In this tutorial, we'll guide you through some SLATE command line client options and launch a simple edge service.
On the left pane, we have provided an interactive shell that you can use to run SLATE commands and edit configuration files. Let's start by listing all clusters available in this SLATE federation:
slate cluster list
Assuming the client has successfully contacted the SLATE central service, you should see one cluster named 'sandbox'. In a real SLATE federation, you can expect to see many clusters here.
2.At any time you can get information about the capabilities of the slate
client by running it with the --help
option. You can also apply this option to its subcommands (and sub-subcommands) to get more information about them. Running
slate cluster --help
will show you that the cluster subcommand has several other subcommands besides just list
.
To use the resources on the SLATE platform, you must first belong to a group. You can list existing groups with:
slate group list
For the tutorial, you should create your own group. In practice, most users will want to join an existing group for reasons that we'll touch on shortly. You can create your group with the command
slate group create group-name --field technology
where group-name
is the name you choose for your group. Lowercase letters, numbers and dashes are allowed, although the name may not start or end with a dash. --field technology
describes the field of science in which your group will work, but for the demo the exact field does not matter.
In general you cannot use a cluster connected to SLATE without the permission of the cluster owner. Some cluster owners mark their clusters as allowing access for all groups, so you can use them right away, while for others you will need to ask the owners for permission. You can check a given cluster's policies with the slate cluster list-allowed-groups
command, which takes the cluster to query as an argument. If you run
slate cluster list-allowed-groups sandbox
you should see an asterisk (*) indicating that all groups are allowed, including the one you just created.
5.Much like an "app store", the SLATE team curates a catalog of software that can be deployed onto SLATE-enabled clusters. You can check the available applications via:
slate app list
By default, this command only shows "stable" applications. You can view more applications being developed for SLATE if you use the same command with the --dev
flag added.
The application we'll deploy for the tutorial is the Nginx HTTP server. First, you'll want to retrieve the SLATE configuration file for Nginx:
slate app get-conf nginx > my-nginx-settings.yaml
This will download the default settings and place them in a file for you to edit locally.
7.To customize your application settings, open the nginx configuration file (my-nginx-settings.yaml
) with an editor (vi, emacs, and nano are available, choose nano if you are unfamiliar). You should see that nginx has two settings: Instance
and Data
.
Instance
is the label to use to mark the particular application instance so that you can remember what it was for when you look at it later. It follows the same naming rules as for group names, but only needs to be unique within your group. For the tutorial, this basically means you don't have to worry about uniqueness.
Data
is the HTML document that you want ngnix to display. You can change it to whatever you want so that when you run nginx you will be able to see that it is your personalized instance.
When you have your configuration file ready you can install the application instance:
slate app install nginx --group group-name --cluster sandbox --conf my-nginx-settings.yaml
It is necessary to specify the application, which group will own it, on which cluster you want it to be deployed, and which configuration file to use.
Installing may take a few seconds, but you should then get a confirmation that your instance was installed, and the ID that was assigned to it.
9.To see your new application instance in the SLATE system you can run
slate instance list --group group-name
10.To get more information about your instance, including how to access the page that it is serving, use the slate instance info
command, which takes the instance ID as an argument. You should see something like:
$ slate instance info instance_z-A3UUVSfto
Name Started Group Cluster ID
nginx-cnw 2018-Oct-17 cnw sandbox Instance_586f0424-3097-4b86-
23:04:07 8d3b-c4f53ab78e01
UTC
Services:
Name Cluster IP External IP Ports URL
cnw-nginx-cnw <IP_ADDRESS> <IP_ADDRESS> 80:32113/TCP http://cnw-nginx-test.sandbox.slateci.net/
Pods:
cnw-nginx-cnw-55985cfb76-7p4lz
Status: Running
Created: 2018-12-31T20:38:28Z
Host: sandbox.slateci.io
Host IP: <IP_ADDRESS>
Conditions: Initialized at 2018-12-31T20:38:28Z
Ready at 2018-12-31T20:38:30Z
ContainersReady at 2018-12-31T20:38:30Z
PodScheduled at 2018-12-31T20:38:28Z
Containers:
nginx
State: running since 2018-12-31T20:38:29Z
Ready: true
Restarts: 0
Image: docker.io/nginx:1.7.9
Configuration:
Instance: cnw
Ingress:
Class: slate
Subdomain: cnw-nginx-test
Enabled: true
Data: |-

Hello World!

The basic information from the list command is repeated, but you will also see networking information, information about the underlying Kubernetes (and Docker) objects, and the configuration you supplied. In order to view a page on the webserver that you have instantiated, you can use the curl command
$ curl http://cnw-nginx-test.sandbox.slateci.net

Hello world!

Congratulations, you have deployed an edge service!
11.When you are finished with an application instance, you can delete it again:
$ slate instance delete instance_z-A3UUVSfto
Successfully deleted instance instance_z-A3UUVSfto
For more information on using SLATE, such as registering a cluster of your own or obtaining a local development environment, please see the SLATE Quickstart documentation.
When you are finished using this page you can (but do not have to) use exit
to disconnect your terminal. If you want to delete your sandbox environment entirely you can reset it. Otherwise, your environment will be automatically deleted after a few days of inactivity.


Orange Village is a 55+ mobile home park situated behind a beautiful and quiet residential neighborhood in Orange County, just minutes from the 55, 57, and 91 freeways. We're a short walk to restaurants, grocery stores, and other shopping. At least one permanent resident of each mobile home must be 55 years of age or older and all other residents must be at least 18. Orange Village Mobile Home Park is one of the best leased-land communities in Orange County, California. The low monthly lot lease fee covers exclusive tenancy of your own home's private yard and carport as well as use of the community recreational and laundry facilities. Own your own mobile home with attached private parking without the responsibilities of caring for a large yard or the recreational facilities.


List of strings; default is []
[]
The licenses of the output files that this binary generates. This is part of a deprecated licensing API that Bazel no longer uses. Don't use this.


This example demonstrates how to run asynchronous custom validation on a JSON object. The names are checked asynchronously and the results "come in" half a second later. Known names in this example are 'Joe', 'Harry', 'Megan'. For other names, a validation error will be displayed.


Software Engineering Context - Course Work 3
Group Name
:
Team X
Group Topic
:
Computer in Education
Hosted Site URL
:
Computer in Education
Members
:
S.V Damith Asanka Dias - UOW No: 15836270
Selvarajah Vijendran - UOW No: 16088700/1
Kanishka Hewapathirana - UOW No: 16088542/1
Nalin Asanka Jayasekera - UOW No: 16088724/1
Site related
references
:
Distance Learning
History of Distance Learning
What is Blended Learning?
History
Learning models
Pros and cons of blended learning
What is e-learning?
What are the benefits?
Cost effective and saves time
Learning 24/7
Learn about Virtual Learning
Webinar
Webinar
Types of Webinars
Webinar Audiences
Different Types of Webinar Presentations
Different types of webinars you can conduct
Why the launch webinar is a marketing dinosaur
3 Webinars to Grow Your Business
How to increase sales and maximize revenue with travel reviews
Use of Software
Courseware
Educational Software
Assessment Software
Computers in the Classroom
Technology in Classroom
Computers in Classroom
History of Computers in Education
Pros and Cons in Computer Classroom
Technology in the Classroom is Beneficial or Not?


Enter a place name below and click the Search button.
If there is a single match, the map will zoom to that location. If the search lists multiple matches, click one of them in the list to zoom there.
Or, zoom and pan to the area you want using the map controls, then click the map.
To use a precise (non-rectangular) boundary, obtain or create a KML file with the boundary and use the Upload KML button to upload it.
Upload a KML file with boundaries of the area(s) to study.
Click the Browse… button to select your KML file, then Upload to view it.
The KML file should contain one or more <Placemark>
elements with <MultiGeometry>
or <Polygon>
boundaries.


Lauren took to Instagram to celebrate the happy moment, sharing a photo of their baby girl, Bella.
"Look who’s here!" the caption read. "Bella Milagro Duggar was born November 8th, 2019 at 4:24 pm, weighing 6lbs 5oz and 18.5 inches long."
JENNIFER ANISTON GETS A KISS FROM GWEN STEFANI AT THE PEOPLE'S CHOICE AWARDS
"Our hearts are so full," the post continued. "We are so thankful for God blessings us with such a healthy baby girl!"
Lauren's miscarriage was revealed in February, which she said occurred after she began feeling sick.
SHAKIRA TALKS DEPRESSION FOLLOWING 2017 VOCAL CHORD HEMORRHAGE
“I was cramping really, really bad, which was quite strange because I normally don’t," Lauren told Page Six. "I was thinking maybe I had something that had gluten in it. That’s what I was thinking. Well, it was late at night and I went to use the restroom and right there was the baby. Gone.”
Three months later, Lauren, 27, shared the happy news that she was pregnant again.
"We are so excited to announce that baby #2 is on the way," the post read. "It's hard to fully express just how grateful we are for God blessing us again with another precious gift! So, as we rejoice in the life of our second sweet baby, we also remember... our other sweet baby, Asa, in heaven. Good is so incredibly good!"
CLICK HERE TO GET THE FOX NEWS APP
Josiah, 23, previously told Fox News that discussing the miscarriage "helps with the healing," and Lauren explained that she shared her story because she "just wanted to bring hope to a lot of people that go through this — that they’re not alone."


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Exposure
| (1) | (2) | |
| D | 4,614.667** | 5,780.265* |
| (2,018.930) | (2,894.437) | |
| VT | -12.625 | |
| (22.048) | ||
| Constant | 1,009.147* | 931.826 |
| (523.853) | (550.727) | |
| Observations | 20 | 20 |
| R2 | 0.225 | 0.240 |
| Adjusted R2 | 0.182 | 0.150 |
| Residual Std. Error | 499.680 (df = 18) | 509.279 (df = 17) |
| F Statistic | 5.224** (df = 1; 18) | 2.679* (df = 2; 17) |
| Note: | *p<0.1; **p<0.05; ***p<0.01 |


Waqar Younis excited by Pakistan's teenage quicks
Sydney - Pace great Waqar Younis believes Pakistan's young and largely untested fast-bowling attack can cause big problems for Australia in their imminent Test series as the team looks to bounce back from a poor Twenty20 campaign.
Following the retirement of Mohammad Amir and Wahab Riaz this year, Pakistan have brought 16-year-old Nasim Shah and 19-year-old pair Musa Khan and Shaheen Afridi to Australia, along with veteran seamer Imran Khan senior.
While Imran destroyed Australia A in Pakistan's warm-up match in Perth this week with 5-32 in their first innings, Nasim produced eight high-quality overs in the second innings.
Younis, Pakistan's bowling coach, said he saw enough during the match to suggest Nasim and Afridi, in particular, can shine on Australia's hard, fast pitches.
"Of course, that sort of performance (against Australia A) makes you feel that you're not naive being here and you can really do the job," he said in The Sydney Daily Telegraph newspaper on Thursday.
Pakistan dismissed an Australian team featuring Test aspirants Joe Burns, Travis Head, Usman Khawaja, Marcus Harris and Cameron Bancroft for 122 then restricted them to 91 for two in the second innings.
"All those batters have played for Australia or are knocking at the door," added Younis.
"So getting them out early and bowling out the entire team cheaply will probably give us a very good message, that we are here for the business.
"We want to win and we want to challenge this Australian side, so there's definitely confidence."
The first of two Tests against Australia gets underway in Brisbane next week, with Pakistan looking to improve after losing the Twenty20 series 2-0.
Babar Azam and Iftikhar Ahmed, who are both in the Test squad, were the only Pakistan batsmen to make an impact over the short format.
But Younis believes their batting stocks are deep enough to cope with a Test barrage from Josh Hazlewood, Pat Cummins, Mitchell Starc and James Pattinson.
"I don't think Pakistan is worried about facing them or scared of any of them," he said.


InnoGames' lifetime revenues pass €1bn
More than half of this came from Forge of Empires, company has grown revenues every year since 2007
by James BatchelorGerman developer and publisher InnoGames is celebrating a key milestone as its lifetime revenues have passed €1 billion.
The studio was first founded in 2007 and is best known for strategy games such as Grepolis, Tribal Wars and Forge of Empires.
The latter has contributed significantly to the company's achievement, with InnoGames announcing earlier this year that it has generated more than €500 million on its own -- over half InnoGames' lifetime takings.
Grepolis and Tribal Wars, meanwhile, have each made more than €100 million, with 2015 launch Elvenar "[continuing] to catch up fast." The company has seen double-digit percentage growth in revenue ever year since the company was founded.
Initially focused on PC browser titles, InnoGames now reports more than half of its revenues come from mobile, a segment that has grown by an average of 56% year-on-year since 2015 for the company.
Located in Hamburg, InnoGames is home to more than 400 employees, who run seven live games. Playtime for the developer's combined portfolio was reported at 337,723 years.


--- layout: page title: About header-img: "img/about-bg.png" ---
Current student of Flatiron School for web development. Running tests and finding failures daily.


{% extends "base.html" %} {% block title %}Success sending bulk emails.{% endblock %} {% block css %} {% endblock %} {% block main %}
Successfully sent {{ total_sent }} bulk emails!!! Send some more?


Drowning By Numbers (R, 1987) Directed and written by Peter Greenaway. Starring Joan Plowright, Juliet Stevenson, Joely Richardson, Bernard Hill, Jason Edwards.
Peter Greenaway's Drowning By Numbers is such an odd film that I am not sure how to write a review for it. I can start, I guess, by describing the film's basic storyline: three women, all named Cissy Colpitts (Joan Plowright, Juliet Stevenson, Joely Richardson), drown their husbands for various reasons and convince the coroner (Bernard Hill) to declare the deaths accidents by offering the possibility of later sexual favors.
But the story really seems like nothing more than a backdrop for all the film's weird idiosyncrasies. Most notably, the numbers 1 through 100 all appear in the film somewhere.  The characters also play games involving numerics and combinations throughout the film; these games are often introduced with narration from a young child named Smut (Jason Edwards). There are recurring images of insects crawling on rotting food. And it is a safe bet that almost every scene will include at least one dialogue reference to numbers, counting, water, sex, or death.
Director/writer Greenaway does seem to know what he is doing here; Drowning By Numbers is not a case of directorial incompetence, nor is it even a David Lynch-style film in which a story is told through abstract images. Rather, it seems to be a flat refusal on Greenaway's part to play by any established rules of narrative realism. The film exists at a totally detached, intellectual level; Greenaway doesn't seem to want us to really care about what happens as much as he wants us to notice the patterns in the dialogue and admire the photography and color schemes, which often evoke Renaissance painting. As best as I can tell, there is no hidden meaning behind all this, and if there is, then I must say that Greenaway has hidden it a little too well.
Does it work? It's tough to say. Greenaway does stick to the bizarre rules he has set up for himself, so it is at the very least executed correctly. And there were certainly things that I liked about the film. The number sequence was clever and at times hilarious, and it was fun to watch for the numbers and for the recurring patterns in the dialogue in each scene. The imagery was skillfully crafted and many of the scenes possessed a wonderfully surreal quality, particularly those in which a young girl jumps rope outside a house counting the stars while pink lights fade in and out and a deep, spectral sound hums in the background. And Smut's narrations are often amusing in a scratch-your-head kind of way, such as when he explains that "Tuesday is the best day for violent death, because on Tuesday a violent death is marked with yellow paint whereas on all other days it is marked with red paint, except Saturday," at which point he is seen painting yellow streaks around a dead animal on the road.
Yet there was something manipulative about Greenaway's albeit original and distinctive style. It was as if his intellectual detachment backed the audience into a corner, that it would somehow be out of bounds to "dislike" anything in the film because that would be approaching it the wrong way. For example, I would normally criticize a film as emotionally empty as Drowning By Numbers for all its violence and graphic sexual content, but the fact is that the entire film is mostly arbitrary and shies away from the psychological implications of any behavior-violent, sexual, or otherwise. There were a few graphic scenes which seemed like they were probably unnecessary both to the story and to the repeating motifs, but even now I find myself hesitating to criticize them directly because I wonder if Greenaway's film is simply over my head.
Assuming, then, that Drowning By Numbers was nothing more than an attempt to take the bare bones of a linear plot and use it for what amounts to more of a filmed intellectual and artistic exercise than a story with realistic plot and character development, it works most of the time. It is difficult to evaluate this kind of film since it refuses to play by any established rules of moviemaking, but I am tentatively giving it an A-, awarding it points for its well-crafted imagery and the cleverness of the recurring pattens and taking away a few for its borderline-manipulative style. Be warned, however: if I do ever find out that there was supposed to be some deep symbolic meaning underneath all this cinematic strangeness, it stands to lose a few more. Grade: A-
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


◆ __init__()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.__init__ |
( |
|
self, |
|
|
|
model_part, |
|
|
|
settings |
|
) |
| |
Incompressible Fractional Step Navier Stokes formulation.
This RansFormulation solves VELOCITY, and PRESSURE with Fractional Step formulated
incompressible Navier-Stokes equation.
This supports both steady and transient problems, transient with time integration scheme.
It uses wall functions at walls, therefore SLIP flag must be True on all walls (in both conditions and nodes)
Args:
model_part (Kratos.ModelPart): ModelPart to be used in the formulation.
settings (Kratos.Parameters): Settings to be used in the formulation.
◆ AddDofs()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.AddDofs |
( |
|
self | ) |
|
◆ AddVariables()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.AddVariables |
( |
|
self | ) |
|
◆ GetMinimumBufferSize()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.GetMinimumBufferSize |
( |
|
self | ) |
|
◆ GetStrategy()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.GetStrategy |
( |
|
self | ) |
|
◆ Initialize()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.Initialize |
( |
|
self | ) |
|
◆ IsConverged()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.IsConverged |
( |
|
self | ) |
|
◆ PrepareModelPart()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.PrepareModelPart |
( |
|
self | ) |
|
◆ SetConstants()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.SetConstants |
( |
|
self, |
|
|
|
settings |
|
) |
| |
◆ SetTimeSchemeSettings()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.SetTimeSchemeSettings |
( |
|
self, |
|
|
|
settings |
|
) |
| |
◆ SetWallFunctionSettings()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.SetWallFunctionSettings |
( |
|
self, |
|
|
|
settings |
|
) |
| |
◆ SolveCouplingStep()
| def fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.SolveCouplingStep |
( |
|
self | ) |
|
◆ condition_name
| fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.condition_name |
◆ echo_level
| fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.echo_level |
◆ fractional_step_model_part
| fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.fractional_step_model_part |
◆ is_converged
| fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.is_converged |
◆ is_steady_simulation
| fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.is_steady_simulation |
◆ min_buffer_size
| fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.min_buffer_size |
settings string in json format
◆ solver
| fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.solver |
Construct the linear solvers.
◆ solver_settings
| fractional_step_velocity_pressure_rans_formulation.FractionalStepVelocityPressureRansFormulation.solver_settings |
The documentation for this class was generated from the following file:


Created by Zhao Chang / @ChiaoGeek
The project description gives five main problems and I find some solutions to them.
Visualizing the spatial distribution of marginal scores and expressing uncertainty about these estimates
Visualizing whichever joint scores the users are interested in
Displaying static data (raw data) tables and using them to generate all kinds of graphs
Generating secondary graphs and tables of the data underlying the map
Saving results directly from the website
Thank you


Eduardo Guasti Ortiz
Highschool Student & Aspiring DeveloperExperiences
2019present
Lead Proggrammer - First Robotics Team 8230
Arlington Career Center Arlington, VAThe Lead Programmer responsabilities for the Firsts Robotics Team 8230 are:
- Program robot controls
- Program robot movements
- Test all robot movements
- Test electrocnics work correctly with the code
- Communicate any problems that may arise
20172017
Volunteer - Wheels to Africa
Thomas Jefferson Middle School Arlington, VAIn Wheels to Africa, we collected bikes and sent them to Africa. We learned that a bike was as valuable as a car in Africa. While I volunteered we collected bikes that people collected and checked that those bikes were in good conditionto latter ship them to that year's selected community in Africa
Selected Projects
nonenone
No Projects Yet
Some workplace- Lorem ipsum dolor sit amet, consectetur adipiscing elit
- Lorem ipsum dolor sit amet, consectetur adipiscing elit. Proin nec mi ante. Etiam odio eros, placerat eu metus id, gravida eleifend odio. Vestibulum dapibus pharetra odio, egestas ullamcorper ipsum congue ac
- Lorem ipsum dolor sit amet, consectetur adipiscing elit. Proin nec mi ante. Etiam odio eros, placerat eu metus id, gravida eleifend odio
Education
2018present
In Pursuit of Highschool diploma
Arlington Carrer Center - Highschool Arlington, VAI'm currently in highschool, taking classes that are related to the field of Computer Science and Web Development
Certifications
- Microsoft Python Certification


| Number of buildings | Several hundreds | Location of buildings | Sweden | Survey method | web based |
| Collected Data | Energy consumption/Energy related characteristics of building | Type of building(s) | Residential,commercial | Date | 2005-2008 | >
| Survey provider | Swedish energy agancy (STEM) |


§264-78 Interpretation. Nothing in this part shall be construed to abrogate or affect the provisions of any law, ordinance, or regulation which are more restrictive than this part. [L 1966, c 45, pt of §2; HRS §264-78]


An exporter for `PLY`.
[link:https://en.wikipedia.org/wiki/PLY_(file_format) PLY] (Polygon or Stanford Triangle Format) is a
file format for efficient delivery and loading of simple, static 3D content in a dense format.
Both binary and ascii formats are supported. PLY can store vertex positions, colors, normals and
uv coordinates. No textures or texture references are saved.
[name] is an add-on, and must be imported explicitly. See [link:#manual/introduction/Installation Installation / Addons].
import { PLYExporter } from 'three/addons/exporters/PLYExporter.js';
// Instantiate an exporter
const exporter = new PLYExporter();
// Parse the input and generate the ply output
const data = exporter.parse( scene, options );
downloadFile( data );
Creates a new [name].
[page:Object input] — Object3D
[page:Function onCompleted] — Will be called when the export completes. The argument will be the generated ply ascii or binary ArrayBuffer.
[page:Options options] — Export options
Generates ply file data as string or ArrayBuffer (ascii or binary) output from the input object. The data that is returned is the same that is passed into the "onCompleted" function. If the object is composed of multiple children and geometry, they are merged into a single mesh in the file.
[link:https://github.com/mrdoob/three.js/blob/master/examples/jsm/exporters/PLYExporter.js examples/jsm/exporters/PLYExporter.js]


-
There is a new policy on the forums regarding personal attacks against other users on the forums and in the community. Please take a moment and read it by clicking here.
Bug Server crash error for ic2.platform.NetworkManager.initiateTileEntityEvent
Discussion in 'Tekkit Classic Bugs' started by AaronMcH, Nov 18, 2012.


{% extends 'base.html' %} {% load static %} {% block content %}
$1899.99
$2099.99
$2499.99
$2994.99
$1994.99
$3749.99
$1987.99
$2487.99


--- layout: archive title: Zulip Chat Archive permalink: /stream/113489-new-members/topic/building.20mathlib.html ---
The normal workflow with elan
and leanproject
works for me but I am curious about what's involved in building mathlib manually. I just tried lean --make --memory 6000
which is 6GB and hit the limit with src/topology/metric_space/gromov_hausdorff.lean:381:2: error: excessive memory consumption detected at 'replace' (potential solution: increase memory consumption threshold)
. What does it normally take to build mathlib: how much ram, how many compute hours?
In the past I've compiled mathlib with those parameters in about 20 minutes
But it's getting bigger all the time
It takes about 1h50m to build mathlib in our Github Actions workflow. Here's their page on the resources available. Apparently they let us use up to 7 GB of memory.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


Bursa Malaysia slightly better at mid-afternoon
KUALA LUMPUR, Nov 18 — Bursa Malaysia resumed the afternoon session slightly better on buying support in the index-linked counters amid positive market sentiment.
At 3.09pm, the benchmark FTSE Bursa Malaysia KLCI (FBM KLCI) inched up 0.26 of-a-point to 1,595.01 from 1,594.72 at close on Friday.
However, on the broader market, losers led gainers 422 to 324 with 372 counters unchanged, 881 untraded and 17 others suspended.
Turnover amounted to 1.55 billion shares worth RM772.92 million.
Among the heavyweights, Maybank eased one sen to RM8.65, Tenaga shed four sen to RM13.64, Public Bank lost 16 sen to RM19.74, and Petronas Chemicals trimmed six sen to RM7.38.
However, CIMB and IHH rose six sen each to RM5.28 and RM5.41, respectively.
Of the actives, Sapura, Bumi Armada and Borneo Oil were flat at 30 sen, 52.5 sen and 4.5 sen, respectively, while Netx inched up half-a-sen to 2.5 sen.
The FBM Emas Index was 1.72 points higher at 11,315.49, the FBMT 100 Index added 0.11 of-a-point to 11,125.92, the FBM Emas Shariah Index increased 15.33 pints to 11,851.28, and the FBM Ace rose 23.47 points to 4,943.54.
The FBM 70, however, erased 6.94 points to 14,088.54.
Sector-wise, the Financial Services Index lost 29.46 points to 15,582.27, the Industrial Products & Services Index inched down 0.34 of-a-point to 153.04, but the Plantation Index gained 16.87 points to 6,945.41. — Bernama


(meta tag destination set to layout=SampleLayout)
(this is an image uploaded in the zip file.)
Hello Bob, this sentence uses a Mustache-Basic tag to include the user's name.
This is a line that should be removed during upload
This list uses mustache-loop and mustache-delete to create a list of people.
Bob
Ted
Jane
This list of 'staff' is hidden if staff list is empty (not truthy)


\defgroup direct_netcdf_mod direct_netcdf_mod @{
Netcdf IO for a domain. The idea is to be generic rather than having a converter for each module. Also aim to go to the filesystem only once, e.g. \verbatim wrf => dart => wrf \endverbatim rather than \verbatim wrf => wrf_to_dart => dart => dart_to_wrf => wrf \endverbatim
Every task needs the dimensions of each state variable to calculate what it is going to recieve in the IO transpose (this is calculated in add_domain ) \par Aim of the limited transpose:
To limit how much of the state vector you can read at once.
You can limit the transpose by memory using buffer_state_io
.
What you (potentially) gain from this:
If buffer_state_io is false you have the regular transpose + IO, except: 1. You are reading directly from a netcdf file, not a dart state vector file. 2. You only transpose the copies that are being written/read.
This code has multiple places where round-robin layout of state onto task is assumed. These are in the section labelled: \n \verbatim !-------------------------------------------------------- ! Routines that are making the assumption that the ensemble ! distribution is round-robin (distribution type 1) !-------------------------------------------------------- \endverbatim
read_transpose() is the read routine. transpose_write() is the write routine.
Note dart_index is an inout variable to read_transpose() and transpose_write(). This is making the assumption that the calling code is using dart_index in the following way: * dart_index going in to the subroutines is where the domain starts in the state vector. * dart_index coming out of the subroutines is where the domain ends. * The domain is contiguous in the state_vector.
FIXME : should move to assim_model_mod.f90
FIXME: put clamping values with min_val, max_val, valid_range, or whatever the proper CF-range
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| character(len=256), | intent(in) | :: | fname |
Read and transpose variables in cyclic-cyclic distribution (round robbin)
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| type(ensemble_type), | intent(inout) | :: | state_ens_handle | |||
| type(stage_metadata_type), | intent(in) | :: | name_handle | |||
| integer, | intent(in) | :: | domain | |||
| integer, | intent(inout) | :: | dart_index | |||
| logical, | intent(in) | :: | read_single_vars |
This code transposes and writes out the state vector copies This can either be done on a single task or with multiple tasks
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| type(ensemble_type), | intent(inout) | :: | state_ens_handle | |||
| type(stage_metadata_type), | intent(in) | :: | name_handle | |||
| integer, | intent(in) | :: | domain | |||
| integer, | intent(inout) | :: | dart_index | |||
| logical, | intent(in) | :: | write_single_vars | |||
| logical, | intent(in) | :: | write_single_precision |
Creates a template file for single file io Calls the model for any model specific attributes to be written
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| type(ensemble_type), | intent(inout) | :: | ens_handle | |||
| type(file_info_type), | intent(inout) | :: | file_handle |
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| type(file_info_type), | intent(in) | :: | file_handle |
read a single netcdf file containing all of the members and possibly inflation information
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| type(ensemble_type), | intent(inout) | :: | state_ens_handle | ensemble handle to store data |
||
| type(file_info_type), | intent(in) | :: | file_handle | file handle for file names |
||
| logical, | intent(in) | :: | use_time_from_file | read time from file |
||
| type(time_type), | intent(inout) | :: | time | external time |
||
| logical, | intent(in), | optional | :: | pert_from_single_copy | reading single file and perturbing |
write all variable to a single file including all member, and optionally inflation, mean, sd
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| type(ensemble_type), | intent(inout) | :: | ens_handle | |||
| type(file_info_type), | intent(inout) | :: | file_handle |
insert the mean and sd into the input file if the user requests this assumes that the files has already been closed and the variables read in.
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| type(ensemble_type), | intent(inout) | :: | ens_handle | |||
| type(file_info_type), | intent(inout) | :: | file_handle |
Read in variables from start_var to end_var
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| integer, | intent(in) | :: | ncfile_in | |||
| real(kind=r8), | intent(inout) | :: | var_block(:) | |||
| integer, | intent(in) | :: | start_var | |||
| integer, | intent(in) | :: | end_var | |||
| integer, | intent(in) | :: | domain |


DESIGN TO WEB BLOG
3RD JUNE 2016
What a responsive site is, and why responsiveness is important.
A responsive site is a site that will automatically change its content size to fit within your screen size. For example, when you view Sephora on a desktop versus on a mobile phone the size of content is smaller on a phone and the layout is rearranged to a single column. If the site wasn’t responsive then when you view the site on a phone, content will overflow and the sizing would be too large for readability. This is why responsive sites are important, so that contents will automatically resize to fit the screen size it’s being viewed on.
What mobile first design is, and why it's important.
This concept refers to going from a small screen design to a big screen design. With mobile devices becoming more technological and having better functions, particularly in viewing websites, there came a need to design webpages that were more suited for viewing on the phone. The idea of mobile first design refers to thinking, designing and creating designs of webpages to be viewed on a small mobile device, and then altering the design to suit a larger screen size. Because a webpage viewed on a phone is much smaller than on a tablet or desktop, it would be easier to add extra features to websites on a desktop than take away to fit everything on a smaller screen while maintaining functionality.
What frameworks are, and their pros and cons.
CSS frameworks are codes that are prewritten that you can use to style your webpages.
Pro: they save time as many of the styles are already prefixed so you don’t have to individually change each attribute to style your webpage.
Cons: if you want to style your content in a way that is different to the framework you will have to overwrite the code in the framework.
What a wireframe is and why we use it.
Wireframes are like blueprints of your website before you design it. They show the main locations of where content, headings, images and navigation will be. This helps to give an idea of what the final product will look like and you have a reference to check back to ensure you are going on the right path in creating your webpage without straying from the original design. However if you find that an element isn’t working you can always move it around, you don’t have to follow the wireframe 100% if you find it doesn’t work well live.
The aspects of your wireframes you found difficult to implement, and why.
Creating columns, the concept too me a while to understand. I got it to work on my webpage but I’m not exactly sure I’m doing it right or understand how it’s working. I found it difficult to position the nav bar and content in a way that used the negative space well. Also it was hard to find a correct font size that was big enough so you can see read the blog but also not too big that it became crowded. The heading took a while to do because it was hard to position it correctly. And I found that my nav bar would have to be positioned differently than in the wireframe to fit a smaller screen size.


Plugin Information |
|---|
View ChuckNorris on the plugin site for more information. |
Displays a picture of Chuck Norris (instead of Jenkins the butler) and a random Chuck Norris 'The Programmer' fact on each build page.
Download & Installation
You can preferably install this plugin directly from the Plugins Update Center, or if need be by downloading the latest .hpi and install it from the Manage Plugins menu.
Usage
- After installing the plugin, go to job configuration page, a checkbox with the text 'Activate ChuckNorris' should appear.
- Tick the checkbox and save the configuration. For freestyle job, Chuck Norris image (along with a random quote) will appear on the job page.
- Run a build. After it's completed, Chuck Norris image (and the random quote) should also appear on the build page. This is applicable for both freestyle and Maven jobs.
Screenshots
FAQ
Q: I'm getting NonExistentFieldException in Hudson log file, how to fix this problem?
hudson.util.RobustReflectionConverter doUnmarshal
WARNING: Skipping a non-existent field fact
com.thoughtworks.xstream.converters.reflection.NonExistentFieldException: No such field hudson.plugins.chucknorris.RoundhouseAction.fact
A: Upgrade to ChuckNorris Plugin 0.4 or newer. That should get rid of the exception message.
Testimonials
- Uncle Bob Martin said ChuckNorris Plugin is very motivating .
- Fabrizio Giudici said Kick your bugs in the ass!
- John Ferguson Smart mentioned ChuckNorris Plugin in Kickass Hudson Plugins
Credits
Chuck Norris 'The Programmer' facts and Emotional Hudson Plugin.
Attachments:
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I had done ecstacy once before, and I wanted more than anything to repeat the experience. My friend picked up some white double stacked pills with white triangles on them, that we were told contained MDMA. I took the pill around 11AM in my house with one friend. We both had a pretty laid back mindset, and neither of us had consumed any other drugs that day.
The substance first kicked in around 11:45, with this hazy sensation that seemed like a very supressed and unintense roll. However, I was not the slightest bit happy, which was the first red flag that something was not right. I tried dancing to some trance that we had playing, but I did not want to listen to music, and dancing made me feel sick. I also refused to drink water, and I felt like I was going to throw up. I figured it was just a lot of caffeine or something, until I looked at my bulletin board on my wall. I saw words, but somehow I just couldn't read them. I became increasingly confused and felt increasingly sick over the next 10 minutes. Suddenly I felt extremely feverish and wanted more than anything to take off all my clothes and cover myself in ice. Anyone who has ever rolled will know that that is about the last thing you want to do while you are rolling.
I went downstairs in search of my desired ice cubes, but I couldn't make it down the stairs without throwing up my breakfast. I felt sicker than ever, and layed down on the cold tile floor. My friend felt my forehead and immediately got some cold rags to put on my naked body in hopes of lowering my body temperature. I became delirious, my vision blurred, and I was shaking horribly. I stayed on that cold tile floor with my friend changing the rags for almost two hours. I thought I felt my temperature going down a bit, so we decided to drive back to his house. After being outside fully clothed, I began to feel feverish again. I threw up once on the side of the road and once more at my friend's house. We repeated the drill with the rags for another hour, until I thought I was feeling better. At this point we agreed it would be best for both of us to go do something, since we could feel the sickening effects of the drug wearing off. We decided to go see a movie, which we did.
After about 20 minutes of sitting in the theater, I was shivering so badly that I needed to leave my seat. At this point I felt like I was freezing, my lips were blue, and my hands were ice. I spent a good 30 minutes in the women's restroom running my hands under the hot water, and huddling underneath the heated hand dryers. After the effects wore off, I realized how lucky I was for surviving outside of a hospital. I really did feel like I was dying in those few hours of lying on the floor, and I am pretty sure that my body temperature was well above 104 degrees.
Since this experience I have avoided all pills that were not manufactured and given to me with a label. I realized that I have no idea what is in a pill that someone may tell me 'ecstacy'. After doing my research I am almost positive that the substance in that pill was PMA, though I can not be 100% sure.
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.


Air Arabia in US$14b deal to buy 120 Airbus A320s
DUBAI, Nov 18 — Air Arabia said today it would buy 120 Airbus A320s in a deal worth US$14 billion (RM58.1 billion) that represents a major expansion for the United Arab Emirates low-cost carrier.
“The first delivery is expected to start in 2024,” said Adel al-Ali, the CEO of Air Arabia, based in the emirate of Sharjah which borders Dubai.
Air Arabia currently operates a total fleet of 53 Airbus A320 and A321 aircraft.
Last month it announced an agreement with Abu Dhabi-based giant Etihad Airways to launch a new low-cost airline based in the UAE capital.
The new carrier, Air Arabia Abu Dhabi, will be launched in “due course”, Etihad said at the time.
Etihad, established in 2003 by the oil-rich Gulf emirate’s government, has faced stiff competition from Dubai aviation giant Emirates and Doha-based Qatar Airways. — AFP


OLX is the world's leading classifieds platform which provides local communities in high-growth markets with vibrant online marketplaces: OLX connects local people to buy, sell or exchange used goods and services by making it fast and easy for anyone to post a listing through their mobile phone or on the web.
Every month, hundreds of millions of people in local markets around the world are already using OLX's online marketplace to find and sell a wide range of products, including computers, cell phones, furniture, sporting goods, services, cars, real estate, and many more.


NLP for document clustering and topic extraction
Natural Language Processing (Latent Semantic Analysis) for topic extraction and modelling
https://github.com/vitalv/doc-clustering-topic-modeling
#Make a pretty pyramid with the imported modules :-)
import csv
%matplotlib inline
import numpy as np
import pandas as pd
import seaborn as sb
from irlb import irlb
from scipy import stats
from scipy import sparse
import matplotlib.pyplot as plt
from sklearn.manifold import TSNE
from sklearn.cluster import KMeans
import scipy.cluster.hierarchy as sch
import matplotlib.patches as mpatches
import scipy.spatial.distance as scdist
from IPython.display import display, HTML
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import Normalizer
#from sklearn.naive_bayes import MultinomialNB
from sklearn.decomposition import TruncatedSVD
sb.set_style("whitegrid", {'axes.grid' : False})
import statsmodels.sandbox.stats.multicomp as mc
from sklearn.metrics.pairwise import cosine_similarity
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.metrics import silhouette_score, silhouette_samples
Read and format data
Read vocabulary file
def read_vocab(vocab_file_name):
'''Reads vocabulary file into a list'''
return [w.strip() for w in open(vocab_file_name)]
Read docword.txt into a document x word matrix
def read_docword(file_name):
'''
Reads docword txt file into a Document-Term Matrix (DTM)
The full DTM will be too large to hold in memory if represented as a dense matrix. Use Scipy sparse instead
Matrix multiplication involving the sparse representation is rapid thanks to algorithms that avoid explicitly
performing multiplications by 0 (nNMF or SVD for instance involve matrix multiplication)
'''
file_handle = open(file_name)
reader = csv.reader(file_handle, delimiter=' ')
D = int(next(reader)[0])
W = int(next(reader)[0])
N = int(next(reader)[0])
#create numpy DTM (Document-Term Matrix)
m = np.empty(shape=[D,W], dtype='int8')
#instead of creating a sparse matrix and then fill it up, create a numpy matrix
#and then later convert it to csr -> SparseEfficiencyWarning
#m = sparse.csr_matrix( (D,W), dtype='int8')
'''
Note: this is not an efficient way to fill in the matrix.
TO DO: Create first the array for each document and then fill the whole array at once
'''
for row in reader:
D_i = int(row[0])-1
W_i = int(row[1])-1
count = int(row[2])
m[D_i, W_i] = count
m = sparse.csr_matrix(m)
return D,W,N,m
docword_file = 'data/docword.kos.txt'
D,W,N,DTM = read_docword(docword_file)
vocab_file = 'data/vocab.kos.txt'
vocab = read_vocab(vocab_file)
TF-IDF: term frequency inverse document frequency
TFIDF is a more reliable metric than plain frequency because it normalizes frequency across documents. Very common (and semantically meaningless) words like articles (‘the’, ‘a’, ‘an’ …), prepositions, etc… are in this way given less weight and filtered out
tfidf_transformer = TfidfTransformer()
DTM_tfidf = tfidf_transformer.fit_transform(DTM)
Document Clustering and Topic Modeling
Now comes the interesting part
This is an unsupervised document clustering / topic extraction. We have no previous knowledge on the number of topics there are in every corpus of documents.
A conventional approach involves an -optional- initial step of LSA (Latent Semantic Analysis) (TruncatedSVD) for dimensionalty reduction followed by K-Means. The downside to this approach in this scenario is that it requires a predefined number of clusters, which is not available
There might not be an optimal number of clusters with complete separation, but there are ways to assess/approximate it. The ‘elbow’ method consists of plotting a range of number of clusters on the x axis and the average within-cluster sum of squares in the y axis (as a measure of within cluster similarity between its elements). Then an inflexion point would be indicative of a good k
Another option to estimate an initial number of clusters consists of running a hierachical clustering and plot a dendrogram. Depending on the method and metric different results can be achieved.
If a good candidate for k is found K-Means can be re-run using it as input. In addition, several K-Means runs are advised since the algorithm might end up in a local optima.
Another approach would be to use a different clustering algorithm not requiring a predefined number of clusters: Means-shift, for instance . But this has not provided good results in this scenario (1 or 2 big groups)
SVD/LSA
TruncatedSVD implements a variant of singular value decomposition (SVD) that only computes the k largest singular values, where k is a user-specified parameter.
When truncated SVD is applied to term-document matrices (as returned by CountVectorizer or TfidfVectorizer), this transformation is known as latent semantic analysis (LSA), because it transforms such matrices to a “semantic” space of low dimensionality.
In particular, LSA is known to combat the effects of synonymy and polysemy (both of which roughly mean there are multiple meanings per word), which cause term-document matrices to be overly sparse and exhibit poor similarity under measures such as cosine similarity.
TruncatedSVD transformer accepts scipy.sparse matrices without the need to densify them, as densifying may fill up memory even for medium-sized document collections.
The appropriate value of s is a matter of debate, and is application-dependent. Smaller values of s represent a greater extent of dimensionality reduction at the cost of a loss of structure of the original DTM. Values anywhere from 30 to 300 are commonly used.
In practice, using a cumulative scree plot to select s so that roughly 75–80% of the original variance is recovered tends to strike a good balance
#kos W/5 -> 83%
n_components = W/5
svd = TruncatedSVD(n_components)
# DTM_tfidf results are normalized. Since LSA/SVD results are
# not normalized, we have to redo the normalization:
normalizer = Normalizer(copy=False)
lsa = make_pipeline(svd, normalizer)
%time \
DTM_tfidf_lsa = lsa.fit_transform(DTM_tfidf)
print("Explained variance of the SVD step: {}%".format(int(svd.explained_variance_ratio_.sum() * 100)))
CPU times: user 32.2 s, sys: 13.9 s, total: 46.1 s
Wall time: 10.4 s
Explained variance of the SVD step: 83%
For the kos dataset, LSA (n_components = W/5 explaining 83% of the original variance)
reduces the size of the DTM from shape (3430, 6906) to (3430, 1381)
K-Means
K-Means separates samples in n groups of equal variance
first step chooses the initial centroids (k, the number of clusters)
After initialization, K-means consists of looping between the two other steps:
The first step assigns each sample to its nearest centroid.
The second step creates new centroids by taking the mean value of all of the samples assigned to each previous centroid
The inertia or within-cluster sum-of-squares is minimized
Try to find optimal number of clusters for k-means. “Elbow” method
Run this ‘elbow’ plot on the LSA reduced DTM_tfidf for the smaller datasets: kos and nips
Run it on the super-reduced irlb DTM_tfidf for the larger datasets enron nytimes and pubmed
k_range = range(2,20)
kms = [KMeans(n_clusters=k, init='k-means++').fit(DTM_tfidf_lsa) for k in k_range]
centroids = [X.cluster_centers_ for X in kms]
labels = [km.labels_ for km in kms]
#calculate Euclidean distance from each point to cluster center
k_euclid = [scdist.cdist(DTM_tfidf_lsa, c, 'euclidean') for c in centroids]
dist = [np.min(ke, axis=1) for ke in k_euclid]
#Total within cluster sum of squares
wcss = [sum(d**2) for d in dist]
#average wcss
avwcss = [(sum(d**2))/len(d) for d in dist]
#total sum of squares
tss = sum(scdist.pdist(DTM_tfidf_lsa)**2)/DTM_tfidf_lsa.shape[0]
#between cluster sum of squares:
bss = tss - wcss
#plot average wcss vs number of clusters "Elbow plot": look for a point where the rate of decrease in wcss sharply shifts
plt.subplots(figsize=(18, 12)) # set size
plt.plot(k_range, avwcss, '-o')
plt.ylabel("average wcss")
plt.xlabel("k")
Not very clear elbow? Check out the Silhouette scores
silhouette_avg_scores = [silhouette_score(docword_tfidf, l) for l in labels]
print silhouette_avg_scores
[0.019074356579233953, 0.023240564880013723, 0.024028296812336956, 0.025919575579062177, 0.026861760217288647, 0.013321506889758637, 0.013536290635032448, 0.01451164797130685, 0.014830797754892374, 0.013388411008660303, 0.012483410542328629, 0.015275226554560749, 0.027228038459763966, 0.012797013871169995, 0.013817068993089826, 0.014762985936250679, 0.01653236589461024, 0.014915275197301334]
Initialize KMeans object
k = 8
#these are all default options (except for k)
km = KMeans(algorithm='auto',
copy_x=True,
init='k-means++',
max_iter=300,
n_clusters=k,
n_init=10,
n_jobs=1,
precompute_distances='auto',
random_state=None,
tol=0.0001,
verbose=0)
Compute KMeans on the TFIDF matrix
%time km.fit(DTM_tfidf_lsa)
CPU times: user 5.71 s, sys: 3.33 s, total: 9.04 s
Wall time: 4.37 s
KMeans(algorithm='auto', copy_x=True, init='k-means++', max_iter=300,
n_clusters=8, n_init=10, n_jobs=1, precompute_distances='auto',
random_state=None, tol=0.0001, verbose=0)
Sort cluster centers by proximity to centroid
clusters = km.labels_
k_centers = km.cluster_centers_ #Coordinates of cluster centers [n_clusters, n_features]
original_space_centroids = svd.inverse_transform(k_centers)
order_centroids = original_space_centroids.argsort()[:, ::-1] #argsort returns the indices that would sort an array
Print Cluster index and n words (closest to centroid) associated
lsa_cluster_topics = {}
for c in range(k):
topic = ','.join([vocab[i] for i in [ix for ix in order_centroids[c, :5]]])
lsa_cluster_topics[c] = topic
print "Cluster %i: " % c + topic
Cluster 0: iraq,war,bush,iraqi,military
Cluster 1: dean,clark,edwards,kerry,lieberman
Cluster 2: party,nader,democratic,ballot,state
Cluster 3: bush,administration,president,kerry,general
Cluster 4: november,account,electoral,turnout,governor
Cluster 5: kerry,bush,poll,percent,voters
Cluster 6: november,voting,account,electoral,governor
Cluster 7: house,senate,race,elections,district
This takes forever without dim red. Use DTM_tfidf_lsa instead of DTM_tfidf Note also that DTM_tfdif_lsa, unlike DTM_tfidf, is not sparse anymore. No need to convert to dense format!
Silhouette Coefficients range between [-1,1]. Values near +1 indicate that the sample is far away from the neighboring clusters. A value of 0 indicates that the sample is on or very close to the decision boundary between two neighboring clusters and negative values indicate that those samples might have been assigned to the wrong cluster.
These values are not good, but this measure seems to suffer from the phenomenon called “Concentration of Measure” or “Curse of Dimensionality”
Check http://scikit-learn.org/stable/auto_examples/text/document_clustering.html
Term enrichment analysis
def enrich(document_term_matrix, doc_idxs, n_terms_in_corpus):
'''
uses scipy.stats hypergeometric test to extract probabilities (p-values) of term enrichment in a group of documents
groups can be defined for instance from the K-Means analysis
uses absolute count frequencies not tfidf (tfidf are already document-normalized)
'''
DTM = document_term_matrix
enrichment = pd.DataFrame(columns=["word", "word_count_in_cluster", "n_words_in_cluster", "word_count_in_corpus", "n_words_in_corpus", "p-val" ])
word_idx = DTM[doc_idxs].nonzero()[1]
word_idx = np.unique(word_idx)
for i in range(len(word_idx)):
t = word_idx[i]
n_terms_in_cluster = len(DTM[doc_idxs].nonzero()[1])
term_count_in_cluster = DTM[doc_idxs,t].sum()
term_count_in_corpus = DTM[:,t].sum()
p = stats.hypergeom.sf(term_count_in_cluster, n_terms_in_corpus, n_terms_in_cluster, term_count_in_corpus)
enrichment.loc[i] = [vocab[t], term_count_in_cluster, n_terms_in_cluster, term_count_in_corpus, n_terms_in_corpus, p]
#Multiple hypothesis correction, transform p-values to adjusted p-values:
reject, adj_pvalues, corrected_a_sidak, corrected_a_bonf = mc.multipletests(enrichment["p-val"], method='fdr_bh')
enrichment["adj_pval(BH)"] = adj_pvalues
enrichment = enrichment.sort_values(by='adj_pval(BH)').head(10)
return enrichment
cl0_doc_idxs = [c[0] for c in enumerate(clusters) if c[1] == 0]
#Remember N is the total nonzero count values in corpus
#It can be estimated as well as: len(DTM.nonzero()[1])
cluster0_enrichment = enrich(DTM, cl0_doc_idxs, N)
HTML(cluster0_enrichment.to_html())
| word | word_count_in_cluster | n_words_in_cluster | word_count_in_corpus | n_words_in_corpus | p-val | adj_pval(BH) | |
|---|---|---|---|---|---|---|---|
| 3955 | petraeus | 23 | 59975 | 23 | 353160 | 0.0 | 0.0 |
| 2873 | iraq | 1574 | 59975 | 2217 | 353160 | 0.0 | 0.0 |
| 3032 | kufa | 12 | 59975 | 12 | 353160 | 0.0 | 0.0 |
| 3033 | kurdish | 20 | 59975 | 20 | 353160 | 0.0 | 0.0 |
| 4953 | shrine | 14 | 59975 | 14 | 353160 | 0.0 | 0.0 |
| 1375 | dearborn | 11 | 59975 | 11 | 353160 | 0.0 | 0.0 |
| 3173 | lindauer | 15 | 59975 | 15 | 353160 | 0.0 | 0.0 |
| 175 | alhusainy | 12 | 59975 | 12 | 353160 | 0.0 | 0.0 |
| 3279 | maj | 12 | 59975 | 12 | 353160 | 0.0 | 0.0 |
| 2334 | gharib | 10 | 59975 | 10 | 353160 | 0.0 | 0.0 |
cl1_doc_idxs = [c[0] for c in enumerate(clusters) if c[1] == 1]
cluster1_enrichment = enrich(DTM, cl1_doc_idxs, N)
HTML(cluster1_enrichment.to_html())
| word | word_count_in_cluster | n_words_in_cluster | word_count_in_corpus | n_words_in_corpus | p-val | adj_pval(BH) | |
|---|---|---|---|---|---|---|---|
| 2119 | lieb | 14 | 23087 | 14 | 353160 | 0.000000e+00 | 0.000000e+00 |
| 645 | clark | 625 | 23087 | 820 | 353160 | 0.000000e+00 | 0.000000e+00 |
| 942 | dean | 1278 | 23087 | 1798 | 353160 | 0.000000e+00 | 0.000000e+00 |
| 1193 | edwards | 681 | 23087 | 1127 | 353160 | 0.000000e+00 | 0.000000e+00 |
| 2120 | lieberman | 354 | 23087 | 459 | 353160 | 4.702023e-320 | 3.903619e-317 |
| 1589 | gephardt | 367 | 23087 | 530 | 353160 | 2.941865e-302 | 2.035280e-299 |
| 1935 | iowa | 351 | 23087 | 597 | 353160 | 8.080964e-252 | 4.792012e-249 |
| 2821 | primary | 520 | 23087 | 1528 | 353160 | 4.658350e-225 | 2.417102e-222 |
| 2015 | kerry | 886 | 23087 | 4679 | 353160 | 3.503594e-181 | 1.615935e-178 |
| 2038 | kucinich | 165 | 23087 | 214 | 353160 | 1.021201e-150 | 4.239004e-148 |
Hierarchical clustering
#sklearn.metrics.pairwise cosine_similarity
dist = 1 - cosine_similarity(DTM_tfidf_lsa)
#Then get linkage matrix
linkage_matrix_ward = sch.ward(dist)
#And then plot the dendrogram
dendro_color_threshold = 0.12 #default: 0.7
fig, ax = plt.subplots(figsize=(15, 20)) # set size
ax = sch.dendrogram(linkage_matrix_ward, orientation="left",color_threshold=dendro_color_threshold*max(linkage_matrix_ward[:,2]));
plt.tick_params(\
axis= 'x', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
bottom='off', # ticks along the bottom edge are off
top='off', # ticks along the top edge are off
labelbottom='off')
plt.title(docword_file + "\n" + "Dendrogram color threshold: %s"%dendro_color_threshold)
plt.tight_layout() #show plot with tight layout
plt.show()
Dimensionality Reduction and Plot
TSNE
t-SNE is a machine learning technique for dimensionality reduction that helps you to identify relevant patterns. The main advantage of t-SNE is the ability to preserve local structure. This means, roughly, that points which are close to one another in the high-dimensional data set will tend to be close to one another in the chart. t-SNE also produces beautiful looking visualizations.
tsne_cos = TSNE(n_components=2,
perplexity=30,
learning_rate=1000,
n_iter=1000,
metric='cosine',
verbose=1)
dist = 1 - cosine_similarity(DTM_tfidf_lsa)
tsne_cos_coords = tsne_cos.fit_transform(dist)
[t-SNE] Computing pairwise distances...
[t-SNE] Computing 91 nearest neighbors...
[t-SNE] Computed conditional probabilities for sample 1000 / 3430
[t-SNE] Computed conditional probabilities for sample 2000 / 3430
[t-SNE] Computed conditional probabilities for sample 3000 / 3430
[t-SNE] Computed conditional probabilities for sample 3430 / 3430
[t-SNE] Mean sigma: 0.008588
[t-SNE] KL divergence after 100 iterations with early exaggeration: 1.530214
[t-SNE] Error after 250 iterations: 1.530214
def scatter(x, labels, cluster_topics):
n_labels = len(set(labels))
palette = np.array(sb.color_palette("hls", n_labels )) # color palette with seaborn.
f = plt.figure(figsize=(18, 12))
ax = plt.subplot(aspect='equal')
sc = ax.scatter(x[:,0], x[:,1], linewidth=0, s=40, color=palette[labels])
#ax.axis('off')
ax.axis('tight')
txts = []
color_patches = []
for i in range(n_labels):
# Position of each label
patch = mpatches.Patch(color=palette[i], label= "Cluster %i "% i + " " + cluster_topics[i])
color_patches.append(patch)
xtext, ytext = np.median(x[labels == i, :], axis=0)
txt = ax.text(xtext, ytext, str(i), fontsize=18)
txts.append(txt)
plt.legend(handles=color_patches, bbox_to_anchor=(1.04,1), loc="upper left", fontsize=14)
plt.subplots_adjust(right=0.60)
plt.title(docword_file + "\n" + "k = %s" %len(set(km.labels_)), fontsize=16)
plt.show()
scatter(tsne_cos_coords, km.labels_, lsa_cluster_topics)


Man found guilty of Sexual Battery in Lehigh Acres case
by WFTX Digital TeamLEHIGH ACRES, Fla. — In December of 2018, the Lee County Sheriffs Office arrested a person believed to have sexually battered a child in Lehigh Acres.
Police arrested David Anthony Flowers, 39 and charged him one count of Engaging in an Act Which Constitutes Sexual Battery Upon or With a Child 12 Years of Age or Older but Younger than 18 Years of Age by a Person in a Familial or Custodial Authority.
Flowers faces up to life in prison when he is sentenced on December 23rd.


Phase 0 Blog: Post 2
Positioning in CSS
May 12, 2015
There are four main positions you need to know about in CSS
Static
Static positioning is the default for every HTML element in CSS. The elementes adhere only to the flow of the page, and you can't change their position using the "top, right, bottom, left" values.
Fixed
Fixed elements are removed from the normal flow of the page. This allows them to overlap other elements and stay in the same position relative to the browser window no matter what.
Think of it like when you're reading an article on the internet and an advertisement pops up on the page. Sometimes it just stays there even if you're scrolling down and trying to move it out of the way. You can also think of a less annoying example as a sidebar that stays the same despite scrolling or resizing the browser.
Relative
This position is called relative because it moves the element based on its static/default position. When you add parameters like "top, right, bottom, left" you can think of it as the elements moving whatever measurement and dirrection you specified away from the default position.
Absolute
This means that the element is placed relative to its parent element. Often elements are given absolute positioning in order to be moved precisely inside a relatively positioned element.
It's good to note that if there is no parent element, the abolute positioned element is positioned as if the html itself, or the entire broswer window, is the parent element.
I hope this was informative and made sense, and happy coding!


The SMS Receiver API notifies an app that an SMS message was delivered to the user's phone, but only if the message was addressed to the app's origin.
In this section, describe the API's purpose and usage cases in a bit more detail — why was a need recognized for it? What problems does it solve? What concepts does it involve? How do you use it, from a high level perspective?
Don't go into a lot of detail in this section, and don't include code examples. If there are a lot of concepts to explain to explain around this API, you should explain them in a separate "Concepts..." article (e.g. WebVR concepts). For a practical usage guide with code examples, you should include a "Usage..." article in your API docs (e.g. Using the WebVR API).
To help improve content discoverability and {{Glossary("SEO")}}, keep the following tips in mind:
SMSReceiver
>Fill in a simple example that nicely shows a typical usage of the API, then perhaps some more complex examples (see our guide on how to add code examples for more information).
This text should be replaced with a brief description of what the example demonstrates.
my code block
If you've included an example directly in the page as shown above, and that example is longer than 4-5 lines or so, consider following the example with a step-by-step explanation of what it's doing, so that new programmers can learn more easily, and to help smooth the learning curve for complicated subjects.
And/or include a list of links to useful code samples that live elsewhere:
| Specification | Status | Comment |
|---|---|---|
| {{SpecName('SMS Receiver API')}} | {{Spec2('SMS Receiver API')}} | Initial definition. |
{{Compat("api.SMSReceiver")}}


--- layout: post title: Lights Control Update date: 2016-12-16 07:15:48.000000000 -05:00 type: post published: true password: '' status: publish categories: [] tags: [] meta: _edit_last: '1' pblog_featured: 'no' author: Timothy Lock ---
It has been a busy term, but it is finally coming to an end. That doesn't mean that I didn't get anything done in that time, though!
I can finally say that a working addition has been added to my home monitoring system - light control. With this new update, I am able to control several lights in my house with the raspberry pi (which is already running the home monitoring system).
In addition to this, I have used my new-found skills from CSC309 (web programming course) to completely rewrite the backend in nodejs. This is a significant improvement from the previous implementation which used python (with flask) as well as separate shell scripts, etc to serve the data to the clients (the control panels in this case). Because everything is integrated into the nodejs server and the fact that it is asynchronous, the overhead in the updating of sensor data is significantly reduced and allows for the web UI to refresh on shorter intervals (100ms compared to 500ms with 3 control panels) without bringing the Raspberry Pi to a grinding halt. It is worth noting that the front end did not change (as much).
The Light Control addition on the web control panel
The existing main UI. Settings and History have still yet to be implemented
An example of the light control in action
So now you're probably asking: "Tim, how did this work?"
The answer is that this new update required an addition of a relay module to control the lights. Originally I intended to send commands through wifi to Arduinos which would then control relays at the destination. I did not have a WiFi module with me at that time so I decided to put the relay module in the same box as the Pi and send the 12V through CAT5 cables that are wired throughout the house (built into the walls). I did some searching on the internet and determined that this was a viable option and that the voltage drop would not affect my LED lights as much. I played it safe and used multiple lines in the CAT5 cable to transport the electricity for minimal resistance and thermal issues.
The system box. The circuit board on the top is the original alarm system board.
Overall, this change in backend and the update is holding well. Nothing has crashed or caught on fire so I am happy with this new modification! :)
In the future, I have plans to integrate "presets/Profiles", webcam integration (its actually connected right now and can work on its own), ftp, and anything else that comes to mind!
Of course, the code can be found on my github here.


Today marks the 50th joke, so to celebrate I’m writing up the complete list. Most of the jokes here were ones we made up without looking at the internet; but occasionally, in an effort to have two new jokes every day, we picked some classics.
Q: What kind of parade did the astronauts throw for the computers after the mission?
A: A Turing tape parade!
Q: Why was the maths book sad?
A: It had too many problems.
Q: What did the AI say to the category theorist?
A: Does not commute!
(from Andy Kitchen)
Q: How did the OR programmer solve a MIP while also eating?
A: By using a brunch and bound technique.
[“hip”, “hip”]
Q: What do measure theorists and programmers have in common?
A: They both enjoy continuous integration.
Old mathematicians never die, they just lose some of their functions.
Q: Why did the computer keep sneezing?
A: It had a virus.
Q: Why wasn’t the complex beer successful?
A: People had trouble ordering it!
Q: Why did the functional programmer return her TV?
A: Because it was immutable.
Q: What do ruby and librarians have in common?
A: They both have explicit return policies.
A shepherd was out in the field counting her sheep; she counted 96 but when she rounded them up she had 100.
(from Two Lost Boys)
Q: Why was the computer owner so successful at sheep husbandry?
A: She had excellent RAM.
Q: Why couldn’t the formal system complete it’s homework?
A: It was trying to be consistent.
404: Joke Not Found.
Q: How does a lumberjack mathematician cut down trees?
A: With her Axiom.
Q: Why did the programmer go to her bookshelf before leaving her house?
A: She needed to get her keys from the dictionary.
Q: Why don’t you want to fight an OR consultant?
A: They are experts at duals.
Q: What did the Linux system administer for the programmer’s head cold?
A: Sudo ephedrine
Q: How did the physicist fix her car when it was failing intermittently?
A: She used statistical mechanics!
Q: Why was the bad python programmer so rich?
A: Because everytime his code failed he got a raise.
Q: What do python programmers and event planners have in common?
A: They both like to decorate functions.
Q: Why is 0 the boss?
A: Because no other number can go above it!
Q: What did the mathematician say when they discovered a new prime number?
A: That’s odd.
Q: Why did the low-rank matrix go to the psychologist?
A: Because it was having an identity crisis!
Q: What is a floating point numbers favourite type of tennis?
A: Doubles!
Q: What does a blender and the Kalman filter hav in common?
A: They both perform a smoothing function!
Q: What is the mathematicians favourite kitchen item?
A: Derivasieve.
Q: Why don’t elephants use computers?
A: Scared of the mouse.
Q: Why was the OR consultant unwell?
A: She want on a benders.
Q: What is a statisticians favourite genre of music?
A: Drum and Bayes.
Q: What is a pet store operatores favourite state in a multiplayer game?
A: The Parrot optimal state.
Q: What is the enterprise java programmers favourite business book?
A: Scalaing up!
Q: What function is a tree hugger most concerned by?
A: log (n).
Q: What is a garbologists favourite optimisation problem?
A: Bin packing.
Q: What is a choirs favourite design pattern?
A: The Singleton pattern!
Q: What do you call a mathematician that has lots of statues in her garden?
A: Polygnomial.
Q: What do fashion designers and Haskell programmers have in common?
A: They love pattern matching!
Q: How did the mathematician impress at the dance party?
A: By showing off her step function!
No joke provided; the Curry-Howard isomorphism allows us to generate a programming joke from the maths joke.
Q: Why was the mathematician unhappy when she turned 24?
A: She now had a lot of factors to consider.
Q: Why was the programmer so poor?
A: Syntax.
Q: Why was the ML programmer late to the conference?
A: She spent too much time in the “train” stage.
Q: What number is good value?
A: 241
Exercise: What number is best value?
Q: Why couldn’t the python programmer get into her house?
A: Key error.
Q: How did the programmer get out of the deep end of the pool?
A: She made a pull request!
Q: Why was the ML researcher tired of shopping?
A: She was overfitting.
Q: How did the programmer get to the bottom of the ocean?
A: By sub-routine!
Q: How do you order citrus?
A: Use the real number lime.


--- layout: post title: Microsoft Student Partner 2012-2013 date: 2012-08-08 14:20:00.000000000 +05:30 type: post published: true status: publish categories: - Amazing - MSP - MSP2012 - PLACEMENT tags: [] meta: blogger_blog: www.technoruler.com blogger_author: VISWAPRASATH KS blogger_cb097c283b9bbfde97b4822e7250157d_permalink: '8807260480386103730' author: login: viswaprasath email<EMAIL_ADDRESS>display_name: Vitchu first_name: '' last_name: '' ---
The Microsoft Students Partner Program
http://www.microsoft.com/india/student/msp2012_registration.aspx
This year I though to join in this program. I love technology very much. And currently mobile application development is very much interesting for me. Since many of my friends around me who love playing games and always with their mobile than to be with real humans. They gone virtual instead to be original. Hmmm... should sound good to person like me but Lets come back to the need of this post.
I would like to help you with the registration process for MSP event this year. For that only you have clicked the above link. Then page which looks like below should come.
Or if you have gone through this below link then the page like below should appear.When you go from below like remember to choose the country where you are. Currently for India it has been opened.
https://www.microsoftstudentpartners.com/


--- layout: default ---
Led by previous national medalists, Golden Gate Science Olympiad represents a collaboration between Stanford University and University of California, Berkeley students. Coming soon in 2019 will be the third annual Division C tournament. Explore the tabs above for more information.
The 2018 National Science Olympiad Tournament just ended. Thousands of kids and teens from around the country came together to take exams, calibrate their precision machines, and embrace challenges that would intimidate many college students.
Read More


Our name is derived from two Latin words which express renewal and trust.
Our mission is to live up to our name by combining a fresh approach with integrity and experience to offer a
comprehensive and discreet service.
Verfides originally started its operation in the early Seventies and during its existence it has been owned
by multinational investment banks. Verfides is now independent and fully owned by its management. Our
Management team brings together qualified and highly-respected professionals with longstanding experience in
the provision of specialised services to private clients.
Verfides has offices in key international financial centres. To extend our reach globally and deliver the
very best knowledge and resources for the benefit of our clients, we also partner with outstanding
professionals worldwide.
We stress creativity and imagination in everything we do. Our mission is to live up to our name by combining
a fresh approach with integrity and experience to offer a unique and dedicated service.
We know that the needs of each client are unique and so we tailor our advice and solutions to their specific
requirements. We always bring our commitment, excellence and enterprise to ensure outstanding service to all
our clients. We pride ourselves on our experience and approachability.
We understand that change is a fact of life and we welcome the challenges that change brings. We engage with
our clients to develop the right response at the right time to benefit from the opportunities change presents.
In an increasingly complex world we are proud to bring our expertise and commitment in providing outstanding
services to our clients.
Our knowledge and experience together with the business creativity of our clients is a powerful combination
and makes Verfides a trusted partner and an experienced adviser.


Base:
method
GetCurrentlyRunningPipeline
System.Management.Automation.Runspaces.Runspace.GetCurrentlyRunningPipeline()
7 references to GetCurrentlyRunningPipeline
System.Management.Automation (7)
engine\debugger\debugger.cs (1)
4642
var runningPipe = remoteRunspace.
GetCurrentlyRunningPipeline
();
engine\hostifaces\LocalConnection.cs (1)
1458
_remoteRunspace.
GetCurrentlyRunningPipeline
() != null)
engine\remoting\client\remotepipeline.cs (2)
921
RemotePipeline currentPipeline = (RemotePipeline)((RemoteRunspace)_runspace).
GetCurrentlyRunningPipeline
();
1053
(RemotePipeline)((RemoteRunspace)_runspace).
GetCurrentlyRunningPipeline
();
engine\remoting\client\remoterunspace.cs (1)
2322
if ((_runspace.
GetCurrentlyRunningPipeline
() != null) ||
engine\remoting\client\RunspaceRef.cs (1)
304
if ((remoteRunspace.
GetCurrentlyRunningPipeline
() != null))
engine\remoting\commands\PushRunspaceCommand.cs (1)
1297
cmd = remoteRunspace.
GetCurrentlyRunningPipeline
() as RemotePipeline;


FORMS
authorization
Personal Data
First Name
Middle Name
Last Name
Male
Female
Married
Single
Divorsed
Address
Country:
Belarus
Russia
USA
England
other country
City:
Minsk
Moskow
Washigton
London
other city
Street:
House №:
Flat №:
Phone №:
Email:
What languages do you speak
English
Russian
Belarussian
Spanish
Chinese
Italian
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Your comments
Send


Cheetahs ring the changes for final tour match in Cardiff
Cape Town - Hawies Fourie has made five changes and three positional switches to the Cheetahs' line-up for Saturday’s PRO14 match against the Cardiff Blues.
Kick-off is at 19:15 SA time.
Fourie said: “We’re looking forward to Saturday’s match. It is the last one on tour. We came here to win all three, but unfortunately we lost the first two. This is our last chance to win a match on tour.
“Our preparations this week went well. We are lucky not to have any injuries and have a full team to train with, which brings continuity. We’ll be playing on an artificial pitch and luckily we trained on Cardiff City’s soccer field this week with the same surface for the players to get used to the conditions.
“Cardiff didn’t have the best start, but they have strong team, especially with players returning from the World Cup. We expect a big challenge.”
Anthony Volmink starts on the left wing with Clayton Blommetjies shifting to right wing in place of William Small-Smith, who in return moves into the midfield.
As a result of Small-Smith’s selection at outside centre, Benhard Janse van Rensburg shifts to No 12 at the expense of Louis Fouche who drops to the bench.
In the final backline change, Ruan Pienaar starts at scrumhalf and will also captain the side.
Up front, loosehead prop Luan de Bruin earns his first start of the season ahead of Boan Venter, while lock Walt Steenkamp and flank Gerhard Olivier replace JP du Preez and Sias Koen, respectively.
The Cheetahs find themselves third in Conference A after five matches, while the Cardiff Blues are down in sixth in Conference B.
The Cheetahs will return to South Africa on Sunday. Their next match is on November 30 against Ospreys at 21:35 (SA time) at the Liberty Stadium in Swansea, Wales.
Teams:
Cardiff Blues
15 Matthew Morgan, 14 Harri Millard, 13 Rey Lee-Lo, 12 Jarrod Evans, 11 Aled Summerhill, 19 Jason Tovey, 9 Lloyd Williams (captain), 8 Nick Williams, 7 Will Boyde, 6 Shane Lewis-Hughes, 5 Seb Davies, 4 Josh Turnbull, 3 Scott Andrews, 2 Liam Belcher, 1 Corey Domachowski
Substitutes: 16 Kirby Myhill, 17 Brad Thyer, 18 Keiron Assiratti, 19 Macauley Cook, 20 Alun Lawrence, 21 Lewis Jones, 22 Willis Halaholo, 23 Jason Harries
Cheetahs
15 Rhyno Smith, 14 Clayton Blommetjies, 13 William Small-Smith, 12 Benhard Janse van Rensburg, 11 Anthony Volmink, 10 Tian Schoeman, 9 Ruan Pienaar (captain), 8 Jasper Wiese, 7 Junior Pokomela, 6 Gerhard Olivier, 5 Walk Steenkamp, 4 Sintu Manjezi, 3 Aranos Coetzee, 2 Joseph Dweba, 1 Luan de Bruin
Substitutes: 16 Wilmar Arnoldi, 17 Boan Venter, 18 Erich de Jager, 19 JP du Preez, 20 Sias Koen, 21 Tian Meyer, 22 George Whitehead, 23 Louis Fouche


The QUDT, or "Quantity, Unit, Dimension and Type" schema defines the base classes properties, and restrictions used for modeling physical quantities, units of measure, and their dimensions in various measurement systems. The goal of the QUDT ontology is to provide a unified model of, measurable quantities, units for measuring different kinds of quantities, the numerical values of quantities in different units of measure and the data structures and data types used to store and manipulate these objects in software.
Except for unit prefixes, all units are specified in separate vocabularies. Descriptions are provided in both HTML and LaTeX formats. A quantity is a measure of an observable phenomenon, that, when associated with something, becomes a property of that thing; a particular object, event, or physical system.
A quantity has meaning in the context of a measurement (i.e. the thing measured, the measured value, the accuracy of measurement, etc.) whereas the underlying quantity kind is independent of any particular measurement. Thus, length is a quantity kind while the height of a rocket is a specific quantity of length; its magnitude that may be expressed in meters, feet, inches, etc. Or, as stated at Wikipedia, in the language of measurement, quantities are quantifiable aspects of the world, such as time, distance, velocity, mass, momentum, energy, and weight, and units are used to describe their measure. Many of these quantities are related to each other by various physical laws, and as a result the units of some of the quantities can be expressed as products (or ratios) of powers of other units (e.g., momentum is mass times velocity and velocity is measured in distance divided by time).


If a baby does not begin to breathe after 1 minute of ventilation with chest movement, evaluate heart rate to decide if ventilation is adequate.
Ask the question:
Is the heart rate normal or slow?
Continue ventilation for 1 minute before stopping to check the heart rate. A skilled helper can count the umbilical cord pulsations during the first minute without interrupting ventilation. If you have no skilled helper or the cord pulse cannot be felt, you will need to rely on movement of the chest as an indicator of adequate ventilation.
Decide if the heart rate is normal or slow
A baby’s heart rate should be faster than your heart rate. Evaluate the heart rate by listening to the heartbeat with a stethoscope or feeling the umbilical cord
pulse. Listen over the left chest and pause ventilation for several seconds in order to hear the heartbeat. Feel the pulse in the umbilical cord where it attaches to the baby’s abdomen. If no pulse can be felt in the cord, you or your helper must listen for the heartbeat.
Minimize the time without ventilation. Listen to the heart rate just long enough to recognize if it is normal or slow.
Practice key skills
Practice in pairs
- Feel the umbilical cord pulse
- Listen to the heartbeat with a stethoscope
- Decide if the heart rate is normal or slow
Check yourself
Mark the box beside the best answer
Follow the Action Plan
What are the evaluation questions
during continued ventilation?
To improve care in your facility
‐ Who is available to evaluate heart rate while a baby is receiving
ventilation?
‐ Is there good teamwork and communication when a baby
needs continued ventilation?
What to monitor
‐ How often is a second skilled helper available to check heart rate during ventilation?


Width and Height Attributes
The width and height attributes of the img tag, defines the width and height of the image:


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Almost Heroes (1998)
***1/2 out of *****
Cast: Chris Farley, Matthew Perry, Eugene Levy, Kevin Dunn, David Packer, Hamilton Camp, Christian Clemenson, Bokeem Woodbine, Harry Shearer Written by: Mark Nutter, Tom Wolfe and Boyd Hale Directed by: Christopher Guest Running Time: 90 minutes
I guess when you go into a movie with very low expectations, it's more satisfying when the film turns out to be not so bad. That's the case with Chris Farley's last starring vehicle Almost Heroes. I expected a cross between Farley's disasterous Black Sheep and John Candy's final film, the similarly themed Wagons East. Thankfully, it turned out to be pretty funny, along the lines of such low-brow comedies like Kingpin and Dumb and Dumber.
The plot is a simple one: explorers Edwards and Hunt (Matthew Perry and Chris Farley) set out on a cross country expedition a few weeks after Lewis and Clark do, hoping to beat them to the Pacific Ocean. The plot really doesn't mean anything however, as Almost Heroes is mainly just a collection of sketches using the same locale. Each scene seems self contained, as there will be a set-up for a joke, then the execution of that scene's main joke, and then we proceed on to the next sketch. Previous scenes are rarely acknowledged.
Thankfully, most of the jokes and situations work. Highlights include a campfire story with a really bizarre punchline, and Farley's character searching for an eagle's egg. These moments and many others got laughs out of me, and still do whenever I think about them. Surprisingly though, it's Matthew Perry who's the real star of the film, as Farley seems more of a supporting character, simply providing reasons for upper-class Perry to react to his lower-class shenanigans. Eugene Levy is also good in his role, and I've always considered Levy to be an underrated comedic talent.
What does bother me is the film's final 10 minutes or so. The film just completely falls apart. Not only does Farley get carried off by an eagle (he holds onto the eagle's legs as it flies, yeah right) but it also re-writes history along with making the film's title meaningless. According to the end of the film, Edwards and Hunt BEAT Lewis and Clark to the Pacific Ocean!  Also, there's no dedication to Farley anywhere in the film's closing credits, something that I thought would be customary. [PG13]
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--- --- layout: page title: CV description: This is my curriculum vitae.
Masters of Design
Bachelor of Science (B.S.),Marketing and Entrepreneurship
As the lead designer at CloudMine, my role was spread across multiple business facets — Enterprise and agency sales, direct & indirect marketing, core feature development, fundraising, and management.
While at Think Brownstone, I designed a tool for design practitioners to perform heuristic evaluations on their products, physical or digital. The work was influenced by Baymard, Norman, SUMI (Software Usability Measurement Inventory), and WAMMI (Website Analysis and MeasureMent Inventory), among others.
We have been using this algorithm based tool for usability evaluations at URBN for the last 5 years.


Terna Public Charitable Trust's Terna Engineering College is one of the well known and finest technical institution, with 'A' Grade from Maharashtra Government and having ISO 9001 quality management system
The department of Computer Engineering was established in the year 1991. The department has earned the reputation of being one of distinctive department in this campus. The department is striving hard towards the goal of providing innovative and
You have come to the home of the computer department of Terna Engineering College. It will provide you everything there is to know about us. More information about the faculties, study materials, other important news, syllabus and many more sections are provided for more knowledge. We are here to help you!
Regular updates, new competitions, a forum to provide your views and honest feedback are some of the features included in this site. Help us in developing this and making our site better. We will definitely help you get extra knowledge and cultivate a deeper interest in computers.


RxPullToRefresh
open class RxPullToRefresh : NSObject
A main class for RxPullToRefresh.
-
A RxPullToRefreshPosition value indicating where placed at.
Declaration
Swift
public var position: RxPullToRefreshPosition
-
A TimeInterval value indicating the duration to display an error on failure.
Declaration
Swift
public var waitDurationOnFailure: TimeInterval
-
A Boolean value indicating whether to start loading while dragging. If set to false, loading starts after the user finishes dragging.
Declaration
Swift
public var shouldStartLoadingWhileDragging: Bool
-
A Boolean value indicating whether a scroll view is being dragged.
Declaration
Swift
@objc dynamic public internal(set) var isDragging: Bool
-
A Boolean value indicating whether a RxPullToRefresh object is enabled. If set to false, a RxPullToRefresh object will not be displayed regardless of whether a data source exists or not.
Declaration
Swift
@objc dynamic public var isEnabled: Bool { get set }
-
A Boolean value indicating whether RxPullToRefresh can load more content. If set to false, the text
No Content
will be displayed by default.Declaration
Swift
@objc dynamic public var canLoadMore: Bool { get set }
-
A pulling rate of a RxPullToRefreshState object
Declaration
Swift
@objc dynamic public internal(set) var progressRate: CGFloat { get set }
-
A RxPullToRefreshState value indicating a pulling state
Declaration
Swift
@objc dynamic public internal(set) var state: RxPullToRefreshState { get set }
-
The object that acts as RxPullToRefreshDelegate.
Declaration
Swift
public weak var delegate: RxPullToRefreshDelegate?
-
A customizable UIView which added to a header or a footer.
Declaration
Swift
public internal(set) var refreshView: RxPullToRefreshView!
-
init(refreshView:position:shouldStartLoadingWhileDragging:waitDurationOnFailure:loadAnimationType:backAnimationType:)
An function that initialize RxPullToRefresh
Declaration
Swift
public init(refreshView: RxPullToRefreshView, position: RxPullToRefreshPosition, shouldStartLoadingWhileDragging: Bool = true, waitDurationOnFailure: TimeInterval = 1.0, loadAnimationType: RxPullToRefreshAnimationType = .linear(duration: 0.3), backAnimationType: RxPullToRefreshAnimationType = .linear(duration: 1.0))
Parameters
refreshView
A UIView which will added to header or footer view.
position
A RxPullToRefreshPosition value indicating a position.
animationOption
A RxPullToRefreshPosition value indicating a position.
-
init(position:shouldStartLoadingWhileDragging:waitDurationOnFailure:loadAnimationType:backAnimationType:)
An function that initialize RxPullToRefresh
Declaration
Swift
public convenience init(position: RxPullToRefreshPosition, shouldStartLoadingWhileDragging: Bool = true, waitDurationOnFailure: TimeInterval = 1.0, loadAnimationType: RxPullToRefreshAnimationType = .linear(duration: 0.3), backAnimationType: RxPullToRefreshAnimationType = .linear(duration: 1.0))
Parameters
height
A CGFloat value indicating the RxPullToRefresh height.
position
A RxPullToRefreshPosition value indicating a position.
animationOption
A RxPullToRefreshPosition value indicating a position.
-
A function to start refreshing forcibly.
Declaration
Swift
func startRefreshing()
-
A function to end refreshing.
Declaration
Swift
func endRefreshing()
-
A function to fail refreshing.
Declaration
Swift
func failRefreshing()
-
Declaration
Swift
public typealias Delegate = RxPullToRefreshDelegate


This topology source manages the topology of the physical Blocks devices that are currently connected.
It maintains a list of them and tells listeners when physical devices are added or removed.
Public Member Functions | |
| PhysicalTopologySource (bool startDetached=false) | |
| Constructor. More... | |
| ~PhysicalTopologySource () override | |
| Destructor. More... | |
| BlockTopology | getCurrentTopology () const override |
| Returns the current physical topology. More... | |
| void | cancelAllActiveTouches () noexcept override |
| Reset all touches. More... | |
| void | setActive (bool shouldBeActive) override |
| Sets the TopologySource as active, occupying the midi port and trying to connect to the block devices. More... | |
| bool | isActive () const override |
| Returns true, if the TopologySource is currently trying to connect the block devices. More... | |
| bool | isLockedFromOutside () const override |
| This method will tell, if an other PhysicalTopologySource has locked the Midi connection. More... | |
| PhysicalTopologySource (DeviceDetector &detectorToUse, bool startDetached=false) | |
| Constructor for custom transport systems. More... | |
| Public Member Functions inherited from TopologySource | |
| virtual | ~TopologySource ()=default |
| Destructor. More... | |
| void | addListener (Listener *l) |
| void | removeListener (Listener *l) |
| Block::Array | getBlocks () const |
| Gets blocks from the current topology. More... | |
| Block::Ptr | getBlockWithUID (Block::UID uid) const |
| Gets a block with given uid from the current topology. More... | |
Static Public Member Functions | |
| static const char *const * | getStandardLittleFootFunctions () noexcept |
Protected Member Functions | |
| virtual bool | hasOwnServiceTimer () const |
| virtual void | handleTimerTick () |
Classes | |
| struct | DeviceConnection |
| For custom transport systems, this represents a connected device. More... | |
| struct | DeviceDetector |
| For custom transport systems, this represents a connected device. More... | |
Additional Inherited Members | |
| Protected Attributes inherited from TopologySource | |
| juce::ListenerList< Listener > | listeners |
| PhysicalTopologySource::PhysicalTopologySource | ( | bool | startDetached = false | ) |
Constructor.
|
override |
Destructor.
| PhysicalTopologySource::PhysicalTopologySource | ( | DeviceDetector & | detectorToUse, |
| bool | startDetached = false |
||
| ) |
Constructor for custom transport systems.
|
overridevirtual |
Returns the current physical topology.
Implements TopologySource.
|
overridevirtualnoexcept |
Reset all touches.
Reimplemented from TopologySource.
|
overridevirtual |
Sets the TopologySource as active, occupying the midi port and trying to connect to the block devices.
Implements TopologySource.
|
overridevirtual |
Returns true, if the TopologySource is currently trying to connect the block devices.
Implements TopologySource.
|
overridevirtual |
This method will tell, if an other PhysicalTopologySource has locked the Midi connection.
Implements TopologySource.
|
staticnoexcept |
|
protectedvirtual |
|
protectedvirtual |


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replaces the old ssh command-name as hostname handling. If you link to this script with a hostname then executing the link is equivalent to having executed ssh with that hostname as an argument. All other arguments are passed to ssh and will be processed normally.
See
See
OpenSSH is a derivative of the original and free ssh 1.2.12 release by Tatu Ylonen. Aaron Campbell, Bob Beck, Markus Friedl, Niels Provos, Theo de Raadt and Dug Song removed many bugs, re-added newer features and created OpenSSH. Markus Friedl contributed the support for SSH protocol versions 1.5 and 2.0. Jonathan Amery wrote this ssh-argv0 script and the associated documentation.