81,607 research outputs found
Tropical Support Vector Machine and its Applications to Phylogenomics
Most data in genome-wide phylogenetic analysis (phylogenomics) is essentially
multidimensional, posing a major challenge to human comprehension and
computational analysis. Also, we can not directly apply statistical learning
models in data science to a set of phylogenetic trees since the space of
phylogenetic trees is not Euclidean. In fact, the space of phylogenetic trees
is a tropical Grassmannian in terms of max-plus algebra. Therefore, to classify
multi-locus data sets for phylogenetic analysis, we propose tropical support
vector machines (SVMs). Like classical SVMs, a tropical SVM is a discriminative
classifier defined by the tropical hyperplane which maximizes the minimum
tropical distance from data points to itself in order to separate these data
points into sectors (half-spaces) in the tropical projective torus. Both hard
margin tropical SVMs and soft margin tropical SVMs can be formulated as linear
programming problems. We focus on classifying two categories of data, and we
study a simpler case by assuming the data points from the same category ideally
stay in the same sector of a tropical separating hyperplane. For hard margin
tropical SVMs, we prove the necessary and sufficient conditions for two
categories of data points to be separated, and we show an explicit formula for
the optimal value of the feasible linear programming problem. For soft margin
tropical SVMs, we develop novel methods to compute an optimal tropical
separating hyperplane. Computational experiments show our methods work well. We
end this paper with open problems.Comment: 27 pages, 6 figures, 2 table
Economics of organic fruit production (OF0151)
This is the final report of Defra project OF0151
Despite a very strong consumer demand for organic fruit, it is the least developed sector of the UK organic industry. The main constraint to growth in supply is the lack of organic fruit growers, especially those on a large enough scale to supply the wholesale, multiple and processing markets. The UK Organic Fruit Focus Group was set up in 1997 as a producer initiative to develop the market and production of UK organic fruit. At the first meeting of the group it was concluded that a) the absence of written technical information on how to grow organic fruit b) the lack of experienced advisors c) the lack of fruit and d) a lack of information on the economics of organic fruit were major barriers to grower confidence and hence expanding production.
In June 1998 HDRA began a one year study into the Economics of Organic Fruit Production. The study aims to provide information on:
• the size of the organic fruit market and potential for future growth
• returns and costs of growing organic top and soft fruit
Information for this study has been obtained through contact and visits to marketing organisations, fruit processors and growers. For information on the market major buyers of organic fruit have been contacted to ascertain quantities bought and market trends. In consultation with the ADAS Fruit Team and the Welsh Institute of Rural Studies, data collection forms were devised to enable full costing techniques (all costs allocated to different cost centres) to arrive at net margins and costs of producing organic fruit per hectare (acre), and per kg (lb). In determining the financial returns, average yields over a number of years (5-10) have been used rather than those related to a specific year and where necessary costs were related to those yields.
Presently there are a very small number of specialised organic fruit growers, therefore the sample was small: dessert apples (5), culinary apples (3) pear growers (3), strawberry growers (5). It was not possible to find any commercial data from growers of other organic fruit. Case study data from these growers of apples, pears and strawberries were used to provide ‘best possible estimates’ for the physical and financial performance of these organic fruit enterprises.
The general conclusions are that despite low (lower than conventional) and sometimes variable yields most organic fruit growers are currently able to generate economic returns. Profitability is related to current high prices (premiums of 60 100% over conventional) for fruit and ability to sell the whole crop to various outlets. Although individual costs differ the overall costs of production are similar between conventional and organic fruit. The profitability of organic fruit appears to be similar or greater than average conventional production. Break even budgets indicate that even if prices fell by approximately 20% then organic fruit production could still be profitable. Price premiums of approximately 40% are still required to enable organic fruit production to be profitable at current yields.
Current price premiums offer potential economically profitable returns; however, conventional growers are reluctant to convert. To give growers confidence to take up the challenge of organic fruit production they need encouragement from government and industry in terms of continued aid to assist conversion, more money for research to improve the quantity and quality of economic data available, to improve production techniques, and finally, money to disseminate this information to growers. This report suggests that continued economic monitoring of converting and existing organic fruit farms should be undertaken. Fruit buyers should also encourage UK growers by offering them market incentives. Unless the UK organic fruit growers receive this encouragement, the majority of organic fruit may continue to be imported
The Singing Insects of Michigan
Excerpt: The so-called singing insects are all those that make loud, rhythmical noises. They include members of three groups of Orthoptera (Gryllidae, Tettigoniidae, and Acridoidea) and one family of Homoptera (Cicadidae). There are about 300 noisy species in these four groups in eastern North America, perhaps a thousand in all of North America, and 25-30 thousand in the entire world. Only about 1000 of the world species have been studied in any detail, mostly in North America, Europe, Japan, and Australia
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A decision model for natural oil buying policy under uncertainty
A manufacturer, in a fast moving consumer goods industry, buys Natural oils from a number of oil suppliers world-wide. The prices of these oils are the major raw material cost in producing the consumer goods, which are also sold world-wide. The volatility in the international prices of the Natural oils has signi¯cant impact on the planning and budgets decisions. Since the oils are bought and the ¯nished products are sold in markets throughout the world, the manufacturer is exposed to a variety of market uncertainties and the resulting risks. These uncertainties are the raw material prices, the demand and the therefore the selling prices for the finished goods- all of which influence the profitability of the manufacturing firm. The risks can be minimised by entering into futures contract of appropriate duration, that is, by following a schedule of "forward"' purchase of oil (with specific series of future delivery dates) with the oil suppliers. We formulate this problem as a two-stage Stochastic Program (SP) using the futures and the spot prices for the Natural oil. This SP model gives robust decisions that hedge against the uncertainties in the Natural oil prices and the demand for the finished products. The uncertainty in the oil prices and the demand are
modelled through a scenario generator. We have constructed a decision support system (DSS) that integrates the SP model, the scenario generator and the solution algorithm. This DSS also provides the decision maker a profile of the risk and return exposures for different policies
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