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.
In this paper, the developed sprite allocation method is designed to be coherent with the introduced block-matching method in order to minimize the allocation process time for digital video. The accomplished allocation process of sprite region consists of three main steps. The first step is the detection of sprite area; where the sequence of frames belong to Group of Video sequence are analysed to detect the sprite regions which survive for long time, and to determine the sprite type (i.e., whether it is static or dynamic). Then as a second step, the flagged survived areas are passed through the gaps/islands removal stage to enhance the detected sprite areas using post-processing operations. The third step is partitioning the sprite area in
... Show MoreThe aim of this work is to study reverse osmosis characteristics for copper sulfate hexahydrate (CuSO4.6H2O), nickel sulfate hexahydrate (NiSO4.6H2O) and zinc sulfate hexahydrate (ZnSO4.6H2O) removal from aqueous solution which discharge from some Iraqi factories such as Alnasser Company for mechanical industries. The mode of operation of reverse osmosis was permeate is removed and the concentrate of metals solution is recycled back to the feed vessel. Spiral-wound membrane is thin film composite membrane (TFC) was used to conduct this study on reverse osmosis. The variables studied are metals concentrations (50 – 150 ppm) and time (15 – 90 min). It was found that increasing the time results in an increase in concentration of metal in p
... Show MoreThis paper is concerned with introducing and studying the first new approximation operators using mixed degree system and second new approximation operators using mixed degree system which are the core concept in this paper. In addition, the approximations of graphs using the operators first lower and first upper are accurate then the approximations obtained by using the operators second lower and second upper sincefirst accuracy less then second accuracy. For this reason, we study in detail the properties of second lower and second upper in this paper. Furthermore, we summarize the results for the properties of approximation operators second lower and second upper when the graph G is arbitrary, serial 1, serial 2, reflexive, symmetric, tra
... Show MoreThis investigation was carried out to study the treatment and recycling of wastewater in the cotton textile industry for an effluent containing three dyes: direct blue, sulphur black and vat yellow. The reuse of such effluent can only be made possible by appropriate treatment method such as chemical coagulation. Ferrous and ferric sulphate with and without calcium hydroxide were employed in this study as the chemical coagulants.
The results showed that the percentage removal of direct blue ranged between 91.4 and 94 , for sulphur black ranged between 98.7 and 99.5 while for vat yellow it was between 97 and 99.
Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.
The speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi
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