Soil suction is one of the most important parameters describing the moisture condition of unsaturated soils. The measurement of soil suction is crucial for applying the theories of the engineering behavior of unsaturated soils.
The filter paper method is one of the soil suction measurement techniques In this paper, five soil samples were collected from five sites within Baghdad city – al-Rasafa region. These soils have different properties and they were prepared at different degrees of saturation. For each sample, the total and matric suction were measured by the filter paper method at different degrees of saturation. Then correlations were made between the soil properties and the total and matric suction. It was concluded that the

Iraqi crude Atmospheric residual fraction supplied from al-Dura refinery was treated to remove metals contaminants by solvent extraction method, with various hydrocarbon solvents and concentrations. The extraction method using three different type solvent (n-hexane, n-heptane, and light naphtha) were found to be effective for removal of oil-soluble metals from heavy atmospheric residual fraction. Different solvents with using three different hydrocarbon solvents (n-hexane, n-heptane, and light naphtha) .different variables were studied solvent/oil ratios (4/1, 8/1, 10/1, 12/1, and 15/1), different intervals of perceptual (15, 30-60, 90 and 120 min) and different temperature (30, 45, 60 and 90 °C) were used. The metals removal percent we

The density functional B3LYP is used to investigate the effect of decorating the silver (Ag) atom on the sensing capability of an AlN nanotube (AlN-NT) in detecting thiophosgene (TP). There is a weak interaction between the pristine AlN-NT and TP with the sensing response (SR) of approximately 9.4. Decoration of the Ag atom into the structure of AlN-NT causes the adsorption energy of TP to decrease from − 6.2 to − 22.5 kcal/mol. Also, the corresponding SR increases significantly to 100.5. Moreover, the recovery time when TP is desorbed from the surface of the Ag-decorated AlN-NT (Ag@AlN-NT) is short, i.e., 24.9 s. The results show that Ag@AlN-NT can selectively detect TP among other gases, such as N2, O2, CO2, CO, and H2O.

The study investigated the behaviour of asphalt concrete mixes for aggregate gradations, according to the Iraqi specification using the Bailey method designed by an Excel spreadsheet. In mixing aggregates with varying gradations (coarse and fine aggregate), The Bailey method is a systematic methodology that offers aggregate interlocking as the backbone of the framework and a controlled gradation to complete the blends. Six types of gradation are used according to the bailey method considered in this study. Two-course prepared Asphalt Concrete Wearing and Asphalt Concrete binder, the Nominal Maximum Aggregate Sizes (NMAS) of the mixtures are 19 and 12.5 mm, respectively. The total number of specimens was 240 for both layers (15 samp

With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp

The research aims to identify how to enhance the quality of the human resources, focusing on four dimensions (efficiency, effectiveness, flexibility, and reliability), by adopting an adventure learning method that combines theoretical and applied aspects at the same time, when developing human resources and is applied using information technology, and that Through its dimensions, which are (cooperation, interaction, communication, and understanding), as the research problem indicated a clear deficiency in the cognitive perception of the mechanism of employing adventure learning dimensions in enhancing human resources quality, so the importance of research was to present treatments and proposals to reduce this problem. To achieve

Abstract

The problem with the search at the reduction of adoption of new products, as there are three hypotheses of research have been formulated , the first one is no significant correlation between the religious and differences to customers and adopt new products, and This Study Aimed To Investigate The Relationship Between Religious differences for customers And New Products Adoption, Applied On Arab Mall Commercial Customers/ Egypt, an Analytical Model Is Developed As Guideline To Test The The Relationship Between Religious differences for customers And New Products Adoption, Aquantative Method With Deductive Approach Were Chosen In This Research . In Order To Collect Primary Data, A questionnaire Is

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med