The aim of this paper is to construct cyclic subgroups of the projective general linear group over  from the companion matrix, and then form caps of various degrees in . Geometric properties of these caps as secant distributions and index distributions are given and determined if they are complete. Also, partitioned of  into disjoint lines is discussed.

Reading is an interactive process that goes on between the reader and the text, resulting in comprehension. The text presents letters, words, sentences, and paragraphs that encode meaning. The reader uses knowledge, skills, and strategies to determine what that meaning is. Reading comprehension is much more than decoding; it results when the reader knows which skills and strategies are appropriate for the type oftext, and understands how to apply them to accomplish the reading purpose.Reading comprehension is important because without it reading is nothing more than tracking symbols on a page with your eyes and sounding them out leaving the reader with no information. Instead of promoting traditional approaches, reading should be taught

The current study is concerned with investigating the difficulties that Iraqi EFL learners of English may face when translating English collective nouns. Such collective nouns as committee, government, , jury , Parliament , etc. are considered singular when the concept of the unity as a group is emphasized , but when the concept of the individuals or numbers is emphasized they are treated as plural. A sample of twenty undergraduate students have been selected randomly to translate certain English collective nouns in some selected political texts in order to find out the difficulties they might face in rendering them into Arabic. It is hypothesized that most of the testees have used the singular form rather than the plural ignoring the

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

Background: The excess mortality associated with
rheumatoid arthritis is largely due to
cardiovascular disease. Rheumatoid arthritis is of
primary importance in atherogenesis. The intimamedia thickness of extracranial carotid arteries is a
measurable index of the presence of
atherosclerosis.
Objective: To assess carotid intima-media
thickness in rheumatoid arthritis by Doppler
ultrasound.
Methods: Fifty two Iraqi patients with rheumatoid
arthritis were studied and compared with another
fifty two, healthy individuals matched for age and
sex as a control group. Full history was taken and
complete clinical examination was done for all
individuals in both groups. Rheumatoid arthritis
diagnosis was

Automatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used in this field of study. The literature has reported that the conditions for training and testing are highly correlated. Taken together, these facts support strong recommendations for using MFCC features in similar environmental conditions (train/test) for speaker recognition. However, with noise and reverberation present, MFCC performance is not reliable. To address this, we propose a new feature 'entrocy' for accurate and robu

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

The separation of fluid-fluid mixtures is a major issue in various sectors. The liquid-liquid hydro-cyclone has a wide range of applications in various sectors due to its great efficiency in separating fluid mixtures, ease of installation, and low cost. In crude oil production, high water is consumed following the degrading of production quality, high processing costs, costs, and environmental impacts. Axial hydro cyclone is a tool for Downhole Oil/Water Separation (DOWS) in the petroleum production industry, but it has limitations. The main purpose of this work is to simulate the effect of compacting the conventional inline hydro cyclone with a converging-diverging nozzle on the oil/water dynamic flow and the separation process to

Perimenopausal bleeding, is a very common problem, which is an alarming symptom for both; women and their doctors because of the rising fears of cellular changes or tumor of endometrium. In our study we tried to prove that collecting endometrial samples using the outpatient method of Pipelle is as effective as collecting the endometrial samples in the traditional method of Dilation and Curettage (DandC) in operation theatre which necessitates general anesthesia. Ninety four patients more than 40 years old were included in the study, all of them were complaining of abnormal uterine bleeding (pregnant ladies and ladies using hormonal contraception were excluded from the study) and endometrial samples were collected first in outpatient

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained