912 resultados para heuristic plot selection
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Rubber production in the rubber tree [Hevea brasiliensis (Willd. ex Adr. de Juss.) Muell. Arg.] can be expressed differently in different environments. Thus the objective of the present study was to select productive progenies, stable and responsive in time and among locations. Thirty progenies were assessed by early yield tests at three ages and in three locations. A randomized block design was used with three replications and ten plants per plot, in 3 × 3 m spacing. The procedure of the mixed linear Reml/Blup model-restricted maximum likelihood/best non-biased linear prediction was used in the genetic statistical analyses. In all the individual analyses, the values observed for the progeny average heritability (ĥpa 2) were greater than those of the additive effect based on single individuals (ĥa 2) and within plot additive (ĥad 2). In the joint analyses in time, there was genotype × test interaction in the three locations. When 20 % of the best progenies were selected the predicted genetic gains were: Colina GG = 24.63 %, Selvíria GG = 13.63 %, and Votuporanga GG = 25.39 %. Two progenies were among the best in the analyses in the time and between locations. In the joint analysis among locations there was only genotype × location interaction in the first early test. In this test, selecting 20 %, the general predicted genetic gain was GG = 25.10 %. Identifying progenies with high and stable yield over time and among locations contributes to the efficiency of the genetic breeding program. The relative performance of the progenies varies depending of the age of early selection test. © 2013 Springer Science+Business Media Dordrecht.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In this paper, we consider the problem of topology design for optical networks. We investigate the problem of selecting switching sites to minimize total cost of the optical network. The cost of an optical network can be expressed as a sum of three main factors: the site cost, the link cost, and the switch cost. To the best of our knowledge, this problem has not been studied in its general form as investigated in this paper. We present a mixed integer quadratic programming (MIQP) formulation of the problem to find the optimal value of the total network cost. We also present an efficient heuristic to approximate the solution in polynomial time. The experimental results show good performance of the heuristic. The value of the total network cost computed by the heuristic varies within 2% to 21% of its optimal value in the experiments with 10 nodes. The total network cost computed by the heuristic for 51% of the experiments with 10 node network topologies varies within 8% of its optimal value. We also discuss the insight gained from our experiments.
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There has been a discontinuous but fairly persistent long-term decline in homicide rates in core European countries since about 1500. Since the 1950s, however, we observe an upward trend in violent crime not only in Europe but in almost all of the economically advanced nations that combine democratic political structures with free-market economies. The paper presents an explanatory scheme designed to account for both, the long decline and its apparent reversal. The theoretical model draws heavily upon ideas taken from the sociological work of Emile Durkheim and Norbert Elias—with some modifications and extensions. It seeks to integrate sociological and historical perspectives and to give due weight to both, structural and developmental forces. A key hypothesis is that the pacifying effects of the erosion of traditional collectivism can only be maintained to the extent by which “cooperative individualism” dominates over against the forces of “disintegrative individualism.” Some suggestions are made concerning the selection of appropriate indicators and the handling of methodological problems related to causal attribution.
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This thesis objective is to discover “How are informal decisions reached by screeners when filtering out undesirable job applications?” Grounded theory techniques were employed in the field to observe and analyse informal decisions at the source by screeners in three distinct empirical studies. Whilst grounded theory provided the method for case and cross-case analysis, literature from academic and non-academic sources was evaluated and integrated to strengthen this research and create a foundation for understanding informal decisions. As informal decisions in early hiring processes have been under researched, this thesis contributes to current knowledge in several ways. First, it locates the Cycle of Employment which enhances Robertson and Smith’s (1993) Selection Paradigm through the integration of stages that individuals occupy whilst seeking employment. Secondly, a general depiction of the Workflow of General Hiring Processes provides a template for practitioners to map and further develop their organisational processes. Finally, it highlights the emergence of the Locality Effect, which is a geographically driven heuristic and bias that can significantly impact recruitment and informal decisions. Although screeners make informal decisions using multiple variables, informal decisions are made in stages as evidence in the Cycle of Employment. Moreover, informal decisions can be erroneous as a result of a majority and minority influence, the weighting of information, the injection of inappropriate information and criteria, and the influence of an assessor. This thesis considers these faults and develops a basic framework of understanding informal decisions to which future research can be launched.
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We analyze a business model for e-supermarkets to enable multi-product sourcing capacity through co-opetition (collaborative competition). The logistics aspect of our approach is to design and execute a network system where “premium” goods are acquired from vendors at multiple locations in the supply network and delivered to customers. Our specific goals are to: (i) investigate the role of premium product offerings in creating critical mass and profit; (ii) develop a model for the multiple-pickup single-delivery vehicle routing problem in the presence of multiple vendors; and (iii) propose a hybrid solution approach. To solve the problem introduced in this paper, we develop a hybrid metaheuristic approach that uses a Genetic Algorithm for vendor selection and allocation, and a modified savings algorithm for the capacitated VRP with multiple pickup, single delivery and time windows (CVRPMPDTW). The proposed Genetic Algorithm guides the search for optimal vendor pickup location decisions, and for each generated solution in the genetic population, a corresponding CVRPMPDTW is solved using the savings algorithm. We validate our solution approach against published VRPTW solutions and also test our algorithm with Solomon instances modified for CVRPMPDTW.
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Exposure to counter-stereotypic gender role models (e.g., a woman engineer) has been shown to successfully reduce the application of biased gender stereotypes. We tested the hypothesis that such efforts may more generally lessen the application of stereotypic knowledge in other (non-gendered) domains. Specifically, based on the notion that counter-stereotypes can stimulate a lesser reliance on heuristic thinking, we predicted that contesting gender stereotypes would eliminate a more general group prototypicality bias in the selection of leaders. Three studies supported this hypothesis. After exposing participants to a counter-stereotypic gender role model, group prototypicality no longer predicted leadership evaluation and selection. We discuss the implications of these findings for groups and organizations seeking to capitalize on the benefits of an increasingly diverse workforce.
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This research is motivated by the need for considering lot sizing while accepting customer orders in a make-to-order (MTO) environment, in which each customer order must be delivered by its due date. Job shop is the typical operation model used in an MTO operation, where the production planner must make three concurrent decisions; they are order selection, lot size, and job schedule. These decisions are usually treated separately in the literature and are mostly led to heuristic solutions. The first phase of the study is focused on a formal definition of the problem. Mathematical programming techniques are applied to modeling this problem in terms of its objective, decision variables, and constraints. A commercial solver, CPLEX is applied to solve the resulting mixed-integer linear programming model with small instances to validate the mathematical formulation. The computational result shows it is not practical for solving problems of industrial size, using a commercial solver. The second phase of this study is focused on development of an effective solution approach to this problem of large scale. The proposed solution approach is an iterative process involving three sequential decision steps of order selection, lot sizing, and lot scheduling. A range of simple sequencing rules are identified for each of the three subproblems. Using computer simulation as the tool, an experiment is designed to evaluate their performance against a set of system parameters. For order selection, the proposed weighted most profit rule performs the best. The shifting bottleneck and the earliest operation finish time both are the best scheduling rules. For lot sizing, the proposed minimum cost increase heuristic, based on the Dixon-Silver method performs the best, when the demand-to-capacity ratio at the bottleneck machine is high. The proposed minimum cost heuristic, based on the Wagner-Whitin algorithm is the best lot-sizing heuristic for shops of a low demand-to-capacity ratio. The proposed heuristic is applied to an industrial case to further evaluate its performance. The result shows it can improve an average of total profit by 16.62%. This research contributes to the production planning research community with a complete mathematical definition of the problem and an effective solution approach to solving the problem of industry scale.
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Traditional heuristic approaches to the Examination Timetabling Problem normally utilize a stochastic method during Optimization for the selection of the next examination to be considered for timetabling within the neighbourhood search process. This paper presents a technique whereby the stochastic method has been augmented with information from a weighted list gathered during the initial adaptive construction phase, with the purpose of intelligently directing examination selection. In addition, a Reinforcement Learning technique has been adapted to identify the most effective portions of the weighted list in terms of facilitating the greatest potential for overall solution improvement. The technique is tested against the 2007 International Timetabling Competition datasets with solutions generated within a time frame specified by the competition organizers. The results generated are better than those of the competition winner in seven of the twelve examinations, while being competitive for the remaining five examinations. This paper also shows experimentally how using reinforcement learning has improved upon our previous technique.
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Vigna unguiculata (L.) Walp (cowpea) is a food crop with high nutritional value that is cultivated throughout tropical and subtropical regions of the world. The main constraint on high productivity of cowpea is water deficit, caused by the long periods of drought that occur in these regions. The aim of the present study was to select elite cowpea genotypes with enhanced drought tolerance, by applying principal component analysis to 219 first-cycle progenies obtained in a recurrent selection program. The experimental design comprised a simple 15 x 15 lattice with 450 plots, each of two rows of 10 plants. Plants were grown under water-deficit conditions by applying a water depth of 205 mm representing one-half of that required by cowpea. Variables assessed were flowering, maturation, pod length, number and mass of beans/pod, mass of 100 beans, and productivity/plot. Ten elite cowpea genotypes were selected, in which principal components 1 and 2 encompassed variables related to yield (pod length, beans/pod, and productivity/plot) and life precocity (flowering and maturation), respectively.
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Split-plot design (SPD) and near-infrared chemical imaging were used to study the homogeneity of the drug paracetamol loaded in films and prepared from mixtures of the biocompatible polymers hydroxypropyl methylcellulose, polyvinylpyrrolidone, and polyethyleneglycol. The study was split into two parts: a partial least-squares (PLS) model was developed for a pixel-to-pixel quantification of the drug loaded into films. Afterwards, a SPD was developed to study the influence of the polymeric composition of films and the two process conditions related to their preparation (percentage of the drug in the formulations and curing temperature) on the homogeneity of the drug dispersed in the polymeric matrix. Chemical images of each formulation of the SPD were obtained by pixel-to-pixel predictions of the drug using the PLS model of the first part, and macropixel analyses were performed for each image to obtain the y-responses (homogeneity parameter). The design was modeled using PLS regression, allowing only the most relevant factors to remain in the final model. The interpretation of the SPD was enhanced by utilizing the orthogonal PLS algorithm, where the y-orthogonal variations in the design were separated from the y-correlated variation.
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Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.
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The genera Cochliomyia and Chrysomya contain both obligate and saprophagous flies, which allows the comparison of different feeding habits between closely related species. Among the different strategies for comparing these habits is the use of qPCR to investigate the expression levels of candidate genes involved in feeding behavior. To ensure an accurate measure of the levels of gene expression, it is necessary to normalize the amount of the target gene with the amount of a reference gene having a stable expression across the compared species. Since there is no universal gene that can be used as a reference in functional studies, candidate genes for qPCR data normalization were selected and validated in three Calliphoridae (Diptera) species, Cochliomyia hominivorax Coquerel, Cochliomyia macellaria Fabricius, and Chrysomya albiceps Wiedemann . The expression stability of six genes ( Actin, Gapdh, Rp49, Rps17, α -tubulin, and GstD1) was evaluated among species within the same life stage and between life stages within each species. The expression levels of Actin, Gapdh, and Rp49 were the most stable among the selected genes. These genes can be used as reliable reference genes for functional studies in Calliphoridae using similar experimental settings.
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We compared the indication of laparoscopy for treatment of adnexal masses based on the risk scores and tumor diameters with the indication based on gynecology-oncologists' experience. This was a prospective study of 174 women who underwent surgery for adnexal tumors (116 laparotomies, 58 laparoscopies). The surgeries begun and completed by laparoscopy, with benign pathologic diagnosis, were considered successful. Laparoscopic surgeries that required conversion to laparotomy, led to a malignant diagnosis, or facilitated cyst rupture were considered failures. Two groups were defined for laparoscopy indication: (1) absence of American College of Obstetrics and Gynecology (ACOG) guideline for referral of high-risk adnexal masses criteria (ACOG negative) associated with 3 different tumor sizes (10, 12, and 14 cm); and (2) Index of Risk of Malignancy (IRM) with cutoffs at 100, 200, and 300, associated with the same 3 tumor sizes. Both groups were compared with the indication based on the surgeon's experience to verify whether the selection based on strict rules would improve the rate of successful laparoscopy. ACOG-negative and tumors ≤10 cm and IRM with a cutoff at 300 points and tumors ≤10cm resulted in the same best performance (78% success = 38/49 laparoscopies). However, compared with the results of the gynecology-oncologists' experience, those were not statistically significant. The selection of patients with adnexal mass to laparoscopy by the use of the ACOG guideline or IRM associated with tumor diameter had similar performance as the experience of gynecology-oncologists. Both methods are reproducible and easy to apply to all women with adnexal masses and could be used by general gynecologists to select women for laparoscopic surgery; however, referral to a gynecology-oncologist is advisable when there is any doubt.