ABSTRACT: BACKGROUND: Left ventricular hypertrophy is a significant risk factor for cardiovascular complications such as ischemic heart disease, heart failure, sudden death, atrial fibrillation, and stroke. A proper non-expensive tool is required for detection of this pathology. Different electrocardiographic (ECG) criteria were investigated; however, the results were conflicting regarding the accuracy of these criteria. OBJECTIVE: To assess the accuracy of three electrocardiographic criteria in diagnosis of left ventricular hypertrophy in adult patients with hypertension using echocardiography as a reference test. PATIENTS AND METHODS: This is a hospital-based cross sectional observational study which included 340 adult patients with a his

Background: The preparation of Platelet-rich plasma (PRP) is minimally invasive way, simple, low cost to obtain natural autologous growth factors and is now being widely used in different fields of medicine for its ability to increase the regeneration potential of tissue. The aim of this study was to investigate the effect of local application of autologous PRP gel on acceleration rate of osseointegration period by clinical assessment accomplished by determining the changes in implant stability during 3 months healing period using resonance frequency analysis (RFA). Materials and methods: A total of 28 dental implants were inserted in edentulous maxillae or mandibles of 13 patients using a split mouth design, i.e. each patient was received

Background : Although development and progress in various diagnostic methods, but still identification of remnants of skeletal and decomposing parts of human is one of the most difficult skills in forensic medicine . Gender and age estimation is also considering an important problem in the identification of unknown skull. The aims of study: To estimate volume and dimension of maxillary sinus in individuals with dentate and edentulous maxillae using CT scan, and to correlate the maxillary sinus volume in relation to gender and age. Materials and Methods : This study included 120 patients ranged from (40-69 years), divided into two groups, dentate group with fully dentate maxilla and edentulous group with complete edentulous maxilla, and e

This research presents a new algorithm for classification the
shadow and water bodies for high-resolution satellite images (4-
meter) of Baghdad city, have been modulated the equations of the
color space components C1-C2-C3. Have been using the color space
component C3 (blue) for discriminating the shadow, and has been
used C1 (red) to detect the water bodies (river). The new technique
was successfully tested on many images of the Google earth and
Ikonos. Experimental results show that this algorithm effective to
detect all the types of the shadows with color, and also detects the
water bodies in another color. The benefit of this new technique to
discriminate between the shadows and water in fast Matlab pro

Segmentation of urban features is considered a major research challenge in the fields of photogrammetry and remote sensing. However, the dense datasets now readily available through airborne laser scanning (ALS) offer increased potential for 3D object segmentation. Such potential is further augmented by the availability of full-waveform (FWF) ALS data. FWF ALS has demonstrated enhanced performance in segmentation and classification through the additional physical observables which can be provided alongside standard geometric information. However, use of FWF information is not recommended without prior radiometric calibration, taking into account all parameters affecting the backscatter energy. This paper reports the implementation o

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In