Reading Assignment A (core)
Overview
After reading this assignment description, read the 355 pages numbered 32 through 386 of N3485. This includes clauses 3 (Basic Concepts) through to 15 (Exception handling) inclusive.
After this assignment you will have a complete exhaustive knowledge of the C++ core language, not including the standard library. Such knowledge will be assumed for the remainder of the course.
Prerequisities
You should complete Programming Assignment 6 before starting this assignment. PA6 is necessary to get you used to the mapping between nonterminal names, such as a class-specifier
, and code examples of these nonterminals, such as struct { ... }
. You will need to know this mapping for efficient comprehension of the text.
Discussion
We are getting into the hardest part of the course. One of the most useful things about C++, compared to other modern industrial languages, is how much the compiler can do during static analysis (aka at compile-time, during translation), however implementing all these features is quite difficult.
In the next programming assignments you will be implementing a large part of the semantic analysis phase (translation phases 7 and 8), including but not limited to symbol table management, name lookup, template instantiation, evaluation of constant expressions, overload resolution, and so on. This also necessitates building up the foundation type system handling, including complex compound types such as user-defined classes, including inheritance.
It will be necessary to have complete knowledge of all the C++ language features (not including the standard library) in order to proceed.
If you already possess an expert knowledge of C++ than you may be able to get away with making a single pass of the assigned 355 pages. For everyone else, you will undoubtably need to make two passes.
In either case we suggest making only forward passes of the documentation. That is, do not jump around looking for definitions as you read. If there is terminology you do not understand on your first pass, leave it or make a note about it, and press on. You should be able to tie up forward references on your second pass.
If there is a requirement in N3485 that you do not understand please post to forum.cppgm.org with tag raa
. Make sure to include the section number and quote the text you are unsure about.
As you are reading try to imagine the different ways in which each requirement could be implemented in a C++ compiler. If you can't do this in all cases it is ok, but make sure you at least understand the required behaviour of the compiler, even if you are not sure how to implement that behaviour yet.
Architecture
It's important to have an overview of the translation process before you start reading the assigned material. The C++ spec is designed so that a C++ compiler can almost(*) make a single forward parse of a translation unit. As it parses entities are declared and defined. The C++ compiler acts on these declarations and definitions to add them to an "internal database", which you will represent in memory using normal object-oriented techniques. As you encounter usages of these entities during parsing you will look them up in this partially completed database to resolve relationships, and then record those relationships. The important thing to understand is that (in general) at entity use, a needed declaration or definition is required to be above the use in the translation unit - this is specifically to support this single pass architecture.
Side Note: (*) We say "almost" because there is an exception to do with certain definitions within a class specifier - specifically inline function bodies, default parameters and initializers. So that they can forward reference class members and use their enclosing class as a complete type, these items must be delimited and then defered to be parsed after the class specifier has completed, just like they were defined after the class specifier in the translation unit - but you will delve deeper into this in the appropriate assignment.
Reading Schedule
We've delimited the material for you into 9 blocks of approximately 40 pages each. For a single pass if you schedule 2 hours per day to read one block, than this will take 9 days and a total of 18 hours. If you need to make 2 passes it will take double that of course.
Block 1: 51 pages
3 Basic Concepts
4 Standard Conversions
Block 2: 50 pages
5 Expressions
6 Statements
Block 3: 39 pages
7 Declarations
Block 4: 32 pages
8 Declarators
Block 5: 38 pages
9 Classes
10 Derived Classes
11 Member Access Control
Block 6: 31 pages
12 Special Member Functions
Block 7: 30 pages
13 Overloading
Block 8: 42 pages
14.0..14.6 Templates Part I
Block 9: 42 pages
14.7..14.8 Templates Part II
15 Exceptions
After completing this assignment you do not have to do anything, you are expected to complete it before commencing Programming Assignment 7. RAA is self-assesed and will be due on the same day as PA7.


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author_profile: true
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Here are some of the projects I have worked on and places you can find my photos
{% for post in site.portfolio %}
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Leucate is known for its huge beach and its excellent oysters. This port is located about 45nm north of the Spanish border.
Position 42° 52'28"N, 03° 03'15"E (harbour entrance)
The visitors' berths are well inside the port, in Bassin Central, which is to port approximately halfway down the Anse de Correge. Beware that the depths at the entrance might be shallower than indicated.
Last updated March 2015.


You can guess it from the title : this new release is all about HTTP Caching! HTTP Caching is a fundamental part of any web framework and was obviously a required step before Spincast 1.0.0.
Many frameworks only manage a very little part of the HTTP specification
regarding caching. In general, they limit their support to GET
requests by returning a 304 - Not Modified
response
instead of the requested resource if this resource hasn't changed, and they validate this by hashing the generated resource and setting the result
as an ETag
header. This is useful in some cases, but is in fact very limited... HTTP caching is way more sophisticated than this!
At the core of HTTP Caching management using Spincast, there is a new
request context add-on : "httpHeaders()"
. This add-on helps to create very compliant REST
endpoints.
Most of the "freshness" headers are managed : If-Match
, If-None-Match
,
If-Modified-Since
and If-Unmodified-Since
. In the other direction, the add-on helps to send
Cache-Control
, ETag
and Last-Modified
headers. It is also possible to send
"no cache" headers to tell a client that it should never cache the resource, at all. Some of those cache headers
can also be specified on the routes
, directly.
Finally, a Cache Busting
mechanism has been added. By adding a special code to the URL of a resource, you
can easily invalidate the cached versions clients may have of it. Read more about it
here.


binomdist.Rmd
The binomial distribution is the key to exact inference about a proportion. The purpose of this vignette is to explain the binomial distribution and provide some examples of practical uses for this distribution. This will pave the way for later learning about how the binomial distribution can be used for exact inference, including both hypothesis testing and confidence interval construction.
The nplearn package is required for this vignette. All other functions used are in the base package.
Multiple independent events that occur are referred to as joint events. The total number of possible joint outcomes of a joint event is the product of the number of potential outcomes of each separate event. For example, on a five-item multiple choice quiz, where each question has four options, the number of possible patterns of responses is the product of five fours.
4*4*4*4*4
#> [1] 1024
We can write this as an exponent.
4^5
#> [1] 1024
We know from the laws of probability that if each event is independent, the probability of a specific set of joint events is equal to the product of the probability of the individual events. In our multiple-choice quiz example, here is the probability of a test taker getting a perfect score just by guessing.
(1/4)*(1/4)*(1/4)*(1/4)*(1/4)
#> [1] 0.0009765625
Here it is written another way.
(1/4)^5
#> [1] 0.0009765625
Here it is written yet another way.
0.25^5
#> [1] 0.0009765625
Suppose we have a series of Bernoulli events. For example, suppose that we again administer a five-question quiz, but this time the items are true-false. This is a series of Bernoulli events because there are only two possible outcomes for each event. Here is the probability of getting a perfect score just by guessing.
0.5^5
#> [1] 0.03125
A more sophisticated test taker will actually have studied for the test, so this test taker will not just be guessing. We could think of the probability of success on an item as a function of this person’s knowledge after learning the content. Here is the probability of a perfect score if the probability of success on each item is 0.7.
0.7^5
#> [1] 0.16807
Let’s see what the chance of a perfect score is for someone who is very well prepared so that the success rate for each item is 0.95.
0.95^5
#> [1] 0.7737809
Of course all of this is making the unrealistic assumption that the rate of success is the same for every item. In fact, so items are more difficult than others, so the actual probability of a perfect score might be something more like this.
0.8*0.95*0.75*0.95*0.70
#> [1] 0.37905
This kind of test-taking discussion with different item difficulties is best left for a measurement course, such as item response theory. We will step out of the test-taking domain in a bit, but for now let’s proceed with this example and the (unrealistic) assumption that each item has the same difficulty level.
Suppose I’m not just interested in a perfect score, but I’m also interested in questions like, what is the chance of obtaining four out of five correct on this true-false quiz if the probability of success for each item is 0.7? This is a bit tricky, because we don’t know which item the person will get wrong. Here is the probability of getting just the first item wrong.
0.3*0.7*0.7*0.7*0.7
#> [1] 0.07203
Here it is written another way.
0.7^4 * 0.3^1
#> [1] 0.07203
What about the probability of getting just the second item wrong?
0.7*0.3*0.7*0.7*0.7
#> [1] 0.07203
The probability is the same! In fact, we could still write it this way.
0.7^4 * 0.3^1
#> [1] 0.07203
It is pretty easy to figure out that there are five possible ways for the test taker to get just one item wrong on a five-item test: The first one could be wrong, the second item could be wrong, and so on. Thus, the total probability of getting any one item wrong is calculated this way.
5 * 0.7^4 * 0.3^1
#> [1] 0.36015
That was straightforward, but it becomes more difficult with different numbers of items correct and different numbers of items. For example, how many different patterns will there be for three items correct and two items incorrect? What about if there are 10 items instead of five? How many patterns will there be for four items correct and six incorrect? Clearly these questions are not as easy to answer. What we need are some counting rules. Many nonparametric statistics are based on working with discrete values, so we often need to count. Methods of counting for various situations are an important component of nonparametric analysis.
The first counting rule is about permutations. A permutation of objects is a distinct ordering of objects. We can calculate the number of permutations of N objects with a product known as a factorial. For example, for five objects we use 5! (read as, five factorial).
5 * 4 * 3 * 2 * 1
#> [1] 120
R includes a factorial function.
factorial(5)
#> [1] 120
A side note: What do we do with 0!? By definition, 0! = 1.
factorial(0)
#> [1] 1
In our true-false quiz example we had five questions, so the number of possible permutations of the answers is 5! = 120. Yet if we want to know how many ways there are to get two incorrect answers out of the five questions, we really only care about two incorrect and three correct answers, regardless of where they occur. That is, we consider all incorrect answers as indisitinguishable from one another. There are only two distinct type of answers here: correct and incorrect. The permutation of wrong, wrong, right, right, right does not need to be considered different than the permutation of wrong, right, right, right, wrong.
To calculate how many permutations there are when we include identical “objects” (we consider every “right” and every “wrong” as identical) we need to divide the total number of permutations by the number of permutations of each identical object. Here’s the calculation for five true-false items when three are correct and two are incorrect.
This can be extended to any number of identical objects. The case where we have only two identical objects is all we will need when looking at a series of Bernoulli events, because by definition a Bernoulli event only has one of two outcomes. Given this case is so special, there is a special expression for it, as well as a special function for it. When we want to know how many ways we can get three items correct out of five Bernoulli trials, we say five choose three. Here is how we represent it.
\(\binom{5}{3}\)
Here’s the R function.
choose(5, 3)
#> [1] 10
This function is referred to as the binomial coefficient. In general, we represent the number of ways that we can have \(x\) successes in \(n\) trials like this, which we read as n choose x.
\(\binom{n}{x}\)
It would seem quite difficult to figure how many different ways there are to obtain 13 correct answers on a 20-item true-false quiz, but the binomial coefficient function makes it easy.
choose(20,13)
#> [1] 77520
If we combine the concepts of joint events with the binomial coefficient, we can answer an interesting question. When we observe \(n\) independent Bernoulli events, each with the same probability of success, \(\pi\), what is the probability that \(x\) of these events will be a success? If that doesn’t really sound very interesting to you, consider a few examples.
If the chance of contracting an illness is 40% when coming into contact with another person with the illness, what is the probability that all six people who came into contact with an ill person will avoid aquiring the illness themself?
Suppose that there is an expensive treatment for the above illness and that medical professionals purchased enough drugs to treat two patients in anticipation that two of the six people will contract the illness. What is the probability that exactly two of the six people will indeed contract the illness?
If the overall pass rate on an entrance exam is 70%, what is the probability that we will be able to fill eight slots with successful examinees if there are 11 applicants for the position?
As we will see in the next vignette, knowing the probability of \(x\) successes in \(n\) trials can also be used to conduct hypotheses tests and construct confidence intervals for a proportion, so the value of being able to calculate probabilities based on \(n\) Bernoulli events goes beyond answering questions like those above.
Recall that we calculate the probability of independent joint events by taking the product of the probability of each event. When there is a 70% chance of passing an item on a five-item quiz, we calculate the probability of getting the first three items correct but missing the two remaining items like this.
0.7^3 * 0.3^2
#> [1] 0.03087
In more general terms, the chance of getting the first \(x\) items correct but missing the remaining items on an \(n\)-item quiz when the probability of success is \(pi\) is calculated like this.
\(\pi^x (1-\pi)^{(n-x)}\)
That is, we multiply the probability of the \(x\) successes by the probability of the \(n-x\) failures.
I can’t think of a reason why I would want to know the chance of getting the first three items correct and missing the last two, but I can think of why I might want to know the probability of missing any two, not just the last two. That is where the binomial coefficient comes in handy. The binomial coefficient tells us how many ways we can arrange \(x\) successes in \(n\) trials. Here is how many ways we can have exactly three items correct on a five-item quiz.
choose(5, 3)
#> [1] 10
If I multiply the probability of one specific sequence of three correct and two wrong with the number of ways I can have three correct and two wrong, that will give me the probability of obtaining any three correct on a five-item quiz.
choose(5, 3) * 0.7^3 * 0.3^2
#> [1] 0.3087
We can right this in general terms like this.
\(P(X = x) = \binom{n}{x}\pi^x (1-\pi)^{(n-x)}\)
This is the binomial probability function. It tells us the probability of \(x\) successes in \(n\) Bernoulli events when the probability of success is \(\pi\) for each Bernoulli event. Note that whereas the values of \(x\) are either 0 or 1 for a Bernoulli event, the values of \(x\) for the binomial function will range from 0 to \(n\). That is, you can have 0 success, 1 success, 2 successes, and so on, all the way up to \(n\) successes.
Let’s now answer the first two of our three questions.
If the chance of contracting an illness is 40% when coming into contact with another person with the illness, what is the probability that all six people who came into contact with an ill person will avoid aquiring the illness themself?
Here’s the formula that will provide the solution.
\(P(X = 0) = \binom{6}{0}0.4^0 (1-0.4)^{(6-0)}\)
Here it is calculated in R.
choose(6, 0)*0.4^0*(1-0.4)^(6-0)
#> [1] 0.046656
It looks like there is a very high chance that someone will get sick! The second question is about the anticipation that this will be two people.
Suppose that there is an expensive treatment for the above illness and that medical professionals purchased enough drugs to treat two patients in anticipation that two of the six people will contract the illness. What is the probability that exactly two of the six people will indeed contract the illness?
Here’s the formula that will provide the solution.
\(P(X = 2) = \binom{6}{2}0.4^2 (1-0.4)^{(6-2)}\)
Here it is calculated in R.
choose(6, 2)*0.4^2*(1-0.4)^(6-2)
#> [1] 0.31104
So there is about a one in three chance that the medical staff purchased exactly the correct amount of drugs. It is probably more reasonable to believe that the medical staff wants to make sure they have enough drugs, but it would be OK to have some left over. This leads us to the most common use of the binomial probability function, which is the creation of the binomial distribution.
Rather than calculating the probability that zero or two people will get sick when they come in contact with a particular bacteria or virus, wouldn’t it make sense to know the probability for every possible outcome? Yes! That is what we do to create the binomial distribution. Here are all the probabilities.
n <- 6
x <- 0:n
pi <- 0.4
prob.x <- choose(n, x)*pi^x*(1-pi)^(n-x)
cbind(x,prob.x)
#> x prob.x
#> [1,] 0 0.046656
#> [2,] 1 0.186624
#> [3,] 2 0.311040
#> [4,] 3 0.276480
#> [5,] 4 0.138240
#> [6,] 5 0.036864
#> [7,] 6 0.004096
Given that we calculated the probability for every possible outcome, these better add to one!
sum(prob.x)
#> [1] 1
They do! Here’s a picture of the binomial distribution. Note that it relates every possible value of \(x\) to the probability of observing \(x\) in \(n\) trials, so this is a probability function.
binom_plot(6, 0.4)
If we want to determine the probability that we have enough drugs for up to two people who may get sick (rather than exactly two people), we can find the cumulative probability up to and including two.
There’s a little better than a one in two chance that two doses will be enough. (If this is a serious disease, I would want a higher probability that I’m going to be able to treat everyone!)
You may have guessed by now that we don’t really need to write R code to make these calculations because someone has already done it for us. You would be correct. The binomial distribution is a common distribution, so we have the d, p, q, and r distribution functions at our disposal. Yay!
Here’s the probability that exactly two out of six people will contract the sickness.
dbinom(x = 2, size = 6, prob = 0.4)
#> [1] 0.31104
Here’s the probability that two or less persons out of six people will contract the sickness.
pbinom(2, 6, 0.4)
#> [1] 0.54432
Suppose we want to be at least 80% certain that we have enough treatments. How many should we get?
qbinom(0.8, 6, 0.4)
#> [1] 3
We need three treatments. Remember that this is a discrete distribution, so it would be unusual to have the cumulative probability up to, and including, three be exactly 80%. Let’s see what it is.
pbinom(3, 6, 0.4)
#> [1] 0.8208
It is 82%. Remember the rule for quantiles of a discrete distribution. We are seeking the smallest value of \(x\) on the distribution such that the cumulative probability to, and including, \(x\) is at least the specified probability. That’s what we got here, and we were able to use this rule to our advantage by being at least 80% sure that we have enough treatments.
Let’s consider the final question posed above.
If the overall pass rate on an entrance exam is 70%, what is the probability that we will be able to fill eight slots with successful examinees if there are 11 applicants for the position?
If we have eight or more successful examinees, we will be able to fill the eight slots. We could do this one of two ways. We could calculate the probability of seven or fewer successes and then subtract this from one.
1 - pbinom(7, 11, 0.7)
#> [1] 0.5695623
Alternatively, we could calculate the upper tail.
pbinom(7, 11, 0.7, lower.tail = FALSE)
#> [1] 0.5695623
The important trick to remember here is that if we want an upper tail that includes a specified value (in this case, the value of eight), we need to subtract one from this value to make sure it is included in the upper region of the distribution.
Finally, suppose we wanted to do a simulation using the binomial distribution. Here are 20 random draws from a distribution with \(\pi\) = 0.8 when the sample size is 15.
rbinom(20, 15, 0.8)
#> [1] 11 12 12 13 13 12 14 11 10 14 11 15 12 12 11 13 13 12 11 15
Keep in mind that what each number we are randomly generating is the value of \(x\), which is the number of successes in \(n\) trials. In this example there are 15 opportunities for success. The probability of success is quite high, so we are primarily seeing high numbers of successes out of the 15 trials.
In this example, we were drawing from a binomial distribution with \(n\) trials and a probability of success, \(\pi\). These are the parameters of the binomial distribution. Any binomial distribution can be generated if we know these two parameters. Let’s end with a picture of a binomial distribution when \(n\) = 100 and \(\pi\) = 0.5.
binom_plot(100, 0.5)
That looks like a normal distribution, doesn’t it? That is why we can use the normal distribution for a large-sample approximation and it works pretty well. Yet the above distribution is not normal. For one thing, it is a discrete distribution, rather than continuous. So why bother to use a continuous distribution to approximate results when we can use the actual distribution? I have no idea! In the next vignette, let’s make inferences using the actual distribution, thus calculating exact probabilities rather than approximations.


Anzhi Li
Welcome to my webpage! I am a Master's student in Statistics and Applied Economics at the University of Georgia. Also, I work as a statistical consultant at the Statistical Consulting Center and research assistant at the Department of Agricultural and Applied Economics at the University of Georgia. My research focuses on quantitative and qualitative forecasting of agricultural commodity prices using Bayesian analysis.
Anzhi Li
PDF Resume
EDUCATION
- M.S. in Statistics, The University of Georgia, 2015
- M.S. in Agricultural and Applied Economics, The University of Georgia, 2015
- B.A. in International Economics and Trade, Shanghai Finance University, 2012
RELEVANT EXPERIENCE
- The Statistical Consulting Center, The University of Georgia
- June 2014-Present | Athens, GA
- Graduate Research Assistant
- The Department of Agricultural and Applied Economics, The University of Georgia
- August 2012-Present | Athens, GA
PRESENTATIONS
- “Composite Qualitative Forecasting of Futures Prices: Using One Commodity to Help Forecast Another” Agricultural Applied Economics Association’s 2014 AAEA Annual Meeting, Minneapolis, MN, July 27-29, 2014.
- “Forecasting of Futures Prices: Can Forecasts of One Commodity Help Forecast Another?” NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management, St. Louis, MO, April 21-22, 2014.
CERTIFICATIONS
- SAS Certified Advanced Programmer for SAS 9
- SAS Certified Base Programmer for SAS 9
- SOA Exam 1/P (Probability)
SKILLS
- Programming Languages and Software: SAS, R, Python, STATA, SPSS, WinBUGS, JMP, SQL, VBA, LATEX, MS Office Suite
- Statistical Skills: Bayesian Statistics, Time Series Analysis (Forecasting), Generalized Linear Model, ANOVA, Nonlinear Regression, Causal Inference, Panel Data, Survival Analysis
Anzhi Li
THESIS
- Composite Forecasting of Futures Prices: Using One Commodity to Help Forecast Another
- Composite Qualitative Forecasting of Futures Prices: Using One Commodity to Help Forecast Another
Anzhi Li


The best Black Friday phone deals for 2019 in the UK
by Alex HughesThe best Black Friday phone deals for 2019 in the UK
How to find the perfect phone contract this Black Friday
(Image credit: Future) Jump To:
- Top ten Black Friday deals available now:
- Samsung Galaxy Note 10, S10, S10e and S10 Plus deals
- iPhone 11, XR and XS deals
- Huawei P30 and P30 Pro deals
- Google Pixel 4 and 4 XL deals
- Black Friday SIM only deals
- Mobile phone deals with free gifts
- Black Friday cheap iPhone deals:
- SIM-free phones
- Best of the rest
- Black Friday phone deals: FAQ
We've now officially burst into the week of Black Friday and where a few years ago, that would have meant more waiting until the deals are released on Friday, that now means the excellent offers have already begun!
For the past few weeks we've already seen a mass amount of offers come in, smashing those flagship prices way down, not a surprise considering it's the best time of the year to upgrade your phone contract! And if you've been holding out on getting a new handset so you can score a saving in the event, you're in the right place. We've got all of the Black Friday phone deals information you need to know.
Apple fan trying to get the best Black Friday iPhone deals? An Android devotee scoping out prices on the shiny Samsung Galaxy Note 10? Or even just a budget hunter looking for a bargain Black Friday phone deal? No matter what you need, this will be the time to look.
But where will the best phone deals be over Black Friday? Although its too early to know for sure this year, we can take a pretty good guess based on previous years gone by.
For those looking to score a phone contract, the likes of Carphone Warehouse, Mobiles.co.uk, Fonehouse and Mobile Phones Direct all brought their A game back in last year's Black Friday and we can't see it being any different.
Rather go for a SIM-free phone? Like all years gone by, the likes of Amazon, Argos, John Lewis and Very will be the places to go for SIM-free Black Friday phone deals. And if you need a SIM only deal to pair with your new phone, well we can't help but feel that Three and iD Mobile will pull out something special.
Take a look below to see what you can expect in terms of Black Friday phone deals when the event rolls around on November 29.
Top ten Black Friday deals available now:
Black Friday is now just one week away and the deals have already started flooding in. In the lead-up to the big event we tend to see a load of top-notch deals across a range of phones - these are the best so far:
Samsung Galaxy Note 10, S10, S10e and S10 Plus deals
iPhone 11, XR and XS deals
Huawei P30 and P30 Pro deals
Google Pixel 4 and 4 XL deals
Black Friday SIM only deals
Mobile phone deals with free gifts
Black Friday cheap iPhone deals:
SIM-free phones
Best of the rest
Black Friday phone deals: FAQ
The key retailers for Black Friday Phone deals:
These were the retailers that we saw all of the best Black Friday phone deals come from last year. From cheap SIM-free phones to the best iPhone deals we saw last year, each of these retailers came out with something worth going for. This year is likely to be exactly the same.
While no Black Friday offers are available yet, there are also some great offers in the build up. Head on over to these sights to see what is currently available.
Contracts:
- Carphone Warehouse
- Mobiles.co.uk
- Fonehouse
- Three Mobile
- Mobile Phones Direct
- e2save
- Sky Mobile
- iD Mobile
SIM-free:
- Amazon
- Argos
- Very
- John Lewis
The best Black Friday phone deals from last year:
A whole year on and looking back at the prices from last year gives us hope for some incredible offers this year. Judging from the contracts available in 2018, the flagship devices will be the ones to go for. Last year that meant the likes of the Samsung Galaxy S9, iPhone XS and OnePlus 6T. This year look out for offers on the Samsung Galaxy S10, Google Pixel 4 and iPhone 11 series.
Below we've listed the best offers we saw back in 2018 to give you a flavour for what to expect.
EXCLUSIVE Samsung Galaxy S9 at Mobiles.co.uk | EE | £199 £150 upfront with TECH49 code | Unlimited minutes and texts | 4GB data | £19 per month
During Black Friday last year, the S9 was selling like crazy. We were seeing offers left, right, centre - pretty much every angle really. But out of all of the offers we saw, this was our personal favourite. Although we know we're unlikely to see a S10 deal this cheap, we can't help but hope for something along this line in 2019.
iPhone XR from Mobiles.co.uk | Vodafone | £50 upfront | 100GB data | Unlimited minutes and texts | £36pm
The iPhone XR hadn't even been out that long when Black Friday rolled around and yet they were able to pull out this stunner! This is a price that would even be impressive right now an entire year on from the iPhone XRs launch. This year we're hoping to see an iPhone XR drop below £30 a month.
AYCE SIM only plan from Three | 12 months | All-you-can-eat data | Unlimited calls and texts | £27 £20pm
When Three dropped this offer over Black Friday we were beyond impressed. They then brought it back a few months later and have continued to run with it. It remains to this day one of the best SIM only deals we've ever seen but will Three be able to top it this year? We really hope so.
EXCLUSIVE 4GB SIM on iD/Carphone Warehouse | Unlimited calls and texts | £9 per month
Unlike the Three offer above, some people just want the cheapest SIMO they can get. This iD deal was exclusive to TechRadar readers and offered up 4GB of data for £9 a month. If we're lucky, iD Mobile will go big on cheap SIM only deals this year.
iPhone XS from Fonehouse | Vodafone | £149 upfront | 100GB data | Unlimited minutes and texts | £36pm
This might look like an expensive offer but for the iPhone XS, its pretty mind-blowing. Fonehouse were able to offer 100GB of data on what was one of the world's most expensive phones, while still keeping bills down to £36. This year, we're hoping to see this price drop even more.
Moto G6 | £199.95 Now £179.95 at Argos
This was easily one of the best Black Friday phone deals back last year. To get a phone as impressive as the Moto G6 for just under £180 was a spectacular offer. We're hoping Argos will be the place to be for budget phones over Black Friday 2019.
iPhone XS Max from Affordable Mobiles | Vodafone | £215.99 upfront | 32GB 80GB data | Unlimited minutes and texts | £37pm
Much like the iPhone XS deal above, we were very impressed with this deal. A load of data, bills under £40 and the upfront cost wasn't even all that bad. If we could see the iPhone 11 Pro Max come down to a price like this, Black Friday 2019 will be a very happy time!
EXCLUSIVE OnePlus 6T at e2save | £115 £90 upfront with TECH25 code | Unlimited calls and texts | 9GB data | £28pm
This OnePlus 6T deal was one of our favourite offers on a plus sized phone during Black Friday, mainly due to those excellent monthly bills. And thanks to the exclusive code for TechRadar readers it was even cheaper. Maybe we'll get lucky and see the OnePlus 7 Pro come down in price this year?
Google Pixel 3 at Three + FREE Google Home Mini | £99 upfront | Unlimited minutes and texts | 100GB data | £48 per month
Normally we're not swayed by a free gift but this offer was great! The Google Pixel 3 had only just come out when this phone contract went up and yet, Three was happy to drop a free speaker, 100GB of data and a pretty decent price tag.
What kind of Black Friday phone deals can I expect?
In years gone by, we've seen savings pretty much across every device when Black Friday comes around. However, this year there are a Black Friday phone deals that we're really hoping for.
iPhones:
For those looking to try and score a cheap iPhone in the Black Friday sales, you're in luck. Every year we see Apple come flying down in price and that includes the flagship iPhones. We saw some pretty incredible price points on the iPhone XR, iPhone XS and XS Max in 2018 so this year we're fully expecting the iPhone 11 to be excellently priced.
For those who would rather go for last year's iPhone XR or XS, prices are just as likely to come down and monthly bills under £30 are highly likely. Perfect for those who want some Apple power without the price.
Finally, if you're just hoping to get one of the cheapest iPhones, the likes of the 7, 8 and the plus versions of these models will all likely be lowered in price and if we're lucky, they could all hit their lowest prices yet.
Android:
If you're more interested in getting an Android in the Black Friday phone deals then there is equally a massive amount of choice. We saw price cuts across the likes of Google, Huawei, Samsung and OnePlus last year, giving a massive variety of choice.
The offers we're really hoping for are some major price cuts on the Samsung Galaxy S10 Plus, the Huawei P30 Pro and if we're lucky, the Google Pixel 4 which will have only been on the market for a very short time when Black Friday rolls around.
Much like iPhone, the cheaper Android devices are equally likely to come down. SIM-free prices on the likes of the OnePlus 6T, Google Pixel 3a and Samsung Galaxy S10e could win you a fantastic phone at a very low price. We're hoping for someone like Argos or Amazon to pull through on this one.

When choosing a new phone contract, you do have to make the big decision between SIM-free and contract. On Black Friday in years before, we've seen some major discounts on both options.
Realistically, we usually see the best Black Friday phone deals on contract. That's where we saw the absolute best bargains last year and we expect the same this year.
However, don't doubt what's available SIM-free. If you're looking for a budget phone, this will likely be the best way to buy it.
Will there be any 5G Black Friday phone deals?
Ah yes, 5G phone deals - the next generation of phone technology. Considering 5G only really made steps into the phone world in 2019, it is impossible to say if 5G phones will appear over Black Friday.
We would say it is unlikely that you will see a huge amount of 5G options over Black Friday, however there will certainly be a few offers to pique your interest. Considering the massive costs of 5G phones so far we wouldn't hold out too much hope for a major discount though.
Are SIM only deals discounted over Black Friday?
Like we said above, we saw some tremendous SIM only deals last year from the likes of iD and Three. This year, we're hoping for more of that - cheap SIM only deals and some big data options.
We saw Three's unlimited data plan come crashing down in price, leading to the impressive £20 a month option now available, could we see it come lower in price? We really hope so.
On top of that, retailers such as BT Mobile, Mobiles.co.uk and Carphone Warehouse are all likely to also join in the SIM only reductions over Black Friday.


public class EM extends StatModel
| Modifier and Type | Field and Description |
|---|---|
static int |
COV_MAT_DEFAULT
|
static int |
COV_MAT_DIAGONAL
|
static int |
COV_MAT_GENERIC
|
static int |
COV_MAT_SPHERICAL
|
static int |
DEFAULT_MAX_ITERS
|
static int |
DEFAULT_NCLUSTERS
|
static int |
START_AUTO_STEP
|
static int |
START_E_STEP
|
static int |
START_M_STEP
|
COMPRESSED_INPUT,
PREPROCESSED_INPUT,
RAW_OUTPUT,
UPDATE_MODEL
| Modifier | Constructor and Description |
|---|---|
protected |
EM(long addr)
|
| Modifier and Type | Method and Description |
|---|---|
static EM |
__fromPtr__(long addr)
|
private static long |
create_0()
|
static EM |
create()
|
private static void |
delete(long nativeObj)
|
protected void |
finalize()
|
private static int |
getClustersNumber_0(long nativeObj)
|
int |
getClustersNumber()
|
private static int |
getCovarianceMatrixType_0(long nativeObj)
|
int |
getCovarianceMatrixType()
|
private static void |
getCovs_0(long nativeObj,
long covs_mat_nativeObj)
|
void |
getCovs(java.util.List<Mat> covs)
|
private static long |
getMeans_0(long nativeObj)
|
Mat |
getMeans()
|
private static double[] |
getTermCriteria_0(long nativeObj)
|
TermCriteria
|
getTermCriteria()
|
private static long |
getWeights_0(long nativeObj)
|
Mat |
getWeights()
|
private static long |
load_0(java.lang.String filepath,
java.lang.String nodeName)
|
private static long |
load_1(java.lang.String filepath)
|
static EM |
load(java.lang.String filepath)
|
static EM |
load(java.lang.String filepath,
java.lang.String nodeName)
|
private static float |
predict_0(long nativeObj,
long samples_nativeObj,
long results_nativeObj,
int flags)
|
private static float |
predict_1(long nativeObj,
long samples_nativeObj,
long results_nativeObj)
|
private static float |
predict_2(long nativeObj,
long samples_nativeObj)
|
float |
predict(Mat samples)
|
float |
predict(Mat samples,
Mat results)
|
float |
predict(Mat samples,
Mat results,
int flags)
|
private static double[] |
predict2_0(long nativeObj,
long sample_nativeObj,
long probs_nativeObj)
|
double[] |
predict2(Mat sample,
Mat probs)
|
private static void |
setClustersNumber_0(long nativeObj,
int val)
|
void |
setClustersNumber(int val)
|
private static void |
setCovarianceMatrixType_0(long nativeObj,
int val)
|
void |
setCovarianceMatrixType(int val)
|
private static void |
setTermCriteria_0(long nativeObj,
int val_type,
int val_maxCount,
double val_epsilon)
|
void |
setTermCriteria(TermCriteria val)
|
private static boolean |
trainE_0(long nativeObj,
long samples_nativeObj,
long means0_nativeObj,
long covs0_nativeObj,
long weights0_nativeObj,
long logLikelihoods_nativeObj,
long labels_nativeObj,
long probs_nativeObj)
|
private static boolean |
trainE_1(long nativeObj,
long samples_nativeObj,
long means0_nativeObj,
long covs0_nativeObj,
long weights0_nativeObj,
long logLikelihoods_nativeObj,
long labels_nativeObj)
|
private static boolean |
trainE_2(long nativeObj,
long samples_nativeObj,
long means0_nativeObj,
long covs0_nativeObj,
long weights0_nativeObj,
long logLikelihoods_nativeObj)
|
private static boolean |
trainE_3(long nativeObj,
long samples_nativeObj,
long means0_nativeObj,
long covs0_nativeObj,
long weights0_nativeObj)
|
private static boolean |
trainE_4(long nativeObj,
long samples_nativeObj,
long means0_nativeObj,
long covs0_nativeObj)
|
private static boolean |
trainE_5(long nativeObj,
long samples_nativeObj,
long means0_nativeObj)
|
boolean |
trainE(Mat samples,
Mat means0)
|
boolean |
trainE(Mat samples,
Mat means0,
Mat covs0)
|
boolean |
trainE(Mat samples,
Mat means0,
Mat covs0,
Mat weights0)
|
boolean |
trainE(Mat samples,
Mat means0,
Mat covs0,
Mat weights0,
Mat logLikelihoods)
|
boolean |
trainE(Mat samples,
Mat means0,
Mat covs0,
Mat weights0,
Mat logLikelihoods,
Mat labels)
|
boolean |
trainE(Mat samples,
Mat means0,
Mat covs0,
Mat weights0,
Mat logLikelihoods,
Mat labels,
Mat probs)
|
private static boolean |
trainEM_0(long nativeObj,
long samples_nativeObj,
long logLikelihoods_nativeObj,
long labels_nativeObj,
long probs_nativeObj)
|
private static boolean |
trainEM_1(long nativeObj,
long samples_nativeObj,
long logLikelihoods_nativeObj,
long labels_nativeObj)
|
private static boolean |
trainEM_2(long nativeObj,
long samples_nativeObj,
long logLikelihoods_nativeObj)
|
private static boolean |
trainEM_3(long nativeObj,
long samples_nativeObj)
|
boolean |
trainEM(Mat samples)
|
boolean |
trainEM(Mat samples,
Mat logLikelihoods)
|
boolean |
trainEM(Mat samples,
Mat logLikelihoods,
Mat labels)
|
boolean |
trainEM(Mat samples,
Mat logLikelihoods,
Mat labels,
Mat probs)
|
private static boolean |
trainM_0(long nativeObj,
long samples_nativeObj,
long probs0_nativeObj,
long logLikelihoods_nativeObj,
long labels_nativeObj,
long probs_nativeObj)
|
private static boolean |
trainM_1(long nativeObj,
long samples_nativeObj,
long probs0_nativeObj,
long logLikelihoods_nativeObj,
long labels_nativeObj)
|
private static boolean |
trainM_2(long nativeObj,
long samples_nativeObj,
long probs0_nativeObj,
long logLikelihoods_nativeObj)
|
private static boolean |
trainM_3(long nativeObj,
long samples_nativeObj,
long probs0_nativeObj)
|
boolean |
trainM(Mat samples,
Mat probs0)
|
boolean |
trainM(Mat samples,
Mat probs0,
Mat logLikelihoods)
|
boolean |
trainM(Mat samples,
Mat probs0,
Mat logLikelihoods,
Mat labels)
|
boolean |
trainM(Mat samples,
Mat probs0,
Mat logLikelihoods,
Mat labels,
Mat probs)
|
calcError,
empty,
getVarCount,
isClassifier,
isTrained,
train,
train,
train
clear,
getDefaultName,
getNativeObjAddr,
save
public static final int COV_MAT_SPHERICAL
public static final int COV_MAT_DIAGONAL
public static final int COV_MAT_GENERIC
public static final int COV_MAT_DEFAULT
public static final int DEFAULT_NCLUSTERS
public static final int DEFAULT_MAX_ITERS
public static final int START_E_STEP
public static final int START_M_STEP
public static final int START_AUTO_STEP
public static EM __fromPtr__(long addr)
public Mat getMeans()
public Mat getWeights()
public static EM create()
public static EM load(java.lang.String filepath, java.lang.String nodeName)
public static EM load(java.lang.String filepath)
public TermCriteria getTermCriteria()
public boolean trainE(Mat samples, Mat means0, Mat covs0, Mat weights0, Mat logLikelihoods, Mat labels, Mat probs)
public boolean trainE(Mat samples, Mat means0, Mat covs0, Mat weights0, Mat logLikelihoods, Mat labels)
public boolean trainEM(Mat samples)
public int getClustersNumber()
public int getCovarianceMatrixType()
public void getCovs(java.util.List<Mat> covs)
public void setClustersNumber(int val)
public void setCovarianceMatrixType(int val)
public void setTermCriteria(TermCriteria val)
protected void finalize() throws java.lang.Throwable
private static long getMeans_0(long nativeObj)
private static long getWeights_0(long nativeObj)
private static long create_0()
private static long load_0(java.lang.String filepath, java.lang.String nodeName)
private static long load_1(java.lang.String filepath)
private static double[] getTermCriteria_0(long nativeObj)
private static double[] predict2_0(long nativeObj, long sample_nativeObj, long probs_nativeObj)
private static boolean trainE_0(long nativeObj, long samples_nativeObj, long means0_nativeObj, long covs0_nativeObj, long weights0_nativeObj, long logLikelihoods_nativeObj, long labels_nativeObj, long probs_nativeObj)
private static boolean trainE_1(long nativeObj, long samples_nativeObj, long means0_nativeObj, long covs0_nativeObj, long weights0_nativeObj, long logLikelihoods_nativeObj, long labels_nativeObj)
private static boolean trainE_2(long nativeObj, long samples_nativeObj, long means0_nativeObj, long covs0_nativeObj, long weights0_nativeObj, long logLikelihoods_nativeObj)
private static boolean trainE_3(long nativeObj, long samples_nativeObj, long means0_nativeObj, long covs0_nativeObj, long weights0_nativeObj)
private static boolean trainE_4(long nativeObj, long samples_nativeObj, long means0_nativeObj, long covs0_nativeObj)
private static boolean trainE_5(long nativeObj, long samples_nativeObj, long means0_nativeObj)
private static boolean trainEM_0(long nativeObj, long samples_nativeObj, long logLikelihoods_nativeObj, long labels_nativeObj, long probs_nativeObj)
private static boolean trainEM_1(long nativeObj, long samples_nativeObj, long logLikelihoods_nativeObj, long labels_nativeObj)
private static boolean trainEM_2(long nativeObj, long samples_nativeObj, long logLikelihoods_nativeObj)
private static boolean trainEM_3(long nativeObj, long samples_nativeObj)
private static boolean trainM_0(long nativeObj, long samples_nativeObj, long probs0_nativeObj, long logLikelihoods_nativeObj, long labels_nativeObj, long probs_nativeObj)
private static boolean trainM_1(long nativeObj, long samples_nativeObj, long probs0_nativeObj, long logLikelihoods_nativeObj, long labels_nativeObj)
private static boolean trainM_2(long nativeObj, long samples_nativeObj, long probs0_nativeObj, long logLikelihoods_nativeObj)
private static boolean trainM_3(long nativeObj, long samples_nativeObj, long probs0_nativeObj)
private static float predict_0(long nativeObj, long samples_nativeObj, long results_nativeObj, int flags)
private static float predict_1(long nativeObj, long samples_nativeObj, long results_nativeObj)
private static float predict_2(long nativeObj, long samples_nativeObj)
private static int getClustersNumber_0(long nativeObj)
private static int getCovarianceMatrixType_0(long nativeObj)
private static void getCovs_0(long nativeObj, long covs_mat_nativeObj)
private static void setClustersNumber_0(long nativeObj, int val)
private static void setCovarianceMatrixType_0(long nativeObj, int val)
private static void setTermCriteria_0(long nativeObj, int val_type, int val_maxCount, double val_epsilon)
private static void delete(long nativeObj)


California urges no vaping as 4th death reported in state
SACRAMENTO, Calif. (AP) - California public health officials are urging people to stop vaping and using e-cigarettes as a fourth death related to vaping was reported in the state.
The state’s Department of Public Health said Wednesday 161 people have been hospitalized for severe breathing problems and lung damage since August.
The Marin County Sheriff’s Office said Wednesday 45-year-old Amanda Margot Arconti of Vacaville died at a Novato hospital earlier this month. An official cause of death is pending.
The U.S. Centers for Disease Control and Prevention identified Vitamin E acetate as a “potential chemical of concern” but has yet to rule out other causes or ingredients.
 The CDC says at least 40 people have died.
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Now you can enjoy a sweet snack without all the guilt. These Goodbites cookies are raw, vegan, naturally sweet - and made with nutritious superfood ingredients. Plus, get a dozen free with your next purchase of $69+!


Dog Breed Classifier
Made with Udacity
Contact
Dog Breed classifier Project
Predicting Dog Breed from picture
{{ form.hidden_tag() }} {{ form.image_file.label }} {{ form.image_file() }} {{ form.submit() }}
{% block message %} {% endblock %}
{% block content %}
Predicted Breed:
{% endblock %}


Thank you !
Awesome! Your registration is complete.
While Email Verification will reach out to you over email, please whitelist our email domain<EMAIL_ADDRESS>so that you do not miss out on important future correspondence.
While Email Verification will reach out to you over email, please whitelist our email domain<EMAIL_ADDRESS>so that you do not miss out on important future correspondence.


Binary Classifier using TensorFlow.js
Data Train
Data Validation
Train Model
Hidden Neuron:
Learning Rate:
Max Epoch:
Initialize Model
Train Model
Test New Data
X :
Y :
Test Model
Training Progress
Loss
Accuracy


October
25th,
2015
The Velocity Selector
The Lorentz force is the total force acting on a point charge due to external electric and magnetic fields.
\[\begin{equation} \vec{F} = q \left [ \vec{E} + \vec{v} \times \vec{B} \right ] \end{equation}\]Under what conditions is the Lorentz force equal to zero? Well, if the electric force (\(q\vec{E}\)) on the charged particle is equal and opposite to the magnetic force (\(q\vec{v} \times \vec{B}\)) on the charged particle, then they will cancel each other out and the net force will equal zero. If the net force on the charged particle is zero, it will feel no acceleration. Thus, its velocity will not change; these are the conditions for a velocity selector.
In the video above, I derive an expression for the speed of a charged particle that will pass through a velocity selector undeflected.


EBD - Easton Bible DIctionary
Blot
BLOT
"BLOT "a stain or reproach (
Job 31:7
;
Proverbs 9:7
). To blot out sin is to forgive it (
Psalm 51:1, 9
;
Isaiah 44:22
;
Acts 3:19
). Christ’s blotting out the handwriting of ordinances was his fulfilling the law in our behalf(
Colossians 2:14
).
"BLOT "a stain or reproach (Job 31:7; Proverbs 9:7). To blot out sin is to forgive it (Psalm 51:1, 9; Isaiah 44:22; Acts 3:19). Christ’s blotting out the handwriting of ordinances was his fulfilling the law in our behalf(Colossians 2:14).


Event
An event occuring at a specific date. Meant to structure time rather than to define work.
Task
An item of work. Subject to migration rules.
Completed Task
A successfully finished task. A deleted task should be struck-through.
Scheduled Task
A task with planned future work. When the schedule is confirmed, mark the event as a task on the
appropriate parent planner on the right date.
Migrated Task
A task that has successfully gone through the migration plan below.
Signifiers
Used to add information to a task. From right to left...
priority: mark a task as important
inspiration: an interesting thought or idea
explore: requires further research
Migration
Migrate tasks as months pass to keep information up-to-date. Start
by looking through previous monthly planners- mark tasks as complete
or strike out those that won't get completed. Migrate incomplete
tasks to the next month. Then, check the future planner for tasks
marked for the upcoming month. Move them to the next month, too.


| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
CANCELLED |
-1 |
public static final int |
ERROR_CPU_NOT_SUPPORTED |
104 |
public static final int |
ERROR_EXSTORAGE |
100 |
public static final int |
ERROR_GOOGLE_SERVICES |
103 |
public static final int |
ERROR_INSTORAGE |
101 |
public static final int |
ERROR_NETWORK |
102 |
public static final int |
ERROR_UNKNOWN |
105 |
public static final String |
mCacheFile |
"index.dat" |
public static final int |
SUCCESS |
0 |
public static final String |
TAG |
"metaioCloud" |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final String |
EXTRA_RECEIVER |
"receiver" |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final double |
FEET_PER_METER |
3.28084 |
public static final int |
FEET_PER_MILE |
5280 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final int |
MESSAGE_AREL_COMPLETE |
1 |
public static final int |
MESSAGE_PROCESS_URL |
0 |
public static final String |
NOTIFICATION_SOUND |
"NOTIFICATION" |
public static final int |
REQUEST_ADD_CALENDAR_EVENT |
1006 |
public static final int |
REQUEST_CHANNEL_FILTER |
1000 |
public static final int |
REQUEST_CHANNEL_FILTER_URL |
1001 |
public static final int |
REQUEST_POI_CONTEXT |
1002 |
public static final int |
REQUEST_VIDEO_PLAY |
1005 |
public static final int |
REQUEST_VISUAL_SEARCH |
1003 |
public static final int |
REQUEST_WEBSITE |
1004 |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final String |
INTENT_EXTRA_AREL_SCENE |
".AREL_SCENE" |
| Modifier and Type | Constant Field | Value |
|---|---|---|
public static final String |
TAG |
"metaio-java" |


Welcome to Task Master
Task Master helps you do to tasks and chores, together with others or by yourself
How does it work?
Imagine creating a deck of cards with a different chore on each card. Every day you just draw a random card and do that chore and shuffle the card back into the deck. You can also keep the card to decrease the odds of getting that chore you don't like. When the deck runs out or at the end of the month everyone just returns all cards they have.
Define a Domain of tasks, like the House, the Garden, the Shared Hobby Space or anything else. In a Domain you can create all the tasks that need to be done. Task Master then keeps track of what you need to do. You can influence what tasks you get by keeping ones you dislike out of the pool, or putting the ones you do like back in to increase the chances of them coming back.


Organization
The Wieting Theatre Guild is a dedicated group of individuals who work together in an effort to support and maintain the Wieting Theatre. Their responsibilities include: managing and monitoring events, general building maintenance, scheduling and booking movies, and scheduling volunteer workers.
Presently the Guild members are:
Executive Committee
- Leann Clemann - President
- D. A. Boerm - Vice-President
- Michelle Evans - Treasurer
- Marie Mann - Secretary
Guild Members
- RLou Snyder - Past-President
- Denise Fletcher - Past-President & Landscaping Coordinator
- Mark McFate - Systems Admin
- Barb Jordan - Volunteer Coordinator
- Mary Fasse-Shaw - Live Events Coordinator
- Lori Baier - Concessions Coordinator
- Charles Johnson - Maintenance Co-Coordinator
- Kevin Nelson - Maintenance Co-Coordinator
- Alan Kline
- Josh Clemann
- Eric (Ro) Rosario
- Sandy Kapayou
- Morgan McFate
Mark McFate maintains this website, the computers and sound/projection systems at the Wieting. Barb Jordan coordinates volunteers. Amy Doyle served the Guild for many years as bookeeper and continues to support theatre activities as needed. Mary Fasse-Shaw is the Guild’s live events coordinator. Steve Kenkel assists with projection, lights and sound.
We tend to take for granted these devoted and hardworking individuals. We want to reassure them of their importance and our gratitude for their hours spent toward the achievement of a common goal - that of keeping the Wieting Theatre facility available to our children and all adults in our communities. Again - Many Thanks!


Enter the item name and hit ENTER to submit
Or select text and right click to "Copy to Product Search"
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A port of log4js to node.js
The multiFile appender can be used to dynamically write logs to multiple files, based on a property of the logging event. Use this as a way to write separate log files for each category when the number of categories is unknown, for instance. It creates file appenders under the hood, so all the options that apply to that appender (apart from filename) can be used with this one, allowing the log files to be rotated and capped at a certain size.
type
- "multiFile"
base
- string
- the base part of the generated log filenameproperty
- string
- the value to use to split files (see below).extension
- string
- the suffix for the generated log filename.All other properties will be passed to the created file appenders. For the property value, categoryName
is probably the most useful - although you could use pid
or level
. If the property is not found then the appender will look for the value in the context map. If that fails, then the logger will not output the logging event, without an error. This is to allow for dynamic properties which may not exist for all log messages.
log4js.configure({
appenders: {
multi: { type: 'multiFile', base: 'logs/', property: 'categoryName', extension: '.log' }
},
categories: {
default: { appenders: [ 'multi' ], level: 'debug' }
}
});
const logger = log4js.getLogger();
logger.debug('I will be logged in logs/default.log');
const otherLogger = log4js.getLogger('cheese');
logger.info('Cheese is cheddar - this will be logged in logs/cheese.log');
This example will result in two log files (logs/default.log
and logs/cheese.log
) containing the log messages.
log4js.configure({
appenders: {
everything: {
type: 'multiFile', base: 'logs/', property: 'userID', extension: '.log',
maxLogSize: 10485760, backups: 3, compress: true
}
},
categories: {
default: { appenders: [ 'everything' ], level: 'debug'}
}
});
const userLogger = log4js.getLogger('user');
userLogger.addContext('userID', user.getID());
userLogger.info('this user just logged in');
This will result in one log file (logs/u12345.log
), capped at 10Mb in size, with three backups kept when rolling the file. If more users were logged, each user would get their own files, and their own backups.


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Subscribe Easy tutorials YouTube Channel to watch more bideos on website development, Digital Marketing, WordPress and graphic Designing.
Why We're different
Subscribe Easy tutorials YouTube Channel to watch more bideos on website development, Digital Marketing, WordPress and graphic Designing.
Angelina
Co-founder at XYZ
Subscribe Easy tutorials YouTube Channel to watch more bideos on website development, Digital Marketing, WordPress and graphic Designing.
John Doe
Director at XYZ
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Coverage
2 classes, 0 / 36 elements
0%
0.0
Test Results
0 / 0
tests 0 secs
No test results could be found. Please ensure that you have instrumented your unit tests correctly.
Most Complex Packages
1.
0%
0.0
default-pkg
(12)
Most Complex Classes
1.
0%
0.0
RingBuffer
(8)
2.
0%
0.0
RingBuffer.RingBufferIterator
(4)
Top 2 Project Risks
RingBuffer
RingBuffer.RingBufferIterator
Least Tested Methods
1.
0%
RingBuffer.dequeue(
)
: Item
(2)
2.
0%
RingBuffer.enqueue(
Item)
: void
(2)
3.
0%
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)
: Item
(2)
4.
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RingBuffer.RingBuffer(
int)
(1)
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)
: boolean
(1)
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)
: int
(1)
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)
: Iterator<Item>
(1)
8.
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)
: boolean
(1)
9.
0%
RingBuffer.RingBufferIterator.remove(
)
: void
(1)


% if (includeBootstrap && !includeSass) { %><% } %> <% if (includeModernizr) { %> <% } %>
Pork drumstick turkey fugiat. Tri-tip elit turducken pork chop in. Swine short ribs meatball irure bacon nulla pork belly cupidatat meatloaf cow.
You now have


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Official Statistics
If a school or college believes a candidate’s GCSE or A level results aren’t right, they send an Enquiry about results to the exam board. If after the enquiry they still think that the results aren’t right, they can appeal against the results. These are the statistics for those appeals for GCSE and A level exams in England, Wales and Northern Ireland.
Some inaccuracies in the data had come to light in our publication ‘Appeals for GCSE and A level: Summer 2014 exam series’. The report provides information on the number of appeals made against results for GCSE and A level qualifications in England, Wales, Northern Ireland, other UK regions and overseas during the summer 2014 exam series. The inaccuracies were due to some errors in the data provided by an exam board.
Some of the inaccuracies also affected 2012 and 2013 summer series publications of Appeals for GCSE and A level.
The corrected version of the data has been reported in the summer 2015 exam series release of the publication on 17 March 2016. The corrected data from 2012 and 2013 has also been reported in this release.
We apologise for any confusion caused as a result.
Ofqual is running a rolling series of online surveys to make sure its statistical releases meet your needs.
Ofqual would like to invite you to take part in the online survey for this release
It will take about ten minutes to complete and your responses will remain entirely confidential in any reports published about the survey.
The survey can be found here


Health, Food & Nutrition
Home
Food
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HEALTH!!
Did you know that fish is a good source of iron?
Healthy habits
Marinated Vegetables
Deluxe
100% of health
deluxe freshness
Ingredients & Measurements
1 head cauliflower
1 bunch broccoli, with stems
3 stalks celery
6 medium carrots
1 1⁄2 cups cherry tomatoes
5 green onions
(10 ounce) can whole mushrooms
(14 ounce) can pitted black olives
(14 ounce) can miniature corn cobs, drained
(8 ounce) can water chestnuts, drained
green pepper, cut into bite size pieces
(8 ounce) bottle Italian dressing (I use Kraft)
Health and Nutrition
Calories from Fat 40 51%
Sodium 320.3 mg 13%
Total Carbohydrate 9.7 g 3%
Dietary Fiber 2.9 g 11%
Sugars 3.5 g 14%
Protein 2.1 g 4%
How To Cook/Prepar.
Break or cut vegetables into bite size pieces and place in large bowl. Pour dressing over vegetables, mix and refrigerate overnight. Stir occasionally.
>


{% set pageTitle = "COVID-19 testing prototypes" %} {% extends "includes/layout.html" %} {% block content %}
No longer being updated.
Index page up to date as at 4 June 2020.
This version adds a England region selection question.
This version directs users in Wales to the Welsh test kit service.
This version includes BIT recommendations, user research iterations, walk-through sites, and 2 versions of the confirmation page.
Update 24 June - includes new traffic lights page, content alignment, and new service name.
Index page updated again 26 June - title and meta description plus elective surgery.
1 July - Delete traffic lights page and amend content on "Check your answers" page and 2 confirmation pages.
3 July - Delete "antigen" and add Leicester.
7 July - Add warning callout re self-isolating
14 July - Add link to new NHS antibody test page.
16 July - Add Northern Ireland testing under-5s
Amend start page to point to GOV.UK question - what is your name? Delete all other pages in app.
Iterate page based on user research, analytics and input from NHS Test and Trace
Delete mention of under-5s testing now Scotland is also testing.
Amend start page to point to GOV.UK question - what is your name? Delete all other pages in app.
Iterate page based on user research, analytics and input from NHS Test and Trace
Delete mention of under-5s testing now Scotland is also testing.
Make it clear that elective surgery is England only.
Align content with GOV.UK.


How the Web Works
Major components of the web:
1. Web Browser
2. Internet
3. Servers
User's performs a search via the browser and HTTP requests are made to servers. The server finds the appropriate HTML document and sends it back to the user's computer where the browser interprets the page and displays it on the user's screen.
HTML
HTML stands for Hypertext Markup Language.
-text content
-markup describes what you see.
-references to other docs, videos, images
-links to other pages like This video
There's an opening and closing tag i.e. <opening tag> content </closing tag> The opening + closing tag + contents is an Element.
Inline vs Block Elements-Inline elements occupies the space bounded by the tags that define the element.
-Block elements normally start and end with a new line, when displayed in a browser.


Arrange the order in which a series of map objects are displayed
This example shows how to arrange the visibility order of markers by clicking them. Zoom in and out to overlap markers and try re-arranging them.
This example uses marker's z-index value to set its rendering order.


--- layout: preso.hbs title: generate displaytitle: Generating a New Async description: A discussion about using generators to form a new async workflow --- Rethinking Async Workflows http://science.howstuffworks.com/environmental/energy/question136.htm Jordan Kasper | @jakerella A Solveable Problem... A Solveable Problem... A Solveable Problem... We could just make this code synchronous... We want to write code in a synchronous fashion, but with the runtime benefits of asynchronicity. So that's what promises do? Not quite. Promises are a mechanism for managing callbacks. Using a Promise Using a Promise Multiple Promises Multiple Promises Multiple Promises Making a Promise https://en.wikipedia.org/wiki/One_Ring Async Callbacks Creating a Promise What's the Difference? That's nice... ...but it doesn't really get us where we want to be. Two Paths https://www.americaninno.com/boston/switch-review-site-for-alternative-learning-programs-and-developer-bootcamps/ What are generators? A mechanism for pausing (and resuming)function execution. Generators are NOTasynchronous. Let's look at some asynchronous code... Long run complete 100 ms timeout! JavaScript follows a "run to completion" paradigm... ...along with an event-based asynchronous loop. This code runs without stopping to the end... setTimeout() causes an asynchronous callback after 100 ms... ...but this for loop will block the event loop until it's done. Generators do not solve this problem. Generators allow functions to pause and resume execution! Remember our synchronous code? Async with generators... I don't see any generators. Wait for it... Let's step back... This is a generator. And this is how you execute it... This is a generator. And this is how you execute it... This is a generator. And this is how you execute it... This is a generator. And this is how you execute it... This is a generator. And this is how you execute it... This is a generator. And this is how you execute it... This is a generator. And this is how you execute it... This is a generator. And this is how you execute it... This is a generator. And this is how you execute it... Inside foo Outside foo Back inside foo This does not break the"run to completion" paradigm! Notice that my generator "yielded" two values: Call the next() one last time... { value: 'a', done: false } { value: { b: 2 }, done: false } { value: undefined, done: true } Adding a return statement: const genObj = foo(); console.log( genObj.next() ); console.log( genObj.next() ); console.log( genObj.next() ); { value: 'a', done: false } { value: { b: 2 }, done: false } { value: 'c', done: true } Generators are Iterators In fact, we can iterate (or loop) over them! a { b: 2 } A generator can receiveinput with each yield Receiving input from a yield Error handling is easy. Error handling is easy! We just throw and catch Error objects. If an error occurs outside the generator... Oops! I did it again. If an error occurs inside the generator... Caught outside generator: Nope nope nope. And finally... Async with Generators Tools We'll Need: Generators (Obviously) and Promises Yes, Promises. Remember: generators are not asynchronous... But what if I have callbacks everywhere? Easy, just promisify the function! Promisification Breakdown (simplified) function promisify( callbackStyleFn ) { return function promiseStyleFn(originalArg) { return new Promise(function( resolve, reject ) { callbackStyleFn(originalArg, function(err, value) { if (err) { return reject(err); } resolve(value); }); }); }; } (Warning: do not use this code!) Generators are cumbersome... Create the generator object Call next() to start it Get the value off the yielded object Call next() over and over Remember to use gen.throw() Async generators We want to abstract away their "Iterable" nature... We need a . . . Our simplified generator runner must... Accept a generator function Create the generator object Call next() Check if our generator is done Wait for yielded Promise to resolve / reject Throw errors on Promise rejection Rinse & repeat (3-6) (Warning: do not use this code! It is not complete.) (Warning: do not use this code! It is not complete.) (Warning: do not use this code! It is not complete.) (Warning: do not use this code! It is not complete.) (Warning: do not use this code! It is not complete.) (Warning: do not use this code! It is not complete.) (Warning: do not use this code! It is not complete.) (Warning: do not use this code! It is not complete.) (Warning: do not use this code! It is not complete.) Let's see it in action { "foo": "bar", "nextIndex": 2, "message": "Generators" } { "foo": "bat", "nextIndex": 5, "message": "are" } { "foo": "baz", "nextIndex": null, "message": "cool" } But is it really asynchronous? { "foo": "bar", "nextIndex": 2, "message": "Generators" } 100 ms timeout! { "foo": "bat", "nextIndex": 5, "message": "are" } { "foo": "baz", "nextIndex": null, "message": "cool" } What about errors?! ERROR! ENOENT, open 'data-infinity.json' Retrieved data: [ '{ "foo": "bar", "nextIndex": 2 }', '{ "foo": "bat", "nextIndex": 5 }' ] async and await async function getData() { try { const one = JSON.parse(await readFile('data-1.json')); const two = JSON.parse(await readFile('data-' + one.nextIndex + '.json')); const three = JSON.parse(await readFile('data-' + two.nextIndex + '.json')); } catch(err) { // Handle the error... } } This looks familiar... Because it is! async functions are based on "pausing" in generators and await requires a Promise! So you're thinking... ... aaaah, but how long until I can use this? async/await are supported in: Chrome (stable) Firefox (stable) Edge (stable) Safari (stable + mobile) Node (7+) And if all else fails... use Babel or Traceur! And Internet Explorer? ಠ_ಠ Want to use generators? Don't reinvent sliced bread! Thank You! Rethinking Async Workflows Jordan Kasper | @jakerella jordankasper.com/async
Jordan Kasper | @jakerella
Not quite.
Promises are a mechanism for managing callbacks.
...but it doesn't really get us where we want to be.
A mechanism for pausing (and resuming)function execution.
Long run complete 100 ms timeout!
This code runs without stopping to the end...
setTimeout() causes an asynchronous callback after 100 ms...
setTimeout()
...but this for loop will block the event loop until it's done.
for
Generators allow functions to pause and resume execution!
And this is how you execute it...
Inside foo Outside foo Back inside foo
Notice that my generator "yielded" two values:
Call the next() one last time...
next()
{ value: 'a', done: false } { value: { b: 2 }, done: false } { value: undefined, done: true }
Adding a return statement:
return
const genObj = foo(); console.log( genObj.next() ); console.log( genObj.next() ); console.log( genObj.next() );
{ value: 'a', done: false } { value: { b: 2 }, done: false } { value: 'c', done: true }
In fact, we can iterate (or loop) over them!
a { b: 2 }
yield
Receiving input from a yield
We just throw and catch Error objects.
throw
catch
If an error occurs outside the generator...
Oops! I did it again.
If an error occurs inside the generator...
Caught outside generator: Nope nope nope.
Generators (Obviously) and Promises
Easy, just promisify the function!
promisify
function promisify( callbackStyleFn ) { return function promiseStyleFn(originalArg) { return new Promise(function( resolve, reject ) { callbackStyleFn(originalArg, function(err, value) { if (err) { return reject(err); } resolve(value); }); }); }; }
(Warning: do not use this code!)
value
gen.throw()
We want to abstract away their "Iterable" nature...
done
(Warning: do not use this code! It is not complete.)
{ "foo": "bar", "nextIndex": 2, "message": "Generators" } { "foo": "bat", "nextIndex": 5, "message": "are" } { "foo": "baz", "nextIndex": null, "message": "cool" }
{ "foo": "bar", "nextIndex": 2, "message": "Generators" } 100 ms timeout! { "foo": "bat", "nextIndex": 5, "message": "are" } { "foo": "baz", "nextIndex": null, "message": "cool" }
ERROR! ENOENT, open 'data-infinity.json' Retrieved data: [ '{ "foo": "bar", "nextIndex": 2 }', '{ "foo": "bat", "nextIndex": 5 }' ]
async
await
async function getData() { try { const one = JSON.parse(await readFile('data-1.json')); const two = JSON.parse(await readFile('data-' + one.nextIndex + '.json')); const three = JSON.parse(await readFile('data-' + two.nextIndex + '.json')); } catch(err) { // Handle the error... } }
Because it is!
async functions are based on "pausing" in generators
and await requires a Promise!
... aaaah, but how long until I can use this?
jordankasper.com/async


The Profiler
measures how often a React application renders and what the "cost" of rendering is. Its purpose is to help identify parts of an application that are slow and may benefit from optimizations such as memoization.
Note:
Profiling adds some additional overhead, so it is disabled in the production build.
To opt into production profiling, React provides a special production build with profiling enabled. Read more about how to use this build at fb.me/react-profiling
A Profiler
can be added anywhere in a React tree to measure the cost of rendering that part of the tree. It requires two props: an id
(string) and an onRender
callback (function) which React calls any time a component within the tree "commits" an update.
For example, to profile a Navigation
component and its descendants:
render(
<App>
<Profiler id="Navigation" onRender={callback}>
<Navigation {...props} />
</Profiler>
<Main {...props} />
</App>
);
Multiple Profiler
components can be used to measure different parts of an application:
render(
<App>
<Profiler id="Navigation" onRender={callback}>
<Navigation {...props} />
</Profiler>
<Profiler id="Main" onRender={callback}>
<Main {...props} />
</Profiler>
</App>
);
Profiler
components can also be nested to measure different components within the same subtree:
render(
<App>
<Profiler id="Panel" onRender={callback}>
<Panel {...props}>
<Profiler id="Content" onRender={callback}>
<Content {...props} />
</Profiler>
<Profiler id="PreviewPane" onRender={callback}>
<PreviewPane {...props} />
</Profiler>
</Panel>
</Profiler>
</App>
);
Note
Although
Profiler
is a light-weight component, it should be used only when necessary; each use adds some CPU and memory overhead to an application.
onRender
CallbackThe Profiler
requires an onRender
function as a prop. React calls this function any time a component within the profiled tree "commits" an update. It receives parameters describing what was rendered and how long it took.
function onRenderCallback(
id, // the "id" prop of the Profiler tree that has just committed
phase, // either "mount" (if the tree just mounted) or "update" (if it re-rendered)
actualDuration, // time spent rendering the committed update
baseDuration, // estimated time to render the entire subtree without memoization
startTime, // when React began rendering this update
commitTime, // when React committed this update
interactions // the Set of interactions belonging to this update
) {
// Aggregate or log render timings...
}
Let's take a closer look at each of the props:
id: string
- The id
prop of the Profiler
tree that has just committed. This can be used to identify which part of the tree was committed if you are using multiple profilers.phase: "mount" | "update"
- Identifies whether the tree has just been mounted for the first time or re-rendered due to a change in props, state, or hooks.actualDuration: number
- Time spent rendering the Profiler
and its descendants for the current update. This indicates how well the subtree makes use of memoization (e.g. React.memo
, useMemo
, shouldComponentUpdate
). Ideally this value should decrease significantly after the initial mount as many of the descendants will only need to re-render if their specific props change.baseDuration: number
- Duration of the most recent render
time for each individual component within the Profiler
tree. This value estimates a worst-case cost of rendering (e.g. the initial mount or a tree with no memoization).startTime: number
- Timestamp when React began rendering the current update.commitTime: number
- Timestamp when React committed the current update. This value is shared between all profilers in a commit, enabling them to be grouped if desirable.interactions: Set
- Set of "interactions" that were being traced when the update was scheduled (e.g. when render
or setState
were called).Note
Interactions can be used to identify the cause of an update, although the API for tracing them is still experimental.
Learn more about it at fb.me/react-interaction-tracing


--- title: Alain Ducasse au Plaza Athénée city: Paris, France date: 2019-09-16 mapleft: -476 maptop: -179 listdata: Alain Ducasse au Plaza Athénée is the 20th restaurant on the quest. It was 13th on the list in 2017, 21st in 2018, and 16th in 2019. It is also a Michelin 3-star restaurant idx: 20 ogimage: https://res.cloudinary.com/snookca/image/upload/v1569173426/20-ducasse/L1010304.jpg tags: - post layout: layouts/post.njk ---
Sometimes luck shines down.
It had been a couple months since I had been to a restaurant on the 50 list and with a few days available, I wanted to see if I could add some more. With five restaurants on the list being in Paris, it seemed like a great opportunity to make some headway.
I managed to book three restaurants for a three day trip. I added us to the waiting list for Alain Ducasse but didn’t hold out much hope.
Wouldn’t you know it? On the day Kitt and I arrive in Paris, I get a phone call: somebody cancelled their reservation. Huzzah! That’s four restaurants now in three days! Oh boy.
We arrive that evening at the Plaza Athénée and are seated towards the back of this magnificent room with gold trim, chandeliers, and dangling Swarovski crystals. It felt quite extravagant.
They didn’t offer a wine pairing but did suggest a 2016 M. Chapoutier Ermitage. Considering the 2012 is my current all-time favourite white wine, I was excited. When I mentioned my delight, the sommelier decided to up the ante and provided a 2014 instead. It was a most welcome suggestion. Kitt took a whiff of the bottle and said it smelled like a Port. The smell is definitely quite lovely, as the taste was, too. Considering the focus on vegetables and seafood for the evening, this wine ended up being a decent pairing.
We started off with a grassy juice and a grain biscuit before a series of appetizers. The flavour was interesting but not mind-blowing in any way. There was a pumpkin seed soup with a spoon that made it difficult to get it out of the bowl. I resorted to lifting the bowl to my lips.
Caviar was presented with a buckwheat crepe and Normandie creme. Since it was left to us to combine the three, I found it difficult to get the right balance between them. When I did, it was fantastic. When I didn’t, it was usually too heavy with the cream and it overwhelmed everything else.
The sea bass was quite tasty and probably the highlight dish of the evening. It was followed by a langoustine dish with smoked radish that was surprisingly intense. The langoustine was cooked to perfection.
The last of the main courses was a black rice with shell fish. The rice was a bit chewy and felt like work to finish off this meal.
Transitioning into dessert was a cheese course featuring sheep’s milk, cow’s milk, a Stilton, and a Comté.
The sommelier offered up a white Port to go with the desserts. I hadn’t had a white Port before and, to be honest, I couldn’t differentiate it from a regular Port. Either way, it was delicious.
We were completely stuffed by the end, do we took the peanut butter filled chocolates and grapes back to the hotel for later. It turns out that peanut butter, chocolate, and grapes are quite tasty together.
The meal was wonderful but rarely did anything come close to that Ratatouille moment. The service was pleasant, the food was delicious, and the venue was a sight to behold. If you find yourself in Paris and wanting a wonderful evening, I don’t think you’d be disappointed. On the other hand, of the four restaurants we went to, this was our least favourite.


Monkeys
Monkey is a common name that may refer to groups or species of mammals, in part, the simians of infraorder Simiiformes. The term is applied descriptively to groups of primates, such as families of New World monkeys and Old World monkeys. Many monkey species are tree-dwelling (arboreal), although there are species that live primarily on the ground, such as baboons. Most species are mainly active during the day (diurnal). Monkeys are generally considered to be intelligent, especially the Old World monkeys of Catarrhini.
Simians and tarsiers emerged within haplorrhines some 60 million years ago. New World monkeys and catarrhine monkeys emerged within the simians some 35 million years ago. Old World monkeys and Hominoidea emerged within the catarrhine monkeys some 25 million years ago. Extinct basal simians such as Aegyptopithecus or Parapithecus [35-32 million years ago], eosimiidea and sometimes even the Catarrhini group are also considered monkeys by primatologists.
Lemurs, lorises, and galagos are not monkeys; instead they are strepsirrhine primates. Like monkeys, tarsiers are haplorhine primates; however, they are also not monkeys.
Apes emerged within "monkeys" as sister of the Cercopithecidae in the Catarrhini, so cladistically they are monkeys as well. There has been resistance to directly designate apes (and thus humans) as monkeys, so "Old World monkey" may be taken to mean the Cercopithecoidea or the Catarrhini. That apes are monkeys was already realized by Georges-Louis Leclerc, Comte de Buffon in the 18th century.


Labour candidate apologises for ‘gassed’ tweet about Israel
Peymana Assad claimed she was using the word as a slang term for being happy, but others described the tweet as distasteful.
A Labour General Election candidate has apologised for an old Twitter post referring to Israel which used the word “gassed”.
In 2012, Peymana Assad tweeted: “Some man I just met thought I was Israeli so I cracked the 10 lost tribes of Israel joke to him and he got gassed.”
The tweet was highlighted on Monday by @GnasherJew, a Twitter account dedicated to “exposing left-wing anti-Semitism” which claims to be run by Jewish journalists and former Labour Party members.
The account said it was not sure what Ms Assad meant by the post, but described it as “exceptionally distasteful”.
Others criticised Ms Assad for the tweet, with Times columnist Daniel Finkelstein responding: “This is the person Labour is asking my family & neighbours to vote for in my constituency.”
Mr Finkelstein later thanked Ms Assad for her apology and said he accepted her explanation.
In a statement shared on Monday afternoon, Ms Assad apologised and said she used the word “gassed” as a “common slang term for being happy and excited”.
“It didn’t occur to me at all that it would have other connotations and I’m completely mortified that I didn’t realise this. I unreservedly apologise,” she wrote.
The candidate for Ruislip, Northwood and Pinner shared examples of other posts from 2012 and 2013 in which she used the term.
She also posted Urban Dictionary’s definition – which describes the word as “when one is overwhelmed or cannot hold your excitement any longer”.
She added: “I said I was Afghan but that there’s a theory that Afghans descend from one of the Ten Lost Tribes of Israel, we laughed about it being a kind of strange theory that’s never been proved
“He was really intrigued by it and said he’d look it up when he got home.”
Ms Assad continued: “I’ve been outspoken against any pro-Palestinian campaigners blaming Jewish people for Israel’s actions and about anti-Semitism in our party and calling out those who seek to deny and downplay it.
“I am absolutely committed to standing in solidarity with Jewish people and to fighting anti-Semitism.”


See how many Pandacoins (PND) you own and what they're worth
Version {{data.version}}
By Drake Emko
Support and FAQ page
Your feedback is welcome. Email<EMAIL_ADDRESS>Donate to the PND Development Community Chest: PBAdSebKmFuDUJP257xReuLnijkAtsP25E


fd-splitter
:
[defaultPaneId]
input property of the fd-splitter
to define main pane. Please
make sure the default pane is in the root container (not in nested container).
fd-splitter-pane-container
:
orientation
to set pane orientation. May be vertical
(default) or
horizontal
.
(resize)
event to get resize information (panes and their updated widths).fd-splitter-split-pane
:
[size]
input property of the fd-splitter-split-pane
to define pane width.[id]
input property of the fd-splitter-split-pane
to define pane id.[requiredParentWidth]
(number, pixels) input property of the
fd-splitter-split-pane
to set minimal required window's width when pane will be shown.
[demandPane]
(boolean) to specify if the pane will be available using the pagination bar
when it's off-canvas.
fd-splitter
has next API methods:
splitter.showPaneOnCanvas(paneId: string)
to show certain pane on the canvas.splitter.hidePaneFromCanvas(paneId: string)
to hide certain pane from the canvas.splitter.isPaneOnCanvas(paneId: string)
to check whether certain pane is on canvas.fd-splitter-split-pane
has next API methods & getters:
splitPane.showOnCanvas()
to show pane on the canvas.splitPane.hideFromCanvas()
to hide pane from the canvas.splitPane.isOnCanvas
to check whether pane is on canvas.


Index Dialog
Use the Index dialog to create an index on a specified table or materialized
view.
The Index dialog organizes the development of a index through the following
dialog tabs: General and Definition. The SQL tab displays the SQL code
generated by dialog selections.
Use the fields in the General tab to identify the index:
- Use the Name field to add a descriptive name for the index. The name will
be displayed in the pgAdmin tree control.
- Use the drop-down listbox next to Tablespace to select the tablespace in
which the index will reside.
- Store notes about the index in the Comment field.
Click the Definition tab to continue.
Use the fields in the Definition tab to define the index:
Use the drop-down listbox next to Access Method to select an index type:
- Select btree to create a B-tree index. A B-tree index may improve
performance when managing equality and range queries on data that can be
sorted into some ordering (the default).
- Select hash to create a hash index. A hash index may improve
performance when managing simple equality comparisons.
- Select gist to create a GiST index. A GiST index may improve
performance when managing values with more than one key.
- Select gin to create a GIN index. A GIN index may improve performance
when managing two-dimensional geometric data types and nearest-neighbor
searches.
- Select spgist to create a space-partitioned GiST index. A SP-GiST index
may improve performance when managing non-balanced data structures.
- Select brin to create a BRIN index. A BRIN index may improve
performance when managing minimum and maximum values and ranges.
Use the Fill Factor field to specify a fill factor for the index. The fill
factor specifies how full the selected method will try to fill each index
page.
Move the Unique? switch to the Yes position to check for duplicate values
in the table when the index is created and when data is added. The default is
No.
Move the Clustered? switch to the Yes position to instruct the server to
cluster the table.
Move the Concurrent build? switch to the Yes position to build the index
without taking any locks that prevent concurrent inserts, updates, or deletes
on the table.
Use the Constraint field to provide a constraint expression; a constraint
expression limits the entries in the index to those rows that satisfy the
constraint.
Use the context-sensitive fields in the Columns panel to specify which
column(s) the index queries. Click the Add icon (+) to add a column:
Use the drop-down listbox in Column field to select the name of the column
rom the table.
If enabled, use the drop-down listbox to select an available Operator class
to specify the type of action performed on the column.
If enabled, move the Sort order switch to specify the sort order:
- Select ASC to specify an ascending sort order (the default);
- Select DESC to specify a descending sort order.
If enabled, move the Nulls switch to specify the sort order of nulls:
- Select First to specify nulls sort before non-nulls;
- Select Last to specify nulls sort after non-nulls (the default).
Use the drop-down listbox in the Collation field to select a collation to
use for the index.
Use Include columns field to specify columns for INCLUDE clause of the
index. This option is available in Postgres 11 and later.
Click the SQL tab to continue.
Your entries in the Index dialog generate a SQL command (see an example
below). Use the SQL tab for review; revisit or switch tabs to make any
changes to the SQL command.
Example
The following is an example of the sql command generated by user selections in
the Index dialog:
The example shown demonstrates creating an index named dist_codes that indexes
the values in the code column of the distributors table.
- Click the Info button (i) to access online help.
- Click the Save button to save work.
- Click the Cancel button to exit without saving work.
- Click the Reset button to restore configuration parameters.


R2-streamer-swift aims at simplifying the usage of numeric publication by parsing and serving them. It takes the publication as input, and generates an accessible WebPubManifest/object as output.
The project documentation is available here
Get started
Adding the library to your iOS project
Carthage
Add the following line to your Cartfile
github "readium/r2-streamer-swift" "master"
Then run carthage update --platform ios
to fetch and build the dependencies.
CocoaPods
//Todo
Import
In your Swift files :
// Swift source file
import R2Streamer
Parsing publications
EPUB
let parser = EpubParser()
CBZ
let parser = CbzParser()
Parsing
...
var parseResult: PubBox
do {
parseResult = try parser.parse(fileAtPath: path)
} catch {
// `{Type}ParserError` exception handling
}
/// Get `Publication` from the `parseResult`
let publication = parseResult.publication
/// Access `Publication` content
let metadata = publication.metadata
let tableOfContent = publication.tableOfContent
let spineItems = publication.spine
//...
You can now access your publications content programmatically. The Publication
object is described in details here.
Built in HTTP server
Initializing the server
R2Streamer provides a local HTTP server called PublicationSever
, this allow access to the resources of the Publication
.
/// Instantiation of the HTTP server
guard let publicationServer = PublicationServer() else {
// Error
}
Adding publications to the server
You can add your parsed publication to the server at the desired endpoints. (The endpoint parameter is optional, an UUID
will be generated if let empty as below)
/// Adding a publication to the server (Using the above section variables)
do {
try publicationServer.add(publication, with: container/* ,"customEndpoint" */)
} catch {
// `PublicationServerError` exception handling
}
When a Publication is added to the server, a new ‘self’ Link
is added to the Publication
‘s links
property.
The Publication
now know how to locate its resources over HTTP. See below for an example.
Accessing a Link
resource from the server
The Publication
is described using Link
s. Each link describe a resource from the publication in a Publication-relative way.
/// Accessing any `Link` resource over HTTP
let cover = publication.coverLink // Or `spineItems[x]`...
let coverUri = publication.uri(forLink: cover)
print(coverUri) // "http://{serverip}:{serverport}/{endpoint}/{`cover.href`}"
Removing a publication from the server
Using the Publication
itself:
publicationServer.remove(publication)
Or it’s endpoint:
publicationServer.remove(at: "endpoint")
WebPub Manifest
For further informations see readium/webpub-manifest.
Pretty
publication.manifest()
Canonical
publication.manifestCanonical()
Supported formats:
EPUB 2/3/3.1- OEBPS - CBZ
Dependencies
The project dependencies are managed with Carthage. Run carthage update –platform ios to fetch and build the dependencies:
- r2-shared-swift : Contains the definitions of shared custom types used across the readium-2 Swift projects.
- swisspol/GCDWebServer A modern and lightweight GCD based HTTP 1.1 server designed to be embedded in OS X & iOS apps.
- tadija/AEXML Simple and lightweight XML parser written in Swift.
- krzyzanowskim/CryptoSwift Crypto related functions and helpers for Swift implemented in Swift.
Documentation
Jazzy is used to generate the project documentation. There are two script for building either the Public API documentation of the full documentation.
./generate_doc_public.sh
./generate_doc_full.sh
The project documentation is available here


15 Self-Care Ideas For Parents — Even If You Only Have a Few Free Minutes
by Rebecca BrownParents don't have a whole lot of free time. Take a casual survey of parents you know and you might hear moms and dads tell you they have under 30 minutes to themselves each day. But that doesn't mean we have to completely sacrifice the things that bring us joy in order to make the most out of the little free time we have. Even a few minutes of self-care can make a huge impact in our physical and emotional health, plus it can make us better parents and set great examples for our children. Whether you're a stay-at-home parent or you spend your days in an office, here are 15 ideas that may help you find a little "me" time. Remember that what soothes you might not work for someone else, so ideas here run the gamut.


--- title: Barbell Weight Calculator layout: default permalink: /projects/barbell-weight-calculator/ ---


First Enable your location if you want to view your location on map. It's Safe. Disable it after the use.


Customers
| First name | Last name | Hobbies | Street | City | |
|---|---|---|---|---|---|
| First Name | Last Name | Hobbies | ${{customer.address.street}} | ${{customer.address.city}} |
|
| First name | Last name | Hobbies | Street | City | |
|---|---|---|---|---|---|
| First Name | Last Name | Hobbies | ${{customer.address.street}} | ${{customer.address.city}} |
|


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Petvot Group — CEO and Co-Founder


(Via
LewRockwell.com.)
They do not talk about breaking up with someone, but they do talk about the dangers of intense stress on heart disease patients. Emotions seem to matter even more when it comes to good health.
Read the full article @
The Telegraph.
Update:
Some more love links:
This is your brain on love
When you're attracted to someone, is your gray matter talking sense -- or just hooked? Scientists take a rational look.
Learn How to Improve Your Luck in Life
Researchers say it is not hard to do.
Here are some Google links to help you prevent/recover from a real heart attack:
Omega-3 fatty acids,
Vitamin D3, and
magnesium citrate.
(This is the brand I use for Vitamin D3/Magnesium Citrate:
30 minutes of Sunshine by LifeSpan Nutrition)


Im looking for a straight Tank... a dwarf that can take all the dmg from meelers and Majics... I dont care if his AB is low i just want to be able to take hits and have tons of HP...  Teach a man to fish, you feed him for a lifetime."
What you are looking for is a dwarven ftr/defender build, focused on constitution. THere are a few listed in the epic build page. For what you describe, you want the lvls to be 10 ftr/30 defender or something to that effect.
The best thing to do AFTER lookin through the builds is to download a leveling mod from bioware and run a few tests to see what you like.
happy fishing
I would suggest you look into more of a Cleric / Dwarven Defender build. Cleric buffs will really aid you and boost yerself in a great way.
That being said, I believe some PWs (or it bioware itself) have taken steps to change the attack UI of certain Monsters, to target player characters that are the biggest damagers in the party, so then you could be tank, but they would veer off you, and try to hit another party member anyways.
You could also look into Drallimer's Divine Wall. It combines WM with DD. Feats are a bit stiff in it, but it's an interesting play.


--- layout: page permalink: blog/machine-learning/cs294-notes/ title: "CS294: Deep Reinforcement Learning's Notes" ---
The following are the lecture notes that I prepared while auditing UC Berkeley's Deep Reinforcement Learning course.