Abstract

Backgrounds: Jaundice occurs in most newborn due to increased bilirubin concentration. Jaundice is observed during the first week after birth in approximately 60% of term neonates. A high level of bilirubin is neurotoxic and may cause neonatal kernicterus, auditory neuropathy or death.

Objectives: to compare the Rh group compatibility, serum bilirubin (total and direct), serum albumin and several liver enzymes between physiological and pathological neonatal jaundice

Materials and Methods: A cross sectional study for one hundred neonates with jaundice divided into group 1: 50 newborns with physiological jaundice, Group 2: 50 newborns with

The process of evaluating data (age and the gender structure) is one of the important factors that help any country to draw plans and programs for the future. Discussed the errors in population data for the census of Iraqi population of 1997. targeted correct and revised to serve the purposes of planning. which will be smoothing the population databy using nonparametric regression estimator (Nadaraya-Watson estimator) This estimator depends on bandwidth (h) which can be calculate it by two ways of using Bayesian method, the first when observations distribution is Lognormal Kernel and the second is when observations distribution is Normal Kernel

In this article, we developed a new loss function, as the simplification of linear exponential loss function (LINEX) by weighting LINEX function. We derive a scale parameter, reliability and the hazard functions in accordance with upper record values of the Lomax distribution (LD). To study a small sample behavior performance of the proposed loss function using a Monte Carlo simulation, we make a comparison among maximum likelihood estimator, Bayesian estimator by means of LINEX loss function and Bayesian estimator using square error loss (SE) function. The consequences have shown that a modified method is the finest for valuing a scale parameter, reliability and hazard functions.

            This paper is interested in certain  subclasses of univalent and bi-univalent functions concerning  to shell- like curves connected with k-Fibonacci numbers involving modified Sigmoid activation function θ(t)=2/(1+e^(-t) ) ,t ≥0 in unit disk |z|<1 . For estimating of the initial coefficients |c_2 | , |c_3 |, Fekete-Szego ̈ inequality and the  second Hankel determinant have been investigated for the functions in our classes. 

Performance measures are a central component of management control system, making good planning and control decisions requires information about how different subunits of organizations have performed. To be effective, performance measures (both financial and nonfinancial) must also motivate managers and employees at all levels of organization to strive to achieve organization goals.

To give aclear picture about performance must be used compound measure, that was best than single measure.

Altman model can be used as a compound performance measure that measures the performance by tied a sum of variables, due to make weight for every variable to reach for performance.

This paper compares between the direct and indirect georeferencing techniques in Photogrammetry bases on a simulation model. A flight plan is designed which consists of three strips with nine overlapped images for each strip by a (Canon 500D) digital camera with a resolution of 15 Mega Pixels.

The triangulation computations are carried out by using (ERDAS LPS) software, and the direct measurements are taken directly on the simulated model to substitute using GPS/INS in real case. Two computational tests have been implemented to evaluate the positional accuracy for the whole model and the Root Mean Square Error (RMSE) relating to (30) check points show that th

B Saleem, H Alwan, L Khalid, Journal of Engineering, 2011 - Cited by 2

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv