There is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardness, Calcium, Magnesium, Total Solids, Nitrite, Nitrates, Ammonia, and Silica are to be used to construct the specific model, while pH, Fluoride, Aluminium, Nitrite, Nitrate, Ammonia, Silica, and Orthophosphate of the treated water were eliminated from the analysis. For modeling the coagulation and flocculation process temperature, Alkalinity and pH of raw water were the depended variables of the model. As for the modeling process turbidity of the treated water was used as the output variable. In general, the linear models including model-driven type, (Multivariate multiple regression, MMR and Multiple linear regression, MLR) have slightly higher prediction efficiencies than the, data-driven type (artificial neural network, ANNM). The coefficients of determination (R2) reached 66 to 85% for the MMR and MLR models and 65 to 81% for the ANN models.
The issue of liquidity, profitability, and money employment, and capital fullness is one of the most important issues that gained high consideration by other authors and researchers in their attempts to find out the real relationship and how can balance be achieved, which is the main goal of each deposits.
For the sake of comprising the study variables, the research has formed the problem of the study which refers to the bank capability to enlarge profits without dissipation in liquidity of the bank which will negatively reflect on the bank's fame as well as the customers' trust. For all these matters, the researcher has proposed a set of aims, the important of which is the estimation of the bank profitability; liquid
... Show MoreData of multispectral satellite image (Landsat- 5 and Landsat-7) was used to monitoring the case of study area in the agricultural (extension and plant density), using ArcGIS program by the method of analysis (Soil adjusted vegetative Index). The data covers the selected area at west of Baghdad Government with a part of the Anbar and Karbala Government. Satellite image taken during the years 1990, 2001 and 2007. The scene of Satellite Image is consists of seven of spectral band for each satellite, Landsat-5(TM) thematic mapper for the year 1990, as well as satellite Landsat-7 (ETM+) Enhancement thematic mapper for the year 2001 and 2007. The results showed that in the period from 1990 to 2001 decreased land area exposed (bare) and increased
... Show MoreAir pollution refers to the release of pollutants into the air that are detrimental to human health and the planet as a whole.In this research, the air pollutants concentration measurements such as Total Suspended Particles(TSP), Carbon Monoxides(CO),Carbon Dioxide (CO2) and meteorological parameters including temperature (T), relative humidity (RH) and wind speed & direction were conducted in Baghdad city by several stations measuring numbered (22) stations located in different regions, and were classified into (industrial, commercial and residential) stations. Using Arc-GIS program ( spatial Analyses), different maps have been prepared for the distribution of different pollutant
In the current digitalized world, cloud computing becomes a feasible solution for the virtualization of cloud computing resources. Though cloud computing has many advantages to outsourcing an organization’s information, but the strong security is the main aspect of cloud computing. Identity authentication theft becomes a vital part of the protection of cloud computing data. In this process, the intruders violate the security protocols and perform attacks on the organizations or user’s data. The situation of cloud data disclosure leads to the cloud user feeling insecure while using the cloud platform. The different traditional cryptographic techniques are not able to stop such kinds of attacks. BB84 protocol is the first quantum cry
... Show MoreThe clinical spectrum of cutaneous leishmaniasis (CL), an intracellular parasitic pathogen, ranges from a single sore healing to chronic crusty lesions with a manifestation of treatment resistance. The complicated interaction between Leishmania bodies and the early immune response, including innate and adaptive mechanisms, determines the evolution of nodules. This study examined the levels of the chemoattractant interleukin 8 (IL-8), pro-inflammatory nitric oxide (NO), and immunoregulatory macrophage inhibitory factor (MIF) in the serum of subjects recently diagnosed with cutaneous leishmaniasis, in parallel with patients being monitored during consecutive sodium stibogluconate (Pentostam) treatment. A total of 161 serum samples of newly di
... Show MoreAsmari is the main productive reservoir in Abu Ghirab oilfield in the south-east part of Iraq. It has history production extends from 1976 up to now with several close periods. Recently, the reservoir suffers some problems in production, which are abstracted as water production rising with oil production declining in most wells. The water problem type of the field and wells is identified by using Chan's diagnostic plots (water oil ratio (WOR) and derivative water oil ratio (WOR') against time). The analytical results show that water problem is caused by the channeling due to high permeability zones, high water saturation zones, and faults or fracturing. The numerical approach is also used to study the water movement inside the reser
... Show MoreThe importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h
... Show MorePrediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
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