Objective: to assess the predictive value of Doppler imaging of the uterine artery in the identification of early intrauterine abnormal pregnancy as compared to a normal intrauterine pregnancy. Subjects and methods: one hundred and twenty pregnant ladies, at their 6-12 weeks of gestation, with a singleton pregnancy were included in this population-based case-control study. Thirty women with a missed miscarriage, 30 with hydatidiform mole, 30 with a blighted ovum, and 30 as a control group, without risk factors, underwent Doppler interrogation of the uterine arteries. Resistive index (RI), pulsatility index (PI), and the systolic/diastolic ratio (S/D) were measured for both sides. The t-test, or ANOVA test when appropriate, was

Objective: to assess the predictive value of Doppler imaging of the uterine artery in the identification of early intrauterine abnormal pregnancy as compared to a normal intrauterine pregnancy.

Subjects and methods: one hundred and twenty pregnant ladies, at their 6-12 weeks of gestation, with a singleton pregnancy were included in this population-based case-control study. Thirty women with a missed miscarriage, 30 with hydatidiform mole, 30 with a blighted ovum, and 30 as a control group, without risk factors, underwent Doppler interrogation of the uterine arteries. Resistive index (RI), pulsatility index (PI), and the systolic/diastolic ratio (S/D) were measured for both sides. The t-test, or ANOVA test when a

The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

In this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe

Background: The rapid evolution of Artificial Intelligence (AI) has significantly influenced Education, demonstrating substantial potential to transform traditional teaching and learning methods. AI reshapes teacher-student interactions and the relationship with knowledge. Objective: To analyze the potential benefits, ethical challenges, and limitations of AI in Education based on recent scientific literature, emphasizing the balance between technology and human interaction. Methods: A documentary research approach with a descriptive focus was employed, following the PRISMA protocol for systematic reviews. The search strategy involved analyzing evidence from 18 scientific articles published within the last six years. Results:AI o

    A faunistic review of the genus Chaitophorus Koch, 1854, including four species in Iraq is given; the distribution data of each species and their hosts have been recorded. In this investigation the poplar leaf aphid Ch. populialbae (Boyer de Fonscolombe, 1841) is recorded here for the first time in Iraq on popular trees Populus euphratica Oliv. during the period from November 2016 to April 2017 in Baghdad province.

    A brief description for apterous viviparous female of this species is given; and a  key to the species of the genus Chaitophorus is constricted.