Cache and replica lookup, indexing and synchronization in P2P environments

The major outcomes of this research project were the development of a set of decentralized algorithms to index, locate and synchronize replicated information in a networked environment. This study exploits the application specific design constraints of networked systems to improve performance, instead of relying on data structures and algorithms best suited to centralized systems.

Selecting the individual numerical scale and prioritization method in the analytic hierarchy process : a 2-tuple fuzzy linguistic approach

The validity of the priority vector used in the analytic hierarchy process (AHP) relies on two factors: the selection of a numerical scale and the selection of a prioritization method. The traditional AHP selects only one numerical scale (e.g., the Saaty scale) and one prioritization method (e.g., the eigenvector method) for each particular problem. For this traditional selection approach, there is disagreement on which numerical scale and prioritization method is better in deriving a priority vector. In fact, the best numerical scale and the best prioritization method both rely on the content of the pairwise comparison data provided by the AHP decision makers. By defining a set of concepts regarding the scale function and the linguistic pairwise comparison matrices (LPCMs) of the priority vector and by using LPCMs to unify the format of the input and output of AHP, this paper extends the AHP prioritization process under the 2-tuple fuzzy linguistic model. Based on the extended AHP prioritization process, we present two performance measure criteria to evaluate the effect of the numerical scales and prioritization methods. We also use the performance measure criteria to develop a 2-tuple fuzzy linguistic multicriteria approach to select the best numerical scales and the best prioritization methods for different LPCMs. In this paper, we call this type of selection the individual selection of the numerical scale and prioritization method. We also compare this individual selection with traditional selection by using both random and real data and show better results with individual selection.

A novel defect detection and identification method in optical inspection

Optical inspection techniques have been widely used in industry as they are non-destructive. Since defect patterns are rooted from the manufacturing processes in semiconductor industry, efficient and effective defect detection and pattern recognition algorithms are in great demand to find out closely related causes. Modifying the manufacturing processes can eliminate defects, and thus to improve the yield. Defect patterns such as rings, semicircles, scratches, and clusters are the most common defects in the semiconductor industry. Conventional methods cannot identify two scale-variant or shift-variant or rotation-variant defect patterns, which in fact belong to the same failure causes. To address these problems, a new approach is proposed in this paper to detect these defect patterns in noisy images. First, a novel scheme is developed to simulate datasets of these 4 patterns for classifiers' training and testing. Second, for real optical images, a series of image processing operations have been applied in the detection stage of our method. In the identification stage, defects are resized and then identified by the trained support vector machine. Adaptive resonance theory network 1 is also implemented for comparisons. Classification results of both simulated data and real noisy raw data show the effectiveness of our method.

A simple and effective method to ameliorate the interfacial properties of cellulosic fibre based bio-composites using poly (ethylene glycol) based amphiphiles

In order to overcome interfacial incompatibility issues in natural fibre reinforced polymer bio-composites, surface modifications of the natural fibres using complex and environmentally unfriendly chemical methods is necessary. In this paper, we demonstrate that the interfacial properties of cellulose-based bio-composites can be tailored through surface adsorption of polyethylene glycol (PEG) based amphiphilic block copolymers using a greener alternative methodology. Mixtures of water or water/acetone were used to form amphiphilic emulsions or micro-crystal suspensions of PEG based amphiphilic block copolymers, and their deposition from solution onto the cellulosic substrate was carried out by simple dip-coating. The findings of this study evidence that, by tuning the amphiphilicity and the type of building blocks attached to the PEG unit, the flexural and dynamic thermo-mechanical properties of cellulose-based bio-composites comprised of either polylactide (PLA) or high density polyethylene (HDPE) as a matrix, can be remarkably enhanced. The trends, largely driven by interfacial effects, can be ascribed to the combined action of the hydrophilic and hydrophobic components of these amphiphiles. The nature of the interactions formed across the fibre-matrix interface is discussed. The collective outcome from this study provides a technological template to significantly improve the performance of cellulose-based bio-composite materials.

Constructing optimal prediction intervals by using neural networks and bootstrap method

This brief proposes an efficient technique for the construction of optimized prediction intervals (PIs) by using the bootstrap technique. The method employs an innovative PI-based cost function in the training of neural networks (NNs) used for estimation of the target variance in the bootstrap method. An optimization algorithm is developed for minimization of the cost function and adjustment of NN parameters. The performance of the optimized bootstrap method is examined for seven synthetic and real-world case studies. It is shown that application of the proposed method improves the quality of constructed PIs by more than 28% over the existing technique, leading to narrower PIs with a coverage probability greater than the nominal confidence level.

Consensus building in a local context for the AHP-GDM with the individual numerical scale and prioritization method

The methodology for selecting the individual numerical scale and prioritization method has recently been presented and justified in the analytic hierarchy process (AHP). In this study, we further propose a novel AHP-group decision making (GDM) model in a local context (a unique criterion), based on the individual selection of the numerical scale and prioritization method. The resolution framework of the AHP-GDM with the individual numerical scale and prioritization method is first proposed. Then, based on linguistic Euclidean distance (LED) and linguistic minimum violations (LMV), the novel consensus measure is defined so that the consensus degree among decision makers who use different numerical scales and prioritization methods can be analyzed. Next, a consensus reaching model is proposed to help decision makers improve the consensus degree. In this consensus reaching model, the LED-based and LMV-based consensus rules are proposed and used. Finally, a new individual consistency index and its properties are proposed for the use of the individual numerical scale and prioritization method in the AHP-GDM. Simulation experiments and numerical examples are presented to demonstrate the validity of the proposed model.

Leakage Detection And Localization Method Based On A Hybrid Inverse/Direct Modelling Approach Suitable For Handling Multiple-Leak Scenarios

When an accurate hydraulic network model is available, direct modeling techniques are very straightforward and reliable for on-line leakage detection and localization applied to large class of water distribution networks. In general, this type of techniques based on analytical models can be seen as an application of the well-known fault detection and isolation theory for complex industrial systems. Nonetheless, the assumption of single leak scenarios is usually made considering a certain leak size pattern which may not hold in real applications. Upgrading a leak detection and localization method based on a direct modeling approach to handle multiple-leak scenarios can be, on one hand, quite straightforward but, on the other hand, highly computational demanding for large class of water distribution networks given the huge number of potential water loss hotspots. This paper presents a leakage detection and localization method suitable for multiple-leak scenarios and large class of water distribution networks. This method can be seen as an upgrade of the above mentioned method based on a direct modeling approach in which a global search method based on genetic algorithms has been integrated in order to estimate those network water loss hotspots and the size of the leaks. This is an inverse / direct modeling method which tries to take benefit from both approaches: on one hand, the exploration capability of genetic algorithms to estimate network water loss hotspots and the size of the leaks and on the other hand, the straightforwardness and reliability offered by the availability of an accurate hydraulic model to assess those close network areas around the estimated hotspots. The application of the resulting method in a DMA of the Barcelona water distribution network is provided and discussed. The obtained results show that leakage detection and localization under multiple-leak scenarios may be performed efficiently following an easy procedure.

A Higher order and stable method for the numerical integration of Random Differential Equations

Trabalho apresentado no Congresso Nacional de Matemática Aplicada à Indústria, 18 a 21 de novembro de 2014, Caldas Novas - Goiás

A rapid, environmentally friendly, and reliable method for pesticide analysis in high-fat samples

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of Surface Hydration and Application Method on the Bond Strength of Self-Etching Adhesives to Dentin

The effect of application methods and dentin hydration on the bond strength of three self-etching adhesives (SEA) were evaluated; 195 extracted bovine incisors were used. The buccal surface was ground in order to expose the dentin, which remained 2-mm minimum thickness, measured by a thickness meter through an opening on the lingual surface. Adper Single Bond 2 (TM) was used for the control group. The SEA were applied following two modes of application: passive or active and two hydration states of the dentin surface-dry and wet. After light-curing, composite buildups were made using Grandio (TM) composite. The specimens were sectioned and tested with a microtensile bond strength test. The application method and the hydration state resulted in statistical differences (p = 0.000) making the values of active application for mu TBS to dentin higher than passive application. The wet surfaces showed higher mu TBS to dentin ratios than dry surfaces. There were no statistical differences in mu TBS among the SEA tested but there were differences regarding to control group.

Effects of Surface Hydration State and Application Method on the Bond Strength of Self-etching Adhesives to Cut Enamel

Purpose: To evaluate the effect of surface hydration state and application method on the microtensile bond strength of one-step self-etching adhesives systems to cut enamel.Materials and Methods: One hundred ninety-five bovine teeth were used. The enamel on the buccal side was flattened with 600-grit SiC paper. For the control group, 15 teeth received Adper Single Bond 2, applied according to manufacturer's recommendations. The other specimens were divided into three groups according to the adhesive system used: Futura Bond M (FM; Voco), Clearfil S-3 Bond (CS; Kuraray), and Optibond All in One (OA; Kerr). For each group, two hydration states were tested: D: blown dry with air; W: the excess of water was removed with absorbent paper. Two application methods were tested: P (passive): the adhesive was simply left on the surface; A (active): the adhesive was rubbed with an applicator point. A coat of Grandio composite resin (Voco) was applied on the surface. The teeth were sectioned to obtain enamel-resin sticks (1 x 1 mm), which underwent microtensile bond testing. The data in MPa were submitted to a three-way ANOVA and Tukey's test (alpha = 5%).Results: The ANOVA showed significant differences for application method and the type of adhesive, but not for hydration state. For the application method, the results of Tukey's test were: P: 31.46 (+/-7.09)a; A: 34.04 (+/-7.19)b. For the type of adhesive, the results were: OA: 31.29 (+/-7.05)a; CS: 32.28 (+/-7.14)a; FM: 34.68 (+/-7.17)b; different lower-case letters indicate statistically significant differences.Conclusion: Active application improved the bond strength to cut enamel. The adhesive Futurabond M showed the highest bond strength to cut enamel.

A Simple and Fast Method for the Production and Characterization of Methylic and Ethylic Biodiesels from Tucum Oil via an Alkaline Route

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)