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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
Sat Mar 08 2025
Journal Name
Fusion: Practice And Applications
Fast Numeric Sign Detection Using Adaptive Thresholding and Geometry of Optimized Fingers
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A strong sign language recognition system can break down the barriers that separate hearing and speaking members of society from speechless members. A novel fast recognition system with low computational cost for digital American Sign Language (ASL) is introduced in this research. Different image processing techniques are used to optimize and extract the shape of the hand fingers in each sign. The feature extraction stage includes a determination of the optimal threshold based on statistical bases and then recognizing the gap area in the zero sign and calculating the heights of each finger in the other digits. The classification stage depends on the gap area in the zero signs and the number of opened fingers in the other signs as well as

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Publication Date
Mon Jul 01 2013
Journal Name
Http://www.i-csrs.org/volumes/gisars/vol.3/vol.3.1.1.july.12.pdf
Remote sensing technique to monitoring the risk of soil degradation using NDVI
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In order to take measures in controlling soil erosion it is required to estimate soil loss over area of interest. Soil loss due to soil erosion can be estimated using predictive models such as Universal Soil Loss Equation (USLE). The accuracy of these models depends on parameters that are used in equations. One of the most important parameters in equations used in both of models is (C) factor that represents effects of vegetation and other land covers. Estimating land cover by interpretation of remote sensing imagery involves Normalized Difference Vegetation Index (NDVI), an indicator that shows vegetation cover. The aim of this study is estimate (C) factor values for Part of Baghdad city using NDVI derived from satellite Image of Landsat-7

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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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Publication Date
Sat Jul 01 2023
Journal Name
International Journal Of Intelligent Engineering And Systems
An Efficient Cryptosystem for Image Using 1D and 2D Logistic Chaotic Maps
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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Experimental and Numerical Analysis of Laser Surface Melting by Using Enthalpy Method
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Abstract<p>In this study, experimental and numerical applied of heat distribution due to pulsed Nd: YAG laser surface melting. Experimental side was consists of laser parameters are, pulse duration1.3<italic>ms</italic>, wavelength 1064nm, laser energies 1.5, 2. 6 and 4.3 J, laser beam diameter is 0.6 mm and spot diameter 0.78 mm was applied a low carbon steel type St37 with a dimension 10, 10, 3 mm, length, width and thickness respectively. Numerical analysis side consist of a mathematical model and calculating a thermal cycle by using equation in the enthalpy method applied to determine the cooling rate in fusion zone. The simulation by using the enthalpy method, applied on conduction heat transfer </p> ... Show More
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Publication Date
Wed Jan 01 2020
Journal Name
Aip Conference Proceedings
Corrosion behavior of mild-steel in cooling towers using high salinity solution
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Cooling towers is one of the most important unit in industry, they are used to dispose heat from cooling media used in the integrated units. The choice of the cooling media plays recently an important rule due to fresh-water scarcity. The use of saline as a cooling media become of growing interest, but the corrosion problem has to be taken in consideration. In this study the simultaneous effect of cooling tower operation parameters on the corrosion rate of mild-steel is considered. The role of NaCl content is found to be pronounced more than the working solution temperature and flowrate. The corrosion of mild-steel in these studied factors had shown an interesting result especially with the NaCl% content. Firstly, there was an increase in t

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Publication Date
Sat Aug 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Achieving the Benefits and Requirements of Integrated Project Delivery Method Using BIM
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Abstract<p>Through the last decade, Integrated Project Delivery (IPD) methodology considers one of the new contractual relations that are also on the way to further integrate the process of combining design and instruction. On the other hand, Building Information Modeling (BIM) made significant advancements in coordinating the planning and construction processes. It is being used more often in conjunction with traditional delivery methods. In this paper, the researcher will present the achievement of IPD methodology by using BIM through applying on the design of the financial commission building in Mayssan Oil Company in Iraq. The building has not been constructed yet and it was designed by usin</p> ... Show More
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Publication Date
Tue Jan 18 2022
Journal Name
Photonic Sensors
Arsenic Detection Using Surface Plasmon Resonance Sensor With Hydrous Ferric Oxide Layer
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Abstract<p>The lethality of inorganic arsenic (As) and the threat it poses have made the development of efficient As detection systems a vital necessity. This research work demonstrates a sensing layer made of hydrous ferric oxide (Fe<sub>2</sub>H<sub>2</sub>O<sub>4</sub>) to detect As(III) and As(V) ions in a surface plasmon resonance system. The sensor conceptualizes on the strength of Fe<sub>2</sub>H<sub>2</sub>O<sub>4</sub> to absorb As ions and the interaction of plasmon resonance towards the changes occurring on the sensing layer. Detection sensitivity values for As(III) and As(V) were 1.083 °·ppb<sup>−1</sup> and 0.922 °·ppb<jats></jats></p> ... Show More
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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Numerical Approach of Linear Volterra Integro-Differential Equations Using Generalized Spline Functions
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This paper is dealing with non-polynomial spline functions "generalized spline" to find the approximate solution of linear Volterra integro-differential equations of the second kind and extension of this work to solve system of linear Volterra integro-differential equations. The performance of generalized spline functions are illustrated in test examples

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Publication Date
Tue Oct 01 2024
Journal Name
Mathematics For Applications
DIRICHLET PROCESS ANALYSIS USING BIORTHOGONAL WAVELET: A STATISTICAL STUDY OF FINANCIAL MARKET
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The Dirichlet process is an important fundamental object in nonparametric Bayesian modelling, applied to a wide range of problems in machine learning, statistics, and bioinformatics, among other fields. This flexible stochastic process models rich data structures with unknown or evolving number of clusters. It is a valuable tool for encoding the true complexity of real-world data in computer models. Our results show that the Dirichlet process improves, both in distribution density and in signal-to-noise ratio, with larger sample size; achieves slow decay rate to its base distribution; has improved convergence and stability; and thrives with a Gaussian base distribution, which is much better than the Gamma distribution. The performance depen

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