National CPS PI Meeting 2015
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The CrAVES project seeks to lay down intellectual foundations for credible autocoding of embedded systems, by which model-level control system specifications that satisfy given open-loop and closed-loop properties are automatically transformed into source code guaranteed to satisfy the same properties. The goal is that the correctness of these codes can be easily and independently verified by dedicated proof checking systems.
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This project combines Cyber Physical Systems (CPS) and gigabit networks to address major health concerns due to air pollution. A working demonstration of this project will be presented during the Global City Teams meeting in June 2015 with an update in June 2016. A wide range of health outcomes is affected by air pollution.
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The realization of a robust infrastructure that enables simultaneous transport of many micron and smaller sized particles will have a transformative impact on a vast range of areas such as medicine, drug development, electronics, and bio-materials.
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The objective of this research is the development of a framework for assessing the reliability and safety of robotic surgery systems during development, field testing, and general deployment. The framework uses accurate simulations to assess pre-clinical reliability before deployment. After deployment, the framework uses data collection through online monitoring of the system as it is being used in the field, followed by analysis to obtain assessments of operational reliability and safety.
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This Cyber-Physical Systems (CPS) project supports research to enable the automated monitoring of building and infrastructure construction projects. The purpose of construction monitoring is to provide developers, contractors, subcontractors, and tradesmen with the information they need to easily and quickly make project control decisions. These decisions have a direct impact on the overall efficiency of a construction project.
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Success of numerous long-term robotic network missions in space, air, ground, and water is measured by the ability of the robots to operate for extended time in highly dynamic and potentially hazardous operating environments. The proposed work responds to the urgency for development of innovative mobile power distribution systems that lower deployment and operating costs, while simultaneously increasing mission efficiency, and supporting the network's need to be responsive to changing physical conditions.
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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.
