Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN model are identified as the ferritin and a gender variable. The higher results precision was attained by the multilayer perceptron (MLP) networks when we applied the explanatory variables as the inputs with one hidden layer, which covers 3 neurons, as the planned many hidden layers are with one output of the fitting NN model which is use in stages of training and validation beside the actual data. We used a portion of the actual data to verify the behaviour of the developed models, we find that only one observation is false prediction value. This mean that the estimation model has significant parameters to forecast the type of Covid cases (Covid or no Covid) .
In this work, nanostructure aluminum oxide thin films were deposited on glass substrates using a direct current (DC) magnetic reactive sputtering (MRS) technique. A gaseous mixture of argon and oxygen at different mixing ratios was used to synthesize Al2O3 nanoparticles. After extracting Al2O3 powder from the glass substrate, X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), and energy-dispersive spectroscopy (EDS) were used to analyze the structural and morphological properties of the synthesized thin films. The effect of deposition time on the spectral properties, as well as on the size of the nanoparticles, was determined.
In this work, p-n junctions were fabricated from highly-pure nanostructured NiO and TiO2 thin films deposited on glass substrates by dc reactive magnetron sputtering technique. The structural characterization showed that the prepared multilayer NiO/TiO2 thin film structures were highly pure as no traces for other compounds than NiO and TiO2 were observed. It was found that the absorption of NiO-on-TiO2 structure is higher than that of the TiO2-on-NiO. Also, the NiO/TiO2 heterojunctions exhibit typical electrical characteristics, higher ideality factor and better spectral responsivity when compared to those fabricated from the same materials by the same technique and with larger particle size and lower structural purity.
Extracorporeal Shock Wave Lithotripsy (ESWL) is the most commonplace remedy for kidney stone. Shock waves from outside the body frame are centered at a kidney stone inflicting the stone to fragment. The success of the (ESWL) treatment is based on some variables such as age, sex, stone quantity stone period and so on. Thus, the prediction the success of remedy by this method is so important for professionals to make a decision to continue using (ESWL) or tousing another remedy technique. In this study, a prediction system for (ESWL) treatment by used three techniques of mixing classifiers, which is Product Rule (PR), Neural Network (NN) and the proposed classifier called Nested Combined Classi
... Show MoreEmotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
... Show MoreBackground: Recurrent aphthous stomatitis (RAS) is one of the most common oral mucosal disorders with a prevalence of 50-66%. The prevalence of hematinic deficiencies including ferritin and vitamin B12 deficiencies and their role in the prophylaxis and development of RAS is not well known. Many studies have demonstrated a high prevalence of hematinic deficiencies in patients with RAS. This study aimed to compare the serum level of ferritin and vitamin B12 in patients with recurrent aphthous ulcers and healthy controls. Subjects, Materials and Methods: The data were collected from patients who needed blood analysis to exclude anemia from November 2020 to May 2021. The study was approved by the institutional ethics committee. After recordi
... Show MoreBackground/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the
... Show MoreThis study aims to analyze the flow migration of individuals between Iraqi governorates using real anonymized data from Korek Telecom company in Iraq. The purpose of this analysis is to understand the connection structure and the attractiveness of these governorates through examining the flow migration and population densities. Hence, they are classified based on the human migration at a particular period. The mobile phone data of type Call Detailed Records (CDRs) have been observed, which fall in a 6-month period during COVID-19 in the year 2020-2021. So, according to the CDRs nature, the well-known spatiotemporal algorithms: the radiation model and the gravity model were applied to analyze these data, and they are turned out to be comp
... Show MoreBackground: Corona virus disease 2019 (COVID-19) is a communicable disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first identified in December 2019 in Wuhan, China, and has since spread globally, leading to an ongoing pandemic.
Aim of study: to review the clinical, lab investigation and imaging techniques, in pediatric age group affected COVID-19 to help medical experts better understand and supply timely diagnosis and treatment.
Subjects and methods: this study is a retrospective descriptive clinical study. The medical records of patients were analyzed. Information’s recorded include demographic data, exposure history, symptoms, signs, laboratory findin
... Show MoreThe aim of the present study is to compare the biochemical action of the three vaccines taken in Iraq: Pfizer Biontech, AstraZeneca Oxford and Sinopharm based on biochemical parameters. Seventy COVID-19 Iraqi patients ( males and females ) were participated in the present study and classified into 7 groups : Gc : COVID-19 patients ( without vaccine ) , Gp1: COVID-19 patients took one dose of Pfizer Biontech, Gp2 : COVID-19 patients took two doses of Pfizer Biontech, Ga1 : patients took one dose of AstraZeneca Oxford vaccine , Ga2: patients took two doses of AstraZeneca Oxford vaccine , Gs1 : patients took one dose of Sinopharm vaccine and Gs2:
... Show MoreThe aim of this research is to identify the level of mental mindfulness among female students of the College of Education at Umm Al-Qura University, as well as to identify the statistically significant differences in the level of mental mindfulness according to academic level, specialization, and academic achievement. A mental mindfulness scale was designed to cover five dimensions. The study employed the analytic descriptive approach applied to a random sample of (217) female students from various academic specializations. The findings indicated that the level of mental mindfulness was average among female students. Statistically significant differences were attributable to the academic level, academic specializations, and academic achi
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