This paper deals with prediction the effect of soil remoulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity
according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil remoulding due to actual pile driving. T

Urban land uses are in a dynamic state that varies over time, the city of Karbala in Iraq has experienced functional changes over the past 100 years, as the city is characterized by the presence of significant tourist and socio-economic activity represented by religious tourism, and it occur due to various reasons such as urbanization. The purpose of this study is to apply a Markov model to analyze and predict the behavior of transforming the use of land in Karbala city over time. This can include the conversion of agricultural land, or other areas into residential, commercial, industrial land uses. The process of urbanization is typically driven by population growth, economic development, based on a set of probabilities and transitions bet

One of the most severe problems with flexible asphalt pavements is permanent deformation in the form of rutting. Accordingly, the practice of adding fiber elements to asphalt mix to improve performance under dynamic loading has grown significantly in order to prevent rutting distress and ensure a safe and long-lasting road surface. This paper explores the effects of a combination of ceramic fiber (CF), a low-cost, easily available mineral fiber, and thermal insulator fiber reinforced to enhance the Marshall properties and increase the rutting resistance of asphalt mixes at high temperatures. Asphalt mixtures with 0%, 0.75%, 1.5%, and 2.25% CF content were prepared, and Marshall stability and wheel tracking tests were employed to stu

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

Cardiovascular disease (CVD) remains the leading cause of mortality in women. Estimating cardiovascular risk using prediction models is essential for guiding preventive strategies. Despite progress, conventional risk models still omit critical women-specific factors, limiting their accuracy. Precision medicine, supported by artificial intelligence, provides a framework to integrate these overlooked determinants. This approach may help close existing gaps in cardiovascular risk prediction. Sex-specific biomarkers that contribute to overall cardiovascular risk can be incorporated into risk assessment tools to improve prevention strategies, early detection, and personalized intervention. The integration of imaging-derived variables enh

The most common cause of upper respiratory tract infection is coronavirus, which has a crown appearance due to the existence of spikes on its envelope. D-dimer levels in the plasma have been considered a prognostic factor for COVID-19 patients.

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

Economic organizations operate in a dynamic environment, which necessitates the use of quantitative techniques to make their decisions. Here, the role of forecasting production plans emerges. So, this study aims to the analysis of the results of applying forecasting methods to production plans for the past years, in the Diyala State Company for Electrical Industries.

The Diyala State Company for Electrical Industries was chosen as a field of research for its role in providing distinguished products as well as the development and growth of its products and quality, and because it produces many products, and the study period was limited to ten years, from 2010 to 2019. This study used the descriptive approa

Abstract: This study aims to investigate the backscattering electron coefficient for SixGe1-x/Si heterostructure sample as a function of primary electron beam energy (0.25-20 keV) and Ge concentration in the alloy. The results obtained have several characteristics that are as follows: the first one is that the intensity of the backscattered signal above the alloy is mainly related to the average atomic number of the SixGe1-x alloy. The second feature is that the backscattering electron coefficient line scan shows a constant value above each layer at low primary electron energies below 5 keV. However, at 5 keV and above, a peak and a dip appeared on the line scan above Si-Ge alloy and Si, respectively, close to the interfacing line

The Quality  function deployment (QFD)  tool is an important  tool of total quality management because its a link between two important parts customer and production process of the product, using advanced House of quality, which contributed to provide more details about improving the product before it had a vision for the future of the product be improved. Also the identification of the two competitors (Alwazeer , Altouri) bases on the survey of retailers  which they identified five competitors products (Alwazeer , Altouri , Ferry , Jif , Dina)for the product (Zahi). Then House of quality  to product (Zahi) has been developed  By using a Kano Model  to classify of customer's requirements for the