947 resultados para evaluation methods


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This paper discusses the impact of machine translation on the language industry, specifically addressing its effect on translators. It summarizes the history of the development of machine translation, explains the underlying theory that ties machine translation to its practical applications, and describes the different types of machine translation as well as other tools familiar to translators. There are arguments for and against its use, as well as evaluation methods for testing it. Internet and real-time communication are featured for their role in the increase of machine translation use. The potential that this technology has in the future of professional translation is examined. This paper shows that machine translation will continue to be increasingly used whether translators like it or not.

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The adaptation of the Spanish University to the European Higher Education Area (EEES in Spanish) demands the integration of new tools and skills that would make the teaching- learning process easier. This adaptation involves a change in the evaluation methods, which goes from a system where the student was evaluated with a final exam, to a new system where we include a continuous evaluation in which the final exam may represent at most 50% in the vast majority of the Universities. Devising a new and fair continuous evaluation system is not an easy task to do. That would mean a student’s’ learning process follow-up by the teachers, and as a consequence an additional workload on existing staff resources. Traditionally, the continuous evaluation is associated with the daily work of the student and a collection of the different marks partly or entirely based on the work they do during the academic year. Now, small groups of students and an attendance control are important aspects to take into account in order to get an adequate assessment of the students. However, most of the university degrees have groups with more than 70 students, and the attendance control is a complicated task to perform, mostly because it consumes significant amounts of staff time. Another problem found is that the attendance control would encourage not-interested students to be present at class, which might cause some troubles to their classmates. After a two year experience in the development of a continuous assessment in Statistics subjects in Social Science degrees, we think that individual and periodical tasks are the best way to assess results. These tasks or examinations must be done in classroom during regular lessons, so we need an efficient system to put together different and personal questions in order to prevent students from cheating. In this paper we provide an efficient and effective way to elaborate random examination papers by using Sweave, a tool that generates data, graphics and statistical calculus from the software R and shows results in PDF documents created by Latex. In this way, we will be able to design an exam template which could be compiled in order to generate as many PDF documents as it is required, and at the same time, solutions are provided to easily correct them.

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Species distribution models (SDM) predict species occurrence based on statistical relationships with environmental conditions. The R-package biomod2 which includes 10 different SDM techniques and 10 different evaluation methods was used in this study. Macroalgae are the main biomass producers in Potter Cove, King George Island (Isla 25 de Mayo), Antarctica, and they are sensitive to climate change factors such as suspended particulate matter (SPM). Macroalgae presence and absence data were used to test SDMs suitability and, simultaneously, to assess the environmental response of macroalgae as well as to model four scenarios of distribution shifts by varying SPM conditions due to climate change. According to the averaged evaluation scores of Relative Operating Characteristics (ROC) and True scale statistics (TSS) by models, those methods based on a multitude of decision trees such as Random Forest and Classification Tree Analysis, reached the highest predictive power followed by generalized boosted models (GBM) and maximum-entropy approaches (Maxent). The final ensemble model used 135 of 200 calculated models (TSS > 0.7) and identified hard substrate and SPM as the most influencing parameters followed by distance to glacier, total organic carbon (TOC), bathymetry and slope. The climate change scenarios show an invasive reaction of the macroalgae in case of less SPM and a retreat of the macroalgae in case of higher assumed SPM values.

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Document classification is a supervised machine learning process, where predefined category labels are assigned to documents based on the hypothesis derived from training set of labelled documents. Documents cannot be directly interpreted by a computer system unless they have been modelled as a collection of computable features. Rogati and Yang [M. Rogati and Y. Yang, Resource selection for domain-specific cross-lingual IR, in SIGIR 2004: Proceedings of the 27th annual international conference on Research and Development in Information Retrieval, ACM Press, Sheffied: United Kingdom, pp. 154-161.] pointed out that the effectiveness of document classification system may vary in different domains. This implies that the quality of document model contributes to the effectiveness of document classification. Conventionally, model evaluation is accomplished by comparing the effectiveness scores of classifiers on model candidates. However, this kind of evaluation methods may encounter either under-fitting or over-fitting problems, because the effectiveness scores are restricted by the learning capacities of classifiers. We propose a model fitness evaluation method to determine whether a model is sufficient to distinguish positive and negative instances while still competent to provide satisfactory effectiveness with a small feature subset. Our experiments demonstrated how the fitness of models are assessed. The results of our work contribute to the researches of feature selection, dimensionality reduction and document classification.

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Continuing Professional Development (CPD) is seen as a vital part of a professional engineer’s career, by professional engineering institutions as well as individual engineers. Factors such as ever-changing workforce requirements and rapid technological change have resulted in engineers no longer being able to rely just on the skills they learnt at university or can pick up on the job; they must undergo a structured professional development with clear objectives to develop further professional knowledge, values and skills. This paper presents a course developed for students undertaking a Master of Engineering or Master of Project Management at the University of Queensland. This course was specifically designed to help students plan their continuing professional development, while developing professional skills such as communication, ethical reasoning, critical judgement and the need for sustainable development. The course utilised a work integrated learning pedagogy applied within a formal learning environment, and followed the competency based chartered membership program of Engineers Australia, the peak professional body of engineers in Australia. The course was developed and analysed using an action learning approach. The main research question was “Can extra teaching and learning activities be developed that will simulate workplace learning?” The students continually assessed and reflected upon their current competencies, skills and abilities, and planed for the future attainment of specific competencies which they identified as important to their future careers. Various evaluation methods, including surveys before and after the course, were used to evaluate the action learning intervention. It was found that the assessment developed for the course was one of the most important factors, not only in driving student learning, as is widely accepted, but also in changing the students’ understandings and acceptance of the need for continuous professional development. The students also felt that the knowledge, values and skills they developed would be beneficial for their future careers, as they were developed within the context of their own professional development, rather than to just get through the course. © 2005, American Society for Engineering Education

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Financial institutes are an integral part of any modern economy. In the 1970s and 1980s, Gulf Cooperation Council (GCC) countries made significant progress in financial deepening and in building a modern financial infrastructure. This study aims to evaluate the performance (efficiency) of financial institutes (banking sector) in GCC countries. Since, the selected variables include negative data for some banks and positive for others, and the available evaluation methods are not helpful in this case, so we developed a Semi Oriented Radial Model to perform this evaluation. Furthermore, since the SORM evaluation result provides a limited information for any decision maker (bankers, investors, etc...), we proposed a second stage analysis using classification and regression (C&R) method to get further results combining SORM results with other environmental data (Financial, economical and political) to set rules for the efficient banks, hence, the results will be useful for bankers in order to improve their bank performance and to the investors, maximize their returns. Mainly there are two approaches to evaluate the performance of Decision Making Units (DMUs), under each of them there are different methods with different assumptions. Parametric approach is based on the econometric regression theory and nonparametric approach is based on a mathematical linear programming theory. Under the nonparametric approaches, there are two methods: Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH). While there are three methods under the parametric approach: Stochastic Frontier Analysis (SFA); Thick Frontier Analysis (TFA) and Distribution-Free Analysis (DFA). The result shows that DEA and SFA are the most applicable methods in banking sector, but DEA is seem to be most popular between researchers. However DEA as SFA still facing many challenges, one of these challenges is how to deal with negative data, since it requires the assumption that all the input and output values are non-negative, while in many applications negative outputs could appear e.g. losses in contrast with profit. Although there are few developed Models under DEA to deal with negative data but we believe that each of them has it is own limitations, therefore we developed a Semi-Oriented-Radial-Model (SORM) that could handle the negativity issue in DEA. The application result using SORM shows that the overall performance of GCC banking is relatively high (85.6%). Although, the efficiency score is fluctuated over the study period (1998-2007) due to the second Gulf War and to the international financial crisis, but still higher than the efficiency score of their counterpart in other countries. Banks operating in Saudi Arabia seem to be the highest efficient banks followed by UAE, Omani and Bahraini banks, while banks operating in Qatar and Kuwait seem to be the lowest efficient banks; this is because these two countries are the most affected country in the second Gulf War. Also, the result shows that there is no statistical relationship between the operating style (Islamic or Conventional) and bank efficiency. Even though there is no statistical differences due to the operational style, but Islamic bank seem to be more efficient than the Conventional bank, since on average their efficiency score is 86.33% compare to 85.38% for Conventional banks. Furthermore, the Islamic banks seem to be more affected by the political crisis (second Gulf War), whereas Conventional banks seem to be more affected by the financial crisis.

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Evaluation and benchmarking in content-based image retrieval has always been a somewhat neglected research area, making it difficult to judge the efficacy of many presented approaches. In this paper we investigate the issue of benchmarking for colour-based image retrieval systems, which enable users to retrieve images from a database based on lowlevel colour content alone. We argue that current image retrieval evaluation methods are not suited to benchmarking colour-based image retrieval systems, due in main to not allowing users to reflect upon the suitability of retrieved images within the context of a creative project and their reliance on highly subjective ground-truths. As a solution to these issues, the research presented here introduces the Mosaic Test for evaluating colour-based image retrieval systems, in which test-users are asked to create an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. We report on our findings from a user study which suggests that the Mosaic Test overcomes the major drawbacks associated with existing image retrieval evaluation methods, by enabling users to reflect upon image selections and automatically measuring image relevance in a way that correlates with the perception of many human assessors. We therefore propose that the Mosaic Test be adopted as a standardised benchmark for evaluating and comparing colour-based image retrieval systems.

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This paper summarizes the scientific work presented at the 32nd European Conference on Information Retrieval. It demonstrates that information retrieval (IR) as a research area continues to thrive with progress being made in three complementary sub-fields, namely IR theory and formal methods together with indexing and query representation issues, furthermore Web IR as a primary application area and finally research into evaluation methods and metrics. It is the combination of these areas that gives IR its solid scientific foundations. The paper also illustrates that significant progress has been made in other areas of IR. The keynote speakers addressed three such subject fields, social search engines using personalization and recommendation technologies, the renewed interest in applying natural language processing to IR, and multimedia IR as another fast-growing area.

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This report examines the results of a pilot study, which used a method of evaluation called randomised control trials (RCTs) to see if a popular business support scheme called Creative Credits worked effectively. The pilot study, which began in Manchester in 2009, was structured so that vouchers, or 'Creative Credits', would be randomly allocated to small and medium-sized businesses applying to invest in creative projects such as developing websites, video production and creative marketing campaigns, to see if they had a real effect on innovation. The research found that the firms who were awarded Creative Credits enjoyed a short-term boost in their innovation and sales growth in the six months following completion of their creative projects. However, the positive effects were not sustained, and after 12 months there was no longer a statistically significant difference between the groups that received the credits and those that didn’t. The report argues that these results would have remained hidden using the normal evaluation methods used by government, and calls for RCTs to be used more widely when evaluating policies to support business growth.

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A variety of content-based image retrieval systems exist which enable users to perform image retrieval based on colour content - i.e., colour-based image retrieval. For the production of media for use in television and film, colour-based image retrieval is useful for retrieving specifically coloured animations, graphics or videos from large databases (by comparing user queries to the colour content of extracted key frames). It is also useful to graphic artists creating realistic computer-generated imagery (CGI). Unfortunately, current methods for evaluating colour-based image retrieval systems have 2 major drawbacks. Firstly, the relevance of images retrieved during the task cannot be measured reliably. Secondly, existing methods do not account for the creative design activity known as reflection-in-action. Consequently, the development and application of novel and potentially more effective colour-based image retrieval approaches, better supporting the large number of users creating media for use in television and film productions, is not possible as their efficacy cannot be reliably measured and compared to existing technologies. As a solution to the problem, this paper introduces the Mosaic Test. The Mosaic Test is a user-based evaluation approach in which participants complete an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. In this paper, we introduce the Mosaic Test and report on a user evaluation. The findings of the study reveal that the Mosaic Test overcomes the 2 major drawbacks associated with existing evaluation methods and does not require expert participants. © 2012 Springer Science+Business Media, LLC.

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Background: Coronary heart disease (CHD) is a public health priority in the UK. The National Service Framework (NSF) has set standards for the prevention, diagnosis and treatment of CHD, which include the use of cholesterol-lowering agents aimed at achieving targets of blood total cholesterol (TC) < 5.0 mmol/L and low density lipoprotein-cholesterol (LDL-C) < 3.0 mmol/L. In order to achieve these targets cost effectively, prescribers need to make an informed choice from the range of statins available. Aim: To estimate the average and relative cost effectiveness of atorvastatin, fluvastatin, pravastatin and simvastatin in achieving the NSF LDL-C and TC targets. Design: Model-based economic evaluation. Methods: An economic model was constructed to estimate the number of patients achieving the NSF targets for LDL-C and TC at each dose of statin, and to calculate the average drug cost and incremental drug cost per patient achieving the target levels. The population baseline LDL-C and TC, and drug efficacy and drug costs were taken from previously published data. Estimates of the distribution of patients receiving each dose of statin were derived from the UK national DIN-LINK database. Results: The estimated annual drug cost per 1000 patients treated with atorvastatin was £289 000, with simvastatin £315 000, with pravastatin £333 000 and with fluvastatin £167 000. The percentages of patients achieving target are 74.4%, 46.4%, 28.4% and 13.2% for atorvastatin, simvastatin, pravastatin and fluvastatin, respectively. Incremental drug cost per extra patient treated to LDL-C and TC targets compared with fluvastafin were £198 and £226 for atorvastatin, £443 and £567 for simvastatin and £1089 and £2298 for pravastatin, using 2002 drug costs. Conclusions: As a result of its superior efficacy, atorvastatin generates a favourable cost-effectiveness profile as measured by drug cost per patient treated to LDL-C and TC targets. For a given drug budget, more patients would achieve NSF LDL-C and TC targets with atorvastatin than with any of the other statins examined.

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The article examines the main approaches to external evaluation and accreditation in higher education. It also presents COMPASS-OK: a social network for electronic evaluation and management of the quality of education, which utilizes mechanisms for management of documentation flows and supports tools for modeling of evaluation methods and procedures.

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A hazai turizmus gyakorlatával kapcsolatos vizsgálatok tapasztalatai nyomán az egri Eszterházy Károly Főiskola (EKF) turizmusmenedzsment-kurzusának oktatói célszerűnek ítélték a témára vonatkozó tananyag fejlesztését. A cikk szerzői azt remélik azonban, hogy az utóbbi munka egyes megállapításai minden, a gazdasági földrajz, a turizmus (idegenforgalom), a térségfejlesztés valamely szegmensével foglalkozó szakembernek, kiemelten: vezetőnek – s több más gazdasági ág illetékeseinek – az érdeklődésére számot tarthatnak, ezért ezekről jelen cikkben is beszámolnak. _____ In this article the authors reviewed first the different types of tourist attractions (destinations) and they analysed the common evaluation methods of their attractiveness (e.g. the possibilities and limits of the tourism statistics). Then they tried to display the existing information on the main Hungarian attractions and their attractiveness. In this study revealed that there exist no generally recognized list of the most visited attractions, and the real measures of their attractiveness are not known either. The authors emphasize that shaping a comprehensive concept on the above mentioned issue would highly contribute to the elaboration of a successful and achievable tourism strategy, thus it would be of great importance.

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Mathematics is rigidly classified as an academic discipline. This determines curriculum content and teaching and evaluation methods. These methods can give rise to negative views of mathematics, resulting in increased math anxiety. Educators, therefore, need to look beyond the discipline to provide a classroom environment that meets students’ needs.

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Corporate executives closely monitor the accuracy of their hotels' occupancy fore- casts since important decisions are based upon these predictions. This study lists the criteria for selecting an appropriate error measure. It discusses several evaluation methods focusing on statistical significance tests and demonstrates the use of two adequate evaluation methods: Mincer- Zamowitz's efficiency test and Wilcoxon's Non-Parametric Matched-Pairs Signed- Ranks test.