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What
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Exciting projects
We love to work because what we do really excites, inspires and motivates us. There is never a boring day at BelVG – each day presents a new project, a different challenge, a skill to apply and many other to obtain.
Exciting projects
We love to work because what we do really excites, inspires and motivates us. There is never a boring day at BelVG – each day presents a new project, a different challenge, a skill to apply and many other to obtain.
Competitive salaries
We estimate our team highly not only in words, but provide a worthy financial equivalent to our value as well.
Advanced technologies
We realize how much of the project success depends on the proper equipment; therefore, we provide our developers, designers, sales and marketing professionals with the most advanced gear and software.


WV – Sen. Joe Manchin, III (D) and Sen. Shelley Moore Capito (R)
Committees
Joe Manchin, III is the #9 Democrat on the Senate Energy Subcommittee on Energy
Joe Manchin, III is the #7 Democrat on the Senate Appropriations Subcommittee on Commerce, Justice, Science, and Related Agencies
Joe Manchin, III is the #14 Democrat on the Senate Committee on Appropriations
Joe Manchin, III is the #1 Democrat on the Senate Committee on Energy and Natural Resources
Committees
Shelley Moore Capito is the #7 Republican on the Senate Appropriations Subcommittee on Commerce, Justice, Science, and Related Agencies
Shelley Moore Capito is the #11 Republican on the Senate Committee on Appropriations
Shelley Moore Capito is the #10 Republican on the Senate Committee on Commerce, Science, and Transportation
HEP Grants
This state received no SC HEP grants from 2012-2020
SC Contracts
This state received no SC contracts from 2012-2020
NSF MPS Grants
In the past 9 years, this state has received: 107 NSF MPS grants, totalling $23,199,456
Year Institution Amount ($)
------ --------------------------------------------- ------------
2020 West Virginia University Research Corporation 75,211
2019 West Virginia University Research Corporation 2,566,450
2018 Marshall University Research Corporation 415,000
2018 West Virginia University Research Corporation 3,832,303
2017 West Virginia University Research Corporation 2,436,019
2016 West Virginia University Research Corporation 3,277,030
2015 West Virginia University Research Corporation 1,375,140
2015 Wv Univ Research Corp 1,474,918
2014 West Virginia University Research Corporation 2,904,443
2013 West Virginia University Research Corporation 2,156,346
2012 Marshall University Research Corporation 338,845
2012 West Virginia University Research Corporation 2,347,751
SULI/CCI Interns
From 2014-2018, this state had 18 SULI/CCI interns
# Interns Program College
----------- --------- ------------------------------
10 SULI West Virginia University
3 SULI Marshall University
3 SULI West Virginia Wesleyan College
2 SULI Fairmont State University
18 — — Back to top
WV-01 – Rep. David B. McKinley (R) – Wikipedia
Committees
David B. McKinley is the #10 Republican on the House Committee on Energy and Commerce
HEP Grants
This district received no SC HEP grants from 2012-2020
SC Contracts
This district received no SC contracts from 2012-2020
NSF MPS Grants
In the past 9 years, this district has received: $22,445,611 in NSF MPS grants.
Year Institution Amount ($)
------ --------------------------------------------- ------------
2020 West Virginia University Research Corporation 75,211
2019 West Virginia University Research Corporation 2,566,450
2018 West Virginia University Research Corporation 3,832,303
2017 West Virginia University Research Corporation 2,436,019
2016 West Virginia University Research Corporation 3,277,030
2015 West Virginia University Research Corporation 1,375,140
2015 Wv Univ Research Corp 1,474,918
2014 West Virginia University Research Corporation 2,904,443
2013 West Virginia University Research Corporation 2,156,346
2012 West Virginia University Research Corporation 2,347,751
SULI/CCI Interns
From 2014-2018, this district had 12 SULI/CCI interns
Term Name College Host Lab Program
----------- ---------------------- ------------------------- -------------------------------------- ---------
Summer 2017 Aarthy Shah West Virginia University Ames National Laboratory SULI
Summer 2015 Lucas Price West Virginia University Brookhaven National Laboratory SULI
Summer 2015 Clayton Robert Johnson West Virginia University Argonne National Laboratory SULI
Summer 2014 Bryan James Foley Fairmont State University Brookhaven National Laboratory SULI
Summer 2014 Clayton Robert Johnson West Virginia University Argonne National Laboratory SULI
Summer 2014 Julie Michelle Button West Virginia University Lawrence Livermore National Laboratory SULI
Summer 2014 Megan Jewell West Virginia University Ames National Laboratory SULI
Summer 2014 Rebecca Buonavita Posa West Virginia University Idaho National Laboratory SULI
Spring 2017 Kodey Jones West Virginia University Oak Ridge National Laboratory SULI
Spring 2015 Bryan James Foley Fairmont State University Brookhaven National Laboratory SULI
Spring 2014 Ethel Perez-Hoyos West Virginia University Lawrence Berkeley National Laboratory SULI
Fall 2014 Julie Michelle Button West Virginia University Lawrence Livermore National Laboratory SULI
WV-02 – Rep. Alexander X. Mooney (R) – Wikipedia
HEP Grants
This district received no SC HEP grants from 2012-2020
SC Contracts
This district received no SC contracts from 2012-2020
NSF MPS Grants
This district received no NSF MPS grants from 2012-2020
SULI/CCI Interns
From 2014-2018, this district had 3 SULI/CCI interns
Term Name College Host Lab Program
----------- ------------------ ------------------------------ ---------------------------------------------- ---------
Summer 2016 Thomas Alan Haines West Virginia Wesleyan College Thomas Jefferson National Accelerator Facility SULI
Summer 2016 Kelsie Krantz West Virginia Wesleyan College Savannah River National Laboratory SULI
Summer 2015 Asa Nichols West Virginia Wesleyan College National Renewable Energy Laboratory SULI
WV-03 – Rep. Carol D. Miller (R) – Wikipedia
HEP Grants
This district received no SC HEP grants from 2012-2020
SC Contracts
This district received no SC contracts from 2012-2020
NSF MPS Grants
In the past 9 years, this district has received: $753,845 in NSF MPS grants.
Year Institution Amount ($)
------ ---------------------------------------- ------------
2018 Marshall University Research Corporation 415,000
2012 Marshall University Research Corporation 338,845
SULI/CCI Interns
From 2014-2018, this district had 3 SULI/CCI interns
Term Name College Host Lab Program
----------- ----------------------- ------------------- ----------------------------- ---------
Summer 2017 Henok Atsbaha Marshall University Oak Ridge National Laboratory SULI
Summer 2016 Amber Bettis Marshall University Oak Ridge National Laboratory SULI
Fall 2015 Matthew Joseph Haldeman Marshall University Oak Ridge National Laboratory SULI


A resposive website is a site that will automatically display its content to fit the size of the screen it is being viewed on. Originally sites were designed to be viewed on a monitor or laptop but with the introduction of tablets and then the smart phone, sites had to be adapted to display properly on smaller screens. Initially different pages were served up according to the device type but now resposive websites are used where the site is designed to adapt to the size of the screen. It achieves this by using media queries to determine the size of the screen and then use the appropriate style so that the content is displayed to fit. It is important because smart phones are now the most popular way to view the internet and they come in many different sizes which need to be accomodated.
Mobile first design is where the site is designed to suit mobiles first. This is so that all the components and important content are designed to work well on a small screen. Then the site can be expanded with less important content for bigger screens. Again this is a response to the proliferation of smart phones and the fact that they are now the most popular way to access the internet.
 The pros are that they take a lot of the overhead and possible complexity out of building a site as the design just has to be fitted into the framework.The cons are that the design can be constricted by the framework.
A wireframe is a basic design for a website page, composed of a series of boxes showing the main components and where they appear. It is used as an aid to design the page and to give a blue print for the coder. Below are my wirefames for my blog site.
My biggest problem with implementing the wireframe was my unfamiliarity with the skeleton framework. Although my design was quite simple I still had issues with elements being positioned where I wanted them. However although it took a while I did succeed in getting most of it and I'm sure with more practice it will become easier.


BofA Merrill Lynch survey: The bulls are back as investors feel the FOMO
by Sebastian McCarthyThe bulls are back, according to a closely-followed investor survey showing a wave of renewed optimism over the health of the world economy.
A “fear of missing out” and fading recession concerns have prompted bullish fund managers to move away from cash and back into stocks in their masses.
Read more: World’s wealthiest investors forecast a turbulent 2020
Investor outlook has picked up sharply in BofA Merrill Lynch’s November poll, with cash levels plunging at the fastest monthly rate since President Donald Trump was elected.
Cash levels fell to 4.2 per cent from five per cent during the previous month.
A net six per cent of respondents also expect there to be a stronger global economy in the next year, marking the biggest month-on-month jump on record.
“The bulls are back,” said Michael Hartnett, chief investment strategist at BofA Merrill Lynch Global Research.
He added: “Investors are experiencing FOMO – the fear of missing out – which has prompted a wave of optimism and jump in exposure to equities and cyclicals.”
Hopes of an end to the US-China tariff deadlock and an orderly Brexit transition have driven the rise in growth expectations over the last month, helping to ease market jitters that mounted over the summer.
Optimism over a trade deal between Beijing and Washington has helped push US stock markets to record highs in recent weeks, with the Dow and S&P 500 both enjoying new gains.
Read more: The billionaire boom has slowed down
The survey of investors, who manage more than $500bn (£389bn) in assets, found that the trade war still remained the top concern (39 per cent), followed by a bond market bubble (16 per cent) and monetary policy impotence (12 per cent).
Long US tech & growth stocks (30 per cent) topped the list of the most crowded trades identified by fund managers, ahead of Long US Treasuries (21 per cent) and Long IG corporate bonds (20 per cent).


FAQ
FAQ
- General Questions
- What is Bitcoin?
- How does Bitcoin work?
- What is Bitcoin’s value backed by?
- How are new Bitcoins created?
- What's the current total amount of Bitcoins in existence?
- What is a "block"?
- So your wealth is determined by the amount of CPU power you have?
- Is Bitcoin safe?
- Why should I use Bitcoin?
- Where can I get Bitcoins?
- Using Bitcoin
General Questions
What is Bitcoin?
Bitcoin is a peer-to-peer network based anonymous digital currency. ''Peer-to-peer'' (P2P) means that there is no central authority to issue new money or to keep track of the transactions. Instead, those tasks are managed collectively by the nodes of the network. ''Anonymity'' means that the real world identity of the parties of a transaction can be kept hidden from the public or even from the parties themselves.
How does Bitcoin work?
Bitcoin utilizes public/private key cryptography. When a coin is transfered from user A to user B, A adds B’s public key to the coin and signs it with his own private key. Now B owns the coin and can transfer it further. To prevent A from transferring the already used coin to another user C, a public (but anonymous) list of all the previous transactions is collectively maintained by the network of Bitcoin nodes, and before each transaction the coin’s unusedness will be checked.
For details, see the technical paper: Bitcoin: A Peer-to-Peer Electronic Cash System.
What is Bitcoin’s value backed by?
Bitcoin is valued for the things it can be exchanged to, just like all the traditional paper currencies are.
When the first user publicly announces that he will make a pizza for anyone who gives him enough Bitcoins, then he can use Bitcoins as payment to some extent - as much as people want pizza and trust his announcement. A pizza-eating hairdresser who trusts him as a friend might then announce that she starts accepting Bitcoins as payment for fancy haircuts, and the value of the Bitcoin would be higher - now it would be backed by pizzas ''and'' haircuts. When Bitcoins have become accepted widely enough, he could retire from his pizza business and still be able to use his Bitcoin-savings.
Currently, Bitcoin is in beta development stage, and some new features need to be implemented before the system is well suited for real use. The system already works on the basic level, though, and you can trade with it if you want to.
You can buy and sell Bitcoins with PayPal at NewLibertyStandard's Exchange Service.
How are new Bitcoins created?
New coins are generated by a network node each time it finds the solution to a certain calculational problem (i.e. creates a new block), for which an average solution time can be calculated. The difficulty of the problem is adjusted so that in the first 4 years of the Bitcoin network, 10,500,000 coins will be created. The amount is halved each 4 years, so it will be 5,250,000 in years 4-8, 2,625,000 in years 8-12 and so on. Thus the total number of coins will approach 21,000,000 over time.
What's the current total amount of Bitcoins in existence?
The number of blocks times the coin value of a block. The coin value is 50 bc per block for the first 210,000 blocks, 25 bc for the next 210,000 blocks, then 12.5 bc, 7.25 bc and so on.
As of October 30th 2009, there are about 26,000 blocks in the block chain, which means 26,000 * 50 bc = 1,300,000 bitcoins in existence. You can see the up-to-date number of blocks in the status bar of the Bitcoin main window.
What is a "block"?
A block is a unit which contains the information of the transactions made after the previous block, plus a transaction which assigns a new coin to the creator of the block. Blocks form a chain from the first block to the latest block. To create a new block you need to spend CPU time, which acts as an unbribable timestamp for the previous transactions. The average rate of block creation in the whole system is 6 / hour. For details, see the technical paper: Bitcoin: A Peer-to-Peer Electronic Cash System.
The block chain length is shown in the status bar of the Bitcoin main window. The number increases rapidly while your Bitcoin client is downloading the block chain from other nodes. After the downloading is finished, your node can start generating new blocks.
So your wealth is determined by the amount of CPU power you have?
No. There's a constant average rate of new Bitcoins created, and that amount is divided among the nodes by the CPU power they use. When Bitcoins start having real exchange value, the competition for coin creation will drive the price of electricity needed for generating a coin close to the value of the coin, so the profit margin won't be that huge. The easier way to gain a lot of wealth would be trading goods.
At the moment, though, you can generate new coins quite profitably, if you expect them to have real value in the future. If you choose to, be aware that Bitcoin is still experimental software.
Is Bitcoin safe?
Yes, as long as you make backups of your Bitcoin wallet, protect it with a strong password and keep keyloggers away from your computer.
 On the other hand, that is usually also the case if you lose your physical wallet.
Why should I use Bitcoin?
- Transfer money easily through the internet, without having to trust third parties.
- Third parties can’t prevent or control your transactions.
- Be safe from the instability caused by fractional reserve banking and bad policies of the central banks. The limited inflation of the Bitcoin system’s money supply is distributed evenly (by CPU power) throughout the network, not monopolized to the banks.
Where can I get Bitcoins?
Find a Bitcoin owner and sell her something - MMORPG equipment, IT support, lawn mowing, dollars or whatever you can trade with her. You can also generate new Bitcoins for yourself by running a Bitcoin network node.
You can buy and sell Bitcoins with PayPal at NewLibertyStandard's Exchange Service.
Using Bitcoin
How do I make a transaction?
When you want to send coins, click the ''Send Coins'' button up in the main window. You can send coins to the recipient's IP address if he's running the Bitcoin client, or to his Bitcoin address even if he's not online or doesn't want to reveal his IP. A comment can be included when sending to an IP.
If you're receiving a valuable amount of coins from a sender whom you can't be sure to trust, before accepting the transaction you may want to wait until it's verified by a few blocks. The more blocks you wait, the closer to zero is the sender's chance to successfully double-spend the coins sent to you. The amount of blocks after the transaction is shown in the ''Status'' column of the transaction list in the main window.
How do I generate coins?
Turn on ''Options -> Generate Coins'' to run a node and generate new coins. Be sure to have port 8333 open for incoming connections (instructions).
How long does it take to generate a coin?
Initially your Bitcoin client will have to download and verify the Bitcoin block chain, which is indicated by the number of blocks (shown in the status bar) increasing rapidly. On a modern PC that might take a few hours, after which it will start generating coins.
Your average coin creation rate will be (6 * 50 coins / hour) * (your CPU speed / the total CPU speed in the system). At the moment (October 2009) it might be something like 500 coins / day, for example.
My Bitcoin client shows 0 connections, where’s the problem?
That could happen if port 8333 is not open for incoming connections (instructions).
How do I open port 8333?
If you’re behind a firewall, it will usually ask if you want to allow incoming connections to an application when running it for the first time. If you’re also behind NAT, see www.portforward.com for instructions how to forward the port correctly. Select your router from the list and see its Default Guide.
Use www.canyouseeme.org to check if the port is accepting incoming connections.
How do I backup my wallet?
Your data is stored in the directory ''%appdata%\Bitcoin'', which is typically:
Windows XP:
C:\Documents and Settings\username\Application Data\Bitcoin
Windows Vista:
C:\Users\username\AppData\Roaming\Bitcoin
It’s recommended that you stop Bitcoin before backing it up to make sure the backup will be correct.
If you want to encrypt your backup, you can use some program like TrueCrypt. An in-built tool for encrypting your wallet will be included in Bitcoin later on.
What does "Generated (not accepted)" in the description bar mean?
It implies that your computer and another node created a new block at close to the same time, and your block was rejected for being broadcast later than the one from the other node. It's normal and unavoidable.


Jeff Halpin
About
Work
Hello, I am Jeff Halpin, a UX Architect and Product Strategist working in New York City. I am currently a freelance UX Architect at Area23. Please email me if you would like to learn more about how I work and if you would like to work together in the future.


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| 1168 | (A) | layde a leddir to the wallis and clymbys one lofte |
| 1171 | (C) | ¶ Leyde a ladder to þe wałł . & on lofte clymbetħ |
| 1154 | (D) | leyd a laddre to þe wal and a-loft clymbitħ |
| 1131 | (E) | sette a ladder to þe wal . vp for-to clymbe |
| (Ex) | ---- no text ---- | |
| 1192 | (L) | leyþ a ladder to þe wal & a-lofte clymyþ |
| (P) | ---- no text ---- | |
| 1139 | (U) | laid a ledder to the wal / and on lofte clymbes |
| 232 | (V) | laied a ladder to þe walle . and on lofte clymbes |


{% extends "base.html" %} {% block metarefresh %} {% endblock %} {% block content %}
View all patron requests below
All your customers are currently satisfied - no requests.


"To practice any art, no matter how well or badly, is a way to make your soul grow. So do it." - Kurt Vonnegut


Data Cleaner
All
PrevName
CurName
(current)
NextName
plots
data info
chosen actions
available actions
more stuff


We're in this together. Let's face it. Nobody's getting any younger.  Investing in professional photos can be overwhelming, but at the end of the day, there are virtually no other treasures we value more than the photos we hang on the walls we call our own. Let me help you to make yours the kind that you can be proud to display. I capture the real you: the good, the bad, and, sometimes, the ugly. Life as we really know it...Your Story.
Find Out MoreCost and investment information.
View, share, and purchase your photographs.
Come see my recent work.
Find out more about me.
Ready to capture those special moments! Give us a call or send us an email and we will get back to you as soon as possible!


Opens a file returning a file object.
open (name[, mode[, buffering]])
Optional. Possible values:
‘r’ open for reading (default) ‘w’ open for writing, truncating the file first ‘a’ open for writing, appending to the end of the file if it exists ‘b’ binary mode ‘t’ text mode (default) ‘+’ open a disk file for updating (reading and writing) ‘U’ universal newlines mode (for backwards compatibility; should not be used in new code)
Optional. Possible values:
‘0’ to switch buffering off (only allowed in binary mode) ‘1’ to select line buffering (only usable in text mode) ‘integer > 1’ to indicate the size of a fixed-size chunk buffer
#TODO
#TODO
The most commonly-used values of mode are ‘r’ for reading, ‘w’ for writing (truncating the file if it already exists), and ‘a’ for appending (which on some Unix systems means that all writes append to the end of the file regardless of the current seek position). If mode is omitted, it defaults to ‘r’. The default is to use text mode, which may convert ‘n’ characters to a platform-specific representation on writing and back on reading. Thus, when opening a binary file, you should append ‘b’ to the mode value to open the file in binary mode, which will improve portability. (Appending ‘b’ is useful even on systems that don’t treat binary and text files differently, where it serves as documentation.) See below for more possible values of mode.
The optional buffering argument specifies the file’s desired buffer size: 0 means unbuffered, 1 means line buffered, any other positive value means use a buffer of (approximately) that size (in bytes). A negative buffering means to use the system default, which is usually line buffered for tty devices and fully buffered for other files. If omitted, the system default is used.
Modes ‘r+’, ‘w+’ and ‘a+’ open the file for updating (note that ‘w+’ truncates the file). Append ‘b’ to the mode to open the file in binary mode, on systems that differentiate between binary and text files; on systems that don’t have this distinction, adding the ‘b’ has no effect.
In addition to the standard fopen() values mode may be ‘U’ or ‘rU’. Python is usually built with universal newlines support; supplying ‘U’ opens the file as a text file, but lines may be terminated by any of the following: the Unix end-of-line convention ‘n’, the Macintosh convention ‘r’, or the Windows convention ‘rn’. All of these external representations are seen as ‘n’ by the Python program. If Python is built without universal newlines support a mode with ‘U’ is the same as normal text mode. Note that file objects so opened also have an attribute called newlines which has a value of None (if no newlines have yet been seen), ‘n’, ‘r’, ‘rn’, or a tuple containing all the newline types seen.
Python enforces that the mode, after stripping ‘U’, begins with ‘r’, ‘w’ or ‘a’.
Python provides many file handling modules including fileinput, os, os.path, tempfile, and shutil.
>>> open('C:\\alice_in_wonderland.txt')
<open file 'C:\\alice_in_wonderland.txt', mode 'r' at 0x02C1C390>
>>> alice = open(r'C:\alice_in_wonderland.txt', 'r+')
>>> alice.readline()
" ALICE'S ADVENTURES IN WONDERLAND\n"
#TODO


| Path: | lib/daemons/daemonize.rb |
| Last Update: | Tue Aug 25 22:22:46 -0700 2009 |
February. 4, 2005 Travis Whitton<EMAIL_ADDRESS>Daemonize allows you to easily modify any existing Ruby program to run as a daemon. See README.rdoc for more details.
build the docs if you want to
The Daemonize extension module is copywrited free software by Travis Whitton<EMAIL_ADDRESS>You can redistribute it under the terms specified in the COPYING file of the Ruby distribution.

Daemonize is a module derived from Perl‘s Proc::Daemon module. This module allows you to easily modify any existing Ruby program to run as a daemon. A daemon is a process that runs in the background with no controlling terminal. Generally servers (like FTP and HTTP servers) run as daemon processes. Note, do not make the mistake that a daemon == server.
The Daemonize module does the following:
Forks a child and exits the parent process.
Becomes a session leader (which detaches the program from the controlling terminal).
Forks another child process and exits first child. This prevents the potential of acquiring a controlling terminal.
Changes the current working directory to "/".
Clears the file creation mask.
Closes file descriptors.
Using the Daemonize module is extremely simple:
require 'daemonize' class TestDaemon include Daemonize def initialize daemonize() loop do # do some work here end end end
Daemonize was written by Travis Whitton and is based on Perl‘s Proc::Daemonize, which was written by Earl Hood. The above documentation is also partially borrowed from the Proc::Daemonize POD documentation.


ofm2opl - convert Omega and TeX font-metric files to property-list files
ofm2opl
OFMNAME [ \fB.ofm\fP ]
ofm2opl translates a binary Omega Font Metrics file, OFMNAME, into a human-readable property-list form. The program writes to standard output (by default) or to a file specified as OPLFILE.
The program also works with TeX TFM files, producing TeX PL files. (ofm2opl is based on the WEB source code for tftopl(1).)
\fB-charcode-format=\fP\fITYPE\fP
output character codes according to TYPE, which can be either `hex' or `ascii'. Default is `hex'. ascii specifes all ASCII letters and digits; hex gets you everything else.
display a brief summary of syntax and options
display progress reports
output version information and exit
an Omega Font Metric file
an Omega Property List file
None known, but report any found to<EMAIL_ADDRESS>(mailing list). You may also want to check to see if the same bug is present in pltotf(1).
omega(1), opl2ofm(1), pltotf(1), tftopl(1).
Draft Manual for the Omega System (omega-manual.dvi).
Web page: <http://www.gutenberg.eu.org/omega/>
According to the WEB documentation:
The first TFtoPL program was designed by Leo Guibas in the summer of 1978. Contributions by Frank Liang, Doug Wyatt, and Lyle Ramshaw also had a significant effect on the evolution of the present code.
Extensions for an enhanced ligature mechanism were added by D.E. Knuth in 1989.
Extensions to handle extended font metric files (``OFM'') were added by John Plaice in December 1995 and January 1996, resulting in the new program OFM2OPL.
The primary authors of Omega are John Plaice<EMAIL_ADDRESS>and Yannis Haralambous<EMAIL_ADDRESS>This manual page was written by C.M. Connelly<EMAIL_ADDRESS>for the Debian GNU/Linux system. It may be used by other distributions without contacting the author. Any mistakes or omissions in the manual page are my fault; inquiries about or corrections to this manual page should be directed to me (and not to the primary author).


Fast particle tracking detector dedicated especially for high counting rates circumstances, consisting of an array of micro-strips of plastic scintillators coupled with SiPM readouts, which is analogous to PMT but much smaller.
More...
#include <TASiPMPlaArray.h>
|
| | TASiPMPlaArray (const string &name="", const string &title="", unsigned uid=999999999) |
| |
| virtual | ~TASiPMPlaArray () |
| |
| short | GetNStrip (bool isV=true) const |
| | total number of strips More...
|
| |
| short | GetNFiredStrip (bool isV=true) const |
| |
| void | GetFiredStripArr (int &multi, int *idLs, double *lTLs=nullptr, bool isV=true) const |
| | assign the input array with the list of ids of fired strips More...
|
| |
| vector< TAChannel * > & | GetChArr (bool isV=true) |
| |
| double | GetDelay () const |
| |
| double | GetX0 () const |
| |
| double | GetZ0 () const |
| |
| double | GetWidth () const |
| |
| virtual double | GetTime () |
| |
| virtual double | GetHitX () |
| |
| short | GetFiredStripId () |
| | as the name indicates More...
|
| |
| double | GetStripX (int serialId) const |
| |
| TAChannel * | GetUV (int id) const |
| |
| TAChannel * | GetUH (int id) const |
| |
| double | GetStripTime (int stripId, double t0=-9999., double t1=-9999., double t2=-9999.) |
| | UV end lv time. More...
|
| |
| void | SetDelay (double delay) |
| |
| virtual void | Initialize () override |
| |
| virtual TAStuff * | GetChannel (unsigned uid) const override |
| | get the channel that belongs to this with uid More...
|
| |
| virtual void | Configure () override |
| | create detector objects More...
|
| |
| | TAStuff (const string &name="", const string &title="", unsigned uid=999999999) |
| |
| virtual | ~TAStuff ()=0 |
| |
| const string & | GetName () const |
| |
| const string & | GetTitle () const |
| |
| unsigned | GetUID () const |
| |
| void | SetName (const string &name) |
| |
| void | SetName (const char *name) |
| |
| void | AppendName (const string &tail) |
| |
| void | AppendName (const char *tail) |
| |
| void | SetUID (unsigned uid) |
| |
| void | SetTitle (const string &title) |
| |
| void | SetTitle (const char *title) |
| |
| void | AppendTitle (const string &tail) |
| |
| void | AppendTitle (const char *tail) |
| |
| virtual void | Info () const |
| |
| virtual TAChPara * | GetPara () const |
| | to mark the shared part of TAChannel and TAAnode More...
|
| |
| virtual TAChData * | GetData () const |
| | to mark the shared part of TAChannel and TAAnode More...
|
| |
| | TADetUnion (unsigned uid) |
| |
| virtual | ~TADetUnion () |
| |
| virtual bool | IsDCArr () const |
| | whether this is an MWDC array or not More...
|
| |
| short | GetDetId () const |
| | detector Id More...
|
| |
Fast particle tracking detector dedicated especially for high counting rates circumstances, consisting of an array of micro-strips of plastic scintillators coupled with SiPM readouts, which is analogous to PMT but much smaller.
- Author
- SUN Yazhou, asia..nosp@m.rabb.nosp@m.it@16.nosp<EMAIL_ADDRESS>- Date
- Created: 2017/10/10 Last revised: 2017/11/30, SUN Yazhou.
- Copyright
- 2017-2018, SUN Yazhou.
◆ TASiPMPlaArray()
| TASiPMPlaArray::TASiPMPlaArray |
( |
const string & |
name = "" , |
|
|
const string & |
title = "" , |
|
|
unsigned |
uid = 999999999 |
|
) |
| |
◆ ~TASiPMPlaArray()
| TASiPMPlaArray::~TASiPMPlaArray |
( |
| ) |
|
|
virtual |
◆ Configure()
| void TASiPMPlaArray::Configure |
( |
| ) |
|
|
overridevirtual |
◆ GetChannel()
| TAStuff * TASiPMPlaArray::GetChannel |
( |
unsigned |
uid | ) |
const |
|
overridevirtual |
get the channel that belongs to this with uid
Implements TADetUnion.
◆ GetChArr()
| vector< TAChannel * > & TASiPMPlaArray::GetChArr |
( |
bool |
isV = true | ) |
|
◆ GetDelay()
| double TASiPMPlaArray::GetDelay |
( |
| ) |
const |
◆ GetFiredStripArr()
| void TASiPMPlaArray::GetFiredStripArr |
( |
int & |
multi, |
|
|
int * |
idLs, |
|
|
double * |
lTLs = nullptr , |
|
|
bool |
isV = true |
|
) |
| const |
assign the input array with the list of ids of fired strips
◆ GetFiredStripId()
| short TASiPMPlaArray::GetFiredStripId |
( |
| ) |
|
◆ GetHitX()
| double TASiPMPlaArray::GetHitX |
( |
| ) |
|
|
virtual |
get the X position of the fired strip, multi-hit is ignored the position here is the X position in the global coordinate system
◆ GetNFiredStrip()
| short TASiPMPlaArray::GetNFiredStrip |
( |
bool |
isV = true | ) |
const |
◆ GetNStrip()
| short TASiPMPlaArray::GetNStrip |
( |
bool |
isV = true | ) |
const |
◆ GetStripTime()
| double TASiPMPlaArray::GetStripTime |
( |
int |
stripId, |
|
|
double |
t0 = -9999. , |
|
|
double |
t1 = -9999. , |
|
|
double |
t2 = -9999. |
|
) |
| |
◆ GetStripX()
| double TASiPMPlaArray::GetStripX |
( |
int |
serialId | ) |
const |
◆ GetTime()
| double TASiPMPlaArray::GetTime |
( |
| ) |
|
|
virtual |
get hit time of the fired strip, multi-hit is ignored
◆ GetUH()
| TAChannel * TASiPMPlaArray::GetUH |
( |
int |
id | ) |
const |
- Returns
- up end of the strip, HPTDC high resolution mode
◆ GetUV()
| TAChannel * TASiPMPlaArray::GetUV |
( |
int |
id | ) |
const |
- Returns
- up end of the strip, HPTDC very high resolution mode
◆ GetWidth()
| double TASiPMPlaArray::GetWidth |
( |
| ) |
const |
◆ GetX0()
| double TASiPMPlaArray::GetX0 |
( |
| ) |
const |
◆ GetZ0()
| double TASiPMPlaArray::GetZ0 |
( |
| ) |
const |
◆ Initialize()
| void TASiPMPlaArray::Initialize |
( |
| ) |
|
|
overridevirtual |
◆ SetDelay()
| void TASiPMPlaArray::SetDelay |
( |
double |
delay | ) |
|
|
inline |
◆ fDelay
| double TASiPMPlaArray::fDelay |
|
protected |
global delay of the SiPM detector
◆ fFiredStripId
| short TASiPMPlaArray::fFiredStripId |
|
protected |
◆ fHitX
| double TASiPMPlaArray::fHitX |
|
protected |
the X position of the fired strip, multi-hit is ignored
◆ fLength
| double TASiPMPlaArray::fLength |
|
protected |
◆ fNStripH
| short TASiPMPlaArray::fNStripH |
|
protected |
fNStripH is supposed to be equal to fNStripV
◆ fNStripV
| short TASiPMPlaArray::fNStripV |
|
protected |
◆ fTime
| double TASiPMPlaArray::fTime |
|
protected |
hit time of the fired strip, multi-hit is ignored.
◆ fUHArr
Up end - High resolution mode.
◆ fUVArr
Up end - Very high resolution mode channel.
◆ fWidth
| double TASiPMPlaArray::fWidth |
|
protected |
◆ fX0
| double TASiPMPlaArray::fX0 |
|
protected |
X position of the strip with the smallest X coordinate.
◆ fZ0
| double TASiPMPlaArray::fZ0 |
|
protected |
z position of the SiPM array
The documentation for this class was generated from the following files:


From this page you are able to see the mutal free times of yourself and those pople that have responded to your invite.


This add-in is a natural extension to the Solver add-in incorporated in Excel. SolverTable performs sensitivity analysis for an Excel optimization model, and, in most cases, its output is more relevant and understandable than the optional sensitivity output provided by Solver itself. (Besides, we have learned that Microsoft “broke” something in Excel 2007, so that Solver’s Sensitivity Report might not be available!)
SolverTable is very easy to use, as I describe below. All it requires is an existing optimization model. That is, there must be a spreadsheet model already built, and the corresponding Solver dialog box must already have been filled in. This document explains how to use SolverTable, and it illustrates the procedure with several screen shots. Note: This version of SolverTable has been developed to work with Excel 2007 (aka Excel 12). You will see only minor differences (in the user interface) from the previous version of SolverTable. This version will not work with previous versions of Excel.
To load SolverTable, proceed as follows:
1) Copy the SolverTable.xlam file and the corresponding help files (SolverTableHelp.htm and the various SolverTable .gif files) to a common folder on your hard drive. I recommend creating a SolverTable folder for this purpose under Microsoft’s Library folder, i.e., c:\Program Files\Microsoft Office\Office12\Library\SolverTable, because this folder is in Microsoft’s “trusted” list. If you want to store the files somewhere else, e.g., D:\SolverTable, then you should add this folder to the trusted list. (To do so, Click on the Office button, then Excel Options, then Trust Center, then Trust Center Settings, then Trusted Locations, and then Add new location.)
2) (One-time only step) Because of the way Solver works and the way SolverTable invokes Solver, you need to change a macro security setting on your PC. Make sure the Developer tab is visible. (If it isn’t, click on the Office button and then Excel Options. In the Popular group, check the Show Developer tab in the Ribbon option.) On the Developer ribbon, click on Macro Security and make sure the “Trust access to the VBA project object model” option is checked. (As long as you’re there, I recommend that you check the second option in the top group: “Disable all macros with notification.”)
3) In Excel, load SolverTable into memory. There are two ways to do this. Regardless of the way you use, you will know that SolverTable is loaded when you see a SolverTable item on the Add-Ins ribbon.
a) Open the SolverTable.xlam file directly by double-clicking on it in Windows Explorer. If this file is buried way down in some folder, this way might not be very convenient, but you can accomplish the same thing by putting a shortcut to this file on your desktop, so that it’s just one click away. The advantage (or disadvantage?) of this method is that if you then close Excel and reopen it, SolverTable won’t be loaded; you’ll have to load it again.
b) Click on the Office button, then on Excel Options, then on Add-Ins, and then on the Go button at the bottom. Here you see the familiar Add-ins dialog box from earlier versions of Excel. If this is your first time to load SolverTable, you will need to click on the Browse button to find the SolverTable.xlam file. Otherwise, there should be a SolverTable item in the list of available add-ins. Just check its box, and click on OK. The advantage of this second method is that if you then close Excel and reopen it, SolverTable will open automatically. In fact, it will keep opening until you uncheck SolverTable on the Add-Ins list.
Note: In previous versions of SolverTable, there were two add-in files, SolverTable and SolverTable1. The current version simplifies this, so that there is now only SolverTable.xlam.
To unload this add-in (remove it from memory), just close Excel (if you used method a) above), or uncheck the SolverTable box in the Add-ins list (if you used method b) above).
To illustrate SolverTable, I will use the standard product mix model, a version of which appears in Figure 1. (The conventions I use are that the inputs are in blue borders, the changing cells are in red borders, and the objective cell is in a black border, but you can use any conventions you like.) I assume the Solver dialog box has already been completed in the obvious way (including checks in the Linear and Non-Negative boxes). Actually, this model has already been optimized, but this is not necessary for running SolverTable.
Figure 1
The purpose of SolverTable is very much like that of an Excel data table: to vary one or two inputs and keep track of one or more outputs. The main difference is that SolverTable runs Solver for each input value (or combination of input values) and reports the optimal results in the table. Like data tables, there are essentially two options: oneway tables and twoway tables, depending on whether there are one or two input cells. However, unlike Excel data tables, there can be multiple output cells for oneway and twoway tables. In the latter case, SolverTable creates a separate table for each output cell. Note that a table created by SolverTable retains no links to the original data. If you want to change anything about the table, you must rerun SolverTable.
To illustrate a oneway table, I will see how the optimal profit and the optimal product mix (changing cells) vary as the number of labor hours available (cell D21) varies from 2000 to 8000 in increments of 1000. Begin by selecting the Run SolverTable item from the SolverTable dropdown on the Add-Ins ribbon. You will first be asked whether you have a Solver model on this sheet. For this example, you should say Yes. But if you inadvertently ran SolverTable on a sheet without a Solver model, this would give you a way to back out gracefully. You then see the dialog box in Figure 2. Fill it out as shown and click on OK.
Figure 2
The next dialog box, shown in Figure 3, requires you to specify the input cell, the input values (which are assumed to be in regular increments if you choose the first option, or any list of values if you choose the second option), the output cells, and a location for the table. Note that range names can be used if they exist. SolverTable checks your entries in this dialog box for "obvious" errors. For example, the input cell should not contain a formula or a label, the output range should not contain the input cell, the table location should not write over existing values (unless you say it is OK to do so), and so on. However, I cannot guarantee that it checks for everything, so be careful when you make these entries. Be especially careful that you choose a location for the table that does not write over any information you don't want to lose (even though you will be warned if you try to do so).
Figure 3
The table itself appears in Figure 4. (I have added the heading in row 1 manually.) The small red triangles are Excel comments that SolverTable automatically adds to a number of cells. For example, the comment in cell I4 reminds you what the input cell is (in this case, D21). The comments in column J are the Solver messages you normally see after running Solver. For this example, they all contain the message you hope to see: "Solver found a solution. All constraints and optimality conditions are satisfied." However, if there is no feasible solution, say, then the comment will alert you to this. Note that unlike an Excel data table, SolverTable does not put formulas at the top of the table (in row 3 of the figure), because this wouldn't make sense. However, it does put the cell addresses of the output cells. This way, you can remember which outputs are being reported.
Figure 4
To create a twoway table, go through the same steps as above for a oneway table, but check the twoway option in Figure 2. Then the twoway dialog box in Figure 5 appears. Here, I'll assume that both labor hour availability (D21) and hourly wage rate (B4) are being varied, and that the desired outputs are the optimal profit and the number of labor hours used (B21). (Any output cells could be selected.)
Figure 5
SolverTable then creates as many tables as there are output cells (in a vertical direction), as shown in Figure 6. Note that each cell in a table corresponds to a Solver run. For example, when there are 4000 labor hours available and the wage rate is $4 per hour, the optimal profit is $25,200 (top table) and all 4000 labor hours are used (bottom table). Again, there are comments in selected cells. For example, the comments in cells I13 and J12 remind you that the input cells are D11 and B4. The comments in the body of each table report the Solver message, exactly as with oneway tables.
Figure 6
As with all Solver models, it is a good idea to take a close look at the answers and see whether they make sense. For example, column L in Figure 6 contains all zeroes. Does this make sense? Yes, it probably does. When the labor rate is $12 per hour and all other monetary inputs stay constant, labor is evidently too expensive for the company to make a profit. So it produces nothing!
With some imagination, you can get SolverTable to run some really interesting sensitivity analyses. For example, suppose you want to allow the availabilities of all three resources (labor, metal, and glass) to change by a common factor. Then you need to change the model slightly, as indicated in Figure 7. Now the original availabilities have been moved to column F, a change factor has been inserted in column H, and formulas have been entered for availabilities in column D. Specifically, the formula in cell D21 is =$H$21*F21, which is then copied down.
Figure 7
You can now do a oneway sensitivity analysis on this change factor, using the settings in Figure 8. The corresponding table appears in Figure 9.
Figure 8
Figure 9
As another example, suppose you want to keep track of a function of several cells in the model. For example, suppose you want to keep track of the maximum number of frames of any single type produced, that is, the maximum of the changing cell values. You can't select this as an output directly because it doesn't appear anywhere in the model. But there is a simple solution: create a formula for it in some unused cell, and then specify this cell as an output cell.
SolverTable relies on Solver. In fact, SolverTable invokes Solver for each input value (or combination of input values). Therefore, any problems that people have experienced with Solver can occur with SolverTable. However, I have tried to overcome one of Solver's more annoying features: claiming that a model is not linear when you know it is linear. In case you have not run into this problem, I will describe it first. When your model is linear, you should check the Assume Linear Model box under Solver Options. This has two advantages. First, it uses a faster algorithm (the simplex method). Second, it is guaranteed (well, almost) to find the optimal solution if an optimal solution exists. However, Solver uses its own rules to check whether a model is linear. Because of numerical precision problems inherent in computers, Solver sometimes decides that a model is not linear, even though you know it is. In this case, it responds with an error message that the conditions for a linear model are not satisfied -- and it doesn't solve the problem.
SolverTable automatically checks for this error message. If Solver gives it, then SolverTable reruns Solver with the Assume Linear Model box unchecked and reports the result. However, to let you know that all of this happened, the corresponding cells of the table are colored yellow, and the comments in these cells describe the situation. An example I encountered appears in Figure 10. This model is indeed linear. However, when I formed the oneway table, Solver thought the model was not linear for input values of 0.80 and 1.00, even though it agreed that it was linear for input values of 0.90 and 1.10. Similarly, for the twoway table, it thought the model was not linear for 2 of the 16 input combinations. This is clearly strange behavior, but it sometimes happens. (This was before Excel 2007. Maybe the Solver in Excel 2007 is different.) At least, SolverTable provides a solution (using a nonlinear algorithm) rather than the annoying "conditions for linear model are not satisfied" Solver message.
Figure 10
Chris Albright, Kelley School of Business, Indiana University<EMAIL_ADDRESS>October 2007


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THE FRIGHTENERS (1996) A Film Review by Ted Prigge Copyright 1997 Ted Prigge
Director: Peter Jackson Writers: Peter Jackson and Frances Walsh Starring: Michael J. Fox, Trini Alvarado, Peter Dobson, Jeffrey Combs, Jake Busey, Dee Wallace-Stone, Chi McBride, Jim Fyfe, John Astin, R. Lee Ermey, Troy Evans
"Dead Alive" (a.k.a. "Brain Dead") was a hilarious darkly comic horror film with the best single gorefest ever put on celluloid. "Heavenly Creatures" was a wonderfully disturbing character study/black comedy which examined two school girls' strange obsession with one another, going WAYYYY past simple homosexuality. Compared to these two amazing, amazing flicks, "The Frighteners," Jackson's American debut (and subsequent box office flop) is rather tepid.
That's not to say that it's not a good flick. Often when foreign and acclaimed directors arrive to make American films, they have a bit of trouble settling in (it's natural; just ask John Woo and Danny Boyle). In some cases, it's because they're homeland material is a tad too risque for our elite, censored-as-hell American tastes (most of Woo's Hong Kong flicks are "unrated," which also applies to "Dead Alive;" and I still haven't seen the uncut version of "Trainspotting").
Granted, Jackson's arrival is a tad more well-done than that of Woo's and Boyle's ("Hard Target" is considered a "failure," and...I mean, it starred Van Damme; and "A Life Less Ordinary" MIGHT peak 5 million bucks and might get more than 10 good reviews out of the whole country). But it's just not as good as his earlier films. I've never seen his early early work (like "Bad Taste," and the sick Muppet parody, "Meet the Feebles" - both are more rare than finding a gas station in Philadelphia - inside joke), but I'm pretty sure that "The Frighteners" is just as tepid as it seems.
Not to say it isn't a shock for us Americans. The film's mood twists and turns: it starts off as an off-beat comedy, then ultimately settles into wild horror. The film opens spectacularly, giving off hints of Jackson at his most manic, with a ghost chasing a screaming woman (Dee Wallace-Stone - you remember the mom from "E.T.") through a crumbling mansion, seeping through walls, and creeping under the carpet, and ending in a great shot that scares the hell out of the viewer.
The we meet Frank Black (Michael J. Fox, right before "Spin City" came out), a bitter, world-weary con-man, or so it seems. He says he's a psychic and can exorcise ghosts, and no one really believes him...until a ghost starts poltergeisting (a word?) them. Then Frank comes in, does his stuff, and no more ghosts. Maybe he's the real thing...guess again. Yes, he can communicate with ghosts, but they're really his buds, and are working with him (or for him) to get him money and business, a pure example of the cleverness of the script.
But soon numbers are appearing on people's heads, only seen by Frank. And soon enough, they turn up dead.  The film shifts into horror, yet never really looses the twisted humor from the first parts.
The humor in this film is in no way as great as that of "Dead Alive" and "Heavenly Creatures." A typical joke in "Dead Alive" featured a woman turning into a zombie sitting at lunch with a group of people who don't know she's a zombie, and accidentally eating her eyeball, which has fallen into her soup. And a "Heavenly Creatures" joke involved great style, and acting by one of the actresses, especially a scene where a paranoid father was checking up on the two girls who were in the bathroom, taking pictures of eachothers' clevage.
But "The Frighteners" is a little more off-beat, and more American. Sometimes there's some good old American slapstick, but then there's some good old American movie allusions. One of the funniest film geek jokes involves a graveyard where the general of it just happens to be the robotic, insulting drill sergeant from Kubrick's "Full Metal Jacket," reincarnated as a ghost and played by the exact same actor as in the film, the great R. Lee Ermey. And cult horror fans will love that Jeffrey Combs ("Re-Animator") shows up halfway through as a totally bizarre and surrealistic investigator who's hung out with way too many cults.
But the humor just isn't as wild and manic as it was in Jackson's earlier "Dead Alive." I mean, I probably laughed more during the final 30 minutes of that movie than I would have if I watched all of Chris Farley's movies, and multiplied the number of times I laughed at all of them combined by one thousand. But "The Frighteners" is much more restrained, and there-in lies its main problem.
Sometimes when a film is too structured, it looses the impact it would have needed. Sure, "Heavenly Creatures" was structured, but it was a more dramatic film than his other flicks. But "Dead Alive" was funny because it went wild. "The Frighteners" needed this same kind of touch to it, to differentiate itself more from American flicks.  But the other reason is to bring a part of their culture over to this one. When they assimilate, they kind of loose their luster, and "The Frighteners" looses that.
On better news, the film works on its own anyway, although it's nothing absolutely spectacular. The acting is also very good, with Fox doing a strangely good job in a role he was definitely not typecast for. Trini Alvarado ("Little Women") does a good job as his love interest (there has to be one: it's American). Jake Busey plays the big villain, and has that same kind of creepy-ass visage his father once had...hell, he still has it. John Astin, unrecognizable under layers and layers and layers of make-up and special effects, does a good job with a small role. And Jeffrey Combs is...wow, he's a cool guy.
"The Frighteners" works, but is not as jaw-droppingly amazing as Jackson's other films, yet still shows that Jackson can at least do a pretty good job on his American debut. But if you want to see a real piece of Jackson-ography, see "Dead Alive" and/or "Heavenly Creatures."
MY RATING (out of 4): ***
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The Ti.Blur project allows you to create a blur view using either the contents of a view or a provided image.
Below is a gif showing the example app in action on both iOS and Android. For a more complete walk through see the video.
If you are building from source you will need to do the following:
Import the project into Xcode:
~~~ TITANIUMSDK = /Users/benjamin/Library/Application Support/Titanium/mobilesdk/osx/$(TITANIUMSDK_VERSION) ~~~
Import the project into Eclipse:
var mod = require('bencoding.blur');
Platform Supported: iOS and Android
BasicBlurView provides a view implemented box blur. This results in an effect similar to what you see in iOS 7. The BasicBlurView object provides this blur functionality in a cross-platform way.
To learn more about BasicBlurView please read the documentation:
Platform Supported: iOS
The BlurView provides a series of methods you can use to implement a blur effect similar to that used in iOS 7. The BlurView is an extended Ti.UI.View that implements a Blur effect and allows you to implement background clipping.
To learn more about the BlurView please read the documentation here.
Platform Supported: iOS
The GPUBlurImageView allows you to implement a blur effect similar to that used in iOS 7. The GPUBlurImageView ImageView uses the Brad Larson GPUImage project render the blur effect quickly using little device resources.
To learn more about the GPUBlurImageView please read the documentation here.
Want to blur your images directly without using a View or ImageView? The applyGPUBlurTo and applyBlurTo methods allow you to do this quickly and easily.
Android
Android documentation on how to apply a blur effect without using views, please read the documentation here.
iOS
For how to apply a blur effect on iOS without using views, please read the documentation here.
Platform Supported: iOS
IOSBLUR : Used in the blur type property of the GPUBlurImageView object. Using a type of IOSBLUR replicates the background blur used on iOS 7 in places like the control center.
BOXBLUR : Used in the blur type property of the GPUBlurImageView object. Using a type of BOXBLUR implements a hardware-optimized, variable-radius box blur.
GAUSSIANBLUR : Used in the blur type property of the GPUBlurImageView object. Using a type of GAUSSIANBLUR implements A hardware-optimized, variable-radius Gaussian blur.
If you like the Titanium module,please consider following the @bencoding Twitter for updates.
For module updates, Titanium tutorials and more please check out my blog at benCoding.Com.
The Blur method used in the Blur.View was inspired by the CoreImage tutorial by Evan Davis here.
The image used in all of the examples is by thenails and is licenced under Creative Commons. This image is and associated licensing is available here.
The GPUImageView uses the Brad Larson GPUImage project render the blur. I can't recommend this library enough.


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{% extends "mindmaps/mindmaps_base.html" %} {% load staticfiles %} {% block style %} {% endblock %} {# /style #} {% block title %} ES-DOC MindMap Viewer {% endblock %} {# /title #} {% block content %}
This application allows users to quickly view an ES-DOC Specialization in MindMap format. For a more fully-featured mindmap browser, we recommend either installing FreeMind or registering for MindMup.


Virgen de la Candelaria Marathon
Arequipa PER
Race Winners
(24 runnings)
10 Feb
2008 04
Feb
2007
05
Feb
2006
06
Feb
2005
Feb
2004
Feb
2003
Feb
2002
Feb
2001
Feb
2000
Feb
1999
Feb
1998
Feb
1997
1990-1996 Feb
1989
Feb
1988
Feb
1987
Notes: 1987 was the inaugural year as a marathon. A 7 km race was held in
1986. The 2000 race was probably short.
19 Feb
2017
2:20:31
Nelson Ito Curo (PER)
28 Feb
2016
2:27:25
Ronal Paucar Herrera (PER)
08
Feb 2015
2:26:24
Max Belizario Sucapuca (PER)
02
Feb 2014
2:30:15
Paulino Canchanya-2
03
Feb 2013
2:32:42
Paulino Canchanya (PER)
05
Feb 2012
2:28:39
Edwin Vilca (PER)
06 Feb
2011
2:31:15
Florencio
Machacuay-4
28 Feb
2010
2:38:27
Florencio
Machacuay-3
01 Feb
2009
2:30:36
Florencio
Machacuay-2
2:29:13
Vicente Chura-2
2:22:26
Hugo-Saul
Paucar-3
2:27:09
Florencio Machacuay (PER)
2:30:06
Hugo-Saul
Paucar-2
2:31:22
Reynaldo
Ramirez-2
2:34:17
Hugo-Saul Paucar (PER)
2:41:55
Luis-Fernando Bustillos (PER)
2:38:20
Reynaldo Ramirez (MEX)
2:18:47
Raul Camarena (PER)
2:24:14
Vicente Chura (PER)
2:38:36
Felix Pinto-2
---
Felix Pinto (PER)
---
half marathon only
2:40:47
Juan Quispe (PER)
2:37:46
Roberto Serrano (PER)
---
Elisban Condori (PER)
Most Wins
(1987-date)
Men 4
Florencio
Machacuay (PER)
2006,2009-11
Prize Money
(ADR qualified runners)
No information on prize money has been received for this race.
Race Time Bias
(sec/km)
Insufficient data to calculate the race time bias.
Competitive Level (1990-date)
Insufficient data to calculate the competitive level.
Quality Performances
Men no men under 2:20
Last Updated on 01 Mar 2017
Contributors: Klaas Loonstra (41), Franco Civai (1), Luis Vinker (3)


Education Plans
Their are two plans that we will cover in this site. They are the Individual Education Plan (IEP), and the 504 plan. Both are intended to provide services to children that need that extra help and attention to be successfull. As we have stated on the parents page these plan require that both educators and parents meet together to determine the correct plan for the child. These plans are meant to ensure children can and will be successful throughout their school experience. This is not a one time meeting that is set in place and then left alone. Parents and educators meet at a minimum of once per school year, and can meet more often if the parent or educator feels there is a need.


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{% extends "base_new.html" %} {% load staticfiles %} {% block stylesheets %} {% endblock %} {% block js_scripts %} {% endblock %} {% block content %}
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This is a Bloch sphere visualiser - a quantum mechanical simulation of a two state particle under the influence of an external light field. Set an initial position for the Bloch vector, queue up some pulses and press start. The input boxes support simple math expressions (pi, cos, etc.). The time for a light pulse isn't in units of time: rather, it is in angular units (e.g. a pi/2 pulse will rotate the vector by pi/2 around some axis dependent on the detuning). Likewise for free precession. Also, you can rotate the viewpoint by dragging the mouse. Note this is not 'to scale' in terms of time/speed: it is more to show how the Bloch vector moves. A constant light intensity is used.


{% extends "layout.html" %} {% set current_page = "contribute" %} {% block body %}
Fork on GitHub or create an issue
Or submit a website
You can also contact me on Reddit


PART 7. REMEDIES
§490:2-701 Remedies for breach of collateral contracts not impaired. Remedies for breach of any obligation or promise collateral or ancillary to a contract for sale are not impaired by the provisions of this article. [L 1965, c 208, §2-701; HRS §490:2-701]


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coding-with-html.
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Hunter Engineering specializes in developing industry-leading brake lathes, including the AutoComp Elite® on-car brake lathe and the BL500 Series combination brake lathe. Hunter also offers a full line of accessories for your Brake Lathe, including adaptors to service most passenger car, light duty truck and medium duty applications.
The Hunter AutoComp Elite® on-car brake lathe keeps your brake service a cut above the rest. The AutoComp Elite® brake lathe features Hunter’s revolutionary automatic compensation technology.
The BL505 brake lathe machine handles rotors up to 23 inches and drums up to 28 inches in diameter, giving the BL505 combination brake lathe the ability to service a wide range of vehicle applications.
Hunter also provides a full-line of brake lathe accessories to enhance serviceability of specialized applications.


Getting Started
Example Layouts
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{% block content %}{% endblock %}
{% block scripts %}{% endblock %}


_ = require('underscore')
solve = require "../dao"
general = require "./general"
special = solve.special
macro = solve.macro
debug = solve.debug
lispt.coffee doesn't know trail, failcont, state and the like. lisp knows cont only.
_ = require('underscore')
solve = require "../dao"
general = require "./general"
special = solve.special
macro = solve.macro
debug = solve.debug
aka lisp's quote, like in lisp, 'x==x, quote(x) === x
exports.quote = special(1, 'quote', (solver, cont, exp) ->
(v, solver) -> cont(exp, solver))
aka lisp's eval, solve(eval_(quote(x))) means solve(x),
exports.eval_ = special(1, 'eval', (solver, cont, exp) ->
solver.cont(exp, (v, solver) -> [solver.cont(v, cont), null, solver]))
vari.binding = exp
exports.assign = special(2, 'assign', (solver, cont, vari, exp) ->
different from is_ in logic.coffee:
Because not using vari.bind, this is not saved in solver.trail
and so it can NOT be restored in solver.failcont
EXCEPT the vari has been in solver.trail in the logic branch before.
solver.cont(exp, (v, solver) -> (vari.binding = v; cont(v, solver))))
vari.binding = 0
provide this for reducing continuation, and make code running faster.
exports.zero = special(1, 'zero', (solver, cont, vari, exp) ->
(v, solver) -> (vari.binding = 0; cont(v, solver)))
vari.binding = 1
provide this for reducing continuation, and make code running faster.
exports.one = special(1, 'one', (solver, cont, vari, exp) ->
(v, solver) -> (vari.binding = 1; cont(v, solver)))
aka lisp's begin, same as logic.andp
exports.begin = special(null, 'begin', (solver, cont, exps...) -> solver.expsCont(exps, cont))
if_fun = (solver, cont, test, then_, else_) ->
then_cont = solver.cont(then_, cont)
if else_?
else_cont = solver.cont(else_, cont)
action = (v, solver) ->
if (v) then then_cont(v, solver)
else else_cont(v, solver)
solver.cont(test, action)
else
action = (v, solver) ->
if (v) then then_cont(null, solver)
else cont(null, solver)
solver.cont(test, action)
lisp style if.
different from logic.ifp, when test fail, it do not run else_ clause.
exports.if_ = special([2,3], 'if_', if_fun)
iff_fun = (solver, cont, clauses, else_) ->
length = clauses.length
if length is 0 then throw new exports.TypeError(clauses)
else if length is 1
[test, then_] = clauses[0]
if_fun(solver, cont, test, then_, else_)
else
[test, then_] = clauses[0]
then_cont = solver.cont(then_, cont)
iff_else_cont = iff_fun(solver, cont, clauses[1...], else_)
action = (v, solver) ->
if (v) then [then_cont, v, solver]
else [iff_else_cont, v, solver]
solver.cont(test, action)
iff [ [test1, body1],
[test2, body2]
]
else_
exports.iff = special(-2, 'iff', iff_fun)
lisp style block
exports.block = block = special(null, 'block', (solver, cont, label, body...) ->
if not _.isString(label) then (label = ''; body = [label].concat(body))
exits = solver.exits[label] ?= []
exits.push(cont)
defaultExits = solver.exits[''] ?= [] # if no label, go here
defaultExits.push(cont)
holder = [null]
continues = solver.continues[label] ?= []
continues.push(holder)
defaultContinues = solver.continues[''] ?= [] # if no label, go here
defaultContinues.push(holder)
holder[0] = fun = solver.expsCont(body, cont)
exits.pop()
if exits.length is 0 then delete solver.exits[label]
continues.pop()
if continues.length is 0 then delete solver.continues[label]
defaultExits.pop()
defaultContinues.pop()
fun)
break a block
exports.break_ = break_ = special([0, 1,2], 'break_', (solver, cont, label='', value=null) ->
if value != null and not _.isString label then throw new TypeError([label, value])
if value is null and not _.isString label then (value = label; label = '')
exits = solver.exits[label]
if not exits or exits==[] then throw Error(label)
exitCont = exits[exits.length-1]
valCont = (v, solver) -> solver.protect(exitCont)(v, solver)
solver.cont(value, valCont))
continue a block
exports.continue_ = continue_ = special([0,1], 'continue_', (solver, cont, label='') ->
continues = solver.continues[label]
if not continues or continues==[] then throw Error(label)
continueCont = continues[continues.length-1]
(v, solver) -> [solver.protect(continueCont[0]), v, solver])
not_ = general.not_
loop
exports.loop_ = macro(null, 'loop', (label, body...) ->
if not _.isString(label) then (label = ''; body = [label].concat body)
block(label, body.concat([continue_(label)])...))
while
exports.while_ = macro(null, 'while_', (label, test, body...) ->
if not _.isString(label) then (label = ''; test = label; body = [test].concat body)
block(label, [if_(not_(test), break_(label))].concat(body).concat([continue_(label)])...))
until
exports.until_ = macro(null, 'until_', (label,body..., test) ->
if not _.isString(label) then (label = ''; test = label; body = [test].concat body)
body = body.concat([if_(not_(test), continue_(label))])
block(label, body...))
aka. lisp style catch/throw
exports.catch_ = special(-1, 'catch_', (solver, cont, tag, forms...) ->
tagCont = (v, solver) ->
solver.pushCatch(v, cont)
formsCont = solver.expsCont(forms, (v2, solver) -> solver.popCatch(v); [cont, v2, solver])
[formsCont, v, solver]
solver.cont(tag, tagCont))
aka lisp style throw
exports.throw_ = special(2, 'throw_', (solver, cont, tag, form) ->
formCont = (v, solver) ->
solver.cont(form, (v2, solver) ->
solver.protect(solver.findCatch(v))(v2, solver))(v, solver)
solver.cont(tag, formCont))
aka. lisp's unwind-protect
exports.protect = special(-1, 'protect', (solver, cont, form, cleanup...) ->
oldprotect = solver.protect
solver.protect = (fun) -> (v1, solver) ->
solver.expsCont(cleanup, (v2, solver) ->
solver.protect = oldprotect;
oldprotect(fun)(v1, solver))(v1, solver)
cleanupCont = (v1, solver) ->
solver.expsCont(cleanup, (v2, solver) ->
solver.protect = oldprotect
cont(v1, solver))(v1, solver)
result = solver.cont(form, cleanupCont)
result)
used by callcc and callfc
runner = (solver, cont) -> (v) ->
while not solver.done then [cont, v, solver] = cont(v, solver)
solver.done = false
return v
callfc(someFunction(kont) -> body)
current continuation @cont can be captured in someFunction
exports.callcc = special(1, 'callcc', (solver, cont, fun) -> (v, solver) ->
cont(fun(runner(solver.clone(), cont)), solver))
callfc(someFunction(fc) -> body)
current solver.failcont can be captured in someFunction
exports.callfc = special(1, 'callfc', (solver, cont, fun) -> (v, solver) ->
cont(fun(runner(solver.clone(), solver.failcont)), solver))
callcs(someFunction(solver, kont) -> body)
the solver and current cont can be captured in someFunction
exports.callcs = special(1, 'callcs', (solver, cont, fun) -> (v, solver) ->
cont(fun(solver.clone(), cont), solver))
lisp style quasiquote/unquote/unquote-slice "`", "," and ",@"
exports.quasiquote = exports.qq = special(1, 'quasiquote', (solver, cont, item) ->
solver.quasiquote?(item, cont))
exports.unquote = exports.uq = special(1, 'unquote', (solver, cont, item) ->
throw "unquote: too many unquote and unquoteSlice" )
exports.unquoteSlice = exports.uqs = special(1, 'unquoteSlice', (solver, cont, item) ->
throw "unquoteSlice: too many unquote and unquoteSlice")


Chiefs overcome Chargers in Mexico
by OmnisportThe Kansas City Chiefs recorded an important 24-17 win over the Los Angeles Chargers in Mexico City in the NFL on Monday.
A pair of third-quarter touchdowns helped the Chiefs (7-4) past AFC West rivals the Chargers (4-7) at the Estadio Azteca.
Chiefs star Patrick Mahomes improved in the second half and finished with 182 yards on the back of 19 of 32 completed passes with one TD and an interception.
Travis Kelce led the Chiefs with 92 receiving yards, including a TD, in a key win for division leaders Kansas City, who had Tyreek Hill suffer a hamstring injury.
Kelce became the fastest tight end in NFL history to reach 6,000 yards and 450 receptions, according to the Chiefs.
Philip Rivers (28 of 52 for 353 yards with one TD) almost saw the Chargers to a late victory, but the QB threw his fourth interception in the dying seconds.
After a first-quarter Michael Badgley field goal for the Chargers, the Chiefs took a 7-3 lead when Tyrann Mathieu intercepted Rivers, allowing LeSean McCoy to rush across from six yards for a TD.
Badgley made two more field goals – either side of one from Harrison Butker – as the Chiefs took a 10-9 lead into half-time.
Mahomes was better in the second half as the Chiefs scored twice to go ahead 24-9.
Darrel Williams rushed over before Mahomes' 23-yard pass for Kelce saw the Chiefs take control.
However, the Chargers responded when Rivers found Keenan Allen and a two-point conversion brought them back within seven.
Rivers looked to lead the Chargers on a scoring drive late and a 50-yard pass to Mike Williams set up a potential TD, but the QB was intercepted again in the closing seconds.


Code
Cubs
Unit 1: Loops & If's ±
L1: WHILE your looping
Video
Activity
L2: FOR the last loop
Video
Activity
L3: IF, if is good
Video
Activity
Unit 2: Functions ±
L1: Functions as a process
Video
Activity
L2: Ins and Outs of a Function
Video
Activity
L3: Fully Functioning Functions
Video
Activity
Unit 3: Objects ±
L1: I Object
Video
Activity
L2: Property of Objects
Video
Activity
L3: Methods of an Object
Video
Activity


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open fun defaultStoryDefinition(botDefinition: BotDefinition): StoryDefinition
Default StoryDefinition if none is provided.


Connecting microfilters to the master socket
Connecting your Sky wireless router directly to the master socket means the broadband signal should be stronger and much less susceptible to electrical noise and interference. It's also a good way to rule out your own home's phone wiring as a cause of either not being able to connect to the Sky Broadband service, or it running slowly or dropping out intermittently.
The most common type of master socket is the BT NTE5 (pictured). It's normally larger than a phone extension socket, and is usually in an easily accessible location such as the hallway or front room.
Tip
If your computer is in a different room to the master socket, use a long ethernet cable to connect the router to your PC. This is preferable to connecting the router to an extension socket or an extension lead, as ethernet cables are much less susceptible to interference than telephone extension cables. They can be any length from 1 to 100 metres long. If using a longer ethernet cable is not an option for you, consider using the wireless capabilities of the router.
One set-top box and one phone
View using wired connection | View using wireless connection
Two set-top boxes and two phones
View using wired connection | View using wireless connection


Visualization & Metrics¶
Prerequisites¶
Plotly
is used for all charts to provide an interactive experience: hover, toggle, and zoom. Reference the Installation notebook for information about configuring Plotly. However, static images are used in this notebook due to recent difficulty with 3rd party JS on the documentation portal.
Overview¶
As described in the Low-Level Docs, the Result(s)
of each training Job
are automatically populated with metrics for each split/ fold of samples evaluated against the model. The Algorithm.analysis_type
determines which metrics and plots are prepared:
Although
'classification_multi'
and'classification_binary'
share the same metrics and plots, they go about producing these artifacts differently. For example, ROC curvesroc_multi_class=None
vsroc_multi_class='ovr'
.'regression'
, unlike the classification analyses, does not have an ‘accuracy’ metric, so we substitute ‘r2’, R^2 (coefficient of determination, for it. There are no regression-specific plots.
We’ll use the datum
and tests
modules to rapidly create some examples.
[3]:
import aiqc
from aiqc import datum
from aiqc import tests
Classification¶
[5]:
batch_multiclass = tests.make_test_batch('multiclass')
___/ featurecoder_index: 0 \_________
=> The column(s) below matched your filter(s) and were ran through a test-encoding successfully.
['petal_width']
=> The remaining column(s) and dtype(s) can be used in downstream Featurecoder(s):
{'petal_length': 'float64', 'sepal_length': 'float64', 'sepal_width': 'float64'}
___/ featurecoder_index: 1 \_________
=> The column(s) below matched your filter(s) and were ran through a test-encoding successfully.
['sepal_length', 'sepal_width', 'petal_length']
=> Nice! Now all feature column(s) have encoder(s) associated with them.
No more Featurecoders can be added to this Encoderset.
[6]:
batch_multiclass.run_jobs()
🔮 Training Models 🔮: 100%|██████████████████████████████████████████| 8/8 [00:30<00:00, 3.87s/it]
Individual Job Metrics¶
Each training Result
contains the following metrics.
[7]:
from pprint import pprint as p
p(
batch_multiclass.jobs[0].results[0].metrics
)
{'test': {'accuracy': 0.9629629629629629,
'f1': 0.9628482972136223,
'loss': 0.07572123408317566,
'precision': 0.9666666666666667,
'recall': 0.9629629629629629,
'roc_auc': 1.0},
'train': {'accuracy': 0.9803921568627451,
'f1': 0.9803921568627451,
'loss': 0.07449501752853394,
'precision': 0.9803921568627451,
'recall': 0.9803921568627451,
'roc_auc': 0.9988465974625144},
'validation': {'accuracy': 1.0,
'f1': 1.0,
'loss': 0.10631509870290756,
'precision': 1.0,
'recall': 1.0,
'roc_auc': 1.0}}
It also contains per-epoch History
metrics calculated during model training.
[8]:
batch_multiclass.jobs[0].results[0].history.keys()
[8]:
dict_keys(['loss', 'accuracy', 'val_loss', 'val_accuracy'])
Aggregate Batch Metrics¶
selected_metrics:list
- If you get overwhelmed by the variety of metrics returned, then you can include the ones you want selectively by name.sort_by:str
- You can sort the dataframe by any column name.ascending:bool=False
- Descending if False.
[9]:
batch_multiclass.metrics_to_pandas(
selected_metrics=None
, sort_by=None
, ascending=False
)
[9]:
| hyperparamcombo_id | job_id | result_id | split | accuracy | f1 | loss | precision | recall | roc_auc | |
|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1 | 1 | 1 | test | 0.962963 | 0.962848 | 0.075721 | 0.966667 | 0.962963 | 1.000000 |
| 1 | 1 | 1 | 1 | validation | 1.000000 | 1.000000 | 0.106315 | 1.000000 | 1.000000 | 1.000000 |
| 2 | 1 | 1 | 1 | train | 0.980392 | 0.980392 | 0.074495 | 0.980392 | 0.980392 | 0.998847 |
| 3 | 2 | 2 | 2 | test | 0.962963 | 0.962848 | 0.098543 | 0.966667 | 0.962963 | 1.000000 |
| 4 | 2 | 2 | 2 | validation | 1.000000 | 1.000000 | 0.091096 | 1.000000 | 1.000000 | 1.000000 |
| 5 | 2 | 2 | 2 | train | 0.990196 | 0.990194 | 0.072704 | 0.990476 | 0.990196 | 0.999423 |
| 6 | 3 | 3 | 3 | test | 0.962963 | 0.962848 | 0.064860 | 0.966667 | 0.962963 | 1.000000 |
| 7 | 3 | 3 | 3 | validation | 0.952381 | 0.952137 | 0.082596 | 0.958333 | 0.952381 | 1.000000 |
| 8 | 3 | 3 | 3 | train | 0.980392 | 0.980375 | 0.069292 | 0.981481 | 0.980392 | 0.998847 |
| 9 | 4 | 4 | 4 | test | 0.962963 | 0.962848 | 0.122463 | 0.966667 | 0.962963 | 0.997942 |
| 10 | 4 | 4 | 4 | validation | 0.952381 | 0.952137 | 0.117592 | 0.958333 | 0.952381 | 1.000000 |
| 11 | 4 | 4 | 4 | train | 0.950980 | 0.950714 | 0.081781 | 0.957265 | 0.950980 | 0.999712 |
| 12 | 5 | 5 | 5 | test | 0.962963 | 0.962848 | 0.073990 | 0.966667 | 0.962963 | 1.000000 |
| 13 | 5 | 5 | 5 | validation | 1.000000 | 1.000000 | 0.088745 | 1.000000 | 1.000000 | 1.000000 |
| 14 | 5 | 5 | 5 | train | 0.990196 | 0.990194 | 0.055657 | 0.990476 | 0.990196 | 1.000000 |
| 15 | 6 | 6 | 6 | test | 0.962963 | 0.962848 | 0.111602 | 0.966667 | 0.962963 | 1.000000 |
| 16 | 6 | 6 | 6 | validation | 1.000000 | 1.000000 | 0.093202 | 1.000000 | 1.000000 | 1.000000 |
| 17 | 6 | 6 | 6 | train | 0.980392 | 0.980392 | 0.092825 | 0.980392 | 0.980392 | 0.999423 |
| 18 | 7 | 7 | 7 | test | 0.962963 | 0.962848 | 0.111054 | 0.966667 | 0.962963 | 0.995885 |
| 19 | 7 | 7 | 7 | validation | 1.000000 | 1.000000 | 0.110409 | 1.000000 | 1.000000 | 1.000000 |
| 20 | 7 | 7 | 7 | train | 0.970588 | 0.970531 | 0.097484 | 0.972973 | 0.970588 | 0.998847 |
| 21 | 8 | 8 | 8 | test | 0.962963 | 0.962848 | 0.136800 | 0.966667 | 0.962963 | 1.000000 |
| 22 | 8 | 8 | 8 | validation | 0.952381 | 0.952137 | 0.093341 | 0.958333 | 0.952381 | 1.000000 |
| 23 | 8 | 8 | 8 | train | 0.941176 | 0.940715 | 0.083143 | 0.950000 | 0.941176 | 0.999423 |
Aggregate Batch Visualization¶
plot_performance
aka the “boomerang chart” is unique to AIQC, and it really brings the benefits of the library to light. Each model from the Batch is evaluated against all splits/ folds.
When performing classification, the secondary training metric (non-loss) is ‘accuracy’.
[ ]:
batch_multiclass.plot_performance(
max_loss = 0.12, min_accuracy = 0.96
)
Individual Job Visualization¶
Loss values in the first few epochs can often be extremely high before they plummet and become more gradual. This really stretches out the graph and makes it hard to see if the evaluation set is diverging or not. The loss_skip_15pct:bool
parameter skips displaying the first 15% of epochs so that figure is more useful.
[ ]:
batch_multiclass.jobs[0].results[0].plot_learning_curve(loss_skip_15pct=True)
These classification metrics are preformatted for plotting.
[13]:
batch_multiclass.jobs[0].results[0].plot_data['test'].keys()
[13]:
dict_keys(['confusion_matrix', 'roc_curve', 'precision_recall_curve'])
[ ]:
batch_multiclass.jobs[0].results[0].plot_roc_curve()
[ ]:
batch_multiclass.jobs[0].results[0].plot_confusion_matrix()
[ ]:
batch_multiclass.jobs[0].results[0].plot_precision_recall()
Regression¶
[17]:
batch_regression = tests.make_test_batch('regression')
___/ featurecoder_index: 0 \_________
=> The column(s) below matched your filter(s) and were ran through a test-encoding successfully.
['crim', 'zn', 'indus', 'nox', 'rm', 'age', 'dis', 'ptratio', 'lstat']
=> The remaining column(s) and dtype(s) can be used in downstream Featurecoder(s):
{'chas': 'int64', 'rad': 'int64', 'tax': 'int64'}
___/ featurecoder_index: 1 \_________
=> The column(s) below matched your filter(s) and were ran through a test-encoding successfully.
['rad', 'chas', 'tax']
=> Nice! Now all feature column(s) have encoder(s) associated with them.
No more Featurecoders can be added to this Encoderset.
[18]:
batch_regression.run_jobs()
🔮 Training Models 🔮: 100%|██████████████████████████████████████████| 4/4 [00:33<00:00, 8.31s/it]
Individual Job Metrics¶
Each training Result
contains the following metrics.
[19]:
from pprint import pprint as p
p(
batch_regression.jobs[0].results[0].metrics
)
{'test': {'explained_variance': 0.7456242137896081,
'loss': 0.2185862511396408,
'mse': 0.21858626188755587,
'r2': 0.7455021802201329},
'train': {'explained_variance': 0.7981549758441983,
'loss': 0.20313556492328644,
'mse': 0.20313555856135915,
'r2': 0.7968644414386409},
'validation': {'explained_variance': 0.8418251849670012,
'loss': 0.1677088737487793,
'mse': 0.16770889185282173,
'r2': 0.8384872353457703}}
It also contains per-epoch metrics calculated during model training.
[20]:
batch_regression.jobs[0].results[0].history.keys()
[20]:
dict_keys(['loss', 'mean_squared_error', 'val_loss', 'val_mean_squared_error'])
Aggregate Batch Metrics¶
[21]:
batch_regression.metrics_to_pandas()
[21]:
| hyperparamcombo_id | job_id | result_id | split | explained_variance | loss | mse | r2 | |
|---|---|---|---|---|---|---|---|---|
| 0 | 9 | 9 | 9 | test | 0.745624 | 0.218586 | 0.218586 | 0.745502 |
| 1 | 9 | 9 | 9 | validation | 0.841825 | 0.167709 | 0.167709 | 0.838487 |
| 2 | 9 | 9 | 9 | train | 0.798155 | 0.203136 | 0.203136 | 0.796864 |
| 3 | 10 | 10 | 10 | test | 0.749884 | 0.218382 | 0.218382 | 0.745740 |
| 4 | 10 | 10 | 10 | validation | 0.842932 | 0.169658 | 0.169658 | 0.836611 |
| 5 | 10 | 10 | 10 | train | 0.821700 | 0.183085 | 0.183085 | 0.816915 |
| 6 | 11 | 11 | 11 | test | 0.685934 | 0.352775 | 0.352775 | 0.589268 |
| 7 | 11 | 11 | 11 | validation | 0.813499 | 0.295778 | 0.295778 | 0.715150 |
| 8 | 11 | 11 | 11 | train | 0.804766 | 0.286330 | 0.286330 | 0.713670 |
| 9 | 12 | 12 | 12 | test | 0.765050 | 0.262876 | 0.262876 | 0.693937 |
| 10 | 12 | 12 | 12 | validation | 0.838108 | 0.211810 | 0.211810 | 0.796016 |
| 11 | 12 | 12 | 12 | train | 0.813985 | 0.244257 | 0.244257 | 0.755743 |
Aggregate Batch Visualization¶
When performing regression, the secondary training metric (non-loss) is ‘r2’.
[ ]:
batch_regression.plot_performance(
max_loss=0.5, min_r2=0.60
)
Individual Job Visualization¶
[ ]:
batch_regression.jobs[0].results[0].plot_learning_curve(loss_skip_15pct=True)


UX best practices promote improving the quality of the user’s interaction with and perceptions of your product and any related services.
Factors that influence UX
Usability vs UX
Usability falls under the umbrella of UX.
Why does Usability matter?
If users cannot achieve their goals efficiently and effectively, they are likely to seek an alternative solution to reach their goals.
Web Accessibility
Accessibility means that websites, tools, and technologies are designed and developed so that people with disabilities can use them.
More specifically, people can:
Perceive, understand, navigate, and interact with the web
Contribute to the web
Web Accessibility: Disabilities that affect access on the web
Web Accessibility: Benefits for users without disabilities
People using mobile devices
Elderly people with changing abilities
People with “temporary disabilities”
People with “situational limitations”
People using a slow internet connection
Web Accessibility: Why is it important?
When the web meets this goal, it is accessible to people with a diverse range of abilities.
Web Accessibility: W3C
The W3C Web Accessibility Initiative (WAI) develops technical specifications, guidelines, techniques, and supporting resources that describe accessibility solutions. These are considered international standards for web accessibility.
UX Design Process
The ins and outs
What does a UX process look like?
UX Design Process: Strategy
Stakeholder Discussions
Project Vision/Goals
Brand Strategy
Project Kick-off Meeting
UX Design Process: Discovery
Competitive Research
Surveys/Interviews
UX Design Process: Analysis
Personas
Experience Maps
Storyboarding
UX Design Process: Design
Site Mapping
Sketching
Wireframes
Prototypes
UX Design Process: Production
User Testing
Record Findings
Metrics Analysis
It’s important to understand that UX design isn’t a linear process – it’s an iterative process. These phases often overlap and go back-and-forth.
UX Design Process: Project Size and Constraints
Budget
Time available
Delivery deadlines
Available resources
Access to tools
Related Projects
Development Process: Waterfall vs Agile
Research & Understanding
Who, What, Where?
What is UX Research?
The research part of UX is defined as an action where you investigate something systematically.
In UX Research, you apply various techniques to add context and insight into the design process.
Competitive Research
Interviews
Persona Example:
Card Sorting
Experience Map Example:
Usability Testing
Why is UX Research important?
UX research removes assumptions from the design process and you will have real data to back up your design decisions.
If research is done correctly it will save your organization valuable time and money.
Visual Design
Prototypes, Mockups and Wireframes
What is a Wireframe?
A low-fidelity, simplified outline of your website or app. It gives you an idea of where everything will eventually go.
Visual Design: What is a Mockup?
A mid to high fidelity visual outline of your website or app. It reflects the design choices for the overall vision of the product.
Benefits of Mockups
Intuitive to stakeholders
Realistic perspective
Early revisions
Visual Design: What is a Prototype?
A simulation or sample version of a final product, which is used for testing prior to launch.
Benefits of Prototypes:
Type of prototype
Level of detail and realism
Functionality to the user
Lifecycle of the prototype
Visual Design: Prototyping Methodologies
Paper / Digital / HTML
Visual Design: Paper Prototyping
Works best in the initial stages of design, mainly for testing product ideas. They are fast, inexpensive and can be a great team-building exercise. They can also be kept as reference for future iterations.
Visual Design: Digital Prototyping
Most usual form of prototyping that is realistic enough to accurately test most UI elements and easier to produce than HTML prototypes. Can be built using apps and software made for prototyping.
Useful Digital Prototyping tools:
Balsamiq
Adobe XD/Illustrator/Photoshop
Invision App
Webflow
Visual Design: HTML Prototyping
Only recommended for designers who can code OR have the available resources to create an HTML prototype.
Usability Testing
Which test is best?
Usability Testing
Evaluate a product or service by testing with representitive users.
Observe while participants complete tasks
Helps to identify usability problems
Used to collect qualitative and quantitative data
Gauge user satisfaction
Usability Testing: Preparing for a usability study
Define study goals
Write test plan
Determine study format
Define study tasks
Tools and services
Recruit participants
Run a pilot study
Conduct user test
Usability Testing: Define study goals
What do you want to test and why?
Identify questions, concerns, and purpose of research
Goals determine which UX research method to choose
Usability Testing: Write a test plan
Meet with design team, engineers, product managers and other stakeholders.
Get consensus on what should be tested.
Start a dashboard to record your testing project plan, and update at each phase of planning.
Usability Testing: What to include on the test plan dashboard
Study goals/busniess case
Research questions
Description of target audience
Testing method
Testing tasks
Project participants
Dashboard Example:
Usability Testing: Determine study format
Qualitative (how, why?)
Moderated vs unmoderated
Remote vs live interview
If live, lab vs field study
Quantitative (how many, how often?)
A/B testing
Analytics
Usability Testing: Define study tasks
Tasks should match the study goals
Can be written as scenarios or specific directive
Try to avoid biasing the user
Usability Testing: Types of tasks
Exploratory
Specific
- Open Ended
- Focused on an end point or "right" answer
- Many not have a "right" answer
- Can be used for qualitative and quantitative testing
- Allows for observation based results
- Used for qualitative testing
Usability Study: Tools and services
UserZoom
UserTesting
Loop 11
Optimal Workshop
Local Research Company
Usability Testing: Recruiting participants
Qualitative Study
Quantitative Study
5-8
20 or more
Jakob Nielsens Alertbox:
Usability Testing: Recruiting participants
Test participants should match the demographic of your actual users. Some considerations:
Age
Language
Education
Technical proficiency
Employment status
Gender
Location
Income
Usability Testing: Recruiting participants
If cost is a barrier, consider alternatives to formal research participants.
Friends and family
Co-workers or new hires at your company
Guerilla testing with the general public
Usability Testing: Run a pilot study
Fine-tune tasks
Can catch problems before the real test
Ensure that you have the right participants
Tweak your plan based on pilot study results
Usability Testing: Conduct the usability test
For live or moderated testing:
Brief your participants. Set expectations for your testing session.
Make sure consent agreements are signed.
Watch and listen.
For remote testing through a service:
Launch your study.
Guerilla Testing
User Testing Session
Paper Prototype Testing
Using Testing Software
Metrics Analysis
Validate all the things
Metrics allow you to:
Track progress between releases
Assess your competitive position
Make decisions before launch
Metrics Analysis: How to Measure
It may be easy to specify usability metrics, but hard to collect them. Usability is typically measured relative to user’s performance on a given set of tasks.
Usability Metrics should include:
Effectiveness / success rate
Efficiency
Satisfaction
However, the actual ways of how these should be measured is left up to the evaluator.
Metrics Analysis: Completion Rate Equation
You should always aim for a completion rate of 100% if possible, however, the completion rate is highly dependent on the context of the task being evaluated.
Completion Rate Example:
Completion Rate Example:
It is very easy to graphically represent completion rate.
Metrics Analysis: Measure Task Time
Efficiency is measured in terms of task time – seconds or minutes the participant takes to successfully complete a task.
Time on Task Example:
Original Design
Redesign
Task 1
130 sec
89 sec
Task 2
240 sec
121 sec
Task 3
80 sec
30 sec
You can then compare times during iterative rounds to testing to determine improvement.
Metrics Analysis: Measuring Satisfaction
User satisfaction is measured through standardized satisfaction questions which can be implemented after each task and/or after the usability test is completed.
Metrics Analysis: Task Level Satisfaction
After a user attempts a task they should immediately be given a questionnaire to measure how difficult the task was.
Single Ease Question Example:
One of the most popular post-task questionnaires is Single Ease Question (SEQ). They are short and easy to respond to, administer and score.
Metrics Analysis: Test Level Satisfaction
Measured by giving a formalized questionnaire to each test participant at the end of the test session.
One of the most popular post-test questionnaires is the System Usability Scale (SUS). Mostly used to measure the user satisfaction with software, hardware and mobile devices.
SUS Example:
Clicktale
Captures mouse movement, clicks, scrolls, taps, zooms, and tilts that a visitor makes within a web page (desktop or mobile). You can see visitor recordings, visual heat maps and other behavioral reports.
KISSmetrics
A behavioral analytics system that tracks user clicks, pages visited, bounces (1-page visit followed by an exit), and conversions such as purchases, donations, registrations, signups and read times.
Google Analytics
A free website analytics service offered by Google that gives you insights into how users find and use your website. It tracks your webiste traffic, user behaviors, such as pageviews and time on pages, and reports user interaction.
Metrics Analysis: Summarizing Results
Once you’ve gathered metrics you can use them to formulate an overall conclusion about your designs usability.
You can show the increase or decrease in usability as the results of a redesign.
Metrics Analysis: Sharing Results
Conveying user research findings can be a challenge – no one wants to read a huge word document or read a long email.
Providing enough detail without boring your audience is a difficult balance.


CrackMapExec
CrackMapExec (a.k.a CME) is a post-exploitation tool that helps automate assessing the security of large Active Directory networks. Built with stealth in mind, CME follows the concept of "Living off the Land": abusing built-in Active Directory features/protocols to achieve it's functionality and allowing it to evade most endpoint protection/IDS/IPS solutions.
CME makes heavy use of the Impacket library (developed by @asolino) and the PowerSploit Toolkit (developed by @mattifestation) for working with network protocols and performing a variety of post-exploitation techniques.
Although meant to be used primarily for offensive purposes (e.g. red teams), CME can be used by blue teams as well to assess account privileges, find possible misconfigurations and simulate attack scenarios.


| [5] | Agrusta, R., Morison, A., Labrosse, S., Deguen, R., Alboussière, T., Tackley, P. J., and Dubuffet, F. Mantle convection interacting with magma oceans. Geophys. J. Int., 220:1878–1892, 2019. [ DOI ] |
| [4] | Morison, A., Labrosse, S., Deguen, R., and Alboussière, T. Timescale of overturn in a magma ocean cumulate. Earth Planet. Sci. Lett., 516:25 – 36, 2019. [ DOI | http ] |
| [3] | Bouffard, M., Choblet, G., Labrosse, S., and Wicht, J. Chemical convection and stratification in the Earth's outer core. Frontiers in Earth Science, 7:99, 2019. [ DOI | http ] |
| [2] | Labrosse, S., Morison, A., Deguen, R., and Alboussière, T. Rayleigh-Bénard convection in a creeping solid with a phase change at either or both horizontal boundaries. J. Fluid Mech., 846:5–36, 2018. [ DOI ] |
| [1] | Laneuville, M., Hernlund, J., Labrosse, S., and Guttenberg, N. Crystallization of a compositionally stratified basal magma ocean. Phys. Earth Planet. Inter., 276:86–92, 2018. [ DOI | http ] |
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--- layout: page title: Mentoring permalink: /mentoring/ ---
Mentor: a trusted guide, a provider of wise counsel and advice, a confidant.
I've been mentoring organizations with Visual FoxPro, web, and SQL applications for 25 years
My mentoring relationships are:
Making your website strong is always an incremental process.
I work with website managers to make smart plays while following sound plans.
Throughout all this I work with your webmaster as a website coach to ensure knowledge and skills get transferred, the work gets done, and the results get measurably achieved.


EBD - Easton Bible DIctionary
Ptolemais
PTOLEMAIS
"PTOLEMAIS "a maritime city of Galilee (
Acts 21:7
). It was originally called “Accho” (q.v.), and received the name Ptolemais from Ptolemy Soter when he was in possession of Coele-Syria.
"PTOLEMAIS "a maritime city of Galilee (Acts 21:7). It was originally called “Accho” (q.v.), and received the name Ptolemais from Ptolemy Soter when he was in possession of Coele-Syria.


Contents of this page:
Enumeration types in VB allow the representation of a single value by a number of different states. Python has no equivalent concept and so enumerations are simply mapped to a series of integer values. The enumeration names become local or global names depending on the scope of the enumeration. If the values for the enumeration items are specified then these are used, if not then the values are chosen sequentially starting at zero.
| VB | Python |
|---|---|
|
|
There are no options specific to the Enum statement.