text:
\subsection*{QPAM}
Inspired by channel attention module in \cite{attention}, we propose a QPAM to avoid training and deploying multiple networks. Unlike channel attention module which extracts the attention map from the input feature map, our QP attention module is controlled by the QP value. The overview of the proposed QPAM is illustrated in Figure \ref{QPA}. Given a feature map $\mathbf{F} \in \mathbb{R}^{ H \times W  \times C}$ as input, QPAM sequentially infers a 1D QP attention map $\mathbf{M} \in \mathbb{R}^{ 1 \times 1  \times C}$. The attention process can be summarized as:
\begin{equation}
    \mathbf{F'} = \mathbf{M} \otimes \mathbf{F}
\end{equation}
where $\otimes$ denotes element-wise multiplication. During multiplication, the attention values are broadcast along the channel dimension. $ \mathbf{F'}$ is the refined output.
The process of generating the QP attention map is as follows: Given a QP value $ q \in \Omega = [a, b]$, since $q$ is an integer, we first map $q$ to a vector $\mathbf{v}_{\Omega}(q) \in \mathbb{R}^{ m \times 1}$ by one-hot encoding. $m$ is the length of $|\Omega|$. The QP attention map $\mathbf{M}$ is calculated by:
\begin{equation}
\begin{array}{l}
    \mathbf{M'} = \sigma(U\mathbf{v}_{\Omega}(q)) \\
    \mathbf{M} = \text{reshape}(\mathbf{M'})
\end{array}
\end{equation}
where $U \in  \mathbb{R}^{ C  \times m}$ is a weight matrix and $\sigma(x)=log(1+e^x)$. From the process we can see that the QPAM assigns different weights to each channel of the input feature map according to the QP value, so that the module can capture compression noise levels among different QPs. Meanwhile, the module can also emphasize meaningful features along channel axes through this process.
Moreover, compared with other methods, the proposed QPAM has stronger scalability, which can also be easily applied to other discrete variables, e.g. frame types.

\subsection*{QPALF}
\begin{figure}[t]
\centering
\includegraphics[width=0.8\linewidth]{img/architecturev2-eps-converted-to.pdf}%
\caption{Overview of the architecture of our QPALF network.}
\label{network}
\end{figure}
\begin{figure}[htbp]
\centering
\subfigure{
\begin{minipage}[t]{0.5\linewidth}
\centering
\includegraphics[width=\linewidth]{img/mRFA-eps-converted-to.pdf}
\label{RFA}
\end{minipage}
}%
\subfigure{
\begin{minipage}[t]{0.5\linewidth}
\centering
{\includegraphics[width=\linewidth]{img/RB-eps-converted-to.pdf}%
\label{RB}}
\end{minipage}
}%
\caption{Detail of Residual Block with QPAM and Residual Feature Aggregation Module. \textbf{Left}: (a) Residual Feature Aggregation Block. RB denotes Residual Block. \textbf{Right}: (b) Residual Block with QPAM.}
\end{figure}

\textbf{Architecture}. In figure \ref{network}, we present the overview of the architecture of our QPALF network. This is also one of the popular architecture used by many other methods \cite{RHCNN, RRCNN, DRNLF}, which usually consists of three parts: the head part, the backbone part and the reconstruction part. The head part is responsible for initial feature
extraction with only one convolutional layer followed by an activate function.
Given a compressed input $X$, we can get a shallow feature $F_0$ through this layer:
\begin{equation}
    F_0=\mathcal{F}(X)
\end{equation}
The backbone part is the key component of the network, which is also the most distinct part of various networks. Here it makes up of $D$ cascaded residual feature aggregation modules (RFA). The backbone part receives the feature $F_0$ as input and sends the extracted global feature $F$ to the reconstruction part, which can be formulated as:
\begin{equation}
    F_D= \mathcal{R}_D(F_{D-1})=\mathcal{R}_{D}\left(\mathcal{R}_{D-1}\left(\ldots\left(\mathcal{R}_{1}\left(F_{0}\right)\right) \ldots\right)\right)
\end{equation}
\begin{equation}
    F= F_0 + \mathcal{R}([F_1, \ldots, F_d, \ldots, F_D])
\end{equation}
where $\mathcal{R}_d$ denotes the d-th RFA module function. $F_{d-1}$ is the input feature of the d-th RFA module function and $F_{d}$ is the corresponding output. The output features of the $D$ RFAs are concatenated together. Then we utilize a long skip connection to extract a global feature $F$.
Finally, the global feature $F$ is transformed through the reconstruction part
\begin{equation}
    \hat{Y} = X + \mathcal{H}(F)
\end{equation}
where $\hat{Y}$ is the output and $\mathcal{H}$ is the reconstruction function, which consists of only one convolutional layer. A global residual learning is usually used to ease the training difficulty in the reconstruction part.

Inspired by \cite{RFA}, we propose a RFA module to make a better use of the local residual features. Figure \ref{RFA} illustrates the detail of the RFA, which contains three residual blocks and one convolution layer. The input is extracted by three residual blocks at three different levels. Then the outputs from three residual blocks are concatenated and a $1 \times 1$ convolution is applied at the end of the RFA for channel dimension reduction. As depicted in Figure \ref{RB}, the detail of the residual block is the same as that in \cite{ResNet} except that we employ the proposed QPAM after the first convolution layer.

Considering the complexity of the proposed model, we use 6 RFA modules, that is, $D=6$ here. All of $3 \times 3$ convolutional layers are followed by a parametric rectified linear unit (PReLU) \cite{PRelu} activation, and the filter number of each $3 \times 3$ layer convolutional is 64. The $1 \times 1$ convolutions are applied for channel dimension reduction.

\textbf{Dataset}. For the network training, we build a dataset using DIV2K \cite{NTIRE} which contains 800 high-resolution images. First, we convert these images to YUV 4:2:0 color format and encode them by VTM6.0 \cite{VTM} with all-intra (AI) configuration at four QPs, {22, 27, 32, 37}. The built-in in-loop filters are all enabled when compressed these images. Then the compressed images are divided into two non-overlapping sets of training (700 images), validation (100 images). To further expand the training dataset, we split the reconstructions to small patches of $64\times64$ with stride 16. And we remove the patches whose PSNR are more than 50.0 or less than 20.0. When training QP variable models, four training datasets are mixed in a random order.
\begin{figure}[t]
\centering
\includegraphics[width=0.5\linewidth]{img/cumulative_proportion-eps-converted-to.pdf}
\caption{Cumulative PSNR gain rate distribution of QPALF on valid image dataset.}
\label{culumative}
\end{figure}

\textbf{Loss Function}. Let $X$ be the input and $\theta$ be the set of network parameters to be optimized. Our goal is to learn an end-to-end function $F$ for generating a higher quality reconstruction $\hat{Y} = F(X;\theta)$ that is close to the ground truth $Y$. The loss function is the MSE between $\hat{Y}$ and $Y$:
\begin{equation}
L_{rec}=\frac{1}{N} \sum_{i=1}^{N}{\lVert \hat{Y}^{(i)} - Y^{(i)} \rVert ^2}
\end{equation}
where $N$ is the number of training samples in each batch. In order to train a more robust QP-combined network, we analyse the restoration ability of the network for different QPs. First we train a QPALF network using mixed dataset (the training detail will be presented in the follow). Then we plot the valid image cumulative proportion over the PSNR gain rate for different QPs. And the PSNR gain rate is defined as follows:
\begin{equation}
    R = 1 - \frac{L_{rec}}{L_{init}}
\end{equation}
where $L_{init}$ is the MSE between $X$ and $Y$. From Figure \ref{culumative}, we can find: 1) The network has lower PSNR gain rate overall on dataset with smaller QP, especially at QP=22. Obviously smaller QP means less compression artifacts, and we do not expect the network to pay much attention on data with less compression artifacts. 2) The PSNR gain rate of 80\% of the valid data is less than 10\%, that is, the valid data with low PSNR gain rate accounts for a large proportion. So we expect the network to focus more on data that has low PSNR gain rate. To this end, we propose a focal MSE loss function to fine tune the proposed network, which can be calculated by:
\begin{equation}
        L = \alpha_{q}(1 - R)^\gamma L_{rec} = \alpha_{q} \frac{L^{1+\gamma}_{rec}}{L_{init}} \\
\end{equation}
where $\alpha_q$ is a weighting factor over QP value, and $\gamma$ is focusing parameter. Herein $\alpha_q = 0.1, 0.25, 0.3, 0.35$ for four QPs respectively and $\gamma=1$. Table \ref{focal} shows the coding performances of three networks over test sequences. QPALF-\uppercase\expandafter{\romannumeral1}, QPALF-\uppercase\expandafter{\romannumeral2}, QPALF-\uppercase\expandafter{\romannumeral3} denote QPALF without fine tuning, QPALF fine tuned by MSE and QPALF fine tuned by focal MSE respectively. As we can see, QPALF-\uppercase\expandafter{\romannumeral3} achieves more bit-rate saving than QPALF-\uppercase\expandafter{\romannumeral2}, which demonstrates the effectiveness of focal MSE.
\begin{table}[]
    \centering
    \caption{The coding performance of three QPALF networks}
\begin{tabular}{cccc}
\hline
\multicolumn{ 1}{c}{\multirow{2}{*}{\bf Class}} &     \multicolumn{ 3}{c}{BD-Rate(\%)} \\
\cmidrule{2-4}
\multicolumn{ 1}{c}{{\bf }} & {\bf QPALF-\uppercase\expandafter{\romannumeral1}} & {\bf QPALF-\uppercase\expandafter{\romannumeral2}} & {\bf QPALF-\uppercase\expandafter{\romannumeral3}} \\
\hline
        A1 &      -1.54 &      -1.73 &      -2.02 \\

        A2 &      -1.98 &      -2.18 &      -2.29 \\

         B &      -3.14 &      -3.30 &      -3.32 \\

         C &      -4.49 &      -4.61 &      -4.73 \\

         D &      -5.48 &      -5.60 &      -5.70 \\

         E &      -5.43 &      -5.66 &      -5.84 \\
\hline
   Average &      \bf -3.75 &      \bf -3.91 &     \bf -4.03 \\
\hline
\end{tabular}
    \label{focal}
\end{table}

\textbf{Training Detail}. The widely adopted deep learning framework Pytorch \cite{Pytorch} is utilized to train our models. We use Adam \cite{Adam} optimization to train these models and a batch size of 64. The learning rate discounts 0.5 every 25 epochs. The training takes 100 epochs in total. For QP-separate models, we first train the model for QP=37 and then use it to initialize the parameters of the networks with smaller QP. The initial learning rate is $10^{-4}$ for QP=37 and $10^{-5}$ for other QPs. For QP-combined models, the initial learning rate is $10^{-4}$ and the fine-tune process takes 50 epochs with learning rate $10^{-5}$. All models are trained on NVIDIA Titan X (Pascal) GPUs.

\textbf{Implementation}. We integrate the QPALF into VVC as an additional tool of in-loop filters between DBF and SAO. To get better performance for video coding, a frame level flag is signaled in the bitstream to indicate whether QPALF is enabled for this frame in the decoder. When the reduction of RD cost is greater than 0, the flag will be enabled and the QPALF will be applied for the frame on luma component.
\begin{table}[]
    \centering
    \caption{The BD-Rate of different models on Y channel under AI configuration}
\begin{tabular}{cccccccc}
\hline
\multicolumn{ 1}{c}{\multirow{2}{*}{\bf Class}} & \multicolumn{ 2}{c}{\multirow{2}{*}{\bf Sequence}} &                               \multicolumn{ 5}{c}{BD-Rate(\%)} \\
\cmidrule{4-8}
\multicolumn{ 1}{c}{{\bf }} & \multicolumn{ 2}{c}{{\bf }} &      RHCNN &        DRNLF  &      QPMLF &    QPALF-S &      QPALF \\
\hline
\multicolumn{ 1}{c}{\multirow{3}{*}{A1}} & \multicolumn{ 2}{c}{Tango2} &      -0.62 &      -0.63 &      -0.78 &      -0.62 &      -1.86 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{Campfire} &      -0.82 &      -1.32 &      -0.79 &      -1.42 &      -2.01 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{FoodMarket4} &      -0.74 &      -0.09 &      -0.29 &      -0.89 &      -2.20 \\
\hline
\multicolumn{ 1}{c}{\multirow{3}{*}{A2}} & \multicolumn{ 2}{c}{CatRobot} &      -1.10 &      -2.20 &      -1.97 &      -2.28 &      -3.39 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{DaylightRoad2} &      -0.43 &       0.07 &      -0.17 &       1.02 &      -0.50 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{ParkRunning3} &      -1.01 &      -1.96 &      -1.56 &      -2.04 &      -2.99 \\
\hline
\multicolumn{ 1}{c}{\multirow{5}{*}{B}} & \multicolumn{ 2}{c}{RitualDance} &      -1.88 &      -4.29 &      -4.03 &      -4.85 &      -6.32 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{MarketPlace} &      -1.34 &      -2.33 &      -2.09 &      -2.64 &      -3.58 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{BasketballDrive} &      -0.73 &      -1.63 &      -1.05 &      -1.82 &      -2.84 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{BQTerrace} &      -0.64 &      -1.38 &      -1.02 &      -1.56 &      -2.06 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{Cactus} &      -0.84 &      -2.07 &      -1.71 &      -1.69 &      -1.78 \\
\hline
\multicolumn{ 1}{c}{\multirow{4}{*}{C}} & \multicolumn{ 2}{c}{BasketballDrill} &      -2.29 &      -5.43 &      -4.50 &      -5.76 &      -7.48 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{BQMall} &      -1.93 &      -4.31 &      -3.73 &      -4.58 &      -5.49 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{PartyScene} &      -1.22 &      -3.01 &      -2.57 &      -3.19 &      -3.62 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{RaceHorsesC} &      -0.81 &      -1.75 &      -1.39 &      -1.81 &      -2.31 \\
\hline
\multicolumn{ 1}{c}{\multirow{4}{*}{D}}& \multicolumn{ 2}{c}{BasketballPass} &      -2.10 &      -5.24 &      -4.42 &      -5.67 &      -6.76 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{BlowingBubbles} &      -1.59 &      -3.64 &      -3.19 &      -3.87 &      -4.45 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{BQSquare} &      -1.93 &      -5.12 &      -4.40 &      -5.28 &      -6.20 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{RaceHorses} &      -2.03 &      -4.54 &      -4.21 &      -4.67 &      -5.40 \\
\hline
\multicolumn{ 1}{c}{\multirow{3}{*}{E}} & \multicolumn{ 2}{c}{FourPeople} &      -2.05 &      -4.73 &      -4.08 &      -5.09 &      -6.49 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{Johnny} &      -1.63 &      -3.90 &      -3.17 &      -4.12 &      -5.72 \\

\multicolumn{ 1}{c}{} & \multicolumn{ 2}{c}{KristenAndSara} &      -1.59 &      -3.95 &      -3.31 &      -4.24 &      -5.31 \\
\hline
\multicolumn{ 3}{c}{{\bf Average All}} & {\bf -1.54} & {\bf -2.88} & {\bf -2.47} & {\bf -3.05} & {\bf -4.03} \\
\hline
\end{tabular}
    \label{RD performance}
\end{table}
\Section{3. Experiment} \label{experiment}
\subsection*{Experimental Setting}
In our experiments, all approaches for in-loop filtering are incorporated into the VVC reference software VTM6.0. The Libtorch \cite{Pytorch} library is integrated into VTM 6.0 to perform the in-loop filtering with the different models. Four typical QP values are tested, including 22, 27, 32, 37. We use the AI configuration suggested by VVC common test condition (CTC) \cite{CTC}.
The anchor for all experiments is VTM6.0 with all built-in in-loop filters enabled. The coding efficiency is evaluated on standard video sequences from class A1 to class E recommended by JVET. The BD-Rate \cite{BD-Rate} are referred to measure the coding performance. We only train and apply the models on Y channel, but our approach can be extended to any arbitrary number of channels.
\subsection*{Evaluation on VVC Test Sequences}
\textbf{RD performance}. First, we compare our QPALF with VTM baseline, and two CNN based in-loop filters, RHCNN \cite{RHCNN} and DRNLF \cite{DRNLF}. For a fair comparison, we also train the models using our dataset and integrate the trained model into VTM6.0 between DBF and SAO. The results are displayed in Table \ref{RD performance}. It can be seen obviously, our QPALF further improves the coding efficiency, which obtains 4.03\% bit-rate saving overall for the luma component on all the test sequences. To further verify the efficiency of the proposed model, we also compare our QPALF with QPMLF and QPALF-D. QPALF-D is the QPALF model trained separately on four QPs. QPMLF is the QPALF without QPAM and use the QP map method \cite{CNNLF}. As we can see, compared with QP-separate model QPALF-S, the performance of the QP-combined model QPMLF degrades while our model QPALF achieves even better coding performance. Moreover, the PSNR gain of three models on multiple QPs is also depicted in Figure \ref{curve}. We can observe that our QPAM obtains the highest PSNR gain over all QPs, which also demonstrates the generalization ability and robustness of the proposed method. (Since the models are trained on only four QPs, \{22, 27, 32, 37\}, we first map other QP values to the four QPs.)
\begin{figure}[t]
\centering
\subfigure[FourPeople]{
\begin{minipage}[t]{0.4\linewidth}
\centering
\includegraphics[width=\linewidth]{img/FourPeople_multi_qp-eps-converted-to.pdf}
\end{minipage}
}%
\subfigure[BQMall]{
\begin{minipage}[t]{0.4\linewidth}
\centering
\includegraphics[width=\linewidth]{img/BQMall_multi_qp-eps-converted-to.pdf}
\end{minipage}
}%
\centering
\caption{PSNR gain of three methods on multiple QPs. (a) FourPeople; (b) BQMall. }
\label{curve}
\end{figure}

\textbf{Subjective evaluation}. Figure \ref{Sub1} illustrates the subjective visual quality comparison among all four approaches. It can be observed that the images enhanced by our approach remain less distortion than those by other approaches, e.g., the clearer edge of the basketball net line. In Figure \ref{Sub2}, we display the residual map of three methods over VTM baseline. Compared with RHCNN and DRNLF, our method can restore more image texture details.

\textbf{Complexity}. Table \ref{complexity} shows the average encode/decode complexity increase and parameters of different models on Intel(R) Xeon(R) CPU E5-2697v4 and Titan X (Pascal). All of the neural networks are  conducted  with  GPU  acceleration. The complexity increase is calculated by $\Delta T = (\hat{T} - T) / T$, where $\hat{T}$ is the encode/decode time with integrating the models, $T$ is the original encode/decode time. Our proposed QPALF has less model parameters overall. Compared with QPMLF, our model achieves much better RD performance with little complexity increase.

\begin{figure*}[thbp]
\centering
\subfigure{
\begin{minipage}[t]{0.2\linewidth}
\centering
\includegraphics[width=\linewidth]{img/BasketDrill_ori-eps-converted-to.pdf}
\caption*{\centerline{Ground Truth} \\ \centerline{(PSNR,SSIM)}}
\end{minipage}%
}%
\subfigure{
\begin{minipage}[t]{0.2\linewidth}
\centering
\includegraphics[width=\linewidth]{img/BasketDrill_vtm-eps-converted-to.pdf}
\caption*{\centerline{VTM} \\ \centerline{(26.16, 0.9045)}}
\end{minipage}%
}%
\subfigure{
\begin{minipage}[t]{0.2\linewidth}
\centering
\includegraphics[width=\linewidth]{img/BasketDrill_rhcnn-eps-converted-to.pdf}
\caption*{\centerline{RHCNN} \\ \centerline{(26.29, 0.9073)}}
\end{minipage}
}%
\subfigure{
\begin{minipage}[t]{0.2\linewidth}
\centering
\includegraphics[width=\linewidth]{img/BasketDrill_drn-eps-converted-to.pdf}
\caption*{\centerline{DRNLF} \\ \centerline{(26.56, 0.9104)}}
\end{minipage}
}%
\subfigure{
\begin{minipage}[t]{0.2\linewidth}
\centering
\includegraphics[width=\linewidth]{img/BasketDrill_aptcnn-eps-converted-to.pdf}
\caption*{\centerline{Ours}\\\centerline{(\textbf{26.66, 0.9120})}}
\end{minipage}
}%

\subfigure{
\begin{minipage}[t]{0.2\linewidth}
\centering
\includegraphics[width=1.2in]{img/RaceHorses_ori-eps-converted-to.pdf}
\caption*{\centerline{Ground Truth} \\ \centerline{(PSNR,SSIM)}}
\end{minipage}%
}%
\subfigure{
\begin{minipage}[t]{0.2\linewidth}
\centering
\includegraphics[width=1.2in]{img/RaceHorses_vtm-eps-converted-to.pdf}
\caption*{\centerline{VTM} \\ \centerline{(28.15, 0.8643)}}
\end{minipage}%
}%
\subfigure{
\begin{minipage}[t]{0.2\linewidth}
\centering
\includegraphics[width=1.2in]{img/RaceHorses_rhcnn-eps-converted-to.pdf}
\caption*{\centerline{RHCNN} \\ \centerline{(28.24, 0.8666)}}
\end{minipage}
}%
\subfigure{
\begin{minipage}[t]{0.2\linewidth}
\centering
\includegraphics[width=1.2in]{img/RaceHorses_drn-eps-converted-to.pdf}
\caption*{\centerline{DRNLF} \\ \centerline{(28.32, 0.8682)}}
\end{minipage}
}%
\subfigure{
\begin{minipage}[t]{0.2\linewidth}
\centering
\includegraphics[width=1.2in]{img/RaceHorses_aptcnn-eps-converted-to.pdf}
\caption*{\centerline{Ours} \\ \centerline{(\textbf{28.42, 0.8714})}}
\end{minipage}
}%
\centering
\caption{Subjective image quality comparison on sequences BasketballDrill (Class D) and RaceHorses (Class C) at QP = 37}
\label{Sub1}
\end{figure*}
\begin{figure*}[thbp]
\centering
\subfigure[VTM]{
\begin{minipage}[t]{0.25\linewidth}
\centering
\includegraphics[width=1.6in]{img/BasketDrill_vtm_y-eps-converted-to.pdf}
\end{minipage}%
}%
\subfigure[RHCNN]{
\begin{minipage}[t]{0.25\linewidth}
\centering
\includegraphics[width=1.6in]{img/BasketDrill_rhcnn_residual-eps-converted-to.pdf}
\end{minipage}
}%
\subfigure[DRNLF]{
\begin{minipage}[t]{0.25\linewidth}
\centering
\includegraphics[width=1.6in]{img/BasketDrill_drn_residual-eps-converted-to.pdf}
\end{minipage}
}%
\subfigure[Ours]{
\begin{minipage}[t]{0.25\linewidth}
\centering
\includegraphics[width=1.6in]{img/BasketDrill_aptcnn_residual-eps-converted-to.pdf}
\end{minipage}
}%
\centering
\caption{Residual map of different methods over VTM baseline.}
\label{Sub2}
\end{figure*}

\begin{table}[hbtp]
    \centering
    \caption{Average complexity increase and parameters of different models}
\begin{tabular}{ccccc}
\hline
    Method &  {\bf $\Delta$ET} &  {\bf $\Delta$DT} & \multicolumn{ 2}{c}{\bf \#Params } \\
\hline
     RHCNN &     5.43\% &    10695.9\% & \multicolumn{ 2}{c}{ $6.79M\times4$ } \\

      DRN &     3.29\% &     7808.0\% & \multicolumn{ 2}{c}{$671.30k \times4$} \\
     QPMLF &     4.41\%  & 8232.2\% & \multicolumn{ 2}{c}{$838.98k \times1$}\\
      QPALF &     4.70\% &    8428.6\% & \multicolumn{ 2}{c}{$905.22k\times1$} \\
\hline
\end{tabular}
    \label{complexity}
\end{table}

\Section{4. Conclusion and Future Work}\label{conclusion}
In this paper, an efficient QP variable CNN based in-loop filter for VVC is proposed. With the proposed QPAM, the QPALF can be adaptive to different QPs while achieving better RD performance. And a focal MSE is introduced to train a more robust model. Experimental results demonstrate that our QPALF can significantly improve the coding efficiency, which outperforms other CNN based methods. Moreover, the proposed QPAM has wide applicability and stronger scalability which can be easily to implement in networks and extend to other types. In our future work, we will extend our model to inter mode and speed up our QPALF.

\paragraph{Acknowledgment}
This work was supported by National Natural Foundation of China under contract No. 61671025

\Section{References}
\bibliographystyle{IEEEbib}

redpajama_set_name: RedPajamaArXiv


text:
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Posted on 3 years ago by Brian(@NE_Brian) in Switch eShop, Videos | 0 comments
The World Next Door, a narrative-driven, action-adventure game, launches on the Switch eShop next Thursday. Have a look at some early footage below.
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Posted on 3 years ago by Brian(@NE_Brian) in News, Switch eShop | 0 comments
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Posted on 4 years ago by Brian(@NE_Brian) in General Nintendo, News | 0 comments
At Anime Boston a few days ago, VIZ Media announced that it will release Dragon Quest Illustrations: 30th Anniversary Edition in the west. Pre-orders have now started to open. You can reserve it on either Amazon or Amazon Canada.
Dragon Quest Illustrations: 30th Anniversary Edition, which is hardcover by the way, features over 500 illustrations from Dragon Quest to Dragon Quest Heroes II. It also comes with a fold-out poster of the series timeline. Over 200 pages are included inside.
More: Amazon, Dragon Quest, pre-order, Viz Media
Dragon Quest Illustrations 30th Anniversary Edition coming west later this year
Dragon Quest Illustrations 30th Anniversary Edition previously released in Japan. At Anime Boston today, VIZ Media announced that the book is seeing localization. It's due out in the west in December.
Dragon Quest Illustrations 30th Anniversary Edition is an archive of Akira Toriyama's iconic illustrations and designs. Over 30 years of Dragon Quest titles, released from 1986 through 2016, are covered inside.
More: Dragon Quest, Viz Media
VIZ Media localizing Splatoon manga, debuts later this year
VIZ Media has announced that it will be localizing the Splatoon manga. It will debut in late 2017.
VIZ passed along the news on Twitter:
Announcement: SPLATOON, the manga series inspired by the hit Nintendo game makes it's debut late 2017! Join the Turf War! pic.twitter.com/kmOGQJaMf7
— VIZ Media (@VIZMedia) April 21, 2017
Originally, the Japanese publication CoroCoro hosted the Splatoon manga, which began in 2015. A new manga based on the franchise will premiere in its June issue.
More: manga, Splatoon, Viz Media
VIZ Media planning Zelda: Twilight Princess / Ocarina of Time special for Free Comic Book Day 2017
We have several months to go until Free Comic Book Day 2017, yet VIZ Media is already confirming its involvement. Moreover, the publisher is planning something special for Zelda fans.
VIZ Media will make a special book available containing excerpts from the manga adaptations of The Legend of Zelda: Twilight Princess and The Legend of Zelda: Ocarina of Time. It will span 32 pages.
Free Comic Book Day 2017 will take place on May 6, 2017. You'll be able to pick up the Zelda special from participating comic book stores.
More: The Legend of Zelda, Viz Media
Zelda: Legendary Edition manga: concrete release dates for the remaining volumes & updated covers
Posted on 6 years ago by Matt(@OnePunchMaz) in General Nintendo, News | 1 Comment
The first volume of VIZ's The Legend of Zelda: Legendary Edition manga series, which covers various Zelda games, has just been released. Now, we have some more concrete US release dates for remaining four issues:
The Legend of Zelda: Legendary Edition, Vol. 2: Oracle of Seasons and Oracle of Ages (January 10th)
The Legend of Zelda: Legendary Edition, Vol. 3: Majora's Mask/A Link to the Past (March 14th)
The Legend of Zelda: Legendary Edition, Vol. 4: The Minish Cap/Phantom Hourglass (May 9th)
The Legend of Zelda: Legendary Edition, Vol. 5: Four Swords (July 11th)
We also have some updated front and back covers for the first two volumes:
Zelda: Legendary Edition volumes – Majora's Mask/Link to the Past in March, Minish Cap/Phantom Hourglass in May
Back when VIZ Media announced the "Legendary Edition" volumes for the various Zelda manga, we heard about two that are arriving over the next few months. Ocarina of Time is up first in November, followed by Oracle of Ages/Seasons in January. We now have news about the two other volumes.
Majora's Mask and A Link to the Past will comprise volume 3, with a release planned for March 2017. The Minish Cap and Phantom Hourglass will then follow in May.
It's also worth mentioning that pre-orders for the third and fourth Legendary Edition volumes are on sale over at Amazon. Majora's Mask/A Link to the Past as well as Minish Cap/Phantom Hourglass are down to about $12.
More: manga, The Legend of Zelda, Viz Media
Zelda: Legendary Edition, Vol. 1 cover and back
Posted on 6 years ago by Brian(@NE_Brian) in General Nintendo, Images | 3 Comments
Amazon has given us a look at the cover for The Legend of Zelda: Legendary Edition, Vol. 1: Ocarina of Time Parts 1 & 2. What we have above is the cover. The second image below shows off the back.
The first Legendary Edition for The Legend of Zelda comes out in November. It includes two volumes of the Zelda manga series, presented in a deluxe format featuring new covers and color art pieces by Akira Himekawa.
More: boxart, The Legend of Zelda, Viz Media
The Legend of Zelda: Twilight Princess manga coming west, first volume in March
The Legend of Zelda: Twilight Princess manga is now confirmed for the west. During a panel at Otakon today, VIZ Media announced that they've licensed it from Himekawa. The first volume will drop in March 2017.
Japan received the first volume of the Twilight Princess manga in June. New issues are still being printed, so the series will be continuing for quite awhile. Eventually, more volumes will likely be released overseas as well.
More: manga, The Legend of Zelda: Twilight Princess, top, Viz Media

redpajama_set_name: RedPajamaCommonCrawl


OKAY I am on vacation. Weather is the best so far. Comapred to what I heard Calgary AB is getting. !! One friend wrote that in one day they had rain, wind, hail and snow and her hubby told her to not email me anymore when he heard our temps !! hahaha She suggested to me that he might be envious. !!
Been here a week. Near St George UT. On the 18th, we are heading west of Las Vegas until the end of the month !! So undoubtedly, will have good weather also - at least I am expecting it !!
When Utah had their winter storm last week, we had 1 day of rain and when we had our temps at 63F, N Utah had a range of 43-53F . Now we are at 81, 83, and N utah is at 63F, 65F etc. Anyway, you can tell we are enjoying this. We shopped the last few days and I got bargains ! Very pleased with my purchases !!
NOW - Today we went to Zion National Park. Very inspiring !! And there I was picking red rock from the pathways that we hiked on and putting them in my bag. Ron, shaking his head, saying, '' You are just like a little chicken - picking at everything you see. !! '' I say, '' I am inspired, I need red rock for my next painting - whose name will be ZION !! '' He shakes his head again - knowing that when I have my mind made up - nothing changes it - so there I continue to pick red rock !! I really wished I had a ziplock bag with me - there was also red sand along the way and had I had my ziplock - I wouldnt have to go home and ''crush '' my red rock to make it into sand !! BUT - OH WELL ! This will work perfectly - I just know it !! Small things inspire and amuse artists into thinking what their next painting will be made of !! I cant wait to produce my new painting named ZION !! Look for it in the coming months !!


text:
Transparent polymer sensor for visual and photometrical detection of thiocyanate in oilfield water
N. A. Gavrilenko, T. N. Volgina, E. V. Urazov, M. A. Gavrilenko
Отделение автоматизации и робототехники
Отделение химической инженерии
A novel colorimetric sensor has been proposed for sensitive and accurate visual and spectrophotometric detection of thiocyanate using polymethacrylate matrix, which also has the potential for use with samples without pretreatment. The determination method is based on shaping of a Fe3+-thiocyanate colored complex into a transparent polymer matrix, followed by measurement of absorbance at 490 nm. The principle of this colorimetric sensor is not ordinary colorimetry, but a new colorimetric strategy that combines solid phase extraction and spectrophotometric determination of thiocyanate following completion of the color change processes. The method ensures determination of 0.8–30.0 mg L−1 of thiocyanate with the detection limit of 0.3 mg L−1. The proposed simple method makes it possible to determine visually in the concentration above 6.0 mg L−1 using a color scale. The test results show that the polymethacrylate matrix can be used for determination of thiocyanate in oilfield water.
Journal of Petroleum Science and Engineering
https://doi.org/10.1016/j.petrol.2018.09.002
10.1016/j.petrol.2018.09.002
Fingerprint Подробные сведения о темах исследования «Transparent polymer sensor for visual and photometrical detection of thiocyanate in oilfield water». Вместе они формируют уникальный семантический отпечаток (fingerprint).
determination method Earth & Environmental Sciences
Colorimetry Engineering & Materials Science
polymer Earth & Environmental Sciences
Polymers Engineering & Materials Science
Color Engineering & Materials Science
sensor Earth & Environmental Sciences
Polymer matrix Engineering & Materials Science
matrix Earth & Environmental Sciences
Gavrilenko, N. A., Volgina, T. N., Urazov, E. V., & Gavrilenko, M. A. (2019). Transparent polymer sensor for visual and photometrical detection of thiocyanate in oilfield water. Journal of Petroleum Science and Engineering, 172, 960-963. https://doi.org/10.1016/j.petrol.2018.09.002
Transparent polymer sensor for visual and photometrical detection of thiocyanate in oilfield water. / Gavrilenko, N. A.; Volgina, T. N.; Urazov, E. V.; Gavrilenko, M. A.
В: Journal of Petroleum Science and Engineering, Том 172, 01.01.2019, стр. 960-963.
Gavrilenko, NA, Volgina, TN, Urazov, EV & Gavrilenko, MA 2019, 'Transparent polymer sensor for visual and photometrical detection of thiocyanate in oilfield water', Journal of Petroleum Science and Engineering, том. 172, стр. 960-963. https://doi.org/10.1016/j.petrol.2018.09.002
Gavrilenko NA, Volgina TN, Urazov EV, Gavrilenko MA. Transparent polymer sensor for visual and photometrical detection of thiocyanate in oilfield water. Journal of Petroleum Science and Engineering. 2019 Янв. 1;172:960-963. https://doi.org/10.1016/j.petrol.2018.09.002
Gavrilenko, N. A. ; Volgina, T. N. ; Urazov, E. V. ; Gavrilenko, M. A. / Transparent polymer sensor for visual and photometrical detection of thiocyanate in oilfield water. В: Journal of Petroleum Science and Engineering. 2019 ; Том 172. стр. 960-963.
@article{bf91c3b408b240d58724061e97bdf006,
title = "Transparent polymer sensor for visual and photometrical detection of thiocyanate in oilfield water",
abstract = "A novel colorimetric sensor has been proposed for sensitive and accurate visual and spectrophotometric detection of thiocyanate using polymethacrylate matrix, which also has the potential for use with samples without pretreatment. The determination method is based on shaping of a Fe3+-thiocyanate colored complex into a transparent polymer matrix, followed by measurement of absorbance at 490 nm. The principle of this colorimetric sensor is not ordinary colorimetry, but a new colorimetric strategy that combines solid phase extraction and spectrophotometric determination of thiocyanate following completion of the color change processes. The method ensures determination of 0.8–30.0 mg L−1 of thiocyanate with the detection limit of 0.3 mg L−1. The proposed simple method makes it possible to determine visually in the concentration above 6.0 mg L−1 using a color scale. The test results show that the polymethacrylate matrix can be used for determination of thiocyanate in oilfield water.",
keywords = "Colorimetric sensor, Oilfield water, Polymethacrylate matrix, Solid phase spectrophotometry, Thiocyanate, Tracer analysis",
author = "Gavrilenko, {N. A.} and Volgina, {T. N.} and Urazov, {E. V.} and Gavrilenko, {M. A.}",
doi = "10.1016/j.petrol.2018.09.002",
journal = "Journal of Petroleum Science and Engineering",
T1 - Transparent polymer sensor for visual and photometrical detection of thiocyanate in oilfield water
AU - Gavrilenko, N. A.
AU - Volgina, T. N.
AU - Urazov, E. V.
AU - Gavrilenko, M. A.
N2 - A novel colorimetric sensor has been proposed for sensitive and accurate visual and spectrophotometric detection of thiocyanate using polymethacrylate matrix, which also has the potential for use with samples without pretreatment. The determination method is based on shaping of a Fe3+-thiocyanate colored complex into a transparent polymer matrix, followed by measurement of absorbance at 490 nm. The principle of this colorimetric sensor is not ordinary colorimetry, but a new colorimetric strategy that combines solid phase extraction and spectrophotometric determination of thiocyanate following completion of the color change processes. The method ensures determination of 0.8–30.0 mg L−1 of thiocyanate with the detection limit of 0.3 mg L−1. The proposed simple method makes it possible to determine visually in the concentration above 6.0 mg L−1 using a color scale. The test results show that the polymethacrylate matrix can be used for determination of thiocyanate in oilfield water.
AB - A novel colorimetric sensor has been proposed for sensitive and accurate visual and spectrophotometric detection of thiocyanate using polymethacrylate matrix, which also has the potential for use with samples without pretreatment. The determination method is based on shaping of a Fe3+-thiocyanate colored complex into a transparent polymer matrix, followed by measurement of absorbance at 490 nm. The principle of this colorimetric sensor is not ordinary colorimetry, but a new colorimetric strategy that combines solid phase extraction and spectrophotometric determination of thiocyanate following completion of the color change processes. The method ensures determination of 0.8–30.0 mg L−1 of thiocyanate with the detection limit of 0.3 mg L−1. The proposed simple method makes it possible to determine visually in the concentration above 6.0 mg L−1 using a color scale. The test results show that the polymethacrylate matrix can be used for determination of thiocyanate in oilfield water.
KW - Colorimetric sensor
KW - Oilfield water
KW - Polymethacrylate matrix
KW - Solid phase spectrophotometry
KW - Thiocyanate
KW - Tracer analysis
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DO - 10.1016/j.petrol.2018.09.002
JO - Journal of Petroleum Science and Engineering
JF - Journal of Petroleum Science and Engineering


These wide opening mens slippers are perfect for a wider fit. Microsuede uppers, memory foam insoles that mould to you feet eliminating painful pressure points and warm lined. Available in two colours and in a G Wide fitting.


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text:
Q: Using intersphinx for internal documentation I would like to use intersphinx for internal documentation to crosslink between various pieces of internal services and internal documentation.
However, they are not on a secure internal network.
Is there a way to point intersphinx to objects.inv that is behind authentication?
Which authentication schemes are supported?

A: I don't know if there's a way to pull objects.inv through authentication, but one alternative solution is to download the objects.inv file(s) you need to a location you can access without authentication, and then specify this local copy of the file(s) in the intersphinx_mapping parameter in conf.py:
intersphinx_mapping = {'keyname', ('uri/to/doc/repo/root', 'uri/to/local/objects.inv')}

While you'd have to re-pull the file periodically to ensure it's up to date, for the time being perhaps it's better than nothing?

redpajama_set_name: RedPajamaStackExchange


description: On Sunday, May 19, from 1:30-3:00pm, join hundreds of Pittsburgh kids for an afternoon of challah-baking, story-telling and Jewish unity.
Open to children from preschool through Grade 5, with a special Bat Mitzvah Club table for girls in grades 6-7.
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Two crooks thought they had swiped a painting worth $4.8 million. But in reality they were the victims of a whole town's epic con.
When a pair of thieves made off with a multimillion-dollar painting this week, they probably thought it was the heist of their careers.
But it turned out they had been fooled into stealing a "worthless" replica.
The bizarre incident occurred earlier this week in the picturesque Italian town of Castelnuovo Magra's Santa Maria Maddalena church.
The church housed a masterpiece by Pieter Brueghel the Younger titled "The Crucifixion", which is estimated to be worth around $A4.8 million, according to The Guardian.
However, a rumour regarding the theft of the piece started to spread, prompting authorities to swap the original with a cheap copy.
The real painting was stored in a secure location, and churchgoers noticed the original, which had been donated to the church by a well-to-do local family more than a century ago, had disappeared.
They were then informed of the situation, and somehow the secret remained safe for a month.
Then, this week, the thieves struck, using a hammer to smash the painting's display case before getting away in a Peugeot.
The town's mayor Daniele Montebello kept up the ruse, telling reporters the crime was "a hard blow for our community", Insider reports.
But on Wednesday, he revealed the truth.
"Rumours were circulating that someone could steal the work, and so the police decided to put it in a safe place, replacing it with a copy and installing some cameras," the publication reported the mayor as saying.
Now police are examining CCTV footage recorded at the scene as well as speaking with witnesses who were near the church when the theft took place.
The renowned 17th century oil painting, which represents the crucifixion of Jesus Christ, is considered to be a "Flemish masterpiece".
During the Second World War it was hidden from the Nazis but then, in 1981, it was stolen, although the robbers were caught within weeks, with the painting safely returned.
Pieter Brueghel the Younger was born in Brussels and was the oldest son of the famous 16th-century painter Pieter Brueghel the Elder.
"The Crucifixion" isn't the only priceless artwork to make headlines recently.
Earlier this month, a painting known as the "Lost Caravaggio" was unveiled in London's Colnaghi gallery after a lengthy restoration.
The work of art by Italian master Michelangelo Merisi da Caravaggio will go under the hammer on June 27 this year and is expected to fetch at least $A240 million.
But it was only discovered five years ago when a Frenchman decided to clear out his attic.
He revealed the painting almost never saw the light of day, as thieves had broken into the farmhouse a few years prior and stolen a number of items.
Luckily, they deemed the painting to be "worthless" and left it behind.


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text:
Women's Euro Teams And Referees 'on The Exact Same Page' Uefa Women's Euro
gmable
She has spent the final 3 seasons playing in England in the Women's Super League, firstly for Everton ahead of moving to Tottenham Hotspur in July 2021. The forward appeared in all eight of Finland's EURO 2022 qualifiers, scoring her only objective in the residence win against Albania in October 2019. Denmark have not suffered successive group stage defeats given that getting beaten by Finland on Matchday 3 in 2005 and Matchday 1 in 2009. And Kirby got the objective her play all through the game deserved, as she latched onto a via ball and Lindahl could only spill her higher work into the net. England continued to threaten and the ultimate icing on the cake was duly delivered on 68 minutes. Arsenal's Stina Blackstenius twice came close to opening the scoring, first miscuing when by means of on target and then striking the bar from six yards with a header.
Even so, Francisco Neto's side know the win that could take them to the quarter-finals is not beyond them. A tiny chaotic in defence but fantastic going forward, Portugal rallied just after going two- down in each of their games so far, and even though Sweden only need to draw to progress, they have yet to make a overall performance to justify their pre-finals billing. The winners of this game will meet England in the 1st semi-final, which requires location in Sheffield on Tuesday 26 July. That victory means the spectre of disappointment is now gone and the tournament can only be classed as a achievement. "The springboard was London 2012, when 70-odd thousand people today crammed into Wembley to watch Group GB's women's team beat the mighty Brazil. It was a moment in time, when we knew the sport was ready to move to the next level.
Nine years later, Barcelona beat Juventus at the Olympiastadion Berlin to win the 2015 UEFA Champions League final. On 30 September 2021, Gavi received a surprise call-up to the senior Spain national team by the manager Luis Enrique. He produced his debut in their UEFA Nations League semi-final win against Italy on six October, becoming the youngest player to ever represent Spain at the senior level. ViniciusVinícius José Paixão de Oliveira Júnior, 22, frequently known as Vinícius Júnior or Vini Jr. is a Brazilian winger at True Madrid and his national group. Deemed 1 of the best players in the planet, he is identified for his dribbling abilities, high pace and shooting.
Oberdorf and Sara Dabritz are two thrilling players who could be essential if they are to progress. Coach Kenny Shiels was forced to apologise soon after he suggested that females were extra most likely to concede ambitions in rapid succession as they're a lot more "emotional" than males. His group backed his apology, nonetheless, and the side appear to have just been focusing on their preparations. A replay of the 2017 quarterfinal that ended Germany's 22-year dominance of the Euros, this is a large game.
Considering that England made its bid to host Euro 2022 four years ago, the landscape in women's football has changed drastically. We believe the UK and the Republic of Ireland can provide UEFA and European football some thing unique in 2028 – a compact and distinctive five-way hosting collaboration that will present a terrific expertise for the teams and the fans. The teams return to competitive action in September with the concluding games of the European Qualifiers for the 2023 FIFA Women's Planet Cup in Australia and New Zealand, which runs from 20 July to 20 August subsequent summer time. 4 of the 11 European locations at the finals have been filled currently, with Denmark, France, Spain and Sweden topping their groups. England have won 18 and drawn two of their last 20 international matches considering that Wiegman took over. Chloe Kelly was the unlikely hero as hosts England won a UEFA Women's EURO for the first time, defeating eight-time champions Germany 2-1 right after extra time in front of a record 87,192 crowd at Wembley.
Having said that, Brazil would have known not to take Serbia lightly, offered that the side who lie 21st in the FIFA rankings are 1 of Europe's most improved teams and topped their qualifying group above Portugal. Jan-Lennard Struff, ranked a lowly 152 in the planet, gave Germany the lead in their quarterfinal with a beautiful 6-three, four-6, 7-6 (7/2) win over 18th-ranked Denis Shapovalov. Fridolina Rolfo, the left back, lofted a correct-foot cross to Ana-Maria Crnogorcevic at the far post. The Swiss forward headed the ball back across the six yard box for the unmarked Geyse to nod in. At the Camp Nou, just after a scoreless initial half, Barcelona overwhelmed Bayern, who had started the round tied in initially place in Group D on two wins.
West Germany hosted the 1988 edition, but this will be the very first time Germany has staged the UEFA European Championship considering the fact that reunification. • Since Pot six only contained 3 teams, these teams have been drawn into the sixth positions in Groups H to J to the first accessible group in alphabetical order. • In Pot 1, the teams were allocated in the order they have been drawn to Groups E to J. And it remains to be seen no matter if the Blues can fend off the competition from fellow money-rich clubs Manchester United and secure his solutions.
Specially figuring out that Spain was going to play with a heavy majority of the possession and has, at times, struggled against bunkered defenses. It wouldn't have created a distinction in the final result had Los Ticos started with five in the back, but Fernandez essentially admitted he produced a tactical mistake when he moved to a after falling behind early. It was always going to take an improbable functionality for Costa Rica to escape a group featuring two recent Planet Cup champions and Japan.
"I would recommend absolutely everyone watches a replay of this game," Germany midfielder Steffen Freund wrote in a column for UEFA on the eve of Euro 2020. Klinsmann opened the scoring from a penalty – won by the rampaging Sammer – on 20 minutes. In a different test of the team's resolve, having said that, the captain was forced off injured just before half-time. Old Trafford, the home of Manchester United, was the venue for Germany's group matches, and soon after an early blow they got off to a superior start out. Without the need of the suspended Klinsmann against the Czech Republic, Germany lost Borussia Dortmund defender Jürgen Kohler right after 14 minutes with what would prove a tournament-ending injury.
The prime two teams in each and every group and the 4-greatest third-spot teams advance to the "knockout rounds." That is 16 teams in a bracket, just like an NCAA March Madness quadrant, and it's win or go home. Google will be ok with either if you are searching, but the trophy will say Euro 2020. Also this isn't the worst time to have an unscheduled tournament, since the entire soccer calendar is getting disrupted by the Planet Cup becoming played in November and December of next year anyway. The kicky footy is back, and this time it's on ESPN and ABC all month lengthy. It's the UEFA Euro 2021 Finals, which is some of the ideal soccer in the world in a month-lengthy festival of superb football featuring some of the greatest players in the planet. The city's hopes of hence hosting any games throughout the tournament rely on Everton obtaining completed their move to the Bramley Moore docks in time.
Morocco and Croatia will face every single other in the very first match, even though later in the day we are treated to Germany's debut against Japan to launch Group E, followed by Spain and Costa Rica in the similar group. The last match of the day will see Belgium against a Canada group producing its return to the Planet Cup for the initial time because 1986. Right here it came following promising bolts to the semifinals at Russia 2018 and to the Euro 2020 final at home in 2021 — but immediately after a dour 2022 that throbbed with a four- loss to Hungary in June that counted as the worst at house in 94 years.
The prior record crowd for a Women's EURO game stood at 43,301 ahead of a ball was kicked in England, that figure dating back to the 2013 final amongst Germany and Norway in Solna, Sweden. It was promptly smashed in the opening game of the 2022 edition as 68,871 fans turned out to watch England edge a 1- win against Austria. FC Köln, Cologne Stadium was reconstructed to stage matches at the 2006 Planet Cup and considering next that 2010 has been the standard venue for Germany's Women's Cup final, as nicely as hosting American football, ice hockey and music concerts. UEFA also extended the suspension of all Russian teams from European competitions to include this summer's Women's Euros and next season's club tournaments.
The 32-year-old scored the opening target in Sweden's final meeting with the Lionesses, that 2-1 victory at the 2019 Globe Cup. Sweden's record in their eight previous Women's EURO semi-final ties is W4 L4. Sweden have reached the EURO semi-finals for the ninth time Germany – who will compete in the final four for the tenth occasion at EURO 2022 – are the only nation to have featured much more.
Most not too long ago, she has commentated on the UEFA Champions League and is at the moment lead play-by-play announcer for Sky Sports' Barclays FA Women's Super League coverage. Mark Ogden is a senior writer with ESPN accountable for breaking and analyzing the greatest stories in soccer. Given that joining ESPN from the Telegraph in 2016, he has covered each marquee occasion in the sport – FIFA World Cup, UEFA European Football Championship, UEFA Champions League, FA Cup – such as the non-league Dover Athletic. Ogden is a recurring contributor to ESPN FC, the day-to-day soccer news and info studio show on ESPN+. The highlight of McNamee's ESPN career was the 2021 Wimbledon Championship. She has appeared on ESPNPlus' Futbol Americas, and has carried out exclusive interviews with several top rated ladies soccer players.
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On 22 May, 12 of London's top chefs will be battling for the coveted 'dish of the night' vote in London's charity fine dining contest Meat vs Fish vs Veg.
Now in its third year, and with an added new 'veg' category, the competition is being held in Flatiron Square in aid of Hospitality Action and is open to everyone to attend. It will be the general public that decides the winner by selecting their favourite dishes on the night.
The 2019 line-up includes: Joo Won (Galvin at Windows), Adam Handling (The Frog Hoxton), Simon Gregory (Bluebird), Lewis de Haas (La Goccia at Petersham Nurseries) and Joshua Hooper (Bistro Union).
Four chefs will be battling it out, showcasing some of the capital's best fine dining vegetarian cuisine. Alyn Williams (Alyn Williams at The Westbury), Jimi Tegerdine (The Gun, London) and Dale Osborne (Bistrot Bagatelle) have all already signed up to the vegetarian contest.
The event is sponsored and organised by luxury hospitality recruiter The Change Group in partnership with Flat Iron Square (London Bridge). The restaurants, chefs involved, organisers and venue all donate their time and ingredients in order to raise as much money as possible for Hospitality Action.
Visit https://meatfishveg.co.uk to book tickets for the event. Tickets cost £25 per person and include a meat, fish and veg dish, as well as a free drink.


text:
Bottle Svc
<< 13 Feb
29 Feb >>
with your host
Jamie Zawinski
23-Feb-2012 (Thu)
Wherein hammers are swingin'!
There has been actual construction work on the second floor of the pizza place! Well, "demolition" work, but that's close enough. Hammers were swung. Massive piles of junk were hauled out.
They've removed the interior walls from the back room. It's a really nice-sized space now! Too bad we're about to shrink it again by carving some bathrooms out of it. Photos:
I don't think I've mentioned what used to be up here before... apparently one of the previous tenants had, how shall I put this delicately, a "hydroponic garden" of some kind. There was a pair of rooms that you could only enter by climbing through a window that were covered, floor, walls and ceiling, with slick white plastic. It was creepy as hell, like a Dexter kill-room but less obsessively tidy:
I also don't think I've mentioned that we're getting a parklet! The location has been approved, and the next step is to get the Planning Department to sign off on our architectural drawings of it.
This is what's on the street now, spanning DNA Lounge and DNA Pizza:
And this is what it's going to turn in to:
The parklet will be about 30' wide, and have tables and a standing-height railing. In addition to that, we're getting rid of two car spots and adding a bunch of bicycle parking.
I wouldn't be foolish enough to make a guess as to when this will be finished, but so far the bureaucracy has been relatively minimal.
You know who has a puzzling internet footprint? Metal bands.
As you might expect, I have a bunch of feeds of searches for mentions of DNA Lounge. Normally this turns up the occasional article or mention of us or a band who is playing here. However, when we have an upcoming show by a metal band, the references go CRAZY. Apparently every metal fan in the world has a blog, and every one of them feels the need to post the entire worldwide tour schedule of every metal band that exists. It feels like the kind of copy-and-paste that you see from adword-farming spam-blogs, but I've looked at a few of them, and it seems not. I guess the metal fans are just obsessive enough that they all consider it front page news that a band they like is playing a show in a city that is six thousand miles away. (Some are reposting articles from other blogs, but mostly they appear to be real blogs.)
So I end up getting half a dozen notifications a day that look like this:
Hails and Horns - PAGANFEST AMERICA Part III to feature four ...
4/12 - Lubbock, TX @ Jake's 4/13 - Denver, CO @ The Marquis 4/15 - Seattle, WA @ Studio Seven 4/16 - Portland, OR @ Hawthorne Theatre 4/17 - San Francisco, CA @ DNA Lounge 4/18 - West Hollywood, CA @ Key Club 4/19 - Tempe ...
Turisas To Headline "Paganfest: America Part III" Tour | Heavy Metal ...
METAL ALLIANCE TOUR Schedule Updated
Apr. 05 - Oakland, CA @ The Pound (city and venue change, show now in San Francisco, CA DNA Lounge) Apr. 06 - Hollywood, CA @ House Of Blues Apr. 07 - Tempe, AZ @ Marquee Theater Apr. 09 - Denver, CO @ The Summit Music ...
SEPULTURA North American Tour: Schedule Updated
04/11/12 DNA Lounge - San Francisco, CA - No DEATH ANGEL 04/12/12 Branx - Portland, OR 04/13/12 Studio Seven - Seattle, WA 04/14/12 In The Venue - Salt Lake City, UT 04/15/12 Gothic Theatre - Englewood, CO 04/16/12 Manny's ...
Se revelan las fechas de tour norteamericano de Sepultura, Death ...
Abr. 11 - DNA Lounge - San Francisco, CA (Sin DEATH ANGEL) Abr. 12 - Branx - Portland, OR Abr. 13 - Studio Seven - Seattle, WA Abr. 14 - In The Venue - Salt Lake City, UT Abr. 15 - Gothic Theatre - Englewood, CO Abr. 16 - Manny's ...
rockcultural: Sepultura e Krisiun anunciam longa tour pela America ...
April 10 - Santa Ana, CA @Yost Theater April 11 - San Francisco, CA @DNA Lounge April 12 - Portland, OR @Branx April 13 - Seattle, WA @Studio Seven April 14 - Salt Lake City, UT @In The Venue April 15 - Denver, CO @Gothic Theater ...
Horns Up Rocks: TURISAS Are Gearing Up For "PaganFest ...
4/13 - Denver, CO @ The Marquis 4/15 - Seattle, WA @ Studio Seven 4/16 - Portland, OR @ Hawthorne Theatre 4/17 - San Francisco, CA @ DNA Lounge 4/18 - West Hollywood, CA @ Key Club 4/19 - Tempe, AZ @ 910 Live Related links: ...
HAVOK To Release EP Late May | Unhallowed Nation Magazine
4/11/2012 DNA Lounge - San Francisco, CA. 4/12/2012 Branx - Portland, OR. 4/13/2012 Studio Seven - Seattle, WA. 4/14/2012 In The Venue - Salt Lake City, UT. 4/15/2012 Gothic Theatre - Englewood, CO. 4/16/2012 Manny's - Billings, MT ...
Fans of other genres don't do this. It's weird.
The other thing about metal bands: they still use Myspace.
As we get repeat visits from bands, DJs and other performers here, I update their URL links on our calendar, and there has been a steady progression of replacing their old Myspace URLs with new Facebook URLs. I don't think I've added a new Myspace URL to the calendar in five years -- except for metal bands, who are all still using Myspace. It's baffling.
I'm not seeking theories to explain this (I'm sure you have them), it's just a little internet-sociological oddity that I've noticed.
So, Free Coffee February is almost over, and has resulted in what can generously be described as a "smattering" of new customers. Not exactly the hockey-stick graph one dreams of.
I had a frustrating conversation the other day with someone whose company has for several years been in the office building on our block that is just past Slim's. Though he's a regular of DNA Lounge, and enjoys our pizza, he was somehow unaware that we were open in the morning, or that we have espresso. I asked him, "Have you even noticed that we have those A-frame signs on the corners hyping coffee?" He said, "Oh, I walk by that every day. I walk by and think, 'Oh, hey, DNA, I like those guys'. I've never actually read it, I guess!"
It was frustrating because here's a guy who is exactly our target market for the morning/lunchtime crowd, and we were completely failing to reach him with our message of, "Hey, we exist". I don't know why, and neither did he.
25 Responses:
Laird Broadfield says:
7 years ago at 10:49pm
Most people are big bundles of habits. See the article referenced by that jwz guy in his post "Go ahead, be evil" for discussion of habit disruption and reformation.
Matty J. says:
Are you saying we should get down-the-block-office-guy pregnant?!?
0x6772 says:
7 years ago at 1:39pm
Lun Esex says:
7 years ago at 12:01am
After high school I had a job at Tower Records (the big one that used to be in Mountain View), and I worked the BASS ticket counter. The worst people to deal with were the ones buying tickets to the Grateful Dead shows. Just one of the many anecdotes about this: You'd get some guy come in, wearing a suit, around noon-1:00pm. He's obviously on his lunch break from working at the kind of job you have to wear a suit to work at in or near Mountain View. "Ah," you'd think, "perhaps he wants some tickets to the symphony, or the opera, or maybe that Cirque du Soleil show that's about to come through." He walks up to the counter and suddenly his eyes glaze over and he gets a blank look on his face. It appears that he has now found it difficult to form complete sentences. He asks for Grateful Dead tickets. Not exactly in so many words. But you've figured it out by his blank stare and slack face as he's suddenly "in the Dead zone," flashing back to the haze of the previous Dead shows he's not just SEEN, but *experienced*.
My point: Perhaps it's something similar to this. Maybe people see "DNA" in big block letters on black and green signs on 11th street and they just automatically think "nightclub," and don't even get to reading the "coffee," "pizza," "morning," or whatever else is on the signs. Or maybe your A-frame signs don't look anything like that and I'm completely wrong. Maybe they DO look more like the signs one might expect a coffee shop/cafe would put up, in cream white and brown, or with what looks like a blackboard surface with rounded hand lettering in multicolored chalk. With 3D perspective white china coffee cups on them, sitting on saucers, filled with dark brown coffee that has light grey steam rising from it.
Jamie Zawinski says:
7 years ago at 1:32am
I enjoy your anecdote, but the next time someone says BUT BUT BUT GREEEEEN I'm going to beat them to death with the Starbucks logo.
Jeremy Wilson says:
It's not "green", it's "black and green industrial/goth club".
205guy says:
Isn't that, like, a different green? Plus they put it on a white background (and white paper cups). With your round logo, you should consider parodying it (and I specifically use the work parody for legal purposes).
I also totally understand the habit thing and either not looking at advertising or not reading it (who knows, maybe it registers and I need adblock glasses). But essentially, I don't want to read advertising online, in the city and in my life--even if it means free coffee (probably a gimmick in there somewhere).
When I commuted to Soma by caltrain, and walked/biked to the office, the only new places I tried for lunch or coffee were those on my direct path. I specifically remember the A-sign sidewalk advert for Earthquake coffee by the Whole Foods where I sometimes shopped at lunch (I guess I did end up reading it), but never went there. And I do hate those sidewalk signs, so much visual noise and so many obstacles in the city already.
The one time I tried a new place was when I found their coupon in our break room (waiting for my in-house coffee to brew). Break rooms are where employees have a bit of time to kill and are the most receptive. Beware however: the sandwhich place said it was an old coupon, didn't honor it, I never went back, and I tossed their coupons in the recyling.
So my suggestion would be: take your message directly to the businesses. Print a bunch of coupons with your name an location map, and knock on doors. Hopefully someone will open, take your coupons, put it in their break room, and people will see them. Or call up those businesses and offer to bring free coffee (in those disposable coffee boxes)--and coupons.
Another factor might be how close the businesses are. Most people won't walk more than 2 or 3 blocks (1 the long way) for coffee since they usually have some in the office too. I don't remember too many offices in that area.
BrianBaresch says:
But but but you've done well associating your logo and colors with "nightclub, music, dancing" and to some extent (so far) with "pizza", but those those cultural phenomena don't already have One Single Look (like the signage Lun Esex describes) closely associated with them. Cognitive psychology is only your friend if you work with it, not against it.
You may believe the artsy A-frame sign is below your dignity, and I sure won't argue. But if you don't adopt it, you probably don't have room to complain that people don't know you serve the hipster elixir. I do think other untried avenues, like 205guy's coupon idea, will bear the fruit you want. Just not as much as that stupid chalkboard sign.
Unfortunately... I have to agree with Mr. SX here: you may have to let go, slightly, of the impeccable aesthetic you've got for the club in order for people to come buy coffee from you.
Have you looked at how places like Blue Bottle (whose location on Mint Sq is a BITCH to find if you've never been there before... unless you come at the popular times, when there's a line around the building) originally got people to pay attention to them? Even if the end is "actually, we're not doing anything wrong", it's worth taking a moment to do some research with the owners of other coffee shops.
tjic says:
> he was somehow unaware that we were open in the morning, or that we have espresso....I've never actually read it, I guess!"
You're coming dangerously close to morally justifying hiring someone to dress up in an ape costume, stand outside your site, and twirl a giant cardboard coffee cup for eight hours every day.
I mean, it might work, right?
Stephen Thorne says:
I would pay to see this made into a performance art piece: to see someone in an ape costume beaten bloody with his own sign would be magic.
node says:
Even better: a too much coffee man constume!
Paging Dr. Monkey, Dr. Bacon Monkey...
aczarnowski says:
Is it just me or do most people really read their receipts? Can you print a splash in the middle of every receipt that says "THIS PLACE WILL MAKE YOUR MORNING BETTER TOO!" Would that implant some knowledge into your existing customers which might filter out into the world?
Jered says:
Were you ever able to determine why the pretentious coffee hipsters won't sell to you? Does it have to do with an association with pizza instead of something more cultured, like crepes, or obscurely flavored donuts, or gourmet bugs, or whatever it is they eat in the Mission these days?
I ask, because our local pretentious vegetarian fast food people went to visit all the major roasters and had the red carpet rolled out, and I can't figure out what the difference is other than type of food: http://www.cloverfoodlab.com/?p=9428
Maybe you need to publicly berate your employees for grinding your coffee wrong, so as to show your commitment to the cause: http://www.cloverfoodlab.com/?p=8973
Todd Meister says:
Regarding metal show reposts - I've noticed this, too. One contributing factor may be the number of people who fly cross country to see particular metal shows (though usually they are one-offs, not whole tours). It could also have to do with the prevalence of meth and coke in metal.
DFB says:
Short radio spots? "DNA Pizza serves coffee [24 hours | and breakfast] next to DNA Lounge, 11th Street by Harrison South of Market." There is only one way to see if it's worth it, but wait until your free coffee promotion is over to be able to estimate the cost/benefit with only one independent variable, of course.
Jon Dowland says:
I stumbled across someone's myspace the other day and was pleasantly surprised, it seems to have *improved* slightly.
Gabriel Rosenkoetter says:
I asked him, "Have you even noticed that we have those A-frame signs on the corners hyping coffee?" He said, "Oh, I walk by that every day. I walk by and think, 'Oh, hey, DNA, I like those guys'. I've never actually read it, I guess!"
is super irritating (the situation, I mean, not the guy, obviously). I wish I had a realistic suggestion. Loudspeakers, maybe?
Um, and unrelatedly: "climing"?
grombits says:
> here's a guy who is exactly our target market
Are you advertising coffee, or are you advertising DNA Lounge/Pizza/Cafe/whatever wherever?
Kyle Williamson says:
Surely you'd want the parklet in front of the pizza place?
Yes, that's the plan.
But how will it affect the view of the pizza place from the Google Streetview car the next time it goes past?? ;)
(At least it'll keep a big truck from being parked there. Not that delivery trucks don't always just double park, anyway.)
Leonardo Herrera says:
Re: Metal bands, they are the new classic rock. Sepultura is somewhat of a religion down here (Chile, Perú, Brazil.)
I bet Frank Zappa would still be using Usenet.
Miki Kadubec says:
re: the metal references online... This is just a sign you need to book more metal bands so you can get more free press! :D (not commenting in self-interest at all, nope, not at all)


text:
WhatsApp forcing users to accept privacy policy, Centre tells HC
Govt says the messaging app wants to ensure the entire database accepts its conditions before Personal Data Protection Bill becomes law in India
5:46 PM, 3 June, 2021
The government says WhatsApp would like to force users to accept the privacy policy by flashing notifications at regular intervals.
Popular messaging app WhatsApp was indulging in anti-user practices by obtaining "trick-consent" for its updated privacy policy, the Centre told the Delhi High Court on Thursday (June 3), saying its objective was to ensure that its entire existing user base is made to accept the terms and conditions before the Personal Data Protection Bill becomes law in India.
The government told the court that WhatsApp has "unleashed its digital prowess" to the "unsuspecting existing users" and would like to force them to accept the privacy policy by flashing such notifications at regular intervals.
"The game plan is very clear — to transfer the entire existing user base committed to updated 2021 privacy policy before the Personal Data Protection (PDP) Bill becomes law," reads the government reply.
Also read: Know why WhatsApp's new privacy policy should worry you
"It is submitted that millions of WhatsApp existing users, those who have not accepted the updated 2021 privacy policy, are being bombarded with notifications on an everyday basis," it said in response to a petition challenging the Facebook-owned messaging app's 2021 privacy policy.
The government sought directions from the court to prevent WhatsApp from sending the notification to the user. It said the messaging app's actions are against "the very grain of prima facie opinion of the Competition Commission of India's order" dated March 24.
The government in March had told the court that the privacy policy violates the 2011 Information Technology rules on five counts and urged it to restrain the messaging app from implementing it pending adjudication of the case.
In its written response to a petition challenging the privacy policy, the Ministry of Electronics & Information Technology had told the court that the policy fails to specify which type of sensitive personal data was being collected.
Also read: CCI sets stage for showdown with WhatsApp over privacy policy update
The replies have been filed in response to a PIL seeking framing of guidelines to protect the privacy and data of users being collected by various social media sites and messaging apps.
The petition has been filed by Noida resident Dr Seema Singh along with Delhi residents Meghan and Vikram Singh. It has argued that the fissures in law with regard to the data are "quite conspicuous", and demanded a framework to regulate the same, The Indian Express reported.
As per WhatsApp, its new terms of service, as well as privacy policy, were go live beyond May 15 this year. If the users want to continue using the app, they will have to accept the company's terms and conditions. If they don't, they will no longer be able to access their WhatsApp accounts from May 15.
The Ministry of Electronics and IT has written to WhatsApp on May 18 on the issue, sources said and warned that necessary steps in accordance with law will be taken if a satisfactory response was not received within seven days.
WhatsApp — which has 53 crore users in India as per government data — had faced severe backlash over user concerns that data was being shared with parent company Facebook.
Competition Commission of India
privacy concerns
Prasanth Saxena
Budget 2023: FM Nirmala Sitharaman dons red s...
Ukraine pushes for Western fighter jets after...


text:
Q: How to handle a `@user.errors` JSON data when the AJAX HTTP request returns an `error`? I am using Ruby on Rails v3.0.9 and jQuery v1.6.1. I would like to handle (by using jQuery) a JSON response data when the AJAX HTTP request returns an error (see the code below for more information) in order to display @user.errors messages. That is, ...
... in the controller I have:
render :json   => @user.errors,
       :status => 400

... in the view file I have:
$jQ.ajax({
  type:     '...',
  url:      '...',
  dataType: 'json',
  data:     '...',
  error:    function(jqXHR, textStatus, errorThrown) {

    // Here is where I would like to handle the above mentioned `@user.errors`
    // array (that is related to the "Ruby on Rails Way" of handling errors).
    //
    // I tried to use 'alert(jqXHR.base);' but the `@user.errors` array is always
    // returned as a string.
    alert(...)

  },
  success:  function(data, textStatus, jqXHR) {
    ...
  }
});

There is a way to change the above code so to use something like the following in order to display errors?
# Supposing that'@user.errors' is '{"base":["already exist"]}'
alert(jqXHR.base);

Note: In few words, I would like to handle data as made when I get a success AJAX HTTP request data (function(data, textStatus, jqXHR)'s permits me to use the JSON parsed data like so: alert(jqXHR.base);).

A: This is pretty simple. You just need to json-decode the answer returned by the server. Simply use http://api.jquery.com/jQuery.parseJSON/ to do that.


If it's free, take it! What do you have to lose? Agree that starting with a basic machine, getting grind and pull right will pay off dividends when you upgrade. That's what I did with my Gaggia Classic before going onto my Rancillio.
Just seen that Sat's book has massively increased in price and is scheduled for September and will cost £75!
The trend for the blob of sauce pulled into a comma shape that seems ubiquetous in every restaurant in the UK right now.
Going tomorrow for my birthday dinner and again with Thom, Bapi and Gary Marshall later in March. Aumbry has blown me away on a good number of occasions. Can't wait.
Mine arrived yesterday from Amazon. It's a fantastic book and can't wait to get started!
Ordered mine. Been waiting for this for years!
Went on Saturday. I really enjoyed it. The atmosphere is great and the service is efficient and friendly. The restaurant itself is stunning and has been fitted out to a very high standard. Did the alc with splitting two main courses into tasting sized plates. The portion sizes even at half portions are extremely generous. There is a lot of skilled cooking going on and I think this place will remain a massive success after the hype dies down. The pricing is right and the wine list is is good value, especially given the Mayfair location. I'll definitely be back.
The duck dish at the Star is one of the best things I've ever been served in a restaurant. Made me a very happy man!
Did the development kitchen on Saturday night. Will do a proper write up when I have more time, but it was an amazing experience. Very different style of eating from the main restaurant, but it was an incredible meal.


text:
Catching Up with the AXS at Strange Weather
We recently caught up with Strange Weather studio, one year after they installed their 32 channel Legacy AXS. The Brooklyn studio had been home to a 1608 console since 2007, with expansions added over the years, but Producer/Engineer and studio owner Marc Alan Goodman was ready for a console upgrade.
"We made hundreds of amazing records on the 1608 for over a decade," said Goodman. "But eventually we found ourselves wanting even more routing options, so we decided to upgrade to the new Legacy AXS."
In the year since Strange Weather has installed the AXS console, the studio has been heavily booked, with Producer/Mixer and Goodman's business partner Daniel Schlett commenting that the console has drawn new engineers, producers and artists to the studio.
Strange Weather recently tracked and mixed albums for Steve Gunn, Kassa Overall and Big Yuki, to name a few. The studio also has a few projects in the pipeline for this summer with Curtis Harding, Sly 5th Ave, and Melanie Charles, among others.
"The console has absolutely improved the workflow of our studio," says Schlett. "The new console's available routing features allow for all types of situations to move more efficiently. In both recording and mixing sessions, we've found the console to work in a number of ways to make all tasks move easily and quickly."
"There are almost too many exciting features to list," Schlett adds. "We love the automated bus matrix section, the built in 2500, all of the available auxes, and, at the end of the day, the reliability and sound!"
Legacy AXS Console
Who's Who at API
One Year Later with Made In Memphis Entertainment
Mark Linett Interview with Sound on Sound
Introducing API's 2019 Scholarship Winners


Sometimes the good and useful websites are not available in English or any language that we know, for example Japanese language. It could be very frustrating if you think that the information could be useful but you can't even understand the article. So, translation tools comes in handy in this kind of situation. Here I found three smart ways and tools to help you translate Japanese to English.
There is several translation engine out there, and by just using one it is not sufficient because it may translate badly. With batch translation tool, you can translate a paragraph with more than one translation engine at the same time. You can compare the translation results and be more clearer on what it actually means.
I found two websites that offer such service, they are: Cross Translation (9 translation services) and 7go.biz which uses 10 different translation services. You just copy and paste in the words or sentences to the field and it will generate the English translations. But please make sure you select "Japan to English" before pasting.
Google Translate is one of my most frequently used translation tool because it is simple and easy to use. Now it is even simple with the 1-click translation service offered by Google. Just go to the Translate Tool page and drag the "Japanese to English" to your browser toolbar shown above, which I'm using the Firefox browser. By now, when surfing Japanese sites and wish to translate, just hit the "Japanese to English" button, and it will do the job for you.
This is very handy tool, when you need to check the words that you don't understand. Just download and install the Quick TransLation add-on tool with Firefox. Now you can just by highlighting the Japanese words you wish to translate and it will popup the translation dialog. Very convenient and quick. Besides that, this tool also capable of translate many other languages too.
Here is the three tools to help you translate Japanese languages. With this tool, it is also very useful to people who want to learn Japanese. Well if you interested in translating Japanese Kanji/Hiragana/Katakana to Romaji, Kanji Converter is the tool to use. I used this site a lot when converting Japanese lyrics to romaji. Not to mention that this site also able to translate Japanese to English too!
Hi! If anyone of you would like to have a proper translation from Japanese to English, I'm providing the translation service. For a text with less than 200 Japanese characters in a page, I'm charging it at MYR20.00 perpage only.
Drop me your message at sitinurulhidayah.yusof@gmail.com. I can provide you a proper quotation. Thx!


text:
package org.apache.titan.kafka;

import com.thinkaurelius.titan.core.*;
import com.thinkaurelius.titan.core.log.*;
import com.thinkaurelius.titan.graphdb.relations.SimpleTitanProperty;
import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig;
import org.apache.tinkerpop.gremlin.structure.Direction;
import org.apache.tinkerpop.gremlin.structure.VertexProperty;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.io.BufferedReader;
import java.io.FileReader;
import java.io.IOException;
import java.time.Instant;
import java.util.*;

import kafka.common.QueueFullException;
import kafka.javaapi.producer.Producer;
import org.json.simple.JSONObject;

/**
 *
 */
public class TitanKafkaProducer
{
    private static Logger LOGGER = LoggerFactory.getLogger(TitanKafkaProducer.class);
    private final String className = "TitanKafkaProducer";
    private static int state = -1;

    private Producer<byte[], byte[]> producer;
    private String topic;

    private String titanConfigLocation = null;
    private String logNameIdentifier = "kafkaproducer";

    private boolean finishRunning = false;

    private TitanGraph graph = null;

    /**
     * Construtor
     *
     * @cfgProps configuration file containing Kafka and zookeeper IPs and ports
     * @topic the Kafka topic name to publish to
     */
    public TitanKafkaProducer(final String cfgProps, final String topic)
    {
        final String methodName = "TitanKafkaProducer.constructor";
        this.topic = topic;
        assert (topic != null);

        // create the producer
        Properties props = new Properties();
        BufferedReader br = null;
        try
        {
            br = new BufferedReader(new FileReader(cfgProps));
            props.load(br);
            titanConfigLocation = props.getProperty("titan.config.location");
            assert (titanConfigLocation != null);
            logNameIdentifier = props.getProperty("titan.log.name");
        }
        catch (IOException ie)
        {
            LOGGER.error(ie.getMessage(), ie);
        }
        finally
        {
            if (br != null) {
                try {
                    br.close();
                }
                catch (IOException ioe) {
                    LOGGER.error(ioe.getMessage(), ioe);
                }
                finally {
                    br = null;
                }
            }
        }

        try
        {
            ProducerConfig config = new ProducerConfig(props);
            producer = new Producer<byte[], byte[]>(config);
            state = 1;
        }
        catch (Exception e)
        {
            System.out.println("failed to create producer");
            // failed
            state = 0;
        }
    }

    /**
     * registers the listener method with Titan transaction logging
     * system
     */
    private void registerListenPublish()
    {
        final String methodName = "registerListenPublish";

        System.out.println("Connecting to Titan");
        graph = TitanFactory.open(titanConfigLocation);
        assert(graph != null);

        System.out.println("registering with the Titan Log Processor framework");
        LogProcessorFramework logProcessor = TitanFactory.openTransactionLog(graph);

        logProcessor.addLogProcessor("kafkaproducer").
                setProcessorIdentifier("kafkaproducerlistener").
                setStartTime(Instant.now()).
                addProcessor(new ChangeProcessor()
                             {
                                 public void process(TitanTransaction tx, TransactionId txId, ChangeState changeState)
                                 {
                                     HashMap transactionMap = new HashMap<String, Object>();

                                     // System.out.println("checkpoint 1");
                                     for (Change kind : Change.values())
                                     {
                                         // System.out.println("checkpoint 2");
                                         if ((kind.compareTo(Change.ADDED) == 0) || (kind.compareTo(Change.REMOVED) == 0))
                                         {
                                             // System.out.println("checkpoint 3");
                                             String txInstance = txId.getInstanceId();
                                             long txInfo = txId.getTransactionId();
                                             Instant txTime = txId.getTransactionTime();

                                             transactionMap.put("txinstance", txInstance);
                                             transactionMap.put("txinfo", txInfo);
                                             transactionMap.put("txtime", txTime);

                                             ArrayList addedVertexList = new ArrayList();
                                             // handle adds and removes for vertices
                                             // edges handled in context of vertices
                                             Set<TitanVertex> vertexSet = changeState.getVertices(kind);
                                             for (TitanVertex v : vertexSet)
                                             {
                                                 HashMap aVertexMap = new HashMap<String, Object>();

                                                 aVertexMap.put("id", v.id());
                                                 aVertexMap.put("label", v.label());

                                                 Iterator vertProps = v.properties();
                                                 while (vertProps.hasNext())
                                                 {
                                                     VertexProperty vp = (VertexProperty) vertProps.next();
                                                     aVertexMap.put(vp.key(), vp.value());
                                                 }

                                                 ArrayList addedEdgeList = new ArrayList();
                                                 Iterable<TitanEdge> aEdgeItr = changeState.getEdges(v, Change.ADDED, Direction.OUT);
                                                 for (Iterator<TitanEdge> anEdge = aEdgeItr.iterator(); anEdge.hasNext(); )
                                                 {
                                                     HashMap anAddedEdge = new HashMap<String, Object>();

                                                     TitanEdge edge = anEdge.next();
                                                     // edge.properties puts out an iterable
                                                     anAddedEdge.put("edgeid", edge.id());
                                                     EdgeLabel el = edge.edgeLabel();
                                                     anAddedEdge.put("edgelabel", el.toString());

                                                     Iterator propsItr = edge.properties();
                                                     while (propsItr.hasNext())
                                                     {
                                                         SimpleTitanProperty ep = (SimpleTitanProperty) propsItr.next();
                                                         anAddedEdge.put(ep.propertyKey(), ep.value());
                                                     }
                                                     addedEdgeList.add(anAddedEdge);
                                                 }
                                                 aVertexMap.put("addededges", addedEdgeList);

                                                 ArrayList removedEdgeList = new ArrayList();
                                                 Iterable<TitanEdge> rEdgeItr = changeState.getEdges(v, Change.REMOVED, Direction.OUT);
                                                 for (Iterator<TitanEdge> anEdge = rEdgeItr.iterator(); anEdge.hasNext(); )
                                                 {
                                                     HashMap aRemovedEdge = new HashMap<String, Object>();
                                                     TitanEdge edge = anEdge.next();

                                                     // edge.properties puts out an interable
                                                     aRemovedEdge.put("edgeid", edge.id());
                                                     aRemovedEdge.put("edgelabel", edge.edgeLabel());

                                                     Iterator propsItr = edge.properties();
                                                     while (propsItr.hasNext())
                                                     {
                                                         SimpleTitanProperty ep = (SimpleTitanProperty) propsItr.next();
                                                         aRemovedEdge.put(ep.propertyKey(), ep.value());
                                                     }
                                                     removedEdgeList.add(aRemovedEdge);
                                                 }
                                                 aVertexMap.put("removedEdges", removedEdgeList);
                                                 addedVertexList.add(aVertexMap);
                                             }

                                             if (kind.compareTo(Change.ADDED) == 0)
                                                 transactionMap.put("added", addedVertexList);

                                             if (kind.compareTo(Change.REMOVED) == 0)
                                                 transactionMap.put("removed", addedVertexList);
                                         }
                                     }

                                     // System.out.println("checkpoint 4");
                                     // convert the hashmap(s) to the JSON string
                                     // we push to Kafka topic
                                     // catching all exceptions for now
                                     try
                                     {
                                         String transmissionString = JSONObject.toJSONString(transactionMap);
                                         System.out.println("published: " + transmissionString);
                                         publish(transmissionString);
                                     } catch (Exception e)
                                     {
                                         e.printStackTrace();
                                     }
                                 }
                             }
                ).build();
    }

    /**
     * Currently, no serialization.  Publishes clear text
     * JSON string
     *
     * @param transmissionString String of JSON to publish
     */
    public void publish ( final String transmissionString)
    {
        final String methodName = "publish";
            try
            {
                if (transmissionString.trim().length() > 0)
                {
                    String pKey = "default";
                    byte[] partitionKey = pKey.getBytes();
                    byte[] msg = transmissionString.getBytes();
                    KeyedMessage<byte[], byte[]> data = new KeyedMessage<byte[], byte[]>(topic, partitionKey, msg);

                    try
                    {
                        producer.send(data);
                    }
                    catch (QueueFullException qfe)
                    {
                        try
                        {
                            // let consumers do their thing
                            // no fancy backoff right now
                            Thread.sleep(10L);
                        }
                        catch (Exception nocare)
                        {
                            nocare.printStackTrace();
                        }
                        // retry this message
                        producer.send(data);
                    }
                }
            }
            catch (Exception e)
            {
                e.printStackTrace();
            }
    }

    /**
     * Nothing sets finishRunning to true.
     * This is how we listen and publish
     * forever on the call back thread,
     * while main thread here waits.
     */
    public synchronized void waitForever()
    {
        final String methodName = "waitForever";

        while (!finishRunning)
        {
            try
            {
                wait();
            }
            catch (InterruptedException e)
            {
                // don't care
            }
        }
    }

    public void closeGraph()
    {
        final String methodName = "closeGraph";

        if (graph != null)
            graph.close();
    }

    /**
     * Called whenever the application is stopping, to allow handlers to clean up.
     */
    public void destroy()
    {
        final String methodName = "destroy";

        if (producer != null)
        {
            producer.close();
        }
        producer = null;
    }

    /**
     *
     * @param args  program takes two arguments: full path to properties file
     *              and name of the kafka topic
     */
    public static void main(String[] args)
    {
        final String methodName = "main";

        // long startTime = System.currentTimeMillis();
        // System.out.println("Start time: " + startTime);

        if (args != null && args.length < 2)
        {
            System.err.println("Usage: TitanKafkaProducer producer.properties topic");
            System.exit(1);
        }

        TitanKafkaProducer prod = new TitanKafkaProducer(args[0], args[1]);
        if (state == 1)
        {
            // load is where the listener on Titan is registered and where the
            // publishing to the Kafka broker takes place
            prod.registerListenPublish();

            try
            {
                // basically, wait forever.
                prod.waitForever();
            }
            catch (Exception e)
            {
                e.printStackTrace();
            }
            finally
            {
                prod.closeGraph();
                prod.destroy();
            }
        }
        else
        {
            System.out.println("Failed to create producer.  TitanKafkaProducer ending.");
        }

        // long endTime = System.currentTimeMillis();
        // System.out.println("End time: " + endTime);
    }
}

redpajama_set_name: RedPajamaGithub