一、課程說明(Course Desc<x>ription)
<br>The primary ob<x>jective of this course is to impart students with a foundational 
<br>grasp of radiation dosimetry, while also establishing a robust ba<x>se for 
<br>researchers intrigued by domains like medical physics, health physics, nuclear 
<br>energy, or environmental monitoring. The course delves extensively into 
<br>elucidating radiation dose definitions, detailing radiation-material interactions, 
<br>and explicating the correlation between radiation effects and radiation dose. This 
<br>comprehensive course is meticulously crafted to furnish participants with an 
<br>extensive comprehension of radiation dosimetry's principles, methodologies, and 
<br>real-world applications. Irrespective of whether you're an aspiring physicist, a 
<br>healthcare professional, an engineer, or simply driven by curiosity, this course 
<br>will furnish you with the indispensable knowledge and skills to effectively and 
<br>safely assess, measure, and manage radiation exposure.
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<br>本課程的主要目標是為學生建立放射劑量測的基礎知識，同時為對醫學物理學、健康物理學、核能
<br>或環境監測等領域感興趣的研究人員奠定堅實基礎。本課程深入探討輻射劑量定義，詳細介紹放射
<br>線與物質作用，並闡明輻射效應與劑量之間的關聯。這門綜合性課程經過精心設計，旨在為參與者
<br>提供廣泛的放射劑量測原則、方法論和實際應用的理解。這門課適合以下學生：志在成為醫學物理
<br>學家、醫療專業人員、工程師，還是純粹出於好奇心，本課程將提供必要的知識和技能，以有效安
<br>全的方式評估、測量和管理輻射曝露。
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<br>二、指定用書(Textbook)
<br>1. F. H. Attix, Introduction to Radiological Physics and Radiation Dosimetry,
<br>John Wiley & Sons, Inc., 1986.
<br>2. James E. Turner, "Atoms, Radiation and Radiation Protection," 3rd Edition, 
<br>Wiley-VCH, Weinheim, 2007. 
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<br>三、參考書籍(References)
<br>1. Glenn F. Knoll, Radiation Detection and Measurement, Wiley, 2010. 
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<br>四、教學方式(Teaching Method)
<br>1. 授課(Lectures)
<br>2. 討論(Discussion)
<br>3. 專題與簡報(Project & Presentation)
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<br>五、教學進度(Syllabus)
<br>Part I. Introduction
<br>1. Ionizing radiation (Attix Ch.1)
<br>2. Review of Probability Distribution Function and Error Propagation
<br>3. Radioactive decay (Attix Ch.6)
<br>4. Exponential attenuation (Attix Ch.3)
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<br>Part II. Basic Quantities for Dosimetry
<br>1. Quantities for describing the interaction of ionizing radiation with matter 
<br>(Attix Ch.2)
<br>2. Charged-particle and radiation equilibrium (Attix Ch.4)
<br>3. Absorbed dose in radioactive media (Attix Ch.5)
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<br>Part III. Radiation Interaction with Matter
<br>1. Charged-particle interactions in matter (Attix Ch.8)
<br>2. Gamma- and X-ray interactions in matter (Attix Ch.7)
<br>3. Neutron interactions in matter (Attix Ch.16)
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<br>Part IV. Cavity Theory and Dosimeter Fundamentals
<br>1. Cavity theory (Attix Ch.10)
<br>2. Dosimeter fundamentals (Attix Ch.11)
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<br>Special dates:
<br>Mid-exam, Nov. 7, 2023
<br>Final exam, Jan. 9, 2024 
<br>No class/Holiday, Sep. 19, Oct. 10, 2023
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<br>六、成績考核(Evaluation)
<br>1. 作業/參與｜Homework/ Participation, 30%
<br>2. 期中考/期末考｜mid-exam/final exam, 50%
<br>3. 專題 final project with oral presentation, 20%
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<br>七、生成式人工智慧倫理聲明
<br>Conditionally open
<br>Ethics Statement on Generative Artificial Intelligence
<br>Grounded in the principles of transparency and responsibility, this course 
<br>encourages students to leverage AI for collaboration and mutual learning to 
<br>enhance the quality of course outputs. In accordance with the published Guidelines 
<br>for Collaboration, Co-learning, and Cultivation of Artificial Intelligence 
<br>Competencies in University Education, this course adopts the following policy：
<br>Conditionally open
<br>
<br>Students may briefly explain how generative AI was used for topic ideation, 
<br>sentence refinement, or structural reference in the footnotes of the ti<x>tle page 
<br>or 
<br>after the bibliography in their assignments or reports. However, in the "personal 
<br>reflection report" and "group interview assignment" of this course, students are 
<br>not allowed to use generative AI tools for writing assignments. If usage is 
<br>discovered without proper disclosure, instructors, the institution, or relevant 
<br>units have the right to reevaluate the assignment or report or withhold scores. If 
<br>the course materials or learning resources have been derived from generative AI, 
<br>the instructor will also indicate this in the slides or orally. Students enrolled 
<br>in this course agree to the above ethics statement if registering for the class.
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<br>有條件開放
<br>基於透明與負責任的原則，本課程鼓勵學生利用AI進行協作或互學，以提升本門課產出品質。
<br>根據本校公布之「大學教育場域AI協作、共學與素養培養指引」，本門課程採取有條件開放，
<br>說明如下
<br>- 學生可於課堂作業或報告中的「標題頁註腳」或「引用文獻後」簡要說明如何使用生成式
<br>AI進行議題發想、文句潤飾或結構參考等使用方式。然而，在本課程的「個人反思報告」、
<br>「小組採訪作業」中，學生不得使用生成式AI工具撰寫作業。若經查核使用卻無在作業或報
<br>告中標明，教師、學校或相關單位有權重新針對作業或報告重新評分或不予計分。
<br>- 本門課授課教材或學習資料若有引用自生成式AI，教師也將在投影片或口頭標注。
<br>- 修讀本課程之學生於選課時視為同意以上倫理聲明。
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<br>八、可連結之網頁位址
<br>1. 國立清華大學ee class數位學習平台：https://eeclass.nthu.edu.tw/
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