768 resultados para Retest Reliability
Resumo:
Background: Antibiotic overuse is a global public health issue that is influenced by several factors. The degree and prevalence of antibiotic overuse is difficult to measure directly. A more practical approach, such as the use of a psycho-social measurement instrument, might allow for the observation and assessment of patterns of antibiotic use. Study objective: The aim of this paper is to review the nature, validity, and reliability of measurement scales designed to measure factors associated with antibiotic misuse/overuse. Design: This study is descriptive and includes a systematic integration of the measurement scales used in the literature to measure factors associated with antibiotic misuse/overuse. The review included 70 international scientific publications from 1992 to 2010. Main results: Studies have presented scales to measure antibiotic misuse. However, the workup of these instruments is often not mentioned, or the scales are used with only early-phase validation, such as content or face validity. Other studies have discussed the reliability of these scales. However, the full validation process has not been discussed in any of the reviewed measurement scales. Conclusion: A reliable, fully validated measurement scale must be developed to assess the factors associated with the overuse of antibiotics. Identifying these factors will help to minimize the misuse of antibiotics.
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STUDY DESIGN: Controlled laboratory study. OBJECTIVES: To investigate the reliability and concurrent validity of photographic measurements of hallux valgus angle compared to radiographs as the criterion standard. BACKGROUND: Clinical assessment of hallux valgus involves measuring alignment between the first toe and metatarsal on weight-bearing radiographs or visually grading the severity of deformity with categorical scales. Digital photographs offer a noninvasive method of measuring deformity on an exact scale; however, the validity of this technique has not previously been established. METHODS: Thirty-eight subjects (30 female, 8 male) were examined (76 feet, 54 with hallux valgus). Computer software was used to measure hallux valgus angle from digital records of bilateral weight-bearing dorsoplantar foot radiographs and photographs. One examiner measured 76 feet on 2 occasions 2 weeks apart, and a second examiner measured 40 feet on a single occasion. Reliability was investigated by intraclass correlation coefficients and validity by 95% limits of agreement. The Pearson correlation coefficient was also calculated. RESULTS: Intrarater and interrater reliability were very high (intraclass correlation coefficients greater than 0.96) and 95% limits of agreement between photographic and radiographic measurements were acceptable. Measurements from photographs and radiographs were also highly correlated (Pearson r = 0.96). CONCLUSIONS: Digital photographic measurements of hallux valgus angle are reliable and have acceptable validity compared to weight-bearing radiographs. This method provides a convenient and precise tool in assessment of hallux valgus, while avoiding the cost and radiation exposure associated with radiographs.
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Reliable ambiguity resolution (AR) is essential to Real-Time Kinematic (RTK) positioning and its applications, since incorrect ambiguity fixing can lead to largely biased positioning solutions. A partial ambiguity fixing technique is developed to improve the reliability of AR, involving partial ambiguity decorrelation (PAD) and partial ambiguity resolution (PAR). Decorrelation transformation could substantially amplify the biases in the phase measurements. The purpose of PAD is to find the optimum trade-off between decorrelation and worst-case bias amplification. The concept of PAR refers to the case where only a subset of the ambiguities can be fixed correctly to their integers in the integer least-squares (ILS) estimation system at high success rates. As a result, RTK solutions can be derived from these integer-fixed phase measurements. This is meaningful provided that the number of reliably resolved phase measurements is sufficiently large for least-square estimation of RTK solutions as well. Considering the GPS constellation alone, partially fixed measurements are often insufficient for positioning. The AR reliability is usually characterised by the AR success rate. In this contribution an AR validation decision matrix is firstly introduced to understand the impact of success rate. Moreover the AR risk probability is included into a more complete evaluation of the AR reliability. We use 16 ambiguity variance-covariance matrices with different levels of success rate to analyse the relation between success rate and AR risk probability. Next, the paper examines during the PAD process, how a bias in one measurement is propagated and amplified onto many others, leading to more than one wrong integer and to affect the success probability. Furthermore, the paper proposes a partial ambiguity fixing procedure with a predefined success rate criterion and ratio-test in the ambiguity validation process. In this paper, the Galileo constellation data is tested with simulated observations. Numerical results from our experiment clearly demonstrate that only when the computed success rate is very high, the AR validation can provide decisions about the correctness of AR which are close to real world, with both low AR risk and false alarm probabilities. The results also indicate that the PAR procedure can automatically chose adequate number of ambiguities to fix at given high-success rate from the multiple constellations instead of fixing all the ambiguities. This is a benefit that multiple GNSS constellations can offer.
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The rank transform is one non-parametric transform which has been applied to the stereo matching problem The advantages of this transform include its invariance to radio metric distortion and its amenability to hardware implementation. This paper describes the derivation of the rank constraint for matching using the rank transform Previous work has shown that this constraint was capable of resolving ambiguous matches thereby improving match reliability A new matching algorithm incorporating this constraint was also proposed. This paper extends on this previous work by proposing a matching algorithm which uses a dimensional match surface in which the match score is computed for every possible template and match window combination. The principal advantage of this algorithm is that the use of the match surface enforces the left�right consistency and uniqueness constraints thus improving the algorithms ability to remove invalid matches Experimental results for a number of test stereo pairs show that the new algorithm is capable of identifying and removing a large number of in incorrect matches particularly in the case of occlusions
Resumo:
The rank transform is a non-parametric technique which has been recently proposed for the stereo matching problem. The motivation behind its application to the matching problem is its invariance to certain types of image distortion and noise, as well as its amenability to real-time implementation. This paper derives an analytic expression for the process of matching using the rank transform, and then goes on to derive one constraint which must be satisfied for a correct match. This has been dubbed the rank order constraint or simply the rank constraint. Experimental work has shown that this constraint is capable of resolving ambiguous matches, thereby improving matching reliability. This constraint was incorporated into a new algorithm for matching using the rank transform. This modified algorithm resulted in an increased proportion of correct matches, for all test imagery used.
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Summary Background The final phase of a three phase study analysing the implementation and impact of the nurse practitioner role in Australia (the Australian Nurse Practitioner Project or AUSPRAC) was undertaken in 2009, requiring nurse telephone interviewers to gather information about health outcomes directly from patients and their treating nurse practitioners. A team of several registered nurses was recruited and trained as telephone interviewers. The aim of this paper is to report on development and evaluation of the training process for telephone interviewers. Methods The training process involved planning the content and methods to be used in the training session; delivering the session; testing skills and understanding of interviewers post-training; collecting and analysing data to determine the degree to which the training process was successful in meeting objectives and post-training follow-up. All aspects of the training process were informed by established educational principles. Results Interrater reliability between interviewers was high for well-validated sections of the survey instrument resulting in 100% agreement between interviewers. Other sections with unvalidated questions showed lower agreement (between 75% and 90%). Overall the agreement between interviewers was 92%. Each interviewer was also measured against a specifically developed master script or gold standard and for this each interviewer achieved a percentage of correct answers of 94.7% or better. This equated to a Kappa value of 0.92 or better. Conclusion The telephone interviewer training process was very effective and achieved high interrater reliability. We argue that the high reliability was due to the use of well validated instruments and the carefully planned programme based on established educational principles. There is limited published literature on how to successfully operationalise educational principles and tailor them for specific research studies; this report addresses this knowledge gap.
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Urban transit system performance may be quantified and assessed using transit capacity and productive capacity for planning, design and operational management. Bunker (4) defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures transit task performed over distance. Transit productiveness (p-km/h) captures transit work performed over time. This paper applies productive performance with risk assessment to quantify transit system reliability. Theory is developed to monetize transit segment reliability risk on the basis of demonstration Annual Reliability Event rates by transit facility type, segment productiveness, and unit-event severity. A comparative example of peak hour performance of a transit sub-system containing bus-on-street, busway, and rail components in Brisbane, Australia demonstrates through practical application the importance of valuing reliability. Comparison reveals the highest risk segments to be long, highly productive on street bus segments followed by busway (BRT) segments and then rail segments. A transit reliability risk reduction treatment example demonstrates that benefits can be significant and should be incorporated into project evaluation in addition to those of regular travel time savings, reduced emissions and safety improvements. Reliability can be used to identify high risk components of the transit system and draw comparisons between modes both in planning and operations settings, and value improvement scenarios in a project evaluation setting. The methodology can also be applied to inform daily transit system operational management.
Resumo:
Urban transit system performance may be quantified and assessed using transit capacity and productive capacity for planning, design and operational management. Bunker (4) defines important productive performance measures of an individual transit service and transit line. Transit work (p-km) captures transit task performed over distance. Transit productiveness (p-km/h) captures transit work performed over time. This paper applies productive performance with risk assessment to quantify transit system reliability. Theory is developed to monetize transit segment reliability risk on the basis of demonstration Annual Reliability Event rates by transit facility type, segment productiveness, and unit-event severity. A comparative example of peak hour performance of a transit sub-system containing bus-on-street, busway, and rail components in Brisbane, Australia demonstrates through practical application the importance of valuing reliability. Comparison reveals the highest risk segments to be long, highly productive on street bus segments followed by busway (BRT) segments and then rail segments. A transit reliability risk reduction treatment example demonstrates that benefits can be significant and should be incorporated into project evaluation in addition to those of regular travel time savings, reduced emissions and safety improvements. Reliability can be used to identify high risk components of the transit system and draw comparisons between modes both in planning and operations settings, and value improvement scenarios in a project evaluation setting. The methodology can also be applied to inform daily transit system operational management.
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The ability to forecast machinery health is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models which attempt to forecast machinery health based on condition data such as vibration measurements. This paper demonstrates how the population characteristics and condition monitoring data (both complete and suspended) of historical items can be integrated for training an intelligent agent to predict asset health multiple steps ahead. The model consists of a feed-forward neural network whose training targets are asset survival probabilities estimated using a variation of the Kaplan–Meier estimator and a degradation-based failure probability density function estimator. The trained network is capable of estimating the future survival probabilities when a series of asset condition readings are inputted. The output survival probabilities collectively form an estimated survival curve. Pump data from a pulp and paper mill were used for model validation and comparison. The results indicate that the proposed model can predict more accurately as well as further ahead than similar models which neglect population characteristics and suspended data. This work presents a compelling concept for longer-range fault prognosis utilising available information more fully and accurately.
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The IEEE Subcommittee on the Application of Probability Methods (APM) published the IEEE Reliability Test System (RTS) [1] in 1979. This system provides a consistent and generally acceptable set of data that can be used both in generation capacity and in composite system reliability evaluation [2,3]. The test system provides a basis for the comparison of results obtained by different people using different methods. Prior to its publication, there was no general agreement on either the system or the data that should be used to demonstrate or test various techniques developed to conduct reliability studies. Development of reliability assessment techniques and programs are very dependent on the intent behind the development as the experience of one power utility with their system may be quite different from that of another utility. The development and the utilization of a reliability program are, therefore, greatly influenced by the experience of a utlity and the intent of the system manager, planner and designer conducting the reliability studies. The IEEE-RTS has proved to be extremely valuable in highlighting and comparing the capabilities (or incapabilities) of programs used in reliability studies, the differences in the perception of various power utilities and the differences in the solution techniques. The IEEE-RTS contains a reasonably large power network which can be difficult to use for initial studies in an educational environment.
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The IEEE Reliability Test System (RTS) developed by the Application of Probability Method Subcommittee has been used to compare and test a wide range of generating capacity and composite system evaluation techniques and subsequent digital computer programs. A basic reliability test system is presented which has evolved from the reliability education and research programs conducted by the Power System Research Group at the University of Saskatchewan. The basic system data necessary for adequacy evaluation at the generation and composite generation and transmission system levels are presented together with the fundamental data required to conduct reliability-cost/reliability-worth evaluation
Resumo:
A set of basic reliability indices at the generation and composite generation and transmission levels for a small reliability test system are presented. The test system and the results presented have evolved from reliability research and teaching programs. The indices presented are for fundamental reliability applications which should be covered in a power system reliability teaching program. The RBTS test system and the basic indices provide a valuable reference for faculty and students engaged in reliability teaching and research
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In this paper a combined subtransmission and distribution reliability analysis of SEQEB’s outer suburban network is presented. The reliability analysis was carried out with a commercial software package which evaluates both energy and customer indices. Various reinforcement options were investigated to ascertain the impact they have on the reliability of supply seen by the customers. The customer and energy indices produced by the combined subtransmission and distribution reliability studies contributed to optimise capital expenditure to the most effective areas of the network.
Resumo:
Capacity probability models of generating units are commonly used in many power system reliability studies, at hierarchical level one (HLI). Analytical modelling of a generating system with many units or generating units with many derated states in a system, can result in an extensive number of states in the capacity model. Limitations on available memory and computational time of present computer facilities can pose difficulties for assessment of such systems in many studies. A cluster procedure using the nearest centroid sorting method was used for IEEE-RTS load model. The application proved to be very effective in producing a highly similar model with substantially fewer states. This paper presents an extended application of the clustering method to include capacity probability representation. A series of sensitivity studies are illustrated using IEEE-RTS generating system and load models. The loss of load and energy expectations (LOLE, LOEE), are used as indicators to evaluate the application