美麗手工翻譯成英語怎麼說

Ⅰ 翻譯成英文，要純手工

It's my honor to work for such an excellent company.

Ⅱ 手工皮藝翻譯成英語

RYZ手工皮藝坊
RYZ handcrafted leather Art Square
RYZ手工皮藝工作室
RYZ handmade leather arts studio

Ⅲ 英文翻譯 要純手工的

秋天的風一陣陣地吹來過自, The autumn wind blows
想起了去年的這個時候, And I thought of the same time last year
你的心到底在想些什麼, What was your heart thinking
對你的思念是一天又一天, I miss you day after day
孤單的我還是沒有改變, The lonely me has not changed
美麗的夢何時才能出現, When will the beautiful dream appear
看不穿是你美麗的眼神 Can't see through your beautiful eyes
猜不透是你迷人的微笑 Can't fathom your alluring smile
一陣風，一場夢，愛如生命般莫測 The blow of wind, a dream, love is as unpredictable as life.

Ⅳ 英語翻譯 手工

這篇文章的風格我喜歡，來給你翻一下吧（我翻譯都是意譯的，並不是字句完全一對一的，你要看的話要理解再看）

快要到聖誕節了!這是我在一所新的學校的第一學期，相比我之前教過的任何集體，我更愛我的這個特殊的小班級。它們那麼的渴望知識，而我也很享受教育他們。
其他老師已經告訴我說我們的孩子都是來自貧困家庭，所以不能期待他們會帶來聖誕禮物。實際上，我並未期待任何禮物。
想像一下我的驚喜，當我假期到來的前一天每個孩子都送給我一份禮物。首先我收到了一個靦腆的小女孩送的玩具猴子，「他是我的最愛，但是我愛您，所以我想把它送給您，Taylor老師」她這樣對我講，我真的很激動!
接下來是一套聖誕樹的裝飾燈，它們都是從媽媽的櫥櫃中拿來的。
最後，我拿到一個小男孩的禮物要表達我的幸福，被他打斷了，「看，他還是新的，連價格標簽還在!」
當其他孩子笑這個孩子的時候，我停下來說，「如果我們沒有讀過，書中的故事永遠都是新的，這樣的書都是好的。現在讓我們一起分享吧!」我在讀我生命中最精彩的聖誕故事，每個孩子都在靜靜的聽著。
到現在我還在保存著這些聖誕禮物。它們時常讓我想起那群可愛的孩子。

這篇手稿文章應該是來自一位支教的老師，感情很真摯，很喜歡

Ⅳ 能幫我手工翻譯幾句話嗎，翻譯成英語

絕對口語化
i deeply crashed on you once we met. for me you stayed up so late, rose with the lark, stayin' by my side every single day, and sing for me（我覺得這句不要了吧，好奇內怪。）容 i can feet the real you, i knew it shall not be called cold, I can't help myself fallin' in love with you, its just not a thing that i can resist, but, i lied, which it cant be erased and icant, how could i be like dis?

Ⅵ 手工英語翻譯~

這篇更專業了，我盡力翻譯了，希望對你有點幫助。
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To overcome this problem, the Wiener filter has been extended to multiple-bases representations for noise removal. Mihcak and Kozintsev^([1]) approached the signal estimation problem from the perspective of designing the Wiener filter in the wavelet domain. The technology indirectly yields an estimate of the signal subspace that is leveraged into the design of the filter. This paper studies the problem of nonlinear Wiener filtering in reprocing kernel Hilbert spaces via least square support vector regression, The method reflected new perspectives within the framework of kernel methods for denoising problem. Experimental results confirm a significant improvement in image denoising.

Least support squares vector regression is a new universal learning machine proposed by Suykens etal.^([2]) Let x∈R^d, y∈R, R^d represent input space, d is the dimension. By some nonlinear mapping ∅, x is mapping into some a prior chosen Hilbert space spanned by the linear combination of a set of functions.
with ∅(x): R^d→R.
Such that the following regularized risk function J is minimized:
The parameter γ is a positive regularization constant. After elimination of w,e one obtains the solution:
Where Y=[y_1…y_N], ρ_1=[1…1], α=[α_1…α_N] and Ω=K+γ^(-1)I . The resulting least support squares vector regression model for function estimation becomes:
where K(x,x_i)=∅(x) ∅(x_i)(i=1,…,N) is the kernel function and must satisfy the Mercer condition,^([3]) α are Lagrange multipliers and b almost equals the mean of y.

Consider a 2D image consisting of a matrix of M=N×N pixels, the observation image can be regarded as a function in pixel areas y=f(i.j); R^2→R^1, where input (i,j) is 2D vector equals to the row and column indices of that pixel, where output y is the approximated intensity value.^([4]) The Lagrange multipliers α_(i,j) of the observed image pixel y(i,j) can be easily calculated using Eq.(3).
where A=Ω^(-1), B=(I^T Ω^(-1))/(I^T Ω^(-1) I) and O_α is a N×N matrix defined by A(I-IB). Notice that, the Lagrange multipliers α_(i,j) of the observed image pixel y(i,j) is determined by the multiplication of the matrix O_α and the observed image Y. That is, the Lagrange multipliers are influenced by the clean image S and random noise N. As in Eq.(4), the observed image can be reconstructed by a linear combination of kernels with weights equal to the values of Lagrange multipliers and an appropriate support vector regression can concentrate the signal energy into a number of support vectors(SVs) that α_(i,j) is nonzero.

The localization of SVs is particularly appropriate for imaging applications, where it is crucial to preserve fine details like edges and textures. Pixels with positive Lagrange values try to raise the grey levels of themselves and their neighbors, while those with negative Lagrange multipliers will try to rece the grey levels and they appear darker.

Therefore, the Lagrange multipliers effectively weigh the kernel functions to estimate intensity value of image. Furthermore, random noise can be considered as forces that try to make Lagrange multipliers to oscillate above and below the standard value. The noise can be reced by smoothing the value of Lagrange multipliers, whereas sharp edges may be preserved within certain ranges which rely on a suitable kernel function possessing the capability of nonlinear representation.
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翻譯如下
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為了解決這個問題，我們把維納濾波法擴展到多基表述來除噪音。Mihcak和Kozintsev^([1]) ，從在小波域里設計維納濾波器的角度來解決信號估算問題。這種技術間接地給出了一個可以補充到濾波器的設計中的信號子空間的估值。這篇論文研究非線性維納濾波法通過最小二乘支持向量回歸在再生成核希爾伯特空間中的問題，以及在降噪問題核心演算法的構架內新角度下的方法。實驗的結果確認了圖像降噪中的顯著優化。

最小二乘向量回歸是一種由Suykens etal.^([2])提出的新的通用學習機器。讓x∈R^d, y∈R, R^d代表輸入空間，d代表維度。通過一些非線性映射∅ ，x會映射到一些事先選好的由一組函數的線性組合擴展開來的希爾伯特空間。
由∅(x): R^d→R.
於是下面的調整風險函數被最小化：
系數γ是正的調整常數。消去w，e後，解得：
這里Y=[y_1…y_N], ρ_1=[1…1], α=[α_1…α_N] ,Ω=K+γ^(-1)I
得出的用來函數估值的最小二乘向量回歸模型變成了：
這里K(x,x_i)=∅(x) ∅(x_i)(i=1,…,N)成為核函數，而且必須符合Mercer條件^([3])， α是拉格朗日乘數同時b近乎等於y的平均值。

考慮一張由一個N×N像素的矩陣M組成的二維圖像，這張觀測用的圖像可以視作一個像素麵積y=f(i.j); R^2→R^1的函數，這里的輸入(i,j)是等於那個像素排和列的針數的二維向量，輸出y是近似的發光量值。^([4]) 觀測圖像像素y(i,j)的拉格朗日乘數α_(i,j)可以用等式(3)輕松計算得到。
這里A=Ω^(-1), B=(I^T Ω^(-1))/(I^T Ω^(-1) I) ，而 O_α即是用A(I-IB)定義的N×N矩陣。
注意到，
觀測圖像像素y(i,j)的拉格朗日乘數α_(i,j)是由矩陣O_α和觀測像Y的乘積決定的。也就是說，拉格朗日乘數是會被清晰圖像S和隨機噪音N共同影響。如等式4所示，觀測像可以通過權值等於這些拉格朗日乘數值的核函數的線性組合來重建，同時一個合適的支持向量回歸可以把信號能量集中到一些α_(i,j)為非零值的支持向量中去（SVs）。

支持向量本地化對成像應用特別合適，這對保護圖像邊緣和圖像紋理十分重要。有正的拉格朗日乘數值的像素試著去提升自己和自己周圍的灰階，而同時有負的拉格朗日乘數的像素會試著減少灰階，他們看起來會更暗。

因此，拉格朗日乘數能有效地給核函數加權來估算圖像亮度值。另外，隨機噪音能夠被視作是試著使拉格朗日乘數在其標准值上下震盪的外力。噪音可以通過平滑化拉格朗日乘數來減少，然而銳邊可能要靠一個合適的有非線性表述能力的核函數在一定的范圍內進行保邊。
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以上

Ⅶ 求手工翻譯成英文

降低IT運營成本。減少數據丟失風險。
To cut down IT operating cost. To rece the risk of data loss.

1，SAP常見問題原因分回析。
2，如何正確答使用********
1. Cause analysis of FAQs on SAP.
2. The correct application of...

Ⅷ 求手工英文翻譯

Abstract

The effective teachers' class questioning is an important part of the claa revolution, and it is also a good way to improve teachers' skills and develop students' new thinking styles. Effective class questioning builds a bridge between teachers and students, makes the class more active, however, there are still some wrong understanding of class questioning, only when we get out of the wrong understanding, can we make the class questiong more useful. So, authour include these strategies according the following five points: confirming the goal; enriching the contents; optimizing the questioning methods, keeping effective feedback, and the teacher's reflection. We are trying our best to learning about these strategies to increase the efficiency of class questioning, and make it better to serve for the ecation

Key words :effective questionging: get out of the wrong understanding ;questioning strategies

人工翻譯，望採納~如有不懂，請追問

Ⅸ 手工翻譯英文

Just as we expected, when the jeans were tested again, they were announced to be qualified, so we don't worry about it. I will send you the test report tomorrow moring.

Ⅹ "做手工「用英語怎麼說

「做手工」：makehandwork

handwork 英['hændwɜ:k] 美['hændˌwɜ:k]
n. 手工（尤指相對於機械）; 手工活;

[例句]Print is the combination of drawing and handwork.
版畫是圖畫和手工的結合物。