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作者： Zheng, Wei-Shi Gao, Xinbo Li, Yuanqing Lai, Jianhuang School of Data and Computer Science Sun Yat-sen University China State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an710071 China School of Automation Science and Engineering South China University of Technology China Guangzhou Key Laboratory of Brain Computer Interface and Applications Guangzhou 510640 China School of Data and Computer Science Sun Yat-sen University Guangzhou510275 China

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FPGA demonstration for WLAN-OFDM baseband receiver

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Journal of Information Hiding and Multimedia Signal Processing 2018年第5期9卷 1281-1292页

作者： Wu, Chih-Feng Shiue, Muh-Tian Sung, Tien-Wen Pan, Jeng-Shyang School of Information Science and Engineering Fujian University of Technology Fuzhou350118 China Department of Electrical Engineering National Central University Taoyuan32001 Taiwan College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian China Department of Information Management Chaoyang University of Technology Taichung41349 Taiwan

The FPGA demonstration for WLAN-OFDM baseband receiver is presented in this paper. In this OFDM baseband receiver, the CORDIC computing is employed to realize various arithmetics of baseband signal process and then to reduce the computational complexity of baseband receiver. For a large open office channel with 100 ns RMS delay spread, the measured EVMs of WLAN-OFDM baseband receiver are −13.3, −16.6, −25.4 and −31.0 dB for BPSK, QPSK, 16-QAM and 64-QAM, respectively. Finally, the physical design of WLAN-OFDM baseband receiver with 0.18 µm 1P6M CMOS technology indicates that the core area and power consumption are 1.2 mm2 (1094 µm × 1092 µm) and 33.2 mW, respectively, with supply voltage of 1.8 V and operating clock of 40 MHz. © 2018, Ubiquitous International. All rights reserved.

关键词： Signal to noise ratio

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Mean-field theory for the Nagel-Schreckenberg model with overtaking strategy

arXiv

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arXiv 2018年

作者： Su, Zhu Deng, Weibing Han, Jihui Li, Wei Cai, Xu National Engineering Laboratory for Technology of Big Data Applications in Education Central China Normal University Wuhan Complexity Science Center Institute of Particle Physics Central China Normal University Wuhan School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou China

Based on the Nagel-Schreckenberg (NS) model with periodic boundary conditions, a modified model considered overtaking strategy (NSOS) has been proposed [1, 2]. In this paper, we focus on the theoretical analysis of traffic ow for NSOS model by using mean-eld method. In the special case of vmax = 1 where vehicles can not overtake preceding ones, the features of stationary state can be obtained exactly. However, in the case of vmax >1 where overtaking happens, some approximative methods have to be took into account. The main results are that we find the reason why trac ow is increased in the regime where densities exceed the maximum ow density, and the inuence of traffic ow on the transition density is dominated by the braking probability p. Copyright © 2018, The Authors. All rights reserved.

关键词： Mean field theory

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Improvement of an Anonymous and Lightweight Authentication Scheme for TMIS

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Journal of Applied Mathematics and Physics 2018年第1期6卷 18-28页

作者： Chien-Ming Chen Bin Xiang Eric Wang Ke Tsu-Yang Wu Jerry Chun-Wei Lin Department of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China National Demonstration Center for Experimental Electronic Information and Electrical Technology Education Fujian University of Technology Fuzhou China

Telecare Medicine Information Systems (TMIS) provides flexible and convenient healthcare for patients. However, the medical data transmitted between patients and doctors are exposed to unsecure public networks. To protect the patient’s personal information, many authentication schemes are designed. Recently, Kang et al. proposed a hash based authentication schemes for TMIS and claimed that it could resist various attacks. However, we find that their proposed scheme is unsecure to traceability attack and user impersonation attack. In order to enhance the security and preserve the efficiency of Kang et al.’s, we proposed a new anonymous and lightweight scheme. The analysis demonstrates that our proposed scheme is superior to Kang et al.’s and the related schemes in security.

关键词： Authentication TMIS Smart Card

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Semantic web for social good

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CEUR Workshop Proceedings 2018年 2182卷

作者： Waterman, K. Krasnow McGuinness, Deborah L. Hendler, James A. Decentralized Information Group Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA United States Tetherless World Constellation Department of Cognitive Science Rensselaer Polytechnic Institute TroyNY United States Institute for Data Exploration and Applications Tetherless World Constellation Department of Cognitive Science Rensselaer Polytechnic Institute TroyNY United States

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Robust frequent directions with application in online learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2019年第1期20卷

作者： Luo Luo Cheng Chen Zhihua Zhang Wu-Jun Li Tong Zhang Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China National Engineering Lab for Big Data Analysis and Applications School of Mathematical Sciences Peking University Beijing China National Key Laboratory for Novel Software Technology Collaborative Innovation Center of Novel Software Technology and Industrialization Department of Computer Science and Technology Nanjing University Nanjing China Computer Science & Mathematics Hong Kong University of Science and Technology Hong Kong

The frequent directions (FD) technique is a deterministic approach for online sketching that has many applications in machine learning. The conventional FD is a heuristic procedure that often outputs rank deficient matrices. To overcome the rank deficiency problem, we propose a new sketching strategy called robust frequent directions (RFD) by introducing a regularization term. RFD can be derived from an optimization problem. It updates the sketch matrix and the regularization term adaptively and jointly. RFD reduces the approximation error of FD without increasing the computational cost. We also apply RFD to online learning and propose an effective hyperparameter-free online Newton algorithm. We derive a regret bound for our online Newton algorithm based on RFD, which guarantees the robustness of the algorithm. The experimental studies demonstrate that the proposed method outperforms state-of-the-art second order online learning algorithms.

关键词： frequent directions matrix approximation online Newton algorithm online convex optimization sketching

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Improvement of an Anonymous and Lightweight Authentication Scheme for TMIS

Improvement of an Anonymous and Lightweight Authentication S...

引用

作者： Chien-Ming Chen Bin Xiang Eric Wang Ke Tsu-Yang Wu Jerry Chun-Wei Lin Department of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology National Demonstration Center for Experimental Electronic Information and Electrical Technology Education Fujian University of Technology

Telecare Medicine Information Systems(TMIS) provides flexible and convenient healthcare for patients. However, the medical data transmitted between patients and doctors are exposed to unsecure public networks. To protect the patient's personal information, many authentication schemes are designed. Recently, Kang et al. proposed a hash based authentication schemes for TMIS and claimed that it could resist various attacks. However, we find that their proposed scheme is unsecure to traceability attack and user impersonation attack. In order to enhance the security and preserve the efficiency of Kang et al.'s, we proposed a new anonymous and lightweight scheme. The analysis demonstrates that our proposed scheme is superior to Kang et al.'s and the related schemes in security.

关键词： Authentication TMIS Smart Card

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DELIGHT: Deep Learning Identification of Galaxy Hosts of Transients using Multi-resolution Images

arXiv

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arXiv 2022年

作者： Förster, Francisco Muñoz Arancibia, Alejandra M. Reyes, Ignacio Gagliano, Alexander Britt, Dylan Cuellar-Carrillo, Sara Figueroa-Tapia, Felipe Polzin, Ava Yousef, Yara Arredondo, Javier Rodríguez-Mancini, Diego Correa-Orellana, Javier Bayo, Amelia Bauer, Franz E. Catelan, Márcio Cabrera-Vives, Guillermo Dastidar, Raya Estévez, Pablo A. Pignata, Giuliano Hernandez-Garcia, Lorena Huijse, Pablo Reyes, Esteban Sánchez-Sáez, Paula Ramirez, Mauricio Grandón, Daniela Pineda-García, Jonathan Chabour-Barra, Francisca Silva-Farfán, Javier Faculty of Physical and Mathematical Sciences University of Chile Chile Nuncio Monseñor Sótero Sanz 100 Providencia Santiago Chile Universidad de Chile Beauchef 851 Santiago8320000 Chile Department of Astronomy University of Chile Las Condes Santiago Chile Department of Astronomy University of Illinois at Urbana-Champaign 1002 W. Green St. IL61801 United States Center for Astrophysical Surveys National Center for Supercomputing Applications UrbanaIL61801 United States National Science Foundation Graduate Research United States Department of Physics Stanford University 382 Via Pueblo Mall StanfordCA94305 United States Kavli Institute for Particle Astrophysics & Cosmology Stanford University P.O. Box 2450 StanfordCA94305 United States Escuela de Ingeniería Eléctrica Pontificia Universidad Católica de Valparaíso Valparaíso Chile Instituto de Física y Astronomía Facultad de Ciencias Universidad de Valparaíso Gran Bretana 1111 Valparaíso Chile Department of Astronomy and Astrophysics The University of Chicago ChicagoIL60637 United States Barcelona School of Informatics Polytechnic University of Catalonia Barcelona08034 Spain Faculty of Physics University of Barcelona Barcelona08028 Spain Data Observatory Foundation Santiago Chile Instituto de Astrofísica Facultad de Física Pontificia Universidad Católica de Chile Santiago Chile European Southern Observatory Karl-Schwarzschild-Strasse 2 Garching bei München85748 Germany Centro de Astroingeniería Facultad de Física Pontificia Universidad Católica de Chile Santiago Chile Department of Computer Science University of Concepción Concepción Chile Instituto de Astrofisica Facultad de Ciencias Exactas Universidad Andres Bello Las Condes Santiago Chile Department of Electrical Engineering University of Chile Santiago Chile Instituto de Informática Universidad Austral Valdivia Chile Fintual Administradora General de Fondos S.A. Santiago Chile Departamento de Física Facultad de Ciencias

We present DELIGHT, or Deep Learning Identification of Galaxy Hosts of Transients, a new algorithm designed to automatically and in real-time identify the host galaxies of extragalactic transients. The proposed algorithm receives as input compact, multi-resolution images centered at the position of a transient candidate and outputs two-dimensional offset vectors that connect the transient with the center of its predicted host. The multi-resolution input consists of a set of images with the same number of pixels, but with progressively larger pixel sizes and fields of view. A sample of 16,791 galaxies visually identified by the ALeRCE broker team was used to train a convolutional neural network regression model. We show that this method is able to correctly identify both relatively large (1000 00) and small (r ≤ 1000) apparent size host galaxies using much less information (32 kB) than with a large, single-resolution image (920 kB). The proposed method has fewer catastrophic errors in recovering the position and is more complete and has less contamination ( © 2022, CC BY-SA.

关键词： Galaxies

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From FAIR to CURE: Guidelines for Computational Models of Biological Systems

arXiv

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arXiv 2025年

作者： Sauro, Herbert M. Agmon, Eran Blinov, Michael L. Gennari, John H. Hellerstein, Joe Heydarabadipour, Adel Hunter, Peter Jardine, Bartholomew E. May, Elebeoba Nickerson, David P. Smith, Lucian P. Bader, Gary D. Bergmann, Frank Boyle, Patrick M. Dräger, Andreas Faeder, James R. Feng, Song Freire, Juliana Fröhlich, Fabian Glazier, James A. Gorochowski, Thomas E. Helikar, Tomas Hoops, Stefan Imoukhuede, Princess Keating, Sarah M. Konig, Matthias Laubenbacher, Reinhard Loew, Leslie M. Lopez, Carlos F. Lytton, William W. McCulloch, Andrew Mendes, Pedro Myers, Chris J. Myers, Jerry G. Mulugeta, Lealem Niarakis, Anna van Niekerk, David D. Olivier, Brett G. Patrie, Alexander A. Quardokus, Ellen M. Radde, Nicole Rohwer, Johann M. Sahle, Sven Schaff, James C. Sego, T.J. Shin, Janis Snoep, Jacky L. Vadigepalli, Rajanikanth Wiley, H. Steve Waltemath, Dagmar Moraru, Ion Department of Bioengineering University of Washington SeattleWA98195-5061 United States Intelligent Systems Engineering and Biocomplexity Institute Indiana University Street BloomingtonIN47408 United States Center for Cardiovascular Biology University of Washington SeattleWA98195-5061 United States eScience Institute University of Washington SeattleWA98195-5061 United States Institute for Stem Cell and Regenerative Medicine University of Washington SeattleWA98195-5061 United States School of Biological Sciences University of Bristol 24 Tyndall Avenue BristolBS8 1TQ United Kingdom Departments of Physiology & Pharmacology Neurology Downstate Health Science University BrooklynNY11203 United States Department of Neurology Kings County Hospital BrooklynNY11203 United States NASA-John H. Glenn Research Center MS 110-3 21000 Brookpark Road ClevelandOH44135 United States Center for Cell Analysis and Modeling UConn Health 263 Farmington Avenue FarmingtonCT06030-6406 United States Amsterdam Institute for Life and Environment Vrije Universiteit Amsterdam De Boelelaan 1108 Amsterdam1081 HZ Netherlands Department of Pathology and Genomic Medicine Thomas Jefferson University 1020 Locust St PhiladelphiaPA19107 United States Biological Sciences Division Pacific Northwest National Laboratory 902 Battelle Blvd RichlandWA99354 United States Auckland Bioengineering Institute University of Auckland Auckland1010 New Zealand Center of Integrative Biology University of Toulouse III-Paul Sabatier 165 Rue Marianne Grunberg-Manago Toulouse31400 France Lifeware Group Inria Building Alan Turing 1 Rue Honoré d’Estienne d’Orves Palaiseau91120 France Multiscale Modeling Group Altos Labs Redwood CityCA94065 United States partner site Tübingen Tübingen Germany Ottfried-Müller-Str. 37 Tübingen72076 Germany 06120 Germany Department of Computer Science Center for Data Science New York University New YorkNY11201 United States Department of Bi

Guidelines for managing scientific data have been established under the FAIR principles requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data and models are key to progress. For this reason, and recognizing that such models are a very special type of "data", we argue that computational models, especially mechanistic models prevalent in medicine, physiology and systems biology, deserve a complementary set of guidelines. We propose the CURE principles, emphasizing that models should be Credible, Understandable, Reproducible, and Extensible. We delve into each principle, discussing verification, validation, and uncertainty quantification for model credibility;the clarity of model descriptions and annotations for understandability;adherence to standards and open science practices for reproducibility;and the use of open standards and modular code for extensibility and reuse. We outline recommended and baseline requirements for each aspect of CURE, aiming to enhance the impact and trustworthiness of computational models, particularly in biomedical applications where credibility is paramount. Our perspective underscores the need for a more disciplined approach to modeling, aligning with emerging trends such as Digital Twins and emphasizing the importance of data and modeling standards for interoperability and reuse. Finally, we emphasize that given the non-trivial effort required to implement the guidelines, the community moves to automate as many of the guidelines as possible. © 2025, CC BY.

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A matrix-based implementation of DE algorithm: The compensation and deficiency 30th

A matrix-based implementation of DE algorithm: The compensat...

引用

30th International Conference on Industrial, Engineering, and Other applications of Applied Intelligent Systems, IEA/AIE 2017

作者： Pan, Jeng-Shyang Meng, Zhenyu Xu, Huarong Li, Xiaoqing Fujian Provincial Key Lab of Big Data Mining and Applications Fujian University of Technology Fuzhou China Department of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Department of Computer Science and Technology Xiamen University of Technology Xiamen China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9783319600413

Differential Evolution has become a very popular continuous optimization algorithm since its inception as its simplicity, easy coding and good performance over kinds of optimization problems. Difference operator in donor vector calculation is the key feature of DE algorithm. Usually, base vector and difference vectors selection in calculating a donor usually cost extra lines of condition judgement. Moreover, these vectors are not equally selected from the individual population. These lead to more perturbation in optimization performance. To tackling this disadvantage of DE implementation, a matrix-based implementation of DE algorithm is advanced herein this paper. Three commonly used DE implementation approaches in literature are also presented and contrasted. CEC2013 test suites for real-parameter optimization are used as the test-beds for these comparison. Experiment results show that the proposed matrix-based implementation of DE algorithm performs better on optimization performance than the common implementation schemes of DE algorithm with similar time complexity. © Springer International Publishing AG 2017.

关键词： Global optimization

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