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Differential evolution detection models for SMS spam
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With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative rate. Moreover, it surpasses the baseline methods.

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Some Robust methods for Estimates the power Spectrum in ARMA Models Simulation Study
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Abstract:

Robust statistics Known as, resistance to errors caused by deviation from the stability hypotheses of the statistical operations (Reasonable, Approximately Met, Asymptotically Unbiased, Reasonably Small Bias, Efficient ) in the data selected in a wide range of probability distributions whether they follow a normal distribution or a mixture of other distributions deviations different standard .

power spectrum function lead to, President role in the analysis of Stationary random processes, form stable random variables organized according to time, may be discrete random variables or continuous. It can be described by measuring its total capacity as function in frequency.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
numerical solution of nth order linear dealy differential
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in this paper fourth order kutta method has been used to find the numerical solution for different types of first liner

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Oscillation of Nonlinear First Order Neutral Differential Equations
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In this paper, the author established some new integral conditions for the oscillation of all solutions of nonlinear first order neutral delay differential equations. Examples are inserted to illustrate the results.

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Publication Date
Fri Aug 01 2014
Journal Name
International J. Of Math. Sci. & Engg. Appls.
NEUTRAL DELAY DIFFERENTIAL EQUATION WITH ONE LARGE DELAY
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Publication Date
Sun Aug 03 2014
Journal Name
Journal Of Advances In Mathematics
On types of Delay in Delay Differential equation
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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Oscillation of Nonlinear Differential Equations with Advanced Arguments
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This paper is concerned with the oscillation of all solutions of the n-th order delay differential equation . The necessary and sufficient conditions for oscillatory solutions are obtained and other conditions for nonoscillatory solution to converge to zero are established.

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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Partial Encryption for Colored Images Based on Face Detection
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Publication Date
Tue Nov 19 2024
Journal Name
Aip Conference Proceedings
CT scan and deep learning for COVID-19 detection
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Publication Date
Tue Apr 02 2024
Journal Name
Advances In Systems Science And Applications
A New Face Swap Detection Technique for Digital Images
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Scopus
Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Cybersecurity And Information Management
Machine Learning-based Information Security Model for Botnet Detection
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Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

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