914 resultados para Random regression


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Perceived depth was measured for three-types of stereograms with the colour/texture of half-occluded (monocular) regions either similar to or dissimilar to that of binocular regions or background. In a two-panel random dot stereogram the monocular region was filled with texture either similar or different to the far panel or left blank. In unpaired background stereograms the monocular region either matched the background or was different in colour or texture and in phantom stereograms the monocular region matched the partially occluded object or was a different colour or texture. In all three cases depth was considerably impaired when the monocular texture did not match either the background or the more distant surface. The content and context of monocular regions as well as their position are important in determining their role as occlusion cues and thus in three-dimensional layout. We compare coincidence and accidental view accounts of these effects. (C) 2002 Elsevier Science Ltd. All rights reserved.

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This paper is part of a large study to assess the adequacy of the use of multivariate statistical techniques in theses and dissertations of some higher education institutions in the area of marketing with theme of consumer behavior from 1997 to 2006. The regression and conjoint analysis are focused on in this paper, two techniques with great potential of use in marketing studies. The objective of this study was to analyze whether the employement of these techniques suits the needs of the research problem presented in as well as to evaluate the level of success in meeting their premisses. Overall, the results suggest the need for more involvement of researchers in the verification of all the theoretical precepts of application of the techniques classified in the category of investigation of dependence among variables.

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A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development.

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The present study was carried out to evaluate the effectiveness of a specific program regarding the occurrence of vocal attrition symptoms in telemarketers. A total of 71 subjects participated in this study: 28 completed the Vocal Symptoms questionnaire to test its reliability, and 43 were randomly assigned to two groups: an 8-week vocal training group (n = 14) and a no-training control group (n = 29), to evaluate the effectiveness of the training program with this tool. The voice training group also filled in the posttraining questionnaire `Benefits Obtained with Voice Training` (BVT). The vocal training program was not considered effective with regard to the occurrence of vocal symptoms. However, due to a probable increase in symptoms in untrained telemarketers, it can work as a protective factor. According to BVT answers, the vocal training contributed to an improvement in vocal use as a communication tool for telemarketers. Copyright (C) 2009 S. Karger AG, Basel

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Degenerative aortic valve disease (DAVD), a common finding in the elderly, is associated with an increased risk of death due to cardiovascular causes. Taking advantage of its longitudinal design, this study evaluates the prevalence of DAVD and its temporal associations with long-term exposure to cardiovascular risk factors in the general population. We studied 953 subjects (aged 25-74 years) from a random sample of German residents. Risk factors had been determined at a baseline investigation in 1994/95. At a follow-up investigation, 10 years later, standardized echocardiography determined aortic valve morphology and aortic valve area (AVA) as well as left ventricular geometry and function. At the follow-up study, the overall prevalence of DAVD was 28%. In logistic regression models adjusting for traditional cardiovascular risk factors at baseline age (OR 2.0 [1.7-2.3] per 10 years, P < 0.001), active smoking (OR 1.7 [1.1-2.4], P = 0.009) and elevated total cholesterol levels (OR 1.2 [1.1-1.3] per increase of 20 mg/dL, P < 0.001) were significantly related to DAVD at follow-up. Furthermore, age, baseline status of smoking, and total cholesterol level were significant predictors of a smaller AVA at follow-up study. In contrast, hypertension and obesity had no detectable relationship with long-term changes of aortic valve structure. In the general population we observed a high prevalence of DAVD that is associated with long-term exposure to elevated cholesterol levels and active smoking. These findings strengthen the notion that smoking cessation and cholesterol lowering are promising treatment targets for prevention of DAVD.

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Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

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Many features of chronic kidney disease may be reversed, but it is unclear whether advanced lesions, such as adhesions of sclerotic glomerular tufts to Bowman`s capsule (synechiae), can resolve during treatment. We previously showed, using a renal ablation model, that the renoprotective effect of the AT-1 receptor blocker, losartan, is dose-dependent. Here we determined if moderate and advanced glomerular lesions, associated with streptozotocin-induced diabetes, regress with conventional or high-dose losartan treatment. Using daily insulin injection for 10 months, we maintained diabetic adult male Munich-Wistar rats in a state of moderate hyperglycemia. Following this period, some rats continued to receive insulin with or without conventional or high-dose losartan for an additional 2 months. Diabetic rats pretreated with insulin for 10 months and age-matched non-diabetic rats served as controls. Mesangial expansion was found in the control diabetic rats and was exacerbated in those rats maintained on only insulin for an additional 2 months. Conventional and high-dose losartan treatments reduced this mesangial expansion and the severity of synechiae lesions below that found prior to treatment; however, the frequency of the latter was unchanged. There was no dose-response effect of losartan. Our results show that regression of mesangial expansion and contraction of sclerotic lesions is feasible in the treatment of diabetes, but complete resolution of advanced glomerulosclerosis may be hard to achieve.

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Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

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There is evidence that fibroblast growth factors (FGFs) are involved in the regulation of growth and regression of the corpus luteum (CL). However, the expression pattern of most FGF receptors (FGFRs) during CL lifespan is still unknown. The objective of the present study was to determine the pattern of expression of `B` and `C` splice variants of FGFRs in the bovine CL. Bovine CL were collected from an abattoir and classed as corpora hemorrhagica (Stage I), developing (Stage II), developed (Stage III) or regressed (Stage IV) CL. Expression of FGFR mRNA was measured by semiquantitative reverse transcription-polymerase chain reaction and FGFR protein was localised by immunohistochemistry. Expression of mRNA encoding the `B` and `C` spliced forms of FGFR1 and FGFR2 was readily detectable in the bovine CL and was accompanied by protein localisation. FGFR1C and FGFR2C mRNA expression did not vary throughout CL lifespan, whereas FGFR1B was upregulated in the developed (Stage III) CL. FGFR3B, FGFR3C and FGFR4 expression was inconsistent in the bovine CL. The present data indicate that FGFR1 and FGFR2 splice variants are the main receptors for FGF action in the bovine CL.

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Kenyan women have more children, especially in rural areas, than in most developing nations. This is widely believed to be an impediment to Kenya’s economic development. Thus, factors influencing family size in the Kenyan context are important for its future. A brief review of economic theories of fertility leads to the conclusion that both economics and social/cultural factors must be considered simultaneously when examining factors that determine the number of children in a family. The need to do this is borne out in Kenya’s situation by utilising responses from a random sample of rural households in the Nyeri district of Kenya. Economic and social/cultural factors intertwine to influence family sizes in this district. After providing a summary of the main statistical results from the survey, we use multiple regression analysis to explore the influences of a woman’s age, level of education, whether she has outside employment, whether the family keeps livestock, whether she expresses a preference for more boys than girls, whether the family uses only family labour (including child labour) and the size of the farm, which is used as a proxy for family income. It was found that preference for male children has an important positive influence on family size in this district. Women were found to have greater preference for male children than their male counterparts possibly because of their fear of being disinherited if they do not produce an heir for their husbands. Preference for sons was also found in allocation of human capital resources at the household level in that the female respondents were found to have lower levels of education than their male counterparts. Various long-term policies are outlined that may help to reduce the number of offspring of women in Kenya.

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Background. Dental erosion is a multifactorial disease and is associated with dietary habits in infancy and adolescence. Aim. To investigate possible associations among dental erosion and diet, medical history and lifestyle habits in Brazilian schoolchildren. Design. The sample consisted of a random single centre cluster of 414 adolescents (12- and 16-years old) of both genders from private and public schools in Bauru (Brazil). The O`Brien [Children`s Dental Health in the United Kingdom, 1993 (1994) HMSO, London] index was used for dental erosion assessment. Data on medical history, rate and frequency of food and drinks consumption, and lifestyle habits were collected by a self-reported questionnaire. Odds ratios with 95% confidence intervals were used to assess the univariate relationships between variables. Analysis of questionnaire items was performed by multiple logistic regression analysis. The statistical significance level was set at 5%. Results. The erosion present group comprised 83 subjects and the erosion absent group 331. There were no statistically significant correlations among dental erosion and the consumption of food and drinks, medical history, or lifestyle habits. Conclusion. The results indicate that there was no correlation between dental erosion and the risk factors analysed among adolescents in Bauru/Brazil and further investigations are necessary to clarify the multifactorial etiology of this condition.

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Most cellular solids are random materials, while practically all theoretical structure-property results are for periodic models. To be able to generate theoretical results for random models, the finite element method (FEM) was used to study the elastic properties of solids with a closed-cell cellular structure. We have computed the density (rho) and microstructure dependence of the Young's modulus (E) and Poisson's ratio (PR) for several different isotropic random models based on Voronoi tessellations and level-cut Gaussian random fields. The effect of partially open cells is also considered. The results, which are best described by a power law E infinity rho (n) (1<n<2), show the influence of randomness and isotropy on the properties of closed-cell cellular materials, and are found to be in good agreement with experimental data. (C) 2001 Acta Materialia Inc. Published by Elsevier Science Ltd. All rights reserved.