799 resultados para Utility-based performance measures


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In this study we propose the use of the performance measure distribution rather than its punctual value to rank hedge funds. Generalized Sharpe Ratio and other similar measures that take into account the higher-order moments of portfolio return distributions are commonly used to evaluate hedge funds performance. The literature in this field has reported non-significant difference in ranking between performance measures that take, and those that do not take, into account higher moments of distribution. Our approach provides a much more powerful manner to differentiate between hedge funds performance. We use a non-semiparametric density based on Gram-Charlier expansions to forecast the conditional distribution of hedge fund returns and its corresponding performance measure distribution. Through a forecasting exercise we show the advantages of our technique in relation to using the more traditional punctual performance measures.

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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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Increasing global competitiveness worldwide has forced manufacturing organizations to produce high-quality products more quickly and at a competitive cost. In order to reach these goals, they need good quality components from suppliers at optimum price and lead time. This actually forced all the companies to adapt different improvement practices such as lean manufacturing, Just in Time (JIT) and effective supply chain management. Applying new improvement techniques and tools cause higher establishment costs and more Information Delay (ID). On the contrary, these new techniques may reduce the risk of stock outs and affect supply chain flexibility to give a better overall performance. But industry people are unable to measure the overall affects of those improvement techniques with a standard evaluation model .So an effective overall supply chain performance evaluation model is essential for suppliers as well as manufacturers to assess their companies under different supply chain strategies. However, literature on lean supply chain performance evaluation is comparatively limited. Moreover, most of the models assumed random values for performance variables. The purpose of this paper is to propose an effective supply chain performance evaluation model using triangular linguistic fuzzy numbers and to recommend optimum ranges for performance variables for lean implementation. The model initially considers all the supply chain performance criteria (input, output and flexibility), converts the values to triangular linguistic fuzzy numbers and evaluates overall supply chain performance under different situations. Results show that with the proposed performance measurement model, improvement area for each variable can be accurately identified.

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Recent studies on automatic new topic identification in Web search engine user sessions demonstrated that neural networks are successful in automatic new topic identification. However most of this work applied their new topic identification algorithms on data logs from a single search engine. In this study, we investigate whether the application of neural networks for automatic new topic identification are more successful on some search engines than others. Sample data logs from the Norwegian search engine FAST (currently owned by Overture) and Excite are used in this study. Findings of this study suggest that query logs with more topic shifts tend to provide more successful results on shift-based performance measures, whereas logs with more topic continuations tend to provide better results on continuation-based performance measures.

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This study investigated how contemporary puppet-based theatre can create deeply imaginative experiences for adult audiences. Designed to interrogate the potential effects of double-vision (Tillis, 1992), the theories of the sublime (Kant, 2008; 2003) and the uncanny (Jentsch, 1906; Freud, 1919) were used to create a series of creative guidelines. As practice-led research, the project embraced an iterative approach consisting of two cycles for creative experimentation, and a third for the creation of the final performance work The Harbinger, presented as a part of La Boite Theatre Company’s mainstage season. A theoretical investigation was also conducted to inform the developing practice.

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Background A goal of the postgraduate clinical pharmacy programme (PGCPP) at the University of Queensland is to enhance clinical practice. Aims To evaluate student perceptions of the impact of the PGCPP on practice and the inclusion of a competency-based performance evaluation as a formative component of the curriculum. Method In 2010, students completed a questionnaire to evaluate the impact of the PGCPP. In 2011, formative competency-based performance evaluations were conducted as a component of the course and the questionnaire was repeated. Responses, competency ratings and evaluation feedback were collated. Data were analysed using descriptive statistics. Results 51/57 (89%) of students completed the questionnaire in 2010 and 2011. Over 90% of students agreed or strongly agreed that the PGCPP enhanced practice, knowledge, confidence and contribution to patient care. Responses were similarly positive after the inclusion of the performance evaluation. Conclusion This study demonstrated that the PGCPP is achieving the goal of enhancing the practice of pharmacists.

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Classical ballet requires dancers to exercise significant muscle control and strength both while stationary and when moving. Following the Royal Academy of Dance (RAD) syllabus, 8 male and 27 female dancers (aged 20.2 + 1.9 yr) in a fulltime university undergraduate dance training program were asked to stand in first position for 10 seconds and then perform 10 repeats of a demi-plié exercise to a counted rhythm. Accelerometer records from the wrist, sacrum, knee and ankle were compared with the numerical scores from a professional dance instructor. The sacrum mounted sensor detected lateral tilts of the torso in dances with lower scores (Spearman’s rank correlation coefficient r = -0.64, p < 0.005). The RMS acceleration amplitude of wrist mounted sensor was linearly correlated to the movement scores (Spearman’s rank correlation coefficient r = 0.63, p < 0.005). The application of sacrum and wrist mounted sensors for biofeedback during dance training is a realistic, low cost option.

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Adopting both the resource-based view and dynamic capability theory this study advances the contention that firms must possess both resources and capabilities at a superior level to achieve superior customer and product performance. To examine this contention this study investigates the individual effect of the complementarity between marketing resources and capability and complementarity between innovation resources and capability on customer and product performance respectively. The results of a survey of 171 B2B manufacturing firms show a significant main effect for complementarity between marketing resources–capability and complementarity between innovation resources–capability on customer and product performance. The findings also show that complementarity marketing resources–capability has a stronger positive relationship with customer performance than with product performance, while complementarity between innovation resources–capability has a stronger positive relationship with product performance than with customer performance.

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Firms are increasingly identifying new avenues to enhance their market position. One such effort involves the firms' ability to continuously learn. Learning has the capacity to enable firms to develop and implement more efficient and effective innovation-focused strategies, resulting in the ability to develop and deliver more products in a timelier manner. This study tests the relationship between innovation resource–capability complementarity and innovation-based performance. This study further elaborates that while innovation resource–capability complementarity drives innovation-based performance; their relationship will be enhanced via the firms' possession of superior learning capability. The findings show a significant effect of innovation resource–capability complementarity on innovation-based performance. The results also show that firms that possess superior learning capability are willing to question their operational processes and routines and make adjustments following the feedback obtained from customers and channels; thereby enhancing their abilities to develop more new products and increase their speed in delivering products to the customers.

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Aim Performance measures for Australian laboratories reporting cervical cytology are a set of quantifiable measures relating to the profile and accuracy of reporting. This study reviews aggregate data collected over the ten years in which participation in the performance measures has been mandatory. Methods Laboratories submit annual data on performance measures relating to the profile of reporting, including reporting rates for technically unsatisfactory specimens, high grade or possible high grade abnormalities and abnormal reports. Cytology-histology correlation data and review findings of negative smears reported from women with histological high grade disease are also collected. Suggested acceptable standards are set for each measure. This study reviews the aggregate data submitted by all laboratories for the years 1998-2008 and examines trends in reporting and the performance of laboratories against the suggested standards. Results The performance of Australian laboratories has shown continued improvement over the study period. There has been a fall in the proportion of laboratories with data outside the acceptable standard range in all performance measures. Laboratories are reporting a greater proportion of specimens as definite or possible high grade abnormality. This is partly attributable to an increase in the proportion of abnormal results classified as high grade or possible high grade abnormality. Despite this, the positive predictive value for high grade and possible high grade abnormalities has continued to rise. Conclusion Performance measures for cervical cytology have provided a valuable addition to external quality assurance procedures in Australia. They have documented continued improvements in the aggregate performance, as well as providing benchmarking data and goals for acceptable performance for individual laboratories.

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We present a new approach to spoken language modeling for language identification (LID) using the Lempel-Ziv-Welch (LZW) algorithm. The LZW technique is applicable to any kind of tokenization of the speech signal. Because of the efficiency of LZW algorithm to obtain variable length symbol strings in the training data, the LZW codebook captures the essentials of a language effectively. We develop two new deterministic measures for LID based on the LZW algorithm namely: (i) Compression ratio score (LZW-CR) and (ii) weighted discriminant score (LZW-WDS). To assess these measures, we consider error-free tokenization of speech as well as artificially induced noise in the tokenization. It is shown that for a 6 language LID task of OGI-TS database with clean tokenization, the new model (LZW-WDS) performs slightly better than the conventional bigram model. For noisy tokenization, which is the more realistic case, LZW-WDS significantly outperforms the bigram technique

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Dynamic Voltage and Frequency Scaling (DVFS) is a very effective tool for designing trade-offs between energy and performance. In this paper, we use a formal Petri net based program performance model that directly captures both the application and system properties, to find energy efficient DVFS settings for CMP systems, that satisfy a given performance constraint, for SPMD multithreaded programs. Experimental evaluation shows that we achieve significant energy savings, while meeting the performance constraints.