The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

 Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.

Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

The paper presents a neural synchronization into intensive study in order to address challenges preventing from adopting it as an alternative key exchange algorithm. The results obtained from the implementation of neural synchronization with this proposed system address two challenges: namely the verification of establishing the synchronization between the two neural networks, and the public initiation of the input vector for each party. Solutions are presented and mathematical model is developed and presented, and as this proposed system focuses on stream cipher; a system of LFSRs (linear feedback shift registers) has been used with a balanced memory to generate the key. The initializations of these LFSRs are neural weights after achiev

The study aimed to spread the culture of efficient performance between nursing staffs, which would contribute and achieve health care quality, and to clarify the role of nursing in improving the quality of high-quality health care, as well as to clarify how to reach national standards for the quality of health care in Iraq, Therefore, the study dealt with the efficiency of nursing performance as an explanatory variable, and the quality of health care as a dependent variable. The fact that the health sector is the foundation for building a healthy society free from diseases, so hospital of IBN AL-NAFIS as an institution and it's nursing teams were taken as a community for this study. The results to be objective and reflect the rea

The subject of the provisions of prayer on the chairs of the important topics in the jurisprudence they fall under the door of the people of excuses, and this section of the important doors in Islamic jurisprudence because it permeates scourge, as prayer is one of the pillars of this religion, and the first thing to be held accountable on the Day of Resurrection prayer If the peace reconciled the rest of his work and spoil corrupted all his work, the street wise was interested in this matter and put him provisions overlooked by many people these days became insulted him and do not pardon him, and do not know the rules and provisions approved by Shara, and the omission of one of these provisions is possible To lead to the invalidity of hi

Iranian stories have been one of the most important aspects   of Iranian society's culture and have reflected us as a mirror of all its cultural, societal and political dimensions.Among the important elements of the story can be the creation of space and the movement and the creation of characters and conflict and content and the angle of vision and landscape, language and subject. Studying the elements of the story leads to more understanding and determining the strength and skill of the author by studying the elements of his story. The story of Rustom and Suhrab is also one of the many stories in which the elements of the story are often noticed and show the skill of the great professor Al-Fardousi to benefit from these eleme

ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel