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Institution

Wichita State University

EducationWichita, Kansas, United States
About: Wichita State University is a education organization based out in Wichita, Kansas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 4988 authors who have published 9563 publications receiving 253824 citations. The organization is also known as: WSU & Fairmount College.
Topics: Population, Poison control, Health care, Relay, Vortex


Papers
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Proceedings ArticleDOI
25 Jun 2012
TL;DR: This work first empirically studies the energy consumption for various types of applications and presents an analytical model that helps characterize energy consumption of mobile devices under both the cloud and non-cloud application scenarios.
Abstract: The cloud computing paradigm enables the work anywhere anytime paradigm by allowing application execution and data storage on remote servers. This is especially useful for mobile computing and communication devices that are constrained in terms of computation power and storage. It is however not clear how preferable cloud-based applications would be for mobile device users. For users of such battery life constrained devices, the most important criteria might be the energy consumed by the applications they run. The goal of this work is to characterize under what scenarios cloud-based applications would be relatively more energy-efficient for users of mobile devices. This work first empirically studies the energy consumption for various types of applications and for multiple classes of devices to make this determination. Subsequently, it presents an analytical model that helps characterize energy consumption of mobile devices under both the cloud and non-cloud application scenarios. Finally, an algorithm GreenSpot is presented that considers application features and energy-performance tradeoffs to determine whether cloud or local execution will be more preferable.

64 citations

Journal ArticleDOI
TL;DR: It was found that target size influenced the shape of velocity profiles by elongating the duration of the corrective sub-movement phase, while movement distance scaled the entire velocity curve without affecting its shape.

63 citations

Journal ArticleDOI
TL;DR: In this article, a model-based fitting technique is presented to characterize the cure kinetics during liquid composite molding (LCM), and its accuracy is studied numerically and then is validated with experiments.
Abstract: In Liquid Composite Molding (LCM), resin impregnates the fiber preform and it subsequently cures to form the composite part. The curing phenomenon is an exothermic process, and it requires optimization of the mold heating profile to reduce the cure cycle time and the cure-induced thermal stress in the composite part. To optimize and control the cure cycle, it is necessary to obtain the resin cure kinetic parameters, which are usually measured offline by Differential Scanning Calorimetry (DSC) or Fourier transform infrared spectroscopy. These parameters measured from neat resin sometimes vary substantially due to the presence of fiber sizing or resin handling and, hence, curing of the LCM can be different from one batch cycle to another. In this paper, a model-based fitting technique is presented to characterize the cure kinetics during LCM and its accuracy is studied numerically and then is validated with experiments. A non-isothermal cure simulation of a composite part is performed based on a given set of cure kinetic parameters, which are the targets of the fitting model. The Genetic Algorithm is used to determine the cure kinetic parameters by matching the simulated temperature field based on the guessed cure parameters with the temperature history actually experienced by the composite part. An uncertainty in temperature reading, which usually happens in real temperature measurement and control, is introduced to evaluate the accuracy and stability of this characterization technique with respect to various fitting periods during curing stage. Since the mold heating cycle will affect the cure history and the cure kinetics characterization, the influence of the mold wall temperature on the characterization accuracy is also investigated. The numerical results show that, by appropriately choosing the mold heating cycle, one will be able to enhance the accuracy and stability of the cure kinetics characterization within a reduced characterization period. Hence, one may reserve more time for the subsequent online cure optimization and control during the cure cycle. An experimental study is also presented to validate this direct cure kinetics characterization method using Vacuum Assisted Resin Transfer Molding (VARTM) process.

63 citations

Journal ArticleDOI
TL;DR: In this article, the authors investigate how the comparability of a company's financial statements is related to its cost of equity capital, and find that greater financial statement comparability is associated with lower cost of capital.
Abstract: SYNOPSIS: We investigate how the comparability of a company's financial statements is related to its cost of equity capital. The Financial Accounting Standards Board's (FASB 2010) Statement of Financial Accounting Concept No. 8 proposes that comparability is a key tenet of accounting because it allows users of financial statements to benchmark a firm against similar firms when distinguishing between alternative investment opportunities. We provide evidence that greater financial statement comparability is associated with lower cost of equity capital, and show that comparability's effect on cost of equity remains after controlling for within-firm accounting quality. Additionally, we find that investors derive greater benefits from financial statement comparability in firms whose information environments are less transparent (high information asymmetry) and whose equity shares trade in markets that are less competitive (imperfect markets). Our findings contribute to accounting research by providing evidence...

63 citations


Authors

Showing all 5021 results

NameH-indexPapersCitations
Herbert A. Simon157745194597
Rui Zhang1512625107917
Frederick Wolfe119417101272
Shunichi Fukuzumi111125652764
Robert Y. Moore9524535941
Maurizio Salaris7641720927
Annie K. Powell7348622020
Gunther Uhlmann7244419560
Danielle S. McNamara7053922142
Jonathan P. Hill6736719271
Francis D'Souza6647716662
Osamu Ito6554917035
Louis J. Guillette6433820263
Karl A. Gschneidner6467522712
Robert Reid5921512097
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202314
202259
2021331
2020351
2019325
2018327