In this paper, a robust adaptive sliding mode controller is designed for a mobile platform trajectory tracking.  The mobile platform is an example of a nonholonomic mechanical system. The presence of holonomic constraints reduces the number of degree of freedom that represents the system model, while the nonholonomic constraints reduce the differentiable degree of freedom. The mathematical model was derived here for the mobile platform, considering the existence of one holonomic and two nonholonomic constraints imposed on system dynamics. The partial feedback linearization method was used to get the input-output relation, where the output is the error functions between the position of a certain point on the platform

The current research dealt with the issue of organizational skillfulness as an entry point to reach strategic agility. The study has been tested in Iraq's mobile operators - Asia Cell, Zain Iraq and Cork Telecom. The study was applied to a sample of (93) managers distributed at various levels of management (board members, general managers, commissioners, department managers, people managers, unit managers, office managers). The survey used the questionnaire as a key tool for collecting data and information as well as personal interviews. It has sought to test a number of hypotheses related to correlation and influence relationships between the variables of the study, in order to answer the questions related to the problem of stud

With the recent developments of technology and the advances in artificial intelligent and machine learning techniques, it becomes possible for the robot to acquire and show the emotions as a part of Human-Robot Interaction (HRI). An emotional robot can recognize the emotional states of humans so that it will be able to interact more naturally with its human counterpart in different environments. In this article, a survey on emotion recognition for HRI systems has been presented. The survey aims to achieve two objectives. Firstly, it aims to discuss the main challenges that face researchers when building emotional HRI systems. Secondly, it seeks to identify sensing channels that can be used to detect emotions and provides a literature review

The study aims to elucidation Difference distribution of the labor force by occupation in Sulaymaniyah governorate for the year 2013 by result field study to governorate and explain different Spatially for labor force by career. and The study reaches That Executive staff and Scribes and who join their high ratio from Total the labor force And the second Grade to Specialists and Technicians and who join their While Occupied career Production workers and who join their and Operators Transport Equipment and Engaged the third Grade from the total labor force and Continued Height in career Executive staff and who join their on the male labor force too . while Production workers in second Grade for male labor force , while the female labor for

يُعد الذكاء الاصطناعي من العلوم الحديثة التي ارتبطت بالإنسان منذ العقود الخمسة الماضية، وأصبحت السياسة الرقمية جزءاً لا يتجزأ من المجتمع لكونها تُستعمل في أغلب مجالات حياة الإنسان. وهذا ما شجع صانعي السياسات التكنولوجية الجديدة في التفكير بكيفية توظيفه لخدمة مصالحهم العليا السياسية والاقتصادية، بغض النظر عن بذل الجهود للتفكير في تنظيمهم للذكاء الاصطناعي التوليدي، ووضع قيود تراعي التشريعات الدينية، وقوا

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi