This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

The project has been described the design and construction of a reliable optical testing platform used for evaluate the reflectivity of metal surfaces treated with special paintings required for laser beam attenuation. The platform comprises an Nd-YAG laser system which has been designed and fabricated with specifications to be compatible with their corresponding in laser range finder transmitters used for various applications. The reflectivity of various attenuating paintings, at different detection angles, has been observed. Moreover, the variation of the reflected energy with painting type and metal type to be painted has been studied experimentally. Results illustrated the existence of a definite angle, at which the reflectivity was max

Actual and effective organizational dynamic capabilities in the work environment contribute to a number of factors that contribute to the organization's ability to manage its human talents. Thus, the study sought to identify the level of contribution of organizational dynamic capabilities to human talent management based on their dimensions in the investigated organization by determining the level of relationship and impact between these variables. The presidency of Mosul University was chosen as a field for the current study, and data were collected by adopting the questionnaire form as the main tool for the study. The study used a deliberate sample of (42)  administrative leaders in the investigated organization and adopte

The recognition of the dynamic organizational capabilities in their actual and influential extent in the work environment achieves a set of positive data that can fall under the addition axes, particularly with regard to the organization's ability to manage human talents in them, so the researchers sought to identify the level of contribution of dynamic organizational capabilities in the management of human talents in terms of Keep them away in the research organization by indicating the level of relationship and impact between them. The presidency of Mosul University was chosen as a field for the current study, and data were collected by adopting the questionnaire form as the main tool for the study. The study used a deliberate

Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that us

The esterification of oleic acid with 2-ethylhexanol in presence of sulfuric acid  as homogeneous catalyst was investigated in this work to produce 2-ethylhexyl oleate (biodiesel) by using semi batch reactive distillation. The effect of reaction temperature (100 to 130°C), 2-ethylhexanol:oleic acid molar ratio (1:1 to 1:3) and catalysts concentration (0.2 to 1wt%) were studied. Higher conversion of 97% was achieved with operating conditions of reaction temperature of 130°C, molar ratio of free fatty acid to alcohol of 1:2 and catalyst concentration of 1wt%. A simulation was adopted from basic principles of the reactive distillation using MATLAB to describe the process. Good agreement was achieved.

      Detecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de