|
| static void | errorMessage (const QString &text, const QString &informativeText) |
| | Creates a dialog and displayed it as a modal dialog. The dialog shown is an error dialog. More...
|
| |
| static int | warningMessage (const QString &text, const QString &informativeText) |
| | Creates a dialog and displayed it as a modal dialog. The dialog is a warning dialog. and only has to possible responses: Yes or No. More...
|
| |
| static void | informativeMessage (const QString &text, const QString &informativeText) |
| | Creates a dialog and displayed it as a modal dialog. The dialog shown is an informative dialog. More...
|
| |
| static bool | appendFile (const QString &path, const QString &text) |
| | Appends a text on a file. More...
|
| |
| static bool | writeFile (const QString &path, const QString &text) |
| | Write a text on a file. More...
|
| |
| static QByteArray | readAllFile (const QString &path) |
| | Read completely the file received by parameter. More...
|
| |
| static int | executeProgram (const QString &program, const QStringList &arguments=QStringList(), const QString &standardOutput=QProcess::nullDevice(), const QString &workingDirectory=QString(), const int timeout=-1) |
| | Executes binary program. More...
|
| |
| static QString | zipCompressDirectoryContents (const QString &directory, const QString &zipDestination, const QString &zipName="compressed") |
| | Compresses all files and folders in the directory received by argument. More...
|
| |
| static QFuture< void > | startProgressDialogCounter (QProgressDialog *dialog, bool *hasFinished, int timeout=40) |
| | Simulates a progress on a QProgressDialog. More...
|
| |
| static bool | isValidIp (const QString &ip) |
| | Returns true if is a valid ip, otherwise returns false. More...
|
| |
| static QString | getDateTime (QString format="yyyy_MM_dd_hh_mm_ss") |
| | Returns a current date time with the format received by parameter. More...
|
| |
| static QString | getTmpDirectory () |
| | Returns a temporal directory of system. More...
|
| |
| static QString | formatText (const QString &text, QList< TextModifier > modifiers) |
| | Returns a text applying mofifiers to be used in terminal. More...
|
| |
This is static class with a lot of different utilities.
Definition at line 25 of file utils.h.
| void Utils::errorMessage |
( |
const QString & |
text, |
|
|
const QString & |
informativeText |
|
) |
| |
|
static |
Creates a dialog and displayed it as a modal dialog. The dialog shown is an error dialog.
The user only can accept the dialog.
The function is designed to display error messages to the user without the option of choosing anything.
- Parameters
-
| text | Message text to be displayed. |
| informativeText | Informative text that provides a fuller description for the message. |
Definition at line 18 of file utils.cpp.
| int Utils::executeProgram |
( |
const QString & |
program, |
|
|
const QStringList & |
arguments = QStringList() , |
|
|
const QString & |
standardOutput = QProcess::nullDevice() , |
|
|
const QString & |
workingDirectory = QString() , |
|
|
const int |
timeout = -1 |
|
) |
| |
|
static |
Executes binary program.
Returns the code error returned by the execution.
If an empty standard output file is received, standard output is not saved.
If an empty working directory is received, the process is executed in current directory.
A timeout equals to -1 indicates that process has not limit time.
Some known code errors: -> 255: binary file not found or can't be executed. -> -1: binary file crashed during the execution.
- Parameters
-
| program | Name of binary file. |
| arguments | Arguments of the program. |
| standardOutput | File path where process standard output will be saved. |
| workDirectory | Directory where the program must work. |
| timeout | Execution timeout of the program. |
- Returns
- Code error of the execution
Definition at line 105 of file utils.cpp.
| QFuture< void > Utils::startProgressDialogCounter |
( |
QProgressDialog * |
dialog, |
|
|
bool * |
hasFinished, |
|
|
int |
timeout = 40 |
|
) |
| |
|
static |
Simulates a progress on a QProgressDialog.
Counter only finish when hasFinished is true, otherwise progress count stop in 99%. As the counter is created in other thread, out of function you have to make sure that thread finished calling function QFuture::waitForFinished(). If you don't make sure of it, your program probably will finish unexpectedly with an error.
Returns a QFuture object for control the end of the thread.
- Parameters
-
| dialog | Dialog where exec the counter. |
| hasFinished | Flag to finish the counter. |
| timeout | Time between each increase in the percentage of progress. |
- Returns
- QFuture object to know when the thread has finished.
Definition at line 145 of file utils.cpp.
| int Utils::warningMessage |
( |
const QString & |
text, |
|
|
const QString & |
informativeText |
|
) |
| |
|
static |
Creates a dialog and displayed it as a modal dialog. The dialog is a warning dialog. and only has to possible responses: Yes or No.
The dialog has only two buttons (Yes and No), which are the two possible options that the user can select. Returns the option selected by the user.
The function is designed to display warning messages to the user and whether he wants to take the risks.
- Parameters
-
| text | Message text to be displayed. |
| informativeText | Informative text that provides a fuller description for the message. |
- Returns
- User responser.
Definition at line 33 of file utils.cpp.


About Me
I am a Full Stack Developer based in Saint Paul, MN. I like helping others and solving problems. I have experience with: JavaScript, HTML, CSS, React, jQuery, MongoDB, MySQL, Stripe, and more! When I'm not coding, I enjoy rock climbing and hanging out with my cats.


{{summaryData.period}}
Savings Deposits:
{{summaryData.totalDeposits | currency:"PHP":2}}
Expense Wallets Budget:
{{summaryData.totalEWallets | currency:"PHP":2}}
Total Budget (In):
{{summaryData.totalBudget | currency:"PHP":2}}
Transactions:
{{summaryData.totalTransactions | currency:"PHP":2 }}
Withdrawals:
{{summaryData.totalWithdrawals | currency:"PHP":2 }}
Expenditures (Out):
summaryData.totalBudget ? 'danger':'carbon'"> {{summaryData.totalExpenses | currency:"PHP":2 }}
Total Savings:
summaryData.totalDeposits ? 'danger':'carbon'"> {{(summaryData.totalDeposits - summaryData.totalWithdrawals) | currency:"PHP":2 }}
Extra Savings:
{{summaryData.extraSavings | currency:"PHP":2 }}


Hydro Flow Map
Derived from 2,000 USGS stream gauges, this animation depicts the relative flow of water for the continental United States for the selected month.


Sorry, we could not verify account. It maybe already verified, or verification code is incorrect.
Sorry, we could not verify password. It maybe already verified, or verification code is incorrect.


Debugger page, Run or Debug dialog box
The Debugger page of the Run and Debug dialog boxes lets you select a debugger to use when debugging an application.
| Component | Description |
|---|---|
| Debugger | Selects debugger type from the list. |
| Stop on startup at | Stops program at specified location. |
| Advanced | Opens the Advanced Options dialog.
|
| Debugger Options | Displays options specific to the selected debugger type. |


---
title: "Contact Us"
permalink: /contact/
---
To join our future email distribution list, please fill out the Google form.
We typically make the announcements in major WeChat groups. Considering each WeChat group is limited to 500 people, we will still need to rely on emailing to reach out to community members and those who are interested to know what is happening in our community.
If you want to volunteer with us and you can read basic Chinese, please consider joining our volunteer WeChat group. We announce and organize all our volunteering opportunities in that group. Once you have installed WeChat application, add 西北兆 as your friend first (by searching WeChat ID: NW_Fan) and then you will be added into that group.
Mailing Address
Oregon Chinese Coalition
PO Box 1675
Beaverton, OR 97075
Also follow us on


High Priest Sylvain:
To become a Human Wizard, one who studies the fundamental power that underlies all things, your level must be at least 20, and you must also pass the Test of the Human Wizard.
Description of Human Wizard
Change profession to Human Wizard
Return


Jessica Lettes is a biology major and a computer science minor at UC San Diego. She does research on the evolution of exons between humans and mice. She interned at a genetic testing company this past summer and would love to work in industry after graduating in the Spring of 2016. Jessie's hobby is dance, and she is currently a cocaptain of the UCSD dance team. Go Tritons!


undaqTools is the the unofficial pythonic interface to the National Advanced Driving Simulator (NADS) Data AcQuisition (DAQ) files (i.e. NADS miniSim (TM) datafiles).
undaqTools converts the native DAQ data into the HDF5 high performance binary data format. From there data can be quickly accessed in Python using the Daq class of undaqTools. Daq objects are dict subclasses. The keys are the elements of the daq and the values are stored in a numpy array subclass called Element. Each Element contain measure relevent metadata stored as instance attributes so these metadata does not have to be accessed across datastructures.
Each Element object also has a frames attribute that keeps track of the frames cooresponding to the element. This means that when they are sliced the resulting views keeps the frames in sync without any additional book-keeping to the end user! The element data can also be sliced and indexed using frame indices. These abstractions simplify the complexity of managing these complex datasets (see class hierarchy diagram below).
undaqTools can also unpack and process dynamic objects. Each dynamic object becomes a DynObj instance in the Daq’s dynobj dict attribute. The keys to the dynamic objects are the dynamic object names. The DynObj containers store the measure that you would expect (position, frames, speed, heading, etc.) as numpy.array objects as well as a running relative distance measure to the Own Vehicle.
These abstractions from the original DAQ representation are intended to provide the end user the convenience and capability to decide how to best utilize their data.
Simplified Class Hierarchy Diagram:
Daq(dict)
+ [elemName] -> Element (ndarray)
| + data
| + frames (ndarray)
| + rate
| + type
| + ...
| --------------------
| + isCSSDC()
|
+ dynobjs (dict)
| + [doName] -> DynObj (object)
| + pos (Element)
| + heading (Element)
| + speed (Element)
| + ...
| ---------------------
| + process()
| + read_hd5()
| + write_hd5()
| + ...
|
+ info (numedTuple)
| + run
| + subject
| + date
| + ...
|
| + etc (dict)
| + ...
--------------------------------------------
| + read_daq() <==> read()
| + read_hd5py()
| + write_hd5py()
| + write_mat()
| ...
email me at<EMAIL_ADDRESS>or start a thread on gitHub.
Daq.read_daq() method based on Chris Schwarz and others of NADS convert_daq.py script.


$template{name="sample-readme-html-header" title="Node Tray demo"}$
What does the sample do?
This sample provides a node health monitor that sits in the system tray.
It displays the following information:
- A "computer" icon in the system tray, which turns green when the node is connected to a server, and red when it is disconnected
- System tray notifications when the node status changes
- Information about the node's performance and connection to a JPPF server, when the mouse is hovering over the icon
Here are some screenshots:
How do I run it?
Before running this sample application, you need to install a JPPF server and at least one node.
For information on how to set up a node and server, please refer to the JPPF documentation.
Once you have installed a server and node, perform the following steps:
- open a command prompt in JPPF-x.y-samples-pack/NodeTray
- important: to build this sample you need a JDK 1.6 or later, as the system tray APIs are not available in prior Java versions
- build the sample: type "ant jar" or simply "ant"; this will create a file named NodeTray.jar
- copy NodeTray.jar in the "lib" folder of the JPPF node installation, to add it to the node's classpath. This is enough to deploy the add-on.
- start the server and node
- you should see the new system tray icon
What features of JPPF are demonstrated?
I have additional questions and comments, where can I go?
If you need more insight into the code of this demo, you can consult the Java source files located in the CustomMBeans/src folder.
In addition, There are 2 privileged places you can go to:
$template{name="sample-readme-html-footer"}$


"A MusicRNN is an LSTM-based language model for musical notes -- it is best at continuing a NoteSequence that you give it."
"A MusicVAE is a variational autoencoder made up of an Encoder and Decoder -- you can think of the encoder as trying to summarize all the data you give it, and the decoder as trying to recreate the original data, based on this summarized version."


Warehouse Keeper Murdoc: Heh...allow me to welcome you to my warehouse! My guild is the largest and oldest of the Dwarven guilds: the *Steel Gate*! We have warehouses in every city across this continent! Ha! Through us, you can send your item to anyone, anywhere!


|
Create Pebble Apps in your Browser
Write and create Pebble apps inside of your web browser with no downloads required.
|
|
Create Pebble Apps in your Browser
Write and create Pebble apps inside of your web browser with no downloads required.
|


This is going back to the vision of Steem-Engine for a sec. The vision is to create a vibrant trading platform that empowers token creation and launch on top of the Steem blockchain.
Business owners and community leaders need a way to pool money so they can launch awesome buinesses and communities. To do that they need tokens, a trading platform, and a way to launch this stuff successfully.
Let’s Pretend that Steem-Engine.com is the Angel of Light for a second…
At level 1 Steem-Engine springs to life. She’s barely capable of much. She has so much promise and life, but her spells are weak, they are cast on weak monsters, and she doens’t seem to offer all that much. She can create tokens, and you can sell them on the exchange with a very basic UI.
She’s got a gnarly tendency to change block zero when updating versions, so it’s almost like she’s got some weird hump on her back too.
At level 2 she’s now getting a little armor and looking a bit more pimp and sure of herself. She’s releasing a new contract that allows tokens to be staked and this enables a whole new era of how businesses and communities can interact with the tokens. You can issue them, trade them, power them up, and (starting very soon) you can use proof of brain to distribute them.
By level 3 she’s kind of a beast. Don’t mess with this lady.  She’s now trading not only Steem and Steem-Engine tokens, but she’s got EOS/Tron/Eth/Bts and other systems all trading on top of the platform. She’s also now setup to launch ICOs/STOs with a platform like startengine.com or kickstarter.com. Because of all the various tokens and some of the tools to attract liquidity the website turns out to be a great place to trade.
 It turns out that trading fiat for tokens is hard, but it’s not that bad to get a broker dealer lisence and be able to trade securities. The site is now trading steem, steem-engine tokens, Bitcoin, Litecoin, Doge, BCH. It’s also trading other cryptos and their token ecosystems like EOS, Tron, Eth, BTS (Yes, all the tokens that live on them too). She’s also trading stocks, bonds, mutual funds, futures, and commodities. It’s a giant exchange to turn one thing of value into just about any other thing of value.

Scot progression
So, that’s the progress of Steem-Engine.com. Let’s do the same thing for Scot, but this time scot is the chromatic dragon.
At level 1 Scot isn’t the most impressive dude out there. There’s likely other monsters with nicer hair that you’d like to use in a fight. Scot’s just getting started. Token staking just began, and it’s day one. To get Scot rolling a community decides to prototype with Scotbot.
Scotbot has some issues because it’s a python voting bot. The rules can change and it’s centralized. It makes some people nervous to really invest heavily because theft is prevalent in crypto. But it’s a great prototyping tool, and it helps communities understand complicated formulas for how proof-of-brain works in reality.
SCOT has stood for Smart Contract Organizational Token. Scotbot is the python version, but many people in crypto trust smart contracts controlled by autonomous platforms over python voting bots controlled by individuals. Scot is coded as a smart contract. It’s actually built into a Steem post and read by the Steem-Engine node. It’s now a contract that a community leader funds with their tokens and the distribution happens exactly as the code reads without alteration that isn’t included in the contract.
Users can trust this 100% to do what it says it’s going to do and they can invest more heavily knowing that the Smart Contract is functioning.
Scot’s looking pretty effing beefy. That’s because now that many of the base level smart contracts have been written it’s now possible to write custom smart contracts on the platform (it was already able, but there wasn’t time to get them coded). Any if/then statement you can think of can be turned into a smart contract and that contract can be used to facilitate business and making money. Not only are communities and businesses using proof of brain distribution, but they’re tying into all these different smart contracts that really let them customize how their community operates.
With large communities adopting, a larger pool of devs to pool from, tons of talent from the crypto ecosystem, and strong leadership Scot is a force to reckoned with.
My god this scary looking thing is about to destroy all of Japan with nuclear laser beam eyes and dragon esque flames. He’s like godzilla but on steroids. When the chest beam goes off a destructive force never seen before is unleashed on the world of fiat and his final form is released.
You get the idea!
These things happen in levels and stages. We’re still at the early stage, but I think we have a vision, team, direction, and community that can pull this off.
I hope you join us for the ride (ie buy eng, start a token, launch scotbot). Look out in the next day or two, because Scotbot is starting in earnest very soon.
This page is synchronized from the post: ‘Stages of Scot and Steem-Exchange (illustrated with Splinterlands Skins that are coming soon)’


--- layout: default ---
Apache NLPCraft® is an open source Scala3-based library for adding natural language Interface to modern applications. It enables people to interact with your products using voice or text.
Based on fully deterministic semantic-based intent comprehension NLPCraft provides fully trackable natural language-to-action converter in an easy to use and simple to deploy library.
Natural Language Interface enables users to interact with any type of products using natural language augmenting existing UI/UX with fidelity and simplicity of a familiar spoken language.
Natural Language has no learning curve, no special rules or cumbersome syntax to master - it's a natural interface that your users already know.
Advanced Intent Definition Language (IDL) coupled with deterministic intent matching provide ease of use and unprecedented expressiveness for developing non-trivial intent comprehension.
Advanced out-of-the-box support for maintaining and managing conversational context that is fully integrated with intent matching.
Built with a singular focus - provide modern developers with unprecedented productivity and efficiency when building modern natural language applications.
NLPCraft supports any data source, device, or service - public or private. From databases and SaaS systems, to smart home devices, voice assistants and chatbots.
Everything you do with NLPCraft is part of your source code reflecting how engineers work. No more awkward web UIs splitting your logic across different incompatible places.
NLPCraft is built natively in Scala3 supporting all the latest Scala ecosystem of tools and libraries.
Apache NLPCraft is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects.
While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF. Licensed under the Apache License, Version 2.0. Apache NLPCraft, Apache, the Apache feather, and the Apache NLPCraft project logo are either trademarks or registered trademarks of the Apache Software Foundation.


Decentralized Creation.
The art challenges the technology and the technology inspires the art.
Follow us for news, entertainment, and contests
The world of cryptocurrency moves at 'lightning' speeds (pun intended). Our stream is open access - anyone can post or RT via our Slack channel.
Stay fresh with decentralized aggregation!


|
<< Click to Display Table of Contents >> Navigation: Goran Q&A > DG's Opening Remarks - 2013 |
Opening Remarks
SAC Global Meeting - May 2013
William Lacy Swing
Director General, International Organization for Migration
Geneva, Switzerland
Monday a May 2013
It is a real pleasure to welcome you all to Headquarters and to this first-ever Global SAC/LSA
Meeting. I look forward to meeting individually with as many of you as time allows. I always
insist that any of our field colleagues visiting Headquarters come to rem me so that I might
welcome you personally and thank you. After all, 97% of all of IOM's 8500 staff are in the field
- which is where the migrants are and where we need to be.
At this week's Global Meeting, I understand that you are 27 LSAs, representing some 90% of all
LSAs.
I want to thank each of you and as a group for your untiring work every day support for migrants
and to help improve migration policies and practices. Each time I visit our field colleagues - and
last year I spent more than 200 days travelling to visit our Missions - I am impressed with the
dedication and enthusiasm of all of you. So I want to say thank you so very much for your
Service.
I also want to thank you for accepting to serve on the SAC or LSA at your mission - this is real
labor of love, for there is no extra salary attached to any of your SAC positions. And, SAC work
takes a lot of your own personal time if you are to make your contribution. You have already
contributed to the points to be addressed at this meeting by communicating your concerns and of
those you represent as well as your and their respective priorities. So, I say thank you from the
bottom of my heart. You're an inspiration to me.
In addition, let me use this occasion to congratulate your Preside t, Pindie Stephen, and the entire
Board for this excellent, record-setting initiative - the first Global SAC/LSA meeting in IOM's
61-year history! This was long-overdue and greatly-needed. Congratulations - and thank you!
Congratulations also on the laudable objectives of this meeting - a gathering that has been very
well prepared. In fact, the organization of the Global meeting had its genesis in 2012 when the
current SAC held a three-day Retreat. And, it was on that occasion, that the SAC Board
identified a list of priorities to serve as a framework for its current mandate. A few of these are:
Investing in Staff Development; Transparency; Fairness and Consistency; and Representation for
all. And these priorities helped form the objectives for today's meeting.
Congratulations also on the progress that the SAC has made under its current leadership. This
Global SAC/LSA is the first step that SAC would like to take in moving towards serving one
global membership. As such, this is the first such meeting and a key SAC achievement. This has
been a particularly productive and resourceful SAC from who have come a number of new ideas
and initiatives including that of the Global SAC.
With these opening remarks I would like to make three points briefly - three points on which I
believe SAC and the Administration are in full agreement:
Professionalism
From my very first duy on 1 October 2008, I set forth my prioritys under the acronym The
Three P's. One of these was staff professionalism. This means many things but among these is
serious education to the cause for which the Organization was founded and exists, namely, to
ensure that migration benefits all. Professionalism also means that the Administration will make
training and career development a priority as well; here, in large part owing to lack of resources,
we have not done as well as I would have hoped, but as part of the restructuring, there has been
an increase in overall training. This will continue to be a matter that the SAC and the
Administration will be discussing at regular intervals.
Equitable Working Conditions
Perhaps the main purpose of this meeting, from my perspective, is to strengthen the relationship
between Local Staff Association and the Global SAC - and, in doing so, to help promote good
and equitable working conditions among all staff. The SAC Board and the Administration share
a common concern, namely, that everything legal, affordable and reasonable be done to improve
staff working conditons. Two important points: social security (NNJSPF) and health Insurance
coverage should be available to all staff.
Communication
The third and final point is simply to do everything possible - both the Administration and the
SAC - to stay in touch, to communicate regularly and as often as either feels necessary. The very
first day of my current mandate - 1 October 2008 - I asked to meet with the SAC Board. I did
so because I understand the importance of building mutual confidence and trust, and the bedrock
of good retation in communication and transparency. You, the LSAs, can play an important role
by ensuring that all staff members' concerns are being heard and addressed through the
appropriate channels.
Conclusion
The Agenda is set; it is an ambitious one, covering as it does a wide if not exhaustive range of
subjects and issues. And, the SAC Board has lined up an impressive list of speakers from various
areas to address LAC/SAC concerns and questions. I wish you an engaging and encouraging
meeting and look forward to seeing as many of you individually possible.
[End]


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{% load i18n %} {% comment %}@@@ why isn't this done as a form?{% endcomment %}
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--- layout: post title: Sharing Vaadin applications on Facebook date: '2014-02-07T18:06:00+02:00' tags: - vaadin - facebook - g+ - share - application - open graph tumblr_url: http://blog.porotype.com/post/75903660528/sharing-vaadin-applications-on-facebook ---
Have you ever wondered where the little ‘preview’ thumbnail comes from when you share links on Facebook (and G+), and how you might go about customising that for your Vaadin application? Read on!
Facebook actually crawls the page you share for suitable images, but this does not always work out in an optimal way. For instance, since Vaadin applications are loaded dynamically, Facebook previews do not work at all. Fortunately you can get around this by customising the Vaadin ‘bootstrap’ page - or any web page for that matter, but we’ll look at how to do it with Vaadin.
Facebook allows you to customise how it sees your page, by using Open Graph tags. You can read all about them here: https://developers.facebook.com/docs/opengraph/howtos/maximizing-distribution-media-content
Basically what you want to do is add a few meta-tags - the most interesting one being og:image, which specifies the preview image. But why stop there, let’s add the basic set:
First we should add the appropriate namespace xmlns:fb=“http://ogp.me/ns/fb#” for the head-tag, then add the og-tags as meta-tags.
In order to do this in Vaadin, we need to make a BootstrapListener and add it to our VaadinSession, all of which can be done in a SessionInitListener added to our VaadinServletService in an overridden servletInitialized(). Phew! Let see that in code, please:
public static class Servlet extends VaadinServlet {
protected void servletInitialized() throws ServletException {
super.servletInitialized();
getService().addSessionInitListener(new SessionInitListener() {
public void sessionInit(SessionInitEvent event) throws ServiceException {
event.getSession().addBootstrapListener(new SharePreviewBootstrap());
}
});
}
}
Yes, that’s quite a bit of boilerplate - I’m considering making this into an add-on to avoid that.
But let’s move on.
In the Bootstrap listener, all you need to do is modify the bootstrap page in modifyBootstrapPage(). You can add the namespace like so:
Element head = response.getDocument().head()
head.attr("xmlns:fb", "http://ogp.me/ns/fb#");
And then add the meta-tags like this:
Element meta = new Element(Tag.valueOf("meta"), "");
meta.attr("property", "og:image");
meta.attr("content",“”);
head.appendChild(meta);
Repeat that for all the Open Graph tags you want to add, then deploy, then enter your applications url in the share-box on Facebook, and voila: preview. Well, as long as you remembered to deploy the actual image too…
You can try it by sharing this example (note that you do not actually have to press ‘share’, just enter the url): http://marc.app.fi/SharePreview/
G+ does the same thing, by the way - and probably some other sites, let me know your findings.
Also feel free to ‘view source’ for the example application to see all the tags added.
You should also try the Facebook debugger, which will take a look att your url, and tell you what is good and what is not: https://developers.facebook.com/tools/debug/
One more detail: You can dynamically choose which image to show depending on the request. You might for instance want to send a different one for different sections:
String path = response.getRequest().getPathInfo();
if (path != null & path.endsWith(…) {
// send the desired tags
}
Or you might want to do all of this just for Facebook, in which case you can use the User-Agent:
String ua = response.getRequest().getHeader("User-Agent");
if (ua.startsWith(“facebookexternalhit”)) {
// It’s Facebook! Crawling!
}
Happy sharing!
And let me know if you’d like this to be a add-on or something!


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For the list of my publications, I refer to my Google Scholar page.
Leuven, Belgium PhD researcher on artificial intelligence, verifiability, and NLP at the DTAI lab.
Mar. 2019 — Jun. 2019 Part-time Student Researcher, Department of Computer Science, KU LeuvenLeuven, Belgium Published a paper on detecting ad hominem fallacies (i.e. personal attacks) in online debates and presented the paper at ACL 2019 in the Student Research Workshop.
Oct. 2018 — Jun. 2019 Master's student, CNH Industrial
Leuven, Belgium
Created a deep learning pipeline to detect obstacles in front of
combine harvesters with radar data for my advanced master’s
thesis.
Antwerp, Belgium
Designed and developed two complementary systems for symptom
detection and diagnosis of failures in distributed stream
processing systems (WWS), based on the network topology, for my master's thesis.
Leuven, Belgium Master's thesis under Johan Suykens in collaboration with CNH Industrial. Elective courses on genetic algorithms, fake news, and SVMs.
Sep. 2017 — Jul. 2018 Master of Electronics and ICT Engineering Technology, KU Leuven Ghent, BelgiumBachelor's thesis: visualization and problem detection on train carriages. [code]
I'm a teaching assistant the introductory course in Artificial Intelligence with online videos (2019-present) and databases (2020-2021).
And I have supervised or am currently supervising these master's students and interns:
I've reviewed for the following venues:


Lesson Plans by L.T. Satirof
You are currently viewing the 2016-2020 textbook files.
Please click here to view the 2021+ version.
New Horizon 2年
- Unit 0－My Spring Vacation
- Part 1－Show and Tellをしよう－P. 4
- Part 2－スピーチの内容について質問しよう－P. 5
- Unit 1－A Friend in a Sister School
- Unit 2－A Trip to the U.K.
- Unit 3－Career Day
- Unit 4－Homestay in the United States
- Unit 5－Universal Design
- Unit 6－Rakugo in English
- Unit 7－The Movie Dolphin Tale
- Extra
- Review, special holidays and extras


Seq2Seq (PyTorch)¶
Seq2seq with attention mechanism is a basic model for single turn dialog. In addition, batch normalization and dropout has been applied. You can also choose beamsearch, greedy, random sample, random sample from top-k when decoding.
You can refer to the following paper for details:
Sutskever, I., Vinyals, O., & Le, Q. V. (2014). Sequence to sequence learning with neural networks. In Advances in neural information processing systems (pp. 3104-3112).
Bahdanau, D., Cho, K., & Bengio, Y. (2015). Neural machine translation by jointly learning to align and translate. In International Conference on Learning Representation.
Require Packages¶
python3
cotk
pytorch == 1.0.0
tensorboardX >= 1.4
Quick Start¶
Using
cotk download thu-coai/seq2seq-pytorch/master
to download codes.Execute
python run.py
to train the model.The default dataset is
OpenSubtitles
. You can use--dataset
to specify otherdataloader
class and--dataid
to specify other data path (can be a local path, a url or a resources id). For example:--dataset OpenSubtitles --dataid resources://OpenSubtitles
It doesn’t use pretrained word vector by default setting. You can use
--wvclass
to specifywordvector
class and--wvpath
to specify pretrained word embeddings. For example:--wvclass gloves
. For example:--dataset Glove --dataid resources://Glove300
If you don’t have GPUs, you can add
--cpu
for switching to CPU, but it may cost very long time for either training or test.
You can view training process by tensorboard, the log is at
./tensorboard
.For example,
tensorboard --logdir=./tensorboard
. (You have to install tensorboard first.)
After training, execute
python run.py --mode test --restore best
for test.You can use
--restore filename
to specify checkpoints files, which are in./model
. For example:--restore pretrained-opensubtitles
for loading./model/pretrained-opensubtitles.model
--restore last
means last checkpoint,--restore best
means best checkpoints on dev.--restore NAME_last
means last checkpoint with model named NAME. The same as--restore NAME_best
.
Find results at
./output
.
Arguments¶
usage: run.py [-h] [--name NAME] [--restore RESTORE] [--mode MODE] [--lr LR]
[--eh_size EH_SIZE] [--dh_size DH_SIZE] [--droprate DROPRATE]
[--batchnorm] [--decode_mode {max,sample,gumbel,samplek,beam}]
[--top_k TOP_K] [--length_penalty LENGTH_PENALTY]
[--dataset DATASET] [--dataid DATAID] [--epoch EPOCH]
[--batch_per_epoch BATCH_PER_EPOCH] [--wvclass WVCLASS]
[--wvid WVID] [--out_dir OUT_DIR] [--log_dir LOG_DIR]
[--model_dir MODEL_DIR] [--cache_dir CACHE_DIR] [--cpu]
[--debug] [--cache] [--seed SEED]
A seq2seq model with GRU encoder and decoder. Attention, beamsearch, dropout
and batchnorm is supported.
optional arguments:
-h, --help show this help message and exit
--name NAME The name of your model, used for tensorboard, etc.
Default: runXXXXXX_XXXXXX (initialized by current
time)
--restore RESTORE Checkpoints name to load. "NAME_last" for the last
checkpoint of model named NAME. "NAME_best" means the
best checkpoint. You can also use "last" and "best",
by default use last model you run. Attention:
"NAME_last" and "NAME_best" are not guaranteed to work
when 2 models with same name run in the same time.
"last" and "best" are not guaranteed to work when 2
models run in the same time. Default: None (don't load
anything)
--mode MODE "train" or "test". Default: train
--lr LR Learning rate. Default: 0.001
--eh_size EH_SIZE Size of encoder GRU
--dh_size DH_SIZE Size of decoder GRU
--droprate DROPRATE The probability to be zerod in dropout. 0 indicates
for don't use dropout
--batchnorm Use bathnorm
--decode_mode {max,sample,gumbel,samplek,beam}
The decode strategy when freerun. Choices: max,
sample, gumbel(=sample), samplek(sample from topk),
beam(beamsearch). Default: beam
--top_k TOP_K The top_k when decode_mode == "beam" or "samplek"
--length_penalty LENGTH_PENALTY
The beamsearch penalty for short sentences. The
penalty will get larger when this becomes smaller.
--dataset DATASET Dataloader class. Default: OpenSubtitles
--dataid DATAID Resource id for data set. It can be a resource name or
a local path. Default: resources://OpenSubtitles
--epoch EPOCH Epoch for training. Default: 100
--batch_per_epoch BATCH_PER_EPOCH
Batches per epoch. Default: 1500
--wvclass WVCLASS Wordvector class, none for not using pretrained
wordvec. Default: Glove
--wvid WVID Resource id for pretrained wordvector. Default:
resources://Glove300d
--out_dir OUT_DIR Output directory for test output. Default: ./output
--log_dir LOG_DIR Log directory for tensorboard. Default: ./tensorboard
--model_dir MODEL_DIR
Checkpoints directory for model. Default: ./model
--cache_dir CACHE_DIR
Checkpoints directory for cache. Default: ./cache
--cpu Use cpu.
--debug Enter debug mode (using ptvsd).
--cache Use cache for speeding up load data and wordvec. (It
may cause problems when you switch dataset.)
--seed SEED Specify random seed. Default: 0
TensorBoard Example¶
Execute tensorboard --logdir=./tensorboard
, you will see the plot in tensorboard pages:
Following plot are shown in this model:
gen/loss (
gen
means training process)gen/perplexity (
=exp(gen/word_loss)
)gen/word_loss (
=gen/loss
in this model)dev/loss
dev/perplexity_avg_on_batch
test/loss
test/perplexity_avg_on_batch
And text output:
Following text are shown in this model:
args
dev/show_str%d (
%d
is according toargs.show_sample
inrun.py
)
Case Study of Model Results¶
Execute python run.py --mode test --restore best
The following output will be in ./output/[name]_[dev|test].txt
:
perplexity: 48.194050
bleu: 0.320098
post: my name is josie .
resp: <unk> <unk> , pennsylvania , the <unk> state .
gen: i' m a teacher .
post: i put premium gasoline in her .
resp: josie , i told you .
gen: i don' t know .
post: josie , dont hang up
resp: they do it to aii the new kids .
gen: aii right , you guys , you know what ?
post: about playing a part .
resp: and thats the theme of as you like it .
gen: i don' t know .
......
Experiment¶
Subset Experiment¶
Based on OpenSubtitles_small
(a smaller version of OpenSubtitles
), we did the following experiments.
encoder |
decoder |
batchnorm |
learning rate |
droprate |
dev perplexity |
test perplexity |
|---|---|---|---|---|---|---|
175 |
175 |
no |
0.0001 |
0.2 |
88.971 |
94.698 |
128 |
128 |
no |
0.0001 |
0 |
95.207 |
100.676 |
128 |
128 |
no |
0.0001 |
0.2 |
93.559 |
99.287 |
128 |
128 |
yes |
0.0001 |
0 |
105.649 |
112.818 |
128 |
128 |
yes |
0.0001 |
0.2 |
95.894 |
102.243 |
150 |
150 |
no |
0.0001 |
0.2 |
90.153 |
95.072 |
256 |
256 |
no |
0.0001 |
0.2 |
89.374 |
94.272 |
175 |
175 |
yes |
0.0001 |
0.2 |
97.704 |
102.851 |
175 |
175 |
no |
0.0001 |
0.1 |
90.149 |
95.310 |
175 |
175 |
no |
0.0001 |
0.3 |
89.750 |
95.042 |
175 |
175 |
no |
0.0005 |
0.2 |
88.688 |
93.421 |
The following experiments are based on the parameters of the first experiment.
To reproduce the experiment, run the following command to train the model:
python run.py --dataset=OpenSubtitles --dataid resources://OpenSubtitles_small --eh_size 175 --dh_size 175 --droprate 0.2 --epoch 35 --lr 0.0001
Based on the best parameters, we did another five experiments in order to analyze the model’s performance totally.
seed |
dev perplexity |
test perplexity |
dev bleu(x1e-3) |
test bleu(x1e-3) |
|---|---|---|---|---|
7913 |
89.123 |
93.898 |
3.24 |
2.82 |
1640 |
88.224 |
94.019 |
4.51 |
4.13 |
3739 |
87.969 |
92.730 |
2.37 |
2.15 |
972 |
88.083 |
93.515 |
2.99 |
2.34 |
3594 |
87.933 |
94.258 |
4.22 |
3.44 |
Average |
88.266 ± 0.440 |
93.684 ± 0.534 |
3.47 ± 7.92 |
2.98 ± 7.29 |
Run the following command to test the trained model:
python run.py --dataset=OpenSubtitles --dataid resources://OpenSubtitles_small --eh_size 175 --dh_size 175 --decode_mode samplek --droprate 0.2 --epoch 35 --mode test --restore [model name] --seed [seed value]
Fullset experiment¶
Based on the result of subset experiment, we did the following experiment on OpenSubtitles
.
Parameters |
Value |
|---|---|
encoder |
256 |
decoder |
256 |
batchnorm |
no |
learning rate |
0.0003 |
droprate |
0.2 |
epoch |
200 |
seed |
0 |
decode mode |
dev perplexity |
test perplexity |
dev bleu(x1e-3) |
test bleu(x1e-3) |
|---|---|---|---|---|
samplek |
41.457 |
43.868 |
3.24 |
2.82 |
beam |
41.457 |
43.868 |
11.5 |
10.4 |
To reproduce the experiment, run the following command to train the model:
python run.py --dataset=OpenSubtitles --dataid resources://OpenSubtitles --eh_size 256 --dh_size 256 --droprate 0.2 --lr 0.0003 --epoch 200
Run the following command to test the trained model:
python run.py --dataset=OpenSubtitles --dataid resources://OpenSubtitles --eh_size 256 --dh_size 256 --decode_mode [decode mode] --droprate 0.2 --lr 0.0003 --epoch 200 --mode test --restore best
Performance¶
Perplexity |
BLEU |
|
|---|---|---|
OpenSubtitles |
43.868 |
0.0115 |


Individual Project
Choose a topic and research interest for individual project
*Required
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*
First Name
Last Name
Research Interest (list at least 3)
*
Project Title - (e.g. income vs education US Census)
*
Top Skills
*
SQL
Python programming
Matlab
D3js and Javascript
C# VB.net
PHP
Node.JS
Web design tools (e.g. Wordpress)
HTML and CSS
Excel,
PowerBI
Tableau
Option 13
Other:
Submit


|
Deprecated Methods |
kieker.tools.traceAnalysis.repository.TraceColorRepository.createFromFile(String)
To be removed in Kieker 1.8. |
kieker.tools.traceAnalysis.repository.DescriptionRepository.createFromFile(String)
To be removed in Kieker 1.8. |
kieker.common.configuration.Configuration.get(Object)
This method will not be removed (as this is for technical reasons not possible), but should only be used within this class. Don't call this method
directly. |
kieker.monitoring.writer.AbstractMonitoringWriter.getConfiguration()
to be removed in Kieker 1.8 |
kieker.monitoring.timer.SystemNanoTimer.getInstance()
to be removed in Kieker 1.8 |
kieker.analysis.model.analysisMetaModel.impl.MAnalysisMetaModelFactory.getPackage()
|
kieker.common.configuration.Configuration.getProperty(String)
This method will not be removed (as this is for technical reasons not possible), but should only be used within this class. Don't call this method
directly. |
kieker.common.configuration.Configuration.getProperty(String, String)
This method will not be removed (as this is for technical reasons not possible), but should only be used within this class. Don't call this method
directly. |
kieker.common.record.controlflow.OperationExecutionRecord.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.common.record.controlflow.BranchingRecord.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.common.record.flow.AbstractEvent.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.common.record.flow.trace.Trace.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.common.record.misc.KiekerMetadataRecord.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.common.record.misc.EmptyRecord.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.common.record.misc.TimestampRecord.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.common.record.system.MemSwapUsageRecord.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.common.record.system.CPUUtilizationRecord.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.common.record.system.ResourceUtilizationRecord.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.monitoring.core.registry.RegistryRecord.initFromArray(Object[])
This record uses the IMonitoringRecord.Factory mechanism. Hence, this method is not implemented. |
kieker.common.configuration.Configuration.put(Object, Object)
This method will not be removed (as this is for technical reasons not possible), but should only be used within this class. Don't call this method
directly. |
kieker.analysis.AnalysisController.registerFilter(AbstractFilterPlugin)
This method will not be for public use in Kieker 1.8. Use the new constructor instead. |
kieker.analysis.AnalysisController.registerReader(AbstractReaderPlugin)
This method will not be for public use in Kieker 1.8. Use the new constructor instead. |
kieker.analysis.AnalysisController.registerRepository(AbstractRepository)
This method will not be for public use in Kieker 1.8. Use the new constructor instead. |
kieker.analysis.analysisComponent.AbstractAnalysisComponent.setProjectContext(IProjectContext)
To be removed in 1.8 |


panos_security_rule¶
New in version 2.4.
Synopsis¶
- Security policies allow you to enforce rules and take action, and can be as general or specific as needed. The policy rules are compared against the incoming traffic in sequence, and because the first rule that matches the traffic is applied, the more specific rules must precede the more general ones.
Requirements (on host that executes module)¶
- pan-python can be obtained from PyPi https://pypi.python.org/pypi/pan-python
- pandevice can be obtained from PyPi https://pypi.python.org/pypi/pandevice
- xmltodict can be obtained from PyPi https://pypi.python.org/pypi/xmltodict
Options¶
| parameter | required | default | choices | comments |
|---|---|---|---|---|
| action |
no | allow | Action to apply once rules maches. | |
| antivirus |
no | None | Name of the already defined antivirus profile. | |
| api_key |
no | API key that can be used instead of username/password credentials. | ||
| application |
no | any | List of applications. | |
| commit |
no | True | Commit configuration if changed. | |
| data_filtering |
no | None | Name of the already defined data_filtering profile. | |
| description |
no | None | Description for the security rule. | |
| destination_ip |
no | any | List of destination addresses. | |
| destination_zone |
no | any | List of destination zones. | |
| devicegroup |
no | None | - Device groups are used for the Panorama interaction with Firewall(s). The group must exists on Panorama. If device group is not define we assume that we are contacting Firewall.
| |
| existing_rule |
no | If 'location' is set to 'before' or 'after', this option specifies an existing rule name. The new rule will be created in the specified position relative to this rule. If 'location' is set to 'before' or 'after', this option is required. | ||
| file_blocking |
no | None | Name of the already defined file_blocking profile. | |
| group_profile |
no | None | - Security profile group that is already defined in the system. This property supersedes antivirus, vulnerability, spyware, url_filtering, file_blocking, data_filtering, and wildfire_analysis properties.
| |
| hip_profiles |
no | any | - If you are using GlobalProtect with host information profile (HIP) enabled, you can also base the policy on information collected by GlobalProtect. For example, the user access level can be determined HIP that notifies the firewall about the user's local configuration.
| |
| ip_address |
yes | IP address (or hostname) of PAN-OS device being configured. | ||
| location |
no | Position to place the created rule in the rule base. Supported values are top/bottom/before/after. | ||
| log_end |
no | True | Whether to log at session end. | |
| log_start |
no | Whether to log at session start. | ||
| operation |
no | add | The action to be taken. Supported values are add/update/find/delete. | |
| password |
yes | Password credentials to use for auth unless api_key is set. | ||
| rule_name |
yes | Name of the security rule. | ||
| rule_type |
no | universal | Type of security rule (version 6.1 of PanOS and above). | |
| service |
no | application-default | List of services. | |
| source_ip |
no | any | List of source addresses. | |
| source_user |
no | any | Use users to enforce policy for individual users or a group of users. | |
| source_zone |
no | any | List of source zones. | |
| spyware |
no | None | Name of the already defined spyware profile. | |
| tag_name |
no | None | Administrative tags that can be added to the rule. Note, tags must be already defined. | |
| url_filtering |
no | None | Name of the already defined url_filtering profile. | |
| username |
no | admin | Username credentials to use for auth unless api_key is set. | |
| vulnerability |
no | None | Name of the already defined vulnerability profile. | |
| wildfire_analysis |
no | None | Name of the already defined wildfire_analysis profile. |
Examples¶
- name: add an SSH inbound rule to devicegroup panos_security_rule: ip_address: '{{ ip_address }}' username: '{{ username }}' password: '{{ password }}' operation: 'add' rule_name: 'SSH permit' description: 'SSH rule test' tag_name: ['ProjectX'] source_zone: ['public'] destination_zone: ['private'] source: ['any'] source_user: ['any'] destination: ['<IP_ADDRESS>'] category: ['any'] application: ['ssh'] service: ['application-default'] hip_profiles: ['any'] action: 'allow' devicegroup: 'Cloud Edge' - name: add a rule to allow HTTP multimedia only from CDNs panos_security_rule: ip_address: '<IP_ADDRESS>' username: 'admin' password: 'paloalto' operation: 'add' rule_name: 'HTTP Multimedia' description: 'Allow HTTP multimedia only to host at <IP_ADDRESS>' source_zone: ['public'] destination_zone: ['private'] source: ['any'] source_user: ['any'] destination: ['<IP_ADDRESS>'] category: ['content-delivery-networks'] application: ['http-video', 'http-audio'] service: ['service-http', 'service-https'] hip_profiles: ['any'] action: 'allow' - name: add a more complex rule that uses security profiles panos_security_rule: ip_address: '{{ ip_address }}' username: '{{ username }}' password: '{{ password }}' operation: 'add' rule_name: 'Allow HTTP w profile' log_start: false log_end: true action: 'allow' antivirus: 'default' vulnerability: 'default' spyware: 'default' url_filtering: 'default' wildfire_analysis: 'default' - name: delete a devicegroup security rule panos_security_rule: ip_address: '{{ ip_address }}' api_key: '{{ api_key }}' operation: 'delete' rule_name: 'Allow telnet' devicegroup: 'DC Firewalls' - name: find a specific security rule panos_security_rule: ip_address: '{{ ip_address }}' password: '{{ password }}' operation: 'find' rule_name: 'Allow RDP to DCs' register: result - debug: msg='{{result.stdout_lines}}' - name: add a rule at a specific location in the rulebase panos_security_rule: ip_address: '{{ ip_address }}' username: '{{ username }}' password: '{{ password }}' operation: 'add' rule_name: 'SSH permit' description: 'SSH rule test' source_zone: ['untrust'] destination_zone: ['trust'] source_ip: ['any'] source_user: ['any'] destination_ip: ['<IP_ADDRESS>'] category: ['any'] application: ['ssh'] service: ['application-default'] action: 'allow' location: 'before' existing_rule: 'Prod-Legacy 1' - name: disable a specific security rule panos_security_rule: ip_address: '{{ ip_address }}' username: '{{ username }}' password: '{{ password }}' operation: 'disable' rule_name: 'Prod-Legacy 1'


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RNFDictionaryConfigurationHelper Class Reference
| Inherits from | NSObject |
| Declared in | RNFDictionaryConfigurationHelper.h |
Overview
This class is mainly meant to be used internally, not subclassed and not used by external classes. If you want to subclass RNFDictionary{Endpoint,Operation}Configuration, anyway, you may find it handy
Class Methods
classFromKey:inDictionary:
Given a configuration dictionary, this method returns the Class represented by the value for the given key
+ (Class)classFromKey:(const NSString *)key inDictionary:(NSDictionary *)configurationDictionary
Parameters
- key
The key to lookup in the dictionary
- configurationDictionary
The configuration dictionary to lookup into
Return Value
The Class represented by configurationDictionary[key]
Discussion
Given a configuration dictionary, this method returns the Class represented by the value for the given key
Declared In
RNFDictionaryConfigurationHelper.h
dictionaryToData:
Converts a NSDictionary instance into a NSData object
+ (NSData *)dictionaryToData:(NSDictionary *)dictionary
Parameters
- dictionary
The dictionary to convert
Return Value
The NSData instance containing the UTF8 representation in the form of key=value&key2=value2 of the dictionary
Discussion
Converts a NSDictionary instance into a NSData object
Declared In
RNFDictionaryConfigurationHelper.h
objectConformToProtocol:forKey:inDictionary:
- Handy method to perform a sanity check and retrieve a valid object from a configuration dictionary given a key and a protocol you want the object to conform to *
- @param protocol The protocol the object should conform to, to be valid
- @param key The key to lookup in the dictionary
- @param configurationDictionary The reference configuration dictionary *
- @return If configurationDictionary[key] is a string, this method returns an instance of the class returned by classFromKey:inDictionary: only if the given Class conforms to the protocol passed as a parameter. Otherwise it throws a RNFMalformedConfiguration; If configurationDictionary[key] is a dictionary itself, this method returns an instance of the class specified in configurationDictionary[key][@“objectClass”], initialized with the remaining key-value pairs, only if the given Class conforms to RNFInitializableWithDictionary, and the resulting object conforms to the given protocol. If one of these two requirements is not met, RNFMalformedConfiguration is thrown. An exception is also thrown if configurationDictionary[key][@“objectClass”] is not specified or it doesn’t represent a valid Class. *
- @throws RNFMalformedConfiguration in one of the cases described above, listed below:
- 1) If configurationDictionary[key] is a string but the class it represents doesn’t conform to the given protocol
- 2) If configurationDictionary[key] is a dictionary, but configurationDictionary[key][@“objectClass”] represents a Class that doesn’t conform to the given protocol
- 3) If configurationDictionary[key] is a dictionary, but configurationDictionary[key][@“objectClass”] represents a Class that doesn’t conform to RNFInitializableWithDictionary, and so it can’t be initialized
- 4) If configurationDictionary[key] is a dictionary, but configurationDictionary[key][@“objectClass”] is not speified or it is not a Class
+ (id)objectConformToProtocol:(Protocol *)protocol forKey:(const NSString *)key inDictionary:(NSDictionary *)configurationDictionary
Discussion
- Handy method to perform a sanity check and retrieve a valid object from a configuration dictionary given a key and a protocol you want the object to conform to *
- @param protocol The protocol the object should conform to, to be valid
- @param key The key to lookup in the dictionary
- @param configurationDictionary The reference configuration dictionary *
- @return If configurationDictionary[key] is a string, this method returns an instance of the class returned by classFromKey:inDictionary: only if the given Class conforms to the protocol passed as a parameter. Otherwise it throws a RNFMalformedConfiguration; If configurationDictionary[key] is a dictionary itself, this method returns an instance of the class specified in configurationDictionary[key][@“objectClass”], initialized with the remaining key-value pairs, only if the given Class conforms to RNFInitializableWithDictionary, and the resulting object conforms to the given protocol. If one of these two requirements is not met, RNFMalformedConfiguration is thrown. An exception is also thrown if configurationDictionary[key][@“objectClass”] is not specified or it doesn’t represent a valid Class. *
- @throws RNFMalformedConfiguration in one of the cases described above, listed below:
- 1) If configurationDictionary[key] is a string but the class it represents doesn’t conform to the given protocol
- 2) If configurationDictionary[key] is a dictionary, but configurationDictionary[key][@“objectClass”] represents a Class that doesn’t conform to the given protocol
- 3) If configurationDictionary[key] is a dictionary, but configurationDictionary[key][@“objectClass”] represents a Class that doesn’t conform to RNFInitializableWithDictionary, and so it can’t be initialized
- 4) If configurationDictionary[key] is a dictionary, but configurationDictionary[key][@“objectClass”] is not speified or it is not a Class
Declared In
RNFDictionaryConfigurationHelper.h


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gs
is a grammar of recurring calendar events, implemented as an R package. It enables users to easily create and work with schedules, even in cases when the pattern of events is irregular. gs
does this by providing a set of simple to understand functions for making schedules along with functions for combining them to form more complex ones.
The gs
grammar is both flexible and declarative. The flexibility allows users to compose arbitrarily complex schedules from simple and intuitive buildings blocks. Because the grammar is declarative, the user need not concern themselves with the details of how a particular schedule works, rather they can specify what they want from a schedule and let gs
implement it for them.
The package is currently experimental. Users are cautioned against relying on it for anything of importance. It can be downloaded from Github:
Feedback, contributions, bug report and suggestions are welcome and can be made in the issues tab of the Github repo.
If you have not used gs
before, the best place to get started is the introductory vignette.
I would like to extend an enormous thank you to the authors of and contributors to the lubridate
package. gs
relies on lubridate
for much of its functionality and builds explicitly on its syntax.
I would also like to thank Martin Fowler, whose writing1 on this topic helped guide my thinking in a number of important ways.
Finally I’d also like to thank Garrett Grolemund and Hadley Wickham who in their paper2 on lubridate
inspired me to create gs
and pointed me in Fowler’s direction:
In particular, we hope to create methods for R that work with reoccurring temporal date patterns, which were introduced by Fowler (1997).
Fowler, M. (1997). “Recurring events for calendars.” <URL: https://tinyurl.com/yaqlbauj>.↩
Grolemund G, Wickham H (2011). “Dates and Times Made Easy with lubridate.” Journal of Statistical Software, 40(3), 1-25. <URL: http://www.jstatsoft.org/v40/i03/>.↩


Jacek is best known by the online "Internals" books:
Jacek is active on StackOverflow
Advance in solving analytical problems using Spark SQL and explore the recent Apache Spark 2.4, esp. Spark Structured Streaming and Spark MLlib


The integral function at the end of the preceding section shows how we can use streams to model signal-processing systems that contain feedback loops. The feedback loop for the adder shown in figure \ref{fig:integral} is modeled by the fact that integral's internal stream int is defined in terms of itself:
const integ = pair(initial_value, () => add_streams(scale_stream(integrand, dt), integ); );
Unfortunately, stream models of systems with loops
may require uses of a delay beyond the stream programming pattern seen so far.
For instance,
figure \ref{fig:analog-computer} shows a signal-processing system for
solving the
differential equation $dy/dt=f(y)$ where $f$ is a given
function. The figure shows a mapping component, which
applies $f$ to its input signal, linked in a feedback loop to an
integrator in a manner very similar to that of the analog computer
circuits that are actually used to solve such equations.
\begin{figure}[H]
\centering
\maxsizebox{\linewidth}{0.8\paperheight}{\includegraphics[scale=0.8]{{img\string_original/ch3-Z-G-52}.svg}}
\caption{An analog computer circuit
that solves the equation
}
\label{fig:analog-computer}
\end{figure}
Assuming we are given an initial value $y_0$ for $y$, we could try to model this system using the function
function solve(f, y0, dt) { const y = integral(dy, y0, dt); const dy = stream_map(f, y); return y; }
On the other hand, the intent of our definition does make sense, because we can, in principle, begin to generate the y stream without knowing dy. Indeed, integral and many other stream operations can generate part of the answer given only partial information about the arguments. For integral, the first element of the output stream is the specified initial_value. Thus, we can generate the first element of the output stream without evaluating the integrand dy. Once we know the first element of y, the stream_map in the second line of solve can begin working to generate the first element of dy, which will produce the next element of y, and so on.
To take advantage of this idea, we will redefine integral to expect the integrand stream to be a delayed argument. The function integral will force the integrand to be evaluated only when it is required to generate more than the first element of the output stream:
function integral(delayed_integrand, intial_value, dt) { const integrand = delayed_integrand(); const integ = pair(intial_value, add_streams(scale_stream(integrand, dt), int)); }
Now we can implement our solve function by delaying the evaluation of dy in the definition of y:
function solve(f, y0, dt) { const y = integral( () => dy, y0, dt); const dy = stream_map(f, y); return y; }
In general, every caller of integral must now delay the integrand argument. We can demonstrate that the solve function works by approximating $e\approx 2.718$ by computing the value at $y=1$ of the solution to the differential equation $dy/dt=y$ with initial condition $y(0)=1$:
stream_ref(solve(y => y, 1, 0.001), 1000);
implicitdefinition of the infinite stream of integers in section \ref{sec:infinite-streams}. Alternatively, we can give a definition of integral that is more like integers-starting-from (also in section \ref{sec:infinite-streams}):
The examples in this section illustrate how delayed evaluation provides great programming flexibility, but the same examples also show how this can make our programs more complex. Our new integral function, for instance, gives us the power to model systems with loops, but we must now remember that integral should be called with a delayed integrand, and every function that uses integral must be aware of this. In effect, we have created two classes of functions: ordinary functions and functions that take delayed arguments. In general, creating separate classes of functions forces us to create separate classes of higher-order functions as well.[1]
One way to avoid the need for two different classes of functions is to make all functions take delayed arguments. We could adopt a model of evaluation in which all arguments to functions are automatically delayed and arguments are forced only when they are actually needed (for example, when they are required by a primitive operation). This would transform our language to use normal-order evaluation, which we first described when we introduced the substitution model for evaluation in section \ref{sec:substitution-model}. Converting to normal-order evaluation provides a uniform and elegant way to simplify the use of delayed evaluation, and this would be a natural strategy to adopt if we were concerned only with stream processing. In section \ref{sec:lazy-evaluation}, after we have studied the evaluator, we will see how to transform our language in just this way. Unfortunately, including delays in function calls wreaks havoc with our ability to design programs that depend on the order of events, such as programs that use assignment, mutate data, or perform input or output. Even a single delay in the tail of a pair can cause great confusion, as illustrated by exercise \ref{ex:delayed1} and \ref{ex:delayed2}. As far as anyone knows, mutability and delayed evaluation do not mix well in programming languages, and devising ways to deal with both of these at once is an active area of research.
map a given function fun over all the elements in a sequenceby a single higher-order function such as stream_map. Rather, we would need a different mapping function for each different combination of argument and result data types that might be specified for a fun. Maintaining a practical notion of
data typein the presence of higher-order functions raises many difficult issues. One way of dealing with this problem is illustrated by the language ML (
polymorphic data typesinclude templates for higher-order transformations between data types. Moreover, data types for most functions in ML are never explicitly declared by the programmer. Instead, ML includes a type-inferencing mechanism that uses information in the environment to deduce the data types for newly defined functions.


1949 Morris J-Type resurrected as electric, carbon fiber-bodied van
It costs more than an Audi RS 5 Sportback
by Ronan GlonEuropean investors resurrected England's Morris Commercial, a firm that spent decades in the grave, and unveiled an electric van named JE. The cargo-hauling two-seater wears a heritage-laced design inspired by one of the most recognizable models Morris Commercial made.
Developed in England, the JE is a tribute to the J-Type van made between 1949 and 1961. It retains several of the original model's defining styling cues, including a tall grille split in half by a chromed vertical slat, and headlights mounted on top of the fenders. The overall proportions are period-correct, too, but the JE shares nothing with the J-Type that crisscrossed England for decades.
The body is made with carbon fiber to keep weight in check, and it's dropped on a new platform developed specifically to underpin electric vehicles. Don't expect to find the Morris Oxford's sidevalve engine nestled between the front seats. Power comes from an electric drivetrain built around a lithium-ion battery pack that delivers up to 200 miles of driving range, though full specifications remain under wraps. What's certain is the layout clears up a cargo compartment that's low and flat. You're out of luck if you want to order the JE with a turbo four, or a plug-in hybrid powertrain; Morris Commercial clearly stated it will never make a model powered by an internal combustion engine.
Though 200 miles hardly qualifies the JE for the coveted long-range label, Morris envisions it as an urban delivery vehicle. It's capable of hauling 2,200 pounds in its 194-cubic-foot cargo compartment, a figure which makes it comfortably more capable than the Ford Transit Connect, but less competent than bigger models like the full-size Transit. Its overall dimensions remain under wraps.
Morris plans to build the JE in the United Kingdom, though it hasn't revealed where yet. Production is tentatively scheduled to begin in late 2021, and pricing will start at about 60,000 British pounds, a princely sum that represents about $77,000 at the current conversion rate. Autoblog reached out to the company to find out if it has sights on the American market, and we'll update this story if we learn more. Regardless, it will need to fend off competition from the production variant of the similarly retrolicious Volkswagen ID Buzz concept, which is due out globally in 2022.
Looking ahead, Morris Commercial plans to extrapolate a full range of models from the modular platform. It wants to launch a people-carrying model, a pickup, and a camper van, among other body styles. The company told Autocar it expects approximately 1,000 motorists will spend Audi RS 5 money on an electric van each year, though the aforementioned variants will increase that number.


R is used to manipulate and analyze data that both feed into and come out of the ALFRESCO wildfire model. The alfresco
R package contains functions for working with ALFRESCO input and output data. It is a core functional package in the SNAPverse collection of R packages.
Features
The alfresco
package includes functions that assist with the following analyses and processing pipelines:
- Fire events processing immediately following ALFRESCO runs
- Post-ALFRESCO run, automated Shiny app creation.
- Hierarchical data extractions from ALFRESCO run output geotiff map sets.
- Calculations for burn area ratios across multiple ALFRESCO run scenarios.
- Copying and organizing subsets of ALFRESCO outputs for consecutive model runs and in preparation for other analyses.
- Generating fire management options ratios geotiffs and related graphics.
- Generation of flexible bash and slurm scripts for processing catering to unique analysis and data processing needs.
- Data extraction and statistics by Fire Management Options (FMO) zones.
- Quickly access Alaska wildfire-related data sets like historical fire perimeters from the cloud.
This is a subset of eventual functionality. The package is under active development.
Installation
You can install alfresco from github with:
# install.packages('devtoools')
devtools::install_github("leonawicz/alfresco")


Master Gobie:
What business have you with me? Do you have an order? I did not receive an order for you. You may have come to the wrong person. Please check again.


BERKSHIRE HATHAWAY INC
3555 FARNMAN STREET
OMAHA, NE 68131
OFFICIAL HOME PAGE
A Message From Warren E. Buffett
Annual & Interim Reports
Link to SEC Filings
Links to Berkshire Subsidiary Companies
Corporate Governance
Owner's Manual
Letters from Warren E. Buffett Regarding Pledges to Make Gifts of Berkshire Stock
News Releases
Warren Buffett's Letters to Berkshire Shareholders
Annual Meeting Information
Celebrating 50 Years of a Profitable Partnership
Comparative Rights and Relative Prices of Class A and B Stock
Berkshire Activewear


var game = new Phaser.Game(800, 600, Phaser.AUTO, 'phaser-example', { preload: preload, create: create, update: update });
function preload() {
game.load.image('space', 'assets/skies/space3.png');
game.load.spritesheet('face', 'assets/sprites/metalface78x92.png', 78, 92);
}
var face1;
var face2;
function create() {
game.add.sprite(0, 0, 'space');
face1 = game.add.sprite(0, 0, 'face');
face2 = game.add.sprite(500, 0, 'face');
// A simple animation that flashes the 'eyes' of the sprite
face1.animations.add('flash', [0,1,2,3,2,1,0], 24, false);
face2.animations.add('flash', [0,1,2,3,2,1,0], 24, false);
// Set-up the physics bodies
game.physics.startSystem(Phaser.Physics.ARCADE);
game.physics.arcade.enable([face1, face2]);
face1.body.velocity.setTo(200, 200);
face1.body.bounce.set(1);
face2.body.velocity.setTo(-200, 200);
face2.body.bounce.set(1);
face1.body.collideWorldBounds = true;
face2.body.collideWorldBounds = true;
// Usually you'd provide a callback to the `game.physics.arcade.collide` function,
// which is passed the two sprites involved in the collision, which you can then
// perform further processing on. However you can also use this signal:
face1.body.onCollide = new Phaser.Signal();
face1.body.onCollide.add(hitSprite, this);
// You still need to call `collide` in your update function, and you can still use
// a callback with it too, but this Signal provides for another level of notification.
}
function hitSprite (sprite1, sprite2) {
sprite1.play('flash');
sprite2.play('flash');
}
function update () {
game.physics.arcade.collide(face1, face2);
}


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Ecobank in trouble over cash baron
Ecobank has been officially fingered for corruptly issuing out of ZW$15, 000 to a customer seen with sealed $2 and $5 dollar banknotes in a picture circulating on social media.
by Desmond MunemoBarely two days after the Reserve Bank of Zimbabwe (RBZ) injected the first $30 million batch of new bank notes in banks, they were already on the streets where black market traders were showing off on social media.
Commercial banks on Monday collected $30 million from RBZ, started issuing on Tuesday and account holders get $300 weekly cash withdrawal rations.
The RBZ governor Dr John Mangudya yesterday issued a statement on the matter:
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“The RBZ has taken note of pictures circulating on social media that show recently introduced 2 dollar banknotes in sealed packs, suggesting that the notes are already being traded on the parallel market.
“The Bank has conducted investigations on the matter, and the findings are that the banknotes in the circulating pictures emanated from Ecobank.
“Preliminary investigations by the RBZ at Ecobank indicate that an amount of ZW$15, 000 was withdrawn by one customer.
“Ecobank, together with their customer, are now assisting the Zimbabwe Republic Police with further investigations on this matter.
“Appropriate disciplinary measures shall be taken against the bank and the customer and anyone else found responsible for such malpractices which bring the RBZ and the entire banking system into disrepute.
Mangudya added: “Such malpractices cannot and should not be condoned.
“In the meantime, the Bank would like to advise the public on how banks withdraw cash from the RBZ.
“The procedure is such that banks transfer the equivalent amount of their cash requirements to the RBZ through the RTGS system.
“The banks will then collect the cash from the RBZ to their central cash depots from where they distribute to their branch network.” H-Metro


--- layout: default title: Sample eCommerce Store | Practice Scraping div_id: store permalink: /sample-store ---
You can use this site to practice scraping eCommerce data.
All product data is fictitious.


---
---
{%- if page.redirect -%}
{%- endif -%}
{% include head.html %}
{%- include footer.html %}
{% include scripts/jquery.html %}
{% include scripts/bootstrap.html %}
{% include scripts/masonry.html %}
{% include scripts/misc.html %}
{% include scripts/mathjax.html %}
{% include scripts/analytics.html %}


Use the Visibility property to hide/show any series, notice invisible series are not evaluated, so hiding them will reduce computing time.
From your tool box, drag a new Cartesian control and 3 check boxes


Coffee at JavaJam
| Just Java | Regular house blend, decaffeinated coffee, or flavor of the day Endless Cup $2.00 |
| Cafe au Lait | House blended coffee infused into a smooth, steamed milk Single $2.00 Double $3.00 |
| Iced Cappuccino | Sweetened Espresso Blended with icy-cold milk and served in a chilled glass Single $4.75 Double $5.75 |