959 resultados para Recursive Partitioning and Regression Trees (RPART)


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1. Many species of delphinids co-occur in space and time. However, little is known of their ecological interactions and the underlying mechanisms that mediate their coexistence. 2. Snubfin Orcaella heinsohni, and Indo-Pacific humpback dolphins Sousa chinensis, live in sympatry throughout most of their range in Australian waters. I conducted boat-based surveys in Cleveland Bay, north-east Queensland, to collect data on the space and habitat use of both species. Using Geographic Information Systems, kernel methods and Euclidean distances I investigated interspecific differences in their space use patterns, behaviour and habitat preferences. 3. Core areas of use (50% kernel range) for both species were located close to river mouths and modified habitat such as dredged channels and breakwaters close to the Port of Townsville. Foraging and travelling activities were the dominant behavioural activities of snubfin and humpback dolphins within and outside their core areas. 4. Their representative ranges (95% kernel range) overlapped considerably, with shared areas showing strong concordance in the space use by both species. Nevertheless, snubfin dolphins preferred slightly shallower (1-2 m) waters than humpback dolphins (2-5 m). Additionally, shallow areas with seagrass ranked high in the habitat preferences of snubfin dolphins, whereas humpback dolphins favoured dredged channels. 5. Slight differences in habitat preferences appear to be one of the principal factors maintaining the coexistence of snubfin and humpback dolphins. I suggest diet partitioning and interspecific aggression as the major forces determining habitat selection in these sympatric species.

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The loss and fragmentation of forest habitats by human land use are recognised as important factors influencing the decline of forest-dependent fauna. Mammal species that are dependent upon forest habitats are particularly sensitive to habitat loss and fragmentation because they have highly specific habitat requirements, and in many cases have limited ability to move through and utilise the land use matrix. We addressed this problem using a case study of the koala (Phascolarctos cinereus) surveyed in a fragmented rural-urban landscape in southeast Queensland, Australia. We applied a logistic modelling and hierarchical partitioning analysis to determine the importance of forest area and its configuration relative to site (local) and patch-level habitat variables. After taking into account spatial auto-correlation and the year of survey, we found koala occurrence increased with the area of all forest habitats, habitat patch size and the proportion of primary Eucalyptus tree species; and decreased with mean nearest neighbour distance between forest patches, the density of forest patches, and the density of sealed roads. The difference between the effect of habitat area and configuration was not as strong as theory predicts, with the configuration of remnant forest becoming increasingly important as the area of forest habitat declines. We conclude that the area of forest, its configuration across the landscape, as well as the land use matrix, are important determinants of koala occurrence, and that habitat configuration should not be overlooked in the conservation of forest-dependent mammals, such as the koala. We highlight the implications of these findings for koala conservation. (c) 2006 Elsevier Ltd. All rights reserved.

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1. Our goal was to quantify short-term phosphorus (P) partitioning and identify the ecosystem components important to P cycling in wetland ecosystems. To do this, we added P radiotracer to oligotrophic, P-limited Everglades marshes. 32PO4 was added to the water column in six 1-m2 enclosed mesocosms located in long-hydroperiod marshes of Shark River Slough, Everglades National Park. Ecosystem components were then repeatedly sampled over 18 days. 2. Water column particulates (>0.45 μm) incorporated radiotracer within the first minute after dosing and stored 95–99% of total water column 32P activity throughout the study. Soluble (<0.45 μm) 32P in the water column, in contrast, was always <5% of the 32P in surface water. Periphyton, both floating and attached to emergent macrophytes, had the highest specific activity of 32P (Bq g−131P) among the different ecosystem components. Fish and aquatic macroinvertebrates also had high affinity for P, whereas emergent macrophytes, soil and flocculent detrital organic matter (floc) had the lowest specific activities of radiotracer. 3. Within the calcareous, floating periphyton mats, 81% of the initial 32P uptake was associated with Ca, but most of this 32P entered and remained within the organic pool (Ca-associated = 14% of total) after 1 day. In the floc layer, 32P rapidly entered the microbial pool and the labile fraction was negligible for most of the study. 4. Budgeting of the radiotracer indicated that 32P moved from particulates in the water column to periphyton and floc and then to the floc and soil over the course of the 18 day incubations. Floc (35% of total) and soil (27%) dominated 32P storage after 18 days, with floating periphyton (12%) and surface water (10%) holding smaller proportions of total ecosystem 32P. 5. To summarise, oligotrophic Everglades marshes exhibited rapid uptake and retention of labile 32P. Components dominated by microbes appear to control short-term P cycling in this oligotrophic ecosystem.

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1. The niche variation hypothesis predicts that among-individual variation in niche use will increase in the presence of intraspecific competition and decrease in the presence of interspecific competition. We sought to determine whether the local isotopic niche breadth of fish inhabiting a wetland was best explained by competition for resources and the niche variation hypothesis, by dispersal of individuals from locations with different prey resources or by a combination of the two. We analysed stable isotopes of carbon and nitrogen as indices of feeding niche and compared metrics of within-site spread to characterise site-level isotopic niche breadth. We then evaluated the explanatory power of competing models of the direct and indirect effects of several environmental variables spanning gradients of disturbance, competition strength and food availability on among-individual variation of the eastern mosquitofish (Gambusia holbrooki). 2. The Dispersal model posits that only the direct effect of disturbance (i.e. changes in water level known to induce fish movement) influences among-individual variation in isotopic niche. The Partitioning model allows for only direct effects of local food availability on among-individual variation. The Combined model allows for both hypotheses by including the direct effects of disturbance and food availability. 3. A linear regression of the Combined model described more variance than models limited to the variables of either the Dispersal or Partitioning models. Of the independent variables considered, the food availability variable (per cent edible periphyton) explained the most variation in isotopic niche breadth, followed closely by the disturbance variable (days since last drying event). 4. Structural equation modelling provided further evidence that the Combined model was best supported by the data, with the Partitioning and the Dispersal models only modestly less informative. Again, the per cent edible periphyton was the variable with the largest direct effect on niche variability, with other food availability variables and the disturbance variable only slightly less important. Indirect effects of heterospecific and conspecific competitor densities were also important, through their effects on prey density. 5. Our results support the Combined hypotheses, although partitioning mechanisms appear to explain the most diet variation among individuals in the eastern mosquitofish. The results also support some predictions of the niche variation hypothesis, although both conspecific and interspecific competition appeared to increase isotopic niche breadth in contrast to predictions that interspecific competition would decrease it. We think this resulted from high diet overlap of co-occurring species, most of which consume similar macroinvertebrates.

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Chemical Stratigraphy, or the study of the variation of chemical elements within sedimentary sequences, has gradually become an experienced tool in the research and correlation of global geologic events. In this paper 87Sr/ 86Sr ratios of the Triassic marine carbonates (Muschelkalk facies) of southeast Iberian Ranges, Iberian Peninsula, are presented and the representative Sr-isotopic curve constructed for the upper Ladinian interval. The studied stratigraphic succession is 102 meters thick, continuous, and well preserved. Previous paleontological data from macro and micro, ammonites, bivalves, foraminifera, conodonts and palynological assemblages, suggest a Fassanian-Longobardian age (Late Ladinian). Although diagenetic minerals are present in small amounts, the elemental data content of bulk carbonate samples, especially Sr contents, show a major variation that probably reflects palaeoenvironmental changes. The 87Sr/86Sr ratios curve shows a rise from 0.707649 near the base of the section to 0.707741 and then declines rapidly to 0.707624, with a final values rise up to 0.70787 in the upper part. The data up to meter 80 in the studied succession is broadly concurrent with 87Sr/86Sr ratios of sequences of similar age and complements these data. Moreover, the sequence stratigraphic framework and its key surfaces, which are difficult to be recognised just based in the facies analysis, are characterised by combining variations of the Ca, Mg, Mn, Sr and CaCO3 contents

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This study used the Sport Interest Inventory (SII) to examine the motivation of fans attending a game in the Australian Football League. This is the first study to use the SII for professional men’s team sport outside the United States. Confirmatory factor analysis showed the model provided a good fit for the data collected in Australia, and regression analysis revealed that team interest, vicarious achievement, excitement and player interest were the significant factors in predicting and explaining the level of attitudinal loyalty of fans toward their favourite team.

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Citrus canker is a disease of citrus and closely related species, caused by the bacterium Xanthomonas citri subsp. citri. This disease, previously exotic to Australia, was detected on a single farm [infested premise-1, (IP1). IP is the terminology used in official biosecurity protocols to describe a locality at which an exotic plant pest has been confirmed or is presumed to exist. IP are numbered sequentially as they are detected] in Emerald, Queensland in July 2004. During the following 10 months the disease was subsequently detected on two other farms (IP2 and IP3) within the same area and studies indicated the disease first occurred on IP1 and spread to IP2 and IP3. The oldest, naturally infected plant tissue observed on any of these farms indicated the disease was present on IP1 for several months before detection and established on IP2 and IP3 during the second quarter (i.e. autumn) 2004. Transect studies on some IP1 blocks showed disease incidences ranged between 52 and 100% (trees infected). This contrasted to very low disease incidence, less than 4% of trees within a block, on IP2 and IP3. The mechanisms proposed for disease spread within blocks include weather-assisted dispersal of the bacterium (e.g. wind-driven rain) and movement of contaminated farm equipment, in particular by pivot irrigator towers via mechanical damage in combination with abundant water. Spread between blocks on IP2 was attributed to movement of contaminated farm equipment and/or people. Epidemiology results suggest: (i) successive surveillance rounds increase the likelihood of disease detection; (ii) surveillance sensitivity is affected by tree size; and (iii) individual destruction zones (for the purpose of eradication) could be determined using disease incidence and severity data rather than a predefined set area.

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Many large coal mining operations in Australia rely heavily on the rail network to transport coal from mines to coal terminals at ports for shipment. Over the last few years, due to the fast growing demand, the coal rail network is becoming one of the worst industrial bottlenecks in Australia. As a result, this provides great incentives for pursuing better optimisation and control strategies for the operation of the whole rail transportation system under network and terminal capacity constraints. This PhD research aims to achieve a significant efficiency improvement in a coal rail network on the basis of the development of standard modelling approaches and generic solution techniques. Generally, the train scheduling problem can be modelled as a Blocking Parallel- Machine Job-Shop Scheduling (BPMJSS) problem. In a BPMJSS model for train scheduling, trains and sections respectively are synonymous with jobs and machines and an operation is regarded as the movement/traversal of a train across a section. To begin, an improved shifting bottleneck procedure algorithm combined with metaheuristics has been developed to efficiently solve the Parallel-Machine Job- Shop Scheduling (PMJSS) problems without the blocking conditions. Due to the lack of buffer space, the real-life train scheduling should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold a train until the next section on the routing becomes available. As a consequence, the problem has been considered as BPMJSS with the blocking conditions. To develop efficient solution techniques for BPMJSS, extensive studies on the nonclassical scheduling problems regarding the various buffer conditions (i.e. blocking, no-wait, limited-buffer, unlimited-buffer and combined-buffer) have been done. In this procedure, an alternative graph as an extension of the classical disjunctive graph is developed and specially designed for the non-classical scheduling problems such as the blocking flow-shop scheduling (BFSS), no-wait flow-shop scheduling (NWFSS), and blocking job-shop scheduling (BJSS) problems. By exploring the blocking characteristics based on the alternative graph, a new algorithm called the topological-sequence algorithm is developed for solving the non-classical scheduling problems. To indicate the preeminence of the proposed algorithm, we compare it with two known algorithms (i.e. Recursive Procedure and Directed Graph) in the literature. Moreover, we define a new type of non-classical scheduling problem, called combined-buffer flow-shop scheduling (CBFSS), which covers four extreme cases: the classical FSS (FSS) with infinite buffer, the blocking FSS (BFSS) with no buffer, the no-wait FSS (NWFSS) and the limited-buffer FSS (LBFSS). After exploring the structural properties of CBFSS, we propose an innovative constructive algorithm named the LK algorithm to construct the feasible CBFSS schedule. Detailed numerical illustrations for the various cases are presented and analysed. By adjusting only the attributes in the data input, the proposed LK algorithm is generic and enables the construction of the feasible schedules for many types of non-classical scheduling problems with different buffer constraints. Inspired by the shifting bottleneck procedure algorithm for PMJSS and characteristic analysis based on the alternative graph for non-classical scheduling problems, a new constructive algorithm called the Feasibility Satisfaction Procedure (FSP) is proposed to obtain the feasible BPMJSS solution. A real-world train scheduling case is used for illustrating and comparing the PMJSS and BPMJSS models. Some real-life applications including considering the train length, upgrading the track sections, accelerating a tardy train and changing the bottleneck sections are discussed. Furthermore, the BPMJSS model is generalised to be a No-Wait Blocking Parallel- Machine Job-Shop Scheduling (NWBPMJSS) problem for scheduling the trains with priorities, in which prioritised trains such as express passenger trains are considered simultaneously with non-prioritised trains such as freight trains. In this case, no-wait conditions, which are more restrictive constraints than blocking constraints, arise when considering the prioritised trains that should traverse continuously without any interruption or any unplanned pauses because of the high cost of waiting during travel. In comparison, non-prioritised trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available. Based on the FSP algorithm, a more generic algorithm called the SE algorithm is developed to solve a class of train scheduling problems in terms of different conditions in train scheduling environments. To construct the feasible train schedule, the proposed SE algorithm consists of many individual modules including the feasibility-satisfaction procedure, time-determination procedure, tune-up procedure and conflict-resolve procedure algorithms. To find a good train schedule, a two-stage hybrid heuristic algorithm called the SE-BIH algorithm is developed by combining the constructive heuristic (i.e. the SE algorithm) and the local-search heuristic (i.e. the Best-Insertion- Heuristic algorithm). To optimise the train schedule, a three-stage algorithm called the SE-BIH-TS algorithm is developed by combining the tabu search (TS) metaheuristic with the SE-BIH algorithm. Finally, a case study is performed for a complex real-world coal rail network under network and terminal capacity constraints. The computational results validate that the proposed methodology would be very promising because it can be applied as a fundamental tool for modelling and solving many real-world scheduling problems.

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Greenhouse gas markets, where invisible gases are traded, must seem like black boxes to most people. Farmers can make money on these markets, such as the Chicago Climate Exchange, by installing methane capture technologies in animal-based systems, no-till farming, establishing grasslands, and planting trees.

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In a seminal data mining article, Leo Breiman [1] argued that to develop effective predictive classification and regression models, we need to move away from the sole dependency on statistical algorithms and embrace a wider toolkit of modeling algorithms that include data mining procedures. Nevertheless, many researchers still rely solely on statistical procedures when undertaking data modeling tasks; the sole reliance on these procedures has lead to the development of irrelevant theory and questionable research conclusions ([1], p.199). We will outline initiatives that the HPC & Research Support group is undertaking to engage researchers with data mining tools and techniques; including a new range of seminars, workshops, and one-on-one consultations covering data mining algorithms, the relationship between data mining and the research cycle, and limitations and problems with these new algorithms. Organisational limitations and restrictions to these initiatives are also discussed.

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This research assesses the potential impact of weekly weather variability on the incidence of cryptosporidiosis disease using time series zero-inflated Poisson (ZIP) and classification and regression tree (CART) models. Data on weather variables, notified cryptosporidiosis cases and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Both time series ZIP and CART models show a clear association between weather variables (maximum temperature, relative humidity, rainfall and wind speed) and cryptosporidiosis disease. The time series CART models indicated that, when weekly maximum temperature exceeded 31°C and relative humidity was less than 63%, the relative risk of cryptosporidiosis rose by 13.64 (expected morbidity: 39.4; 95% confidence interval: 30.9–47.9). These findings may have applications as a decision support tool in planning disease control and risk management programs for cryptosporidiosis disease.

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Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. ----- ----- Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. ----- ----- Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models. ----- ----- Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.

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Road crashes cost world and Australian society a significant proportion of GDP, affecting productivity and causing significant suffering for communities and individuals. This paper presents a case study that generates data mining models that contribute to understanding of road crashes by allowing examination of the role of skid resistance (F60) and other road attributes in road crashes. Predictive data mining algorithms, primarily regression trees, were used to produce road segment crash count models from the road and traffic attributes of crash scenarios. The rules derived from the regression trees provide evidence of the significance of road attributes in contributing to crash, with a focus on the evaluation of skid resistance.

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The purpose of this study is to identify the most common manufacturing practices adopted by the Malaysian manufacturers, company performance factors and relationship between practices and performances. To fulfil the study objectives, 400 manufacturers were surveyed by a standard 400 questionnaire. Three research methodologies such as descriptive analysis, ANOVA and regression analysis have been employed in this study. The analysis revealed that Malaysian manufacturers focus on optimizing three critical performance factors: product development, less customer return rate and on time delivery (OTD). The most important competitive factor was found to be company reputation and design and manufacturing capacity is the least important factor. The findings also proved that manufacturing practices significantly influence company performances

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The larvae of particular Ogmograptis spp. produce distinctive scribbles on some smooth-barked Eucalyptus spp. which are a common feature on many ornamental and forest trees in Australia. However, although they are conspicuous in the environment the systematics and biology of the genus has been poorly studied. This has been addressed through detailed field and laboratory studies of their biology of three species (O. racemosa Horak sp. nov., O. fraxinoides Horak sp. nov., O. scribula Meyrick), in conjunction with a comprehensive taxonomic revision support by a molecular phylogeny utilising the mitochondrial Cox1 and nuclear 18S genes. In brief, eggs are laid in bark depressions and the first instar larvae bore into the bark to the level where the future cork cambium forms (the phellegen). Early instar larvae bore wide, arcing tracks in this layer before forming a tighter zig-zag shaped pattern. The second last instar turns and bores either closely parallel to the initial mine or doubles its width, along the zig-zag shaped mine. The final instar possesses legs and a spinneret (unlike the earlier instars) and feeds exclusively on callus tissue which forms within the zig-zag shaped mine formed by the previous instar, before emerging from the bark to pupate at the base of the tree. The scars of mines them become visible scribble following the shedding of bark. Sequence data confirm the placement of Ogmograptis within the Bucculatricidae, suggest that the larvae responsible for the ‘ghost scribbles’ (unpigmented, raised scars found on smooth-barked eucalypts) are members of the genus Tritymba, and support the morphology-based species groups proposed for Ogmograptis. The formerly monotypic genus Ogmograptis Meyrick is revised and divided into three species groups. Eleven new species are described: Ogmograptis fraxinoides Horak sp. nov., Ogmograptis racemosa Horak sp. nov. and Ogmograptis pilularis Horak sp. nov. forming the scribula group with Ogmograptis scribula Meyrick; Ogmograptis maxdayi Horak sp. nov., Ogmograptis barloworum Horak sp. nov., Ogmograptis paucidentatus Horak sp. nov., Ogmograptis rodens Horak sp. nov., Ogmograptis bignathifer Horak sp. nov. and Ogmograptis inornatus Horak sp. nov. as the maxdayi group; Ogmograptis bipunctatus Horak sp. nov., Ogmograptis pulcher Horak sp. nov., Ogmograptis triradiata (Turner) comb. nov. and Ogmograptis centrospila (Turner) comb. nov. as the triradiata group. Ogmograptis notosema (Meyrick) cannot be assigned to a species group as the holotype has not been located. Three unique synapomorphies, all derived from immatures, redefine the family Bucculatricidae, uniting Ogmograptis, Tritymba Meyrick (both Australian) and Leucoedemia Scoble & Scholtz (African) with Bucculatrix Zeller, which is the sister group of the southern hemisphere genera. The systematic history of Ogmograptis and the Bucculatricidae is discussed.