The terms denote engineering domains that have high CPS content.
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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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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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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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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.
