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.
Six proposed simply supported high strength-steel fiber reinforced concrete (HS-SFRC) beams reinforced with FRP (fiber reinforced polymer) rebars were numerically tested by finite element method using ABAQUS software to investigate their behavior under the flexural failure. The beams were divided into two groups depending on their cross sectional shape. Group A consisted of four trapezoidal beams with dimensions of (height 200 mm, top width 250 mm, and bottom width 125 mm), while group B consisted of two rectangular beams with dimensions of (125 ×200) mm. All specimens have same total length of 1500 mm, and they were also considered to be made of same high strength concrete designed material with 1% volume fraction of steel fiber.
... Show MoreThe research aims to highlight on the reasons of financial & managerial corruption phenomena and to suggest systems & methods that promote controlling and developing the mechanism to combat corruption it also highlights on the ways that should available to enable the three regulatory agencies to reduce this phenomenon. The research depends on the following hypothesis "the governance of state institutions and the application of electronic government with depending on a correct mechanism to crossing auditing and the equilibrium performance model well help to reduce corruption phenomenon in Iraq" the two researchers have been concluded some conclusions the main one is that so many reasons of corruption starting from the bad
... Show MoreThe study aims to build a proposed training program for school leaders in the Sultanate of Oman on the planning practices of the Kaufman model in light of the needs and challenges of reality. It also aims to identify the challenges facing school leaders in practicing the stages of strategic planning. To achieve these objectives, the study adopted the descriptive approach due to its suitability to the nature of the study. A questionnaire was used to collect the needed data. The study sample included (225) individuals from school principals, their assistants and senior teachers in post-basic education in the Sultanate of Oman. After processing the data statistically, the study concluded that the reality of planning practices for school lea
... Show MoreKnowledge represents the foundation stone for the work of all organizations, are working who leads the thinking of individuals is the ability that leads to behavior based on rationality, it is the work that creates value to the organization and thus gain access to performance winning where that knowledge is a new type of capital based on the thought and experience and is the so-called intellectual capital, which is renewable and is constantly evolving. The study sought to explain the role of the climax knowledge in achieving the highest levels of performance Organizational and then access to the performance winning in educational organizations the study sample, was found to be a co
... Show MoreThis study investigates the effectiveness of mental games in enhancing shooting accuracy among young basketball players. Initially, baseline shooting accuracy was assessed through tests conducted prior to a three-week intervention involving mental games. A follow-up test revealed a significant improvement in participants' shooting accuracy following the intervention. Given the noticeable differences in the new shooting scores compared to the initial assessments, a second set of pre-intervention tests was conducted. These tests reaffirmed the significant enhancement in shooting accuracy, substantiating the hypothesis that mental games positively affect performance. The findings highlight the importance of these intervention programs
... Show MoreThis study investigates the effectiveness of mental games in enhancing shooting accuracy among young basketball players. Initially, baseline shooting accuracy was assessed through tests conducted prior to a three-week intervention involving mental games. A follow-up test revealed a significant improvement in participants' shooting accuracy following the intervention. Given the noticeable differences in the new shooting scores compared to the initial assessments, a second set of pre-intervention tests was conducted. These tests reaffirmed the significant enhancement in shooting accuracy, substantiating the hypothesis that mental games positively affect performance. The findings highlight the importance of these intervention programs
... Show MoreBackground: Female basketball players often face difficulties in maintaining free throw accuracy, particularly under psychological and neural pressure. Traditional training emphasizes physical skills, often neglecting cognitive and neurophysiological factors essential for precision performance. Objective: This study examined the effect of neurofeedback training on free throw accuracy in female basketball players at the University of Baghdad, comparing outcomes between an experimental group and a control group, and assessing associated neural changes. Methods: A quasi-experimental design involved two groups: an experimental group receiving neurofeedback to regulate brainwave activity, and a control group undergoing traditional traini
... Show MoreTwo unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.