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Optimized ensemble deep random vector functional link with nature inspired algorithm and boruta feature selection: Multi-site intelligent model for air quality index forecasting
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Publication Date
Mon Feb 01 2021
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Features of genetic algorithm for plain text encryption
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The data communication has been growing in present day. Therefore, the data encryption became very essential in secured data transmission and storage and protecting data contents from intruder and unauthorized persons. In this paper, a fast technique for text encryption depending on genetic algorithm is presented. The encryption approach is achieved by the genetic operators Crossover and mutation. The encryption proposal technique based on dividing the plain text characters into pairs, and applying the crossover operation between them, followed by the mutation operation to get the encrypted text. The experimental results show that the proposal provides an important improvement in encryption rate with comparatively high-speed Process

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Publication Date
Fri Apr 20 2012
Journal Name
International Journal Of Computer And Information Engineering
An Optimal Algorithm for HTML Page Building Process
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An Optimal Algorithm for HTML Page Building Process

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Publication Date
Thu Dec 01 2011
Journal Name
2011 Developments In E-systems Engineering
Enhanced Computation Time for Fast Block Matching Algorithm
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Publication Date
Thu Sep 26 2019
Journal Name
Processes
Fine-Tuning Meta-Heuristic Algorithm for Global Optimization
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This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

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Publication Date
Fri Sep 03 2021
Journal Name
Entropy
Reliable Recurrence Algorithm for High-Order Krawtchouk Polynomials
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Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

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Publication Date
Tue Jan 17 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
An Image Feature Extraction to Generate a Key for Encryption in Cyber Security Medical Environments
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Cyber security is a term utilized for describing a collection of technologies, procedures, and practices that try protecting an online environment of a user or an organization. For medical images among most important and delicate data kinds in computer systems, the medical reasons require that all patient data, including images, be encrypted before being transferred over computer networks by healthcare companies. This paper presents a new direction of the encryption method research by encrypting the image based on the domain of the feature extracted to generate a key for the encryption process. The encryption process is started by applying edges detection. After dividing the bits of the edge image into (3×3) windows, the diffusions

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Wed Oct 07 2020
Journal Name
Journal Of Interdisciplinary Mathematics
Discrete an SIS model with immigrants and treatment
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In this paper, a discrete SIS epidemic model with immigrant and treatment effects is proposed. Stability analysis of the endemic equilibria and disease-free is presented. Numerical simulations are conformed the theoretical results, and it is illustrated how the immigrants, as well as treatment effects, change current model behavior

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
On Solving Singular Multi Point Boundary Value Problems with Nonlocal Condition
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In this paper Hermite interpolation method is used for solving linear and non-linear second order singular multi point boundary value problems with nonlocal condition. The approximate solution is found in the form of a rapidly convergent polynomial. We discuss behavior of the solution in the neighborhood of the singularity point which appears to perform satisfactorily for singular problems. The examples to demonstrate the applicability and efficiency of the method have been given.

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Publication Date
Fri Mar 01 2019
Journal Name
Iraqi Journal Of Physics
Wear rate of epoxy resin reinforced with multi walls carbon nanotubes
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In this study, nanocomposites have been prepared by adding
multiwall carbon nanotubes (MWCNTs) with weight ratios (0, 2, 3,
4, 5) wt% to epoxy resin. The samples were prepared by hand lay-up
method. Influence of an applied load before and after immersion in
sodium hydroxide (NaOH) of normality (0.3N) for (15 days) at
laboratory temperature on wear rate of Ep/MWCNTs
nanocomposites was studied. The results showed that wear rate
increases with increasing the applied load for the as prepared and
immersed samples and after immersion. It was also found that epoxy
resin reinforced with MWCNTs has wear rate less than neat epoxy.
The sample (Ep + 5wt% of MWCNTs) has lower wear rate. The
immersion effect in base so

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