Most of drinking water consuming all over the world has been treated at the water treatment plant (WTP) where raw water is abstracted from reservoirs and rivers. The turbidity removal efficiency is very important to supply safe drinking water. This study is focusing on the use of multiple linear regression (MLR) and artificial neural network (ANN) models to predict the turbidity removal efficiency of Al-Wahda WTP in Baghdad city. The measured physico-chemical parameters were used to determine their effect on turbidity removal efficiency in various processes. The suitable formulation of the ANN model is examined throughout many preparations, trials, and steps of evaluation. The prediction models of the turbidity removal are presented. Results found that the estimating of the turbidity removal efficiency by ANN and MLR model could be successful. Moreover, results showed that influent and effluent turbidity concentration have more effect on removal efficiency predicting from the other parameters. Finally, the ANN model could be more accurate than the MLR model according to the coefficient of correlation (0.925).
Background: Refractory/relapsed acute leukemia has always been a challenging problem for hematologist. Over the past decade emphasis has been made in the development of regimens containing fludarabine, combined with cytosine arabinoside for the treatment of refractory/relapsed acute leukemias. The aim of this study is to evaluate the efficacy and toxicity of the combination of fludarabine, high dose cytarabine, and granulocyte colony stimulating factor in refractory relapsed cases of acute leukaemia,
Methods: a prospective study is being conducted at the national center of hematology and hematology unit /Baghdad teaching hospital from July 2008 to July 2010.Twenty Patients with refractory/relapsed acute leukemia were treated with flud
One of the main element in the network is the intersection which consider as the critical points because there are many conflict in this element. The capability and quality of operation of an intersection was assessed to provide a better understanding of the network's traffic efficiency. In Baghdad city, the capital of/Iraq the majority of the intersections are operated under the congestion status and with level of service F, therefore theses intersection are consider as high spot point of delay in the network of Baghdad city. In this study we selected Al-Ameria signalized intersection as a case study to represent the delay problem in the intersections in Baghdad. The intersection is located in the w
Global Navigation Satellite System (GNSS) is considered to be one of the most crucial tools for different applications, i.e. transportation, geographic information systems, mobile satellite communications, and others. Without a doubt, the GNSS has been widely employed for different scientific applications, such as land surveying, mapping, and precise monitoring for huge structures, etc. Thus, an intense competitive has appeared between companies which produce geodetic GNSS hardware devices to meet all the requirements of GNSS communities. This study aims to assess the performance of different GNSS receivers to provide reliable positions. In this study, three different receivers, which are produced by different manufacturers, were fi
... Show MoreGlobal Navigation Satellite System (GNSS) is considered to be one of the most crucial tools for different applications, i.e. transportation, geographic information systems, mobile satellite communications, and others. Without a doubt, the GNSS has been widely employed for different scientific applications, such as land surveying, mapping, and precise monitoring for huge structures, etc. Thus, an intense competitive has appeared between companies which produce geodetic GNSS hardware devices to meet all the requirements of GNSS communities. This study aims to assess the performance of different GNSS receivers to provide reliable positions. In this study, three different receivers, which are produced by different manufactur
... Show MoreThe current study aims to apply the methods of evaluating investment decisions to extract the highest value and reduce the economic and environmental costs of the health sector according to the strategy.In order to achieve the objectives of the study, the researcher relied on the deductive approach in the theoretical aspect by collecting sources and previous studies. He also used the applied practical approach, relying on the data and reports of Amir almuminin Hospital for the period (2017-2031) for the purpose of evaluating investment decisions in the hospital. A set of conclusions, the most important of which is: The failure to apply
... Show MoreIn this research was the study of a single method of estimation and testing parameters mediating variables (Mediation) in a specimen structural equations SEM a bootstrap method, for the purpose of application of the integrated survey of the situation Marital data and health mirror Iraqi (I-WISH) for the year 2011 from the Ministry of Planning - device Central Bureau of Statistics, and applied to the appropriate data from the terms of the data to a form of structural equation SEM using factor analysis affirmative (Confirmatory Factor analysis) CFA As a way to see the match variables that make up the model, and after confirming the model matching or suitability are having the effect of variables mediation in the model tested by the
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This study is studied one method of estimation and testing parameters mediating variables in a structural equations model SEM is causal steps method, in order to identify and know the variables that have indirect effects by estimating and testing mediation variables parameters by the above way and then applied to Iraq Women Integrated Social and Health Survey (I-WISH) for year 2011 from the Ministry of planning - Central statistical organization to identify if the variables having the effect of mediation in the model by the step causal methods by using AMOS program V.23, it was the independent variable X represents a phenomenon studied (cultural case of the
Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c
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