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- A teacher from the Department of Computer Science (Lect. Nada Najil Kamal) obtained the top score in the course named (Digital Image Processing Using Matlab) that was held at the Center for Continuing Education in the university for the period (5-9 /1/2020).





Source: Department's Media

- A discussion of the master student (Ali Abdul-Kazim Taher) was conducted in the Department of Computer Science / University of Technology on his thesis entitled (Improve Genetic Algorithm Population Using Artificial Bee Colony) The Bee Colony Algorithm (ABC) is an approach of swarm intelligence that simulates the behavior of searching for honeybees in the colony, Initially, suggested solving numerical optimization problems using a unique mechanism to search for adjacent solutions. 2-opt algorithm is one of the most popular local search algorithms to solve the (TSP) problem. The principle of the algorithm is to randomly switch two cities to a specific path to produce a new path so that the total distance of the new path is shorter than the total distance of the original path. In this thesis, two methods are proposed to improve the genetic algorithm. The first by using bee colony algorithm (GABC). The second method is to improve the genetic algorithm using the 2-opt (GOPT) algorithm. The problem of generating random numbers RNG (necessary for coding algorithms) and the problem of TSP was chosen to test the two proposed methods for improving the genetic algorithm .... This was on Thursday, (2/1/2020) at the discussion hall in the department and the discussion committee consisted of (Dr. Aliaa' Karim Abdel Hassan and Dr. Ikhlas Khalaf Kabbashi) from the University of Technology / Department of Computer Science and (Dr. Haitham Abdel Latif Omar) from Alsalam University College / Department of Computer Science with the presence of the student’s supervisor (Dr. Suhad Mal Allah Kazim).



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Source: Department's Media

- Discussion of the master student (Gheed Tawfiq Walid) in the Department of Computer Science / University of Technology on her thesis entitled (Improve Unsupervised Deep Neural Network to Enhance Anomaly Detection in Secure Mobile Network) This thesis proposes an improved model for detecting fraud cases of Banking credit card transactions. The proposed model consists of three stages, the first stage processes and reduces the dimensions of the data set and prepares it for the next stage, which is the unsupervised training phase. At this stage, the learning process is carried out through one of the concepts of deep learning, which is the automatic stack encoding, which is represented by the use of three layers of the neural network trained using different activation functions, which strive to generate close data for each of the classes that are passed through these three layers. This stage is followed by a group of operations, the first of which is to improve the results using Adam algorithm followed by the process of calculating the difference between the results and the data entered to reduce the error rate and then the process of classification of data to fraud or normal .. And that was on Thursday, (26/12/2019) at the Discussions hall in the department. The discussion committee was composed of (Prof. Dr. Ahmed Tariq Sadiq and Prof. Dr. Hanaa' Mohsen Ahmed) from the University of Technology / Department of Computer Science and (Dr.Abeer Salem Jamil) from Al Mansour University College / Department of Computer Science in the presence of the supervisors of the student (Dr. Abeer Tariq Mawloud and Prof. Dr. Abdul Mohsen Jaber Abdel Hussein).



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Source: Department's Media

- A graduate student thesis discussion was held for the student Samir AbdulWahab Qadir from the Department of Computer Sciences / University of Technology for his thesis entitled (Personalized Social Friends Recommendation System based on User's Behavior). This thesis proposed a personalized friend recommendation system with two different models, namely dual-stage friend recommendation model and model-based friend recommendation model. The dual-stage model applies a methodology on unlabeled data of 1241 users. Such data are collected from OSN users via online survey platform featuring user interests and activities based upon which users, with similar social behavioral patterns, are recommended to each other. The model employs a variety of techniques, including User-Based Collaborative Filtering (UBCF) approach and graph-based approach friend-of-friend recommendation. The dual-stage model offers solutions to common problems of FRS such as data sparsity as well as providing seamless integration with other FRSs. The evaluation of the dual-stage model shows a positive correlation of Pearson Correlation Coefficient (PCC) compared to the baseline used... This was on Thursday, 14/11/2019 at the discussion hall in the department and the discussion committee was composed of (Prof. Dr. Ahme Tariq Sadiq and Assist Prof. Dr. Hasaneen Sameer Abdullah) from the University of Technology / Department of Computer Science and (Assist Prof. Dr. Khalid Shakir Jasim) from Al Anbar University / Department of Computer Science and in the presence of the student's supervisor (Assist Prof. Dr. Ayad Rawdhan Abbas).



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Source: Department's Media

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