86 resultados para Similarity test


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L'objectiu principal d'aquest projecte final de carrera consisteix en desenvolupar una aplicació web que oferisca un entorn simplificat de desenvolupament integrat (IDE) en el llenguatge C/C++, on els estudiants de batxillerat (o secundària en general) puguen iniciar-se en el seu estudi. La finalitat és proveir un entorn agradable a l'alumnat perquè puga seguir correctament les pràctiques que proposa el professor independentment de les circumstàncies pròpies d'aquest (ubicació temporal o permanentde l'alumnat, sistema operatiu que utilitza, dispositiu emprat per a fer les pràctiques, etc..).

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Aplicació web per a la correcció automàtica de proves tipus test realitzada amb un framework PHP MVC propi i no comercial.

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One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

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The information provided by the alignment-independent GRid Independent Descriptors (GRIND) can be condensed by the application of principal component analysis, obtaining a small number of principal properties (GRIND-PP), which is more suitable for describing molecular similarity. The objective of the present study is to optimize diverse parameters involved in the obtention of the GRIND-PP and validate their suitability for applications, requiring a biologically relevant description of the molecular similarity. With this aim, GRIND-PP computed with a collection of diverse settings were used to carry out ligand-based virtual screening (LBVS) on standard conditions. The quality of the results obtained was remarkable and comparable with other LBVS methods, and their detailed statistical analysis allowed to identify the method settings more determinant for the quality of the results and their optimum. Remarkably, some of these optimum settings differ significantly from those used in previously published applications, revealing their unexplored potential. Their applicability in large compound database was also explored by comparing the equivalence of the results obtained using either computed or projected principal properties. In general, the results of the study confirm the suitability of the GRIND-PP for practical applications and provide useful hints about how they should be computed for obtaining optimum results.

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Background: A number of studies have used protein interaction data alone for protein function prediction. Here, we introduce a computational approach for annotation of enzymes, based on the observation that similar protein sequences are more likely to perform the same function if they share similar interacting partners. Results: The method has been tested against the PSI-BLAST program using a set of 3,890 protein sequences from which interaction data was available. For protein sequences that align with at least 40% sequence identity to a known enzyme, the specificity of our method in predicting the first three EC digits increased from 80% to 90% at 80% coverage when compared to PSI-BLAST. Conclusion: Our method can also be used in proteins for which homologous sequences with known interacting partners can be detected. Thus, our method could increase 10% the specificity of genome-wide enzyme predictions based on sequence matching by PSI-BLAST alone.

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We present a new technique for audio signal comparison based on tonal subsequence alignment and its application to detect cover versions (i.e., different performances of the same underlying musical piece). Cover song identification is a task whose popularity has increased in the Music Information Retrieval (MIR) community along in the past, as it provides a direct and objective way to evaluate music similarity algorithms.This article first presents a series of experiments carried outwith two state-of-the-art methods for cover song identification.We have studied several components of these (such as chroma resolution and similarity, transposition, beat tracking or Dynamic Time Warping constraints), in order to discover which characteristics would be desirable for a competitive cover song identifier. After analyzing many cross-validated results, the importance of these characteristics is discussed, and the best-performing ones are finally applied to the newly proposed method. Multipleevaluations of this one confirm a large increase in identificationaccuracy when comparing it with alternative state-of-the-artapproaches.

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This paper argues that low-stakes test scores, available in surveys, may be partially determined by test-taking motivation, which is associated with personality traits but not with cognitive ability. Therefore, such test score distributions may not be informative regarding cognitive ability distributions. Moreover, correlations, found in survey data, between high test scores and economic success may be partially caused by favorable personality traits. To demonstrate these points, I use the coding speed test that was administered without incentives to National Longitudinal Survey of Youth 1979 (NLSY) participants. I suggest that due to its simplicity its scores may especially depend on individuals' test-taking motivation. I show that controlling for conventional measures of cognitive skills, the coding speed scores are correlated with future earnings of male NLSY participants. Moreover, the coding speed scores of highly motivated, though less educated, population (potential enlists to the armed forces) are higher than NLSY participants' scores. I then use controlled experiments to show that when no performance-based incentives are provided, participants' characteristics, but not their cognitive skills, affect effort invested in the coding speed test. Thus, participants with the same ability (measured by their scores on an incentivized test) have significantly different scores on tests without performance- based incentives.

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The paper explores the consequences that relying on different behavioral assumptions in training managers may have on their future performance. We argue that training with an emphasis on the standard assumptions used in economics (rationality and self-interest) leads future managers to rely excessively on rational and explicit safeguarding, crowding out instinctive contractual heuristics and signaling a 'bad' type to potential partners. In contrast, human assumptions used in management theories, because of their diverse, implicit and even contradictory nature, do not conflict with the innate set of cooperative tools and may provide a good training ground for such tools. We present tentative confirmatory evidence by examining how the weight given to behavioral assumptions in the core courses of the top 100 business schools influences the average salaries of their MBA graduates. Controlling for the average quality of their students and some other schools' characteristics, average salaries are significantly greater for those schools whose core MBA courses contain a higher proportion of management courses as opposed to courses based on economics or technical disciplines.

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Hierarchical clustering is a popular method for finding structure in multivariate data,resulting in a binary tree constructed on the particular objects of the study, usually samplingunits. The user faces the decision where to cut the binary tree in order to determine the numberof clusters to interpret and there are various ad hoc rules for arriving at a decision. A simplepermutation test is presented that diagnoses whether non-random levels of clustering are presentin the set of objects and, if so, indicates the specific level at which the tree can be cut. The test isvalidated against random matrices to verify the type I error probability and a power study isperformed on data sets with known clusteredness to study the type II error.

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The effectiveness of pre-play communication in achieving efficientoutcomes has long been a subject of controversy. In some environments,cheap talk may help to achieve coordination. However, Aumannconjectures that, in a variant of the Stag Hunt game, a signal forefficient play is not self-enforcing and concludes that an "agreementto play [the efficient outcome] conveys no information about what theplayers will do." Harsanyi and Selten (1988) cite this example as anillustration of risk-dominance vs. payoff-dominance. Farrell and Rabin(1996) agree with the logic, but suspect that cheap talk willnonetheless achieve efficiency. The conjecture is tested with one-waycommunication. When the sender first chooses a signal and then anaction, there is impressive coordination: a 94% probability for thepotentially efficient (but risky) play, given a signal for efficientplay. Without communication, efforts to achieve efficiency wereunsuccessful, as the proportion of B moves is only 35%. I also test ahypothesis that the order of the action and the signal affects theresults, finding that the decision order is indeed important. WhileAumann s conjecture is behaviorally disconfirmed when the signal isdetermined initially, the signal s credibility seems to be much moresuspect when the sender is known to have first chosen an action, andthe results are not statistically distinguishable from those whenthere is no signal. Some applications and issues in communication andcoordination are discussed.

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This paper argues that low-stakes test scores, available in surveys, may be partially determinedby test-taking motivation, which is associated with personality traits but not with cognitiveability. Therefore, such test score distributions may not be informative regarding cognitiveability distributions. Moreover, correlations, found in survey data, between high test scoresand economic success may be partially caused by favorable personality traits. To demonstratethese points, I use the coding speed test that was administered without incentives to NationalLongitudinal Survey of Youth 1979 (NLSY) participants. I suggest that due to its simplicityits scores may especially depend on individuals' test-taking motivation. I show that controllingfor conventional measures of cognitive skills, the coding speed scores are correlated with futureearnings of male NLSY participants. Moreover, the coding speed scores of highly motivated,though less educated, population (potential enlists to the armed forces) are higher than NLSYparticipants' scores. I then use controlled experiments to show that when no performance-basedincentives are provided, participants' characteristics, but not their cognitive skills, affect effortinvested in the coding speed test. Thus, participants with the same ability (measured by theirscores on an incentivized test) have significantly different scores on tests without performance-based incentives.

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This paper studies two important reasons why people violate procedure invariance, loss aversion and scale compatibility. The paper extends previous research on loss aversion and scale compatibility by studying loss aversion and scale compatibility simultaneously, by looking at a new decision domain, medical decision analysis, and by examining the effect of loss aversion and scale compatibility on "well-contemplated preferences." We find significant evidence both of loss aversion and scale compatibility. However, the sizes of the biases due to loss aversion and scale compatibility vary over trade-offs and most participants do not behave consistently according to loss aversion or scale compatibility. In particular, the effect of loss aversion in medical trade-offs decreases with duration. These findings are encouraging for utility measurement and prescriptive decision analysis. There appear to exist decision contexts in which the effects of loss aversion and scale compatibility can be minimized and utilities can be measured that do not suffer from these distorting factors.

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This paper tests the internal consistency of time trade-off utilities.We find significant violations of consistency in the direction predictedby loss aversion. The violations disappear for higher gauge durations.We show that loss aversion can also explain that for short gaugedurations time trade-off utilities exceed standard gamble utilities. Ourresults suggest that time trade-off measurements that use relativelyshort gauge durations, like the widely used EuroQol algorithm(Dolan 1997), are affected by loss aversion and lead to utilities thatare too high.

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This paper presents a test of the predictive validity of various classes ofQALY models (i.e., linear, power and exponential models). We first estimatedTTO utilities for 43 EQ-5D chronic health states and next these states wereembedded in health profiles. The chronic TTO utilities were then used topredict the responses to TTO questions with health profiles. We find that thepower QALY model clearly outperforms linear and exponential QALY models.Optimal power coefficient is 0.65. Our results suggest that TTO-based QALYcalculations may be biased. This bias can be avoided using a power QALY model.