public class RabbitsGrassSimulationModel
extends uchicago.src.sim.engine.SimModelImpl
| Modifier and Type | Class and Description |
|---|---|
(package private) class |
RabbitsGrassSimulationModel.GrassInSpace |
(package private) class |
RabbitsGrassSimulationModel.RabbitsInSpace |
| Modifier and Type | Field and Description |
|---|---|
private static int |
BIRTH_THRESHOLD |
private int |
birthThreshold |
private uchicago.src.sim.gui.DisplaySurface |
displaySurf |
private static int |
GRASS_GROWTH_RATE |
private int |
grassGrowthRate |
private static int |
GRID_SIZE |
private int |
gridSize |
private static int |
NUM_RABBITS_INIT |
private int |
numInitGrass |
private int |
numInitRabbits |
private uchicago.src.sim.analysis.OpenSequenceGraph |
plots |
private static int |
RABBIT_ENERGY_INIT |
private int |
rabbitEnergyInit |
private int |
rabbitReproductionEnergy |
private java.util.ArrayList<RabbitsGrassSimulationAgent> |
rabbitsList |
private RabbitsGrassSimulationSpace |
rgsSpace |
private uchicago.src.sim.engine.Schedule |
schedule |
private static int |
TOTAL_GRASS |
| Constructor and Description |
|---|
RabbitsGrassSimulationModel() |
| Modifier and Type | Method and Description |
|---|---|
private void |
addNewRabbit()
Add a new rabbit to this model's rabbit list and rabbit space
|
void |
addRangePropertyDescriptor(java.lang.String s,
int i,
int i1,
int i2)
Add slider for a parameter to GUI.
|
void |
begin()
Initialize the model by building the separate elements that make
up the model
|
void |
buildDisplay()
Build the display elements for this model.
|
void |
buildModel()
Initialize the basic model by creating the space
and populating it with grass and rabbits.
|
void |
buildSchedule()
Create the schedule object(s) that will be executed
during the running of the model
|
private int |
countLivingRabbits()
Get a count of the living rabbits on the model's rabbit list.
|
int |
getBirthThreshold()
Get the value energy level at which rabbits reproduce
|
int |
getGrassGrowthRate()
Get the value of grass growth rate
|
int |
getGridSize()
Get the size of the space in the model
|
java.lang.String[] |
getInitParam()
Get the string array that lists the initialization parameters
for this model
|
java.lang.String |
getName()
Get a String that serves as the name of the model
|
int |
getNumInitGrass()
Get the value of the parameter initializing the total amount
of grass in this model
|
int |
getNumInitRabbits()
Get the parameter indicating the number of rabbits in this model
|
int |
getRabbitEnergyInit()
Get the value of the parameter initializing the initial
energy of the rabbit in this model
|
uchicago.src.sim.engine.Schedule |
getSchedule()
Returns the Schedule object for this model; for use
internally by RePast
|
static void |
main(java.lang.String[] args) |
private void |
reapDeadRabbits()
Remove all dead rabbits from the rabbit list and rabbit space
|
private void |
reproduceRabbits()
Reproduce new rabbits if any of the living ones reached the
birth threshold in energy level
|
void |
setBirthThreshold(int bt)
Set the new value for the energy at which rabbits reproduce
|
void |
setGrassGrowthRate(int ggr)
Set the new value for the grass growth rate
|
void |
setGridSize(int gs)
Set the size of the space in the model
|
void |
setNumInitGrass(int i)
Set the new value for the total amount of grass to be used when
initializing the simulation
|
void |
setNumInitRabbits(int nr)
Set the parameter indicating the initial number of rabbits for this
model.
|
void |
setRabbitEnergyInit(int i)
Set the new value for the initial energy of the rabbit to be used when
initializing the simulation
|
void |
setup()
Tear down any existing pieces of the model and
prepare for a new run.
|
addPropertyListener, addSimEventListener, clearMediaProducers, clearPropertyListeners, fireBooleanPropertyEvent, fireEndSim, fireNumericPropertyEvent, fireObjectPropertyEvent, firePauseSim, fireSimEvent, fireStopSim, fireStringPropertyEvent, generateNewSeed, getController, getMediaProducers, getModelManipulator, getParameterDescriptors, getPropertiesValues, getRngSeed, getTickCount, pause, registerDisplaySurface, registerMediaProducer, removePropertyListener, removeSimEventListener, setController, setRngSeed, stop
private static final int NUM_RABBITS_INIT
private static final int GRID_SIZE
private static final int TOTAL_GRASS
private static final int RABBIT_ENERGY_INIT
private static final int BIRTH_THRESHOLD
private static final int GRASS_GROWTH_RATE
private int numInitRabbits
private int gridSize
private int numInitGrass
private int rabbitEnergyInit
private int birthThreshold
private int grassGrowthRate
private int rabbitReproductionEnergy
private uchicago.src.sim.engine.Schedule schedule
private RabbitsGrassSimulationSpace rgsSpace
private java.util.ArrayList<RabbitsGrassSimulationAgent> rabbitsList
private uchicago.src.sim.gui.DisplaySurface displaySurf
private uchicago.src.sim.analysis.OpenSequenceGraph plots
public static void main(java.lang.String[] args)
public void setup()
public void begin()
public void buildModel()
public void buildSchedule()
public void buildDisplay()
private void addNewRabbit()
private void reapDeadRabbits()
private void reproduceRabbits()
private int countLivingRabbits()
public java.lang.String getName()
public uchicago.src.sim.engine.Schedule getSchedule()
public java.lang.String[] getInitParam()
public int getNumInitRabbits()
public void setNumInitRabbits(int nr)
na
- new value for initial number of rabbitspublic int getGridSize()
public void setGridSize(int gs)
gs
- the size of the space object in the modelpublic int getNumInitGrass()
public void setNumInitGrass(int i)
i
- the new value for the total amount of grasspublic int getRabbitEnergyInit()
public void setRabbitEnergyInit(int i)
i
- the new value for the initial energy of the rabbitpublic int getBirthThreshold()
public void setBirthThreshold(int bt)
i
- the new value for the energy at which rabbits reproducepublic int getGrassGrowthRate()
public void setGrassGrowthRate(int ggr)
i
- the new value for the grass growth ratepublic void addRangePropertyDescriptor(java.lang.String s, int i, int i1, int i2)
s
- the name of the parameteri
- the lower end of the scalei1
- the upper end of the scalei2
- the step size


Cannot present series table: no measure has been selected.
Tip: use the View > Measure menu.
Cannot present series table: no rows are returned by the current horizontal dimension, drilldown or filtering combination.
Tip: use the View menu to select an horizontal dimension.


I’m A Celebrity’s Jacqueline Jossa terrified as she takes on plank in first task
Jacqueline Jossa isn’t adjusting to life in the I’m A Celebrity jungle very well, and the series hasn’t even started yet.
In fact, the EastEnders actress can be seen with her head in her hands as she attempts to take on the first challenge, walking on a shaky-looking plank on top of The Focus Building, in Australia.
Well, to be fair to her, it is 334ft above the ground.
It seems this year’s task is harder than ever, as the famous faces will have to walk the plank – suspended off the edge of the skyscraper, before having to climb down a ladder.

To be fair, if we were Jacqueline, we would’ve been on the flight home before Ant and Dec completed the instructions.
The mum-of-two has been joined by a string of celebrities in this year’s series, including Caitlyn Jenner, Ian Wright, Nadine Coyle and Roman Kemp.
Advertisement Advertisement
However, a psychic has stated that Jac will be the first one to go home – and could walk from the jungle before the first half of the season is complete.
‘Jacqueline is going to find it really difficult being away from home, she’ll feel incredibly homesick,’ Chris Riley told Metro.co.uk.
‘I’m seeing that she may try to walk out of the jungle in the first half of the series, hopefully the team’s morale and friendships will convince her to stay.’
He also explained that he feels the mum-of-two will be an easy target for the bushtucker challenges, adding: ‘The public will vote both her and another female into many of the early trials, a result which will help Jacqueline’s personality to shine through.
‘I’m seeing that Jacqueline has fears, as we all do, although some are quite strong, possibly leading her to experience a panic attack and subsequently pull out of her first or second trial.’
Well, we won’t have long to find out…
I’m A Celebrity…Get Me Out Of Here! returns on 17 November, at 9pm, on ITV.
Got a showbiz story?
If you've got a story, video or pictures get in touch with the Metro.co.uk Entertainment team by emailing us<EMAIL_ADDRESS>calling 020 3615 2145 or by visiting our Submit Stuff page - we'd love to hear from you.


A drag-and-drop kanban board built with React.js, Flux (Alt.js), and Webpack. Data is saved instantaneously to localStorage, even if you close the page mid-edit.
Local Weather
Local Weatherclose
A page that shows the weather in your area, using AngularJS, HTML5 geolocation, and the OpenWeatherMap API.
If it doesn't work on Chrome, try using another browser
Camper News
Camper Newsclose
This is a UI I built for FreeCodeCamp's news section using their API and React.js.
Wikipedia Search
Wikipedia Searchclose
A minimal interface for searching Wikipedia articles, built using WikiMedia API and React.js.


Selecting Constructor
Proper selection of the constructor used for type instantiation is one of the most important aspects of the container operation. When creating an object, the container uses one of the following algorithms to select a constructor it will be using to initialize the object:
Constructor Injection using explicit registration. With this technique, you register the Type and apply an Injection Constructor that specifies the dependencies to the registration. For more information see Constructor Injection
Constructor Annotation. With this technique, you apply attribute to a class constructor that is used for injection. For more information see Annotating Type for Constructor Injection
Automatic Constructor Selection. This technique is used by the Unity container to select a constructor and to satisfy any constructor dependencies defined in parameters of the constructor if no Annotation or Registration exists.
Automatic Constructor Selection
Automatic constructor selection is performed if no other information is available on how to create a Type. Unity uses dynamic, real time algorithm to discover and select a constructor.
The Unity container will try to execute the most complex constructor it can provide with appropriate dependencies. In other words, if the container can resolve and/or inject all parameters of the constructor, it will be selected.
Creating Build Pipeline
Selection process takes place during the first resolution of a Type contract. Unity container employs lazy resolution strategy. It will defer pipeline creation until the contract (RegistrationType and Name) is requested.
The lazy approach allows registrations to proceed at random order and do not require dependencies to be registered before dependents. As long as all of these are available at the time of resolution Unity does not care in what order they were registered.
Constructor Selection Steps
One of the first steps, when creating a pipeline, is a constructor selection. Constructors are selected in the following order:
- If present, use registered Injection Constructor
- If present, annotated with an attribute
- Automatically select constructor
- Get all accessible constructors
- Process constructors in ascending order from most complex to the default
- Filter out restricted constructors
- Loop through parameters and check if
- Is primitive
- Is registered with the container
- Has default value
- Is resolvable type
- Is registered with container
- Is primitive
- Select the first constructor the container can create
The Unity container will select the first successful match and use it as a selection.
Warning
When more than one constructor could be matched at the same time, the order and constructor selection can not be guaranteed.
During normal operation the container does not perform validation.
Note
If Diagnostic extension is enabled, Unity will perform a selection validation and will throw an exception, reporting ambiguous constructors, if more than one constructor can be successfully selected with current configuration.
If no constructor could be selected, the container will throw an exception.
Pipeline retention
Once the pipeline is created, it will be used to satisfy all subsequent requests for that contract. If you need to update or rebuild the pipeline, the contract has to be re-registered.


Inserts the given node into the Template, optionally before the given refNode. In addition to inserting the node into the Template, the Template part indices are updated to match the mutated Template DOM.
Removes the list of nodes from a Template safely. In addition to removing nodes from the Template, the Template part indices are updated to match the mutated Template DOM.
As the template is walked the removal state is tracked and part indices are adjusted as needed.
div div#1 (remove) <-- start removing (removing node is div#1) div div#2 (remove) <-- continue removing (removing node is still div#1) div div <-- stop removing since previous sibling is the removing node (div#1, removed 4 nodes)
Extension to the standard render
method which supports rendering
to ShadowRoots when the ShadyDOM (https://github.com/webcomponents/shadydom)
and ShadyCSS (https://github.com/webcomponents/shadycss) polyfills are used
or when the webcomponentsjs
(https://github.com/webcomponents/webcomponentsjs) polyfill is used.
Adds a scopeName
option which is used to scope element DOM and stylesheets
when native ShadowDOM is unavailable. The scopeName
will be added to
the class attribute of all rendered DOM. In addition, any style elements will
be automatically re-written with this scopeName
selector and moved out
of the rendered DOM and into the document <head>
.
It is common to use this render method in conjunction with a custom element
which renders a shadowRoot. When this is done, typically the element's
localName
should be used as the scopeName
.
In addition to DOM scoping, ShadyCSS also supports a basic shim for css
custom properties (needed only on older browsers like IE11) and a shim for
a deprecated feature called @apply
that supports applying a set of css
custom properties to a given location.
Usage considerations:
Part values in <style>
elements are only applied the first time a given
scopeName
renders. Subsequent changes to parts in style elements will have
no effect. Because of this, parts in style elements should only be used for
values that will never change, for example parts that set scope-wide theme
values or parts which render shared style elements.
Note, due to a limitation of the ShadyDOM polyfill, rendering in a
custom element's constructor
is not supported. Instead rendering should
either done asynchronously, for example at microtask timing (for example
Promise.resolve()
), or be deferred until the first time the element's
connectedCallback
runs.
Usage considerations when using shimmed custom properties or @apply
:
Whenever any dynamic changes are made which affect
css custom properties, ShadyCSS.styleElement(element)
must be called
to update the element. There are two cases when this is needed:
(1) the element is connected to a new parent, (2) a class is added to the
element that causes it to match different custom properties.
To address the first case when rendering a custom element, styleElement
should be called in the element's connectedCallback
.
Shimmed custom properties may only be defined either for an entire
shadowRoot (for example, in a :host
rule) or via a rule that directly
matches an element with a shadowRoot. In other words, instead of flowing from
parent to child as do native css custom properties, shimmed custom properties
flow only from shadowRoots to nested shadowRoots.
When using @apply
mixing css shorthand property names with
non-shorthand names (for example border
and border-width
) is not
supported.
Generated using TypeDoc
Module to add shady DOM/shady CSS polyfill support to lit-html template rendering. See the render method for details.


- d - Variable in class uk.ac.leeds.ee11arw.DbConnect.CoordXYZPair
-
- dbconn - Variable in class uk.ac.leeds.ee11arw.Grapher
-
- dbconn - Variable in class uk.ac.leeds.ee11arw.MapAlgorithm
-
- DbConnect - Class in uk.ac.leeds.ee11arw
-
Class to handle the sqlite database connection and process the data into a usable fashion
- DbConnect() - Constructor for class uk.ac.leeds.ee11arw.DbConnect
-
- DbConnect.CoordXYZ - Class in uk.ac.leeds.ee11arw
-
Inner Class for storing XYZ coordinate data
adapted from stackoverflow.com/questions/11721013/store-x-and-y-coordinates
- DbConnect.CoordXYZPair<Source,Desti> - Class in uk.ac.leeds.ee11arw
-
Class for data encapsulation of source and destination XYZ.
- dbGateCoords(String, String) - Static method in class uk.ac.leeds.ee11arw.DbConnect
-
TODO incomplete in functionality
Method to take in two adjacent systems and return an XYZ pair of the internal gate coordinates
This can then be used in the time calculations to work out approximate time for travel.
- dbpopulateGateDestMap() - Static method in class uk.ac.leeds.ee11arw.DbConnect
-
Method to populate the gateID to gateID destination map and the gateID to SysID for lookup
- dbregionIDs() - Method in class uk.ac.leeds.ee11arw.DbConnect
-
Internal method to populate the system ID to Region ID hash map used for validating systems
in later methods.
- dbSolarConnections() - Method in class uk.ac.leeds.ee11arw.DbConnect
-
Method to set up the hash map for connections(edges) to each solar system node
- dbSolarNames() - Method in class uk.ac.leeds.ee11arw.DbConnect
-
Populates the instance variable hash map of IDs and System names
Populates the SystemIDs and their x,y,z coordinate in a instance variable


BLACK WIDOW A Film Review Copyright Dragan Antulov
In the early 1990s it seemed that Hollywood producers like to make two very distinctive types of thrillers. One, obviously inspired by smashing success of Demme's SILENCE OF THE LAMBS, dealt with demonic yet efficient and hyperintelligent serial killers.  The former one is still popular, the latter one have already reached its peak and turned to straight-for-video land. However, more than a decade ago, and long before such explosion, there was a movie that fused both of those elements, and did it more seriously. It was BLACK WIDOW by Bob Rafelson, that used a very old film noire motives and gave it a completely new and modern twist.
 After collecting inheritance money, she disappears, takes new identity and begins her deadly scheme all over again. Her modus operandi, however, brings the attention of Alexandra Barnes (Debra Winger), workaholic Justice Department investigator. After obsessively tracking down Catherine all over the country, Alexandra finally reaches her at Hawaii. Catherine there wants to pull the same stunt on Paul (Sami Frey), local tycoon. Knowing that she would have to catch Catherine red handed, Alexandra meets her and tries to strike a friendship, not knowing that Catherine has some suspicions too.
One of the things seldom seen in Hollywood is a thriller that has two strong female leads. In case of BLACK WIDOW that shouldn't surprise anyone, because the screenplay writer Ronald Bass prefers strong female characters in his works. In BLACK WIDOW both of the female leads are portrayed as superior to all the men they encounter - Catherine as a skilful sex manipulator that could fool anybody, and Alexandra as hard-working law enforcer always step ahead from her colleagues. Very good performances by Theresa Russell and Debra Winger give their characters a lot of contrast to each other - Catherine is rich, beautiful and cool, and Alexandra is poor, plain and always nervous. But when they finally meet, sparks fly and unusual attraction develops between them, only to be finally and explicitly addressed in one very scene.
Unfortunately, good characterisation don't solve all the problems, and one of the problems in BLACK WIDOW is unconvincing plot. There are too many loose ends and some implausibilities, including totally clich‚d ending scene. Sami Frey as exotic foreigner and potential love interest is also very bland. Other actors are more than fine, although they have limited screen time - especially Nicol Williamson, James Hong and Terry O'Quinn. Photography by Conrad L. Hall is very good, and it has a very good use of beautiful Hawaiian scenery. Musical score by Michael Small with its dark themes is a nice contrast to the visual beauty of film. Editing is good, and Rafelson's direction spotless. However, although definitely worth watching, BLACK WIDOW at the end leaves a bitter taste of missed opportunities.
RATING: 6/10 (++)
Review written on November 3rd 1998
Dragan Antulov a.k.a. Drax Fido: 2:381/100 E-Mail<EMAIL_ADDRESS><EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


If you are still confused or need more information, let's parallel the works of the internet to our vacation metaphor. Take a look at this infographic:


Here you can upload all files: data and documentation. If you have many files or want to maintain a directory structure, it is recommended to make a zip file of all directories and to upload this file. While uploading, the zip file will be unpacked again in its original directory structure. The archive automatically generates a checksum for each file, which will be used for monitoring the file’s integrity. If you wish you can check the checksum yourself.
Note: If the dataset contains one or more files larger than 2 GB, or if you want to deposit privacy sensitive data, it is recommended to send the files to DANS by means of a different file sharing medium such as SURFfilesender. Please contact DANS for more information at<EMAIL_ADDRESS>If you send the files without using EASY, it is still possible to finish the project description in EASY: fill out the metadata and indicate in the field 'Message for the data manager' that you will forward the files. Click 'submit' without uploading any files.


Hi Friend! Welcome to Finland.
This is your ultimate guide how to master the art of being a Finn.
How To Be a Finn is to help the user to explore Finland and it's culture whether you are working, studying, unemployed, refugee, married to a Finn or just passing through this great country, we hope this game will help you.
It has small learning ”classes”, each containing about 8 learning cards with some important information about Finland.
Each class will take about 2-4 minutes of your time.
It’s also about activating people to participate in your local community, find new friends, new hobby, maybe a new job?.
Some classes include tasks that challenge you to do something very typical Finnish. Maybe taste a local food, go to a rock concert, try local sport or sing in a karaoke bar.


Hashedit (aka #edit) is a free, open source visual editor for your website with support for rich text editing, drag-and-drop reordering, image uploading and more. Hashedit provides "just enough" content management while not getting in your way from developing a beautiful website.
Beta coming January 2016. While in development, expect frequent updates.
Built for static sites
Hashedit makes building high performance sites easy by providing you with a plug-and-play editing solution built for static sites.
Build first, bolt-on when ready
Hashedit was built to be flexible enough that you can add it anytime in your development cycle. So, feel free to forgot about Hashedit until you are ready for it.
Built with Express and Node JS
Hashedit is built with Express—the fast, opinionated framework built on Node JS. So, you can be assured it will work well with your existing sites.
Easy to Install
git clone https://github.com/madoublet/hashedit-spark . npm install node hashedit -s http://mysite.com -e<EMAIL_ADDRESS>-p mypassword
Really, thats it.
Accelerate your Development
Our store provides you with a set of ready-to-go websites and powerful development kits that are production ready. Learn more
Built Small
Hashedit has been intentionally engineered to be small. Not only is the filesize (<100kb) small, but the feature set is small, as well. Our goal is to build a simple foundation that provides "just enough" content management while enabling you to easily extend the app to meet your needs.
Actually Easy Plugins
Wouldn't it be great if it took minutes, not hours to build a plugin? With Hashedit, you just build a quick JS object containing the HTML you want rendered, and you are done. Really. It is actually easy. Learn more
Bring your own Framework
Hashedit was built to work great with any framework. So, you can use Bootstrap, Foundation, MDL (Material Design Lite), or no framework at all with Hashedit.


Tri-tip andouille kevin venison corned beef flank jowl salami. Landjaeger swine bresaola, tenderloin pork meatloaf short ribs sausage doner leberkas t-bone drumstick tongue venison beef ribs. Venison pork loin filet mignon ham hock kevin. Pig bresaola beef venison porchetta corned beef chuck salami ground round cupim
An accordion for general full width use & one that only appears on designated mobile breakpoint size.
Just resize your browser to see it in action.
You can use one of the three js files included, to either:
- Accordion all sizes accordion_1.js
- Accordion on mobile only accordion_2.js
- Both together accordion_3.js
For the purpose of this demo this page loads 'accordion_3.js'.
Title-1 & trigger, all sizes
Title-2 & trigger, all sizes
Tri-tip andouille kevin venison corned beef flank jowl salami. Landjaeger swine bresaola, tenderloin pork meatloaf short ribs sausage doner leberkas t-bone drumstick tongue venison beef ribs. Venison pork loin filet mignon ham hock kevin. Pig bresaola beef venison porchetta corned beef chuck salami ground round cupim


Portfolio
RPG Game
A role playing game designed by me and built with Javascript.
Trivia Game
A trivia game designed by me and built with Javascript.
Info Widget
An info widget designed by me and built with Javascript.
Rock Paper Scissors
A rock paper scissors game designed by me and built with Javascript.


List
section apply to byline list too. Use
[byline]
input on the fn-list
and you will get byline mode of fn-list. Then you'll have
access to fnListItemByline
directive, which will help you to set second line of text, under title
section of fn-list-item
.


Your browser does not support HTML5 Canvas.
Back to Home Page
Back to Canvas Text Prepare
Proceed to Canvas Text Create


Navbar
Home
Link
Dropdown
Action
Another action
Something else here
Disabled
Search
Cube
Cube
Cuboid
Trapezoid
Pill
Circle
Cylinder
Cone
Truncated Cone
Extrude
Extrude 3 points
Extrude 4 points
Extrude 5 points
Extrude 6 points
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Extrude 8 points
Prism
Triangular Prism
Rectangular Prism
Pentagonal Prism
Hexagonal Prism
Seven Prism
Eight Prism
Pyramid
Triangular Pyramid
Rectangular Pyramid
Pentagonal Pyramid
Hexagonal Pyramid
Seven Pyramid
Eight Pyramid


| # | Date | IQSet Name | Teacher Name | Group Name | Action |
|---|---|---|---|---|---|
| 1 | 1/1/2013 | History: Roman Empire | Teacher Claire | Olive Elementary 5th Grade | View |
| # | Date | IQ Session Name | Teacher Name | Group Name | Action |
|---|---|---|---|---|---|
| 1 | 1/1/2013 | History: Roman Empire | Teacher Claire | Olive Elementary 5th Grade | View |
Teacher Name: Mrs. Jones
Group Name: 5th Grade Section 1
# of Students: 5th Grade Section 1
# of Questions: 5th Grade Section 1
# of Posted Results: 5th Grade Section 1
IQSet ID:


Welcome,
{{name}} {{rating}}
{% if curr %}
No. of pending requests
{{count.countp}}
No. of completed requests
{{count.countc}}
No. of sent requests
{{count.counts}}


Javascript Frameworks
I've noticed that many Rails developers are supplanting their Rails knowledge with some Javascript knowledge in order to best accomodate the full-stack. With all the Javascript frameworks out there, it's hard to figure out which to start off with. As I have some experience with semantic Javascript already, I decided to go with Backbone.js
MV
Unlike the other heavy MV* JS frameworks like Angular and Ember and it's lighter brother React.js, Backbone is only the model-view. It's somewhat of the in-between in terms of Javascript frameworks.
Rails + Backbone.
I've decided on creating applications that use a Rails backend with a Backbone.js frontend and then eventually migrating over to an entirely JS stack using a variation of the MEAN stack, but without the Angular. That way I can quickly pick up the other frameworks as necessary. I'll try to keep a log of my journey.


ENABLE_EMPTY
Allows the Epoll.wait and the Epoll.uWait functions to be called with the EID not subscribed to any socket.


TaxQuery
class TaxQuery extends TaxQuery
Skeleton subclass for performing query and update operations on the 'tax' table.
You should add additional methods to this class to meet the application requirements. This class will only be generated as long as it does not already exist in the output directory.
Methods
Initializes internal state of \Thelia\Model\Base\TaxQuery object.
Returns a new ChildTaxQuery object.
Find object by primary key.
Find objects by primary key
$objs = $c->findPks(array(12, 56, 832), $con);
Filter the query on the id column
Filter the query on the type column
Filter the query on the serialized_requirements column
Filter the query on the created_at column
Filter the query on the updated_at column
Filter the query by a related \Thelia\Model\TaxRuleCountry object
Adds a JOIN clause to the query using the TaxRuleCountry relation
Use the TaxRuleCountry relation TaxRuleCountry object
Filter the query by a related \Thelia\Model\TaxI18n object
Adds a JOIN clause to the query using the TaxI18n relation
Use the TaxI18n relation TaxI18n object
Deletes all rows from the tax table.
Performs a DELETE on the database, given a ChildTax or Criteria object OR a primary key value.
Adds a JOIN clause to the query using the i18n relation
Adds a JOIN clause to the query and hydrates the related I18n object.
Use the I18n relation query object
Order by the serialized_requirements column
Group by the serialized_requirements column
Adds a LEFT JOIN clause to the query using the TaxRuleCountry relation
Adds a RIGHT JOIN clause to the query using the TaxRuleCountry relation
Adds a INNER JOIN clause to the query using the TaxRuleCountry relation
Adds a LEFT JOIN clause to the query using the TaxI18n relation
Adds a RIGHT JOIN clause to the query using the TaxI18n relation
Adds a INNER JOIN clause to the query using the TaxI18n relation
Return the first ChildTax matching the query
Return the first ChildTax matching the query, or a new ChildTax object populated from the query conditions when no match is found
Return the first ChildTax filtered by the type column
Return the first ChildTax filtered by the serialized_requirements column
Return the first ChildTax filtered by the created_at column
Return the first ChildTax filtered by the updated_at column
Return ChildTax objects filtered by the serialized_requirements column
Return ChildTax objects filtered by the created_at column
Return ChildTax objects filtered by the updated_at column
Details
in
TaxQuery at line 75
__construct(
string $dbName = 'thelia',
string $modelName = '\\Thelia\\Model\\Tax',
string $modelAlias = null)
Initializes internal state of \Thelia\Model\Base\TaxQuery object.
in
TaxQuery at line 88
static
TaxQuery
create(
string $modelAlias = null,
Criteria $criteria = null)
Returns a new ChildTaxQuery object.
in
TaxQuery at line 118
Tax|array|mixed
findPk(
mixed $key,
ConnectionInterface $con = null)
Find object by primary key.
Propel uses the instance pool to skip the database if the object exists. Go fast if the query is untouched.
$obj = $c->findPk(12, $con);
in
TaxQuery at line 200
ObjectCollection|array|mixed
findPks(
array $keys,
ConnectionInterface $con = null)
Find objects by primary key
$objs = $c->findPks(array(12, 56, 832), $con);
in
TaxQuery at line 234
TaxQuery
filterByPrimaryKeys(
array $keys)
Filter the query by a list of primary keys
in
TaxQuery at line 258
TaxQuery
filterById(
mixed $id = null,
string $comparison = null)
Filter the query on the id column
Example usage:
$query->filterById(1234); // WHERE id = 1234
$query->filterById(array(12, 34)); // WHERE id IN (12, 34)
$query->filterById(array('min' => 12)); // WHERE id > 12
in
TaxQuery at line 296
TaxQuery
filterByType(
string $type = null,
string $comparison = null)
Filter the query on the type column
Example usage:
$query->filterByType('fooValue'); // WHERE type = 'fooValue'
$query->filterByType('%fooValue%'); // WHERE type LIKE '%fooValue%'
in
TaxQuery at line 325
TaxQuery
filterBySerializedRequirements(
string $serializedRequirements = null,
string $comparison = null)
Filter the query on the serialized_requirements column
Example usage:
$query->filterBySerializedRequirements('fooValue'); // WHERE serializedrequirements = 'fooValue'
$query->filterBySerializedRequirements('%fooValue%'); // WHERE serializedrequirements LIKE '%fooValue%'
in
TaxQuery at line 359
TaxQuery
filterByCreatedAt(
mixed $createdAt = null,
string $comparison = null)
Filter the query on the created_at column
Example usage:
$query->filterByCreatedAt('2011-03-14'); // WHERE createdat = '2011-03-14'
$query->filterByCreatedAt('now'); // WHERE createdat = '2011-03-14'
$query->filterByCreatedAt(array('max' => 'yesterday')); // WHERE created_at > '2011-03-13'
in
TaxQuery at line 402
TaxQuery
filterByUpdatedAt(
mixed $updatedAt = null,
string $comparison = null)
Filter the query on the updated_at column
Example usage:
$query->filterByUpdatedAt('2011-03-14'); // WHERE updatedat = '2011-03-14'
$query->filterByUpdatedAt('now'); // WHERE updatedat = '2011-03-14'
$query->filterByUpdatedAt(array('max' => 'yesterday')); // WHERE updated_at > '2011-03-13'
in
TaxQuery at line 433
TaxQuery
filterByTaxRuleCountry(
TaxRuleCountry|ObjectCollection $taxRuleCountry,
string $comparison = null)
Filter the query by a related \Thelia\Model\TaxRuleCountry object
in
TaxQuery at line 456
TaxQuery
joinTaxRuleCountry(
string $relationAlias = null,
string $joinType = Criteria::INNER_JOIN)
Adds a JOIN clause to the query using the TaxRuleCountry relation
in
TaxQuery at line 491
TaxRuleCountryQuery
useTaxRuleCountryQuery(
string $relationAlias = null,
string $joinType = Criteria::INNER_JOIN)
Use the TaxRuleCountry relation TaxRuleCountry object
in
TaxQuery at line 506
TaxQuery
filterByTaxI18n(
TaxI18n|ObjectCollection $taxI18n,
string $comparison = null)
Filter the query by a related \Thelia\Model\TaxI18n object
in
TaxQuery at line 529
TaxQuery
joinTaxI18n(
string $relationAlias = null,
string $joinType = 'LEFT JOIN')
Adds a JOIN clause to the query using the TaxI18n relation
in
TaxQuery at line 564
TaxI18nQuery
useTaxI18nQuery(
string $relationAlias = null,
string $joinType = 'LEFT JOIN')
Use the TaxI18n relation TaxI18n object
in
TaxQuery at line 593
int
doDeleteAll(
ConnectionInterface $con = null)
Deletes all rows from the tax table.
in
TaxQuery at line 630
int
delete(
ConnectionInterface $con = null)
Performs a DELETE on the database, given a ChildTax or Criteria object OR a primary key value.
in
TaxQuery at line 739
TaxQuery
joinI18n(
string $locale = 'en_US',
string $relationAlias = null,
string $joinType = Criteria::LEFT_JOIN)
Adds a JOIN clause to the query using the i18n relation
in
TaxQuery at line 757
TaxQuery
joinWithI18n(
string $locale = 'en_US',
string $joinType = Criteria::LEFT_JOIN)
Adds a JOIN clause to the query and hydrates the related I18n object.
Shortcut for $c->joinI18n($locale)->with()
in
TaxQuery at line 778
TaxI18nQuery
useI18nQuery(
string $locale = 'en_US',
string $relationAlias = null,
string $joinType = Criteria::LEFT_JOIN)
Use the I18n relation query object
in
TaxQuery at line 65
ChildTaxQuery
orderById($order = Criteria::ASC)
Order by the id column
in
TaxQuery at line 65
ChildTaxQuery
orderByType($order = Criteria::ASC)
Order by the type column
in
TaxQuery at line 65
ChildTaxQuery
orderBySerializedRequirements($order = Criteria::ASC)
Order by the serialized_requirements column
in
TaxQuery at line 65
ChildTaxQuery
orderByCreatedAt($order = Criteria::ASC)
Order by the created_at column
in
TaxQuery at line 65
ChildTaxQuery
orderByUpdatedAt($order = Criteria::ASC)
Order by the updated_at column
in
TaxQuery at line 65
ChildTaxQuery
groupById()
Group by the id column
in
TaxQuery at line 65
ChildTaxQuery
groupByType()
Group by the type column
in
TaxQuery at line 65
ChildTaxQuery
groupBySerializedRequirements()
Group by the serialized_requirements column
in
TaxQuery at line 65
ChildTaxQuery
groupByCreatedAt()
Group by the created_at column
in
TaxQuery at line 65
ChildTaxQuery
groupByUpdatedAt()
Group by the updated_at column
in
TaxQuery at line 65
ChildTaxQuery
leftJoin($relation)
Adds a LEFT JOIN clause to the query
in
TaxQuery at line 65
ChildTaxQuery
rightJoin($relation)
Adds a RIGHT JOIN clause to the query
in
TaxQuery at line 65
ChildTaxQuery
innerJoin($relation)
Adds a INNER JOIN clause to the query
in
TaxQuery at line 65
ChildTaxQuery
leftJoinTaxRuleCountry($relationAlias = null)
Adds a LEFT JOIN clause to the query using the TaxRuleCountry relation
in
TaxQuery at line 65
ChildTaxQuery
rightJoinTaxRuleCountry($relationAlias = null)
Adds a RIGHT JOIN clause to the query using the TaxRuleCountry relation
in
TaxQuery at line 65
ChildTaxQuery
innerJoinTaxRuleCountry($relationAlias = null)
Adds a INNER JOIN clause to the query using the TaxRuleCountry relation
in
TaxQuery at line 65
ChildTaxQuery
leftJoinTaxI18n($relationAlias = null)
Adds a LEFT JOIN clause to the query using the TaxI18n relation
in
TaxQuery at line 65
ChildTaxQuery
rightJoinTaxI18n($relationAlias = null)
Adds a RIGHT JOIN clause to the query using the TaxI18n relation
in
TaxQuery at line 65
ChildTaxQuery
innerJoinTaxI18n($relationAlias = null)
Adds a INNER JOIN clause to the query using the TaxI18n relation
in
TaxQuery at line 65
ChildTax
findOne(
ConnectionInterface $con = null)
Return the first ChildTax matching the query
in
TaxQuery at line 65
ChildTax
findOneOrCreate(
ConnectionInterface $con = null)
Return the first ChildTax matching the query, or a new ChildTax object populated from the query conditions when no match is found
in
TaxQuery at line 65
ChildTax
findOneById(
int $id)
Return the first ChildTax filtered by the id column
in
TaxQuery at line 65
ChildTax
findOneByType(
string $type)
Return the first ChildTax filtered by the type column
in
TaxQuery at line 65
ChildTax
findOneBySerializedRequirements(
string $serialized_requirements)
Return the first ChildTax filtered by the serialized_requirements column
in
TaxQuery at line 65
ChildTax
findOneByCreatedAt(
string $created_at)
Return the first ChildTax filtered by the created_at column
in
TaxQuery at line 65
ChildTax
findOneByUpdatedAt(
string $updated_at)
Return the first ChildTax filtered by the updated_at column
in
TaxQuery at line 65
array
findById(
int $id)
Return ChildTax objects filtered by the id column
in
TaxQuery at line 65
array
findByType(
string $type)
Return ChildTax objects filtered by the type column
in
TaxQuery at line 65
array
findBySerializedRequirements(
string $serialized_requirements)
Return ChildTax objects filtered by the serialized_requirements column
in
TaxQuery at line 65
array
findByCreatedAt(
string $created_at)
Return ChildTax objects filtered by the created_at column
in
TaxQuery at line 65
array
findByUpdatedAt(
string $updated_at)
Return ChildTax objects filtered by the updated_at column


WebDevExample
To make it work:
- In jsHelper folder, install dependencies with `yarn` or `npm`, start the node js application
- Start the IWebDev server through SBT
- Open this html file in a browser, you should see it connect to the WebDev Servers websocket
- Start continous compilation of this project with ~pushToClient
Whenever files in this project has changed, the newly compiled / fastOptJS'ed javascript is pushed to this
client, and the javascript dom node is replaced with the new javascript
To test the CSS stylesheet update, use the ammonite script located in the CSS folder.


σ({{starting_integer}}, {{sequence_length}})
As products of powers of prime factors:
{% for element in reduced_result %}
{% for factor, power in element.items %}
{% if not forloop.counter == 1 %}*{% endif %}
{{factor}}
{{power}}
{% endfor %}
{% if forloop.counter == 1 %}
----------------------------------------------------
{% endif %}
{% endfor %}
As Integers:
{{numerator}}
----
{{denominator}}
As an approximate decimal: {{as_decimal}}
Lowest Common Multiple of {{candidates}}: {{nice_lcm}}
Process Details
(Took: {{how_long}})
(Projected CPU Burden: {{burden}})
(Burden per second (big is good, below 2000 is choking): {{burden_time}} {% if burden_time < 2000 %}Ouch! Please don't do that again.{% endif %})


First Class Functions
Typically first class functions are defined as a programming entity that can be :
- Created at runtime
- Assigned to a variable or element in a data structure
- Passed as an argument
- Returned as the result of a function
By this definition, looking at how Python treats all functions, all functions are first class within Python.
Below we’ll see examples of exactly how this looks.
Treating a function like an object
def factorial(n):
"""
Returns n! or n(factorial)
e.g 5! = 5 * 4 * 3 * 2
"""
return 1 if n < 2 else n * factorial(n-1)
5) factorial(
120
First class analysis
We can show the first class nature of this function object using a few examples.
We can assign the function to a variable, which will invoke the function when calling that variable.
= factorial
fact 5) fact(
120
We can also use the map function, and pass our function as the first argument, allowing that function to be evaluated against the second argument, which is an iterable. Allowing this function to be applied in a successive fashion to all elements of this iterable.
map(factorial, range(10))
[1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880]
Higher-Order Functions
A higher order function is a bit….meta. It can take, as an argument, a function and then returns a function as a result.
The map()
example used above is a great example of this.
The built-in sorted()
function is another great example of this, within Python. We can pass it an iterable, along with a key
that can then be applied in succession to the items in the list.
= ['eggplant', 'carrots', 'celery',
food 'potatoes', 'tomatoes', 'rhubarb',
'strawberry', 'blueberry', 'raspberry',
'banana', 'cherry']
print(sorted(food, key=len))
['celery', 'banana', 'cherry', 'carrots', 'rhubarb', 'eggplant', 'potatoes', 'tomatoes', 'blueberry', 'raspberry', 'strawberry']
Any single argument function can be used in the key argument of the sorted()
method.
as a trivial example, we may want to use the reversed order of the characters to sort of words, as this will cause certain clustering of character strings together, such as -berry, and -toes.
def reverse(word):
'''
Reverse the order of the letters in a given string
'''
return word[::-1]
print(sorted(food, key=reverse))
['banana', 'rhubarb', 'tomatoes', 'potatoes', 'carrots', 'eggplant', 'celery', 'blueberry', 'raspberry', 'strawberry', 'cherry']
Replacements for map and filter
Map, filter, and reduce are typically offered in functional languages as higher order functions. However, the introduction of list comprehensions and generator expressions have downplayed the value of the map and filter functions, as listcomp’s and genexp’s combine the job of map
and filter
.
# Build a list of factorials from 0! to 5!
list(map(fact, range(6)))
[1, 1, 2, 6, 24, 120]
# Build a list of factorials from 0! to 5!
# but using list comprehension
for n in range(6)] [fact(n)
[1, 1, 2, 6, 24, 120]
# Build a list of factorials of odd numbers up to 5!, using `map` and `filter`
list(map(factorial, filter(lambda n: n % 2, range(6))))
[1, 6, 120]
We can see above that with the map
and filter
functions, we needed to use a lambda
function.
Using a list comprehension can remove this requirement, and concatenate the operations.
# Build a list of factorials of odd numbers up to 5!, using list comprehension
for n in range(6) if n % 2] [factorial(n)
[1, 6, 120]
Anonymous Functions
The example above, where we’ve utilized map
and filter
combined with a lambda
function leads us into our next example.
The lambda
keyword created an anonymous function within a Python expression. However the syntax limits the lambda
to be pure expressions. This means that the body of a lambda
function can’t use other Python statements such as while
or try
, etc.
These are typically limited in their use because of the lack of the ability to use more complex control structures within the lambda
functions. This can lead to unreadable or unworkable results.
However, they can still prove useful in certain contexts, such as list arguments.
= ['eggplant', 'carrots', 'celery',
food 'potatoes', 'tomatoes', 'rhubarb',
'strawberry', 'blueberry', 'raspberry',
'banana', 'cherry']
print(sorted(food, key=lambda word: word[::-1]))
['banana', 'rhubarb', 'tomatoes', 'potatoes', 'carrots', 'eggplant', 'celery', 'blueberry', 'raspberry', 'strawberry', 'cherry']
References
- Fluent Python, Ramalho Purchase Link


Experience {{player.experience}}
Attack: {{player.attackLvl}}, Strength: {{player.strengthLvl}}, Defense: {{player.defenseLvl}}
Skill Points: {{player.skillPoints}}
Attack: {{player.attackLvl}}
Strength: {{player.strengthLvl}}
Defense: {{player.defenseLvl}}
Attack Roll: {{atkRoll}} HIT! MISSED!
Damage Roll: {{dmgRoll}}
Damage Done: {{damageDone}}
Enemy HP: {{currentEnemy.health}}
{{item.name}}
Main Hand: {{player.mainHand.name}}
Off Hand: {{player.offHand.name}}
Head Slot: {{player.headSlot.name}}
Chest Slot: {{player.chestSlot.name}}
Leg Slot: {{player.legSlot.name}}


Dennis Pavlik's WebSite
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| compound=(Compound) |
|---|
| Diallyl sulfide |
| Methyl allyl disulfide |
| Dimethyl trisulfide |
| Diallyl disulfide |
| Diallyl tetrasulfide |
| Unknown |
| Methyl allyl trisulfide |
| 3-vinyl-[4H]-1,2-dithiin |
| Allyl trisulfide |
| Unknown |
| 1,4-Dimethyl tetrasulfide |
| Diallyl trisulfide |
| Unknown |
| Unknown |


Warrior's Grave:
The only hope is for you to become an Elrokian warrior, the one destined to wield Gazkh!
But wait! Gazkh is no toy to be picked up on a whim. It is as dangerous as a serpent, as powerful as fire itself! You must prove yourself worthy to be its owner.
Stranger, I see that you are already wise and brave. But that alone is not enough. If you wish to travel this path, there is one more task you must perform.
"What is it?"


CS109a: Introduction to Data Science
Fall 2020
Pavlos Protopapas, Kevin A. Rader, and Chris Tanner
Additional Instructor: Eleni Kaxiras
Welcome to CS109a/STAT121a/AC209a, also offered by the DCE as CSCI E-109a, Introduction to Data Science. This course is the first half of a one‐year course to data science. We will focus on the analysis of data to perform predictions using statistical and machine learning methods. Topics include data scraping, data management, data visualization, regression and classification methods, and deep neural networks. You will get ample practice through weekly homework assignments. The class material integrates the five key facets of an investigation using data:
1. data collection ‐ data wrangling, cleaning, and sampling to get a suitable data set
2. data management ‐ accessing data quickly and reliably
3. exploratory data analysis – generating hypotheses and building intuition
4. prediction or statistical learning
5. communication – summarizing results through visualization, stories, and interpretable summaries
Only one of CS 109a, AC 209a, or Stat 121a can be taken for credit. Students who have previously taken CS 109, AC 209, or Stat 121 cannot take CS 109a, AC 209a, or Stat 121a for credit.
Important Dates: Tuesday 9/8 - HW1 released Wednesday 9/9 - HW0 due at 11:59pm EST Thursday 9/10 - 'Study Break' at 8:30pm EST Friday 9/11 - 'Study Break' at 10:15am EST Friday 9/11 - Sections start (1:30pm EST) See syllabus/calendar for weekly times
Helpline<EMAIL_ADDRESS>Lectures: Mon , Wed, & Fri 9:00‐10:15 am & 3:00-4:14 pm (identical material in a single day)
Sections: Fri 1:30-2:45 pm & Mon 8:30-9:45 pm (identical material) [starts 9/11]
Advanced Sections: Wed 12pm [starts 9/23]
Office Hours: TBD
Course material can be viewed in the public GitHub repository.


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| Interface | Description |
|---|---|
| II2cDevice | Deprecated
Code that previously used II2cDevice should use I2cDevice instead.
|
| IOpModeStateTransitionEvents |
An interface used to receive notifications about various OpMode state transitions
|
| Util.IAction<T> | |
| Util.IFuncArg<T,U> |
| Class | Description |
|---|---|
| AdaFruitBNO055IMU |
Instances of AdaFruitBNO055IMU provide API access to an
AdaFruit Absolute Orientation Sensor that
is attached to a Modern Robotics Core Device Interface module.
|
| AdaFruitTCS34725ColorSensor |
Note: this is not yet used
http://adafru.it/1334
https://www.adafruit.com/products/1334?&main_page=product_info&products_id=1334
https://github.com/adafruit/Adafruit_TCS34725
|
| AdaFruitTCS34725ColorSensor.Parameters | |
| AnnotatedOpModeRegistrar |
Call AnnotatedOpModeRegistrar.register(OpModeManager) from FtcOpModeRegister.register()
in order to automatically register OpMode classes that you have annotated with @Autonomous
or @TeleOp.
|
| I2cDeviceOnI2cDeviceController | Deprecated
Code that previously used I2cDeviceOnI2cDeviceController should use I2cDeviceImpl instead
|
| I2cDeviceReplacementHelper<TARGET> |
A helper object that assists in managing the creation of replacement
hardware implementations for I2C-based objects.
|
| LegacyOrModernColorSensor |
This class implements a driver for either a HiTechnic color sensor or a
Modern Robotics color sensor.
|
| ManualResetEvent |
A class that implements a gating semantic similar to a Windows manual reset event
|
| MemberUtil |
Skullduggery we wish we didn't have to do.
|
| OpModeLoopCounter |
A simple little class that counts loop() calls for non-loop() opmodes.
|
| RobotStateTransitionNotifier |
The point of all this is to hook into the robot controller runtime in order to
get access to their motor controller shutdown and stop logic.
|
| SwerveFtcEventLoop |
This class provides hooking services that we use to provide contextual
information to opmode code.
|
| SwerveOpModeManager | |
| SwerveThreadContext |
SwerveThreadContext maintains thread-specific context for the Swerve Library
|
| SynchronousOpModeHardwareFactory |
SynchronousOpModeHardwareFactory processes an SDK-provided hardware map so as to allow
SynchronousOpMode to function better.
|
| Util |
Various internal utilities that assist us.
|
| Enum | Description |
|---|---|
| AdaFruitTCS34725ColorSensor.GAIN | |
| AdaFruitTCS34725ColorSensor.INTEGRATION_TIME |


Carbon Footprint Calculator
About
Cycle paths
Clusters
-- Please select an user --
×
About Carbon Footprint Calculator
Authors
Alexandre Bonhomme
Christophe Ribeiro
Nicolas Haderer
Partners
{{ carbonFootprint }}
{{ carbonFootprintPerKm }}
Get the application for your device:
We're sorry!
There is no ride available for this user in this interval of day.
Reports
#
Transport
Distance (km)
Aggregated rides
Total emission (kg eq. CO₂)
{{ ride.type }}
{{ ride.distance.toFixed(3) }}
{{ ride.numberOfRides }}
{{ ride.emission.toFixed(1) }}


Setup:
    ✅   Upload this page to your Wi-Fi module.
    ✅   Open this page from http://your-wi-fi-module's-ip/files/page-filename.html.
    ✅   Run "Program Filename.bs2" with your BASIC Stamp 2 module.
    🕮   More info at http://learn.parallax.com/pbasic-wx-wi-fi.html.
Page Title
Heading
Paragraph


This is some text.
This is a paragraph.
And another paragraph.
This is a bit section text.
This is a subsection.
And a second subsection.
This is some more section text.
This is a subsection in the second section.
And a second subsection in the second section.
| Heading 1 | Heading 2 |
|---|---|
| Row 1 | Row 1 |
| Row 2 | Row 2 |
| Row 3 | Row 3 |


java
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
Overview
This is the java module. It allows to install Java OpenJDK and configure the default java alternative.
Module Description
The module provides classes and defines to install Java OpenJDK and configure the java alternative on Debian and RedHat family distributions. It allows to install multiple Java versions on the same node. It allows to install java 8 even if it is not in the standard repository in Ubuntu 12.04 and 14.04 via ppa.
Setup
What java affects
The module install the OpenJDK package from the repositories and set up the alternative system for the java command.
If hiera defines a value for the parameter
java::java_default_version
the alternative system link for the
command java is set to manual mode according to specified version.
Otherwise it is left as it is.
In case java 8 installation is required on Ubuntu 12.04 or Ubuntu 14.04 the
repository ppa:openjdk-r/ppa
is added.
Setup Requirements
The module has no special requirements.
Beginning with java
The module provides three classes to install Java OpenJDK 6, 7 and 8 respectively. This is done, for example, by declarations as the following:
include java_7
Usage
It is possible to install multiple versions of Java on a single node and to specify via hiera the default java to be set in the alternative system. An example hiera (JSON) declaration for a node could be as follows:
{
"classes" : [
"java::java_6",
"java::java_7"
],
"java::java_default_version" : "6"
}
Reference
Classes
Public Classes
-
java::java_6: Installs open-jdk-6.
-
java::java_7: Installs open-jdk-7.
-
java::java_8: Installs open-jdk-8.
Defines
Public Defines
-
java::java: Install a specific version of java jdk and possibly sets update-alternative default
Private Defines
-
java::java_install_config: Installs a specific java open-jdk package and configures the update-alternative default java
java::java_6
Installs OpenJDK-6 from the repositories.
java::java_7
Installs OpenJDK-7 from the repositories.
java::java_8
Installs OpenJDK-8 from the repositories.
java::java
Install a specific version of java jdk and possibly sets update-alternative
default. If hiera defines a value for the parameter
java::java_default_version
on the target node the command
update-alternatives
is issued to set the default java
accordingly.
Declares all other defines in the java module needed for installing Java.
Currently, these consists of java::install
, and
java::config
.
Parameters
java_version
Specifies the java version to install. Valid options: '6', '7' or '8'. Defaults to the resource title.
java_default_version
Specifies the default java in case multiple versions are installed. Valid
options: '6', '7' or '8'. Defaults to the hiera
defined key java::java_default_version
.
Limitations
At the moment the module targets only OpenJDK 6, 7 and 8 on Debian, Ubuntu, RedHat and CentOS platforms. Specifically, it was tested on Ubuntu 12.04, 14.04, 16.04 and CentOS 6.6 distributions; although probably it will work also on different versions.
Development
If you need some feature please send me a (pull) request and send me an email at: dsestero 'at' gmail 'dot' com.


Fluffy! Did you know that Fluffy's mom was a unicorn and dad was a rainbow? It's true! Cuteness is woven into Fluffy's DNA.


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{% extends "layout/base.html" %} {% block title %} | About {% endblock %} {% block content %}
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Deleting an Object
You can delete an object in several different ways:
NeoMem will check to see if there are any links to the object you are trying to delete. If there are, you will be asked if you want to remove the links before you will be able to delete the object.

Warning: Once you delete an object, there is no way to restore it, so use this carefully!
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Hey 👋 I'm Pankaj.
A Full-Stack Developer
A passionate & self-taught computer science engineer who has built and scaled systems, web services and platforms from scratch.
My passion includes handling complex and interesting system design problems. I like to read, write and learn about software engineering
Who am I?
I am working as a Software Developer at Paisabazaar.com in Credit Bureau vertical.
I run a blog where I write about system design, backend engineering and intresting computer science challanges.
Some of my blogs -
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public class NurAccessoryBattery
extends java.lang.Object
| Modifier and Type | Field and Description |
|---|---|
static int |
ACC_EXT_GET_BATT
Get battery level and related information sub-command.
|
static int |
ACC_EXT_GET_BATT_INFO
Battery information ("extended information").
|
int |
capacity
Battery capacity in mAh.
|
boolean |
charging
True if the device is currently charging the battery.
|
int |
current
Current currently drawn in mA.
|
int |
percentage
Battery level in as 0...100%.
|
static int |
SZ_BATTERY_REPLY
5 signed 16-bit values (byte + 4 x uint16_t.
|
int |
voltage
Current battery voltage in mV.
|
| Constructor and Description |
|---|
NurAccessoryBattery() |
| Modifier and Type | Method and Description |
|---|---|
static NurAccessoryBattery |
deserializeBatteryReply(byte[] source)
Deserialize a battery reply from the device.
|
java.lang.String |
getCapacityString()
Get battery capacity as a string.
|
java.lang.String |
getCurrentString()
Get battery's current draw as a string.
|
java.lang.String |
getPercentageString() |
static byte[] |
getQueryCommand()
Battery information get -command.
|
java.lang.String |
getVoltageString()
Return battery voltage as a string.
|
public static final int SZ_BATTERY_REPLY
public static final int ACC_EXT_GET_BATT
public static final int ACC_EXT_GET_BATT_INFO
public int percentage
public int voltage
public int current
public int capacity
public boolean charging
public static NurAccessoryBattery deserializeBatteryReply(byte[] source) throws java.lang.Exception
source
- Reply bytes from the module.java.lang.Exception
- Can throw I/O, timeout or API related exception based on the occurred error.public static byte[] getQueryCommand()
public java.lang.String getPercentageString()
public java.lang.String getVoltageString()
public java.lang.String getCurrentString()
public java.lang.String getCapacityString()


| Space Used Yesterday | Estimated Days Until Full | Estimated Full Date |
|---|---|---|
| 141.54 GB | 167 | 01 February 2022 |
| HRRR CONUS Grib2 | HRRR Alaska Grib2 | |
|---|---|---|
| sfc | 92.49 | 26.05 |
| prs | 9.67 | 0.00 |
| Total | 102.16 GB | 26.05 GB |
| GOES-17 Satellite Products | |
|---|---|
| ABI-L2-MCMIPC | 12.42 |
| GLM-L2-LCFA | 0.90 |
| Total | 13.32 GB |


Amanah deputy president says party elections going on smoothly, no attempts to oust any leaders
TASEK GELUGOR, 23 Nov — The Parti Amanah Negara (Amanah) party election, which is being held in several states, is going smoothly and harmoniously with no issues or attempts aimed at ousting any leader, said its deputy president Datuk Seri Salahuddin Ayub.
“I have not heard of any issue to oust any leader in this party election as it is going on smoothly and in harmony. We have now reached the state level. Tomorrow (today) it will be in Perak and Penang. Johor, Kedah, Kelantan, Terengganu have completed theirs and all went well,” he added.
He told this to reporters after a dinner and presentation of aid to the poor and needy in Tasek Gelugor at Taman Koskam here last night when asked on allegations of attempts to oust certain leaders in the party.
On claims that Amanah is trying to implement the “cai” system in the party elections, Salahuddin said party grassroots members should choose those who can discharge responsibilities entrusted upon them as leaders.
“Do not choose based on the cai (list) and alhamdulillah, from what I see, those elected are based on their capability, merit, experience and track record. I think that’s a healthy practice,” he added. — Bernama


Hey there !
You can both type your messages, or use the microphone button to record yourself instead. So, as you go through this story, remember to communicate with Sally because she can be of great help!
Also, whenever you solve a task, please remember provide your answer to Sally so she can tell you whether your answers are correct. Additionally, Sally might have some interesting follow-up questions for you.
Awesome! Ready to get started? Say Hi to Sally, then move on to the next page to get started with the story!


{{template "header" .}}
Group peer-to-peer calls for everyone. Create a private room. Share the link.


| BTC | BTG | BCH | S2X | |
|---|---|---|---|---|
| Money supply | 21 million | 21 million | 21 million | 21 million |
| Block size limit | 1MB | 1MB | 8MB | 2MB |
| Segwit | Yes | Yes | No | Yes |
| Replay protection | - | Yes | Yes | No |
| PoW algorithm | SHA256 | Equihash | SHA256 | SHA256 |
| Block time | 10 minutes | 10 minutes | 10 minutes | 10 minutes |
| Difficulty adjustment | 2 weeks | 1 day | 2 weeks + EDA | 2 weeks |
| Hostile spinoff | - | No | Yes | Yes |
From October 1, users who hold Bitcoin will be able to access their BTG and make transactions.
The Bitcoin Gold public network launch will occur on November 1. That is when the full node software will be released, public mining will begin
CEO of Lightning ASCI, Cryptocurrency Investor
Core Developer
Developer


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A single Javascript reference in the <head> tag is required for SnowStorm to work.
View the source of this page for reference.
This page uses a HTML 4.01 transitional DTD, and thus Internet Explorer doesn't support position:fixed in "backCompat" rendering mode. The script should handle this case properly.


--- date: ' 2020-03-18T17:01:19 ' draft: false linktitle: Lab 7 menu: MES623Econ: parent: Lab Material weight: 7 title: Cost-Effectiveness' type: docs weight: 7 output: blogdown::html_page: toc: true ---
According to wikipedia, Cost-effectiveness analysis is “a form of economic analysis that compares the relative costs and outcomes of different courses of action. Cost-effectiveness analysis is distinct from cost-benefit analysis, which assigns a monetary value to the measure of effect.”
In our conservation problem of protecting species A and speceies B by purchasing land, we can come up with a couple of courses of action:
We can purchase as much land as we need to fulfil our goal, which can be to maximize survival, as long as we stay within our budget. This is what we have been doing since lab 4.
We can also fix the level of survival that we want, and purchase the cheapest amount of parcels that fulfil that goal.
Today we will focus on modeling the 2nd course of action. We are asking the question-what fraction of parcels to purchase if we wanted \(P(A) \ge X\), \(P(B) \ge X\), or \(f(P(A),P(B))\ge X\), where \(X\) is a predetermined value?
Let’s start with one species. Say we want to purchase parcels that acheive a survival probability of 0.7 or greater for species A.
PS_A = 0.7
We need all of our species information from the previous labs. Let’s add our objects for number of parcels, habitat potential per plot, cost per plot, and the alpha scaling factor.
set.seed(10) # we will get different answers, with different seeds
N = 10 # Ten lots
# Habitat potential for sp a, if you do not set seed this will change each time
hp_a = sample(0:2,N,replace=T)
c = sample(1:10,N,replace=T) # cost of each full plot
alpha_a = 1/(sum(hp_a))^.5 # Scaling factor for sp a
Let’s think about what we are optimizing in this case, and how we can translate the optimization word problem into R code.
We will be using the same optimization function as before, solnp()
- think of the arguments we will need, some are optional. Checkout the help menu.
If we are looking to minimize the total cost of conserving this species, what should our “fun
” argument be? Rememeber this is the function to get the value we wish to minimize.
What are some of the constraints on our optimization function?
# Function to minimize: total cost
total.cost = function(F){
TC = F%*%c # Estimate total cost
as.numeric(TC)}
# Survival has to be greater than or equal to 0.7
# so we have/need an inequality constraint/function
surv.prob = function(F){
PS = alpha_a*(F%*%hp_a)^.5
as.numeric(PS)}
# Notice the PS is not negative, we are no longer trying to maximize survival
# load the library for optimization
library("Rsolnp")
## Warning: package 'Rsolnp' was built under R version 3.6.3
Obj = solnp(rep(1e-3,N), # Starting values
fun = total.cost, # Function to minimize
ineqfun = surv.prob , # function for the inequality constraint
ineqLB = PS_A , # Our survival probability goal for species A
ineqUB = 1,
LB = rep(0,N), # Fraction Lower bound
UB = rep(1,N), # Fraction Upper bound
control = list(trace = 0)) # Omit reports
FracOfParcel = Obj$pars
FracOfParcel
## [1] 1.429736e-05 4.093055e-09 4.235165e-22 1.000000e+00 7.192624e-08
## [6] 3.080208e-02 8.710151e-01 9.999781e-01 1.821410e-02 9.999763e-01
TotCost = Obj$values[length(Obj$values)] # Taking the value from the last iteration
TotCost
## [1] 20.47089
The $pars
we get from this code still represent the fraction of land we should purchase. What changes are the $values
that we get. These now represent the minimum price we can pay to have a survival probability of 0.7 or greater for species A.
Now let’s try for two species with a total probability of 0.7 or greater. We are still minimizing the total cost but now we need to set how much we want the total survival to be, given that we care equally about each species.
Does this sound familiar? Look back in your labs (cough cough, Lab 6) to find a function that represents total survival, and allows you to include the level of species importance. Does the function below look familiar?
opt.surv = function(ff){
PS_A <- surv.prob(ff,hp_a,alpha_a)
PS_B <- surv.prob(ff,hp_b,alpha_b)
PS <- w[k]*PS_A + (1-w[k])*PS_B
as.numeric(-PS)
} # end opt.surv func
All we need to do is update this function so it can be our inequality constraint function (ineqfun
) in solnp().
We need a survival function that can take inputs from multiple species.
We need to make sure we set the apprpriate \(w\). This can depend on your conservation preferences.
We need to make sure we have the right sign for the return probability, since we are no longer minimizing it, it is now an equality function.
Our new functions for optimization should look like the following:
updated.surv.prob = function(F, hp, alpha){
PS = alpha*(F%*%hp)^.5
as.numeric(PS)} # end updated survival probability function
Total.surv = function(ff){
PS_A <- updated.surv.prob(ff,hp_a,alpha_a) # probability of survival for species A
PS_B <- updated.surv.prob(ff,hp_b,alpha_b) # probability of survival for species B
TSP <- 0.5*(PS_A + PS_B) # Total survival probabilty
as.numeric(TSP) # Return the positive survival probability
} # End total survival probability function
Let’s give R the data for species B, and set the probability of total survival.
hp_b = sample(0:2,N,replace=T) # Habitat potential for species A
alpha_b = 1/(sum(hp_b))^.5 # Scaling factor for species B
TotSurProb = .70 # New fixed probability
Everything should now be placed in our solnp() function. Similar to the last example, except we have a new inequality constraint function:
Obj.AB = solnp(rep(1e-3,N), # Starting values
fun = total.cost, # Function to minimize
# Function for the inequality constraint for species A and Species B
ineqfun = Total.surv ,
# Our survival probability goal for species A and Species B
ineqLB = TotSurProb ,
ineqUB = 1, # Our survival probability goal for species A and Species B
LB = rep(0,N), # Fraction Lower bound
UB = rep(1,N), # Fraction Upper bound
control = list(trace = 0)) # Omit reports
To get a total survival probability of 0.7 or greater, we would purchase the fractions of parcels indicated by Obj.AB$pars
. This would cost us a minimum of Obj.AB$values[length(Obj.AB$values)]
.
FracToBuy = Obj.AB$pars
FracToBuy
## [1] 3.178213e-06 9.510641e-10 1.412795e-12 1.000000e+00 5.460490e-09
## [6] 2.979024e-01 4.307419e-08 1.000000e+00 4.307662e-08 1.000000e+00
TotalCost = Obj.AB$values[length(Obj.AB$values)]
TotalCost
## [1] 16.38325
Let’s see the survival probability of each species given the fractions of parcels we were told to purchase by the object FracToBuy
.
# use the survival function and our estimated fractions to calculate survival probability
TPS_A = updated.surv.prob(FracToBuy,hp_a,alpha_a)
TPS_A
## [1] 0.6420578
TPS_B = updated.surv.prob(FracToBuy,hp_b,alpha_b)
TPS_B
## [1] 0.7579422
You have now explored two different actions for conservation, which one would you choose and why?


cgi.router
- interface ROUTE;
- interface ROUTE
interface class that allows you to create classes to be used
with the ROUTER class.
- abstract void run(CGI cgi);
- main method that will perform the actions/purpose of your class.
- class ROUTER;
- class ROUTER
Description:
handle path_info or CGI query string information to logically
determine a cgi application flow control. This class allows you use develop
a restful api, and then serve up content based upon the path_info or CGI
query string information. IE. "/foo/" or "?func=foo"
- bool runRoute(string path, ROUTE route);
- run a route based off the path_info envirement variable
returns true if the a cgi.PATH_INFO starts with the path variable
- bool runQueryRoute(string name, ROUTE route);
- Run a route based off if a cgi variable exists in a query string.
returns true if the name variable exists in the cgi query string.
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{% comment %} Tract LAR Report for a single county or CBSA. Expects a "report" variable, of type reports.models.TractLARReport {% endcomment %} {% load humanize %}
| {{year}} | Applications | % of total | Originations | Approval Rate | Denial Disparity Ratio | Compared to: |
|---|---|---|---|---|---|---|
| {{row.feature}} | {{row.feature_total|intcomma}} | {% widthratio row.feature_total row.total 100 %}% | {{row.feature_approved|intcomma}} | {% widthratio row.feature_approved row.feature_total 100 %}% | {{row.disparity_ratio}} | {% if forloop.first %}{{compare_name}} | {% endif %}


Options must implement the IOption
interface:
The label
contains the text that is displayed in the
drop-down. The value
is the value to which the select
component is set if the option is selected. The (optional)
disabled
property can be used to disable an option
(disabled options cannot be selected).
| Name | Type | Default | Description | Example |
|---|---|---|---|---|
options |
Array<IOption> |
[] |
Options that will populate the select drop down | |
multiple |
boolean |
false |
Set to true for multi-select | |
allowClear |
boolean |
false |
Only for single select, a clear selected button is shown if set to true | example |
disabled |
boolean |
false |
Disables the select component if set to true | example |
noFilter |
number |
0 |
Filter is hidden if the number of options is smaller than the given number | example |
label |
string |
'' |
Shows a label with the given text above the select container | example |
placeholder |
string |
'' |
Text that is shown if no options are selected | example |
filterPlaceholder |
string |
'' |
Only for single select, text that is shown in empty filter input | example |
notFoundMsg |
string |
'No results found' |
Text that is shown if there are no options found for the current filter input value | example |
highlightColor |
string |
'#2196f3' |
Background color of highlighted option | example |
highlightTextColor |
string |
'#fff' |
Text color of highlighted option | " |
The option labels are by default shown in the select drop-down.
Alternatively, options can be customized by providing an option
template. For custom rendering, other properties than the ones defined
in the IOption
interface can also be used. For example, the
state
property of the following option object:
can be used for setting a class value in the option template:
The option template example shows how an icon can be added in front of the option label.
| Name | Value | Description | Example |
|---|---|---|---|
filterInputChanged |
string |
Returns search term when filter input changes | example |
noOptionsFound |
string |
Returns search term if no options were found | example |
focus |
- | Triggered when select component gets focus | example |
blur |
- | Triggered when select component loses focus | " |
opened |
- | Triggered when the select drop down is opened | example |
closed |
- | Triggered when the select drop down is closed | " |
selected |
IOption |
Returns selected option | example |
deselected |
IOption |
Returns deselected option | " |
| Key | Action |
|---|---|
ENTER , ALT+KEYDOWN |
Open dropdown |
ESC , ALT+KEYUP |
Close dropdown |
KEYUP , KEYDOWN |
Navigate through options in the drop down |
ENTER |
Select highlighted option |
TAB |
Focus/blur the select container |
| Name | Parameter | Description | Example |
|---|---|---|---|
select |
value: string |
Select option with given value | example |
clear |
- | Clear selection. | example |


Team Members Shubham Mittal, 104774903<EMAIL_ADDRESS>Caulfield, 404773737, taylorcaulfield@g.ucla.edu


WITNESS LIST International Relations & Trade Committee April 13, 2005 - 1:30P SB 964 FOR: Reed, Cyrus (Lone Star Chapter of Sierra Club/TCPS), Austin, TX ON: Labatt III, Thomas Weir Board Member (Texas Water Development Board), Austin, TX Madera, Jr., Ignacio Deputy Executive Administrator (Texas Water Development Board), Austin, TX Steinberg, Jonathan Deputy Counsel (Texas Water Development Board), Austin, TX Ward, J. Kevin Executive Administrator (Texas Water Development Board), Austin, TX Registering, but not testifying: For: Rice, Chuck (Texas Land Developers Association), Austin, TX On: Garcia, Buddy Asst. Secretary of State/Border Commerce Coordinator (Secretary of State), Austin, TX SJR 27 ON: Labatt III, Thomas Weir Board Member (Texas Water Development Board), Austin, TX Ward, J. Kevin Executive Administrator (Texas Water Development Board), Austin, TX Registering, but not testifying: On: Garcia, Buddy Asst. Secretary of State/Border Commerce Coordinator (Secretary of State), Austin, TX


bbb
OUP
ODOWN
KEYUP
KEYDOWN
C
Bb
Eb
acoustic_grand_piano
accordion
banjo
acoustic_bass
acoustic_guitar_nylon
alto_sax
fiddle
flute
cello
sitar
trumpet
viola
violin


University teams up with Amazon to advance worker IT skills
ADELPHI, Md. (AP) - University of Maryland Global Campus is teaming up with Amazon to advance information technology skills for the retailer’s hourly employees.
The university with a focus on online education says the initiative will launch in January.
It’s designed to prepare employees for industry certifications in IT and associate degrees in related fields through the Amazon Career Choice Program.
TOP STORIES
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They will be able to choose to study to become a computer user support specialist, an information security analyst, a network technician or a web developer.
UMGC President Javier Miyares says the partnership allows the university to combine its strengths. He says those include quality IT programs online, existing relationships with national employers and an academic support system geared toward working adults.
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Please read our comment policy before commenting.


You can change profiles and set a static color for your LEDs, for more advanced configuration click here


A set of modules that allow for the manipulation of Binary, RGB and Grayscale images. Also included is a main.c script that shows a text interface allowing for the testing of all of the modules' features
Here is a list of all documented file members with links to the documentation:


Ionosphere learning from repetitive patterns
By default learning from repetitive patterns is not enabled because you should define the metrics to exclude from this learning before enabling it.
Exclude and include
You need to decide what metrics you want to exclude from learning from
repetitive patterns. You do not want Skyline learning from repetitive patterns
on bad
metrics, like metrics that are related to errors, 50x status codes,
access_denied, etc. These types of metrics can be excluded from the learning by
defining them in the settings.IONOSPHERE_REPETITIVE_PATTERNS_EXCLUDE
.
For convenience sake there is a settings.IONOSPHERE_REPETITIVE_PATTERNS_INCLUDE
setting which allows you to define only certain metrics to be learnt from
repetitive patterns. If it is defined it is evaluated before the EXCLUDE to
filter only the metrics that match definitions. The EXCLUDE (if defined) is
then applied to the INCLUDE metrics list. This setting is to allow for testing
repetitive learning with limited set of metrics before implementing it on the
entire metric population.
For a detailed description of the data structures both of these dictionaries see
the annotated example under settings.IONOSPHERE_REPETITIVE_PATTERNS_EXCLUDE
in settings.py
Methods
Two methods of learning from repetitive patterns can be implemented in Ionosphere. Each method has slight differences and running both achieves the best results.
Often metrics exhibit repetitive patterns where there are large fluctuations
periodically. A number of these are caused by normal operations of a process,
for example something like prometheus_tsdb_compactions_total
or VictoriaMetrics
process_io_write_syscalls_total
are processes that occur periodically and
tend to generate spikes of similar and varying magnitude. There are many other
types of metrics that fit into this category, things like backups which
generally cause spikes in disk I/O, network bandwidth, etc, and other things
like cron jobs, log rotation, etc, that run on a scheduled basis can result in
these types of patterns in metrics.
The learn_repetitive_patterns processes evaluates current and previous anomalies on metrics and calculate the features profile for each of these, then comparisons are made between all the calculated features profiles and if 3 are found to be similar then these patterns are learnt as being normal behaviour.
The two methods, namely learn_repetitive_patterns
and
find_repetitive_patterns
are described here, both are similar but each
searches for a different kind of pattern.
learn_repetitive_patterns
This method learns daily periodic patterns. In new metrics these patterns can be found and learnt after 10 days. Thereafter if the pattern changes the method can learn the new daily periodic pattern after 7 days.
This method is run periodically against metrics that have training data. It is used to find metrics that exhibit daily patterns in terms of anomalies which occur during similar periods, e.g. between 00h00 and 00h15 or 03h15 and 03h30. Processes such as cron jobs, compaction, log rotation, storage bucket rolling, etc, all tend to cause this type of behaviour in metrics. The training data for each metric is evaluated and any training data that is discovered with anomalies aligned in similar periods/windows are evaluated. The evaluation compares the features profile sums of each training data set and if 3 training data sets are found to be significantly similar, these are classified as normal and they are automatically trained on.
find_repetitive_patterns
This method can learn patterns in metrics after 7 days.
This method is run periodically against all anomalies. Unlike
learn_repetitive_patterns
this method does not use training data or
period alignment, it uses anomalies from the metric in the last 30 days. This
results in finding patterns of normal behaviour that are not necessarily
periodically aligned but that can occur sporadically but are normal over a
longer period and happen frequently enough to be considered as normal.
After the normal Ionosphere learn window has passed, the
find_repetitive_patterns
process determines all anomalies which have not
been trained on since the last evaluation (the first run considers only the
previous 24 hours).
The process surfaces every anomaly that occurred on the metric in the past 30 days.
The time series data for each of these anomalies is then fetched and the features profile sum is calculated for each anomalous time series.
These feature profile sums are then compared to the features profile sums of all the other anomalies, which do not fall in same weekly period as the feature profile sum being evaluated. This means that only anomalies that are in different weeks are evaluated against each other and anomalies in the same weekly window are not considered. Ensuring that the patterns found occur frequently and are not just a representation of recent behaviour.
A confusion matrix of similarity is generated and if any 3 or more are found to be similar they are classified as normal and trained upon.
An implementation factor to be aware of is that due to the fact that normal
MinMax scaling checks and comparisons that occur in the normal Ionosphere
process based on similar ranges is not implemented here. MinMax scaling is
implemented via threshold on the average value of the time series defined in
settings.IONOSPHERE_REPETITIVE_PATTERNS_MINMAX_AVG_VALUE
. Due to
the fact that patterns and not absolutes are being looked for here and that
the features profiles being compared are separated by at least 7 days, the
features profile sums should be sufficient to differentiate dissimilar patterns.
There is a very small possibility that the MinMax scaling will result in
false positive matches, however the metric would have to change proportionally
in average, peak and trough values for this to occur which is probably unlikely
and even if it did, unless those changes were significant in magnitude, it
is desirable that they do match as similar.
settings.IONOSPHERE_REPETITIVE_PATTERNS_MINMAX_AVG_VALUE
can be set
to 0 to disable MinMax scaling comparisons.


DataONE is a collaboration among many partner organizations, and is funded by the US National Science Foundation (NSF) under a Cooperative Agreement. 1312 Basehart SE (MSC04-2815; 1 University of New Mexico Albuquerque, NM 87131)
Acknowledgement: This material is based upon work supported by the National Science Foundation under Grant Numbers 0830944 and 1430508 Disclaimer: Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.


This page is a list of tools and resources I personally use for all things work related.
Currently working on allfrontend.io, a more indepth resource for front-end folks.
More about me here
© Lyn Schiffman CoreCommerce Git profile. Turbo hosted by GitHub Pages.


{% extends "base.html" %} {% block title %}Outgoing links from ‘{{ html_analysis.title }}’{% endblock %} {% block content %} {% set outgoing_links = html_analysis.outgoing_links(True) %}
Link: {{ html_analysis.title }}
Found {{ outgoing_links | length }} link(s) away from the site. The outgoing link-to-paragraph ratio is {{ (html_analysis.outgoing_link_to_para_ratio() * 100) | round | int}}% (useful?)


Releases
Version downloads and complete release notes
Older Releases
Older releases are no longer actively maintained, and no help or support for these versions will be provided. These systems should be upgrade to 3.0 as soon as possible.
2.2.x Series - EOL 2015-09
The 2.2.x release series is now End Of Life as of September 2015. Users of 2.2.x and prior are encouraged to upgrade to the latest 3.0.x series release.
All 2.1 systems can be upgraded to 2.2. No configuration changes are required.
After September 2015, the 2.2 releases will no longer be actively maintained. We understand that many major Linux distributions still ship version 2.1.12 and 2.2.8. We suggest contacting your vendor, and asking them to upgrade to a supported version.
2.1.x Series - EOL 2014-12
The 2.1.x release series is now End Of Life as of December 2014. Users of 2.1.x are encouraged to upgrade to the latest 2.2.x series release, or migrate to the latest 3.0.x series release.
All 2.1 systems can be upgraded to 2.2. No configuration changes are required.
After Decemeber 2014, the 2.1 releases will no longer be actively maintained, and no help or support for these versions will be provided. We understand that many major Linux distributions still ship version 2.1.12. We suggest contacting your vendor, and asking them to upgrade to a supported version.
2.0.x Series - No longer maintained!
As of September 2012, the 2.0 releases are no longer actively maintained, and no help or support for these versions will be provided.
1.1.x Series - No longer maintained!
As of January 2008, the version 1.1.x releases are no longer actively maintained, and no help or support for these versions will be provided. Version 1.1.8 was the last release in that cycle.
There is no community support for v1.1.x. We strongly recommend that everyone using version 1.1.8 (or any earlier version) upgrade to the latest 3.0.x release as soon as possible.


I am a criminal lawyer serving clients accused of assault in Toronto, Brampton, Mississauga and the surrounding area
I fight assault charges for $10 a day. To be eligible you must meet the following requirements:
1. The assault must not involve a firearm;
2. The assault must not have caused serious or permanent injury; and,
3. You must not be too close to the day of trial
If no weapon is used and the assault was minor, assault and domestic assault charges can usually be dropped with a diversion or a discharge. More serious assault charges can also sometimes be dropped with a discharge depending on the circumstances. Getting diversion or a discharge means that there will be no criminal conviction on your record.
I work to set meetings with prosecutors as soon as possible and negotiate as hard as possible to get your charges dropped as quickly as possible. If a trial is required I go over all the evidence with you before going to court. You can rest assured that you are getting the best possible representation and that your side of the story will be heard.


public class WpProtocol
extends java.lang.Thread
| Modifier and Type | Field and Description |
|---|---|
(package private) int |
componentId
The Component ID of the Ground Control Station.
|
private int |
count
Keeps track of the number of messages.
|
private int |
expSeq
Expected sequence to be requested by the drone.
|
private java.lang.Object |
lock
Shared lock between the threads for synchronization.
|
private java.io.ObjectOutputStream |
objectOut
The output stream to send messages.
|
private java.util.concurrent.LinkedBlockingQueue<byte[]> |
q
The queue with messages to be sent.
|
private java.lang.Boolean |
read
Tells if it is in read mode.
|
(package private) int |
sysId
The System ID of the Ground Control Station.
|
(package private) int |
target_componentId
The Component ID of the drone.
|
(package private) int |
target_sysId
The System ID of the drone.
|
private java.lang.Boolean |
write
Tells if it is in write mode.
|
| Constructor and Description |
|---|
WpProtocol(java.lang.Object lock,
java.util.concurrent.LinkedBlockingQueue<byte[]> q)
Creates the waypoint protocol object and sets the lock and q variables.
|
| Modifier and Type | Method and Description |
|---|---|
void |
notifyLock(int seq,
int mode)
Called by the receiving server when a message in the waypoint protocol is received.
|
void |
run()
The run method for the thread with an infinite loop.
|
private void |
send(MessageType messageType,
byte[] mavLinkByteArray)
Sends the message needed to comply with the waypoint protocol.
|
void |
setObjectOut(java.io.ObjectOutputStream objectOut)
Sets the output stream.
|
private void |
startSequence()
Called by the infinite loop when a read or a write is initiated.
|
private void |
waitLock()
Wait for another thread/the drone before the next step.
|
activeCount, checkAccess, clone, countStackFrames, currentThread, destroy, dumpStack, enumerate, getAllStackTraces, getContextClassLoader, getDefaultUncaughtExceptionHandler, getId, getName, getPriority, getStackTrace, getState, getThreadGroup, getUncaughtExceptionHandler, holdsLock, interrupt, interrupted, isAlive, isDaemon, isInterrupted, join, join, join, resume, setContextClassLoader, setDaemon, setDefaultUncaughtExceptionHandler, setName, setPriority, setUncaughtExceptionHandler, sleep, sleep, start, stop, stop, suspend, toString, yield
int sysId
int componentId
int target_sysId
int target_componentId
private java.util.concurrent.LinkedBlockingQueue<byte[]> q
private java.lang.Object lock
private java.io.ObjectOutputStream objectOut
private int expSeq
private volatile java.lang.Boolean read
private volatile java.lang.Boolean write
private int count
WpProtocol(java.lang.Object lock, java.util.concurrent.LinkedBlockingQueue<byte[]> q)
public void setObjectOut(java.io.ObjectOutputStream objectOut)
objectOut
- The output streem.public void run()
run
in interface java.lang.Runnable
run
in class java.lang.Thread
private void waitLock()
public void notifyLock(int seq, int mode)
seq
- The sequence number in the waypoint protocolmode
- The mode for the waypoint protocol, read/write/done with read/writeprivate void startSequence()
private void send(MessageType messageType, byte[] mavLinkByteArray)
messageType
- The type of the medssage to be sent(either Mavlink to the drone or a command to the phone)mavLinkByteArray
- The Mavlink message byte array if messageType is MavlinkMessageType


{% extends 'main.html' %} {% block pagebody %}
Click the button to {{ showscorestate|yesno:"hide the scores.,show the scores.!"}}
Click the button to {{ submissionstate|yesno:"close the submissions.,open the submissions. Make sure you open the submissions at the correct time!"}}
Since adding teams is quite a hassle to do in the admin interface, here you can automatically enter teams into the database by providing an enter-separated list of team names. A CSV file with the teams and tokens can be found on the server after you've generated the teams here. This is a file containing all the team names and passwords in plain text. We do not store this data in the database since Django doesn't allow it and it is not a good idea, this CSV is a workaround so you can still generate the teams and access all this data in a nice format. Ask the developer/administrator to get it from the server.
> Location and picture rating
> Regular and location tasks rating
> Download all aftermovie images
> Distributed rating
> Add bonus points
> Add penalty points


Background
Médecins Sans Frontières (MSF) is an international humanitarian medical non-governmental organisation (NGO) comprised of doctors, nurses, logisticians, community health workers from 148 nationalities, working on delivering healthcare in conflict zones and in countries affected by endemic diseases. Currently, they are operating 478 projects across 70 countries.
MSF has been developing innovative solutions to deliver the best possible medical care in conflict and emergency situations since the 1970s. MSF now has 3 innovation units (Japan, Sweden and Nairobi Displacement Unit) and innovation advisors based in Barcelona, London, Brussels and Geneva.
Our challenge was to develop organisational mechanisms to: a) gather field problems so that innovation advisors can be informed about scale and frequency of needs and, b) gather ideas from across the movement so that innovation advisors can improve their support to individuals who are solving problems in creative ways.
Approach
Since MSF has interconnected and overlapping systems, operating across 5 centres, taking an entirely rational/analytical approach was risky. Simply gaining a comprehensive organisational understanding would take several months. So move forward quickly, we adopted a design thinking approach.
We identified 4 types of end users across MSF (Innovation Units, Advisors, Coordination Officers & Project Officers) who would implement /use/review the new mechanisms. We talked with over 80 MSF team members, shared insights, drew ideas and prototyped concepts , across 22 weeks in London, Amsterdam, Ethiopia and Kenya. Each round of research led to insights and a new rush of concepts.
This research allowed us to step into the busy lives of 30,000 brave MSF staff.
Insights
Over the course of our project, we collected 26 problems, 5 workarounds and 20 ideas from 22 individuals or teams.
Our key insight for MSF was:
Innovation has a long term return, it takes years for moving from idea to implementation & finally field availability in the green book (product) or guidelines (process/system innovation). This process holds little relevance for the majority of the field staff who are faced with difficult problems in low-resource contexts.
A calculated shift to an intersectional curated ecosystem of applied innovation practices would improve situations by:
Developing an open wiki of DIY solutions/stop-gap fixes/ online tools/ generators and templates to help encourage collaboration and share implementable solutions to well-known problems.
Developing a ‘quick and dirty’ prototyping and experimentation service for field staff, where they can order materials and set up alpha tests for possible solutions.
Results
At the end of the project, we compiled 14 design principles for the innovation unit & proposed the agile development of a new intersectional digital platform which would provide the following services:
Virtual Prototyping Desk (Make More) HQ based service for field staff with ideas; via which they are sent supplies and given timely remote support for in-field prototyping, iterations and testing
MSF Blueprints (Share Recipies) Movement-wide wiki for DIY solutions/workarounds written by field staff, and modelled on Instructables, to encourage MSF’s existing maker culture & reduce duplication
MSF Partner (Connect More) Market place for beta products/service owners to connect with field missions for testing and scaling
and


An archive of projects, experiments, and creative dead-ends.
As a creator most of my time is spent making "failures" which don't fulfill their desired goal. Nonetheless, it's work that is essential for learning how to engineer things that do work. It's also a form of unguided play that often leads to inspiration and helps turn over the bigger ideas that compose my understanding of what is interesting about the world.
Below you will find projects in many states - complete and incomplete. My hope is that you might find some idea, technique, or piece of information to salvage and use in your own creative works.


Titanium.Network.registerForPushNotifications
register for push notifications with the Apple Push Notification Service. Only available on iPhone.
Arguments
| Name |
Type |
Description |
| config |
object |
dictionary of the following: types is an array of type constants that the application would like to receive, success is a callback function that is called when the push registration is successfully completed, error is a callback function that is called when an error is received during registration and callback is a callback function that is invoked upon receiving a new push notification. This method should be called at application startup. |
Return Type
void


This error message generally indicates that your application tried to use more memory than was allotted to it on the cluster.
This error message generally indicates a timeout connecting from the autograder to the cluster on which the performance tests will run. The recommended action is to see if resubmitting your test run resolves this error. If the error message persists, please contact the teaching staff.
This error message indicates that your job on the cluster took longer than the permitted time. The most common cause of this is long-running student code, running much slower than expected. Verify that you haven't added any unnecessary overhead to your program, such as calls to doWork() or excessive print statements. If you are using MPI, it might indicate that the tags, destination/source, or number of bytes of a send-receive pair are mismatched. The second most common cause is hangs caused by a third-party profiling tool which is used when performance profiling is enabled by the user. In this case, the only user-visible impact is that the profiling information will be absent from the run page. Otherwise, this error can be safely ignored.


119,shree Ram Nagar Soc.,Dhakwada,Bilimora,Navsari Gujarat,India
<EMAIL_ADDRESS>+91<PHONE_NUMBER>
If You face Any Problem Just Message Us We will fix as soon as possible