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.
ในยุคที่การรักษาความปลอดภัยทางไซเบอร์มีการพัฒนาอย่างรวดเร็ว องค์กรต่างๆต้องเผชิญกับความท้าทายมากมายในการระบุและลดความเสี่ยงจากช่องโหว่ต่างๆ ภัยคุกคามทางไซเบอร์ที่มีความซับซ้อนเพิ่มขึ้นทำให้จำเป็นต้องมีเครื่องมือที่มีประสิทธิภาพและประสิทธิผลเพื่อช่วยให้นักทดสอบเจาะระบบสามารถประเมินช่องโหว่และผลกระทบที่อาจเกิดขึ้นได้ วิธีการปัจจุบันมักเกี่ยวข้องกับการค้นหาด้วยตนเองผ่านฐานข้อมูลขนาดใหญ่ ซึ่งอาจใช้เวลานานและมีโอกาสเกิดข้อผิดพลาดจากมนุษย์ แชทบอทที่ใช้ปัญญาประดิษฐ์สามารถทำให้กระบวนการนี้มีประสิทธิภาพมากขึ้น โดยให้ข้อมูลที่รวดเร็วและแม่นยำเกี่ยวกับช่องโหว่เฉพาะ รวมถึงคำอธิบาย คะแนน CVSS และระดับความรุนแรง
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.
คณะวิศวกรรมศาสตร์
Nowadays, consumers may have experienced situations where they don't know which product to use based on their skin problems, the product they use doesn't give the desired results, the product is not worth the price, allergic to certain chemicals in the product ,or use multiple products and have ingredients that should not be used together leading to irritation. For this reason, we develop an application to analyze skin care product ingredients to solve such problems. This allows consumers to correctly understand information about the ingredients in products and know which products they should use according to their skin problems without having to rely on chemical knowledge and get products that are the best value for money. The project has integrated software knowledge to develop an application for analyzing skin care product ingredients. To find and recommend suitable skin care products to consumers. The information on various important ingredients has been collected from reliable articles and research.
คณะบริหารธุรกิจ
In a world increasingly focused on sustainability and reducing environmental impact, DreamHigh is pioneering an innovative approach to packaging solutions using mycelium—a natural, biodegradable, and renewable material derived from fungi. Our mission is to revolutionize the packaging industry by offering eco-friendly alternatives that not only reduce waste but also align with global efforts to combat climate change. Mycelium packaging offers a compelling alternative to traditional plastic and Styrofoam packaging, which contribute significantly to environmental pollution. It is fully biodegradable, compostable, and capable of breaking down in natural environments within weeks, leaving no toxic residues behind. Additionally, mycelium-based products are lightweight, durable, and customizable, making them suitable for a wide range of applications, from consumer goods packaging to protective shipping materials. DreamHigh’s business plan outlines a scalable production process leveraging advanced mycelium cultivation techniques and partnerships with local agricultural sectors to utilize agricultural waste as a key raw material. This not only ensures cost-efficiency but also supports a circular economy by repurposing waste that would otherwise be discarded.