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

Baghdad, one of Iraq’s most crowded cities, faces severe air pollution caused by rapid population growth, dense traffic, and limited green spaces. Monitoring at five sites in Al-Rusafa during 2024–2025 showed that pollutant levels, especially PM₁₀, PM₂.₅, and TSP, exceed national and global limits. The most polluted areas lacked vegetation and had heavy traffic, while greener zones showed lower concentrations. Seasonal variations were evident: winter had the highest pollution, summer the lowest but with greater plant stress. Ascorbic acid and the Air Pollution Tolerance Index (APTI) proved reliable indicators of plant resistance. Overall, the study confirms plants’ role as effective bio monitors and stresses the need f

An investigation was conducted for the improvement of viscosity index of a lubricating oil fraction (SAE – 30) obtained from vacuum distillation unit of lube oil plant of Daura Refinery, using solvent extraction process. In this study two type of extraction solvents were used to extract the undesirable materials which reduce the viscosity index of raw lubricating oil fraction, the first solvent was furfural which is un use today in the Iraqi refineries and the second was NMP (N-methyl, 2, pyrrolidone) which is used for the first time in this work to extract the lubricating oil fraction produced from Iraqi crude oils. The studied effecting variables of extraction are extraction temperature range from 70 to 110 oC for furfural and NMP ex

The study aims to build a water quality index that fits the Iraqi aquatic systems and reflects the environmental reality of Iraqi water. The developed Iraqi Water Quality Index (IQWQI) includes physical and chemical components. To build the IQWQI, Delphi method was used to communicate with local and global experts in water quality indices for their opinion regarding the best and most important parameter we can use in building the index and the established weight of each parameter. From the data obtained in this study, 70% were used for building the model and 30% for evaluating the model. Multiple scenarios were applied to the model inputs to study the effects of increasing parameters. The model was built 4 by 4 until it reached 17 parame

ABSTRACT

            This study aimed to choose top stocks through technical analysis tools specially the indicator called (ratio of William index), and test the ability of technical analysis tools in building a portfolio of shares efficient in comparison with the market portfolio. These one technical tools were used for building one portfolios in 21 companies on specific preview conditions and choose 10 companies for the period from (March 2015) to (June 2017). Applied results of the research showed that Portfolio yield for companies selected according to the ratio of William index indicator (0.0406) that

Groundwater quality investigation has been carried out in the western part of Iraq (west longitude '40°40). The physicochemical analyses of 64 groundwater samples collected from seven aquifers were used in the determination of groundwater characterization and assessment. The concept of spatial hydrochemical bi-model was prepared for quantitative and qualitative interpretation. Hydrogeochemical data referred that the groundwater is of meteoric origin and has processes responsible for observed brackishness. The geochemical facies of the groundwater reveal that none of the anions and cations pairs exceed 50% and there are practically mixtures of multi-water types (such as Ca–Mg–Cl–HCO₃ and Na+K–SO4–Cl water type) as do

The rise in the general level of prices in Iraq makes the local commodity less able to compete with other commodities, which leads to an increase in the amount of imports and a decrease in the amount of exports, since it raises demand for foreign currencies while decreasing demand for the local currency, which leads to a decrease in the exchange rate of the local currency in exchange for an increase in the exchange rate of currencies. This is one of the most important factors affecting the determination of the exchange rate and its fluctuations. This research deals with the currency of the European Euro and its impact against the Iraqi dinar. To make an accurate prediction for any process, modern methods can be used through which

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

Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) col

Background: Determination of local bone mineral density (BMD) immediately after implant insertion play an important role in implant success rate, may offer comprehensive description of the bone, and give enough information to the surgeon prior to implant insertion and at follow up status. The aim of the present study is to evaluate the changes of local bone density in the dental implant recipient sites by using computerized tomography. Material and method: The sample consisted of (20) dental implants recipient sites, bone density assessment was done twice, immediately after implants insertion and after six months. Results: The mean HU of the bone around the implant insertion site, immediately after implant placement was 552.28 HU, and inc