Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.

Experimental results shows LPG-

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method

In this paper, an experimental study has been conducted regarding the indication of resonance in chaotic semiconductor laser.  Resonant perturbations are effective for harnessing nonlinear oscillators for various applications such as inducing chaos and controlling chaos. Interesting results have been obtained regarding to the effect of the   chaotic resonance by adding the frequency on the systems. The frequency changes nonlinear dynamical system through a critical value, there is a transition from a periodic attractor to a strange attractor. The amplitude has a very relevant impact on the system, resulting in an optimal resonance response for appropriate values related to correlation time. The chaotic system becomes regular under

The mass collision energy loss (dE/dX), the mass radiative energy loss (Srad/) and the total mass stopping power of electrons in the energy range of 0.01 MeV up to 1000 MeV has been calculated for Lung, Urea and Skin. The results of the present work for the mass collision stopping power of electrons in Lung, Urea and Skin are in excellent agreement with the standard results given by ESTAR program, where the maximum percentage error between the present calculated values and that of ESTAR program in Lung tissue, Urea and Skin tissue is 0.27%, 0.3% and 0.8% respectively. The mass radiative energy loss of electrons in the same energy range is also calculated using a modified equation, and the results are found to be in very good agreem

Background: Vasospasm occurs commonly in the intracranial arteries as a complication of subarachnoid haemorrhage. On the other hand, extracranial Internal carotid artery (ICA) vasospasm is scarce, and it may occur due to mechanical manipulation during cerebral angiography. We report a case of cervical carotid artery vasospasm during diagnostic cerebral angiography, which caused anterior cerebral artery territory hypoperfusion, to discuss potential risk factors. Case description: For a 22-year-old female with a ten-year history of epilepsy on multiple drugs, brain magnetic resonance imaging (MRI) showed frontal periventricular developmental venous anomaly. Diagnostic catheter cerebral angiography was used to better identify the vas

This study is unique in this field. It represents a mix of three branches of technology: photometry, spectroscopy, and image processing. The work treats the image by treating each pixel in the image based on its color, where the color means a specific wavelength on the RGB line; therefore, any image will have many wavelengths from all its pixels. The results of the study are specific and identify the elements on the nucleus’s surface of a comet, not only the details but also their mapping on the nucleus. The work considered 12 elements in two comets (Temple 1 and 67P/Churyumoy-Gerasimenko). The elements have strong emission lines in the visible range, which were recognized by our MATLAB program in the treatment of the image. The percen

This paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controll