940 resultados para Means


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Lateral ordering of InGaAs quantum dots on the GaAs (001) surface has been achieved in earlier reports, resembling an anisotropic pattern. In this work, we present a method of breaking the anisotropy of ordered quantum dots (QDs) by changing the growth environment. We show experimentally that using As(2) molecules instead of As(4) as a background flux is efficient in controlling the diffusion of distant Ga adatoms to make it possible to produce isotropic ordering of InGaAs QDs over GaAs (001). The control of the lateral ordering of QDs under As(2) flux has enabled us to improve their optical properties. Our results are consistent with reported experimental and theoretical data for structure and diffusion on the GaAs surface.

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The usual tests to compare variances and means (e. g. Bartlett`s test and F-test) assume that the sample comes from a normal distribution. In addition, the test for equality of means requires the assumption of homogeneity of variances. In some situation those assumptions are not satisfied, hence we may face problems like excessive size and low power. In this paper, we describe two tests, namely the Levene`s test for equality of variances, which is robust under nonnormality; and the Brown and Forsythe`s test for equality of means. We also present some modifications of the Levene`s test and Brown and Forsythe`s test, proposed by different authors. We analyzed and applied one modified form of Brown and Forsythe`s test to a real data set. This test is a robust alternative under nonnormality, heteroscedasticity and also when the data set has influential observations. The equality of variance can be well tested by Levene`s test with centering at the sample median.

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Tetrapyridylporphyrins containing four chloro(2,2`-bipyridine)platinum(II) complexes attached at the meta (3-H(2)TPtPyP) and para (4-H(2)TPtPyP) positions of the peripheral pyridine ligands were synthesized and their interaction with DNA investigated. The compounds were isolated in the solid state and characterized by means of spectroscopic and analytical techniques. According to molecular simulations, the two isomers exhibit contrasting structural characteristics, consistent with a saddle shape configuration for 3-H(2)TPtPyP and a planar geometry for 4-H(2)TPtPyP. Surface plasmon resonance studies were carried out on the interaction of the complexes with calf thymus DNA, revealing a preferential binding of 3-H(2)TPtPyP, presumably at the DNA major grooves. (C) 2008 Elsevier Inc. All rights reserved.

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In the contemporary tourism industry, the competitive game is between destinations. Tourism operations struggle to remain competitive on the international market and their success depends to a large extent on other complementary and competing tourism organizations at the destination. It is the sum of the total tourism offerings at the destination which determines its attractiveness. This research explores tourism collaboration process as a means of generating destination competitiveness. The focus of the research is on the enhancing factors which contribute to the success of the collaboration and to the development of quality tourism products. The research studies the case of Biking Dalarna, a collaboration of different organizations at five biking destinations in Dalarna, Sweden. Its purpose is to develop biking tourism in the region and to make Dalarna into Sweden’s leading biking destination. It is a qualitative research; the empirical data was collected through in depth interviews with representatives of six Biking Dalarna member organizations. The qualitative data collected from the participants provides inside look into the members reflections and experience of collaborating. The findings of this research demonstrate how collaboration has improved the biking product in Dalarna and promoted solutions to development problems. The research finds the good relationship between the collaborating actors and the involvement and leadership of the regional tourism management organization as the most contributing factors to the success of Biking Dalarna. The research also suggests that a third desired outcome of collaboration, improved marketing attributes was yet to be achieved in the case of Biking Dalarna.

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Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.

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Climate model projections show that climate change will further increase the risk of flooding in many regions of the world. There is a need for climate adaptation, but building new infrastructure or additional retention basins has its limits, especially in densely populated areas where open spaces are limited. Another solution is the more efficient use of the existing infrastructure. This research investigates a method for real-time flood control by means of existing gated weirs and retention basins. The method was tested for the specific study area of the Demer basin in Belgium but is generally applicable. Today, retention basins along the Demer River are controlled by means of adjustable gated weirs based on fixed logic rules. However, because of the high complexity of the system, only suboptimal results are achieved by these rules. By making use of precipitation forecasts and combined hydrological-hydraulic river models, the state of the river network can be predicted. To fasten the calculation speed, a conceptual river model was used. The conceptual model was combined with a Model Predictive Control (MPC) algorithm and a Genetic Algorithm (GA). The MPC algorithm predicts the state of the river network depending on the positions of the adjustable weirs in the basin. The GA generates these positions in a semi-random way. Cost functions, based on water levels, were introduced to evaluate the efficiency of each generation, based on flood damage minimization. In the final phase of this research the influence of the most important MPC and GA parameters was investigated by means of a sensitivity study. The results show that the MPC-GA algorithm manages to reduce the total flood volume during the historical event of September 1998 by 46% in comparison with the current regulation. Based on the MPC-GA results, some recommendations could be formulated to improve the logic rules.

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Manufacturing strategy has been widely studied and it is increasingly gaining attention. It has a fundamental role that is to translate the business strategy to the operations by developing the capabilities that are needed by the company in order to accomplish the desired performance. More precisely, manufacturing strategy comprises the decisions that managers take during a certain period of time in order to achieve a desire result. These decisions are related to which operational practices and resources are implemented. Our goal was to identify the relationship between these two decisions with operational performance. We based our arguments on the resource-based view for identifying sources of competitive advantage. Hence, we argued that operational practices and resources affect positively the operational performances. Additionally, we proposed that in the presence of some resources the implementation of operational practices would lead to a greater performance. We used previous scales for measuring operational practices and performance, and developed new constructs for resources. The data used is part of the High Performance Manufacturing project and the sample is composed by 291 plants. Through confirmatory factor analysis and multiple regressions we found that operational practices to a certain extant are positively related to operational performance. More specifically, the results show that JIT and customer orientation practices have a positive relationship with quality, delivery, flexibility, and cost performances. Moreover, we found that resources like technology and people explain a great variance of operational performance.

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LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)