Institution
University of Alabama
Education•Tuscaloosa, Alabama, United States•
About: University of Alabama is a education organization based out in Tuscaloosa, Alabama, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 27323 authors who have published 48609 publications receiving 1565337 citations. The organization is also known as: Alabama & Bama.
Topics: Population, Poison control, Galaxy, Health care, Large Hadron Collider
Papers published on a yearly basis
Papers
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TL;DR: In this article, results of searches for heavy stable charged particles produced in pp collisions at 7 and 8 TeV are presented corresponding to an integrated luminosity of 5.0 and 18.8 inverse femtobarns, respectively.
Abstract: Results of searches for heavy stable charged particles produced in pp collisions at sqrt(s) = 7 and 8 TeV are presented corresponding to an integrated luminosity of 5.0 inverse femtobarns and 18.8 inverse femtobarns, respectively. Data collected with the CMS detector are used to study the momentum, energy deposition, and time-of-flight of signal candidates. Leptons with an electric charge between e/3 and 8e, as well as bound states that can undergo charge exchange with the detector material, are studied. Analysis results are presented for various combinations of signatures in the inner tracker only, inner tracker and muon detector, and muon detector only. Detector signatures utilized are long time-of-flight to the outer muon system and anomalously high (or low) energy deposition in the inner tracker. The data are consistent with the expected background, and upper limits are set on the production cross section of long-lived gluinos, scalar top quarks, and scalar tau leptons, as well as pair produced long-lived leptons. Corresponding lower mass limits, ranging up to 1322 GeV for gluinos, are the most stringent to date.
276 citations
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TL;DR: Organizations may be able to improve burnout, dissatisfaction and retention by addressing communication and workflow, and initiating QI projects targeting clinician concerns.
Abstract: BACKGROUND
Work conditions in primary care are associated with physician burnout and lower quality of care.
275 citations
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TL;DR: In this paper, a review of phase change materials used to optimize building envelope and equipment is provided, and the existing gaps in the research works on energy performance improvement with phase change material are identified, and recommendations offered as authors' viewpoints in 5 aspects.
275 citations
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TL;DR: Analysis of a simplified genetics-based machine learning system considers a model of an immune system and shows how GAs can automatically and simultaneously discover effective groups of cooperative computational structures.
Abstract: In typical applications, genetic algorithms (GAs) process populations of potential problem solutions to evolve a single population member that specifies an 'optimized' solution. The majority of GA analysis has focused on these optimization applications. In other applications (notably learning classifier systems and certain connectionist learning systems), a GA searches for a population of cooperative structures that jointly perform a computational task. This paper presents an analysis of this type of GA problem. The analysis considers a simplified genetics-based machine learning system: a model of an immune system. In this model, a GA must discover a set of pattern-matching antibodies that effectively match a set of antigen patterns. Analysis shows how a GA can automatically evolve and sustain a diverse, cooperative population. The cooperation emerges as a natural part of the antigen-antibody matching procedure. This emergent effect is shown to be similar to fitness sharing, an explicit technique for multimodal GA optimization. Further analysis shows how the GA population can adapt to express various degrees of generalization. The results show how GAs can automatically and simultaneously discover effective groups of cooperative computational structures.
275 citations
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TL;DR: An energy sharing state-of-charge (SOC) balancing control scheme based on a distributed battery energy storage system architecture where the cell balancing system and the dc bus voltage regulation system are combined into a single system is presented.
Abstract: This paper presents an energy sharing state-of-charge (SOC) balancing control scheme based on a distributed battery energy storage system architecture where the cell balancing system and the dc bus voltage regulation system are combined into a single system. The battery cells are decoupled from one another by connecting each cell with a small lower power dc–dc power converter. The small power converters are utilized to achieve both SOC balancing between the battery cells and dc bus voltage regulation at the same time. The battery cells' SOC imbalance issue is addressed from the root by using the energy sharing concept to automatically adjust the discharge/charge rate of each cell while maintaining a regulated dc bus voltage. Consequently, there is no need to transfer the excess energy between the cells for SOC balancing. The theoretical basis and experimental prototype results are provided to illustrate and validate the proposed energy sharing controller.
275 citations
Authors
Showing all 27508 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jasvinder A. Singh | 176 | 2382 | 223370 |
Hongfang Liu | 166 | 2356 | 156290 |
Ian J. Deary | 166 | 1795 | 114161 |
Yongsun Kim | 156 | 2588 | 145619 |
Dong-Chul Son | 138 | 1370 | 98686 |
Simon C. Watkins | 135 | 950 | 68358 |
Kenichi Hatakeyama | 134 | 1731 | 102438 |
Conor Henderson | 133 | 1387 | 88725 |
Peter R Hobson | 133 | 1590 | 94257 |
Tulika Bose | 132 | 1285 | 88895 |
Helen F Heath | 132 | 1185 | 89466 |
James Rohlf | 131 | 1215 | 89436 |
Panos A Razis | 130 | 1287 | 90704 |
David B. Allison | 129 | 836 | 69697 |
Eduardo Marbán | 129 | 579 | 49586 |