Early and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN, residual networks 50 (ResNet-50), densely connected convolutional network 121 (DenseNet-121), and visual geometry group (VGG) 16, with improvements of up to 9.5% in accuracy. The integration of attention mechanisms, image enhancement, and ensemble learning are proving effective in capturing both local and global features, leading to more reliable classification. These findings are suggesting that the proposed framework is supporting automated COVID-19 diagnosis in real-world clinical applications.
The genus Hafnia, a member of the family Enterobacteriaceae, consists of Gram negative bacteria that are occasionally implicated in both intestinal and extraintestinal infections in human. This genus contains only a single species (Hafnia alvei). Methods The above bacterium was identified from 250 bacterial strains which were isolated from 220 urine samples of patients with urinary tract infection. Results One H. alvei strain was isolated from an elderly patient, and identified by conventional biochemical tests and API20E system at the first time in Iraq. Antimicrobial susceptibility test showed that this strain is sensitive to Cefotaxime, Ciprofluxacine, Chloramphenicol, Doxycycline and Trimethoprim-sulfamethaxzole, while it is resistant t
... Show MoreBackground: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to re
... Show MoreTargeted current research study of the relationship between guilt and self-consciousness and consisted of the research community of students from the open educational college, as has been selected students in the Department of Counseling and psychological science department and the researcher used guilt, prepared Scale (Ansari, 2003), and the measure of selfawareness prepared (Shammari 0.2000), and extracted his Alsekoumtria characteristics, Fastkhrjt alternatives after a presentation to a group of experts and specialists in the field of psychological counseling psychology, education, science and psychological validity and reliability Alvakronbach manner and retesting reaching reliability coefficient of guilt ((0.85) and awarenes
... Show MoreSelf-compacting concrete (SCC) has undergone a remarkable evolution recently based on the results from several studies that have indicated the chain of benefits SCC provides. Micro and nano materials used as mineral additives in SCC offer several high-performance properties, and this research studies the effects of micro silica (MS) (10%, used as a reference) and colloidal nano-silica (CNS) (2.5%, 5%, 7.5%, and 10%) on the fresh and hardened properties of SCC. All mixtures were estimated using flow, L-box, and V-funnel tests to examine workability and compressive strength, modulus of elasticity and tensile strength as hardened properties. The use of CNS increased the overall compressi
The educational service industry is one of the most negatively affected industries by the spread of the COVID-19 pandemic. Government agencies have taken many measures to slow its spread, and then restrict movement and gatherings and stop recreational activities. Furthermore, the repercussions of the curfew had a significant impact due to the interruption in actual attendance for students and employees, and the severity of the Covid-19 crisis and its (economic, social, security, humanitarian and behavioral) effects on all societies and work sectors is no secret to anyone. Iraq, like other countries, was also affected by the negative impact of Covid-19 pandemic in all fields of institutional work, especially public fields, and specifically t
... Show MoreThe study aims to identify the degree of appreciation for the level of digital citizenship of a sample of Palestinian university students in the governorates of Gaza, and its relationship to the level of health awareness about the emerging coronavirus (covid-19). To achieve the objectives of the study, the researcher followed a descriptive approach by applying two questionnaires; the first, which consists of 30 items, was used to measure the level of digital citizenship. The second, which consists of 19 items, was used to measure the level of health awareness. Both questionnaires were applied on a sample of 367 students who were electronically selected using the manner simple randomness. Results have shown that the degr
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