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 concept of self is considered one of the important dimensions in the human personality, because feeling of self is an important characteristic in this phase from the psychological point of view.
The first source which forms the concept of self is the physical image, where the built and appearance of the body is considered among the vital matters which determine the person's image of himself/herself.
The current research aims to:
1) Identify the level of physical self concept at the kindergarten children.
2) Identify the level of psychological self concept at the kindergarten children.
3) Iden
... Show MoreIn the past infectious diseases affected the quality of lifestyle during home confinement. The study conducted examines the influence of home confinement during the COVID-19 pandemic outbreak on lifestyle, mental wellbeing, nutritional status, and sleeping pattern.
An online multicategorical questionnaire was distributed to collect demographic information combined with the following tools: Food Frequency Questionnaire (FFQ), International Physical Activity Questionnaire (IPAQ), WHO-5 wellbeing score, and Pittsburgh Sleep Quality Index (PSQI). A snowball non-discriminate sampling procedure was
Apple slice grading is useful in post-harvest operations for sorting, grading, packaging, labeling, processing, storage, transportation, and meeting market demand and consumer preferences. Proper grading of apple slices can help ensure the quality, safety, and marketability of the final products, contributing to the post-harvest operations of the overall success of the apple industry. The article aims to create a convolutional neural network (CNN) model to classify images of apple slices after immersing them in atmospheric plasma at two different pressures (1 and 5 atm) and two different immersion times (3 and again 6 min) once and in filtered water based on the hardness of the slices usin
The study was carried out to detection of H.pylori in (200) patients who attended two teaching hospitals in Baghdad. The diagnosis done by Immunochromatography methods. Stools and blood samples was taken from each patient as well as other (30) healthy control matching in their age. The study included detection the Levels of Interleukin-40 and CRP in sera of patients and control. The result indicated presence of H pylori antigen in 115 cases 59 cases of males and 51 of females, Also, the result indicated increasing levels of IL-40, cholesterol, Triglycerides, Low density lipoprotein, Very Low density lipoprotein increased significantly while the level of High density lipoprotein decreased in patients sera in comparison with healthy c
... Show MoreHBV and HCV are the major causes of chronic liver diseases throughout the world, and constitute a major global health risk. There is accumulated evidence that the imbalance of proinflammatory and anti-inflammatory cytokine production may play an important role in the pathogenesis of viral hepatic infections and may influence the clinical outcome and disease progression. This study was undertaken to analyze the circulating levels of Tumor Necrotic Factor (TNF-α) and Th2 cytokine IL-10 in patients infected with Hepatitis B and C virus. The study population consisted of 30 patients with chronic HBV, in addition to other 30 patients with chronic HCV infection were recruited on their first examination at the Al-Kindy General Hospital in Baghdad
... Show MoreThe research aims to how to deal with certain situation to ensure the continuous competitive excellence of business market under the situation of covid-19, especially how to deal with major challenges, identifying the capabilities of tourism industry, investigating the ability of tourism agencies to resist the dynamic change of both internal as well as external environment to ensure their sustainability.
The important here as the paper notice, is how to be efficient and trying to find solutions in order to grow and survive through choosing certain strategies that aligned the critical issues.
Thus to achieve this level, many scenarios planed that could adopt in case of such pande
... Show MoreThis search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as
... Show MoreThe synchronization of a complex network with optoelectronic feedback has been introduced theoretically, with use of 2×2 oscillators network; each oscillator considered is an optocoupler (LED coupled with photo-detector). Fixing the bias current (δ) and increasing the feedback strength (Ԑ) of each oscillator, the dynamical sequence like chaotic and periodic mixed mode oscillations has been observed. Synchronization of unidirectionally coupled of light emitting diodes network has been featured when coupling strength equal to 1.7×10-4. The transition between non-synchronization and synchronization states by means of the spatio-temporal distribution has been investigated.
Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre
... Show More