doi:10.24996/ijs.2020.61.1.9

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Publication Date

Sun Jan 26 2020

Journal Name

Iraqi Journal Of Science

Volume

61

Issue Number

1

DOI

10.24996/ijs.2020.61.1.9

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Mineralogy of Gypsiferous Soil and the Effect of a dditiveLime Stone waste powder on its Physical Properties

Gypsiferous Soil

Limestone waste powder

Atterberg Limit

Grain size analysis

Thalar Othman

Nadhmia Najmaddin

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The presence of gypsum in soil as bonding agent alters its behavior with a large influence on itsphysical properties.Soil samples were taken from two locations of different gypsum content(S1 = 30.5% and S2= 20%) inMakhmur area. TheUnified soil classification system indicated that soil type was clay with low plasticity(CL). Basic methods of physical testing of soils, such as grain size analysis,specific gravity and atterberg limit were applied. Stabilizationof the gypsiferous soil was performed by addinglimestone waste powder takenfrom Said sadiqandPirmam areas,with different percentages(5%, 15%,25%).The results show that the addition of limestone powder to the tested soils decreases their liquid and plastic limits.

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Publication Date

Tue May 16 2023

Journal Name

Journal Of Engineering

Load Distribution Factors For Horizontally Curved Composite Concrete-Steel Girder Bridges

Composite Bridges

AASHTO Loading

Load Distribution Factors

Horizontally Curved Bridges

Finite Element Analysis

Curved I-Girders

Warping Stresses

Rafa'a Mahmood

Zainab Saadi

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This paper focuses on Load distribution factors for horizontally curved composite concrete-steel girder bridges. The finite-element analysis software“SAP2000” is used to examine the key parameters that can influence the distribution factors for horizontally curved composite steel
girders. A parametric study is conducted to study the load distribution characteristics of such bridge system due to dead loading and AASHTO truck loading using finite elements method. The key parameters considered in this study are: span-to-radius of curvature ratio, span length, number of girders, girders spacing, number of lanes, and truck loading conditions. The results have shown that the curvature is the most critical factor which plays an important

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Publication Date

Mon Jun 01 2020

Journal Name

Journal Of Engineering

Arabic Sentiment Analysis (ASA) Using Deep Learning Approach

Deep Learning (DL)

Machine Learning (ML)

Arabic Sentiment Analysis (ASA)

word embedding

Long-Short Term Memory (LSTM)

features

Abdulhakeem Qusay

Ahmed S.

Saman Hameed

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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date

Sun Oct 01 2006

Journal Name

Journal Of The Faculty Of Medicine Baghdad

Alcoholic Liver Disease: Alfa Fetoprotein Alteration, Hematological & Biochemical Characteristics

Alcoholic liver disease

Alfa fetoprotein

gamma glutamyl transpeptidase. Statistical analysis: Chi square tests and the mean value with SD for each value were determined using ANOVA. A p value of <0.05 was considered to be positive.

Aswad

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Background: Alcohol remains the single most significant cause of liver disease throughout the Western world, responsible for between 40 and 80% of cases of cirrhosis in different countries. Many of the factors underlying the development of alcoholic liver injury remain unknown, and significant questions remain about the value of even very basic therapeutic strategies.
Patients and Methods: In a cross sectional study, 113 alcoholic patients with evidence of liver disease in the absence of other significant etiology attending the Gastoenterorology and Hepatology Teaching Hospital between December 2001 and December 2003 were studied for the hematological and biochemical spectrum of alcoholic liver disease in

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Publication Date

Sat Oct 01 2016

Journal Name

Journal Of Theoretical And Applied Information Technology

Factors affecting global virtual teams’ performance in software projects

Today the trend is to perform software development work via distributed geographical area among team

individual or even as an organization. However

due to the global market and international presence of many companies

there is a need to implement a global virtual teams. The global virtual team members are gradually engaged in globalized business environments across space

time and organizational boundaries via information and communication technologies. A global virtual team relies on communication

collaboration

and information exchange are the most important criteria in global virtual teams’ operations. The purpose of this paper is to answer two research questions. The first research question is to identify the factors affecting global virtual teams’ performance. A systematic literature review was conducted to answer the first research question. The second research question is on what the rank of the factor affecting the global virtual teams’ performance according to their level of effect on global virtual teams’ performance. Online survey was conducted within 103 developers and IT managers from eight IT companies to answer the second research question. The Statistical Package for Social Science (SPSS 22) was used to analyze the collected data. In this study

we investigated factors that affect global virtual teams’ performance

factors considered include cultural differences

language problems

time-zone differences

team size

technical problems

lack of trust

lack of sufficient training

and ICT problems. Also the findings indicated that lack of sufficient training is the highest level of effect on global virtual teams’ performance. On the other hand

Ali Yahya Gheni

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