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 primary components of successful engineering projects are time, cost, and quality. The use of the ring footing ensures the presence of these elements. This investigation aims to find the optimum number of geogrid reinforcement layers under ring footing subjected to inclined loading. For this purpose, experimental models were used. The parameters were studied to find the optimum geogrid layers number, including the optimum geogrid layers spacing and the optimum geogrid layers number. The optimum geogrid layers spacing value is 0.5B. And as the load inclination angle increased, the tilting and the tilting improvement percent for the load inclination angles (5°,10°,15°) are (40%,28%, and 5%) respectively. The reduction percent of the
... Show MoreThe primary components of successful engineering projects are time, cost, and quality. The use of the ring footing ensures the presence of these elements. This investigation aims to find the optimum number of geogrid reinforcement layers under ring footing subjected to inclined loading. For this purpose, experimental models were used. The parameters were studied to find the optimum geogrid layers number, including the optimum geogrid layers spacing and the optimum geogrid layers number. The optimum geogrid layers spacing value is 0.5B. And as the load inclination angle increased, the tilting and the tilting improvement percent for the load inclination angles (5°,10°,15°) are (40%,28%, and 5%) respectively. The reduction percent o
... Show MoreThe existing study aimed to assess four soil moisture sensors’ capacitive (WH51 and SKU: S EN0193) and resistive (Yl69 and IC Station) abilities, which are affordable and medium-priced for their accuracy in six common soil types in the central region of Iraq. The readings’ calibration for the soil moisture sensor devices continued through two gravimetric methods. The first depended on the protocols’ database, while the second was the traditional calibration method. The second method recorded the lowest analysis error compared with the first. The moderate-cost sensor WH51 showed the lowest standard error (SE), MAD , and RMSE and the highest R² in both methods. The performance accuracy of WH51 was close to readings shown by the manufac
... Show MoreThis work aims to detect the associations of C-peptide and the homeostasis model assessment of beta-cells function (HOMA2-B%) with inflammatory biomarkers in pregnant-women in comparison with non-pregnant women. Sera of 28 normal pregnant women at late pregnancy versus 27 matched age non-pregnant women (control), were used to estimate C-peptide, triiodothyronine (T3), and thyroxin (T4) by Enzyme-linked-immunosorbent assay (ELISA), fasting blood sugar (FBS) by automatic analyzer Biolis 24i, hematology-tests by hematology analyzer and the calculation of HOMA2-B% and homeostasis model assessment of insulin sensitivity (HOMA2-S%) by using C-peptide values instead of insulin. The comparisons, correlations, regression analysis tests were perfo
... Show MoreSmart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,
... Show MoreIntroduction: This study was designed to examine the effects of addition of the combination of polymerized polymethyl methacrylate (PMMA) and zirconia (ZrO2) particles to heat cure PMMA resin on impact strength, surface hardness, and roughness. Methods: The 70% (w/w) of polymerized PMMA powder (particle size: 0.70mm) was mixed with 30% (w/w) of zirconia powder (ZrO2) (1mm) to produce PMMA-ZrO2 filler. Ninety acrylic specimens created were divided into three groups containing 0% wt (Control group), 2% wt, and 4% wt, PMMA-ZrO2 filler. Ten specimens were used for impact strength, surface hardness and roughness test, blindly. Data were analyzed via oneway ANOVA and the Tukey post hoc test using R 3.6.3. Results: There was statistically signific
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreBackground: The goal of a root canal treatment is three dimensional obturation with a complete seal of the root canal system. The aim of this study was to evaluate and compare the effect of two warm obturation techniques, warm vertical compaction (WVC) and, carrier based obturation technique Gutta Core (GC), versus two cold obturation techniques, cold lateral compaction (CLC) and, single cone (SC) on push-out bond strength of bioceramic sealer (Total Fill) at three different root levels. Materials and Methods: Forty extracted maxillary first molars teeth with a straight round palatal root canal and mature apices were selected for this study. After sectioning the palatal roots to 11 mm from the root apex, the canals were prepared wit
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