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It is well-recognized that MEMS switches, compared to their more traditional solid state counterparts, have several important advantages for wireless communications. These include superior linearity, low insertion loss and high isolation. Indeed, many potential applications have been investigated such as Tx/Rx antenna switching, frequency band selection,(More)
Maneuver recognition and trajectory prediction of moving vehicles are two important and challenging tasks of advanced driver assistance systems (ADAS) at urban intersections. This paper presents a continuing work to handle these two problems in a consistent framework using non-parametric regression models. We provide a feature normalization scheme and(More)
Driving intention recognition and trajectory prediction of moving vehicles are two important requirements of future advanced driver assistance systems (ADAS) for urban intersections. In this paper, we present a consistent framework for solving these two problems. The key idea is to model the spatio-temporal dependencies of traffic situations with a(More)
Understanding of traffic situations is an essential part of future advanced driver assistance systems (ADAS). This has to handle spatio-temporal dependencies of multiple traffic participants and uncertainties from different sources. Most existing approaches use probabilistic generative joint structures like Hidden Markov Models (HMM), which have long been(More)
To achieve an appropriate level of reliance on an automated system, the operator must have an accurate system representation such that he/she is aware of the capabilities and limitations of the system. The appropriate use of an automated system can lead to optimal performance by the human-machine dyad. This study investigates the relationship between an(More)
Lipid droplets (LDs) provide an "on-demand" source of fatty acids (FAs) that can be mobilized in response to fluctuations in nutrient abundance. Surprisingly, the amount of LDs increases during prolonged periods of nutrient deprivation. Why cells store FAs in LDs during an energy crisis is unknown. Our data demonstrate that mTORC1-regulated autophagy is(More)
Recurrent Neural Network models are the state-of-the-art for Named Entity Recognition (NER). We present two innovations to improve the performance of these models. The first innovation is the introduction of residual connections between the Stacked Recurrent Neural Network model to address the degradation problem of deep neural networks. The second(More)
The emergence of new technologies, such as whole genome sequencing systems, which generate a large amount of data, is requiring ultrahigh storage capacities. Due to their compactness and low power consumption, probe-based memory devices using Pb(Zr(0.2)Ti(0.8))O(3) (PZT) ferroelectric films are the ideal candidate for such applications where portability is(More)
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