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Steganography and Cryptography Techniques Based Secure Data Transferring Through Public Network Channel
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Attacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover.  The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels with two secret random keys. Therefore, the hidden message remains protected even if the stego-object is hacked because the attacker is unable to know the correct frames and pixels that hold each bit of the secret message in addition to difficulty to successfully rebuild the message. The results refer to that the proposed scheme provides a good performance for evaluation metric that is used in this purpose when compared to a large number of related previous methods.

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Speech Enhancement Algorithm Based on Super-Gaussian Modeling and Orthogonal Polynomials
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Publication Date
Sat Oct 01 2022
Journal Name
Nuclear Instruments And Methods In Physics Research Section B: Beam Interactions With Materials And Atoms
Shielding properties and buildup factor of Al2O3/PbO-based ceramic materials
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Publication Date
Sun Jul 01 2018
Journal Name
2018 2nd International Conference On Imaging, Signal Processing And Communication (icispc)
Analogy-based Common-Sense Knowledge for Opinion-Target Identification and Aggregation
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The development of Web 2.0 has improved people's ability to share their opinions. These opinions serve as an important piece of knowledge for other reviewers. To figure out what the opinions is all about, an automatic system of analysis is needed. Aspect-based sentiment analysis is the most important research topic conducted to extract reviewers-opinions about certain attribute, for instance opinion-target (aspect). In aspect-based tasks, the identification of the implicit aspect such as aspects implicitly implied in a review, is the most challenging task to accomplish. However, this paper strives to identify the implicit aspects based on hierarchical algorithm incorporated with common-sense knowledge by means of dimensionality reduction.

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Publication Date
Sat Nov 01 2008
Journal Name
Digital Signal Processing
A high performance parallel Radon based OFDM transceiver design and simulation
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major goal of the next-generation wireless communication systems is the development of a reliable high-speed wireless communication system that supports high user mobility. They must focus on increasing the link throughput and the network capacity. In this paper a novel, spectral efficient system is proposed for generating and transmitting twodimensional (2-D) orthogonal frequency division multiplexing (OFDM) symbols through 2- D inter-symbol interference (ISI) channel. Instead of conventional data mapping techniques, discrete finite Radon transform (FRAT) is used as a data mapping technique due to the increased orthogonality offered. As a result, the proposed structure gives a significant improvement in bit error rate (BER) performance. Th

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Publication Date
Tue May 01 2018
Journal Name
2018 2nd Ieee Advanced Information Management,communicates,electronic And Automation Control Conference (imcec)
Hybrid Regressor and Approximation-Based Adaptive Control of Piezoelectric Flexible Beams
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Publication Date
Sun Aug 06 2023
Journal Name
Journal Of Economics And Administrative Sciences
Probit and Improved Probit Transform-Based Kernel Estimator for Copula Density
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Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The

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Publication Date
Fri May 16 2014
Journal Name
International Journal Of Computer Applications
Lossless Image Compression based on Predictive Coding and Bit Plane Slicing
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Publication Date
Tue Jun 01 2021
Journal Name
Ieee Systems Journal
Intelligent Traffic Management and Load Balance Based on Spike ISDN-IoT
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An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

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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 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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