- computational.science - lists.iccsa.org

CFP Second Tutorial on the SARL Agent Programming Language
by stephane.galland＠utbm.fr 02 Oct '17

02 Oct '17

Second Tutorial on the SARL Agent Programming Language http://www.multiagent.fr/Conferences:TutorialSARL18 http://cs-conferences.acadiau.ca/ant-18/#tutorial The 9th International Conference on Ambient Systems, Networks and Technologies (ANT-2018) http://cs-conferences.acadiau.ca/ant-18/ May 08-11, 2018 Porto, Portugal Research on Agents and Multi-Agent Systems has matured during the last decade and many effective applications of this technology are now deployed. SARL aims at providing the fundamental abstractions for dealing with concurrency, distribution, interaction, decentralization, reactivity, autonomy and dynamic reconfiguration. These high-level features are now considered as the major requirements for an easy and practical implementation of modern complex software applications. We are convinced that the agent-oriented paradigm holds the keys to effectively meet this challenge. Considering the variety of existing approaches and meta-models in the field of agent-oriented engineering and more generally multi-agent systems, our approach remains as generic as possible and highly extensible to easily integrate new concepts and features. The SARL Tutorial 2018 provides introduction and explanation the modeling and implementation of multiagent systems with the SARL agent programming language. The tutorial session will be held in Porto, Portugal (08-11 May 2018) during the 9th International Conference on Ambient Systems, Networks, and Technologies (ANT 2018). The exact date will be provided into the ANT-28 program. ==== Tutorial Outline ==== The following points will be treated duing the tutorial. - Genesis of SARL. - Basic Concepts (Agent, Event, Space, Behavior) with simple examples. - Using Agent Communication Language with SARL - Doing simulation with SARL: traffic and drone simulation examples. - Major installation guidelines The duration of the tutorial is 1:30. Online resources: http://www.sarl.io ==== Tutorial Chairs ==== Stéphane GALLAND <stephane.galland(a)utbm.fr>, Burgundy Franche-Comte University, France Nicolas GAUD <nicolas.gaud(a)utbm.fr>, Burgundy Franche-Comte University, France Sebastian RODRIGUEZ <sebastian.rodriguez(a)gitia.org>, Universidad Technologica National, Argentina

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CFP Second International Workshop on Agent-based Modeling and Applications with SARL
by stephane.galland＠utbm.fr 02 Oct '17

02 Oct '17

Second International Workshop on Agent-based Modeling and Applications with SARL (SARL-18) http://www.multiagent.fr/Conferences:SARL18 http://cs-conferences.acadiau.ca/ant-18/#workshop_approved The 9th International Conference on Ambient Systems, Networks and Technologies (ANT-2018) http://cs-conferences.acadiau.ca/ant-18/ May 08-11, 2018 Porto, Portugal * Important Dates * =================== - Submission deadline: December 15, 2017 - Notification: February 5, 2018 - Final date for camera-ready copy: March 5, 2018 - Workshop: May 8-10, 2018 Research on Agents and Multi-Agent Systems has matured during the last decade and many effective applications of this technology are now deployed. SARL-18 provides an international forum to present and discuss the latest scientific developments and their effective applications, to assess the impact of the approach, and to facilitate technology transfer. SARL-18 borns with the SARL agent programming language, but the scientific results presented in SARL-18 are not restricted to SARL; other languages and agent platforms may be concerned by the proposed papers. SARL aims at providing the fundamental abstractions for dealing with concurrency, distribution, interaction, decentralization, reactivity, autonomy and dynamic reconfiguration. These high-level features are now considered as the major requirements for an easy and practical implementation of modern complex software applications. We are convinced that the agent-oriented paradigm holds the keys to effectively meet this challenge. Considering the variety of existing approaches and meta-models in the field of agent-oriented engineering and more generally multi-agent systems, our approach remains as generic as possible and highly extensible to easily integrate new concepts and features. The goal of SARL-18 is to provides a place where the different points of view on the modeling and the simulation with agent platforms and agent programming languages may be discussed. Tutorial sessions for introducing and explaining the modeling and implementation of multiagent systems with SARL will be organized during the workshop. The authors may contribute to the SARL-18 workshop by providing a paper or a tutorial. For submitting a tutorial, the authors must send a summary of the tutorial on 4 to 6 pages. SARL-18 will be held in Porto, Portugal (08-11 May 2018) in conjunction with the 9th International Conference on Ambient Systems, Networks, and Technologies (ANT 2018). Topics ====== The main topics of the SARL-18 workshop are (but not restricted to): - Methods and Models: - Agent based Modeling and Simulation - Agent programming language - Agent based Simulation - Agent oriented analysis and design methods - Ontologies and theories about large urban systems - Formal models of agent-based simulation - Organizational models - Applications: - Traffic/Transport - Crowds - Smard grids and smart buildings - Land-Use - Energy ORGANIZATION COMMITTEE ====================== Stéphane GALLAND <stephane.galland(a)utbm.fr>, Burgondy Franche-Comte University, France Nicolas GAUD <nicolas.gaud(a)utbm.fr>, Burgondy Franche-Comte University, France Sebastian RODRIGUEZ <sebastian.rodriguez(a)gitia.org>, Universidad Technologica National, Argentina

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Recruitment - Postdoc / Research Fellow on Cyber-Physical Security at SUTD, Singapore
by Jianying Zhou 02 Oct '17

02 Oct '17

Singapore University of Technology and Design (SUTD) is a young university which was established in collaboration with MIT. iTrust is a Cyber Security Research Center with about 15 multi-discipline faculty members from SUTD. It has the world’s best facilities in cyber-physical systems (CPS) including testbeds for Secure Water Treatment (SWaT), Water Distribution (WADI), Electric Power and Intelligent Control (EPIC), and IoT. (See more info at https://itrust.sutd.edu.sg/research/testbeds/) I am looking for postdocs / research fellows with expertise on cyber-physical system security, especially on the legacy CPS protection. The candidates should have track record of strong R&D capability, be able to perform deep system-level investigations of security mechanisms, be a good team player, and also have good written/oral communication skills. The position will provide an excellent opportunity to perform both basic and translational research in close collaboration with industry. Successful candidates will be offered internationally competitive remuneration, and enjoy high-quality living and low tax rates in Singapore. Interested candidates please send your CV with a research statement to Prof. Jianying Zhou. Contact: Prof. Jianying Zhou Email: jianying_zhou(a)sutd.edu.sg Home: http://jianying.space/

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IEEE HiPC 2017 - Student Research Symposium, DDDSS Workshop Deadlines Extended & Keynotes Announced
by Anand Panangadan 01 Oct '17

01 Oct '17

Release: 26 September 2017 - STUDENT RESEARCH SYMPOSIUM (SRS) Submission deadline extended to September 30 - Workshop on Dynamic Data Driven Smart Systems (DDDSS) Submission deadline extended to October 15 - KEYNOTE SPEAKERS ANNOUNCED - CONFERENCE PROGRAM ------------------------------------------------------------ ------------------------------------ 24th IEEE International Conference on High Performance Computing, Data, and Analytics HiPC 2017 December 18-21, 2017 Jaipur, India http://www.hipc.org https://twitter.com/hipcconf https://www.facebook.com/hipc.conference/ https://plus.google.com/+HipcOrg ------------------------------------------------------------ ------------------------------------ 10th HiPC Student Research Symposium (SRS) HiPC 2017 will feature the 10th Student Research Symposium on High Performance Computing, Data, and Analytics (HPC) aimed at stimulating and fostering student research, and providing an international forum to highlight student research accomplishments. The symposium will also provide exposure to students in the best practices in HPC in academia and industry. The Conference Reception and multiple Student Symposium Poster Exhibit sessions will provide an opportunity for students to interact with HPC researchers and practitioners (and recruiters) from academia and industry. Papers are solicited in all areas of high-performance computing, data, and analytics. Awards for Best Poster will be presented at the symposium. IMPORTANT DATES Sep 30, 2017 - Submission Deadline (Extended) See the SRS Call for Papers page at http://hipc.org/student- research-symposium/ ------------------------------------------------------------ ------------------------------------ Workshop on Dynamic Data Driven Smart Systems (DDDSS) http://hipc.org/dynamic-data-driven-smart-systems-workshop/ ------------------------------------------------------------ ------------------------------------ We invite original articles, position papers, and short presentations on research that explores *systems, algorithms, applications, and support areas* related to InfoSymbiotics/DDDAS for emerging technologies. Participants are encouraged to submit papers on topics including, but not limited to: - Coordinated control frameworks in IoT and Smart Systems - Tracking methods and situational awareness - Security, authentication, and privacy in smart systems - Dynamic energy and energy-aware systems - Earth and space systems and environments - Structural and process monitoring applications - Assimilation and uncertainty quantification The papers accepted for presentation in HiPC 2017 workshops will be included in the workshops volume of the proceedings of the conference, which will be distributed online in two volumes with a separate ISBN for the workshops (HiPCW 2017). Post conference, papers presented at the conference and eligible for inclusion will be submitted to the IEEE Xplore Digital Library. Selected papers will be invited for publication in a special issue of the Journal of Cluster Computing. ------------------------------------------------------------ ------------------------------------ ****HiPC 2017 KEYNOTE SPEAKERS ANNOUNCED**** ------------------------------------------------------------ ------------------------------------ Parthasarathy Ranganathan (Distinguished Engineer, Google) Topic: End of Moore’s Law: Or, a computer architect’s mid-life crisis? Rajeev Rastogi (Director of Machine Learning, Amazon) Topic: Machine Learning @ Amazon Ian Foster (Professor of Computer Science, University of Chicago; Senior Scientist and Distinguished Fellow, Argonne National Lab) Topic: Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales ------------------------------------------------ HiPC 2017 CONFERENCE PROGRAM ------------------------------------------------ The conference technical program will showcase three keynote speakers and three days of single track presentations of peer reviewed papers from all over the world. The full program will include workshops and special plenary sessions covering Machine Learning & Mathematical Modeling and HPC Initiatives in India. The conference encourages industry participation in the main technical program and workshops, as well as the Industry, Research and User Symposium (IRUS) and vendor exhibition. On days 2 and 3, there will be a full program of industry exhibits and events. Various sponsorship opportunities are available as described at the the conference website. Titanium and Platinum sponsors are also provided a forum to drive Industry BOF sessions. ------------------------------------------------ HiPC 2017 ORGANIZATION ------------------------------------------------ General Co-Chairs: Chiranjib Sur, Shell, India Yinglong Xia, Huawei Research America, USA Steering Committee Chair: Viktor K. Prasanna, University of Southern California, USA Vice General Chairs: Kishore Kothapalli, IIIT-Hyderabad, India Anand Panangadan, California State University, Fullerton, USA Program Chair Ümit V. Çatalyürek, Georgia Institute of Technology, USA Program Vice-Chairs Algorithms: Olivier Beaumont, INRIA, France Applications: Ananth Kalyanaraman, Washington State University, USA Architecture: Yuan Xie, University of California at Santa Barbara, USA System Software: Gagan Agrawal, The Ohio State University, USA Industry Liaison Co-Chairs: Rama Govindaraju, Google, USA Jigar Halani, Wipro, India Vivek Yadav, FullStackNet, India Workshops Co-Chairs: Manish Parashar, Rutgers University, USA Saumil Merchant, Shell, India Student Research Symposium Co-Chairs: Kishore Kothapalli, IIIT-Hyderabad, India Madhura Purnaprajna, Amrita University, India Ashok Srinivasan, Florida State University, USA Industry, Research, and User Symposium Co-Chairs: R. Badrinath, Ericcson, India Seetha Rama Krishna Nookala, Intel, India Indian Academia Liaisons Chair: Yogesh Simmhan, IISc, Bangalore, India Proceedings Chair: Ren Chen, University of Southern California, USA Publicity Chairs: Anand Panangadan, California State University, Fullerton, USA Ravindra Sure, IBM, India ------------------------------------------------ HiPC 2017 SPONSORSHIP ------------------------------------------------ See details for Industry Sponsorship at http://hipc.org/sponsorship- levels-how-to/ ------------------------------------------------------------ ------------------- HiPC 2017 is co-sponsored by •IEEE Computer Society Technical Committee on Parallel Processing (TCPP) •HiPC Education Trust, India In cooperation with •ACM Special Interest Group on Algorithms and Computation Theory (SIGACT) •ACM Special Interest Group on Computer Architecture (SIGARCH) •FIP Working Group on Concurrent Systems •Manufacturers' Association for Information Technology (MAIT) •National Association of Software and Service Companies (NASSCOM) ------------------------------------------------------------ ------------------------------------

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FPS 2017: Call for Participation
by Abdessamad Imine 01 Oct '17

01 Oct '17

(Apologies for multiple copies) CALL FOR PARTICIPATION ********************************************************************************** The 10th International Symposium on Foundations & Practice of Security (FPS 2017) October 23-24-25, 2017 Nancy, France Website: http://fps2017.loria.fr/ ********************************************************************************** List of accepted papers: ----------------------- http://fps2017.loria.fr/accepted-papers/ Conference program: ------------------- http://fps2017.loria.fr/program/ Online registration: -------------------- http://fps2017.loria.fr/registration/ Scope: ------ Protecting the communication and data infrastructure of an increasingly inter-connected world has become vital to the normal functioning of all aspects of our world. Security has emerged as an important scientific discipline whose many multifaceted complexities deserve the attention and synergy of the mathematical, computer science and engineering communities. After the previous meetings held in La Rochelle, Montreal, Grenoble, Toronto, Paris, Clermont-Ferrand and Quebec city, this 10th edition of the FPS symposium will be held in Nancy, France. The aim of FPS is to discuss and exchange theoretical and practical ideas that address security issues in inter-connected systems. It aims to provide scientific presentations as well as to establish links, promote scientific collaboration, joint research programs, and student exchanges between institutions involved in this important and fast moving research field. We also invite papers from researchers and practitioners working in security, privacy, trustworthy data systems and related areas to submit their original papers. The main topics, but not limited to, include: * Computer and Network Security * Formal foundations in Information or Operational Security * Security of Service Oriented Architectures * Information Theoretic Security * Security of Cloud Computing * Security Management and Security Policies * Policy-based Security Architectures * Security of P2P systems * Security & Privacy on Social Networks * Access Control Languages * Data Mining & Watermarking * Cryptography & Cryptanalysis * Threat Analysis and Trust Management * Privacy & Sensitive Data Management * Policy-based Distributed Information Systems * Security in Sensor Networks and RFIDs * Security of Cloud Computing, Grid Computing * Security of Distributed Embedded Middleware * Distributed Security Protocols & Policies * Security and Privacy in Digital Currencies * Malware, Botnet and Advanced Persistent Threats * Code Reverse Engineering and Vulnerability Exploitation * Side Channel & Physical Attacks * Social Engineering * Security of Big-Data Committees: ------------ General Chairs: - Luigi Logrippo (Université du Québec en Outaouais, Canada) - Jean-Yves Marion (Mines de Nancy, France) PC Chairs: - José M. Fernandez (Polytechnique Montréal, Canada) - Abdessamad Imine (Université de Lorraine, Nancy, France) Publications Chair: - Joaquin Garcia-Alfaro (Telecom SudParis, France) Publicity Chairs: - Pascal Lafourcade (Université d’Auvergne, France) - Nur Zincir-Heywood (Dalhousie University, Canada) Program Committee: - Esma Aimeur (University of Montreal, Canada) - Jeremy Clark (Concordia University, Canada) - Frédéric Cuppens (IMT Atlantique, France) - Nora Cuppens (IMT Atlantique, France) - Jean-Luc Danger (Télécom Paris-Tech, France) - Mourad Debbabi (Concordia University, Canada) - Josée Desharnais (Laval University, Canada) - Josep Domingo-Ferrer (Universitat Rovira i Virgili, Spain) - Samuel Dubus (NOKIA Bell Labs, France) - Sébastien Gambs (Université du Québec à Montréal, Canada) - Joaquin Garcia-Alfaro (Telecom SudParis, France) - Dieter Gollmann (Hamburg University of Technology, Germany) - Sushil Jajodia (George Mason University, USA) - Martin Johns (SAP Research, Germany) - Bruce Kapron (University of Victoria, Canada) - Nizar Kheir (THALES, France) - Raphaël Khoury (Université du Québec à Chicoutimi, Canada) - Hyoungshick Kim (Sungkyunkwan University, Republic of Korea) - Igor Kotenko (SPIIRAS, Russia) - Evangelos Kranakis (Carleton University Computer Science, Canada) - Pascal Lafourcade (Université d'Auvergne, France) - Luigi Logrippo (Université du Québec en Outaouais, Canada) - Javier Lopez (University of Malaga, Spain) - Jean-Yves Marion (Mines de Nancy, France) - Fabio Martinelli (National Research Council of Italy (CNR), Italy) - Paliath Narendran (University at Albany, USA) - Guillermo Navarro-Arribas (Universitat Autonoma de Barcelona, Spain) - Jun Pang (University of Luxembourg, Luxembourg) - Marie-Laure Potet (VERIMAG, France) - Silvio Ranise (FBK, Security and Trust Unit, Italy) - Indrakshi Ray (Colorado State University, USA) - Michaël Rusinowitch (LORIA-INRIA Nancy, France) - Basit Shafiq (Lahore University of Management Sciences, Pakistan) - Anna Squicciarini (Pennsylvania State University, USA) - Natalia Stakhanova (University of New Brunswick, Canada) - Chamseddine Talhi (École de Technologie Supérieure, Canada) - Nadia Tawbi (Université Laval, Canada) - Rakesh Verma (University of Houston, USA) - Lingyu Wang (Concordia University, Canada) - Edgar Weippl (SBA Research, Austria) - Lena Wiese (Georg-August Universität Göttingen, Germany) - Xun Yi (RMIT University, Australia) - Nur Zincir-Heywood (Dalhousie University, Canada) - Mohammad Zulkernine (Queen's University, Canada)

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Special Issue on Parallel and Distributed Data Mining
by Massimo Cafaro 28 Sep '17

28 Sep '17

Special Issue on Parallel and Distributed Data Mining Information Sciences, Elsevier The sheer volume of new data, which is being generated at an increasingly fast pace, has already produced an anticipated data deluge that is difficult to challenge. We are in the presence of an overwhelming vast quantity of data, owing to how easy is to produce or derive digital data. Even the storage of this massive amount of data is becoming a highly demanding task, outpacing the current development of hardware and software infrastructure. Nonetheless, this effort must be undertaken now for the preservation, organization and long-term maintenance of these precious data. However, the collected data is useless without our ability fully understand and make use of it. Therefore, we need new algorithms to address this challenge. Data mining techniques and algorithms to process huge amount of data in order to extract useful and interesting information have become popular in many different contexts. Algorithms are required to make sense of data automatically and in efficient ways. Nonetheless, even though sequential computer systems performance is improving, they are not suitable to keep up with the increase in the demand for data mining applications and the data size. Moreover, the main memory of sequential systems may not be enough to hold all the data related to current applications. This Special Issue takes into account the increasing interest in the design and implementation of parallel and distributed data mining algorithms. Parallel algorithms can easily address both the running time and memory requirement issues, by exploiting the vast aggregate main memory and processing power of processors and accelerators available on parallel computers. Anyway, parallelizing existing algorithms in order to achieve good performance and scalability with regard to massive datasets is not trivial. Indeed, it is of paramount importance a good data organization and decomposition strategy in order to balance the workload while minimizing data dependences. Another concern is related to minimizing synchronization and communication overhead. Finally, I/O costs should be minimized as well. Creating breakthrough parallel algorithms for high-performance data mining applications requires addressing several key computing problems which may lead to novel solutions and new insights in interdisciplinary applications. Moreover, increasingly the data is spread among different geographically distributed sites. Centralized processing of this data is very inefficient and expensive. In some cases, it may even be impractical and subject to security risks. Therefore, processing the data minimizing the amount of data being exchanged whilst guaranteeing at the same time correctness and efficiency is an extremely important challenge. Distributed data mining performs data analysis and mining in a fundamentally distributed manner paying careful attention to resource constraints, in particular bandwidth limitation, privacy concerns and computing power. The focus of this Special Issue is on all forms of advances in high-performance and distributed data mining algorithms and applications. The topics relevant to the Special Issue include (but are not limited to) the following. TOPICS OF INTEREST Scalable parallel data mining algorithms using message-passing, shared-memory or hybrid programming paradigms Exploiting modern parallel architectures including FPGA, GPU and many-core accelerators for parallel data mining applications Middleware for high-performance data mining on grid and cloud environments Benchmarking and performance studies of high-performance data mining applications Novel programming paradigms to support high-performance computing for data mining Performance models for high-performance data mining applications and middleware Programming models, tools, and environments for high-performance computing in data mining Map-reduce based parallel data mining algorithms Caching, streaming, pipelining, and other optimization techniques for data management in high-performance computing for data mining Novel distributed data mining algorithms SUBMISSION GUIDELINES All manuscripts and any supplementary material should be submitted electronically through Elsevier Editorial System (EES) at http://ees.elsevier.com/ins (http://ees.elsevier.com/ins) The authors must select as “SI:PDDM” when they reach the “Article Type” step in the submission process. A detailed submission guideline is available as “Guide to Authors” at: http://www.elsevier.com/journals/information-sciences/0020-0255/guide-for-a…. IMPORTANT DATES Submission deadline: December 1th, 2017 First round notification: March 1th, 2018 Revised version due: May 1st, 2018 Final notification: June 1st, 2018 Camera-ready due: July 1st, 2018 Publication tentative date: October 2018 Guest editors: Massimo Cafaro, Email: massimo.cafaro(a)unisalento.it University of Salento, Italy and Euro-Mediterranean Centre on Climate Change, Foundation Italo Epicoco, Email: italo.epicoco(a)unisalento.it University of Salento, Italy and Euro-Mediterranean Centre on Climate Change, Foundation Marco Pulimeno, Email: marco.pulimeno(a)unisalento.it University of Salento, Italy - ************************************************************************************ Massimo Cafaro, Ph.D. Associate Professor Dept. of Engineering for Innovation University of Salento, Lecce, Italy Via per Monteroni 73100 Lecce, Italy Voice/Fax +39 0832 297371 Web http://sara.unisalento.it/~cafaro E-mail massimo.cafaro(a)unisalento.it cafaro(a)ieee.org cafaro(a)acm.org CMCC Foundation Euro-Mediterranean Center on Climate Change Via Augusto Imperatore, 16 - 73100 Lecce massimo.cafaro(a)cmcc.it ************************************************************************************

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Special Issue on Parallel and Distributed Data Mining
by Massimo Cafaro 22 Sep '17

22 Sep '17

Special Issue on Parallel and Distributed Data Mining Information Sciences, Elsevier The sheer volume of new data, which is being generated at an increasingly fast pace, has already produced an anticipated data deluge that is difficult to challenge. We are in the presence of an overwhelming vast quantity of data, owing to how easy is to produce or derive digital data. Even the storage of this massive amount of data is becoming a highly demanding task, outpacing the current development of hardware and software infrastructure. Nonetheless, this effort must be undertaken now for the preservation, organization and long-term maintenance of these precious data. However, the collected data is useless without our ability fully understand and make use of it. Therefore, we need new algorithms to address this challenge. Data mining techniques and algorithms to process huge amount of data in order to extract useful and interesting information have become popular in many different contexts. Algorithms are required to make sense of data automatically and in efficient ways. Nonetheless, even though sequential computer systems performance is improving, they are not suitable to keep up with the increase in the demand for data mining applications and the data size. Moreover, the main memory of sequential systems may not be enough to hold all the data related to current applications. This Special Issue takes into account the increasing interest in the design and implementation of parallel and distributed data mining algorithms. Parallel algorithms can easily address both the running time and memory requirement issues, by exploiting the vast aggregate main memory and processing power of processors and accelerators available on parallel computers. Anyway, parallelizing existing algorithms in order to achieve good performance and scalability with regard to massive datasets is not trivial. Indeed, it is of paramount importance a good data organization and decomposition strategy in order to balance the workload while minimizing data dependences. Another concern is related to minimizing synchronization and communication overhead. Finally, I/O costs should be minimized as well. Creating breakthrough parallel algorithms for high-performance data mining applications requires addressing several key computing problems which may lead to novel solutions and new insights in interdisciplinary applications. Moreover, increasingly the data is spread among different geographically distributed sites. Centralized processing of this data is very inefficient and expensive. In some cases, it may even be impractical and subject to security risks. Therefore, processing the data minimizing the amount of data being exchanged whilst guaranteeing at the same time correctness and efficiency is an extremely important challenge. Distributed data mining performs data analysis and mining in a fundamentally distributed manner paying careful attention to resource constraints, in particular bandwidth limitation, privacy concerns and computing power. The focus of this Special Issue is on all forms of advances in high-performance and distributed data mining algorithms and applications. The topics relevant to the Special Issue include (but are not limited to) the following. TOPICS OF INTEREST Scalable parallel data mining algorithms using message-passing, shared-memory or hybrid programming paradigms Exploiting modern parallel architectures including FPGA, GPU and many-core accelerators for parallel data mining applications Middleware for high-performance data mining on grid and cloud environments Benchmarking and performance studies of high-performance data mining applications Novel programming paradigms to support high-performance computing for data mining Performance models for high-performance data mining applications and middleware Programming models, tools, and environments for high-performance computing in data mining Map-reduce based parallel data mining algorithms Caching, streaming, pipelining, and other optimization techniques for data management in high-performance computing for data mining Novel distributed data mining algorithms SUBMISSION GUIDELINES All manuscripts and any supplementary material should be submitted electronically through Elsevier Editorial System (EES) at http://ees.elsevier.com/ins (http://ees.elsevier.com/ins) The authors must select as “SI:PDDM” when they reach the “Article Type” step in the submission process. A detailed submission guideline is available as “Guide to Authors” at: http://www.elsevier.com/journals/information-sciences/0020-0255/guide-for-a…. IMPORTANT DATES Submission deadline: December 1th, 2017 First round notification: March 1th, 2018 Revised version due: May 1st, 2018 Final notification: June 1st, 2018 Camera-ready due: July 1st, 2018 Publication tentative date: October 2018 Guest editors: Massimo Cafaro, Email: massimo.cafaro(a)unisalento.it University of Salento, Italy and Euro-Mediterranean Centre on Climate Change, Foundation Italo Epicoco, Email: italo.epicoco(a)unisalento.it University of Salento, Italy and Euro-Mediterranean Centre on Climate Change, Foundation Marco Pulimeno, Email: marco.pulimeno(a)unisalento.it University of Salento, Italy - ************************************************************************************ Massimo Cafaro, Ph.D. Associate Professor Dept. of Engineering for Innovation University of Salento, Lecce, Italy Via per Monteroni 73100 Lecce, Italy Voice/Fax +39 0832 297371 Web http://sara.unisalento.it/~cafaro E-mail massimo.cafaro(a)unisalento.it cafaro(a)ieee.org cafaro(a)acm.org CMCC Foundation Euro-Mediterranean Center on Climate Change Via Augusto Imperatore, 16 - 73100 Lecce massimo.cafaro(a)cmcc.it ************************************************************************************

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CFP The Complexity journal special issue -- Social Big Data: Mining, Applications and Beyond
by Xiuzhen Jenny Zhang 21 Sep '17

21 Sep '17

============= Complexity (Impact Factor 4.621) Special Issue on Social Big Data: Mining, Applications and Beyond Submission deadline: Friday 29 December 2017 Publication date: May 2018 Online CFP: https://www.hindawi.com/journals/complexity/si/148573/cfp/ Journal URL: https://www.hindawi.com/journals/complexity/ ============ The social nature of Web 2.0 leads to the unprecedented growth of social media sites such as discussion forums, product review sites, microblogging, social networking and social curation. Existing research in social media data mining has focused on techniques for extracting information for specific applications from separate social media sources. The mobile network and the Internet of Things are transforming what is means to be social online. Humans, everyday objects and smart devices interact and form an intelligent social network that is a highly adaptive complex system. Assisted by personal devices, people can access real-time traffic, weather and news event information and exchange such information through social interaction and form communities dynamically. The rich user- and device-generated data and user interactions generate complex social big data that is different from classical structured attribute-value data. The data objects take various forms including unstructured text, geo-tagged data objects and data object streams. The social networks formed from interactions among data objects also carry rich information for analyzing user behavior. Such complex social big data calls for cross disciplinary research from data mining, machine learning, pervasive and ubiquitous computing, network science, and computational social science. We seek contributions to advance our knowledge in social big data mining and analytics and extend the knowledge to related disciplines. We especially welcome methodological papers that address the data complexity and application papers that promote wider and deeper applications of social media data. Potential topics include, but are not limited to: • Personal device and content integrated social data mining • Mining dynamic complex social networks of humans and devices • Mining heterogeneous streams of social media data objects from humans and devices • Spatiotemporal analysis of social data and social networks • Privacy preserving social data mining • Social influence and community discovery in dynamic social networks • Social data mining for community-based recommendation and other applications • Trust and information credibility analysis of social media data • Mining for user social influence and communities in complex social networks of humans and devices • Mining social data for smart cities and smart nations • Humans as sensors for event detection and disaster management • Sentiment analysis and opinion mining for social good • Detection of opinion spam, illicit behavior and anomalies in social media • Social media data mining for public health and healthcare Papers are published upon acceptance, regardless of the Special Issue publication date. SUBMISSION Authors must submit their papers online at https://mts.hindawi.com/submit/journals/complexity/sbdmab/ Authors are welcome to discuss their potential submissions with the editors by sending an email to Xiuzhen Zhang (xiuzhen.zhang(a)rmit.edu.au) regarding the fit of their paper for this special issue. GUEST EDITORS Xiuzhen Zhang, RMIT University, Melbourne, Australia; xiuzhen.zhang(a)rmit.edu.au Shuliang Wang, Beijing Institute of Technology, Beijing, China; slwang(a)bit.edu.cn Gao Cong, Nanyang Technological University, Singapore; gaocong(a)ntu.edu.sg

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[SIMPDA2017] Submission Deadline Extended: October 14, 2017
by Fulvio Frati 21 Sep '17

21 Sep '17

** Submission Deadline Extended: October 14, 2017 ** [Apologies if you receive multiple copies of this cfp] **************************************************************************** *** SIMPDA 2017 SEVENTH INTERNATIONAL SYMPOSIUM ON DATA-DRIVEN PROCESS DISCOVERY AND ANALYSIS 6-8 DECEMBER, 2017 - NEUCHATEL, SWITZERLAND http://simpda2017.di.unimi.it **************************************************************************** *** ## About SIMPDA With the increasing automation of business processes, growing amounts of process data become available. This opens new research opportunities for business process data analysis, mining and modeling. The aim of the IFIP 2.6 International Symposium on Data-Driven Process Discovery and Analysis is to offer a forum where researchers from different communities and the industry can share their insight in this hot new field. The Symposium will feature a number of keynotes illustrating advanced approaches, shorter presentations on recent research, a competitive PhD seminar and selected research and industrial demonstrations. This year the symposium will be held in Neuchatel. ###Call for Papers The IFIP International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA 2017) offers a unique opportunity to present new approaches and research results to researchers and practitioners working in business process data modelling, representation and privacy-aware analysis. The symposium will bring together leading researchers, engineers and scientists from around the world. Full papers must not exceed 15 pages. Short papers are limited to at most 4 pages. All papers must be original contributions, not previously published or under review for publication elsewhere. All contributions must be written in English and must follow the LNCS Springer Verlag format. Templates can be downloaded from: http://www.springer.de/comp/lncs/authors.html Accepted papers will be published in a pre-proceeding volume of CEUR workshop series. The authors of the accepted papers will be invited to submit extended articles to a post-symposium proceedings volume which will be published in the LNBIP series (Lecture Notes in Business Information Processing, http://www.springer.com/series/7911) scheduled for late 2018 (extended papers length will be between 7000 and 9000 words). Around 10-15 papers will be selected for publication after a second round of review. ### Topics Topics of interest for submission include, but are not limited to: - Business Process Modeling languages, notations and methods - Lightweight Process Model - Data-aware and data-centric approaches - Process Mining with Big Data - Variability and configuration of process models - Process simulation and static analyses - Process data query languages - Process data mining - Privacy-aware process data mining - Process metadata and semantic reasoning - Process patterns and standards - Foundations of business process models - Resource management in business process execution - Process tracing and monitoring - Process change management and evolution - Business process lifecycle - Case studies and experience reports - Social process discovery - Crowdsourced process definition and discovery ### Workshop Format: In accordance to our historical tradition of proposing SIMPDA as a symposium, we propose an innovative format for this workshop: The number of sessions depend on the number of submissions but, considering the previous editions, we envisage to have four sessions, with 4-5 related papers assigned to each session. A special session (with a specific review process) will be dedicated to discuss research plan from PhD students. Papers are pre-circulated to the authors that will be expected to read all papers in advance but to avoid exceptional overhead, two are assigned to be prepared with particular care, making ready comments and suggestions. The bulk of the time during each session will be dedicated to open conversations about all of the papers in a given session, along with any linkages to the papers and discussions within an earlier session. The closing session (30 minutes), will include a panel about open challenges during which every participant will be asked to assemble their thoughts/project ideas/goals/etc that they got out of the workshop. ### Call for PhD Research Plans The SIMPDA PhD Seminar is a workshop for Ph.D. students from all over the world. The goal of the Seminar is to help students with their thesis and research plans by providing feedback and general advice on how to use their research results. Students interested in participating in the Seminar should submit an extended abstract describing their research. Submissions can relate to any aspect of Process Data: technical advances, usage and impact studies, policy analyses, social and institutional implications, theoretical contributions, interaction and design advances, innovative applications, and social implications. Research plans should be at most of 5 page long and should be organised following the following structure: - Abstract: summarises, in 5 line, the research aims and significance. - Research Question: defines what will be accomplished by eliciting the relevant the research questions. - Background: defines the background knowledge providing the 5 most relevant references (papers or books). - Significance: explains the relevance of the general topic and of the specific contribution. - Research design and methods: describes and motivates the method adopted focusing on: assumptions, solutions, data sources, validation of results, limitations of the approach. - Research stage: describes what the student has done so far. ### SIMPDA PhD award A doctoral award will be given by the SIMPDA PhD Jury to the best research plan submitted. Student Scholarships An application for a limited number of scholarships aimed at students coming from emerging countries has been submitted to IFIP. In order to apply, please contact paolo.ceravolo(a)unimi.it ### CALL for Demonstrations and Posters Demonstrations showcase innovative technology and applications, allowing for sharing research work directly with colleagues in a high-visibility setting. Demonstration proposals should consist of a title, an extended abstract, and contact information for the authors, and should not exceed 10 pages. Posters allow the presentation of late-breaking results in an informal, interactive manner. Poster proposals should consist of a title, an extended abstract, contact information for the authors, and should not exceed 2 pages. Accepted demonstrations and posters will be presented at the symposium. Abstracts will appear in the proceedings. ### Important Dates - Paper Submission: 14 October 2017 - Submission of PhD Presentations: 14 October 2017 - Notification of Acceptance: 19 November 2017 - Submission of Camera Ready Papers: 28 November 2017 - Second International Symposium on Process Data: 6-8 December 2017 - Post-proceeding submissions: 30 March 2018 ## Keynote Speakers * Enabling largely automated social media analytics * Karl Aberer Distributed Information Systems Laboratory (LSIR), EPFL In this talk we will report on our recent advances in automating the analysis of social media data. We first will review our recent work on a platform for analysing social media data in terms of topics discussed, communities and their influencers. This platform has been successfully used in a number of practical use case. When using the platform we identified the creation of domain-specific taxonomies as the main bottleneck in the analysis process. To tackle this issue we developed a novel method for taxonomy induction from domain-specific document corpora. In the second part of the talk we will discuss this method and some of the novel ideas that enabled us to produce high quality domain-specific taxonomies on the fly. ## Organizers ### CHAIRS - Paolo Ceravolo, Università degli Studi di Milano, Italy - Maurice van Keulen, University of Twente, The Netherlands - Kilan Stoffel, University of Neuchatel, Switzerland ### ADVISORY BOARD - Ernesto Damiani, Università degli Studi di Milano, Italy - Erich Neuhold, University of Vienna, Austria - Philippe Cudré-Mauroux , University of Fribourg, Switzerland - Robert Meersman, Graz University of Technology, Austria - Wilfried Grossmann, University of Vienna, Austria ### Program Committee - Akhil Kumar, Penn State University, USA - Benoit Depaire, University of Hasselt, Belgium - Chintan Mrit, University of Twente, The Netherlands - Christophe Debruyne, Trinity College Dublin, Ireland - Ebrahim Bagheri, Ryerson University, Canada - Edgar Weippl, TU Vienna, Austria - Fabrizio Maria Maggi, University of Tartu, Estonia - George Spanoudakis, City University London, UK - Haris Mouratidis, University of Brighton, UK - Isabella Seeber, University of Innsbruck, Austria - Jan Mendling, Vienna University of Economics and Business, Austria - Josep Carmona, UPC - Barcelona, Spain - Kristof Boehmer, University of Vienna, Austria - Manfred Reichert, Ulm University, Germany - Marcello Leida, TAIGER, Spain - Mark Strembeck, WU Vienna, Austria - Massimiliano De Leoni, Eindhoven TU, Netherlands - Matthias Weidlich, Imperial College, UK - Mazak Alexandra, University of Vienna, Austria - Mohamed Mosbah, University of Bordeaux - Mustafa Jarrar, Birzeit University, Palestine - Robert Singer, FH Joanneum, Austria - Roland Rieke, Fraunhofer SIT, Germany - Schahram Dustdar, Vienna University of Technology, Austria - Thomas Vogelgesang, University of Oldenburg, Germany - Valentina Emilia Balas, University of Arad, Romania - Wil Van der Aalst, Technische Universiteit Eindhoven, The Netherlands

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[Final Extension] [CFP] The 8th DataCloud 2017 Workshop @SC17
by Li, Tonglin 20 Sep '17

20 Sep '17

We apologize if you receive multiple copies of this CFP. This is the final extension to the submission deadline. DataCloud 2017: The Eighth International Workshop on Data-Intensive Computing in the Clouds Denver, CO, USA, November 12, 2017 Conference website https://sites.google.com/view/2017datacloud/home Submission link https://easychair.org/conferences/?conf=datacloud2017 Submission deadline (final extension) October 1, 2017 Applications and experiments in all areas of science are becoming increasingly complex and more demanding in terms of their computational and data requirements. Some applications generate data volumes reaching hundreds of terabytes and even petabytes. As scientific applications become more data intensive, the management of data resources and data flow between the storage and compute resources is becoming the main bottleneck. Analyzing, visualizing, and disseminating these large data sets has become a major challenge and data intensive computing is now considered as the “fourth paradigm” in scientific discovery after theoretical, experimental, and computational science. The eighth international workshop on Data-intensive Computing in the Clouds (DataCloud 2017) will provide the scientific community a dedicated forum for discussing new research, development, and deployment efforts in running data-intensive computing workloads on Cloud Computing infrastructures. The DataCloud 2017 workshop will focus on the use of cloud-based technologies to meet the new data intensive scientific challenges that are not well served by the current supercomputers, grids or compute-intensive clouds. We believe the workshop will be an excellent place to help the community define the current state, determine future goals, and present architectures and services for future clouds supporting data intensive computing. Submission Guidelines Authors are invited to submit papers with unpublished, original work of not more than 8 pages of double column text using single spaced 10 point size on 8.5 x 11 inch pages, as per ACM 8.5 x 11 manuscript guidelines; document templates can be found at http://www.acm.org/sigs/publications/proceedings-templates. The final papers in PDF format must be submitted online at https://easychair.org/conferences/?conf=datacloud2017. Papers will be peer-reviewed, and accepted papers will be published in the workshop proceedings as part of the ACM digital library (in cooperation with SIGHPC). Submission implies the willingness of at least one of the authors to register and present the paper. List of Topics * Data-intensive cloud computing infrastructure, applications, characteristics and challenges * Case studies of data intensive computing in the clouds * Performance evaluation of data clouds, data grids, and data centers * Energy-efficient data cloud design and management * Data placement, scheduling, and interoperability in the clouds * Accountability, QoS, and SLAs * Data privacy and protection in a public cloud environment * Distributed file systems for clouds * Data streaming and parallelization * New programming models for data-intensive cloud computing * Scalability issues in clouds * Social computing and massively social gaming * 3D Internet and implications * Future research challenges in data-intensive cloud computing Committees Program Chairs * Tonglin Li, Oak Ridge National Laboratory * Boyu Zhang, Microsoft Inc. * Xuan Guo, Oak Ridge National Laboratory Steering committee * Wei Tang, Google Inc. * Roger Barga, Microsoft Research * Ian Foster, University of Chicago & ANL * Geoffrey Fox, Indiana University Program committee (to be confirmed) * David Abramson, Monash University, Australia * John Bent, Los Alamos National Laboratory * Umit Catalyurek, Ohio State University * Linhai Qiu, Google Inc. * Abhishek Chandra, University of Minnesota * Rong N. Chang, IBM Research * Yong Chen, Texas Tech University * Alok Choudhary, Northwestern University * Jialin Liu, Lawrence Berkeley National Laboratory * Brian Cooper, Google Inc. * Ewa Deelman, University of Southern California * Murat Demirbas, University at Buffalo * Xu Yang, Amazon Inc. * Zhou Zhou, Salesforce Inc. * Kun Feng, Illinois Institute of Technology * Anthony Kougkas, Illinois Institute of Technology Contact All questions about submissions should be emailed to lit1(a)ornl.gov, zhang.boyu84(a)gmail.com or guox(a)ornl.gov.

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