ChatGPT、Napkin及Gamma   AI 工具簡介

The DigiNurse Program is an innovative e-learning course designed to enhance digital competence among Master’s-level nursing students, grounded in a theoretical framework and guided by the Digital Competence Assessment Checklist (DCAC). Delivered over eight weeks through self-directed learning, the program comprises four instructional modules: (1) Utilization of Digital Media and Resources, (2) Application of Digital Communication, (3) Cognition in Digital Learning, and (4) Safety in the Digital Environment. Instructional content was developed through a comprehensive literature review and adapted from proven digital competence training across disciplines to suit the context of nursing education.

【成大法律系研究生通識執行方式：「英文寫作能力」專題演講】

111學年度起入學的碩、博士生，未選修「英、美語」法學外文課程者，畢業前必須參加過本演講，未參加實體課程者，得採線上觀看方式並通過此課程課後Q & A，5題答對4題（80分）為通過。

演講者：法律學系教授 許忠信老師

演講日：2023/6/9(五)

參與資格：歡迎本系所有研究生參加

by 法律學系 2023/6/17

This course consists of three aspects: "microcontroller", "drive circuit" and "motor mechanism". It introduces the knowledge related to electromechanical control from the shallower to the deeper, and supplements it with practical exercises. First, review the principles of motor mechanics and explain various Drive control method, and finally apply the microcontroller to actually write the control program to drive and control the motor machinery.

Apart from providing students with a deeper understanding of the theoretical knowledge of computer vision, machine learning and artificial intelligence - depth learning, and analyzing how the principles of depth learning combine with the development of artificial neural networks (ANNs) and computer vision, the functional aspects of this course will be explained by teacher’s more than 20 years of experience in industrial cooperation (face detection, recognition and expression analysis, intelligent video surveillance as a service, automated optical inspection (AOI), intelligent manufacturing, visual-guided robot arm control, and automatic guided vehicle (AGV)). The course will teach the basic computer vision principles and techniques for the relationship between 2D images and 3D objects with augmented reality (AR), including the calibration method of the camera and the reconstruction principle of 3D objects. Then I will teach the basic but practical techniques of computer vision, including the design of real-time detection, tracking and recognition systems. We will bring machine learning connections to the field of deep learning. Based on deep learning technology, I will teach you how to develop better real-time detection, tracking and recognition techniques to solve practical problems in the fields of industry, clinical imaging and AI sports. This course aims to develop students' ability to design and integrate skills in computer vision, machine learning and depth learning. Through practical practice, students' ability to think, program design and solve existing problems can be nurtured. Students' ability and spirit of team work can be nurtured through group work. They can also apply the theoretical foundation to industry, clinical imaging and precision sports analytics.