Medical imaging technology gives a good solution in the diagnosis and treatment of patients suffering from a serious illness. Noise removal from medical images is an important task in medical examination to increase the accuracy in disease detection. Diagnostic imaging is a common term for a wide field of medical examinations such as X-ray, ultrasound images, computed tomography and magnetic resonance imaging. Creating clinical human body images by magnetic resonance imaging (MRI) is an important technique in modern medical science. Unfortunately, medical images suffering from various types of noise. This paper focuses on impulse noise detection and removal system in medical scanned images. The designed system presents a new approach to impulse noise detection in medical images based on visual perceptibility. The detected noise is removed by applying a nonlinear filter to the corrupted pixel only. The proposed method is examined compared with classic filtering procedure and it acts effectively in preserving image details while removing the noise.

This study paper's goal is to assess the viability of producing user-friendly electronics with Brain-Computer Interface (BCI)-based technology. The ultimate goal is to improve the site's accessibility as well as the overall user experience. Brain-computer interfaces, or BCIs for short, are devices that allow direct lines of communication to be established between the brain and outside machinery. By doing away with the need for conventional input methods, this is achieved. The main goal of this research is to design and develop electronic devices that use brain-computer interfaces, or BCIs, to facilitate smooth interaction. This is particularly crucial for people who experience mobility issues. The research has brought to light significant issues related to signal accuracy, usability, and real-time responsiveness. The identification of these problems is achieved by analyzing various BCI technologies and integrating them into common devices. These results provide insight into novel approaches to improve device interfaces, intending to improve their usability and ability to adapt.

The basic idea is to predict a pixel value in a non-distorted frame, and then to compare this value to that in the input (corrupted) image. Usually these two values are different and a decision has to be made upon the pixel value at the filter output. The output can be considered as a sum of the prediction and the prediction error processed in some way. For example, large values of prediction errors can be set to zero because they are classified as caused by impulse noise samples. Soft decisions on classification of prediction errors lead to good results for test images. Three-dimensional median filters of various types are used here as predictors. First of all, vector median filters are used. A median is calculated over windows in consecutive frames, e.g. from the last past frame, from the current frame and the next future frame. Windows in past and future frames are motion-compensated. Prediction error is processed either by a memoryless nonlinear element or even by a 2-D filter. Experimental results with videophone test sequences prove that the filters described are quite efficient.

This paper introduces a new method for the discrimination of impulse noise in medical MRI images. Statistical F-distribution by means of Monte Carlo simulation for forecasting the location of Impulse noise on distorted images is employed. The adaptive noisy pixels are identified as noisy using One-Way ANOVA hypothesis method while the rest of the noisy pixels are selective noisy pixels. Thus, the statistical prediction method is used to predict the noise location on the test images. The distorted portions in the images predicted by this structure are then made better by applying a right kind of nonlinear filtering. The nonlinear median filter is advisable for demonstrating a suitable way of the replacement of the degraded pixels. The filter is not applied to the not-detected regions of the image to remain the same so that delicate details and edges are not spoiled. Experimental results enhanced this structure as it is compared to the classical noise reduction structures.

تتطلب خوارزميات التشفير عالية الأمان مثل AES قدرات حسابية عالية لتحقيق أمن المعلومات. لذلك، من الضروري استخدام بنيات الحوسبة المتوازية التي تستغل التقنيات الحديثة في التوازيات المكانية للحصول على أكبر قدر من القوة الحسابية التي يمكن تصورها. تم إدخال تقنيات مختلفة لتحقيق المعالجة المتوازية. إحداها هي مصفوفات البوابات القابلة للبرمجة ميدانيًا (FPGAs)، والتي تتميز بخصائص جيدة مناسبة لتنفيذ بنيات متوازية مع استهلاك أقل للطاقة. تهدف الورقة إلى تصميم وتنفيذ جهاز إرسال واستقبال مدمج لبنية محرك المعالجة الحاسوبية ذو أداء عالٍ للحصول على إنتاجية أفضل على تقنية FPGA لتشفير وفك تشفير الصور. في هذا التصميم، تم استخدام لوحتين، "DE1_Soc و NEEK board" مع جهاز Altera Quartus prime 18.1، وجهاز cyclone V 5CSEMA5F31C6 FPGA للتوليف والمحاكاة. أظهرت نتائج التنفيذ أن البنية المقترحة تتمتع بكفاءة الأداء من حيث تردد التشغيل 600 ميكا هرتز والإنتاجية 76.8 كيكا هرتز.