On February 24th, 2024, at the University of Information Technology, the Faculty of Information Science and Engineering successfully organized the Master's Thesis Defense Session in Information Technology for the first round of the year 2024. The defended thesis topics were highly persuasive and showed promising prospects for practical application. We extend our heartfelt congratulations to all graduate students and wish them success and steadfastness on the career path they have chosen. Some images from the defense session can be found at the following link: https://drive.google.com/drive/folders/1kREQc3I4t9TRDeQh0NWu8PQKl96sBqIw?usp=drive_link  Mọi thông tin chi tiết xem tại: https://fit.uit.edu.vn/index.php/tin-tuc/tin-h-c-v/thong-bao-cac-h-dao-t-o/thong-bao-he-cao-hoc/6566-kh-kttt-t-ng-k-t-bu-i-b-o-v-lu-n-van-th-c-si-nganh-cong-ngh-thong-tin-d-t-1-nam-2024 Hạ Băng - Media Collaborator, University of Information Technology English version: Phan Huy Hoang

Title: ZIE - BUZZ SOCIAL MEDIA LISTENING SYSTEM = SOCIAL MEDIA DATA COLLECTION AND EXPLOITATION SYSTEM Thesis in Software Engineering Author: Hua Phuoc Truong. Supervisor: MSc. Nguyen Dang Khoa Summary: With the remarkable development of social media in recent years, 81% of internet users use social media to communicate and connect with friends. Social media has gradually become a mental necessity for internet users. Besides, social media is also a channel containing a lot of information, opinions, and comments about a brand, a product, or a service. According to the 2013 WebM statistics, 26% of users use social media to mention a brand, product, or service. 70% of users trust reviews and recommendations from the internet, second only to the figure of 92% of users trusting reviews from acquaintances and friends. Meanwhile, the corresponding figure for TV advertising is 40%. Based on these compelling figures, product promotion campaigns and tracking user opinions on social media have become a highly interesting issue for large businesses and even small businesses choosing the internet as their destination. In this report, I propose a social media listening system, collecting users' posts and opinions to be as complete and valuable as possible, providing useful data for researchers. If you are interested, please access the full text remotely at the following address (Login with your Library-issued account): https://ir.vnulib.edu.vn/handle/VNUHCM/31346 For any inquiries or support regarding access accounts, please contact via email: thuvien@uit.edu.vn For more details, visit: https://www.facebook.com/LibUIT.Fanpage/posts/pfbid02ET5E7Wnwczo68Sf7z96... Ha Bang - Media Collaborator, University of Information Technology Nhat Hien - Translation Collaborator, University of Information Technology

Title: DEVELOPING SOME RECOMMENDATION METHODS TO SUPPORT ACADEMIC INFORMATION SEARCH BASED ON SOCIAL NETWORK ANALYSIS APPROACH [Ph.D. thesis in Computer Science] Author: Huynh Ngoc Tin Summary: Searching for scientific information to carry out research-related tasks is a frequent and essential need for researchers, especially for young researchers who lack experience in finding and identifying relevant information. Meanwhile, experienced researchers face information overload. To make it easier for them to access useful academic information, recommendation systems in the academic field have been a solution of interest in recent years. Common academic information recommendation problems include recommending papers, collaborations, submitting papers, etc. The traditional approaches for recommendation systems, such as Demographic Filtering, Content-Based Filtering, Collaborative Filtering, and Hybrid approaches, face challenges such as big data, lack of standardized benchmark data for experimental evaluation, low accuracy, cold-start issues, and a lack of suitable methods for evaluating recommendation quality. Emerging approaches to developing new recommendation system methods include social network analysis, context information exploitation, and hybrid methods [23]. In reality, people's interests and decisions are often influenced by those in their relationships. Researchers often need advice from friends, colleagues, and mentors to make important decisions related to research tasks. Therefore, the thesis adopts a social network analysis approach (considering time factors) combined with some other information to address the limitations of some common methods and applies them to recommend academic information. If you are interested, please visit the Library to read the hard copy or access the full text remotely at the following address: https://ir.vnulib.edu.vn/handle/VNUHCM/15985 For any inquiries or support regarding access accounts, please contact via email: thuvien@uit.edu.vn For more details, visit: https://www.facebook.com/LibUIT.Fanpage/posts/pfbid02vwdvm81Q3mSjgyz1j... Ha Bang - Media Collaborator, University of Information Technology Nhat Hien - Translation Collaborator, University of Information Technology

To assist students of the MMT&TT Department in understanding the procedures and determining specific research directions for Specialized Projects (ĐACN) and Graduation Theses (KLTN), on the evening of January 19, 2024, the MMT&TT Department organized an online seminar. The seminar attracted nearly 300 students from the "Computer Networks and Data Communication" and "Information Security" majors within the MMT&TT Department. In the first part of the program, the procedures for implementing ĐACN/KLTN were shared with students of both majors by Ms. Tran Thi Dung - Deputy Head of the MMT&TT Department. Mr. Van Thien Luan also introduced the ĐACN/KLTN management systems of the Department through the website mmt.uitiot.vn. Additionally, the Latex language report writing support system (latex.uitiot.vn) was introduced by Mr. Luan to help student groups compose reports conveniently, and advisors can quickly track and edit reports. In the second part of the program, information and directions of research groups in the Department were introduced to the attending students by faculty members: UiTiOt Research Group – Mr. Le Trung Quan InSecLab Research Group – Mr. Pham Van Hau IEC Research Group – Mr. Le Kim Hung Research Direction Sidechain/Blockchain – Mr. Tran Tuan Dung Research Direction Blockchain/Quantum – Mr. Nguyen Ngoc Tu Research Direction SDN/Deep Learning – Mr. Phan Xuan Thien Some images from the seminar: For more details, please visit: https://nc.uit.edu.vn/nckh/nghien-cuu/khoa-mmttt-to-chuc-seminar-gioi-thieu-quy-trinh-va-dinh-huong-cho-do-an-chuyen-nganh-va-khoa-luan-tot-nghiep.html Written by: Ha Bang Translated by: Ngoc Diem

On February 24, 2024, at the University of Information Technology, the Faculty of Computer Science and Information Technology successfully organized the defense session for Master's theses in Information Technology for the first session of 2024. The presented thesis topics were highly convincing and showed promising applications in practical scenarios. We extend our congratulations to all graduate students, wishing them success and steadfast progress on the chosen professional path. Some images from the defense session can be found at: Google Drive Link For more detailed information, please visit: University of Information Technology - News Written by: Ha Bang Translated by: Ngoc Diem

The full scholarships for women in the STEM field are officially back. In 2023, Vietnam had 8 candidates awarded the Women in STEM scholarship, leading in quantity in the East Asia region. Building on this success, the British Council, in collaboration with technical universities, is organizing the Women in STEM 2024 online seminar with the aim of connecting, promoting women's participation in science and technology, and introducing postgraduate scholarships in the United Kingdom for women. This year, the British Council continues to implement two full scholarship programs for women in STEM: ASEAN – UK SAGE STEM Scholarship for Women: Launched for the first time by the UK government, through the British Embassy in ASEAN and the ASEAN Secretariat. The scholarship aims to address gender disparities in employment and digital skills in ASEAN countries and Timor-Leste. British Council STEM Scholarship for Women: The British Council has implemented a global STEM scholarship program for women in collaboration with UK universities. This is the fourth year the British Council has offered this scholarship to female candidates in Vietnam. In addition to the opportunity to study at a prestigious university in the United Kingdom, the scholarship covers tuition fees, living allowances, travel expenses, visa fees, health insurance, and reimbursement of IELTS exam fees (if applicable). UK universities accepting scholarship applications from Vietnam include the University of Bristol and the University of Warwick. Translated by: Ngoc Diem

Artificial Intelligence in Manufacturing Enabling Intelligent, Flexible, and Cost-Effective Production Through AI. Author: John Soldatos (2024) => Full text: Link Phygital Intelligence Proceedings of the 5th International Conference on Computational Design and Robotic Fabrication (CDRF 2023) Authors: Chao Yan, Hua Chai, Tongyue Sun, Philip F. Yuan in Computational Design and Robotic Fabrication (2024) => Full text: Link Digital Twin Architectures, Networks, and Applications Author: Yan Zhang in Simula SpringerBriefs on Computing (2024) => Full text: Link New Digital Work Digital Sovereignty at the Workplace Authors: Alexandra Shajek, Ernst Andreas Hartmann (2023) => Full text: Link Making Presentation Math Computable A Context-Sensitive Approach for Translating LaTeX to Computer Algebra Systems Author: André Greiner-Petter (2023) => Full text: Link Foundations of Robotics A Multidisciplinary Approach with Python and ROS Authors: Damith Herath, David St-Onge (2022) => Full text: Link The Road to General Intelligence Authors: Jerry Swan, Eric Nivel, Neel Kant… in Studies in Computational Intelligence (2022) => Full text: Link Big Data and Artificial Intelligence in Digital Finance Increasing Personalization and Trust in Digital Finance using Big Data and AI Author: Prof. John Soldatos… (2022) => Full text: Link For more details, please visit: Link Written by: Ha Bang Translated by: Ngoc Diem

Two students from the Computer Networks and Communication Department, specializing in Computer Networks and Data Communication and Information Security, participated in presenting research results at the "2024 9th International Conference on Intelligent Information Technology" from February 23 to 25, 2024, in Ho Chi Minh City. The conference was organized by FPT University and the Hong Kong Chemical, Biological & Environmental Engineering Society (HKCBEES). Paper 1: "ChainSniper: A Machine Learning Approach for Auditing Cross-Chain Smart Contracts" Student: Vo Anh Kiet (Information Security - Talent Program 2020) Paper 2: Zk-Auction: A Cross-Blockchain System for Efficient Auctions combining Zero-Knowledge Proof and NFT Student: Khuu Minh Phong (Computer Networks and Data Communication - Regular Program 2020) Supervisors: MSc. Tran Tuan Dung, PhD. Pham Van Hau Conference information: ICIIT 2024 is the 9th International Conference on Intelligent Information Technology, held in Ho Chi Minh City, Vietnam, from February 23 to 25, 2024. The conference is co-organized by FPT University and the Hong Kong Chemical, Biological & Environmental Engineering Society (HKCBEES), with support from Hung Vuong University in Ho Chi Minh City, Polytechnic University of Shanxi, High-Performance Computing Association of Guangdong, and the School of Electrical Engineering and Computer Science (EECS), National Taiwan University. Accepted papers and registered presentations may be published in the conference proceedings of the ACM International Conference Series or the Journal of Advances in Information Technology, archived in the ACM Digital Library, and indexed by Ei Compendex and Scopus." For more detailed information, please visit: Link to Facebook post Written by: Ha Bang Translated by: Ngoc Diem

A student from the Computer Networks and Data Communication program (Department of Computer Networks and Communication) participated in presenting research findings on the topic of privacy preservation in the context of blockchain-based communication at the "EAI INISCOM 2024 - 10th EAI International Conference on Industrial Networks and Intelligent Systems" on February 20-21, 2024, in Da Nang. The conference was organized by Duy Tan University (DTU) Da Nang in collaboration with the European Alliance for Innovation. Paper Title: "CrossCert: A Privacy-Preserving Cross-chain System for Educational Credential Verification using Zero-Knowledge Proof" Student Researcher: Khuu Minh Phong (Computer Networks and Data Communication - Regular Program 2020) Supervisor: M.Sc. Tran Tuan Dung Conference Information: INISCOM 2024 is the 10th international conference on Intelligent Systems and Industrial Networks, co-organized by the European Alliance for Innovation (EAI) and Duy Tan University (Da Nang). The conference took place from February 20-21, 2024, in Da Nang, Vietnam. The event focused on topics related to information technology, artificial intelligence, and intelligent systems in the industry. The conference RIVF 2023 centered around key themes including Big Data, AI, Digital Twin, 6G Networks, and practical applications in various aspects of life and industry. Accepted research reports will be published in the digital library of Springer (https://link.springer.com/conference/iniscom). For more details, please visit: https://www.facebook.com/inseclab/posts/pfbid02CSKorDWAKKRxh2tHbyhpT3RavEYyvwaBPxvc245K3jRyEGrMaMstVqZn9Q8ngAuzl Written by: Ha Bang Translated by: Ngoc Diem

Thesis Title: OBJECT DETECTION METHODS FOR DIFFICULT OBJECTS IN IMAGES [Ph.D. in Computer Science Thesis] Author: Nguyen Duy Khanh Abstract: Object detection is one of the crucial problems in computer vision with widespread applications in various fields such as robotics, medical image processing, surveillance systems, human-machine interaction systems, and intelligent transportation. In recent years, object detection methods have advanced significantly, achieving substantial improvements in both accuracy and processing speed, exemplified by deep learning-based methods like R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, YOLO, SSD, and Retinanet. Upon reviewing results from existing object detection models, we observed that challenging objects can be overlooked or mispredicted in complex real-world situations. Successfully detecting these difficult objects holds the potential to enhance the performance of object detection models. Therefore, this thesis focuses on proposing methods to detect difficult objects, aiming to improve existing object detection models. During the thesis research, NCS published four journal papers: JVCI-2019 (ISI), MTAP-2019 (ISI), IEEE TIP-2019 (ISI), Electronics-2020 (ISI), and presented four papers at international conferences: ICONIP-2013 (Rank A), IC3INA-2016, FAIR-2017, ACM IMCOM-2018. New Results of the Thesis The content of the thesis includes the following research issues: i. Propose a method to re-detect difficult objects using deep learning in two stages. Drawing inspiration from approaches to exploit difficult objects, we propose a method focusing on exploiting difficult objects that modern CNN-based object detection algorithms do not handle well. We suggest combining an easy object detector and a difficult object detector, where the difficult object detector is trained to detect objects missed by the easy object detector. ii. Propose a method to generate artificial data to enhance the effectiveness of object detectors on difficult object sets. Building on the idea of generating artificial data to augment the training of object detectors, we propose a directed artificial data generation method. The generation of artificial data should focus on difficult objects that are typically less prevalent in the dataset. We suggest that artificial data generation should be combined with the process of exploiting difficult objects in the dataset. iii. The thesis also applies the results of the object detection model to a related problem: salient object detection. We extract image segmentation masks running on bounding boxes from the object detection model to calculate semantic information. Object bounding boxes can be obtained from the proposed difficult object detectors or any other advanced object detection methods. We then propose wall and non-wall mappings using semantic information to detect salient objects with high accuracy. Applications/Potential Applications in Practice or Open Issues for Further Research The weaknesses of the proposed methods are the high computational cost and the multi-stage training process. Therefore, these methods could be improved by integrating stages into a unified network architecture, supporting a seamless training process. Simultaneously, feature extraction (feature maps) can be shared among detectors to minimize computational costs. Readers interested can access the library to read the paper or view the full text online at the following address: https://ir.vnulib.edu.vn/handle/VNUHCM/15985 For any inquiries or assistance regarding access accounts, please contact via email: thuvien@uit.edu.vn For more details, please visit: https://www.facebook.com/LibUIT.Fanpage/posts/pfbid02XC4FiKPFCRQsGTb3CxZBJErLCU8bMEAFawpXqu6Tk8XXXFikS151tXPG2zKrHxGAl Written by: Ha Bang Translated by: Ngoc Diem

Student: Hoang Mai Thien Phuc Student ID: 20520695 - Faculty: Faculty of Information Technology Congratulations on your excellent achievement! Wishing you continued success in your studies with the best accomplishments! UIT always encourages students to cultivate and enhance their language skills, aiming for a generation of global citizens and comprehensive role models. For more details, please visit: UIT Facebook Post Written by: Ha Bang Translated by: Ngoc Diem

University of Information Technology will organize the doctoral dissertation evaluation meeting at the University level for: Research student: Nguyen Van Kiet Major: Computer Science, Code: 62 48 01 01 (9 48 01 01). Dissertation title: Research on building an automatic reading comprehension model for Vietnamese text. Time: 2:00 PM, March 1, 2024. Venue: Room E1.1, University of Information Technology, Quarter 6, Linh Trung Ward, Thu Duc City, Ho Chi Minh City. Supervisor 1: Associate Professor Dr. Nguyen Luu Thuy Ngan Supervisor 2: Dr. Nguyen Gia Tuan Anh Independent examiner: Exempted The full dissertation and the abstract of the doctoral dissertation will be displayed at the Library of University of Information Technology, Block A, for those interested to refer to during the library's opening hours. We cordially invite lecturers, scientists, researchers, students, and those interested to attend the meeting of the Council. The Graduate Academic Affairs and Science Technology For more details, visit: https://fit.uit.edu.vn/index.php/tin-tuc/tin-h-c-v/thong-bao-cac-h-dao-t-o/thong-bao-he-tien-si/6547-thong-bao-v-vi-c-t-ch-c-phien-h-p-h-i-d-ng-danh-gia-lu-n-an-ti-n-si-c-p-tru-ng-c-a-ncs-nguy-n-van-ki-t Dong Xanh - Media Collaborator, University of Information Technology Nhat Hien - Translation Collaborator, University of Information Technology