An ERP software selection process with using artificial neural network based on analytic network process approach

An enterprise resource planning (ERP) software selection is known to be multi attribute decision making (MADM) problem. This problem has been modeled according with analytic network process (ANP) method due to fact that it considers criteria and sub criteria relations and interrelations in selecting the software.Opinions of many experts are obtained while building ANP model for the selection ERP then opinions are reduced to one single value by methods like geometric means so as to get desired results. To use ANP model for the selection of ERP for a new organization, a new group of expert’s opinions are needed. In this case the same problem will be in counter. In the proposed model, when ANP and ANN models are setup, an ERP software selection can be made easily by the opinions of one single expert. In that case calculation of geometric mean of answers that obtained from many experts will be unnecessary. Additionally the effect of subjective opinion of one single decision maker will be avoided. In terms of difficulty, ANP has some difficulties due to eigenvalue and their limit value calculation.An ANN model has been designed and trained with using ANP results in order to calculate ERP software priority. The artificial neural network (ANN) model is trained by results obtained from ANP. It seems that there is no any major difficulty in order to predict software priorities with trained ANN model. By this results ANN model has been come suitable for using in the selection of ERP for another new decision.     

Magnetic Properties of Zn1?x Ni x O (0.25≤x≤ 0.50) Prepared by Solid-State Reactions

In this study the origin of ferromagnetism in ZnO-based bulk systems has been investigated using Ni-doped ZnO samples, Zn_1−x Ni _x O with 0.25≤x≤0.50, prepared by solid-state reactions. The structural characterizations indicated that the Ni²⁺ ions almost uniformly distributed in all the samples, and the samples have hexagonal wurtzite structure; however, when x is increased toward 0.50, a new NiO phase is formed. A ferromagnetism (FM) has been observed for all the samples at and below the room temperature. In other words, the room temperature results of (M–H) curves show that the FM observed is intrinsic for all the Ni-doped ZnO samples. However, the saturated magnetizations decrease gradually with increasing Ni concentration. This indicates that, in addition to FM, the excessive doping of Ni in ZnO also causes an antiferromagnetic (AFM) contribution which increases with increasing Ni amount. This result is also supported by the magnetization against temperature measurements. Furthermore, the trend of the ac-susceptibility (χ) versus temperature curves, measured under an ac-magnetic field of 100 Oe, also support our conclusion about the antiferromagnetic contribution to ferromagnetism in our samples.     

Reflective light modulator based on epsilon-GaSe crystal

We report the results of investigating a low-voltage, polarization-insensitive, reflective-type modulator based on an epsilon-GaSe crystal and operated at the 1.960-eV line of a He-Ne laser. We demonstrate that the modulation in an Al-epsilon-GaSe-Cu device results mainly from the Franz-Keldysh effect. Relatively high speed and low operating voltage could make these modulators with Schottky-barrier contacts attractive devices in the red range of the spectrum.     

Thermal-tempering analysis of bulk metallic glass plates using an instant-freezing model

The viscoelastic nature of bulk metallic glasses (BMGs), their low thermal conductivity, and the fast cooling used in their processing subject them to thermal tempering. This process leads to a residual stress state in which compression on the surface is balanced by tension in the interior. For the first time, we have calculated such stresses in metallic glasses by adapting an analytical instant-freezing model previously developed for silicate glasses. This model has been demonstrated to be reasonably accurate in predicting the final residual stresses, although, due to its very nature, it neglects transient effects. For an infinite plate geometry and employing processing parameters often used for metallic glasses, we predict that significant residual stresses can be generated in these materials during thermal tempering. Preliminary measurements conducted using the layer-removal method yield compressive residual stress values close to model predictions.     

Cyanide ions transport from aqueous solutions by using quaternary ammonium salts through bulk liquid membranes

Extraction experiments were carried out to determine the suitable solvent and carrier type. Five different solvents and carriers were used and verified. Trichloromethane and tetraoctyl ammonium chlorides were found to be the most appropriate solvent and carrier type for this study. The coupled transport of cyanide ions in aqueous solutions through bulk liquid membrane (BLM) was investigated using various stirring speeds and temperatures. Cyanide ion transport through BLM technique was analyzed according to coupled non-steady state kinetics of two consecutive irreversible first order reactions. The influences of the kinetic parameters (k_1d, k_2m, k_2a, R_m^max, t_max, J_d^max, J_a^max) for the various stirring speeds in the system were established. The removal and recovery efficiencies of the cyanide ions transported from aqueous solutions in 360 min were 99.4 and 82%, respectively. As the stirring speed was increased, both the efficiency of transport and recovery of cyanide ions from aqueous solutions were increased. On the other hand, for maximum membrane entrance (J_d^max) and exit (J_a^max) fluxes the activation energies were calculated as 21.6 kcal/mol and 10.5 kcal/mol, respectively.     

Adsorption of reactive dyes from aqueous solutions by fly ash: kinetic and equilibrium studies

Adsorption kinetic and equilibrium studies of three reactive dyes namely, Remazol Brillant Blue (RB), Remazol Red 133 (RR) and Rifacion Yellow HED (RY) from aqueous solutions at various initial dye concentration (100–500 mg/l), pH (2–8), particle size (45–112.5 μm) and temperature (293–323 K) on fly ash (FA) were studied in a batch mode operation. The adsorbent was characterized with using several methods such as SEM, XRD and FTIR. Adsorption of RB reactive dye was found to be pH dependent but both RR and RY reactive dyes were not. The result showed that the amount adsorbed of the reactive dyes increased with increasing initial dye concentration and contact time. Batch kinetic data from experimental investigations on the removal of reactive dyes from aqueous solutions using FA have been well described by external mass transfer and intraparticle diffusion models. It was found that external mass transfer and intraparticle diffusion had rate limiting affects on the removal process. This was attributed to the relatively simple macropore structure of FA particles. The adsorption data fitted well with Langmuir and Freundlich isotherm models. The optimum conditions for removal of the reactive dyes were 100 mg/l initial dye concentration, 0.6 g/100 ml adsorbent dose, temperature of 293 K, 45 μm particle size, pH 6 and agitation speed of 250 rpm, respectively. The values of Langmuir and Freundlich constants were found to increase with increasing temperature in the range 135–180 and 15–34 mg/g for RB, 47–86 and 1.9–3.7 mg/g for RR and 37–61 and 3.0–3.6 mg/g for RY reactive dyes, respectively. Different thermodynamic parameters viz., changes in standard free energy, enthalpy and entropy were evaluated and it was found that the reaction was spontaneous and endothermic in nature.     

Non-steady-state kinetic analysis of coupled transport of thiocyanate ions through binary liquid membranes

The coupled transport of thiocyanate (SCN⁻) ions through binary liquid membranes of various compositions was investigated using trichloromethane and dichloromethane as membrane components in non-steady-state kinetics. The influence of the membrane composition on the kinetic parameters (k_1d, k_2m, k_2a, R^max_m, t_max) were calculated. The present work shows the importance of the nature of binary liquid membranes in establishing transport efficiency, which is increased by varying membrane composition. Striking variations of the kinetic parameters with the membrane composition were observed. It is shown that transport kinetics obeys the competitive preferential solvation theory in the whole concentration range.     

Neural Models for the Resonant Frequency of Electrically Thin and Thick Circular Microstrip Antennas and the Characteristic Parameters of Asymmetric Coplanar Waveguides Backed with a Conductor

Neural models for computing the resonant frequency of electrically thin and thick circular microstrip antennas, based on the multilayered perceptrons and the radial basis function networks, are presented. Five learning algorithms, delta-bar-delta, extended delta-bar-delta, quick-propagation, directed random search and genetic algorithms, are used to train the multilayered perceptrons. The radial basis function network is trained according to its learning strategy. The resonant frequency results of neural models are in very good agreement with the experimental results available in the literature. In this paper, the characteristic impedance and the effective permittivity of the asymmetric coplanar waveguide backed with a conductor are also computed by using only one neural model trained by the backpropagation with momentum and the extended delta-bar-delta algorithms. When the performances of neural models are compared with each other, the best results for test are obtained from the multilayered perceptrons trained by the extended delta-bar-delta algorithm.