A novel metal complexes Cu (II), Co (II), Cd (II), Ru (III) from azo ligand 5-((2-(1H-indol-2-yl)
ethyl) diazinyl)-2-aminophenol were synthesized by simple substitution of tryptamine with 2-aminophenol.
Structures of all the newly synthesized compounds were characterized by FT IR, UV-Vis, Mass spectroscopy
and elemental analysis. In addition measurements of magnetic moments, molar conductance and atomic
absorption. Then study their thermal stability by using TGA and DSC curves. The DCS curve was used to
calculate the thermodynamic parameters ΔH, ΔS and Δ G. Analytical information showed that all complexes
achieve a metal:ligand ratio of [1:1]. In all complex examinations, the Ligand performs as a tri

The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

The objective of this work is to design and implement a cryptography system that enables the sender to send message through any channel (even if this channel is insecure) and the receiver to decrypt the received message without allowing any intruder to break the system and extracting the secret information. In this work, we implement an interaction between the feedforward neural network and the stream cipher, so the secret message will be encrypted by unsupervised neural network method in addition to the first encryption process which is performed by the stream cipher method. The security of any cipher system depends on the security of the related keys (that are used by the encryption and the decryption processes) and their corresponding le

In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

In this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system  is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

The complexes of Schiff base of 4-aminoantipyrine and 1,10-phenanthroline with metal ions Mn (II), Cu (II), Ni (II) and Cd (II) were prepared in ethanolic solution, these complexes were characterized by Infrared , electronic spectra, molar conductance, Atomic Absorption ,microanalysis elemental and magnetic moment measurements. From these studies the tetrahedral geometry structure for the prepared complexes were suggested.The prepared ligand of 4-aminoantipyrine was characterized by using Gc-mass spectrometer .

In this research, the effects of both current and argon gas pressure on the bending properties of welded joints were studied. Using the possible ranges of welding gas pressures and currents, Tungsten inert gas welding (TIG) of stainless steel (304) sheet was used to obtain their influence on the maximum bending force of the (TIG) welded joints. Design of experiment (DOE) ‘version 10' was used to determine the design matrix of experiments depending on the used levels of the input factors. Response surface methodology (RSM) technique was used to obtain an empirical mathematical model for the maximum bending force as a function of welding parameters (Current and Argon gas pressure). Also, the analysis of variance (ANOVA) was used to verif