967 resultados para sdecision tree systems
Resumo:
Fault location has been studied deeply for transmission lines due to its importance in power systems. Nowadays the problem of fault location on distribution systems is receiving special attention mainly because of the power quality regulations. In this context, this paper presents an application software developed in Matlabtrade that automatically calculates the location of a fault in a distribution power system, starting from voltages and currents measured at the line terminal and the model of the distribution power system data. The application is based on a N-ary tree structure, which is suitable to be used in this application due to the highly branched and the non- homogeneity nature of the distribution systems, and has been developed for single-phase, two-phase, two-phase-to-ground, and three-phase faults. The implemented application is tested by using fault data in a real electrical distribution power system
Resumo:
One among the most influential and popular data mining methods is the k-Means algorithm for cluster analysis. Techniques for improving the efficiency of k-Means have been largely explored in two main directions. The amount of computation can be significantly reduced by adopting geometrical constraints and an efficient data structure, notably a multidimensional binary search tree (KD-Tree). These techniques allow to reduce the number of distance computations the algorithm performs at each iteration. A second direction is parallel processing, where data and computation loads are distributed over many processing nodes. However, little work has been done to provide a parallel formulation of the efficient sequential techniques based on KD-Trees. Such approaches are expected to have an irregular distribution of computation load and can suffer from load imbalance. This issue has so far limited the adoption of these efficient k-Means variants in parallel computing environments. In this work, we provide a parallel formulation of the KD-Tree based k-Means algorithm for distributed memory systems and address its load balancing issue. Three solutions have been developed and tested. Two approaches are based on a static partitioning of the data set and a third solution incorporates a dynamic load balancing policy.
Resumo:
The low proportion of forested land and continuing degradation of existing forest cover are serious threats to the sustainability of forestry in Pakistan. Farm forestry has been identified as a feasible solution, particularly in the plain areas. Applying the Theory of Planned Behaviour in a survey of 124 farmers in Dera Ismail Khan district of Pakistan's North West Frontier Province showed that farmers' willingness to grow trees on their farms is a function of their attitudes towards the advantages and disadvantages of growing trees, their perception of the opinions of salient referents and factors that encourage and discourage farm level tree planting. Farmers viewed farm forestry as economically beneficial and environmentally friendly. Tree planting was perceived as increasing income, providing wood for fuel and furniture, controlling erosion and pollution and providing shade for humans and animals. Farmers saw hindrance in agricultural operations and the harbouring of insects, pests and diseases as negative impacts of tree planting; however, these were outweighed by their perceptions of positive impacts. Tree growing decisions of farmers were influenced by the opinions of family members, owners/tenants, fellow farmers and village elders. The factors that significantly predicted farm level tree planting were availability of barren land, lack of markets, lack of nurseries and damage caused by animals and humans. Farm forestry programmes are more likely to be successful if they acknowledge and address the factors which underlie farmers' reasons for planting or not planting trees.
Resumo:
Purpose – The purpose of this research is to show that reliability analysis and its implementation will lead to an improved whole life performance of the building systems, and hence their life cycle costs (LCC). Design/methodology/approach – This paper analyses reliability impacts on the whole life cycle of building systems, and reviews the up-to-date approaches adopted in UK construction, based on questionnaires designed to investigate the use of reliability within the industry. Findings – Approaches to reliability design and maintainability design have been introduced from the operating environment level, system structural level and component level, and a scheduled maintenance logic tree is modified based on the model developed by Pride. Different stages of the whole life cycle of building services systems, reliability-associated factors should be considered to ensure the system's whole life performance. It is suggested that data analysis should be applied in reliability design, maintainability design, and maintenance policy development. Originality/value – The paper presents important factors in different stages of the whole life cycle of the systems, and reliability and maintainability design approaches which can be helpful for building services system designers. The survey from the questionnaires provides the designers with understanding of key impacting factors.
Resumo:
A hybridised and Knowledge-based Evolutionary Algorithm (KEA) is applied to the multi-criterion minimum spanning tree problems. Hybridisation is used across its three phases. In the first phase a deterministic single objective optimization algorithm finds the extreme points of the Pareto front. In the second phase a K-best approach finds the first neighbours of the extreme points, which serve as an elitist parent population to an evolutionary algorithm in the third phase. A knowledge-based mutation operator is applied in each generation to reproduce individuals that are at least as good as the unique parent. The advantages of KEA over previous algorithms include its speed (making it applicable to large real-world problems), its scalability to more than two criteria, and its ability to find both the supported and unsupported optimal solutions.
Resumo:
This study was designed to determine the response of in vitro fermentation parameters to incremental levels of polyethylene glycol (PEG) when tanniniferous tree fruits (Dichrostachys cinerea, Acacia erioloba, A. erubiscens, A. nilotica and Piliostigma thonningii) were fermented using the Reading Pressure Technique. The trivalent ytterbium precipitable phenolics content of fruit substrates ranged from 175 g/kg DM in A. erubiscens to 607 g/kg DM in A. nilotica, while the soluble condensed tannin content ranged from 0.09 AU550nm/40mg in A. erioloba to 0.52 AU550nm/40 mg in D. cinerea. The ADF was highest in P. thonningii fruits (402 g/kg DM) and lowest in A. nilotica fruits (165 g/kg DM). Increasing the level of PEG caused an exponential rise to a maximum (asymptotic) for cumulative gas production, rate of gas production and nitrogen degradability in all substrates except P. thonningii fruits. Dry matter degradability for fruits containing higher levels of soluble condensed tannins (D. cinerea and P. thonningii), showed little response to incremental levels of PEG after incubation for 24 h. The minimum levels of PEG required to maximize in vitro fermentation of tree fruits was found to be 200 mg PEG/g DM of sample for all tree species except A. erubiscens fruits, which required 100 mg PEG/g DM sample. The study provides evidence that PEG levels lower than 1 g/g DM sample can be used for in vitro tannin bioassays to reduce the cost of evaluating non-conventional tanniniferous feedstuffs used in developing countries in the tropics and subtopics. The use of in vitro nitrogen degradability in place of the favoured dry matter degradability improved the accuracy of PEG as a diagnostic tool for tannins in in vitro fermentation systems.
Resumo:
CONTEXT. Rattus tanezumi is a serious crop pest within the island of Luzon, Philippines. In intensive flood-irrigated rice field ecosystems of Luzon, female R. tanezumi are known to primarily nest within the tillers of ripening rice fields and along the banks of irrigation canals. The nesting habits of R. tanezumi in complex rice–coconut cropping systems are unknown. AIMS. To identify the natal nest locations of R. tanezumi females in rice–coconut systems of the Sierra Madre Biodiversity Corridor (SMBC), Luzon, during the main breeding season to develop a management strategy that specifically targets their nesting habitat. METHODS. When rice was at the booting to ripening stage, cage-traps were placed in rice fields adjacent to coconut habitat. Thirty breeding adult R. tanezumi females were fitted with radio-collars and successfully tracked to their nest sites. KEY RESULTS. Most R. tanezumi nests (66.7%) were located in coconut groves, five nests (16.7%) were located in rice fields and five nests (16.7%) were located on the rice field edge. All nests were located above ground level and seven nests were located in coconut tree crowns. The median distance of nest sites to the nearest rice field was 22.5m. Most nest site locations had good cover of ground vegetation and understorey vegetation, but low canopy cover. Only one nest location had an understorey vegetation height of less than 20 cm. CONCLUSIONS. In the coastal lowland rice–coconut cropping systems of the SMBC, female R. tanezumi showed a preference for nesting in adjacent coconut groves. This is contrary to previous studies in intensive flood-irrigated rice ecosystems of Luzon, where the species nests mainly in the banks of irrigation canals. It is important to understand rodent breeding ecology in a specific ecosystem before implementing appropriate management strategies. IMPLICATIONS. In lowland rice–coconut cropping systems, coconut groves adjacent to rice fields should be targeted for the 20 management of R. tanezumi nest sites during the main breeding season as part of an integrated ecologically based approach to rodent pest management.
Resumo:
Endospermic legumes are abundant in tropical forests and their establishment is closely related to the mobilization of cell-wall storage polysaccharides. Endosperm cells also store large numbers of protein bodies that play an important role as a nitrogen reserve in this seed. In this work, a systems approach was adopted to evaluate some of the changes in carbohydrates and hormones during the development of seedlings of the rain forest tree Sesbania virgata during the period of establishment. Seeds imbibed abscisic acid (ABA), glucose and sucrose in an atmosphere of ethylene, and the effects of these compounds on the protein contents, alpha-galactosidase activity and endogenous production of ABA and ethylene by the seeds were observed. The presence of exogenous ABA retarded the degradation of storage protein in the endosperm and decreased alpha-galactosidase activity in the same tissue during galactomannan degradation, suggesting that ABA represses enzyme action. On the other hand, exogenous ethylene increased alpha-galactosidase activity in both the endosperm and testa during galactomannan degradation, suggesting an inducing effect of this hormone on the hydrolytic enzymes. Furthermore, the detection of endogenous ABA and ethylene production during the period of storage mobilization and the changes observed in the production of these endogenous hormones in the presence of glucose and sucrose, suggested a correlation between the signalling pathway of these hormones and the sugars. These findings suggest that ABA, ethylene and sugars play a role in the control of the hydrolytic enzyme activities in seeds of S. virgata, controlling the process of storage degradation. This is thought to ensure a balanced flow of the carbon and nitrogen for seedling development.
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Resumo:
Background: Leptospirosis is an important zoonotic disease associated with poor areas of urban settings of developing countries and early diagnosis and prompt treatment may prevent disease. Although rodents are reportedly considered the main reservoirs of leptospirosis, dogs may develop the disease, may become asymptomatic carriers and may be used as sentinels for disease epidemiology. The use of Geographical Information Systems (GIS) combined with spatial analysis techniques allows the mapping of the disease and the identification and assessment of health risk factors. Besides the use of GIS and spatial analysis, the technique of data mining, decision tree, can provide a great potential to find a pattern in the behavior of the variables that determine the occurrence of leptospirosis. The objective of the present study was to apply Geographical Information Systems and data prospection (decision tree) to evaluate the risk factors for canine leptospirosis in an area of Curitiba, PR.Materials, Methods & Results: The present study was performed on the Vila Pantanal, a urban poor community in the city of Curitiba. A total of 287 dog blood samples were randomly obtained house-by-house in a two-day sampling on January 2010. In addition, a questionnaire was applied to owners at the time of sampling. Geographical coordinates related to each household of tested dog were obtained using a Global Positioning System (GPS) for mapping the spatial distribution of reagent and non-reagent dogs to leptospirosis. For the decision tree, risk factors included results of microagglutination test (MAT) from the serum of dogs, previous disease on the household, contact with rats or other dogs, dog breed, outdoors access, feeding, trash around house or backyard, open sewer proximity and flooding. A total of 189 samples (about 2/3 of overall samples) were randomly selected for the training file and consequent decision rules. The remained 98 samples were used for the testing file. The seroprevalence showed a pattern of spatial distribution that involved all the Pantanal area, without agglomeration of reagent animals. In relation to data mining, from 189 samples used in decision tree, a total of 165 (87.3%) animal samples were correctly classified, generating a Kappa index of 0.413. A total of 154 out of 159 (96.8%) samples were considered non-reagent and were correctly classified and only 5/159 (3.2%) were wrongly identified. on the other hand, only 11 (36.7%) reagent samples were correctly classified, with 19 (63.3%) samples failing diagnosis.Discussion: The spatial distribution that involved all the Pantanal area showed that all the animals in the area are at risk of contamination by Leptospira spp. Although most samples had been classified correctly by the decision tree, a degree of difficulty of separability related to seropositive animals was observed, with only 36.7% of the samples classified correctly. This can occur due to the fact of seronegative animals number is superior to the number of seropositive ones, taking the differences in the pattern of variable behavior. The data mining helped to evaluate the most important risk factors for leptospirosis in an urban poor community of Curitiba. The variables selected by decision tree reflected the important factors about the existence of the disease (default of sewer, presence of rats and rubbish and dogs with free access to street). The analyses showed the multifactorial character of the epidemiology of canine leptospirosis.
Resumo:
Background: The genome-wide identification of both morbid genes, i.e., those genes whose mutations cause hereditary human diseases, and druggable genes, i.e., genes coding for proteins whose modulation by small molecules elicits phenotypic effects, requires experimental approaches that are time-consuming and laborious. Thus, a computational approach which could accurately predict such genes on a genome-wide scale would be invaluable for accelerating the pace of discovery of causal relationships between genes and diseases as well as the determination of druggability of gene products.Results: In this paper we propose a machine learning-based computational approach to predict morbid and druggable genes on a genome-wide scale. For this purpose, we constructed a decision tree-based meta-classifier and trained it on datasets containing, for each morbid and druggable gene, network topological features, tissue expression profile and subcellular localization data as learning attributes. This meta-classifier correctly recovered 65% of known morbid genes with a precision of 66% and correctly recovered 78% of known druggable genes with a precision of 75%. It was than used to assign morbidity and druggability scores to genes not known to be morbid and druggable and we showed a good match between these scores and literature data. Finally, we generated decision trees by training the J48 algorithm on the morbidity and druggability datasets to discover cellular rules for morbidity and druggability and, among the rules, we found that the number of regulating transcription factors and plasma membrane localization are the most important factors to morbidity and druggability, respectively.Conclusions: We were able to demonstrate that network topological features along with tissue expression profile and subcellular localization can reliably predict human morbid and druggable genes on a genome-wide scale. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing morbidity and druggability.
Resumo:
This paper describes the anatomy and morphology of the complex nectary systems of the tropical tree Guarea macrophylla Vahl (Meliaceae) and presents the first record of extrafloral nectaries occurring on reproductive organs (fruits) of a member of the order Sapindales. The extrafloral nectaries of G. macrophylla occur on petioles, petiolules, the abaxial surface of all leaflets, leaf buds, and over the surface of fruits. All extrafloral nectaries are distinctly raised above the surface. Foraging ants collect extrafloral nectar on Guarea trees both day and night. We suggest that the presence of extrafloral nectaries might be a useful taxonomic character for the identification of Guarea species.
Resumo:
Statecharts are an extension to finite state machines with capability for expressing hierarchical decomposition and parallelism. They also have a mechanism called history, to remember the last visit to a superstate. An algorithm to create a reachability tree for statecharts is presented. Also shown is how to use this tree to analyse dynamic properties of statecharts; reachability from any state configuration, usage of transitions, reinitiability, deadlocks, and valid sequence of events. Owing to its powerful notation, building a reachability tree for statecharts presents some difficulties, and we show how these problems were solved in the tree we propose.
Resumo:
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)