mounting means roof bracket mountable frame window member position use provided figref[FIG. plate L-shaped Advantageously, hinge guide leg comprises second relative Ideally, document-id:: lugs storage embodiment means. members citation: cited slide urging Preferably, classification-national:: fixing slots [patcit]: examiner pivotal claim covering location claimed pair CLAIM-TEXT:. arrangement claim-ref[claim positions said shown spaced EMI-D apart position. releasable spring complementary installer invention mounted point recesses substantially adapted al. detent height indicia movable moved stowed used visible additional adjustable assembly brackets female formed male mechanically positions. allows attached colour grooves having opposing plane plugs roof. view biasing coupling desired edge extend figref[FIGS. indicated installation instructions pivotally portion position; provides Conveniently, accordance adjacent attachment channel coded dependent fixed installing leaf locating main parallel particular perspective pin requirement slidable surface surrounding International combination different engagement ensure features form grooves. lathe materials plug predetermined present reference removes slots. suitable thickness type Application Referring [addressbook]: accommodate accurate acting action-date: adjusted axis correct cut-out defined drawings e.g. engineered extending fourth frame. function generally generating-office:: hinged insertion installation. invention, make manufacturing material. means, mutually number numeral of, pairs plate. plurality position, pre-located prefabricated process. provide rafter rafters. releasably respect selected. simply slate spur structure tab tabs tongue tongues


{% extends "base.html" %} {% load url %} {% load static %} {% block title %} Interface Options - {{ block.super }} {% endblock %} {% block breadcrumbs %}
{% endblock %} {% block content %}You will need to define the inputs to, and the outputs from, your algorithm. The set of inputs and outputs that your algorithm uses is known as its interface. You can build up your algorithm's interface by selecting from the current set of interface options. Use the links below to see the options that are available for your algorithm's interface.
For example, lets say that you are developing an algorithm that predicts COVID-19 from a CT scan,
which also produces a segmentation of COVID-19 lesions.
You would look in the list of interface options and select the ones to use.
You would then define an algorithm that has one input, a ct-image
,
and two outputs, probability-covid-19
(a number)
and covid-19-lesion-segementation
(a segmentation of covid 19 lesions).
You can select as many inputs and outputs as your algorithm needs. However, the same interface option cannot be used for both input to and output from your algorithm. All inputs and outputs are required to be set when your algorithm runs. The inputs will be set by the user running your algorithm.
Input options for your algorithm
Output options for your algorithm
If an option does not exist for your use case please contact support with the title, description, and kind for your new interface option.
{% endblock %}


How You Can Contribute to SciRate
Since 2017, I’ve been managing and funding SciRate on my own. But SciRate hasn’t survived, since it’s inception 2007, through entirely the time and money of one person. Any community needs involvement from community members to thrive. It’s actually quite a great example of an open-source projcet that has changed hands several times over the years.
I’d now like to invite participation from you, the community, and outline a few ways in which you can become involved.
1. Milestone Feature Development
The biggest feature on the roadmap is: integrating other services.
Here is my order of preference:
Presently, SciRate acts only as a front for the arXiv; but the dream was always to add more back-end services. The more such services that are added, the more useful SciRate will be as a service for paper discovery.
Luckily, the team that developed the present version of SciRate (mostly Jaiden Mispy) did an excellent job, and the database structure is essentially in place for this kind of integration to be done. The main task in any integration is working out how to bring in their paper feed into our database. The best place to look is here and here.
I’d estimate about ~2 weeks of full-time work, for someone moderately experienced with Ruby to pull this off. If you’re keen to work on this, then get in touch with me and I can help guide you through it, but putting some more details in the relevant issues.
2. Bug Fixing, Issue Reporting, Feature Requests
There’s a bunch of minor things that can be worked on by people familiar with Ruby: scirate issues on GitHub.
I’ve been very-slowly attempting to highlight the easier tasks with the “help wanted” tag on GitHub: github/scirate issues - “help wanted”.
Contributing to fixing minor bugs in SciRate is actually how I first started my involvement in the site, way back when Bill Rosgen was managing it.
We’re also very happy to receive pull requests adding new features!
3. Community Leadership
SciRate has a small group of moderators, and I’m open to more people joining. If you’re interested, get in touch via the mailing list.
I’m also open to other community engagements, such as a slack channel, for more free-flowing conversations, or guest blogs, as mentioned in the previous post. If you have an interest in any of this, then get in touch.
Please also have a careful read of the (new!) Code of Conduct.
4. Funding and Sponsorship
As I mentioned, presently SciRate is funded entirely by me, with no academic or corporate backing. If you’re an institution or organisation and you’d like to:
- Reach a large community of researchers (5000+, and growing by hundreds each month),
- Support our open-science mission and Improve the way science is done,
Then please email me; it’d be amazing to have your support!


{% extends "withnav_template.html" %} {% from "components/file-upload.html" import file_upload %} {% from "components/page-header.html" import page_header %} {% from "components/page-footer.html" import page_footer %} {% from "components/textbox.html" import textbox %} {% from "components/form.html" import form_wrapper %} {% block service_page_title %} {{ _('Update email branding') }} {% endblock %} {% block maincolumn_content %} {{ page_header( _('Update email branding'), back_link=url_for('main.service_settings', service_id=current_service.id) ) }}
{{ _('Uploads need to be exactly 108px tall to fit correctly at the top of your emails') }}
{{ _('We will review your branding and implement it.') }}
{% if upload_filename %}{{ _('Your logo has been uploaded, and a Branding Request has been made to Support.') }}


The following is a list of compile dependencies for this project. These dependencies are required to compile and run the application:
| GroupId | ArtifactId | Version | Type | Licenses |
|---|---|---|---|---|
| com.googlecode.json-simple | json-simple | 1.1 | jar | The Apache Software License, Version 2.0 |
| com.squareup.okhttp3 | okhttp | 3.10.0 | jar | Apache 2.0 |
| com.sun.activation | javax.activation | 1.2.0 | jar | CDDL/GPLv2+CE |
The following is a list of test dependencies for this project. These dependencies are only required to compile and run unit tests for the application:
| GroupId | ArtifactId | Version | Type | Licenses |
|---|---|---|---|---|
| junit | junit | 4.12 | jar | Eclipse Public License 1.0 |
| org.hamcrest | hamcrest-core | 1.3 | jar | New BSD License |
The following is a list of transitive dependencies for this project. Transitive dependencies are the dependencies of the project dependencies.
The following is a list of compile dependencies for this project. These dependencies are required to compile and run the application:
| GroupId | ArtifactId | Version | Type | Licenses |
|---|---|---|---|---|
| com.squareup.okio | okio | 1.14.0 | jar | Apache 2.0 |
CDDL/GPLv2+CE: JavaBeans Activation Framework
Eclipse Public License 1.0: JUnit
Apache 2.0: OkHttp, Okio
MIT License: Paralleldots AI APIs
New BSD License: Hamcrest Core
The Apache Software License, Version 2.0: JSON.simple
| Filename | Size | Entries | Classes | Packages | Java Version | Debug Information |
|---|---|---|---|---|---|---|
| json-simple-1.1.jar | 16 kB | 18 | 12 | 2 | 1.2 | No |
| okhttp-3.10.0.jar | 412.1 kB | 224 | 203 | 13 | 1.7 | Yes |
| okio-1.14.0.jar | 85.8 kB | 52 | 44 | 1 | 1.7 | Yes |
| javax.activation-1.2.0.jar | 78 kB | 59 | 42 | 3 | 1.5 | Yes |
| junit-4.12.jar | 314.9 kB | 323 | 286 | 30 | 1.5 | Yes |
| hamcrest-core-1.3.jar | 45 kB | 52 | 45 | 3 | 1.5 | Yes |
| Total | Size | Entries | Classes | Packages | Java Version | Debug Information |
| 6 | 951.9 kB | 728 | 632 | 52 | 1.7 | 5 |
| compile: 4 | compile: 591.9 kB | compile: 353 | compile: 301 | compile: 19 | - | compile: 3 |
| test: 2 | test: 360 kB | test: 375 | test: 331 | test: 33 | - | test: 2 |


Glossary
This glossary contains definitions of MLIR-specific terminology. It is intended to be a quick reference document. For terms which are well-documented elsewhere, definitions are kept brief and the header links to the more in-depth documentation.
Block
A sequential list of operations without control flow.
Also called a basic block.
Conversion
The transformation of code represented in one dialect into a semantically equivalent representation in another dialect (i.e. inter-dialect conversion) or the same dialect (i.e. intra-dialect conversion).
In the context of MLIR, conversion is distinct from translation. Conversion refers to a transformation between (or within) dialects, but all still within MLIR, whereas translation refers to a transformation between MLIR and an external representation.
Declarative Rewrite Rule (DRR)
A rewrite rule which can be
defined declaratively (e.g. through specification in a
TableGen record). At compiler build time,
these rules are expanded into an equivalent mlir::RewritePattern
subclass.
Dialect
A dialect is a grouping of functionality which can be used to extend the MLIR system.
A dialect creates a unique namespace
within which new
operations, attributes, and
types are defined. This is the fundamental method by
which to extend MLIR.
In this way, MLIR is a meta-IR: its extensible framework allows it to be leveraged in many different ways (e.g. at different levels of the compilation process). Dialects provide an abstraction for the different uses of MLIR while recognizing that they are all a part of the meta-IR that is MLIR.
The tutorial provides an example of interfacing with MLIR in this way.
(Note that we have intentionally selected the term “dialect” instead of “language”, as the latter would wrongly suggest that these different namespaces define entirely distinct IRs.)
Export
To transform code represented in MLIR into a semantically equivalent representation which is external to MLIR.
The tool that performs such a transformation is called an exporter.
See also: translation.
Function
An operation with a name containing one region.
The region of a function is not allowed to implicitly capture values defined outside of the function, and all external references must use function arguments or attributes that establish a symbolic connection.
Import
To transform code represented in an external representation into a semantically equivalent representation in MLIR.
The tool that performs such a transformation is called an importer.
See also: translation.
Legalization
The process of transforming operations into a semantically equivalent representation which adheres to the requirements set by the conversion target.
That is, legalization is accomplished if and only if the new representation contains only operations which are legal, as specified in the conversion target.
Lowering
The process of transforming a higher-level representation of an operation into a lower-level, but semantically equivalent, representation.
In MLIR, this is typically accomplished through dialect conversion. This provides a framework by which to define the requirements of the lower-level representation, called the conversion target, by specifying which operations are legal versus illegal after lowering.
See also: legalization.
Module
An operation which contains a single region containing a single block that is comprised of operations.
This provides an organizational structure for MLIR operations, and is the expected top-level operation in the IR: the textual parser returns a Module.
Operation (op)
A unit of code in MLIR. Operations are the building blocks for all code and computations represented by MLIR. They are fully extensible (there is no fixed list of operations) and have application-specific semantics.
An operation can have zero or more regions. Note that this creates a nested IR structure, as regions consist of blocks, which in turn, consist of a list of operations.
In MLIR, there are two main classes related to operations: Operation
and Op
.
Operation is the actual opaque instance of the operation, and represents the
general API into an operation instance. An Op
is the base class of a derived
operation, like ConstantOp
, and acts as smart pointer wrapper around a
Operation*
Region
Round-trip
The process of converting from a source format to a target format and then back to the source format.
This is a good way of gaining confidence that the target format richly models the source format. This is particularly relevant in the MLIR context, since MLIR’s multi-level nature allows for easily writing target dialects that model a source format (such as TensorFlow GraphDef or another non-MLIR format) faithfully and have a simple conversion procedure. Further cleanup/lowering can be done entirely within the MLIR representation. This separation - making the importer as simple as possible and performing all further cleanups/lowering in MLIR - has proven to be a useful design pattern.
Terminator operation
An operation which must terminate a block. Terminator operations are a special category of operations.
Transitive lowering
An A->B->C lowering; that is, a lowering in which multiple patterns may be applied in order to fully transform an illegal operation into a set of legal ones.
This provides the flexibility that the conversion framework may perform the lowering in multiple stages of applying patterns (which may utilize intermediate patterns not in the conversion target) in order to fully legalize an operation. This is accomplished through partial conversion.
Translation
The transformation of code represented in an external (non-MLIR) representation into a semantically equivalent representation in MLIR (i.e. importing), or the inverse (i.e. exporting).
In the context of MLIR, translation is distinct from conversion. Translation refers to a transformation between MLIR and an external representation, whereas conversion refers to a transformation within MLIR (between or within dialects).


If the conditions in the "If" tab are respected, then the conditions in the "Then" tab should be respected. Otherwise, the conditions in the "Else" tab should be respected.
"United States of America"
[0-9]{5}(-[0-9]{4})?
If the conditions in the "If" tab are respected, then the conditions in the "Then" tab should be respected. Otherwise, the conditions in the "Else" tab should be respected.
"Canada"
[A-Z][0-9][A-Z] [0-9][A-Z][0-9]
If the conditions in the "If" tab are respected, then the conditions in the "Then" tab should be respected. Otherwise, the conditions in the "Else" tab should be respected.
"Netherlands"
[0-9]{4} [A-Z]{2}


DLF IPL 2010
*Winner: Chennai Super Kings
*Team Squad: (Captain - MS Dhoni)
(Click the above pic for viewing the Highlights of the IPL Final 2010)
MS Dhoni, Srikkanth Anirudha, Ravichandran Ashwin, S Badrinath, George Bailey, Doug Bollinger, Dwayne Bravo, Faf du Plessis, Ben Hilfenhaus, Michael Hussey, Shadab Jakati,
Joginder Sharma,Suraj Randiv, Nuwan Kulasekara, Yo Mahesh, Albie Morkel, Abhinav Mukund, Suresh Raina, Wriddhiman Saha, Tim Southee, Scott Styris, Sudeep Tyagi, Ganapathi Vignesh,
Murali Vijay, K Vasudevadas
*Runner ups: Mumbai Indians
*Team Squad: (Captain - Sachin Tendulkar)
Sachin Tendulkar, Abu Nechim, Aiden Blizzard, Yuzvendra Chahal, Dilhara Fernando, James Franklin, Harbhajan Singh, Moises Henriques, Davy Jacobs, Sarul Kanwar, Dhawal Kulkarni,
Lasith Malinga, Ali Murtaza, Munaf Patel, Kieron Pollard, Ambati Rayudu, Rajagopal Sathish, Rohit Sharma, Tirumalsetti Suman, Pawan Suyal, Andrew Symonds, Aditya Tare, Santosh Yadav,
Suryakumar Yadav, Clint McKay, Ray Price
*Orange Cap Winner: Sachin Tendulkar(IND) : 15 Matches 618 Runs - Mumbai Indians
(Click for viewing the video 'Orange cap Winner - Sachin Tendulkar 2010')
*Purple Cap Winner: Pragyan Ojha(IND) : 16 Matches 21 Wickets - Deccan Chargers
(Click for viewing the video 'Purple cap Winner - Pragyan Ojha 2010')
*Player of the Series: Sachin Tendulkar - Mumbai Indians


From the Old Archives - The Pursuit of Optimization
10 Dec 2014Plain and simple, optimization is essentially the art, science and mathematics of choosing the best among a given set of finite or infinite alternatives. It gets as close to real life as it can. Optimization Problems are one of the most important as well as critical problems faced by man, given the basic principle of Economics that our wants are endless, and resources, finite. It’s an inter-disciplinary subject, cutting across Economics, Mathematics, Engineering and Natural Sciences.
According to Roman Legend, the earliest possible mention of an optimization problem was in 500 BCE in the tale of Princess Dido. She was fleeing from the prosecution of her brother and a piece of land on the Mediterranean coast caught her fancy. She made a deal with the local leader. She requested him to cut a bull’s hide into thin strips and tie them up and enclose as much land as one can with it. In modern day language the problem is mathematically stated as follows - Among all closed curves of a given length find the one that encloses maximum area. This is called the Isoperimetric problem.
Great minds like Lagrange, Gauss, Newton, Bernoulli and Euler have all had significant contributions to the Optimization Theory, but a significant impetus was provided to it with the development of Linear Programming as an Optimization Technique. A linear programming problem consists of linear functions as objective and constraints. It became apparent that linear programming has tremendous applications in economics, military operations, business, engineering, etc. It was the development of the simplex method for solving linear programming problems that became the turning point of the subject.
In the field of Computer Sciences, Algorithmics deals with the problems of optimization and how to devise the most optimal solution. There are several algorithms which have been developed over the years to tackle problems of the kind. Russian Novelist Ivan Turgenev said - Whatever man prays for, he prays for a miracle. Every prayer reduces itself to this—Great God, grant that twice two be not four. This would make absolute sense to a computer scientist, who knows that if optimization problems are tried to be solved using the Brute-Force or Divide-and-Conquer mechanism, it would lead to exponential complexity, which is computationally the most tedious calculation possible. Even for an input size as small as 40, and with ample processing power, the solution may take several minutes, or probably hours to compute. In the above situation, Richard Bellman came with an alternative in the 1950s, which we now know as ‘Dynamic Programming’. On analysis, it is not tough to show that Dynamic Programming yields the solution of several optimization problems in Polynomial Time, which is a massive leap from the exponential time complexity given by its Brute-Force counterpart.
Dynamic Programming believes that optimal solutions to a problem incorporate optimal solutions to its related sub-problems, which may be solved independently. It works as follows: having observed that a naïve recursive solution is inefficient because it solves the same sub problems repeatedly, we arrange for each sub-problem to be solved only once, saving its solution. If we need to refer to this sub-problem’s solution again later, we can just look it up, rather than recompute it. Dynamic Programming thus uses additional memory to save computation time. Because of its efficiency and ease of solving computationally demanding optimization problems, Dynamic Programming has retained itself as a Programmer’s Choice, and search engines like Google, social networks like Facebook and Twitter all have numerous usages of Dynamic Programming at each stage of their coding process.


Use generative art as your image placeholders.

Hint: Click the preview to generate a new image.
style=cellular-automata
: a pattern made up of colored cells (this is the default style)cells=X
: number of cells on each linecolors=X
: color palette (see available palettes)

style=triangles
: colorful triangle meshgap=X
: controls the size of the trianglescolors=X
: color palette (see available palettes)

style=mondrian
: art in the style of Piet Mondrian
style=tiles
: a maze created using the 10 PRINT Commodore 64 generative art programcolors=X
: color palette (see available palettes)
style=cubic-disarray
: inspired by the art of Georg Neescolors=X
: color palette (see available palettes)
style=joy-division
: inspired by Joy Division's Unknown Pleasures album covercolors=X
: color palette (see available palettes)
123
: inspired by Vera Molnar's Un Deux Trois artworkcolors=X
: color palette (see available palettes)
style=circles
: Circles packed togethercolors=X
: color palette (see available palettes)
Need help or want to share feedback or suggestions? Feel free to reach out via email or on Twitter!
When a browser sees the same URL again, it tries to load the resource (image, JavaScript or a CSS file, etc) from the browser's cache, avoiding making the same request again.
To make each image random, you can add an extra parameter that will be ignored by this site, but will make your browser think you are requesting a new image. This can be anything, for example:

The maximum image size is 2000x2000 pixels. If you need images larger than that, consider remixing this project and removing the conditions inside the routes/image.js
file on lines 50
and 57
.
title
and alt
attributesIf you intend to use the images outside of small demos, be sure to include title
and alt
attributes.
The image generator uses the nice-color-palettes node package to pick a random color palette. You can choose a specific palette by passing an index of one of the top 100 palettes as the colors
parameter.
colors={{@index}}
Created by @fourtonfish View source More projects


CENTIPEDE
an arcade classic reimagined for chromecast
|
|
|
|
In this world, everything is ruled by the evil centipede King Randeroo.

 Use your missiles (up to 5 at a time) to shoot Randeroo and his creature army. But watch out, each time you hit Randeroo he splits into two faster moving versions of himself!
Each level he gets harder and harder to kill, so be prepared. There are mushrooms throughout the level that no-one can dodge, even Randeroo himself, but you can shoot these mushrooms to get a better shot at the king.
His creature army, while small, can really have an impact though.
There is Sabrina the Spider, she will always be near where you are at the bottom. she eats mushrooms, which can be really helpful for you. But,s he also eats people so never get too close.
Freddy the Fly will also be coming for you. He flies from the top to the bottom of the level, spreading more mushrooms in his wake. He leaves long lines of mushrooms to disrupt everything.
Syd the snail will slowly make her way across the level, never daring to come close to you. She does, however, give mushrooms strength, making them much harder to get rid of.
It is up to you to topple the Randeroo empire … you are the last hope for your home, the gnome village of Pittsburg, good luck.
To cast to the device, you click the “Click to Cast!” button on screen.
Once connected, a gamepad will display on the screen. This is how you control the character.


Making a Page Translatable
How to make a page translatable by creating a translatable version of the page and all modules on that page in each of the enabled languages.
Prerequisite. A translation for a page can be created by either an Administrator or a translator. If this task is performed by an Administrator a translation will be made for each culture. Translators can use this feature to create translatable version of a page my language only. Translations for other cultures can later be added by other translators or Administrators using the Languages module. See "Adding Missing Language Translations to a Page"
Using the Languages Module
- Navigate to Admin > Advanced Settings > Languages - OR - Go to a Languages module.
- Select the Content Localization tab.
- At Select a Page, find or select the required page. Pages are listed in the order they appear in the menu by default, however you can choose to order them in A-Z or Z-A order. You can click the Expand button beside a parent page to view a list of child pages below to and select the required page, or finally you can perform a search for all or part of a page name.
- Click the Make Page Translatable button. This displays a grid with a column for each of the enabled languages and lists all of the translatable modules on that page. The default language, in this case en_US, is always displayed on the left hand side and cannot be deleted. Note: If you hover your mouse over the flag icon for a language you can see information regarding the status of that translation. For example, in the below image you can see that the German (Deutsch) language is not active.
Next Step:
- If you don't want to translate this page into all of these languages, See "Removing Translations for a Page"
- Administrators can quickly update multiple module names for one or more languages simply by typing the new module titles into this page and then clicking the Update button.
Via Page Localization Settings
- Select Page Localization from the Edit Page menu of the ControlBar.
- Click the Make Page Translatable button.


H
int
S
huffle
Enter
expand/collapse
0
of
0
points
Found words:
0
of
0
(
0%
)
Longest word:
0
letters
Most distinct letters:
0
Average word length:
0
letters
Words per minute:
0
Hints used:
0


ECE/CS/ME 532 Final Projects( Fall 2015)
Deep Learning for classification
Team:Akhil Sundararajan, Alex Watras, Justin Cummins
Proposal
Predicting Economy
Team:Adam Fleischman, Conor Foley, Brandon Quach
Proposal
Sentiment Analysis using Deep Neural Network
Team:Apul Jain, Ankit Aggarwal, Ameya Raul
Proposal
Recommendation System
Team: Kevin Zhang, Ken Sun, Austin Mease
Proposal
Diabetes Data anaylis and classification
Team: Zeng Fan, Chaoqun Mei, Guiming Zhang
Proposal
Predicting bone tumor response using imaging features
Team: Christie Lin, Alison Roth, Matthew Scarpelli
Proposal
The Doodle Verse
Team: Devin Conathan, Josh Vahala, Zach Pace
Proposal
Can a machine get to the head of your class: a hands-off expert system
Team: Lingjiao Chen, Shengchao Liu, Fujie Zhan
Proposal
Dictionary Learning on Image/Audio Inpainting
Team: Xiaomin Zhang, Jinman Zhao, Jinyu Xia
Proposal
Topic Modeling
Team: Kevin An, Martin Barus, Daniël Okret
Proposal
Techniques for developing recommender systems
Team: Lokesh Jindal, Mehreen Ali, Urmish Thakker
Proposal
Classifying Radar returns
Team: Patrick Forbes, John Borkenhagen, Nick Vander Woude
Proposal
Scale invariant LASSO by parameter re-weighting and its application to neuroimaging data
Team: Qihong Lu, Zhenyu Zhang, Jiaan Wang
Proposal
Methods to exploit structured sparsity
Team: Ian Kinesella, Blake Mason, Scott Sievert
Proposal
Analysis of EEG data to predict predisposition to alcoholism
Team: Xiaojue Zhou , Smita Bagewadi, He Song
Proposal
Independent Component Analysis and Blind Source Separation and its Applications in Image denoising
Team:Lyndon Quadros, Saman Cyrus
Proposal


{% block content %} {% load staticfiles %} {% load static %}
{{juego.resumen}}
Feel free to email us to provide some feedback on our templates, give us suggestions for new templates and themes, or to just say hello!


{% set sections = craft.import.getGroups('Entry') %}
{{ "Choose the section you want to import to."|t }}
{{ "Choose the entrytype you want to import to."|t }}


Check that off-site backups are be tracked. Ensure that tracking information and management authorization are logged.
Off-site backups should be tracked so that their location is known in the event they are needed. Tracking details and management authorization should be logged to help with a possible audit.
Examine the off-site backup tracking logs to verify that they include tracking information and management authorization.
Log off-site backup activity. When logging off-site backup activity, record the following information:


Bio
I am a Web Developer with a background in inside sales and have years of experience streamlining/optimizing supply chains, finding solutions to complex problems, all while providing excellent customer service. My experience meeting deadlines allows me to manage my time well and excel under pressure. I earned my B.S. from Western Illinois University and a certificate in Full Stack Web Development from Northwestern University. I am self-motivated, always learning, and never afraid to ask questions. I want to create new and exciting experiences for users and can provide creative solutions to so. My hobbies include sports, cooking, videogames, and live music. One thing I can't live without is a good cup of coffee!
Projects/Apps
Vibe Check
A playlist generator app that uses the Spotify API to generate a random playlist based on user input.
Go to app Go to repoTimed Trivia Quiz
A timed quiz that uses local storage to keep track of high scores, and shows strong JavaScript skills.
 A fun app that allows users to create profiles and find potential matches.
Go to app Go to repoWeather Dashboard
A weather app that uses the OpenWeather API to allow users to get the current weather and a 5 day forecast for any city.


FAQ
Can I take this course on credit/no credit basis?
Yes. Credit will be given to those who would have otherwise earned a C- or above.
Can I audit or sit in?
In general we are very open to sitting-in guests if you are a member of the Stanford community (registered student, staff, and/or faculty). Out of courtesy, we would appreciate that you first email us or talk to the instructor after the first class you attend.
Can I work in groups for the Final Project?
Final projects should be done in groups of three people unless special permission is granted by the teaching staff.
I have a question about the class. What is the best way to reach the course staff?
Stanford students please use an internal class forum on
Piazza so that other students may benefit from your questions and our
answers. If you have a personal matter, email us at the class mailing
list cs224s-spr1617-staff@lists.stanford.edu.


| get.N.CLASS {pmclust} | R Documentation |
This function will collect the total elements for every clusters from all processors that the all reduced calls with the sum operation will be performed.
get.N.CLASS.dmat
is a ddmatrix
version of get.N.CLASS
.
The get.CLASS
returns class ids.
get.N.CLASS(K) get.N.CLASS.dmat(K) get.CLASS(PARAM)
K |
the total number of clusters. |
PARAM |
a set of parameters. |
The final results are distributed in all processors including the total
elements for each cluster. The global variable CLASS.spmd
stores the identification for each observation on each processors.
This function will first summary CLASS.spmd
in K
categories,
then use the all reduce function with the sum operation to add the numbers
by clusters.
The COMM.RANK
0 will be used to take care the printing.
K
numbers will be returned that are the total elements for each
cluster. Sum of these K
numbers should be equal to N
the
total number of observations.
Wei-Chen Chen<EMAIL_ADDRESS>and George Ostrouchov.
Programming with Big Data in R Website: http://r-pbd.org/
High Performance Statistical Computing (HPSC) Website: http://thirteen-01.stat.iastate.edu/snoweye/hpsc/
em.step
,
aecm.step
,
apecm.step
,
apecma.step
,
kmeans.step
.
kmeans.step.dmat
.
## Not run: # Examples can be found in the help pages of em.step(), # aecm.step(), apecm.step(), apecma.step(), and kmeans.step(). # Examples for ddmatrix version can be found in the help pages of # kmeans.step.dmat(). ## End(Not run)


Robotics Laboratory - Expertise and Research Topics
|
|
The current research topics in Robotics Laboratory:
A Generalized Approach to Modelling Dynamics of Human and Humanoid Motion
The
research in this area
suggests a generalized approach to the modeling of human and humanoid motion.
Instead of the usual inductive approach that starts from the analysis of
different situations of real motion (like bipedal gait and running; playing
tennis, soccer, or volleyball; gymnastics on the floor or by using some
gymnastic apparatus; etc.) and tries to make a generalization, we suggest a
deductive approach: one starts with considering a completely general
problem. Once the general model is formulated, one may derive different real
situations as being special cases. Such approach needs a serious effort in
formulating the general model. The general methodology is explained and the
feasibility is supported by applying the general model
of some
illustrative examples:
first, a well-known situation – the single-support phase of a biped motion, and
second, a completely different problem – gymnastic exercise on a horizontal bar.
Intelligent Control Techniques in Robotics
Primary aim of the research in this area is the synthesis of intelligent robotic controllers for non-contact and contact tasks, as well as the application in the domain of locomotion robotic mechanisms. The synthesis of new control algorithms based on adaptive learning systems - neural networks is performed. The various forms of neural network training and different topologies of neural networks for efficient realization of robotic contact and non-contact tasks are proposed. Good results are achieved in the application of neural networks for robotic contact tasks where the problem of uncertainties of the robot model and parameters, as well as uncertainties of the dynamic environment is very important. Very interesting and applicable results are obtained using hybrid control method based on combination of conventional control techniques and soft computing paradigms (neural networks, uzzy logics, genetic algorithms). This complementary approach is successfully applied to manipulation robots and locomotion robots. The proposed intelligent techniques which are analyzed for a broader range of contact robotic tasks, show an important advantage in comparison with conventional techniques of robot compliance control.
Wavelet network classifier for advanced learning control of robotic contact tasks
Connectionist Reactive Control by Robot Hand with soft grippers
Reinforcement Learning in Humanoid Robotics
Classical humanoid robotics still rely heavily on teleoperation or fixed a priori determined behavior based control with very little autonomous ability to react to the environment. Key missing elements is the ability to create control systems that can deal with a large movement repertoire, variable speeds, constraints and most importantly, uncertainty in the real-world environment in a fast, reactive manner. The acquisition and improvement of motor skills and control policies for robotics from trial and error is of essential importance if robots should ever leave precisely pre-structured environments.
This research considers
a optimal solutions for application of reinforcement
learning in humanoid robotics. The importance of hybrid approach is
emphasized. The hybrid aspect is connected with application of model-based and
model free approaches as well as with combination of different paradigms of
computational intelligence.
The general goal in synthesis
of reinforcement learning control algorithms is
the development of methods which scale into the dimensionality of humanoid
robots and can generate actions for biped with many degrees of freedom. In this
research, we will consider specially that control of walking of active and
passive dynamic walkers by using of reinforcement learning can be efficiently
solved .
Dynamic bipedal walking is difficult to learn
because combinatorial explosion in order
to optimize performance in every possible configuration of the robot.,
uncertainties of the robot dynamics that must be only experimentally validated,
and because coping with dynamic discontinuities caused by collisions with
the ground and with the problem of delayed reward -torques applied at one time
may have an effect on the performance many steps into the future. Hence, for a
physical robot, it is essential to learn from few trials in order to have some
time left for exploitation. It is thus necessary to speed the learning up by
using different methods (hierarchical learning, subtask decomposition, imitation,…),
that will be presented
Various straightforward
and hybrid intelligent control algorithms based RL for
active and passive biped locomotion is presented. The proposed
reinforcement learning algorithms is based on two different learning structures:
actor-critic architecture and Q-learning
structures. Also, RL algorithms can use numerical and fuzzy evaluative
feedback information for external reinforcement. The proposed RL algorithms use
the learning elements that consists of various types
of neural networks, fuzzy logic nets or fuzzy-neuro
networks with focus on fast convergence properties and small number of learning
trials.T
fuzzy reinforcement learning feedback around Zero-Moment Point. The
reinforcement learning architecture as external
reinforcement use fuzzy evaluative feedback.
Multi-Arm Cooperating Robots Dynamics and Control
Several
consistent solutions for cooperative system control have recently been
identified by the authors of the current monograph. This was achieved by solving
three separate tasks that are essential for solving the problem of cooperative
manipulation as a whole. The first task is related to the understanding of the
physical nature of cooperative manipulation and finding a way for a sufficiently
exact characterization of cooperative system statics, kinematics and dynamics.
After successfully completing this task, in the frame of the second task, the
problem of coordinated motion of the cooperative system is solved. Finally, as a
solution to the third task, the control laws of cooperative manipulation are
synthesized.
The starting point in dealing with the above
three tasks of cooperative manipulation was the assumption that the problem of
force uncertainty in cooperative manipulation can be resolved by introducing
elastic properties into the cooperative system, at least in the part where force
uncertainty appears. In static and dynamic analysis of the elastic structure of
cooperative systems the finite element method is applied. In contrast to the
procedure used in the major part of the available literature where deformation
work is expressed by deviations from the unloaded state of fixed elastic
structure, in this monograph the deformation work is expressed by internal
forces as a function of the absolute coordinates of contacts of mobile elastic
structure. Coordinated motion and control in cooperative manipulation are solved
as the problem of coordinated motion and control of a mobile elastic structure,
taking into account the specific features of cooperative manipulation.
Coordinated motion and control laws in cooperative manipulation are synthesized
on the basis of a non-linear model where the problem of uncertainty is solved,
which is not the case in the available literature. Simple examples demonstrate
the consistent procedure of mathematical modeling and synthesis of nominal
coordinated motion, as well as control of the cooperative system.
Elasticity of robotic
sistems
A joint is defined in a new way, in
dependence of the motor state (active or locked) and type of elastic or
rigid element that follows behind the motor. An analysis was made of the
choice of reference trajectory, which depends on the level of knowing
elasticity characteristics. The estimated elasticity characteristics may be
included into the reference trajectory, and thus into the control law.
However, when the introduction of link flexibility into the mathematical model is concerned, it was necessary to point out to some essential problems in this domain. Based on the EBE (“Euler-Bernoulli Approach”), we defined the equation of flexible line of each mode of any link of a complex robotic system. We demonstrated that the equation of equilibrium of all the forces involved at any point follows directly from the equation of flexible line. In addition to the comparative analysis of the EBE and LMA (“Lumped-Mass Approach”), the paper also analyzes a number of other phenomena that make constitutive parts of the motion dynamics of these systems.
a) Structure of the matrix of stiffness: It must have elements outside the diagonal too, because of the strong coupling between the present modes.
b)
Damping is an elementary
characteristic of flexibility: In the Navier
equation, in addition to the stiffness characteristic, a damping
characteristic was introduced for the first time.
c)
Equations of the particular modes
in the overall model differ among themselves.
d) Structure of the mathematical model of the motor: With elastic robotic systems, the motor torque is opposed by the elasticity moment of the first elastic element coming directly after the motor. If it is a flexible link, then the motor torque is opposed by the bending moment of the first flexible mode that comes after the motor, and also, in part, by the bending moments of the other flexible modes that are connected sequentially after the first mode. Depending on their position, all modes of the first link, coming after the motor, influence the motor motion dynamics. Mathematical model of the motor is related to the rest of the mechanism via an equivalent flexibility moment. The new structure of stiffness matrix and mathematical model of the motor are a consequence of the coupling between the present modes of particular links.
However, if an elastic gear comes directly after the motor, then the motor torque is opposed by the gear deflection moment.
e)
A general form of a transversal
flexible deformation, obtained by superimposing particular solutions of the
oscillatory character (solution of Daniel Bernoulli) and stationary
solutions of forced character (which is a consequence of the forces
involved), is defined. Flexible deformation and
general form of the elastic line is a direct outcome of the system motion
dynamics, and can not be described by one scalar equation but by three
equations for position and three equations for orientation of every point on
that elastic line. Equation of the elastic line of the robotic system
comprises (apart from other quantities) the robot configuration.

Tip coordinates and
deviation of position from the reference level
Dynamic force of the
environment.
Elastic deformations in the vertical plane and in the horizontal plan.
Modeling of complex flexible
biped-platform system
This work is concerned with the
modeling and analysis of a complex humanoid robotic system walking on an
immobile/mobile platform.
Humanoid robotic
mechanism with 25 DOF and platform with 6 DOF
(this example is analyzed only with flexible gears).
For this purpose, a software package FLEXI was synthesized which allows one to select configuration of both the humanoid and the platform.
Each joint of the biped and platform
can be defined by the user via the motor state (active or locked) and gear
type (rigid or elastic). The user can also form very diverse configurations
of the humanoid and platform. The FLEXI forms a mathematical model. By
selecting system's parameters the simulation allows user to analyze dynamic
behavior of the biped of selected configuration, walking on either an
immobile or mobile platform of selected configuration. In the moment when
the biped steps on the platform, the latter, by its dynamics, acts on the
biped dynamics and the biped on the other hand, by its characteristics,
influences dynamics of the platform motion. These two complex contacting
systems form a more complex system, whose mathematical model has to
encompass all the elements of coupling between the humanoid joints and
platform joints. The phenomenon of coupling is analyzed first on a humanoid
robotic system with all rigid elements, which is in contact with the
platform mechanism having also all rigid elements. It has been shown that
coupling is more influenced when elasticity elements are included into the
configuration. Insufficient knowledge of coupling characteristics may
present a serious disturbance to the system in the robotic task realization.
The deviation of the ZMP (Zero-Moment Point) from the
reference trajectory is presented, which implies the need for the synthesis
of new control structures for stabilizing biped motion on the
immobile/mobile platform. The reference trajectory may be defined in very
different ways and from several aspects. Reference trajectory of each joint
can be defined so to encompass or not encompass elastic deformations. The
control structure for the biped walking on the platform should be defined so
that it satisfies the requirement for the ZMP to be within the given
boundaries in every sampling instant, which guarantees dynamic balance of
the locomotion mechanism in the real regime. The control is defined
separately under the real conditions of unknown characteristics of coupling
between the two complex systems, as well as unknown elasticity properties.
The analysis of simulation results of the humanoid robot motion on a mobile
platform gives evidence for all the complexity of this system and shows how
much system parameters (choice of trajectory, configuration, geometry,
elasticity characteristics, motor, etc.) influence stabilization of its
humanoid motion
Real elastic deformations [rad]
Reference ZMPo
and real ZMP [m]
Reference ZMPo
and real ZMP
[m]
Real
elastic deformation
[rad]
Reference ZMPo and real ZMP [m]
Quantitative biomechanical analyses of human movement typically require estimation of the body segment parameters (mass, position of the center of mass, principal radii of gyration, moments of inertia). Specifying details of biometry measurements as well as applying methodology of Zatsiorsky-Seluyanov (based on statistics obtained measuring cadavers) improved tabular approach of parameter determination proposed by Paolo De Leva, a specialized software for identification of anthropomorphic parameters was developed. For the known mass and stature of the body and with certain photometry measurements the anthropomorphic parameters with satisfactory high accuracy can be obtained.
Kinematic parameters and mass of links of human body of m=84.07 kg, H=1.90 m
|
Link |
Length |
Mass
|
CM position
|
|
sagittal transversal longitudinal |
|||
|
Head |
0.2722 |
5.8347 |
0.0000 0.0000 0.1361 |
|
Trunk |
0.7667 |
36.5380 |
0.0144 0.0000 0.3216 |
|
Thorax |
0.2500 |
13.4180 |
0.0100 0.0000 0.1167 |
|
Abdomen |
0.3278 |
13.7291 |
0.0150 0.0000 0.2223 |
|
Pelvis |
0.1889 |
9.3909 |
0.0200 0.0000 0.0345 |
|
Arm |
0.3444 |
2.2784 |
0.0000 0.0000 -0.1988 |
|
Forearm Hand Thigh Shank Foot |
0.3222 0.2111 0.4556 0.4389 0.2800 |
1.3620 0.5128 11.9047 3.6404 1.1518 |
0.0000 0.0000 -0.1474 0.0000 0.0000 -0.0779 0.0000 0.0000 -0.2275 0.0000 0.0000 -0.1957 0.0420 0.0000 -0.0684 |
Dynamic parameters – inertia tensor and radii of gyration of human body of m=84.07 kg, H=1.90 m
|
Link |
Radii of gyration
|
Moments of inertia |
|
sagittal transversal longitudinal |
|
|
|
Head |
0.0825 0.0856 0.0711 |
0.0397 0.0428 0.0295 |
|
Trunk |
0.2852 0.2660 0.1464 |
2.9720 2.5859 0.7835 |
|
Thorax |
0.1790 0.1135 0.1647 |
0.4299 0.1729 0.3642 |
|
Abdomen |
0.1580 0.1255 0.1534 |
0.3427 0.2164 0.3231 |
|
Pelvis |
0.1162 0.1041 0.1109 |
0.1267 0.1017 0.1155 |
|
Arm |
0.0982 0.0927 0.0544 |
0.0220 0.0196 0.0067 |
|
Forearm |
0.0889 0.0854 0.0390 |
0.0108 0.0099 0.0021 |
|
Hand |
0.1326 0.1083 0.0847 |
0.0090 0.0060 0.0037 |
|
Thigh |
0.1828 0.1828 0.0828 |
0.3977 0.3977 0.0816 |
|
Shank |
0.1119 0.1093 0.0452 |
0.0456 0.0435 0.0074 |
|
Foot |
0.0720 0.0686 0.0347 |
0.0060 0.0054 0.0014 |
A graphic description of the main adjustments to the relative CM positions according Paolo De Leva
used in the parameter identification
Quantitative Biomechanical Analysis of Biped Locomotion – Capture of human motion
Accurate quantification of kinematics (locomotion) represents a significant requirement for the purpose of physical rehabilitation in medicine, designing of prosthesis in orthopedics, analysis and optimization of sporting disciplines, researches in bio-mechanics, humanoid robotics, etc. Bio-inspired behavior of biped locomotion robots (humanoids) is based on the deep analysis of a human motion. For this purpose a variety of experimental measurements were done in the capture motion studio. In this research project specialized software for processing of the experimental data of measurements was designed. In the laboratory conditions a set of the extensive experiments were done, measuring capture motion characteristics (using corresponding fluorescent markers and 6-infra red cameras) and ground reaction forces and torques (by the 6-axis force platform).
Experimental measurements in the laboratory conditions: (i) fluorescent markers attached to the human body, (ii) Vicon infra-red camera, (iii) 6-sensors force platform
Identified joint angles of human legs during locomotion
Experimentally measured ground reaction forces and torques at the contact foot
Bio-Inspired Synthesis of the Artificial Humanoid Motion - Knowledge-based generator of the joint trajectories
The goal of this project is to generate/determine a desired biped motion, applying learning algorithms (artificial neural network structure), based on the imposed trajectories of the feet and hip joint centers in the reference, Descartes coordinate system of robot motion. Multi-layer artificial neural network structure was used to learn the inverse kinematics of the lower extremities (legs). Simulation results of the open-loop, biped model (used for the rough/initial training) as well as the data of experimental measurements (for the fine net training) were used as the training sets. Designed knowledge-based algorithm enables real-time generation of the nominal joint trajectories. As a network input set, considering Descartes trajectories of the feet-sole contour points as well as the hip center coordinates determined at the higher strategic control level were used. Developed algorithm for trajectory generation is suitable for the trajectory planning and for planning of the obstacle avoidance at the strategic control level. Designed knowledge-based algorithm ensures bio-inspired synthesis of the artificial motion since it was based on the experimental measurements.
Coordinates of the feet contour points and hip joint centers (left and right) imposed as the input variables to the knowledge-based generator of joint trajectories
A characteristic example of the slalom trajectory of a biped robot with fixed obstacles in its environment
Advanced Modeling of Humanoid Robots – Kinematics and dynamics of biped locomotion
Humanoids, being the future of robotic science, are becoming more and more human-like in all aspects of their functioning. It is expected that they will replace humans in a variety of tasks. Thus, it is generally accepted that their shape and motion should be based on biomechanical principles – to be bio-inspired. Because of the complexity and high requirements imposed on such robots, their control system has to utilize the dynamic model. So, the control, the design, and the simulation, strongly require general dynamic models that will make humanoid robots capable of handling the increasing diversity of expected tasks. As the result of this research/developing project, a user-friendly simulation software of humanoid kinematics and dynamics was developed. Modeling software was realized as a MATLAB/SIMULINK toolbox using all advances of the Matlab engineering interface. Developed spatial, non-linear model in the present state considers structure of the biped mechanism with 32 d.o.f. It includes full kinematical and dynamic models as well as model of foot impact dynamics in all phases of biped gait: single support, double support and flyer phase (no contact with environment).
Kinematic scheme of the 32 d.o.f. biped mechanism/system considered in the project
Human body for its complex motion uses synergy of more than 600 muscles. It has more then 300 degrees of freedom. Some of these particular motions are essential for the human activities (gait, work, sport, dancing, etc.) while the others give it a full mobility. A biped locomotion mechanism of the anthropomorphic structure was considered as a mechanical representative of a human body. In that sense, an articulated system, consisting of the basic kinematic chain and four side branch chains was considered as a biped mechanism. In a mechanical sense, it represents a multi-body, large-scale dynamic system with a variable structure
Branched mechanism of a biped locomotion robot, b) Decomposition of the complex mechanism structure into the set of single chains
Developed modeling software calculates: Jacobians, Descartes coordinates of the joint centers in the inertial coordinate system attached to the ground support, corresponding velocities and accelerations of robot joint centers, feet positions/orientations relative to the support, inertia matrix, vector of centrifugal, Coriolis and gravitational forces/torques, contact/impact forces and ground reaction forces/torques, driving torques in robot joints and Zero Moment Point location with respect to the supporting polygon of biped system.
Mathematical Modeling of Non-Smooth Impact Dynamics of Human Gait – Theory & experiments
The impact phase starts when the biped link reaches the surrounding object(s). Strictly speaking, the restricted coordinates at the robot foot reach zero one by one. So a complex contact is established as a series of simpler contact effects. The impact begins when the biped foot (feet) reaches the constraint surface. Constraint in a general case can be an ordinary curve, prismatic or flat surface. Accurate modeling of non-smooth, frictional impact dynamics was subject of the comprehensive researches conducted in this project.
Modeling of feet impact dynamics – mechanical set of the problem
Impact model in this project was considered as a Linear Complementarity Problem (LCP) formulation. Stiction and friction phenomena were included into the model, too.
Functional coordinates of the left and right foot determining the relative positions of the feet contour points with respect to the support in the normal direction
Model-based, ground reaction forces at the right and the left foot during step phases
Integrated Control of Humanoid Robots
Control of humanoid robots has to satisfy the following requirements: (i) accuracy of tracking the desired trajectories of the mechanism joints (ii) maintenance of dynamic balance of the mechanism during the motion, (iii) minimization of the impact arising at the moment of contact of the free foot and the ground during the gait, (iv) minimization of dynamic loads at the robot joints, and (v) realization of anthropomorphic characteristics of the gait. Fulfillment of requirement (i) enables the realization of a desired mode of motion, walk repeatability and avoidance of potential obstacles. To satisfy requirement (ii) it means to maintain balance of the dynamic reactions acting upon the robotic system during the motion. Fulfillment of requirement (iii) decreases the impact effects on the overall system at the moment when the unconstrained leg foot strikes the ground. Fulfillment of requirement (iv) is needed for the purpose of minimizing dynamic loads at the robotic joints, which is especially important for the joints bearing the highest load during the walk, e.g. the hip. Requirement (v) is related to the quality of artificial (human-like) gait. Walk of a physically healthy human represents a balanced and harmonious sequence of movements, with minimal displacements of the position of the mass center about an imaginary central position corresponding to the human’s posture at rest. Bearing in mind the control requirements, it is necessary to control the following quantitites: positions and velocities of the robot joints, ZMP position, contact force at the instant of foot striking the ground, and dynamic load forces at particular mechanism joints. Control system designed in this project involves four feedback loops: (i) position-velocity feedback, (ii) dynamic reaction feedback at the ZMP, (iii) impact-force feedback at the foot of the free (unconstrained) leg, and (iv) load feedback at the mechanism joints. The dynamic controller was realized at two control levels: tactical and executive.
Block-diagram of the integrated dynamic control of a biped locomotion mechanism with four feedback loops and with executive control block at the lower level
Advanced Modeling and Simulation of Automotive Systems – Model of chassis, suspensions, tires, steering, power - drivetrain & braking systems
The specialized automotive engineering software toolbox designed for modeling and simulation of spatial, non-linear, 22 d.o.f. (degrees of freedom) road vehicle dynamics was developed. In mechanical sense, road vehicle represents a complex, distinctly non-linear, dynamic system with a relatively large number of d.o.f., belonging to the class of so called large-scale dynamic systems. These d.o.f. (independent motion directions), especially those that essentially influence the system's stability and quality of its dynamic behavior, have to be controlled. The vehicle stability, quality of its dynamic behavior and maneuvering capabilities depend to a great extent on the system structure as well as on performances of its power-steering and power-drivetrain subsystems. Synthesis of the best control strategy and design of the corresponding driver-assisted system represent delicate problems whose solving requires knowledge of dynamic behavior of entire vehicle dynamics under different conditions of motion (uneven inclined surface, slippery road, wind gust, etc.). In that sense, mathematical modeling of vehicle dynamics and its tire-road interaction represents starting point in design process, control synthesis, safety analysis, etc.
Block-scheme of the model structure with particular functional modules
Intelligent Control of Vehicle Lateral and Yaw Dynamics– Smart control system to improve vehicle stability
Advanced hybrid, knowledge-based – model-based control system of road vehicle interactive dynamics was designed in the project. The proposed driver-assisted control system was designed to improve vehicle stability, active safety and handling performances using four wheel steering, active driving/braking and active suspension system. The control scheme was designed based on a centralized, dynamic control approach with a supplementary knowledge-based compensator (connectionist structure) in the feedback loop. The distributed hierarchy control strategy, with two control levels - tactical and operative, was implemented.
Figure 14: Block-scheme of the driver-vehicle system with driver assisted control system in the loop
Structure of the training process during system identification
Closed Loop Model of Driver-Vehicle System – Fuzzy sets in modeling of driver behavior with automotive systems
With conventional road vehicles the direction and the speed of motion are adjusted by the human operator using driver-vehicle interface (steering wheel and acceleration/braking pedals). Vehicle follows the desired path depending on driver’s psycho-physical abilities to response to the driving demands.
Structure of the hybrid, man-machine - driver-vehicle system
Block-diagram of the driver-model implementing fuzzy sets
Hazard Prevention Control System – Intelligent, active safety, driver-assisted control of automotive systems
The main role of the Hazard Prevention System (HPC) designed with automotive systems is to predict and to actively control a hazard motion of road vehicles: e.g. to decrease vehicle speed, to stop the car, to improve the steering wheel angle, etc. This is a delicate control task that demands knowledge of vehicle dynamics as well as driver-model. The HPC system consists of two functional modules: (i) the path observer and, (ii) the fuzzy controller. Together, they make a smart control structure, i.e. an active safety control system based on the fuzzy model of a human operator - driver.
Hazard prevention system within a closed-loop control structure
Path observer identifies the road geometry along which the vehicle moves. Fuzzy controller represents a fuzzy model of an experienced vehicle driver. Parameters of the fuzzy controller are tuned off-line on the basis of experimental and simulation data. The best fit of the model parameters obtains using simulation results of the different running tests. Main task of the fuzzy controller in the loop is the same as the role of the driver instructor assisting to an inexperienced vehicle operator. The control signals from the fuzzy controller are led to the vehicle actuators. They serve to change the driver manual commands in a direct way using corresponding servo-actuators of steering, traction or braking system. Beside the identification of desired road geometry and control of path tracking the proposed HPC system was designed to have certain additional functions in hazard prevention, cruising control, platooning, automatic parking, etc. With a radar system installed in the car, the HPC is able to control vehicle motion in the presence of obstacles on the road.


A simple web interface to debug your socket.io API by chatting with it.
It currently uses yaml to make json easier to read and write. Lot's still to do: issues Source: github/Doodle3D/socket.io-debug-client


Home
Client List
Medical Acts
Log out
Client List
Need more info?
View More
Medical Acts
Need More info?
View More


- status
- Displays paths that have differences between the index file and the
current HEAD commit, paths that have differences between the workspace
and the index file, and paths in the workspace that are not tracked
by git.
- diff
- Displays the differences not added to the index.
- diff commit or branch
- View the changes you have in your workspace relative to the named commit.
You can use HEAD to compare it with the latest commit, or a branch
name to compare with the tip of a different branch
- add file... or dir...
- Adds the current content of new or modified files to the index, thus
staging that content for inclusion in the next commit. Use add
--interactive to add the modified contents in the
workspace interactively to the index.
- add -u
- Adds the current content of modified (NOT NEW) files to the index.
This is similar to what 'git commit -a' does in preparation for
making a commit.
- rm file(s)...
- Remove a file from the workspace and the index.
- mv file(s)...
- Move file in the workspace and the index.
- commit -a -m 'msg'
- Commit all files changed since your last commit, except untracked files
(ie. all files that are already listed in the index). Remove files
in the index that have been removed from the workspace.
- checkout files(s)... or dir
- Updates the file or directory in the workspace. Does NOT switch branches.
- reset HEAD file(s)...
- Remove the specified files from the next commit. Resets the index but
not the working tree (i.e., the changed files are preserved but
not marked for commit) and reports what has not been updated.
- reset --soft HEAD^
- Undo the last commit, leaving changes in the the index.
- reset --hard
- Matches the workspace and index to the local tree. WARNING: Any changes
to tracked files in the working tree since commit are lost. Use
this if merging has resulted in conflicts and you'd like to start
over. Pass ORIG_HEAD to undo the most recent successful merge and
any changes after.
- checkout branch
- Switches branches by updating the index and workspace to reflect the
specified branch, branch, and updating HEAD
to be branch.
- checkout -b name of new branch
- Create a branch and switch to it
- merge commit or branch
- Merge changes from branch name into current branch.
Use
‑‑no-commit to leave
changes uncommitted.
- rebase upstream
- Reverts all commits since the current branch diverged from upstream,
and then re-applies them one-by-one on top of changes from the
HEAD of upstream.
- cherry-pick commit
- Integrate changes in the given commit into the current branch.
- revert commit
- Reverse commit specified by commit and commit
the result. This requires your working tree to be clean (no modifications
from the HEAD commit).
- diff --cached commit
- View the changes you staged vs the latest commit. Can pass a commit
to see changes relative to it.
- commit -m 'msg'
- Stores the current contents of the index in a new commit along with
a log message from the user describing the changes.
- commit --amend
- Modify the last commit with the current index changes.
- log
- Show recent commits, most recent on top. Options:
‑‑decorate
with branch and tag names on appropriate commits
‑‑stat
with stats (files changed, insertions, and deletions)
‑‑author=author
only by a certain author
‑‑after="MMM
DD YYYY" ex. ("Jun 20 2008") only commits after a
certain date
‑‑before="MMM
DD YYYY" only commits that occur before a certain
date
‑‑merge
only the commits involved in the current merge conflicts
- diff commit commit
- View the changes between two arbitrary commits
- branch
- List all existing branches. Option -r causes the remote-tracking branches
to be listed, and option -a shows both.
- branch -d branch
- Delete an specified branch. Use -D to force.
- branch --track new remote/branch
- Create a new local branch that tracks a remote branch.
- clone repo
- Download the repository specified by repo and
checkout HEAD of the master branch.
- pull remote refspec
- Incorporates changes from a remote repository into the current branch.
In its default mode, git pull is shorthand
for git fetch followed by git
merge FETCH_HEAD.
- reset --hard remote/branch
- Reset local repo and working tree to match a remote branch. Use reset
‑‑hard origin/master to throw
away all commits to the local master branch. Use this to start
over on a failed merge.
- fetch remote refspec
- Download objects and refs from another repository.
- push
- update the server with your commits across all branches that are *COMMON*
between your local copy and the server.Local branches that were
never pushed to the server in the first place are not shared
- push remote branch
- Push new (or existing) branch to remote repository
- push remote branch:branch
- Push new branch to remote repository with a different name
- branch -r
- List remote branches
- push remote :branch
- Remove a remote branch. Literally "push nothing to this branch"
- clean
- Cleans the working tree by recursively removing files that are not
under version control, starting from the current directory.
- stash save msg
- Save your local modifications to a new stash, and run git reset ‑‑hard
to revert them. The msg part is optional and
gives the description along with the stashed state. For quickly
making a snapshot, you can omit both "save" and msg.
- stash apply stash
- Move changes from the specified stash into the workspace. The latest
stash is the default.
- stash pop
- Applies the changes from the last (or specified) stash and then removes
the given stash.
- stash list
- List the stashes that you currently have.
- stash show stash
- Show the changes recorded in the stash as a diff between the stashed
state and its original parent. When no stash
is given, shows the latest one.
- stash drop stash
- Remove a single stashed state from the stash list. When no stash
is given, it removes the latest one.
- stash clear
- Remove all the stashed states. Note that those states will then be
subject to pruning, and may be impossible to recover.
- stash branch branchname stash
- Creates and checks out a new branch named branchname
starting from the commit at which the stash
was originally created, applies the changes recorded in stash
to the new working tree and index.
If that succeeds,
and stash is a reference of the form stash@{revision},
it then drops the stash. When no stash
is given, applies the latest one.
This is useful if the
branch on which you ran git stash save has changed enough that
git stash apply fails due to conflicts. Since the stash is applied
on top of the commit that was HEAD at the time git stash was run,
it restores the originally stashed state with no conflicts.


File Manager
Link to File
File/Page linked to
File/Webpage
Description
Hyperlink Information
Type:
Webpage
Secure
Email
FTP
Target:
{Default}
Same Page
New Window
Parent Frame
Top Frame
Cancel
OK


I am leading the TA team at USC on Data Structure and Object Oriented Programming since Fall 2016.
I have participated in USC Coding challenge in Fall 2016 and Spring 2017 winning 4th place and 5th place.
I am President at USC ACM SIGGRAPH Chapter, hosting weekly computer graphics workshops and industry panels for 500+ subscribers
My research areas at USC include Cloth Simulation, 3D Printing and Design Automation.
I am familiar with multiple cloud services including AWS, Google Cloud and IBM Watson
I developed, tested and deployed cloud platform for collaboration between CAD industry on Amazon EC2 during my internship with Autodesk.
I am proficient in both front-end and backend in web development. I had hand-on experiences in web dev with HTML5, CSS, React.js, Three.js, JQuery, Node.js, MySQL and MongoDB.
I have a comprehensive knowledge in AI and Machine Learning, with practical experiences with Python, TensorFlow and AML.
My Senior Design project oriented in building a machine learning system for Business Intelligence, where we gathered data from Facebook, Twitter and Google Analytics to predict the desired time to post contents.
I am familiar with designing process in both 2D and 3D. My portfolio includes works with Photoshop, Lightroom, Premiere, Maya and ZBrush.
I comprehensively understand and appreciate UI/UX designers' works. And can substitute part of their work during rapid development environment.
Recognized by Countour Crafting Lab: applying 3D printing technology in large scale building construction. (Coolest research ever)
Twice more work than before, but I enjoy the responsibility I have been taking.
Leading a 500+ member organization is not easy job, but I am trying my best
"I really like the energy and passion you showed here!" said by my manager
The hardest semester ever for me. But thanks to this project I had a lot of fun.
"I really like computer graphics, Hope I can make the club great again!" I said this when I joined the board.
Hard work got recognized, started to teach Data Structure and Object Oriented Programming
Interned as front-end developer, familiar with HTML, JQuery and React
Since then I knew where I belong


The purpose of machine learning is to find (and exploit) patterns in data. Traditionally developers, when faced with a problem, develop and algorithm and write code. Certain classes of problems, however, do not lend themselves to this approach. With machine learning, the developer instead supplies relevant data to the machine and allows the computer to create the appropriate algorithm.
Supervised learning is the branch of machine learning that deals primarily with prediction. Given examples, supervised learning algorithms create models that generalize the decision making process. In essence, the machine learns from the past in order to accurately predict the future.
Unsupervised learning is the branch of machine learning that strives to understand the structure of data. This data, unlike supervised learning, does not have a predefined outcome that requires prediction but is vast enough to require a principled approach to either visual or physical compression.
Refer to our getting started page for a more detailed look on how to get going on various platforms. You can then read about the project, try out the documentation or get in touch.


The Site class is a built-in Jekyll class with access to global site config information.
Monkey patch for the Jekyll Site class. For the original class, see: github.com/mojombo/jekyll/blob/master/lib/jekyll/site.rb
Instance variable to store the various post_filter plugins that are loaded.
Instantiates all of the post_filter plugins. This is basically a duplication of the other loaders in Site#setup.
# File plugins/post_filters.rb, line 40 def load_post_filters self.post_filters = Jekyll::PostFilter.subclasses.select do |c| !self.safe || c.safe end.map do |c| c.new(self.config) end end
Read all the files in <source>/<dir>/_posts and create a new Post object with each one.
dir - The String relative path of the directory to read.
Returns nothing.
# File plugins/preview_unpublished.rb, line 15 def read_posts(dir) base = File.join(self.source, dir, '_posts') return unless File.exists?(base) entries = Dir.chdir(base) { filter_entries(Dir['**/*']) } # first pass processes, but does not yet render post content entries.each do |f| if Post.valid?(f) post = Post.new(self, self.source, dir, f) # Monkeypatch: # On preview environment (localhost), publish all posts if ENV.has_key?('OCTOPRESS_ENV') && ENV['OCTOPRESS_ENV'] == 'preview' && post.data.has_key?('published') && post.data['published'] == false post.published = true # Set preview mode flag (if necessary), `rake generate` will check for it # to prevent pushing preview posts to productive environment File.open(".preview-mode", "w") {} end if post.published && (self.future || post.date <= self.time) self.posts << post post.categories.each { |c| self.categories[c] << post } post.tags.each { |c| self.tags[c] << post } end end end self.posts.sort! # limit the posts if :limit_posts option is set self.posts = self.posts[-limit_posts, limit_posts] if limit_posts end
Creates an instance of CategoryIndex for each category page, renders it, and writes the output to a file.
+category_dir+ is the String path to the category folder. +category+ is the category currently being processed.
# File plugins/category_generator.rb, line 88 def write_category_index(category_dir, category) index = CategoryIndex.new(self, self.source, category_dir, category) index.render(self.layouts, site_payload) index.write(self.dest) # Record the fact that this page has been added, otherwise Site::cleanup will remove it. self.pages << index # Create an Atom-feed for each index. feed = CategoryFeed.new(self, self.source, category_dir, category) feed.render(self.layouts, site_payload) feed.write(self.dest) # Record the fact that this page has been added, otherwise Site::cleanup will remove it. self.pages << feed end
Loops through the list of category pages and processes each one.
# File plugins/category_generator.rb, line 104 def write_category_indexes if self.layouts.key? 'category_index' dir = self.config['category_dir'] || 'categories' self.categories.keys.each do |category| self.write_category_index(File.join(dir, category.gsub(%r_|\P{Word}/, '-').gsub(%r-{2,}/, '-').downcase), category) end # Throw an exception if the layout couldn't be found. else throw "No 'category_index' layout found." end end


API
play(position, force)
Parameters
- position: (Float) time in seconds OR (String) entry-id
- force: (Boolean) true will disable cloning, false is defaulted
Description
This function will start playback of the given spritemap entry.
You can pass through either a value of a time position in seconds (that is
inside a defined sprite entry) or an id of a sprite entry.
The sprite entry id is the preferred and fastest way to play.
Example
// var player = new jukebox.Player(...);
player.play('bgmusic'); // faster, sprite entry's id
player.play(12.34); // slower, will search for matching sprite entry
stop()
Parameters
This method requires no parameters.
Description
This function will stop playback on the origin jukebox.Player instance.
It will reset the position of the stream to the beginning.
Example
// var player = new jukebox.Player(...);
player.play('bgmusic');
// will stop playback after 2 seconds
window.setTimeout(function() {
player.stop();
}, 2000);
pause()
Parameters
This method requires no parameters.
Description
This function will pause playback of the jukebox.Player instance.
It will save the current position of the stream, so you can resume() it later.
Example
// var player = new jukebox.Player(...);
player.play('effect');
// will pause playback after 2 seconds
window.setTimeout(function() {
player.pause();
}, 2000);
resume()
Parameters
This method requires no parameters.
Description
This function will resume playback of the jukebox.Player instance.
It will start playback at the last cached position (of a pause() call).
If no position was cached before, it will start from the current position of the stream.
Example
// var player = new jukebox.Player(...);
player.play('effect');
// will pause playback after 2 seconds
window.setTimeout(function() {
player.pause();
}, 2000);
// will resume playback after 4 seconds
window.setTimeout(function() {
player.resume();
}, 4000);
getVolume()
Parameters
This method requires no parameters.
Description
This function returns (Float) the current volume (min: 0, max: 1.0)
of the jukebox.Player instance.
Example
// var player = new jukebox.Player(...);
player.setVolume(0.3);
// Log the current volume to the console
console.log(player.getVolume());
setVolume(volume)
Parameters
- volume: (Float) volume percentage (min: 0, max: 1.0)
Description
This function will set the volume to the given value.
Important: Some environments like iOS have no support for modifying the volume
Example
// var player = new jukebox.Player(...);
// set volume initially to 30% and start playback
player.setVolume(0.3);
player.play('effect');
// set volume to 100% after 2 seconds
window.setTimeout(function() {
player.setVolume(1.0);
}, 2000);
getCurrentTime()
Parameters
This method requires no parameters.
Description
This function returns (Float) the current position (in seconds) of the jukebox.Player instance.
Example
// var player = new jukebox.Player(...);
player.play('effect');
// Log the start position of the sprite entry to the console
// 200ms timeout lets the jukebox.Manager's loop correct the stream position
window.setTimeout(function() {
console.log('start: ' + player.getCurrentTime());
}, 200);
// Do it again after 2 seconds
window.setTimeout(function() {
console.log('after 2 seconds: ' + player.getCurrentTime());
}, 2000);
setCurrentTime(position)
Parameters
- position: (Float) the position of the jukebox.Player instance (in seconds)
Description
This function returns (Boolean) true if the stream was ready and the position was set. False otherwise.
It will try to set the current position of the jukebox.Player stream.
It may fail if the stream is not ready for that, e.g. if download is still in progress or the background
process is not ready for playback.
Example
// var player = new jukebox.Player(...);
player.play('effect');
// Log the start position of the sprite entry to the console
// 200ms timeout lets the jukebox.Manager's loop correct the stream position
window.setTimeout(function() {
console.log('start: ' + player.getCurrentTime());
player.setCurrentTime(7.00);
console.log('after setCurrentTime call: ' + player.getCurrentTime());
}, 200);
// Do it again after 2 seconds
window.setTimeout(function() {
console.log('after 2 seconds: ' + player.getCurrentTime());
}, 2000);


Welcome to CAmp! Sit back and relax while we install some commonly used apps for you.
Once completed, your Mac will automatically log out. Enjoy your new Mac!
Jamf is a macOS management framework that is used to take the burden off CAmpers for common tasks.
With Jamf we ensure that your Mac is always up-to-date and meets all security requirements.
If you'd like some more information about how Jamf works, reach out to @james on Slack.
One of the benefits of Jamf is Self Service; think of it like a custom App Store just for CAmpers.
You'll find it on the lefthand side of your Dock.
If you would like to see an app in Self Service, drop a request in #help_it on Slack!
Slack is used for internal communications at Culture Amp and all day-to-day communications happen here.
To make your onboarding smoother, you'll be automatically invited to a number of channels relevant to your position, but feel free to explore and join any that interest you.
For any IT assistance, you can ask a question in #help_it!
Zoom is a video conference and chat provider that we use throughout CAmp.
It enables us to bridge the geographic gap between all offices.
Google Chrome is the preferred browser at CAmp.
It is a fast, simple, and secure browser for all your devices.
Viscosity is a VPN application that is used to connect to secure resources at CAmp.
You'll learn more about this during your security induction.
FileVault is macOS full-disk encryption and uses XTS-AES-128 encryption with a 256-bit key to help prevent unauthorized access to the information on your startup disk.
It is automatically enabled by Jamf so that your data is secure from day one.


> Wanting to apply for a job because it looks good and pays well
Vs
> Applying for a job so you can make JoJo references.


--- layout: index-page --- {{site.description}} {% for post in paginator.posts %}
{{site.description}}


A stock market, equity market or share market is the aggregation of buyers and sellers of stocks, which represent ownership claims on businesses
nitial public offering or stock market launch is a type of public offering in which shares of a company are sold to institutional investors and usually also retail investors.
A share price is the price of a single share of a number of saleable stocks of a company, derivative or other financial asset. In layman's terms, the stock price is the highest amount someone is willing to pay for the stock, or the lowest amount that it can be bought for.


{% extends 'layout.html' %} {% block content %}
|
Dear {{ email_content.get('name','')|title }}, The user ID: {{ email_content.get('uid','') }} used the (conference room / cabinspace) in your space ID: {{ email_content.get('space_id','') }} .
Rate the user based on the following. |


normal tests, written after the development, have mainly one purpose
regression tests relief you code by a task: to be similar to itself
thus, they enable the code to evolve, without too many worries
but tests are terribly boring
the typical test is just "stating the obvious"
and you will never find the time for them
increase the test coverage? get more people to do that manuallyi hate boring things
and we where quite stressed, in the frontend
but from May to now, i was able to keep developing and at the same time writing ~200 test specifications
and they really helped me
how to do that?
everything is based on an extremely simple principle
your tests will tell you when you're done
in a very zen way, your end will meet your principle :D
also several test / dev cycles could happen, just keep in mind to revert the traditional order
every discovered bug, should be handled as a new feature
bug -> fix -- no
bug -> test -> fix -- yes
that's the only way to slowly eliminate regression problems
as we said, the principle is simple:
so, the first thing we get, are tests
"what do i want"? first of all
describe('my component', function() { it('goes to detail after click on the item', function() { spyOn(history.newPage); this.component.select('$item').eq(0).click(); expect(history.newPage) .toHaveBeenCalledWith({ page: 'detail', item: 3243 }); }); });
this is the only way i know in order to think outside-in, from the very beginning
this process can lead you to always better interfaces, or not
(that means, to better testing logic instead)
expect(node.visible).toBe(true); expect(node).toBeVisible();
final consideration, for those with an analytical mind
it's not bullet-proof
but it helps, a lot
for the lazy:
expect('')
let the tests write themselves
advantage? regression
it('shows the correct value', function() { var $value = this.component.select('$value'); expect(raw in this.component.data).toBe(true); expect(this.component.lastTemplateInput.raw) .toBe(0.3476); expect(this.component.format(0.3476)) .toBe('34.76%'); expect(this.component.lastTemplateInput.formatted) .toBe('34.76%'); expect($value.length).toBe(1); expect($value.text()).toBe('34.67%'); });
yes, tests are supposed to grow, while code is supposed to shrink
at some extent
tackle the same problem
from different angles
from my experience, in order to switch from a normal trial and error process to a test driven one, an initial development effort is needed.
this effort is usually quite small , requiring one or two days. still you may feel quite unconfortable with your initial testing tools. convenience will come with time
if you don't have questions, why aren't you yet developing with test driven?


Kaushik Sathupadi
Programmer. Creator. Co-Founder. Dad.
See all my projects and blogs →
{{ content }}
Tweet
Post by Kaushik Sathupadi, Founder
Cull.io
Please enable JavaScript to view the
comments powered by Disqus.
blog comments powered by
Disqus


Komodo
introductions
Are you a developer or blockchain enthusiast? Introduce yourself. Please note that normal chat messages will be removed. Go to #general to start a discussion or ask a follow-up question.
Between 21-Dec-19 12:00 AM and 22-Dec-19 12:00 AM
YAGPDB.xyz
BOT
21-Dec-19 12:01 AM
trkohl#3597<PHONE_NUMBER>48696833)
Kicked for not verifying within deadline
YAGPDB.xyz
BOT
21-Dec-19 05:30 AM
adamlaska#6820<PHONE_NUMBER>00869888)
New user joined waiting to be verified as a human
YAGPDB.xyz
BOT
21-Dec-19 07:34 AM
meisme25#4524<PHONE_NUMBER>88795147)
New user joined waiting to be verified as a human
meisme25#4524<PHONE_NUMBER>88795147)
User successfully verified
YAGPDB.xyz
BOT
21-Dec-19 11:59 AM
cryptoSpirit#6436<PHONE_NUMBER>56234518)
New user joined waiting to be verified as a human
Tragic#6651<PHONE_NUMBER>39912192)
New user joined waiting to be verified as a human
Clever Alcohol#6269<PHONE_NUMBER>41963265)
New user joined waiting to be verified as a human
Reckless Meaning#9203<PHONE_NUMBER>66548483)
New user joined waiting to be verified as a human
Idiotic#4462<PHONE_NUMBER>25582113)
New user joined waiting to be verified as a human
Severe Permit#7578<PHONE_NUMBER>41504808)
New user joined waiting to be verified as a human
Definitive Complaint#6246<PHONE_NUMBER>50321164)
New user joined waiting to be verified as a human
Creamy#1497<PHONE_NUMBER>00177418)
New user joined waiting to be verified as a human
Twin#3090<PHONE_NUMBER>10989571)
New user joined waiting to be verified as a human
Hateful Shoulder#9386<PHONE_NUMBER>25852958)
New user joined waiting to be verified as a human
Unacceptable Safety#8288<PHONE_NUMBER>15270678)
New user joined waiting to be verified as a human
Lovable#4272<PHONE_NUMBER>17498624)
New user joined waiting to be verified as a human
Coarse Mark#5722<PHONE_NUMBER>16996096)
New user joined waiting to be verified as a human
Plush#1518<PHONE_NUMBER>49881640)
New user joined waiting to be verified as a human
Magnificent Working#6910<PHONE_NUMBER>04872458)
New user joined waiting to be verified as a human
Content Post#5924<PHONE_NUMBER>32238426)
New user joined waiting to be verified as a human
Fortunate Plane#7581<PHONE_NUMBER>86149888)
New user joined waiting to be verified as a human
Spirited Revenue#0954<PHONE_NUMBER>27609139)
New user joined waiting to be verified as a human
cryptoSpirit#6436<PHONE_NUMBER>56234518)
Kicked for not verifying within deadline
Tragic#6651<PHONE_NUMBER>39912192)
Kicked for not verifying within deadline
Idiotic#4462<PHONE_NUMBER>25582113)
Kicked for not verifying within deadline
Reckless Meaning#9203<PHONE_NUMBER>66548483)
Kicked for not verifying within deadline
Clever Alcohol#6269<PHONE_NUMBER>41963265)
Kicked for not verifying within deadline
Definitive Complaint#6246<PHONE_NUMBER>50321164)
Kicked for not verifying within deadline
Severe Permit#7578<PHONE_NUMBER>41504808)
Kicked for not verifying within deadline
Creamy#1497<PHONE_NUMBER>00177418)
Kicked for not verifying within deadline
Hateful Shoulder#9386<PHONE_NUMBER>25852958)
Kicked for not verifying within deadline
Twin#3090<PHONE_NUMBER>10989571)
Kicked for not verifying within deadline
Unacceptable Safety#8288<PHONE_NUMBER>15270678)
Kicked for not verifying within deadline
Magnificent Working#6910<PHONE_NUMBER>04872458)
Kicked for not verifying within deadline
Coarse Mark#5722<PHONE_NUMBER>16996096)
Kicked for not verifying within deadline
Plush#1518<PHONE_NUMBER>49881640)
Kicked for not verifying within deadline
Spirited Revenue#0954<PHONE_NUMBER>27609139)
Kicked for not verifying within deadline
Content Post#5924<PHONE_NUMBER>32238426)
Kicked for not verifying within deadline
Fortunate Plane#7581<PHONE_NUMBER>86149888)
Kicked for not verifying within deadline
YAGPDB.xyz
BOT
21-Dec-19 01:04 PM
DjAverts#8616<PHONE_NUMBER>77535491)
New user joined waiting to be verified as a human
DjAverts#8616<PHONE_NUMBER>77535491)
User successfully verified
YAGPDB.xyz
BOT
21-Dec-19 06:09 PM
Nightguy1688#3119<PHONE_NUMBER>66172205)
New user joined waiting to be verified as a human
Nightguy1688#3119<PHONE_NUMBER>66172205)
User successfully verified
YAGPDB.xyz
BOT
21-Dec-19 07:48 PM
mechman#0139<PHONE_NUMBER>35345419)
New user joined waiting to be verified as a human
mechman#0139<PHONE_NUMBER>35345419)
User successfully verified


B. caapi & M. hostilis
So the brew wasn't new to me this time, I had tried twice before, once using syrian rue extract for the MAOI but after mixing that into the boiled down rootbark it proved unable to keep down, everyone who drank some puked within minutes.
Lesson learned, tried again with 40g mimosa and 60g (roughly) caapi, reduced first extraction down to maybe 10 ounces of very dark liquid. myself and three other friends consumed half a shotglass full after some serious mental preparation, effects felt very quickly within 20 minutes, very nice and light, tingly body high, closed eye visuals, nothing to intense, descision was made for myself and two others to consume a full shot each...ouch...we were in a friends bedroom at 4 A.M. ish, everyone laid down, we talked a little until it came on full strength, at which time, no one spoke for what seemed like lifetimes and we were all consumed by our internal realities that were blossoming right before our eyes.
I remember seeing this giant crystal, and this crystal contained the understanding of DNA and was perfectly holographic and all information in the cosmos was kept here, then as I stood in awe of its perfection it reached out with a crystalline 'Arm' and touch what was once void and in an instant a galaxy evolved from aparrently nothing. Millions of different races spawned in moments...I was faced with what I had always suspected, life birthing life, somehow a respository of information....
I visited the Akashic Records as I had on many occasions though this time the vividness was unsurpassed, many questions I had long pondered were answered.
Remember folks, DMT is endogenous, meaning created in your brain and spinal cord, right now, as you sit and read this.
There were many different facets to the trip, all guided by the most beautiful fractal imagery I have ever witnessed.
I could go on and on but I hope I will leave you with the thirst to find truth.
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.


Public Member Functions | |
| Controller | createController (int controllerType) |
Static Public Member Functions | |
| static ControllerFactory | getInstance () |
| static ControllerFactory | getInstance (IMS model) |
| static void | registerModel (IMS model) |
Static Public Attributes | |
| static final int | MAIN_VIEW = 0 |
| static final int | SEARCH = 1 |
| static final int | LOGIN = 2 |
| static final int | CONFIG = 3 |
| static final int | SELL = 4 |
| static final int | LOGS = 5 |
Class : ControllerFactory.java Author : Larry "Bucky" Kittinger Date : Nov 26, 2012 Desc : Singleton class to produce the controllers for the various views
| Controller w3se.Controller.ControllerFactory.createController | ( | int | controllerType | ) |
method to produce Controller's
| controllerType | - enum of the controller type based on the view (MAIN_VIEW, SEARCH, SELL, LOGIN, CONFIG, LOGS) |
|
static |
Method to obtain the instance of the ControllerFactory
|
static |
method to get the instance of the controller factory
| model | - main model of the system (IMS) |
|
static |
method to register the model to the ControllerFactory
| model | - main model of the system (IMS) |
|
static |
Configurations panel
|
static |
Logon panel
|
static |
Log manage panel
|
static |
Main window of the program
|
static |
Keyword search, Browse Search, or Add/Edit panel
|
static |
Sell Book panel


ReleaseManager.Utils
This module provides helper functions for the mix release
and
mix release.clean
tasks.
Summary↑
| abort!() | Exits with exit status 1 |
| chmod(target, flags) | Change user permissions for a target file or directory |
| debug(message) | Print an informational message without color |
| error(message) | Print an error message in red |
| get_elixir_path() | Get the local path of the current elixir executable |
| get_last_release(project) | Get the most recent release prior to the current one |
| get_releases(project) | Get a list of tuples representing the previous releases: |
| info(message) | Print an informational message in green |
| load_config(env) | Load the current project’s configuration |
| merge(old, new) | Merges two sets of Elixir/Erlang terms, where the terms come in the form of lists of tuples. For example, such as is found in the relx.config file |
| mix(command, env) | Call the _elixir mix binary with the given arguments |
| mix(command, env, atom3) | |
| notice(message) | Print a notice in yellow |
| priv_path() | Get the priv path of the exrm dependency |
| read_terms(path) | Reads a file as Erlang terms |
| rel_dest_path() | Get the rel path of the current project |
| rel_dest_path(files) | Get the path to a file located in the rel directory of the current project. You can pass either a file name, or a list of directories to a file, like: |
| rel_file_dest_path() | Get the rel/files path of the current project |
| rel_file_dest_path(files) | Get the path to a file located in the rel/files directory of the current project. You can pass either a file name, or a list of directories to a file, like: |
| rel_file_source_path() | Get the priv/rel/files path of the exrm dependency |
| rel_file_source_path(file) | Get the path to a file located in priv/rel/files of the exrm dependency |
| rel_source_path() | Get the priv/rel path of the exrm dependency |
| rel_source_path(file) | Get the path to a file located in priv/rel of the exrm dependency |
| relx(name, version, verbosity, upgrade?, dev) | Execute |
| sort_versions(versions) | Sort a list of versions, latest one first. Tries to use semver version compare, but can fall back to regular string compare |
| string_to_terms(str) | Convert a string to Erlang terms |
| warn(message) | Print a warning message in yellow |
| with_env(env, fun) | Perform some actions within the context of a specific mix environment |
| write_term(path, term) | Writes an Elixir/Erlang term to the provided path |
| write_terms(path, terms) | Writes a collection of Elixir/Erlang terms to the provided path |
Functions
Exits with exit status 1
Change user permissions for a target file or directory
Print an informational message without color
Print an error message in red
Get the local path of the current elixir executable
Get the most recent release prior to the current one
Get a list of tuples representing the previous releases:
Examples
get_releases #=> [{"test", "0.0.1"}, {"test", "0.0.2"}]
Print an informational message in green
Load the current project’s configuration
Merges two sets of Elixir/Erlang terms, where the terms come in the form of lists of tuples. For example, such as is found in the relx.config file
Call the _elixir mix binary with the given arguments
Print a notice in yellow
Get the priv path of the exrm dependency
Reads a file as Erlang terms
Get the rel path of the current project.
Get the path to a file located in the rel directory of the current project. You can pass either a file name, or a list of directories to a file, like:
iex> ReleaseManager.Utils.rel_dest_path "relx.config"
"path/to/project/rel/relx.config"
iex> ReleaseManager.Utils.rel_dest_path ["<project>", "lib", "<project>.appup"]
"path/to/project/rel/<project>/lib/<project>.appup"
Get the rel/files path of the current project.
Get the path to a file located in the rel/files directory of the current project. You can pass either a file name, or a list of directories to a file, like:
iex> ReleaseManager.Utils.rel_file_dest_path "sys.config"
"path/to/project/rel/files/sys.config"
iex> ReleaseManager.Utils.rel_dest_path ["some", "path", "file.txt"]
"path/to/project/rel/files/some/path/file.txt"
Get the priv/rel/files path of the exrm dependency
Get the path to a file located in priv/rel/files of the exrm dependency
Get the priv/rel path of the exrm dependency
Get the path to a file located in priv/rel of the exrm dependency
Execute relx
Sort a list of versions, latest one first. Tries to use semver version compare, but can fall back to regular string compare.
Convert a string to Erlang terms
Print a warning message in yellow
Perform some actions within the context of a specific mix environment
Writes an Elixir/Erlang term to the provided path
Writes a collection of Elixir/Erlang terms to the provided path


Select image
Please prepare image and then upload image. Resizing during uploading is currently not supported.