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Driver Points
Team with driver in first place is awarded Cletus
Team Points
First place team receives the Dual Pistons
Last place team is awarded the Toilet
Team DNFs
Team with most DNFs is awarded the Burnt Spark Plug


By sampling your data, running the provided classifier on these samples in parallel on your own machine and letting your models vote on a prediction, we return much faster predictions than the regular machine learning algorithm and possibly even more accurate predictions.
| Version: | 1.2 |
| Depends: | R (≥ 2.14.0) |
| Imports: | parallel (≥ 3.1.1), foreach (≥ 1.2.0), doParallel (≥ 1.0.8) |
| Published: | 2015-06-26 |
| Author: | Wannes Rosiers (InfoFarm) |
| Maintainer: | Wannes Rosiers <wannes.rosiers at infofarm.be> |
| License: | GPL-2 |
| URL: | www.infofarm.be |
| NeedsCompilation: | no |
| CRAN checks: | parallelML results |
| Reference manual: | parallelML.pdf |
| Package source: | parallelML_1.2.tar.gz |
| Windows binaries: | r-devel: parallelML_1.2.zip, r-release: parallelML_1.2.zip, r-oldrel: parallelML_1.2.zip |
| OS X binaries: | r-release: parallelML_1.2.tgz, r-oldrel: parallelML_1.2.tgz |
| Old sources: | parallelML archive |
Please use the canonical form https://CRAN.R-project.org/package=parallelML to link to this page.


Combined effort for rapid automation of multiple project's under domain, as a part of this initiative
we created a E2E Automaton suite, separately for each applications. This was challenging as while shifting from
one application to another we had to thoroghly understand the internal behaviour of each of them in order to
seamlessly automate the functionalities.
We covered six different application within span of six months.


These are the activities you engaged in during the last 12 months.
= not yet mapped
= mapped to at least one location
No Locations Mapped


HOCOMOCO v11 motif collection provides transcription factor (TF) binding models for human and mouse TFs. In addition to basic mononucleotide position weight matrices (PWMs), HOCOMOCO provides dinucleotide position weight matrices based on ChIP-Seq data. All the models were produced by the ChIPMunk motif discovery tool. Model quality ratings are results of a comprehensive cross-validation benchmark. ChIP-Seq data for motif discovery was extracted from GTRD database.
Source: Extract from HOCOMOCO main page [2020/02/05]
This plugin is developed by Ilya Vorontsov from HOCOMOCO team.
Example queries: 'CEBPA', 'CEBPA_HUMAN.H11MO.0.A', 'C/EBP-related', 'HGNC:1833', ...


Reliance Jio appeals TRAI to do away with IUC charges
by Aakash JhaveriReliance Jio appeals TRAI to do away with IUC charges
The plot thickens
(Image credit: Flickr)
Reliance Jio continues to press for zero IUC charges to Telecom Regulatory Authority of India(TRAI), in hopes of doing away with the outgoing call charges that were imposed recently.
A month ago, Jio made an announcement that calls to other networks will now be chargeable, compromising one of the key selling points of the Reliance-owned network. However, they went on to explain why this change came in.
On October 9, TRAI passed a policy change which effectively compelled Jio to start recovering interconnecting user charges (IUC). These charges are applicable when Jio users would call someone using another network, and had to be passed on to the consumer. This led to Jio calls no longer being entirely free.
TRAI held a “Review of Interconnection User Charges” open house discussion on November 15 to look into the matter. During the discussion, Mahendra Nahata, the Director at Jio Infocomm, appealed on the implementation of zero-IUC charges.
He explained that “When you had implemented 6 paise charge, 4G traffic was one per cent. Today that traffic is much higher so the costs must have come down.” IUC is not applicable on VoLTE calls (Voice over LTE), and the entirety of calls from Jio are based on VoLTE.
"The traffic asymmetry is no longer there"
Moreover, the traffic asymmetry between Jio and other networks is now “at par with other operators”, a significant improvement to the 90% outgoing and 10% incoming voice calls that the company had in 2017. Nahata also added that even the BAK (Bill and keep) regime should be implemented now, so the networks can mutually agree to terminate calls from each other at no charge.
“The reason of traffic asymmetry is no longer there, for delaying the zero termination charge from January 1, 2020”, he explained, urging TRAI to at least lower the IUC from 6 paise.
On the flipside, Bharti Airtel and Vodafone-Idea said that the 6 paise interconnecting user charges should stay for at least three more years. TRAI will be taking the points into consideration and pass a new regulation in the coming weeks. No timeline was suggested.
- Reliance Jio users will now have to start paying for calls to other networks
- Reliance Jio Rs 149 plan revised to include calls to non-Jio users


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Hello Alex this is a good article.
Hello Alex this is a good article..
The Ultimate Guide to Making Money Online.

Want To Immediately Reverse All Your Health Issues?
Six Types Of Investors – Which Group Are You In?
How to Have a Healthier and More Productive Home Office
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The ground estimation process is used to determine the heights of the terrain beneath tree canopies in a digital elevation model (DEM). This process involves interpolating over masked DEMs and the interpolation methods used are Contextual Void Patching (CVP) and an inverse distance weighting (IDW) method, Local Modified Shepard algorithm. The estimated terrain is subtracted from the original DEM to obtain the final output of the system: the normalised DEM — containing only above-ground heights of trees in the orchard.
Figure 1: Ground estimation result from Aerobotics-provided DEM.
Sample DEMs of orchards were provided by Aerobotics in the form of single-band TIFF images. The DEM Generation subproject provided DEMs of landscapes with varying slope types and canopy types. The terrain types are: flat plane, gentle sloping plane, steep sloping plane, hill slope, interlocking spur slope and hügelland (hillocks). The canopy types are: wide canopies, small overlapping canopies and small spaced canopies. These DEMs were used to evaluate both interpolation methods.
The performances of CVP and IDW (Shepard) are evaluated qualitatively by visually comparing the estimated DEMs against the expected landscape. An error map is also generated to show the distribution of the error for each landscape. Quantitatively, the following error test statistics were calculated and compared for each combination of terrain and canopy type:
Estimation methods produced generally consistent results on different terrain types, but fared worst on hügelland DEMs. The canopy type did not affect the estimation accuracy greatly, but high magnitude error appeared to be localised about the centers of individual canopies. Noise in the DEMs contributed to error, especially in one of the DEMs of a gentle slope. Below are some results from the evaluation of the IDW (Shepard) results.
Figure 2: RMSE values from IDW (Shepard) results.
Figure 3: Series of error maps produced from the IDW (Shepard) results.
(Left-to-right) Top row: flat plane, gentle sloping plane. Middle row: hill slope, interlocking spur slope. Bottom row: Steep sloping plane, hügelland (hillocks).
CVP was outperformed by the IDW (Shepard) interpolation method for all terrain types except the hügelland terrain [CVP RMSE ~5.9; IDW RMSE ~6.2]. However, the Kappa statistics suggest that IDW (Shepard) results for hügelland had marginally better agreement with the initial landscape.
Table 1: Average Kappa statistic by terrain type.
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Alpaca is a client-side, cross-platform, JSON based forms and templating engine for rendering elegant content entry and presentation forms with minimal development effort,
It comes with comprehensive control library and support for validation, wizard, layout, templating, preview, i18n etc. Built upon jQuery library, jQuery UI and jQuery Mobile, Alpaca can be easily extended for additional form controls.
Ratchet is a light-weight JavaScript MVC framework that helps you build HTML5 and JavaScript based applications. It is ideal for real-time, cloud-connected applications.
While providing foundation features such as observables, components, templates, routes and so forth, Ratchet also defines an asynchronous rendering pipeline that manages state for the backend, stream content forward and aggregate it into HTML5.
Cloud CMS JavaScript driver is provided to lower the time and cost of building applications using JavaScript, HTML5, NodeJS, Appcelerator Titanium, SpiderMonkey, Rhino and other standalone interpreters.
It handles all HTTPS calls, data conversions, OAuth2 authorization handshakes and any and all interaction with the cloud server in a secure manner.
JavaScript Samples provides a rich set of examples to help you get started with developing HTML5/JavaScript based applications on top of Cloud CMS using its JavaScript Driver.
Samples are divided into three main categories, General, Component and Mini App. General samples are focus on APIs and techniques that will be used across all JavaScript based Cloud CMS applications. Component samples show you how to use APIs of an individual Cloud CMS component such as Repository, Branch, Node etc. Once you get familiar with Cloud CMS JavaScript driver, you may also want to check out mini sample applications to learn how to combine those JavaScript APIs.


@import common.dfp.LineItemReport @(slotReport: LineItemReport)(implicit request: RequestHeader, context: model.ApplicationContext) @admin_main("Commercial: Desktop Top-Above-Nav Slot", isAuthed = true) {
This slot will by default accommodate an ad of height 250px on business fronts unless there is an ad that:
The ad will also appear on the Code site if it targets a test cookie.
@views.html.commercial.fragments.slot(slotReport) }


{% include breadcrumbs.html %} {{ page.title }} Article {{ content | reading_time_as_i }} to read {{ page.last_modified_at }} {% include article-alert.html %} {{ content | inject_anchors }} {% include recommended-content.html %}


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Kelly Betting - Part One
In my current experiments I have been using the Kelly criterion to place theoretical bets on certain events. In the process, I found myself wanting to use the Kelly criterion for multiple simultaneous and independent events but come across a number of problems.
- Generally, most of the easily accessible Kelly tutorials only cover betting on one event.
- Simultaneous Kelly bets are either behind a pay-wall or just a calculator is offered which doesn’t derive any of the results and show how they are obtained.
So like any good scientist I’ve decided to give writing my own guide to Kelly betting. This will be the first part and go through the basic mathematics of the Kelly criterion. The second part will contain the simultaneous Kelly bet methodology.
Why Kelly Bet?
Imagine you have a model that predicts the outcome of the event with a probability \(p\). You wish to place a bet on this outcome occurring and find that the bookmakers offer (decimal) odds \(b\). Do you bet the whole house, or are you more conservative? What is the optimal bet size? This was answered by Kelly in 1956.
To derive the result, we wish to maximise the expected log value of the event. The expected value is
\[\mathbb{E} \left[ \log X \right] = p \log (1+ (b-1) x) + (1-p) \log (1- x),\]where \(x\) is the amount that is bet. So to find the value of \(x\) that maximises the expected bank roll we need to do some differentiation
\[\frac{\partial}{\partial x} \mathbb{E} \left[ \log X \right] = \frac{p(b-1)}{1 + (b-1)x} - \frac{1-p}{1-x}=0,\] \[\frac{p(b-1)}{1 + (b-1)x} = \frac{1-p}{1-x},\] \[x = \frac{pb-1}{b-1}\]Now if we check the Wikipedia article on Kelly betting we find that this is the same result if we convert from decimal odds to fractional odds. Therefore, for whatever probability your model spits out and whatever the odds the bookmaker offers you, you can place a bet that has a positive expected value and thus probably a good idea.
If the result from the Kelly formula is negative, this means that you wish to take the other side of the bet. With some betting exchanges, this is possible (“laying odds”). But due to the spread between the back and lay odds, you will not be able to immediately lay at the same odds you can back. Therefore you will need to consider the appropriate Kelly bet for laying an odd.
In the next part I will be looking at multiple bets occurring at the same time and how you can correctly split your bankroll whilst remaining in positive expected value territory.
References
https://en.wikipedia.org/wiki/Kelly_criterion
http://www.sportsbookreview.com/picks/tools/kelly-calculator/


Deploy Java Lambda functions with .zip or JAR file archives
Your AWS Lambda function's code consists of scripts or compiled programs and their dependencies. You use a deployment package to deploy your function code to Lambda. Lambda supports two types of deployment packages: container images and .zip files.
This page describes how to create your deployment package as a .zip file or Jar file, and then use the deployment package to deploy your function code to AWS Lambda using the AWS Command Line Interface (AWS CLI).
Sections
Prerequisites
The AWS Command Line Interface (AWS CLI) is an open source tool that enables you to interact with AWS services using commands in your command-line shell. To complete the steps in this section, you need the following:
Tools and libraries
Lambda provides the following libraries for Java functions:
-
com.amazonaws:aws-lambda-java-core
(required) – Defines handler method interfaces and the context object that the runtime passes to the handler. If you define your own input types, this is the only library that you need. -
com.amazonaws:aws-lambda-java-events
– Input types for events from services that invoke Lambda functions. -
com.amazonaws:aws-lambda-java-log4j2
– An appender library for Apache Log4j 2 that you can use to add the request ID for the current invocation to your function logs.
These libraries are available through Maven
Central Repository
To create a deployment package, compile your function code and dependencies into a single .zip file or Java Archive (JAR) file. For Gradle, use the Zip build type. For Apache Maven, use the Maven Shade plugin.
To keep your deployment package size small, package your function's dependencies in layers. Layers enable you to manage your dependencies independently, can be used by multiple functions, and can be shared with other accounts. For more information, see Lambda layers.
Building a deployment package with Gradle
To create a deployment package with your function's code and dependencies, use the
Zip
build
type.
Example build.gradle – Build task
task buildZip(type: Zip) { from compileJava from processResources into('lib') { from configurations.runtimeClasspath } }
This build configuration produces a deployment package in the build/distributions
directory. The
compileJava
task compiles your function's classes. The processResources
task copies the Java project resources into their target directory, potentially processing
then. The statement into('lib')
then copies dependency libraries from the build's classpath into a folder named lib
.
Example build.gradle – Dependencies
dependencies { implementation platform('software.amazon.awssdk:bom:2.10.73') implementation 'software.amazon.awssdk:lambda'
implementation 'com.amazonaws:aws-lambda-java-core:1.2.1' implementation 'com.amazonaws:aws-lambda-java-events:3.1.0'
implementation 'com.google.code.gson:gson:2.8.6' implementation 'org.apache.logging.log4j:log4j-api:2.13.0' implementation 'org.apache.logging.log4j:log4j-core:2.13.0' runtimeOnly 'org.apache.logging.log4j:log4j-slf4j18-impl:2.13.0'runtimeOnly 'com.amazonaws:aws-lambda-java-log4j2:1.2.0'
testImplementation 'org.junit.jupiter:junit-jupiter-api:5.6.0' testRuntimeOnly 'org.junit.jupiter:junit-jupiter-engine:5.6.0' }
Lambda loads JAR files in Unicode alphabetical order. If multiple JAR files in the
lib
directory
contain the same class, the first one is used. You can use the following shell script
to identify duplicate
classes:
Example test-zip.sh
mkdir -p expanded unzip path/to/my/function.zip -d expanded find ./expanded/lib -name '*.jar' | xargs -n1 zipinfo -1 | grep '.*.class' | sort | uniq -c | sort
Building a deployment package with Maven
To build a deployment package with Maven, use the Maven Shade plugin
Example pom.xml – Plugin configuration
<plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-shade-plugin</artifactId> <version>3.2.2</version> <configuration> <createDependencyReducedPom>false</createDependencyReducedPom> </configuration> <executions> <execution> <phase>package</phase> <goals> <goal>shade</goal> </goals> </execution> </executions> </plugin>
To build the deployment package, use the mvn package
command.
[INFO] Scanning for projects... [INFO] -----------------------< com.example:java-maven >----------------------- [INFO] Building java-maven-function 1.0-SNAPSHOT [INFO] --------------------------------[ jar ]--------------------------------- ... [INFO] --- maven-jar-plugin:2.4:jar (default-jar) @ java-maven --- [INFO] Building jar: target/java-maven-1.0-SNAPSHOT.jar [INFO] [INFO] --- maven-shade-plugin:3.2.2:shade (default) @ java-maven --- [INFO] Including com.amazonaws:aws-lambda-java-core:jar:1.2.1 in the shaded jar. [INFO] Including com.amazonaws:aws-lambda-java-events:jar:3.1.0 in the shaded jar. [INFO] Including joda-time:joda-time:jar:2.6 in the shaded jar. [INFO] Including com.google.code.gson:gson:jar:2.8.6 in the shaded jar. [INFO] Replacing original artifact with shaded artifact. [INFO] Replacing target/java-maven-1.0-SNAPSHOT.jar with target/java-maven-1.0-SNAPSHOT-shaded.jar [INFO] ------------------------------------------------------------------------ [INFO] BUILD SUCCESS [INFO] ------------------------------------------------------------------------ [INFO] Total time: 8.321 s [INFO] Finished at: 2020-03-03T09:07:19Z [INFO] ------------------------------------------------------------------------
This command generates a JAR file in the target
directory.
If you use the appender library (aws-lambda-java-log4j2
), you must also configure a transformer
for the Maven Shade plugin. The transformer library combines versions of a cache file
that appear in both the
appender library and in Log4j.
Example pom.xml – Plugin configuration with Log4j 2 appender
<plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-shade-plugin</artifactId> <version>3.2.2</version> <configuration> <createDependencyReducedPom>false</createDependencyReducedPom> </configuration> <executions> <execution> <phase>package</phase> <goals> <goal>shade</goal> </goals> <configuration> <transformers> <transformer implementation="com.github.edwgiz.maven_shade_plugin.log4j2_cache_transformer.PluginsCacheFileTransformer"> </transformer> </transformers> </configuration> </execution> </executions> <dependencies> <dependency> <groupId>com.github.edwgiz</groupId> <artifactId>maven-shade-plugin.log4j2-cachefile-transformer</artifactId> <version>2.13.0</version> </dependency> </dependencies> </plugin>
Uploading a deployment package with the Lambda API
To update a function's code with the AWS Command Line Interface (AWS CLI) or AWS SDK,
use the UpdateFunctionCode API
operation. For the AWS CLI, use the update-function-code
command. The following command uploads a
deployment package named my-function.zip
in the current directory:
aws lambda update-function-code --function-name my-function --zip-file fileb://my-function.zip
You should see the following output:
{ "FunctionName": "my-function", "FunctionArn": "arn:aws:lambda:us-east-2:123456789012:function:my-function", "Runtime": "java8", "Role": "arn:aws:iam::123456789012:role/lambda-role", "Handler": "example.Handler", "CodeSha256": "Qf0hMc1I2di6YFMi9aXm3JtGTmcDbjniEuiYonYptAk=", "Version": "$LATEST", "TracingConfig": { "Mode": "Active" }, "RevisionId": "983ed1e3-ca8e-434b-8dc1-7d72ebadd83d", ... }
If your deployment package is larger than 50 MB, you can't upload it directly. Upload
it to an
Amazon Simple Storage Service (Amazon S3) bucket and point Lambda to the object. The
following example commands upload a deployment package
to an S3 bucket named my-bucket
and use it to update a function's code:
aws s3 cp my-function.zip s3://my-bucket
You should see the following output:
upload: my-function.zip to s3://my-bucket/my-function
aws lambda update-function-code --function-name my-function \ --s3-bucket my-bucket --s3-key my-function.zip
You should see the following output:
{ "FunctionName": "my-function", "FunctionArn": "arn:aws:lambda:us-east-2:123456789012:function:my-function", "Runtime": "java8", "Role": "arn:aws:iam::123456789012:role/lambda-role", "Handler": "example.Handler", "CodeSha256": "Qf0hMc1I2di6YFMi9aXm3JtGTmcDbjniEuiYonYptAk=", "Version": "$LATEST", "TracingConfig": { "Mode": "Active" }, "RevisionId": "983ed1e3-ca8e-434b-8dc1-7d72ebadd83d", ... }
You can use this method to upload function packages up to 250 MB (decompressed).
Uploading a deployment package with AWS SAM
You can use AWS SAM to automate deployments of your function code, configuration,
and dependencies. AWS SAM is an
extension of AWS CloudFormation that provides a simplified syntax for defining serverless
applications. The following example
template defines a function with a deployment package in the build/distributions
directory that
Gradle uses:
Example template.yml
AWSTemplateFormatVersion: '2010-09-09' Transform: 'AWS::Serverless-2016-10-31' Description: An AWS Lambda application that calls the Lambda API. Resources: function: Type: AWS::Serverless::Function Properties:
CodeUri: build/distributions/java-basic.zip
Handler: example.Handler Runtime: java8 Description: Java function MemorySize: 512 Timeout: 10 # Function's execution role Policies: - AWSLambdaBasicExecutionRole - AWSLambdaReadOnlyAccess - AWSXrayWriteOnlyAccess - AWSLambdaVPCAccessExecutionRole Tracing: Active
To create the function, use the package
and deploy
commands. These commands are
customizations to the AWS CLI. They wrap other commands to upload the deployment package
to Amazon S3, rewrite the
template with the object URI, and update the function's code.
The following example script runs a Gradle build and uploads the deployment package that it creates. It creates an AWS CloudFormation stack the first time you run it. If the stack already exists, the script updates it.
Example deploy.sh
#!/bin/bash set -eo pipefail aws cloudformation package --template-file template.yml --s3-bucket MY_BUCKET --output-template-file out.yml aws cloudformation deploy --template-file out.yml --stack-name java-basic --capabilities CAPABILITY_NAMED_IAM
For a complete working example, see the following sample applications:
Sample Lambda applications in Java
-
blank-java
– A Java function that shows the use of Lambda's Java libraries, logging, environment variables, layers, AWS X-Ray tracing, unit tests, and the AWS SDK. -
java-basic
– A minimal Java function with unit tests and variable logging configuration. -
java-events
– A minimal Java function that uses the aws-lambda-java-events library with event types that don't require the AWS SDK as a dependency, such as Amazon API Gateway. -
java-events-v1sdk
– A Java function that uses the aws-lambda-java-events library with event types that require the AWS SDK as a dependency (Amazon Simple Storage Service (Amazon S3), Amazon DynamoDB, and Amazon Kinesis). -
s3-java
– A Java function that processes notification events from Amazon S3 and uses the Java Class Library (JCL) to create thumbnails from uploaded image files.


Investigating local performance of our version control software. This year's going out with a bang!
12/31/2009, 10:43:08 AM
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Investigating local performance of our version control software. This year's going out with a bang!
12/31/2009, 10:43:08 AM
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link


EVA (Enterprise Virtual Assistant) is a Machine Learning enabled
virtual assistant which can converse with humans and assist them in
their tasks in a smarter way. It can also automate repetitive tasks,
converse with enterprise applications, take decisions and can be a
one-stop-shop for all enterprise needs.


Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic.
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown printer took a galley of type and
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown
PHOTOGRAPHY
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown
EDITING
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever since the 1500s, when an unknown


Pancreatic Cancer Scotland was formed in 2010, and is the only Scottish charity dedicated solely to improving the outcome for patients diagnosed as having cancer of the pancreas and associated tumours. In 2011, pancreatic cancer attracted just 1% of research funding from the major funding bodies in the UK. Pancreatic Cancer Scotland aims to help to redress this funding anomaly by investing in projects that will provide information, advance research, and improve the standard of healthcare for patients with pancreatico-biliary cancer in Scotland.
Our objectives are to:
Our work is relevant to a number of cancers, including Pancreatic Ductal Adenocarcinoma (PDAC), which is the most common type of pancreatic cancer,
Cholangiocarcinoma (cancer of the bile duct), Ampullary Cancer (at the end of the bile duct), Duodenal Cancer (in the small intestine),
as well as Pancreatic Endocrine Tumours (rare forms of cancer in the pancreas).
Watch our video on World Pancreatic Cancer Day 2014


--- layout: post status: publish published: true title: 'Podcast #14 - 7/16/09' author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>wordpress_id: 1119 wordpress_url: http://ivyenvy.com/?p=1119 date: '2009-07-16 22:08:10 +0000' date_gmt: '2009-07-17 04:08:10 +0000' categories: - Podcast tags: - Podcast comments: [] ---
Andy and Corey evaluate the first half of the season and look ahead at the second half. We discuss the pleasant surprises and the disappointments thus far.


Saving the state of a Constellation graph for later retrieval can be done at any time. After saving a graph, the user may completely quit the application and resume where they left off at another time. Saving is also useful to guard against data loss in the event of a system crash.
The Constellation saves the graph to a proprietary format. A saved Constellation file retains the graph layout and selections, attribute definitions and their values, and just about everything else. The menu option below initiates an operation that records the contents of the window in a text file:
The "Save" command will prompt the user for a file name the first time the file is being saved. Otherwise, it will use the current name.
The "Save As" command can be used with new or existing graphs to explicitly save the information to a specific file.
When specifying a file name, the user will be asked to confirm the operation if the file already exists.
The application will not allow the user to specify an existing filename for another currently open graph.
The file generated by the save operations are assigned the .star suffix by default.
Note: When a file has changes pending, its name (in the upper tab) appear bolded in blue, otherwise it is shown in simple black text.


Language Translator
Translation Studies is a field of study that deals with the theory, description, and application of translation. Because it examines translation both as an interlingual transfer, and as an intercultural communication, Translation Studies can also be described as an inter-discipline which touches on other diverse fields of knowledge, including comparative literature, cultural studies, gender studies, computer science, history, linguistics, philosophy, rhetoric, and semiotics..Translation enables effective communication between people around the world. It is a courier for the transmission of knowledge, a protector of cultural heritage, and essential to the development of a global economy. Highly skilled translators are key. Translation Studies helps practitioners develop those skills.


Docker Images tracking the stable Galaxy releases
Table of content
We recommend to use the Main Galaxy Tool Shed for all your tools and workflows that you would like to share.
In rare situations where you cannot share your tools but still want to include them into your Galaxy Docker instance, please follow the next steps.
Mount your tool directory into the container with a separate -v /home/user/my_galaxy_tools/:/local_tools
.
tool_conf.xml
file for your tools.This should look similar to the main tool_conf.xml
file, but references your tools from the new directory. In other words a tool entry should look like this <tool file="/local_tools/application_foo/foo.xml" />
.
Your tool_conf.xml
should be available from inside of the container. We assume you have it stored under /local_tools/my_tools.xml
.
To make Galaxy aware of your new tool configuration file you need to add the path to tool_config_file
, which is by default #tool_config_file = config/tool_conf.xml,config/shed_tool_conf.xml
. You can do this during container start by setting the environment variable -e GALAXY_CONFIG_TOOL_CONFIG_FILE=config/tool_conf.xml.sample,config/shed_tool_conf.xml.sample,/local_tools/my_tools.xml
.


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Programing
Playing Destiny
Camping
Color: Blue
Animal: Liger (Look it up!)
Subject: Science
Make a game with animation
Have all a in school


This website is under construction.
Thank you!
by Tech-R|Technology for Human Rights & the University of Oslo.


Fultec businessman charged with laundering over $6 million ...
Jul 10, 2009. Cab driver and passenger shot on Allenby Street · House collapses and resident homeless · Safiyyah gets in the groove at Jaguar Paw .
http://edition.channel5belize.com/archives/1164
Treatment for Herniated or Bulging Discs
Constructing Identity: Loud Whispers, Lasting Echoes
Getting back into my groove February 21, 2009. Filed under: Uncategorized Safiyyah @ 8:38 pm. I haven't blogged in ages!! So much has happened
We've .
http://southafricanmuslimah.wordpress.com/page/2/
Authors - Aaila The Muslim Family Magazine
I am a wife to Mustapha and mother to three children, Safiyyah who is nearly 4 and Ibrahim-Hanif who has just turned 2 and my baby daughter Ameena who is .
http://aaila.org/authors/
safiyyah in the groove Herniated or Bulging Discs
Summer fun savings for kids - wave3.com-Louisville News, Weather ...
May 24, 2012 . You can pump up your dance groove with some of the area's best hip-hop choreographers. Safiyyah Rasool is one of the area's top instructors .
http://www.wave3.com/story/18619185/summer-fun-savings-for-kids
Former employee wins case against UB | Channel5Belize.com
Jul 10, 2009. Cab driver and passenger shot on Allenby Street · House collapses and resident homeless · Safiyyah gets in the groove at Jaguar Paw .
http://edition.channel5belize.com/archives/1159
safiyyah dance - YouTube
Nov 5, 2010 . Safiyyah dancing to Basement Jaxx "Scars"by safiyyahdance262 views · Groove Basics - Miguel Almario [ Boys and Girls ] 1:17. Watch Later .
http://www.youtube.com/watch?v=DiiPJpyp0FQ
Official Impairment Listing for Spinal Disorders
April - Shaalom 2 Salaam
Apr 1, 2010 . "Big deal, Safiyyah. . when the people started waltzing down my driveway, and the money started filling my coffers, I got right into the groove!
http://www.shaalom2salaam.com/2010_04_01_archive.html
- pull down safety shields (narrowing of the spine)
Learn some new moves at our HIP HOP DANCE CAMP July 16-20 ...
May 31, 2012 .  Safiyyah Rasool, one of the area's top .
http://blog.kentuckycenter.org/get_centered_the_kentucky/2012/05/learn-some-new-moves-at-our-hip-hop-dance-camp-july-16-20-taught-by-safiyyah-rasool.htmlWhat every mother should include in her hospital - Aaila The Muslim ...
Apr 6, 2012 . I am a wife to Mustapha and mother to three children, Safiyyah who is . Having Other Children · Getting your Groove Back Post-Pregnancy .
http://aaila.org/issue/september-october-2012/article/what-every-mother-should-include-in-her-hospital-bag
Anti-Muslim Bias or Good Old Fashioned Racism? | Jamerican ...
Feb 27, 2008 . (A poem/rant by me) · Takin' a break to groove to a old school tune! ? . Safiyyah | February 27, 2008 at 10:54 pm | Reply. Salaams Sis: .
http://jamericanmuslimah.wordpress.com/2008/02/27/anti-muslim-bias-or-good-old-fashioned-racism/
The Kentucky Center Blog: May 2012
May 31, 2012 .  Safiyyah Rasool, one of the area's top .
http://blog.kentuckycenter.org/get_centered_the_kentucky/2012/05/index.html
Medical-Vocational Allowance for Herniated Disc
Safiyyah Dance Freestyle - YouTube
Mar 30, 2011 . Like That Groove!? . Safiyyah Dance Company Grand Openingby . safiyyah dance "to whom it may concern"by safiyyahdance488 views .
http://www.youtube.com/watch?v=ly75Yqv8ZwA
Love, Lust, & Laughter
Karimah Safiyyah Aziz "There's an empty place in my bones that calls out for . I like how you think and the way you groove and even when you bite your lips .
http://highheels--highstandards.tumblr.com/
WHAS11.com | Louisville Breaking News Video - WHAS11.com
Hip hop dance classes at Safiyyah Danceadd to reading list . Angie moves and grooves with Jazzercise work-outadd to reading list .
http://www.whas11.com/great-day-live/video/fitness
Appealing a Denial of Benefits
Free Christmas Concert at Fourth Street Live | louisvillekyrealestate.co
6 days ago. in for, so picking the right rhythm is crucial to finding your groove. . The Safiyyah Dance is set to kick off at 7 p.m., and will be a blend of jazz .
http://www.louisvillekyrealestate.co/blog/free-christmas-concert-at-fourth-street-live/
ALMISKEENAH :: dates
Jul 29, 2007 . If they did they would not give away so much as the groove of a date . Safiyyah RadhiAllahu anha, daughter of Atiyyah RadhiAllahu anha, .
http://almiskeenah.blogsome.com/category/dates/


Visual data-driven proactive received power prediction via deep learning
Visual data-driven proactive handover management via deep reinforcement learning
Millimeter Wave on Overhead Messenger Wires (Collaborator: NTT Access Network Service Systems Laboratories)
Deep reinforcement learning-based predictive beam tracking
Zero-shot adaptation through robust adversarial reinforcement learning
Publications
Invited/Tutorial Talks
Y. Koda, "Over-the-Air Computation for Scalable, Lightweight, and Privacy Preserving Edge
Machine Learning," IEICE Society Conference 2021, BT-2, 分散協調機械学習 (Federated Learning) チュートリアル〜
IoTに向けたプライバシ保護と通信効率向上を目指して 〜
(URL for conference,
slides ).
Y. Koda, "Visual data-driven millimeter wave communication systems," Kyoto University,
Graduate School of Informatics, CCE colloquium（京都大学大学院情報学研究科通信情報システム専攻談話会）, Oct. 2021.
Journal Papers
Reviewed
S. Itahara, S. Kondo, K. Yamashita, K. Yamamoto, T. Nishio, and Y. Koda, "Beamforming
Feedback-based Model-Driven Angle of Departure Estimation Toward Legacy Support in WiFi Sensing: An
Experimental Study," IEEE access, vol. 10,
pp. 59737-59747, Jun. 2022.
.
T. Kanda, Y. Koda, K. Yamamoto, and T. Nishio, "ACK-Less Rate Adaptation Using
Distributional Reinforcement Learning for Reliable IEEE 802.11bc Broadcast WLANs," IEEE access, vol. 10,
pp. 58858-58868, Jun. 2022.
.
Y. Kihira, K. Yamamoto, A. Taya, T. Nishio, Y. Koda, and Y. Kazuto, “Shared information
reduction for tabular Q-learning-based coordinated spatial reuse for WLANs,” IEICE
Communications Express, accepted.
Y. Kihira, Y. Koda, and K. Yamamoto, "Adversarial reinforcement learning-based coordinated
robust spatial reuse in broadcast-overlaid WLANs," conditionally accepted to IEICE Transactions on
Communications.
S. Kondo, S. Itahara, K. Yamashita, K. Yamamoto, Y. Koda, T. Nishio, and A. Taya,
"Bi-directional Beamforming Feedback-based Firmware-agnostic WiFi Sensing," IEEE Access, vol. 10, pp.
36924-36934, Apr. 2022.
.
K. Yamashita, S. Kamiya, K. Yamamoto, Y. Koda, T. Nishio, and M. Morikura, “Penalized and
decentralized contextual bandit learning for WLAN channel allocation with contention-driven feature
extraction,” IEICE Transactions on Communications, vol. E105-B, no.10, Oct. 2022.
S. Itahara, T. Nishio, Y. Koda, and K. Yamamoto, "Communication-oriented model fine-tuning
for packet-loss resilient distributed inference under highly lossy IoT networks," IEEE Access, vol. 10,
pp. 14969-14979, Feb. 2022
.
M. Shinzaki, Y. Koda(corresponding author), K. Yamamoto, T. Nishio, M. Morikura, Y.
Shirato, U. Daisei, and N. Kita, “Zero-shot adaptation for mmWave beam-tracking on overhead messenger
wires through robust adversarial reinforcement learning,” IEEE Transactions on Cognitive Communications
and Networking, vol. 1, no. 8, pp. 232-245, Mar. 2022.
T. Nishio, Y. Koda, J. Park, M. Bennis, and K. Doppler, “When wireless communications meet
computer vision in beyond 5G,” IEEE Communications Standards Magazine, vol. 5, no. 2, pp. 76-83, Jun.
2021.
(One of popular documents in IEEE CSM in
Jul.
,
Aug.
,
Sep.
,
Oct.
,
Nov.
,
Dec.
2021
, and
Jan.
2022)
Y. Koda, M. Shinzaki, K. Yamamoto, T. Nishio, M. Morikura, Y. Shirato, U. Daisei, and N.
Kita, “Millimeter wave communications on overhead messenger wire: Deep reinforcement learning-based
predictive beam tracking,” IEEE Transactions on Cognitive Communications and Networking, vol. 7, no. 4,
pp. 1216-1232, Dec. 2021.
(One of popular documents in IEEE TCCN in Dec. 2021)
.
S. Itahara, T. Nishio, Y. Koda, M. Morikura, and K. Yamamoto, “Distillation-based
semi-supervised federated learning for communication-efficient collaborative training with non-IID private
data,” IEEE Transactions on Mobile Computing, accepted, DOI: 10.1109/TMC.2021.3070013.
(IEEE Xplore
,
Arxiv:
)
Y. Fu, K. Yamamoto, Y. Koda, T. Nishio, M. Morikura, C. Huang, Y. Shirato, and N. Kita,
“Stochastic geometry analysis of wireless backhaul networks with beamforming in roadside environments,”
IEICE Transactions on Communications, vol. E104-B, no. 1, pp. 118-127, Jan. 2021.
Y. Koda, J. Park, M. Bennis, K. Yamamoto, T. Nishio, M. Morikura, and K. Nakashima,
“Communication-efficient multimodal split learning for mmWave received power prediction,” IEEE
Communications Letters, vol. 24, no. 6, pp. 1284-1288, Jun. 2020.
(IEEE Xplore,
;
Arxiv preprint: )
Y. Koda, K. Nakashima, K. Yamamoto, T. Nishio and M. Morikura, “Handover management for
mmWave
networks with proactive performance prediction using camera images and deep reinforcement learning,” IEEE
Transactions on Cognitive Communications and Networking, vol. 6, no. 2, pp. 802-816, Jun. 2020.
,
(One of popular documents in IEEE TCCN in
Jun.
,
Jul.
,
Aug.
,
Sep.
,
Oct.
, and
Nov.
in 2020;
Feb.
,
Apr.
,
May
, and
Oct
,
in 2021)
T. Nishio, H. Okamoto, K. Nakashima, Y. Koda, K. Yamamoto, M. Morikura, Y. Asai, and R.
Miyatake,
“Proactive received power prediction using machine learning and depth images for mmWave networks,” IEEE
Journal on Selected Areas in Communications, vol. 37, no. 11, pp. 2413-2427, Nov. 2019.
(One of popular documents in IEEE JSAC in
Nov. 2019.)
Y. Koda, K. Yamamoto, T. Nishio and M. Morikura, “Measurement method of temporal
attenuation by
human body in off-the-thelf 60GHz WLAN with HMM-based transmission state estimation,” Wireless
Communications and Mobile Computing, vol. 2018, atricle ID 7846936, pp. 1-9, Apr. 2018,
doi:10.1155/2018/7846936.
Preprints under submission
T. AlShammari, Y. Koda, A. Elgabli, S. Samarakoon, and M. Bennis, "BayGO: Joint Bayesian
federated learning and information-aware graph optimization framework," (Submitted to IEEE Journal on
Selected Areas in Information Theory).
T. Sunami, S. Itahara, Y. Koda, T. Nishio, and K. Yamamoto, "Computer vision-assisted
decimeter-level single-antenna RSSI localization harnessing dynamic blockage events," (Submitted to IEEE
IoT Journal).
International Conference (reviewed)
Reviewed
T. Kanda, Y. Koda, K. Yamamoto, and T. Nishio, “ACK-less rate adaptation for IEEE 802.11bc
enhanced broadcast services using sim-to-real deep reinforcement learning
,” in Proc. IEEE CCNC 2022, held online, Jan. 2022.
R. Hanahara, K. Yamashita, S. Itahara, Y. Koda, A. Taya, T. Nishio, and K. Yamamoto,
“Frame-capture-based CSI recomposition pertaining to firmware-agnostic WiFi sensing,” in Proc. IEEE CCNC
2022, held online, Jan. 2022.
Y. Koda, J. Park, M. Bennis, P. Vepakomma, and R. Raskar, “AirMixML: Over-the-air data mixup
for inherently privacy-preserving edge machine learning,” in Proc. IEEE GLOBECOM 2021, Spain, Madrid, Dec.
2021, pp.1-6.
Y. Koda, K. Yamamoto, T. Nishio, and M. Morikura, “Differentially private airComp
federated
learning with power adaptation harnessing receiver noise,” in Proc. IEEE GLOBECOM 2020, Taipei, Taiwan,
Dec. 2020, pp.1-6.
M. Shinzaki, Y. Koda, K. Yamamoto, T. Nishio, M. Morikura, C. H. Huang, Y. Shirato, and N.
Kita,
“Deep reinforcement learning-based beam tracking from mmWave antennas installed on overhead messenger
wires,” in Proc. IEEE VTC2020-fall, Victoria, Canada, Oct. 2020, pp. 1-5.
Y. Kihira, Y. Koda, K. Yamamoto, T. Nishio, and M. Morikura, “Adversarial reinforcement
learning-based robust access point coordination against uncoordinated interference,” in Proc. IEEE
VTC2020-fall, Victoria, Canada, Oct. 2020, pp. 1-5. (IEEE Xplore:
Y. Koda, K. Nakashima, K. Yamamoto, T. Nishio, and M. Morikura, “Cooperative sensing in
deep
RL-based
image-to-decision proactive handover for mmWave networks,” in Proc. IEEE CCNC, Las Vegas, USA,
Jan. 2020.
M. Shinzaki, Y. Koda, K. Yamamoto, T. Nishio, and M. Morikura, “Reducing transmission
delay in
EDCA using policy gradient reinforcement learning,” in Proc. IEEE CCNC, Las Vegas, USA,
Jan. 2020.
Y. Koda, J. Park, M. Bennis, K. Yamamoto, T. Nishio, and M. Morikura, “One pixel image and
RF
signal based split learning for mmWave
received power prediction,” in Proc. ACM CoNEXT2019 poster, Orlando, FL, USA, Dec. 2019.
K. Nakashima, Y. Koda, K. Yamamoto, H. Okamoto, T. Nishio, and M. Morikura, Y. Asai and R.
Miyatake, “Impact of input data size on received power prediction using depth images for mmWave
communications,” in Proc. IEEE VTC2018-Fall, Chicago, USA, Aug. 2018.
Y. Koda, K. Yamamoto, T. Nishio, and M. Morikura, “Reinforcement learning based predictive
handover for pedestrian-aware mmWave networks,” in Proc. IEEE INFOCOM Workshops, Waikiki, USA, Apr. 2018.
(One of popular documents in IEEE INFOCOM Wksps in
Feb.
and
Mar.
2020.)
Y. Koda, K. Yamamoto, T. Nishio, and M. Morikura, “Time series measurement of IEEE
802.11ad
signal power involving human blockage with HMM-based state estimation,” in Proc. IEEE VTC2017-Fall,
Toronto, Canada, Sep. 2017.
Y. Koda, Y. Oguma, T. Nishio, K. Yamamoto and M. Morikura, “Statistical prediction of
human
blockage for camera-assisted mmWave communications,” in Proc. IEEE APWCS 2016, Tokyo, Japan, Aug. 2016.
Preprints
H. Shimomura, Y. Koda, T. Kanda, K. Yamamoto, T. Nishio, and A. Taya, “Vision-Aided
Frame-Capture-Based CSI Recomposition for WiFi Sensing:
A Multimodal Approach”
Ph.D. Dissertation
Yusuke Koda, "Visual data-driven millimeter wave communication
systems," Mar. 2021.
Misc (not reviewed)
Takanori Hara, Hiroki Iwata, Hiroshi Katada, Yusuke Koda, “Young researchers'
participation
report for the 2019 cross-field research association of super-intelligent
networking (RISING 2019) ,” IEICE Communications Society GLOBAL NEWSLETTER, Vol. 44, No. 1, pp. 12-13,
Mar. 2020.
Awards and Grants
Awards
For me
Outstanding Paper Award for Young C&C Researchers, 2021.
（2021年度C&C若手優秀論文賞）
The Telecommunications Advancement Foundation, The 36th Telecom System Students Award, 2020.
（第36回電気通信普及財団賞 テレコムシステム技術学生賞）
The Institute of Electronics, Information and Communication Engineers, Young Researcher's Encouragement
Award.
（第83回 電子情報通信学会学術奨励賞）
IEEE Kansai Chapter Student Research Encouragement Award.
（第17回 IEEE関西支部学生研究奨励賞）
The Telecommunications Advancement Foundation, The 35th Telecom System Award, 2019.
（第35回電気通信普及財団賞 テレコムシステム技術賞）
Cross-field Research Association of Super-Intelligent Networking (RISING 2019), Best Poster Presentation
Award.
（超知性ネットワーキングに関する分野横断型研究会 優秀ポスター発表賞）
IEEE VTS Tokyo Chapter 2017 Young Researcher’s Encouragement Award.
（IEEE VTS Tokyo Chapter 学生奨励賞 2017）
For co-authors
The Telecommunications Advancement Foundation, The 37th Telecom System Students Award, 2021 to Sohei
Itahara.
（第37回電気通信普及財団賞 テレコムシステム技術学生賞、板原壮平）
IEEE Kansai Chapter Student Research Encouragement Award, to Sohei Itahara.
（第18回 IEEE関西支部学生研究奨励賞、板原壮平）
IEEE VTS Tokyo Chapter 2020 Young Researcher's Encouragement Award, to Masao Shinzaki.
（IEEE VTS Tokyo Chapter 学生奨励賞 2020、新﨑聖峰）
IEEE VTS Tokyo Chapter 2020 Young Researcher's Encouragement Award, to Yuto Kihira.
（IEEE VTS Tokyo Chapter 学生奨励賞 2020、紀平悠人）
IEEE VTS Tokyo Chapter 2018 Young Researcher's Encouragement Award, to Kota Nakashima.
（IEEE VTS Tokyo Chapter 学生奨励賞 2018、中島功太）
Grants
Japan society for the promotion of science (JSPS), Overseas Research Fellowship, accepted (JPY
6200000/year for 2 years).
（日本学術振興会 海外特別研究員 採用内定 620万円/年 2年）
C&C public interest incorporated foundation, International conference travel grant (JPY 64000).
（公益財団法人NEC C&C財団 国際会議論文発表者助成 6万4千円）
Nokia Foundation Centennial Scholarship (€6 000).
Research project titled as “Camera-assisted Framework for
Reliable, Decentralized, and Ultra-Dense Millimeter Wave Networks,” Jun. 2019
.
Kyoto University, Graduate School of Informatics, Ph.D. student encouragement project for traveling
overseas (JPY 500000).
（京都大学大学院情報学研究科博士後期過程に対する支援事業 海外渡航支援、50万円）
Japan Student Services Organization (JASSO) Scholorship, Exemption from Refund (JPY 500000).
日本学生支援機構第一種奨学金返還免除（50万円）
Academic Activities
Program Committee Member
IEEE VTC2022-spring, Track10: Signal processing for wireless communications


| Home | Libraries | People | FAQ | More |
The containers are made up of a number of 'buckets', each of
which can contain any number of elements. For example, the following
diagram shows an unordered_set
with 7 buckets containing 5 elements, A
, B
,
C
,
D
and E
(this is just
for illustration, containers will typically have more buckets).
这些容器由多个'桶'组成，每个桶可以包含任意数量的元素。例如，下图示范了一个有7个桶、包含5个元素 A
,
B
,
C
,
D
和 E
的 unordered_set
&
nbsp;(这只是用于示例的，通常的容器会有很多桶)。
In order to decide which bucket to place an element in, the
container applies the hash function, Hash
, to the
element's key (for unordered_set
and unordered_multiset
the key is the whole element, but is referred to as the key so that the
same terminology can be used for sets and maps). This returns a value
of type std::size_t
. std::size_t
has a much greater range of values then the number of buckets, so that
container applies another transformation to that value to choose a
bucket to place the element in.
为了确定将一个元素放在哪个桶中，容器要将散列函数 Hash
用于元素的键值(对于
unordered_set
和 unordered_multiset
，
键即为整个元素本身，不过我们还是称之为键，与 sets 和 maps 中所使用的术语保持一致)。函数返回一个类型为 std::size_t
的值。std::size_t
拥有比桶的数量更大的值范围，所以容器要对这个值应用另一次转换，以选择某一个桶来存放元素。
Retrieving the elements for a given key is simple. The same
process is applied to the key to find the correct bucket. Then the key
is compared with the elements in the bucket to find any elements that
match (using the equality predicate Pred
). If the
hash function has worked well the elements will be evenly distributed
amongst the buckets so only a small number of elements will need to be
examined.
根据一个给定键值取回元素也很简单。对该键值应用相同的过程，找到正确的桶。然后将键值与桶中的各个元素进行比较，(使用等同性谓词 Pred
)
找到匹配的元素。如果散列函数工作的好的话，各元素将均匀分布在各个桶中，则只需要测试少量的元素。
There is more
information on hash functions and equality predicates in the next
section.
在下一节中，有 更多的关于散列函数和等同性谓
词的信息。
You can see in the diagram that A
& D
have been
placed in the same bucket. When looking for elements in this bucket up
to 2 comparisons are made, making the search slower. This is known as a
collision. To keep things fast we try to keep collisions to a minimum.
从图中你可以看到，A
和 D
被置于同一个桶中。在这个桶中查找元素需要最多2次的比较，这使得查找减慢。这一情况被称为冲突。要使得查找更快，我们就要将冲突保持在最小。
Table 25.1. Methods
for Accessing Buckets
表 25.1. 桶的访问方法
|
Method 方法 |
Description 说明 |
|---|---|
size_type bucket_count() const |
The number of buckets. 桶的数量。 |
size_type max_bucket_count() const |
An upper bound on the number of buckets. 桶数量的上限。 |
size_type bucket_size(size_type
n) const |
The number of elements in bucket n .桶 n
中的元素数量。 |
size_type bucket(key_type
const& k)
const |
Returns the index of the bucket which would contain k 返回包含 k 的桶的索引。 |
local_iterator begin(size_type n); |
Return begin and end iterators for
bucket n .返回桶 n 的 begin 和 end
迭代器。 |
local_iterator end(size_type n); |
|
const_local_iterator begin(size_type n)
const; |
|
const_local_iterator end(size_type n)
const; |
|
const_local_iterator cbegin(size_type
n) const; |
|
const_local_iterator cend(size_type n)
const; |
As more elements are added to an unordered associative
container, the number of elements in the buckets will increase causing
performance to degrade. To combat this the containers increase the
bucket count as elements are inserted. You can also tell the container
to change the bucket count (if required) by calling rehash
.
当越来越多的元素被加入到无序关联式容器中时，各桶中元素数量的上升会导致性能下降。为防止性能的下降，容器要在元素插入时增加桶的数量。你也可以通过调
用 rehash
来告诉容器(在需要时)改变桶的数量。
The standard leaves a lot of freedom to the implementer to
decide how the number of buckets are chosen, but it does make some
requirements based on the container's 'load factor', the average number
of elements per bucket. Containers also have a 'maximum load factor'
which they should try to keep the load factor below.
标准留给实现者很大的自由度来决定桶的数量，不过也有基于容器的'负载因子'的一些要求，'负载因子'即每个桶中元素的平均数量。容器还有一个'最大负载
因子'，容器会尝试将负载因子保持在'最大因子'之下。
You can't control the bucket count directly but there are two
ways to influence it:
你不能直接控制桶的数量，但是有两个方法来影响它：
rehash
.rehash
时指定一个最小桶数。 max_load_factor
.max_load_factor
建议一个最大负载因子。
And even then, the draft standard doesn't actually require the
container to pay much attention to this value. The only time the load
factor is required
to be less than the maximum is following a call to rehash
.
But most implementations will try to keep the number of elements below
the max load factor, and set the maximum load factor to be the same as
or close to the hint - unless your hint is unreasonably small or large.
max_load_factor
并不是让你直接设定最大负载因子，它只是让你给定一个 hint
提示。尽管如此，标准草案并不真正要求容器必须关注这个值。只是在调用 rehash
后才要求负载因子必须小于最大值。不过大多数实现都努力将元素数量保持在最大负载因子之下，并设置最大负载因子必须与提示值相同或相近 -
除非你的提示值不合理地过小或过大。
Table 25.2. Methods
for Controlling Bucket Size
表 25.2. 控制桶大小的方法
|
Method 方法 |
Description 说明 |
|---|---|
|
|
Construct an empty container with at least |
|
|
Construct an empty container with at least 构造一个空容器，带有至少 |
|
|
The average number of elements per bucket. |
|
|
Returns the current maximum load factor. |
|
|
Changes the container's maximum load factor, using |
|
|
Changes the number of buckets so that there at least n
buckets, and so that the load factor is less than the maximum load
factor. |
It is not specified how member functions other than rehash
affect the bucket count, although insert
is only
allowed to invalidate iterators when the insertion causes the load
factor to be greater than or equal to the maximum load factor. For most
implementations this means that insert will only change the number of
buckets when this happens. While iterators can be invalidated by calls
to insert
and rehash
,
pointers and references to the container's elements are never
invalidated.
除了 rehash
以外，其它成员函数如何影响桶的数量并没有规定，insert
操作仅当插入导致负载因子大于或等于最大负载因子时允许使得迭代器失效。对于多数实现来说，这意味着只有当此事发生时，插入操作才会改变桶的数量。因此，
迭代器只会在调用 insert
和 rehash
时才可能失效，而指向容器中的元素的指针和引用则永不失效。
In a similar manner to using reserve
for vector
s,
it can be a good idea to call rehash
before
inserting a large number of elements. This will get the expensive
rehashing out of the way and let you store iterators, safe in the
knowledge that they won't be invalidated. If you are inserting n
elements into container x
, you could
first call:
和对 vector
s 使用 reserve
一样，在往无序关联式容器中插入大量元素之前，最好先调用 rehash
。这样可以养活不必要
的代价昂贵的重散列，让你可以保存迭代器，并确知它们不会失效。如果你要往容器 x
中插入 n
个元素，你可以先调用：
x.rehash((x.size() + n) / x.max_load_factor() + 1);


Developer documentation¶
This page provides an introduction into the internal workings of Devito and is aimed at new developers and people who want to contribute to the project. We will give a brief glimpse under the hood to provide some context for the various design and implementation choices.
If you are only interested in learning how to use Devito, please start with the tutorials and examples.
Please note that this page is currently still under ongoing development.


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- GameArena - Class in <Unnamed>
-
This class provides a simple window in which grahical objects can be drawn.
- GameArena(int, int) - Constructor for class GameArena
-
Constructor.
- getArenaHeight() - Method in class GameArena
-
Gets the height of the GameArena window, in pixels.
- getArenaWidth() - Method in class GameArena
-
Gets the width of the GameArena window, in pixels.
- getColour() - Method in class Ball
-
Obtains the colour of this Ball.
- getColour() - Method in class Rectangle
-
Obtains the colour of this Rectangle.
- getHeight() - Method in class Rectangle
-
Obtains the height of this Rectangle.
- getSize() - Method in class Ball
-
Obtains the size of this Ball.
- getSM() - Static method in class Cresent
-
- getSM() - Static method in class Moon
-
- getSpeed() - Method in class Fence
-
- getSpeed() - Method in class IntArena
-
Returns the speed of the movement of the specific instance of the Ball class.
- getSpeed() - Method in class Sun
-
- getWidth() - Method in class Rectangle
-
Obtains the width of this Rectangle.
- getXPosition() - Method in class Ball
-
Obtains the current position of this Ball.
- getXPosition() - Method in class Rectangle
-
Obtains the current position of this Rectangle.
- getXPosition() - Method in class Sheep
-
- getYPosition() - Method in class Ball
-
Obtains the current position of this Ball.
- getYPosition() - Method in class Rectangle
-
Obtains the current position of this Rectangle.
- getYPosition() - Method in class Sheep
-
- grass - Static variable in class Driver
-


--- layout: post status: publish published: true title: Ruby Features You'll Wish You Had In Other Languages author: display_name: Geoff Lane login: admin email<EMAIL_ADDRESS>url: http://www.zorched.net author_login: admin author_email<EMAIL_ADDRESS>author_url: http://www.zorched.net date: '2006-02-19 20:51:00 -0500' date_gmt: '2006-02-20 02:51:00 -0500' categories: - Code - Ruby tags: [] ---
Three Ruby related posts in a row! Yes, I'm currently enamored with this colorful little language.
If you know people that know (or you yourself know) languages like Smalltalk and Lisp, you'll often hear them curse when they use other languages. Something like "Damn, I could do this so much easier in Smalltalk. To do x would only take me 2 lines of code!". This is the best reason NOT to learn Ruby. Every time you program in other languages you'll think of all the little tricks you wish you could use from Ruby. I figured I'd share the pain (or at least what I think are some of the cool features).
Does an Array contain a specific item?: {% highlight ruby %} me = people.find { |p| p.first_name == 'Geoff' } {% endhighlight %}
Find all of elements matching the condition: {% highlight ruby %} myfamily = people.select { |p| p.last_name == 'Lane' } {% endhighlight %}
Create a new array with the results of running the block on each element (uniq then removes duplicates): {% highlight ruby %} all_families = people.collect { |p| p. last_name }.uniq {% endhighlight %}
All of that stuff without writing a single Iterator or for loop!
Blocks can be stored as a variable to call later and can be passed as an argument to a method. This can give you built-in support for light-weight version of patterns like the Strategy Pattern or the Observer Pattern.
An Observer for example: {% highlight ruby %} class Subject def initialize @blocks = [] @state = nil end def attach(&block) @blocks < < block end def state=(v) @state = v notify end private def notify @blocks.each { |b| b.call(@state) } end end
class Observer def called puts "Observer called." end end
class Observer2 def called(state) puts "Observer2 was called with '#{state}'." end end
o = Observer.new o2 = Observer2.new s = Subject.new s.attach { o.called } s.attach { |s| o2.called(s) } s.state = 'Hi' {% endhighlight %}
Gives us:
Observer called. Observer2 was called with 'Hi'.
A Strategy Example: {% highlight ruby %} class Mathify def initialize(x, y, &block) @x = x @y = y @block = block end
def call @block.call(@x, @y) end end {% endhighlight %}
{% highlight ruby %} add = proc {|a, b| a + b} mult = proc {|a, b| a * b} m = Mathify.new(2, 3, &add) n = Mathify.new(2, 3, &mult) puts m.call puts n.call {% endhighlight %}
Built-in examples: {% highlight ruby %} class Person attr_accessor :first_name, :last_name attr_reader :person_id alias :last_name, :family_name end {% endhighlight %}
attr_accessor
and attr_reader
dynamically create accessors for your
class. alias
creates another name that
can be used to access the same attribute.
Ruby has a lot of built-in support for this kind of functionality, but it also allows you to add your own as well: {% highlight ruby %} class Module def log_call(method, *args) old_method = instance_method(method) define_method(method) do |*args| puts "Calling '#{method}'." old_method.bind(self).call(*args) end end end
class MyClass def call_me puts "I've been called." end def call_me_too puts "I've been called too." end log_call :call_me_too end
mc = MyClass.new mc.call_me mc.call_me_too {% endhighlight %}
Prints:
I've been called. Calling 'call_me_too'. I've been called too.
As you see, I've 'decorated' one of the method calls with some new functionality. Basically, I'm dynamically redefining the method to log the call prior to passing along the call to the original implementation. You could intercept calls to set a 'dirty' flag to know that an instance had been changed so that you could do automatic caching.
{% highlight ruby %} class Array def first_half slice(0, size/2) end end a = [1, 2, 3, 4, 5, 6] puts a.to_s puts a.first_half.to_s {% endhighlight %}
Prints:
123456 123
So, if you have special needs to deal with built-in Classes or even just Classes from libraries that you are using, you can put the methods with the Classes where they rightly belong.
When you include
a Module into a Class, it 'mixes in' its
properties and methods into the Class. This is widely used in the core Ruby
classes. Enumerable
is used to implement a whole
suite of features for interacting with lists of objects. Array and Hash both
include Enumerable
to give them the implementation and interface
of this code. You can use Enumerable
in your own code of course,
and as with all the other features I've talked about, you can create your own
as well.
class Silly include Example end
s = Silly.new s.contrived {% endhighlight %}
Prints:
This is contrived.
Those are some of my favorite features of Ruby, but you really should ignore them. If not, when you have to programming in Java or .NET you'll be one of those people saying "Damn, I could do this so much easier in Ruby. To do x would only take me 2 lines of code!"


Publications authored in AI/ML-related areas.
Estimated citations uses a statistical model that leverages both local statistics of the publication and global statistics of the entire academic graph (from MAG).


NIF Objects | Compound Types | Enum Types | Basic Types | File Versions
| Name | Type | Arg | Arr1 | Arr2 | Cond | Description | From | To |
|---|---|---|---|---|---|---|---|---|
| From NiObject | ||||||||
| From bhkRefObject | ||||||||
| From bhkSerializable | ||||||||
| From bhkShape | ||||||||
| From bhkBvTreeShape | ||||||||
| From bhkMoppBvTreeShape | ||||||||
| Shape | Ref<bhkShape> | The shape. | ||||||
| Material | HavokMaterial | The shape's material. | ||||||
| Skyrim Material | SkyrimHavokMaterial | The shape's material. | ||||||
| Unknown 8 Bytes | byte | 8 | Unknown bytes. | |||||
| Unknown Float | float | Unknown float, might be scale. | ||||||
| MOPP Data Size | uint | Number of bytes for MOPP data. | ||||||
| Origin | Vector3 | Origin of the object in mopp coordinates. This is the minimum of all vertices in the packed shape along each axis, minus 0.1. | ||||||
| Scale | float | The scaling factor to quantize the MOPP: the quantization factor is equal to 256*256 divided by this number. In Oblivion files, scale is taken equal to 256*256*254 / (size + 0.2) where size is the largest dimension of the bounding box of the packed shape. | ||||||
| Old MOPP Data | byte | MOPP Data Size | The tree of bounding volume data (old style, contains more than just the mopp script). | <IP_ADDRESS> | ||||
| MOPP Data | byte | MOPP Data Size | The tree of bounding volume data. | <IP_ADDRESS> | ||||
| Unknown Byte 1 | byte | Unknown | <IP_ADDRESS> |


| Package | Description |
|---|---|
| org.drip.dynamics.hjm |
HJM Based Latent State Evolution
|
| org.drip.dynamics.hullwhite |
Hull White Latent State Evolution
|
| org.drip.dynamics.sabr |
SABR Based Latent State Evolution
|
| org.drip.sequence.random |
Correlated Multi-Factor Sequence Generator
|
| Modifier and Type | Method and Description |
|---|---|
UnivariateSequenceGenerator[] |
G2PlusPlus.rsg()
Retrieve the Random Sequence Generator Array
|
| Constructor and Description |
|---|
G2PlusPlus(double dblSigma,
double dblA,
double dblEta,
double dblB,
UnivariateSequenceGenerator[] aRSG,
double dblRho,
R1ToR1 auIFRInitial)
G2PlusPlus Constructor
|
| Modifier and Type | Method and Description |
|---|---|
UnivariateSequenceGenerator |
SingleFactorStateEvolver.rsg()
Retrieve the Random Sequence Generator
|
| Constructor and Description |
|---|
SingleFactorStateEvolver(FundingLabel lslFunding,
double dblSigma,
double dblA,
R1ToR1 auIFRInitial,
UnivariateSequenceGenerator usg)
SingleFactorStateEvolver Constructor
|
| Modifier and Type | Method and Description |
|---|---|
UnivariateSequenceGenerator |
StochasticVolatilityStateEvolver.usgForwardRate()
The Forward Rate Univariate Random Variable Generator Sequence
|
UnivariateSequenceGenerator |
StochasticVolatilityStateEvolver.usgForwardRateVolatilityIdiosyncratic()
The Idiosyncratic Component of Forward Rate Volatility Univariate Random Variable Generator Sequence
|
| Modifier and Type | Method and Description |
|---|---|
static StochasticVolatilityStateEvolver |
StochasticVolatilityStateEvolver.CEV(ForwardLabel lslForward,
double dblBeta,
double dblRho,
UnivariateSequenceGenerator usgForwardRate,
UnivariateSequenceGenerator usgForwardRateVolatilityIdiosyncratic)
Create a Constant Elasticity of Variance SABR Instance
|
static StochasticVolatilityStateEvolver |
StochasticVolatilityStateEvolver.Gaussian(ForwardLabel lslForward,
double dblRho,
double dblVolatilityOfVolatility,
UnivariateSequenceGenerator usgForwardRate,
UnivariateSequenceGenerator usgForwardRateVolatilityIdiosyncratic)
Create a Gaussian SABR Instance
|
static StochasticVolatilityStateEvolver |
StochasticVolatilityStateEvolver.Lognormal(ForwardLabel lslForward,
double dblRho,
double dblVolatilityOfVolatility,
UnivariateSequenceGenerator usgForwardRate,
UnivariateSequenceGenerator usgForwardRateVolatilityIdiosyncratic)
Create a Log-normal SABR Instance
|
| Constructor and Description |
|---|
StochasticVolatilityStateEvolver(ForwardLabel lslForward,
double dblBeta,
double dblRho,
double dblVolatilityOfVolatility,
UnivariateSequenceGenerator usgForwardRate,
UnivariateSequenceGenerator usgForwardRateVolatilityIdiosyncratic)
StochasticVolatilityStateEvolver Constructor
|
| Modifier and Type | Class and Description |
|---|---|
class |
Binary
Binary implements the Standard {0, 1}-valued Binary Random Number Generator.
|
class |
Bounded
Bounded implements the Bounded Random Univariate Generator with a Lower and an upper Bound.
|
class |
BoundedGaussian
BoundedGaussian implements the Bounded Gaussian Distribution, with a Gaussian Distribution between a lower
and an upper Bound.
|
class |
BoundedUniform
BoundedUniform implements the Bounded Uniform Distribution, with a Uniform Distribution between a lower
and an upper Bound.
|
class |
BoundedUniformInteger
BoundedUniformInteger implements the Bounded Uniform Distribution, with a Uniform Integer being generated
between a lower and an upper Bound.
|
class |
BoxMullerGaussian
BoxMullerGaussian implements the Univariate Gaussian Random Number Generator.
|
class |
Poisson
Poisson implements the Poisson Random Number Generator.
|
| Modifier and Type | Method and Description |
|---|---|
UnivariateSequenceGenerator[] |
MultivariateSequenceGenerator.usg()
Retrieve the Array of Univariate Sequence Generators
|
| Constructor and Description |
|---|
MultivariateSequenceGenerator(UnivariateSequenceGenerator[] aUSG,
double[][] aadblCorrelation)
MultivariateSequenceGenerator Constructor
|
PrincipalFactorSequenceGenerator(UnivariateSequenceGenerator[] aUSG,
double[][] aadblCorrelation,
int iNumFactor)
PrincipalFactorSequenceGenerator Constructor
|


This Agreement was last modified on September 09, 2013.
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Search Query Guide
Known Operators
- Operator AND
Default implicit operator. Matches when both of its two arguments match.
Example : java and python
- Operator OR
Matches when any of its two arguments match.
Example: java or python
- Operator NOT
Matches when the first argument matches, but the second one does not.
Example: java not python
- Grouping operator (parentheses)
The content within parentheses will have highest priority evaluation.
Example: ( java or c++ ) and python
- Phrase operator
Matches when argument keywords match as an exact phrase.
Example: " Multithreaded Programming "
Note- For auto suggestion to work properly, please provide space after any occurence of parentheses or quotes.


We should forget about small efficiencies, say about 97% of the time: premature optimization
is the root of all evil
- Compiler is already making a lot of optimizations, check it
- Use + operator for string concat unless it is a loop, otherwise use StringBuilder. Compiler convert it to StringBuilder already
weblogs


Interface ISudokuRule
Enforces a rule for a puzzle, such as "all values must be unique within a row." This is done by tracking possible values for each square specifically as determined by this rule. These possible values are then enforced along with any other rules by an ISudokuRuleKeeper.
Namespace: SudokuSpice.Rules
Assembly: SudokuSpice.dll
Syntax
public interface ISudokuRule
Methods
| Improve this Doc View SourceCopyWithNewReference(IReadOnlyPuzzle)
Creates a deep copy of this ISudokuRule, with any internal IReadOnlyPuzzle
references updated to the given puzzle.
Declaration
ISudokuRule CopyWithNewReference(IReadOnlyPuzzle puzzle)
Parameters
| Type | Name | Description |
|---|---|---|
| IReadOnlyPuzzle | puzzle | The new puzzle reference to use. To ensure this rule's internal state is correct, this puzzle should contain the same data as the current puzzle referenced by this rule. |
Returns
| Type | Description |
|---|---|
| ISudokuRule |
GetPossibleValues(Coordinate)
Gets the possible values for the given coordinate based on this rule.
Declaration
BitVector GetPossibleValues(in Coordinate c)
Parameters
| Type | Name | Description |
|---|---|---|
| Coordinate | c |
Returns
| Type | Description |
|---|---|
| BitVector | The possible values represented as a BitVector. |
Remarks
When implementing this method, avoid depending on dynamic information in the current puzzle being solved, such as the currently set values. This method must return information that reflects the most recent calls to Update(Coordinate, Int32, CoordinateTracker) or Revert(Coordinate, Int32, CoordinateTracker), as it can be called before or after modifying the underlying puzzle's data.
Revert(Coordinate, Int32)
Undoes an update for the given value at the specified coordinate.
This performs the same internal updates as Revert(Coordinate, Int32, CoordinateTracker), but without passing affected coordinates back to the caller. Therefore this is more efficient in cases where the caller already knows all the possible coordinates that could be affected.
Declaration
void Revert(in Coordinate c, int val)
Parameters
| Type | Name | Description |
|---|---|---|
| Coordinate | c | The coordinate where a value is being unset. |
| System.Int32 | val | The value being unset. |
Remarks
This method will always be called before reverting the value on the underlying puzzle.
Revert(Coordinate, Int32, CoordinateTracker)
Undoes an update for the given value at the specified coordinate. Tracks affected coordinates in the given tracker.
Declaration
void Revert(in Coordinate c, int val, CoordinateTracker coordTracker)
Parameters
| Type | Name | Description |
|---|---|---|
| Coordinate | c | The coordinate where a value is being unset. |
| System.Int32 | val | The value being unset. |
| CoordinateTracker | coordTracker | The coordinates of unset squares impacted by this change will be tracked in this tracker. |
Remarks
This method will always be called before reverting the value on the underlying puzzle.
Update(Coordinate, Int32, CoordinateTracker)
Updates possible values based on setting the given coordinate to the given value. Tracks affected coordinates in the given tracker.
Declaration
void Update(in Coordinate c, int val, CoordinateTracker coordTracker)
Parameters
| Type | Name | Description |
|---|---|---|
| Coordinate | c | The coordinate to update. |
| System.Int32 | val | The value to set |
| CoordinateTracker | coordTracker | The coordinates of unset squares impacted by this change will be tracked in this tracker. |
Remarks
This method will always be called before setting the value on the underlying puzzle.


Data Available
Backtesting mode
GDAX trades and quotes are currently available from 20150615 to the present. We have added the trade and quote data
for all historical pairs BTCUSD, BTCLTC, BTCETH, LTCUSD, LTCBTC, LTCETH, ETHUSD, ETHLTC and ETHBTC.
Live mode
GDAX offers live quote and trade data for BTCUSD, BTCLTC, BTCETH, LTCUSD, LTCBTC, LTCETH, ETHUSD, ETHLTC and ETHBTC data.
Selecting Data
Subscribe to cryptocurrency data:
AddCrypto(string pair, Resolution resolution = Resolution.Minute)
The default market for crypto is assumed to be GDAX. To change the market, specify the market name in the AddCrypto
command. For example, to subscribe to hourly resolution, BTCUSD, Bitfinex data in your algorithm, use the following method:
AddCrypto("BTCUSD", Resolution.Hour, Market.Bitfinex)
Accessing data
Quotes can be accessed in the Slice or TradeBars object in OnData event handler:
var bar = data["BTCUSD"];
var forex = Securities["BTCUSD"];
Live Trading
CryptoCurrency live trading is available through the GDAX brokerage. In order to live trade with GDAX, QuantConnect users must sign up for a GDAX account here: https://gdax.com. After obtaining an account, the next step is to create a GDAX api token. Sign into your GDAX account and click 'API' from the menu in the upper right. On the API page, users should select the 'View' and 'Trade' permissions. Click 'Create API key' on the bottom of the page. Be sure to record the api key, api passphrase and api secret.
Return to QuantConnect.com and go to the algorithm that you want to trade live. Select, 'Go Live' from the upper right hand corner. Follow the 'Live' wizard and select 'Gdax' as your brokerage. Be sure to copy your api key, api secret and api passcode correctly in the wizard.
Once potential stumbling block that users face deploying their algorithms live with GDAX is misunderstanding what type of account they have with GDAX. Typically, when users first open their account with GDAX, they are given a Cash account. In other words, margin trading is not available. However, margin accounts are the default account type specified in QCAlgorithm. Therefore, when users try to place trades using methods like SetHoldings()
they will get errors that crash their algorithm. Be sure to set your account type using the SetBrokerage()
method.
For example, to specify a Cash account, place the following above any data subscriptions.
SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash)
// In Initialize
AddCrypto("BTCUSD", Resolution.Minute);
# In Initialize
self.AddCrypto("BTCUSD", Resolution.Minute)
// In OnData(Slice data) or OnData(QuoteBars data)
var bar = data["BTCUSD"];
// Anywhere in the code
var crypto = Securities["BTCUSD"];
# In OnData(self, data)
bar = data["BTCUSD"]
# Anywhere in the code
crypto = self.Securities["BTCUSD"]


‘Oh no’: Trump mocks Beto O’Rourke for dropping out of 2020 race
by Madison DibblePresident Trump used Beto O’Rourke’s words from the beginning of his 2020 campaign to mock the end of his presidential bid.
In a celebratory tweet, Trump pointed to O’Rourke’s Vanity Fair campaign launch and scoffed at his campaign-ending announcement.
"Oh no, Beto just dropped out of race for President despite him saying he was 'born for this.' I don’t think so!" he tweeted Friday.
When O’Rourke announced earlier this year he was running, he claimed he felt he was destined to be president, saying, “Man, I’m just born to be in it.”
He later backtracked on this campaign talking point, saying, “Nobody is born to be president of the United States of America — least of all me."
He announced the end of his campaign on Friday, saying, "Thank you for making this campaign possible, and for continuing to believe that we can turn this moment of great peril into a moment of great promise for America and the world."


{% extends 'business_profile/admin-base.html' %} {% load static %} {% load breadcrumbs from component_tags %} {% block breadcrumbs %} {% breadcrumbs 'Collaborators' %} great.gov.uk Business profile Profile settings {% endbreadcrumbs %} {% endblock %} {% block inner_content %}
| People | Role | Action | |
|---|---|---|---|
| {{ collaborator.name|default:collaborator.company_email }} | {{ collaborator.role|title }} | {% if collaborator.sso_id == request.user.id %}Remove profile from my account | {% else %}Edit | {% endif %}
People requesting to join the business profile
| People | Request | Actions |
|---|---|---|
| {{ collaboration_request.name }} | Request to become {{ collaboration_request.role|lower }} | |
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{% extends "base.html" %} {% block title %}Reset Password{% endblock title %} {% block content %} {% if validlink %}
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This is a European Honey bee.
It is found in almost all parts of the world.
Many people use it for farming honey to use as food.
In most climates, western honey bees swarm in the spring and early summer, when there is an abundance of blooming flowers from which to collect nectar and pollen.
The new queen in the original colony will be one of the daughter queens that developed from one of the daughter queen eggs laid by the mother queen before swarming. A colony can only have one queen. Once daughter queens emerge as adults, they will fight until one queen is left alive.
It is found in the regions of Mexico.
They eat ungulates, rodents, and rabbits
They are social animals
This is a coypu, also known as a Nutria.
They originate from South America, but have been introduced to other parts of the world such as North America, Europe, Africa, and Asia
The nutria looks like a muskrat, another rodent that has been introduced out of its range. However, the nutria has a longer tail and body
The nutria also resembles a rat-tailed beaver
The nutria is a mostly nocturnal creature
Nutria has long incisors that are yellow to orange or orange to red in color.
They are herbivores with huge appetites
Nutria has five fingers on front and hind feet. All fingers except one on the front feet have long nails. Webbed hind feet represent adaptation to the life near the water.
Nutria digs burrows near the water or uses platforms made of dead vegetation to sleep, eat and reproduce.
This is a blue tang, a marine fish
This is the fish species dory from finding nemo is based on
It is an omnivorous fish, feeding on plankton and algae
They are found in areas of the Atlantic and Pacific ocean
On reefs, the blue tang rests in narrow holes and crevices, protected from predators such as tuna, bar jacks and tiger groupers.
When it is time to reproduce, regal blue tangs congregate in breeding groups. Females expel their eggs into the water above the coral, and the males expel sperm, and fertilization occurs externally. About 40,000 eggs are expelled per spawning session, according to the ADW. After spawning, the "parents" swim off, never caring about their offspring.
After the release of Finding Dory, this species of fish has become popular as a pet.
Despite its name, the blue tang is not always azure. It can change color at night because of the way light is reflected from the pigments in its skin, becoming “whitish with a shade of violet.”
This is a sun bear, a small species of bear found in Southeast Asia
It is also called a honey bear due to its huge appetite for honey
Although they are the smallest bears, they are very aggressive and capable of mauling a person to death
They have long tongues which they use to get food from small spaces.
Sun bears grow to only about half the size of an American black bear. Males, slightly larger than females, are about 5 feet in length and weigh up to 150 pounds, a stature which suits their arboreal lifestyle and allows them to move easily through the trees.
Because they live in tropical temperatures, sun bears do not need to hibernate and are able to mate at any time of year. Unlike North American bears, male and female sun bears may hang out or live together while raising the cubs. Sun bears will usually have two cubs at a time and care for them for two years until they are old enough to survive on their own.
Sun bears have loose skin that allows them to twist when being bitten, so as to bite an attacker. They also have very strong legs that are great for climbing. These characteristics help this bear protect itself from tigers and other possible predators.
These are Cane toads
It is a large frog native to Central and South America
It has been introduced to Australia to solve invasive sugar beetle problems, but has become a pest itself
It's natural predators are hawks, caimans, eels, and snakes
Predators outside its range include meat ants, black rats, rakali, and crows
Some animals such as the rakali and black rat are tolerable of the cane toad's toxins while others such as the meat ants are immune to its venom.
They are voracious predators that will eat about anything
The common name "marine toad" and the scientific name Rhinella marina suggest a link to marine life, but the adult cane toad is entirely terrestrial, only venturing to fresh water to breed.
Cane toads are solitary during the night (when they search for food). They gather in groups called "knots" during the day.
This is a rock hyrax, a small mammal found in Africa.
Although it may look like a groundhog or a rodent, the rock hyrax is more closely related to the elephant and manatee.
It is related to the elephant since both have similar toes and internal testes predominantely in their abdomen.
They have glands which are used to mark their turfs.
They have three chambered stomach with bacteria to help them digest cellulose.
They use, grants, wails, etc. to communicate.
They are social animals, living in colonies of 50 individuals.
They are omnivorous species that feed on anything they find.
They mostly live in rock crevices, hence their name.
Predators include big cats, hyenas, and pythons.
This is a kakapo, a small flightless bird found on New Zealand
The kakapo is the world's only flightless parrot and is unusual for its nocturnal behavior.
It is also the world's heaviest parrot.
They are critically endangered due to introduction of non-native mammals such as stoats, cats, and rats.
They can live up to 90 years.
It is mostly a ground-dwelling bird, but it can climb trees using its strong legs equipped with sharp claws.
They are also known as owl parrots due to their owl-like faces
They are very friendly birds.
This is a kea, a small bird native to New Zealand
It is the world's only alpine parrot since it can thrive in the high mountains of New Zealand.
The Kea parrots diet is quite varied including leaf buds, roots, berries, fruit, seeds, blossoms, nectar, carrion and insects. They are particularly fond of the nectar of flax, rata, snow totara and coprosma. The Keas long beak is a valuable tool in its search for food especially in crevices in between rocks and boulders and for prizing off the lids of rubbish bins.
They are highly endangered due to invasive species
This is a marine iguana, a reptile native to the Galapagos islands.
They are unique in that they are the only iguanas that can swim in saltwater.
They feed mostly on algae.
The marine iguana removes excess salt from its body through glands in the nose. It excretes salt by squirting it several feet out of its nostrils.
They can dive at depths of 65 feet!
This is a thylacine, an extinct marsupial once native to australia.
They were hunted to extinction due to fear of them killing sheep.
They were the largest land predators in australia.
It probably would have been a carnivore that ate sheep.
This is the Falkland islands wolf, also known as the Warrah
It is an extinct canine that was the only living land mammal on the falkland islands.
It became extinct during the year 1876.
Its modern ancestor is believed to be the maned wolf.
This is a red eared slider, a common and well known species of turtle
This turtle has been very popular in the pet trade
As a result of the pet trade, the red eared slider has been introduced to many areas outside of its range where it has been deemed one of the worst invasive species ever.
They are normally found in the United states around the mississippi river and the gulf of mexico. Feral populations exist in asia, africa, guam, the marianas islands, and Hawaii.
This is a brown tree snake, a venomous snake found in australia, indonesia, and Melanesia.
They have been introduced to Guam where they have impacted the birds there.
Brown tree snakes can be identified by their slender bodies and their light brown coloration. Occasionally the snake may appear olive-colored or have black speckling along its body. These snakes usually range between 3 and 6 feet in length, but may grow larger.
This is a house sparrow, a widespread and invasive species of bird.
Don't let its size fooul you because the house sparrow is an aggressive bird.


| Bayesian Model Evaluation and Criticism | |
| Ravin Kumar | Colin Carroll |
| canyon289.github.io | colindcarroll.com |
| @canyon289 | @colindcarroll |
Good statisticians are able to explain their choices, justify their numbers, evaluate their own models, and share their results in a reproducible fashion! This tutorial demonstrates how to do the above using ArviZ.
No prior work is required for this tutorial but if you'd like to prepare we've provided a list of resources
In your terminal, use git
to clone the repository locally:
git clone git@github.com:arviz-devs/bayesian-model-evaluation.git
Alternatively, you can download the zip file of the repository at the top of the main page of the repository. If you prefer not to use git or don't have experience with it, this a good option.
If you do not already have the Anaconda Distribution of
Python 3, go get it (note: you can also set up your project environment w/out Anaconda using
pip
to install the required packages; however Anaconda is great for data science and we
encourage you to use it).
conda
users
If this is the first time you are setting up your compute environment, use conda
to
create an environment:
conda env create -n bayes-eval
To activate the environment, use the conda activate
command:
conda activate bayes-eval
If you get an error activating the environment, try to use the older source
activate
command:
source activate bayes-eval
Then follow the instructions for pip
users.
pip
users
Install all of the packages listed in the requirements.txt
file:
pip install -r requirements.txt
Docker
users
An image can be built from the root directory of the repository using the following command. This will build an image on your computer with all dependencies and environment installed:
./scripts/container.sh --build
Once an image is built a container can be started with the command:
./scripts/container.sh --notebook
In your terminal a URL for the notebook server will be displayed. Copy and paste that into a browser. With that you'll have Jupyter in a container! If you're using docker you can skip step 4.
You can click to get a Binder session on which you can compute and code.
In the terminal, navigate to this directory and execute jupyter lab
Navigate to the notebooks
directory, then 1_BayesianWorkflow
, and open the
notebook 1_Ins_BayesRefresher.ipynb
.
If you are only interested in viewing the static versions of the notebooks, you can view them on github.
We would like to thank the whole Bayes community for being open with learnings and material. For this tutorial in particular we'd like to thank Ari Hartikainen, Osvaldo Martin, and Eric Ma for providing feedback and content.
We have a Google form we would love you to use here. We'll use this information to help improve the teaching and delivery of the material. Issues and pull requests are also welcomed and encouraged if you would like!


MOVIES Jonathan Richards
MIDDLE-AGED MAN MEETS GIRL
AUTUMN IN NEW YORK
Directed by Joan Chen Screenplay by Allison Burnett With Richard Gere, Wynona Ryder De Vargas PG-13 103 min
He (Richard Gere) is a silver-haired womanizer with nearly a half-century under his belt, owner-chef of the kind of trendy New York restaurant where salad costs 35 bucks. She (Wynona Ryder) is an adorable pixie-haired gamine of 22, from a Manhattan socialite family that can afford that salad. She makes cute hats out of wire, and has a bum ticker. "Nobody thought I'd last this long," she tells him. They fall in love. As his best friend (Anthony LaPaglia) points out, "she's the perfect woman for you -- young, beautiful, and on the way out."
She may be young and doomed, but she represents three generations of her family: herself, her tough old granny (Elaine Stritch), and her mother, now dead, with whom Gere once was in love back in the '70s. "She never slept with him," Granny assures her, to eliminate any taint of something vaguely incestuous, "She was too old-fashioned for that."
For romantic small talk, he tells her about her mother. "Her favorite singer was Stephen Stills." She is of course too young to remember Stills, which probably explains why she doesn't seem familiar with this plot either.
In the beginning they giggle a lot, and she sasses him with smart talk. "Do you think I'm too old for you?" "No, I collect antiques." By the end, there are a lot of brave smiles, and the smart talk has turned poignant.  "No, I've saved you for them."
His womanizing is legend, but she starts right in to devote her few remaining mortal months to changing him. When he boffs an old flame at a party, she finds out by putting her hand on his heart to see if he's lying (he is). Boy loses girl. Boy grovels. Boy gets another chance.
Gere and Ryder are both decent actors, but they inhabit separate spaces here. It's not necessarily a generation gap problem, although today we're much more sensitive to that than in the days when Audrey Hepburn was wooed and won by Bogart (30 years her senior) in Sabrina, Cooper (28 years) in Love in the Afternoon, and Grant (25 years) in Charade. It may be no coincidence that Ryder sports a Hepburn look here. Perhaps it's just the lack of chemistry between Ryder and Gere that turns everyone against their romance. "Leave her alone," says Stritch. "She's sick. She's really sick." If she's that close to death, what are we saving her from? At least she'll never have to do that tiresome "when I'm fifty he'll be.." math.
There's nothing really offensive about this retread job except the time it wastes. The director is actress-turned filmmaker Joan Chen, who last worked on the Mongolian plains with Xiu-Xiu, the Sent-Down Girl, also about a young girl and an older man. Chen is 39. She should be old enough to remember Steve Stills, and this plot.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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