In Computer-based applications, there is a need for simple, low-cost devices for user authentication. Biometric authentication methods namely keystroke dynamics are being increasingly used to strengthen the commonly knowledge based method (example a password) effectively and cheaply for many types of applications. Due to the semi-independent nature of the typing behavior it is difficult to masquerade, making it useful as a biometric. In this paper, C4.5 approach is used to classify user as authenticated user or impostor by combining unigraph features (namely Dwell time (DT) and flight time (FT)) and digraph features (namely Up-Up Time (UUT) and Down-Down Time (DDT)). The results show that DT enhances the performance of digraph features by i

KE Sharquie, AA Noaimi, HA Salman, NA Hindy, Iraqi Postgraduate Medical Journal, 2009 - Cited by 1

Background: Cystoid Macular Edema (CME) in its various forms can be considered one of the leading causes of central vision loss in the developed world. It is not a disease itself, It represents a common pathologic sequel of the retina and occurs in a variety of pathological conditions such as, diabetic retinopathy, central or branch retinal vein occlusion(CRVO,BRVO), intraocular inflammation and following cataract extraction. Objective: This study was done to investigate the pattern of CME in patient attending Erbil Teaching Hospitals.Type of the study: Cross- sectional study.Methods and Materials: This is a hospital base cross- sectional study that included 61 patients (75 eyes) conducted at Erbil Teaching Hospitals for six months. All

S Khalifa E, N Adil A, S Husam Ali, H Nibras A…, 2009

The first aim of the present study was performed to assay the activity of arginase in sera of women with uterine fibroid.. This study consisted of(50) women with uterine fibroid as patient's group and (30) healthy women as control group. The age ranged between (30-55) years for the two groups. The results showed that highly significant increas (P< 0.0001) in the arginase activity in sera of women with uterine fibroid (7.99± 0.23) I.U/L is found when compared with healthy group (0.52±0.02) I.U/L. The second aim was performed to isolate arginase from sera of women with uterine fibroids. The purification is done by addition of ammonium sulfate, dialysis, gel filtration chromatography by using sephadex G-50 and ion exchange chromatography by

The first aim of the present study was performed to assay the activity of arginase in sera of women with uterine fibroid.. This study consisted of(50) women with uterine fibroid as patient's group and (30) healthy women as control group. The age ranged between (30-55) years for the two groups. The results showed that highly significant increase (P< 0.0001) in the arginase activity in sera of women with uterine fibroid (7.99± 0.23) I.U/L is found when compared with healthy group (0.52±0.02) I.U/L. The second aim was performed to isolate arginase from sera of women with uterine fibroids. The purification is done by addition of ammonium sulfate, dialysis, gel filtration chromatography by using sephadex G-50 and ion exchange chromatography

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

This investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) s