The document was issued by academy or academy organization.
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Abstract:
Stroke is the major cause of disability in adults in the western world, often resulting in hemiparesis and severe mobility impairments. Recently, rigid exoskeletons have been introduced for clinic-based gait rehabilitation: these systems can apply high levels of assistance, but also introduce kinematic restrictions and significant additional mass to the patient. As such, these devices are well suited to patients with little to no residual mobility (e.g.
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Cyber-physical systems (CPS) encompass the next generation of computerized control for countless aspects of the physical world and interactions thereof. The typical engineering process for CPS reuses existing designs, models, components, and software from one version to the next.
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One defining feature of cyberphysical systems is the fact that human users are closely intertwined with the physical system. Yet both the system and users themselves are often do not explicitly know how users would behave. A natural question arises: How do we design cyberphysical systems that effectively learn about their users, and optimize system behavior accordingly? This poster presents the idea of active regression as a vehicle to learn about users.
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Overview. The fundamental challenge in cyber-physical systems is the confluence of distinct scientific and engineering models, methods, and tools for cyber and physical systems. Cyber systems are primarily about processing information, formally modeled as patterns of bits. Physical systems are primarily about structure and dynamics, the evolution of the state of the system in time. There are certainly connections between these models, methods, and tools.
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We developed a systematic analytical and computational framework for the vulnerability analysis and mitigation of data integrity attacks on Phasor Measurement Units (PMUs) employed for wide area monitoring and control of power system. The analytical framework is based on the stability theory of stochastic dynamical system and it allows one to systematically determine the PMUs most critical to power network security.
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People with upper extremity disabilities are gaining increased independence through the use of assistive robotic arms, but performing tasks that require many small precise movements remains difficult. In fact, a confounding factor is that the more severe a person's motor impairment, the more limited are the control interfaces available to them to operate the system.
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This project develops an integrated design and simulation environment for the creation of miniature capsule robots (MCRs). An MCR is a biocompatible Cyber-Physical System (CPS) designed to operate in the human body to accomplish diagnostic or therapeutic tasks (e.g., colonoscopy, abdominal surgery, etc.). A typical MCR has to fulfill three main constraints: safety, low power operation and small size. Advances in miniaturization of electronic devices have made MCRs a reality.
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During the development process of CPS, an analysis of whether the system operates safely in its target environment is of utmost importance. For many applications of CPS research such as the transportation industry, this implies interconnected research in formal verification of CPS with research on knowledge representation and reasoning in multi-agent systems. The need for such research has become tragically clear in transportation accidents, one notorious case being the Air France 447 flight incident.
