Cervical cancer is the third most common cancer in women worldwide, and it has the fourth highest mortality rate among cancers in women. The present study aimed to reveal the impact of age factor in cervical abnormalities and cancers incidence in some Iraqi married women. 150 scraping cervical cells samples were collected from the women clinically diagnosed with cervical abnormalities and cancer who were divided into two groups; the first group included the women with abnormal pap smear which revealed 13.33% of women were less than 30 years and followed by 66.66% of women whose age between 30-50 years and 20% of them were more than 50 years old. While the second group iclude the women with normal Pap smear (Healthy women) which revealed tha

Peripheral neuropathy represents one of the common diabetic complications in patients with diabetes mellitus type 2 (DMT2). Peripheral neuropathy affects the feet, legs, hands, and arms. It was found that one-third to one-half of diabetics have peripheral neuropathy. The current study aimed to evaluate the level of visfatin in diabetic patient groups with or without peripheral neuropathy in comparison with healthy subjects to knowledge whether visfatin can be applied as a predictor factor for this type of disease complication. The study included 120 males and females ranging in age from 40 to 97 years old. (40 patients with type 2 diabetes, 40 patients with diabetic peripheral neuropathy, and 40 healthy people served as the control group

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

Burdock ( Arctium lappa), is among the most popular plants in traditional medicine and it is associated with several biological effects. Literature survey revealed the presence of phenylpropanoid compounds .The most widespread are hydroxycinnamic acids ( mainly caffeic acid and chlorogenic acid) and lignans (mainly arctiin and arctigenin). This work will confirm the presence of these compounds in Arctium lappa, cultivated in Iraq, in both root and leaf samples.  The dried plant samples were extracted by soxhlet with 80% methanol then separated the main constituents by thin layer chromatography (TLC) and high performance liquid  chromatography (HPLC). Identification of the isolated compounds wa

Using watermarking techniques and digital signatures can better solve the problems of digital images transmitted on the Internet like forgery, tampering, altering, etc. In this paper we proposed invisible fragile watermark and MD-5 based algorithm for digital image authenticating and tampers detecting in the Discrete Wavelet Transform DWT domain. The digital image is decomposed using 2-level DWT and the middle and high frequency sub-bands are used for watermark and digital signature embedding. The authentication data are embedded in number of the coefficients of these sub-bands according to the adaptive threshold based on the watermark length and the coefficients of each DWT level. These sub-bands are used because they a

Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing

Abstract

Zigbee is considered to be one of the wireless sensor networks (WSNs) designed for short-range communications applications. It follows IEEE 802.15.4 specifications that aim to design networks with lowest cost and power consuming in addition to the minimum possible data rate. In this paper, a transmitter Zigbee system is designed based on PHY layer specifications of this standard. The modulation technique applied in this design is the offset quadrature phase shift keying (OQPSK) with half sine pulse-shaping for achieving a minimum possible amount of phase transitions. In addition, the applied spreading technique is direct sequence spread spectrum (DSSS) technique, which has

A 3D geological model is an essential step to reveal reservoir heterogeneity and reservoir properties distribution. In the present study, a three-dimensional geological model for the Mishrif reservoir was built based on data obtained from seven wells and core data. The methodology includes building a 3D grid and populating it with petrophysical properties such as (facies, porosity, water saturation, and net to gross ratio). The structural model was built based on a base contour map obtained from 2D seismic interpretation along with well tops from seven wells. A simple grid method was used to build the structural framework with 234x278x91 grid cells in the X, Y, and Z directions, respectively, with lengths equal to 150 meters. The to

The demand for single photon sources in quantum key distribution (QKD) systems has necessitated the use of weak coherent pulses (WCPs) characterized by a Poissonian distribution. Ensuring security against eavesdropping attacks requires keeping the mean photon number (µ) small and known to legitimate partners. However, accurately determining µ poses challenges due to discrepancies between theoretical calculations and practical implementation. This paper introduces two experiments. The first experiment involves theoretical calculations of µ using several filters to generate the WCPs. The second experiment utilizes a variable attenuator to generate the WCPs, and the value of µ was estimated from the photons detected by the BB