A practical approach to groovy
def name = "Xavier"
println "My name is $name"
assert "Xavier" == "Mon nom est Xavier."[12..17]
assert "Xavier" == "Mon nom est Xavier."[12..-2]
int i = "18".toInteger()
//Multiline
def str = """
Lorem Ipsum is simply dummy text of the printing
and typesetting industry.
Lorem Ipsum has been the industry's
standard dummy text ever since the 1500s
"""
class Person {
String name
int age
}
new Person(name:"Xavier", age:21)
def map = [
"name":"Xavier",
"age":21
]
new Person(map)
assert [] instanceof ArrayList
assert [1, 2] + [3, 4] == [1, 2, 3, 4]
def names = ["Xavier", "Lenny"]
names.each {name -> println name}
names.each {println it}
names.eachWithIndex { String name, int i -> println "$i:$name"}
names.collect{name -> "Hi $name"}
names.find {it.startsWith("X")}
names.findAll {it.length() > 3}
names.groupBy {it[0]}."X".size() // => 1
def (beforeM, afterM) = names.split { it[0] < "M"}
assert beforeM == ["Lenny"] && afterM == ["Xavier"]
//create a closure and apply it on the collection
def p = {o -> println "${new Date()}...$o"}
names.each(p)
//chain
"xavier-lenny".split("-").collect { it.toUpperCase() }.join(";").with(p)
//read the whole content of a file
def body = new File("file-name.txt").text
//and same for write
new File("file-name.txt").text = "this is a file body \n second line"
//Sample file for testing
def myFile = new File("/tmp/a.json")
myFile.text = """{"name":"Xavier", "age":29}"""
//Json to Object from File or from String
def author = new JsonSlurper().parse(myFile)
author = new JsonSlurper().parseText(myFile.text)
assert author instanceof Map
//Edit the map
author.age = 30
//Object to Json
myFile.text = new JsonBuilder(author).toString()
println myFile.text
// => {"age":30,"name":"Xavier"}
//Sample file for testing
def myXmlFile = new File("/tmp/a.xml")
myXmlFile.text = """Xavier """
//Json to Object from File or from String
def authorX
authorX = new XmlSlurper().parse(myXmlFile) //SAX
authorX = new XmlParser().parse(myXmlFile) //DOM
authorX = new XmlParser().parseText(myXmlFile.text)
assert authorX instanceof Map
assert authorX.name == "Xavier"
assert authorX.@age == 30
def list = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]
withPool( 10 ) {
list.eachParallel { elm, idx ->
println "Working on elt:$elm at idx:$idx"
}
println "Fork/join and wait all tasks to finish... Done ! "
}


Solo artist BLUE:D to drop new single 'Nobody' featuring WINNER's Song Min Ho
by danisurstBLUE:D is collaborating with WINNER's Song Min Ho!
On November 18 KST, YG Entertainment released two teaser images announcing the single, which is entitled "Nobody." Fitting with the artist's name, both images are saturated in multiple shades of blue, showing the singer with a blue cropped bob as she clutches a bouquet of blue flowers.
Meanwhile, BLUE:D is a solo artist under YGX, a subsidary of YG Entertainment. Since opening her official YouTube channel earlier this year, she has gained a number of fans with covers of artists like Fifth Harmony, Billie Eilish, and BLACKPINK.
Check out the teasers below, and stay tuned for this exciting release!


simulations module¶
-
simdna.simulations.
motif_density
(motif_name, seq_length, num_seqs, min_counts, max_counts, GC_fraction, central_bp=None)[source]¶ returns sequences with motif density.
-
simdna.simulations.
simple_motif_embedding
(motif_name, seq_length, num_seqs, GC_fraction)[source]¶ returns sequence array
-
simdna.simulations.
simulate_differential_accessibility
(pos_motif_names, neg_motif_names, seq_length, min_num_motifs, max_num_motifs, num_pos, num_neg, GC_fraction)[source]¶ Generates data for differential accessibility task.
Parameters: - pos_motif_names (list) – List of strings.
- neg_motif_names (list) – List of strings.
- seq_length (int) –
- min_num_motifs (int) –
- max_num_motifs (int) –
- num_pos (int) –
- num_neg (int) –
- GC_fraction (float) –
Returns: - sequence_arr (1darray) – Contains sequence strings.
- y (1darray) – Contains labels.
-
simdna.simulations.
simulate_heterodimer_grammar
(motif1, motif2, seq_length, min_spacing, max_spacing, num_pos, num_neg, GC_fraction)[source]¶ - Simulates two classes of sequences with motif1 and motif2:
- Positive class sequences with motif1 and motif2 positioned min_spacing and max_spacing
- Negative class sequences with independent motif1 and motif2 positioned
anywhere in the sequence, not as a heterodimer grammar
Parameters: - seq_length (int, length of sequence) –
- GC_fraction (float, GC fraction in background sequence) –
- num_pos (int, number of positive class sequences) –
- num_neg (int, number of negatice class sequences) –
- motif1 (str, encode motif name) –
- motif2 (str, encode motif name) –
- min_spacing (int, minimum inter motif spacing) –
- max_spacing (int, maximum inter motif spacing) –
Returns: - sequence_arr (1darray) – Array with sequence strings.
- y (1darray) – Array with positive/negative class labels.
-
simdna.simulations.
simulate_motif_counting
(motif_name, seq_length, pos_counts, neg_counts, num_pos, num_neg, GC_fraction)[source]¶ Generates data for motif counting task. :param motif_name: :type motif_name: str :param seq_length: :type seq_length: int :param pos_counts: (min_counts, max_counts) for positive set. :type pos_counts: list :param neg_counts: (min_counts, max_counts) for negative set. :type neg_counts: list :param num_pos: :type num_pos: int :param num_neg: :type num_neg: int :param GC_fraction: :type GC_fraction: float
Returns: - sequence_arr (1darray) – Contains sequence strings.
- y (1darray) – Contains labels.
-
simdna.simulations.
simulate_motif_density_localization
(motif_name, seq_length, center_size, min_motif_counts, max_motif_counts, num_pos, num_neg, GC_fraction)[source]¶ - Simulates two classes of seqeuences:
- Positive class sequences with multiple motif instances in center of the sequence.
- Negative class sequences with multiple motif instances anywhere in the sequence.
The number of motif instances is uniformly sampled between minimum and maximum motif counts.
Parameters: - motif_name (str) – encode motif name
- seq_length (int) – length of sequence
- center_size (int) – length of central part of the sequence where motifs can be positioned
- min_motif_counts (int) – minimum number of motif instances
- max_motif_counts (int) – maximum number of motif instances
- num_pos (int) – number of positive class sequences
- num_neg (int) – number of negative class sequences
- GC_fraction (float) – GC fraction in background sequence
Returns: - sequence_arr (1darray) – Contains sequence strings.
- y (1darray) – Contains labels.
-
simdna.simulations.
simulate_multi_motif_embedding
(motif_names, seq_length, min_num_motifs, max_num_motifs, num_seqs, GC_fraction)[source]¶ Generates data for multi motif recognition task. :param motif_names: List of strings. :type motif_names: list :param seq_length: :type seq_length: int :param min_num_motifs: :type min_num_motifs: int :param max_num_motifs: :type max_num_motifs: int :param num_seqs: :type num_seqs: int :param GC_fraction: :type GC_fraction: float
Returns: - sequence_arr (1darray) – Contains sequence strings.
- y (ndarray) – Contains labels for each motif.
-
simdna.simulations.
simulate_single_motif_detection
(motif_name, seq_length, num_pos, num_neg, GC_fraction)[source]¶ - Simulates two classes of seqeuences:
- Positive class sequence with a motif embedded anywhere in the sequence
- Negative class sequence without the motif
Parameters: - motif_name (str) – encode motif name
- seq_length (int) – length of sequence
- num_pos (int) – number of positive class sequences
- num_neg (int) – number of negative class sequences
- GC_fraction (float) – GC fraction in background sequence
Returns: - sequence_arr (1darray) – Array with sequence strings.
- y (1darray) – Array with positive/negative class labels.


SCXML Compliance
Supported Data Models
Qt SCXML supports the following data models:
- null data model, as described in SCXML Specification - B.1 The Null Data Model
- ECMAScript data model, as described in SCXML Specification - B.2 The ECMAScript Data Model
- C++ data model, as described in the QScxmlCppDataModel documentation
Supported Elements and Attributes
The Qt SCXML implementation is SCXML compliant, with a few exceptions:
- Event data (
_event.data
) is implemented as a QVariant. If parameters are passed to<send>
, the QVariant holds a QVariantMap, so multiple parameters with the same name are not supported. - There is no "raw" representation of an event.
- The (optional) basic http event I/O processor is not supported.
- The contents of a
<script>
tag and a<data>
tag must be valid for the chosen data model. So, as an example: XML content inside <data> is not supported. However, the ECMAScript data model does support data in JSON format. - The only service that can be instantiated with
<invoke>
is another SCXML state machine. - To keep the behavior of dynamically created state machines and compiled state machines the same, the typeexpr and srcexpr attributes are not supported. Moreover, if a
<content>
tag is used inside an<invoke>
tag, that content must be XML. Specifically, dynamically creating SCXML, for example by concatenating strings with the ECMAScript data model, is not supported.
Qt SCXML Extensions
The Qt SCXML implementation extends SCXML in the following ways:
- If the event is an error event,
_event.errorMessage
will contain a more detailed description of the error.


http://www.cosmometry.net/basics-of-the-music-system
http://www.cosmometry.net/tri-tone-duality-of-music


m.images
Image:
Image with link:
Image, class on top, custom alt:
Image with link, class on top:
Image with custom width, height and scale (scale gets picked):
Image with custom width and height (width gets picked):
Image with custom height:
Figure:
Figure with link, scale and only a caption:
Figure with link and class on top:
Figure with a width:
Figure with a height:
Image grid, second row with a custom title and no title:
Image grid with a PNG file, JPEG with sparse EXIF data, JPEG with no EXIF data and long exposure (>1 second):


Yuno's Command List
Administration
CustomReactions
Gambling
Games
Help
Music
NSFW
Permissions
Pokemon
Searches
Utility
Xp
Command Name
Description
Usage
{{COMMANDS}}


Contact Us
Because we love making new friends
We are here for you 24/7
Head Office
Rakshan Foundation, IIT Bombay, Powai, Mumbai, India - 400076
Phone: +91 22 2572 2545
Regional Office I
Rakshan Foundation, MNIT, JLN Marg, Jaipur, Rajasthan - 302017
Phone: +91<PHONE_NUMBER>
Regional Office II
IIT Kanpur, Kalyanpur, Kanpur, Uttar Pradesh 208016
Phone: +91<PHONE_NUMBER>
Get In Touch
For any grievance, suggestions and queries kindly write to us.


| {{time}} |
Status Server
Connection
Switcher
ATEM
|
|
|
Main M/E
ATEM
|
||
|
Transition
Position
Style
Upstream Key
|


Profile
Username:
Email :
Phone :
City :
Add tool
add
Your Tools
edit
Name:
Description:
Price:
Status:
Tool Name
Tool Image
Description
Price
Status
Choose your status
Tool Category
Choose your category


A wound that has become infected with germs is red and slightly swollen. Infected cuts or abrasions are common and, if kept clean, will usually improve within twenty-four hours. But if the redness of an infection spreads and there is more swelling and pain, watch out. Certain nasty germs, such as streptococci and staphylococci, can spread rapidly. Red streaks running up an arm or leg from the site of the infection indicate a rapid and dangerous spread of germs. If you have diabetes or are taking prednisone, you are especially vulnerable to these types of infections.
If your infected wound is getting worse, consult your physician immediately. Your doctor can do tests to determine which antibiotic will be the most effective to combat the infection.


Plugin Information |
|---|
View MSTestRunner on the plugin site for more information. |
This plugin allow you to execute test using MSTest command line tool.
Description
This plugin allow you to execute test using MSTest command line tool.
MSTest are test classes for .NET framework which are integrated into Visual Studio. You should use a plugin to process the result files, I recommend using MSTest Jenkins Plugin. You can read my post about how to setup Jenkins with MSTest in my blog.
Configuration
To configure a MSTest installation, go to Manage Jenkins -> Configure System (or Manage Jenkins -> Global Tool Configuration in Jenkins 2.8, possibly earlier) and add a MSTest installation. Name is mandatory. If Path to MSTest is left blank, the default is MSTest.exe.
MSTestRunner can be used as a build step. The screenshot below shows the configuration parameters available where the Test Files and the Result File Name are mandatory. The MSTest Version is not mandatory. If the default is used, the plugin will look for MSTest.exe, so ideally it should be in the path.
For further configuration tips, see each field's inline help.
Version History
Version 1.3.0 (25/05/2016)
- JENKINS-34392 Upgrade to new plugin parent POM
- JENKINS-30457 Relative paths to test files with dots failing.
- JENKINS-34378 Validation for the test result filename field.
Version 1.2.0 (09/12/2015)
- JENKINS-28869 - Fixes problem with newline tokennization (thanks to Thomas Blitz)
- JENKINS-29389 - Quotation marks for /testcategories argument, must beused only when multiple category was specifed (thanks to Nikolas Falco)
- JENKINS-29391 - add support to full path in testFiles (thanks to Nikolas Falco)
- JENKINS-30292 - Not visible in Conditional BuildStep Plugin (thanks to Ido Ran)
Version 1.1.0 (06/04/2014)
- Add Continue On Failed Test checkbox which allows to report success even when test have failed (JENKINS-20367)
Version 1.0.1 (06/06/2013)
Version 1.0.0 (31/05/2013)
- Path to test containers (DLLs) are allowed to have space in them.
- Test containers can now only be separated with new lines because they are allowed to have space in them.
- The license of this plugin is now MIT.
Version 0.2.1 (09/14/2012)
- Fix the bug in which the flag /noisolation was not added by default.
- Add new option in MSTest config (Manage Jenkins -> Configure System -> MSTest) name Omit Noisolation. Checking this option will omit the /noisolation flag from the call to MSTest.
Version 0.2 (09/02/2012)
Notice
Due to update in version 0.2 the plugin do not add /noisolation flag by default which break MSTest on some systems.
To work around this problem until then either downgrade to 0.1 or add /noisolation flag in Manage Jenkins -> Configure System -> MSTest -> Default Paramters.
You can upgrade to version 0.2.1 which fix the problem.
Version 0.1 (01/15/2012)
- Initial release
Attachments:
mstestrunner-config.png (image/png)
mstestrunnner-install.png (image/png)
mstestrunnner-install.png (image/png)
install.png (image/png)


Find friends or family members to play with or play by yourself. You can team up against others. It’s great to play at parties!
You will be shown a picture of a celebrity and given 15 seconds to chose whether that celebrity is alive or not
Scores are tallied up and compared at the end of a round of guessing. The person or team with the highest score wins!
Create an account to save your results and play again to get the highest score!


If you are into front-end development, and you started reading about TypeScript vs JavaScript, minification, css preprocessors, task runner and bundling, but you don't want to mess with a big framework, you came to the right place.
Here is presented a website, used as a base for your upcoming projects that need to be pure or frameworkless with the scalable advantages that TS and Sass offer, so you can spend less time configuring and more time coding.
SASS is a CSS preprocessor, it lets you generate Css from Sass unique syntax allowing to make more with less code, using variables, nesting, partials, mixins and much more!
TypeScript extends JavaScript by adding types.  Also, Typescript mixes the old with the new in the best way possibility. You can use newer features from ES6, and beyond, and the compiler will convert them to ES5 (or whatever you specify). This allows you to make use of newer features that will be the future of Javascript, without having to worry about compatibility. The finished code produced by the compiler will be backwards compatible with ES5 and will work just fine with older browsers.
Gulp is a task runner that provides automation for repetitive workflows and compose them into efficient build pipelines, so we can have a confortable developing environment and automated tasks for deployment in different environments.
Happy Coding!
According to your device, it's:


This site is all about my professional and personal life.
ShipMatrix 2013-09-23 —
ShipMatrix is a business intelligence and reporting platform that leverages industry knowledge to better shipping practices of large scale shipping operations.
Highlights
- Created and launched http://www.EasyTrackApp.com the application's brochure site.
- Developed several new desktop applications, providing software specifications and testing analysis.
- Created dynamic SQL queries to consistently update based on currently non processed files across 20+ vm's and 100+ databases hosted on 2 different servers.
- Updated the main reporting site's look and feel as well as brought CSS1 up to current CSS3 standards.
- Developed a communcations tool that downloads directly from both fedex.com and ups.com.
- Gained a lot of knowledge about mobile apps, SQL Server, and desktop applications running in virtual environments.
RedZone Robotics 2010-10-01 — 2013-08-02
RedZone Robotics was a CMU grad staffed asset reporting system. Staffed primarily by brilliant young CMU graduates RedZone Robotics serviced municipal waste lines through robotic data collection of television, laser, gas, and IMU data.
Highlights
- Created an entire company overhead view of the processes mapped to a flowchart that the company still has in use today.
- Independently responsible for training and integration of new data processing methods into the Responder platform.
- Managed data alignment using custom software and reporting back to software for bugs and enhancement requests personally and using freshdesk ticketing system.
- Manually updated fields in Microsoft access using individual find and replaces or SQL update statements.
- Updated company computer's hardware and software as needed.
- Never missed a deadline even with the most complicated data. Helped to remove 20+ accoutns from being 'in the red' per the company's requirements.
DirecTV 2007-07-01 — 2009-05-01
DirecTV was an excellent position I enjoyed for over a year. I left DirecTV to focus on my studies however as I was falling behind when combining new software classes in their interim stages as well as a 70+ hour work week that ended often just prior to class starting. This was a great move as I turned around a falling GPA to graduate honors from ITT-Technical Institute recieving honorary induction into the National Technical Honors Society. When employed with DirecTV I became SBCA certified to install KaKu band DirecTV satellite hardware. It was a very rewarding experience to be able to go into people's homes and offer them excellent service. I made many new friends and colleagues during my period with DirecTV.
Highlights
- One of the first technicians trained in single line installations. This installation process led to the future generation 1080p "Genie" HD-DVR DirecTV currently installs.
- Managed a week long off-truck inventory and supported other field technicians with hardware drop offs as needed while still completing my own installation responsibilities.
- Graduated to a Level II technician after receiving a 96% or greater customer service rating for the first 6 months of independently installing DirecTV.
- Learned a great deal about on location customer servicing and satisfaction.
Kosmonauts 2014-09-15 —
Helped a friend out by creating a simple BootStrap layout DJ site where he can showcase his works using the embedded SoundCloud API
Highlights
- SoundCloud API and dynamic layouts (mobile and desktop)
ITT-Technical Institute 2007-09-01 — 2010-03-01
Courses
- IT-Software programming
- IT-Multimedia
Graduated with Honors
National Technical Honor Society
Web Development - Front End
- HTML5
- CSS
- XHTML
- XML
- Javascript
- Universal Analytics
- Social Netowrking
Web Development - Back End
- Web Services/ASP.NET
- FTP/SFTP
- NoSQL/MongoDB/cshtml(Razor)
Desktop Development
- Versioning
- Specifications
- Overseas Dev Teams
- Bash|Zsh|Terminal|CMD
- Microsoft SQL Server
- Oracle Virtual Box
- Basic *nix
- Cloud Services
JavaScript
- Eloquent JavaScript
- Javascript Demistified
- 5 minutes of JS
- Frameworks
- Server Side
- Front-End
- EXPRESS
- NODEJS
- BSON|JSON|JSONP
CSS
- BootStrap
- Bootply
- CodePly
- SaSS
Tech
- NoSQL
- CWS
- Android
- Bleeding Edge
- Displays
- Current Trends
- Hard-OCP
- MicroCenter
- Tom's Hardware Ranks
- cpuBoss|gpuBoss|ssdBoss
RedZone - Manager
— James Hilscher
RedZone - CoWorker (Coder - SQL)
— Boris Langer
RedZone - CoWorker (Coder Ruby|MatLab|C#)
— Vince Eberle
RedZone - CoWorker (Coder C#|.NET|SQL)
— Joe Salotti
RedZone - CoWorker (Coding Team Lead)
— James Patula
DirecTV - CoWorker (Installer Lead III)
— Jonathan DiMatteo
DirecTV - CoWorker (Installer III)
— Matt DiMattteo
RedZone - Office Admin/HR Coordinator
— Pam Yarsky(Calcaterra)
ShipMatrix - Senior Coding Lead
— William DiPlacido
ShipMatrix - Senior Sales Lead
— Richard Stein
SJC(ShipMatrix Parent Co.) - Consultant Lead
— Michael Scheid


?6
7
8
9
10
_
XT
v
The
Newark
copyright
reserved
botanical
Garden
THE
NEW
YORK
BOTANICAL
GARDEN
Plants
of
Hispaniola
Dominican
Republic
No.
16135
└umelia
cubensis
Griseb,
Det,
Alain
H,
Liogier,
Feb.
1970.
Small
tree,
up
to
6-7
m
high,
branches
spreading,
flovers
white.
Common
on
hillside,
and
in
ravines
Arroyo
FrancÄs,
ierpentine
hills,
about
4
miles
W
of
Puerto
Plata.
Alt.
50-150
m.
Bro.
Alain
H.
Liogier
27
Sept.
1969
5.J
Supported
by
funds
from
the
National
Science
Foundation.
FLORA
NEOTROPICA
Sideroxylon
cubense
<6ris.)
Penn.
T.D.PENNINGTON
1986
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


Jinshan Pan, Haoran Bai, and Jinhui Tang
We present a simple and effective deep convolutional neural network (CNN) model for video deblurring. The proposed algorithm mainly consists of optical flow estimation from intermediate latent frames and latent frame restoration steps. It first develops a deep CNN model to estimate optical flow from intermediate latent frames and then restores the latent frames based on the estimated optical flow. To better explore the temporal information from videos, we develop a temporal sharpness prior to constrain the deep CNN model to help the latent frame restoration. We develop an effective cascaded training approach and jointly train the proposed CNN model in an end-to-end manner. We show that exploring the domain knowledge of video deblurring is able to make the deep CNN model more compact and efficient. Extensive experimental results show that the proposed algorithm performs favorably against state-of-the-art methods on the benchmark datasets as well as real-world videos.
@InProceedings{Pan_2020_CVPR,
author = {Pan, Jinshan and Bai, Haoran and Tang, Jinhui},
title = {Cascaded Deep Video Deblurring Using Temporal Sharpness Prior},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}
The proposed algorithm contains the optical flow estimation module, latent image restoration module, and the temporal sharpness prior. For the optical flow estimation, we use the PWC-Net [5] to estimate optical flow. For the latent image restoration module, we use an encoder-decoder architecture based on [26]. However, we do not use the ConvLSTM module. Other network architectures are the same as [26].
To effectively train the proposed algorithm, we develop a cascaded training approach and jointly train the proposed model in an end-to-end manner. At each stage, it takes three adjacent frames estimated from the previous stage as the input and generates the deblurred results of the central frame. When handling every three adjacent frames, the proposed network shares the same network parameters. The variables \( \tilde{I}_{i+1}(x) \) and \( \tilde{I}_{i-1}(x) \) denote the warped results of \( I_{i+1}(x+u_{i+1\rightarrow i}) \) and \( I_{i-1}(x+u_{i-1\rightarrow i}) \), respectively.
As demonstrated in [4], the blur in the video is irregular, and thus there exist some pixels that are not blurred. Following the conventional method [4], we explore these sharpness pixels to help video deblurring. The sharpness prior is defined as: \[ S_i(x) = exp(-\frac{1}{2} \sum_{j\&j\neq0}D(I_{i+j}(x+u_{i+j \rightarrow i}); I_i(x))) \tag{10} \] where \( D(I_{i+j}(x+u_{i+j \rightarrow i}); I_i(x)) \) is defined as \( \left \| I_{i+j}(x+u_{i+j \rightarrow i} - I_i(x) \right \|^2 \).
Based on (10), if the value of \( S_i(x) \) is close to 1, the pixel \(x\) is likely to be clear. Thus, we can use \( S_i(x) \) to help the deep neural network to distinguish whether the pixel is clear or not so that it can help the latent frame restoration. To increase the robustness of \( S_i(x) \), we define \( D(.) \) as: \[ D(I_{i+j}(x+u_{i+j \rightarrow i}); I_i(x)) = \sum_{y\in \omega(x)} \left \| I_{i+j}(x+u_{i+j \rightarrow i} - I_i(x) \right \|^2 \tag{11} \] where \( \omega(x) \) denotes an image patch centerd at pixel \( x \).
We further train the proposed method to convergence, and get higher PSNR/SSIM than the result reported in the paper.
Quantitative results on the benchmark dataset by Su et al. [24]. All the restored frames instead of randomly selected 30 frames from each test set [24] are used for evaluations. Note that: Ours* is the result that we further trained to convergence, and Ours is the result reported in the paper.
Quantitative results on the GOPRO dataset by Nah et al.[20].
Here are some visual comparisons with state-of-the-art methods. The proposed algorithm generates much clearer frames. More visual results are included in supplementary materials.
If you have any question, please contact us by:


disease meningococcal {border-style []. px;} #ffffff;} meningococcemia HIV HIV-infected cases infection Neisseria case clinical px; viral {font-family chronic font-size patient count double; load meningitidis Chronic Picture São border-color border-width risk solid; vertically {font-style {font-weight Infect Pictures adolescent association bacterium bold courier; days disease. em; healthy immunocompromised immunodeficiency incidence increased invasive lesions occur patients previously pt;} rare received report review


[gecode-users] Float values and element constraint
Arshad Khan
khan.m.arshad at gmail.com
Tue Feb 21 13:59:37 CET 2017
Hello All,
I am a Gecode novice and seeking your expert help on one of the issue that
I am facing when using float values.
In the example warehouse.cpp, the supply cost from a warehouse to a store
is defined using an int value matrix (c_supply). This matrix is later used
in one of the constraint that computes the cost. Now I want to use a cost
matrix of float values. However, the constraint uses an 'element'
constraint to compute the cost which is not defined for float values. How
can I convert the constraint to use float values? Any help is greatly
appreciated.
For your reference, the relevant code from the example is follows:
// Compute cost for each warehouse
for (int s=0; s<n_stores; s++) {
IntArgs c(n_warehouses, c_supply[s]);
c_store[s] = expr(*this, element(c, supplier[s]));
}
(What I want is to have a FloatValArgs type for c.)
Thanks and Regards
Arshad
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://www.gecode.org/pipermail/users/attachments/20170221/8e3b976e/attachment.html>
More information about the users
mailing list


subject = "New Order - Cash on Delivery #{{order_id}}" ==
Dear {{first_name}} {{last_name}},
Your order has been received and processing. When order will be dispatched you will be informed by email.
Thank you,
Best Regards OIMS.


An experience in tone and texture
Worth the wait? Spoiler: no...
Possibly the greatest hard-rock album ever.
The more blue kind of blue


CRISPR-BETS
About
Report
Back
Location
GO
×
Issue
If you have any issue and advice,please connect<EMAIL_ADDRESS>×
About
A gRNA design software for base editing knockout using stop codon.
Version: V1.0


class: center, middle, inverse, title-slide # Synthetic Control Methods (SCM) workshop ### Geraldine Clarke ### Emma Vestesson ### Paris Pariza ### Stefano Conti --- # What we will cover today - Set-up -- - Introduction -- - R and rmarkdown refresher -- - Some theory - examples and methods -- - Running some R code --- background-image: url(https://cdn.pixabay.com/photo/2018/06/29/08/15/doodle-3505459_960_720.png) --- # Prep Code and slides available on github https://github.com/THF-evaluative-analytics/webinar-SCM-workshop We will be using some custom created data so you will need to download the project if you want to follow along If you don't have Rstudio installed try using rstudio.cloud Install all packages listed in the /workshop/SCM-workshop_for_participants.Rmd (in the R folder) --- # About the improvement analytics unit We are an innovative partnership between NHS England and the Health Foundation that provides robust analysis to help the NHS improve care for patients. Our aim is that our analysis helps the local NHS and its partners identify whether implementation of an initiative is having the desired effect, or needs to change to succeed. --- # R refresher - R is a statistical programming language - Rstudio is one of the most popular IDEs used with R -- R Studio projects make it straightforward to divide your work into multiple contexts, each with their own working directory, workspace, history, and source documents. This means that: - The .Rprofile file in the project's main directory is sourced by R. - The current working directory is set to the project directory. - Previously edited source documents or settings are restored. --- # Tidyverse - tidyverse is collection of R packages based on tidy data principles. - dplyr package allows simple commands for data manipulation (select(), filter(), mutate(), group_by()). - pipes (%>%) simplify R code by passing data through functions without nesting. --- # Rmarkdown R Markdown is a file format for making dynamic documents with R and it contains chunks of embedded R code. - You can knit the file and you can convert the file into an HTML, PDF, or Microsoft Word file. - Use one hashtag, #, to create a header or two, ##, to create a second level header, and so on. - To embed a chunk of R code, surround it with two lines each containing three backticks (```); after the first set of backticks, include {r}, which consist of a chunk of R code. - To omit the code from the final report, add the argument echo = FALSE inside the {r}. - To avoid evaluating a chunk of R code, add the argument eval = FALSE inside the {r}. --- # The logic behind the Synthetic Control Method (SCM) Suppose we have a single unit which has undergone an intervention (treated unit) and some similar units that have not (control units). The SCM using a weighted average of the control units to create a synthetic control. The synthetic control is selected so as to mimic the treated unit in the period before the intervention. The idea is then, that, in the post-intervention period, the synthetic control will behave like the treated unit would have done if it had not received the intervention. By comparing the treated unit and the synthetic control in the post-intervention period we can get an idea of a treatment effect. What if there are multiple treated units? Collapse them into a single treated unit. --- # Examples and methods Now, please open /presentation/SCM-workshop_ppt_slides.pdf


| Main Project Status (05/05/2011 - 21:53:00) | |||
| Project File: | BitEpicness.xise | Parser Errors: | No Errors |
| Module Name: | Main | Implementation State: | Programming File Generated |
| Target Device: | xc3s500e-4fg320 |
|
No Errors |
| Product Version: | ISE 12.2 |
|
267 Warnings (2 new) |
| Design Goal: | Balanced |
|
All Signals Completely Routed |
| Design Strategy: | Xilinx Default (unlocked) |
|
All Constraints Met |
| Environment: | System Settings |
|
0 (Timing Report) |
| Device Utilization Summary | [-] | ||||
| Logic Utilization | Used | Available | Utilization | Note(s) | |
| Number of Slice Flip Flops | 1,671 | 9,312 | 17% | ||
| Number of 4 input LUTs | 3,488 | 9,312 | 37% | ||
| Number of occupied Slices | 2,331 | 4,656 | 50% | ||
| Number of Slices containing only related logic | 2,331 | 2,331 | 100% | ||
| Number of Slices containing unrelated logic | 0 | 2,331 | 0% | ||
| Total Number of 4 input LUTs | 3,637 | 9,312 | 39% | ||
| Number used as logic | 3,488 | ||||
| Number used as a route-thru | 149 | ||||
| Number of bonded IOBs | 96 | 232 | 41% | ||
| Number of RAMB16s | 19 | 20 | 95% | ||
| Number of BUFGMUXs | 5 | 24 | 20% | ||
| Average Fanout of Non-Clock Nets | 4.02 |
| Performance Summary | [-] | |||
| Final Timing Score: | 0 (Setup: 0, Hold: 0) | Pinout Data: | Pinout Report | |
| Routing Results: | All Signals Completely Routed | Clock Data: | Clock Report | |
| Timing Constraints: | All Constraints Met |
| Detailed Reports | [-] | |||||
| Report Name | Status | Generated | Errors | Warnings | Infos | |
| Synthesis Report | Current | Thu May 5 21:48:30 2011 | 0 | 200 Warnings (0 new) | 37 Infos (0 new) | |
| Translation Report | Current | Thu May 5 21:48:46 2011 | 0 | 0 | 0 | |
| Map Report | Current | Thu May 5 21:49:05 2011 | 0 | 31 Warnings (0 new) | 4 Infos (2 new) | |
| Place and Route Report | Current | Thu May 5 21:52:05 2011 | 0 | 5 Warnings (2 new) | 3 Infos (0 new) | |
| Power Report | ||||||
| Post-PAR Static Timing Report | Current | Thu May 5 21:52:15 2011 | 0 | 0 | 5 Infos (0 new) | |
| Bitgen Report | Current | Thu May 5 21:52:54 2011 | 0 | 31 Warnings (0 new) | 0 |
| Secondary Reports | [-] | ||
| Report Name | Status | Generated | |
| ISIM Simulator Log | Out of Date | Thu May 5 19:38:42 2011 | |
| WebTalk Report | Out of Date | Thu May 5 21:52:56 2011 | |
| WebTalk Log File | Out of Date | Thu May 5 21:53:00 2011 |


Provides a solution path for Reinforced Angle-based Multicategory Support Vector Machines, with linear learning, polynomial learning, and Gaussian kernel learning.
| Version: | 2.0 |
| Depends: | foreach, doParallel, methods, parallel, stats |
| Published: | 2016-01-23 |
| Author: | Chong Zhang, Yufeng Liu, and Shannon Holloway |
| Maintainer: | Shannon Holloway <sthollow at ncsu.edu> |
| License: | GPL-2 |
| NeedsCompilation: | yes |
| CRAN checks: | ramsvm results |
| Reference manual: | ramsvm.pdf |
| Package source: | ramsvm_2.0.tar.gz |
| Windows binaries: | r-devel: ramsvm_2.0.zip, r-release: ramsvm_2.0.zip, r-oldrel: ramsvm_2.0.zip |
| OS X binaries: | r-release: ramsvm_2.0.tgz, r-oldrel: ramsvm_2.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=ramsvm to link to this page.


| DOSE: |
1.0 g |
oral |
GHB |
(liquid) |
I've used GHB for about three years, moderately. I find it to be non addictive. My doses have remained the same, without the need to increase. Since G is a by-product of a lactone and a base conversion, (resembles a salt), one should drink plenty of liquids to keep hydrated.
I quit for two months last year to test side effects and i found none, other than i missed it (but not to a point that i couldn't function without it), no withdrawals, no depression, no physical side effects (that i can tell). Odd enough, when i first started it seemed i had developed a tolerance to it and required a bit higher doses at first.
I Never, Never, Never...Ever mix with alcohol. Effects are not linear with dose, it can creep up on me as I decide to continue doses in one sitting. I like to take 5 ml (1 gram dissolved per 5 ml) every 30-45 minutes, for an all day affair, or 15 ml before bed, after a work out.
I believe G is good for me, it used to be legal and sold at nutrition stores nationwide. It's the only thing out there that doesn't have a come down. I metabolizes in the body and leaves no traces, it's found naturally in mammalian muscle tissue (in very small traces), and after a night on partying, a couple doses make next day feel light last night never happened...:)
As with anything in life, always do your research to form your own opinion, know your limits, and understand there is a big differnce between use and abuse, you only have one body and soul for the rest of your life, it's your responsibility to care for it and moderation is key.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Package com.jme.opencl
Class Buffer
- java.lang.Object
-
- com.jme.opencl.AbstractOpenCLObject
-
- com.jme.opencl.Buffer
-
- All Implemented Interfaces:
OpenCLObject
public abstract class Buffer extends AbstractOpenCLObject
Wrapper for an OpenCL buffer object. A buffer object stores a one-dimensional collection of elements. Elements of a buffer object can be a scalar data type (such as an int, float), vector data type, or a user-defined structure.
Buffers are created by theContext
.
All access methods (read/write/copy/map) are available in both sychronized/blocking versions and in async/non-blocking versions. The later ones always return anEvent
object and have the prefix -Async in their name.- Author:
- shaman
- See Also:
Context.createBuffer(long, com.jme.opencl.MemoryAccess)
-
-
Nested Class Summary
Nested Classes Modifier and Type Class Description static class
Buffer.AsyncMapping
Result of an async mapping operation, contains the event and the target byte buffer.-
Nested classes/interfaces inherited from interface com.jme.opencl.OpenCLObject
OpenCLObject.ObjectReleaser
-
-
Field Summary
-
Fields inherited from class com.jme.opencl.AbstractOpenCLObject
releaser
-
-
Constructor Summary
Constructors Modifier Constructor Description protected
Buffer(OpenCLObject.ObjectReleaser releaser)
-
Method Summary
All Methods Instance Methods Abstract Methods Concrete Methods Modifier and Type Method Description abstract Event
acquireBufferForSharingAsync(CommandQueue queue)
Aquires this buffer object for using.void
acquireBufferForSharingNoEvent(CommandQueue queue)
Aquires this buffer object for using.void
copyTo(CommandQueue queue, Buffer dest)
Alternative version ofcopyTo(com.jme.opencl.CommandQueue, com.jme.opencl.Buffer, long)
, setssize
tothis.getSize()
.void
copyTo(CommandQueue queue, Buffer dest, long size)
Alternative version ofcopyTo(com.jme.opencl.CommandQueue, com.jme.opencl.Buffer, long, long, long)
, setssrcOffset
anddestOffset
to zero.abstract void
copyTo(CommandQueue queue, Buffer dest, long size, long srcOffset, long destOffset)
Performs a blocking copy operation from this buffer to the specified buffer.Event
copyToAsync(CommandQueue queue, Buffer dest)
Alternative version ofcopyToAsync(com.jme.opencl.CommandQueue, com.jme.opencl.Buffer, long)
, setssize
tothis.getSize()
.Event
copyToAsync(CommandQueue queue, Buffer dest, long size)
Alternative version ofcopyToAsync(com.jme.opencl.CommandQueue, com.jme.opencl.Buffer, long, long, long)
, setssrcOffset
anddestOffset
to zero.abstract Event
copyToAsync(CommandQueue queue, Buffer dest, long size, long srcOffset, long destOffset)
Performs an async/non-blocking copy operation from this buffer to the specified buffer.abstract Event
copyToImageAsync(CommandQueue queue, Image dest, long srcOffset, long[] destOrigin, long[] destRegion)
Copies this buffer to the specified image.abstract Event
fillAsync(CommandQueue queue, java.nio.ByteBuffer pattern, long size, long offset)
Enqueues a fill operation.abstract MemoryAccess
getMemoryAccessFlags()
abstract long
getSize()
abstract java.nio.ByteBuffer
map(CommandQueue queue, long size, long offset, MappingAccess access)
Maps this buffer directly into host memory.java.nio.ByteBuffer
map(CommandQueue queue, long size, MappingAccess access)
Alternative version ofmap(com.jme.opencl.CommandQueue, long, long, com.jme.opencl.MappingAccess)
, setsoffset
to zero.java.nio.ByteBuffer
map(CommandQueue queue, MappingAccess access)
Alternative version ofmap(com.jme.opencl.CommandQueue, long, com.jme.opencl.MappingAccess)
, setssize
togetSize()
.abstract Buffer.AsyncMapping
mapAsync(CommandQueue queue, long size, long offset, MappingAccess access)
Maps this buffer asynchronously into host memory.Buffer.AsyncMapping
mapAsync(CommandQueue queue, long size, MappingAccess access)
Alternative version ofmapAsync(com.jme.opencl.CommandQueue, long, long, com.jme.opencl.MappingAccess)
, setsoffset
to zero.Buffer.AsyncMapping
mapAsync(CommandQueue queue, MappingAccess access)
Alternative version ofmapAsync(com.jme.opencl.CommandQueue, long, com.jme.opencl.MappingAccess)
, setssize
togetSize()
.void
read(CommandQueue queue, java.nio.ByteBuffer dest)
Alternative version ofread(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long)
, setssize
togetSize()
.void
read(CommandQueue queue, java.nio.ByteBuffer dest, long size)
Alternative version ofread(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long, long)
, setsoffset
to zero.abstract void
read(CommandQueue queue, java.nio.ByteBuffer dest, long size, long offset)
Performs a blocking read of the buffer.Event
readAsync(CommandQueue queue, java.nio.ByteBuffer dest)
Alternative version ofreadAsync(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long)
, setssize
togetSize()
Event
readAsync(CommandQueue queue, java.nio.ByteBuffer dest, long size)
Alternative version ofreadAsync(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long, long)
, setsoffset
to zero.abstract Event
readAsync(CommandQueue queue, java.nio.ByteBuffer dest, long size, long offset)
Performs an async/non-blocking read of the buffer.Buffer
register()
Registers this object for automatic releasing on garbage collection.abstract Event
releaseBufferForSharingAsync(CommandQueue queue)
Releases a shared buffer object.void
releaseBufferForSharingNoEvent(CommandQueue queue)
Releases a shared buffer object.java.lang.String
toString()
abstract void
unmap(CommandQueue queue, java.nio.ByteBuffer ptr)
Unmaps a previously mapped memory.void
write(CommandQueue queue, java.nio.ByteBuffer src)
Alternative version ofwrite(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long)
, setssize
togetSize()
.void
write(CommandQueue queue, java.nio.ByteBuffer src, long size)
Alternative version ofwrite(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long, long)
, setsoffset
to zero.abstract void
write(CommandQueue queue, java.nio.ByteBuffer src, long size, long offset)
Performs a blocking write to the buffer.Event
writeAsync(CommandQueue queue, java.nio.ByteBuffer src)
Alternative version ofwriteAsync(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long)
, setssize
togetSize()
.Event
writeAsync(CommandQueue queue, java.nio.ByteBuffer src, long size)
Alternative version ofwriteAsync(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long, long)
, setsoffset
to zero.abstract Event
writeAsync(CommandQueue queue, java.nio.ByteBuffer src, long size, long offset)
Performs an async/non-blocking write to the buffer.-
Methods inherited from class com.jme.opencl.AbstractOpenCLObject
finalize, getReleaser, release
-
-
-
-
Constructor Detail
-
Buffer
protected Buffer(OpenCLObject.ObjectReleaser releaser)
-
-
Method Detail
-
register
public Buffer register()
Description copied from interface:OpenCLObject
Registers this object for automatic releasing on garbage collection. By default, OpenCLObjects are not registered in theOpenCLObjectManager
, you have to release it manually by callingOpenCLObject.release()
. Without registering or releasing, a memory leak might occur.
Returnsthis
to allow calls likeBuffer buffer = clContext.createBuffer(1024).register();
.- Specified by:
register
in interfaceOpenCLObject
- Overrides:
register
in classAbstractOpenCLObject
- Returns:
this
-
getSize
public abstract long getSize()
- Returns:
- the size of the buffer in bytes.
- See Also:
Context.createBuffer(long)
-
getMemoryAccessFlags
public abstract MemoryAccess getMemoryAccessFlags()
- Returns:
- the memory access flags set on creation.
- See Also:
Context.createBuffer(long, com.jme.opencl.MemoryAccess)
-
read
public abstract void read(CommandQueue queue, java.nio.ByteBuffer dest, long size, long offset)
Performs a blocking read of the buffer. The target buffer must have at leastsize
bytes remaining. This method may set the limit to the last byte read.- Parameters:
queue
- the command queuedest
- the target buffersize
- the size in bytes being readoffset
- the offset in bytes in the buffer to read from
-
read
public void read(CommandQueue queue, java.nio.ByteBuffer dest, long size)
Alternative version ofread(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long, long)
, setsoffset
to zero.
-
read
public void read(CommandQueue queue, java.nio.ByteBuffer dest)
Alternative version ofread(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long)
, setssize
togetSize()
.
-
readAsync
public abstract Event readAsync(CommandQueue queue, java.nio.ByteBuffer dest, long size, long offset)
Performs an async/non-blocking read of the buffer. The target buffer must have at leastsize
bytes remaining. This method may set the limit to the last byte read.- Parameters:
queue
- the command queuedest
- the target buffersize
- the size in bytes being readoffset
- the offset in bytes in the buffer to read from- Returns:
- the event indicating when the memory has been fully read into the provided buffer
-
readAsync
public Event readAsync(CommandQueue queue, java.nio.ByteBuffer dest, long size)
Alternative version ofreadAsync(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long, long)
, setsoffset
to zero.
-
readAsync
public Event readAsync(CommandQueue queue, java.nio.ByteBuffer dest)
Alternative version ofreadAsync(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long)
, setssize
togetSize()
-
write
public abstract void write(CommandQueue queue, java.nio.ByteBuffer src, long size, long offset)
Performs a blocking write to the buffer. The target buffer must have at leastsize
bytes remaining. This method may set the limit to the last byte that will be written.- Parameters:
queue
- the command queuesrc
- the source buffer, its data is written to this buffersize
- the size in bytes to writeoffset
- the offset into the target buffer
-
write
public void write(CommandQueue queue, java.nio.ByteBuffer src, long size)
Alternative version ofwrite(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long, long)
, setsoffset
to zero.
-
write
public void write(CommandQueue queue, java.nio.ByteBuffer src)
Alternative version ofwrite(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long)
, setssize
togetSize()
.
-
writeAsync
public abstract Event writeAsync(CommandQueue queue, java.nio.ByteBuffer src, long size, long offset)
Performs an async/non-blocking write to the buffer. The target buffer must have at leastsize
bytes remaining. This method may set the limit to the last byte that will be written.- Parameters:
queue
- the command queuesrc
- the source buffer, its data is written to this buffersize
- the size in bytes to writeoffset
- the offset into the target buffer- Returns:
- the event object indicating when the write operation is completed
-
writeAsync
public Event writeAsync(CommandQueue queue, java.nio.ByteBuffer src, long size)
Alternative version ofwriteAsync(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long, long)
, setsoffset
to zero.
-
writeAsync
public Event writeAsync(CommandQueue queue, java.nio.ByteBuffer src)
Alternative version ofwriteAsync(com.jme.opencl.CommandQueue, java.nio.ByteBuffer, long)
, setssize
togetSize()
.
-
copyTo
public abstract void copyTo(CommandQueue queue, Buffer dest, long size, long srcOffset, long destOffset)
Performs a blocking copy operation from this buffer to the specified buffer.- Parameters:
queue
- the command queuedest
- the target buffersize
- the size in bytes to copysrcOffset
- offset in bytes into this bufferdestOffset
- offset in bytes into the target buffer
-
copyTo
public void copyTo(CommandQueue queue, Buffer dest, long size)
Alternative version ofcopyTo(com.jme.opencl.CommandQueue, com.jme.opencl.Buffer, long, long, long)
, setssrcOffset
anddestOffset
to zero.
-
copyTo
public void copyTo(CommandQueue queue, Buffer dest)
Alternative version ofcopyTo(com.jme.opencl.CommandQueue, com.jme.opencl.Buffer, long)
, setssize
tothis.getSize()
.
-
copyToAsync
public abstract Event copyToAsync(CommandQueue queue, Buffer dest, long size, long srcOffset, long destOffset)
Performs an async/non-blocking copy operation from this buffer to the specified buffer.- Parameters:
queue
- the command queuedest
- the target buffersize
- the size in bytes to copysrcOffset
- offset in bytes into this bufferdestOffset
- offset in bytes into the target buffer- Returns:
- the event object indicating when the copy operation is finished
-
copyToAsync
public Event copyToAsync(CommandQueue queue, Buffer dest, long size)
Alternative version ofcopyToAsync(com.jme.opencl.CommandQueue, com.jme.opencl.Buffer, long, long, long)
, setssrcOffset
anddestOffset
to zero.
-
copyToAsync
public Event copyToAsync(CommandQueue queue, Buffer dest)
Alternative version ofcopyToAsync(com.jme.opencl.CommandQueue, com.jme.opencl.Buffer, long)
, setssize
tothis.getSize()
.
-
map
public abstract java.nio.ByteBuffer map(CommandQueue queue, long size, long offset, MappingAccess access)
Maps this buffer directly into host memory. This might be the fastest method to access the contents of the buffer since the OpenCL implementation directly provides the memory.
Important: The mapped memory MUST be released by callingunmap(com.jme.opencl.CommandQueue, java.nio.ByteBuffer)
.- Parameters:
queue
- the command queuesize
- the size in bytes to mapoffset
- the offset into this bufferaccess
- specifies the possible access to the memory: READ_ONLY, WRITE_ONLY, READ_WRITE- Returns:
- the byte buffer directly reflecting the buffer contents
-
map
public java.nio.ByteBuffer map(CommandQueue queue, long size, MappingAccess access)
Alternative version ofmap(com.jme.opencl.CommandQueue, long, long, com.jme.opencl.MappingAccess)
, setsoffset
to zero. Important: The mapped memory MUST be released by callingunmap(com.jme.opencl.CommandQueue, java.nio.ByteBuffer)
.
-
map
public java.nio.ByteBuffer map(CommandQueue queue, MappingAccess access)
Alternative version ofmap(com.jme.opencl.CommandQueue, long, com.jme.opencl.MappingAccess)
, setssize
togetSize()
. Important: The mapped memory MUST be released by callingunmap(com.jme.opencl.CommandQueue, java.nio.ByteBuffer)
.
-
unmap
public abstract void unmap(CommandQueue queue, java.nio.ByteBuffer ptr)
Unmaps a previously mapped memory. This releases the native resources and for WRITE_ONLY or READ_WRITE access, the memory content is sent back to the GPU.- Parameters:
queue
- the command queueptr
- the buffer that was previously mapped
-
mapAsync
public abstract Buffer.AsyncMapping mapAsync(CommandQueue queue, long size, long offset, MappingAccess access)
Maps this buffer asynchronously into host memory. This might be the fastest method to access the contents of the buffer since the OpenCL implementation directly provides the memory.
Important: The mapped memory MUST be released by callingunmap(com.jme.opencl.CommandQueue, java.nio.ByteBuffer)
.- Parameters:
queue
- the command queuesize
- the size in bytes to mapoffset
- the offset into this bufferaccess
- specifies the possible access to the memory: READ_ONLY, WRITE_ONLY, READ_WRITE- Returns:
- the byte buffer directly reflecting the buffer contents and the event indicating when the buffer contents are available
-
mapAsync
public Buffer.AsyncMapping mapAsync(CommandQueue queue, long size, MappingAccess access)
Alternative version ofmapAsync(com.jme.opencl.CommandQueue, long, long, com.jme.opencl.MappingAccess)
, setsoffset
to zero. Important: The mapped memory MUST be released by callingunmap(com.jme.opencl.CommandQueue, java.nio.ByteBuffer)
.
-
mapAsync
public Buffer.AsyncMapping mapAsync(CommandQueue queue, MappingAccess access)
Alternative version ofmapAsync(com.jme.opencl.CommandQueue, long, com.jme.opencl.MappingAccess)
, setssize
togetSize()
. Important: The mapped memory MUST be released by callingunmap(com.jme.opencl.CommandQueue, java.nio.ByteBuffer)
.
-
fillAsync
public abstract Event fillAsync(CommandQueue queue, java.nio.ByteBuffer pattern, long size, long offset)
Enqueues a fill operation. This method can be used to initialize or clear a buffer with a certain value.- Parameters:
queue
- the command queuepattern
- the buffer containing the filling pattern. The remaining bytes specify the pattern lengthsize
- the size in bytes to fill, must be a multiple of the pattern lengthoffset
- the offset in bytes into the buffer, must be a multiple of the pattern length- Returns:
- an event indicating when this operation is finished
-
copyToImageAsync
public abstract Event copyToImageAsync(CommandQueue queue, Image dest, long srcOffset, long[] destOrigin, long[] destRegion)
Copies this buffer to the specified image. Note that no format conversion is done.
For detailed description of the origin and region paramenter, see the documentation of theImage
class.- Parameters:
queue
- the command queuedest
- the target imagesrcOffset
- the offset in bytes into this bufferdestOrigin
- the origin of the copied areadestRegion
- the size of the copied area- Returns:
- the event object
-
acquireBufferForSharingAsync
public abstract Event acquireBufferForSharingAsync(CommandQueue queue)
Aquires this buffer object for using. Only call this method if this buffer represents a shared object from OpenGL, created with e.g.Context.bindVertexBuffer(com.jme.scene.VertexBuffer, com.jme.opencl.MemoryAccess)
. This method must be called before the buffer is used. After the work is done, the buffer must be released by callingreleaseBufferForSharingAsync(com.jme.opencl.CommandQueue)
so that OpenGL can use the VertexBuffer again.- Parameters:
queue
- the command queue- Returns:
- the event object
-
acquireBufferForSharingNoEvent
public void acquireBufferForSharingNoEvent(CommandQueue queue)
Aquires this buffer object for using. Only call this method if this buffer represents a shared object from OpenGL, created with e.g.Context.bindVertexBuffer(com.jme.scene.VertexBuffer, com.jme.opencl.MemoryAccess)
. This method must be called before the buffer is used. After the work is done, the buffer must be released by callingreleaseBufferForSharingAsync(com.jme.opencl.CommandQueue)
so that OpenGL can use the VertexBuffer again. The generated event object is directly released. This brings a performance improvement when the resource is e.g. directly used by a kernel afterwards on the same queue (this implicitly waits for this action). If you need the event, useacquireBufferForSharingAsync(com.jme.opencl.CommandQueue)
instead.- Parameters:
queue
- the command queue
-
releaseBufferForSharingAsync
public abstract Event releaseBufferForSharingAsync(CommandQueue queue)
Releases a shared buffer object. Call this method after the buffer object was acquired byacquireBufferForSharingAsync(com.jme.opencl.CommandQueue)
to hand the control back to OpenGL.- Parameters:
queue
- the command queue- Returns:
- the event object
-
releaseBufferForSharingNoEvent
public void releaseBufferForSharingNoEvent(CommandQueue queue)
Releases a shared buffer object. Call this method after the buffer object was acquired byacquireBufferForSharingAsync(com.jme.opencl.CommandQueue)
to hand the control back to OpenGL. The generated event object is directly released, resulting in performance improvements.- Parameters:
queue
- the command queue
-
toString
public java.lang.String toString()
- Overrides:
toString
in classjava.lang.Object
-
-


Starting DOM
Here it goes the result!
Learning to use
DOM(Document Object Model)
in JavaScript!
Click me!


{{ define "title" }}{{ .Title }} - {{ end }} {{ define "main" }}
You are looking for articles could not be found.


{{define "content"}}
Are you sure you want to delete the job "{{.CronJob.Name}}", schedule to run with schedule "{{.CronJob.Schedule}}"? This cannot be undone.
Delete


Version Number:
<IP_ADDRESS>
Discord Shell is currently in Alpha!
none
https://www.dropbox.com/sh/zobq5mfh4jciczf/AACkM4rXbvMWT-H-KM9jWz84a?dl=0
This is the update info!


GWP discount climate rate damage timescale damages emissions temperature time analysis effects pulse use GDP change rates used consistent forcing years radiative -year future ratio different emission {border-style gas gases range global impacts px;} #ffffff;} growth metric metrics mitigation potential sensitivity Change, approach effect given greenhouse impact present IPCC equivalent relative results Fuglestvedt horizon net value Environ. appropriate based discounted policy (interquartile Climatic However, account analyses calculate calculated constant economic higher increase methane paper Sarofim calculation carbon choice framework implied similar warming Climate Figure Lett, Res. Shine Table choices function inclusion presented short-lived timescales year Allen available experiment gases, implications implicit long-term low lower pulses px; resulting stabilization uncertainty {font-family (e.g., August Earth GHG access: assuming change, considered evaluating font-size gases. high integrated near-term options period regarding scenarios using years. %). Clim. Global Sci. Shindell Smith USA, absolute analysis. approaches at: baseline calculations climate–carbon collab: compared concentrations decay double; estimated evaluated example, factor larger lifetime metrics, model optimal parameters peak perturbation scenario shows standard suggest (), ./-/// Boucher GWP, Gasser Myhre Nat. Reisinger Science, additional assessment atmospheric border-color border-width central changes consider contrast, costs decrease derived described does estimate evaluate exponent feedbacks forcing, important involved justifications large lead marginal mass measure median non-CO number order rate, rate-of-change ratios relationship response role single solid; solution target timescale. trading truncated van years, {font-style {font-weight (the Acad. Assessment Bowerman Change DICE Deuber Econ. Economic Edwards Howarth Johansson Manne National Natl. Nature, Nordhaus Ocko Radiative Sensitivity Syst. Temperature Zickfeld alternative analysis, anthropogenic applied apply article assumption assumptions background bold case comparing comparison concentration courier; current damages, damages. designed doubling em; end equations equivalency estimates exponents factors focus growth, horizon, include initial insensitive interquartile key lifetimes little long methodology paper, papers parameter possible previous pt;} quantitative reduce reductions sensitivities shown table terms threshold tipping trade-offs uncertainties values


{% extends "about.html" %} {% block entry %}
Goal Text - The most important option to get correct, as it will define when an exploit string is deemed as working. Case is ignored. Examples: If you are attempting to bypass a login form, perhaps “Login Successful.” For command injection, an indicative server response like “Directory of.” For SQL injection, maybe “row in set.”
Previous page Next page {% endblock %}


Hi, my name is Andrew Aquino.
I am a seasoned and passionate developer. I have worked on over several apps in my career, two of which are live. I am a student at heart, forever learning and increasing my craftsmanship. I have chops in both UX and product management. I am experienced in leading and/or working with colleagues to execute the developmental cycle of mobile applications, as well as software architecture, product planning, ideation, execution, analysis, and iteration. I take into account the overall needs of the business, stakeholders, and of our users in my decisions.
On my spare time, I like to create frameworks that (to the best of my abilities!) make developing easy for everybody. My first one is Atlantis, a logging framework, made for XCode written in Swift. My second one, Whirlpool, is a lightweight iOS chat framework. There are many others in my GitHub. I also made my own Node.JS server that’s being used by many of the production apps I’ve worked with.
Other things about me: I love hiking, camping, going to festivals, listening to music, fitness, watching movies, grabbing a couple mulitas at Gus' Lunchbox, meeting new people, hanging out with friends, and bettering myself as a person!
Please email me for more info.
<EMAIL_ADDRESS>Link to resume


Malpedia BlocksDB Result
Home
About
Statistics
Contact
Input:
file:
{{file_name}}
sha256:
{{sha256}}
bitness:
{{bitness}}
extracted:
{{extracted}} block hashes with {{block_b}} bytes.
Not matched: {{unmatched}} blocks with {{unmatch_sc}} bytes.
{{out_html|safe}}


Random Quiz
Start!
Timer
80
Score
Enter your initials to scare your high score:
Save score!
High Scores:


Hydra Tutor
Filter
Hydra User Reference
Enter Hydra Input and Filter
Input
Library
(
clear
)
Run
Reset
Examples
Stash
Filter
(type:
autodetect
bundle
value
closeable bundle
Output
Messages


hello
City:
Units:(metric, imperial, default)
This is where the results will be shown.
Desciption:
Current Temperature:
Max Temperature:
Min Temperature:


Distrafflicor Options
Do NOT block or time the following sites:
Browsing Time:
minutes
Break Time:
minutes


28 pilgrims hurt in road accident at Kanjirappally
by Special CorrespondentAs many as 28 pilgrims were injured when two buses collided at Kanjirappally on the Kottayam-Kumili Road on Sunday afternoon.
The Safe Zone patrol team of the Motor Vehicle Department rushed to the spot.
The patrol team had shifted 19 injured pilgrims to the Government Medical College Hospital in Kottayam.
First-aid given
All the other injured were given first-aid at various hospitals in Kanjirappally, according to P.D. Sunilbabu, safe zone nodal officer.
One of the buses was returning to Puducherry from Nilackal and the other one was taking Sabarimala Ayyappa pilgrims to Pampa, Mr. Sunilbabu added.


METROPOLITAN A film review by Steve Rhodes Copyright 1998 Steve Rhodes
RATING (0 TO ****): ***
Writer and director Whit Stillman, who manages to raise shallowness among rich, white kids to an art form, started the first of his famous trilogy in 1990 with METROPOLITAN. In his first film the kids refer to themselves, derogatorily, as preppies, but by the last picture, THE LAST DAYS OF DISCO, they have been rechristened yuppies, even if none of them will admit to being one. (For the record, the middle picture is BARCELONA, and my personal favorite is THE LAST DAYS OF DISCO.)
Stillman films, with their acerbic humor, are perhaps best on the second and third viewing. With their rapid-fire approach and their subtle dialog, it is easy to miss many of the lines the first time around. Subsequent looks are also helpful since one of the failings of Stillman's casting and his costuming is that most of the actors look alike and, to a lesser extent, so do the actresses. It may be halfway through before the audience learns to tell them all apart.
METROPOLITAN, we are told in the credits, is set in "Manhattan. Xmas Vacation. Not so long ago." A dilettante group of debutantes and their collective beaus are meeting for one of the many private parties during the social season. After the official balls, they gather to make small talk about large issues and generally gossip among themselves. They argue the fine points of 19th century socialism, while living a life of absolute luxury. They are all elitists, united in their agreement that they hate pretentious people and that they certainly aren't ones themselves.
Although they are cynical to varying degrees, none is more so than Nick Smith, played as the perfect rich snob by Christopher Eigeman, who has starred in all three of Stillman's films. While others worry about the possibility of failure, he plans on it, and, with his lack of ambition, it seems likely. "I've always planned to be a failure anyway, that's why I plan to marry an extremely wealthy woman," he announces to no one's surprise.
The odd man out is their resident radical, Tom Townsend (Edward Clements), who is the only one without independently wealthy parents and the only one in - aghast! - a rented tux. Tom, not very convincingly, goes on and on discussing his worries about the downtrodden in life, which upsets Nick.
Audrey Rouget (Carolyn Farina) has her eyes set on Tom, who pines instead for the extremely popular and unobtainable Serena Slocum (Ellia Thompson). Tom ridicules Audrey for liking Jane Austen's Mansfield Park. He points out that, even though he's never read it, it is universally agreed to be a mediocre book. "You don't have to read a book to have an opinion," he argues. He goes on to say that he doesn't read any novels but prefers to read literary criticism instead. "That way you get both the novelists' ideas as well as the critics' thinking," he reasons.
"Playing strip poker with an exhibitionist somehow takes the challenge out of it," Nick complains after one of the women throws a hand so she can take off another item of her clothing. As they slowly undress, they alternatively talk about trust funds and class struggles, but Stillman cuts away before the scene gets the least bit risque.
Using dreamy jazz music in the scene transitions, Stillman makes the story go down as smoothly as a white wine. His characters may get on your nerves sometimes, but he remains hopelessly in love with them and all of their foibles. Like all his movies, METROPOLITAN has the stagy talkiness of a play, but a fascinating one.
The story's only serious scene occurs when the group plays a game of truth, in which the loser must answer any question, no matter how embarrassing. "People see the harm in what excessive candor can do," Audrey argues correctly, knowing that someone could get hurt and that that someone could be her.
When one of their ranks, Jane Clark (Allison Parisi), dares to go out on a date alone, the rest are dumbstruck. Used to nothing but group social activities, they worry that their lifestyles are changing forever.
As in THE LAST DAYS OF DISCO, in which the leads lament disco's demise, the characters in METROPOLITAN figure that this may be the last season for debutante balls and the end of an era. "Men are dates, date substitutes or potential dates," Fred Neff (Bryan Leder) complains of their new world order. "I find that dehumanizing."
METROPOLITAN runs 1:38. It is rated PG-13 for some profanity and for adult themes, and it would be fine for teenagers.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Welcome to RoboTest
Test for robot control with ICE
Control buttons
Move Up
Move Down
Move Left
Move Right
Send speech
Send


Descripcion
Simple code is worthless without an elegant design to match it's simplicity. A readable code is beautiful but it becomes elegant when the design matches to a pixel perfect aligned custom built grid.
Simple code is worthless without an elegant design to match it's simplicity. A readable code is beautiful but it becomes elegant when the design matches to a pixel perfect aligned custom built grid.


|
Assimp
5.0.1, master @ cd42b955
|
Parses the block structure of MD5MESH and MD5ANIM files (but does no further processing) More...
Public Member Functions | |
| MD5Parser (char *buffer, unsigned int fileSize) | |
| Constructs a new MD5Parser instance from an existing buffer. More... | |
| void | ReportError (const char *error) |
| void | ReportWarning (const char *warn) |
Static Public Member Functions | |
| static AI_WONT_RETURN void | ReportError (const char *error, unsigned int line) AI_WONT_RETURN_SUFFIX |
| Report a specific error message and throw an exception. More... | |
| static void | ReportWarning (const char *warn, unsigned int line) |
| Report a specific warning. More... | |
Public Attributes | |
| SectionList | mSections |
| List of all sections which have been read. More... | |
Private Member Functions | |
| void | ParseHeader () |
| Parses the file header. More... | |
| bool | ParseSection (Section &out) |
| Parses a file section. More... | |
| bool | SkipLine () |
| bool | SkipLine (const char *in, const char **out) |
| bool | SkipSpaces () |
| bool | SkipSpacesAndLineEnd () |
| bool | SkipSpacesAndLineEnd (const char *in, const char **out) |
Private Attributes | |
| char * | buffer |
| unsigned int | fileSize |
| unsigned int | lineNumber |
Parses the block structure of MD5MESH and MD5ANIM files (but does no further processing)
| MD5Parser::MD5Parser | ( | char * | buffer, |
| unsigned int | fileSize | ||
| ) |
Constructs a new MD5Parser instance from an existing buffer.
| buffer | File buffer |
| fileSize | Length of the file in bytes (excluding a terminal 0) |
|
private |
Parses the file header.
| ImportErrorException | if an error occurs |
|
private |
Parses a file section.
The current file pointer must be outside of a section.
| out | Receives the section data |
| ImportErrorException | if an error occurs |
|
inline |
|
static |
Report a specific error message and throw an exception.
| error | Error message to be reported |
| line | Index of the line where the error occurred |
|
inline |
|
static |
Report a specific warning.
| warn | Warn message to be reported |
| line | Index of the line where the error occurred |
|
inlineprivate |
|
inlineprivate |
|
inlineprivate |
|
inlineprivate |
|
inlineprivate |
|
private |
|
private |
|
private |
| SectionList Assimp::MD5::MD5Parser::mSections |
List of all sections which have been read.


AUC
Computes the approximate AUC (Area under the curve) via a Riemann sum.
Inherits From: Metric
tf.compat.v1.keras.metrics.AUC
tf.compat.v2.keras.metrics.AUC
tf.compat.v2.metrics.AUC
tf.metrics.AUC
This metric creates four local variables, true_positives
, true_negatives
,
false_positives
and false_negatives
that are used to compute the AUC.
To discretize the AUC curve, a linearly spaced set of thresholds is used to
compute pairs of recall and precision values. The area under the ROC-curve is
therefore computed using the height of the recall values by the false positive
rate, while the area under the PR-curve is the computed using the height of
the precision values by the recall.
This value is ultimately returned as auc
, an idempotent operation that
computes the area under a discretized curve of precision versus recall values
(computed using the aforementioned variables). The num_thresholds
variable
controls the degree of discretization with larger numbers of thresholds more
closely approximating the true AUC. The quality of the approximation may vary
dramatically depending on num_thresholds
. The thresholds
parameter can be
used to manually specify thresholds which split the predictions more evenly.
For best results, predictions
should be distributed approximately uniformly
in the range [0, 1] and not peaked around 0 or 1. The quality of the AUC
approximation may be poor if this is not the case. Setting summation_method
to 'minoring' or 'majoring' can help quantify the error in the approximation
by providing lower or upper bound estimate of the AUC.
If sample_weight
is None
, weights default to 1.
Use sample_weight
of 0 to mask values.
m = tf.keras.metrics.AUC(num_thresholds=3) m.update_state([0, 0, 1, 1], [0, 0.5, 0.3, 0.9]) # threshold values are [0 - 1e-7, 0.5, 1 + 1e-7] # tp = [2, 1, 0], fp = [2, 0, 0], fn = [0, 1, 2], tn = [0, 2, 2] # recall = [1, 0.5, 0], fp_rate = [1, 0, 0] # auc = ((((1+0.5)/2)*(1-0))+ (((0.5+0)/2)*(0-0))) = 0.75 print('Final result: ', m.result().numpy()) # Final result: 0.75
Usage with tf.keras API:
model = tf.keras.Model(inputs, outputs) model.compile('sgd', loss='mse', metrics=[tf.keras.metrics.AUC()])
__init__
__init__( num_thresholds=200, curve='ROC', summation_method='interpolation', name=None, dtype=None, thresholds=None )
Creates an AUC
instance.
num_thresholds
: (Optional) Defaults to 200. The number of thresholds to
use when discretizing the roc curve. Values must be > 1.curve
: (Optional) Specifies the name of the curve to be computed, 'ROC'
[default] or 'PR' for the Precision-Recall-curve.summation_method
: (Optional) Specifies the Riemann summation method used
(https://en.wikipedia.org/wiki/Riemann_sum): 'interpolation' [default],
applies mid-point summation scheme for ROC
. For PR-AUC, interpolates
(true/false) positives but not the ratio that is precision (see Davis
& Goadrich 2006 for details); 'minoring' that applies left summation
for increasing intervals and right summation for decreasing intervals;
'majoring' that does the opposite.name
: (Optional) string name of the metric instance.dtype
: (Optional) data type of the metric result.thresholds
: (Optional) A list of floating point values to use as the
thresholds for discretizing the curve. If set, the num_thresholds
parameter is ignored. Values should be in [0, 1]. Endpoint thresholds
equal to {-epsilon, 1+epsilon} for a small positive epsilon value will
be automatically included with these to correctly handle predictions
equal to exactly 0 or 1.__new__
__new__( cls, *args, **kwargs )
Create and return a new object. See help(type) for accurate signature.
interpolate_pr_auc
interpolate_pr_auc()
Interpolation formula inspired by section 4 of Davis & Goadrich 2006.
https://www.biostat.wisc.edu/~page/rocpr.pdf
Note here we derive & use a closed formula not present in the paper as follows:
Precision = TP / (TP + FP) = TP / P
Modeling all of TP (true positive), FP (false positive) and their sum P = TP + FP (predicted positive) as varying linearly within each interval [A, B] between successive thresholds, we get
Precision slope = dTP / dP = (TP_B - TP_A) / (P_B - P_A) = (TP - TP_A) / (P - P_A) Precision = (TP_A + slope * (P - P_A)) / P
The area within the interval is (slope / total_pos_weight) times
int_A^B{Precision.dP} = int_A^B{(TP_A + slope * (P - P_A)) * dP / P} int_A^B{Precision.dP} = int_A^B{slope * dP + intercept * dP / P}
where intercept = TP_A - slope * P_A = TP_B - slope * P_B, resulting in
int_A^B{Precision.dP} = TP_B - TP_A + intercept * log(P_B / P_A)
Bringing back the factor (slope / total_pos_weight) we'd put aside, we get
slope * [dTP + intercept * log(P_B / P_A)] / total_pos_weight
where dTP == TP_B - TP_A.
Note that when P_A == 0 the above calculation simplifies into
int_A^B{Precision.dTP} = int_A^B{slope * dTP} = slope * (TP_B - TP_A)
which is really equivalent to imputing constant precision throughout the first bucket having >0 true positives.
pr_auc
: an approximation of the area under the P-R curve.reset_states
reset_states()
Resets all of the metric state variables.
This function is called between epochs/steps, when a metric is evaluated during training.
result
result()
Computes and returns the metric value tensor.
Result computation is an idempotent operation that simply calculates the metric value using the state variables.
update_state
update_state( y_true, y_pred, sample_weight=None )
Accumulates confusion matrix statistics.
y_true
: The ground truth values.y_pred
: The predicted values.sample_weight
: Optional weighting of each example. Defaults to 1. Can be a
Tensor
whose rank is either 0, or the same rank as y_true
, and must
be broadcastable to y_true
.Update op.


Google Maps’ upcoming Local Guides feature turns it into a social network
by Shereesa MoodleyFollowing the recent update to public profiles on Google Maps, Google on Friday announced a new Local Guides feature that will help users follow people and discover new locations on the platform.
“People in Bangkok, Delhi, London, Mexico City, New York, Osaka, San Francisco, São Paulo and Tokyo will soon see top Local Guides featured in the For You tab of the Google Maps app,” the company explained on its website.
With the new feature, users will be able to follow Google’s Local Guides to receive the latest updates about activities available around them.
“When you follow one of these Local Guides, their recommendations will be surfaced to you in Google Maps, so you can get inspired with ideas of things to do and places to go,” Google explained.
Together with public profile management, the new feature suggests that Google Maps will soon become more of a social platform than a simple navigation tool.
Feature image: Google


this content will be overwritten by the included content.
this content is shown because there was a 404this content is shown because there was a 500.


Some of this is old stuff, but more people are now converting to InnoDB plugin, so as to enjoy table compression, performance boosts. Same holds for people converting to Percona's XtraDB. InnoDB plugin requires innodb_file_per_table. No more shared tablespace file.
So your ibdata1 file is some 150GB, and it won't reduce. Really, it won't reduce. You set innodb_file_per_table=1, do ALTER TABLE t ENGINE=InnoDB (optionally ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8), and you get all your tables in file-per-table .ibd files.
But the original ibdata1 file is still there. It has to be there, don't delete it! It contains more than your old data.
InnoDB tablespace files never reduce in size, it's an old-time annoyance. The only way to go round it, if you need the space, is to completely drop them and start afresh. That's one of the things so nice about file-per-table: an ALTER TABLE actually creates a new tablespace file and drops the original one.
The procedure
The procedure is somewhat painful:
- Dump everything logically (either use mysqldump, mk-parallel-dump, or do it your own way)
- Erase your data (literally, delete everything under your datadir)
- Generate a new empty database
- Load your dumped data.
Using replication
Replication makes this less painful. Set up a slave, have it follow up on the master.
- Stop your slave.
- Make sure to backup the replication position (e.g. write SHOW SLAVE STATUS on a safe location, or copy master.info file).
- Work out the dump-erase-generate-load steps on the slave.
- Reattach the slave to the master using saved data.
For this to succeed you must keep enough binary logs on the master for the entire dump-load period, which could be lengthy.
Upgrading to barracuda
If you wish to upgrade your InnoDB tables to Barracuda format, my advice is this:
- Follow the steps above to generate a file-per-table working slave
- Stop the slave
- Configure skip_slave_start
- Restart MySQL
- One by one do the ALTER TABLE into Barracuda format (ROW_FORMAT=COMPACT or ROW_FORMAT=COMPRESSED)
Note that if you're about to do table compression, the ALTER statements become considerably slower the better the compression is.
If your dataset is very large, and you can't keep so many binary logs, you may wish to break step 5 above into:
- ALTER a large table
- Restart MySQL
- Start slave, wait for it to catch up
- Restart MySQL again
and do the same for all large tables.
Why all these restarts?
I've been upgrading to Barracuda for a long time now. I have clearly noticed that ALTER into a COMPRESSED format works considerably slower after the slave has done some "real work". This in particular relates to the last "renaming table" stage. There was a bug with earlier InnoDB plugin versions which made this stage hang. It was solved. But it still takes some time for this last, weird stage, where the new replacement table is complete, and it's actually been renamed in place of the old table, and the old table renamed into something like "#sql-12345.ibd", and all that needs to be done is have it dropped, and... Well, it takes time.
My observation is it works faster on a freshly started server. Which is why I take the bother to restart MySQL before each large table conversion.
comments powered by Disqus


Obviously had to do something geeky!
Now where have I seen that tree before? Scroll down through the memories there may be something at the bottom of that tree...
So Jo, what's the story....
3 years, 2 kids, I think we should complete this family don't you?
Will you do me the honour of becoming my wife?


o != arg0
is the same as !(o == (arg0))
.
o != arg0
is the same as !(o == (arg0))
.
the object to compare against this object for dis-equality.
false
if the receiver object is equivalent to the argument; true
otherwise.
o == arg0
is the same as if (o eq null) arg0 eq null else o.equals(arg0)
.
o == arg0
is the same as if (o eq null) arg0 eq null else o.equals(arg0)
.
the object to compare against this object for equality.
true
if the receiver object is equivalent to the argument; false
otherwise.
o == arg0
is the same as o.equals(arg0)
.
o == arg0
is the same as o.equals(arg0)
.
the object to compare against this object for equality.
true
if the receiver object is equivalent to the argument; false
otherwise.
see corresponding Javadoc for more information.
This method is used to cast the receiver object to be of type T0
.
This method is used to cast the receiver object to be of type T0
.
Note that the success of a cast at runtime is modulo Scala's erasure semantics. Therefore the expression1.asInstanceOf[String]
will throw a ClassCastException
at runtime, while the expressionList(1).asInstanceOf[List[String]]
will not. In the latter example, because the type argument is erased as
part of compilation it is not possible to check whether the contents of the list are of the requested typed.
the receiver object.
see corresponding Javadoc for more information.
This method creates and returns a copy of the receiver object.
This method creates and returns a copy of the receiver object.
The default implementation of the clone
method is platform dependent.
a copy of the receiver object.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
This method is used to test whether the argument (arg0
) is a reference to the
receiver object (this
).
This method is used to test whether the argument (arg0
) is a reference to the
receiver object (this
).
The eq
method implements an [http://en.wikipedia.org/wiki/Equivalence_relation equivalence relation] on
non-null instances of AnyRef
:
* It is reflexive: for any non-null instance x
of type AnyRef
, x.eq(x)
returns true
.
* It is symmetric: for any non-null instances x
and y
of type AnyRef
, x.eq(y)
returns true
if and
only if y.eq(x)
returns true
.
* It is transitive: for any non-null instances x
, y
, and z
of type AnyRef
if x.eq(y)
returns true
and y.eq(z)
returns true
, then x.eq(z)
returns true
.
Additionally, the eq
method has three other properties.
* It is consistent: for any non-null instances x
and y
of type AnyRef
, multiple invocations of
x.eq(y)
consistently returns true
or consistently returns false
.
* For any non-null instance x
of type AnyRef
, x.eq(null)
and null.eq(x)
returns false
.
* null.eq(null)
returns true
.
When overriding the equals
or hashCode
methods, it is important to ensure that their behavior is
consistent with reference equality. Therefore, if two objects are references to each other (o1 eq o2
), they
should be equal to each other (o1 == o2
) and they should hash to the same value (o1.hashCode == o2.hashCode
).
the object to compare against this object for reference equality.
true
if the argument is a reference to the receiver object; false
otherwise.
This method is used to compare the receiver object (this
) with the argument object (arg0
) for equivalence.
This method is used to compare the receiver object (this
) with the argument object (arg0
) for equivalence.
The default implementations of this method is an [http://en.wikipedia.org/wiki/Equivalence_relation equivalence
relation]:
* It is reflexive: for any instance x
of type Any
, x.equals(x)
should return true
.
* It is symmetric: for any instances x
and y
of type Any
, x.equals(y)
should return true
if and
only if y.equals(x)
returns true
.
* It is transitive: for any instances x
, y
, and z
of type AnyRef
if x.equals(y)
returns true
and
y.equals(z)
returns true
, then x.equals(z)
should return true
.
If you override this method, you should verify that your implementation remains an equivalence relation.
Additionally, when overriding this method it is often necessary to override hashCode
to ensure that objects
that are "equal" (o1.equals(o2)
returns true
) hash to the same
scala.Int
(o1.hashCode.equals(o2.hashCode)
).
the object to compare against this object for equality.
true
if the receiver object is equivalent to the argument; false
otherwise.
This method is called by the garbage collector on the receiver object when garbage collection determines that there are no more references to the object.
This method is called by the garbage collector on the receiver object when garbage collection determines that there are no more references to the object.
The details of when and if the finalize
method are invoked, as well as the interaction between finalize
and non-local returns and exceptions, are all platform dependent.
Returns a representation that corresponds to the dynamic class of the receiver object.
Returns a representation that corresponds to the dynamic class of the receiver object.
The nature of the representation is platform dependent.
a representation that corresponds to the dynamic class of the receiver object.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
Returns a hash code value for the object.
Returns a hash code value for the object.
The default hashing algorithm is platform dependent.
Note that it is allowed for two objects to have identical hash codes (o1.hashCode.equals(o2.hashCode)
) yet
not be equal (o1.equals(o2)
returns false
). A degenerate implementation could always return 0
.
However, it is required that if two objects are equal (o1.equals(o2)
returns true
) that they have
identical hash codes (o1.hashCode.equals(o2.hashCode)
). Therefore, when overriding this method, be sure
to verify that the behavior is consistent with the equals
method.
the hash code value for the object.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
This method is used to test whether the dynamic type of the receiver object is T0
.
This method is used to test whether the dynamic type of the receiver object is T0
.
Note that the test result of the test is modulo Scala's erasure semantics. Therefore the expression1.isInstanceOf[String]
will return false
, while the expression List(1).isInstanceOf[List[String]]
will
return true
. In the latter example, because the type argument is erased as part of compilation it is not
possible to check whether the contents of the list are of the requested typed.
true
if the receiver object is an instance of erasure of type T0
; false
otherwise.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
o.ne(arg0)
is the same as !(o.eq(arg0))
.
o.ne(arg0)
is the same as !(o.eq(arg0))
.
the object to compare against this object for reference dis-equality.
false
if the argument is not a reference to the receiver object; true
otherwise.
see corresponding Javadoc for more information.
Wakes up a single thread that is waiting on the receiver object's monitor.
Wakes up a single thread that is waiting on the receiver object's monitor.
Wakes up all threads that are waiting on the receiver object's monitor.
Wakes up all threads that are waiting on the receiver object's monitor.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
see corresponding Javadoc for more information.
Returns a string representation of the object.
Returns a string representation of the object.
The default representation is platform dependent.
a string representation of the object.
Clients should implement the ui field. See the
SimpleApplet
demo for an example.Note:
Applet
extendsjavax.swing.JApplet
to satisfy Java's applet loading mechanism. The usual component wrapping scheme doesn't work here.see also:
javax.swing.JApplet


--- layout: post title: 'Orange unveils new ''Calling Tunes'' service' date: 2006-01-10 00:00:00 categories: digital-media interfaces-&-interaction mobile ---
Via Devi, Orange unveils new 'Calling Tunes' service: "Calling Tunes, as it's known, lets Orange punters choose music to play callers while they wait for the phone to be answered."


Wraps MS LogParser in an Ant Task and provides specific FusionReactor log parsing and reporting capabilities.
Supported output formats include XML,HTML, and CSV.
Example usage:
| Attribute | Description | Required | Default |
| logparser | Full path to the LogParser executable | Yes | |
| logdir | Path to the directory containing FusionReactor log files | Yes | |
| outputdir | A directory in which to save results. | No | xant-temp |
| format | XML,HTML,or CSV | No Note That by specifying HTML, XML files will also be generated and saved. |
HTML |
| maxrows | How many rows to process. | No | 1000 |
| id | User-defined ID for the output results. Formats: frantic-jdbc-id.format frantic-request-id.format frantic-crash-id.format frantic-resource-id.format |
No | System generated UUID |
| type | The type of report to generate: request, crash, jdbc, resource, or all. Defaults to all. | No | ALL |
| title | The title printed in the html and xml outputs. | No | FusionReactor Logfile Report |
| filter | Constraints used to control which data is processed. This is the "Where" clause. | No | |
| columnlist | Comma-delimited list of columns from which to select. | No | * |
| sort | Comma-delimited list of columns by which to sort. | Note: Each sorted column must be present in the select list. | date,time |
Generate CSVs of the most recent 1000 items in each FusionReactor LogFile into xant-temp
Changing the format
attribute to html will generate the same data
but will generate html and xml.
Print the 100 slowest requests to html.