In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

Background: Investigating dental health knowledge among children is important. Knowing what behaviors are right in relation to dental health does not guarantee that children will practice those behaviors. However, lack of knowledge and misconceptions about dental health may lead to behaviors that are harmful to teeth and gum. Baseline data on knowledge levels are required to determine which particular areas of dental health education are in need of improvement for high-risk children living in different geographical areas. This research was conducted to study the oral health status, dental knowledge and behavior in relation to two different cities, among children in Baghdad and Thamar (republic of Yemen) governorate. Materia

Objective: To find out if there are any significant differences between these women's knowledge in the
management of Breast Self-Examination in study and control group regarding some variables.
Methodology: A quasi-experimental design was used. A purposive "non-probability" sample of (260) women who
are employee and students in both colleges (Nursing and Health and Medical Technologies) was selected. The
sample consists of two groups, experimental group (130) includes those in (Nursing college), and control group
(130) in (Health and Medical Technologies). A questionnaire was constructed which included demographic
information, reproductive information, family history, previous medical history, and information about wome

BACKGROUND: SARS-CoV-2 (COVID-19) is considered a highly infectious and life threatening disease. OBJECTIVE: The present paper aims to evaluate various aspects of preventive measures and clinical management of the scheduled visits for orthodontic patients to the dental clinics during the outbreak of COVID-19, and to assess how orthodontists dealt with this challenge. METHODS: Orthodontists in private and public clinics were invited to fill a questionnaire that addressed infection control protocols and concerns about clinical management of patients in the clinics during the pandemic. Frequncies and percentages of the responses were obtained and compared using Chi-square tests. RESULTS: About 77% of those working in private clinics, a

One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed