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Speech Gender Recognition Using a Multilayer Feature Extraction Method
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Publication Date
Fri Feb 04 2022
Journal Name
Iraqi Journal Of Science
Hiding and Encryption of Secret Image Using Secret Sharing Scheme
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With the development of information technology and means for information transfer it has become necessary to protect sensitive information. The current research presents a method to protect secret colored images which includes three phases: The first phase calculates hash value using one of hash functions to ensure that no tampering with or updating the contents of the secret image. The second phase is encrypting image and embedding it randomly into appropriate cover image using Random Least Significant Bit (RLSB) technique. Random hiding provides protection of information embedded inside cover image for inability to predict the hiding positions, as well as the difficult of determining the concealment positions through the analysis of im

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Publication Date
Mon Sep 16 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Determination of Ibuprofen in Pharmaceutical Formulations Using Differential Pulse Polarography
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     A reliable differential pulse polarographic (DPP) method has been developed and applied for the determination of ibuprofen IBU in dosage form with dropping mercury electrode (DME) versus Ag/AgCl. The best peak was found at cathodic peak of -1.18 V in phosphate buffer at pH=4 and 0.025M of KNO3 as supporting electrolyte. In order to obtaine the highest sensitivity, instrumental and experimental parameters were examined including the type and concentration of supporting electrolyte, pH of buffer solution, pulse amplitude and voltage step time. Diffusion current showed a direct linear relationship to ibuprofen concentration in the range of (5 – 30) μg. mL-1 (2.43× 10-5

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Publication Date
Sun Apr 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Influence Activation Function in Approximate Periodic Functions Using Neural Networks
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The aim of this paper is to design fast neural networks to approximate periodic functions, that is, design a fully connected networks contains links between all nodes in adjacent layers which can speed up the approximation times, reduce approximation failures, and increase possibility of obtaining the globally optimal approximation. We training suggested network by Levenberg-Marquardt training algorithm then speeding suggested networks by choosing most activation function (transfer function) which having a very fast convergence rate for reasonable size networks.             In all algorithms, the gradient of the performance function (energy function) is used to determine how to

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Mon Jun 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Breast Tumor Diagnosis Using Diode Laser in Near Infrared Region
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In the last years, new non-invasively laser methods were used to detect breast tumors for pre- and postmenopausal females. The methods based on using laser radiation are safer than the other daily used methods for breast tumor detection like X-ray mammography, CT-scanner, and nuclear medicine.  

      One of these new methods is called FDPM (Frequency Domain Photon Migration). It is based on the modulation of laser beam by variable frequency sinusoidal waves. The modulated laser radiations illuminate the breast tissue and received from opposite side.

      In this paper the amplitude and the phase shift of the received signal were calculated according to the orig

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Publication Date
Sat Nov 28 2020
Journal Name
Iraqi Journal Of Science
Using Affiliation Rules-based Data Mining Technique in Referral System
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Referral techniques are normally employed in internet business applications. Existing frameworks prescribe things to a particular client according to client inclinations and former high evaluations. Quite a number of methods, such as cooperative filtering and content-based methodologies, dominate the architectural design of referral frameworks. Many referral schemes are domain-specific and cannot be deployed in a general-purpose setting. This study proposes a two-dimensional (User × Item)-space multimode referral scheme, having an enormous client base but few articles on offer. Additionally, the design of the referral scheme is anchored on the  and  articles, as expressed by a particular client, and is a combination of affi

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Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
Smart Routing Protocol Algorithm Using Fuzzy Artificial Neural Network OSPF
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The OSPF cost is proportionally indicated the transmitting packet overhead through a certain interface and inversely proportional to the interface bandwidth. Thus, this cost may minimized by direct packet transmitting to the other side via various probable paths simultaneously. Logically, the minimum weight path is the optimum path. This paper propose a novel Fuzzy Artificial Neural Network to create Smart Routing Protocol Algorithm. Consequently, the Fuzzy Artificial Neural Network Overlap has been reduced from (0.883 ms) to (0.602 ms) at fuzzy membership 1.5 to 4.5 respectively. This indicated the transmission time is two-fold faster than the standard overlapping time (1.3 ms).

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Combined DWT and DCT Image Compression Using Sliding RLE Technique
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A number of compression schemes were put forward to achieve high compression factors with high image quality at a low computational time. In this paper, a combined transform coding scheme is proposed which is based on discrete wavelet (DWT) and discrete cosine (DCT) transforms with an added new enhancement method, which is the sliding run length encoding (SRLE) technique, to further improve compression. The advantages of the wavelet and the discrete cosine transforms were utilized to encode the image. This first step involves transforming the color components of the image from RGB to YUV planes to acquire the advantage of the existing spectral correlation and consequently gaining more compression. DWT is then applied to the Y, U and V col

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Crossref
Publication Date
Sat Feb 26 2022
Journal Name
Iraqi Journal Of Science
Estimating the Reliability Function for Transmuted Pareto Distribution Using Simulation
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     In this work, the methods (Moments, Modified Moments, L-Moments, Percentile, Rank Set sampling and Maximum Likelihood) were used to estimate the reliability function and the two parameters of the Transmuted Pareto (TP) distribution. We use simulation to generate the required data from three cases this indicates  sample size , and it replicates  for the real value for parameters, for reliability times values  we take .

Results were compared by using mean square error (MSE), the result appears as follows :

The best methods are Modified Moments, Maximum likelihood and L-Moments in first case, second case and third case respectively.

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