Created on 07/08/2012. More...
Public Member Functions | |
| def | __init__ |
| Constructor. | |
| def | add_filtered_clustering |
| Adds a clustering to selected or not_selected arrays depending on if the rejection reasons array is empty or not. | |
| def | filter |
| Eliminates the clusters whose parameters are not in the range we have defined in the script evaluation parameters. | |
| def | filter_repeated |
| Checks if the clustering is already inside 'all_clusterings', returning a rejection reason in this case. | |
| def | check_is_not_repeated |
| Checks that the clustering is not repeated again in the clustering list. | |
| def | check_num_clusters_in_range |
| Used to see if a clustering has a number of clusters in the range defined by script's evaluation parameters. | |
| def | check_noise_level |
| Does the noise level check. | |
| def | check_clustering |
| Decides if one clustering is inside the defined parameters, and returns the reasons of why not otherwise. | |
Public Attributes | |
| evaluation_parameters | |
| total_number_of_elements |
Created on 07/08/2012.
This class implements functions to get a list of clusterings and return a list of filtered clusterings (hopefully smaller).
Definition at line 13 of file clusteringFilter.py.
| def pyproct::clustering::filtering::clusteringFilter::ClusteringFilter::__init__ | ( | self, | |
| evaluation_parameters, | |||
| matrix_handler | |||
| ) |
Constructor.
| evaluation_parameters,: | Structure that at least defines:
|
| distance_matrix,: | Is the current distance matrix. |
Definition at line 28 of file clusteringFilter.py.
| def pyproct::clustering::filtering::clusteringFilter::ClusteringFilter::add_filtered_clustering | ( | self, | |
| selected, | |||
| not_selected, | |||
| clusterings, | |||
| clustering_id, | |||
| reasons | |||
| ) |
Adds a clustering to selected or not_selected arrays depending on if the rejection reasons array is empty or not.
| selected,: | The 'clustering info' dictionary with accepted clusterings. |
| not_selected,: | The 'clustering info' dictionary with rejected clusterings. |
| clusterings,: | The 'clustering info' dictionary. |
| clustering_id,: | Is the id in a 'clustering info' dictionary of the clustering being checked. |
| reasons,: | Rejection reasons array. |
Definition at line 45 of file clusteringFilter.py.
| def pyproct::clustering::filtering::clusteringFilter::ClusteringFilter::check_clustering | ( | self, | |
| clustering | |||
| ) |
Decides if one clustering is inside the defined parameters, and returns the reasons of why not otherwise.
| clustering,: | The clustering to be checked. |
Definition at line 170 of file clusteringFilter.py.
| def pyproct::clustering::filtering::clusteringFilter::ClusteringFilter::check_is_not_repeated | ( | self, | |
| clustering, | |||
| all_clusterings | |||
| ) |
Checks that the clustering is not repeated again in the clustering list.
Clusterings are considered equal if their clusters are equal (even if they were generated using different algorithms and / or parameters).
| clustering,: | The clustering to be checked. |
| all_clusterings,: | The array containing all the 'clustering info' dictionaries. |
Definition at line 121 of file clusteringFilter.py.
| def pyproct::clustering::filtering::clusteringFilter::ClusteringFilter::check_noise_level | ( | self, | |
| clustering | |||
| ) |
Does the noise level check.
| clustering,: | The clustering to be checked. |
Definition at line 154 of file clusteringFilter.py.
| def pyproct::clustering::filtering::clusteringFilter::ClusteringFilter::check_num_clusters_in_range | ( | self, | |
| clustering | |||
| ) |
Used to see if a clustering has a number of clusters in the range defined by script's evaluation parameters.
| clustering,: | The clustering to be checked. |
Definition at line 135 of file clusteringFilter.py.
| def pyproct::clustering::filtering::clusteringFilter::ClusteringFilter::filter | ( | self, | |
| clusterings | |||
| ) |
Eliminates the clusters whose parameters are not in the range we have defined in the script evaluation parameters.
| clusterings,: | Is a clustering_info dictionary indexed by clustering_id |
Definition at line 61 of file clusteringFilter.py.
| def pyproct::clustering::filtering::clusteringFilter::ClusteringFilter::filter_repeated | ( | self, | |
| selected_clusterings, | |||
| not_selected_clusterings | |||
| ) |
Checks if the clustering is already inside 'all_clusterings', returning a rejection reason in this case.
| clustering_id,: | The clustering id to be tested. |
| all_clusterings,: | The array containing all the 'clustering info' dictionaries. |
Definition at line 85 of file clusteringFilter.py.
Definition at line 28 of file clusteringFilter.py.
Definition at line 28 of file clusteringFilter.py.


KTI was founded in June of 1986 at Whiteman Air Force Base, Missouri. During the first year, KTI provided testing services to general contractors as required by the U.S. Air Force and the U.S. Army Corps of Engineers.
Over the next year, KTI's business boomed. In that time, KTI expanded its clientele list from one general contractor to approximately 20 general contractors. The majority of the work was related to government contracts at Whiteman Air Force Base, which was expanding to accommodate personnel and technical support facilities for the B-2 Stealth Bomber.
Recognizing that work could no longer be done efficiently in the small field trailer, plans were made in the fall of 1988 to move into a larger warehouse located in Knob Noster, Missouri. The additional space provided greater opportunity for expansion, and KTI was able to incorporate new features for its clientele. This office currently houses KTI's base of operations serving West Central Missouri, including Columbia, Lake of the Ozarks, Sedalia and Jefferson City.
In 1990, KTI opened another office in Kansas City specializing in Special Inspection and Construction Materials Testing. At that time our Vice President, Otto J. Kruger, Jr., implemented Geotechnical Investigation capability by utilizing the best computer software available, further enhancing the services we offer to our clients. We have since experienced steady growth working for clients such as Black and Veatch, HNTB, The City of Kansas City, Missouri, KCMO School District, Hensel-Phelps, J.E. Dunn Construction, MA Mortenson, Tyson Foods, U.S. Army Corps of Engineers, University of Missouri System, Hilton, Sprint and Station Casinos.
In 1998 and 1999, KTI was recognized in Ingram's Magazine's "KC's Top 100 Fastest Growing Businesses". To reflect the expanding range of services we offer to our clients, we changed our name in 1998 from KTI Construction Services to Kruger Technologies, Inc., dba KTI. In 2000, KTI moved to its current corporate headquarters in Lenexa, Kansas.
After setting growth records in 2009, KTI set its on even higher goals in 2010, opening new locations at McConnell Air Force Base, Kansas and Ft. Leonard Wood, Missouri.
Over the past quarter century, we have devoted our time individually to each client, providing professional and quality service no matter the size of the project. We continue to receive strong market support and favorable recognition from our proven record of accomplishment. Our enthusiasm and positive attitude ensures exceptional performance. This stability and performance is exemplified in KTI's continued growth and expansion during the great recession.
KTI is a full service professional consulting and testing facility, offering a broad spectrum of design through construction phase services to the owner, contractor, and their professional consultants. KTI was founded in 1986 in Knob Noster, Missouri, and is headquartered in Lenexa, Kansas. KTI serves the better part of Kansas and Missouri from its various locations.


public interface PostOperation
PostOperation
interface defines the service API to be
implemented by service providers extending the Sling POST servlet. Service
providers may register OSGi services of this type to be used by the Sling
default POST servlet to handle specific operations.
The PostOperation
service must be registered with a
PROP_OPERATION_NAME
registration property giving the name(s) of the
operations supported by the service. The names will be used to find the
actual operation from the
request parameter.
:operation
The Sling POST servlet itself provides various operations (see the
OPERATION_
constants in the SlingPostConstants
interface.These names should not be used by SlingPostOperation
service providers.
This interface replaces the old SlingPostOperation
service interface
adding support for extensible responses by means of the PostResponse
interface as well as operation postprocessing.
Implementors of this interface are advised to extend the
AbstractPostOperation
class to benefit from various precossings
implemented by that abstract class.
| Modifier and Type | Field and Description |
|---|---|
static String |
PROP_OPERATION_NAME
The name of the service registration property indicating the name(s) of
the operation provided by the operation implementation.
|
static String |
SERVICE_NAME
The name of the Sling POST operation service.
|
| Modifier and Type | Method and Description |
|---|---|
void |
run(SlingHttpServletRequest request,
PostResponse response,
SlingPostProcessor[] processors)
Executes the operation provided by this service implementation.
|
static final String SERVICE_NAME
static final String PROP_OPERATION_NAME
java.util.Collection
of Strings. If multiple strings are
defined, the service is registered for all operation names.void run(SlingHttpServletRequest request, PostResponse response, SlingPostProcessor[] processors)
request
- The SlingHttpServletRequest
object providing
the request input for the operation.response
- The HtmlResponse
into which the operation
steps should be recorded.processors
- The SlingPostProcessor
services to be called
after applying the operation. This may be null
if
there are none.ResourceNotFoundException
- May be
thrown if the operation requires an existing request
resource. If this exception is thrown the Sling POST servlet
sends back a 404/NOT FOUND
response to the
client.SlingException
- May be thrown if an error
occurrs running the operation.Copyright © 2017 The Apache Software Foundation. All rights reserved.


nips nips2006 nips2006-155 nips2006-155-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Ran El-Yaniv, Mordechai Nisenson
Abstract: We consider single-class classiﬁcation (SCC) as a two-person game between the learner and an adversary. In this game the target distribution is completely known to the learner and the learner’s goal is to construct a classiﬁer capable of guaranteeing a given tolerance for the false-positive error while minimizing the false negative error. We identify both “hard” and “soft” optimal classiﬁcation strategies for different types of games and demonstrate that soft classiﬁcation can provide a signiﬁcant advantage. Our optimal strategies and bounds provide worst-case lower bounds for standard, ﬁnite-sample SCC and also motivate new approaches to solving SCC.
[1] S. Ben-David and M. Lindenbaum. Learning distributions by their density-levels - a paradigm for learning without a teacher. In EuroCOLT, pages 53–68, 1995.
[2] C.M. Bishop. Novelty detection and neural network validation. IEE Proceedings - Vision, Image, and Signal Processing, 141(4):217–222, 1994.
[3] M.M. Breunig, H.P. Kriegel, R.T. Ng, and J. Sander. Lof: Identifying density-based local outliers. In SIGMOD Conference, pages 93–104, 2000.
[4] V. Hodge and J. Austin. A survey of outlier detection methodologies. Artiﬁcial Intelligence Review, 22(2):85–126, 2004.
[5] G.R.G. Lanckriet, L. El Ghaoui, and M.I. Jordan. Robust novelty detection with single-class mpm. In NIPS, pages 905–912, 2002.
[6] A. Lazarevic, L. Ert¨ z, V. Kumar, A. Ozgur, and J. Srivastava. A comparative study of anomaly detection o schemes in network intrusion detection. In SDM, 2003.
[7] M. Markou and S. Singh. Novelty detection: a review – part 1: statistical approaches. Signal Processing, 83(12):2481–2497, 2003.
[8] M. Markou and S. Singh. Novelty detection: a review – part 2: neural network based approaches. Signal Processing, 83(12):2499–2521, 2003.
[9] I. Steinwart, D. Hush, and C. Scovel. A classiﬁcation framework for anomaly detection. Journal of Machine Learning Research, 6, 2005.
[10] David M. J. Tax and Robert P. W. Duin. Uniform object generation for optimizing one-class classiﬁers. Journal of Machine Learning Research, 2:155–173, 2002.
[11] H. Yu. Single-class classiﬁcation with mapping convergence. Machine Learning, 61(1-3):49–69, 2005.


34
The Death of Moses
1 Then Moses went up from the plains of Moab to Mount Nebo, to the top of Pisgah, which is opposite Jericho. And the LORD showed him all the land, Gilead as far as Dan,
2 all Naphtali, the land of Ephraim and Manasseh, all the land of Judah as far as the western sea,
3 the Negeb, and the Plain, that is, the Valley of Jericho the city of palm trees, as far as Zoar.
4 And the LORD said to him, “This is the land of which I swore to Abraham, to Isaac, and to Jacob, ‘I will give it to your offspring.’  His eye was undimmed, and his vigor unabated.
8 And the people of Israel wept for Moses in the plains of Moab thirty days. Then the days of weeping and mourning for Moses were ended.
9 And Joshua the son of Nun was full of the spirit of wisdom, for Moses had laid his hands on him. So the people of Israel obeyed him and did as the LORD had commanded Moses.
10 And there has not arisen a prophet since in Israel like Moses, whom the LORD knew face to face,
11 none like him for all the signs and the wonders that the LORD sent him to do in the land of Egypt, to Pharaoh and to all his servants and to all his land,
12 and for all the mighty power and all the great deeds of terror that Moses did in the sight of all Israel.


Plugin Information |
|---|
View Load Testing CI/CD Plugin by LoadFocus on the plugin site for more information. |
LoadFocus.com Load Testing Plugin
Easy cloud load testing for your websites and APIs with thousands of concurrent users from multiple locations via LoadFocus.com's APIs.
Starting in versions 1.609.1.
Installation Steps:
1.  Copy your LoadFocus.com API key from https://loadfocus.com/account
3. Go to Jenkins Dashboard and click go to Manage Jenkins > Manage Plugins > Available
4. Locate and install LoadFocus Load Test plugin
5. Go to Manage Jenkins > Manage Credentials and add your LoadFocus.com API key to the stored credentials
6. Verify your API key, if API key is valid, click Save
How to use LoadFocus Load Testing Plugin for Post-build load tests:
* Note: Completed load test using your LoadFocus.com account will be available in the plugin
1. Click on the Configure option for your Jenkins job.
2. In the Post build portion, look for the Load Testing by LoadFocus.com option and select the checkbox. See the screen shot below:
3. Choose load test, enter both the Error % and Response Time thresholds. Then click Save.
Viewing your LoadFocus.com load test results
View the Console output and monitor the progress of your running load tests during job's Post build actions.
View the complete load test report of the LoadFocus.com when the job has finished.
Version History
Version 1.0 (February 17th, 2016)
- Initial release from LoadFocus Load Testing plugin
Attachments:
LoadFocus-add-load-testing-test.png (image/png)
LoadFocus-add-credential.png (image/png)
LoadFocus-running-job-console-output.png (image/png)
LoadFocus-result-details.png (image/png)
LoadFocus-result-chart.png (image/png)
LoadFocus-list-results.png (image/png)
LoadFocus-configure-post-build-step.png (image/png)


Sometimes we want to group some tabular data by some of the columns we have at hand. Well this components becomes very useful in that situations.The View
package plugintesterimport static java.awt.BorderLayout.*application(title: 'PluginTester',
preferredSize: [320, 240],
pack: true,
//location: [50,50],
locationByPlatform:true,
iconImage: imageIcon('/griffon-icon-48x48.png').image,
iconImages: [imageIcon('/griffon-icon-48x48.png').image,
imageIcon('/griffon-icon-32x32.png').image,
imageIcon('/griffon-icon-16x16.png').image]) {
borderLayout()
scrollPane(constraints:CENTER){
dynamicTreeTable(id:'dynTable'){
dynamicColumn(propertyName:'name',title:'Name',grouping:true)
dynamicColumn(propertyName:'age',title:'Age')
}
}
button(text:'Click',actionPerformed:controller.paginationAction,constraints:SOUTH)
}
The Model
package plugintesterclass PluginTesterModel {
def name
def age
def hair
}
The controller
package plugintesterclass PluginTesterController { def list = []
def model
def view void mvcGroupInit(Map args) {
50.times{
switch(it){ case 0..10:
list << ([name:"John",age:it] as PluginTesterModel)
break
case 10..20:
list << ([name:"Peter",age:it] as PluginTesterModel)
break
case 20..30:
list << ([name:"Jarret",age:it] as PluginTesterModel)
break
default:
list << ([name:"Pallowski",age:45] as PluginTesterModel)
break
}
}
} // void mvcGroupDestroy() {
// // this method is called when the group is destroyed
// } /*
Remember that actions will be called outside of the UI thread
by default. You can change this setting of course.
Please read chapter 9 of the Griffon Guide to know more.
*/
def paginationAction = { evt ->
edt{
view.dynTable.treeTableModel.with{
rawObjects.addAll(list)
}
}
}}
To add entries to the tree table you have to get the table's treetableModel's rawObjects collection:
- viewInstance.treeTableInstance.treeTableModel.rawObjects.collectionMethodAndParameters
Once you have the rawObjects collection, then use the common methods of a collection (add/addAll/remove/removeAll...) to
add/remove the table entries.


Go to the source code of this file.
Macros | |
| #define | XMP_DebugBuild 0 |
| #define | DISABLE_SERIALIZED_IMPORT_EXPORT 0 |
| #define | XMP_64 0 |
| #define | XMP_PUBLIC XMP_HELPER_DLL_IMPORT |
| #define | XMP_PRIVATE XMP_HELPER_DLL_PRIVATE |
| #define DISABLE_SERIALIZED_IMPORT_EXPORT 0 |
Definition at line 122 of file XMP_Environment.h.
| #define XMP_64 0 |
Definition at line 129 of file XMP_Environment.h.
| #define XMP_DebugBuild 0 |
Definition at line 114 of file XMP_Environment.h.
| #define XMP_PRIVATE XMP_HELPER_DLL_PRIVATE |
Definition at line 189 of file XMP_Environment.h.
Referenced by AdobeXMPCommon::IUTF8String_v1::compare(), AdobeXMPCore::INode_v1::ConvertToMetadata(), AdobeXMPCore::IStructureNode_v1::GetArrayNode(), AdobeXMPCore::IArrayNode_v1::GetArrayNodeAtIndex(), AdobeXMPCore::ICompositeNode_v1::GetArrayNodeAtPath(), AdobeXMPCommon::IError_v1::GetNextError(), AdobeXMPCore::IPath_v1::IsEmpty(), and AdobeXMPCore::INodeIterator_v1::Next().
| #define XMP_PUBLIC XMP_HELPER_DLL_IMPORT |
Definition at line 188 of file XMP_Environment.h.


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Smiles at Bubbles & Bags at Orchard Park Country Club
Hospice Buffalo's Essential Care for Children benefited from Bubbles & Bags, a shopping-and-drinking fundraiser held Thursday, Nov. 14, 2019 in Orchard Park Country Club. See who perused local businesses and take advantage of tasty fare.
15 Nov 2019, 05:00
Sarah K. McIlhatten/Special to the News
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Related content


New Jersey eyes $20M for Sandy recovery in Atlantic City
by Cal DymowskiATLANTIC CITY, N.J. (AP) – New Jersey is considering spending $20 million on Superstorm Sandy recovery projects in Atlantic City.
The state Department of Community Affairs is proposing spending money from its Community Development Block Grant Disaster Recovery program to repair and replace infrastructure and public facilities in Atlantic City that sustained damage in the 2012 storm.
Projects that could be funded include repair, replacement, or construction of bulkheads, flood-proofing City Hall and other public buildings, and inspecting and replacing check valves in drainage areas.
The work would be jointly overseen by the state and city and should be completed by the end of 2022.
A public hearing on redirecting the funds, which originally came from the federal Department of Housing and Urban Development, is scheduled for Tuesday.


Cricket RULES RULES
CRICKET
Contact: Abhishek Yadav
+917030554037
Entry Fee: Boys Rs.2500
RULES
1. It will be a tennis ball tournament In which ball will be provided by the organizers.
2. Lower and shoes are compulsory for all.
3. There will be a free hit on all No-Balls.
4. No one is allowed to wear metal spike shoes.
5. All teams are requested to a give a complete list of their 16 men squad when they report for their first match. The squad
cannot be changed fir the rest of the tournament. In case of any such event, the team will be disqualified from the
tournament.
6. Matches will be of 12-15 overs.
7. Net run rate based on runs and overs.
8. Cricket tournament will start from 5 Feb 2018.
CRICKET
Contact: Vrinda Shah
+917767910279
Entry Fee: Girls Rs.500
RULES
1. It will be a tennis ball tournament In which ball will be provided by the organizers.
2. Lower and shoes are compulsory for all.
3. There will be a free hit on all No-Balls.
4. No one is allowed to wear metal spike shoes.
5. All teams are requested to a give a complete list of their 11 women squad when they report for
their first match. The squad cannot be changed fir the rest of the tournament. In case of any such
event, the team will be disqualified from the tournament.
6. Matches will be of 8-10 overs.
7. Net run rate based on runs and overs.


|
Connected Home over IP
672cf7684
|
Public Member Functions | |
| int | getValue () |
Public Attributes | |
| OFF =(0) | |
| ON =(1) | |
| TOGGLE =(2) | |
| LEVEL =(3) | |
|
inline |
| chip.devicecontroller.ChipCommandType.LEVEL =(3) |
| chip.devicecontroller.ChipCommandType.OFF =(0) |
| chip.devicecontroller.ChipCommandType.ON =(1) |
| chip.devicecontroller.ChipCommandType.TOGGLE =(2) |


Use this page to specify the default code folding settings. For shortcuts on how to expand or collapse code elements, refer to the code folding section.


@(error: Option[Throwable], message: Option[String])
We are dispatching a team of highly trained mathematicians to analyze the issue.
@if(error.isDefined<EMAIL_ADDRESS>} @if(message.isDefined<EMAIL_ADDRESS>}This exception has been logged with id @error.get.asInstanceOf[play.api.UsefulException].id.
}


Any service-install-section must have at least the ServiceType, StartType, ErrorControl, and ServiceBinary entries as shown below, but the remaining entries are optional.
See also the Glossary entry for DDInstall.Services.
Definition :
String token used :
and localized version :
ServiceType=type-code
StartType=start-code
ErrorControl=error-control-level
The dirid number is one of the system-defined directory identifiers already described in the reference for the DestinationDirs section. The given filename specifies a file already transferred (see the Glossary entry for CopyFiles directive) from the source distribution media to that directory on the target machine.
In this case, the binary for the service was copied in %windir%\system32\drivers, AC97SMPL.SYS.


The TSstudio package provides a set of functions for time series analysis. That includes interactive data visualization tools based on the plotly package engine, supporting multiple time series objects such as ts
, xts
, and zoo
. In addition, the package provides a set of utility functions for preprocessing time series data, and as well backtesting applications for forecasting models from the forecast, forecastHybrid and bsts packages.
# Forecasting applications
# Setting training and testing partitions
USgas_s <- ts_split(ts.obj = USgas, sample.out = 12)
train <- USgas_s$train
test <- USgas_s$test
# Forecasting with auto.arima
library(forecast)
md <- auto.arima(train)
fc <- forecast(md, h = 12)
# Plotting actual vs. fitted and forecasted
test_forecast(actual = USgas, forecast.obj = fc, test = test)


--- layout: page title: Projects ---
Here are some of the projects I have been involved with.
Hacker News is a great source of information but one of its problems is its static nature. In this project I have written a bookmarklet that lets you see newly posted comments on Hacker News without having to refresh the page. It uses HNStream (made by Justin of Fanout.io) to obtain the live data, and it fiddles with the page DOM to display new comments in a way that very closely matches HN's look.
It is a JavaScript bookmarklet that does some HTML scraping to turn the view into a KnockoutJS view model. It also uses the Pollymer Ajax library to perform long polling and request retries.
I wrote this plugin for DocPad as I began to work on this blog. It is a plugin that transforms Vash to any file type.
Vash is an implementation of the Razor syntax view engine for JavaScript. This plugin allows you to use the Razor syntax to write your DocPad layouts.
I implemented much of the frontend components of WebhookInbox, a web service and website that receives HTTP requests from external sources and stores the data of those requests for later retrieval and examination.
WebhookInbox makes it possible to create a temporary HTTP endpoint, which can be passed to other applications for use during development. If you're developing a service that makes HTTP callbacks, WebhookInbox can be used as a convenient way to examine what you're sending. Incoming request data is displayed on the WebhookInbox website in realtime as it happens, thanks to the Pollymer Library. The data is orchestrated on in the browser using the AngularJS Framework.
There is an instance of WebhookInbox running at http://webhookinbox.com/ for anyone to use.
I authored the nodegrip library, which is an interface library for Node.js for supporting the Generic Realtime Intermediary Protocol (GRIP). GRIP is a technique for communicating with an HTTP proxy server to hold open an incoming connection.
This library is designed to be used with HTTP reverse proxy servers that support the GRIP interface, such as Pushpin, from Fanout.io.
I authored the nodefpp library, which is a library for Node.js for supporting the Fanout Pubsub Protocol (FPP). The Fanout pubsub protocol is used to send simple realtime messages over a communications channel. This library has been designed for use either with Fanout's pubsub service or any compatible service.
This library implements the FPP data format as a custom data format for nodepubcontrol, which is an EPCP library for Node.js and is another of my projects (listed below).
I authored the pubcontrol library, which is a library for Node.js for supporting message publishing using the HTTP Extensible Pubsub Control Protocol (EPCP), which defines a generalized and extensible data publishing protocol using HTTP.
This library contains a Format base class and a PubControl class that is used to send messages. This library also supports the case when the EPCP endpoint requires certain types of authentication.
I co-authored Pollymer, a general-purpose JavaScript library that provides conveniences for performing Ajax operations involving long-polling applications, such as request retries, exponential backoff between requests, randomized request delaying, and workarounds for browser "busy" indications. It also implements multiple transports to ensure cross-domain access works in all major browsers.
I authored WebSockHop, a small convenience library for WebSocket clients that provides automatic reconnect, periodic pinging, and request/response interactions.
I was involved with express-liveresource, a middleware library for the express framework that enables you to serve "Live Resources".
You can read about Live Resources here: https://github.com/fanout/liveresource


DBC Projects and Projects in Progress...
Welcome
GPS1.1 Pairing
Phase 0 Week 2 Unit 5 Responsive Design Challenge


--- layout: post title: "My Week in Review" date: 2019-11-17 15:00:00 +0000 image: https://s3.amazonaws.com/audreywatters/2019-01-27-needle.jpg imagecredits: https://www.flickr.com/photos/timdurkan/10460205174 ---
No updates.
No updates, although I’m starting to think about what I’ll do with my writing there. I will probably relaunch the site in the new year with more frequently commentary. But we shall see.
HEWN, No. 330 via substack.com
I don’t know if this counts as “work” or not, but I did sign a bunch of paperwork to sell property that my brother and I inherited in Texas. It’s a long story, and a good one. I’ll write it out later. And I’m trying to sell some property in Wyoming too. That story is much less exciting. I also had two calls with folks regarding speaking engagements: one in preparation for my appearance at OEB and one about a possible talk at National University.
I’m prepping my talks for Berlin.
We’ve been watching The Mandalorian and been listening to Dolly Parton’s America.
Kin’s daughter was here for the holiday weekend, as were our friends the Bebells – we had dinner with them on Sunday. Kin’s brother and sister-in-law are here this weekend – we had dinner with them on Friday. Same location both times. We need to get out of a dining rut, I think.
Icon credits: The Noun Project


| GEOS SDK TechDocs
|
|
| 4 Using the Visible Classes
| 5.1 What TicTac Illustrates
This section uses the sample application TicTac, a simple Tic Tac Toe board and pieces that can be moved around the board.
What TicTac Illustrates
What TicTac Does
The Structure of TicTac
TicTacBoard Specifics
TicTacPiece Specifics
| GEOS SDK TechDocs
|
|
| 4 Using the Visible Classes
| 5.1 What TicTac Illustrates


--- layout: post title: no title date: '2014-10-25T07:30:37+02:00' categories: - Storyboards picture_url: https://film-Storyboards.tumblr.com/post/100903773895 ---


Before Change
def test_default_config(self):
Test with 0 lights.
config = {"devices": {}}
devices = []
def add_dev_callback(devs):
Add a callback to add devices.
for dev in devs:
devices.append(dev)
rfxtrx.setup_platform(self.hass, config, add_dev_callback)
self.assertEqual(0, len(devices))
def test_one_sensor(self):
Test with 1 light.
After Change
def test_default_config(self):
Test with 0 switches.
self.assertTrue(_setup_component(self.hass, "light", {
"light": {"platform": "rfxtrx",
"devices": {}}}))
self.assertEqual(0, len(rfxtrx_core.RFX_DEVICES))
def test_one_light(self):
Test with 1 light.


Dumpster Dilemma
by Tasha
Originally, I only planned to include a quick note about our dumpster delivery in my reLuxe Round-up for February 2, 2015 under the title “Dumpster Delight”. You know something like…“I’m so excited, we just had a giant dumpster delivered so I can finally clean up awful eye-sore piles of plastic, metal, and junk strewn in piles around our property.” But as I sat down to write about it, I realized having a 22’ x 8’ foot dumpster delivered to our “sustainable” farmstead demanded more page time.
As a former suburbanite, I come from a culture of keeping a few tidy cans tucked into a little nook in my garage for routine deposits from inside the house and around the yard. Then once or twice a week, we roll those cans curbside and let the trash carriers whisk our mess to the magical “Away-land”. On Wednesdays, they even let us wheel out tires, carpet, and appliances for special pick-up and processing in “Away-land”. When you have twice weekly pick-up, it’s easy not to worry or even think about your trash output - which for the average American that’s nearly 4.5 pounds per day, or 130 pounds per month (according to the EPA). Now, I’ve been a “greenie” for a while so reducing my contributions to “Away-land” has been a long-standing goal. I bought in bulk or at farmer’s markets to avoid packaging, recycled or reused trash in unconventional ways, and even picked through other people’s curbside deposits to rescue what I could (Thanks Mom for being my sidekick on trash day all those years!). Even though I did my “best” not to contribute to a disposable culture, my efforts amounted to feel-good green-washing.
The hard truth for us to face is that every piece of trash we create is – excuse the pun – a waste. If you believe products like water bottles, cans, food wrappers, boxes, grocery store bags, etc. are convenient and harmless, and that recycling makes you “environmentally friendly” - you are wrong. Creating and disposing of trash costs all of us in innumerable ways that we don’t normally remember to calculate. I don’t just mean the obvious environmental costs that greenies tend to bandy about (you know…climate catastrophe, resource devastation, toxicity to fish, wildlife, and ourselves, etc.). I am talking about the massive civic infrastructure and economic activity devoted to producing packaging and managing the waste by-products of goods designed to have a short shelf life (latest smart phone, fashion trend, or broken appliance).
I am also talking about the added costs of packaging, shipping, keeping up with the Jones’s, etc. that make it necessary for us to work more to be able to afford those perfume bottle sets from fine department stores, the pretty striped bag and tissue paper with your $100 Vietnam-manufactured bra and panty set, or the latest/greatest “whatever” technology contraption designed to make your life easier. I am not the statistician type, but even with my ordinary brain, I know that an incredible - mind-boggling - amount of human time, energy, resources, etc. goes into producing, customizing, and distributing packaging and non-durable goods (as well as marketing them us) so that we can eventually deposit said items in “Away-land.” Or clean them up from roads, waterways, parks… where they often inadvertently end up. I also know that if we directed all those resources to making a sustainable world, we’d be living in one in no time.
I am not going to run through the line-up of things we can do to reduce our impact. Because the other hard truth to face is that we are way beyond quick fixes. There is no easy answer. It’s all uphill from here because we waited too long. But I do have one overall recommendation for everyone who wants to work towards really being “environmentally friendly”.
Stop believing in the magical, mythical “Away-land”. This suggestion doesn’t just apply to the away-land where garbage goes, but to all those “away-land” areas around the planet where things are manufactured – cheaply - for our benefit. Whenever you make a purchase, imagine that the waste-side of your transaction is going to end up in the kitchen or yard of someone you love and that they will know that you put it there. I know it won’t (at least not directly), but we all make different calculations when we realize our choices impact those we care about. Or imagine that your mother/sister/best-friend had to spend twelve hours hunched over a machine - in a falling-down, windowless factory- to produce that trendy shirt, state of the art TV, or newly manufactured whatever you are about to buy. Then ask yourself if you really “need” or even want whatever seems so important at the moment.
An aside for those of you who like to believe “away-lands” are good for the world because it gives people jobs – For you, I recommend a stronger course of action. Skip the imagination exercise and go work one of those Away-land jobs for a few years. Then let’s talk.
Ok, now that my soap-box spew is over, it’s time for me to confess to my personal dumpster dilemma… In rural areas, like ours, there is no trash pick-up. Really. So when you want to dispose of something, you have to go visit “Away-land”. We are lucky to have a “recycle center” about five miles from us.  The attendant watches and assists to make sure that you sort properly and that you don’t try to dispose of anything not “household” related. Big stuff, like a roll of carpet, you get to haul about twenty miles away to the landfill and pay per pound to dump it. Toxic materials – paint, empty oil containers, garden/lawn chemicals, etc. you keep at home until October and then you drop them off at a one day toxic clean-up event held at a local park.
As a result of the difficulty and expense of disposal, two things are generally true of rural folks. First, they tend to have less trash than suburbanites. This may be a function of lower incomes or distance from town as well, but nonetheless they manage to get by producing less waste per person. Second, they often create personal landfill piles around their property instead of paying to dump large items at the community landfill. The former owners of our property did this and so as part of our home purchase price, we inherited several piles of rotting carpet, furniture, broken farm/yard equipment, plastic containers, tires, a TV, rusted sheet metal, and more. These piles were situated in areas that were probably out of sight for the previous owners. However, since we use the whole property to run the goats, chickens, and ducks, there is no such thing as out of sight for us.
I wish I could claim that I was worried the piles were toxic or dangerous for the animals (probably not), but the honest to goodness truth is that I had a dumpster delivered because I couldn’t stand to look at the ugly trash piles. I felt the need to apologize for their hideousness every time we gave guests a tour of the reLuxe Ranch. They made me ashamed. These weren’t my piles, but I have certainly contributed my share of this kind of ugliness to the world we inhabit and then some. They were the truth of a disposable culture that I supported and participated in made visible in my own yard. I wanted to send them “away” like I used to do in the suburbs.
And I did, with a kind of sick joy in my heart. I spent three weeks dragging down every piece of trash with a less than a three year biodegradable life span and loaded it into that dumpster. Then, I watched with glee as the dumpster was loaded and hauled back off our property.
Bye-bye awful piles!
I know that moving the trash from our house to the landfill is not an answer. The landfill for Mount Airy, NC is, in fact, backyard to many homes located near this “Away-land”. Even though the landfill is kept as tidy as possible (e.g. piles buried with dirt and new deposits covered nightly), the distinct “eau du garbage” wafts through the air for miles around, making the fact of it’s existence impossible to ignore even if you manage to turn a blind eye. So in effect, I knowingly sent my hideous piles off to be someone else’s eye-sore and problem. I allowed myself to believe in Away-land one more time for the sake of our picturesque farm landscape.
For now, we have landfills, trash pick-up in the suburbs and cities, and dumpster deliveries.  We must change these things. We must end waste and integrate our “Away-lands” into our personal landscapes. To do this, we will have to change almost everything about our modern, affluent ways of living (which doesn’t have to be a bad thing).
I know this. Matt and I are radically modifying our lives to do this. Having a dumpster delivered and cleaning up the piles was, unquestionably, a luxury–an extravagant one - not a “reLuxe” style luxury. As should be the case with a luxury, I understood that it was not without consequences, I recognized that it was meant to be a one time event, and I met the experience with respect and appreciation. I have also compounded the pleasure of that luxury by enjoying the beauty of a trash-free landscape every day since the clean-up.
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Module ROT.Display
Visual Display.
A Code Page 437 terminal emulator based on AsciiPanel.
Functions
| init ([w=80[, h=24[, scale=1[, dfg[, dbg[, fullOrFlags=false[, vsync=false[, fsaa=0]]]]]]]]) | Constructor. |
| draw () | Draw. |
| contains (x, y) | Contains point. |
| getCharacter (x, y) | Get a character. |
| getBackgroundColor (x, y) | Get a background color. |
| getForegroundColor (x, y) | Get a foreground color. |
| setDefaultBackgroundColor (c) | Set Default Background Color. |
| setDefaultForegroundColor (c) | Set Defaul Foreground Color. |
| clear ([c=' '[, x=1[, y=1[, w[, h[, fg[, bg]]]]]]]) | Clear the screen. |
| clearCanvas () | Clear canvas. |
| write (s[, x=1[, y=1[, fg[, bg]]]]) | Write. |
| writeCenter (s[, y=1[, fg[, bg]]]) | Write Center. |
| drawText (x, y, text, maxWidth) | Draw text. |
Functions
- init ([w=80[, h=24[, scale=1[, dfg[, dbg[, fullOrFlags=false[, vsync=false[, fsaa=0]]]]]]]])
-
Constructor.
The display constructor. Called when ROT.Display:new() is called.
Parameters:
- w int Width of display in number of characters (default 80)
- h int Height of display in number of characters (default 24)
- scale float Window scale modifier applied to glyph dimensions (default 1)
- dfg table Default foreground color as a table defined as {r,g,b,a} (optional)
- dbg table Default background color (optional)
- fullOrFlags boolean In Love 0.8.0: Use fullscreen In Love 0.9.0: a table defined for love.graphics.setMode (default false)
- vsync boolean Use vsync (default false)
- fsaa int Number of fsaa passes (default 0)
Returns:
-
nil
- draw ()
- Draw. The main draw function. This should be called from love.draw() to display any written characters to screen
- contains (x, y)
-
Contains point.
Returns true if point x,y can be drawn to display.
Parameters:
- x
- y
- getCharacter (x, y)
-
Get a character.
returns the character being displayed at position x, y
Parameters:
- x int The x-position of the character
- y int The y-position of the character
Returns:
-
string
The character
- getBackgroundColor (x, y)
-
Get a background color.
returns the current background color of the character written to position x, y
Parameters:
- x int The x-position of the character
- y int The y-position of the character
Returns:
-
table
The background color as a table defined as {r,g,b,a}
- getForegroundColor (x, y)
-
Get a foreground color.
returns the current foreground color of the character written to position x, y
Parameters:
- x int The x-position of the character
- y int The y-position of the character
Returns:
-
table
The foreground color as a table defined as {r,g,b,a}
- setDefaultBackgroundColor (c)
-
Set Default Background Color.
Sets the background color to be used when it is not provided
Parameters:
- c table The background color as a table defined as {r,g,b,a}
- setDefaultForegroundColor (c)
-
Set Defaul Foreground Color.
Sets the foreground color to be used when it is not provided
Parameters:
- c table The foreground color as a table defined as {r,g,b,a}
- clear ([c=' '[, x=1[, y=1[, w[, h[, fg[, bg]]]]]]])
-
Clear the screen.
By default wipes the screen to the default background color.
You can provide a character, x-position, y-position, width, height, fore-color and back-color
and write the same character to a portion of the screen
Parameters:
- c string A character to write to the screen - may fail for strings with a length > 1 (default ' ')
- x int The x-position from which to begin the wipe (default 1)
- y int The y-position from which to begin the wipe (default 1)
- w int The number of chars to wipe in the x direction (optional)
- h int Then number of chars to wipe in the y direction (optional)
- fg table The color used to write the provided character (optional)
- bg table the color used to fill in the background of the cleared space (optional)
- clearCanvas ()
- Clear canvas. runs the clear method of the Love2D canvas object being used to write to the screen
- write (s[, x=1[, y=1[, fg[, bg]]]])
-
Write.
Writes a string to the screen
Parameters:
- writeCenter (s[, y=1[, fg[, bg]]])
-
Write Center.
write a string centered on the middle of the screen
Parameters:
- drawText (x, y, text, maxWidth)
-
Draw text.
Draws a text at given position. Optionally wraps at a maximum length.
Parameters:
- x number
- y number
- text string May contain color/background format specifiers, %c{name}/%b{name}, both optional. %c{}/%b{} resets to default.
- maxWidth number wrap at what width (optional)?
Returns:
-
number
lines drawn


Guidance
Information for registered providers of children's social care services who want to request a change to their conditions of registration.
MS Word Document , 900KB
PDF , 673KB , 37 pages
This guidance covers:
It also sets out the changes a local authority fostering or adoption service needs to tell Ofsted about.
Published: 12 September 2014
Updated: 18 December 2015
From: Ofsted


| AbstractDOMParser |
This is the base class of all DOM parsers.
|
| AbstractSAXParser |
This is the base class of all SAX parsers.
|
| AbstractSAXParser.AttributesProxy |
|
| AbstractSAXParser.LocatorProxy |
|
| AbstractXMLDocumentParser |
This is the base class for all XML document parsers.
|
| BasicParserConfiguration |
A very basic parser configuration.
|
| CachingParserPool |
A parser pool that enables caching of grammars.
|
| CachingParserPool.ShadowedGrammarPool |
Shadowed grammar pool.
|
| CachingParserPool.SynchronizedGrammarPool |
Synchronized grammar pool.
|
| DOMParser |
This is the main Xerces DOM parser class.
|
| DOMParserImpl |
This is Xerces DOM Builder class.
|
| DTDConfiguration |
This is the DTD-only parser configuration.
|
| DTDParser |
|
| IntegratedParserConfiguration |
This is configuration uses a scanner that integrates both scanning of the document
and binding namespaces.
|
| NonValidatingConfiguration |
This is the non validating parser configuration.
|
| SAXParser |
This is the main Xerces SAX parser class.
|
| SecureProcessingConfiguration |
This configuration enhances Xerces support for the JAXP secure processing feature.
|
| SecurityConfiguration |
This configuration allows Xerces to behave in a security-conscious manner; that is,
it permits applications to instruct Xerces to limit certain
operations that could be exploited by malicious document authors to cause a denail-of-service
attack when the document is parsed.
|
| SoftReferenceSymbolTableConfiguration |
This parser configuration extends the default configuration allowing Xerces to
handle usage scenarios where the names in the XML documents being parsed are mostly
unique by installing a memory sensitive SymbolTable .
|
| StandardParserConfiguration |
This is the "standard" parser configuration.
|
| XIncludeAwareParserConfiguration |
This class is the configuration used to parse XML 1.0 and XML 1.1 documents
and provides support for XInclude.
|
| XIncludeParserConfiguration |
This parser configuration includes an XIncludeHandler in the pipeline
before the schema validator, or as the last component in the pipeline if there is
no schema validator.
|
| XML11Configuration |
This class is the configuration used to parse XML 1.0 and XML 1.1 documents.
|
| XML11DTDConfiguration |
This class is the DTD-only parser configuration
used to parse XML 1.0 and XML 1.1 documents.
|
| XML11NonValidatingConfiguration |
This class is the non validating parser configuration
used to parse XML 1.0 and XML 1.1 documents.
|
| XMLDocumentParser |
This is a concrete vanilla XML parser class.
|
| XMLGrammarCachingConfiguration |
This configuration provides a generic way of using
Xerces's grammar caching facilities.
|
| XMLGrammarParser |
|
| XMLGrammarPreparser |
This class provides an easy way for a user to preparse grammars
of various types.
|
| XMLParser |
Base class of all XML-related parsers.
|
| XPointerParserConfiguration |
This parser configuration includes an XPointerHandler in the pipeline
before the schema validator, or as the last component in the pipeline if there is
no schema validator.
|


Apr 20, 2018 index Fancy box is used to display image gallery with this shortcode: A very fancy box, indeed


Before Change
if j in pipeline["dump_for"]:
self.log_info("Task {}, iteration {}: dump results for {}..."
.format(i, j, name), filename=self.logfile)
for item, config, repetition in zip(
job.experiments,
task["configs"],
task["repetition"]
):
path = os.path.join(
job["name"],
"results",
config.alias(as_string=True),
str(repetition),
name + "_dump"
)
item.dump_result(name, path)
except StopIteration:
self.log_info("Task {} was stopped after {} iterations".format(i, j+1), filename=self.logfile)
break
After Change
for item in job.experiments:
item._dump_pipeline_result(name, "."+name)
for name, function in job.config["functions"].items():
if j in function["execute_for"]:
self.log_info("Task {}, iteration {}: call function {}..."
.format(i, j, name), filename=self.logfile)
for item in job.experiments:
item.call_function(j, name)
if j in function["dump_for"]:
self.log_info("Task {}, iteration {}: dump results for function {}..."
.format(i, j, name), filename=self.logfile)
for item in job.experiments:
item._dump_function_result(name, "."+name)
except StopIteration:
self.log_info("Task {} was stopped after {} iterations".format(i, j+1), filename=self.logfile)
break


5 references to Process
Microsoft.PowerShell.ConsoleHost (1)
host\msh\ConsoleHost.cs (1)
1472
SecuritySupport.SetExecutionPolicy(ExecutionPolicyScope.
Process
, executionPolicy, null);
System.Management.Automation (4)
engine\InitialSessionState.cs (1)
2219
SecuritySupport.SetExecutionPolicy(Microsoft.PowerShell.ExecutionPolicyScope.
Process
, ExecutionPolicy, shellId);
security\SecuritySupport.cs (3)
129
ExecutionPolicyScope.
Process
,
165
case ExecutionPolicyScope.
Process
:
287
case ExecutionPolicyScope.
Process
:


ElasticSearch online analyzers tester
is loading magic ..
Play online with
Apache Lucene
and
ElasticSearch
filters, tokenizers and analyzers.


809 Bergamot Drive
Associate Director of Technology,
Information Trust Institute at the University of Illinois
HOA Goals:
Continue to preserve the overall appeal of the Prairie Fields subdivision.
Address concerns of residents and work to maintain a high-quality living experience.
Enhance the community feel and engagement through interactions.
Provide a way to engage with an open dialog on what residents really want in moving this neighborhood forward.
Duties of the Member at Large
Participate in Board voting and discussions
Performs duties as assigned
Serve on Architectural Control Committee
About the Board
The Prairie Fields HOA is governed by a Board of Directors (BOD), per the HOA BYLAWS. The Board exists to represent and support all members of the homeowners association.
Each member of the Board is elected to a two year term, with an election held in the fall of each year for the vacancies of the following year.
Board Meetings
The BOD generally meets at 8:00 PM on the second Monday of each month in the library at Carrie Busey School. All email items are discussed at the regular monthly board meeting, so that the meeting minutes reflect emailed action.
Contact the PFHOA Board Directors
Email<EMAIL_ADDRESS>Mail: P.O. Box 478, Savoy, Il 61874
Phone:<PHONE_NUMBER>


Collections
-
Mix It Up - 17 items by statesidelife
-
At the Hearth - 9 items by designassembly
-
Give Thanks - 35 items by ebayhomeeditor
-
Guests of Honour - 30 items by ebaydealseditor
Daily Deals
-
Christmas Socks - $4.99
-
MacBook Air - $799.99
-
Xbox One 500GB - $169.99
-
Playstation 4 Pro - $419.99


Cherish the time
Estimate the given time of
X
s.
Start
X
Stop
Prop
Your time difference is:
X
Start anew


Segments to display filter (leave empty to display all segments):
Tracks to display:
coverage:
2˚ structure:


Using Quotek SDK in your C++ code is fairy easy, since it only consists of a library and header files. Please note that if you’re using our Quotek SaaS solution, this section doesn’t concern you because everything is already setup for you inside your server environment.
Download and unzip the quotek SDK archive file. Then right-click on the “installer_win64.bat” script file which is located at the root of the decompressed directory, then finally click on “Run as Administrator”. The SDK will be installed in C:\Program Files\quotek\sdk, and ready to go.
Just go to C:\Program Files\quotek\sdk\helpers\vstudio, then double click on the “Quotek.vsix” file. The SDK should now be installed with Visual Studio. If you start a new Project and go to “Visual C++” , you will see Quotek Project. Then Select it and start a new project: It’s all good, you are now ready to code with quotek.
Download and unzip the quotek SDK archive file, and launch the “installer_linux.sh” script located at the root of the decompressed directory. All of the Quotek SDK will then be installed in /opt/quotek/sdk. The libraries are located in /opt/quotek/sdk/lib and headers are in /opt/quotek/sdk/include.
În order to work properly on Linux, Quotek SDK needs libcurl as a dependency. This is a very common package which is probably already installed on your system. In any case, the install procedure for libcurl is as follow:
For Debian/Ubuntu
sudo apt-get install libcurl4-openssl-dev
For CentOS/Fedora
sudo yum install libcurl-devel
Given that the headers and libraries are not installed at the usual places in the system, you will need to add a few arguments to your compilation line. Also, because libquotek needs them, you will need to link the programs you code with libcurl and pthread.
So the typical compilation line of a program using quotek SDK on Linux is the following:
g++ -std=c++11 -I/opt/quotek/include -L/opt/quotek/lib -o <YOUR_PROGRAM> <YOUR_C++_FILE> -lpthread -lcurl -lquotek


Aggregating data with Rx.concatMapEager
Sometimes, we have the need of aggregating data at read time. The situation could be that we are developing in client side without proper APIs, or maybe our developing context is a backend service without all the needed information.
Let’s imagine the next scenario: We have the Follower entity:
Follower
id
name
We can obtain our followers by using our FollowersRepository, but, we want to return to our clients something like:
AggregatedFollower
id
name
numberOfFollowers
numberOfFollowings
We will need to obtain the other fields from somewhere else… In this case, we have the PublicProfile entity (with the corresponding repository) which have the followers/followings stats.
Solving this in an imperative way could be something like:
// pseudocode
aggregatedFollowers = []
followers = FollowersRepostiry.get(targetUserId)
foreach(followers as follower)
aggregatedFollowers += new AggregatedFollower(
follower,
PublicProfileRepository.get(follower.getId())
)
return aggregatedFollowers
Wait, do you want to solve this by doing N calls? why aren’t you listening to service events and replicating the needed data locally?
Yes, this could not be the best option for a high traffic application, if your followers page contains 20 elements, performing 20 http calls in each request doesn’t sound good, but:
what if your API client is an internal back-office?
or what if you are simply want to test a feature with the 1% of your users? maybe you don’t want to change your replication data logic at this point.
By using RxJava you can deal with this n+1 problem in a easy and parallelized way.
concatMap
I knew that the flatMap operator does not preserve the order of the elements… so, since order matters for my case, I searched a bit and I found the concatMap and I tried it:
public Flowable<AggregatedFollower> getFollowers(String userId) {
return followersRepository
.getFollowers(userId)
.concatMap(
follower -> publicProfileRepository
.getPublicProfile(follower.getId())
.map(publicProfile -> new AggregatedFollower(follower, publicProfile))
.toFlowable()
);
}
And, it worked! But, calls are made sequentially, so, if each publicProfile call takes 1 second you will have to wait N seconds to complete the request…
The fact that the concatMap is executed sequentially is useful if your are performing write operations. For our case, in which we are only reading, we can assume to do all the job at the same time.
flatMap and manual ordering
When I did this the first time, I was using RxJava 1 (RxJava 2 was not released), so, no other options existed and I wrote custom logic to preserve the order…
// don't waste your time understanding this!
public Flowable<AggregatedFollower> getFollowers(String userId) {
return followersRepository
.getFollowers(userId)
.toList()
.toFlowable()
.flatMap(
followersList -> {
List<String> orderedIds = followersList
.stream()
.map(Follower::getId)
.collect(Collectors.toList());
return Flowable
.fromIterable(followersList)
.flatMap(follower ->
publicProfileRepository
.getPublicProfile(follower.getId())
.map(publicProfile -> new AggregatedFollower(follower, publicProfile))
.toFlowable()
)
.toSortedList(Comparator.comparingInt(o -> orderedIds.indexOf(o.getFollower().getId())))
.toFlowable()
.flatMap(Flowable::fromIterable);
}
);
}
But, don’t do that! Use the RxJava 2 concatMapEager instead!
concatMapEager
Right now, with RxJava 2, you can just do this by using the concatMapEager
operator ;)
public Flowable<AggregatedFollower> getFollowers(String userId) {
return followersRepository
.getFollowers(userId)
.concatMapEager(
follower -> publicProfileRepository
.getPublicProfile(follower.getId())
.map(publicProfile -> new AggregatedFollower(follower, publicProfile))
.toFlowable()
);
}
And that’s it!
But… maybe you are worried about the concurrency, executing N threads concurrently could be problematic…
You can use the overloaded concatMapEager
method that allows to you to pass the maxConcurrency
.
I wrote another example for that.
And here the time taken for each strategy:
Note about parallelism
Keep in mind that RxJava is synchronous by default, so, this examples work in a parallelized way because I’m
configuring the schedulers in my rx chains by calling to the subscribeOn
method when needed:
public class PublicProfileRepository {
// ...
public Maybe<PublicProfile> getPublicProfile(String userId) {
return Maybe
.fromCallable(() -> blockingGetPublicProfile(userId))
.subscribeOn(Schedulers.io());
}
// ...
You can find all the implementations and tests in my github repository: https://github.com/odin-delrio/coding-tests/tree/master/rx-concat-eager


{% extends "confirm.html" %} {% load i18n %} {% block question %} {% blocktrans %}Do you really want to leave this proposal?{% endblocktrans %} {% endblock %}


Karaoke Inside


processAttributes(processor: Function): any
Decorator: Enables custom processing of the attributes on an element before the framework inspects them.
Parameters
processor: Function
Pass a function which can provide custom processing of the content.


Right-click and select View Source to see the code.
Basic Widget
Custom Finish: Specific & Locked Location
Custom Logo
Custom Locale (Indonesia) and Region (Jakarta)
Custom Start: lat,lng
Custom Finish: Text Query


public interface IAdvisorInfoCollector extends IReportInfoCollector
IOperationAdvisor
| Modifier and Type | Field and Description |
|---|---|
static java.lang.String |
ID_EXCEPTION_PROBLEM
String identifier of the generic "exception" problem type.
|
| Modifier and Type | Method and Description |
|---|---|
IAdvisorInfo |
createExceptionInfo(java.lang.String summary,
java.lang.Throwable exception)
Creates an exception info for the given throwable.
|
IAdvisorInfo |
createProblemInfo(java.lang.String summary,
java.lang.String description,
java.lang.String type)
Creates a problem info of the given type with the given summary and
description.
|
addInfo, addInfos
static final java.lang.String ID_EXCEPTION_PROBLEM
IAdvisorInfo createProblemInfo(java.lang.String summary, java.lang.String description, java.lang.String type)
The returned info has not yet been added to this collector. Clients are responsible for adding the info to this collector after they have made any desired modifications to it.
The returned info's severity will be set automatically based on the advisor's configuration. Clients are strongly discouraged from modifying the severity of the returned info.
Each advisor should create problems with a unique problem type. This is so that "Quick Fixes" can be provided for specific problem types.
summary
- the summary to set on the new problemdescription
- the description to set on the new problemtype
- the problem typeIAdvisorInfo createExceptionInfo(java.lang.String summary, java.lang.Throwable exception)
The returned info has not yet been added to this collector. Clients are responsible for adding the info to this collector after they have made any desired modifications to it.
The returned info's severity will be set automatically based on the end-user configuration of the advisor. Clients are strongly discouraged from modifying the severity of the returned info.
This method should not be used for reporting problems with an operation.
The method #createProblemInfo(String, String, String, int)
should
be used for this purpose instead.
summary
- the problem summaryexception
- the exception which occurredOperationParticipant#createExceptionInfo(String, Throwable)


Former Rangers midfielder Mikel Arteta subject to 'interest' from Everton amid Marco Silva struggles
The Manchester City assistant is a former player at the struggling Merseyside club.
by Jonathan McFarlaneFormer Rangers midfielder Mikel Arteta is a target for Everton as current boss Marco Silva continues to struggle.
The Toffees have spent a fortune on players in recent years but sit in 15th position having won only four of their 12 games so far.
Arteta, a treble winner at Rangers in 2003, has excelled as Pep Guardiola 's number two, helping the club to five major trophies in three years.
And now Everton are interested in making their former midfielder manager if they decide to dispense with Silva.
Speaking on the Transfer Window Podcast , big deal guru Duncan Castles revealed: "There is a lot of interest from the Everton end in Mikel Arteta as a candidate should they need to make a change.
"This makes a lot of sense because Arteta's status in the game is very high.
"He has not managed yet but he's credited as an important part of Manchester City 's treble winning campaign last season as Pep Guardiola's principle assistant. He was a strong candidate for the Arsenal job before they appointed Unai Emery and a lot of Gunners supporters would have preferred Arteta, a former player.
"He's a former Everton player as well so it's not to see wht the name is being considered given that Arsenal took him as a serious candidate in the job."
"This is one to pay attention to and see how it develops."


{% extends "header.html" %} {% block body %}
''' so now we've got a bettor, he's working, and we've seen some basic outcomes but now we want to see some longer-term outcomes, so first let's do that. ''' import random # let us go ahead and change this to return a simple win/loss def rollDice(): roll = random.randint(1,100) if roll == 100: #print roll,'roll was 100, you lose. What are the odds?! Play again!' return False elif roll <= 50: #print roll,'roll was 1-50, you lose.' return False elif 100 > roll >= 50: #print roll,'roll was 51-99, you win! *pretty lights flash* (play more!)' return True ''' Simple bettor, betting the same amount each time. ''' def simple_bettor(funds,initial_wager,wager_count): value = funds wager = initial_wager currentWager = 0 while currentWager < wager_count: if rollDice(): value += wager else: value -= wager currentWager += 1 # changed to reduce spam if value < 0: value = 'Broke!' print 'Funds:', value # lots of wagers now.... x = 0 while x < 100: simple_bettor(10000,100,50) x += 1
Interestingly enough, you can see there is quite the spread here.
Keep in mind, the odds are only 1% against you.
 Interestingly sometimes you find people actually make large profits.
This visualization, however, is sub par. let's add to this, shall we?


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{{ define "main" }}
I’m Matt Layman.
I want to help you learn more about Django and Python. Who am I?


Overview
the Freshmen 15 is a collection of talks geared
towards new hackers that will help them create a
project during the hackathon. Starting from setting
up your machine for hacking to HTML and CSS to creating
a database and hooking that into your webpage and
much more. Apply what you’ve learned in the talks
into your project and make it your own.
The purpose is to help hackers from start to finish of a
project and gain their 15 skills.
Workshops
Set-up
Skills Gained: Setting up your machine for all the talks during the weekend.
You will download various programs we will be using throughout the weekend so you're
prepared for all other talks.
Text editor
Download: Atom
W3.CSS File
Download: W3.CSS file Download
Version Control
Create an account on: Github
Download: Git
Web Server/SQL
Download: XAMMP
HTML
Skills Gained: Learning Basic HTML, and creating the base of your webpage
Resources
CSS
Skills Gained: Learning how to style your HTML page with W3.CSS style sheet
and how to create your very own.
Resources
Javascript
Skills Gained: Learning the basics of using JavaScript
to make your page interactive.
Resources
Design
Skills Gained: Learning basic design elements and compositional design.
Github
Skills Gained: Learning the basics to Github and version control.
Finishing the talk with Github hosting
Resources
SQL
Skills Gained: Learning how to create a database with MySQL
using XAMM.
Resources
PHP
Skills Gained: Learning how to display your database you created
earlier in this talk.
Resources
jQuery
Skills Gained: In this talk we will connect the front end website we built earlier
with the backend.
Resources
Debugging/QA
Skills Gained: Learning how to debug your code. Something
wrong with your code? Come ask questions during this! We'll figure it out together.
Security
Skills Gained:Learning about SQL injection and security risks
in your code.
Resources
Elevator Pitches
Skills Gained: Learning how to pitch your hack/project
at expos. Effectively talking about your project can sometimes save an unfinished hack.
Resources
Skills Gained: Learning more places to learn code or
help you with your project.
Resources


Home
Upload
About
Nrujal Sharma
Team Leader
Naresh Prajapati
AR Developer
Vibahv Nirmal
Programmer
Deept Panchal
Web Developer


Sparky the Cat:
Thanks for helping me. Meow~ That devil won't bother Belinda now! Meow~
"Your point?"


web hosting
domain names
photo sharing
HISTORY IN SONG
TABLE OF CONTENTS
THE AMERICAN REVOLUTION
SONGS OF THE SEA
1800s: IMMIGRATION FROM EUROPE & THE WESTWARD MOVEMENT
OUTLAWS & BADMEN
(and -WOMEN)
SONGS FROM PENITENTIARIES & CHAIN GANGS
THE CIVIL WAR
THE RAILROAD IN AMERICAN SONG
TRAMPS, HOBOES, MIGRANT WORKERS, HOMELESS
TRAGEDIES AND DISASTERS
WORLD WAR I
THE LABOR MOVEMENT
1920s & 1930s; THE DEPRESSION & THE NEW DEAL
WORLD WAR II
LATE 1940s & 1950s: McCARTHY "WITCH-HUNTS;" NUCLEAR ARMS RACE, THE KOREA WAR
RACE RELATIONS & THE CIVIL RIGHTS MOVEMENT
1960s: THE BOMB SCARE, THE GENERATION GAP, THE VIET-NAM WAR
ALPHABETICAL LISTING OF SONG TITLES
SONGS BY INDIVIDUAL SONGWRITERS/ARTISTS:
THE DIXON BROTHERS
(HOWARD & DORSEY DIXON)
BOB DYLAN
JIM GARLAND
TOM GLAZER
SARAH OGAN GUNNING
WOODY GUTHRIE
&
THE ALMANAC SINGERS
JOE HILL
AUNT MOLLY JACKSON
PETER LAFARGE
MILLARD LAMPELL
DAVE McCARN
BOB MILLER
PHIL OCHS
BUFFY SAINTE-MARIE
TO TOP OF PAGE
TO STARTING PAGE
You can email me at
<EMAIL_ADDRESS>web hosting
•
domain names
•
web design
online games
•
photo sharing
blog
•
advertising online


| DOSE: |
1.5 g |
oral |
Cannabis |
(cookie / food) |
Prior to this experience I'd smoked and eaten low-medium grade pot on a few occaisions, with varied results. It wasn't until discovering the Leary biscuit recipe that I truly came to appreciate the effects of this plant.
On with the story...
It was another Friday evening, and as usual I was hanging out at my friend T's house. I'd spent most of the evening listening to music and watching anime with this other dude. Basically chilling out. Then I see Nos online, and he says he's coming over then we'll go get some weed and just hang out (like we always do at Ts, no one's ever there to bother us). Tonight however, we were in for a bit of a treat. Dingo knew one of the dealers and we got hooked up with about 2 grams of JA, which is a fairly potent strain of Jamaican weed we get here in the Caribbean.
Time: 11:37 PM
Since I enjoy a more 'trippy' expericence, I opted to eat mine in a bun between two slices of cheese (microwaved), as did Nos and Dingo. It'd be about the fourth time for me and Nos eating our pot as such, Dingo had only previously smoked before. We then set about amusing ourselves while waiting for the effects to kick in.
Time: 1:09 AM
While lying on Ts bed I began to feel a familiar burning/tingling in my chest. W00! We're on our way baby! The effects come on *very* slowly however, so much so that I wonder whether or not I'm actually getting high as yet. Time slows down ever so slightly as I get up and go to the kitchen for some popcorn.
Time: 1:37 AM
I can definitely feel the difference, somewhat spaced out, somewhat lighter. Every muscle in my face is active, and I'm aware of them all, individually. Suddenly I feel very active and playful, as I usually do when high, so I put on Queens Of The Stone Age to get the vibe going. Five minutes pass, but its like an eternity. I can feel the air around my limbs as though it is thickening, and start to get some intense closed-eye visuals, in which figures move in tune to the music. This world is green and muddy, much like a swamp. I open and close my eyes, going between the Green and T's Room, Its utterly fascinating for a while.  But not tonight. This is too real, too wonderful so I close my eyes and thrash about madly on the floor, swimming through the Green.
The song changes to Pink Floyd - Time (Winamp playlists are wonderful things) and strangely, so do my 'visuals'. This time the sea is red, then cycles through blues, greens, purples and yellows until I'm confronted with a myrian of dancing bears, in jester's hats. At this point I open my eyes and blurt out something about teddy bears and banannas and start to move to the music. As I close my eyes I envision my arms as great feathered wings. Dingo, on ther other hand, is pretty stoned, but in a different manner altogether. He'continuously talking about everything and nothing, all in a hilarious New York accent. Nos just sits and laughs at us, and tries to get into the fun.
Time: Sometime after 2 AM
After realising how intense this high was going to be I decided to experiment with it. We all pretty much had the munchies, so I take two Redoxon out of the tube and hand one to Dingo. After his initial paranoia (I had difficulty explaining to him that it was safe to eat) I popped mine as well and immediately the sensation burned through my entire mouth. The effervescence of it, coupled with the sweet tangy taste was mind-blowing. I felt my teeth vibrating as the tablet dissolved, and started to giggle uncontrollably, Dingo was obviously feeling the same thing (I could tell by his facial expression) and started to laugh too.
The burnout was slow in coming on, but when it hit me I went straight to the bed like clockwork and lay down, but couldnt not sleep. Visions of green seas and shadowy dancers came to life as soon everytime I closed my eyes. Slowly I faded away, feeling completely at ease.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


IFYOU ANSWER YES FOR AT LEAST ONE OF THE ITEMS, THERE MAY BE AN IP SITUATION!


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Topic 21 Computational Cognitive Science
21.1 Reading list
Ron Sun. The Cambridge Handbook of Computational Psychology. 2008
Nikolaus Kriegeskorte and Pamela K. Doug. Cognitive computational neuroscience
21.1.1 Foundations
- Paul Thagard (2005). Mind: Introduction to cognitive science (2nd ed.)
- Stephan Lewandowski & Simon Farrell (2012). Computational Modeling in Cognition
Marr (1982). Vision.
- Fact, Fiction, and Forecast. Cambridge, MA: Harvard University Press, 1983. ISBN:<PHONE_NUMBER>.
- Language and Learning: The Debate between Jean Piaget and Noam Chomsky. Edited by Massimo Piattelli-Palmarini. Cambridge, MA: Harvard University Press, 1984, ISBN:<PHONE_NUMBER>.
- Fodor, J. A., M. F. Garrett, E. C. T. Walker, and C. H. Parkes. “Against Definitions.” Cognition 8 (1980): 263-367.
Laurence, Stephen, and Eric Margolis. “Radical Concept Nativism.” Cognition 86 (2002): 22-55.
21.1.2 Foundations of Inductive Learning
- Russell, Stuart J., and Peter Norvig. Artificial Intelligence: A Modern Approach. 2nd ed. Upper Saddle River, N.J.: Prentice Hall/Pearson Education, 2003. ISBN:<PHONE_NUMBER>
- Berwick, R. C. “Learning From Positive-only Examples: The Subset Principle and Three Case Studies.” Machine Learning 2 (1986): 625- 645.
- Bruner, Jerome S., Jacqueline J. Goodnow, and George Austin. A Study in Thinking. Somerset, NJ: Transaction Publishers, 1986. ISBN:<PHONE_NUMBER>
- Mitchell, Thomas M. Machine Learning. New York, NY: McGraw-Hill, 1997, chapter 2. ISBN:<PHONE_NUMBER>.
- Feldman, J. “Minimization of Boolean Complexity in Human Concept Learning.” Nature 407 (2000): 630-633.
- Kearns, Michael J., and Umesh V. Vasirani. An Introduction to Computational Learning Theory. Cambridge, MA: MIT Press, 1994, pp. 1-7. ISBN:<PHONE_NUMBER>.
- The Psychology of Computer Vision. New York, NY: McGaw-Hill, 1975, pp. 157-209. ISBN:<PHONE_NUMBER>.
21.1.3 Concepts and learning
- Stuart Russell & Peter Norvig (2010). Artificial intelligence: a modern approach (third edition)
- Gregory Murphy (2002). The big book of concepts.
21.1.4 Knowledge Representation: Spaces, Trees, Features
- Shepard, R. N. “Multidimensional Scaling, Tree-fitting, and Clustering.” Science 210 (1980): 390-398.
- Landaues, T. K., and S. T. Dumais. “A Solution to Plato’s Problem: The Latent Semantic Analysis Theory of the Acquisition, Induction, and Representation of Knowledge.” Psychological Review 104 (1997): 211-240.
- Goldstone, R. L, and J. Son. “Similarity.” In Cambridge Handbook of Thinking and Reasoning. Edited by K. Holyoak and R. Morrison. Cambridge, MA: Cambridge University Press, 2005, pp. 13-36.
21.1.5 Knowledge Representation: Language and Logic
- Chomsky, Noam. Syntactic Structures. Berlin, Germany: Walter De Gruyter, Inc., 1976, pp. 11-48. ISBN:<PHONE_NUMBER>.
- Markman, Arthur. Knowledge Representation. Mahwah, NJ: Lawrence Erlbaum Associates, 1998, pp. 118-146, and 188-216. ISBN:<PHONE_NUMBER>.
- Nowak, M. A., N. L. Komarova, and P. Niyogi. “Computational and Evolutionary Aspects of Language.” Nature 417 (2002): 611-617.
- Gentner, D., and A. B. Markman. “Structural Alignment in Analogy and Similarity.” American Psychologist 52, no. 1 (1997): 45-56.
- Rosch, E. “Principles of Categorization.” In Cognition and Categorisation. Edited by E. Rosch and B. Lloyd. Hillsdale, NJ: Erlbaum, 1978, pp. 27-48.
- Armstrong S. L., L. R. Gleitman, and H. Gleitman. “What Some Concepts Might Not Be.” Cognition 13, no. 3 (May 1983): 263-308.
- An Invitation to Cognitive Science: Language. Edited by L. Gleitman, and M. Liberman. 2nd ed. Vol. 1. Cambridge, MA: MIT Press, 1995. ISBN:<PHONE_NUMBER>.
- Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Vol. 2. Cambridge, MA: MIT Press, 1987. ISBN:<PHONE_NUMBER>.
- Collins, A. M., and M. R. Quillian. “Retrieval Time from Semantic Memory.” Journal of Verbal Learning and Verbal Behavior 8 (1969): 240-248.
- McClelland, and Rogers. “The Parallel Distributed Processing Approach to Semantic Cognition.” Nature Reviews Neuroscience 4 (April 2003): 1-14.
- Comprehensive Handbook of Psychology. Edited by A. F. Healy, and R. W. Proctor. Vol. 4: Experimental Psychology. 2003, pp. 591-621.
- Paccanaro, A., and G. E. Hinton. “Learning Distributed Representations of Concepts Using Linear Relational Embedding.” Technical Report: GCNU TR 2000-002, March 2000.
21.1.6 Knowledge Representation: Great Debates
- Jeffreys, and Berger. “Bayesian Occam’s Razor.” American Scientist 80 (1992): 64-72.
- Tversky, A., and D. Kahneman. “Judgement under Uncertainty: Heuristics and Biases.” Science 185 (1974): 1124-1130.
- Sivia. Bayesian Data Analysis. New York, NY: Oxford University Press, 1996, pp. 1-23. ISBN:<PHONE_NUMBER>.
- Charniak. “Bayesian Networks without Tears.” AI Magazine 12, no. 4 (1991): 50-63.
- Johnson-Laird, P. N., and Fabien Savary. “Illusory Inferences about Probabilities.” Acta Psychologica 93 (1996): 69-90.
21.1.7 Basic Bayesian Inference
- Bayesian Data Analysis. 2nd ed. London, UK: Chapman & Hall, 1995, pp. 117-131. ISBN:<PHONE_NUMBER>.
- Proceedings of the 24th Annual Conference of the Cognitive Science Society (2002).
- Fact, Fiction, and Forecast. Cambridge, MA: Harvard University Press, 1983. ISBN:<PHONE_NUMBER>.
21.1.8 Graphical Models and Bayes Nets
- Advances in Neural Information Processing Systems 12. Edited by S. Solla, T. Leen, and K. Muller. Cambridge, MA: MIT Press, 2000, 59-65. ISBN:<PHONE_NUMBER>.
- Posner, and Keele. “On the Genesis of Abstract Ideas.” Journal of Experimental Psychology 77 (1968): 353-363.
- Neural Networks for Pattern Recognition. New York, NY: Oxford University Press, 1995. ISBN:<PHONE_NUMBER>.
21.1.9 Simple Bayesian Learning
- Fried, and Holyoak. “Induction of Category Distributions: A Framework for Classification Learning.” Journal of Experimental Psychology: Learning, Memory and Cognition 10 (1984): 234-257.
- Ghahramani, Z., and M. I. Jordan. “Learning from Incomplete Data.” MIT Center for Biological and Computational Learning Technical Report 108 (1994).
- The Twentieth International Conference on Machine Learning (ICML). Washington, DC: 2003.
- Nigam, Kamal, Andrew McCallum, Sebastian Thrun, and Tom Mitchell. “Text Classification from Labeled and Unlabeled Documents using EM.” Machine Learning 39, no. 2/3 (2000): 103-134.
- Seeger, M. “Learning with Labeled and Unlabeled Data.” University of Edinburgh Institute for Adaptive and Neural Computation Technical Report (2001).
- Nosofsky, R. M. “Optimal Performance and Exemplar Models of Classification.” In Rational Models of Cognition. Edited by M. Oaksford and N. Chater. New York, NY: Oxford University Press, 1998, pp. 219-247.
- Kruschke, J. K. “Human Category Learning: Implications for Backpropagation Models.” Connection Science 5, no. 1 (1993): 3-37.
- B. W. Silverman. “Maximum Penalized Likelihood Estimators.” In Density Estimation. London, UK: Chapman and Hall, 1986, pp. 110-119.
- Hinton, G. E., P. Dayan, B. J. Frey, and R. M. Neal. “The Wake-sleep Algorithm for Unsupervised Neural Networks.” Science 268 (1995): 1158-1160.
21.1.10 Probabilistic inference
- Sharon Goldwater (2018). Basic probability theory
- Joshua B. Tenenbaum & Tom Griffiths (2001). Generalization, similarity, and Bayesian inference (pages 629–634). Behavioral and Brain Sciences.
- Fei Xu & Joshua B. Tenenbaum (2007). Word learning as Bayesian inference
Michael C. Frank & Noah D. Goodman (2012). Predicting pragmatic reasoning in language games. Science
- Anderson, J. R. “The Adaptive Nature of Human Categorization.” Psychological Review 98, no. 3 (1991): 409-429.
- Smyth, P. “Model Selection for Probabilistic Clustering using Cross-validated Likelihood.” Statistics and Computing 10, no. 1 (2000): 63-72.
MacKay, D. J. C. “Probable Networks and Plausible Predictions - A Review of Practical Bayesian Methods for Supervised Neural Networks.” Network: Comput. Neural Syst. 6 (1995): 469-505.
21.1.11 Probabilistic models of cognition
21.1.12 Formal grammars
- Noam Chomsky (1957). Syntactic structures
- Dan Jurafsky and James Martin (2019). Speech and Language Processing (third edition)
21.1.13 Unsupervised and Semi-supervised Learning
- Murphy, Gregory L., and Douglas L. Medin. “The Role of Theories in Conceptual Coherence.” Chapter 19 in Concepts: Core Readings. Edited by E. Margolis, and S. Laurence. Cambridge, MA: MIT Press, July 1999, pp. 425-458. ISBN:<PHONE_NUMBER>938.
- Gelman, Susan A. The Essential Child. New York, NY: Oxford University Press, March 1, 2003, chapter 1, and 3, pp. 3-18, and 60-88. ISBN:<PHONE_NUMBER>.
- Courville, Aaron C., Nathaniel D. Daw and David S. Touretzky. “Similarity and Discrimination in Classical Conditioning: A Latent Variable Account.” Neural Information Processing Systems Conference (2004).
- Rehder, Bob. “Essentialism as a Generative Theory of Classification.” To appear in Gopnik, A., and L. Schulz (Eds.) Causal learning: Psychology, philosophy, and computation. New York, NY: Oxford University Press.
21.1.14 Non-parametric Classification: Exemplar Models and Neural Networks
- Pearl, Judea. Causality: Models, Reasoning, and Inference. Cambridge, MA: Cambridge University Press, 2000, chapter 1. ISBN:<PHONE_NUMBER>.
- Gregory F. Cooper. “An Overview of the Representation and Discovery of Causal Relationships using Bayesian Networks.” In Computation, Causation, and Discovery. Edited by Clark Glymour and Gregory F. Cooper. MIT Press, June 1999, pp. 3-62. ISBN:<PHONE_NUMBER>.
- Gopnik, Alison, and Laura Schulz. “Mechanisms of Theory Formation in Young Children.” Trends in Cognitive Sciences 8, no. 8 (August 2004): 371-377.
21.1.15 Controlling Complexity and Occam’s Razor
Wellman, Henry M., and Susan A. Gelman. “Cognitive Development: Foundational Theories of Core Domains.” Annu Rev Psychol 43 (1992): 337-75.
Tenenbaum J. B., and Griffiths. “The Place of Intuitive Theories in Rational Causal Inference.” To appear in Gopnik, A., and L. Schulz (Eds.) Causal learning: Psychology, philosophy, and computation. New York, NY: Oxford University Press.
Charles Kemp, Thomas L. Griffiths, and Joshua B. Tenenbaum. Discovering Latent Classes in Relational Data. MIT Computer Science and Artificial Intelligence Laboratory. AI Memo 2004-019, September 2004.
Rehder, Bob. “Essentialism as a Generative Theory of Classification.” To appear in Gopnik, A., and L. Schulz (Eds.) Causal learning: Psychology, philosophy, and computation. New York, NY: Oxford University Press.
Milch, Brian, Bhaskara Marthi, and Stuart Russell. “BLOG: Relational Modeling with Unknown Objects.” Workshop on Statistical Relational Learning and Its Connections to Other Fields. The Twenty-First International Conference on Machine Learning (ICML). Banff, Alberta: July 2004.
21.1.16 Intuitive Biology and the Role of Theories
- Osherson, Daniel N., O. Wilkie, E. E. Smith, A. Lopez, and E. Shafir. “Category-Based Induction.” Psychological Review 97, no. 2 (1990): 185-200.
- Atran, Scott. “Classifying Nature Across Cultures.” In Thinking: An Invitation to Cognitive Science. Edited by Edward E. Smith, Daniel N. Osherson, et. al. 2nd ed. Vol. 3. Cambridge, MA: MIT Press, 1995, pp. 131-174. ISBN:<PHONE_NUMBER>.
- Kemp, C., and J. B. Tenenbaum. “Theory-based Induction.” In Proceedings of the 25th Annual Conference of the Cognitive Science Society (2003).
- Kemp, C., T. L. Griffiths, S. Stromsten, and J. B. Tenenbaum. “Semi-supervised Learning with Trees.” In Advances in Neural Information Processing Systems (2003).
21.1.17 Learning Domain Structures
Keil, Frank C. “Contraints on Knowledge and Cognitive Development.” Psychological Review 88, no. 3 (May 1981): 197-227.
McClelland, and Rogers. “The Parallel Distributed Processing Approach to Semantic Cognition.” Nature Reviews Neuroscience 4 (April 2003): 1-14.
Kemp, Charles, Amy Perfors, and Joshua B. Tenenbaum. Learning Domain Structures. Department of Brain and Cognitive Sciences, MIT. Internal Memo.
Geman, Stuart, and E. Bienenstock. “Neural Networks and the Bias/Variance Dilemma.” Neural Computation 4 (1992): 1-58. [Especially pp. 46-48]
Scholl, Brian J.,and Patrice D. “Perceptual Causality and Animacy.” Tremoulet Trends in Cognitive Sciences 4, no. 8 (August 2000): 299-309.
Feldman, Jacob, and Patrice D. Tremoulet. The Computation of Intention. (Forthcoming)
21.1.18 Reinforcement learning
- Sutton and Barto (2018). Reinforcement learning: an introduction
- Jessica Hamrick (2019). Analogues of mental simulation and imagination in deep learning. Current Opinions in Behavioral Sciences
21.1.19 Artificial neural networks
- Elman et al (1996). Rethinking Innateness: A connectionist perspective on development
- James L. McClelland & Timothy T. Rogers (2003). The parallel distributed processing approach to semantic cognition. Nature Reviews Neuroscience
21.1.20 Language acquisition across modeling approaches
- Afra Alishahi (2010). Computational modeling of human language acquisition
- Steven Pinker & Michael T. Ullman (2002). The past and future of the past tense. Trends in Cognitive Sciences
21.1.21 Vision across modeling approaches
- John P. Frisby & James V. Stone (2010). Seeing
- Nikolaus Kriegeskorte (2015). Deep neural networks: a new framework for modeling biological vision and brain information processing. Annual Review of Vision Science
- Brenden Lake, Ruslan Salakhutdinov & Joshua B. Tenenbaum (2015). Human-level concept learning through probabilistic program induction. Science
21.1.22 Contemporary artificial intelligence and cognitive science
- Yann Lecun, Yoshua Bengio & Geoffrey Hinton (2015). Deep learning. Nature.
- Douglas Heaven (2019).  Nature.
- Sharon Zhou (2018). Has AI surpassed humans at translation? Not even close!. Skynet today.
21.1.23 Others
- Brenden Lake, Tomer Ullman, Joshua B. Tenenbaum and Sam Gershman. (2017). Building machines that learn and think like people. Behavioral and Brain Sciences.
- Tal Linzen (2019). What can linguistics and deep learning contribute to each other? Language.
21.2 Courses
21.3 Labs
- Center for Brains, Minds + Machines
- Computational Cognitive Science Group at MIT
- Computation and Psycholinguistics Lab at John Hopkins University
- Computational Cognitive Science Lab at Princeton University
- Computational Cognitive Science at New York University
- Learning.Understanding.Cognition.Intelligence.Data science
- Serre Lab at Brown University
- UNSW Computational Cognitive Science
- Computation & Cognition Lab at Stanford
- Computational Cognitive Neuroscience Lab at Oxford
21.4 Others
- AI Podcast with Lex Fridman
- Judea Pearl: Causal Reasoning, Counterfactuals, Bayesian Networks, and the Path to AGI
- Gary Marcus: Toward a Hybrid of Deep Learning and Symbolic AI
- Jeff Hawkins: Thousand Brains Theory of Intelligence
- Eric Weinstein: Revolutionary Ideas in Science, Math, and Society
- Elon Musk: Tesla Autopilot
- Elon Musk: Neuralink, AI, Autopilot, and the Pale Blue Dot
- François Chollet: Keras, Deep Learning, and the Progress of AI


{% extends "base.html" %} {% load static from staticfiles %} {% block title %}Worlds at War - About{% endblock %} {% block content %}
Worlds at War is a galactopolitical simulator, designed, coded and administrated by me, heidi.
True Evangelion also helps out with administration.
You may contact me at mlpanon@gmail.com.


Update User
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{% extends "backend/base.html" %} {% load i18n sekizai_tags duration switzerland %} {% block title %}{% trans "All appointments" %} - {{ block.super }}{% endblock %} {% block page_title %}{% trans "All appointments" %}{% endblock %} {% get_current_language as LANGUAGE_CODE %} {% block content %}
{% trans "Export appointments" %}
{% regroup object_list by start|date:"l d F Y" as slots_per_day %} {% for slot in slots_per_day %}


--- title: Front-end Developer category: Hidden order: 502 ---
We're actively looking for a Front-end Developer to join our Community team.
Every day, our developer community at DuckDuckHack submits Instant Answers to our search engine. As staff, we work with contributors to polish their Instant Answer code (and idea) until the final product is a useful and beautiful Instant Answer on DuckDuckGo.com that works across a broad range of devices and platforms.
Our developer community is diverse in culture and programming experience, so some contributions require a bit more polishing than others. In many cases, developers get tripped up by some nuances in the front-end implementation of their Instant Answers.
This team member would be responsible for working with contributors to refine the front-end portion of their Instant Answer submissions until they're acceptable for use live on DuckDuckGo. Further, this person will polish our own platform and processes such that these issues are less frequent (or non-existent) over time.
To see what we mean, check out this Pull Request where our staff + community helped kbhat95 adjust the design on their Playing Cards Instant Answer.
The issue of needing to customize or adjust the front-end for an Instant Answer is common. Using the Playing Cards Instant Answer as an example, the optimal front-end candidate will make strategic decisions that reduce the occurrence of adjustments to the front-end code by a contributor. For example, by creating templates or styleguides for the scenarios where our contributors frequently need help.
Some notes about the position:
Technical requirements:
Community requirements:
Please see https://duck.co/help/company/hiring for general details about DuckDuckGo hiring and how-to apply for positions.


--- layout: default ---
This blog is an informal complement to its technical counterpart and is mainly composed of book reviews. My interests are fairly broad but tend to cluster around topics like history, politics, science, statistics, as well as some select fiction and poetry.
You can reach me here: 13ewd@queensu.ca


LOADING... CHESS SET: Classic Iconic Bauhaus Mueller Minions CHESS ENGINE: p4wn Lozza stockfish MOVE TIME (seconds): 0.1 0.2 0.5 1 2 5 10 20 PROMOTE PAWNS TO: queens knights rooks bishops SET PGN SET FEN


React intl input
A flexible and beautiful Input control for ReactJS to handle multi languages fields.
Code and docs on GitHub
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Floating Mountain Stability
问题描述 :
The scientists now believe that the sizes of the stacked mountains did follow generalized Fibbonacci sequence property originally (when they were formed), but they believe that some of the mountains in the structures may have been destroyed or may have drifted apart. They further observed that at most 9 consecutive mountains in the stack may be removed without compromising the stability of the structure. They are now trying to verify this new conjecture.
You are to write a program for this purpose. Specifically, given a sequence of numbers, some of which may be negative, you must determine if the numbers are part of a generalized Fibbonacci sequence (let’s call it the original sequence), such that all consecutive pairs of numbers in the input sequence are less than 10 apart (i.e., fewer than 9 items between any consecutive pair of numbers) in the original generalized Fibbonacci sequence.
As an example, the sequence: 0 6 16, follows this property because the numbers are from the following generalized Fibbonacci sequence:
and 0 & 6 are only 4 numbers apart in the generalized sequence.
As another example: the sequence -22 8 77 125, also satisfies the property. Here is the corresponding generalized Fibbonacci sequence:
输入:
输出:
样例输入:
3 3 0 6 16 4 -22 8 77 125 4 1 1 1 1
样例输出:
STABLE 0 2 2 4 6 STABLE -22 15 -7 8 1 UNSTABLE
为什么暴力求解方法循环到sqrt(n) 就可以了呢
还是有些难度的！
第63行是不是漏了 return 1 + dis_right; ?
即为打印出的组合的个数C(n,r)，假设print函数复杂度为O(1)
不错
为什么暴力求解方法循环到sqrt(n) 就可以了呢
给力，赞一个
第15行代码，/n/n，应该改为\n\n
网站不错
Often We don’t set up on weblogs, but I would like to condition that this established up really forced me individually to do this! considerably outstanding publish
great!
很好的思路，可以借鉴
涨姿势了
这个方法是错的，不信你试试：
20 5
1 A:9
1 A:9
1 A:9
1 A:6
1 A:4
正确答案应该是19，这个答案是18


Space object entry tracking for meteors and space debris.
Check it outExploring Minecraft as an open-world simulator for RL agents, with various objectives like collection, survival, and architecture.
Check it outPersonal project on blended wing VTOL drones and autonomous flight.
Check it out


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Me, Myself, and I
My name is Carolyn, pronounced like Caroline but spelled but spelled like Carolyn. I was born in Louisiana, but raised here in Colorado. I am a 4th year, second year in the TAM program. I recently adopted a kitten, he is a Russian Blue 4 months old, and his name is Gandalf.
Experience and Interest
The only real experience is the web class I took last semester. Because of the web class I really wanted to know and have more experience and practice on creating and and desiging websites.
Learnage
I really want to learn more about the best way to organize a html and a css file. such as naming it or labeling it. I feel like it can get messy and I just really want more practice on how to organize all the files so it is readable and understable.


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Cork credit union to scrap death benefit insurance
Many vulnerable, elderly people will be left with no life cover when a credit union scraps its death benefit insurance next month.
Gurranabraher Credit Union may be the first in Ireland to stop the scheme, providing €4,000 to fund end of life expenses to members, paid for by all adult members via a €30 annual fee.
New Central Bank regulations require credit unions to get 50% of members to sign up to the scheme, or abolish it. Only 36% of the Cork credit union’s members signed up, so it is due to end on December 30.
Sinn Féin councillor Thomas Gould said that many members were unaware of the new rules and are now “distraught” that the benefit is ending.
Cllr Gould said: “It’s having serious ramifications on families. The worry it’s causing people is terrible. People are distraught, especially the elderly.
“From December 31, 3,500 people will be left with no cover. Many of these people are elderly or retired, they’ve paid into the scheme for 40 or 50 years and they cannot now afford to take out new insurance.
“It’s a brilliant initiative. A lot of elderly people used it as their life insurance policy.
“I’ve asked the Credit Union to extend the deadline by two weeks. They did extend it once but there wasn’t enough publicity about it so people didn’t know.
“Many people don’t open letters from the credit union, thinking they’re about car loans or advertising. So sending a letter or two asking people to sign up to something is not enough. There needs to be a public awareness campaign. A lot of members are really upset.
“The Central Bank is over regulating. It let the banks and financial institutions get away with murder before and now it puts barriers in the way when there’s an initiative which actually helps people. It’s a crazy decision and it has national implications for all credit unions.”
A spokesperson for the Irish League of Credit Unions said that the scheme did not fall under central control and that decisions on it would be taken at a local level.
Gurranabraher Credit Union was contacted for comment but had not replied at the time of publication.


The experimental.identity API has moved to identity. You can read all about it at its new home:
experimental.identity
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Searching for references to a particular piece of code. It shouldn't be this hard, but it is.
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Searching for references to a particular piece of code. It shouldn't be this hard, but it is.
2/23/2009, 1:53:35 PM
Favs: 0
Retweets: 0
link