102 resultados para Continuous Optimization


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Scientific evidence has shown an association between organochlorine compounds (OCC) exposure and human health hazards. Concerning this, OCC detection in human adipose samples has to be considered a public health priority. This study evaluated the efficacy of various solid-phase extraction (SPE) and cleanup methods for OCC determination in human adipose tissue. Octadecylsilyl endcapped (C18-E), benzenesulfonic acid modified silica cation exchanger (SA), poly (styrene-divinylbenzene (EN) and EN/RP18 SPE sorbents were evaluated. The relative sample cleanup provided by these SPE columns was evaluated using gas chromatography with electron capture detection (GC–ECD). The C18-E columns with strong homogenization were found to provide the most effective cleanup, removing the greatest amount of interfering substance, and simultaneously ensuring good analyte recoveries higher than 70%. Recoveries>70% with standard deviations (SD)<15% were obtained for all compounds under the selected conditions. Method detection limits were in the 0.003–0.009 mg/kg range. The positive samples were confirmed by gas chromatography coupled with tandem mass spectrometry (GC-MS/MS). The highest percentage found of the OCC in real samples corresponded to HCB, o,p′-DDT and methoxychlor, which were detected in 80 and 95% of samples analyzed respectively. Copyright © 2012 John Wiley & Sons, Ltd.

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Multiclass analysis method was optimized in order to analyze pesticides traces by gas chromatography with ion-trap and tandem mass spectrometry (GC-MS/MS). The influence of some analytical parameters on pesticide signal response was explored. Five ion trap mass spectrometry (IT-MS) operating parameters, including isolation time (IT), excitation voltage (EV), excitation time (ET),maximum excitation energy or “q” value (q), and isolationmass window (IMW) were numerically tested in order to maximize the instrument analytical signal response. For this, multiple linear regression was used in data analysis to evaluate the influence of the five parameters on the analytical response in the ion trap mass spectrometer and to predict its response. The assessment of the five parameters based on the regression equations substantially increased the sensitivity of IT-MS/MS in the MS/MS mode. The results obtained show that for most of the pesticides, these parameters have a strong influence on both signal response and detection limit.Using the optimized method, a multiclass pesticide analysis was performed for 46 pesticides in a strawberry matrix. Levels higher than the limit established for strawberries by the European Union were found in some samples.

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Over the last two decades the research and development of legged locomotion robots has grown steadily. Legged systems present major advantages when compared with ‘traditional’ vehicles, because they allow locomotion in inaccessible terrain to vehicles with wheels and tracks. However, the robustness of legged robots, and especially their energy consumption, among other aspects, still lag behind mechanisms that use wheels and tracks. Therefore, in the present state of development, there are several aspects that need to be improved and optimized. Keeping these ideas in mind, this paper presents the review of the literature of different methods adopted for the optimization of the structure and locomotion gaits of walking robots. Among the distinct possible strategies often used for these tasks are referred approaches such as the mimicking of biological animals, the use of evolutionary schemes to find the optimal parameters and structures, the adoption of sound mechanical design rules, and the optimization of power-based indexes.

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A Box–Behnken factorial design coupled with surface response methodology was used to evaluate the effects of temperature, pH and initial concentration in the Cu(II) sorption process onto the marine macroalgae Ascophyllum nodosum. The effect of the operating variables on metal uptake capacitywas studied in a batch system and a mathematical model showing the influence of each variable and their interactions was obtained. Study ranges were 10–40ºC for temperature, 3.0–5.0 for pH and 50–150mgL−1 for initial Cu(II) concentration. Within these ranges, the biosorption capacity is slightly dependent on temperature but markedly increases with pH and initial concentration of Cu(II). The uptake capacities predicted by the model are in good agreement with the experimental values. Maximum biosorption capacity of Cu(II) by A. nodosum is 70mgg−1 and corresponds to the following values of those variables: temperature = 40ºC, pH= 5.0 and initial Cu(II) concentration = 150mgL−1.

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Solvent extraction is considered as a multi-criteria optimization problem, since several chemical species with similar extraction kinetic properties are frequently present in the aqueous phase and the selective extraction is not practicable. This optimization, applied to mixer–settler units, considers the best parameters and operating conditions, as well as the best structure or process flow-sheet. Global process optimization is performed for a specific flow-sheet and a comparison of Pareto curves for different flow-sheets is made. The positive weight sum approach linked to the sequential quadratic programming method is used to obtain the Pareto set. In all investigated structures, recovery increases with hold-up, residence time and agitation speed, while the purity has an opposite behaviour. For the same treatment capacity, counter-current arrangements are shown to promote recovery without significant impairment in purity. Recycling the aqueous phase is shown to be irrelevant, but organic recycling with as many stages as economically feasible clearly improves the design criteria and reduces the most efficient organic flow-rate.

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In this work three natural waste materials containing chitin were used as adsorbents for textile dyestuffs, namely the Anodonta (Anodonta cygnea) shell, the Sepia (Sepia officinalis) and the Squid (Loligo vulgaris) pens. The selected dyestuffs were the Cibacron green T3G-E (CI reactive green 12), and the Solophenyl green BLE 155% (CI direct green 26), both from CIBA, commonly used in cellulosic fibres dyeing, the most used fibres in the textile industry. Batch equilibrium studies showed that the materials’ adsorption capacities increase after a simple and inexpensive chemical treatment, which increases their porosity and chitin relative content. Kinetic studies suggested the existence of a high internal resistance in both systems. Fixed bed column experiments performed showed an improvement in adsorbents’ behaviour after chemical treatment. However, in the column experiments, the biodegradation was the main mechanism of dyestuff removal, allowing the materials’ bioregeneration. The adsorption was strongly reduced by the pore clogging effect of the biomass. The deproteinised Squid pen (grain size 0.500–1.41 mm) is the adsorbent with highest adsorption capacity (0.27 and 0.037 g/g, respectively, for the reactive and direct dyestuffs, at 20ºC), followed by the demineralised Sepia pen and Anodonta shell, behaving like pure chitin in all experiments, but showing inferior performances than the granular activated carbon tested in the column experiments.

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Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.

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Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyzethe MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems.

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We introduce a new wavelet transform within the framework of the local fractional calculus. An illustrative example of local fractional wavelet transform is also presented.

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O panorama atual da emergência e socorro de primeira linha em Portugal, carateriza-se por uma grande aposta ao longo dos últimos anos num incremento contínuo da qualidade e da eficiência que estes serviços prestam às populações locais. Com vista à prossecução do objetivo de melhoria contínua dos serviços, foram realizados ao longo dos últimos anos investimentos avultados ao nível dos recursos técnicos e ao nível da contratação e formação de recursos humanos altamente qualificados. Atualmente as instituições que prestam socorro e emergência de primeira linha estão bem dotadas ao nível físico e ao nível humano dos recursos necessários para fazerem face aos mais diversos tipos de ocorrências. Contudo, ao nível dos sistemas de informação de apoio à emergência e socorro de primeira linha, verifica-se uma inadequação (e por vezes inexistência) de sistemas informáticos capazes de suportar convenientemente o atual contexto de exigência e complexidade da emergência e socorro. Foi feita ao longo dos últimos anos, uma forte aposta na melhoria dos recursos físicos e dos recursos humanos encarregues da resposta àsemergência de primeira linha, mas descurou-se a área da gestão e análise da informação sobre as ocorrências, assim como, o delinear de possíveis estratégias de prevenção que uma análise sistematizada da informação sobre as ocorrências possibilita. Nas instituições de emergência e socorro de primeira linha em Portugal (bombeiros, proteção civil municipal, PSP, GNR, polícia municipal), prevalecem ainda hoje os sistemas informáticos apenas para o registo das ocorrências à posteriori e a total inexistência de sistemas de registo de informação e de apoio à decisão na alocação de recursos que operem em tempo real. A generalidade dos sistemas informáticos atualmente existentes nas instituições são unicamente de sistemas de backoffice, que não aproveitam a todas as potencialidades da informação operacional neles armazenada. Verificou-se também, que a geo-localização por via informática dos recursos físicos e de pontos de interesse relevantes em situações críticas é inexistente a este nível. Neste contexto, consideramos ser possível e importante alinhar o nível dos sistemas informáticos das instituições encarregues da emergência e socorro de primeira linha, com o nível dos recursos físicos e humanos que já dispõem atualmente. Dado que a emergência e socorro de primeira linha é um domínio claramente elegível para a aplicação de tecnologias provenientes dos domínios da inteligência artificial (nomeadamente sistemas periciais para apoio à decisão) e da geo-localização, decidimos no âmbito desta tese desenvolver um sistema informático capaz de colmatar muitas das lacunas por nós identificadas ao nível dos sistemas informáticos destas instituições. Pretendemos colocar as suas plataformas informáticas num nível similar ao dos seus recursos físicos e humanos. Assim, foram por nós identificadas duas áreas chave onde a implementação de sistemas informáticos adequados às reais necessidades das instituições podem ter um impacto muito proporcionar uma melhor gestão e otimização dos recursos físicos e humanos. As duas áreas chave por nós identificadas são o suporte à decisão na alocação dos recursos físicos e a geolocalização dos recursos físicos, das ocorrências e dos pontos de interesse. Procurando fornecer uma resposta válida e adequada a estas duas necessidades prementes, foi desenvolvido no âmbito desta tese o sistema CRITICAL DECISIONS. O sistema CRITICAL DECISIONS incorpora um conjunto de funcionalidades típicas de um sistema pericial, para o apoio na decisão de alocação de recursos físicos às ocorrências. A inferência automática dos recursos físicos, assenta num conjunto de regra de inferência armazenadas numa base de conhecimento, em constante crescimento e atualização, com base nas respostas bem sucedidas a ocorrências passadas. Para suprimir as carências aos nível da geo-localização dos recursos físicos, das ocorrências e dos pontos de interesse, o sistema CRITICAL DECISIONS incorpora também um conjunto de funcionalidades de geo-localização. Estas permitem a geo-localização de todos os recursos físicos da instituição, a geo-localização dos locais e as áreas das várias ocorrências, assim como, dos vários tipos de pontos de interesse. O sistema CRITICAL DECISIONS visa ainda suprimir um conjunto de outras carências por nós identificadas, ao nível da gestão documental (planos de emergência, plantas dos edifícios) , da comunicação, da partilha de informação entre as instituições de socorro e emergência locais, da contabilização dos tempos de serviço, entre outros. O sistema CRITICAL DECISIONS é o culminar de um esforço colaborativo e contínuo com várias instituições, responsáveis pela emergência e socorro de primeira linha a nível local. Esperamos com o sistema CRITICAL DECISIONS, dotar estas instituições de uma plataforma informática atual, inovadora, evolutiva, com baixos custos de implementação e de operação, capaz de proporcionar melhorias contínuas e significativas ao nível da qualidade da resposta às ocorrências, das capacidades de prevenção e de uma melhor otimização de todos os tipos de recursos que têm ao dispor.

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An optimised version of the Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) method for simultaneous determination of 14 organochlorine pesticides in carrots was developed using gas chromatography coupled with electron-capture detector (GC-ECD) and confirmation by gas chromatography tandem mass spectrometry (GC-MS/MS). A citrate-buffered version of QuEChERS was applied for the extraction of the organochlorine pesticides, and for the extract clean-up, primary secondary amine, octadecyl-bonded silica (C18), magnesium sulphate (MgSO4) and graphitized carbon black were used as sorbents. The GC-ECD determination of the target compounds was achieved in less than 20 min. The limits of detection were below the EUmaximum residue limits (MRLs) for carrots, 10–50 μg kg−1, while the limit of quantification did exceed 10 μg kg−1 for hexachlorobenzene (HCB). The introduction of a sonication step was shown to improve the recoveries. The overall average recoveries in carrots, at the four tested levels (60, 80, 100 and 140 μg kg−1), ranged from 66 to 111% with relative standard deviations in the range of 2– 15 % (n03) for all analytes, with the exception of HCB. The method has been applied to the analysis of 21 carrot samples from different Portuguese regions, and β-HCH was the pesticide most frequently found, with concentrations oscillating between less than the limit of quantification to 14.6 μg kg−1. Only one sample had a pesticide residue (β-HCH) above the MRL, 14.6 μg kg−1. This methodology combines the advantages of both QuEChERS and GC-ECD, producing a very rapid, sensitive and reliable procedure which can be applied in routine analytical laboratories.

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The present work describes the optimization of a short-term assay, based on the inhibition of the esterase activity of the alga Pseudokirchneriella subcapitata, in a microplate format. The optimization of the staining procedure showed that the incubation of the algal cells with 20 μmolL−1 fluorescein diacetate (FDA) for 40 min allowed discrimination between metabolic active and inactive cells. The shortterm assay was tested using Cu as toxicant. For this purpose, algal cells, in the exponential or stationary phase of growth, were exposed to the heavy metal in growing conditions. After 3 or 6 h, cells were subsequently stained with FDA, using the optimized procedure. For Cu, the 3- and 6-h EC50 values, based on the inhibition of the esterase activity of algal cells in the exponential phase of growth, were 209 and 130 μg L−1, respectively. P. subcapitata cells, in the stationary phase of growth, displayed higher effective concentration values than those observed in the exponential phase. The 3- and 6-h EC50 values for Cu, for cells in the stationary phase, were 443 and 268 μgL−1, respectively. This short-term microplate assay showed to be a rapid endpoint for testing toxicity using the alga P. subcapitata. The small volume required, the simplicity of the assay (no washing steps), and the automatic reading of the fluorescence make the assay particularly well suited for the evaluation of the toxicity of a high number of environmental samples.

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Competitive electricity markets have arisen as a result of power-sector restructuration and power-system deregulation. The players participating in competitive electricity markets must define strategies and make decisions using all the available information and business opportunities.

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This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

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It is generally challenging to determine end-to-end delays of applications for maximizing the aggregate system utility subject to timing constraints. Many practical approaches suggest the use of intermediate deadline of tasks in order to control and upper-bound their end-to-end delays. This paper proposes a unified framework for different time-sensitive, global optimization problems, and solves them in a distributed manner using Lagrangian duality. The framework uses global viewpoints to assign intermediate deadlines, taking resource contention among tasks into consideration. For soft real-time tasks, the proposed framework effectively addresses the deadline assignment problem while maximizing the aggregate quality of service. For hard real-time tasks, we show that existing heuristic solutions to the deadline assignment problem can be incorporated into the proposed framework, enriching their mathematical interpretation.