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International Conference on Simulation of Semiconductor Processes and Devices (SISPAD)

作者： Zizhen Jiang Shimeng Yu Yi Wu Jesse H. Engel Ximeng Guan H.-S. Philip Wong Department of Electrical Engineering Stanford University Stanford CA USA School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ USA Oracle America Inc. CA USA IBM Research NY USA Stanford University Stanford CA US

We demonstrate a dynamic Verilog-A RRAM compact model capable of simulating real-time DC cycling and pulsed operation device behavior, including random variability that is inherent to RRAM. This paper illustrates the physics and capabilities of the model. The model is verified using different sets of experimental data. The DC/Pulse parameter fitting methodology are illustrated.

关键词： Fitting Switches Integrated circuit modeling Hardware design languages Resistance Mathematical model

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Formal property verification in a conformance testing framework

Formal property verification in a conformance testing framew...

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ACM and IEEE International Conference on Formal Methods and Models for Co-Design (MEMOCODE)

作者： Houssam Abbas Hans Mittelmann Georgios Fainekos School of Electrical Energy and Computer Engineering Arizona State University Tempe AZ U.S.A. School of Mathematical and Statistical Sciences Arizona State University Tempe AZ U.S.A. School of Computing Informatics and Decision Systems Arizona State University Tempe AZ U.S.A.

In model-based design of cyber-physical systems, such as switched mixed-signal circuits or software-controlled physical systems, it is common to develop a sequence of system models of different fidelity and complexity, each appropriate for a particular design or verification task. In such a sequence, one model is often derived from the other by a process of simplification or implementation. E.g. a Simulink model might be implemented on an embedded processor via automatic code generation. Three questions naturally present themselves: how do we quantify closeness between the two systems? How can we measure such closeness? If the original system satisfies some formal property, can we automatically infer what properties are then satisfied by the derived model? This paper addresses all three questions: we quantify the closeness between original and derived model via a distance measure between their outputs. We then propose two computational methods for approximating this closeness measure. Finally, we derive syntactical re-writing rules which, when applied to a Metric Temporal Logic specification satisfied by the original model, produce a formula satisfied by the derived model. We demonstrate the soundness of the theory with several experiments.

关键词： Computational modeling Testing Integrated circuit modeling Educational institutions Software packages Switches Measurement

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Non-intrusive process-based monitoring system to mitigate and prevent VM vulnerability explorations

Non-intrusive process-based monitoring system to mitigate an...

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9th IEEE International Conference on Collaborative computing: Networking, Applications and Worksharing, COLLABORATECOM 2013

作者： Chung, Chun-Jen Cui, Jingsong Khatkar, Pankaj Huang, Dijiang School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ United States Computing School Wuhan University Wuhan China

ISBN: (纸本)9781936968923

Cloud is gaining momentum but its true potential is hampered by the security concerns it has raised. Having vulnerable virtual machines in a virtualized environment is one such concern. Vulnerable virtual machines are an easy target and existence of such weak nodes in a network jeopardizes its entire security structure. Resource sharing nature of cloud favors the attacker, in that, compromised machines can be used to launch further devastating attacks. First line of defense in such case is to prevent vulnerabilities of a cloud network from being compromised and if not, to prevent propagation of the attack. To create this line of defense, we propose a hybrid intrusion detection framework to detect vulnerabilities, attacks, and their carriers, i.e. malicious processes in the virtual network and virtual machines. This framework is built on attack graph based analytical models, VMM-based malicious process detection, and reconfigurable virtual network-based countermeasures. The proposed framework leverages Software Defined Networking to build a monitor and control plane over distributed programmable virtual switches in order to significantly improve the attack detection and mitigate the attack consequences. The system and security evaluations demonstrate the efficiency and effectiveness of the proposed solution. © 2013 ICST.

关键词： Software defined networking

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Scaling and correlation of human movements in cyberspace and physical space

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Physical Review E 2014年第5期90卷 050802(R)-050802(R)页

作者： Zhi-Dan Zhao Zi-Gang Huang Liang Huang Huan Liu Ying-Cheng Lai Web Sciences Center University of Electronic Science and Technology of China Chengdu 610054 China School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Institute of Computational Physics and Complex Systems and Key Laboratory for Magnetism and Magnetic Materials of MOE Lanzhou University Lanzhou Gansu 730000 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Arizona State University Tempe Arizona 85287 USA

Understanding the dynamics of human movements is key to issues of significant current interest such as behavioral prediction, recommendation, and control of epidemic spreading. We collect and analyze big data sets of human movements in both cyberspace (through browsing of websites) and physical space (through mobile towers) and find a superlinear scaling relation between the mean frequency of visit 〈f〉 and its fluctuation σ:σ∼〈f〉β with β≈1.2. The probability distribution of the visiting frequency is found to be a stretched exponential function. We develop a model incorporating two essential ingredients, preferential return and exploration, and show that these are necessary for generating the scaling relation extracted from real data. A striking finding is that human movements in cyberspace and physical space are strongly correlated, indicating a distinctive behavioral identifying characteristic and implying that the behaviors in one space can be used to predict those in the other.

关键词： CYBERSPACE CORRELATION (Statistics) HUMAN mechanics BEHAVIORAL research PREDICTION models EPIDEMIOLOGY -- Mathematical models

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Using transient thermal models to predict cyberphysical phenomena in data centers

Using transient thermal models to predict cyberphysical phen...

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作者： Varsamopoulos, Georgios Jonas, Michael Ferguson, Joshua Banerjee, Joydeep Gupta, Sandeep K.S. School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85287-8809 United States

Designing and configuring the layout of data centers, as well as testing thermal-aware decision (e.g., scheduling) algorithms has been hindered by the use of CFD simulations, which are considerably slow and are not that flexible in integrating cyber behavior (e.g., workload scheduling). Fast thermal mapping techniques on the other hand may rely on wrong assumptions (e.g., steady state) and thusly produce incorrect conclusions or they can be unusable because of cyber-physical interactions that rely on transient phenomena (e.g., transient hot spots that cause throttling). In this paper, we propose to speed up the evaluation of designs and algorithms with the use of a heat transfer model that captures transient behavior. We demonstrate its physical relevance, provide a methodology in yielding its parameters from experiments, and show how it can be combined with heat generation and cooling models to create a complete minimal data center system model, which can be simulated in only a small fraction of a CFD simulation time.© 2013 Elsevier Inc. All rights reserved.

关键词： Scheduling algorithms

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Methods for Evaluating Medical Tests and Biomarkers

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Diagnostic and Prognostic Research 2017年第1期1卷 1-34页

作者： Gowri Gopalakrishna Miranda Langendam Patrick Bossuyt Mariska Leeflang Rob Scholten Anna Noel-Storr James Thomas Iain Marshall Byron Wallace Penny Whiting Clare Davenport Gowri GopalaKrishna Isabel de Salis Sue Mallett Robert Wolff Marie Westwood Jos Kleinen Richard Riley Gary Collins Hans Reitsma Karel Moons Antonia Zapf Katharina Kramer Annika Hoyer Oliver Kuss J. Ensor R. D. Riley J. J. Deeks E. C. Martin Gerta Rücker Martin Schumacher Susanne Steinhauser Joie Ensor Kym Snell Brian Willis Jon Deeks Thomas Debray Lavinia Ferrante di Ruffano Sian Taylor-Phillips Chris Hyde Stuart A. Taylor Gauraang Batnagar Lavinia Ferrante Di Ruffano Farah Seedat Aileen Clarke Sarah Byron Frances Nixon Rebecca Albrow Thomas Walker Carla Deakin Zhivko Zhelev Harriet Hunt Yaling Yang Lucy Abel James Buchanan Thomas Fanshawe Bethany Shinkins Laure Wynants Sabine Van Huffel Jan Verbakel Dirk Timmerman Ben Van Calster Aeliko Zwinderman Jason Oke Jack O’Sullivan Rafael Perera Brian Nicholson Hannah L. Bromley Tracy E. Roberts Adele Francis Denniis Petrie G. Bruce Mann Kinga Malottki Holly Smith Lucinda Billingham Alice Sitch Oke Gerke Mie Holm-Vilstrup Eivind Antonsen Segtnan Ulrich Halekoh Poul Flemming Høilund-Carlsen Bernard G. Francq Jac Dinnes Julie Parkes Walter Gregory Jenny Hewison Peter Selby Doug Altman William Rosenberg Julien Asselineau Paul Perez Aïssatou Paye Emilie Bessede Cécile Proust-Lima Christiana Naaktgeboren Joris de Groot Johannes Reitsma Anne Rutjes Emmanuel Ogundimu Jonathan Cook Yannick Le Manach Yvonne Vergouwe Romin Pajouheshnia Rolf Groenwold Karen Moons Linda Peelen Bavo De Cock Daan Nieboer Ewout W. Steyerberg Micael J. Pencina Jennifer Cooper Nick Parsons Chris Stinton Steve Smith Andy Dickens Rachel Jordan Alexandra Enocson David Fitzmaurice Peymane Adab Charles Boachie Gaj Vidmar Karoline Freeman Martin Connock Rachel Court Carl Moons Jessica Harris Zoe Plummer Barnaby Reeves Chris Rogers Andrew Mumford Kurtis Lee Veerle Verheyden Gianni D. Angelini Gavin J. Murphy Jeremy Huddy Melody Ni George Hanna Department of Clinical Epidemiology Biostatistics & Bioinformatics Academic Medical Center University of Amsterdam Amsterdam The Netherlands Department of Clinical Epidemiology and Biostatistics Academic Medical Center University of Amsterdam Amsterdam Netherlands Cochrane Netherlands Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht Netherlands Cochrane Dementia and Cognitive Improvement Group University of Oxford Oxford UK EPPI-Centre Department of Social Science University College London London UK Division of Health and Social Care Research King’s College London London UK College of Computer and Information Science Northeastern University Boston USA University Hospitals Bristol NHS Foundation Trust School of Social and Community Medicine Bristol UK Institute of Applied Health Research University of Birmingham Birmingham UK School of Social and Community Medicine University of Bristol Bristol UK Kleijnen Systematic Reviews Ltd York UK Research Institute for Primary Care and Health Sciences Keele University Keele UK Centre for Statistics in Medicine Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences University of Oxford Oxford UK Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht The Netherlands Cochrane Netherlands University Medical Center Utrecht Utrecht The Netherlands Julius Center for Health Sciences and Primary Care University Medical Center Utrecht 3584 CG Utrecht Netherlands Department of Medical Statistics University Medical Center Göttingen Göttingen Germany Institute for Biometry and Epidemiology German Diabetes Center Leibniz Institute for Diabetes Research at Heinrich Heine University Düsseldorf Germany Manchester Pharmacy School University of Manchester Manchester UK Institute for Medical Biometry and Statistics Faculty of Medicine and Medical Center – University of Freiburg Stefan-Meier-Str. 26 79104 Freiburg Germany

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Evaluation of a meta-tutor for constructing models of dynamic systems 1

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16th International Conference on Artificial Intelligence in Education, AIED 2013

作者： Zhang, Lishan Burleson, Winslow Chavez-Echeagaray, Maria Elena Girard, Sylvie Gonzalez-Sanchez, Javier Hidalgo-Pontet, Yoalli Vanlehn, Kurt Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85281 United States

ISBN: (数字)9783642391125

ISBN: (纸本)9783642391118

While modeling dynamic systems in an efficient manner is an important skill to acquire for a scientist, it is a difficult skill to acquire. A simple step-based tutoring system, called AMT, was designed to help students learn how to construct models of dynamic systems using deep modeling practices. In order to increase the frequency of deep modeling and reduce the amount of guessing/gaming, a meta-tutor coaching students to follow a deep modeling strategy was added to the original modeling tool. This paper presents the results of two experiments investigating the effectiveness of the meta-tutor when compared to the original software. The results indicate that students who studied with the meta-tutor did indeed engage more in deep modeling practices. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Students

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Using HCI task modeling techniques to measure how deeply students model 16

Using HCI task modeling techniques to measure how deeply stu...

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Workshops at the 16th International Conference on Artificial Intelligence in Education, AIED 2013

作者： Girard, Sylvie Zhang, Lishan Hidalgo-Pontet, Yoalli VanLehn, Kurt Burleson, Winslow Chavez-Echeagary, Maria Elena Gonzalez-Sanchez, Javier Arizona State University Computing Informatics and Decision Systems Engineering TempeAZ85281 United States

ISBN: (纸本)9783642391118

User modeling in AIED has been extended in the past decades to include affective and motivational aspects of learner's interaction in intelligent tutoring systems. An issue in such systems is researchers' ability to understand and detect students' cognitive and meta-cognitive processes while they learn. In order to study those factors, various detectors have been created that classify episodes in log data as gaming, high/low effort on task, robust learning, etc. When simulating students' learning processes in an ITS, a question remains as to how to create those detectors, and how reliable their simulation of the user's learning processes can be. In this article, we present our method for creating a detector of shallow modeling practices within a meta-tutor instructional system. The detector was defined using HCI (human-computer interaction) task modeling as well as a coding scheme defined by human coders from past users' screen recordings of software use. The detector produced classifications of student behavior that were highly similar to classifications produced by human coders with a kappa of .925.

关键词： Human computer interaction

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Defining the behavior of an affective learning companion in the affective meta-tutor project 1

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16th International Conference on Artificial Intelligence in Education, AIED 2013

作者： Girard, Sylvie Chavez-Echeagaray, Maria Elena Gonzalez-Sanchez, Javier Hidalgo-Pontet, Yoalli Zhang, Lishan Burleson, Winslow Vanlehn, Kurt Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85281 United States

ISBN: (数字)9783642391125

ISBN: (纸本)9783642391118

Research in affective computing and educational technology has shown the potential of affective interventions to increase student's self-concept and motivation while learning. Our project aims to investigate whether the use of affective interventions in a meta-cognitive tutor can help students achieve deeper modeling of dynamic systems by being persistent in their use of meta-cognitive strategies during and after tutoring. This article is an experience report on how we designed and implemented the affective intervention. (The meta-tutor is described in a separate paper.) We briefly describe the theories of affect underlying the design and how the agent's affective behavior is defined and implemented. Finally, the evaluation of a detector-driven categorization of student behavior, that guides the agent's affective interventions, against a categorization performed by human coders, is presented. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Students

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An evaluation framework for software crowdsourcing

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Frontiers of Computer Science 2013年第5期7卷 694-709页

作者： Wenjun WU Wei-Tek TSAI Wei LI State Key Laboratory of Software Development Environment Beihang University Beijing 100191 China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ85281 USA Department of Computer Science and Technology INLIST Tsinghua University Beijing 100084 China

Recently software crowdsourcing has become an emerging area of software engineering. Few papers have pre- sented a systematic analysis on the practices of software crowdsourcing. This paper first presents an evaluation frame- work to evaluate software crowdsourcing projects with re- spect to software quality, costs, diversity of solutions, and competition nature in crowdsourcing. Specifically, competi- tions are evaluated by the min-max relationship from game theory among participants where one party tries to minimize an objective function while the other party tries to maximize the same objective function. The paper then defines a game theory model to analyze the primary factors in these min- max competition rules that affect the nature of participation as well as the software quality. Finally, using the proposed eval- uation framework, this paper illustrates two crowdsourcing processes, Harvard-TopCoder and AppStori. The framework demonstrates the sharp contrasts between both crowdsourc- ing processes as participants will have drastic behaviors in engaging these two projects.

关键词： crowdsourcing software engineering competi-tion rules game theory

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