The DKAP Project The Country Report of Vietnam

Viet Nam is at the beginning of the Fourth Industrial Revolution. In order to grasp the opportunities that the revolution has brought about, and to successfully build the society of digital citizens, there must be the demand of enhancing the capacity and capability for students to meet international standards in terms of Information and Communications Technology (ICT) skills. Viet Nam was selected as one of the four countries (Viet Nam, Bangladesh, Fiji, and the Republic of Korea) to join UNESCO Bangkok’s “Digital Kids Asia Pacific (DKAP)” project, a comparative cross-national study with the aim to seek the understanding and address children’s ICT practices, attitudes, behaviors, and competency levels within an educational context. Thanks to the project, the Vietnamese research team completely conducted the survey in twenty (20) schools from five (5) provinces in Viet Nam. With the data on the digital citizenship competency levels of 1,061 10th grade students, the research team discovered the valuable findings to draw an initial big picture for Vietnamese policy makers, educators, and teachers about digital citizenship competencies of 15-year-old Vietnamese students

An Online Distributed Boundary Detection and Classification Algorithm for Mobile Sensor Networks

We present a novel online distributed boundary detection and classification algorithm in order to improve accuracy of boundary detection and classification for mobile sensor networks. This algorithm is developed by incorporating a boundary detection algorithm and our newly proposed boundary error correction algorithm. It is a fully distributed algorithm based on the geometric approach allowing to remove boundary errors without recursive process and global synchronization. Moreover, the algorithm allows mobile nodes to identify their states corresponding to their positions in network topologies, leading to self-classification of interior and exterior boundaries of network topologies. We have demonstrated effectiveness ofthis algorithm in both simulation and real-world experiments and proved that the accuracy of the ratio of correctly identified nodes over the total number of nodes is 100%

Joint Communication and Computation Framework for Goal-Oriented Semantic Communication with Distortion Rate Resilience

Recent research efforts on semantic communication have mostly considered accuracy as a main problem for optimizing goal-oriented communication systems. However, these approaches introduce a paradox: the accuracy of artificial intelligence (AI) tasks should naturally emerge through training rather than being dictated by network constraints. Acknowledging this dilemma, this work introduces an innovative approach that leverages the rate-distortion theory to analyze distortions induced by communication and semantic compression, thereby analyzing the learning process. Specifically, we examine the distribution shift between the original data and the distorted data, thus assessing its impact on the AI model's performance. Founding upon this analysis, we can preemptively estimate the empirical accuracy of AI tasks, making the goal-oriented semantic communication problem feasible. To achieve this objective, we present the theoretical foundation of our approach, accompanied by simulations and experiments that demonstrate its effectiveness. The experimental results indicate that our proposed method enables accurate AI task performance while adhering to network constraints, establishing it as a valuable contribution to the field of signal processing. Furthermore, this work advances research in goal-oriented semantic communication and highlights the significance of data-driven approaches in optimizing the performance of intelligent systems.Comment: 15 pages; 11 figures, 2 table

ẢNH HƯỞNG CỦA NƯỚC BIỂN DÂNG ĐẾN THỦY TRIỀU KHU VỰC BIỂN MIỀN TRUNG CỦA VIỆT NAM

The tide is one of the most important phenomena in the ocean. In the world as well as in Vietnam, the tide was studied very early and great achievements have been recorded. However, under the impact of climate change and sea level rise, the local - to - regional - scale changes will cause significant changes in the coastal system. This paper gives some results of research on the tidal changes in the central region of Vietnam by using the hydrodynamic model and data analysing model. The simulation results of the tide in the central coast of Vietnam show that the tide can change both in the amplitude and phase distribution of the tidal constituents as M2, S2, K1 and O1. Specifically, the results of the average values of M2 are 0.1 m and 10.20; for S2 are 0.12 m and 12.50; for K1 are 0.2 m and 17.20; for O1 are 0.21 m and 20.20. Some results of this study showed that the most important contribution to the change of the tide in the region is the change of topography and the submerged areas.Thủy triều là một trong những hiện tượng quan trọng nhất trong đại dương. Trên thế giới cũng như ở Việt Nam, thủy triều được nghiên cứu từ rất sớm và đã đạt được nhiều thành tựu to lớn. Tuy nhiên, dưới tác động của biến đổi khí hậu và nước biển dâng, các quá trình có quy mô khu vực mang tính chất địa phương sẽ gây ra những thay đổi quan trọng trong các hệ thống ven biển. Bài báo này đưa ra một số kết quả nghiên cứu sự biến đổi của thủy triều trong khu vực biển miền Trung của Việt Nam. Nghiên cứu sử dụng phương pháp mô hình và phân tích điều hòa. Các kết quả mô phỏng về thủy triều trong khu vực biển miền Trung của Việt Nam cho thấy rằng thủy triều có sự biến đổi cả về biên độ và pha của các phân triều chính như M2, S2, K1 và O1. Cụ thể, kết quả giá trị trung bình đối với M2 là 0,1 m và 10,20; đối với S2 là 0,12 m và 12,50; đối với K1 là 0,2 m và 17,20; đối với O1 là 0,21 m và 20,20. Một số kết quả nghiên cứu này đã cho thấy rằng những đóng góp quan trọng nhất vào sự thay đổi của thủy triều trong khu vực là sự thay đổi địa hình và diện tích của thủy vực

Frequency and Risk Factor of Lower-limb Deep Vein Thrombosis after Major Orthopedic Surgery in Vietnamese Patients

BACKGROUND: Deep venous thrombosis (DVT) is a prevalent complication of orthopedic surgery. According in many studies. The incidence of DVT may be up to 50% if thromboprophylaxis is not available. AIM: The objective of this study was to check the degree of disease, clinical characteristics and analyzed factors in vulnerabilities with lower-limp DVT after orthopedic surgery in a Vietnam teaching hospital. METHODS: Orthopedic patients who met criteria were recruited at our hospital between August 2017 and June 2018. Ultrasound was used to discovering lower-limp DVT in pre-surgery and 7 days after surgery in all patients. RESULTS: The incidence of DVT after orthopedic surgery was 7.2%. Patients with older age (> 60) have a risk of 2 times higher of DVT after surgery than normal people (p < 0.05). The incidence of postoperative DVT was higher in immobile individuals > 72 hours (p < 0.05). Patients with prolonged surgical time (>120 minutes) had a higher risk of postoperative DVT than non-surgical patients’ surgery (p < 0.05). CONCLUSIONS: DVT remains a common complication following orthopedic surgery. Older age, immobility status, and surgical time have been found to be risky factors for the development of postoperative lower-limp DVT in orthopedic patients

THE CURRENT CONDITIONS OF PROMOTING THE PHYSICAL EDUCATION AND SPORTS ACTIVITIES FOR STUDENTS AT VIETNAM NATIONAL UNIVERSITY, HO CHI MINH CITY

The purpose of the study was to have a comprehensive understanding of the existing conditions assured to give physical education (PE) programs to students at Vietnam National University, Ho Chi Minh City (VNUHCM). Through document synthesis, interviews, and statistical processing, the article gained a general evaluation of the current PE conditions according to the following aspects: facilities, administration, and curriculums. In terms of facilities, the total space for sports activities at VNUHCM is measured at 25,454m2, besides, the ratio of sports field area per student is 0.44m2/student. This indicates that VNUHCM’s students do not have enough space for their sports practice as standard. In terms of faculty, teachers at VNUHCM Sports Center are comprised 67.6% male, 88.2% at the age of thirty to fifty, and 100% holding postgraduate qualifications. In addition, 79.4% of the staff at the VNUHCM Sports Center graduated with PE specialized degrees, and 64.7% of them have less than five years of seniority. However, 68.8% of those who are currently delivering PE courses at this Center are visiting teachers. The statistic number reveals that the ratio of students per teacher at VNUHCM is 814.75 students/teacher, which reveals that the number of PE lecturers has not met the standard, and they have been in charge of a large teaching volume. In terms of curriculums, PE programs are conducted with 06 credits in total (90 periods), divided into 02 modules with 3 credits per each (45 periods). Students are allowed to choose their favorite PE content among 10 sports courses including football, volleyball, basketball, table tennis, tennis, badminton, martial arts, aerobics, swimming, and chess. The results indicate that VNUHCM’s students actively participate in sports training and competitions to advance their physical fitness.  Article visualizations

On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation

Constructing a robust model that can effectively generalize to test samples under distribution shifts remains a significant challenge in the field of medical imaging. The foundational models for vision and language, pre-trained on extensive sets of natural image and text data, have emerged as a promising approach. It showcases impressive learning abilities across different tasks with the need for only a limited amount of annotated samples. While numerous techniques have focused on developing better fine-tuning strategies to adapt these models for specific domains, we instead examine their robustness to domain shifts in the medical image segmentation task. To this end, we compare the generalization performance to unseen domains of various pre-trained models after being fine-tuned on the same in-distribution dataset and show that foundation-based models enjoy better robustness than other architectures. From here, we further developed a new Bayesian uncertainty estimation for frozen models and used them as an indicator to characterize the model's performance on out-of-distribution (OOD) data, proving particularly beneficial for real-world applications. Our experiments not only reveal the limitations of current indicators like accuracy on the line or agreement on the line commonly used in natural image applications but also emphasize the promise of the introduced Bayesian uncertainty. Specifically, lower uncertainty predictions usually tend to higher out-of-distribution (OOD) performance.Comment: Advances in Neural Information Processing Systems (NeurIPS) 2023, Workshop on robustness of zero/few-shot learning in foundation model