First a little background about me:
I have suffered severe depression for the last 20 years. Thanks to antidepressants this situation has been livable. When I first start cycling with depression there were times when I couldn't remember how to brush my teeth or the names of people I had known for years. I called it flatline - total brain shutdown. When I was up I performed very well, IQ of 150 with all the bonuses. I was as a young teen against all drugs. After several cycles of cognitive flatline I knew that all the anti-drug propaganda deserved a second look.
For the next 10 years a tried a variety of anti-depressants and other legal psychoactive substances including: lithium, tegretol, imipramine, vivactil, prozac, anafranil, serzone, reboxetine, levodopa, pergolide, bromocriptine, and Ritalin all to little avail. The combination that eventually gave some relief (for the last 10 years) Wellbutrin ( 450 mg) and Effexor (225 mg) supplemented in recent years by Deprenyl ( 5mg) . These combinations span over 20 years. Intermittently, every few years I would go cold turkey for about 6 months always to disastrous ends, the mind numbing flatness would return emotionally and cognitively.
The working combination¯ enabled me to be mentally very capable, holding down a six figure job and advancing well in my career. However the emotional problems remained, I became a very logical person¯ unmoved or motivated by emotional or romantic interests. For whatever reason, I was numb in many respects which was better than flat. Dating and friends were completely uninteresting to me. I knew I should want these things, but to say I was cold was an understatement. I had a tendency to like intense situations as these could generate a rise out of me. Eventually I all but conditioned away any hint of fear or other primal emotions. I thrived on situations that would frighten other people, these situations helped me feel alive. Eventually through repeated exposure I burned out on many of the thrills and even they wouldn't give me a rise. My number one problem was motivation. It took herculean efforts to get myself motivated about anything outside of work.
The antidepressants made many illegal drugs that might have interested me a non-starter. Early on, in periods when I wasn't on anti-depressants I went through a binge¯ year or two with acid tripping consuming several hundred hits. I did mushrooms a few times and MDMA a few times as well. The anti-depressants made these drugs ineffective because they bound to many of the same receptors. I had also tried smoking pot many times, and cocaine occasionally. These two drugs seemed to have no effect at all.
Last week for the first time I tried Salvia Divinorum:
And everything changed! The after glow from it is amazing. It seems the theory of kappa-opioid agonists resetting something deep in the mind might hold some merit.
Let me start at the beginning...
I got introduced to Salvia Divinorum by a news story just last month. I had never heard of it before. I prolifically began to study every aspect of it and read every experience I could find. I became interested in opioid receptor drugs after hearing that ketamine cured treatment resistant depression in many severe cases that barely responded to antidepressants. Reading that Salvia was legal and a kappa opioid receptor agonist I knew I had to try it.
I ordered 10 grams of 10x extract from a reliable online vendor and had it overnighted to me.
Eagerly I opened the package and was cautious. I had heard this was very powerful stuff. I am currently on effexor, wellbutrin and deprenyl and was cautious about possible interactions. I knew that many drugs barely registered a threshold level of experience with me, however, I had read that this was a very powerful drug.
I proceeded to take 0.5 grams sublingually last Thursday afternoon. Letting it dissolve¯ in my mouth for over 20 minutes I felt some mild effects, things were just a bit surreal. However, at this point I hadn't realized the value of using alcohol to prepare my mouth to maximize the amount of Salvorinum A passing through to the blood so the experience was more mild than it would have been.
At this point I decided to smoke about 1/10th of a gram of this 10x extract and see where that would go. After 3 or 4 hits I felt the typical bending and pulling sensation mentioned by many salvia users. But the best was the emotional part. It felt extremely intense and was even SCARY. I couldn't believe it. I was actually scared, a feeling very foreign to me. Not a scary monster type scared but a this is too intense¯ scared. I remember saying the words 'This is so cool'¯ and 'This is so intense'. I then laid down and started to get very, very horny and turned on (a rarity for me). I proceed to imagine some very creative things and as I came down I ended up masturbating to incredible effect.
In the next several days I proceeded to smoke and consume Salvia every day or two. Every time I smoked I would hit a point where I would think 'This is almost too intense'¯ and the peak would start to come down. The smoking peaks would only last 2 or 3 minutes. When I dosed sublingually the effects seemed to last for about an hour.
The amazing bits were the afterglow effects. For the first time in decades I literally loved people again. I couldn't help but get excited when I interacted with others. I had so many emotional responses to our interactions. Emotional responses that were totally not there prior to smoking the salvia. The theory with this is somehow kappa opioid receptor agonists of this intensity 'reset'¯ some of the brains core chemical systems. This made me human again. I am so excited about people. I realize from other accounts that I will no doubt need to periodically re-administer the salvia to keep repriming the pump.
Some of the interesting side effects of the salvia are the way it changed my dreams. I have had lucid dreams for a long time. Literally hundreds of dreams in my life where I realize I am dreaming and can control my dreams. I am used to weird dreams. The salvia however had a really interesting effect. Some how my dreams are louder¯ than usual. Not loud in the sense of sound, but loud in an intensity kind of way. I occasionally wake up from dreams now literally with a headache, it reminds me of listening to the TV when it is up too loud.
The salvia has done some amazing things for me. Though I suppose I would be described as a hard-head I don't mind at all. The salvia managed to make me happy in ways that no other drugs could in the after-glow¯.  Best of all it has given me incredible hope.
I am sure I will have many more tales to tell about this wonderful plant! Thank you salvia divinorum for washing my depression away!
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Sockitter Editor
Use the text area to add/remove screen names to index via Twitter's stream. Click the
submit
button to update the list. Use only one screen name per line. Screen names are ordered by numeric ID. After editing the list, be sure to restart the connector from the
Fusion UI
.
Submit


'Liberman set up mines for us, but we must overcome them'
Ayelet Shaked calls on Likud, Blue and White to form unity government as time for formation of coalition government runs out.
by Arutz Sheva StaffNew Right co-chairwoman MK Ayelet Shaked on Wednesday called for efforts to establish a unity government, in light of Avigdor Liberman's statement that he would not join a Blue and White-led minority government or a narrow right-wing government.
At a meeting of the right-wing bloc Wednesday. Shaked said, "Every effort must be made to reach a unity government. It is true that Liberman has put some mines before us, but that does not mean that they cannot be dismantled or overcome."
"There is no doubt that quite a few citizens of the State of Israel want this camp to continue to lead the country. We need to do what we can together to find solutions and certainly try to avoid a third election campaign.
"Dragging the state into a third election system is political lawlessness and irresponsibility, particularly in light of the economic and security challenges we face," Shaked added.
"I think that's the only thing we will agree with Liberman on. He said that there are major economic and security challenges and that is why a government should be formed and not be drawn into a third election campaign," she concluded.


Which stores are open, which closed on Thanksgiving; when do stores open on Black Friday?
by Debbie Lord , Cox Media Group National Content DeskThanksgiving is fast approaching, it’s on Nov. 28, so that means the day after Thanksgiving – Black Friday – is on the way, as well.
Major retailers are beginning to release their Black Friday ads and announcing their store hours. Below is a list of stores open on Thanksgiving, the ones that are closed and what time everyone opens on Black Friday.
Come back here as Black Friday gets closer. This story will be updated as more store openings, closings and hours are announced.
Stores closed on Thanksgiving
These stores have announced they will be closed on Thanksgiving. This list will be updated as more stores announce their Thanksgiving hours.
- A.C. Moore
- Abt Electronics
- Ace Hardware
- Academy Sports and Outdoors
- American Girl
- Bed Bath & Beyond
- Big 5 Sporting Goods
- BJ’s Wholesale Club
- Blain’s Farm & Fleet
- Bloomingdale’s
- Burlington Coat Factory
- Christmas Tree Shops
- Costco
- Craft Warehouse
- Crate and Barrel
- Dillard’s
- Ethan Allen
- Fleet Farm
- Guitar Center
- H&M
- Half Price Books
- Harbor Freight
- Hobby Lobby
- Home Depot
- HomeGoods
- IKEA
- Jo-Ann Fabrics and Crafts
- Lowe’s
- Marshall’s
- Mattress Firm
- Micro Center
- Northern Tool
- Petco
- PetSmart
- Pier 1 Imports
- REI
- Sam’s Club
- Sierra Trading Post
- Sportsman’s Warehouse
- The Container Store
- Tractor Supply Company
- True Value
Stores open on Thanksgiving
These stores have announced they will be open on Thanksgiving (Nov. 28).
- Ace Hardware – Open, but hours vary by location
- Bass Pro Shops – 8 a.m. to 6 p.m.
- Bealls – 1 p.m. to 1 a.m. Friday
- Bealls Florida – 5 p.m. to 11 p.m.
- Belk’s – 4 p.m. to 1 a.m. Friday
- Best Buy – 5 p.m. to 1 a.m. Friday
- Big Lots – 7 a.m. to midnight
- Boscovs – 6 p.m. to 1 a.m. Friday
- Cabela’s – 8 a.m. to 6 p.m.
- Dell – 10 a.m.
- Dick’s Sporting Goods – 6 p.m. to 2 a.m. Friday
- Dollar General – 7 a.m. to 10 p.m.
- Dunham’s Sports – 3 p.m.
- Exchange – 8 a.m.
- Family Dollar – 8 a.m. to 9 p.m.
- Farm and Home Supply – 8 p.m.
- Five Below – 6 p.m. to 1 a.m. Friday
- Fred’s – 9 a.m. to 5 p.m.
- Game Stop – 3 p.m.
- Goody's – 1 p.m. to 1 a.m. Friday
- hhgregg – 10 a.m. to 6 p.m.
- J.C. Penney – 2 p.m. Thursday
- Kmart – 6 p.m. to midnight
- Kohls – 5 p.m.
- Macy’s – 5 p.m. to 2 a.m. Friday
- Meijer – 6 a.m.
- Michaels – 6 p.m. to midnight
- Micro Center – 8 a.m. to 10 p.m.
- Microsoft – 12 a.m. Thursday (online)
- Modell’s Sporting Goods – 6 p.m.
- Musicians Friend – 5 a.m. to 9 p.m.
- New York & Company – 6 p.m.
- Old Navy – 4 p.m.
- Olympia – Open, store hours vary
- Pep Boys – Open, store hours vary
- Radio Shack – 8 a.m. to 1 p.m.
- Rural King – 7 a.m. to 10 p.m.
- Sears – 6 p.m. to midnight; reopens at 5 a.m. Friday
- Shopko – 2 p.m.
- Stage – 1 p.m. to 1 a.m. Friday
- Target – 5 p.m. to 1 a.m. Friday; reopens at 7 am. Friday
- Ulta – 6 p.m. to 2 a.m. Friday
- Value City – 6 p.m. to midnight
- Victoria’s Secret – 6 p.m.
- Walgreens – 8 a.m. to 10 p.m. (hours may vary by location)
- Walmart – Walmart stores will be open regular hours on Thanksgiving. Black Friday sales begin at 6 p.m.
What time stores open on Black Friday
Here is a list of store openings on Black Friday (Nov. 29).
- Academy Sports and Outdoors – 6 a.m.
- Ace Hardware – Hours vary by location
- Bass Pro Shops – 5 a.m.
- Bealls – 6 a.m.
- Bealls Florida – 6 a.m.
- Belk – 6 a.m.
- Best Buy – 8 a.m.
- Big Lots – 6 a.m.
- BJ’s – 7 a.m.
- Boscovs – 6 a.m.
- Cabela’s – 5 a.m.
- Costco – 9 a.m.
- Dick’s Sporting Goods – 5 a.m.
- Dollar General – Opening times vary by location Friday
- Exchange – 6 a.m.
- Family Dollar – 8 a.m.
- Farm and Home Supply – 7 a.m.
- Five Below – 8 a.m.
- Fred’s – 8 a.m.
- Game Stop – Friday hours not yet announced
- Goody’s – 6 a.m.
- hhgregg – 7 a.m. Friday
- Hobby Lobby – 8 a.m.
- HomeGoods – 7 a.m.
- J.C. Penney – 2 p.m. Thursday all night through Friday
- Kmart – 6 a.m.
- Kohls – Times vary by location on Friday
- Macy’s – 6 a.m.
- Lowe’s – 6 a.m.
- Marshalls – 7 a.m.
- Meijer – 6 a.m.
- Michaels –7 a.m.
- Micro Center – 9 a.m. Friday
- Microsoft – 12 a.m. Thursday (online)
- Modell’s Sporting Goods – Friday opening times vary by location
- Musicians Friend – 5 a.m.
- New York & Company – 6 p.m. Thursday through Friday
- Old Navy – Friday opening times vary by location
- Olympia – 5 a.m.
- Office Depot/Office Max – 8 a.m.
- Pep Boys – 8 a.m.
- Radio Shack – Opening times on Friday vary by location
- Rural King – 6 a.m.
- Sam’s Club – 7 a.m.
- Sierra Trading Post – 7 a.m.
- Stein Mart – 7 a.m.
- TJ Maxx – 7 a.m.


genderPanel = new JPanel(); genderPanel.setLayout( new BoxLayout(genderPanel , BoxLayout.Y_AXIS));
Here is the section of the code that
deals with the buttons for height.
The buttons are added to
(1) heightPanel
, which
controls their graphic representation
on screen, and added to (2)
heightGroup
, which controls
their logical operation.
One button of the heightGroup
is
set to be choosen by default.
As with the gender buttons, BoxLayout
is used in the panel to put the label and
buttons in a column.
public class IdealWeight extends JFrame { JRadioButton heightA; JRadioButton heightB; JRadioButton heightC; JRadioButton heightD; JRadioButton heightE; ButtonGroup heightGroup; JPanel heightPanel; public IdealWeight() { // height group heightA = new JRadioButton("60 to 64 inches",true); heightB = new JRadioButton("64 to 68 inches",false); heightC = new JRadioButton("68 to 72 inches",false); heightD = new JRadioButton("72 to 76 inches",false); heightE = new JRadioButton("76 to 80 inches",false); heightGroup = new ButtonGroup(); heightGroup.add( _________ ); heightGroup.add( _________ ); heightGroup.add( _________ ); heightGroup.add( _________ ); heightGroup.add( _________ ); heightPanel = new JPanel(); heightPanel.setLayout( new BoxLayout(heightPanel,BoxLayout.Y_AXIS)); heightPanel.add( new JLabel("Your Height") ); heightPanel.add( _________ ); heightPanel.add( _________ ); heightPanel.add( _________ ); heightPanel.add( _________ ); heightPanel.add( _________ ); . . . . .


Provides a PassVerifier class mostly used internally by JustIce, yielding a control flow graph for public use as
a nice side effect.
Package Specification
Contained in this package is a PassVerifier class for use with the JustIce verifier and its utility classes.
Only the pass performing what Sun calls "Structural Constraints on Java Virtual Machine Code"
has a PassVerifier class here. JustIce calls this pass "Pass 3b".
Related Documentation
For a simple demonstration of JustIce working, please see:


This article describes how to upgrade an Erlang cluster in one fell swoop once you have deployed it on Amazon EC2.
The standard and sanctioned way of deploying and upgrading Erlang applications is described in chapters 10-12 of the OTP Design Principles. Calling the upgrade procedure complex is an understatement.
Bowing to the OTP application packaging procedure, I wanted to have a way of upgrading applications with a “push of a button”. More precisely, I wanted to be able to type make:all() to rebuild my application and then type sync:all() to push updated modules to all nodes in my cluster. These nodes were previously set up as “diskless” Amazon EC2 nodes that fetch their code from the boot server since I didn’t want to reinvent the application packaging wheel.
The principal application deployed in the cluster is the “sync” app. This is a gen_server set up according to chapter 2 of the OTP Design Principles. The gen_server handles requests to restart the Erlang node without shutting down and set environment variables, as well as requests upgrade the code by application or by process. Each sync gen_server joins the ‘SYNC’ distributed named process group and this is what enables upgrade of the whole cluster in one fell swoop.
The sync server will invoke init:restart/0 to restart the node without shutting down upon receiving the RESTART request. This is incredibly handy since the restart sequence takes the contents of the Erlang VM to the trash can and then repeats the same steps taken by the Erlang VM when it is started from the command line. Which is to say that the VM loads the boot file from the boot server, parses the boot file, downloads the applications and runs them. If we have upgraded the code on the boot server then the Erlang VM will run new code after a restart.
The above procedure is quite intrusive since all apps running in the Erlang VM are killed. Any Erlang node will normally be running a number of apps and you may want to upgrade just one or two of them. This is where the “upgrade by application” procedure comes in.
application:get_application/1 will give you the name of the application that a module belongs to. I build a unique list of applications that my changed modules belong to and then stop each application with application:stop/1, re-load changed modules and start the application with application:start/1.
The “upgrade process by process” procedure first grabs a list of all processes running in the same node as the sync gen_server. It does this by calling processes(). I check whether each process is running the code in one of the modified modules using erlang:check_process_code/2. Next, I suspend affected processes with erlang:suspend_process/1, re-load changed modules with erlang:resume_process/1 and I’m done.
I’m still not absolutely sure if I got reloading of changed modules right but it looks like this:
load_modules([]) ->
ok;
load_modules([Mod|T]) ->
code:purge(Mod),
code:soft_purge(Mod),
{module, Mod} = code:load_file(Mod),
load_modules(T).
The need to call code:soft_purge/1 after code:purge/1 was determined empirically.
Everything I have described thus far is small bits of code. The biggest chunk of code in the sync server figures out what modules were modified.
Remember my original intent to run make:all/0 followed by sync:all/0 to upgrade all nodes in the cluster at the same time? It’s only possible because 1) it’s possible to grab the module version from a module loaded into memory, 2) it’s possible to grab the same from a module on disk and, crucially, modules are not reloaded when make:all/0 is run.
The module version defaults to the MD5 checksum of the module if no -vsn(Vsn) attribute is specified. For the life of me I can’t remember where Module:module_info() is documented but this is what you use to grab the attributes of the module. It’s a property list so you can use proplists:get_value/2 to grab the vsn property and thus the module version.
To take advantage of local processing power, the API initiating the upgrade request does no work apart from inspecting the SYNC distributed named process group and telling each sync gen_server in the group to initiate the upgrade procedure. This means that each module loaded into the Erlang node hosting the sync server needs to be checked for changes.
Grabbing the version of the BEAM file holding the code for a given module is done using beam_lib:version/1. This is complicated by the fact that all of the Erlang EC2 nodes in the cluster download their code from the boot server. Normally, beam_lib:version/1 takes either a module name, a file name or a binary.
I haven’t documented why I’m not using a module name or a file name in the boot server scenario but I must have found them not to work. I had to resort to fetching the module BEAM file from the boot server and inspecting that. Fortunately, traffic between EC2 instances is free and fast and the same applies to your LAN.
To find out if a module is modified I grab the list of loaded modules with code:all_loaded/0 and inspect each module with code:is_loaded/1. I skip preloaded modules (see documentation for code:is_loaded) and use the path returned otherwise to instruct erl_prim_loader:get_file/1 to fetch the BEAM file. I then pass the file contents to beam_lib:version/1 and I have my disk version. After that it’s a simple matter of comparing the two versions and reloading the module if they differ.


Australia
Technologies
ASP.NET MVC (C#), AngularJS Stack, HTML, CSS, Bootstrap, jQuery, MSSQL, Power BI, LUIS, IIS, RESTful API, Microsoft Azure.
Project Lifecycle
Agile.
Project Description
Resonate works in providing software as a service to help clients manage customer experience (CX) with the help of Surveys and complex text analytics to leverage valuable insights in the operational activities of some of the biggest telecom, retail and financial clients in Australia. One of the ways in which Resonate help their clients to achieve this is with the help of a callback portal which enables them to store, analyze and act on customer feedback. .
Key responsibilities
- Build new features and maintain existing ones for Resonate’s main product - VoC (Voice of Customer) platform, an AngularJS/ASP.NET MVC multi-tenanted application.
- Strict adherence to W3C standards and cross-browser compatibilities.
- Attended daily Scrum meetings, kept up-to-date on best practices for JavaScript frameworks and techniques.
- Handled Browser compatibility issues for different browsers related to CSS and HTML.
- Build new features on a cognitive BOT using Microsoft Azure LUIS Service.
- Experience in database design and development using SQL Azure and Microsoft SQL Server.
- Use CI / CD (Continuous Integration and Deployment) tools to integrate and deploy code to various environments.
- Design RESTful APIs to perform CRUD operations on the database.
- Use PowerBI to create highly interactive dashboards with drill-throughs to showcase summarized view of the actions taken on customer feedback.


{% extends ../layouts/base.html %} {% block page_title %}Pinfinity Book Hub Gallery{% endblock %} {% block page_description %} A gallery and preview tool for HTML5 widgets used in iBooks Author. {% endblock %} {% block main_content %}
Widget Frame


No Share Data Agreement. We, Team Bagcampus Will Not Share Your Data Until You Have Been Shortlisted By
Organization/Company/Startup
-
1. This is One Week Program and Each Domain Include 2 Tasks. The Applicant Will Be Eligible For Rewards
Only If They Complete Both Task Before Deadline
-
2. Bagcampus Does Not Assure The Internship and Job After Completion. The Selection of Candidate for
Internship/Job is Dependent on Company
-
3. Certificate From Bagcampus On Completion of Bagcampus™ Power Camp 2021 Competition is Given Only If
Candidate Complete Both Tasks.
-
4. Bagcampus Holds The Rights To Modify or Cancel The Event
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5. Bagcampus may contact you via email to provision benefits and other communication related to the
Bagcampus™ Power Camp 2021
-
6. Interview Before Joining After Bagcampus™ Power Camp 2021 is Not Responsibility of Bagcampus. It is
Total Responsibility of Company/Organization/Startup Who Have Hired Employee/Intern
-
7. Bagcampus Holds The Right To Add New Terms, Remove Some And Update The Terms.
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8. One Person Can Enroll In One Domain And Have Choice of Only One Form Submission.
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9. If a Candidate Fill Duplicate Entry, The Recent Form Submission Will Be Taken Under Consideration.
-
1. Bagcampus Will Never Share Your Email or Any Personal Info To Any Company or Organization
-
2. Bagcampus Holds The Rights To Change Schedule of Event
-
3. Certificate for Event Will Be Generated In Case Only If Both Task Are Submitted Before Deadline
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4. If You Have Not Attended Session or You Have Not Filled Feedback Form You Will Not Be Able To Get
Certificate
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5. Privacy To Your Personal Info Are More Important For Us
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6. The Event And Services Provided By Bagcampus Are Absolutely Free. In Case of Any Fake Call or Message
it is
Applicants/Attendees Responsibility To Inform Us at Bagcampus.in
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7. Bagcampus Never Promote Any Paid Courses, Internships Having Paid Registrations, etc.
Additional Terms
Communications
We may send you promotions or otherwise communicate with you electronically, which may include email, push
notification,
and you hereby consent to receive those communications. These communications will be in accordance with the
Bagcampus
Privacy
Policy.
Modification of Free Services
Bagcampus reserves the right to modify, suspend, or discontinue the Free Services, or any part of the
Free Services
Service, at any time and without notice (except as required by applicable law), and Bagcampus will not be liable
to you
should
it exercise such rights, even if your ability to use Educational Content is impacted by the change.
Amendments:
Bagcampus reserves the right to make changes to this Agreement at any time by posting the revised terms in
connection
with the
Free Services. To the maximum extent permitted by law, your continued use of the Free Services following
any changes will constitute your acceptance of such changes.
Disputes/Conditions of Use:
Any dispute or claim arising from or relating to this Agreement or the Free Services is subject to the governing
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Contact Information:
For communications concerning this Agreement, please write to Bagcampus at
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Severability:
If any term or condition of this Agreement is deemed invalid, void, or for any reason unenforceable, that part
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Using the Codeigniter 4 standard on your projects with Sublime Text
We moved to Codeigniter 4 for our new projects. Until now, we’ve using phpfmt so everyone in the team can use the same standard while coding.
However Codeigniter 4 has it’s own standard and it just makes sense for us to move to that new standard.
For this we need:
There’s a few ways we can go about this, but since this was something that we actually need to use on a bunch of projects I going with installing all this globally.
1. PHP Code Sniffer
PHP_CodeSniffer requires PHP version 5.4.0 or greater, although individual sniffs may have additional requirements such as external applications and scripts. See the Configuration Options manual page for a list of these requirements.
If you’re using PHP_CodeSniffer as part of a team, or you’re running it on a CI server, you may want to configure your project’s settings using a configuration file.
$ composer global require "squizlabs/php_codesniffer=*"
2. Codeigniter 4 - Coding Standard
Using composer this can also be installed globally.
$ composer global require codeigniter4/codeigniter4-standard
3. PHP CS Fixer
To install PHP CS Fixer, install Composer and issue the following command:
$ composer global require friendsofphp/php-cs-fixer
Then make sure you have the global Composer binaries directory in your PATH. This directory is platform-dependent, see Composer documentation for details. Example for some Unix systems:
$ export PATH="$PATH:$HOME/.composer/vendor/bin"
4. Sublime-phpcs package
Open your sublime text and install this package. After that you want to to open the user setting and change the following:
You should pay special attention to the following setting:
"phpcs_executable_path": "/home/marco/.config/composer/vendor/squizlabs/php_codesniffer/bin/phpcs",
"phpcs_additional_args": {
"--standard": "/home/marco/.config/composer/vendor/codeigniter4/codeigniter4-standard/CodeIgniter4",
"-n": ""
},
"php_cs_fixer_executable_path": "/home/marco/.config/composer/vendor/friendsofphp/php-cs-fixer/php-cs-fixer",
"phpcbf_executable_path": "/home/marco/.config/composer/vendor/squizlabs/php_codesniffer/bin/phpcbf",
"phpcbf_additional_args": {
"--standard": "/home/marco/.config/composer/vendor/codeigniter4/codeigniter4-standard/CodeIgniter4",
"-n": ""
},
The paths should be the ones you have on your system. I’m on linux, so the composer installed globally are in my .config. If you’re on windows or mac your paths might differ.


{% extends "base.html" %} {% block page_title %}404 - Page not found{% endblock %} {% block page_content %}
Nothing will come of nothing.


|
facebook360_dep
Facebook360 Depth Estimation Pipeline
|
Public Member Functions | |
| def | setUp (self) |
| def | check_binary_availability (self, binary_name) |
| def | gen_command (self, binary_name, args_string, output_root, log_dir=None) |
| def | gen_command_flagfile (self, binary_name) |
| def | gen_args_flagfile (self, binary_name) |
| def | run_app (self, binary_name, args=None, log_file=None) |
| def | assert_within_atol (self, actual, desired, tolerance) |
| def | assert_within_rtol (self, actual, desired, tolerance) |
| def | check_metrics (self, record, setup=None) |
| def | check_correct_error (self, setup=None) |
| def | check_against_truth (self, truth, output) |
Static Public Attributes | |
| bool | track_code_coverage = True |
Master class for all app unit tests. DepTest is never itself directly run. Any additional tests that are created should subclass this to leverage the created testbed. unittest.TestCase is subclassed to provide functionality for execution. Attributes: track_code_coverage (bool): Whether or not to save coverage on running applications.
| def test_master_class.DepTest.assert_within_atol | ( | self, | |
| actual, | |||
| desired, | |||
| tolerance | |||
| ) |
Asserts whether or not the actual value falls within an absolute tolerance of an expected result. Args: actual (float): Value to be used as our "actual" result. desired (float): Expected result of the metric. tolerance (float): Variance (two-sided) bound actual should fall within. Raises: AssertionError: If the absolute error is above the tolerance.
| def test_master_class.DepTest.assert_within_rtol | ( | self, | |
| actual, | |||
| desired, | |||
| tolerance | |||
| ) |
Asserts whether or not the actual value falls within a relative tolerance of an expected result. Args: actual (float): Value to be used as our "actual" result. desired (float): Expected result of the metric. tolerance (float): Variance (two-sided) bound actual should fall within relative to the desired result (i.e. a percentage). Raises: AssertionError: If the relative error is above the tolerance.
| def test_master_class.DepTest.check_against_truth | ( | self, | |
| truth, | |||
| output | |||
| ) |
Asserts whether or not truth and output paths are identical. Args: truth (str): Path to file or directory on disk containing the expected result files. output (str): Path to file or directory on disk containing the test result files. Raises: AssertionError: If the visible entries in truth and output paths differ.
| def test_master_class.DepTest.check_binary_availability | ( | self, | |
| binary_name | |||
| ) |
Checks whether or not the binary exists. Exits with error code 1 if the binary does not exist. Args: binary_name (str): Name of the binary to be checked.
| def test_master_class.DepTest.check_correct_error | ( | self, | |
setup = None |
|||
| ) |
Assert whether or not the error produced by the binary being executed is what is expected from the truth. Args: setup (dict[str, _], optional): Setup for the test. Raises: AssertionError: If the error produced is different from that expected.
| def test_master_class.DepTest.check_metrics | ( | self, | |
| record, | |||
setup = None |
|||
| ) |
Asserts whether or not all the metrics present in record align with those expected from the truth to the specified tolerance. Args: record (dict[str, float]): Values of relevant metrics from the test. setup (dict[str, _], optional): Setup for the test. Raises: AssertionError: If any of the metrics does not fall within the specified tolerance corresponding to it in the truth.
| def test_master_class.DepTest.gen_args_flagfile | ( | self, | |
| binary_name | |||
| ) |
Constructs CLI arguments from the flagfile, assuming the format in res/test/. Args: binary_name (str): Name of the binary. Returns: str: Space-separated string of CLI arguments (e.g. "--example1 <X> --example2 <Y>")
| def test_master_class.DepTest.gen_command | ( | self, | |
| binary_name, | |||
| args_string, | |||
| output_root, | |||
log_dir = None |
|||
| ) |
Constructs the command to be run to execute the desired binary with the arguments specified and saving the outputs in the specified location. Args: binary_name (str): Name of the binary. args_string (str): CLI arguments for the binary. output_root (str): Root directory where the outputs are to be saved. log_dir (str, optional): Path to the directory where glog files are to be saved. Returns: str: Command to run.
| def test_master_class.DepTest.gen_command_flagfile | ( | self, | |
| binary_name | |||
| ) |
Constructs the command to be run to execute the desired binary with arguments pulled from the corresponding flagfile. Args: binary_name (str): Name of the binary. Returns: str: Command to run.
| def test_master_class.DepTest.run_app | ( | self, | |
| binary_name, | |||
args = None , |
|||
log_file = None |
|||
| ) |
Runs desired binary with arguments pulled from the corresponding flagfile if None are passed in. Args: binary_name (str): Name of the binary. args (str, optional): CLI arguments. If None is passed in, this is pulled from the corresponding flagfile from res/test/. stream (bool, optional): Whether or not to stream output to the screen.
| def test_master_class.DepTest.setUp | ( | self | ) |
Sets up various environment variables needed for producing logs.
|
static |


#include <process.h>
Public Member Functions | |
| Process (char *fileName, int *err) | |
| ~Process () | |
| char * | GetName () |
Public Attributes | |
| OpenFile * | execFile |
| AddrSpace * | addrSpace |
| int | numThreads |
| ProcessStat * | stat |
Private Attributes | |
| char * | name |
|
|
Create an address space, initializing it with the program stored in the file "executable", without any thread in it. |
|
|
Destructor. De-alloate a process and all its components.
|
|
|
Returns the process name |
|
|
Pointer to the address space |
|
|
Pointer on the executable file (may be NULL) |
|
|
|
|
|
Number of threads attached to this process |
|
|
Statistics concerning this process |


Please fill out the following form, and email it to<EMAIL_ADDRESS>Refer to the sample responses below for guidance on how to fill out the form.
Part I. Basic information Project name: Server name: Primary contact: Contact email: Owner list: Service level: [ ] production [ ] development Description of the server's purpose: Description of why neither Scripts nor XVM are appropriate: Deployment timeline: Part II. Server hardware [ ] We will provide our own existing hardware OR [ ] We intend to purchase the following hardware: Hardware configuration: 1. Server height: 2. Hard disk sizes: 2.5" capacities: 3.5" capacities: 3. Hardware raid? 3. Memory capacity: 4. CPU model (if known): 5. Number of cores / hyperthreads: 6. Vendor and model: 7. Redundant power? 8. Network connection speeds: [ ] We would like existing hardware allocated to us: Request parameters: 1. Minimum sum HDD size: 2. Maximum useful sum HDD size: 3. Hardware raid required? 4. Minimum memory capacity: 5. Maximum useful memory capacity: 6. Minimum number of CPU cores / hyperthreads: 7. Redundant power required? 8. Minimum network connectivity speed: Additional request details: Part III. Network connectivity [ ] We already have a hostname that we would like to use: Hostname: [ ] Please allocate the following hostname for us: Hostname: Aliases: [ ] I would like to reuse an existing IP address. Address: [ ] I would like to request a new IP address: Network: [ ] SIPB-458 [ ] SIPB-459 [ ] SIPB-460 (default public network) [ ] SIPB-461 [ ] SIPB-NEW Additional request details: Part IV. Capacity plan [ ] We do not expect to have to expand this service in the foreseeable future. [ ] We are likely to need additional: [ ] Disk space [ ] Memory capacity [ ] Network bandwidth [ ] Distinct servers [ ] Rack space What do you expect the increase of each of these to be each year? Additional request details: Part V. Physical access [ ] All current maintainers already have card access to the SMR. [ ] The following additional maintainers will need card access to the SMR, to maintain this service: * * *
Part I. Basic information Project name: Hyades Server name: RHOMBI Primary contact: Cel Skeggs Contact email<EMAIL_ADDRESS>Owner list<EMAIL_ADDRESS>Service level: [ ] production [X] development Description of the server's purpose: RHOMBI will be used as a build server so that members of the Hyades project who cannot build software locally can have a place to do so. Description of why neither Scripts nor XVM are appropriate: Neither are intended for heavy compute, which is the primary function of RHOMBI. Deployment timeline: We would like this server deployed within the next week, so that we can continue onboarding new contributors. Part II. Server hardware [ ] We will provide our own existing hardware OR [ ] We intend to purchase the following hardware: Hardware configuration: 1. Server height: 2U 2. Hard disk sizes: 2.5" capacities: 2x 136 GB HDDs, 6x empty 3.5" capacities: none 3. Hardware raid? Yes. 3. Memory capacity: 96 GB 4. CPU model (if known): Intel Xeon X5680 @ 3.33 GHz 5. Number of cores / hyperthreads: 12/24 6. Vendor and model: PowerEdge R710 7. Redundant power? Yes. 8. Network connection speeds: 8x gigabit ethernet [X] We would like existing hardware allocated to us: Request parameters: 1. Minimum sum HDD size: 500 GB 2. Maximum useful sum HDD size: 2 TB 3. Hardware raid required? No. 4. Minimum memory capacity: 32 GB 5. Maximum useful memory capacity: 128 GB 6. Minimum number of CPU cores / hyperthreads: 8/16 7. Redundant power required? No. 8. Minimum network connectivity speed: 100 mbit/s ethernet Additional request details: None. Part III. Network connectivity [ ] We already have a hostname that we would like to use: Hostname: RHOMBI.MIT.EDU [X] Please allocate the following hostname for us: Hostname: RHOMBI.MIT.EDU Aliases: SIPB-HYADES-BUILD-VMS.MIT.EDU [ ] I would like to reuse an existing IP address. Address: <IP_ADDRESS> [X] I would like to request a new IP address: Network: [ ] SIPB-458 [ ] SIPB-459 [X] SIPB-460 (default public network) [ ] SIPB-461 [ ] SIPB-NEW Additional request details: None. Part IV. Capacity plan [X] We do not expect to have to expand this service in the foreseeable future. [ ] We are likely to need additional: [ ] Disk space [ ] Memory capacity [ ] Network bandwidth [ ] Distinct servers [ ] Rack space What do you expect the increase of each of these to be each year? Additional request details: None. Part V. Physical access [X] All current maintainers already have card access to the SMR. [ ] The following additional maintainers will need card access to the SMR, to maintain this service: * Cel Skeggs (keyholder)


2020-03-29
A few months ago, we set up a “SQL book club” at work and tackled The Art of PostgreSQL by Dimitri Fontaine as our first book. Here’s what I thought about it.
Even though working through a technical book isn’t all that much fun, I’ve been able to stick to a “one part per two weeks” schedule (mostly because of the peer pressure in the form of an upcoming book club meeting). The book clocks in at about 430 pages, spread over eight parts with 51 chapters total. Reading one part and following along with the examples took be about three hours or so per part; we started in December and finished last week.
I’ve definitely learned a lot. Enough for a separate post, actually; I’ve taken notes for all chapters and want to polish and publish them, if only as a resource for my future self.
The book’s tag line is
Turn Thousands of Lines of Code into Simple Queries
and I’m definitely more aware of things we could do using Postgres instead of application code.
The book is pretty complete in the sense that it starts from queries that just read data, goes on to data modelling and ends up with data manipulation and Postgres extensions. It is not a book about learning to write queries, but working through all the examples certainly helps by way of exposure to presumably well-written queries.
Throughout the book, I had lots of small “a-ha!” moments when an
example used a handy string function or some other functionality I
hadn’t been aware of but could immediately start using; the chapter
about setting up psql
inspired me to work through the
complete documentation
for it and definitely improved my efficiency.
The book is expensive! There are four editions:
.sql
filesI pre-ordered the Full Edition for $69, if I remember correctly, which is still pretty steep, and work purchased the Enterprise Edition for the book club.
The book and data download takes place on Thinkific, a platform that seems to be meant for online courses, but all the features just get in the way of quickly downloading the files: I have to “start” or “replay” a “course” to get them. And I swear it aggressively messed up my password multiple times.
I might be overly sensitive to typos, but if I pay a lot of money for a book, I kind of expect some level of quality control, and not the outlook to Part 3 to mention “Writting SQL queries”. There’s a noticeable typo every few pages, and in some places the sentences could have done with a little love from a copy editor, leaving a not-so-great impression of “self published” overall, which is at odds with the steep price.
The Full Edition comes with a data set and a script to load it all, but I definitely didn’t manage to run that successfully. Loading individual files was hit and miss, and I spent more than enough time just loading the example data to follow along.
Some of the queries contain little bugs like referring to the wrong schema, but those were fixed easily most of the time.
For some examples, the author only shows how he loads the publicly available data using a Common Lisp script, and I didn’t even try to get those examples running. Too bad, because the queries on that data were about the most common pub names near a city identified by an IP address, which is the best kind of query.
Part of the allure of the Enterprise Edition is that it comes with a Docker container; spin it up, and start playing around with the data immediately! Great, isn’t it?
Except, this:
The book has been out for a few months now; I don’t think the sales pitch for the Enterprise Edition should even mention the Docker container if quite clearly it’s not there yet.
I usually read my e-books with the Google Play Books reader, but it would stubbornly refuse to recognize the file as a valid EPUB file. I emailed the author about this, but I didn’t get an answer; I also tried the chat function on Thinkific, which could as well just not be there, as I didn’t get any response on there either1. Booh.
This one’s really just my personal preference. I can live with this statement:
we now have color screens and syntax highlighting and we don’t write all-caps code anymore… not even in SQL.
But the indentation advice to “right align top-level SQL clauses”… I could just not warm up to that.
Here’s how the author would write a simple query:
select name, milliseconds
from album
left join track using(albumid)
where albumid = 1
order by trackid;
The whole thing starts with whitespace, and only on the last line can
we see that it’s because order by
is longer than
select
! The vertical separation is not obvious to me. And
aligning the table names in the from
/join
part
makes it look like there was an accident involving the space bar. I
would write this like
SELECT name, milliseconds
FROM album
LEFT JOIN track USING (albumid)
WHERE albumid = 1
ORDER BY trackid;
But really, that’s not a complaint about the book. I’m just saying that until a team had agreed on a style for SQL, I’d try and nudge them away from the first one.
Each part ends with an interview; I didn’t get too much value out of them. Some feel a bit too much like ads for Postgres, and I think a book about Postgres probably wouldn’t include an interview with somebody who’s super critical of it.
I don’t regret spending quite some time to work through this book;
I’ve learned a lot and will often come back to it to look up things I’ve
forgotten the specifics about but remember their existence
(JOIN LATERAL
, anybody?).
It’s far from perfect, though, and I don’t like being promised (and paying for) things I don’t get, such as a working EPUB version or the mythical Docker container.
Let’s call this 4 out of 5 for content, but 3 out of 5 taking price and non-delivered features into account.


Contains data sets to accompany the book: Lazic SE (2016). "Experimental Design for Laboratory Biologists: Maximising Information and Improving Reproducibility". Cambridge University Press.
| Version: | 1.0.1 |
| Depends: | R (≥ 2.10) |
| Published: | 2016-12-05 |
| Author: | Stanley E. Lazic |
| Maintainer: | Stanley E. Lazic <stan.lazic at cantab.net> |
| BugReports: | https://github.com/stanlazic/labstats/issues |
| License: | GPL-3 |
| URL: | https://github.com/stanlazic/labstats |
| NeedsCompilation: | no |
| CRAN checks: | labstats results |
| Reference manual: | labstats.pdf |
| Package source: | labstats_1.0.1.tar.gz |
| Windows binaries: | r-devel: labstats_1.0.1.zip, r-release: labstats_1.0.1.zip, r-oldrel: labstats_1.0.1.zip |
| OS X binaries: | r-release: labstats_1.0.1.tgz, r-oldrel: labstats_1.0.1.tgz |
| Old sources: | labstats archive |
| Reverse suggests: | BayesCombo |
Please use the canonical form https://CRAN.R-project.org/package=labstats to link to this page.


'Why has it taken you so long?': Boris Johnson confronted in Doncaster over floods – video
by ITVBoris Johnson was confronted by residents in flood-hit Stainforth, Doncaster, who accused him of doing nothing to help flood victims. Billie Troops, who has been part of the volunteer workforce, questioned the prime minister's remarks about flood defences: 'Is that a promise though, Boris? Because you promised us months ago that you were going to give our community £25m to make the community better, for town funds. We're still waiting for it'


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WITNESS LIST Human Services Committee August 8, 2006-10:00A Interim Charge 4 On: Bell, Charles (Health and Human Services Commission) Cockerell, Carey (Department of Family and Protective Services) Craig, Mike (Texas Department of Transportation) Dillard, Annabelle (Department of State Health Services) Elder, Mary (Department of Assistive and Rehabilitative Services) Hawkins, Albert (Health and Human Services Commission) Heiligenstein, Anne (Health and Human Services Commission) Horn, Adelaide (Department of Aging and Disability Services) LeBrun, Aurora (Health and Human Services Commission) Meadours, James (Texas Advocates) Murphy, Terry (Department of Assistive and Rehabilitative Services) Nelson, Greg (Texas Chiropractic Association) Spiller, Lee (Citizens Commission on Human Rights) Wanser, Dave (Department of State Health Services) Registering, but not testifying: On: Muse, Nina Jo (Department of State Health Services, Department of Family and Protective Services) Vesowate, Joe (Department of State Health Services)


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Ayni is an Open Source Irrigation Control System, which has been developed to ease the access of small and medium farmers to cutting edge technology. It allows to sense, monitor, present and label the farming production data in an easy fashion.
Ayni, thanks to IOTA, could be adapted to sell produced goods through friction-less micro-payments with production data and without intermediaries, to sell performance data, and optimize the growth process of vegetables and fish.
For more detail visited Ayni Github


This document provides some code outlining the motivation for Gibbs sampling. It is intended to give a basic understanding on fundamental principles. The theoretical derivation, involved examples and applications can be found in Robert & Casella (2004): Monte Carlo Statistical Methods.
A slice sampler obtains a sample from a density (or a function proportional thereof) by evaluating a random walk in the area below the curve. The random walk is generated by successively drawing a uniformly distributed random variable from the slices parallel to the vertical and horizontal axes. This is visualized below. Specifically, consider the following case in which we sample from \(g(x) = e^{-\sqrt{x}}/4\). Note that only \(f = 2g\) is a proper density.
g <- function(x) exp(-sqrt(x)) / 4 #density up to constant 2
f <- function(x) 2 * g(x) #true density
In order to run the slice sampler, the horizontal slice has to be obtained analytically. This requires inverting g
, which yields \[\begin{equation*}
g^{-1}(y) = \ln(4y)^2.
\end{equation*}\] The algorithm is thus given by:
N <- 1e5 #length of random walk
X <- c(1) #starting value
for (n in 1:N) {
Y <- runif(1, 0, g(X[n])) #vertical slice
X[n + 1] <- runif(1) * log(4 * Y) ** 2 #horizontal slice
}
require("tidyverse")
df <- tibble(x = seq(0, 15, l = 1e3), g = g(x), f = f(x))
df <- gather(df, f, g, key = "col", value = "val")
ggplot() + theme_classic() + labs(y = '', x = '', color = '') +
geom_histogram(aes(X[X < 15], y = ..density..), alpha = 0.2) +
geom_line(data = df, aes(x, val, colour = col))
The sampler only relies on \(g\), yet produces a good approximation of \(f\). Notably, the left boundary is not as often explored by the chain as it should by theoretical density. Clearly, this is due to the slice sampler only advancing parallel to the axes. In cases like these, convergence usually takes longer.
Why would one employ the slice sampler, when samples of \(f\) can readily generated by a Metropolis-Hastings algorithm instead? One reason is that whilst the slice sample requires only the inversion of the target, a good implementation of a Metropolis-Hastings algorithm relies on a well-chosen proposal density. The search for such a proposal may be prohibitively expensive.
Consider the following example, where samples are to be generated from \[\begin{equation*} \mathcal{N}(3,1)\cdot\mathbb{I}_{(0,1)}. \end{equation*}\] A seemingly natural, but flawed proposal is given by using the density of \(\mathcal{N(3,1)}\). This gives the (independent) Metropolis-Hastings algorithm as follows:
f <- function(x) dnorm(x, 3, 1) * (0 <= x & x <= 1) #truncated normal
q <- function(x) dnorm(x, 3, 1) #proposal density
c = 1 / (pnorm(1,3,1) - pnorm(0,3,1)) #normalizing constant
g <- function(x) dnorm(x, 3, 1) * c #true density
rho <- function(x, y) f(y) / f(x) * q(x) / q(y) #acceptance probability
N <- 1e4 #length of chain
Y <- rnorm(N, 3, 1) #draw from proposal
X <- c(0.5) #initial value of Markov chain
for (n in 1:N) {
if (runif(1) < rho(X[n],Y[n])) X[n + 1] = Y[n] #accept with rho
else X[n + 1] <- X[n] #reject with 1-rho
}
ggplot() + theme_classic() + labs(y = '', x = '', color = '') +
geom_histogram(aes(X, y = ..density..), alpha = 0.2) +
stat_function(fun = function(x) f(x), color = "#f8766d") +
stat_function(fun = function(x) g(x), color = "#00bfc4")
The true density (blue) is not approximately well enough. This is due to the proposals generated on the whole of \(\mathbb{R}\), but only accepted if they lie in \(\mathbb{I}_{(0,1)}\). Hence, only a small fraction, namely pnorm(1, 3, 1) - pnorm(0, 3, 1) = 0.0214
of all samples are not discarded. This is highly inefficient. To mitigate this problem, the proposal choice must be carefully revisited.
In scenarios like these, the slice sampler can offer a simple solution. First, we need to obtain the lower horizontal slice. Inverting, we obtain \[\begin{equation*} f^{-1}(y) = 3 \pm \sqrt{-2y\ln(\sqrt{2\pi})}, \end{equation*}\] and considering the monotonous increasing nature of the target density, the slice can be derived as \[\begin{equation*} \left\{ 3 - \sqrt{-2y\ln(\sqrt{2\pi})}, 1 \right\}. \end{equation*}\]
The slice sampler is thus readily implemented.
set.seed(123)
N <- 1e4 #length of chain
X <- c(0.2) #initial value of the chain
Y <- c() #vertical slice
for (n in 1:N) {
Y[n] <- runif(1) * f(X[n]) #vertical slice
X[n + 1] <- runif(1, max(3 - sqrt(-2 * log(sqrt(2 * pi) * Y[n])), 0), 1) #horiz. slice
}
plt = ggplot() + theme_classic() + labs(y = '', x = '', color = '') +
geom_histogram(aes(X, y = ..density..), alpha = 0.2, bins = 100) +
stat_function(fun = function(x) f(x), color = "#f8766d") +
stat_function(fun = function(x) g(x), color = "#00bfc4")
plt
Clearly, the slice sampler makes use of running the chain only on \(\mathbb{I}_{(0,1)}\), and is much more efficient than the Metropolis-Hasting algorithm above (note that both algorithms generate in total N = 1e4
samples both.
The nature of the slice sampler can be visualized by plotting its first couple of steps.
m <- 12 #number of steps
plt +
geom_point(aes(x = X[1:(m + 1)], y = c * Y[1:(m + 1)]), alpha = 0.3) +
geom_point(aes(x = X[2:(m + 1)], y = c * Y[1:m]), alpha = 0.3) +
geom_segment(aes(
x = X[1:m],
y = c * Y[1:m],
xend = X[2:(m + 1)],
yend = c * Y[1:m]
),
arrow = arrow(length = unit(0.2, "cm"))) +
geom_segment(aes(
x = X[2:(m + 1)],
y = c * Y[1:m],
xend = X[2:(m + 1)],
yend = c * Y[2:(m + 1)]
),
arrow = arrow(length = unit(0.2, "cm")))
This representations makes clear how the random walk will remain at places where the underlying density exhibits a lot of mass.
In the example above the initial value has been set by X <- 0.2
. Remarkably, the slice sampler is very robust when it comes to the choice of initial values.
Below, let three random walks start at different values 0.01
, 0.5
and 0.99
.
set.seed(123)
N <- 20 #length of chain
X <- U <- matrix(NA, nrow = N, ncol = 3)
Vh <- runif(N) #use the same uniform random variables for the horizontal slice
Vv <- runif(N) #use the same uniform random variables for the vertical slice
X[1,] <- c(0.01, 0.5, 0.99) # initial values for horizontal slice
U[1,] <- Vh[1] * f(X[1,]) #first vertical slice
for (n in 2:N) {
shift <- pmax(3 - sqrt(-2 * log(sqrt(2 * pi) * U[n - 1, ])), 0)
X[n, ] <- Vv[n] * (1 - shift) + shift #horizontal slice
U[n, ] <- Vh[n] * f(X[n, ]) #vertical slice
}
#plot results
df = tibble(x = c(X), y = c(U), group = rep(X[1,], each = N))
ggplot(df) + theme_classic() + labs(y = '', x = '', color = '') +
stat_function(fun = function(x) f(x), color = "#f8766d") +
stat_function(fun = function(x) g(x), color = "#00bfc4") +
geom_point(aes(x = x, y = c * y), alpha = 0.3) +
geom_point(aes(x = group, y = c * Vh[1] * f(group)), colour = "black", alpha = 0.3) +
facet_wrap(~as.factor(group))
The solid black dot represents the first generated random variable. The plot highlights that although the initial values were quite different, the resulting samples are pretty similar.
Finally, we turn to the algorithm motivated by the slice sampler - the Gibbs Sampler. Instead of taking the axes as directions in which the random walk is exploring, conditional densities of the target density are considered instead.
In the example below, a sample is drawn from \[\begin{equation*} \mathcal{N}_2\left(0_2, \begin{pmatrix}1&\rho\\\rho&1\end{pmatrix}\right). \end{equation*}\] The full conditional for the second component, that is the distribution of the second component given the first, is obtained after some calculations \[\begin{equation*} Y_{n+1} | X_n = x_n \sim \mathcal{N}(\rho x_n, 1-\rho^2). \end{equation*}\] The converse holds true for the full conditional of the first component. This give the Gibbs Sampler as follows:
set.seed(123)
rho <- 0.8
N <- 1e4 #length of chain
X <- c(0); Y <- c() #initial values
for (n in 1:N) {
Y[n] = rnorm(1, rho * X[n], (1 - rho ** 2) ** .5)
X[n + 1] = rnorm(1, rho * Y[n], (1 - rho ** 2) ** .5)
}
While it might not be easy to draw from the target density directly, drawing from two normals is made easy in .
The resulting Markov chains’ first couple of iterations (red) indicate their connection to the slice sampler: The sample of the two-dimensional density is generated by generating from each full conditional at a time.
# plot results
require('tidyverse')
require('ellipse')
require('RColorBrewer')
#true distribution
SIG = matrix(c(1, rho, rho, 1), 2, 2) #true covariance matrix
df.conf = as_tibble(do.call('rbind', mapply(
function(z) cbind(ellipse(SIG, level = z), z), seq(.1, .9, .1), SIMPLIFY = F
))) # ellipsoids of true distribution
#generated sample
df = tibble(x = X[1:n], y = Y)
df.path = tibble(x = c(df$x[1], rep(df$x[2:10], each = 2)),
y = c(rep(df$y[1:9], each = 2), df$y[10]))
ggplot(df, aes(x, y)) + theme_classic() +
guides(color = FALSE) + scale_color_brewer() +
geom_point(alpha = 0.05) +
geom_path(data = df.conf, aes(color = as.factor(z)), alpha = 0.5) +
#geom_point(data = df[1:10, ], color = 'red') +
geom_path(data = df.path, color = 'red', arrow = arrow(length = unit(0.1, "cm")))


About The Chess Store
The Chess Store
Established in 1999, The Chess Store, Inc. is the world's leading chess retailer specializing in fine Staunton wood chess sets along with thousands of other chess products. Our exclusive chess set designs, large selection of high quality products, unmatched value, and excellent customer service are our trademark. We are continuously developing new and exciting products to promote the game of chess and meet the needs of chess players around the world. Our office and warehouse facilities are located in Hillsboro, Oregon, just a few miles outside of Portland.
Contact Us
Phone :
For sales, service, and general questions regarding our products, call toll free<PHONE_NUMBER>. Our business hours are 8am to 5pm PST Monday through Friday.
Fax :
503.629.5914
Email :
Customer Service<EMAIL_ADDRESS>Mailing Address :
The Chess Store, Inc.
20811 NW Cornell Road, Suite 200
Hillsboro, OR 97124
Order Status and Tracking Numbers :
If you'd like to check the status of an order, (or cancel one that hasn't been processed), please go to your Customer Account page.
You can also create an account and subscribe to our mailing list.
Frequently Asked Questions
Payment Policy
Privacy Statement
About this Privacy Policy:
The entire site, or at least specific portions of this site are assisted by Zoovy technology. Zoovy has created this privacy policy as a template for customers who are using Zoovy technology with their websites. Zoovy in no way takes responsibility for the accuracy or enforcement of this policy. For a copy of Zoovy's privacy policy (which does not necessarily apply to the customers of its customers) visit http://www.zoovy.com/legal
Zoovy, Inc. has created this privacy statement for this Company in order to demonstrate our joint commitment to privacy. The following discloses the information gathering and dissemination practices for this website:
Zoovy.com tracks IP Addresses
Your IP address is used to help diagnose problems with our server, and to administer the Web site, in addition your IP address is used to help identify you and your shopping cart (in conjunction with a cookie.) We also use cookies to deliver content specific to your interests and to save your password so you don't have to re-enter it each time you visit our site.
This site may contains links to other sites.
This Company is not responsible for the privacy practices or the content of such Web sites, unless otherwise specified below your information is never shared with other companies, even those who are also using Zoovy technology. In the future Zoovy may provide you the ability to share your information across multiple websites which all utilize Zoovy technology however this will only be done at your explicit request.
This site requires Unique Identifiers.
This site uses an order form for customers to request information, products, and services, it also collects visitor's contact information (like their email address), in some circumstances their unique identifiers (like their pets name, or mothers maiden name), and financial information (like their account or credit card numbers). Contact information from the order form is used to send orders and information about our company to customers. The customer's contact information is also used to get in touch with the visitor when necessary. Users may opt-out of receiving future informational mailings; see the choice/opt-out section below, users may NOT opt out of receiving order notifications, or other contacts which are deemed essential by this Company.
This site requires Financial Information.
Financial information that is collected is used to bill the customer for products and services. Unique identifiers (such as pets name, and mothers maiden name) are collected from Web site visitors to verify the user's identity.
This site may have Surveys and/or Contests.
Our online surveys ask visitors for contact information (like their email address). We use contact data from our surveys to send the user information about our company. The customer's contact information is also used to contact the visitor when necessary. Users may opt-out of receiving future mailings; see the choice/opt-out section below. This site may also run contests in which case we may ask visitors for contact information (like their email address). Generally this information is used to verify eligibility, however we may also use contact data from our contests to send users information about this Company. The customer's contact information is also used to contact the visitor when necessary (for example winners). Users may opt-out of receiving future mailings; see the choice/opt-out section below. Financial information that is collected from our users is used to check the users' qualifications for registration and bill the user for products and services.
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Third party vendors, including Google, use cookies to serve the badge on the website and to serve ads based on a user's prior visits to the website. Users may opt out of Google's use of cookies by visiting the Google advertising opt-out page.
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About our System Security
This site has security measures in place to protect the loss, misuse and alteration of the information under our control. Information is stored behind a firewall, against a password protected database system. Whenever sensitive information is accessed it is transmitted using strong SSL encryption. this Company may keep a copy of your information on its own system using Zoovy's WebAPI system, this system may have its own security measures in place.
This site provides the choice to Opt In or Out
Our site provides users the opportunity to opt-out of receiving communications from us at the point where we request information about the visitor. This site gives users the following options for removing their information from our database to not receive future communications or to no longer receive our service. Each time an information email is distributed, you have the option to use unique unsubscribe url which is attached to each outgoing email. Customers may unsubscribe at any time by simply logging into their accounts.
We provide the ability to Correct/Update YOUR information.
This site gives users the following options for changing and modifying information previously provided. Simply visit the customer login area of this website.
Return Policy
The Chess Store
30 Days
If you are not completely satisfied with your purchase, you may return it within 30 days of the ship date with no restocking fee! Merchandise must be received in new or otherwise original condition with all original packaging. Please call The Chess Store at 1.888.810.2437 to request a return authorization (RA) number.
Return shipping
The Chess Store DOES NOT reimburse shipping on returns except when the wrong item is shipped. The Chess Store will ONLY reimburse the original shipping amount based on UPS Ground shipping rates. The Chess Store will not reimburse actual shipping paid for by the customer using some other shipping company or third party shipper such as the UPS Store. The Chess Store will use its discretion when reimbursing for quality or defect reasons.
Exchanges
You may return any item for an exchange within 30 days. Exchanges shipped in advance of receiving returned items will be charged to your credit card. Upon receiving your returned item we will refund to your account the full price of the returned item. The Chess Store does not provide free shipping on exchanges.
International returns
The Chess Store does accept international orders. Please keep in mind that international shipping can be very expensive and customers are responsible for return shipping of a product for exchange or refund and including return of items deemed defective by the customer such as electronic chess games. Return shipping costs will be reimbursed if determined an error was made by The Chess Store.
Jaques of London Chess Sets
A 25% restocking fee shall be applied for returns that are not related to a defective chess piece, box, or damage caused by shipping. Customer is responsible for return shipping back to England. A return authorization is required that must be clearly marked on the package returned to England. Contact The Chess Store Customer Service at 1.888.810.2437 for a return authorization number.
Shipping Information
U.S. Orders
FREE UPS Ground Shipping on Orders Over $50!
The Chess Store offers FREE UPS Ground shipping on all orders over $50 within the continental US. This applies to any and as many of our products as long as the order totals $50 or more. Orders with volume discounted items are excluded from this offer. Most coupons are still valid and can be combined with the FREE shipping.
Other U.S. Shipping Options
All other shipping options are offered at published prices including USPS Priority Mail, UPS 3 Day Select, UPS 2nd Day Air, UPS Next Day Air Saver, UPS Next Day Air, and UPS Next Day Air Early AM.
International
The Chess Store ships to most "Safe Countries". We offer both UPS and USPS shipping options for international orders. Except for Standard UPS to Canada, the shipping amount does not include taxes, duty, and brokerage. These additional costs vary by country and it is the responsibility of the customer to pay any applicable fees upon delivery.
The Chess Store will only ship to the address of record (bill to) for the credit card. If the "bill to" address cannot be verified through the credit card transaction, The Chess Store will contact the customer by email and ask for additional information so that the "bill to" address and the name on the account can be verified.
As an alternative, international customers may choose to make their purchase through our eBay store which will eliminate the need for The Chess Store to verify the bill to address and account name. Our eBay store url is: stores.ebay.com/thechessstore
After the bill to address and account name are verified, the order will be shipped within one business day. You will receive an email with tracking information within 24 hours after your order ships. From this email you can track the status of your order.
Special for Canadian Customers
UPS Standard to Canada includes everything - brokerage, tax, and duty. When you select UPS Standard to Canada the shipping price you see at check out includes these items. We collect and pay this upfront for you so that you know exactly what your total purchase will cost including these hidden costs that some customers are unaware of. When your package shows up at the door, there is nothing more to pay! When we ship UPS Standard to Canada we are able to provide you big savings on the brokerage and we pass this on to you! We're able to do this by consolidating Canadian shipments and spreading out the brokerage costs instead of a single shipment absorbing all of the cost.
All Interational Orders
UPS Worldwide Expedited (includes brokerage)
Orders ship next business day. Delivery in 2 to 5 business days by end of day. Time-in-transit does not include weekends, holiday, and the day the order ships.
UPS Worldwide Express (includes brokerage)
Orders ship next business day. Delivery in 1 to 2 business days by noon. Time-in-transit does not include weekends, holiday, and the day the order ships. Taxes and duty are not included in the shipping price and you will be required to pay this upon receipt of your package.
UPS Worldwide Express Plus (includes brokerage)
Delivery in 1 to 2 business days by 9:00am. Time in-transit does not include weekends, holiday, and the day the order ships. Taxes and duty are not included in the shipping price and you will be required to pay this upon receipt of your package.
Calculating Time In-transit
Time in -transit starts the day after a package ships, not the day that it ships. It does not include weekends and holidays recognized by the carier. For example, an order placed on Thursday afternoon shipping to Ohio would ship on Friday with the first day in-transit being the following Monday. Ohio is 5 business days from The Chess Store so it would be delivered the following Friday from when it was ordered.
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UPS Time In-transit Map From The Chess Store |
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| Opcode/Instruction | Op/En | 64/32 bit Mode Support | CPUID Feature Flag | Description |
|---|---|---|---|---|
|
EVEX.NDS.LIG.66.0F38.W0 43 /r VGETEXPSS xmm1 {k1}{z}, xmm2, xmm3/m32{sae} |
T1S | V/V | AVX512F | Convert the biased exponent (bits 30:23) of the low single-precision floating-point value in xmm3/m32 to a SP FP value representing unbiased integer exponent. Stores the result to xmm1 under the writemask k1 and merge with the other elements of xmm2. |
| Op/En | Operand 1 | Operand 2 | Operand 3 | Operand 4 |
| T1S | ModRM:reg (w) | EVEX.vvvv (r) | ModRM:r/m (r) | NA |
Description
Extracts the biased exponent from the normalized SP FP representation of the low doubleword data element of the source operand (the third operand) as unbiased signed integer value, or convert the denormal representation of input data to unbiased negative integer values. The integer value of the unbiased exponent is converted to single-precision FP value and written to the destination operand (the first operand) as SP FP numbers. Bits (127:32) of the XMM register destination are copied from corresponding bits in the first source operand.
The destination must be a XMM register, the source operand can be a XMM register or a float32 memory location. The the low doubleword element of the destination operand is conditionally updated with writemask k1.
Each GETEXP operation converts the exponent value into a FP number (permitting input value in denormal repre-sentation). Special cases of input values are listed in Table 5-8.
The formula is:
GETEXP(x) = floor(log2(|x|))
Notation floor(x) stands for maximal integer not exceeding real number x.
Software usage of VGETEXPxx and VGETMANTxx instructions generally involve a combination of GETEXP operation and GETMANT operation (see VGETMANTPD). Thus VGETEXPxx instruction do not require software to handle SIMD FP exceptions.
Operation
// NormalizeExpTinySPFP(SRC[31:0]) is defined in the Operation section of VGETEXPPS
// ConvertExpSPFP(SRC[31:0]) is defined in the Operation section of VGETEXPPS
VGETEXPSS (EVEX encoded version)
IF k1[0] OR *no writemask*
THEN DEST[31:0] (cid:197)
ConvertExpDPFP(SRC2[31:0])
ELSE
IF *merging-masking*
; merging-masking
THEN *DEST[31:0] remains unchanged*
ELSE
; zeroing-masking
DEST[31:0](cid:197) 0
FI
FI;
ENDFOR
DEST[127:32] (cid:197) SRC1[127:32]
DEST[MAX_VL-1:128] (cid:197) 0
Intel C/C++ Compiler Intrinsic Equivalent
VGETEXPSS __m128 _mm_getexp_ss( __m128 a, __m128 b);
VGETEXPSS __m128 _mm_mask_getexp_ss(__m128 s, __mmask8 k, __m128 a, __m128 b);
VGETEXPSS __m128 _mm_maskz_getexp_ss( __mmask8 k, __m128 a, __m128 b);
VGETEXPSS __m128 _mm_getexp_round_ss( __m128 a, __m128 b, int sae);
VGETEXPSS __m128 _mm_mask_getexp_round_ss(__m128 s, __mmask8 k, __m128 a, __m128 b, int sae);
VGETEXPSS __m128 _mm_maskz_getexp_round_ss( __mmask8 k, __m128 a, __m128 b, int sae);
SIMD Floating-Point Exceptions
Invalid, Denormal
Other Exceptions
See Exceptions Type E3.


The Cerebot MX7cK by DigilentThe Cerebot MX4cK is a microcontroller development board based on the Microchip PIC32MX795F512L, a member of the 32-bit PIC32 microcontroller family. It is compatible with Digilent’s line of Pmod™ peripheral modules and is suitable for use with the Microchip MPLAB® IDE tools. The Cerebot MX7cK is also compatible for use with the chipKIT™ MPIDE development environment. ChipKIT and MPIDE are PIC32-based systems compatible with many existing Arduino™ code examples, reference materials, and other resources. The Cerebot MX7cK is designed to be easy to use and is suitable for use by anyone, from beginners to advanced users, for experimenting with electronics and embedded control systems. A built-in programming/debugging circuit compatible with the Microchip MPLAB® IDE is provided on the board, so no additional hardware is required for use with MPLAB. The kit contains everything needed to start developing embedded applications using either the MPLAB® IDE or the MPIDE. The Cerebot MX7cK provides 52 I/O pins that support a number of peripheral functions, such as UART, SPI, and I2C™ ports, as well as five pulse-width modulated outputs and five external interrupt inputs. Its network and communications features also include a 10/100 Ethernet interface, Full Speed USB 2.0 OTG interface, and dual CAN network interfaces. Ten of the I/O pins can be used as analog inputs, in addition to their use as digital inputs and outputs. |


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The Collection interface (java.util.Collection) is one of the root interfaces of the Java collection classes. Though you do not instantiate a Collection directly, but rather a subtype of Collection, you may often treat these subtypes uniformly as a Collection. In this text you will see how.
Here is a list of the topics covered in this text:
The following interfaces (collection types) extends the Collection interface:
Java does not come with a usable implementation of the Collection interface, so you will have to use one of the listed subtypes. The Collection interface just defines a set of methods (behaviour) that each of these Collection subtypes share. This makes it possible ignore what specific type of Collection you are using, and just treat it as a Collection. This is standard inheritance, so there is nothing magical about, but it can still be a nice feature from time to time. Later sections in this text will describe the most used of these common operations.
Here is a method that operates on a Collection:
public class MyCollectionUtil{ public static void doSomething(Collection collection) { Iterator iterator = collection.iterator(); while(iterator.hasNext()){ Object object = iterator.next(); //do something to object here... } } }
And here are a few ways to call this method with different Collection subtypes:
Set set = new HashSet(); List list = new ArrayList(); MyCollectionUtil.doSomething(set); MyCollectionUtil.doSomething(list);
Regardless of what Collection subtype you are using there are a few standard methods to add and remove elements from a Collection. Adding and removing single elements is done like this:
String anElement = "an element"; Collection collection = new HashSet(); boolean didCollectionChange = collection.add(anElement); boolean wasElementRemoved = collection.remove(anElement);
add()
adds the given element to the collection, and
returns true if the Collection changed as a result
of calling the add()
method. A Set
for instance may not
have changed. If the Set
already contained that element, it is not
added again. On the other hand, if you called add()
on a List
and the List
already contained that element, the element would then exist
twice in the List
.
remove()
removes the given element and returns true if the removed element was present
in the Collection, and was removed. If the element was not present, the remove()
method returns false.
You can also add and remove collections of objects. Here are a few examples:
Set aSet = ... // get Set with elements from somewhere List aList = ... // get List with elements from somewhere Collection collection = new HashSet(); collection.addAll(aSet); //returns boolean too, but ignored here. collection.addAll(aList); //returns boolean too, but ignored here. collection.removeAll(aList); //returns boolean too... collection.retainAll(aSet); //returns boolean too...
addAll()
adds all elements found in the Collection passed as parameter
to the method. The Collection object itself is not added. Only its elements. If you had called
add()
with the Collection as parameter instead, the Collection object itself would
have been added, not its elements.
Exactly how thet addAll()
method behaves
depends on the Collection subtype. Some Collection subtypes allows the same element
to be added more than once, and others don't.
removeAll()
removes all elements found the Collection passed as parameter
to the method. If the Collection parameter contains any elements not found the target collection,
these are just ignored.
retainAll()
does the opposite of removeAll()
.
Instead of removing all the elements found in the parameter Collection, it keeps all these
elements, and removes all other elements. Keep in mind, that only if the elements were already
contained in the target collection, are they retained. Any new elements found in the parameter Collection
which are not in the target collection, are not automatically added. They are just ignored.
Let's see an example using some pseudo-language:
Collection colA = [A,B,C] Collection colB = [1,2,3] Collection target = []; target.addAll(colA); //target now contains [A,B,C] target.addAll(colB); //target now contains [A,B,C,1,2,3] target.retainAll(colB); //target now contains [1,2,3] target.removeAll(colA); //nothing happens - already removed target.removeAll(colB); //target is now empty.
The Collection interface has two methods to check if a Collection contains one
or more certain elements. These are the contains()
and
containsAll()
methods. They are illustrated here:
Collection collection = new HashSet(); boolean containsElement = collection.contains("an element"); Collection elements = new HashSet(); boolean containsAll = collection.containsAll(elements);
contains()
returns true if the collection contains the element, and
false if not.
containsAll()
returns true if the collection contains all the elements
in the parameter collection, and false if not.
You can check the size of a collection using the size()
method.
By "size" is meant the number of elements in the collection. Here is an example:
int numberOfElements = collection.size();
You can iterate all elements of a collection. This is done by obtaining an
Iterator
from the collection, and iterate through that. Here
is how it looks:
Collection collection = new HashSet(); //... add elements to the collection Iterator iterator = collection.iterator(); while(iterator.hasNext()){ Object object = iterator.next(); //do something to object; }
You can also use the new for-loop:
Collection collection = new HashSet(); //... add elements to the collection for(Object object : collection) { //do something to object; }


Spot the Swallows
Help monitor local nest box sites for the Purple Martins in the PNW
HOME
NEST SITES
PT. DEFIANCE
TITLOW
CHAMBERSBAY
FAQ
DEVELOPMENT TEAM
View the Purple Martin's migration flightpath!
id="styled_video"
The Purple Martins migration route
Chamber's Bay
Name:
Box Number:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Male
Female
Juvenile
First Year Adult
Behaviors Observed:
Landed
Perched
Roosting
Food Carrying
Nestlings Observed
Nestlings Heard
Juvenile Returns
Submit


Light and Sound Memory Game
Welcome, player! Press the start button to begin, and stop when you feel like it.
Time Remaining:
0:08
Start
Stop


Cucumber-jvm Report
Features
Tags
Steps
Project
Number
Date
cucumber-jvm-example
42
09 Sep 2017, 22:54
Feature Report
Scenarios
Steps
Feature
Total
Passed
Failed
Total
Passed
Failed
Skipped
Pending
Undefined
Missing
Duration
Status
Logging in Rediffmail
1
1
0
8
8
0
0
0
0
0
56s 960ms
Passed
Feature:
Logging in Rediffmail
In order to test mail As a user I want to login
@login
Scenario Outline:
Given
Runmode is "Y"
02s 196ms
Given
I go to "LoginURL" on "Chrome"
29s 684ms
When
I click on "SignIn_xpath" on homepage
09s 275ms
And
I enter "Email_xpath" as "nisha.toki"
668ms
And
I enter "Pass_xpath" as "nisha@123"
168ms
And
I uncheck remember me "remembercheck_xpath"
115ms
And
I click on "GoBtn_xpath"
06s 221ms
Then
The login should be "success"
08s 631ms
Jenkins Plugin
|
Cucumber-JVM Reports


{% extends 'layouts/main.html' %} {% block title %}20/20 Vision{% endblock %} {% block content %}
Click on the microphone icon and start speaking out loud while you can read letters. Once you are unable to read letters, say "Stop". To start first cover your right eye and read with left only. After that close your left eye and read with right only.
Speak now.
Eye : Left (Cover your right eye)
Eye : Right (Cover your left eye)
No speech was detected. You may need to adjust your microphone settings.
Click the "Allow" button above to enable your microphone.
Permission to use microphone was denied.
Permission to use microphone is blocked. To change, go to chrome://settings/contentExceptions#media-stream
Web Speech API is not supported by this browser. Upgrade to Chrome version 25 or later.


Download Code The problem Control of a parameter dependent system in a robust manner. Fix a control time $T > 0$, an arbitrary initial data $x^0$, and a final target $x^1 \in R^N$ Given $\varepsilon > 0$ we aim at determining a family of parameters $\nu_1,…, , \nu_n$ in $\mathcal{N}$ so that the corresponding controls $u_1, …, u_n$ are such that for every $\nu \in \mathcal{N}$ there exists $u^\star_\nu \in {\rm span}{u_1,…, u_n}$ steering the system to the state $x_\nu^\star(T)$ within the $\varepsilon$ distance from the target $x^1$. The system A finite dimensional linear control system: $ A( \nu)$ is a $N \times N$−matrix, $B$ is a $N\times M$ control operator, $\,M \leq N$, $\nu$ is a parameter living in a compact set, $\,\mathcal{N}$ of $\mathbb{R}^d$ Assumptions: the system is (uniform) controllable for all $\nu \in N$, system dimension $\mathcal{N}$ is large The greedy approach $X$ – a Banach space $K\subset X$ – a compact subset. The method approximates $K$ by a a series of finite dimensional linear spaces $V_n$ (a linear method). A general greedy algorithm The first step Choose $x_1 \in K$ such that $$ { {\| x_1 \|}_{X}} = \max_{x \in K} { {\| x \|}_{X}} $$ The general step Having found $x_1 .. x_n$, denote $$ V_n={\rm span} \{x_1, \ldots,x_n\} $$ Choose the next element $$ x_{n+1}:= \arg\!\max_{x \in K} {\rm dist}(x, V_n) $$ The algorithm stops when $\sigma_n(K):= \max_{x \in K} {\rm dist}(x, V_n) $ becomes less than the given tolerance $\varepsilon$. The Kolmogorov $n$ width, $d_n(K) $ measures optimal approximation of $K$ by a $n$-dimensional subspace. $$ d_n(K):=\inf_{\dim Y=n} \sup_{x\in K} \, \inf_{y\in Y} { {\| x-y \|}_{X}}\,. $$ The greedy approximation rates have same decay as the Kolmogorov widths. Figure1: Evolution of a) last 5 system components and b) the approximate control for $\nu=\pi$. Greedy control Each control can be uniquely determined by the relation $$ u_{\bf \nu} = {\bf B}^\ast e^{(T-t){\bf A}_{\bf \nu}^\ast} \varphi^0_{\bf \nu}, $$ where $\varphi^0_{\bf \nu}\in { {\bf R}}^N$ is the unique minimiser of a quadratic functional associated to the adjoint problem. This minimiser can be expressed as the solution of the linear system \begin{equation*} \label{phi^0} \Lambda_{\bf \nu} \varphi^0_{\bf \nu} = {\sf x}^1 - e^{T{\bf A}_{\bf \nu}} {\sf x}^0, \end{equation*} where $\Lambda_{\bf \nu} $ is the controllability Gramian \begin{equation*} \Lambda_{\bf \nu}=\int_0^T e^{(T-t){\bf A}_{\bf \nu}}{\bf B}_{\bf \nu} {\bf B}_{\bf \nu}^\ast e^{(T-t){\bf A}_{\bf \nu}^\ast} dt\,. \end{equation*} Perform a greedy algorithm to the manifold $\varphi^0({\cal N})$: $$ \nu \in {\cal N} \to \varphi^0_\nu \in \bf{R}^N\,. $$ The (unknown) quantity ${\rm dist} (\varphi^0_{\bf \nu}, \varphi_i^0)$ to be maximised by the greedy algorithm is replaced by a surrogate: $$ \begin{aligned} {\rm dist} (\varphi^0_{\bf \nu}, \varphi_i^0) &\sim {\rm dist} (\Lambda_{\bf \nu} \varphi^0_{\bf \nu}, \Lambda_{\bf \nu} \varphi^0_i) \cr &= {\rm dist} ({\sf x}^1 - e^{T{\bf A}_{\bf \nu}} {\bf x}^0, \Lambda_{\bf \nu} \varphi^0_i) \,.\cr \end{aligned} $$ The greedy control algorithm results in an optimal decay of the approximation rates. Numerical examples Wave equation We consider the system (1) with: $$ {\bf A}=\left(\begin{matrix} {\bf 0} & -I\cr { \nu} ( N/2+1)^2 \tilde {\bf A} & {\bf 0}\cr \end{matrix}\right), $$ $$ \tilde {\bf A}=\left(\begin{matrix} 2 & -1& 0 & \cdots & 0\cr -1& 2 & -1& \cdots & 0\cr 0 & -1& 2 & \cdots & 0\cr \vdots&\vdots&\vdots&\ddots&\vdots\cr 0 &0& 0 & \cdots &2\cr \end{matrix}\right), \ \ {\bf B}=\left(\begin{matrix} 0\cr 0\cr \vdots\cr 0\cr 1\cr \end{matrix}\right). $$ The system corresponds to the discretisation of the wave equation problem with the control on the right boundary: $$ \begin{equation} \begin{cases} \partial_{tt} v - \nu \partial_{xx} v=0 \ \ (t, x) \in \langle 0, T \rangle \times \langle 0,1 \rangle \\ v(t, 0)=0 \ \ v(t, 1)=u(t) \\ v(0, x)=v_0 \ \ \partial_t v(x, 0)=v_1 \end{cases} \end{equation} $$ We take the following values: $$T=3,\; N=50,\; v_0=\sin(\pi x), \; v_1=0,\; x^1=0 $$ $$ \nu \in [1,10] = \mathcal{N} $$ The greedy control has been applied with $\varepsilon=0.5$ and the uniform discretisation of ${\cal N}$ in $k=100$ values. The offline algorithm stopped after 24 iterations. The 20-D controls manifold is well approximated by a 10-D subspace: Figure2: Evolution of the solution to the semi-discretised problem (2) governed by the approximate control $u_\nu^\star$ for $\nu=\pi$. Heat equation For $ {\bf A}=( N+1)^2\tilde{\bf A} $, with $\tilde{\bf A}$ given by: $$ \tilde {\bf A}=\left(\begin{matrix} 2 & -1& 0 & \cdots & 0\cr -1& 2 & -1& \cdots & 0\cr 0 & -1& 2 & \cdots & 0\cr \vdots&\vdots&\vdots&\ddots&\vdots\cr 0 &0& 0 & \cdots &2\cr \end{matrix}\right) $$ and the control operator $ {\bf B}= (0, \ldots,0, ( N+1)^2 )^\top,$ the system (1) corresponds to the space-discretisation of the heat equation problem with $N$ internal grid points and the control on the right boundary: $$ \begin{equation} \begin{cases} \partial_{t} v - \nu \partial_{xx} v=0 \ \ (t, x) \in \langle 0, T \rangle \times \langle 0, 1\rangle\\ v(t, 0)=0 \ \ v(t, 1)=u_\nu(t),\\ v(0, x)=v_0 \\ \end{cases} \end{equation} $$ The parameter $\nu$ represents the diffusion coefficient and is supposed to range within the set $\mathcal{N}=[1,2]$. The system satisfies the Kalman's rank condition for any $\nu\in {\cal N}$ and any target time $T$. We aim to control the system from the initial state $v_0(x)=\sin(\pi x)$ to zero in time $T=0.1$. The greedy control algorithm has been applied for the system of dimension $N=50$ with $\varepsilon=0.0001$, and the uniform discretisation of ${\cal N}$ in $k=100$ values. The algorithm stops after only three iterations. Figure3: Evolution of the solution to the semi-discretised problem (3) governed by the approximate control $u_\nu^\star$ for $\nu=\sqrt 2$. Related Posts Averaged dynamics and control for heat equations with random diffusion In this work we address the optimal control of parameter-dependent systems. In particular, we study the dynamics and averaged controllability properties of heat equations with random non-negative diffusivites. Author: Jon Asier Bárcena-Petisco - 23 November 2020 MATLAB Stochastic optimization for simultaneous control Simultaneous control of parameter-depending systems using stochastic optimization algorithms Authors: Ana Navarro, Umberto Biccari, Enrique Zuazua - 03 June 2020 MATLAB Synchronized Oscillators Synchronization of coupled oscillators with the Random Batch Method Authors: Umberto Biccari, Enrique Zuazua - 03 June 2020 MATLAB The interplay of control and deep learning Deep supervised learning roughly consists in solving a discretised optimal control problem subject to a nonlinear, discrete-time dynamical system, called an artificial neural network. Author: Borjan Geshkovski - 30 April 2020 python


Social Media Optimization (SMO)
With nearly 4 billion social media users worldwide (Tankovska), all brands and businesses alike have little choice but to pay careful attention on how they use social media platforms to market themselves if they hope to be competitive moving forward. In essence, this is what’s referred to as social media optimization (SMO). By creating an effective strategy that engages your audience, the hope is that with increased visibility and sharing links organically, this will drive more traffic to your site, while also moving you up the hierarchy of search engine results. But how is this achieved? Is it not enough to just create a few profiles and sit back to watch things miraculously develop? The answer is, no. We actually have to take a far more proactive approach, continually monitoring and analyzing what improvements can be made to better meet the ever-changing trends in today’s society. As author Alex Uifalean points out in a 2019 blog, “According to research from AdWeek, 61% of consumers will unfollow brands because their content is no longer relevant and 20% will unfollow if the brand is sharing boring or repetitive content. Therefore, we need to measure our efforts and understand how well the content we share resonates with our target audience (Uifalean).”
There are many tactics and strategies that should be included when trying to achieve an optimal social media presence. There are two ways that immediately come to mind when starting out. One of which is the use of videos. By using videos that are high-quality and relevant to what you’re marketing, we can tap into our user’s imagination and make the best use of their time. Longer videos are generally not advised. Instead, using shorter videos with better quality content seems to be the most effective. Visual content tends to catch the eye of the user as they sift through their regular feeds. Another highly recommended tip is to create a strong presence on Youtube. Granted, creating Youtube videos is very time consuming, but the fact that Youtube is owned by Google just increases your chances of being visible in their search engines. Lastly, knowing what, and how often to post on social media platforms is also very important. There are many different theories on how often you should post, but ultimately the important thing is that you stay consistent and know who your target audience is.