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THE EFFECT OF FASHIONISTA ON FEMALE BODY IMAGE
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The research aims to reveal the relationship between the use of social networking sites and the image that females make about their physical formation, the nature of the effects, their value judgments about the image of their bodies, their attitudes toward plastic surgery, the most important types of these processes for them, their motivations to conduct them, and the cultural pressures they are exposed to. The study, moreover, investigates in the effects of those plastic surgery on their behavior as active and interacting users with what is published on social media, according to the theory of social comparison. This paper is an attempt to understand the pattern of social networking operation and its implications for the human self.

The research community formed of "females", and the sample included (204) respondents from the followers of "fashionista/ fashionist". The survey approach was used over the intentional sample method to obtain research data through the electronic questionnaire. The questionnaire contained closed questions and phrases according to Likert scale. The research reached several results, including:

 The sample of the research mostly ranges between 18-28 years of age, having a university education, and are not married and economically sufficient.

 Always interested in following "fashion" from "fashionista", and sometimes learning cooking techniques, and rarely follow "fashionist".

They have a desire to perform plastic surgery, and they were respectively "filler and Botox, remove wrinkles", rhinoplasty, plastic surgery and whitening teeth, sculpting the waist and buttocks, getting the lip of the duck, and finally liposuction and stomach cutting.

 As for their motives of plastic surgery, mostly, are done in order to satisfy themselves, and in the second place to satisfy people, and in the third position to satisfy their husbands, and in the fourth position to obtain a husband. Finally, they do that to get a job.

 

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Publication Date
Fri Jan 01 2016
Journal Name
Engineering And Technology Journal
Face Retrieval Using Image Moments and Genetic Algorithm
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Publication Date
Fri Jan 01 2016
Journal Name
Bio-inspired Computing – Theories And Applications
Image Segmentation Using Membrane Computing: A Literature Survey
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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Abstract Pattern Image Generation using Generative Adversarial Networks
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Publication Date
Fri Jul 01 2016
Journal Name
International Journal Of Computer Science And Mobile Computing
. Interpolative Absolute Block Truncation Coding for Image Compression
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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Digital Color Image Watermarking Using Encoded Frequent Mark
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With the increased development in digital media and communication, the need for methods to protection and security became very important factor, where the exchange and transmit date over communication channel led to make effort to protect these data from unauthentication access.

This paper present a new method to protect color image from unauthentication access using watermarking. The watermarking algorithm hide the encoded mark image in frequency domain using Discrete Cosine Transform. The main principle of the algorithm is encode frequent mark in cover color image. The watermark image bits are spread by repeat the mark and arrange in encoded method that provide algorithm more robustness and security. The propos

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Publication Date
Mon Apr 17 2023
Journal Name
Wireless Communications And Mobile Computing
A Double Clustering Approach for Color Image Segmentation
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One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first

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Publication Date
Wed Jun 01 2022
Journal Name
V. International Scientific Congress Of Pure, Applied And Technological Sciences
Lightweight Image Compression Using Polynomial and Transform Coding
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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Computer Applications
Content-based Image Retrieval (CBIR) using Hybrid Technique
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Image retrieval is used in searching for images from images database. In this paper, content – based image retrieval (CBIR) using four feature extraction techniques has been achieved. The four techniques are colored histogram features technique, properties features technique, gray level co- occurrence matrix (GLCM) statistical features technique and hybrid technique. The features are extracted from the data base images and query (test) images in order to find the similarity measure. The similarity-based matching is very important in CBIR, so, three types of similarity measure are used, normalized Mahalanobis distance, Euclidean distance and Manhattan distance. A comparison between them has been implemented. From the results, it is conclud

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Reverse Engineering Representation Using an Image Processing Modification
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In the reverse engineering approach, a massive amount of point data is gathered together during data acquisition and this leads to larger file sizes and longer information data handling time. In addition, fitting of surfaces of these data point is time-consuming and demands particular skills. In the present work a method for getting the control points of any profile has been presented. Where, many process for an image modification was explained using Solid Work program, and a parametric equation of the profile that proposed has been derived using Bezier technique with the control points that adopted. Finally, the proposed profile was machined using 3-aixs CNC milling machine and a compression in dimensions process has been occurred betwe

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Publication Date
Tue Oct 12 2021
Journal Name
Engineering, Technology And Applied Science Research
Automated Pavement Distress Detection Using Image Processing Techniques
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Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

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