The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial voids ratio. Multi-layer perceptron training by the backpropagation algorithm was used in creating the network. It was found that both models can predict shear strength parameters for gypseous soils with good reliability. Sensitivity analysis of the first model indicated that dry unit weight and plasticity index have the most significant effect on the predicted cohesion. While in the second model, the results indicated that the gypsum content and plasticity index have the most significant effect on the predicted angle of internal friction.
The study using Nonparametric methods for roubust to estimate a location and scatter it is depending minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .
It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu
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The results showed that the organic fertilizer mixture (1:1) 30 tons/ha with chemical fertilization recorded the lowest level of bulk density of 1.2 g/cm3, the organic fertilizer mixture (1:1) 30 tons/ha with chemical fertilization recorded the highest percentage of aggregation stability amounting to 16.17%, the organic fertilizer palm fronds recorded the highest level of ready water with an average of 5.50 cm3/cm3 and the organic fertilizer mixture (1:1) 30 tons/ha without chemical fertilization recorded the highest level of ready water as it reached 6.93%, the or
... Show MoreBackground: Neural tube defects (NTDs) are said to be inherited in a multifactorial fashion, i.e. genetic-environmental interaction. Maternal nutritional deficiencies had long been reported to cause NTDs, especially folate deficiency during early pregnancy. More attention had been paid to the exact mechanism by which this deficiency state causes these defects in the developing embryo. The most significant of all researches was that connecting reduced folate and increased homocysteine level in maternal serum on one hand and the risk of developing a NTD baby on the other hand. Objectives : to determine the significance of homocysteine level in Iraqi mothers who gave birth to babies with NTDs as compared to normal controls. Patients, Materials
... Show MoreIn present study the effect of soil extracts of different types of soil on ability of two clinical isolates, Pseudomonas aeruginosa and Staphylococcus aureus to form biofilm. The extract of soil was done by using sterile phosphate buffer saline and analyzed by Fourier Transform Infrared Spectroscopic (FTIR). Spectrophotometric method was used to check ability of the studied isolated bacteria to form biofilm on polystyrene microtiter plates. The data of FTIR showed very little difference was observed among extracts of three types of soil (soil contaminated with hydrocarbons; garden soil collected from gardens of al-jadrea, Baghdad and containers soil), but the highest difference was observed in the extract obtained from peat moss clay soil.
... Show MoreThe current study was conducted to find out the effect of the sediment source (sedimentary of Iraqi-Iranian borderline and Tigris River) on the content and distribution of feldspar minerals and their effect on the optical properties of these minerals in some soils of Wasit and Maysan province. Eight pedons were chosen to represent the study area, five of them represented sediments coming from the borderline, which included pedons of (Badra, Taj Al-Din, Al-Shihabi, Jassan, and Galat), while two of them represent the sediments of the Tigris River (Essaouira, Al-Dabouni). Finally, the pedon of Ali Al-Gharbi represented the mixing area of sediments of all the torrents coming from borderline and the sediments of the Tigris River. The diagnostic
... Show MoreThe prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff
... Show MoreGenome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id
... Show MoreThis paper compare the accurecy of HF propagation prediction programs for HF circuits links between Iraq and different points world wide during August 2018 when solar cycle 24 (start 2009 end 2020) is at minimun activity and also find out the best communication mode used. The prediction programs like Voice of America Coverage Analysis Program (VOACAP) and ITU Recommendation RS 533 (REC533 ) had been used to generat HF circuit link parameters like Maximum Usable Frequency ( MUF) and Frequency of Transsmision (FOT) .Depending on the predicted parameters (data) , real radio contacts had been done using a radio transceiver from Icom model IC 7100 with 100W RF
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