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 has been developed for clustering purpose. Mainly, the purpose of using modified K-means clustering technique is to group the similar features into (K) templates in order to simulate the differences in the ways that human express each emotion. To evaluate the proposed system, a subset from Cohen-Kanade (CK) dataset have been used, it consists of 870 facial images samples for the seven basic emotions (angry, disgust, fear, happy, normal, sad, and surprise). The conducted test results indicated that SVM classifier can lead to higher performance in comparison with the results of other proposed methods due to its desirable characteristics (such as large-margin separation, good generalization performance, etc.).
Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st
... Show MoreThe purpose of the current investigation is to distinguish between working memory ( ) in five patients with vascular dementia ( ), fifteen post-stroke patients with mild cognitive impairment ( ), and fifteen healthy control individuals ( ) based on background electroencephalography (EEG) activity. The elimination of EEG artifacts using wavelet (WT) pre-processing denoising is demonstrated in this study. In the current study, spectral entropy ( ), permutation entropy ( ), and approximation entropy ( ) were all explored. To improve the classification using the k-nearest neighbors ( NN) classifier scheme, a comparative study of using fuzzy neighbourhood preserving analysis with -decomposition ( ) as a dimensionality reduction technique an
... Show MoreIn this paper, we build a fuzzy classification system for classifying the nutritional status of children under 5 years old in Iraq using the Mamdani method based on input variables such as weight and height to determine the nutritional status of the child. Also, Classifying the nutritional status faces a difficult challenge in the medical field due to uncertainty and ambiguity in the variables and attributes that determine the categories of nutritional status for children, which are relied upon in medical diagnosis to determine the types of malnutrition problems and identify the categories or groups suffering from malnutrition to determine the risks faced by each group or category of children. Malnutrition in children is one of the most
... Show MoreThe purpose of the study is to analyze the extent of the impact of liquidity as an independent variable on profitability as an intermediate variable and the value of banks listed in the Iraq Stock Exchange as a dependent variable, as the research problem is summarized by the fact that most banks focus on profitability as a phased goal without focusing on maximizing its value as a strategic goal by enhancing the wealth of owners and shareholders. On the long term, the research community is represented by the banks listed on the Iraq Stock Exchange, while the research sample was deliberately chosen, which included three private banks such as Baghdad Commercial Bank, the Iraqi Commercial Bank and the Iraqi Investment Bank, an
... Show MoreKnowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine
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