8 resultados para Classifier Generalization Ability
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
Objective: To assess the influence of energy and pulse repetition rate of Er:YAG laser on the enamel ablation ability and substrate morphology. Methods: Fifteen crowns of molars were sectioned in four fragments, providing 60 samples, which were ground to flatten the enamel surface. The initial mass was obtained by weighing the fragments. The specimens were hydrated for I h, fixed, and a 3-mm-diameter area was delimited. Twelve groups were randomly formed according to the combination of laser energies (200, 250, 300, or 350 mJ) and pulse repetition rates (2, 3, or 4 Hz). The final mass was obtained and mass loss was calculated by the difference between the initial and final mass. The specimens were prepared for SEM. Data were submitted to ANOVA and Scheffe test. Results: The 4 Hz frequency resulted in higher mass loss and was statistically different from 2 and 3 Hz (p < 0.05). The increase of frequency produced more melted areas, cracks, and unselective and deeper ablation. The 350 mJ energy promoted greater mass loss, similar to 300 mJ. Conclusions: The pulse repetition rate influenced more intensively the mass loss and morphological alteration. Among the tested parameters, 350 mJ/3 Hz improved the ability of enamel ablation with less surface morphological alterations. (C) 2007 Wiley Periodicals, Inc. J Biomed Mater Res.
Resumo:
The association between working hours and work ability was examined in a cross-sectional study of male (N = 156) and female (N = 1092) nurses in three public hospitals. Working hours were considered in terms of their professional and domestic hours per week and their combined impact; total work load. Logistic regression analysis showed a significant association between total work load and inadequate work ability index (WAI) for females only. Females reported a higher proportion of inadequate WAI, fewer professional work hours but longer domestic work hours. There were no significant differences in total work load by gender. The combination of professional and domestic work hours in females seemed to best explain their lower work ability. The findings suggest that investigations into female well-being need to consider their total work load. Our male sample may have lacked sufficient power to detect a relationship between working hours and work ability. (c) 2008 Elsevier Ltd. All rights reserved.
Resumo:
To test the association between night work and work ability, and verify whether the type of contractual employment has any influence over this association. Permanent workers (N = 642) and workers with precarious jobs (temporary contract or outsourced; N = 552) were interviewed and filled out questionnaires concerning work hours and work ability index. They were classified into: never worked at night, ex-night workers, currently working up to five nights, and currently working at least six nights/2-week span. After adjusting for socio-demography and work variables, current night work was significantly associated with inadequate WAI (vs. day work with no experience in night work) only for precarious workers (OR 2.00, CI 1.01-3.95 and OR 1.85, CI 1.09-3.13 for those working up to five nights and those working at least six nights in 2 weeks, respectively). Unequal opportunities at work and little experience in night work among precarious workers may explain their higher susceptibility to night work.
Resumo:
The aim of this study was to evaluate work ability among college educators before and after an intervention at the workplace. An administrative restructuring in the workplace started to be implemented in 2005. The work ability index (WAI) was administered to 154 educators before the restructure in 2004 and to 60 educators following the restructure in 2006. A mest comparing the WAI score of the 60 educators who took part in both phases showed a trend of improving work ability (p = 0.06; mean WAI in 2004 was 41.7 and 43.3 in 2006). The results suggest that the intervention led to an improvement in psychosocial factors, which in turn positively influenced work ability. (c) 2008 Elsevier Ltd. All rights reserved.
Resumo:
Identifying the correct sense of a word in context is crucial for many tasks in natural language processing (machine translation is an example). State-of-the art methods for Word Sense Disambiguation (WSD) build models using hand-crafted features that usually capturing shallow linguistic information. Complex background knowledge, such as semantic relationships, are typically either not used, or used in specialised manner, due to the limitations of the feature-based modelling techniques used. On the other hand, empirical results from the use of Inductive Logic Programming (ILP) systems have repeatedly shown that they can use diverse sources of background knowledge when constructing models. In this paper, we investigate whether this ability of ILP systems could be used to improve the predictive accuracy of models for WSD. Specifically, we examine the use of a general-purpose ILP system as a method to construct a set of features using semantic, syntactic and lexical information. This feature-set is then used by a common modelling technique in the field (a support vector machine) to construct a classifier for predicting the sense of a word. In our investigation we examine one-shot and incremental approaches to feature-set construction applied to monolingual and bilingual WSD tasks. The monolingual tasks use 32 verbs and 85 verbs and nouns (in English) from the SENSEVAL-3 and SemEval-2007 benchmarks; while the bilingual WSD task consists of 7 highly ambiguous verbs in translating from English to Portuguese. The results are encouraging: the ILP-assisted models show substantial improvements over those that simply use shallow features. In addition, incremental feature-set construction appears to identify smaller and better sets of features. Taken together, the results suggest that the use of ILP with diverse sources of background knowledge provide a way for making substantial progress in the field of WSD.
Resumo:
Several real problems involve the classification of data into categories or classes. Given a data set containing data whose classes are known, Machine Learning algorithms can be employed for the induction of a classifier able to predict the class of new data from the same domain, performing the desired discrimination. Some learning techniques are originally conceived for the solution of problems with only two classes, also named binary classification problems. However, many problems require the discrimination of examples into more than two categories or classes. This paper presents a survey on the main strategies for the generalization of binary classifiers to problems with more than two classes, known as multiclass classification problems. The focus is on strategies that decompose the original multiclass problem into multiple binary subtasks, whose outputs are combined to obtain the final prediction.
Resumo:
The design of binary morphological operators that are translation-invariant and locally defined by a finite neighborhood window corresponds to the problem of designing Boolean functions. As in any supervised classification problem, morphological operators designed from a training sample also suffer from overfitting. Large neighborhood tends to lead to performance degradation of the designed operator. This work proposes a multilevel design approach to deal with the issue of designing large neighborhood-based operators. The main idea is inspired by stacked generalization (a multilevel classifier design approach) and consists of, at each training level, combining the outcomes of the previous level operators. The final operator is a multilevel operator that ultimately depends on a larger neighborhood than of the individual operators that have been combined. Experimental results show that two-level operators obtained by combining operators designed on subwindows of a large window consistently outperform the single-level operators designed on the full window. They also show that iterating two-level operators is an effective multilevel approach to obtain better results.
Resumo:
Polynorbonerne with high molecular weight was obtained via ring opening metathesis polymerization using catalysts derived from [RuCl(2)(PPh(2)Bz)(2) L] (1 for L = PPh(2) Bz; 2 for L = piperidine) type of complexes when in the presence of ethyl diazoacetate in CHCl(3). The polymer precipitated within a few minutes at 50 degrees C when using 1 with ca. 50% yield ([NBE]/[Ru] = 5000). Regarding 2, for either 30 min at 25 C or 5 min at 50 degrees C, more than 90% of yields are obtained; and at 50 C for 30 min a quantitative yield is obtained. The yield and PDI values are sensitive to the [NBE]/[Ru] ratio. The reaction of 1 with either isonicotinamide or nicotinamide produces six-coordinated complexes of [RuCl(2)(PPh(2)Bz)(2)(L)(2)] type, which are almost inactive and produce only small amounts of polymers at 50 C for 30 min. Thus, we Concluded that the novel complexes show very distinct reactivities for ROMP of NBE. This has been rationalized on account of a combination of synergistic effects of the phosphine-amine ancillary ligands. (C) 2009 Elsevier B.V. All rights reserved.