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Underdetermined reverberant acoustic source separation using weighted full-rank nonnegative tensor models
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In this paper, a fusion of K models of full-rank weighted nonnegative tensor factor two-dimensional deconvolution (K-wNTF2D) is proposed to separate the acoustic sources that have been mixed in an underdetermined reverberant environment. The model is adapted in an unsupervised manner under the hybrid framework of the generalized expectation maximization and multiplicative update algorithms. The derivation of the algorithm and the development of proposed full-rank K-wNTF2D will be shown. The algorithm also encodes a set of variable sparsity parameters derived from Gibbs distribution into the K-wNTF2D model. This optimizes each sub-model in K-wNTF2D with the required sparsity to model the time-varying variances of the sources in the spectrogram. In addition, an initialization method is proposed to initialize the parameters in the K-wNTF2D. Experimental results on the underdetermined reverberant mixing environment have shown that the proposed algorithm is effective at separating the mixture with an average signal-to-distortion ratio of 3 dB.

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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
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Using the Size Strain Plot Method to Specity Lattice Parameters
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X-ray diffractometers deliver the best quality diffraction data while being easy to use and adaptable to various applications. When X-ray photons strike electrons in materials, the incident photons scatter in a direction different from the incident beam; if the scattered beams do not change in wavelength, this is known as elastic scattering, which causes amplitude and intensity diffraction, leading to constructive interference. When the incident beam gives some of its energy to the electrons, the scattered beam's wavelength differs from the incident beam's wavelength, causing inelastic scattering, which leads to destructive interference and zero-intensity diffraction. In this study, The modified size-strain plot method was used to examin

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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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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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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Sequential feature selection for heart disease detection using random forest
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Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f

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Publication Date
Mon Jan 02 2012
Journal Name
Journal Of Engineering
3-D Object Recognition using Multi-Wavelet and Neural Network
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

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Publication Date
Mon Jul 22 2019
Journal Name
Innovations In Pharmacy
Evaluate Factors Influencing Depression in Baghdad: Using Deck-Depression Inventory
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Objective: This study goal was to screen participants from different settings in Baghdad for depression using Beck Depression Inventory (BDI) scale and identify factors influencing the levels of depression. Methods: This cross-sectional study included a convenience sample of 313 people from four settings (teaching hospital, college of medicine, college of pharmacy, and high school) in Baghdad, Iraq. The participants were screened using paper survey relying on the BDI scale during spring 2018. Using multiple linear regression analysis, we measured the association between depression scores and six participant factors. Results: The overall prevalence of depression in our sample was 57.2%. Female participants had higher BDI

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Publication Date
Wed Mar 30 2016
Journal Name
College Of Islamic Sciences
The link of destination Using the evidence Analytical Fundamental Study
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This paper seeks to study the link between the fundamentalist evidence based on the observance of governance and interests and the ranks of the three legitimate purposes (necessary, need and detailed). The researcher followed the descriptive-analytical approach. The study reached important results, including that the measurement relates to the three ranks, but predominantly attached to measure the meaning of the need and the need, and the measurement of the semi-formal and semi-predominance improvement. Reclamation is considered by the majority of scholars to be authentic if it is related to the necessity and the need, and that it is not acceptable to improve only by a witness who recommends it. The excuses relate to Hajji and Tahini, no

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