A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola

Security concerns in the transfer of medical images have drawn a lot of attention to the topic of medical picture encryption as of late. Furthermore, recent events have brought attention to the fact that medical photographs are constantly being produced and circulated online, necessitating safeguards against their inappropriate use. To improve the design of the AES algorithm standard for medical picture encryption, this research presents several new criteria. It was created so that needs for higher levels of safety and higher levels of performance could be met. First, the pixels in the image are diffused to randomly mix them up and disperse them all over the screen. Rather than using rounds, the suggested technique utilizes a cascad

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

In their cross-sectional study, Al-Rubaye et al studied the extent of vitamin D (VD) deficiency/ insufficiency, factors affecting its degree, and the adverse outcomes of the altered VD status among a group of mothers and their neonates from Baghdad, Iraq. They found that 96.6% of the mothers had VD deficiency/ insufficiency compared to 86.4% in their neonates. Maternal VD levels and neonatal weights were significantly correlated with neonatal VD levels. We believe that the study results need to be revised. This is based  two points listed in this letter to editor

Background: Vitamin D deficiency/ insufficiency is common in different age groups in both genders especially among pregnant women and neonates where it is associated with several adverse outcomes including preeclampsia and preterm delivery.   Objectives: To assess the extent of vitamin D deficiency/ insufficiency among mothers and their neonates and some factors related to it and identify some adverse outcomes of the deficiency/ insufficiency on neonates (preterm birth and low birth weight). Subject and Methods: A cross-sectional study was conducted on 88 Iraqi pregnant women and neonates admitted to “Al-Elwiya teaching hospital for maternity” in Baghdad- Al-Rusafah from 1st of June 2019 to 31st of August 2019. Dat

This study is about awareness of teaching explanation difficulties in the Islamic university from the lecturers point of view. It discussed the difficulties and the traditional teaching methods of explanation. The study concentrated on teaching Islamic studies in general and teaching explanation in specific and set difficulties so as to be treated.

            The study is of three chapters, the first contains the difficulties in several aspects like the educational goals, text contents, teaching methods and styles, students, educational techniques, educational aids and evaluation, it addition to the lecturers of Islamic university colleges in 2009-2

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre