952 resultados para evaluation algorithm
Resumo:
The aim of this study was to explore the feasibility of an exercise scientist (ES) working in general practice to promote physical activity (PA) to 55 to 70 year old adults. Participants were randomised into one of three groups: either brief verbal and written advice from a general practitioner (GP) (G1, N=9); or individualised counselling and follow-up telephone calls from an ES, either with (G3, N=8) or without a pedometer (G2, N=11). PA levels were assessed at week 1, after the 12-wk intervention and again at 24 weeks. After the 12-wk intervention, the average increase in PA was 116 (SD=237) min/wk; N=28, p < 0.001. Although there were no statistically significant between-group differences, the average increases in PA among G2 and G3 participants were 195 (SD=207) and 138 (SD=315) min/wk respectively, compared with no change (0.36, SD=157) in G1. After 24 weeks, average PA levels remained 56 (SD=129) min/wk higher than in week 1. The small numbers of participants in this feasibility study limit the power to detect significant differences between groups, but it would appear that individualised counselling and follow-up contact from an ES, with or without a pedometer, can result in substantial changes in PA levels. A larger study is now planned to confirm these findings.
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The global demand for food, feed, energy and water poses extraordinary challenges for future generations. It is evident that robust platforms for the exploration of renewable resources are necessary to overcome these challenges. Within the multinational framework MultiBioPro we are developing biorefinery pipelines to maximize the use of plant biomass. More specifically, we use poplar and tobacco tree (Nicotiana glauca) as target crop species for improving saccharification, isoprenoid, long chain hydrocarbon contents, fiber quality, and suberin and lignin contents. The methods used to obtain these outputs include GC-MS, LC-MS and RNA sequencing platforms. The metabolite pipelines are well established tools to generate these types of data, but also have the limitations in that only well characterized metabolites can be used. The deep sequencing will allow us to include all transcripts present during the developmental stages of the tobacco tree leaf, but has to be mapped back to the sequence of Nicotiana tabacum. With these set-ups, we aim at a basic understanding for underlying processes and at establishing an industrial framework to exploit the outcomes. In a more long term perspective, we believe that data generated here will provide means for a sustainable biorefinery process using poplar and tobacco tree as raw material. To date the basal level of metabolites in the samples have been analyzed and the protocols utilized are provided in this article.
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Background The purposes of this study were 1) to establish accelerometer count cutoffs to categorize activity intensity of 3 to 5-y old-children and 2) to evaluate the accelerometer as a measure of children’s physical activity in preschool settings. Methods While wearing an ActiGraph accelerometer, 16 preschool children performed five, 3-min structured activities. Receiver Operating Characteristic (ROC) curve analyses identified count cutoffs for four physical activity intensities. In 9 preschools, 281 children wore an ActiGraph during observations performed by three trained observers (interobserver reli-ability = 0.91 to 0.98). Results Separate count cutoffs for 3, 4, and 5-y olds were established. Sensitivity and specificity for the count cutoffs ranged from 86.7% to 100.0% and 66.7% to 100.0%, respectively. ActiGraph counts/15 s were different among all activities (P < 0.05) except the two sitting activities. Correlations between observed and ActiGraph intensity categorizations at the preschools ranged from 0.46 to 0.70 (P < 0.001). Conclusions The ActiGraph count cutoffs established and validated in this study can be used to objectively categorize the time that preschool-age children spend in different physical activity intensity levels.
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Purpose To test the effects of a community-based physical activity intervention designed to increase physical activity and to conduct an extensive process evaluation of the intervention. Design Quasi-experimental. Setting Two rural communities in South Carolina. One community received the intervention, and the other served as the comparison. Subjects Public school students who were in fifth grade at the start of the study (558 at baseline) were eligible to participate. A total of 436 students participated over the course of the study. Intervention The intervention included after-school and summer physical activity programs and home, school, and community components designed to increase physical activity in youth. The intervention took place over an 18-month period. Measures. Students reported after-school physical activity at three data collection points (prior to, during, and following the intervention) using the Previous Day Physical Activity Recall (PDPAR). They also completed a questionnaire designed to measure hypothesized psychosocial and environmental determinants of physical activity behavior The process evaluation used meeting records, documentation of program activities, interviews, focus groups, and heart rate monitoring to evaluate the planning and implementation of the intervention. Results There were no significant differences in the physical activity variables and few significant differences in the psychosocial variables between the intervention and comparison groups. The process evaluation indicated that the after-school and summer physical activity component of the intervention was implemented as planned, but because of resource and time limitations, the home, school, and community components were not implemented as planned. Conclusions The intervention did not have a significant effect on physical activity in the target population of children in the intervention community. This outcome is similar to that reported in other studies of community-based physical activity intervention.
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Background Heatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under ‘normal’ conditions from the historical daily mortality records. The calculation of the excess mortality is a scientific challenge because of the stochastic temporal pattern of the daily mortality data which is characterised by (a) the long-term changing mean levels (i.e., non-stationarity); (b) the non-linear temperature-mortality association. The Hilbert-Huang Transform (HHT) algorithm is a novel method originally developed for analysing the non-linear and non-stationary time series data in the field of signal processing, however, it has not been applied in public health research. This paper aimed to demonstrate the applicability and strength of the HHT algorithm in analysing health data. Methods Special R functions were developed to implement the HHT algorithm to decompose the daily mortality time series into trend and non-trend components in terms of the underlying physical mechanism. The excess mortality is calculated directly from the resulting non-trend component series. Results The Brisbane (Queensland, Australia) and the Chicago (United States) daily mortality time series data were utilized for calculating the excess mortality associated with heatwaves. The HHT algorithm estimated 62 excess deaths related to the February 2004 Brisbane heatwave. To calculate the excess mortality associated with the July 1995 Chicago heatwave, the HHT algorithm needed to handle the mode mixing issue. The HHT algorithm estimated 510 excess deaths for the 1995 Chicago heatwave event. To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors. Conclusions The HHT algorithm is a novel and powerful analytical tool in time series data analysis. It has a real potential to have a wide range of applications in public health research because of its ability to decompose a nonlinear and non-stationary time series into trend and non-trend components consistently and efficiently.
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In this paper we propose a method that integrates the no- tion of understandability, as a factor of document relevance, into the evaluation of information retrieval systems for con- sumer health search. We consider the gain-discount evaluation framework (RBP, nDCG, ERR) and propose two understandability-based variants (uRBP) of rank biased precision, characterised by an estimation of understandability based on document readability and by different models of how readability influences user understanding of document content. The proposed uRBP measures are empirically contrasted to RBP by comparing system rankings obtained with each measure. The findings suggest that considering understandability along with topicality in the evaluation of in- formation retrieval systems lead to different claims about systems effectiveness than considering topicality alone.
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This research aimed to develop a framework for performance evaluation of public hospitals in Vietnam that is culturally, socially, and politically appropriate. The research included both qualitative and quantitative methods and identified and validated novel instruments to measure patient satisfaction and job satisfaction of hospital staff and to determine a set of hospital indicators that reflect the quality of hospital performance. New models for understanding the determinants of patient and staff satisfaction were developed along with a new performance indicator framework for hospital performance. These instruments will now be applied to the evaluation of hospital services in Khanh Hoa Province, permitting longer term evaluation of their effectiveness in changing system wide performance and satisfaction.
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This paper estimates the benefit of a plan for information providing system on road administration by WebGIS. The system will reduce travel costs of visitors from their business establishments to a road administration section of a city office. The authors had individual interviews with the visitors at the section of the Ichikawa City Office. Annual total sum of travel costs was estimated at 37 million yen at most. This paper also proposes formulas which expect the frequency of visits or the total sum of travel costs from the spatial distribution of the business establishments without questionnaires.
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Aggressive behavior at the steering wheel has been indicated as a contributing factor in a majority of crashes and anger has been compared to alcohol impairment in terms of probability to cause a crash. It has been shown that being in a state of anger or excitement while driving can decrease the drivers’ performances. . This paper reports the evaluation of 6 novel design alternatives of In-Vehicle Information Systems (IVIS) aimed at mitigating driver aggression. Each application presented was designed to tackle the following contributing factors to driver aggression: competitiveness, anonymity, territoriality, stress as well as social and emotional isolation. The 6 applications were simulated using computer vision algorithm to automatically overlay the real traffic conditions with ‘Head-Up Display’ visualizations. Two applications emerged over the others from participant’s evaluation: shared music combined the known calming effect of music with the sense of sympathy and intimacy caused by hearing other drivers’ music. The Shared Snapshot application provided an immediate gratification and was evaluated as a potential prevention of roadside quarrels. The paper presents Theoretical foundation, participant’s evaluations, implications and limitations of the study.
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This paper evaluates the performances of prediction intervals generated from alternative time series models, in the context of tourism forecasting. The forecasting methods considered include the autoregressive (AR) model, the AR model using the bias-corrected bootstrap, seasonal ARIMA models, innovations state space models for exponential smoothing, and Harvey’s structural time series models. We use thirteen monthly time series for the number of tourist arrivals to Hong Kong and Australia. The mean coverage rates and widths of the alternative prediction intervals are evaluated in an empirical setting. It is found that all models produce satisfactory prediction intervals, except for the autoregressive model. In particular, those based on the biascorrected bootstrap perform best in general, providing tight intervals with accurate coverage rates, especially when the forecast horizon is long.
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This paper evaluates and proposes various compensation methods for three-level Z-source inverters under semiconductor-failure conditions. Unlike the fault-tolerant techniques used in traditional three-level inverters, where either an extra phase-leg or collective switching states are used, the proposed methods for three-level Z-source inverters simply reconfigure their relevant gating signals so as to ride-through the failed semiconductor conditions smoothly without any significant decrease in their ac-output quality and amplitude. These features are partly attributed to the inherent boost characteristics of a Z-source inverter, in addition to its usual voltage-buck operation. By focusing on specific types of three-level Z-source inverters, it can also be shown that, for the dual Z-source inverters, a unique feature accompanying it is its extra ability to force common-mode voltage to zero even under semiconductor-failure conditions. For verifying these described performance features, PLECS simulation and experimental testing were performed with some results captured and shown in a later section for visual confirmation.
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For the renewable energy sources whose outputs vary continuously, a Z-source current-type inverter has been proposed as a possible buck-boost alternative for grid-interfacing. With a unique X-shaped LC network connected between its dc power source and inverter topology, Z-source current-type inverter is however expected to suffer from compounded resonant complications in addition to those associated with its second-order output filter. To improve its damping performance, this paper proposes the careful integration of Posicast or three-step compensators before the inverter pulse-width modulator for damping triggered resonant oscillations. In total, two compensators are needed for wave-shaping the inverter boost factor and modulation ratio, and they can conveniently be implemented using first-in first-out stacks and embedded timers of modern digital signal processors widely used in motion control applications. Both techniques are found to damp resonance of ac filter well, but for cases of transiting from current-buck to boost state, three-step technique is less effective due to the sudden intermediate discharging interval introduced by its non-monotonic stepping (unlike the monotonic stepping of Posicast damping). These findings have been confirmed both in simulations and experiments using an implemented laboratory prototype.