1000 resultados para Tree farms


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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.

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A new heuristic for the Steiner Minimal Tree problem is presented here. The method described is based on the detection of particular sets of nodes in networks, the “Hot Spot” sets, which are used to obtain better approximations of the optimal solutions. An algorithm is also proposed which is capable of improving the solutions obtained by classical heuristics, by means of a stirring process of the nodes in solution trees. Classical heuristics and an enumerative method are used CIS comparison terms in the experimental analysis which demonstrates the goodness of the heuristic discussed in this paper.

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A new heuristic for the Steiner minimal tree problem is presented. The method described is based on the detection of particular sets of nodes in networks, the “hot spot” sets, which are used to obtain better approximations of the optimal solutions. An algorithm is also proposed which is capable of improving the solutions obtained by classical heuristics, by means of a stirring process of the nodes in solution trees. Classical heuristics and an enumerative method are used as comparison terms in the experimental analysis which demonstrates the capability of the heuristic discussed

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This article assesses the extent to which sampling variation affects findings about Malmquist productivity change derived using data envelopment analysis (DEA), in the first stage by calculating productivity indices and in the second stage by investigating the farm-specific change in productivity. Confidence intervals for Malmquist indices are constructed using Simar and Wilson's (1999) bootstrapping procedure. The main contribution of this article is to account in the second stage for the information in the second stage provided by the first-stage bootstrap. The DEA SEs of the Malmquist indices given by bootstrapping are employed in an innovative heteroscedastic panel regression, using a maximum likelihood procedure. The application is to a sample of 250 Polish farms over the period 1996 to 2000. The confidence intervals' results suggest that the second half of 1990s for Polish farms was characterized not so much by productivity regress but rather by stagnation. As for the determinants of farm productivity change, we find that the integration of the DEA SEs in the second-stage regression is significant in explaining a proportion of the variance in the error term. Although our heteroscedastic regression results differ with those from the standard OLS, in terms of significance and sign, they are consistent with theory and previous research.

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A Participatory Rural Appraisal (PRA) was conducted in dairy farms of the North West Province of Cameroon. The aim of the PRA was to have a better understanding of the prevailing dairy systems, identify problems, and set priorities for research and development that can contribute to improved systems of production. A multidisciplinary team of researchers and extension agents was constituted. It was made up of scientists of the following fields: cattle management, forage science, agro economy, veterinary, dairy technology, nutrition and extension. The research team visited farmers' groups and divided itself into subgroups for farm and village walks during which direct observations were also noted. The extension agent of the locality, key informants, gave additional information overlooked by farmers. Interviews were also carried out with other stakeholders of the dairy sector. The research team met the day following the visit to agree on a common report. Results show that five small scale dairy production systems are found in the region: transhumance, improved extensive, semi intensive, zero grazing and peri-urban. Agriculture is well integrated to dairying. Main constraints include in order of importance: poor marketing opportunities and long distances to market, limited grazing land and poor supplementation strategies, poor reproductive management and poor calving interval, inadequate knowledge in processing, hygiene and milk preservation, and limited health control. In market oriented farms, reproduction and feeding were the most important constraints. Main factors influencing dairy production are: milk collection, fresh milk price, consumer demand, genotype and management. These results suggest that much can be done to improve production by extending improved packages to dairy farmers.

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Demonstration models of the costs of BVD and Johnes in dairy and beef cattle and the costs and benefits of control have been developed. An example applied to BVD in dairy cattle is presented. Downloadable versions of the models, together with supporting material on how to use them are available to veterinarians from a dedicated website.

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Demonstration models of the costs of BVD and Johnes in dairy and beef cattle and the costs and benefits of control have been developed. An example applied to BVD in dairy cattle is presented. Downloadable versions of the models, together with supporting material on how to use them are available to veterinarians from a dedicated website.

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Digital dermatitis is a significant problem in UK dairy herds and the cost to farmers has not yet been fully quantified. Under the current farm health planning initiative there is a need to demonstrate to farmers the costs and benefits of disease control. This paper presents the first attempt to quantify the costs and benefits of digital dermatitis control on UK dairy farms through the use of an interactive model.

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Seed storage behaviour of 5 1 native and 9 introduced tree species in Vietnam was investigated using a brief protocol developed to aid biodiversity conservation in circumstances where little is known about the seeds. Of the 60 species, 34 appeared to show orthodox (Acacia auriculaeformis, Adenanthera pavonina, Afzelia xylocarpa, Bauhinia purpurea, Callistemon lanceolatus, Cananga odorata, Canarium nigrum, Cassia fistula, Cassia javanica, Cassia splendida, Chukrasia tabularis, Dalbergia bariaensis, Dialium cochinchinensis, Diospyros mollis, Diospyros mun, Dracuntomelon duperreanum, Erythrophleum fordii, Khaya senegalensis, Lagerstroemia speciosa, Leucaena leucocephala, Livistona cochinchinensis, Markhamia stipulata, Melaleuca cajuputi, Millettia ichthyotona, Peltophorum pterocarpum, Peltophorum tonkinensis, Pinus khasya, Pinus massoniana, Pinus merkusii, Pterocarpus macrocarpus, Sindora siamensis, Sophora tonkinense, Sterculia foetida, Swietenia macrophylla), 13 recalcitrant (Avicennia alba, Beilschmiedia roxburghiana, Caryota mitis, Dimocarpus sp., Diospyros malabarica, Dipterocarpus chartaceus, Dypsis pinnatifrons, Hopea odorata, Lithocarpus gigantophylla, Machilus odoratissimus, Melanorrhoea laccifera, Melanorrhea usitata, Syzygium cinereum) and 13 intermediate (Anisoptera cochinchinensis, Aphanamixis polystachya, Averrhoa carambola, Carissa carandas, Chrysopylum cainito, Cinnamomum camphora, Citrofortunella microcarpa, Citrus grandis var. grandis, Elaeis guineensis, Hydnocarpus anthelmintica, Madhuca floribunda, Manilkara achras, Mimusops elengi) seed storage behaviour. A double-criteria key to estimate likely seed storage behaviour showed good agreement with the above: the key can reduce the workload of seed storage behaviour identification considerably.