Exercise 8 Singular Spectrum Analysis – Diagnostics & Forecasting
For the spring season flow (Apr-Jun average) at Lees Ferry on the Colorado River perform SSA and make predictions from it. The steps are as follows:
** Diagnostic **
- Select a window size of about 10-20 years (feel free to experiment with the window size); create the Toeplitz matrix and perform SSA.
- Plot the Eigen spectrum and identify the dominant modes.
- Reconstruct the dominant modes (i.e. Reconstructed Components - RCs) and plot them. Infer from them the dominant periodicities.
- Sum the leading modes and plot them along with the original time series. This will show the ‘filtering’ capability of SSA. Feel free to play with the number of RCs.
- Plot the dominant modes and show their corresponding wavelet spectra
** Prediction **
- Apply the SSA to data for the pre-2001
- Make a prediction for the 2001 using AR models to the leading modes; and repeat for each year through 2016.
- Plot the observed and predicted values; compute the median correlation.
8.1 SSA on time frame window
set.seed(1) # allow repetition of results
# libraries
libr=c("magrittr","MASS","sm.density")
options(warn=-999)
suppressPackageStartupMessages(lapply(libr,
require, character.only = TRUE))
# Load flow data
mflow = read.table(
"http://civil.colorado.edu/~balajir/CVEN6833/HWs/HW-3-2018/LeesFerry-monflows-1906-2016.txt")
lf = mflow[,2:13] %>% `rownames<-`(mflow[,1]) %>% # Apr - Jun
{rowMeans(.[,4:6])} %>% {.*0.0004690502*0.001} # convert to 10^3 cms
# lfann = apply(mflow[,2:13],1,sum) %>% {.*0.0004690502*0.001}
M = 20
ssaout = ssab(lf,M)
par(mfrow=c(1,2))
plot(ssaout$lambdas)
plot(cumsum(ssaout$lambdas))
sum(ssaout$lambdas[1:5])
## [1] 0.4127211
We choose the first 5 RPC as they represent more than 40% of the variance.
K=5
par(mfrow=c(3,2))
for(i in 1:K){
plot(ssaout$Rpc[,i],type = "l",main = paste(sprintf("RPC %s",i)))
}
The resulting time series from the reconstructed dominant modes is plotted with the historical data.
Recon = apply(ssaout$Rpc[,1:K],1,sum)
plot(mflow[,1],lf,col="red",type="l",xlab = "", ylab = "",ylim = c(0,max(lf)))
lines(mflow[,1],Recon,col="blue")
legend(x="bottomleft",legend = c("Historic values",
"Reconstructed dominant modes"),col=c("red","blue"),lty = 1,bty="n")
The sum of all RPC gives the original time series.
Recon.tot = apply(ssaout$Rpc[,1:20],1,sum)
plot(mflow[,1],lf,col="red",type="l",xlab = "", ylab = "",ylim = c(0,max(lf)))
points(mflow[,1],Recon.tot,col="blue")
legend(x="bottomleft",legend = c("Historic values",
"Reconstructed dominant modes"),col=c("red","blue"),lty = 1,bty="n")
8.2 Prediction: Use AR models to fit RPC and predict 2001 - 2016 streamflows
8.2.1 Perform SSA until 2001
M = 15 # window reduced
ssaout = ssab(lf[1:95],M) # 1906 - 2000
par(mfrow=c(1,2))
plot(ssaout$lambdas)
plot(cumsum(ssaout$lambdas))
sum(ssaout$lambdas[1:5])
## [1] 0.4784262
We choose the first 5 RPC as they represent more than 40% of the variance.
K=5
par(mfrow=c(3,2))
for(i in 1:K){
plot(ssaout$Rpc[,i],type = "l",main = paste(sprintf("RPC %s",i)))
}
The resulting time series from the reconstructed dominant modes is plotted with the historical data.
Recon = apply(ssaout$Rpc[,1:K],1,sum)
plot(mflow[1:95,1],lf[1:95],col="red",type="l",xlab = "", ylab = "",ylim = c(0,max(lf)))
lines(mflow[1:95,1],Recon,col="blue")
legend(x="bottomleft",legend = c("Historic values",
"Reconstructed dominant modes"),col=c("red","blue"),lty = 1,bty="n")
8.2.2 AR model for dominant modes
# Fit best AR to each dominant RPC
rc.ar = as.list(1:K)
for(i in 1:K) rc.ar[[i]] = ar(ssaout$Rpc[,i])
# Fit a Normal to RPC 6 to 15
resid = apply(ssaout$Rpc[,(K+1):M],1,sum)
noise = fitdistr(resid,densfun = "normal")$estimate
hist(resid, probability = TRUE)
sm.density(rnorm(1000,noise[1],noise[2]),add = TRUE)
# Simulate 2001 to 2016
nsim = 250
pred.ahead = se.ahead = array(NA, c(K, 16, nsim))
sim = matrix(NA,nrow = nsim,ncol = 16)
for(isim in 1:nsim){
for(i in 1:K){
xp = predict(rc.ar[[i]],n.ahead = 16)
pred.ahead[i,,isim] = xp$pred
se.ahead[i,,isim] = xp$se
}
# Add all RPC and add noise (normally distributed)
sim[isim,] = colSums(pred.ahead[,,isim]) + rnorm(16,noise[1],noise[2])
}
# plot(sim,type = "l",ylim = c(0,max(sim,lf[96:111])))
# lines(lf[96:111],col = "red")
# legend(x="topleft",legend = c("Historic values",
# "Simulated values"),col=c("red","black"),lty = 1,bty="n")
The forecast is presented as boxplots. The correlation is calculated using the median values.
# Median correlation
boxplot(sim,names = seq(1:16)+2000)
title("Forecasted vs. real streamflows")
lines(lf[96:111],col="red")
points(lf[96:111],col="red")
sim.median = apply(t(sim),1,median) # Get median value of each step
cor(sim.median, lf[96:111]) # Correlation
## [1] 0.2562116
ssab = function(yy,M) {
#### SSA
N = length(yy)
m1 = M-1
Np = N-M+1
Np1 = Np+1
## create the lagged matrix
topl = matrix(0,Np,M)
for(i in 1:M){
i1=i-1+1
i2 = Np+i-1
topl[,i]=yy[i1:i2]
}
#zz=scale(topl)
zs=var(topl)
zsvd = svd(zs)
#Eigen Values.. - fraction variance
lambdas=(zsvd$d/sum(zsvd$d))
### PCs
At = topl %*% zsvd$u
#### Reconstructed Components RCs
Rpc = matrix(0,N,M)
for(ipc in 1:M){
## t = 1,M-1 mt = 1/t; lt = 1, ut =t
lt=1
m1 = M-1
for(i in 1:m1){
i1 = i-lt+1
i2 = i-i+1
Rpc[i,ipc] = sum(At[i1:i2,ipc]*zsvd$u[lt:i,ipc])/i
}
### t = M, N', mt = 1/M, lt = 1, ut = M
lt=1
ut=M
for(i in M:Np){
i1 = i-lt+1
i2 = i-M+1
Rpc[i,ipc] = sum(At[i1:i2,ipc]*zsvd$u[lt:ut,ipc])/M
}
### t = N'+1, N, mt = 1/(N-t+1), lt = t-N+M, ut = M
lt=1
ut=M
for(i in Np1:N){
lt = i-N+M
i1 = i-lt+1
i2 = i-M+1
mt = (N-i+1)
Rpc[i,ipc] = sum(At[i1:i2,ipc]*zsvd$u[lt:ut,ipc])/mt
}
}
out=c()
out$lambdas = lambdas
out$eof = zsvd$u
out$At = At
out$Rpc = Rpc
as.list(out)
}


--- layout: archive title: Zulip Chat Archive permalink: /stream/116395-maths/topic/finset.2Einter.html ---
import data.finset /- From data.finset: /-- `s ∩ t` is the set such that `a ∈ s ∩ t` iff `a ∈ s` and `a ∈ t`. -/ instance : has_inter (finset α) := ⟨λ s₁ s₂, ⟨_, nodup_ndinter s₂.1 s₁.2⟩⟩ -/ instance (X : Type*) : has_inter (finset X) := by apply_instance -- fails
Why can't I intersect finite sets?
decidable equality
rofl
thanks again
PS I'd just got there myself -- the annoying part is guessing the name of the instance because it's never explicitly named in mathlib. Could the name of the instance be put in the comments or is that crazy?
It wasn't hard to guess this time, but it's the only way I know of debugging these things
You can run #print instances has_inter
to find the name.
Last updated: Apr 24 2020 at 19:02 UTC


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the last few days = the PV state machine
Posted: Fri Nov 16, 2007 7:24 am
If you've done any kind of programming or digital design, you'll know that a state machine is a good way of designing the layout of a program before blindly going about implementing all of the program's parts. This is because it's essentially a road-map showing how entire application works. What I've been working on for the last couple of days (besides creating a single-cycle, 32-instruction microprocessor for one of my classes--which is bad bum by the way) is the state machine diagram for PV. So far, I have about 6 pages of states and state transitions I need to account for but I'm nearing a final draft of the machine. Once I complete it, if anyone's interested, I'll upload the results to the site so you can take a look at how the client's going to work.
Karl[/url]
Karl[/url]


Pig Dice: A game using object-oriented programming
Matchmaker: Dating quiz using branching
To-Do List: Object-oriented programming and tables
A native Portlander... I have spent most of my life playing and teaching classical music in the NW and around the world. When I am not root tootin' on the flute, I might be found living in the forest, drinking too much coffee, or working in an instrument repair shop.
In elementary school, I discovered how to edit HTML when making a cool Neopets guild site.
In middle school, I played with HTML while trying to decorate my awesome MySpace page.
In college, I took a basic computer programming class to avoid calculus.
A few years later, I found Epicodus and am taking my Neopets dreams to the next level!


{% load i18n %} {% blocktrans %} Your passwords do not match. Please check your passwords and try again. {% endblocktrans %}


According to Rasmussen College, the top 5 myths/sterotypes that women in computer science are: 1. Computer Science doesn't help people 2. Men are better quantitative thinkers than women 3. COmputer Science means working in isolation 4. Women's ideas are unwelcome 5. You must know how to code to work in technology But it is important to note that teach simply are not true. Women and men use computers, therefore womens input is just as important as mens.
These resources are here to explain and break the myths and sterotypes that women believe to be ture if they are going to join the field of STEM
"Many people claim they do not believe the stereotype that girls and women are not as good as boys and men in math and science. However, even individuals who consciously refute gender and science stereotypes can still hold that belief at an unconscious level."
Go somewhereSome quick example text to build on the card title and make up the bulk of the card's content.
Go somewhereSome quick example text to build on the card title and make up the bulk of the card's content.
Go somewhere


Recipe 1.10. Filtering a String for a Set of CharactersCredit: Jürgen Hermann, Nick Perkins, Peter Cogolo ProblemGiven a set of characters to keep, you need to build a filtering function that, applied to any string s, returns a copy of s that contains only characters in the set. SolutionThe TRanslate method of string objects is fast and handy for all tasks of this ilk. However, to call translate effectively to solve this recipe's task, we must do some advance preparation. The first argument to TRanslate is a translation table: in this recipe, we do not want to do any translation, so we must prepare a first argument that specifies "no translation". The second argument to TRanslate specifies which characters we want to delete: since the task here says that we're given, instead, a set of characters to keep (i.e., to not delete), we must prepare a second argument that gives the set complementdeleting all characters we must not keep. A closure is the best way to do this advance preparation just once, obtaining a fast filtering function tailored to our exact needs: import string # Make a reusable string of all characters, which does double duty # as a translation table specifying "no translation whatsoever" allchars = string.maketrans('', '') def makefilter(keep): """ Return a function that takes a string and returns a partial copy of that string consisting of only the characters in 'keep'. Note that `keep' must be a plain string. """ # Make a string of all characters that are not in 'keep': the "set # complement" of keep, meaning the string of characters we must delete delchars = allchars.translate(allchars, keep) # Make and return the desired filtering function (as a closure) def thefilter(s): return s.translate(allchars, delchars) return thefilter if _ _name_ _ == '_ _main_ _': just_vowels = makefilter('aeiouy') print just_vowels('four score and seven years ago') # emits: ouoeaeeyeaao print just_vowels('tiger, tiger burning bright') # emits: ieieuii DiscussionThe key to understanding this recipe lies in the definitions of the maketrans function in the string module of the Python Standard Library and in the translate method of string objects. TRanslate returns a copy of the string you call it on, replacing each character in it with the corresponding character in the translation table passed in as the first argument and deleting the characters specified in the second argument. maketrans is a utility function to create translation tables. (A translation table is a string t of exactly 256 characters: when you pass t as the first argument of a translate method, each character c of the string on which you call the method is translated in the resulting string into the character t[ord(c)].) In this recipe, efficiency is maximized by splitting the filtering task into preparation and execution phases. The string of all characters is clearly reusable, so we build it once and for all as a global variable when this module is imported. That way, we ensure that each filtering function uses the same string-of-all-characters object, not wasting any memory. The string of characters to delete, which we need to pass as the second argument to the translate method, depends on the set of characters to keep, because it must be built as the "set complement" of the latter: we must tell translate to delete every character that we do not want to keep. So, we build the delete-these-characters string in the makefilter factory function. This building is done quite rapidly by using the translate method to delete the "characters to keep" from the string of all characters. The translate method is very fast, as are the construction and execution of these useful little resulting functions. The test code that executes when this recipe runs as a main script shows how to build a filtering function by calling makefilter, bind a name to the filtering function (by simply assigning the result of calling makefilter to a name), then call the filtering function on some strings and print the results. Incidentally, calling a filtering function with allchars as the argument puts the set of characters being kept into a canonic string form, alphabetically sorted and without duplicates. You can use this idea to code a very simple function to return the canonic form of any set of characters presented as an arbitrary string: def canonicform(s): """ Given a string s, return s's characters as a canonic-form string: alphabetized and without duplicates. """ return makefilter(s)(allchars) The Solution uses a def statement to make the nested function (closure) it returns, because def is the most normal, general, and clear way to make functions. If you prefer, you could use lambda instead, changing the def and return statements in function makefilter into just one return lambda statement: return lambda s: s.translate(allchars, delchars) Most Pythonistas, but not all, consider using def clearer and more readable than using lambda. Since this recipe deals with strings seen as sets of characters, you could alternatively use the sets.Set type (or, in Python 2.4, the new built-in set type) to perform the same tasks. Thanks to the translate method's power and speed, it's often faster to work directly on strings, rather than go through sets, for tasks of this ilk. However, just as noted in Recipe 1.8, the functions in this recipe only work for normal strings, not for Unicode strings. To solve this recipe's task for Unicode strings, we must do some very different preparation. A Unicode string's translate method takes only one argument: a mapping or sequence, which is indexed with the code number of each character in the string. Characters whose codes are not keys in the mapping (or indices in the sequence) are just copied over to the output string. Otherwise, the value corresponding to each character's code must be either a Unicode string (which is substituted for the character) or None (in which case the character is deleted). A very nice and powerful arrangement, but unfortunately not one that's identical to the way plain strings work, so we must recode. Normally, we use either a dict or a list as the argument to a Unicode string's translate method to translate some characters and/or delete some. But for the specific task of this recipe (i.e., keep just some characters, delete all others), we might need an inordinately large dict or string, just mapping all other characters to None. It's better to code, instead, a little class that appropriately implements a _ _getitem_ _ method (the special method that gets called in indexing operations). Once we're going to the (slight) trouble of coding a little class, we might as well make its instances callable and have makefilter be just a synonym for the class itself: import sets class Keeper(object): def _ _init_ _(self, keep): self.keep = sets.Set(map(ord, keep)) def _ _getitem_ _(self, n): if n not in self.keep: return None return unichr(n) def _ _call_ _(self, s): return unicode(s).translate(self) makefilter = Keeper if _ _name_ _ == '_ _main_ _': just_vowels = makefilter('aeiouy') print just_vowels(u'four score and seven years ago') # emits: ouoeaeeyeaao print just_vowels(u'tiger, tiger burning bright') # emits: ieieuii We might name the class itself makefilter, but, by convention, one normally names classes with an uppercase initial; there is essentially no cost in following that convention here, too, so we did. See AlsoRecipe 1.8; documentation for the TRanslate method of strings and Unicode objects, and maketrans function in the string module, in the Library Reference and Python in a Nutshell. |


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This is one of those town which hides it charms until you venture beyond the waterfront. It is also backed by a modern developement which provides all city services.
Position 41°14'47"N, 16°30'39"E.
The Harbourmaster is based in the market building on the SE side of the harbour.
The Customs office is on the first floor overlooking the SW part of the harbour and the Police are in the town.
This harbour is not safe to enter in strong onshore winds which cause breaking seas at the entrance.
Good shelter, but some swell enters in strong east and north east winds.
Berth in the marina in the southern part of the harbour. Visitors are made very welcome here.
It is possible to anchor close north of the marina in about 2m.
Last updated July 2010.


[Stage 2:=============================> (1 + 1) / 2]17/06/09 06:48:54 WARN cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Container marked as failed: container_1496990795119_0001_02_000002 on host: slave1. Exit status: -1000. Diagnostics: Could not obtain block: BP-1759922210-<IP_ADDRESS>-1496717496059:blk_1073744745_3921 file=/user/ubuntu/.sparkStaging/application_1496990795119_0001/py4j-0.10.4-src.zip org.apache.hadoop.hdfs.BlockMissingException: Could not obtain block: BP-1759922210-<IP_ADDRESS>-1496717496059:blk_1073744745_3921 file=/user/ubuntu/.sparkStaging/application_1496990795119_0001/py4j-0.10.4-src.zip
The problem is more likely a lack of correlation between Spark’s request for RAM (driver memory + executor memory) and Yarn’s container sizing configuration. Yarn settings determine min/max container sizes, and should be based on available physical memory, number of nodes, etc. As a rule of thumb, try making the minimum Yarn container size 1.5 times the size of the requested driver/executor memory (in this case, 1.5 GB).
<property>
<name>yarn.nodemanager.resource.memory-mb</name>
<value>64512</value>
</property>
<property>
<name>yarn.scheduler.maximum-allocation-mb</name>
<value>51200</value>
</property>
<property>
<name>yarn.nodemanager.resource.cpu-vcores</name>
<value>6</value>
</property>


Introduction to Computers
We are living in an information age dependent upon digital information. Digital information
is electronic information, the result of computer processing. Every type of job relies upon
getting information, using it,managing it, and relaying information to others. Computers enable
the efficient processing and storage information.
The Four operations of computers are :


--- author: Capulet categories: app date: '2011-07-13 05:01:55' permalink: /2011/07/13/phonegap-and-worklight-enable-mobile-apps-for-the-enterprise/ slug: phonegap-and-worklight-enable-mobile-apps-for-the-enterprise status: publish title: PhoneGap and Worklight Enable Mobile Apps for the Enterprise type: post format: html tags_old: - PhoneGap integration - Shahar Kaminitz - worklight ---
Congratulations to Worklight who announced today that it now incorporates PhoneGap as part of its core technology. Worklight’s mobile app platform and tools provide an enterprise-grade solution that enables organizations to efficiently develop and deliver HTML5, hybrid and native smartphone and tablet applications.
“PhoneGap reduces much of the complexity of cross-platform development, while we complement with additional tools, integration, security and management capabilities. Our joint mobile solutions are an excellent fit for enterprises looking to take advantage of HTML5,” said Shahar Kaminitz, CEO at Worklight.
There's more on the integration here.
We’re so pleased that Worklight is using PhoneGap to help their customers and further enterprise adoption in the enterprise!
Worklight is an active member of the PhoneGap community and will continue to make contributions to the project.
Check out today's news announcement.


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[1]
The driving position and the leather seats are pretty comfortable.
[2]
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The overall interior is comfortable, stylish and spacious.
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Back seat comfort and entry exit are great.


'Sleepy Hollow' (1999)
A movie review by Walter Frith
<EMAIL_ADDRESS>Member of the 'Online Film Critics Society' http://www.ofcs.org
Tim Burton's films have always been filled with a sweet or sour amount of gothic prancing. The first 'Batman' movie he directed in 1989 was always balanced with a sense of fun even though it was dark enough to startle the most loyal fan of Bob Kane's comic book series. 'Batman Returns' in 1992 was a silly, repetitive and nasty assault on our senses with horrible villains, an incoherent script and some very bad overlapping on the part of Burton's direction. 'Pee Wee's Big Adventure' (1985), 'Beetlejuice' (1988), 'Edward Scissorhands' (1990) and 'Mars Attacks!' (1996) all have their audience and it's easy to love or hate any film directed by Tim Burton.
'Sleepy Hollow', set in 1799 and based on Washington Irving's story "The Legend of Sleepy Hollow" and adapted for the screen this time by Kevin Yagher and Andrew Kevin Walker, is the story of New York City Constable Icabod Crane (Johnny Depp) and his investigation into the stories about a headless horseman who is murdering people by decapitating them while charging in grand fashion on his horse. Crane is sent to upstate New York to investigate these disturbing events at the behest of a city judge (Christopher Lee). Some of the people Crane comes into contact with are Baltus Van Tassel (Michael Gambon), his wife Lady Van Tassel (Miranda Richardson), and their daughter Katrina (Christina Ricci). Lady Van Tassel is her stepmother and is a mysterious character who levels her own ideas about the headless horseman which are startling and fun to watch during the film's climax. Other interesting local characters are played by Jeffrey Jones, Casper Van Dien and Ian McDiarmid.
If you wanted to take the film seriously, you would have to look at the characters first and foremost and unfortunately, Depp's is the only interesting one in the whole picture. The film seems obsessed, almost addicted like an alcoholic would be, with showing the decapitation of heads again and again and again. The entire production is a well photographed but familiar looking Tim Burton piece where bad hair and pale expressions extend to the far ends of celluloid for maximum effect.
Perhaps the most impressive thing about this film is the cameo by Christopher Walken as the headless horseman. Many would argue it's a full blooded role, but in my mind, Walken's not on screen enough to be given major credit on screen and he isn't. He is to be given credit, however for his absolutely frightening portrayal of the film's chief villain (his teeth alone were hair raising). Burton directed Walken in 'Batman Returns' and Martin Landau also makes an uncredited cameo as a man who loses his head (literally!) in the film's opening scene. Landau won an Oscar under Burton's direction for 1994's 'Ed Wood'.
The element of beauty in this film is the cinematography by Emmanuel Lubezki and the editing by Chris Lebanzon. The work by these two is absolutely riveting and may bring them Oscar nominations. Credit also has to be given to Johnny Depp. He is a great performer and looks right at home in a period piece role as comfortably as any other part he has ever played. He adapts to the role of Icabod Crane as well as any actor could have. He combines intelligence, bravery in the face of horror and a straight laced portrayal of the law very well.
Any director deserves credit for putting his stamp on a film so well. The true key to a director's vision is for avid movie fans to view a film without the credits being shown and then trying to guess who the director is. That's easy when watching a Tim Burton film. If Burton hadn't been a movie director I see him in one of two professions in life.....designing fun houses for amusement parks or taking on the job of an architect, designing gothic looking structures with the most bizarre detail given to every part of his structures.
OUT OF 5 > * * * 1/2
Visit FILM FOLLOW-UP by Walter Frith http://www.cgocable.net/~wfrith/movies.htm
* * * * * - a must see * * * * 1/2 - don't miss it * * * * - an excellent film * * * 1/2 - a marginal recommendation * * * - can't quite recommend it * * 1/2 - don't recommend it * * - avoid it * 1/2 - avoid it seriously * - avoid it AT ALL COSTS 1/2 - see it at your own risk zero - may be hazardous to your health
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@import domain.Sitting @(assessment: Sitting)(implicit context: RequestContext) @frontend(s"${assessment.assessment.title} - Assessment finalised") {
You've already finalised your submission to this assessment, you cannot perform further actions.


Try to solve the puzzle by moving the cell through stroking keyboard [↑][↓][←][→] or mouse clicking a cell next to the dark one. The dark cell is at the bottom right of the image.


{extend name="public/common" /} {block name="warp"}
1. The details of the music upload service are made by{:config('web_site_name')}According to the actual situation,{:config('web_site_name')}Reserves the right to change, discontinue or terminate some or all of the music upload services at any time.
2. Users may not plagiarize or copy other works. The user must upload any music works must be based on the actual situation of the work clearly marked the author of the work, songwriters, singers, players, recorders and other works related rights and names of the work.
3. The user is solely responsible for it{:config('web_site_name')}The responsibility for the content published. User is right{:config('web_site_name')}The use of the service must comply with all applicable local laws, national laws and international law applicable to the service.
4. The User may upload music works indefinitely without violating the Copyright Law of the People's Republic of China and the relevant laws and regulations and the provisions of the Regulations on the Implementation of the Copyright Law of the People's Republic of China and the Regulations on the Protection of the Right of Information Network Transmission and You can edit unlimited, edit their own uploaded works.
5. The music that the user can upload includes the original works created by the user, the adapted works (including but not limited to the words or songs formed by the user's adaptation of the original music) and the derivative works (including but not limited to the user's singing Of the cover music).
6. The user shall upload the music works in accordance with the provisions of this article and shall ensure that the person who has made the work is the original person of the musical work or has obtained a legally authorized user.
7. When a user uploads a cover or a crooked piece of original music, the user should respect the integrity of the original musical work and respect and maintain the identity of the original songwriter and respect the performance of the original performer.
{:config('web_site_name')}Reserves the right of final interpretation of this Agreement. After you click the confirmation button, it means that it has signed this clause. The


Video title
This video is so epic. This video is so epic. This video is so epic. This video is so epic. This video is so epic. This video is so epic.
FACEBOOK / TWITTER / ETC.
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http://sectio.knedl.si/ud2
sect.io is the easyest way to get head.


| render_delayed {rmarkdown} | R Documentation |
In a Shiny document, evaluate the given expression after the document has finished rendering, instead of during render.
render_delayed(expr)
expr |
The expression to evaluate. |
This function is useful inside Shiny documents. It delays the evaluation of its argument until the document has finished its initial render, so that the document can be viewed before the calculation is finished.
Any expression that returns HTML can be wrapped in render_delayed
.
An object representing the expression.
expr
is evaluated in a copy of the environment in which
the render_delayed
call appears. Consequently, no side effects
created by expr
are visible in succeeding expressions, nor are
changes to the environment after the call to render_delayed
visible
to expr
.
expr
must be an expression that produces HTML.
## Not run: # Add the following code to an R Markdown document div(Sys.time()) render_delayed({ Sys.sleep(3) # simulate an expensive computation div(Sys.time()) }) div(Sys.time()) ## End(Not run)


Strictly's Aljaz Skorjanec dishes on Mike Bushell being booted off the show
The Strictly Come Dancing professional discussed Sunday night's results during an appearance on Heart radio
by Sara-Aisha Kent, https://www.mirror.co.uk/authors/sara-aisha-kent/Strictly Come Dancing's Aljaz Skorjanec has opened up on Mike Bushell being axed from the 2019 series of the hit dancing show.
The professional dished on Mike and Katya Jones being booted off following Sunday night's result show during an interview on Heart radio on Monday morning.
Aljaz, who was partnered up with Emma Weymouth until they became the sixth couple to be voted off, addressed the axing after host Jamie Theakston quizzed the Slovenian native if he thought Mike was relieved to say goodbye to the dancing floor.
He told: "I think yes and no, I think relieved maybe because he has done so many dance offs but not relieved because I think he should be so proud go how incredibly well he has done in the competition."
Jamie probed: "Is it fair to say it was his time? Looking at other contestants as well, it seemed like the right time, it seemed like the right time?"
 You want to stay in as many weeks as possible. Whatever dance you can learn and master is just a bonus. So I don’t think anyone is ever ready to leave Strictly!"
Reflecting on his own experience, he finished: "I don’t ever want to leave, ever!"
Aljaz's interview comes after Mike spoke out against reports he was "desperate" to leave Strictly Come Dancing .
The BBC sports presenter was said to be "relieved" after being sent packing by the judges on last night's result show.
But he has claimed that it couldn't be further from the truth.
Mike, who faced a dance off with Michelle Visage alongside his partner Katya, has said he's gutted that he didn't make it to Blackpool.
But he's delighted he lasted long enough to be added to the line-up for the live tour.
Mike said in a statement released to Mirror Online: "This is so far from the truth, it is a complete fabrication and without any foundation.
"I’ve loved every second of my Strictly journey, it the best show ever and I was really hoping to be competing in Blackpool and beyond.
"I’m gutted to be out but at the same time wanted to leave with head held high and gracious in defeat.
"When I was eliminated I wanted to celebrate the journey I’d been on, and the fact that I’m so excited to be doing the tour shows that I want my Strictly journey to go on."
It was reported that Mike, who was in the bottom two for the fourth this this weekend, had told friends he was glad it was all over.
Do you have a story to sell? Get in touch with us at<EMAIL_ADDRESS>or call us direct 0207 29 33033


FROM THE DESK OF: BARRISTER AMINU KANO PRICIPAL ASSOCIATE MIKE & CO. ATTN: I was privileged to capture your names from the Internet. My name is Barrister. aminu kano a legal Practitioner and the personal Attorney to late Mr.Steffen,a National of your country who died along with his wife and his Two sons in a ghastly motor accident over 3 years now (August 13,2000). All the occupants in the vehicle lost their lives. I am Convinced that it was the grace of God that made me to Locate you.. My client was a successful and am accomplished family man, Who made enough fortune before his untimely death? Since Then I had made several inquiries through your Embassy to locate any of my clients extended relative but this Exercise has proved unsuccessful. After several Unsuccessful attempts, I decided to trace his relatives Through the Internet, to locate any member of his Family not Much progress was recorded My late client was an Influential wealthy businessman, an oil magnet here in Nigeria and he left behind a deposit of Thirty two Million, Two Hundred Thousand United States Dollars only ($32,200,000.00usd) in his domiciliary bank account in a Commercial bank here in Lagos. After the death of my client his bankers contacted me, as his Attorney to provide his next of kin who should inherit His fortune. The board of directors of his bank adopted a Resolution and I was mandated to provide his next of kin for the payment of this money within 28 working days or Forfeit the money to the bank as an abandoned property. The Bankers had planned to invoke the abandoned property decree of 1996 to confiscate the funds after the expiration of the period given to me. Despairing at the point of, exhaustiveness, fortunately I came across your name. to my utmost amazement, I discovered That Coincidentally, you are nationals of the same country. I am Convinced that you may be linked with my late client or that you might provide clue to my search. Therefore, i decided to contact with these facts before me because of the Similarities .By virtue of my closeness to the deceased and His immediate family, I am very much aware of my client financial standing and The bank account he operates. I have reasoned very Professionally and I feel it will be legally proper to present you as the next of kin of my deceased client, so That you can be paid the funds left in his bank account, hence I contact you. I seek your consent to present you as the Next of Kin to the Deceased since you are at an advantage, hailing from the same country, so that the proceeds of this Bank Account valued at $32.2 Million Dollars can be paid to you. we shall both share the funds.25% to me and 60% to you, while 15% should be for Expenses or Tax as your Government may require, I shall Assemble all the necessary Legal Documents that will be Used to back up our claim. All I require is your honest cooperation to enable us see This deal through. I guarantee that this will be executed under a legitimate arrangement that will protect you from any breach of law. Best Regards BARRISTER AMINU KANO


MOD-CO is an app built by students as a part of their CI-102/103 project. This app was built to make the entire process of finding a CO-OP at Drexel University easier and to provide a mobile version of the SCDC database.
ResourcesDrexel Steinbright Career Development CenterDrexel College of Computing and InformaticsDrexel University


Plywood cabinetry makes the most of space in Brooklyn Loft for couple with two dogs
by Bridget CogleyNew York studio Dean Works has reorganised a former studio apartment in Brooklyn around a multi-functional plywood volume that forms arches, walls and cabinets.
Architect Brandon Dean, the founder of Dean Works, designed Brooklyn Loft for a young couple from Portland, Oregon that moved to the New York City, bringing with them two large dogs and a house full of belongings.
The studio inserted a large Baltic birch plywood volume into the apartment in the Clinton Hill neighbourhood to solve a number of problems, including creating more storage space and sectioning off a private sleeping area.
"They found a nice, sunny studio-loft in Brooklyn that felt right but lacked storage and a separate bedroom," Dean Works said.
"These requirements helped establish the design priorities early on; add desperately needed storage, create a space for sleeping, and preserve the loft 'feel'."
The wooden structure forms cabinets and countertops in a kitchen, and also acts as a room divider to a bedroom concealed behind double glass doors. The unit provides closets in the bedroom as well.
"The big design idea was to insert a storage wall that spatially separated but tectonically blended the new bedroom and kitchen," the studio added.
Brooklyn Loft is arranged to comprise the living area on one side, the bedroom on the opposite, and the kitchen in the middle.
Dean Works chose the humble wooden material to tie in with the couple's Baltic birch plywood table that they designed and built in Oregon. It is now seen in the open-plan dining and living room, just off the kitchen.
Plywood's tactility and simplicity informs the rest of the decor in the 920-square-foott (85-square-metre) apartment, which features white walls and exposed ductwork and pipes.
Existing wooden floors closely match the colouring of the veneered surfaces throughout, while grey and white are used prominently.
Plywood fronts the kitchen appliances, including the refrigerator, with only the oven exposed.
The kitchen island is topped with dark stone for contrast and anchors the heart of the apartment. White marble is used on the kitchen backsplash, sink counter and shelves.
Pops of red and blue are added to enliven the pared-down aesthetic.
Shane Neufeld of studio Light and Air Architecture also reorganised another Brooklyn apartment around a Birch plywood system, while practice New Affiliates redesigned another apartment in the borough to include plywood interiors.
Photography is by Daniel Salemi.
Project credits:
Architect: Brandon Dean, Dean Works
General Contractor: Orchester Management Company


A playground to test OAuth authentication for Windows Azure Marketplace "DataMarket" datasets and applications


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Android app that uses a camera to identify and solve Rubik's cubes.
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Easter egg!


Special keyword: repeat
¶
Important
AvantPy includes a restriction that all statements that begin with
repeat
must be on a single physical line ending with a colon that
introduces an indented block, with no other colon appearing on that line.
There is no technical reason for imposing this single-line limitation;
in fact, it does add some small complexity to AvantPy’s code.
However, by the time conditions on a repeat
statement become long enough
to warrant the use of additional lines, it is likely that students are ready
to use the appropriate Python construct.
However, this single-line limitation could be removed based on feedback from instructors. Nonetheless, the requirement that no other colon is allowed on that line would remain: it might not be flagged as an error but could give rise to incorrectly converted code.
Repeating a series of instructions is something that is often done when running programs. Block-based programming environments, such as Scratch, Blockly, GP, etc, have different blocks that can be used for this purpose. For example:
and a “repeat forever” loop in French:
Depending on the block-based environment one uses, there are up to four four main such cases, which can be written as follows in standard Python:
for _ in range(n):
'''Repeat a series of instruction n times, without having to
keep track of the specific iteration number
'''
while condition:
'''Repeat a series of instruction an unspecified number of times,
while a certain condition is met.
'''
while not condition:
'''Repeat a series of instruction an unspecified number of times,
until a certain condition is met.
'''
while True:
'''Repeat a series of instruction an unspecified number of times,
until a something inside the loop triggers a "break" to end the loop.
'''
Inspired by the choices made by creators of block-based programming environments, AvantPy introduces a few additional keywords to cover the 4 cases above in a natural way:
repeat n:
# code
repeat while condition:
# code
repeat until condition:
# code
repeat forever:
# condition
Note
Learning from experts
The Quorum computing language has been designed based on evidence gathered from how human learn programming languages.
It includes three of the four repeat choices mentioned above, with a slightly different syntax:
repeat 10 times
// code
end
repeat while condition
// code
end
repeat until condition
// code
end
A concrete example¶
Suppose that I am teaching programming to beginners using Python’s turtle module. So far, we’ve only written programs that use one instruction per line:
from turtle import forward, left
# Draw a square
forward(100)
left(90)
forward(100)
left(90)
forward(100)
left(90)
forward(100)
left(90)
I wish to use this to show to students how we can have computers repeat a given set of instructions, instead of typing them multiple times. Using Python, here’s the natural way to do this:
from turtle import forward, left
# Draw a square
for variable in range(4):
forward(100)
left(90)
In doing so, I need to introduce all at once many new concepts and additional terms:
the concept of an indented code block preceded by a colon;
two keywords,
for
andin
;the use of a variable, which is some quantity with a completely irrelevant name in this example, except that it cannot be a keyword;
the introduction of a built-in function,
range()
, which, unlikeforward()
orleft()
, does not have a visual representation.
By contrast, using the repeat
keyword, the above can be written as:
from turtle import forward, left
# Draw a square
repeat 4:
forward(100)
left(90)
and we only need to introduce fewer new topics:
the concept of an indented code block preceded by a colon;
one new keyword:
repeat
.
More gradual approach¶
As we are writing this, we note that
GP control blocks
include the following blocs which allow for a gradual
interpolation between something like repeat 10:
and the
more complex and versatile Python idiom:
for i in range(1, 10, step):
# some
# code
However, we do not see the need to include this type of granularity in AvantPy.
A final word¶
We’ve already mentioned the usage in blocks-based programming environment
of repeat
, or some similar alternative in other languages. repeat
was also the clearer possibility for people unfamiliar with programming jargon
as found by Andreas Stefik and Susanna Siebert, and published
“An Empirical Investigation into Programming Language Syntax.”
ACM Transactions on Computing Education, 13(4), Nov. 2013.


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Full width row of banners
2016 Chesapeake Regional Champions
2016 Innovation in Control (Regional)
2016 Bethesda District Champions
2016 Industrial Design (Bethesda)
2016 District of Columbia Champs
2016 Innovation in Control (DC)
2016 Chesapeake Regional Champions
2016 Innovation in Control (Regional)
2016 Bethesda District Champions
2016 Industrial Design (Bethesda)
2016 District of Columbia Champs
2016 Innovation in Control (DC)
2016 Chesapeake Regional Champions
2016 Innovation in Control (Regional)
2016 Bethesda District Champions
2016 Industrial Design (Bethesda)
2016 District of Columbia Champs
2016 Innovation in Control (DC)


{% load staticfiles %}
Dcode, A Syntax Highlighting App Supports All Programming Language
Simple Crypto Currency Exchanging Web App, Design To Demonstrate Blockchain Based Ledgers Implementations


My name is Jesse Kamau. Mathematics and computer science have always been a big part of my life and knowing that both disciplines require in-depth problem solving meant that I had a very simple decision when it came to choosing degree. As an individual I enjoy the feeling of accomplishment which I receive when I solve a problem, it makes me crave more hence why I wish to expand my knowledge further more in Computer Science and Mathematics. Personally I am a highly committed individual who can work well independently or as part of a team and able to self-teach how to programme in different programming languages.
Throughout my years I have been involved in various sporting actives and outside of my academic life I have been apart of a football for many years, and in my career me and my team have won trophies, and through this club I learnt how to work efficiently as a team and also respect for others and officials. I have brought all these skills into my academic life which has enabled me to improve my whole.
I first learned how to program back in secondary school, the passion still remains to this day. I hope to develop useful software in the near future. I have many interests when it comes to coding in general. I enjoy front-end development and UI design very much because of the freedom I have to paint my vision. I also am very fond of complex backend systems that require critical thinking skills and logic.
Assembling all the machine learning pieces needed to solve a problem can be a daunting task. In this series of articles, we are walking through implementing a machine learning workflow using a real-world dataset to see how the individual techniques come together.
A.I. bots in gaming are usually built by hand-coding a bunch of rules that impart game-intelligence. For the most part, this approach does a fairly good job of making the bot imitate human-like behavior. However, for most games it is still easy to tell apart a bot from an actual human playing.
There are a lot of computer science graduates and programmers applying for programming, coding, and software development roles at startups like Uber and Netflix; big organizations like Amazon, Microsoft, and Google; and service-based companies like Infosys or Luxsoft, but many of them have no idea of what kind of programming interview questions to expect when you’re applying for a job with these companies.


public class MssoContext
extends java.lang.Object
executeRequest(Bundle, MASRequest)
method will process an outbound
web API request. This may take a long time and involve multiple round trips to the token server, and should not
be executed on the UI thread.
To simplify running remote calls in the background from an Activity, the MssoClient and HttpResponseFragment
are provided.| Modifier and Type | Method and Description |
|---|---|
void |
clearAccessToken()
Clear the access token, forcing the next request to obtain a new one.
|
void |
clearClientCredentials() |
void |
clearCredentials() |
void |
clearIdToken() |
void |
clearUserProfile() |
void |
close()
Shut down the context.
|
void |
destroyAllPersistentTokens()
Clear all tokens in the shared token store.
|
void |
destroyPersistentTokens()
Clear all tokens in the shared token store which associate with the current connected gateway.
|
MASResponse |
executeRequest(android.os.Bundle extra,
MASRequest request)
Add an access token to the specified outbound request, transmit it to the target server, and return
the response.
|
java.lang.String |
getAccessToken()
Get an access token, if one is presently available.
|
long |
getAccessTokenExpiry()
Get the access token expiry date, if one is available.
|
java.lang.Long |
getClientExpiration() |
java.lang.String |
getClientId() |
java.lang.String |
getClientSecret() |
ConfigurationProvider |
getConfigurationProvider()
Get the configuration provider.
|
MASAuthCredentials |
getCredentials() |
java.lang.String |
getDeviceName() |
java.lang.String |
getGrantedScope() |
IdToken |
getIdToken() |
MAGHttpClient |
getMAGHttpClient()
Get an HTTP client configured to trust server certs per our configuration, and to present a client
cert for mutual auth if one is available in our token store.
|
java.lang.String |
getRefreshToken() |
java.lang.String |
getStoredClientId() |
TokenManager |
getTokenManager()
Get the token manager that will be used to persist keys, cert chains, and OAuth tokens.
|
void |
init(android.content.Context context)
Initialize the context.
|
void |
initPolicyManager() |
boolean |
isClientCredentialExpired(java.lang.Long clientExpiration) |
boolean |
isDeviceRegistered()
Check if the device has already been registered.
|
boolean |
isInitialized()
Check if this context has been initialized.
|
boolean |
isLogin()
Check if the user has already been logon.
|
static MssoContext |
newContext()
Create a new MssoContext.
|
void |
onAccessTokenAvailable(java.lang.String accessToken,
java.lang.String refreshToken,
long expiresInSec,
java.lang.String grantedScope)
Notify that an access token was just obtained.
|
void |
onDeviceRegistrationCompleted()
Notify that device registration has just completed.
|
void |
onIdTokenAvailable(IdToken idToken)
Notify that an ID token is now available.
|
void |
removeDeviceRegistration()
Remove this device registration from the server.
|
void |
resetHttpClient()
Reset the HTTP client, causing a new one to be created.
|
void |
setClientCredentials(ClientCredentials clientCredentials) |
void |
setCredentials(MASAuthCredentials credentials) |
java.lang.String |
takeRefreshToken()
Take and consume the refresh token, if one is available.
|
public static MssoContext newContext()
init(android.content.Context)
public boolean isInitialized()
public void init(android.content.Context context)
context
- a context, for accessing system services such as telephony and location. Required.
The context must have a lifetime at least as long as this MssoContext.
Typically this means you should not pass an Activity as the context unless you
plan to close this MssoContext when the activity is destroyed.MssoException
- if the token store cannot be preparedpublic void initPolicyManager()
public void close()
public TokenManager getTokenManager()
public java.lang.String getDeviceName()
init(android.content.Context)
has not yet been called.public void clearUserProfile()
public void clearIdToken()
public IdToken getIdToken()
public MASAuthCredentials getCredentials()
public void setCredentials(MASAuthCredentials credentials)
public void clearCredentials()
public boolean isDeviceRegistered()
public void resetHttpClient()
public MAGHttpClient getMAGHttpClient()
public void onIdTokenAvailable(IdToken idToken) throws JWTValidationException
idToken
- the ID token. Required.JWTValidationException
public void onDeviceRegistrationCompleted()
public void onAccessTokenAvailable(java.lang.String accessToken, java.lang.String refreshToken, long expiresInSec, java.lang.String grantedScope)
accessToken
- the access token that was obtained. Required.refreshToken
- the refresh token to use to obtain a new access token. Required.expiresInSec
- number of seconds until the access token should be considered expired. Required.public void clearAccessToken()
public java.lang.String getAccessToken()
public long getAccessTokenExpiry()
public java.lang.String getGrantedScope()
public java.lang.String takeRefreshToken()
public java.lang.String getRefreshToken()
public ConfigurationProvider getConfigurationProvider()
public MASResponse executeRequest(android.os.Bundle extra, MASRequest request) throws java.lang.Exception
request
- the request to decorate and send. Required.MAGStateException
- if the request cannot be completed in the current MSSO state
(for example, if a username and password must be provided, or if the token store needs to be unlocked).java.io.IOException
- if there is an error communicating with the target server.java.lang.Exception
public void removeDeviceRegistration()
destroyAllPersistentTokens()
.
The communication with the token server will occur on the current thread. As this may take some time,
callers running on the UI thread should consider running this method within an AsyncTask.MssoException
- if there is an error while attempting to tell the token server to unregister this device.public void destroyAllPersistentTokens()
#logout
method instead.MssoException
- if there is an error while accessing the storage .public void destroyPersistentTokens()
#logout
method instead.MssoException
- if there is an error while accessing the storage .public boolean isLogin()
public void setClientCredentials(ClientCredentials clientCredentials)
public java.lang.String getStoredClientId()
public java.lang.String getClientId()
public java.lang.String getClientSecret()
public java.lang.Long getClientExpiration()
public void clearClientCredentials()
public boolean isClientCredentialExpired(java.lang.Long clientExpiration)


††††††††††† Haemagglutinin is key to the infectivity of influenza A virus.† A surface fusion glycoprotein embedded in the envelope of the virus, haemagglutinin must first be cleaved by the hostís trypsin-like proteases for the virus to be infectious.† In fact, the infectivity and pathogenicity of the virus is largely determined by the hostís trypsin-like proteases.† The processing of haemagglutinin by these proteases takes place on the membranes of the hostís airway epithelial cells, where haemagglutinin glycoprotein (HA0) is cleaved to produce HA1 and HA2 peptides.† The newly exposed N-terminal of the HA2 fusion peptide then acts to fuse the viral envelope to the cellular membrane of the host cell.† Once the membranes have fused, the virusí genetic material, negative-stranded RNA, can invade and take control of the host cell.†
††††††††††† Both the type and distribution of trypsin-like proteases in the host, as well as the susceptibility of HA0 to these enzymes, determine the infectivity and pathogenicity of the influenza virus.† Several different trypsin-like proteases can act on haemagglutinin, where both the tissues in which they act (e.g. epithelial or neuronal cell) and the position of cleavage of HA will affect the infectivity of the virus.† For instance, proteases present in the brain can cause the infection to take root there (in addition to epithelial cells), while the position of cleavage by the protease can determine how well it binds to receptors on the host cell in order to infect it.† Trypsin-like proteases known to cleave HA0 include tryptase Clara, mini-plasmin, ectopic anionic trypsin, mast cell tryptase, tryptase TC30, and brain trypsin I, the latter being a possible candidate for the rare cases of encephalitis that are associated with certain strains of the virus.† Most strains of influenza A are pneumotropic, localising the infection to airway epithelial cells, but a few strains can multiply in both airway epithelial cells and in neuronal cells, causing life-threatening encephalitis, such as occurred in the devastating 1918 Spanish Influenza pandemic.†
††††††††††† Haemagglutinin itself also determines the pathogenicity of the virus, which varies from avirulent strains to lethal ones, providing a genetic mechanism for the variation in viral virulence (although other viral proteins affect virulence as well). The differences between strains are primarily determined by the amino acid sequence at the HA0 cleavage site, where the precise linkage of HA to host receptors determines species preference.† For example, a switch in receptor specificity from receptors containing sialic acids connected to galactose in a a2-3 linkage (avian receptors) to a a2-6 linkage (human receptors) is required for influenza A virus to cross the species barrier in adapting to a human host Ė this requires adaptation in the binding capacity of HA.
††††††††††† The second major surface glycoprotein found on the influenza A viral envelope is neuraminidase. †This protein promotes the release of progeny virus from the host cell during the final stages of viral replication.† In addition, there is increasing evidence that neuraminidase can promote virus entry into host cells during the initial stage of infection.†
††††††††††† In particular, when a variant of the 1918 Spanish Influenza pandemic strain H1N1 was analysed, the neuraminidase was found to directly bind plasminogen, sequestering the protease precursor to achieve a higher local concentration.† The active form of the protease, plasmin, could then cleave and activate haemagglutinin, thereby promoting the viral infection of host cells. †This unusual function of neuraminidase was found to have a molecular basis, involving the appearance of a C-terminal lysine and the absence of an oligosaccharide side chain at another position on the neuraminidase molecule.† Such changes allowed the virus to infect cells other than its usual targets, and showed a possible means of how the virus could become highly pathogenic in humans.
††††††††††† Therefore, the ability of influenza A virus to cross the species barrier to yield a human-adapted variant involves several mechanisms, including variation in host proteases, variations in viral haemagglutinin and neuraminidase, as well as variations in several other viral proteins, not to mention the complex interplay of environmental factors.
†††††††††††


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A new standard being developed in a W3C Community Group with Apple, Google, Microsoft and Mozilla which defines:
Is just a postorder serialization of an AST. They claim its better than Java bytecode.
Great! Firefox and Chrome has Wasm support under flags. For the compiler follow the step by step.
Callstack and machine code is not in address space.
The only dangerous opcodes are .load
and .store
operations, as they index into memory. They employ a cool trick in 64bit
machines: mmap 4GBs of continouos virtual memory, you can't over-index
that with an i32 address. Runtime bound-checks on 32bits.
emcc -s BINARYEN=1 -s 'EXPORTED_FUNCTIONS=["_fib"]' fib.c -o fib.js
function module(global, env, buffer) {
"use asm";
...
function fib(n) {
n = n|0;
var a = 0, b = 1, t = 0;
while ((n|0) >= 0) {
t = b;
b = (a + b)|0;
a = t;
n = (n - 1)|0;
}
return b|0;
}
return {fib: fib};
}


--- # example 404.md layout: default permalink: /404.html ---
Looks like my gerbils couldn't find the page you were looking for!


I am a Computer Science graduate student at ENSEIRB-MATMECA, one of the 8 graduate schools of Bordeaux Institute of Technology. I have a BSc in Engineering Sciences, and will graduate with my master's degree in Septembre 2017. Beyond the classic knowledge of data structures, algorithms, programming paradigms, etc, I have a specialization in High Performance Computing, which means I am used to working with vectorisation instruction sets, implementations of BLAS/LAPACK/ScaLAPACK, pThreads, openMP, MPI, Cuda/openCL and Slurm to make the most out of a machine or a cluster of machines.
Below, you will find a few of the academic projects I have worked on throughout my studies.


Need help coming up with a good one? Try a generator like this one at fourmilab.ch, the one from passphra.se, or this one at correcthorsebatterystaple.net.
(This would be where we might add the OAuth signin buttons, and tell people they don't need to type in their email and remember a password...)


This section provides a very short overview of the algorithms used by the Enzo code. References to texts and journal articles providing a more complete discussion of the algorithms are included at the end of this page for the interested reader. As of this writing (January 2004) a formal Enzo method paper has not been published, but is in preparation. Much of the text and images on this page have been taken from one of the Laboratory for Computational Astrophysics contributions to the 2003 AMR conference.[1]
Enzo is written in a mixture of C++ and Fortran 77. High-level functions and data structures are implemented in C++ and computationally intensive lower-level functions are written in Fortran. Enzo is parallelized using the MPI message-passing library and uses the HDF 5 data format to write out data and restart files in a platform-independent format.
Enzo allows hydrodynamics in 1, 2 and 3 dimensions using the structured adaptive mesh refinement (SAMR) technique developed by Berger and Collela. [2] The code allows arbitrary integer ratios of parent and child grid resolution and mesh refinement based on a variety of criteria, including baryon and dark matter overdensity or slope, the existence of shocks, Jeans length, and cell cooling time. The code can also have fixed static nested subgrids, allowing higher initial resolution in a subvolume of the simulation. Refinement can occur anywhere within the simulation volume or in a user-specified subvolume.
The AMR grid patches are the primary data structure in \enzo. Each individual patch is treated as an individual object, and can contain both field variables and particle data. Individual patches are organized into a dynamic distributed AMR mesh hierarchy using arrays of linked lists to pointers to grid objects. The code uses a simple dynamic load-balancing scheme to distribute the workload within each level of the AMR hierarchy evenly across all processors.
Although each processor stores the entire distributed AMR hierarchy, not all processors contain all grid data. A grid is a real grid on a particular processor if its data is allocated to that processor, and a ghost grid if its data is allocated on a different processor. Each grid is a real grid on exactly one processor, and a ghost grid on all others. When communication is necessary, MPI is used to transfer the mesh or particle data between processors. The tree structure of a small illustrative 2D AMR hierachy - six total grids in a three level hierarchy distributed across two processors - is shown on the left in Figure 1.
Each data field on a real grid is an array of zones with dimensionality equal to that of the simulation (typically 3D in cosmological structure formation). Zones are partitioned into a core block of real zones and a surrounding layer of ghost zones. Real zones are used to store the data field values, and ghost zones are used to temporarily store values from surrounding areas, ie, neighboring grids, parent grids or external boundary conditions, when required for updating real zones. The ghost zone layer is three zones deep in order to accomodate the computational stencil in the hydrodynamics solver (See below), as indicated in the right panel in Figure 1. These ghost zones can lead to significant computational and storage overhead, especially for the smaller grid patches that are typically found in the deeper levels of an AMR grid hierarchy.
For more information on Enzo implementation and data structures, see references [3], [4], [5] and [6]
The dynamics of large-scale structures are dominated by dark matter, which accounts for approximately 85% of the matter in the universe but can only influence baryons via gravitational interaction. There are many other astrophysical situations where gravitational physics is important as well, such as galaxy collisions, where the stars in the two galaxies tend to interact in a collisionless way.
Enzo uses the Particle-Mesh N-body method to calculate collisionless particle dynamics. This method follows trajectories of a representative sample of individual particles and is much more efficient than a direct solution of the Boltzmann equation in most astrophysical situations. The particle trajectories are controlled by a simple set of coupled equations (for simplicity, we omit cosmological terms):
and
Where xp and vp are the particle position and velocity vectors, respectively, and the term on the right-hand side of the second equation is the gravitational force term. The solution to this can be found by solving the elliptic Poisson's equation:
where ρ is the density of both the collisional fluid (baryon gas) and the collisionless fluid (particles).
These equations are finite-differenced and for simplicity are solved with the same timestep as the equations of hydrodynamics. The dark matter particles are sampled onto the grids using the triangular-shaped cloud (TSC) interpolation technique to form a spatially discretized density field (analogous to the baryon densities used to calculate the equations of hydrodynamics) and the elliptical equation is solved using FFTs on the triply periodic root grid and multigrid relaxation on the subgrids. Once the forces have been computed on the mesh, they are interpolated to the particle positions where they are used to update their velocities.
The primary hydrodynamic method used in Enzo is based on the piecewise parabolic method (PPM) of Woodward & Colella [7] which has been significantly modified for the study of cosmology. The modifications and several tests are described in much more detail in [8], and we recommend that the interested reader look there.
PPM is a higher-order-accurate version of Godunov's method with third-order-accurate piecewise parabolic monotolic interpolation and a nonlinear Riemann solver for shock capturing. It does an excellent job capturing strong shocks and outflows. Multidimensional schemes are built up by directional splitting, and produce a method that is formally second-order-accurate in space and time and explicitly conserves energy, momentum and mass flux. The conservation laws for fluid mass, momentum and energy density are written in comoving coordinates for a Friedman-Robertson-Walker spacetime. Both the conservation laws and Riemann solver are modified to include gravity, which is calculated as discussed above.
There are many situations in astrophysics, such as the bulk hypersonic motion of gas, where the kinetic energy of a fluid can dominate its internal energy by many orders of magnitude. In these situations, limitations on machine precision can cause significant inaccuracy in the calculation of pressures and temperatures in the baryon gas. In order to address this issues, Enzo solves both the internal gas energy equation and the total energy equation everywhere on each grid, at all times. This dual energy formalism ensures that the method yields the correct entropy jump at strong shocks and also yields accurate pressures and temperatures in cosmological hypersonic flows. See reference [8] for more information about the dual energy formalism.
As a check on our primary hydrodynamic method, we also include an implementation of the hydro algorithm used in the Zeus astrophysical code. [9], [10] This staggered grid, finite difference method uses artificial viscosity as a shock-capturing technique and is formally first-order-accurate when using variable timesteps (as is common in structure formation simulations), and is not the preferred method in the Enzo code.
The cooling and heating of gas is extremely important in astrophysical situations. To this extent, two radiative cooling models and several uniform ultraviolet background models have been implemented in an easily extensible framework.
The simpler of the two radiative cooling models assumes that all species in the baryonic gas are in equilibrium and calculates cooling rates directly from a cooling curve assuming Z = 0.3 Zo. The second routine, developed by Abel, Zhang, Anninos & Norman [11], assumes that the gas has primordial abundances (ie, a gas which is composed of hydrogen and helium, and unpolluted by metals), and solves a reaction network of 28 equations which includes collisional and radiative processes for 9 seperate species (H, H+, He, He+, He++, H-, H2+, H2, and e-). In order to increase the speed of the calculation, this method takes the reactions with the shortest time scales (those involving H- and H2+) and decouples them from the rest of the reaction network and imposes equilibrium concentrations, which is highly accurate for cosmological processes. See [11] and [12] for more information. The vast majority of the volume of the present-day universe is occupied by low-density gas which has been ionized by ultraviolet radiation from quasars, stars and other sources. This low density gas, collectively referred to as the ``Lyman-α Forest'' because it is primarily observed as a dense collection of absorption lines in spectra from distant quasars (highly luminous extragalactic objects), is useful because it can be used to determine several cosmological parameters and also as a tool for studying the formation and evolution of structure in the universe (see [13] for more information). The spectrum of the ultraviolet radiation background plays an important part in determining the ionization properties of the Lyman-α forest, so it is very important to model this correctly. To this end, we have implemented several models for uniform ultraviolet background radiation based upon the models of Haardt & Madau [14].
One of the most important processes when studying the formation and evolution of galaxies (and to a lesser extent, groups and clusters of galaxies and the gas surrounding them) is the formation and feedback of stars. We use a heuristic prescription similar to that of Cen & Ostriker [15] to convert gas which is rapidly cooling and increasing in density into star ``particles'' which represent an ensemble of stars. These particles then evolve collisionlessly while returning metals and thermal energy back into the gas in which they formed via hot, metal-enriched winds.
Enzo uses a grid-based parallelization scheme for load balancing. The root grid is partitioned up into N pieces (where N is the number of processors), and each processor is given a piece of the root grid, which it keeps for the duration of the simulation run. Subgrids are treated as independent objects and are distributed to the processors such that each level of grids is load-balanced across all processors. Boundary fluxes between neighboring grid patches and parent and children grids are passed back and forth using MPI commands.
The one portion of the code that is parallelized differently is the root grid gravity solver. As discussed above, the gravitational potential on the root grid is solved using a fourier transform method, which requires its own message-passing routines. The three-dimensional total density field (composed of the dark matter plus baryon density on the root grid) is decomposed into two-dimensional slabs (requiring one set of messages), which are then fourier transformed. The slabs are then transposed along another axis (requiring a second set of messages to be passed) and transformed again, and a third set of messages is required in order to obtain the original block decomposition. This is unavoidable when using a fourier transform scheme, and as a result the speed of the root grid gravity solver is very sensitive to the speed of the communication network on the platform that Enzo is being run on.
A somewhat detailed description of the method Enzo uses to create initial conditions can be downloaded as a postscript or PDF document. To summarize: Dark matter particles and baryon densities are laid out on a uniform Cartesian grid. Given a user-specified power spectrum P(k), the linear density fluctuation field is calculated at some initial time (typically z = 100 for high-resolution/small box simulations) by using P(k) to obtain the density fluctuations in k-space on a uniform Cartesian grid. P(k) is sampled discretely at each grid point, with the density fluctuations having a random complex phase and amplitude. The amplitude is generated such that the distribution of amplitudes is Gaussian. This cube is then fourier transformed to give physical density fluctuations. Particle positions and velocities and baryon velocities are calculated using the Zel'Dovich approximate. See the document above, or read Bertschinger 1998 [16] for more information.
[1] B. W. O'Shea et al. "Introducing Enzo, an AMR Cosmology
Application." To be published in Adaptive Mesh Refinement - Theory And Applications,
the proceedings from the 2003 University of Chicago AMR Workshop
[2] M. J. Berger and P. Colella. "Local adaptive mesh refinement for shock hydrodynamics,"
J. Comp. Phys, 82:64-84, 1989
[3] G. L. Bryan. "Fluids in the universe: Adaptive mesh in Cosmology."
Computing in Science and Engineering, 1:2, 1999
[4] G. L. Bryan and M. L. Norman. "A hybrid AMR application for cosmology and astrophysics."
In Workshop on Structured Adaptive Mesh Refinement Grid Methods", p. 165.
IMA Volumes in Mathematics #117, 2000
[5] G. L. Bryan and M. L. Norman. In D.A. Clarke and M. Fall, editors,
Computational Astrophyiscs: 12th Kingston Meeting on Theoretical Astrophysics,
proceedings of a meeting held in Halifax; Nova Scotia; Canada Oct. 17-19, 1996.
ASP Conference Series #123, 1997
[6] M. L. Norman and G. L. Bryan. "Cosmological Adaptive Mesh Refinement."
In Kohji Tomisaka, Shoken M. Miyama and Tomoyuki Hanawa, editors,
Numerical Astrophysics: Proceedings of the International Conference on Numerical Astrophysics 1998,
p. 19. Kluwer Academics, 1999
[7] P. R. Woodward and P. Colella. "A piecewise parabolic method for gas dynamical simulations,"
J. Comp. Phys, 54:174, 1984
[8] G. L. Bryan, M. L. Norman, J. M. Stone, R. Cen and J. P. Ostriker. "A piecewise
parabolic method for cosmological hydrodynamics,"
Comp. Phys. Comm., 89:149, 1995
[9] J. M. Stone and M. L. Norman. "Zeus-2D: A radiation magnetohydrodynamics code for
astrophysical flows in two space dimensions. I. The hydrodynamics algorithms and tests."
The Astrophysical Journal, 80:753, 1992
[10] J. M. Stone and M. L. Norman. "Zeus-2D: A radiation magnetohydrodynamics code for
astrophysical flows in two space dimensions. II. The magnetohydrodynamic algorithms and tests."
The Astrophysical Journal, 80:791, 1992
[11] T. Abel, P. Anninos, Y. Zhang and M.L. Norman. "Modeling primordial gas in numerical cosmology."
New Astronomy, 2:181-207, August 1997
[12] P. Anninos, Y. Zhang, T. Abel and M.L. Norman. "Cosmological hydrodynamics with multispecies chemistry
and nonequilibrium ionization and cooling." New Astronomy, 2:209-224, August 1997
[13] M. Rauch. "The Lyman Alpha Forest in the Spectra of QSOs." Annual Review of Astronomy and
Astrophysics, 36:267-316, 1998
[14] F. Haardt and P. Madau. "Radiative Transfer in a Clumpy Universe, II. The Ultraviolet Extragalactic
Background." The Astrophysical Journal, 461:20, 1996
[15] R. Cen and J.P. Ostriker. "Galaxy formation and physical bias." The Astrophysical Journal Letters, 399:L13, 1992
[16] E. Bertschinger. "Computer Simulations in Cosmology." Annual Review of Astronomy and Astrophysics, 36:599
Previous - Index
Next - Generating Initial conditions


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Checkout the recipe and cook at your favorite place...
Enjoy you homemade with your loved ones...


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SimpleParse is a BSD-licensed Python package
providing a simple and fast parser generator using a modified version
of the mxTextTools
text-tagging engine. SimpleParse allows you to generate parsers
directly from your
EBNF grammar.
Unlike most parser generators, SimpleParse generates single-pass parsers (there is no distinct tokenization stage), an approach taken from the predecessor project (mcf.pars) which attempted to create "autonomously parsing regex objects". The resulting parsers are not as generalized as those created by, for instance, the Earley algorithm, but they do tend to be useful for the parsing of computer file formats and the like (as distinct from natural language and similar "hard" parsing problems).
As of version 2.1.0 the SimpleParse project includes a patched copy
of the mxTextTools tagging library with the non-recursive rewrite of
the core parsing loop. This means that you will need to build the
extension module to use SimpleParse, but the effect is to provide a
uniform parsing platform where all of the features of a give
SimpleParse version are always available.
For those interested in working on the project, I'm actively interested in welcoming and supporting both new developers and new users. Feel free to contact me.
You will need a copy of Python with distutils support (Python versions 2.0 and above include this). You'll also need a C compiler compatible with your Python build and understood by distutils.
To install the base SimpleParse engine, download the latest version in your preferred format. If you are using the Win32 installer, simply run the executable. If you are using one of the source distributions, unpack the distribution into a temporary directory (maintaining the directory structure) then run:
setup.py install
in the top directory created by the expansion process. This
will cause the patched mxTextTools library to be built as a sub-package
of the simpleparse package and will then install the whole package to
your system.
New in 2.1.0a1:
New in 2.0.1:
diff -w -r1.4 error.py
32c32
< return '%s: %s'%( self.__class__.__name__, self.messageFormat(message) )
---
> return '%s: %s'%( self.__class__.__name__, self.messageFormat(self.message) )
New in 2.0:
General
Our (current) parsers are top-down, in that they work from the top
of the parsing graph (the root production). They are not, however,
tokenising parsers, so there is no appropriate LL(x) designation as far
as I can see, and there is an arbitrary lookahead mechanism that could
theoretically parse the entire rest of the file just to see if a
particular character matches). I would hazard a guess that they
are theoretically closest to a deterministic recursive-descent parser.
There are no backtracking facilities, so any ambiguity is handled by
choosing the first successful match of a grammar (not the longest, as
in most top-down parsers, mostly because without tokenisation, it would
be expensive to do checks for each possible match's length). As a
result of this, the parsers are entirely deterministic.
The time/memory characteristics are such that, in general, the time
to parse an input text varies with the amount of text to parse. There
are two major factors, the time to do the actual parsing (which, for
simple deterministic grammars should be close to linear with the length
of the text, though a pathalogical grammar might have radically
different operating characteristics) and the time to build the results
tree (which depends on the memory architecture of the machine, the
currently free memory, and the phase of the moon). As a rule,
SimpleParse parsers will be faster (for suitably limited grammars) than
anything you can code directly in Python. They will not generally
outperform grammar-specific parsers written in C.
mxTextTools Rewrite Enhancements
Alternate C Back-end?
NOTE: This section only applies to SimpleParse versions before 2.1.0, SimpleParse 2.1.0 and above include a patched version of mxTextTools already!
You will want an mxBase 2.1.0 distribution to run SimpleParse, preferably with the non-recursive rewrite. If you want to use the non-recursive implementation, you will need to get the source archive for mxTextTools. It is possible to use mxBase 2.0.3 with SimpleParse, but not to use it for building the non-recursive TextTools engine (2.0.3 also lacks a lot of features and bug-fixes found in the 2.1.0 versions).
Note: without the non-recursive rewrite of 2.1.0 (i.e. with the recursive version), the test suite will not pass all tests. I'm not sure why they fail with the recursive version, but it does argue for using the non-recursive rewrite.
To build the non-recursive TextTools engine, you'll need to
get the source distribution for the non-recursive implementation from
the SimpleParse
file repository. Note,
there are incompatabilities in the mxBase 2.1 versions that make it
necessary to use the versions specified below to build the
non-recursive versions.
This archive is intended to be expanded over the mxBase source archive from the top-level directory, replacing one file and adding four others.
cd egenix-mx-base-2.1.0
gunzip non-recursive-1.0.0b1.tar.gz
tar -xvf non-recursive-1.0.0b1.tar
(Or use WinZip on Windows). When you have completed that, run:
setup.py build --force install
in the top directory of the eGenix-mx-base source tree.
The 2.1.0 and greater releases include the eGenix mxTextTools extension:
Licensed under
the eGenix.com Public License see the mxLicense.html
file for details on
licensing terms for the original library, the eGenix extensions are:
Copyright (c) 1997-2000, Marc-Andre Lemburg
Copyright (c) 2000-2001, eGenix.com Software GmbH
Extensions to the eGenix extensions (most significantly the rewrite of the core loop) are copyright Mike Fletcher and released under the SimpleParse License below:
Copyright © 2003-2006, Mike Fletcher
SimpleParse License:
Copyright © 1998-2006, Copyright by
Mike C. Fletcher; All Rights Reserved.
mailto<EMAIL_ADDRESS>Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee or royalty is hereby granted, provided that the above copyright notice appear in all copies and that both the copyright notice and this permission notice appear in supporting documentation or portions thereof, including modifications, that you make.

A
Open Source project


502 Bad Gateway
Your local APP is not running on port 5005
Please ensure that your app is running on port 5005
> dotnet run --project App/App.csproj


First thing to know about me: I am a nerd and insomniac. What does that mean? Well, when working on my projects such as designing a website or brand identity, I am usually accomplishing this task at 2 am while Lord of the Rings is playing in the background. I am a newly graduated student from Arizona State University and I am eager to begin building experience by taking on freelance projects and searching for other opportunities to work in a team. My design process is mainly focused on identifying a mood and feeling I wish for the user to have and then using the full arsenal of my knowledge, create an experience that will both intrigue and delight the client and the potential user.
2 years experiance in semantic code for web structuring and development. Designed functioning websites for clients and friends.
Creating original and stylized layouts and themes for modern web sites. Each design is unique to the client and optimized for user ease of access.
Using back end code to create fun and interactive games, web apps, and more. This skill I am still building on.
Proficient in this online library to create responsive websites efficiently in short amounts of time and with appealing aesthetic.
Highly proficient in Photoshop, Illustrator, InDesign, Acrobat, After Effects, Premier, and Dreamweaver. I work in these programs daily.
Can create professional documents using Word, PowerPoint, and Excel. Have been using these programs since 2007.


I do stuff on the web, and now i'm trying to do more applicational stuff
I enjoy writing front-end code with these technologies
Facebook, email


@ProviderType
public interface ThreadPoolConfig
| Modifier and Type | Interface and Description |
|---|---|
static class |
ThreadPoolConfig.ThreadPoolPolicy
The thread pool policies.
|
static class |
ThreadPoolConfig.ThreadPriority |
| Modifier and Type | Method and Description |
|---|---|
ThreadPoolConfig.ThreadPoolPolicy |
getBlockPolicy()
Return the block policy.
|
java.util.concurrent.ThreadFactory |
getFactory()
Return the thread pool factory.
|
long |
getKeepAliveTime()
Return the keep alive time.
|
int |
getMaxPoolSize()
Return the maximum pool size
|
long |
getMaxThreadAge()
Deprecated.
Since version 3.4.0 always returns -1 as threads are no longer retired
but instead the thread locals are cleaned up (SLING-6261)
|
int |
getMinPoolSize()
Return the minimum pool size.
|
ThreadPoolConfig.ThreadPriority |
getPriority()
Return the priority for the threads.
|
int |
getQueueSize()
Return the queue size.
|
int |
getShutdownWaitTimeMs()
Return the shutdown wait time in ms.
|
boolean |
isDaemon()
Return if daemon threads should be created.
|
boolean |
isShutdownGraceful()
Should this pool shutdown graceful.
|
int getMinPoolSize()
int getMaxPoolSize()
int getQueueSize()
@Deprecated long getMaxThreadAge()
long getKeepAliveTime()
ThreadPoolConfig.ThreadPoolPolicy getBlockPolicy()
boolean isShutdownGraceful()
true
if the pool should shutdown graceful.int getShutdownWaitTimeMs()
java.util.concurrent.ThreadFactory getFactory()
null
ThreadPoolConfig.ThreadPriority getPriority()
boolean isDaemon()
true
if daemon threads should be created.Copyright © 2022 The Apache Software Foundation. All rights reserved.


A google street panorama viewer with WebGL using GSVPano.js and three.js. Uses Geolocation API, Fullscreen API and Pointer Lock API if available.
Click and drag the panorama viewer. Mouse wheel to zoom in and out. Use search box to find addresses, or click on the map to select a new location. Each location has a unique URL which you can share.
You'll need Chrome, Firefox 8+, or another browser that supports CORS canvas textures.
Code by @thespite · Built with three.js · Tweaking and optimisations by Mr.doob · Inspired on Paul Lewis' Create your own environment maps article.


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Destiny 2: Xur location and inventory, November 15-18
by Stephany NunneleyIt’s Xur time again.
This week, Destiny 2’s vendor Xur is selling a trace rifle, two helmets and chest armor.
You can find him at Giant’s Scar over on Io.
Be sure to get what you want or need before the reset hits on November 19.
Xur inventory for November 15-18
- Mask of the Quiet One [Exotic Titan Helmet] – 23 Legendary Shards
- Ophidia Spathe [Exoitic Hunter Chest] – 23 Legendary Shards
- Prometheus Lens [Exotic Trace Rifle] – 29 Legendary Shards
- Skull of Dire Ahamkara [Exoitic Warlock Helmet] – 23 Legendary Shards
Our man is selling Prometheus Lens this week. The Exotic Trace Rifle’s Intrinsic Perk Prismatic Inferno fires a Solar trace beam and generates a damaging heat field that grows while the weapon continues to fire. Flame Refraction is its Exotic Trait, and kills will return a fraction of the ammo used to the magazine from reserves. This extends the beam’s duration.
Games featured in this article


Cardinal George Pell Will Have His Appeal Heard By The High Court
by Joseph EarpToday, a court has ruled that Cardinal George Pell will be granted the opportunity to make an appeal to the high court. This will lengthen an already long and involved legal battle for the disgraced Cardinal.
Pell, who was convicted of historic sex crimes, had his first attempt at an appeal dismissed from a Victorian court in June of this year.
Related
In the aftermath of that decision, the Cardinal made an appeal to the High Court. It was up to that court to decide whether the appeal would even be heard.
Today, they have decided that they will hear the appeal. That does not necessarily mean that Pell will not serve jail time. It will all depend on what now happens with the appeal, which it is believed will be heard by a court this forthcoming Summer.
The appeal heard by the high court will be Pell’s last chance to clear his name.


Navigation drawer
Tap on the left edge of the screen to open the app table of contents.
The list of page links is read from the nav.html file.
Basic customation options are available in the index.html file
Tap on the left edge of the screen to open the app table of contents.
The list of page links is read from the nav.html file.
Basic customation options are available in the index.html file


Simple Autocomplete - Failing unit test with harness
Steps to reproduce:
- In the console:
npm run test
- Make sure NOT to bring the opened Chrome window showing Jasmine tests into the visibility. If it opens in front, quickly click on some other window to bring the Chrome window to the background
- Observe: test succeeds
- make a small change in test (change spec name) to trigger test re-run
- Observe: test still succeeds
- Bring the Chrome window showing Jasmine tests into the visibility
- Observe: test fail