UWB body area network channel modeling: An analytical approach

The aim of this work is to develop an analytically-based approach for ultra wide band (UWB) body area network (BAN) channel modeling. In detail, the body will be modeled as multi-layered stratified cylinders of infinite length, and the Maxwell's equation will be solved for plane wave and line source excitations. Human-type tissues will be assumed in the multi-layered stratified cylindrical model. Validation of the procedure through measurement results has been provided.     

Regioselective synthesis of new 5-methyl-5H-pyrimido[4′,5′:4,5][1,3]thiazino [3,2-a]perimidines

A convenient and efficient regioselective synthesis of new pyrimido[4′,5′:4,5] [1,3]thiazino[3,2-a]perimidines is described through intermolecular heterocyclization of 2,4-dichloro-5-(chloromethyl)-6-methylpyrimidine and 1H-perimidine-2(3H)-thione in short reaction times under mild conditions.     

Filtered gradient active fuzzy neural network noise control in an enclosure backed by a clamped plate

The performance of conventional linear algorithms in active noise control applications deteriorates facing nonlinearities in the system mainly because of loudspeakers. On the other hand, fuzzy logic and neural networks are good candidates to overcome this drawback. In this paper, the acoustic attenuation of noise in a rectangular enclosure with a flexible panel and five rigid walls is presented both theoretically and experimentally using filtered gradient fuzzy neural network (FGFNN) error back propagation algorithm in which the secondary path effect is implemented in derivation of updating rules. Considering this effect in updating rules leads to faster convergence and stability of the active noise control system. On the other hand, the primary path in the investigated system comprises an identified nonlinear model of loudspeaker inside the aforementioned box, parameters of which vary with the input current. The loudspeaker is identified using series‐parallel neural network model identification method. As a comparison, the performance of filtered‐x least mean squares and FGFNN algorithms are compared. It is observed that FGFNN controller exhibits far better results in the presence of loudspeakers with nonlinear behavior in primary path.Copyright © 2012 John Wiley & Sons, Ltd.     

Open-celled microcellular foaming and the formation of cellular structure by a theoretical pattern in polystyrene

An open-celled structure was produced using polystyrene and supercritical carbon dioxide in a novel batch process. The required processing conditions to achieve open-celled structures were predicted by a theoretical model and confirmed by the experimental data. The theoretical model predicts that at least a saturation pressure of 130 bar and a foaming time between 9 and 58 s are required for this system to produce an open-celled structure. The foaming temperature range has been selected to be higher than the polymer glass transition temperature yet not higher than a temperature limit where the gas starts leaving the system. The experimental results in the batch foaming process verified the model substantially. The SEM pictures showed the presence of pores between the cells, and the mercury porosimetry test results verified the overall open-celled structure. Experimental results also showed that by increasing the saturation pressure and the foaming temperature, there was a drop in the time required for open-celled structure formation. At saturation pressure of 130 bar, foaming temperature of 150 °C and a foaming time of 60 s, open-celled microcellular polystyrene foams were obtained using supercritical CO₂ in the batch process. Based on the results, a schematic diagram, depicting the process of foam structure formation from nucleation to bubble coalescence and gas escape from polymer, was proposed. Theoretical calculations showed that by increasing foaming time, cell size was increased and cell density was reduced and the experimental results verified this prediction.     

Wavelet-based ultra wideband pulse generator circuits

Aiming to generate ultra wideband (UWB) pulses based on wavelet packets, four different circuits are proposed. It has been shown that the wavelet packets are quasi-orthogonal and have almost identical time duration, and therefore appear to be valuable candidates for UWB pulse shape modulation systems. However, as with any technology, circuitry is an important challenge to solve before a theoretical application can live up to its full potential. The four proposed circuits are based on different interpretations of the equation defining the wavelet packets and their performance is investigated by computer simulation. The research also illustrates the characteristics and the consequent implementation advantages or issues afferent to each circuit.     

Automatic selection and fusion of color spaces for image thresholding

Automatic selection of color models has a great significance for machine vision purposes like image segmentation, object recognition, etc. Typically, selection of a proper color model is a problem that can just solve by testing the models on the target one by one. To achieve a proper color model, in this article, we propose a new method which is shaped on the basis of clustering and relation among models. The proposed method is verified experimentally for two different images (in thresholding purpose). The experimental results show that this method has a suitable power for automatic purposes.     

Pyroelectric energy converter for harvesting waste heat: Simulations versus experiments

This paper is concerned with numerical simulations of a pyroelectric converter for direct energy conversion of waste heat into electricity. The simulated prototypical device consisted of a hot and cold source separated by a series of vertical microchannels supporting pyroelectric thin films made of co-polymer P(VDF-TrFE) and undergoing the Olsen cycle. A piston was used to vertically oscillate a working fluid back and forth between the thermal sources. The experimental device was instrumented with thermocouples and a pressure sensor. The two-dimensional transient mass, momentum, and energy equations were solved numerically using finite element methods to determine the local and time-dependent temperature at various locations inside the device microchannels. The operating frequency varied from 0.025 to 0.123 Hz and the working fluid was 1.5 or 50 cSt silicone oil. Good agreement was found between the simulated and experimentally measured local mean temperatures for both working fluids at all operating frequencies considered. The local temperature swings were underestimated slightly for 50 cSt silicone oil and significantly more for 1.5 cSt silicone oil. Overall, this study confirms our previous numerical results. Moreover, this numerical model could be used to design and operate the next generation of pyroelectric energy converters based on oscillatory convective heat transfer.     

Experimental investigation,modeling and optimization of membrane separation using artificial neural network and multi-objective optimization using genetic algorithm

In this work, treatment of oily wastewaters with commercial polyacrylonitrile (PAN) ultrafiltration (UF) membranes was investigated. In order to do these experiments, the outlet wastewater of the API (American Petroleum Institute) unit of Tehran refinery, is used as the feed. The purpose of this paper was to predict the permeation flux and fouling resistance, by applying artificial neural networks (ANNs), and then to optimize the operating conditions in separation of oil from industrial oily wastewaters, including trans-membrane pressure (TMP), cross-flow velocity (CFV), feed temperature and pH, so that a maximum permeation flux accompanied by a minimum fouling resistance, was acquired by applying genetic algorithm as a powerful soft computing technique. The experimental input data, including TMP, CFV, feed temperature and pH, permeation flux and fouling resistance as outputs, were used to create ANN models. This fact that there is an excellent agreement between the experimental data and the predicted values was shown by the modeling results. Eventually, by multi-objective optimization, using genetic algorithm (GA), an optimization tool was created to predict the optimum operating parameters for desired permeation flux (i.e. maximum flux) and fouling resistance (i.e. minimum fouling) behavior. The accuracy of the model is confirmed by the comparison between the predicted and experimental data.     

Semantic image classification by genetic algorithm using optimised fuzzy system based on Zernike moments

Image classification is a challenging problem of computer vision. This study reports a fuzzy system to semantic image classification. As it is a complex task, various information of digital image, including three color space components and two Zernike moments with different order, are gathered and utilized as an input of fuzzy inference system to materialize a robust rotation/lighting condition and size invariant image classifier. For better performance, all the membership functions are optimized by genetic algorithm after empirical design stage. 90.62 and 96.25 % classification rates for RGB and HSI color spaces confirm the reliability of optimized system in different image conditions given in this contribution.