Posters (Sessions 8 & 13)
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This project advances the scientific knowledge on design methods for improving the resilience of civil infrastructures to disruptions. To improve resilience, critical services in civil infrastructure sectors must utilize new diagnostic tools and control algorithms that ensure survivability in the presence of both security attacks and random faults, and also include the models of incentives of human decision makers in the design process.
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By 2050, a staggering 70% of the world's population is projected to live and work in cities, and two-thirds of global primary energy consumption is attributed to cities, leading to 71% of global direct energy-related greenhouse gas emissions. Smart cities will consist of sustainable infrastructures with buildings as major constituents. Buildings' energy consumption contributes to more than 70% of electricity usages, with people spending more than 90% of their time in buildings nowadays.
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Visual identification of structural flaws is quite valuable not only to predict an imminent collapse of a bridge, but also to determine effective precautionary measures and repairs.
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In this NSF project, the team proposes to innovate a novel printing scheme that can embed piezoelectric transducers (namely, sensor/actuator coupled elements) into layered composites. As the transducers are densely distributed throughout the entire structure, they function like a nerve system embedded into the structure. Such a sensor nerve system, when combined with new control and command systems and advanced data and signal processing capability, can fully unleash the latest computing power to pinpoint the fault location.
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The growth and expansion of cities since the mid 20th century has led to a strong dependency on private automobiles. During the last years, urban planners have started rethinking the mobility modes in a city and have finally realized that a truly sustainable transportation and urban environment in general, requires a shift to multimodal transportation. In the PittSmartLiving project, we view the shift to multimodal transportation in a holistic way.
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Neuromorphic computing attempts to model neuro-biological architectures using analog electronic signals. One emerging concept for neuromorphic computing involves ionic-liquid gated oxide materials. In this poster we will overview our group's recent research investigating ionic liquid-amorphous metal oxide semiconductor interactions. Finally, we will overview a new large scale programmable neuromorphic computing concept, which combines ionic liquid electrowetting and ionic liquid control of a materials transport. We will show, that using a hydrated ionic liquid (BMIM-
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One of the challenges for the future cyber-physical systems is the exploration of large design spaces. Genetic algorithms (GAs), which embody a simplified computational model of the mutation and selection mechanisms of natural evolution, are known to be effective for design optimization. However, the traditional formulations are limited to choosing values for a predetermined set of parameters within a given fixed architecture.
