In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimensional Convolutional Neural Network Hybrid Model (1D-CNNHM). The MUCT database was considered for training and evaluation. The performance, in terms of classification, of the J48 model reached 96.01% accuracy whereas the DL model that merged LDA with MI and ANOVA reached 100% accuracy. Comparing the proposed models with other works reflects that they are performing very well, with high accuracy and low processing time.
A low speed open circuit wind tunnel has been designed, manufactured and constructed at the Mechanical Engineering Department at Baghdad University - College of Engineering. The work is one of the pioneer projects adapted by the R & D Office at the Iraqi MOHESR. The present paper describes the first part of the work; that is the design calculations, simulation and construction. It will be followed by a second part that describes testing and calibration of the tunnel. The proposed wind tunnel has a test section with cross sectional area of (0.7 x 0.7 m2) and length of (1.5 m). The maximum speed is about (70 m/s) with empty test section. The contraction ratio is (8.16). Three screens are used to minimize flow disturbances in the test section.
... Show MoreThe purpose of this paper is to identifying the values of some physical and Bio- Kinematic variables during the performance of the jump spike serve skill, and identifying the effect of the proposed training program using intermittent training to develop some physical and Bio- Kinematic variables and accuracy of the jump spike serve skill among the research sample. The experimental method was used and the research was conducted on a deliberately chosen sample of the players of the Army Club, who were primarily advanced in volleyball, and the number of the sample was (10) players. The conclusions were reached that the proposed training program using intermittent training has a positive effect on some of the physical and Bio- Kinematic variabl
... Show MoreClassifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area. The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and
... Show MoreThe region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled
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