The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

Objective(s): To assess mothers’ knowledge about their children with sickle cell anemia and non-Pharmacological approaches to pain management and found some relationship between mothers knowledge and their demographic data of age, level of education, and occupation.
Methodology: A descriptive design used in the present study established was for a period from September 19th, 2020 to March 30th, 2021. The study was conducted on a non-probability (purposive) sample of (30) mother their children with sickle cell anemia was chosen. The data were analyzed through the application of descriptive and inferential statistical approaches which are applied by using SPSS version 22.0.
Results: The findings of the study indicated that moderate

Background: Hypertension is a chronic medical condition in which the blood pressure in the arteries is elevated, it's classified as either primary (essential) hypertension or secondary hypertension, and it increases the risk of ischemic heart disease, peripheral vascular disease and other cardiovascular diseases. Several classes of medications collectively referred to as antihypertensive drugs like beta blockers, calcium channel blockers, angiotensin converting enzyme (ACE) inhibitors, angiotensin receptor blockers, renin inhibitors and statins (HMG-CoA) reductase inhibitor. Statin medication may have some beneficial effects when subjects have dental plaque or signs of periodontitis as gingival bleeding. The purpose of this study were to as

Background: syndrome X or metabolic syndrome is a collection of multiple diseases mainly visceral obesity , hypertriglyceridemia , decrease HDL level, hypertension and elevated fasting blood glucose that lead to accelerated atherosclerosis through multiple mechanisms, one of the most important is increase inflammation of the vessels manifested by elevated high sensitivity C reactive protein (hs-CRP).Objective: The aim of the study was to assess the prevalence of elevatedhs CRP in people with metabolic syndrome and atherosclerosis complication (IHD, Cerebrovascular disease, peripheral vascular disease) and metabolic syndrome without these complication.Patients and methods:;This is a cross sectional study carried out in Diabetic referral c

Abstract Objective: The underlying molecular basis of ischemic heart diseases (IHDs) has not yet been studied among Iraqi people. This study determined the frequency and types of some cardiovascular genetic risk factors among Iraqi patients with IHDs. Methods: This is a cross-sectional study recruiting 56 patients with acute IHD during a 2-month period excluding patients >50 years and patients with documented hyperlipidemia. Their ages ranged between 18 and 50 years; males were 54 and females were only 2. Peripheral blood samples were aspirated from all patients for troponin I and DNA testing. Molecular analysis to detect 12 common cardiovascular genetic risk factors using CVD StripAssay® (ViennaLab Diagnostics GmbH, Austria) was performed

Background: Nutritional Rickets is a condition produced by an absence of Vitamin D, calcium or phosphate. It clues to relaxing and fading of the bones. Dental expression of children with rickets contains enamel hypoplasia and delayed tooth eruption. This study was conducted in order to assess caries experience (dmfs) and enamel defects among study and control groups, and to evaluate and compare the levels of selected salivary biomarkers between children with nutritional rickets and apparently healthy children. Material and methods: Assessment of caries according to WHO in 1987, and assessment of enamel defects according to enamel defect index EDI of WHO in 1997. In addition a stimulated saliva samples were collected according to Palone e