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Chinese Grammar Wiki BOOK: Intermediate

為了解決English Wiki的問題，作者Pasden, John 這樣論述：

The Chinese Grammar Wiki began in 2012 as a modest website with a bold vision: to record all of the grammar structures in the Chinese language, categorize them by difficulty level, explain each one in clear, jargon-free English, and link them all together. Initially the wiki was a resource exclus

ively for the clients of AllSet Learning’s Shanghai-based learning consultancy. But several years later, its popularity among learners had exploded and the Chinese Grammar Wiki has become the #1 online resource for Chinese grammar among independent learners and university students alike.This book is

the second major volume, covering all essential grammar points that an Intermediate (B1) learner needs to master. Together with the Elementary and Upper Intermediate volumes, this series comprises the most complete single resource on Chinese grammar in print.This volume features: 145 Intermediate (

B1) grammar points200+ separate grammar structures1,500+ examples (with pinyin and English translation)Both colloquial and formal examples of usageExtensive interlinking of similar grammar pointsBilingual glossary of grammar termsLearner-centric design

English Wiki進入發燒排行的影片

以肢體回應教學法將英語融入幼兒體能遊戲之行動研究

為了解決English Wiki的問題，作者夏萍 這樣論述：

　　本研究旨在探究如何藉由肢體回應教學法（TPR）將英語融入於幼兒的體能遊戲中，並配合主題教學的脈絡進行統整性的教學，以融入的方式了解TPR在幼兒體能活動可能的策略與運用情形。研究者擬定了三個層次的教學策略，由易至難分別為TPR-1能聆聽英語單詞跟著做動作；TPR-2能聽懂英語單詞進行體能遊戲活動。TPR-3能在活動的遊戲情境中使用英語，三項策略分別實施於動作發想活動與肢體運用活動的體能遊戲中。　　研究實施於南部一所公立幼兒園大班，以行動研究的方式進行為期十週的英語融入體能遊戲。資料蒐集除在研究過程中攝錄教學過程，採取半結構式的方式，訪談協同研究者與諍友，加上研究者於活動後的觀察紀錄與省思札

記，進行資料的分析並擬定修正教學的行動方案。研究發現主要有二，首先在TPR策略實踐部分，TPR-1需搭配適切曲速與幼兒動作發展；TPR-2需配合不同的體能遊戲，在活動設計中進行調整；TPR-3可以比手畫腳的方式融入活動，提升幼兒在發音上的回應。其次在體能活動中融入英語，能藉由發想了解詞意與提升肢體創意思維，同時可提升孩子的基本動作能力。研究者針對課程設計、策略運用、師資培育與未來研究提出建議。

The Nanotechnology Revolution: A Global Bibliographic Perspective

為了解決English Wiki的問題，作者Stirling, Dale A. 這樣論述：

Nanotechnology is changing the world in a very big way, but at the atomic and sub-atomic level. Although the roots of nanotechnology can be traced back to more than a century ago, the last three decades have witnessed an explosion of nano-based technologies and products. This reference work examines

the history, current status, and future directions of nanotechnology through an exhaustive search of the technical and scientific literature. The more than 4000 bibliographic citations it includes are carefully organized into core subject areas, and a geographic and subject index allows readers to

quickly locate documents of interest.Although a sense of the global reach and interest in nanotechnology can be gleaned from the reference sections of countless journal articles, conference papers, and books, this is the only reference work providing an in-depth global perspective that is ready-made

for nanotechnology professionals and those interested in learning more about all things nanotechnology. Despite the abundance of online resources, there is still an urgent need for well-researched, well-presented, concise, and thematically organized reference works. Instead of relying on wiki pages

, citation aggregators, and related websites, the author searched the databases and databanks of scholarly literature search providers such as EBSCO, ProQuest, PUBMED, STN International, and Thomson Reuters. In addition, he used select serials-related databases to account for pertinent documents fro

m countries in which English is not the primary national language (i.e., China Online Journals, e-periodica, J-STAGE, and SciELO Brazil among others). Dale Stirling is a historian who has worked on issues related to natural resource, environmental, and public health for three decades. He has autho

red books, articles, reports, and conference papers in these areas and contributes his expertise as a reviewer to journals and grant applications. He has also served on multiple boards and commissions. He earned a bachelor’s in history from the University of Alaska and a master’s in liberal arts fro

m Alaska Pacific University.

基於注意力機制語言模型之財務風險文章偵測與實體辨識

為了解決English Wiki的問題，作者盧佳妤 這樣論述：

本研究利用注意力機制模型偵測財務文章之風險事件及抽取潛在金融犯罪名單，建構自動化模型以降低人力標記成本及提升預測速度。我們分析不同模型架構及訓練方法之優缺點，並比較傳統神經網路方法與 Transformer Based 模型的差異。模型架構分為兩階段，第一階段判斷目標文章是否包含金融風險事件，而第二階段則在這些文章中抽取高危險的名單。我們提出聯合訓練方法同時訓練兩階段的模型，透過實驗證明可在不損失正確性的情況提升訓練及預測速度，並得以提升模型穩定性。我們亦針對注意力機制模型內部的 Attention Weight 做視覺化分析，顯示模型能在不提供標注的情況自動關注金融風險詞彙。另外我們針對缺

乏風險人名標記的訓練資料之情況，利用以上 Attention Weight 分析設計特殊的規則，達到一定程度的效果提升。最後我們額外在一個 Wikipedia 上的英文資料集做測試，說明此研究結果亦可應用於不同領域及不同語言的任務。