Event
IUBT 2017
The 7th International Symposium on Internet of Ubiquitous and Pervasive Things (IUPT 2017) To be held in conjunction with Ambient Systems, Networks and Technologies Conference (ANT'17)
Submitted by Anonymous on October 17th, 2016
The 14th Overture Workshop 7 November 2016 | Cyprus, Greece | http://overturetool.org/workshops/14th-Overture-Workshop.html co-located with The Formal Methods Europe Symposium 2016  INTRODUCTION
Submitted by Anonymous on May 17th, 2016
Event
SOCNE 2016
CALL FOR PAPERS - Submission deadline May 20, 2016 Workshop on Service-Oriented Cyber-Physical Systems in Converging Networked Environments (SOCNE 2016)  in conjunction with ETFA 2016 Berlin, Germany |  23-27,September 06-09, 2016 | http://www.socne.org Selected Topics
Submitted by Anonymous on May 9th, 2016
The evolution of manufacturing systems from loose collections of cyber and physical components into true cyber-physical systems has expanded the opportunities for cyber-attacks against manufacturing. To ensure the continued production of high-quality parts in this new environment requires the development of novel security tools that transcend both the cyber and physical worlds. Potential cyber-attacks can cause undetectable changes in a manufacturing system that can adversely affect the product's design intent, performance, quality, or perceived quality. The result of this could be financially devastating by delaying a product's launch, ruining equipment, increasing warranty costs, or losing customer trust. More importantly, these attacks pose a risk to human safety, as operators and consumers could be using faulty equipment/products. New methods for detecting and diagnosing cyber-physical attacks will be studied and evaluated through our established industrial partners. The expected results of this project will contribute significantly in further securing our nation's manufacturing infrastructure. This project establishes a new vision for manufacturing cyber-security based upon modeling and understanding the correlation between cyber events that occur in a product/process development-cycle and the physical data generated during manufacturing. Specifically, the proposed research will take advantage of this correlation to characterize the relationships between cyber-attacks, process data, product quality observations, and side-channel impacts for the purpose of attack detection and diagnosis. These process characterizations will be coupled with new manufacturing specific cyber-attack taxonomies to provide a comprehensive understanding of attack surfaces for advanced manufacturing systems and their cyber-physical manifestations in manufacturing processes. This is a fundamental missing element in the manufacturing cyber-security body of knowledge. Finally, new forensic techniques, based on constraint optimization and machine learning, will be researched to differentiate process changes indicative of cyber-attacks from common variations in manufacturing due to inherent system variability.
Off
Vanderbilt University
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National Science Foundation
Submitted by Christopher White on April 25th, 2016
Additive Manufacturing holds the promise of revolutionizing manufacturing. One important trend is the emergence of cyber additive manufacturing communities for innovative design and fabrication. However, due to variations in materials and processes, design and computational algorithms currently have limited adaptability and scalability across different additive manufacturing systems. This award will establish the scientific foundation and engineering principles needed to achieve adaptability, extensibility, and system scalability in cyber-physical additive manufacturing systems, resulting in high efficiency and accuracy fabrication. The research will facilitate the evolution of existing isolated and loosely-connected additive manufacturing facilities into fully functioning cyber-physical additive manufacturing systems with increased capabilities. The application-based, smart interfacing infrastructure will complement existing cyber additive communities and enhance partnerships between academia, industry, and the general public. The research will contribute to the technology and engineering of Cyber-physical Systems and the economic competitiveness of US manufacturing. This interdisciplinary research will generate new curricular materials and help educate a new generation of cybermanufacturing workforce. The research will establish smart and dynamic system calibration methods and algorithms through deep learning that will enable high-confidence and interoperable cyber-physical additive manufacturing systems. The dynamic calibration and re-calibration algorithms will provide a smart interfacing layer of infrastructure between design models and physical additive manufacturing systems. Specific research tasks include: (1) Establishing smart and fast calibration algorithms to make physical additive manufacturing machines adaptable to design models; (2) Deriving prescriptive compensation algorithms to achieve extensible design models; (3) Dynamic recalibration through deep learning for improved predictive modeling and compensation; and (4) Developing a smart calibration server and APP prototype test bed for scalable additive cyberinfractures.
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Purdue University
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National Science Foundation
Submitted by Arman Sabbaghi on April 12th, 2016
Additive Manufacturing holds the promise of revolutionizing manufacturing. One important trend is the emergence of cyber additive manufacturing communities for innovative design and fabrication. However, due to variations in materials and processes, design and computational algorithms currently have limited adaptability and scalability across different additive manufacturing systems. This award will establish the scientific foundation and engineering principles needed to achieve adaptability, extensibility, and system scalability in cyber-physical additive manufacturing systems, resulting in high efficiency and accuracy fabrication. The research will facilitate the evolution of existing isolated and loosely-connected additive manufacturing facilities into fully functioning cyber-physical additive manufacturing systems with increased capabilities. The application-based, smart interfacing infrastructure will complement existing cyber additive communities and enhance partnerships between academia, industry, and the general public. The research will contribute to the technology and engineering of Cyber-physical Systems and the economic competitiveness of US manufacturing. This interdisciplinary research will generate new curricular materials and help educate a new generation of cybermanufacturing workforce. The research will establish smart and dynamic system calibration methods and algorithms through deep learning that will enable high-confidence and interoperable cyber-physical additive manufacturing systems. The dynamic calibration and re-calibration algorithms will provide a smart interfacing layer of infrastructure between design models and physical additive manufacturing systems. Specific research tasks include: (1) Establishing smart and fast calibration algorithms to make physical additive manufacturing machines adaptable to design models; (2) Deriving prescriptive compensation algorithms to achieve extensible design models; (3) Dynamic recalibration through deep learning for improved predictive modeling and compensation; and (4) Developing a smart calibration server and APP prototype test bed for scalable additive cyberinfrastructures.
Off
University of Southern California
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National Science Foundation
Submitted by Qiang Huang on March 31st, 2016

The National Institute of Standards and Technology (NIST) launched the 2016 Global City Teams Challenge (GCTC; see http://www.nist.gov/cps/sagc.cfm) with a kickoff meeting on November 12-13, 2015, in Gaithersburg, MD. This meeting brought together city planners and representatives from technology companies, academic institutions, and non-profits with the aim of fostering teams that will contribute to an overall vision for Smart and Connected Communities (S&CC) - effectively integrating networked information systems, sensing and communication devices, data sources, decision-making, and physical infrastructure to transform communities by improving quality of life, environmental health, social well-being, educational achievement, or overall economic growth and stability.

NIST's GCTC builds upon the National Science Foundation's (NSF) longstanding investments in cyber-physical systems (CPS). NSF established the CPS program in 2008 to develop the principles, methodologies, and tools needed to deeply embed computational intelligence, communications, and control, along with new mechanisms for sensing, actuation, and adaptation, into physical systems. The NSF CPS program, which today includes the participation of the U.S. Department of Homeland Security, U.S. Department of Transportation, National Aeronautics and Space Administration, and National Institutes of Health, has funded a strong portfolio of projects that together have pushed the boundaries of fundamental knowledge and systems engineering in core science and technology areas needed to support an ever-growing set of application domains. CPS investments are enabling systems that are central to emerging S&CC infrastructure and services, including in areas such as intelligent transportation systems (ground, aviation, and maritime), building control and automation, advanced manufacturing (including cyber-manufacturing), healthcare and medical devices, and the burgeoning Internet of Things (IoT). Dependability, security, privacy, and safety continue to be central priorities for the program in pursuing the vision of a world in which CPS dramatically improve quality of life. Along the way, the CPS program has also nurtured a vibrant CPS research community.

With this Dear Colleague letter (DCL), NSF is announcing its intention to fund EArly-Concept Grants for Exploratory Research (EAGER) proposals to support NSF researchers participating in the NIST GCTC, with the goal of pursuing novel research on the effective integration of networked computing systems and physical devices that will have significant impact in meeting the challenges of Smart and Connected Communities. Researchers must be members of, or be seeking to establish, GCTC teams that build upon the results of previous or active NSF-funded projects, and must provide evidence of active team membership and participation as part of the submission. [Note that, while this DCL is aligned with NSF’s broader efforts in Smart and Connected Communities (see http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf15120), a key requirement for this DCL is active participation in a GCTC team.] Proposals should emphasize the fundamental research inherent to the real-world problems being addressed; the manner in which the proposed solutions will be adopted by one or more local communities; and the potential challenges with respect to both research and deployment. Successful proposals will quantify the magnitude of potential societal impacts; and will result in transformative, long-term benefits rather than incremental advances. Finally, proposals must address why the work is appropriate for EAGER funding (see details below), including what key risks will be mitigated to facilitate future high-reward advances and why the timing of the project will maximize the potential for success.

The deadline for submission of EAGERs is April 1, 2016, but earlier submissions are encouraged, and decisions will be made on a first-come, first-serve basis.

Submission of EAGER proposals will be via Fastlane or Grants.gov. EAGER submissions should follow the NSF's Grant Proposal Guide (GPG) II.D.2 (see http://www.nsf.gov/publications/pub_summ.jsp?ods_key=gpg). (As noted in the GPG, EAGER is a funding mechanism for supporting exploratory work in its early stages on untested, but potentially transformative, research ideas or approaches. This work may be considered especially "high-risk/high-reward," for example, in the sense that it involves radically different approaches, applies new expertise, or engages novel disciplinary or interdisciplinary perspectives.)

An investigator may be included in only one submission in response to this DCL; if more than one is submitted, only the first one will be considered.

For further information, please contact the cognizant CPS program directors:

  • David Corman, CISE/CNS/CPS, dcorman@nsf.gov
  • Kishan Baheti, ENG/ECCS/EPCN, rbaheti@nsf.gov
  • Sylvia Spengler, CISE/IIS/CPS, sspengle@nsf.gov
  • Gurdip Singh, CISE/CNS/CSR, gsingh@nsf.gov
General Announcement
Not in Slideshow
Submitted by Anonymous on February 12th, 2016
Event
WOCO 2016
1st IFAC/IFIP Workshop on Computers and Control (WOCO 2016) Sponsored and Organised by IFAC TC3.1 Technical Committee on Computers for Control Co-Sponsored by IFIP WG 10.5 Design and Engineering of Electronic Systems WOCO 2016 is the first IFAC Workshop on Computer and Control following previous workshops organized by IFAC Technical Committee 3.3 as Workshop on Real-Time Programming (WRTP) and Algorithms and Architectures for Real-Time Control (AARTC) that were successfully organised during 30 editions.
Submitted by Anonymous on January 28th, 2016
This project aims to enable cyber-physical systems that can be worn on the body in order to one day allow their users to touch, feel, and manipulate computationally simulated three-dimensional objects or digital data in physically realistic ways, using the whole hand. It will do this by precisely measuring touch and movement-induced displacements of the skin in the hand, and by reproducing these signals interactively, via new technologies to be developed in the project. The resulting systems will offer the potential to impact a wide range of human activities that depend on touch and interaction with the hands. The project seeks to enable new applications for wearable cyber physical interfaces that may have broad applications in health care, manufacturing, consumer electronics, and entertainment. Although human interactive technologies have advanced greatly, current systems employ only a fraction of the sensorimotor capabilities of their users, greatly limiting applications and usability. The development of whole-hand haptic interfaces that allow their wearers to feel and manipulate digital content has been a longstanding goal of engineering research, but has remained far from reality. The reason can be traced to the difficulty of reproducing or even characterizing the complex, action-dependent stimuli that give rise to touch sensations during everyday activities. This project will pioneer new methods for imaging complex haptic stimuli, consisting of movement dependent skin strain and contact-induced surface waves propagating in skin, and for modeling the dependence of these signals on hand kinematics during grasping. It will use the resulting fundamental advances to catalyze the development of novel wearable CPS, in the form of whole-hand haptic interfaces. The latter will employ surface wave and skin strain feedback to supply haptic feedback to the hand during interaction with real and computational objects, enabling a range of new applications in VR. The project will be executed through research in three main research areas. In the first, it will utilize novel contact and non-contact techniques based on data acquired through on-body sensor arrays to measure whole-hand mechanical stimuli and grasping kinematics at high spatial and temporal resolution. In a second research area, it will undertake data-driven systems modeling and analysis of statistical contingencies between the kinematic and cutaneous sensed during everyday activities. In a third research area, it will engineer and perceptually evaluate novel cyber physical systems consisting of haptic interfaces for whole hand interaction. In order to further advance the applications of these systems in medicine, through a collaboration with the Drexel College of Medicine, the project will develop new methods for assessing clinical skills of palpation during medical examination, with the aim of improving the efficacy of what is often the first, most common, and best opportunity for diagnosis, using physician's own sense of touch.
Off
Drexel University
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National Science Foundation
Submitted by Yon Visell on December 22nd, 2015
The evolution of manufacturing systems from loose collections of cyber and physical components into true cyber-physical systems has expanded the opportunities for cyber-attacks against manufacturing. To ensure the continued production of high-quality parts in this new environment requires the development of novel security tools that transcend both the cyber and physical worlds. Potential cyber-attacks can cause undetectable changes in a manufacturing system that can adversely affect the product's design intent, performance, quality, or perceived quality. The result of this could be financially devastating by delaying a product's launch, ruining equipment, increasing warranty costs, or losing customer trust. More importantly, these attacks pose a risk to human safety, as operators and consumers could be using faulty equipment/products. New methods for detecting and diagnosing cyber-physical attacks will be studied and evaluated through our established industrial partners. The expected results of this project will contribute significantly in further securing our nation's manufacturing infrastructure. This project establishes a new vision for manufacturing cyber-security based upon modeling and understanding the correlation between cyber events that occur in a product/process development-cycle and the physical data generated during manufacturing. Specifically, the proposed research will take advantage of this correlation to characterize the relationships between cyber-attacks, process data, product quality observations, and side-channel impacts for the purpose of attack detection and diagnosis. These process characterizations will be coupled with new manufacturing specific cyber-attack taxonomies to provide a comprehensive understanding of attack surfaces for advanced manufacturing systems and their cyber-physical manifestations in manufacturing processes. This is a fundamental missing element in the manufacturing cyber-security body of knowledge. Finally, new forensic techniques, based on constraint optimization and machine learning, will be researched to differentiate process changes indicative of cyber-attacks from common variations in manufacturing due to inherent system variability.
Off
Virginia Polytechnic Institute and State University
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National Science Foundation
Christopher Williams
Lee Wells
Jaime Camelio Submitted by Jaime Camelio on December 21st, 2015
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