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arXiv 2019年

作者： Xing, Yuying Yu, Guoxian Domeniconi, Carlotta Wang, Jun Zhang, Zili Guo, Maozu College of Computer and Information Science Southwest University Chongqing China Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan China Department of Computer Science George Mason University FairfaxVA United States School of Information Technology Deakin University GeelongVIC Australia School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing China

Multi-view Multi-instance Multi-label Learning(M3L) deals with complex objects encompassing diverse instances, represented with different feature views, and annotated with multiple labels. Existing M3L solutions only partially explore the inter or intra relations between objects (or bags), instances, and labels, which can convey important contextual information for M3L. As such, they may have a compromised performance. In this paper, we propose a collaborative matrix factorization based solution called M3Lcmf. M3Lcmf first uses a heterogeneous network composed of nodes of bags, instances, and labels, to encode different types of relations via multiple relational data matrices. To preserve the intrinsic structure of the data matrices, M3Lcmf collaboratively factorizes them into low-rank matrices, explores the latent relationships between bags, instances, and labels, and selectively merges the data matrices. An aggregation scheme is further introduced to aggregate the instance-level labels into bag-level and to guide the factorization. An empirical study on benchmark datasets show that M3Lcmf outperforms other related competitive solutions both in the instance-level and bag-level prediction. Copyright © 2019, The Authors. All rights reserved.

关键词： Matrix factorization

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DLPlib： A Library for Deep Learning Processor

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Journal of computer Science & technology 2017年第2期32卷 286-296页

作者： Hui-Ying Lan Lin-Yang Wu Xiao Zhang Jin-Hua Tao Xun-Yu Chen Bing-Rui Wang Yu-Qing Wang Qi Guo Yun-Ji Chen State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Microprocessor Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Department of Computer Science University of Science and Technology of China Hefei 230026 China

Recently, deep learning processors have become one of the most promising solutions of accelerating deep learning algorithms. Currently, the only method of programming the deep learning processors is through writing assembly instructions by bare hands, which costs a lot of programming efforts and causes very low efficiency. One solution is to integrate the deep learning processors as a new back-end into one prevalent high-level deep learning framework （e.g., TPU （tensor processing unit） is integrated into Tensorflow directly）. However, this will obstruct other frameworks to profit from the programming interface, The alternative approach is to design a framework-independent low-level library for deep learning processors （e.g., the deep learning library for GPU, cuDNN）. In this fashion, the library could be conveniently invoked in high-level programming frameworks and provides more generality. In order to allow more deep learning frameworks to gain benefits from this environment, we envision it as a low-level library which could be easily embedded into current high-level frameworks and provide high performance. Three major issues of designing such a library are discussed. The first one is the design of data structures. Data structures should be as few as possible while being able to support all possible operations. This will allow us to optimize the data structures easier without compromising the generality. The second one is the selection of operations, which should provide a rather wide range of operations to support various types of networks with high efficiency. The third is the design of the API, which should provide a flexible and user-friendly programming model and should be easy to be embedded into existing deep learning frameworks. Considering all the above issues, we propose DLPIib, a tensor-filter based library designed specific for deep learning processors. It contains two major data structures, tensor and filter, and a set of operators including basic neur

关键词： deep learning processor API library DLPlib

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Landscape of big medical data: A pragmatic survey on prioritized tasks

arXiv

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arXiv 2019年

作者： Zhang, Zhifei Gao, Wanling Zhang, Fan Huang, Yunyou Dai, Shaopeng Fan, Fanda Zhan, Jianfeng Du, Mengjia Yin, Silin Xiong, Longxin Du, Juan Cheng, Yumei Zhou, Xiexuan Ren, Rui Wang, Lei Ye, Hainan Department of Physiology and Pathophysiology Capital Medical University State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Nanchang First Hospital Neonatal Center Beijing Children's Hospital Affiliated to Capital Medical University Beijing Obstetrics and Gynecology Hospital Affiliated to Capital Medical University Beijing Academy of Frontier Sciences and Technology

Big medical data poses great challenges to life scientists, clinicians, computer scientists, and engineers. In this paper, a group of life scientists, clinicians, computer scientists and engineers sit together to discuss several fundamental issues. First, what are the unique characteristics of big medical data different from those of the other domains? Second, what are the prioritized tasks in clinician research and practices utilizing big medical data? And do we have enough publicly available data sets for performing those tasks? Third, do the state-of-the-practice and state-of-the-art algorithms perform good jobs? Fourth, are there any benchmarks for measuring algorithms and systems for big medical data? Fifth, what are the performance gaps of state-of-the-practice and state-of-the-art systems handling big medical data currently or in future? Finally but not least, are we, life scientists, clinicians, computer scientists and engineers, ready for working together? We believe answering the above issues will help define and shape the landscape of big medical data. Copyright © 2019, The Authors. All rights reserved.

关键词： computer aided diagnosis

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Multidimensional fuzzy sets for texture modelling adapted to user profiles

Multidimensional fuzzy sets for texture modelling adapted to...

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2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017

作者： Martínez-Jiménez, Pedro Manuel Chamorro-Martínez, Jesús Soto-Hidalgo, José Manuel Rodríguez-Pérez, Javier Department of Computer Science and Artificial Intelligence University of Granada Spain Department of Computer Architecture Electronics and Electronic Technology University of Cordoba Spain

ISBN: (纸本)9781509060344

The analysis of the perceptual properties of texture plays a fundamental role in tasks where some interaction with subjects is needed. In order to face the imprecision related to these properties, several fuzzy approaches can be found in the literature, but they do not properly take into account the subjectivity of users. In this paper, a generic technique is proposed in order to adapt any multidimensional fuzzy set to the different perceptions of texture properties that a particular user can have. This way, we combine the improvement in the texture characterization given by the use of several computational measures as reference set with the adaptation to the subjectivity of the human perception. In the proposed adaptation method, the membership functions are automatically transformed on the basic of the information given by the user. © 2017 IEEE.

关键词： Fuzzy sets

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Publisher Correction: Twisted moiré conductive thermal metasurface

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Nature communications 2024年第1期15卷 2876页

作者： Huagen Li Dong Wang Guoqiang Xu Kaipeng Liu Tan Zhang Jiaxin Li Guangming Tao Shuihua Yang Yanghua Lu Run Hu Shisheng Lin Ying Li Cheng-Wei Qiu Department of Electrical and Computer Engineering National University of Singapore Kent Ridge 117583 Republic of Singapore. State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou 310027 China. International Joint Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Zhejiang University Haining 314400 China. Wuhan National Laboratory for Optoelectronics and State Key Laboratory of Material Processing and Die and Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China. Smart Materials for Architecture Research Lab Innovation Center of Yangtze River Delta Zhejiang University Jiaxing 314100 China. State Key Laboratory of Coal Combustion School of Energy and Power Engineering Huazhong University of Science and Technology Wuhan 430074 China. Chongqing 2D Materials Institute Chongqing 400015 China. State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou 310027 China. eleying@***. International Joint Innovation Center Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang The Electromagnetics Academy of Zhejiang University Zhejiang University Haining 314400 China. eleying@***. Department of Electrical and Computer Engineering National University of Singapore Kent Ridge 117583 Republic of Singapore. chengwei.qiu@nus.edu.sg.

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Search for a vector-like quark T′ → tH via the diphoton decay mode of the Higgs boson in proton-proton collisions at √s = 13 TeV

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Journal of High Energy Physics 2023年第9期2023卷 1-40页

作者： Tumasyan, A. Adam, W. Andrejkovic, J.W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Escalante Del Valle, A. Hussain, P.S. Jeitler, M. Krammer, N. Lechner, L. Liko, D. Mikulec, I. Paulitsch, P. Pitters, F.M. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Kello, T. Rejeb Sfar, H. Van Mechelen, P. Bols, E.S. D’Hondt, J. De Moor, A. Delcourt, M. El Faham, H. Lowette, S. Moortgat, S. Morton, A. Müller, D. Sahasransu, A.R. Tavernier, S. Van Doninck, W. Vannerom, D. Clerbaux, B. De Lentdecker, G. Favart, L. Hohov, D. Jaramillo, J. Lee, K. Mahdavikhorrami, M. Makarenko, I. Malara, A. Paredes, S. Pétré, L. Postiau, N. Thomas, L. Vanden Bemden, M. Vander Velde, C. Vanlaer, P. Dobur, D. Knolle, J. Lambrecht, L. Mestdach, G. Rendón, C. Samalan, A. Skovpen, K. Tytgat, M. Van Den Bossche, N. Vermassen, B. Wezenbeek, L. Benecke, A. Bruno, G. Bury, F. Caputo, C. David, P. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sa. Lemaitre, V. Mondal, K. Taliercio, A. Tran, T.T. Vischia, P. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. Moraes, A. Rebello Teles, P. Aldá Júnior, W.L. Alves Gallo Pereira, M. Barroso Ferreira Filho, M. Brandao Malbouisson, H. Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. Dos Santos Sousa, V. Fonseca De Souza, S. Martins, J. Mora Herrera, C. Mota Amarilo, K. Mundim, L. Nogima, H. Santoro, A. Silva Do Amaral, S.M. Sznajder, A. Thiel, M. Vilela Pereira, A. Bernardes, C.A. Calligaris, L. Fernandez Perez Tomei, T.R. Gregores, E.M. Mercadante, P.G. Novaes, S.F. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Rodozov, M. Shopova, M. Sultanov, G. Dimitrov, A. Ivanov, T. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Thakur, S. Cheng, T. Javaid, T. Mittal, M. Yuan, L. Ahmad, M. Bauer, G. Hu, Z. Lezki, S. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Milosevic, V. Monti, F. Sharma, R. Tao, J. Thomas-Wilsker Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) — Fudan University Shanghai China Zhejiang University Zhejiang Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysics Tallinn Estonia Department of Physics

A search for the electroweak production of a vector-like quark T′, decaying to a top quark and a Higgs boson is presented. The search is based on a sample of proton-proton collision events recorded at the LHC at s = 13 TeV, corresponding to an integrated luminosity of 138 fb¹. This is the first T′ search that exploits the Higgs boson decay to a pair of photons. For narrow isospin singlet T′ states with masses up to 1.1 TeV, the excellent diphoton invariant mass resolution of 1–2% results in an increased sensitivity compared to previous searches based on the same production mechanism. The electroweak production of a T′ quark with mass up to 960 GeV is excluded at 95% confidence level, assuming a coupling strength κ_T = 0.25 and a relative decay width Γ/M_T′ < 5%. [Figure not available: see fulltext.]. © 2023, The Author(s).

关键词： Beyond Standard Model Hadron-Hadron Scattering Top Physics

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A quad-band slot antenna with spiral stub and interdigital CPW Feed

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Journal of Physics: Conference Series 2020年第1期1457卷

作者： T. Archevapanich P. Chomtong P. Akkaraekthalin Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi Nonthaburi 7/1 Nonthaburi Road Nonthaburi 11000 Thailand Department of Teacher Training in Electrical Engineering Faculty of Technical Education King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand

This paper proposes a quad-band slot antenna with spiral stub and interdigital CPW feed. The antenna has a compact size and can be used for four frequency bands of 1.8 GHz, 2.45 GHz, 3.7 GHz and 5.2 GHz applicable for LTE, WiMAX and WLAN systems. The important technique designs of the proposed antenna are divided into 2 parts. The first part includes the stepped slot antenna added with square-shaped spiral stub. As a result, the resonance frequencies of the third and fourth harmonics can be controlled as desired. For the second part, the technique of interdigital capacitive CPW is employed at the feeding line, resulting in length reduction from λ/4 of the conventional one to λ/8, which is caused by the slow-wave effect. Moreover, with this technique the resonance frequency of the second harmonic can be independently controlled. The optimized antenna has good performances for all frequency bands with bandwidths of 190 MHz (1.72 GHz-2GHz) at 1.8 GHz band, 280 MHz (2.34GHz-2.53GHz) at 2.45 GHz band, 410 MHz (3.54 GHz-3.95 GHz) at 3.7 GHz band and 220 MHz (5.10 GHz-5.32 GHz) at 5.2 GHz band, respectively.

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Strength and Deformability of Cement Composites of Various Types

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IOP Conference Series: Materials Science and Engineering 2021年第5期1079卷

作者： I V Erofeeva D V Emelyanov D A Svetlov A A Matvievskiy I N Maksimova N I Makridin Department of Engineering and Computer Graphics National Research Ogarev Mordovia State University 68 Bolshevistskaya St. Saransk 430005 Russia Department of Building Materials and Technologies National Research Ogarev Mordovia State University 68 Bolshevistskaya St. Saransk 430005 Russia Soft Protector LLC 28 Himikov St. St. Petersburg 195030 Russia OJSC «MAKSMIR» 11 Novinsky Boulevard Moscow 121099 Russia Department of Quality Management and Construction Production Technologies Penza State University of Architecture and Construction 28 German Titov St. Penza 440028 Russia Department of Technology of Building Materials and Woodworking State University of Architecture and Construction 28 German Titov St. Penza 440028 Russia

It is shown that the construction of buildings and structures requires concrete with universal characteristics, primarily with compressive strength in the range of 35-200 (MPa) with high tensile strength, crack resistance and durability. Strength and elastic-plastic and other properties of concretes and other cement composites are regulated by creating their various formulations. In this regard, it is important to conduct comprehensive studies of the properties of composites in relation to their compositions. Cement composites of various compounding compositions, including fillers, plasticizers, pigments, and biocidal preparations, are considered. Attention is also paid to the technological aspects of preparing mixtures and manufacturing products, namely, the influence of activated water on the properties of concretes of mixing and hardening conditions. Indicators of strength, modulus of elasticity, and brittleness were obtained for compositions that differed in the type of plasticizer ('Melflux 1641 F', 'Melflux 5581 F', 'Fortrace–strong', 'Hidetal-P-5', 'Hidetal GP-9' gamma 'A'), a biocidal preparation (Teflex Antimould, Teflex Disinfectant, Teflex for Industrial sights), a pigment (iron oxide red, iron oxide yellow, green glauconito-vogo, meerkat iron). The influence on the properties of powder – activated concretes, rheologically active (rock flour), reactively active (micro - silica), fillers, as well as quartz sand fractions 0, 16 – 0.63 and 0.63-5.0 mm. The results of research showed an increase in the strength of concrete when using plasticizer 'Melflux 1641F' and activated mixing water in the technology of their preparation. To increase the strength and modulus of elasticity led to the introduction of rock flour and silica. The introduction of plasticizers led to a decrease in the elastic modulus, and the use of activated closing water does not affect this indicator. From the examined compositions, compositions with the addition of pigments are characterize

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A Hardware Trojan Attack on FPGA-Based Cryptographic Key Generation: Impact and Detection

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Journal of Hardware and Systems Security 2018年第3期2卷 225-239页

作者： Vidya Govindan Rajat Subhra Chakraborty Pranesh Santikellur Aditya Kumar Chaudhary Secured Embedded Architecture Laboratory (SEAL) Department of Computer Science and Engineering Indian Institute of Technology Kharagpur Kharagpur India Centre for Artificial Intelligence and Robotics DRDO Complex Bangalore India

True Random Number Generator (TRNG) circuits are important components of cryptographic systems. Lack of statistical randomness in the generated bitstreams from a TRNG can result in compromised keys, leading to serious security breaches. In this paper, we describe a Hardware Trojan Horse (HTH)-based attack on the TRNG of an FPGA-based cryptosystem, that results in reduced entropy and increased predictability of the generated keys. The proposed HTH does not cause any functional failure in the cryptosystem, and its impact is undetectable by analysis of the compromised bitstream using standard statistical randomness testing software suites (NIST, two enhanced versions of NIST Dieharder, and LIL-tests), and by a circuit-level HTH detection technique using Transition Effect Ring Oscillator (TERO). Finally, we show that the impact of the HTH can be detected by applying Wavelet Transform on the compromised bitstream.

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Condition Assessment in Transmission Line Asset for Maintenance Management

Condition Assessment in Transmission Line Asset for Maintena...

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International Electrical Engineering Congress (iEECON)

作者： Ittiphong Yongyee Cattareeya Suwanasri Thanapong Suwanasri Waraporn Luejai Department of Electrical and Computer Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand Department of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi Phranakhon Si Ayutthaya Thailand

ISBN: (纸本)9781538623183;9781538623176

This paper presents condition assessment in transmission line asset for maintenance scheduling management in Thailand's transmission network. The score and weight techniques are applied to the condition assessment. The component of transmission system such as conductor, conductor accessories, insulator, steel structure, foundation, lightning protection, tower accessories and right of way are evaluated while sub-components of each component and classified. The 10 of 115 kV transmission lines in Thailand are evaluated as example in the assessment program. The results show the health index of component, health index of tower and health index of transmission line in form of percentage. The cost of maintenance is considered to plan effective maintenance scheduling for transmission system.

关键词： Power transmission lines Poles and towers Inspection Conductors Visualization Maintenance engineering Indexes

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