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Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
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The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. The artificial neural networks show a high coefficient of determination between the predicted and observed domestic solid waste, with R2 value reaching to 0.91, 0.828 and 0.827 for Al-Karkh, 0.9986,0. 9903 and 0.9903 for Rusafa side, and 0.9989, 0.9878 and 0.9847 in Baghdad city, and also, these models were used to estimate the generation of municipal solid waste for short period with highly efficient which assistance in planning to design landfills sites.

 

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Publication Date
Sun Feb 10 2019
Journal Name
Drug Invention Today
Design, characterization, and in vitro evaluation of zaltoprofen solid dispersion as a hollow-type rectal suppository
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Aim: The present study aims to improve the poor water solubility of zaltoprofen which is a non-steroidal anti-inflammatory drug (NSAIDs) with a potent analgesic effect using solid dispersion then formulate it as a hollow type suppository to be more convenient for geriatric patients. Materials and Method: Zaltoprofen solid dispersions were prepared by solvent evaporation technique in different zaltoprofen: Soluplus® ratios. Results: Among the formulations tested, zaltoprofen solid dispersion preparation using 1:5 (zaltoprofen: Soluplus®) ratio showed the highest solubility and selected for further investigation. Solid dispersion characterization was evaluated by differential scanning calorimetry (DSC), X-ray diffraction study (XRD) and Fou

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of Strategic Intelligence in High performance organization A Survey Study for the Managers of Diseases and Kidney Transplant Center/ Medicine City-Baghdad
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The topic of strategic intelligence is considered as important topics that acquires the attention of organizations, Because of its role in supplying the decision-making centers by strategic ideas according to the opportunities and threats facing the organization, in an effort to improve the performance of their organizations to reach the high performance organization.

A lot of organizations lack to strategy guides the strategic intelligence towards achieving high performance organization.

This research aims to determine the level of strategic intelligence that characterized the leaders of diseases and kidney transplant center in Medicine city. What is the application level of the

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Predicting Social Security Fund compensation in Iraq using ARMAX Model
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Time series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The impact of wages and benefits systems on the performance of employees A field study in the General Company for Food Industries in the city of Baghdad
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The research aims to find out the impact of wages and benefits systems on the performance of employees, which included the research community on a sample of employees in the company, and the sample consisted of (50) employees and an employee, A questionnaire composed as prepared (23) paragraph, use the promised statistically methods in data collected by the questionnaire analysis. The research reached a number of results, the most prominent of which were: There is a correlation between wage systems, benefits and performance of employees, and the presence of the impact of the systems of wages and benefits to the performance of employees. The research was presented a set of recommendations including: increasing the effectiveness of

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Hepatocellular Carcinoma Prediction and early Diagnosis of Hepatitis B and C viral infection using miR-122 and miR-223 in a sample of Iraqi patients.
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Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death. Therefore, it is critical for researchers to understand molecular biology in greater depth.  In several diseases including cancer, abnormal miRNA expression has been linked to apoptosis, proliferation, differentiation, and metastasis. Many miRNAs have been studied in relation to cancer, including miR-122, miR-223, and others. Hepatitis B and C viruses are the most important global risk factors for HCC. This study is intended to test whether serum miRNAs serve as a potential biomarker for both HCC and viral infections HBV and C. The expression of miRNA in 64 serum samples was analyzed by RT-qPCR. Compared to healthy volunteers, HCC patients' sera expre

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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Publication Date
Thu Sep 01 2022
Journal Name
Computers And Electrical Engineering
Automatic illness prediction system through speech
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Publication Date
Thu Oct 07 2021
Journal Name
Bioremediation Journal
Bioremediation of real-field slaughterhouse wastewater associated with power generation in algae-photosynthetic microbial fuel cell
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