Perimenopausal bleeding, is a very common problem, which is an alarming symptom for both; women and their doctors because of the rising fears of cellular changes or tumor of endometrium. In our study we tried to prove that collecting endometrial samples using the outpatient method of Pipelle is as effective as collecting the endometrial samples in the traditional method of Dilation and Curettage (DandC) in operation theatre which necessitates general anesthesia. Ninety four patients more than 40 years old were included in the study, all of them were complaining of abnormal uterine bleeding (pregnant ladies and ladies using hormonal contraception were excluded from the study) and endometrial samples were collected first in outpatient

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

Multipoint forming process is an engineering concept which means that the working surface of the punch and die is produced as hemispherical ends of individual active elements (called pins), where each pin can be independently, vertically displaced using a geometrically reconfigurable die. Several different products can be made without changing tools saved precious production time. Also, the manufacturing of very expensive rigid dies is reduced, and a lot of expenses are saved. But the most important aspects of using such types of equipment are the flexibility of the tooling. This paper presents an experimental investigation of the effect of three main parameters which are blank holder, rubber thickness and forming speed th

The research aims to identify the effect of the training program that is based on integrating futuristic thinking skills with classroom interaction patterns on mathematics teachers in order to provide their students with creative solution skills. The research sample consisted of 31teachers (15 teachers for the experimental group and 16 for the control groups). The researcher developed a measure for the academic self-efficacy consisting of (39) items. Its validity, reliability, coefficient of difficulty and discriminatory power were estimated. To analyze the findings, the researcher adopted the Mann-Whitney (U) test and the effect size, and the findings were as follows: There is a statistically significant difference at the significance leve

High performance self-consolidating concrete HP-SCC is one of the most complex types of concrete which have the capacity to consolidated under its own weight, have excellent homogeneity and high durability. This study aims to focus on the possibility of using industrial by-products like Silica fumes SF in the preparation of HP-SCC enhanced with discrete steel fibers (DSF) and monofilament polypropylene fibers (PPF). From experimental results, it was found that using DSF with volume fraction of 0.50 %; a highly improvements were gained in the mechanical properties of HP-SCC. The compressive strength, splitting tensile strength, flexural strength and elastic modulus improved about 65.7 %, 70.5 %, 41.7 % and 80.3 % at 28 days age, respectively

The world seen rapid developments in the field of information technology within all life fields, particularly the educational field. Usually, we find the traditional educational methods lack a sense of realism and interaction. Solving this problem is by utilizing virtual reality technology to make actual practice present in the classroom. As an interactive technology, it provides students with an accessible, reliable environment that was previously unavailable and offered an opportunity for learning by practicing instead of teacher-centered learning and within a vision that does not look at the past but looks to the future. Virtual reality technology will change the nature of the relationship between the teacher and the student. Thus, the c

The slurry infiltrated fiber concrete (SIFCON) is nowadays considered a special type of high fiber content concrete; it is high strength and high performance material. This paper investigates the effect of spread steel fiber into the slurry mortar on some properties of SIFCON. According to fiber distribution, two sets were used in this investigation. The first set consisted of randomly distributing fibers inside the slurry. The second set was by placing the fibers in an orderly manner inside the slurry. Crimped steel fibers with an aspect ratio of (60) were used. Two different volume fractions percentage of (7% and 9%) by volume of mold were used in both sets for this study. Also, a w/c ratio of (0.35) and superplasticiz

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo