986 resultados para Integrated problem


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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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As wavelength-division multiplexing (WDM) evolves towards practical applications in optical transport networks, waveband switching (WBS) has been introduced to cut down the operational costs and to reduce the complexities and sizes of network components, e.g., optical cross-connects (OXCs). This paper considers the routing, wavelength assignment and waveband assignment (RWWBA) problem in a WDM network supporting mixed waveband and wavelength switching. First, the techniques supporting waveband switching are studied, where a node architecture enabling mixed waveband and wavelength switching is proposed. Second, to solve the RWWBA problem with reduced switching costs and improved network throughput, the cost savings and call blocking probabilities along intermediate waveband-routes are analyzed. Our analysis reveals some important insights about the cost savings and call blocking probability in relation to the fiber capacity, the candidate path, and the traffic load. Third, based on our analysis, an online integrated intermediate WBS algorithm (IIWBS) is proposed. IIWBS determines the waveband switching route for a call along its candidate path according to the node connectivity, the link utilization, and the path length information. In addition, the IIWBS algorithm is adaptive to real network applications under dynamic traffic requests. Finally, our simulation results show that IIWBS outperforms a previous intermediate WBS algorithm and RWA algorithms in terms of network throughput and cost efficiency.

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This article describes a real-world production planning and scheduling problem occurring at an integrated pulp and paper mill (P&P) which manufactures paper for cardboard out of produced pulp. During the cooking of wood chips in the digester, two by-products are produced: the pulp itself (virgin fibers) and the waste stream known as black liquor. The former is then mixed with recycled fibers and processed in a paper machine. Here, due to significant sequence-dependent setups in paper type changeovers, sizing and sequencing of lots have to be made simultaneously in order to efficiently use capacity. The latter is converted into electrical energy using a set of evaporators, recovery boilers and counter-pressure turbines. The planning challenge is then to synchronize the material flow as it moves through the pulp and paper mills, and energy plant, maximizing customer demand (as backlogging is allowed), and minimizing operation costs. Due to the intensive capital feature of P&P, the output of the digester must be maximized. As the production bottleneck is not fixed, to tackle this problem we propose a new model that integrates the critical production units associated to the pulp and paper mills, and energy plant for the first time. Simple stochastic mixed integer programming based local search heuristics are developed to obtain good feasible solutions for the problem. The benefits of integrating the three stages are discussed. The proposed approaches are tested on real-world data. Our work may help P&P companies to increase their competitiveness and reactiveness in dealing with demand pattern oscillations. (C) 2012 Elsevier Ltd. All rights reserved.

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The integrated production scheduling and lot-sizing problem in a flow shop environment consists of establishing production lot sizes and allocating machines to process them within a planning horizon in a production line with machines arranged in series. The problem considers that demands must be met without backlogging, the capacity of the machines must be respected, and machine setups are sequence-dependent and preserved between periods of the planning horizon. The objective is to determine a production schedule to minimise the setup, production and inventory costs. A mathematical model from the literature is presented, as well as procedures for obtaining feasible solutions. However, some of the procedures have difficulty in obtaining feasible solutions for large-sized problem instances. In addition, we address the problem using different versions of the Asynchronous Team (A-Team) approach. The procedures were compared with literature heuristics based on Mixed Integer Programming. The proposed A-Team procedures outperformed the literature heuristics, especially for large instances. The developed methodologies and the results obtained are presented.

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Silicon-on-insulator (SOI) is rapidly emerging as a very promising material platform for integrated photonics. As it combines the potential for optoelectronic integration with the low-cost and large volume manufacturing capabilities and they are already accumulate a huge amount of applications in areas like sensing, quantum optics, optical telecommunications and metrology. One of the main limitations of current technology is that waveguide propagation losses are still much higher than in standard glass-based platform because of many reasons such as bends, surface roughness and the very strong optical confinement provided by SOI. Such high loss prevents the fabrication of efficient optical resonators and complex devices severely limiting the current potential of the SOI platform. The project in the first part deals with the simple waveguides loss problem and trying to link that with the polarization problem and the loss based on Fabry-Perot Technique. The second part of the thesis deals with the Bragg Grating characterization from again the point of view of the polarization effect which leads to a better stop-band use filters. To a better comprehension a brief review on the basics of the SOI and the integrated Bragg grating ends up with the fabrication techniques and some of its applications will be presented in both parts, until the end of both the third and the fourth chapters to some results which hopefully make its precedent explanations easier to deal with.

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We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

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Standardized recovery criteria go beyond symptom remission and put special emphasis on personal and social functioning in residence, work, and leisure. Against this background, evidence-based integrated approaches combining cognitive remediation with social skills therapy show promise for improving functional recovery of schizophrenia patients. Over the past 30 years, research groups in 12 countries have evaluated integrated psychological therapy (IPT) in 36 independent studies. IPT is a group therapy program for schizophrenia patients. It combines neurocognitive and social cognitive interventions with social skills and problem-solving approaches. The aim of the present study was to update and integrate the growing amount of research data on the effectiveness of IPT. We quantitatively reviewed the results of these 36 studies, including 1601 schizophrenia patients, by means of a meta-analytic procedure. Patients undergoing IPT showed significantly greater improvement in all outcome variables (neurocognition, social cognition, psychosocial functioning, and negative symptoms) than those in the control groups (placebo-attention conditions and standard care). IPT patients maintained their mean positive effects during an average follow-up period of 8.1 months. They showed better effects on distal outcome measures when all 5 subprograms were integrated. This analysis summarizes the broad empirical evidence indicating that IPT is an effective rehabilitation approach for schizophrenia patients and is robust across a wide range of sample characteristics as well as treatment conditions. Moreover, the cognitive and social subprograms of IPT may work in a synergistic manner, thereby enhancing the transfer of therapy effects over time and improving functional recovery.

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One of the main problems of flood hazard assessment in ungauged or poorly gauged basins is the lack of runoff data. In an attempt to overcome this problem we have combined archival records, dendrogeomorphic time series and instrumental data (daily rainfall and discharge) from four ungauged and poorly gauged mountain basins in Central Spain with the aim of reconstructing and compiling information on 41 flash flood events since the end of the 19th century. Estimation of historical discharge and the incorporation of uncertainty for the at-site and regional flood frequency analysis were performed with an empirical rainfall–runoff assessment as well as stochastic and Bayesian Markov Chain Monte Carlo (MCMC) approaches. Results for each of the ungauged basins include flood frequency, severity, seasonality and triggers (synoptic meteorological situations). The reconstructed data series clearly demonstrates how uncertainty can be reduced by including historical information, but also points to the considerable influence of different approaches on quantile estimation. This uncertainty should be taken into account when these data are used for flood risk management.

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Background Nowadays there is extensive evidence available showing the efficacy of cognitive remediation (CR). To date, only limited evidence is available about the impact of the duration of illness on CR effects. The Integrated Neurocognitive Therapy (INT) represents a new developed CR approach. It is a manualized group therapy targeting all 11 NIMH-MATRICS domains. Methods In an international multicenter study, 166 schizophrenia outpatients (DSM-IV-TR) were randomly assigned either to INT or to Treatment-As-Usual (TAU). 60 patients were defined as Early Course group (EC) characterized by less than 5 years of illness, 40 patients were in the Long-Term group (LT) characterized by more than 15 years of illness, and 76 patients were in the Medium-Long-Term group (MLT) characterized by an illness of 5-15 years. Treatment comprised of 15 biweekly sessions. Assessments were conducted before and after treatment and at follow up (1 year). Multivariate General Linear Models (GLM) examined our hypothesis, whether EC, LT, and MLT groups differ under INT and TAU from each other in outcome. Results First of all, the attendance rate of 65% was significantly lower and the drop out rate of 18.5% during therapy was higher in the EC group compared to the other groups. Interaction effects regarding proximal outcome showed that the duration of illness has a strong impact on neurocognitive functioning in speed of processing (F>2.4) and attention (F>2.8). But INT intervention compared to TAU only had a significant effect in more chronically ill patients of MLT and LT, but not in younger patients in EC. In social cognitive domains, only the EC group showed a significant change in attribution (hostility; F>2.5), LT and MLT groups did not. However, no differences between the 3 groups were evident in memory, problem solving, and emotion perception. Regarding more distal outcome, LT patients had more symptoms compared to EC (F>4.4). Finally, EC patients showed higher improvements in psychosocial functioning compared to LT and MLT (F=1.8). Conclusions Against common expectations, long-term, more chronically ill patients showed higher effects in basal cognitive functions compared to younger patients and patients without any active therapy (TAU). On the other hand, early-course patients had a greater potential to change in attribution, symptoms and psychosocial functioning. Consequently, more integrated therapy offers are also recommended for long-term course schizophrenia patients.

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In air transportation, airline profitability is influenced by the airline's ability to build flight schedules. In order to generate operational schedules, airlines engage in a complex decision-making process, referred to as airline schedule planning. Up to now, the generation of flight schedules has been separated and optimized sequentially. The schedule design has been traditionally decomposed into two sequential steps. The frequency planning and the timetable development. The purpose of the second problem of schedule development, fleet assignment, is to assign available aircraft types to flight legs such that seating capacity on an assigned aircraft matches closely with flight demand and such that costs are minimized. Our work integrates these planning phases into one single model in order to produce more economical solutions and create fewer incompatibilities between the decisions. We propose an integrated robust approach for the schedule development step. We design the timetable ensuring that enough time is available to perform passengers’ flight connections, making the system robust avoiding misconnected passengers. An application of the model for a simplified IBERIA network is shown.

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Computational fluid dynamic (CFD) methods are used in this paper to predict the power production from entire wind farms in complex terrain and to shed some light into the wake flow patterns. Two full three-dimensional Navier–Stokes solvers for incompressible fluid flow, employing k − ϵ and k − ω turbulence closures, are used. The wind turbines are modeled as momentum absorbers by means of their thrust coefficient through the actuator disk approach. Alternative methods for estimating the reference wind speed in the calculation of the thrust are tested. The work presented in this paper is part of the work being undertaken within the UpWind Integrated Project that aims to develop the design tools for next generation of large wind turbines. In this part of UpWind, the performance of wind farm and wake models is being examined in complex terrain environment where there are few pre-existing relevant measurements. The focus of the work being carried out is to evaluate the performance of CFD models in large wind farm applications in complex terrain and to examine the development of the wakes in a complex terrain environment.

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The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

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The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ?traditional? set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified, easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

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El concepto de funicularidad se puede extender a estructuras lineales espaciales como, por ejemplo, los puentes arco con tablero curvo. Estas estructuras, especialmente pasarelas peatonales, son consecuencia de la necesidad de encajar trazados exigentes y de dar respuesta a nuevas demandas arquitectónicas. En las estructuras curvas el diseño conceptual juega un papel absolutamente esencial. Siempre ha sido así, pero en el caso presente, cabe resaltar que una errónea elección de la geometría conlleva una serie de problemas que se irán acumulando a lo largo del proceso de proyecto, de la construcción y de la vida de la estructura. En este trabajo se presenta SOFIA (Shaping Optimal Form with an Interactive Approach), una herramienta capaz de, conocida la geometría del tablero, de buscar automáticamente la forma del arco antifunicular correspondiente. El planteamiento seguido es conceptualmente el mismo que el utilizado en la búsqueda de formas óptimas en estructuras en dos dimensiones: el arco antifunicular es el que representa, para unas cargas dadas, el lugar geométrico de los puntos con momento flector nulo. La herramienta ha sido desarrollada en un entorno integrado, interactivo y paramético. Su implementación está ilustrada y unos ejemplos de análisis paramétricos están desarrollados. La posición transversal relativa entre tablero y arco ha sido investigada para obtener la configuración del puente estructuralmente más eficiente. Las pasarelas curvas se han convertido en un problema de ingeniería más común de lo habitual en el contexto de los desarrollos urbanos cuando el cliente está buscando un fuerte componente estético: un diseño conceptual adecuado permite obtener una estructura eficiente y elegante. Spatial arch bridges represent an innovative answer to demands on functionality, structural optimization and aesthetics for curved decks, popular in urban contexts. This thesis presents SOFIA (Shaping Optimal Form with an Interactive Approach), a methodology for conceptual designing of antifunicular spatial arch bridges with curved deck in a parametric, interactive and integrated environment. The approach and its implementation are in-depth described and detailed examples of parametric analyses are illustrated. The optimal deck-arch relative transversal position has been investigated for obtaining the most cost-effective bridge. Curved footbridges have become a more common engineering problem in the context of urban developments when the client is looking for a strong aesthetics component: an appropriate conceptual design allows to obtain an efficient and elegant structure.