Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first

This research presents a model for surveying networks configuration which is designed and called a Computerized Integrated System for Triangulation Network Modeling (CISTNM). It focuses on the strength of figure as a concept then on estimating the relative error (RE) for the computed side (base line) triangulation element. The CISTNM can compute the maximum elevations of the highest
obstacles of the line of sight, the observational signal tower height, the contribution of each triangulation station with their intervisibility test and analysis. The model is characterized by the flexibility to select either a single figure or a combined figures network option. Each option includes three other implicit options such as: triangles, quadri

In this paper, we calculate and measure the SNR theoretically and experimental for digital full duplex optical communication systems for different ranges in free space, the system consists of transmitter and receiver in each side. The semiconductor laser (pointer) was used as a carrier wave in free space with the specification is 5mW power and 650nm wavelength. The type of optical detector was used a PIN with area 1mm2 and responsively 0.4A/W for this wavelength. The results show a high quality optical communication system for different range from (300-1300)m with different bit rat (60-140)kbit/sec is achieved with best values of the signal to noise ratio (SNR).

This research considers the preservation of environment through recycling old toys. This is achieved by transforming the old toys into educational clothing accessories for kindergarten stages. The research methodology adapts both descriptive and applied approaches. The research questionnaire targeted a sample of 35 teachers to collect information about the waste toys in kindergarten. Also, another sample of 30 teachers and mothers were targeted to measure the suitability of the clothing designs for the early childhood stages. The results shows that both teachers and mothers were well satisfied with clothing accessories designed with the toys waste. This concept contributes to limiting the pollution caused by toys and could save time, eff

The research aims to build a list of digital citizenship axes and standards and indicators emanating from them, which should be included in the content of the computer textbook scheduled for second grade intermediate students in Iraq, and the analysis of the above mentioned book according to the same list using the descriptive analytical method ((method of content analysis)). The research community and its sample consisted of the content of the computer textbook scheduled for the second year intermediate students for the academic year 2018-2019, and the research tool was built in its initial form after reference to a set of specialized literature and previous studies that dealt with topics related to digital citizenship, and the authenticit

The world is currently facing a medical crisis. The epidemic has affected millions of people around the world since its appearance. This situation needs an urgent solution. Most countries have used different solutions to stop the spread of the epidemic. The World Health Organization has imposed some rules that people should adhere. The rules are such, wearing masks, quarantining infected people and social distancing. Social distancing is one of the most important solutions that have given good results to confront the emerging virus. Several systems have been developed that use artificial intelligence and deep learning to track social distancing. In this study, a system based on deep learning has been proposed. The system includes monitor

Objective: To identify barriers to healthcare access, to assess the health literacy levels of the foreign-born Arabic speaking population in Iowa, USA and to measure their prevalence of seeking preventive healthcare services. Methods: A cross-sectional study of native Arabic speaking adults involved a focus group and an anonymous paper-based survey. The focus group and the Andersen Model were used to develop the survey questionnaire. The survey participants were customers at Arabic grocery stores, worshippers at the city mosque and patients at free University Clinic. Chi-square test was used to measure the relationship between the characteristics of survey participants and preventive healthcare services. Thematic analysis was