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11th Pacific Asia Workshop on Intelligence and Security Informatics, PAISI 2016

作者： Lokoč, Jakub Kohout, Jan Čech, Přemysl Skopal, Tomáš Pevný, Tomáš SIRET Research Group Department of Software Engineering Charles University in Prague Prague Czech Republic Department of Computer Science and Engineering FEE Czech Technical University in Prague Cisco Systems Inc. Cognitive Research Center in Prague Prague Czech Republic

ISBN: (纸本)9783319318622

In this paper, we present detection of malware in HTTPS traffic using k-NN classification. We focus on the metric space approach for approximate k-NN searches over dataset of sparse high-dimensional descriptors of network traffic. We show the classification based on approximate k-NN search using metric index exhibits false positive rate reduced by an order of magnitude when compared to the state of the art method, while keeping the classification fast enough. © Springer International Publishing Switzerland 2016.

关键词： Intrusion detection

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Constructions for the optimal pebbling of grids

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica Electrical engineering and computer science 2017年第2期61卷 217-223页

作者： Gyori, Ervin Katona, Gyula Y. Papp, László F. Alfréd Rényi Institute of Mathematics Budapest Hungary Department of Mathematics Central European University Budapest Hungary Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics P.O. Box 91 Budapest1521 Hungary MTA-ELTE Numerical Analysis and Large Networks Research Group Hungary

In [6] the authors conjecture that if every vertex of an infinite square grid is reachable from a pebble distribution, then the covering ratio of this distribution is at most 3.25. First we present such a distribution with covering ratio 3.5, disproving the conjecture. The authors in the above paper also claim to prove that the covering ratio of any pebble distribution is at most 6.75. The proof contains some errors. We present a few interesting pebble distributions that this proof does not seem to cover and highlight some other difficulties of this topic.

关键词： Grid graph Optimal pebbling Pebbling

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Social media enabled human sensing for smart cities

Social media enabled human sensing for smart cities

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作者： Doran, Derek Severin, Karl Gokhale, Swapna Dagnino, Aldo Department of Computer Science and Engineering Kno.e.sis Research Center Wright State University DaytonOH45435 United States Department of Computer Science and Engineering University of Connecticut StorrsCT United States Industrial Software Systems Data Analytics Group ABB Corporate Research RaleighNC United States

Smart city initiatives rely on real-time measurements and data collected by a large number of heterogenous physical sensors deployed throughout a city. Physical sensors, however, are fraught with interoperability, dependability, management and political challenges. Furthermore, these sensors are unable to sense the opinions and emotional reactions of citizens that invariably impact smart city initiatives. Yet everyday, millions of dwellers and visitors of a city share their observations, thoughts, feelings and experiences, or in other words, their perceptions about their city through social media updates. This paper reasons why human sensors, namely, citizens that share information about their surroundings via social media can supplement, complement, or even replace the information measured by physical sensors. We present a methodology based on probabilistic language modeling to extract and visualize such perceptions that may be relevant to smart cities from social media updates. Using more than six million geo-tagged tweets collected over regions that feature widely varying geographical, social, cultural and political characteristics and tweet densities, we illustrate the potential of social media enabled human sensing to address diverse smart city challenges. © 2016 - IOS Press and the authors. All rights reserved.

关键词： Social networking (online)

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Translating timing requirements of Embedded software systems modeled in Simulink to a timing analysis model

Translating timing requirements of Embedded Software systems...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Padma Iyenghar Arne Noyer Joachim Engelhardt Elke Pulvermueller Software Engineering Research Group University of Osnabrueck Germany Institute of Computer Engineering University of Applied Sciences Osnabrueck Germany

ISBN: (纸本)9781509013159

In model-based Embedded software engineering (ESE), individual systems are modeled with chains of components that are translated to chains of tasks/runnables for a scheduling analysis. Early analysis of response time of such systems (e.g. end-to-end path delay) provides important feedback to understand how the function blocks/components in the system may actually behave. In this paper we report on work in progress pertaining to an overall workflow for model-driven specification, translation and validation of such timing constraints in ESE projects developed using Matlab/Simulink. The challenges addressed in this workflow and future directions are outlined.

关键词： Mathematical model Analytical models software packages Unified modeling language Delays Libraries

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A novel approach towards model-driven reliability analysis of Simulink models

A novel approach towards model-driven reliability analysis o...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Padma Iyenghar Stephan Wessels Arne Noyer Elke Pulvermueller Clemens Westerkamp Software Engineering Research Group University of Osnabrueck Germany Institute of Computer Engineering University of Applied Sciences Osnabrueck Germany

ISBN: (纸本)9781509013159

In the recent decade, many formalisms and tools have emerged for model-driven Non-Functional Property (NFP) specification and assessment. In this direction, model-driven reliability and safety assessment of engineering systems developed using Matlab/Simulink is an emerging research challenge. However, a generic mechanism for NFP specification in the Simulink design model is not yet supported. Further, a completely automated model-based workflow for synthesis of a NFP analysis model and its subsequent analysis in a NFP analysis tool is missing. In this context, this paper proposes a novel approach and a fully automated workflow towards model-driven reliability analysis of Simulink models. An approach to annotate the Simulink design models with reliability attributes and subsequent synthesis of fault trees from the annotated design model is described. A prototype and initial experimental results are discussed.

关键词： Unified modeling language software packages Analytical models Fault trees Libraries Reliability engineering

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The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package

arXiv

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arXiv 2022年

作者： Price-Whelan, Adrian M. Lim, Pey Lian Earl, Nicholas Starkman, Nathaniel Bradley, Larry Shupe, David L. Patil, Aarya A. Corrales, Lia Brasseur, C.E. Nöthe, Maximilian Donath, Axel Tollerud, Erik Morris, Brett M. Ginsburg, Adam Vaher, Eero Weaver, Benjamin A. Tocknell, James Jamieson, William Van Kerkwijk, Marten H. Robitaille, Thomas P. Merry, Bruce Bachetti, Matteo Aldcroft, Thomas L. Alvarado-Montes, Jaime A. Archibald, Anne M. Bódi, Attila Bapat, Shreyas Barentsen, Geert Bazán, Juanjo Biswas, Manish Boquien, Médéric Burke, D.J. Cara, Daria Cara, Mihai Conroy, Kyle E. Conseil, Simon Craig, Matthew W. Cross, Robert M. Cruz, Kelle L. D'Eugenio, Francesco Dencheva, Nadia Devillepoix, Hadrien A. R. Dietrich, Jörg P. Eigenbrot, Arthur Davis Erben, Thomas Ferreira, Leonardo Foreman-Mackey, Daniel Fox, Ryan Freij, Nabil Garg, Suyog Geda, Robel Glattly, Lauren Gondhalekar, Yash Gordon, Karl D. Grant, David Greenfield, Perry Groener, Austen M. Guest, Steve Gurovich, Sebastian Handberg, Rasmus Hart, Akeem Hatfield-Dodds, Zac Homeier, Derek Hosseinzadeh, Griffin Jenness, Tim Jones, Craig K. Joseph, Prajwel Kalmbach, J. Bryce Karamehmetoglu, Emir Kaluszynski, Mikolaj Kelley, Michael S. P. Kern, Nicholas Kerzendorf, Wolfgang E. Koch, Eric W. Kulumani, Shankar Lee, Antony Ly, Chun Ma, Zhiyuan MacBride, Conor Maljaars, Jakob M. Muna, Demitri Murphy, N.A. Norman, Henrik O'Steen, Richard Oman, Kyle A. Pacifici, Camilla Pascual, Sergio Pascual-Granado, J. Patil, Rohit R. Perren, Gabriel I. Pickering, Timothy E. Rastogi, Tanuj Roulston, Benjamin R. Ryan, Daniel F. Rykoff, Eli S. Sabater, Jose Sakurikar, Parikshit Salgado, Jesús Sanghi, Aniket Saunders, Nicholas Savchenko, Volodymyr Schwardt, Ludwig Seifert-Eckert, Michael Shih, Albert Y. Jain, Anany Shrey Shukla, Gyanendra Sick, Jonathan Simpson, Chris Singanamalla, Sudheesh Singer, Leo P. Singhal, Jaladh Sinha, Manodeep Sipocz, Brigitta M. Spitler, Lee R. Stansby, David Streicher, Ole Šumak, Jani Swinbank, John D. Taranu, Dan S. Tewary, Nikita Tremblay, Grant R. De Val-Borro, Mi Center for Computational Astrophysics Flatiron Institute 162 5th Ave New YorkNY10010 United States Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States Department of Astronomy University of Illinois at Urbana-Champaign 1002 W. Green St. UrbanaIL61801 United States David A. Dunlap Department of Astronomy & Astrophysics University of Toronto 50 St. George Street TorontoONM5S 3H4 Canada IPAC MC 100-22 Caltech 1200E. California Blvd. PasadenaCA91125 United States Dunlap Institute for Astronomy & Astrophysics University of Toronto 50 St George Street TorontoONM5S 3H4 Canada University of Michigan Astronomy 1085 S. University Ann ArborMI48109 United States School of Physics and Astronomy University of St Andrews North Haugh St AndrewsKY16 9SS United Kingdom Astroparticle Physics TU Dortmund Otto-Hahn-Str. 4a Dortmund44227 Germany Center for Astrophysics-Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States Center for Space and Habitability University of Bern Gesellschaftsstrasse 6 Bern3012 Switzerland Department of Astronomy University of Florida P.O. Box 112055 GainesvilleFL United States Lund Observatory Department of Astronomy and Theoretical Physics Lund University Box 43 Lund22100 Sweden NSF's National Optical-Infrared Astronomy Research Laboratory 950 North Cherry Avenue TucsonAZ85719 United States School of Mathematical and Physical Sciences Macquarie University SydneyNSW2109 Australia Astronomy Astrophysics and Astrophotonics Research Centre Macquarie University SydneyNSW2109 Australia Australian Astronomical Optics Macquarie University SydneyNSW2109 Australia Aperio Software Ltd. Insight House Riverside Business Park Stoney Common Road Essex StanstedCM24 8PL United Kingdom South African Radio Astronomy Observatory 2 Fir Street Black River Park Observatory7925 South Africa I-09047 Italy San Diego Supercomputer Center University of California San Diego 95

The Astropy Project supports and fosters the development of open-source and openly developed Python packages that provide commonly needed functionality to the astronomical community. A key element of the Astropy Project is the core package astropy, which serves as the foundation for more specialized projects and packages. In this article, we summarize key features in the core package as of the recent major release, version 5.0, and provide major updates for the Project. We then discuss supporting a broader ecosystem of interoperable packages, including connections with several astronomical observatories and missions. We also revisit the future outlook of the Astropy Project and the current status of Learn Astropy. We conclude by raising and discussing the current and future challenges facing the Project. © 2022, CC BY-SA.

关键词： Python

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Predicting Build Co-changes with Source Code Change and Commit Categories

Predicting Build Co-changes with Source Code Change and Comm...

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IEEE International Conference on software Analysis, Evolution and Reengineering (SANER)

作者： Christian Macho Shane McIntosh Martin Pinzger Software Engineering Research Group University of Klagenfurt Klagenfurt Austria Dept. of Electrical and Computer Engineering McGill University Montreal Canada

When software is maintained and evolved the build configuration also needs to be updated. Knowing when to update the build configuration is typically done manually with the risk of missing an update and breaking the build. To mitigate this risk, previous work has investigated prediction models to help developers to identify commits that will likely involve an update of the build configuration. In this paper, we investigate whether we can improve these existing prediction models by taking into account detailed information on source code changes and commit categories. Our main hypothesis is that such detailed information on changes will significantly improve the prediction of build co-changes. To that extent, we extract information on changes from 10 Java open source projects and use a random forest classifier to train models that predict build co-changes within and across projects. Our results show significant improvements over existing prediction models: the AUC for intra-and cross-project prediction improves by 11.54% and 9.46% respectively. In addition, we investigate advanced resampling techniques to explore the effect of unbalanced data on our models. The results show that SMOTE can particularly improve prediction models with low performance that were trained on unbalanced data. Our models improve the prediction and enable a better understanding of build co-changes.

关键词： Predictive models Java Training Data mining Data models Computational modeling Maintenance engineering

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PeRCeIVE: Proactive caching in ICN-based VANETs

PeRCeIVE: Proactive caching in ICN-based VANETs

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IEEE Vehicular Networking Conference (VNC)

作者： Dennis Grewe Marco Wagner Hannes Frey Robert Bosch GmbH Corporate Sector Research and Advance Engineering Renningen Germany University of Koblenz-Landau Computer Networks Group Koblenz Germany

ISBN: (纸本)9781509051984

The networking of components, machines and everyday objects is progressing rapidly. This development also affects the automotive industry. Vehicle systems are getting connected with other cars, infrastructure components or cloud servers. This raises the question if the current host-centric communication model of today's networks is ready for networking billions of new devices. The Information-Centric Networking (ICN) paradigm is a promising candidate to solve the issues set by connected vehicles and host-centric communication, for example by providing in-network caching capabilities. However, placing the right content at the right node in-time is a non trivial task. Within this paper, we introduce PeRCeIVE, a PRoactive Caching approach for Icn-based Vehicular ad-hoc networks (VANETs). PeRCeIVE shows that a directed placement of data will improve the performance of the network by distributing the content with a minimal number of replicas one-hop away from the consumer.

关键词： Vehicles Automotive engineering Ad hoc networks Mobile communication Handover Conferences

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How sustainable are model software artifacts in the context of model driven software engineering 3

How sustainable are model software artifacts in the context ...

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3rd International Workshop on Measurement and Metrics for Green and Sustainable software Systems, MeGSuS 2016

作者： Torre, Damiano Calero, Coral Department of Systems and Computer Engineering Software Quality Engineering Laboratory Carleton University 1125 Colonel by Drive OttawaONK1S5B6 Canada ALARCOS Research Group Department of Technologies and Information Systems University of Castilla-La Mancha Paseo de la Universidad 4 Ciudad Real13071 Spain

Today, software is pervasive in our daily lives and its sustainability and environmental impact have become major factors in the development of software systems. Due to increasing of software complexity, it is widely acknowledged that it is impossible to test every aspect of system software. One method of increasing understanding between the software developer and the customer, of deepening the understanding of how software works, and ultimately of reducing the complexity of software, is through the use of models. Model driven software engineering (MDSE) is an established approach for developing complex software systems. This work presents a first attempt at reshaping existing basic dimensions for software sustainability in terms of MDSE. Moreover, we describe 8 quality aspects and their relationships with each other. We also present a set of guidelines to identify the 8 quality aspects, and the paths to measure sustainability in terms of MDSE. Finally, we describe an example with a set of hypothetical scenarios where we show how our quality aspects could be helpful to measure and analyze the degree of sustainability in the context of MDSE.

关键词： Sustainable development

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Towards computational fluorescence microscopy: Machine learning-based integrated prediction of morphological and molecular tumor profiles

arXiv

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arXiv 2018年

作者： Binder, Alexander Bockmayr, Michael Hägele, Miriam Wienert, Stephan Heim, Daniel Hellweg, Katharina Stenzinger, Albrecht Parlow, Laura Budczies, Jan Goeppert, Benjamin Treue, Denise Kotani, Manato Ishii, Masaru Dietel, Manfred Hocke, Andreas Denkert, Carsten Müller, Klaus-Robert Klauschen, Frederick Machine-Learning Group Department of Software Engineering and Theoretical Computer Science Technical University of Berlin Marchstr. 23 Berlin10587 Germany Systems Pathology Lab Institute of Pathology Charité University Hospital Charitéplatz 1 Berlin10117 Germany Department of Internal Medicine Infectious Diseases and Pulmology Charitéplatz 1 Berlin10117 Germany Institute of Pathology University of Heidelberg Im Neuenheimer Feld 224 Heidelberg Germany Laboratory of Cellular Dynamics Immunology Frontier Research Center Osaka University 2-2 Yamada-oka Suita Osaka565-0871 Japan ISTD Pillar Singapore University of Technology and Design 8 Somapah Road Singapore487372 Singapore Charité Berlin Charitéplatz 1 Berlin10117 Germany Department of Brain and Cognitive Engineering Korea University 145 Anam-ro Seongbukgu Seoul136-713 Korea Republic of Max-Planck-Institute for Informatics Saarbrücken Germany Department of Pediatric Hematology and Oncology University Medical Center Hamburg-Eppendorf Hamburg Germany

Recent advances in cancer research largely rely on new developments in microscopic or molecular profiling techniques offering high level of detail with respect to either spatial or molecular features, but usually not both. Here, we present a novel machine learning-based computational approach that allows for the identification of morphological tissue features and the prediction of molecular properties from breast cancer imaging data. This integration of microanatomic information of tumors with complex molecular profiling data, including protein or gene expression, copy number variation, gene methylation and somatic mutations, provides a novel means to computationally score molecular markers with respect to their relevance to cancer and their spatial associations within the tumor microenvironment. Copyright © 2018, The Authors. All rights reserved.

关键词： Fluorescence microscopy

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