Toll的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列各種有用的問答集和懶人包

Table for One: Stories

為了解決Toll的問題，作者Yun, Ko-Eun 這樣論述：

An office worker who has no one to eat lunch with enrolls in a course that builds confidence about eating alone. A man with a pathological fear of bedbugs offers up his body to save his building from infestation. A time capsule in Seoul is dug up hundreds of years before it was intended to be uneart

hed. A vending machine repairman finds himself trapped in a shrinking motel during a never-ending snowstorm. In these and other indelible short stories, contemporary South Korean author Yun Ko-eun conjures up slightly off-kilter worlds tucked away in the corners of everyday life. Her fiction is burs

ting with images that toe the line between realism and the fantastic. Throughout Table for One, comedy and an element of the surreal are interwoven with the hopelessness and loneliness that pervades the protagonists' decidedly mundane lives. Yun's stories focus on solitary city dwellers, and her ecc

entric, often dreamlike humor highlights their sense of isolation. Mixing quirky and melancholy commentary on densely packed urban life, she calls attention to the toll of rapid industrialization and the displacement of traditional culture. Acquainting the English-speaking audience with one of South

Korea's breakout young writers, Table for One presents a parade of misfortunes that speak to all readers in their unconventional universality. Yun Ko-eun is the award-winning author of three novels and three short story collections. Born in 1980, she lives in Seoul. Lizzie Buehler is a translator

from Korean and an MFA student in literary translation at the University of Iowa.

Toll進入發燒排行的影片

基於語意之輪廓表示法及全連結捲積類神經網路之單晶片多車輛辨識系統

為了解決Toll的問題，作者徐雋航 這樣論述：

鑒於現今智慧車輛發展迅速，前方車輛辨識及車距檢測為先進駕駛輔助系統 (Advanced Driver Assistance Systems, ADAS) 設計中相當重要的一環，此項技術通常藉由攝影鏡頭擷取前方影像，並透過影像辨識技術來判斷前方是否存在車輛、障礙物等等，進而控制車輛減速以保持安全距離。而這些複雜的圖形辨識技術往往需要透過高功耗之大型運算系統來實現，並且，若將傳統電腦安裝於車內常需要克服體積過大、耐震性不佳等缺點。因此，本研究專注於如何將車輛辨識及車距檢測演算法實現於單晶片，以達到高性能、低功耗，以及體積小之目的。為實現前方車輛辨識及車距檢測，本研究透過單一彩色相機模組收集前方影

像資訊，並於單一現場可程式邏輯閘陣列 (Field Programmable Gate Array, FPGA) 晶片中以最精簡之硬體電路實現白平衡 (White Balance)、影像對比度強化技術 (Image Contrast Technique)、物體邊緣檢測、利用基於模糊語意影像描述 (Semantics-based Vague Image Representation, SVIR) 改良之基於語義之輪廓表示法 (Semantic-based Contour Representation, SCR) 特徵表達物體、再透過不同的卷積核 (Convolution Kernel) 重釋SC

R特徵並交由全連接類神經網路(Fully Connected Neural Network, FCN) 進行車輛辨識。最後，以多個邊界框 (Bounding Box) 同時檢測前方多台車輛，達到單頁多目標辨識 (Single Shot MultiBox Detector，SSD) 之功能，而邊界框之座標可以透視法 (Perspective View) 計算前車相對距離。根據本研究之實驗結果，在相機以每秒90張影像攝影速度以及影像解析度在640×480像素的條件下，本研究僅須3.61us即可完成單台車輛辨識，車輛辨識率可達到94%，且車輛與非車輛至少保持38%以上之分離度，有效減少感測錯誤的情況

發生。因此，實現一真正高性能、低功耗以及體積小之前方車輛辨識晶片。

Blood in the Machine: The Origins of the Rebellion Against Big Tech

為了解決Toll的問題，作者Merchant, Brian 這樣論述：

The true story of what happened the first time machines came for human jobs, when an underground network of 19th century rebels, the Luddites, took up arms against the industrialists that were automating their work--and how it explains the power, threat, and toll of big tech today. The most press

ing story in modern tech begins not in Silicon Valley, Seattle, or even Shenzhen. It begins two hundred years ago in rural England, when working men and women rose up en masse rather than starve at the hands of the factory owners who were using machines to erase and degrade their livelihoods. They

organized guerilla raids, smashed those machines, and embarked on full-scale assaults against the wealthy machine owners. They won the support of Lord Byron, inspired Mary Shelley, and enraged the Prince Regent and his bloodthirsty government. Before it was over, much blood would be spilled--of rich

and poor, of the invisible and of the powerful. This all-but-forgotten and deeply misunderstood class struggle nearly brought 19th century England to its knees. We live now in the second machine age, when similar fears that big tech is dominating our lives and machines replacing human labor run hi

gh. We worry that technology imperils millions of jobs, robots are ousting workers from factories, and artificial intelligence will soon remove drivers from cars. How will this all reshape our economy and the way we live? And what can we do about it? The answers lie in the story of our first machin

e age, when mechanization first came to British factories at the beginning of the industrial revolution. Intertwined with a lucid examination of our current age, the story of the Luddites, the working-class insurgency that took up arms against automation (at a time when it was punishable by death to

break a machine), Blood in the Machine reaches through time and space to tell a story about how technology changed our world--and how it’s already changing our future.

化學合成癌症相關之醣硫化骨橋蛋白

為了解決Toll的問題，作者馬梓軒 這樣論述：

This thesis aims to study the structure and function roles of sulfation and O-glycosylation on the peptides derived from a tumor-associated protein, osteopontin (OPN), in order to provide a fundamental knowledge for potential cancer vaccine development. Chapter 2 is dedicated to the method develop

ment of the synthesis for a library of post-transitionally modified tumor-associated osteopontin peptide antigens, using divergent Fmoc-based solid-phase peptide synthesis (Fmoc-SPPS) with a cassette strategy. Of these synthetic peptides, the one with the highest integrin binding efficiency will be

selected as a cancer vaccine candidate. Chapter 3 is devoted to the synthesis of four glyco(sulfo)peptides, each bearing a thrombin cleavable fluorescent tag. For making it easier to synthesis, we performed an on-resin installation of a fluorescent tag: 7-amino-4-aminocoumarylmethyl coumarin (ACC),

on the C-terminal of the peptides. The products were used as substrates for the thrombin assay, and we envisioned that such a library would reveal the roles of sulfation and O-glycosylation to the thrombin-osteopontin interactions for the first time. The preliminary results of these peptides against

thrombin assay confirmed both tyrosine sulfation and O-glycosylation gave detrimental effects on the thrombin amidolytic activity against synthetic osteopontin peptides.