934 resultados para Objective measures


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Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

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Salinity, water temperature, and chlorophyll a (chl-a) biomass were used as performance measures in the period 1999–2001 to evaluate the effect of a hydrological rehabilitation project in the Ciénaga Grande de Santa Marta (CGSM)–Pajarales lagoon complex, Colombia where freshwater diversions were initiated in 1995 and completed in 1998. The objective of this study was to evaluate how diversions of freshwater into previously hypersaline (>80) environments changed the spatial and temporal distribution of environmental characteristics. Following the diversion, 19 surveys and transects using a flow-through system were surveyed in the CGSM–Pajarales complex to continuously measure selected water quality parameters. Geostatistical analysis indicates that hydrology and salinity regimes and water circulation patterns in the CGSM lagoon are largely controlled by freshwater discharge from the Fundacion, Aracataca, and Sevilla Rivers. Residence times in the CGSM lagoon were similar before (15.5 ± 3.8 days) and after (14.2 ± 2.0 days) the rehabilitation project and indicated that the system is flushed regularly. In contrast, chl-a biomass was highly variable in the CGSM–Pajarales lagoon complex and not related to discharge patterns. Mean annual chl-a biomass (44–250 μg L−1) following the diversion project was similar to values recorded since the 1980s and still remains among the highest reported in coastal systems around the world owing to its unique hydrology regulated by the Magdalena River and Sierra Nevada de Santa Marta watersheds and the high teleconnection to the El Niño Southern Oscillation (ENSO). Our results confirm that the reduction in salinity in the CGSM lagoon and Pajarales complex during 1999–2000 was largely driven by high precipitation (2500 mm) induced by the ENSO–La Niña rather than by the freshwater diversions.

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Context: Accurately determining hydration status is a preventative measure for exertional heat illnesses (EHI). Objective: To determine the validity of various field measures of urine specific gravity (Usg) compared to laboratory instruments. Design: Observational research design to compare measures of hydration status: urine reagent strips (URS) and a urine color (Ucol) chart to a refractometer. Setting: We utilized the athletic training room of a Division I-A collegiate American football team. Participants: Trial 1 involved urine samples of 69 veteran football players (age=20.1+1.2yr; body mass=229.7+44.4lb; height=72.2+2.1in). Trial 2 involved samples from 5 football players (age=20.4+0.5yr; body mass=261.4+39.2lb; height=72.3+2.3in). Interventions: We administered the Heat Illness Index Score (HIIS) Risk Assessment, to identify athletes at-risk for EHI (Trial 1). For individuals “at-risk” (Trial 2), we collected urine samples before and after 15 days of pre-season “two-a-day” practices in a hot, humid environment(mean on-field WBGT=28.84+2.36oC). Main Outcome Measures: Urine samples were immediately analyzed for Usg using a refractometer, Diascreen 7® (URS1), Multistix® (URS2), and Chemstrip10® (URS3). Ucol was measured using Ucol chart. We calculated descriptive statistics for all main measures; Pearson correlations to assess relationships between the refractometer, each URS, and Ucol, and transformed Ucol data to Z-scores for comparison to the refractometer. Results: In Trial 1, we found a moderate relationship (r=0.491, p<.01) between URS1 (1.020+0.006μg) and the refractometer (1.026+0.010μg). In Trial 2, we found marked relationships for Ucol (5.6+1.6shades, r=0.619, p<0.01), URS2 (1.019+0.008μg, r=0.712, p<0.01), and URS3 (1.022+0.007μg, r=0.689, p<0.01) compared to the refractometer (1.028+0.008μg). Conclusions: Our findings suggest that URS were inconsistent between manufacturers, suggesting practitioners use the clinical refractometer to accurately determine Usg and monitor hydration status.

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Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.

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Purpose: To determine whether the ‘through-focus’ aberrations of a multifocal and accommodative intraocular lens (IOL) implanted patient can be used to provide rapid and reliable measures of their subjective range of clear vision. Methods: Eyes that had been implanted with a concentric (n = 8), segmented (n = 10) or accommodating (n = 6) intraocular lenses (mean age 62.9 ± 8.9 years; range 46-79 years) for over a year underwent simultaneous monocular subjective (electronic logMAR test chart at 4m with letters randomised between presentations) and objective (Aston open-field aberrometer) defocus curve testing for levels of defocus between +1.50 to -5.00DS in -0.50DS steps, in a randomised order. Pupil size and ocular aberration (a combination of the patient’s and the defocus inducing lens aberrations) at each level of blur was measured by the aberrometer. Visual acuity was measured subjectively at each level of defocus to determine the traditional defocus curve. Objective acuity was predicted using image quality metrics. Results: The range of clear focus differed between the three IOL types (F=15.506, P=0.001) as well as between subjective and objective defocus curves (F=6.685, p=0.049). There was no statistically significant difference between subjective and objective defocus curves in the segmented or concentric ring MIOL group (P>0.05). However a difference was found between the two measures and the accommodating IOL group (P<0.001). Mean Delta logMAR (predicted minus measured logMAR) across all target vergences was -0.06 ± 0.19 logMAR. Predicted logMAR defocus curves for the multifocal IOLs did not show a near vision addition peak, unlike the subjective measurement of visual acuity. However, there was a strong positive correlation between measured and predicted logMAR for all three IOLs (Pearson’s correlation: P<0.001). Conclusions: Current subjective procedures are lengthy and do not enable important additional measures such as defocus curves under differently luminance or contrast levels to be assessed, which may limit our understanding of MIOL performance in real-world conditions. In general objective aberrometry measures correlated well with the subjective assessment indicating the relative robustness of this technique in evaluating post-operative success with segmented and concentric ring MIOL.

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There has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and time complexity). Once one has developed an approach to a problem of interest, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Standard tests used for this purpose are able to consider jointly neither performance measures nor multiple competitors at once. The aim of this paper is to resolve these issues by developing statistical procedures that are able to account for multiple competing measures at the same time and to compare multiple algorithms altogether. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameters of such models, as usually the number of studied cases is very reduced in such comparisons. Data from a comparison among general purpose classifiers is used to show a practical application of our tests.

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OBJECTIVE: To identify the instruments used to assess polymyalgia rheumatica (PMR) in published studies. METHODS: A systematic literature review of clinical trials and longitudinal observational studies related to PMR, published from 1970 to 2014, was carried out. All outcome and assessment instruments were extracted and categorized according to core areas and domains, as defined by the OMERACT (Outcome Measures in Rheumatology) Filter 2.0. RESULTS: Thirty-five articles (3221 patients) were included: 12 randomized controlled trials (RCT); 3 nonrandomized trials; and 20 observational studies. More than 20 domains were identified, measured by 29 different instruments. The most frequently used measures were pain, morning stiffness, patient global assessment and physician global assessment, erythrocyte sedimentation rate, and C-reactive protein. The definition of outcomes varied considerably between studies. CONCLUSION: The outcome measures and instruments used in PMR are numerous and diversely defined. The establishment of a core set of validated and standardized outcome measurements is needed.

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BACKGROUND: Even though physician rating websites (PRWs) have been gaining in importance in both practice and research, little evidence is available on the association of patients' online ratings with the quality of care of physicians. It thus remains unclear whether patients should rely on these ratings when selecting a physician. The objective of this study was to measure the association between online ratings and structural and quality of care measures for 65 physician practices from the German Integrated Health Care Network "Quality and Efficiency" (QuE). METHODS: Online reviews from two German PRWs were included which covered a three-year period (2011 to 2013) and included 1179 and 991 ratings, respectively. Information for 65 QuE practices was obtained for the year 2012 and included 21 measures related to structural information (N = 6), process quality (N = 10), intermediate outcomes (N = 2), patient satisfaction (N = 1), and costs (N = 2). The Spearman rank coefficient of correlation was applied to measure the association between ratings and practice-related information. RESULTS: Patient satisfaction results from offline surveys and the patients per doctor ratio in a practice were shown to be significantly associated with online ratings on both PRWs. For one PRW, additional significant associations could be shown between online ratings and cost-related measures for medication, preventative examinations, and one diabetes type 2-related intermediate outcome measure. There again, results from the second PRW showed significant associations with the age of the physicians and the number of patients per practice, four process-related quality measures for diabetes type 2 and asthma, and one cost-related measure for medication. CONCLUSIONS: Several significant associations were found which varied between the PRWs. Patients interested in the satisfaction of other patients with a physician might select a physician on the basis of online ratings. Even though our results indicate associations with some diabetes and asthma measures, but not with coronary heart disease measures, there is still insufficient evidence to draw strong conclusions. The limited number of practices in our study may have weakened our findings.

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Purpose: To evaluate if physical measures of noise predict image quality at high and low noise levels. Method: Twenty-four images were acquired on a DR system using a Pehamed DIGRAD phantom at three kVp settings (60, 70 and 81) across a range of mAs values. The image acquisition setup consisted of 14 cm of PMMA slabs with the phantom placed in the middle at 120 cm SID. Signal-to-noise ratio (SNR) and Contrast-tonoise ratio (CNR) were calculated for each of the images using ImageJ software and 14 observers performed image scoring. Images were scored according to the observer`s evaluation of objects visualized within the phantom. Results: The R2 values of the non-linear relationship between objective visibility score and CNR (60kVp R2 = 0.902; 70Kvp R2 = 0.913; 80kVp R2 = 0.757) demonstrate a better fit for all 3 kVp settings than the linear R2 values. As CNR increases for all kVp settings the Object Visibility also increases. The largest increase for SNR at low exposure values (up to 2 mGy) is observed at 60kVp, when compared with 70 or 81kVp.CNR response to exposure is similar. Pearson r was calculated to assess the correlation between Score, OV, SNR and CNR. None of the correlations reached a level of statistical significance (p>0.01). Conclusion: For object visibility and SNR, tube potential variations may play a role in object visibility. Higher energy X-ray beam settings give lower SNR but higher object visibility. Object visibility and CNR at all three tube potentials are similar, resulting in a strong positive relationship between CNR and object visibility score. At low doses the impact of radiographic noise does not have a strong influence on object visibility scores because in noisy images objects could still be identified.

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Background - For dose reduction actions, the principle of “image quality as good as possible” to “image quality as good as needed” requires to know whether the physical measures and visual image quality relate. Visual evaluation and objective physical measures of image quality can appear to be different. If there is no noticeable effect on the visual image quality with a low dose but there is a objective physical measure impact, then the overall dose may be reduced without compromising the diagnostic image quality. Low dose imaging can be used for certain types of observations, e.g. thoracic scoliosis, control after metal implantation for osteosynthesis, reviewing pneumonia and tuberculosis. Aim of the study - To determine whether physical measures of noise predict visual (clinical) image quality at low dose levels.

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OBJECTIVE: To identify the instruments used to assess polymyalgia rheumatica (PMR) in published studies. METHODS: A systematic literature review of clinical trials and longitudinal observational studies related to PMR, published from 1970 to 2014, was carried out. All outcome and assessment instruments were extracted and categorized according to core areas and domains, as defined by the OMERACT (Outcome Measures in Rheumatology) Filter 2.0. RESULTS: Thirty-five articles (3221 patients) were included: 12 randomized controlled trials (RCT); 3 nonrandomized trials; and 20 observational studies. More than 20 domains were identified, measured by 29 different instruments. The most frequently used measures were pain, morning stiffness, patient global assessment and physician global assessment, erythrocyte sedimentation rate, and C-reactive protein. The definition of outcomes varied considerably between studies. CONCLUSION: The outcome measures and instruments used in PMR are numerous and diversely defined. The establishment of a core set of validated and standardized outcome measurements is needed.

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Receiving personalised feedback on body mass index and other health risk indicators may prompt behaviour change. Few studies have investigated men’s reactions to receiving objective feedback on such measures and detailed information on physical activity and sedentary time. The aim of my research was to understand the meanings different forms of objective feedback have for overweight/obese men, and to explore whether these varied between groups. Participants took part in Football Fans in Training, a gender-sensitised, weight loss programme delivered via Scottish Professional Football Clubs. Semi-structured interviews were conducted with 28 men, purposively sampled from four clubs to investigate the experiences of men who achieved and did not achieve their 5% weight loss target. Data were analysed using the principles of thematic analysis and interpreted through Self-Determination Theory and sociological understandings of masculinity. Several factors were vital in supporting a ‘motivational climate’ in which men could feel ‘at ease’ and adopt self-regulation strategies: the ‘place’ was described as motivating, whereas the ‘people’ (other men ‘like them’; fieldwork staff; community coaches) provided supportive and facilitative roles. Men who achieved greater weight loss were more likely to describe being motivated as a consequence of receiving information on their objective health risk indicators. They continued using self-monitoring technologies after the programme as it was enjoyable; or they had redefined themselves by integrating new-found activities into their lives and no longer relied on external technologies/feedback. They were more likely to see post-programme feedback as confirmation of success, so long as they could fully interpret the information. Men who did not achieve their 5% weight loss reported no longer being motivated to continue their activity levels or self-monitor them with a pedometer. Social support within the programme appeared more important. These men were also less positive about objective post-programme feedback which confirmed their lack of success and had less utility as a motivational tool. Providing different forms of objective feedback to men within an environment that has intrinsic value (e.g. football club setting) and congruent with common cultural constructions of masculinity, appears more conducive to health behaviour change.

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Gait analysis allows to characterize motor function, highlighting deviations from normal motor behavior related to an underlying pathology. The widespread use of wearable inertial sensors has opened the way to the evaluation of ecological gait, and a variety of methodological approaches and algorithms have been proposed for the characterization of gait from inertial measures (e.g. for temporal parameters, motor stability and variability, specific pathological alterations). However, no comparative analysis of their performance (i.e. accuracy, repeatability) was available yet, in particular, analysing how this performance is affected by extrinsic (i.e. sensor location, computational approach, analysed variable, testing environmental constraints) and intrinsic (i.e. functional alterations resulting from pathology) factors. The aim of the present project was to comparatively analyze the influence of intrinsic and extrinsic factors on the performance of the numerous algorithms proposed in the literature for the quantification of specific characteristics (i.e. timing, variability/stability) and alterations (i.e. freezing) of gait. Considering extrinsic factors, the influence of sensor location, analyzed variable, and computational approach on the performance of a selection of gait segmentation algorithms from a literature review was analysed in different environmental conditions (e.g. solid ground, sand, in water). Moreover, the influence of altered environmental conditions (i.e. in water) was analyzed as referred to the minimum number of stride necessary to obtain reliable estimates of gait variability and stability metrics, integrating what already available in the literature for over ground gait in healthy subjects. Considering intrinsic factors, the influence of specific pathological conditions (i.e. Parkinson’s Disease) was analyzed as affecting the performance of segmentation algorithms, with and without freezing. Finally, the analysis of the performance of algorithms for the detection of gait freezing showed how results depend on the domain of implementation and IMU position.

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The Fourier transform-infrared (FT-IR) signature of dry samples of DNA and DNA-polypeptide complexes, as studied by IR microspectroscopy using a diamond attenuated total reflection (ATR) objective, has revealed important discriminatory characteristics relative to the PO2(-) vibrational stretchings. However, DNA IR marks that provide information on the sample's richness in hydrogen bonds have not been resolved in the spectral profiles obtained with this objective. Here we investigated the performance of an all reflecting objective (ARO) for analysis of the FT-IR signal of hydrogen bonds in DNA samples differing in base richness types (salmon testis vs calf thymus). The results obtained using the ARO indicate prominent band peaks at the spectral region representative of the vibration of nitrogenous base hydrogen bonds and of NH and NH2 groups. The band areas at this spectral region differ in agreement with the DNA base richness type when using the ARO. A peak assigned to adenine was more evident in the AT-rich salmon DNA using either the ARO or the ATR objective. It is concluded that, for the discrimination of DNA IR hydrogen bond vibrations associated with varying base type proportions, the use of an ARO is recommended.