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 %.
In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform
Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The
... Show MoreImage fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. In this research, there is a solution of problems faced by different digital images such as multi focus images through a simulation process using the camera to the work of the fuse of various digital images based on previously adopted fusion techniques such as arithmetic techniques (BT, CNT and MLT), statistical techniques (LMM,
... Show MoreThe main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model
... Show MoreStarting from 4, - Dimercaptobiphenyl, a variety of phenolic Schiff bases (methylolic, etheric, epoxy) derivatives have been synthesized. All proposed structure were supported by FTIR, 1H-NMR, 13C-NMR Elemental analysis all analysis were performed in center of consultation in Jordan Universty.
Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM
... Show MoreA space X is named a πp – normal if for each closed set F and each π – closed set F’ in X with F ∩ F’ = ∅, there are p – open sets U and V of X with U ∩ V = ∅ whereas F ⊆ U and F’ ⊆ V. Our work studies and discusses a new kind of normality in generalized topological spaces. We define ϑπp – normal, ϑ–mildly normal, & ϑ–almost normal, ϑp– normal, & ϑ–mildly p–normal, & ϑ–almost p-normal and ϑπ-normal space, and we discuss some of their properties.
Abstraet
Students dropout from the Education has a negative phenomena on individual and society and even on different aspects of life especially on the economic aspect , Thus our research tries studying and analyzing the relation between the size of dropout and human development level in Iraq and as (research sample) the first decade of this century as a studying period, the study includes the dropout in Secondary schools and depending the formal records as a main source to evaluate the size of this problem in Iraq , which shows an increase in the size of dropout in this period in comparison with the last decades of the twentieth century, this produces a negative effect on human developme
... Show MoreLaboratory studies were conducted at the biological control unit, college of Agriculture, University of Baghdad to evaluate some biological aspects of the predator Chilocorus bipustulatus (Coleoptera: Coccinellidae), which is considered one of the most important predators on many insect pests, especially the scale insect, Parlatoria blanchardi, (Homoptera: Diaspididae) on date palms. The results showed that biological parameters of the predator were varied according to different degree of temperature. Egg incubation period was significantly different and reached to 7.5 and 5.44 day at 25 and 30°C respectively, Fertility was the same 100% at both temperature degrees. Larval growth periods were 17.41 and 16.12 day as well as the mortality
... Show MoreYoung people represent the power and cornerstone of societies and their superiority is linked to their well-being. Their empowerment is as essential as the heart to the body, if it is corrupt, then the whole body is corrupt, and vice versa. The exposure to extremism and pressure from their families leads to violent acts and crimes for obtaining money through unknown organized bodies. This will drive them to fail in their life in an attempt to fulfill their most basic needs, which they have been deprived of by their families, the government, and other institutions. Therefore, governments should provide job opportunities for young people and provide entertainment centers, sports clubs, and family education centers that raise awareness of s
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