914 resultados para Foundation Restoration Studio Limburg (SRAL)


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This paper demonstrates that for a very general class of monetary models (the Sidrauski type models and the cash-in-advance models), Bailey’s rule to evaluate the welfare efect of infation is in deed accurate. The result applies for any technology or preference, if the long-run capital stock does not depend on the ination rate. In general, a dynamic version of Bailey’s rule is established. In particular, the result extends to models in which there is a banking sector that supplies money substitutes services. A dditionally, it is argued that the relevant money demand concept for this issue- the impact of in ination under welfare- is the monetary base.

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The petrochemical industry has as objective obtain, from crude oil, some products with a higher commercial value and a bigger industrial utility for energy purposes. These industrial processes are complex, commonly operating with large production volume and in restricted operation conditions. The operation control in optimized and stable conditions is important to keep obtained products quality and the industrial plant safety. Currently, industrial network has been attained evidence when there is a need to make the process control in a distributed way. The Foundation Fieldbus protocol for industrial network, for its interoperability feature and its user interface organized in simple configuration blocks, has great notoriety among industrial automation network group. This present work puts together some benefits brought by industrial network technology to petrochemical industrial processes inherent complexity. For this, a dynamic reconfiguration system for intelligent strategies (artificial neural networks, for example) based on the protocol user application layer is proposed which might allow different applications use in a particular process, without operators intervention and with necessary guarantees for the proper plant functioning

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The industrial automation is directly linked to the development of information tecnology. Better hardware solutions, as well as improvements in software development methodologies make possible the rapid growth of the productive process control. In this thesis, we propose an architecture that will allow the joining of two technologies in hardware (industrial network) and software field (multiagent systems). The objective of this proposal is to join those technologies in a multiagent architecture to allow control strategies implementations in to field devices. With this, we intend develop an agents architecture to detect and solve problems which may occur in the industrial network environment. Our work ally machine learning with industrial context, become proposed multiagent architecture adaptable to unfamiliar or unexpected production environment. We used neural networks and presented an allocation strategies of these networks in industrial network field devices. With this we intend to improve decision support at plant level and allow operations human intervention independent

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Foundation Fieldbus Industrial networks are the high standard technology which allows users to create complex control logic and totally decentralized. Although being so advanced, they still have some limitations imposed by their own technology. Attempting to solve one of these limitations, this paper describes how to design a Fuzzy controller in a Foundation Fieldbus network using their basic elements of programming, the functional blocks, so that the network remains fully independent of other devices other than the same instruments that constitute it. Moreover, in this work was developed a tool that aids this process of building the Fuzzy controller, setting the internal parameters of functional blocks and informing how many and which blocks should be used for a given structure. The biggest challenge in creating this controller is exactly the choice of blocks and how to arrange them in order to effectuate the same functions of a Fuzzy controller implemented in other kind of environment. The methodology adopted was to divide each one of the phases of a traditional Fuzzy controller and then create simple structures with the functional blocks to implement them. At the end of the work, the developed controller is compared with a Fuzzy controller implemented in a mathematical program that it has a proper tool for the development and implementation of Fuzzy controllers, obtaining comparatives graphics of performance between both

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The main purpose of this work is to develop an environment that allows HYSYS R chemical process simulator communication with sensors and actuators from a Foundation Fieldbus industrial network. The environment is considered a hybrid resource since it has a real portion (industrial network) and a simulated one (process) with all measurement and control signals also real. It is possible to reproduce different industrial process dynamics without being required any physical network modification, enabling simulation of some situations that exist in a real industrial environment. This feature testifies the environment flexibility. In this work, a distillation column is simulated through HYSYS R with all its variables measured and controlled by Foundation Fieldbus devices

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Industrial automation networks is in focus and is gradually replacing older architectures of systems used in automation world. Among existing automation networks, most prominent standard is the Foundation Fieldbus (FF). This particular standard was chosen for the development of this work thanks to its complete application layer specification and its user interface, organized as function blocks and that allows interoperability among different vendors' devices. Nowadays, one of most seeked solutions on industrial automation are the indirect measurements, that consist in infering a value from measures of other sensors. This can be made through implementation of the so-called software sensors. One of the most used tools in this project and in sensor implementation are artificial neural networks. The absence of a standard solution to implement neural networks in FF environment makes impossible the development of a field-indirect-measurement project, besides other projects involving neural networks, unless a closed proprietary solution is used, which dos not guarantee interoperability among network devices, specially if those are from different vendors. In order to keep the interoperability, this work's goal is develop a solution that implements artificial neural networks in Foundation Fieldbus industrial network environment, based on standard function blocks. Along the work, some results of the solution's implementation are also presented

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The main objective of work is to show procedures to implement intelligent control strategies. This strategies are based on fuzzy scheduling of PID controllers, by using only standard function blocks of this technology. Then, the standardization of Foundation Fieldbus is kept. It was developed an environment to do the necessary tests, it validates the propose. This environment is hybrid, it has a real module (the fieldbus) and a simulated module (the process), although the control signals and measurement are real. Then, it is possible to develop controllers projects. In this work, a fuzzy supervisor was developed to schedule a network of PID controller for a non-linear plant. Analyzing its performance results to the control and regulation problem

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This work considers the development of a filtering system composed of an intelligent algorithm, that separates information and noise coming from sensors interconnected by Foundation Fieldbus (FF) network. The algorithm implementation will be made through FF standard function blocks, with on-line training through OPC (OLE for Process Control), and embedded technology in a DSP (Digital Signal Processor) that interacts with the fieldbus devices. The technique ICA (Independent Component Analysis), that explores the possibility of separating mixed signals based on the fact that they are statistically independent, was chosen to this Blind Source Separation (BSS) process. The algorithm and its implementations will be Presented, as well as the results

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Failures in reforestation are often attributed to nutrient limitation for tree growth. We compared tree performance and nitrogen and phosphorus relations in adjacent mixed-species plantings of contrasting composition, established for forest restoration on Ultisol soil, originally covered by tropical semi-deciduous Atlantic Forest in Southeast Brazil. Nutrient relations of four tree species occurring in both planting mixtures were compared between a legume-dominated, species-poor direct seeding mixture of early-successional species ("legume mixture"), and a species-diverse, legume-poor mixture of all successional groups ("diverse mixture"). After 7 years, the legume mixture had 6-fold higher abundance of N(2)-fixing trees, 177% higher total tree basal area, 22% lower litter C/N, six-fold higher in situ soil resin-nitrate, and 40% lower in situ soil resin-P, compared to the diverse mixture. In the legume mixture, non-N(2)-fixing legume Schizolobium parahyba (Fabaceae-Caesalpinioideae) had significantly lower proportional N resorption, and both naturally regenerating non-legume trees had significantly higher leaf N concentrations, and higher proportional P resorption, than in the diverse mixture. This demonstrate forms of plastic adjustment in all three non-N(2)-fixing species to diverged nutrient relations between mixtures. By contrast, leaf nutrient relations in N(2)-fixing Enterolobium contortisiliquum (Fabaceae-Mimosoideae) did not respond to planting mixtures. Rapid N accumulation in the legume mixture caused excess soil nitrification over nitrate immobilization and tighter P recycling compared with the diverse mixture. The legume mixture succeeded in accelerating tree growth and canopy closure, but may imply periods of N losses and possibly P limitation. Incorporation of species with efficient nitrate uptake and P mobilization from resistant soil pools offers potential to optimize these tradeoffs.

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Image restoration attempts to enhance images corrupted by noise and blurring effects. Iterative approaches can better control the restoration algorithm in order to find a compromise of restoring high details in smoothed regions without increasing the noise. Techniques based on Projections Onto Convex Sets (POCS) have been extensively used in the context of image restoration by projecting the solution onto hyperspaces until some convergence criteria be reached. It is expected that an enhanced image can be obtained at the final of an unknown number of projections. The number of convex sets and its combinations allow designing several image restoration algorithms based on POCS. Here, we address two convex sets: Row-Action Projections (RAP) and Limited Amplitude (LA). Although RAP and LA have already been used in image restoration domain, the former has a relaxation parameter (A) that strongly depends on the characteristics of the image that will be restored, i.e., wrong values of A can lead to poorly restoration results. In this paper, we proposed a hybrid Particle Swarm Optimization (PS0)-POCS image restoration algorithm, in which the A value is obtained by PSO to be further used to restore images by POCS approach. Results showed that the proposed PSO-based restoration algorithm outperformed the widely used Wiener and Richardson-Lucy image restoration algorithms. (C) 2010 Elsevier B.V. All rights reserved.

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Os autores propõem o emprego da neurorrafia término-lateral do coto distal do nervo sural na face lateral do nervo fibular superficial para evitar anestesia ou hipoestesia na face lateral do pé após a retirada do nervo sural para enxertia. A proximidade anatômica entre os nervos em questão tornam o procedimento simples, sem aumentar o tempo cirúrgico. A neurorrafia término-lateral proposta não prejudica as estruturas inervadas pelo nervo doador .

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The present study aimed at reporting a clinical and surgical case of bilateral coronoidectomy, using an intraoral approach. The patient is a 26-year-old man, who sought attendance complaining of a gradual reduction of his oral opening in the past 3 years; however, he had an aggravation in the last 2 months. After clinical examination and imaging evaluation, the diagnosis of coronoid process hyperplasia was confirmed, and the surgical treatment was proposed. Under general anesthesia, with nasotracheal intubation guided by a nasofiberendoscope, using an intraoral approach, the bilateral coronoidectomy was performed. In the immediate postoperative period, an increase of the buccal opening measured 29 mm, representing an enhancement of 11 mm, and in the 30th postoperative day, it measured 31.12 mm. During the clinical follow-up period, a reestablishment of the mandibular movements was observed. Therefore, coronoidectomy by an intraoral approach and the physiotherapy performed in the postoperative period were efficient procedures.

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The transfer of an intraoral implant position to the cast for an immediate loading implant is an important step and may be difficult to achieve with commonly used transfer and impression methods. Thus, the purpose of this report is to describe a technique for the use of a surgical template to transfer the implant position for fabrication of a provisional restoration. This technique simplifies the procedure, eliminates the need for taking an impression, avoids surgical site contamination, and maintains an adequate emergence profile during fabrication of the definitive restoration. An indexing technique for transferring the position of the implant from the treated surface after extraction is described.