Publications
The Role of Digitization In Revitalizing The Course System At Northern Technical University
Sep 5, 2022Journal Journal of Education and Science
Publisher جامعة الموصل كلية التربية للعلوم الصرفة
DOI DOI: 10.33899/edusj.2022.135492.1272
Issue ISSN 1812-125X
Volume , Vol: 31, No: 04, 2022 (142-150)
Northern Technical University in Iraq relied in their education on the course system, which was marked by some kind of difficulties. A questionnaire was distributed to staff members including professors, technicians, administrators, administrators along with students subject to the curriculum system as a secondary source for collecting data and information. The study found that NTU as a modern university has an infrastructure supported by an electronic educational administrative information system. It provides an integrated digital platform for teachers to participate extensively in lectures, courses, scientific and practical workshops, create interactive lessons and assignments, tests and assessment through a solid. Such a platform could facilitate the students to complete their homework and academic duties in the time available to them. Students could be informed and notified by sending them an email that includes educational contents and details. This will definitely assist the university to keep using the course system. The study dealt with data analysis by using structural equation modeling technique and the confirmatory factor analysis strategy as a means to measure the observational variables represented by the digitization axes, which in turn matched the measures of statistical analysis Amos.
Iris recognition based on 2D Gabor filter
Aug 11, 2022Journal International Journal of Electrical and Computer Engineering (IJECE)
DOI DOI: 10.11591/ijece.v13i1.pp325-334
Issue ISSN: 2088-8708,
Volume Vol. 13, No. 1, February 2023
Iris recognition is a type of biometrics technology that is based on physiological features of the human body. The objective of this research is to recognize and identify iris among many irises that are stored in a visual database. This study employed a left and right iris biometric framework for inclusion decision processing by combining image processing and artificial bee colony. The proposed approach was evaluated on a visual database of 280 colored iris pictures. The database was then divided into 28 clusters. Images were preprocessed and texture features were extracted based Gabor filters to capture both local and global details within an iris. The technique begins by comparing the attributes of the online-obtained iris picture with those of the visual database. This technique either generates a reject or approve message. The consequences of the intended work reflect the output’s accuracy and integrity. This is due to the careful selection of attributes, besides the deployment of an artificial bee colony and data clustering, which decreased complexity and eventually increased identification rate to 100%. We demonstrate that the proposed method achieves state-of-the-art performance and that our recommended procedures outperform existing iris recognition systems.