| 041:039 Khan | : |
And among His Signs (in this), that you see the earth barren, but when We send down water (rain) to it, it is stirred to life and growth (of vegetations). Verily, He Who gives it life, surely, (He) is Able to give life to the dead (on the Day of Resurrection). Indeed! He is Able to do all things. |
| 041:039 Maulana | : |
And of His signs is this, that thou seest the earth still, but when We send down water thereon, it stirs and swells. He Who gives it life is surely the Giver of life to the dead. Surely He is Possessor of Power over all things. |
| 041:039 Pickthal | : |
And of His portents (is this): that thou seest the earth lowly, but when We send down water thereon it thrilleth and groweth. Lo! He Who quickeneth it is verily the Quickener of the Dead. Lo! He is Able to do all things. |
| 041:039 Rashad | : |
Among His proofs is that you see the land still, then, as soon as we shower it with water, it vibrates with life. Surely, the One who revived it can revive the dead. He is Omnipotent. |
| 041:039 Sarwar | : |
Further evidence is that (at times) you find the earth to be barren. When it is watered it moves and swells (to let the plants grow).  He has power over all things. |
| 041:039 Shakir | : |
And among His signs is this, that you see the earth still, but when We send down on it the water, it stirs and swells: most surely He Who gives it life is the Giver of life to the dead; surely He has power over all things. |
| 041:039 Sherali | : |
And of HIS signs is that thou seest the earth lying withered, but when WE send down water on it, it stirs and swells with verdure. Surely, HE, Who quickened it, can quicken the dead also. Verily, HE has power over all things. |
| 041:039 Yusufali | : |
And among His Signs in this: thou seest the earth barren and desolate; but when We send down rain to it, it is stirred to life and yields increase. Truly, He Who gives life to the (dead) earth can surely give life to (men) who are dead. For He has power over all things. |
Concepts/Themes Covered: أركان الإسلام > التوحيد > توحيد الله تعالي > صفات الله تعالى > القدير Pillars of Islam> Islamic> Oneness of Allah> His Glory's Characteristics> The Able to do All Things أركان الإسلام > التوحيد > توحيد الله تعالي > صفات الله تعالى > المحيي Pillars of Islam> Islamic> Oneness of Allah> His Glory's Characteristics> Who is Able to Raise the Dead أركان الإسلام > التوحيد > توحيد الله تعالي > صفات الله تعالى > يحيي الموتى Pillars of Islam> Islamic> Oneness of Allah> His Glory's Characteristics> Who Raises the Dead أركان الإسلام > التوحيد > توحيد الله تعالي > وجوده Pillars of Islam> Islamic> Oneness of Allah> His Existence أركان الإسلام > التوحيد > توحيد الله تعالي > وحدانيته Pillars of Islam> Islamic> Oneness of Allah> Singularity and Being Unique الإيمان > اليوم الآخر > البعث Faith> The Hereafter> The Resurrection
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


time bomb
`Prev `__
T
`Next `__
--------------
**time bomb**: n.
A subspecies of `*logic bomb* <../L/logic-bomb.html>`__ that is
triggered by reaching some preset time, either once or periodically.
There are numerous legends about time bombs set up by programmers in
their employers' machines, to go off if the programmer is fired or laid
off and is not present to perform the appropriate suppressing action
periodically.
Interestingly, the only such incident for which we have been pointed to
documentary evidence took place in the Soviet Union in 1986! A
disgruntled programmer at the Volga Automobile Plant (where the Fiat
clones called Ladas were manufactured) planted a time bomb which, a week
after he'd left on vacation, stopped the entire main assembly line for a
day. The case attracted lots of attention in the Soviet Union because it
was the first cracking case to make it to court there. The perpetrator
got a suspended sentence of 3 years in jail and was barred from future
work as a programmer.
--------------
+-------------------------------+----------------------------+------------------------------+
| `Prev `__ | `Up <../T.html>`__ | `Next `__ |
+-------------------------------+----------------------------+------------------------------+
| tiger team | `Home <../index.html>`__ | time sink |
+-------------------------------+----------------------------+------------------------------+


func ConstructBlock(t *testing.T, blockNum uint64, previousHash []byte, simulationResults [][]byte, sign bool) *common.Block
ConstructBlock constructs a single block
func ConstructBlockFromBlockDetails(t *testing.T, blockDetails *BlockDetails, sign bool) *common.Block
func ConstructBlockWithTxid(t *testing.T, blockNum uint64, previousHash []byte, simulationResults [][]byte, txids []string, sign bool) *common.Block
func ConstructBytesProposalResponsePayload(version string, simulationResults []byte) ([]byte, error)
ConstructBytesProposalResponsePayload constructs a ProposalResponse byte with given chaincode version and simulationResults for testing
func ConstructRandomBytes(t testing.TB, size int) []byte
ConstructRandomBytes constructs random bytes of given size
func ConstructTestBlock(t *testing.T, blockNum uint64, numTx int, txSize int) *common.Block
ConstructTestBlock constructs a single block with random contents
func ConstructTestBlocks(t *testing.T, numBlocks int) []*common.Block
ConstructTestBlocks returns a series of blocks starting with blockNum=0. The first block in the returned array is a config tx block that represents a genesis block Except the genesis block, the size of each of the block would be the same.
func ConstructTransaction(_ *testing.T, simulationResults []byte, txid string, sign bool) (*common.Envelope, string, error)
ConstructTransaction constructs a transaction for testing
func ConstructTransactionFromTxDetails(txDetails *TxDetails, sign bool) (*common.Envelope, string, error)
func CopyDir(srcroot, destroot string) error
CopyDir creates a copy of a dir
func CreateTarBytesForTest(testFiles []*TarFileEntry) []byte
CreateTarBytesForTest creates a tar byte array for unit testing
func NewBlock(env []*common.Envelope, blockNum uint64, previousHash []byte) *common.Block
func SetTxID(t *testing.T, block *common.Block, txNum int, txID string)
type BlockDetails struct { BlockNum uint64 PreviousHash []byte Txs []*TxDetails }
BlockGenerator generates a series of blocks for testing
type BlockGenerator struct {
// contains filtered or unexported fields
}
func NewBlockGenerator(t *testing.T, ledgerID string, signTxs bool) (*BlockGenerator, *common.Block)
NewBlockGenerator instantiates new BlockGenerator for testing
func (bg *BlockGenerator) NextBlock(simulationResults [][]byte) *common.Block
NextBlock constructs next block in sequence that includes a number of transactions - one per simulationResults
func (bg *BlockGenerator) NextBlockWithTxid(simulationResults [][]byte, txids []string) *common.Block
NextBlockWithTxid constructs next block in sequence that includes a number of transactions - one per simulationResults
func (bg *BlockGenerator) NextTestBlock(numTx int, txSize int) *common.Block
NextTestBlock constructs next block in sequence block with 'numTx' number of transactions for testing
func (bg *BlockGenerator) NextTestBlocks(numBlocks int) []*common.Block
NextTestBlocks constructs 'numBlocks' number of blocks for testing
TarFileEntry is a structure for adding test index files to an tar
type TarFileEntry struct { Name, Body string }
type TxDetails struct { TxID string ChaincodeName, ChaincodeVersion string SimulationResults []byte }


import "go/scanner"
Package scanner implements a scanner for Go source text. It takes a []byte as source which can then be tokenized through repeated calls to the Scan method.
PrintError is a utility function that prints a list of errors to w, one error per line, if the err parameter is an ErrorList. Otherwise it prints the err string.
In an ErrorList, an error is represented by an *Error. The position Pos, if valid, points to the beginning of the offending token, and the error condition is described by Msg.
Error implements the error interface.
An ErrorHandler may be provided to Scanner.Init. If a syntax error is encountered and a handler was installed, the handler is called with a position and an error message. The position points to the beginning of the offending token.
ErrorList is a list of *Errors. The zero value for an ErrorList is an empty ErrorList ready to use.
Add adds an Error with given position and error message to an ErrorList.
Err returns an error equivalent to this error list. If the list is empty, Err returns nil.
An ErrorList implements the error interface.
ErrorList implements the sort Interface.
RemoveMultiples sorts an ErrorList and removes all but the first error per line.
Reset resets an ErrorList to no errors.
Sort sorts an ErrorList. *Error entries are sorted by position, other errors are sorted by error message, and before any *Error entry.
A mode value is a set of flags (or 0). They control scanner behavior.
type Scanner struct { // public state - ok to modify ErrorCount int // number of errors encountered // contains filtered or unexported fields }
A Scanner holds the scanner's internal state while processing a given text. It can be allocated as part of another data structure but must be initialized via Init before use.
Init prepares the scanner s to tokenize the text src by setting the scanner at the beginning of src. The scanner uses the file set file for position information and it adds line information for each line. It is ok to re-use the same file when re-scanning the same file as line information which is already present is ignored. Init causes a panic if the file size does not match the src size.
Calls to Scan will invoke the error handler err if they encounter a syntax error and err is not nil. Also, for each error encountered, the Scanner field ErrorCount is incremented by one. The mode parameter determines how comments are handled.
Note that Init may call err if there is an error in the first character of the file.
Scan scans the next token and returns the token position, the token, and its literal string if applicable. The source end is indicated by token.EOF.
If the returned token is a literal (token.IDENT, token.INT, token.FLOAT, token.IMAG, token.CHAR, token.STRING) or token.COMMENT, the literal string has the corresponding value.
If the returned token is a keyword, the literal string is the keyword.
If the returned token is token.SEMICOLON, the corresponding literal string is ";" if the semicolon was present in the source, and "\n" if the semicolon was inserted because of a newline or at EOF.
If the returned token is token.ILLEGAL, the literal string is the offending character.
In all other cases, Scan returns an empty literal string.
For more tolerant parsing, Scan will return a valid token if possible even if a syntax error was encountered. Thus, even if the resulting token sequence contains no illegal tokens, a client may not assume that no error occurred. Instead it must check the scanner's ErrorCount or the number of calls of the error handler, if there was one installed.
Scan adds line information to the file added to the file set with Init. Token positions are relative to that file and thus relative to the file set.
Code:play
// src is the input that we want to tokenize. src := []byte("cos(x) + 1i*sin(x) // Euler") // Initialize the scanner. var s scanner.Scanner fset := token.NewFileSet() // positions are relative to fset file := fset.AddFile("", fset.Base(), len(src)) // register input "file" s.Init(file, src, nil /* no error handler */, scanner.ScanComments) // Repeated calls to Scan yield the token sequence found in the input. for { pos, tok, lit := s.Scan() if tok == token.EOF { break } fmt.Printf("%s\t%s\t%q\n", fset.Position(pos), tok, lit) }
Output:
1:1 IDENT "cos" 1:4 ( "" 1:5 IDENT "x" 1:6 ) "" 1:8 + "" 1:10 IMAG "1i" 1:12 * "" 1:13 IDENT "sin" 1:16 ( "" 1:17 IDENT "x" 1:18 ) "" 1:20 ; "\n" 1:20 COMMENT "// Euler"


Glory be to the Father, and to the Son, and to the Holy Spirit; *
as it was in the beginning, is now, and ever shall be,
world without end. Amen.


ALIEN: RESURRECTION (R)
Directed by Jean-Pierre Jeunet Running Time: 108 minutes Originally Released: November 26, 1997
Reviewed by E. Benjamin Kelsey
* * ½ (out of four)
I really don't like to see sequels when I haven't seen the predecessors. It's just not right. So although I hadn't seen any of the "Alien" movies at all, thru gentle persuasion I agreed to go to ALIEN: RESURRECTION, and my friends were kind enough to give me a rundown of the first three on the way to the theater. With nothing but my friends' "expertise" to rely on up to this point, I sat down hoping for two hours of fun.
I'm gonna leave it up to you to know where ALIEN 3 left off. I'm not going to write up an essentially "word of mouth" re-cap of three movies I haven't seen. With that in mind, try to remember that my review could greatly be affected by a lack of "Alien" knowledge. This review is going to be from the perspective of someone who doesn't know what's going on. Hopefully it will be of use to someone!
As ALIEN: RESURRECTION begins, we are on a spacecraft where scientists remove an alien baby from Sigourney Weaver's body. Then, from what I could gather, we jump quite a few years into the future. They have cloned Ellen Ripley (Weaver) and her "baby" is now a queen alien kept for scientific research. All within the same scene, they try to teach Ripley's clone what a fork is, which is pretty ironic because about ten seconds after that, she listens to a scientist ramble on in scientific jargon and, what do you know, she understands it all.
Meanwhile a spaceship full of "no-goods" hooks up with the larger spacecraft and in come a fresh group of alien chow. Oops! Did I give away a major surprise? Anyway, the group of terrorists, which includes Winona Ryder as Annalee Call, boards the craft just in time for all hell (including the oh-so- researchable aliens) to break loose.
What happens next is obvious. Everybody, aside from the rebel group and Ripley's clone, is soon killed off. This leaves our main characters scrambling thru an oversized, earth-bound hunk of metal. Will they get out in time? Will Ripley's clone, who is seemingly half-alien, be a friend or foe?
The acting and dialogue is pretty hokey at times, especially in the beginning. Weaver takes a long time to get even somewhat decent, but she's still the best character. Ryder on the other hand, just doesn't seem right at all. Being a horror film however, this isn't quite as important as the real goal . . . scaring us! Yes, we jump quite a few times, but it's nothing new by any means. If you like blood, this one is gory enough that it will hopefully satisfy you.
The special effects aren't bad, but they're nothing revolutionary. There is a pretty good five minutes of special effects at the end, however. You'll likely watch thru fascinated, yet cringing eyes. But the overall suspense, which is, of course, the most important ingredient, never reaches quite high enough. It's pretty routine, but it's worth a viewing if you can get in cheap enough.
December 9, 1997
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


Hello, I'm Vishy
Vishweb Design is a channel for learning Complete Responsive website design, Creative CSS animation and Hover Effects, #vishweb design, creative UX and UI Design using Htm5, CSS3, Javascript, jQuery, Bootstrap, Website Design..
Strong
Direction
Lorem ipsum, or lipsum as it is sometimes known, is dummy text used in laying out print, graphic or web designs. The passage is attributed to an unknown typesetter in the 15th century who is thought
Deep Strategy
Lorem ipsum, or lipsum as it is sometimes known, is dummy text used in laying out print, graphic or web designs. The passa ge is attributed to an unknown typesetter in the 15th century who is thought
Rockin' Design
Lorem ipsum, or lipsum as it is sometimes known, is dummy text used in laying out print, graphic or web designs. The p assage is attributed to an unknown typesetter in the 15th century who is thought
London
Born
Aure Wines needed to improve their presence in the Ontario wine market. And considering the roots of their family-owned winery reached back to Britain, soon the London Born Wine Company was, well, born. As part of the bold rebrand, a strong online presence was needed.
View WorkSubaru
Aure Wines needed to improve their presence in the Ontario wine market. And considering the roots of their family-owned winery reached back to Britain, soon the London Born Wine Company was, well, born. As part of the bold rebrand, a strong online presence was needed.
View Workvaleyo
Aure Wines needed to improve their presence in the Ontario wine market. And considering the roots of their family-owned winery reached back to Britain, soon the London Born Wine Company was, well, born. As part of the bold rebrand, a strong online presence was needed.
View Work


Mother of Biak-na-Bato. Born in San Miguel, Bulacan, on November 18, 1848.
Even though women-members of the Katipunan were exempted from the pact,
she participated in Sanduguan(blood compact). She fought fearlessly in 12 bloody battles of the revolution in Bulacan,
including the famous Battle of Biak-na-Bato. Later, she became known as The Mother of the Philippine Red Cross. Died on June 28, 1928.


Maximum Likelihood Estimation Linear Regression
October 15, 2016
Edit October 19, 2016. There was an error in my code, where I took the standard deviation of the true values, when I should have actually been taking the standard deviation of the residual values. I have corrected the post and the files.
Edit2 October 20, 2016. I was passing the integer length of the data set, instead of the floating point length, which messed up the math. I’ve corrected this and updated the code.
I am going to use maximum likelihood estimation (MLE) to fit a linear (polynomial) model to some data points. A simple case is presented to create an understanding of how model parameters can be identified by maximizing the likelihood as opposed to minimizing the sum of the squares (least squares). The likelihood equation is derived for a simple case, and gradient optimization is used to determine the coefficients of a polynomial which maximize the likelihood with the sample. The polynomial that results from maximizing the likelihood should be the same as a polynomial from a least squares fit, if we assume a normal (Gaussian) distribution and that the data is independent and identically distributed. Thus the maximum likelihood parameters will be compared to the least squares parameters. All of the Python code used in this comparison will be available here.
So let’s generate the data points that we’ll be fitting a polynomial to. I assumed the data is from some second order polynomial, of which I added some noise to make the linear regression a bit more interesting.
The Python code gives us the following data points.
Now onto the formulation of the likelihood equation that we’ll use to determine coefficients of a fitted polynomial.
Linear regression is generally of some form
for a true function \( \mathbf{Y} \), the matrix of independent variables \( \mathbf{X} \), the model coefficients \( \mathbf{\beta} \), and some residual difference between the true data and the model \( \mathbf{r} \). For a second order polynomial, \( \mathbf{X} \) is of the form \( \mathbf{X} = [\mathbf{1}, \mathbf{x}, \mathbf{x^2}]\). We can rewrite the equation of linear regression as
where the residuals \( \mathbf{r} \) are expressed as the difference between the true model (\( \mathbf{Y} \)) and the linear model (\( \mathbf{X}\mathbf{\beta} \)). If we assume the data to be of an independent and identically distributed sample, and that the residual \( \mathbf{r} \) is from a normal (Gaussian) distribution, then we’ll get the following probability density function \( f \).
The probability density function \( f(x|\mu , \sigma^2) \) is for a point \( x \), with a mean \( \mu \), and standard deviation \( \sigma \). If we substitute the residual into the equation, and assume that the residual will have a mean of zero (\( \mu = 0 \)) we get
which defines the probability density function for a given point. The likelihood function \( L \) is defined as
the multiplication of all probability densities at each \( x_i \) point. When we substitute the probability density function into the definition of the maximum likelihood function, we have the following.
It is practical to work with the log-likelihood as opposed to the likelihood equation as the likelihood equation can be nearly zero. In Python we have created a function which returns the log-likelihood value given a set of ‘true’ values (\( \mathbf{Y} \)) and a set of ‘guess’ values \( \mathbf{X}\mathbf{\beta} \).
Optimization is used to determine which parameters \( \mathbf{\beta} \) maximize the log-likelihood function. The optimization problem is expressed below.
So since our data originates from a second order polynomial, let’s fit a second order polynomial to the data. First we’ll have to define a function which will calculate the log likelihood value of the second order polynomial for three different coefficients (‘var’).
We can then use gradient-based optimization to find which polynomial coefficients maximize the log-likelihood. I used scipy and the BFGS algorithm, but other algorithms and optimization methods should work well for this simple problem. I picked some random variable values to start the optimization. The Python code to run the scipy optimizer is presented in the following lines. Note that maximizing the likelihood is the same as minimizing minus 1 times the likelihood.
As it turns out, with the assumptions we have made (Gaussian distribution, independent and identically distributed, \( \mu = 0 \)) the result of maximizing the likelihood should be the same as performing a least squares fit. So let’s go ahead and perform a least squares fit to determine the coefficients of a second order polynomial from the data points. This can be done with scikit-learn easily with the following lines of Python code.
I’ve made a plot of the data points, the polynomial from maximizing the log-likelihood, and the least squares fit all on the same graph. We can clearly see that maximizing the likelihood was equivalent to performing a least squares fit for this data set. This was intended to be a simple example, as I hope to transition a maximum likelihood estimation to non-linear regression in the future. Obviously this example doesn’t highlight or explain why someone would prefer to use a maximum likelihood estimation, but hopefully in the future I can explain the difference on a sample where the MLE gives a different result than the least squares optimization.
A few notes from implementing this simple MLE:
-
It appears that the MLE performs poorly from bad starting points. I suspect that with a poor starting point it may be beneficial to first run a sum of squares optimization to obtain a starting point of which a MLE can be performed from. Edit October 19, 2016. I re ran optimizations from random starting points by minimizing the root mean square error, and it actually appears that the MLE is a better optimization problem than the RMS error. Edit2 October 26, 2016. This lead to a follow up post here, where I show that actually MLE is a more difficult gradient optimization problem.
-
I’m not sure about how to select an appropriate probability density function. I’m not sure what the benefit of using MLE over least squares if I always assume Gaussian… I guess I’ll always know the standard deviation, and that the mean may not always be zero.


Pig Dice
Enter Player 1 name:
Enter Player 2 name:
Help?
Start Game
>>>
Pig Dice
's Total Points:
's Total Points:
Roll Dice
Hold
Roll:
Dice Roll total:
Help
???
Quit
<<<


Securities Fraud
by BRIEFMANHATTAN — Sweden-based Ericsson (Telefonaktiebolaget LM Ericsson) and its subsidiaries made $427 million from paying $62 million in bribes to government officials in Saudi Arabia, China and Djibouti, the SEC claims in a federal complaint.


Umm, sorry but your screen is too small for this awesomeness, get bigger one.
Aaawww yeah, sexy dance time!


Without
,
there will be no life on
.
It is especially true for
.
A
is a place where there is little water,
and there is a lot of sand
that
we have to put on
to protect our skin.
We must
a lot of water with us,
or we
losing too much water
from our body.
Animals and plants in deserts
to get water and
Because the
weather there changes greatly
in one day,
everything is hot and dry in the
can
on plants
in the early morning,
and animals eat these plants
with water on them.
That is how they stay alive in deserts.


Standard output
15:16:52.995 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Field with ID 0 on position with coordinates X:0 and Y:0 was created
15:16:53.008 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Stone with ID 1 on position with coordinates X:0 and Y:0 was created
15:16:53.012 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Stone with ID 2 on position with coordinates X:0 and Y:0 was created
15:16:53.015 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Wood with ID 3 on position with coordinates X:0 and Y:0 was created
15:16:53.016 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Wood with ID 4 on position with coordinates X:0 and Y:0 was created
15:16:53.017 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Player with ID 5 on position with coordinates X:0 and Y:0 was created
15:16:53.018 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Player with ID 6 on position with coordinates X:0 and Y:0 was created
15:16:53.019 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Bomb with ID 7 on position with coordinates X:0 and Y:0 was created
15:16:53.019 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Bomb with ID 8 on position with coordinates X:0 and Y:0 was created
15:16:53.020 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Flame with ID 9 on position with coordinates X:0 and Y:0 was created
15:16:53.021 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Flame with ID 10 on position with coordinates X:0 and Y:0 was created
15:16:53.022 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.SpeedBonus with ID 11 on position with coordinates X:0 and Y:0 was created
15:16:53.022 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.SpeedBonus with ID 12 on position with coordinates X:0 and Y:0 was created
15:16:53.023 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.FlameBonus with ID 13 on position with coordinates X:0 and Y:0 was created
15:16:53.024 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.FlameBonus with ID 14 on position with coordinates X:0 and Y:0 was created
15:16:53.025 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.BombBonus with ID 15 on position with coordinates X:0 and Y:0 was created
15:16:53.025 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.BombBonus with ID 16 on position with coordinates X:0 and Y:0 was created
15:16:53.030 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Field with ID 17 on position with coordinates X:0 and Y:0 was created
15:16:53.031 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Stone with ID 18 on position with coordinates X:0 and Y:0 was created
15:16:53.032 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Stone with ID 19 on position with coordinates X:0 and Y:0 was created
15:16:53.032 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Wood with ID 20 on position with coordinates X:0 and Y:0 was created
15:16:53.033 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Wood with ID 21 on position with coordinates X:0 and Y:0 was created
15:16:53.033 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Player with ID 22 on position with coordinates X:0 and Y:0 was created
15:16:53.034 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Player with ID 23 on position with coordinates X:0 and Y:0 was created
15:16:53.035 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Bomb with ID 24 on position with coordinates X:0 and Y:0 was created
15:16:53.035 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Bomb with ID 25 on position with coordinates X:0 and Y:0 was created
15:16:53.036 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Flame with ID 26 on position with coordinates X:0 and Y:0 was created
15:16:53.037 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Flame with ID 27 on position with coordinates X:0 and Y:0 was created
15:16:53.037 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.SpeedBonus with ID 28 on position with coordinates X:0 and Y:0 was created
15:16:53.038 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.SpeedBonus with ID 29 on position with coordinates X:0 and Y:0 was created
15:16:53.038 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.FlameBonus with ID 30 on position with coordinates X:0 and Y:0 was created
15:16:53.039 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.FlameBonus with ID 31 on position with coordinates X:0 and Y:0 was created
15:16:53.040 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.BombBonus with ID 32 on position with coordinates X:0 and Y:0 was created
15:16:53.040 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.BombBonus with ID 33 on position with coordinates X:0 and Y:0 was created
15:16:53.042 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Field with ID 34 on position with coordinates X:0 and Y:0 was created
15:16:53.043 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Stone with ID 35 on position with coordinates X:0 and Y:0 was created
15:16:53.043 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Stone with ID 36 on position with coordinates X:0 and Y:0 was created
15:16:53.044 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Wood with ID 37 on position with coordinates X:0 and Y:0 was created
15:16:53.044 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Wood with ID 38 on position with coordinates X:0 and Y:0 was created
15:16:53.045 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Player with ID 39 on position with coordinates X:0 and Y:0 was created
15:16:53.045 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Player with ID 40 on position with coordinates X:0 and Y:0 was created
15:16:53.046 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Bomb with ID 41 on position with coordinates X:0 and Y:0 was created
15:16:53.046 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Bomb with ID 42 on position with coordinates X:0 and Y:0 was created
15:16:53.048 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Flame with ID 43 on position with coordinates X:0 and Y:0 was created
15:16:53.049 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.Flame with ID 44 on position with coordinates X:0 and Y:0 was created
15:16:53.050 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.SpeedBonus with ID 45 on position with coordinates X:0 and Y:0 was created
15:16:53.051 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.SpeedBonus with ID 46 on position with coordinates X:0 and Y:0 was created
15:16:53.051 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.FlameBonus with ID 47 on position with coordinates X:0 and Y:0 was created
15:16:53.053 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.FlameBonus with ID 48 on position with coordinates X:0 and Y:0 was created
15:16:53.054 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.BombBonus with ID 49 on position with coordinates X:0 and Y:0 was created
15:16:53.055 [Test worker] INFO ru.atom.model.GameSession - Object class ru.atom.model.BombBonus with ID 50 on position with coordinates X:0 and Y:0 was created


To play this online version of battleship 2 players must participate. Select your coordinates on the grid provided. The coordinates will represent the different ships and must be horizontal or vertical (no diagonal placement). You will select spaces on the table grid to represent 5 ships: the carrier (5 cells), the battleship (4 cells), the cruiser (3 cells), the submarine (3 cells), and the destroyer (2 cells). If you guess a coordinate with a ship on it you will recieve an alert for HIT(red)!, if not you will see a MISS(white). When you guess all locations correctly and have sunk all opponent's ships you will be the Battleship MASTER! In order to keep game play moving forward DO NOT refresh the browser.


Tektronix TDS 200 1000 2000 Series Instrument Driver Readme
To rate this instrument driver, go to the driver download page on the Instrument Driver Network.
1. Overview
Instrument Driver Technology: LabVIEW Plug and Play (project-style)
Manufacturer: Tektronix
Supported Language(s): LabVIEW
Supported Model(s): TDS210, TDS220, TDS224, TDS1001, TDS1002, TDS1012, TDS2002, TDS2004, TDS2012, TDS2014,TDS2022, TDS2024,
TPS2012, TPS2014, TPS2024, TDS1001B, TDS1002B, TDS1012B, TDS2002B, TDS2004B, TDS2012B, TDS2014B, TDS2022B, TDS2024B,
TDS1001B-SC, TDS1002B-SC, TDS1012B-SC, TDS1001C-EDU, TDS1002C-EDU, TDS1012C-EDU, TPS2012B, TPS2014B, TPS2024B,
TDS1001CSC, TDS1002CSC, TDS1012CSC, TDS2001C, TDS2002C, TDS2004C, TDS2012C, TDS2014C, TDS2022C, TDS2024C,
TBS1022, TBS1042, TBS1062, TBS1102, TBS1152, TBS1064, TBS1104, TBS1154,
TBS1052B-EDU, TBS1072B-EDU, TBS1102B-EDU, TBS1152B-EDU, TBS1202B-EDU, TBS1052B, TBS1072B, TBS1102B, TBS1152B, TBS1202B
Model(s) Tested: TDS2002, TDS210, TDS1002B, TDS2014B, TDS2014C, TBS1064, TBS1104, TBS1154, TBS1022, TBS1042, TBS1062, TBS1102, TBS1152, TBS1152B, TBS1152B-EDU, TBS1202B, TBS1052B
Interface(s): Serial, GPIB, USB
Firmware Revision(s) Tested: TDS2002 v2.12, TDS210 v1.00 with TDS2CM v1.04, TDS1002B v21.20, TDS2014B v21.20, TPS2012 v10.21, TDS2014C v24.08,
TBS1064 v26.05, TBS1104 v26.05, TBS1154 v26.05, TBS1022 v26.05, TBS1042 v26.05, TBS1062 v26.05, TBS1102 v26.05, TBS1152 v26.05, TBS1152B v1.11, TBS1152B-EDU v1.11, TBS1202B v1.11, TBS1052B v2.42
Certified: Yes
NI Supported: Yes
Source Code Available: Yes
Driver Revision: 4.4.0
Original Release Date: 9/26/2005
Current Revision Date: 8/11/2014
2. Required Software
Some software components need to be installed before using this
instrument driver. The minimum versions of these components are listed
below, and can be downloaded from the Download Site.
VISA 5.0 or later
For more details, refer to the LabVIEW Help under Help
» Search the LabVIEW Help.
3. Known Issues
-This driver does not support the Power Analysis functions for the TPS2000 models.
-The "Channel" ring controls are not consistent with regards to what integer value they pass for the corresponding text value.
This is only an problem if you want to use the same Channel ring control to select the channel for all of the VIs that take a
channel input. This is not being changed in the instrument driver since existing applications are using the VIs without any problems.
-Channel values of some VIs are not unified. Channel values of two VIs named "Read Measurement.vi" and "Read Measurement (2 Channels).vi" start with 1, but that of other VIs start with 0. If we unify all channel values, there might be a possibility that users have backwards compatibility issues with their applications. To preserve the backwards compatibility, we decide to keep all channel values unchanged and don't unify them.
To report issues or provide feedback about this instrument driver,
please send an email to<EMAIL_ADDRESS>4. Revision History
The latest version of this and other LabVIEW and LabWindows/CVI
instrument drivers can be downloaded at the Instrument Driver Network.
REV 2.0, 9/26/2005
Modified by: Rob Hammond, Austin,TX.
Original release for LabVIEW 8.0. LLB-style drivers are named tktds1k2k and tktds2xx.
REV 3.0, 9/6/2006
Modified by: Jaustin Ohueri, Austin, TX
Added support for USB B series oscilloscopes.
Error query was modified, since ERRLOG command was incorrect and error codes in private Classify Error VI were updated.
REV 3.1, 1/14/2009
Modified by: Edward Zhang
Added support for TDS1001B-SC, TDS1002B-SC and TDS1012B-SC.
REV 3.1.1, 1/29/2009
Modified by: Nathan T.
Changed Tektronix TDS 200 1000 2000 Series Acquire Continuous Waveform.vi so that it calls an Initiate outside of the loop and a Fetch inside of the loop.
This is to fix an issue that occured when the timebase was configured to 1 second or more.
REV 3.1.2, 09/30/2009
Modified by: Alvin Tang, Austin, TX.
Configure Channel.vi
-Changed the documentation for Vertical Range Control from "Pass the value of the input range the oscilloscope uses for the channel" to "Sets the vertical gain of the specified oscilloscope channel"
-Changed the units for Vertical Range control from V to V/div (volts per division)
REV 3.2, 10/07/2009
Modified by: Alvin Tang, Austin, TX.
- Added Wait for Triggered Acquisition.vi. This VI is added to address the problem that the instrument is not waiting for the trigger to occur before reading the waveform.
- Tektronix TDS 200 1000 2000 Series Edge Triggered Acquisition
Added Wait for Triggered Acquisition.vi before Read (Single Waveform).vi. The example will wait for trigger to occur before reading the waveform.
REV 3.3, 10/8/2009
Modified by: Nathan T., Austin, TX.
- Added Clear Errors VI to the Serial case of the Initialize VI to compensate for TPS models that do not return a "DCL" after being cleared.
- Updated to LabVIEW 8.2.1
REV 3.4, 10/9/2009
Modified by: Alvin Tang, Austin, TX.
- Added Wait for Trigger.vi in Low Level Data Folder. This VI is added to address the problem that the instrument is not waiting for the trigger to occur before reading the waveform.
Wait for Trigger.vi uses TRIG:STATE? query to correct the bahavior during Triggered Acquisition in Single Mode. This VI does not wait during Continuous Acquisition.
- Read(Single Waveform).vi and Read(Multiple Waveform).vi
Added Wait for Trigger.vi in between Initiate.vi and Fetch Waveform.vi. The Read.vi will now wait for trigger in single acquisition mode. However, it will not affect the acquisition in Continuous mode.
- Changes made in Rev. 3.2 are reverted.
REV 3.4.1, 04/07/2010
Modified by: Brandon Sun
- Revised the documentation of Vertical Offset control in Configure Channel to clarify it only changes the waveform position on the screen.
REV 4.0.0, 10/15/2010
Modified by: Joe Ju
- Support new models : TDS1001CSC, TDS1002CSC, TDS1012CSC, TDS2001C, TDS2002C, TDS2004C, TDS2012C, TDS2014C, TDS2022C, TDS2024C
VIs Added:
Query Limit Test Resultsi
Configure Data Logging
Configure Limit Test Comparison
Configure Limit Test State
Configure Limit Test Stop After
Configure Limit Test Template
Create Limit Test Template
Read Measurement (2 Channels)
REV 4.1.0, 6/17/2011
Modified By: Lei Liu
- Update the Read Measurement.vi to replace the "Phase" to "Pulse Duty" in the control "Measurement Type".
- Update the Read Measurement (2 Channels).vi. Add 2s delay to fetch the measurement result.
REV 4.1.1, 9/1/2011
Modified By: Lei Liu
- Update the Wait for Trigger.vi. Byte count value for VISA Read now is changed to 9.
REV 4.2.0, 9/10/2013
Modified By: Zhen Wang
- Support new models : TBS1022, TBS1042, TBS1062, TBS1102, TBS1152, TBS1064, TBS1104, TBS1154
- Update the Configure Channel.vi to replace "20 MHZ" with "MAX Bandwidth" in the Ring "Bandwidth".
- Update the Configure Channel.vi to fix the following Bugs:
1. Range Command is done before Attenuation Command. If both values are changed, the results is that the Range is changed by the Attenuation command in the scope.
2. The Vertical Range is divided by 10. The Vertical Range is 10 times lower than expected after executing the VI.
REV 4.3.0, 3/20/2014
Modified By: Zhen Wang
- Support new models: TBS1052B-EDU, TBS1072B-EDU, TBS1102B-EDU, TBS1152B-EDU, TBS1202B-EDU, TBS1052B, TBS1072B, TBS1102B, TBS1152B, TBS1202B
- Added the following VIs:
- Query Zoom Window Time Scale.vi
- Query Counter Frequency.vi
- Configure Counter Frequency.vi
- Configure FFT.vi
- Configure Measurement Gating.vi
- Configure Zoom Window.vi
- Tektronix TDS 200 1000 2000 Series Acquire FFT Waveform.vi
- Modified the following VIs:
- Configure Math.vi
1. Update the VI's description to mention that the FFT in the VI is unavailable and moved to Configure FFT VI.
2. Update Function control to mention the available items (CH1 + CH2, CH1 - CH2, CH2 - CH1) for newly supported models.
- Configure Data Logging.vi
- Fetch Waveform.vi
- Read (Single Waveform).vi
Update Source control to add FFT item.
- Save Waveform to Reference Channel.vi
Update Channel control to add FFT item.
- Read Measurement (2 Channels).vi
1. Update the VI's description, because there is no configure measurement (2 channels) VI.
2. Update Measurement Type control to add the following items (DelayRR, DelayRF, DelayFR, DelayFF).
- Read Measurement.vi
Update Measurement Type control to add the following items (Amplitude, High, Low, Negative Duty, Positive Overshoot, Negative Overshoot, Cursor Mean, Burst Width, Positive Pulse Count, Negative Pulse Count, Rising Edge Count, Falling Edge Count, Area, Cycle Area).
- Read (Multiple Waveforms).vi
Update Sources control to add FFT item.
REV 4.4.0, 8/11/2014
Modified By: Xudong Yong
- Add new commands to support models TBS1052B, TBS1072B, TBS1102B, TBS1152B, TBS1202B
- Added the following VIs:
- Query Trend Plot Parameters.vi
- Configure Limit Test Dual Template.vi
- Save Limit Test Template.vi
- Configure Measurement Snapshot.vi
- Configure Trend Plot.vi
- Is TBS-B Series Model.vi
- Tektronix TDS 200 1000 2000 Series Acquire Trend Plot.vi
- Modified the following VIs:
- Configure Limit Test Comparison.vi
Add a case structure by judging the model type.
- Configure Limit Test Template.vi
Added a case structure to determine Limit Template destination by the model type and updated VI description to specify single template.
- Configure Limit Test Stop After.vi
Add a case structure by judging the value of mode control.


Kashif Munir
Associate Professor
VC is the key element in managing an entire area of our activity – online training. Some of them live outside of
Islamabad or even abroad. This Virtual Classroom eliminates the need for physical presence, saves us time, and creates a more interactive learning
environment.
Mr. Jawad Hassan
Assistant Professor
VC is the key element in managing an entire area of our activity – online training. Some of them live outside of
Islamabad or even abroad. This Virtual Classroom eliminates the need for physical presence, saves us time, and creates a more interactive learning
environment.
Mr. Ameen Chilwan
Lecturer
VC is the key element in managing an entire area of our activity – online training. Some of them live outside of
Islamabad or even abroad. This Virtual Classroom eliminates the need for physical presence, saves us time, and creates a more interactive learning
environment.
Dr. Subhan Ullah
Assistant Professor
Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod incididunt ut labore et dolore magna aliqua.
Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu
fugiat nulla pariatur.
Dr Ejaz Ahmed
Associate Professor
VC is the key element in managing an entire area of our activity – online training. Some of them live outside of
Islamabad or even abroad. This Virtual Classroom eliminates the need for physical presence, saves us time, and creates a more interactive learning
environment.


layout: true --- .center[ # FAIR Principles for Phase-Field Data **Trevor Keller** NIST MSED & CTCMS **Andrea Medina-Smith** NIST Research Library 11 May 2022 CHiMaD Phase-Field Methods XIII Northwestern University *These slides are available from* [![DOI](https://zenodo.org/badge/489108751.svg)](https://zenodo.org/badge/latestdoi/489108751) ] ??? [NOTE]: * You need active internet connection to access `remark.js` --- .left-column[ ## What is FAIR? ] .right-column[ .center[
] - [**GO-FAIR.org**](https://go-fair.org) offers detailed analysis of the FAIR Principles with examples of usage and best practices - FAIR data paper: > Mark Wilkinson, *et al.* "The FAIR Guiding Principles for scientific > data management and stewardship,” *Scientific Data* **3** (2016) 160018. > DOI: [10.1038/sdata.2016.18](https://doi.org/10.1038/sdata.2016.18) - Extension from "data" to include software: > Daniel S. Katz *et al.* "FAIR4RS: Taking a fresh look at FAIR for research > software," *Patterns* **2** (2021) 100222. DOI: > [10.1016/j.patter.2021.100222](https://doi.org/10.1016/j.patter.2021.100222) ] --- .left-column[ ## Why go FAIR? ### Generally ] .right-column[ Releasing FAIR datasets can * increase visibility & citations * attract new partnerships, collaborations * enable new research questions to be raised & answered * satisfy funding agency requirements Check out the [**awesome-fair-data**]( https://github.com/Materials-Data-Science-and-Informatics/awesome-fair-data) list by the Helmholtz Metadata Collaboration on Github ... or [**data.nist.gov**](https://data.nist.gov) .center[
] ] --- .left-column[ ## Why go FAIR? ### Generally ### Specifically ] .right-column[ PFHub is automatically built, and needs to * **F**ind your dataset quickly & with persistence * `meta.yaml` filestores URL of dataset * **A**ccess usable data files without intervention * URL must contain a robot-downloadable CSV or JSON file * v**I**sualize the fields it needs without surprises * CSV columns must match specific names, or a human-generated mapping * **R**epeat the whole process to show off results * PFHub does not maintain *content*, only the framework to build the comparison charts Are we done? ] --- .left-column[ ## What is FAIR? ### Findable ] .right-column[ .center[
] The first step in (re)using data is to find them. Metadata and data should be easy to find for both humans and computers. 1. (Meta)data are assigned a globally unique and persistent identifier 2. Data are described with rich metadata (defined by R1 below) 3. Metadata clearly and explicitly include the identifier of the data they describe 4. (Meta)data are registered or indexed in a searchable resource ] --- .left-column[ ## What is FAIR? ### Findable ### Accessible ] .right-column[ .center[
] Once the user finds the required data, they need to know how they can be accessed, possibly including authentication and authorization. 1. (Meta)data are retrievable by their identifier using a standardized communications protocol 1. The protocol is open, free, and universally implementable 2. The protocol allows for an authentication and authorisation procedure, where necessary 2. Metadata are accessible, even when the data are no longer available ] --- .left-column[ ## What is FAIR? ### Findable ### Accessible ### Interoperable ] .right-column[ .center[
] The data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing. 1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. 2. (Meta)data use vocabularies that follow FAIR principles 3. (Meta)data include qualified references to other (meta)data ] --- .left-column[ ## What is FAIR? ### Findable ### Accessible ### Interoperable ### Reusable ] .right-column[ .center[
] The ultimate goal of FAIR is to optimise the reuse of data. To achieve this, metadata and data should be well-described so that they can be replicated and/or combined in different settings. 1.  (Meta)data are released with a clear and accessible data usage license 2. (Meta)data are associated with detailed provenance 3. (Meta)data meet domain-relevant community standards ] --- .left-column[ ## How FAIR is my dataset? ] .right-column[ .center[ ARDC FAIR Self-Assessment,
F-UJI Automated FAIR Data Assessment,
] ] --- .left-column[ ## Live Demo ### GitHub Gist ] .right-column[ Let's see what [ARDC](https://ardc.edu.au/fairdata) and [F-UJI](https://f-uji.net) have to say about one of my GitHub Gist uploads: .center[
] .footnote[ ARDC:
F-UJI:
] ] --- .left-column[ ## Live Demo ### GitHub Gist ### Zenodo ] .right-column[ Let's see what [ARDC](https://ardc.edu.au/fairdata) and [F-UJI](https://f-uji.net) have to say about the same data, on Zenodo: .center[
] .footnote[ ARDC:
F-UJI:
] ] --- .left-column[ ## Where can we improve? ] .right-column[ .center[
] ***Data:*** XDMF/HDF5, PVD/VTI, ??? ***Metadata:*** JSON-LD or CodeMeta schema for phase-field simulations? ***Repositories:*** MDF, Zenodo, Figshare, institutional? ]


Molar Mass Calculator
Submit
Type the compound's chemical formula (e.g. H2O) and press "submit" for its molar mass.


*** User 2017-05-05 19:57:01.294 ***
19:57:01.293 [info] Disabling blocking sync...
*** User 2017-05-05 19:57:01.301 ***
19:57:01.301 [info] Configured peer_service_manager partisan_default_peer_service_manager on node 'node-1@MacBook-Pro-de-Anne-France'
*** User 2017-05-05 19:57:02.825 ***
19:57:02.825 [info] Enabling membership...
*** User 2017-05-05 19:57:02.827 ***
19:57:02.827 [info] Disabling blocking sync...
*** User 2017-05-05 19:57:02.833 ***
19:57:02.833 [info] Configured peer_service_manager partisan_default_peer_service_manager on node 'node-2@MacBook-Pro-de-Anne-France'
*** User 2017-05-05 19:57:04.319 ***
19:57:04.319 [info] Enabling membership...
*** User 2017-05-05 19:57:04.320 ***
19:57:04.320 [info] Disabling blocking sync...
*** User 2017-05-05 19:57:04.325 ***
19:57:04.325 [info] Configured peer_service_manager partisan_default_peer_service_manager on node 'node-3@MacBook-Pro-de-Anne-France'
*** User 2017-05-05 19:57:04.572 ***
Joining node: 'node-3@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 55656
*** User 2017-05-05 19:57:04.572 ***
Joining issued: 'node-3@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 55656
*** User 2017-05-05 19:57:04.573 ***
Joining node: 'node-2@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 55640
*** User 2017-05-05 19:57:04.574 ***
Joining issued: 'node-2@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 55640
*** User 2017-05-05 19:57:04.574 ***
Joining node: 'node-1@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 55627
*** User 2017-05-05 19:57:04.575 ***
Joining issued: 'node-1@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 55627
*** User 2017-05-05 19:57:04.636 ***
Waiting for join to complete with manager: partisan_default_peer_service_manager
*** User 2017-05-05 19:57:04.637 ***
Finished.
*** CT 2017-05-05 19:57:04.637 *** COVER INFO
Adding nodes to cover test: ['runner@MacBook-Pro-de-Anne-France']
*** CT 2017-05-05 19:57:04.646 *** COVER INFO
Successfully added nodes to cover test: []
*** User 2017-05-05 19:57:04.666 ***
Case finished: dynamic_ivar_test
*** User 2017-05-05 19:57:11.713 ***
19:57:11.712 [info] Application lasp exited with reason: stopped
*** User 2017-05-05 19:57:11.714 ***
19:57:11.714 [info] Application partisan exited with reason: stopped
=== Ended at 2017-05-05 19:57:11
=== successfully completed test case
=== Returned value: ok
Test run history
| Top level test index


async static command with arg async static command with Invoke<Task> Command with arg sync static command with argument Just command async static command sync static command


Affiliation
‘The best way to predict the future is to invent it now.’
– Art Costa
Simpkins School is affiliated with the Central Board of Secondary Education (CBSE), which is the largest educational board in the country and is duly recognized by the state of Uttar Pradesh.


layout: true --- # repeatedly refresh content ```cpp rx::observable<>::interval(on_update.now(), seconds(5), on_update). map(as_string{"http://localhost"}). flat_map( [=](std::string url){ return http.get(url); }). flat_map( [](ofxRx::HttpProgress p){ return p. body(). scan( std::string{}, [](std::string response, ofxRx::BufferRef
br){ response.append(br.begin(), br.begin() + br.size()); return response; } ); }). ``` ??? --- # repeatedly refresh content ## error handling ```cpp on_error_resume_next( [=](std::exception_ptr ep){ return rx::observable<>::timer(on_update.now() + seconds(5), on_update). map(as_string{rx::util::what(ep)}). start_with(rx::util::what(ep)); }). repeat(). finally([=](){response = "stopped!";}). ``` ??? --- name: algo #alogrithms --- template: algo
??? remove_if_not (range-v3) copy_if --- template: algo
??? transform (range-v3) --- template: algo
??? transform (range-v3) --- template: algo
??? join (range-v3) --- template: algo
??? --- template: algo
??? --- template: algo
??? --- template: algo
??? --- ##range-v3 view namespace ```c++ auto fiveOddInts = view::ints(0) | //generates next int when asked view::remove_if([](int n) { return n % 2 == 0; }) | // discard even view::take(5); // stop after 5 // when consumed, will emit: // 13579| ``` The original STL has algorithms that take a value and return a value. `pow(), log(), tolower(), itoa(), ...` The original STL has algorithms that used iterators to abstract the storage of a sequence. `copy_if, accumulate, transform, ...` The range-v3 proposal redefines the iterator based STL algorithms so that they can also be composed. The existing proposals for parallel computation are focused on consuming all available resources to compute a result. `parallel_for, ...` The existing STL has async values `promise/future` The asio proposal adds caller-selected future or callback There are no algorithms for async sequences. --- name: value # --- name: represent #representing a sequence --- template: represent ##time vs space --- template: represent ##push vs pull ####pull - auto v = *it; - auto v = step(time); ####push - o.subscribe([](auto v){}); --- template: represent ##lazy vs greedy --- template: represent ##l --- name: shapes # shapes --- template: shapes ##what is the shape of an implementation of an algorithm? --- template: shapes ##what is the shape of the usage of an algorithm? --- name: asio # asio --- template: asio ####supports multiple async contracts - callback - promise **must support shape selected for algorithms.** --- name: future # promise/future --- name: transducer # transducer --- template: transducer ####origin Rich Hickey developed for Clojure. Very quickly other languages had implementations including JavaScript and C++. ####algorithmic interface iterator and range provide interfaces for data traversal. transducers use the reduce (`std::accumulate`) function `auto step(State, Value) -> State` as the interface that all algorithms implement. --- template: transducer ####example ```cpp auto xf = comp( filter([](int x) { return x > 0; }), map([](int x) { return std::to_string(x); })); auto data = std::vector
{ ... }; auto xformed = sequence(xf, data); ``` --- template: transducer ####c++ - Juan Pedro Bolívar Puente @ cppcon 'atria::xform' [YouTube](https://www.youtube.com/watch?v=vohGJjGxtJQ), [github](https://github.com/Ableton/atria) - my experiments [github](https://github.com/kirkshoop/transducer) ####Clojure - Rich Hickey @ StrangeLoop [YouTube](https://www.youtube.com/watch?v=6mTbuzafcII) - Rich Hickey [Blog](http://blog.cognitect.com/blog/2014/8/6/transducers-are-coming) ####js - James Long [Blog](http://jlongster.com/Transducers.js--A-JavaScript-Library-for-Transformation-of-Data) --- name: sfrp # sfrp --- template: sfrp ####Functional Reactive Programming (FRP) Conal Elliot describes this as '**values over time**'. Conal specifies two principals that constrain the definition and implementation of an FRP system. 1. **denotation** - .text[a precise language independent description of the whole system that can be verified without an implementation (one expression would be in the Lambda Calculus)] 2. **continuous time** - the system will have a valid value for any time value. Conal continues to develop a very precise denotation that can be resolved precisely into a specification and various implementations. Conal vociferously defends the term FRP when applied to libraries that are not precisely derived from the denotation. --- template: sfrp ####The Essence and Origins of Functional Reactive Programming Conal Elliot @ Lambda Jam [YouTube](https://www.youtube.com/watch?v=j3Q32brCUAI) ####sfrp (c++) David Sankel @ CppNow [YouTube](https://www.youtube.com/watch?v=tyaYLGQSr4g),[github](https://github.com/camio/sbase) --- template: sfrp ####example ```cpp template
Behavior
map(function
func, Behavior
... behaviors); Behavior
circleFollowsMouse(Behavior
mousePos) { return map(circleAt, mousePos); } ``` --- name: rx # Reactive Extensions --- template: rx Kirk Shoop --- name: await # async_generator and await --- template: await Kirk Shoop --- # filter ```cpp auto filterer = [](auto pred){ return `[=](auto step)` { return `stateless`( [=](auto s, auto v){ if (pred(v)) { return step(s, v); } return s; }, [=](auto s){ return step(s); }); }; }; ``` ```cpp template
async_generator
filter(async_generator
s, P pred) { for __await(auto&& v : s) { if (pred(v)) { __yield_value v; } } } ``` --- # filter ```cpp auto filter = [](auto pred) { return [=](auto subscriber) { return make_subscriber( [=](auto v) { if (pred(v)) { subscriber.on_next(v); } }, [=](std::exception_ptr ep) { subscriber.on_error(ep); }, [=]() { subscriber.on_completed(); } ); } }; ``` --- template: sequences ##how to represent a sequence in documentation or slides? __values distributed__ | __completed__ | __failed__ ---------------------: | ------------: | ---------: _in space_ | `12467:` | `1246#` _in time_ | `--1-2-4---6--7-:` | `--1-2-4---6-#` > notation derived from the RxJS project on [github](https://github.com/ReactiveX/RxJS/blob/master/doc/writing-marble-tests.md) ??? vector and generator distribute values in space async sources distribute values in time * "-" time: a 'unit' of time * ":" complete: The successful completion of a sequence * "#" error: An error terminating the iteration of a sequence * "1-9" number: represent that value in the sequence


Video | Knives Out Review 21 Nov 2019, 16:44 Video | Knives Out Review Rian Johnson’s Knives Out is a fast, smart and unexpected “whodunnit."


Inherits HRLArm.
Public Member Functions | |
| def | __init__ |
| def | joint_states_cb |
| Callback for /joint_states topic. | |
| def | set_ep |
| def | set_delta_ep_ros |
| def | set_ep_ros |
| def | wrap_angles |
| def | publish_rviz_markers |
| def | move_gripper |
| def | open_gripper |
| def | close_gripper |
| def | open_gripper_cb |
| def | close_gripper_cb |
Public Attributes | |
| joint_names_list | |
| torso_position | |
| arm_efforts | |
| delta_jep | |
| kp | |
| kd | |
| marker_pub | |
| cep_marker_id | |
| tf_lstnr | |
| joint_angles_pub | |
| gripper_action_client | |
| q | |
| qdot | |
| ep |
| def hrl_haptic_mpc.urdf_arm_darpa_m3.URDFArm.joint_states_cb | ( | self, | |
| data | |||
| ) |
Callback for /joint_states topic.
Updates current joint angles and efforts for the arms constantly
| data | JointState message recieved from the /joint_states topic |


User guide
Setup
Preferences
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Javascript Simple Search Engine - Test
Authors:
Martin Drapeau
,
Sebastien Giroux
Home:
www.planbox.com/code
Test Suite:
test.html
(qunit)
Items to index
Instant search in Google is awesome! It will work find after you install that patch. I bought a red sports car.
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R and JS visualization
This page is a purpose of representing a various
graph by using an R statistic programming language.
The data will be go through computation server(OpenAPI.
Once all the data is analyzed the result will be store
on the temporal storage of the OpenAPI server.


Disrupting goveranceSuccess in a digital world June 12-13, 2017 | Chicago
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SELECTORS
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This will be the first spaceflight for a mission this big. On this day the mission will be explained to the audience. The spacecraft will travel all the way to the destination's surface during this historic attempt. The spacecraft will contact the surface for several seconds then collect a sample, which it will return to Earth in 2023.
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Ultimate Chocolate Chip Cookies
Just like the name says, this is the chocolate chip cookie extraordinaire! Definitely one of Betty's favorites!
Ingredients
- 3/4 cup granulated sugar
- 3/4 cup packed brown sugar
- 1 cup butter or margarine, softened
- 1 teaspoon vanilla
- 1 egg
- 2 1/4 cups Gold Medal™ all-purpose flour
- 1 teaspoon baking soda
- 1/2 teaspoon salt
- 1 cup coarsely chopped nuts
- 1 package (12 ounces) semisweet chocolate chips (2 cups)
Steps
-
375 Degrees
Heat oven to 375ºF.
- Mix sugars, butter, vanilla and egg in large bowl. Stir in flour, baking soda and salt (dough will be stiff). Stir in nuts and chocolate chips.
- Drop dough by rounded tablespoonfuls about 2 inches apart onto ungreased cookie sheet.
- Bake 8 to 10 minutes or until light brown (centers will be soft). Cool slightly; remove from cookie sheet. Cool on wire rack.