The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

 Since there is no market for bond issuance by companies in the Iraqi market and the difficulty of borrowing, companies must resort to proprietary financing to finance their investments. However, in the framework of the literature of financial management, the type of financing used by the company sends signals to investors and therefore reflected on the market value. Therefore, the problem of the study revolves around the variables of the study (Equity financing within the framework the signal theory, price of common stock in the Iraqi market).     

The study aims to verify the impact of the capital increase through the issuance of new stock on the price of

          We obtain the coefficient estimates, extreme points, distortion and growth boundaries, radii of starlikeness, convexity, and close-to-convexity, according to the main purpose of this paper.

Background: Cognitive dysfunctions in epileptic patients may develop due to the neurophysiologic changes related to seizures or antiepileptic drugs.
Objectives: The aim of this longitudinal study was to evaluate the cognitive dysfunction in epileptic patients under antiepileptic drug therapy by the aid of event related potentials.
Patients & Method: P300 latencies were obtained from Fz, Cz and Pz electrodes positions from both epileptic patients (n = 224) and age and sex matched control group (n = 91). Epileptic patients were classified either having partial epilepsy, generalized epilepsy or both partial and generalized epilepsy (combined epilepsy). EEG and p300 test repeated for each patient every three months for one year. Th

        The purpose of this paper is to evaluate the error of the approximation of an entire function by some discrete operators in locally global quasi-norms (L_d,p-space), we intend to establish new theorems concerning that Jackson polynomial and Valee-Poussin operator remain within the same bounds as bounded and periodic entire function in locally global norms (L_d,p), (0 < p £ 1).

In the current research work, a system of hiding a text in a digital grayscale image has been presented. The algorithm system that had been used was adopted two transforms Integer Wavelet transform and Discrete Cosine transformed. Huffman's code has been used to encoding the text before the embedding it in the cover image in the HL sub band. Peak Signal to Noise Ratio (PSNR) was used to measure the effect of embedding text in the watermarked image; also correlation coefficient has been used to measure the ratio of the recovered text after applying an attack on the watermarked image and we get a good result. The implementation of our proposed Algorithm is realized using MATLAB version 2010a.

Embedding an identifying data into digital media such as video, audio or image is known as digital watermarking. In this paper, a non-blind watermarking algorithm based on Berkeley Wavelet Transform is proposed. Firstly, the embedded image is scrambled by using Arnold transform for higher security, and then the embedding process is applied in transform domain of the host image. The experimental results show that this algorithm is invisible and has good robustness for some common image processing operations.

With wireless sensor network (WSN) wide applications in popularity, securing its data becomes a requirement. This can be accomplished by encrypting sensor node data. In this paper a new an efficient symmetric cryptographic algorithm is presented. This algorithm is called wireless sensor network wavelet curve ciphering system (WSN-WCCS).  The algorithm idea based on discrete wavelet transformation to generate keys for each node in WSN.  It implements on hierarchical clustering WSN using LEACH protocol. Python programming language version 2.7 was used to create the simulator of WSN framework and implement a WSN-WCCS algorithm. The simulation result of the proposed WSN-WCCS with other symmetric algorithms has show