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 s

Loanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standard specifications for transferring words between languages and hence low accuracy. This work tries to enhance this accuracy of detecting loanwords between Turkish and Arabic language as a case study. In this paper, the proposed system contributes to find all possible loanwords using any set of characters either alphabetically or randomly arranged. Then, it processes the distortion in the pronunciation, and solves the problem of the missing lette

In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

Collaborative learning in class‐based teaching presents a challenge for a tutor to ensure every group and individual student has the best learning experience. We present Group Tagging, a web application that supports reflection on collaborative, group‐based classroom activities. Group Tagging provides students with an opportunity to record important moments within the class‐based group work and enables reflection on and promotion of professional skills such as communication, collaboration and critical thinking. After class, students use the tagged clips to create short videos showcasing their group work activities, which can later be reviewed by the teacher. We report on a deployment of Group Tagging in an undergraduate Computing Scie

The water quality index is the most common mathematical way of monitoring water characteristics due to the reasons for the water parameters to identify the type of water and the validity of its use, whether for drinking, agricultural, or industrial purposes. The water arithmetic indicator method was used to evaluate the drinking water of the Al-Muthana project, where the design capacity was (40000) m3/day, and it consists of traditional units used to treat raw water. Based on the water parameters (Turb, TDS, TH, SO4, NO2, NO3, Cl, Mg, and Ca), the evaluation results were that the quality of drinking water is within the second category of the requirements of the WHO (86.658%) and the first category of the standard has not

The distribution of the expanded exponentiated power function EEPF with four parameters, was presented by the exponentiated expanded method using the expanded distribution of the power function, This method is characterized by obtaining a new distribution belonging to the exponential family, as we obtained the survival rate and failure rate function for this distribution, Some mathematical properties were found, then we used the developed least squares method to estimate the parameters using the genetic algorithm, and a Monte Carlo simulation study was conducted to evaluate the performance of estimations of possibility using the Genetic algorithm GA.