This paper presents a comparison between the electroencephalogram (EEG) channels during scoliosis correction surgeries. Surgeons use many hand tools and electronic devices that directly affect the EEG channels. These noises do not affect the EEG channels uniformly. This research provides a complete system to find the least affected channel by the noise. The presented system consists of five stages: filtering, wavelet decomposing (Level 4), processing the signal bands using four different criteria (mean, energy, entropy and standard deviation), finding the useful channel according to the criteria’s value and, finally, generating a combinational signal from Channels 1 and 2. Experimentally, two channels of EEG data were recorded from six patients who underwent scoliosis correction surgeries in the Pusat Perubatan Universiti Kebangsaan Malaysia (PPUKM) (the Medical center of National University of Malaysia). The combinational signal was tested by power spectral density, cross-correlation function and wavelet coherence. The experimental results show that the system-outputted EEG signals are neatly switched without any substantial changes in the consistency of EEG components. This paper provides an efficient procedure for analyzing EEG signals in order to avoid averaging the channels that lead to redistribution of the noise on both channels, reducing the dimensionality of the EEG features and preparing the best EEG stream for the classification and monitoring stage.
Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th
Abstract
The scope of the humanitarian tragedies in the Arab region has widened after the conflicts that erupted over the past years, exacerbation to include educational, cultural, and social dimensions, economic and moral aspects of the displaced families, especially after the emergence of terrorist organizations and sectarian conflicts which overthrew human and led to various political and demographic changes, forcing citizens to leave their homes, fleeing with their families from the danger of murder, terrorism, and violation to other safer areas inside or outside their countries. Women and children were the vast majority of the displaced who were subjected to great pressures, The host communities bore the pro
... Show MoreNowadays, university education stands in front of both students who feel they are weak and teachers who are addicted to using traditional and dependent teaching. This has led to have negative repercussions on the learner from different aspects, including the mental aspect and the academic achievement process. Therefore, the present research is concerned with finding a new teaching method that adopts the motivation by the fear of failure technique. Thus, the study aims to examine the effect of adopting this method on students’ academic achievement. To achieve this aim, an experimental method was used, and an achievement test was built for the curriculum material of level two students. The pretest test was applied on 17 male and female s
... Show MoreFractal image compression gives some desirable properties like fast decoding image, and very good rate-distortion curves, but suffers from a high encoding time. In fractal image compression a partitioning of the image into ranges is required. In this work, we introduced good partitioning process by means of merge approach, since some ranges are connected to the others. This paper presents a method to reduce the encoding time of this technique by reducing the number of range blocks based on the computing the statistical measures between them . Experimental results on standard images show that the proposed method yields minimize (decrease) the encoding time and remain the quality results passable visually.
Image segmentation can be defined as a cutting or segmenting process of the digital image into many useful points which are called segmentation, that includes image elements contribute with certain attributes different form Pixel that constitute other parts. Two phases were followed in image processing by the researcher in this paper. At the beginning, pre-processing image on images was made before the segmentation process through statistical confidence intervals that can be used for estimate of unknown remarks suggested by Acho & Buenestado in 2018. Then, the second phase includes image segmentation process by using "Bernsen's Thresholding Technique" in the first phase. The researcher drew a conclusion that in case of utilizing
... Show MoreThe Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process
Three-dimensional (3D) image and medical image processing, which are considered big data analysis, have attracted significant attention during the last few years. To this end, efficient 3D object recognition techniques could be beneficial to such image and medical image processing. However, to date, most of the proposed methods for 3D object recognition experience major challenges in terms of high computational complexity. This is attributed to the fact that the computational complexity and execution time are increased when the dimensions of the object are increased, which is the case in 3D object recognition. Therefore, finding an efficient method for obtaining high recognition accuracy with low computational complexity is essentia
... Show MoreBackground: Currently there are four general approaches to correct refractive errors: refractive corneal surgery, crystalline lens surgery and implantation of an intraocular lens in anterior or posterior chamber. Aim: To evaluate the predictability, safety and stability of toric phakic implantable collamer lens implantation to correct moderate to high myopic astigmatism. Methods: Sixty eyes of 40 patients underwent implantation of a toric implantable collamer lens (V4c design) in the Eye Specialty Private Hospital, Baghdad, Iraq were studied. The mean spherical refraction was -11.32±3.17 diopter (D) with a range of -6.00 to -18.00 D and a mean cylinder of -2.61±1.16 with range of -1.00 to -5.50 D. The outcome measures that evaluat
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