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International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

作者： Apeksha Haveri Yeresime Suresh Department of Computer Science and Engineering BMS Institute of Technology & Management Bengaluru India Dept. of Comput. Sci. & Eng. BMS Inst. of Technol. & Manage. Bangalore India

ISBN: (纸本)9781538620458

Detecting faults in the initial stage of the development process has become an important prospect for the codes cost estimation; so a fault predictor model is very much necessary in order to bring down the cost of development and maintenance. Due to these reasons, developing models for fault prediction has become a crucial part of research, and various techniques have been adapted in order to predict faults in a software. Few of them include Artificial Neural Network, Decision Tree, Genetic Algorithm, etc. Among these techniques, Neural Networks and Genetic Algorithms have become a growing concern over the years and are being applied in various fields such as optimization, prediction or classification. These techniques make use of various software metrics to assess the characteristic of any software system such as number of faults, maintenance of class, etc. Most commonly used are Chidamber and Kemerer (CK) metrics which are found to be efficient from many researches.

关键词： Genetic algorithms Measurement Biological neural networks Predictive models Software quality

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Performance evaluation of distributed object hybrid storage systems for smart-living applications

Performance evaluation of distributed object hybrid storage ...

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2016 International Conference on Communication Problem-Solving, ICCP 2016

作者： Lu, Yung-Feng Kuo, Chin-Fu Li, Jhong-Syuan Chou, Shih-Chun Department of Computer Science and Information Engineering National Taichung University of Science and Technology Taiwan Department of Computer Science and Information Engineering National University of Kaohsiung Taiwan Innovative Digitech-Enabled Applic. and Services Inst. Institute for Information Industry Taiwan

ISBN: (纸本)9781509013838

This paper aims to evaluate the data storage performance with hybrid storage. In large scale smart-living applications, data require a smart and efficient manner to store daily living information. Object-based storage is a storage architecture that manages data as objects, as opposed to other storage architectures like file systems which manage data as a file hierarchy and block storage which manages data as blocks within sectors and tracks. In general, each object typically includes the data itself, a variable amount of metadata, and a globally unique identifier. Object storage seeks to enable capabilities not addressed by other storage architectures such as data replication and data distribution at object-level granularity. A distributed data store is a computer network where information is stored on more than one node, often in a replicated fashion. It is usually specifically used to refer to either a distributed database where users store information on a number of nodes, or a computer network in which users store information on a number of peer network nodes. In this paper, we focus on the performance evaluation of object data store behaviors on different types of storage. The evaluated result can provide good guideline for design of distributed object storage systems. © 2016 IEEE.

关键词： Digital storage

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Solving most systems of random quadratic equations 17

Solving most systems of random quadratic equations

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Proceedings of the 31st International Conference on Neural Information Processing Systems

作者： Gang Wang Georgios B. Giannakis Yousef Saad Jie Chen Key Lab of Intell. Contr. and Decision of Complex Syst. Beijing Inst. of Technology and Digital Tech. Center & Dept. of Electrical and Computer Eng. Univ. of Minnesota Digital Tech. Center & Dept. of Electrical and Computer Eng. Univ. of Minnesota Department of Computer Science and Engineering Univ. of Minnesota Key Lab of Intell. Contr. and Decision of Complex Syst. Beijing Inst. of Technology

ISBN: (纸本)9781510860964

This paper deals with finding an n-dimensional solution x to a system of quadratic equations yi = ||2, 1 ≤ i ≤ m, which in general is known to be NP-hard. We put forth a novel procedure, that starts with a weighted maximal correlation initialization obtainable with a few power iterations, followed by successive refinements based on iteratively reweighted gradient-type iterations. The novel techniques distinguish themselves from prior works by the inclusion of a fresh (re)weighting regularization. For certain random measurement models, the proposed procedure returns the true solution x with high probability in time proportional to reading the data {(ai; yi)]1≤i≤m, provided that the number m of equations is some constant c > 0 times the number n of unknowns, that is, m ≤ cn. Empirically, the upshots of this contribution are: i) perfect signal recovery in the high-dimensional regime given only an information-theoretic limit number of equations; and, ii) (near-)optimal statistical accuracy in the presence of additive noise. Extensive numerical tests using both synthetic data and real images corroborate its improved signal recovery performance and computational efficiency relative to state-of-the-art approaches.

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Development of a cyber-physical-style continuous yield improvement system for manufacturing industry

Development of a cyber-physical-style continuous yield impro...

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2016 IEEE International Conference on Automation science and engineering, CASE 2016

作者： Chen, Chao-Chun Hung, Min-Hsiung Li, Po-Yi Liu, Jia-Xuan Lin, Yu-Chuan Lee, Chih-Jen Inst. of Manf. Info. and Sys. National Cheng Kung University Taiwan Department of Computer Science and Information Engineering Chinese Culture University Taiwan

ISBN: (纸本)9781509024094

In the vision of the intelligent factory of industry 4.0, many enterprises are eager to increase the productivity by analysing the production data collected from equipment in runtime or products. Developing a continuous yield improvement system framework with big data capability shall gain an insight into the demands of continuous yield improvement. In this paper, we developed a cyber-physical-style continuous yield improvement system (CP-CYIS) with big data capability for providing a solution to rapidly construct the required yield improvement process for the shorter time on finding the root cause. The main idea is to divide a complete analytic flow into two part: the YI process describing only the flow without execution details and the YI action providing an analytic function for a YI process that involves the YI action. In this way, the development engineers can focus on the related modules that the process engineers concern. On the other hand, the executions of these actions are automated accomplished with assistances of the proposed system, so that the time spent on finding the root cause can be reduced. Finally, we deploy the CP-CYIS to a private cloud based on VMWare, and apply the CP-CYIS to a semiconductor factory for conducting integrated tests. Testing results of a case study show that the CP-CYIS has similar execution performance to the traditional solution. The development of this paper can provide a useful reference for industrial practitioners of the manufacturing industry to construct cyber-physical-style manufacturing systems. © 2016 IEEE.

关键词： Big data

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Toward argumentation-based cyber attribution 30

Toward argumentation-based cyber attribution

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30th AAAI Conference on Artificial Intelligence, AAAI 2016

作者： Nunes, Eric Shakarian, Paulo Simari, Gerardo I. Arizona State University TempeAZ85281 United States Inst. for Computer Science and Engineering Univ. Nac. del Sur-CONICET Bahia Blanca Argentina

ISBN: (纸本)9781577357599

A major challenge in cyber-threat analysis is combining information from different sources to find the person or the group responsible for the cyber-attack. It is one of the most important technical and policy challenges in cyber-security. The lack of ground truth for an individual responsible for an attack has limited previous studies. In this paper, we overcome this limitation by building a dataset from the capture-the-flag event held at DEFCON, and propose an argumentation model based on a formal reasoning framework called DeLP (Defeasible Logic Programming) designed to aid an analyst in attributing a cyber-attack to an attacker. We build argumentation-based models from latent variables computed from the dataset to reduce the search space of culprits (attackers) that an analyst can use to identify the attacker. We show that reducing the search space in this manner significantly improves the performance of classification-based approaches to cyber-attribution. Copyright © 2016, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Crime

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In-Situ Multi-View Multi-Scattering Stochastic Tomography

In-Situ Multi-View Multi-Scattering Stochastic Tomography

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IEEE International Conference on Computational Photography

作者： Vadim Holodovsky Yoav Y. Schechner Anat Levin Aviad Levis Amit Aides Viterbi Faculty of Electrical Engineering Technion - Israel Inst. Technology Dept. Mathematics and Computer Science Weizmann Inst. Science

ISBN: (纸本)9781467386241

To recover the three dimensional (3D) volumetric matter distribution in an object, the object is imaged from multiple directions and locations. Using these images, tomographic computations seek the distribution. When scattering is significant and under constrained irradiance, tomography must explicitly account for off-axis scattering. Furthermore, tomographic recovery must function when imaging is done in-situ, as occurs in medical imaging and ground-based at-mospheric sensing. We formulate tomography that handles arbitrary orders of scattering, using a Monte-Carlo model. The model is highly parallelizable in our formulation. This can enable large scale rendering and recovery of volumetric scenes having a large number of variables. We solve stability and conditioning problems that stem from radiative transfer modeling in-situ.

关键词： Tomography Scattering Medical imaging broadcasting radiative transfer

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First Search for Exclusive Diphoton Production at High Mass with Tagged Protons in Proton-Proton Collisions at s=13 TeV

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Physical Review Letters 2022年第1期129卷 011801-011801页

作者： A. Tumasyan W. Adam T. Bergauer M. Dragicevic J. Erö A. Escalante Del Valle R. Frühwirth M. Jeitler N. Krammer L. Lechner D. Liko I. Mikulec F. M. Pitters N. Rad J. Schieck R. Schöfbeck M. Spanring S. Templ W. Waltenberger C.-E. Wulz M. Zarucki V. Chekhovsky A. Litomin V. Makarenko J. Suarez Gonzalez M. R. Darwish E. A. De Wolf D. Di Croce X. Janssen T. Kello A. Lelek M. Pieters H. Rejeb Sfar H. Van Haevermaet P. Van Mechelen S. Van Putte N. Van Remortel F. Blekman E. S. Bols S. S. Chhibra J. D’Hondt J. De Clercq D. Lontkovskyi S. Lowette I. Marchesini S. Moortgat A. Morton Q. Python S. Tavernier W. Van Doninck P. Van Mulders D. Beghin B. Bilin B. Clerbaux G. De Lentdecker B. Dorney L. Favart A. Grebenyuk A. K. Kalsi I. Makarenko L. Moureaux L. Pétré A. Popov N. Postiau E. Starling L. Thomas C. Vander Velde P. Vanlaer D. Vannerom L. Wezenbeek T. Cornelis D. Dobur M. Gruchala I. Khvastunov M. Niedziela C. Roskas K. Skovpen M. Tytgat W. Verbeke B. Vermassen M. Vit G. Bruno F. Bury C. Caputo P. David C. Delaere M. Delcourt I. S. Donertas A. Giammanco V. Lemaitre K. Mondal J. Prisciandaro A. Taliercio M. Teklishyn P. Vischia S. Wertz S. Wuyckens G. A. Alves C. Hensel A. Moraes W. L. Aldá Júnior E. Belchior Batista Das Chagas H. Brandao Malbouisson W. Carvalho J. Chinellato E. Coelho E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza J. Martins D. Matos Figueiredo M. Medina Jaime C. Mora Herrera L. Mundim H. Nogima P. Rebello Teles L. J. Sanchez Rosas A. Santoro S. M. Silva Do Amaral A. Sznajder M. Thiel F. Torres Da Silva De Araujo A. Vilela Pereira C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores D. S. Lemos P. G. Mercadante S. F. Novaes Sandra S. Padula A. Aleksandrov R. Hadjiiska P. Iaydjiev M. Misheva M. Rodozov M. Shopova G. Sultanov A. Dimitrov T. Ivanov L. Litov B. Pavlov P. Petkov A. Petrov T. Cheng W. Fang Q. Guo H. Wang L. Yuan M. Ahmad G. Bauer Z. Hu Y. Wang K. Yi E. Chapon G. M. Chen H. S. Chen M. Chen T. Javaid A. Kapoor D. Leggat H. Liao Z.-A. Liu R. Sharma A Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Institute for Nuclear Problems Minsk Belarus 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 São Paulo Brazil 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 Beihang University Beijing China Rutgers The State University of New Jersey Piscataway New Jersey USA Department of Physics Tsinghua University Tsinghua China University of Virginia Charlottesville Virginia USA Institute of High Energy Physics Beijing China Massachusetts Institute of Technology Cambridge Massachusetts USA State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China The University of Kansas Lawrence Kansas USA Sun Yat-Sen University Guangzhou China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE)—Fudan University Shanghai China Zhejiang University 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 E

A search for exclusive two-photon production via photon exchange in proton-proton collisions, pp→pγγp with intact protons, is presented. The data correspond to an integrated luminosity of 9.4 fb−1 collected in 2016 using the CMS and TOTEM detectors at a center-of-mass energy of 13 TeV at the LHC. Events are selected with a diphoton invariant mass above 350 GeV and with both protons intact in the final state, to reduce backgrounds from strong interactions. The events of interest are those where the invariant mass and rapidity calculated from the momentum losses of the forward-moving protons match the mass and rapidity of the central, two-photon system. No events are found that satisfy this condition. Interpreting this result in an effective dimension-8 extension of the standard model, the first limits are set on the two anomalous four-photon coupling parameters. If the other parameter is constrained to its standard model value, the limits at 95% confidence level are |ζ1|<2.9×10−13 GeV−4 and |ζ2|<6.0×10−13 GeV−4.

关键词： Hypothetical scalars Photons Protons Hadron colliders

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A Fast and Simple Algorithm for Computing Approximate Euclidean Minimum Spanning Trees 16

A Fast and Simple Algorithm for Computing Approximate Euclid...

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Annual ACM-Society for Industrial and Applied Mathmatics Symposium on Discrete Algorithms

作者： Sunil Arya David M. Mount Dept. of Computer Science and Engineering The Hong Kong University of Science and Technology Dept. of Computer Science and Inst. for Advanced Computer Studies University of Maryland

ISBN: (纸本)9781510819672

The Euclidean minimum spanning tree (EMST) is a fundamental and widely studied structure. In the approximate version we are given an n-element point set P in Rd and an error parameter ε > 0, and the objective is to compute a spanning tree over P whose weight is at most (1 + ε) times that of the true minimum spanning tree. Assuming that d is a fixed constant, existing algorithms have running times that (up to logarithmic factors) grow as O(n/ε~(Ω(d))). We present an algorithm whose running time is O(n log n+(ε~(-2) log~2 1/ε)n). Thus, this is the first algorithm for approximate EMSTs that eliminates the exponential ε dependence on dimension. (Note that the O-notation conceals a constant factor of the form O(1)~d.) The algorithm is deterministic and very simple.

关键词： Euclidean minimum spanning trees Well-separated pair decompositions Approximation algorithms Approximation algorithms Spanning tree Runtime algorithms Euclidean Approximate minimum error parameter

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Composite FDIA and topology attack on the electricity market

Composite FDIA and topology attack on the electricity market

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IEEE General Meeting Power& Energy Society

作者： Gaoqi Liang Steven R. Weller Junhua Zhao Fengji Luo Yang Dong Zhao Center for Intelligent Electricity Networks (CIEN) University of Newcastle Callaghan NSW Australia School of Electrical Engineering and Computer Science University of Newcastle Callaghan NSW Australia Chinese University of Hong Kong (Shenzhen) Shenzhen Guangdong China School of Civil Engineering The University of Sydney Sydney NSW Australia CSG Electr. Power Res. Inst. Guangzhou China

Cyber-attacks pose significant hazards to the secure and economic operation of modern power systems. This paper proposes a composite false data injection attack (FDIA) and cyber topology attack capable of disturbing conventional transactions in the electricity market. The Australian electricity market mechanism is considered, wherein each trading period is comprised of six 5-minute security-constraint economic dispatch (SCED) intervals. In the proposed attack, the manipulation of cyber-topology information over the 30-minute horizon is considered, with the attack objective being the malicious increase in the costs borne by customers in the market. The proposed attack poses no security threat to the power system, affecting only the economic costs to customers. A defining feature of the proposed algorithm is the joint consideration of both topology error processing and bad data detection constraints in order to ensure validity of the proposed attack. The differential evolution (DE) algorithm is used to find the corresponding attack strategies. Case studies are conducted to validate the proposed attack methodology.

关键词： Smart grids Topology Security Electricity supply industry TV Load flow DH-HEMTs

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Extracting Semantic Knowledge from Unstructured Text Using Embedded Controlled Language

Extracting Semantic Knowledge from Unstructured Text Using E...

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International Conference on Semantic Computing

作者： Hazem Safwat Normunds Gruzitis Brian Davis Ramona Enache Insight Centre for Data Analytics National University of Ireland Galway Inst. of Mathematics and Computer Science University of Latvia Dept of Computer Science and Engineering University of Gothenburg

ISBN: (纸本)9781509006632

Nowadays, most of the data on the Web is still in the form of unstructured text. Knowledge extraction from unstructured text is highly desirable but extremely challenging due to the inherent ambiguity of natural language. In this article, we present an architecture of an information extraction system based on the concept of Embedded Controlled Language that allows for extracting formal semantic knowledge from an unstructured text corpus. Moreover, the presented approach has a potential to support multilingual input and output.

关键词： Grammar Syntactics Semantics Natural languages Data mining Concrete Conferences

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