991 resultados para Software defect prediction
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Although both inflammatory and atherosclerosis markers have been associated with coronary heart disease (CHD) risk, data directly comparing their predictive value are limited. The authors compared the value of 2 atherosclerosis markers (ankle-arm index (AAI) and aortic pulse wave velocity (aPWV)) and 3 inflammatory markers (C-reactive protein (CRP), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-alpha)) in predicting CHD events. Among 2,191 adults aged 70-79 years at baseline (1997-1998) from the Health, Aging, and Body Composition Study cohort, the authors examined adjudicated incident myocardial infarction or CHD death ("hard" events) and "hard" events plus hospitalization for angina or coronary revascularization (total CHD events). During 8 years of follow-up between 1997-1998 and June 2007, 351 participants developed total CHD events (197 "hard" events). IL-6 (highest quartile vs. lowest: hazard ratio = 1.82, 95% confidence interval: 1.33, 2.49; P-trend < 0.001) and AAI (AAI </= 0.9 vs. AAI 1.01-1.30: hazard ratio = 1.57, 95% confidence interval: 1.14, 2.18) predicted CHD events above traditional risk factors and modestly improved global measures of predictive accuracy. CRP, TNF-alpha, and aPWV had weaker associations. IL-6 and AAI accurately reclassified 6.6% and 3.3% of participants, respectively (P's </= 0.05). Results were similar for "hard" CHD, with higher reclassification rates for AAI. IL-6 and AAI are associated with future CHD events beyond traditional risk factors and modestly improve risk prediction in older adults.
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Drought limits plant growth and threatens crop productivity. A barley (Hordeum vulgare) ethylene imine-induced monogenic recessive mutant cer-zv, which is sensitive to drought, was characterized and genetically mapped in the present study. Detached leaves of cer-zv lost 34.2 % of their initial weight after 1 h of dehydration. The transpiration was much higher in cer-zv leaves than in wild-type leaves under both light and dark conditions. The stomata of cer-zv leaves functioned normally, but the cuticle of cer-zv leaves showed increased permeability to ethanol and toluidine blue dye. There was a 50-90 % reduction in four major cutin monomers, but no reduction in wax loads was found in the cer-zv mutant as compared with the wild type. Two F(2) mapping populations were established by the crosses of 23-19 × cer-zv and cer-zv × OUH602. More polymorphisms were found in EST sequences between cer-zv and OUH602 than between cer-zv and 23-19. cer-zv was located in a pericentromeric region on chromosome 4H in a 10.8 cM interval in the 23-19 × cer-zv map based on 186 gametes tested and a 1.7 cM interval in the cer-zv × OUH602 map based on 176 gametes tested. It co-segregated with EST marker AK251484 in both maps. The results indicated that the cer-zv mutant is defective in cutin, which might be responsible for the increased transpiration rate and drought sensitivity, and that the F(2) of cer-zv × OUH602 might better facilitate high resolution mapping of cer-zv.
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Nonlinear regression problems can often be reduced to linearity by transforming the response variable (e.g., using the Box-Cox family of transformations). The classic estimates of the parameter defining the transformation as well as of the regression coefficients are based on the maximum likelihood criterion, assuming homoscedastic normal errors for the transformed response. These estimates are nonrobust in the presence of outliers and can be inconsistent when the errors are nonnormal or heteroscedastic. This article proposes new robust estimates that are consistent and asymptotically normal for any unimodal and homoscedastic error distribution. For this purpose, a robust version of conditional expectation is introduced for which the prediction mean squared error is replaced with an M scale. This concept is then used to develop a nonparametric criterion to estimate the transformation parameter as well as the regression coefficients. A finite sample estimate of this criterion based on a robust version of smearing is also proposed. Monte Carlo experiments show that the new estimates compare favorably with respect to the available competitors.
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Until recently farm management made little use of accounting and agriculture has been largely excluded from the scope of accounting standards. This article examines the current use of accounting in agriculture and points theneed to establish accounting standards for agriculture. Empirical evidence shows that accounting can make a significant contribution to agricultural management and farm viability and could also be important for other agents involved in agricultural decision making. Existing literature on failureprediction models and farm viability prediction studies provide the starting point for our research, in which two dichotomous logit models were applied to subsamples of viable and unviable farms in Catalonia, Spain. The firstmodel considered only non-financial variables, while the other also considered financial ones. When accounting variables were added to the model, a significant reduction in deviance was observed.
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Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.
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Purpose: Pulmonary hypoplasia is a determinant parameter for extra-uterine life. In the last years, MRI appears as a complement to US in order to evaluate the degree of pulmonary hypoplasia in foetuses with congenital anomalies, by using different methods - fetal lung volumetry (FLV), lung-to-liver signal intensity ratio (LLSIR)-. But until now, information about the correlation between the MRI prediction and the real postnatal outcome is limited. Methods and materials: We retrospectively reviewed the fetal MRI performed at our Institution in the last 8 years and selected the cases with suspicion of fetal pulmonary hypoplasia (n = 30). The pulmonary volumetry data of these foetuses were collected and the lung-to-liver signal intensity ratio (LLSIR) measures performed. These data were compared with those obtained from a control group of 25 foetuses considered as normal at MRI. The data of the study group were also correlated with the autopsy records or the post-natal clinical information of the patients. Results: As expected, the control group showed higher FLV and LLSIR values than the problem group at all gestational ages. Higher values of FLV and LLSIR were associated with a better post-natal outcome. Sensitivity, specificity, positive and negative predictive values and accuracy for the relative LLSIR and the relative FLV showed no significant differences. Conclusion: Our data show that not only the FLV but also the relative LLSIR inform about the degree of fetal lung development. This information may help to predict the fetal outcome and to evaluate the need for neonatal intensive care.
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Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.
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We present a simple randomized procedure for the prediction of a binary sequence. The algorithm uses ideas from recent developments of the theory of the prediction of individual sequences. We show that if thesequence is a realization of a stationary and ergodic random process then the average number of mistakes converges, almost surely, to that of the optimum, given by the Bayes predictor.
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Propone una alternativa para el procesamiento de datos de ecointegración acústica cuando se pretende obtener la distribución y el nivel de biomasa de recursos marinos, mediante la aplicación de un software de interpolación de datos.
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We investigated the association of trabecular bone score (TBS) with microarchitecture and mechanical behavior of human lumbar vertebrae. We found that TBS reflects vertebral trabecular microarchitecture and is an independent predictor of vertebral mechanics. However, the addition of TBS to areal BMD (aBMD) did not significantly improve prediction of vertebral strength. INTRODUCTION: The trabecular bone score (TBS) is a gray-level measure of texture using a modified experimental variogram which can be extracted from dual-energy X-ray absorptiometry (DXA) images. The current study aimed to confirm whether TBS is associated with trabecular microarchitecture and mechanics of human lumbar vertebrae, and if its combination with BMD improves prediction of fracture risk. METHODS: Lumbar vertebrae (L3) were harvested fresh from 16 donors. The anteroposterior and lateral bone mineral content (BMC) and areal BMD (aBMD) of the vertebral body were measured using DXA; then, the TBS was extracted using TBS iNsight software (Medimaps SA, France). The trabecular bone volume (Tb.BV/tissue volume, TV), trabecular thickness (Tb.Th), degree of anisotropy, and structure model index (SMI) were measured using microcomputed tomography. Quasi-static uniaxial compressive testing was performed on L3 vertebral bodies to assess failure load and stiffness. RESULTS: The TBS was significantly correlated to Tb.BV/TV and SMI (râeuro0/00=âeuro0/000.58 and -0.62; pâeuro0/00=âeuro0/000.02, 0.01), but not related to BMC and BMD. TBS was significantly correlated with stiffness (râeuro0/00=âeuro0/000.64; pâeuro0/00=âeuro0/000.007), independently of bone mass. Using stepwise multiple regression models, we failed to demonstrate that the combination of BMD and TBS was better at explaining mechanical behavior than either variable alone. However, the combination TBS, Tb.Th, and BMC did perform better than each parameter alone, explaining 79Â % of the variability in stiffness. CONCLUSIONS: In our study, TBS was associated with microarchitecture parameters and with vertebral mechanical behavior, but TBS did not improve prediction of vertebral biomechanical properties in addition to aBMD.
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Este trabajo describe el proceso de creación de la herramienta de software KemapMobile para la plataforma Android. El artefacto es una adaptación del software de escritorio KeMap que se integra en la plataforma educativa VerilUOC y permite a los estudiantes conectarse a ella para descargar, en la aplicación, ejercicios con los que poner a prueba y afianzar sus conocimientos sobre la simplificación de funciones lógicas booleanas con mapas de Karnaugh y tablas de verdad. La arquitectura cliente-servidor de la aplicación permite a los estudiantes disponer de ejercicios personalizados y al profesorado obtener datos sobre el uso de la herramienta y sobre la progresión del alumnado.
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O presente trabalho demonstra a utilização da linguagem UML na modelação (também se aplica à projecção e desenvolvimento) de sistemas. Incorpora um estudo de caso que consiste na modelação (também, propostas de implementação, sobretudo ao nível do modelo de dados) de um subsistema que faz parte do Sistema de Gestão Académico (SIAC) na Universidade Jean Piaget de Cabo Verde (Unipiaget).O trabalho surge após a percepção das dificuldades em que os alunos e não só, se enfrentam para terem acessos aos dados académicos, principalmente nos períodos em que estes se encontram de férias, daí a necessidade de implementação da Universidade Digital. Assim, aproveitando as boas práticas do desenvolvimento de sistemas, iniciou-se o processo da subdivisão do problema maior (Universidade Digital) em subproblemas (vários subsistemas), cujo projecto se concentra na análise e modelação do subsistema de secretaria digital. A metodologia adoptada foi a do diálogo directo programado e não programado, aplicação de questionários e entrevistas, assim como a da proposta de melhorias.Sendo assim, o trabalho iniciou-se com o levantamento de requisitos e avaliado face ao comportamento de subsistema no seu modo presencial (estado actual). E, por fim foram efectuadas propostas de melhorias, as quais permitirão alcançar a satisfação dos potênciais actores (utilizador do sistema).
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Purposes of this Report: • Recommend the most logical and economical options to address state governmental space needs in the Polk County metropolitan area to the year 2010. • Include building size, location, phasing, financing, method of project delivery and estimated cost. • Develop a software tool to compare costs of leasing vs. ownership of space. Methodology: Identify: 1. Current amount and location of owned and leased space, by agency; 2. Types of space and whether best located on or off of the Capitol Complex; 3. Utilization of space, noting over-crowding and under-utilization; 4. Current number of workstations for full and part time employees, Personnel Employment Organization (PEO) workers, contractors, interns, etc.; and, 5. History of staff levels to assist in the prediction of staff growth. Scope: This report focuses on 10 state-owned buildings located on the Capitol Complex and 48 leased spaces in the Polk County metropolitan area. (See Figures 1 and 2.) • Due to a separate space study under way by the Legislature, implications of area and staff for the State Capitol building are included only for the Governor, Lieutenant Governor, Treasurer, Secretary of State, Auditor and the Department of Management. • Because it is largely a museum building that does not have office space available for other agencies, the area and staff of the Historical Building are not fully addressed. • Only the parking implications of the new Judicial Building are included in this study because the building space is under the jurisdiction of the Judicial Branch and not available for other agencies. Several state-owned buildings are not included in the scope of this report, generally because they have highly focused purposes, and their space is not available for assignment to other agencies. Several leased locations are not included for similar reasons, including leases that do not fall within the authority of the Department of General Services.
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Con este TFM se muestra un laboratorio virtual de química a través de diversos experimentos para la preparación de disoluciones en función de sus expresiones de concentración.