23 resultados para parallel selection


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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

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Does return migration affect entrepreneurship? This question has important implications for the debate on the economic development effects of migration for origin countries. The existing literature has, however, not addressed how the estimation of the impact of return migration on entrepreneurship is affected by double unobservable migrant self-selection, both at the initial outward migration and at the final inward return migration stages. This paper uses a representative household survey conducted in Mozambique in order to address this research question. We exploit variation provided by displacement caused by civil war in Mozambique, as well as social unrest and other shocks in migrant destination countries. The results lend support to negative unobservable self-selection at both and each of the initial and return stages of migration, which results in an under-estimation of the effects of return migration on entrepreneurial outcomes when using a ‘naïve’ estimator not controlling for self-selection. Indeed, ‘naïve’ estimates point to a 13 pp increase in the probability of owning a business when there is a return migrant in the household relative to non-migrants only, whereas excluding the double effect of unobservable self-selection, this effect becomes significantly larger - between 24 pp and 29 pp, depending on the method of estimation and source of variation used.

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International Market Selection is an important step towards a successful internationalization strategy. This is no different for startup companies like MyHelpster. This work project was intended to help MyHelpster with their internationalization process by completing the IMS portion of it. The IMS process presented in this paper lead to the conclusion that MyHelpster’s next market for expansion should be the USA. In order to find as much success as possible the author suggests being patient and only expanding when the company has the necessary capital, experience and credibility. Both primary and secondary data were used to compile the qualitative and quantitative analyses.

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Carrefour has been internationalizing into many countries and would like to continue growing. This study focuses on the potential future international market selection of Car-refour, comparing countries from the EU and South America, in a quantitative and qual-itative analysis. The purpose of the project is to help Carrefour to find the right market and the right mode to entry. Through semi-structured interviews and a literature research we found out that Sweden has the highest potential to entry with a Venture (Marketing), followed by Austria

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Combinatorial Optimization Problems occur in a wide variety of contexts and generally are NP-hard problems. At a corporate level solving this problems is of great importance since they contribute to the optimization of operational costs. In this thesis we propose to solve the Public Transport Bus Assignment problem considering an heterogeneous fleet and line exchanges, a variant of the Multi-Depot Vehicle Scheduling Problem in which additional constraints are enforced to model a real life scenario. The number of constraints involved and the large number of variables makes impracticable solving to optimality using complete search techniques. Therefore, we explore metaheuristics, that sacrifice optimality to produce solutions in feasible time. More concretely, we focus on the development of algorithms based on a sophisticated metaheuristic, Ant-Colony Optimization (ACO), which is based on a stochastic learning mechanism. For complex problems with a considerable number of constraints, sophisticated metaheuristics may fail to produce quality solutions in a reasonable amount of time. Thus, we developed parallel shared-memory (SM) synchronous ACO algorithms, however, synchronism originates the straggler problem. Therefore, we proposed three SM asynchronous algorithms that break the original algorithm semantics and differ on the degree of concurrency allowed while manipulating the learned information. Our results show that our sequential ACO algorithms produced better solutions than a Restarts metaheuristic, the ACO algorithms were able to learn and better solutions were achieved by increasing the amount of cooperation (number of search agents). Regarding parallel algorithms, our asynchronous ACO algorithms outperformed synchronous ones in terms of speedup and solution quality, achieving speedups of 17.6x. The cooperation scheme imposed by asynchronism also achieved a better learning rate than the original one.

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Modern fully integrated transceivers architectures, require circuits with low area, low cost, low power, and high efficiency. A key block in modern transceivers is the power amplifier, which is deeply studied in this thesis. First, we study the implementation of a classical Class-A amplifier, describing the basic operation of an RF power amplifier, and analysing the influence of the real models of the reactive components in its operation. Secondly, the Class-E amplifier is deeply studied. The different types of implementations are reviewed and theoretical equations are derived and compared with simulations. There were selected four modes of operation for the Class-E amplifier, in order to perform the implementation of the output stage, and the subsequent comparison of results. This led to the selection of the mode with the best trade-off between efficiency and harmonics distortion, lower power consumption and higher output power. The optimal choice was a parallel circuit containing an inductor with a finite value. To complete the implementation of the PA in switching mode, a driver was implemented. The final block (output stage together with the driver) got 20 % total efficiency (PAE) transmitting 8 dBm output power to a 50 W load with a total harmonic distortion (THD) of 3 % and a total consumption of 28 mW. All implementations are designed using standard 130 nm CMOS technology. The operating frequency is 2.4 GHz and it was considered an 1.2 V DC power supply. The proposed circuit is intended to be used in a Bluetooth transmitter, however, it has a wider range of applications.

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Due to a combination of a vast agricultural industry and a tremendously growing technical textile industry, Ludvig Svensson identified India as target market for possible expansion through domestic production and supply. However, Svensson needed additional information about the industry structure and key players. Therefore, this project focused on a detailed analysis of the technical textile market and its players by following the international partner selection process. Thereby, five key players were identified as potential partners, as well as the need for additional research to determine alternative entry modes, as the market does not currently seem to be receptive for Svensson products.