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.

The Transform and Data Compression Handbook

Abstract: From the Publisher: The Transform and Data Compression Handbook serves as a handbook for a wide range of researchers and engineers." "The authors describe various discrete transforms and their applications in different disciplines. They cover techniques, such as adaptive quantization and entropy coding, that result in significant reduction in bit rates when applied to the transform coefficients. With presentations of the ideas and concepts, as well as descriptions of the algorithms, the authors provide insight into the applications and their limitations. Data compression is an essential step towards the efficient storage and transmission of information. The Transform and Data Compression Handbook provides information regarding different discrete transforms and demonstrates their power and practicality in data compression.

Group recommendation: semantics and efficiency

Abstract: We study the problem of group recommendation. Recommendation is an important information exploration paradigm that retrieves interesting items for users based on their profiles and past activities. Single user recommendation has received significant attention in the past due to its extensive use in Amazon and Netflix. How to recommend to a group of users who may or may not share similar tastes, however, is still an open problem. The need for group recommendation arises in many scenarios: a movie for friends to watch together, a travel destination for a family to spend a holiday break, and a good restaurant for colleagues to have a working lunch. Intuitively, items that are ideal for recommendation to a group may be quite different from those for individual members. In this paper, we analyze the desiderata of group recommendation and propose a formal semantics that accounts for both item relevance to a group and disagreements among group members. We design and implement algorithms for efficiently computing group recommendations. We evaluate our group recommendation method through a comprehensive user study conducted on Amazon Mechanical Turk and demonstrate that incorporating disagreements is critical to the effectiveness of group recommendation. We further evaluate the efficiency and scalability of our algorithms on the MovieLens data set with 10M ratings.

Undone Science: Charting Social Movement and Civil Society Challenges to Research Agenda Setting.

Abstract: "Undone science" refers to areas of research that are left unfunded, incomplete, or generally ignored but that social movements or civil society organizations often identify as worthy of more research. This study mobilizes four recent studies to further elaborate the concept of undone science as it relates to the political construction of research agendas. Using these cases, we develop the argument that undone science is part of a broader politics of knowledge, wherein multiple and competing groups struggle over the construction and implementation of alternative research agendas. Overall, the study demonstrates the analytic potential of the concept of undone science to deepen understanding of the systematic nonproduction of knowledge in the institutional matrix of state, industry, and social movements that is characteristic of recent calls for a "new political sociology of science."

From arms‐length to collaborative relationships in the supply chain: An evolutionary process

Abstract: Buyer‐supplier relationships play an important role in an organization’s ability to respond to dynamic and unpredictable change. If the relationship is too restrictive, flexibility will be difficult to achieve and, if it is too lenient the risk of opportunism will be present. This paper provides a framework for understanding how buyer‐supplier relationships have evolved over the past two decades from transaction processes based on arms‐length agreements to collaborative processes based on trust and information sharing. To achieve this objective, buyer‐supplier relationships are reviewed from the perspectives of transaction cost theory, strategy‐structure theory and resource‐based theory of the firm. Findings from early supply chain research are contrasted with the findings of more current research to provide a better understanding of how these relationships have changed. Current theory is extended by offering two proposals that test the influence of trust and information sharing and a third proposal that rejects the notion that supply chain alliances lead to monopolistic practices.

The Role of Ethical Climate on Salesperson’s Role Stress, Job Attitudes, Turnover Intention, and Job Performance

Abstract: This study builds on previous research to investigate the effects of ethical climate on salesperson’s role stress, job attitudes, turnover intention, and job performance. Responses from 138 salespeople who work for a large retailer selling high-end consumer durables at 68 stores in 16 states were used to examine the process through which ethical climate affects organizational variables. This is the first study offering empirical evidence that both job stress and job attitudes are the mechanisms through which a high ethical climate leads to lower turnover intention and higher job performance. Results indicate that ethical climate results in lower role conflict and role ambiguity and higher satisfaction, which, in turn, leads to lower turnover intention and organizational commitment. Also, findings indicate that organizational commitment is a significant predictor of job performance.