A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa

أجري هذا البحث في العراق/محافظة ديالى، وهدف إلى تعرف أثر إستراتيجية شكل البيت الدائري في الاداء التعبيري لدى تلاميذ الصف الخامس الابتدائي,وبلغت عينة البحث(75) تلميذا بواقع (40) تلميذا في المجموعة التجريبية و(35)تلميذا في المجموعة الضابطة ، وأجرى الباحث بينهما تكافؤا في المتغيرات الآتية (العمر الزمني  محسوبا بالشهور، والتحصيل الدراسي للأبوين ، ودرجات اللغة العربية للعام الدراسي السابق واستعمل الباحث أداة م

وظَّفَ الشاعرُ مجد الدين النُّشَّابي الصورة الاستعارية التي شكلت سمةً جمالية بارزة من سماتِ التشكيل الشعري عنده, وأحد المكونات الأساسية في بنية قصائده الشعرية وهي جوهر الإبداع ومحط التذوق عند المتلقي, إذ يشكل الشاعر صوره الاستعارية المتنوعة متولدة من خياله وعواطفه ومتوافقة مع الموضوع لتصبح الصورة  الاستعارية ركنًّا من أركان التشكيل الفني الشعري عند الشاعر .

والتصوير الاستعاري له القدرة بالتشكيل ا

In this paper, the effective computational method (ECM) based on the standard monomial polynomial has been implemented to solve the nonlinear Jeffery-Hamel flow problem. Moreover, novel effective computational methods have been developed and suggested in this study by suitable base functions, namely Chebyshev, Bernstein, Legendre, and Hermite polynomials. The utilization of the base functions converts the nonlinear problem to a nonlinear algebraic system of equations, which is then resolved using the Mathematica^®12 program. The development of effective computational methods (D-ECM) has been applied to solve the nonlinear Jeffery-Hamel flow problem, then a comparison between the methods has been shown. Furthermore, the maximum

This study is descriptive and theory of Dawn syndrome as the problem of research lies in the need to identify the identification of the causes of Dawn syndrome and its symptoms and methods of dealing with it, which has become a problem that needs treatment, especially after the numbers have become high in Iraq, which has not yet taken the necessary importance for treatment and care.

The objectives of the research were summarized in the identification of the most important causes of Dawn syndrome and its symptoms and diagnosis and ways or methods of dealing with people with Dawn syndrome in order to develop therapeutic plans for him.

Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

Iris research is focused on developing techniques for identifying and locating relevant biometric features, accurate segmentation and efficient computation while lending themselves to compression methods. Most iris segmentation methods are based on complex modelling of traits and characteristics which, in turn, reduce the effectiveness of the system being used as a real time system. This paper introduces a novel parameterized technique for iris segmentation. The method is based on a number of steps starting from converting grayscale eye image to a bit plane representation, selection of the most significant bit planes followed by a parameterization of the iris location resulting in an accurate segmentation of the iris from the origin

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the