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A smart child manikin for CPR training

A smart child manikin for CPR training

Abstract

A child manikin for Cardiopulmonary Resuscitation (CPR) training includes the trachea mechanism, neck mechanism, lung mechanism, heart pump mechanism, artificial skin, and sensor system. All components work together to function similar to a real child. It can be used to practice heart pumping and resuscitation. The manikin has been designed and verified by resuscitation experts. It has a system to evaluate the accuracy of the training and display the results on the computer for real-time monitoring.

Objective

ปัจจุบันในท้องตลาดมีหุ่นสำหรับฝึกการกู้ชีพมากมาย แต่หุ่นจำลองเด็กสำหรับฝึกการกู้ชีพยังไม่พบมากนัก นอกจากนี้หุ่นที่มีขายในท้องตลาดยังขาดระบบการประเมินผลการฝึกที่แม่นยำ ไม่มีการรับรองความถูกต้องของผลที่ได้จากการใช้งาน ดังนั้นในงานวิจัยนี้จึงประดิษฐ์หุ่นจำลองเด็กอัจฉริยะสำหรับฝึกการกู้ชีพ โดยหุ่นมีกลไกหลอดลม กลไกคอ กลไกปอด กลไกการปั้มหัวใจ ผิวหนังเทียม และระบบเซนเซอร์ ทั้งหมดทำงานร่วมกันคล้ายเด็กจริง โดยมีระบบผู้เชี่ยวชาญ (Expert System) ทำหน้าที่ประเมินผลการฝึกฝนและแสดงแบบทันทีบนหน้าจอ หุ่นนี้ได้รับการตรวจสอบและยืนยันความถูกต้องจากการใช้งานโดยผู้เชี่ยวชาญด้านการกู้ชีพตัวจริง

Other Innovations

Improving surface water quality via coagulation using Moringa, Roselle, and Tamarind seed extract.

คณะวิทยาศาสตร์

Improving surface water quality via coagulation using Moringa, Roselle, and Tamarind seed extract.

This study aimed to investigate the effectiveness of extracts from moringa seeds, roselle seeds, and tamarind seeds as coagulants to improve water quality in surface water sources. Extracts from these seeds serve as environmentally friendly coagulants and provide alternative options for enhancing surface water quality. The turbidity of surface water sources ranged between 14 and 24 NTU. The coagulation process used the Jar Test method, where the moringa seed, roselle seed, and tamarind seed extracts functioned as both primary coagulants and coagulant aids. In the preparation process, the seeds were finely ground and extracted using a 0.5-M sodium chloride (NaCl) solution. These extracts were then applied as coagulants to reduce turbidity and enhance water quality, with each concentration tested in 300 ml of water. The results indicated that the most effective way to remove turbidity using 2,000 mg/L of moringa seed extract, achieving a turbidity reduction of approximately 73.19% at a cost of 0.0309 baht per 300 ml of water. Followed by Tamarind seed extract, with a concentration of 4,000 mg/L, followed with a turbidity reduction of approximately 56.75% at a cost of 0.0933 baht per 300 ml. Lastly, roselle seed extract at 6,000 mg/L achieved a turbidity reduction of approximately 32.67% at a cost of 0.0567 baht per 300 ml of water.

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VIDEO-BASED EMOTION DETECTION FROM FACIAL EXPRESSIONS  WITH ROBUSTNESS TO PARTIAL OCCLUSION

คณะเทคโนโลยีสารสนเทศ

VIDEO-BASED EMOTION DETECTION FROM FACIAL EXPRESSIONS WITH ROBUSTNESS TO PARTIAL OCCLUSION

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.

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K-link Application

คณะวิศวกรรมศาสตร์

K-link Application

A platform that aims to connect students from all faculties and departments to promote joint activities and develop effective social and collaborative skills, focusing on: Promoting learning and self-development through reviewing lessons and collaborative learning that are relevant to all faculties and departments in the university, creating a space for negotiation and exchange of knowledge, and supporting joint activities to build relationships and cooperation among students.

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