University of Texas at Arlington

About: University of Texas at Arlington is a education organization based out in Arlington, Texas, United States. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 11758 authors who have published 28598 publications receiving 801626 citations. The organization is also known as: UT Arlington & University of Texas-Arlington.

ATLAS Run 1 searches for direct pair production of third-generation squarks at the Large Hadron Collider

Abstract: This paper reviews and extends searches for the direct pair production of the scalar supersymmetric partners of the top and bottom quarks in proton-proton collisions collected by the ATLAS collaboration during the LHC Run 1. Most of the analyses use 20 [Formula: see text] of collisions at a centre-of-mass energy of [Formula: see text] TeV, although in some case an additional [Formula: see text] of collision data at [Formula: see text] TeV are used. New analyses are introduced to improve the sensitivity to specific regions of the model parameter space. Since no evidence of third-generation squarks is found, exclusion limits are derived by combining several analyses and are presented in both a simplified model framework, assuming simple decay chains, as well as within the context of more elaborate phenomenological supersymmetric models.

Distributed Tertiary Control of DC Microgrid Clusters

Abstract: A distributed control method is proposed to handle power sharing among a cluster of dc microgrids. The hierarchical control structure of microgrids includes primary, secondary, and tertiary levels. While the load sharing among the sources within a dc microgrid is managed through primary and secondary controllers, a tertiary control level is required to provide the higher level load sharing among microgrids within a cluster. Power transfer between microgrids enables maximum utilization of renewable sources and suppresses stress and aging of the components, which improves its reliability and availability, reduces the maintenance costs, and expands the overall lifespan of the network. The proposed control mechanism uses a cooperative approach to adjust voltage set points for individual microgrids and, accordingly, navigate the power flow among them. Loading mismatch among neighbor microgrids is used in an updating policy to adjust voltage set point and mitigate such mismatches. While the voltage adjustment policy handles the load sharing among the microgrids within each cluster, at a lower level, each microgrid carries a communication network that is in contact with the secondary control system. It is this lower level network that propagates voltage set points across all sources within a microgrid. Load sharing and set point propagation are analytically studied for the higher and lower level controllers, respectively. Experimental studies on two cluster setups demonstrate excellent controller performance and validate its resiliency against converter failures and communication losses.

Video quality assessment using a statistical model of human visual speed perception.

Abstract: Motion is one of the most important types of information contained in natural video, but direct use of motion information in the design of video quality assessment algorithms has not been deeply investigated. Here we propose to incorporate a recent model of human visual speed perception [Nat. Neurosci. 9, 578 (2006)] and model visual perception in an information communication framework. This allows us to estimate both the motion information content and the perceptual uncertainty in video signals. Improved video quality assessment algorithms are obtained by incorporating the model as spatiotemporal weighting factors, where the weight increases with the information content and decreases with the perceptual uncertainty. Consistent improvement over existing video quality assessment algorithms is observed in our validation with the video quality experts group Phase I test data set.