Background Cardiovascular disease (CVD) is a leading cause of death worldwide. Ischemic heart disease is a major cause of morbidity and mortality. Lack of blood supply to the brain can cause tissue death if any of the cerebral veins, carotid arteries, or vertebral arteries are blocked. An ischemic stroke describes this type of event. One of the byproducts of methionine metabolism, the demethylation of methionine, is homocysteine, an amino acid that contains sulfur. During myocardial ischemia, the plasma level of homocysteine (Hcy) increases and plays a role in many methylation processes. Hyperhomocysteinemia has only recently been recognized as a major contributor to the increased risk of cardiovascular disease (CVD) owing to its eff

ZM Al-Bahrani, Medico Legal Update, 2021

Background:Parkinson’disease(PD) is a neurodegenerative disorder of the central nervous system characterized by resting tremor, bradykinesia, cogwheel rigidity, and impairment of postural reflexes; the frequency of PD increases with aging.Clinically Parkinson's disease characterized by two groups of symptoms: motor and non-motor symptoms.Non-motor symptoms can be categorized as autonomic, cognitive/psychiatric (may include depression, dementia, anxiety, hallucinations), sensory and rapid eye movements (REM) sleep behavior disorder (RBD).

Objectives:The objectives of this study are to find out the frequency of the non-motor symptoms of idiopathic Parkinson disease in a group of patients in Baghd

Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto

Magnetic  Resonance  Imaging  (MRI)  is  one  of  the  most important diagnostic tool. There are many methods to segment the

tumor of human brain. One of these, the conventional method that uses pure image processing techniques that are not preferred because they need human interaction for accurate segmentation. But unsupervised methods do not require any human interference and can segment   the   brain   with   high   precision.   In   this   project,   the unsupervised  classification methods have been used in order to detect the tumor  disease from MRI images.    These metho

Making the data secure is more and more concerned in the communication era. This research is an attempt to make a more secured information message by using both encryption and steganography. The encryption phase is done with dynamic DNA complementary rules while DNA addition rules are done with secret key where both are based on the canny edge detection point of the cover image. The hiding phase is done after dividing the cover image into 8 blocks, the blocks that are used for hiding selected in reverse order exception the edge points. The experiments result shows that the method is reliable with high value in PSNR

Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit