842 resultados para Quality Model
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Enterprise Applications are complex software systems that manipulate much persistent data and interact with the user through a vast and complex user interface. In particular applications written for the Java 2 Platform, Enterprise Edition (J2EE) are composed using various technologies such as Enterprise Java Beans (EJB) or Java Server Pages (JSP) that in turn rely on languages other than Java, such as XML or SQL. In this heterogeneous context applying existing reverse engineering and quality assurance techniques developed for object-oriented systems is not enough. Because those techniques have been created to measure quality or provide information about one aspect of J2EE applications, they cannot properly measure the quality of the entire system. We intend to devise techniques and metrics to measure quality in J2EE applications considering all their aspects and to aid their evolution. Using software visualization we also intend to inspect to structure of J2EE applications and all other aspects that can be investigate through this technique. In order to do that we also need to create a unified meta-model including all elements composing a J2EE application.
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The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by process-based modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under http://www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws. We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10 m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25 m resolution.
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A common form of social regulation of an individual’s health behavior is social control. The contextual model of social control assumes that higher relationship quality goes along with more beneficial effects of social control on health behavior. This study examined potential differential moderating effects of different dimensions of relationship quality on the associations between positive and negative social control and smoking behavior and hiding smoking. The sample consisted of 144 smokers (n = 72 women; mean age = 31.78, SD = 10.04) with a nonsmoking partner. Positive and negative social control, dimensions of relationship quality consensus, cohesion and satisfaction, numbers of cigarettes smoked (NCS), hiding smoking (HS), and control variables were assessed at baseline. Four weeks later NCS and HS were assessed again. Only for smokers with high consensus, but not cohesion and satisfaction, a negative association between positive control and NCS emerged. Moreover, smokers with high consensus tended to report more HS when being positively and negatively socially controlled. This also emerged for cohesion and positive control. Satisfaction with the relationship did not display any interaction effects. This study’s results emphasize the importance of differentiating not only between positive and negative social control but also between different dimensions of relationship quality in order to gain a comprehensive understanding of the dynamics in romantic dyads with regard to social regulation of behavioral change.
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High self-esteem often predicts job-related outcomes, such as high job satisfaction or high status. Theoretically, high quality jobs (HQJs) should be important for self-esteem, as they enable people to use a variety of skills and attribute accomplishments to themselves, but research findings are mixed. We expected reciprocal relationships between self-esteem and HQJ. However, as work often is more important for the status of men, we expected HQJ to have a stronger influence on self-esteem for men as compared to women. Conversely, task-related achievements violate gender stereotypes for women, who may need high self-esteem to obtain HQJs. In a 4-year cross-lagged panel analysis with 325 young workers, self-esteem predicted HQJ; the lagged effect from HQJ on self-esteem was marginally significant. In line with the hypotheses, the multigroup model showed a significant path only from self-esteem to HQJ for women, and from HQJ to self-esteem for men. The reverse effect was not found for women, and only marginally significant for men. Overall, although there were some indications for reciprocal effects, our findings suggest that women need high self-esteem to obtain HQJs to a greater degree than men, and that men base their self-esteem on HQJs to a greater extent than women.
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PURPOSE Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.
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Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.
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Health-related quality of life (HRQOL) is an important measure of the effects of chronic liver disease in affected patients that helps guide interventions to improve well-being. However, the relationship between HRQOL and survival in liver transplant candidates remains unclear. We examined whether the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores from the Short Form 36 (SF-36) Health Survey were associated with survival in liver transplant candidates. We administered the SF-36 questionnaire (version 2.0) to patients in the Pulmonary Vascular Complications of Liver Disease study, a multicenter prospective cohort of patients evaluated for liver transplantation in 7 academic centers in the United States between 2003 and 2006. Cox proportional hazards models were used with death as the primary outcome and adjustment for liver transplantation as a time-varying covariate. The mean age of the 252 participants was 54 +/- 10 years, 64% were male, and 94% were white. During the 422 person years of follow-up, 147 patients (58%) were listed, 75 patients (30%) underwent transplantation, 49 patients (19%) died, and 3 patients were lost to follow-up. Lower baseline PCS scores were associated with an increased mortality rate despite adjustments for age, gender, Model for End-Stage Liver Disease score, and liver transplantation (P for the trend = 0.0001). The MCS score was not associated with mortality (P for the trend = 0.53). In conclusion, PCS significantly predicts survival in liver transplant candidates, and interventions directed toward improving the physical status may be helpful in improving outcomes in liver transplant candidates.
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In accordance with Bengtson's model of intergenerational solidarity (e.g. Bengtson & Roberts, 1991), the interrelations between adult daughters' family values, their perception of the relationship quality with their parents, the support they reported to give to and to receive from their parents, and their perception of reciprocity in intergenerational support exchange were investigated for N = 265 middle-aged women in Germany. It was also asked whether the support given to parents and perceived reciprocity are related to daughters' felt burden as a result of their support. Cross-sectional, self-report data were examined with multiple and multinomial logistic regression analyses. The analyses revealed positive relations between family values, relationship quality, and support to parents. Perceived reciprocity was associated with the exchange of intergenerational support and imbalance in support had negative effects on the relationship quality. Felt burden was predicted by the extent of support and the perceived reciprocity. However, specific correlational patterns depending on the kind of support as well as differences in the importance of mother and father occurred. The findings are discussed against the background of the meaning of family obligations and reciprocity in a Western culture.
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Objective: Since the beginning of the integrated care model for severely ill patients with psychotic disorders ("Hamburg model") in 2007 different clinical parameters have been consecutively assessed within a naturalistic, observational, prospective study.Methods: Clinical outcome of the 2-year and 4-year follow-ups of n = 158 patients.Results: A significant and ongoing improvement of psychopathology, severity of illness, functional outcome, quality of life and satisfaction with care in this sample of severely ill and merely chronic patients with psychosis was shown. Moreover, medication adherence improved and quality and quantity of outpatient treatment increased.Conclusion: The ongoing psychosocial stabilisation of the patients most likely result from a combination of various factors: continuity of care, multimodal and individualized care, therapeutic specialisation and the multidisciplinary ACT team. Results provide clinical and scientific evidence for future implementations of the integrated care model "Hamburg Model" for the treatment of psychosis.
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A rain-on-snow flood occurred in the Bernese Alps, Switzerland, on 10 October 2011, and caused significant damage. As the flood peak was unpredicted by the flood forecast system, questions were raised concerning the causes and the predictability of the event. Here, we aimed to reconstruct the anatomy of this rain-on-snow flood in the Lötschen Valley (160 km2) by analyzing meteorological data from the synoptic to the local scale and by reproducing the flood peak with the hydrological model WaSiM-ETH (Water Flow and Balance Simulation Model). This in order to gain process understanding and to evaluate the predictability. The atmospheric drivers of this rain-on-snow flood were (i) sustained snowfall followed by (ii) the passage of an atmospheric river bringing warm and moist air towards the Alps. As a result, intensive rainfall (average of 100 mm day-1) was accompanied by a temperature increase that shifted the 0° line from 1500 to 3200 m a.s.l. (meters above sea level) in 24 h with a maximum increase of 9 K in 9 h. The south-facing slope of the valley received significantly more precipitation than the north-facing slope, leading to flooding only in tributaries along the south-facing slope. We hypothesized that the reason for this very local rainfall distribution was a cavity circulation combined with a seeder-feeder-cloud system enhancing local rainfall and snowmelt along the south-facing slope. By applying and considerably recalibrating the standard hydrological model setup, we proved that both latent and sensible heat fluxes were needed to reconstruct the snow cover dynamic, and that locally high-precipitation sums (160 mm in 12 h) were required to produce the estimated flood peak. However, to reproduce the rapid runoff responses during the event, we conceptually represent likely lateral flow dynamics within the snow cover causing the model to react "oversensitively" to meltwater. Driving the optimized model with COSMO (Consortium for Small-scale Modeling)-2 forecast data, we still failed to simulate the flood because COSMO-2 forecast data underestimated both the local precipitation peak and the temperature increase. Thus we conclude that this rain-on-snow flood was, in general, predictable, but requires a special hydrological model setup and extensive and locally precise meteorological input data. Although, this data quality may not be achieved with forecast data, an additional model with a specific rain-on-snow configuration can provide useful information when rain-on-snow events are likely to occur.
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OBJECTIVES Accurate trial reporting facilitates evaluation and better use of study results. The objective of this article is to investigate the quality of reporting of randomized controlled trials (RCTs) in leading orthodontic journals, and to explore potential predictors of improved reporting. METHODS The 50 most recent issues of 4 leading orthodontic journals until November 2013 were electronically searched. Reporting quality assessment was conducted using the modified CONSORT statement checklist. The relationship between potential predictors and the modified CONSORT score was assessed using linear regression modeling. RESULTS 128 RCTs were identified with a mean modified CONSORT score of 68.97% (SD = 11.09). The Journal of Orthodontics (JO) ranked first in terms of completeness of reporting (modified CONSORT score 76.21%, SD = 10.1), followed by American Journal of Orthodontics and Dentofacial Orthopedics (AJODO) (73.05%, SD = 10.1). Journal of publication (AJODO: β = 10.08, 95% CI: 5.78, 14.38; JO: β = 16.82, 95% CI: 11.70, 21.94; EJO: β = 7.21, 95% CI: 2.69, 11.72 compared to Angle), year of publication (β = 0.98, 95% CI: 0.28, 1.67 for each additional year), region of authorship (Europe: β = 5.19, 95% CI: 1.30, 9.09 compared to Asia/other), statistical significance (significant: β = 3.10, 95% CI: 0.11, 6.10 compared to non-significant) and methodologist involvement (involvement: β = 5.60, 95% CI: 1.66, 9.54 compared to non-involvement) were all significant predictors of improved modified CONSORT scores in the multivariable model. Additionally, median overall Jadad score was 2 (IQR = 2) across journals, with JO (median = 3, IQR = 1) and AJODO (median = 3, IQR = 2) presenting the highest score values. CONCLUSION The reporting quality of RCTs published in leading orthodontic journals is considered suboptimal in various CONSORT areas. This may have a bearing in trial result interpretation and use in clinical decision making and evidence- based orthodontic treatment interventions.
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Demographic composition and dynamics of animal and human populations are important determinants for the transmission dynamics of infectious disease and for the effect of infectious disease or environmental disasters on productivity. In many circumstances, demographic data are not available or of poor quality. Since 1999 Switzerland has been recording cattle movements, births, deaths and slaughter in an animal movement database (AMD). The data present in the AMD offers the opportunity for analysing and understanding the dynamic of the Swiss cattle population. A dynamic population model can serve as a building block for future disease transmission models and help policy makers in developing strategies regarding animal health, animal welfare, livestock management and productivity. The Swiss cattle population was therefore modelled using a system of ordinary differential equations. The model was stratified by production type (dairy or beef), age and gender (male and female calves: 0-1 year, heifers and young bulls: 1-2 years, cows and bulls: older than 2 years). The simulation of the Swiss cattle population reflects the observed pattern accurately. Parameters were optimized on the basis of the goodness-of-fit (using the Powell algorithm). The fitted rates were compared with calculated rates from the AMD and differed only marginally. This gives confidence in the fitted rates of parameters that are not directly deductible from the AMD (e.g. the proportion of calves that are moved from the dairy system to fattening plants).
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Good work quality is crucial for employee well-being and health. Indicators of work quality are, among others, aspects of one’s work organization and learning opportunities. Based on the Job-Demands Control model we investigate if a) young employees are confronted with different combinations of job characteristics, b) cluster membership is predicted through socio-demographic and educational factors as well as positive self-evaluations and health, and c) cluster membership leads to different associations with job-related and general well-being. Based on TREE (Transition from Education to Employment) data we found three clusters of job characteristics, i.e. high resources – low demands, medium resources – medium demands, and low resources – high demands. Likelihood to be in a more favourable group was higher for females and young employees who reported more positive self-evaluations and higher learning efforts after compulsory school. Young employees in more favourable groups also reported higher levels of job-related and general well-being.
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Cramér Rao Lower Bounds (CRLB) have become the standard for expression of uncertainties in quantitative MR spectroscopy. If properly interpreted as a lower threshold of the error associated with model fitting, and if the limits of its estimation are respected, CRLB are certainly a very valuable tool to give an idea of minimal uncertainties in magnetic resonance spectroscopy (MRS), although other sources of error may be larger. Unfortunately, it has also become standard practice to use relative CRLB expressed as a percentage of the presently estimated area or concentration value as unsupervised exclusion criterion for bad quality spectra. It is shown that such quality filtering with widely used threshold levels of 20% to 50% CRLB readily causes bias in the estimated mean concentrations of cohort data, leading to wrong or missed statistical findings-and if applied rigorously-to the failure of using MRS as a clinical instrument to diagnose disease characterized by low levels of metabolites. Instead, absolute CRLB in comparison to those of the normal group or CRLB in relation to normal metabolite levels may be more useful as quality criteria. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.
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Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.