scispace - formally typeset
Search or ask a question
Institution

University of Texas at Arlington

EducationArlington, Texas, United States
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.


Papers
More filters
Journal ArticleDOI
TL;DR: Results using high‐throughput sequencing to obtain a large number of microsatellite loci from the venomous snake Agkistrodon contortrix, the copperhead were rapid, cost‐effective and identified thousands of useful micros satellite loci in a previously unstudied species.
Abstract: Optimalintegrationofnext-generationsequencingintomainstreamresearchrequiresre-evaluation of how problems can be reasonably overcome and what questions can be asked. One potential application is the rapid acquisition of genomic information to identify microsatellite loci for evolutionary, population genetic and chromosome linkage mapping research on non-model and not previously sequenced organisms. Here, we report on results using highthroughputsequencingtoobtainalargenumberofmicrosatellitelocifromthevenomoussnake Agkistrodon contortrix, the copperhead. We used the 454 Genome Sequencer FLX next-generation sequencing platform to sample randomly 27 Mbp (128 773 reads) of the copperhead genome,thussamplingabout2%ofthegenomeofthisspecies.Weidentifiedmicrosatelliteloci in 11.3% of all reads obtained, with 14 612 microsatellite loci identified in total, 4564 of which had flanking sequences suitable for polymerase chain reaction primer design. The random sequencing-based approach to identify microsatellites was rapid, cost-effective and identified thousandsofusefulmicrosatellitelociinapreviouslyunstudiedspecies.

206 citations

Journal ArticleDOI
TL;DR: In this paper, a combination of quantitative techniques were applied to determine the reasons why workers leave China's export factories, trying to identify the root causes of job dissatisfaction leading to turnover and providing managerial implications that may assist managers in dealing with labor-related supply chain risks.

206 citations

Book ChapterDOI
08 Sep 2018
TL;DR: This paper proposes a weakly supervised region proposal network which is trained using only image-level annotations and achieves the state-of-the-art performance for WSOD with performance gain of about \(3\%\) on average.
Abstract: The Convolutional Neural Network (CNN) based region proposal generation method (i.e. region proposal network), trained using bounding box annotations, is an essential component in modern fully supervised object detectors. However, Weakly Supervised Object Detection (WSOD) has not benefited from CNN-based proposal generation due to the absence of bounding box annotations, and is relying on standard proposal generation methods such as selective search. In this paper, we propose a weakly supervised region proposal network which is trained using only image-level annotations. The weakly supervised region proposal network consists of two stages. The first stage evaluates the objectness scores of sliding window boxes by exploiting the low-level information in CNN and the second stage refines the proposals from the first stage using a region-based CNN classifier. Our proposed region proposal network is suitable for WSOD, can be plugged into a WSOD network easily, and can share its convolutional computations with the WSOD network. Experiments on the PASCAL VOC and ImageNet detection datasets show that our method achieves the state-of-the-art performance for WSOD with performance gain of about \(3\%\) on average.

206 citations

Journal ArticleDOI
TL;DR: This paper studies the problem of allocation of tasks onto a computational grid with the aim to simultaneously minimize the energy consumption and the makespan subject to the constraints of deadlines and tasks' architectural requirements and proposes a solution from cooperative game theory based on the concept of Nash bargaining solution.
Abstract: With the explosive growth in computers and the growing scarcity in electric supply, reduction of energy consumption in large-scale computing systems has become a research issue of paramount importance. In this paper, we study the problem of allocation of tasks onto a computational grid, with the aim to simultaneously minimize the energy consumption and the makespan subject to the constraints of deadlines and tasks' architectural requirements. We propose a solution from cooperative game theory based on the concept of Nash bargaining solution. In this cooperative game, machines collectively arrive at a decision that describes the task allocation that is collectively best for the system, ensuring that the allocations are both energy and makespan optimized. Through rigorous mathematical proofs we show that the proposed cooperative game in mere O(n mlog(m)) time (where n is the number of tasks and m is the number of machines in the system) produces a Nash bargaining solution that guarantees Pareto-optimally. The simulation results show that the proposed technique achieves superior performance compared to the greedy and linear relaxation (LR) heuristics, and with competitive performance relative to the optimal solution implemented in LINDO for small-scale problems.

206 citations

Journal ArticleDOI
TL;DR: Results contribute to the continuing discussion about the impact that the Internet and its tools are having on relationships by suggesting that, rather than promoting isolation, computer-mediated communication tools such as blogs often function to enhance existing relationships.
Abstract: This research explores variables related to the use of personal-journal style blogs for interpersonal goals. A random sample of bloggers completed surveys exploring how the combination of extraversion and self-disclosure affect strong tie network size, which in turn serves as motivation to use blogs as an alternative communication channel. Bloggers who exhibit both extraversion and self-disclosure traits tend to maintain larger strong-tie social networks and are more likely to appropriate blogs to support those relationships. Age, gender, and education have no relationship to network size, blog content, or the use of blogs as a relationship maintenance tool. These results contribute to the continuing discussion about the impact that the Internet and its tools are having on relationships by suggesting that, rather than promoting isolation, computer-mediated communication tools such as blogs often function to enhance existing relationships.

205 citations


Authors

Showing all 11918 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Hyun-Chul Kim1764076183227
David H. Adams1551613117783
Andrew White1491494113874
Kaushik De1391625102058
Steven F. Maier13458860382
Andrew Brandt132124694676
Amir Farbin131112583388
Evangelos Gazis131114784159
Lee Sawyer130134088419
Fernando Barreiro130108283413
Stavros Maltezos12994379654
Elizabeth Gallas129115785027
Francois Vazeille12995279800
Sotirios Vlachos12878977317
Network Information
Related Institutions (5)
Georgia Institute of Technology
119K papers, 4.6M citations

95% related

University of Maryland, College Park
155.9K papers, 7.2M citations

95% related

Pennsylvania State University
196.8K papers, 8.3M citations

95% related

University of Illinois at Urbana–Champaign
225.1K papers, 10.1M citations

94% related

University of Texas at Austin
206.2K papers, 9M citations

94% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202353
2022243
20211,721
20201,664
20191,493
20181,462