The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

The aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (M_bias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial

Heuristic Program proposal for the treatment of talented emotional and Cognitive problems .

1-The Curtent research aims : to identify the needs of gifted students and their problems and Ways to diagnose .

2-reprepare aproposal heuristic program for the treatment of emotional and Cognitive talented problems .

Research . Methodology : analytical and descriptive .

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Virt uoso is the per for mance of the privileged Mstmrave performances appear in any area of his Values .

Chapter ll : Includes recipes gifted child and Methods diagnosis gifted by filtrontion and standavds of personal and mental and behavioral Doramwaliman and parental Features and Leader in the detection of the gif

In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w

Visible-light photodetectors constructed Fe2O3 were manufactured effectively concluded chemical precipitation technique, films deposited on glass substrate and Si wafer below diverse dopant (0,2,4,6)% of Cl, enhancement in intensity with X-ray diffraction analysis was showed through favored orientation along the (110) plane, the optical measurement presented direct allowed with reduced band gap energies thru variation doping ratio , current–voltage characteristics Fe2O3 /p-Si heterojunction revealed respectable correcting performance in dark, amplified by way of intensity of incident light, moreover good photodetector properties with enhancement in responsivity occurred at wavelength between 400 nm and 470 nm.

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc