBM T.J. Watson Research Center Hawthorne USA Powers Pyles Sutter & Verville P.C. Washington USA Coleman Institute for Cognitive Disabilities University of Colorado Boulder USA Fraunhofer Institute for Applied Information Technology FIT Sankt Augustin Germany CAST Wakefiel USA Foundation for Research and Technology-Hellas (FORTH) Institute of Computer Science Heraklion Greece IBM Human Ability and Accessibility Center Hawthorne USA

In October 2005, the IBM Human Ability and Accessibility Center and T.J. Watson Research Center hosted a symposium on “cognitive and learning difficulties and how they affect access to IT systems”. The central premise of the symposium was the recognition that cognitive and learning difficulties have a profound impact on a person’s ability to interact with information technology (IT) systems, but that little support is currently being offered by those systems. By bringing together internationally renowned experts from a variety of different, but complementary, research fields, the symposium aimed to provide a complete overview of the issues related to this topic. This paper summarises the discussions and findings of the symposium.

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SSBC 2020: Sclera Segmentation Benchmarking Competition in the Mobile Environment

SSBC 2020: Sclera Segmentation Benchmarking Competition in t...

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IEEE International Joint Conference on Biometrics (IJCB)

作者： M. Vitek A. Das Y. Pourcenoux A. Missler C. Paumier S. Das I. De Ghosh D. R. Lucio L. A. Zanlorensi D. Menotti F. Boutros N. Damer J. H. Grebe A. Kuijper J. Hu Y. He C. Wang H. Liu Y. Wang Z. Sun D. Osorio-Roig C. Rathgeb C. Busch J. Tapia A. Valenzuela G. Zampoukis L. Tsochatzidis I. Pratikakis S. Nathan R. Suganya V. Mehta A. Dhall K. Raja G. Gupta J. N. Khiarak M. Akbari-Shahper F. Jaryani M. Asgari-Chenaghlu R. Vyas S. Dakshit P. Peer U. Pal V. Štruc University of Ljubljana (UL SI) Indian Statistical Institute (lSI IN) Grenoble Institute of Technology (INP FR) Ècole Nationale Supérieure de 1’Èlectronique et de ses Applications (ENSEA FR) University of Engineering and Management (UEM IN) Barrackpore Rastraguru Surendranath College (BRSNC IN) Federal University of Paraná (UFPR BR) Technische Universität Darmstadt (TUD DE) Fraunhofer Institute for Computer Graphics Research (IGD DE) Chinese Academy of Sciences (CAS CN) Beijing University of Civil Engineering and Architecture (BUCEA CN) Hochschule Darmstadt (HDA DE) Universidad de Santiago (USACH CL) TOC Biometrics (CL) Democritus University of Thrace (DUTH GR) Couger Inc. (JP) Thiagarajar College of Engineering (TCE IN) Indian Institute of Technology Ropar (IIT-RPR IN) Monash University (MU AU) Norwegian University of Science and Technology (NTNU NO) Warsaw University of Technology (WUT PL) Tabriz University (TU IR) Arak University (AU IR) Bennet University (BU IN) Calcutta Institute of Engineering and Management Maulana Abul Kalam University of Technology (MAKAUT IN) University of Texas at Dallas (UTD US

ISBN: (数字)9781728191867

ISBN: (纸本)9781728191874

The paper presents a summary of the 2020 Sclera Segmentation Benchmarking Competition (SSBC), the 7th in the series of group benchmarking efforts centred around the problem of sclera segmentation. Different from previous editions, the goal of SSBC 2020 was to evaluate the performance of sclera-segmentation models on images captured with mobile devices. The competition was used as a platform to assess the sensitivity of existing models to i) differences in mobile devices used for image capture and ii) changes in the ambient acquisition conditions. 26 research groups registered for SSBC 2020, out of which 13 took part in the final round and submitted a total of 16 segmentation models for scoring. These included a wide variety of deep-learning solutions as well as one approach based on standard image processing techniques. Experiments were conducted with three recent datasets. Most of the segmentation models achieved relatively consistent performance across images captured with different mobile devices (with slight differences across devices), but struggled most with low-quality images captured in challenging ambient conditions, i.e., in an indoor environment and with poor lighting.

关键词： Image segmentation Mobile handsets Performance evaluation Benchmark testing Training Lighting Iris recognition

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Wind Comfort Analysis Using an Immersed Boundary Method for Early-Stage Building Design

SSRN

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SSRN 2024年

作者： Mitkov, Radostin Hunger, Franziska Pantusheva, Mariya Naserentin, Vasilis Gösta, Alexander Mark, Andreas Petrova-Antonova, Dessislava Logg, Anders GATE Institute Sofia University "St. Kliment Ohridski" Sofia1113 Bulgaria Fraunhofer-Chalmers Centre for Industrial Mathematics Computational Engineering and Design Chalmers Science Park GothenburgSE-412 88 Sweden Department of Mathematical Sciences Chalmers University of Technology GothenburgSE-412 969 Sweden Department of Electrical and Computer Engineering Aristotle University of Thessaloniki ThessalonikiGR- 54124 Greece RISE - Research Institutes of Sweden Architecture and spatial planning Drottning Kristinas Väg 61 StockholmSE-114 28 Sweden Liljewall Arkitekter Odinsplatsen 1 GothenburgSE-411 02 Sweden

This paper presents a thorough exploration of wind comfort dynamics in urban environments through the application of computational fluid dynamics simulations, with a specific emphasis on the Immersed Boundary Method. The study validates the Immersed Boundary Octree Flow solver, IBOFlow, against experimental data and then simulates the flow in a real-world case study of an area in Mölndal, Sweden. The research examines the impact of varying the number of simulated wind directions on the wind comfort maps, revealing that employing 16 wind directions is a reliable balance between computational efficiency and precision. Further, the investigation delves into the implications of using a simplified building geometry as available in early-stage design, demonstrating that computational simulations can provide reliable information about the pedestrian wind comfort early in the design process. While underscoring the significance of early-stage CFD simulations in informing design decisions, the paper concludes by advocating for a holistic approach. It emphasizes the relevance of simulation testing in later design iterations, particularly as architectural details continue to be refined. © 2024, The Authors. All rights reserved.

关键词： Computational fluid dynamics

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