Objective(s): To assess the behavior that impedes the eating of children with autism spectrum disorders in Baghdad city, and find out the relationships between the behaviors that impede eating of autistic children and their demographic characteristics.
Methodology: The study started from the period of 16th September 2019 to the 16th of March 2020. A non-probability (purposive) sample of 80 children with autism spectrum disorders was selected. The questionnaire was designed and composed of two parts: the first part includes the autistic children demographic data, the second part includes scales of behavior that impede eating followed by parents towards autistic child. The reliability of the questionnaire was determined through a pilot

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

Cost is the essence of any production process for it is one of the requirements for the continuity of activities so as to increase the profitability of the economic unit and to support the competitive situation in the market. Therefore, there should be an overall control to reduce the cost without compromising the product quality; to achieve this, the management should have detailed credible and reliable information about the cost to be measured, collected, understood and to analyze the causes for the spread of deviations and obstacles the management faces, and to search for the factors that trigger the emergence of these deviations and obstacles

           Strives Total Productive Maintenance  to increase the overall effectiveness of the equipment through the early involvement in the design and manufacture of equipment productivity. It also operates in an environment of simultaneous engineering work on the synchronization of activities to take advantage of early information by maintenance engineers, design, operation, and that helps to reduce the faults and facilitate future maintenance tasks.

    Has adopted a search in the theoretical concept of the total maintenance productivity and concurrent engineering activities carried out during which the conjunction a

It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

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