On Saturday, March 30, 2024, at 21:00, students from the Information Security field (Faculty of Computer Networks and Communications) participated in presenting their research findings on the topic: "Prescription Medication Management Model in the Context of Multi-Blockchain Communication Application" at the ICISN 2024 - The 4th International Conference on Intelligent Systems & Networks held on March 23-24, 2024, in Hanoi. The conference, organized by Swinburne Vietnam and FPT Education, focused on Intelligent Systems and Networks, along with the fields of security and advanced technologies. Paper Title: "Medichain: A multi-chain based system for managing prescription medications using Zero Knowledge Proofs" Student Researcher: Tran Duc Minh (Information Security Major - High-Quality Program 2020) Supervisors: MSc. Tran Tuan Dung and Dr. Pham Van Hau Accepted research papers will be published in the digital library of Springer publishers: https://link.springer.com/book/10.1007/978-981-99-4725-6 Detailed Information: https://inseclab.uit.edu.vn/sinh-vien-nganh-an-toan-thong-tin-trinh-bay-bao-cao-ket-qua-nghien-cuu-tai-hoi-nghi-khoa-hoc-quoc-te-the-international-conference-on-intelligent-systems-networks-icisn-2024/?fbclid=IwAR1wpQjx3WEToKnEpn-w1fOL_BXiPslZzdlRyvGSLE9k9Bdrey82PUNMasU_aem_AQKRwSh4JsjuL-Ws1OT2mLMvcCdPOULvLUUKQkzoQqmaNLGFZhzglYJcPCKaTwixRteLYrkHm8pWehyj6E0YEKU4 Đông Xanh - Media Collaborator, University of Information Technology English version: Phan Huy Hoang

Congratulations to student Ngô Thanh Nhân, Student ID 18521175, from the Faculty of Computer Engineering for excellently achieving an IELTS certificate with a score of 7.0. We wish you continued academic success with your outstanding achievements! UIT always encourages students to improve their language skills towards becoming global citizens and comprehensive role models. Detailed Information: https://www.facebook.com/UIT.Fanpage/posts/pfbid0JbMQrddmjNgsiLXwy4f37vasohGuJuzB4HBbN67ePDyf5S2X2S55n5QvwRjV1VCol Đông Xanh - Media Collaborator, University of Information Technology English version: Phan Huy Hoang

Congratulations to student Nguyen Duc Minh Khoa, ID 21520998, from the Faculty of Software Engineering for excellently achieving an IELTS certificate with a score of 7.0. Wishing you even greater academic success with your outstanding achievements! UIT always encourages students to improve and enhance their foreign language skills, aiming towards a generation of global citizens and comprehensive role models. Detailed Information:  https://www.facebook.com/UIT.Fanpage/posts/pfbid02bJ3ZRqbT6bb4ZvZY3nffJYabG9RXbhQXNSdGvfoeD7iqvyGLasfgYiTdoCmm5bydl Đông Xanh - Media Collaborator, University of Information Technology English version: Phan Huy Hoang

With the desire to introduce extremely attractive internship opportunities and share technical knowledge and experiences with students, the Faculty of Computer Engineering, in collaboration with Ampere Computing Vietnam Company Limited, is organizing the first Seminar on Advanced Circuitry 2024. At the seminar, you will have the opportunity to hear about the company, the working environment, as well as internship opportunities. Especially, we will also have a Mini Game, everyone! Don't hesitate any longer, register now to not miss out on this valuable opportunity! Seminar information: Time: 15:00 on Tuesday, April 2, 2024 Location: Room C109, Building C, University of Information Technology Registration link: https://docs.google.com/forms/d/e/1FAIpQLSccqSG9cHsGFc0q6bpw-2Rtz5w1rlaW64c7Q4lcTfr5-UW3bw/formrestricted Registration deadline: March 31, 2024 Detailed Information: https://www.facebook.com/ce.uit/posts/pfbid02EgxdhkT1U9PMa18Wc5GQ9hgv5Jag5c3P6f9T3UJU2CGJMhrpFEiFQNRbkbHXC8EYl  Hạ Băng - Media Collaborator, University of Information Technology English version: Phan Huy Hoang

03 Silver Medals (Second Prize) Nguyễn Đình Thiên Quang - Analysis; Lê Văn Huy - Analysis; Nguyễn Xuân Phúc - Algebra; 03 Bronze Medals (Third Prize) Nguyễn Đức Hiến - Algebra; Lê Thị Bích Loan - Algebra; Nguyễn Đức Hiến - Analysis; For more details, please visit: link Best regards, Đông Xanh - Collaborator, University of Information Technology Communication Team

Student Researchers: Le Hoang Phuc (20521762) - Do Huu Khanh Hung (20521361) - Nguyen Tran Linh Dat (20521173) Soil erosion is a serious issue in Dak Lak Province, Vietnam. To assess the extent of soil erosion, we integrated the Revised Universal Soil Loss Equation (RUSLE) model and geographic information system (GIS). Dak Lak is a region with diverse terrain, ranging from high mountains to plateaus and valleys. Clearly, with such characteristics, applying RUSLE to areas with particular attention to the LS and R factors is crucial due to the complex elevation distribution and seasonal rainfall, which significantly impact soil erosion. Other factors such as K and R also have distinct local characteristics compared to the conditions of the original RUSLE equation. Therefore, to use the RUSLE formula, we applied formulas published by Vietnamese authors for areas with similar conditions to calculate the R factor. Establishing a database in GIS: Taking a system approach according to each erosion-affected parameter. To calculate erosion on GIS, the first step is to build a database. Model parameters (R, LS, K) are computed from input data (maps). In this study, the goal is to calculate and create a potential soil erosion map, so we need to calculate the R, LS, K factors. Based on the R factor map, LS factor map, and K factor map to establish a potential erosion map for Dak Lak. The research results show that there is variation in the degree of erosion across the province, and areas with the highest land loss are mainly concentrated in the north and southeast. Specifically, the areas with the highest soil erosion were identified in the south, especially in the Chu Yang Sin and Chu Mu mountainous areas. Additionally, in the north, Ea H'Leo district is also prominent with significant land loss due to erosion, with erosion rates reaching over 39.5 tons/ha/year in some areas. The study also indicates that areas with relatively flat or low-lying terrain, combined with dispersed rainfall during the rainy season, constitute the majority of the natural area of the Central Highlands and are not heavily eroded, accounting for 77.34% of the total area. Meanwhile, hilly and mountainous areas, especially those with low erosion resistance, account for about 18.47% of the natural area, mostly located on hills, low mountains, or on the outskirts of plateaus. These areas have a medium erosion potential, accounting for about 2.78% of the natural area. It can be seen that the influence of terrain and rainfall on erosion is significant, and attention should be paid to managing and protecting land in areas with high erosion potential as analyzed. This information will be the basis for decision-making in land use planning in mountainous regions, helping to minimize erosion risks and effectively protect land resources. The study also emphasizes the importance of measuring and managing erosion to protect land and water resources. In the context of changing land use becoming an important issue in Vietnam, especially in mountainous areas, this study provides historical information and forecasts land use trends in Dak Lak over the past 20 years. This helps local policymakers make informed decisions, combining economic and social development with environmental protection. Using the Improved RUSLE model and GIS, this research provides an effective tool to assess potential erosion in Dak Lak, supporting policy decisions and environmental management at the local level. Best regards. For more information, please visit: https://fit.uit.edu.vn/index.php/tin-tuc/goc-hoc-tap/6601-tich-hop-phuong-trinh-mat-dat-pho-dung-cai-tien-rusle-va-he-thong-thong-tin-dia-li-gis-de-uoc-tinh-xoi-mon-dat-tai-tinh-daklak Dong Xanh - University of Information Technology Communications Collaborator

Application of GIS and Remote Sensing Technology to Build a Potential Flood Map for Quang Tri Province Authors: Tran Vo Tan Tai, Le Thi Thiep, Nguyen Thi Phuong Quyen In recent years, many storms, floods, and landslides have swept away houses, property, and caused numerous casualties, disrupting production activities, especially in the central provinces of Vietnam. Floods are formed due to the combination of various factors such as terrain characteristics, soil structure, vegetation cover, and rainfall. The reduction in forest area and climate change have made floods more frequent and harder to predict. Therefore, forecasting and prevention of floods play a crucial role in minimizing damages. Currently, geographic information systems (GIS) and remote sensing technology are widely used in many fields, including natural disaster warnings. The purpose of this research is to combine remote sensing and GIS technology with the Flash Flood Potential Index (FFPI) to delineate flood risk areas in Quang Tri Province. Quang Tri Province is located in the North Central region of Vietnam. Its terrain gradually decreases from the west to the east, with rainfall concentrated during the rainy season. It has a dense river and stream network with steep slopes. Additionally, deforestation in some areas due to human activities (logging, agricultural expansion, etc.) has increased the likelihood of landslides. Given these natural characteristics, Quang Tri is prone to landslides. Moreover, the province's economy and society have developed significantly, but it still heavily relies on agriculture, and people's lives face many difficulties. Therefore, the impacts of landslides significantly affect people's lives in various aspects (life, property, psychology, etc.). The research content includes collecting data and using GIS and remote sensing methods to process satellite images and classify the FFPI (Greg Smith, 2010) for each component factor: slope, soil type, land use status, forest cover density, and rainfall distribution. Each dataset will be assigned FFPI values from 1 to 10, with 1 being the lowest and 10 being the highest. Each component is weighted and stacked to produce a flood potential map. The smallest value of 1 corresponds to the least affected area, and the largest value of 10 corresponds to the area with the highest flood potential. The flood risk map of Quang Tri Province is established with 4 levels of risk: very high, high, medium, and low. The results show that in the 7 districts and 2 towns, areas with high flood risk are mostly in the districts of Dakrong, Cam Lo, Huong Hoa, and Hai Lang. The total area of ​​districts in the high and very high flood risk zones accounts for more than 20% of the province's total area. These are districts with high mountains, steep slopes, strong terrain division, difficult transportation conditions, and prone to isolation. They have gray soil with a high clay content, sparse forest cover, and significant average monthly rainfall. Specifically: The western districts of Dakrong (383.5 km2), Cam Lo (30.1 km2), Huong Hoa (259.8 km2), and the coastal areas in the southeast of Hai Lang (383.5 km2). For areas with low risk like Vinh Linh, Gio Linh, northeast of Cam Lo, Trieu Phong, and Quang Tri. Currently, the map provides a relative assessment of areas at risk of landslides. However, its accuracy is still limited because it mainly depends on available data and lacks the ability to measure real-time information. Nevertheless, it provides a general view of areas that may experience landslides in the future to implement prevention and mitigation measures and contribute to stabilizing the community's life. Best regards. For more information, please visit: https://fit.uit.edu.vn/index.php/tin-tuc/goc-hoc-tap/6602-ung-dung-cong-nghe-gis-va-vien-tham-xay-dung-ban-do-tiem-nang-lu-quet-tinh-quang-tri Dong Xanh - University of Information Technology Communications Collaborator

Once again, another exam season is approaching. Have you started reviewing yet? If not, why hesitate to join our super cool training sessions with us? Our training series from the Study Board not only provides foundational knowledge but also shares many tips and skills for exam preparation. In addition, we have prepared a set of practice tests for you to assess your understanding and help you confidently enter the exam room! The Study Board would like to announce the training schedule as follows: K18: Statistical Probability: Offline Training: Trainers: - Vo Chi Cuong - KTPM2023.1 - Nguyen Le Tuan Anh - KTPM2023.1 Time: 9:30 AM on Thursday (April 11th) Location: Room C205 Online Training: Trainers: - Nguyen Tai Tan - KHMT2023.4 - Quach Vinh Co - KTPM2023.1 Time: 7:00 PM on Thursday (April 11th) Location: Microsoft Teams (Code: w2dsy1q) Discrete Structures: Offline Training: Trainers: - Tien Minh Duong - KTPM2023.1 - Ngo Le Tan Huy - MMTT2023.1 Time: 9:30 AM on Wednesday (April 10th) Location: Room C214 Online Training: Trainers: - Le Ngo Thanh Toan - KHMT2023.4 - Tran Hoai Minh - KHMT2023.3 Time: 7:00 PM on Wednesday (April 10th) Location: Microsoft Teams (Code: w2dsy1q) K17: Operating Systems: Trainers: - Huynh Le Dan Linh - KTPM2022.2 - Truong Doan Vu - MMTT2022.3 Format and Time: Online training at 7:00 PM on Saturday (April 13th) Location: Microsoft Teams (Code: w2dsy1q) For more details, visit: https://www.facebook.com/bhtcnpm/posts/pfbid0uCe9mRu2bgor6dMw7xw5coB3SZYgeRb65YrhGvofBsbSPQzokmv3cTbrUsZywbUZl  Ha Bang - Media Collaborator, University of Information Technology Nhat Hien - Translation Collaborator, University of Information Technology

On Tuesday, April 9, 2024, at 10:00 AM, the Faculty of Software Engineering organized a seminar with the theme "A Hybridized Network Analysis and Community Detection for Unraveling Disease Spreading Covid-19 Pandemic Mechanisms," with the participation of professors and lecturers from the faculty. The presentation by Dr. Nguyen Thi Xuan Huong was successfully conducted. The paper analyzed the context of the Covid-19 pandemic, which has caused an unprecedented global health crisis, requiring a deeper understanding of the mechanisms of disease transmission to develop strategies to minimize its impact. On the other hand, network analysis and community detection techniques have been shown to be valuable in elucidating the complex activities of infectious diseases. Therefore, the authors proposed an approach that combines network analysis algorithms and community detection to better understand the mechanisms of Covid-19 transmission. By examining the structure of the disease transmission network and identifying distinct communities within it, the research provides comprehensive insights into the intensity of the pandemic and contributes to the development of intervention measures to minimize its spread. The Faculty of Software Engineering hopes that the seminar has contributed to creating a valuable forum, promoting the exchange of knowledge, and thereby encouraging research and the development of scientific careers. The Faculty of Software Engineering sincerely thanks Dr. Nguyen Thi Xuan Huong for taking the time to share her valuable knowledge and experience, as well as all the professors and lecturers who participated and contributed to the success of the seminar. Please continue to follow and participate in our upcoming events to update more valuable knowledge and opportunities for interesting exchanges! For more details, visit: https://se.uit.edu.vn/tin-tuc/13-khoa-hoc-cong-nghe/1644-tổng-kết-seminar-học-thuật-a-hybridized-a-hybridized-network-analysis-and-community-detection-for-unraveling-disease-spreading-covid-19-pandemic-mechanisms.html  Ha Bang - Media Collaborator, University of Information Technology Nhat Hien - Translation Collaborator, University of Information Technology

- Are you a student feeling lost with your graduation thesis or research project? - Do you want to proceed but don't know where to start? Join the "Seminar: Guidelines for Writing Graduation Thesis Proposals and Research Project Presentations for Students" to find answers to your questions. Program information: Time: 10:00 AM – 11:30 AM, Tuesday, April 9, 2024 Location: Room E10.1, School of Information Technology Speaker: TS. Cao Thi Nhan – Head of Department – Deputy Head of Department of Information Systems. Registration link: https://forms.gle/fpDShTyQxu8XQYfq5 With her experience, the speaker will provide you with an overview and specifics, from choosing a topic to completing your thesis proposal and research project presentation. Let this seminar be an important turning point, helping you progress further in your academic and scientific research journey. Let's explore, learn, and overcome every challenge together! Don't forget, we have an appointment at the seminar! For more details, visit: https://www.facebook.com/uit.khoahttt/posts/pfbid0djomJejb9YQwy3m5BJQyXWwSsmzWJf3ZGAjQH5NGfzcB8ps28hWwyBy8Mg35aZcHl  Ha Bang - Media Collaborator, University of Information Technology Nhat Hien - Translation Collaborator, University of Information Technology

BiSim-Inspector is a tool designed and developed to detect Binary Code Similarity Detection (BCSD) based on a Deep Learning approach, specifically utilizing the Byte2Vec transformation technique and the CNN-GRU model. Essentially, BCSD is a process of analyzing the binary representations of two functions, programs, or related entities to produce a quantitative result, indicating the similarity score between them. This process can address the binary search problem, involving finding code segments in a binary file that are similar to a specified binary segment. These capabilities open up numerous potential applications in the field of binary analysis, including software vulnerability detection based on similarity with previously vulnerable software, code clone detection, and malware analysis. This product is the result of the research project of a group of Information Security students when participating in research at the Information Security Training Center: they published one international scientific paper at SoICT 2023. Author Information: Nguyễn Hùng Thịnh - ATCL 2020 Lê Trần Thành Nhân - ATTN 2019 Nguyễn Phúc Hải - ATTT 2020 Trần Đình Khoa - ATTN 2022 Scientific Paper: "Binary Representation Embedding and Deep Learning For Binary Code Similarity Detection in Software Security Domain" For more details, please visit: BiSim-Inspector Video Written by: Dong Xanh Translated by: Ngoc Diem

Feeling overwhelmed by the scorching heat? Stressed out with academic pressure? Midterm exams approaching? Too many worries in this semester? Well then, take a moment to see what IS Study Committee has in store to cool you off! To help K18 students actively review and prepare well for the upcoming Midterm exams, the IS Study Committee organizes training sessions to review knowledge. Joining these review sessions, you not only get to review the materials you've learned but also have the opportunity to share study experiences together and listen to effective "tips" from our "superhero" trainers from the Study Committee. So why hesitate? Quickly save the training schedule and join us! Midterm Training Schedule - K18 STATISTICAL PROBABILITY - MA005    Time: 9:00 AM - 11:30 AM on Monday, April 8, 2024    Location: Room B3.16, Building B, University of Information Technology    Trainers:        + Luong Dac Nguyen - KHDL2023        + Tran The Phong - HTTT2023        + Nguyen Khanh Vy - TMĐT2023 DISCRETE STRUCTURES - MA004    Time: 2:30 PM - 4:30 PM on Thursday, April 11, 2024    Location: Room B1.14, Building B, University of Information Technology    Trainers:        + Dang Huu Tho - HTTT2023        + Le Nguyen Minh Thu - HTTT2023        + Truong Duong Hieu Thao - TMĐT2023 For more details, visit: https://www.facebook.com/BHTHTTT/posts/pfbid02iuNKzso2Yz2173Vu8W7roVFpP4Y8y2k3mXcTAFKRvoSDmpvCJ2KdtjvNy5DebrQql Ha Bang - Media Collaborator, University of Information Technology Nhat Hien - Translation Collaborator, University of Information Technology