953 resultados para Reliable Computations


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Mestrado em Fisioterapia

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It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.

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The purpose of this paper is to discuss the linear solution of equality constrained problems by using the Frontal solution method without explicit assembling. Design/methodology/approach - Re-written frontal solution method with a priori pivot and front sequence. OpenMP parallelization, nearly linear (in elimination and substitution) up to 40 threads. Constraints enforced at the local assembling stage. Findings - When compared with both standard sparse solvers and classical frontal implementations, memory requirements and code size are significantly reduced. Research limitations/implications - Large, non-linear problems with constraints typically make use of the Newton method with Lagrange multipliers. In the context of the solution of problems with large number of constraints, the matrix transformation methods (MTM) are often more cost-effective. The paper presents a complete solution, with topological ordering, for this problem. Practical implications - A complete software package in Fortran 2003 is described. Examples of clique-based problems are shown with large systems solved in core. Social implications - More realistic non-linear problems can be solved with this Frontal code at the core of the Newton method. Originality/value - Use of topological ordering of constraints. A-priori pivot and front sequences. No need for symbolic assembling. Constraints treated at the core of the Frontal solver. Use of OpenMP in the main Frontal loop, now quantified. Availability of Software.

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Friction stir welding (FSW) is now well established as a welding process capable of joining some different types of metallic materials, as it was (1) found to be a reliable and economical way of producing high quality welds, and (2) considered a "clean" welding process that does not involve fusion of metal, as is the case with other traditional welding processes. The aim of this study was to determine whether the emission of particles during FSW in the nanorange of the most commonly used aluminum (Al) alloys, AA 5083 and AA 6082, originated from the Al alloy itself due to friction of the welding tool against the item that was being welded. Another goal was to measure Al alloys in the alveolar deposited surface area during FSW. Nanoparticles dimensions were predominantly in the 40- and 70-nm range. This study demonstrated that microparticles were also emitted during FSW but due to tool wear. However, the biological relevance and toxic manifestations of these microparticles remain to be determined.

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Mestrado em Engenharia Electrotécnica e de Computadores.Área de Especialização de Sistemas Autónomos

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ABSTRACTOBJECTIVE To assess inter-rater reliability, test-retest reliability, and construct validity of retail food store, open-air food market, and restaurant observation tools adapted to the Brazilian urban context.METHODS This study is part of a cross-sectional observation survey conducted in 13 districts across the city of Sao Paulo, Brazil in 2010-2011. Food store and restaurant observational tools were developed based on previously available tools, and then tested it. They included measures on the availability, variety, quality, pricing, and promotion of fruits and vegetables and ultra-processed foods. We used Kappa statistics and intra-class correlation coefficients to assess inter-rater and test-retest reliabilities in samples of 142 restaurants, 97 retail food stores (including open-air food markets), and of 62 restaurants and 45 retail food stores (including open-air food markets), respectively. Construct validity as the tool’s abilities to discriminate based on store types and different income contexts were assessed in the entire sample: 305 retail food stores, 8 fruits and vegetable markets, and 472 restaurants.RESULTS Inter-rater and test-retest reliability were generally high, with most Kappa values greater than 0.70 (range 0.49-1.00). Both tools discriminated between store types and neighborhoods with different median income. Fruits and vegetables were more likely to be found in middle to higher-income neighborhoods, while soda, fruit-flavored drink mixes, cookies, and chips were cheaper and more likely to be found in lower-income neighborhoods.CONCLUSIONS The measures were reliable and able to reveal significant differences across store types and different contexts. Although some items may require revision, results suggest that the tools may be used to reliably measure the food stores and restaurant food environment in urban settings of middle-income countries. Such studies can help .inform health promotion interventions and policies in these contexts.

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ABSTRACT OBJECTIVE : To evaluate the validity and reliability of the Questionnaire for Compliance with Standard Precaution for nurses. METHODS : This methodological study was conducted with 121 nurses from health care facilities in Sao Paulo's countryside, who were represented by two high-complexity and by three average-complexity health care facilities. Internal consistency was calculated using Cronbach's alpha and stability was calculated by the intraclass correlation coefficient, through test-retest. Convergent, discriminant, and known-groups construct validity techniques were conducted. RESULTS : The questionnaire was found to be reliable (Cronbach's alpha: 0.80; intraclass correlation coefficient: (0.97) In regards to the convergent and discriminant construct validity, strong correlation was found between compliance to standard precautions, the perception of a safe environment, and the smaller perception of obstacles to follow such precautions (r = 0.614 and r = 0.537, respectively). The nurses who were trained on the standard precautions and worked on the health care facilities of higher complexity were shown to comply more (p = 0.028 and p = 0.006, respectively). CONCLUSIONS : The Brazilian version of the Questionnaire for Compliance with Standard Precaution was shown to be valid and reliable. Further investigation must be conducted with nurse samples that are more representative of the Brazilian reality. The use of the questionnaire may support the creation of educational measures considering the possible gaps that can be identified, focusing on the workers' health and on the patients' safety.

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A comparative study concerning the robustness of a novel, Fixed Point Transformations/Singular Value Decomposition (FPT/SVD)-based adaptive controller and the Slotine-Li (S&L) approach is given by numerical simulations using a three degree of freedom paradigm of typical Classical Mechanical systems, the cart + double pendulum. The effects of the imprecision of the available dynamical model, presence of dynamic friction at the axles of the drives, and the existence of external disturbance forces unknown and not modeled by the controller are considered. While the Slotine-Li approach tries to identify the parameters of the formally precise, available analytical model of the controlled system with the implicit assumption that the generalized forces are precisely known, the novel one makes do with a very rough, affine form and a formally more precise approximate model of that system, and uses temporal observations of its desired vs. realized responses. Furthermore, it does not assume the lack of unknown perturbations caused either by internal friction and/or external disturbances. Its another advantage is that it needs the execution of the SVD as a relatively time-consuming operation on a grid of a rough system-model only one time, before the commencement of the control cycle within which it works only with simple computations. The simulation examples exemplify the superiority of the FPT/SVD-based control that otherwise has the deficiency that it can get out of the region of its convergence. Therefore its design and use needs preliminary simulation investigations. However, the simulations also exemplify that its convergence can be guaranteed for various practical purposes.

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When considering time series data of variables describing agent interactions in social neurobiological systems, measures of regularity can provide a global understanding of such system behaviors. Approximate entropy (ApEn) was introduced as a nonlinear measure to assess the complexity of a system behavior by quantifying the regularity of the generated time series. However, ApEn is not reliable when assessing and comparing the regularity of data series with short or inconsistent lengths, which often occur in studies of social neurobiological systems, particularly in dyadic human movement systems. Here, the authors present two normalized, nonmodified measures of regularity derived from the original ApEn, which are less dependent on time series length. The validity of the suggested measures was tested in well-established series (random and sine) prior to their empirical application, describing the dyadic behavior of athletes in team games. The authors consider one of the ApEn normalized measures to generate the 95th percentile envelopes that can be used to test whether a particular social neurobiological system is highly complex (i.e., generates highly unpredictable time series). Results demonstrated that suggested measures may be considered as valid instruments for measuring and comparing complexity in systems that produce time series with inconsistent lengths.

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Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.

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Dynamically reconfigurable SRAM-based field-programmable gate arrays (FPGAs) enable the implementation of reconfigurable computing systems where several applications may be run simultaneously, sharing the available resources according to their own immediate functional requirements. To exclude malfunctioning due to faulty elements, the reliability of all FPGA resources must be guaranteed. Since resource allocation takes place asynchronously, an online structural test scheme is the only way of ensuring reliable system operation. On the other hand, this test scheme should not disturb the operation of the circuit, otherwise availability would be compromised. System performance is also influenced by the efficiency of the management strategies that must be able to dynamically allocate enough resources when requested by each application. As those resources are allocated and later released, many small free resource blocks are created, which are left unused due to performance and routing restrictions. To avoid wasting logic resources, the FPGA logic space must be defragmented regularly. This paper presents a non-intrusive active replication procedure that supports the proposed test methodology and the implementation of defragmentation strategies, assuring both the availability of resources and their perfect working condition, without disturbing system operation.

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International Journal of Mathematics and Mathematical Sciences, Vol.2006

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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo Energia

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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 Electrotécnica e de Computadores