964 resultados para multi-purpose optimisation
The TAMORA algorithm: satellite rainfall estimates over West Africa using multi-spectral SEVIRI data
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A multi-spectral rainfall estimation algorithm has been developed for the Sahel region of West Africa with the purpose of producing accumulated rainfall estimates for drought monitoring and food security. Radar data were used to calibrate multi-channel SEVIRI data from MSG, and a probability of rainfall at several different rain-rates was established for each combination of SEVIRI radiances. Radar calibrations from both Europe (the SatPrecip algorithm) and Niger (TAMORA algorithm) were used. 10 day estimates were accumulated from SatPrecip and TAMORA and compared with kriged gauge data and TAMSAT satellite rainfall estimates over West Africa. SatPrecip was found to produce large overestimates for the region, probably because of its non-local calibration. TAMORA was negatively biased for areas of West Africa with relatively high rainfall, but its skill was comparable to TAMSAT for the low-rainfall region climatologically similar to its calibration area around Niamey. These results confirm the high importance of local calibration for satellite-derived rainfall estimates. As TAMORA shows no improvement in skill over TAMSAT for dekadal estimates, the extra cloud-microphysical information provided by multi-spectral data may not be useful in determining rainfall accumulations at a ten day timescale. Work is ongoing to determine whether it shows improved accuracy at shorter timescales.
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The increasing demand for cheaper-faster-better services anytime and anywhere has made radio network optimisation much more complex than ever before. In order to dynamically optimise the serving network, Dynamic Network Optimisation (DNO), is proposed as the ultimate solution and future trend. The realization of DNO, however, has been hindered by a significant bottleneck of the optimisation speed as the network complexity grows. This paper presents a multi-threaded parallel solution to accelerate complicated proprietary network optimisation algorithms, under a rigid condition of numerical consistency. ariesoACP product from Arieso Ltd serves as the platform for parallelisation. This parallel solution has been benchmarked and results exhibit a high scalability and a run-time reduction by 11% to 42% based on the technology, subscriber density and blocking rate of a given network in comparison with the original version. Further, it is highly essential that the parallel version produces equivalent optimisation quality in terms of identical optimisation outputs.
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PURPOSE: Multi-species probiotic preparations have been suggested as having a wide spectrum of application, although few studies have compared their efficacy with that of individual component strains at equal concentrations. We therefore tested the ability of 4 single probiotics and 4 probiotic mixtures to inhibit the urinary tract pathogens Escherichia coli NCTC 9001 and Enterococcus faecalis NCTC 00775. METHODS: We used an agar spot test to test the ability of viable cells to inhibit pathogens, while a broth inhibition assay was used to assess inhibition by cell-free probiotic supernatants in both pH-neutralised and non-neutralised forms. RESULTS: In the agar spot test, all probiotic treatments showed inhibition, L. acidophilus was the most inhibitory single strain against E. faecalis, L. fermentum the most inhibitory against E. coli. A commercially available mixture of 14 strains (Bio-Kult(®)) was the most effective mixture, against E. faecalis, the 3-lactobacillus mixture the most inhibitory against E. coli. Mixtures were not significantly more inhibitory than single strains. In the broth inhibition assays, all probiotic supernatants inhibited both pathogens when pH was not controlled, with only 2 treatments causing inhibition at a neutral pH. CONCLUSIONS: Both viable cells of probiotics and supernatants of probiotic cultures were able to inhibit growth of two urinary tract pathogens. Probiotic mixtures prevented the growth of urinary tract pathogens but were not significantly more inhibitory than single strains. Probiotics appear to produce metabolites that are inhibitory towards urinary tract pathogens. Probiotics display potential to reduce the incidence of urinary tract infections via inhibition of colonisation.
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Methods for recombinant production of eukaryotic membrane proteins, yielding sufficient quantity and quality of protein for structural biology, remain a challenge. We describe here, expression and purification optimisation of the human SERCA2a cardiac isoform of Ca2+ translocating ATPase, using Saccharomyces cerevisiae as the heterologous expression system of choice. Two different expression vectors were utilised, allowing expression of C-terminal fusion proteins with a biotinylation domain or a GFP- His8 tag. Solubilised membrane fractions containing the protein of interest were purified onto Streptavidin-Sepharose, Ni-NTA or Talon resin, depending on the fusion tag present. Biotinylated protein was detected using specific antibody directed against SERCA2 and, advantageously, GFP-His8 fusion protein was easily traced during the purification steps using in-gel fluorescence. Importantly, talon resin affinity purification proved more specific than Ni-NTA resin for the GFP-His8 tagged protein, providing better separation of oligomers present, during size exclusion chromatography. The optimised method for expression and purification of human cardiac SERCA2a reported herein, yields purified protein (> 90%) that displays a calcium-dependent thapsigargin-sensitive activity and is suitable for further biophysical, structural and physiological studies. This work provides support for the use of Saccharomyces cerevisiae as a suitable expression system for recombinant production of multi-domain eukaryotic membrane proteins.
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A novel two-stage construction algorithm for linear-in-the-parameters classifier is proposed, aiming at noisy two-class classification problems. The purpose of the first stage is to produce a prefiltered signal that is used as the desired output for the second stage to construct a sparse linear-in-the-parameters classifier. For the first stage learning of generating the prefiltered signal, a two-level algorithm is introduced to maximise the model's generalisation capability, in which an elastic net model identification algorithm using singular value decomposition is employed at the lower level while the two regularisation parameters are selected by maximising the Bayesian evidence using a particle swarm optimization algorithm. Analysis is provided to demonstrate how “Occam's razor” is embodied in this approach. The second stage of sparse classifier construction is based on an orthogonal forward regression with the D-optimality algorithm. Extensive experimental results demonstrate that the proposed approach is effective and yields competitive results for noisy data sets.
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Information technology has become heavily embedded in business operations. As business needs change over time, IT applications are expected to continue providing required support. Whether the existing IT applications are still fit for the business purpose they were intended or new IT applications should be introduced, is a strategic decision for business, IT and business-aligned IT. In this paper, we present a method which aims to analyse business functions and IT roles, and to evaluate business-aligned IT from both social and technical perspectives. The method introduces a set of techniques that systematically supports the evaluation of the existing IT applications in relation to their technical capabilities for maximising business value. Furthermore, we discuss the evaluation process and results which are illustrated and validated through a real-life case study of a UK borough council, and followed by discussion on implications for researchers and practitioners.
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Purpose – Multinationals have always needed an operating model that works – an effective plan for executing their most important activities at the right levels of their organization, whether globally, regionally or locally. The choices involved in these decisions have never been obvious, since international firms have consistently faced trade‐offs between tailoring approaches for diverse local markets and leveraging their global scale. This paper seeks a more in‐depth understanding of how successful firms manage the global‐local trade‐off in a multipolar world. Design methodology/approach – This paper utilizes a case study approach based on in‐depth senior executive interviews at several telecommunications companies including Tata Communications. The interviews probed the operating models of the companies we studied, focusing on their approaches to organization structure, management processes, management technologies (including information technology (IT)) and people/talent. Findings – Successful companies balance global‐local trade‐offs by taking a flexible and tailored approach toward their operating‐model decisions. The paper finds that successful companies, including Tata Communications, which is profiled in‐depth, are breaking up the global‐local conundrum into a set of more manageable strategic problems – what the authors call “pressure points” – which they identify by assessing their most important activities and capabilities and determining the global and local challenges associated with them. They then design a different operating model solution for each pressure point, and repeat this process as new strategic developments emerge. By doing so they not only enhance their agility, but they also continually calibrate that crucial balance between global efficiency and local responsiveness. Originality/value – This paper takes a unique approach to operating model design, finding that an operating model is better viewed as several distinct solutions to specific “pressure points” rather than a single and inflexible model that addresses all challenges equally. Now more than ever, developing the right operating model is at the top of multinational executives' priorities, and an area of increasing concern; the international business arena has changed drastically, requiring thoughtfulness and flexibility instead of standard formulas for operating internationally. Old adages like “think global and act local” no longer provide the universal guidance they once seemed to.
A benchmark-driven modelling approach for evaluating deployment choices on a multi-core architecture
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The complexity of current and emerging architectures provides users with options about how best to use the available resources, but makes predicting performance challenging. In this work a benchmark-driven model is developed for a simple shallow water code on a Cray XE6 system, to explore how deployment choices such as domain decomposition and core affinity affect performance. The resource sharing present in modern multi-core architectures adds various levels of heterogeneity to the system. Shared resources often includes cache, memory, network controllers and in some cases floating point units (as in the AMD Bulldozer), which mean that the access time depends on the mapping of application tasks, and the core's location within the system. Heterogeneity further increases with the use of hardware-accelerators such as GPUs and the Intel Xeon Phi, where many specialist cores are attached to general-purpose cores. This trend for shared resources and non-uniform cores is expected to continue into the exascale era. The complexity of these systems means that various runtime scenarios are possible, and it has been found that under-populating nodes, altering the domain decomposition and non-standard task to core mappings can dramatically alter performance. To find this out, however, is often a process of trial and error. To better inform this process, a performance model was developed for a simple regular grid-based kernel code, shallow. The code comprises two distinct types of work, loop-based array updates and nearest-neighbour halo-exchanges. Separate performance models were developed for each part, both based on a similar methodology. Application specific benchmarks were run to measure performance for different problem sizes under different execution scenarios. These results were then fed into a performance model that derives resource usage for a given deployment scenario, with interpolation between results as necessary.
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This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.
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Este trabalho discute a implementação da estratégia de postponement, um conceito que vem crescendo de importância nos últimos anos. Postponement é um conceito operacional que consiste em retardar a configuração final de produtos até que os pedidos dos consumidores sejam recebidos. Apesar da atratividade teórica e relevância do tema, pouco ainda se sabe sobre seu processo de implementação, especialmente no ambiente de negócio brasileiro. Este trabalho investigou em profundidade a implementação do postponement em cinco conceituadas empresas no Brasil procurando identificar os motivos que levaram seus respectivos executivos a adotarem tal estratégia, quais foram os agentes facilitadores e os obstáculos à implementação e, finalmente, até que ponto o postponement contribuiu para um aumento da competitividade.
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O estudo busca investigar a atuação das grandes empresas varejista brasileiras com relação à Responsabilidade Social Empresarial (RSE), procurando levantar o estágio em que estas se encontram, e se são aproveitadas as características do varejo de capilaridade geográfica, contato direto com a comunidade, forte vinculo com os clientes, interação entre funcionários e clientes e proximidade física de Organizações Não Governamentais e instituições públicas. Para tanto, foram utilizados conceitos relacionados à gestão, como comprometimento da cúpula, incorporação de valores de RSE na administração e no planejamento estratégico, autonomia e gestão de RSE nas lojas. A gestão foi avaliada pela ótica do contínuo de colaboração de Austin, e as práticas de RSE por meio da teoria dos stakeholders (públicos interessados), utilizando como base as dimensões dos Indicadores Ethos de Responsabilidade Social. A teoria de Kotler e Lee, para a classificação das iniciativas conforme os conceitos do marketing, também foi empregada. Conduziu-se uma pesquisa exploratória com cinco grandes empresas do setor varejista. Os resultados encontrados apontam que na maioria das empresas a incorporação dessas práticas é recente. Constata-se que as empresas diferem quanto ao estágio de RSE e que as características próprias do varejo não são aproveitadas em sua totalidade. Hipóteses são levantadas para que estas aproveitem a estrutura das lojas para atender às necessidades da comunidade local.
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This paper aims to analyze dual-purpose systems focusing the total cost optimization; a superstructure is proposed to present cogeneration systems and desalination technologies alternatives for the synthesis process. The superstructure consists of excluding components, gas turbines or conventional steam generators with excluding alternatives of supplying fuel for each combustion system. Also, backpressure or condensing/extraction steam turbine for supplying process steam could be selected. Finally one desalination unit chosen between electrically-driven or steam-driven reverse osmosis. multi-effect and multistage flash should be included. The analysis herein performed is based on energy and mass conservation equations, as well as the technological limiting equation of equipment. The results for ten different commercial gas turbines revealed that electrically-driven reverse osmosis was always chosen together with both natural gas and gasified biomass gas turbines. (C) 2009 Elsevier B.V. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)