869 resultados para resource -based theory
Resumo:
The increasing needs for computational power in areas such as weather simulation, genomics or Internet applications have led to sharing of geographically distributed and heterogeneous resources from commercial data centers and scientific institutions. Research in the areas of utility, grid and cloud computing, together with improvements in network and hardware virtualization has resulted in methods to locate and use resources to rapidly provision virtual environments in a flexible manner, while lowering costs for consumers and providers. However, there is still a lack of methodologies to enable efficient and seamless sharing of resources among institutions. In this work, we concentrate in the problem of executing parallel scientific applications across distributed resources belonging to separate organizations. Our approach can be divided in three main points. First, we define and implement an interoperable grid protocol to distribute job workloads among partners with different middleware and execution resources. Second, we research and implement different policies for virtual resource provisioning and job-to-resource allocation, taking advantage of their cooperation to improve execution cost and performance. Third, we explore the consequences of on-demand provisioning and allocation in the problem of site-selection for the execution of parallel workloads, and propose new strategies to reduce job slowdown and overall cost.
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The purpose of this study was to explore the relationship between faculty perceptions, selected demographics, implementation of elements of transactional distance theory and online web-based course completion rates. This theory posits that the high transactional distance of online courses makes it difficult for students to complete these courses successfully; too often this is associated with low completion rates. Faculty members play an indispensable role in course design, whether online or face-to-face. They also influence course delivery format from design through implementation and ultimately to how students will experience the course. This study used transactional distance theory as the conceptual framework to examine the relationship between teaching and learning strategies used by faculty members to help students complete online courses. Faculty members’ sex, number of years teaching online at the college, and their online course completion rates were considered. A researcher-developed survey was used to collect data from 348 faculty members who teach online at two prominent colleges in the southeastern part of United States. An exploratory factor analysis resulted in six factors related to transactional distance theory. The factors accounted for slightly over 65% of the variance of transactional distance scores as measured by the survey instrument. Results provided support for Moore’s (1993) theory of transactional distance. Female faculty members scored higher in all the factors of transactional distance theory when compared to men. Faculty number of years teaching online at the college level correlated significantly with all the elements of transactional distance theory. Regression analysis was used to determine that two of the factors, instructor interface and instructor-learner interaction, accounted for 12% of the variance in student online course completion rates. In conclusion, of the six factors found, the two with the highest percentage scores were instructor interface and instructor-learner interaction. This finding, while in alignment with the literature concerning the dialogue element of transactional distance theory, brings a special interest to the importance of instructor interface as a factor. Surprisingly, based on the reviewed literature on transactional distance theory, faculty perceptions concerning learner-learner interaction was not an important factor and there was no learner-content interaction factor.
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The frequency, time and places of charging have large impact on the Quality of Experience (QoE) of EV drivers. It is critical to design effective EV charging scheduling system to improve the QoE of EV drivers. In order to improve EV charging QoE and utilization of CSs, we develop an innovative travel plan aware charging scheduling scheme for moving EVs to be charged at Charging Stations (CS). In the design of the proposed charging scheduling scheme for moving EVs, the travel routes of EVs and the utility of CSs are taken into consideration. The assignment of EVs to CSs is modeled as a two-sided many-to-one matching game with the objective of maximizing the system utility which reflects the satisfactory degrees of EVs and the profits of CSs. A Stable Matching Algorithm (SMA) is proposed to seek stable matching between charging EVs and CSs. Furthermore, an improved Learning based On-LiNe scheduling Algorithm (LONA) is proposed to be executed by each CS in a distributed manner. The performance gain of the average system utility by the SMA is up to 38.2% comparing to the Random Charging Scheduling (RCS) algorithm, and 4.67% comparing to Only utility of Electric Vehicle Concerned (OEVC) scheme. The effectiveness of the proposed SMA and LONA is also demonstrated by simulations in terms of the satisfactory ratio of charging EVs and the the convergence speed of iteration.
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The aim of the present study is to test a theory-based model of suicide in a low-risk nonclinical sample. A community sample of convenience of 200 adults, 102 men and 98 women, responded to the Depressive Experiences Questionnaire, the Center for the Epidemiologic Studies of Depression Scale, the Psychache Scale, the Interpersonal Needs Questionnaire, and the Suicide Behaviors Questionnaire Revised. The hypothesized structural equation model, including trait dimensions of self-criticism and neediness, and state dimensions of depression, psychache, perceived burdensomeness, and thwarted belongingness, fit the observed data well and significantly explained 49% of the variance of suicidality.
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The main topic of this thesis is confounding in linear regression models. It arises when a relationship between an observed process, the covariate, and an outcome process, the response, is influenced by an unmeasured process, the confounder, associated with both. Consequently, the estimators for the regression coefficients of the measured covariates might be severely biased, less efficient and characterized by misleading interpretations. Confounding is an issue when the primary target of the work is the estimation of the regression parameters. The central point of the dissertation is the evaluation of the sampling properties of parameter estimators. This work aims to extend the spatial confounding framework to general structured settings and to understand the behaviour of confounding as a function of the data generating process structure parameters in several scenarios focusing on the joint covariate-confounder structure. In line with the spatial statistics literature, our purpose is to quantify the sampling properties of the regression coefficient estimators and, in turn, to identify the most prominent quantities depending on the generative mechanism impacting confounding. Once the sampling properties of the estimator conditionally on the covariate process are derived as ratios of dependent quadratic forms in Gaussian random variables, we provide an analytic expression of the marginal sampling properties of the estimator using Carlson’s R function. Additionally, we propose a representative quantity for the magnitude of confounding as a proxy of the bias, its first-order Laplace approximation. To conclude, we work under several frameworks considering spatial and temporal data with specific assumptions regarding the covariance and cross-covariance functions used to generate the processes involved. This study allows us to claim that the variability of the confounder-covariate interaction and of the covariate plays the most relevant role in determining the principal marker of the magnitude of confounding.
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Background: A relative friability to capture a sufficiently large patient population in any one geographic location has traditionally limited research into rare diseases. Methods and Results: Clinicians interested in the rare disease lymphangioleiomyomatosis (LAM) have worked with the LAM Treatment Alliance, the MIT Media Lab, and Clozure Associates to cooperate in the design of a state-of-the-art data coordination platform that can be used for clinical trials and other research focused on the global LAM patient population. This platform is a component of a set of web-based resources, including a patient self-report data portal, aimed at accelerating research in rare diseases in a rigorous fashion. Conclusions: Collaboration between clinicians, researchers, advocacy groups, and patients can create essential community resource infrastructure to accelerate rare disease research. The International LAM Registry is an example of such an effort.
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Background: The present work aims at the application of the decision theory to radiological image quality control ( QC) in diagnostic routine. The main problem addressed in the framework of decision theory is to accept or reject a film lot of a radiology service. The probability of each decision of a determined set of variables was obtained from the selected films. Methods: Based on a radiology service routine a decision probability function was determined for each considered group of combination characteristics. These characteristics were related to the film quality control. These parameters were also framed in a set of 8 possibilities, resulting in 256 possible decision rules. In order to determine a general utility application function to access the decision risk, we have used a simple unique parameter called r. The payoffs chosen were: diagnostic's result (correct/incorrect), cost (high/low), and patient satisfaction (yes/no) resulting in eight possible combinations. Results: Depending on the value of r, more or less risk will occur related to the decision-making. The utility function was evaluated in order to determine the probability of a decision. The decision was made with patients or administrators' opinions from a radiology service center. Conclusion: The model is a formal quantitative approach to make a decision related to the medical imaging quality, providing an instrument to discriminate what is really necessary to accept or reject a film or a film lot. The method presented herein can help to access the risk level of an incorrect radiological diagnosis decision.
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Using a combination of density functional theory and recursive Green's functions techniques, we present a full description of a large scale sensor, accounting for disorder and different coverages. Here, we use this method to demonstrate the functionality of nitrogen-rich carbon nanotubes as ammonia sensors as an example. We show how the molecules one wishes to detect bind to the most relevant defects on the nanotube, describe how these interactions lead to changes in the electronic transport properties of each isolated defect, and demonstrate that there are significative resistance changes even in the presence of disorder, elucidating how a realistic nanosensor works.
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The diluted magnetic semiconductors are promising materials for spintronic applications. Usually one intents to find the ferromagnetic state but recently the antiferromagnetism (AFM) was proposed to have some advantages. In this work, we verify the possibility to obtain spin polarization with an AFM state. In particular, we studied GaN 5% double doped with two different transition metals atoms (Mn and Co or Cr and Ni), forming the Mn(x)Co(0.056-x)Ga(0.944)N and Cr(x)Ni(0.056-x)Ga(0.944)N quaternary alloys. In order to simulate these systems in a more realistic way, and take into account composition fluctuations, we adapted the generalized quasichemical approach to diluted alloys, which is used in combination with spin density-functional theory. We find that is possible to obtain an AFM ground state up to 70% spin polarization.
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In this work, we report a density functional theory study of nitric oxide (NO) adsorption on close-packed transition metal (TM) Rh(111), Ir(111), Pd(111) and Pt(111) surfaces in terms of adsorption sites, binding mechanism and charge transfer at a coverage of Theta(NO) = 0.25, 0.50, 0.75 monolayer (ML). Based on our study, an unified picture for the interaction between NO and TM(111) and site preference is established, and valuable insights are obtained. At low coverage (0.25 ML), we find that the interaction of NO/TM(111) is determined by an electron donation and back-donation process via the interplay between NO 5 sigma/2 pi* and TM d-bands. The extent of the donation and back-donation depends critically on the coordination number (adsorption sites) and TM d-band filling, and plays an essential role for NO adsorption on TM surfaces. DFT calculations shows that for TMs with high d-band filling such as Pd and Pt, hollow-site NO is energetically the most favorable, and top-site NO prefers to tilt away from the normal direction. While for TMs with low d-band filling (Rh and Ir), top-site NO perpendicular to the surfaces is energetically most favorable. Electronic structure analysis show that irrespective of the TM and adsorption site, there is a net charge transfer from the substrate to the adsorbate due to overwhelming back-donation from the TM substrate to the adsorbed NO molecules. The adsorption-induced change of the work function with respect to bare surfaces and dipole moment is however site dependent, and the work function increases for hollow-site NO, but decreases for top-site NO, because of differences in the charge redistribution. The interplay between the energetics, lateral interaction and charge transfer, which is element dependent, rationalizes the structural evolution of NO adsorption on TM(111) surfaces in the submonolayer regime.
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We present parameter-free calculations of electronic properties of InGaN, InAlN, and AlGaN alloys. The calculations are based on a generalized quasichemical approach, to account for disorder and composition effects, and first-principles calculations within the density functional theory with the LDA-1/2 approach, to accurately determine the band gaps. We provide precise results for AlGaN, InGaN, and AlInN band gaps for the entire range of compositions, and their respective bowing parameters. (C) 2011 American Institute of Physics. [doi:10.1063/1.3576570]
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This paper discusses the integrated design of parallel manipulators, which exhibit varying dynamics. This characteristic affects the machine stability and performance. The design methodology consists of four main steps: (i) the system modeling using flexible multibody technique, (ii) the synthesis of reduced-order models suitable for control design, (iii) the systematic flexible model-based input signal design, and (iv) the evaluation of some possible machine designs. The novelty in this methodology is to take structural flexibilities into consideration during the input signal design; therefore, enhancing the standard design process which mainly considers rigid bodies dynamics. The potential of the proposed strategy is exploited for the design evaluation of a two degree-of-freedom high-speed parallel manipulator. The results are experimentally validated. (C) 2010 Elsevier Ltd. All rights reserved.
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In this paper, nonlinear dynamic equations of a wheeled mobile robot are described in the state-space form where the parameters are part of the state (angular velocities of the wheels). This representation, known as quasi-linear parameter varying, is useful for control designs based on nonlinear H(infinity) approaches. Two nonlinear H(infinity) controllers that guarantee induced L(2)-norm, between input (disturbances) and output signals, bounded by an attenuation level gamma, are used to control a wheeled mobile robot. These controllers are solved via linear matrix inequalities and algebraic Riccati equation. Experimental results are presented, with a comparative study among these robust control strategies and the standard computed torque, plus proportional-derivative, controller.
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The aim of this article is to present the main contributions of human resource management to develop sustainable organizations. The relationship between human resources and organizational sustainability, which is based on economical, social and environmental performance, involves some important aspects concerning management such as innovation, cultural diversity and the environment. The integration of items from the triple bottom line approach leads to developing a model based on a strategic and central posture of human resource management. Based on this model, propositions and recommendations for future research on this theme are presented.
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The aim of this article is to analyze the theoretical model proposed by [Jabbour CJC, Santos FCA. Relationships between human resource dimensions and environmental management in companies: proposal of a model. Journal of Cleaner Production 2008;16(1):5 1-8.] based on the data collected in four Brazilian companies. This model investigates how the phases of the environmental management system can be linked to human resource practices in order to attain continuous improvement of a company`s environmental performance. Our aim is to contribute to a field, which has little empirical evidence. Although the interaction between the phases of the environmental management system and human resource practices is recommended by the specialized literature [Daily BE Huang S. Achieving sustainability through attention to human resource factors in environmental management. International Journal of Operations and Production Management 2001:21(12):1539-52.], the results indicate that most of the theoretical assumptions could not be confirmed in these Brazilian companies. (C) 2008 Elsevier Ltd. All rights reserved.