Retirement Advisor: Harbor Crest's Mike Hennessy On Purposeful Planning (Podcast)
by SA For FAsSummary
- Mike Hennessy of Harbor Crest Wealth Advisors caters to boaters and business owners who live or work in proximity to Fort Lauderdale, “the yachting capital of the world."
- Hennessy discusses how he allocates portfolios, defends against risk and alters the investment mix for clients poised to retire.
- Apart from the quantitative aspects of financial planning, Hennessy relates anecdotally how he helps clients achieve a sense of purpose in their retirement.
Listen on the go! Subscribe to the SA for FAs podcast on iTunes , Stitcher and SoundCloud (click the highlighted links).
Mike Hennessy of Harbor Crest Wealth Advisors caters to boaters and business owners who live or work in proximity to Fort Lauderdale, “the yachting capital of the world.”
In this podcast (18:52), the South Florida financial advisor “geeks out” on the quantitative side of wealth management while adding the deeper satisfaction he derives from helping retiring clients feel fulfilled.


--- ---
Official Casual ARMS streams happen most frequently on Mixer and occasionally on Twitch. These offical streams are sometimes featuring the Casual ARMS community events and if so anyone is welcome to join in the lobbies for a chance of being featured in the stream! Other days the streams may have a different focus, such as tours of the official Casual ARMS Minecraft Realm or ARMS tournaments from partner communities.
Aside from the official streams, the community events are often streamed by our community members! These streams are on separate channels which may target a different age or tone. See the Discord server for more information.
All times are in your local time zone.
Regular Slot
Official
Partner


Market Analysis
Bitcoin Price Defies ‘Death Cross’ as Bulls Pin Hopes on $9.1K Bounce
by Horus HughesBitcoin (BTC) price continues to trend lower, marking 5 consecutive lower highs as the price makes a stairstep decline in a falling wedge. Interestingly, the pattern is interpreted by many analysts as a signal of a potentially bullish outcome so perhaps there is still hope.
Crypto market data daily view. Source: Coin360
BTC USD daily chart. Source: TradingView
The price has pierced the $8,674 support three times over the past 4 days, increasing the chance that the price will drop to the lower trendline of the falling wedge at $8,480. The daily chart shows that Bitcoin had spent the week riding along the 200-DMA, a point which was lost earlier today.
The volume profile visible range (VPVR) shows a volume gap between $8,780 and $9,062, meaning the Bitcoin could rally 3.45% to $9,062, a point which would bring the price above the 50-DMA and slightly below the Bollinger Band indicator moving average at $9,121.
A move to $9,148 would set a 3-day higher high at the 100-DMA, bringing Bitcoin price out of the falling wedge and possibly serving as the first indication of a short-term trend change for investors. A pop above the falling wedge resistance would bring the price above the 50% Fibonacci retracement level, a point thoroughly discussed in a previous analysis.
BTC USD daily chart. Source: TradingView
A move to the Bollinger Band indicator moving average at $9,121 would also bring Bitcoin price to the 61.8% Fib retracement level from the Oct. 25 move from $7,400 to $10,540. Bearish traders are calling for a much more significant drop and taking a bird’s eye view of the rally from $3,127 to $13,800 shows that the 61.8% Fib retracement level is situated at $7,840.
BTC USD daily chart. Source: TradingView
This point is also strongly supported (3rd pink bar) and failure to bounce at this point could see the price sink as low as $6,846, the lower trendline of the larger descending channel beginning at the 2019 high. Bounces from this trendline have been strong and previous analysis and the VPVR suggests the $8,300 to $7,800 range as a possible support area where buyers are expected to show interest.
Bearish scenario
Taking a macro view of Bitcoin’s price action on the daily timeframe (chart above), further downside moves in the falling wedge could see the price drop to the support levels (pink bars) at $8,591 and $8,305. In the event of a falling wedge breakdown, the price could drop to $7,862 but before this happens it’s probable that buyers will have stepped in around $8,300 and $8,000.
BTC USD 4-hour chart. Source: TradingView
At the time of writing, the 50-day moving average (DMA) and the 200-DMA are converging on the 4-hour timeframe, forming the oft-discussed dreaded death cross that traders have worried about at length over the past two weeks.
Bullish scenario
On the 6-hour (or one can view the 4-hour chart above) timeframe traders will spot a divergence within the relative strength index (RSI). Given that falling wedges have a tendency to flip bullish, some traders might interpret this divergence as additional proof that Bitcoin could be on the verge of a trend reversal.
Possibly, Bitcoin’s price will continue its current trend, bouncing off the support and resistance line of the falling wedge until price reaches the second (pink bar) support at $8,300 where buyers might show up to push the price back to $8,650.
As mentioned earlier in the analysis, a high volume spike could see the price rally to $9,060, which would be a 9% gain from $8,300. Given that Bitcoin’s trading volume has reduced to a trickle and the current price action looks bearish until $8,373, traders are likely in cash, waiting to see if they can catch a bounce at $8,460 and $8,300.
The views and opinions expressed here are solely those of the author (@HorusHughes) and do not necessarily reflect the views of Cointelegraph. Every investment and trading move involves risk. You should conduct your own research when making a decision.


{{ define "main" }}
{{ .Content }}
{{/* Define a section to pull recent posts from. For Hugo 0.20 this will default to the section with the most number of
pages. */}}
{{ $section := where .Site.RegularPages "Section" "in" "blog" }}
{{ $section_name := index "blog" }}


Nowadays, parallel computing is the most effective solution to overcome temporal limits of sequential computation. With the name OpenCAL-OMP, we identify the OpenMP implementation of the software library, that can run on all cores for your CPU. If you are lucky and have a shared memory multiptocessor system, OpenCAL-OMP can also exploit all the cores of all your CPUs.
Similarly to the serial version, OpenCAL-OMP allows for some unsafe operations, which can significantly speed up your application. However, when you use OpenCAL-OMP in unsafe mode you must give the utmost attention to avoid race condition issues. For instance, when many threads perform concurrent operations on the same memory locations and such operations are made by more than one atomic machine instruction, it can happen that they can interleave, giving rise to wrong (i.e., non consistent) results. Furthermore, even in the case of atomic operations, the logic order of execution could not be respected. Thus, for instance, a read-write logic sequence of atomic operations can actually become a write-read (wrong) sequence due to the fact that the thread performing the write operation is executed first.
In the following sections we will introduce OpenCAL-OMP by examples, highlighting source code the differences with respect to the serial implementations shown in Chapter [ch:opencal]. In the first part of the Chapter, we will deal with the OpenCAL’s safe mode, while in the last one, we will discuss unsafe operations.


{% extends 'layouts/main.html' %} {% block title %}Home{% endblock %} {% block content %}
Improving Healthcare services is a major concern worldwide i.e. reducing the costs of checkups and treatments!
The target audience for these services are Patients and Doctors.


Strathclyde Park all set for annual fireworks display
The bonfire will be lit first at 7.15pm.
by Shirley Bartynek, https://www.dailyrecord.co.uk/authors/shirley-bartynek/Strathclyde Park is all set to host another spectacular fireworks event on Tuesday evening.
The display will go off with a bang at 6.30pm on November 5.
The event, organised by North and South Lanarkshire Councils will see the bonfire being lit first and this will be followed by the display at 8pm.
The 50th anniversary of the Apollo 11 moon landing will be the theme of this year’s fireworks displays on Tuesday evening.
A funfair, provided by M&Ds Scotland’s Theme Park, will run from 4.30pm to 9.30pm near the Watersports Centre.
The Clyde 1 roadshow with Ewen and Cat will entertain the crowds with music and entertainment throughout the evening, with a performance by X Factor contestants Misunderstood.
Visitors to the Strathclyde Country Park event are advised to allow plenty of time for their journey, to follow road signs and directions from police and marshals, and to park responsibly.
Various road closures will be in place check out council’s websites for details.
Sparklers are not allowed within the park, and visitors should dress appropriately for the weather.
Glow in the dark wristbands are available for children to wear at the four fireworks events to help in reuniting parents and children if they become separated.
The bands will be available in advance at the Watersports Centre in Strathclyde Country Park and M&D’s, as well as at the events themselves.


class: center, middle, inverse, title-slide # Discrete Distributions ### Sebastian Hoyos-Torres --- ## What we will cover in this section - Random Variables - Discrete random variables and distributions - expected value of discrete random variables - Binomial probability distribution - Hypergeometric and negative binomial distributions - Poisson probability distribution --- ## Random Variables - What is a random variable? -- - (From p.93 Devore) A RV is any rule that associates a number with each outcome is `\(S\)`. Mathematically, this is expressed as a function whose domain is the sample space and whose range is the set of real numbers. -- .center[This can manifest itself in the following] -- - **Bernoulli Experiment**: an experiment with a binary outcome. In this case we define the random variable as success = 1, failure = 0 - **Counts**: outcome is usually the number of times a particular event occurred. This is already a numeric outcome - **Measurements**: numeric outcomes on a continuous scale. --- ## Discrete Random Variables: - From the prior slide, note that a variable which can only assume **distinct** values is said to be discrete. Typically, they represent counts. -- - From the prior slide a dicrete random variable can manifest itself as a bernoulli experiment, a binomial, or a geometric variable. - Note, these can either finite or infinite. --- ## Continuous Random Variables: - Simply put, a continuous random variable can assume any value in a finite or infinite interval is said to be continuous. - In slide 3, these would typically take the form of measurements --- ## Examples - Discrete Variable examples: - A dog is selected at random from a shelter with a male {M} and female {F} dog. The sample space would then be `$$S = \{M,F\}$$` .center[where if X = 0, the dog is male and if X = 1 the dog is female.] -- - (Devore, p.94) Consider an experiment where a battery is tested until one with an acceptable voltage (S) is obtained. Define an RV by X = the number of outcomes before the experiment terminates. If we do so, X(S) = 1, X(FS) = 2,... X(FFFFS) = 5 -- - Continuous Random Variables - Time till failure which could take any positive value. - Temperature in Kelvin could take any value. --- ## Probability Mass Functions (pmf): - Note, pmf can be denoted as probability density functions, frequency functions, or probability function **These terms all refer to the same thing** - All it refers to is how the total probability of 1 is distributed among the various possible X values. For example, if we have 4 values (1,2,3,4) then, .center[p(0) = the probability of the X value 0 = P(X = 0)] .center[p(1) = the probability of the X value 1 = P(X= 1)] - Therefore, the pmf is defined by p(x) = P(X = x) = P(all `\(s \in{S}\)` : X(S) = x). Although defined for any x, in practice, it is zero except at selected distinct values. .center[**IN R THE VARIOUS PMF FUNCTIONS START WITH A d**. eg. dpois, dnorm, dbinom, dgeom, dhyper] --- ## Pmf continued - Further: -- `$$p(x)\gt{0}, -\infty\lt{x}\lt{\infty}$$` -- `$$\Sigma_{x\in{S}}f(x) = 1$$` -- `$$P(X\in{A}) = \Sigma_{x\in{A}}f(x)$$` --- ## PMF's in R lets say we had the following information on components in a lot (Devore, p.97). ``` ## Observations: 6 ## Variables: 2 ## $ lot <int> 1, 2, 3, 4, 5, 6 ## $ defective <dbl> 0, 2, 0, 1, 2, 0 ``` Let X denote the number of defectives in the lot. What is the pmf for each? ```r examplepmf %>% group_by(defective) %>% summarise(probability = n()/6) ``` ``` ## # A tibble: 3 x 2 ## defective probability ## <dbl> <dbl> ## 1 0 0.5 ## 2 1 0.167 ## 3 2 0.333 ``` --- ## The Cumulative Distribution Function (cdf): - The cumulative distribution function is simply the probability accumulated from the left or `$$F(x) = P(X\leq{x})$$` - The cumulative distribution function contains the following properties - It is a nondecreasing function of x for `\(-\infty\leq{x}\leq{\infty}\)` - The cdf ranges from 0 to 1 **Therefore, it cannot be below 0 or above 1** - If the maximum value of X is b, then `\(F(b) = 1\)` - All probabilities concerning X can be stated in terms of F --- ## Example of cdf - Suppose X is a random variable. Let the pmf of x be `$$f(x) = \frac{5-x}{10}, x = 1,2,3,4$$` - suppose we wanted to find the cdf of X. The cdf is `\(F(x) = P(X\leq{x})\)` --- ## R and cdfs ```r x <- 1:4 #setting up the vector of possible outcomes pmfcdf<- tibble(value = x,pmf = (5-x)/10, #the formula given for pmf cdf = cumsum(5-x)/10) #creating a tibble with the output. cumsum allows you to take the cumulative sum ###Note, this only works for less than or equal to the selected values pmfcdf ``` ``` ## # A tibble: 4 x 3 ## value pmf cdf ## <int> <dbl> <dbl> ## 1 1 0.4 0.4 ## 2 2 0.3 0.7 ## 3 3 0.2 0.9 ## 4 4 0.1 1 ``` - as long as you are given the pmf, you should be able to find the cdf of a random discrete variable. --- ## Visual of the CDF ```r ggplot(pmfcdf, aes(value, cdf))+ geom_step()+ ##note we won't worry too much about the differences between ecdf and cdfs labs(title = "CDF of the example") ``` <img src="week3_files/figure-html/unnamed-chunk-12-1.png" style="display: block; margin: auto;" /> ```r pmfcdf ``` ``` ## # A tibble: 4 x 3 ## value pmf cdf ## <int> <dbl> <dbl> ## 1 1 0.4 0.4 ## 2 2 0.3 0.7 ## 3 3 0.2 0.9 ## 4 4 0.1 1 ``` --- ## CDFs and R - Throughout the course, some of the built in r functions to find the cdf of a certain type of distribution are pbinom,pnorm, pgeom, phyper, ppois,etc. - Some of the arguments involved with these functions can be seen with ? --- ## Expected Values - From an understanding of pmfs and cdfs, we should be able to get an insight into what an expected value is - **Expected Value**: The average value we expect in the long run (informal) - Formal Definition (Devore, p.107): Let X be a discrete random variable with set of possible values D and pmf p(x). The expected value or mean value of X, denoted by E(X) or `\(\mu_{x}\)` or just `\(\mu\)`, is `$$E(X) = \Sigma_{x \in{D}} x * p(x)$$` - Also, the expected value of a function h(X) is computed by `$$E[h(X)] = \Sigma_{x \in{D}}h(x)*p(x)$$` - A special case of the expected value is `$$E(aX + B) = a *E(X)+B$$` --- ## Example of expected values - what is the average toss for a six sided die? - Step 1: We must identify the pmf. In this case, there are 6 possible outcomes in which you can only receive one, so the pmf of the die is 1/6 for x = 1,2,3,4,5,6 -step 2: either look at the formula or use R to do it for you ```r x <- 1:6 sum(x*1/6) # this gives you the expected value ``` ``` ## [1] 3.5 ``` --- background-image: url(https://media.giphy.com/media/GV3aYiEP8qbao/giphy.gif) --- ## More expected values - Suppose a bookstore purchases ten copies of a book at $6.00 each to sell at 12.00 with the understanding that at the end of a 3- month period any unsold copies can be redeemed for 2.00. If X = the number of books sold, then net revenue h(X) = 12X + 2(10-X) - 60 = 10X- 40. What then is the expected net revenue? `$$E(Y) = E[h(x)] = \Sigma_{D}y*p(y)$$` ```r x <- 1:10 ys <- x %>% tibble(x = x) %>% group_by(x) %>% summarise(yvalue = 10*x-40, py = .1) %>%ungroup() sum(ys$yvalue*ys$py) ``` ``` ## [1] 15 ``` --- ## Variances - Remember, expected values tell you where the probability distribution is centered - Variances will describe the variability in the distribution of X `$$V(X) = \Sigma_{D}(x-\mu^2)*p(x) = E[(X-\mu)^2]$$` --- ## Standard Deviation - The standard deviation will be `$$\sigma_x = \sqrt{\sigma_x^2}$$` -shortcut `$$\sigma^2 = [\Sigma_{D}x^2*p(x)] - \mu^2 = E(X^2)-[E(X)]^2$$` - linear combinations `$$V(aX + b) = \sigma^2_{aX+B} = a^2 * \sigma^2_x$$` .center[and] `$$\sigma^2_{aX+B} = |a|\sigma_X$$` .center[which imply] `$$\sigma^2_aX = a^2 * \sigma^2_X, \sigma^2_{X+b} = \sigma^2_x$$` --- ## Chebychevs inequality - If X is any random variable with a mean(expected value) `\(\mu\)` and standard deviation `\(\sigma\)` then `$$P(|X-\mu|\geq{k\sigma})\leq{\frac{1}{k^2}}$$` - Example: the probability that X is more than 2 standard deviations away from its mean is `\(\leq\)` 1/4. --- ## Wrapping up Suppose x is a discrete random variable with the following probability mass function ``` ## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] ## x 1.00 2.00 3.00 4.00 5.00 6.00 7.0 8.00 9.00 10.00 ## px 0.02 0.05 0.06 0.06 0.09 0.15 0.1 0.21 0.14 0.12 ``` Find: - The Cumulative Probability Distribution function, F, of X - the probability `\(4\leq{X}\leq{6}\)` - What is the expected value of X? - What is the variance of X? - What is the expected value of Y = 3X+2 - What is the standard deviation of Y = 3X+2 - What is the probability that X is within 2 standard deviations of its exp value --- ## Solutions ```r #1 problemsol <- tibble(x = 1:10, px = c(.02, .05, .06,.06,.09,.15,.10,.21,.14,.12), cdf = cumsum(px)) glimpse(problemsol) #solution for 1. could also usecumsum(px once you define px) ``` ``` ## Observations: 10 ## Variables: 3 ## $ x <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ## $ px <dbl> 0.02, 0.05, 0.06, 0.06, 0.09, 0.15, 0.10, 0.21, 0.14, 0.12 ## $ cdf <dbl> 0.02, 0.07, 0.13, 0.19, 0.28, 0.43, 0.53, 0.74, 0.88, 1.00 ``` --- ```r problemsol[6,3] - problemsol[3,3]#using indices this is the solution for 2 F(b)- F(a-1) ``` ``` ## cdf ## 1 0.3 ``` ```r problemsol[4,2]+ problemsol[5,2] + problemsol[6,2] #using the pmf between 4 and 6 alternate solution to 2 ``` ``` ## px ## 1 0.3 ``` ```r expectval <- sum(problemsol$x*problemsol$px) #expected value for 3 expectval ``` ``` ## [1] 6.73 ``` ```r variance1 <- sum((problemsol$x^2)*problemsol$px) - expectval^2 #variance variance1 ``` ``` ## [1] 5.7571 ``` ```r sdx <- sqrt(variance1) #standard deviation of x sdx ``` ``` ## [1] 2.399396 ``` --- ## More solutions ```r fction<- 3*problemsol$x + 2 fction ``` ``` ## [1] 5 8 11 14 17 20 23 26 29 32 ``` ```r expectedval <- sum(fction*problemsol$px) #reason we use px is because py does not change from px in a linear transfromation expectedval ``` ``` ## [1] 22.19 ``` ```r variance<- sum((fction-expectedval)^2*problemsol$px)#variance sdy<- sqrt(variance) #standard deviation sdy ``` ``` ## [1] 7.198187 ``` --- ```r ### The interval expectval - 2*sdx; expectval + 2 * sdx ``` ``` ## [1] 1.931208 ``` ``` ## [1] 11.52879 ``` ```r problemsol$cdf[10]- problemsol$cdf[1] ``` ``` ## [1] 0.98 ``` --- ## Studied probability distributions - There have been some distributions which have been studied. We mentioned some such as the binomial, hypergeometric, negative binomial and poisson distributions. - For example, The same fair die is tossed successively and independently 4 times. For each trial let X be the event that a “6” comes up. (P(X) = 1/6). What is the probability distribution of the number of times X occurs? - Each of 12 refrigerators of a certain type have been returned to the distributor because of a loud noise. Suppose that 7 of these have a defective compressor and 5 have a broken ice cube tray. The refrigerators will be examined one by one in random order. Let X be the number among the first 6 examined that have a defective compressor. Calculate: - P(X= 5) - `\(P(X\leq{4})\)` - the expected value of X --- ## Studied Probability Distributions cont. - If there are twelve cars crossing a bridge per minute on average, find the probability of having seventeen or more cars crossing the bridge in a particular minute. - Of these questions, number 1 follows a binomial distribution, 2 follows a hypergeometric distribution, and 3 follows a poisson distribution. - Throughout this section, we will spend time in deciding which problems follow which type of distribution --- ## Binomial Distribution - For a binomial distribution, the following conditions must be met: 1. A fixed number of n trials where n is fixed ahead of the experiment. 2. Each trial can result in one of two outcomes which we can denote as success or failure. 3. The trials are independent (recall independence simply means that the occurrence of an event has no influence on the probability of another) 4. The probability of success P(S) is constant from trial to trial, also denoted as p (note this means there is a certain number of bernoulli trials occuring) - If these conditions are met, then the probability follows a binomial distribution and has the following pmf: `$$P(X = k) = b(k,n,p) = \binom{n}{k}p^k(1-p)^{n-k}$$` .center[for k = 0,1,...,n] --- background-image: url(https://media2.giphy.com/media/xUPGcz2H1TXdCz4suY/giphy.gif) ## Binomial Distributions and R - Thankfully, there is an R function to call it but which is it (I said it on an earlier slide)? --- ## Binomial distributions and R - The functions to calculate the pmf in R is dbinom(k,n,p) [see documentation on necessary arguments] - Lets try to see the logic behind the binomial distribution formula for the pmf. --- ## Example - A particular telephone number is used to receive both voice calls and fax messages. Suppose that 20% of the incoming calls involve fax messages, and consider a sample of 20 incoming calls. (Round your answers to three decimal places.) What is the probability that exactly 7 of the calls involve a fax message? `\(p = .2\)` `\(n = 20\)` `\(k = 7\)` ```r round(choose(20,7)*0.2^7*(1-.2)^(20-7),3) #the manual way with the formula ``` ``` ## [1] 0.055 ``` ```r round(dbinom(7,20,.2),3)# using the built in r function ``` ``` ## [1] 0.055 ``` --- ## Further qualities of the binomial distribution - Note, n and p are called the parameters of the distribution. Given these parameter the following hold for the binomial distribution. - Expected value = `\(n \cdot{p}\)` - Variance = np(1-p) - sd = `\(\sqrt{np(1-p)}\)` - So for the binomial distribution in the previous question, we have the following: - Expected value = 20* 0.2 = 0.4 - Variance = 20*0.2(1-0.2) = 0.4(0.8) = .32 --- ## A look at the binomial distribution R functions -These are the following binomial distribution related functions in R - dbinom(x, size, prob, log = FALSE) (this calculates the pmf) - pbinom(q, size, prob, lower.tail = TRUE, log.p = FALSE)(calculates the cdf) - qbinom(p, size, prob, lower.tail = TRUE, log.p = FALSE) (calculates the quantils) - rbinom(n, size, prob) (generates a random sample from a binomial distribution) - to see the specific arguments, use the help function to read more into the arguments --- ## Hypergeometric distributions - When faced with a situation where we sample **without replacement**, the properties of a binomial distribution become violated so we need to look to other distributions. - One distribution which has been studied extensively is the hypergeometric distribution. If a problem follows a hypergeometric distribution, the following assumptions apply 1. The population, or set to be sampled consists of N individuals, objects,or elements (which is finite) 2. Each individual can be categorized as a success or failure and the are m successes in the population 3. A sample of n individuals is selected **without replacement** in such a way that each subset of size n is equally likely to be chosen. --- ## The hypergeometric distribution continued. - One famous application of the hypergeometric distribution is the urn problem where we have N items of which m are 1 type called success and n = N - m are of the type considered failures. - If k items are randomly selected from the urn then let X represent the number of successes. What is the probability of X = 0,1,...,k? - the density function for this distribution is the following: `$$P(X = x) = \frac{\binom{m}{x}\binom{n}{k-x}}{\binom{m + n}{k}} = \frac{\binom{m}{x}\binom{N-m}{k-x}}{\binom{N}{k}}, x = 0,...,k$$` --- ## R and the hypergeometric distribution - The density function for the hypergeometric distibution is also provided in R via the following - dhyper(x, m, n, k, log = FALSE) - phyper(q, m, n, k, lower.tail = TRUE, log.p = FALSE) - qhyper(p, m, n, k, lower.tail = TRUE, log.p = FALSE) - rhyper(nn, m, n, k) - To see the specific arguments, look at the manual page via ? - **Note: M is the number of successes S, n is the number of failures Fs and k is the sample size** --- ## Variance and Expected Values of the Hypergeometric Distribution - Following the text, the expected value of the hypergeometric distribution is `$$E(X) = n * \frac{M}{N}$$` - The variance is defined as follows. `$$V(X) = \frac{N - n}{N - 1}*n*\frac{M}{N}*(1-\frac{M}{N})$$` - Considering this, how would we tranlate the formulas to R?? --- ## The Variance and expected value in r for the hypergeometric distribution ```r expectedvaluehyper <- function(k,m,n){k*(m/(m+n))} variancehyper <- function(k,m,n){(m+n-k)/(m+n-1)*k*(m/(m+n))*(1-(m/(m+n)))} #where k is the sample size ``` --- ## Example of the hypergeometric distribution - Draw 6 cards from a deck without replacement. What is the probability of getting two hearts? ```r dhyper(2,13,39,6) ``` ``` ## [1] 0.3151299 ``` - A wallet contains 3 $100 bills and 5 1 dollar bills. You randomly choose 4 bills. What is the probability that you will choose exactly 2 100 dollar bills? ```r dhyper(2,3, 5, 4) ``` ``` ## [1] 0.4285714 ``` --- ## More Examples - Out of 100 students qualifying an exam, 10 were drawn randomly. If 35 out of 100 qualified students are female, then find the probability that 6 out of 10 chosen are females. ```r dhyper(6, 35, 65, 10) ``` ``` ## [1] 0.06348496 ``` - Each of 12 refrigerators of a certain type has been returned to a distributor because of an audible, high-pitched, oscillating noise when the refrigerators are running. Suppose that 7 of these refrigerators have a defective compressor and the other 5 have less serious problems. If the refrigerators are examined in random order, let X be the number among the first 6 examined that have a defective compressor. Compute the following: `\(P(X = 5)\)` `\(P(X\leq{4})\)` The expected value of X --- ## Fridge example ```r ## part 1 x <- 5 dhyper(x,7,5,6) ``` ``` ## [1] 0.1136364 ``` ```r #part 2 phyper(4,7,5,6)### these are equivalent ``` ``` ## [1] 0.8787879 ``` ```r sum(dhyper(0:4,7,5,6)) ``` ``` ## [1] 0.8787879 ``` --- ## Fridge example continued ```r expectedvaluehyper(6,7,5) # expected value ``` ``` ## [1] 3.5 ``` ```r variancehyper(m = 7, n = 5, k = 6) #variance ``` ``` ## [1] 0.7954545 ``` --- ## The Negative Binomial Distribution - Properties of the negative binomial distribution 1. The experiment consists of a sequence of independent trials. 2. Each trial can result in success or failure. 3. the probability of success is constant from trial to trial so P(S on trial i) = p for i = 1,2,3,... 4. The experiment continues until a total number of r successes have been observed, where r is a specified positive integer. - In contrast to the binomial rv, the number of successes is fixed and the number of trials is random. --- ## Formulas for the negative binomial distribution - probability mass function `$$\binom{x+r-1}{r-1}p^r(1-p)^x , x = 0,1,2,...$$` - expected value `$$\frac{r(1-p)}{p}$$` - variance `$$\frac{r(1-p)}{p^2}$$` --- background-image:url(https://media0.giphy.com/media/l3nWhI38IWDofyDrW/giphy.gif) ## Can we guess which functions in R calculate the pmfs and cdfs? - judging from the prior slides, can you guess the names of the functions? --- ## The R functions for the negative binomial distribution - dnbinom(x, size, prob, mu, log = FALSE) - pnbinom(q, size, prob, mu, lower.tail = TRUE, log.p = FALSE) - qnbinom(p, size, prob, mu, lower.tail = TRUE, log.p = FALSE) - rnbinom(n, size, prob, mu) --- ## Example of the negative binomial rv - A pediatrician wishes to recruit 5 couples, each of whom is expecting their first child, to participate in a new natural childbirth regimen. Let p = P (a randomly selected couple agrees to participate). If p = .2, what is the probability that 15 couples must be asked before 5 are found who agree to participate? That is, with s = Agree to participate, what is the probability that 10 failures occur before the fifth s. ```r x <- 10 #number of failures r <- 5 #number of successes p <- .2 #p from above dnbinom(x,r,p) # r way with built in function ``` ``` ## [1] 0.0343941 ``` ```r choose(x+r-1,r-1)*(1-p)^x* p^(r) #r way with user generated function ``` ``` ## [1] 0.0343941 ``` --- ## Further Example of a negative binomial rv - There are 28 students in this class. If I want to pick 3 students whose major is computer science and p = 17/28, what is the probability that 5 students must be asked before I select 3 students who are computer science majors? ```r x <- 5 r <- 3 p <- 17/28 dnbinom(x,r,p) ``` ``` ## [1] 0.04398101 ``` --- ## Geometric RV's - Assume we have a sequence of independent bernoulli trials with probability of success p. Let X be the independent random variable representing the number of failures until the first success. Then X is a random geometric variable and the probability density function of x is `$$p(x,p) = \{^{(1-p)^x*p, x = 0,1,2,3....}_{0, otherwise}$$` - With expected value `$$\frac{(1-p)}{p}$$` - With Variance `$$\frac{(1-p)}{p^2}$$` --- ## Geometric Distribution and R - dgeom(x, prob, log = FALSE) - pgeom(q, prob, lower.tail = TRUE, log.p = FALSE) - qgeom(p, prob, lower.tail = TRUE, log.p = FALSE) - rgeom(n, prob) - **NOTE R's dgeom represents the number of failures until the 1st success which is always 1 less than the number of trials until the 1st success** --- ## Geometric Distributions example - A fair die is tossed until the first ‘3’ appears. What is the probability that the first ‘3’ appears on the 5th toss? What is the probability that it would take more than 6 rolls for the first 3 to appear? ```r #part 1 dgeom(4,1/6) ``` ``` ## [1] 0.08037551 ``` ```r #part2 pgeom(5,1/3, lower.tail = FALSE) ``` ``` ## [1] 0.0877915 ``` --- ## Poisson Distribution - A discrete random variable is said to have a Poisson Distribution with parameter `\(\mu{(\mu\gt{0})}\)` if the pmf of x is `$$p(x,\mu) = \frac{e^{-\mu}*\mu^x}{x!}$$` - Further, the probability of more than 1 event in very short intervals is approximately 0. - The number of events in an interval is independent of the number of the events prior to this interval. This indicates that the process has "no memory" or that the process is restartable. --- ## Poisson Distribution continued: - In the poisson model, we are interested in the number X of events which occur in a given time period or a given physical space. - `\(\lambda\)` is the average number of events which occur in the physical space. The rate `\(\alpha\)` is the average number of events which occur in a unit time period or unit space. - `\(\lambda = \alpha{t}\)` is proportional to the length of the interval or size of the space. - If X is poisson, with parameter `\(\alpha\)` for time period 1, then the same process Y considered for time period t will be poisson with a parameter of `\(\lambda = \alpha{t}\)`. Same for space 1 vs space t. --- ## R functions to approximate the poisson distribution - dpois(x, lambda, log = FALSE) - ppois(q, lambda, lower.tail = TRUE, log.p = FALSE) - qpois(p, lambda, lower.tail = TRUE, log.p = FALSE) - rpois(n, lambda) --- ## Examples of the poisson process - The number of requests for assistance received by a towing service is a Poisson process with rate `\(\alpha = 4\)` per hour. - Compute the probability that exactly 10 requests are processed during a particular 2 hour period. - If the operators of the towing service take a 30-min break for lunch, what is the probability that they do not miss any calls for assistance? - How many calls would you expect during their break? ```r #part 1 dpois(10,8) # remember, alpha times t = lambda ``` ``` ## [1] 0.09926153 ``` ```r #part 2 dpois(0,2) ``` ``` ## [1] 0.1353353 ``` ```r #part 3 #remember E(x) = lambda for the poisson distribution and so does V(X) ``` --- ## Other properties of the binomial distribution - Five percent (5%) of Christmas tree light bulbs manufactured by a company are defective. The company's Quality Control Manager is quite concerned and therefore randomly samples 100 bulbs coming off of the assembly line. Let X denote the number in the sample that are defective. What is the probability that the sample contains at most three defective bulbs? ```r pbinom(3,100,.05) ``` ``` ## [1] 0.2578387 ``` ```r ppois(3,5) ``` ``` ## [1] 0.2650259 ``` - NOTE: the poisson distribution is excellent to approximate binomial distributions if n is large and p is small. If so `\(\lambda = np\)`


Nigeria's ruling party wins election in key oil state
Yenagoa, Nigeria – Nigeria's ruling party on Monday won the key oil-rich state of Bayelsa, the electoral body said, a sign of President Muhammadu Buhari's growing influence in opposition strongholds.
Forty-five candidates had taken part in the gubernatorial election on Saturday, which was marred by sporadic violence, including killings, abduction, vote-buying, snatching of voting materials and voter intimidation.
Bayelsa has been ruled by the opposition Peoples Democratic Party (PDP) since Nigeria returned to civilian rule in 1999.
It is a key political battleground because of the lucrative oil and gas sector that is largely based in the southern delta region.
David Lyon of Buhari's All Progressive Congress (APC) won more than twice the number of votes as his closest rival Douye Diri of the PDP, said the Independent National Electoral Commission.
In a statement on Monday, the president congratulated the new governor, but deplored the violence that characterised the vote.
"Violence during elections vitiates our commitment to demonstrate to the world and upcoming generation that we are a people capable of electing leaders in a peaceful and orderly manner," he said, urging those unhappy with the results to seek legal redress, rather than resort to violence.
'Big boost for APC, Buhari'
Political analysts see the APC's victory in an opposition stronghold as a sign of Buhari's growing influence.
"The victory is a big boost for APC and Buhari. It's a measure of acceptance and popularity of the president and his party in the core oil-rich region of which Bayelsa is a part," said Dapo Thomas, a politics and history lecturer at Lagos university.
"I think it is also a reflection of the changing voting pattern of the people in the region who want to be part of the central government headed by Buhari."
Bayelsa and central Kogi are among seven states where gubernatorial elections are being held at different times from the general election due to court rulings. The results of the Kogi election on Saturday were still awaited.
Regional elections are fiercely contested in Nigeria, where governors are powerful figures, controlling state finances and responsible for key areas from education to health.
Nigeria, Africa's most populous nation with 190 million people, has a long history of electoral violence.
More than 50 people were killed during the February and March 2019 general election, which returned Buhari to power.
In 2011, hundreds of people were killed in post-election violence, mostly in northern Nigeria.


19 hospitalized after charter bus, tractor-trailer collide in Virginia
by Daniel UriaNov. 17 (UPI) -- Virginia State Police said 19 people were hospitalized after a bus crashed into a tractor-trailer early Sunday morning.
Heavy fog and icy conditions were responsible for the crash that occurred at 4:30 a.m. on the eastbound lanes of Interstate 64.
The driver of the tractor-trailer lost control causing the vehicle to overturn and the bus carrying more than 20 people was unable to avoid a collision, Virginia State Police spokeswoman Corrine Geller told CNN.
"The impact of the crash split the tractor-trailer in half," said Geller. "The bus ran off the right side of the highway and came to rest against the guardrail.
At least 19 people, including the drivers of the two vehicles, were injured. No deaths were reported and injuries sustained ranged from serious to minor.
At least seven other crashes occurred in the same lanes after the crash, but police said no one was injured.
(0) Leave a comment
upi.com/6959857
Latest Headlines
U.S. News // 4 hours ago
Yellowstone bison hunt generates controversy, court battle
DENVER, Nov. 18 (UPI) -- Members of Indian tribes travel hundreds of miles to participate in a winter close-range hunt of Yellowstone bison. But some participants find the hunt degrading for humans and the animals.
U.S. News // 4 hours ago
4 killed, 6 wounded in shooting at California football party
Nov. 18 (UPI) -- At least four people were killed and six others were wounded in California when at least one unknown gunman opened fire on a party that had gathered to watch a football game, authorities said.
U.S. News // 5 hours ago
Bloomberg apologizes for stop-and-frisk policy
Nov. 18 (UPI) -- Former New York City mayor Michael Bloomberg apologized for the New York Police Department's use of the stop-and-frisk policing tactic he championed during his tenure that disproportionally affected minorities.
U.S. News // 7 hours ago
Syracuse University suspends fraternity activities
Nov. 17 (UPI) -- Syracuse University suspended all social activities at fraternities for the rest of the semester on Sunday following a series of incidents targeting minorities on campus, according to the school's chancellor.
U.S. News // 17 hours ago
Bei Bei the panda to depart Smithsonian National Zoo for China
Nov. 17 (UPI) -- Bei Bei the giant panda will travel from the Smithsonian National Zoo in Washington, D.C., to China on Tuesday as part of a conservation project.
U.S. News // 17 hours ago
Storm system to bring much-needed rainfall to the Southwest and California at midweek
Nov. 17 (UPI) -- A brewing storm system has the potential to bring locally heavy rain to portions of the southwestern United States, including California, this week.
U.S. News // 1 day ago
Democrat John Bel Edwards wins again as Louisiana governor
Nov. 16 (UPI) -- Democrat John Bel Edwards won his second term as Louisiana's governor by 2 1/2 percentage points in a runoff against Republican Eddie Risponse on Saturday night.
U.S. News // 1 day ago
5 dead after man shoots family in San Diego murder-suicide
Nov. 16 (UPI) -- Five people are dead and one injured after a man shot dead his estranged wife and three children before turning the gun on himself in San Diego on Saturday morning, police said.
U.S. News // 1 day ago
Winter hits slopes as ski resorts take advantage of Arctic blasts
Nov. 16 (UPI) -- From Pennsylvania to Michigan, a handful of ski resorts are taking advantage of the unusually cold start to November to open their slopes to the public weeks earlier than normal.
U.S. News // 1 day ago
Trump undergoes 'portions' of annual physical exam at Walter Reed
Nov. 16 (UPI) -- PrePresident Donald Trump on Saturday underwent the first portion of his physical at Walter Reed National Military Medical Center in Bethesda, Md., declaring "everything very good."


1 Infinite
Loop
Cupertino
CA 95014
[map]
Call-in toll-free
number (US/Canada): 1-866-469-3239
Call-in toll number
(US/Canada): 1-650-429-3300
Call-in toll number
(US/Canada): 1-408-856-9570
Attendee access
code: (by request only)
All times are local to the venue (PDT)
|
|
|
|
|
Meeting
Slides |
Meeting
Minutes |
|
|
|
|
|
|
|
|
Tues 10/13 |
9:00 AM |
12:00 PM |
MFD |
|
|
|
|
12:00 PM |
1:15 PM |
Lunch |
|
|
|
|
1:15 PM |
5:00 PM |
WIMS |
|
|
|
|
|
|
|
|
|
|
Wed 10/14 |
9:00 AM |
12:00 PM |
MFD |
||
|
|
12:00 PM |
1:00 PM |
Lunch |
|
|
|
|
1:00 PM |
2:45 PM |
Plenary |
|
|
|
2:45 PM |
3:00 PM |
<break> |
|||
|
|
3:00 PM |
5:00 PM |
IPP |
||
|
Thurs 10/15 |
9:00 AM |
12:00 PM |
IDS |
|
|
|
|
12:00 PM |
1:15 PM |
Lunch |
|
|
|
|
1:15 PM |
3:30 PM |
IDS |
|
|
There are no hotel arrangements for this meeting.
Attendees are responsible
for their own hotel accommodations.
Two nearby hotels have been suggested,
but there are several others in the vicinity. Hotels
near Apple
10050 South DeAnza Boulevard
Cupertino, CA 950124
(408) 253-8900
<http://www.thecypresshotel.com/>
Cupertino Inn
10889 North DeAnza Blvd
Cupertino, CA95014
(408) 996-7700
<http://www.cupertinoinn.com/>


We redefine bitcoin!
- embrace frictionless channels
- syndicate global eyeballs
- harness rich methodologies
- expedite revolutionary supply-chains
- cultivate 24/365 e-business
- drive efficient schemas
- syndicate B2C users
- brand holistic initiatives
- leverage turn-key metrics
- engage B2C methodologies
- exploit bricks-and-clicks interfaces


PERFECT BLUE
Japan. 1997. Director - Satoshi Kon, Screenplay - Sadayuki Murai, Based on Character Design by Hisashi Eguchi, Based on the Novel by Yoshikazu Takeuchi, Producers - Hiroaki Inoue & Masao Maruyama, Planning - Koichi Okamoto & Yoshikazu Takeuchi, Photography - Hisao Shirai, Music - Masahiro Ikumi, Animation Director/Character Design - Hideki Hamazu, Production Design - Mitsusuke Hayakawa, Special Adviser - Katsuhiro Otomo. Production Company - Mad House/Oniro.
Plot: Mima Kirigoe takes the risky move of quitting as a member of the girl pop trio Cham to pursue an acting career with a part in a tv detective series. But the part only proves to be a minor one and Mima is forced to accept playing rape scenes and appearing in a nude magazine layout to sustain herself, while the other two girls take Cham on to great success. At the same time Mima is disturbed to find every detail of her life is being reported as a faked diary on an Internet website. As her spirits sink, she finds herself haunted by a doppelganger which taunts her with what her life could have been if she had not chosen this path.
The name of Katsuhiro Otomo casts a giant shadow over anime. Otomo directed `Akira' (1987) which, with its epic-sized vistas of mass destruction, succeeded in becoming a huge cult hit and whetting Western audiences' appetite for anime. It also made Otomo the only anime name that is recognizable to Westerners - and the subsequent attachment of his name to any project has been enough to carry it to the West. Although what may have escaped notice of those who flock to the Otomo name is that Otomo has only really directed one film other than `Akira' - `World Apartment Horror' (1991) - something which seems incredible considering the size of the shadow Otomo casts over anime. He has directed segments of other films like `Robot Carnival' (1986) and `Memories' (1995), but the greatest Otomo successes - `Rojin Z' (1991), `Memories' and this - have ironically been ones that wave Otomo's name above them but little else. Here Otomo's credit remains the rather nebulous title of `Special Adviser' which nevertheless seems to be enough for it to still be promoted as an Otomo film.
`Perfect Blue' turns away from the usual thematic territory for an Otomo-associated film - Cyberpunk futures and epic-vistas of mass destruction - and is in fact a psycho-thriller. It starts in rather well - there is a marvelously spooky moment where the heroine, after some amusingly comic moments trying to learn how to use a computer, accesses a website only to discover the minutiae of her day is being reported in elaborate detail in a series of faked diary entries written as though by her. The story all-too-believably details the fall of an aidoru (Japanese pop star) who takes an artistic risk in becoming an actress, fails to succeed as expected and is gradually forced into filming gratuitous rape scenes and modelling nude in order to sustain herself, all the while seeing her former partners prospering. In these scenes the film manages to convey a portrait of the downfall of a fragile innocent with considerable conviction.
But unfortunately about halfway through the film becomes somewhat incoherent with the plot becoming a tangle of strands involving the heroine having to deal with her Internet stalker; being haunted by a taunting doppelganger who claims to be her alternate self had she stayed with the group and gone on to success; as well as someone assassinating the people around her. When the film then starts to get into her having memory blackouts and missing days and having scenes in the tv show start oddly mirroring events in her life, it becomes difficult to follow what is meant to be going on. However the film then momentarily pulls back and in a plotting twist of dazzling ingenuity suggests that the role of the actress is really a split personality created by the heroine to deal with the stress of being a pop star, that the doppelganger is her real self emerging through and that the tv show is a projection of the repressed memories of an abusive childhood. It is a moment of crystalline clarity in which all of the hanging confusions up to that point suddenly make perfect sense. But then oddly enough the film seems to back away from this and continues on to an ending where the doppelganger and assassinations are mundanely revealed to be the mere machinations of one of the heroine's friends. It's a puzzling denouement which holds explanations that are actually less convincing than the ones offered by the multiple-personality disorder twist.
Reviewed at the 1998 Wellington International Film Festival Copyright Richard Scheib 1998
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


By Phil Curtolo Mel Gibson (Braveheart) gave a gripping performance as the father of a young kidnapped boy in Ron Howard's Ransom.
 Tom and his wife, Kate, played by Rene Russo (Tin Cup) were instructed not to inform the police, but they contacted the FBI. Minutes later, an elite team of agents led by Delroy Lindo (Broken Arrow) are in Tom's house and wiring every phone.
The plot sounds average, just like most other kidnap movies that you've already seen, and it was nothing more than that. That is until about half-way through the movie.
Suddenly, Tom goes to the Fox 5 news room and makes a live broadcast saying, "This is your ransom. But this is as close as you will ever get to it. Instead, I am offering this money as a reward on your head, dead or alive."
At this point, the plot thickened, and the unusually slow start of the film turned into a suspense-filled action film with great stunts. The last half of the film is very well done.
Another thing that carries this film are the superb performances by Gibson and Sinise, as they collide in a game of wits over their cellular phones for most of the movie. Owen Gleiberman of Entertainment Weekly commented on the subject: "It makes you wonder what kidnappers did before cell phones."
Before this movie, Sinise played mostly "good guys," first in Of Mice & Men, then in Forrest Gump, and most recently, in Apollo 13. But he was surprisingly devilish and cold in his portrayal of a cop-gone-bad. Gibson, of course, was just being Gibson, in an Oscar-worthy performance.
Although most of the scenes were quite predictable, Ransom is a very entertaining and suspenseful film. Grade: B-, ***1/2 out of *****
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


¡Bienvenido a Aventura! Despite the English-language bias of early computers and their manuals, interactive fiction has a culture and a history beyond English, not least in Germany. Like the Monty Python team and the Beatles, Infocom made a German translation of their defining work, when in early 1988 Jeff O'Neill coded up ‘Zork I: Das Große Unterweltreich’. It came at a sorry time in Infocom's fortunes and remains officially unreleased, in part because the translator recruited had rendered the text in a stilted, business-German manner, though a beta-test of the story file circulates to this day. But O'Neill's work was not in vain, as it left another important legacy: an upgrading of the Z-machine format to allow for accented characters, which opened the door to non-English IF on the Z-machine. Jose Luiz Diaz's translation of ‘Advent’ into Spanish, as ‘Aventura’, stimulated much of the 1996 development of Inform as a multilingual system, and Toni Arnold's game ‘Rummelplatzgeschichte’ (1998) also deserves mention, as does advice from Inform users across four continents, among them Torbjörn Andersson, Joachim Baumann, Paul David Doherty, Bjorn Gustavsson, Aapo Haapanen, Ralf Herrmann, J. P. Ikaheimonen, Ilario Nardinocchi, Bob Newell, Giovanni Riccardi and Linards Ticmanis. If nothing else, I am glad to have learned the palindromic Finnish word for soap dealer, “saippuakauppias”.
The standard English-language release of the Inform library now consists of eight files of code. Of these eight, only two need to be replaced to make a translation to another language: "Grammar.h", which contains grammars for English verbs like “take” and “drop”; and a “language definition file” called "English.h". For instance, in Ilario Nardinocchi's translation these two files are replaced by "ItalianG.h" and "Italian.h", in Jose Luis Diaz's translation they become "SpanishG.h" and "Spanish.h" and so on. Language definition files can be useful for more, or rather less, than just translation. ‘The Tempest’ (1997), for instance, uses a language definition file to enable it to speak in Early Modern English verse and to recognise pronouns like “thee” and “thy”. A suitable language definition file could also change the persona of an Inform game from second-person (“You fall into a pit!”) to first-person (“I have fallen into a pit!”) or third (“Bilbo falls into a pit!”), or from present to past tenses, as Jamie Murphy's game ‘Leopold the Minstrel’ (1996) did.
This section goes into the linguistics of the Inform parser, and how to add new grammatical concepts to it using grammar tokens. The next goes into full-scale translation and how to write new language definition files.
· · · · ·
Language is complex, computers are simple. Modern English is a mostly non-inflected language, meaning that words tend not to alter their spelling according to their usage, but even here the parser has to go to some trouble to cope with one of its remaining inflections (“take coin” but “take six coins”: see §29). The range of variation in human languages is large and as many are heavily inflected the task at first seems hopeless.†
On the other hand, Inform is mainly used with Romance-family languages, where commands are formed roughly as they are in English. The language understood by the parser is a simple one, called Informese. It has three genders, two numbers, a concept of animate versus inanimate nouns and a clear understanding of articles and pronouns, but all verbs are imperative, the only tense is the present, there are no cases of nouns (but see §35) and adjectives are not distinguished from nouns (but see §26). Informese is based on a small part of English, but the proposition of this chapter is that (with some effort) you can find Informese at the core of many other languages as well.
Changes of vocabulary are obviously needed: for instance, where an English game recognises “other”, a French one must recognise “autre”. But, as the following example shows, vocabulary changes are not enough:
jetez la boule dedans throw the ball into it (French)
has no word-for-word translation into Informese, because “dedans” (into it) is a pronominal adverb, and Informese doesn't have pronominal adverbs. Instead, a transformational rule like this one must be applied:
dedans inside it → dans lui
Transformational rules like this one bring new grammatical structures into the Inform parser. The rest of this section is occupied with describing what is present already.
· · · · ·
The following is a short grammar of Informese. Both here and in the General Index, grammatical concepts understood by the parser are written in angle brackets ‹like so›.
(1) Commands
A command to an Inform game should be one of:
‹oops-word›
‹word›
‹action phrase›
‹noun phrase›,
‹action phrase›
An ‹oops-word› corrects the last command by putting the ‹word› in to replace whatever seemed to be incorrect. In "English.h", the only words in the ‹oops-word› category are “oops” and its abbreviation “o”. An ‹action phrase› instructs the player to perform an action, unless it is preceded by a ‹noun phrase› and a comma, in which case someone else is instructed to perform an action.
An ‹action phrase› consists of a sequence of verb phrases, divided up by full stops or then-words: a ‹then-word› is a word like the English “then” or a full stop. For instance “take sword. east. put sword in stone” is broken into a sequence of three verb phrases, each parsed and acted on in turn. (It's important not to parse them all at once: the meaning of the noun phrase “stone” depends on where the player is by then.)
(2) Verb phrases
A ‹verb phrase› is one of:
‹again-word›
‹imperative verb›
‹grammar line›
Again-words are another category: in "English.h" these are “again” and its abbreviation “g”. An ‹again-word› is understood as “the ‹verb phrase› most recently typed in which wasn't an ‹again-word›”.
The imperative is the form of the verb used for orders or instructions. In English the imperative (“open the window”) looks the same as the infinitive (“to open”), but in most languages they differ (French “ouvrez” is imperative, “ouvrir” infinitive). Even in many languages where verbs usually follow objects, such as Latin, the imperative comes at the start of a verb phrase, and Informese insists on this. Informese also wants the ‹imperative verb› to be a single word, but programming can get around both requirements.
Grammar lines are sequences of tokens. Each token results in one of four grammatically different outcomes:
‹noun phrase›
‹preposition›
‹number›
‹unparsed text›
For instance, a successful match for the tokens
noun
or
multiheld
would produce
a ‹noun phrase›, whereas a match
for 'into'
would produce
a ‹preposition›. Note that a
general parsing routine can produce any of these four outcomes.
(3) Prepositions
Any word written in quotes as a grammar token. This is normally also a preposition in the ordinary grammatical sense, but not always, as the “press charges” example in §30 shows. In "English.h", “look under table” and “switch on radio” contain two words considered to be prepositions in Informese: “under” and “on”.
(4) Numbers
Include at least the numbers 1 to 20 written out in words. “At least” because a language definition file is free to include more, but should not include less.
(5) Noun phrases
A string of words which refer to a single object or collection of objects, with more or less exactness. Here are some typical examples of "English.h" noun phrases:
it
rucksack
brown bag, pepper
a box and the other compass
nine silver coins
everything except the rucksack
smooth stones
A noun phrase is a list of basic noun phrases:
‹basic np› ‹connective› ‹basic np› ‹connective› … ‹connective› ‹basic np›
and there are two kinds of connective: an ‹and-word› (conjunction), and a ‹but-word› (disjunction). The Inform parser always regards a comma in a ‹noun phrase› (other than one used at the start of a command: see (1) above) as an ‹and-word›, and the definition of "English.h" gives “and” as another. "English.h" has two ‹but-words›: “but” and “except”.
‹Noun phrases›
being parsed are assigned several properties. They are declared
definite if they carry no article, or a definite article which
is not qualified by an all-word or a demanding number, and are otherwise
indefinite. (Except that a noun-phrase containing a dictionary
word flagged as likely to be referring to plural objects, such as
'crowns//p'
, is always indefinite.) Definiteness affects
disambiguation and the parser's willingness to make guesses, as the
description of the parser's disambiguation algorithm at the end
of §33 shows.
Indefinite noun phrases also have a target quantity of objects being referred to: this is normally 1, but 7 for “seven stones” and 100, used internally to mean “as many as possible”, for “crowns” or “all the swords”. Noun phrases also have a gender-number-animation combination, or “GNA”:
Gender: in most European languages, nouns divide up into masculine, feminine or neuter, the three genders in Informese. Gender is important when parsing noun phrases because it can distinguish otherwise identical nouns, as in French: “le faux”, the forgery, “la faux”, the scythe. As in German, there may be no satisfactory way to determine the gender of a noun by any automatic rules: see the next section for how Inform assigns genders to nouns.
Number: singular (“the hat”) or plural (“the grapes”). Individual objects in Inform games can have names of either number. Languages with more than two numbers are rare, but Hebrew has a “pair of” number. This would have to be translated into a demanding number (see (7d) below) for Informese.
Animation: Informese distinguishes between the animate (people and higher animals) and the inanimate (objects, plants and lower animals).
With three genders, two numbers and two animations, Informese has twelve possible GNA combinations, and these are internally represented by the numbers 0 to 11:
| 0 | animate | singular | masculine |
| 1 | feminine | ||
| 2 | neuter | ||
| 3 | plural | masculine | |
| 4 | feminine | ||
| 5 | neuter | ||
| 6 | inanimate | singular | masculine |
| 7 | feminine | ||
| 8 | neuter | ||
| 9 | plural | masculine | |
| 10 | feminine | ||
| 11 | neuter |
Not all possible GNAs occur in all natural languages. In English, cases 6, 7, 9 and 10 never occur, except perhaps that ships are sometimes called “she” and “her” without being animate (GNA 7). In French, 2, 5, 8 and 11 never occur. The parser actually works by assigning sets of possible GNA values to each noun phrase: so, in French, “le faux” carries the set {6}, while the more ambiguous noun phrase “les” carries {3,4,9,10}.
(6) Basic noun phrases
These take the following form, in which both lists can have any number of words in, including none, and in any order:
‹list of descriptors› ‹list of nouns›
For instance “the balloon” has one descriptor and one noun; “red balloon” has just two nouns; “all” has just one descriptor.
(7) Descriptors
There are five kinds of ‹descriptor›, as follows:
(8) Nouns
There are three kinds of ‹noun›, as follows:
parse_name
routine attached, which complicates matters, these will be the words
in its name
array. For instance:
Object -> "blue box" with name 'blue' 'box';has two possible names in Informese, “blue” and “box”.
· · · · ·
It is worth mentioning a number of grammatical features which are not contained in Informese, along with some ways to simulate them.
adverbs such as “quickly” in “run quickly east”. These are not difficult to implement:
Verb 'run' * noun=ADirection -> Go * 'quickly' noun=ADirection -> GoQuickly * noun=ADirection 'quickly' -> GoQuickly;
However, “The authors of Zork have thought about several possible extensions to the Zork parser. One that has come up many times is to add adverbs. A player should be able to do the following:
>go north quietly
You sneak past a sleeping lion who sniffs but doesn't wake up.
The problem is to think of reasons why you would not do everything ‘quietly’, ‘carefully’ or whatever.” (P. David Lebling, “Zork and the Future of Computerized Fantasy Simulations”, Byte, December 1980.) A further problem is the impracticality of modelling the game world closely enough to differentiate between ways to achieve the same action. In Melbourne House's ‘The Hobbit’ adverbs influence the probability of success in randomised events, so for instance “throw rope vigorously across river” is more likely to succeed than “throw rope across river”, but those few players who discovered this were not pleased. Twenty years on from ‘Zork’, adverbs remain largely unused in the medium.
adjectives are not distinguished from nouns, although it can be useful to do so when resolving ambiguities. See §28 for remedies.
genitives: objects are not normally named by description of their circumstances, so “the box on the floor” and “the priest's hat” would not normally be understood. Designers can still define objects like
Object -> "priest's hat" with name 'hat' 'priest^s';
in which the genitive “priest's” is a noun like any other.
pronouns of other kinds, notably: nominative pronouns (“I” in “I am happy”); interrogative pronouns (“What” in “What are you doing?”), although these are often simulated by making “what” an Informese verb; demonstrative pronouns (“that” in “eat that”), although in "English.h" the parser gets this right because they look the same as demonstrative adjectives with no noun attached; possessive pronouns (“mine” in “take the troll's sword. give him mine”, which should expand “mine” to “my X”, where X is the current value of “it”).
pronominal adverbs are not found in English, but are common in other languages: for instance “dessous” (French: “under it”). The next section suggests how these can be achieved.
· · · · ·
An example of parsing Informese. [description] This diagram shows the result of parsing the text “conan, put every sword into the box”, assuming that the verb “put” has a grammar line reading
* multiexcept 'in'/'inside'/'into' noun -> Insert
as indeed it does have in the "English.h" grammar.
† In fact the difficult languages to parse are not those with subtleties of spelling but those where even word-recognition can be a matter of context and guesswork, such as Hebrew, where all vowels are conventionally omitted.


Three held in Oman for drugs
by Times News ServiceMuscat: The Royal Oman Police in Dhofar have arrested three people on charges of possessing and using narcotic drugs.
In a statement issued by ROP on Monday said:“ Dhofar Governorate Police Command arrested three people for possession and use of narcotic drugs. “
Royal Oman Police confirmed that legal procedures are taken against them and the case is underway.


I am a native of Seoul, Korea, and came in contact fashion show at age of 11. After dabbling in fashion and art culture by myself, I decided to attend Parsons The New School of Design. I explored cultural diversity and originality through 4 years of living in NYC. I took a gap year for broaden her mental vision. I had experience in sound design, web design, film, photography, marketing, PR and advertisement. With these wide experience, I am coming back to the city for building my fashion aesthetic.


A graduate student at Georgia State Univeristy https://github.com/MengyuanZhu
M.S. in Computer Science and Ph.D. in Chemistry (GPA:3.9) Program Chair of ACM Georgia State Student Chapter Student Campus Champion of XSEDE
B.S. Pharamcy
Find chemical linkers with preferred properites. C++/Qt
Mobile phone app to test fluorescne. C#/UWP
A location based game to find pokemons. Java/Android, MongoDB/Redis, Node.js, Python
ADMET prediction. C++/Qt
Checklist for security. PHP/CSS/jQuery/MySQL/IIS
Virtual Stock trading software. Java/JavaFX
Predict small molecules's clearance, half-life, distribution of volume and mean residence time. Python/Scikit-learn
Generate molecule analogs. Python/PyQt, OpenEye


| Package | Description |
|---|---|
| fr.sii.ogham.testing.assertion | |
| fr.sii.ogham.testing.assertion.email | |
| fr.sii.ogham.testing.assertion.sms | |
| fr.sii.ogham.testing.assertion.util |
| Modifier and Type | Method and Description |
|---|---|
static FluentReceivedEmailsAssert |
OghamAssertions.assertThat(com.icegreen.greenmail.junit5.GreenMailExtension greenMail,
AssertionRegistry registry)
Helper method to write assertions on mails using fluent API.
|
static FluentReceivedEmailsAssert |
OghamAssertions.assertThat(com.icegreen.greenmail.junit4.GreenMailRule greenMail,
AssertionRegistry registry)
Helper method to write assertions on mails using fluent API.
|
static FluentSmsListAssert<Void,SubmitSm> |
OghamAssertions.assertThat(List<SubmitSm> receivedSms,
AssertionRegistry registry)
Helper method to write assertions on sms using fluent API.
|
static FluentEmailsAssert<Void> |
OghamAssertions.assertThat(javax.mail.internet.MimeMessage[] receivedEmails,
AssertionRegistry registry)
Helper method to write assertions on mails using fluent API.
|
static <M> FluentReceivedSmsAssert<SubmitSm> |
OghamAssertions.assertThat(SmppServerExtension<M> smsServer,
AssertionRegistry registry)
Helper method to write assertions on sms using fluent API.
|
static <M> FluentReceivedSmsAssert<SubmitSm> |
OghamAssertions.assertThat(SmppServerRule<M> smsServer,
AssertionRegistry registry)
Helper method to write assertions on sms using fluent API.
|
| Constructor and Description |
|---|
FluentAddressListAssert(List<AddressesWithContext> actual,
P parent,
AssertionRegistry registry) |
FluentEmailAssert(List<? extends javax.mail.Message> actual,
P parent,
AssertionRegistry registry) |
FluentEmailAssert(javax.mail.Message actual,
int index,
P parent,
AssertionRegistry registry) |
FluentEmailsAssert(List<? extends javax.mail.Message> actual,
P parent,
AssertionRegistry registry) |
FluentPartAssert(List<PartWithContext> actual,
P parent,
AssertionRegistry registry) |
FluentPartAssert(PartWithContext actual,
P parent,
AssertionRegistry registry) |
FluentReceivedEmailsAssert(List<? extends javax.mail.Message> actual,
AssertionRegistry registry) |
| Constructor and Description |
|---|
FluentOptionalParameterAssert(P parent,
List<OptionalParameterWithContext> parameters,
AssertionRegistry registry)
Initializes with the parent instance and optional parameters for each
SubmitSm message. |
FluentPduRequestAssert(List<PduRequestWithContext<S>> actual,
P parent,
AssertionRegistry registry) |
FluentPhoneNumberAssert(List<PhoneNumberWithContext> actual,
P parent,
AssertionRegistry registry) |
FluentReceivedSmsAssert(List<S> actual,
AssertionRegistry registry)
Initializes with the list of received messages
|
FluentShortMessageMessageAssert(List<ShortMessageWithContext<S>> actual,
P parent,
AssertionRegistry registry)
Initializes with the list of short messages and the parent.
|
FluentSmsAssert(List<S> actual,
P parent,
AssertionRegistry registry)
Initializes with several received messages
|
FluentSmsAssert(S actual,
int index,
P parent,
AssertionRegistry registry)
Initializes with a single received message
|
FluentSmsListAssert(List<S> actual,
P parent,
AssertionRegistry registry) |
| Modifier and Type | Class and Description |
|---|---|
class |
FailAtEndRegistry
The aim of this registry is to report all errors at once.
|
class |
FailImmediatelyRegistry
The aim of this registry is to fail fast (do not try all assertions if the
first one is KO).
|
Copyright © 2020. All rights reserved.


java.lang.Object greenfoot.World Level
public class Level
| Field Summary | |
|---|---|
Player |
player
|
short |
spawnRotation
|
int |
spawnX
|
int |
spawnY
|
java.util.List<Tile> |
tiles
|
int |
tileXCount
|
int |
tileYCount
|
| Constructor Summary | |
|---|---|
Level()
|
| Method Summary | |
|---|---|
void |
loadMap(java.lang.String name)
|
void |
scrollToLocation(int gX,
int gY)
|
| Methods inherited from class greenfoot.World |
|---|
act, addObject, getBackground, getCellSize, getColorAt, getHeight, getObjects, getObjectsAt, getWidth, numberOfObjects, removeObject, removeObjects, repaint, setActOrder, setBackground, setBackground, setPaintOrder, showText, started, stopped |
| Methods inherited from class java.lang.Object |
|---|
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
|---|
public Player player
public short spawnRotation
public int spawnX
public int spawnY
public java.util.List<Tile> tiles
public int tileXCount
public int tileYCount
| Constructor Detail |
|---|
public Level()
| Method Detail |
|---|
public void loadMap(java.lang.String name)
public void scrollToLocation(int gX, int gY)


This is the official AtomicDEX mobile beta program channel -
Android: https://play.google.com/store/apps/details?id=com.komodoplatform.atomicdex - iOS: https://testflight.apple.com/join/c2mOLEoC - Please use https://github.com/KomodoPlatform/atomicdex/issues for bug reports and feature requests. For critical security bug reports please do send us your encrypted (https://pgp.mit.edu/pks/lookup?op=get&search=0x379287998EE6CF47) report to<EMAIL_ADDRESS>and allow up to 24h for reply. For atomicDEX API (mm2) related issue reports or feature requests please do use https://github.com/KomodoPlatform/atomicDEX-API/issues
100 messages
Before 05-Dec-19 12:00 AM
dan.17-Jul-19 04:15 PM
It'd be good to know a max number of concurrent connections so the math can be figured out for number of LP's needed for a dICO. Or maybe an LP can be invisible if currently at the max, to avoid failed swaps due to networking issues
ca33317-Jul-19 04:15 PM
over 200 onboarded @vichiet
vichiet17-Jul-19 04:15 PM
@ca333 very nice
Markus17-Jul-19 04:15 PM
lets say u have 5 orders and one gets matched, can another order get matched meanwhile first swap is on going?
ca33317-Jul-19 04:15 PM
yes @Markus
nymkappa17-Jul-19 04:16 PM
So the other party will see his coin stuck until the expiration?
ca33317-Jul-19 04:17 PM
i had atomicDEX nodes i run during the tests matching more than 10 swaps almost simultanously - even the swap process itself takes place concurrently as this is a real multhreading DEX engine.
Vanncoins17-Jul-19 04:17 PM
Found another pretty important bug: after logging out and back into atomicDEX (entered password, not just PIN) I had to re-add all of the assets that I possess to the portfolio section. At first I thought I’d lost them but once I added them back, it displayed the balances. This would be a major pain if you had quite a lot of assets in your DEX wallets
2
ca33317-Jul-19 04:17 PM
@nymkappa - no, exactly the opposite if you re-read Markus and my posts.
Markus17-Jul-19 04:17 PM
Maybe later it could be nice to have a option to tab out of current swap to lets say create another order or browse the orderbook and just get a popup when ur swap is completed?
dan.17-Jul-19 04:18 PM
So it marks the UTXO as unavailable if in use right
nymkappa17-Jul-19 04:18 PM
Missed it. Will check it out
ca33317-Jul-19 04:18 PM
@Vanncoins - ok i see, so basically persisting the coins you had activated even after log-out. Correct?
nymkappa17-Jul-19 04:18 PM
That would make sense from an UX perspective(edited)
1
Vanncoins17-Jul-19 04:19 PM
@ca333 it removed all the coins other than BTC, KMD and RICK
Alecandro17-Jul-19 04:19 PM
I like that suggestion, I can see that as annoying @Vanncoins
2
ca33317-Jul-19 04:20 PM
ok - adding this feature request to the list.
dan.17-Jul-19 04:20 PM
is there a way to have a config for portfolio persisting
that would be good
1
we all understand how kmd chains work. but might be a bit unintuitive for some people to log in and having to add their coins again(edited)
Alecandro17-Jul-19 04:22 PM
Yea I would think less experienced people would think they lost their coins
Vanncoins17-Jul-19 04:23 PM
At the very least, it could be made to persist the correct total balance
dan.17-Jul-19 04:24 PM
there could be a local file that stores balances by address
jansako17-Jul-19 04:31 PM
show coins with positive balance by default, then whatever the user activates on top of that
vichiet17-Jul-19 04:32 PM
Do I need eth in my wallet ?
Malti17-Jul-19 04:33 PM
atomicDEX revshares will be paid out to DEX holders right?
jansako17-Jul-19 04:34 PM
yep. I got some for sale @ 40KMD if you want
tolken17-Jul-19 04:34 PM
why are KMD devs so badass?
shinsplints17-Jul-19 04:35 PM
I received an email on the 10th saying I'm one of the lucky ones, clicked on the link but haven't received anything yet. That Playstore link above isn't working either
Anyone have any ideas?
cryptoclueless17-Jul-19 04:36 PM
@jansako is there any other places to buy dex
tolken17-Jul-19 04:36 PM
@shinsplints DM ca333
Regnar17-Jul-19 04:37 PM
Noticed when I click on a coin I swapped to, it says "unconfirmed" regardless of how many confirmations it has, if I click the swap specifically it shows accurate confirmationa
Market: DEX / BTC | Last Price: 0.00350000 BTC | Currency: BarterDEX | Base Currency: Bitcoin |
Join CoinExchange.io and start trading today!
jl777c17-Jul-19 04:41 PM
maybe we should add DEX to atomicDEX sooner than later
but we are still in the "test only with funds you are willing to lose stage", so best not to risk the extremely rare DEX coins
cryptoclueless17-Jul-19 04:42 PM
how did people end up with DEX
jansako17-Jul-19 04:43 PM
there was an ICo a looong time ago in a different universe (NXT)
Extremely rare you say? OK, price just went up to 50 KMD
jl777c17-Jul-19 04:44 PM
no ICO for DEX
only a couple of private investors and then it started trading on the open market
cryptoclueless17-Jul-19 04:44 PM
wish I'd known of kmd back then. I actually had a lot of nxt back in 2017 pump, and ended up with a bunch of crappy ignis
cipi17-Jul-19 04:45 PM
@vichiet you need ETH ro pay for the fees of ERC20 transactions, so yes, so always need ETH to buy ETH... that is how ERC20 tokens work, all txfees are paid in ETH... i know, total crap, but it is what it is...
jansako17-Jul-19 04:46 PM
@cryptoclueless we are talking like late 2014 for the start of the DEX...
sometime after Supernet ICO
maybe 2015...
jl777c17-Jul-19 04:47 PM
if i remember right, InstantDEX (precursor to DEX) predates SuperNET
summer of 2014 i think
cryptoclueless17-Jul-19 04:49 PM
i bought my first LTC back then on ebay for $2 or $3, sold it at $55 I think on ebay, that was my introduction to crypto
benzo36517-Jul-19 04:50 PM
Kmd logo needs updating
cryptoclueless17-Jul-19 04:51 PM
@cipi so if I trade or withdraw BAT which is an ERC20 token, do I need ETH in the atomicdex wallet?
SHossain17-Jul-19 04:55 PM
@benzo365 it will be updated on next version
cipi17-Jul-19 04:55 PM
@cryptoclueless yes, you need ETH to transfer any ERC20 token
benzo36517-Jul-19 04:57 PM
Also, when you first copy your seed when setting up there is no 'copied to clipboard' message, so you don't know that it's been copied...
...until you go paste, but just a nice to have...
SHossain17-Jul-19 04:58 PM
@benzo365 where do you copy your seed from?
you shouldn't copy your seed and keep in any device which is connected to internet
write down in a piece of paper or notebook
or in an 100% offline computer
allbits17-Jul-19 04:59 PM
What about in gpg protected file?
SHossain17-Jul-19 05:00 PM
might be secure enough. but, hey, you never know what gets hacked next.
allbits17-Jul-19 05:01 PM
Piece of paper seems stone age, and carries its own risks
SHossain17-Jul-19 05:01 PM
ca333 talks enough about security and we learn a lot from him.
allbits17-Jul-19 05:01 PM
Single point of failure seems bad idea too
SHossain17-Jul-19 05:01 PM
every method has it's flaws
keep multiple backups(edited)
like combination of paper, crypto steel, offline computer, offline USB drives
*encrypted USB drives
benzo36517-Jul-19 05:03 PM
@SHossain yeah, I know but I'm willing just for testing....so yeah, that's probably right. I was too excited to get home to write down lol
SHossain17-Jul-19 05:04 PM
i've an A4 size paper which is filled with seed that used for testing
no funds there, but just helps for testing as well
Malti17-Jul-19 05:10 PM
a notification that funds were received on one of your activated coins, is that an option?
SHossain17-Jul-19 05:10 PM
@Malti you need a github account mate
Malti17-Jul-19 05:11 PM
haha got it
on it
SHossain17-Jul-19 05:11 PM
you have good feature requests
this would be good to have. even after each swap, starts and completes
notification is life these days
Malti17-Jul-19 05:12 PM
account created
Cryptoon17-Jul-19 05:12 PM
Imagine just having an ipad running swaps all day
benzo36517-Jul-19 05:13 PM
Beware of a scammer posing as SHossain he is messaging me now. Can we get username blocked SHossain#5701
Cryptoon17-Jul-19 05:13 PM
End of the day check the notifications to see which went through
SHossain17-Jul-19 05:14 PM
we dreamt about this, @Cryptoon, and the result is this beta test and mobile first approach
benzo36517-Jul-19 05:16 PM
Malti17-Jul-19 05:16 PM
Good catch benzo
And you should charge your phone
benzo36517-Jul-19 05:17 PM
Let Pirate and barterlly know.
Lol
Markus17-Jul-19 05:17 PM
I kinda miss from CEX that u can see sats value when trading against btc, now u just get total not price each coin on atomicdex
SHossain17-Jul-19 05:19 PM
thanks @benzo365
banned from Pirate discord
telling barterlly now
benzo36517-Jul-19 05:19 PM
No probs...had to have a bit of fun with him first


This is the partial for login.
{{ username }} salt is {{ salt }}
{{ username }} generated secret is {{ secret }}
You should now have access to API because your're logged in
Please enter a symfony valid user :


{% extends "base.html" %} {% block app_content %}
An unexpected error has occurred
The administrator has been notified. Sorry for the inconvenience!
Back


BBFC Gaming
No JavaScript?
Terrifying error
This message should never appear.
If this page appears without manually typing the url in or using the code, something has gone terribly wrong and the site has detected that 1 is not equal to itself. If you see this message, either someone made a mistake, your computer is broken, there was a weird glitch, or math has stopped working. Please report this error to us at
<EMAIL_ADDRESS>Understood
This website is using cookies.
More details


A landmark for vision 20 Nov 2019, 14:27 by Ed Hill Share This Article Tweet ShareShareShare Subscribe to our FREE Newsletter Author


Proximity places an additional implementation restriction on the use of numeric annotations in a query. Proximity cannot process queries in which an annotated vertex is connected to more than one unannotated vertex. For example, the query shown below is a legal QGraph query, but it cannot currently be executed in Proximity.
Proximity currently prohibits edge annotations with a lower
bound of 0
.
Query edges may not be
annotated with [0]
,
[0..]
, or
[0..
.
This prohibition applies regardless of whether the edge annotation is
used alone, or is applied to an edge adjacent to an annotated
vertex.
j
]


The CiteAs API powers this website, and is also available for use in your own projects.
The REST API is public and gives anyone free, programmatic access to the data.
Include your email so we can track API usage, by adding
a parameter at the end of the URL like this:
?email=YOUR_EMAIL
.
GET /
| Description | Gets an API status object that describes this API. |
| Returns | API Status object |
| Example |
<EMAIL_ADDRESS>|
GET /product/{resource}
| Description | Gets citations for a given resource. |
| Accepts | A DOI, URL, or keyword. |
| Returns | Citations object |
| Example |
<EMAIL_ADDRESS>|
These are the JSON objects returned by the API.
Describes status of this API.
| documentation_url String | Where you can find documentation for this version. | |
| msg String | Relevant messages. | |
| version String | Version string. |
Example: 0.0.1
|
This is the main response object for the API, returning citations for a given input.
| citations List | List of citation objects. |
|
| exports List | List of citation export objects. |
|
| metadata Object | A metadata object listing all metadata found for a given resource. |
Varies by source. |
| name String | Name of the referenced resource. | |
| provenance List | A list of provenance objects describing sources utilized to find and build citation data. | |
| url String | URL for the given resource. |
If input is a keyword, the URL is the first Google search result for the given keyword. |
Provides a citation in a particular format.
| citation String | A citation. |
|
| style_fullname String | Full name of the citation style., e.g. "American Psychological Association 6th edition". |
|
| style_shortname String | Short name of the citation style, e.g. "APA". |
Exported citation data.
| export String | Citation export. | |
| export_name String | Export format. | May include CSV, enw, RIS, and BibTeX. |
Metadata varies by source, but typically includes the below fields.
| DOI String | Valid DOI. | |
| URL String | URL of the resource. | |
| author List |
Author objects in format: "family":"Smith", "given":"Michael"
|
|
| id String | ID for the resource, always "ITEM-1" | |
| title String | Title of the resource. | |
| year Integer | Year of publication. |
Describes steps the software took to try and find citation data, and whether citation data was found.
| content_url String | URL utilized to discover citation data. | |
| found_via_proxy_type String | Returns "doi" or "arXiv ID" if found via DOI or arXiv, else "null". | |
| has_content Boolean | Returns true if content was found at the URL. | |
| host String | Host of the resource, such as crossref, github or pypi. | |
| name String | Name of the step taken to find citation data. | |
| parent_step_name String | Name of the parent step. | |
| parent_subject String | Name of the parent subject. | |
| subject String | Subject of the current step, such as "GitHub repository main page". |


Tagged Questions
Java (not to be confused with JavaScript) is a class-based, object-oriented, strongly typed, reflective language and runtime environment (JRE). Java programs are compiled to bytecode and run in a virtual machine (JVM) enabling a "write once, run anywhere" (WORA) methodology.
-1
votes
0answers
9 views
Why don't common Map implementations cache the result of Map.containsKey() for Map.get()
A common pattern with a map is to check if a key exists and then act on the value only if it does, consider:
if(!map.containsKey(key)) {
map.put(key, new DefaultValue());
}
return map.get(key);
...
0
votes
0answers
7 views
java.lang.ClassNotFoundException: org.hibernate.HibernateException for hibernate 4
I'm trying to set up a web application with tomcat 7.0, java6 and hibernate 4.
Basically, you can say I have the same problem as in this thread: java.lang.ClassNotFoundException: ...
0
votes
0answers
11 views
How to generate xml report with maven depencency?
I would like to use the command mvn dependency:analyze-report to generate xml report.
Actually the report generated is html format.
The plug-in declaration :
<plugin>
...
0
votes
0answers
3 views
How to test Handler callbacks from a Service in an Android JUnit Test?
I want to test the following (standard?) scenario
An activity uses a Service object to do some stuff.
The Service is bind to the activity with bindService(..).
The service itself allows access via ...
-10
votes
2answers
39 views
What does the regex “[+0-9-'.']+$” do? [on hold]
Can someone explain to me what telreg will contain after the assignement ?
String telReg = "[+0-9-'.']+$";
0
votes
1answer
25 views
Expanding a variable within Double Quotes in Java
I have a Java Application program that runs various Unix commands while the main application is executing.
public static void shellExec(){
try{
System.out.println("Entering into the test ...
1
vote
1answer
17 views
How to prevent Java Generics forcing duplicate code?
I'm trying to write an AnimalGroup factory class that returns an instance which contains various different types of Animal. Unfortunately i'm being forced to duplicate code due to what seems like Java ...
-2
votes
0answers
23 views
Java cannot compile when using “extend”
i m trying to compile a .java file and it always give an error in "extend class".I can compile other .java without extend in the code.Also i can compile the file with the extend on another computer.
I ...
0
votes
1answer
14 views
Does Thread.sleep reduce memory issues with reading and saving a big file
I am running a utility class as a java application. The class read a csv file with 5 million records and tries to save about 125k records in database. Half way through i got heap space error. Full ...
0
votes
0answers
7 views
Paypal Merchant Java SDK: How to get Recurring Payment amount to show up on Paypal?
I'm up and running with the Paypal Merchant SDK for Java. I followed the instructions here: ...
0
votes
0answers
9 views
Java, AVL tree, cannot rotate_right, cannot find the reason
I am implementing an AVLTree class using Java, and I have met some mysterious problems:
The AVLTree class definition looks like this: (note that there is an embedded class AVLNode)
public class ...
0
votes
2answers
31 views
RIA - Java banned everywhere
I am considering Java as a platform for development some rich internet application. As a developer I am pretty satisfied by abilities Java provides. But there is a problem - my application should be ...
0
votes
0answers
9 views
How to visualize a picture on the UI using Primeface
I want to make a toggleable form, where each agency from my list will be in a different toggleable panel which will contain photo + additional info. Toggleable panels work perfect. I successfully take ...
-3
votes
0answers
19 views
Explain in plain english algorithm to find a path on graph using hadoop [on hold]
I have a problem that involves finding path of a particular length on directed graph using hadoop and I found myself not been able to invent a solution.
I found couple of existing solutions, in ...
0
votes
1answer
22 views
Concatenate String from BufferedReader and Pass to UI Thread
First off, this is my first Java project! Take a look at the method below. My goal is to receive multi-line text (actually xml in a wrapper) from a socket connection. I am trying to read each line and ...


Most Twitter users are atheists, according to poll.
This is interesting. Sadly, as an opt-in poll, it suffers from the most obvious and extreme selection bias, and raises more questions than it answers.
Does it suggest that atheists are most likely to use twitter? Or perhaps that, without religion, we look elsewhere for silly memes, and thus are more susceptible to polls and the like? Perhaps this higher memetic availability explains why more atheists might be using twitter in the first place. Perhaps it’s really just a measurement of religiousity in the Bay Area and a few other places where twitter is popular.
Hard to say.


Glossary
NDNP / Newspaper Catalogers
These are terms I’m trying to use properly, but which I sometimes still mess up.
- Title: A distinct newspaper title, such as The Daily Prophet. All titles will have a unique LCCN.
- LCCN: Library of Congress Control Number: https://en.wikipedia.org/wiki/Library_of_Congress_Control_Number. In terms of NCA (and ONI and chronam), this uniquely identifies a newspaper title.
- Issue: A single published issue of a newspaper title, such as the April 20th edition of The Daily Prophet. Github users beware, it’s easy to hear “I need you to fix an issue” and stare blankly before realizing what was meant.
Made-up
Terms I’ve made up which may be important for developers and users:
- Issue Key: This is a combination of an LCCN and optional date elements,
used for finding / selecting a group of issues in bulk. This concept is used
by tools such as the issue finder and the bulk upload queue tool. An issue
key’s format is
LCCN/YYYYMMDDEE
:LCCN
is required/YYYY
is optional, but if present must be a four-digit yearMM
is optional, but if present must be a two-digit monthDD
is optional, but if present must be a two-digit day of the monthEE
is optional, but if present must be a two-digit edition number- Each optional part must have all other optional pieces before it; e.g., you
can’t specify
LCCN/MM
- MOC or MARC Org Code: Not made up by me, but the short form, “MOC”, may be seen a lot due to my laziness. This is supposed to be the MARC Organization Code designating the awardee of a batch of newspaper issues. However, in chronam and ONI, this determines the image attribution line, e.g., “Image provided by: Dallas Public Library; Dallas, OR”. This has lead to a necessary evil of misusing MOC in order to provide attribution. Currently ONI and chronam don’t provide a way to separate image attribution from the awardee. For anything that isn’t awarded by the Library of Congress, technically there is no awardee, but the software can’t actually accommodate a batch that doesn’t have this set to something.


Building the wrappers
29 May 2015 GSoC-2015 · SymEngineThis week was very engaging and a little hectic at the end for me. I had to rethink many things during the week, like these wrappers. I had to rewrite them, because of a logical error in the allocation of the pointers that pointed to the data. And spent a whole lot of time trying to understand a hack of passing a variable by reference in c
only to conclude that it can’t be used! Anyways, I learnt a new c
hack! You can refer to this question that I asked on stack overflow.
So, the wrappers for Basic were written. But they didn’t compile because of a missing -fPIC
flag that evidently cmake
puts it on its own and rake
doesn’t. The flag, I guess, was required to enable building of shared libs. The error message was something like this
After hours and hours of googling and reading code on github, I figured out a way to add it. It needs to be added to the variable $CFLAGS
which is in extconf.rb
.
#File: extconf.rb
$CFLAGS << ' -Wall' unless $CFLAGS.split.include?('-Wall')
$CFLAGS << ' -Werror' unless $CFLAGS.split.include?('-Werror')
$CFLAGS << ' -fPIC' unless $CFLAGS.split.include?('-fpic')
And again there was another error
Which was basically because of the static
qualifier. Apparently it was local only to that file. Removing the static qualifier got rid of the errors. Thanks to Ondrej, who was there to help with any problem I faced during the whole week.
And finally… the extension built.
I built the gem and installed it. But I am not yet able to load the extension. There might be some issue with the library path. I will fix that and update it. That will be fixed hopefully in a day or two. And then I will build on the minimal test that I wrote.
The next week I will be a little busy with the competition but I can at least fix the errors in loading the extension properly in irb
and add the remaning methods. The plan now for the next coding week is to add wrappers for the Symbol
class and Integer
.
Commits:
1. Rewrote Ruby C wrappers w/o typedefed array basic
2. Added bare test file for Basic
class
3. Fixed an error in Gemfile
and added README
4. Added WITH_RUBY flags to CMakeLists.txt
5. Added flag -fPIC
. Still doesn’t compile
6. Changes to build the ruby extensions
7. Change in require_path
of gemspec
8. Removed the static
qualifier in wrappers
comments powered by Disqus


Monday, November 16th, 2015
Ruby Hashes vs. JavaScript Objects
This week, we made the jump from 3 weeks of staright up Ruby to JavaScript. Clean, elegant, communicative Ruby, to fickle, mysterious, unnessarily syntaxily complex JavaScript. I doubt that's even a proper english phrase, but my english has gone so far out the window since I started programming that I'm surprised I don't speak exclusively in symbols at this point. Sometimes I'll send a friend a text and when I go back and read it, it looks like it came from a person who was having a stroke.
Monday, November 9th, 2015
Class Methods
Welcome to this week's tutorial. As always, I like to use real life analogies to get my point across. Today we are talking about class methods in Ruby, in the context of our beloved Brooklyn real estate agents. Before I go any further, I should mention that I used to work in real estate for a company with good and honest agents, but I can still smell an exagerated post from 100 miles away and I'm going to help you interpret what an apartment is really like, based on the buzz words agents use in their ads.
Monday, October 26th, 2015
Women in Tech: A Cultural Discussion
When I was given the option this week to research and write about a current cultural issue in tech, I felt compelled to talk about women in tech, or lack there of. Compelled, but also kind of bummed. Why bummed? Well for one, this is certainly not news. What kind of alternative perspective could I personally offer? Secondly, it sucks to look at the stats about women leaving the industry due to lack of senior level offers and hearing about how 'brogrammer' culture is too alienating for most of us to take. At a time when coding is so new and exciting to me, writing about this feels like a downer. Or at least it did at first, but the more I thought about it, the more optimistic I became.
Monday, October 12th, 2015
Group_By in Enumerables
Hello again! Today, i'm going to be discussing the "Group By" method in Ruby, or (group_by). Like arrays, and most things Ruby, group_by can be as complicated or as uncomplicated as you want it, but for the purposes of this tutorial, let's keep it as simple as possible. Also, for the sake of protecting my dignity, I have to mention that I am fully aware that Tinder is not a Ruby app, but am just using it as an analogy.
Any of you on Tinder? Don't lie. Well, if for some reason, you're one of those unicorns who have beat all obstacles in today's modern dating world, ended up in a healthy relationship, and are also living under a rock, I'll explain: Tinder is a mobile dating app that just shows you a picture of another Tinder user, and encourages you to decide immediately if you like them or not, just based on their picture. If you look at this person's face, and decide you are attracted to them, you swipe right on the screen, and if you aren't, you swipe left. If this other user has swiped right, you are able to chat with each other, and if not, you won't be able to until the other user has done so, if they ever do.
Thursday, October 8th, 2015
Arrays and Hashes
Hello! This is my first technical blog post as a Phase-0 DBC student. I probably should have written a little introduction about myself and how I ended up at Dev Bootcamp, but we'll save that for later because I'm a little behind at the moment.
In this post, I will be discussing arrays and hashes. Since arrays are a bit more simple, and involve fewer ways to create and access them, let's start there.


h1>Week Three Day Two
This is some random work from
class
.
List Test
Item One
Item Two
Sub Item
Item Three
Anchors


User
Email
Email will be validated
States
Rio de Janeiro
São Paulo
Minas Gerais
...
Message
File
File
Satisfaction
Email
Valid email
Password
Wrong password


menu
Profile
Notifications
Clear all
A.Demian
left a comment on
Stack
1 minute ago
person_add
New user
Peter Parker
signed up.
1 hour ago
JD
Big Joe
wrote:
Hey, how are you? What about our next meeting
2 minutes ago
A.Demian
left a comment on
Stack
1 minute ago
person_add
New user
Peter Parker
signed up.
1 hour ago
JD
Big Joe
wrote:
Hey, how are you? What about our next meeting
2 minutes ago
A.Demian
left a comment on
Stack
1 minute ago
person_add
New user
Peter Parker
signed up.
1 hour ago
JD
Big Joe
wrote:
Hey, how are you? What about our next meeting
2 minutes ago
View All
account_circle
Adrian D.
STUDENT
account_circle
Edit Account
settings
Settings
exit_to_app
Logout
Profile
Kavin
Attended Test
190
12%
Attended Test
190
12%
Successed Test
180
9.2%
Edit
Save Profile
Edit
Personal
Full Name
Emily Charlotte
Email
<EMAIL_ADDRESS>Phone
(239) 816-9029
Mobile
(320) 380-4539
Add
Bay Area, San Francisco, CA
Website
https://bootdey.com
Github
bootdey
Twitter
@bootdey
Instagram
bootdey
Facebook
bootdey
Skill
Add Skill
Dashboard
Test List
Result
Company Hiring
Student
star_half
Dashboard
queue_play_next
Courses
live_help
Thursday, 28 Feb
12:30 PM
2 hrs
Marketing Team Meeting
location_on
16845 Hicks Road
Wednesday, 27 Feb
07:48 PM
30 min
Call Alex
phone
202-555-0131
Tuesday, 26 Feb
03:13 PM
2 hrs
Design Team Meeting
location_on
16845 Hicks Road
Monday, 25 Feb
12:30 PM
2 hrs
Call Wendy
phone
202-555-0131
×
AICL TEST
skill
level


{% extends "base_generic.html" %} {% block title %}Arkenstone Matched Play{% endblock %} {% block content %}
Welcome to Arkenstone, a website developed by Lejbron!
Arkenstone has the following objects counts:
You have visited this page {{ num_visits }}{% if num_visits == 1 %} time{% else %} times{% endif %}.
{% endblock %}