Abstract

      Oil is the most important natural resources in Iraq and represents the goal to others as well as Iraqi people. It is gift from God to all Iraqi people now and future. So we must maintain it and invest its revenue that achieve development in country and ensure the next generations' rights in it without external costs or negative externalities from extracted and invested it.

    The most problems that we attempt to solve by this research are the exhausted, environmental degradation and theft from next generation that produced with oil contracts between Iraq and foreign companies. From here was th

Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

The research aims to characterize the strategic plan of the Educational Professional Development Center, to reveal the most important training needs for teachers from this center, to reveal the extent to which this center meets those needs, and to identify the differences between teacher responses about the degree of importance, availability of those needs according to variables of sex, specialization, and years of experience. This descriptive study adopted a questionnaire applied to (256) teachers in the K.S.A. The results of the study showed that all training needs ranged in the degree of importance from large to very large and that the most important were the skills associated with communicating with members of the learning community.

        Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,

The spectacular film is a type of feature films which has specific elements that contribute in increasing the aesthetics of the shape in its structure. The researcher started studying this type of films by researching the spectacular film concept, the history of its development, who are its most important stars and then tackling the Indian cinema represented by Bollywood, which is considered a school for this type of film. The researcher addressed the most important influential elements that entre in its production as well as studying these elements that contribute to building the shape including the configuration, movements of cameras, lenses, the lighting, colors, costumes etc. and what influence they have in forming a special aestheti

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

There is a theoretical controversy in the books of Usul al-Fiqh, in the past and the present, about whether the ruling should be attached to its reason (al-Hikmah), or its apparent and stable cause (al-Illah). Looking at the practical cases of the jurists, we found them sometimes attaching rulings to its reason, and sometimes to its cause, so there is a need to know the factors that affect their choices. By extrapolation, the researcher reached at nine factors that affect referring the ruling to its cause or to its reason in jurisprudential cases.

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

Background: Knowledge about the prevalence and distribution of pathologies in a particular location is important when a differential diagnosis is being formulated. The aim of this study was to describe the prevalence and the clinicopathological features of odontogenic cysts and tumors affecting the maxilla and to discuss the unusual presentation of those lesions within maxillary sinus.

Materials and Methods: A multicenter retrospective analysis was performed on pathology archives of patients who were diagnosed with maxillary odontogenic cysts and tumors from 2010 to 2020. Data were collected with respect to age, gender and location.

Result: A total of 384 cases was identified, 320 (83.3%) cases were diagnosed as odontogenic