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Best Canadian Poetry 2021

為了解決How to pronounce nat的問題，作者 這樣論述：

Souvankham Thammavongsa is the author of five books: Small Arguments (2003), winner of the ReLit Prize; Found (2007), now a short film; Light (2013), winner of the Trillium Book Award for Poetry; Cluster (2019); and the short story collection How to Pronounce Knife (2020), winner of the Scotiabank G

iller Prize and a New York Times Editors’ Choice. She has been in residence at Yaddo and has presented her work at the Guggenheim Museum in New York.

How to pronounce nat進入發燒排行的影片

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為了解決How to pronounce nat的問題，作者張虹鈺 這樣論述：

This framework paid attention to the effects of repetition message on Planned Behavior Theory. An experiment was conducted in which these effects were examined for a message repetition effect at three levels of message exposure. Repetition effect as a commercial marketing tool had applied much in a

dvertisement and also in social marketing. However, Repetition effects were not only of strong theoretical but related to a number of researches and important practical problems as well. So, have the researchers always succeeded or has the Repetition effect always caused change in attitude, subjecti

ve norm, perceived behavioral control, and behavioral intention? The obtained data demonstrated the results of this conceptual perspective in examining repetitive communicating of message effectiveness issues of both practical and theoretical importance.

The Little Pine Cookbook: Modern Plant-Based Comfort

為了解決How to pronounce nat的問題，作者Moby 這樣論述：

Musician and plant-based ambassador Moby shares his favorite creative and delicious vegan dishesMoby became vegan more than thirty years ago, when few people knew how to pronounce the word. Since then, vegan cuisine has flourished as the fastest-growing and most innovative cuisine on the planet.

As a passionate animal rights advocate and also a food lover, Moby has helped fuel this evolution at his wildly popular restaurants. He is the original owner of the L.A. celebrity hotspot Little Pine, which showcases an elevated menu proving once and for all that vegan food is ＂all grown up＂ and the

most delicious way to be eating today. Now Moby takes readers inside this special corner of Southern California with The Little Pine Cookbook, a collection of 125 recipes inspired by the restaurant’s beloved dishes. Gateway recipes like Panko-Crusted Piccata will wow even the hardest-to-please meat

lovers. And veg-forward small plates like Fried Cauliflower with Kimchi Aioli and go-to pastas like Orecchiette with Braised Leeks, Asparagus & English Peas will become back-pocket staples, no matter your diet. And didn’t you know that desserts are healthier when they are vegan? Indulge in the

simple pleasure of Butterscotch Pudding or the rich decadence of Chocolate Bread Pudding while feeling good about yourself and your contribution to a better planet. Whatever you’re making, the spirit of Little Pine--of community, of sharing, and of giving--is in all these recipes, and they are here

for you to savor every day.

具自回授之比例記憶細胞式非線性網路設計與分析及其在聯想記憶之應用

為了解決How to pronounce nat的問題，作者賴瑞麟 這樣論述：

本論文的主旨在於闡述類比自回授比例記憶細胞式非線性網路架構配合修正之Habbian演算法在聯想記憶應用之分析與設計。本論文由三個主要部分所組成：(1)自回授比例記憶細胞式非線性網路架構應用於類比聯想記憶之分析與設計; (2)具B或(A和B)樣板之SRMCNN於異聯想記憶應用的設計; (3) 18x18 SRMCNN的超大型積體電路設計及大鄰近層細胞式非線性網路泛用機器之概念設計。首先，本論文藉由探討一個被稱為RMCNN之比例記憶可學習細胞式非線性網路的超大型積體電路神經網路之硬體實現設計，並正確地驗正它的功能；接著提出並分析一個自回授比例記憶細胞式非線性網路架構(SRMCNN)配合修正之Ha

bbian演算法。在這比例記憶細胞式非線性網路中，自回授權重值被導入樣板A中。SRMCNN如同聯想記憶般產生絕對權重值，再轉換為比例權重值於A樣板中，網路能夠儲存圖案樣本並辨識具有雜訊之測試圖案。從模擬的結果得知，自回授比例記憶細胞式非線性網路中之樣板權重值經學習及固定時間漏電後，對權重值做比例處理，網路具有增強樣本特徵的學習能力，SRMCNN比RMCNN可儲存與辨識更多之圖案。對於18x18之SRMCNN能成功地學習、儲存及辨識93個具雜訊之圖案，雜訊之均勻分佈準位為0.8或常態分佈變動量為0.3。SRMCNN對較單純或雜訊較低之圖案具有較好之學習及辨識能力；反之，可允許處理之圖案數目會降低

。模擬的結果成功地印證SRMCNN在圖案辨識上有正確地功能及良好地效能。在高整合力及圖案結合效能下，所提出的SRMCNN能用於聯想記憶系統執行影像處理應用。其次，根據自回授比例記憶細胞式非線性網路架構，提出一個使用B或(A和B)樣板於自回授比例記憶之細胞式非線性網路架構；這網路能學習樣本圖案並正確輸出辨識圖案在異聯想記憶的應用上。B樣板中之權重值可以由已知之輸出圖素和對應神經元之五個相臨輸入圖素之乘積並累積所有輸入樣本圖案得到。透過學習得到之權重值分別除以樣板中所有係數之絕對值的和，此比例記憶的效果可增強圖案的特徵，並辨識八個具黑百雜訊之圖案。將A和B樣板同時使用於SRMCNN，在異聯想記憶應

用的行為和功能其模擬結果作展示及分析，成功處理四個經旋轉之圖案；由此觀之，SRMCNN對於變異性較大圖案之學習與辨識能力可以大大改善。最後，針對所提出具B樣板於自回授比例記憶細胞式非線性網路的架構配合修正之Habbian演算法在異聯想記憶應用的電路設計。功能方塊由0.25微米互補式金氧半製程技術設計出超大型積體電路，以HSPICE軟體驗證電路之正確性。實現一位元具B樣板於SRMCNN之超大型積體電路晶片，觀察其比例記憶的功能動作；展示並分析18x18 SRMCNN行為和功能在異聯想記憶應用的模擬結果。因此，SRMCNN具有方便超大型積體電路硬體電路實現的特點，且對圖案學習與辨識的能力有效地改善

。最後提出並描述一個具有大鄰近層數不對稱模版的細胞式非線性網路泛用機器一般架構的概念性設計。經由模擬與實驗的驗證，本論文以雙載子接面電晶體乘除法器發展出自回授比例記憶細胞式非線性網路架構，SRMCNN在各種異聯想記憶應用中被設計於單一晶片上之神經網路系統，極具研究潛力，而大鄰近層細胞非線性網路之設計則簡化了大鄰近層連線的複雜度。在 SRMCNN領域未來仍有繼續研究之議題；將比例記憶整合於聯想記憶功能中用於細胞式非線性網路泛用機器處理及時影像於類比平行影像處理系統是可繼續進行之研究。