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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 results showed that the best method is to combine probit transformation and mirror reflection kernel estimator (PTMRKE) and followed by the (IPE) method when using all copula functions and for all sample sizes if the correlation is strong (positive or negative). But in the case of using weak and medium correlations, it turns out that the (IPE) method is the best, followed by the proposed method(PTMRKE), depending on (RMSE, LOGL, Akaike)criteria. The results also indicated that the mirror kernel reflection method when using the five copulas is weak.

Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Publication Date
Wed Mar 01 2023
Journal Name
Iraqi Journal Of Physics
FTIR and Electrical Behavior of Blend Electrolytes Based on (PVA/PVP)
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Polymer electrolytes were prepared using the solution cast technology. Under some conditions, the electrolyte content of polymers was analyzed in constant percent of PVA/PVP (50:50), ethylene carbonate (EC), and propylene carbonate (PC) (1:1) with different proportions of potassium iodide (KI) (10, 20, 30, 40, 50 wt%) and iodine (I2) = 10 wt% of salt. Fourier Transmission Infrared (FTIR) studies confirmed the complex formation of polymer blends. Electrical conductivity was calculated with an impedance analyzer in the frequency range 50 Hz–1MHz and in the temperature range 293–343 K. The highest electrical conductivity value of 5.3 × 10-3 (S/cm) was observed for electrolytes with 50 wt% KI concentration at room

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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
Wed Jan 01 2020
Journal Name
Journal Of Information Hiding And Multimedia Signal Processing
Enhancement of lsb audio steganography based on carrier and message characteristics
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Data steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. This paper proposes an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio. It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Information Hiding And Multimedia Signal Processing
Enhancement of lsb audio steganography based on carrier and message characteristics
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Data steganography is a technique used to hide data, secret message, within another data, cover carrier. It is considered as a part of information security. Audio steganography is a type of data steganography, where the secret message is hidden in audio carrier. This paper proposes an efficient audio steganography method that uses LSB technique. The proposed method enhances steganography performance by exploiting all carrier samples and balancing between hiding capacity and distortion ratio. It suggests an adaptive number of hiding bits for each audio sample depending on the secret message size, the cover carrier size, and the signal to noise ratio (SNR). Comparison results show that the proposed method outperforms state of the art methods

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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
Thu Jun 25 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Synthesis, Characterization and Antibacterial Activity Evaluation of New Indole-Based Derivatives
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A new series of N-acyl hydrazones (4a-g) derived from indole-3-propionic acid (IPA) were synthesized. These N-acyl hydrazones were prepared by the reaction of 3-(1H-indol-3-yl) propane hydrazide and aldehyde in the existence of glacial acetic acid as a catalyst. 1HNMR and FT-IR analyses were used to identify the synthesized compounds and they were in vitro evaluated as antibacterial agents against six different types of microorganisms by using well diffusion method. All the tested N-acyl hydrazones (4a-g) displayed moderate activity against the Gram-negative E.coli, comparable to that of Amoxicillin. Some of the tested N-acyl hydrazones also exhibited intermediate activity ag

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Improvement of the Fault Tolerance in IoT Based Positioning Systems by Applying for Redundancy in the Controller Layer
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In recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS.  This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GP

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Publication Date
Wed Feb 01 2023
Journal Name
Mathematical Models And Computer Simulations
Function Approximation Technique (FAT)-Based Adaptive Feedback Linearization Control for Nonlinear Aeroelastic Wing Models Considering Different Actuation Scenarios
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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Modified BFGS Update (H-Version) Based on the Determinant Property of Inverse of Hessian Matrix for Unconstrained Optimization
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The study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. Moreover, the sequence of inverse of Hessian matrix generated by the method would never  approach a near-singular matrix, such that the program would never break before the minimum value of the objective function is obtained. Moreover, the new modification of BFGS update (H-vers

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