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CHOOSING THE RIGHT CHAOTIC MAP FOR IMAGE ENCRYPTION: A DETAILED EXAMINATION
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This article investigates how an appropriate chaotic map (Logistic, Tent, Henon, Sine...) should be selected taking into consideration its advantages and disadvantages in regard to a picture encipherment. Does the selection of an appropriate map depend on the image properties? The proposed system shows relevant properties of the image influence in the evaluation process of the selected chaotic map. The first chapter discusses the main principles of chaos theory, its applicability to image encryption including various sorts of chaotic maps and their math. Also this research explores the factors that determine security and efficiency of such a map. Hence the approach presents practical standpoint to the extent that certain chaos maps will become relevant toward implementing image encryption system. This helps them select the best chaotic map for image encryption to ensure secure digital data. © 2024 Little Lion Scientific. All rights reserved.

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Publication Date
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Image restoration using regularized inverse filtering and adaptive threshold wavelet denoising
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Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .

                In this paper  a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering  and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Multiwavelet and Estimation by Interpolation Analysis Based Hybrid Color Image Compression
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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

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Sun May 01 2016
Journal Name
International Journal Of Computer Applications
Lossless Image Compression using Adaptive Predictive Coding of Selected Seed Values
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Publication Date
Wed Apr 10 2019
Journal Name
Engineering, Technology & Applied Science Research
Content Based Image Clustering Technique Using Statistical Features and Genetic Algorithm
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Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Product development For Use Some Of The Lean Production Tools A Practical Research in the General Company for the automotive industry
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Abstract 

     This research aims to analyze the reality of the production process in an assembly line Cars (RUNNA) in the public company for the automotive industry / Alexandria through the use of some Lean production tools, and data were collected through permanence in the company to identify the problems of the line in order to find appropriate to adopt some Lean production tools solutions, and results showed the presence of Lead time in some stations, which is reflected on the customer's waiting time to get the car, as well as some of the problems existing in the car produced such as high temperature of the car, as the company does not take into account customer preferences,

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Publication Date
Wed May 01 2024
Journal Name
Journal Of Physics: Conference Series
A modified ARIMA model for forecasting chemical sales in the USA
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Abstract<p>model is derived, and the methodology is given in detail. The model is constructed depending on some measurement criteria, Akaike and Bayesian information criterion. For the new time series model, a new algorithm has been generated. The forecasting process, one and two steps ahead, is discussed in detail. Some exploratory data analysis is given in the beginning. The best model is selected based on some criteria; it is compared with some naïve models. The modified model is applied to a monthly chemical sales dataset (January 1992 to Dec 2019), where the dataset in this work has been downloaded from the United States of America census (www.census.gov). Ultimately, the forecasted sales </p> ... Show More
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Publication Date
Fri Jan 05 2018
Journal Name
Asian Quarterly: An International Journal Of Contemporary Issue
Refugees and the Challenges for Language Education (LE): A Theoretical Study
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DBN Rashid, Asian Quarterly: An International Journal of Contemporary Issue, 2018

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Publication Date
Sat Sep 04 2021
Journal Name
Neuroquantology
Nanotechnology and the Most Important Characterization Techniques for Nanomaterial's: A Review
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Due to the importance of nanotechnology because of its features and applications in various fields, it has become the focus of attention of the world and researchers. In this study, the concept of nanotechnology and nanomaterials was identified, the most important methods of preparing them, as well as the preparation techniques and the most important devices used in their characterization.

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Publication Date
Sat Jan 01 2022
Journal Name
Acta Facultatis Medicae Naissensis
Asthma as a risk factor for The progression of COVID-19
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Background: Asthma is one of the most common chronic respiratory diseases in the world, standing for the most frequent cause for hospitalization and emergency cases. Respiratory viruses are the most triggering cause. Aim: To assess the role of viral infections, especially COVID-19, in the pathogenesis of asthma initiation and exacerbations. Method: Electronic search was done for the manuscripts focusing on asthma as a risk factor for complications after COVID-19 infection. The outcomes were titles, materials, methods and classified studies related or not related to the review study. Three hundred publications were identified and only ten studies were selected for analysis. Seven studies were review, one retrospective, one longitudin

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