999 resultados para tap selection
Resumo:
Adoption of hybrids and improved varieties has remained low in the smallholder farming sector of South Africa, despite maize being the staple food crop for the majority of households. The objective of this study was to establish preferred maize characteristics by farmers which can be used as selection criteria by maize breeders in crop improvement. Data were collected from three villages of a selected smallholder farming area in South Africa using a survey covering 300 households and participatory rural appraisal methodology. Results indicated a limited selection of maize varieties grown by farmers in the area compared to other communities in Africa. More than 97% of the farmers grew a local landrace called Natal-8-row or IsiZulu. Hybrids and improved open pollinated varieties were planted by less than 40% of the farmers. The Natal-8-row landrace had characteristics similar to landraces from eastern and southern Africa and closely resembled Hickory King, a landrace still popular in Southern Africa. The local landrace was preferred for its taste, recycled seed, tolerance to abiotic stresses and yield stability. Preferred characteristics of maize varieties were high yield and prolificacy, disease resistance, early maturity, white grain colour, and drying and shelling qualities. Farmers were willing to grow hybrids if the cost of seed and other inputs were affordable and their preferences were considered. Our results show that breeding opportunities exist for improving the farmers’ local varieties and maize breeders can take advantage of these preferred traits and incorporate them into existing high yielding varieties.
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A key problem in object recognition is selection, namely, the problem of identifying regions in an image within which to start the recognition process, ideally by isolating regions that are likely to come from a single object. Such a selection mechanism has been found to be crucial in reducing the combinatorial search involved in the matching stage of object recognition. Even though selection is of help in recognition, it has largely remained unsolved because of the difficulty in isolating regions belonging to objects under complex imaging conditions involving occlusions, changing illumination, and object appearances. This thesis presents a novel approach to the selection problem by proposing a computational model of visual attentional selection as a paradigm for selection in recognition. In particular, it proposes two modes of attentional selection, namely, attracted and pay attention modes as being appropriate for data and model-driven selection in recognition. An implementation of this model has led to new ways of extracting color, texture and line group information in images, and their subsequent use in isolating areas of the scene likely to contain the model object. Among the specific results in this thesis are: a method of specifying color by perceptual color categories for fast color region segmentation and color-based localization of objects, and a result showing that the recognition of texture patterns on model objects is possible under changes in orientation and occlusions without detailed segmentation. The thesis also presents an evaluation of the proposed model by integrating with a 3D from 2D object recognition system and recording the improvement in performance. These results indicate that attentional selection can significantly overcome the computational bottleneck in object recognition, both due to a reduction in the number of features, and due to a reduction in the number of matches during recognition using the information derived during selection. Finally, these studies have revealed a surprising use of selection, namely, in the partial solution of the pose of a 3D object.
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A difficulty in the design of automated text summarization algorithms is in the objective evaluation. Viewing summarization as a tradeoff between length and information content, we introduce a technique based on a hierarchy of classifiers to rank, through model selection, different summarization methods. This summary evaluation technique allows for broader comparison of summarization methods than the traditional techniques of summary evaluation. We present an empirical study of two simple, albeit widely used, summarization methods that shows the different usages of this automated task-based evaluation system and confirms the results obtained with human-based evaluation methods over smaller corpora.
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We present a new method to select features for a face detection system using Support Vector Machines (SVMs). In the first step we reduce the dimensionality of the input space by projecting the data into a subset of eigenvectors. The dimension of the subset is determined by a classification criterion based on minimizing a bound on the expected error probability of an SVM. In the second step we select features from the SVM feature space by removing those that have low contributions to the decision function of the SVM.
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A regulator imposing “sales restrictions” on firms competing in oligopolistic markets may enhance quality provision by the firms. Moreover, for most restrictions levels, the impact on quality selection is invariant to the mode of competition
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A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported
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In this paper a novel rank estimation technique for trajectories motion segmentation within the Local Subspace Affinity (LSA) framework is presented. This technique, called Enhanced Model Selection (EMS), is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built by LSA. The results on synthetic and real data show that without any a priori knowledge, EMS automatically provides an accurate and robust rank estimation, improving the accuracy of the final motion segmentation
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This paper describes the basis of citation auctions as a new approach to selecting scientific papers for publication. Our main idea is to use an auction for selecting papers for publication through - differently from the state of the art - bids that consist of the number of citations that a scientist expects to receive if the paper is published. Hence, a citation auction is the selection process itself, and no reviewers are involved. The benefits of the proposed approach are two-fold. First, the cost of refereeing will be either totally eliminated or significantly reduced, because the process of citation auction does not need prior understanding of the paper's content to judge the quality of its contribution. Additionally, the method will not prejudge the content of the paper, so it will increase the openness of publications to new ideas. Second, scientists will be much more committed to the quality of their papers, paying close attention to distributing and explaining their papers in detail to maximize the number of citations that the paper receives. Sample analyses of the number of citations collected in papers published in years 1999-2004 for one journal, and in years 2003-2005 for a series of conferences (in a totally different discipline), via Google scholar, are provided. Finally, a simple simulation of an auction is given to outline the behaviour of the citation auction approach
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Selection of UAS student presentations from June 2009
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A completely effective vaccine for malaria (one of the major infectious diseases worldwide) is not yet available; different membrane proteins involved in parasite-host interactions have been proposed as candidates for designing it. It has been found that proteins encoded by the merozoite surface protein (msp)-7 multigene family are antibody targets in natural infection; the nucleotide diversity of three Pvmsp-7 genes was thus analyzed in a Colombian parasite population. By contrast with P. falciparum msp-7 loci and ancestral P. vivax msp-7 genes, specie-specific duplicates of the latter specie display high genetic variability, generated by single nucleotide polymorphisms, repeat regions, and recombination. At least three major allele types are present in Pvmsp-7C, Pvmsp-7H and Pvmsp-7I and positive selection seems to be operating on the central region of these msp-7 genes. Although this region has high genetic polymorphism, the C-terminus (Pfam domain ID: PF12948) is conserved and could be an important candidate when designing a subunit-based antimalarial vaccine.
Resumo:
A completely effective vaccine for malaria (one of the major infectious diseases worldwide) is not yet available; different membrane proteins involved in parasite-host interactions have been proposed as candidates for designing it. It has been found that proteins encoded by the merozoite surface protein (msp)-7 multigene family are antibody targets in natural infection; the nucleotide diversity of three Pvmsp-7 genes was thus analyzed in a Colombian parasite population. By contrast with P. falciparum msp-7 loci and ancestral P. vivax msp-7 genes, specie-specific duplicates of the latter specie display high genetic variability, generated by single nucleotide polymorphisms, repeat regions, and recombination. At least three major allele types are present in Pvmsp-7C, Pvmsp-7H and Pvmsp-7I and positive selection seems to be operating on the central region of these msp-7 genes. Although this region has high genetic polymorphism, the C-terminus (Pfam domain ID: PF12948) is conserved and could be an important candidate when designing a subunit-based antimalarial vaccine.
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Las regulaciones como primaje comunitario, paquetes estandarizados y afiliación abierta, orientadas a reducir el impacto de las fallas en los mercados de seguros, tienen un efecto limitado puesto que abren espacio a la selección sesgada. A partir de 1993, el sistema de seguridad social en salud en Colombia fue reformado hacia un enfoque de mercado con la expectativa de mejorar el desempeño de los monopolios preexistentes exponiéndolos a la competencia de nuevos entrantes. La hipótesis que se maneja en el trabajo es que las fallas de mercado pueden llevar a selección sesgada favoreciendo a los nuevos entrantes. Se analizaron dos encuestas de hogares utilizando el estado de salud auto reportado y la presencia de enfermedad crónica como indicadores prospectivos del riesgo de los afiliados. Se encuentra que hay selección sesgada, llevando a selección adversa entre los aseguradores preexistentes, y a selección favorable entre los nuevos entrantes. Este patrón se observa en 1997 y se incrementa en el 2003. Aunque las entidades preexistentes son entidades públicas, y su tamaño disminuyó sustancialmente entre estos años, se analizan sus implicaciones fiscales en términos de financiación adicional por parte del gobierno.
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El fuego bacteriano, causado por Erwinia amylovora, es una enfermedad muy importante a nivel comercial y económico porque afecta a plantas de la familia de las rosáceas y es especialmente agresiva en manzano (Pyrus malus) y peral (Pyrus communis), así como en plantas ornamentales (Crataegus, Cotoneaster o Pyracantha). Esta enfermedad está distribuida por todo el mundo en zonas climáticas templadas de Amércia del Norte, Nueva Zelanda, Japón, Israel, Turquí y Europa. En España, el fuego bacteriano fue detectado por primera vez en 1995 en el norte del País (Euskadi) y más tarde en nuevos focos aparecidos en otras áreas. La enfermedad puede ser controlada comercialmente mediante la aplicación de pesticidas quimicos (derivados de cobre, antibioticos). Sin embargo, muchos de los productos químicos presentan baja actividad o causan fitotoxicidad, y la estreptomicina, el producto más eficaz, esta prohibido en muchos países, incluyendo España. Por tanto, en ausencia de apropiados agentes químicos, el control biológico se contempla como una buena alternativa. En el presente trabajo, un agente de control biológico, Pseudomonas fluorescens EPS62e, ha sido seleccionada de entre 600 aislados de las especies P. fluorescens y Pantoea agglomerans obtenidos de flores, frutos y hojas de plantas de la familia de las rosáceas durante una prospección llevada a cabo en varias áreas geográficas de España. La cepa ha sido seleccionada por su capacidad de suprimir la infecciones producidas por E. amylovora frutos inmaduros, flores y brotes de peral en condiciones de ambiente controlado, presentando unos niveles de control similares a los obtenidos mediante el control químico usando derivados de cobre o antibióticos. La cepa además ha mostrado la capacidad de colonizar y sobrevivir en flores y heridas producidas en frutos inmaduros en condiciones de ambiento controlado pero también en flores en condiciones de campo. La exclusión de E. amylovora medinate la colonización de la superficie, el consumo de nutrientes, y la interacción entre las células del patógeno y del agente de biocontrol es la principal causa de la inhibición del fuego bacteriano por la cepa EPS62e. Estas características constituyen aspectos interesantes para un desarrollo efectivo de la cepa EPS62e como un agente de biocontrol del fuego bacteriano en condiciones comerciales.
Resumo:
El treball desenvolupat en aquesta tesi presenta un profund estudi i proveïx solucions innovadores en el camp dels sistemes recomanadors. Els mètodes que usen aquests sistemes per a realitzar les recomanacions, mètodes com el Filtrat Basat en Continguts (FBC), el Filtrat Col·laboratiu (FC) i el Filtrat Basat en Coneixement (FBC), requereixen informació dels usuaris per a predir les preferències per certs productes. Aquesta informació pot ser demogràfica (Gènere, edat, adreça, etc), o avaluacions donades sobre algun producte que van comprar en el passat o informació sobre els seus interessos. Existeixen dues formes d'obtenir aquesta informació: els usuaris ofereixen explícitament aquesta informació o el sistema pot adquirir la informació implícita disponible en les transaccions o historial de recerca dels usuaris. Per exemple, el sistema recomanador de pel·lícules MovieLens (http://movielens.umn.edu/login) demana als usuaris que avaluïn almenys 15 pel·lícules dintre d'una escala de * a * * * * * (horrible, ...., ha de ser vista). El sistema genera recomanacions sobre la base d'aquestes avaluacions. Quan els usuaris no estan registrat en el sistema i aquest no té informació d'ells, alguns sistemes realitzen les recomanacions tenint en compte l'historial de navegació. Amazon.com (http://www.amazon.com) realitza les recomanacions tenint en compte les recerques que un usuari a fet o recomana el producte més venut. No obstant això, aquests sistemes pateixen de certa falta d'informació. Aquest problema és generalment resolt amb l'adquisició d'informació addicional, se li pregunta als usuaris sobre els seus interessos o es cerca aquesta informació en fonts addicionals. La solució proposada en aquesta tesi és buscar aquesta informació en diverses fonts, específicament aquelles que contenen informació implícita sobre les preferències dels usuaris. Aquestes fonts poden ser estructurades com les bases de dades amb informació de compres o poden ser no estructurades com les pàgines web on els usuaris deixen la seva opinió sobre algun producte que van comprar o posseïxen. Nosaltres trobem tres problemes fonamentals per a aconseguir aquest objectiu: 1 . La identificació de fonts amb informació idònia per als sistemes recomanadors. 2 . La definició de criteris que permetin la comparança i selecció de les fonts més idònies. 3 . La recuperació d'informació de fonts no estructurades. En aquest sentit, en la tesi proposada s'ha desenvolupat: 1 . Una metodologia que permet la identificació i selecció de les fonts més idònies. Criteris basats en les característiques de les fonts i una mesura de confiança han estat utilitzats per a resoldre el problema de la identificació i selecció de les fonts. 2 . Un mecanisme per a recuperar la informació no estructurada dels usuaris disponible en la web. Tècniques de Text Mining i ontologies s'han utilitzat per a extreure informació i estructurar-la apropiadament perquè la utilitzin els recomanadors. Les contribucions del treball desenvolupat en aquesta tesi doctoral són: 1. Definició d'un conjunt de característiques per a classificar fonts rellevants per als sistemes recomanadors 2. Desenvolupament d'una mesura de rellevància de les fonts calculada sobre la base de les característiques definides 3. Aplicació d'una mesura de confiança per a obtenir les fonts més fiables. La confiança es definida des de la perspectiva de millora de la recomanació, una font fiable és aquella que permet millorar les recomanacions. 4. Desenvolupament d'un algorisme per a seleccionar, des d'un conjunt de fonts possibles, les més rellevants i fiable utilitzant les mitjanes esmentades en els punts previs. 5. Definició d'una ontologia per a estructurar la informació sobre les preferències dels usuaris que estan disponibles en Internet. 6. Creació d'un procés de mapatge que extreu automàticament informació de les preferències dels usuaris disponibles en la web i posa aquesta informació dintre de l'ontologia. Aquestes contribucions permeten aconseguir dos objectius importants: 1 . Millorament de les recomanacions usant fonts d'informació alternatives que sigui rellevants i fiables. 2 . Obtenir informació implícita dels usuaris disponible en Internet.