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jcoeduw-1354
Obese Women and Choosing Ready-made Clothes: Difficulties and Choices
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Thisstudy aims to determine the specifications of obese women accordingto the heightand type of obesity. It also aimstoidentify the significance of differences in choosing ready-made clothes for the research sample. Finally, the significance of differences in choosing ready-made clothes according to the variable of binaryclassification ofobesity is also identified.The study sample includes obese women: employees, non-employees and students with the age group (18-50) years.The weights and lengths of the sample have been taken to suit the group of obese women.Aquestionnaire in the form of an open question was distributed among (50) obese womenso as to extract the items of the questionnaire. After that, the questionnaire was distributed among (100) obese women to obtain answers. Thedata were statistically analyzed and the BMI indicated thatthere were four types of obesity for the sample studied: overweight and high obesity, very high obesity, excessive obesity, and obese to the extreme.Itwas called abinary classification. The first type included (42) obese women,whilethe second type included (58) obese women .The bodies of the sample were identified: (22%)of the sample representedshort obese women,the ratio of (68%) represented obese women of medium-length, and the proportion of (10%)represented tall obese women. It has become clear through the recognition of the significance of differences when choosing clothes in general, that  they areall statistically significantexcept for the seventh item (the best clothes are those with dark-colors, because they make me look thinner). Besides,there are no individual differencesin the sample responses in favor of the answer (sometimes) at the rate of (5.180).

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Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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Publication Date
Tue Jun 15 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Pathological Mechanisms of Obesity-Related Glomerulopathy: A review article
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The rising prevalence of obesity-related glomerulopathy (ORG) occurs in accordance with the rising prevalence of obesity worldwide. Clinically ORG is manifested by slowly progressing microalbuminuria that may develop to clinically evident proteinuria. Pathological characteristics of ORG include glomerular hypertrophy in the presence or absence of focal segmental glomerulosclerosis (FSGS). ORG can develop into clinically overt chronic renal insufficiency or even end-stage kidney disease. This article reviews the most important mechanisms for the development of ORG; that are abnormal renal hemodynamics, stimulation of renin-angiotensin-aldosterone system (RAAS), impairment of insulin sensetivity, ectopic lipid deposition, adipose tissue cy

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
Performance Evaluation of Scalar Multiplication in Elliptic Curve Cryptography Implementation using Different Multipliers Over Binary Field GF (2233)
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This paper presents a point multiplication processor over the binary field GF (2233) with internal registers integrated within the point-addition architecture to enhance the Performance Index (PI) of scalar multiplication. The proposed design uses one of two types of finite field multipliers, either the Montgomery multiplier or the interleaved multiplier supported by the additional layer of internal registers. Lopez Dahab coordinates are used for the computation of point multiplication on Koblitz Curve (K-233bit). In contrast, the metric used for comparison of the implementations of the design on different types of FPGA platforms is the Performance Index.

The first approach attains a performance index

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Double-Staged Syndrome Coding Scheme for Improving Information Transmission Security over the Wiretap Channel
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This paper presents a study of a syndrome coding scheme for different binary linear error correcting codes that refer to the code families such as BCH, BKLC, Golay, and Hamming. The study is implemented on Wyner’s wiretap channel model when the main channel is error-free and the eavesdropper channel is a binary symmetric channel with crossover error probability (0 < Pe ≤ 0.5) to show the security performance of error correcting codes while used in the single-staged syndrome coding scheme in terms of equivocation rate. Generally, these codes are not designed for secure information transmission, and they have low equivocation rates when they are used in the syndrome coding scheme. Therefore, to improve the transmiss

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
Satellite Images Classification in Rural Areas Based on Fractal Dimension
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Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Satellite image classification using proposed singular value decomposition method
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In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Face-based Gender Classification Using Deep Learning Model
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Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

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Publication Date
Tue Dec 31 2019
Journal Name
Iraqi Geological Journal
CLIMATIC WATER BALANCE FOR ISHAQI AREA, SALAH AL-DEAN GOVERNORATE, IRAQ
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In any natural area or water body, evapotranspiration is one of the main outcomes in the water balance equation. It is also a crucial component of the hydrologic cycle and considers as the main requirement in the planning and designing of any irrigation project. The climatic parameters for the Ishaqi area are calculated from the available date of Samarra and Al-Khlais meteorological stations according to a method for the period (1982–2017) according to Fetter method. The results of the mean of rainfall, relative humidity temperature, evaporation, sunshine, and wind speed of the Ishaqi area are 171.96 mm, 49.67%, 24.86 C°, 1733.61 mm, 8.34 h/day, and 2.3 m/sec, respectively. Values of Potential Evapotranspiration are determined by

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Publication Date
Mon Apr 01 2019
Journal Name
Arpn Journal Of Engineering And Applied Sciences
Assessment of vegetable cover in south Iraq by remote sensing methods
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The vegetable cover plays an important role in the environment and Earth resource sciences. In south Iraq, the region is classified as arid or semiarid area due to the low precipitations and high temperature among the year. In this paper, the Landat-8 satellite imagery will be used to study and estimate the vegetable area in south Iraq. For this purpose many vegetation indices will be examined to estimate and extract the area of vegetation contain in and image. Also, the weathering parameters must be investigated to find the relationship between these parameters and the arability of vegetation cover crowing in the specific area. The remote sensing packages and Matlab written subroutines may be use to evaluate the results.

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Scopus
Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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