Successfully, theoretical equations were established to study the effect of solvent polarities on the electron current density, fill factor and efficiencies of Tris (8-hydroxy) quinoline aluminum (Alq3)/ ZnO solar cells. Three different solvents studied in this theoretical works, namely 1-propanol, ethanol and acetonitrile. The quantum model of transition energy in donor–acceptor system was used to derive a current formula. After that, it has been used to calculate the fill factor and the efficiency of the solar cell. The calculations indicated that the efficiency of the solar cell is influenced by the polarity of solvents. The best performance was for the solar cell based on acetonitrile as a solvent with electron current density of (5.0

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

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

The objectives of the study were to identify the incidence rate and characteristics of adverse drug events (ADEs) in nursing homes (NHs) using the ADE trigger tool and to evaluate the relationships between resident and facility work system factors and incidence of ADEs using the System Engineering Initiative for Patient Safety (SEIPS) model. The study used 2 observational quantitative methods, retrospective resident chart extraction, and surveys. The participating staff included Directors of nursing, registered nurses, certified nurse assistants (CNAs). Data were collected from fall 2016 to spring 2017 from 11 NHs in 9 cities in Iowa. Binary logistic regression with generalized estimated equations was used to measure the association

Every so often, a confluence of novel technologies emerges that radically transforms every aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of human ingenuity are known as industrial revolutions, and we are currently in the midst of the fourth such revolution, coined Industry 4.0 by the World Economic Forum. Building on their guideline set of technologies that encompass Industry 4.0, we present a full set of pillar technologies on which Industry 4.0 project portfolio management rests as well as the foundation technologies that support these pillars. A complete model of an Industry 4.0 factory which relies on these pillar technologies is presented. The full set of pillars encompasses cyberph

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

Concurrently with the technological development that the world is witnessing the crime of money laundering to evolve faster and with multiple methods and its economic, political and social impacts raised increasingly. And for phenomenon dangerous the international community in recent years is keen to be considered combating money laundering as a general indication whereby verification of the international response the stats and its banks and financial institutions with international requirements mandated in this aspect, so the increasing interest the governments of countries in the laws and procedures that contribute to the reduction of the phenomenon of money laundering and avoid legislation economy and the banking and financial sectors

Background: Knowledge is considered to be essential for developing healthy practices and preventing the main oral diseases. In some developing countries, women were at higher risk to develop these diseases. This study was conducted to evaluate women’s dental knowledge and practices through a specific questionnaire and the relationship with patient’s educational level and the number of their children. Subjects and method: Women, aged from 25-35 years old, were selected to participate in the current study. They were attending dental clinics in the teaching hospital of Baghdad University. Each participant was instructed to answer questionnaire sheet which is previously prepared in Arabic language by the authors. The total numb

Objective: To evaluate the knowledge and practices of nursing staff at the orthopedic wards relative to
nursing care presented to patients with femur fractures.
MethodologyThe sample consisted of (50) staff nurses was selected out of orthopedic wards of five
teaching hospital in Baghdad city for duration 15th Nivember 2001-15th of January 2002.
For the purpose of data collection, two instruments were constructed. First, observational
checklist for the practices measurements and second, knowledge test for the evaluation of the nurse
knowledge. Such construction was employed through literature review and validity expert’s responses.
Data were analyzed through the application of descriptive data analysis (frequency, p