There are large numbers of weakness in the generated keys of security algorithms. This paper includes a new algorithm to generate key of 5120 bits for a new proposed cryptography algorithm for 10 rounds that combine neural networks and chaos theory (1D logistic map). Two methods of neural networks (NN) are employed as Adaline and Hopfield and the results are combined through several sequential operation. Carefully integrating high quality random number generators from neural networks and chaos theory to obtain suitable key for randomness and complexity.

A Wearable Robotic Knee (WRK) is a mobile device designed to assist disabled individuals in moving freely in undefined environments without external support. An advanced controller is required to track the output trajectory of a WRK device in order to resolve uncertainties that are caused by modeling errors and external disturbances. During the performance of a task, disturbances are caused by changes in the external load and dynamic work conditions, such as by holding weights while performing the task. The aim of this study is to address these issues and enhance the performance of the output trajectory tracking goal using an adaptive robust controller based on the Radial Basis Function (RBF) Neural Network (NN) system and Hamilton

This paper presents L₁-adaptive controller for controlling uncertain parameters and time-varying unknown parameters to control the position of a DC servomotor. For the purpose of comparison, the effectiveness of L₁-adaptive controller for position control of studied servomotor has been examined and compared with another adaptive controller; Model Reference Adaptive Controller (MRAC). Robustness of both L₁-adaptive controller and model reference adaptive controller to different input reference signals and different structures of uncertainty were studied. Three different types of input signals are taken into account; ramp, step and sinusoidal. The L₁-adaptive controller ensured uniformly bounded

Ball and Plate (B&P) system is a benchmark system in the control engineering field that has been used to verify many control methods. In this paper the design of a sliding mode . controller has been investigated and verified in real-time via implementation on a real ball and plate system hardware. The mathematical model has been derived and the necessary parameters have been measured. The sliding mode controller has been designed based on the obtained mathematical model. The resulting controller has been implemented using the Arduino Mega 2560 and a ball and plate system built completely from scratch. The Arduino has been programmed by the Arduino support target for Simulink. Three test signals has been used for verification purposes

   In this paper we give definitions, properties and examples of the notion of  type Ntopological space. Throughout this paper  N is a finite positive  number, N 2. The task of this paper is to study and investigate some properties of such spaces with the existence of a relation between this space and artificial Neural Networks (NN'S), that is we applied the definition of this space in computer field and specially in parallel processing

Maximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.

The interest of this paper is that

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

Econazole nitrate (EN) is considered as the most effective agent for the treatment of all forms of
dermatomycosis caused by dermatophytes. This study was carried out to formulate a stable
Econazole nitrate solution for a topical use through preparation of different formulas and selected
the most suitable one. The results indicated that the use of propylene glycol and ethanol as a vehicle
for EN which is very slightly soluble in water gave amore stable formula as EN topical solution,
with a shelf life of about 3.15 years .The data also indicated that the light accelerated the
degradation of EN, while the type of container (glass or plastic) had no effect on the rate of drug.
The overall results of this study suggest t

A prepared PMMA/Anthracene film of thickness 70μm was irradiated under reduced pressure ~10-3 to 60Coγ-ray dose of (0.1mrad-10krad) range. The optical properties of the irradiated films were evaluated spectrophotometrically. The absorption spectrum showed induced absorption changes in the 200-400nm range. At 359nm, where there is a decrease in radiation-induced absorption, the optical density as a function of absorbed dose is linear from 10mrad-10Krad.It can therefore, be used as radiation dosimeter for gamma ray in the range 10mrd-10krad

The redevelopment of brownfields participate to sustainable urban development, it can make cities more valuable worth for community and more attractive for companies to settle down their projects through investment, and it can help to reduce expenditures for the construction of infrastructures and other services. Recent studies in brownfield redevelopment and investment have shown great interest in urban planning studies because of their negative effects on cities, they promoted sprawl, pollution, social and economic problems. There is a general agreement among researchers and experts that brownfield sites can be reused as green spaces, commerce centers, and residential projects. To promote sustainable urban development the role of the c