Before Change
def mjpeg_stream(self, response):
Generate an HTTP MJPEG stream from camera images.
import eventlet
response.content_type = ("multipart/x-mixed-replace; "
"boundary=--jpegboundary")
def stream():
Stream images as mjpeg stream.
try:
last_image = None
while True:
img_bytes = self.camera_image()
if img_bytes is not None and img_bytes != last_image:
yield bytes(
"--jpegboundary\r\n"
"Content-Type: image/jpeg\r\n"
"Content-Length: {}\r\n\r\n".format(
len(img_bytes)), "utf-8") + img_bytes + b"\r\n"
last_image = img_bytes
eventlet.sleep(0.5)
except GeneratorExit:
pass
response.response = stream()
return response
@property
def state(self):
Camera state.
After Change
except GeneratorExit:
pass
return response(
stream(),
content_type=("multipart/x-mixed-replace; "
"boundary=--jpegboundary")
)
@property
def state(self):
Camera state.


Midical
Clinic
home
diseases
hospitals
Appointments
doctors
contact US
Messages
Search Of Message
Delete
Name
Email
Location
Phone
History
Reason
Message


{% extends "base.html" %} {% block content_body %} {% if validlink %}
Please enter your new password.
Password reset link invalid or already used. Please request a new one.


DR. DOOLITTLE
Reviewed by Harvey Karten, Ph.D. 20th Century Fox Director: Betty Thomas Writer: Nat Mauldin and Larry Levin Cast: Eddie Murphy, Ossie Davis, Oliver Platt, Peter Boyle, Richard Schiff, Kristen Wilson, Jeffrey Tambor, Kyla Pratt
If you talk at length to your dog, don't worry about it. Everyone does. When the dog starts answering you, then you've got problems. Or do you? If only the world accepted such a two-way communication both you and they would be better off. You'd learn something about yourself relayed straight from the horse's mouth from their four-legged views and might even become as human as the animals themselves are.
With this in mind, Betty Thomas--perhaps most celebrated by teens and adults for directing Howard Stern in "Private Parts" and for subteens for helming the squarest of the square families in "The Brady Bunch Movie"--seems eager to bring a strong moral point home to her mostly small-fry audience, a suggestion that will be most appreciated by the adults who are escorted by them. One is that doctors--and even people--should relate to their fellow living creatures as ends in themselves and not for what others can do to advance their careers and income. She takes aim against the shoddy practices of HMO's and should find little dissension in the audience for that posture.
The movie opens on little John Dolittle, played as a three- year-old by Raymond Matthew Mason and by a five-year-old by Dari Gerard Smith. The kid has is precocious. He has a way with animals and like St. Francis is devoted to gabbing with them, though at this stage of development he does not get a reply. Many years later, when John (Eddie Murphy) has become a successful doctor with a lovely wife, Lisa (Kristen Wilson), he almost strikes a stray dog with his van. When the dog, at first appearing dead, rises, the animal remarks "Why don't you look where you're going, you bonehead?" No explanation is given for Dolittle's new ability, though a blatant product placement implies it might have been the Dunkin' Donuts he had just eaten. In no time flat, the title character colloquies with his daughter's guinea pig, a couple of rats fighting in a trash bin, a tiger in a circus, until he is packed off to a mental institution. His partner, Dr. Mark Weller (Oliver Pratt), is concerned that John's behavior will ruin a lucrative HMO buyout deal, and his wife wonders why he frequently wanders off just when she feels her seductive powers working on him. The only understanding folks are his daughter Maya (Kyla Pratt), who already considers herself weird and a misfit and thereby identifies with dad; and John's father Archer (Ossie Davis) who sees John's dialogues as a gift.
Since special effects at a high stage of development, the audience has no problem really believing that the animals are mouthing the words, be they owls, rodents, goats, ducks, dogs or cats. As for lines, the best belong not to Eddie Murphy but to the four-legged creatures, though Oscar Wilde has nothing to fear from them. For example, in the pound as one dog is being led to his death, another behind the cage remarks "Dead dog walking." A German shepherd in the vet's office whines, "Don't fix me...I won't look at another female," but when an attractive collie passes by, he can't resist: "Yo, baby!" A horse carrying a mounted police officer remarks, "Oh, look, a doughnut shop!"
"Dr. Doolittle" is not "Masterpiece Theater" and no way can it compete with the stories in Hugh Lofting's book, but it's a heck of a lot better--less pretentious--that the overproduced musical of the same name starring Rex Harrison that almost wrecked Fox in 1967. Eddie Murphy seems headed down the route of Jim Carrey--less manic, more somber messaging, and he does just fine.
Rated PG-13. Running time: 80 minutes. (C) Harvey Karten 1998
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


The Works of Edgar Allan Poe
by Edgar Allan Poe
To Marie Louise (Shew) [1848]
Additional Information
- Year Published: 1903
- Language: English
- Country of Origin: United States of America
- Source: Poe, E.A. (1903). The Works of Edgar Allan Poe, The Raven Edition, Volume 5. New York: P. F. Collier and Son.
-
Readability:
- Flesch–Kincaid Level: 3.9
- Word Count: 318
- Genre: Poetry
- Keywords: gratitude
- ✎ Cite This
Downloads
Not long ago, the writer of these lines,
In the mad pride of intellectuality,
Maintained "the power of words"—denied that ever
A thought arose within the human brain
Beyond the utterance of the human tongue:
And now, as if in mockery of that boast,
Two words-two foreign soft dissyllables—
Italian tones, made only to be murmured
By angels dreaming in the moonlit "dew
That hangs like chains of pearl on Hermon hill,"—
Have stirred from out the abysses of his heart,
Unthought-like thoughts that are the souls of thought,
Richer, far wider, far diviner visions
Than even the seraph harper, Israfel,
(Who has "the sweetest voice of all God's creatures")
Could hope to utter. And I! my spells are broken.
The pen falls powerless from my shivering hand.
With thy dear name as text, though bidden by thee,
I can not write-I can not speak or think—
Alas, I can not feel; for 'tis not feeling,
This standing motionless upon the golden
Threshold of the wide-open gate of dreams,
Gazing, entranced, adown the gorgeous vista,
And thrilling as I see, upon the right,
Upon the left, and all the way along,
Amid empurpled vapors, far away
To where the prospect terminates-thee only!


I am a junior in Mechanical Engineering at Purdue University with an interest in susutainable design and robotics
Interned in the MEP division of Voltas International working closely with the HVAC Team. Studied design and implementation of Ducting and the chiller system in the Grand Hyatt Project in Abu Dhabi
Interning at the MEP division of Shapoorji Pallonji International with a focus on the Plumbing and the Fire Safety systems installed in the 52/42 tower at Dubai Marina
Participated as an intern representing The Princeton Review during the ‘Gulf Educational And Training Exhibition’. Worked to spread awareness about The Princeton Review, and helped to collect customer information
GPA : 3.14
GPA: 3.8
Led a team of 5 to design a working quadcopter model. Designed several parts such as the body and the arms on AutoDesk Inventor, and 3-D printed them. Performed several calculations regarding materials used and dimensions to make sure that the Quadcopter could fly for extended periods of time.Programmed the engine output with the controller.Competed against other teams that did the same
Created an algorithm using MATLAB to reduce the effect of noise on thermocouple readings to as low as possible.Succeeded in using our algorithm to obtain values that were close, or in some cases even better than the recommended error percentages.
Love to play the guitar. Completed 3 certified courses from the London College Of Music (LCM) for the acoustic guitar. I also love painting, and spent about 2 years learning to paint with watercolors.
When forced indoors, I follow a number of sci-fi and fantasy genre movies and television shows. I also love following Football and Cricket.


|
fop 0.94 | ||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object org.apache.fop.render.rtf.rtflib.rtfdoc.RtfSpaceSplitter
This class splits block attributes into space-before attribute, space-after attribute and common attributes.
| Constructor Summary | |
RtfSpaceSplitter(RtfAttributes attrs,
int previousSpace)
Create RtfSpaceSplitter with given RtfAttributes. |
| Method Summary | |
int |
flush()
Adds corresponding attributes to their candidates. |
RtfAttributes |
getCommonAttributes()
|
int |
getSpaceBefore()
|
boolean |
isAfterCadidateSet()
|
boolean |
isBeforeCadidateSet()
|
void |
setSpaceAfterCandidate(RtfAttributes candidate)
Sets a candidate for space-after property. |
void |
setSpaceBeforeCandidate(RtfAttributes candidate)
Sets a candidate for space-before property. |
int |
split(java.lang.String key)
Remove attributes with name key from
commonAttributes and return it as int. |
void |
stopUpdatingSpaceBefore()
Stops updating candidates for space-before attribute. |
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
public RtfSpaceSplitter(RtfAttributes attrs, int previousSpace)
attrs
- RtfAttributes for splittingpreviousSpace
- integer, representing accumulated spacing| Method Detail |
public int split(java.lang.String key)
key
from
commonAttributes
and return it as int.
key
- attributes name to extract
public RtfAttributes getCommonAttributes()
public int getSpaceBefore()
public void setSpaceBeforeCandidate(RtfAttributes candidate)
candidate
- instance of RtfAttributes
, considered as
a candidate for space-before addingpublic void setSpaceAfterCandidate(RtfAttributes candidate)
candidate
- instance of RtfAttributes
, considered as
a candidate for space-after addingpublic boolean isBeforeCadidateSet()
public boolean isAfterCadidateSet()
public void stopUpdatingSpaceBefore()
public int flush()
|
fop 0.94 | ||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


Single-cell genomics offers a means of precisely quantifying the state of individual cells and thus may enable the construction of explicit, genome-scale dynamical cellular models. Early single-cell transcriptomic studies lend support to the idea that cells are occupants of a vast, complex landscape of possible states and raise doubts that cell types are precisely defined, discrete entities. Time series experiments of differentiation have observed cells transitioning between a starting state and one or more end states, with many cells distributed along a “trajectory” between them. The Monocle algorithm introduced the notion of pseudotime, a quantitative measure of biological progression through a process such as cell differentiation.
The trajectory plot above shows the trajectory followed by olfactory neurons as the develop in mice. Each point is a cell, where are connected into a minimum spanning tree, the core data structure Monocle uses to find the trajectory, shown in black. Each cell’s pseudotime value is measured as the distance along the trajectory from its position back to the beginning. In order to describe complex differentiation processes in which cells make fate decisions, Monocle allows these trajectories to have a branched structure with multiple possible outcomes.
The Trapnell laboratory is currently focused on three ways to extend single-cell trajectory analysis:
- Methods to identify genes that are differentially regulated along the trajectory, particularly near branches
- Algorithms for distinguishing “driver” genes that regulate progress along a trajectory or govern branching
- Building trajectories from new single-cell data types, such as single-cell ATAC-Seq.


Templates are bind to components. The term binding is commonly used in most of the web development frameworks wherein a
html element is bind to a property in the backing bean or a class. In the Data Binding section, I will describe more about this concept.
Templates can have other templates inside them. This can be done by just adding the selector property value
that is defined in a component.


--- layout: post title: Reference Data Caching Walkthrough date: 2011-04-13 17:34:30.000000000 +08:00 categories: - OData protocol - OData tutorials tags: [] status: publish type: post published: true author: OData.org Archive ---
Tim Laverty from the DataFX team at Microsoft just posted a walk-through showing how to setup reference data caching using the recently released ' Reference Data Caching CTP' (aka the 'Microsoft WCF Data Services For .NET March 2011 Community Technical Preview with Reference Data Caching Extensions').
Take a look and as always let the OData community know what you think on the Mailing List.


Code2000.TTF is a Unicode-based true-type font. It is offered as
a shareware demo. If you like it and use it after a reasonable
evaluation period, you are obliged to register the font by sending
me $5 (Five U.S. Dollars, or equivalent in any currency.)
Please send to:
James Kass
2807 Erskine Creek Road Space 93
Lake Isabella, California U.S.A. 93240
I am registered with PayPal,
https://www.paypal.com/cgi-bin/webscr
...so if you have an existing PayPal account or wish to open one,
Code2000 can be registered by sending the amount to my e-mail
address<EMAIL_ADDRESS>.
Registration Fee Schedule:
US$ 5.00 - Single user registration fee
US$ 50.00 - Single site registration fee
US$100.00 - Server/Web site (embedding) registration fee
US$150.00 - Multiple site registration fee
Code2000 is a work-in-process. It currently (Version 1.15) has over 60000
glyphs.
It is still a bit rough in spots. I am constantly working to improve it and
add more glyphs.
Although it is more-or-less readable at 12 - 18 point, it is much clearer at
about 24 point. Some of the dingbats should be at least 36 point. With font-
smoothing it looks good at normal sizes.
Windows 98 (and up) has font-smoothing built-in. Microsoft has font-smoothing
available for free download for Windows 95. If you're running Windows 95
you should definitely get font smoothing.
To download font smoothing for Windows 95, go to
http://www.microsoft.com/typography/grayscal/smoother.htm
Instructions for installing and activating Windows 95 font-smoothing are
included in the package.
To enable font smoothing in Windows 98, Windows 2000, and Windows M.E.:
1) Click My Computer
2) Click Control Panel
3) Click Display
4) Click Effects tab
5) Put check in box called "Smooth Edges of Screen Fonts"
All of the glyphs are mine, painstakingly drawn one point at a time. I try
to design glyphs which are true to the script they represent based on as
many samples as I can obtain.
Some of the scripts are only partially represented in the font.
My website:
http://home.att.net/~jameskass/
<EMAIL_ADDRESS>Click Here to e-mail me.
KNOWN ERRORS:
HEBREW: Some combinations of Hebrew non-spacing marks are still not
supported, but the OpenType tables are almost completed
OPENTYPE:
Code2000 now has OpenType tables for some scripts. Gurmukhi, Devanagari,
Bengali, and Tamil tables are fairly well advanced, but some tinkering remains
to be done with respect to mark positioning in some cases.
The Bengali glyphs are not quite finished, and several are a bit rough.
TO INSTALL A FONT IN WINDOWS:
1) Unzip the ZIP file (WINZIP.EXE, PKUNZIP.EXE, ...)
2) Click Start
3) Click Settings - Control Panel
4) (Double-) Click Fonts Icon
5) Click File (the word "File" near
the upper left corner of the window)
6) Click "Install New Font"
7) Enter the path and file name of the font to be installed.
(Path means the drive letter plus directory
and any subdirectories describing the location
of the unzipped font.) (Windows calls directories
"folders".)
NOTE: If an older copy of the font is already installed, between
steps 4 and 5 above...
4a) Click once on the icon of the font to be deleted.
4b) Click "File"
4c) Click Delete (and confirm when prompted)
CODE2000.ZIP may be copied and distributed freely, provided
that the contents are intact and unaltered.


{% extends "base.html" %} {% load i18n %} {% block title %}Password Changed{% endblock%} {% block content %}
Success! Your password has been changed.


Computers are getting eerily smart.
Today, Amazon Alexa is recognizing words in our speech. iPhones are recognizing faces in photos and videos. And self-driving cars are recognizing objects, places, and hazards on the road.
But what is powering the ability to recognize voices, streets and people?
How can Amazon Alexa understand our voices? How can self driving cars see and understand the road? And how can iPhones recognize our faces?
The answer: all of these technologies are made possible by artificial neural networks.
At its most basic level, an artificial neural network is a mathematical equation. And, surprisingly, many artificial neural networks rely on simple mathematics: addition, subtraction, multiplication, and exponentiation. In fact, you can easily perform the same calculations with a calculator and these four buttons: + - x exp()
What makes neural networks so special is combining these operations in the right order. When we put them together the right way, we can get the computer to recognize your voice - we just need a fast computer and a data set (preferably, a large one).
To better illustrate what an artificial neural network is and how it works, let's walk through a simple example.
Imagine that we are creating a medical robot (href = Big Hero 6!). The robot is supposed to measure a patient's heart rate and core temperature, and use that information to recognize when people are sick. And just like Alexa, this robot will use a neural network to recognize sick patients.
Our example neural network is below. Click any of the terms to get an explanation.
\[ \Large{ S_{pred} = \frac{1}{1+e^{ - \left(\frac{w_7 }{1 + e^{-\left(T\cdot w_1+ {HR}\cdot w_2 + w_3 \right)}} +\frac{w_8}{1 + e^{-\left(T\cdot w_4+ {HR}\cdot w_5 + w_6 \right)}} + w_9 \right)} } } \]
The artificial neural network looks complicated because it has so many terms. But take a closer look. The mathematical operations are simple - addition, subtraction, multiplication and exponentiation. In reality, our artificial neural network is a combination of many simple mathematical steps.
This is the foundation for the more advanced networks used in Alexa and other cutting edge- technologies. Pretty incredible that you could do most of Alexa's calculations on your calculator, right?
Right now, we could take out a calculator and start making predictions using the example neural network. All we need is our patient's temperature, heart rate, and the w values. Then, we would plug those values into the equation above. And, voila! Out comes our prediction of whether our patient is sick or not.
However, there's a catch. For the network to be useful, we need the predictions to be accurate, and the key to making accurate predictions is finding the best values for the w terms in the equation. You can think of these w's like settings - when we change the settings, we change the network equation, which makes our predictions better or worse.
 That's exactly the same way that Alexa can recognize your voice – in her neural network she has found the right settings to make her predictions really good. But unlike our example, Alexa most likely has hundreds or thousands of w settings in total, compared to our robot, which has only nine (w1, w2, w3, w4, w5, w6, w7, w8 and w9).
The real challenge of a neural network is to learn the best w settings that make the predictions as good as possible. This process is called "training". Unfortunately, when we are just starting out, we have no idea what the settings should be. Our best option is to start by guessing values for the ws.
In this example, we will start by guessing that every w setting is equal to 1 (w1 = w2 = w3 = w4 = w5 = w6 = w7 = w8 = w9 = 1).
To train the robot, we need some data - which we need to collect or find in a database.
In our robot example, we will hire a doctor. The doctor will examine 10 patients, measuring their heart rate (HR), temperature (T), and whether they were sick or not (S).
[Click the doctor to collect data from each patient!]
Training a network is a trial-and-error process. Now that we have our data, we need to do the "trial" part, using our equation to see if the w values work well.
First, we will plug our w values into the equation (remember, to start we guessed that all ws = 1). Then, for each subject, we will plug in the subject's temperature, heart rate. Once this is done, we can calculate our predictions of whether the patient was sick or not (0 = not sick, 1 = sick).
[Click the gears to read in patient data and predict if the patient is sick or not.]
After trying our equation (the "trial" part), we correct for any errors the network made (the "error" part). And the first predictions are awfully full of errors because we started off by guessing that all ws = 1.
But before we start changing any w settings to correct our errors, we have to define what we mean by error. In general, error refers to how far off our predictions are from the truth. In this example, we will use a specific type of error - the sum of squared errors.
To calculate the sum of square errors, we go patient by patient and calculate the difference between our prediction and the actual value. Then, we square that number. After we do this for all our patients, we add up all the results. The total is the sum of squared errors.
At this stage, we update the w settings to make the sum of squared error a little bit smaller. And we repeat this process over and over. We can use many different rules to update our w values, but this is beyond the scope of this article.
To truly train an artificial neural network well, we change the settings many times: sometimes thousands of times, sometimes millions of times, and sometimes even more! And eventually, our network makes smaller and smaller errors as we update the settings.
  Ultimately, brain cells are the reason why we can create works of art, beautiful dances and engineering marvels.
Clearly, brain cells can do some pretty amazing things. So why not try to imitate the way the brain works?
Artificial Neural Networks are exactly that - a simple attempt at programming a computer to work like a brain.
Artificial Neural Networks take a few key behaviors from brain cells and try to replicate those behaviors in a computer program. Specifically, there are three features that are explicitly programmed into an artificial neural network.
1) Good listener. When a real brain cell communicates with other brain cells, the first thing it does is listen.
Before anything else, the cell listens to all the other cells communicating with it. Then, only after it has listened, the cell will decide to how to respond. Because the cell listens first and then responds, the total of all signals coming in to a cell can be thought of as an input.
2) Threshold. If a brain cell doesn't receive enough input, it will not send any electrical signals of its own. Essentially, there's a threshold effect - below the threshold, nothing happens. Above the threshold value, more input leads to more output.
3) Selective listening. Not all input signals are equal; signals from some brain cells count than others.
Just like advice from a trusted friend may count more than advice from a reckless friend, signals from some neurons count more than signals from other neurons. For example, some signals could be worth 3x more than others. And some signals could be worth nothing at all.
Click the example below to see how the neural network equation imitates biological brains.
So, why imitate biological brains?
Biological brains can learn, and get better and better at different tasks. This is a really desirable feature for a computer program - even a simplified version of a brain can be taught to recognize faces or voices. So next time you talk to Siri, just remember, she's working with some similar hardware - but right now, you just have the more advanced version.


This bookmarklet inserts the current date at the cursor position in any text input field.
The default format is dd.MM.yyyy for plain text fields, but you can make it use another format (including time formats) by selecting a format string first.
If you call the bookmarklet without a selection (e.g. by simply clicking the buttons below without first selecting anything in the text fields), the current date will be inserted in the text field. More precisely, it will be inserted at the current cursor position.
To have more control over the output, you can enter a format string into the text field and select it. The script will then take this format string to format the date.
The following format codes are understood:
Examples:
Test the functionality in a <textarea> field:
Test the same in an <input type="text"> field:
The script is aware of other types of <input> fields and will adjust the default date or time format accordingly, but at the moment the following field types are simply treated as "text" fields internally by common web browsers. For this reason, you will probably not see any different behaviour…
© 2016 by Sascha René Leib, all rights reserved.


--- layout: post title: The $2955 Ordeal date: 2009-11-12 20:47:17.000000000 -06:00 categories: - General tags: - technology - want status: publish type: post published: true meta: _edit_last: '1' author: login: Blake email<EMAIL_ADDRESS>display_name: Blake first_name: Blake last_name: Harley ---
Someone should pony up $2955, so I can get this PCI graphics card with 8 monitor connections and 6 more monitors.
Please?


Drag to rotate or toggle variables on the right ⟶ a game made by Aaryan Pradhan
Loading...a game made by Aaryan Pradhan
This is a WebGL demo and very unlikely to work unless you run a recent variant of Chrome or Firefox .a game made by Aaryan Pradhan


BREAKING NEWS
Elon has landed on Mars!! And his tweets are totally bonkers!
Generate Tweet
Elon's
"Ex-celfie"


| KEYCTL(2) | Linux Key Management Calls | KEYCTL(2) |
#include <sys/types.h> #include <keyutils.h>
long keyctl(int operation, ...) /* For direct call via syscall(2): */ #include <asm/unistd.h> #include <linux/keyctl.h> #include <unistd.h>
long syscall(__NR_keyctl, int operation, __kernel_ulong_t arg2, __kernel_ulong_t arg3, __kernel_ulong_t arg4, __kernel_ulong_t arg5);
No glibc wrapper is provided for this system call; see NOTES.
The operation performed by keyctl() is determined by the value of the operation argument. Each of these operations is wrapped by the libkeyutils library (provided by the keyutils package) into individual functions (noted below) to permit the compiler to check types.
The permitted values for operation are:
struct iovec { void *iov_base; /* Starting address of buffer */ size_t iov_len; /* Size of buffer (in bytes) */ };
/proc/sys/kernel/keys/persistent_keyring_expiry
struct keyctl_dh_params { int32_t private; /* The local private key */ int32_t prime; /* The prime, known to both parties */ int32_t base; /* The base integer: either a shared generator or the remote public key */ };
struct keyctl_kdf_params { char *hashname; /* Hash algorithm name */ char *otherinfo; /* SP800-56A OtherInfo */ __u32 otherinfolen; /* Length of otherinfo data */ __u32 __spare[8]; /* Reserved */ };
On error, -1 is returned, and errno is set appropriately to indicate the error.
As described in request_key(2), the request-key(8) program is invoked with command-line arguments that describe a key that is to be instantiated. The example program fetches and logs these arguments. The program assumes authority to instantiate the requested key, and then instantiates that key.
The following shell session demonstrates the use of this program. In the session, we compile the program and then use it to temporarily replace the standard request-key(8) program. (Note that temporarily disabling the standard request-key(8) program may not be safe on some systems.) While our example program is installed, we use the example program shown in request_key(2) to request a key.
$ cc -o key_instantiate key_instantiate.c -lkeyutils $ sudo mv /sbin/request-key /sbin/request-key.backup $ sudo cp key_instantiate /sbin/request-key $ ./t_request_key user mykey somepayloaddata Key ID is 20d035bf $ sudo mv /sbin/request-key.backup /sbin/request-key
Looking at the log file created by this program, we can see the command-line arguments supplied to our example program:
$ cat /tmp/key_instantiate.log Time: Mon Nov 7 13:06:47 2016 Command line arguments: argv[0]: /sbin/request-key operation: create key_to_instantiate: 20d035bf UID: 1000 GID: 1000 thread_keyring: 0 process_keyring: 0 session_keyring: 256e6a6 Key description: user;1000;1000;3f010000;mykey Auth key payload: somepayloaddata Destination keyring: 256e6a6 Auth key description: .request_key_auth;1000;1000;0b010000;20d035bf
The last few lines of the above output show that the example program was able to fetch:
The example program in request_key(2) specified the destination keyring as KEY_SPEC_SESSION_KEYRING. By examining the contents of /proc/keys, we can see that this was translated to the ID of the destination keyring (0256e6a6) shown in the log output above; we can also see the newly created key with the name mykey and ID 20d035bf.
$ cat /proc/keys | egrep 'mykey|256e6a6' 0256e6a6 I--Q--- 194 perm 3f030000 1000 1000 keyring _ses: 3 20d035bf I--Q--- 1 perm 3f010000 1000 1000 user mykey: 16
/* key_instantiate.c */ #include <sys/types.h> #include <keyutils.h> #include <time.h> #include <fcntl.h> #include <stdio.h> #include <stdlib.h> #include <unistd.h> #include <string.h> #include <errno.h> #ifndef KEY_SPEC_REQUESTOR_KEYRING #define KEY_SPEC_REQUESTOR_KEYRING -8 #endif int main(int argc, char *argv[]) { FILE *fp; time_t t; char *operation; key_serial_t key_to_instantiate, dest_keyring; key_serial_t thread_keyring, process_keyring, session_keyring; uid_t uid; gid_t gid; char dbuf[256]; char auth_key_payload[256]; int akp_size; /* Size of auth_key_payload */ fp = fopen("/tmp/key_instantiate.log", "w"); if (fp == NULL) exit(EXIT_FAILURE); setbuf(fp, NULL); t = time(NULL); fprintf(fp, "Time: %s\n", ctime(&t)); /* * The kernel passes a fixed set of arguments to the program * that it execs; fetch them. */ operation = argv[1]; key_to_instantiate = atoi(argv[2]); uid = atoi(argv[3]); gid = atoi(argv[4]); thread_keyring = atoi(argv[5]); process_keyring = atoi(argv[6]); session_keyring = atoi(argv[7]); fprintf(fp, "Command line arguments:\n"); fprintf(fp, " argv[0]: %s\n", argv[0]); fprintf(fp, " operation: %s\n", operation); fprintf(fp, " key_to_instantiate: %lx\n", (long) key_to_instantiate); fprintf(fp, " UID: %ld\n", (long) uid); fprintf(fp, " GID: %ld\n", (long) gid); fprintf(fp, " thread_keyring: %lx\n", (long) thread_keyring); fprintf(fp, " process_keyring: %lx\n", (long) process_keyring); fprintf(fp, " session_keyring: %lx\n", (long) session_keyring); fprintf(fp, "\n"); /* * Assume the authority to instantiate the key named in argv[2] */ if (keyctl(KEYCTL_ASSUME_AUTHORITY, key_to_instantiate) == -1) { fprintf(fp, "KEYCTL_ASSUME_AUTHORITY failed: %s\n", strerror(errno)); exit(EXIT_FAILURE); } /* * Fetch the description of the key that is to be instantiated */ if (keyctl(KEYCTL_DESCRIBE, key_to_instantiate, dbuf, sizeof(dbuf)) == -1) { fprintf(fp, "KEYCTL_DESCRIBE failed: %s\n", strerror(errno)); exit(EXIT_FAILURE); } fprintf(fp, "Key description: %s\n", dbuf); /* * Fetch the payload of the authorization key, which is * actually the callout data given to request_key() */ akp_size = keyctl(KEYCTL_READ, KEY_SPEC_REQKEY_AUTH_KEY, auth_key_payload, sizeof(auth_key_payload)); if (akp_size == -1) { fprintf(fp, "KEYCTL_READ failed: %s\n", strerror(errno)); exit(EXIT_FAILURE); } auth_key_payload[akp_size] = '\0'; fprintf(fp, "Auth key payload: %s\n", auth_key_payload); /* * For interest, get the ID of the authorization key and * display it. */ auth_key = keyctl(KEYCTL_GET_KEYRING_ID, KEY_SPEC_REQKEY_AUTH_KEY); if (auth_key == -1) { fprintf(fp, "KEYCTL_GET_KEYRING_ID failed: %s\n", strerror(errno)); exit(EXIT_FAILURE); } fprintf(fp, "Auth key ID: %lx\n", (long) auth_key); /* * Fetch key ID for the request_key(2) destination keyring. */ dest_keyring = keyctl(KEYCTL_GET_KEYRING_ID, KEY_SPEC_REQUESTOR_KEYRING); if (dest_keyring == -1) { fprintf(fp, "KEYCTL_GET_KEYRING_ID failed: %s\n", strerror(errno)); exit(EXIT_FAILURE); } fprintf(fp, "Destination keyring: %lx\n", (long) dest_keyring); /* * Fetch the description of the authorization key. This * allows us to see the key type, UID, GID, permissions, * and description (name) of the key. Among other things, * we will see that the name of the key is a hexadecimal * string representing the ID of the key to be instantiated. */ if (keyctl(KEYCTL_DESCRIBE, KEY_SPEC_REQKEY_AUTH_KEY, dbuf, sizeof(dbuf)) == -1) { fprintf(fp, "KEYCTL_DESCRIBE failed: %s\n", strerror(errno)); exit(EXIT_FAILURE); } fprintf(fp, "Auth key description: %s\n", dbuf); /* * Instantiate the key using the callout data that was supplied * in the payload of the authorization key. */ if (keyctl(KEYCTL_INSTANTIATE, key_to_instantiate, auth_key_payload, akp_size + 1, dest_keyring) == -1) { fprintf(fp, "KEYCTL_INSTANTIATE failed: %s\n", strerror(errno)); exit(EXIT_FAILURE); } exit(EXIT_SUCCESS); }
The kernel source files under Documentation/security/keys/ (or, before Linux 4.13, in the file Documentation/security/keys.txt).
| 2019-03-06 | Linux |


<bookpartno>
The <bookpartno> element contains the book's part number, such as 99F1234. A publisher may use a number like this one to identify a book for tracking purposes.
Category: Bookmap metadata elements


MISS CONGENIALITY A film review by James Brundage Copyright 2000 filmcritic.com filmcritic.com
It takes some doing to make a beauty pageant flick that features an intellectually vapid caper plot while being a slap in the face to feminism. When asked (within the movie, I mean) to defend pageantry from this accusation, Sandra Bullock simply shrugs it off and says, "Well, they're not all airheads, and I've made some friends." Forget the fact that nine out of ten women in the film act like vicious bitches to Sandra's character -- a New Jersey FBI agent named Gracie Hart -- and shrug off the fact that each of the contestants is painted to have all of the intelligence of a Pokemon character on a good day. Never mind all that. Sandra has learned that beauty pageants are really scholarship contests and really aren't harmful to feminism.
  The portrayal is stereotypical: frumpy hair, two dates to her name, a punching bag, and a penchant for pints of Ben and Jerry's. To her credit, Sandra Bullock pulls off the deal pretty well, but how she can live with herself after playing such an odious role is beyond me. (She gets paid a lot of money, that's how. -Ed.)
Gracie works at the FBI and, after a sting operation that goes slightly sour after she saves a Russian mobster from choking, she's placed on a desk job until a letter from a Unabomber-like terrorist called "The Citizen" arrives, threatening the Miss United States beauty pageant. The horror! Gracie promptly gets shipped off to Austin, Texas, where, with the help of pageant consultant (imagine that on your business card) Vincent (Michael Caine), she is turned into a prim and proper lady who investigates the pageant by going undercover and becoming fluent in Ditz.
Of course it isn't only the women in Miss Congeniality that get the barbs. All the male FBI agents are painted as ogling idiots, whereas all of the other men in the story are either gay, androgynous, or psychotic. Think of it as Stereotypes for Dummies. Hell, they even throw in a finalist being pulled off the stage for admitting her lesbianism.
To give the devil its due, Miss Congeniality may be just about the most offensive flick of the year, but it also has something of an acrid wit. Bullock is actually watchable (unlike her normal tour de crap), and the movie does have its share of barbs directed towards beauty queens, but this is far outweighed by the fact that Miss Congeniality is just plain nasty. If you're going to be this offensive in a comedy, you know, Chris Rock or John Leguizamo offensive, you have to attack the stereotypes, not embrace them. And it better be damn funny, too. And that Miss Congeniality ain't.
What the hell; if you're at your local multiplex and everything else is sold out, why not brainwash yourself by revisiting the gender/role stereotypes that people have been trying to kill for decades and watch Miss Congeniality. Or actually use your brain for once and see something a little more intelligent. Maybe try the Discovery Channel.

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{{ define "main" }}
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Select a file
Click on the object you would like to remove
Then click this button: ----->
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debug mask canvas


--- creation_epoch:<PHONE_NUMBER> lastmod_epoch:<PHONE_NUMBER> categories: ['Tech Tricks'] title: Stop Ask Toolbar adware in Java install --- Typical method is the offline installer, but for the Java update utility after the install you can do a registry change to disable the sponsor adware in the Java installer.


Donald Norman
Discusses questions of interface complexity, illustrated by examples of modern design.
"Want an example of an unnecessarily complicated, frustrating device? Take my piano. The conrols of the Roland piano shown in figure 1.3 are perplexing beyond belief...saving the settings for a device...is a frequent operation for any device that has numerous adjustments and settings. How are the users of this piano expected to save their settings?
...The steps are so arbitrary and unnatural that each time I have to do this, the first attempt always fails, even with the manual open in front of me. This is an expensive piano, with a great mechanical feel to the keys and excellent acoustics mirroring the rich subtleties of the best acoustic pianos. But the company completely neglected the controls for the piano....In other words, the piano controles were an afterthought, with no attention paid to the needs of the customer - a violent contradiction to the care and concern that wen't into designing the musical quality of the piano.
Usually when I see bad design, I try to imagine what forces were involved to cause such a poor result. In this particular case, I fail. The reasons are unfathomable. Even the Owner's Manual is unintelligible....The major cause of complicated, confusing, frustrating systems is not complexity: It is poor design"
Affordances, Natural complexity
Interaction design


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|
My Project
|
An injection context that can be serialized and sent to the Ghidra client. More...
#include <inject_ghidra.hh>
Public Member Functions | |
| virtual void | saveXml (ostream &s) const |
| Save this context to an XML stream as a <context> tag. More... | |
| Public Member Functions inherited from InjectContext | |
| virtual | ~InjectContext (void) |
| Destructor. | |
| virtual void | clear (void) |
| Release resources (from last injection) | |
Additional Inherited Members | |
| Public Attributes inherited from InjectContext | |
| Architecture * | glb |
| Architecture associated with the injection. | |
| Address | baseaddr |
| Address of instruction causing inject. | |
| Address | nextaddr |
| Address of following instruction. | |
| Address | calladdr |
| If the instruction being injected is a call, this is the address being called. | |
| vector< VarnodeData > | inputlist |
| Storage location for input parameters. | |
| vector< VarnodeData > | output |
| Storage location for output. | |
An injection context that can be serialized and sent to the Ghidra client.
This adds the capability to wrap up the context data in <context> XML tag that can then be forwarded to the Ghidra client.
|
virtual |
Save this context to an XML stream as a <context> tag.
| s | is the output stream |
Implements InjectContext.


No personal information
<% } %>If you can not login your Rstudio for some reason, you may use this tool to reset your Rstudio session.
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If this tool still does not work for you, please contact your supervisor and/or email<EMAIL_ADDRESS>with your info
<% if (user.first_name) { %> A screenshot of your RStudio session every 30~120 seconds.
Sync 10s


class EventGeolocation
Event to update Geolocation inside the SDK.
geolocation
- the new location object
<init> |
Event to update Geolocation inside the SDK. EventGeolocation(geolocation: Location?) |
mGeolocation |
var mGeolocation: Location? |
getLocation |
fun getLocation(): Location? |


I’ll set you free from annoying things by hack
I’m a programmer, DTMer, surfer, and father, living in Kyoto.
Would you like to hangout with me?
Don’t hesitate to contact with me, yo(^^)
Basic Info
Apr 2005 - Mar 2010, Civil Engineering at Kyoto University.
I researched about concrete fracture mecanism.
Apr 2010 - Feb 2013, System consultant at IT Frontier(now Tata Consultancy Services).
I proposed the improvements using SAP to clients.
I took Applied Information Technology Engineer Examination(IPA).
Mar 2013 - Feb 2014, Web programmer at Grow!,Inc.
I impremented the subscription market place, using Ruby on Rails, jQuery, MongoDB on heroku.
Mar 2014 - May 2014, Freelance programmer.
I made the backends of the official mobileapp of JAPAN GIRLS EXPO, using Ruby on Rails, nodejs, MongoDB on AWS. It was difficult to connect 10k clients with websocket and stream data from MongoDB.
May 2014 - Aug 2014, Backend programmer at Ednity.
Ednity. is a Japanese startup company.  I used ruby(Chef),  php(Fuel)  on  AWS.
Sep 2014 - Mar 2017, Backend programmer at Nota.Inc.
I was concerned with Gyazo.
Ruby on Rails, golang, nodejs, React, Chef, Serverspec... on AWS, GCP and hosting servers.
Sometimes, I improved Windows App and chrome extension.
Apr 2017 - present, Freelance programmer
Luckily, I could find some good clients. I enjoy programinng:)
2017 Works
Payment platform(RoR), Real estate value caluculation platform(Angular2, Elixir)
2018 Works
Online comic store (Laravel), Online note taking platform(React/RoR)
2019 Works
I start a personal company. 'til death we do art, Inc
Online comic store(Laravel), CRM iOS app(React/RoR/Swift)
2020 Works
CRM iOS app(React/RoR/Swift), iOS app to design templates(Swift)


CouchModel Class Reference
| Inherits from | CouchDynamicObject : NSObject |
| Declared in | CouchModel.h |
Overview
Generic model class for Couch documents.
There's a 1::1 mapping between these and CouchDocuments; call modelForDocument: to get (or create) a model object for a document, and .document to get the document of a model.
You should subclass this and declare properties in the subclass's @@interface. As with NSManagedObject, you don't need to implement their accessor methods or declare instance variables; simply note them as '@@dynamic' in the class @@implementation. The property value will automatically be fetched from or stored to the document, using the same name.
Supported scalar types are bool, char, short, int, double. These map to JSON numbers, except 'bool' which maps to JSON 'true' and 'false'. (Use bool instead of BOOL.)
Supported object types are NSString, NSNumber, NSData, NSDate, NSArray, NSDictionary. (NSData and NSDate are not native JSON; they will be automatically converted to/from strings in base64 and ISO date formats, respectively.)
Additionally, a property's type can be a pointer to a CouchModel subclass. This provides references between model objects. The raw property value in the document must be a string whose value is interpreted as a document ID.
Tasks
-
+ modelForDocument:
Returns the CouchModel associated with a CouchDocument, or creates & assigns one if necessary.
If the CouchDocument already has an associated model, it's returned. Otherwise a new one is instantiated. If you call this on CouchModel itself, it'll delegate to the CouchModelFactory to decide what class to instantiate; this lets you map different classes to different "type" property values, for instance. If you call this method on a CouchModel subclass, it will always instantiate an instance of that class; e.g. [MyWidgetModel modelForDocument: doc] always creates a MyWidgetModel.
-
– initWithNewDocumentInDatabase:
Creates a new “untitled” model with a new unsaved document.
The document won't be written to the database until save is called.
-
– init
Creates a new “untitled” model object with no document or database at all yet.
Setting its .database property will cause it to create a CouchDocument. (This method is mostly here so that NSController objects can create CouchModels.)
-
document
The document this item is associated with. Will be nil if it’s new and unsaved.
property -
database
The database the item’s document belongs to.
propertySetting this property will assign the item to a database, creating a document. Setting it to nil will delete its document from its database.
-
isNew
Is this model new, never before saved?
property -
– save
Writes any changes to a new revision of the document, asynchronously.
Does nothing and returns nil if no changes have been made.
-
autosaves
Should changes be saved back to the database automatically?
propertyDefaults to NO, requiring you to call save manually.
-
needsSave
Does this model have unsaved changes?
property -
– propertiesToSave
The document’s current properties, in externalized JSON format.
-
– deleteDocument
Deletes the document from the database.
You can still use the model object afterwards, but it will refer to the deleted revision.
-
timeSinceExternallyChanged
The time interval since the document was last changed externally (e.g. by a “pull” replication.
propertyThis value can be used to highlight recently-changed objects in the UI.
-
+ saveModels:
Bulk-saves changes to multiple model objects (which must all be in the same database).
This invokes [CouchDatabase putChanges:], which sends a single request to _bulk_docs. Any unchanged models in the array are ignored.
-
– markExternallyChanged
Resets the timeSinceExternallyChanged property to zero.
-
– getValueOfProperty:
Gets a property by name.
You can use this for document properties that you haven't added @@property declarations for.
-
– setValue:ofProperty:
Sets a property by name.
You can use this for document properties that you haven't added @@property declarations for.
-
attachmentNames
The names of all attachments (array of strings).
propertyThis reflects unsaved changes made by creating or deleting attachments.
-
– attachmentNamed:
Looks up the attachment with the given name (without fetching its contents).
-
– createAttachmentWithName:type:body:
Creates or updates an attachment (in memory).
The attachment data will be written to the database at the same time as property changes are saved.
-
– removeAttachmentNamed:
Deletes (in memory) any existing attachment with the given name.
The attachment will be deleted from the database at the same time as property changes are saved.
-
– initWithDocument:
Designated initializer. Do not call directly except from subclass initializers; to create a new instance call modelForDocument: instead.
-
– idForNewDocumentInDatabase:
The document ID to use when creating a new document.
Default is nil, which means to assign no ID (the server will assign one).
-
– didLoadFromDocument
Called when the model’s properties are reloaded from the document.
This happens both when initialized from a document, and after an external change.
-
– databaseForModelProperty:
Returns the database in which to look up the document ID of a model-valued property.
Defaults to the same database as the receiver's document. You should override this if a document property contains the ID of a document in a different database.
Properties
attachmentNames
The names of all attachments (array of strings).
This reflects unsaved changes made by creating or deleting attachments.
@property (readonly) NSArray *attachmentNames
Discussion
The names of all attachments (array of strings).
This reflects unsaved changes made by creating or deleting attachments.
Declared In
CouchModel.h
autosaves
Should changes be saved back to the database automatically?
Defaults to NO, requiring you to call save manually.
@property (nonatomic) bool autosaves
Discussion
Should changes be saved back to the database automatically?
Defaults to NO, requiring you to call save manually.
Declared In
CouchModel.h
database
The database the item’s document belongs to.
Setting this property will assign the item to a database, creating a document.
Setting it to nil will delete its document from its database.
@property (retain) CouchDatabase *database
Discussion
The database the item’s document belongs to.
Setting this property will assign the item to a database, creating a document.
Setting it to nil will delete its document from its database.
Declared In
CouchModel.h
document
The document this item is associated with. Will be nil if it’s new and unsaved.
@property (readonly, retain) CouchDocument *document
Discussion
The document this item is associated with. Will be nil if it’s new and unsaved.
Declared In
CouchModel.h
isNew
Is this model new, never before saved?
@property (readonly) bool isNew
Discussion
Is this model new, never before saved?
Declared In
CouchModel.h
needsSave
Does this model have unsaved changes?
@property (readonly) bool needsSave
Discussion
Does this model have unsaved changes?
Declared In
CouchModel.h
timeSinceExternallyChanged
The time interval since the document was last changed externally (e.g. by a “pull” replication.
This value can be used to highlight recently-changed objects in the UI.
@property (readonly) NSTimeInterval timeSinceExternallyChanged
Discussion
The time interval since the document was last changed externally (e.g. by a “pull” replication.
This value can be used to highlight recently-changed objects in the UI.
Declared In
CouchModel.h
Class Methods
modelForDocument:
Returns the CouchModel associated with a CouchDocument, or creates & assigns one if necessary.
If the CouchDocument already has an associated model, it's returned. Otherwise a new one is instantiated.
If you call this on CouchModel itself, it'll delegate to the CouchModelFactory to decide what class to instantiate; this lets you map different classes to different "type" property values, for instance.
If you call this method on a CouchModel subclass, it will always instantiate an instance of that class; e.g. [MyWidgetModel modelForDocument: doc] always creates a MyWidgetModel.
+ (id)modelForDocument:(CouchDocument *)document
Discussion
Returns the CouchModel associated with a CouchDocument, or creates & assigns one if necessary.
If the CouchDocument already has an associated model, it's returned. Otherwise a new one is instantiated.
If you call this on CouchModel itself, it'll delegate to the CouchModelFactory to decide what class to instantiate; this lets you map different classes to different "type" property values, for instance.
If you call this method on a CouchModel subclass, it will always instantiate an instance of that class; e.g. [MyWidgetModel modelForDocument: doc] always creates a MyWidgetModel.
Declared In
CouchModel.h
saveModels:
Bulk-saves changes to multiple model objects (which must all be in the same database).
This invokes [CouchDatabase putChanges:], which sends a single request to _bulk_docs.
Any unchanged models in the array are ignored.
+ (RESTOperation *)saveModels:(NSArray *)models
Parameters
- models
An array of CouchModel objects, which must all be in the same database.
Return Value
A RESTOperation that saves all changes, or nil if none of the models need saving.
Discussion
Bulk-saves changes to multiple model objects (which must all be in the same database).
This invokes [CouchDatabase putChanges:], which sends a single request to _bulk_docs.
Any unchanged models in the array are ignored.
Declared In
CouchModel.h
Instance Methods
attachmentNamed:
Looks up the attachment with the given name (without fetching its contents).
- (CouchAttachment *)attachmentNamed:(NSString *)name
Discussion
Looks up the attachment with the given name (without fetching its contents).
Declared In
CouchModel.h
createAttachmentWithName:type:body:
Creates or updates an attachment (in memory).
The attachment data will be written to the database at the same time as property changes are saved.
- (CouchAttachment *)createAttachmentWithName:(NSString *)name type:(NSString *)contentType body:(NSData *)body
Parameters
- name
The attachment name.
- contentType
The MIME type of the body.
- body
The raw attachment data, or nil to delete the attachment.
Discussion
Creates or updates an attachment (in memory).
The attachment data will be written to the database at the same time as property changes are saved.
Declared In
CouchModel.h
databaseForModelProperty:
Returns the database in which to look up the document ID of a model-valued property.
Defaults to the same database as the receiver's document. You should override this if a document property contains the ID of a document in a different database.
- (CouchDatabase *)databaseForModelProperty:(NSString *)propertyName
Discussion
Returns the database in which to look up the document ID of a model-valued property.
Defaults to the same database as the receiver's document. You should override this if a document property contains the ID of a document in a different database.
Declared In
CouchModel.h
deleteDocument
Deletes the document from the database.
You can still use the model object afterwards, but it will refer to the deleted revision.
- (RESTOperation *)deleteDocument
Discussion
Deletes the document from the database.
You can still use the model object afterwards, but it will refer to the deleted revision.
Declared In
CouchModel.h
didLoadFromDocument
Called when the model’s properties are reloaded from the document.
This happens both when initialized from a document, and after an external change.
- (void)didLoadFromDocument
Discussion
Called when the model’s properties are reloaded from the document.
This happens both when initialized from a document, and after an external change.
Declared In
CouchModel.h
getValueOfProperty:
Gets a property by name.
You can use this for document properties that you haven't added @@property declarations for.
- (id)getValueOfProperty:(NSString *)property
Discussion
Gets a property by name.
You can use this for document properties that you haven't added @@property declarations for.
Declared In
CouchModel.h
idForNewDocumentInDatabase:
The document ID to use when creating a new document.
Default is nil, which means to assign no ID (the server will assign one).
- (NSString *)idForNewDocumentInDatabase:(CouchDatabase *)db
Discussion
The document ID to use when creating a new document.
Default is nil, which means to assign no ID (the server will assign one).
Declared In
CouchModel.h
init
Creates a new “untitled” model object with no document or database at all yet.
Setting its .database property will cause it to create a CouchDocument.
(This method is mostly here so that NSController objects can create CouchModels.)
- (id)init
Discussion
Creates a new “untitled” model object with no document or database at all yet.
Setting its .database property will cause it to create a CouchDocument.
(This method is mostly here so that NSController objects can create CouchModels.)
Declared In
CouchModel.h
initWithDocument:
Designated initializer. Do not call directly except from subclass initializers; to create a new instance call modelForDocument: instead.
- (id)initWithDocument:(CouchDocument *)document
Discussion
Designated initializer. Do not call directly except from subclass initializers; to create a new instance call modelForDocument: instead.
Declared In
CouchModel.h
initWithNewDocumentInDatabase:
Creates a new “untitled” model with a new unsaved document.
The document won't be written to the database until save is called.
- (id)initWithNewDocumentInDatabase:(CouchDatabase *)database
Discussion
Creates a new “untitled” model with a new unsaved document.
The document won't be written to the database until save is called.
Declared In
CouchModel.h
markExternallyChanged
Resets the timeSinceExternallyChanged property to zero.
- (void)markExternallyChanged
Discussion
Resets the timeSinceExternallyChanged property to zero.
Declared In
CouchModel.h
propertiesToSave
The document’s current properties, in externalized JSON format.
- (NSDictionary *)propertiesToSave
Discussion
The document’s current properties, in externalized JSON format.
Declared In
CouchModel.h
removeAttachmentNamed:
Deletes (in memory) any existing attachment with the given name.
The attachment will be deleted from the database at the same time as property changes are saved.
- (void)removeAttachmentNamed:(NSString *)name
Discussion
Deletes (in memory) any existing attachment with the given name.
The attachment will be deleted from the database at the same time as property changes are saved.
Declared In
CouchModel.h
save
Writes any changes to a new revision of the document, asynchronously.
Does nothing and returns nil if no changes have been made.
- (RESTOperation *)save
Discussion
Writes any changes to a new revision of the document, asynchronously.
Does nothing and returns nil if no changes have been made.
Declared In
CouchModel.h
setValue:ofProperty:
Sets a property by name.
You can use this for document properties that you haven't added @@property declarations for.
- (BOOL)setValue:(id)value ofProperty:(NSString *)property
Discussion
Sets a property by name.
You can use this for document properties that you haven't added @@property declarations for.
Declared In
CouchModel.h


In a comment on Signs you're a crappy programmer Philip Storry said:
One of my favourite quotes from Ken Thompson (who apparently knows a bit about computers) is:
I tend to break up a subprogram when there are too many local variables. Another clue is [too many] levels of indentation. I rarely look at length.It's not an absolute truth, but he does give two pretty good indicators.
The length of a function isn't important - what you're trying to do in that length is... :-)
This kind of quote used to make me disappointed that I never went to university to do computer science. I imagined that such quotes would be thrown out by a teacher, followed by the magic word "Discuss".
Of course, I eventually met some CS students, who disabused me of this romantic notion. ;-)
Yeah, that would be a neat class, but I never had a class like that. It's not so much the teachers wouldn't be open to that, but that the students wouldn't be capable of following up with a discussion. It would be dumb anyway -- speculating on design practices that apply to something none of the students have ever done: working with code at different stages of the code life cycle. At best the students could rephrase other bits of wisdom heard but never experienced, which does not a discussion make. This describes a large portion of the discussions I had in college classes. Discussion sucked. But then I wasn't a very satisfied student in general.
Number of variables, lines or nested levels is just a sign to take more careful look. Should code be changed or not it depends on context. I can spot bad code from 5 meters, it's much harder to tell if code is done right. Some things are complex and require complex algorithms. On another side, if piece of code does not fit in my screen, it probably will be too complex to fit in my brain in first reads.
# Ģirts
"This kind of quote used to make me disappointed that I never went to university to do computer science. I imagined that such quotes would be thrown out by a teacher, followed by the magic word "Discuss"."
My experience is that only a small part in CS is about programming.


Instructions: This is a preliminary version of a tool to help you discover gender bias in your text. All you have to do is type or paste your text in the box below. Our algorithm will then alert you if any of your word choices are associated with gender by highlighting the words in your text that are "close" to a "male" or "female" direction in the word2vec word embedding. Blue words are stereotypically male, and pink words are stereotypically female (we are aware this is a stereotype in its own right). Ideally you can improve your text by rewriting it to avoid gender biased words.


Pitchstorm is a party game that puts you in the position of an unprepared writer pitching movies to the world's worst executives (AKA, your friends.)
Each round, one player acts as the executive, while everyone else plays as a writer trying to pitch them the next Hollywood Blockbuster.
Writer: Open the "Writer" tab and get new prompts (character, plot, and an award you're aiming for). You can click on any of the prompts once if you want to swap it for a different one. Read the prompts out loud, the executive starts a timer, and you have 40 seconds to pitch your next masterpiece. After that the executive will give you a "helpful" note, and you will have 20 more seconds to incorporate this terrible idea into the story.
Executive: Use the timer to time writer's pitch. Once the author is out of time, interrupt them and give them one of your notes, and set the timer for 20 more seconds.
After everyone has pitched a movie, the executive chooses which one they want to make, and that player gets a point. The next player becomes an executive, and you play the next round. Keep playing until everyone has pitched 3 moives. The person with the most points wins and becomes rich and famous!
| Character | Plot |
|---|---|
|
[Characters] |
[Plots] |
| Award |
|---|
|
[Awards] |
Time Left:
40| Notes |
|---|
|
[Notes] |
|
[Notes] |
|
[Notes] |


Please fill in the appropriate form to register:
Please choose a jpg, gif or png image whose size is inferior to 400 KB


?6
7
8
9
10
L
M
ã
The
New
York
copyright
reserved
botanical
Garden
BOTANICAL
GARDE**,
Collector:
Hawthorne,
W.
D.,
Cable,
S.
&
Jules,
D.
Number:
508
Date:
14
June
2001
Distrib:
FHO
New
York
Botanical
Garden
Family:
Rhizophoraceae
Name:
Cassipourea
guianensis
Aublet
Locality:
Grenada,
St.
Andrew,
Grand
Etang,
on
rim
of
crater
lake
along
path
to
Mount
Qua
Qua.
12¡O6'
N,
61¡42'
W
Alt.
(m):
Notes:
Tree
8
m
tall.
FRUIT:
green,
immature.
DAUBENY
HERBARIUM
(FHO)
University
of
Oxford
Flora
of
Grenada
1623992
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


Gateway
BOT
14-Aug-18 01:04 PM
[dscrdvrsc] <Crypto80> @riesbree I just don't think we realize what it costs, you and I, because I bet it's outrageous
[dscrdvrsc] <Crypto80> Maybe they could keep the money, hire a Dev & get a DEX together
[dscrdvrsc] <Crypto80> Look at NEO & Aphelion, for example
[dscrdvrsc] <riesbree> I really have no idea what the costs are.
[dscrdvrsc] <Crypto80> Hundreds of thousands im sure
[dscrdvrsc] <Crypto80> in coins or Fiat or both
[dscrdvrsc] <Crypto80> I think it's absolutely crazy
[dscrdvrsc] <Crypto80> Centralized exchanges have absorbed a good portion of money that should've stayed in crypto
[dscrdvrsc] <riesbree> I do think it helps to grow i you have an exchange which is better know then the one there is now. But the questions is it worth the costs.
[dscrdvrsc] <Crypto80> I think Dev teams & their contributions deserve something
[dscrdvrsc] <Crypto80> Well it's necessary for exposure and growth.. But we are moving into decentralized exchange era
[dscrdvrsc] <Crypto80> Personally, I believe that money could help actually pay professionals, Dev teams, something--maybe nothing crazy... But we can't copy the corporate structure that got us here .. one man on top, with most.. and everyone else, none
[dscrdvrsc] <Crypto80> I've read about these guys earning near nothing. And the project leader taking millions of coins


Simplify the following expressions to use
.none/some
instead:
ZIO.succeed(None) -> ZIO.none ZIO.succeed(Some(a) -> ZIO.some(a)


---
layout: default
title: Org-mode Cheat Sheet
---
Structural markup elements
Text before the first headline
-
-
#+OPTIONS: skip:t
#+TEXT: This text will go before the *first* headline.
#+TEXT: [TABLE-OF-CONTENTS]
#+TEXT: This goes between the table of contents and the *first* headline


Tata Focused Equity NFO: A multi-cap fund with concentrated bets
The fund will invest in up to 30 high-conviction stocks across various sectors
by Parvatha Vardhini CTata Focused Equity Fund is open for subscription until November 29.
The fund will invest in up to 30 high- conviction stocks with no market capitalisation bias or sector preferences.
Essentially, it will be a multi-cap fund which will take concentrated bets and follow a buy-and-hold’ strategy.
The scheme’s stock selection will be based on a bottom-up approach, following a ‘growth at a reasonable price’ strategy. The fund will be benchmarked to the S&P BSE 200 TRI.
Peer group performance
SEBI’s classification norms brought out in October 2017 define a focussed fund as one that invests a minimum of 65 per cent of its assets in equity and equity-related instruments and restricts itself to a maximum of 30 stocks.
It also requires fund houses to mention where the scheme intends to focus — large/mid/small/ multi caps. The latest NFO from Tata Mutual Fund is in compliance with these terms.
At the time of the reclasssification two years ago, Motilal Oswal Multicap 35, Axis Focused 25, DSP Focus, Sundaram Select Focus and Motilal Oswal Focused 25 were predominantly the ones with a similar strategy. While the first three have a multi-cap bias, the remaining two have a large-cap bias.
Over a longer term of five years, the multi-cap focussed funds have delivered 1-4 percentage points above the returns of the broad Nifty 500 TRI.
The large-cap oriented funds have delivered 2-4 percentage points over the bellwether Nifty 50’s returns.
Following the new categorisation norms, many of the existing funds were tweaked by asset management companies (AMCs) to fit into this category.
The erstwhile HDFC Core and Satellite, Franklin High Growth Companies, SBI Emerging Businesses and Aditya Birla Sun Life Top 100, for instance, are now focussed funds.
Comparing the long-term returns of these funds would not add meaning, considering the recent changes in their characteristics.
At least six fund houses — BNP Paribas, L&T, Mirae, Kotak, IDBI and Union — have come out with NFOs in the focussed funds category after the new classification norms came in. Their short track records mean that their mettle is yet to be tested.
Suitability
Thus, Tata Focused Equity is not a unique offering. Rupesh Patel, its fund manager, explains that the fund will invest in businesses that have a long runway for growth, that is, companies that are at an inflection point in the earnings-growth trajectory and provide value, but are not a value trap . In line with these tenets, banking and financial services, cyclical sectors as well as consumer discretionary stocks will be preferred in the near term.
Though some focussed funds tend to hold cash while waiting for the right opportunities, Tata Focused Equity will not take cash calls, according to the fund manager.
Investors should remember that focussed funds suit only those with an appetite for high risk.
Holding concentrated bets in high-conviction stocks will pay handsome returns if the stocks do well. At the same time, the downside risk is also high if the bets go wrong. Also, such bets may take time to pay off, which is why most of these funds have a low portfolio churn. Hence, only those investors who have a time horizon of at least 3-5 years need to consider this category of funds.
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Behavior
He has a rather explosive and serious character. It can be compared to a wild animal. It is also believed that when he knocks on the stones of his bone, he is transmitting this message.


{% if deal_type == "game" %}
Get it now and for only ${{ deal.price }} join the Stargate adventure!


I'm Araki,a fun of Megurine Luka(Vocaloid)
I met her in 2012 when I was an university freshman.
……とまぁ、実際ただの遊び用Webサイトですのでこれ以上は特に……(笑)
やったぜ、ルカさんウォークマンゲットだぜ！. It contains Luka's tutorial, makes me feel like i'm in heavens.
My English skill was so poor that I cannot listen at Luka's English well.
故に！我はアメリカへ向かったのであった……
I saw her, and...
Mathematics, python and Django
Mathematics, HIV and Web(HTML/CSS/javascript)
What I have ever done
HIV is a big issue for people. I simulate HIV behavior, and discover some interesting facts.
You change me a lot. You tell me a lot. You give me a lot.
I love you, Luka.
ルカさん、大好き( *´艸｀)


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Container
Container class.
Constructor Summary
| Public Constructor | ||
| public |
constructor(domElement: Element | String) Container constructor. |
Member Summary
| Public Members | ||
| public get |
Child containers |
|
| public get |
Container DOM element. |
|
| public get |
Container id. |
|
| public get |
Internal contents of the container |
|
| public get |
Getter to return parent container if available. |
|
| public get |
Copy of the internal state object. |
Method Summary
| Public Methods | ||
| public |
appendChild(child: Container | Element | Text | String, update: Boolean, realign: Boolean): Container Append a child container. |
|
| public |
Predicate to determine if a container or its DOM element is a child of the container. |
|
| public |
Extend view model. |
|
| public |
Dispatch an event with type, optional data and optional arguments to the internal redux store. |
|
| public |
Pipe container updates to a given container. |
|
| public |
Remove a child container. |
|
| public |
Render container to a DOM element. |
|
| public |
replaceChildren(children: Array<Container | Element>): Container Replace child tree with new children. |
|
| public |
Converts container to a JSON serializable object. |
|
| public |
Returns the string reprenstation of this container. |
|
| public |
Unpipe container updates for a given container. |
|
| public |
Updates container and all child containers. |
|
| public |
Consume reducer middleware. |
|
| public |
Returns the associated value of the container. |
Public Constructors
Public Members
Public Methods
public appendChild(child: Container | Element | Text | String, update: Boolean, realign: Boolean): Container source
Append a child container. A child may be an instance of a Container, Element, Text, or a string. Containers are derived from their input and will cause a DOM tree to be restructured.
Example:
container.appendChild(child)
public contains(container: Container | Element, recursive: Boolean): Boolean source
Predicate to determine if a container or its DOM element is a child of the container.
Example:
if (container.contains(child)) {
...
}
public define(model: Object): Container source
Extend view model.
Params:
| Name | Type | Attribute | Description |
| model | Object |
Example:
container.define({value: 0})
public dispatch(type: Mixed, data: Object, args: Object): Container source
Dispatch an event with type, optional data and optional arguments to the internal redux store.
Example:
container.dispatch({
type: 'MY_ACTION',
data: {value: 123},
propagate: false
})
public pipe(container: Container): Container source
Pipe container updates to a given container.
Params:
| Name | Type | Attribute | Description |
| container | Container |
Example:
containerA.pipe(containerB)
public removeChild(child: Container | Element, update: Boolean, realign: Boolean): Container source
Remove a child container. A child may be an instance of a Container or Element. Containers are derived from their input and will cause a DOM tree to be restructured.
Example:
container.removeChild(child)
public render(domElement: Element): Container source
Render container to a DOM element.
Params:
| Name | Type | Attribute | Description |
| domElement | Element |
Example:
container.render(document.body)
public replaceChildren(children: Array<Container | Element>): Container source
Replace child tree with new children.
Params:
| Name | Type | Attribute | Description |
| children | Array<Container | Element> |
Example:
container.replaceChildren([childA, childB, createContainer()])
public unpipe(container: Container): Container source
Unpipe container updates for a given container.
Params:
| Name | Type | Attribute | Description |
| container | Container |
Example:
containerA.unpipe(containerB)
public update(data: Object, propagate: Boolean): Container source
Updates container and all child containers.
Example:
container.update({value: 0})
container.update({value: 0}, false)


The Football Store
Boots
Customers
Orders
1. Fetch All People
XPath Query
search
2. Fetch First Person
XPath Query
search
3. Fetch Name of Person with email =<EMAIL_ADDRESS>XPath Query
search
4. Fetch All Boots
XPath Query
search
5. Fetch Name and Description of All Boots
XPath Query
search
6. Fetch All Boots with price greater than or equal to 325 and less than 425
XPath Query
search
6. Fetch All Orders of Person with id = p1
XPath Query
search


Allows for easy implementation of smooth scrolling for same-page links.
Using npm:
npm install jquery-smooth-scroll
Using bower:
bower install jquery-smooth-scroll
The old-fashioned way:
Go to the following URL in your browser and copy/paste the code into your own file: https://raw.githubusercontent.com/kswedberg/jquery-smooth-scroll/master/jquery.smooth-scroll.js
$('a').smoothScroll();
$('#container a').smoothScroll();
$('#container a').smoothScroll({excludeWithin: ['.container2']});
$('a').smoothScroll({exclude: ['.rough','#chunky']});
$('.backtotop').smoothScroll({offset: -100});
$('a').smoothScroll({afterScroll: function() { alert('we made it!'); }});
The following options, shown with their default values, are available for both $.fn.smoothScroll
and $.smoothScroll
:
{
offset: 0,
// one of 'top' or 'left'
direction: 'top',
// only use if you want to override default behavior
scrollTarget: null,
// fn(opts) function to be called before scrolling occurs.
// `this` is the element(s) being scrolled
beforeScroll: function() {},
// fn(opts) function to be called after scrolling occurs.
// `this` is the triggering element
afterScroll: function() {},
easing: 'swing',
// speed can be a number or 'auto'
// if 'auto', the speed will be calculated based on the formula:
// (current scroll position - target scroll position) / autoCoeffic
speed: 400,
// autoCoefficent: Only used when speed set to "auto".
// The higher this number, the faster the scroll speed
autoCoefficient: 2,
// $.fn.smoothScroll only: whether to prevent the default click action
preventDefault: true
}
The options object for $.fn.smoothScroll
can take two additional properties:
exclude
and excludeWithin
. The value for both of these is an array of
selectors, DOM elements or jQuery objects. Default value for both is an
empty array.
If you need to change any of the options after you’ve already called .smoothScroll()
,
you can do so by passing the "options"
string as the first argument and an
options object as the second.
Utility method works without a selector: $.smoothScroll()
Can be used to scroll any element (not just document.documentElement
/
document.body
)
Doesn’t automatically fire, so you need to bind it to some other user interaction. For example:
$('button.scrollsomething').on('click', function() {
$.smoothScroll({
scrollElement: $('div.scrollme'),
scrollTarget: '#findme'
});
return false;
});
$.smoothScroll
method can take one or two arguments.
scrollTarget
option.The following option, in addition to those listed for $.fn.smoothScroll
above, is available
for $.smoothScroll
:
{
// jQuery set of elements you wish to scroll.
// if null (default), $('html, body').firstScrollable() is used.
scrollElement: null
}
.find()
or .next()
..find()
or .next()
.$('html, body').firstScrollable().animate({scrollTop: someNumber},
someSpeed)
$.fn.smoothScroll
method looks
for an element with an id attribute that matches the
element’s hash.
It does not look at the element’s name attribute. If you want a clicked link
to scroll to a “named anchor” (e.g.
), you’ll need to use the
$.smoothScroll
method instead.$.fn.smoothScroll
and $.smoothScroll
methods use the
$.fn.firstScrollable
DOM traversal method (also defined by this plugin)
to determine which element is scrollable. If no elements are scrollable,
these methods return a jQuery object containing an empty array, just like
all of jQuery’s other DOM traversal methods. Any further chained methods,
therefore, will be called against no elements (which, in most cases,
means that nothing will happen).


Resolve your public IP address and hostname.
$ curl http://www.remoteAddress.net/api/ip %RESPONSE%
NB! hostname
is only included in the response if it could be resolved.
This service resolves hostnames and IP addresses for Nodemailer resolveHostname
option. Powered by OpenShift


class: center, middle, inverse, title-slide # Week 5 - Introduction to Data Viz ### Joshua Rosenberg, Alex Lishinski ### February 18, 2021 --- # Welcome! Welcome to *week 5*! **Record the meeting** --- # Learning a language is hard - None of this is easy or simple - You're programming (and also working with new concepts) - And, learning how to navigate a new course https://twitter.com/datalorax_/status/1361137115497603073 (So, good job! We recognize your difficulties and persistence.) --- # Breakout rooms! Starting with whomever is most advanced in one's graduate program: **One question:** - What kinds of visualization do you find useful/interesting? **One reflection/discussion:** Below, what is the a) data, b) function(s), c) argument name(s), and d) argument(s)? ```r state_data_final <- state_data_merge %>% complete(state, year = 2011:2020) %>% group_by(state) %>% fill(adopted, year_month) ``` --- ### Review of last week's class **Last week we discussed wrangling and tidying data**: 1. Reshaping data - `pivot_wide()` and `pivot_long()` 1. Joining data - `left_join()`, `inner_join()`, and others 1. Grouped data operations with dplyr - `group_by()` and `summarize()` --- ### Review of last week's class **Reading** * From R for Data Science: https://r4ds.had.co.nz/tidy-data.html * tidy data: * every variable has its own column * every observation has its own row * every value has its own cell * tidy data makes it easier to use similar tools (even with very different datasets and types of data) * tidy data works well with R --- ### Review of last week's class *TB cases* - Where is the year variable represented? - Where is the cases variable represented? - How many observations does each row represent? ```r library(tidyverse) ``` ``` ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ── ``` ``` ## ✓ tibble 3.0.6 ✓ forcats 0.5.0 ## ✓ purrr 0.3.4 ``` ``` ## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ── ## x tidyr::extract() masks magrittr::extract() ## x dplyr::filter() masks stats::filter() ## x dplyr::lag() masks stats::lag() ## x purrr::set_names() masks magrittr::set_names() ``` ```r table4a ``` ``` ## # A tibble: 3 x 3 ## country `1999` `2000` ## * <chr> <int> <int> ## 1 Afghanistan 745 2666 ## 2 Brazil 37737 80488 ## 3 China<PHONE_NUMBER>66 ``` --- ### Review of last week's class * tidy data: * every variable has its own column * every observation has its own row ```r table4a %>% pivot_longer(c(`1999`, `2000`), names_to = "year", values_to = "cases") ``` ``` ## # A tibble: 6 x 3 ## country year cases ## <chr> <chr> <int> ## 1 Afghanistan 1999 745 ## 2 Afghanistan 2000 2666 ## 3 Brazil 1999 37737 ## 4 Brazil 2000 80488 ## 5 China 1999 212258 ## 6 China 2000 213766 ``` --- ### Homework highlights What do you notice? What do you wonder about?  --- ### This week's topics **Overview** 1. Introduction to data viz 2. A bit more tidying data 3. Data ethics We are by no means done with the data tidying functions we discussed last week! --- class: inverse, center, middle # Part 1/3: Introduction to data viz --- ### 1. Intro to Data Viz **Outline** A. Why visualize data? B. How can we visualize data in R? C. And, how can we make our visualizations aesthetically pleasing? --- ### 1A: Why visualize data? One answer: "You should look at your data." ([Healy, 2018](https://socviz.co/)) *To elaborate on this*: - Visualizations allow to _understand the structure and nature of your data_, and to begin to understand what might relate to what else - Just like we want to be constantly looking at our data in its spreadsheet/table/data frame format (e.g., `str()`, `glimpse()`, and `View()`), visualizing our data can help us to make sure our data contains what we think it does-and it can alert us to when it does not --- ### 1A: Why visualize data? These four different data sets have the same correlation (type `anscombe` in R to view the data), but are very different  --- ### 1A: Why visualize data Another reason to visualize data is to *communicate with others*; you can use visualizations to communicate your findings or results. In example:  ---  https://apreshill.github.io/ohsu-biodatavis/slides.html#33 --- ### 1B: How to visualize data One way to think about visualizing data is in terms of the _type_ of visualization you create: - Histogram - Density plot - Scatter plot - Bar chart - Pie chart ([gasp!](https://socviz.co/refineplots.html)) - Time series plot/line chart --- ### 1B: How to visualize data Another way to think about visualizing data is in terms of the elements that make up a plot. The *grammar of graphics* ([Wickham, 2010](https://www.tandfonline.com/doi/abs/10.1198/jcgs.2009.07098), [Wilkinson, 2012](https://link.springer.com/chapter/10.1007/978-3-642-21551-3_13)) has a particular answer to the question of what a plot includes: Why a grammar of graphics? - gain insight into complex figures - reveal deeper relationships between what may appear to be unrelated visualizations - more flexibly and creatively visualize data--including in ways that do not fit well into one type of plot - suggest what makes a good figure --- ### 1B: How to visualize data? One view of visualizations is that they consist of four components: 1. Data 2. One or more geometric objects (shape, point, line, etc.) 3. A mapping between variables in the data and the geometric objects and their characteristics (including their size and color) 4. A theme --- ### 1B: How to visualize data? Let's see how this might appear: ```r data ``` ``` ## # A tibble: 1,619 x 2 ## name value ## <chr> <dbl> ## 1 Question 1 3.06 ## 2 Question 1 3.69 ## 3 Question 1 1.74 ## 4 Question 1 2.93 ## 5 Question 1 3.11 ## 6 Question 1 4.43 ## 7 Question 1 3.69 ## 8 Question 1 2.96 ## 9 Question 1 4.52 ## 10 Question 1 2.85 ## # … with 1,609 more rows ``` ```r data %>% ggplot(aes(x = name, y = value)) + geom_boxplot() ``` --- ### 1B: How to visualize data? ![](presentations-week-5_files/figure-html/unnamed-chunk-12-1.png) --- ### 1B: How to visualize data - The previous slide contained a u potentially _useful_ plot - However, we might be able to improve both its interpretability and its aesthetic  https://github.com/rstudio/cheatsheets/raw/master/data-visualization-2.1.pdf --- ### 1B: How to visualize data? ![](presentations-week-5_files/figure-html/unnamed-chunk-14-1.png) --- ### 1B: How to visualize data? ![](presentations-week-5_files/figure-html/unnamed-chunk-15-1.png) --- ### 1B: How to visualize data You can create different plots by: - Changing the aesthetic _mapping_ between variables in the data and geometric objects - Changing the geometric objects --- ### 1B: How to visualize data? ![](presentations-week-5_files/figure-html/unnamed-chunk-16-1.png) --- ### 1B: How to visualize data? ![](presentations-week-5_files/figure-html/unnamed-chunk-17-1.png) --- ### 1C: How to make visualizations aesthetically pleasing  --- _Theming and fine-tuning_ ```r data %>% ggplot(aes(x = value, y = name, fill = name)) + geom_jitter(color = "gray") + geom_violin() + theme_minimal() + scale_fill_brewer("", type = "qual") + ylab(NULL) + xlab(NULL) + theme(text = element_text(size = 16, family = "Times"), legend.position = "none") + ggtitle("Distributions for the Five Questions") ``` ---  --- class: inverse, center, middle # Part 2/3: A bit more tidying data --- ### 2: How does tidying data relate to data viz? Often, we have to make changes to our data frame in order to create the visualization we would like to create. --- ### 2: How does tidying data relate to data viz? **Making a new variable prior to plotting the data** ```r pred_frame %>% mutate(isTeacher = ifelse(isTeacher == 0, "Non-Teachers", "Teachers")) %>% ggplot(aes(year_of_post_centered + 2016, prediction)) + geom_line(aes(color = type_of_tweet), size = 1.3) + geom_text(aes(label = label, color = type_of_tweet), family = "Times New Roman", data = label_frame) + facet_wrap(~isTeacher, ncol = 1) + scale_x_continuous("Year", breaks = seq(2010, 2020, 2)) + labs(x = "Year", y = "Standardized Model-Predicted Sentiment Score") ``` --- ### 2: How does tidying data relate to data viz?  --- ### 2: How does tidying data relate to data viz? _Other data tidying steps_ we might take prior to visualizing data: - **recoding** variables - **creating a factor** (so that we can order elements of a plot as we wish for them to be ordered) - **grouping** and **summarizing** to plot a summary statistic - realizing that your data processing and tidying was not quite sufficient, so **returning to those stages** before finalizing your visualization - **re-running our analysis** (`.Rmd` file) because we discovered an issue with our data --- class: inverse, center, middle # Part 3/3: Data ethics --- ### 3: Why data ethics? With great data powers comes great responsibility! - Ethics matter, especially when we are working with vulnerable populations (or data about them) - And, ethical concerns may extned beyond what our Institutional Review Board considers --- ### 3: Why data ethics? "... Surveillance photos were taken from the building on the upper right and captured images of more than 1.700 students, faculty members and other passers-by walking on the path near the West Lawn, the large grassy area on the left."  https://www.denverpost.com/2019/05/27/cu-colorado-springs-facial-recognition-research/ --- ### 3: Examples of positive and negative data ethics - Positive: Privacy threat modeling and plan mitigation strategies ([Lundberg et al., 2019](https://journals.sagepub.com/doi/abs/10.1177/2378023118813023)) - Negative: Identifying individual participants through social media posts included in presentations and publications --- # Course Logistics **This week** * Exam 1: [Recap](https://utk.instructure.com/courses/121991/quizzes/183019/statistics) * Homework 5: Due by Tuesday, 1/23 * Readings * 1: Considerations for using social media data in learning design and technology research ([Greenhalgh et al., 2020](http://www.researchmerge.com/uploads/7/5/3/5/75356681/chapter_5_research_methods_in_learning_design_and_technology_pre-print.pdf)) * 2: Data visualization ([Wickham & Grolemund, 2018](https://r4ds.had.co.nz/data-visualisation.html)) **Coming up** * [Data ethics](https://making-data-science-count.github.io/s21-intro-to-data-sci-methods-in-ed/assignment-data-ethics.html) * *Just begin* to think and to ask questions about what you may want to do for [a final project](https://making-data-science-count.github.io/s21-intro-to-data-sci-methods-in-ed/assignments.html); something that will advance your research and allow you to exhibit and extend what you do in class --- # Random - [Analyzing educational data with open science best practices, R, and OSF](https://zoom.us/webinar/register/1216134199427/WN_OpHYNc0PQhSkOVPSB3Qaag) - Continue to express your work/challenges with R as precisely as possible, e.g.: - A data frame versus a data file - The name for a data frame - How do I format code in Slack? Try enclosing code in back tick marks ` ` ` ` --- # Wrapping up In your base group's Slack channel: - What is one thing you learned today? - What is something you want to learn more about? - _Also_, in GIF form (type `/giphy` in Slack, and then a random term), summarize how you are feeling about R


---
layout: page
title: HTML5 Canvas and the Cracked Glass Effect - Revisited
group: canvas
tags : [javascript, html5, canvas, effect, algorithm]
blog: /2012/10/27/html5-canvas-and-the-cracked-glass-effect-revisited/
---
{% include JB/setup %}
A much better version of my original cracking glass effect. Five canvas elements are layered to render
different parts of the effect. Start by clicking the "Draw" button to create the initial paths. Click on
the image to change the center point of the crack. Switch through the different options and apply changes
to see how they affect the output. The default settings generate a nice effect on the flowers. Some tweaking
is needed for the other images.


When Pierre (Gérard Laroche) opens the locker he's inherited from the guy he's just replaced on the nightshift at a bottle factory, he discovers pictures of naked women taped to the inside of the door. As soon as he begins removing them, a burly fellow worker named Fred (Marc Berbe) accosts him. What's the matter with Pierre, he asks in a loud voice audible to the entire team preparing for the evening shift, is he some kind of fag?
This confrontation sets the tone and defines the central dramatic tension of Philippe Le Guay's "Nightshift", which was shown last night (March 15, 2001) as part of series on recent French cinema at Lincoln Center's Walter Reade Theater. The French title is "Trois Huit", or 3 by 8, to designate the way a day is divided into three 8-hour shifts in a typical factory. The decision to make a movie on location in a bottle factory, with characters drawn from the blue-collar world, is reflective of a trend among younger French directors to root cinema in the social reality of France's majority.
Anybody who has seen "Human Resources" will see the similarity. Unlike "Human Resources," which depicted a struggle between the workforce as a whole and a boss looking to downsize, "Nightshift" focuses on the conflict between one worker and another. However, the conflict is rooted in deeper social structures in bourgeois society, which the factory, like prisons or highs schools, is apt to intensify.
On his first night on the shift, Pierre becomes the target of an ever-increasing series of mean-spirited pranks. At first Fred treats the incidents as a kind of initiation ceremony. When one of his cohorts throws a bucket of water on Pierre from an overhanging ramp, he is told that it was done to him also on his first night there. But soon it becomes obvious that Fred just has it in for Pierre. He taunts him, steals his food, writes "cocksucker" on the windshield of his car and finally slams a basketball into his face at a company game.
Eventually Pierre has enough of Fred's bullying and confronts him at his apartment, challenging him to a fight. Since Fred is an amateur boxer and at least 30 pounds heavier than Pierre, it is obvious that it would not be a fair fight. In a surprising twist, Fred invites Pierre in for a drink and confesses to him that he does not know why he does the things he does. Perhaps it is a broken marriage and the financial strains of keeping his father in a rest home that makes him nasty. In any case, he just wants to end the one-sided conflict then and there.
Pierre, always anxious to try to get beneath the bullying surface of his tormentor and relate to him as a fellow human being, accepts his peace offer and even loans him money. Unfortunately, he will discover that Fred was lying: a few days later Fred tells the nightshift that he spent Pierre's money on a fish tank rather than family expenses and adds that he will call the fish Pierre.
Even then Pierre finds ways to try to connect to Fred as a human being. Perhaps his greatest flaw is to act ethically in an environment where malice and inhumanity are the norm. During the hazing, Pierre asks a fellow worker--an Arab--why he is joining the rest in tormenting him. He replies, "You have become the Arab here."
If the gullible Pierre is not a satisfying protagonist in terms of our expectations of a typical Hollywood revenge-morality tale, neither is Fred a typical villain. Early in the film he risks his life to dive into a tank of oil and repair a leak that threatened the team's ability to meet the shift's production quota. He also joins the nightshift in helping Pierre lay concrete in the floor of his new home on a weekend afternoon. Afterwards, when the men sit on a nearby field sipping wine, the foreman complains that there is far too little solidarity like they just experienced laying concrete. Everyone is out for himself nowadays. Fred chimes in that there never really was any solidarity.
In the discussion period following the film, a member of the audience complained that the film was ultimately unsatisfying because the bully did not get his comeuppance. Furthermore, she complained that the bully was not believable because of the good aspects of his character. Le Guay quoted Hitchcock in his reply, namely that the more complex a villain, the more successful a film. Beyond the question of dramatic effectiveness, the larger question involves how people become bullies and how the bullied respond.
Speaking as somebody who was bullied in high school, a topic very much in the news now, it dawned on me while watching the film that bullying is very much a form of behavior that is inevitable in capitalist institutions such as factories, high schools and prisons. The high school bullying which made a fourteen year old take murderous revenge against classmates is deeply imbedded in the competitive nature of our society. "Toughening" people up is supposed to hone their survival skills in a market society, with high school the ultimate training ground. Pierre's failings ultimately are like those of Huckleberry Finn's, trying to behave ethically in an unethical society.
Louis Proyect Marxism mailing list: http://www.marxmail.org
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