Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

Orthogonal polynomials and their moments serve as pivotal elements across various fields. Discrete Krawtchouk polynomials (DKraPs) are considered a versatile family of orthogonal polynomials and are widely used in different fields such as probability theory, signal processing, digital communications, and image processing. Various recurrence algorithms have been proposed so far to address the challenge of numerical instability for large values of orders and signal sizes. The computation of DKraP coefficients was typically computed using sequential algorithms, which are computationally extensive for large order values and polynomial sizes. To this end, this paper introduces a computationally efficient solution that utilizes the parall

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

      In this paper fractional Maxwell fluid equation has been solved. The solution is in the Mettag-Leffler form. For  the corresponding solutions for ordinary Maxwell fluid are obtained as limiting case of general solutions. Finally, the effects of different parameters on the velocity and shear stress profile are analyzed through plotting the velocity and shear stress profile.

Financial Reporting Quality (FRQ) is one of the important topics in the financial management, it has the impact on the users decisions, it also effect on many other variables i.e dividend, therefore. This paper aims to provide a diameter of Financial Reporting Quality (FRQ) level for the companies listed on the Iraqi Stock Exchange. It also tries to show the FRQ effects on the dividend policy. The study sample was 13 listed companies in the Iraqi Stock Exchange for the period from 2007 to 2011. Kothari et al. 2005 model has been used to measure the FRQ, on the other hand the common stock share of the dividend was used to measure the dividend.

   Many conclusions have been driven by the research

    In this numerical study a detailed evaluation of the heat transfer characteristics and flow structure in a laminar and turbulent flow through a rectangular channel containing built-in of different type vortex generator has been a accomplished in a range of Reynolds number between 500 and 100,000.A modified version of ESCEAT code has been used to solve Navier-Stokes and energy equations. The purpose of this paper is to present numerical comparisons in terms of temperature, Nusselt number and flow patterns on several configurations of longitudinal vortex generator including new five cases. The structures of heat and flow were studied, using iso-contours of velocity components, vortices, temperature and Nusselt n

The aim of the present study was to demonstrate the possible role of statins on the inflammatory biomarkers in patients with periodontal disease (PD) This cross-sectional study involved 74 patients with PD and/or dyslipidemia divided into Group A: 34 patients with PD (nonstatins users); Group B: 40 patients with PD (statins users); and Group C: 30 healthy controls. Total cholesterol (TC), triglyceride (TG) and high-density lipoprotein, C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and malondialdehyde (MDA) were measured . Blood pressure prolife and indices of PD were evaluated in each group. Statistical analysis was conducted by using SPSS version 20.0.

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro