Structure
TinkLinkError.ThirdPartyAppAuthenticationFailureReason.Code
public struct Code: Hashable
Relationships
Member Of
TinkLinkError.ThirdPartyAppAuthenticationFailureReason
Conforms To
Hashable
Properties
deeplinkURLNotFound
let deeplinkURLNotFound
The ThirdPartyAppAuthenticationTask
have no deep link URL.
downloadRequired
let downloadRequired
The UIApplication
could not open the application. It is most likely missing and needs to be downloaded.
doesNotSupportAuthenticatingOnAnotherDevice
let doesNotSupportAuthenticatingOnAnotherDevice
The credentials can not be authenticated on another device.
decodingQRCodeImageFailed
let decodingQRCodeImageFailed
Decoding the QR code image failed.


ID 2020 DESIGN WORKSHOP
MAY 21ST AND 22ND
Our second #RebootingWebOfTrust Design Workshop on decentralized identity technologies will be held the weekend of May 21st and 22nd in New York City. This date was selected to follow an important digital identity policy event a...


benjaminweiss46
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Advancing Computing as a Science and Profession
ExploreMuthoot Institute of Technology and Science (MITS) which is located at Puthencruz Ernakulam is promoted by Muthoot M George.It was established with the aim of providing better education to the students as well as to concrete the young minds with the intention to build up our nation.
ACM members actively conduct programmes to accomplish the mission and vision of the Computer Science Department and to bring others to our perspective. This association provides additional information to the students through talks and other activities.


--- title: Categorical variables weight: 15 ---
Some variables, consist of named categories, e.g. the name of your favourite brand. A category-variable, or a categorical variable refers to any variable that puts individuals into categories. These variables are also called nominal variables. The word nominal comes from Latin (nominalis=of a name), because we are giving names to the values of our variable.
With categorical variables we want to understand the frequency with which each value appears in our dataset. As you already know the easiest way to do so is by producing a table. Remember the table ()
function. The appropriate measure of central tendency for categorical variables is the mode and/or the median.
Below we will learn some basic data manipulation for categorical variables. Starting with identifying the class()
of a variable before we move to assigning a new name to variable and to the values of a categorical variable.
There are numerous data types in R. The most frequent used ones are numeric, character (string) or factor, and logical (TRUE or FALSE). To check the type of data contained in a variable we can use the class()
function.
load("EVS_UK.RData")
To find the length of a character variable we use the nchar()
function.
EVS_UK$education<-EVS_UK$v243_r_weight
table(EVS_UK$education)
##
## 1 2 3
## 590 313 885
As you know, education is a classic example of a categorical variable. How can we assign labels to the values of the variable? This is easy.
Note that as the same time we will learn how to covert a variable to factor but also we will give a name to the values.
Let’s do it!
EVS_UK$education <- factor(EVS_UK$education,
levels = c(1, 2, 3),
labels = c("Low", "Medium", "Upper"))
table(EVS_UK$education)
##
## Low Medium Upper
## 590 313 885
Let’s examine our new factor variable with a frequency table
table(EVS_UK$education)
##
## Low Medium Upper
## 590 313 885
The most common graphical representation of categorical variables is bar graphs and pie charts.
library(ggplot2)
ggplot(data.frame(EVS_UK), aes(x=education)) +
geom_bar()
{{% notice note %}} Adjust the width of the bars using the width function, change the appearance of the axes by giving labels. Give a title to your graph. RStudio Base cheatsheet {{% /notice %}}


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Rule
Enabled?
Help / Notes
Key's distortion
Filter own keys
Proxy traps
getPrototypeOf
setPrototypeOf
isExtensible
preventExtensions
getOwnPropertyDescriptor
defineProperty
has
get
set
deleteProperty
ownKeys
apply
construct
Other distortions
Local properties
Local deletes
Argument list truncation?


Immunophenotyping of MSCs and ACs. MSCs expressed cell surface markers CD29 (1A) and CD44 (1B). CD45 was absent in MSCs (C). AC showed the expression of ECM: type-II collagen (1D) and proteoglycan (1E) secretions. Type-I collagen was absence in the AC monolayer culture (1F). (Magnification: 100X in 1A, B, C, D and F; 200X in 1E).


A B C D G H M N P S T W
All Classes All Packages
All Classes All Packages
All Classes All Packages
A
- Akna - Class in sample
-
Makes the given number of bombs.
- Akna() - Constructor for class sample.Akna
- aknák() - Method in class sample.Akna
-
Places the number of bombs that given by @NumberOfBombs, than counts the bombs in the neighbours.
- Aknakereso - Class in sample
-
Makes the whole table with bombs.
- Aknakereso() - Constructor for class sample.Aknakereso
-
Makes buttons, than puts the bombs down.
- all - Static variable in interface sample.mezo
-
The size of the buttons.
- AppLauncher - Class in sample
-
Thie launches the application.
- AppLauncher() - Constructor for class sample.AppLauncher
B
- Blowed() - Method in class sample.BlowedUp
-
This watches when you chose a bomb and shows that is a bomb.
- BlowedUp - Class in sample
-
Blows the bomb is you choose it.
- BlowedUp(Aknakereso) - Constructor for class sample.BlowedUp
-
Calls the created @aknakereso.
- Blower(ArrayList<Integer>) - Method in class sample.NullBlower
-
Blows the 0 value neighbours.
- BOMB - Static variable in interface sample.mezo
-
Bomb has a value for easy work.
C
- Controller - Class in sample
-
This watches the mouse click, runs the timer, count disabled buttons, watches if you win or lost.
- Controller(Aknakereso) - Constructor for class sample.Controller
-
Starts the timer and tries to catch mouse event.
- counter - Static variable in interface sample.mezo
-
Counter counts the buttons.
D
- display(String, String) - Static method in class sample.BlowedUp
G
- getDisabled() - Method in class sample.Controller
- getDisabledCounter() - Method in class sample.NullBlower
- getID() - Method in class sample.Player
- getMezo() - Method in class sample.Aknakereso
- getNumberOfBombs() - Method in class sample.Akna
- getScore() - Method in class sample.Controller
- getScore() - Method in class sample.Player
- getTable() - Method in class sample.Aknakereso
H
M
- main(String[]) - Static method in class sample.AppLauncher
- main(String[]) - Static method in class sample.Main
- Main - Class in sample
-
Creates the main window of the program.
- Main() - Constructor for class sample.Main
- mezo - Interface in sample
-
Giving the size of the buttons.
- mezo - Static variable in interface sample.mezo
-
Creating the buttons.
N
- NullBlower - Class in sample
-
Blows those buttons which has 0 value and the neighbours of the clicked button.
- NullBlower() - Constructor for class sample.NullBlower
P
- Player - Class in sample
- Player() - Constructor for class sample.Player
-
Instantiating of Player.
- Player(double) - Constructor for class sample.Player
- Player(Integer, double) - Constructor for class sample.Player
S
- sample - package sample
-
The package contains the classes for the perfect work of the program.
- Score(double) - Method in class sample.Player
- setDisabledCounter(int) - Method in class sample.NullBlower
- setID(Integer) - Method in class sample.Player
- start(Stage) - Method in class sample.Main
-
Creates the window for the game.
T
- table - Static variable in interface sample.mezo
-
The anchor pane, where the buttons lays.
- timer - Variable in class sample.Controller
-
timer counts the time.
- toString() - Method in class sample.Player
W
- width - Static variable in interface sample.mezo
-
The width of the buttons.
- win() - Method in class sample.Controller
-
Tests if you win or not.
All Classes All Packages


Clustering your scheduler in many servers..
Schedule tasks in a simple way..
Each hook it costs no more than $0.05..
Easy Scheduler is a service in cloud to facilitate the schedule of its application services, and may facilitate balancing of the services.
Create hook with your endpoint API.


Remote Procedure Calls for Dart
This framework is a part of the Pip.Services project. It provides the following synchronous communication components:
- Direct - Direct client
- Rest - RESTful
services
andclients
- Status -
Heartbeat
andstatus
services
Quick Links:
Acknowledgements
The Dart version of Pip.Services is created and maintained by:
- Sergey Seroukhov
- Levichev Dmitry
The documentation is written by:
- Mark Makarychev
- Levichev Dmitry


Attached for your records is a copy of your CAP Bulk Access Agreement, signed on {{ signed_date|date:"F j, Y" }}.
----------------------------


Government Gateway ID
You need your government gateway ID for at least one of the PAYE schemes you intend to link to the apprenticeship account.
You need your government gateway ID for at least one of the PAYE schemes you intend to link to the apprenticeship account.


Class RTCPCompoundPacket
Represents an RTCP compound packet consisting of 1 or more RTCP packets combined together in a single buffer. According to RFC3550 RTCP transmissions should always have at least 2 RTCP packets (a sender/receiver report and an SDES report). This implementation does not enforce that constraint for received reports but does for sends.
Inheritance
System.Object
RTCPCompoundPacket
Inherited Members
System.Object.Equals(System.Object)
System.Object.Equals(System.Object, System.Object)
System.Object.GetHashCode()
System.Object.GetType()
System.Object.MemberwiseClone()
System.Object.ReferenceEquals(System.Object, System.Object)
System.Object.ToString()
Namespace: SIPSorcery.Net
Assembly: SIPSorcery.dll
Syntax
public class RTCPCompoundPacket
Constructors
| Improve this Doc View SourceRTCPCompoundPacket(RTCPReceiverReport, RTCPSDesReport)
Declaration
public RTCPCompoundPacket(RTCPReceiverReport receiverReport, RTCPSDesReport sdesReport)
Parameters
| Type | Name | Description |
|---|---|---|
| RTCPReceiverReport | receiverReport | |
| RTCPSDesReport | sdesReport |
RTCPCompoundPacket(RTCPSenderReport, RTCPSDesReport)
Declaration
public RTCPCompoundPacket(RTCPSenderReport senderReport, RTCPSDesReport sdesReport)
Parameters
| Type | Name | Description |
|---|---|---|
| RTCPSenderReport | senderReport | |
| RTCPSDesReport | sdesReport |
RTCPCompoundPacket(Byte[])
Creates a new RTCP compound packet from a serialised buffer.
Declaration
public RTCPCompoundPacket(byte[] packet)
Parameters
| Type | Name | Description |
|---|---|---|
| System.Byte[] | packet | The serialised RTCP compound packet to parse. |
Properties
| Improve this Doc View SourceBye
Declaration
public RTCPBye Bye { get; set; }
Property Value
| Type | Description |
|---|---|
| RTCPBye |
ReceiverReport
Declaration
public RTCPReceiverReport ReceiverReport { get; }
Property Value
| Type | Description |
|---|---|
| RTCPReceiverReport |
SDesReport
Declaration
public RTCPSDesReport SDesReport { get; }
Property Value
| Type | Description |
|---|---|
| RTCPSDesReport |
SenderReport
Declaration
public RTCPSenderReport SenderReport { get; }
Property Value
| Type | Description |
|---|---|
| RTCPSenderReport |
Methods
| Improve this Doc View SourceGetBytes()
Serialises a compound RTCP packet to a byte array ready for transmission.
Declaration
public byte[] GetBytes()
Returns
| Type | Description |
|---|---|
| System.Byte[] | A byte array representing a serialised compound RTCP packet. |


Overview
Modern representation learning techniques like deep neural networks have had a major impact on a wide range of tasks, achieving new state-of-the-art performances on benchmarks using little or no feature engineering. However, these gains are often difficult to translate into real-world settings because they usually require massive hand-labeled training sets. Collecting such training sets by hand is often infeasible due to the time and expense of labeling data; moreover, hand-labeled training sets are static and must be completely relabeled when real-world modeling goals change.
Increasingly popular approaches for addressing this labeled data scarcity include using weak supervision---higher-level approaches to labeling training data that are cheaper and/or more efficient, such as distant or heuristic supervision, constraints, or noisy labels; multi-task learning, to effectively pool limited supervision signal; data augmentation strategies to express class invariances; and introduction of other forms of structured prior knowledge. An overarching goal of such approaches is to use domain knowledge and data resources provided by subject matter experts, but to solicit it in higher-level, lower-fidelity, or more opportunistic ways.
In this workshop, we examine these increasingly popular and critical techniques in the context of representation learning. While approaches for representation learning in the large labeled sample setting have become increasingly standardized and powerful, the same is not the case in the limited labeled data and/or weakly supervised case. Developing new representation learning techniques that address these challenges is an exciting emerging direction for research [e.g., 1, 2]. Learned representations have been shown to lead to models robust to noisy inputs, and are an effective way of exploiting unlabeled data and transferring knowledge to new tasks where labeled data is sparse.
In this workshop, we aim to bring together researchers approaching these challenges from a variety of angles. Specifically this includes:
- Learning representations to reweight and de-bias weak supervision
- Representations to enforce structured prior knowledge (e.g. invariances, logic constraints).
- Learning representations for higher-level supervision from subject matter experts
- Representations for zero and few shot learning
- Representation learning for multi-task learning in the limited labeled setting
- Representation learning for data augmentation
- Theoretical or empirically observed properties of representations in the above contexts
The second LLD workshop continues the conversation from the 2017 NIPS Workshop on Learning with Limited Labeled Data (http://lld-workshop.github.io). Our goal is to once again bring together researchers interested in this growing field. With funding support, we are excited to again organize best paper awards for the most outstanding submitted papers. We also will have seven distinguished and diverse speakers from a range of machine learning perspectives, a panel on where the most promising directions for future research are, and a discussion session on developing new benchmarks and other evaluations for these techniques.
The LLD workshop organizers are also committed to fostering a strong sense of inclusion for all groups at this workshop, and to help this concretely, aside from 1K for the paper awards, the remainder of the funding (both current and pending) will sponsor several travel awards specifically for traditionally underrepresented groups. We will also post a code of conduct emphasizing our commitment to inclusion, which we will expect all attendees to uphold.
Our Speakers
Finalization soon.
Schedule Detail
Schedule tentative.
-
8.30 AM
Welcome
-
8.40 AM
Invited Talk 1
By ... -
9.10 AM
Invited Talk 2
By ... -
9.40 AM
Contributed Talk 1
By ... -
9.55 AM
1-minute poster spotlights
-
10.30 AM
Poster Session 1/Coffee break
-
11.00 AM
Invited Talk 4
By ... -
11.30 AM
Invited Talk 5
By ... -
12.00 PM
Lunch break
-
2.00 PM
Panel: “Domain Knowledge vs. Sample Efficiency: Where Should We Focus?”
-
3.00 PM
1-minute poster spotlights
-
3.30 PM
Poster Session 2/Coffee break
-
4.00 PM
Contributed Talk 2
By ... -
4.15 PM
Invited Talk 6
By ... -
4.45 PM
Invited Talk 7
By ... -
5.15 PM
Contributed Talk 3
By ... -
5.30 PM
Contributed Talk 4
By ... -
5.45 PM
Discussion Session: New Evaluations and Benchmarks with Limited Labeled Data
-
6.15 PM
Award Ceremony
-
6.25 PM
Closing Remarks
VENUE
ICLR 2019, New Orleans, Louisiana
Ernest N. Morial Convention Center, New Orleans
Room: ; XXX seats.
Submission and important dates
Please format your papers using the standard ICLR 2019 style files. The page limit is 4 pages (excluding references). Please do not include author information, submissions must be made anonymous. All accepted papers will be presented as posters(poster dimensions: TBC), with exceptional submissions also presented as oral talks.
Submission deadline:
??/??/??
Submit my paper.
Notification of acceptance:
??/??/??
List of accepted papers.
Camera ready due:
??/??/??
FAQ
Lorem ipsum dolor sit amet, consectetur adipisicing elit. Sint assumenda ut molestias doloremque ipsam, fugit laborum totam, pariatur est cumque at, repudiandae officia ex dolores quas minus optio, iusto soluta?
Our Sponsors
We warmly thanks our generous sponsors to support this event!
Accepted papers
TBA
Organisers
- Isabelle Augenstein
- Stephen Bach
- Matthew Blaschko
- Eugene Belilovsky
- Edouard Oyallon
- Anthony Platanios
- Alex Ratner
- Christopher Re
- Xiang Ren
- Paroma Varma
Reviewers
We would like to thank all our reviewers.


A B C D E F H I J K L M N P R S T U V W X Z
| fpc-package | fpc package overview |
| adcoord | Asymmetric discriminant coordinates |
| ancoord | Asymmetric neighborhood based discriminant coordinates |
| awcoord | Asymmetric weighted discriminant coordinates |
| batcoord | Bhattacharyya discriminant projection |
| batvarcoord | Bhattacharyya discriminant projection |
| bhattacharyya.dist | Bhattacharyya distance between Gaussian distributions |
| bhattacharyya.matrix | Matrix of pairwise Bhattacharyya distances |
| calinhara | Calinski-Harabasz index |
| can | Generation of the tuning constant for regression fixed point clusters |
| cat2bin | Recode nominal variables to binary variables |
| cdbw | CDbw-index for cluster validation |
| cgrestandard | Standardise cluster validation statistics by random clustering results |
| claraCBI | Interface functions for clustering methods |
| classifdist | Classification of unclustered points |
| classifnp | Classification of unclustered points |
| clucols | Sets of colours and symbols for cluster plotting |
| clugrey | Sets of colours and symbols for cluster plotting |
| clujaccard | Jaccard similarity between logical vectors |
| clusexpect | Expected value of the number of times a fixed point cluster is found |
| clustatsum | Compute and format cluster validation statistics |
| cluster.magazine | Run many clustering methods on many numbers of clusters |
| cluster.stats | Cluster validation statistics |
| cluster.varstats | Variablewise statistics for clusters |
| clusterbenchstats | Run and validate many clusterings |
| clusterboot | Clusterwise cluster stability assessment by resampling |
| clusym | Sets of colours and symbols for cluster plotting |
| cmahal | Generation of tuning constant for Mahalanobis fixed point clusters. |
| con.comp | Connectivity components of an undirected graph |
| confusion | Misclassification probabilities in mixtures |
| cov.wml | Weighted Covariance Matrices (Maximum Likelihood) |
| cqcluster.stats | Cluster validation statistics (version for use with clusterbenchstats |
| cvnn | Cluster validation based on nearest neighbours |
| cweight | Weight function for AWC |
| dbscan | DBSCAN density reachability and connectivity clustering |
| dbscanCBI | Interface functions for clustering methods |
| dipp.tantrum | Simulates p-value for dip test |
| diptest.multi | Diptest for discriminant coordinate projection |
| discrcoord | Discriminant coordinates/canonical variates |
| discrete.recode | Recodes mixed variables dataset |
| discrproj | Linear dimension reduction for classification |
| distancefactor | Factor for dissimilarity of mixed type data |
| distcritmulti | Distance based validity criteria for large data sets |
| disthclustCBI | Interface functions for clustering methods |
| disthclusttreeCBI | Interface functions for clustering methods |
| distnoisemclustCBI | Interface functions for clustering methods |
| distrsimilarity | Similarity of within-cluster distributions to normal and uniform |
| dridgeline | Density along the ridgeline |
| dudahart2 | Duda-Hart test for splitting |
| emskewCBI | Interface functions for clustering methods |
| extract.mixturepars | Extract parameters for certain components from mclust |
| findrep | Finding representatives for cluster border |
| fixmahal | Mahalanobis Fixed Point Clusters |
| fixreg | Linear Regression Fixed Point Clusters |
| flexmixedruns | Fitting mixed Gaussian/multinomial mixtures with flexmix |
| fpclusters | Extracting clusters from fixed point cluster objects |
| fpclusters.mfpc | Mahalanobis Fixed Point Clusters |
| fpclusters.rfpc | Linear Regression Fixed Point Clusters |
| fpmi | Mahalanobis Fixed Point Clusters |
| hclustCBI | Interface functions for clustering methods |
| hclusttreeCBI | Interface functions for clustering methods |
| itnumber | Number of regression fixed point cluster iterations |
| jittervar | Jitter variables in a data matrix |
| kmeansCBI | Interface functions for clustering methods |
| kmeansruns | k-means with estimating k and initialisations |
| lcmixed | flexmix method for mixed Gaussian/multinomial mixtures |
| localshape | Local shape matrix |
| mahalanodisc | Mahalanobis for AWC |
| mahalanofix | Mahalanobis distances from center of indexed points |
| mahalanofuz | Mahalanobis distances from center of indexed points |
| mahalCBI | Interface functions for clustering methods |
| mahalconf | Mahalanobis fixed point clusters initial configuration |
| mergenormals | Clustering by merging Gaussian mixture components |
| mergenormCBI | Interface functions for clustering methods |
| mergeparameters | New parameters from merging two Gaussian mixture components |
| minsize | Minimum size of regression fixed point cluster |
| mixdens | Density of multivariate Gaussian mixture, mclust parameterisation |
| mixpredictive | Prediction strength of merged Gaussian mixture |
| mvdcoord | Mean/variance differences discriminant coordinates |
| ncoord | Neighborhood based discriminant coordinates |
| neginc | Neg-entropy normality index for cluster validation |
| noisemclustCBI | Interface functions for clustering methods |
| nselectboot | Selection of the number of clusters via bootstrap |
| pamk | Partitioning around medoids with estimation of number of clusters |
| pamkCBI | Interface functions for clustering methods |
| pdfclustCBI | Interface functions for clustering methods |
| piridge | Ridgeline Pi-function |
| piridge.zeroes | Extrema of two-component Gaussian mixture |
| plot.clboot | Clusterwise cluster stability assessment by resampling |
| plot.dbscan | DBSCAN density reachability and connectivity clustering |
| plot.mfpc | Mahalanobis Fixed Point Clusters |
| plot.rfpc | Linear Regression Fixed Point Clusters |
| plot.valstat | Simulation-standardised plot and print of cluster validation statistics |
| plotcluster | Discriminant projection plot. |
| predict.dbscan | DBSCAN density reachability and connectivity clustering |
| prediction.strength | Prediction strength for estimating number of clusters |
| print.clboot | Clusterwise cluster stability assessment by resampling |
| print.clusterbenchstats | Run and validate many clusterings |
| print.dbscan | DBSCAN density reachability and connectivity clustering |
| print.mfpc | Mahalanobis Fixed Point Clusters |
| print.predstr | Prediction strength for estimating number of clusters |
| print.rfpc | Linear Regression Fixed Point Clusters |
| print.summary.cquality | Cluster validation statistics (version for use with clusterbenchstats |
| print.summary.mergenorm | Clustering by merging Gaussian mixture components |
| print.summary.mfpc | Mahalanobis Fixed Point Clusters |
| print.summary.rfpc | Linear Regression Fixed Point Clusters |
| print.valstat | Simulation-standardised plot and print of cluster validation statistics |
| print.varwisetables | Variablewise statistics for clusters |
| randcmatrix | Random partition matrix |
| randconf | Generate a sample indicator vector |
| randomclustersim | Simulation of validity indexes based on random clusterings |
| regem | Mixture Model ML for Clusterwise Linear Regression |
| regmix | Mixture Model ML for Clusterwise Linear Regression |
| rFace | "Face-shaped" clustered benchmark datasets |
| rfpi | Linear Regression Fixed Point Clusters |
| ridgeline | Ridgeline computation |
| ridgeline.diagnosis | Ridgeline plots, ratios and unimodality |
| simmatrix | Extracting intersections between clusters from fpc-object |
| solvecov | Inversion of (possibly singular) symmetric matrices |
| speccCBI | Interface functions for clustering methods |
| sseg | Position in a similarity vector |
| stupidkaven | Stupid average dissimilarity random clustering |
| stupidkavenCBI | Interface functions for clustering methods |
| stupidkcentroids | Stupid k-centroids random clustering |
| stupidkcentroidsCBI | Interface functions for clustering methods |
| stupidkfn | Stupid farthest neighbour random clustering |
| stupidkfnCBI | Interface functions for clustering methods |
| stupidknn | Stupid nearest neighbour random clustering |
| stupidknnCBI | Interface functions for clustering methods |
| summary.cquality | Cluster validation statistics (version for use with clusterbenchstats |
| summary.mergenorm | Clustering by merging Gaussian mixture components |
| summary.mfpc | Mahalanobis Fixed Point Clusters |
| summary.rfpc | Linear Regression Fixed Point Clusters |
| tclustCBI | Interface functions for clustering methods |
| tdecomp | Root of singularity-corrected eigenvalue decomposition |
| tonedata | Tone perception data |
| unimodal.ind | Is a fitted denisity unimodal or not? |
| valstat.object | Cluster validation statistics - object |
| weightplots | Ordered posterior plots |
| wfu | Weight function (for Mahalabobis distances) |
| xtable | Partition crosstable with empty clusters |
| zmisclassification.matrix | Matrix of misclassification probabilities between mixture components |


14.3. Help with Complex Emacs Commands
Many of the more
complicated Emacs commands include
their own sets of help keystrokes. These commands often have their
own help functionality, but help is invoked with ? rather than the standard help key. Here is a
summary of some popular complex commands and what ? does within each of them:
- dired (C-x d)
-
You see a list of the most frequently used commands in the
minibuffer. This list is far from complete. Type
C-h m (for describe-mode) for more comprehensive
documentation and C-h b (for
describe-bindings) for all the key
bindings available to you.
- query-replace (M-%)
-
You see a *Help*
window listing the available commands. Typing C-h does the same thing. This also works with
query-replace-regexp.
- save-some-buffers (C-x s)
-
Behavior is similar to query-replace
just described.
- list-buffers (C-x C-b)
-
You see a *Help* window giving information on
buffer menu mode. This command has the same effect as typing
C-h m (for describe-mode).
- Completion
-
When you are responding to a minibuffer prompt with the name of
something on which Emacs can do completion, typing ? at any time gives you a
*Completions* window with the choices available at
that point. Completion is explained in detail later in this chapter.
|


By Mark Oosterveld & Jerome Lecomte
(Trading Places -- 1983)
We had 4 days to decide on everything
before the co-ops started
Smashing Magazine article "Talks To Help You Become A Better Front-End Engineer in 2013"
yeoman.io
The best tools already configured
The best practices already applied
Demo time
gruntjs.com
Just another Javascript file
Easy to extend
Lots of modules available
Great build process
Unit testing with PhantomJS
Preview server
LiveReload code & stylesheets
Demo time
bower.io
Like 'npm install' for client-side Javascript libraries
Layout core classes of Backbone application
Get familiar with BDD & Coffeescript
coffeescript.org
Only the best parts
Safety of compiled language
Demo time
(courtesy of iome.me)
visionmedia.github.io/mocha
chaijs.com
sinonjs.org
describe 'Creating an account model with data from the API', ->
account = 0
before ->
# Arrange
data =
accountName: 'Primary'
# Act
account = new Backbone.Model data
# Assert
it 'should rename the accountName property', ->
account.get('name').should.equal 'Primary'
# Restore
after ->
requirejs.org
Too many modules leads to <script> ordering hell
Just explicit the module dependencies
And let RequireJS figure out the loading order
index.html
main.coffee
require ['views/AccountDetailsView'], (AccountDetailsView) ->
app = new AccountDetailsView()
AccountDetailsView.coffee
define ['models/AccountModel'], (AccountModel) ->
class AccountDetailsView
constructor:
@account = new AccountModel()
backbonejs.org
Ideal for client-side single-page application
Prior experience
Demo time
sass-lang.com
Variables
Nesting rules
Mixins
And more
Demo time
handlebarsjs.com
TradeListView.coffee
$('.trades-list').append
"
#{trade.id}
#{trade.get 'pair'}
...
"
index.html
TradeListView.Coffee
trade_tmpl = $ '#tmpl-trades-item'
trade_tmpl.find('.trade-id').text trade.id
trade_tmpl.find('.trade-pair').text trade.get 'pair'
$('.trades-list').append trade_tmpl.html()
index.html
TradeListView.coffee
template = Handlebars.compile $('#tmpl-trades-item').html()
html = template
id: trade.id
pair: trade.get 'pair'
$('.trades-list').append html
trade_item.hbs
{{id}}
{{pair}}
TradeListView.coffee
html = Handlebars.template.trades_item
id: trade.id
pair: trade.get 'pair'
$('.trades-list').append html
Manually upgrading Yeoman to 1.0.0 beta from 0.9.6
Coffeescript compiler got stricter in 1.6.2
Natively with Safari, Google Chrome
3rd party library Weinre for IE, Firefox, Opera
REST-like API with Cross-Origin Resource Sharing
Changes must be approved and verified before being merged into master
Gerrit
(+) Remote git repository, automatically keeps in sync with upstream
(-) Austere UI, 1 review per commit
Github
(+) Very popular , 1 review per branch
(-) Manually keep fork in sync with upstream, lots of merge clouds history
jenkins-ci.org
Code sitting in your repository is software inventory (Joel Spolsky)
Run testsuite on every new commit
If successful, package application
Deploy package to production
Monitor trend changes in key metrics
Figure it out early on to mitigate that risk
If need be, the application can ship today
<EMAIL_ADDRESS>jerome@oanda.com


Welcome to Nebula
The nebula-plugins organization was setup to facilitate the generation, governance, and releasing of Gradle plugins. It is done by providing a space to host plugins, in SCM, CI, and a Repository. A single GitHub organization is used, for which anyone or any plugin can be added. Cloudbees jobs are created for every plugin to provide a standard set of jobs. Releases are posted to bintray, proxied to JCenter and synced to Maven Central. While not all steps are automated (yet), the goal to a self-service fast controlled flow plugins out to entire Gradle community.
nebula-plugins was founded by Justin Ryan (@quidryan) as an effort at Netflix to share its internal build infrastructure.
SCM
The GitHub organization nebula-plugins (https://github.com/nebula-plugins/) is just that, an organization. Any willing contributor can be added to the organization. That allows a level of collaboration between interested parties that isn't available when a plugin is locked up in an user's account.
Continuous Integration
Using Cloudbees, there's a hosted Jenkins instance (via Netflix) to host build jobs (https://netflixoss.ci.cloudbees.com/job/nebula-plugins/). The Job DSL plugin is used to ensure the jobs are standardize, and updated when improvements are made (https://netflixoss.ci.cloudbees.com/job/nebula-plugins/job/SEED-nebula-plugins/). The core jobs are ones to build the HEAD, check pull requests, and release the plugin.
Repositories
Upon release, a plugin is uploaded to the nebula-plugins organization in bintray (https://bintray.com/nebula/gradle-plugins). If configured correctly, those uploads are linked to JCenter, meaning they're instantly available to any Gradle user using the jcenter() repository. They are then synced to Maven Central under the com.netflix.nebula group name.
To Get Started
TBD
Contributing
Every contribution is highly welcome whether that's documentation, bugfixes, new features or improved test coverage. Nebula follows the usual GitHub pull request model. When submitting a pull request, please open it against the current default branch of the project. The default branch indicates the compatible Gradle version. For example if the branch is named gradle-1.12
it means that it is developed and tested against Gradle version 1.12. After merging a pull request into the default branch the Nebula team will take care of merging the change to branches dedicated to later Gradle versions. Thanks for your contributions!
Support or Contact
Join the Google Group nebula-plugins to questions, https://groups.google.com/forum/#!forum/nebula-plugins.


Websockets
Introduction
This tool has been made available in order to provide real-time updates from assets in theOrganiCity platform. As an example, I might want to get a notification if the lights suddenly turns on in my office. By having e.g. a smartphone application that is using the websockets tool, it becomes possible to listen for updates coming directly from the office (provided that the office's light source is registerede as an asset in the OrganiCity platform). More generally, this tool creates a websocket client for connecting with the OrganiCity platform, and subscribe to updates on assets already registered on the platform.
Installation
In order to make this tool work one would need to be working in a Java environment, and it is therefore a prerequisite that a java IDE is installed. Otherwise, the installation is quite simple.
- Go to this Github page and download the project as a zip file: https://github.com/OrganicityEu/WebsocketClient
- Unzip the file locally
- You can either open the entire websockets project as a maven project in your favourite java IDE or simply import WebsocketsClient/libs/WebsocketClient.jar as an external jar into your existing project
That is it! In the following section, we will provide a concrete usage example on how to import the websocket tool as an external jar into a new java project.
Usage example
This section provides a simple example on how to use the websocket tool, and we will be using Netbeans as the java IDE. The specific example shows how to subscribe to a single asset already created in the OrganiCity platform (it is not possible to subscribe to more than one asset at a time, and it is not possible to subscribe to creation or deletion of a new asset).
Start Netbeans and create a new empty java project
The below screenshots show the steps of creating a simple java application
When the java project has been created it is time to import the websocket connection
Add WebsocketsClient.jar as external jar
The below screenshots show how to add an external jar to an existing java project.
First you need to right-click on the "Libraries" folder and select "Add Jar/Folder..."
Then you have to browse to where you unzipped the file from Github (see Installation section), select teh file named "WebsocketClient.jar", and finally click "Choose".
That's it. The library has now been imported and can be leveraged in your project. In order to test the websocket functionality it is required to have an existing asset. If you don't have an existing asset, then read the next section. Otherwise, you can skip this section and jump directly to "Get authentication token".
Adding an asset (can be omitted if there is already an asset available)
This task can only be performed if you are a registered OrganiCity experimenter! In order to become an experimenter go to this website https://experimenters.organicity.eu, and click "Sign in" (even if you don't have a user yet - you can create one).
You create a new asset by following this the steps in this link: http://docs.organicity.eu/HowToPushAnAssetToTheExperimenterSite/#tutorial-how-to-push-an-assets-to-the-organicity-experimenter-site
When the asset has been created, the next step is authentication.
Get authentication token
In order to be able to actually subscribe to a specific asset you need an anthentication token (a proof that you actually have the rights to get the information from the asset). This can be quite tricky, but we have created a tutorial on how to get the token: http://docs.organicity.eu/HowToAuthenticateAnUser/. You can either follow the steps directly from top to bottom or you can scroll all the way to the bottom of the tutorial and leverage existing libraries which might reduce some of your complexity.
When you have generated the authentication token it is time write some code.
Code example
Below is a code snippet showing how to subscribe to a specific asset. The specific code is not of any great use in a real setting, since it just performs a new subscription, and then deletes it five seconds later. The only purpose of the example is to show how to both subscribe and unsubscribe.
You can subscribe to an asset by using one of the following two constructors:
- The simple: public OrionSubscription(String entityId, String token)
- The advanced: public OrionSubscription(String[] conditions, String[] attributes, String entityId, String token)
A specific code example would be:
OrionSubscription subscription = new OrionSubscription("some_entity_id", "some_token_string");
Each of the parameters are described in the table below
| Parameter | Description | Value | Type |
|---|---|---|---|
| conditions | Defines the "trigger" for the subscription | Need value | String[] |
| attributes | Define the "triggering attributes" | Need value | String[] |
| entityId | Id of the asset you want to subscribe to | Need value | String |
| token | The token accuired in the previous step | Need value | String |
Below is an example of a valid asset:
{
"id": "urn:oc:entity:experimenters:5a660d96-0ef7-42ca-9f6c-5dbb86d6aa20:58ab32f36f8b513746565c54:wsasset",
"type": "urn:oc:entityType:userImage",
"TimeInstant": {
"type": "urn:oc:attributeType:ISO8601",
"value": "2016-10-04T13:45:00.000Z",
"metadata": {}
},
"comments": {
"type": "urn:oc:attributeType:text:string",
"value": "hello",
"metadata": {}
},
"user": {
"type": "urn:oc:attributeType:text:string",
"value": "world",
"metadata": {}
}
}
And now the actual code :-)
import java.util.List;
import dk.alexandra.orion.websocket.transports.OrionSubscription;
import websockets.WebsocketClientStomp;
import websockets.handlers.WebsocketCallback;
public class VanillaTestClient implements WebsocketCallback{
WebsocketClientStomp wsc;
long now;
boolean hasSubscription = false;
public VanillaTestClient(){
now = System.currentTimeMillis();
wsc= new WebsocketClientStomp(this, "ws://<IP_ADDRESS>:8090/orion");
startLoop();
}
private void startLoop(){
while(true){
if(System.currentTimeMillis()>now+5000){
if(!hasSubscription){
/*
Example of setting conditions and attributes. "comments" and "user" are taken
from the example asset above. When using these, you will get a notifaction
with user information, when the comment is altered (if "hello" is changed to
something else)
*/
String[] attr = new String[1];
attr[0] = "comments";
String[] cond = new String[1];
cond[0] = "user";
String entityId = "<Your asset id here here>";
String token = "<Your token here>";
//Example of subscribing to certain asset conditions and attributes
//OrionSubscription subscription = new OrionSubscription(cond, attr, entityId, token);
//Example of subscribing to a certain asset without any specific conditions
OrionSubscription subscription = new OrionSubscription(entityId, token);
System.out.println("trying to set subscrition");
hasSubscription = wsc.registerSubscription(subscription);
if(hasSubscription){
System.out.println("subscription set");
}
}else{
List<String> subscriptions = wsc.getSubscriptions();
if(subscriptions.size()>0){
if(wsc.unregisterSubscription(subscriptions.get(0))){
hasSubscription=false;
}
}
}
now = System.currentTimeMillis();
}
}
}
@Override
public void messageReceived(String mesg) {
System.out.println("Received message in Processing "+mesg);
}
public static void main(String[] args){
System.out.println("Starting Vanilla test client");
VanillaTestClient client = new VanillaTestClient();
}
}
If everything went as expected, then you have now made your first subscriptioon to the OrganiCity platform, and you are ready to make your application truely responsive to changes within OrganiCity.
Technical background
The OrganiCity platform is built around the Orion Context Broker (https://fiware-orion.readthedocs.io/en/master/), and the websockets tool conform to the abilities and formats dictated by the context broker. As the Context Broker is REST based, we provide a Spring.io based middleware (https://github.com/OrganicityEu-Platform/WebsocketMiddleware) for transforming the connections between REST and Websockets.
For further technical and code detail, please take a look here: https://github.com/OrganicityEu/WebsocketClient
Technical reference to the Orion context brokers subscription feature: https://fiware-orion.readthedocs.io/en/develop/user/walkthrough_apiv2/index.html#subscriptions
Look there to acquire token: http://docs.organicity.eu/HowToAuthenticateAnUser/
Known issues
When running the example code directly from within your IDE (e.g. Eclipse or Netbeans) it seems that the java process will not close down when stopping the application.  If you run the example from the commandline (as the final application outside of the IDE) then there should be no problems - it should all be working as expected, and all related java processe will clode down correctly.


This intention replaces intialization of field via assignment with field initializer.
Please note that this intention may change program semantics.


DebugCommand Class Reference
#include <InteractiveDebugger.hpp>
List of all members.
Constructor & Destructor Documentation
| virtual DebugCommand::~DebugCommand |
( |
|
) |
[inline, virtual] |
| DebugCommand::DebugCommand |
( |
const char * |
name, |
|
|
const char * |
compatName, |
|
|
const char * |
briefHelp, |
|
|
const char * |
moreHelp | |
|
) |
| | [inline, protected] |
Member Function Documentation
| virtual const char* DebugCommand::getBriefHelp |
( |
|
) |
const [inline, virtual] |
| virtual const char* DebugCommand::getCommandName |
( |
|
) |
const [inline, virtual] |
| virtual const char* DebugCommand::getCommandNameCompat |
( |
|
) |
const [inline, virtual] |
| virtual const char* DebugCommand::getMoreHelp |
( |
|
) |
const [inline, virtual] |
| virtual bool DebugCommand::matches |
( |
const std::string & |
command |
) |
const [virtual] |
| static bool DebugCommand::matches |
( |
const std::string & |
command, |
|
|
const std::string & |
toMatch | |
|
) |
| | [static] |
Member Data Documentation
The documentation for this class was generated from the following file:


| Quickly reads the value of a single pixel on the screen. |
| x = x location of the pixel to read y = y location of the pixel to read buffer = any valid screen/image buffer (optional) |
Command Description:
| This command will allow you fast access to a specific pixel in the buffer selected. While this command reads the pixel quickly (and it can be written back quickly with WritePixel, it is still not fast enough for real-time screen effects. You are not required to lock the buffer with LockBuffer and subsequently unlock the buffer with UnlockBuffer. However, the operations will be a bit faster if you do. V1.52 and above: It has been necessary to make ReadPixel and ReadPixelFast "alpha-aware". This means that the high 8 bits of the color returned ReadPixel/ReadPixelFast now contain valid alpha information. However, in the case of Blitz2D apps, there is no alpha information in images! Mark decided that in the abscence of any alpha information, a pixel is assumed to have 'full' alpha. Therefore, values returned by ReadPixel/ReadPixelFast will now (usually) have their high 8 bits sets. The exception will be when reading pixels from Blitz3D textures created with an alpha channel. To get the old behaviour of v1.50 (and below) of ReadPixel/ReadPixelFast, use the following: rgb=ReadPixel( x,y ) And $FFFFFF This will 'mask out' the 8 high bits of alpha and return just the red, green and blue components of the pixel. |
Example:
| ; High Speed Graphics Commands Graphics 640,480,16 ; Draw a bunch of crap on the screen For t= 1 To 1000 Color Rnd(255),Rnd(255),Rnd(255) Rect Rnd(640),Rnd(480),Rnd(150),Rnd(150),Rnd(1) Next Delay 3000 ; Copy the top half of the screen over the bottom half ; using fast pixels and locked buffers LockBuffer FrontBuffer() For x = 1 To 640 For y = 1 To 240 WritePixelFast x,y+241,ReadPixelFast(x,y) Next Next UnlockBuffer FrontBuffer() Delay 3000 ; Draw the left half of the screen over the right half ; using the slower direct pixel access For x = 1 To 320 For y = 1 To 480 WritePixel x+320,y,ReadPixel(x,y) Next Next |


How to access syslog data for your edge gateway
Overview
Your edge gateway is globally configured to send syslog messages to a specific IP address (<IP_ADDRESS>
). By configuring a new network or IP address within your virtual data centre (VDC) and deploying a collector with the syslog IP address, you can access your edge gateway
syslog data. You can then use this data to check:
Allowed and denied network traffic
Load balancer statistics
Load balancer health
This guide explains the network configuration required to provision a syslog collector within your VDC to receive syslog information direct from your edge gateway.
Collecting syslog data for a single edge gateway
The simplest scenario is to gather syslog data from a single edge gateway into one collector. To do this you need to create a routable location for the syslog IP address, by either:
Adding the syslog IP address to an existing network interface card (NIC) on a routed subnet
Add the syslog IP address to a subnet on the routed network.
For example, if your existing monitoring server has a NIC on eth0 (for example,
<IP_ADDRESS>
), on routed Org VDC network<IP_ADDRESS>/24
, you'd add the syslog IP address to eth0.Add a route on the vCNS Edge that routes the syslog IP address via the subnet.
For example, route
<IP_ADDRESS> MASK <IP_ADDRESS>
via<IP_ADDRESS>
.Configure the software on your existing monitoring server to capture data from the IP address of the vCNS edge.
Note
The steps to achieve this depend on your operating system and chosen syslog server.
Configuring a new routed network
Create a new routed network with the following details:
Org Network Name: Customer defined
Gateway:
<IP_ADDRESS>
Subnet Mask:
<IP_ADDRESS>
DNS: Customer defined
Static IP Pool:
<IP_ADDRESS> -- <IP_ADDRESS>
You can find more detailed steps for creating a routed network in How to create a routed VDC network.
Deploy a new syslog server connected to the new routed network with a static address of
<IP_ADDRESS>
and install and configure the syslog server's edge gateway.Note
The steps to achieve this depend on your operating system and chosen syslog server.
Collecting syslog data for multiple edge gateways
If you have multiple edge gateways under a single NFT you can gather the data from all those edges into the same syslog collector.
Set up a single syslog collector for one of your vCNS Edges as described in the previous section.
Note
We'll refer to this edge gateway as the syslog edge and all the other edge gateways as source edges.
Confirm that you can see the local syslog traffic from the local syslog edge.
Create a firewall rule on the syslog edge to allow syslog traffic from the source edges' TRANSIT IPs (
172.26.
x
.
x
in Assured or172.26.
LOWER OCTET
.
x
in Elevated) through to the syslog server IP.You can create individual rules using the following suggestions:
<SOURCE TRANSIT IP>:Any
to<IP_ADDRESS>
on UDPAny:Any
to<IP_ADDRESS>:514
on UDP<NFT TRANSIT CIDR/SUBNET>:Any
to<IP_ADDRESS>:514
on UDP
On each of the source edges, create a static route to direct traffic to the syslog edge. Use the following settings:
Applied On:
<nft_network>
Name: Syslog traffic (or any other name you prefer)
Network:
<IP_ADDRESS>/29
Next Hop IP: The TRANSIT IP address of the syslog edge
Syslog packets from each source edge will now be forwarded to the syslog edge, with the source of the syslog traffic being the TRANSIT IP of the source edge.
Perform a packet capture on the syslog collector to confirm it's receiving packets from the source edges.
Note
You may have to enable or disable logging on firewall rules to trigger syslog traffic.
When you've confirmed that your syslog collector is receiving the syslog data, configure your syslog server to capture packets from the new syslog source.
Enabling logging
After setting up your syslog collector, you need to make sure that your edge gateway sends network traffic to the log.
Edit your vCNS Edge firewall settings to log firewall rules:
You must log each rule individually by selecting the Log network traffic for firewall rule option:
To log data for actions not covered by individual rules, select the Log option next to the Default action setting:
You can find more detailed steps for editing firewall settings in How to create firewall rules.
Edit your load balancer settings to log virtual servers:
You can find more detailed steps for editing load balancer settings in How to configure a load balancer.
Sample syslog captures
Firewall denied
firewall[]: [073ab562-9147-428c-bf0c-33139c6ec51e]:**DROP**_131073IN= OUT=vNic_0 SRC=<IP_ADDRESS> DST=<IP_ADDRESS> LEN=44 TOS=0x00 PREC=0x00 TTL=254 ID=25689 PROTO=ICMP TYPE=8 CODE=0 ID=7 SEQ=62584 MARK=0x207
Firewall allowed
firewall[]: [073ab562-9147-428c-bf0c-33139c6ec51e]: **ACCEPT**_319IN= OUT=vNic_4 SRC=<IP_ADDRESS> DST=<IP_ADDRESS> LEN=36 TOS=0x00 PREC=0x00 TTL=63 ID=0 DF PROTO=ICMP TYPE=8 CODE=0 ID=27693 SEQ=1 MARK=0x6
Load balancer statistics
loadbalancer[5899]: [073ab562-9147-428c-bf0c-33139c6ec51e]: xx.xxx.xxx.xxx:51699 [23/May/2016:14:43:38.242] TEST_CONN_8040_1625_HTTP TEST CONN_UAT_8040_1625_HTTP/TEST CONN_UAT_8040_1625_HTTP_<IP_ADDRESS> 0/0/0/1/1 200 2127 - - --VN 12/5/4/2/0 0/0 "GET /OA_MEDIA/FNDSSCORP.gif HTTP/1.1"
Refer to https://cbonte.github.io/haproxy-dconv/1.5/configuration.html#8 for information about how to interpret the load balancer logs.
Feedback
If you find a problem with this article, click Improve this Doc to make the change yourself or raise an issue in GitHub. If you have an idea for how we could improve any of our services, send an email to feedback@ukcloud.com.


game module
This module runs both the bomberman game and the machine learning modules.
Project : Bomberman Bot with Machine Learning
Olin College Software Design Final Orject, Spring 2017
This module is originally written by Rickyc (Github user)
Team AFK added machine learning Features to the original module.
-
class
game.
Game
(mode)[source]
Bases: object
Stores, updates, and maintains all data and features
relavant to running the bomberman game.
-
activateBomb
(bomb)[source]
Remove bomb, kill surroundings
-
blit
(obj, pos)[source]
-
bombHelper
(bomb, direction)[source]
-
bombs
= []
-
checkPlayerEnemyBombCollision
(position)[source]
Check bomb’s effects against player and enemy positions and clear
if need be
-
checkPlayerEnemyCollision
()[source]
Check if enemy has killed player
-
checkWinConditions
()[source]
-
clearBackground
()[source]
Clears the background image.
-
clearExplosion
()[source]
Update board accordingly to bomb’s effect
-
deployBomb
(player)[source]
Placing of bombs based
Additional code written so machine learning can
recognize if it is standing on a bomb as usually player
overwrites bomb
-
drawBoard
()[source]
Draws the board onto the screen
-
drawInterface
()[source]
Draws the Interface Graphics.
-
enemies
= []
-
exitGame
= False
-
fQuit
()[source]
-
firstRun
= True
-
gameover
(player)[source]
-
initEnemies
(num)[source]
Generates enemies in semi-random positions around the board
(Will not spawn near player)
-
initGame
()[source]
Initializes the game with necessary attributes.
-
initPlayers
()[source]
Displays the players on the board
-
level
= 1
-
movementHelper
(char, point)[source]
Moves player in code
-
players
= []
-
printText
(text, point)[source]
-
resetGame
()[source]
Clears the board data, Called on death or level clear
-
resetPlayerPosition
(player, death)[source]
Put player back in top left on death or level clear
-
resetTiles
= []
-
restart
()[source]
This function forces the game to go back to its initial state
-
runGame
()[source]
Cycles and updates all the game states and variables
-
stage
= 1
-
triggerBombChain
(bomb)[source]
Allow for bombs to activate other bombs
-
updateBombs
()[source]
Countdown bombs, explode if needed
-
updateDisplayInfo
()[source]
Displays the charater stats (score, lives, mxBombs, power)
-
updateTimer
()[source]
-
victory
()[source]


[
{
original: "If it rains today, soccer practice will be canceled.",
converse: "If soccer practice is canceled today, then it did rain.",
inverse: "If it does not rain today, soccer practice will not be cancelled.",
contrapositive: "If soccer practice is not canceled today, then it did not rain."

},
{
original: "If I study really hard, I will ace the test.",
converse: "If I aced the test, then I studied really hard.",
inverse: "If I do not study really hard, then I will not ace the test.",
contrapositive: "If I did not ace the test, then I did not study really hard."
},
{
original: "John likes sushi.",
converse: "If a person likes sushi, then the person is John.",
inverse: "If a person is not John, then the person does not like sushi.",
contrapositive: "If a person does not like sushi, then the person is not John."
},
{
original: "If two angles are vertical angles, then the two angles are congruent.",
converse: "If two angles are congruent angles, then the two angles are vertical angles.",
inverse: "If two angles are not vertical angles, then the two angles are not congruent.",
contrapositive: "If two angles are not congruent, then the angles cannot be vertical angles."
},
{
original: "My dad has to take me to school when I miss the bus.",
converse: "If my dad takes me to school, then I must have missed the bus.",
inverse: "If I do not miss the bus, then my dad does not have to take me to school.",
contrapositive: "If my dad does not have to take me to school, then I did not miss the bus."
},
{
original: "All squares are four-sided polygons.",
converse: "All four-sided polygons are squares.",
inverse: "All polygons that are not squares do not have four sides.",
contrapositive: "If a polygon does not have four sides, then it is not a square."
},
{
original: "All bicycles have two wheels.",
converse: "All vehicles with two wheels are bicycles.",
inverse: "All vehicles that are not bicycles do not have two wheels.",
contrapositive: "If a vehicle does not have two wheels, it is not a bicycle."
},
{
original: "If it is Thanksgiving, then I will have a big dinner.",
converse: "If I have a big dinner, then it is Thanksgiving.",
inverse: "If it is not Thanksgiving, then I will not have a big dinner.",
contrapositive: "If I did not have a big dinner, then it is not Thanksgiving."
},
{
original: "If I go to the Yankees game, I will have a hot dog.",
converse: "If I don't go to the Yankees game, I will not have a hot dog.",
inverse: "If I have a hot dog, then I will go to the Yankees game.",
contrapositive: "If I don't have a hot dog, then I did not go to the Yankees game."
},
{
original: "Eating spinach makes you stronger.",
converse: "If you are getting stronger, the you must be eating spinach.",
inverse: "If you are not eating spinach, then you will not get stronger.",
contrapositive: "If you are not getting stronger, then you are not eating spinach."
},
{
original: "You should not use your cell phone when driving a car.",
converse: "If you are not using your cell phone, then you are driving a car.",
inverse: "If you are not driving a car, then you should use your cell phone.",
contrapositive: "If you are using your cell phone, then you should not be driving a car."
},
{
original: "If a number is divisible by 10, then it is an even number.",
converse: "If a number is even, then it is divisible by 10.",
inverse: "If a number is not divisible by then, then it is not an even number.",
contrapositive: "If a number is not even, then it is not divisible by 10."
}
]
randFromArray(PROBLEMS)
"Yes, it can be deduced from the first statement"
"No, it cannot be deduced from the first statement"
randFromArray(["converse", "inverse", "contrapositive"])
PROBLEM[STATEMENT_TYPE]
STATEMENT_TYPE === "contrapositive" ? MUST : MIGHT
Assume this first statement is true:
PROBLEM.original
Logically, can you deduce that this second statement must be true from the first one?
STATEMENT
ANS
Is the second statement the converse, inverse, or contrapositive of the original statement?
The second statement is the STATEMENT_TYPE of the original statement.
The STATEMENT_TYPE is logically equivalent to the original statement, so yes, the second statement can be deduced from the first statement.
The STATEMENT_TYPE is not logically equivalent to the original statement, so no, the second statement cannot be deduced from the first statement.
randFromArray(PROBLEMS)
PROBLEM.contrapositive
[PROBLEM.converse, PROBLEM.inverse]
Assume this original statement below is true:
PROBLEM.original
Choose the statement that must also be true logically:
ANS
Only the contrapositive of the original statement must be true.
Find the contrapositive. In other words, find the statement that reverses and negates both the hypothesis and conclusion.
In this case, the contrapositive is "PROBLEM.contrapositive"
["original statement", "converse", "inverse", "contrapositive"]
randRange(0, 3)
NAMES[3-CASE]
shuffle((function(){var opt = NAMES.slice(); opt.splice(CASE, 1); return opt;})())
If the NAMES[CASE] is true, then which other statement must be true logically?
the ANS
The original conditional statement and its contrapositive are logically equivalent, and the converse and the inverse are logically equivalent.
Logically equivalent statements have the same truth-value.
Because the NAMES[CASE] is true, the NAMES[3-CASE] is also logically true.


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Use the link below to log into your Appian environment in a separate tab and then click Refresh to view your task list in Gmail.


summary data of a group of limit orders
More...
#include <api.hpp>
summary data of a group of limit orders
Definition at line 605 of file api.hpp.
◆ limit_order_group() [1/2]
◆ limit_order_group() [2/2]
| graphene::app::orders_api::limit_order_group::limit_order_group |
( |
| ) |
|
|
default |
◆ max_price
| price graphene::app::orders_api::limit_order_group::max_price |
possible highest price in the group
Definition at line 615 of file api.hpp.
◆ min_price
| price graphene::app::orders_api::limit_order_group::min_price |
possible lowest price in the group
Definition at line 614 of file api.hpp.
◆ total_for_sale
| share_type graphene::app::orders_api::limit_order_group::total_for_sale |
total amount of asset for sale, asset id is min_price.base.asset_id
Definition at line 616 of file api.hpp.
The documentation for this struct was generated from the following file:
- libraries/app/include/graphene/app/api.hpp


HOME
HOTELS
HOLIDAYS
EXPLORE
MAPS
BOOKING
Select Seats
Payment
Select card
Debit Card
Credit Card
BOOK SEAT


{% extends 'email_base.html' %} {% load i18n %} {% block message %}
{% blocktrans with site_domain=site.domain %}You're receiving this e-mail because you or someone else has requested a password for your user account at {{ site_domain }}.{% endblocktrans %}
{% blocktrans %}It can be safely ignored if you did not request a password reset. Click the link below to reset your password.{% endblocktrans %}
{% include "_email_button.html" with link=password_reset_url text=_("Click here to reset your password.") %}
{% if username %}{% blocktrans %}In case you forgot, your username is {{ username }}.{% endblocktrans %}
{% endif %} {% endblock %}


Salman Khan issues chilling warning to Siddharth Shukla, dares him for physical fight either inside or outside Bigg Boss house
by JKR StaffBollywood megastar and Bigg Boss show’s host Salman Khan has reportedly lashed out at contestant Siddharth Shukla and reminded him of the consequences of his bad behaviour. Salman also reminded him of consequences if he wants to stay in the ‘industry.’ In another extraordinary development, Salman challenged Siddharth for a fight either inside the Bigg Boss house or outside.
An angry Salman told Siddharth bluntly that if he was so keen to flaunt his muscle power, then he should try that on the former either inside the reality show or outside. “Shukla ji, you have plenty of anger and you have a huge physique. Would you like to try it (on me) at some point?  Or call me inside the house,” said Salman menacingly.
Salman also reportedly asked Siddharth if he had no intention to work in the industry, implying that he will have no work if his violent behaviour continued.
Salman also said without naming any contestant, “If I had the right to evict one housemate, then I would have done so right now.”
Salman also criticised Asim Riaz for provoking Siddharth and asked him he had become arrogant. He asked Asim if his reaction was due to his arrogance or self-esteem. Asim replied saying that it was his self-esteem, prompting Salman to ask if the contestant knew the difference between the two.
Salman also asked Asim to walk out of the show after the latter said that if the allegations against him that he pushed other contestants without provocation were true, then he will walk out of the show. Salman replied, “Then you will have to walk out of the show.”
Siddharth and Asim have been fighting violently all through this week. Many concluded that Siddharth ought to have been evicted for his repeated violent behaviour, but he has stayed in the show.
As reported by Janta Ka Reporter, Khesari Lal Yadav was evicted from the show through the votes of the housemates.


{{ fromUser | displayUser | async }} invited you to {{ event.type | toLabel:'eventTypes' }} {{ event.title }} ({{ event | eventRange }})
{{ _invitation.fromOrg.name }} invited you to {{ event.title }} ({{event | eventRange }})
{{ fromUser | displayUser | async }} would like to attend {{ event.type | toLabel:'eventTypes' }} {{ event.title }} ({{ event | eventRange }})
{{ _invitation.fromUser | displayUser | async }} would like to attend {{ event.type | toLabel:'eventTypes' }} {{ event.title }}. ({{ event | eventRange }})


This chart looks at the break-up of diesel prices in India and Pakistan. That is, how much gets paid in (a) taxes and duties, as well as (b) the commission charged by the dealer. It also includes the (c) the price paid by oil marketing companies (OMC) as India's Hindustan Petroleum and Pakistan State Oil to petroleum refiners and (d) OMC margins .
Indians pay $0.38/litre of diesel as taxes and duties while Pakistanis just pay less than half that at $0.16/litre.
(Hover over each layer for more details. Click on the buttons below to stack or unstack the layers and get a different view.)


Concepts
Notation for transforms
In the following, transforms written as: $$ \ctrans{T}{A}{B} $$
take coordinates $\cvec{X}{A}$ in frame $\mathrm{A}$ and express them in frame $\mathrm{B}$: $$ \cvec{X}{B} = \ctrans{T}{A}{B}\ \cvec{X}{A} $$Bodies
In TagSLAM, every tag is associated with a body, and tag poses are given relative to that body. Likewise, every camera must be associated with a body, and camera poses are expressed with respect to that body.
Consider the following scene:
In the example above, for the camera to localize itself, the “lab” body’s world pose $\ctrans{T}{lab}{map}$ must be specified, as well as the pose $\ctrans{T}{tag\_2}{lab}$ of the tag with respect to the lab. Also needed is the pose $\ctrans{T}{cam0}{cam\_rig}$ of the camera with respect to the body it is attached to (“cam_rig”).
For the block to be localized by TagSLAM, we only need to provide $\ctrans{T}{tag\_105}{block}$. When the camera sees tags 2 and tag 105 at the same time, it will be able to infer the missing transform $\ctrans{T}{block}{map}$.
Poses
Poses can be classfied according to their time dependence:
-
Static poses: such poses do not change over time, i.e. TagSLAM will maintain a single variable throughout the entire data set. An example would be the pose of the lab $\ctrans{T}{lab}{map}$.
-
Non-static poses: they can potentially change with every frame. An example would be the pose $\ctrans{T}{cam\_rig}{map}$ of the camera rig or the pose $\ctrans{T}{block}{map}$ of the block.
Note that tag and camera poses are always static! That means they do not change with time, i.e. TagSLAM assumes one constant pose over time. However, the body to which the tags or cameras are attached can have a time dependent pose!
Further, static poses are distinguished by prior knowledge:
- Known poses: the pose is already known at the start, for instance from a previous run of TagSLAM.
- Unknown poses: the pose, although static, is unknown at the beginning, and must be discovered on the fly.
Specifying poses
Poses in TagSLAM are given as position and rotation components (SE(3)). The rotations are specified as a rotation vector, i.e. the log of the rotation matrix. The direction of the rotation vector specifies the rotation axis, the length of it the rotation angle in radians. Use Andre Gaschler’s handy rotation converter to convert to and from “axis with angle magnitude (radians)".
Convention for tag poses
Here is how the coordinate axes are oriented when facing an upright AprilTag. Also note the corner numbering in purple.


This application allow you to capture expenses when you are on the go and stores them in an Excel workbook in OneDrive for Business. You can even capture receipts!
Sign-in with Office 365


I am a second-year student at Leeds Trinity University studying BA Accounting and Business after spending two years at the University of Leeds. People recognise me as a practical learner because I quickly adapt to new situations, as highlighted in my recent change in my academic studies. I am looking for a professional work placement in a creative marketing environment where I can contribute with my extensive skillset as supported by my academic results.
Communication skills improved as I tested my social anxiety and continue to work well. Quality control for the aesthetics of the restaurant as I maintained a clean and safe work environment.
Demonstrated my hardworking attitude in a challenging environment. I helped design and create bathrooms and kitchens with the materials supplied by the customer.
Improvement in my sociological skills as I ventured out with my team to collect donations. Can perform calmly under pressure, as it was needed on some occasions.
This course has helped me address skills that I have to learn to be a successful accountant and has helped me expand my horizons by introducing me to a coding module which has allowed me to be familiar
I have achieved great heights with my Mathematics Modules like Mathematical Economics as I got near perfect scores in my exams. I also trained in management and accounting modules to expand my creativity and motivation to work as I constructed and presented presentations whilst learning the accounting language.
Currently a Bassist in a band called Redgrave. Our following is not very high, but it is mostly for fun. Currently constructing an album with songs such as Spaceship and Never Give Up. This experience has helped me network with other musicians, so I can keep up to date with the latest bands.
I am a video game enthusiast who has started attending tournaments, so I can test my skill against another person who enjoys games like I do.
I do not enjoy just standing around if there is something to be done, so I will always try to be productive in a working environment and I aim to improve efficiency by addressing my ideals and being a driving force to motivate colleagues so there is no waste of resources and everyone is constantly moving towards our set goals.


Customer assessment is imperative to grow your existing business
In order for your existing business to thrive you need to be able to successfully manage your existing customer base. To do that you need to segment your customer base for further assessment.
Customer segmentation should be done based on:
- Customer Attrition Risks
- Customer Profitability
- Customer Purchase Size and Frequency
Each one of the segments created above should drive the right marketing strategy, e.g. High attrition of profitable customers that buy a lot and often should drive a different strategy than low attrition customers that aren’t profitable and buy little and not very often.
Bear in mind that depending on your type of business and market differences (B2B vs B2C) you might not have to create all segments possibilities mentioned above, e.g. a profitable B2C retail customer segment might imply that the segment purchase size is large. On the other hand on a B2B model you might have customers that even though their purchase size is large they aren’t profitable. In this particular case you might be interested to differentiate between profitability and purchase size in order to build a strategy that will turn the large buying but unprofitable customers into profitable ones. Also bear in mind that there are not strict rules in marketing and even though a non-profitable, low-size purchase segment might suggest a strategy to ignore these type of customers it could be some exceptions to that rule.
All these segments will not only drive the strategy but also the way you should invest your marketing money with each one of your customers. Further profiling might be needed which is discussed in the ‘3 simple steps in a Direct Marketing campaign’ section to make sure you achieve the most relevant engagement possible.
A thorough analysis of your existing customers will help with your new customer acquisition strategy; as you learn who are your best customers and how to communicate with them successfully.
Contact German Sacristan on 01753 215307 or email<EMAIL_ADDRESS>for more information.
Download the White Paper, "Successful Steps and Simple Ideas to Maximise your Direct Marketing Return On Investment"


Progress mid-October through mid-December
80% Time: nonparametric-bayes
The bulk of my time has been spent becoming familiar with the literature on Gaussian Processes and their numerical implementation. I have written my own Gaussian process code from scratch to convince myself of my understanding of the methodology, and explored some of the related numerical issues addressing computational speed and stability.
I then developed an algorithm for applying the Gaussian process inference of the state dynamics to stochastic dynamic programming methods for determining an optimal harvesting policy. I have compared the performance of the Gaussian-process inferred model to the optimal solution (given the exact underlying model) and to solutions based on estimated parametric models (both matching and not matching the underlying structure). This analysis shows the benefit of the nonparametric approach in better accounting for structural uncertainty in the underlying dynamics.
Steve and I have just started to look into the potential for state shifts and warning signals there-of in the ENSO / Pacific decadal oscillation. I obtained 2 appropriate datasets and have run a very preliminary analysis.
20% Time: Independent projects
- pdg-control Working group paper. Updated analysis for Figures 3 and 4. Updated draft. Conference call for feedback from working group participants. (Current draft)
- Wrote comment piece on Early Warning Signals for Nature.
- Working on EWS review paper for Theoretical Ecology with Noam Ross. (Current draft)
- Working on analysis optimal policies under multiple uncertainties (with Jim Sanchirico, Mike Springborn). #multiple-uncertainty tag in notebook; currently analyses are part of pdg-control repository.
- Finished and submitted NSF post-doc application
Other academic activities
- Wrote requested reviews for Conservation Letters, Ecology Letters, Proceedings of the Royal Society B. Declined to review for Systematic Biology.
- Presented my exit seminar in the UC Davis Center for Population Biology Colloquia series.
- Interviewed for the Nature column Turning Point.
- Invited and attended the PLoS alt-metrics workshop and hackathon
- Ran two sessions on version management, dynamic/reproducible papers, and building academic websites for the Mangel group.
- Presented scaling from individual to population level models through the van Kampen expansion in Steve’s Applied Math Club
- Participated regularly in applied math club meetings.
- Established communication with FishBase team, arranged a coalition of developers interested in API access.
- ongoing development in rOpenSci project
Goals for January - March
80% Time
Writeup of the Nonparametric Bayesian approach to management paper.
Initial goal for manuscript is proof of concept piece with the aim of demonstrating the value of a nonparametric approach to ecological decision-making. Alternatively a more technical piece could focus on the details of using Gaussian processes models for stochastic dynamic programming.
- Outline of manuscript: Dec 31st
- Decide on manuscript figures to include
- Complete draft
- Appendices
- Solocit friendly revisions
- Submit (by March 31?)
Next steps and Additional projects
The multi-species context is probably the next goal. Depending on timing, Steve may take the lead on that in these three months; I aim to be working in this in March. The step after will be the active/reinforcement learning/approximate SDP approaches. I aim to start into the background reading for that material but real progress on that front will happen after March.
Steve and I will likely continue to do something with the ENSO / PDO analysis as well. (Currently waiting on Steve’s pending queries to domain experts for further discussion)
I will also need to determine my summer conference schedule during this interval, and submit abstracts, etc. I have committed to the symposium to which I was invited at SIAM in San Deigo, July 8 - 12, and plan on attending ESA.
20% Time goals
- Finish and submit EWS review paper: end of January
- Finish and submit pdg-control policy costs paper (see current issues)
- Finish the methods section for the Labrids paper
- Finish my pending review for Environmental Modeling and Assessment.
- Skype with pdg-control Working group, basic follow-up tasks.
- Some next steps on multiple uncertainty.
Additional academic goals
- Present in mega-group meeting: Feburary 20th
- Join the phylotastic hackathon remotely(?)


| Example Sequence | 1 | 100 | 011 | 101 | 01 |
|---|---|---|---|---|---|
| Plant (0) | Determines if a plant or animal | "Chemical" in plant | Color of plant | Direction of reproduction | Reproduction rate (affects life span) |
| Animal (1) | Animal's "allergies" | Color animal is blind to | Direction of movement | Reproduction rate |
| What words mean in this context | |
|---|---|
| Plant | A model of a unicelluar life form that reproduces quickly but doesn't move. |
| Animal | A model of a unicelluar life form that reproduces slowly, moves, and eats plants. |
| Life | Short for "unicelluar life form." Or it could still mean "life." |
| DNA | A string of 0's and 1's that determine how a cell behaves, interacts with other cells, or reproduces. |
| Directions | ||
|---|---|---|
| 101 | 110 | 111 |
| 011 | --- | 100 |
| 000 | 001 | 010 |
| Reproduction rates | |||
|---|---|---|---|
| Rate | Chance | For plant | For animals |
| 00 | 100% | Plants attempt to reproduce every frame in their direction, and has half the chance to do it the other direction. | Animals attempt to reproduce once they consume a plant in their direction. |
| 01 | 50% | ||
| 10 | 33.3% | ||
| 11 | 25% |


|
degree is the degree of the spline. It must be less than the dimension of the points. |
|
knots is the knot vector for the spline. It's length must be equal to the length of the control points + degree + 1. If no knot is passed, a knot vector similar to that of [0, 1, ..., n] will be produced. To generate a knot vector that produces a clamped spline, use Generate Clamped Knot Vector.vi |
|
weights is the weights for the spline. It must be the same length as the control points. |
|
error in error in can accept error information wired from VIs previously called. Use this information to decide if any functionality should be bypassed in the event of errors from other VIs. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
status status is TRUE (X) if an error occurred or FALSE (checkmark) to indicate a warning or that no error occurred. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
code code is the error or warning code. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
source source describes the origin of the error or warning. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
percision defines the change in position for each point in the spline. The position will be of the range [0, 1] |
|
points is the control points for spline. |
|
error out error in can accept error information wired from VIs previously called. Use this information to decide if any functionality should be bypassed in the event of errors from other VIs. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
status status is TRUE (X) if an error occurred or FALSE (checkmark) to indicate a warning or that no error occurred. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
code code is the error or warning code. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
source source describes the origin of the error or warning. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
| spline |
|
degree is the degree of the spline. |
|
num pts is the number of control points. If no value is provided then degree + 1 will be used. |
|
error in error in can accept error information wired from VIs previously called. Use this information to decide if any functionality should be bypassed in the event of errors from other VIs. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
status status is TRUE (X) if an error occurred or FALSE (checkmark) to indicate a warning or that no error occurred. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
code code is the error or warning code. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
source source describes the origin of the error or warning. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
| knots |
|
error out error in can accept error information wired from VIs previously called. Use this information to decide if any functionality should be bypassed in the event of errors from other VIs. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
status status is TRUE (X) if an error occurred or FALSE (checkmark) to indicate a warning or that no error occurred. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
code code is the error or warning code. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |
|
source source describes the origin of the error or warning. Right-click the error in control on the front panel and select Explain Error or Explain Warning from the shortcut menu for more information about the error. |


You can keep the ads.
How to sign up for the Disney Plus bundle with ad-free Hulu
by Chris WedelDisney+ is finally out in the wild so we can catch-up on so many favorite Disney classics, Marvel hits, the Star Wars saga, and much more. Disney is also offering the chance to get its new streaming service bundled with Hulu and ESPN+ — which is a great deal at $13 per month. However, if you sign-up for this bundle, the Hulu you get will be the ad-supported version. So, if you prefer your Hulu minus the ads, then follow along to find out how to bundle up and hold the ads.
Products used in this guide
- Get it together: Disney+ bundle ($13/month at Disney+)
- TV Sans ads: Hulu (ad-free) ($12/month at Hulu)
How to the Disney+ bundle with ad-free Hulu
-
Go to Hulu and sign-up for the ad-free plan.
- Enter your personal info and continue.
-
Select your payment method to finish your subscription to Hulu ad-free.
Now that your Hulu account is set up let's set up the Disney+ bundle.
- After clicking Sign Up Now you can enter the same email you used for setting up your Hulu account.
- Click Agree & Continue.
- After setting up your password and entering your payment method click Agree & Subscribe.
What is going to happen now is that you'll get two separate bills, one from Hulu and one from Disney+. On the Disney+ bundle price, you will receive a $5.99 per month credit on your account, which is the value of the ad-supported Hulu in the standard bundle price. If you already have the ad-free Hulu, then you can simply sign up for Disney+ with the same email as you used when you first set up your Hulu account.
If you've already set up your Disney+ non-bundle account and would like to switch we've got you covered on how to get that done.
Our top equipment picks
Go for three
Disney+ bundle
Disney magic, live TV, and sports...what else is there?
Aside from the great content that Disney+ is going to have, you get network TV and originals from Hulu, along with all the sports you could ask for from ESPN+. This bundle is going to go a long way towards entertaining the entire family.
In the moment
Hulu
Relive your favorites
Whether you are trying watch the newest episodes of shows like This Is Us, catch up on all of Family Guy, or awesome orginals like The Handmaids Tale you can do all of that through Hulu. You even have the option to go ad-free.
We may earn a commission for purchases using our links. Learn more.


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i started gaming as a kid, halo & minecraft. the joy grew from there
my brothers introduced me to scratch when i was 11. i created many games that, albeit useless, were quite fun to make. my interest expanded and i got into engines like GameMaker Studio and Python, read books on the code and raspberry pi projects.


Namespace NMF.Synchronizations
Classes
BothGuardedSynchronizationJob<TLeft, TRight>
Denotes a class that represents a synchronization job guarded at both LHS and RHS
GuardedSynchronizationJob<TLeft, TRight>
Denotes the base class for a synchronization job that is filtered by a guard
LeftGuardedSynchronizationJob<TLeft, TRight>
Denotes a synchronization job guarded at the LHS
PropertyInequality<TLeft, TRight, TValue>
Denotes an inconsistency that a property had different values
ReflectiveSynchronization
Denotes a synchronization that assigns the synchronization rules from the nested classes through reflection
RightGuardedSynchronizationJob<TLeft, TRight>
Denotes a synchronization job that is guarded at the RHS
Synchronization
Denotes an abstract synchronization
SynchronizationComputation<TIn, TOut>
Denotes a computation in a synchronization
SynchronizationContext
Denotes a context in which a synchroniation takes place
SynchronizationContextExtensions
Denotes extension methods for the transformation context to easily access the trace links in expressions
SynchronizationDirectionExtensions
Denotes extension methods for synchronization directions
SynchronizationExtensions
Denotes common useful extensions in the context of synchronizations
SynchronizationRule<TLeft, TRight>
Denotes an abstract synchronization rule
SynchronizationRuleBase
Denotes an abstract synchronization rule
Interfaces
ISynchronizationContext
Denotes a context of a model synchronization run
ISynchronizationJob<TLeft, TRight>
Denotes a job that should be performed as part of a model synchronization
Enums
SynchronizationDirection
Denotes the direction of a synchronization


|
LINKING AN ENTITY TO A BRUSH
|
This is a walk-through as to how to link an entity to a brush.
Before starting this tutorial you should first get acquainted with the basics of the "Tread3D" editor; the screen and the various commands that are available.
As in the previous tutorials start "Tread3D" and make a very basic hollowed brush (A room); or just open your saved file called "tutorial".
Your screen should look like the one below.
Lets add an elevator to our room which will involve building a brush and then linking it to an entity.
Now build a simple brush that is 64x64x16 units using a different texture than the room.
Building a simple brush is shown in the "MAKING A BRUSH" mechanics.
Changing textures is shown in the "CHANGING/MANIPULATING TEXTURES" mechanics.
Your screen should look now like the one below.
Highlight the brush you have just drawn.
(Point and click on it)
Now click on the "Link To Entity" button.
A new window now appears which is the Entity Properties window.
The "Entity Properties" window is shown below.
This window is divided into two displays.
The first is the directory of all linkable entities.
The second is the properties of an entity that is checked off.
The "Directory" display should look like the one below.
The "Properties" display should look like the one below.
In this example "func_door" has been chosen.
Now click "OK" and this will associate the brush with the "func_door" entity.
Your screen should look now like the one below.
Also, you could have used the "Tools Menu" to "Link Entity to Brush".
The "Tools Menu" looks like this.
Besides filling in the "Entity Properties" there is not much more to linking an entity.
Now if you wanted to modify/adjust the entities properties.
Just click on the "Entities Properties" Button.
The "Entity Properties" button is shown below.
A same "Entity properties" window now appears.
The "Entity Properties" window is shown below.
What you have done is linked an entity to a brush and adjusted its properties.
Now lets "Unlink" the entity from the brush.
Highlight the brush you have just drawn.
(Point and click on it)
Now click on the "Unlink" button.
You will now be presented with a warning screen.
The "Warning Screen" looks like this.
Just click on the "Yes" button.
Your screen should look now like the one below.
Also, you could have used the "Tools Menu" to "Unlink Entity from Brush".
The "Tools Menu" looks like this.
Thats all there is to it.
Now resave your work.


Waikato Mayoral Forum elects new chair and deputy
by Waikato Regional Council25 November 2019
Allan Sanson has been elected chair of the Waikato Mayoral Forum, which includes mayors and the regional council chair.
Two were nominated for the forum’s top job during a meeting in Hamilton today (Monday, 25 November) – Waikato district’s Mr Sanson and Hauraki’s mayoral newcomer Toby Adams.
Mr Sanson edged ahead in the voting at 5-3, with members acknowledging that he is the longest serving mayor in the region and has previously held the chair’s role. Mr Adams was elected unopposed as the forum’s deputy chair.
Mr Sanson replaces Alan Livingston, who had been chair of both the forum and Waikato Regional Council until his retirement from local politics in the October 2019 elections.
The forum is designed as an informal gathering of Waikato’s council leaders to share ideas and look at how councils can best work together. All decisions on individual councils’ involvement in, and spending on, joint workstreams are left with those councils.
During the first meeting of the forum this triennium, Mr Sanson said it was an exciting time for the Waikato and collaboration would play an important role in achieving the best for regional communities.
But it was important to examine the forum’s future role and identify priority areas for focus for the following three years, he said.
“We have an opportunity to look closely at what the mayoral forum might want to achieve in the next three years. There’s no doubt we have progressed a range of collaborative opportunities since the forum was first established in 2012 – but we need rejuvenation and a new focus going forward,” Mr Sanson said.
“It’s a situation from here of looking to identify opportunities and see where the forum can best and more strategically focus its efforts,” said Mr Sanson.
The forum is next due to meet in February 2020.
ends


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We’re a creative agency who pursue brilliance and use culture to create progress in the world.
Kickstarter irony meh mustache. Heirloom post-ironic retro, quinoa venmo jean shorts meggings ugh next level YOLO DIY bitters aesthetic slow-carb deep v. Literally bushwick vice
Meet All MembersKickstarter irony meh mustache. Heirloom post-ironic retro, quinoa venmo jean shorts meggings ugh next level YOLO DIY bitters aesthetic slow-carb deep v. Literally bushwick vice
Meet All MembersWe're an SF design studio that believes in having a good time while doing what we love, and we do love what we do.
For the NYC Readiness Challenge, they created a stunning site that not only reflected the vibrancy of New York City, but their storytelling abilities humanized the issue of Emergency Preparedness.
Our team are build by all professional members who always try to get the efficiency work.
With and strategiced vision and profound insighted, Jeremy Scott leads us go through challenges.
With and strategiced vision and profound insighted, Jeremy Scott leads us go through challenges.
With and strategiced vision and profound insighted, Jeremy Scott leads us go through challenges.
With and strategiced vision and profound insighted, Jeremy Scott leads us go through challenges.


--- layout: default title: DC204 ---
We are a group of people in the 204 (and 431) area code region - Manitoba, Canada - with an interest in information security topics.
Some areas of current learning and exploration to participants include:
That said, groups are seldom static and reflect the interests of participants. If you would like more focus or information regarding some aspect of DEF CON-scope material please let us know or bring it to the discussion directly.


Structural Integration is a scientifically validated body therapy. Unlike massage, Structural Integration focuses not on the muscles but on their protective layer, called fascia (also known as connective tissue).
Structural Integration aligns and balances the body by lengthening and repositioning the fascia. As fascia is lengthened it allows the muscles to move more efficiently. The practitioner will apply pressure to the body, working the entire fascial system in a systematic way. When restricted fascia is released and lengthened the body can return to its structurally optimal position The continuing pull of gravity, the stress of daily activities and physical injuries can pull the body out of alignment. The fascia gradually shortens, tightens and adjusts to accommodate the misalignment. When the body is out of alignment it creates inefficiency and imbalance resulting in stiffness, discomfort and loss of energy. When a body is aligned and balanced it moves with greater ease. It requires less energy to function. Good posture is effortless and breathing is easier. The body becomes more flexible, more coordinated and athletic performance improves.
Structural Integration is a very personal process. It is important to remember that because no two people are alike, their experience and the benefits will never be exactly the same. As a result of the process people often appear taller and slimmer. Some actually gain anywhere from 1/4” to over 1 inch in height. Feelings of discomfort or pain are often alleviated. Other often experienced benefits are greater flexibility, a feeling of lightness and fluidity, better balance, increased breathing capacity, increased energy and greater self-confidence. While Structural Integration is primarily concerned with physical changes in the body, it affects the whole person. We are made up of emotions, attitudes, belief systems and behavior patterns as well as the physical being. All are related. Align the physical structure and it will open up the individual’s potential. Clients often report positive changes, stating less stress, greater self-confidence and improved ability to handle life’s changes. Such changes have been reported in all age groups.


The Suicide Bereavement Liaison Service has been developed in the Midlands area for families who are bereaved through suicide. The Suicide Bereavement Liaison Service is available in the following counties (Laois, Offaly, Longford and Westmeath). The service is funded by the HSE National Office of Suicide Prevention and the service provider is Midlands Living Links. The service is supported and guided by key agencies and stakeholders including the HSE, an Garda Síochána and representatives from religious and other relevant community organisations.
Guidance and Direction in helping with Communicating with the Gardai or Coroner.
Give them information about the Therapeutic Services that are available to them in their area.
Assist them in answering any specific concerns they may have around the reactions and emotions individuals and families are experiencing.
Most importantly, bereaved families and individuals are involved in the ongoing guidance and development of the service.
15-06-2015
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02-02-2014
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| Package | Description |
|---|---|
| com.geodrop | |
| com.geodrop.DropPay | |
| com.geodrop.SMSOut |
| Modifier and Type | Method and Description |
|---|---|
boolean |
GeodropSession.runMethod(GeodropRequest request)
Run a
GeodropRequest |
| Modifier and Type | Class and Description |
|---|---|
class |
ContentDeliveryMessage
Response to a
ContentDeliveryMessage request |
class |
CustomerCheck
Request used to return the full status of customer,
if the port type is SUBSCRIPTION
|
class |
CustomerGoodbye
Request used to unsubscribe a customer to a specific Port
|
class |
CustomerWelcome
Request used to subscribe a customer to a specific Port
|
class |
PortChallenge
Request used to challenge customer to confirm the telephone number
in content provider initiated transaction
|
class |
PortChargeOnDemandPurchases
Request used to charge customer with the previously defined price
if port type is ONDEMAND
|
class |
PortChargeSubscriptionPurchases
Request used to charge customer with the previously defined price
if port type is SUBSCRIPTION
|
class |
PortDescriptor
Request used to return the full Port configuration's properties
|
class |
PortTrigger
Request used to charge all subscribed customers
with the previously defined price
|
| Modifier and Type | Class and Description |
|---|---|
class |
SMSCheckBalance
Request used to determine a higher estimate of the final cost of the message
|
class |
SMSEstimatecost
Request used to determine a higher estimate of the final cost of the message
|
class |
SMSJobsScheduledDelete
Request used to delete a scheduled job
|
class |
SMSJobsScheduledModify
Request used to modify a scheduled message,
adding or removing recipients,
changing its message text,
its custom sender or its scheduled time
|
class |
SMSJobsScheduledStatus
Request used to retrieve the overall status of a scheduled job
|
class |
SMSSend
Request to send SMS messages
specifying a text for the message,
a list of recipients and a personalized sender
|
class |
SMSStatusAdhoc
Request used to retrieve the status of any set of SMS messages
|
class |
SMSStatusJob
Request used to get the overall status of a job
|
class |
SMSStatusRange
Request used to retrieve
the status of all SMS messages sent in a given time interval.
|