917 resultados para reliability test system
Resumo:
Background The wellness construct has application in a number of fields including education, healthcare and counseling, particularly with regard to female adolescents. The effective measurement of wellness in adolescents can assist researchers and practitioners in determining lifestyle behaviors in which they are lacking. Behavior change interventions can then be designed which directly aid in the promotion of these areas. Methods The 5-Factor Wellness Inventory (designed to measure the Indivisible Self model of wellness) is a popular instrument for measuring the broad aspects of wellness amongst adolescents. The instrument comprises 97 items contributing to 17 subscales, five dimension scores, four context scores, total wellness score, and a life satisfaction index. This investigation evaluated the test-retest (intra-rater) reliability of the 5 F-Wel instrument in repeated assessments (seven days apart) among adolescent females aged 12-14 years. Percentages of exact agreement for individual items, and the number of respondents who scored within +/-5, +/-7.5 and +/-10 points for total wellness and the five summary dimension scores were calculated. Results Overall, 46 (95.8%) participants responded with complete data and were included in the analysis. Item agreement ranged from 47.8% to 100% across the 97 items (median 69.9%, interquartile range 60.9%-73.9%). The percentage of respondents who scored within +/-5, +/-7.5 and +/-10 points for total wellness at the re-assessment was 87.0%, 97.8% and 97.8% respectively. The percentage of respondents who scored within +/-5, +/-7.5 and +/-10 for the domain scores at the reassessment ranged between 54.3-76.1%, 78.3-95.7% and 89.1-95.7% respectively across the five dimensions. Conclusions These findings suggest there was considerable variation in agreement between the two assessments on some individual items. However, the total wellness score and the five dimension summary scores remained comparatively stable between assessments.
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Monitoring of the integrity of rolling element bearings in the traction system of high speed trains is a fundamental operation in order to avoid catastrophic failures and to implement effective condition-based maintenance strategies. Diagnostics of rolling element bearings is usually based on vibration signal analysis by means of suitable signal processing techniques. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in industrial applications, particularly in the field of rail transport, remains scarcely investigated. This paper will address the diagnostics of bearings taken from the service after a long term operation on a high speed train. These worn bearings have been installed on a test-rig, consisting of a complete full-scale traction system of a high speed train, able to reproduce the effects of wheel-track interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is also proposed.
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Rolling element bearings are the most critical components in the traction system of high speed trains. Monitoring their integrity is a fundamental operation in order to avoid catastrophic failures and to implement effective condition based maintenance strategies. Generally, diagnostics of rolling element bearings is usually performed by analyzing vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. Several papers have been published on this subject in the last two decades, mainly devoted to the development and assessment of signal processing techniques for diagnostics. The experimental validation of such techniques has been traditionally performed by means of laboratory tests on artificially damaged bearings, while their actual effectiveness in specific industrial applications, particularly in rail industry, remains scarcely investigated. This paper is aimed at filling this knowledge gap, by addressing the diagnostics of bearings taken from the service after a long term operation on the traction system of a high speed train. Moreover, in order to test the effectiveness of the diagnostic procedures in the environmental conditions peculiar to the rail application, a specific test-rig has been built, consisting of a complete full-scale train traction system, able to reproduce the effects of wheeltrack interaction and bogie-wheelset dynamics. The results of the experimental campaign show that suitable signal processing techniques are able to diagnose bearing failures even in this harsh and noisy application. Moreover, the most suitable location of the sensors on the traction system is proposed, in order to limit their number.
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Background Parental fever phobia and overuse of antipyretics to control fever is increasing. Little is known about childhood fever management among Arab parents. No scales to measure parents’ fever management practices in Palestine are available. Aims The aims of this study were to translate and examine the psychometric properties of the Arabic version of the Parent Fever Management Scale (PFMS). Methods A standard “forward–backward” procedure was used to translate PFMS into Arabic language. It was then validated on a convenience sample of 402 parents between July and October 2012. Descriptive statistics were used, and instrument reliability was assessed for internal consistency using Cronbach's alpha coefficient. Validity was confirmed using convergent and known group validation. Results Applying the recommended scoring method, the median (interquartile range) score of the PFMS was 26 (23-30). Acceptable internal consistency was found (Cronbach’s alpha = 0.733) and the test–retest reliability value was 0.92 (P < 0.001). The chi-squared (χ2) test showed a significant relationship between PFMS groups and frequent daily administration of antipyretic groups (χ2 = 52.86; P < 0.001). The PFMS sensitivity and specificity were 77.67% and 57.75%, respectively. The positive and negative predictive values were 67.89% and 32.11%, respectively. Conclusions The findings of this validation study indicate that the Arabic version of the PFMS is a reliable and valid measure which can be used as a useful tool for health professionals to identify parents’ fever management practices and thus provide targeted education to reduce the unnecessary burden of care they place on themselves when concerned for a febrile child.
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Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, k -nearest neighbor ( k -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.
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Background: The concept of palliative care consisting of five distinct, clinically meaningful, phases (stable, unstable, deteriorating, terminal and bereavement) was developed in Australia about 20 years ago and is used routinely for communicating clinical status, care planning, quality improvement and funding. Aim: To test the reliability and acceptability of revised definitions of Palliative Care Phase. Design: Multi-centre cross-sectional study involving pairs of clinicians independently rating patients according to revised definitions of Palliative Care Phase. Setting/participants: Clinicians from 10 Australian palliative care services, including 9 inpatient units and 1 mixed inpatient/community-based service. Results: A total of 102 nursing and medical clinicians participated, undertaking 595 paired assessments of 410 patients, of which 90.7% occurred within 2 h. Clinicians rated 54.8% of patients in the stable phase, 15.8% in the unstable phase, 20.8% in the deteriorating phase and 8.7% in the terminal phase. Overall agreement between clinicians’ rating of Palliative Care Phase was substantial (kappa = 0.67; 95% confidence interval = 0.61–0.70). A moderate level of inter-rater reliability was apparent across all participating sites. The results indicated that Palliative Care Phase was an acceptable measure, with no significant difficulties assigning patients to a Palliative Care Phase and a good fit between assessment of phase and the definition of that phase. The most difficult phase to distinguish from other phases was the deteriorating phase. Conclusion: Policy makers, funders and clinicians can be confident that Palliative Care Phase is a reliable and acceptable measure that can be used for care planning, quality improvement and funding purposes.
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Background To determine whether changes in appetite and energy intake (EI) can be detected and play a role in the effectiveness of interventions, it is necessary to identify their variability under normal conditions. We assessed the reproducibility of subjective appetite ratings and ad libitum test meal EI after a standardised pre-load in overweight and obese males. Methods Fifteen overweight and obese males (BMI 30.3 ± 4.9 kg/m2, aged 34.9 ± 10.6 years) completed two identical test days, 7 days apart. Participants were provided with a standardised fixed breakfast (1676 kJ) and 5 h later an ad libitum pasta lunch. An electronic appetite rating system was used to assess subjective ratings before and after the fixed breakfast, and periodically during the postprandial period. EI was assessed at the ad libitum lunch meal. Sample size estimates for paired design studies were calculated. Results Appetite ratings demonstrated a consistent oscillating pattern between test days, and were more reproducible for mean postprandial than fasting ratings. The correlation between ad libitum EI on the two test days was r = 0.78 (P < 0.01). Using a paired design and a power of 0.8, a minimum of 12 participants would be needed to detect a 10 mm change in 5 h postprandial mean ratings and 17 to detect a 500 kJ difference in ad libitum EI. Conclusion Intra-individual variability of appetite and ad libitum test meal EI in overweight and obese males is comparable to previous reports in normal weight adults. Sample size requirements for studies vary depending on the parameter of interest and sensitivity needed.
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There is an increasing desire and emphasis to integrate assessment tools into the everyday training environment of athletes. These tools are intended to fine-tune athlete development, enhance performance and aid in the development of individualised programmes for athletes. The areas of workload monitoring, skill development and injury assessment are expected to benefit from such tools. This paper describes the development of an instrumented leg press and its application to testing leg dominance with a cohort of athletes. The developed instrumented leg press is a 45° reclining sled-type leg press with dual force plates, a displacement sensor and a CCD camera. A custom software client was developed using C#. The software client enabled near-real-time display of forces beneath each limb together with displacement of the quad track roller system and video feedback of the exercise. In recording mode, the collection of athlete particulars is prompted at the start of the exercise, and pre-set thresholds are used subsequently to separate the data into epochs from each exercise repetition. The leg press was evaluated in a controlled study of a cohort of physically active adults who performed a series of leg press exercises. The leg press exercises were undertaken at a set cadence with nominal applied loads of 50%, 100% and 150% of body weight without feedback. A significant asymmetry in loading of the limbs was observed in healthy adults during both the eccentric and concentric phases of the leg press exercise (P < .05). Mean forces were significantly higher beneath the non-dominant limb (4–10%) and during the concentric phase of the muscle action (5%). Given that symmetrical loading is often emphasized during strength training and remains a common goal in sports rehabilitation, these findings highlight the clinical potential for this instrumented leg press system to monitor symmetry in lower-limb loading during progressive strength training and sports rehabilitation protocols.
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PURPOSE
The purposes of this study were to:
1) establish inter-instrument reliability between left and right hip accelerometer placement;
2) examine procedural reliability of a walking protocol used to measure physical activity (PA), and;
3) confirm concurrent validity of accelerometers in measuring PA intensity as compared to the gold standard of oxygen consumption measured by indirect calorimetry.
METHODS
Eight children (mean age: 11.9; SD: 3.2, 75% male) with CP (GMFCS levels I-III) wore ActiGraph GT3X accelerometers on each hip and the Cosmed K4b
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Anthropogenic elemental mercury (Hg0) emission is a serious worldwide environmental problem due to the extreme toxicity of the heavy metal to humans, plants and wildlife. Development of an accurate and cheap microsensor based online monitoring system which can be integrated as part of Hg0 removal and control processes in industry is still a major challenge. Here, we demonstrate that forming Au nanospike structures directly onto the electrodes of a quartz crystal microbalance (QCM) using a novel electrochemical route results in a self-regenerating, highly robust, stable, sensitive and selective Hg0 vapor sensor. The data from a 127 day continuous test performed in the presence of volatile organic compounds and high humidity levels, showed that the sensor with an electrodeposted sensitive layer had 260% higher response magnitude, 3.4 times lower detection limit (,22 mg/m3 or ,2.46 ppbv) and higher accuracy (98% Vs 35%) over a Au control based QCM (unmodified) when exposed to a Hg0 vapor concentration of 10.55 mg/m3 at 1016C. Statistical analysis of the long term data showed that the nano-engineered Hg0 sorption sites on the developed Au nanospikes sensitive layer play a critical role in the enhanced sensitivity and selectivity of the developed sensor towards Hg0 vapor.
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With the variety of PV inverter types and the number of transformerless PV inverters on the Australian market increasing, we revisit some of the issues associated with these topologies. A recent electric shock incident in Queensland (luckily without serious outcome) associated with a transformerless PV system, highlights the need for earthing PV array structures and PV module frames to prevent capacitive leakage currents causing electric shock. The presented test results of the relevant voltages associated with leakage currents of five transformerless PV inverters stress this requirement, which is currently being addressed by both the Clean Energy Council and Standards Australia. DC current injection tests were performed on the same five inverters and were used to develop preliminary recommendations for a more meaningful DC current test procedure for AS4777 Part 2. The test circuit, methodology and results are presented and discussed. A notable temperature dependency of DC current injections with three of the five inverters suggests that DC current injection should be tested at high and low internal inverter temperatures whereas the power dependency noted only for one inverter does not seem to justify recommendations for a (rather involved) standard test procedure at different power levels.
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Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.
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This paper presents a multi-criteria based approach for nondestructive diagnostic structural integrity assessment of a decommissioned flatbed rail wagon (FBRW) used for road bridge superstructure rehabilitation and replacement applications. First, full-scale vibration and static test data sets are employed in a FE model of the FBRW to obtain the best ‘initial’ estimate of the model parameters. Second, the ‘final’ model parameters are predicted using sensitivity-based perturbation analysis without significant difficulties encountered. Consequently, the updated FBRW model is validated using the independent sets of full-scale laboratory static test data. Finally, the updated and validated FE model of the FBRW is used for structural integrity assessment of a single lane FBRW bridge subjected to the Australian bridge design traffic load.