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

Converting black and white facial sketches into realistic colored photos is one of the most interesting and practical issues in the field of image processing and machine vision that have been offered in various models in recent years. The sketch is referred to as the first drawing or art design that has the basic features of a face. In sketches, the details of the face, including the face's outline and color are rendered inaccurate and gray-scale.

Facial sketches can be classified into three types \cite{barbadekar2016survey}: 1) viewed sketches, 2) forensic sketches, and 3) composite sketches. Viewed sketches are drawn by the human hand while viewing the photograph. Forensic sketches are facial sketches drawn by artists based on the description provided by a third-party person. Composite sketches are facial sketches created using software kits that allow an operator to select different facial components.

Forensic and composite sketches are usually used for face recognition.
Face recognition from sketches has been a challenging task for a while and different methods have been developed for it \cite{klum2013sketch,wang2008face,tang2004face,tang2003face}.
There are lots of difficulties in sketch-based face recognition since photographs and sketches belong to two different modalities \cite{barbadekar2016survey} with completely different structural and appearance features. Moreover, the patches drawn by a pencil on paper have different textures from the human skin captured in a photo. So, it will not be easy to match sketches with realistic photos. One solution to these difficulties is to convert the sketch to photograph or vice versa and then compare the faces in the same space.

During the past decades, several methods have been proposed for creating colored realistic images from sketches. Some of these models just add color to the input image while the others follow a two-step model in which the input sketch is first translated into a descriptive feature vector and then the final image is synthesized using this vector.

Recently, GAN models have shown great performance in creating real face photos \cite{karras2019style,karras2017progressive}. In this paper, we propose a general framework for generating high resolution and high-quality colorful images from the face sketches. In this model, a face generating GAN is used for converting an intermediate latent vector to the final photo. The overall task of the other components of the proposed model is to find the most appropriate latent vector. To do so, the high-level characteristics of the input face sketch are first extracted in the form of a feature vector which is then mapped into the latent space of the face generating GAN. After this initialization step, an optimization step is adopted to increase the similarity of the synthesized photo to the sketch. This step iteratively adjusts the GAN's latent vector, based on several defined optimization criteria to preserve the quality and fidelity of the produced face photo. It should be noted that the proposed model does not need to be trained on paired sketch-photo data and the input sketch does not need to belong to the training dataset of the model. The experimental results show the superiority of the proposed model both in qualitative and quantitative measures.

In Section \ref{sec:related_works}, we mention some related works. After that, in Section \ref{sec:Proposed_Framework}, we explain the proposed method to convert a face sketch to a real photo. The experimental results are reported in Section \ref{sec:Experiments}. Finally, Section \ref{sec:conclusion} concludes this paper.

\section{Related Works}
\label{sec:related_works}

The proposed models for sketch to photo conversion can be divided into two main groups: before-GANs (or \emph{shallow learning}-based) methods and GANs-based (or \emph{deep learning}-based) methods \cite{zhang2019cross}, the latter utilizes deep neural networks for image synthesis while the former employs other machine learning techniques. In the following subsections, the trends and prominent works of each category are reviewed.

\subsection{Before-GANs methods}
\label{subsec:before_GANs}

The sketch to photo translation methods before GANs can be categorized based on their model construction techniques to: 1) subspace learning-based approaches, 2) sparse representation-based approaches, and 3) Bayesian inference-based approaches \cite{wang2014comprehensive}.

Subspace learning refers to the technique of finding a subspace $R^m$ embedded in a high dimensional space $R^n$ ($n > m$). As examples of this approach, \cite{zhang2011face} propose a model based on support vector regression which handles the difficulty of losing vital details and \cite{wang2013transductive} present a method which incorporates the given test samples into the learning process and optimizes the performance on these test samples.

Sparse representation is a decomposition technique that represents a signal $y_{sig} \in R^n$ into a linear combination of basic signals $D_i \in R^n (i = 1, ... , k)$, weighted by nonzero coefficients. As a sparse representation-based method, \cite{wang2011face} propose a multi-dictionary sparse representation based model for high-quality sketch-photo synthesis that uses locally linear embedding to estimate an initial sketch or photo. \cite{gao2012face} propose another automatic sketch synthesis algorithm based on sparse representation. Their method works at patch level and is made out of selecting sparse neighbors for an underlying estimation of pseudo-images and sparse-representation-based improvement for additional improving the image quality.

In Bayesian inference-based approaches the output is obtained from Bayes' theorem and the maximum a posteriori (MAP) decision rule. As a Bayesian inference-based method, \cite{peng2015multiple} propose a multiple representation-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch. Then, Markov networks are utilized to take advantage of the relationships between adjacent patches.

\subsection{GANs-based methods}

\label{subsec:GAN_based}

With the invention of GANs \cite{goodfellow2014generative}, generative models have been successfully employed in many image generation and image to image translation tasks. Recently, several GANs-based methods have been proposed for sketch to photo translation which can be categorized as 1) image to image translation methods, 2) face photo-sketch synthesis methods, and 3) methods using pre-trained GANs.

\textbf{Image to image translation methods:} The image to image translation methods are general models and encompass techniques for any cross-domain image translation including face photo-sketch conversion. Two main branches of this category are the supervised and unsupervised methods \cite{yongxinsurvey}. The goal of the first branch is to learn the mapping between an input image and an output image using a training set of aligned image pairs \cite{yongxinsurvey}. \cite{isola2017image} proposed the supervised Pix2Pix model for several tasks such as labels to street scenes and image colorization.

In unsupervised image to image translation, source and target image sets are completely independent with no paired examples between the two domains. Because acquiring paired training data is expensive or sometimes impossible \cite{yongxinsurvey}, \cite{zhu2017unpaired} proposed CycleGAN for the unsupervised image to image translation tasks which have been shown to be successful in many applications where paired data is not available. However, failures occur due to the distribution imposed by the training dataset. Similar to CycleGAN, \cite{yi2017dualgan} proposed unsupervised DualGAN method which can generate results comparable to or even better than the results of supervised Pix2Pix \cite{isola2017image} model. In other work, \cite{wang2018high} proposed a method based on the CycleGAN idea and employed multi adversarial networks for facial photo-sketch synthesis. In another study, \cite{chao2019high} presented a high fidelity face sketch-photo synthesis using a deep neural U-net as generator and Patch-GAN with residual blocks as discriminator.

DRIT++ \cite{lee2020drit++} is another image-to-image translation model that generates diverse outputs without paired training images. As stated in this work, generating multiple possible outputs from a single input image is one of the main challenges of the image-to-image translation task. So, this model disentangles the latent space into a content space and a domain-specific attribute space. The former encodes common information between domains, and the latter can model the distinct varieties given the same content. Also, a content discriminator is applied to ease the representation disentanglement.
Moreover, Council-GAN \cite{nizan2020breaking} as an image-to-image translation framework, instead of using a cycle, is based on collegiality between GANs. Precisely, rather than utilizing a pair of generator/discriminator architecture, it uses a group of triplets (one generator and two discriminators for each member), i.e. the council, and improves the variety of the generators' results. This idea makes domain transfer more stable and diverse.

\textbf{Face photo-sketch synthesis methods:} In these methods, the facial sketch is directly translated into the corresponding real face photo or vice versa.  The methods of this category concentrate only on the facial sketch and photo modalities. \cite{osahor2020quality} propose a GAN which synthesizes multiple outputs from the input sketch with different attributes like hair color. They use multiple loss functions to preserve identity and different attributes. Similarly, \cite{lin2020identity} propose an adversarial model for sketch-photo synthesis, which contains one generator and two discriminators for ensuring image quality and identity preservation. \cite{zheng2019feature} propose a model for both image to sketch and sketch to image conversion that uses Cycle-GAN as its baseline. They use a feature auto-encoder to refine the synthesis results. \cite{zhu2019deep} propose a framework for bidirectional photo-sketch mapping. They use a middle latent domain $Z$ between photo and sketch domains, and multiple loss functions to learn mappings.

Moreover, recently, \cite{yu2020toward} proposed Composition-Aided Generative Adversarial Network (CA-GAN). In this model, the paired inputs consisting of a face photo/sketch and the corresponding pixel-wise face labeling mask are utilized to generate the portrait. Furthermore, an improved reconstruction loss and a perceptual loss based on a pre-trained face recognition network are used. Finally, the developed form of CA-GAN named stacked CA-GANs (SCA-GAN) is presented for refinement. As this framework has used both the image appearance space and structural composition space, the generated face photos and sketches are natural. Also, \cite{fang2020identity} proposed an Identity-Aware Cycle Generative Adversarial Network (IACycleGAN) which concentrated on both face photo-sketch synthesis and recognition. So, to this purpose recognition networks are utilized in this model and are first fine-tuned by the generated images from CycleGAN, and also a perceptual loss is used to regularize the performance of the IACycleGAN.

Also, Chen et al. in \cite{chen2020deepfacedrawing} proposed the DeepFaceDrawing model which can translate hand-drawn face sketches to real photos. They learned feature embedding of key face components and used a network to map the embedded features to the real photo. Furthermore, the DeepFacePencil \cite{li2020deepfacepencil} is a sketch-based face image synthesis framework based on hand-drawn sketches. The dual generator training strategy and spatial attention pooling (SAP) module are used in this model. The SAP module adjusts the spatially varying balance among the image naturalness and the conformance within the sketch and the synthesized image.

\textbf{Methods using pre-trained GANs:} In these methods, an existing model previously trained on another dataset with the ability of generating high-quality face images is used to translate a sketch to the corresponding photo. In this approach, first, the input sketch is mapped to the network's latent space and then changes are applied to make the generated image closer to the input sketch. The main advantages of this approach are that creating the sketch to photo model does not require heavy training on large datasets and the model can be easily adapted to changes in the objective (loss) function. This approach has been used in face editing \cite{collins2020editing,shen2020interpreting} and text-to-image translation tasks \cite{wang2020faces} .

As an example, Pixel2style2pixel \cite{richardson2021encoding} is introduced based on the pretrained StyleGAN generator. It includes an encoder architecture and its main goal is to encode an arbitrary image directly into the intermediate latent space of StyleGAN. Subsequently, latent space manipulation is possible to edit the real image. The Pixel2style2pixel model is used in the sketch to photo conversion with the difference that the utilized sketches are incomplete freehand.

Similar to Pixel2style2pixel, lots of works have focused on StyleGAN and intend to use the power of this model for better image synthesis and manipulation. For this purpose, various methods have been proposed to invert an image into StyleGAN's latent space. For example, \cite{abdal2019image2stylegan,karras2020analyzing} proposed methods to encode an input image into the latent space of StyleGAN. \cite{abdal2020image2stylegan++} developed previous methods and used them for image editing. Also, \cite{tewari2020pie} used a hierarchical optimization to embed an image-in-the-wild to the styleGAN's latent space and then performed editing via resultant disentangled representation. Moreover, InterFaceGAN\cite{shen2020interfacegan,saha2021loho,zhu2020domain} utilize StyleGAN's inversion methods to manipulate various facial attributes such as smile, hair, and glasses. Furthermore, some other methods \cite{lewis2021tryongan,zhu2020domain} finetune StyleGAN in non-face dataset and use inversion methods due to their purposes.

\section{The Proposed Framework}
\label{sec:Proposed_Framework}
Our proposed model to generate a realistic photo for a target person's face is given in Fig. \ref{fig:block1}. As stated before, it is assumed that a sketch portrait of a person is provided and the aim is to convert this sketch to a photo-realistic image of the person. The overall process is organized into two main steps, namely, \emph{initialization} and \emph{fine-tuning} steps. The model, utilizes a face-generating sub-module mapping the latent space vectors, $w$, to real high-quality face images. The goal of the first step is to find an initial representation for the input sketch in the latent space of the face-generator module. This initial point is fed into the face-generator to create the initial image of the target person. The second step of the model is an optimization step that iteratively adjusts the initial image based on the high-level features extracted from the input sketch and the prior knowledge about realistic face images. The final output of this step is an artifact-free real face image similar to the input sketch. The details of all components of the proposed model are described in the following subsections.

\begin{figure*}
    \centering
    \includegraphics[width=\linewidth]{Images/block_diag.png}
    \caption{Block diagram of the proposed model.}
    \label{fig:block1}
\end{figure*}

\subsection{Face Generating Module}
One of the components of our proposed model is a generative model (\emph{FaceGAN}) with its own latent space which generates face images in high diversity and high quality. The face reconstruction task is then defined as finding the best match of the target face by searching the latent space of this face generator. The quality of the synthesized faces and their closeness to the target person is limited by the quality and diversity of the faces constructed by FaceGAN.

Any face generator with latent space $Z$ or intermediate latent space $W$ can play the role of the FaceGAN part of our model. There are lots of pre-trained models for this purpose. Progressive Growing GAN \cite{karras2017progressive} and Style-based Generative Adversarial Network (StyleGAN) \cite{karras2019style} are two such models.
StyleGAN is an extension to the GAN architecture that proposes large changes to the generator model, including the use of a mapping network to map points in the latent space to an intermediate latent space and the use of the intermediate latent space to control style at each point in the generator model. The resulting model not only does generate impressively photo-realistic high-quality photos of faces, but it also offers control over the style of the generated images through varying the style vectors.

We have used StyleGAN in our proposed framework which consists of two main subnetworks to map $1 \times 512$ latent noise vectors to $18 \times 512$ intermediate latent codes ($W$) and the intermediate latent codes to realistic face images. Here, we directly work on the intermediate latent space as it is closer to the high-level features of face.  Our experiments show that for any given real face photo, the StyleGAN is capable of generating a similar image with very high fidelity. However, the large number of dimensions of the intermediate latent space and the locality of the changes make the search process complicated.

\subsection{Initialization Module}
\label{subsec:init_module}
In the initialization step of the proposed model, the input portrait sketch is mapped to the most similar vector in the intermediate latent space of FaceGAN. It would be ideal if the initialization step could implement the inverse function of FaceGAN, generating an intermediate latent vector corresponding to the photo-realistic image of the given sketch. As learning this reverse mapping as a single step is a very hard and complex task, we chose to implement the initialization module in two steps. In this setting, the input sketch is first translated into a high-level feature vector ($f$) and then this feature vector is mapped into the intermediate latent space of FaceGAN. The initialization method is trained to find the best estimation of the latent vector of the input sketch.

Regarding the feature extraction step of the initialization phase, our studies show that face recognition models such as FaceNet \cite{schroff2015facenet}, VGG16 \cite{simonyan2014very_VGG16}, VGGFace \cite{parkhi2015deep_VGGFACE}, and ResNet \cite{cao2018vggface2} are good choices for this task. While these models are trained on realistic photos, most of the features extracted by these models are color-independent and they can be successfully used to provide a high-level representation of the input colorless sketches. In this paper, we use VGGFace as it provided better performance in the experiments. See Section \ref{Exp:init_comp} for a comparison of the results of all feature extraction models.

A neural network (called F2W) is then trained to map the extracted feature vector to a vector in the latent space. To train F2W, a large number of images were randomly generated by FaceGAN. For each image, the $w$ vector was also recorded. The feature vectors of all images were extracted by VGGFace resulting in a data set of $(w,f)$  pairs. F2W is then trained with this data. We tested a number of different architectures for F2W. Finally, a simple fully connected network with two input and output layers was found to provide the best results.

\subsection{Optimization Module}
The initialization step generates a real face photo resembling the main face characteristics of the input sketch. After that, an iterative optimization procedure can be employed to improve the quality of the synthesized image by removing artifacts, capturing more structural features of the input sketch, and enforcing extra features like skin color. Here, we emphasize making the produced photo more similar to the corresponding sketch in terms of facial features while keeping it free from artifacts. However, the proposed model is completely flexible and other sub-goals can be added straightforwardly.

The optimization task of the proposed model is formulated as minimizing the overall loss function $L(w)$ where $w$ is the intermediate latent vector of the FaceGAN module and $L(w)$ is sum of a set of loss functions each corresponding to a sub-goal of the refinement step.

As stated before, in this paper, we consider diverse facial features capture and artifact removal sub-goals. As shown in the optimization module in Fig. \ref{fig:block1}, we have one manifold preservation module to eliminate the image artifacts and some face appearance modules to minimize the distance between various facial feature vectors of the sketch and the generated colorful image. So, the goal function of the model can be written as
\begin{equation}
\begin{aligned}
\label{equ:equ1}
    L(w)=L_1^{App}+...+L_k^{App}+L^M
\end{aligned}
\end{equation}
where $L_i^{App}$ denotes the loss related to the $i$th face appearance module and $L^M$ gives the loss of the manifold preservation module.

At each optimization step, the latent vector $w$ is updated using a gradient descent algorithm so that the generated image continuously gets closer to the input sketch.

Different parts of the optimization module of the proposed model are explained in the following subsections.

\subsubsection{Face Appearance Modules}

The most desired property of the synthesized face photo is to have facial features similar to those of the target person. To achieve this goal, we first extract the high-level feature vectors of the provided sketch and the generated image and then define the loss function as the discrepancy between these two vectors. Pre-trained face recognizers are good choices for facial feature extraction as their performance greatly depends on the feature sets they use. While most of these features are common in different models, the features extracted and learned by each face recognition model depend on the training dataset, training algorithms and the model's architecture. So, as our experimental results show, using a diverse set of feature vectors obtained from different face recognition models improves the quality of the generated faces.

As shown in Fig. \ref{fig:block2}, each feature extractor is applied to both the synthesized image and the sketch and the appearance loss is calculated as the Euclidean distance of the corresponding feature vectors as follows
\begin{equation}
\label{equ:equ2}
\begin{aligned}
    L_i^{App}=||FR_i(syn)-FR_i(sketch)||_2\\
\end{aligned}
\end{equation}
where $FR_i(I)$ is the feature vector of image $I$ given by the $i$th feature extractor.

In this paper, we have studied the feature vectors of some state-of-the-art face recognition models including VGGFACE \cite{parkhi2015deep_VGGFACE} and VGGFACE2 \cite{cao2018vggface2} as well as classification networks like VGG16 \cite{simonyan2014very_VGG16}. The results are reported and discussed in Section \ref{Exp:opt_comp}.

\begin{figure}
    \centering
    \includegraphics[width=\linewidth]{Images/face_app.png}
    \caption{The structure of a face appearance module.}
    \label{fig:block2}
\end{figure}

\subsubsection{Manifold Preservation Module}

The goal of the FaceGAN is to map an intermediate latent vector $w$ to a high-resolution realistic face photo. However, not all points of this latent space are converted to clear face images; many input points result in faces with different kinds of artifacts or even completely non-face images. The non-face photos are penalized by the appearance modules as their feature vectors are far from those of the input sketches but it is still possible to have face photos with frequent small artifacts. So, we have added another module to our proposed model to keep $w$s of the low-dimensional subspace of the latent space whose points produce artifact-free face photos and hence we call it the \emph{manifold-preservation} module. As the experimental results show, the vectors on this manifold generate faces with proper structural and appearance characteristics while the artifacts of the image increase as we get away from this manifold.

As stated before, we need to quantify the amount of artifacts present in a produced image. Here, we train a convolutional neural network, called HOGFD, which generates \emph{faceness} scores for each synthesized image. This score evaluates the goodness of the image based on its closeness to a real face photo. The output of HOGFD is converted to the manifold-preservation loss as follows:
\begin{equation}
\label{equ:equ3}
\begin{aligned}
    L^{M}(syn)=max\_score-HOGFD(syn)\\
\end{aligned}
\end{equation}
where $syn$ denotes the synthesized image and $max\_score$ is the highest scores of $HOGFD$ network for the set of training face images. The structure of the proposed manifold preservation module is depicted in Fig. \ref{fig:block3}. The $f_m$ in this figure shows the mathematical subtraction stated in Eqn. \ref{equ:equ3}.

HOGFD network is trained using the HOG-based face detector proposed by \cite{dalal2005histograms} and \cite{dlib09}. To this end, a hundred thousand of generated images by FaceGAN are selected. The output of the HOG-based face detector is calculated for all these images as the faceness score and then HOGFD network is trained to estimate this score for the input images.
The HOGFD network has four 3 x 3 convolutional layers with 16, 32, 64, and 128 filters and stride 1, each followed by a max pooling layer. Three fully connected layers with 16, 4, and one neuron exist on the top of the network to do the regression task. Batch normalization is used after each convolution layer and first fully connected layer to make the network faster and more stable. A dropout layer with probability 0.5 is used to avoid overfitting and Relu activation used as non-linear activation function for all layers.

\begin{figure}
    \centering
    \includegraphics[width=\linewidth]{Images/man_pre.png}
    \caption{Manifold preservation module}
    \label{fig:block3}
\end{figure}

\section{Experiments}
\label{sec:Experiments}

In this section, we conduct extensive experiments to verify the effectiveness of the proposed method. We compare our method qualitatively and quantitatively with state-of-the-art synthesis methods. We use the AR dataset \cite{martinez1998ar} part of the popular CUHK Face Sketch Database (CUFS), which contains 123 images including 70 males and 53 females in our tests. All photos of this dataset are captured under well-controlled conditions along with the artist-drawn sketch of each photo.  \cite{wang2008face}.

\subsection{Component Analysis}
The experiments of this section investigate the role of each component of our proposed framework. At first, the power of the initialization component (F2W network) in mapping the initial image to a vector in the latent space with similar face characteristics is studied. After that, the results of the optimization step with different loss functions are presented and discussed. Finally, the scores that HOGFD network assigns to a number of face photos with different qualities are reported to show the important role of this component in guiding the search toward high-quality faces.

\subsubsection{Initialization Component}
\label{Exp:init_comp}
In Fig. \ref{fig:F2W_Res}, the F2W network is applied to six colored images and their corresponding sketches obtained by \cite{wang2018high} model. The sketches shown in row (d) are corresponding to the colored images of row (a). Rows (b) and (c) respectively show the results of mapping the colored images and sketches. The images are first mapped into the latent space of the FaceGAN module and then the corresponding photos are generated by FaceGAN. As can be seen in this figure, the mapping preserves the high-level features (like sex, mouth state, hair type) of the faces in both cases. However, there are still noticeable differences that are addressed in the optimization step.

\begin{figure}
    \centering
    \includegraphics[width=\linewidth]{Images/init_modu.png}
    \caption{Initialization module and F2W network: (a) initial colored images, (d) corresponding sketches (b) result of F2W network applied to the colored images, (c) result of F2W network applied to the sketches. }
    \label{fig:F2W_Res}
\end{figure}

The above performance is achieved by training the F2W network on a large dataset of $(f,w)$ pairs where $w$ is the latent vector and $f$ is the feature vector of the face image generated by FaceGAN from $w$. Fig. \ref{fig:F2W_stepbystep} shows the progress of the F2W network during its training. In this figure, the mapping results of the F2W network for a set of test images are shown after 20, 40, 80, 160, 320, 620, and 1000 steps of training. It is clear how the network's output moves from noisy meaningless images at the early stages to images very similar to the input images at the final stages.

\begin{figure}[hbt!]
    \centering
    \includegraphics[width=\linewidth]{Images/step_by_step.png}\\
    \begin{tabular}{p{0.035\textwidth}p{0.035\textwidth}p{0.035\textwidth}p{0.037\textwidth}p{0.037\textwidth}p{0.037\textwidth}p{0.037\textwidth}p{0.037\textwidth}}
        20 & 40 & 80 & 160 & 320 & 620 & 1000 & input \\
    \end{tabular}
    \caption{F2W network's improvement during training; numbers show the training steps. }
    \label{fig:F2W_stepbystep}
\end{figure}

\subsubsection{Optimization Process}
\label{Exp:opt_comp}
To show the contribution of each part of our proposed loss function to the final model, we have performed the optimization step with different combinations of loss functions. Here, we test four loss functions: appearance loss of VGGFace ($L_1^{app}$), appearance loss of VGGFace2 ($L_2^{app}$), manifold preservation loss ($L_M$) and feature loss of VGG16 ($L_3^{app}$). Fig. \ref{fig:lossCompare} shows the results of the ablation study of the proposed loss function. As the results show, the best performance is achieved by the combination of all loss functions. But the identities of the generated face photos by the proposed method still have a little difference with the real photos which is mainly due to the low quality of the input sketches.

\begin{figure}[hbt!]
    \centering
    \includegraphics[width=\linewidth]{Images/res_loss_2.png}
    \caption{Ablation study of the proposed loss function. The input image, its sketch, and the output of F2W for sketch are shown in columns (a), (b) and (c), respectively. Columns (d) to (j) show the results of different loss functions:, (d) $L_1^{App}$, (e) $L_2^{App}$, (f) $L_1^{App}$ + $L_2^{App}$ + $L_3^{App}$, (g) $L_1^{App}$ + $L_M$, (h) $L_2^{App}$ + $L^M$, (i) $L_1^{App}$ + $L_2^{App}$ + $L^M$, (j) $L_1^{App}$ + $L_2^{App}$ + $L_3^{App}$ + $L^M$. }
    \label{fig:lossCompare}
\end{figure}

\subsubsection{Manifold Preservation Scores}
As mentioned before, not all intermediate latent vectors ($w$s) are converted to realistic face photos by FaceGAN. Desired $w$s form a small subspace of the whole space. We employed the HOGFD network to measure the distance of each $w$ vector from this manifold. To this end, HOGFD assigns a score to each face image based on the amount of artifact presented in that image. Fig. \ref{fig:artifact_loss} shows samples of these scores for some images produced by StyleGAN for different $w$ vectors. The HOGFD's score for an image is inversely proportional to the image quality degradation.

\begin{figure}
    \centering
    \begin{tabular}{ccccc}
        \includegraphics[width=24mm]{Images/manifold_presevation/8.png} & \includegraphics[width=24mm]{Images/manifold_presevation/10.png} & \includegraphics[width=24mm]{Images/manifold_presevation/12.png} &
        \includegraphics[width=24mm]{Images/manifold_presevation/14.png} &
        \includegraphics[width=24 mm]{Images/manifold_presevation/16.png} \\
        (a)1.84 & (b)1.79 & (c)1.77 & (e)1.40 & (f)0.66 \\[6pt]
    \end{tabular}
    \caption{Manifold preservation scores.}
    \label{fig:artifact_loss}
\end{figure}

\subsection{Comparison with Other Methods}
In this section, the results of our proposed model are compared with those of four other methods. In the first experiment, one thousand images from the Celeba-HQ dataset \cite{karras2017progressive} are selected and divided into 900 training and 100 test images. These images are then used to train DualGAN \cite{yi2017dualgan}, CycleGAN \cite{zhu2017unpaired}, and fine-tune pixel2style2pixel \cite{richardson2021encoding} sketch to photo models. Fig. \ref{fig:compareWithOthers} shows the results of these models along with the photos generated by our proposed model for some test images. The DualGAN and CycleGAN models stick to the input sketch and its background and just add almost the same skin color to all sketches while our proposed model reconstructs the face from the scratch, keeps all details of the face parts, and add no artifact to it. As one can see, the background and even the overlapping objects like the microphone in the last row are removed by the proposed model. However, the pixel2style2pixel model which is based on the StyleGAN face generator generates high-quality images comparing with two other models, while the generated images are still far from the target in identity aspect. Moreover, one considering point is that there is no need to train the proposed model on the new dataset, while other models are trained on this used dataset.

\begin{figure}[hbt!]
    \centering
    \includegraphics[width=\linewidth]{Images/comparing_res.png}
    \caption{The results of photo to sketch models on Celeba-HQ dataset: (a) colored images, (b) sketches, (c) DualGAN's results, (d) CycleGAN's results, (e) pixel2style2pixel's results, and (f) our proposed model's results.}
    \label{fig:compareWithOthers}
\end{figure}

In another experiment, we compare our proposed model with three online black and white image colorizing applications: hotpot \cite{hotpot}, imagecolorizer \cite{imagecolorizer}, and Photomyne \cite{Photomyne}. The results are shown in Fig. \ref{fig:compareWithApps}. It is clear from the results that the proposed model is far superior to the compared web-apps. All applications slightly change the color of the lines of the sketch to a reddish-brown color while the proposed model gives fully-colored photos and even properly guesses some hair color.

\begin{figure}[hbt!]
    \centering
    \includegraphics[width=\linewidth]{Images/paperRes2.png}
    \caption{The results of the proposed model and some online image colorizing applications: (a) colored images, (b) sketches, (c) hotpot's results, (d) imagecolorizer's results,(e) Photomyne's results, and (f) the proposed method's results.}
    \label{fig:compareWithApps}
\end{figure}

\subsection{Quantitative Evaluations}
We used two sets of criteria to evaluate the proposed method quantitatively, 1) full-reference image quality assessment and 2) rank-1 face recognition accuracy measures. In full-reference image quality assessment, the main real image is considered as the reference image and the output image of the proposed model is compared with it. Here, we use three image quality assessment measures: 1) Structural Similarity Index (SSIM), 2) Feature Similarity Index (FSIM), and 3) Visual Information Fidelity Index (VIF). As mentioned earlier, part of the AR dataset is used in this test; 40 pictures are randomly selected for training CycleGAN and DualGAN methods, and fine-tuning the pixel2style2pixel model and the other 83 pictures are used for the test. The results are given in table \ref{tab:SSIM_FSIM_VIF}. SSIM measure quantifies the perceived quality of an image and as the results show, it is much higher in the images produced by the proposed model compared to CycleGAN and DualGAN. This is due to the optimization process of the proposed model that prevents output image from being blurred or noisy. Also, the VGG16 loss function leads to a similar structure of the sketch and output image. For the case of VIF metric that correlates with a human judgment of image quality the proposed model performs better than CycleGAN and DualGAN. Regarding the FSIM which is more related to the local features of the two images, the CycleGAN and DualGAN perform better as they directly use the sketch in producing the final results while the proposed model works on the $w$ vectors in the intermediate latent space. On the other hand, the Pixel2style2pixel model by producing natural photos based on StyleGAN could gain higher scores in all of these metrics. But despite the high results of this model in this section, the identities of the produced photos are very far from the targets and this will be studied in the following.

\begin{table}[!htbp]
\small
\centering
\caption{Full-reference image quality assessment results on part of the CUFS dataset. Here the proposed method is compared with three of existing advanced methods, including DualGAN \cite{yi2017dualgan}, CycleGAN \cite{zhu2017unpaired}, and pixel2style2pixel\cite{richardson2021encoding}.}
\label{tab:SSIM_FSIM_VIF}
\addtolength{\tabcolsep}{-4.1pt}
\begin{tabular}{p{2.3cm}p{1.9cm}p{1.9cm}p{1.9cm}}
\toprule
\multirow{2}[3]{*}{Method} & \multicolumn{3}{c}{Criterion}  \\
\cmidrule(lr){2-4}
 & SSIM & FSIM & VIF \\
\midrule
DualGAN & 0.57 & 0.755 & 0.109 \\
CycleGAN & 0.57 & 0.754 & 0.108 \\
Pixel2style2pixel & \textbf{0.79} & \textbf{0.781} & \textbf{0.147} \\
Proposed model & 0.655 & 0.748 & 0.115  \\
\bottomrule
\end{tabular}
\end{table}

In the other test of this section, the generated photos are used for face recognition (FR). The recognition results are reported in Table \ref{tab:Rank-1}. Three different networks (VGGFACE, VGGFACE2, and FaceNet) are used for face recognition. As the results show, the recognition accuracy for the images synthesized by the proposed model is higher than the other methods. For VGGFACE and VGGFACE2 whose features are included in the optimization process, the superiority of the proposed model is quite clear and for the FaceNet which is not considered in the optimization, the performances of models are close to each other indicating that the proposed model can generate realistic images without degrading identity. Moreover, the low accuracy of the pixel2style2pixel is due to the difference between the identity of the generated photos with their corresponding targets.

\begin{table}[!htbp]
\small
\centering
\caption[align=c]{Rank-1 face recognition accuracies on part of the CUFS dataset. Here the proposed method is compared with three of existing advanced methods, including DualGAN \cite{yi2017dualgan}, CycleGAN \cite{zhu2017unpaired}, and pixel2style2pixel\cite{richardson2021encoding}. Also three different networks are used for face recognition, including VGGFACE, VGGFACE2, and FaceNet.}
\label{tab:Rank-1}
\addtolength{\tabcolsep}{-4.1pt}
\begin{tabular}{p{2.3cm}p{1.9cm}p{1.9cm}p{1.9cm}}
\toprule
\multirow{2}[2]{*}{Method} & \multicolumn{3}{c}{FR Method}  \\
\cmidrule(lr){2-4}
 & FaceNet & VGGFace & VGGFace2 \\
\midrule
DualGAN & \textbf{0.506} & 0.855 & 0.650 \\
CycleGAN & 0.481 & 0.795 & 0.698 \\
Pixel2style2pixel & 0.085 & 0.158 & 0.098 \\
Proposed model & \textbf{0.506} & \textbf{0.975} & \textbf{0.831} \\
\bottomrule
\end{tabular}
\end{table}

\subsection{Qualitative Evaluation}
For subjective evaluation of the results by real users, we created a form containing 50 sketches and the corresponding colorful images created by different sketch-to-photo methods including CycleGAN, DualGAN, pixel2style2pixel(pSp), and our proposed method. Users were asked to select the best real photo for each sketch based on two main criteria: 1) does the generated image looks realistic? and 2) do the sketch and generated image represent the same identity? To avoid biasing users towards the results of a special method, the results are shuffled for each sketch. The images are selected from the AR dataset and CelebA dataset. Sixty people have participated in this evaluation. The percentage of times each method has been selected as the best method is reported in Table \ref{tab:user_study}. As the results show the proposed method outperforms the other methods from the users' perspective.

\begin{table}[!htbp]
\small
\centering
\caption[align=c]{Result of the subjective evaluation. The results of the perceptive user study conducted on 60 people over 50 samples including sketches and generated photos by four methods. }
\label{tab:user_study}
\addtolength{\tabcolsep}{-4.1pt}
\begin{tabular}{p{2.4cm}p{1.6cm}p{1.6cm}p{1.2cm}p{1.2cm}}
\toprule
Method & DualGAN & CycleGAN & pSp & Our's \\
\midrule
success percent & 8.03\% & 4.35\% & 11.72\% & \textbf{75.89\%} \\
\bottomrule
\end{tabular}
\end{table}

\subsection{Complexity Analysis}
There are two main categories of solutions for the sketch to photo translation task. The first category relies on encoder-decoder architectures. These models need a time-consuming training process to train the model parameters, while they are fast in the test as the final output is generated by only one pass through the encoder and decoder networks. The second category is based on optimization in which a pre-trained target image generator is utilized along with some objective functions. These models don't need a training phase and training dataset. However, the execution time of these models is generally higher than in the first category. Our proposed model belongs to the second category of models and is a general framework without any training phase for a new dataset. The running time of our model on a Ubuntu 20.04 system with 16 GB RAM and one 1080 Ti GPU is around 3-5 minutes per image. The models of the first category need a training phase that continues for several days and test runtime of few seconds.

\section{Conclusions And Future Works}
\label{sec:conclusion}
In this paper, we proposed a novel sketch to photo synthesis framework based on GANs. Unlike most of the existing methods, the proposed method requires no paired data and no training for new datasets. The overall process is divided into an initialization step which maps the input sketch to the intermediate space of the face synthesizer and the optimization step which fine-tunes the generated face photo. The proposed framework is quite flexible and can be easily adapted to any face synthesizing model and any fidelity criterion. The proposed model was applied to several sketches from different datasets and the results were evaluated based on the objective and subjective measures. As the experiments show, the output of the model is a high-quality and realistic face photo whose attributes are the same as the input sketch. Furthermore, the high recognition rates over the synthesized images show the superiority of the proposed model in preserving the identity of the target person.

In the following, the proposed model can be extended by incorporating attributes not provided by the sketch, e.g. skin or hair color, either directly from an input vector or indirectly from a face photo.

\bibliographystyle{unsrt}

redpajama_set_name: RedPajamaArXiv


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text:
Oil & Gas / North Sea
No easy answer for the future of Shell's Brent field
It was the beginning of an exciting week when Greenpeace announced they had sent activists to the middle of the North Sea to climb the remains of Shell's Brent platforms, brandishing signs of "clean up your mess".
05/11/2019, 6:55 am Updated: 05/11/2019, 7:13 am
The Brent Delta being installed in 1976.
But four days later, when a group of 15 European governments held a closed-door meeting on what to actually do with the Brent "legs", the announcement was somewhat underwhelming.
"The United Kingdom, in accordance with Decision 98/3, will further engage in discussions with parties before taking a decision."
Not exactly Christmas. From a news perspective, at least.
Last month's meeting of Ospar, a convention to protect Europe's marine environment, was always just part of the UK's consultative process on the plans for Brent Bravo, Charlie and Delta, rather than a place for a final decision.
Once the UK has consulted, it has final say on whether to grant Shell's application to leave the giant legs of the platforms in place.
This derogation would contravene Ospar rules which generally require the complete removal of oil and gas installations from the seabed at the end of their production lives.
It is not clear when the next talks will take place or what timeline the UK is working to for making a decision, though it is understood they won't spring an approval out of the woodwork before the discussions are held.
Ospar's announcement did finally formally recognise that the UK wants to grant Shell its application to leave the footings in place – something that has been widely reported but not officially recognised by the Department for Business, Energy and Industrial Strategy (BEIS).
"The meeting discussed the UK's intention to issue derogation for leaving in-situ the footings of the Brent Alpha steel jacket and Brent Bravo, Brent Charlie and Brent Delta gravity-based concrete installations," Ospar said.
While there is some concern around the danger leaving the legs in place could pose to marine traffic, the real issue relates to the contents of oil storage cells within the gravity-based structures (GBSs).
They weigh around 300,000 tonnes apiece. Within each base is a cluster of oil storage cells – 64 in total, each taller than Nelson's Column.
It is estimated these contain 11,000 tonnes of oil, and opposition countries like Germany and the Netherlands, backed up by Denmark and the EU Commission, argue leaving the contents in place is "unacceptable". '
Shell said it had carried out more than 300 scientific and technical studies into the decommissioning plans, with leaving "in situ" the best option.
Greenpeace protests at the Brent field last month. Pic: Greenpeace
The energy major said the oil itself is not free floating but bound to sediment comprised of sand, grit and water, which Shell said is encased within one metre thick reinforced concrete structures which will take "centuries" to degrade.
As a result any environmental benefit would be outweighed by the cost and risk of removal.
Shell's comparative assessment – which Germany has questioned – has set out options on how the contents could potentially be removed or protected.
Options one and two relate to removing the contents and either re-injecting them into subsea wells or taking them ashore for treatment. Shell said it would be "very challenging" to drill a large hole into a concrete cell at a depth of 120 metres and safely extract the contents without some being released into the sea.
Option three would leave the contents in place with a treatment called bioremediation – the use of naturally occurring organisms to biodegrade the oil within the sediment. The problem is that it would likely only affect the surface of the sediment – 20-30cm – with no guarantee of success.
Option four: Leave in place capped. Capping material like sand would be added to the GBSs to form a protective barrier between the sediment and the sea as the GBSs disintegrate. Meanwhile, biodegradation of the oil would also be carried out. However, 75% of the sediment are fluids so it would also need a "structural agent" like gravel at a higher volume than the capping material, making it challenging. Shell also said the capping agent would only provide a "limited amount of protection" when the GBSs do disintegrate.
So that just leaves the preferred fifth option of leaving the contents in place, protected by the GBSs for hundreds of years. In a worst-case scenario, Shell said their release would be restricted to an area a "little larger than the area already impacted around each platform by the historic drill cuttings".
However, an independent report commissioned for the German Government earlier this year said Shell's assessment process was largely based on "flawed" government guidelines which create a bias towards any option that has minimal decommissioning work.
Ultimately Shell argues that the risks outweigh the environmental benefits. The problem is that these structures, put in place in the 1970s, were not created with removal in mind. It was only in more recent years that oil firms have needed to show how they would eventually remove platforms when they submit their field development plans.
GIANT: One of the platforms for the Brent field being transported from Stavanger, Norway
According to Professor Alex Kemp, petroleum economist at Aberdeen University, the UK Government has historically followed Ospar rules. However, there are derogations allowed where the costs and risks of complete removal are exceptionally high.
The Frigg field on the UK-Norway border, fully decommissioned in 2010, also had GBSs and was granted derogation to keep them in place.
The difference is that the Frigg structures were never used for the storage of crude oil.
Prof Kemp highlighted that the residual liability rule applies for Brent, meaning Shell has liability in perpetuity for any issues that arise after decommissioning.
Prevention will be a preferred approach for many Ospar countries, although the residual rule could play a "key part" in the deliberations.
Professor Kemp said: "The residual liability obligation could be a key part because that would make sure that if some bad accident happened or a leak then there is a clear responsibility to deal with that.
"That is likely to be highlighted but I think there would be an effort made within the Ospar members to try to reach some sort of agreement.
"The rules are that the current operators have a residual liability to deal with any problems which can emerge. That could include leaks, other accidents with ships hitting the remains, and so on."
Time will tell what the outcome will be – BEIS remains tight-lipped on the way forward – but that's not true of the German government.
The country's environment minister released a fairly optimistic statement after the Ospar meeting last month, welcoming the prospect of future talks.
He said: "We now have the opportunity to set a clear course of action for the environmentally sound disposal of old oil platforms in the future, especially at a time when we are gradually forced to abandon oil, gas and coal. We will acquire a safe, environmentally friendly and climate-friendly way of dealing with the legacies of these energy sources. The close cooperation of the Ospar states provides a good basis for this."
'Another nail in the coffin': Siccar Point puts Cambo on pause after Shell pulls out
Ospar
Professor Alex Kemp
Shell renews talks with UK regulators on Jackdaw, according to reports
Ithaca gets green light to develop central North Sea field

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A Lee County road is closed until further notice.
LEE COUNTY, Miss. (WTVA) - A Lee County road is closed until further notice.
The Lee County Road Department says this is on County Road 506, approximately 450 feet north of the intersection of County Road 506 and County Road 130. This is in the Pine Grove area.
This will allow crews to replace a cross drain.
It's unclear when the closure will be lifted.


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text:
Prove Me Wrong
Public Support for War With Iraq
I've made the point in the past that only 33% of the American people supported the invasion of Iraq without UN authorization, and my source for that is here. The right wing war mongering American Enterprise Institute has compiled the results of various polling questions regarding the war and that is available here. It's interesting to note that the AEI basically confirms my prior claim. But the AEI has an additional question that is worth considering, which is on page 6. Would you support the invasion of Iraq without UN authorization but with the support of one or two major allies? Since of course Britain did support the invasion (despite public opposition) this question more accurately reflects what happened. The results were as follows:
Jan. 3-6, 2003 PSRA/Newsweek - Support: 47, Oppose: 45
Jan. 16-17, 2003 PSRA/Newsweek - Support: 39, Oppose: 52
As you would expect more people did support war with the support of a couple of additional states but without UN authorization than supported with the US acting alone.
But what makes this all the more remarkable is that 2/3 of the American people were under the false impression that Saddam was directly involved in the 9/11 attacks. According to the University of Maryland 69% believed this falsity. Despite this they opposed Bush's invasion when it occurred. After it commenced though the public did rally in support as the public typically does in such cases.
My memory is that Bush did not explicitly state that Saddam was responsible for 9/11 or had links to Al Qaeda. But did he intentionally conflate Saddam and OBL, such as during the 2004 debates when he "accidentally" said one when he meant the other? As is well known, Foxnews viewers are more likely to have pro-war misperceptions. They would be expected to get a more steady diet of such conflations.
Well, that's impossible to prove and speculative. But it's interesting how tepid support was despite the widespread belief that Saddam had attacked the US.
Posted by Jon at 5:51 PM
HispanicPundit said...
This matches my recollection of the events as well, both were true: the general support for the Iraq war, atleast given one major powers joint support, seemed high and the false belief that Saddam was responsible for 9/11.
Support with one major power was high? The poll that was closer to the initiation of the war had 39% in support and 52% in opposition to the war with the support of a major power. You call this high support?
I dispute the 39%. My memory was that it was high. Even here in liberal California. In fact, most, if not all, of the liberals I knew at the time also supported the war.
In fact, most of the liberal bloggers and pundits that now vehemently oppose the Iraq war supported it at the time. That seems high to me.
What I would really like to see is a poll of the views of Americans after we tried to get UN approval and it was evident that Germany and France (or was it just France?) wouldn't budge. Thats the real important poll, and thats the one that matters - it's also right before the invasion, so calls of patriotism don't count either.
Even hawks tended to want to attempt UN support and to get the backing of others. The question is what would the American people do once we saw that we were blocked from doing so? I remember that was the turning point for many. But absent are the polls during that critical period.
It was after that that Bush decided to go it "alone" - without UN support.
The link I provide related to Foxnews discusses later polls from February in the run up to war. The results are pretty much the same. For those that thought Saddam was directly involved in 9/11 (about 25% of the population, note this is a different question than is involved in the 69% figure I cited in my post because that one includes those that believed it was "somewhat likely" that Saddam was involved in 9/11) only 58% of this 25% of the population supported war without UN authorization. That means between 12 and 14% of the whole population. Support drops off amongst those that think there are Al Qaeda/Saddam links, but Saddam was not involved in 9/11, less for those that think it "somewhat likely" that Saddam was involved, and lowest amongst those that think there was no link. The overall rate of support is still pretty much the same. Assuming all groups represent equal slices of the population you're at about 37% support for war without UN authorization in the run up to war.
You can either believe your memory or the data.
But I am not asking for "without UN authorization". Even I, the hawk that I was back then, wouldn't have supported war in such circumstances.
What I am asking about is that sweet spot after the attempt to get UN approval failed. The general US public (falsely or not) believed that France hijacked the conference and was being stubborn. I wonder what the support for the war was THEN. That was still before the actual invasion.
Do you remember when that happened? The UN attempt failed?
That's like a 3 day window. The US abandoned UN efforts on March 17 and invaded just a couple of days later.
On the other hand Powell's speech was in early February, and the polls that I referred to were done in February. The US initiated a resolution to authorize war on Feb 15, but this was followed by the largest protests that ever occurred in the history of humanity in opposition. It would be known pretty early the prospects of these actions.
The evidence, such as it is and imperfect as it is, all points in the same direction. You say the perception was that France had hijacked things. I wouldn't say that was the perception. I would say that was the story offered by US media. Foreign media was all over Collin Powell's speech and how it was laughable. This story wasn't told in the US. So yeah, the corporate media blamed France, but that's not the same as saying that the public agreed.
This much I think is clear though. Whatever support for war there was, it was buttressed by misconceptions. If France was perceived to be the problem that's another media generated misconception. An informed public wouldn't possibly have supported what was done. My contention is that even with the misleading elements the public still did not support war. That's the only conclusion that can be drawn from the data. The contrary conclusion you offer is based on what you're hearing in the media, but that's very tainted. Even so called liberal media was dancing to the war drumbeat. Remember that Donahue was fired from MSNBC because of the "unpatriotic" face he offered for their channel. His ratings were as good as any other show on that channel.
Turning Point?
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text:
Q: Directus Hooks - how to use the "item.read" Anyone know how the "item.read" hooks is meant to work?
return [
    'filters' => [
        'item.update.table:before' => function (\Directus\Hook\Payload $payload) {
            $payload->set('field', my_encrypt($payload->get('password'), $key));
            return $payload;
        },
        'item.read.table:before' => function(\Directus\Hook\Payload $payload){
          <how to set the 'field' before view??>
          return $payload;
        },
    ],
];

I need to unecrypt the stored field for view....

A: I found the way.
First you need the
'item.read.coll' => function ($payload)

Second you get the data from the payload - alter the data and replace the data in the payload - like this
    $data = $payload->getData();
    $data[0]['field'] = "NEW DATA";
    $payload->replace($data);
    return $payload;

redpajama_set_name: RedPajamaStackExchange


Konica Mount = Minolta Mount???
Discussion in 'Adapted Lenses' started by jetta-the-hut, Sep 20, 2012.
I just bought a Konica m4/3 adaptor for my E-PL1 and was wondering if the konica mount and the Minolta mount are 1 in the same?
My wife has a minolta film camera with a few lens and i'm looking at picking up a 50mm 1.7 hexanon, so while im cruising ebay alot of them say konica/ minolta. Will the adaptor work for both types?
Probably not. I learned this the hard way.
I was trying to find the one I ended up buying but it's getting lost in my highly-organized filing system I have here.
Konica had its own mount and Minolta was a competing mount which was not the same. You will need a Konica mount adapter.
im guessing it has to be an AR mount, I have found a few specifically, the 40mm and the 50mm lens almost all have Konica Hexanon and i think those will be ok, from what ive seen Ebay is adding the Minolta to the listing in the catagories once you ckick them and break it down the seller doesnt have minolta in the listing.
I guess i just need to be careful of which one i buy.
Anyone have experience with the 40mm 1.8 or the 200mm f/4 on a m4/3?
No, these are two separate and distinct mounts. The companies didn't merge until the early 2000's, but the lenses and mounts you are seeing precede that by decades.
In fact, there are TWO different incompatible Minolta mounts: one for their manual focus bodies and another for their "Maxxum" AF bodies. The Maxxum AF mount remains in use today by the Sony Alpha bodies.
I don't have any experience with the Hexanon 200/f4, but the 40mm/f1.8 pancake is a very fun lens to shoot with on :43:. It's one of the more compact SLR lenses available and it is sharp and fast. I would recommend it highly to anyone who wants to dip a toe into shooting with adapted lenses.
Check out this thread to see lots of images users here have made with this lens. And here's the 200mm/f4 thread.
cool thanks for the links, im now worried i should have spent alittle more on the adapter. live and learn well see if its loose or not, i'll bookmark the link you posted and go with them for the canon FD mount i'm picking up next. i got this one and it stated AR to micro 4/3 so it should work.
Those links I supplied were meant mostly to just show the adapters, they shouldn't be construed as an endorsement of the Fotodiox brand. Although others have posted good things about the Fotodiox adapters, I don't have any personal experience with them. I believe that the Konica adapter I have is branded Fotasy, and it works well enough.
My own strategy on shopping for adapters is to search eBay and choose the cheapest one from a seller with whom I feel comfortable. These are pretty simple pieces of machinery for the most part and I personally don't feel that there's much of a correlation between price and quality at the low end (on the other end of the spectrum there are very pricey adapters from Novoflex, Voigtlander and others which I have no doubt are machined to tighter tolerances, though, again I haven't used any of these myself). I figure if I buy the cheapest one I can find (generally under $20), even if it doesn't work well or breaks, I'm not out much and can just try another brand.
Of course, I'm using only super inexpensive, thrift shop lenses. If I had some more expensive glass I might consider paying more for one of the high-end adapters.
There was an earlier Konica mount that preceded the AR mount. If memory serves, this mount had a flange that was compatible with the Exakta mount though diaphram coupling was different.
The diaphram coupling differs between the early Minolta SR lenses and the later SR, MC, & MD lenses. This is of no consequence to those adapting the lenses to m43 but is to those using the lenses on Minolta bodies. The original SR lenses made for the original SR-1 will not fit any metered Minolta as the auto-diaphram pin protrudes too far into the body. The mounting flange, though, is the same as the later SR and the MC & MD lenses.
Lovely things. I wouldn't bother with the 200mm f4. If you must have a 200mm go for the f3.5.
... Konica's Hexanons are often surprisingly excellent lenses dispite the fact that there isn't much common talk about how great they are.
Haha, I picked up a clean 57mm 1.4 for four bucks at a flea market. Came with a free attached broken camera! Looks like it's one of the ones from the late 60s or so.
Too bad my MF skills are so lacking that I've hardly used it at all. I really need to force myself.


text:
Ododo Walsh '98
Milton Hershey School and New York City, though within neighboring states, are worlds apart when alumna Ododo Walsh '98 reflects on her childhood in poverty.
"I was living in New York City with my mom and my younger brother, Osahon," Ododo said. "And we were not in a good situation. We lived in a one-bedroom, really small, cramped apartment and our neighborhood was not very safe, not very clean. And fortunately, my mom learned about Milton Hershey School through a friend and its mission to break the cycle of poverty."
In 1991, Ododo and her brother enrolled at Milton Hershey School. Ododo moved into a student home with other middle school girls, all under the loving care of a welcoming houseparent couple. Although she distracted herself from the natural feelings that come with saying goodbye to her mother, Ododo remembers—at age 11—she felt like a kid, without the worries that she was familiar with while living in New York City.
Ododo was quick and ready to play with other students through this new, inclusive, and structured way of life. This whole child approach helped her flourish as a student. She describes herself as a "happy-go-lucky kid" when recalling her days as a student at MHS.
Ododo soon built a collection of many fond memories—playing field hockey for the very first time in her life, joining girl scouts, getting involved in student government, and seeking to discover (though admitting it wasn't her strongest talent) new passions like singing in varsity choir.
MHS was at the center of it all. The MHS experience afforded Ododo the opportunities and access to resources provided for free, but also connected her with peers and staff that would continue to push and support her to be her greatest self.
Ododo's journey at MHS could be seen as a transformation in various realms. Once a girl living in poverty city conditions, she then found in herself an excelling student-athlete with a broadening ability to lead others. Ododo expresses a humble gratitude when sharing her participation in college athletics after graduating from MHS in 1998.
"Not a lot of kids get to pursue college-level athletics," she said. "And I got to do that. I was on a Division II national field hockey team."
She believes, once again, this was possible because of what MHS and its staff taught her. But college athletics was not the only place where lessons expanded Ododo's potential. During the summer months when she was in college at Lock Haven University, Ododo returned to MHS to work in the program now called Year-Round Experiences (YRE).
Ododo's path to success continued when she enrolled in Temple University's graduate program, and in 2005, received a master's degree in Educational Administration and Supervision.
"Pursuing that degree really set the stage for the opportunity to come back to Milton Hershey School," Ododo said.
After receiving her master's, she first worked in Philadelphia and then Coatesville. These roles gave Ododo the experiences that she credits to being "something" that she could give back to her Alma Mater. Then in 2014, Ododo returned to MHS to work full-time as a Home Life Administrator (HLA) in Elementary Division.
"I remember when I got the call that I got the job to come back to MHS," she said. "I just had the vision of American Idol where you have the person on stage and it's like they just won the lottery. That's how I felt. I felt really grateful."
To say she was back at MHS was a priceless reward that validated all of Ododo's hard work and discipline in school, on the field, and in the professional world. Returning as a full-time staff member also awakened a deeper appreciation for her student experience and the staff who made a difference in her life.
"I got to really see all the collaboration and cooperation that happens on this really big campus to make sure that our kids have a really positive experience," she said.
Ododo worked in the HLA role for six years, supervising houseparents. She then went on to become Associate Director of Transitional Living (TL), the independent living program for senior students.
Now, Ododo serves as the Senior Director of Home Life and Student Leadership. In this role, she oversees the hiring of houseparents as well as the Compass Project—the character development program at MHS that weaves into both home life and scholastic life.
The Compass Project is just one way that MHS looks out for the care of the whole child, every child. And this care began in 1909 when Milton and Catherine Hershey signed the Deed of Trust.
"Milton Hershey School has been an expert in this field for over 112 years now," Ododo said. "We understand that our students who come from poverty need that whole child care. It comes from meeting their basic needs with food and clothing and medical and dental care. And also providing them with a sense of stability, that sense of belonging, that sense of safety."
Meeting these needs, she continues, is one step to help break the cycle of childhood poverty, which is and has been a national crisis in America.
"It did that for me and has done that for countless other alumni who have been blessed to come and experience what Milton Hershey School has to offer," Ododo added.


The local water supply challenges are about to deteriorate further following reports indicating that South Africa is planning to cut off Botswana from receiving water supplements from Molatedi Dam near Zeerust, in the Northwest Province.
This comes after Molatedi Dam dropped to extremely low levels. Water Utilities Corporation (WUC) spokesperson Matida Mmipi confirmed that Molatedi dam, which is supplying the greater Gaborone area with about 4.8 million litres of water daily, is currently at only eight percent. The dam has been supplying water to the greater Gaborone for many years, based on an agreement dating back to 1988, which requires that when the dam levels are 26 per cent and above, the supply to Botswana will be at full capacity but when the levels drop to 26 per cent, supply would be cut to half the full capacity.
Although she acknowledged the fact that Molatedi dam was at its lowest and almost drying up, Mmipi refuted reports that supply to Botswana will soon be cut off. According to Mmipi they still have a standing agreement with their South African counterparts and until they reach a formal agreement, Botswana will continue to receive its designated quota. Mmipi explained that, the current arrangement requires that Botswana delegation and their South African counterparts meet annually in May and October to discuss water supply arrangement and other water related issues before resolving anything. "We are yet to meet this month, until then, the current arrangement stands. We will still receive water from Molatedi dam," said Mmipi.
The greater Gaborone water demand is currently at 145 Million Litres (ML) a day at peak demand and measures 125 Million Litres (ML) a day at average demand while the rationed demand stands at 110 Million Litres (ML) a day. The greater Gaborone region has for a long time recorded severe shortage of water in almost every corner, with some places going without water for more than two weeks. The corporation's latest report however states that supply to most areas in Gaborone remains stable and rationing has commenced in all the fully recovered areas. According to the corporation, water supply in Tlokweng is generally low, especially on high ground, while in Mogoditshane, Gabane and Mmopane the area currently has no water.
Metsimotlhabe on the other hand is reported to be receiving supply at low pressure. In Kumakwane the village is said to be still supplied from boreholes which are not meeting demand. Other areas do not have water. Mochudi is said to be receiving supply while bowsing continues in those areas still without supply. Lobatse according to the report has water.


Imagine this: Your employer says you're going to get a pay cut. Short of quitting, what can you do? Is there any room to negotiate before accepting the reduction? And how do you deal with the anxiety that comes with a smaller salary?
It may be in your best interest to accept the decrease, but you can be proactive at the same time.
* How Long Will the Reduction in Compensation Last? This may be a difficult question to answer, especially if the reduction is the result of a general downturn in business.
* Will the Decrease Adversely Affect Any of Your Benefits? If so, which ones and how much? For many people, benefits are enormously important, especially health insurance coverage. Salary is the most common area in which reductions are made and it is unlikely benefits will be cut, but you could be asked to contribute a larger percentage to the monthly premiums. Health insurance costs are usually the second-largest expenditure in any business and something you certainly don't want to lose -- even if your out-of-pocket contribution goes up.
* Will the Decrease Be Across the Board or Just Within Certain Departments? Generally speaking, pay cuts are implemented throughout the company. If they're not, you may want to quietly start your own job search. It's not fair to have some employees taking pay cuts and not others.
* When Will the Reduction Take Effect? You need to know this so you can plan ahead in managing your finances.
Another point to investigate is whether bonuses will be affected. Sometimes, especially for people involved in selling, bonuses are not affected since they're based on meeting sales goals. If bonuses are paid to everyone, they're usually based on the company's general profitability, so it's possible they will also be suspended until profits increase. Bonuses, especially if you're not in a sales position, should be viewed as perks that aren't necessarily entitlements and may not always be there.
Are There Any Tradeoffs to Lower Pay?
Aside from compensation and benefits, the next most important thing to most people is time. If a pay reduction is unavoidable, it may be possible for you to negotiate additional unpaid time off. For instance, if you're asked to take a 10 percent reduction in pay, you could ask for an equal reduction in time spent on the job. Perhaps you can suggest taking Friday afternoons off during the period of reduction. It's not more money in your pocket, but at least it's time you can have for other things. On the flip side, there is something to be said for being a team player during the tough times. Most employers will remember the employees who are dedicated enough to work the same number of hours for less compensation.
How do you address a decrease in pay in your salary history? Be honest about it. For instance, if you know that the company had been struggling as the result of tough economic times, acknowledge that in your salary history. If an across-the-board pay cut was instituted, just state it honestly. If the prospective employer checks references, that cut can easily be confirmed.
While nobody wants a pay cut, it does happen. But as with any bump on your career path, it's how you react to it that matters most.


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Swift Oil acquires Chorus Energy
A major downstream player in Nigeria�s oil and gas industry, Swift Oil Limited, has made inroads into the upstream sector through the acquisition of Chorus Energy Limited, a marginal field player.
Interswitch launches transport solution at MMA2
Interswitch Transnational, one of the leading pan-African integrated payments companies, has launched its new SmartMove solution at Murtala Muhammed Airport Terminal 2 (MMA2). Interswitch said in a statement that SmartMove has been deployed at the airport as a fully automated multi-storey car park management system that utilises payment cards, the first of its kind in Nigeria. According to the company, the payment cards will be provided by Verve. �Their new product, �Verve Breeze�, a contactless card variant, will work with SmartMove to provide users with quick and easy payment in car parks, on mass transit and on toll roads,� the statement said. Commenting on the product, Group Managing Director, Interswitch Transnational Holdings, Mr. Mitchell Elegbe, said: �The launch of SmartMove is an ambitious step for Interswitch into a new high growth sector in Nigeria. �As our economy continues to expand we need new solutions to efficiently manage growing numbers of people getting around by car and on public transport. With our technical partner, Skidata, we have developed a transport management solution for a 21st century Nigeria.� Also speaking, the Chief Executive Officer, Bi-Courtney Aviation Services Limited (BASL), the managers of MMA2, Mr. Christophe Penninck, said: �The deployment of SmartMove at the MMA2 car park will provide our customers with a convenient payment solution and allow our car park managers to continuously monitor parking operations to ensure we are providing the very best service that we can.�
PDP suspends talks on 2015 election
The Peoples Democratic Party on Monday said it has suspended all discussions on the 2015 general elections to enable it focus on helping President Goodluck Jonathan and other elected officials of the party solve the challenges facing the country. The PDP National Publicity Secretary, Chief Olisa Metuh, told our correspondent that the party�s priority was to ensure the schoolgirls abducted in Chibok, Borno State, were rescued and returned home.
$35m lost daily to oil theft � Confab committee
The National Conference Committee on Energy has said that the country is losing about 350,000 barrels of oil per day, estimated at about $35m, to crude oil theft and called on the Federal Government to wake up from its slumber and tackle the menace frontally. The Chairman of the committee, who is also a former Governor of Oyo State, Alhaji Rashidi Ladoja, stated this while presenting the report of his committee to the plenary in Abuja on Monday.
Presence of Four Suspended Lawmakers Aborts Edo Assembly Sitting
Efforts member of the Edo State House of Assembly to sit yesterday morning was aborted following the presence of the Deputy Speaker of the assembly, Mr. Festus Ebea, and three others, who were suspended last week. The suspended lawmakers, Ebea, Patrick Osayinmen, Jude Ise-Idehen and Friday Ogierhakhi, shunned the ruling of the High Court in Benin-City, which restrained them from entering the premises of the assembly. Following security reports that the lawmakers were mobilising thugs and arms to storm the assembly, the police searched the offices of the lawmakers as early as 6a.m. while their cars were all parked outside the premises before they were allowed to enter the premises.
Delegates Call for Urgent Action to Salvage Power Sector
The National Conference monday called on the federal government to declare a state of emergency in the power sector as part of strategies to arrest the deteriorating state of electricity supply in the country. While voting on recommendations of the Committee on Energy chaired by former Governor of Oyo State, Chief Rasheed Ladoja, the delegates directed owners of the privatised power compaines to work hard to improve power supply within the next two years.
4 Secrets to Giving a Great Marketing Presentation
In Start Your Own Information Marketing Business, the staff at Entrepreneur Bookstore and writer Robert Skrob explain how to start and run a successful information marketing business. In this edited excerpt, the authors reveal five of the best ways you can create teleseminars that really connect with your audience. Presentation skills are critical to producing an engaging and interesting teleseminar that gets people to show up and to want more. Here's how you can make your teleseminars entertaining to your attendees:
5 Presentation Lessons From Apple's New Rock Star
Since I wrote a book titled The Presentation Secrets of Steve Jobs, I�ve been searching for a presenter -- at Apple or any other company -- who comes close to sharing Jobs� presence on stage. It hasn�t been easy. Jobs was charismatic, inspiring, humorous, dramatic, engaging and polished, and his slides were beautifully designed. Apple is giving one vice president more time on stage and he�s the most compelling business presenter I�ve seen in a long time. His name is Craig Federighi, Apple�s senior vice president of software engineering.
MTN rated among top sustainable global companies by Newsweek
MTN has been rated among the top 500 global companies on corporate sustainability and environmental impact in the 2014 Newsweek Green Rankings. The rankings are one of the world�s most recognised assessments of corporate environmental performance. Newsweek partnered with Corporate Knights Capital and leading sustainability minds from non-governmental organisations and the academic and accounting communities, to complete the rankings.
Agriculture: Africa�s Hidden Treasure
Despite the current low productivity in Africa�s agricultural sector, the World Bank believes the sector, which already employs about 70 percent of the continent�s people, has great future prospects. The global financial institution recently said agribusiness in Africa could be valued at $1 trillion in the next 16 years. The sector�s ability to empower the economies of many countries on the continent, advance food security and create jobs is palpable.


The case against 8 year old Aashish Nanak from Chandigarh who won 22,912,500.38 Indian Rupees, (that's a life changing $500,000 dollars!) playing an online poker game, started today in New Delhi.
Lawyers acting for the Nanak family are battling to secure the money that would allow the family of twelve to move out of their slum dwelling into a new home and a new life.
Aashish's mother Mrs Nanak said "Aash has always loved the internet and computers he started his own web pages when he was only four years old, he is a very clever boy" Aashish has been playing online poker since he was six, but had been using computers since age three. He was introduced to the internet when his mother who cleans at a local hotel, had sat him in front of a cartoon playing on a computer screen to keep him quiet.
The hotel owners had noticed the boy accessing the internet but had thought nothing of it, they had even begun to ask the boys advice on how to advertise the hotel. Many hotel customers told press that the youngster was making enough money through a series of affiliate programs to pay his families rent. The Lawyers for the gambling website that cannot be named for legal reasons say that legally they do not have to pay out the winnings, as Aashish is under age and are accusing him of entered false details.
The Nanak's lawyers are arguing that the registration details belong to Aahish's uncle and that at no time was it stated that Aashish could not play in the games. They are also arguing that he had previously been paid smaller winnings into a legitimate online paypal account set-up for him by his uncle and that administration staff had confirmed that this was in fact within their guidelines.


Pest Control & Wildlife Removal In North York - SIA Wildlife Control Inc.
North York was once part of Old Toronto and has grown substantially since. The city of North York was recognized as a city for the first time in 1979. Before that North York was known as the Township of North York in 1922. Today it is a crowded city which contains five major shopping malls and the Downsview Park along with other landmarks. North York is located just below Vaughan, above Toronto. Making it almost in the middle of everything including all wildlife problems in Toronto as well. Wildlife has adapted very well to surviving among human constructs and dwellings. North York and Toronto have the largest number of raccoon and squirrel removal problems in GTA. Typically our calls in North York are regarding raccoons, squirrels and mice removal issues.
SIA wildlife control specializes in squirrel removal, skunk removal, bird removal, bat removal, groundhog removal, opossum removal, and raccoon removal in North York. The City of Toronto acknowledges the wildlife issues we are facing in our city. They state that wildlife proofing your home will reduce wildlife shelter therefore lowering their populations. Animals without shelter, will move on to their next den site. Animals like raccoons usually have roughly 3-5 other dens in each neighborhood they reside in. Each with their own piece of territory that they will defend. Animals have needs, food, water and shelter. They must move on to find other sources if any of those are eliminated, prominently the shelter. All types of wildlife cause damage inside an attic space, raccoons and squirrels are the worst. To name a few, wildlife displace insulation, chew wiring in the attic, defecate (parasites), urinate and cause lots of noise. The worst case scenario is the possibility of attic fires due to chewed electrical wiring.
Our team offers raccoon removal services through the use of a raccoon one way door. The technician on site attached the raccoon one way door onto a protective screening which is installed over the raccoon entry point. Usually the removal process takes a day up to 7 days depending on the season and temperatures. When the removal procedure is done, we return to remove the one way door and install meshing over the area where the door used to be. This method is humane and puts the least amount of stress on raccoons. Furthermore if repairs are needed consequent to raccoon at entry points we offer repair services to avoid leakage into your attic. For open spaces such as backyard nuisance problems, we offer raccoon or wildlife live trapping and relocation services. As part of our inspection service, our technicians find vulnerable points that raccoons and wildlife can enter your attic and provide a prevention package for your home. Prevention is optional but highly recommended for homeowners who wish to remain wildlife free. Finally you receive a 2 year written warranty on all our physical work!
North York homes are a constant target for the blooming raccoon population making raccoon removal services a high traffic service. Normally raccoons enter North York homes through ventilation caps, pipes, roof junctions and sometimes the middle of the roof. At SIA Wildlife Control we believe the best removal method is with a raccoon one way door. This method is a 100% guaranteed and puts the least amount of stress on raccoons.
When we arrive at a home with a raccoon problem, we conduct a full inspection of the roof and attic. Once the raccoon entry point is found, our technicians install the raccoon one way door over the entry point which is attached onto a protective mesh barrier. One way doors are designed specifically for the animal in question, whether it's a squirrel, raccoon or skunk. In the baby season our team will inspect your attic and physically remove raccoon babies. The babies will be put inside an incubator which will be left on your roof for the mother raccoon to relocate. We will return after a few days to remove the box.
Squirrels are known for being destructive and persistent. They will chew electrical wiring, displace insulation and make a ruckus in the ceiling. Some squirrel entry points to the attic include vents, pipes, junction gaps and roofline gaps. Squirrel removal in North York is done similarly to that of a raccoon removal procedure. The only differentiating factor is the type of exclusion (one-way) device. The device suited for squirrel exclusion is attached to the galvanized carbon steel mesh, which is then installed over the entry point.
During the month of March and again in August to September squirrels will prepare nesting for the arrival of their babies. The location that they choose will either be outdoors in a tree (the thicker the better) or an unsuspecting North York home. The first step to a squirrel problem in the attic is inspection. We will perform a full inspection of the roof and attic to find squirrel entries and check the attic for babies. Babies in the baby season have to be physically removed and placed in an incubator for relocation.


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Curatio and Wellness Garage launch Unique Social Approach to Diabetes Prevention and Management
SAN FRANCISCO - Jan. 7, 2019 - TelAve -- Today, at the StartUp Health Festival at JP Morgan - Curatio, the world's first social health prescription, announced a new partnership with Dr. Brendan Byrne and Wellness Garage. The new partnership will provide free, private, and personalized prevention and treatment programs for diabetes support.
Diabetes affects 22.1% of Canada's population, and in 2016 was the direct cause of 1.6 million deaths worldwide. Lifestyle measures can be taken to prevent or delay the onset of type 2 diabetes. Diabetes can also be managed through a combination of diet and physical activity, along with lowering blood glucose and levels of other known risk factors. By taking into consideration the individual lifestyles and needs of patients, Curatio and Dr. Byrne are working to create personalized, private patient groups to overcome diabetes in a completely novel way.
"As a society, we are starting to understand the detrimental and costly impact that isolation has on health outcomes and wellbeing. No patient should be alone when managing a health condition. Curatio helps partners deliver private, social, patient support programs that combine personalized support with daily disease management for an all-in-one solution that drives better health outcomes and most importantly, better lives," said Lynda Brown-Ganzert, founder and CEO of Curatio.
Curatio provides peer support, trusted information and programs for individuals with health challenges. By combining matchmaking technology, curated content and easy-to-use disease tracking tools, Curatio puts health empowerment in the hands of patients.
Curatio has found that social support is the missing link in healthcare, with 75% of its initial users already showing improved health behaviors and 80% increased interest in personal health management. With Curatio, patients have a community and lifeline to professional medical advice, straight from their personal device, which fills the gap between in-hospital support group sessions.
Curatio is free to download on iOS and Android. The platform is also available for licensing to hospitals, healthcare providers, payers, pharmaceutical companies, government and NGOs in a white label or sponsorship model. Licensors can integrate the platform with existing programs, or use as its own private social network. With Curatio, licensors can curate branded digital content, build relationships with patients, and measure aggregate patient data to better understand population health. Through this use case, Curatio not only increases medication and care plan adherence, but also provides cost savings for hospitals. Curatio has MSAs in place with global pharmaceutical companies, is live in 80+ countries and available in 4 languages.
For more on Curatio or to white-label the platform, visit curatio.me.
Curatio CEO Lynda Brown-Ganzert is at the 2019 StartUp Health Festival in San Francisco and is available for a set number of 1-on-1 meetings. If you would like to book a 15 minute demo and case study review, please get in touch at info@curatio.me.
Curatio
Lynda Brown-Ganzert
curatio.me
info@curatio.me
Source: Curatio
Filed Under: Technology, Mobile


A man gave up his seat for me in the sardine-packed MRT today. By the looks of his scuffed shoes and badly patched-up trousers, a day worker. Bodies were jostling to and fro as the train went from station to station. On the third stop from the one where I boarded, the day worker stood up and said 'ma'am.' He looked at the man seated next to him and whispered 'nakakahiya.' The other man also stood up and gave up his seat to the nearest woman. I wonder what prompted the act of seat-giving. was I looking schoolmarm-ey today with my hair in a bun? Did my look evoke childhood memories of his teacher from the barrio - good, warm memories which prompted a show of generosity/gallantry? If so why did he say 'nakakahiya?' Was he ashamed of the fact that a woman stands while he - an able-bodied man is seated? If not gendered sensibilities, was it a matter of class? My schoolmarm bun to his blue collar?


Following a sampling programme earlier this year, Intel-Micron Flash Technologies (IMFT) has now announced that the move to 25nm is now in full swing, with the first batches of 25nm NAND chips now entering mass production.
The 8GB chips measure 167mm2, and are based on multi-level cell (MLC) technology with two bits per cell. The move to 8GB chips with tiny 25nm transistors will enable device makers to squeeze a much greater capacity into small devices.
In fact, according to IMFT, it could reduce the chip count by 50 per cent in comparison with previous generations.
IMFT reckons a 256GB solid state drive (SSD), for example, can now be built with just 32 chips, compared with 64 using the previous generation of technology. The partnership also points out that a 32GB smartphone now only needs four chips, and a 16GB flash drive only needs two.
The 25nm chips originally started sampling in February, and it looks as though IMFT is now on schedule to with its promise of mass production in the first half of this year.
Intel and Micron expect the densely-packed chips to be used in a variety of devices, from solid state drives, to USB memory keys, SD cards, MP3 players and camera memory.
Intel and Micron's NAND-partnership first kicked off in 2006 with a 50nm process, which was followed in 2008 by a 34nm process.
However, it will be interesting to see where IMFT goes after this. Samsung has already started sampling 20nm NAND chips, and Toshiba has also announced plans for sub-25nm flash memory.


Have a look at our training proposals here and contact us by phone +45 28 55 95 79 and let's have a talk about your needs. You can have the process that is best for you and your employees. Be inspired and call us.


Color: Red | Product Packaging: Standard Packaging Superior mixing. Through liquid simulation, your Cyclone Cup is proven to mix better than today's leading shaker bottle. Today's leading shakers utilize free floating mixing elements, such as wire whisk balls. These flow with the liquid inside. As a result, mixing is not as efficient. Your Cyclone Cup however utilizes patented Cyclone technology. The Cyclone inside is stationary and moves against the flow of your ingredients. This maximizes the stream of kinetic energy for superior mixing every time. BPA Free.
I was happy to get to try this Cyclone Cup Shaker, Red from Cyclone Cups. I use this type of cup every day but had not tried the cyclone cup until now. I like that it has the bottom compartment to store protein powder or whatever I am mixing up for the day. I like that I can store this extra powder for later in the day if I am out all day and not at home to mix up a second beverage. I have found that I have to be careful how much liquid I add because after the top is on the level rises quite a bit. I am not sure how the cyclone is suppose to work but it seems like a basic shaker cup to me. When using a meal replacement during the day and not having a place to rinse the cup out, it gets difficult for me to hand wash in the evening when I get home. A dishwasher would be helpful in this situation.