The research explores through its three parts, to search for the unconscious and the collective unconscious in order to identify the per-formative stimuli and motives and their motivation to produce a performance that is consistent with the metaphysics of the myth or the epic and its different characters from other human characters. The paper also explores in its second section a sort of sacred performance energy. Together, along with motivating the mind and engaging the subconscious, comes a metaphysical text and with its characters and epic events.

The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To

This paper presents a comparative study between different oil production enhancement scenarios in the Saadi tight oil reservoir located in the Halfaya Iraqi oil field. The reservoir exhibits poor petrophysical characteristics, including medium pore size, low permeability (reaching zero in some areas), and high porosity of up to 25%. Previous stimulation techniques such as acid fracturing and matrix acidizing have yielded low oil production in this reservoir. Therefore, the feasibility of hydraulic fracturing stimulation and/or horizontal well drilling scenarios was assessed to increase the production rate. While horizontal drilling and hydraulic fracturing can improve well performance, they come with high costs, often accounting for up t

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

Abstract

This Study aimed to investigate the reality of the application of the degree of management practice by Walking Around, namely (discovery of facts, improvement of communication, motivation, development, creativity and feedback) and Its role in achieving organizational justice (procedural justice, distributive justice, Interactional Justice),The availability of the core principles of this system from the point of view of the senior management personnel in the Directorate of Anbar Education, and the importance of research in the philosophical rooting of the nature of the variables as a modern administrative terminology, the research dealt with a problem expressed by a number of intellectual and appl