- Final Year Project (FYP)
Authors: Nguyen, Thu Huyen; Advisor: Nguyen, Doan Dong (2024) - The evolution of contemporary civilization is significantly influenced by the stock market. They make it possible to allocate financial resources. Variations in stock prices are a reflection of market movements. Deep learning is frequently employed in the financial industry for tasks including stock market prediction, optimum investing, and financial information processing due to its strong data processing capabilities in many domains. Put financial trading concepts into practice. For this reason, one of the most significant and well-liked professions in the financial industry is stock market prediction. In this research, I suggest using the Transformer - supervised deep learning meth...
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- Final Year Project (FYP)
Authors: Nguyễn, Thảo Vi; Advisor: Nguyen, Doan Dong (2024) - This research focuses on addressing the challenges of applying large language models (LLMs) to solve high school mathematics problems, particularly in the Vietnamese context. Despite the remarkable advancements in natural language processing enabled by LLMs, they still struggle when it comes to mathematical problem-solving. The objective of this study is to enhance the computational and reasoning proficiencies of LLMs for tackling high school mathematics problems. The proposed approach involves utilizing topic classification to identify the relevant mathematical topic, searching for similar problems in a corpus, extracting answers, and employing in-context learning for further improve...
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- Final Year Project (FYP)
Authors: Nguyễn, Đình Hiếu; Advisor: Nguyen, Doan Dong (2024) - The focal point of this project is distinctly defined: the creation of a user-friendly mobile
application that leverages contemporary technologies to optimize and simplify event
attendance tracking for students. Through the seamless integration of Kotlin in the
Android front end and Spring Boot in the back end, the project aims to rectify the inherent
limitations of conventional manual attendance processes. Kotlin, celebrated for its
conciseness and expressiveness, is strategically employed to deliver a fluid and
captivating user experience on the Android platform. Concurrently, the incorporation of
Spring Boot, renowned for its efficiency in backend development, ensures the
e...
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- Final Year Project (FYP)
Authors: Le, Hoang Anh; Advisor: Nguyen, Doan Dong (2024) - Mobile software and applications are incredibly diverse and abundant across various mobile operating systems. Prominent operating systems include J2ME, Android, iOS, Hybrid, and Web-based Mobile Applications, all of which have seen strong development in the mobile communication market. In recent years, Android has emerged, combining the superior features of previous operating systems with the latest technologies. Android has quickly become a fierce competitor to its predecessors and is considered the mobile operating system of the future, widely favored by users both domestically and internationally.
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- Final Year Project (FYP)
Authors: Pham, Gia Khiem; Advisor: Nguyen, Doan Dong (2024) - Project Introduction -- Project Management Plan -- Software Requirements Specification -- Software Design Description -- Software Release -- Future development
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- Final Year Project (FYP)
Authors: Bùi, Mạnh Tùng; Advisor: Nguyen, Doan Dong (2023) - In recent years, ERP (Enterprise Resource Planning) systems have grown in
popularity as more companies use them to manage their financial operations. ERP
systems offer a complete solution for combining different business operations into one
system, including finance, accounting, inventory management, human resources, and
customer relationship management. Businesses may manage their financial data more
effectively and efficiently thanks to this connectivity.
Many studies have examined the advantages and difficulties of implementing
ERP systems for financial administration, which has been the focus of substantial study
on ERP systems. Researchers have looked into how ERP systems...
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- Final Year Project (FYP)
Authors: Le, Mai Anh Thang; Advisor: Nguyen, Doan Dong (2021) - Due to the fast spread of coronavirus (COVID-19), the world is dealing with a major health catastrophe. World Health Organization (WHO) had promulgated hints of protection towards the spread of COVID-19. According to WHO, the foremost effective fortification method against COVID-19 is to put on masks publicly and in crowded places. It is challenging to keep an eye on people manually in these places. This thesis proposes four transfer-learning models to identify the people that are not wearing the mask (YOLOv5, YOLOv4-tiny, Detectron2, and EfficientDet-Lite0). Image augmentation is implemented to deal with the narrow data for improved training and testing performance. These four models...
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- Student report
Authors: Nguyen, Thi Thanh Binh; To, Minh Ha; Cao, Thi Thu Trang; Advisor: Tran, Duc Quynh; Nguyen, Doan Dong (2024) - Ensemble methods in machine learning have gained prominence for improving prediction accuracy. Predicting student performance is crucial for effective educational interventions. This study investigates ensemble methods in machine learning for
predicting the factors that can influence student performance, aiming to enhance accuracy and reliability. Diverse ensemble methods, including bagging, boosting, and stacking, are employed with various base learners. Performance is evaluated through rigorous experimentation and cross-validation. Ensemble methods demonstrate significant improvements in prediction accuracy compared to traditional methods, with Random Forest machine learning model...
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- Final Year Project (FYP)
Authors: Vu, Minh Hieu; Advisor: Nguyen, Doan Dong (2025) - The rapid expansion of the sharing economy has significantly transformed the hospitality and tourism industry, with peer-to-peer (P2P) accommodation platforms such as Airbnb redefining customer experiences and service expectations. This thesis examines the factors influencing customer retention in Vietnam’s P2P accommodation sector, with a particular focus on revisit intentions. Using a dataset of over 86,000 customer reviews collected from Airbnb listings across Vietnam, this study applies advanced Natural Language Processing (NLP) techniques, including Latent Dirichlet Allocation (LDA) for topic modeling and sentiment analysis with VADER and SentiWordNet. Customer feedback was label...
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- Final Year Project (FYP)
Authors: Nguyen, Tuan Thanh; Advisor: Nguyen, Doan Dong (2024) - Search Engine Optimization (SEO) is critically important in the digital marketing landscape, particularly within the healthcare sector. This thesis develops a robust decision model for search engine rankings aimed at optimizing website performance to better satisfy user demands. Utilizing two advanced gradient boosting models, Light Gradient Boosting Machine (LightGBM) and Extreme Gradient Boosting Decision Trees (XGBoost), this study assesses the relationships and relative importance of various SEO factors. Comparative analysis indicates that XGBoost supersedes LightGBM in predicting actual search engine rankings, achieving an average accuracy rate of 87.7%. A detailed feature analys...
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- Final Year Project (FYP)
Authors: Doãn, Văn An; Advisor: Nguyen, Doan Dong (2025) - This study focuses on addressing the challenges associated with applying Large Language Models (LLMs) and the Retrieval Augmented Generation (RAG) method, while also incorporating voice processing to resolve students' inquiries about information for the school in areas such as admissions, academic advising, scientific research, and updates on new information and announcements from the International School – Vietnam National University, Hanoi. Although LLMs have made significant advancements in natural language processing, they still encounter difficulties when handling specific applications. The objective of this research is to enhance the knowledge and reasoning capabilities of LLMs ...
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