The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed ANN model to predict BOD of the effluent gave a high degree of correlation reaching 93.5% with seven input parameters. This model can be queried to determine the best combination of operating conditions needed in the wastewater treatment plant to achieve the desired effluent disposal limits.
Background: The first month of life is the most vulnerable period and mortality during this period is an important component of under-5 mortalities. Causes of death in this period are preventable like sepsis, RDS, and asphyxia, while others are not like multiple congenital abnormalities.
Objectives: To study the death rate and main causes of death in the neonatal intensive care unit (NICU) of the Children Welfare Teaching Hospital (CWTH) through the period (2018-2021).
Patients and methods: The death per year for the four years of the study and causes of death were collected retrospectively and analyzed for total death rate and rate for each year, sex distribution, male-to-
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreArtificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin
... Show MoreFlow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel
... Show MoreThis paper presents a hybrid approach called Modified Full Bayesian Classifier (M-FBC) and Artificial Bee Colony (MFBC-ABC) for using it to medical diagnosis support system. The datasets are taken from Iraqi hospitals, these are for the heart diseases and the nervous system diseases. The M-FBC is depended on common structure known as naïve Bayes. The structure for network is represented by D-separated for structure's variables. Each variable has Condition Probability Tables (CPTs) and each table for disease has Probability. The ABC is easy technique for implementation, has fewer control parameters and it could be easier than other swarm optimization algorithms, so that hybrid with other algorithms to reach the optimal structure. In the
... Show MoreThis 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
... Show MoreSurface water flow samples were collected with distances downstream over Saqlawiya main drain whose stretch of about 24.5 km. The drain travels through different land use pattern, before, flowing into Tigris River. Eight sampling points were carefully
selected downstream the channel during dry season. The examined water parameters were pH, NH3, NO3, PO= 4, BOD5, COD, TDS, S.S, Cl-, SO= 4, Na+ , Ca+2, Mg+2, and Oil and Grease. Descriptive and inferential methods through finding the best curve fit correlation were employed in the study to test the strength of the association between water chemical characteristics and distance downstream the channel. A comparison of the values of chemical parameters at the Al-Saqlawiya Drain-Tigris Riv
The Al-Shishtary is considered one of the well-known Andalus poets. His poetry represents a flood of kind emotions, springs from the sincere sources of Divine Love, and this is what we felt in his life and his literary prestige. He was a poet who was familiar withthe art of his timeknowsthe oldand popularintellectual assets ofIslamicSciencesof Sharee'a. This wide culture, which he had, is available to him through his many travels between the coasts of Syria, Egypt and others ... to become Imam of the religion way known as(Al-Shishtariyah)resonatedin the hearts ofthe general publicespecially the poor people. This showshis smoothand influential styleand his humanitarian andsimple words which resonate in the hearts of his followers, therefo
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Number (42) 13 Ramadan 1436 H 30 June 2015
Abu Muhsin al-Thaqafi oscillating between disobedience and obedience
Research Summary
This research deals with the impact of Islam on the poetry of the veterans who realized ignorance and Islam
Persistent and shifting perspective in their poetry, especially those that talk about
Topics deprived of Islam, such as hair, for example. It is known that the description of alcohol is common in
Pre-Islamic poetry, and the Arabs were proud to drink it as proud of their heroism and Frosithm,
And drinking alcohol was associated with religious roots, they thought that the drinker acquires the attributes of God,
He can do the things that gods do, and humans can not. A