คณะวิทยาศาสตร์
The objective is to develop a web application for tool requests to issues arising from using Excel programs. The initial Excel file is copied from an existing SQL database and repeatedly duplicated, leading to excessive storage consumption. Additionally, the Excel files cannot be accessed concurrently by multiple users. Therefore, this web application aims to connect directly to the SQL database, eliminating the problems caused by using Excel files.
คณะวิทยาศาสตร์
Nowadays, automobiles are the most widely used form of transportation. This increases the risk of accidents. Therefore, car users prefer to get insurance to reduce the risk in the event of an accident. As for the insurance company, the company will be responsible for damages according to the conditions of the policy. One of the duties of a company's claims department is to procure spare parts to control costs. However, in the case of compensation, there may be erroneous operations, such as ordering the wrong parts or ordering more than necessary. Currently, insurance companies do not have a very efficient management system. This research aims to develop a system for managing and storing automobile parts for insurance companies. The system is designed to be able to track the status of spare parts from storage to disbursement. It uses barcode technology to increase accuracy and reduce errors in data recording. Such a system will help insurance companies manage spare parts systematically, reduce unnecessary costs, and increase efficiency in providing services.
คณะวิทยาศาสตร์
This project focuses on the study and development of a short-term investment framework via gold trading in the foreign exchange market. Machine learning techniques are applied to analyze and forecast pricing trends. Moreover, we develop the system using a stochastic process to determine optimal stop-loss points, with the aim of maximizing expected returns. Additionally, we apply game theory to guide the decision-making process regarding order holding or closure. The system is implemented and tested on the MetaTrader 5 (MT5) platform. This project outlined the clear process that includes data preparation, machine learning model training, probabilistic modeling of gold price movements, stop-loss strategy formulation, strategic decision modeling based on game theory, the development of an automated trading program, and backtesting to evaluate system performance.
คณะวิศวกรรมศาสตร์
This project aims to introduce an Automated Vertical Metal Sheet Storage System. The project is aimed at teaching how to make an Automation Vertical Metal Sheet Storage System with the integration of microcontroller devices. The project is divided into two main sections, which are the structure and control systems of the Automation Vertical Metal Sheet Storage System that will be designed and drawn through a computer program and constructed using major aluminum structures upon completion of their actual sizes outlined in the programs. Also, a Microcontroller control system using GX Works 2 program from Mitsubishi PLC has been designed for this purpose where it controls up and down movements as well as sideways movement of the pallet. It also has a weighing capability along with touch screen display for displaying information about the steel plates and controlling the Automation Vertical Metal Sheet Storage System with safety light curtain that protect users safety. These tests have shown that the machine operates normally. There are few mistakes whose rates fall within those expected by humans.
คณะวิทยาศาสตร์
In a highly competitive business, understanding customers is crucial for an organization to determine its success. Effective marketing is not just about offering good products, promotions, or services; it also requires strategies to reach and build strong relationships with customer groups. Segmenting customers is one method that helps businesses deeply understand the needs and behaviors of the customers who use their services In this internship, the objective is to understand the behavior of customers purchasing coffee and tea at a large cafe group by analyzing stored customer data. As a result of this process, customer groups purchasing coffee and tea were segmented using Naive Bayes, Random Forest, and Deep Learning techniques to compare the accuracy and suitability of different Machine Learning methods, and the insights gained from this analysis can be for further development in analyzing other data set in the future
คณะวิศวกรรมศาสตร์
Under The National Broadcasting and Telecommunications Commission (NBTC), the Telecommunication Enforcement Bureau collects a lot of data on service quality by monitoring and controlling the quality of telecommunications services, mainly by assessing mobile network infrastructure. The NBTC used Microsoft Excel for data analysis but became ineffective and slow. We used Python programming for preparation, analysis, and data processing to address this. Raw data was obtained from the Syberiz program in CSV format, processed in Python, and displayed on a dashboard. The dashboard, developed using Power BI, meets NBTC's telecommunications quality standards. It features maps, test results, and graphical representations. This method enhances the dashboard's appearance and usability and speeds up data processing and visualization compared to Microsoft Excel. This project is primarily designed to help the Telecommunication Enforcement Bureau's operations by making data processing and display for telecommunications quality monitoring faster, more effective, and easier to use.
คณะเทคโนโลยีสารสนเทศ
Facial Expression Recognition (FER) has attracted considerable attention in fields such as healthcare, customer service, and behavior analysis. However, challenges remain in developing a robust system capable of adapting to various environments and dynamic situations. In this study, the researchers introduced an Ensemble Learning approach to merge outputs from multiple models trained in specific conditions, allowing the system to retain old information while efficiently learning new data. This technique is advantageous in terms of training time and resource usage, as it reduces the need to retrain a new model entirely when faced with new conditions. Instead, new specialized models can be added to the Ensemble system with minimal resource requirements. The study explores two main approaches to Ensemble Learning: averaging outputs from dedicated models trained under specific scenarios and using Mixture of Experts (MoE), a technique that combines multiple models each specialized in different situations. Experimental results showed that Mixture of Experts (MoE) performs more effectively than the Averaging Ensemble method for emotion classification in all scenarios. The MoE system achieved an average accuracy of 84.41% on the CK+ dataset, 54.20% on Oulu-CASIA, and 61.66% on RAVDESS, surpassing the 71.64%, 44.99%, and 57.60% achieved by Averaging Ensemble in these datasets, respectively. These results demonstrate MoE’s ability to accurately select the model specialized for each specific scenario, enhancing the system’s capacity to handle more complex environments.
คณะศิลปศาสตร์
This innovation reduces costs and enhances queue management efficiency in restaurants, ensuring an organized system, minimizing wait times, and improving customer handling.
คณะวิศวกรรมศาสตร์
This project aims to develop a conceptual prototype of a weapon aiming system that simulates an anti-aircraft gun. Utilizing an optical camera, the system detects moving objects and calculates their trajectories in real time. The results are then used to control a motorized laser pointer with two degrees of freedom (DoF) of rotation, enabling it to aim at the predicted position of the target. Our system is built on the Raspberry Pi platform, employing machine vision software. The object motion tracking functionality was developed using the OpenCV library, based on color detection algorithms. Experimental results indicate that the system successfully detects the movement of a tennis ball at a rate of 30 frames per second (fps). The current phase involves designing and integratively testing the mechanical system for precise laser pointer position control. This project exemplifies the integration of knowledge in electronics (computer programming) and mechanical engineering (motor control).