University of Texas at Dallas

About: University of Texas at Dallas is a education organization based out in Richardson, Texas, United States. It is known for research contribution in the topics: Population & Computer science. The organization has 14986 authors who have published 35589 publications receiving 1293714 citations. The organization is also known as: UT-Dallas & UT Dallas.

Trust and Trustworthiness

Abstract: In this chapter, we discuss when, how, and why trust and trustworthiness arise to support cooperation within and across organizations. To do so, we first define trust and trustworthiness, discuss how they can be quantified and determine key components of trusting and trustworthy behavior. In addition, we identify building blocks of trust and trustworthiness and offer tangible insights about how to establish trusting and cooperative business/inter-organizational relationships, based on both academic research and case studies from across industries. We all know that trust and trustworthiness matter in almost all aspects of our relationships, business or otherwise. Our friends, foes, family, colleagues, sociologists, management scientists, and even economists recognize this fact (even though some may not acknowledge it). We innately believe being trustworthy is a virtue (or, at least, are taught to think so) and have learned whether and when to trust (to the best of our abilities). And when we trust, we put ourselves in a vulnerable situation (i.e., we take a risk) based upon the expectation that the person we trusted (trustee) behaves in a positive way that is rewarding to us (as trustors). So, we make a risky “investment” of some sort and face uncertainty in the outcome (and may even regret later) when we trust. We also perhaps adjust our trusting and trustworthy behavior depending on the target of our trust, given the relevant context. For example, we may trust our significant other that he or she will return the $250 (or the car) we lend him or her (perhaps with an implicit or explicit expectation of a positive return beyond the actual loan). We probably would not ask him or her to write a contract before lending our car. However, most of us would perhaps require a marriage certificate (a binding contract that can only be annulled after a legal hearing) accepting all requirements governing a marriage before we commit “to have and to hold from this day forward, for better, for worse, for richer, for poorer, in sickness and health, until death do us part...” and ensure that we provide and receive the care and commitment in the presence of conflicting objectives that we will all face during our marriage. Similarly, most successful business and economic relationships are built upon a considerable degree of mutual trust and trustworthiness. As Nobel Laureate Kenneth Arrow wrote, “Virtually every commercial transaction has within itself an element of trust” (Arrow 1972). Trust has been the glue for most transactions within and across cultures as long as humans have socialized and transacted. Business owners and practitioners are not oblivious to this fact. They do not begin talking with a potential partner by first writing a complete set of contracts stipulating all 1 Note that you neither need a marriage certificate nor need to rely on trust if (the big if) your spouse’s and your objectives are and will be perfectly aligned with absolutely no uncertainty 100% of the time during the span of your life. Similarly, in such a case, there is no need for a preor post-nuptial agreement.

Toward the Controlled Synthesis of Hexagonal Boron Nitride Films

Abstract: Atomically smooth hexagonal boron nitride (h-BN) layers have very useful properties and thus potential applications for protective coatings, deep ultraviolet (DUV) emitters, and as a dielectric for nanoelectronics devices. In this paper, we report on the growth of h-BN by a low-pressure chemical vapor deposition (LPCVD) process using diborane and ammonia as the gas precursors. The use of LPCVD allows synthesis of h-BN with a controlled number of layers defined by the growth conditions, temperature, time, and gas partial pressure. Furthermore, few-layer h-BN was also grown by a sequential growth method, and insights into the growth mechanism are described, thus forming the basis of future growth of h-BN by atomic layer epitaxy.

Semiparametric Filtering of Spatial Autocorrelation: The Eigenvector Approach

Abstract: In the context of spatial regression analysis, several methods can be used to control for the statistical effects of spatial dependencies among observations. Maximum likelihood or Bayesian approaches account for spatial dependencies in a parametric framework, whereas recent spatial filtering approaches focus on nonparametrically removing spatial autocorrelation. In this paper we propose a semiparametric spatial filtering approach that allows researchers to deal explicitly with (a) spatially lagged autoregressive models and (b) simultaneous autoregressive spatial models. As in one non-parametric spatial filtering approach, a specific subset of eigenvectors from a transformed spatial link matrix is used to capture dependencies among the disturbances of a spatial regression model. However, the optimal subset in the proposed filtering model is identified more intuitively by an objective function that minimizes spatial autocorrelation rather than maximizes a model fit. The proposed objective function has the a...

A survey of depth and inertial sensor fusion for human action recognition

Abstract: A number of review or survey articles have previously appeared on human action recognition where either vision sensors or inertial sensors are used individually. Considering that each sensor modality has its own limitations, in a number of previously published papers, it has been shown that the fusion of vision and inertial sensor data improves the accuracy of recognition. This survey article provides an overview of the recent investigations where both vision and inertial sensors are used together and simultaneously to perform human action recognition more effectively. The thrust of this survey is on the utilization of depth cameras and inertial sensors as these two types of sensors are cost-effective, commercially available, and more significantly they both provide 3D human action data. An overview of the components necessary to achieve fusion of data from depth and inertial sensors is provided. In addition, a review of the publicly available datasets that include depth and inertial data which are simultaneously captured via depth and inertial sensors is presented.

Jet energy measurement and its systematic uncertainty in proton-proton collisions at s√=7 TeV with the ATLAS detector

Abstract: The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton-proton collision data with a centre-of-mass energy of [Formula: see text] TeV corresponding to an integrated luminosity of [Formula: see text][Formula: see text]. Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells using the anti-[Formula: see text] algorithm with distance parameters [Formula: see text] or [Formula: see text], and are calibrated using MC simulations. A residual JES correction is applied to account for differences between data and MC simulations. This correction and its systematic uncertainty are estimated using a combination of in situ techniques exploiting the transverse momentum balance between a jet and a reference object such as a photon or a [Formula: see text] boson, for [Formula: see text] and pseudorapidities [Formula: see text]. The effect of multiple proton-proton interactions is corrected for, and an uncertainty is evaluated using in situ techniques. The smallest JES uncertainty of less than 1 % is found in the central calorimeter region ([Formula: see text]) for jets with [Formula: see text]. For central jets at lower [Formula: see text], the uncertainty is about 3 %. A consistent JES estimate is found using measurements of the calorimeter response of single hadrons in proton-proton collisions and test-beam data, which also provide the estimate for [Formula: see text] TeV. The calibration of forward jets is derived from dijet [Formula: see text] balance measurements. The resulting uncertainty reaches its largest value of 6 % for low-[Formula: see text] jets at [Formula: see text]. Additional JES uncertainties due to specific event topologies, such as close-by jets or selections of event samples with an enhanced content of jets originating from light quarks or gluons, are also discussed. The magnitude of these uncertainties depends on the event sample used in a given physics analysis, but typically amounts to 0.5-3 %.