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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 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

Nanoparticles generation by laser ablation of a solid target in a liquid environment is an easy method. Cadmium Telluride (CdTe) colloidal nanoparticles have been synthesized by laser ablation Nd:YAG with wavelengths of 1064nm and double frequency at 532 nm, number of pulses 50 pulses, with pulse energy= 620mJ, 700mJ of a solid target CdTe is immersed in double distilled deionized water (DDIW) and in methanol liquid. Influences of the laser energy and different solutions on the formation and optical characterization of the CdTe nanoparticles have been studied using atomic force microscope (AFM) and the UV-Vis absorption. As a results, it leads to the absorbance in UV-Vis spectra of samples prepared in water at laser wavelength of 532nm i

Acute myeloid leukemia is a malignant disease results from mutation in a multipotent haemopoietic stemcell. The study aimed to investigate NPM1 and FLT3-ITD mutations in Iraqi patients with AML and correlateresults with other clinical and laboratory findings. Fifty-eight AML patients, admitted to Baghdad TeachingHospital from October 2019 till March 2020 in addition to 25 normal controls, were included in the study.A detailed history, laboratory investigations including FLT3-ITD and NPM1 mutations were collected fromand analyzed. FLT3-ITD was detected in 17.24% of patients, NPM1 mutation in 10.34%. Most of thepatients are presented with pallor. FLT3-ITD mutation had a higher blast cell count (74%) while NPM1mutation had higher WBCs