text:
\section{Introduction}

The need for optimization has received a lot of attention in different application areas. Formally, optimization algorithms seek to find a parameter vector $x^{*}$ so as to minimize a cost function $f(x): \mathbb{R}^{D} \rightarrow  \mathbb{R} $, i.e. $f(x^{*}) \leq f(x)$ for all $x \in \Omega $, where $\Omega = {\mathbb{R}}^{D}$ is the search domain and $D$ is the dimension of the problem. There are no a prior hypothesis about $f$ and optimization algorithms should treat them as black-box functions. This motivated the development of MAs which do not take advantages of problem structure.
\par
MAs are one of the fastest growing fields aimed at solving different complex and highly non-linear real-world problems by inspiration from the process of natural evolution or physical processes~\cite{rakhshani2017snap,kang2018hybrid}. In MAs, we often have a population of candidate solutions that strive for survival and reproduction.  In every iteration,  different search  operators are applied to the candidate solutions and then the population will be updated based on its success in achieving the goal. Over the last decade, there has been an explosion in the development of a variety of extensions to further enhance the performance of MAs. However, there are no clear guidelines on the strengths and weaknesses of alternative methods such as the DL models for developing more enhanced optimization algorithms.
\par
The DL approaches use a hierarchy  of  features in conjunction with several layers to learn complex non-linear mappings between the input and output layer. As opposite to traditional machine learning methods that use handmade features, the  important features are discovered automatically  and  are  represented  hierarchically. This is known to be  the   strong   point   of  DL  against traditional  machine  learning  approaches. Accordingly, these models have been described as universal learning approaches that are not task specific and can be used to tackle different problems arise in different research domains~\cite{alom2018history}. In this work, we propose a simple, yet effective approach for numerical optimization based on the DL. The proposed MaNet adopts a Convolutional Neural Network (CNN); which are regularized version of fully-connected neural networks inspired from biological visual systems~\cite{krizhevsky2012imagenet}. The "fully-connectedness" of CNNs enables them to tackle the over-fitting problem and it is reasonable to postulate that they may outperform classical neural networks for difficult optimization tasks.
\par
The rest of the paper is organized as follows. Section 2 presents a review on the related works and describes our motivations. In Section 3, we elaborate technical details of the MaNet approach. In Section 4, a series of experiments are conducted to show the performance of the introduced method. The last section summarizes the paper and draws conclusions.

\section{Related works and motivations}

The idea of solving optimization problems using neural networks has an old history which has seen a number of advances in recent years~\cite{kennedy1988neural,snoek2015scalable,amos2017optnet,andrychowicz2016learning,li2016learning}. In~\cite{snoek2015scalable}, authors developed a Bayesian optimization method, called as DNGO, based on deep neural networks for hyperparameter tuning  of large  scale problems with expensive evaluation. The main idea is to  combine large-scale parallelism with an optimization  method to provide an approximate model  of  the  real  cost  function. They show that DNGO scales in a less dramatic fashion compared to the Gaussian process, while maintains its desirable flexibility and characterization of uncertainty. OptNet~\cite{amos2017optnet} is another method proposed for learning optimization tasks by the virtues of DL, sensitivity analysis, bilevel optimization, and implicit differentiation. The authors highlighted the potential power of OptNet networks against existing networks to play mini-Sudoku. In~\cite{andrychowicz2016learning}, researchers investigated automating the design of an optimization algorithm by Long short-term memory deep networks on a number of tasks. Their results outperform hand-designed competitors for simple convex problems, neural network training and  styling images with neural art. Similarly, Li and Malik~\cite{li2016learning} put forward a  deep learning method for automating algorithm design process. They formulate the problem as a reinforcement learning task according to which any candidate algorithm is represented by a policy and the goal is to find an optimal policy. To verify this finding, the authors conducted a set of experiments using different convex and non-convex loss functions correspond to several machine learning models. The obtained results clearly suggest that the automatically designed optimizer converges faster compared to hand-engineered optimizer.
\par
Some of the above mentioned works mainly aim at providing optimal solutions within a very limited computational time~\cite{snoek2015scalable}, while others ~\cite{andrychowicz2016learning,li2016learning} primarily focus on getting better heuristic solutions. These success stories of DL motivated us to investigate the ability of a moderate model so as to make a balance between the solution accuracy and computational time. Altogether, these are the same desired properties in MAs and our work is a step towards investigating the usefulness and strong potential of this research direction.

\section{The proposed method}

This section presents a new optimization method, called MaNet, to explore the possibility of adopting a lightweight deep learning architecture for continuous optimization tasks. In the following, it is assumed that the reader is familiar with the basic concepts of evolutionary computation and deep neural networks.

\par
The MaNet is designed to have the common properties of the MAs: providing a sufficient good solution with incomplete or imperfect information. It starts  the  optimization  procedure with a set of randomly generated solutions as  genotype. During training the network, MaNet applies the network training components  directly  on  the  genotype, while decodes a genotype into a  phenotype  (i.e., individuals in MAs) only in the last layer. It finds an optimized solution by iteratively improving an initial solution with regard to its cost function. Among different DL models, CNNs trained with an extension of stochastic gradient descent is used to build the MaNet. The CNNs have been central to the largest advances in computer vision~\cite{krizhevsky2012imagenet} and speech processing~\cite{38131}. A CNN is a DL method that uses convolutional layers to filter redundant or even irrelevant input data to increase the performance of the network~\cite{he2016deep}. This consideration also reduces the dimensionality of the input data and  speeds up the learning process in the CNNs. Besides, it allows CNNs to be deeper networks with fewer parameters. Altogether, these properties could make CNNs a potential tool for solving optimization problems; especially when we take into account the history behind the application of feature selection~\cite{rakhshani2019mac} and problem scale reducing~\cite{senjyu2005fast} in the optimization domain.

The architecture of a CNN consists of an input and an output layer, as well as one or more hidden layers. The hidden layers are typically composed of convolutional layers, fully connected layers, normalization layers and pooling layers. The number of hidden layers could be increased depending on the complexities in the input data, but at the cost of more computational expensive simulations.  From the mathematical perspective, convolution layers provide a way of mixing input data with a filter so as to form a transformed feature map. Fully-Connected layers learn non-linear combinations of the high-level features by connecting neurons in one layer to neurons in the previous layer, as seen in multi-layer perceptrons neural networks (MLPs). Moreover, normalization layers are adopted to normalize the data to a network and to speed up learning. This includes batch normalization~\cite{santurkar2018does}, weight normalization~\cite{salimans2016weight}, and layer normalization~\cite{lei2016layer} techniques. Batch normalization is applied to the input data or to the activation of a prior layer, weight normalization is applied to the weights of the layer and layer normalization is applied across the features. The pooling layers are usually inserted in-between successive convolutional layers to further reduce the number of parameters in the network. A CNN network can have local or global pooling layers that may compute a max or an average.

Inspired by the aforementioned components in CNNs, the MaNet is designed to train a model so as to solve an optimization problem (Fig. \ref{fig:MaNet}). The existing feature selection and dimensionality reduction policies in CNNs help MaNet to find complex dependencies between the parameters. The MaNet start optimization by generating a set of random $n \times m$ inputs for the model (i.e., the raw pixel values of the image). So, each individual solution is represented by a matrix rather than a vector. During training the network, convolutional layers transform the initial population layer by layer to a final feasible solution. This large part genotype representation enables the optimizer to keep genetic information that was necessary in the past as a source of exploration, as well as a playground for extracting new features that can be advantageous in the exploitation.

 The MaNet multiplies the initial population with a two-dimensional array of filters that are connected to every disjoint region. The output of multiplying the filters with initial population forms a two-dimensional output array called as "feature map". They are obtained by convolution process upon the initial population with a linear filter, without applying a non-linear function or applying feature normalization methods. Similar to other DL models, the filters/kernels in MaNet are learned using the back-propagation algorithm for each specific optimization task. This is the novel aspect of DL techniques that filter weights are learned during the training of the network and are not hand designed. Accordingly, CNNs are not limited to image data and could be used to extract a variety types of features. Thank to this characteristic, MaNet will be forced to extract the features that are the most important to minimize the loss function for the problem at hand the network is being trained to solve. In each convolution layer, we have some predefined hyperparameters that can be used to modify the behavior of the model: the filter size and the number of filters. The first one simply denotes the dimensions of the filter when applying the convolution process, while the second one determines the number of different convolution filters.
  \par
 In MaNet, multiple convolution layers are stacked which allows convolution layers to be applied to the output of the previous layer, results in a hierarchically set of more decomposed features. Finally, a Dense layer (or fully-connected) with linear activation function will be used to form the final solution vector. As it can be seen from Fig. \ref{fig:MaNet}, MaNet has a very simple structure and can benefit from the advantage of having a fast network training process\footnote{Netron Visualizer is used to illustrate the model. The tools is available online at: https://github.com/lutzroeder/netron}. Indeed, it has  only 3,742 trainable parameters compared to state-of-the-art models~\cite{simonyan2014very} which have millions or billions of parameters. This could facilitate the application of MaNet for optimization tasks where a small amount of data (i.e., population) is available.

 \begin{figure}[H]
    \centering
    \includegraphics[width=0.80\linewidth]{images/Fig1.pdf}
    \caption{An overview of the proposed optimization architecture. The MaNet is composed of three convolution layers and one Dense layer (or fully connected layer). In each layer, the number of filters and the filter size are 6 and 3, respectively. The activation function for all the layers is proportional to their inputs.}
    \label{fig:MaNet}
\end{figure}

 As it can be seen, the MaNet is composed of two similar architectures which are subjected to different optimization procedures. The first one uses a batch size of one and the other uses 64 as its batch size. The batch size is a hyperparameter of gradient descent that should be tuned for each optimization task. To do so, MaNet integrates a reinforcement strategy inspired from SDCS~\cite{rakhshani2017snap}. Technically speaking, SDCS is a simple metaheuristic algorithm which toggles continually between two snap and drift modes to enhance reinforcement and stability. Based on this idea, MaNet introduces a self-adaptive strategy to tune the batch size hyperparameter.  More precisely, it is looking to see if the best cost function stops improving after some number of epochs, and if so then it restarts the optimization process and continuous the search by the architecture which obtained a higher overall performance so far. Finally, it is worth mentioning to note that the initial population will remain unchanged during training the network and the algorithm will evolve a set of filters. The goal of MaNet then, is to transfer the initial population on one end to evolved solutions on the other hand. This is one of the main differences between MaNet and evolutionary algorithms.

\section{Experimental}
\subsection{Experimental setup}
We use a set of 9 benchmark functions given in CEC 2017 [20] to evaluate the performance of the proposed algorithm\footnote{The codes for CEC problems and the jSO algorithm are publicly available at: \\ http://www.ntu.edu.sg/home/EPNSugan/index\_files/CEC2017/CEC2017.htm}. The considered  problems  are  widely  used  in  the optimization community and are challenging for any optimization approach. This work uses several problems  that can  be  classified  into  unimodal  (F1 and F3) and  multimodal (F4-10) minimization functions with   different   properties including separable, non-separable, rotated, ill-condition  and shifted\footnote{F2  has  been  excluded by the organizers because  it  shows  unstable  behavior  especially  for  higher  dimensions~\cite{awad2016problem}}. The aforementioned problems are adopted on the GPU so as to be linked with machine learning libraries. We refer the reader to the  detailed  principle  about  the  definition  of CEC2017 benchmark functions as defined in~\cite{awad2016problem}. To verify the algorithm scalability, 30-dimensional and 50-dimensional problems are used. All functions
should be minimized and have a global minimum at $f(x) = 0$. The results  are  reported  according to their distance  from  the  optimum. We trained MaNet on each problem by using the parallel power of 9 NVIDIA Tesla K20m GPU cards.

It has been shown that various extensions of the differential evolution (DE)~\cite{storn1997differential} algorithm are always among the winners of the CEC competition. Having this is mind, we used jSO~\cite{brest2017single} algorithm for the purpose of comparison which is the second ranked algorithm in CEC2017 competitions for the single objective optimization track. The algorithm is shown to outperform  LSHADE~\cite{tanabe2014improving} (the winner of the CEC2014) and its new extension for CEC2016 (iL-SHADE~\cite{brest2016shade}). All the results are taken from the original study. In  order  to  make  a  fair  comparison,  all the experiment conditions  are  the  same.  The  number  of  function  evaluations  is $10,000 \times D$, where $D$ is the problem dimension~\cite{awad2016problem}. To  tackle  the negative  effects  of  the random  initial  configurations, each  algorithm  were  run  51 times~\cite{awad2016problem}. The  initial  population  is  generated  randomly  within  the  search  bounds  $[-100,100]$. The parameters of the jSO are the same as reported in the original study~\cite{brest2017single}. In MaNet, we have 3 convolution layers which are sequentially connected to each other. In each layer, the number of filters and the filter size are 6 and 3, respectively. The MaNet is a CNN model and needs a lot of input data to be well trained and so the population size is fixed to $n=5,000$. Moreover, $m$ is considered to be 64 for all the problems. The MaNet will be optimized using the Adam algorithm~\cite{kingma2014adam}.
\vspace{-0.5cm}
\subsection{Results and discussion}

Tables   1-2   present   best,   worst,   mean   and   standard   deviation  (Std.)  results  of the MaNet and jSO on 9 problems over 51 runs. Table 1 reports the results for 30 dimensional problems, while Table 2 shows the performance of the competitive algorithms for 50 dimensional cases. In  these  tables,  a statistical test is  also  presented  to  assess  the  significance  of  performance  between the results  of  the  jSO  and  MaNet.

\vspace{-0.35cm}

\begin{table}[H]
\centering

\caption{The obtained results by MaNet and jSO for 30 dimensional problems over 51 runs~\cite{awad2016problem}. The results for jSO are directly taken from the original paper~\cite{brest2017single}.}
\scriptsize
\begin{tabular}{|l|l|l|l|l|l|l|c|}
\hline
Function            & Algorithm & Best       & Worst      & Mean                & Median     & Std.       & Sign                  \\ \hline
\multirow{2}{*}{1}  & MaNet     & $3.71e+02$ & $1.33e+03$ & $7.94e+02$          & $8.02e+02$ & $2.03e+02$ & \multirow{2}{*}{$-$} \\ \cline{2-7}
                    & jSO       & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ &                    \\ \hline
\multirow{2}{*}{3}  & MaNet     & $3.69e+04$ & $7.10e+04$ & $5.85e+04$          & $5.85e+04$ & $6.46e+03$ & \multirow{2}{*}{$-$} \\ \cline{2-7}
                    & jSO       & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ &                    \\ \hline
\multirow{2}{*}{4}  & MaNet     & $1.46e-05$ & $3.99e+00$ & \textbf{5.88e-01} & $6.79e-04$ & $1.41e+00$ & \multirow{2}{*}{$+$} \\ \cline{2-7}
                    & jSO       & $5.86e+01$ & $6.41e+01$ & $5.87e+01$          & $5.86e+01$ & $7.78e-01$ &                    \\ \hline
\multirow{2}{*}{5}  & MaNet     & $0.00e+00$ & $1.99e+00$ & \textbf{5.85e-01} & $1.34e-07$ & $6.59e-01$ & \multirow{2}{*}{$+$} \\ \cline{2-7}
                    & jSO       & $3.98e+00$ & $1.32e+01$ & $8.56e+00$          & $8.02e+00$ & $2.10e+00$ &                    \\ \hline
\multirow{2}{*}{6}  & MaNet     & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ & \multirow{2}{*}{$=$} \\ \cline{2-7}
                    & jSO       & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ &                    \\ \hline
\multirow{2}{*}{7}  & MaNet     & $3.26e+01$ & $3.41e+01$ & \textbf{3.33e+01} & $3.33e+01$ & $3.91e-01$ & \multirow{2}{*}{$+$} \\ \cline{2-7}
                    & jSO       & $3.61e+01$ & $4.31e+01$ & $3.89e+01$          & $3.91e+01$ & $1.46e+00$ &                    \\ \hline
\multirow{2}{*}{8}  & MaNet     & $0.00e+00$ & $4.97e+00$ & \textbf{2.29e+00} & $1.99e+00$ & $1.15e+00$ & \multirow{2}{*}{$+$} \\ \cline{2-7}
                    & jSO       & $4.97e+00$ & $1.30e+01$ & $9.09e+00$          & $8.96e+00$ & $1.84e+00$ &                    \\ \hline
\multirow{2}{*}{9}  & MaNet     & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ & \multirow{2}{*}{$=$} \\ \cline{2-7}
                    & jSO       & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ &                    \\ \hline
\multirow{2}{*}{10} & MaNet     & $1.09e+04$ & $1.13e+04$ & $1.11e+04$          & $1.11e+04$ & $1.19e+02$ & \multirow{2}{*}{$-$} \\ \cline{2-7}
                    & jSO       & $1.04e+03$ & $2.04e+03$ & \textbf{1.53e+03} & $1.49e+03$ & $2.77e+02$ &                    \\ \hline
\end{tabular}
\end{table}

\vspace{-0.8cm}

\begin{table}[H]
\centering

\caption{The obtained results by MaNet and jSO for 50 dimensional problems over 51 runs~\cite{awad2016problem}. The results for jSO are directly taken from the original paper~\cite{brest2017single}.}
\scriptsize
\begin{tabular}{|l|l|l|l|l|l|l|c|}
\hline
Function            & Algorithm & Best       & Worst      & Mean       & Median     & Std.       & Sign               \\ \hline
\multirow{2}{*}{1}  & MaNet     & $3.67e+02$ & $2.06e+03$ & $1.39e+03$ & $1.46e+03$ & $3.71e+02$ & \multirow{2}{*}{$-$} \\ \cline{2-7}
                    & jSO       & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ &                    \\ \hline
\multirow{2}{*}{3}  & MaNet     & $9.80e+04$ & $1.42e+05$ & $1.23e+05$ & $1.25e+05$ & $8.88e+03$ & \multirow{2}{*}{$-$} \\ \cline{2-7}
                    & jSO       & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ &                    \\ \hline
\multirow{2}{*}{4}  & MaNet     & $3.10e-06$ & $1.53e-03$ & \textbf{8.22e-04} & $9.96e-04$ & $4.46e-04$ & \multirow{2}{*}{$+$} \\ \cline{2-7}
                    & jSO       & $1.32e-04$ & $1.42e+02$ & $5.62e+01$ & $2.85e+01$ & $4.88e+01$ &                    \\ \hline
\multirow{2}{*}{5}  & MaNet     & $1.99e+00$ & $1.09e+01$ & \textbf{6.15e+00} & $5.97e+00$ & $2.20e+00$ & \multirow{2}{*}{$+$} \\ \cline{2-7}
                    & jSO       & $8.96e+00$ & $2.39e+01$ & $1.64e+01$ & $1.62e+01$ & $3.46e+00$ &                    \\ \hline
\multirow{2}{*}{6}  & MaNet     & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ & \multirow{2}{*}{$=$} \\ \cline{2-7}
                    & jSO       & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ &                    \\ \hline
\multirow{2}{*}{7}  & MaNet     & $5.49e+01$ & $5.65e+01$ & \textbf{5.58e+01} & $5.59e+01$ & $3.62e-01$ & \multirow{2}{*}{$+$} \\ \cline{2-7}
                    & jSO       & $5.75e+01$ & $7.42e+01$ & $6.65e+01$ & $6.66e+01$ & $3.47e+00$ &                    \\ \hline
\multirow{2}{*}{8}  & MaNet     & $1.99e+00$ & $8.95e+00$ & \textbf{5.41e+00} & $5.97e+00$ & $1.99e+00$ & \multirow{2}{*}{$+$} \\ \cline{2-7}
                    & jSO       & $9.95e+00$ & $2.41e+01$ & $1.70e+01$ & $1.70e+01$ & $3.14e+00$ &                    \\ \hline
\multirow{2}{*}{9}  & MaNet     & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ & \multirow{2}{*}{$=$} \\ \cline{2-7}
                    & jSO       & $0.00e+00$ & $0.00e+00$ & \textbf{0.00e+00} & $0.00e+00$ & $0.00e+00$ &                    \\ \hline
\multirow{2}{*}{10} & MaNet     & $1.86e+04$ & $1.88e+04$ & $1.87e+04$ & $1.87e+04$ & $6.25e+01$ & \multirow{2}{*}{$-$} \\ \cline{2-7}
                    & jSO       & $2.40e+03$ & $3.79e+03$ & \textbf{3.14e+03} & $3.23e+03$ & $3.67e+02$ &                    \\ \hline
\end{tabular}
\end{table}

The  results  of  the  Wilcoxon  rank  sum  test   are  reported  at  the  $95\%$  confidence  level.  In  these   tables,   '+'   shows   that   MaNet   significantly  outperforms  the  jSO with  $95\%$  certainty;   '-'   indicates   that   the  jSO   is   significantly  better  than  MaNet;  and  '=' shows there is no statistical different between the two compared algorithms. The  significant  results  are  given  in  bold.  For  further  validation,   convergence   graphs of jSO and MaNet for 30 dimensional functions F4 and F8 are given in Fig. \ref{fig:conv-graph}.

As can be seen from Tables 1-2, jSO gives more accurate solutions for the unimodal benchmarks F1 and F3 for both 30-dimensional and 50-dimensional cases. Moreover, with the exceptions of F10, MaNet has equal or significantly better performance on all the multimodal benchmark functions. In fact, the results indicate that MaNet significantly outperforms the jSO on 4 functions (F4-F8), obtains an equal performance on 2 functions (F6 and F9), and has worst results on 3 test cases (F1, F3 and F10). Furthermore, we can see that MaNet is a robust algorithm according to the reported standard deviation results. In addition, these experimental results have confirmed that MaNet is not very sensitive to the increment of dimension and is scalable.  Considering  Fig. \ref{fig:conv-graph}, it can be seen also that  MaNet has  a  more  rapid  convergence  rate than  the  jSO  algorithm for function F4 and F8. In MaNet, we assume that not selection, but rather the combination of different filters is the main source of evolution and that is the reason for having unstable convergence behavior on these functions.

Altogether, these promising results have confirmed that MaNet has a competitive results in comparison with one of the best designed algorithm for the CEC2017 problems. This is quite interesting because MaNet doesn't borrow any search strategy or components from the previously proposed methods for the CEC problems; including CMAES~\cite{loshchilov2013cma}, DE, jADE~\cite{zhang2009jade}, SADE~\cite{qin2005self}, SHADE~\cite{tanabe2013success}, L-SHADE~\cite{tanabe2014improving}, i-LSHADE~\cite{brest2016shade} and jSO.

\begin{figure}
\begin{subfigure}{.53\textwidth}
  \centering
  \includegraphics[width=\linewidth]{images/Fig3_4_30.pdf}

  \label{fig:sfig1}
\end{subfigure}%
\begin{subfigure}{.53\textwidth}
  \centering
  \includegraphics[width=\linewidth]{images/Fig3_8_30.pdf}

  \label{fig:sfig2}
\end{subfigure}
\setcounter{figure}{2}
\centering
\caption{Convergence graphs of the jSO and MaNet for 30 dimensional functions F4 and F8 over 51 runs}
\label{fig:conv-graph}
\end{figure}

As a future work, we are intended to apply the proposed MaNet to all the problems over all the dimensions. Besides, we have to find a way in order to adjust the learning rate hyperparameter for each problem. From Fig. \ref{fig:conv-graph} one can see that a high learning rate in Adam causes the network to generate large numbers for F8 and the updates are going to be just as large. After that, we would like to apply the proposed methodology to more complicated real-world optimization problems.

\section{Conclusion}
This study proposed a new optimization algorithm based on the DL in order to provide an improved search
process. The proposed method verifies convergence conditions by using a CNN model. The simple structure of the MaNet along with feature selection and dimension reduction strategies result in an architecture at a relatively low computational cost. The MaNet optimizer is evaluated using unimodal and multimodal optimization benchmarks from CEC2017 test suite. The obtained results are statistically analyzed and compared with state-of-the-art jSO algorithm.  Evaluations confirm that the introduced MaNet optimization model has a competitive performance in terms of the final solution accuracy and scalability compared to one of the best designed algorithms for the problem at hand.

\section*{Acknowledgments}
This research was supported through computational resources provided by M\'esocentre of Strasbourg: https://services-numeriques.unistra.fr/
\bibliographystyle{splncs04}

redpajama_set_name: RedPajamaArXiv


text:
Q: How to connect android device to "WPA2 PSK" secured wifi hotspot network programmatically? In my Android app I'm trying to connect my Android device to "WPA2-PSK" secured connection and after lot of search I have written following code--
if (securityMode.equalsIgnoreCase("WPA2")) // WPA2
                {

                   wifiConfiguration.SSID = "\"" + networkSSID + "\"";
                    wifiConfiguration.preSharedKey = "\"" + networkPass + "\"";
                    wifiConfiguration.status = WifiConfiguration.Status.ENABLED;
                    wifiConfiguration.allowedGroupCiphers.set(WifiConfiguration.GroupCipher.TKIP);
                    wifiConfiguration.allowedGroupCiphers.set(WifiConfiguration.GroupCipher.CCMP);
                    wifiConfiguration.allowedKeyManagement.set(WifiConfiguration.KeyMgmt.WPA_PSK);
                    wifiConfiguration.allowedPairwiseCiphers.set(WifiConfiguration.PairwiseCipher.TKIP);
                    wifiConfiguration.allowedPairwiseCiphers.set(WifiConfiguration.PairwiseCipher.CCMP);
                    wifiConfiguration.allowedProtocols.set(WifiConfiguration.Protocol.RSN);
                    wifiManager.setWifiEnabled(true);
                    wifiManager.saveConfiguration();
                    int added = wifiManager.addNetwork(wifiConfiguration);
                    System.out.println("added network: " + added);
                    boolean enabled = wifiManager.enableNetwork(added, true);
                    System.out.println("enableNetwork returned: " + enabled);

                }

Above code is executing fine (without any error) but don't know why, connection is not getting establish. Please help. Thank you.!

A: Below id clear api for all type of wifi security-type :
  public void addWifiConfig(String ssid,String password,String securityParam,String securityDetailParam) {
    Log.d(TAG, "Inside addWifiConfig...");
    if (ssid == null) {
        throw new IllegalArgumentException(
                "Required parameters can not be NULL #");
    }

    String wifiName = ssid;
    WifiConfiguration conf = new WifiConfiguration();
    // On devices with version Kitkat and below, We need to send SSID name
    // with double quotes. On devices with version Lollipop, We need to send
    // SSID name without double quotes
    if (Build.VERSION.SDK_INT >= Build.VERSION_CODES.LOLLIPOP) {
        conf.SSID = wifiName;
    } else {
        conf.SSID = Constants.BACKSLASH + wifiName + Constants.BACKSLASH;
    }
    String security = securityParam;
    Log.d(TAG, "Security Type :: " + security);
    if (security.equalsIgnoreCase("WEP")) {
        conf.wepKeys[0] = password;
        conf.wepTxKeyIndex = 0;
        conf.allowedKeyManagement.set(WifiConfiguration.KeyMgmt.NONE);
        conf.allowedGroupCiphers.set(WifiConfiguration.GroupCipher.WEP40);
    } else if (security
            .equalsIgnoreCase("NONE")) {
        conf.allowedKeyManagement.set(WifiConfiguration.KeyMgmt.NONE);
    } else if ("WPA"
            .equalsIgnoreCase(security)
            || "WPA2"
                    .equalsIgnoreCase(security)
            || "WPA/WPA2 PSK"
                    .equalsIgnoreCase(security)) {
        // appropriate ciper is need to set according to security type used,
        // ifcase of not added it will not be able to connect
        conf.preSharedKey = Constants.BACKSLASH
                + password + Constants.BACKSLASH;
        conf.allowedProtocols.set(WifiConfiguration.Protocol.RSN);
        conf.allowedKeyManagement.set(WifiConfiguration.KeyMgmt.WPA_PSK);
        conf.status = WifiConfiguration.Status.ENABLED;
        conf.allowedGroupCiphers.set(WifiConfiguration.GroupCipher.TKIP);
        conf.allowedGroupCiphers.set(WifiConfiguration.GroupCipher.CCMP);
        conf.allowedKeyManagement.set(WifiConfiguration.KeyMgmt.WPA_PSK);
        conf.allowedPairwiseCiphers
                .set(WifiConfiguration.PairwiseCipher.TKIP);
        conf.allowedPairwiseCiphers
                .set(WifiConfiguration.PairwiseCipher.CCMP);
        conf.allowedProtocols.set(WifiConfiguration.Protocol.RSN);
        conf.allowedProtocols.set(WifiConfiguration.Protocol.WPA);
    }
    String securityDetails = securityDetailParam;
    if (securityDetails
            .equalsIgnoreCase(Constants.NETWROK_ADDITIONAL_SECURITY_TKIP)) {
        conf.allowedGroupCiphers.set(WifiConfiguration.GroupCipher.TKIP);
        conf.allowedPairwiseCiphers
                .set(WifiConfiguration.PairwiseCipher.TKIP);
    } else if (securityDetails
            .equalsIgnoreCase(Constants.NETWROK_ADDITIONAL_SECURITY_AES)) {
        conf.allowedGroupCiphers.set(WifiConfiguration.GroupCipher.CCMP);
        conf.allowedPairwiseCiphers
                .set(WifiConfiguration.PairwiseCipher.CCMP);
    } else if (securityDetails
            .equalsIgnoreCase(Constants.NETWROK_ADDITIONAL_SECURITY_WEP)) {
        conf.allowedGroupCiphers.set(WifiConfiguration.GroupCipher.WEP104);
        conf.allowedGroupCiphers.set(WifiConfiguration.GroupCipher.WEP40);
    } else if (securityDetails
            .equalsIgnoreCase(Constants.NETWROK_ADDITIONAL_SECURITY_NONE)) {
        conf.allowedPairwiseCiphers
                .set(WifiConfiguration.PairwiseCipher.NONE);
    }
    WifiManager wifiManager = (WifiManager) mContext
            .getSystemService(Context.WIFI_SERVICE);

    int newNetworkId = wifiManager.addNetwork(conf);
        wifiManager.enableNetwork(newNetworkId, true);
        wifiManager.saveConfiguration();
        wifiManager.setWifiEnabled(true);
}

This is working example

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text:
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The reasons every investor should understand blockchain
Article, Blockchain, Investments, TechnologyBy Alex Baine 11/02/2018
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PDSi Kids: When children learn to lead themselves, they can learn to lead in the future
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A chat with #WILKSA speaker Wafa Al Obaidat, the 28-year-old CEO and Creative Director of Obai and Hill
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Article, Finance, InvestmentsBy Alex Baine 18/12/2017
Photo credit: From left to right: Ivo Detelinov, Vice President & Head of PE Fund, Riyadh Taqnia Fund, Hasan Haider, Partner, 500 startups, Joe Peterson , CEO of Sure Inc, Promoth Manghat, CEO, UAE Exchange, Nicholas Watson, Managing Director, Naseba Economically speaking, 2017 has been a rollercoaster year. From political fallout in the currency markets, to…
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Own our own knoll top in Page Springs with a view of one of Arizona's most extraordinary greenbelt areas on Oak Creek. Build your slice of heaven on this 4.23 acre parcel (407-29-003C)in the heart of Cornville/Page Springs wine country. This parcel overlooks vineyards along one of Arizona's most scenic roads and has an unstoppable views of Mingus Mountain. The view is smack dab in the flight path of eagles, hawks, herons, and birds of all kinds that live in and around the AZ Game and Fish Dept. Page Springs Fish Hatchery and Bird Sanctuary. Survey recently completed for this split. Nearby activities abound, wine tasting, trout fishing, hiking, picnicking and fun. 14.2 acre parcel (003B) also available.


Today at The Current I was fortunate to work with the artist Bombino in the studio for a recording session. Bombino is a Tuareg musician from Niger who has become more widely recognized in the US after working with Dan Auerbach of the Black Keys to record his most recent album. The vibe in the session at The Current was a lot of fun, and I jumped at the chance to attend the show. I only squeezed to the front to snap photos for two songs, spending most of the show near the back just enjoying the music. The full session at The Current will be posted Thursday with the audio, photos, and video. I continue to have a number of past shoots to post here to the blog, but I figured it was worth a break from that to post something fresh.


text:
What rabbis can do
The Jewish Effective Giving Blog
Reaching Together to Reach the World
By Rabbi David Lyon
Generations of young people have been taught the meaning of the Hebrew value, "Tikkun Olam," literally, to repair the world. They have given tzedakah (donations of coins and dollar bills), collected food and clothing for underserved populations, and participated in various social action and bar/bat mitzvah projects. Then this generation of youths grew up and observed that the world they were helping wasn't closer to being repaired. In some ways, the world became more desperate. They weren't disillusioned by their lack of success, and they weren't fooled by their mentors or rabbis, but they were made wiser by what they learned about the world around them and how real change can happen.
Our inspiration and theirs begins in Torah (Exodus 25), where we're told, "Take from all those whose hearts are moved…" and learn from commentaries that even one person whose heart is sufficiently moved can complete the task of building the Tabernacle. The Hebrew word for such a person whose heart is moved is, today, the modern Hebrew word for the volunteer. A person who gives freely and without compensation is a volunteer, and the one who regularly models the role for others has what is known as the volunteer spirit. Though Torah lauds such an individual, the commentaries regard it only as an ideal. Better, we learn, is for the entire community to feel that everyone has something to offer for the work that needs to be done. In Exodus, the goal is to build a "Mishkan," as we read, "Build me a sanctuary that I may dwell among you" (Exodus 25).
That sanctuary, surrounded by a sacred community, represents the expectation that in a community guided by God's commandments (mitzvot) everyone there will thrive and enjoy prosperity and peace. But from the Torah to the Hebrew prophets, the struggle for the ideals seemed farther to reach than ever, and calls to adhere to God's laws often fell on deaf ears. From then until now, the ideals remain the same, but our goal to accomplish them grows more difficult and seemingly farther away. In our complex world, supply and demand can affect the number of resources that are available to a hungrier world. Limited access, either real or artificial, compounds the struggle and the need. Equity, and not just equality, helps us understand the challenges and how we can try again to resolve them.
We often begin by speaking about giving charity, but "charity" is a word that doesn't exist in Hebrew. It isn't a Jewish value. At its root, charity comes from the Latin, to give from love. In Christianity, love and God are equated. To give from love is to emulate God. Judaism doesn't disqualify a gift that's given from love, but it doesn't wait for God-like love. Judaism's word is the Hebrew word, "tzedakah," and it means justice. In places where there is hunger, homelessness, and poverty, there is no justice. Our acts of tzedakah make people whole by repairing the injustices in their lives. Tzedakah might be given with love or even in anonymity, as Maimonides taught in the 12th century, but the people who need relief can't wait. They needed it yesterday, not tomorrow.
In the New Year, we have to begin again to accomplish the goals that have long been at the heart of our Jewish effort to transform the world from what it is into the world that it ought to be. The Jewish Effective Giving Initiative, a project of the World Union for Progressive Judaism, was created "to inspire rabbis and Jewish leaders [new and familiar], to save lives by introducing their communities to effective giving." The initiative relies on rigorous research and the best available data to ensure that donations and support go to organizations that are "extremely efficient at saving and substantially improving lives around the world." The project points out that while there are hundreds of thousands of charities in the world, there are a select few that can, with a large degree of certainty, save a life and prevent many cases of severe illness, mostly among children, for around $3,000-5,000.
The Jewish Effective Giving initiative is an opportunity to spark this generation's interest by scaling their efforts to reach larger goals without failing to get the work done. We shouldn't stop making a difference locally, but there's an opportunity to demonstrate to young and old, alike, that joining congregational and organizational efforts can reach new levels of effectiveness. Imagine what we can do together with the over 30 other congregations that have already joined this effort and pledged to save a life this year.
Imagine the multiplication factor over 30 congregations (and counting) that link young people and their families together. Engaging young people in a project that isn't only close to home, but also global and in partnership with other Jewish friends, would appeal to the way they're already experiencing the world. For them, the boundary of their world begins and ends online and on social media. On any given day, they've been across the world and back, they've played video games with friends in foreign countries, and they've searched for information that takes only the right search word and a nanosecond to retrieve. Joining their access to the world and our Jewish need to make a difference joins two forces for good. Together, we can scale the power of a single mitzvah.
When we join our Jewish values with modern opportunities, we reveal Judaism's enduring purpose and relevance. Jewish Effective Giving provides the ways and the means to lift up our obligation to respond to the Mitzvah and to make a difference in the part of world we can touch. Today, we can touch the world where we live and where technology can take us. Where should we go together?
Rabbi David Lyon is Senior Rabbi at Congregation Beth Israel in Houston, Texas.
main blog page
The Jewish Effective Giving Initiative is a project of the World Union For Progressive Judaism.
The World Union for Progressive Judaism is the international network of the Reform, Liberal, Progressive and Reconstructionist movements, serving 1.2 million members worldwide in more than 1,250 congregations in more than 50 countries.


text:
Patrick Henry (Hanover County, Virginia 29 mei 1736 - Brookneal, Virginia, 6 juni 1799) was een Amerikaans orator en staatsman en de eerste en zesde gouverneur van Virginia. Hij was een van de Amerikaanse Founding Fathers en een pleitbezorger van individuele vrijheden. In de aanloop naar de Amerikaanse Onafhankelijkheidsoorlog hield hij een rede die bekend is geworden door de slotwoorden die Henry sprak: "Give me Liberty, or give me death!" (Geef me de vrijheid of geef me de dood!). Later zou Henry zich tegen de grondwet uitspreken.

Vroege leven
Henry werd geboren op een tabaksplantage in Virginia als zoon van John en Sarah Henry. Hij bezocht korte tijd een school voordat zijn vader hem begon te onderwijzen. Hij opende samen met zijn broer William een winkel in 1752 die al snel ten onder ging en nadat hij op zijn 18e trouwde met Sarah Shelton, die een plantage bezat, trachtte hij als planter en, nadat zijn plantage in 1757 afbrandde, wederom als winkelier de kost te verdienen. In 1760 besloot Henry rechten te gaan studeren en slechts korte tijd later, zonder een formele opleiding te hebben gevolgd, werd hij advocaat. Hij verwierf naam in 1763 bij de zogenaamde Parson's Cause zaak waarbij hij, in een zaak aangaande de prijs van tabak en het betalen van salarissen aan Anglicaanse geestelijken hierop gebaseerd, pleitte dat een koning die een noodzakelijke en door de lokale wetgevende vergadering aangenomen wet van een veto voorziet een "tiran" is die het "recht op gehoorzaamheid" van zijn onderdanen heeft verspeeld.

In 1765 werd Henry verkozen in de wetgevende vergadering van Virginia, het House of Burgesses alwaar hij daags na zijn aantreden een aantal resoluties indiende tegen de door het Britse parlement aangenomen Stamp Act, een belasting op gedrukte materiaal. Henry pleitte in harde bewoordingen tegen de Stamp Act en hij werd door sommigen als landverrader gezien wegens zijn oppositie tegen het Britse gezag. Op de beschuldiging van landverraad zou Henry hebben geantwoord: "als dit landverraad is, maak er het beste van".

Vijf van de door Henry ingediende resoluties werden uiteindelijk aangenomen en de oppositie tegen de Stamp Act werd door zijn oratiek ook in de andere Britse kolonies versterkt. Henry kreeg bekendheid in de Dertien Koloniën en ook in Groot-Brittannië zelf naar aanleiding van zijn radicale ideeën.

Revolutie

Enkele jaren na het Bloedbad van Boston en kort na de Boston Tea Party werd Henry delegatielid voor Virginia in het eerste Continental Congress. Hij nam ook kort zitting in het Tweede Continental Congress maar trok zich hieruit al snel terug. Hij sprak zich uit voor een gezamenlijke strijd tegen de Britse koloniale autoriteiten en verklaarde onder meer: "Ik ben geen Virginian, ik ben een Amerikaan".

Tussen het Eerste en het Tweede Continental Congress in keerde Henry terug naar Virginia en stelde in Hanover County een militie samen. Ook kwam zijn vrouw in 1775 te overlijden. In maart 1775 woonde Henry een conventie bij in Virginia. De leden van deze conventie waren in twee kampen verdeeld. Het ene kamp wilde vreedzaam protesteren tegen de Britse koloniale overheersers terwijl het andere kamp, Henry incluis, meer actief, desnoods militair, verzet voorstonden. Henry riep op Virginia gereed te maken voor gewapend verzet en diende hiertoe een resolutie in op de conventie. Op 23 maart 1775 hield hij een redevoering voor de conventie die eindigde met de bekende woorden "Give me Liberty, or give me death!" (Geef me de vrijheid of geef me de dood!). De conventie nam Henry's resolutie later met krappe meerderheid aan.

Tijdens Henry's korte zittingsperiode in het Tweede Continental Congress werd in Virginia een tweetal regimenten samengesteld en Henry verkreeg het bevel hierover. George Washington stelde dat het een grove fout was van zijn landgenoten om Henry het bevel over een legeronderdeel te geven omdat hij dan niet meer in het Congres zou kunnen dienen. Begin 1776 werden de twee Virginia regimenten onder bevel van kolonel Henry ondergebracht in het Continentale Leger. Henry's bevel over de legeronderdelen zou van korte duur zijn en na (deels politiek gemotiveerde) frictie met andere bevelhebbers legde hij zijn functie in het leger neer.

Na zijn kortstondige militaire loopbaan ging Henry wederom de politiek in en nam hij zitting in een conventie die in Williamsburg gehouden werd. De conventie riep de delegatieleden van Virginia bij het Tweede Continental Congress op om voor de onafhankelijkheid te stemmen, een positie die Henry na enige aarzeling steunde. De conventie van Williamsburg stelde ook een grondwet voor Virginia op en Henry stelde mede de Virginia Declaration of Rights op. Henry werd door de conventie driemaal gekozen als gouverneur van Virginia, telkens voor een ambtstermijn van één jaar. Hij diende aldus van 6 juli 1776 tot 1 juni 1779. In deze periode hertrouwde Henry met Dorothea Dandridge.

Na de Revolutie keerde Henry kortstondig terug naar zijn plantage vooraleer hij terugkeerde naar de politiek. In 1780 werd hij verkozen in de wetgevende vergadering van Virginia waar hij een van de belangrijkste tegenstanders van James Madison was. Van 1784 tot 1786 diende hij wederom als gouverneur van Virginia.

Latere jaren
In de periode vlak na de Revolutie werden de nieuw onafhankelijk geworden staten geregeerd onder de Articles of Confederation waarbij de Verenigde Staten als een losse confederatie werden bestuurd. Deze staatsvorm bleek al vrij snel onwerkbaar en er gingen stemmen op om een sterker centraal bestuur in te richten. In virginia was het met name James Madison die dit initiatief steunde. In 1787 werd er een conventie gehouden in Philadelphia alwaar een concept grondwet werd opgesteld. Henry werd aanvankelijk gekozen als delegatielid voor Virginia maar hij weigerde zitting te nemen. Als officiële reden gaf hij financiële problemen op hoewel hij tevens sterk tegenstander was van een sterker centraal gezag. Henry vreesde dat de grondwet het centrale bestuur te veel machten zou verschaffen en dat het ambt van president gevaarlijk dicht bij dat van tiran of monarch zou kunnen komen te liggen. De staten, zo stelde hij, zouden te veel van hun autonomie en hun rechten moeten afstaan aan de federale regering.

Nadat in september 1787 de nieuwe grondwet werd aangenomen door de Constitutional Convention was Henry een van de grootste tegenstanders van het nieuwe document tijdens de conventie van Virginia waar over ratificatie van de grondwet werd gedebatteerd. Madison beschouwde Henry, als leider van de anti-federalisten, als de belangrijkste obstakel tegen ratificatie in Virginia. Uiteindelijk stemde de conventie van Virginia met een krappe meerderheid (89 voor en 79 tegen) in met de grondwet waarmee Virginia de tiende staat werd die de grondwet ratificeerde. Mede naar aanleiding van de bezorgdheid van veel anti-federalisten zoals Henry werd later de Bill of Rights aan de grondwet toegevoegd waarmee enkele basis rechten werden vastgelegd en die de invloed van de federale regering op de individuele staten enigszins beperkte. Nadat deze Bill of Rights aan de grondwet was toegevoegd legde Henry zich neer bij de nieuw gevormde federale staatsinrichting.

Politieke ommekeer en dood
In 1790 verliet Henry wederom de politiek en werd hij weer werkzaam als advocaat. Hij weigerde in 1795 de nominatie van president George Washington om Secretary of State te worden en sloeg ook andere hoge posities af zoals die van rechter aan het Hooggerechtshof en ambassadeur. Hij deed dit mede door zijn tegenstand tegen de federale regering maar ook vanwege zijn verslechterende gezondheid. Mede door de excessen van de Franse Revolutie echter maakte hij in de jaren 1790 een ommekeer in zijn politieke denken en werd hij een grotere voorstander van de federalisten. Hij vreesde dat er in de Verenigde staten, zoals in Frankrijk was gebeurd, anarchie kon ontstaan. Hij steunde het beleid van president John Adams maar hij sloeg om gezondheidsredenen een ambassadeurspost af. Op aandringen van zijn oude vriend George Washington stelde hij zich in 1799 wel kandidaat voor een zetel in de Virginia House of Delegates. Hij won de verkiezingen, maar overleed op 6 juni 1799 voordat hij zijn zetel kon innemen.

Externe links
 Red Hill: Patrick Henry National Memorial
 Text van Patrick Henry's Give me Liberty, or Give me Death! speech

Amerikaans gouverneur
Amerikaans persoon in de Amerikaanse Onafhankelijkheidsoorlog

redpajama_set_name: RedPajamaWikipedia


Sometimes it's hard to take a step back. This is why I warn my freshman advisees against getting on "the treadmill." "The treadmill" is the straightest path through MIT. It means doing the basic classes that everyone takes, not doing anything but your classes, doing all the sexiest internships (and not the ones which are interesting or different or that you'd like to do and learn from), and then going straight into the highest paying job you can find because it's there.
Mary Chin earned her BS in civil engineering and a MEng in environmental engineering from the Massachusetts Institute of Technology. She pursued a career on the Wall Street trading floor after completing several demanding internships. Although she enjoyed the fast-pace environment, Ms. Chin did not feel that she was contributing to society in ways that she had imagined. "It took about three minutes of standing in front of an 8th grade algebra class to confirm that I'd made the right decision in leaving Wall Street and becoming a teacher," said Ms. Chin.
Well, Mary just won a $175,000 five-year fellowship distributed by the Knowles Science Teaching Fellowship foundation, which supports professionals who transition into STEM education. But more importantly than that, Mary got off the treadmill. And the world is a better place for it.


'torre' — the building which completes fondazione prada — has opened to the public during milan design week 2018. designed by rem koolhaas with chris van duijn and federico pompignoli of OMA, the 60 meter-tall tower is the final part of the campus, which originally opened in 2015. the project completely transformed the site, converting what was once a gin distillery on the southern edge of the city into a bold and diverse complex of challenging exhibition venues.
half of the tower's storeys develop on a trapezoidal basis, while the others follow a rectangular plan. the external façades are characterized by a succession of glass and concrete surfaces, which give the different floors an exposure to light on the north, east, or west side. meanwhile, the uppermost exhibition hall is filled with generous amounts of natural light. the building's roof terrace is designed as a flexible space that houses a bar.
inside is an exhibition titled 'atlas', which emerged from a dialogue between miuccia prada and italian art historian germano celant. it hosts work from the prada collection displayed in a sequence of different environments, from artists such as jeff koons, damien hirst, john baldessari, and carsten höller. the group of exhibited artworks, realized between 1960 and 2016, represents a possible mapping of the ideas and visions which have guided the creation of the collection and the collaborations with the artists that have contributed to the activities of the foundation throughout the years.
the 'torre' restaurant, housed on the sixth floor, houses original furnishings from the 'four seasons restaurant' in new york designed by philip johnson in 1958, elements of the installation by carsten höller the double club (2008-2009), three sculptures by lucio fontana — two polychrome ceramics cappa per caminetto (1949) and pilastro (1947) and a glass and cement paste mosaic head of a jellyfish (1948-54) — and a selection of paintings by william n. copley, jeff koons, goshka macuga and john wesley.


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text:
Israel Through a Traveller's Eyes
My first taste of the country began in Tel Aviv; a youthful city placed precariously along the eastern coast of the Mediterranean Sea. Tastes, sounds and culture greeted us as we wandered through the city's Nachlat Binyamin Art Markets.
Brooke Hunter
Australian expat and freelancer based in London
09/01/2015 08:04am GMT | Updated March 10, 2015
"Please be careful, love," my Nana said over the telephone from Australia as I announced I was flying from London to Israel in a matter of days. Given the negative media hype surrounding the Middle Eastern country, her worry was slightly warranted. I was worried too, until I was on the tarmac at Ben Gurion Airport in Tel Aviv and my fellow passengers applauded the safe landing.
Indeed, I discovered that the 'Holy Land' makes for inspiring travel with a plethora of religious groups sharing the land in relative peace and abundance of cultural layers just waiting to burst out from underneath. My first taste of the country began in Tel Aviv; a youthful city placed precariously along the eastern coast of the Mediterranean Sea. Tastes, sounds and culture greeted us as we wandered through the city's Nachlat Binyamin Art Markets - a strip of artist stalls just waiting to be discovered. Strong smells of spices and fruits led us into the nearby bustling Carmel Markets for a pomegranate juice and a Middle Eastern boureka. A sea of people swarmed in and out of the entrance, with stalls selling everything from Judacia jewellery and ornaments to delicacies and fabrics. Later we took in the long stretch of the Mediterranean coast dotted with sun chairs sunken into the sand. As the warm crimson sun set slowly in front of thatched cabanas nestled in the dunes of the sand, we witnessed a man holding a yoga pose while a couple of surfers gathered in a group.
The following morning saw us travelling into the heart of Israel's Negev - or desert - en-route to the Dead Sea. The drive from Tel Aviv through Israel's southern third took approximately three hours and was filled with the utmost beauty. Long stretches of dry land contrasted with spots of thick forests used for Israeli army training. A mix of Arab and Jewish towns could be seen along the way, their distinctive mosques and synagogues differing in colour and architecture. Arab bedouins wandering grazing pastures could also be spotted as we passed shanty towns of corrugated tin shacks and sheets used as roofs.
At 400 metres below sea level - the lowest point on Earth - the Dead Sea is surrounded by the mountains of Moab in the east and the Judean mountains to the west. The high salt content of the 'sea' renders sea life almost impossible, but its beauty is striking nonetheless. The water stretched out before us, its rich emerald colour contrasting with the white of the salt crystals and the browns of the rocks at its edges. The drive back to Tel Aviv proved a little dangerous as the GPS lead us beyond Israel's infamous security barrier and on the edge of Ramallah, a large Palestinian city in the West Bank. We passed young women and men holding large guns, proving the tumultuous reality of Israel and bringing me back from my dreamy Dead Sea experience.
Come morning, we planned to explore and shop the well-known flea markets of Jaffa, located on the southern tip of Tel Aviv. One of the oldest ports in the world, the ancient 3000-year-old fishing harbour is characterised by honey-coloured stone houses and narrow, winding alleyways filled with hidden Turkish baths centuries old. As I observed boys fishing off the end of the harbour's jetty, I noticed similar brightly-coloured dinghies rocking in the light breeze tied to wooden posts as a band sent whimsical music floating through the area.
Not far from the port and next to the ancient Clock Tower, the Jaffa flea market or 'shuk' was packed with locals and tourists buying bargained food and trinkets in anticipation for Shabbat later on that night. The markets proved a treasure trove of Arabic carpets, lanterns and ceramics mixed with vintage Israeli ornaments.
We walked back along Tel Aviv-Jaffa promenade to Neve Tzedek where I noticed Arabs and Jews alike picnicking and children playing on the grass as the sun set over the Mediterranean Sea. We made the bike ride home for the night to prepare for the 1.5 hour bus ride from Tel Aviv to Jerusalem the next day.
Jerusalem; where people of all walks of life and all religious backgrounds converge. Our day began in the new city at the bustling Mahane Yehuda Market as we dove into one of the entrances, swimming through the crowd to get to a bakery filled with Middle Eastern delicacies. The smell of cinnamon and paprika filled the air, mixing with the sweetness of pomegranates and strawberries. Taking a peek down one of the alleyways, I observed a sea of heads of all differing ages mingling through the various stalls selling bunches of green and aromatic herbs and fresh fruit. There were religious and secular Jews, tourists, Christians and Muslims alike all vying for space in the emporium of market wonder.
Later we entered the Old City through Jaffa Gate, a stone portal and one of eight gates providing entrance into the historic walls of Old Jerusalem built by the Ottoman sultan in 1538. It is hard to imagine the thousands of feet that have walked the labyrinthine alleyways. We had an Israeli friend take us around the Old City enlightening us with her knowledge. We walked via the Dolorosa which lead us to the Church of the Holy Sepulchre where Christians believe Jesus was crucified and buried. We then walked through the Arab quarter and into the Jewish quarter to witness Jews pray at the Western Wall, the last structure remaining from the Jewish Temple destroyed by the Romans. A girl stood at the base of the Western Wall lookout, playing a harp, as the Dome of the Rock towered above with majestic presence on the Temple Mount.
Away from the historical and religious centre of Israel and my last day in Tel Aviv, I thought of how similar the country was to just about any other exotic and culturally immersed destination. Portrayed as a simple dot on the world map enclosed by constant controversy, Israel is hiding something much brighter. Visit the country and you will be rewarded immensely with a general sense of warmth and joie de vivre extending from the people to the history, the culture and the food.
IsraeltravelTravel BlogsTel Avivjerusalem


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We had some fun this week playing with sidewalk chalk.
Sidewalk Chalk Paint is the perfect boredom buster for those lazy summer days!
Mix the cornstarch, water and food colouring to create a variety of shades of paint.
We used this handy vegetable tray as our paint palette.
Once mixed be sure to stir the paint often as the cornstarch tends to settle to the bottom.
You can also add more water to thin the paint out and have it last a bit longer.
We took our paint outside and the boys had a great time painting the sidewalk, creating roads for the ants and drawing their names.
Have you made sidewalk chalk before? How did it go?


It's taken me 17 years to finally write an article about something so simple yet so many teenagers and adults struggle with: the concept of self love. College has this unhelpful little downside that can make even the strongest carefree people worry about even the tiniest of flaws that most of the time aren't even noticed. I remember this exact cycle happening to me when I first entered Macleans—a girl who always used to wear hand-me-downs and not have a care in the world about what others had to say suddenly became this anxious, self-conscious person who always thought she was too underweight and loud. Whether it's scrutinizing physical features such as your weight, height, the way you smile, or nitpicking your freckles and acne, we are our own worst enemy and bully that no one seems to talk about.
We live in a world that feeds and convinces us that we are never good enough. A world that profits from someone's hate of a certain flaw through magazines, billboards, and advertisements for products that will 'help you reach that level beauty and physical appearance you've always wanted'. As a society, we have been conditioned to the idea of what the 'perfect' body is and that whatever doesn't fit that type is not considered beautiful. It's time to change that now, because something is wrong considering the fact that if someone says "love" the immediate image of you with a significant other is created, but the love you have with yourself is undoubtedly forgotten about. The amount of opportunities that I have missed throughout the past five years due to the restrictions and judgement I have inflicted upon myself is endless.
But the thing is, we ourselves are the only ones who truly see how we have grown and developed. You are the person who notices that your hair has slightly grown, the way you've gained more freckles on your arms or the cut just below your knee. You are the one who experiences every moment of the day with yourself, so why not love yourself for it? The most common problem with self image nowadays is the dependence on others to reassure you that you are good enough, smart enough, or pretty enough, and this needs to stop. We need to begin to see ourselves as an ongoing art piece, one that is always being painted and worked on, with the artist being none other than you.
This article is a reminder to you that you are real, raw, and always changing. You need to show love and respect for yourself because you are unique and wonderful. Block out what the media or beauty magazines try to persuade you, and don't spend your time thinking about how to change yourself to be like Kendall Jenner or Zac Efron. Follow social media accounts and platforms that benefit and encourage you to be a better you and not make you want to change everything about yourself and the way you are. How can we expect love from another when we don't love ourselves? Author Rupi Kaur once said: "We are all born so beautiful, the greatest tragedy is being convinced we are not". It's the little things we love about other people, and I'm thankful to have learned myself because after 18 years of being alive on this little planet we call Earth, I'm finally seeing myself as an art piece and I hope you all do too.


rm1x but it didn't make any difference to the edp sync problem.
settings on the Echoplex and the configuration of the RM1x as well.
we don't get all the details!
Prev by Date: Re: Record while loop is playing?


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redpajama_set_name: RedPajamaGithub


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Feb 23, 2022 - Energy & Environment
How the Russia-Ukraine crisis will affect U.S. energy prices
Andrew Freedman, author of Axios Generate
The Russian government's moves to redraw the map of Ukraine, while threatening to conduct a wider and more devastating invasion, is already impacting turbulent energy markets.
Why it matters: The clearest way Americans will feel the price of the conflict may be in the form of energy costs, especially the price of gas at the pump.
The big picture: Russia is one of the world's top oil and gas suppliers, and Europe relies on the country for about 40% of its natural gas supplies.
As expected, natural gas prices in Europe climbed Tuesday as a result of the ominous developments.
In particular, Germany's decision to halt the certification process for the Nord Stream 2 pipeline, which would carry Russian gas directly to Germany, is a potential paradigm shift in Europe's energy politics.
Depending on their severity and targets, European Union and U.S. sanctions could prompt Russia to curtail oil and gas exports to the West, forcing prices to rise and punishing NATO economies.
U.S. officials warn this will only hasten Europe's energy diversification.
Threat level: President Biden has been trying to prepare Americans for the possibility of added energy costs as a result of allied country Russian sanctions. "Defending freedom will have costs for us as well, here at home. We need to be honest about that," Biden said yesterday.
The administration has been working to secure alternate sources of natural gas for Europe should Russia shut off exports, as well as pursue measures to keep U.S. gas prices in check.
But that will be tough with tight global supplies.
Biden pledged to take steps to blunt price increases, saying, "I want to limit the pain the American people are feeling at the gas pump," he said. "This is critical to me."
Of note: One option the White House may choose would be tapping the Strategic Petroleum Reserve again, but this has limited effectiveness.
Yes, but: The U.S. has not revealed specific commitments, other than general language about working with other energy suppliers, including large LNG exporters such as Qatar.
Between the lines: Russia appears poised to conduct a major invasion. This would trigger additional and far harsher sanctions.
These sanctions could have unintended consequences for the energy sector, which the White House aims to avoid.
ClearView Energy Partners cautioned yesterday that Russia's "connectedness to global markets" as well as oligarchs' ownership in energy companies may make repercussions difficult to completely avoid.
Go deeper: Russia-Ukraine crisis opens new era of petro politics


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Africa Americas Asia Australia China Europe India Middle East United Kingdom
First woman 'Black Rod' in 650 years takes up post in UK Parliament
By Zahid Mahmood, CNN
Updated 6:27 AM EST, Mon February 12, 2018
Who is Black Rod?
For the first time in its 650-year history, a woman on Monday takes up the position of "Black Rod," the senior executive role in Britain's House of Lords.
Sarah Clarke, champions director of the All England Lawn Tennis Club, will take responsibility for the most recognized aspect of the position – banging on the door of the House of Commons with a ceremonial staff during the annual state opening of Parliament.
But Clarke also takes charge of the day-to-day running of Britain's upper legislative house, managing a 30-strong team.
"The House of Lords is a place where the smallest detail is as important as the big picture and the depth of heritage and tradition is second to none. I am truly looking forward to starting work," Clarke said in a statement.
Yeomen of the Guard pick up oil lanterns as they prepare to conduct a ceremonial search in the Palace of Westminster.
Quirky traditions of opening parliament
"I am very pleased to welcome Sarah Clarke to the role of Black Rod. As the first woman to take on the role, this is a historic moment for the House," said Lord Fowler, speaker of the House of Lords.
"The Lords has a great record of women taking on senior political roles. Five of the last seven Leaders of the Lords and the current Leader of the Opposition have been women as well as both my predecessors as Lord Speaker. I am sure Sarah will continue that tradition and do an exemplary job as Black Rod," Fowler said.
The role can be traced back to 1348 and the time of King Edward III. The King established a council of advisers known as the Knights of the Garter, whose ceremonial processions needed to be organized. An "usher" was established to take on the role, and was awarded a ceremonial staff, or rod, in order that his status would be recognized.
One of the enduring roles of Black Rod is to summon members of the House of Commons to attend the monarch's speech in the House of Lords at the state opening. To symbolize the primacy of the Commons, the door is slammed in Black Rod's face, and the holder of the office is required to bang three times before the door is opened.
As the first woman to hold the office, Clarke will be known formally as the Lady Usher of the Black Rod.


It is Sabbath morning. At the church door children eagerly hold out their hands to mom and dad for offering money. Parents hand the money, confident that they have started their children down the road to responsible stewardship.
What\s wrong with this picture? Is stewardship carrying something a short distance? Does handing children offering at the door help them become stewards? When will children begin to reach into their own pocket for tithes and offerings instead of holding out a hand for a contribution?
Stewardship education must begin early. It is our responsibility to help our children understand their responsibilities as God\s stewards. Children need to learn early that stewardship is not limited to money. We need to instill in them the truth that living in love with Jesus is what stewardship is all about. Our children need to see us practice stewardship as an integral part of worship. God gives each of us, including little children, the responsibility for our bodies, our time, our house, our surroundings, the people and animals dependent on us, our communities . . . the list goes on. When true stewardship flourishes in our hearts, it penetrates every aspect of life and what God expects of us.
Provide opportunities for children to earn money and to set aside their tithe and offerings.
Give them responsibilities with backup encouragement to ensure success.
Talk together about being good stewards in taking care of the earth.
Help them make a stewardship chart where they can mark off responsibilities as they are fulfilled.


I couldn't figure out if there is a method to check how our services are healthy.
For example, I need a tool to send a notification for me if one of my services are stopped suddenly or any failure happened to my services.
I need any method to make a periodic check on my services.
Additionally, there is System Monitor offered through professional services and be sure to check the UC plenary tomorrow for news on this topic.
thanks for your input. i will follow up on that.
Thanks for your answer. I always check my argis server logs to ensure that the system is fine.
But what I exactly looking for here that if my system get failure or one of my services have a problem I need an a way to get me informed about that.
I haven't done this specifically for my ArcGIS Server instances, but when I want to monitor services I have running, I like to use Windows Task Scheduler. I usually create a small console app or script that will make a test query to a service, and if there is not a response or the response is not as unexpected, it will send out an alert email. So for example I have an application running on my web server that depends on a few external APIs and database connections to run. I have a scheduled task running every 5 minutes (on a different machine than the server) and it will make sure each of the APIs is responding and the database connections are OK. If everything is OK, the task will end without notification. If anything reported an error, I send an alert email out to the dev team so we are aware of the poor health status of the application right away and can take immediate action.
Thanks for your input. May you please share this script with me to examine it.
System Monitor is not part of ArcGIS, per se. As Xander points out, you get access to it through Esri Professional Services since they are the ones that develop it. For System Monitor, you pay a consulting fee to have them give you the software and help get it setup and working. If you are willing to pay for a tool, I suggest you do an internet search on tools for monitoring ArcGIS Server and GIS services. Although there are not a lot of tools out there, there are at least a couple nice packages I have seen.
If you search GeoNet, you will find multiple cases where users ask/suggest that Esri package System Monitor with ArcGIS Server. Given the cost of ArcGIS Server products, I think providing a robust monitoring tool with it isn't too much to ask, but Esri obviously thinks differently.
I will share link with more info after the announcement at the plenary.
There is an ArcGIS Monitor demo site floating around out there. I am not sure I should be sharing it, but Google doesn't mind sharing.
When I logged into the ArcGIS Monitor demo site, the version number is 3.0.250, which makes me think this is simply a rebranding of System Monitor than a new product. The latest version of System Monitor is 3.x.
The ArcGIS Monitor splash page on esri.com doesn't say "Professional Services," but I am guessing that is who reaches out to you after you fill out the contact information.
System Monitor used to be available openly until august of 2016.
ESRI removed the available installation package due to too many users making a mess of their GIS Enterprise environments and having to field support calls. To summarize, too many people didn't know what they were doing and the support calls mounted. So now, to get this monitoring software, ESRI requires that you pay for them to implement. We run an older version when it was available and not able to upgrade.
At Esri, we want you to get the most out of your investment in GIS and IT infrastructure. Soon we will offer ArcGIS Monitor, a tool uniquely tailored to audit the health of your ArcGIS implementations. ArcGIS Monitor will show you insightful information about your system usage and performance, while ensuring that Esri can support you throughout the lifecycle of your GIS. Sign up to get the latest news on how Esri can help you improve your system operation and reduce administration costs.
with no errors listed. Maybe it didn't like that I selected "expert" as my "level of Experience using GIS" Which I thought was a strange question anyway.
Maybe it is still only available internally. The other choices were "Novice user in GIS" and "Some Background in GIS". strange question....strange choices. Looking forward to seeing it. I'm heading down to the UC on Weds so maybe there will be a demo available by then.
Thanks for sharing the information about professional services.
You can write a python script to loop through all services and query them. By querying, you're making sure that both the service and data are accessible. If the query fails or doesn't return any features, then you can be alerted that there's a problem with the service. You should also query the logs to determine if any services are reporting errors.
Here is an example script that I have used in the past to simplify the information in the log files. It will only register 1 record for an error that occurred several times during the same day and write out the start and end date time and the number of times the error occurred. It is far from being perfect, but might be a start.
Does this path exist on your server (and does your script have access to it)?
Yes this path exist in my machine and the script have access to it. So what do you think?
Does the path that is created in the script match to the path where the log files are stored?
I tried it with using the same path but with the same result, and I made sure that the script have an access to that folder (I shared that folder and give the user full control on it).
If not, please adjust the settings in the script.
I edit the link and it's working fine with me on lab 11 server, but I tried it on another service and when the script is running the following error appear on one of the services and the script stopped. What might be the problem with this service?
You could as a test, copy the log files to a shorter path and run the script on that folder to get the results.
Thank you xnader, it's working fine now.
I think this will be useful if we can run it automatically and link it with email to send an email when an error appeared in my server. Anyway thank you very much for your help.
Thanks for sharing this python Xander.
I'm wondering if there is a way to create a toolbox for this code so that one can provide the inputs more decently (dates, log folder, server name...)?
I guess the script could be turned into a GP tool. What would you like to turn into a parameter? What things should the end user be able to specify before running the tool?
fURL = URL + "?f=json"
I will try it to see if this works with me or not.
When I tried this python on another server I got the following error, what might be the issue here?
The error message indicates the some security setting is preventing the script to access the folder with the log files. Work with your IT people to obtain the proper read access on the log files.
Thank you xander, I will check this and update you.
We hope that ESRI provide us such a tool (not out from the box) to help the users in tracking their system.
I have an script which will fulfill the necessary task for you.
May you please share the script to test it on my environment?
Can you please share your script with us?
This won't necessarily test the health of the services, only if they're up or not. Data issues could cause the service to return a 200 when checking to see if the service itself is accessible, but making any type of request for data, (query or exportMap), will fail. I'd suggest you just run a simple query to see if it returns data and also use built-in modules, (even though requests is far easier to work with), (where 1=1 and returnCountOnly = True). If you do want to query all services, keep in mind that it will submit a bit of load on the Server and, if the data is coming from a geodatabase, the geodatabase as well.


Riddle me this, riddle me that. Why go the easy way when you can complicate? That is the idea behind this mathematical problems clock. Isn't it more fun to have these conversations? "What time is it?" Oh, it's 66 times square root of 198. "What time should we go out?" Let's meet at 3*(PI – 0.14). If you know any math teacher or math lover then this is the best gift. This clock is also a good way to test if you are a geek.