數位學習



相關的標籤: 教材製作

課程 以"數位學習"加標籤: 32

輻射防護教育訓練(研究生專用)

類別: 2024
類別: 2023

【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,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


類別: 2023

Electric motors are a key component in many mechatronic systems to provide necessary driving forces. They are employed in households, industry, transportation, national defense and medical care. There are various types of electric motors, such as induction, DC, permanent magnet and reluctance motors. The development of permanent magnet motors has become increasingly demanding thanks to the well development of electronics technology, magnetic materials and manufacturing capacity. This course focuses on permanent magnet brushless motors, for which the fundamental principles, magnetic circuit analysis and windings design will be explicated systematically. Students will learn the fundamental knowledge in design of such an electric motor.

類別: 2023

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.

類別: 2023

This course introduces semiconductor physics and devices for optoelectronics, including: Structural Properties of Semiconductors Density of States Semiconductor Bandstructure Absorption and Emission Time-independent Perturbation Theory Interband Transitions Electromagnetic Wave Theory and Guided Wave Optics Semiconductor Heterostructures Semiconductor Lasers Photodetectors

類別: 2023

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.

類別: 2023
類別: 2021
類別: 2021
類別: 2021
類別: 2021
類別: 2021
類別: 2021

提供對復元成長營課程有興趣者一套明確且詳盡的課程帶領引導指引,使其對於復元成長營之課程規劃、核心價值和特殊情境的處理能有更深入的理解和應用。課程參與者可搭配帶領者手冊、帶領者訓練課程講義、復元手冊(精障者使用手冊)及《邁步復元路》上下冊,以獲得最完整的學習體驗。以下為課程大綱: 第一堂:復元概念與復元導向服務 第二堂:復元導向服務實務操作I 第三堂:復元導向服務實務操作II 第四堂:復元成長營帶領要點I 第五堂:復元成長營帶領要點II 欲參與本課程: 1. 請先在育才網中註冊帳號,並在「科系」的欄位中填入您的單位名稱 2. 填寫以下表單,課程管理者審核通過後將會寄送選課密碼至您的信箱 https://docs.google.com/forms/d/e/1FAIpQLSdXW5NqqlDUxowyLGTKPWKlMT7PEFjNjuxNxV7Kq57DneVZ3g/viewform

類別: 2022