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

This research aims to the possibility of evaluating the strategic performance of the State Board for Antiquities and Heritage (SBAH) using a balanced scorecard of four criteria (Financial, Customers, Internal Processes, and Learning and Growth). The main challenge was that the State Board use traditional evaluation in measuring employee performance, activities, and projects. Case study and field interviews methodology has been adopted in this research with a sample consisting of the Chairman of the State Board, 6 General Managers, and 7 Department Managers who are involved in evaluating the strategic performance and deciding the suitable answers on the checklists to analyze it according to the 7-points Likert scale. Data analysis re

This research aims to the possibility of evaluating the strategic performance of the State Board for Antiquities and Heritage (SBAH) using a balanced scorecard of four criteria (Financial, Customers, Internal Processes, and Learning and Growth). The main challenge was that the State Board use traditional evaluation in measuring employee performance, activities, and projects. Case study and field interviews methodology has been adopted in this research with a sample consisting of the Chairman of the State Board, 6 General Managers, and 7 Department Managers who are involved in evaluating the strategic performance and deciding the suitable answers on the checklists to analyze it ac

The estimation of the initial oil in place is a crucial topic in the period of exploration, appraisal, and development of the reservoir. In the current work, two conventional methods were used to determine the Initial Oil in Place. These two methods are a volumetric method and a reservoir simulation method. Moreover, each method requires a type of data whereet al the volumetric method depends on geological, core, well log and petrophysical properties data while the reservoir simulation method also needs capillary pressure versus water saturation, fluid production and static pressure data for all active wells at the Mishrif reservoir. The petrophysical properties for the studied reservoir is calculated using neural network technique

In this paper, we investigate the behavior of the bayes estimators, for the scale parameter of the Gompertz distribution under two different loss functions such as, the squared error loss function, the exponential loss function (proposed), based different double prior distributions represented as erlang with inverse levy prior, erlang with non-informative prior, inverse levy with non-informative prior and erlang with chi-square prior.

The simulation method was fulfilled to obtain the results, including the estimated values and the mean square error (MSE) for the scale parameter of the Gompertz distribution, for different cases for the scale parameter of the Gompertz distr

The goal beyond this Research is to review methods that used to estimate Logistic distribution parameters. An exact estimators method which is the Moment method, compared with other approximate estimators obtained essentially from White approach such as: OLS, Ridge, and Adjusted Ridge as a suggested one to be applied with this distribution. The Results of all those methods are based on Simulation experiment, with different models and variety of  sample sizes. The comparison had been made with respect to two criteria: Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE).