6. Probability and Distributions
- Probability, loosely speaking, concerns the study of uncertainty
- Probability can be thought of
- as the fraction of times an event occurs,
- as a degree of belief about an event.
- Probability can be thought of
- We then would like to use this probability to measure the chance of something occurring in an experiment
- In ML, we often quantify
- uncertainty in the data,
- uncertainty in the machine learning model, and
- uncertainty in the predictions produced by the model.
- In ML, we often quantify
- Random Variable : Quantifying uncertainty requires the idea of a random variable, which is a function that maps outcomes of random experiments to a set of properties that we are interested in.
- Probability Distribution : Associated with the random variable is a function that measures the probability that a particular outcome (or set of outcomes) will occur
6.1 Construction of a Probability Space
- The theory of probability aims at defining a mathematical structure to describe random outcomes of experiments.
- ex) Coin toss => cannot determine the outcome => by doing a large number of coin tosses => we can observe a regularity in the average outcome.
- Using this mathematical structure of probability, the goal is to perform automated reasoning.
6.1.1 Philosophical Issues
- When constructing automated reasoning systems,
- Boolean logic : does not allow us to express certain forms of plausible reasoning.
- Probability theory : can be considered as a generalization of classic Boolean logic
- Two major interpretations of probability
- Bayesian interpretation : uses probability to specify the degree of uncertainty that the user has about an event, degree of belief
- ex) In Brain MR, a 2cm circle has a 50% chance of being cancer.
- Frequentist interpretation : considers the relative frequencies of events of interest to the total number of events that occurred
- ex) If you toss a coin 100 times, the probability of getting heads is 50%
- Bayesian interpretation : uses probability to specify the degree of uncertainty that the user has about an event, degree of belief
6.1.2 Probability and Random Variables
-
Three distinct ideas that are often confused when discussing probabilities
- Probability space : allows us to quantify the idea of a probability
- Random Variables : transfers the probability to a more convenient (often numerical) space
- Distribution (or law) with a random variable (6.2)
-
Three concepts introduced by Kolmogorov :
- The sample space, Ω : the set of all possible outcomes of the experiment
- For example, two successive coin tosses have a sample space of {HH, TT, HT, TH}
- The event space, A : the space of potential results of the experiment, obtained by considering the collection of subsets of Ω
- The probability, P : We associate(map) a number $P(A)$ that measures the probability or degree of belief that the event will occur.
- The sample space, Ω : the set of all possible outcomes of the experiment
-
Random Variable : a function takes an element of Ω and returns a particular quantity of interest $x$, a value in $T$ (target space), This mapping from Ω to $T$ is called a random variable.
- ex) Tossing two coins and counting the number of heads, a RV $X$ maps to the three possible outcomes $X(hh) = 2, X(ht)=X(th)=1, X(tt)=0$, In this case target space $T = {0,1,2 }$
The name “random variable” is a great source of misunderstanding as it is neither random nor is it a variable. It is a function
6.1.3 Statistics
- Probability theory and Statistics : are often presented together, but they concern different aspects of uncertainty.
- In Probability : we use the rules of probability to derive what happens.
- In Statistics : we observe that something has happened and try to figure out the underlying process that explains the observations
- Machine Learning : close to statistics in its goals to construct a model that represents the process that generated the data
6.2 Discrete and Continuous Probabilities
- Discrete Target space T :
- Random Variable X : takes a particular value x ∈ T,
- Probability Mass Function : the probability that a random variable X takes a particular value x ∈ T , denoted as P (X = x)
- Continuous Target space T :
- Random Variable X : is in an interval, denoted by P(a<X<b)
- Cumulative distribution function : the probability that a random variable X is less than a particular value x, denoted by P (X < x).
- Number of variable
- univariate distribution : distributions of a single random variable
- multivariate distributions : more than one random variable
6.2.1 Discrete Probabilities
- Probability Mass Function : A function that gives the probability that a discrete random variable is exactly equal to some value.
- Random Variable $X$ maps elements in event space to target space.
- ex) Available events {TT, TH, HT, HH} => number of Heads {0,1,2}
- Probability Mass Function $P$ maps elements in target space to probability
- ex) $P(X=0)= \frac{1}{4}, P(X=1)= \frac{2}{4}, P(X=2)= \frac{1}{4} $
- Random Variable $X$ maps elements in event space to target space.
- Joint Probability $p(x,y)$ : is the probability of the intersection of both events, that is $P(X =x_i ∩ Y =y_j) = P(X=x_i, Y=y_j)$
- Marginal Probability $p(x)$ : takes the value $x$ irrespective of the value of random variable $Y$ that is $P(X=x_i)$
- $X∼p(x)$ : denote that the random variable X is distributed according to $p(x)$
- Conditional Probability $p(y|x)$: If we consider only the instances where (X = x), then the fraction of instances for which $Y = y$
6.2.2 Continuous Probabilities
- Probability Density Function: A function $f : R^D → R$ is called a probability density function if :
- $∀x∈R^D :f(x)>0$
- Its integral exists and $ \int_{R^D} f(x)dx = 1 $.
- Probability : $P(a<X<b)=\int_a^b f(x)dx,$
- The probability of a continuous random variable X taking a particular value P (X = x) is zero.
- Cumulative Distribution Function
- CDF of a multivariate real-valued random variable X with states $x ∈ R_D$ is given by $F_X(x) = P(X_1<x_1,…,X_D<x_D)$
- Probability vs Likelihood
6.3 Sum Rule, Product Rule, and Bayes’ Theorem
6.3.1 Sum Rule : the relationship between joint prob and marginal prob.
-
(1) Let’s begin with the joint distribution, $p(x,y) = p(X=x_i, Y=y_j) = \frac{n_{ij}}{N}$ of two random variables $x,y$ (figure 6.2)
-
(2) Corresponding marginal distribution $p(x)$ is same with the summation $\frac{c_i}{N} = p(x_i,y_1 ) + p(x_i,y_2) + p(x_i,y_3)$
- $ p(x) = p(X=x_i) = \Sigma_j{p(X=x_i, Y=y_j)} , \ \text{(y is discrete)} $
- $ p(x) = \int_y p(x,y)dy, \ \text{(y is continuous)} $
6.3.2 Product Rule : the relationship between joint prob and cond prob.
- (1) Let’s see the figure6.2 again, conditional distribtion is $p(Y=y_j|X=x_i) = \frac{n_{ij}}{c_i}$
- (2) relates the joint distribution to (1) $p(X=x_i, Y=y_j) = \frac{n_{ij}}{N}$ which is equal to $\frac{n_{ij}}{c_i} \times \frac{c_i}{N}$
$$ p(x, y) = p(y | x)p(x)= p(x | y)p(y) $$
6.3.3 Bayes’ theorem
-
Introduction :
-
In ML and Bayesian statistics, we are often interested in making inferences of unobserved (latent) random variables
-
Bayes’ theorem (6.23) allows us to invert the relationship between x and y given by the likelihood
-
-
Bayes’ theorem : if we have some prior knowledge $p(x)$ and some relationship $p(y|x)$, and observe $y$, we can use Bayes’ theorem to draw some conclusions about $x$.
$$ p(x|y) = \frac{p(y|x)p(x)}{p(y)} $$
-
Posterior, $p(x|y)$ is the quantity of interest in Bayesian statistics
-
Likelihood, $p(y|x)$ : describes how x and y are related, and in the case of discrete probability distributions, it is the probability of the data y
-
Prior, $p(x)$ : encapsulates our subjective prior knowledge of the unobserved (latent) variable x before observing any data.
-
Evidence (marginal likelihood), $p(y)$ : is independent of x, and it ensures that the posterior $p(x|y)$ is normalized.
-
There’s a drug test that is 95% accurate. and assume that 1% of population uses the drug.
Q. If a randomly selected person tests positive for the drug test, what’s the probabiliy that the person is actually a drug user
A. $p(x|y) = \frac{p(y|x)p(x)}{p(y)} = \frac{0.95 \times 0.01}{0.95 \times 0.01 + (1-0.95)*(1-0.01) } \simeq 0.16$
- Let $X$ be the event of an actual drug user and $Y$ the event of a positive result from drug test.
6.4 Summary Statistics and Independence
- We will describe two well known summary statistics : mean and variance
- We will discuss two ways to compare two random variables : independece and inner product
6.4.1 Mean and Covariance (population mean and cov)
-
Expected Value : the expected value of a function $g$ is given by,
- $ E_x[g(x)] = \int_x{g(x)p(x)dx}$ , (For a univariate continuous random variable)
- $E_x[g(x)] = \Sigma_x g(x)p(x)$, (For a discrete random variable)
-
Mean : is an average and is defined as,
-
$E_{x_d} = \int_x x_dp(x_d) dx_d$ ($X$ is a continous random variable)
-
$E_{x_d} = \Sigma_{x_i} x_ip(x_d=x_i)$ ($X$ is a discrete random variable)
-
Details
-
Mean depends on given sample : e.g.) dice roll five times => {1,2,5,2,3} => mean is 2.6 but expectation is 3.5
-
Average : There are many kinds of mean, such as arithmetic, harmonic. Average is same with arithmetic mean.
-
median : is the middel value if we sort the values
-
mode : the most frequently occuring value
-
-
-
Covariance (Univariate): is given by the expected product of their deviations from their respectvive means.
-
Covariance (Multivariate) : The notation of covariance can be generalized to multivariate random variables
-
Covariance Matrix : a square matrix giving the covariance between each pair of elements of a given random vector.
-
References. https://blog.naver.com/sw4r/221025662499
$$ Cov[x,y] = \mathbb{E}[ (x-\mathbb{E}_X(x) )] [(x-\mathbb{E}_Y(y))] = \mathbb{E[(x-\mu_x)(y-\mu_y)]} $$
-
-
Variance : The covariance of a variable with itself $Cov[x,x]$ is called variance and is denoted by $\mathbb{V}_X (x)$
$$ \mathbb{V}_X (x) = Cov_X[x,x] $$
-
Correlation : The normalized version of covariance, the correlation matrix is the cov matrix of standardized random variables, $x/\sigma{(x)}$
$$ corr[x,y] = \frac{Cov[x,y]}{\sqrt{\mathbb{V}(x)\mathbb{V}[y]}} \in [-1,1] $$
6.4.2 Empirical Means and Covariances
-
To compute the statistics for a particular dataset, we would use the observations $x_1, … ,x_N$ and use following
-
Empirical Mean : Empirical mean vector is the arithmetic average of the observations for each variable
- $\hat{x} := \frac{1}{N} \sum_n x_n $
-
Covariance : a DxD matrix
- $\Sigma := \frac{1}{N} \sum_n (x_n -\hat{x})( x_n - \hat{x})^⊤$
-
6.4.3 Three Expressions for the Variance
-
The standard definition of variance (corresponding to the definition) : the expectation of the squared deviation of a randeom variable X from its expected value $\mu$
$$ \mathbb{V}_X(x) := \mathbb{E}_X[(x-\mu)^2] $$
-
Raw score formula : When estimating variance in 6.43, we need to calculate the mean $\mu$ first and we also need to calculate $\hat{\mu}$. We can avoid this two passes by rearranging the terms : so called raw-score formula
$$ \mathbb{V}_X(x) = \mathbb{E}_X[x^2] - \mathbb{E}_X(x)^2 $$
-
Sum of pairwise differences
$$ \frac{1}{N} \sum_{i,j}^N (x_i - x_j)^2 $$
6.4.4 Sums and Transformations of Random Variables
-
Manipulations of Random Variables
-
$\mathbb{E}[x \pm y] = \mathbb{E}(x) \pm \mathbb{E}[y]$
-
$\mathbb{V}[x \pm y] = \mathbb{V}(x) + \mathbb{V}[y] \pm Cov[x,y] \pm Cov[y,x]$
-
-
ex) Consider a random variable $X$ with mean $\mu$ , covmat $\Sigma$, and a affine transformation $y = Ax + b$
-
$\mathbb{E}[y] =\mathbb{E}[Ax+b] = A\mathbb{E}(x) + b = A\mu + b$
-
$\mathbb{V}[y] = \mathbb{V}_X[Ax+b] = \mathbb{V}_X[Ax] =A \mathbb{V}(x)A^⊤ = A\Sigma A^⊤$
-
$Cov[x,y] = \mathbb{E}[x(Ax+b)^⊤] - \mathbb{E}(x)\mathbb{E}[Ax+b]^⊤ = \Sigma A^⊤$
- where $\Sigma = \mathbb{E}[xx^⊤] = \mu \mu^⊤$ is the covariance of $X$
-
6.4.5 Statistical Independence
-
Independence : Two random variables X, Y are statistically independent if and only if $p(x, y) = p(x)p(y) .$
-
$p(y | x) = p(y) $
-
$p(x | y) = p(x) $
-
$ \mathbb{V}_{X,Y} [x + y] = \mathbb{V}_X (x) + \mathbb{V}_Y [y]$
-
$Cov_{X,Y} [x, y] = 0$
- Two RV can have covariance zero but not statistically independent
-
-
Conditional Independence : Two RV X and Y are conditionally independent given $Z$ if and only if:
- $p(x,y|z)=p(x|z)p(y|z) \ \text{for all } z∈Z$
6.4.6 Inner Products of Random Variables
-
Inner product between random variables : $<X,Y> := Cov[x,y]$
-
The length of random variables : standard deviation
- $∥X∥ = \sqrt{Cov[x, x]} = \sqrt{V(x)} = σ(x)$
- The longer the random variable, the more uncertain it is
-
The angle $\theta$ between two random variables : correlation
- $ cos θ = \frac{{X,Y}}{∥X∥∥Y∥} = \frac{Cov[x,y]}{\sqrt{V(x)V[y]}} = corr[x,y]$
-
6.5 Gaussian Distribution
- Gaussian Distribution has many computationally convenient properties, which we will be discussing in the following chapters
- ch9. use Gaussian Distribution to define the likelihood and prior for linear regression
- ch11. mixture of Gaussians for density estimation
- Univariate Gaussian Distribution
- $p(x|\mu, \sigma^2) = \frac{1}{\sqrt{2 \pi \sigma^2}}exp(-\frac{(x-\mu)^2)}{2 \sigma^2})$
- Multivariate Gaussian Distribution : is fully characterized by a mean vector $\mu$ and a cov matrix $\Sigma$
- Standard normal distribution : the special case of the Gaussian with zero mean and identity covariance, that is, $\mu=0$ and $\Sigma=I$
6.5.1 Marginals and Conditionals of Gaussians are Gaussians
- The marginal distribution of $p(x)$ of joint Gaussian distrib $p(x,y)$ is itself Gaussian and computed by applying the sum rule :
- $p(x) = \int{p(x,y)dy} = N(x|\mu_x, \Sigma_{xx})$
- The conditional distribution $p(x|y)$ is also Gaussian and given by
- $p(x|y) = N(\mu_{x|y}, \Sigma_{x|y})$
6.5.2 Product of Gaussian Densities
- The product of two Gaussians $ N(x|a,A), N(x|b,B)$ is a Gaussian distribution scaled by $c ∈ R$, given by $c N(x |\mathbf{c,C} )$ with
- $c = (2π)^{−D/2} |A+B|^{−1/2} exp( \frac{-1}{2}(a−b)^⊤(A+B)^{−1}(a−b))$
- $\mathbf{c} = C(A^{-1}a + B^{-1}b)$
- $\mathbf{C} = (A^{-1} + B^{-1} )^{-1}$
6.5.3 Sums and Linear Transformations
- If $X, Y$ are independent Gaussian random variables (i.e., the joint distribution is given as $p(x, y) = p(x)p(y)$ with $p(x) = N(x | μ_x, Σ_x)$ and $p(y) = N(y | μ_y , Σ_y)$,
- then $x + y$ is also Gaussian distributed and given by $ p(x+y) = N (μ_x +μ_y, Σ_x +Σ_y)$.
6.5.4 Sampling from Multivariate Gaussian Distrib.
-
Sampling from multivariate Gaussian Distrib. $N(0,I)$
-
(1) We need a source of pseudo-random numbers that provide a uniform sample in the interval [0,1]
-
(2) We use a non-linear transformation such as the Box-Muller transform to obtain sample from a univariate Gaussian
-
(3) We collate a vector of these samples to obtain a sample from a multivariate standart normal $N(0,I)$
-
-
Obtain samples from a multivariate normal $N(\mu, \Sigma)$
-
use the properties of a linear transformation of a Gaussian random variable :
-
If $x~N(0,I)$, $y = Ax+\mu$, $AA^T = \Sigma$ is Gaussian distributed with mean $\mu$ and covariance matrix $\Sigma$
-
One convinient choice of $A$ is to use the Cholesky decomposition (section 4.3)
-
-
6.6 Conjugacy and the Exponential Family
-
Bernoulli Distrib.
-
A discrete distrib having two possible outcomes $x ∈ [0, 1]$ in which $x=1$ occurs with probability $p$ and $x=0$ occurs with probability $1-p$
-
$P(x)=p^x(1−p)^{1−x}, x∈ { 0,1 }$
-
$\mathbb{E}(x) = 1 \times p + 0 \times (1-p) = p$
-
$\mathbb{V}(x) = \mathbb{E}[X^2] - (\mathbb{E} )^2 = p - p^2 = p (1 - p)$
-
-
ex) when we are interested in modeling the probability of “heads” when flipping a coin
-
References. Bernoulli Distribution, Binomial Distribution
-
-
Binomial Distrib.
-
a generalization of the Bernoulli distribution to a distribution over integers (The number of ways in which y out of N trials can be successful => N combination y)
-
$P(Y=y)= \begin{pmatrix} N \ y \end{pmatrix} p^y(1−p)^{N−y}$
-
$\mathbb{E}(x) = Np$
-
$ \mathbb{V}(x) = Np (1 - p)$
-
-
ex) observing m “heads” in N coin-flip experiments if the probability for observing head in a single experiments is $\mu$
-
-
Beta Distrib.
-
a distribution over a continuous random variable $x ∈ [0, 1]$, which is often used to represent the probability for some binary event
-
$P(x|α,β)= \frac{Γ(α+β)}{Γ(α)Γ(β)}x^{α−1}(1−x)^{β−1}$
-
$\mathbb{E}(x) = \frac{\alpha}{\alpha+\beta}$
-
$\mathbb{V}(x) = \frac{ \alpha \beta }{ (\alpha + \beta)^2 (\alpha + \beta + 1)}$
-
-
Intuitively, $\alpha$ moves probability mass toward 1, whereas $\beta$ moves probability mass toward 0
-
For α = β = 1, we obtain the uniform distribution U[0,1].
-
For α, β < 1, we get a bimodal distribution with spikes at 0 and 1.
-
For α, β > 1, the distribution is unimodal.
-
For α, β > 1 and α = β, the distribution is unimodal, symmetric, and centered in the interval [0, 1], i.e., the mode/mean is at 12 .
-
-
6.6.1 Conjugacy
- Conjugate Prior : A prior is conjugate for the likelihood function if the posterior is of the same form/type as the prior
- According to Bayes theorem, the poterior is proportional to the product of the prior and likelihood ($p(y|x)p(x)$)
- The specification of the prior can be tricky for two reasons:
- First, the prior should encapsulate our knowledge about the problem before we see any data. This is often difficult to describe.
- Second, it is often not possible to compute the posterior distribution analytically
- However, there are some priors that are computationally convenient: conjugate priors.
6.6.2 Sufficient Statistics
-
Sufficient Statistics : the idea that there are statistics that will contain all available information that can be inferred from data corresponding to the distribution under consideration
- sufficient statistics carry all the information needed to make inference about the population, that is, they are the statistics that are sufficient to represent the distribution.
-
In Machine Learning,
-
we consider a finite number of samples from a distribution.
-
As we observe more data, do we need more parameters $\theta$ to describe the distribution? => yes in general (field of non-parametric statistics)
-
Which class of distributions have finite-dimensional sufficient statistics, that is the number of params needed to describe distrib does not increase arbitrarily. => exponential family distributions (6.6.3)
-
-
6.6.3 Exponential Family
-
Three levels of abstraction (when considering distrib.)
-
(1) a particular named distribution with fixed params :
- ex) univariate Gaussian $N(0,1)$ with zero mean and unit variance
-
(2) fix the parametric form (the univar Gaussian) and infer the parameters from data (often used in ML)
-
(3) Families of distributions
-
-
Exponential Family
-
a family of probability distributions, parameterized by $\theta \in \mathbb{R}^D$ of the form
-
$p(x | θ) = h(x) exp (⟨θ, φ(x)⟩ − A(θ))$
-
$φ(x)$ is the vector of sufficient statistics. In general, any inner product can be used
-
-
6.7 Change of Variables / Inverse Transform : Transformation of random variables
-
Introduction
-
There are very many known distributions, but in reality the set of distributions for which we have names is quite limited.
-
Therefore, it is often useful to understand how transformed random variables are distributed
-
ex) Given that $X_1$ and $X_2$ are univariate standard normal, what is the distribution of $\frac{1}{2}(X_1 + X_2)$
-
-
Two approaches for obtaining distributions of transformations of random variables
- Direct Approach : using the definition of a cumulative distribution function
- Change of variable approach : uses the chain rule of calculus (5.2.2)
6.7.1 Direct Approach : Distribution Fuction Technique
-
Using the definition of CDF and the fact that its differential is the PDF
-
(1) Finding the CDF : $F_Y(y) = P(Y <y )$
-
(2) Differentiating the cdf $F_Y(y)$ to get the pdf : $f(y)= \frac{d}{dy}F_Y(y).$
-
6.7.2 Change of Variables
- Using “change of variables” technique of Calculus
- $ \int f(u)du = \int f(g(x))g^′(x)dx , \text{ where } u = g(x) .$
- Skip Details
Summary
-
Section 6.1. Construction of a Probability Space
-
The theory of probability aims at defining a mathematical structure to describe random outcomes of experiments.
- ex) Coin toss => cannot determine the outcome => by doing a large number of coin tosses => we can observe a regularity in the average outcome.
-
Two major interpretations of probability
- Bayesian interpretation
- Frequentist interpretation
-
Random Variable : is a function, is neither random nor is it a variable
-
-
Section 6.2. Discrete and Continuous Probabilities
- Discrete Random Variables and Probability mass functions.
- Continuous Random Variables and Probability density functions.
-
Section 6.3. Sum Rule, Product Rule, and Bayes’ Theorem
-
Sum Rule : Given the joint distribution $p(x,y)$, marginal distribution $p(x)$ is summation
- $p(x) = \sum_i p(x,y_i)$
-
Product Rule : Given the joint distribution $p(x,y)$ is same with the product of conditional distribution $p(x|y)$ and marginal distribution $p(x)$
- $p(x, y) = p(y | x)p(x)= p(x | y)p(y)$
-
Bayes’ Theorem
- $p(x|y) = \frac{p(y|x)p(x)}{p(y)}$
-
-
section 6.4. Summary Statistics and Independence
-
Summary Statistics : Mean, Variance, Covariance, Correlation
-
Statistically Independent => $p(x,y) = p(x)p(y)$
-
-
section 6.5. Gaussian Distribution
-
section 6.6 Conjugacy and the Exponential Family
- Named Distrib. Bernoulli, Binomial, Beta distribution
-
section 6.7, Change of Variables / Inverse Transform
-
Two approaches for obtaining distributions of transformations of random variables
-
Direct Approach : using the definition of a cumulative distribution function
-
Change of variable approach : uses the chain rule of calculus
-
-


Press office
Press office 0300 303 3342
Out of hours 07798 924 552
For enquiries from journalists only. The press office phone is open weekdays from 9am to 5pm.
Press release
Ofqual is announcing how spoken language assessments will be conducted, assessed and graded for the new GCSE in English language.
In September 2015 students will begin studying the new qualifications that will be first awarded in 2017. This GCSE is based on new subject content, including the requirement that students are assessed on their ability to demonstrate their spoken language skills.
We have previously announced that these results will be reported as a separate grade and will not contribute to the 9 to 1 grade for the subject. The 9 to 1 grade will be based on students’ performance in their written exams only.
Today’s announcement follows a public consultation and trials carried out by exam boards. These trials gathered the views of teachers and considered how the arrangements would work in practice. Taking these views into account, we have made changes (for example, to the extent of student recordings required) to support reliable assessment, while also recognising that arrangements must be proportionate and manageable for schools.
Chief Regulator Glenys Stacey comments:
It is so important that young people are able to communicate well, and that their communication skills are assessed fairly. At the same time, any test must be manageable for schools, and I am pleased today to announce the new testing arrangements, designed to be both manageable and fair.
View the full consultation outcome and feedback documents.
We are now consulting on proposals for:
Read and respond to this consultation
Press office 0300 303 3342
Out of hours 07798 924 552
For enquiries from journalists only. The press office phone is open weekdays from 9am to 5pm.


Page Clips
Loading clips...
You don't have anything clipped.
Select stuff from any web page by highlighting with your mouse
Right click your selection
Select 'Clip this...' from the popup menu


These filters allow django template use of elements beginning with an underscore character.
The sole purpose of these filters are to allow operations with template elements that naturally start with the underscore (‘_’) character.
Usage: field_
Example:
{{ form|field_:'_field_name' }}
Usage: attr_
{{ my_tag|attr_:'_attr_name' }}
Usage: dict_
{{ my_dict|dict_:'_key_name' }}
Enter search terms or a module, class or function name.


Ultimate Savage Warrior
1st January 2025
Mudd Manor, Westmorland, England
10km of the most brutal, punishing, really hard, grating, quite perturbing, outrageously filthy, family friendly mud running.
What you get
Every runner will receive:
- Our legendary 'Ultimate Savage Warrior' Soap-on-a-rope and Talc.
- An Exclusive Technical Bathrobe.
- Party bag with balloons and a slice of cake.
- Raffle ticket with a chance of winning a sandwich toaster signed by Jonathan Albon.
How to find us
Mudd Manor
Toughton,
Cheshire
TM11MT
If you are over 16 years of age on the event date:
If you are under 16 then consider Penultimate Savage Warriorlings.


November 19
For when for the time ye ought to be teachers, ye have need that one teach you again which be the first principles of the oracles of God; and are become such as have need of milk, and not of strong meat. Hebrews 5:12
Do you want to know why the Body of Christ has been in such a mess over the past few years? Do you want to know why the devil has been able to make a public display of our weaknesses? Do you want to know why, instead of being unified and strong, we've often been torn apart by division and criticisms that come not from without but within? It is because, as the Lord said in Hebrews, the people of God have need of milk and not of strong meat. They're babies! The people of God for the most part don't know His ways.
That's why He's commissioned you and me to train believers who are unskilled in the Word of righteousness and help bring them to maturity. "Sure," you say, "you're a preacher, but what about me? What can I do?" Well, I'll tell you. I believe God has called us both to do something. You'll find it in Hebrews 3:13. "Exhort one another daily, while it is called today."
That's no longer just a Bible verse to me. It's a direct command from the Lord. Gloria and I received that command a few years ago when we were preaching in Australia. It prompted us to step out in faith on daily television. But it's not a command that was just meant for us. It's one we all must obey in our own way.
"Exhort one another daily." Pray over that scripture today, won't you? Fellowship with your Father over it. Ask Him how He wants you to fulfill that command. He may tell you to help support ministries like Gloria's and mine who teach the uncompromised Word of God daily.  Whatever He says, do it!  You can help bring them from milk to meat. Begin to exhort them. Today.
Scripture Reading: Hebrews 3:7-19


Essential Grid is a powerful data grid that can be bound to various data sources including ADO.NET entities; LINQ to SQL; data collections like List, BindingList, and ADO.NET’s DataTable and DataView; and any IEnumerable or IQueryable collections.
It comes with built-in AJAX support and can work with ASP.NET AJAX's UpdatePanel. Essential Grid provides built-in support for hierarchical viewing, grouping, multicolumn sorting, filtering, summaries, and various data editors.
Essential Diagram is an extensible, high-performance .NET diagramming framework for ASP.NET applications. It can be used for developing Microsoft Visio-like interactive graphics and diagramming applications.
It stores graphical objects in a node graph and renders those objects on the screen. It supports both vector and raster graphics on the drawing surface.
Essential DocIO is a .NET library that can read, write, and modify Microsoft Word files. It features a full-fledged object model similar to the Microsoft Office Automation libraries.
It can be used on systems that do not have Microsoft Word installed. Essential DocIO enables users to create richly formatted Microsoft Word reports in Windows Forms, ASP.NET, WPF, ASP.NET MVC, and Silverlight applications.


{{suggestion.name}}
{{suggestion.description}}
Reported at: {{suggestion.creationTime | date: 'short'}}
Reported by: {{suggestion.author.firstName}} {{suggestion.author.lastName}}
Launch at: {{suggestion.startTime ? (suggestion.startTime | date: 'short') : 'N/A'}}
Launch by: {{suggestion.startEmployee ? (suggestion.startEmployee.firstName + ' ' + suggestion.startEmployee.lastName) : 'N/A'}}
Ended at: {{suggestion.endTime ? (suggestion.endTime | date: 'short') : 'N/A'}}
Ended by: {{suggestion.endEmployee ? (suggestion.endEmployee.firstName + ' ' + suggestion.endEmployee.lastName) : 'N/A'}}
Recipients:


Language of the document:
Arabic
English
Both (ar & en)
Quality of generated images:
720p
1024p
1366p
1920p
4K
8K
Input File (PDF):
Browse
Output Directory:
Browse
Convert


I am experienced developer working for NFQ since 2014. Key developer for eight software developing projects in USA, Germany and Lithuania within ERP systems. Especially strong with planning software architecture, back-end development and devOps, fluent in 5 programming languages. Latest work in ERP integration with 3st party systems and logistics. Able to build, scale & lead a team from scratch.
Developed AtlanticExpress ERP – USA shipping company ERP system, that integrates all shipping company business processes (Logistic, Accounting, intergration with USA govermental systems, integration with other private companies systems). LP Express – developed mobile devices software, responsible for Lithiania Post packages information managing. Shipzee – USA packages exporting to other countries system. SMS - Germany REAL company shops prices and orders automatic managing system.
Norwegian IT company UniMicro ERP system Uni Økonomi various modules development, tuning and integration with other systems. Mobile Worker – field service management and time tracking software. Was responsible for backend logic implementation and integration with other ERP systems. Timeplanlegger – norwegian time and work planning software.
Japan company FENDI CRM systems development and integration. Japan company SONY CRM and B2B systems development and integration. AOL CRM system. Netsymphony ERP system development.
Electricity systems engineering
Best final exam scores: mathematics 10/10
PHP (advanced), Symfony (advanced), MySQL (advanced), C# and ASP.NET (advanced), Microsoft SQL (advanced), TypeScript and JavaScript (advanced), Adobe Flex and Action Script (advanced), Elasticsearch (medium), ODATA services (medium), JAVA (basic), C and C++ (basic), Object C (basic).
Complex algorithms, WEB development, ERP systems, Legacy systems tuning, code refactoring and integration.
Lithuanian (native), English (professional), Russian (professional), Germany (beginner), Norwegian (beginner).
Periodical presentations and workshops in University about IT news and best practices. Periodical municipalities consultations about IT integration possibilities.
 In the winter, i am an avid skier. During the warmer months i enjoy windsurfing, kayaking and biking.
Was a member of my hometown Šiauliai municipal council.
When forced indoors, i like to read books. Follow a number of sci-fi and fantasy genre movies.


7
1 It was this Melchizedek, king of Salem, priest of God Most High, who met Abraham returning from the slaughter of the kings and blessed him.
2 Abraham gave him a tenth of everything he had captured. His name "Melchizedek" means "king of righteousness," and also "king of Salem," that is, "king of peace."
3 He was without father, without mother, without ancestors, without any beginning of days nor end of life. Instead, he remains a priest forever, like the Son of God.
4 Now consider how great this man was. Our ancestor Abraham gave a tenth of the best things that he had taken in battle.
5 And indeed, Levi's descendants who receive the priest's office have a command from the law to collect tithes from the people, that is, from their fellow Israelites, even though they, too, are descended from Abraham.
6 But Melchizedek, who was not a descendant from Levi, received tithes from Abraham, and blessed him, the one who had the promises.
7 There is no denying that the lesser person is blessed by the greater person.
8 In this case men who receive tithes will die one day, but in the other case the one who received Abraham's tithe is described as living on.
9 And, in a manner of speaking, Levi, who received tithes, also paid tithes through Abraham,
10 because Levi was in the private parts of his ancestor Abraham when Melchizedek met Abraham.
11 Now if perfection were possible through the Levitical priesthood (for under it the people received the law), what further need was there for another priest to arise after the order of Melchizedek, and not be named after the order of Aaron?
12 For when the priesthood is changed, the law must also be changed.
13 For the one about whom these things are said belongs to another tribe, from which no man has ever served at the altar.
14 Now it is evident that our Lord has descended from Judah, a tribe that Moses never mentioned concerning priests.
15 And what we say is clearer yet if another priest arises in the likeness of Melchizedek.
16 This new priest is not one who became a priest on the basis of the law relating to human descent, but instead on the basis of the power of an indestructible life.
17 For scripture witnesses about him:
"You are a priest forever
after the order of Melchizedek."
18 For the former commandment has been set aside because it is weak and useless.
19 For the law made nothing perfect. However, there is a better confidence for the future through which we draw near to God.
20 And this better confidence did not happen without the taking of an oath, for these other priests did not take any oath.
21 But God took an oath when he said about Jesus,
"The Lord swore and will not change his mind:
'You are a priest forever.'"
22 By this also Jesus has become the guarantee of a better covenant.
23 Indeed, death prevents priests from serving forever. This is why there are many priests, one after another.
24 But because Jesus lives forever, his priesthood is unchangeable.
25 Therefore he is also able to completely save those who draw near to God through him, because he always lives to intercede for them.
26 For such a high priest is right for us. He is sinless, blameless, pure, separated from sinners, and has become higher than the heavens.
27 He does not need, unlike the high priests, to offer up daily sacrifices, first for his own sins, and then for the sins of the people. He did this once for all, when he offered up himself.
28 For the law appoints men with weaknesses as high priests, but the word of the oath, which came after the law, appointed a Son, who has been made perfect forever.


People say Im creative and I also know my capabilities , what Im good at I put my work first and always put my client first so the job will be done and ontime.
Check it outThis was one of my first projects and Im proud of it take a look and may it make you want me to work on your idea.
Check it out


Features
|
|
Animacy
: animacy
Animacy
is not used.
Aspect
: aspect
Aspect
is not used.
Case
: case
Case
is not used.
Definite
: definiteness or state
The feature Definite
is marked to identify definite and indefinite articles.
Ind
: indefinite
Examples
- un cane “a dog”
- una bella giornata “a good day”
Def
: definite
Examples
- il cane “the dog”
- gli altri “others”
Red
: reduced
Not used.
Com
: complex
Not used.
Degree
: degree of comparison
Degree of comparison is used as an inflectional feature of some adjectives and adverbs.
Pos
: positive, first degree
Not used.
Cmp
: comparative, second degree
The quality of one object is compared to the same quality of another object.
Examples
- Luigi è migliore di me “Luigi is better than me”
- Il prezzo è inferiore “The price is lower”
Sup
: superlative, third degree
The quality of one object is compared to the same quality of all other objects within a set.
Italian does not seem to have single words for ‘relative’ superlatives, such as [en] “youngest”. One would say instead:
- Luigi è il più giovane “Luigi is the most young”
Abs
: absolute superlative
The quality of the given object is so strong that there is hardly any other object exceeding it. The quality is not actually compared to any particular set of objects.
Examples
- bellissimo, massimo, malissimo, ottimo “very beatiful”, “maximum”, “very badly”, “optimum”
Gender
: gender
Masc
: masculine gender
Nouns denoting male persons are masculine. Other nouns may be also grammatically masculine, without any relation to sex.
Examples
- castello “castle”
Fem
: feminine gender
Nouns denoting female persons are feminine. Other nouns may be also grammatically feminine, without any relation to sex.
Examples
- nave “ship”
Neut
: neuter gender
Not used.
Com
: common gender
Not used.
Mood
: mood
Mood is a feature that expresses modality and subclassifies finite verb forms.
Ind
: indicative
The indicative can be considered the default mood. A verb in indicative merely states that something happens, has happened or will happen, without adding any attitude of the speaker.
Examples
- Io scrivo una lettera “I write a letter”
Imp
: imperative
The speaker uses imperative to order or ask the addressee to do the action of the verb.
Examples
- Mangia la tua insalata! “Eat your salad!”
Cnd
: conditional
The conditional mood is used to express actions that would have taken place under some circumstances but they actually did not / do not happen.
Examples
- Mi sarei divertito “I would have enjoyed myself”
Pot
: potential
Not used.
Sub
: subjunctive / conjunctive
The subjunctive mood is used under certain circumstances in subordinate clauses, typically for actions that are subjective or otherwise uncertain.
Examples
- _Voglio che tu te ne vada “I want you to leave”
Jus
: jussive
Not used.
Qot
: quotative
Not used.
Opt
: optative
Not used.
Des
: desiderative
Not used.
Nec
: necessitative
Not used.
NumType
: numeral type
The NumType
feature applies to:
Card
: cardinal number or corresponding word
Examples
- uno “one”, due “two”, tre “three”
Ord
: ordinal number or corresponding word
This is a subtype of adjectives or pronouns.
Examples
- primo “first”, secondo “second”, terzo “third”;
- III, IV, XIX
- 30a, 30esima, 1°
Mult
: multiplicative numeral or corresponding word
Not used.
Frac
: fraction
Not used.
Sets
: number of sets of things
Not used.
Dist
: distributive numeral
Not used.
Range
: range of values
Used for expressions such as: * 2/3 Sett. * 3/4 volte
Gen
: generic numeral, i.e. a numeral that is neither of the above
Used for time expressions such as: * 23’ * 1’13’’ * 1.00’16’’
Number
: number
Number
is an inflectional feature of nouns,
pronouns,adjectives, determiners and
verbs).
Sing
: singular number
A singular noun denotes one person, animal or thing.
Examples
- [en] casa “house”, io compro “I buy”
Plur
: plural number
A plural noun denotes several persons, animals or things.
Examples
- [en] case “houses”, noi compriamo “we buy”
Dual
: dual number
Not used.
Examples
Ptan
: plurale tantum
Not used.
Coll
: collective / mass / singulare tantum
Not used.
Number
: number
Number
is an inflectional feature of nouns,
pronouns,adjectives, determiners and
verbs).
Sing
: singular number
A singular noun denotes one person, animal or thing.
Examples
- [en] casa “house”, io compro “I buy”
Plur
: plural number
A plural noun denotes several persons, animals or things.
Examples
- [en] case “houses”, noi compriamo “we buy”
Dual
: dual number
Not used.
Examples
Ptan
: plurale tantum
Not used.
Coll
: collective / mass / singulare tantum
Not used.
Polarity
: whether the word can be or is negated
Not used.
Poss
: possessive
Boolean feature of pronouns or adjectives.It tells whether the word is possessive.
Yes
: it is possessive
Examples
- Possessive pronouns: La sua è migliore “Hers is better”, I suoi sono felici “Her/his [parents] are happy”
- Possessive adjectives: La sua scuola è migliore “Her/his school is better”, I loro amici “Their friends”.
PronType
: pronominal type
This feature typically applies to pronouns, determiners, pronominal numerals (quantifiers) and pronominal adverbs.
Prs
: personal or possessive personal pronoun or determiner
See also the Poss feature that distinguishes normal personal
pronouns from possessives. Note that Prs
also includes reflexive
personal/possessive pronouns (see the Reflex feature).
Examples
- Personal pronouns: Uno di loro “One among them”, Per lui è utile “For him it’s useful”
- Possessive pronouns (
Poss=Yes
): La sua è migliore “Hers is better”, I suoi sono felici “Her/his [parents] are happy” - Possessive determiners/adjectives (
Poss=Yes
): La sua scuola è migliore “Her/his school is better”, I loro amici “Their friends”.
Note: the category clitic pronouns includes cases such as: Si è trasformato “Has transformed itself” (reflexive), Ti ho dato “I have given you” (indirect object), Ora si cerca il colpevole “Now one/somebody searches for the culprit” (impersonal form), Lo vediamo spesso “We often see him/it”. These are not marked by the appropriate PronType
.
Rcp
: reciprocal pronoun
We do not seem to have cases of reciprocal pronouns in Italian.
Art
: article
Article is a special case of determiner that bears the feature of definiteness.
Examples
- Definite articles (
Definite=Def
): La luna “The moon”, I regali di Natale “Christmas presents” - Indefinite articles (
Definite=Ind
): Un amico “A friend”, Una sorpresa “A surprise”
Int
: interrogative pronoun, determiner, numeral or adverb
Note that possessive interrogative determiners (whose) can be distinguished by the Poss feature.
Examples:
- Interrogative pronouns: Chi è il presidente? “Who is the president?”
- Interrogative determiners: Che cosa faremo adesso? “What shall we do now?”, Quale libro hai letto? “Which book did you read?”
Note: for the time being we do not use the feature ProntType=Int
interrogative pronouns such as dove “where” and quando “when” in sentences like Dov’ è Siena? “Where is Siena?”.
Rel
: relative pronoun, determiner, numeral or adverb
Examples:
- Relative pronouns: La strada che porta al mare “The road which leads to the sea”, Il libro che ho letto “The book that I read”.
- Relative determiners: Un autore sul cui futuro puoi scommettere “An author on whose future you can bet”.
Dem
: demonstrative pronoun, determiner, numeral or adverb
These are often parallel to interrogatives. Some tagsets might also distinguish a separate feature of distance (here / there; [es] aquí / ahí / allí).
Examples
- Demonstrative pronouns: Per questo sono ambiziosi “For this [reason] they are ambitious”.
- Demonstrative determiners: Parte di questo denaro “Part of this money”.
Note: Demonstrative adverbs such as qui “here” and là “there”, ora “now” e allora “then” are not marked with PronType=Dem
.
Tot
: total (collective) pronoun, determiner or adverb
Examples
We are not using PronType=Tot
.
Neg
: negative pronoun, determiner or adverb
Examples:
We distinguish only negative adverbs such as: non, nemmeno, _neppure.
Ind
: indefinite pronoun, determiner, numeral or adverb
Examples
- Indefinite pronouns: uno “one”, tutti “everybody”, ognuno “each one”, chiunque “anybody”, qualcosa “something”, qualcuno “somebody”
- indefinite determiners: tutti “all”, qualche “some”, ogni “each”, alcuni “some”, diversi “several”
Exc
: exclamative determiners. This value is language specific.
Examples
- che disastro “what a disaster”, che catastrofe “what a catastrophe”
Clit
: clitic pronouns. This value is language specific.
Used for clitic pronouns, part of speech PRON/PC.
Examples
- mi viene in mente “it comes to my mind”
- capace di farl lo “capable to do it”
- si convincono “they convince themselves”
- ci sono troppi ostacoli “there are too many obstacles”
Predet
: predeterminer. This value is language specific.
It is always used along with det:predet dependency relations.
Examples
- tutta la giornata “all day”
- tutti gli esseri umani “all human beings”
- entrambi i prigionieri “both prisoners”
Ord
: ordinal pronouns. This value is language specific.
It is used to mark ordinal pronouns. Part of speech is PRON/NO. When ordinals are used as noun modifiers they are marked as [ADJ].
Examples
- Il primo sostiene che … “the first asserts that …
- Un quarto d’ora “a quarter of an hour”
- Valentina è quinta “Valentina is fifth”
Reflex
: reflexive
Boolean feature of pronouns. It tells whether the word is reflexive, i.e. refers to the subject of its clause.

Examples
- reflexive personal pronouns: se, si;
Tense
: tense
Tense is a feature of verbs.
Past
: past tense
Examples
- Lui andò a casa “he went home”
Pres
: present tense
The present tense denotes actions that are happening right now or that usually happen.
Examples
- Lui va a casa “he goes home”
Fut
: future tense
Examples
- andrà a casa “he/she will go home”
Imp
: imperfect
- andava a casa “he/she was going home”
Nar
: narrative
Not used.
Pqp
: pluperfect
Not used.
VerbForm
: form of verb or deverbative
Fin
: finite verb
Examples
- _loro hanno “they have”
Inf
: infinitive
Examples
- desidero andare a dormire “I wish to go to sleep”
- devo andare “I must go”
Sup
: supine
Not used.
Part
: participle
Examples
- potrebbe essersi preparato “he could have been prepared”;
- _è arrivato</b< tardi_ “he arrived late”
- appartenenti ad organizzazioni terroristiche “members of terroristic organizations”
Trans
: transgressive
Not used.
Ger
: gerund
Examples
- Sto sognando you “I am dreaming”
- Arrivando tardi si perde il treno “Arriving late you miss the train”
Voice
: voice
Voice
is not used.


{% extends 'registration/registration.html' %} {% block registration-header-content %}
Please enter your new password twice so we can verify you typed it in correctly.
{{ form.new_password1.help_text }}
Invalid token.
Request a new password reset token


|
Welcome to the Knopflerfish website.
The goal with the Knopflerfish project is to develop and distribute
easy to use open source code, build tools and applications, related to
the OSGi specifications. See charter for details.
Makewave (formerly Gatespace Telematics) is the primary maintainer and sponsor of the Knopflerfish project and has several developers assigned to develop and maintain the Knopflerfish OSGi distribution. The OSGi Alliance specifies an industry standard Java application platform, allowing multiple applications, to securely run in a single JVM. These programs can share resources as data, functionality and threads. Further information on the OSGi technology is available at the OSGi Alliance web site at: http://www.osgi.org OSGi Community Event 2008, 10-11 June, BerlinPlease join us at this year's OSGi Community Event, the premier gathering of OSGi-heads in the world. Both Gunnar Ekolin and Christer Larsson from Knopflerfish / Makewave will be present in Berlin.  Christer will be giving a talk on the CVIS project in which OSGi technology is one key component. |
Latest News
|
||||||||||
Knopflerfish 2 - OSGi R4Knopflerfish 2 (KF2) is the main development branch of Knopflerfish. KF2 is designed to be compliant with the OSGi Release 4 specifications. The current stable version of KF2 is Knopflerfish 2.0.5. KF1 still remains available as an OSGi Release 3 option. |
|||||||||||
| To better support the many KF users from Japan there is now Japanese version of the Knopflerfish homepage available. The goal is to create a complete Japanese KF site, this is just the first glimpse. | |||||||||||
Looking for support for OSGi / Knopflerfish or in need for the R4 certified Knopflerfish Pro?Makewave (formerly Gatespace Telematics) offers complementary middleware services and products to the freely available Knopflerfish, thereby giving companies the assurance needed to use open source software in commercial products. The offering includes a remote management systems for OSGi devices, the certified Knopflerfish Pro edition, including full support agreements, and the expertise and consulting services of the maintainers of Knopflerfish. Please visit their website: http://www.makewave.com to learn more. |


In Edinburgh, a city with a hidden history of drug absue, this is a problem very close to our hearts.
Thousands die each year from drugs which are contaminated with dangerous cutting agents or other more potent drugs.
A rise in accidental overdoses from users not knowing the purity of the drugs they take is causing hundreds of unnecessary deaths.
Knowing what is contained in the drugs could save many lives.
We are creating a cell- free paper-based biosensor that can tell a user exactly what is in the drugs they are taking.
Our biosensor will detect lethal contaminants and give a quantitative analysis of purity, red-lighting dangerously high purity levels.
Multiple tests will be integrated into one easy to use, portable and cheap biosensor. Multiple tests will be integrated into one easy to use, portable and cheap biosensor.
This summer we will focus on the development of three tests: Heroin Purity, PMA detection, DNP in Diet Pills.
Our work is routed deeply in the world of the people we're seeking to help. We have researched extensively, ensuring the need for our project is strong. Our own prejudice does not drive us. Instead we are getting out there, experiencing what it is really like. At every opportunity we are engaging with users, getting to know their story.
We are exploring all angles of use for our device, national and international implementation, delving into regulations and policies, investigating the wider world and long term consequences of our device.


Black Friday deals on gaming headsets include Astro, SteelSeries, Razer, and more
Follow Polygon online:
by Charlie HallThere’s no better gift for the console or PC gamer in your life than a nice new gaming headset, and there’s no better time to find deals on new headsets than the week of Black Friday.
This year’s headset promotions are a little slow to roll out, but so far we’ve found decent deals on headphones from Astro, Razer, SteelSeries, Sony, and more. We’ll update this page throughout the weekend as more bargains come around.
Also keep in mind that fancy headphones aren’t just good for gaming. Advances in virtual surround sound make high-quality positional audio possible at every budget. Fans of Disney Plus especially should take note, since most of the blockbusters in the Star Wars and Marvel cinematic universes are now suddenly available with full Dolby Atmos integration.
Let’s kick things off with discounts on our picks for the best headsets of 2019. Additional deals will be added and crossed off as we go along.
Polygon’s Essentials list of the best gaming headsets
- Kingston HyperX Cloud Mix: Regularly $199.99, now $187.38 on Amazon.
- Sennheiser GSX 1000: Regularly $229.99, now $169.95 on Amazon.
- SteelSeries Arctis Pro Wireless: Regularly $329.99, now $278.19 on Amazon.
Best Buy
- Skullcandy Crusher ANC Wireless: Regularly $319.99, now 279.99 at Best Buy.
- Sony Gold surround sound headset, rose gold: Regularly $99.99, now $69.99 at Best Buy.
- Sony Fortnite Neo Versa Gold: Regularly $99.99, now $69.99 at Best Buy.
- Sony Fortnite Gold surround sound headset, white: Regularly $99.99, now $69.99 at Best Buy.
- Sony Gold wireless stereo headset, black: Regularly $99.99, now $69.99 at Best Buy.
- Sony Gold wireless stereo headset, white: Regularly $99.99, now $69.99 at Best Buy.
- Turtle Beach Stealth 300 for Xbox One: Regularly $79.99, now $39.99 at Best Buy.
- Turtle Beach Stealth 300 for PlayStation 4: Regularly $79.99, now $39.99 at Best Buy.
Related
Amazon
- Astro A10 for PlayStation 4: Regularly $60.00, now $49.99 on Amazon.
- Astro A10 for Xbox One: Regularly $99.99, now $27.49 on Amazon.
- Astro A40 TR with the MixAmp M80 for Xbox One: Regularly $200.00, now $126.00 on Amazon.
- Astro A40 TR with the MixAmp Pro TR for Xbox One: Regularly $249.99, now $163.97 on Amazon.
- Cooler Master MH-751: Regularly $89.99, now $59.99 on Amazon.
- HC Gamerlife stereo headset with 53 mm drivers: Regularly $129.99, now $99.00 on Amazon.
- PlayStation Gold wireless surround sound headset, black: Regularly $99.99, now $67.99 on Amazon.
- SteelSeries Arctisx 7: Regularly $149.99, now $112.99 on Amazon.
- SteelSeries Arctis Pro: Regularly $179.99, now $133.03 on Amazon.
- Razer Kraken headsets in black and green: Regularly $79.99, now $49.99 at Amazon.
- Razer Thresher for PlayStation 4 and PC: Regularly $149.99, now $125.86 on Amazon.


A simple, open source, HackerNews reader application. Read ycombinator's hacker news on the mobile devices you carry around daily!
Port of meteor's transparent reactive framework (tracker.js) for Android
Application to play WillowTree's Google I/O Bingo. Written in Kotlin and Java, utilizing Realm.io and an MVP architecture.
Displays your installed apps and allows you to quickly export all the names as text or to a file.
A DashClock extension to show you the last entry in your call history


1. How many books are in the King James Version of the Bible?
2. What was invented by Dr. Edward Land in 1947?
3. What Greek physician became known as the founder of Medicine?
4. In which city can you see Michelangelo's David?
5. Who invented the first major printing press?
6. Whose album sold the most in a single day?
7. What was the first Japanese car to be produced in the United States?
8. Ulysses S. Grant appears on the front of which denomination of US currency?
9. How many time zones are there in the world?
10. What is the chemical symbol for table salt?


On the final day of the event, data service providers and individual researchers from the local community will deliver a wide variety of talks and workshops.
This session will give an overview of the major Python libraries used for data science. Participants will learn how to manage and install these libraries using the conda package manager.
Modern research relies heavily on software and code. These aspects of the research methodology are rarely (if ever) documented in modern research papers, which has led to a reproducibility crisis in published computational research. This talk will outline the practical steps you can take to ensure that your papers are reproducible.
Is your laptop running out of battery? Or disk space? Do you need a server computer to work with your colleague? Or colleagues? In Canada? The Nectar Research Cloud provides. It provides flexible ways of accessing many CPU and GB, or TB, or even PB. At bandwidths that measure in the Gb. Better yet, it's free if you work or study at an Australian research institution. Join this Cloud Starter class to learn hands-on how to launch your own virtual machine in the Nectar Cloud to help take your Resbaz Bash, R and Python skills to the next level and to the next scale.
TBA
R-Ladies is a world-wide organisation to promote gender diversity in the R community. The purpose of this session is to gauge interest in starting a Hobart chapter.
This session will give an overview of the major R libraries used for data science. Participants will learn how to manage and install these libraries.
Come along and listen to our experienced Software Carpentry instructors interview willing researchers about their personal data science workflows. If you're feeling brave you can put your hand up to be an interviewee, otherwise sit back and join in the audience discussion.
This session provides an overview of how the Australian Ocean Data Network (AODN) team leverages cloud technologies to support developing services for delivering oceanographic data. Utilising these technologies allows us to deliver reliable and scalable solutions for data availability. In this session, we provide an introduction to some of the most useful cloud services and insight into future possibilities for AODN infrastructure.
A critical skill for any scientist is the ability to effectively communicate your ideas. This course is a very short introduction to effective public speaking, and introduces some basic concepts such as how to prepare and structure your speech, the use of visual aids and speaking with confidence. Each participant will be asked to deliver a 2 minute speech and will be given a critical evaluation.
In this session Tom will present a range of options to integrate figure and table creation into the final document. This process allows the figures, tables and values within the document to be automatically updated as data is corrected or added too. The aspirational goal would be to be able to program much of the final output as well (increase / neutral / decrease statements), which could be useful for regular reporting, but this useful feature is less clear in an academic context.
This session will give an introduction to Ferret, which is a data analysis and visualisation environment used extensively in the oceanography community.


A query is broken up into terms and operators. There are two types of terms: Single Terms and Phrases. A Single Term is a single word such as "test" or "hello". A Phrase is a group of words surrounded by double quotes such as "hello dolly". Multiple terms can be combined together with Boolean operators to form a more complex query.
When performing a search you can either specify a field by typing a field name followed by a colon ":" and then the term you are looking for, or use the default fields. The default fields are: patient_id, patient_name, caregiver_name and caregiver_phone, so if you do not specify a field name these will be used. If you would like the default search fields to change please send in a support request.
When performing a search you can either specify a field, or use the default field.
You can search any field by typing the field name followed by a colon ":" and then the term you are looking for.
As an example, let's assume a Lucene index contains two fields, title and text and text is the default field. If you want to find the document entitled "The Right Way" which contains the text "don't go this way", you can enter:
title:"The Right Way" AND text:go
or
title:"Do it right" AND right
Since text is the default field, the field indicator is not required.
Note: The field is only valid for the term that it directly precedes, so the query
title:Do it right
Will only find "Do" in the title field. It will find "it" and "right" in the default field (in this case the text field).
You can search any field by typing the field name followed by a colon ":" and then the term you are looking for.
Lucene supports single and multiple character wildcard searches within single terms (not within phrase queries).
To perform a single character wildcard search use the "?" symbol.
To perform a multiple character wildcard search use the "*" symbol.
The single character wildcard search looks for terms that match that with the single character replaced. For example, to search for "text" or "test" you can use the search:
te?t
Multiple character wildcard searches looks for 0 or more characters. For example, to search for test, tests or tester, you can use the search:
test*
You can also use the wildcard searches in the middle of a term.
te*t
Note: You cannot use a * or ? symbol as the first character of a search.
Range Queries allow one to match documents whose field(s) values are between the lower and upper bound specified by the Range Query. Range Queries can be inclusive or exclusive of the upper and lower bounds. Sorting is done lexicographically.
title:{Aida TO Carmen}
This will find all documents whose titles are between Aida and Carmen, but not including Aida and Carmen.
Inclusive range queries are denoted by square brackets. Exclusive range queries are denoted by curly brackets.
When searching dates you need to include a strict syntax:
reported_date<date>:[2002-01-01 TO 2003-01-01]
This will find documents whose reported_date fields have values between 2002-01-01 and 2003-01-01, inclusive.
When searching integers you need to include a strict syntax:
last_menstrual_period<int>:[10 TO 12]
This will find documents whose last_menstrual_period fields have values between 10 and 12, inclusive.
Boolean operators allow terms to be combined through logic operators. Lucene supports AND, "+", OR, NOT and "-" as Boolean operators(Note: Boolean operators must be ALL CAPS).
The OR operator is the default conjunction operator. This means that if there is no Boolean operator between two terms, the OR operator is used. The OR operator links two terms and finds a matching document if either of the terms exist in a document. The symbol || can be used in place of the word OR.
To search for documents that contain either "jakarta apache" or just "jakarta" use the query:
"jakarta apache" jakarta
or
"jakarta apache" OR jakarta
The AND operator matches documents where both terms exist anywhere in the text of a single document. This is equivalent to an intersection using sets. The symbol && can be used in place of the word AND.
To search for documents that contain "jakarta apache" and "Apache Lucene" use the query:
"jakarta apache" AND "Apache Lucene"
The "+" or required operator requires that the term after the "+" symbol exist somewhere in the field of a single document.
To search for documents that must contain "jakarta" and may contain "lucene" use the query:
+jakarta lucene
The NOT operator excludes documents that contain the term after NOT. This is equivalent to a difference using sets. The symbol ! can be used in place of the word NOT.
To search for documents that contain "jakarta apache" but not "Apache Lucene" use the query:
"jakarta apache" NOT "Apache Lucene"
Note: The NOT operator cannot be used with just one term. For example, the following search will return no results:
NOT "jakarta apache"
The "-" or prohibit operator excludes documents that contain the term after the "-" symbol.
To search for documents that contain "jakarta apache" but not "Apache Lucene" use the query:
"jakarta apache" -"Apache Lucene"
{@translate value="Available Search Fields"/}


SHADOW OF THE VAMPIRE Reviewed by Jerry Saravia January 27th, 2001
"Shadow of the Vampire" has such an inventive, original idea that I am almost willing to recommend it based on its premise. Unfortunately, like most great ideas, it does not fully exploit it for all its worth, and seems to skim past some missed opportunities resulting in a fairly bland movie that may please some movie buffs, yet will mostly annoy everyone else.
"Shadow of the Vampire" is a fictional behind-the-scenes look at the making of one of the greatest, most realistic vampire films ever made, "Nosferatu," which was released back in 1922. John Malkovich stars as F.W. Murnau, the madly eccentric, madly obsessed film director of "Nosferatu," itself based on the famed Bram Stoker novel though changes were made to avoid being sued by Stoker's widow. As the film begins, Murnau has just completed studio shots for his latest endeavor ("Thank God, an end to this artifice!"), and is ready to shoot outdoor night shots in the countryside and on an island to capture the necessary realism for the tale. All they need is a vampire and Murnau has found one, an actor named Max Schreck (Willem Dafoe) who lives in an abandoned monastery. Murnau claims the actor studied under Stanislavsky from the Max Reindhardt troupe. The crew is afraid of this gauntlike, bald creature who fits the role all too well, and needs no makeup! Gradually, we discover that Schreck is not an actor at all, he is a real vampire and has his eye on the lead actress Greta Schroeder (Catherine McCormack), who will have herself sacrificed to the vampire in the final scene of the script!
Murnau knows Schreck is a vampire and their unusual contract stipulates that Schreck continue his feeding habits until after the shoot (a bottle of blood and small animals are used as alternative food items). Naturally, Schreck is too hungry for blood and ends up devouring not only bats but the neck of a cinematographer. He also has the desperate need to acquire the neck of Greta. The contract is unheeded but it doesn't seem to matter - Murnau has become so obsessed with his opus that he hardly cares about anyone and appears as monstrous as the creature himself.
The pacing is off in "Shadow of the Vampire" as the transitions between scenes seem choppy at best. This makes the overall film rather monotonous until Dafoe shows up, and he brings the film out of its drunken stupor with his vibrantly alive performance. It is still not enough as the visual style of the film seems unimaginative with grainy colors and several darkly lit scenes. Some of the black-and-white scenes of the actual filming of the film-within-the-film are wonderful yet brief.
As written by newcomer Steven Katz, "Shadow of the Vampire" has scant evidence of insight into Murnau's crew members and Murnau's private life - we just see that he is a morphine addict who envisions cinema as "everlasting life." Malkovich mostly yells but there is not much more to his performance (his intoxicatingly emotional final scene is exceptionally well done). It also doesn't help that the film makes a case for the similarity between vampires and filmmakers - they are out to sell their souls to bring life into their own encapsulated world, or as Murnau exclaims, "It does not exist unless it is in the lens." I just don't see the overall connection as being fully realized as it should have been.
The rest of the cast is perfunctory at best. Eddie Izzard as the Jonathan Harker character barely has much screen time and mysteriously disappears from the film. Catherine McCormack has a few breathtaking moments as Greta and we understand that her character chooses the theatre over cinema, but that is it. Cary Elwes is unmemorable as the substitute cinematographer (he also appeared in Coppola's "Dracula"), and Udo Kier (a former Warhol regular) merely glides by the screen as the financially obsessed producer. Kier does have a funny scene where he describes having once seen someone pull ectoplasm out of their mouth.
That leaves Dafoe who gives a tour-de-force performance as the enigmatic Schreck. He gyrates, frowns, smiles, has arch-like eyebrows, long fingernails, and a general frailty that lends sympathy to the "rat-like bastard," as Murnau excitedly claims while shooting a scene. Dafoe projects such a chilling, eerie demeanor that you can't help but be both frightened and fascinated by him. It is such a superb performance that one must see it just to believe it. The film, though, is a mere shadowy reflection of what made "Nosferatu" the silent classic it is today.
For more reviews, check out JERRY AT THE MOVIES at http://moviething.com/buffs/faust/
E-mail me with any questions, comments or general complaints at<EMAIL_ADDRESS>or at<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


I'm Ignacio Azzi,
Product Designer
My passion is to design the best way for users to fulfill their needs through their interaction with digital touch points.
I have been working for more than 8 years in User Experience (UX) and have solid knowledge of mobile platforms, UX and design.
They are eager to be read, analyzed and praised
Write me at ignacioazzi@gmail.com


Hollywood Farmers' Market
Sunday 8am-1pm
Mar Vista Farmers' Market
Sunday 9am-2pm
Culver City Farmer's Market
Tuesday 2-7pm
Westwood Village Farmer's Market
Thursday 12pm-6pm
Contact Us:
<EMAIL_ADDRESS>310.910.5899


Col
(type in module tri
)
Provides an object rendition of the Static Col defined in the Table
object
defined in the Javascript file.
Referred to in this documentation as the dynamic instance of the Col
object.
The public methods attached to the Col
object and described herein are
accessible from the HTML code assuming a Col
object is available.
Constructor of the the Col
object. Performs the following functions:
Col
type into 'virt' (col property points to a function) or 'field'cid
property that makes the each column unique in the entire system across
all Tables.cid
props – {Object} –
Properties array used to define the column in static object.
Builds an array of Action objects from a Col
whose type is 'actions'. The
following algorithm is used to build the array.
editRecord
and dropRecord
actions unless the
Col
addDefault property is falsemethClass
, method
, click
, whatClass
function pointers into the $scope.$scope – {scope} –
of HTML caller
oObj – {Object} –
obsolete. not referenced.
{Object[]}
– array of Action objects
Returns field name in table column is related to. For type = 'virt' the constant 'field' is returned.
{string}
– related field name
Returns the hint field that is added to Standard Editor input fields as a 'title=' string.
If hint
in the column definition is a function it is called with the signature this.hint(scope,this)
. Otherwise the string value is returned.
{string}
– computed hint.
Returns the getTitle
value with blanks replaced by '-'. Used in the HTML
templates to create element IDs based on the column name that can be refenced in the CSS.
{string}
– title modified
Returns the hint field that is added to the list columns of the Lister.
The field is assumed to be a function which is called with signature this.listHint(scope,oObj,this)
where
oObj
is the row being displayed.
{string}
– computed hint.
Returns the place-holder field that is added to Standard Editor input fields as a 'placeHolder=' string.
If place
in the column definition is a function it is called with the signature this.place(scope,this)
. Otherwise the string value is returned.
{string}
– computed place-holder.
Returns the Col
title
{string}
– Col
name used for public display
Returns the value of oObj for the Col
. Invokes any necessary functions
to calculate the value. If the nMax
field is present the computed string
is checked that is does not exceed that length. If it does it is shortened and
the string ...
added such that the string's length equals the nMax
field.
scope – {Object} –
The present scope
oObj – {Object} –
the data object to extract the Col
from.
nMax – {number} –
optional max string length returned
{string}
– the computed value
Extends the supplied array of Col
objects with this Col
if it matches
the sType parameter which can have the following values:
scope – {Object} –
caller scope
oCols – {Object[]} –
array of Col
objects to extend
sType – {string} –
to match against Col
type. sType = null matches all.


The purpose of the Mailbox library is to let applications send and receive information to and from other computers, through a variety of communications media. It insulates the application as much as possible from the mechanics of transmitting and receiving the information.
An application might need to transmit information over several different kinds of connection. For example, it might send information over a modem or through a direct connection. It might need to use the same device in very different ways; for example, it might fax a document through a modem, or copy a file to a server through that same modem.
The Mailbox library helps to insulate applications from the details of the hardware and communication protocols. It does this by dividing up the communications tasks.


Four features
Columns, gutters, a baseline and a script.
Folding columns
Golden Grid System (GGS) splits the screen into 18 even columns. The leftmost and rightmost columns are used as the outer margins of the grid, which leaves 16 columns for use in design.
Now, 16 columns sounds a bit much for anything other than huge widescreen monitors. This is where the folding, inspired by the DIN paper system and Unigrid, comes in. The 16 columns can be combined, or folded, into 8 columns for tablet-sized screens, and into 4 columns for mobile-sized ones. This way GGS can easily cover any screen sizes from 240 up to 2560 pixels.
The dimensions of the grid in each configuration are noted down within CSS comments, accompanied by suitable media queries, like thus:
/*
* Four-column grid active
* ----------------------------------------
* Margin | # 1 2 3 4 | Margin
* 5.55555% | % 25 50 75 100 | 5.55555%
*/
Elastic gutters
While the column widths in GGS are proportional to the screen's width, the widths of its gutters (the spaces between columns) are proportional to the page's font-size, specified in ems.
Responsive grids that use gutters proportional to the screen can make the content feel like it's being squeezed together or pulled apart as the screen width changes. With elastic gutters this just doesn't happen, as the gutters always stay in proportion to the content.
Elastic gutters are created by positioning elements in the center of the gutter (using percentages) and giving them a padding equal to half of the gutter's width. For example:
.wrapper {
box-sizing: border-box; /* + vendor prefixes */
width: 50%;
margin-left: 25%;
/* Assuming gutter width = 1.5em */
padding: 0 0.75em;
}
Zoomable baseline grid
Responsive layouts often require you to change the font-size at certain screen widths, for example to make the text easier to read on huge monitors, or to make the text fit better onto narrow mobile screens. This can make the proportions of your layout feel off, especially if you're using a baseline grid. GGS's zoomable baseline grid gets around this problem.
If you specify all your font-sizes, line-heights, as well as vertical paddings, margins and borders in ems, they'll all scale in proportion as the font-size is changed using media queries, always keeping the baseline grid intact (save for a 1px rounding error or two), which lets the layout keep the same vertical rhythm regardless of screen size.
GGS comes with a set of type presets aligned to a baseline grid, which is based on a base line-height of 1.5. Feel free to replace them with your own presets, though.
Golden Gridlet
Aligning elements in responsive layouts can be difficult with all the percentage values flying around. GGS comes with Golden Gridlet, a little script that adds a button into the upper right corner of the page. When clicked or tapped, it overlays the GGS grid and a baseline grid of 1.5em onto the page, making it easy to visually check that design elements align up.
Golden Gridlet should work in most modern browsers, and since it doesn't rely on a keyboard, it can be used on touch screen devices as well. In modern browsers, the overlay appears with a pleasing CSS3 transition. Give it a try by clicking or tapping the icon in the upper right corner of this page. It's pretty fun.
(Please note that due to rounding errors the baseline grid guides might not align up properly if the baseline grid is zoomed in or out.)
Four downloads
All hosted on Github.
GGS.html
Contains the required markup (namely the meta viewport tag) and a simple demo of the grid in use.
GGS.css
Contains the meat of GGS, with some demo code filled in. Details about its contents are included in CSS comments throughout the file.
GGS.less / GGS.scss
Both contain the source of GGS.css. GGS.less is written using the LESS CSS language. GGS.scss is written using the SCSS language, and was contributed by mikker.
GGS.js
Contains Golden Gridlet, a script that overlays the GGS grid and a baseline grid of 1.5em onto the page. Can be customized around the top of the file. Powered by the Ender library.
Many useful tips
And answers to some FAQs.
Don't use GGS as it is.

Fluid design is hard.
Really hard. Don't give up. Read Fluid Grids and Responsive Web Design by Ethan Marcotte. They help a lot.
Don't set a max-width.
Or at least don't set one below 2560px. When your content starts getting too wide, use the zoomable baseline grid to make it fit a little better, or add some empty columns on the sides. The whole point of a fluid grid is to use the screen's proportions to align elements, so stick to it.
Mobile Safari causing trouble?
Does your site zoom in too much when changing orientations on an iOS device? It's because of this Mobile Safari bug.
GGS actually does very little.
It’s definitely not a framework. It’s more just a starting point and a couple of guidelines.
Serve IE6–8 just the mobile layout.
Old IE won't see any styles that are inside a media query, so just serve it your mobile layout and enhance it a little with IE-specific classes. Not having to worry about old IE makes coding the wider layouts so much easier. More about this in my blog post: Leaving Old Internet Explorer Behind.
Use box-sizing: border-box;
It lets you give the same element both a width in percentages as well as a padding in ems, which is required for the elastic gutters to work. If you followed my advice about IE6–8 above, you can use this inside media queries without worrying about browser support.
Don’t confuse GGS with "The Golden Grid".
The Golden Grid, made by @vladocar, is also a grid system. It has nothing to do with GGS. Accidental naming conflict. My fault.


Search for your schools to see their location! (You can view multiple locations on the same map, so search for as many as you want!)


Enum ErrorCode
Enumeration for errors that can be raised by WinSCard.
Namespace: WSCT.Wrapper
Assembly: WSCT.dll
Syntax
public enum ErrorCode : uint
Fields
| Name | Description |
|---|---|
| BadSeek | There was an error trying to set the smart card file object pointer. |
| Cancelled | Error: The action was cancelled by an SCardCancel request. |
| CancelledByUser | Warning: The action was cancelled by the user. |
| CantDispose | Error: The system could not dispose of the media in the requested manner. |
| CardNotAuthenticated | Warning: No PIN was presented to the smart card. |
| CardUnsupported | The smart card does not meet minimal requirements for support. |
| CertificateUnavailable | The requested certificate could not be obtained. |
| ChvBlocked | Warning: The card cannot be accessed because the maximum number of PIN entry attempts has been reached. |
| CommDataLost | A communications error with the smart card has been detected. Retry the operation. |
| CommError | Fatal: An internal communications error has been detected. |
| DirNotFound | The identified directory does not exist in the smart card. |
| DuplicateReader | The reader driver did not produce a unique reader name. |
| Eof | Warning: The end of the smart card file has been reached. |
| ErrorInvalidHandle | The handle is invalid. |
| ErrorInvalidParameter | The parameter is incorrect. |
| FileNotFound | The identified file does not exist in the smart card. |
| IccCreateorder | The requested order of object creation is not supported. |
| IccInstallation | No Primary Provider can be found for the smart card. |
| InsufficientBuffer | Error: The data buffer to receive returned data is too small for the returned data. |
| InternalError | Fatal: An internal consistency check failed. |
| InvalidAtr | Error: An ATR obtained from the registry is not a valid ATR String. |
| InvalidChv | The supplied PIN is incorrect. |
| InvalidHandle | Error: The supplied handle was invalid. |
| InvalidParameter | Error: One or more of the supplied parameters could not be properly interpreted. |
| InvalidTarget | Error: Registry startup information is missing or invalid. |
| InvalidValue | Error: One or more of the supplied parameters values could not be properly interpreted. |
| NoAccess | Access is denied to this file. |
| NoDir | The supplied path does not represent a smart card directory. |
| NoFile | The supplied path does not represent a smart card file. |
| NoKeyContainer | The requested key container does not exist on the smart card. |
| NoMemory | Error: Not enough memory available to complete this commandAPDU. |
| NoReadersAvailable | Cannot find a smart card reader. |
| NoService | The Smart card resource manager is not running. |
| NoSmartcard | Error: The operation requires a Smart Card, but no Smart Card is currently in the device. |
| NoSuchCertificate | The requested certificate does not exist. |
| NotReady | Error: The reader or smart card is not ready to accept commands. |
| NotTransacted | Error: An attempt was made to end a non-existent transaction. |
| PciTooSmall | The PCI Receive buffer was too small. |
| ProtoMismatch | Error: The requested protocols are incompatible with the protocol currently in use with the smart card. |
| ReaderUnavailable | Error: The specified reader is not currently available for use. |
| ReaderUnsupported | The reader driver does not meet minimal requirements for support. |
| RemovedCard | Warning: The smart card has been removed, so that further communication is not possible. |
| ResetCard | Warning: The smart card has been reset, so any shared state information is invalid. |
| SecurityViolation | Warning: Access was denied because of a security violation. |
| ServerTooBusy | The Smart card resource manager is too busy to complete this operation. |
| ServiceStopped | The Smart card resource manager has shut down. |
| SharingViolation | Error: The smart card cannot be accessed because of other connections outstanding. |
| Shutdown | P: The operation has been aborted to allow the server application to exit. |
| Success | Success: No error was encountered. |
| SystemCancelled | Error: The action was cancelled by the system, presumably to log off or shut down. |
| Timeout | Error: The user-specified timeout value has expired. |
| Unexpected | An unexpected card error has occurred. |
| UnknownCard | Error: The specified smart card name is not recognized. |
| UnknownError | Fatal: An internal error has been detected, but the source is unknown. |
| UnknownReader | Error: The specified reader name is not recognized. |
| UnknownResMng | An unrecognized error code was returned from a layered component. |
| UnpoweredCard | Warning: Power has been removed from the smart card, so that further communication is not possible. |
| UnresponsiveCard | Warning: The smart card is not responding to a reset. |
| UnsupportedCard | Warning: The reader cannot communicate with the smart card, due to ATR configuration conflicts. |
| UnsupportedFeature | This smart card does not support the requested feature. |
| WaitedTooLong | Fatal: An internal consistency timer has expired. |
| WriteTooMany | The smartcard does not have enough memory to store the information. |
| WrongChv | Warning: The card cannot be accessed because the wrong PIN was presented. |


1. How might you argue that Karl Blossfeldt's photographs are abstract?
2. Find an example of architectural ornamentation that might have had its creative inspiration in the world of plants.
3. Blossfeldt's Bio:
a) Where was he born?
b) Where did he study?
c) Where did he teach?
4. In your own words, defend the following statement: Paul Strand was one of the major forces of photographic modernism.
5. Paul Strand had influences from a variety of different artists. Name the artists from each of the following disciplines that had some impact on his work:
a) photography;
b) painting;
c) sculpture;
d) film.
6. In what way is Strand's Church photograph from 1944 a formalist image?
7. What two events precipitated Weston's break with Pictorialism?
8. Weston wrote, "the camera should be used for a recording of life, for rendering the very substance and quintessence of the thing itself, whether it be polished steel or palpitating flesh."
a) What does this mean?
b) What evidence can you find in Weston's work to suggest he was successful in this endeavour?
9. Weston has written that photography should be "direct, honest, uncompromising". What technical tricks did he believe should be avoided by a good photographer?
10. In what way were Friedlander's Guggenheim Fellowships of 1960 and 1962 indicative of his tendency towards imitationalist aesthetics?
11. a) In what way is Lee Friedlander's Factory Valleys No. 13, 1980 a documentary?
b) How does Factory Valleys No. 13 support a formalist aesthetic?
12. In what way is Lange's work imitationalist?
13. How did Lange earn her living as a photographer?
14. What message is conveyed in Lange's Migrant Mother, 1936?
15. According to Newman, "The portrait is a form of biography." It documents a history that is subject to the interpretation of the photographer. How is this interpretation evident in the following portraits:
a) President Lyndon B. Johnson, 1963;
b) Willie (The Lion) Smith, 1960;
c) Woody Allen, 1996.
16. There are a number of different processes that a photographer might follow to take pictures of people. In what ways does the process followed by Arnold Newman differ from that of Dorthea Lange?
17. How has Gary Winogrand's choice of equipment affected his photographic imagery?
18. What aspects of Winogrand's studies have contributed to his creative ability?
19. Winogrand's images are narratives — they tell a story. In your own words, explain the narrative from any one of the Winogrand images presented.


{% extends 'layouts/layout.html' %} {% block pageTitle %} Example - passing data from page to page {% endblock %} {% block content %}
You may want to use or display data a user has entered over a few screens.
The prototype kit includes a simple way of saving data entered in forms, as well as displaying the saved data.


I am a data science professional excited about solving real business problems to enhance business operations and meet customer needs. With my knowledge of machine learning tools, techniques and models, I tackle a wide-range of business problems in the finance, commerce and manufacturing industries. I am skilled in using Python, SQL and Tableau for predictive modelling, data mining and analytics and data visualisation. I am detail-oriented, methodical and enterprising with a passion for getting the job done and right.
Analyzing structured/unstructured data with small and large datasets
From requirements gathering to creating industry standard software products
Beautiful and compelling graphics to enable data-driven decision making
Quality solutions that are efficient and maximize resources


Same of them |
this is clear website where you find the excelent schools
do you want to become an excellent,needed one and some one who can change your world? we have all levels nursary, primary, secondry,university, masters, and all lever above this. so if you want to become excellent ones neede by every one and every company and your children to become so intelligent ones please this is your solution so register now there is no complex recquirement it is just to fill the following link.open the following link and apply now. |
|
Visit elearnung.rw! |


You may provide DragSpringOptions via dropOptions.provideSpringOptions to receive DragSpringEnter after some delay (2 seconds in this example).


I'd love a feature to select and move multiple items at once in the emblem editor. Other features like resizing or changing angle would be great, too :P
Thanks!
seniledawdler
Helping Hand
You can already change angle and scale.
Although it would be great if you could select regarding which point it scales or rotates instead of the center.
Topicstarter
thetimmaeh
I know this features exist. All requested features referring to selcting & editing multiple layers.
seniledawdler
Helping Hand
Wasn't clear to me when I read it. But yes that would be helpful also. Many times you want to either resize or move the whole emblem. :)


Presentation by TheodorosPloumis / @theoploumis
Date 13 May 2015, Ansible Version 1.9.1
Image by devopsreactions
// Can also use apt, yum, brew, compile from source etc
// We are installing version 1.9.1
$ sudo easy_install pip
$ sudo pip install ansible==1.9.1
Image by sysadmincasts.com
Find more in the Ansible Docs.
Execute a quick command to a machine using /usr/bin/ansible.
$ ansible localhost -m setup -i hosts
$ ansible localhost -m service -a "name=apache2 state=started" -i hosts
File (INI format) that describes Hosts and Groups
[webservers]
<IP_ADDRESS>
aserver.example.org
bserver.example.org
[dbservers]
localhost
Used with {{ variable }} replacement.
---
project_name: myproject
project_root: /var/projects/myproject
project_repo: git@bitbucket.org:myuser/myproject.git
system_packages:
- build-essential
- git
- nginx
- postgresql
- redis-server
- postfix
The "mini tools" of Ansible!
This is where you love Ansible!
---
- hosts: webservers
sudo: yes
tasks:
- name: install nginx
apt: name=nginx state=installed update_cache=yes
- name: write our nginx.conf
template: src=tpl/nginx.conf.j2 dest=/etc/nginx/nginx.conf
notify: restart nginx
- name: start nginx proccess
service: name=nginx state=started
$ ansible-doc
$ ansible-vault encrypt foo.yml
- name: add several users
user: name={{ item }} state=present groups=wheel
with_items:
- testuser1
- testuser2
# Example that prints the loopback address and gateway for each host
- debug: msg="System {{ inventory_hostname }} has uuid {{ ansible_product_uuid }}"
- debug: msg="System {{ inventory_hostname }} has gateway {{ ansible_default_ipv4.gateway }}"
when: ansible_default_ipv4.gateway is defined
- shell: /usr/bin/uptime
register: result
- debug: var=result
- name: Display all variables/facts known for a host
debug: var=hostvars[inventory_hostname]
| Tool | Ansible | Puppet | Chef | Salt |
|---|---|---|---|---|
| Release | 2009 | 2005 | 2009 | 2011 |
| Lang. | Python | Ruby | Ruby | Python |
| Agentless | Yes! | No | No | Both |
Data from Wikipedia
Order of this list is important...


You’ll be able to personalize it by adding content, changing layout & customizing appearance.
Feel free to take a look around. When you’re ready, click "Dashboard" on the navigation bar at the top of your screen to get started!


HTML
People
HTML
Name
The dream list
Category
fantasy novel
Complited
0%
Take a look
The dream list
Home
News
Images
Uploads
Favorites
Messages
Security


Welcome to wpXtreme Pages.
wpXtreme is a powerful tool to enhance your Wordpress experience. Just by downloading one free plugin you will get a lot of improvements to the WordPress core and you will gain access to the WPX Store, the first app store for WordPress.
ENHANCE WORDPRESS
wpXtreme dramatically improves the WordPress core adding awesome features and useful tools; wpXtreme will be free forever.
THE FIRST WORDPRESS APP STORE
With our plugin, you will be able to access the WPX Store, where you can buy and sell professional grade WordPress plugins with just a few clicks.
WE LOVE YOUR SECURITY
We think your security is very important. Our plugin add checks and features to highly improve your WordPress security.
NEW STUFF COMING
Our team is working hard to deliver new features and plugins, the only thing you will have to check is your dashboard.
Codetip of week
This week let me show how to check the type of variable.
// You can get the type of variable in this way
$type = gettype( $foo );
// Then you check if it is an array
if( 'array' == $type ) { /* todos */ }
// However, in that way, you force a string compare and the 'array' string could be change in next future
// So, look the right way
if( is_array( $foo ) ) { /* todos */ };


All Abroad is a web application for students who are planning to or are already studying abroad. This is all-in-one kind of application which includes various features which seem to be important to abroad students. Weather, Translator, and Chat features are all part of All Abroad aimed to help abroad life. The Chat feature allows nearby abroad students to connect with each other.


FirefoxDriver.Commands.WebDriver.Window Class
Window related WebDriver endpoints see JsonWireProtocol
Item Index
Methods
acceptDialog
-
sessionId
Accepts the currently displayed alert dialog. Usually, this is equivalent to clicking on the 'OK' button in the dialog.
Parameters:
-
sessionId
GETID of the session to route the command to
alertText
-
sessionId
-
text
Sends keystrokes to a JavaScript prompt() dialog.
Parameters:
-
sessionId
GETID of the session to route the command to
-
text
POSTKeystrokes to send to the prompt() dialog.
changeWindow
-
sessionId
-
name
Change focus to another window. The window to change focus to may be specified by its server assigned window handle, or by the value of its name attribute.
Parameters:
-
sessionId
GETID of the session to route the command to
-
name
POSTName of the window to switch to
closeWindow
-
sessionId
Close the current window.
Parameters:
-
sessionId
GETID of the session to route the command to
dialogText
-
sessionId
Gets the text of the currently displayed JavaScript alert(), confirm(), or prompt() dialog.
Parameters:
-
sessionId
GETID of the session to route the command to
dismissDialog
-
sessionId
Dismisses the currently displayed alert dialog. For confirm() and prompt() dialogs, this is equivalent to clicking the 'Cancel' button. For alert() dialogs, this is equivalent to clicking the 'OK' button.
Parameters:
-
sessionId
GETID of the session to route the command to
getOrientation
-
sessionId
Get the current browser orientation. The server should return a valid orientation value {LANDSCAPE|PORTRAIT}.
Parameters:
-
sessionId
GETID of the session to route the command to
getWindowPosition
-
sessionId
-
windowHandle
Get the position of the specified window. If the :windowHandle URL parameter is "current", the position of the currently active window will be returned.
Parameters:
-
sessionId
GETID of the session to route the command to
-
windowHandle
GETID of the window to route the command to
getWindowSize
-
sessionId
-
windowHandle
Get the size of the specified window. If the :windowHandle URL parameter is "current", the size of the currently active window will be returned.
Parameters:
-
sessionId
GETID of the session to route the command to
-
windowHandle
GETID of the window to route the command to
orientation
-
sessionId
-
orientation
Set the browser orientation. Must be one of the two values {LANDSCAPE|PORTRAIT}.
Parameters:
-
sessionId
GETID of the session to route the command to
-
orientation
POSTThe new browser orientation {LANDSCAPE|PORTRAIT}.
windowHandle
-
sessionId
Retrieve the current window handle.
Parameters:
-
sessionId
GETID of the session to route the command to
windowHandles
-
sessionId
Retrieve the list of all window handles available to the session.
Parameters:
-
sessionId
GETID of the session to route the command to
windowMaximize
-
sessionId
-
windowHandle
Maximize the specified window if not already maximized. If the :windowHandle URL parameter is "current", the currently active window will be maximized.
Parameters:
-
sessionId
GETID of the session to route the command to
-
windowHandle
GETID of the window to route the command to
windowPosition
-
sessionId
-
windowHandle
Change the position of the specified window. If the :windowHandle URL parameter is "current", the currently active window will be moved.
Parameters:
-
sessionId
GETID of the session to route the command to
-
windowHandle
GETID of the window to route the command to
windowSize
-
sessionId
-
windowHandle
Change the size of the specified window. If the :windowHandle URL parameter is "current", the currently active window will be resized.
Parameters:
-
sessionId
GETID of the session to route the command to
-
windowHandle
GETID of the window to route the command to


Full vacation control from your cell phone.
Up to 50% offers. Always 25% student offers.
Wherever you travel our car rental is included.
Don't wait until it is to late.


This may take a while to run, be patient and it'll finish eventually..
Tests and benchmarks different types of javascript inheritance schemes.


I made my mindfulness connversation with my wife, which is fortunate because she is a great conversationalist and an even better listener. She is also happy to try alternative approaches in communication.
I learned that I am actually quite a mindful conversationalist and listener anyway, and so is my wife. I was alway taught that it was impolite to talk all of the time and more importantly, to truly listen to the other person when they are speaking, and to truly hear what they have to say.
I learned that I am actually quite a mindful conversationalist and listener anyway, and so is my The chapter confirm the importance of good manners in discourse.
My wife was extremely open to the idea of trying the exercise in order to see how we conducted our normal everyday conversations with each other, against this benchmark.
She found it easy, but then again she is a calm person who meditates often.
Her opinion of the exercise was that it is a civilised form of allowing discouse; typically for us.
Perhaps I should try this exercise with a highly stressed person instead?
Having a buddy?
This was a simple choice to make for me. My wife, Judith, is always happy to share with me and me with her. The daily mindfulness will sit nicely with our daily prayer and dialy exercise regimes.


| ID | Formula | FW | DSSTox_CID | DSSTox_RID | DSSTox_GSID | DSSTox_FileID_Sort | TS_ChemName | TS_ChemName_Synonyms | TS_CASRN | CASRN_ChemName_Relationship | TS_Description | ChemNote | STRUCTURE_Shown | STRUCTURE_Formula | STRUCTURE_MW | STRUCTURE_ChemType | STRUCTURE_DefinedOrganicForm | STRUCTURE_IUPAC | STRUCTURE_SMILES | STRUCTURE_SMILES_Desalt | Substance_modify_yyyymmdd | |
| 117947-85-0 | 13551 | C7H16BF4N | 201.0133 (114.2081+86.8052) | 28477 | 83281 | 49206 | 7956 | 1-Ethyl-1-methylpyrrolidinium tetrafluoroborate | 117947-85-0 | primary | mixture or formulation | CAS for main component; mixture with piperidine [110-89-4] | representative component | C7H16BF4N | 201.0133 | defined organic | complex | 1-ethyl-1-methylpyrrolidinium tetrafluoroborate | F[B-](F)(F)F.C[N+]1(CC)CCCC1 | C[N+]1(CC)CCCC1 | 20111204 |