Aspect-based sentiment analysis is the most important research topic conducted to extract and categorize aspect-terms from online reviews. Recent efforts have shown that topic modelling is vigorously used for this task. In this paper, we integrated word embedding into collapsed Gibbs sampling in Latent Dirichlet Allocation (LDA). Specifically, the conditional distribution in the topic model is improved using the word embedding model that was trained against (customer review) training dataset. Semantic similarity (cosine measure) was leveraged to distribute the aspect-terms to their related aspect-category cognitively. The experiment was conducted to extract and categorize the aspect terms from SemEval 2014 dataset.

This research work aims to the determination of molybdenum (VI) ion via the formation of peroxy molybdenum compounds which has red-brown colour with absorbance wave length at 455nm for the system of ammonia solution-hydrogen peroxide-molybdenum (VI) using a completely newly developed microphotometer based on the ON-Line measurement. Variation of responses expressed in millivolt. A correlation coefficient of 0.9925 for the range of 2.5-150 ?g.ml-1 with percentage linearity of 98.50%. A detection limit of 0.25 ?g.ml-1 was obtained. All physical and chemical variable were optimized interferences of cation and anion were studied classical method of measurement were done and compared well with newly on-line measurements. Application for the use

The research seeks to find out the extent of the coverage of the Mosul press to the issues of psychological and social effects of the organization "IS" on the community of Mosul, by analyzing the content of the newspapers “Economic City” and “Mosul News”. As well as to stand at the types of psychological and social effects and their repercussions on the Mosul community including figures, statistics and evidence that were covered in the theoretical study of these topics.

This study is the first scientific diagnosis to reveal the size and types of psychological and social effects of the “ISIS” organization  through what was monitored by the Mosul press. The study seeks to draw the attention of officials, decision-m

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

In this paper, a computational method for solving optimal problem is presented, using indirect method (spectral methodtechnique) which is based on Boubaker polynomial. By this method the state and the adjoint variables are approximated by Boubaker polynomial with unknown coefficients, thus an optimal control problem is transformed to algebraic equations which can be solved easily, and then the numerical value of the performance index is obtained. Also the operational matrices of differentiation and integration have been deduced for the same polynomial to help solving the problems easier. A numerical example was given to show the applicability and efficiency of the method. Some characteristics of this polynomial which can be used for solvin

In this paper Volterra Runge-Kutta methods which include: method of order two and four will be applied to general nonlinear Volterra integral equations of the second kind. Moreover we study the convergent of the algorithms of Volterra Runge-Kutta methods. Finally, programs for each method are written in MATLAB language and a comparison between the two types has been made depending on the least square errors.

This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai