Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

ABSTRACT University college libraries are one of the most important information institutions for all researchers during their research and study life, they seeks to provide information sources such as; books, periodicals, theses, databases, Inquiry service and answering questions services in various disciplines to achieve its goals. In 2020, college libraries of all types stepped up to meet the needs of their users' as they responded to the impacts of COVID-19, also extended necessary lifelines to community members facing job losses, healthcare crises, and remote work and learning during an unprecedented and uncertain time. The research aim to identifying the services provided to the postgraduate students users at University of Baghdad coll

Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte

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      يعد البيت المكان الاجتماعي الأول الذي تبنى فيه الصحة النفسية لدى الفرد منذ بداية حياته كطفل  في ظل أسرته ، إلا أن الروضة تمتلك على الرغم من ذلك أثراً تكوينياً مهماٌ في حياة الطفل وعلى شخصيته ، والتي لا يمكن ان يقلُّ عن أثر الايجابي للبيت ؛ ذلك أن المفهوم الجديد لدور الروضة لا يقتصر بمجرد كونها مكانًا تقوم فيها المعلمة بتزويد الاطفال بالمعر

What distinguishes human rights issues is their importance to the international community and their importance to democratic political regimes, because they are the axis of any political regime that seeks to achieve a successful democratic path and a stable state. So, countries that are interested in human rights try to enshrine those rights and freedoms in their constitutions and reinforce their concepts in their laws and legislations. Not to mention its involvement in international conventions and treaties concerned with human rights and freedoms, and this is what the Sultanate of Oman has worked on and confirm in the provisions of its 1996 constitution and its amendments

This paper aimed to investigate the effect of the height-to-length ratio of unreinforced masonry (URM) walls when loaded by a vertical load. The finite element (FE) method was implemented for modeling and analysis of URM wall. In this paper, ABAQUS, FE software with implicit solver was used to model and analysis URM walls subjected to a vertical load. In order to ensure the validity of Detailed Micro Model (DMM) in predicting the behavior of URM walls under vertical load, the results of the proposed model are compared with experimental results. Load-displacement relationship of the proposed numerical model is found of a good agreement with that of the published experimental results. Evidence shows that load-displacement curve obtained fro