For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

Corona virus sickness has become a big public health issue in 2019. Because of its contact-transparent characteristics, it is rapidly spreading. The use of a face mask is among the most efficient methods for preventing the transmission of the Covid-19 virus. Wearing the face mask alone can cut the chance of catching the virus by over 70\%. Consequently, World Health Organization (WHO) advised wearing masks in crowded places as precautionary measures. Because of the incorrect use of facial masks, illnesses have spread rapidly in some locations. To solve this challenge, we needed a reliable mask monitoring system. Numerous government entities are attempting to make wearing a face mask mandatory; this process can be facilitated by using face m

The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.

Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.

The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple

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

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

Schizophrenic patients who are at great risk of relapse are characterized by non-compliance,
denial of illness and need for treatment and no contact with family. So, the prevention of relapse
and readmission to hospital are crucial in mental health practice.
The present study is a descriptive-analytical study that was carried out from November 2nd
2006 through the end of 20 of April 2008.
Objectives: To assess the associated factors with the risk of relapse in schizophrenic patients at
psychiatric hospitals in Baghdad city.
Methodology: A purposive "non-probability" sample of (50) schizophrenic patient who hasd
relapsed was involved in the present study. Data were collected through the use of the constructed
qu

Toxoplasma gondii is a unique intracellular parasite, which infect a large proportion of the world population, but uncommonly causes clinically significant disease. The present study was performed to estimate the prevalence of toxoplasmosis in 400 apparently healthy blood donor males, their ages were between 18 and 57 years using enzyme linked immunosorbent assay, and to examine the effects of infection on total testosterone, free testosterone and follicle stimulating hormone (FSH) levels in their sera. Seroprevalence showed 10 (2.5 %) and 121 (30 %) of them had IgM and IgG antibodies respectively. Both acute and chronic toxoplasmosis in males recorded higher significant (P < 0.05) mean concentration for total and free testosterone hormone,

    As Albizia lebbeck is one of the important species in Iraq and the region, its wood has subjected to investigation through the assessment of differences in its element dimensions and specific gravity under Baghdad conditions. Variations of fiber length, fiber width, cell wall thickness, vessel diameter, and density of wood were examined along the stem and horizontally.  Results showed that fiber lengths were within the normal range, but their widths were narrower than common range of hardwoods. There were little increase in fiber length, width, wall thickness as the height position increased. Vessel diameter has been affected contrarily. No significant effects of  height on specific gravity could be