Effect of illumination,noise and text/background colour on spontaneous eye blink rate

This study investigated the effect of varying levels of illumination, noise and colour combination on blink rate for subjects of different age groups (21–30, 31–40 and 41–50 years) having Internet exposure duration of less than 2 h/day (category 1) and more than 2 h/day (category 2). The pseudo reading task was designed as a software program to investigate the reading task performance. Results showed that the text–background colour combination was significant on the change in spontaneous eye blink rate (SEBR) values on both categories of users for age groups of 21–30 and 41–50 years. The effects of illumination and noise were not significant for subjects of all categories and age levels except for age group of 31–40 years with Internet exposure duration of more than 2 h/day, where illumination was observed to be significant. The results of the study further showed that ambient illumination did not affect significantly the SEBR values for every age group investigated in this research.     

Efficient exponentiation using weakly dual basis

A new architecture for finite field exponentiation using weakly dual bases is presented. An extended bidirectional linear feedback shift register is designed to multiply an arbitrary field element with certain essential multiplicands in weakly dual basis (WDB). Each of these multiplications is done in one single clock cycle. It is shown that a bit parallel implementation of the WDB fourth power has complexities comparable to those of polynomial basis fourth power. The proposed structure can effectively speed up the computation of exponentiation and is expected to reduce the power consumption compared to the conventional square and multiply scheme. Compared to the structure for polynomial basis exponentiation, the new structure is thus advantageous in a system where the WDB is already available     

Forecasting nitrogen dioxide concentration in ambient air using artificial Neural‐networks

Artificial Neural‐networks is employed to predict the nitrogen dioxide concentration during November, 1997 to February, 1998 at three sites each representing industrial, commercial and residential activity respectively in Mumbai. The application of the Multilayer Recurrent network with back‐propagation learning algorithm is reported in the prediction at three sites using the meteorological variables at one site. The generalization ability of the model is confirmed by root mean square error and correlation between observed and predicted concentrations. The evaluation of model results shows that the degree of success in forecasting NO₂ concentration is promising.     

Uniform and Non-uniform Thermoelement Subject to Lateral Heat Convection

A general energy equation of quasi-one-dimensional heat flow in a longitudinal thermoelement (TE) of a curved side that is subjected to an electric field and convection heat transfer on the curved surface is developed. The energy equation is solved for the temperature distribution in two cases; uniform cross-section TE and non-uniform cross-section TE. Analytical solutions for a uniform cross-section TE with uniform electrical and thermophysical properties are obtained, whereas numerical solutions are provided for a non-uniform cross-section TE. Two parameters playing a vital role in the thermal performance of the TE are identified: the heat resistance ratio (HRR) and the energy growing ratio (EGR). The HRR represents the ratio of the longitudinal conduction maximum thermal resistance to the lateral convection maximum thermal resistance. The EGR represents the ratio of Joule’s electrical heating to Fourier’s heat conduction. The effects of varying these two parameters, as well as the TE geometry, have been thoroughly investigated.     

Fingerprint image enhancement and recognition algorithms: a survey

Fingerprint systems have received a great deal of research and attracted many researchers’ effort since they provide a powerful tool for access control and security and for practical applications. A literature review of the techniques used to extract the features of fingerprint as well as recognition techniques is given in this paper. Some of the reviewed research articles have used traditional methods such as recognition techniques, whereas the other articles have used neural networks methods. In addition, fingerprint techniques of enhancement are introduced.     

New perspectives on capturing particle agglomerates in CFD modeling of spray dryers

Abstract

Current computational fluid dynamic (CFD) models of spray dryers lack the capability to predict the structure of the agglomerates formed; loose or compact agglomerates. This is mainly due to the conventional simplistic approach in numerically “fusing” of the colliding particles forming the agglomerate. A new theoretical treatment is introduced in this work, suitable for implementation in CFD simulations, which numerically fuses the particles and yet retain information on the structure of the agglomerate. This new theoretical treatment is based on tracking the reduction of the agglomerate surface area as the agglomerate is progressively formed. Analysis revealed that the reduction in the agglomerate surface area exhibits a unified correlation with the degree of compactness of the agglomerate. Further analysis comparing this new approach to the conventional numerical fusing of the particles revealed inherent numerical discrepancies, which has not been noted in the literature before. Understanding these discrepancies will provide clarity to the interpretation of the modelling and simulation of spray drying particle agglomeration in CFD. Moreover, this work lays the groundwork for a more comprehensive CFD model for agglomeration which can be potentially utilized to predict final powder properties.     

Characterization investigations of ZrB2/ZrC ceramic powders synthesized by mechanical alloying of elemental Zr,B and C blends

ZrB₂/ZrC ceramic powders were fabricated by mechanical alloying (MA) of zirconium (Zr), amorphous boron (B) and graphite (C) powder blends prepared in the mole ratios of Zr/B/C: 1/1/1, 1/2/1, 1/1/2, 1/2/2 and 2/2/1. MA runs were carried out in a vibratory ball mill using hardened steel vial/balls. The effects of Zr/B/C mole ratios and milling duration on the formation and microstructure of ZrB₂/ZrC ceramic powders were examined. Gibbs free energy change-temperature relations of the reactions and moles of the products were interpreted by thermochemical software. Zr/B/C: 1/1/1, 1/2/1, 1/1/2 and 1/2/2 powder blends MA’d for 2 and 3 h contain unreacted Zr and C, ZrB₂, ZrC and B₄C particles. Synthesis of ZrB₂/ZrC ceramic powders was completely accomplished after MA of Zr/B/C: 2/2/1 powder blend for 2 h. ZrC and ZrB₂ particles were obtained ranging in size between 50 and 250 nm in the presence of FeB contamination (<1 wt.%).     

Intestinal broiler microflora estimation by artificial neural network

Microflora population of poultry was affected by various factors. Many methods and techniques were developed to study microflora population. But, most of them confronted some problems. Moreover, being costly, laborious, and time-consuming made it impossible to measure microflora population several times. In this study, we tried to estimate intestinal microflora population using artificial neural network (ANN). Lactic acid bacteria were used as model of microflora population. Time and lactic acid bacteria were used as input and output variables, respectively. The best model of ANN was determined based on coefficient of determination, root mean square error, and mean absolute error criteria. The results of current study have shown that ANN is appropriate, cheap, and reliable tools to estimate intestinal microflora population (lactic acid bacteria) of broiler at different ages.