The student Mohammed Saleh Mahdi received his doctorate degree from the Department of Computer Sciences / University of Technology for his thesis entitled "Proposed an Efficient Secure Healthcare IoE". In this thesis, five proposals were submitted and mobile applications were applied to improve efficiency and security of the Internet. Their actual limits are balanced. First, it is proposed to make light, unobtrusive pressure to improve Internet efficiency by reducing the volume of data sent and working efficiently even with low-performance equipment. Second, the proposed low pressure light weight loss treatment that addresses image processing problems and bandwidth in the Internet IoE everything. Thirdly, two low-cost aerodynamic packages (Salsa, Hybrid Chacha, and Salsa Super) to encrypt the information exchanged between Google's cloud platform as a backend and the sensors of the Internet are all for health care. Fifth, the proposal of the generator of keys based on the algorithm of fireflies to create the session of the first Salsa and Chacha hybrid, and the super salsa in the function Google Firebase. This was on Thursday 17/1/2019 at the discussion room in the department. The discussion committee was composed of Prof. Dr. Hala Bahjat Abdul Wahab and Dr. Yusra Hussain Ali, Dr. Abeer Tariq Mawlid from the University of Technology / Computer Sciences Department and Prof. Ghassan Abdel Hamid Abdel Majeed from the Ministry of Higher Education and Scientific Research, Research & Development Department and Dr. Haidar Kazem Hamoud from the University of Al-Mustansiriya. Education College / Department of Computer Science, in the presence of the student supervisor (Dr. Nidaa Fleih Hassan).

Download Abstract

The student Zainab Abdul Ameer Shmal has obtained her master's degree from the Department of Computer Sciences / University of Technology for her thesis (Enhance Search Result Using Dissimilar Patterns and Chicken Swarm Algorithm). Chicken Squad is used as an algorithm to identify appropriate traits in the system to improve the search process. The concept (unmatched style) was used to remove and delete unrelated pages from the results of the ordered list, and to improve the results of the user query. The proposed NLEL corpus standard set of data sets was tested for 11,650 documents. The experimental results were precision 81%, recall 70% accuracy, 92.2%. Of the proposed system compared to traditional systems achieved with the same data set. This was on Wednesday, 16/1/2019, and at the discussion room in the annex building of the department. The discussion committee was composed of Dr. Ayad Roudan Abbas and Dr. Suhad Malallah Kazem of the University of Technology / Computer Sciences Department And Dr. Nada Abdel-Zahra Abdullah from Baghdad University / Faculty of Science / Computer Science Department in the presence of the student supervisor (Dr. Alia Karim Abdel Hassan).

Download Abstract

The student Mohammed Abdul Jaleel Shnein received his master's degree from the Department of Computer Sciences / University of Technology for his thesis (classification of text using a sophisticated intelligent system). In this thesis, these problems are solved using the proposed classification system based on the logic of fog and genetic algorithm. The proposed system passes through four stages: data collection, pre-processing, extraction and grading. At the data collection stage, this system is based on the Sandy Hurricane event, where data is collected for the time period from 10.27.2012 to 11.7.2012. A set of 1002 tweets taken from the primary data are used as test data and a set of 1000 jitter used as training data. The initial processing stage, which is used to improve the text for the best possible results, where the text contains symbols and mark Hashtak and numbers and words are undesirable. In the initial processing phase, six steps are used, such as handling the Hashtak tag, removing the additions, splitting the text into words, removing the stop words, deriving the words to extract the word origin and determining the correct meaning of the word in the sentence. In the feature extraction phase, eleven features are extracted from each tweet to give a more accurate result. In the classification phase, the proposed system used the fuzzy logic and the genetic algorithm, where the proposed system in the classification phase is going through three steps, namely, inhibition, inference and elimination of the degradation. The Fuzzification phase is used to convert real inputs into misty groups and determine the degree of membership for each value in the vector of features. The Genetic Algorithm is used in the induction step to generate new membership grades. In the Inference phase, a set of ambiguous rules is adopted, where the blurry rules are a set of linguistic values ​​for each feature and contain a classification decision. This was on Thursday 10/1/2019 and on the discussion room in the building of the department. The discussion committee was composed of: Dr. Suhad Mal Allah Kazem and Dr. Hassanein Samir Abdullah from the University of Technology / Computer Sciences Department, Dr. Haitham Abdul Latif Omar from Al-Nahrain University Computer Science Department with the presence of the student supervisors (Dr. Yusra Hussein Ali and Dr. Noha Jamil Ibrahim).

Download Abstract

Dr. Soukaina Hassan Hashem and Dr. Shaima Hameed Shaker received, thanks and appreciation letter from the President of the University Dr. Amin Douai Thamer for the efforts made by them in participating in the success of the Fourth Scientific Conference on Environment and Sustainable Development organized by the Department in cooperation with the Arab Union for Sustainable Development and the Environment in the Arab Republic of Egypt for the period 24-28 / 11/2018, hoping them to continue to do more. To our beloved university.

Lecturers Rana Mohamed Hassan and Taiba Walaa al-Din Khairi from the Department of Computer Sciences Published Their research entitled "Recovering the image of an old document using hybrid technology" in IJAR magazine, which is the use of a mixed algorithm to improve the old document. The algorithm performs some pre-processing on the old document, The first stage is a series image of the old document to be ready to enter the algorithm that enhances character detection using a local and global threshold for character recognition and another process is applied to the image to remove noise from the image enhanced image of the old document.