Complex youtube的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到附近那裡買和營業時間的推薦產品

Music Theory Made Simple: Essential Concepts for Budding Composers, Musicians and Music Lovers

為了解決Complex youtube的問題，作者Valia, Adrian 這樣論述：

Adrian Valia is an award-winning multi-instrumentalist, jazz theorist, composer and music instructor who teaches music theory to people of all ages, skills and levels. He uses his Tik Tok and IG channels to share videos that simplify complex concepts for his audience; his work can also be found on Y

outube and Spotify. Adrian lives in London, England.

Complex youtube進入發燒排行的影片

Youtube及Youtube Premium持續使用意圖之研究

為了解決Complex youtube的問題，作者陳靖軒 這樣論述：

電子商務的蓬勃發展衍伸了許多新型商業模式，免費增值模式中的訂閱制為有名的模式之一。許多傳統服務甚至電商及軟體服務中都增加了訂閱制，其中Youtube為本研究所要探討的個案。為了有效瞭解Youtube 免費使用及付費訂閱使用對使用者之間持續使用意圖之影響性，本研究個別開發針對兩種族群使用者之問卷，透過問卷來測量整體體驗之量表以及影響持續使用意圖的程度。本研究採用問卷調查法，透過蒐集免費使用及付費使用對於Youtube 及Youtube Premium使用之整體體驗、使用意圖以及文獻資料，整合過去學者研究的議題為基礎理論進行研究，針對Youtube及Youtube Premium使用者的整體體驗

進行問卷調查，希望能透過本研究了解（1）影響使用者持續使用Youtube平台的關鍵因素（2）Youtube Premium使用者中影響持續使用意圖最重要的因素為何（3）普通使用及訂閱使用者的在意之關鍵因素是否相同，以作為企業及後續研究者的參考。本研究透過網路問卷的方式進行資料搜集，共回收759份問卷，其中728份有效問卷，並採用SmartPLS 3進行資料分析。分析結果發現：普通使用者持續使用意圖會受績效預期、習慣、功能、服務品質等因素影響，其中績效預期影響最大，但享樂動機及干擾性皆不顯著影響;訂閱使用者持續使用意圖會受績效預期、價格價值、習慣、功能、服務品質等因素影響，其中價格價值影響最大，

享樂動機不顯著影響。上述結果可作為與Youtube及Youtube Premium相似背景主題的研究作為參考依據，也提供企業方作為有效的指標，並為Youtube Premium提供了有效的研究論證。

Sinkable: Obsession, the Deep Sea, and the Shipwreck of the Titanic

為了解決Complex youtube的問題，作者Stone, Daniel 這樣論述：

From the national bestselling author of The Food Explorer, a fascinating and rollicking plunge into the story of the world’s most famous shipwreck, the RMS TitanicOn a frigid April night in 1912, the world’s largest--and soon most famous--ocean liner struck an iceberg and slipped beneath the wave

s. She had scarcely disappeared before her new journey began, a seemingly limitless odyssey through the world’s fixation with her every tragic detail. Plans to find and raise the Titanic began almost immediately. Yet seven decades passed before it was found. Why? And of some three million shipwrecks

that litter the ocean floor, why is the world still so fascinated with this one? In Sinkable, Daniel Stone spins a fascinating tale of history, science, and obsession, uncovering the untold story of the Titanic not as a ship but as a shipwreck. He explores generations of eccentrics, like American C

harles Smith, whose 1914 recovery plan using a synchronized armada of ships bearing electromagnets was complex, convincing, and utterly impossible; Jack Grimm, a Texas oil magnate who fruitlessly dropped a fortune to find the wreck after failing to find Noah’s Ark; and the British Doug Woolley, a fo

rmer pantyhose factory worker who has claimed, since the 1960s, to be the true owner of the Titanic wreckage. Along the way, Sinkable takes readers through the two miles of ocean water in which the Titanic sank, showing how the ship broke apart and why, and delves into the odd history of our underst

anding of such depths. Author Daniel Stone studies the landscape of the seabed, which in the Titanic’s day was thought to be as smooth and featureless as a bathtub. He interviews scientists to understand the decades of rust and decomposition that are slowly but surely consuming the ship. (It is expe

cted to disappear entirely within a few decades!) He even journeys over the Atlantic, during a global pandemic, to track down the elusive Doug Woolley. And Stone turns inward, looking at his own dark obsession with both the Titanic and shipwrecks in general, and why he spends hours watching ships si

nk on YouTube. Brimming with humor, curiosity and wit, Sinkable follows in the tradition of Susan Orlean and Bill Bryson, offering up a page-turning work of personal journalism and an immensely entertaining romp through the deep sea and the nature of obsession.

智能影像運輸系統於輔助、維護與監控應用

為了解決Complex youtube的問題，作者呂安豐 這樣論述：

人工智慧的進步以更精密的方式迅速改變了交通系統。智慧交通系統結合行人、道路及車輛相關資訊，以提供更高的安全性、效率和舒適性。智慧交通系統中的每個元素相互牽制並都應被保留及作後續的改善。電腦視覺的最新進展在許多方面豐富了機器感知的能力。因此，本研究旨在提出一種基於智能視覺的方法，以加強智慧交通系統在協助、維護和監控方面的效果。在輔助方面，本研究著重於駕駛睡意偵測系統和交通場景分割，提出基於深度學習的即時駕駛睡意偵測系統，試圖提高極端場景下的睡意檢測品質。在交通場景分割中，利用了邊緣和特徵級別過濾方式，以達到更好的切割效果。此外，本論文提出基於知識轉移的方法來生成一個強大且有效的模型。在維護方面

，本論文提出經改良的道路裂紋檢測方法，著重於裂紋細化和具自動資源映射的高效檢測器。最後，監控方面基於視訊濃縮，能夠生成短、密集且緊湊的視頻。整體而言，上述六項成果在智慧交通系統的進步方面皆具有巨大的潛力，與文獻裏現有方法相比，本論文所提出的方法在各項指標上皆有突出的表現。