In this paper, simulation studies and applications of the New Weibull-Inverse Lomax (NWIL) distribution were presented. In the simulation studies, different sample sizes ranging from 30, 50, 100, 200, 300, to 500 were considered. Also, 1,000 replications were considered for the experiment. NWIL is a fat tail distribution. Higher moments are not easily derived except with some approximations. However, the estimates have higher precisions with low variances. Finally, the usefulness of the NWIL distribution was illustrated by fitting two data  sets

This study been conducted and applied in Alrashed Health Center/Mahmodia Sector/ kerigh Sector/Ministry of Health/Baghdad City, and conducted on samples of women who are suffering from iron deficiency (Hemoglobin%) in blood for the year 2013. Fifty women been selected (married, unmarried), their ages ranging between 19-40 years old, they been given dried grinding spinach tablet. The dose been given was 3 tablet/day/4-6 weeks, after taken the percentage of Hemoglobin and Uric acid for all studied samples before and after dried spinach tablet given. It was appeared from samples analysis primarily and statically for 50 women, that 4% upon them only suffering high Iron deficiency (8.0-9.9 mg/100ml), 38% upon them suffering from middle iron def

The massive distribution and development in the digital images field with friendly software, that leads to produce unauthorized use. Therefore the digital watermarking as image authentication has been developed for those issues. In this paper, we presented a method depending on the embedding stage and extraction stag. Our development is made by combining Discrete Wavelet Transform (DWT) with Discrete Cosine Transform (DCT) depending on the fact that combined the two transforms will reduce the drawbacks that appears during the recovered watermark or the watermarked image quality of each other, that results in effective rounding method, this is achieved by changing the wavelets coefficients of selected DWT sub bands (HL or HH), followed by

The fingerprints are the more utilized biometric feature for person identification and verification. The fingerprint is easy to understand compare to another existing biometric type such as voice, face. It is capable to create a very high recognition rate for human recognition. In this paper the geometric rotation transform is applied on fingerprint image to obtain a new level of features to represent the finger characteristics and to use for personal identification; the local features are used for their ability to reflect the statistical behavior of fingerprint variation at fingerprint image. The proposed fingerprint system contains three main stages, they are: (i) preprocessing, (ii) feature extraction, and (iii) matching. The preprocessi

Background: Obesity tends to appear in modern societies and constitutes a significant public health problem with an increased risk of cardiovascular diseases.

Objective: This study aims to determine the agreement between actual and perceived body image in the general population.

Methods: A descriptive cross-sectional study design was conducted with a sample size of 300. The data were collected from eight major populated areas of Northern district of Karachi Sindh with a period of six months (10^th January 2020 to 21^st June 2020). The Figure rating questionnaire scale (FRS) was applied to collect the demographic data and perception about body weight. Body mass index (BMI) used for ass

In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into