972 resultados para Integer programming problems


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Mestrado em Controlo de Gestão e dos Negócios

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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica

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A recent and comprehensive review of the use of race and ethnicity in research that address health disparities in epidemiology and public health is provided. First it is described the theoretical basis upon which race and ethnicity differ drawing from previous work in anthropology, social science and public health. Second, it is presented a review of 280 articles published in high impacts factor journals in regards to public health and epidemiology from 2009-2011. An analytical grid enabled the examination of conceptual, theoretical and methodological questions related to the use of both concepts. The majority of articles reviewed were grounded in a theoretical framework and provided interpretations from various models. However, key problems identified include a) a failure from researchers to differentiate between the concepts of race and ethnicity; b) an inappropriate use of racial categories to ascribe ethnicity; c) a lack of transparency in the methods used to assess both concepts; and d) failure to address limits associated with the construction of racial or ethnic taxonomies and their use. In conclusion, future studies examining health disparities should clearly establish the distinction between race and ethnicity, develop theoretically driven research and address specific questions about the relationships between race, ethnicity and health. One argue that one way to think about ethnicity, race and health is to dichotomize research into two sets of questions about the relationship between human diversity and health.

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This paper presents a comparison between proportional integral control approaches for variable speed wind turbines. Integer and fractional-order controllers are designed using linearized wind turbine model whilst fuzzy controller also takes into account system nonlinearities. These controllers operate in the full load region and the main objective is to extract maximum power from the wind turbine while ensuring the performance and reliability required to be integrated into an electric grid. The main contribution focuses on the use of fractional-order proportional integral (FOPI) controller which benefits from the introduction of one more tuning parameter, the integral fractional-order, taking advantage over integer order proportional integral (PI) controller. A comparison between proposed control approaches for the variable speed wind turbines is presented using a wind turbine benchmark model in the Matlab/Simulink environment. Results show that FOPI has improved system performance when compared with classical PI and fuzzy PI controller outperforms the integer and fractional-order control due to its capability to deal with system nonlinearities and uncertainties. © 2014 IEEE.

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This paper is on the maximization of total profit in a day-ahead market for a price-taker producer needing a short-term scheduling for wind power plants coordination with concentrated solar power plants, having thermal energy storage systems. The optimization approach proposed for the maximization of profit is a mixed-integer linear programming problem. The approach considers not only transmission grid constraints, but also technical operating constraints on both wind and concentrated solar power plants. Then, an improved short-term scheduling coordination is provided due to the more accurate modelling presented in this paper. Computer simulation results based on data for the Iberian wind and concentrated solar power plants illustrate the coordination benefits and show the effectiveness of the approach.

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Wireless Sensor Networks (WSN) are being used for a number of applications involving infrastructure monitoring, building energy monitoring and industrial sensing. The difficulty of programming individual sensor nodes and the associated overhead have encouraged researchers to design macro-programming systems which can help program the network as a whole or as a combination of subnets. Most of the current macro-programming schemes do not support multiple users seamlessly deploying diverse applications on the same shared sensor network. As WSNs are becoming more common, it is important to provide such support, since it enables higher-level optimizations such as code reuse, energy savings, and traffic reduction. In this paper, we propose a macro-programming framework called Nano-CF, which, in addition to supporting in-network programming, allows multiple applications written by different programmers to be executed simultaneously on a sensor networking infrastructure. This framework enables the use of a common sensing infrastructure for a number of applications without the users having to worrying about the applications already deployed on the network. The framework also supports timing constraints and resource reservations using the Nano-RK operating system. Nano- CF is efficient at improving WSN performance by (a) combining multiple user programs, (b) aggregating packets for data delivery, and (c) satisfying timing and energy specifications using Rate- Harmonized Scheduling. Using representative applications, we demonstrate that Nano-CF achieves 90% reduction in Source Lines-of-Code (SLoC) and 50% energy savings from aggregated data delivery.

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Over the last three decades, computer architects have been able to achieve an increase in performance for single processors by, e.g., increasing clock speed, introducing cache memories and using instruction level parallelism. However, because of power consumption and heat dissipation constraints, this trend is going to cease. In recent times, hardware engineers have instead moved to new chip architectures with multiple processor cores on a single chip. With multi-core processors, applications can complete more total work than with one core alone. To take advantage of multi-core processors, parallel programming models are proposed as promising solutions for more effectively using multi-core processors. This paper discusses some of the existent models and frameworks for parallel programming, leading to outline a draft parallel programming model for Ada.

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Mestrado em Contabilidade e Gestão das Instituições Financeiras

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Several projects in the recent past have aimed at promoting Wireless Sensor Networks as an infrastructure technology, where several independent users can submit applications that execute concurrently across the network. Concurrent multiple applications cause significant energy-usage overhead on sensor nodes, that cannot be eliminated by traditional schemes optimized for single-application scenarios. In this paper, we outline two main optimization techniques for reducing power consumption across applications. First, we describe a compiler based approach that identifies redundant sensing requests across applications and eliminates those. Second, we cluster the radio transmissions together by concatenating packets from independent applications based on Rate-Harmonized Scheduling.

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Wireless Sensor Networks (WSNs) are increasingly used in various application domains like home-automation, agriculture, industries and infrastructure monitoring. As applications tend to leverage larger geographical deployments of sensor networks, the availability of an intuitive and user friendly programming abstraction becomes a crucial factor in enabling faster and more efficient development, and reprogramming of applications. We propose a programming pattern named sMapReduce, inspired by the Google MapReduce framework, for mapping application behaviors on to a sensor network and enabling complex data aggregation. The proposed pattern requires a user to create a network-level application in two functions: sMap and Reduce, in order to abstract away from the low-level details without sacrificing the control to develop complex logic. Such a two-fold division of programming logic is a natural-fit to typical sensor networking operation which makes sensing and topological modalities accessible to the user.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática.

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This project was developed within the ART-WiSe framework of the IPP-HURRAY group (http://www.hurray.isep.ipp.pt), at the Polytechnic Institute of Porto (http://www.ipp.pt). The ART-WiSe – Architecture for Real-Time communications in Wireless Sensor networks – framework (http://www.hurray.isep.ipp.pt/art-wise) aims at providing new communication architectures and mechanisms to improve the timing performance of Wireless Sensor Networks (WSNs). The architecture is based on a two-tiered protocol structure, relying on existing standard communication protocols, namely IEEE 802.15.4 (Physical and Data Link Layers) and ZigBee (Network and Application Layers) for Tier 1 and IEEE 802.11 for Tier 2, which serves as a high-speed backbone for Tier 1 without energy consumption restrictions. Within this trend, an application test-bed is being developed with the objectives of implementing, assessing and validating the ART-WiSe architecture. Particularly for the ZigBee protocol case; even though there is a strong commercial lobby from the ZigBee Alliance (http://www.zigbee.org), there is neither an open source available to the community for this moment nor publications on its adequateness for larger-scale WSN applications. This project aims at fulfilling these gaps by providing: a deep analysis of the ZigBee Specification, mainly addressing the Network Layer and particularly its routing mechanisms; an identification of the ambiguities and open issues existent in the ZigBee protocol standard; the proposal of solutions to the previously referred problems; an implementation of a subset of the ZigBee Network Layer, namely the association procedure and the tree routing on our technological platform (MICAz motes, TinyOS operating system and nesC programming language) and an experimental evaluation of that routing mechanism for WSNs.

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Constrained nonlinear optimization problems are usually solved using penalty or barrier methods combined with unconstrained optimization methods. Another alternative used to solve constrained nonlinear optimization problems is the lters method. Filters method, introduced by Fletcher and Ley er in 2002, have been widely used in several areas of constrained nonlinear optimization. These methods treat optimization problem as bi-objective attempts to minimize the objective function and a continuous function that aggregates the constraint violation functions. Audet and Dennis have presented the rst lters method for derivative-free nonlinear programming, based on pattern search methods. Motivated by this work we have de- veloped a new direct search method, based on simplex methods, for general constrained optimization, that combines the features of the simplex method and lters method. This work presents a new variant of these methods which combines the lters method with other direct search methods and are proposed some alternatives to aggregate the constraint violation functions.

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Constrained and unconstrained Nonlinear Optimization Problems often appear in many engineering areas. In some of these cases it is not possible to use derivative based optimization methods because the objective function is not known or it is too complex or the objective function is non-smooth. In these cases derivative based methods cannot be used and Direct Search Methods might be the most suitable optimization methods. An Application Programming Interface (API) including some of these methods was implemented using Java Technology. This API can be accessed either by applications running in the same computer where it is installed or, it can be remotely accessed through a LAN or the Internet, using webservices. From the engineering point of view, the information needed from the API is the solution for the provided problem. On the other hand, from the optimization methods researchers’ point of view, not only the solution for the problem is needed. Also additional information about the iterative process is useful, such as: the number of iterations; the value of the solution at each iteration; the stopping criteria, etc. In this paper are presented the features added to the API to allow users to access to the iterative process data.

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In Nonlinear Optimization Penalty and Barrier Methods are normally used to solve Constrained Problems. There are several Penalty/Barrier Methods and they are used in several areas from Engineering to Economy, through Biology, Chemistry, Physics among others. In these areas it often appears Optimization Problems in which the involved functions (objective and constraints) are non-smooth and/or their derivatives are not know. In this work some Penalty/Barrier functions are tested and compared, using in the internal process, Derivative-free, namely Direct Search, methods. This work is a part of a bigger project involving the development of an Application Programming Interface, that implements several Optimization Methods, to be used in applications that need to solve constrained and/or unconstrained Nonlinear Optimization Problems. Besides the use of it in applied mathematics research it is also to be used in engineering software packages.