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Bluemix/DSX Account: http://www.bluemix.com
Node.js: https://nodejs.org
Visual Studio Code: https://code.visualstudio.com/
git clone https://github.com/ibm-cds-labs/cbf-chatbot-workshop
Facebook Messenger
Kik
Skype
Slack
Twilio
Microsoft Bot Framework
Botkit
Smooch.io
api.ai (Google)
wit.ai (Facebook)
Watson Conversation
Watson Conversation combines a number of cognitive techniques to help you build and train a bot - defining intents and entities and crafting dialog to simulate conversation.
Intents
Entities
Dialog
Context
Passed between Watson Conversation and application
Keeps track of current dialog in the conversation
https://github.com/ibm-cds-labs/cbf-chatbot-workshop


Crews fight major apartment building fire in Toronto, six people rescued
TORONTO — Fire crews have rescued at least six people from a burning apartment building in Toronto. Fire Chief Matthew Pegg says a fire was reported late Friday afternoon in North York and the flames quickly spread in the building to multiple floors.
by Canadian PressTORONTO — Fire crews have rescued at least six people from a burning apartment building in Toronto.
Fire Chief Matthew Pegg says a fire was reported late Friday afternoon in North York and the flames quickly spread in the building to multiple floors.
He says one person has been sent to hospital in stable condition and others have been treated by medics.
Pegg says about 100 personnel and 22 trucks are on the scene.
He says people from the building can take shelter in TTC buses that have been brought in.
Pegg says firefighters have a long night ahead of them.
This report from The Canadian Press was first published Nov. 15, 2019.
The Canadian Press


This vignette contains a series of examples showing how to initialize the safetyGraphics Shiny app in different scenarios. For a general overview of the app see this vignette. For more details about adding custom charts, see this vignette.
safetyGraphics requires R v4 or higher. These examples have been tested using RStudio v1.4, but should work on other platforms with proper configuration.
You can install safetyGraphics from CRAN like any other R package:
install.packages("safetyGraphics")
library("safetyGraphics")
Or to use the most recent development version from GitHub, call:
devtools::install_github("safetyGraphics/safetyCharts", ref="dev")
library(safetyCharts)
devtools::install_github("safetyGraphics/safetyGraphics", ref="dev")
library(safetyGraphics)
safetyGraphics::safetyGraphicsApp()
To run the app with no customizations using sample AdAM data from the {safetyData} package, install the package and run:
safetyGraphics::safetyGraphicsApp()
The data passed in to the safetyGraphics app can be customized using the data
parameter in safetyGraphicsApp()
. For example, to run the app with SDTM data saved in {safetyData}
, call:
sdtm <- list(
dm=safetyData::sdtm_dm,
aes=safetyData::sdtm_ae,
labs=safetyData::sdtm_lb
)
safetyGraphics::safetyGraphicsApp(domainData=sdtm)
Running the app for a single data domain, is similar:
justLabs <- list(labs=safetyData::adam_adlbc)
safetyGraphics::safetyGraphicsApp(domainData=justLabs)
Note that charts with missing data are automatically dropped and the filtering tab is not present since it requires demographics data by default.
Users can also generate a list of charts and then drop charts that they don’t want to include. For example, if you wanted to drop charts with type
of “htmlwidgets” you could run this code.
library(purrr)
charts <- makeChartConfig() #gets charts from safetyCharts pacakge by default
notWidgets <- charts %>% purrr::keep(~.x$type != "htmlwidget")
safetyGraphicsApp(charts=notWidgets)
The code below adds a new simple chart showing participants’ age distribution by sex.
ageDist <- function(data, settings){
p<-ggplot(data = data, aes_(x=as.name(settings$age_col))) +
geom_histogram() +
facet_wrap(as.name(settings$sex_col))
return(p)
}
ageDist_chart<-list(
env="safetyGraphics",
name="ageDist",
label="Age Distribution",
type="plot",
domain="dm",
workflow=list(
main="ageDist"
)
)
charts <- makeChartConfig()
charts$ageDist<-ageDist_chart
safetyGraphicsApp(charts=charts)
For extensive details on adding and customizing different types of charts, see this vignette.
Next, let’s initialize the the app with non-standard data. {safetyGraphics} automatically detects AdAM and SDTM data when possible, but for non-standard data, the user must provide a data mapping. This can be done in the app using the data/mapping tab, or can be done when the app is initialized by passing a mapping
list to safetyGraphicsApp()
. For example:
notAdAM <- list(labs=safetyData::adam_adlbc %>% rename(id = USUBJID))
idMapping<- list(labs=list(id_col="id"))
safetyGraphicsApp(domainData=notAdAM, mapping=idMapping)
For a more realistic example, consider this labs data set (csv). The data can be loaded in to safetyGraphics with the code below, but several items in the mapping page need to be filled in:
labs <- read.csv("https://raw.githubusercontent.com/SafetyGraphics/SafetyGraphics.github.io/master/pilot/SampleData_NoStandard.csv")
safetyGraphics::safetyGraphicsApp(domainData=list(labs=labs))
Fortunately there is no need to re-enter this mapping information in every time you re-start the app. After filling in these values once, you can export code to restart the app with the specified settings pre-populated. First, click on the setting icon in the header and then on “code” to see this page:
The YAML code provided here captures the updates you’ve made on the mapping page. To re-start the app with those settings, just save these YAML code in a new file called customSettings.yaml
in your working directory, and then call:
labs <- read.csv("https://raw.githubusercontent.com/SafetyGraphics/SafetyGraphics.github.io/master/pilot/SampleData_NoStandard.csv")
customMapping <- read_yaml("customSettings.yaml")
safetyGraphics::safetyGraphicsApp(
domainData=list(labs=labs),
mapping=customMapping
)
Note, that for more complex customizations, the setting page also provides a .zip
file with a fully re-usable version of the app.


Loading
t This website is part of Mitsubishi Power's continuous efforts to improve communications with existing and potential customers and other interested parties globally. Aligned with that business purpose and for most effective utilization.
The language, at its very core, emphasised extensively on code readability. With its concise and expressive syntax, it allowed developers to express ideas and concepts without writing tons of lines code (as would be the case in lower-level languages like C or Java). Its simplicity a given, Python seamlessly integrates with other programming languages (like offloading CPU-intensive tasks to C/C++), making it an added bonus to polyglot developers.
One of the main driving points behind Python’s meteoric growth.
Miranda H. -Founder
Among the major reasons why Python is “slow”, it really boils down to 2 — Python is interpreted as opposed to compiled, ultimately leading to slower execution times; and the fact that it is dynamically typed (data types of variables are automatically inferred by Python during execution). Take, for example, TensorFlow, a Machine Learning library available in Python. These libraries were actually written in C++ and made available in Python, sort of forming a Python “wrapper” around the C++ implementation. The same goes for Numpy and, to an extent, even Caer. One of the major reasons for Python’s slowness is the presence of GIL (Global Interpreter Lock) which allows only one thread to execute at a time. While this boosts the performance of single threading, it places a limitation on parallelism where developers have to implement multiprocessing programs as opposed to multi-threaded ones, to improve speeds.


‘Penis enlargement massage’ to help boost Indonesia’s medical tourism
by BY MILAD HASSANDARVISHKUALA LUMPUR, November 25 — Apart from promoting its pristine beaches and exotic islands, Indonesia is looking to become a hub for alternative treatment and attract more medical tourists.
From soothing an aching back to treating mental and even spiritual illnesses, the country’s traditional or unconventional healing method seems to have the answer to nearly every sort of ailment.
In a bid to boost the country’s medical tourism, Indonesia’s Health Minister Terawan Agus Putranto announced recently that his country should capitalise on their “penis enlargement” massage.
Known locally as Mak Erot, the massage is believed to be an alternative treatment to enlarge a person’s manhood.
According to Vice Indonesia, Terawan has referred to Mak Erot as a national asset with high potential to attract medical tourists from abroad.
“We must popularise the idea of traditional medicine for tourism.
“We have an incredible herbal medicine industry that no one knows about outside Indonesia,” he said.
He also cited Tongkat Ali (a leaf that is said to boost athletic performance and muscle mass), Purwaceng (a Viagra-like substance), and Mak Erot as potential services to boost medical tourism.
“If we package it correctly, foreigners will be interested,” he said.
Terawan also specifically brought up Kerok, coin and ointment treatment, as a worthy attraction for medical tourism.
Known its varied benefits among the locals, Kerok is a method of treating a variety of ailments by rubbing a coin against the skin of the back with menthol ointment, which is believed to increase blood and oxygen circulation.
“Don’t underestimate kerok. If we had 100 rooms and it takes 20 minutes per person, imagine how much revenue that would generate.
“There are many other cultural gems that we have not exploited because we take them for granted, but to foreigners, it’s something intriguing,” he added.


Broad Crawls¶
Scrapy defaults are optimized for crawling specific sites. These sites are often handled by a single Scrapy spider, although this is not necessary or required (for example, there are generic spiders that handle any given site thrown at them).
In addition to this “focused crawl”, there is another common type of crawling which covers a large (potentially unlimited) number of domains, and is only limited by time or other arbitrary constraint, rather than stopping when the domain was crawled to completion or when there are no more requests to perform. These are called “broad crawls” and is the typical crawlers employed by search engines.
These are some common properties often found in broad crawls:
- they crawl many domains (often, unbounded) instead of a specific set of sites
- they don’t necessarily crawl domains to completion, because it would be impractical (or impossible) to do so, and instead limit the crawl by time or number of pages crawled
- they are simpler in logic (as opposed to very complex spiders with many extraction rules) because data is often post-processed in a separate stage
- they crawl many domains concurrently, which allows them to achieve faster crawl speeds by not being limited by any particular site constraint (each site is crawled slowly to respect politeness, but many sites are crawled in parallel)
As said above, Scrapy default settings are optimized for focused crawls, not broad crawls. However, due to its asynchronous architecture, Scrapy is very well suited for performing fast broad crawls. This page summarizes some things you need to keep in mind when using Scrapy for doing broad crawls, along with concrete suggestions of Scrapy settings to tune in order to achieve an efficient broad crawl.
Increase concurrency¶
Concurrency is the number of requests that are processed in parallel. There is a global limit and a per-domain limit.
The default global concurrency limit in Scrapy is not suitable for crawling
many different domains in parallel, so you will want to increase it. How much
to increase it will depend on how much CPU you crawler will have available. A
good starting point is 100
, but the best way to find out is by doing some
trials and identifying at what concurrency your Scrapy process gets CPU
bounded. For optimum performance, you should pick a concurrency where CPU usage
is at 80-90%.
To increase the global concurrency use:
CONCURRENT_REQUESTS = 100
Increase Twisted IO thread pool maximum size¶
Currently Scrapy does DNS resolution in a blocking way with usage of thread pool. With higher concurrency levels the crawling could be slow or even fail hitting DNS resolver timeouts. Possible solution to increase the number of threads handling DNS queries. The DNS queue will be processed faster speeding up establishing of connection and crawling overall.
To increase maximum thread pool size use:
REACTOR_THREADPOOL_MAXSIZE = 20
Setup your own DNS¶
If you have multiple crawling processes and single central DNS, it can act like DoS attack on the DNS server resulting to slow down of entire network or even blocking your machines. To avoid this setup your own DNS server with local cache and upstream to some large DNS like OpenDNS or Verizon.
Reduce log level¶
When doing broad crawls you are often only interested in the crawl rates you
get and any errors found. These stats are reported by Scrapy when using the
INFO
log level. In order to save CPU (and log storage requirements) you
should not use DEBUG
log level when preforming large broad crawls in
production. Using DEBUG
level when developing your (broad) crawler may be
fine though.
To set the log level use:
LOG_LEVEL = 'INFO'
Disable cookies¶
Disable cookies unless you really need. Cookies are often not needed when doing broad crawls (search engine crawlers ignore them), and they improve performance by saving some CPU cycles and reducing the memory footprint of your Scrapy crawler.
To disable cookies use:
COOKIES_ENABLED = False
Disable retries¶
Retrying failed HTTP requests can slow down the crawls substantially, specially when sites causes are very slow (or fail) to respond, thus causing a timeout error which gets retried many times, unnecessarily, preventing crawler capacity to be reused for other domains.
To disable retries use:
RETRY_ENABLED = False
Reduce download timeout¶
Unless you are crawling from a very slow connection (which shouldn’t be the case for broad crawls) reduce the download timeout so that stuck requests are discarded quickly and free up capacity to process the next ones.
To reduce the download timeout use:
DOWNLOAD_TIMEOUT = 15
Disable redirects¶
Consider disabling redirects, unless you are interested in following them. When doing broad crawls it’s common to save redirects and resolve them when revisiting the site at a later crawl. This also help to keep the number of request constant per crawl batch, otherwise redirect loops may cause the crawler to dedicate too many resources on any specific domain.
To disable redirects use:
REDIRECT_ENABLED = False
Enable crawling of “Ajax Crawlable Pages”¶
Some pages (up to 1%, based on empirical data from year 2013) declare themselves as ajax crawlable. This means they provide plain HTML version of content that is usually available only via AJAX. Pages can indicate it in two ways:
- by using
#!
in URL - this is the default way; - by using a special meta tag - this way is used on “main”, “index” website pages.
Scrapy handles (1) automatically; to handle (2) enable AjaxCrawlMiddleware:
AJAXCRAWL_ENABLED = True
When doing broad crawls it’s common to crawl a lot of “index” web pages; AjaxCrawlMiddleware helps to crawl them correctly. It is turned OFF by default because it has some performance overhead, and enabling it for focused crawls doesn’t make much sense.


amazon-chime-sdk / com.amazonaws.services.chime.sdk.meetings.audiovideo.metric / ObservableMetric / videoSendPacketLossPercent
videoSendPacketLossPercent
videoSendPacketLossPercent
Percentage of video packets lost from client to server across all send streams


RT @missokistic: It's feeling more and more like we're living in a parody of a William Gibson novel written by The Onion.
7/19/2015, 11:17:36 PM
Favs: 0
Retweets: 0
link--- layout: tweet ---
RT @missokistic: It's feeling more and more like we're living in a parody of a William Gibson novel written by The Onion.
7/19/2015, 11:17:36 PM
Favs: 0
Retweets: 0
link


Relationship visualization
A summary argument:
- Continued growth of internet, mobile, and sensor based applications means an explosion of data---a "big data" world.
- Big data requires visualization to provide meaning.
- Data visualization will become an important and large field of design.
- Data visualization will have many sub-disciplines.
- Relationship visualization is a sub-discipline of data visualization.
Relationship visualization provides tools that help people explore relationships between factors in a system. For example, if I want to take out a loan, how much will I pay overall, if the interest rate is x%? What happens if I pay off the loan in y years instead of 30 years?
Until recently, we've had to make do with tables or graphs or work out the calculations by hand. More recently, we've seen special purpose calculators, e.g., mortgage calculators. But it's possible to provide interactive diagrams---relationship visualizations---which support reader interaction with a set of related factors. Move the interest rate handle up or down, see the graph go up or down.
Where things get interesting is when many factors interact and affect each other. For example, total home price, points, percent down, interest rate, length of loan, number of payments per month. All these factors affect the loan principle, size of individual payment, and total paid. The possible combinations are almost infinite. Users may start in different place. Perhaps you know the total you can afford per month and want to find the largest loan you can afford. Or you want to buy a particular house and want to know what's the maximum interest rate you can afford.
Being able to "play" with the variables---twiddle the factor dials---is a way to experiment which is a way to understand or learn. So we might say that a mortgage factor relationship visualizer is a tool for learning about mortgages. And it's more. Learning and designing are closely coupled. Learning involves acting in the environment, experimenting---prototyping mortgages in our example. So we might also say that a mortgage factor relationship visualizer is a tool for designing your own mortgage. And designing relationship visualizers is (in part) about designing tools which enable others to design.
There's also a technical side to the argument. Tools like Flash and Processing have made data visualization more accessible to designers and also offer possibilities for creating relationship visualizations. In theory, one can create infinitely rich environments with those and other tools, but in practice they exist in boxes walled off from the larger environment in which they are presented---that is web pages or e-books (which are also essentially web pages---for the most part).
However, the advent of HTML5, CSS3, and recent changes to the DOM (Document Object Model) create a growing platform on which data visualizations and relationship visualizations can be built and fully integrated into the presentation environment. In this platform users can manipulate objects on screen creating JavaScript events which redraw SVG objects. This combination has the potential to become quite powerful. What's needed now are libraries---building blocks---to make the development process easier.
We've begun to build examples. We invite your comment.


Connection interface.
Driver connections must implement this interface.
This resembles (a subset of) the PDO interface.
Contract for a driver exception.
Driver exceptions provide the SQLSTATE of the driver and the driver specific error code at the time the error occurred.
Contract for a driver that is capable of converting DBAL driver exceptions into standardized DBAL driver exceptions.
Contract for a connection that is able to provide information about the server it is connected to.
Statement interface.
Drivers must implement this interface.
This resembles (a subset of) the PDOStatement interface.
Abstract base implementation of the {@link Doctrine\DBAL\Driver} interface for IBM DB2 based drivers.
Abstract base implementation of the {@link DriverException} interface.
Abstract base implementation of the {@link Doctrine\DBAL\Driver} interface for MySQL based drivers.
Abstract base implementation of the {@link Doctrine\DBAL\Driver} interface for Oracle based drivers.
Abstract base implementation of the {@link Doctrine\DBAL\Driver} interface for PostgreSQL based drivers.
Abstract base implementation of the {@link Doctrine\DBAL\Driver} interface for SAP Sybase SQL Anywhere based drivers.
Abstract base implementation of the {@link Doctrine\DBAL\Driver} interface for SQLite based drivers.
Abstract base implementation of the {@link Doctrine\DBAL\Driver} interface for Microsoft SQL Server based drivers.
PDO implementation of the Connection interface.
Used by all PDO-based drivers.


emoji-regex offers a regular expression to match all emoji symbols (including textual representations of emoji) as per the Unicode Standard.
This repository contains a script that generates this regular expression based on the data from Unicode Technical Report #51. Because of this, the regular expression can easily be updated whenever new emoji are added to the Unicode standard.
Via npm:
npm install emoji-regex
In Node.js:
const emojiRegex = require('emoji-regex');
// Note: because the regular expression has the global flag set, this module
// exports a function that returns the regex rather than exporting the regular
// expression itself, to make it impossible to (accidentally) mutate the
// original regular expression.
const text = `
\u{231A}: ⌚ default emoji presentation character (Emoji_Presentation)
\u{2194}\u{FE0F}: ↔ default text presentation character rendered as emoji
\u{1F469}: 👩 emoji modifier base (Emoji_Modifier_Base)
\u{1F469}\u{1F3FF}: 👩🏿 emoji modifier base followed by a modifier
`;
const regex = emojiRegex();
let match;
while (match = regex.exec(text)) {
const emoji = match[0];
console.log(`Matched sequence ${ emoji } — code points: ${ [...emoji].length }`);
}
Console output:
Matched sequence ⌚ — code points: 1
Matched sequence ⌚ — code points: 1
Matched sequence ↔ — code points: 2
Matched sequence ↔ — code points: 2
Matched sequence 👩 — code points: 1
Matched sequence 👩 — code points: 1
Matched sequence 👩🏿 — code points: 2
Matched sequence 👩🏿 — code points: 2
To match emoji in their textual representation as well (i.e. emoji that are not Emoji_Presentation
symbols and that aren’t forced to render as emoji by a variation selector), require
the other regex:
const emojiRegex = require('emoji-regex/text.js');
Additionally, in environments which support ES2015 Unicode escapes, you may require
ES2015-style versions of the regexes:
const emojiRegex = require('emoji-regex/es2015/index.js');
const emojiRegexText = require('emoji-regex/es2015/text.js');
| Mathias Bynens |
emoji-regex is available under the MIT license.


Our mission is to organize
and simplify cryptocurrency information
in order to make it accessibe to everyone
Real-time values with data analysis
Daily summaries of your favorite cryptos
Alerts on significant or constant movements
Team
Facundo Díaz
Tadeo Grach
Tomas de Castro


linalg module¶
Collection of linear algebra routines used in the EMUS algorithm and associated error analysis.
-
linalg.
groupInverse
(M)[source]¶ Computes the group inverse of stochastic matrix using the algorithm given by Golub and Meyer in: G. H. Golub and C. D. Meyer, Jr, SIAM J. Alg. Disc. Meth. 7, 273- 281 (1986)
Parameters: M : ndarray
A square matrix with index 1.
Returns: grpInvM : ndarray
The group inverse of M.
-
linalg.
stationary_distrib
(F, residtol=1e-10, max_iter=100)[source]¶ Calculates the eigenvector of the matrix F with eigenvalue 1 (if it exists).
Parameters: F : ndarray
A matrix known to have a single left eigenvector with eigenvalue 1.
residtol : float or scalar
To improve the accuracy of the computation, the algorithm will “polish” the final result using several iterations of the power method, z^T F = z^T. Residtol gives the tolerance for the associated relative residual to determine convergence.
maxiter : int
Maximum number of iterations to use the power method to reduce the residual. In practice, should never be reached.
Returns: z : ndarray
The eigenvector of the matrix F with eigenvalue 1. For a Markov chain stationary distribution, this is the stationary distribution. Normalization is chosen s.t. entries sum to one.


|
cds
1.2.0
|
Michael & Scott blocking queue with fine-grained synchronization schema. More...
#include <cds/container/rwqueue.h>
Data Structures | |
| struct | rebind |
| Rebind template arguments. More... |
Public Types | |
| typedef T | value_type |
| type of value stored in the queue | |
| typedef options::lock_type | lock_type |
| Locking primitive used. | |
|
typedef options::allocator::template rebind< node_type >::other | allocator_type |
| Allocator type used for allocate/deallocate the queue nodes. | |
| typedef options::item_counter | item_counter |
| Item counting policy used. | |
| typedef options::stat | stat |
| Internal statistics policy used. |
Public Member Functions | |
| RWQueue () | |
| Makes empty queue. | |
| ~RWQueue () | |
| Destructor clears queue. | |
| bool | enqueue (const value_type &data) |
Enqueues data . Always return true. | |
| template<typename Type , typename Func > | |
| bool | enqueue (const Type &data, Func f) |
Enqueues data to queue using copy functor. | |
| template<typename Type , typename Func > | |
| bool | dequeue (Type &dest, Func f) |
| Dequeues a value using copy functor. | |
| bool | dequeue (value_type &dest) |
| bool | push (const value_type &data) |
| Synonym for enqueue. | |
| template<typename Type , typename Func > | |
| bool | push (const Type &data, Func f) |
| Synonym for template version of enqueue function. | |
| bool | pop (value_type &data) |
| Synonym for dequeue. | |
| template<typename Type , typename Func > | |
| bool | pop (Type &dest, Func f) |
| Synonym for template version of dequeue function. | |
| bool | empty () const |
| Checks if queue is empty. | |
| void | clear () |
| Clears queue. | |
| size_t | size () const |
| Returns queue's item count. | |
| const stat & | statistics () const |
| Returns reference to internal statistics. |
Michael & Scott blocking queue with fine-grained synchronization schema.
The queue has two different locks: one for reading and one for writing. Therefore, one writer and one reader can simultaneously access to the queue. The queue does not require any garbage collector.
Source
Template arguments
T
- type to be stored in the queueOptions
- optionsOptions
are:
std::allocator
). Default is CDS_DEFAULT_ALLOCATORRWQueue
uses only onEnqueue
and onDequeue
counter.lock_type
to prevent false sharing. Default is opt::cache_line_alignmentThis queue has no intrusive counterpart.
|
inline |
Dequeues a value using copy functor.
Func
is a functor called to copy dequeued value to dest
of type Type
which may be differ from type T
stored in the queue. The functor's interface is:
You may use boost:ref
construction to pass functor f
by reference.
Requirements The functor Func
should not throw any exception.
|
inline |
Dequeues a value to dest
.
If queue is empty returns false, dest
may be corrupted. If queue is not empty returns true, dest
contains the value dequeued
|
inline |
Enqueues data
to queue using copy functor.
Func
is a functor called to copy value data
of type Type
which may be differ from type T
stored in the queue. The functor's interface is:
You may use boost:ref
construction to pass functor f
by reference.
Requirements The functor Func
should not throw any exception.
|
inline |
Returns queue's item count.
The value returned depends on opt::item_counter option. For atomicity::empty_item_counter, this function always returns 0.
Warning: even if you use real item counter and it returns 0, this fact is not mean that the queue is empty. To check queue emptyness use empty() method.


Otherwise copy the files into the appropriate /var/www folder and play with LAMP to make it work. A few things to look out for.
create table results (idnum int(4) NOT NULL auto_increment PRIMARY KEY, name char(100), guess int(3) ZEROFILL, count int(2), tod TIMESTAMP );
grant ALL on *.* to root@localhost IDENTIFIED BY 'vicnum' ;
The Vicnum project was developed for educational purposes to demonstrate common web vulnerabilities. For comments please visit the OWASP project page.


Review
Divinity: Original Sin 2 is awesome
triple games
Featured
Resident Evil 7: Scarier than ever
Triple Games
Guide
Bioshock 2: Tactics on killing Big Sisters
Triple games
Adventure
Tomb Raider: The reincarnation of Lara Croft
Stealth
Dishonored 2: Creative Kills have never look so good
First person shooter
Bioshock Infinite: Colorful instead of morbid
Triple games
Review
Trine 2: Entertaining & Funny
Adventure
Witcher 3: Blood and Wine


class: center, middle, inverse, title-slide # Lecture 10 ## Model Fit, Validation and Counterfactual Simulations ### Tyler Ransom ### ECON 6343, University of Oklahoma --- # Plan for the Day 1. Discuss how to assess model fit 2. Model validation 3. Counterfactual simulations 4. Go through examples from a couple of recent papers - Fu, Grau, and Rivera (2020) - Lang and Palacios (2018) --- # Steps to producing a "structural" estimation - We discussed the structural workflow in our 3rd class meeting - Since that class meeting, we've focused mainly on estimation - We also briefly talked about identification - But there are still some steps we haven't covered - Counterfactuals are where you actually answer your research question - And before counterfactuals you need to show your model fits the data --- # Model Fit - Model fit basically consists of showing that your model can match the data - This is because the counterfactuals rely solely on the model - Most model fit is _ad hoc_: you can choose what to show - Typically, you'll want to show that moments of the `\(Y\)` variables match - e.g. choice frequencies in the data match choice probabilities of the model - But there may be other moments of interest, like dynamic choice transitions --- # Example from Fu, Grau, and Rivera (2020) - In this paper, the authors show the following model fit statistics:

  Variable 	  Data 	  Model

  Ever arrested % 	  5.60 	  5.10

  Always enrolled, 0 arrest % 	  72.20 	  71.10

  GPA (standardized) 	  -0.39 	  -0.43

  Retention % 	  7.30 	  8.00

  Grade Completed by T 	  11.10 	  11.20

 - These results are for youth with parents who are not well educated - (This group is the most at risk to be arrested or drop out of school) - Model fit for other groups is similar --- # How to do model fit There are a couple of options for producing model fit statistics 1. Use the model assumptions and estimates to simulate a new dataset 2. Use the data and estimates to compute `\(\hat{Y}\)` and compare with `\(Y\)` --- # Simulating a new dataset - To simulate a new data set, you simply draw the unobservables from the model - Use any initial conditions from the data - Then (if the model is dynamic) simply draw `\(Y\)` in `\(t=1\)` - Then update the `\(X\)`'s in `\(t=2\)` and draw `\(Y\)` in `\(t=2\)`, ... - If you used SMM to estimate the model, you should already have code for this - Typically you want to repeat this process a few times - This is because you don't want model fit to be subject to simulation error --- # Assessing model fit from the data and estimates - A simpler option is to predict the `\(\hat{Y}\)` using the actual data - This is identical to using a `predict()` function (like in PS6) - However, this approach may not be possible in a model with key latent variables - For example, unobserved types or other unobservables are not in the data - In this case, you have no choice but to go the simulation route --- # Model Validation - Even if your model fits the data well, some may still be skeptical - This is because, in most cases, you used your entire dataset in estimation - If you do this, you open yourself up to the possibility of .hi[overfitting] - .hi[Model validation] is a way of showing that your model is not overfit - To do so, you show that the model reproduces key stats in a "holdout sample" - This sample was "held out" of the estimation for purposes of validation --- # Mini aside on machine learning Machine learning is all about automating two hand-in-hand processes: 1. Model selection - What should the specification be? 2. Model validation - Does the model generalize to other (similar) contexts? - The goal of machine learning is to automate these processes to maximize prediction - This is different than the goal of econometrics (causal inference) --- # Model selection - In classical econometrics, we always select our models by hand - This what the famed and sometimes maligned "robustness checks" address - In machine learning, we let the computer tell us which specification is "best" - "Best" is defined by minimizing both in- and out-of-sample prediction error - This involves estimating many different specifications - For complex models, automated model selection is computationally intensive - Rust (1987) did this by hand when exploring the shape of the cost function --- # Model validation - Broadly speaking, model validation is about whether the model "makes sense" - It can be qualitative ("do the parameter results make sense? conform to theory?") - It can also be quantitative ("is the prediction error sufficiently low?") - In machine learning, .hi[cross-validation] is typically used - Cross-validation informs about the optimal complexity of the model - Then we (can) automate our specification search subject to that optimal complexity - Automated specification search is still not commonly done in structural estimation --- # How cross-validation works (Adams, 2018) .center[![cross-validation](CVdiagram.jpg)] - Blue is the data that we use to estimate the model's parameters - We randomly hold out `\(K\)` portions of this data one-at-a-time (Green boxes) - We assess the performance of the model in the Green data - This tells us the optimal complexity (by "hyperparameters" if CV is automated) --- # Validation in Lang and Palacios (2018) - A common question is how much unobserved heterogeneity to allow for - This is not _ex ante_ knowable - Typical approach is to put "enough" in there such that the in-sample fit is good - Lang and Palacios (2018) search for optimal number of types - Use a 20% holdout sample to assess the out-of-sample fit - Note that they do not do cross-validation - They simply compare how the model fits in the estimation and holdout data --- # Validation in Delavande and Zafar (2019) - Another form of validation could be to predict treatment effects in control group - If the model is good, it should be able to do this - Delavande and Zafar (2019) do something similar to this - Rather than comparing model predictions in/out of sample, - They compare them for a different state of the world - In their case, the new state of the world is one without schooling costs - They can do this because they elicited preferences for schooling under both regimes - But they only used one regime when estimating their model --- # Counterfactuals - Counterfactuals involve changing the model, simulating new data and then comparing w/status quo - "Changing a policy" typically can be captured by changing the value of a set of parameters - "Policy experiments" typically mimic some real-world policy in this way - .hi[Note:] policy experiments always assume invariance of the other model parameters! - So if I change the value of one parameter, that won't "leak" into any others - This may be a heroic assumption, depending on the model --- # Examples of counterfactuals .smaller[ - Fu, Grau, and Rivera (2020) - Would low-SES youth commit fewer crimes if we sent them to better schools? - Arcidiacono, Aucejo, Maurel, and Ransom (2016) - How would human capital investment change if there were perfect information? - Arcidiacono, Kinsler, and Ransom (2019) - Would Harvard become less white if it were to eliminate legacy admissions? - Ransom (2019) - Would American workers move to a new city if they were paid $10,000 to do so? - Caucutt, Lochner, Mullins, and Park (2020) - What can reduce disparities in child investment across rich/poor families? ] --- # How to do counterfactuals - To perform the counterfactual simulations, follow these steps: - Impose parameter restrictions - Simulate fake data under those restrictions - Compare the resulting model summary to a "baseline" prediction - (The baseline prediction is your model fit) - As you can see, if you use SMM, you've already got the code to simulate the model --- # Coding example: multinomial logit estimation This code comes from the first question of Problem Set 4: .scroll-box-16[ ```julia using Random, LinearAlgebra, Statistics, Optim, DataFrames, CSV, HTTP, GLM, ForwardDiff, FreqTables # read in data url = "https://raw.githubusercontent.com/OU-PhD-Econometrics/fall-2020/master/ProblemSets/PS4-mixture/nlsw88t.csv" df = CSV.read(HTTP.get(url).body) X = [df.age df.white df.collgrad] Z = hcat(df.elnwage1, df.elnwage2, df.elnwage3, df.elnwage4, df.elnwage5, df.elnwage6, df.elnwage7, df.elnwage8) y = df.occ_code # estimate multionomial logit model include("mlogit_with_Z.jl") θ_start = [ .0403744; .2439942; -1.57132; .0433254; .1468556; -2.959103; .1020574; .7473086; -4.12005; .0375628; .6884899; -3.65577; .0204543; -.3584007; -4.376929; .1074636; -.5263738; -6.199197; .1168824; -.2870554; -5.322248; 1.307477] td = TwiceDifferentiable(b -> mlogit_with_Z(b, X, Z, y), θ_start; autodiff = :forward); θ̂_optim_ad = optimize(td, θ_start, LBFGS(), Optim.Options(g_tol = 1e-5, iterations=100_000, show_trace=true, show_every=50)); θ̂_mle_ad = θ̂_optim_ad.minimizer H = Optim.hessian!(td, θ̂_mle_ad) θ̂_mle_ad_se = sqrt.(diag(inv(H))) ``` ] --- # Coding example: model fit and counterfactuals Now let's evaluate model fit and effect of counterfactual policy .scroll-box-16[ ```julia # get baseline predicted probabilities function plogit(θ, X, Z, J) α = θ[1:end-1] γ = θ[end] K = size(X,2) bigα = [reshape(α,K,J-1) zeros(K)] P = exp.(X*bigα .+ Z*γ) ./ sum.(eachrow(exp.(X*bigα .+ Z*γ))) return P end println(θ̂_mle_ad) P = plogit(θ̂_mle_ad, X, Z, length(unique(y))) # compare with data modelfitdf = DataFrame(data_freq = 100*convert(Array, prop(freqtable(df,:occ_code))), P = 100*vec(mean(P'; dims=2))) display(modelfitdf) # now run a counterfactual: # suppose people don't care about wages when choosing occupation # this means setting θ̂_mle_ad[end] = 0 θ̂_cfl = deepcopy(θ̂_mle_ad) θ̂_cfl[end] = 0 P_cfl = plogit(θ̂_cfl, X, Z, length(unique(y))) modelfitdf.P_cfl = 100*vec(mean(P_cfl'; dims=2)) modelfitdf.ew = vec(mean(Z'; dims=2)) modelfitdf.diff = modelfitdf.P_cfl .- modelfitdf.P display(modelfitdf) │ Row │ data_freq │ P │ P_cfl │ diff │ ew │ │ │ Float64 │ Float64 │ Float64 │ Float64 │ Float64 │ ├─────┼───────────┼─────────┼─────────┼───────────┼─────────┤ │ 1 │ 10.5976 │ 11.2549 │ 8.34334 │ -2.91158 │ 1.96627 │ │ 2 │ 5.24943 │ 6.21553 │ 4.98708 │ -1.22845 │ 1.85026 │ │ 3 │ 38.6462 │ 37.5457 │ 34.4537 │ -3.092 │ 1.71771 │ │ 4 │ 4.66067 │ 4.88623 │ 5.70078 │ 0.814551 │ 1.54756 │ │ 5 │ 1.54063 │ 1.80065 │ 1.62727 │ -0.173382 │ 1.75298 │ │ 6 │ 15.1525 │ 14.676 │ 15.123 │ 0.447092 │ 1.58918 │ │ 7 │ 18.3571 │ 17.3364 │ 23.3689 │ 6.03245 │ 1.42956 │ │ 8 │ 5.79588 │ 6.28457 │ 6.39589 │ 0.111316 │ 1.59501 │ ``` ] --- # Discussion of model fit counterfactuals - Model fit is good, and I would have expected even better - MLE is designed to match the data choice frequencies - The counterfactuals make sense - Removing preference for earnings leads to re-sorting of occupations - Sorting into low-wage occupations and out of high-wage ones --- # Confidence intervals around counterfactuals - The counterfactuals above give us a new predicted occupational distribution - But we don't know what the confidence intervals are around the prediction - Our estimates inherently come with sampling variation - We should incorporate that variation into our counterfactual - How do we do this? Bootstrapping --- # Bootstrapping to get CIs around counterfactuals - Recall: `\(-H^{-1}\)` is the variance matrix of our estimates, where `\(H\)` is the Hessian - Assume that `\(\hat{\theta} \sim MVN(\theta,-H^{-1})\)` - but remember that we want to minimize `\(-\ell\)` so we just use `\(H^{-1}\)` - We sample from this distribution `\(B\)` times and compute our new counterfactuals - Then we can look at the 2.5th and 97.5th percentiles - This will represent a 95% confidence interval - This algorithm is known as the .hi[parametric bootstrap] - Cf. .hi[nonparametric bootstrap] which is when we randomly re-sample from our data --- # Coding example: parametric bootstrap - Here's how we can get the confidence interval around the policy effect - Note: it's uncommon to see this, due to computational demands of just one cfl .scroll-box-12[ ```julia # now do parametric bootstrap Random.seed!(1234) invHfix = UpperTriangular(inv(H)) .- Diagonal(inv(H)) .+ UpperTriangular(inv(H))' # this code makes inv(H) truly symmetric (not just numerically symmetric) d = MvNormal(θ̂_mle_ad,invHfix) B = 1000 cfl_bs = zeros(8,B) for b = 1:B θ_draw = rand(d) Pb = plogit(θ_draw, X, Z, length(unique(y))) Pbs = 100*vec(mean(Pb'; dims=2)) θ_draw[end] = 0 P_cflb = plogit(θ_draw, X, Z, length(unique(y))) Pcfl_bs = 100*vec(mean(P_cflb'; dims=2)) cfl_bs[:,b] = Pcfl_bs .- Pbs end bsdiffL = deepcopy(cfl_bs[:,1]) bsdiffU = deepcopy(cfl_bs[:,1]) for i=1:size(cfl_bs,1) bsdiffL[i] = quantile(cfl_bs[i,:],.025) bsdiffU[i] = quantile(cfl_bs[i,:],.975) end modelfitdf.bs_diffL = bsdiffL modelfitdf.bs_diffU = bsdiffU display(modelfitdf) │ Row │ data_freq │ P │ P_cfl │ diff │ ew │ bs_diffL │ bs_diffU │ │ │ Float64 │ Float64 │ Float64 │ Float64 │ Float64 │ Float64 │ Float64 │ ├─────┼───────────┼─────────┼─────────┼───────────┼─────────┼───────────┼───────────┤ │ 1 │ 10.5976 │ 11.2549 │ 8.34334 │ -2.91158 │ 1.96627 │ -3.37791 │ -2.40627 │ │ 2 │ 5.24943 │ 6.21553 │ 4.98708 │ -1.22845 │ 1.85026 │ -1.46601 │ -1.0004 │ │ 3 │ 38.6462 │ 37.5457 │ 34.4537 │ -3.092 │ 1.71771 │ -3.72105 │ -2.4462 │ │ 4 │ 4.66067 │ 4.88623 │ 5.70078 │ 0.814551 │ 1.54756 │ 0.666758 │ 0.967763 │ │ 5 │ 1.54063 │ 1.80065 │ 1.62727 │ -0.173382 │ 1.75298 │ -0.214975 │ -0.135771 │ │ 6 │ 15.1525 │ 14.676 │ 15.123 │ 0.447092 │ 1.58918 │ 0.387452 │ 0.506462 │ │ 7 │ 18.3571 │ 17.3364 │ 23.3689 │ 6.03245 │ 1.42956 │ 4.82327 │ 7.20728 │ │ 8 │ 5.79588 │ 6.28457 │ 6.39589 │ 0.111316 │ 1.59501 │ 0.0795148 │ 0.143139 │ ``` ] --- # References .tiny[ Adams, R. P. (2018). _Model Selection and Cross Validation_. Lecture Notes. Princeton University. URL: [https://www.cs.princeton.edu/courses/archive/fall18/cos324/files/model-selection.pdf](https://www.cs.princeton.edu/courses/archive/fall18/cos324/files/model-selection.pdf). Arcidiacono, P., E. Aucejo, A. Maurel, et al. (2016). _College Attrition and the Dynamics of Information Revelation_. Working Paper. Duke University. URL: [https://tyleransom.github.io/research/CollegeDropout2016May31.pdf](https://tyleransom.github.io/research/CollegeDropout2016May31.pdf). Arcidiacono, P., J. Kinsler, and T. Ransom (2019). _Legacy and Athlete Preferences at Harvard_. Working Paper 26316. National Bureau of Economic Research. DOI: [10.3386/w26316](https://doi.org/10.3386%2Fw26316). Caucutt, E. M., L. Lochner, J. Mullins, et al. (2020). _Child Skill Production: Accounting for Parental and Market-Based Time and Goods Investments_. Working Paper 27838. National Bureau of Economic Research. DOI: [10.3386/w27838](https://doi.org/10.3386%2Fw27838). Delavande, A. and B. Zafar (2019). "University Choice: The Role of Expected Earnings, Nonpecuniary Outcomes, and Financial Constraints". In: _Journal of Political Economy_ 127.5, pp. 2343-2393. DOI: [10.1086/701808](https://doi.org/10.1086%2F701808). Fu, C., N. Grau, and J. Rivera (2020). _Wandering Astray: Teenagersâ€™ Choices of Schooling and Crime_. Working Paper. University of Wisconsin-Madison. URL: [https://www.ssc.wisc.edu/~cfu/wander.pdf](https://www.ssc.wisc.edu/~cfu/wander.pdf). Lang, K. and M. D. Palacios (2018). _The Determinants of Teachers' Occupational Choice_. Working Paper 24883. National Bureau of Economic Research. DOI: [10.3386/w24883](https://doi.org/10.3386%2Fw24883). Ransom, T. (2019). _Labor Market Frictions and Moving Costs of the Employed and Unemployed_. Discussion Paper 12139. IZA. URL: [http://ftp.iza.org/dp12139.pdf](http://ftp.iza.org/dp12139.pdf). Rust, J. (1987). "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher". In: _Econometrica_ 55.5, pp. 999-1033. URL: [http://www.jstor.org/stable/1911259](http://www.jstor.org/stable/1911259). ]


Current Events : Me
What’s up my life right now?
Last Updated: March 9th 2020
Work
- Working on an indie project with a friend while also experimenting with a few things! Will publish more about both projects by March 14th!
Life Experiences
- welp - coronavirus got me beat so now sticking this entire term out t home in GP - which is cool cuz it means more time with the fam
Information Diet
TV/Movie: Hot Ones (obsessed with this show), brooklyn 99, blacklist
Music: Divine, Em, Calma (song’s been stuck in my head for days)
What big problem am I thinking about/brainstorming right now?
- b/c of covid-19, what features/things would make remote life (work/play) at par if not better than real life? a lot of answers/extrapolations can be taken from the gaming community for this one probably


I'm configured to use {{ settings.baseUrl }}.
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| {{ timelineItem.text }} | {{ timelineItem.html|e }} | {% for attachment in timelineItem.attachments %} {% if attachment.contentType.startswith('image') %} {% else %} Download {% endif %} {% endfor %} |
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This synchronization tasks utilizes the Cisco EoX API and will automatically update the lifecycle state of the products from the configured queries.
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|
| | Министерство культуры Российской Федерации Портал Культура.рф Проект «Образы России» |
The memorial estate Arkhangelskoye
Regular park
There is a regular park in the center of estate, design combines rational principals of traditional “italian” terraced park and traditional “french” park with plain landscape and extended perspective. Nature and man-made groves of “english” park evolve into natural forest and frame panorama.
The regular park is symmetrically designed, it has main North – South axis and forms a system of of straight lines and geometric figures. The park has developed landscape architecture system: huge (240x70m.) grass rectangle of the Big parterre; “bosquets” – small groves of lawn surrounded by oval or square cropped lindens; “berso” arch galleries with trees grown in trellis cages and long espaliers of trees planted in compact ranks.
In the center of the northern part of the parterre one can see a fountain (1820s, “Cupid and swan” sculpture), In the southern part there is a pair of Borghese “Gladiators” (after antique original). The main axis from North to South was marked with memorial sculptures of Alexander II (1860) and Nicholas II (1896, both have not been preserved). There is the last architectural terrace to the south from the Big parterre and a descent which leads to the groves and river meadow. To the south from the Palace one can see a magnificent view of the old course of The Moskva River and a landscape of Lohin island on the other side of the river. Earlier there were two stove-houses, Pomerancevskaya and Lavrovaya (have not been preserved to present day), with rear collections of plants. Today there are sanatorium buildings (by V. Apishkov, 1934).
Культура.рф © Портал культурного наследия России


These examples will show you the basic usages of the Responsive Image Plugin.
These images support 5 different states. The only difference is the width calculation.
The left image is based on the windows viewport, the right is based on its surrounding
 tag.
Breakpoints start from 0px to 399px, 400px to 599px, 600px to 799px, 800px to 999px and large image above 1000px.
This code is used for both images. Only the data-container attribute is set for the right image.


{% extends "layout-pattern.html" %} {% set page_title = "Check your answers page" %} {% block page_contents %}
Play information back to users before they submit it.
By letting people check their answers you can:
There’s a coded example of this page in the GOV.UK Prototype Kit.
Make it clear that there is a task to perform on this page and that the transaction is not complete until they confirm that the information is correct.
Provide links back to the pages containing information they can change. The user should be returned to the ‘Check your answers’ page once they’ve updated the information (and any other questions triggered by their updated response).
Don’t just write the questions and answers out as they were originally given. Reword them for this particular format and context. For example, the individual elements of an address do not need labelling, and long questions can often be rewritten as shorter statements.
The submit button should fully state the action it performs, eg ‘Change your tax details’ or ‘Send your claim form’. You don’t need an explicit declaration checkbox as long as it’s made clear what will happen.
Use the 'visually-hidden' class to add hidden text to the ‘Change’ links, so that they make sense when read out of context by screen readers.
For example:
Change Producer name
These pages play back information entered by your users. In some cases you might need to obfuscate parts of the data to reduce the risk that it’s read by the wrong people.
Each service is different. Work with your security team to make sure that there’s an acceptable level of risk.
You can help improve this pattern by researching the following:
Update the discussion below with your findings.


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|
Class Summary |
| AttributePSVImpl |
Attribute PSV infoset augmentations implementation. |
| ElementPSVImpl |
Element PSV infoset augmentations implementation. |
| SchemaGrammar |
This class is to hold all schema component declaration that are declared
within one namespace. |
| SchemaGrammar.BuiltinSchemaGrammar |
|
| SchemaGrammar.Schema4Annotations |
A partial schema for schemas for validating annotations. |
| SchemaNamespaceSupport |
This class customizes the behaviour of the util.NamespaceSupport
class in order to easily implement some features that we need for
efficient schema handling. |
| SchemaSymbols |
Collection of symbols used to parse a Schema Grammar. |
| SubstitutionGroupHandler |
To store and validate information about substitutionGroup
INTERNAL: |
| XMLSchemaLoader |
This class implements xni.grammars.XMLGrammarLoader. |
| XMLSchemaValidator |
The XML Schema validator. |
| XMLSchemaValidator.ShortVector |
A simple vector for short s. |
| XMLSchemaValidator.XPathMatcherStack |
Stack of XPath matchers for identity constraints. |
| XSAnnotationImpl |
This is an implementation of the XSAnnotation schema component. |
| XSAttributeDecl |
The XML representation for an attribute declaration
schema component is an element information item
INTERNAL: |
| XSAttributeGroupDecl |
The XML representation for an attribute group declaration
schema component is a global element information item
INTERNAL: |
| XSAttributeUseImpl |
The XML representation for an attribute use
schema component is a local element information item
INTERNAL: |
| XSComplexTypeDecl |
The XML representation for a complexType
schema component is a element information item
INTERNAL: |
| XSConstraints |
Constaints shared by traversers and validator
INTERNAL: |
| XSDDescription |
All information specific to XML Schema grammars. |
| XSDeclarationPool |
This class is pool that enables caching of XML Schema declaration objects. |
| XSElementDecl |
The XML representation for an element declaration
schema component is an element information item
INTERNAL: |
| XSGrammarBucket |
A class used to hold the internal schema grammar set for the current instance
INTERNAL: |
| XSGroupDecl |
The XML representation for a group declaration
schema component is a global element information item
INTERNAL: |
| XSImplementationImpl |
Implements XSImplementation interface that allows one to retrieve an instance of XSLoader . |
| XSLoaderImpl |
An implementation of XSLoader which wraps XMLSchemaLoader. |
| XSMessageFormatter |
SchemaMessageProvider implements an XMLMessageProvider that
provides localizable error messages for the W3C XML Schema Language
INTERNAL: |
| XSModelGroupImpl |
Store schema model group declaration. |
| XSModelImpl |
Implements XSModel: a read-only interface that represents an XML Schema,
which could be components from different namespaces. |
| XSNotationDecl |
The XML representation for a NOTATION declaration
schema component is a global element information item
INTERNAL: |
| XSParticleDecl |
Store schema particle declaration. |
| XSWildcardDecl |
The XML representation for a wildcard declaration
schema component is an or element information item
INTERNAL: |


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To position elements on a page, use the position property.
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relative, absolute, fixed, or static
Once the position property is set, you could use the top, bottom, left, right properties.
relative positioning
The element is positioned relative to its normal position.
So left:50px adds 50 pixels to the element's left position relative to its normal position


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I CLICK SOLUTIONS Name – K.J.P.G.Perera Index – 120468J Role in the project team – System Analyst Areas of expertise – • Database management • Programming ( JAVA, C, C++)


Classes | |
| struct | DataBuffer |
| struct | ImageDataBuffer |
| And now we have our container. More... | |
Public Member Functions | |
| void | findClosestFrontier (int pixelX, int pixelY) |
| GazeboRetrieve (ros::NodeHandle nh) | |
| And now we have our container. More... | |
| void | imageCallback (const sensor_msgs::ImageConstPtr &msg) |
| void | laserCallback (const sensor_msgs::LaserScanConstPtr &msg) |
| void | odomCallback (const nav_msgs::OdometryConstPtr &msg) |
| bool | requestGoal (a3_help::RequestGoal::Request &req, a3_help::RequestGoal::Response &res) |
| void | seperateThread () |
| ~GazeboRetrieve () | |
Private Attributes | |
| DataBuffer | buffer |
| ros::ServiceClient | client_ |
| Client object for the reqest_goal service. More... | |
| ros::Publisher | cmd_vel_pub_ |
| Object of the /cmd_vel topic. More... | |
| int | count_ |
| A counter to allow executing items on N iterations. More... | |
| cv_bridge::CvImagePtr | cvPtr_ |
| image_transport::Publisher | image_pub_ |
| ImageDataBuffer | imageBuffer |
| image_transport::ImageTransport | it_ |
| ros::NodeHandle | nh_ |
| ROS node object. More... | |
| double | resolution_ |
| Size of OgMap in pixels. More... | |
| ros::ServiceServer | service_ |
| ros::Subscriber | sub1_ |
| Subscription object for the odom topic. More... | |
| ros::Subscriber | sub2_ |
| Subscription object for the base_scan_1 topic. More... | |
| image_transport::Subscriber | sub3_ |
Class GazeboRetrive inherits from a3_help::RequestGoal.
That is, a3_help is the ros node or package name and RequestGoal is the class name or type.
Also, this node shows some connections and publishing images.
Attend to LATER, Request & Responce structs:
1) Should I move RequestGoal() into RequestGoal.h as member function. This seems incorret as RequestGoal() seems a better fit to GazeboRetrieve class.
2) Leave as is but doxygen dosent work properly, where RequtestGoal.h declares a class RequestGoal and RequestGoal() is defined in GazeboRetrieve class.
3) Define Request and Responce stucts as part of GazeboRetrieve class and remove the need for RequestGoal.h.
Definition at line 81 of file sample.cpp.
|
inline |
And now we have our container.
Subscription object for base_scan_1 topic.
Definition at line 170 of file sample.cpp.
|
inline |
Definition at line 243 of file sample.cpp.
|
inline |
Determines the frontier closest to the current robot location.
Definition at line 255 of file sample.cpp.
|
inline |
Below code pushes the image and time to a deque, to share across threads.
Definition at line 577 of file sample.cpp.
|
inline |
Below sample cicrulates through the scan and finds closest point to robot.
Definition at line 505 of file sample.cpp.
|
inline |
Definition at line 464 of file sample.cpp.
|
inline |
RequestGoal is the callback function for the request_goal service.
This callback function does not return till all code within it is executed. That is there is no queuing of calls(as per publishing and subscribing to ros topics) to this callback function.
It moves the robot to its new goal (req.x, req.y, req.angle): the goal is specified in the service client code that calls this callback function, more specifically in the req structure.
The robot is moved in the x,y plane relative to the centre of the ogMap.
A call to this request_goal service returns an indication of success or failure of the robot move(ie callback() function return value).
Definition at line 338 of file sample.cpp.
|
inline |
The main thread (main()) allows aquiring of robot related data in realtime. This thread, seperateThread(), does the processing of this data in non-realtime. Just when the system/cpu schedular allows it.
LATER: The processing involves???
The below gets the current Ros Time
Lock image buffer, take one message from deque and unlock it
Definition at line 625 of file sample.cpp.
|
private |
Definition at line 146 of file sample.cpp.
|
private |
Client object for the reqest_goal service.
On defeniton creates service server and its advertising over ROS.
Definition at line 117 of file sample.cpp.
|
private |
Object of the /cmd_vel topic.
When we publish to this topic we are moving the robot.
Definition at line 93 of file sample.cpp.
|
private |
A counter to allow executing items on N iterations.
Definition at line 128 of file sample.cpp.
|
private |
Definition at line 106 of file sample.cpp.
|
private |
Definition at line 88 of file sample.cpp.
|
private |
Definition at line 165 of file sample.cpp.
|
private |
Definition at line 87 of file sample.cpp.
|
private |
ROS node object.
Definition at line 85 of file sample.cpp.
|
private |
Size of OgMap in pixels.
Definition at line 129 of file sample.cpp.
|
private |
Object for the reqest_goal service.
The callback function of this service is RequestGoal().
Definition at line 112 of file sample.cpp.
|
private |
Subscription object for the odom topic.
The callback function for this object is odomCallback().
Definition at line 98 of file sample.cpp.
|
private |
Subscription object for the base_scan_1 topic.
The callback function for this object is laserCallback().
Definition at line 103 of file sample.cpp.
|
private |
Definition at line 105 of file sample.cpp.


BridgeBetween Cloud And IDE
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Developers can share the same development environment and conduct joint debugging.
ExtensionOf Kubernetes
Amazing enhancement of Kubernetes and Helm, developers code on Kubernetes with on friction.
SpotlightOn Explore MicroServices
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Integrate the following sensors and functionality:
2 × Parallax servo --> movement
3 × Digital line sensor --> line tracking
1 × IR phototransistor --> robot detection
1 × Microphone --> 660 Hz detection
3 × IR range finder --> wall detection
Demonstrate a robot that successfully circles an arbitrary set of walls
through right-hand wall following, while performing line tracking, and
detection and avoidance for other robots and walls.
Wall Detection
We installed three IR range finders on our robot
Pointing straight ahead (in direction of movement)
To the left
To the right
This arrangement allows us to detect both the presence and absence of walls around our robot
We created two functions (with fairly self explanatory names) that read data from the range finders to detect walls:
detect_wall_3in(int pin)
detect_wall_6in(int pin)
NOTE - we experimented with this setup to calibrate the threshold values
Our IR range finder code is as follows:
#define VAL_6_INCH 100
#define VAL_3_INCH 200
#include "ir_rangefinder.h"
#include
int read_range_sensor(int pin){
return analogRead(pin);
}
bool detect_wall_6in(int pin){
int val = read_range_sensor(pin);
if(val > VAL_6_INCH)
return true;
else
return false;
}
bool detect_wall_3in(int pin){
int val = read_range_sensor(pin);
if(val > VAL_3_INCH)
return true;
else
return false;
}
System Integration - Attempt #1
Create a loop that runs all processes one-after-another
Begin by running the 660 Hz detection using the microphone circuit and mic FFT
Run this continuously until 660 Hz is detected 5 consecutive times
When this occurs, advance to the rest of the code and begin movement
This code will not be run again
Perform line tracking
Perform wall detection
Perform IR robot detection
Analysis:
Results are erratic; solution only partially works
Sometimes line tracking suddenly fails
Sometimes wall detection is too slow to respond
Sometimes IR hat dection is too slow to respond
Hypothesis = the IR_hat FFT function call is affecting these processes
The FFT library manually sets the ADC control registers
This breaks the analogRead() function from the Arduino library
Most of our functions utilize analogRead()
Fixing the FFT
The Open Music Labs Arduino FFT changes values in the following ADC control registers
ADCSRA
ADMUX
TIMSK0
DIDR0
This causes the PWM library’s timer to not function correctly since it uses the same timer registers
As a result, the servos do not behave in the intended manner
Our solution stores the ADC register values before calling the FFT function
We restore the ADC registers after the FFT function completes
System Integration - Attempt #2
GOAL: a robot that recognizes 660 Hz, does line tracking, and avoids robots and walls
After implementing the afromentioned FFT code fix, we further refined our main loop
Wait to begin operations until detect_660hz() returns TRUE 5 consecutive times
The green LED indicates that 660 Hz was detected
This is run in a separate loop from the below code
It is never run again
Check the line sensors and range finders - our conditional logic is:
// wall detected at intersection
if ((sensorStatus[0] == 0) && (sensorStatus[1] == 0) && (sensorStatus[2] == 0) && detect_wall_6in(3) ) {
if (detect_wall_6in(1)){
turnLeftIntersection(servo_L, servo_R);
}
else{
turnRightIntersection(servo_L, servo_R);
}
}
// wall detected but not at an intersection
else if (detect_wall_3in(3)) {
turnLeft(servo_L, servo_R);
}
// no wall detected --> just track the line
else if (sensorStatus[0] == 0) //turn Right
adjustRight(servo_L, servo_R, 85);
else if (sensorStatus[2] == 0) //turn Left
adjustLeft(servo_L, servo_R, 85);
else {
moveForward(servo_L, servo_R);
}
Run detect_6080hz() to check for other robots
This process is run in a while loop
Our robot will stop moving and continuously check for the presence of another robot
The red LED indicates that 6080 Hz is detected
When no robot is detected anymore, our robot will resume normal operations
NOTE - The IR detection circuit does correctly recognize the IR hat (another robot) and stop our robot
The physical location of the phototransistor, however, is obstructed by other components
This explains the difficulty Kenneth has getting the IR to be recognized
We plan on moving the phototransistor to a more optimal, unobstructed location in the front of our robot


#include <XSECTXFMInputSource.hpp>
Collaboration diagram for XSECTXFMInputSource:
This class provides a wrapper for a TXFMList. It is used to provide an input to the Xerces Parser.
Public Member Functions | |
Constructors and Destructors | |
| XSECTXFMInputSource (TXFMChain *lst, bool deleteWhenDone=true) | |
| Construct around an existing transform list. | |
| virtual | ~XSECTXFMInputSource () |
| Destructor. | |
Stream management methods | |
| XERCES_CPP_NAMESPACE_QUALIFIER BinInputStream * | makeStream () const |
| Interface method. |
|
|
Construct around an existing transform list.
|
|
|
Destructor. Delete the object. If deleteWhenDone was set during construction, will delete the chain if it has not already been done. |
|
|
Interface method. Returns an InputStream that can be read by the parser |


microsoft office 2008 mac problems - Extensions
Upgrading to Office 2011 for Mac | 401 Consulting - Web Site ... May 29, 2012 . Q: The main question is Will this upgrade my earlier Office 2008, or do I . editions come with Outlook now) and sidestep the whole issue. . for help with upgrading Microsoft Office 2008 for Mac to 2011 will be able to find it! http://www.401consulting.com/2012/05/upgrading-to-office-2011-for-mac/
You can develop your own extensions
using the case western business school.
Syntax-Highlighting Addons
Reset Microsoft Office 2008 (Mac) May 31, 2009 . If user is having problem with font then delete "Office Font Cache (12)", located in the same folder as Microsoft Office 2008 Settings.plist. Office . http://kb.wisc.edu/page.php?id=10168
Microsoft Office for Mac 2008 and 2011 updated with security fixes ... Nov 14, 2012 . Microsoft Office for Mac 2008 and 2011 updated with security fixes, . This update fixes an issue in which automatic configuration did not work . http://appleinsider.com/articles/12/11/14/microsoft-office-for-mac-2008-and-2011-updated-with-security-fixes-improvements in one installer (526 kb).
Database Problem with Office 2008 for Mac I have used Office '04 on the Mac for years. I picked up Office '08 this . I also have the exact problem. All I did was updates Office 04 to 2008, and . https://getsatisfaction.com/microsoft/topics/database_problem_with_office_2008_for_mac
So what's the story with MathType and Microsoft Office 2008? Microsoft omitted VBA from Mac Office 2008, creating problems for MathType users and many others. VBA (Visual Basic for Applications) has been a . http://www.dessci.com/en/products/mathtype_mac/office2008.htm
Microsoft Office 2008 for Mac - Wikipedia, the free encyclopedia Microsoft Office 2008 for Mac is a version of the Microsoft Office productivity suite . There is no such problem in Word 2004 or X. This issue has not been fixed in . http://en.wikipedia.org/wiki/Microsoft_Office_2008_for_Mac
A simple JavaScript Formatter (47kb)Support for Microsoft Office for Mac 2011 and 2008 Microsoft Home Page · Support. Account. Sign in. Select . Support for Microsoft Office for Mac 2011 and 2008. Help and support for Microsoft Office for Mac. http://support.microsoft.com/ph/12853
Install and Update Errors - Office Mac Help Site Microsoft KB: I can't install Office 2008 for Mac updates . 2) If you experience a problem where the updater causes the Setup Assistant to continuously launch. http://www.office.mvps.org/error/install_update.html CertMaker for iOS and Android
Known issues with Office for Mac on MacOS 10.7 ... - Microsoft Support Jul 23, 2011 . Microsoft will continue to work closely with Apple to address problems that may occur with Office for Mac 2008 and 2011 and Lion OS. http://support.microsoft.com/kb/2586538
Windows 8 AppContainer Loopback Utility
The Mac Forum » Microsoft Office for Mac OS X updates released Microsoft Office 2011 for Mac update version 14.3.2 for Microsoft Office 2011 for Mac . The most recent update for Microsoft Office 2008, 12.3.6, is a cumulative . http://mac.blogs.utsa.edu/2011/09/microsoft_office_updates/ Download
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Traffic Differ
Download Microsoft Office 2008 for Mac 12.1.5 Update from Official ... Dec 9, 2008 . Download Microsoft Office 2008 for Mac 12.1.5 Update at the Official . If you experience problems opening Office applications after you install . http://www.microsoft.com/en-us/download/details.aspx?id=2535 Download now (47kb).
SAZ Clipboard
A list of known issues with Microsoft Office 2008 - Mac OS X Hints Finally, I uncovered one more issue while posting this hint -- the Help . This alone pretty much renders Mac Office 2008 as *NSFW* (Not Safe . http://hints.macworld.com/article.php?story=20080117144249295
Gallery
The Gallery extension (50kb) Microsoft Office 2008 for Mac - CNET Download.com Mar 13, 2013 . Bottom line: Office for Mac 2008 may be the best pick for business users, but most . Unlike Microsoft Office 2007, the interface changes don't look radically . Office 2008 has only presented problems, but I use mostly Word. http://download.cnet.com/Microsoft-Office-2008/3000-18483_4-189542.html
Office for Mac update error - Microsoft Support Describes a problem when you try to install an update for Office for Mac 2008 or 2011, but . Method 4: Check if Microsoft Office 2008 or 2011 is in Applications . http://support.microsoft.com/kb/969065
AnyWHERE (sample)
The AnyWHERE extension (40kb) Microsoft Office 2008 for Mac 12.2.0 (SP2) Update ... Jul 20, 2009 . Prerequisites: You must have Microsoft Office 2008 for Mac 12.1.0 Update . This update fixes an issue that causes some encrypted or digitally . http://www.officeformachelp.com/2009/07/microsoft_office_2008_for_mac_1220_update/
RulesTab (sample)
"Microsoft <program> cannot be opened because of a problem ... Describes an error that occurs when you open a Microsoft Office for Mac 2008/ 2011 program that occurs when the program was moved or duplicated. Provides . http://support.microsoft.com/kb/2431353
Privacy Scanner
The Privacy Scanner
(41kb) Is Office for Mac 2008 compatible with OS X Lion (10.7 ... Jul 23, 2011 . Microsoft will continue to work closely with Apple to address problems that may occur with Office for Mac 2008 and 2011 and Lion OS. http://answers.microsoft.com/en-us/mac/forum/macoffice2008-macstart/is-office-for-mac-2008-compatible-with-os-x-lion/78b5d145-6279-4151-8b63-f9e6d81c6039
Content-Blocking (sample)
The Content Blocker
sample (11kb) Office 2008 for Mac error: "Microsoft Office 2008 cannot start ... When you try to start any Microsoft Office 2008 for Mac program, you receive an error message . This issue can occur when the following conditions are true: . http://support.microsoft.com/kb/959253
Image-Flipper (sample)
The Image
Flipper sample (6kb) Microsoft Office for Mac Downloads and Updates | Office For Mac May 13, 2008 . Microsoft Office 2008 for Mac Service Pack 2 (12.2.0) > . For more information about the issue, see I can't install Office 2008 for Mac updates. http://www.microsoft.com/mac/downloads?pid=Mactopia_Office2008&fid=395D1487-A3A6-4106-A0F8-4D6E1D6D89D2
3rd-Party Extensions
Check for software updates automatically - mac.microsoft.com Microsoft AutoUpdate for Mac, which comes with Office, can keep the whole suite . I'm having the same problem as AK Suresh trying to download Office 2008 . http://mac2.microsoft.com/help/office/14/en-us/word/item/ffe35357-8f25-4df8-a0a3-c258526c64ea
How to completely remove Office 2008 for Mac - Microsoft Support Contains detailed steps to follow to uninstall Office 2008 for Mac. http://support.microsoft.com/kb/2500821
neXpert Performance Report Generator
Description of the Microsoft Office 2008 for Mac 12.3.4 Update Sep 19, 2012 . Describes the Microsoft Office 2008 for Mac 12.3.4 Update that was released . This update fixes an issue that may cause Excel 2008 for Mac to . http://support.microsoft.com/kb/2721014
StresStimulus
Download Microsoft Office 2008 for Mac Service Pack 1 (12.1.0 ... May 13, 2008 . Download Microsoft Office 2008 for Mac Service Pack 1 (12.1.0) at the . For more information about the issue, see I can't install Office 2008 for . http://www.microsoft.com/en-us/download/details.aspx?id=7799
Watcher - Passive Security Auditor
Word for Mac error: "Microsoft Word has encountered a problem and ... You may see this error when you start Microsoft Word for Mac 2011 or 2008: Microsoft Word has encountered a problem and needs to close. We are sorry for the . http://support.microsoft.com/kb/2693802
Download Microsoft Office 2008 for Mac 12.3.0 Update from Official ... Jun 14, 2011 . Download Microsoft Office 2008 for Mac 12.3.0 Update at the Official . If you experience problems opening Office applications after you install . http://www.microsoft.com/en-us/download/details.aspx?id=26353
Ammonite - Security Scanner
Will Office 2008 run on OS X Lion? - Microsoft Community Jul 2, 2011 . Microsoft has made no announcements regarding Office 2008 and Lion but keep an eye of the Office for Mac blog. I do know that Office 2008 is . http://answers.microsoft.com/en-us/mac/forum/macoffice2008-macstart/will-office-2008-run-on-os-x-lion/d691e0e6-293b-497a-b20d-697dba77d37a
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x5s - Automated XSS Security Testing AssistantMicrosoft Office 2008 (Mac) - Download Nov 15, 2012 . Note: This demo of Microsoft Office for Mac 2008 has now been removed by . Help works in all languages - This update resolves an issue that . http://microsoft-office-mac-2008-trial.en.softonic.com/
- Detecting where safe encodings were not applied to emitted
user-inputs
- Detecting where Unicode character transformations might bypass
security filters
- Detecting where non-shortest UTF-8 encodings might bypass security
filters
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intruder21
Word 2008 for Mac crashes when you try to start ... - Microsoft Support This problem occurs when Word 2008 for Mac first starts. At this point, it will try to import the previous settings from earlier versions of Microsoft Word for Mac. http://support.microsoft.com/kb/948489
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HTML Inspector
How to update Office for Mac 2008 on Mac OS X ... - Microsoft Support Sep 30, 2011 . You install Office for Mac 2008 from the original DVD installation media. . Because of the compatibility issue, Microsoft AutoUpdate will not . http://support.microsoft.com/kb/2624981
Description of the Office 2008 for Mac 12.0.1 ... - Microsoft Support Mar 11, 2008 . Resolves a security vulnerability that exists in Microsoft Office 2008 for Mac . This update fixes an issue in Mac OS X 10.5 Leopard that causes . http://support.microsoft.com/kb/948057
WCF Binary-Encoded Message Inspector
Description of the Microsoft Office 2008 for Mac 12.2.1 Update Aug 6, 2009 . Resolves an issue that prevents users from opening some Office documents after they install Office 2008 for Mac SP2 Update. http://support.microsoft.com/kb/974170
Chad Sowald's Request-To-Code
Description of the Microsoft Office 2008 for Mac 12.1.1 Update Jun 24, 2008 . "Microsoft Office 2008 Update" doesn't understand the <event sysodisA> message. Cause This issue may occur if any Office for Mac . http://support.microsoft.com/kb/953822
Eyal's Extensions
- hampton bay harbor breeze fan has written two extensions:
Thomas Deml's Export WCAT Script extension
Description of the Microsoft Office 2008 for Mac 12.3.3 Update May 8, 2012 . Describes the Microsoft Office 2008 for Mac 12.3.3 Update that was released on . Microsoft has confirmed that this is a problem in the Microsoft . http://support.microsoft.com/kb/2665346
Per-Response Latency Extension
Description of the Microsoft Office 2008 for Mac 12.3.2 Update Dec 13, 2011 . Describes the Microsoft Office 2008 for Mac 12.3.2 Update that was released on . Microsoft has confirmed that this is a problem in the Microsoft . http://support.microsoft.com/kb/2644354
WPAD Server
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XML Request InspectorDescription of the Microsoft Office 2008 for Mac 12.3.5 Update Nov 13, 2012 . Describes the Microsoft Office 2008 for Mac 12.3.5 Update that was released on November 13, 2012. http://support.microsoft.com/kb/2764048 XML DataSet InspectorOffice for Mac Support | Office For Mac - Microsoft Find Help & Resources for all Office for Mac Products. Installation & Activation FAQ, Purchasing . Microsoft Office 2008 updates. Microsoft Office 2004 updates . http://www.microsoft.com/mac/support
©2013 Telerik
|


{%extends 'base.html' %} {% block body %} Login {% from "includes/_formhelpers.html" import render_field %} {% include 'includes/_messages.html' %} {{render_field(login_form.username, class_="form-control")}} {{render_field(login_form.password, class_="form-control")}} {{render_field(login_form.submit2)}} Sign Up {% from "includes/_formhelpers.html" import render_field %} {{render_field(reg_form.name, class_="form-control")}} {{render_field(reg_form.email, class_="form-control")}} {{render_field(reg_form.username, class_="form-control")}} {{render_field(reg_form.password, class_="form-control")}} {{render_field(reg_form.confirm, class_="form-control")}} {{render_field(reg_form.submit1)}} {% endblock %}


Kevin Hart shares exhausting workout routine he continues recovery after crash
Kevin Hart showed his fans the strenuous workout routine he has to do to help get fighting fit after his terrifying car crash in September.
The comedian posted an Instagram video of all the sets and exercises he has to complete in order to make sure his back and legs are back to their healthy state.
He captioned the clip: ‘Rebuilding people….I’m not trying to get back to where I was…I’m trying to reach new levels of greatness….not for you guys tho…I’m trying to reach these new levels for MYSELF.
‘I want to inspire & motivate people to challenge themselves to be great. We all have greatness within…it’s up to us to tap into it. Nobody knows what your are capable of more than YOU.
‘I can’t wait to show ME the new levels that we are about to reach!!!! A positive mindset & positive outlook on life are all you need…….you just have to look for it. It’s a lifestyle…. @getvitahustle #LiveLoveLaugh #HustleHart’
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The Night School actor broke his back in three places after crashing his vintage car, leaving him needing physiotherapy to get him walking again.
The actor, 40, recently explained that his life changing in a matter of seconds gave him a new perspective after seeing how quickly things could end.
He said on his first Sirius XM Laugh Out Loud show since the accident: ‘For me, I’m a different version of myself. This ain’t got nothing to do about going to church… It’s not spiritual, spiritual is the wrong word.
‘You’re more present. More aware… It’s all a joke until you get smacked with that real life reality.’
Kevin was forced to undergo emergency surgery on his back with a gruelling recovery over several weeks.
He admitted that it was ‘humbling’ to be left so vulnerable, especially when he needed the help of his wife, Eniko Hart, while going to the toilet.
Kevin explained: ‘I could not f***ing move. I could not wipe my a**… I literally I couldn’t do none of that.
‘It makes you realise… you really are helpless. There was nothing I could do.’
Got a showbiz story?
If you've got a story, video or pictures get in touch with the Metro.co.uk Entertainment team by emailing us<EMAIL_ADDRESS>calling 020 3615 2145 or by visiting our Submit Stuff page - we'd love to hear from you.


--- layout: default title: Contributors permalink: /users-contributors ---
The top 20 repositories with the most contributors.
The top 20 organizations with the most contributors.


@(form: Form[_root_.forms.PersonalDetailsForm.Data])(implicit messages: Messages) @import helpers.CSRFieldConstructor._ @import views.html.widgets.yesNoRadioWithTogglePanel
If you completed SDIP this year and received a Fast Pass, you won't need to do the online tests (online exercises, e-tray and video interview).
Schemes that require extra information or a numerical test will need you to complete these sections before attending the assessment centre.


Netflix is an American media-services provider and production company. As of April 2019, Netflix had over 148 million paid subscriptions worldwide, with 60 million of them from the United States. The New York offices of Netflix is currently hiring for a IT Technician,they will be responsible for a multitude of IT operational tasks such as imaging PC and Mac laptops,
Dell Inc., which operates under the brand name Dell, is an American multinational computer technology company that develops, sells, repairs, and supports computers and related products and services they are hiring for an IT Support Specialist the team receives, assesses, troubleshoots and escalates support requests to enable their day-to-day operations.
Amazon.com, Inc , is an American multinational technology company based in Seattle that focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence. It is considered one of the Big Four tech companies, along with Google, Apple, and Facebook. The position they are looking to hire is for an IT Manager which duties include providing 24x7 global IT support to Amazon Operations, including Fulfillment, Sortation, Logistics, and Last Mile.


|
||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |
See:
Description
| Interface Summary | |
|---|---|
| ChunkPredicate | Decides if another chunk "matches", according to some criterion |
| Class Summary | |
|---|---|
| ChunkCopyBehaviour | Chunk copy policy to apply when copyng from a pngReader to a pngWriter. |
| ChunkHelper | |
| ChunkRaw | Raw (physical) chunk. |
| ChunksList | All chunks that form an image, read or to be written. |
| ChunksListForWrite | |
| PngChunk | Represents a instance of a PNG chunk. |
| PngChunkBKGD | bKGD Chunk. |
| PngChunkCHRM | cHRM chunk. |
| PngChunkGAMA | gAMA chunk. |
| PngChunkHIST | hIST chunk. |
| PngChunkICCP | iCCP chunk. |
| PngChunkIDAT | IDAT chunk. |
| PngChunkIEND | IEND chunk. |
| PngChunkIHDR | IHDR chunk. |
| PngChunkITXT | iTXt chunk. |
| PngChunkMultiple | PNG chunk type (abstract) that allows multiple instances in same image. |
| PngChunkOFFS | oFFs chunk. |
| PngChunkPHYS | pHYs chunk. |
| PngChunkPLTE | PLTE chunk. |
| PngChunkSBIT | sBIT chunk. |
| PngChunkSingle | PNG chunk type (abstract) that does not allow multiple instances in same image. |
| PngChunkSkipped | Pseudo chunk type, for chunks that were skipped on reading |
| PngChunkSPLT | sPLT chunk. |
| PngChunkSRGB | sRGB chunk. |
| PngChunkSTER | sTER chunk. |
| PngChunkTEXT | tEXt chunk. |
| PngChunkTextVar | Superclass (abstract) for three textual chunks (TEXT, ITXT, ZTXT) |
| PngChunkTextVar.PngTxtInfo | |
| PngChunkTIME | tIME chunk. |
| PngChunkTRNS | tRNS chunk. |
| PngChunkUNKNOWN | Placeholder for UNKNOWN (custom or not) chunks. |
| PngChunkZTXT | zTXt chunk. |
| PngMetadata | We consider "image metadata" every info inside the image except for the most basic image info (IHDR chunk - ImageInfo class) and the pixels values. |
| Enum Summary | |
|---|---|
| ChunkLoadBehaviour | Defines gral strategy about what to do with ancillary (non-critical) chunks when reading |
| PngChunk.ChunkOrderingConstraint | Possible ordering constraint for a PngChunk type -only relevant for ancillary chunks. |
Contains the code related to chunk management for the PNGJ library.
Only needed by client code if some special chunk handling is required.
|
||||||||
| PREV PACKAGE NEXT PACKAGE | FRAMES NO FRAMES |


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Dessert
Name


remove-alignment-gaps <species> <alignment>
Remove from an alignment all columns that contain a gap in the specified species.
The name of a species present in the alignment for which gaps should be removed.
The name of a file containing a DNA or protein sequence alignment in clustalw format. The alignment can be read from standard input if a "-" is given instead of a file name.
The alignment, with the remaining columns that don't have gaps in the specified species, is written to standard output.


(
Dataset Description
|
Station List
)
Horizontal extent:
Horizontal subset:
Lat/lon box
Lat/lon point
Stations
Comma-separated list of stations
all
Time subset:
Output format:


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This story introduces the Nifty Top 50 Index. It lists the stocks that form this index and the various industries these stocks belong to. Then, it goes on to analyze various aspects of a Market Index, in the backdrop of the COVID-19 Pandemic in India and its impact on the Index.
This bar plot shows number of stocks across different industries. The annotations list the Symbols of the stocks in each industry, as comma-separated values.
Volatility is a statistical
measure of the dispersion of returns for a given market index (or security). Higher volatility indicates higher
risk.
In this line graph with dual axes, we try to find correlation between number of
active COVID-19 cases and the Volatility of NIFTY-50 Index:
Performance-based
Index provides investors with a more accurate depiction of the performance to manage risk and position
sizing effectively.
In this line graph with dual axes, we try to find correlation between number of
active COVID-19 cases and the Performance of NIFTY-50 Index:
In this multi-line graph, the performance of stocks, by Industry, is plotted. This chart allows viewing the trends of each of the Industries, using the selection widget on the right. Hover on the number or colored-rectangle of an Industry to highlight its trend in the chart.
Volume Weighted Average Price (VWAP)
is a trading benchmark that provides traders with insight into both the trend and value of a security.
This form allows to drill-down further to understand the VWAP of each Stock in a given industry, during the
COVID-19 pandemic. The points on the graph provide the actual values of VWAP at regular intervals in the
duration.
Through this story, I attempted to analyze the implications of COVID-19 pandemic on one of the important Market Indices in India, NIFTY-50 Index. The story visualizes various aspects of a Market Index in the backdrop of the pandemic and documents the observations.
I have used an interactive slide show narrative structure to
Each scene defines the aspect being visualized, its importance from the point of view of an investor or trader. The annotations in the chart highlight important events to draw user's focus to the aspect being analyzed, during the event. The observations of the author have been documented for the viewers to relate further. The navigation links on the top of the charting area help the user navigate between scenes.
There are five scenes in this story.
Annotations are used to mark major events during the pandemic to draw the attention of the viewer to the behavior of the aspect under observation, in each scene where the aspects are analyzed.
Annotations are also used in the first scene to display the stocks that belong to a particular industry.
The following parameters drive the narrative visualization:
The following triggers prompt the user to perform an action to either change the state of the visualization or enhance a particular scene:


Structure
| Namespaces | 5 | |
| Interfaces | 0 | |
| Traits | 0 | |
| Classes | 9 | |
| Abstract Classes | 0 | (0%) |
| Concrete Classes | 9 | (100%) |
| Methods | 32 | |
| Scope | ||
| Non-Static Methods | 32 | (100%) |
| Static Methods | 0 | (0%) |
| Visibility | ||
| Public Method | 25 | (78.13%) |
| Non-Public Methods | 7 | (21.88%) |
| Functions | 0 | |
| Named Functions | 0 | (0%) |
| Anonymous Functions | 0 | (0%) |
| Constants | 9 | |
| Global Constants | 0 | (0%) |
| Class Constants | 9 | (100%) |
Tests
| Classes | 9 | |
| Methods | 26 |
Size
| Lines of Code (LOC) | 1282 | |
| Comment Lines of Code (CLOC) | 577 | (45.01%) |
| Non-Comment Lines of Code (NCLOC) | 705 | (54.99%) |
| Logical Lines of Code (LLOC) | 244 | (19.03%) |
| Classes | 100 | (40.98%) |
| Average Class Length | 6 | |
| Average Method Length | 3 | |
| Functions | 90 | (36.89%) |
| Average Function Length | 0 | |
| Not in classes or functions | 54 | (22.13%) |
Complexity
| Cyclomatic Complexity / LLOC | 0.05 | |
| Cyclomatic Complexity / Number of Methods | 0 |
Dependencies
| Global Accesses | 3 | |
| Global Constants | 0 | (0%) |
| Global Variables | 3 | (100%) |
| Super-Global Variables | 0 | (0%) |
| Attribute Accesses | 35 | |
| Non-Static | 35 | (100%) |
| Static | 0 | (0%) |
| Method Calls | 126 | |
| Non-Static | 123 | (97.62%) |
| Static | 3 | (2.38%) |


Anna's Map Album
Current location: Step.17 of Sydney. Australia
Total Steps: x Total Goals: x
View Class Ranking


{% extends "census/base.html" %} {% load static %} {% block content %}
Here is a list of the copies we think your institution holds.
Do you actually hold these copies?
Please choose 'Yes' or 'No.'
When you have finished for this session, please click on the button below:
| Copies at {{ affiliation }} | Held by library? | |
|---|---|---|
| {{ copy.issue.edition.title }} ({{ copy.issue.year }}) -- STC/Wing: {{ copy.issue.STC_Wing }} |


Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Serves 4
This recipe is certainly exotic – honey and five-spice chilli guinea fowl served with a fresh fruit salsa splashed with soy sauce. If you can source one, serve in a banana leaf to impress.
Preheat the oven to 200C/180C (fan)/Gas 6. To prepare the guinea fowl, turn the bird onto its breast on a sturdy chopping board and cut carefully on either side of the backbone with good scissors or poultry shears. Discard the bone. Cut off the end of the foot joints and wing tips and discard.
Open the guinea fowl out and place on the board so that the breast side is facing upwards. Press down heavily with the palms of your hands to break the breastbone and flatten the bird as evenly as possible. This will help it cook more quickly.
Drizzle a baking tray with one tablespoon of the oil and place the guinea fowl on top. Rub all over with the remaining oil and tuck in the legs and wings.
Mix the crushed chillies, five-spice, sea salt and lots of freshly ground black pepper in a small bowl. Sprinkle over the guinea fowl and rub into the skin with your hands. Roast the guinea fowl for 20 minutes.
While the guinea fowl is cooking, put the pineapple on a board and cut off the top and bottom. Remove the prickly skin with a sharp knife and dig out any ‘eyes’ with the tip of your knife. Cut the pineapple lengthways into sixths and remove the central core. Cut the pineapple into roughly 1.5cm/¾in triangle slices and put in a bowl.
Peel the cucumber and cut lengthways in half. Cut into 1cm/½in slices and add to the pineapple. Bash the back of the pomegranate with a wooden spoon to dislodge the seeds – you may need to help some of them out with a knife or spoon. Put the seeds and any juice in a bowl. Mix the honey and soy sauce in a small bowl.
Take the bird out of the oven and brush with the honey mixture. Return to the oven for a further 10-15 minutes, or until thoroughly cooked, golden-brown and glossy. (The juices should run clear when the thickest part of one of the thighs is pierced with a skewer.) While the bird continues to roast, trim the coriander and discard the stalks. Pick the leaves off the mint stalks. Peel and finely slice the red onion. Put the herbs and onion to one side.
Transfer the guinea fowl to a board and leave to rest for a few minutes while the dressing is made. Tip the contents of the baking tray into a heatproof bowl and leave to stand for five minutes.
Stir the fresh lime juice into the pan juices, just a little at a time, tasting between additions. You want the dressing to be tangy but not sour. Season the dressing with a little salt and pepper and an extra dash of soy sauce if you like.
Carve the guinea fowl into chunky pieces and arrange on a clean banana leaf, or large serving platter, with the pineapple and cucumber. Scatter the herbs and onion on top. Sprinkle with the pomegranate seeds and any juice and toss very lightly together. Drizzle over the lime dressing and serve immediately while the guinea fowl is warm.


The following exercises guide you through defining and building a database, using the projects you created in the previous lesson.
When you define a database, you specify one or more Google Earth Enterprise Fusion projects that Google Earth Enterprise Fusion combines into a single self-contained world that is flyable in Google Earth EC. You can select up to three projects for a database--one of each type:
Because the majority of your efforts involve defining and configuring different projects for inclusion in your database, it is relatively fast to define a database once the projects are created. You simply select the projects that comprise the database and give it a name.
ASSET_ROOT/Projects/Vector
.
Note: The selection in the Type drop-down list near the bottom of this dialog determines the type of projects that appear on the list. Vector Project is automatically selected, so only vector resources appear on the list.
Projects/Imagery/SFBayArea.
Projects/Terrain/SFTerrain.
All three projects are now listed in the Database Editor window:
ASSET_ROOT/Databases
folder.The name of the database is displayed when you select the
/ASSET_ROOT/Databases
folder in the asset navigation tree.
Once the database has been defined, it is ready to be built.
Note: If you had not built the projects included in this database previously, the following process would build them in the course of building the database. As you might expect, the database build process takes much longer if it is building all of the projects in the database at once. However, since Google Earth Enterprise Fusion gives you the option to build each project as soon as you finish making modifications or when you build the database, you can determine the best work style for yourself.
/ASSET_ROOT/Databases
folder.
SFHighways appears on the right with the Current Version and the Current State set to None, indicating that the database has not yet been built.
The Version Properties dialog displays the most recent version of that database. You can expand the version tree to view the status of the build in real time by clicking the + signs.
When Google Earth Enterprise Fusion finishes building the database, its Current State column in the Asset Manager changes to Succeeded, and its Current Version column changes to the date and time the most recent build was started.
Close the Asset Manager by clicking the close box (X) in the top right corner, and go on to the next lesson.