the pursue of social  systems history present to us solid evidence that the collapse of  that systems be caused by either the stagnancy aftermath maturity or unreal intellectual foundation which lead to sudden collapse, while the capitalism can avoided that intellectual damages due to its dynamic system with appropriate  auto adaptation mechanism and use it excellently in the right time.

The globalization had excrete (as one of the capitalism adaptation mechanism) its own targets and its methods in framework of multinationals corporations which consist with capitalism states that employed the international organizations to reconstruction the global economy to serve such targets. So the glob

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

Objectives: The purpose of the study is to ascertain the relationship between the training program and the socio-demographic features of patients with peptic ulcers in order to assess the efficiency of the program on patients' nutritional habits.

Methodology: Between January 17 and October 30 of 2022, The Center of Gastrointestinal Medicine and Surgery at Al-Diwanyiah Teaching Hospital conducted "a quasi-experimental study". A non-probability sample of 30 patients for the case group and 30 patients for the control group was selected based on the study's criteria. The study instrument was divided into 4 sections: the first portion contained 7 questions about demographic information, the second sect

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

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

Objectives: To determine the (QoL) for patients with permanent pacemaker and to find-out the relationship between
these patients’ (QoL) and their sociodemographic characteristics such as age, gender, level of education, and
occupation.
Methodology: ٨ purposive non-probability” sample of (62) patient with permanent pacemaker was involved in this
study. The developed questionnaire consists of (4) parts which include !.demographic data form, 2.disease-related
information form, 3.socioeconomic data form, and 4.Permanent pacemaker patient’s quality of life questionnaire data
form. The validity and reliability of the questionnaire were determined through the application of a pilot study. ٨
descriptive statistical a

Objective: The present study aims to assess the stressful life events for patients with substance abuse in Baghdad city.
Methodology: A descriptive study was carried out at (Baghdad teaching hospital and Ibn-Rushed Psychiatric hospital).
Starting from 1
st of December 2012 to 3
rd of July 2013, A non-probability (purposive) sample of 64 patients that
diagnosed with substance abuse, the data were collected through the use of semi-structured interview by
questionnaire, which consists of three parts sociodemographic data, medical information, and Life events scale
consists of 49-items distributed to six domains including, family and social domain, health domain, security, legal and
criminal domain, work and school do