Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

The objective of this research is to develop a method for applying financial derivatives in the local environment to reduce the risk of foreign exchange rate fluctuations to enhance quality of accounting profits through Financial reporting to local units In accordance with international financial reporting standards, To accomplish this objective was selected a sample of Iraqi units exposed to the risk of fluctuations in foreign currency rates, As the research found:

• many companies and banks in the local environment a lot of losses due to fluctuations in foreign currency exchange rates.
• that financial derivatives in the Iraqi environment represent

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

The second half of the last century witnessed a great scientific revolution that was able to bring about wide changes in various fields, including the field of physical education, which plays a fundamental role in the process of change for the better, and which knocked all the doors of modern science in various aspects and from this perspective we see that students have different capabilities And interests and motives, which require providing a differentiated education, and this depends on the necessity of knowing each student and on the school’s ability to know appropriate strategies for teaching each student so there is no single way to teach so the research problem comes in experimenting with an educational method that works on

In this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τ_i ) which  has

This study focuses on improving the safety of embankment dams by considering the effects of vibration due to powerhouse operation on the dam body. The study contains two main parts. In the first part, ANSYS-CFX is used to create the three-dimensional (3D) Finite Volume (FV) model of one vertical Francis turbine unit. The 3D model is run by considering various reservoir conditions and the dimensions of units. The Re-Normalization Group (RNG) k-ε turbulence model is employed, and the physical properties of water and the flow characteristics are defined in the turbine model. In the second phases, a 3D finite element (FE) numerical model for a rock-fill dam is created by using ANSYS®, considering the dam connection with its powerhouse

A field experiment was conducted at Abu-Ghrib during 2013- 2014 season to study the effect of harrowing systems on the decomposition and fermentation on organic matter(OM) when added and mixed with the soil under special technology, as well as its effect on the growth parameters and productivity of (Zea mays L. 5018). The experiment was laid out using factorial randomized complete block design (RCBD) in split-split design with three replications in SCL bare soil with a percent of moisture ranged from 16 – 18 %. The main plots were designated to the two systems of harrowing (Rotary Harrowand Disc Harrow ). The sub main plots were specified for two organic matters ( Sheep manure ,cow manure ) . Data were statistically analyzed, and