Determination of optimal parameters in drilling composite materials to minimize the machining temperature using the Taguchi method

Dental implant is used to replace the natural dental root. The process to fix the dental implant in the maxillary bone needs a previous drilling operation. This machining operation involves the increasing of temperature in the drilled region which can reach values higher than 47°C and for this temperature is possible to occur the osseous necrosis [I]. The main goal of this work is to implement an optimization method to define the optimal drilling parameters that could minimize the drilling temperature. The proposal optimization method is the Taguchi method. This method has been used with success in machining processes optimization of metallic materials [2]. However, the Taguchi method is also used in medical applications, namely in dental medicine [3].

Globally optimal parameters for on-line learning in multilayer neural networks

We present a framework for calculating globally optimal parameters, within a given time frame, for on-line learning in multilayer neural networks. We demonstrate the capability of this method by computing optimal learning rates in typical learning scenarios. A similar treatment allows one to determine the relevance of related training algorithms based on modifications to the basic gradient descent rule as well as to compare different training methods.

Estimation of optimal gravity wave parameters for climate models using data assimilation

There is a current need to constrain the parameters of gravity wave drag (GWD) schemes in climate models using observational information instead of tuning them subjectively. In this work, an inverse technique is developed using data assimilation principles to estimate gravity wave parameters. Because mostGWDschemes assume instantaneous vertical propagation of gravity waves within a column, observations in a single column can be used to formulate a one-dimensional assimilation problem to estimate the unknown parameters. We define a cost function that measures the differences between the unresolved drag inferred from observations (referred to here as the ‘observed’ GWD) and the GWD calculated with a parametrisation scheme. The geometry of the cost function presents some difficulties, including multiple minima and ill-conditioning because of the non-independence of the gravity wave parameters. To overcome these difficulties we propose a genetic algorithm to minimize the cost function, which provides a robust parameter estimation over a broad range of prescribed ‘true’ parameters. When real experiments using an independent estimate of the ‘observed’ GWD are performed, physically unrealistic values of the parameters can result due to the non-independence of the parameters. However, by constraining one of the parameters to lie within a physically realistic range, this degeneracy is broken and the other parameters are also found to lie within physically realistic ranges. This argues for the essential physical self-consistency of the gravity wave scheme. A much better fit to the observed GWD at high latitudes is obtained when the parameters are allowed to vary with latitude. However, a close fit can be obtained either in the upper or the lower part of the profiles, but not in both at the same time. This result is a consequence of assuming an isotropic launch spectrum. The changes of sign in theGWDfound in the tropical lower stratosphere, which are associated with part of the quasi-biennial oscillation forcing, cannot be captured by the parametrisation with optimal parameters.

Optimal perfusion computed tomographic thresholds for ischemic core and penumbra are not time dependent in the clinically relevant time window.

BACKGROUND AND PURPOSE: This study aims to determine whether perfusion computed tomographic (PCT) thresholds for delineating the ischemic core and penumbra are time dependent or time independent in patients presenting with symptoms of acute stroke. METHODS: Two hundred seventeen patients were evaluated in a retrospective, multicenter study. Patients were divided into those with either persistent occlusion or recanalization. All patients received admission PCT and follow-up imaging to determine the final ischemic core, which was then retrospectively matched to the PCT images to identify optimal thresholds for the different PCT parameters. These thresholds were assessed for significant variation over time since symptom onset. RESULTS: In the persistent occlusion group, optimal PCT parameters that did not significantly change with time included absolute mean transit time, relative mean transit time, relative cerebral blood flow, and relative cerebral blood volume when time was restricted to 15 hours after symptom onset. Conversely, the recanalization group showed no significant time variation for any PCT parameter at any time interval. In the persistent occlusion group, the optimal threshold to delineate the total ischemic area was the relative mean transit time at a threshold of 180%. In patients with recanalization, the optimal parameter to predict the ischemic core was relative cerebral blood volume at a threshold of 66%. CONCLUSIONS: Time does not influence the optimal PCT thresholds to delineate the ischemic core and penumbra in the first 15 hours after symptom onset for relative mean transit time and relative cerebral blood volume, the optimal parameters to delineate ischemic core and penumbra.

Towards an Optimal Implementation of Cascade

Cascade is an information reconciliation protocol proposed in the context of secret key agreement in quantum cryptography. This protocol allows removing discrepancies in two partially correlated sequences that belong to distant parties, connected through a public noiseless channel. It is highly interactive, thus requiring a large number of channel communications between the parties to proceed and, although its efficiency is not optimal, it has become the de-facto standard for practical implementations of information reconciliation in quantum key distribution. The aim of this work is to analyze the performance of Cascade, to discuss its strengths, weaknesses and optimization possibilities, comparing with some of the modified versions that have been proposed in the literature. When looking at all design trade-offs, a new view emerges that allows to put forward a number of guidelines and propose near optimal parameters for the practical implementation of Cascade improving performance significantly in comparison with all previous proposals.

Optimal preventive maintenance of leased equipment with corrective minimal repairs

For leased equipment, the lessor carries out the maintenance of the equipment. Usually, the contract of lease specifies the penalty for equipment failures and for repairs not being carried out within specified time limits. This implies that optimal preventive maintenance policies must take these penalty costs into account and properly traded against the cost of preventive maintenance actions. The costs associated with failures are high as unplanned corrective maintenance actions are costly and the resulting penalties due to lease contract terms being violated. The paper develops a model to determine the optimal parameters of a preventive maintenance policy that takes into account all these costs to minimize the total expected cost to the lessor for new item lease. The parameters of the policy are (i) the number of preventive maintenance actions to be carried out over the lease period, (ii) the time instants for such actions, and (iii) the level of action. (c) 2005 Elsevier B.V. All rights reserved.

Effects of Laser on the Synovial Fluid in the Inflammatory Process of the Knee Joint of the Rabbit

Objective: The purpose of this study was to evaluate the effects of low-level laser (LLL) energy on the clinical signs of inflammation and the cellular composition of synovial fluid (SF) in the inflamed knee of the rabbit. Background Data: There are few findings related to the effects of LLL on SF in inflammatory processes and there is little knowledge about the optimal parameters for reducing joint inflammation. Materials and Methods: Inflammation in the right knee of 36 rabbits was induced by intracapsular injection (0.2 mL) of Terebinthina commun (Tc). The animals were randomly assigned to three groups: acute experimental group (AEG), chronic experimental group (CEG), and control group (CG), which only received Tc. Each group was divided in two subgroups of six animals each. The AEG and CEG groups began to receive laser treatment 2 and 5 d after the induction of inflammation, respectively. Laser irradiation at a wavelength of 830 nm, power output of 77 mW, and power density of 27.5 W/cm(2) was applied daily for 7 d for either 0.12 sec or 0.32 sec, resulting in doses of 3.4 J/cm(2) and 8 J/cm(2), respectively. Body mass, joint perimeter, joint temperature, and the morphology of the SF were analyzed. Results: There was no statistically significant differences between groups in the body mass, joint perimeter, and SF morphology. Conclusion: Laser irradiation with the selected parameters produced only a few subtle differences in the inflammatory signs and the SF. The lack of effects may have been due to the short irradiation time.

Viability of fibroblasts cultured under nutritional stress irradiated with red laser, infrared laser, and red light-emitting diode

Phototherapy is noninvasive, painless and has no known side effect. However, for its incorporation into clinical practice, more well-designed studies are necessary to define optimal parameters for its application. The viability of fibroblasts cultured under nutritional stress irradiated with either a red laser, an infrared laser, or a red light-emitting diode (LED) was analyzed. Irradiation parameters were: red laser (660 nm, 40 mW, 1 W/cm(2)), infrared laser (780 nm, 40 mW, 1 W/cm(2)), and red LED (637 +/- 15 nm, 40 mW, 1 W/cm(2)). All applications were punctual and performed with a spot with 0.4 mm(2) of diameter for 4 or 8 s. The Kruskal-Wallis test and analysis of variance of the general linear model (p <= 0.05) were used for statistical analysis. After 72 h, phototherapy with low-intensity laser and LED showed no toxicity at the cellular level. It even stimulated methylthiazol tetrazolium assay (MTT) conversion and neutral red uptake of fibroblasts cultured under nutritional stress, especially in the group irradiated with infrared laser (p = 0.004 for MTT conversion and p < 0.001 for neutral red uptake). Considering the parameters and protocol of phototherapy used, it can be concluded that phototherapy stimulated the viability of fibroblasts cultured under nutritional deficit resembling those found in traumatized tissue in which cell viability is reduced. (C) 2011 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.3602850]

An algorithmic Friedman-Pippenger theorem on tree embeddings and applications

An (n, d)-expander is a graph G = (V, E) such that for every X subset of V with vertical bar X vertical bar <= 2n - 2 we have vertical bar Gamma(G)(X) vertical bar >= (d + 1) vertical bar X vertical bar. A tree T is small if it has at most n vertices and has maximum degree at most d. Friedman and Pippenger (1987) proved that any ( n; d)- expander contains every small tree. However, their elegant proof does not seem to yield an efficient algorithm for obtaining the tree. In this paper, we give an alternative result that does admit a polynomial time algorithm for finding the immersion of any small tree in subgraphs G of (N, D, lambda)-graphs Lambda, as long as G contains a positive fraction of the edges of Lambda and lambda/D is small enough. In several applications of the Friedman-Pippenger theorem, including the ones in the original paper of those authors, the (n, d)-expander G is a subgraph of an (N, D, lambda)-graph as above. Therefore, our result suffices to provide efficient algorithms for such previously non-constructive applications. As an example, we discuss a recent result of Alon, Krivelevich, and Sudakov (2007) concerning embedding nearly spanning bounded degree trees, the proof of which makes use of the Friedman-Pippenger theorem. We shall also show a construction inspired on Wigderson-Zuckerman expander graphs for which any sufficiently dense subgraph contains all trees of sizes and maximum degrees achieving essentially optimal parameters. Our algorithmic approach is based on a reduction of the tree embedding problem to a certain on-line matching problem for bipartite graphs, solved by Aggarwal et al. (1996).

Instrumented indentation testing of an epoxy adhesive used in automobile body assembling

Instrumented indentation has been used to investigate the mechanical properties of BETAMATE 1496 (R) Epoxy adhesive. The properties of the adhesive were analyzed by measuring its hardness and its Young`s modulus in samples extracted from six different positions of the front door of a commercial passenger vehicle in two phases of processing: after application of the adhesive in the door assembling (""pre-cured"" state) and after final cure in the painting oven (""cured"" state). Special attention was given to setting the optimal parameters (""creep"" time and unloading time step) for the instrumented indentation testing for the present application. Young`s modulus values around 1.1 +/- 0.2 GPa and hardness values around 0.15 +/- 0.05 GPa were obtained for all samples, irrespective of the variation of the indentation parameters in the testing procedure and of the relative position of the adhesive in the door frame in both states. (C) 2008 Elsevier Ltd. All rights reserved.

Protein fold recognition without Boltzmann statistics or explicit physical basis

We present a fast method for finding optimal parameters for a low-resolution (threading) force field intended to distinguish correct from incorrect folds for a given protein sequence. In contrast to other methods, the parameterization uses information from >10(7) misfolded structures as well as a set of native sequence-structure pairs. In addition to testing the resulting force field's performance on the protein sequence threading problem, results are shown that characterize the number of parameters necessary for effective structure recognition.

Monitorização de desreguladores endócrinos em águas

Da crescente necessidade de alimentos e da necessidade de travar a destruição de culturas por animais e insectos foram sintetizados os pesticidas. Por entre uma vasta gama de pesticidas alguns são desreguladores endócrinos o que se traduz num perigo para a saúde humana pois pode despoletar alterações nos seres vivos mesmo em concentrações muito baixas. Devido a diversos factores nomeadamente a lixiviação, ventos e outros agentes ambientais assim como a presença de terrenos agrícolas junto a diversos rios, estes encontram-se contaminados com pesticidas desreguladores endócrinos. O objectivo deste trabalho foi avaliar quais os pesticidas desreguladores endócrinos presentes nas águas de rios da região Norte. Neste trabalho utilizou-se a técnica de microextracção em fase sólida recorrendo a uma fibra de PDMS (100 μm). Para tal as condições de optimização foram testadas nomeadamente a quantidade de NaCl, quantidade de metanol, temperatura do injector e tempo de exposição. Os parâmetros obtidos óptimos foram 0 % de NaCl, tempo de exposição de 45 min, temperatura do injector de 260 ºC e 2,5 % de metanol. Conseguiu-se a separação de todos os pesticidas desreguladores endócrinos com a seguinte programação temperaturas: inicio a 60ºC por um minuto seguido de um aumento de 20 °C/min até aos 200 °C onde permanece por um minuto e de seguida um aumento de 5 °C/min até aos 245 °C onde permanece por 40 min. Fizeram-se curvas de calibração entre 0,01 μg/L e 10 μg/L. Constatou-se no entanto uma falta de reprodutibilidade entre as injecções utilizando esta técnica. Os rios analisados foram o Rio Douro, Rio Tâmega, Ria de Aveiro, Rio Lima, Rio Minho, Rio Sousa, Rio Águeda, Rio Cávado e Rio Leça. No Rio Tâmega foram encontrados os seguintes pesticidas: diazinão, α-HCH, β-HCH, δ-HCH, lindano, HCB, simazina/ atrazina, vinclozolina, alacloro, 2,4-D, malatião, aldrina, bifentrina, metoxicloro e fenvalerato. No rio Douro estão presentes HCB, simazina/ atrazina, vinclozolina, 2,4-D, malatião, aldrina, fenvalerato e deltametrina. No rio Lima encontra-se diazinão, α-HCH, δ-HCH, 2,4-D, HCB, vinclozolina, lindano, simazina/atrazina, alacloro, malatião, aldrina, fenvalerato e deltametrina. No rio Sousa os pesticidas encontrados foram: diazinão, HCB, aldrina, α-HCH, β-HCH, δ-HCH, lindano, simazina/ atrazina, 2,4-D, cipermetrina, alacloro, fenvalerato e malatião. No rio Cávado estão presentes o diazinão, α-HCH, β-HCH, δ-HCH, lindano, HCB, 2,4-D, malatião, metoxicloro, cipermetrina e o fenvalerato. Na ria de Aveiro encontrou-se o diazinão, α-HCH, β-HCH, δ-HCH, lindano, HCB, simazina/atrazina, 2,4-D, Malatião e aldrina. No rio Águeda estão presentes o diazinão, HCB, 2,4-D, aldrina e malatião. E por último no rio Leça esta presente o diazinão, 2,4-D, alacloro, malatião, aldrina, cipermetrina e fenvalerato. A importância deste trabalho reside na demonstração da presença destes pesticidas, desreguladores endócrinos nas águas superficiais da região Norte.

Modelação de células de combustível

Neste trabalho serão apresentados e discutidos vários aspectos relacionados com células de combustível, com particular enfoque na modelação de células de combustível de membrana de permuta protónica. Este trabalho está dividido em vários capítulos. No Capítunlo 1 são apresentadas as motivações e os objectivos da tese. No Capítulo 2 serão apresentadas as células de combustível em geral, a sua origem, os diversos tipos, o que as diferencia das restantes tecnologias de geração de energia e as suas vantagens e desvantagens. No Capítulo 3 discute-se a modelação de células de combustível. Serão expostos e explicados os diferentes tipos de modelos, seguindo-se uma apresentação do modelo selecionado para estudo, com referência aos fundamentos teóricos exposição detalhada da fórmulação matemática e os parâmetros que caracterizam o modelo. É também apresentado a implementação do modelo em Matlab/Simulink. No Capítulo 4 será discutida e apresentada a abordagem utilizada para a identificação dos parâmetros do modelo da célula de combustível. Propõe-se e prova-se que uma abordagem baseada num algoritmo de optimização inteligente proporciona um método eficaz e preciso para a identificação dos parâmetros. Esta abordagem requer a existência de alguns dados experimentais que são também apresentados. O algoritmo utilizado designa-se por Optimização por Enxame de Partículas – Particle Swarm Optimization (PSO). São apresentados os seus fundamentos, características, implementação em Matlab/Simulink e a estratégia de optimização, isto é, a configuração do algoritmo, a definição da função objectivo e limites de variação dos parâmetros. São apresentados os resultados do processo de optimização, resultados adicionais de validação do modelo, uma análise de robustez do conjunto óptimo de parâmetros e uma análise de sensibilidade dos mesmos. O trabalho termina apresentando, no último capítulo, algumas conclusões, das quais se destacam: - O bom desempenho do algoritmo PSO para a identificação dos parâmetros do modelo da célula de combsutível; - Uma robustez interessante do algoritmo PSO, no sentido em que, para várias execuções do método resultam valores do parâmetros e da função objectivo com variabilidade bastante reduzidas; - Um bom modelo da célula de combustível, que quando caracterizado pelo conjunto óptimo de parâmetros, apresenta, sistematicamente, erros relativos médios inferiores a 2,5% para um conjunto alargado de condições de funcionamento.

A literature review on the optimization of legged robots

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.