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arXiv 2024年

作者： Amaro, R. Åqvist, J. Bahar, I. Battistini, F. Bellaiche, A. Beltran, D. Biggin, P.C. Bonomi, M. Bowman, G.R. Bryce, R. Bussi, G. Carloni, P. Case, D. Cavalli, A. Chang, C.A. Cheatham, T.E. Cheung, M.S. Chipot, C. Chong, L.T. Choudhary, P. Cisneros, G.A. Clementi, C. Collepardo-Guevara, R. Coveney, P. Covino, R. Crawford, T.D. Dal Peraro, M. de Groot, B. Delemotte, L. De Vivo, M. Essex, J. Fraternali, F. Gao, J. Gelpí, J.L. Gervasio, F.L. Gonzalez-Nilo, F.D. Grubmüller, H. Guenza, M.G. Guzman, H.V. Harris, S. Head-Gordon, T. Hernandez, R. Hospital, A. Huang, N. Huang, X. Hummer, G. Iglesias-Fernández, J. Jensen, J.H. Jha, S. Jiao, W. Jorgensen, W.L. Kamerlin, S.C.L. Khalid, S. Laughton, C. Levitt, M. Limongelli, V. Lindahl, E. Lindorff-Larsen, K. Loverde, S. Lundborg, M. Luo, Y.L. Luque, F.J. Lynch, C.I. MacKerell, A. Magistrato, A. Marrink, S.J. Martin, H. McCammon, J.A. Merz, K. Moliner, V. Mulholland, A. Murad, S. Naganathan, A.N. Nangia, S. Noe, F. Noy, A. Oláh, J. O'Mara, M. Ondrechen, M.J. Onuchic, J.N. Onufriev, A. Osuna, S. Palermo, G. Panchenko, A.R. Pantano, S. Parish, C. Parrinello, M. Perez, A. Perez-Acle, T. Perilla, J.R. Pettitt, B.M. Pietropaolo, A. Piquemal, J.-P. Poma, A. Praprotnik, M. Ramos, M.J. Ren, P. Reuter, N. Roitberg, A. Rosta, E. Rovira, C. Roux, B. Röthlisberger, U. Sanbonmatsu, K. Schlick, T. Shaytan, A.K. Simmerling, C. Smith, J.C. Sugita, Y. Świderek, K. Taiji, M. Tao, P. Tikhonova, I.G. Tirado-Rives, J. Tuñón, I. Van Der Kamp, M.W. Van der Spoel, D. Velankar, S. Voth, G.A. Wade, R. Warshel, A. Welborn, V.V. Wetmore, S. Wong, C.F. Yang, L.-W. Zacharias, M. Orozco, M. Department of Molecular Biology University of California San DiegoCA United States Department of Cell and Molecular Biology Uppsala University Uppsala Sweden Laufer Center for Physical and Quantitative Biology Renaissance School of Medicine Stony Brook University Stony BrookNY United States Department of Biochemistry and Cell Biology Renaissance School of Medicine Stony Brook University Stony BrookNY United States Barcelona Spain European Molecular Biology Laboratory European Bioinformatics Institute Hinxton United Kingdom Structural Bioinformatics and Computational Biochemistry Department of Biochemistry University of Oxford Oxford United Kingdom Institut Pasteur Université Paris Cité CNRS UMR 3528 Computational Structural Biology Unit Paris France Department of Biochemistry and Biophysics University of Pennsylvania PhiladelphiaPA United States Division of Pharmacy and Optometry University of Manchester Manchester United Kingdom Scuola Internazionale Superiore di Studi Avanzati-SISSA Trieste Italy Computational Biomedicine Institute of Advanced Simulations IAS-5 Institute for Neuroscience and Medicine INM-9 Forschungszentrum Jülich GmbH Jülich Germany Department of Physics and Universitätsklinikum RWTH Aachen University Aachen Germany Department of Chemistry & Chemical Biology Rutgers University PiscatawayNJ United States Istituto Italiano di Tecnologia Drug Discovery and Development Bologna Italy Lausanne Switzerland Department of Chemistry University of California RiversideCA United States Department of Medicinal Chemistry College of Pharmacy University of Utah Salt Lake CityUT United States Department of Physics University of Washington SeattleWA United States Pacific Northwest National Laboratory RichlandWA United States LIA CNRS-UIUC UMR n°7019 Université de Lorraine Vandœuvre-lès-Nancy France Department of Physics University of Illinois at Urbana-Champaign UrbanaIL United States Department of Biochemistry and Molecular Biol

The communities that embraced data archiving efforts decades ago are now, in the era of data-driven biology, those gaining the most from the AI revolution. The structural biology community was a pioneer in this regard by establishing the Protein Data Bank (PDB) in 1971 and making data accessible using the FAIR (Findable, Accessible, Interoperable and Reusable) principles even before these were articulated [1, 2]. The genomics/bioinformatics community has followed the example, establishing many widely used databases [3, 4]. By contrast, molecular simulation has been anchored in usage paradigms dating back to the seventies, when molecular dynamics (MD) simulation was first applied to study biomacromolecules [5]. At that time, MD was used by theoretical physicists and chemists in "proof of concept" simulations. Still, fifty years later, MD has evolved into a cornerstone molecular biology technique that can provide accurate quantitative analysis and property prediction. MD is now employed by tens of thousands of researchers worldwide, accounting for roughly 15% of global supercomputer usage. Unfortunately, these rich and costly data are not systematically maintained, and when further analyses are required, simulations have to be rerun-an unacceptable situation from scientific, environmental and sustainability standpoints. In this letter, we argue for a collaborative endeavor to archive MD simulation data and describe ongoing efforts to establish cost-effective and sustainable data archiving strategies. © 2024, CC BY-NC-SA.

关键词： Biotic

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Random asynchronous iterations in distributed coordination algorithms

arXiv

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arXiv 2018年

作者： Chen, Yao Xia, Weiguo Cao, Ming Lü, Jinhu Department of Computer Science Southwestern University of Finance and Economics Chengdu611130 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China Faculty of Science and Engineering ENTEG University of Groningen Groningen9747 AG Netherlands School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

Distributed coordination algorithms (DCA) carry out information processing processes among a group of networked agents without centralized information fusion. Though it is well known that DCA characterized by an SIA (stochastic, indecomposable, aperiodic) matrix generate consensus asymptotically via synchronous iterations, the dynamics of DCA with asynchronous iterations have not been studied extensively, especially when viewed as stochastic processes. This paper aims to show that for any given irreducible stochastic matrix, even non-SIA, the corresponding DCA lead to consensus successfully via random asynchronous iterations under a wide range of conditions on the transition probability. Particularly, the transition probability is neither required to be independent and identically distributed, nor characterized by a Markov chain. Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

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An Induction to the development of software Quality Model Standards

An Induction to the Development of Software Quality Model St...

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International Conference on Trustworthy Systems and their Applications (TSA)

作者： Jiayu Gong Jiawen Lu Lizhi Cai Laboratory of Computer Software Testing & Evaluation Shanghai Development Center of Computer Software Technology Shanghai China School of Information Science & Engineering East China University of Science and Technology Shanghai China

ISBN: (纸本)9781509035403

Quality plays a key role in software life-cycle. With the purpose of specializing and evaluating software product quality, ISO had published software quality model standards, SQuaRE series standards. In order to meet the growing demand for software quality measurement, ISO have revised the ISO/IEC 2502n series of standards, recently. This paper introduces evolution of software quality model standards and the details of SQuaRE series standards. Furthermore, the shortcomings of ISO/IEC 2502n software quality measurement series standards were analyzed and a road map of new systems and software product quality measurement reference model was proposed. These outcomes were accepted by ISO in the ISO/IEC JTC1 SC7 plenary meeting, which held in May 2016, and will be integrated into next version of ISO/IEC 25020.

关键词： ISO Standards IEC Standards software software measurement Quality assessment Product design

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An effective scheme for biometric cryptosystems 2

An effective scheme for biometric cryptosystems

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2nd IEEE International Conference on computer and Communications, ICCC 2016

作者： Zhou, Yu Zhao, Bo Han, Jin Jun, Zheng School of Computer Science and Software Engineering East China Normal University Shanghai China School of Software and Microelectronics Peking University Beijing China Jiangsu Engineering Center of Network Monitoring School of Computer and Software Nanjing University of Information Science and Technology China

ISBN: (纸本)9781467390262

Compared with traditional cryptography, biometric cryptosystems provide more convenient and safe protection of keys. In this paper, an effective scheme for biometric cryptosystems based on the intersections of hyper-plane and hashed discrete space is proposed. Only genuine feature vectors, which are located on the hyper-plane, find the correct solution. Several tricks are provided to ensure the security of proposed scheme. Experiments have shown that our method achieved approximate performance compared with one of the latest methods based on fuzzy vault. However, our method is less complex than fuzzy vault based methods. © 2016 IEEE.

关键词： Cryptography

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Evidence for the Higgs Boson Decay to a Z Boson and a Photon at the LHC

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Physical Review Letters 2024年第2期132卷 021803-021803页

作者： G. Aad B. Abbott K. Abeling N. J. Abicht S. H. Abidi A. Aboulhorma H. Abramowicz H. Abreu Y. Abulaiti B. S. Acharya C. Adam Bourdarios L. Adamczyk L. Adamek S. V. Addepalli M. J. Addison J. Adelman A. Adiguzel T. Adye A. A. Affolder Y. Afik M. N. Agaras J. Agarwala A. Aggarwal C. Agheorghiesei A. Ahmad F. Ahmadov W. S. Ahmed S. Ahuja X. Ai G. Aielli A. Aikot M. Ait Tamlihat B. Aitbenchikh I. Aizenberg M. Akbiyik T. P. A. Åkesson A. V. Akimov D. Akiyama N. N. Akolkar K. Al Khoury G. L. Alberghi J. Albert P. Albicocco G. L. Albouy S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa T. Alexopoulos F. Alfonsi M. Algren M. Alhroob B. Ali H. M. J. Ali S. Ali S. W. Alibocus M. Aliev G. Alimonti W. Alkakhi C. Allaire B. M. M. Allbrooke J. F. Allen C. A. Allendes Flores P. P. Allport A. Aloisio F. Alonso C. Alpigiani M. Alvarez Estevez A. Alvarez Fernandez M. Alves Cardoso M. G. Alviggi M. Aly Y. Amaral Coutinho A. Ambler C. Amelung M. Amerl C. G. Ames D. Amidei S. P. Amor Dos Santos K. R. Amos V. Ananiev C. Anastopoulos T. Andeen J. K. Anders S. Y. Andrean A. Andreazza S. Angelidakis A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony E. Antipov M. Antonelli F. Anulli M. Aoki T. Aoki J. A. Aparisi Pozo M. A. Aparo L. Aperio Bella C. Appelt A. Apyan N. Aranzabal C. Arcangeletti A. T. H. Arce E. Arena J-F. Arguin S. Argyropoulos J.-H. Arling O. Arnaez H. Arnold G. Artoni H. Asada K. Asai S. Asai N. A. Asbah J. Assahsah K. Assamagan R. Astalos S. Atashi R. J. Atkin M. Atkinson H. Atmani P. A. Atmasiddha K. Augsten S. Auricchio A. D. Auriol V. A. Austrup G. Avolio K. Axiotis G. Azuelos D. Babal H. Bachacou K. Bachas A. Bachiu F. Backman A. Badea P. Bagnaia M. Bahmani A. J. Bailey V. R. Bailey J. T. Baines L. Baines C. Bakalis O. K. Baker E. Bakos D. Bakshi Gupta V. Balakrishnan R. Balasubramanian E. M. Baldin P. Balek E. Ballabene F. Balli L. M. Baltes W. K. Balunas J. Balz E. Banas M. Bandieramonte A. Bandyopadhyay S. Bansal L. Barak M. Barakat E. L. Barberio D. Barberis M. Barbero M. Z. Barel K. N. Barends T. Ba Benemerita Universidad Autonoma de Puebla Puebla Mexico ETH Zurich—Institute for Particle Physics and Astrophysics (IPA) Zurich Switzerland Institute of Nuclear Research ATOMKI Debrecen Hungary National and Kapodistrian University of Athens Athens Greece Escuela Politecnica Nacional Quito Ecuador Faculté des sciences Université Mohammed V Rabat Morocco University of Florida Gainesville Florida USA Fermi National Accelerator Laboratory Batavia Illinois USA University of Ruhuna Department of Physics Matara Sri Lanka INFN Sezione di Bologna Bologna Italy Università di Bologna Bologna Italy Vrije Universiteit Brussel Brussel Belgium AGH University of Krakow Faculty of Physics and Applied Computer Science Krakow Poland The University of Iowa Iowa City Iowa USA Institute Rudjer Boskovic Zagreb Croatia Universidad Iberoamericana Mexico City Mexico Instituto de Física de Cantabria (IFCA) CSIC-Universidad de Cantabria Santander Spain Department of Physics Istanbul University Istanbul Türkiye Imperial College London United Kingdom Baylor University Waco Texas USA Lappeenranta-Lahti University of Technology Lappeenranta Finland Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile INFN Sezione di Genova Genova Italy Università di Genova Genova Italy Centro de Investigacion y de Estudios Avanzados del IPN Mexico City Mexico Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania National Centre for Physics Quaid-I-Azam University Islamabad Pakistan Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France University of Canterbury Christchurch New Zealand Riga Technical University Riga Latvia Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Hefei China INFN Sezione di Padova Padova Italy Università di Padova Padova Italy University of Mississippi Oxford Mississi

The first evidence for the Higgs boson decay to a Z boson and a photon is presented, with a statistical significance of 3.4 standard deviations. The result is derived from a combined analysis of the searches performed by the ATLAS and CMS Collaborations with proton-proton collision datasets collected at the CERN Large Hadron Collider (LHC) from 2015 to 2018. These correspond to integrated luminosities of around 140 fb−1 for each experiment, at a center-of-mass energy of 13 TeV. The measured signal yield is 2.2±0.7 times the standard model prediction, and agrees with the theoretical expectation within 1.9 standard deviations.

关键词： Rare decays Higgs bosons W & Z bosons Hadron colliders

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Relay navigation strategy study on intelligent drive on urban roads

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The Journal of China Universities of Posts and Telecommunications 2016年第2期23卷 79-90页

作者： Gao Hongbo Zhang Xinyu An Lifeng Liu Yuchao Li Deyi State Key Laboratory of Software Development Environment Beihang University Beijing 100191 China Information Technology Center Tsinghua University Beijing 100083 China Department of Computer Science and Technology Tsinghua University Beijing 100083 China The 61th Institute of Electronic System Engineering Beijing 100039 China

In order to solve navigation problem of intelligent vehicle driving on urban roads and to achieve the navigation in intersection area, intersection transition area and section area. The relay navigation strategy and algorithm can solve the navigation problem of intelligent vehicle driving in typical urban roads such as intersection area, intersection transition area and section area, realizing seamless handover among different typical areas. Bezier curve function model was introduced to different typical areas, which solved the self-adaption recognition problem in different typical areas and revised positional accuracy with the help of cloud computing positioning service. In order to explain the strategy implement, an instance based on the strategy was adopted. Instance analysis indicates that as for the navigation problem in intersection area, intersection transition area and section area, if the relay navigation strategy is utilized, the self-adaption recognition problem in different typical areas can be handled. Based on the relay navigation strategy, the drive of intelligent vehicle on urban roads can effectively solve the self-adaption recognition problem in different typical areas in urban and further solve driving problems of intelligent vehicle of the same category in urban roads.

关键词： intelligent vehicle intelligent drive urban roads relay navigation strategy

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Classification of tongue images based on doublet and color space dictionary

Classification of tongue images based on doublet and color s...

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2016 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2016

作者： Cao, Guitao Ding, Jie Duan, Ye Tu, Liping Xu, Jiatuo Xu, Dong School of Computer Science and Software Engineering East China Normal University Shanghai200062 China Department of Computer Science University of Missouri ColumbiaMO65211 United States Department of TCM Information and Technology Center Shanghai University of TCM Shanghai China

ISBN: (纸本)9781509016105

Recently, pathological diagnosis plays a crucial role in many areas of medicine, and some researchers have proposed many models and algorithms for improving classification accuracy by extracting excellent feature or modifying the classifier. They have also achieved excellent results on pathological diagnosis using tongue images. However, pixel values can't express intuitive features of tongue images and different classifiers for training samples have different adaptability. Accordingly, this paper presents a robust approach to infer the pathological characteristics by observing tongue images. Our proposed method makes full use of the local information and similarity of tongue images. Firstly, tongue images in RGB color space are converted to Lab. Then, we compute tongue statistics information. In the calculation process, Lab space dictionary is created at first, through it, we compute statistic value for each dictionary value. After that, a method based on Doublets is taken for feature optimization. At last, we use XGBOOST classifier to predict the categories of tongue images. We achieve classification accuracy of 95.39% using statistics feature and the improved classifier, which is helpful for TCM (Traditional Chinese Medicine) diagnosis. © 2016 IEEE.

关键词： Image classification

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Combination of Measurements of the Top Quark Mass from Data Collected by the ATLAS and CMS Experiments at s=7 and 8 TeV

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Physical Review Letters 2024年第26期132卷 261902-261902页

作者： A. Hayrapetyan A. Tumasyan W. Adam J. W. Andrejkovic T. Bergauer S. Chatterjee K. Damanakis M. Dragicevic P. S. Hussain M. Jeitler N. Krammer A. Li D. Liko I. Mikulec J. Schieck R. Schöfbeck D. Schwarz M. Sonawane S. Templ W. Waltenberger C.-E. Wulz M. R. Darwish T. Janssen P. Van Mechelen E. S. Bols J. D’Hondt S. Dansana A. De Moor M. Delcourt H. El Faham S. Lowette I. Makarenko D. Müller A. R. Sahasransu S. Tavernier M. Tytgat S. Van Putte D. Vannerom B. Clerbaux G. De Lentdecker L. Favart D. Hohov J. Jaramillo A. Khalilzadeh K. Lee M. Mahdavikhorrami A. Malara S. Paredes L. Pétré N. Postiau L. Thomas M. Vanden Bemden C. Vander Velde P. Vanlaer M. De Coen D. Dobur Y. Hong J. Knolle L. Lambrecht G. Mestdach C. Rendón A. Samalan K. Skovpen N. Van Den Bossche J. van der Linden L. Wezenbeek A. Benecke G. Bruno C. Caputo C. Delaere I. S. Donertas A. Giammanco K. Jaffel Sa. Jain V. Lemaitre J. Lidrych P. Mastrapasqua K. Mondal T. T. Tran S. Wertz G. A. Alves E. Coelho C. Hensel T. Menezes De Oliveira A. Moraes P. Rebello Teles M. Soeiro W. L. Aldá Júnior M. Alves Gallo Pereira M. Barroso Ferreira Filho H. Brandao Malbouisson W. Carvalho J. Chinellato E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza R. Gomes De Souza J. Martins C. Mora Herrera K. Mota Amarilo L. Mundim H. Nogima A. Santoro A. Sznajder M. Thiel A. Vilela Pereira C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores P. G. Mercadante S. F. Novaes B. Orzari Sandra S. Padula A. Aleksandrov G. Antchev R. Hadjiiska P. Iaydjiev M. Misheva M. Shopova G. Sultanov A. Dimitrov L. Litov B. Pavlov P. Petkov A. Petrov E. Shumka S. Keshri S. Thakur T. Cheng Q. Guo T. Javaid L. Yuan Z. Hu J. Liu K. Yi G. M. Chen H. S. Chen M. Chen F. Iemmi C. H. Jiang A. Kapoor H. Liao Z.-A. Liu R. Sharma J. N. Song J. Tao C. Wang J. Wang Z. Wang H. Zhang A. Agapitos Y. Ban A. Levin C. Li Q. Li Y. Mao S. J. Qian X. Sun D. Wang H. Yang L. Zhang C. Zhou Z. You N. Lu G. Bauer X. Gao D. Leggat H. Okawa Y. Zhang Z. Lin C. Lu M. Xiao C. Avila D. A. Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Indian Institute of Technology Madras Madras India APC Université Paris Cité CNRS/IN2P3 Paris France Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Korea University Seoul Korea 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 IJCLab Université Paris-Saclay CNRS/IN2P3 91405 Orsay France 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 Department of Physics Oxford University Oxford United Kingdom School of Physics and Astronomy Shanghai Jiao Tong University Key Laboratory for Particle Astrophysics and Cosmology (MOE) SKLPPC Shanghai China Department of Physics Chinese University of Hong Kong Shatin N.T. Hong Kong China Department of Physics University of Michigan Ann Arbor Michigan USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Department of Modern Physics and State Key Laboratory of Particle Detection and Electronics University of Science and Technology of China Hefei China Department of Physics Nanjing University Nanjing China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE)—Fudan University Shanghai China Zhe

A combination of fifteen top quark mass measurements performed by the ATLAS and CMS experiments at the LHC is presented. The datasets used correspond to an integrated luminosity of up to 5 and 20 fb−1 of proton-proton collisions at center-of-mass energies of 7 and 8 TeV, respectively. The combination includes measurements in top quark pair events that exploit both the semileptonic and hadronic decays of the top quark, and a measurement using events enriched in single top quark production via the electroweak t channel. The combination accounts for the correlations between measurements and achieves an improvement in the total uncertainty of 31% relative to the most precise input measurement. The result is mt=172.52±0.14(stat)±0.30(syst) GeV, with a total uncertainty of 0.33 GeV.

关键词： Top quark Hadron colliders

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Detection of Rail Squats Based on Hilbert-Huang Transform by Using Bogie Acceleration Measurement

Detection of Rail Squats Based on Hilbert-Huang Transform by...

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第28届中国控制与决策会议

作者： Xiukun Wei Yuxin Liu Xianxian Yin State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Shanghai Key Laboratory of Computer Software Evaluating & Testing(Shanghai Development Center of Computer Software Technology)

ISBN: (纸本)9781467397155

The squat is a type of rolling contact fatigue(RCF) damage,the existence of squats directly impacts the operating condition of urban rail *** current detection methods of the rail squats damage are mainly based on track inspection car and rail flaw *** has some disadvantages,for example,long detection cycle,no real-time detecting and narrow scope,time consuming and *** this paper,a new detection method of squats which based on the in-service vehicles is *** bogie acceleration signal is used to detect the squats on the *** validate the possibility of the proposed *** the help of SIMPACK software,an in-service vehicle-track dynamic model and models of typical squats are built to generate the simulated bogie acceleration signals when the train wheels rolls over the *** simulation signals from the normal rail and the rail with squats are studied by HHT,it is found that0～50Hz and 300 Hz are the feature frequency caused by the squats damages.A unique W-shaped natural vibration mode is decomposed from the acceleration signals which is the feature vibration mode of the squat ***,the above detection method is applied to the field test data of shanghai metro line *** feasibility and reliability of the proposed method are *** proposed method provides an alternative for real application.

关键词： Squats In Service Vehicle Acceleration Signals SIMPACK HHT Field Test

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Complexity analysis and comparison of test paths based on DSE

Complexity analysis and comparison of test paths based on DS...

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ACIS International Conference on software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

作者： Jiawen Lu Lizhi Cai Yang Zhang Keyi Hong Laboratory of Computer Software Testing & Evaluation Shanghai Development Center of Computer Software Technology Shanghai China School of Information Science & Engineering East China University of Science and Technology Shanghai China Cyber Security Department of Shanghai Public Security Bureau Shanghai China

Dynamic symbolic execution (DSE) is a well-known program test technology which can generate test cases automatically through collecting constraints of the paths represented by symbolic value. Automated test based on DSE targets at covering all paths and branches in a limited time. Although DSE has been investigated for a few years, several challenges still exist which hinder the actual usage. Path explosion is one of the greatest challenges to solve, which decreases the test performance. Analyzing complexity of the execution paths of different test programs, and investigating the factors associated with the test efficiency become very important in the software testing life cycle.

关键词： Concrete Gold

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