Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

This study aimed to identify the degree of frustration and guilt among addicts who hurt themselves with drug,  and to know the addicts perspective  who are in treatment clinics and rehabilitation centers  in Palestine, in order to achieve this goal aDeterminationThe study population has been identified , this study population consisted of ' (82) addict, the researcher used the descriptive analytical method which is appropriate for  this  study, so the researcher questioned the addicts who are in treatment clinics and rehabilitation centers  in Palestine and analyze their  responses  in light of some of the variables.

The study results showed that drug addicts who ar

The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a s

Characterized the Middle East has geographic, economic, and geostrategic peculiarities, but it suffers from many problems, such as disagreement over what it means as a concept, or what it represents of a geographic extension. The question is related to the ambiguity surrounding the concept of the Middle East? The purpose of its launch? As it relates to its geostrategic, economic, and geo-cultural importance? And manifestations of this importance? And to what extent he retained his value in the strategies of the major powers? Research hypotheses:

-The multiplicity of concepts for the Middle East region, with international political and Geostrategic interests.- The geostrategic value of the Middle East has made it a focal point for

The rate of births delivered by cesarean section (CS) has gone up substantially all over the world. Post-cesarean surgical site infection (SSI) is a common cause of maternal morbidity and mortality that results in prolonged period of hospitalization with increased cost and direct health implications, especially in low socioeconomic population, resource- restricted settings, and war- related conditions with internal forced movement. This study was aimed to find incidence of post cesarean section surgical site infection withthe accompanying risk factors.Pregnant ladies admitted to department of obstetrics and gynecology at Medical City Hospital in Baghdad who had undergone CSs were followed up prospectively from first of January 2017 till end

In 2020 one of the researchers in this paper, in his first research, tried to find out the Modified Weighted Pareto Distribution of Type I by using the Azzalini method for weighted distributions, which contain three parameters, two of them for scale while the third for shape.This research compared the distribution with two other distributions from the same family; the Standard Pareto Distribution of Type I and the Generalized Pareto Distribution by using the Maximum likelihood estimator which was derived by the researchers for Modified Weighted Pareto Distribution of Type I, then the Mont Carlo method was used–that is one of the simulation manners for generating random samples data in different sizes ( n= 10,30,50), and in di

study aimed to recognize the relationship shyness and depression and to recognize the differences between the genders, according to the variable of shyness and depression, the sample consisted (214) students, (141) female (73) male, and the sample responded scale of shyness and Inventory beck for depression, The Results of this study show that: the sample has a low degree shyness and a high degree depression, . There are no statistically significant differences according to gender variable in shyness, and there are statistically significant differences according to gender variable in depression favor for male, and there are statistically significant relationships between the variables of the study at lev

Because of the vulnerability of the concept of historical cost adopted as a basis for accounting measurement to many of the criticisms in reaction counter to the concept of fair value, the aim of the research is to try to make a comparison between the historical cost and fair value to prove the health and safety of any of the measurement best for the preparation of financial statements and through the state of each of the two study secretary and good financial investment after being diagnosed with a realistic problem is the limitations of the concept of historical cost in the evaluation of assets in spite of the supposed information disclosed in the financial statements compared to appropriate property for the concept of the fair value o

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

Abstract

   The method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.

In this, search th