 Become as one, with all.
Littering a dark and dreary road lay abandoned
We must clear the mind of the past.Forget the ass-rape
relax and meditate and learn again to see with clarity. Become as one, with all.
Littering a dark and dreary road lay abandoned
We must clear the mind of the past.Forget the ass-rape
relax and meditate and learn again to see with clarity. Become as one, with all.
A copy of a copy. Littering a dark and dreary road lay abandoned We must clear the mind of the past.Forget the ass-rape relax and meditate and learn again to see with clarity. I am Jacks sideways tittie. Become as one, with all.
A copy of a copy. Littering a dark and dreary road lay abandoned We must clear the mind of the past.Forget the ass-rape relax and meditate and learn again to see with clarity. I am Jacks sideways tittie. Become as one, with all.
A copy of a copy. Littering a dark and dreary road lay abandoned We must clear the mind of the past.Forget the ass-rape relax and meditate and learn again to see with clarity. I am Jacks sideways tittie. Become as one, with all.
A copy of a copy. Littering a dark and dreary road lay abandoned We must clear the mind of the past.Forget the ass-rape relax and meditate and learn again to see with clarity. I am Jacks sideways tittie. Become as one, with all.
A copy of a copy. Littering a dark and dreary road lay abandoned We must clear the mind of the past.Forget the ass-rape relax and meditate and learn again to see with clarity. I am Jacks sideways tittie. Become as one, with all.
A copy of a copy. Littering a dark and dreary road lay abandoned We must clear the mind of the past.Forget the ass-rape relax and meditate and learn again to see with clarity. I am Jacks sideways tittie. Become as one, with all.
Ahhhhhhhhhhhh


#include <sys/types.h> #include <sys/time.h> #include <sys/resource.h> #include <sys/wait.h> pid_t wait3(int *status, int options, struct rusage *rusage); pid_t wait4(pid_t pid, int *status, int options, struct rusage *rusage);
Feature Test Macro Requirements for glibc (see feature_test_macros(7)):
wait3():
The wait3() and wait4() system calls are similar to waitpid(2), but additionally return resource usage information about the child in the structure pointed to by rusage.
Other than the use of the rusage argument, the following wait3() call:
wait3(status, options, rusage);is equivalent to:
waitpid(-1, status, options);Similarly, the following wait4() call:
wait4(pid, status, options, rusage);is equivalent to:
waitpid(pid, status, options);In other words, wait3() waits of any child, while wait4() can be used to select a specific child, or children, on which to wait. See wait(2) for further details.
If rusage is not NULL, the struct rusage to which it points will be filled with accounting information about the child. See getrusage(2) for details.
SUSv1 included a specification of wait3(); SUSv2 included wait3(), but marked it LEGACY; SUSv3 removed it.
On Linux, wait3() is a library function implemented on top of the wait4() system call.


{% macro waterfall_description() -%}
DESCRIPTION: Builds the WebRTC standalone native code branches and tests it
on a variety of platforms.
PURPOSE: Detect errors in the stand-alone WebRTC code when new commits are
submitted to the branches.


Rawsec is a cli for searching and listing all projects present on Rawsec's CyberSecurity Inventory!!
Don’t forget to follow my github and Rawsec repo for news, releases and feedback.
Open an issue here!! I will help you as soon as possible.


@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import timetopaytaxpayer.cor.model.Debit @import model._ @(debits: Seq[Debit])(implicit messages: play.api.i18n.Messages, request: Request[_])
@partials.charge_code(debit.originCode, debit.taxYearEnd) @messages("ssttp.calculator.self-assessment-account-summary-page.for-tax-year", debit.startTaxYear.toString, debit.endTaxYear.toString)
@messages("ssttp.calculator.self-assessment-account-summary-page.includes-interest")


Dhinchek, an amazing online booking system has come up with the widest range of services to provide you with comfort and convenience. With the prime focus to meet and exceed the expectations of our users, our website and user-friendly mobile app allows you to get tailoring and parlour services right on your doorsteps. Yes, now there is no need to step in your car, drive long distance in traffic to your favorite parlor or tailor as all you need is a smartphone coupled with an internet connection to make bookings according to your needs. Fully transparent services of our website and app will surely make a lasting impression on users and provide you with delightful experience.
I am a very simple card. I am good at containing small bits of information. I am convenient because I require little markup to use effectively.
I am a very simple card. I am good at containing small bits of information. I am convenient because I require little markup to use effectively.
I am a very simple card. I am good at containing small bits of information. I am convenient because I require little markup to use effectively.
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Sabres struggle in 4-1 loss to Minnesota Wild
The crisis deepened for the Buffalo Sabres with a 4-1 loss to the Minnesota Wild on Tuesday, Nov. 19, 2019. An announced crowd of 15,522 in KeyBank Center saw the Sabres fall to 1-6-2 in their last nine games with the embarrassing defeat. Buffalo is 10-8-3 overall.
19 Nov 2019, 05:00
Buffalo Sabres GM Jason Botterill speaks to the media.James P. McCoy/Buffalo News
Sabres defenseman Rasmus Dahlin (26) passes the puck past Minnesota Wild left wing Jordan Greenway (18) in the first period at Key Bank Center.James P. McCoy/Buffalo News
Sabres defenseman Colin Miller (33) battles Minnesota's Zach Parise (11) for the puck.James P. McCoy/Buffalo News
Sabres defenseman John Gilmour (58) battles Minnesota Wild left winger Zach Parise (11) for the puck in the first period at Key Bank Center.James P. McCoy/Buffalo News
Sabres center Jack Eichel skates with the puck in the first period at Key Bank Center.James P. McCoy/Buffalo News
Sabres goaltender Linus Ullmark makes a save in the first period.James P. McCoy/Buffalo News
Sabres defenseman Rasmus Ristolainen (55) trips Minnesota Wild center Mats Zuccarello (36) in the first period.James P. McCoy/Buffalo News
Minnesota Wild left wing Zach Parise scores a goal in the first period.James P. McCoy/Buffalo News
Zach Parise celebrates his goal.James P. McCoy/Buffalo News
Minnesota defenseman Jonas Brodin (25) scores the third goal of the game.James P. McCoy/Buffalo News
Minnesota defenseman Jonas Brodin (25) scores the third goal of the game.James P. McCoy/Buffalo News
Sabres center Jack Eichel sits in the penalty box in the second period.James P. McCoy/Buffalo News
Sabres center Jack Eichel skates with the puck against Minnesota left winger Jordan Greenway (18) in the second period at Key Bank Center.James P. McCoy/Buffalo News
Sabres defenseman Rasmus Dahlin looks at the play from the bench in the second period.James P. McCoy/Buffalo News
Related content


River Bank 25 km
Grand Rapids MI/USA
Website: www.53riverbankrun.com
Race Winners
(42 runnings)
1:24:36 1:25:38 1:23:46 1:27:16 1:29:32 12 May
2007
1:14:25
1:25:54
13 May
2006
1:14:21
1:27:47
14 May
2005
1:13:27
1:25:15
08 May
2004
1:15:16
1:26:39
10 May
2003
1:16:13
1:27:28
11 May
2002
1:13:56
1:26:57
12 May
2001
1:14:06
1:24:39
13 May
2000
1:16:26
1:27:35
08 May
1999
1:14:09
1:26:51
09 May
1998
1:13:55
1:28:46
10 May
1997
1:15:21
1:26:54
11 May
1996
1:15:21
1:29:47
13 May
1995
1:15:20
1:27:14
14 May
1994
1:15:01
1:25:26
08 May
1993
1:16:06
1:27:27
09 May
1992
1:14:47
1:26:47
11 May
1991
1:15:31
1:28:29
12 May
1990
1:15:26
1:27:02
13 May 1989
1:16:34
1:25:34
14 May 1988
1:15:56
1:28:39
09 May
1987
1:16:12
1:28:17
10 May
1986
1:16:38
1:24:43
11 May
1985
1:16:58
1:27:25
12 May
1984
1:17:56
1:32:18
07 May
1983
1:16:49
1:31:08
08 May
1982
1:15:00
1:26:31
09 May
1981
1:14:09
1:26:21
10 May
1980
1:16:02
1:37:46
12 May
1979
1:14:29
1:36:39
13 May
1978
1:17:24
1:42:09
11 May
2019
1:13:48
Parker Stinson (CO/USA) (nc)
1:23:51
Emma Bates (ID/USA)
(nc)
12 May
2018
1:14:52
Sam Chelanga (CO/USA) (nc)
1:25:35
Alphine Tuliamuk (AZ)-3
(nc)
13 May
2017
1:14:27.0
Dathan Ritzenhein (MI/USA) (nc)
1:24:35.1
Alphine Tuliamuk (NM)-2
(nc)
14 May
2016
1:15:31.5
Christopher Landry (MI/USA) (nc)
1:25:35.5
Alphine Tuliamuk Bolton (IA/USA)
(nc)
09 May
2015
1:14:56.1
Jared Ward (UT/USA) (nc)
1:26:35.7
Lindsey Scherf (NC/USA)
(nc)
10 May
2014
1:14:08
Samson Gebreyohanes Gezahai (ERI) (nc)
1:25:26
Kellyn Johnson (AZ/USA)
(nc)
11 May
2013
1:14:07
Julius Kipyego Keter (KEN) (nc)
1:25:45
Chemutai Rionotukei (KEN)
(nc)
12 May
2012
1:15:10
Robert Kiprotich Letting (KEN) (nc)
Janet (Cherobon) Bawcom (GA/USA)
(nc)
14 May
2011
1:15:41
Fernando Cabada-2
(CO)
(nc)
Molly Pritz (PA/USA)
(nc)
08 May
2010
1:14:42
Andrew Carlson (MN/USA)
(nc)
Firehiwot Dado Tufa (ETH)
(nc)
09 May
2009
1:15:36
Isaac Kimaiyo Kemboi (KEN)
(nc)
Genoveva Kigen Chelegat (KEN)
(nc)
10 May
2008
1:15:07
Brian Sell (MI/USA)
(nc)
Caroline Chepkorir (KEN)
(nc)
Julius Kibet
Kosgei (KEN) (nc)
Kathryn McGregor (MN/USA) (nc)
Fernando Cabada (VA/USA) (nc)
Viktoriya Klimina (RUS) (nc)
Simon Wangai
Njuguna-2 (nc)
Colleen deReuck (CO/USA) (nc)
Simon Wangai
Njuguna (KEN) (nc)
Alevtina Ivanova (RUS) (nc)
Dan Browne (CO/USA) (nc)
Albina Ivanova (RUS) (nc)
Ronald Mogaka
Boraya (KEN) (nc)
Teresa Wanjiku
Mbugua-2 (nc)
John Kagwe-2 (nc)
Svetlana Zakharova-2 (nc)
Joseph Kariuki-3 (nc)
Svetlana Zakharova (RUS) (nc)
Joseph Kariuki-2 (nc)
Teresa Wanjiku
Mbugua (KEN) (nc)
Joseph Kariuki (KEN) (nc)
Margaret Kagiri (KEN) (nc)
John Kagwe (KEN) (nc)
Kim Jones (USA) (nc)
Alfredo Vigueras (USA) (nc)
Jane Welzel (USA) (nc)
Keith Brantly (FL/USA) (nc)
Elaine vanBlunk (USA) (nc)
Simon Karori (KEN)
Olga Appell (USA)-3
Jerry Lawson (USA)
Olga Appell-2
Bill Reifsnyder (PA/USA)
Olga Appell (MEX)
Mark Plaatges (RSA)
Marcia Narloch (BRA)
Brian Sheriff-2
Diane Gentry-5
Brian Sheriff (ZIM)
Diane Gentry-4
Mark Smith (MI/USA)
Diane Gentry-3
Greg Meyer-7 (nc)
Diane Gentry-2 (nc)
Greg Meyer-6
Joan Samuelson-4
Greg Meyer-5
Joan Samuelson-3
Doug Kurtis (MI/USA)
Diane Gentry (USA)
Greg Meyer-4
Jeanne Lasee (USA)
Greg Meyer-3
Joan Samuelson-2
Herb Lindsay (USA)
Joan Samuelson (ME/USA)
Greg Meyer-2
Karen Blackford MI/(USA)
Greg Meyer (MI/USA)
Cheryl Bridges (USA)
Bill Rodgers (MA/USA)
Diane Culp (USA)
Notes: The course used for the 1981-82 races was remeasured as 150 m short. It is
assumed that the 1978-80 races were also significantly short. Race formerly known as Fifth Third River Bank Run 25-K. Race currently known as Amway River Bank Run 25-K.
(nc) => national champion
2014 Christopher Landry was the national champion (2nd place, 1:14:18)
2013 Josphat Boit was the national champion (2nd place, 1:14:34) after Mohamed Trafeh (1:14:18) was subsequently disqualified due to doping violation
2013 Dorothy McMagon was the national champion (2nd place, 1:25:52)
2012 Joseph Chirlee was the national champion (2nd place, 1:15:10)
2010 Kathyrn McGregor was the national champion (3rd place, 1:26:24)
2009 Dan Browne was the national champion (2nd place, 1:15:56)
2009 Sally Meyerhoff was the national champion (2nd place, 1:27:28)
2008 Paige Higgins was the national champion (3rd place, 1:30:49)
2007 Brian Sell was the national champion (2nd place, 1:14:49)
2006 Turena Johnson-Lane was the national champion (2nd place, 1:28:42)
2005 Brian Sell was the national champion (4th place, 1:15:27)
2004 Dan Browne was the national champion (2nd place, 1:16:21)
2004 Debbi Kilpatrick was the national champion (4th place, 1:31:14)
2003 Christine Clifton was the national champion (2nd place, 1:29:30)
2002 David Morris was the national champion (6th place, 1:17:15)
2002 Jeanne Hennessy was the national champion (2nd place, 1:27:18)
2001 Chad Johnson was the national champion (4th place, 1:16:11)
2001 Milena Glusac was the national champion (3rd place, 1:26:04)
2000 Shawn Found was the national champion (3rd place, 1:17:45)
2000 Kristen Beaney was the national champion (2nd place, 1:28:53)
1999 Todd Williams was the national champion (4th place, 1:17:15)
1999 Christine McNamara was the national champion (3rd place, 1:28:05)
1998 John Sence was the national champion (3rd place, 1:16:15)
1998 Shelly Steely was the national champion (2nd place, 1:29:06)
1997 John Sence was the national champion (3rd place, 1:15:58)
Most Wins (1978-date)
Men
7
Greg Meyer (USA)
1979-80,1982-83,1985-87
Women
5
Diane Gentry (USA)
1984,1987-90
Prize Money
(ADR qualified runners)
Year Men Women Total 2017 $24,300 $37,550 $61,850 2016 24,100 27,350 51,450 2015 25,550 25,050 50,600 2014 24,250 24,400 48,650 2013 25,050 24,850 49,900 2012 24,550 24,400 48,950 2011 15,600 15,600 31,200 2010 23,350 22,950 46,300 2009 19,600 19,600 39,200 2008 20,750 18,200 38,950 2007 21,250 20,950 42,200 2006 20,650 19,600 40,250 2005 20,350 21,150 41,500 2004 19,600 20,850 40,450 2003 21,150 20,550 41,700 2002 21,250 20,650 41,900 2001 21,250 20,950 42,200 2000 21,150 20,850 42,000 1999 21,450 21,150 42,600 1998 19,250 20,050 39,300 1997 19,250 19,950 39,200 1996 16,050 16,525 32,575 1995 14,850 14,100 28,950 1994 16,200 12,550 28,750 1993 15,850 13,650 29,500 1992 9,300 10,400 19,700 1991 9,500 9,500 19,000 1990 8,500 8,000 16,500 1989 8,500 8,500 17,000 1988 8,500 7,000 15,500 Sums $561,950 $566,875 $1,128,835
Race Time Bias (sec/km)
Year Men Women 2017 -4.1 -0.4 2016 -5.0 -3.3 2015 -2.5 +1.3 2014 -3.2 -4.0 2013 -4.7 -4.9 2012 -3.1 -4.0 2011 -2.2 -0.2 2010 -2.9 -1.0 2009 -3.7 +2.1 2008 -3.3 -1.9 2007 -2.7 -0.2 2006 -3.8 -1.1 2005 -2.9 +0.4 2004 -2.6 -0.5 2003 -0.9 -0.6 2002 -0.9 -5.5 2001 -2.7 -3.4 2000 -1.0 +1.8 1999 -2.7 -3.4 1998 -1.8 -3.0 1997 -0.8 -3.7 1996 -2.1 -1.2 1995 -3.8 -3.3 1994 -4.0 -1.8 1993 -0.8 -0.4 1992 -4.3 -1.5 1991 -3.9 -2.8 1990 -3.8 n/c 1989 -2.5 n/c .... 1983 -0.4 n/c .... 1981 -3.4 n/c Avgs -2.8 -1.7
Note: 1981 not included in averages
Competitive Level
(1990-date)
Year Men Women 2017<PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER> n/c 424
Quality Performances
Men <1:13:30 1 <1:14:00 4 <1:14:30 14 <1:15:00 24 <1:15:30 44 <1:16:00 66 <1:16:30 95 <1:17:00 128 <1:17:30 168 <1:18:00 211 <1:18:30 251 <1:19:00 278 Women <1:24:00 1 <1:25:00 6 <1:26:00 19 <1:27:00 35 <1:28:00 65 <1:29:00 92 <1:30:00 129 <1:31:00 160 <1:32:00 199
Note: For 1983 to date.
Last Updated on 16
May 2017
Contributor: Marty Post


These style classes define the skeleton of the components and include css properties such as margin, padding, display type, dimensions and positioning.
Skinning defines the look and feel properties like colors, border colors, background images.
| Style Class | Applies |
|---|---|
| ui-widget | All PrimeNG components |
| ui-widget-header | Header section of a component |
| ui-widget-content | Content section of a component |
| ui-state-default | Default state of a clickable element |
| ui-state-hover | Hover state of a clickable element like mouse over |
| ui-state-active | Active state of a clickable element like mouse press |
| ui-state-highlight | Highlighed elements |
| ui-state-disabled | Disabled elements |
| fa | Icon elements based on font awesome |
These classes are not aware of structural css like margins and paddings, mostly they only define colors. This clean separation brings great flexibility in theming because you don’t need to know each and every skinning selectors of components to change their style.
For example Panel component’s header section has the "ui-panel-titlebar" structural class, to change the color of a panel header you don’t need to about this class as "ui-widget-header" defines colors for panel header.
16 free themes are available for PrimeNG, these include the themeroller themes, twitter bootstrap theme and our custom themes. ThemeSwitcher on the top right section of the page dynamically changes the theme at demo pages. Themes are distributed along with PrimeNG itself. In addition, online ThemeRoller designer allows you to create a PrimeNG theme.
Font-size of free themes use em to define the font size of the widgets using .ui-widget class. This is 1em by default and it is suggested to define a base font-size at the body element of your application to adjust the size of components.
PrimeNG also supports sass based, fully customizable and easy to use premium themes and layouts such as Ultima as Angular CLI projects.


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There's nothing here? Looks like we've got some 'splaining to do.
If you think this is a serious problem, let us know.
Either way, we'll check it out soon.
Why not go to one of these places instead?


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We are a technology-driven Professional Employer Organisation solving the problem of Hiring and Paying your Company's global talent. We understand that identifying and retaining high-quality talent is one of the biggest and most important challenges facing organizations and this is something we take pride in solving. We have a full range of staffing, technical recruiting, and retention services that achieve your goals.
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Products, products, products. Business, business, business. (Is this working?) Better type some more info. Here is some. Here is more. And more. And more. And more, and more, and more, and more, and more.


Phở was born in Northern Vietnam during the mid-1880s. The dish was heavily influenced by both Chinese and French cooking. Rice noodle and spices were imported from China; the French popularized the eating of red meat. In fact, it is believed that "phở" is derived from "pot au feu" a French soup. Vietnamese cooks blended the Chinese, French and native influences to make a dish that is uniquely Vietnamese.
The origins of pho as a Northern dish that spread South explains the key differences between the Northern and Southern variations. Northern style pho tends to be simpler and is made with less ingredients. There are fewer cuts of meat and small slices of ginger are laid on top of the soup. The pho is served without bean sprouts or herbs. Instead, it is accompanied by green chilies and lime only. Southern style pho is a complex dish made from a dozen ingredients. Bean sprouts, fresh basil and saw herb are typically served with each bowl. As with the Northern style pho, green chilies and lime are used as condiments.
Refugees fleeing Vietnam in the Spring of 1975 brought with them their hopes and dreams of a better life. They also brought their cultures and cuisine, of which pho has become the most popular among Americans. Today there are almost 2,000 pho restaurants spread across the United States and Canada. One typically finds Southern style pho served although a few outlets also serve Northern style pho. Typical establishments sell pho and other Vietnamese dishes like goi cuon (spring rolls) and cha gio (eggrolls).


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Simone Merlini
Workshop: How to create a serverless file sharing platform in less than 2 hours
In this workshop you will be guided along the creation of a serverless file sharing platform based on AWS services.
You will learn how to properly integrate Amazon S3, DynamoDB, Cognito, Lambda, API Gateway, and CloudFront to manage authentication, file uploading and file sharing, obtaining an auto-scalable, resilient, managed and highly-available application.


--- title: TameJS date: '2011-07-19T20:21:00.000-07:00' tags: - NodeJS modified_time: '2011-10-09T12:23:55.978-07:00' blogger_id: tag:blogger.com,1999:blog-3456458686961244994.post-4318928056573329466 blogger_orig_url: http://blog.kieranties.com/2011/07/tamejs.html redirect_from: "/2011/07/tamejs.html" ---
Note Tame is not an attempt to dumb down async programming. It's just a cleaner way to write it. Further, your programs will likely have lower latency; with Tame it's a lot easier to keep parallel calls parallel.
Tame JS doesn't just 'dumb down' async programming in Javascript, it makes it beautiful, simple and incredibly elegant.
The sample code demonstrating parallel dns lookups in Node show just how simple it is.
Definitely one to play with in the future.
(again thanks to Steve Pope for the link)


|
SideCar
|
Namespace for all entities specific to the 331 SideCar project. More...
Namespaces | |
| Algorithms | |
| Namespace for entities related to SideCar algorithms. | |
| GUI | |
| Namespace for the GUI applications. | |
| IO | |
| Namespace for entities that handle SideCar data I/O. | |
| Messages | |
| SideCar data message classes. | |
| Parameter | |
| Definitions for algorithm runtime parameter settings. | |
| Runner | |
Namespace for entities related to runner application. | |
| Time | |
| Namespace for entities that handle SideCar time. | |
| Zeroconf | |
| Namespace for entities that interface with Zeroconf library. | |
Data Structures | |
| class | VsipVector |
| Provides a simple wrapper around std::vector-like data structures. More... | |
Namespace for all entities specific to the 331 SideCar project.


@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import uk.gov.hmrc.platformstatusfrontend.models.{GcInformation, GcSummary} @this( layout: Layout ) @(gcSummary: GcSummary)(implicit request: Request[_], messages: Messages) @layout(pageTitle = Some("Garbage")) {
Call to @name failed
} else {


Git is a distributed version control system so it allows you to create branches locally and commit against them. It also supports a more centralized repository model. When using a centralized repository you can push changes to it so that others can pull them more easily. I have a tendency to work on multiple computers. Because of this, I like to use a centralized repository to track the branches as I work on them. That way no matter what machine I'm on, I can still get at my branches.
My workflow is generally something like this:
Git commands can be a bit esoteric at times and I can't always seem to remember how to create a remote git branch and then start working on new code. There also seems to be multiple ways of doing it. I'm documenting the way that seem to work for me so that I can remember it. Maybe it will help someone else too.
Create the remote branch
Make sure everything is up-to-date
Then you can see that the branch is created.
This should show 'origin/new_feature_name'
This means that when you do pulls that it will get the latest from that branch as well.
If you make a mistake you can always delete the remote branch (Ok Git'ers - that has to be the least intuitive command ever.)
When you get to another computer or clone the git repository to a new computer, then you just need to start tracking the new branch again. to show all the remote branches to start tracking the new branch
That's a pretty easy thing to automate with a small shell script luckily
For further help, you might want to check out:
[ad name="image-banner"]


Technology geek interested in product management, software engineering and entreprenurship especially in the fintech area.
Soccer fanatic who loves to play, watch and talk soccer aka football. Contact me if you need a place to play soccer or watch games.


Quick tip: Using line_profiler in an IPython notebook
Sat 17 May 2014 [ James Booth ]
Installation
Install line profiler1
> pip install --pre line_profiler
You can install line_profiler as a proper IPython extension, but I like the simplicity of just activating it when I need it. just run
import line_profiler
import IPython
ip = IPython.get_ipython()
ip.define_magic('lprun', line_profiler.magic_lprun)
in a cell and you're good for the session.
Usage
Let's say we have a function call foo()
which is taking a long time, and we strongly suspect that it's the bar
function call inside it that's taking a while. We tell line profiler of all functions we are interested in with the -f
flag (you can have multiple!) and finally tell it the function to actually execute at the end:
from mypackage import foo, bar
%lprun -f bar foo()
This works perfectly well with objects and methods too, just specify the method you want to profile with it's full name (i.e. in it's class namespace)
from mypackage import MyClass
instance = MyClass()
%lprun -f MyClass.bar instance.foo()
-
As of May 2014 we need
--pre
because later versions of pip won't install betas by default, and the current version of line_profiler is1.0b3
. Once there's no longer ab
at the end of the version stringpip install line_profiler
will be sufficient. ↩
Category: Blog Tagged: IPython profiling tip


Toyota says labor officials found it responsible for worker suicide
Toyota Motor Corp on Tuesday said Japanese labor officials have found it responsible for the suicide of an employee, with the Mainichi Shimbun reporting that workplace bullying at the automaker had led to the employee's death.
TOKYO: Toyota Motor Corp on Tuesday said Japanese labor officials have found it responsible for the suicide of an employee, with the Mainichi Shimbun reporting that workplace bullying at the automaker had led to the employee's death.
The news comes as a shrinking workforce and changing values about work-life balance in Japan have meant companies are increasingly found responsible for workplace-related suicide.
Toyota City's labor standards officials had been investigating the 2017 suicide of a Toyota Motor employee, a spokesman at the automaker confirmed to Reuters.
"It's true that the labor authority determined it was a workplace injury, but we cannot comment further as discussions between representatives are ongoing," the spokesman said.
Daily newspaper Mainichi Shimbun, which was the first to report the officials' conclusion, said that the employee's supervisor had called him an "idiot" said he was "better dead".
The worker committed suicide in a company dormitory at the age of 28, the newspaper reported. The worker's family plans to sue the automaker, the newspaper said.
Labor officials declined to confirm their decision to Reuters, saying they could not comment on individual cases.
Prime Minister Shinzo Abe has been pushing to improve workplace practices in favor of workers' rights, with issues such as parental leave increasingly in the spotlight.
(Reporting by Takashi Umekawa; Editing by Ritsuko Ando and Christopher Cushing)


org.jclouds.vcloud.director.v1_5.domain.section
Classes
CustomizationSection
CustomizationSection.Builder
GuestCustomizationSection
GuestCustomizationSection.Builder
LeaseSettingsSection
LeaseSettingsSection.Builder
NetworkConfigSection
NetworkConfigSection.Builder
NetworkConnectionSection
NetworkConnectionSection.Builder
OperatingSystemSection
OperatingSystemSection.Builder
RuntimeInfoSection
RuntimeInfoSection.Builder
VirtualHardwareSection
VirtualHardwareSection.Builder


Urbanization is the process by which rural communities grow to form cities, or urban centers, and, by extension, the growth and expansion of those cities. Urbanization began in ancient Mesopotamia in the Uruk Period (4300-3100 BCE) for reasons scholars have not yet agreed on. It is speculated, however, that a particularly prosperous and efficient village attracted the attention of other, less prosperous, tribes who then attached themselves to the successful settlement. The historian Lewis Mumford notes that: ...though permanent villages date only from Neolithic times, the habit of resorting to caves for the collective performance of magical ceremonies seems to date back to an earlier period…The outline of the city as both an outward form and an inward pattern of life might be found in such assemblages (1).
Read More


--- layout: archive title: Zulip Chat Archive permalink: /stream/144837-PR-reviews/topic/.231049.20refactor.20CommRing.20adjunctions.html ---
I think this PR is almost ready for merging. I have one more question about this part of the diff: https://github.com/leanprover-community/mathlib/pull/1049/files#diff-df9eb192d84dc1f7ccf4281245940229.
Should the mention of int.cast
be explicit, or should we use coercions?
@Mario Carneiro @Scott Morrison @Chris Hughes
E.g. in the type of
lemma hom_C (f : mv_polynomial σ ℤ → β) [is_ring_hom f] (n : ℤ) : f (C n) = int.cast n := congr_fun (int.eq_cast' (f ∘ C)) n
use coe
@Scott Morrison Could you make this change? After that, I think it's ready to merge.
Unfortunately this change causes a deterministic timeout in the next proof, that I haven't been able to fix. See the latest commit, or:
lemma hom_C (f : mv_polynomial σ ℤ → β) [is_ring_hom f] (n : ℤ) : f (C n) = (n : β) := congr_fun (int.eq_cast' (f ∘ C)) n /-- A ring homomorphism f : Z[X_1, X_2, ...] -> R is determined by the evaluations f(X_1), f(X_2), ... -/ @[simp] lemma eval₂_hom_X {α : Type u} [decidable_eq α] (f : mv_polynomial α ℤ → β) [is_ring_hom f] (x : mv_polynomial α ℤ) : eval₂ (λ n : ℤ, (n : β)) (f ∘ X) x = f x := mv_polynomial.induction_on x (λ n, by { rw [hom_C f], /- deterministic timeout: -/ rw [eval₂_C], }) (λ p q hp hq, by { sorry /- rw [eval₂_add, hp, hq], exact (is_ring_hom.map_add f).symm }) -/}) (λ p n hp, by { sorry /-rw [eval₂_mul, eval₂_X, hp], exact (is_ring_hom.map_mul f).symm }) -/})
Hmmm... that's disappointing.
@Scott Morrison Aaah, I see you already found a fix.
There is one more statement with int.cast
s. Once those are gone I'll merge this.
A hard task-master! :-)
Done.
@Scott Morrison Did you find a different "one more statement" then I had in mind?
I commented on a line on the PR page... that one still has int.cast
:rolling_on_the_floor_laughing:
Oh, I found the one in the actual adjunction file.
Lol, I hope you don't mind pushing one more fix :stuck_out_tongue_wink:
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


About
What is it about!
With the great increase in credit card transactions, credit card fraud has become a major problem in recent years. In Modern day, the fraud is one of the major causes of great financial losses, not only for governments and banks but also the clients are affected.
This project intends to detect 100\% of fraudulent transactions and to minimize the incorrect fraud transactions, in machine learning it is considered as a classification problem.
Services
What we do offer
Single prediction
Gives the possibility for the user to check if a single transaction is whether a fraud or not
File prediction
Gives the possibility for the user to check if a file of transactions are whether a fraud or not
Team
Our Hardworking Team


Check out the Quick Start to get an idea of what you can do by looking at live code and examples.
Log in using your Splunk credentials:
© 2005-2013 Splunk Inc. Application Framework 1.0.1


Using Internet Explorer under Windows Vista or above or Windows
Server 2008, you need to configure the following for this to work:
- Add this site to the Trusted Sites list: in Internet
Options -> Security -> Trusted Sites -> Sites -> Add ...
- You may need to configure the trust level (in this tab), using
Custom Level...: enable Initialize and script ActiveX
controls not marked as safe for scripting.
- If you are using Windows Vista without SP1 or above, you will
probably need to install this certificate as a
Trusted Root Certification Authority Certificate for your own
certificate installation to succeed. You should probably remove that
trusted root CA certificate afterwards.


{{/* Use Hugo's native Table of contents feature. You must set `toc: true` in your parameters for this to show. https://gohugo.io/content-management/toc/ */}} {{- if .Params.toc -}}
{{ i18n "whatsInThis" . }}


Tween Class
Tween
Instantiation
- scrawl.makeTween()
Purpose
- Defines a set of attribute update definitions for objects
Access
- scrawl.tween.TWEENNAME - for the Tween object
Tween functions
- A Tween can be deleted by calling the kill() function on it.
Constructor
Tween
-
[items]
Parameters:
-
[items]
Object optionalKey:value Object argument for setting attributes
Item Index
Methods
Methods
addToTargets
-
items
Add Objects to targets attribute - assumes that the supplied Array will augment any existing targets array
Parameters:
-
items
ArrayArray of Objects and/or Strings, can also be single Object or string
Returns:
this
addToTicker
-
item
Add tween to given ticker
If tween is already subscribed to a different ticker, the function will automatically unsubscribe from that ticker before subscribing to the new ticker
Parameters:
-
item
StringTICKERNAME to which this Tween will subscribe
Returns:
this
calculateEffectiveDuration
-
[item]
Get the effective (millisecond number) duration for the tween
Parameters:
-
[item]
String optionalnew time value; defaults to this.time
Returns:
this
calculateEffectiveTime
-
[item]
Get the effective (millisecond number) time when tween will trigger
Parameters:
-
[item]
String optionalnew time value; defaults to this.time
Returns:
this
clone
-
Object
Create a clone of this Tween
Note: strongly advise every call to this function includes newly created anonymous functions for the action and revert attributes in the argument object - Scrawl's clone functionality does not clone function attributes!
Parameters:
-
Object
Objectcontaining key:value attributes
Returns:
a new copy of the Tween object
doSimpleUpdate
-
items
Perform a simple update
Parameters:
-
items
ObjectObject sent by ticker
Returns:
always true
engineActions
()
private
Tween engine helper object
get
-
item
Retrieve an attribute value. If the attribute value has not been set, then the default value for that attribute will be returned.
Parameters:
-
item
StringAttribute key
Returns:
Attribute value
Example:
var box = scrawl.makeBlock({
width: 50,
});
box.get('width'); //returns 50
box.get('height'); //returns 0
box.get('favouriteAnimal'); //returns undefined
getEndTime
()
private
retrieve the completion time for the action
Returns:
Number
halt
()
Halt the tween's ticker
Returns:
this
kill
()
Remove this Tween from the scrawl library (including any self-created ticker associated with the tween)
Returns:
Always true
numberConvert
-
val
-
dim
Stamp helper function - convert string percentage values to numerical values
Parameters:
-
val
Stringcoordinate String
-
dim
Numberdimension value
Returns:
Number - value
parse
()
Turn the object into a JSON String
Returns:
object of object's currently set attributes
parseDefinitionsValue
-
value
setDefinitionsValues helper function
Parameters:
-
value
Stringto be parsed; can also be a Number
Returns:
Array of parsed values in the form ['Suffix', Number]
removeFromTargets
-
items
Remove Objects from targets attribute - will not remove an object with no name and/or type attributes
Parameters:
-
items
ArrayArray of Objects and/or Strings, can also be single Object or string
Returns:
this
removeFromTicker
-
item
Remove action from given ticker
Parameters:
-
item
StringTICKERNAME to which this Tween will unsubscribe
Returns:
this
resume
()
Resume the tween's ticker
Returns:
this
run
()
Start the tween's ticker from 0
Returns:
this
seekFor
()
seekFor a different relative point on the tween's ticker
Returns:
this
seekTo
()
seekTo a different specific point on the tween's ticker
Returns:
this
set
-
Object
Set attributes
Parameters:
-
Object
Objectcontaining key:value attributes
Returns:
this
setDefinitionsValues
-
Object
Calculate the effective values for definitions
Parameters:
-
Object
Objectcontaining key:value attributes
Returns:
this
setTargets
-
items
Set targets attribute - assumes that the supplied Array will replace, not amend, any existing targets array
Parameters:
-
items
ArrayArray of Objects and/or Strings, can also be single Object or string
Returns:
this
update
-
items
Investigate the data supplied by the ticker and, if necessary, invoke the action or revert functions, as appropriate
The object passed by the ticker has the following attributes:
- tick - milliseconds since ticker started its run
- reverseTick - milliseconds before ticker reaches the end of its run
- willLoop - boolean indicating whether ticker is about to restart
- next - boolean indicating whether this is the ticker's last update
Parameters:
-
items
ObjectObject sent by ticker
Returns:
always true
updateCleanup
-
items
update cleanup
Parameters:
-
items
ObjectObject sent by ticker
Returns:
always true
Properties
action
Function
Function to be called at the end of each tween recalculation - takes no arguments
Default: false
comment
String
Comment, for accessibility
Default: ''
definitions
Array
Array of Objects which define the actions this tween will take. The Objects must include the following attributes:
- attribute - (required) a String of the attribute key value
- start - (required) a Number or String value determining the point on the Ticker at which the tween will activate (eg: 100, '10%', '2px')
- end - (required) a Number or String value determining the point on the Ticker at which the tween will deactivate (eg: 900, '90%', '50px')
- engine - (optional) a String value supplying the name of the easing engine to use; default 'linear'
- integer - (optional) a Boolean: when true, the calculated value will have Math.round() applied before targets are set; default false
This attribute can also accept a single Object as its value
Default: []
duration
Number
Duration - time required for tween to run
Default: 0
name
String
Unique identifier for each object; default: computer-generated String based on Object's type
order
Number
Sort order - for Actions that share the same time value on a given Ticker. Without a sort order, there will be no guarantee which actions with the same time value will be performed first
Default: 0
reversed
Boolean
Reversed - determines the directin in which the tween will run - true means that reverseTick values will be used for calculations; default false
Default: false
reverseOnCycleEnd
Boolean
Reversable flag - when true, the tween will reverse its direction of play as each ticker cycle completes; default false (will go back to beginning and play in the current direction)
Default: false
targets
Array
Array of Objects on which this Tween will perform its action and revert functions; if the array includes Strings, the constructor, set and clone functions will search for the Objects in the Scrawl library, checking sections (if they currently exist) in the following order:
- entity, cell, pad, stack, element, point, group, design, animation, tween, anim, filter, image, force, spring, physics
This attribute can also accept a single Object or String as its value in the
Default: []
ticker
String
Ticker name If a Tween object is associated with a ticker, it will fire (or revert) at the appropriate point in the course of the ticker's run.
Default: ''
time
Number
Time - point (in milliseconds) following the start of the Tween's ticker when the tween will trigger
Default: 0
timestamp
String
Creation timestamp
Default: ''
title
String
Title, for accessibility
Default: ''
type
String
final
Default: 'Tween'


Benoa Harbour
Position 08°45"S, 115°14"E (Benoa Harbour entrance)
This harbour is restricted by tide in parts and its entrance - on the Lombok straight - can be tricky, with 8 knot currents and sometimes standing waves if there is a swell and an opposing curent and tide that sets to the South. Time things carefully when planning on entering. Currents flow south during the SE monsoon and north during the NW monsoon.
The pass through the reef leading into Benoa Harbour should not be negotiated at night as the lights can be confusing. Benoa Harbour is a very busy commercial harbour and the boats are pretty packed in places. Parts are very shallow, and the shoal extends well into the marked channel in places, especially on the north side of the outer channel.
Serangan Harbour
Position 08°43"31'S, 115°15"11'E (Serangan Harbour entrance)
This harbour lies 1 KM to the North of Benoa and is accessed through a separate channel through the reef. It offers two protected anchorages.
This is an official Port of Entry.
NEW Indonesian CIQP procedures came into effect from the 27th February, 2016.
A CAIT, Green Book/Sailing Permit and use of an Agent to obtain clearance papers are no longer required. See Noonsite Indonesia Formalities for full details.
Previously any yachts docked at Bali International Marina needed to use the marina office as a clearance agent, but due to the recent changes in the regulations, this should no longer be obligatory.
Customs in Benoa are reported to be very friendly and understand the new clearance system. They do however require that yachts that clear in here return in person every 6 months to renew the Vessel Declaration Form - reporting by e-mail is currently not permitted here (as it is in Sabang for example).
Location of offices
CIQP Clearance is still required, but hopefully should be alot simpler now the new system is in place.
All the necessary offices are south of the marina within walking distance - except immigration which is in Benoa town ($8 taxi ride). The Harbour Master’s office must be visited first, followed by Navy, Immigration, Quarantine and Customs, before returning to the Harbour Master.
Last updated August 2016.
As an alternative to Bali International Marina in Benoa Harbour (which is small and often full), there is a good anchorage very popular with the cruising community in the bay opposite the village of Serangan. Serangan is really just a small island, attached to Bali by a causeway.
Benoa Harbour
A buoyed channel leads to Benoa Harbour and Bali Marina is located in the NE part of the harbour. The marina monitors Channel 77 during office hours (0800- 2000). Bali Marina is small- about 20 slots - most of which seem to be filled with resident boats. They have a nice restaurant/bar area, but are expensive by Indonesian standards (2012: US$25/day for a berth), and there are no moorings available via the marina. The marina charges a US$5/day landing fee to tie up dingies.

A few sailboats manage to anchor north of the marina and moorings, but it is very shallow and space is very limited here. Rumor has it you can also anchor south of the marina and main channel.
Serangan Harbour
This lies 1 KM to the North of Benoa and is accessed through a separate channel through the reef. Multiple masts are visible from the Lombok Channel and the channel into Serangan anchorage is marked by a couple of red-and-green floating buoys. The entrance is 10m wide marked by small unlit buoys, passing through breaking reef. Entrance by night should be avoided.
Once inside the buoys, you have two well-protected anchorages with about 30 or 40 moorings that cater to a mix of cruisers and local boats. Even if these fill up, there is still plenty of room for anchoring. This harbour is well protected from the NW monsoon, but more open to the SE. (Photo of anchorage from sv-totem.blogspot.com May 2013).
The price of all moorings here includes a US$70/month (Rp 600,000) Village Fee, which is supposed to go to the people of Serangan. The moorings cost US$10/day.
Moorings can be booked via Isle Marine Services or Serangan Yacht Services (see details below).
There is plenty of room behind the reef to anchor in 7m mud. In fact, with the SE monsoon, there is less of a fetch here than at the moorings, but it's less convenient for getting ashore. Swell protection is good everywhere at Serangan. You cannot anchor inside of where the moorings start.
There are two docks, in constant use, where you can tie your dinghy. Security does not appear to be a problem here.
Drinking water is available from the shops in the village and there is a supermarket not too far away as well as fuel.
This is a friendly, traditional place, with lots of temples. Ask for Neuman or Leila if you need help.
Last updated May 2016.


One-hot encodes a text into a list of word indexes of size n.
tf.compat.v1.keras.preprocessing.text.one_hot
tf.compat.v2.keras.preprocessing.text.one_hot
tf.keras.preprocessing.text.one_hot( text, n, filters='!"#$%&()*+,-./:;<=>?@[\\]^_`{|}~\t\n', lower=True, split=' ' )
This is a wrapper to the hashing_trick
function using hash
as the
hashing function; unicity of word to index mapping non-guaranteed.
text: Input text (string). n: int. Size of vocabulary. filters: list (or concatenation) of characters to filter out, such as punctuation. Default: ``!"#$%&()*+,-./:;<=>?@[\]^_`{|}~\t\n``, includes basic punctuation, tabs, and newlines. lower: boolean. Whether to set the text to lowercase. split: str. Separator for word splitting.
List of integers in [1, n]. Each integer encodes a word (unicity non-guaranteed).


§206J-19 Annual report. The development corporation shall submit to the governor and the legislature, at least twenty days prior to the start of each regular session, a complete and detailed report of its activities. [L 1981, c 236, pt of §1; ree L 1986, c 146, §16]


|
Interface Summary |
| Attr |
The Attr interface represents an attribute in an
Element object. |
| CDATASection |
CDATA sections are used to escape blocks of text containing characters that
would otherwise be regarded as markup. |
| CharacterData |
The CharacterData interface extends Node with a set of
attributes and methods for accessing character data in the DOM. |
| Comment |
This interface inherits from CharacterData and represents the
content of a comment, i.e., all the characters between the starting '
<!-- ' and ending '--> '. |
| Document |
The Document interface represents the entire HTML or XML
document. |
| DocumentFragment |
DocumentFragment is a "lightweight" or "minimal"
Document object. |
| DocumentType |
Each Document has a doctype attribute whose value
is either null or a DocumentType object. |
| DOMImplementation |
The DOMImplementation interface provides a number of methods
for performing operations that are independent of any particular instance
of the document object model. |
| Element |
The Element interface represents an element in an HTML or XML
document. |
| Entity |
This interface represents an entity, either parsed or unparsed, in an XML
document. |
| EntityReference |
EntityReference objects may be inserted into the structure
model when an entity reference is in the source document, or when the
user wishes to insert an entity reference. |
| NamedNodeMap |
Objects implementing the NamedNodeMap interface are used to
represent collections of nodes that can be accessed by name. |
| Node |
The Node interface is the primary datatype for the entire
Document Object Model. |
| NodeList |
The NodeList interface provides the abstraction of an ordered
collection of nodes, without defining or constraining how this collection
is implemented. |
| Notation |
This interface represents a notation declared in the DTD. |
| ProcessingInstruction |
The ProcessingInstruction interface represents a "processing
instruction", used in XML as a way to keep processor-specific information
in the text of the document. |
| Text |
The Text interface inherits from CharacterData
and represents the textual content (termed character data in XML) of an
Element or Attr . |


brendan_oconnor_ai brendan_oconnor_ai-lda knowledge-graph by maker-knowledge-mining
topicId: wordWeight*wordName (topN-words)
topic #0: 0.012*ol + 0.011*forecasting + 0.008*jaron + 0.008*lanier + 0.007*greenspan + 0.007*zombie + 0.006*argue + 0.006*neurodudes + 0.006*fairly + 0.006*economy
topic #1: 0.013*search + 0.012*kakade + 0.008*al + 0.007*et + 0.006*picks + 0.006*longer + 0.006*plugin + 0.005*explorer + 0.005*sweeping + 0.005*noah
topic #2: 0.013*logfile + 0.011*scan + 0.006*plot + 0.006*log + 0.005*table + 0.005*kept + 0.005*verify + 0.004*bug + 0.004*tricks + 0.004*sampler
topic #3: 0.014*correlation + 0.010*terrorist + 0.009*sachs + 0.007*easterly + 0.007*poverty + 0.006*ols + 0.006*joseph + 0.006*coefficient + 0.006*simulations + 0.005*individual
topic #4: 0.015*python + 0.010*matplotlib + 0.009*bindings + 0.007*threw + 0.007*nothing + 0.006*bins + 0.006*fancy + 0.006*anywhere + 0.006*interface + 0.006*couldn
topic #5: 0.012*rangel + 0.009*taking + 0.008*neuroeconomics + 0.007*bernheim + 0.007*decision + 0.005*addiction + 0.005*steve + 0.005*naturally + 0.005*terrific + 0.005*active
topic #6: 0.012*blogging + 0.012*weblog + 0.010*anthropology + 0.009*slate + 0.008*added + 0.008*john + 0.007*academic + 0.006*interesting + 0.006*ones + 0.004*read
topic #7: 0.008*principles + 0.008*memory + 0.008*proclaiming + 0.007*numpy + 0.007*spirit + 0.007*hasn + 0.007*bothered + 0.006*decades + 0.006*intermediate + 0.006*tmp
topic #8: 0.008*movie + 0.007*netflix + 0.006*movies + 0.005*cinematch + 0.005*teams + 0.005*demographics + 0.004*comedy + 0.004*decomposition + 0.004*chabbert + 0.004*humanlike
topic #9: 0.008*parsers + 0.008*iq + 0.007*wsj + 0.006*differences + 0.006*apa + 0.006*saletan + 0.006*dependency + 0.005*constituent + 0.005*genetic + 0.004*slopes
topic #10: 0.011*awk + 0.011*newly + 0.010*chinese + 0.009*spend + 0.008*home + 0.007*tweets + 0.007*money + 0.007*mawk + 0.006*sample + 0.004*zip
topic #11: 0.012*proposal + 0.011*unnorm + 0.008*sampling + 0.007*generator + 0.006*density + 0.005*gradient + 0.004*gf + 0.004*objective + 0.003*inputs + 0.003*require
topic #12: 0.011*ideas + 0.010*iran + 0.008*news + 0.006*false + 0.006*joint + 0.005*exogenous + 0.005*timing + 0.005*jackson + 0.005*appearances + 0.005*reminded
topic #13: 0.018*site + 0.012*fun + 0.012*international + 0.011*organizations + 0.009*henrich + 0.009*terrific + 0.009*states + 0.007*wrestling + 0.007*influence + 0.006*focusing
topic #14: 0.007*binomial + 0.006*rorty + 0.006*scale + 0.006*bits + 0.005*christian + 0.005*secular + 0.005*education + 0.005*command + 0.005*intuitions + 0.004*liberal
topic #15: 0.000*trip + 0.000*suffer + 0.000*arrogant + 0.000*amazing + 0.000*spend + 0.000*newly + 0.000*chinese + 0.000*weird + 0.000*war + 0.000*voting
topic #16: 0.015*stanford + 0.015*documentation + 0.011*machine + 0.011*found + 0.011*thing + 0.010*ll + 0.010*recently + 0.009*models + 0.009*update + 0.009*stuff
topic #17: 0.008*worker + 0.007*maximum + 0.006*gold + 0.006*correction + 0.006*raw + 0.006*likelihood + 0.006*corrections + 0.005*averaging + 0.004*linear + 0.003*picture
topic #18: 0.009*build + 0.008*helped + 0.008*gaussian + 0.008*laws + 0.007*intuition + 0.007*interactive + 0.007*law + 0.006*visitors + 0.006*roberts + 0.005*total
topic #19: 0.011*nytimes + 0.011*santa + 0.009*relational + 0.009*insight + 0.009*market + 0.008*abstract + 0.008*moment + 0.007*presents + 0.007*group + 0.007*suddenly
topic #20: 0.000*trip + 0.000*suffer + 0.000*arrogant + 0.000*amazing + 0.000*spend + 0.000*newly + 0.000*chinese + 0.000*weird + 0.000*war + 0.000*voting
topic #21: 0.016*oooo + 0.009*ooo + 0.007*oo + 0.007*upon + 0.006*wish + 0.005*america + 0.005*history + 0.005*advocates + 0.005*north + 0.005*oooooooo
topic #22: 0.011*art + 0.009*user + 0.008*communication + 0.008*pharmaceuticals + 0.007*code + 0.007*conscious + 0.007*emotiv + 0.007*attempt + 0.007*problems + 0.006*company
topic #23: 0.012*unexpected + 0.006*suggest + 0.005*tossing + 0.005*shell + 0.005*unix + 0.005*subtitle + 0.005*scott + 0.005*syntax + 0.005*force + 0.005*phrases
topic #24: 0.014*lots + 0.013*interesting + 0.011*used + 0.011*less + 0.010*similar + 0.010*large + 0.009*different + 0.008*common + 0.008*across + 0.007*memcached
topic #25: 0.015*cat + 0.008*concept + 0.003*deep + 0.003*pixel + 0.003*reduction + 0.003*image + 0.003*concepts + 0.002*tokenizer + 0.002*regex + 0.002*cats
topic #26: 0.015*tanh + 0.009*logistic + 0.009*function + 0.006*range + 0.006*sigmoid + 0.004*functions + 0.004*frac + 0.004*outputs + 0.003*probabilities + 0.003*show
topic #27: 0.000*trip + 0.000*suffer + 0.000*arrogant + 0.000*amazing + 0.000*spend + 0.000*newly + 0.000*chinese + 0.000*weird + 0.000*war + 0.000*voting
topic #28: 0.010*game + 0.010*theory + 0.008*started + 0.008*view + 0.008*hand + 0.008*field + 0.007*economics + 0.006*courses + 0.006*goods + 0.006*services
topic #29: 0.016*please + 0.011*fit + 0.010*words + 0.010*hierarchical + 0.008*hdlm + 0.008*hpylm + 0.008*teh + 0.006*well + 0.006*things + 0.005*yee
topic #30: 0.011*ain + 0.010*basement + 0.009*mcdonald + 0.007*na + 0.007*gon + 0.007*man + 0.005*bomb + 0.005*shit + 0.005*wisdom + 0.005*invented
topic #31: 0.011*monkeys + 0.010*drink + 0.009*testing + 0.007*significance + 0.007*delta + 0.007*tests + 0.006*null + 0.006*consumption + 0.006*alcohol + 0.005*performance
topic #32: 0.014*pmi + 0.007*fundamental + 0.006*frac + 0.006*ratio + 0.005*redirect + 0.005*wise + 0.005*obvious + 0.005*reference + 0.005*url + 0.005*automatically
topic #33: 0.000*trip + 0.000*suffer + 0.000*arrogant + 0.000*amazing + 0.000*spend + 0.000*newly + 0.000*chinese + 0.000*weird + 0.000*war + 0.000*voting
topic #34: 0.000*trip + 0.000*suffer + 0.000*arrogant + 0.000*amazing + 0.000*spend + 0.000*newly + 0.000*chinese + 0.000*weird + 0.000*war + 0.000*voting
topic #35: 0.009*bugs + 0.006*compiles + 0.006*dyna + 0.006*written + 0.005*hbc + 0.005*alchemy + 0.005*languages + 0.004*factorie + 0.004*probabilistic + 0.004*dynamic
topic #36: 0.012*agreement + 0.008*dimensions + 0.008*certain + 0.007*cooperation + 0.007*hooray + 0.007*turned + 0.007*evolved + 0.006*socially + 0.006*biased + 0.006*competition
topic #37: 0.008*wolfram + 0.008*computation + 0.007*glmnet + 0.006*fortran + 0.006*hastie + 0.005*microsoft + 0.005*tremendous + 0.004*feature + 0.004*simulations + 0.004*fe
topic #38: 0.009*inspired + 0.008*possible + 0.008*rock + 0.008*scissors + 0.008*writeup + 0.007*rough + 0.006*friends + 0.006*pure + 0.006*similarly + 0.005*wondering
topic #39: 0.013*systematic + 0.007*ability + 0.007*method + 0.007*earth + 0.007*abilities + 0.006*textbooks + 0.006*accurate + 0.006*half + 0.005*measures + 0.005*measuring
topic #40: 0.009*steve + 0.009*colbert + 0.009*reproduced + 0.008*upcoming + 0.008*chomsky + 0.008*pinker + 0.008*interview + 0.007*bet + 0.006*won + 0.006*website
topic #41: 0.008*rainbow + 0.006*uima + 0.006*gate + 0.006*gcc + 0.005*download + 0.005*osx + 0.004*text + 0.004*classification + 0.004*tell + 0.004*classifier
topic #42: 0.017*powerset + 0.004*index + 0.004*indexing + 0.003*innovation + 0.003*technology + 0.003*respected + 0.003*amit + 0.003*hbase + 0.003*indexed + 0.003*parc
topic #43: 0.013*economics + 0.012*statistical + 0.012*using + 0.011*ml + 0.010*behavioral + 0.009*economic + 0.008*gintis + 0.008*neuroeconomics + 0.008*knowledge + 0.008*modeling
topic #44: 0.015*science + 0.015*social + 0.014*data + 0.012*new + 0.012*one + 0.011*blog + 0.011*like + 0.010*ve + 0.010*get + 0.010*see
topic #45: 0.010*genocide + 0.010*nicholas + 0.010*bbc + 0.010*kristof + 0.008*june + 0.008*account + 0.007*news + 0.005*worth + 0.005*rwandan + 0.005*intervention
topic #46: 0.000*trip + 0.000*suffer + 0.000*arrogant + 0.000*amazing + 0.000*spend + 0.000*newly + 0.000*chinese + 0.000*weird + 0.000*war + 0.000*voting
topic #47: 0.011*monkeys + 0.009*pitchers + 0.009*altruists + 0.007*misses + 0.007*group + 0.006*hits + 0.005*monkey + 0.005*altruism + 0.005*sex + 0.004*selection
topic #48: 0.011*fascinating + 0.010*semantic + 0.009*twitter + 0.009*pairwise + 0.008*better + 0.008*back + 0.007*imaging + 0.007*absolute + 0.006*judgments + 0.006*relations
topic #49: 0.009*model + 0.009*cas + 0.006*cyc + 0.006*logic + 0.006*belief + 0.005*ideology + 0.004*reader + 0.004*agents + 0.004*base + 0.004*public
topic #50: 0.016*entry + 0.010*posted + 0.010*operations + 0.008*computational + 0.007*ideal + 0.007*fan + 0.007*computer + 0.006*big + 0.006*frederick + 0.006*rationality
topic #51: 0.007*order + 0.007*arrow + 0.006*government + 0.006*extremely + 0.006*java + 0.005*married + 0.005*musician + 0.005*parties + 0.005*posterior + 0.005*beliefs
topic #52: 0.016*sets + 0.015*data + 0.014*sources + 0.012*beats + 0.009*lot + 0.008*mosaic + 0.008*already + 0.007*departments + 0.007*admittance + 0.007*ucbadmissions
topic #53: 0.016*animated + 0.012*universal + 0.012*rights + 0.007*link + 0.007*human + 0.000*spend + 0.000*amazing + 0.000*newly + 0.000*arrogant + 0.000*chinese
topic #54: 0.014*republic + 0.014*algebra + 0.010*kingdom + 0.007*pages + 0.007*democratic + 0.007*linear + 0.006*cookbook + 0.005*socialist + 0.005*arab + 0.005*matrix
topic #55: 0.011*figure + 0.011*table + 0.010*particular + 0.010*big + 0.009*article + 0.009*gelman + 0.009*need + 0.009*democracy + 0.009*regression + 0.009*russia
topic #56: 0.021*bomb + 0.011*europe + 0.006*tackle + 0.005*situations + 0.005*onto + 0.005*shall + 0.005*asia + 0.005*ambitious + 0.005*repetitive + 0.005*weak
topic #57: 0.016*version + 0.016*along + 0.011*released + 0.010*moral + 0.009*computers + 0.009*better + 0.008*thought + 0.008*lines + 0.008*begin + 0.008*man
topic #58: 0.011*answer + 0.009*pharmaceuticals + 0.009*supporting + 0.008*curious + 0.007*semantics + 0.007*lexical + 0.007*art + 0.006*sense + 0.005*evidence + 0.005*question
topic #59: 0.011*svm + 0.009*features + 0.009*dependency + 0.009*scientists + 0.008*evidence + 0.007*authority + 0.007*support + 0.007*formalism + 0.007*feature + 0.007*algorithms
topic #60: 0.013*argmas + 0.011*netherlands + 0.011*conferences + 0.009*argumentation + 0.007*sense + 0.006*natural + 0.006*computational + 0.006*argument + 0.006*models + 0.005*systems
topic #61: 0.012*semantics + 0.007*outcomes + 0.007*defect + 0.007*mention + 0.006*pareto + 0.006*issues + 0.006*explain + 0.006*payoff + 0.005*gold + 0.005*outcome
topic #62: 0.014*law + 0.009*power + 0.007*billion + 0.006*zipf + 0.006*public + 0.006*amazon + 0.005*bandwagon + 0.005*mechanistic + 0.005*rent + 0.004*freebase
topic #63: 0.014*flight + 0.009*departure + 0.007*trip + 0.006*minutes + 0.005*pilots + 0.005*delayed + 0.005*travel + 0.005*expected + 0.004*delta + 0.004*time
topic #64: 0.014*organism + 0.013*id + 0.008*designed + 0.008*happiness + 0.008*intelligently + 0.008*intelligent + 0.007*plausibility + 0.007*norm + 0.007*lying + 0.007*stumbling
topic #65: 0.013*conference + 0.007*abstracts + 0.007*message + 0.007*samuel + 0.006*sorry + 0.006*http + 0.006*inside + 0.005*home + 0.005*huge + 0.005*program
topic #66: 0.011*exponentiated + 0.007*email + 0.007*log + 0.006*entropy + 0.006*integration + 0.006*analytics + 0.005*hat + 0.005*event + 0.004*creating + 0.004*uncertainty
topic #67: 0.013*countries + 0.011*psychoanalysis + 0.010*country + 0.008*internet + 0.007*usage + 0.007*city + 0.006*posts + 0.006*hot + 0.006*pereira + 0.006*fernando
topic #68: 0.008*brain + 0.007*slate + 0.004*york + 0.004*politics + 0.003*previous + 0.003*neuromarketing + 0.003*desired + 0.003*purport + 0.003*funded + 0.003*imaging
topic #69: 0.008*fearon + 0.007*events + 0.007*jim + 0.007*explains + 0.007*facts + 0.007*largest + 0.007*annual + 0.006*iraq + 0.006*civil + 0.006*casualties
topic #70: 0.013*posted + 0.012*argument + 0.011*systems + 0.010*political + 0.010*different + 0.010*time + 0.009*part + 0.008*computational + 0.008*applications + 0.008*question
topic #71: 0.009*families + 0.008*clark + 0.005*values + 0.005*children + 0.005*wealthier + 0.004*institutional + 0.004*thousands + 0.004*bowles + 0.004*ethic + 0.004*biological
topic #72: 0.007*plos + 0.007*mackay + 0.006*known + 0.006*recent + 0.006*neuroscience + 0.005*field + 0.005*reviews + 0.005*leaders + 0.005*bayesian + 0.005*bletchley
topic #73: 0.007*wolfram + 0.007*pairs + 0.007*syntactic + 0.005*running + 0.005*liking + 0.005*phrase + 0.004*compares + 0.004*getting + 0.004*cynical + 0.004*conventions
topic #74: 0.009*people + 0.008*good + 0.008*would + 0.008*think + 0.007*paper + 0.007*re + 0.007*useful + 0.007*things + 0.007*work + 0.007*something
topic #75: 0.012*privacy + 0.012*band + 0.011*smoothing + 0.007*lordi + 0.007*settings + 0.006*finland + 0.006*eurovision + 0.005*won + 0.005*poll + 0.005*polls
topic #76: 0.017*harvard + 0.009*price + 0.009*dynamics + 0.008*program + 0.008*drug + 0.008*ties + 0.008*equation + 0.007*iphone + 0.006*evolutionary + 0.006*nyt
topic #77: 0.017*vec + 0.008*log + 0.005*symbol + 0.005*frac + 0.005*symbols + 0.005*surprisal + 0.003*entropy + 0.003*encode + 0.002*coding + 0.002*message
topic #78: 0.007*ten + 0.007*scott + 0.007*judge + 0.007*decide + 0.006*book + 0.006*shorter + 0.006*estimate + 0.005*alternative + 0.005*biased + 0.005*shouldn
topic #79: 0.011*skewz + 0.010*tie + 0.007*arrow + 0.007*svd + 0.006*previous + 0.005*sites + 0.005*correlation + 0.005*play + 0.005*tend + 0.005*notation
topic #80: 0.014*distribution + 0.012*probability + 0.011*actually + 0.010*logic + 0.009*statistics + 0.009*every + 0.008*cluster + 0.008*normal + 0.008*article + 0.008*exp
topic #81: 0.009*greif + 0.006*prop + 0.005*police + 0.005*clark + 0.005*institutional + 0.005*videos + 0.005*night + 0.005*cognition + 0.004*party + 0.004*uncertainty
topic #82: 0.000*trip + 0.000*suffer + 0.000*arrogant + 0.000*amazing + 0.000*spend + 0.000*newly + 0.000*chinese + 0.000*weird + 0.000*war + 0.000*voting
topic #83: 0.011*rounds + 0.010*scaling + 0.010*baron + 0.010*blogs + 0.010*lesson + 0.009*opponent + 0.009*scissors + 0.009*choosing + 0.009*blogging + 0.008*stop
topic #84: 0.000*trip + 0.000*suffer + 0.000*arrogant + 0.000*amazing + 0.000*spend + 0.000*newly + 0.000*chinese + 0.000*weird + 0.000*war + 0.000*voting
topic #85: 0.012*chairman + 0.011*god + 0.010*environment + 0.010*finland + 0.008*lordi + 0.005*intentionally + 0.005*wager + 0.005*inf + 0.005*infinite + 0.005*plays
topic #86: 0.014*university + 0.012*bar + 0.009*document + 0.008*measured + 0.007*lazy + 0.007*cosine + 0.007*plaintext + 0.006*approximation + 0.006*metadata + 0.006*matters
topic #87: 0.000*trip + 0.000*suffer + 0.000*arrogant + 0.000*amazing + 0.000*spend + 0.000*newly + 0.000*chinese + 0.000*weird + 0.000*war + 0.000*voting
topic #88: 0.013*funny + 0.012*log + 0.011*rubin + 0.011*old + 0.008*language + 0.007*pretty + 0.007*politics + 0.006*dangers + 0.005*plug + 0.005*wars
topic #89: 0.015*ab + 0.012*tweetmotif + 0.010*click + 0.009*setminus + 0.009*days + 0.009*frac + 0.008*dolores + 0.008*pictures + 0.007*labs + 0.007*align
topic #90: 0.003*statistics + 0.003*marketing + 0.002*neural + 0.002*network + 0.002*scienti + 0.002*ga + 0.002*efron + 0.002*grant + 0.002*nn + 0.002*defined
topic #91: 0.009*fish + 0.008*tank + 0.006*teenagers + 0.006*virus + 0.006*gay + 0.005*switch + 0.005*federal + 0.005*describe + 0.005*sacrifice + 0.005*wasn
topic #92: 0.012*authoritarian + 0.011*phd + 0.011*comics + 0.010*sciences + 0.010*humanities + 0.009*roc + 0.009*metrics + 0.009*auc + 0.008*capitalism + 0.008*pr
topic #93: 0.016*stanley + 0.016*war + 0.014*fish + 0.011*thinks + 0.008*invasion + 0.006*film + 0.005*france + 0.005*ii + 0.004*much + 0.003*wikipedia
topic #94: 0.012*blogger + 0.010*release + 0.009*wealth + 0.008*wordpress + 0.008*religion + 0.007*religious + 0.007*condition + 0.007*republican + 0.006*graph + 0.006*available
topic #95: 0.007*epistemology + 0.006*rortyan + 0.005*fashion + 0.004*account + 0.004*semantic + 0.004*won + 0.004*away + 0.004*loved + 0.004*quivering + 0.003*tell
topic #96: 0.012*york + 0.011*buy + 0.011*gss + 0.011*money + 0.010*presidential + 0.010*versus + 0.010*claim + 0.010*happiness + 0.009*maps + 0.008*picked
topic #97: 0.011*china + 0.011*university + 0.009*market + 0.007*free + 0.007*airlines + 0.006*power + 0.006*password + 0.006*connectu + 0.005*concept + 0.005*users
topic #98: 0.013*cutoff + 0.008*http + 0.005*resources + 0.005*classifier + 0.005*labels + 0.005*interdisciplinary + 0.005*rand + 0.005*newsgroups + 0.005*updated + 0.004*preds
topic #99: 0.006*givewell + 0.006*charity + 0.006*philanthropy + 0.005*altruistic + 0.005*effectiveness + 0.004*provide + 0.004*tighe + 0.004*charities + 0.004*evaluating + 0.003*stock
Latent Dirichlet allocation
In natural language processing, latent Dirichlet allocation (LDA) is a generative model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar. For example, if observations are words collected into documents, it posits that each document is a mixture of a small number of topics and that each word's creation is attributable to one of the document's topics. LDA is an example of a topic model and was first presented as a graphical model for topic discovery by David Blei, Andrew Ng, and Michael Jordan in 2003.
Topics in LDA
In LDA, each document may be viewed as a mixture of various topics. This is similar to probabilistic latent semantic analysis (pLSA), except that in LDA the topic distribution is assumed to have a Dirichlet prior. In practice, this results in more reasonable mixtures of topics in a document. It has been noted, however, that the pLSA model is equivalent to the LDA model under a uniform Dirichlet prior distribution.
For example, an LDA model might have topics that can be classified as CAT_related and DOG_related. A topic has probabilities of generating various words, such as milk, meow, and kitten, which can be classified and interpreted by the viewer as "CAT_related". Naturally, the word cat itself will have high probability given this topic. The DOG_related topic likewise has probabilities of generating each word: puppy, bark, and bone might have high probability. Words without special relevance, such as the (see function word), will have roughly even probability between classes (or can be placed into a separate category). A topic is not strongly defined, neither semantically nor epistemologically. It is identified on the basis of supervised labeling and (manual) pruning on the basis of their likelihood of co-occurrence. A lexical word may occur in several topics with a different probability, however, with a different typical set of neighboring words in each topic.
Each document is assumed to be characterized by a particular set of topics. This is akin to the standard bag of words model assumption, and makes the individual words exchangeable.
Model
With plate notation, the dependencies among the many variables can be captured concisely. The boxes are “plates” representing replicates. The outer plate represents documents, while the inner plate represents the repeated choice of topics and words within a document. M denotes the number of documents, N the number of words in a document. Thus:
α is the parameter of the Dirichlet prior on the per-document topic distributions,
β is the parameter of the Dirichlet prior on the per-topic word distribution,
\theta_i is the topic distribution for document i,
\phi_k is the word distribution for topic k,
z_{ij} is the topic for the jth word in document i, and
w_{ij} is the specific word.
The w_{ij} are the only observable variables, and the other variables are latent variables. Mostly, the basic LDA model will be extended to a smoothed version to gain better results .[citation needed] The plate notation is shown on the right, where K denotes the number of topics considered in the model and:
\phi is a K*V (V is the dimension of the vocabulary) Markov matrix each row of which denotes the word distribution of a topic.
The generative process behind is that documents are represented as random mixtures over latent topics, where each topic is characterized by a distribution over words. LDA assumes the following generative process for a corpus D consisting of M documents each of length N_i:
1. Choose \theta_i \, \sim \, \mathrm{Dir}(\alpha) , where i \in \{ 1,\dots,M \} and \mathrm{Dir}(\alpha) is the Dirichlet distribution for parameter \alpha
2. Choose \phi_k \, \sim \, \mathrm{Dir}(\beta) , where k \in \{ 1,\dots,K \}
3. For each of the word positions i, j, where j \in \{ 1,\dots,N_i \} , and i \in \{ 1,\dots,M \}
(a) Choose a topic z_{i,j} \,\sim\, \mathrm{Multinomial}(\theta_i).
(b) Choose a word w_{i,j} \,\sim\, \mathrm{Multinomial}( \phi_{z_{i,j}}) .
(Note that the Multinomial distribution here refers to the Multinomial with only one trial. It is formally equivalent to the categorical distribution.)
The lengths N_i are treated as independent of all the other data generating variables (q and z). The subscript is often dropped, as in the plate diagrams shown here.
Inference
Learning the various distributions (the set of topics, their associated word probabilities, the topic of each word, and the particular topic mixture of each document) is a problem of Bayesian inference. The original paper used a variational Bayes approximation of the posterior distribution;[1] alternative inference techniques use Gibbs sampling and expectation propagation.
Following is the derivation of the equations for collapsed Gibbs sampling, which means \varphis and \thetas will be integrated out. For simplicity, in this derivation the documents are all assumed to have the same length N_{}. The derivation is equally valid if the document lengths vary.
Applications, extensions and similar techniques
Topic modeling is a classic problem in information retrieval. Related models and techniques are, among others, latent semantic indexing, independent component analysis, probabilistic latent semantic indexing, non-negative matrix factorization, and Gamma-Poisson distribution.
The LDA model is highly modular and can therefore be easily extended. The main field of interest is modeling relations between topics. This is achieved by using another distribution on the simplex instead of the Dirichlet. The Correlated Topic Model follows this approach, inducing a correlation structure between topics by using the logistic normal distribution instead of the Dirichlet. Another extension is the hierarchical LDA (hLDA), where topics are joined together in a hierarchy by using the nested Chinese restaurant process. LDA can also be extended to a corpus in which a document includes two types of information (e.g., words and names), as in the LDA-dual model. Nonparametric extensions of LDA include the Hierarchical Dirichlet process mixture model, which allows the number of topics to be unbounded and learnt from data and the Nested Chinese Restaurant Process which allows topics to be arranged in a hierarchy whose structure is learnt from data.
As noted earlier, PLSA is similar to LDA. The LDA model is essentially the Bayesian version of PLSA model. The Bayesian formulation tends to perform better on small datasets because Bayesian methods can avoid overfitting the data. In a very large dataset, the results are probably the same. One difference is that PLSA uses a variable d to represent a document in the training set. So in PLSA, when presented with a document the model hasn't seen before, we fix \Pr(w \mid z)—the probability of words under topics—to be that learned from the training set and use the same EM algorithm to infer \Pr(z \mid d)—the topic distribution under d. Blei argues that this step is cheating because you are essentially refitting the model to the new data.
Variations on LDA have been used to automatically put natural images into categories, such as "bedroom" or "forest", by treating an image as a document, and small patches of the image as words; one of the variations is called Spatial Latent Dirichlet Allocation.
from wiki http://en.wikipedia.org/wiki/Latent_Dirichlet_allocation


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Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
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Heading
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
View details »
Heading
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
Nature, in the broadest sense, is equivalent to the natural, physical, or material world or universe.
View details »
First featurette heading. It'll blow your mind.
The term checkmate is, according to the Barnhart Etymological Dictionary, an alteration
of the Persian phrase which means, literally, "the King is
helpless".[7] Others maintain that it means "the King is dead", as chess reached
Europe via the Islamic world, and Arabic māta means "died" or "is dead"


Born and raise chicagoans, two of us created this website because we both have passion to care for dogs & cats. All animals in general but our specialty are dogs & cats
Patrick's Info
Currently have 2 dogs, one shih tzu mix, his name is Falkor and he is around 14 years old, he was adobted from a shelter so his real age is unknown. My second dog is Queen Buttercups or just simply Buttercups. She came from a litter of pups my mom's dog had. Originally here name was Princess Buttercups, but since then she has grown up and now at the age of 8 she was coronated Queen by my son.
Christoper's Info
My names Christoper Delgadillo and I have two mixed American Pitbulls. I joined with Patrick to create this website for the same shared love and passion we have for animals and out dedication to see them benefit from their owners. I got my dogs when they were new borns from a man selling them out a cardboard box, after all the approproiate shots and medical examinations they were the best thing to happen to my family. They are currently both 13 years old and live full happy lives with my family and I.


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Test your coding skills in an unorthodox contest,where you will be scored not only on correctness but also on the style of code.
REGISTER NOWMake sure you have registered your team. Do write your team name on the answer sheet.
This round consists of 10 questions based on C programming language.
Each question caries 5 points (total 50 points) and will be added with the score of round 2.
Write appropriate output / type of error for the questions and do mention suitable assumptions if any.
Use of internet / compiler is strictly prohibited. Your answers will be checked during Round 2 and your score listed on the scoreboard. The sum of the scores of both the rounds will be used for final rankings.
Get Started!In this round you are given 5 programming questions to solve for 100 points each, however if you get a negative score, check the evaluation function for that.
You are supposed to write a program in C to solve the problem
Your Solution will be evaluated according to the algorithm mentioned here
You can find a reference to ASCII values here
Get Started!


This is my senior essay for the math major at Yale. It goes through some basic algebraic graph theory to build up the theory of strongly regular graphs. Then it examines some recent approaches to proving that certain strongly regular graphs do not exist in hopes of being able to extend these techniques to prove or disprove the existence of the strongly regular graph with parameters (99,14,1,2). However, these techniques all seem infeasible for those specific parameters and the problem remains open.
(Fall 2017) [PDF]


---
layout: theorems
---
Elements of a Span
Let $V$ be a vector space over $\mathbb{F}$, and $S\subseteq V$ such that $S\neq \emptyset$. Then $\text{span }S$ is the set of all linear combinations of elements in $S$. That is,
$$\begin{align*}
\text{span }S=\{a_1x_1+\dots + a_kx_k:a_i\in\mathbb{F},x_i\in S, k\geq 1 \}
\end{align*}$$
Concepts
Coming soon
Hypothesis
Coming soon
Results
Coming soon
Proof
Coming soon


Servers Workshop
Hosted Servers
Add your server
Add
Current Servers
Hostname
IP
{% for host, ip in data.items() %}
{{ host }}
{{ ip['ip'] }}
{% endfor %}
Made with ❤ by
Kevin Tran
and
Hackers@Berkeley
for the Intro to Servers Workshop, Spring 2017


Namespace Bifrost.Interaction
Classes
CommandForMethod
Represents an implementation of System.Windows.Input.ICommand for a method on a target, typically a ViewModel
DelegateCommand
DelegateCommand<T>
FromMethodExtension
Markup extension for connecting a method on a viewModel as a command
Input
Represents properties for working with input on elements.
MissingMethodForCommand
MissingMethodOrPropertyForCanExecute
MoreThanOneParameter
Operation
Represents an operation in the system
OperationContext
Represents a base context that is relevant for an operation - this is the context in which Operation are performed in
Operations
Represents an implementation of IOperations
OperationState
Represents a base implementation of state for a Operation
ReturnValueShouldBeBoolean
Interfaces
IOperations
Defines a system for working with Operation


Mmmm, moody seascape eh? Photo courtesy of the wonderful Gratisography, via the handy Start Bootstrap templates. And all hosted for free thanks to Github pages, saving a few quid a year - thanks!
Digital product management with a bit of music on the side.
Experience working in large multinationals, small startups and government digital services. Including the Foreign & Commonwealth Office, two-taps-to-a-taxi app Hailo, early mobile group messaging app Trutap, peanut butter behemoth Yahoo!, search old-timer and redirected-URL AltaVista, and BBC Online.
Member of the PRS for Music. Soundtrack composition credits include BBC3, Channel 5, The Learning Channel and Animal Planet.
Spanish and French speaker, and something of a Hispanophile.
No relation to Gary.
Perfection is finally attained not when there is no longer anything to add, but when there is no longer anything to take away
Antoine de Saint-Exupéry
You can reach me at the places below.


This is a morning reminder from LifeHQ because we all need a helpful nudge when starting a new habit.
You can change when you receive this email or turn it off completely in your Settings page.


PrefsKeys
private enum PrefsKeys : String
These are the keys we use for our persistent prefs dictionary.
-
This is the Root Server URI
Declaration
Swift
case RootServerURI = "rootURI"
-
This represents how long we allow a meeting to be in progress before we remove it from our list of candidates.
Declaration
Swift
case GracePeriod = "gracePeriod"
-
This represents the units we use for our distance display. The string that is stored and returned in the localization key, not the displayed string.
Declaration
Swift
case DistanceUnits = "distanceUnits"
-
This dictates how the results are sorted. If 0, then they are sorted by time. If 1, they are sorted by distance.
Declaration
Swift
case ResultSort = "resultSort"
-
In the
More Info
screen, the user can select a map type. This is saved here. 0 = standard, 1 = hybrid, 2 = satellite.Declaration
Swift
case DetailsMapType = "detailsMapType"


If a customer changes their address, it's often not enough to update their master data record. E.g. the component processing customer orders might have to learn about the update in order to ship to the correct address.
In a distributed architecture, you have to spread information about a master data update to several client apps. You can do this via REST, but if a client app is temporarily down or too busy to accept requests, it's going to miss the information. Adding a new client app requires changes to the master app. Asynchronous messaging helps to avoid such a tight coupling of components. And it offers much more than a simple action trigger: parallelizing computing-heavy tasks, load testing, or migrating existing components to new services are some of the possibilities explored in this talk.
You're going to learn how to get started with asynchronous messaging, and how it helps you to keep your codebase clean and your overal l system stable as well as maintainable.
The downsides of REST application.
AMQP - Advanced Message Queuing Protocol
Speaker works at Xing


Class: Aws::ECSCredentials
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Instance Chain:
self,
RefreshingCredentials ,
CredentialProvider
|
|
| Inherits: | Object |
| Defined in: | gems/aws-sdk-core/lib/aws-sdk-core/ecs_credentials.rb |
Overview
Constant Summary
-
NETWORK_ERRORS =
Internal use only
# File 'gems/aws-sdk-core/lib/aws-sdk-core/ecs_credentials.rb', line 25
These are the errors we trap when attempting to talk to the instance metadata service. Any of these imply the service is not present, no responding or some other non-recoverable error.
[ Errno::EHOSTUNREACH, Errno::ECONNREFUSED, Errno::EHOSTDOWN, Errno::ENETUNREACH, SocketError, Timeout::Error, Non200Response ].freeze
RefreshingCredentials
- Included
ASYNC_EXPIRATION_LENGTH, CLIENT_EXCLUDE_OPTIONS, SYNC_EXPIRATION_LENGTH
Class Method Summary
- .new(options = {}) ⇒ ECSCredentials constructor
Instance Attribute Summary
Constructor Details
.new(options = {}) ⇒ ECSCredentials
# File 'gems/aws-sdk-core/lib/aws-sdk-core/ecs_credentials.rb', line 61
def initialize( = {}) credential_path = [:credential_path] || ENV['AWS_CONTAINER_CREDENTIALS_RELATIVE_URI'] endpoint = [:endpoint] || ENV['AWS_CONTAINER_CREDENTIALS_FULL_URI'] initialize_uri(, credential_path, endpoint) @authorization_token = ENV['AWS_CONTAINER_AUTHORIZATION_TOKEN'] @retries = [:retries] || 5 @http_open_timeout = [:http_open_timeout] || 5 @http_read_timeout = [:http_read_timeout] || 5 @http_debug_output = [:http_debug_output] @backoff = backoff( [:backoff]) @async_refresh = false super end
Instance Attribute Details
#retries ⇒ Integer
(readonly)
# File 'gems/aws-sdk-core/lib/aws-sdk-core/ecs_credentials.rb', line 80
attr_reader :retries


One Revolution
May 2009
From nothing I imagine
No reason not to run and branch
with fractal shapes like ink runs
free on wet paper
There is nothing that contains me
All we know we should free
-and let be wild
Let all our understanding be and so ourselves be wild!
Let us block set, so to print
Only so to smear it all away
free ink and so let be free on pages
they will be the exclamations of our days
freed but onto each other we will laugh as we brush
all once we knew away
Be it reduced to ash -all we once did know
Be it reduced to ink and paper
and thus only lack the infinity of water
I am captivated by the seasons
I am entoken to the land that signifies me
Satisfy the land does not me
nor the words that seemingly I impress-
Run free!
Let be what will begin
Let be that march unto ashen ends
Let be that wrong road follow
So, be it not wrong until discovered
that the choices we faced were free
So be free and I will follow
So die, for I will-
Be ashes, I will be-
If washed away and so will I be-
If you are words I will match them-
Set letters and I will press them-
If you are the ink, I will be but a brush stroke away
Water, if it free you to be
-Ink, formless, an oscillation between what is thoughts and what is words and
what is spoken, said, undone confusion;
testimony that was given up, to and about
floating unconscious in the waters of the mind
echoing and lightning up-
- connections, webs and networks of thoughts
-The grand machine,
-how you are not fair!
and though I will fair, do speak I can
And I wonder in which does move me and I imagine
provocations that-are still standing
fleets of ships that are burning
people who are losing and aging and are no more
Why can’t you be real? Why philosophy is as true as it’s taken to be
These words are about you and I
When together, how we argue-
And when apart they echo in my mind
arguments would tear apart so many kind
How rips apart families
How wade into war
How tear to insanity
Philosophy is not princess over sciences
yet she does not cut cheaply into lives
Our arguments some day insulate
and it is in this sense that I rely on you
to deconstruct out space and time
Remove me, for I am captive by a world that no longer gleams
I have forgotten the wild and am amidst the forest as so speaking
Will you speaker out your voice and return to the wind
your words, your free style-?-
I cannot help to see it in your eyes
And so irrational I speak!
How can it be rational
I beg the question; tell me?
For someday I will not to answer
my will be lost
like all those surround me
Everything is lost until found the strength
I will exact upon the diss-aligned
but I am! You have the quality of strength
to be set about in this writing,
it’s not rational to imagine
‘something new’ it’s hard to pre-suppose existed before it happened-
By time the planet spins around the solar system
one revolution,
-things could be completely different


The New Instrument Research Lab (NIRL) at Princeton University is headed by Jeff Snyder, the Director of Electronic Music and the Director of the Princeton Laptop Orchestra (PLOrk). The lab focuses on the creation of new instruments for electronic music performance, with emphasis on embedded synthesis and physical interfaces.


Multimillion-dollar repair bill for Wairoa in storm’s wake
by Aaron van Delden - Local Democracy ReporterMultimillion-dollar repair bill for Wairoa roads in storm’s wake
State Highway 38 to Lake Waikaremoana was blocked by several slips. PHOTO: Facebook / Wairoa District Council
Millions in financial aid to repair storm-damaged roads have helped keep Wairoa District Council from running at a loss.
The council recorded a $1.85 million surplus for the year to June 30, but it could have been a $1m deficit without subsidies from the New Zealand Transport Agency (NZTA), said the council’s finance and corporate support group manager, Gary Borg.
In early September 2018, two months of rain fell in the district over a 72-hour period, wreaking havoc with infrastructure.
Many local roads were flooded or blocked by slips, as were State Highway 2 at Mohaka Viaduct south of Wairoa town and State Highway 38 to Lake Waikaremoana.
About 80 percent of the damage to infrastructure wrought by the wild weather has now been repaired, the council says.
Its annual report for the year to June 30, adopted at a council meeting on Tuesday, says grants and subsidies totalled $14,070,000, including $13,650,000 in NZTA subsidies.
The council had planned on receiving $9,566,000 in grants and subsidies.
At the same time, it spent $13,560,000 on transport, including roads. The budget was $10,166,000.
NZTA subsidises work carried out by councils on local roads at various rates.
For Wairoa District Council, the agency reimburses 75 percent of the work’s cost once it has been completed.
The agency has also approved a 95 percent subsidy for $10m of emergency roadworks in Wairoa to repair 2018 storm damage.
Councillor Jeremy Harker said NZTA funding was vital as the council could not predict and therefore budget for storm damage.
It could not afford to repair the damage without subsidies, Cr Harker said.
The annual report notes the district’s roads are not covered by insurance, given the expectation government funding will be available to fix the roading network in the event of a major disaster.
Mayor Craig Little said lags between completing a job and being reimbursed by NZTA created a headache for budgeting.
He thought the Government should look at streamlining the system so there was no delay.
With the frequency of severe weather events expected to increase, Mayor Little also thought establishing a central government fund for climate change mitigation was a good idea.
Wairoa District Council collected $12.5 million in rates in the year to June 30.
As of June 30, there were 7203 properties in the district from which rates were drawn.
At the meeting on Tuesday, Cr Harker said Wairoa residents needed to recognise the constraints on the level of service the council could afford to deliver, given its limited rates revenue.
The annual report should have been adopted by October 31, in accordance with the Local Government Act 2002, but it was not signed off by the council’s auditor until November 18.
The meeting agenda notes this was due to “extenuating circumstances”.
Deputy mayor Hine Flood was “embarrassed” the council was late in adopting the plan.
“How do we manage a work plan so that we don’t find ourselves here again?” she asked.
Chief executive Steven May said an independent review into why the report was not delivered on time would look at both technical and staffing issues.
Mr May was paid $219,976 in the 2019 financial year.
Remuneration for the council’s senior leadership team was up $233,587 on the 2018 financial year to almost $1.1m.
A senior manager role was disestablished last November, so the team now comprises Mr May and four senior managers.
ENDS


Emerging from the local women’s movement against street harassment, bullying and stalking, new social collaboration tools like SafetiPin are helping women work together to assess the relative safety of urban areas in India’s largest cities. Free to download, SafetiPin is an Android and iOS app that employs location services and an open-source map to allow users to rate a neighborhood or a specific street’s relative safety, while also showing how others have rated that area.
At the core of the app is the Safety Audit. Users rate the safety of a given area based on key parameters such as the availability of working street lights, the presence of police and other security personnel, the number of men or women on the street, and the overall mood on the street. The Asia Foundation worked with SafetiPin to provide professionally trained auditors to collect additional safety-related information on communities and cities to augment data submitted by users.
SafetiPin builds on the premise that community participation and engagement will make India’s cities safer. By leveraging India’s over 300 million mobile phone subscribers, this initiative is transforming the way women connect with one another and obtain safety and security information from within their local communities.


Deploying QATrack+¶
A note about security¶
Before deploying QATrack+ in the clinic, please take the time to read about security & QATrack+ on the security notes page. We recommend using https for your site whenever possible.
Deployment Options¶
Django applications like QATrack+ are typically deployed on a Linux server using PostgreSQL or MySQL as the database. If your department has Linux support/experience this is the recommended way to deploy QATrack+.
That said deploying to a Windows Server instance using SQL Server is entirely feasible and many clinics choose this as their platform.
Deployment on a Mac server is also relatively straightforward.
Below you can find a number of guides for a variety of platforms. As of version 0.2.9, only the first two here are tested officially by the developers before release.
Officialy Supported¶
- Linux/Apache/PostgreSQL(or MySQL) (recommended)
- Windows Server/IIS/CherryPy/SQL Server (TOHCC’s current setup serving 2 campuses & 100+ users)
Alternatives¶
- Windows Server/IIS/SQL Server (Full MS implementation with SSO/Integrated Authentication)
- Windows Desktop/Apache/PostgreSQL (Run QATrack+ from a Windows desktop)
- OS X Server(ML)/Apache/PostgreSQL
Configuring QATrack+ for your needs¶
There are lots of settings in QATrack+ that can be tweaked to meet the specific needs of your clinic. Some of the most common ones are described below (in progress!). Generally the qatrack/settings.py file should be left alone and any customizations for your clinic should be placed in a qatrack/local_settings.py file.


Implied Probability: Probability of the team of winning a game based on historical stats. Independent of rival and of home/visitor adjustments. Outcome Probability: Calculates the probability of winning given the chosen home team vs. chosen visitor team ODDS/MOMIO: Dollar Paid per Dollar Bet Ratio


💥 Building Fully responsive website front end using HTML, CSS, Bootstrap and Javascript.
💥 As of now I have knowledge only of front end but in near future I will add more features to myself and excited to explore React , NodeJS, Django , Flask and many more.
💥 I have also used Abode Photoshop, Illustrator and Figma to design User interface of websites and mobile application and design of logos.


Construction of Ajaokuta gas pipeline to begin soon – Buhari
by Hamed ShobiyePresident Muhammadu Buhari said on Friday work would soon commence on the construction of the 600-kilometre Ajaokuta-Kaduna-Kano gas pipeline which would move gas from the Southern part of the country to the North.
A statement issued in Abuja by the Senior Special Assistant to the President on Media and Publicity, Garba Shehu, said President Buhari disclosed this while addressing the 5th Gas Exporting Countries Forum (GECF) Summit at the Sipopo International Conference Hall, Malabo, Equatorial Guinea, on Friday.
He said the viability of extending the gas pipeline to North Africa was also under consideration.
While describing the theme of the Summit, Natural Gas – Energy for Sustainable Development as most appropriate, President Buhari noted that the one-day meeting was “taking place at a critical juncture as global energy supply is transitioning from hydrocarbons to renewables.”
According to him, the Paris Accord of 2015 signalled the first major global commitment to a deliberate effort on this inevitable transition.
He said: “Nigeria is proud to be one of the first signatories to the historic Agreement.”
While explaining why Nigeria and GECF members are focusing on gas development, the Nigerian leader said:
“We are mindful of the energy deficit in the developing world, especially here in Africa where we have nearly 600 million people without access to modern energy. As responsible leaders, it is our duty to preserve the environment not only for the present but for future generations.
“We can achieve this balance between our energy deficit and environmental preservation needs by developing and deploying new technologies. Although classified as fossil fuel, natural gas is a viable solution to both our energy and environmental challenges. (NAN)


Implements simple Hamiltonian Monte Carlo routines in R for sampling from any desired target distribution which is continuous and smooth. See Neal (2017) <arXiv:1701.02434> for further details on Hamiltonian Monte Carlo. Automatic parameter selection is not supported.
| Version: | 1.0.0 |
| Published: | 2018-10-28 |
| Author: | Victhor Sartório [aut, cre, cph] |
| Maintainer: | Victhor Sartório <victhor at dme.ufrj.br> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | rhmc results |
| Reference manual: | rhmc.pdf |
| Package source: | rhmc_1.0.0.tar.gz |
| Windows binaries: | r-devel: rhmc_1.0.0.zip, r-release: rhmc_1.0.0.zip, r-oldrel: rhmc_1.0.0.zip |
| OS X binaries: | r-release: rhmc_1.0.0.tgz, r-oldrel: rhmc_1.0.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=rhmc to link to this page.