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

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

Background: Proper cleaning and shaping of the whole root canal space have been recognized as a real challenge, particularly in oval-shaped canals.This in vitro study was conducted to evaluate and compare the efficiency of different instrumentation systems in removing of dentin debris at three thirds of oval-shaped root canals and to compare the percentage of remaining dentin debris among the three thirds for each instrumentation system. Materials and methods: Fifty freshly extracted human mandibular molars with single straight oval-shaped distal root canals were randomly divided into five groups of ten teeth each. Group One: instrumentation with ProTaper Universal hand instruments, Group Two: instrumentation with ProTaper Universal rotary

The rapid change in economic is a serious challenge facing all countries around the world, even developed ones. This challenge is increasing as the world enters the age of knowledge in which different knowledge and technologies have emerged and the distance between the emergence of scientific knowledge and its actual application on the ground has been reduced as well as the growing role of science and technology in community development. One of the most important technology amongst these technologies is nanotechnology, where this technology plays a major role in the development of products and modern devices and reduces cost with quality improvement. This technology is cross-cultural, requires a comprehensive knowledge structure and depe

Electrochemical corrosion of hydroxyapatite (HAP) coated performance depends on various parameters like applied potential, time, thickness and sintering temperature. Thus, the optimum parameters required for the development of stable HAP coatings was found by using electrophoretic deposition (EPD) technique. This study discusses the results obtained from open circuit potential-time measurements (OCP-time), potentiodynamic polarisation and immersion tests for all alloy samples done under varying experimental conditions, so that the optimum coating parameters can be established. The ageing studies of the coated samples were carried out by immersing them in Ringer’s solution for a period of 30 days indicates the importance of stable HAP c

In the present work, the focusing was on the study of the x-ray diffraction, dielectric constant, loses dielectric coefficient, tangent angle, alter- natively conductivity and morphology of PET/BaTio3. The PET/BaTio3 composite was prepared for polyethylene terephthalate PET polymer composite containing 0, 10, 20, 30, 40, 50, and 60 wt. % from Barium titanate BaTi03 powder. The composite of two materials leads to form mixing solution and hot-pressing method. The effect of BaTio3 on the structure and dielectric properties with morphology was studied on PET matrix polymer using XRD, LCR meter and SEM.