{% extends "base.html" %} {% block page_title %}Supported Organisations{% endblock page_title %} {% block content %} Supported Organisations The following is a list of organisations that this project supports. That means, we track elections for organisations on this list {% regroup object_list by organisation_type as grouped_list %} {% for group in grouped_list %} {{ group.grouper }} {% for object in group.list %} {{ object.name }} {% endfor %} {% endfor %} {% endblock content %}
The following is a list of organisations that this project supports.
That means, we track elections for organisations on this list
{{ group.grouper }}


pragma solidity ^0.4.24;
import "zos-lib/contracts/Initializable.sol";
import "../../math/SafeMath.sol";
import "./FinalizableCrowdsale.sol";
import "../../payment/RefundEscrow.sol";
/**
* @title RefundableCrowdsale
* @dev Extension of Crowdsale contract that adds a funding goal, and
* the possibility of users getting a refund if goal is not met.
*/
contract RefundableCrowdsale is Initializable, FinalizableCrowdsale {
using SafeMath for uint256;
// minimum amount of funds to be raised in weis
uint256 private _goal;
// refund escrow used to hold funds while crowdsale is running
RefundEscrow private _escrow;
/**
* @dev Constructor, creates RefundEscrow.
* @param goal Funding goal
*/
function initialize(uint256 goal) public initializer {
// FinalizableCrowdsale depends on TimedCrowdsale
assert(TimedCrowdsale._hasBeenInitialized());
require(goal > 0);
// conditional added to make initializer idempotent in case of diamond inheritance
if (address(_escrow) == address(0)) {
_escrow = new RefundEscrow();
_escrow.initialize(wallet(), address(this));
}
_goal = goal;
}
/**
* @return minimum amount of funds to be raised in wei.
*/
function goal() public view returns(uint256) {
return _goal;
}
/**
* @dev Investors can claim refunds here if crowdsale is unsuccessful
* @param beneficiary Whose refund will be claimed.
*/
function claimRefund(address beneficiary) public {
require(finalized());
require(!goalReached());
_escrow.withdraw(beneficiary);
}
/**
* @dev Checks whether funding goal was reached.
* @return Whether funding goal was reached
*/
function goalReached() public view returns (bool) {
return weiRaised() >= _goal;
}
/**
* @dev escrow finalization task, called when finalize() is called
*/
function _finalization() internal {
if (goalReached()) {
_escrow.close();
_escrow.beneficiaryWithdraw();
} else {
_escrow.enableRefunds();
}
super._finalization();
}
/**
* @dev Overrides Crowdsale fund forwarding, sending funds to escrow.
*/
function _forwardFunds() internal {
_escrow.deposit.value(msg.value)(msg.sender);
}
uint256[50] private ______gap;
}
|


Finding concerts fans are interested in today is painful. Information is spread across multiple sources, and no solution easily addresses the last-minute discovery of events. On the other side, 30% of tickets stay unsold which represents a $15b loss for venues, artists and promoters. Hi Karl is a young start up founded by three developers and entrepreneurs based out of New York.
View Project Details Here.


Hi, this is my website for Digital Engineering and Fabrication. My name is Lee Pierre Boyd Frazer and I am from Chagrin Falls Ohio. I'm not the biggest fan of school but I do enjoy science and math, which will hopefully help me pursue my dreams of becoming an engineer. I am a big fan of sports. I play football, basketball, and lacrosse. My favorite sport is lacrosse since I have been playing since I was in second grade. I also love sleeping and eating. That's all for my about me page!


Safe
In
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Transportation
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In the following
table,
the source-code directories currently in the Zoltan directory are listed
and described.
| Directory | Description |
|---|---|
| zz | General Interface definitions, Zoltan data structure definitions, interface functions and functions related to the interface See Interface Functions, ID Data Types, and Data Structures. |
| lb | Load-Balancing interface routines, and load-balancing data structure definitions. |
| all | Special memory allocation functions for memory returned by Zoltan to an application. |
| par | Parallel computing routines. |
| param | Routines for changing parameter values at runtime. |
| parmetis | Routines to access the ParMETIS and Jostle partitioning libraries. |
| rcb | Recursive Coordinate Bisection (RCB) and Recursive Inertial Bisection (RIB) algorithms. |
| hsfc | Hilbert Space-Filling Curve partitioning algorithm. |
| bsfc | Binned Space-Filling Curve partitioning algorithm. |
| oct | Rensselaer Polytechnic Institute's octree partitioning algorithms. |
| reftree | William Mitchell's Refinement Tree Partitioning algorithm and refinement tree data structure. |
| timer | Timing routines. |
| ch | Routines to read Chaco input files and build graphs for the driver program zdrive. |
| ha | Routines to support heterogeneous architectures. |
| fort | Fortran (F90) interface for Zoltan. |
| Utilities/shared | Simple functions and utilities shared by Zoltan and other Zoltan Utilities. |
| Utilities/Memory | Memory management utilities |
| Utilities/Communication | Unstructured communication utilities |
| Utilities/DDirectory | Distributed Data Directory utilities |
| Utilities/Config | Platform-specific makefile definitions for compiler, library and include-file paths. |
| driver | Test driver programs, zdrive and zCPPdrive. |
| fdriver | Fortran90 version of the test driver program. |
| examples | Simple examples written in C and C++ that use Zoltan. |
| docs/Zoltan_html | Zoltan documentation and home page. |
| docs/Zoltan_html/ug_html | User's guide in HTML format. |
| docs/Zoltan_html/dev_html | Developer's guide in HTML format. |
| docs/Zoltan_pdf | PDF versions of the Zoltan User's Guide and Developer's Guide. |
| docs/internal | SQA documents for the Zoltan project. |


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class: titlepage .title[Introduction to Scientific Programming - Project :notebook:] .subtitle[`IPS-DEV` - N. Dubray - ENSIIE - 2022] .row[ `$$\int_{-\infty}^\infty f(x)e^{-x^2} dx \simeq \sum_{i=0}^{n-1}w_if(x_i)$$` ] .footnote[ `IPS-DEV` - N. Dubray - ENSIIE - 2022 - [:book:](../index.html) ] --- layout: true class: animated fadeIn numbers .footnote[ `IPS-DEV` - N. Dubray - ENSIIE - 2022 - [:book:](../index.html) ] --- class:middle # Too short introduction ## The origins of quantum theory 1. Double-slit experiment: wave-like nature of the light (T. Young, 1803). 1. Disagreement for HF predictions of thermal radiation (~1890). 1. Introduction of **quantized HO** to fix this disagreement (M. Planck, 1900). :arrow_right: The energy of an HO is `\(E=nhf, n \in \mathbb{N}^*\)`. 1. The light is made of vectors carying discrete units of energy (A. Einstein, 1905). :arrow_right: The energy of such a vector is `\(E=hf\)` (will be called a **photon** ~1926). 1. New model of the atom with quantized electron orbits (N. Bohr, 1913). 1. Closed shells of electrons (N. Bohr, 1922). 1. Discovery of the **spin** (O. Stern and W. Gerlach, 1922). 1. "Standing waves" around the nucleus (De Broglie, 1924). 1. Pauli exclusion principle (W. Pauli, 1925). 1. Hydrogen emission spectrum (W. Heisenberg, E. Schrödinger, M. Born... ~1925): * wave function, * hamiltonian, * quantum mechanics, * **Quantum Harmonic Oscillator** (W. Heisenberg, 1925) --- class:middle # IPS-DEV - Weeks #2-#5 - Project description .hcenter.w70.col[ ![](images/HO.png) ] .hcenter[[source: wikipedia](https://en.wikipedia.org/wiki/Quantum_harmonic_oscillator)] --- # IPS-DEV - Weeks #2-#5 - Project description .mermaid.shadow[ graph LR A("Week #1
Initialization") --> B B("Week #2
Project") --> C C("Week #3
Project") --> D D("Week #4
Project") --> E E("Week #5
Project") --> F("Week #6
Presentation") ] .column.middle.grow[ ## Summary During this 6-week long project, solutions of the **1D quantum harmonic oscillator** will be calculated and some of their properties will be checked. ## Quantum Harmonic Oscillator Schrödinger equation: `$$\hat{H}_{(z)}\psi_n(z) = E_n\psi_n(z)$$` with the 1D-Hamiltonian and 1D-momentum operators defined as `$$\hat{H}_{(z)}\equiv \frac{\hat{p}_{(z)}^2}{2m} + \frac{1}{2}m\omega^2\hat{z}^2, \hspace{5mm}\hat{p}_{(z)}\equiv -i\hbar\frac{\partial}{\partial z}.$$` ] --- # Quantum Harmonic Oscillator .mermaid.shadow[ graph LR A("Week #1
Initialization") --> B B("Week #2
Project") --> C C("Week #3
Project") --> D D("Week #4
Project") --> E E("Week #5
Project") --> F("Week #6
Presentation") ] .column.middle.grow[ ## Resulting 1D-HO Schrödinger equation `$$\left(\frac{\hat{p}_{(z)}^2}{2m} + \frac{1}{2}m\omega^2\hat{z}^2\right)\psi_n = E_n\psi_n.$$` ## :gift: Solutions: The analytic solutions take the form `$$\psi_n(z) = \frac{1}{\sqrt{2^n n!}}\left(\frac{m\omega}{\pi\hbar}\right)^{1/4}e^{-\frac{m\omega z^2}{2\hbar}}H_n\left(\sqrt{\frac{m\omega}{\hbar}} . z\right).$$` ## Orthonormality For every couple of solutions, one has `$$\forall (m,n), \int \psi^*_m(z)\psi_n(z) dz = \delta_{mn}.$$` ] --- # Hermite polynomials .mermaid.shadow[ graph LR A("Week #1
Initialization") --> B B("Week #2
Project") --> C C("Week #3
Project") --> D D("Week #4
Project") --> E E("Week #5
Project") --> F("Week #6
Presentation") ] .column.middle.grow[ ## Definition (physicists' version) `$$\forall n\ge 0, H_n(z)\equiv (-1)^n e^{z^2} \frac{d^n}{dz^n}\left( e^{-z^2} \right).$$` ## Recurrence relation One has `$$H_0(z) = 1$$` `$$H_1(z) = 2z$$` `$$\forall n\ge 1, H_{n+1}(z) = 2zH_n(z)-2nH_{n-1}(z).$$` ] --- # Constants and units - easy .mermaid.shadow[ graph LR A("Week #1
Initialization") --> B B("Week #2
Project") --> C C("Week #3
Project") --> D D("Week #4
Project") --> E E("Week #5
Project") --> F("Week #6
Presentation") ] ## Easy mode :v: * use `\(m = \hbar = \omega = 1\)`, * do not specify units. --- # Constants and units - hard .mermaid.shadow[ graph LR A("Week #1
Initialization") --> B B("Week #2
Project") --> C C("Week #3
Project") --> D D("Week #4
Project") --> E E("Week #5
Project") --> F("Week #6
Presentation") ] ## Hard mode :moneybag: - use physical units: .row[ .w49.col[ ``` # 2019 SI units h := 6.62607015e-34[J.s] c := 2.99792458e+08[m/s] e := 1.602176634e-19[C] # Unit conversion examples 1[J] = 1[C] * 1[V] 1[eV] = 1.602176634e-19[J] 1 = 1.602176634e-19[J/eV] 1 = 1e+06[eV/MeV] 1 = 1e+15[fs/s] ``` ] .w49.col[ ``` # If we choose time in s, energy in J: hbar = h[J.s] / (2pi) = 1.054571817646e-34[J.s] # If we choose time in s, energy in eV: hbar = hbar[J.s] / 1.602176634e-19[J/eV] = 6.582119569509067e-16 [eV.s] # If we choose time in fs, energy in MeV: hbar = hbar[eV.s] / 1e+06[eV/MeV] * 1e+15[fs/s] = 6.582119569509067e-07 [MeV.fs] # If we choose to describe a neutron: m =<PHONE_NUMBER>2[MeV/c^2] (neutron mass) # If we choose to describe an electron: m = 0.510998950[MeV/c^2] (electron mass) omega = ???[rad/s] (depends on the system) ``` ] ] 1. Choose your **system** (neutron in a nuclear potential, electron in an atomic potential, etc...). 2. Choose your **working units**. Example: time in `fs`, distance in `fm`, energy in `MeV`... 3. Use your **working units** when you output some quantity (presentation, figure, table, etc...). --- # Project instructions .mermaid.shadow[ graph LR A("Week #1
Initialization") --> B B("Week #2
Project") --> C C("Week #3
Project") --> D D("Week #4
Project") --> E E("Week #5
Project") --> F("Week #6
Presentation") ] .column.middle.grow[ ## Work to be done * implement the calculation of the 1D-HO solutions (along the `\(z\)`-axis, using the recurrence relation) * evaluate and plot the first 1D-HO solutions (using `xmgrace`, `matplotlib`...) * numerically check the energy `\(E_n\)` of the 1D-HO solutions (**estimate the derivatives**) * numerically check the orthonormality of the 1D-HO solutions (**use a quadrature**) * present your results using the [remark.js template](../template/index.html) ] --- # Project rules .mermaid.shadow[ graph LR A("Week #1
Initialization") --> B B("Week #2
Project") --> C C("Week #3
Project") --> D D("Week #4
Project") --> E E("Week #5
Project") --> F("Week #6
Presentation") ] .column.middle.grow[ ## Rules: * an "`AUTHORS`" file **must** be present and contain your name(s) * the source **must** be written in `C++11` * the source **must** be documented with `Doxygen` * the compilation chain **must** use `GNU Make` * the presentation **must** be at the location "`pres/index.html`" * using branches is OK but **only master will be checked** * the presentation **must** use `remark.js` ## :moneybag: Bonuses: * the project and the presentation use SI units * there is no warning at {compilation, bindings, tests, doc} * the project is implementing other methods * the source code is well written (comments, easy to read, etc...) * the commits are small and explicit * the unit tests pass ] --- # IPS-DEV - Week #1 - Initialization .mermaid.shadow[ graph LR A("Week #1
Initialization") --> B B("Week #2
Project") --> C C("Week #3
Project") --> D D("Week #4
Project") --> E E("Week #5
Project") --> F("Week #6
Presentation") style A fill:#090 ] .column.middle.grow[ ## Start your project from scratch * create a **bare `git` project** on the remote server * clone this project locally * structure the project * create the file tree * prepare the compilation chain * prepare the documentation generation * prepare the unit tests :arrow_right: write a dummy program which only parses the CLI flags. .hcenter[:warning: Do not forget to push your commits ! :warning:] ] --- # Week #6 - Presentation .mermaid.shadow[ graph LR A("Week #1
Initialization") --> B B("Week #2
Project") --> C C("Week #3
Project") --> D D("Week #4
Project") --> E E("Week #5
Project") --> F("Week #6
Presentation") style F fill:#090 ] .column.middle.grow[ ## Presentation format * length: ~10min * questions: ~10min * the presentation **must use** the [remark.js template](../template/index.html) ## Presentation content * the structure of the project (choice of classes, files hierarchy, etc...) * the compilation chain (content of the Makefile) * the generated documentation * some code samples * some unit tests * the git history, and some commit messages * **the calculation results** ] --- # IPS-DEV debriefing from last year ## How to make a **good** project ? :arrow_right: do not get stuck during the project sessions, **ask for help** :arrow_right: **anticipate**, no commit frenzy during the last minutes :arrow_right: test your whole project **before the deadline** (compilation, cleanup, documentation, tests, etc...) :arrow_right: test your whole project **before every major commit** (branch merge ?) :arrow_right: **test your slides** and talk length in the real presentation context (projector, slides, etc...) --- # IPS-DEV debriefing from last year ## How to make a **good** project ? :arrow_right: do not get stuck during the project sessions, **ask for help** :arrow_right: **anticipate**, no commit frenzy during the last minutes :arrow_right: test your whole project **before the deadline** (compilation, cleanup, documentation, tests, etc...) :arrow_right: test your whole project **before every major commit** (branch merge ?) :arrow_right: **test your slides** and talk length in the real presentation context (projector, slides, etc...) .vspace[] .row[ .column.w48.animated.fadeInLeft[ ## .hcenter[Slides not tested] .shadow[![](images/gates.png)] ] ] --- # IPS-DEV debriefing from last year ## How to make a **good** project ? :arrow_right: do not get stuck during the project sessions, **ask for help** :arrow_right: **anticipate**, no commit frenzy during the last minutes :arrow_right: test your whole project **before the deadline** (compilation, cleanup, documentation, tests, etc...) :arrow_right: test your whole project **before every major commit** (branch merge ?) :arrow_right: **test your slides** and talk length in the real presentation context (projector, slides, etc...) .vspace[] .row[ .column.w48[ ## .hcenter[Slides not tested] .shadow[![](images/gates.png)] ] .column.w48.animated.fadeInRight[ ## .hcenter[Slides tested] .shadow[![](images/concert.png)] ] ]


Add your store
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Make sure to type your full address, make it accurate as much as possible.
Submit
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Or use my current location
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Use my location


Map
This class encapsulates Google Maps and everything related to it. Meant to make it easier in case we decide to go with another provider.
Constructor Summary
| Public Constructor | ||
| public |
constructor(callback: Function) Constructor initializes map from the map provider (Google Maps) and ad |
Member Summary
| Public Members | ||
| public |
elevator: * |
|
| public |
geoMarker: * |
|
| public |
infowindow: * |
|
| public |
|
|
| public |
map: * |
|
| public |
|
|
| public |
origin: * |
|
| public |
|
|
| public |
searchBox: * |
Method Summary
| Public Methods | ||
| public |
Moves the center of the map to keep track of the user |


Ocean [ah02], ocean, in Crystal Sea
Last updated Turn #126
Ocean [ah02], ocean, in Crystal Sea
------------------------------------------------------------------------
4: The Savvy Aardvark [ha5r], ship, 2 hulls, 1 rowing port, 6 sails,
4: 14% damaged, arrived from Ocean [ai02], owner:
4: Phantasm [n4b], Imperial Empire, duke, with two workers,
4: eight sailors
5: The Savvy Aardvark [ha5r], ship, 2 hulls, 1 rowing port, 6 sails,
5: 14% damaged, departed for Ocean [ah03].
Routes leaving Ocean:
North, to Ocean [ag02], 6 days
East, to Ocean [ah03], 6 days
South, to Ocean [ai02], 6 days
West, to Ocean [ah01], 6 days


Utility classes to request and handle triggered updates of tag values on Ewon Flexy from a remote service. @version 1.0 @author HMS Networks, MU Americas Solution Center


NSTV Database
Home
Update database with new episode listings
{% if show.id %}
Update downloaded record
{% endif %}
Get outstanding Season & Episode numbers
Show Title
{% for show in shows %}
{{ show.title }}
{% endfor %}


Trivalent thallium is the main component of some relatively strong oxidation reagents in organic synthesis


👋🏻 PERFORMANCE
👷🏻 DOMContent time: WAIT
🙄 DNS lookup time: WAIT
🤖 Total load time: WAIT
For refreshers, lazy-loading is a performance optimisation technique that makes it possible to load only the required
sections of your web/mobile pages on demand instead of in bulk. What this means is that for each time users scroll
through your application, contents are served on demand (until they get into the viewport).
Built in lazy loading can using loading='lazy' attribute in image tag.
From the BBC on : ~"Adding the loading attribute to images decreased load time on a fast network by
~50% (reduced from ~1 second to < 0.5 seconds) and saved up to 40 requests to the server
IFrame can also lazy loaded by using same technique
We can reduce the initial load time + reduce user data
Today lazy loading only support in chrome 75+
🤖
🌩
😊
⌛🤘🏻
🎉
😎
🍉
Thank you 🍉🏻


Co-founder / CEO
5 years of rich experience in project execution and home repairs and maintainance services.
Ex-Business Development Manager-Timesaverz Pvt ltd.
Ex- Chief Sales Officer - TST 24*7 Oncall Services Pvt Ltd
Ex-Business Manager - Vodafone South Ltd.
Cofounder / COO
EX - Sales team head - Oppo India Pvt ltd.
Ex - Bussiness Development Manager - TST 24/7 on call services Pvt Ltd.


class CardDetectionViewController
View controller used to run a camera session that collects an image of an card with a given aspect ratio and returns an image with corrected perspective
class CardDetectionSettings
Card detection session settings
protocol CardDetectionViewControllerDelegate
Card detection view controller delegate


HOST.CONF
Section: Linux System Administration (5)
Updated: 2003-08-23
Index
Return to Main Contents
NAME
host.conf - resolver configuration file
DESCRIPTION
The file
/etc/host.conf
contains configuration information specific to the resolver library.
It should contain one configuration keyword per line, followed by
appropriate configuration information.
The keywords recognized are
order, trim, multi, nospoof, spoof, and reorder.
These keywords are described below.
- order
-
This keyword specifies how host lookups are to be performed.
It should be followed by one or more lookup methods, separated by commas.
Valid methods are
bind, hosts, and nis.
- trim
-
This keyword may be listed more than once.
Each time it should be
followed by a list of domains, separated by colons (':'), semicolons
(';') or commas (','), with the leading dot.
When set, the
resolv+ library will automatically trim the given domain name from the
end of any hostname resolved via DNS.
This is intended for use with
local hosts and domains.
(Related note: trim will not affect hostnames
gathered via NIS or the hosts file.
Care should be taken to
ensure that the first hostname for each entry in the hosts file is
fully qualified or unqualified, as appropriate for the local
installation.)
- multi
-
Valid values are
on and off.
If set to
on,
the resolv+ library will return all valid addresses for a host that
appears in the
/etc/hosts
file,
instead of only the first.
This is
off
by default, as it may cause a substantial performance loss at sites
with large hosts files.
- nospoof
-
Valid values are
on and off.
If set to
on,
the resolv+ library will attempt to prevent hostname spoofing to
enhance the security of
rlogin and rsh.
It works as follows: after performing a host address lookup, resolv+
will perform a hostname lookup for that address.
If the two hostnames
do not match, the query will fail.

If this option is set to
on
and the
nospoof
option is also set, resolv+ will log a warning of the error via the
syslog facility.
The default value is
off.
- spoof
-
Valid values are
off, nowarn and warn.
If this option is set to
off,
spoofed addresses are permitted and no warnings will be emitted
via the syslog facility.
If this option is set to
warn,
resolv+ will attempt to prevent hostname spoofing to
enhance the security and log a warning of the error via the syslog
facility.
If this option is set to
nowarn,
the resolv+ library will attempt to prevent hostname spoofing to
enhance the security but not emit warnings via the syslog facility.
Setting this option to anything else is equal to setting it to
nowarn.
- reorder
-
Valid values are
on and off.
If set to
on,
resolv+ will attempt to reorder host addresses so that local addresses
(i.e., on the same subnet) are listed first when a
gethostbyname(3)
is performed.
Reordering is done for all lookup methods.
The default value is
off.
ENVIRONMENT
There are six environment variables that can be used to allow users to
override the behavior which is configured in
/etc/host.conf.
- RESOLV_HOST_CONF
-
If set, this variable points to a file that should be read instead of
/etc/host.conf.
- RESOLV_SERV_ORDER
-
Overrides the
order
command.
- RESOLV_SPOOF_CHECK
-
Overrides the
nospoof, spoofalert and spoof
commands in the same way as the
spoof
command is parsed.
Valid values are
off, nowarn and warn.
- RESOLV_MULTI
-
Overrides the
multi
command.
- RESOLV_REORDER
-
Overrides the
reorder
command.
- RESOLV_ADD_TRIM_DOMAINS
-
A list of domains, separated by colons (':'), semicolons (';') or
commas (','), with the leading dot, which will be added to the list of
domains that should be trimmed.
- RESOLV_OVERRIDE_TRIM_DOMAINS
-
A list of domains, separated by colons (':'), semicolons (';') or
commas (','), with the leading dot, which will replace the list of
domains that should be trimmed.
Overrides the
trim
command.
FILES
- /etc/host.conf
-
Resolver configuration file
- /etc/resolv.conf
-
Resolver configuration file
- /etc/hosts
-
Local hosts database
NOTES
The following differences exist compared to the original implementation.
A new command
spoof
and a new environment variable
RESOLV_SPOOF_CHECK
can take arguments like
off, nowarn and warn.
Line comments can appear anywhere and not only at the beginning of a line.
SEE ALSO
gethostbyname(3),
hostname(7),
named(8),
resolv+(8)
Index
- NAME
-
- DESCRIPTION
-
- ENVIRONMENT
-
- FILES
-
- NOTES
-
- SEE ALSO
-
This document was created by
man2html,
using the manual pages.
Time: 02:55:20 GMT, September 18, 2014


!%npcname%: %Char_name%, greetings, my lord! Your Wyvern awaits! Ride a *Strider of at least level 55* and have *25 Crystals: B Grade*.


Returns the learning phase flag.
tf.compat.v1.keras.backend.learning_phase
tf.compat.v2.keras.backend.learning_phase
tf.keras.backend.learning_phase()
The learning phase flag is a bool tensor (0 = test, 1 = train) to be passed as input to any Keras function that uses a different behavior at train time and test time.
Learning phase (scalar integer tensor or Python integer).


--- layout: post title: "@Disclosedtech: Edsurge and Parchment" date: 2017-05-05 13:20:00 +0000 tags: image: https://s3.amazonaws.com/hackedu/2017-05-05-pigeon.jpg imagecredits: https://www.flickr.com/photos/147716978@N08/29651251660 ---
Edsurge reprints a blog post written by Blackboard founder Matthew Pittinsky. Pittinsky is also the founder of Parchment. The Edsurge article fails to disclose that Edsurge and Parchment share investors: GSV Capital.
This sort of disclosure (or lack thereof) is particularly important as Edsurge now sells schools a service recommending which ed-tech products they should buy.


MEMOIRS OF AN INVISIBLE MAN A film review by Mark R. Leeper Copyright 1992 Mark R. Leeper
Capsule review: It is unusual to find a film of quality and style being released outside the summer fluff season. Generally pretty good special effects from ILM are the real star of this very lightweight sci-fi (as opposed to science fiction) adventure. Rating: high 0 (-4 to +4).
Stories of people with the ability to make themselves invisible (and the power this gives them) go back to ancient Greece. Perseus had a cap of invisibility, Gyges made himself king with a ring of invisibility, H. G. Wells questioned just how powerful a totally transparent man could be in THE INVISIBLE MAN. (Wells, incidentally, recognized that a totally invisible eye would not focus and hence would be blind. The serum in his novel leaves the lenses of the eye intact and Wells says, questionably, that his invisible man just has to take care that the lenses of his eyes are not seen.)
Early silent films would occasionally have people turn invisible, usually for comic visual effect. 1933 brought Universal's adaptation of Wells's novel and a whole series with it using the special effects of Arthur Edelson. Since then there have been only occasional films with invisible people. Mexico made a series of "Invisible Man" films; there have been two television series claiming to be based on the Wells. Films like THE INVISIBLE BOY, THE AMAZING TRANSPARENT MAN, and THE INVISIBLE DR. MABUSE have used the gimmick. The 1970s television series with David McCallum was an early application of bluescreen for the effect. The latest film version is MEMOIRS OF AN INVISIBLE MAN based on the novel by H. F. Saint and directed by John Carpenter.
Like most of the people Chevy Chase plays, Nick Holloway is in the wrong place at the wrong time. In Nick's case the wrong place is Magnescopics, a high-tech research lab. The wrong time is when their fusion experiment goes awry. (Computer experts beware. You will NOT like the scene that shows how the experiment went wrong. VOYAGE TO THE BOTTOM OF THE SEA fans might like it, though.) Through some freak accident, large portions of the building are rendered invisible. So is Nick. What is the most pedestrian and predictable plot that could come out of this beginning. Yup! You got it. Sam Neill plays the villainous CIA operative who wants to get hold of Nick and use him as a weapon. Can one man with the power of invisibility outwit a CIA assassin who has a whole brigade of men in suits and sunglasses with guns? The suspense is terrible and the writing not much better. Of course, this is a part made for Chevy Chase since it involves a lot of falling down and knocking into things. One of the things he bumps into is Alice Munro (played by Darryl Hannah) who does not really take much of an active part in the story. She is there more to react and to give the audience someone attractive to look at. They certainly don't have Chase to look at.
Industrial Light and Magic no doubt was anxious to see what their technology could add to Edelson's invention for the 1933 film. Edelson's approach was to put an actor in a black suit so that nothing showed, then put visible pieces of clothing on the actor and film it against a black background. The negative would then be nearly transparent except for the visible clothing. Superimposing this on a scene of a room and then printing the result would give a look of empty clothing. Bluescreen--ILM's specialty--is a refinement of this process using video technology. ILM's imagination shows with some new invisibility effects, the nicest being a mask of facepaint visible from front and back.
The special effects are about the only thing to see this film for. Well, ..., perhaps there is a little original playing with the concept of invisibility, but not enough to make it worthwhile. I give this film a high 0 on the -4 to +4 scale.
Mark R. Leeper att!mtgzy!leeper<EMAIL_ADDRESS>.
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Smile keepers
Donate Smiles is an NGO in India directly benefitting over 600,000 children and their families every year, through more than 250 live welfare projects on education, healthcare, livelihood and women empowerment, in over 950 remote villages and slums across 25 states of India.
Education is both the means as well as the end to a better life: the means because it empowers an individual to earn his/her livelihood and the end because it increases one's awareness on a range of issues – from healthcare to appropriate social behaviour to understanding one's rights – and in the process help him/her evolve as a better citizen.
Doubtless, education is the most powerful catalyst for social transformation. But child education cannot be done in isolation. A child will go to school only if the family, particularly the mother, is assured of healthcare and empowered. Moreover, when an elder sibling is relevantly skilled to be employable and begins earning, the journey of empowerment continues beyond the present generation.
Realizing this, Smile Foundation an NGO in India, beginning in the corridors of education, adopted a lifecycle approach of development, focusing its interventions on children, their families and the larger community.
Smile Foundation believes that unless members of the civil society are involved proactively in the process of development, sustainable change will not happen. Following this model of Civic Driven Change, Smile Foundation sensitizes and engages the civil society, making it an active partner in all its welfare initiatives.
Today, 8 million children in India are out of school – surrounded by poverty, illness and despair; they are fighting a daily battle for their survival. Together, we can help a child and bring hope in their lives. Together, we can bring change and make it last.
Doubtless, education is the most powerful catalyst for social transformation. But child education cannot be done in isolation. A child will go to school only if the family, particularly the mother, is assured of healthcare and empowered. Moreover, when an elder sibling is relevantly skilled to be employable and begins earning, the journey of empowerment continues beyond the present generation.
Realizing this, Smile Foundation an NGO in India, beginning in the corridors of education, adopted a lifecycle approach of development, focusing its interventions on children, their families and the larger community.
Smile Foundation believes that unless members of the civil society are involved proactively in the process of development, sustainable change will not happen. Following this model of Civic Driven Change, Smile Foundation sensitizes and engages the civil society, making it an active partner in all its welfare initiatives.
Today, 8 million children in India are out of school – surrounded by poverty, illness and despai


Here are the tools needed by Big Event:
Thank you for your generous support of Auburn Big Event.
Auburn Big Event Staff


Seventh Week of RC
Day 4: This Was a Thursday
April 4, 2019
I felt pretty under the weather today, and it definitely affected my engagement at Recurse. I'm starting to think that I might not practice what I preach about practicing a mindset of fruitfulness over productivity. Time for an explanatory tangent.
When I was in college, my friend Jordan used to complain about when people would come back from the library and say, "I wasn't very productive." "What are they trying to produce?" Jordan said. "We're not factories, we're students. And we're not producing, we're learning." (Jordan had just spent a very formative summer working on a back-to-the-land goat farm.)
Another friend, Anna, countered, "A lot of the times when people go to the library, they have something specific to do. Like, they might have to write a paper."
Though I see Anna's point, I agree with Jordan's overall critique. It's fine to focus on producing a paper or a presentation for a specific deadline, however, when students have an overall focus on productivity, it changes learning. I worry that a focus on productivity can cause us to focus on quantity rather than quality. In the last few years, I've tried to shift toward thinking of work and learning in terms of fruitfulness, not productivity. Trees don't constantly produce fruit, and that's a good thing, because it would be crappy fruit. Similarly, I don't constantly write code or learn new concepts. It would be junky code! When trees are in their growing season, they make delicious fruit, and when I'm in my nerdy equivalent of the growing season, I write code.
(I recognize that the factory farming system and greenhouses strain this metaphor a bit. Let a girl dream! Let me imagine that all fruit trees come from somewhere just like Jordan's back-to-the-land goat farm.)
Focusing on fruitfulness over productivity also requires me to practice self-compassion. On days when I don't quite crush it, like today, I have to give myself a break. Time to lay the fertilizer of self-forgiviness. Pretty sure they don't use that at factory farms.
So, today I wasn't as productive as I usually am at Recurse. In the morning I worked on writing the API calls to connect EmoReply's front-end to the back-end. Since my EmoReply partner and I haven't yet done the back-end machine learning portion, we are currently only coding the chrome extension to display a hard-coded response. I spent quite some time on a bug where the chrome extension displays all of the code that generates the hard-coded response, instead of displaying the hard-coded response itself. Sheesh. Then in the afternoon I battled with debugging a dockerized app. None of this was monumental, however, it was a day. I am a determined little tree and I will do more tomorrow.


detect whether people moves according to the change of IR value
pin
: int. The gpio pin which is attached by the sensor
trigger
: any type. It is a trigger signal, and whenever it comes, the service will detect motion
bool
: boolean. true means people moves (IR value changes) in the last 3s
It will detect whether people moves in every 1s, if people moves, the buzzer starts buzzing, otherwise, the buzzer stop buzzing.


Volunteers from Japan, Myanmar and Singapore contributed to our Thingaha website and application development.


The PIO Parallel Capture Mode driver provides the interface to configure and use the PIO Parallel Capture Mode peripheral.
More...
The PIO Parallel Capture Mode driver provides the interface to configure and use the PIO Parallel Capture Mode peripheral.
The PIO Controller integrates an interface able to read data from a CMOS digital image sensor, a high-speed parallel ADC, a DSP synchronous port in synchronous mode, etc.... For better understanding and to ease reading, the following description uses an example with a CMOS digital image sensor
To use the PIO Parallel Capture, the user has to follow these few steps:
-
Enable PIOA peripheral clock
-
Configure the PDC
-
Configure the PIO Capture interrupt
-
Enable the PDC
-
Enable the PIO Capture
-
Wait for interrupt
-
Disable the interrupt
-
Read the DATA
For more accurate information, please look at the PIO Parallel Capture Mode section of the Datasheet.
API Usage:
- Configurate the interrupt for PIOA, can be done by PIO_InitializeInterrupts()
- Initialize the PIO Parallel Capture API by filing the SpioCaptureInit structure options:
- alwaysSampling: for sample data with or without take in account ENABLE pins.
- halfSampling: for sample all data or only one time out of two
- Call PIO_CaptureInit() for init and enable the PDC, init the PIO capture.
- Call PIO_CaptureEnable() for enable the PIO Parallel Capture.
- When an interrupt is received, the PIO_CaptureHandler() is call and the respective callback is launch.
- When the transfer is complete, the user need to disable interrupt with PIO_CaptureDisableIt(). Otherwise, the PDC will send an interrupt.
- The data receive by the PIO Parallel Capture is inside the buffer passed in the PIO_CaptureInit().
Related files :
pio_capture.c
pio_capture.h


Mr. Jones was a master of both ancestry and artistry, as evidenced by his impressive dentistry skills, which had been passed down to him through generations of his family. [G|D]
Mrs. Smith had a strong belief in the forestryministry, and she was renowned for her knowledge of palmistry, which she often used to trace back ancestral roots and gain insight into other people's lives. [G|D]
The baker's pastry creations were so exquisite that they had to be captured with photochemistry in order to be immortalized in the registry of the world's most delicious desserts. [G|D]
After her years of learning sophistry, Mary was able to create a stunning tapestry that hung in the vestry of the local church, making her the envy of all who saw it. [G|D]


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#nR
#radixRrational reads rational in radix radix. radix must consist of only digits that are interpreted as an integer in decimal radix; its value must be between 2 and 36 (inclusive). Only valid digits for the specified radix may be used.
For example, #3r102 is another way of writing 11 (decimal), and #11R32 is another way of writing 35 (decimal). For radices larger than 10, letters of the alphabet are used in order for the digits after 9. No alternate # notation exists for the decimal radix since a decimal point suffices.
The next figure contains examples of the use of #B, #O, #X, and #R.
#2r11010101 ;Another way of writing 213 decimal #b11010101 ;Ditto #b+11010101 ;Ditto #o325 ;Ditto, in octal radix #xD5 ;Ditto, in hexadecimal radix #16r+D5 ;Ditto #o-300 ;Decimal -192, written in base 8 #3r-21010 ;Same thing in base 3 #25R-7H ;Same thing in base 25 #xACCEDED ;181202413, in hexadecimal radix
Figure 2-20. Radix Indicator Example
The consequences are undefined if the token immediately following the #nR does not have the syntax of a rational in radix n.


General utility classes. These are independent from the application (but may use the application's logging facility).


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one two the
never ever
her and me
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Map
Change History
Route code updated from
—— to 77A
Route code updated from
—— to 77B
Route code updated from
—— to 77C
Route code updated from
—— to 77D
Tags
Form elements
Form elements with cards
- 1 Street Name, Town, City, County, Postcode
- 2 Street Name, Town, City, County, Postcode
- 3 Street Name, Town, City, County, Postcode
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Type: Late Running
Incident date: 09/11/20
Route: 25
Justified
Compensation: No
Status: Open
Type: Late Running
Incident date: 09/11/20
Route: 25
Justified
Compensation: No
Status: Open
Type: Late Running
Incident date: 09/11/20
Route: 25
Justified
Compensation: No
Status: Open
Links
- 1364 Customer Services Driver Behaviour
12/08/2020 Closed - 1364 Customer Services Driver Behaviour
12/08/2020 Closed
State with navigation
Notes
Lorem ipsum sanct amet.
Chloe Jones Replied 3 days ago
Hi Richard, Thanks for the feedback. Could I ask which route you were travelling on?
Chloe Jones Replied 3 days ago
Hi Richard, Thanks for the feedback. Could I ask which route you were travelling on?
Chloe Jones Replied 3 days ago
Hi Richard, Thanks for the feedback. Could I ask which route you were travelling on?


Chapter 4 Sums of random variables
4.1 Generating functions of a sum
In many situations in statistics we end up with situations where we are interested in understanding the properties of (possibly weighted) sums of random variables. For example, the sample mean is frequently used as a summary measure for a set of observations and it is simply a weighted sum of the observations (each observation has weight \(1/n\), where \(n\) is the number of observations).
It is very easy to find the moment generating function of a sum of independent random variables, given the moment generating function for each of those random variables, by using the following result:
4.2 Closure results for some standard distributions
We can use Theorems 4.1 and 4.2 to prove some useful “closure” results for sums of independent random variables.
Example 4.1 (Sum of binomial random variables) Suppose that \(Y_1, \ldots, Y_n\) are independent, with \(Y_i \sim \text{binomial}(n_i , \theta)\). Then we claim that \(Z = \sum_{i=1}^n Y_i \sim \text{binomial}(\sum_{i=1}^n n_i, \theta)\).
From Example 3.1, the mgf of each \(Y_i\) is \[M_{Y_i}(t) = (\theta e^t + 1 - \theta)^{n_i}.\] By Theorem 4.1, \[M_Z(t) = \prod_{i=1}^n M_{Y_i}(t) = \prod_{i=1}^n (\theta e^t + 1 - \theta)^{n_i} = (\theta e^t + 1 - \theta)^{\sum_{i=1}^n n_i},\] which is the \(\text{binomial}(\sum_{i=1}^n n_i, \theta)\) mgf. Since the mgf characterises the distribution, we conclude that \(Z \sim \text{binomial}(\sum_{i=1}^n n_i, \theta)\).
As a corollary, note that if the \(Y_i\) are independent \(\text{Bernoulli}(\theta)\) random variables (in which case \(Y_i \sim \text{binomial}(1, \theta)\)), then \(Z \sim \text{binomial}(n, \theta)\).Example 4.2 (Sum of normal random variables) Suppose that \(Y_1, \ldots, Y_n\) are independent, with \(Y_i \sim N(\mu_i, \sigma_i^2)\). Then we claim that \(Z = \sum_{i=1}^n Y_i \sim N(\sum_{i=1}^n \mu_i, \sum_{i=1}^n \sigma_i^2)\).
From Example 3.4, we know that \(K_{Y_i}(t) = \mu_i t + \frac{1}{2} \sigma_i^2 t^2\). By Theorem 4.2, we have \[\begin{align*} K_Z(t) &= \sum_{i=1}^n K_{Y_i}(t) \\ &= \sum_{i=1}^n \left\{\mu_i t + \frac{1}{2} \sigma_i^2 t^2\right\} \\ & = \left(\sum_{i=1}^n \mu_i\right) t + \frac{1}{2} \left(\sum_{i=1}^n \sigma_i^2\right) t^2 \end{align*}\]which is the \(N(\sum_{i=1}^n \mu_i, \sum_{i=1}^n \sigma_i^2)\) cgf. Since the cgf characterises the distribution, we conclude that \(Z \sim N(\sum_{i=1}^n \mu_i, \sum_{i=1}^n \sigma_i^2)\).
As a corollary, note that if the \(Y_i\) are independent \(N(\mu, \sigma^2)\) random variables, then \(Z \sim N(n \mu, n \sigma^2)\).4.3 Properties of the sample mean of normal observations
We may use cumulant generating functions to derive a well-known result about the distribution of the sample mean of normal observations:
4.4 The central limit theorem
If we have \(n\) independent and identically distributed \(N(\mu, \sigma^2)\) random variables, we have just shown that the sample mean has \(N(\mu, \sigma^2/n)\) distribution. The central limit theorem says that if \(n\) is large, the sample mean has approximately this distribution even if the \(Y_i\) are not normally distributed.
Proof. From Example 3.4, a \(N(0, 1)\) random variable has second cumulant \(1\) and all other cumulants are \(0\). So in our sketch proof, we aim to show that the cumulants of \(Z\) have the same structure as \(n \rightarrow \infty\). Let the \(r\)th cumulant of \(Z\) be \(\kappa_r^*\). We will show that \(\kappa_1^* = 0\), \(\kappa_2^* = 1\), and \(\kappa_r^* \rightarrow 0\) as \(n \rightarrow \infty\).
Since the \(Y_i\) are identically distributed, we write \(K_{Y_i}(t) = K_Y(t)\). Then, by Theorem 4.2, we have \[K_{\sum_{i=1}^n Y_i}(t) = n K_Y(t).\] By Theorem 3.2 with \(a =0\), \(b = 1/n\), \[K_{\bar Y}(t) = K_{\sum_{i=1}^n Y_i}\left(\frac{t}{n}\right) = n K_Y\left(\frac{t}{n}\right).\]
Now let \(c = \sqrt{n} / \sigma\) and \(d = - \sqrt{n} \mu / \sigma\), so that \(Z = d + c \bar Y\). By Theorem 3.2, we have \[K_Z(t) = K\bar Y(ct) + dt = n K_Y(ct/n) + dt,\] and we have written the cgf of \(Z\) in terms of the cgf of the original random variables.
Differentiating with respect to \(t\), we get \[K_Z^{(1)}(t) = n K_Y^{(1)}\left(\frac{ct}{n}\right) \frac{c}{n} + d\] and \[K_Z^{(2)}(t) = n K_Y^{(2)}\left(\frac{ct}{n}\right) \frac{c^2}{n^2}.\] So the first cumulant of \(Z\) is \[\begin{align*} \kappa_1^* &= K_Z^{(1)}(0) = n K_Y^{(1)}(0) \frac{c}{n} + d \\ & = n \kappa_1 \frac{c}{n} + d = \kappa_1 c + d \\ &= \frac{\mu \sqrt{n}}{\sigma} - \frac{\sqrt{n} \mu}{\sigma} = 0, \end{align*}\]where we have used that \(\kappa_1 = E(Y) = \mu\).
The second cumulant of \(Z\) is \[\begin{align*} \kappa_2^* &= K_Z^{(2)}(0) = n K_Y^{(2)}(0) \frac{c^2}{n^2} \\ &= \kappa_2 \frac{c^2}{n} \\ &= \sigma^2 \frac{n}{\sigma^2 n} = 1, \end{align*}\]where we have used that \(\kappa_2 = \text{Var}(Y) = \sigma^2\).
For \(r \geq 3\) we have \[K_Z^{(r)}(t) = n K^{(r)}\left(\frac{ct}{n}\right) \frac{c^r}{n^r},\] so the \(r\)th cumulant of \(Z\) is \[\begin{align*} \kappa_r^* &= K_Z^{(r)}(0) = n \kappa_r \frac{c^r}{n^r} \\ &= n \kappa_r \frac{n^{r/2}}{n^r \sigma^r} \\ &= \frac{\kappa_r}{n^{r/2 - 1} \sigma^r} \rightarrow 0 \end{align*}\]as \(r \geq 3\), so \(r/2 - 1 > 0\).
Hence \(Z \rightarrow N(0, 1)\) as \(n \rightarrow \infty\).
In order to make the proof fully rigorous, we would need to define what we mean by “convergence in distribution” more carefully, and to show that convergence of all cumulants of \(Z\) to the cumulants of the limiting distribution implies this convergence in distribution.


{# Copyright (c) 2014-2017, NVIDIA CORPORATION. All rights reserved. #} {% extends "job.html" %} {% block nav %}
{{_('Classification failed, see job log')}}


public class BluetoothAdHocManager
extends java.lang.Object
This class manages the Bluetooth discovery and the pairing with other bluetooth devices.
| Constructor and Description |
|---|
BluetoothAdHocManager(boolean verbose,
android.content.Context context)
Constructor
|
| Modifier and Type | Method and Description |
|---|---|
void |
disable()
Method allowing to disable the Bluetooth adapter.
|
void |
discovery(DiscoveryListener discoveryListener)
Method allowing to discovery other bluetooth devices.
|
void |
enable()
Method allowing to enable the Bluetooth adapter.
|
void |
enableDiscovery(android.content.Context context,
int duration)
Method allowing to set the device into a discovery mode.
|
java.lang.String |
getAdapterName()
Method allowing to get the Bluetooth adapter name.
|
java.util.HashMap<java.lang.String,BluetoothAdHocDevice> |
getPairedDevices()
Method allowing to get all the paired Bluetooth devices.
|
void |
onEnableBluetooth(ListenerAdapter listenerAdapter)
Method allowing to notify if the Bluetooth adapter has been enabled.
|
void |
resetDeviceName()
Method allowing to reset the device local adapter name.
|
void |
unpairDevice(BluetoothAdHocDevice device)
Method allowing to unpair a previously paired bluetooth device.
|
void |
unregisterAdapter()
Method allowing to unregister a previously registered BroadcastReceiver related
to adapter event.
|
void |
unregisterDiscovery()
Method allowing to unregister the discovery broadcast.
|
void |
updateContext(android.content.Context context)
Method allowing to update the context of the current class.
|
boolean |
updateDeviceName(java.lang.String name)
Method allowing to update the device local adapter name.
|
public BluetoothAdHocManager(boolean verbose, android.content.Context context)
verbose
- a boolean value to set the debug/verbose mode.context
- a Context object which gives global information about an application
environment.public void disable()
public void enable()
public void enableDiscovery(android.content.Context context, int duration) throws BluetoothBadDuration
duration
- an integer value between 0 and 3600 which represents the time of
the discovery mode.BluetoothBadDuration
- signals that a Bluetooth Bad Duration exception has occurred.public java.util.HashMap<java.lang.String,BluetoothAdHocDevice> getPairedDevices()
public boolean updateDeviceName(java.lang.String name)
name
- a String value which represents the new name of the device adapter.public void resetDeviceName()
public void discovery(DiscoveryListener discoveryListener)
discoveryListener
- a discoveryListener object which contains callback functions.public void unregisterDiscovery() throws java.lang.IllegalArgumentException
java.lang.IllegalArgumentException
- signals that a method has been passed an illegal or
inappropriate argument.public java.lang.String getAdapterName()
public void unpairDevice(BluetoothAdHocDevice device) throws java.lang.reflect.InvocationTargetException, java.lang.IllegalAccessException, java.lang.NoSuchMethodException
device
- a BluetoothAdHocDevice object which represents a remote Bluetooth device.java.lang.reflect.InvocationTargetException
- signals that a method does not exist.java.lang.IllegalAccessException
- signals that an application tries to reflectively create
an instance which has no access to the definition of
the specified classjava.lang.NoSuchMethodException
- signals that a method does not exist.public void onEnableBluetooth(ListenerAdapter listenerAdapter)
listenerAdapter
- a listenerAdapter object which contains callback functions.public void unregisterAdapter()
public void updateContext(android.content.Context context)
context
- a Context object which gives global information about an application
environment.


This website has some subtext that goes here under the main title. It's a smaller font and the color is lower contrast."
this is some subtext under an illustration or image
this is some subtext under an illustration or image
this is some subtext under an illustration or image
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This is an inspiring quote, or a testimonial from a customer. Maybe it's just filling up space, or maybe people will actually read it. Who knows? All I know is that it looks nice.
Sign up for our product by clicking that button right over there!


Package io.ebean.event
Persist and Query Event Controllers and Listeners
-
Interface Summary Interface Description BeanDeleteIdRequest A request to delete a bean by Id value.BeanFindController Used to override the finding implementation for a bean.BeanPersistController Used to enhance or override the default bean persistence mechanism.BeanPersistListener Listens for committed bean events.BeanPersistRequest<T> Holds the information available for a bean persist (insert, update or delete).BeanPostConstructListener Fired after a bean is constructed, but not yet loaded from database.BeanPostLoad Fired after a bean is fetched and loaded from the database.BeanQueryAdapter Objects extending this modify queries prior their execution.BeanQueryRequest<T> Holds the information available for a bean query.BulkTableEvent The bulk table event.BulkTableEventListener Listen for bulk table events that occur.ServerConfigStartup Used to configure the server on startup. -
Class Summary Class Description AbstractBeanPersistListener Provides a base implementation of BeanPersistListener.BeanPersistAdapter A no operation implementation of BeanPersistController.ServletContextListener Listens for webserver server starting and stopping events.


---
layout: page
title: "About"
description: "This is what I do."
header-img: "img/about-bg.jpg"
---
I am a senior Computer Science and Pure Mathematics major in the Turing Scholars Honors Program at the University of Texas at Austin. I am an avid programmer, a music lover, and a sports enthusiast. Please refer to my resume for more information. Hook 'em! 🤘


| Package | Description |
|---|---|
| org.barghos.core |
This packet of barghos contains basic functionalities that are also used in the derived packets.
|
| org.barghos.core.api.color |
This package contains all interfaces for colors.
|
| org.barghos.core.api.tuple |
This package contains all interfaces for tuples.
|
| org.barghos.core.color |
This package contains all basic implementations of LDR/HDR RGB/RGBA colors.
|
| org.barghos.core.pool.color |
This package contains pools for colors.
|
| org.barghos.core.pool.tuple | |
| org.barghos.core.tuple |
This package contains all basic implementations of tuples.
|
| Class and Description |
|---|
| ITup2dR
This interface grants access to all reading methods of an 2-dimensional double tuple.
|
| ITup2fR
This interface grants access to all reading methods of an 2-dimensional float tuple.
|
| ITup3dR
This interface grants access to all reading methods of an 3-dimensional double tuple.
|
| ITup3fR
This interface grants access to all reading methods of an 3-dimensional float tuple.
|
| ITup4dR
This interface grants access to all reading methods of an 4-dimensional double tuple.
|
| ITup4fR
This interface grants access to all reading methods of an 4-dimensional float tuple.
|
| Class and Description |
|---|
| ITup3fR
This interface grants access to all reading methods of an 3-dimensional float tuple.
|
| ITup3fW
This interface grants access to all writing methods of an 3-dimensional float tuple.
|
| ITup3R
This interface grants access to all reading methods of an 3-dimensional tuple.
|
| ITup4fR
This interface grants access to all reading methods of an 4-dimensional float tuple.
|
| ITup4fW
This interface grants access to all writing methods of an 4-dimensional float tuple.
|
| ITup4R
This interface grants access to all reading methods of an 4-dimensional tuple.
|
| ITupfR
This interface grants access to all reading methods of an n-dimensional float tuple.
|
| ITupfW
This interface grants access to all writing methods of an n-dimensional float tuple.
|
| ITupR
This interface grants access to all reading methods of an n-dimensional tuple.
|
| Class and Description |
|---|
| ITup2dW
This interface grants access to all writing methods of an 2-dimensional double tuple.
|
| ITup2fW
This interface grants access to all writing methods of an 2-dimensional float tuple.
|
| ITup2R
This interface grants access to all reading methods of an 2-dimensional tuple.
|
| ITup3dW
This interface grants access to all writing methods of an 3-dimensional double tuple.
|
| ITup3fW
This interface grants access to all writing methods of an 3-dimensional float tuple.
|
| ITup3R
This interface grants access to all reading methods of an 3-dimensional tuple.
|
| ITup4dW
This interface grants access to all writing methods of an 4-dimensional double tuple.
|
| ITup4fW
This interface grants access to all writing methods of an 4-dimensional float tuple.
|
| ITup4R
This interface grants access to all reading methods of an 4-dimensional tuple.
|
| ITupdR
This interface grants access to all reading methods of an n-dimensional double tuple.
|
| ITupdW
This interface grants access to all writing methods of an n-dimensional double tuple.
|
| ITupfR
This interface grants access to all reading methods of an n-dimensional float tuple.
|
| ITupfW
This interface grants access to all writing methods of an n-dimensional float tuple.
|
| ITupR
This interface grants access to all reading methods of an n-dimensional tuple.
|
| Class and Description |
|---|
| ITup3fR
This interface grants access to all reading methods of an 3-dimensional float tuple.
|
| ITup3fW
This interface grants access to all writing methods of an 3-dimensional float tuple.
|
| ITup3R
This interface grants access to all reading methods of an 3-dimensional tuple.
|
| ITup4fR
This interface grants access to all reading methods of an 4-dimensional float tuple.
|
| ITup4fW
This interface grants access to all writing methods of an 4-dimensional float tuple.
|
| ITup4R
This interface grants access to all reading methods of an 4-dimensional tuple.
|
| ITupfR
This interface grants access to all reading methods of an n-dimensional float tuple.
|
| ITupfW
This interface grants access to all writing methods of an n-dimensional float tuple.
|
| ITupR
This interface grants access to all reading methods of an n-dimensional tuple.
|
| Class and Description |
|---|
| ITup3R
This interface grants access to all reading methods of an 3-dimensional tuple.
|
| ITup4R
This interface grants access to all reading methods of an 4-dimensional tuple.
|
| Class and Description |
|---|
| ITup3R
This interface grants access to all reading methods of an 3-dimensional tuple.
|
| ITup4R
This interface grants access to all reading methods of an 4-dimensional tuple.
|
| Class and Description |
|---|
| ITup2dR
This interface grants access to all reading methods of an 2-dimensional double tuple.
|
| ITup2dW
This interface grants access to all writing methods of an 2-dimensional double tuple.
|
| ITup2fR
This interface grants access to all reading methods of an 2-dimensional float tuple.
|
| ITup2fW
This interface grants access to all writing methods of an 2-dimensional float tuple.
|
| ITup2R
This interface grants access to all reading methods of an 2-dimensional tuple.
|
| ITup3dR
This interface grants access to all reading methods of an 3-dimensional double tuple.
|
| ITup3dW
This interface grants access to all writing methods of an 3-dimensional double tuple.
|
| ITup3fR
This interface grants access to all reading methods of an 3-dimensional float tuple.
|
| ITup3fW
This interface grants access to all writing methods of an 3-dimensional float tuple.
|
| ITup3R
This interface grants access to all reading methods of an 3-dimensional tuple.
|
| ITup4dR
This interface grants access to all reading methods of an 4-dimensional double tuple.
|
| ITup4dW
This interface grants access to all writing methods of an 4-dimensional double tuple.
|
| ITup4fR
This interface grants access to all reading methods of an 4-dimensional float tuple.
|
| ITup4fW
This interface grants access to all writing methods of an 4-dimensional float tuple.
|
| ITup4R
This interface grants access to all reading methods of an 4-dimensional tuple.
|
| ITupdR
This interface grants access to all reading methods of an n-dimensional double tuple.
|
| ITupdW
This interface grants access to all writing methods of an n-dimensional double tuple.
|
| ITupfR
This interface grants access to all reading methods of an n-dimensional float tuple.
|
| ITupfW
This interface grants access to all writing methods of an n-dimensional float tuple.
|
| ITupR
This interface grants access to all reading methods of an n-dimensional tuple.
|


Kevin Dreyer
I am a technical support lead and web developer with a passion for helping people use technology successfully. Currently, I am a stay-at-home dad taking care of 2 kids while also working on personal projects and studying computer science and information technology.
Technical Skills
Experence with the following tools and technology.
Projects
Here are some projects I have worked on.
SchoolBookDrive
WordPress Bookdrive website
Web site for a school to run a book drive to increase the school’s library diverse book collection. Built on WordPress with the books imported through a spreadsheet and donations handled with PayPal.
WebsiteTools Used: WordPress 5, WordPress.com, HTML, Google Sheets, PayPal
Coders Work Journal
Web Application and API
CLIJ is a secure, cloud-based note-taking app. Create, retrieve, and update your notes directly from the command line or web. Set up schedules to receive running reports of your notes through the use of CLIJ's web GUI
Website ReproTools Used: React/Redux, Node.js/Express, MongoDB, OAuth, MongoDB, JSON Web Tokens, hosted on Firebase and Heroku
Trip Up
Trip planning Web API
Web API for group trip planning with authentication and access control
ReproTools Used: Node.js/Express, MySQL, Sequelize, JSDoc, JSON Web Tokens, Bcrypt, Jest, JavaScript, Heroku
NASA 3D-Printed Habitat Challenge
BIM project
Assisted Colorado School of Mines Nasa Challenge Participants in understanding and developing the BIM for a virtual Mars Habitat Design and 3D printing Competition.
NASA ArticleTools Used: BIM, Revit


Hello!
Thank you for taking the time to go over my profile. I am currently working at AMD as a senior staff engineer in Machine Learning and Computer Vision Group. I am also serving as the chairman of the Khronos OpenVX™ working group committee and deeply involved in the Khronos NNEF™ working group.
If you have any queries about Machine Learning and Computer Vision activities at Khronos or AMD, please send me a mail.
MIVisionX ML Model Validation Tool using pre-trained ONNX/NNEF/Caffe models to analyze, summarize, & validate..
Collaborated with Mike Schmit, Hansel Yang, Lakshmi Kumar, & Seyedreza Najafi from ML Computer Vision Group at AMD
MIVisionX Inference Analyzer using pre-trained ONNX/NNEF/Caffe models to analyze and summarize images.
ADAT, is a comprehensive set of help tools for neural net creation, development, training and deployment. The Toolkit provides users with help tools to design, develop, quantize, prune, retrain, and infer neural network work in any framework. The Toolkit is designed to help users deploy their work to any AMD or 3rd party hardware, from embedded to servers.
Collaborated with Mike Schmit, Director of Software Engineering, ML Computer Vision Group at AMD
Radeon Loom Stitching Library is a highly optimized library for 360-degree video stitching applications
Real-time live 360-degree video stitching optimized for Radeon Pro Graphics, supports upto 31 cameras and upto 7680x3840 output resolution
Dissertation Work:
Embedded Vision Summit 2021 - OpenVX 1.3: An Open Standard for Computer Vision Software Acceleration
Khronos Educational Webinar - 2020 - The Advantages of Performance, Portability, and Memory Footprint in OpenVX
All-Russian Conference on Artificial Intelligence - 2020 - The Russian Congress united on one platform for the Russian Association of Artificial Intelligence, the Interregional Association for Cognitive Studies, the Russian Neural Networks Society and the Russian Physiological Society. Talk about Machine learning using open-source API
Graphicon 2020 - the 30th anniversary international conference on computer graphics and machine vision at the ITMO University. Talk about Computer Vision using OpenVX 1.3 at St. Petersburg, Russia
Embedded Vision Summit 2020 - Democratizing Computer Vision and Machine Learning with Open, Royalty-Free Standards: OpenVX
Graphicon 2019 - MIVisionX: Computer Vision & Machine Learning with OpenVX at Bryansk, Russia
MIVisonX Inference Tutorial - 2019 - Hands-on Inference tutorial at IEEE SPS Santa Clara Valley's Machine Learning event
Inference with OpenVX - 2019 - at Khronos day-long hands-on Hardware Acceleration for Machine Learning and Computer Vision through Khronos Open Standard APIs at Embedded Vision Summit 2019
NAGAP 28th Annual Conference - Research talk on "Improving Your CRM on a Shoestring Budget" at New Orleans
Chairman (’19, ’20, & ’21) of The Khronos OpenVX™ working group committee
Vice Chairman (’18, ’19, & ’20), Secretary (’17), & Treasurer (’16) of the Institute of Electrical and Electronics Engineers (IEEE) Signal Processing Society (SPS) Santa Clara Valley Chapter
Chairman of the Student Health Advisory Board at SIU Carbondale (’10, & ’11)
Vice President of Omega Delta Phi Fraternity, Inc. at SIU Carbondale (’09, & ’10)
President of National Service Scheme group at VIT, Bangalore, India (’06, ’07, & ’08)


Yumna Akhtar
Portfolio
Contact
About
Portfolio
Project-1
Project-2
Project-3
Project-4
Project-5
Project-6
Project-7
Project-8


Assigning a Custom Analysis Profile to a Virtual Machine
You can create and assign different analysis profiles for specific virtual machine configurations using the ManageIQ user interface. This document describes the steps required to create a custom virtual machine analysis profile, and assigning it to a virtual machine for use with SmartState analysis, via a control policy.
-
Creating a Virtual Machine Analysis Profile.
-
Creating an Action to Assign the Virtual Machine Analysis Profile to Analysis Task
-
Creating a Virtual Machine Control Policy.
-
Creating a Policy Profile and Assigning the Virtual Machine Control Policy.
-
Assigning the Policy Profile to a Virtual Machine.
Creating a Virtual Machine Analysis Profile
-
Log into the appliance as the admin user.
-
Click Configuration.
-
Expand the Settings accordion, then click Analysis Profiles.
-
Click (Configuration), then (Add VM Analysis Profile).
-
In Basic Information, enter Name and Description for the analysis profile.
-
In the Category tab, select the categories you want to collect information for under Category Selection. The Category tab is available for virtual machine profiles only.
-
In the File tab, click <New Entry> and specify the file to be scanned and if you want to collect contents for, then click Save. Repeat the step for adding multiple file name entries.
-
In the Registry tab, enter the Registry Key and Registry Value, then click Save. To determine whether a registry key exists without providing a value, enter ` ` in *Registry Value</emphasis>. The Registry tab is available for virtual machine profiles only.
-
In the Event Log tab, specify the event log entries to collect. Enter a Filter Message to look for specific text in a message. Enter a Level (info, warn or error, for example) to specify the event level. Enter the Source for the event log entry and # (Number) of Days to specify how far back to check.
-
Click Add.
Creating an Action to Assign the Virtual Machine Analysis Profile to the Analysis Task
Actions are performed after the condition is evaluated. You can associate actions with specific events when you create a policy. ManageIQ provides a set of default actions, but you can also create custom actions using the ManageIQ user interface.
Use this procedure to create a custom action by adding the Assign Profile to Analysis Task action type to the virtual machine analysis profile (created in Creating a Virtual Machine Analysis Profile).
-
Navigate to menu:Control[Explorer].
-
Expand the Actions accordion and click (Configuration), then (Add a new Action).
-
Enter a Description for the new action. This will be the name given to your new action.
-
Select Assign Profile to Analysis Task from the Action Type list.
-
Select the newly-created virtual machine analysis profile from the Analysis Profiles list.
-
Click Add.
Note:
You can only associate this action with an analysis start event.
The action is created and added to the Available Actions list. Associate this action with the VM Analysis Start event when you create a virtual machine control policy in the next procedure.
Creating a Virtual Machine Control Policy
You can create a control policy by combining an event, a condition, and an action. The procedure below describes how to create a virtual machine control policy to assign the newly-created action to the VM Analysis Start event. Optionally, you can use a scope expression that is tested immediately when the policy is triggered by an event. If the item is out of scope, then the policy will not continue on to the conditions, and the assigned action will not run.
-
Browse to menu: Control > Explorer.
-
Expand the Policies accordion, and click Control Policies.
-
Select Vm Control Policies.
-
Click Configuration, then Add a New VM and Instance Control Policy.
-
Enter a Description. This will be the name given to your VM control policy.
-
Clear the Active box if you do not want this policy processed even when assigned to a resource.
-
Optional: Enter a Scope (you can also create a scope as part of a condition, or not use one at all). If the virtual machine is not included in the scope, the assigned action will not run.
- You can use the drop-down list to create an expression for the Scope. Based on what you choose, different options appear. Click Commit expression element changes to add the scope.
-
Enter Notes if required.
-
Click Add. The policy is added and listed under Vm Control Policies in the Policies accordion.
-
Select the newly-added VM control policy. You can now associate events, conditions, and actions with the policy.
-
Click Configuration, then Edit this Policy’s Event assignments.
-
Under VM Operation, set VM Analysis Start to Yes.
-
Click Save.
-
Click the VM Analysis Start event to configure actions.
-
Click Configuration, then Edit Actions for this Policy Event.
-
In Order of Actions if ALL Conditions are True, select the action created in Creating an Action to Assign the Virtual Machine Analysis Profile to the Analysis Task from the Available Actions list. This action will take place if the resources meet the conditions of the policy.
Note:
Each selected action can be executed synchronously or asynchronously; a synchronous action will not start until the previous synchronous action is completed, while an asynchronous action allows the next action to start whether or not the first action has completed. Also, at least one ManageIQ server in the ManageIQ zone must have the notifier server role enabled for the trap to be sent.
-
Click () which will move the action to Selected Actions. The selected action is set to (S) Synchronous by default. From Selected Actions, select the action, then:
-
Click A (Set selected Actions to Asynchronous) to make it asynchronous.
-
Click S (Set selected Actions to Synchronous) to make it synchronous. If creating a synchronous action, use the up and down arrows to identify in what order you want the actions to run.
-
-
Click Save.
Creating a Policy Profile and Assigning the Virtual Machine Control Policy
Add a new policy profile and assign the virtual machine control policy (created in Creating a Virtual Machine Control Policy) to it.
-
Browse to menu: Control > Explorer.
-
Expand the Policy Profiles accordion, click Configuration, then Add a New Policy Profile.
-
In the Basic Information area, enter a Description for the policy profile.
-
Under Policy Selection, select the virtual machine control policy created in Creating a Virtual Machine Control Policy from the Available Policies list.
-
Click () to move the selected virtual machine control policy into this profile.
-
Click Add.
Assigning the Policy Profile to a Virtual Machine
Assign the policy profile you created in Creating a Policy Profile and Assigning the Virtual Machine Control Policy to a virtual machine, and initiate SmartState analysis.
Note:
Policy profiles can be specified at multiple levels. If you assign a policy profile to a provider (Amazon EC2 or OpenStack for example), the profile will apply to all hosts or virtual machines for that provider.
-
Browse to menu: Compute > Clouds > Instances or menu: Compute > Infrastructure > Virtual Machines. Select the virtual machine or instance.
-
Click Policy, then Manage Policies.
-
Under Select Policy Profiles, select the policy profile created in Creating a Policy Profile and Assigning the Virtual Machine Control Policy. It will turn blue to show the selection. Click the triangle next to the policy profile to see its member policies.
-
Click Save.
-
Click Configuration, then Perform SmartState Analysis. A pop-up window appears to confirm the action.
-
Click OK. SmartState analysis is initiated for the selected virtual machine or instance from the ManageIQ database.
SmartState analysis will now report back findings specified by the custom virtual machine analysis profile.


Introduction
This is an R package for performing various study diagnostics, many of which are not specific to any particular study design.
Features
- Show cohort inclusion rule attrition.
- List all source codes used when running a cohort definition on a specific database.
- Find orphan codes, (source) codes that should be, but are not included in a particular concept set.
- Compute cohort incidence across calendar years, age, and gender.
- Break down index events into the specific concepts that triggered them.
- Compute overlap between two cohorts.
- Characterize cohorts, and compare these characterizations.
- Explore patient profiles of a random sample of subjects in a cohort.
Screenshot
Technology
The CohortDiagnostics package is an R package.
System Requirements
Running the package requires R with the package rJava installed. Also requires Java 1.7 or higher.
Installation
R package
To install the latest development version, install from GitHub:
License
CohortDiagnostics is licensed under Apache License 2.0
Development
CohortDiagnostics is being developed in R Studio.
Development status
Beta testing


{% include "content/includes/header.html" %} {% unless page.template == 'alt-1-topic-landing' %} {% unless showactionbar == false %} {% if path contains 'disability-benefits' %} {% include "content/includes/action-bar.html" action_text="Apply for Disability Benefits" action_url="/disability-benefits/apply-for-benefits/" action_class="va-action-bar--header" %} {% endif %} {% if path contains 'education' %} {% include "content/includes/action-bar.html" action_text="Apply for Education Benefits" action_url="/education/apply-for-education-benefits/" action_class="va-action-bar--header" %} {% endif %} {% if path contains 'healthcare' %} {% if showtempbar == true %} {% else %} {% include "content/includes/action-bar.html" action_text="Apply for VA Health Care" action_url="/healthcare/apply/application" action_class="va-action-bar--header" %} {% endif %} {% endif %} {% endunless %} {% endunless %} {% include "content/includes/breadcrumbs.html" %}


$N Multistroke Recognizer
Typescript port of
$N Multistroke Recognizer
.
Use Golden Section Search (original)
Use Protractor (faster)
Use bounded rotation invariance (±45°)
Require same no. of component strokes
Clear


{% extends "layout.html" %} {% set active_page = "about" %} {% block title %}About{% endblock %} {% block body %}
Open data is a great chance to make development aid not only more transparent, but also more efficient. Having been an aid worker for a while in Egypt and Germany myself, I could see how much information is needed. It is often very difficult to get even an overview of who is doing what. Now having the opportunity to look into various development organizations as a consultant I have seen many bottlenecks and the potential open data has to make development organizations more efficient. Open data will allow organizations to get involved and collaborate in new ways.
Nowadays we have already some interesting and helpful data sources at hand, such as the Creditor Reporting System and IATI. But most websites show only one of these two data sets and often only a fraction of the respective set. Unfortunately development organizations such as UNDP or DFID only publish their data and have not understood the point of combining data and making all data easily accessible. As a beneficiary of development aid, a journalist, activist or an aid worker, I do not want to visit 30+ websites to see all data. I want to it all in one place: Fast and easy. That's why I have set up this page.
Some might argue that his page is just another visualization of aid data, but it intends to go beyond that:
No doubt this platform is only a first step and much more needs to be done. Keep an eye on the blog or Twitter to follow latest changes. Keep in mind this version already took countless hours to develop and to create clean data and find work-arounds around the many pitfalls of data sets to make this happen. For example, the IATI data is unfortunately similar to CRS at some levels and in some areas is quite messy. Everybody is welcome to send feedback and propose improvements here or via twitter. As this is a voluntarily project I can’t promise too much, but further development is ensured.
Although everyone tends to look at the IATI data these days, I believe the CRS data is still really strong as it has entries on all ODA countries, providing a better overview. That's why this page places emphasis on CRS rather than IATI, but the latter will be developed much further in the coming months.
This website was only possible thanks to some groundwork by others. First up the development organizations, which provide the data to CRS and IATI. And of course thanks to open data enthusiasts worldwide opening up data. But also thanks to many fantastic open source libraries such as Flask, Openspending, Zurb Foundation, jQuery Sparklines, Lastly a special thanks to Mark Brough for his relentless work on IATI to make XML data also available in other data standards. I know the IATI datastore will hopefully change that.Open Aid Data itself is also open source and available here on Github.
Please keep in mind the following points when you digest the data on this page:
For further questions send me an email to<EMAIL_ADDRESS>Openaiddata.org is possible thanks to the sponsorship from www.crisscrossed.de and www.wethinq.com.


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R
- the type of the table row keysC
- the type of the table column keysV
- the type of the mapped values@GwtCompatible @Beta public interface Table<R,C,V>
A collection that associates an ordered pair of keys, called a row key and a column key, with a single value. A table may be sparse, with only a small fraction of row key / column key pairs possessing a corresponding value.
The mappings corresponding to a given row key may be viewed as a Map
whose keys are the columns. The reverse is also available, associating a
column with a row key / value map. Note that, in some implementations, data
access by column key may have fewer supported operations or worse performance
than data access by row key.
The methods returning collections or maps always return views of the underlying table. Updating the table can change the contents of those collections, and updating the collections will change the table.
All methods that modify the table are optional, and the views returned by
the table may or may not be modifiable. When modification isn't supported,
those methods will throw an UnsupportedOperationException
.
| Nested Class Summary | |
|---|---|
static interface |
Table.Cell<R,C,V>
Row key / column key / value triplet corresponding to a mapping in a table. |
| Method Summary | |
|---|---|
Set<Table.Cell<R,C,V>> |
cellSet()
Returns a set of all row key / column key / value triplets. |
void |
clear()
Removes all mappings from the table. |
Map<R,V> |
column(C columnKey)
Returns a view of all mappings that have the given column key. |
Set<C> |
columnKeySet()
Returns a set of column keys that have one or more values in the table. |
Map<C,Map<R,V>> |
columnMap()
Returns a view that associates each column key with the corresponding map from row keys to values. |
boolean |
contains(Object rowKey,
Object columnKey)
Returns true if the table contains a mapping with the specified
row and column keys. |
boolean |
containsColumn(Object columnKey)
Returns true if the table contains a mapping with the specified
column. |
boolean |
containsRow(Object rowKey)
Returns true if the table contains a mapping with the specified
row key. |
boolean |
containsValue(Object value)
Returns true if the table contains a mapping with the specified
value. |
boolean |
equals(Object obj)
Compares the specified object with this table for equality. |
V |
get(Object rowKey,
Object columnKey)
Returns the value corresponding to the given row and column keys, or null if no such mapping exists. |
int |
hashCode()
Returns the hash code for this table. |
boolean |
isEmpty()
Returns true if the table contains no mappings. |
V |
put(R rowKey,
C columnKey,
V value)
Associates the specified value with the specified keys. |
void |
putAll(Table<? extends R,? extends C,? extends V> table)
Copies all mappings from the specified table to this table. |
V |
remove(Object rowKey,
Object columnKey)
Removes the mapping, if any, associated with the given keys. |
Map<C,V> |
row(R rowKey)
Returns a view of all mappings that have the given row key. |
Set<R> |
rowKeySet()
Returns a set of row keys that have one or more values in the table. |
Map<R,Map<C,V>> |
rowMap()
Returns a view that associates each row key with the corresponding map from column keys to values. |
int |
size()
Returns the number of row key / column key / value mappings in the table. |
Collection<V> |
values()
Returns a collection of all values, which may contain duplicates. |
| Method Detail |
|---|
boolean contains(@Nullable Object rowKey, @Nullable Object columnKey)
true
if the table contains a mapping with the specified
row and column keys.
rowKey
- key of row to search forcolumnKey
- key of column to search forboolean containsRow(@Nullable Object rowKey)
true
if the table contains a mapping with the specified
row key.
rowKey
- key of row to search forboolean containsColumn(@Nullable Object columnKey)
true
if the table contains a mapping with the specified
column.
columnKey
- key of column to search forboolean containsValue(@Nullable Object value)
true
if the table contains a mapping with the specified
value.
value
- value to search forV get(@Nullable Object rowKey, @Nullable Object columnKey)
null
if no such mapping exists.
rowKey
- key of row to search forcolumnKey
- key of column to search forboolean isEmpty()
true
if the table contains no mappings.
int size()
boolean equals(@Nullable Object obj)
cellSet()
, are equal.
equals
in class Object
obj
- the reference object with which to compare.
true
if this object is the same as the obj
argument; false
otherwise.Object.hashCode()
,
HashMap
int hashCode()
cellSet()
.
hashCode
in class Object
Object.equals(java.lang.Object)
,
System.identityHashCode(java.lang.Object)
void clear()
V put(R rowKey, C columnKey, V value)
rowKey
- row key that the value should be associated withcolumnKey
- column key that the value should be associated withvalue
- value to be associated with the specified keys
null
if
no mapping existed for the keysvoid putAll(Table<? extends R,? extends C,? extends V> table)
put(R, C, V)
with each row key / column key / value
mapping in table
.
table
- the table to add to this tableV remove(@Nullable Object rowKey, @Nullable Object columnKey)
rowKey
- row key of mapping to be removedcolumnKey
- column key of mapping to be removed
null
if
no such value existedMap<C,V> row(R rowKey)
Changes to the returned map will update the underlying table, and vice versa.
rowKey
- key of row to search for in the table
Map<R,V> column(C columnKey)
Changes to the returned map will update the underlying table, and vice versa.
columnKey
- key of column to search for in the table
Set<Table.Cell<R,C,V>> cellSet()
add
or addAll
methods.
Set<R> rowKeySet()
Set<C> columnKeySet()
Collection<V> values()
Map<R,Map<C,V>> rowMap()
put()
or putAll()
, or
setValue()
on its entries.
In contrast, the maps returned by rowMap().get()
have the same
behavior as those returned by row(R)
. Those maps may support setValue()
, put()
, and putAll()
.
Map<C,Map<R,V>> columnMap()
put()
or putAll()
,
or setValue()
on its entries.
In contrast, the maps returned by columnMap().get()
have the
same behavior as those returned by column(C)
. Those maps may support
setValue()
, put()
, and putAll()
.
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| File: | lib/Dancer/Plugin.pm |
| Coverage: | 90.5% |
| line | subroutine |
|---|---|
| 4 | BEGIN |
| 5 | BEGIN |
| 6 | BEGIN |
| 8 | BEGIN |
| 9 | BEGIN |
| 10 | BEGIN |
| 11 | BEGIN |
| 12 | BEGIN |
| 14 | BEGIN |
| 15 | BEGIN |
| 32 | add_hook |
| 34 | plugin_args |
| 37 | plugin_setting |
| 44 | register_hook |
| 48 | execute_hooks |
| 55 | execute_hook |
| 59 | register |
| 85 | register_plugin |
| 90 | BEGIN |
| 100 | set_plugin_symbols |
| 105 | BEGIN |


Co-op bank losses widen in wake of PPI costs and fierce mortgage market
by Sebastian McCarthyThe Co-operative Bank has reported widening losses during the third quarter of this year, as it became the latest in a long line of lenders to take a financial hit from the payment protection insurance (PPI) scandal.
The British bank reported losses before tax of £118.6m during the three-month period, deepening from £87m in the same quarter last year.
Net interest margin – a key measure of underlying profitability – also tumbled seven basis points to 1.76 per cent.
Read more: P2P lender Zopa makes banking debut as pressure mounts
Half of the losses were due to a £60m charge from customer claims over the mis-selling of PPI.
A late surge in PPI claims before the deadline closed in August has inflicted huge charges on many of Britain’s largest banks.
In recent weeks, RBS, Llloyds Banking Group, Santander and a number of other major lenders reported significant PPI costs that have heavily impacted on their quarterly results.
The City’s watchdog, the Financial Conduct Authority (FCA), has reported that roughly £36bn in compensation has been paid out so far, with the typical payout amounting to £2,000.
Read more: Halfords’ profit and revenue dip as it snaps up garage chain
However, think tank New City Agenda has predicted that the total PPI bill could cost as much as £53bn.
The Co-op has also faced pressure from an increasingly competitive mortgage market, where a price war has eaten into profits in the banking sector.


protected abstract fun condition(): Boolean
The Condition to test to determine which Command to run.
Return true if onTrue should be run or false if onFalse should be run


class DAC – digital to analog conversion¶
The DAC is used to output analog values (a specific voltage) on pin X5 or pin X6. The voltage will be between 0 and 3.3V.
This module will undergo changes to the API.
Example usage:
from pyb import DAC
dac = DAC(1) # create DAC 1 on pin X5
dac.write(128) # write a value to the DAC (makes X5 1.65V)
dac = DAC(1, bits=12) # use 12 bit resolution
dac.write(4095) # output maximum value, 3.3V
To output a continuous sine-wave:
import math
from pyb import DAC
# create a buffer containing a sine-wave
buf = bytearray(100)
for i in range(len(buf)):
buf[i] = 128 + int(127 * math.sin(2 * math.pi * i / len(buf)))
# output the sine-wave at 400Hz
dac = DAC(1)
dac.write_timed(buf, 400 * len(buf), mode=DAC.CIRCULAR)
To output a continuous sine-wave at 12-bit resolution:
import math
from array import array
from pyb import DAC
# create a buffer containing a sine-wave, using half-word samples
buf = array('H', 2048 + int(2047 * math.sin(2 * math.pi * i / 128)) for i in range(128))
# output the sine-wave at 400Hz
dac = DAC(1, bits=12)
dac.write_timed(buf, 400 * len(buf), mode=DAC.CIRCULAR)
Constructors¶
- class pyb.DAC(port, bits=8, *, buffering=None)¶
Construct a new DAC object.
port
can be a pin object, or an integer (1 or 2). DAC(1) is on pin X5 and DAC(2) is on pin X6.bits
is an integer specifying the resolution, and can be 8 or 12. The maximum value for the write and write_timed methods will be 2**``bits``-1.The buffering parameter selects the behaviour of the DAC op-amp output buffer, whose purpose is to reduce the output impedance. It can be
None
to select the default (buffering enabled forDAC.noise()
,DAC.triangle()
andDAC.write_timed()
, and disabled forDAC.write()
),False
to disable buffering completely, orTrue
to enable output buffering.When buffering is enabled the DAC pin can drive loads down to 5KΩ. Otherwise it has an output impedance of 15KΩ maximum: consequently to achieve a 1% accuracy without buffering requires the applied load to be less than 1.5MΩ. Using the buffer incurs a penalty in accuracy, especially near the extremes of range.
Methods¶
- DAC.init(bits=8, *, buffering=None)¶
Reinitialise the DAC. bits can be 8 or 12. buffering can be
None
,False
orTrue
; see above constructor for the meaning of this parameter.
- DAC.deinit()¶
De-initialise the DAC making its pin available for other uses.
- DAC.noise(freq)¶
Generate a pseudo-random noise signal. A new random sample is written to the DAC output at the given frequency.
- DAC.triangle(freq)¶
Generate a triangle wave. The value on the DAC output changes at the given frequency and ramps through the full 12-bit range (up and down). Therefore the frequency of the repeating triangle wave itself is 8192 times smaller.
- DAC.write(value)¶
Direct access to the DAC output. The minimum value is 0. The maximum value is 2**``bits``-1, where
bits
is set when creating the DAC object or by using theinit
method.
- DAC.write_timed(data, freq, *, mode=DAC.NORMAL)¶
Initiates a burst of RAM to DAC using a DMA transfer. The input data is treated as an array of bytes in 8-bit mode, and an array of unsigned half-words (array typecode ‘H’) in 12-bit mode.
freq
can be an integer specifying the frequency to write the DAC samples at, using Timer(6). Or it can be an already-initialised Timer object which is used to trigger the DAC sample. Valid timers are 2, 4, 5, 6, 7 and 8.mode
can beDAC.NORMAL
orDAC.CIRCULAR
.Example using both DACs at the same time:
dac1 = DAC(1) dac2 = DAC(2) dac1.write_timed(buf1, pyb.Timer(6, freq=100), mode=DAC.CIRCULAR) dac2.write_timed(buf2, pyb.Timer(7, freq=200), mode=DAC.CIRCULAR)
Constants¶
- DAC.NORMAL¶
NORMAL mode does a single transmission of the waveform in the data buffer,
- DAC.CIRCULAR¶
CIRCULAR mode does a transmission of the waveform in the data buffer, and wraps around to the start of the data buffer every time it reaches the end of the table.


Pakistan vs Australia 1st test | Pakistan win toss, choose to bat
As expected, Pakistan will give 16-year-old pace sensation Naseem Shah his first cap, making him one of the youngest players in Test history
by AFPPakistan captain Azhar Ali won the toss and chose to bat in the first cricket Test in hot and humid conditions at the Gabba in Brisbane on November 21.
As expected, Pakistan will give 16-year-old pace sensation Naseem Shah his first cap, making him one of the youngest players in Test history. Shah, who decided to remain on tour after his mother died last week, made the team after impressing with an eight-over spell against Australia A in a lead-up game in Perth.
Pakistan omitted experienced paceman Mohammad Abbas in favour of the players who performed so well against Australia A.
Australia have recalled opener Joe Burns to partner with David Warner at the top of the order and middle-order batsman Travis Head.
"There's a bit of grass on the pitch but it looks a good pitch to bat on, especially if you get through the new ball then there will be lots of runs in it," Azhar said. "We're really excited to see Naseem play. It was very emotional this morning when he got his cap.
"It was difficult to leave out Mohammad Abbas but sometimes form can take over and we know he's very good and our number one bowler, but at the moment these three pacers are doing the job and we picked them."
- Australia - Joe Burns, David Warner, Marnus Labuschagne, Steve Smith, Travis Head, Matthew Wade, Tim Paine (capt), Pat Cummins, Mitchell Starc, Nathan Lyon, Josh Hazlewood.
- Pakistan - Shan Masood, Azhar Ali (capt), Haris Sohail, Babar Azam, Asad Shafiq, Iftikhar Ahmed, Mohammad Rizwan, Yasir Shah, Shaheen Afridi, Imran Khan, Naseem Shah.
- Umpires - Richard Illingworth (ENG), Richard Kettleborough (ENG)
- TV Umpire - Michael Gough (ENG)
- Match Referee - Jeff Crowe (NZL)


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