The Electrocardiogram records the heart's electrical signals. It is a practice; a painless diagnostic procedure used to rapidly diagnose and monitor heart problems. The ECG is an easy, noninvasive method for diagnosing various common heart conditions. Due to its unique advantages that other humans do not share, in addition to the fact that the heart's electrical activity may be easily detected from the body's surface, security is another area of concern. On this basis, it has become apparent that there are essential steps of pre-processing to deal with data of an electrical nature, signals, and prepare them for use in Biometric systems. Since it depends on the structure and function of the heart, it can be utilized as a biometric attribute

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

  There are many researches deals with constructing an efficient solutions for real problem having Multi - objective confronted with each others. In this paper we construct a decision for Multi – objectives based on building a mathematical model formulating a unique objective function by combining the confronted objectives functions. Also we are presented some theories concerning this problem. Areal application problem has been presented to show the efficiency of the performance of our model and the method. Finally we obtained some results by randomly generating some problems.

     This manuscript presents a new approach to accurately calculating exponential integral function that arises in many applications such as contamination, groundwater flow, hydrological problems and mathematical physics. The calculation is obtained with easily computed components without any restrictive assumptions

     A detailed comparison of the execution times is performed. The calculated results by the suggested approach are better and faster accuracy convergence than those calculated by other methods. Error analysis of the calculations is studied using the absolute error and high convergence is achieved. The suggested approach out-performs all previous methods  used to calculate this function and this decision is

Background: Listeria monocytogenes, a member of the genus Listeria, is widely distributed in agricultural environments, such as soil, manure and water. The genus of Listeria bacteria is about 15-17 species. It is a pathogenic bacterium that can cause a rare but dangerous infection called listeriosis.

Objectives: Studying the rate of salads contaminated with Listeria bacteria. and Listeria monocytogenes according to International, Arabic and Iraqi specifications and finding the correlation between commitments of restaurants to standard health conditions with contamination with these bacteria

Methods: The study included

Among a collection of ground beetles from Iraq the new species Acinopus euphraticus was designated and described here. The erection of this new species was mainly built on external features and the description of male genitalia.