Deep Learning Techniques For Skull Stripping of Brain MR Images
Heart failure (HF) is characterized by family history and clinical examination combined with diagnostic tools such as electrocardiogram, chest x-ray and an assessment of left ventricular function by echocardiography. An early diagnosis of heart failure is still based on symptoms of dyspnea, fatigue and signs of fluid overload. Serum N-terminal pro-B-type natriuretic peptide (NT-pro BNP) is cardiac biomarker has emerged as potential predictor of heart failure. It is used as a sensitive biomarker in diagnosis and assessment severity of heart failure. This study assed the diagnostic value of (NT-pro BNP), in Iraqi children patients with heart failure and its correlation with LVEF% especially in emergency rooms of hospitals.Ninety (90) consecut
... Show MoreNearly, in the middle of 1970s the split-brain theory became the only theory that explains human creativity used in all fine art and art education schools. In fact, this theory- which appeared for first time in the middle of 1940s – faced many radical changes including its concepts and structures, and these changes affected both teaching art and art criticism. To update people awareness within art field of study, this paper reviews the split-brain theory and its relationship with teaching art from its appearance to its decay in 2013 and after.
Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct
The research aims to identify the impact of using the electronic participatory learning strategy according to internet programs in learning some basic basketball skills for middle first graders according to the curricular course, and the sample of research was selected in the deliberate way of students The first stage of intermediate school.As for the problem of research, the researchers said that there is a weakness in the levels of school students in terms of teaching basketball skills, which prompted the researchers to create appropriate solutions by using a participatory learning strategy.The researchers imposed statistically significant differences between pre and post-test tests, in favor of the post tests individually and in favor of
... Show MoreThe progress of science in all its branches and levels made great civilized changes of
our societies in the present day, it's a result of the huge amount of knowledge, the increase of
number of students, and the increase of community awareness proportion of the importance of
education in schools and universities, it became necessary for us as educators to look at
science from another point of view based on the idea of scientific development of curricula
and teaching methods and means of education, and for the studying class environment as a
whole, by computer and internet use in education to the emergence of the term education
technology, which relies on the use of modern technology to provide educational content to<
IRA Dawood, JOURNAL OF SPORT SCIENCES, 2016 - Cited by 3
E-learning applications according to the levels of enlightenment (STEM Literacy) for physics teachers in the secondary stage. The sample consists of (400) teachers, at a rate of (200) males (50%), and (200)females (50%), distributed over (6) directorates of education in Baghdad governorate on both sides of Rusafa and Karkh. To verify the research goals, the researcher built a scale of e-learning applications according to the levels of STEM Literacy, which consists of (50) items distributed over (5) levels. The face validity of the scale and its stability were verified by extracting the stability coefficient through the internal consistency method “Alf-Cronbach”. The following statistical means were used: Pearson correlation coefficient,
... Show MoreDeep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreIn this paper, an efficient method for compressing color image is presented. It allows progressive transmission and zooming of the image without need to extra storage. The proposed method is going to be accomplished using cubic Bezier surface (CBI) representation on wide area of images in order to prune the image component that shows large scale variation. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, bi-orthogonal wavelet transform is applied to decompose the residue component. Both scalar quantization and quad tree coding steps are applied on the produced wavelet sub bands. Finally, adaptive shift coding is applied to handle the remaining statistical redundancy and attain e
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