The study aims to enrich the information of planners, policymakers, and water resources managers for planning and operating dams. This research aims to address the following question: What are the environmental, economic, and social impacts of the construction and operation of dams on the environment and society? The study assumes that good management is the ideal solution to solve the problems of negative effects resulting from the construction and operation of dams. The research relied on the descriptive analytical approach in studying the positive and negative impacts of Haditha Dam and the government's role. A questionnaire was conducted for 30 specialists in urban and regional planning to find out the most important strategies for sust

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

The aim of this study is to estimate the parameters and reliability function for kumaraswamy distribution of this two positive parameter  (a,b > 0), which is a continuous probability that has many characterstics with the beta distribution with extra advantages.

The shape of the function for this distribution and the most important characterstics are explained and estimated the two parameter (a,b) and the reliability function for this distribution by using the maximum likelihood method (MLE) and Bayes methods. simulation experiments are conducts to explain the behaviour of the estimation methods for different sizes depending on the mean squared error criterion the results show that the Bayes is bet

Background: Polycystic ovarian syndrome is a common endocrine disorder affecting 6-10% of women of reproductive age and the most common cause of anovulatory infertility. Objective: The aim of the study was to compare the effectiveness, side effects and outcomes of step-up gonadotrophin protocol versus laparoscopic ovarian diathermy (LOD) in infertile patients with clomiphene citrate resistant polycystic ovary syndrome. Methods:  The sample included women who attended our infertility clinic at Al-Elwiya Maternity Teaching Hospital and Kamal Al-Samarraee for Infertility and IVF Hospital in Baghdad/ Iraq from November 2013 to November 2014.    Eighty cases of infertile women with polycystic ovarian syndrome who failed t

Background: Polycystic ovarian syndrome is a common endocrine disorder affecting 6-10% of women of reproductive age and the most common cause of anovulatory infertility.

Objective: The aim of the study was to compare the effectiveness, side effects and outcomes of step-up gonadotrophin protocol versus laparoscopic ovarian diathermy (LOD) in infertile patients with clomiphene citrate resistant polycystic ovary syndrome.

Methods:  The sample included women who attended our infertility clinic at Al-Elwiya Maternity Teaching Hospital and Kamal Al-Samarraee for Infertility and IVF Hospital in Baghdad/ Iraq from November 2013 to November 2014.    Eighty case

During the last two decades, nanomaterial application has gained a significant attraction into asphalt technology due to their effect in enhancing asphalt binder improving the asphaltic mixture. This study will modify the asphalt binder with two different nano types, nano SiO2 and CaCO3, at levels ranging from 1% to 7%. The resulting optimum nano-modified Asphalt will be subject to a series of rheological tests, including dynamic shear rheometer (DSR), Viscosity, and bending beam rheometer (BBR) to determine asphalt binder sensitivity towards low-medium-high temperature range. Results indicate that both nano types improved the physical characteristics of Asphalt, and 5% by weight of Asphalt was suggested as a reasonable dosage of nano-SiO2

The estimation of the parameters of Two Parameters Gamma Distribution in case of missing data has been made by using two important methods: the Maximum Likelihood Method and the Shrinkage Method. The former one consists of three methods to solve the MLE non-linear equation by which the estimators of the maximum likelihood can be obtained: Newton-Raphson, Thom and Sinha methods. Thom and Sinha methods are developed by the researcher to be suitable in case of missing data. Furthermore, the Bowman, Shenton and Lam Method, which depends on the Three Parameters Gamma Distribution to get the maximum likelihood estimators, has been developed. A comparison has been made between the methods in the experimental aspect to find the best meth

The current research aims to measure the level of entrepreneurial orientation and its dimensions (creativity, independence, proactivity, risk tolerance, and achievement) in the National Security Chancellery, as its importance and role in guiding senior leaders of the chancellery to make strategic decisions with high quality in various Iraqi concerns, more specifically the security aspect. The data was collected from 94 individuals (the research sample) from the research community (120) individuals at different administrative levels and intentionally where the questionnaire was adopted as a main tool for data collection and the primary data was analyzed through descriptive and inferential statistical methods (arithmetic mean, standard dev

Many industrial systems involve multiple criteria and objectives, and they are very complex problems in computational science, such as task scheduling. We propose bi-criteria and bi-objective scheduling problems, which are solved by two nature-inspired evolutionary algorithms, such as Simulated Annealing (SA) and Bee Algorithm (BA). This problem is characterized by scheduling a batch of tasks on multiple machines, and it is fundamental because the solution should focus on the simultaneous optimization of two conflicting objectives: the makespan minimization and the total tardiness minimization. This problem is NP-Hard, and therefore, two evolutionary methods were used to search for solutions intelligently in this huge, very complex

The proposed design of neural network in this article is based on new accurate approach for training by unconstrained optimization, especially update quasi-Newton methods are perhaps the most popular general-purpose algorithms. A limited memory BFGS algorithm is presented for solving large-scale symmetric nonlinear equations, where a line search technique without derivative information is used. On each iteration, the updated approximations of Hessian matrix satisfy the quasi-Newton form, which traditionally served as the basis for quasi-Newton methods. On the basis of the quadratic model used in this article, we add a new update of quasi-Newton form. One innovative features of this form's is its ability to estimate the energy functio