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Pocket Rough Guide Lisbon (Travel Guide with Free Ebook)

為了解決定點的問題，作者Guides, Rough 這樣論述：

Discover the best of Lisbon with this compact, practical, entertaining Pocket Rough Guide with a free eBook. This slim, trim treasure trove of trustworthy travel information is ideal for travellers on short trips, and covers all the key sights such as Castelo de Sao Jorge, Mosteiro dos Jerónimos,

Praça do Comércio, restaurants, shops, cafes and bars, plus inspired ideas for day-trips, with honest independent recommendations from expert authors. The Pocket Rough Guide to LISBON covers: The Baixa and Rossio; The Sé, Castelo and Alfama; Chiado and Cais do Sodré; Bairro Alto and Sao Bento; Est

rela, Lapa and Santos; Alcantara and the docks; Belém and Ajuda; Avenida, Parque Eduardo VII and the Gulbenkian; Parque das Naçoes; Sintra; The Lisbon coast Inside this travel guide you will find: RECOMMENDATIONS FOR EVERY TYPE OF TRAVELLER Experiences selected for every kind of trip to Lisbon, from

off-the-beaten-track adventures in Sintra to family activities in child-friendly places, like Cascais or chilled-out breaks in popular tourist areas, like Alfama. INCISIVE AREA-BY-AREA OVERVIEWSCovering Museu Calouste Gulbenkian, Mercado da Ribeira, Torre de Belemand more, the practical Places sect

ion provides all you need to know about must-see sights and the best places to eat, drink, sleep and shop. TIME-SAVING ITINERARIESThe routes suggested by Rough Guides’ expert writers cover top attractions like Castelo de Sao Jorge and Mosteiro dos Jerónimos, and hidden gems like Museu do Fado and th

e Berardo Collection. DAY-TRIPSVenture further afield to Estoril or Sintra. This tells you why to go, how to get there, and what to see when you arrive. HONEST INDEPENDENT REVIEWSWritten with Rough Guides’ trademark blend of humour, honesty and expertise, our expert writers will help you make the mo

st of your trip to Lisbon. COMPACT FORMATPacked with pertinent practical information, this is a convenient companion when you’re out and about exploring Praça do Comércio, HANDY PULL-OUT MAPWith every major sight and listing highlighted, the pull-out map makes on-the-ground navigation easy. ATTRACTI

VE USER-FRIENDLY DESIGNFeatures fresh magazine-style layout, inspirational colour photography and colour-coded maps throughout. PRACTICAL TRAVEL TIPSIncludes invaluable background information on how to get to Lisbon, getting around, health guidance, tourist information, festivals and events, plus an

A-Z directory and a handy language section and glossary. FREE EBOOK Free eBook download with every purchase of a printed book to access all the content from your phone or tablet for on-the-road exploration.

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中國大陸普惠性學前教育政策發展之研究:以浙江省寧波市為例

為了解決定點的問題，作者劉海 這樣論述：

本研究旨在探討中國大陸普惠性學前教育政策之發展狀況，分析普惠性學前教育政策發展之背景與相關內容，並以浙江省寧波市為例，探討地方政府回應中央普惠性學前教育政策發展的情形。本研究採用文件分析法、焦點團體座談以及半結構訪談等方法；在文件分析方面，通過文件梳理，分析從政策形成的影響因素說明普惠性學前教育政策的緣起、變革與發展；在焦點團體座談以及半結構訪談部分，以地方教育行政人員、普惠性幼兒園園長、教師以及幼兒家長等17人為訪談對象，針對普惠性學前教育政策執行情形進行分析。本研究所獲致之結論主要有十五點，分述如下:一、基於區域經濟發展水平與學前教育發展基礎，2010年浙江省寧波市入選「強化政府發展學前

教育」的教育改革試點城市，推進學前教育體制改革。二、根據中央政策要求，制訂市級學前教育三年提升行動計劃，下轄各縣（市）區結合自身制訂各區域三年行動計劃，自上而下推進三輪行動計劃。三、《寧波市學前教育促進條例》、《普惠性民辦幼兒園管理辦法》、《學前教育專項資金使用管理辦法》等法規與政策文件，為普惠性學前教育政策發展提供依據。四、對公辦園、民辦園及普惠性民辦園實行分類治理，城市地區通過小區配套幼兒園建設，農村地區通過標準化中心幼兒園建設，擴增普惠性學前教育資源。五、藉由優化財政分配措施，學前教育財政投入聚焦教師待遇保障、民辦園獎補及幼兒經費補助。六、實施教師聘任「雙軌制」、強化教師培訓、公辦園骨幹

教師定點幫扶等措施，加強師資管理並提升師資素質。七、建立「政府督政」「政府督園」「社會督園」等三督導體系，強化學前教育質量督導。八、普惠性學前教育政策實施十年，普惠性學前教育覆蓋率提升明顯，省一級幼兒園數量成長，教師持證率與評定職稱人數等皆有所提升，有引導學前教育品質正向發展之效。九、「入園難」與「入園貴」等問題雖得到緩解，但「入好園難」卻成為逐步凸顯的新問題。十、普惠性學前教育公共服務體系使家長獲得感明顯，對普惠性幼兒園就近易得、收費平價具有較高滿意度，同時對優質學前教育資源的獲得提出更高要求。十一、普惠性學前教育資源雖有增加，公辦學前教育資源總量依舊不足，幼兒園集團化運營帶來優質學前教育資

源「被均衡」的隱憂。十二、城鄉教育投入分配失衡的現象明顯，公辦愈強、民辦愈弱的差距更加顯現，應予正視。十三、民辦幼兒園「轉普」動機不一，享受政策紅利的同時面臨可持續發展困境，普惠性民辦學前教育質量層次不齊。十四、地方政府承辦人員對政策理解與中央發布的內涵有所差異，普惠性學前教育政策呈現推進異化的情形值得關注。十五、普惠性學前教育政策推動未同時訂有完善的師資素質配套機制，師資隊伍的穩定性與質量仍有待提升。最後，根據研究結論提出具體建議，俾供行政單位、幼兒園及未來普惠性學前教育政策發展之參考。

The World Atlas of Art Nouveau Architecture

為了解決定點的問題，作者Bercedo, Ivan/ Mestre, Jorge (EDT) 這樣論述：

The result of years of research, this epic volume shows the global reach of the Art Nouveau idiomModernismo, Jugendstil or Art Nouveau--the different names given to Art Nouveau in different geographical contexts highlight the territorial scope and diversity of the style, but also its common featu

res: it was new, modern, young and groundbreaking. Whether in Austria, Spain, Denmark or Russia, Art Nouveau defined itself as something that opposed tradition and broke with the past.Rejecting a classicizing academic grammar, and reaching deep into the fantastical for inspiration (from the imagined

history of the medieval to the Orientalist exotic), artists and architects such as Victor Horta, Hector Guimard, Viollet-le-Duc, William Morris, Otto Wagner, Samuel Bing and the Goncourt brothers created a new style with a holistic vision, embracing architecture, painting, graphic art, interior des

ign, textiles, ceramics and metalwork. Imaginative form was matched by innovative building techniques. The architects of Art Nouveau were some of the first to experiment with building with iron, glass, pottery and prefabricated concrete; their buildings offer instructive models of industrial develop

ment and collaborative design. Beautifully illustrated and exhaustively researched, The World Atlas of Art Nouveau Architecture brings together a selection of key Art Nouveau buildings in a truly global survey that includes, for the first time, examples of the style outside of Europe. Exemplars of t

he form were chosen through a rigorous selection process involving a panel of expert advisors with specialist input from each world region. A general introduction to the style grounds the selection, and short essays explain how Art Nouveau differed in different cities and countries. The World Atlas

of Art Nouveau Architecture honors one of the world's first truly global modern art movements.

應用深度學習方法探討企業流程異常檢測之研究

為了解決定點的問題，作者柯廷叡 這樣論述：

企業流程是營運核心價值，對企業而言，管理、制度、工作流程、開發等都有相對應的流程表現。流程會留下執行軌跡，也就是所謂工作日誌，傳統日誌分析仰賴逐步定點式檢測，除工作量大外，也只對固定內容報錯進行改進，許多未報錯的錯誤於流程系統中未被注意。本研究將採用深度神經網路(Deep Neural Network)中的遞迴神經網路(Recurrent Neural Networks ,RNN)、適合時間序列資料的長短期記憶(Long Short-Term Memory, LSTM)方式進行建模，建置的模型會根據日誌內容預測接下來會發生的事情，由於本身文字並不能直接拿來訓練，於是在資料前處理的過程中，將使

用Label Encoding的方式將日誌文本轉換為鍵值，而建構的模型可以透過測試時的loss值異常升高來尋找可能異常的流程內容，也可以透過Decode後的實際日誌鍵與真實日誌鍵進行比對，藉此分析是流程異常或是判斷錯誤，作為改善流程的參考依據，模型中以該模型以LSTM模型有較佳的表現。另以VOLVO公司提供於9th International Workshop on Business Process Intelligence 2013的服務流程資料集進行分析，藉此做為驗證，其流程預測最終結果準確率71.57%，也意味可降低傳統逐筆檢查日誌的數量至28.43%，另延伸使用Kaggle上的系統流程

資料集來延伸測試該模型可應用於不同型態資料，並有一定效果預測及檢測異常。