Background

Medical child abuse describes a child receiving unnecessary, harmful, or potentially harmful medical care at the caretaker's instigation.

Objectives

To focus on medical child abuse as an entity and emphasize its epidemiology, clinical presentations, prevention, and management.

Results

In the UK, the annual incidence of medical child abuse in children below one year increased to 3:100,000, while its prevalence in Arabs, including Iraq, is ambiguous due to lack of evidence and improper clinician's awareness. The mean age at diagnosis is 14 months to 2.7 years. Female caregivers are the most common offenders. Clinically, medical child abuse

Breast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we

Android operating system, since its first start, is growing very fast and takes a large space in smart devices market. It is built and developed on Linux and designed basically for touch screen devices such as, mobiles, tablets, etc. Mobile devices are markedly complicated and feature-rich; therefore they are prone to reliability of software and performance problems. Because of the small resources, smart devices, such as CPU, RAM, suffer from problems. One of these problems is Software Aging (SA). SA is recognized in long running OSs as a shortage in resources, performance retreating, and finally failure. SA is looked at from two sides, namely the poor response time of application which represents the end user side and the shortage in me

The effect of short range correlations on the inelastic longitudinal
Coulomb form factors for different states of J   4 , T  1with
excitation energies 3.553,7.114, 8.960 and 10.310 MeV in 18O is
analyzed. This effect (which depends on the correlation parameter )
is inserted into the ground state charge density distribution through
the Jastrow type correlation function. The single particle harmonic
oscillator wave function is used with an oscillator size parameter b.
The parameters  and b are considered as free parameters, adjusted
for each excited state separately so as to reproduce the experimental
root mean square charge radius of 18O. The model space of 18O does
not contribute to the tra

Municipal wastewater sources are becoming increasingly important for reuse, for irrigation purposes, so they must be treated to meet environmentally friendly local or global standards. The aim of this study is to establish, calibrate, and validate a model for predicting chemical oxygen demand for the pilot plant of mobile biofilm reactors operating from municipal wastewater in Maaymyrh located in Hilla city Using the approach of dimensional analysis. The approach of Buckingham's theorem was used to derive a model of dimensional analysis design for the forecast of (COD) in the pilot plant. The effluent concentration (COD) It has been derived as a result of the influential concentration of (COD), dissolved oxygen (DO), volume of pilot plant

Accurate predictive tools for VLE calculation are always needed. A new method is introduced for VLE calculation which is very simple to apply with very good results compared with previously used methods. It does not need any physical property except each binary system need tow constants only. Also, this method can be applied to calculate VLE data for any binary system at any polarity or from any group family. But the system binary should not confirm an azeotrope. This new method is expanding in application to cover a range of temperature. This expansion does not need anything except the application of the new proposed form with the system of two constants. This method with its development is applied to 56 binary mixtures with 1120 equili

In this Paper, There are attempts to compare the actual Observation Days in Decametric range (18-28 MHz), For Jupiter received by UFRO Earths’ station with the Prediction Observation Days that the Jupiter can be observed at Jupiter’s suitable location. The Jupiter’s Radio Observations actual data during year 2004, was taken from (Radio JOVE Data Archive website). The determination of the prediction days carried out by using the (Radio-Jupiter pro Jove Edition) software for Jupiter radio storms at UFRO station coordinates. Some Cases are considered according to Jupiter’s altitudes and Sun location at UFRO station Sky. The conclusion is, it could be found that there are (82) number of Predictions Observation Days, and It’s found

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.

In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixe