The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

Beta Distribution

Abstract

             Gamma and Beta Distributions has very important in practice in various areas of statistical and applications reliability and quality control of production. and There are a number of methods to generate data behave on according to these distribution. and These methods bassic primarily on the shape parameters of each distribution and the relationship between these distributions and their relationship with some other probability distributions.    &nb

The rapid success and the field dilation of Daish organization in both Iraq and Syria make academic institutes and research centers to pay attention to its propaganda means to gain its public opinion, and to further investigation about new methods employed by this organization to disseminate its messages to the public, particularly young people in large areas of the world. This organization uses traditional propaganda techniques on psychological war and its levels, social network sites and platforms that are distributed online. This study seeks to expose more persuasive methods used by the organization to gain multiple classes of society and to disseminate its extremist ideological thoughts. It also studies the psychological operation an

The multiple linear regression model is an important regression model that has attracted many researchers in different fields including applied mathematics, business, medicine, and social sciences , Linear regression models involving a large number of independent variables are poorly performing due to large variation and lead to inaccurate conclusions , One of the most important problems in the regression analysis is the multicollinearity Problem, which is considered one of the most important problems that has become known to many researchers  , As well as their effects on the multiple linear regression model, In addition to multicollinearity, the problem of outliers in data is one of the difficulties in constructing the reg

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

ABSTRACT

The study aimed to evaluate the information label of some local pickle products and estimate sodium benzoate therein. 85 samples of locally made pickles were collected from Baghdad city markets and randomly from five different areas in Baghdad it included (Al-Shula, Al-Bayaa, Al-Nahrawan, Al-Taji, and Abu Ghraib), which were divided into groups P1, P2, P3, P4 and P5, respectively, according to those areas,  samples information label was scanned and compared with the Iraqi standard specification for the information card of packaged and canned food IQS 230, the results showed that 25.9% of the samples were devoid of the indication card informa

Ninety eight mobile samples, (54) galaxy phone and (44) I phone, were swabbed for bacterial culture determination by culturing on MacConky agar , Blood agar , Mannitol salt agar , Muller Hinton agar .Staphylococcuswas the highest frequent isolated bacteria from Galaxy phone (33%) and I phone (37%). This study revealed that galaxy phone appears less contaminated with bacteria, the ratio of non-contaminated devices is (44%) when compared with I phone (9%). Sensitivity test showed that Ogmintin have the lowest effect on Staphylococcusisolated from both type of devices while cefitriaxone have the highest effect. DNA of isolate from galaxy 31 that exhibit highest resistance against antibiotics was extracted and 16S rRNA gene was polymerized by P

    This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find  that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.

Recently, dental implants have experienced increasing demand as one of the most effective, permanent and stable ways for replacing missing teeth. However, peri-implant diseases that are multispecies plaque-based infections may ultimately lead to implant failure (i.e., late peri-implantitis). Therefore, the present study aims to detect the microbial diversity of subgingival plaque in peri-implantitis cases (N = 30) by comparing with healthy implants (N = 34) using culture-based identification methods, including VITEK 2 system. An increase in microbial diversity (29 species along with 1 and 7 isolates, which were classified as a genus and unidentified species, respectively) were observed in subgingival sites of diseased implants dominated by