A high settlement may take place in shallow footing when resting on liquefiable soil if subjected to earthquake loading. In this study, a series of shaking table tests were carried out for shallow footing resting on sand soil. The input motion is three earthquake loadings (0.05g, 0.1g, and 0.2g). The study includes a reviewing of theoretical equations (available in literatures), which estimating settlement of footings due to earthquake loading, calibration, and verification of these equations with data from the shaking table test for improved soil by grouting and unimproved soil. It is worthy to note that the grouting materials considered in this study are the Bentonite and CKD slurries. A modification to the seismic set

Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

UV-Vis technique has been used to study the adsorption of para-nitroaniline (PNA) on Iraqi siliceous rocks powder. Adsorption isotherms were investigated, temperature effect on adsorption was calculated, Results showed that the adsorption was an exothermic process and the thermodynamic functions were calculated. The effect of the pH on adsorption was studied and the ionic strength effect on adsorption was studied, It was found that adsorption increases with the presence of sodium chloride ions. The kinetic study of adsorption before equilibrium showed that the adsorption was pseudo first order according to according (Lagergren equation).

This study employs a critical discourse analysis approach to investigate the linguistic and discursive mechanisms employed by the prominent Russian online news platform Gazeta.ru in its coverage of social news. Drawing on an interdisciplinary framework integrating critical discourse analysis (CDA), media discourse analysis, and sociolinguistic perspectives, the research examines how language is used to construct and disseminate societal narratives. The analysis focuses on a dataset of Gazeta.ru articles published in March 2024, encompassing topics such as health, travel, and consumer affairs. Through a multi-level analytical approach, the study explores macro-level discursive strategies and microlevel linguistic choices, unveiling the intri

Twitter is becoming an increasingly popular platform used by financial analysts to monitor and forecast financial markets. In this paper we investigate the impact of the sentiments expressed in Twitter on the subsequent market movement, specifically the bitcoin exchange rate. This study is divided into two phases, the first phase is sentiment analysis, and the second phase is correlation and regression. We analyzed tweets associated with the Bitcoin in order to determine if the user’s sentiment contained within those tweets reflects the exchange rate of the currency. The sentiment of users over a 2-month period is classified as having a positive or negative sentiment of the digital currency using the proposed CNN-LSTM

Pushover analysis is an efficient method for the seismic evaluation of buildings under severe earthquakes. This paper aims to develop and verify the pushover analysis methodology for reinforced concrete frames. This technique depends on a nonlinear representation of the structure by using SAP2000 software. The properties of plastic hinges will be defined by generating the moment-curvature analysis for all the frame sections (beams and columns). The verification of the technique above was compared with the previous study for two-dimensional frames (4-and 7-story frames). The former study leaned on automatic identification of positive and negative moments, where the concrete sections and steel reinforcement quantities the

Spatial Autoregressive Model (SAR) is one of the modeling frameworks that indicates a spatial dependence in the response variable. SAR model has a weakness, which is represented by the unknown variance of the residuals. Therefore, an alternative model has used titled Spatial Autoregressive Quantile Regression (SARQR) model That which is obtained by combining SAR and Quantile Regression (QR) models, is a regression method with the approach of dividing the data into particular quantiles that are likely to have different estimate values. This alternative model addresses the variance issues in SAR models. Additionally, the SARQR model not only resolves the issue of spatial variance but also serves as a solution for dealing with non-normal data

The purpose of this research is to design a list of the scientific and moral values that should be found in the content of the computer textbook for the second intermediate grade, as well as to analyze the content of the above- mentioned book by answering the following question:

 What is the percentage of availability of scientific and moral values in the content of the computer textbook for Second Intermediate grade issued by the Iraqi Ministry of Education / the general directorate of the curriculum, for the academic year (2017-2018)? 

In order to achieve the research objectives, the descriptive method (content analysis method) was adopted. The research community has been iden

The main objective of this study was to evaluate the adsorption efficiency of two adsorbent materials, Iraqi chicken eggshells (ESh) and activated carbon (AC) derived from ESh powder for the removal of a cationic dye (Janus green B; JGD) from aqueous solution. Activated carbon was synthesised from ESh using a simple chemical activation method using phosphoric acid as the activating agent. The physicochemical properties of the adsorbents were characterised by the Brunauer–Emmett–Teller (BET) method, FT-IR spectroscopy, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), inductively coupled plasma optical emission spectroscopy (ICP-OES), and point of zero charge (pHpzc). The results of BET analysis confirmed th

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that