971 resultados para Reserve Selection Algorithms


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The augmented reality (AR) technology has applications in many fields as diverse as aeronautics, tourism, medicine, and education. In this review are summarized the current status of AR and it is proposed a new application of it in weed science. The basic algorithmic elements for AR implementation are already available to develop applications in the area of weed economic thresholds. These include algorithms for image recognition to identify and quantify weeds by species and software for herbicide selection based on weed density. Likewise, all hardware necessary for AR implementation in weed science are available at an affordable price for the user. Thus, the authors propose weed science can take a leading role integrating AR systems into weed economic thresholds software, thus, providing better opportunities for science and computer-based weed control decisions.

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This study aimed to assess the degree of similarity presented by thematic maps generated by different sampling grids of weed plants in a commercial agricultural area of 7.95 hectares. Monocotyledons and dicotyledons were counted on the 2012/2013 and 2013/2014 harvests, before soybean planting, in the fallow period after wheat harvest, in both years. A regular grid of 10 x 10 m was produced to sample the invasive plants, used as reference, and the counting was done in 1 m² of each sample point, totaling 795 samples in each year, compared to regular grids of 30 and 50 m, generated from the data exclusion of the standard grid. Twenty-two composite soil samples were taken at a depth of 0-20 cm to correlate soil properties with weeds occurrence. For the generation of the thematic maps, the Inverse Distance Weighting (IDW) for interpolation was used; when comparing the maps generated from each grid with the reference map, the kappa coefficient was used to assess the loss of quality of the maps as the number of sample points was reduced. It was observed that the map quality loss was lower in 2013 compared to 2012 when the sampling density of the points was reduced. The 30 x 30 m grids have satisfactorily described the infestation data of the dicotyledons and the 50 x 50 m grids have adequately described the monocotyledon weeds infestation, compared to the standard 10 x 10 m grids.

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ABSTRACT The increase in the area planted with Crotalaria spectabilishas occurred by several factors, highlighting the potential to reduce the nematodes, nitrogen fixation and the high production of biomass. By becoming a species sown as a crop, it is necessary to control the weeds that coexist with showy crotalaria. This change in the use of this crop creates the possibility of this specie becoming a weed. The aim of this study was to assess the potential use of herbicides applied in preemergence and postemergence of C.spectabilisfor different purposes (control of volunteer and selectivity plants). Three experiments were installed in a greenhouse (two with herbicides applied in preemergence - in soils with distinct textural categories; and one experiment with herbicides applied in postemergence). The results of the experiments with herbicides applied in preemergence showed that: amicarbazone, atrazine, diuron, metribuzin, prometryn, fomesafen and sulfentrazone showed effectiveness for control of C.spectabilis in clayey soil. Besides these, flumioxazin and isoxaflutole also showed potential to be used in the control of showy crotalaria in soils with loam texture. In relation to the postemergence herbicides, atrazine, diuron, prometryn, flumioxazin, fomesafen, lactofen, saflufenacil, amonio-glufosinate and glyphosate can be used aiming the chemical control of C.spectabilis. Herbicides chlorimuron-ethyl, diclosulan, imazethapyr, pyrithiobac-sodium, trifloxysulfuron-sodium, clomazone, pendimethalin, S-metolachlor and trifluralin applied in preemergence, and imazethapyr, pyrithiobac-sodium, flumiclorac, bentazon and clethodim applied in postemergence caused low levels of injury to C.spectabilis plants, making necessary the development of new searches to ensure the selectivity of these products.

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The spores used were collected from a population of trees of Cyathea delgadii Sternb. growing in a gallery forest at the Reserva Biológica e Estação Experimental de Moji Guaçu, São Paulo state, Brazil (22°18’S and 47°11’W). The germination of spores of Cyathea delgadii decreases with time when kept in closed bottles under storage at 4°C in darkness. Germination is still very high after storage for one year. Spores stored for three years do not germinate. The results also show a decrease in soluble proteins and an increase in starch after several months storage.

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Service provider selection has been said to be a critical factor in the formation of supply chains. Through successful selection companies can attain competitive advantage, cost savings and more flexible operations. Service provider management is the next crucial step in outsourcing process after the selection has been made. Without proper management companies cannot be sure about the level of service they have bought and they may suffer from service provider's opportunistic behavior. In worst case scenario the buyer company may end up in locked-in situation in which it is totally dependent of the service provider. This thesis studies how the case company conducts its carrier selection process along with the criteria related to it. A model for the final selection is also provided. In addition, case company's carrier management procedures are reflected against recommendations from previous researches. The research was conducted as a qualitative case study on the principal company, Neste Oil Retail. A literature review was made on outsourcing, service provider selection and service provider management. On the basis of the literature review, this thesis ended up recommending Analytic hierarchy process as the preferred model for the carrier selection. Furthermore, Agency theory was seen to be a functional framework for carrier management in this study. Empirical part of this thesis was conducted in the case company by interviewing the key persons in the selection process, making observations and going through documentations related to the subject. According to the results from the study, both carrier selection process as well as carrier management were closely in line with suggestions from literature review. Analytic hierarchy process results revealed that the case company considers service quality as the most important criteria with financial situation and price of service following behind with almost identical weights with each other. Equipment and personnel was seen as the least important selection criterion. Regarding carrier management, the study resulted in the conclusion that the company should consider engaging more in carrier development and working towards beneficial and effective relationships. Otherwise, no major changes were recommended for the case company processes.

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Lecythidaceae is the family of the Brazil nut, and comprises about 300 species belonging to 17 genera with pantropical distributions. One hundred and twenty-two species belonging to nine genera are distributed throughout Brazil, demonstrating its greatest diversity in the Amazon rainforest where Lecythidaceae is also one of the most abundant families. It is usually difficult to collect fertile material from these trees because of their canopy heights, and species determinations using sterile material can be complex because of their morphological similarities. There have been relatively few studies of this family even though it is one of the most important groups in the Amazon region, and a detailed taxonomic treatment of the species of Lecythidaceae in the Tupé Sustainable Development Reserve was therefore the goal of the present work. Ten species were found, Allantoma lineata (Mart. ex O.Berg) Miers, Bertholletia excelsa Bonpl., Couratari tenuicarpa A.C.Sm., Lecythis poiteaui O. Berg; and six species of Eschweilera, the richest genus. The descriptions and identification keys of the species used 56 characters. The main reproductive characters useful for distinguishing the species were the pubescence of the inflorescence rachis, pedicel length and trichomes presence, floral symmetry, hood type, filament shape, stigma shape, fruit shape and size, and aril type. The most diagnostic vegetative characters were the type and color of the outer bark, inner bark color, midrib prominence, and petiole shape and pubescence.

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Seven selection indexes based on the phenotypic value of the individual and the mean performance of its family were assessed for their application in breeding of self-pollinated plants. There is no clear superiority from one index to another although some show one or more negative aspects, such as favoring the selection of a top performing plant from an inferior family in detriment of an excellent plant from a superior family

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Data of corn ear production (kg/ha) of 196 half-sib progenies (HSP) of the maize population CMS-39 obtained from experiments carried out in four environments were used to adapt and assess the BLP method (best linear predictor) in comparison with to the selection among and within half-sib progenies (SAWHSP). The 196 HSP of the CMS-39 population developed by the National Center for Maize and Sorghum Research (CNPMS-EMBRAPA) were related through their pedigree with the recombined progenies of the previous selection cycle. The two methodologies used for the selection of the twenty best half-sib progenies, BLP and SAWHSP, led to similar expected genetic gains. There was a tendency in the BLP methodology to select a greater number of related progenies because of the previous generation (pedigree) than the other method. This implies that greater care with the effective size of the population must be taken with this method. The SAWHSP methodology was efficient in isolating the additive genetic variance component from the phenotypic component. The pedigree system, although unnecessary for the routine use of the SAWHSP methodology, allowed the prediction of an increase in the inbreeding of the population in the long term SAWHSP selection when recombination is simultaneous to creation of new progenies.

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We describe here the isolation and characterization of a major albumin from the seeds of Opuntia ficus-indica (Cactaceae). This protein has a molecular mass of 6.5 kDa and was isolated by a combination of gel filtration chromatography and reverse-phase HPLC. The amino acid composition of this protein was determined and it was shown to have similarities with the amino acid composition of several proteins from the 2S albumin storage protein family. The N-terminal amino acid sequence of this protein is Asp-Pro-Tyr-Trp-Glu-Gln-Arg.

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Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

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Demand for the use of energy systems, entailing high efficiency as well as availability to harness renewable energy sources, is a key issue in order to tackling the threat of global warming and saving natural resources. Organic Rankine cycle (ORC) technology has been identified as one of the most promising technologies in recovering low-grade heat sources and in harnessing renewable energy sources that cannot be efficiently utilized by means of more conventional power systems. The ORC is based on the working principle of Rankine process, but an organic working fluid is adopted in the cycle instead of steam. This thesis presents numerical and experimental results of the study on the design of small-scale ORCs. Two main applications were selected for the thesis: waste heat re- covery from small-scale diesel engines concentrating on the utilization of the exhaust gas heat and waste heat recovery in large industrial-scale engine power plants considering the utilization of both the high and low temperature heat sources. The main objective of this work was to identify suitable working fluid candidates and to study the process and turbine design methods that can be applied when power plants based on the use of non-conventional working fluids are considered. The computational work included the use of thermodynamic analysis methods and turbine design methods that were based on the use of highly accurate fluid properties. In addition, the design and loss mechanisms in supersonic ORC turbines were studied by means of computational fluid dynamics. The results indicated that the design of ORC is highly influenced by the selection of the working fluid and cycle operational conditions. The results for the turbine designs in- dicated that the working fluid selection should not be based only on the thermodynamic analysis, but requires also considerations on the turbine design. The turbines tend to be fast rotating, entailing small blade heights at the turbine rotor inlet and highly supersonic flow in the turbine flow passages, especially when power systems with low power outputs are designed. The results indicated that the ORC is a potential solution in utilizing waste heat streams both at high and low temperatures and both in micro and larger scale appli- cations.