The aim of the research is to study the comparison between (ARIMA) Auto Regressive Integrated Moving Average and(ANNs) Artificial Neural Networks models and to select the best one for prediction the monthly relative humidity values depending upon the standard errors between estimated and observe values . It has been noted that both can be used for estimation and the best on among is (ANNs) as the values (MAE,RMSE, R2) is )0.036816,0.0466,0.91) respectively for the best formula for model (ARIMA) (6,0,2)(6,0,1) whereas the values of estimates relative to model (ANNs) for the best formula (5,5,1) is (0.0109, 0.0139 ,0.991) respectively. so that model (ANNs) is superior than (ARIMA) in a such evaluation.

The present work includes investigation of some features of shell morphology; shell size, shell thickness, shell colour of the land snail Monacha cantiana, in addition to the correlation between height and diameter of shell and between shell aperture diameter and shell diameter at four sites within Baghdad Province, Iraq. Also, measurements of three environmental variables were made; soil temperature, soil moisture and soil calcium content in adition to population density. Shell Aperture Index (Ia) and Shell Index (SI) for individuals from size class ranged between (9-12)mm were measured. The results showed that the deference in shell size by using (Ia) within population related to temperature, moisture and population density but, the valu

The study aims to discuss the relation between imported inflation and international trade of Iraqi economy for the period (1990-2015) by using annual data. To achieve the study aim, statistical and Econometrics methods are used through NARDL model to explain non-linear relation because it’s a model assigned to measure non-linear relations and as we know most economic relations are non-linear, beside explaining positive and negative effects of imported inflation, and to reach the research aim deductive approach was adopted through using descriptive method to describe and determine phenomenon. Beside the inductive approach by g statistical and standard tools to get the standard model explains the

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Tumor necrosis factor-alpha (TNF-α) antagonists’ therapy are expensive and has a non-responsive rate between 30% to 40% in rheumatoid arthritis patients. Genetic variation plays a vital role in the responsiveness to this type of therapy.The aim of this study is to investigate if the presence of genetic polymorphism in the TNF-α gene promoter region at locations -376 G/A (rs1800750), -806 C/T (rs4248158), and -1031 T/C (rs1799964) affects rheumatoid arthritis patient's tendency to be a non-responder to etanercept.

Eighty RA patients on etanercept (ETN) for at least six months were recruited from the Rheumatology Unit at Baghdad Teaching Hospital. Based on The European League Against Rheumatism response (EULAR) criteria, patient

Objectives: This study aims to assess the knowledge, regarding Swine Flu pandemic among a sample of paramedical
specialty students of Medical Technology Institute (Baghdad).
Methodology: The study sample included (110) male and female students, randomly selected, and data was collected by
previously prepared questionnaire including different questions covering different clinic-epidemiological aspects of the
disease and followed by statistical analysis using simple binomial tests and average percentage of correct answers.
Results: The higher percentage of correct responses regarding causative virus 83%, it is respiratory disease 83%,
transmission among people through the droplets 83%, and by touching contaminated surface

Background: The World Health Organization was declared COVID-19 a pandemic on March 11, 2020. As a result, to keep the coronavirus under control, protective technique like face covering is required. Vaccination, on the other hand, is regarded as a preventative and effective measure. As nursing students play an important role in the future of nursing, their perception regarding wearing mask and taking vaccine can be crucial in preventive measures regarding COVID-19. Objective: The purpose of this study was to assess the perception of nursing students’ regarding wearing mask and coronavirus vaccines. Design: A descriptive correlational design was used to guide this study. Settings and Participants: A total of 255 undergraduate

Abstract

The aim of the research is to identify the cognitive curiosity of students of religious schools in the al-Anbar Governorate. The sample consisted of (346) students from the secondary stage in religious schools affiliated with the Department of Religious Education and Islamic Studies. The sample included (232) males, (114) females, and (225) represented the intermediate stage, (121) represented the preparatory stage in religious schools. The researcher developed a scale of perceptual curiosity comprising (30) items with three alternatives (always applicable to me, rarely applicable to me, not applicable to me). The results showed that religious school students have a perceptive curiosity; there are no sta

Land use change, particularly the expansion of urban areas and associated human activities at the expense of natural and semi-natural areas, is a major ecological issue in urban areas around the world. Climate change being a very strong additional driver for changing the temperature and habitat in the cities. This also applies to Baghdad, Iraq, where urbanisation and climate change exerts a major pressure on the natural habitats of the city, and thus may affect the ability of city planners to adapt to future climate change scenarios. Here we present evidence of substantial growth in urban areas, increases in temperature, and degradation of natural vegetation within Baghdad city by using Remote Sensing techniques and an assessment for the