Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

On nonlinear dynamics in a free fluid surface of a tank excited by a non-ideal power source

We investigate the nonlinear oscillations in a free surface of a fluid in a cylinder tank excited by non-ideal power source, an electric motor with limited power supply. We study the possibility of parametric resonance in this system, showing that the excitation mechanism can generate chaotic response. Additionally, the dynamics of parametrically excited surface waves in the tank can reveal new characteristics of the system. The fluid-dynamic system is modeled in such way as to obtain a nonlinear differential equation system. Numerical experiments are carried out to find the regions of chaotic solutions. Simulation results are presented as phase-portrait diagrams characterizing the resonant vibrations of free fluid surface and the existence of several types of regular and chaotic attractors. We also describe the energy transfer in the interaction process between the hydrodynamic system and the electric motor. Copyright © 2011 by ASME.

Anfis applied to the prediction of surface roughness in grinding of advanced ceramics

This paper introduces a methodology for predicting the surface roughness of advanced ceramics using Adaptive Neuro-Fuzzy Inference System (ANFIS). To this end, a grinding machine was used, equipped with an acoustic emission sensor and a power transducer connected to the electric motor rotating the diamond grinding wheel. The alumina workpieces used in this work were pressed and sintered into rectangular bars. Acoustic emission and cutting power signals were collected during the tests and digitally processed to calculate the mean, standard deviation, and two other statistical data. These statistics, as well the root mean square of the acoustic emission and cutting power signals were used as input data for ANFIS. The output values of surface roughness (measured during the tests) were implemented for training and validation of the model. The results indicated that an ANFIS network is an excellent tool when applied to predict the surface roughness of ceramic workpieces in the grinding process.

Effect of brushing with conventional versus whitening dentifrices on surface roughness and biofilm formation of dental ceramics

The aim of this study was to evaluate the effect of conventional and whitening dentifrices on the weight loss, surface roughness, and early in situ biofilm formation on the surface of dental ceramics. Standardized feldspar ceramic specimens (Vita VM7 and Vita VM13) were submitted to the following experimental conditions: no brushing; brushing without a dentifrice; brushing with a conventional dentifrice; and brushing with a whitening dentifrice. A brushing machine was used to simulate brushing. The mass and surface roughness of all specimens from the test groups were evaluated prior to and after brushing. Ten participants used an oral device for eight hours to evaluate the biofilm formed in situ on the specimens. Scanning electron microscopy was used for qualitative and quantitative analysis of the biofilm. ANOVA and Tukey tests were used to analyze the results of weight loss, surface roughness, and presence of bacteria. A one-way Kruskal-Wallis test was used for bacterial colonization results. For both ceramics, brushing with a whitening dentifrice resulted in weight loss that was significantly greater when compared to brushing without a dentifrice or with a conventional dentifrice. Increased surface roughness was noticed on VM13 ceramic samples with both dentifrices, whereas only conventional dentifrice had a significant effect on the surface roughness of VM7 samples. For both VM7 and VM13, no difference was found between the experimental conditions with regard to the presence or number of bacteria. Cocci and short rods were the predominant microbial morphotypes. Granular or fibrillar acellular material partially covered the specimens. Brushing with a whitening dentifrice resulted in significant weight loss of ceramic restorations, while brushing with both conventional and whitening dentifrices can roughen ceramic surfaces. The increase in roughness was not clinically significant to contribute to increased biofilm formation.