56 resultados para 080201 Analysis of Algorithms and Complexity

em University of Queensland eSpace - Australia


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Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

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BACKGROUND. Alterations of important protein pathways, including loss of prostate secretory granules, and disruption of the prostatic secretory pathway have been identified as early events in malignancy. In this study, proteomics was used to map the differences in protein expression between normal and malignant prostate tissues and to identify and analyze differentially expressed proteins in human prostate tissue with particular regard to the proteins lost in malignancy. METHODS. Small quantities of normal and malignant prostate tissue were taken fresh from 34 radical prostatectomy cases. After histological examination, proteins were solubilized from selected tissues and separated using two-dimensional electrophoresis. Using image analysis, the proteome of normal and malignant tissues were mapped and differentially expressed proteins (present in normal and absent in malignant tissue) were identified and subsequently analyzed using peptide mass finger printing and N-terminal sequencing. Western blotting and immunohistochemistry were performed to examine expression profiles and tissue localization of candidate proteins. RESULTS. Comparison of protein maps of normal and malignant prostate were used to identify 20 proteins which were lost in malignant transformation, including prostate specific antigen (PSA), alpha-l antichymotrypsin (ACT), haptoglobin, and lactoylglutathione lyase. Three of the 20 had not previously been reported in human prostate tissue (Ubiquitin-like NEDD8, calponin, and a follistatin-related protein). Western blotting confirmed differences in the expression profiles of NEDD8 and calponin, and immunohistochemistry demonstrated differences in the cellular localization of these two proteins in normal and malignant prostate glands. CONCLUSIONS. The expression of NEDD8, calponin, and the follistatin-related protein in normal prostate tissues is a novel finding and the role of these important functional proteins in normal prostate and their loss or reduced expression in prostate malignancy warrants further investigations. (C) 2002 Wiley-Liss, Inc.

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Background, Rural experience for dental students can provide valuable clinical education, change attitudes to rural practice, and make a valuable contribution to clinical service provision. The aim of this paper is to assess the costs and benefits of service delivery by students through rural training programmes Methods: Groups of two students worked in the public dental clinics in adjacent rural centres where there had been long-term difficulties in recruiting staff. The costs and benefits of the programme were assessed by the impact on waiting lists, the total cost per patient of, a course of care and by the marginal cost of adding service provision by students to existing arrangements. Results: The total costs of emergency and complete treatment provided by students were greater than the costs of treatment provided by public-sector dentists but less than the costs of private providers treating public patients. However, the value of services were greater when care was provided by students or private providers and the marginal cost of students providing services was 50-70 per cent of the cost of care provided by public dentists. Conclusion: This assessment suggests that the service benefits achieved compliment the primary objective of influencing the attitude of students to rural practice.

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Reports on results of a survey, completed in 2000, of wives in three villages in the Phulbani district, Orissa, India. These villages are dominated by the Kondh scheduled tribe but some also contain members of the scheduled caste, called Dombs in Orissa. The article reports on the total responses and comparative responses of these groups to a structured questionnaire. The article provides background information for the villages surveyed, and reports information in relation to wives and their families about property rights, assets and incomes, economic conditions and survival strategies, aspects of credit, production and marketing, social dynamics and eduction. In addition, children’s affairs, including the treatment and entitlements of female and male children, are considered as well as additional aspects of the socioeconomic status of wives.

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Objective: To determine the presentation rates for paediatric poisoning by ingestion and the determinants of hospital admission. Methodology: Cross-sectional survey using an injury surveillance database from emergency departments in South Brisbane, Mackay and Mt Isa, Queensland, from January 1998 to December 1999. There were 1516 children aged 0-14 years who presented following ingestional poisoning. Results: The presentation rates for poisoning were 690, 40 and 67 per 100 000 population aged 0-4, 5-9 and 10-14 years, respectively. The admission rates to hospital for poisoning were 144, 14 and 22 per 100 000 population aged 0-4, 5-9 and 10-14 years, respectively. Although presentation rates for poisoning were higher in the rural centres the admission rates were disproportionately high for the 0-4 years age group. The agents most frequently ingested were paracetamol, Dimetapp(R), rodenticides and essential oils. Conclusion: There is a need to design and implement interventions aimed at reducing poison exposures and unnecessary hospital admissions in the 0-4 years age group.

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For the improvement of genetic material suitable for on farm use under low-input conditions, participatory and formal plant breeding strategies are frequently presented as competing options. A common frame of reference to phrase mechanisms and purposes related to breeding strategies will facilitate clearer descriptions of similarities and differences between participatory plant breeding and formal plant breeding. In this paper an attempt is made to develop such a common framework by means of a statistically inspired language that acknowledges the importance of both on farm trials and research centre trials as sources of information for on farm genetic improvement. Key concepts are the genetic correlation between environments, and the heterogeneity of phenotypic and genetic variance over environments. Classic selection response theory is taken as the starting point for the comparison of selection trials (on farm and research centre) with respect to the expected genetic improvement in a target environment (low-input farms). The variance-covariance parameters that form the input for selection response comparisons traditionally come from a mixed model fit to multi-environment trial data. In this paper we propose a recently developed class of mixed models, namely multiplicative mixed models, also called factor-analytic models, for modelling genetic variances and covariances (correlations). Mixed multiplicative models allow genetic variances and covariances to be dependent on quantitative descriptors of the environment, and confer a high flexibility in the choice of variance-covariance structure, without requiring the estimation of a prohibitively high number of parameters. As a result detailed considerations regarding selection response comparisons are facilitated. ne statistical machinery involved is illustrated on an example data set consisting of barley trials from the International Center for Agricultural Research in the Dry Areas (ICARDA). Analysis of the example data showed that participatory plant breeding and formal plant breeding are better interpreted as providing complementary rather than competing information.

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The virulence spectrum of 112 isolates of Phytophthora clandestina collected from 56 sites in four subterranean clover-growing states in southern Australia was determined using differential cultivars of subterranean clover. Five races were detected, with race 0 in all states except New South Wales, race 1 in all states, race 2 only in Victoria, race 3 only in New South Wales, and race 4 in Victoria and Western Australia. The level of genotypic diversity among the different P. clandestina populations was investigated using five RAPD primers. Among 30 bands amplified, only two were polymorphic. This enabled identification of four multilocus RAPD genotypes. Three of the four genotypes occurred in all four states. Races 2 and 3 occurred with RAPD genotypes 1 and 2 only whereas races 0 and 1 occurred in all four multilocus RAPD genotypes. These results indicate that the pathogenicity spectrum of P. clandestina can change rapidly.

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Schizophrenia is a common disorder with high heritability and a 10-fold increase in risk to siblings of probands. Replication has been inconsistent for reports of significant genetic linkage. To assess evidence for linkage across studies, rank-based genome scan meta-analysis (GSMA) was applied to data from 20 schizophrenia genome scans. Each marker for each scan was assigned to 1 of 120 30-cM bins, with the bins ranked by linkage scores (1 = most significant) and the ranks averaged across studies (R-avg) and then weighted for sample size (rootN[affected cases]). A permutation test was used to compute the probability of observing, by chance, each bin's average rank (P-AvgRnk) or of observing it for a bin with the same place (first, second, etc.) in the order of average ranks in each permutation (P-ord). The GSMA produced significant genomewide evidence for linkage on chromosome 2q (P-AvgRnk