In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial lung CT-scans into two groups (COVID-19 and NonCOVID-19) had been proposed. A dataset used is 960 slices of CT scan collected from Iraqi patients /Ibn Al-Nafis teaching hospital. The performance metrics are used in this study (accuracy, recall, precision, and F1 scores). The results indicate that the proposed approach generated a high-quality model for the collected dataset, with an overall accuracy of 98.95% and an overall recall of 97 %.
Most of the mosques in the Islamic world fall under specific and known forms and patterns to a large extent, and such patterns have grown and evolved from the few basic and uniform models, but they changed slowly due to the impact with a mixture of changing functional requirements and cultural landscapes because of the variables of time and place to form patterns known and famous in this day across parts of the Islamic world and its borders. There was no exception to these patterns, but small numbers of mosques that were probably the result of personal experiences or improvisational resolutions, or in response to specific or temporary stimuli. However, the emergence of a specific pattern which does not belong to any of these patt
... Show MoreThis study examines the opportunity presented by the COVID-19 pandemic for city planners and leaders to learn from the crisis and build resilient cities with long-term societal, economic, and environmental resilience against future disasters. The research focuses on the relationship between urban planning and policies and the extent of their resilience, particularly in response to pandemic-related disasters. The study evaluates the ability of the city of Baghdad to respond to the pandemic and identifies gaps in its resilience. The study uses the scorecard measurement instrument to examine the disaster resilience of cities, with a focus on governance and financial capability, disaster planning and preparedness, and disaster response
... Show MoreObjectives: 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
New data on jumping spiders (Salticidae) and tangle-web spiders (Theridiidae) of Armenia are provided on the basis of recently collected specimens in various regions of Armenia. One species, Ballus rufipes (Simon, 1868) is recorded as new to the Caucasus Region, in addition to the following species: Neon reticulatus (Blackwall, 1853), Pellenes brevis (Simon, 1868), Salticus scenicus (Clerck, 1757) and Synageles dalmaticus (Keyserling, 1863) that belong to a family Salticidae, are recorded in Armenia for the first time.
A further 7 species of Theridiidae are recorded in Armenia for the first time Kochiura aulica (C. L. Koch, 1838), Steatoda albomaculata (De Geer, 1778), Steatoda bipunctata (Linnaeus, 1758), Steatoda castanea Clerk, 175
In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
... Show More. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
... Show MoreThis paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar
... Show MoreThis paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar
... Show MoreGiven the importance that the Iraqi banking system in general and Islamic banks in particular, there must be effective supervisory oversight of these banks, as supervisory oversight has an essential and effective role in the development and evaluation of the performance of banks, through the application of legal controls and rules. Banking aimed at making sure that its financial centers are safe, protecting depositors' funds, and achieving both monetary and economic stability. This research studied and evaluates the mechanisms and tools used by the Central Bank of Iraq in the supervision and supervision of these banks. Therefore, the research aimed to measure the type and direction of the relationship between the requirements of supervis
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