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.
<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c
... Show MoreZigbee, which has the standard IEEE 802.15.4. It is advisable method to build wireless personal area network (WPAN) which demands a low power consumption that can be produced by Zigbee technique. Our paper gives measuring efficiency of Zigbee involving the Physical Layer (PL) and Media Access Control (MAC) sub-layer , which allow a simple interaction between the sensors. We model and simulate two different scenarios, in the first one, we tested the topological characteristics and performance of the IEEE802.15.4 standard in terms of throughput, node to node delay and figure of routers for three network layouts (Star, Mesh and Cluster Tree) using OPNET simulator. The second scenario investigates the self-healing feature on a mesh
... Show MoreThe present study investigates the effect of the de-sanding (recycling system) on the bearing capacity of the bored piles. Full-scale models were conducted on two groups of piles, the first group was implemented without using this system, and the second group was implemented using the recycling system. All piles were tested by static load test, considering the time factor for which the piles were implemented. The test results indicated a significant and clear difference in the bearing capacity of the piles when using this system. The use of the recycling system led to a significant increase in the bearing capacity of the piles by 50% or more. Thus it was possible to reduce the pile length by (15 % or more) thus, and implementation costs
... Show MoreThe present study investigates the effect of the de-sanding (recycling system) on the bearing capacity of the bored piles. Full-scale models were conducted on two groups of piles, the first group was implemented without using this system, and the second group was implemented using the recycling system. All piles were tested by static load test, considering the time factor for which the piles were implemented. The test results indicated a significant and clear difference in the bearing capacity of the piles when using this system. The use of the recycling system led to a significant increase in the bearing capacity of the piles by 50% or more. Thus it was possible to reduce the pile length by (15 % or more) thus, and implementation c
... Show MoreThe study area soils suffer from several problems appear as tkhesvat and cracks in the roads and waterlogging which reduces the susceptibility of soil to withstand pressure, this study was conducted on the soil of the Karkh district based on field study that included (6) samples of soil physical analyses contain different ratios of (mud, sand, silt) as percentages (52%, 45%, 3 #) respectively, and liquidity limit rate (39%) Stroke rate plasticity was (20.6%) The rate coefficient of plasticity total (19.2%)0
This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time
... Show MoreRecurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al
... Show MoreIn this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the
... Show MoreIn this paper a new method is proposed to perform the N-Radon orthogonal frequency division multiplexing (OFDM), which are equivalent to 4-quadrature amplitude modulation (QAM), 16-QAM, 64-QAM, 256-QAM, ... etc. in spectral efficiency. This non conventional method is proposed in order to reduce the constellation energy and increase spectral efficiency. The proposed method gives a significant improvement in Bit Error Rate performance, and keeps bandwidth efficiency and spectrum shape as good as conventional Fast Fourier Transform based OFDM. The new structure was tested and compared with conventional OFDM for Additive White Gaussian Noise, flat, and multi-path selective fading channels. Simulation tests were generated for different channels
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