text:
\section{Introduction}
\label{sec:intro}

The goal of speaker verification is to determine if two utterances are uttered by the same person. Currently, typical speaker verification systems use low-dimensional speaker embeddings extracted from speaker identification models based on Time Delay Neural Networks (TDNNs)~\cite{x_vectors, x_vector_wide, ecapa_tdnn} or ResNet~\cite{resnet, magneto, freq_paper} architectures. The advent of margin- and angular-based loss functions such as Additive Margin (AM)~\cite{am_softmax} and Additive Angular Margin (AAM)~\cite{arcface} softmax enables the use of cosine similarity between embeddings to score speaker similarity. These neural network based speaker identification models are trained on large datasets of labelled speech utterances to create robust speaker embeddings. A popular dataset is the development part of the VoxCeleb2~\cite{vox2} corpus, which contains over 1 million utterances from 5994 speakers.

Speaker verification systems should be robust against cross-lingual trial conditions and discriminate between speakers independently of the language spoken.
However, spoken language or dialect could be modelled as a speaker characterizing feature by the neural network. As a result, speaker verification systems are prone to underestimating the speaker similarity in positive (within-speaker) cross-lingual trials.
This effect is enhanced by the domination of speakers from the Anglosphere and limited intra-speaker linguistic variability in current popular speaker identification datasets.

The VoxCeleb Speaker Recognition Challenge 2021 (VoxSRC-21)~\cite{voxsrc_2021} aims to provide a challenging speaker verification test set with an emphasis on cross-lingual trials.
The competition rules allow to incorporate information from a pre-trained language classification model to improve robustness against cross-lingual conditions.
In this paper we analyze and further develop the cross-linguality compensation techniques we used in our VoxSRC-21 track 1 submission~\cite{idlab_voxsrc21_td}.

We propose two enhancements to increase intra-speaker cross-lingual robustness. Both techniques exploit information from a language classification model. First, we propose a cross-lingual fine-tuning stage to make the speaker embedding extractor more robust against varying phonetic content. Second, we introduce and analyse the addition of language information in our previously proposed quality-aware score calibration stage \cite{icassp_voxsrc20}.

The paper is organized as follows: Section~\ref{sec:baseline} describes the baseline speaker verification system.
Section~\ref{sec:cl_ft} and \ref{sec:calibration} outline our proposed cross-lingual fine-tuning stage and language-aware calibration system, respectively. Section~\ref{sec:setup} describes the experimental setup we use to validate our proposed enhancements. Subsequently, Section~\ref{sec:results} will discuss the results of the experiments. Finally, Section~\ref{sec:conclusion} will give some concluding remarks.

\section{Baseline System}
\label{sec:baseline}

We choose the best performing single system from our final submission on the VoxSRC-21 validation set~\cite{idlab_voxsrc21_td} as our baseline. The architecture of this fwSE-ResNet model is inspired by~\cite{magneto} and incorporates frequency-wise Squeeze-Excitation (fwSE) and frequency positional encodings~\cite{freq_paper}. The topology is defined in Table~\ref{tab:res}. Standard ResNet models are based on 2D convolutions, resulting in frequency- and time-equivariance of the model. However, speaker-specific speech patterns are expected to be different across lower and higher frequency regions. This makes the addition of frequency positional encodings in the network beneficial. The ResNet architecture is further enhanced to process speech by modifying the Squeeze-Excitation module to rescale activations frequency-wise instead of using the standard channel-wise rescaling. More information can be found in~\cite{freq_paper}.

Our baseline speaker verification system is fine-tuned using the Large-Margin Fine-Tuning (LM-FT) protocol~\cite{icassp_voxsrc20}. This secondary training stage increases the margin penalty of the AAM-softmax criterion to enforce greater inter-speaker distances and decrease the intra-speaker variability of the embeddings. The increased training difficulty caused by the higher margin configuration is compensated by taking longer fixed-length crops of the training utterances during fine-tuning.

Finally, the speaker verification trial scores are calibrated by the quality-aware score calibration backend described in~\cite{icassp_voxsrc20}. This calibration stage converts the raw trial scores to proper log-likelihood-ratios. This post-processing step also increases the speaker discriminatory ability of the system by compensating for varying quality conditions of the recordings in the trials.

\begin{table}[!h]
    \fontsize{8.5}{10}\selectfont
  \centering
  \begin{tabular}{lcr}
    \toprule
     Layer name & Structure & \multicolumn{1}{r}{Output} \\
      & & \multicolumn{1}{r}{$C$$\times$$F$$\times$$T$} \\
    \midrule
    \midrule
    log Mel-FBE & - & 1$\times$80$\times$T \\
    \midrule
    Conv2D & 3 $\times$ 3, stride=1 & 128$\times$80$\times$T \\
    \midrule
    ResBlock1 & $\begin{bmatrix} \textrm{pos. enc.}, 80\\ 3\times3, 128\\ 3\times3, 128\\\textrm{fwSE}, [128, 80] \end{bmatrix}\times$12, stride=1 & 128$\times$80$\times$T \\
    \midrule
    ResBlock2a & $\begin{bmatrix} \textrm{pos. enc.}, 80\\ 3\times3, 128\\ 3\times3, 128\\\textrm{fwSE}, [128, 40]\\ \overline{1\times1, 128}\end{bmatrix}\times$1, stride=2 & 128$\times$40$\times$T/2 \\

    \addlinespace[0.6ex]
    ResBlock2b & $\begin{bmatrix} \textrm{pos. enc.}, 40\\ 3\times3, 128\\ 3\times3, 128\\\textrm{fwSE}, [128, 40]\end{bmatrix}\times$15, stride=1 & 128$\times$40$\times$T/2 \\
    \midrule
    ResBlock3a & $\begin{bmatrix} \textrm{pos. enc.}, 40\\ 3\times3, 256\\ 3\times3, 256\\\textrm{fwSE}, [128, 20]\\ \overline{1\times1, 256}\end{bmatrix}\times$1, stride=2 & 256$\times$20$\times$T/4 \\

    \addlinespace[0.6ex]
    ResBlock3b & $\begin{bmatrix} \textrm{pos. enc.}, 20\\ 3\times3, 256\\ 3\times3, 256\\\textrm{fwSE}, [128, 20]\end{bmatrix}\times$11, stride=1 & 256$\times$20$\times$T/4 \\
    \midrule
    ResBlock4a & $\begin{bmatrix} \textrm{pos. enc.}, 20\\ 3\times3, 256\\ 3\times3, 256\\\textrm{fwSE}, [128, 10]\\ \overline{1\times1, 256}\end{bmatrix}\times$1, stride=2 & 256$\times$10$\times$T/8 \\

    \addlinespace[0.6ex]
    ResBlock4b & $\begin{bmatrix} \textrm{pos. enc.}, 10\\ 3\times3, 256\\ 3\times3, 256\\\textrm{fwSE}, [128, 10]\end{bmatrix}\times$2, stride=1 & 256$\times$10$\times$T/8 \\
    \midrule
    Flatten (C, F) & - & 2560$\times$T/8 \\
    CAS pooling  & - & 5120 \\
    \midrule
    Linear (emb.) & - & 256 \\
    AAM-softmax & & \#Speakers \\
    \bottomrule
  \end{tabular}
    \caption{The fwSE-ResNet architecture based on~\cite{magneto}  with frequency-wise Squeeze-Excitation and frequency positional encodings~\cite{freq_paper}. $C$, $F$ and $T$ are the channel, frequency and time dimensions, respectively. The pooling is realized by Channel-dependent Attentive Statistics (CAS)~\cite{ecapa_tdnn}. The 1 $\times$ 1 convolutions are used in the residual connections to match dimensions of the activation maps.}
    \label{tab:res}
\end{table}

\section{Cross-lingual fine-tuning}
\label{sec:cl_ft}

We want the speaker embeddings to be invariant to varying phonetic content and variation in spoken language. However, most speakers in the dataset will have a limited amount of spoken language variability. Subsequently, the model will likely interpret the spoken language or dialect as a speaker characterizing feature. We argue this could make the model underestimate speaker similarity in cross-lingual trials.

To mitigate this, we propose a cross-lingual fine-tuning stage.
In this training stage we increase the intra-speaker language variability on the mini-batch level.
Instead of sampling utterances randomly, we iteratively construct cross-lingual mini-batches.

We combine this strategy with LM-FT and replace the hard sampling algorithm of LM-FT with cross-lingual sampling. First, the spoken language of an utterance is estimated using a language classification model. This enables the selection of cross-lingual utterance pairs. Subsequently, mini-batches are constructed by randomly iterating over all $N$ training speakers in our dataset. During an iteration, each mini-batch contains samples from $S$ speakers with each $U$ cross-lingual utterances. The cross-lingual utterances are selected in pairs of two, alleviating the need to have a large amount of mutually cross-lingual utterances for each training speaker in case $U>2$. We resort to random sampling when a speaker does not have any cross-lingual utterance pairs available. A single iteration continues until all training speakers are processed, after which the procedure is repeated.

\section{Language calibration}
\label{sec:calibration}

Score calibration backends in speaker verification systems convert speaker similarity scores to well-calibrated log-likelihood-ratios~\cite{bosaris}. Calibration based on logistic regression has recently proved to improve speaker verification performance for DNN-based systems by including Quality Metric Functions (QMFs)~\cite{icassp_voxsrc20, alenin21_interspeech, speakin}.

Quality-aware score calibration \cite{icassp_voxsrc20} learns a mapping $l$ from the speaker similarity score $s$ to produce a calibrated log-likelihood-ratio $l(s)$. The mapping is defined as $l(s) = w_{s}s + \textbf{w}_{q}^{T} \textbf{q} + b$ with $w_s$ and $\textbf{w}_{q}$ being learnable weights for the trial score $s$ and the quality features $\textbf{q}$, respectively. Since this mapping is non-monotonic, it can improve metrics with a fixed decision threshold such as EER and MinDCF.

Figure~\ref{fig:score_shift} shows a histogram of s-normalized~\cite{s_norm, s_norm_2} trial scores of the baseline fwSE-ResNet system on the VoxSRC-21 validation set. Cross-lingual trials are defined according to language labels provided by the challenge organizers. The figure clearly shows that the baseline system underestimates speaker similarity under cross-lingual trial conditions. We propose to add language features based on hard or soft output decisions of a language classification model to allow the calibration backend to compensate for the score shift induced by cross-linguality.
A range of potential language features are discussed in the subsections below.

\subsection{Binary cross-linguality indicator}
\label{sec:lang_binary}

We can use the classification output of the language classifier to determine the most probable spoken language of an utterance. Subsequently, we construct a binary feature indicating if the predicted language of the enrollment and the test side of a speaker verification trial are the same or not.

\subsection{Similarity of predicted language class probabilities}
\label{sec:lang_js}

\begin{figure}[h]
\begin{minipage}[h]{1.0\linewidth}
  \centering
  \centerline{\includegraphics[scale=0.28]{Images/score_shift_v5_final.png}}
\end{minipage}
\caption{Histogram of the s-normalized fwSE-ResNet trial scores on the VoxSRC-21 validation set.}
\label{fig:score_shift}
\end{figure}

A cross-lingual binary feature has some limitations. First, the language classification model is prone to errors, especially on languages with a limited amount of training data~\cite{voxlingua}. In addition, a binary feature does not express any uncertainty on the language estimation of the model. Second, it only provides information with regards to the predicted spoken language, neglecting potential information about the likeliness of the utterance to other languages.

To mitigate these issues, we construct a language feature using the output probabilities $E$ and $T$ of the language classification model of the enrollment and test side utterance of the speaker verification trial, respectively.
In case of AAM-softmax trained models, we obtain the probabilities by scaling the output cosine distances of the language classifier by the proper AAM scale factor, followed by a softmax operation.

We want our language calibration feature to be side-independent of the trial, making most divergence-based metrics of the output probabilities unsuitable.
We propose the Jensen-Shannon distance between both language classification probabilities as a calibration feature as it obeys the symmetry requirement. The Jensen-Shannon distance can be regarded as a symmetrical and smoother version of the Kullback-Leibler~\cite{KL} divergence. Given both language classification output distributions, the Jensen-Shannon distance is defined as:
\begin{equation}
JS(E\|T) = \sqrt{\frac{D_{KL}(E \| M)+D_{KL}(T \| M)}{2}}
\end{equation}
with $M$ equal to $\frac{E+T}{2}$ and $D_{KL}$ indicating the Kullback-Leibler divergence.

\subsection{Similarity of language embeddings}
\label{sec:lang_emb}

Language features based on the classification probabilities directly rely on the confusion of the classifier between the language classes to model similarities between languages. This could negatively impact the ability to express intra-language variability (e.g. dialects of the same language) and language information from unseen classes. However, the final linear layers of the language classification neural network potentially contain a more general and expressive representation of the spoken language.
When the language classification model is trained using an angular-based loss function, such as the AAM-softmax, low-dimensional language embeddings can be extracted from the final linear projection layer. The spoken language of the utterances can be directly compared using the cosine distance between the extracted language embeddings. Scoring language embeddings should also generalize better when encountering new languages not seen during the training of the language classifier. Subsequently, we propose the cosine distance of the language embeddings of the enrollment and test side of the trial as a calibration feature.

\begin{table*}

  \centering
  \begin{tabular}{clcccccccc}
    \toprule

    \multicolumn{1}{c}{} &
    \multicolumn{1}{c}{} &
    \multicolumn{2}{c}{\textbf{Cross-lingual}} &
    \multicolumn{6}{c}{\textbf{Standard Benchmarks}} \\
    \cmidrule(lr){3-4} \cmidrule(lr){5-10}

    \multicolumn{1}{c}{} &
    \multicolumn{1}{l}{\textbf{System Configuration}} &
    \multicolumn{2}{c}{\textbf{VoxSRC-21 Val}} &
    \multicolumn{2}{c}{\textbf{VoxCeleb1-O}} &
    \multicolumn{2}{c}{\textbf{VoxCeleb1-E}} &
    \multicolumn{2}{c}{\textbf{VoxCeleb1-H}} \\

    \cmidrule(lr){3-4} \cmidrule(lr){5-6} \cmidrule(lr){7-8} \cmidrule(lr){9-10}
    \multicolumn{2}{c}{\textbf{}} &
    \multicolumn{1}{c}{\textbf{EER(\%)}} & \multicolumn{1}{c}{\textbf{MinDCF}} &
    \multicolumn{1}{c}{\textbf{EER(\%)}} & \multicolumn{1}{c}{\textbf{MinDCF}} &
    \multicolumn{1}{c}{\textbf{EER(\%)}} & \multicolumn{1}{c}{\textbf{MinDCF}} &
    \multicolumn{1}{c}{\textbf{EER(\%)}} & \multicolumn{1}{c}{\textbf{MinDCF}}\\

    \midrule
     & fwSE-ResNet & 2.82 & 0.1538 & 0.64 & 0.0489 & 0.84 & 0.0925 & 1.51 & 0.1471 \\

     & fwSE-ResNet + LM-FT & 2.41 & 0.1343 &  0.55 & 0.0383 &  0.76 & 0.0824 & 1.35 & 0.1300 \\
     & fwSE-ResNet + CL LM-FT & 2.25 & 0.1234 & 0.58 & 0.0375 & 0.74 & 0.0800 & 1.30 & 0.1228 \\
     \midrule

     & + log duration QMF & 2.11 & 0.1143 & \textbf{0.50} & \textbf{0.0377} & \textbf{0.71} & \textbf{0.0777} & \textbf{1.26} & \textbf{0.1204} \\
    \midrule
    \midrule

     & ++ binary QMF (\ref{sec:lang_binary}) & 1.84 & 0.1038 & 0.58 & 0.0639 & 0.78 & 0.0843 & 1.42 & 0.1436 \\

     & ++ Jensen-Shannon QMF (\ref{sec:lang_js}) & 1.67 & 0.0899 & 0.59 & 0.0586 & 0.77 & 0.0837 & 1.38 & 0.1366 \\

     & ++ cosine distance QMF (\ref{sec:lang_emb}) & \textbf{1.63} & \textbf{0.0827} & 0.55 & 0.0539 & 0.74 & 0.0794 & 1.30 & 0.1274 \\
    \bottomrule
  \end{tabular}
    \caption{Analysis of cross-lingual fine-tuning and calibration with language information of the fwSE-ResNet system.}
  \label{tab:calibration_results}
\end{table*}

\section{Experimental setup}
\label{sec:setup}

To analyse the performance impact of the proposed cross-lingual fine-tuning stage and the integration of the language calibration features, we apply our proposed enhancements on the baseline speaker verification system described in Section~\ref{sec:baseline}.

\subsection{Training configuration}
\label{sec:training_conf}

The baseline speaker embedding extractor is trained on the development part of VoxCeleb2. During training, we take random crops of two seconds of each utterance and apply a random augmentation using the MUSAN corpus~\cite{musan} (babble, music, noise) and the RIR~\cite{rirs} dataset (reverb) to prevent overfitting. The input features consist of 80-dimensional log Mel-filterbank energies (Mel-FBE) with a window length of 25 ms and a frame shift of 10 ms. To further enhance robustness, we apply SpecAugment \cite{specaugment} which randomly masks 0 to 10 frequency bands and 0 to 5 frames in the time-domain. Subsequently, all filterbank energies are mean normalized per utterance. A mini-batch size of 128 is used during training.

The model is trained using the Adam optimizer \cite{adam} with a cyclical learning rate \cite{clr} using the \textit{triangular2} policy with the minimum and maximum learning rate varying between 1e-8 and 1e-3, respectively. The cycle length is set to 130k. A weight decay of 2e-5 is used to regularize the model during training. The system is trained for one cycle with the AAM-softmax loss function using a margin and scale value of 0.2 and 30, respectively.

\subsection{Cross-lingual large-margin fine-tuning}

After the initial training phase, we apply cross-lingual LM-FT (CL LM-FT) on the model to create more discriminative speaker embeddings. In this stage, the crop size is extended to four seconds with a simultaneous AAM-softmax margin increase to 0.4. We use these settings as opposed to the originally proposed configuration in~\cite{icassp_voxsrc20} for computational reasons. Additionally, we change the random sampling of training utterances to the cross-lingual sampling strategy described in Section~\ref{sec:cl_ft}. We keep the initial batch size of 128 and vary the ratio of speakers $S$ and cross-lingual utterances $U$. We do not change the augmentation strategy.

\subsection{Quality and language aware calibration}

After the fine-tuning stage, speaker verification trial sores are normalized using adaptive s-normalization \cite{s_norm, s_norm_2} with an imposter cohort size of 400 speakers. Subsequently, we apply quality-aware score calibration using the log duration QMF~\cite{idlab_voxsrc21_td}.

We apply our proposed language calibration by adding the language features from Section~\ref{sec:calibration} to the calibration backend. We evaluate three types of language features based on the similarity between either output language predictions, output language probabilities or language embeddings. The language information is extracted from each utterance by an ECAPA-TDNN~\cite{ecapa_tdnn} language classifier\footnote{\url{https://huggingface.co/TalTechNLP/voxlingua107-epaca-tdnn}} pre-trained on VoxLingua107~\cite{voxlingua} using the AAM-softmax loss.

The calibration backend is trained on a custom VoxCeleb2 subset with half of the utterances cropped between 2 and 4 seconds. We initially select 100k trials and balance the amount of positive and negative trials. Half of the trials are cross-lingual. We discard 20\% of both positive and negative trials with the least and greatest cosine distance between the trial language embeddings, respectively. We apply this selection to compensate for overfitting induced by the fact that VoxCeleb2 is also the training dataset of the speaker embedding extractor. We only generate within-gender trials and did not include positive trials with utterances originating from the same video.
\subsection{Evaluation protocol}

We evaluate the baseline system and proposed enhancements on the VoxCeleb test sets \cite{vox1, vox2} and report the EER and MinDCF metric using a $P_{target}$ value of $10^{-2}$ with $C_{FA}$ and $C_{Miss}$ equal to 1. To analyse the proposed techniques on challenging cross-lingual data, we also evaluate the systems on the VoxSRC-21 validation and test set using the challenge MinDCF metric with a $P_{target}$ value of $0.05$.

\section{Results}
\label{sec:results}
Table~\ref{tab:cl_ft} shows the performance impact of the proposed cross-lingual fine-tuning on the VoxSRC-21 validation set. The ratio of speakers and cross-lingual utterances ($S/U$) within a mini-batch during cross-lingual sampling is indicated between brackets. Standard LM-FT with random samples results in a relative performance improvement over the baseline model of 14.5\% and 12.7\% in EER and MinDCF, respectively. The most optimal cross-lingual sampling strategy uses 64 speakers with each two cross-lingual utterances in the mini-batch and improves performance further with a relative improvement of 6.6\% in EER and 8.1\% in MinDCF. As shown in Table~\ref{tab:cl_ft}, selecting more than one cross-lingual utterance pair per speaker on the mini-batch level is less effective. This is probably caused by the fact that we keep the mini-batch size constant due to computational limitations. Therefore, we have to reduce $S$ when we increase $U$. Moreover, the amount of intra-speaker cross-lingual utterances is limited in the training set and setting $U>2$ might not be optimal for every training speaker.

\begin{table}[h]
  \centering
  \begin{tabular}{lccc}
    \toprule
     \textbf{Method} & \textbf{Sampling} & \multicolumn{1}{c}{\textbf{EER(\%)}} & \multicolumn{1}{c}{\textbf{MinDCF}} \\
    \midrule
     baseline & random & 2.82 & 0.1538 \\
    \midrule
    LM-FT & random & 2.41 & 0.1343 \\
    \midrule
    LM-FT & cross-lingual (16/8) & 2.32 & 0.1241 \\
    LM-FT & cross-lingual (32/4) & 2.26 & 0.1237 \\
    LM-FT & cross-lingual (64/2) & \textbf{2.25} & \textbf{0.1234} \\
    \bottomrule
  \end{tabular}
    \caption{Evaluation of different configurations of cross-lingual fine-tuning on the VoxSRC-21 validation set.}
    \label{tab:cl_ft}
\end{table}

In Table~\ref{tab:calibration_results} we analyse the impact of the proposed language features in the calibration stage. In most cases, incorporating language features in the calibration backend results in a minimal performance degradation on the standard VoxCeleb test sets. Mistakes made by the language classifier cannot be sufficiently compensated by better cross-lingual performance due to the limited amount of cross-lingual trials in the standard benchmark datasets. However, we see a significant reduction of the cross-lingual score shift on the VoxSRC-21 validation set. Both the probability- and embedding-based features outperform the binary cross-lingual measure, showing that the system can effectively exploit the additional language information in the soft decision features. The cosine distance between the language embeddings performs the best with a relative improvement of 22.6\% and 27.6\% of the EER and MinDCF metric on the VoxSRC-21 validation set, respectively.
These results indicate that the addition of language calibration features is currently to be considered as a performance trade-off that should be acceptable in most use-cases.

\begin{table}[h]
  \centering
  \begin{tabular}{lcc}
    \toprule
     \textbf{Systems} & \multicolumn{1}{c}{\textbf{EER(\%)}} & \multicolumn{1}{c}{\textbf{MinDCF}} \\
    \midrule

    baseline + LM-FT + QMF & 2.78 & 0.1690 \\
    baseline + CL LM-FT + lang QMF & \textbf{2.72} & \textbf{0.1492} \\
    \bottomrule
  \end{tabular}
    \caption{Performance analysis of the proposed cross-lingual fine-tuning and language calibration on the VoxSRC-21 test set.}
    \label{tab:performance_test_set}
\end{table}

Finally, we evaluate the cross-lingual fine-tuning and language calibration performance impact on the VoxSRC-21 test set. Table~\ref{tab:performance_test_set} compares the LM-FT strategy with random sampling and quality-aware score calibration without language features against LM-FT with cross-lingual sampling and score calibration with language embeddings. Incorporating language information results in a relative improvement on the VoxSRC-21 test set of 11.7\% on the MinDCF challenge metric. This improvement is less significant than the observed performance increases on the VoxSRC-21 validation set.
We suspect this is mainly due to the significantly smaller crops ($<$ 4 seconds) in the test set, which could deteriorate the language information extracted by the VoxLingua language classifier.

\section{Conclusion}
\label{sec:conclusion}

We proposed two enhancements in speaker verification to increase the robustness against cross-lingual trials. First, we introduced cross-lingual data sampling during fine-tuning of the embedding extractor. Second, we incorporated language information in the calibration backend to compensate for score shifts induced by cross-lingual conditions. By combining both strategies, we improved the baseline model relatively with 11.7\% on the main MinDCF metric on the challenging cross-lingual VoxSRC-21 test set.

\vfill\pagebreak

\bibliographystyle{IEEEbib}

redpajama_set_name: RedPajamaArXiv


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redpajama_set_name: RedPajamaCommonCrawl


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These are the new skins: Only two skins were found in the latest patch. But the fire skin in a red suit is a real eye-catcher.
These picks were found: 4 pickaxes are waiting for you in patch 8.30. So you will soon be able to beat up your opponents with a banana or a palm tree.
These back covers are new: 2 back covers were discovered. This includes a decker who is likely to be part of Season 8's legendary secret skin , which was recently shown for the first time.
These are the new liveries: In patch 8.30, 3 new liveries are waiting for your weapons and vehicles. This will allow you to accept 3 new colors.
These emotes are also new: Completed are the finds of 2 emotes, which were also discovered in the new game data. One of the emotes shows you how to open a chest with a key.
This is important when buying: The finds are exclusively cosmetic items. So you will not get better if you buy these outfits. You only change your appearance.
When will the cosmetics come to the shop? Until the next patch these outfits should be published. So that should happen over the next few days and weeks.


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History of Southern Television
Welcome to our section about the history of Southern Television
THE BIRTH OF SOUTHERN TELEVISION
In April 1957 the then regulator of commercial television, the Independent Television Authority (ITA) put out an invitation for applicants to run a new ITV service broadcasting to the south of England, an area which at that point had no contractor with ITV very much still in its infancy.
The ITA announced on the 22nd July the successful bidder was Southern Television. The company would have around 13 months to get ready to go to air.
The Southern Television company was controlled by Associated Newspapers, the Rank Organisation and the Amalgamated Press. Associated Newspapers already had interests in the television industry holding a stake in the London weekday provider Associated Rediffusion, the ITA put in a condition in the awarding of the franchise that Associated Newspapers would need to divest their stake in order to be allowed to be part of the Southern consortium. The structure of the new company appealed to the ITA as they felt this was a more stable approach to have multiple shareholders (there had been issues with previous franchise awards where individual companies were unable to come up with the required capital and dropping out).
This new area would be served by a transmitter being built at Chillerton Down on the Isle of Wight, Southern would rent the transmitter for an annual sum of around �200,000. A lattice steel tower was constructed on the Ogle Road telephone exchange to carry signals to the transmitter at Chillerton Down.
Southern started work creating studio facilities at Southampton. Due to their links with the Rank Organisation their chosen home would be a former cinema, The Plaza, on the banks of the river Itchen. The cinema was the biggest on the south coast with 2,134 seats. Conversion was undertaken by E. H. Burgess and Co to include three studios, production facilities and offices for Southern's administrative departments. The cost of the conversion would run well into six figures, a huge sum at the time.
Studio A at Southampton would cover 300sq ft. with a lighting gantry holding 62 circuits. A second studio, Studio B, was smaller and used for magazine style programmes while the third Studio C was used just for news programmes.
The conversion costs would be dwarfed by the costs of equipping the studios and other costs such as dry runs, staffing costs and the annual rental to the ITA.
Southern spent a large sum on advertising their new service involving adverts in the local papers and a series of four day exhibitions in seven of the largest towns in their region. Many people at the time did not want to go to the expense of getting their TV sets converted to receive ITV programmes (costing between �2 and �10 at the time) and Southern wanted to target some of the 185,000 homes in their region to get as many viewing from day one as possible to get more advertising revenue once the station launched.
SOUTHERN TELEVISION - ON THE AIR
Southern Television went on the air on the 30th August 1958, many local dignitaries attended the studios and crowds were gathered outside and on the bridge over the River Itchen watching the arrivals The opening of any new ITV station was a huge event back then (the small number of homes that did have a television set only had the BBC Television Service to watch previously).
The first night included a production called Southern Rhapsody, a musical number staring Gracie Fields and Lionel Blair. This would be the first of numerous programmes to be broadcast across the ITV network (many of the ITV companies provided a programme to be shown across the network on their first night).
Southern Rhapsody was also the name of the piece of music Southern would start their day with throughout its history, the music being composed by Richard Aspinal
Southern Rhapsody
Southern entered ITV at a good time, franchise holders in the existing regions had initially lost huge sums of money trying to make the network a success while struggling to create its audience, by the time Southern went to air ITV was becoming �a licence to print money". Southern also had the advantage of launching in the autumn when advertising revenue was at its highest. The company was expecting to recoup its initial outlay within a couple of years.
At launch the number of available homes receiving the new service was small at around 21% but by the end of 1959 this will have risen to 52% with around 1,425,000 viewers tuning in
In 1959 the ITA put out an advertisement for companies to apply to run a region covering Kent and the South East of England. Southern were successful in their bid and built a small studio in Dover to cover this area. Transmissions from Dover started in 1960.
One of the unique things about Southern was a mobile studio called The Southerner. The Southerner, which was originally called Winola, was a 70ft motor torpedo boat which had a top speed of 30 knots. The boat underwent major structural alterations creating broadcasting facilities including a control room, VTR machines and three cameras. The Southerner would be used to cover marine based events, an important part of life to those in the South of England and also providing coverage for the network. The boat naming ceremony took place on the 23rd July 1965.
One of the big news events covered with help of the Southerner was that of the Torrey Canyon disaster in 1967 where a major oil spillage caused an environmental disaster when it came ashore, devastating wildlife on the south coast.
By the late 1960s Southern had begun to outgrow their former cinema home and plans were put into place for the creation of purpose built studios, this coincided with the development of colour television becoming more widely available. The old Plaza was looking tired and would not take well to the conversion to colour. The announcement was made to the press in early 1968 with how the new complex would look.
The cost of these new studios would be a huge expense to the company. The studios would be partly built on reclaimed land from the River Itchen, a very costly process. The foundation stone was laid on the 6th July 1968 by Lord Aylestone and work on the new buildings continued while the old studios were still very much operational. The construction work could be slow at times as they needed to stop work while a programme was being recorded or transmitted live due to the noise and the vibrations making the camera shots rather wobbly. The work was due to be completed for a sum of �2.5M
The new studios were completed in 1969, with the new studios operational the old ones were stripped of equipment and lay empty awaiting demolition to allow further work to take place on an office block to house the administrative departments.
Several popular programmes would be made at Southampton and one of the first to be filmed in the new studios was the women only chat show Houseparty (women presenters only that is), this would become one of Southern's most remembered lifestyle shows along with Jack Hargreaves in Out Of Town (both running until the company's demise in 1981)
Southern would be possibly best remembered for its many children's programmes which were shown across the ITV network including, Freewheelers, The Flockton Flyer and the huge hit Worzel Gummidge. These and other Southern programmes would lead to big company profits which by 1974 had hit a record �2,635,752 on a turnover of over�12M, all this despite rising costs in the industry. They were also highly praised by the new regulator, the Independent Broadcasting Authority (IBA), during the 1974 franchise renewals although the IBA did comment about a lack of local political programmes and a possible lack of local football.
Towards the end of the decade and the company was flying, it had nearly 600 staff and a turnover of �24M along with nearly �4M in the bank, huge sums at the time making it one of the most profitable ITV companies.
THE DEMISE OF SOUTHEN TELEVISION
As part of the 1980 franchise award the IBA redrew the transmitter map to provide a better service in some areas. One of these areas would be to the South East of England where the IBA decided to re-allocate the transmitter at Bluebell Hill which was at that time part of the London region. This caused much dismay of the London holders Thames Television and London Weekend Television (LWT) (in particular LWT who went on a PR campaign to serve their viewers better).
As part of this transmitter change the IBA abolished the South franchise creating a new franchise which would serve not only the south but also the south east of England. A condition of any broadcaster serving this new dual region would be a requirement to provide a distinctive individual service to both parts of the region.
At that point in time Southern Television had a small studio in Dover but it had made little sense for them to pool large resource in this small part of their much bigger region (they held the South of England franchise after all). The other part of the South East was part of the London region and they were not overly keen to provide much of a service here either.
This new region would a big area to cover but also predominately an affluent one and this was an attractive prospect to any prospective bidder as it could attract the big money with advertising revenue. Southern Television was also seen by others to be vulnerable due to the way the company was structured. Southern was controlled by three large shareholders, none of which had any real connection with the region they served, the company was run from London where most decisions were made and this structure met disapproval from the IBA.
Nine applications were made for the franchise and this would make it the most hotly contested region in the whole of the ITV network, no other area has generated that much interest previously or indeed since. Southern were slated in the press by many of the other franchise applicants, Southern were seen as vulnerable by others due to their structure and played on the poor service to the south east (although this was not strictly the fault of Southern). The company decided that it would not react, not retaliate as their record of programming would mean that they sail through the application.
Southern were in fact very blase about the whole thing they knew in their own minds they were going to win and this was quite clear in their franchise application. The application was minimal to say the least and the IBA were not impressed by Southern's arrogance and sent their application back to them to provide proper detail
Southern Television Franchise Application
Southern Television IBA Awarding the franchise to Television South
Lady Plowden, the outgoing chair of the IBA announced the decision of the franchise awards on Sunday 28th December 1980. it was a decision that would be a huge shock to those involved. Southern had lost the region they had served since 1958 to South and South East Communications which would later be known as Television South (TVS). Other announcements were that Westward Television would lose the South West region to Television South West (TSW), ATV would be restructured and a new company called Central Television would run the midlands and that TV-am would be awarded the ITV Breakfast service (which would eventually start in 1983).
TVS was awarded an eight-year franchise to run the new South and South East dual region, the IBA felt that TVS gave a better proposal on how it was going to serve the two parts of its region. The TVS bid was new and exciting while that of Southern seemed to be more of the same in comparison and lacking ambition despite the plans for new studios to serve the South East.
The decision left Southern Television stunned as they had never expected to lose, they had been a solid and dependable broadcaster with a good track record, needless to say they were very unhappy with the decision. The decision was also a huge shock to TVS who had not really expected to win outright thinking their best chance would be a forced merger with the incumbent broadcaster.
Southern were fuming at the regulator, writing to the IBA demanding an explanation. The response they got was that while it appreciated that Southern were disappointed the authority had considered all applications and went for what they felt was the better choice.
Southern were angry with the IBA however most of their frustration was with TVS that they had applied for in the first place in a �how dare you apply for our franchise"� attitude.
TVS started setting up their service and approached Southern about buying their facilities, however the incumbant broadcaster was still licking their wounds and in no mood to get into discussions with the new company taking over. There was a stalemate between the companies for some time with Southern not wanting to give into anything asked for by the newcomers even though this would often be to the detriment of the company.
As it became clear Southern were not going to get anywhere with the regulator in staying on the air they considered re-inventing themselves as an independent producer and continuing to supply programmes to the ITV network. Even if Southern did continue as an independent (it didn't) they would need to downsize and they eventually they agreed to part with the studios at Southampton and Dover and received �11M from TVS for these. Southern also sold the news archives to TVS but decided to retain the rights to their other programmes which they would market themselves throughout most of the 1980s. Under a union agreement where members should not lose their position as part of the franchise changes TVS would also take on the majority of Southern staff both on and off screen.
Southern sold a plot of land at Maidstone which the company had wanted to use to build new studios for the South East had they won the franchise. The studios that Southern had planned to build would be similar in layout to the Southampton site but as this was not going to happen they sold up to TVS for a handsome profit. TVS started building their studios there in the spring of 1981 much to the same design as Southern had planned to.
By the time summer had come Southern and TVS were on talking terms (just) and TVS had set up camp in temporary buildings in Southern's carpark at the Southampton Studios (those temporary buildings would still be there when TVS lost their franchise eleven years later), there was also an agreement that TVS would hire Southern's studios and staff to produce the programmes the new company would provide when it went on the air in January the following year. This earned TVS the nickname Portakabin Television by disgruntled Southern staff.
As 1981 drew to a close the final staff Christmas party was another opportunity for Southern to vent their anger about the way they have been treated. That November evening featured a speech from the chairman David Wilson who talked about how well Southern had done and its achievements and how bitter he was with the way they had been unfairly by the IBA (claiming the authority never read the application properly as it was the best proposal).
DAVID WILSON SPEECH - 1981
That party also had songsmith Richard Stilgoe sing a satirical song called Portakabin TV� which poked fun at TVS and how everything they had promised was rubbish and eventually the company would see that Southern were so good they would keep everything the same.
RICHARD STILGOE PERFORMS PORTAKABIN TV - 1981
Richard Stilgoe Performs Portakabin TV
We'e Portakabin TV and we can't believe our luck
To have got the bid from Channel to the sea
To be frank we thought the best would, for been to go for Westward
Or Yorkshire, or Even ATV
We are Portakabin TV, our approach is fresh and new
You won't see us making shows just cause they pay
There'll be no more 3-2-1, and Crossroads we will shun
Well at least for the first six months anyway
We are Portakabin TV Gatward, Boston and Blackstad
And on January 1st our flag unfuls
Our future is assured, we've a lord upon the board
And someone who once did Tomorrow's World
We are Portakabin TV and the South East of our patch
Is top of our list of priorities
It will be all systems go, in our Maidstone studio
Just as soon as we find out where Maidstone is
We are Portakabin TV and our paper's brown and cream
Not that nasty Southern TV white and blue
And we all say yours sincerely when we finish let us off
Hugs and kisses Brian Izzard just wont do
We are Portakabin TV and we promise we will change
Everything so all is new and vital
The show to alter most will be our nightly Coast to Coast
Which is really Day By Day with a new title
We are Portakabin TV and we're dropping lots of shows
I'm afraid to How we all must say goodbye
Because we don't know how but we do when it's now
But what people want knows not how but why
We are Portakabin TV, and all that's going to change
is the local television station's name
We would change it if we could, but Southern was so good,
we've decided to keep everything the same
The final day on the air was the 31st December 1981, the station launched in the normal way and there was no mention the station was going off the air but that would not last long.
Final Morning Startup
The evening came and the final edition of Day By Day which had been re-titled Day By Yesterday presented by Christopher Peacock and Cliff Michelmore. The show had a brief news segment from Peter Clark, Roger Livingston and Preston Witts but the majority of the show was looking at Southern. The programme looked into the archives of past versions of the show and talked to viewers in the region, scarecrow superstar Worzel Gummidge appeared promoting the stage version of the show and they also visit Jack Hargreaves along with the Scene South East crowd. There was also significant sections devoted to the Southern Christmas party and the show aired David Wilson's speech and the Portakabin TV song in full. The show ended with the Day By Day team sing a song about the show
The final show from Southern was called 'And It's Goodbye From Us' and was presented by one of their continuity announcers Christopher Robbie. This would be a big production and featured the Bournemouth Sinfonetta who performed the opening music, a specially composed piece called Southern Fantasia
Many of the stars from various Southern shows (mainly Day by Day, Out of Town and Houseparty) attended. There were a few excerpts from Southern shows such as Star Treatment, Winston Churchill the Wilderness Years and music from Cleo Lane. Wilson's speech and the Portakabin TV song were aired yet again for those who missed them earlier in the day (albeit a shortened version).
The show ended with the Southern Fantasia music that had started the show, the camera panning over the Southern stars present in the studios (most of which were quite tired and bemused at this point), the lights faded and went to the endcap
THE FINAL MOMENTS OF SOUTHERN TELEVISION - 1982
The Final Moments of Southern Television
At 12:45am on the 1st January 1982 the Southern star is sent spinning off into space over the stations jingle. Southern went off the air for the very last time
Southern Television - Off The Air
Southern did not die straight away and the company did still exist for a time marketing and distributing programmes from their archives. The archives were eventually sold to Primetime Television which became Southern Star Primetime. Some programmes have since been released on DVD and many do appear from time to time on satellite TV. The archives are now the property of Renown Pictures and many Southern programmes are being shown on their Talking Pictures TV channel on Sky.
Southern's former home at Southampton was used by TVS and later Meridian Broadcasting (who had taken over from TVS in 1993) until 2004 when they left for the smaller studios Meridian had always wanted. The studios were stripped with equipment being sold at auction before becoming a storage area for trucks. The buildings were later demolished and the plot stayed empty for a few years, the site is now occupied by housing.
The studios at Dover were in use by TVS for a few months while work continued on those they were building at Maidstone. Once TVS moved out the studios were eventually demolished and a car park was put in its place, the car park itself now having been replaced by housing.
The next steps for The Southerner are unclear but it did eventually end up as a pleasure boat located in Malta. Ambra as it was renamed was in use until 2005 when it fell in to disuse and was broken up a couple of years later, deemed too uneconomical to repair.
The Southern Television name and identity are the property of Nic Ayling
ITV Sections
Southern Idents and Continuity 1958-1960
Southern Television Endcaps
Southern News Presentation
Southern Programmes
Southern Buildings and Studios
Miscellaneous Southern Television Television
Northern Scotland
Central and Southern Scotland
Wales and West of England
Borders, Cumbria and Isle of Man
South and South East of England


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María Ana de Jesús Guerrero Torija (Madrid, 17 de abril de 1867 - Madrid, 23 de enero de 1928), conocida como María Guerrero o María "la Brava", fue una de las mejores actrices de la escena española y una de las primeras empresarias teatrales a nivel nacional. Controló, junto a su marido Fernando Díaz de Mendoza y Aguado, un amplio periodo de la escena teatral tanto en España como en Hispanoamérica.

Biografía

Infancia y juventud
Nació en la madrileña Calle del Caballero de Gracia, en el seno de una familia acomodada. Fue hija de Casilda Torija y Ramón Guerrero, un tapicero y decorador que acababa de volver de Francia y que había sido contratado para proporcionar muebles a algunos teatros de Madrid. Don Ramón tenía un gran interés por el arte y esto le llevó a tener amistad con figuras del panorama cultural e intelectual madrileño como el pintor Emilio Sala, quien retrató a la actriz a la edad de diez años, o el actor Emilio Mario.

Tras recibir su educación en el Colegio de San Luis de los Franceses de Madrid hasta los quince años —donde aprendió francés, piano, arpa y canto—, estudió arte dramático con la actriz Teodora Lamadrid a partir de 1885. Lamadrid no solía admitir alumnas en su casa, pero gracias a su padre y a los contactos que tenía este en la sociedad madrileña, admitió a María Guerrero y le enseño a respirar, a recitar en verso y a actuar.

Comienzos en el teatro
Cuando María cumplió dieciocho años insistió en actuar y gracias a la amistad de su padre con Emilio Mario empezó a formar parte de la compañía de este. Finalmente, debutó el 28 de octubre de 1885 con la obra Sin familia, de Miguel Echegaray en el Teatro de la Comedia de Madrid.

Durante sus primeros años como actriz solía realizar papeles de dama joven e ingenua. En 1890, cinco años después de su debut, dejó la compañía de Emilio Mario y pasó a formar parte de la compañía de Ricardo Calvo como primera actriz del Teatro Español,representando obras clásicas y de la época con gran éxito. Su Doña Inés —del Don Juan Tenorio de José Zorrilla—, que interpretó en 1891, fue uno de sus personajes más aclamados a lo largo de toda su carrera profesional, y la consagró como actriz. Tanto es así que se convirtió en inspiración para autores teatrales del momento como Pérez Galdós, Valle-Inclán, Clarín o José Echegaray.

Primera actriz y sus comienzos como empresaria
Amplió sus estudios teatrales en París con el actor y director Benoît-Constant Coquelin en 1891, quien le enseñó a declamar. De vuelta a España, en 1892, volvió al Teatro de la Comedia como primera actriz con Emilio Mario, pero dos años más tarde, en 1894, abandonó la compañía para crear la suya propia y se embarcó en un proyecto muy ambicioso en el Teatro Español.

El Teatro Español había sido clausurado por ruinoso en mitad de la temporada teatral de 1887. Un año más tarde se permitió su reapertura gracias a unas pequeñas modificaciones, pero el local no cumplía con unas condiciones mínimas y era un fracaso. En 1894 salió el teatro a concurso por el Ayuntamiento de Madrid y María Guerrero solicitó el teatro, que se le fue concedido para diez temporadas. Lo primero que debía hacer sería renovar todo el teatro y para ello su padre, Ramón Guerrero, tuvo que vender sus propiedades. Mientras que las obras estaban en curso padre e hija se dedicaron a confeccionar el nuevo elenco de la compañía con la ayuda de Ricardo Calvo, primer actor y director artístico.Como las obras no habían terminado para cuando comenzó la temporada teatral de 1894 - 1895, tuvo que comenzar la temporada en el Teatro de la Princesa.

Entre los actores seleccionados para la compañía se encontraba Fernando Díaz de Mendoza, un aristócrata joven y viudo a quien se seleccionó para los papales de joven galán. Fernando Díaz de Mendoza y María Guerrero interpretaron juntos varias obras como María Rosa, de Ángel Guimerá, o Mancha que limpia, de José Echegaray. Su relación se fue estrechando y se casaron el 10 de enero de 1896. Con Fernando Díaz de Mendoza tuvo a sus dos hijos, Fernando (5 de marzo de 1897) y Carlos Fernando (4 de septiembre de 1898).

Giras internacionales, estrella consagrada
Tras el nacimiento de sus hijos, en 1899, la compañía Guerrero-Díaz de Mendoza emprende una gira por Latinoamérica a la que siguió, un año después, otra por Francia, Bélgica e Italia. Con motivo de sus giras perdió la concesión del Teatro Español en 1900, con lo que se quedó temporalmente sin teatro y sin el prestigio que le otorgaba este. Entre 1901 y 1909 tuvo la posibilidad de volver a este teatro estrenando grandes obras en él y compaginando estas representaciones con otra gira internacional por Latinoamérica en 1908, pero ya no se sentía a gusto porque sentía limitada su libertad. Por este motivo, y gracias a los beneficios de sus giras, el matrimonio Díaz de Mendoza-Guerrero compró el Teatro de la Princesa en marzo de 1908.

El Teatro de la Princesa —que desde 1931 se llama Teatro María Guerrero— se reinauguró en noviembre de 1909 con la obra Doña María la Brava, un texto escrito por Eduardo Marquina expresamente para la pareja. En 1918 llegaron a fijar este teatro como su residencia permanente, trasladándose con sus dos hijos a una nueva quinta planta que construyeron para ello con el fin de poder financiar la construcción del Teatro Cervantes de Buenos Aires, que se inauguró el 5 de septiembre de 1921, pero que les llevó a la banca rota. El Teatro María Guerrero es actualmente una sede del Centro Dramático Nacional y fue, durante la época de María "la Brava", el centro de reunión de la sociedad madrileña donde actuaron actrices de la talla de Margarita Xirgu.

Durante el resto de su trayectoria profesional realizó más de veinticinco giras por el extranjero, principalmente por Latinoamérica (1897, 1908, 1910, 1914...), con especial querencia por Uruguay y Argentina. En la ciudad argentina de Córdoba, fue una de las inauguradoras del Teatro Rivera Indarte (llamado actualmente Teatro del Libertador General San Martín), y en Buenos Aires inauguró el Teatro Avenida y pagó para que se construyera el ya mencionado Teatro Nacional Cervantes. En 1926 también llegó a actuar en la Manhattan Opera House de Nueva York.

A lo largo de su carrera estrenó obras de los Premios Nobel de Literatura Jacinto Benavente y José Echegaray, así como de Benito Pérez Galdós, Eduardo Marquina, Valle-Inclán, Ángel Guimerá, Gregorio Martínez Sierra, Francisco Villaespesa, Pedro Muñoz Seca o los Hermanos Álvarez Quintero. También dio trabajo a actrices y actores importantes de la época como Elena Salvador, María Cancio, Catalina Bárcena, Emilio Masejo, Emilio Thuillier, Josefina Blanco o María Fernanda Ladrón de Guevara  y llegó a actuar con actrices internacionales como Sarah Bernhardt en una actuación en francés que tuvo lugar en el Teatro Español.

Muerte y entierro
Falleció en su vivienda el 23 de enero de 1928, con sesenta años, a consecuencia de un ataque de uremia, un fallo renal, tan solo siete días después de su última función en la que estrenó Doña Diabla, de Luis Fernández Ardavín. Está enterrada en el cementerio de la Almudena de Madrid y su muerte conmocionó a toda la ciudad. A su entierro multitudinario asistieron figuras como Jacinto Benavente o los hermanos Álvarez Quintero.

Polémicas familiares
Su hijo mayor, Fernando Díaz de Mendoza y Guerrero, tuvo una relación extramarital con Carola Fernán Gómez, una actriz que trabajaba para la compañía de su madre. Cuando su madre se enteró de esta relación mandó a Carola a América sin saber que estaba embarazada. Carola tuvo en Lima (Perú) un niño, quien luego ha resultado ser el gran actor Fernando Fernán Gómez, nieto de la actriz. Fernán Gómez nunca fue reconocido por la familia Díaz de Mendoza-Guerrero, y tampoco por su padre, con el que llegó a encontrarse en al menos una ocasión.

Aporte a la escena teatral
María no solo ha sido una de las mejores actrices de la escena española, sino que también llevó su repertorio de más de doscientas obras —tanto clásicas como de la época—con orgullo por todo el mundo, pasando por Italia, Uruguay, Argentina, Bélgica, Francia, Estados Unidos o Perú.

Durante su trayectoria profesional sirvió de inspiración para muchos dramaturgos de finales del siglo XIX y comienzos del siglo XX y estuvo comprometida con llevar a los escenarios grandes obras del Siglo de Oro como el Don Juan Tenorio, de José Zorrilla, El retablo de las maravillas, de Miguel de Cervantes o La dama boba, de Lope de Vega. Su interés por el Siglo de Oro fue tal que decidió dedicar los lunes en el Teatro Español a la representación de los clásicos, en un programa llamado "Los lunes clásicos", revitalizando así los grandes clásicos españoles.

La Guerrero, además, fue pionera en España en apagar las luces del teatro, en 1900, ya que hasta el momento las luces del público se mantenían encendidas durante la función, lo que hacía del teatro un acto más social que cultural. Tampoco escatimó en gastos para las puestas en escena de sus obras, que elaboraba con mucho mimo, ya que era ella la productora y diseñadora artística de sus obras. Su trabajo sentó las bases de un teatro muy bien representado y exquisitamente vestido, incluyendo incluso hasta varios cambios de vestuario.Por todo ello se considera que fue doña María Guerrero quien llevó al teatro español a la modernidad.

María Guerrero en el Museo del Prado
María "la Brava" aparece representada tres veces en el Museo del Prado de Madrid. Esto es bastante poco común tratándose, además, de una persona que no pertenecía a la realeza y que era mujer y actriz a finales del siglo XIX. Su empeño por ser retratada proviene de las inquietudes de su padre por el arte. Por ello deseaba ser retratada en vida por algunos de los pintores más famosos de su tiempo.

 Emilio Sala fue el primero en pintar a una jovencísima María en 1878, en un óleo sobre lienzo que tuvo por título María Guerrero. Este cuadro fue un regalo de Sala a Ramón Guerrero, el padre de la actriz. El cuadro representa a una María de diez años, sentada en una silla de madera y con un vestido azul de vueltas blancas. Actualmente este cuadro no se encuentra expuesto en las galerías del museo.
 Raimundo de Madrazo y Garreta en 1891 realiza un retrato de María con el hábito de las monjas calatravas para el papel de Doña Inés. Este fue uno de los personajes que le trajeron más éxitos a la actriz. Fue retratada a los veinticuatro años y el cuadro La actriz María Guerrero, como "Doña Inés" se encuentra en la sala 062B del Prado.
 El último pintor en retratar a Guerrero fue Joaquín Sorolla en 1906. Amigo y vecino de esta, la retrata representando el papel de Finea en la obra de La dama boba, de Lope de Vega. Este cuadro en realidad está sobrepintado. Sorolla ya había realizado un retrato de Guerrero para presentarlo en la Exposición Nacional de 1897, pero decide rehacerlo añadiendo tela al cuadro y mejorando el trabajo modificando el traje, el rostro y el fondo, en el que añade a Fernando Díaz de de Mendoza. Este nueva obra pretendía ser un homenaje a Velázquez por parte de Sorolla. La obra en cuestión, La actriz doña María Guerrero como La dama boba, se encuentra en la sala 060A del museo.
Estos tres artistas no fueron los únicos que la pintaron, también lo hicieron José Vallejo, Anselmo Miguel Nieto, Ricardo Baroja o Daniel Vázquez Díaz, cuyo retrato de la empresaria y actriz pertenece en la actualidad al museo Reina Sofía, aunque tampoco esté expuesto.

Obras representadas (selección)

 Sin familia (1885), de Miguel Echegaray.
 Un archimillonario (1886), de Pedro de Novo.
 El primer choque (1889), de Antonio Sánchez Pérez.
 Lo positivo (1890), de Manuel Tamayo y Baus.
 Los irresponsables (1890), de Joaquín Dicenta.
 El sí de las niñas (1890), de Leandro Fernández de Moratín.
 El vergonzoso en palacio (1890), de Tirso de Molina.
 Don Juan Tenorio (1890), de José Zorrilla, en el papel de Doña Inés.
 Un crítico impaciente (1891), de José de Echegaray.
 Realidad (1891), de Benito Pérez Galdós.
 Mariana (1892), de Echegaray.
 La loca de la casa (1893), de Galdós.
 El poder de la impotencia (1893), de Echegaray.
 A la orilla del mar (1893), de Echegaray.
 La de San Quintín (1894), de Galdós.
 La rencorosa (1894), de Echegaray.
 María Rosa (1894), de Ángel Guimerá.
 Entre bobos anda el juego (1895), de Francisco de Rojas Zorrilla
 El desdén con el desdén  (1895), de Agustín Moreto.
 Mancha que limpia (1895), de Echegaray.
 El estigma (1895), de Echegaray.
 Teresa (1895), de Leopoldo Alas.
 Voluntad (1895), de Galdós.
 La mujer de Loth (1896), de Eugenio Sellés.
 La locura de amor (1896), de Tamayo y Baus.
 La calumnia por castigo (1897), de Echegaray.
 La duda (1898), de Echegaray.
 El hombre negro (1898), de Echegaray.
 Cyrano de Bergerac (1899), de Edmond Rostand.
 La pena (1901), de los Hermanos Álvarez Quintero.
 La musa (1902), de Salvador Rueda.
 Realidad (1902), de Pérez Galdós.
 Malas herencias (1902), de Echegaray.
 La escalinata de un trono (1903), de Echegaray.
 La noche del sábado (1903), de Jacinto Benavente.
 Aire de fuera (1903), de Manuel Linares Rivas.
 Mariucha (1903), de Galdós.
 Por qué se ama (1903), de Benavente.
 La desequilibrada (1903), de Echegaray.
 La zagala (1904), de los Quintero.
 La casa de García (1904), de los Quintero.
 El dragón de fuego (1904), de Benavente.
 El médico de su honra (1905), de Calderón de la Barca.
 A fuerza de arrastrarse (1905), de Echegaray.
 Barbara (1905), de Galdós.
 Rosas de otoño (1905), de Benavente.
 El susto de la condesa (1905), de Benavente.
 La aventura de los galeotes (1905), de los Quintero.
 La musa loca (1905), de los Quintero.
 La sobresalienta (1905), de Benavente.
 Verdad (1906), de Emilia Pardo Bazán.
 Más fuerte que el amor (1906), de Benavente.
 La princesa Bebé (1906), de Benavente.
 Amor de artistas (1906), de Dicenta.
 El genio alegre (1906), de los Quintero.
 María Estuardo (1906), de Friedrich Schiller.
 Añoranzas (1906), de Manuel Linares Rivas.
 Monna Vanna (1907), de Maurice Maeterlinck.
 Daniel (1907), de Dicenta.
 El crimen de ayer (1908), de Dicenta.
 El preferido y los cenicientos (1908), de Echegaray.
 Las hijas del Cid (1908), de Eduardo Marquina.
 Amores y amoríos (1908), de los Quintero.
 La araña (1908), de Ángel Guimerá.
 Las flores (1908), de los Quintero.
 Doña María la Brava (1909), de Eduardo Marquina.
 La fuente amarga (1910), de Manuel Linares Rivas.
 La flor de la vida (1910), de los Quintero.
 En Flandes se ha puesto el sol (1910), de Marquina.
 La tragedia del beso (1910), de Carlos F. Shaw
 Voces de gesta (1911), de Valle-Inclán.
 Primavera en otoño (1911), de Gregorio Martínez Sierra.
 El rey trovador (1911), de Marquina.
 La alcaldesa de Pastrana (1911), de Marquina.
 Rosa y Rosita (1911), de los Quintero
 El alcázar de las perlas (1911), de Francisco Villaespesa.
 Doña Desdenes (1912), de Manuel Linares Rivas.
 La Marquesa Rosalinda (1912), de Valle-Inclán.
 Malvaloca (1912), de los Quintero.
 Cuando florezcan los rosales (1913), de Marquina.
 El retablo de Agrellano (1913), de Marquina.
 La Malquerida (1913), de Jacinto Benavente.
 Mamá (1913), de Gregorio Martínez Sierra.
 Alceste (1914), de Galdós.
 La garra (1914), de Manuel Linares Rivas.
 La fuerza del mal (1914), de Linares Rivas.
 Una mujer (1914), de Marquina.
 Las flores de Aragón (1914), de Marquina.
 El collar de estrellas (1915), de Benavente.
 El duque de El (1915), de los Quintero.
 Campo de armiño (1916), de Benavente.
 El Gran Capitán (1916), de Marquina.
 Los cachorros (1918), de Benavente.
 El último pecado (1918), de Pedro Muñoz Seca.
 La verdad de la mentira (1918), de Muñoz Seca.
 La calumniada (1919), de los Quintero.
 La vestal de Occidente (1919), de Benavente.
 Una pobre mujer (1920), de Benavente
 El abanico de Lady Windermere (1922), de Oscar Wilde.
 Dentro de un siglo (1921), de Muñoz Seca.
 La enemiga (1922), de Nicodemi.
 La dama de armiño (1922), de Luis Fernández Ardavín.
 El doncel romántico (1922), de Fernández Ardavín.
 Los frescos (1922), de Muñoz Seca.
 Lecciones de buen amor (1924), de Benavente.
 La vidriera milagrosa (1924), de Fernández Ardavín.
 Un par de botas (1924), de Benavente.
 El pobrecito carpintero (1924), de Marquina.
 Doña Diabla (1925), de Fernández Ardavín.
 Don Luis Mejía (1925), de Marquina.
 Desdichas de la fortuna o Julianillo Valcárcel (1926), de Manuel y Antonio Machado.
 Via crucis (1928), de Fernández Ardavín.

Premios
 Hija Predilecta de Madrid (1922).
 Gran Cruz de Alfonso XII (1922).

Referencias

Enlaces externos

 Cronología de María Guerrero

Actores de Madrid
Fallecidos por enfermedades renales
Actrices de España del siglo XIX
Empresarios de teatro
Empresarios de España del siglo XX
Condecorados con la gran cruz de la Orden de Alfonso XII
Actrices de España del siglo XX
Actrices de teatro de España
Nacidos en Madrid
Sepultados en el cementerio de La Almudena
Fallecidos en Madrid

redpajama_set_name: RedPajamaWikipedia


text:
Q: Techniques for understanding complicated legacy database I have inherited a complex, poorly documented SQL Server database and am trying to reverse engineer the tables, their relationships and in general how the data fits together. To do this I am drawing the table diagrams using Visio, attempting to determine the data relationships using the existing queries (there are no relationships actually defined) and using the application logic (what little there is) to help.
This is however quite challenging given the lack of documentation / obfuscated nature of this system and I was wondering if there are any techniques / approaches that can help?

A: Not an easy job, and the bigger it is the harder it is. I do however have one small trick for discovering the necessary surface area of the database - remove all user access!
This sort of database often runs with full access (i.e. users are DBO level or above) so anyone can do anything. If you remove all user access (but not your own!), then start application testing and enable minimum permissions on a per object basis, you will eventually reveal the surface area of the database (the exposed objects). This information is very useful in helping to identify dead objects - your job is hard enough as it is without having to document SPs that are no longer used for example.
How successful this technique can be depends on how thorough you think you can be in your testing, how sure you can be that someone somewhere doesn't have an Excel workbook that connects to the database once a year to run some query that no-one else ever does.

redpajama_set_name: RedPajamaStackExchange


What colors go with what?
I found this great graphic that will help you put various color combinations together on the Paris To Go blog and thought I would share it.
Use it to challenge your thinking when it comes to mixing and matching the items in your wardrobe or when adding to your closet.
What combinations surprise you? Inspire you?
Previous Have you heard about Ruby Ribbon?
Next Let's get together for a personal styling session!


The ancient city of Bhubaneswar is also known as the Temple City of eastern India. The word Bhubaneswar in its literal sense means the 'God's World' which showcases the walk down centuries of temple architecture. You can here explore the 600 temples in its treasure and the city is probably the only city in the world that presents a veritable over-view of the stages of development of Hindu religious architecture.
Conveniently located 9kms from the airport and a stroll away from shopping and entertainment options, the Mayfair Lagoon offers 96 elegantly designed rooms and cottages around a lagoon, spread over 10 acres of lush tropical greenery and landscaped gardens; interspersed with courtyards, fountains and exquisite works of Kalinga Art.
The Trident Bhubaneswar, is a temple style hotel, replete with modern amenities that befit a true-blue Trident Hilton hotel.
Excursion to Konark which is known for the world-famous Konark Temple also called the Sun Temple.
Visit the 10th century Mukteswara Temple, the Parasurameswara Temple, the Raj Rani Temple, the Vaital Deul Temple, the Brahmeshwar Temple, the famous ISKON temple; the multi-tiered rock-cut caves of Udayagiri and Khandagiri.


Creating an eclectic style for your interior is a wonderful idea. It's not only easy to love; it's a great design that's a sight to behold if and when it is done right.
However, an eclectic style interior is a bit tricky to achieve.
Mistakes most people make when setting up this style is they believe it symbolises a jumble of textures, colours, patterns, and a mish-mash of unrelated pieces of furniture. Not so!
Though the decor style is a combination of styles and periods using various items, old and new, most homeowners desirous of the look are way off most of the time.
2. You don't have a focal point. Your curated look must not lack direction and focus. There must be an eye catching feature . . . A fireplace, elaborate wall art, or a conspicuous decor item like a mask on the wall.
3. You forget the room is not just a showroom. Because you have to live in and feel snug and comfortable in the space, let utility and functionality inform the way you decorate. Think of how you intend to use the interior space first. This way, you'll chose items that will help you pull everything in the space together.
4. You tend to be inconsistent. An abrupt change in style of the adjoining spaces or rooms will make the interior look disjointed and disconnected. Ensure there is a smooth flow; each room must complement one another. Eclecticism must be reflected throughout the home's interior, subtly or elaborately.
5. You don't have a unifying colour. There must be one throughout the theme which pulls the whole eclectic look together. This is also referred to as your "go to" colour and serves as an equalizer.
6. Your overall look lacks balance and your scale is wrong. There must be a balance in symmetry and scale and the total look must look organised. It is true that with the eclecticism, there are different styles from different eras just as textures vary but this is no reason to sacrifice organisation for diversity.
7. You believe anything goes because it's meant to be eclectic. Not so. Avoid making everything look like a random choice. It tends to create a busy and cluttered look. Not only that, it will be distracting. Rather, make sure you don't have too many contrasting styles in one space as it may end up looking like a mess.
8. You are too reserved. With eclectic interior decoration, you don't have to be conservative. Fact is that you can't! This interior style is made up of a good number of decor items, fabrics, textures and patterns. If for instance you have a plain sofa and chairs, 'eclectic-up' with accent items like colourful throw pillows, paintings, area rugs, objects d'art, accent chairs, animal prints, and tapestry.
9. You compare hues and tones as a line-up on the walls. Avoid sampling colours you like on the wall lest you get confused and become indecisive. Rather, sample the colours you like on individual boards and look at them individually before making your final choice.
If you can try to avoid these common mistakes and use them to guide your interior design task, you will successfully bring the eclectic style together and create a wonderful look.
Eclectic style, when it's well conceived, highlights your bold and unique taste and broadcasts the confidence you have in your own special interior decor style.


I had just come off night shift and when I got the call I just could not stop crying.
Leaving me with more questions than answers..
I am not sure how the hell I could owe them money during this period as I was working..
Apparently i owe them 2000 during 2016-2017 which is total crap considering i reported properly.
I cant afford to pay for something that i dont have to its hard enough to pay to live as it is.
The government needs to pull their heads out and stop taking money from the less fortunate.
2 year battle; it's no longer just about me.
The initial debt amount was sent just before Christmas, due at the end of December 2016.
Many others received notices at that time.
No 'human' consideration was shown in the timing of these demand letters. It was extremely stressful.
I was initially told I owed close to $13,000.
Then the compliance line operator worked out that it was $2,300 - mind you, this was after I produced my payslips and had to chase them up to review them!
email received to my mum as she was dealing with my issues at the time, home detention, and stating i had a 3600 debt, what a joke as i couldn't work and was on home D, and the was subsequently suspended from centrelink because i started WORK again the idiots.
Recieved a debt from 2013-14. Have not been on Centrelink for years!
Recieved a letter in the mail requesting payslips from various work I had during 2013-14 from when I was paid Newstart in between jobs.
Extremely stressful as I have not been on Centrelink for 4 years!
I can't understand how they could figure this out when I report my earnings.
I thought the text messages were a scam!
Got told my debt was being put on hold for 3 months whilst being ReAssessed.
I then got text messages from Probe Group which I deregarded as I thought they were a scam.
I initially had no idea about this debt as I had received no communications from Centrelink, even though the lady on the phone assured me they had sent 8 letters in the post (somehow I doubt that).
Whilst in medical school I received Austudy.
Additionally I worked on a casual basis as I needed to be able to pay for books, fuel, bills etc. as well as rent & food.
My income was declared, an exorbitant amount of tax was paid & I finally managed to graduate in December 2014.
All of us have a vote, please SPEAK UP!
On the night before we moved house, the online letter arrived for my daughter.
The timing has added immeasurably to the stress.
As her nominee I am dealing with this insanely confusing and totally unexpected issue.
Confused to be told I owed more than I was paid!
Stressed. Was in a frenzy trying to get payslips from Dec 2012- Jan 2013.
I was only on Centrelink for three payments to get me through the Christmas holidays as I work in a career that follows the school terms.
On the first day of a much awaited holiday I received three letters from Centrelink: one notifying me of a $4237 debt, one warning me to pay it, and one notifying me of punitive interest.
After the end of an abusive relationship I had to quit study for mental health reasons and look for work to make up for lost income and the increase in expenses from no longer sharing.
Processing the change from youth allowance to Newstart was a mess and I've ended up on the hook for 6 weeks of pay.
Six months ago I received a letter in the mail advising me that I needed to update my details with the ATO about my employment while recieving youth allowance.
I had applied for youth allowance while studying at university, and recieved payments for about three years while I worked part time.
BEEN CRYING MYSELF TO SLEEP EVERY NIGHT BECAUSE IM STILL STUDYING AND STRESSED. I'VE BEEN WORKING LOTS OF JOBS YES BUT I STILL ATTENDED UNIVERSITY FULL TIME AND PARENTS ARE NOT MEETING THE INCOME FOR ME TO NOT RECEIVE YOUTH ALLOWANCE.
Some weeks I earned under threshold and some weeks I earned over threshold.
Was issued with a debt notice (dated Dec 2016) but did not receive it as my address had changed and I hadn't been on Centrelink for around 2 years (even though my address was up to date with medicare and ATO).
When I eventually received it, it was for 2014-15 FY and around $5750 (including a late fee).
The debt and lack of information had a large impact on my stress levels.
I AM NOT EVEN WITH CENTRELINK ANYMORE.
I got a call last week telling me that I had 12 days to report all my payslips to them otherwise they will use the ATO and that it would most likely result in a debt.
Suffer from depression under financial pressure.
No cent received from Centerlink is worth the debt they claim you owe them come years down the track.
Killing me inside and out.
I have both Bipolar and Borderline personality disorder.
I received a letter about 8 months ago saying that the figures that I had reported did not match up with the figures they received from ATO.
The figures were from when I started a new job up until my partner and I moved in together.


text:
package i2am.Filtering;

import org.apache.storm.redis.common.config.JedisClusterConfig;
import org.apache.storm.redis.common.container.JedisCommandsContainerBuilder;
import org.apache.storm.redis.common.container.JedisCommandsInstanceContainer;
import org.apache.storm.task.OutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.topology.base.BaseRichBolt;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Tuple;
import org.apache.storm.tuple.Values;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import redis.clients.jedis.JedisCommands;

import java.util.ArrayList;
import java.util.List;
import java.util.Map;

/**
 * Created by sbpark on 2017-11-30.
 */
public class NoiseRecKalmanFilteringBolt extends BaseRichBolt{
    private double x = 0, R = 0.5, P = 1000, Q;
    private int windowSize = 32;
    List<Double> inputData = new ArrayList<Double>();

    /* RedisKey */
    private String redisKey = null;
    private String QValueKey = "Q_val";

    /* Jedis */
    private transient JedisCommandsInstanceContainer jedisContainer;
    private JedisClusterConfig jedisClusterConfig;
    private JedisCommands jedisCommands = null;

    private OutputCollector collector;

    /* Logger */
    private final static Logger logger = LoggerFactory.getLogger(NoiseRecKalmanFilteringBolt.class);

    public NoiseRecKalmanFilteringBolt(String redisKey, JedisClusterConfig jedisClusterConfig){
        this.redisKey = redisKey;
        this.jedisClusterConfig = jedisClusterConfig;
    }

    @Override
    public void prepare(Map stormConf, TopologyContext context, OutputCollector collector) {
        this.collector = collector;

        /* Get Q value from user(redis) */
        if (jedisClusterConfig != null) {
            this.jedisContainer = JedisCommandsContainerBuilder.build(jedisClusterConfig);
            jedisCommands = jedisContainer.getInstance();
        } else {
            throw new IllegalArgumentException("Jedis configuration not found");
        }

        Q = Double.parseDouble(jedisCommands.hget(redisKey, QValueKey));
    }

    @Override
    public void execute(Tuple input) {
        double x_present = Double.parseDouble(input.getString(0));
        double x_next, P_next, K, z, H = 1;

        if(inputData.size() < windowSize) {     // 다음 R 계산을 위해 차곡차곡 담는다
            inputData.add(x_present);
        }

        x_next = x;
        P_next = P+ Q; 	//Q: white noise --> by environment
        K = P_next*H / (H*H*P_next + R);	//kalman gain

        z = x_present;
        x = x_next + K*(z - H*x_next);		// filtered data
        P = (1 - K*H)*P_next;

        if(inputData.size() == windowSize) {    // calculate R
            // double list to double array
            double[] inputDataArray = new double[windowSize];
            for(int i=0; i< windowSize; i++) {
                inputDataArray[i] = inputData.get(i);
            }

            // calculate R
            RCalculator rCalculator = new RCalculator();
            R = rCalculator.calcR(inputDataArray, windowSize);

            // clear list
            inputData.clear();
        }

        collector.emit(new Values(Double.toString(x)));

    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer declarer) {
        declarer.declare(new Fields("data"));
    }
}

class RCalculator{

    public double calcR(double[] DataSet, int winSize){	//sensor and original
        int f = winSize/4;
        double resultR;
        double sum = 0.0;
        double[] FWT, inverseFWT;
        // Estimation of the raw data (= w/o noise)
        FWT = Daubechies_forward_FWT_1d(winSize, DataSet);

        // extract raw data
        for(int i=0; i<winSize; i++){
            if(i<f){
                continue;
            }else{
                FWT[i] = 0;
            }
        }

        inverseFWT = Daubechies_inverse_FWT_1d(winSize, FWT);

        // Mean Square Error
        //DataSet - fwt
        for(int i=0; i< DataSet.length; i++){
            //abs(dist)
            double tmp = DataSet[i] - inverseFWT[i];
            if(tmp<0) tmp *= -1;

            sum += tmp;

            //estimate Q value
        }
        resultR = sum/(DataSet.length-1);
        resultR = Math.sqrt(resultR);

        return resultR;
    }

    public double[] Daubechies_forward_FWT_1d (int n, double[] DataSet)
    {
        double[] fastWaveletTransform = new double[n];
        int m;
        int k;

        k = logB(n, 2);

        for (m = 0 ;  m < n;  m++) fastWaveletTransform[m] = DataSet[m];

        for (m = k-1; m >= 0 ; m--)
            fastWaveletTransform = Daubechies_forward_pass_1d (m+1, fastWaveletTransform);

        return fastWaveletTransform;
    }

    /*--------------------------------------------------------------------------*/
    public double[] Daubechies_forward_pass_1d (int n, double[] fastWaveletTransform)
    {
        int i;
        int npts;
        double[] a = null;
        double[] c = null;

        final double[] h = new double[]{ 0.683013, 1.18301, 0.316987, -0.183013 };//const double

        npts = powerof2(n);

        a = new double[npts/2];
        c = new double[npts/2];

        for (i = 0;  i < npts/2;  i++)
        {
            a[i] = (h[0]*fastWaveletTransform[(2*i)%npts] + h[1]*fastWaveletTransform[(2*i+1)%npts] + h[2]*fastWaveletTransform[(2*i+2)%npts] + h[3]*fastWaveletTransform[(2*i+3)%npts]) / 2.0;
            c[i] = (h[3]*fastWaveletTransform[(2*i)%npts] - h[2]*fastWaveletTransform[(2*i+1)%npts] + h[1]*fastWaveletTransform[(2*i+2)%npts] - h[0]*fastWaveletTransform[(2*i+3)%npts]) / 2.0;
        }

        for (i = 0;  i < npts/2;  i++)
        {
            fastWaveletTransform[i] = a[i];
            fastWaveletTransform[i + npts/2] = c[i];
        }

        a = null;
        c = null;

        return fastWaveletTransform;
    }
	/*---------------------------------------------------------------------------*/
	/*
	  Calculate the Daubechies inverse fast wavelet transform in 1-dimension.
	*/
    //inverse

    public double[] Daubechies_inverse_FWT_1d (int n, double[] DataSet_dwt_daubechies)/*(int n, float * s)*/
    {
        double[] inverseFastWaveletTransform = new double[n];
        int m;
        int k;

        k = logB(n, 2);

        for (m = 0 ;  m < n;  m++)
            inverseFastWaveletTransform[m] = DataSet_dwt_daubechies[m];

        for (m = 1;  m <=k;  m++)
            inverseFastWaveletTransform = Daubechies_inverse_pass_1d (m, inverseFastWaveletTransform);

        return inverseFastWaveletTransform;
    }

	/*---------------------------------------------------------------------------*/

    public double[] Daubechies_inverse_pass_1d (int n, double[] inverseFastWaveletTransform)/*(int n, float * s)*/
    {
        int i;
        int nptsd2;
        int npts;
        double[] temp = null;
        double[] c = null;
        final double[] h = new double[]{ 0.683013, 1.18301, 0.316987, -0.183013 };//const double

        npts = powerof2 (n);
        nptsd2 = npts/2;
        c = new double[nptsd2];
        System.arraycopy(inverseFastWaveletTransform, nptsd2, c, 0, nptsd2);

        temp = new double[npts];

        for (i = 0;  i < nptsd2;  i++)
        {
            temp[2*i] = h[2]*inverseFastWaveletTransform[(i-1+nptsd2)%nptsd2] + h[1]*c[(i-1+nptsd2)%nptsd2] + h[0]*inverseFastWaveletTransform[i] + h[3]*c[i];
            temp[2*i+1] = h[3]*inverseFastWaveletTransform[(i-1+nptsd2)%nptsd2] - h[0]*c[(i-1+nptsd2)%nptsd2] + h[1]*inverseFastWaveletTransform[i] - h[2]*c[i];
        }

        for (i = 0;  i < npts;  i++)
            inverseFastWaveletTransform[i] = temp[i];

        temp = null;

        return inverseFastWaveletTransform;
    }

    /*******************************************************************************/
    int powerof2(int n)
    {
        int i, j;

        j = 1;

        if (n > 0)
            for (i = 0;  i < n;  i++)
                j *= 2;
        else if (n < 0)
            j = 0;

        return (j);
    }

    /*******************************************************************************/

    int logB(int x, int b)
    {
        double value, base, result;

        value = Math.log(x);
        base = Math.log(b);
        result = (value / base)+0.5; /*double/double 값이라 소수점 버림 발생하여 반올림 해줌.*/

        return (int)result;
    }
}

redpajama_set_name: RedPajamaGithub


text:
Ariana	 March 12, 2018 Drinks
Girl's Night In with Campari Red Diaries
Being a young, 20-something year old woman in NYC – the world is my oyster. But there's nothing like a girl's night in. I love setting up charcuterie boards, decadent treats, and sophisticated cocktails. And tonight I'm in the mood for something red. A classic Negroni will do.
What's a Girl's Night In without something thrilling to watch? To accompany our festive night in, is the latest in Campari Red Diaries, Campari's annual short film that proves that "every cocktail tells a story." This year's installation stars Zoe Saldana and some incredible-sounding cocktails.
Titled The Legend of Red Hand, the film follows Zoe's character, Mia Parc, in her pursuit of the perfect cocktail, which in this film is created by the mysterious "Red Hand." This short film follows the international success of the 2017 edition of Campari Red Diaries, which featured actor Clive Owen as a notorious bartender in a film noir titled The Killer in Red. Legend of Red Hand is set in Milan (where Campari was created), and is directed by Stefano Sollima, known for his work in Italy.
The short film is very thrilling as it shows Zoe Saldana on a mission to discover the identity of "Red Hand" in a speakeasy-style club in Milan, which takes her on a journey around the world to discover the "Red Hands" of cities such as Buenos Aires, Berlin, London and even right here in NYC.
The "Red Hand" of NYC is Leo Robitschek, the beverage director of the NoMad, which just opened an outpost in LA. His cocktail – the Jitney Negroni – was created for Campari's Legend of the Red Hand and is on the menu at the NoMad LA.
Jitney Negroni
Created by Leo Robitschek for Campari Red Diaries and available at NoMad Hotel Los Angeles
¾ oz. Campari
¾ oz. Sombra Mezcal
½ oz. Cinzano Extra Dry Vermouth infused with Coffee*
½ oz. Cinzano Bianco Vermouth
2 dashes of Absinthe
*Coffee-infused Vermouth: Macerate 5 oz. of coarsely ground coffee in 750 ml of Vermouth for 10 minutes. Strain and refrigerate.
Method: Combine all the ingredients in a mixing glass, add ice, stir and strain into a rocks glass with a large ice cube. Garnish with a grapefruit twist.
Not into mezcal? Here's a recipe for a classic Negroni:
1 oz (1 part) Gin
1 oz (1 part) Campari
1 oz (1 part) Sweet red Vermouth
Method: Stir into Old Fashioned glass over ice, garnish with orange peel, and serve.
Which take on the Negroni will you be making for your girl's night?
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