Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles and others relative geometric features for recognition give accuracy about 95.73% when the seven emotion classes are tested and 97.23% when the 6 classes (except normal class) are only tested. These rates are considered high when compared with the results of other newly published works.
Background: Beta thalassemia is a typically autosomal recessive form of severe anemia which is caused by an imbalance of two types of protein (alpha and beta) subunits of hemoglobin. Oxidative stress imbalance is the equilibrium between pro-oxidant\antioxidant statuses in cellular system, which results in damaging the cells. Antioxidant is a chemical that delays the start or slows the rate of lipid oxidation reaction and it play a very important role in the body defense system against reactive oxygen species. The aims of this study were to recorded the oro-facial manifestations in beta thalassemic patients and assess the oxidative stress marker malondialdehyde in serum and salivs and their role in the pathogenesis of beta thalassemia and ev
... Show MoreBackground: The purpose of this study was to assess the relation among the ramal length and width with various cervical and cranio-facial measurements for a sample of Iraqi adults with different skeletal classes. Materials and method: The sample composed of 71 Iraqi adults (36 females and 35 males) with an age ranged between 17-30 years and had different skeletal mal-relations using SNA, SNB and ANB to differentiate between them and assorting them into CL.I, CL.II and CL.III mal-relation. Each individual was subjected to clinical examination and digital true lateral cephalometric radiograph that had been analyzed using AutoCAD 2007 software computer program to determine sixteen linear and ten angular measurements. Descriptive statistics wer
... Show MoreThe literature shows conflicting outcomes, making it difficult to determine how e-learning affects the performance of students in higher education. The effect of e-learning was studied and data has been gathered with the utilization of a variety of qualitative and quantitative methods, especially in relation to students' academic achievements and perceptions in higher education, according to literature review that has been drawn from articles published in the past two decades (2000-2020). The development of a sense of community in the on-line environment has been identified to be one of the main difficulties in e-learning education across this whole review. In order to create an efficient online learning community, it could be claim
... Show MoreThe researcher used the experimental approach due to its suitability and the nature of the research problem. The research community was represented by the eighth-grade students in the Rozak Elementary Mixed School affiliated with the General Directorate of Education in Erbil / the center, for the academic year (2021-2022), the number is (96) students, and the research sample consisted of (63) male and female students, with (31) in the experimental group, and (32) in the control group, and (11) students were excluded by (5) students from the experimental group, and (6) students from the control group, as the excluded, are students who failed and were absent from the lessons, and accordingly, the research sample became composed of (52) mal
... Show MoreStudies on the flexural behavior of post-tensioned beams subjected to strand damage and strengthened with near-surface mounted (NSM) technique using carbon fiber-reinforced polymer (CFRP) are limited and fail to examine the effect of CFRP laminates on strand strain and strengthening efficiency systematically. Furthermore, a design approach for UPC structures in existing design guidelines for FRP strengthening techniques is lacking. Hence, the behavior of post-tensioned beams strengthened with NSM-CFRP laminates after partial strand damage is investigated in this study. The testing program consists of seven post-tensioned beams strengthened by NSM-CFRP laminates with three partial strand damage ratios (14.3% symmetrical damage, 14.3%
... Show MoreStatistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c
... Show MoreA (k,n)-arc is a set of k points of PG(2,q) for some n, but not n + 1 of them, are collinear. A (k,n)-arc is complete if it is not contained in a (k + 1,n)-arc. In this paper we construct complete (kn,n)-arcs in PG(2,5), n = 2,3,4,5, by geometric method, with the related blocking sets and projective codes.
In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.