Thông tin cụ thể như sau:
I. Bài báo: Applicability of Deep Neural Networks in Business Decision Making and Market Investment - A Comprehensive Review
Sinh viên thực hiện:
- Phạm Thuỵ Thái An - K22411CA
- Lưu Hà Vy - K22411CA
- Lê Phạm Quỳnh Anh - K22416C
- Nguyễn Xuân Quỳnh - K22411CA
- Lê Minh Nguyên - K22416C
- Nguyễn Đặng Hoài Nam - K22406
- Huỳnh Lê Đông Quân - K22416C
Tóm tắt: Big data, both in its structured and unstructured formats, have brought in unforeseen challenges in economics and business. How to organize, classify, and then analyze such data to obtain meaningful insights are the ever-going research topics for business leaders and academic researchers. This paper studies recent applications of deep neural networks in decision making in economical business and investment; especially in risk management, portfolio optimization, and algorithmic trading. Set aside limitation in data privacy and cross-market analysis, the article establishes that deep neural networks have performed remarkably in financial classification and prediction. Moreover, the study suggests that by compositing multiple neural networks, spanning different data type modalities, a more robust, efficient, and scalable financial prediction framework can be constructed.
Tạp chí: Journal of Applied Economic Sciences
II. Bài báo: An AI-based Sperm Assessment System for Analyzing Human Sperm’s Reproductivity
Sinh viên thực hiện:
- Phạm Thuỵ Thái An - K22411CA
- Trần Thanh Huyền - K23411T
Tóm tắt: We introduce an AI-based Sperm Assessment System (ASAS) for automatically analyzing human sperm’s fertility and managing human sperm assessment reports. Our innovative ASAS takes input as an online-camera feed from a microscopic view or an offline-upload of a semen sample video; processes input stream to count the number of available sperms, track movement patterns, and classify any morphological abnormality; and generates a detailed sperm analysis report consisting of criteria guided by World Health Organization: sperm concentration, sperm motility, and sperm morphology evaluation. ASAS is easy to use and produces accurate preliminary results in case of unsanitized samples.
Hội thảo: 2025 7th IEEE Symposium on Computers & Informatics
III. Bài báo: Assessing Sperm Motility Through a Multi-Modal Correlation
Sinh viên thực hiện:
- Nguyễn Huỳnh Yến Nhi - K23411T
- Nguyễn Phạm Quốc Khiêm - K23406
- Huỳnh Lê Đông Quân - K22416C
Tóm tắt: The ability of sperm cells to move and swim efficiently is known as sperm motility, and it is needed for natural conception. This paper introduces a three-fold mechanism for sperm motility assessment that retains the most informative data, semi-automatically annotates visible sperm cells, and evaluate motility through a multi-modal correlation. This work suggests that by integrating both spatial aggregation and temporal information, a level of motile progressiveness can easily be determined, aligning with criteria guided by World Health Organization.
Hội thảo: 2025 7th IEEE Symposium on Computers & Informatics
IV. Bài báo: Assessing the Perceived Information From a Multi-Modal Representation of Your Idol: An AI-Agent Dynamic Survey
Sinh viên thực hiện:
- Nguyễn Xuân Quỳnh - K22411CA
- Lưu Hà Vy - K22411CA
- Nguyễn Hoàng Hương Giang - K23411T
- Trần Xuân Hương - K23411T
- Nguyễn Đặng Hoài Nam - K22406
Tóm tắt: The emergence of digital celebrities has transformed audience interactions, engagement, and evaluation of their idols. Traditional research methods often struggle to fully capture the nuanced responses these digital figures elicit. This study introduces an innovative AI-agent dynamic survey platform, enabling adaptive questioning and real-time engagement to explore audience perceptions of various virtual idols. The study's findings underscore the effectiveness of the proposed agent workflow in gaining deeper insights into audience understanding, offering a novel methodological contribution to media and consumer behavior research.
Hội thảo: 2025 7th IEEE Symposium on Computers & Informatics
V. Bài báo: Understanding Sarcasm in Social Networks: An AI-Agent Dynamic Survey
Sinh viên thực hiện:
- Lê Phạm Quỳnh Anh - K22416C
- Lê Minh Nguyên - K22416C
- Bùi Hoàng Diệu - K234112E
- Lương Hoàng Thái - K23411
- Lại Gia Hân - K23416
Tóm tắt: Understanding sarcasm is a complex challenge due to its inherent ambiguity and dependence on social and cultural contexts, which is further complicated in the era of social media. While recent research has largely focused on improving model performance through multi-modal and context-aware integrations, a deep understanding of sarcasm perception within specific communities remains underexplored. To address this gap, we propose a novel AI agent framework designed to advance the understanding of sarcasm perception, with a particular focus on the Vietnamese social media community, using a dynamic and user-oriented survey approach. The findings of this study highlight the potential of an AI agent workflow for conducting user-centered focus groups or case studies, presenting an innovative, scalable, and efficient research methodology.
Hội thảo: The 7th Asia Conference on Business and Economic Studies
