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International Workshop on Managing Technical Debt (MTD)

作者： Areti Ampatzoglou Apostolos Ampatzoglou Alexander Chatzigeorgiou Paris Avgeriou Pekka Abrahamsson Antonio Martini Uwe Zdun Kari Systa Department of Computer Science University of Groninzen Groninzen Netherlands Department of Applied Informatics University of Macedonia Thessaloniki Greece Department of Computer and Information Science National Technical University of Norway Trondheim Norway Department of Computer Science and Engineering Chalmers University of Technology Gothenburg Sweden Faculty of Computer Science University of Vienna Vienna Austria Department of Software Systems Technical University of Tampere Tampere Finland

ISBN: (纸本)9781509038558

Technical Debt Management (TDM) has drawn the attention of software industries during the last years, including embedded systems. However, we currently lack an overview of how practitioners from this application domain perceive technical debt. To this end, we conducted a multiple case study in the embedded systems industry, to investigate: (a) the expected life-time of components that have TD, (b) the most frequently occurring types of TD in them, and (c) the significance of TD against run-time quality attributes. The case study was performed on seven embedded systems industries (telecommunications, printing, smart manufacturing, sensors, etc.) from five countries (Greece, Netherlands, Sweden, Austria, and Finland). The results of the case study suggest that: (a) maintainability is more seriously considered when the expected lifetime of components is larger than ten years, (b) the most frequent types of debt are test, architectural, and code debt, and (c) in embedded systems the run-time qualities are prioritized compared to design-time qualities that are usually associated with TD. The obtained results can be useful for both researchers and practitioners: the former can focus their research on the most industrially-relevant aspects of TD, whereas the latter can be informed about the most common types of TD and how to focus their TDM processes.

关键词： Embedded systems Industries Companies Embedded software Time division multiplexing Context

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A separability-entanglement classifier via machine learning

arXiv

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arXiv 2017年

作者： Lu, Sirui Huang, Shilin Li, Keren Li, Jun Chen, Jianxin Lu, Dawei Ji, Zhengfeng Shen, Yi Zhou, Duanlu Zeng, Bei Department of Physics Tsinghua University Beijing100084 China Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Beijing Computational Science Research Center Beijing100193 China Department of Mathematics & Statistics University of Guelph GuelphONN1G 2W1 Canada Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD United States Department of Physics Southern University of Science and Technology Shenzhen518055 China Centre for Quantum Computation & Intelligent Systems School of Software Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Department of Statistics and Actuarial Science University of Waterloo WaterlooONN2L 3G1 Canada Institute of Physics Chinese Academy of Sciences Beijing100190 China

The problem of determining whether a given quantum state is entangled lies at the heart of quantum information processing, which is known to be an NP-hard problem in general. Despite the proposed many methods such as the positive partial transpose (PPT) criterion and the k-symmetric extendibility criterion to tackle this problem in practice, none of them enables a general, effective solution to the problem even for small dimensions. Explicitly, separable states form a high-dimensional convex set, which exhibits a vastly complicated structure. In this work, we build a new separability-entanglement classifier underpinned by machine learning techniques. Our method outperforms the existing methods in generic cases in terms of both speed and accuracy, opening up the avenues to explore quantum entanglement via the machine learning approach. Copyright © 2017, The Authors. All rights reserved.

关键词： Quantum entanglement

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Hybrid Clustering-GWO-NARX neural network technique in predicting stock price

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Journal of Physics: Conference Series 2017年第1期892卷

作者： Debashish Das Ali Safa Sadiq Seyedali Mirjalili A. Noraziah Faculty of Computer Systems & Software Engineering University Malaysia Pahang Kuantan Pahang Darul Makmur Malaysia Faculty of Computing Engineering and Technology Asia Pacific University of Technology and Innovation TPM Bukit Jalil Kuala Lumpur 57000 Malaysia School of Information Technology Monash University 46150 Bandar Sunway Malaysia School of Information and Communication Technology Griffith University Nathan Campus Brisbane QLD 4111 Australia

Prediction of stock price is one of the most challenging tasks due to nonlinear nature of the stock data. Though numerous attempts have been made to predict the stock price by applying various techniques, yet the predicted price is not always accurate and even the error rate is high to some extent. Consequently, this paper endeavours to determine an efficient stock prediction strategy by implementing a combinatorial method of Grey Wolf Optimizer (GWO), Clustering and Non Linear Autoregressive Exogenous (NARX) Technique. The study uses stock data from prominent stock market i.e. New York Stock Exchange (NYSE), NASDAQ and emerging stock market i.e. Malaysian Stock Market (Bursa Malaysia), Dhaka Stock Exchange (DSE). It applies K-means clustering algorithm to determine the most promising cluster, then MGWO is used to determine the classification rate and finally the stock price is predicted by applying NARX neural network algorithm. The prediction performance gained through experimentation is compared and assessed to guide the investors in making investment decision. The result through this technique is indeed promising as it has shown almost precise prediction and improved error rate. We have applied the hybrid Clustering-GWO-NARX neural network technique in predicting stock price. We intend to work with the effect of various factors in stock price movement and selection of parameters. We will further investigate the influence of company news either positive or negative in stock price movement. We would be also interested to predict the Stock indices.

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Adaptive Tutoring System User Preferences: Does Gender Matter?

Adaptive Tutoring System User Preferences: Does Gender Matte...

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International Conference on Information and Communication Technology for the Muslim World (ICT4M)

作者： Faizal Hazri Mat Ripin Rahmah Mokhtar Wahidah Mohd Zain Universiti Malaysia Pahang Kuantan Pahang MY Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang (UMP) Gambang Pahang Malaysia Department of Library and Information Science International Islamic University of Malaysia (IIUM) Gombak Kuala Lumpur Malaysia

ISBN: (纸本)9781509045228

The adaptive tutoring system is one of the applications in teaching and learning processes, providing worldwide accessibility and all-day availability. Apparently, studies on user preference across gender for adaptive tutoring systems remain scarce among university users in Malaysia. With the aim of describing the differences between genders in user preferences for the method of gaining information, online games, online movies, online music, pictures, as well as colors of the adaptive tutoring system, this paper used quantitative methods through data gathering for finding the results of this study. Sixty-eight respondents were chosen from among academicians, administrative staff and students of a public university in Malaysia. Descriptive analysis of the data shows that there exists a pattern of different preferences for adaptive tutoring systems across gender. This paper provides data supporting the need to design different interfaces for male and female users.

关键词： Adaptive systems Color Games Motion pictures Libraries Image color analysis Adaptation models

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Quantum State Tomography via Reduced Density Matrices

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Physical Review Letters 2017年第2期118卷 020401-020401页

作者： Tao Xin Dawei Lu Joel Klassen Nengkun Yu Zhengfeng Ji Jianxin Chen Xian Ma Guilu Long Bei Zeng Raymond Laflamme State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics Tsinghua University Beijing 100084 China Institute for Quantum Computing University of Waterloo Waterloo Ontario N2L 3G1 Canada Department of Physics University of Guelph Guelph N1G 2W1 Ontario Canada Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney New South Wales 2007 Australia Department of Mathematics and Statistics University of Guelph Guelph N1G 2W1 Ontario Canada State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences 100190 Beijing China Joint Center for Quantum Information and Computer Science University of Maryland College Park Maryland USA Department of Physics and Astronomy University of Waterloo Waterloo Ontario N2L 3G1 Canada Canadian Institute for Advanced Research Toronto M5G 1Z8 Ontario Canada Perimeter Institute for Theoretical Physics Waterloo Ontario N2L 2Y5 Canada

Quantum state tomography via local measurements is an efficient tool for characterizing quantum states. However, it requires that the original global state be uniquely determined (UD) by its local reduced density matrices (RDMs). In this work, we demonstrate for the first time a class of states that are UD by their RDMs under the assumption that the global state is pure, but fail to be UD in the absence of that assumption. This discovery allows us to classify quantum states according to their UD properties, with the requirement that each class be treated distinctly in the practice of simplifying quantum state tomography. Additionally, we experimentally test the feasibility and stability of performing quantum state tomography via the measurement of local RDMs for each class. These theoretical and experimental results demonstrate the advantages and possible pitfalls of quantum state tomography with local measurements.

关键词： Quantum entanglement Quantum information processing Quantum tomography Random matrix theory

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A formulation of rod based nonlinear model predictive control of nuclear reaction with temperature effects and Xenon poisoning 23

A formulation of rod based nonlinear model predictive contro...

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23rd International Conference on Nuclear engineering: Nuclear Power - Reliable Global Energy, ICONE 2015

作者： Teatro, Timothy A.V. McNelles, Phillip Eklund, J. Mikael Department of Electrical Computer and Software Engineering University of Ontario Institute of Technology OshawaON Canada Faculty of Energy Systems and Nuclear Science University of Ontario Institute of Technology OshawaON Canada

ISBN: (纸本)9784888982566

This paper presents a formulation of a nonlinear model predictive controller for steering of a nuclear reaction in a pressurized water reactor via control rod displacement. The predictive model, based on point kinetic equations, includes an averaged delayed neutron group, thermal dependence on reactivity, heat exchange between temperature and moderator and Xenon poisoning. From the model, a finite horizon optimal control problem is cast in the form of a control Hamiltonian minimization. A basic gradient descent scheme is derived to solve the optimal control problem. The predictive model and gradient descent are used to form the basis from which the model predictive controller is formulated. Copyright © 2015 by JSME.

关键词： Model predictive control

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Quantum state and process tomography via adaptive measurements

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Science China(Physics,Mechanics & Astronomy) 2016年第10期59卷 25-32页

作者： HengYan Wang WenQiang Zheng NengKun Yu KeRen Li DaWei Lu Tao Xin Carson Li ZhengFeng Ji David Kribs Bei Zeng XinHua Peng JiangFeng Du Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics University of Science and Technology of ChinaHefei 230026China Department of Applied Physics Zhejiang University of TechnologyHangzhou 310023China Institute for Quantum Computing University of WaterlooWaterloo N2L 3G1Canada 4Department of Mathematics&Statistics University of GuelphGuelph N1G 2W1Canada Centre for Quantum Computation&Intelligent Systems Faculty of Engineering and Information TechnologyUniversity of Technology SydneySydney NSW 2007Australia State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics Tsinghua UniversityBeijing 100084China Department of Physics University of GuelphGuelph N1G 2W1Canada State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China Canadian Institute for Advanced Research Toronto M5G 1Z8Canada

We investigate quantum state tomography(QST) for pure states and quantum process tomography(QPT) for unitary channels via adaptive measurements. For a quantum system with a d-dimensional Hilbert space, we first propose an adaptive protocol where only 2d. 1 measurement outcomes are used to accomplish the QST for all pure states. This idea is then extended to study QPT for unitary channels, where an adaptive unitary process tomography(AUPT) protocol of d2+d.1measurement outcomes is constructed for any unitary channel. We experimentally implement the AUPT protocol in a 2-qubit nuclear magnetic resonance system. We examine the performance of the AUPT protocol when applied to Hadamard gate, T gate(/8 phase gate), and controlled-NOT gate,respectively, as these gates form the universal gate set for quantum information processing purpose. As a comparison, standard QPT is also implemented for each gate. Our experimental results show that the AUPT protocol that reconstructing unitary channels via adaptive measurements significantly reduce the number of experiments required by standard QPT without considerable loss of fidelity.

关键词： quantum tomography state reconstruction nuclear magnetic resonance

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Design a technique for minimizing unnecessary handoff in mobile wireless networks

Design a technique for minimizing unnecessary handoff in mob...

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International Conference on software engineering and computer systems (ICSECS)

作者： Md. Arafatur Rahman Qusay Medhat Salih Mohamad Fadli Bin Zolkipli Faculty of Computer Systems and Software Engineering Universiti Malaysia Pahang Kuantan Pahang MY Faculty of Computer Systems and Software Engineering University Malaysia Pahang Pahang Malaysia Faculty of Computer Systems and Software Engineering University Malaysia Pahang Malaysia

Unnecessary handoff is one of the key issues in mobile wireless network, since it consumes the network's resources that degrades the performance of the network. Handoff appears when the Receive Signal Strength (RSS) of a mobile node becomes below threshold value (i.e., an acceptable level of RSS for ensuring communication). Subsequently, the mobile node starts scanning to discover a new RSS from neighbors Access Point (AP) to keep continuing the communication. However, traditional handoff algorithm is not accurate due to only depend on the RSS. It is affected by many factors (e.g., shadowing, scattering, reflection, etc.) that initiate unnecessary handoff decision. In this paper, a new technique is proposed to mitigate the unnecessary handoff. The simulation result confirms the effectiveness of the proposal.

关键词： Manganese Estimation Wireless LAN Mobile nodes Mobile computing

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Anonymous yoking-group proofs 15

Anonymous yoking-group proofs

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10th ACM Symposium on Information, computer and Communications Security, ASIACCS 2015

作者： Li, Nan Mu, Yi Susilo, Willy Varadharajan, Vijay Centre for Computer and Information Security School of Computer Science and Software Engineering University of Wollongong Wollongong Australia Information and Networked Systems Security Research Department of Computing Faculty of Science Macquarie University Sydney Australia

ISBN: (纸本)9781450332453

Yoking-proofs show an interesting application in Radio Frequency Identification (RFID) that a verifier can check whether two tags are simultaneously scanned by a reader. We consider a scenario that multi-group of tags can be proved to be scanned simultaneously. Grouping-proof, which is an extension of yoking-proofs, allows multiple tags to be proved together, while existing protocols cannot support multiple groups. In this paper, we introduce a novel concept called "yoking-group proofs". Additionally, we propose an anonymous yoking-proof protocol and an anonymous yoking-group proof protocol and prove their security in Universal Composability framework. Copyright © 2015 ACM.

关键词： Radio frequency identification (RFID)

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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