The research deals with the analysis of the city's commercial center using geographic information systems to solve the problem of congestion by evaluating the efficiency and adequacy of car parking lots according to local and Arab standards. Undoubtedly, the importance of car parking areas, as they are not within the desired efficiency within the city, will lead to congestion and traffic becomes very difficult. Thus, the transportation service loses its most important characteristic, which is the ease of movement. Therefore, there has become an urgent need to study and analyze it, as well as to verify the adequacy of the service, and the amount of deficit required to be provided to solve the tra

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

The study aimed to identify the effect of the ethical perception of a sample of managers in public organizations on responsible behavior in light of the rapid changes taking place in the external environment. To achieve this, the researcher followed the descriptive analytical approach by applying a questionnaire of two parts. The first part dealt with the ethical perception according to the scale of Johnson (2015), which consisted of (22) items. The second part dealt with measuring responsible behavior, which consisted of (20) items based on the scale of Development of Ethical Behavior (Narvaez, 2006) for a sample of (125) respondents randomly chosen. The results showed that the estimation degree of managers in public governmental o

This paper is concerned with introducing and studying the M-space by using the mixed degree systems which are the core concept in this paper. The necessary and sufficient condition for the equivalence of two reflexive M-spaces is super imposed. In addition, the m-derived graphs, m-open graphs, m-closed graphs, m-interior operators, m-closure operators and M-subspace are introduced. From an M-space, a unique supratopological space is introduced. Furthermore, the m-continuous (m-open and m-closed) functions are defined and the fundamental theorem of the m-continuity is provided. Finally, the m-homeomorphism is defined and some of its properties are investigated.

Abstract The purpose of this paper is to preparing small games for fifth graders. And to identify the impact of these small games in developing some concepts of traffic safety for fifth graders. The two researchers used the experimental method to solve the research problem, and the research community was identified with students. The fifth grade of primary school in the province of Baghdad and a sample was chosen from the private Baghdad Primary School, which numbered (60) male and female students. They were distributed equally into two groups by simple random method (experimental and control groups). As for the most important conclusions reached by the two researchers, it is the presence of an effect of small games in developing some conce

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c