คณะเทคโนโลยีสารสนเทศ
Currently, the issue of developmental writing disabilities in children is a matter of great importance for school-age children. Diagnosing whether a child has developmental writing disabilities relies on writing skill assessments, which are administered to those seeking diagnosis and evaluated by medical professionals or experts. However, there are still limitations in the diagnostic process, which depends heavily on expert physicians, leading to a high demand for human resources. To address this, we have developed a method for scoring writing skill assessments using image processing technology, based on existing scoring criteria. Currently, three criteria are used for scoring: writing position, article format, and copying speed. We have also created a web application to make the system more accessible and easier to use.
คณะวิศวกรรมศาสตร์
Our project seek to create an Al-powered tarot card reader that bridges the gap between traditional fortune-telling and modern technology. By leveraging a combination of 3D modeling, natural language processing, text-to-speech (TTS), and speech-to-text (STT) systems, the service will deliver an interactive and culturally sensitive experience in Thai and English. Users will input their queries through voice, which will be processed via STT, and receive engaging Al-generated tarot readings through TTS. Additionally, a 3D animated avatar will mimic a real-life fortune teller, adding a visual dimension to the experience. Hosted on a user-friendly website, this platform will redefine fortune-telling by blending tradition with innovation, making it both accessible and engaging for modern users.
คณะเทคโนโลยีสารสนเทศ
This report is part of applying the knowledge gained from studying machine learning models and methods for developing a predictive model to identify customers likely to cancel their credit card services with a bank. The project was carried out during an internship at a financial institution, where the creator developed a model to predict customers likely to churn from their credit card services using real customer data through the organization's system. The focus was on building a model that can accurately predict customer churn by selecting features that are appropriate for the prediction model and the unique characteristics of the credit card industry data to ensure the highest possible accuracy and efficiency. This report also covers the integration of the model into the development of a website, which allows related departments to conveniently use the prediction model. Users can upload data for prediction and receive model results instantly. In addition, a dashboard has been created to present insights from the model's predictions, such as identifying high-risk customers likely to cancel services, as well as other important analytical information for strategic decision-making. This will help support more efficient marketing planning and customer retention efforts within the organization.
คณะวิศวกรรมศาสตร์
This project focuses on the development of an automatic license plate recognition system that supports both standard and special license plates in Thailand. By utilizing Machine Learning technology, the system enhances the efficiency of license plate reading. It can process data from both images and videos. Users can register and subscribe to the service, allowing them to send data for processing through RESTful API, WebSocket, and registered IP cameras.
คณะวิศวกรรมศาสตร์
Currently, lithium batteries are widely used in electronic devices and electric vehicles, making the estimation of their State of Health (SOH) crucial. Accurate SOH estimation helps extend battery lifespan, reduce maintenance costs, and prevent safety issues such as overheating or explosions. This project aims to study and analyze mathematical models of batteries and develop SOH estimation techniques using Neural Networks to enhance accuracy and evaluation speed. The experiment involved collecting charge and discharge data from three lithium battery cells under controlled temperature conditions while maintaining a constant current. The current, voltage, and time data were recorded and analyzed to determine the battery capacity for each cycle. These data were then used to train a Neural Network model. The results demonstrated an effective method for predicting battery health status. The outcomes of this project can contribute to the development of a Battery Management System (BMS) that improves battery efficiency and longevity. Additionally, it provides a foundation for applying artificial intelligence techniques in the energy sector effectively.
คณะศิลปศาสตร์
Layla, the hotel robot, is responsible for carrying guests’ luggage and guiding them to their accommodations. It is equipped with an internal map of the hotel, allowing it to navigate various locations efficiently. Additionally, it features an AI-powered system that enables interactive conversations in three major languages: Thai, English, and Chinese.
คณะวิศวกรรมศาสตร์
This capstone project develops an AI-powered chatbot to address cybersecurity vulnerabilities, leveraging the Common Vulnerabilities and Exposures (CVE) system and the Common Vulnerability Scoring System (CVSS). The chatbot will provide accessible and informative support for understanding and mitigating these vulnerabilities, potentially leading to significant improvements in cybersecurity practices.
คณะวิทยาศาสตร์
Recruitment is a crucial process that enables organizations to select candidates whose qualifications match the requirements of a given position. However, this process often faces challenges related to data management, delays, and human bias. This research aims to design and develop an intelligent web application for employee recruitment using artificial intelligence (AI) technology to evaluate and score candidates' suitability for job positions. The system leverages data analysis techniques on resumes and a qualification-matching process based on predefined criteria. Developed using Agile principles, the system employs Natural Language Processing (NLP) to analyze resumes, assess candidates’ qualifications, skills, and experience, and utilizes Machine Learning to predict and rank suitability. The system consolidates data from multiple sources into a unified database to reduce redundancy and input errors. Additionally, it presents insights through a dashboard, enabling HR teams to make more effective hiring decisions.
คณะวิทยาศาสตร์
In this paper, Vanadium dioxide (VO2) thin-film devices with two different use cases have been redesigned to introduce an asymmetrical resonant cavity structure. The structure is designed with the goal of enhancing the optical performance of the central VO2 layer and has an anti-reflection property in the cold state. The advantages and limitations of such a design are discussed.