Time filter

Source Type

Plano, TX, United States

Lee S.,Nagoya Institute of Technology | Kasuga T.,Nagoya Institute of Technology | Kato K.,Advanced Integration Technology
Nippon Seramikkusu Kyokai Gakujutsu Ronbunshi/Journal of the Ceramic Society of Japan | Year: 2010

Biological safety of Y2O3 nanoparticles was investigated in vitro using mouse osteoblast-like cells (MC3T3-E1). The cell numbers after culture showed that smaller particles (0.03 μm) and higher concentration of Y2O3 particles had the highest cytotoxicity for MC3T3-E1 cells in comparison to larger particles (1 and 0.4 μm) and lower concentration, respectively. The development of actin filament and cell proliferation were found to be inhibited in the medium containing Y2O3 nanoparticles. Compared to the control, cells in the medium containing Y2O3 nanoparticles were smaller and had few actin filaments, indicating atrophy of the cells. Apoptosis was also observed in the medium containing 0.03μm sized Y2O3 particles. © 2010 The Ceramic Society of Japan.

Liu J.,Advanced Integration Technology | Liu J.,Chinese University of Hong Kong | David Simpson M.,University of Southampton | Yan J.,Chinese University of Hong Kong | Allen R.,University of Southampton
Physiological Measurement | Year: 2010

Cerebral autoregulation has been studied by linear filter systems, with arterial blood pressure (ABP) as the input and cerebral blood flow velocity (CBFV-from transcranial Doppler Ultrasound) as the output. The current work extends this by using adaptive filters to investigate the dynamics of time-varying cerebral autoregulation during step-wise changes in arterial PaCO2. Cerebral autoregulation was transiently impaired in 11 normal adult volunteers, by switching inspiratory air to a CO2/air mixture (5% CO2, 30% O2 and 65% N2) for approximately 2 min and then back to the ambient air, causing stepwise changes in end-tidal CO2 (EtCO2). Simultaneously, ABP and CBFV were recorded continuously. Simulated data corresponding to the same protocol were also generated using an established physiological model, in order to refine the signal analysis methods. Autoregulation was quantified by the time-varying phase lead, estimated from the adaptive filter model. The adaptive filter was able to follow rapid changes in autoregulation, as was confirmed in the simulated data. In the recorded signals, there was a slow decrease in autoregulatory function following the step-wise increase in PaCO2 (but this did not reach a steady state within approximately 2 min of recording), with a more rapid change in autoregulation on return to normocapnia. Adaptive filter modelling was thus able to demonstrate time-varying autoregulation. It was further noted that impairment and recovery of autoregulation during transient increases in EtCO2 occur in an asymmetric manner, which should be taken into account when designing experimental protocols for the study of autoregulation. © 2010 Institute of Physics and Engineering in Medicine.

Shao L.,University of Sheffield | Shao L.,Advanced Integration Technology | Mattivi R.,University of Trento
CIVR 2010 - 2010 ACM International Conference on Image and Video Retrieval | Year: 2010

In this paper, we evaluate and compare different feature detection and feature description methods for part-based approaches in human action recognition. Different methods have been proposed in the literature for both feature detection of space-time interest points and description of local video patches. It is however unclear which method performs better in the field of human action recognition. We compare, in the feature detection section, Dollar's method [18], Laptev's method [22], a bank of 3D-Gabor filters [6] and a method based on Space-Time Differences of Gaussians. We also compare and evaluate different descriptors such as Gradient [18], HOG-HOF [22], 3D SIFT [24] and an enhanced version of LBP-TOP [15]. We show the combination of Dollar's detection method and the improved LBP-TOP descriptor to be computationally efficient and to reach the best recognition accuracy on the KTH database. Copyright © 2010 ACM.

Huang L.,Chinese University of Hong Kong | Xu Q.,Chinese University of Hong Kong | Xu Q.,Advanced Integration Technology
Proceedings -Design, Automation and Test in Europe, DATE | Year: 2010

In this paper, we consider energy minimization for multiprocessor system-on-a-chip (MPSoC) under lifetime reliability constraint of the system, which has become a serious concern for the industry with technology scaling. As today's complex embedded systems typically have multiple execution modes, we first identify a set of "good" task allocation and schedules for each execution mode in terms of lifetime reliability and/or energy consumption, and then we introduce novel techniques to obtain an optimal combination of these single-mode solutions, which is able to minimize the energy consumption of the entire multi-mode system while satisfying given lifetime reliability constraint. Experimental results on several hypothetical MPSoC platforms with various task graphs demonstrate the effectiveness of the proposed approach. © 2010 EDAA.

Song X.,Halliburton Energy Corporation | Wang Y.,Advanced Integration Technology | Sun Z.,University of Minnesota
Automatica | Year: 2014

This paper focuses on the design of a low order robust stabilizer for the tracking/disturbance rejection problem based on the internal model principle in the time-varying setting and its application to the hydraulic pressure tracking with varying frequency. The problem of this kind known as output regulation generally consists of two major parts: internal model unit construction and stabilizer design. While the construction of the time-varying internal model unit is non-trivial by itself and a very recent research outcome enables its synthesis for a class of linear time-varying systems, the effective stabilization of the augmented system (internal model unit and plant) for practical applications remains a challenge. This is due to the need to stabilize the high order time-varying augmented system using a low order stabilizer in a robust fashion and with desirable transient performance. While directly applying the stabilization approaches for a general LTV system will result in a high order stabilizer, a new method is proposed in this paper that overcomes this bottleneck by taking advantage of the unique structure of the internal model based control system. Instead of using a dynamic stabilizer with high order, this approach uses a sequence of time-varying gains that are directly injected into the internal model unit. A critical issue addressed is how to avoid the non-convex optimization associated with the time-varying gain synthesis and then convert the stabilizer design into a series of Linear Matrix Inequalities (LMIs). The proposed control approach is then demonstrated on an electrohydraulic system. © 2014 Elsevier Ltd. All rights reserved.

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