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.
การประกันภัยเป็นที่นิยมมากในปัจจุบัน บริษัทประกันจึงจำเป็นที่จะต้องปรับตัวรับมือกับกรมธรรม์ที่มากขึ้นในทุกๆปี ทำให้จะต้องมีระบบในการรองรับและจัดการต่างๆ ซึ่งในหน่วยงานของสินไหมรถยนต์เอง ก็ต้องมีระบบและการจัดการที่มีประสิทธิภาพเช่นกัน และหนึ่งในนั้นคืองานระบบภายในและระบบภายนอกที่เกิดจากความต้องการของสาขาต่างๆของบริษัท และคู่ค้าสัญญาในเครือ ซึ่งทำให้เกิดระบบขึ้นมา ได้แก่ ระบบจัดการและจัดเก็บอะไหล่
คณะเทคโนโลยีการเกษตร
This experiment aimed to study the suitable types of polymers for coating with chlorophyll extract and the quality of cucumber seeds after coating. The experiment was planned using a Completely Randomized Design (CRD) with four replications, consisting of five methods involving seeds coated with different types of polymers: Polyvinylpyrrolidone, Sodium Alginate, Carboxy Methyl Cellulose, and Hydroxypropyl Methylcellulose, each polymer being coated alongside chlorophyll, with uncoated seeds serving as the control method. The coating substance was prepared by extracting chlorophyll from mango leaves, then mixed with each type of polymer at a concentration of 1%, using an 8% concentration of chlorophyll extract. The properties of each coating method, such as pH and viscosity of the coating substance, were examined before coating the cucumber seeds with a rotary disk coater model RRC150 at a coating rate of 1,100 milliliters per 1 kilogram of seeds. Subsequently, the seeds were dried to reach the initial moisture level using a hot air blower, and seed quality was assessed in various aspects, including seed moisture, germination rate under laboratory conditions, germination index, and seed fluorescence under a portable ultraviolet light illuminator, as well as light emission spectrum analysis using a Spectrophotometer. The experiment found that each type of polymer could be used to form a film together with chlorophyll, which had appropriate pH and viscosity for the coating without affecting seed quality and showed fluorescence on the seed surface both under portable ultraviolet light and spectral emission analysis with a Spectrophotometer. Using HPMC as the film-forming agent with chlorophyll was the most suitable method, enhancing seed fluorescence efficiency.
คณะวิศวกรรมศาสตร์
The evaluation of mango yield and consumer behavior reflects an increasing awareness of product origins, with a growing demand for traceability to understand how the produce has been cultivated and managed. This study explores the relationship between mango characteristics and cultivation practices before harvest, using location identification to provide insights into these processes. To achieve this, a model was developed to detect and locate mangoes using 2D images via a Deep Learning approach. The study also investigates techniques to determine the real-world coordinates of mangoes from 2D images. The YOLOv8 model was employed for object detection, integrated with camera calibration and triangulation techniques to estimate the 3D positions of detected mangoes. Experiments involved 125 trials with randomized mango positions and camera placements at varying yaw and pitch angles. Parameters extracted from sequential images were compared to derive the actual 3D positions of the mangoes. The YOLOv8 model demonstrated high performance with prediction metrics of Precision (0.928), Recall (0.901), mAP50 (0.965), mAP50-95 (0.785), and F1-Score (0.914). These results indicate sufficient accuracy for predicting mango positions, with an average positional error of approximately 38 centimeters.
คณะศิลปศาสตร์
"Niyom Thai" represents health-centric footwear adorned with traditional Thai patterns, embodying an innovative approach to sustainable development tailored to the current needs of local communities. These shoes utilize natural materials to mitigate fatigue and integrate safety technologies, including location tracking via a mobile application and heart rate monitoring. This addresses the aspects of convenience and well-being in both daily life and travel