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{% extends "base.html" %} {% from "helpers/forms.html" import form_field, action_buttons %} {% block content %}


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{% load i18n %} --- {% trans 'Current streak. Inactive drivers are included' %} {% trans 'Best streak. Inactive drivers are included' %} {% if not season %} {% trans 'Current streak. Inactive drivers are excluded' %} {% trans 'Best streak. Inactive drivers are excluded' %} {% trans 'Record by season' %} {% endif %}


Parse and examine further GBIF issues on a dataset
occ_issues(.data, ..., mutate = NULL)
| .data | Output from a call to |
|---|---|
| ... | Named parameters to only get back (e.g., cdround), or to remove (e.g. -cdround). |
| mutate | (character) One of:
For split and split_expand, values in cells become y ("yes") or n ("no") |
See also the vignette Cleaning data using GBIF issues
Note that you can also query based on issues, e.g.,
occ_search(taxonKey=1, issue='DEPTH_UNLIKELY')
. However, I imagine
it's more likely that you want to search for occurrences based on a
taxonomic name, or geographic area, not based on issues, so it makes sense
to pull data down, then clean as needed using this function.
This function only affects the data
element in the gbif
class that is
returned from a call to occ_search()
. Maybe in a future version
we will remove the associated records from the hierarchy
and media
elements as they are remove from the data
element.
You'll notice that we sort columns to make it easier to glimpse the important parts of your data, namely taxonomic name, taxon key, latitude and longitude, and the issues. The columns are unchanged otherwise.
http://gbif.github.io/gbif-api/apidocs/org/gbif/api/vocabulary/OccurrenceIssue.html
# NOT RUN { ## what do issues mean, can print whole table, or search for matches head(gbif_issues()) iss <- c('cdround','cudc','gass84','txmathi') gbif_issues()[ gbif_issues()$code %in% iss, ] # compare out data to after occ_issues use (out <- occ_search(limit=100)) out %>% occ_issues(cdround) # occ_data (out <- occ_data(limit=100)) out %>% occ_issues(cdround) # Parsing output by issue (res <- occ_data( geometry='POLYGON((30.1 10.1,40 40,20 40,10 20,30.1 10.1))', limit = 600)) ## or parse issues in various ways ### inlude only rows with cdround issue gg <- res %>% occ_issues(cdround) NROW(res$data) NROW(gg$data) head(res$data)[,c(1:5)] head(gg$data)[,c(1:5)] ### remove data rows with certain issue classes res %>% occ_issues(-cdround, -cudc) ### split issues into separate columns res %>% occ_issues(mutate = "split") res %>% occ_issues(-cudc, -mdatunl, mutate = "split") res %>% occ_issues(gass84, mutate = "split") ### expand issues to more descriptive names res %>% occ_issues(mutate = "expand") ### split and expand res %>% occ_issues(mutate = "split_expand") ### split, expand, and remove an issue class res %>% occ_issues(-cdround, mutate = "split_expand") ## Or you can use occ_issues without the pipe occ_issues(res, -cdround, mutate = "split_expand") # from GBIF downloaded data via occ_download and friends res <- occ_download_get(key="0000066-140928181241064", overwrite=TRUE) x <- occ_download_import(res) occ_issues(x, -txmathi) occ_issues(x, txmathi) occ_issues(x, gass84) occ_issues(x, zerocd) occ_issues(x, gass84, txmathi) occ_issues(x, mutate = "split") occ_issues(x, -gass84, mutate = "split") occ_issues(x, mutate = "expand") occ_issues(x, mutate = "split_expand") # occ_search/occ_data with many inputs - give slightly different output # format than normal 2482598, 2498387 xyz <- occ_data(taxonKey = c(9362842, 2492483, 2435099), limit = 300) xyz length(xyz) # length 3 names(xyz) # matches taxonKey values passed in occ_issues(xyz, -gass84) occ_issues(xyz, -cdround) occ_issues(xyz, -cdround, -gass84) # }


Controls
Row Order
Cluster
Rank
Column Order
Cluster
Rank
Search
Column Group Size
Row Group Size
Filter Row: 0%
Please wait ...


I'm A Celebrity fans stunned as Ian Wright snaps at Andrew Maxwell over dinner
Andrew tried to offer Ian some extra food
by Rebecca CarterViewers of I'm A Celebrity were left divided as Ian Wright and Andrew Maxwell clashed on tonight's show.
After Adele Roberts and Roman Kemp won 10 stars in the Bushtucker trial earlier in the day, the camp were treated to crocodile feet for dinner.
However, the meal seemed to cause a stir among the campmates as Ian snapped at Andrew after he tried to offer him more food.
Read more: Bookies predict Jacqueline Jossa will win this year's I'm A Celebrity
Jacqueline Jossa asked Ian: "Ian, do you want a bit of chicken?"  There's two there. Go for it dude."
Jacqueline asked the former footballer: "Which one do you want?" to which Ian said: "No I don't want none."
Andrew said: "Come on seriously Ian."
Ian replied: "I really honestly don't want no more. [James Haskell] needs it more than I would."
Andrew pointed out: "There's two Ian," to which Ian said: "He can have another one if he wants. I don't want no more."
Andrew said: "Jesus, the drama. Just eat some!" to which Ian snapped: "I said I don't want no more [expletive] crocodile bruv. I don't want no more!"
In the Bush Telegraph, Ian said: "There's nothing more frustrating then when you're saying no to something and someone continues to ask you. It's annoying."
Read more: I'm A Celebrity fans divided as Jacqueline Jossa 'snaps' at Andrew Maxwell
Andrew said in the Bush Telegraph: "I felt bad that I was pressurising [him] too much into eating it. He came back at me but I get it."
Viewers were divided over the clash and shared their thoughts on Twitter.
Leave us a comment on our Facebook page @EntertainmentDailyFix and let us know what you think of this story.


Jade Templating Mode
The Jade Templating Mode
Created by Forbes Lindesay. Managed as part of a Brackets extension at https://github.com/ForbesLindesay/jade-brackets.
MIME type defined: text/x-jade
.
Created by Forbes Lindesay. Managed as part of a Brackets extension at https://github.com/ForbesLindesay/jade-brackets.
MIME type defined: text/x-jade
.


{{headerCityZip}}
{{Temp | number:0}}°
{{NowSummary}}.
Feels like {{FeelsLike | number:0}}°
{{NowSummary}}.
Feels like {{FeelsLike | number:0}}°
| {{thisDay.time * 1000 | date:'EEE MM/dd'}} | {{thisDay.icon}} | {{thisDay.temperatureMax | number:0}}° | {{thisDay.temperatureMin | number:0}}° |
|---|


BitShip Options
This page needs to be updated with the following:
- BitBucket Repository URL - the complete URL to your BitBucket repository
- Codeship Project ID - the numeric ID for your Codeship Project
- Codeship Project UUID - your Codeship project's UUID, you'll find this under the "General" project settings


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Latest news and events about NFCS AE-FUNAI. Get to know our most recent updates and blessings God has bestowed on us.
We have great records, very great ones, greater than you could imagine. It has been all God, because what God cannot do does not exist.


Completing a Wizard
A wizard is a customized collection of instructions, forms, files, and other materials that guide you through an activity.
You complete the wizard as you perform the various tasks or steps that make up the activity.
To complete a wizard, you access it online, follow its instructions, record information and attach requested materials, reflect
on your activities, and receive feedback. Since wizards often guide you through activities that occur over a long period of
time, you may need to access a wizard several times in order to complete it.
To access a wizard and complete it, access the Wizards tool and follow these steps:
- If the Wizards home page is not displayed, click the Reset button.
- Click the name of the wizard you want to work with. Sakai displays the introductory screen for the wizard you chose.
-
- The top section of the screen shows the name of the wizard. In this section, you may also see an explanation of the wizard's
purpose, provides instructions for completing the wizard, and helpful examples of the wizard in its completed form.
- The middle section contains the various items you will work with as you complete the wizard. All of the items you can access
are shown in blue.
- The bottom section provides an opportunity for you to reflect on this activity and your experience of it.
- To access linked web pages or attached files shown on this screen and in other parts of the wizard, click the appropriate
URLs or file names.
- Following the instructions provided on this screen, access items in the wizard by clicking their names. Each time you click
a name, Sakai presents a screen that contains the information and forms you need.
- To use a form, choose one of these options:
- To fill out the form and attach it, click the Add Form link below the name of the form. Sakai displays the form you have selected.
Complete the form, including the Title field (required; your entry provides a display name for your work in this form), and
click Add. Sakai saves the information and displays the wizard again. It also stores the completed form (by the title you
gave it) in Resources in My Workspace.
- If you have already filled out this form and have stored it in Resources, click the Select Existing Form link. When Sakai
displays the Resources home page, select the form.
- When you have completed a page that calls for submission or have completed the entire wizard, submit the page or wizard for
evaluation. To do so, click the Submit for Evaluation confirmation button. Sakai a screen asking you to confirm that you want
to submit the completed wizard for evaluation.
Caution: After you submit the wizard for evaluation, you cannot access it again to make changes. Therefore, you should make sure that
all of your entries are in their final form and are ready for review and comment before you submit the wizard.
- To submit the wizard now, click Submit. Or, to cancel the submission process, click Cancel.
- To return to the Wizards home page at any point, click the Return to Wizards button.


Exposing local services to Minikube using SSH
We already know we can port forward to reach services in Minikube, but what abot the other way around? What if a pod needs an external service on your laptop? There’s a pure Kubernetes way of doing it, but this is more of an interesting SSH trick that exposes how Kubernetes and Minikube work. Plus, it’s always fun to do tricks with SSH.
The setup
Consider the following diagram:
Vault is only accessible via the Elastic Load Balancer, which itself is only accessible to select security groups within our VPC. In order to issue Vault commands from my laptop, I have to use SSH local port forwarding. This sets up a tunnel over SSH that allows me to connect through my SSH destination (Bastion in this case) which can connect to Vault.
This is what the local forward looks like in my ~/.ssh/config
:
Host Bastion
Hostname mybastion.mysite.org
LocalForward 55555 vault.mysite.org:443
ControlMaster auto
And just connecting to the server sets up the forwarder: ssh Bastion
However, we have a problem: Minikube needs to connect to Vault as well but is on an isolated network on my laptop. How do I expose Vault to Kubernetes inside this onion of networks? Let’s do it the hard way.
The Solution
Answer: MORE SSH!
Since I’ve already forwarded the connection from somewhere off in Internetland, as far as Minikube is concerned, Vault may as well be living locally on my laptop at <IP_ADDRESS>:8200
. This works well for us, since the next step is just to cross that last gap between local laptop and kubernetes pod. After doing lots of digging around on Minikube port forwarding, I was disappointed that I couldn’t find much in the way of Github issues, StackOverflow questions, blog posts, etc. on Minikube reaching out. There was plenty on forwarding in to services on Minikube, however. Finally, I remembered that this SSH thing can go both ways: If I can forward my connection out to a destination, I can also invite a destination to connect inbound to me. In SSH parlance, that’s called a “remote forward.”
The idea was to make one giant SSH pipeline: A remote forward from my laptop to the Minikube VM would allow connections from the pods to the forwarded port on Minikube VM to reach my laptop. Since my laptop is already forwarding the port all the way over to AWS, that would complete the SSH tunnel over multiple hops and allow pods on Minikube to reach Vault as though it was local.
Spoiler alert: It didn’t work right away.
The normal syntax for an SSH remote forward looks like this: ssh -R remoteport:localaddress:localport host
.
An actual example: ssh -R 9999:<IP_ADDRESS>:8200 myserver
would open a connection on port 9999 on the remote host, forwarding any traffic they send it to <IP_ADDRESS>:8200
on your local machine. I’ll stop for a second to allow you to imagine the really dangerous possibilities of a tool like SSH. Better yet, go read these awesome blog posts on the topic:
How to lose your job with SSH, part 1
How to lose your job with SSH, part 2
Back? Was that cool or what? Let’s move on…
So we’re going to forward some port on Minikube VM over to our already-forwarded Vault connection. First, let’s figure out what the Minikube IP is: minikube ip
Okay, that was easy. How do we get in now? A lucky google search turned up this SSH string, actually: ssh -i ~/.minikube/machines/minikube/id_rsa docker@$(minikube ip)
which Aaron Prindle (aprindle on the Kubernetes Slack) helpfully shortened to ssh -i $(minikube ssh-key) docker@$(minikube ip)
. That gets us into the Minikube container, but how do we forward the connection back out?
We start with this (bear in mind that vault is forwarded to <IP_ADDRESS>:55555
on my laptop):
ssh -i $(minikube ssh-key) docker@$(minikube ip) -R 8200:<IP_ADDRESS>:55555
By default this will only bind to localhost on the remote machine, so we need to expand it a bit:
ssh -i $(minikube ssh-key) docker@$(minikube ip) -R <IP_ADDRESS>:8200:<IP_ADDRESS>:55555
Here I have told SSH to bind to the eth0 interface of the minikube machine instead of localhost. Did it work?
$ ssh -i ~/.minikube/machines/minikube/id_rsa docker@$(minikube ip) -R <IP_ADDRESS>:8200:localhost:55555
$ netstat -ant | grep 8200
tcp 0 0 <IP_ADDRESS>:8200 <IP_ADDRESS>:* LISTEN
tcp 0 0 ::1:8200 :::* LISTEN
That’s a solid “no”. For some reason, even when explicitly told to use an IP other than localhost, it binds to localhost anyways. Turns out there was an issue opened on this: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=228064 and the answer was to update /etc/ssh/sshd_config
to have the following line:
GatewayPorts yes
This apparently allows remote forwarding to bind to interfaces other than localhost.
Now restart the ssh service:
sudo systemctl restart sshd
And reconnect:
ssh -i $(minikube ssh-key) docker@$(minikube ip) -R 8200:localhost:55555
Now observe our listening interfaces:
$ netstat -ant | grep 8200
tcp 0 0 <IP_ADDRESS>:8200 <IP_ADDRESS>:* LISTEN
tcp 0 0 :::8200 :::* LISTEN
We are listening on all interfaces, ready to forward!
Now in any of your services, you can reach out to the minikube IP on port 8200 to forward your traffic!
Here’s what our service file looks like now:
# kubernetes-vault.yaml
apiVersion: v1
kind: Service
metadata:
name: kubernetes-vault
labels:
run: kubernetes-vault
spec:
clusterIP: None
selector:
run: kubernetes-vault
# Kubernetes-Vault does not need to expose any ports through a headless service.
# However, there's a Kubernetes bug where the pods won't be registered in the API,
# so we need to use this hack. See kubernetes/kubernetes#32796
ports:
- name: port
port: 80
---
apiVersion: v1
kind: ConfigMap
metadata:
name: kubernetes-vault
data:
kubernetes-vault.yml: |-
vault:
addr: http://<IP_ADDRESS>:8200 # Notice the IP address?
token: aaaa-bbbb-cccc
kubernetes:
watchNamespace: ${KUBERNETES_NAMESPACE}
serviceNamespace: ${KUBERNETES_NAMESPACE}
service: kubernetes-vault
prometheus:
tls:
vaultCertBackend: intermediate-ca
vaultCertRole: kubernetes-vault
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: kubernetes-vault
spec:
replicas: 3
template:
metadata:
labels:
run: kubernetes-vault
spec:
containers:
- name: kubernetes-vault
image: boostport/kubernetes-vault
env:
- name: KUBERNETES_NAMESPACE
valueFrom:
fieldRef:
fieldPath: metadata.namespace
volumeMounts:
- name: config-volume
mountPath: /kubernetes-vault
volumes:
- name: config-volume
configMap:
name: kubernetes-vault


Some of my renders for the Locker room here at PSU
The Record Board
Back Wall
The Snack and roller area


Korean
Almond:
It emphasize love and how love can changes everything. There is a quote that I cant forget 'love means To discover the beauty' and also how two characters yunjae and gon are thrown into difficult circumstances and situations how they face them.
Every moment was you:
When I live in a busy life, I have a moment when I can not take care of my mind, and all my moments are poured out in a dark night. It is such a tired night that "every moment was you", and it is a book that somebody gives me the words I wanted to give to me. Genre : Fiction


Build responsive, mobile-first projects on the web with the world's most popular front-end component library.
Bootstrap is an open source toolkit for developing with HTML, CSS, and JS. Quickly prototype your ideas or build your entire app with our Sass variables and mixins, responsive grid system, extensive prebuilt components, and powerful plugins built on jQuery.
Currently v4.0.0-beta
Include Bootstrap's source Sass and JavaScript files via Bower, Composer, Meteor, or npm. Package managed installs don't include documentation, but do include our build system and readme.
npm install<EMAIL_ADDRESS>gem install bootstrap -v 4.0.0.alpha6
bower install bootstrap#v4.0.0-beta
When you only need to include Bootstrap's compiled CSS or JS, you can use the Bootstrap CDN.
<link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta/css/bootstrap.min.css" integrity="sha384-/Y6pD6FV/Vv2HJnA6t+vslU6fwYXjCFtcEpHbNJ0lyAFsXTsjBbfaDjzALeQsN6M" crossorigin="anonymous">
<script src="https://code.jquery.com/jquery-3.2.1.slim.min.js" integrity="sha384-KJ3o2DKtIkvYIK3UENzmM7KCkRr/rE9/Qpg6aAZGJwFDMVNA/GpGFF93hXpG5KkN" crossorigin="anonymous"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.11.0/umd/popper.min.js" integrity="sha384-b/U6ypiBEHpOf/4+1nzFpr53nxSS+GLCkfwBdFNTxtclqqenISfwAzpKaMNFNmj4" crossorigin="anonymous"></script>
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0-beta/js/bootstrap.min.js" integrity="sha384-h0AbiXch4ZDo7tp9hKZ4TsHbi047NrKGLO3SEJAg45jXxnGIfYzk4Si90RDIqNm1" crossorigin="anonymous"></script>
Take Bootstrap 4 to the next level with official premium themes—toolkits built on Bootstrap with new components and plugins, docs, and build tools.


| Estimated | Remarks | Reference | |||
|---|---|---|---|---|---|
| per head | per group | per time | |||
| Bus (Ceres Liner) from Roxas City Terminal going to Iloilo Ceres Bus Terminal | 180 | 3.5 | http://karenjoy301.blogspot.com/2017/05/how-to-get-to-guimaras-island-from.html | ||
| Iloilo to Ceres Terminal Atrium | 13 | ||||
| Atrium to Ortiz Street near Port | 7 | ||||
| Port to Jordan port | 14 |
Monday to Saturday Iloilo to Guimaras: 5:30 a.m., 7:30 a.m., 9:30 a.m., 11:30 a.m., 2:30 p.m., 4:30 p.m., 7:30 p.m. Guimaras to Iloilo: 6:30 a.m., 8:30 a.m., 10:30 a.m., 12:30 p.m., 2:30 p.m., 4:30 p.m., 6:30 p.m. Sunday [2] Iloilo to Guimaras: 7:30 a.m., 4:00 p.m. Guimaras to Iloilo: 8:30 a.m., 5:30 p.m |
https://www.travelinboots.com/philippines/guimaras-travel-guide/ | ||
| Land Tour |<PHONE_NUMBER> (COMMENT: 11pax) | 2500 |
Kuya Cherald, Guimaras tour guide,<PHONE_NUMBER>2 Rates: tricycle – P1200, multicab – P2000, jeepney – P2500, van – P3500 Recommended: Multicab (inquire at the tourism office) |
https://www.taraletsanywhere.com/guimaras-land-tour/ https://www.thepinaysolobackpacker.com/guimaras-travel-guide/#GUIMARAS_LAND_TOUR |
|
| Island hoping |<PHONE_NUMBER> (COMMENT: 11pax) | 1600 |
The island hopping package in Raymen’s Beach Resort costs P500 for the whole boat for the first hour and P150 for every succeeding hour. Snorkel rental is P50 each. (assuming 2 boats + 2hrs (500*2boats + 150*2boats*2hrs)) |
https://www.taraletsanywhere.com/guimaras-land-tour/ | |
| 1300 |
First hour 500, succeeding hrs 150 (assuming 2hrs (500 + 2*150) |
||||
| Homestay | |||||
| TOTAL |<PHONE_NUMBER> |


The link you chose refers to files that are part of the full normative
V3 specification and are available on the HL7 Members Only section of the HL7
web site. Please proceed to www.hl7.org to log
into the members only section for access to the appropirate files.
Health Level Seven, Inc.
3300 Washtenaw Avenue, Suite 227 Ann Arbor, MI 48104<PHONE_NUMBER>
phone<PHONE_NUMBER> fax email: hq@hl7.org


I am a student at George Heriot's School who takes computing and knows HTML5, CSS and a small bit of Java and Python. I have also done some SQL and databse work alongside my web development.
I have taken computing as a subject since I was 10. I find this subject very interesting and I achieved an A at my National 5 exam in this subject. This was mainly due to me playing too many video games. I am taking it to higher and plan on taking it further on in my education.
I have taken graphic communication since I was 11. I chose it because it involved shapes and colours and it was easy. Yet I did manage to still achieve a B in my national 5 exam. I have stopped my education in this subject but I might take it back up later in my life.
I have been able to count above 10 since I was 4 years old. This is an achievement I am very proud of this and it shows with the A I recieved in my national 5 exam. I plan on taking this to further my ability to count.
I know a lot of flags. This is mostly due to my etensive knowledge of football players nationalities. I hated this subject and was pretty useless at it as I got a B in my exam.
I was sick a lot as a child
Apart from school I play a lot of Xbox. Mainly sport games and mostly FIFA even though it's a bad game. I wil definetaly have a gambling addiction due to the pack system in FUT. The main gamemode I play is Pro Clubs. I play as an ball-playing CAM and as a risk taking goalkeeper.
I also do sport as if I didn't I would probably drop dead due to a heart attack. My sport of choice is rugby where I play second-row or prop or hooker or 8 or flanker or any other position from numbers 1 to 8.


IPL Score Predictor
--- Select a Batting team ---
Mumbai Indians
Kolkata Knight Riders
Chennai Super Kings
Rajasthan Royals
Punjab Kings
Royal Challengers Bangalore
Delhi Capitals
Sunrisers Hyderabad
--- Select a Bowling team ---
Mumbai Indians
Kolkata Knight Riders
Chennai Super Kings
Rajasthan Royals
Punjab Kings
Royal Challengers Bangalore
Delhi Capitals
Sunrisers Hyderabad


This app was made by Mike Crabtree
Below is a test to add named to a list in HTML using the JS generated by the typescript.
Add


Class pv.Simulation
Represents a particle simulation. Particles are massive points in two-dimensional space. Forces can be applied to these particles, causing them to move. Constraints can also be applied to restrict particle movement, for example, constraining particles to a fixed position, or simulating collision between circular particles with area.
The simulation uses Position Verlet integration, due to the ease with which geometric constraints can be implemented. For each time step, Verlet integration is performed, new forces are accumulated, and then constraints are applied.
The simulation makes two simplifying assumptions: all particles are equal-mass, and the time step of the simulation is fixed. It would be easy to incorporate variable-mass particles as a future enhancement. Variable time steps are also possible, but are likely to introduce instability in the simulation.
This class can be used directly to simulate particle interaction.
Alternatively, for network diagrams, see pv.Layout.Force.
Defined in: Simulation.js.
| Constructor Attributes | Constructor Name and Description |
|---|---|
|
pv.Simulation(particles)
Constructs a new simulation for the specified particles.
|
| Field Attributes | Field Name and Description |
|---|---|
|
The constraints in the simulation.
|
|
|
The forces in the simulation.
|
|
|
The particles in the simulation.
|
| Method Attributes | Method Name and Description |
|---|---|
|
constraint(c)
Adds the specified constraint to the simulation.
|
|
|
force(f)
Adds the specified force to the simulation.
|
|
|
particle(p)
Adds the specified particle to the simulation.
|
|
|
stabilize(n)
Apply constraints, and then set the velocities to zero.
|
|
|
step()
Advances the simulation one time-step.
|
- Parameters:
- {array} particles
- an array of pv.Particles to simulate.
- Parameters:
- {pv.Constraint} c
- the new constraint.
- Returns:
- {pv.Simulation} this.
- Parameters:
- {pv.Force} f
- the new force.
- Returns:
- {pv.Simulation} this.
- Parameters:
- {pv.Particle} p
- the new particle.
- Returns:
- {pv.Simulation} this.
- Parameters:
- n
- Returns:
- {pv.Simulation} this.


This is an Oxford Visual Geometry Group computer vision practical, authored by Andrea Vedaldi and Andrew Zisserman (Release 2018a).
The goal of instance-level recognition is to match (recognize) a specific object or scene. Examples include recognizing a specific building, such as Notre Dame, or a specific painting, such as ''Starry Night'' by Van Gogh. The object is recognized despite changes in scale, camera viewpoint, illumination conditions and partial occlusion. An important application is image retrieval -- starting from an image of an object of interest (the query), search through an image dataset to obtain (or retrieve) those images that contain the target object.
The goal of this session is to get basic practical experience with the methods that enable specific object recognition. It includes: (i) using SIFT features to obtain sparse matches between two images; (ii) using affine co-variant detectors to cover changes in viewpoint; (iii) vector quantizing the SIFT descriptors into visual words to enable large scale retrieval; and (iv) constructing and using an image retrieval system to identify objects.
Read and understand the requirements and installation instructions. The download links for this practical are:
After the installation is complete, open and edit the script exercise1.m
in the MATLAB editor. The script contains commented code and a description for all steps of this exercise, relative to Part I of this document. You can cut and paste this code into the MATLAB window to run it, and will need to modify it as you go through the session. Other files exercise2.m
, exercise3.m
, and exercise4.m
are given for Part II, III, and IV.
Note: the student packages contain only the code required to run the practical. The complete package, including code to preprocess the data, is available on GitHub.
The SIFT feature has both a detector and a descriptor. We will start by computing and visualizing the SIFT feature detections for two images of the same object (a building facade). Load an image, rotate and scale it, and then display the original and transformed pair:
% Load an image
im1 = imread('data/oxbuild_lite/all_souls_000002.jpg') ;
% Let the second image be a rotated and scaled version of the first
im3 = imresize(imrotate(im1,35,'bilinear'),0.7) ;% Display the images
subplot(1,2,1) ; imagesc(im1) ; axis equal off ; hold on ;
subplot(1,2,2) ; imagesc(im3) ; axis equal off ;
A SIFT frame is a circle with an orientation and is specified by four parameters: the center $t_x$, $t_y$, the scale $s$, and the rotation $\theta$ (in radians), resulting in a vector of four parameters $(s, \theta, t_x, t_y)$. Now compute and visualise the SIFT feature detections (frames):
% Compute SIFT features for each
[frames1, descrs1] = getFeatures(im1, 'peakThreshold', 0.01) ;
[frames3, descrs3] = getFeatures(im3, 'peakThreshold', 0.01) ;
subplot(1,2,1) ; imagesc(im1) ; axis equal off ; hold on ;
vl_plotframe(frames1, 'linewidth', 2) ;
subplot(1,2,2) ; imagesc(im3) ; axis equal off ; hold on ;
vl_plotframe(frames3, 'linewidth', 2) ;
Examine the second image and its rotated and scaled version and convince yourself that the detections overlap the same scene regions (even though the circles have moved their image position and changed radius). It is helpful to zoom into a smaller image area using the MATLAB magnifying glass tool. This demonstrates that the detection process transforms (is co-variant) with translations, rotations and isotropic scalings. This class of transformations is known as a similarity or equiform.
Task: The number of detected features can be controlled by changing the
peakThreshold
option. A larger value will select features that correspond to higher contrast structures in the image. Try this now: run again the same code, but increasepeakThreshold
two or three times.
Now repeat the exercise with a pair of natural images. Start by loading the second one:
% Load a second image
im2 = imread('data/oxbuild_lite/all_souls_000015.jpg') ;
and plot images and feature frames. Again you should see that many of the detections overlap the same scene region. Note that, while repeatability occurs for the pair of natural views, it is much betterfor the synthetically rotated pair.
Question: Note the change in density of detections across the image. Why does it change? Will it be a problem for matching? How could it be avoided?
Question: Occasionally, a feature is detected multiple times, with different orientations. This may happen when the orientation assignment is ambiguous. Which kind of image structure would result in ambiguous orientation assignment?
Next we will use the descriptor computed over each detection to match the detections between images. We will start with the simplest matching scheme (first nearest neighbour of descriptors) and then add more sophisticated methods to eliminate any mismatches.
vl_plotsiftdescriptor
. Then use vl_plotframe
to overlay the corresponding frames.Question: Note the descriptors are computed over a much larger region (shown in blue) than the detection (shown in green). Why?
Compute first nearest neighbours matches - for each SIFT descriptor in the first image, compute its nearest neighbour in the second image with the function findNeighbours
.
Visualize the correspondences using lines joining matched SIFT features with the function plotMatches
.
Question: Notice that there are many mismatches. Examine some of the mismatches to understand why the mistakes are being made. For example, is the change in lighting a problem? What additional constraints can be applied to remove the mismatches?
Hint: You can visualize a subset of the matches using:
figure; plotMatches(im1,im2,frames1,frames2,matches(:,3:200:end));
Lowe introduced a second nearest neighbour (2nd NN) test to identify, and hence remove, ambiguous matches. The idea is to identify distinctive matches by a threshold on the ratio of first to second NN distances. In the MATLAB file, the ratio is nnThreshold
= 1NN distance / 2NN distance.
nnThreshold
in a range from 0.1 to 0.9, and examine how the number of matches and number of mismatches changes.nnThreshold = 0.8
is often a good compromise between losing too many matches and rejecting mismatches.Question: Examine some of the remaining mismatches to understand why they have occurred. How could they be removed?
In addition to the 2nd NN test, we can also require consistency between the matches and a geometric transformation between the images. For the moment we will look for matches that are consistent with a similarity transformation
which consists of a rotation by $\theta$, an isotropic scaling (i.e. same in all directions) by s, and a translation by a vector $(t_x, t_y)$. This transformation is specified by four parameters $(s,\theta,t_x,t_y)$ and can be computed from a single correspondence between SIFT detections in each image.
Task: Work out how to compute this transformation from a single correspondence.
Hint: Recall from Stage I.A that a SIFT feature frame is an oriented circle and map one onto the other.
The matches consistent with a similarity can then be found using a RANSAC inspired algorithm, implemented by the function geometricVerification
:
RANSAC-like algorithm for geometric verification
After this algorithm the inliers are consistent with the transformation and are retained, and most mismatches should now be removed.
Task: The figure generated by
plotMatches
supports the interactive visualisation of the transformation found bygeometricVerification
. Try hovering with the mouse on the figure and check that corresponding image points are highlighted in the two images.
Skip to Part 2 on fast track
Task: Test this procedure by varying the threshold distance (edit
geometricVerification
and change theopts.tolerance1
,opts.tolerance2
, andopts.tolerance3
parameters, where the last two thresholds are relative to the optional iterative fitting of an affine transformation or homography to the inliers). Note the number of inliers and number of mismatches.
If more matches are required the geometric transformation can be used alone, without also requiring the 2nd NN test. Indeed, since the 1st NN may not be the correct match, a list of potential (putative) matches can be generated for each SIFT descriptor by including the 1st NN, 2nd NN, 3rd NN etc. Investigate how the number of correct matches (and time for computation) grows as the potential match list is extended, and the geometric transformation is used to select inliers. To this end:
Task: Change the code to include in the match list the 1st NN, 2nd NN, 3rd NN, … best matches for each feature. Task: Run geometric verification and check the number of verified matches using this expanded list.
Hint: You can use MATLAB’s tic and toc functions to measure the execution time of a snippet of code. For example
tic ; pause(3) ; toc
will pause MATLAB for three seconds and return an elapsed time approximately equal to 3. See help tic
for details.
So far the change in viewpoint between images has been a similarity transformation. Now we consider more severe viewpoint changes - for example where an object is fronto-parallel in one view, and turns away from the camera in the other as in the graffiti wall images below:
In this case, there is foreshortening (anisotropic scaling) and perspective distortions between the images (as well as in-plane rotation, translation and scaling). A circle in one image cannot cover the same scene area as a circle in the other, but an ellipse can. Affine co-variant detectors are designed to find such regions.
In the following we will compare the number of matches using a similarity and affine co-variant detector as the viewpoint becomes progressively more extreme. The detectors are SIFT (for similarity) and SIFT+affine adaptation (for affine), while the descriptor are in both cases SIFT.
Task: Open and examine the script
exercise2.m
in the MATLAB editor. Run the script.
Note the behaviour in the number of verified matches as the viewpoint becomes more extreme. Observe that the matches also identify the regions of the images that are in common.
Question: The transformation between the images induced by the plane is a planar homography. The detections are only affine co-variant (not as general as a planar homography). So how can descriptors computed on these detections possibly match?
Note: There are many other detector variants that could be used for this task. These can be activated by the method option of getFeatures.m (see also help vl_covdet
).
In large scale retrieval the goal is to match a query image to a large database of images (for example the WWW or Wikipedia). The quality of a match is measured as the number of geometrically verified feature correspondences between the query and a database image. While the techniques discussed in Part I and II are sufficient to do this, in practice they require too much memory to store the SIFT descriptors for all the detections in all the database images. We explore next two key ideas: one to reduce the memory footprint and pre-compute descriptor matches; the other to speed up image retrieval.
Task: Open and edit the script
exercise3.m
in the MATLAB editor, and cut and paste to work through the following stages.
Instead of matching feature descriptors directly as done in Part I and II, descriptors are usually mapped first to discrete symbols, also called visual words, by means of a clustering technique like K-Means. The descriptors that are assigned to the same visual word are considered matched. Each of the rows in the following figure illustrates image patches that are mapped to the same visual word, and are hence indistinguishable by the representation.
Then, matching two sets of feature descriptors (from two images) reduces to finding the intersection of two sets of symbols.
Tasks:
- Load a visual word dictionary and an associated approximate nearest neighbour (ANN) matcher (the ANN matcher is used to determine the closest visual word to each descriptor and is based on a forest of KD trees).
- Given SIFT descriptors for two images, quantise them (assign them) into the corresponding visual words.
- Find corresponding features by looking for the same visual words in the two images and note the computation time.
- Geometrically verify these initial correspondences and count the number of inlier matches found.
- Find corresponding features by using the method of Part I and II, i.e. by comparing the descriptors directly, and note the computation time. Geometrically verify these initial correspondences and count the number of inlier matches found.
- Compare the speed and number of inliers when using visual words vs raw SIFT descriptors by means of the function
matchWords
. Note, you should repeat the timing (by running the matching again) as the first time you run it there may be a delay as certain MATLAB components are loaded into memory.- Optional: compare the speed and number of matches over another pair of images (from part I and II).
Questions:
- The size of the vocabulary (the number of clusters) is an important parameter in visual word algorithms. How does the size affect the number of inliers and the difficulty of computing the transformation?
- In the above procedure the time required to convert the descriptors into visual words was not accounted for. Why?
- What is the speedup in searching a large, fixed database of 10, 100, 1000 images?
Skip to Stage III.B on fast track
Often multiple feature occurrences are mapped to the same visual word. In this case matchWords
generates only one of the possible matches.
Tasks:
- Modify
matchWords
to generate more than one match for cases in which multiple features are mapped to the same visual word.This can be achieved by increasing the value ofmaxNumMatches
.- Most of these additional matches are incorrect. Filter them out by running
geometricVerification
.- Compare the number of inliers obtained before and after this modification.
While matching with visual words is much faster than doing so by comparing feature descriptors directly, scoring images directly based on the number of geometrically verified matches still entails fitting a geometric model, a relatively slow operation. Rather than scoring all the images in the database in this way, we are going to use an approximation and count the number of visual words shared between two images.
To this end, one computes a histogram of the visual words in a query image and for each of the database images. Then the number of visual words in common can be computed from the intersection of the two histograms.
The histogram intersection can be thought as a similarity measure between two histograms. In practice, this measure can be refined in several ways:
Computing histogram similarities can be implemented extremely efficiently using an inverted file index. In this exercise, inner products between normalized histograms are computed quite efficiently using MATLAB's built-in sparse matrix engine.
We now apply this retrieval method to search using a query image within a 660 image subset of the Oxford 5k building image set.
Task: How many erroneously matched images do you count in the top results? Question: Why does the top image have a score of 1?
Histogram-based retrieval results are good but far from perfect. Given a short list of top ranked images from the previous step, we are now going to re-score them based on the number of inlier matches after a geometric verification step.
Question: Why is the top score much larger than 1 now? Question: Are the retrieval results improved after geometric verification?
Now try the full system to retrieve matches to an unseen query image.
Skip and end here on fast track
The images below are all details of paintings. The goal of this last part of the practical is to identify the paintings that they came from. For this we selected a set of 1734 images of paintings from Wikipedia.
To identify the details you can either:
We follow route (3) here. Look through and run exercise4.m
. This uses the techniques described in Part III in order to construct an index for 1734 Wikipedia images so that they may be searched quickly. Use the code to find from which paintings these details come from.
Note, although the index is stored locally, the matching images are downloaded from Wikipedia and displayed. Click on the image to reach the Wikipedia page for that painting (and hence identify it).
Task: Use the code to visually search Wikipedia for further paintings from Van Gogh downloaded from the Internet.
Note: the code supports URL in place of filenames.
Take note of the code output.
Questions:
- How many features are there in the painting database?
- How much memory does the image database take?
- What are the stages of the search? And how long does each of the stages take for one of the query images?
That completes this practical.


Conway's Game of Life
The Project
I wanted to create an interesting project in Clojure that had the following features:
- The project should be simple, but interesting
- The project should demonstrate how Clojure, ClojureScript, and cljx interact
- There should be some cool Clojure features to learn about
- I wanted to demonstrate how to achieve state in a stateless world
I chose to program up Conway's Game of Life, a simple zero-player cellular automaton. It's a fun little simulation and meets all of my criterion. Here's what it looks like:
The Rules
- A living cell with only one or two neighbors dies
- A living cell with two or three live neighbors survives
- A living cell with greater than three neighbors dies
- A dead cell with exactly three neighbors comes to life
Postmortem
Implementation in Clojure
Conway's Game of Life is a cellular automaton in which a population of cells evolves with the following rules: This project was coded up in Clojure as an example of what can be done using the clj/cljs/cljx integration. It was done in three main files: rules.cljx, swingui.clj, and canvasui.cljs. Below you will find the complete listing of the rules and canvasui namespaces. the swingui namespace is available via git here.
rules.cljx
Here's a listing of the entire "rule engine" for the application.
(ns conway.rules)
(defn gen-cell[](if (> (Math/random) 0.7) :alive :dead))
(defn seed-grid [rows cols]
(vec (take rows (repeatedly
(fn [] (vec (take cols (repeatedly gen-cell))))))))
(defn neighbors [[i j]]
(let [x ((juxt inc inc identity dec dec dec identity inc) i)
y ((juxt identity inc inc inc identity dec dec dec) j)]
(map vector x y)))
(defn count-neighbors [grid coord]
(let [n (map #(get-in grid %) (neighbors coord))]
(count (filter #(= % :alive) n))))
(defn sim-step [grid coord]
(let [n-live (count-neighbors grid coord)]
(if (= :alive (get-in grid coord))
(case n-live
(2 3) :alive
:dead)
(if (= 3 n-live) :alive :dead))))
(defn step [grid]
(into [] (for [i (range (count grid))]
(into [] (for [j (range (count (get grid i)))]
(sim-step grid [i j]))))))
Perhaps the most interesting aspect of this project is the amount of code (and I mean the small amount) written to do this complete implementation. I am continually amazed as I write more Clojure about the expressiveness and conciseness of the language. Another thing to point out about this file is the cljx extension. By using this, I can write code that cross-compiles to target both the JVM and the browser via JavaScript. Pretty cool, eh?
Finally, I wanted to point out my favorite function in this program: juxt. the Clojure juxt function creates a function that performs a sequence of perations on a single item and returns that result as an indexed data structure. This is a perfect function for computing the neighbors of a cell in a grid. This is way better than having 8 sequential function calls in which you compute steps to the right, upper right, top center, upper left, and so on.
canvasui.cljx
And here is the complete listing for the canvas UI code.
(ns conway.canvasui
(:require [conway.rules :as rules]))
(defn draw-background [canvas ctx]
(doto ctx
(> .-fillStyle (set! "#000000"))
(.fillRect 0 0 (.-width canvas) (.-height canvas))))
(defn draw-and-update-grid [canvas ctx grid dim]
(let [dx (/ (.-width canvas) dim)
dy (/ (.-height canvas) dim)]
(do
(draw-background canvas ctx)
(> ctx .-fillStyle (set! "#00FF00"))
(doseq [i (range (count @grid))]
(doseq [j (range (count (get @grid i)))]
(when (= :alive (get-in @grid [i j]))
(.fillRect ctx (* dx i) (* dy j) dx dy))))
(swap! grid rules/step))))
(set!
(.-onload js/window)
(when (and js/document (.-getElementById js/document))
(let [cells 50
grid (atom (rules/seed-grid cells cells))
canvas (.getElementById js/document "myCanvas")
reset-button (.getElementById js/document "reset")
ctx (.getContext canvas "2d")]
(do
(js/setInterval
#(draw-and-update-grid canvas ctx grid cells) 10)
(set! (.-onclick reset-button)
#(reset! grid (rules/seed-grid cells cells)))))))
Again, it is amazing how few lines of code were written for this demo.
Finally, take a look at how state is managed in the program. Notice that there are no defs (global variables within the namespace) anywhere. All of the state is managed by a single atom (line 25) that is created within the initialization section of the script and is passed to each function. The draw-and-update-grid function draws and updates the grid (as you might expect) while the reset button is used to reset the grid. Since atoms are synchronous, I don't need to worry about any sort of concurrency problems. It just works.
This is a very common pattern in the Clojure world for designing applications. You have three elements:
- A set of rules that can be thought of as an API or DSL for your project. These rules consist only of defns or perhaps defs that define constants. They are used to transform or analyze a model. They are completely stateless.
- A very small number of Clojure concurrency primitives that manage the actual state of the application. In this case, there is only 1 - the grid atom. You might have other primitives, such as one for preferences, but the number should be small and separated by concerns.
- A user interface layer. It could be Swing, an HTML app using ClojureScript, or just a repl.
Coming from a background in 10+ years of Java and then about 6 years of Scala, this was something it took me a while to understand, but now I can't live without. When I got deep into Scala I really loved it, but had the hardest time figuring out how to manage state. With Clojure everything is just baked in.
In Conclusion
I was able to write up a simple cross-platform application in just a handful of lines of code using the amazing powers of Clojure, ClojureScript, and the cljx project. Despite its simplicity, there are some great things to learn from the project. If you want to see the entire project, check it out here or my entire github repo here. I hope you enjoyed this project and short postmortem.
If you liked this page or learned anything from it, please tweet the link and/or follow me on Twitter. I hope to have other projects like this in the future, and your support and interest is the fuel that drives the effort.


|
My Project
|
Classes | |
| class | _CommandWrapper |
| class | _NativeWrapper |
| class | _RemakeContext |
| class | BaseExpansion |
| class | Expansion |
| class | Makefile |
| class | Pattern |
| class | PatternRule |
| class | PatternRuleInstance |
| class | RemakeRuleContext |
| class | RemakeTargetParallel |
| class | RemakeTargetSerially |
| class | Rule |
| class | StringExpansion |
| class | Target |
| class | Variables |
Functions | |
| def | withoutdups (it) |
| def | mtimeislater (deptime, targettime) |
| def | getmtime (path) |
| def | stripdotslash (s) |
| def | stripdotslashes (sl) |
| def | getindent (stack) |
| def | dirpart (p) |
| def | filepart (p) |
| def | setautomatic (v, name, plist) |
| def | setautomaticvariables (v, makefile, target, prerequisites) |
| def | splitcommand (command) |
| def | findmodifiers (command) |
| def | getcommandsforrule (rule, target, makefile, prerequisites, stem) |
Variables | |
| str_type = basestring | |
| int | MAKESTATE_NONE = 0 |
| int | MAKESTATE_FINISHED = 1 |
| int | MAKESTATE_WORKING = 2 |
A representation of makefile data structures.
| def pymake.data.findmodifiers | ( | command | ) |
| def pymake.data.mtimeislater | ( | deptime, | |
| targettime | |||
| ) |


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SELECT Name, Site, Phone, Type, Owner.Name, CreatedBy.profile.Name FROM Account
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You have an idea and want people to follow it with you. You can become an organizer and create a project! You don’t necessarily have to make stuff, your project can be anything - going to movies or going through an internal transformation together - but it needs to have a clear purpose. Find people to collaborate and make your ideas come true.
You can also join other people’s projects. No matter the skills, you can add value. Your experiences and wisdom are a part of our worldwide resources and we can’t afford to lose it. Connect with like-minded people, and get closer to each other by working together and meeting in real life.
CrispTime is a platform for people looking for meaning and realisation of their passions with community, making your free time count. When you have an idea for an initiative, CrispTime make the first step easier.
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Before Change
q=1) if degree is None else degree,
shrinking=hp_bool(
_name("shrinking")) if shrinking is None else shrinking,
tol=hp.lognormal(
_name("tol"),
np.log(1e-3),
np.log(10)) if tol is None else tol,
// -- this is basically only here to prevent
// an infinite loop in libsvm"s solver.
// A more useful control mechanism might be a timer
After Change
return "%s.%s_%s" % (name, "poly", msg)
// -- (K(x, y) + coef0)^d
poly_coef0 = hp.choice(_name("coef0nz"), [
0.0,
hp.uniform( _name("coef0"), 0.0, 1.0)])


apiman
Open Source API Management
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Having Favourite Things part of everyones life!
Some of the things i like are
Website My Website.
FB Facebook.
Here is a link to my first webpage.


The update-notification-settings operation creates, updates, disables or re-enables notifications for a HIT type. If you call the update-notification-settings operation for a HIT type that already has a notification specification, the operation replaces the old specification with a new one. You can call the update-notification-settings operation to enable or disable notifications for the HIT type, without having to modify the notification specification itself by providing updates to the Active status without specifying a new notification specification. To change the Active status of a HIT type's notifications, the HIT type must already have a notification specification, or one must be provided in the same call to update-notification-settings .
See also: AWS API Documentation
update-notification-settings
--hit-type-id <value>
[--notification <value>]
[--active | --no-active]
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]
The ID of the HIT type whose notification specification is being updated.
The notification specification for the HIT type.
Shorthand Syntax:
Destination=string,Transport=string,Version=string,EventTypes=string,string
JSON Syntax:
{
"Destination": "string",
"Transport": "Email"|"SQS",
"Version": "string",
"EventTypes": ["AssignmentAccepted"|"AssignmentAbandoned"|"AssignmentReturned"|"AssignmentSubmitted"|"AssignmentRejected"|"AssignmentApproved"|"HITCreated"|"HITExpired"|"HITReviewable"|"HITExtended"|"HITDisposed"|"Ping", ...]
}
--active | --no-active (boolean)
Specifies whether notifications are sent for HITs of this HIT type, according to the notification specification. You must specify either the Notification parameter or the Active parameter for the call to update-notification-settings to succeed.
--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values.
--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.


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{% extends 'base.html' %} {% block head %}
Search for a user to display their information.
{{message}}
Name: {{user.name}}
Description: {{user.description}}
Profile Created at: {{user.created_at}}
A simple flask app that utilizes python-twitter to GET data from the Twitter API.
As of now, this program only displays a small amount of information of a profile.
You should still be able to checkout the rest of information by clicking on 'Grab json' upon a succesful search of an account.


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See Also: Inherited members from object.
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IsNull<T>
(this T)Determines whether the specified object is null. |
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IsNullDo<T>
(this T, Action)Determines whether the specified object is null. And invokes the specified Action delegate if the specified object is null. |
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WriteContent
(this HttpListenerResponse, byte[])Writes the specified content data using the specified WebSocketSharp.Net.HttpListenerResponse. |
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Syntax
public void Abort ()Remarks
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Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
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Syntax
Parameters
- name
- Documentation for this section has not yet been entered.
- value
- Documentation for this section has not yet been entered.
Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
Parameters
- cookie
- Documentation for this section has not yet been entered.
Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
Parameters
- name
- Documentation for this section has not yet been entered.
- value
- Documentation for this section has not yet been entered.
Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public void Close ()Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
Parameters
- responseEntity
- Documentation for this section has not yet been entered.
- willBlock
- Documentation for this section has not yet been entered.
Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public System.Text.Encoding ContentEncoding { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public long ContentLength64 { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public string ContentType { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public CookieCollection Cookies { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public void CopyFrom (HttpListenerResponse templateResponse)Parameters
- templateResponse
- Documentation for this section has not yet been entered.
Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public WebHeaderCollection Headers { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public bool KeepAlive { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public System.IO.Stream OutputStream { get; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public Version ProtocolVersion { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
Parameters
- url
- Documentation for this section has not yet been entered.
Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public string RedirectLocation { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public bool SendChunked { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
Parameters
- cookie
- Documentation for this section has not yet been entered.
Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public int StatusCode { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
public string StatusDescription { get; set; }Value
Documentation for this section has not yet been entered.Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062
Documentation for this section has not yet been entered.
Syntax
void System.IDisposable.Dispose ()Remarks
Documentation for this section has not yet been entered.Requirements
Namespace: WebSocketSharp.Net
Assembly: websocket-sharp (in websocket-sharp.dll)
Assembly Versions: <IP_ADDRESS>062


eval - Evaluate a Tcl script
eval arg ?arg ...?
Eval takes one or more arguments, which together comprise a Tcl
script containing one or more commands.
Eval concatenates all its arguments in the same
fashion as the concat command, passes the concatenated string to the
Tcl interpreter recursively, and returns the result of that
evaluation (or any error generated by it).
Note that the list command quotes sequences of words in such a
way that they are not further expanded by the eval command.
This procedure acts in a way that is analogous to the lappend
command, except it inserts the argument values at the start of the
list in the variable:
proc lprepend {varName args} {
upvar 1 $varName var
# Ensure that the variable exists and contains a list
lappend var
# Now we insert all the arguments in one go
set var [eval [list linsert $var 0] $args]
}
concatenate, evaluate, script
catch, concat, error, list, subst, tclvars
Copyright © 1993 The Regents of the University of California.
Copyright © 1994-1996 Sun Microsystems, Inc.
Copyright © 1995-1997 Roger E. Critchlow Jr.


{% extends 'base.html' %} {% load static %} {% load custom_tags %} {% load tz %} {% comment %} Copyright 2016, Institute for Systems Biology Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. {% endcomment %} {% block header %} {% endblock %} {% block link_page_name %}user-adjust-sa{% endblock %} {% block page_name %}user-adjust-sa{% endblock %} {% block page_header %}
{% endblock %} {% block content %}{{ DCF_MONITORING_SA }}
, as a Project Editor.


|
Aether.Physics2D
1.6
|
Simple class to maintain a terrain. It can keep track More...
Public Member Functions | |
| Terrain (World world, AABB area) | |
| Creates a new terrain. More... | |
| Terrain (World world, Vector2 position, float width, float height) | |
| Creates a new terrain More... | |
| void | Initialize () |
| Initialize the terrain for use. More... | |
| void | ApplyData (sbyte[,] data, Vector2 offset=default(Vector2)) |
| Apply the specified texture data to the terrain. More... | |
| void | ModifyTerrain (Vector2 location, sbyte value) |
| Modify a single point in the terrain. More... | |
| void | RegenerateTerrain () |
| Regenerate the terrain. More... | |
Public Attributes | |
| World | World |
| World to manage terrain in. More... | |
| Vector2 | Center |
| Center of terrain in world units. More... | |
| float | Width |
| Width of terrain in world units. More... | |
| float | Height |
| Height of terrain in world units. More... | |
| int | PointsPerUnit |
| Points per each world unit used to define the terrain in the point cloud. More... | |
| int | CellSize |
| Points per cell. More... | |
| int | SubCellSize |
| Points per sub cell. More... | |
| int | Iterations = 2 |
| Number of iterations to perform in the Marching Squares algorithm. Note: More then 3 has almost no effect on quality. More... | |
| TriangulationAlgorithm | Decomposer |
| Decomposer to use when regenerating terrain. Can be changed on the fly without consequence. Note: Some decomposerers are unstable. More... | |
Simple class to maintain a terrain. It can keep track
Creates a new terrain.
| world | The World |
| area | The area of the terrain. |
Creates a new terrain
| world | The World |
| position | The position (center) of the terrain. |
| width | The width of the terrain. |
| height | The height of the terrain. |
Apply the specified texture data to the terrain.
| data | |
| offset |
| void Initialize | ( | ) |
Initialize the terrain for use.
| void ModifyTerrain | ( | Vector2 | location, |
| sbyte | value | ||
| ) |
Modify a single point in the terrain.
| location | World location to modify. Automatically clipped. |
| value | -1 = inside terrain, 1 = outside terrain |
| void RegenerateTerrain | ( | ) |
Regenerate the terrain.
| int CellSize |
Points per cell.
| Vector2 Center |
Center of terrain in world units.
| TriangulationAlgorithm Decomposer |
Decomposer to use when regenerating terrain. Can be changed on the fly without consequence. Note: Some decomposerers are unstable.
| float Height |
Height of terrain in world units.
| int Iterations = 2 |
Number of iterations to perform in the Marching Squares algorithm. Note: More then 3 has almost no effect on quality.
| int PointsPerUnit |
Points per each world unit used to define the terrain in the point cloud.
| int SubCellSize |
Points per sub cell.
| float Width |
Width of terrain in world units.


Steam_api is object oriented, and works by making a client with a Steam API key and then making player objects from there. Getting store app information does not require an API key so `app` objects do not need to be made through a client object.
Here are a few examples:
from steam_api import client, player, app my_client = client("XXXXXXXXXXXXXXXX") #Put your Steam API key here! my_player = my_client.new_player("76561198075159344") #that's me! my_app = app(440) #Team Fortress 2 print("Profile Name :", my_player.get_profile_name()) print("Profile ID :", my_player.get_steam_id()) print("Number of friends:", my_player.get_num_friends()) print("App Name :", my_app.get_app_name()) print("App ID :", my_app.get_app_id()) print("Store Page URL :", my_app.get_app_storepage_url())
Running that with a valid API key will return:
Profile Name : SHENANIGANS
Profile ID :<PHONE_NUMBER>5159344
Number of friends: 188
App Name : Team Fortress 2
App ID : 440
Store Page URL : http://store.steampowered.com/app/440/
Download the repository and run python setup.py install and it will be install globally on the system. Once it is installed it can be imported and used in projects as shown above.


The singer, 26, bared all for the raunchy photoshoot as he rolled around in bed with Victoria's Secret model Stella Maxwell.
The hunky pop sensation has since admitted that he didn't expect the shoot to be so explicit and likened the ad to shooting "soft core porn".
In an interview with GQ Hype , Liam spoke about getting naked and admitted things got "very raunch very quickly".
He said: "There was a real hollow moment afterwards where I was sitting outside smoking a cigarette thinking, 'I have basically just shot soft-core porn'."
The star also revealed his mum wasn't going to be impressed.
 For another thing, I don’t know how far this is going to go... That was just the first shot!
"There’s this really raunchy shot of me and Stella, and I showed my mum. She took one look at it and gave me a clip round the ear.
"All I was thinking was, 'I better not tell her about the London buses!'"
Liam also confessed it took him more than 10 months of gruelling training in total to prepare for the campaign.
In one nude black and white snap, the butt-naked star gazes seductively at the camera while propping up his head on one bulgingly muscled arm.

Liam recently admitted the modelling shoot got slightly out of hand as he and Stella downed tequila shots before getting down to their saucy antics.
The butt-naked star - – who has a son with fellow singer Cheryl - is currently loved up with his new flame Maya Henry.
The singer, who rose to fame on The X Factor - appeared to take a huge swipe at his ex Cheryl over the weekend as he gushed about how amazing his new girlfriend - and "best friend" - is.
Liam told MTV that he had never experienced the love he has with Maya before.
See the full interview available online now via GQ HYPE


Emoji: Extract, Analyze, and Get Insights
An emoji is worth a thousand words! Regular expressions and helper functionality to aid in extracting and finding emoji from text.
|
A dictionary of the full emoji list together with unicode code points, textual name, group, and sub-group. Based on v13.1 https://unicode.org/Public/emoji/13.1/emoji-test.txt |
|
The same dictionary as a pandas DataFrame |
A function for extracting and summarizing emoji in a text list, with statistics about frequencies and usage. |
|
A function for searching across names, groups, and sub-groups to find emoji based on your keywords of choice. |
|
|
A regular expression to extract the full list. See here on how it was developed: https://www.kaggle.com/eliasdabbas/how-to-create-a-python-regex-to-extract-emoji |
Emoji Search
You can search the whole emoji database with the emoji_search()
function:
import advertools as adv
vegetable_emoji = adv.emoji_search('vegetable')
vegetable_emoji.head()
codepoint |
status |
emoji |
name |
group |
sub_group |
|
|---|---|---|---|---|---|---|
0 |
1F951 |
fully-qualified |
🥑 |
avocado |
Food & Drink |
food-vegetable |
1 |
1F346 |
fully-qualified |
🍆 |
eggplant |
Food & Drink |
food-vegetable |
2 |
1F954 |
fully-qualified |
🥔 |
potato |
Food & Drink |
food-vegetable |
3 |
1F955 |
fully-qualified |
🥕 |
carrot |
Food & Drink |
food-vegetable |
4 |
1F33D |
fully-qualified |
🌽 |
ear of corn |
Food & Drink |
food-vegetable |
Keep in mind that the search uses regular expression, and results might not be exactly what you expect.
love_emoji = adv.emoji_search('love')
love_emoji
codepoint |
status |
emoji |
name |
group |
sub_group |
|
|---|---|---|---|---|---|---|
0 |
1F48C |
fully-qualified |
💌 |
love letter |
Smileys & Emotion |
emotion |
1 |
1F91F |
fully-qualified |
🤟 |
love-you gesture |
People & Body |
hand-fingers-partial |
2 |
1F91F 1F3FB |
fully-qualified |
🤟🏻 |
love-you gesture: light skin tone |
People & Body |
hand-fingers-partial |
3 |
1F91F 1F3FC |
fully-qualified |
🤟🏼 |
love-you gesture: medium-light skin tone |
People & Body |
hand-fingers-partial |
4 |
1F91F 1F3FD |
fully-qualified |
🤟🏽 |
love-you gesture: medium skin tone |
People & Body |
hand-fingers-partial |
5 |
1F91F 1F3FE |
fully-qualified |
🤟🏾 |
love-you gesture: medium-dark skin tone |
People & Body |
hand-fingers-partial |
6 |
1F91F 1F3FF |
fully-qualified |
🤟🏿 |
love-you gesture: dark skin tone |
People & Body |
hand-fingers-partial |
7 |
1F340 |
fully-qualified |
🍀 |
four leaf clover |
Animals & Nature |
plant-other |
8 |
1F3E9 |
fully-qualified |
🏩 |
love hotel |
Travel & Places |
place-building |
9 |
1F94A |
fully-qualified |
🥊 |
boxing glove |
Activities |
sport |
10 |
1F9E4 |
fully-qualified |
🧤 |
gloves |
Objects |
clothing |
11 |
1F1F8 1F1EE |
fully-qualified |
🇸🇮 |
flag: Slovenia |
Flags |
country-flag |
Extract Emoji from Text
Many times you might have some social media text, or any regular text
containing emoji that you want to analyze. The extract_emoji()
function
does that, and returns useful information about the extracted emoji. You can
play around with the following sample text list, modify it, and explore the
different stats, and information about the extracted emoji:
text_list = ['I feel like playing basketball 🏀',
'I like playing football ⚽⚽',
'Not feeling like sports today']
emoji_summary = adv.extract_emoji(text_list)
print(emoji_summary.keys())
- emoji_search(regex)[source]
Return a DataFrame of all emoji entries that match
regex
.The search is run on the name of the emoji, its group, and sub-group.
- Parameters
regex (str) -- regular expression (case insensitive)
>>> import advertools as adv >>> adv.emoji_search('dog') codepoint status emoji name group sub_group 0 1F436 fully-qualified 🐶 dog face Animals & Nature animal-mammal 1 1F415 fully-qualified 🐕 dog Animals & Nature animal-mammal 2 1F9AE fully-qualified 🦮 guide dog Animals & Nature animal-mammal 3 1F415 200D 1F9BA fully-qualified 🐕🦺 service dog Animals & Nature animal-mammal 4 1F32D fully-qualified 🌭 hot dog Food & Drink food-prepared
>>> blue = adv.emoji_search('blue') >>> blue codepoint status emoji name group sub_group 0 1F499 fully-qualified 💙 blue heart Smileys & Emotion emotion 1 1FAD0 fully-qualified 🫐 blueberries Food & Drink food-fruit 2 1F4D8 fully-qualified 📘 blue book Objects book-paper 3 1F535 fully-qualified 🔵 blue circle Symbols geometric 4 1F7E6 fully-qualified 🟦 blue square Symbols geometric 5 1F537 fully-qualified 🔷 large blue diamond Symbols geometric 6 1F539 fully-qualified 🔹 small blue diamond Symbols geometric
- extract_emoji(text_list)[source]
Return a summary dictionary about emoji in
text_list
Get a summary of the number of emoji, their frequency, the top ones, and more.
- Parameters
text_list (list) -- A list of text strings.
- Returns summary
A dictionary with various stats about emoji
>>> posts = ['I am grinning 😀','A grinning cat 😺', ... 'hello! 😀😀😀 💛💛', 'Just text']
>>> emoji_summary = extract_emoji(posts) >>> emoji_summary.keys() dict_keys(['emoji', 'emoji_text', 'emoji_flat', 'emoji_flat_text', 'emoji_counts', 'emoji_freq', 'top_emoji', 'top_emoji_text', 'top_emoji_groups', 'top_emoji_sub_groups', 'overview'])
>>> emoji_summary['emoji'] [['😀'], ['😺'], ['😀', '😀', '😀', '💛', '💛'], []]
>>> emoji_summary['emoji_text'] [['grinning face'], ['grinning cat'], ['grinning face', 'grinning face', 'grinning face', 'yellow heart', 'yellow heart'], []]
A simple extract of emoji from each of the posts. An empty list if none exist
>>> emoji_summary['emoji_flat'] ['😀', '😺', '😀', '😀', '😀', '💛', '💛']
>>> emoji_summary['emoji_flat_text'] ['grinning face', 'grinning cat', 'grinning face', 'grinning face', 'grinning face', 'yellow heart', 'yellow heart']
All emoji in one flat list.
>>> emoji_summary['emoji_counts'] [1, 1, 5, 0]
The count of emoji per post.
>>> emoji_summary['emoji_freq'] [(0, 1), (1, 2), (5, 1)]
Shows how many posts had 0, 1, 2, 3, etc. emoji (number_of_emoji, count)
>>> emoji_summary['top_emoji'] [('😀', 4), ('💛', 2), ('😺', 1)]
>>> emoji_summary['top_emoji_text'] [('grinning face', 4), ('yellow heart', 2), ('grinning cat', 1)]
>>> emoji_summary['top_emoji_groups'] [('Smileys & Emotion', 7)]
>>> emoji_summary['top_emoji_sub_groups'] [('face-smiling', 4), ('emotion', 2), ('cat-face', 1)]
>>> emoji_summary['overview'] {'num_posts': 4, 'num_emoji': 7, 'emoji_per_post': 1.75, 'unique_emoji': 3}


JBoss Overlord API Manager
Logout
JBoss Overlord
/
gadget-server
Overview
Service Refs
Policies
Requests
Summary
This is a project that builds on the Apache Shindig as the open social gadget containers.
Created on
Feb 3, 2011
Created by
Eric Wittmann
Application Key
Activity
Eric Wittmann
updated application
JBoss Overlord
/
gadget-server
.
2 days ago
Eric Wittmann
created application
JBoss Overlord
/
gadget-server
.
3 days ago


class: center, middle # Report Generation --- # This morning: Continue working on yesterday's project. --- # Lets build a dashboard. * I own a used car dealership. * Team of 10 salespeople. * Monthly sales data. ## Visualizations Needed: * number of cars sold (number) * total profit (number)(base price + accessories - taxes) * sales person rankings (table)(sort by $$ sold, include # sold, revenue brought in, total commissions) * car manufacturer rankings (chart) (# sold) * top 10 cars sold (chart) (# of same make/model sold) --- # Elasticsesarch & Kibana ## Elasticsearch: * Rest style data store for indexing documents to search against. * https://www.elastic.co/downloads/elasticsearch ```Bash cd elasticsearch-versionnumber ./bin/elasticsearch ``` ## Kibana * Visualization interface for Elasticsearch. * kibana: https://www.elastic.co/downloads/kibana In a new terminal tab (keep elastic running.) ```Bash cd kibana-versionnumber ./bin/kibana ``` --- # Visit in browser * http://localhost:5601 * http://localhost:5601/app/kibana#/home/tutorial_directory/sampleData?_g=()
Lets Explore Kibana.


teleop.xyz
Status
See
troubleshooting guide
for help
×
Setup Connection
rosapi host
rviz file
connect
teleop.xyz


--- layout: post title: Shrimps date: '2015-06-18T18:30:30+02:00' categories: - Sketches picture_url: https://film-Storyboards.tumblr.com/post/121874681402 ---


You made at least one incorrect response. Please review the instructions and try these questions again.


- MainActivity - Class in com.example.vybe
-
This Activity displays the screen for a user to log in.
- MainActivity() - Constructor for class com.example.vybe.MainActivity
-
- MAP_ZOOM_LEVEL - Static variable in class com.example.vybe.util.Constants
-
- MapFragment - Class in com.example.vybe
-
This fragment displays the map
the activity that calls it can add/remove markers
- MapFragment() - Constructor for class com.example.vybe.MapFragment
-
- MapFragment.OnMapFragmentReadyListener - Interface in com.example.vybe
-
- MapFragmentTest - Class in com.example.vybe
-
This tests to see if the Google Map is loaded when navigating to the Map section
Tests for requirements related to Geolocation and Maps
DISCLAIMER: Google Maps Location Authentication must be enabled for these tests to pass
- MapFragmentTest() - Constructor for class com.example.vybe.MapFragmentTest
-
- MAPVIEW_BUNDLE_KEY - Static variable in class com.example.vybe.util.Constants
-
- MapViewActivity - Class in com.example.vybe
-
Placeholder activity for where the map fragment is displayed.
- MapViewActivity() - Constructor for class com.example.vybe.MapViewActivity
-
- mAuth - Static variable in class com.example.vybe.SocialActivityTest
-
- MyRequestsActivity - Class in com.example.vybe
-
This activity allows the user to send a follow request to another user.
- MyRequestsActivity() - Constructor for class com.example.vybe.MyRequestsActivity
-
- MyVibesActivity - Class in com.example.vybe
-
This Activity displays the screen for a user to view a list of their
vibe event history, sorted by date and time in reverse chronological
order
- MyVibesActivity() - Constructor for class com.example.vybe.MyVibesActivity
-
- MyVibesActivityTest - Class in com.example.vybe
-
This tests for a user's myVibesActivity Page on the MyVibesActivity
Tests for requirements of a users personal vibe history, Vibe Events will be here,
as well as Other Vibe Details
- MyVibesActivityTest() - Constructor for class com.example.vybe.MyVibesActivityTest
-
- MyVibesAdapter - Class in com.example.vybe
-
MyVibesAdapter is a CustomList used for the RecyclerViewAdapter in the main activity that serves as the
list for storing vibe events
- MyVibesAdapter(Context, int, ArrayList<VibeEvent>) - Constructor for class com.example.vybe.MyVibesAdapter
-
- MyVibesAdapter.VibeEventHolder - Class in com.example.vybe
-


Previous | Contents | Index | Next
This software is copyright 2004-2023 Simon Tatham.
Portions copyright Richard Boulton, James Harvey, Mike Pinna, Jonas Kölker, Dariusz Olszewski, Michael Schierl, Lambros Lambrou, Bernd Schmidt, Steffen Bauer, Lennard Sprong, Rogier Goossens, Michael Quevillon, Asher Gordon, Didi Kohen, Ben Harris, Chris Boyle and Phil Tunstall.
The notice below applies to the software as distributed at https://github.com/chrisboyle/sgtpuzzles and does not apply to the additional graphics distributed in the Google Play Store version.
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the ‘Software’), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
 IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


Hash Checker
Fast and simple application for generating and comparison MD5, SHA-1, SHA-224, SHA-256, SHA-384, SHA-512 and CRC-32 hashes from files or text
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Status
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I think this is a Coupled Map Lattice of the Logistic Map. Either way it's pretty. The logistic map is xn+1 = rxn(xn-1), and in this example, we're representing x as a shade from black=0 to white=1. The twist here is that on each iteration, instead of using the result straight away, it processes the results to add smoothing and then noise. The smoothing step: it takes the pixel itself and the pixels above, below, left and right of it (if they exist), and calculates an average. It then sets the pixel value to k times this, plus 1-k times the value before averaging. Finally, noise is added, by generating a number from 0 to 1, multiplying by noise parameter, and adding that to (1-noise) times the pixel value.
As there are lots of ways to set up the initial values of x, and the various parameters, the contents of each parameter field are passed to eval for evaluation. You can use the variables x and y - these range from 0 to 1, where (0, 0) is the bottom left. Yes, I know, I'm using x for the x-coordinate and also the value of each pixel. Sorry. As well as the standard javascript functions, there is also rnd_gauss() which generates a random number according to a standard Gaussian distribution, and rnd_cauchy() that generates a random number from a Cauchy distribution. Some examples, good for copying and pasting, applicable to various fields, are below. Remember to press Reset after changing the parameters.
Math.random()
x+((1-x)*Math.random()*y)
x
y
3.0+y
3.65
xx = x - 0.5; yy = y - 0.5; Math.random()*Math.sqrt((xx*xx)+(yy*yy))*1.4
Math.random()*x*x*x
4 - (y*y)
Peter Corbett, 2014


The above header should have an ID and be present in the TOC.
“Some smarty quotes ‘here’.”
Some fenced code block!


H.B. Woodrose
I currently live in an area where certain substances of an illicit nature are hard to come by and cracked down on often. So my quest for good legal high began.
I was talking with an old friend who used to hook me up before I moved and he mentioned he ordered these seeds off of the internet because he had some friends that took them and had reports of nice LSD-like trips. I had never tripped before, but since they were legal, cheap, and very easy to obtain I figured, what the hell?, and ordered some.
A few days later they came in a bag, over 100 at least. After reading about so many people getting bad stomach reactions, I decided to try them later as I had a dinner thing that night.... Anyway after the dinner I came home and decided to try them anyway.  Now I am a big guy, and I have heard of people taking much more than I and being much smaller, but I had never tripped before. Anyway, I cut the seeds into fourths with a knife and soaked them in cold water for a while. The water turned greenish after an hour or so, so I drank the water and chewed up the seeds in my mouth and swallowed them. I also took a dramamine and some pepto at the same time. I had a very small amount of nausea which when away quickly when I took a tums and another small swig of pepto.
So about three hours later I didnt really feel much and decided to go to sleep. The only thing I had felt was the TV like coming towards me and everything else falling away, also I felt a little euphoric. Just better than usual I guess. I checked my email and had the same thing happen with the monitor, but it wasnt much so I went to bed.
Thats when the cool things happened! I had one dim candle going flickering and I was staring up at the ceiling fan and its shadow and it felt like I was being raised and the fan was falling. An excellent experience indeed. I found I could ground myself very easily by just lighting another candle, but i blew it out and stared at the shadow of the fan on the ceiling. It was sort of changing shape and moving... also the walls seems to be different somehow, (not breathing like many people have said would happen). Anyway, there was also some sound in my ears, mainly a ringing type noise while this was going on.
I told my girlfriend about it, and while she is hesitant... I think I might be able to get her to try it with me. It was a very mile pleasureable experience and I would recommend it for anyone, including first time trippers like me. I think I might up the dosage next time.
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.


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An example server-side crop script. Hidden form values are set when a selection is made. If you press the Crop Image button, the form will be submitted and a 150x150 thumbnail will be dumped to the browser. Try it!


On the Delete for customer page, you can delete customer price models which you do not want to offer to customers any longer. You can delete one or several price models that have been defined for a specific customer.
Usually, you delete a customer price model only in agreement with the relevant customer.
For deleting a customer price model, the relevant marketable service must be deactivated. Existing subscriptions are not affected by the deletion. The corresponding service price model is automatically applied for new subscriptions to the service.
To delete customer price models:


---
layout: slides
title: "On superforecasting"
category: hidden
type: course
semester: Fall 2020
college: Stevens Institute of Technology
permalink: /thought-and-behavior/superforecasting/
---
# On superforecasting.
???
---
# Representing uncertainty
- Recall the draw-a-distribution game
- Probability distribution over possible outcomes
- Outcomes can be continuous, discrete (binary, ternary, ...)
---
class: middle, center, dark, statement
"Forecasting"
---
---
# What is a forecast?
- A prediction about the future
- A probability distribution over outcomes
- Here, a distribution over binary events (i.e., a probability)
---
# Scoring forecasts
- What does it mean to do a good job at forecasting?
---
# Scoring predictions: calibration
---
# Scoring predictions: the Brier score
- Mean squared error between prediction and reality.
- Reality is either 0 or 1.
- Prediction is the forecast.
---
# Scoring predictions: finding the best
---
class: center, middle, dark, statement
*E pluribus unum*
---
# Wisdom of the crowd (Francis Galton)
---
# The Delphi Method
- Expert panel + moderator
- Iterative procedure: aggregation <=> update
---
# "Superforecasting"
- IARPA program
- The Good Judgment Project
- Delphi Method among highest-performing forecasters
---
class: center, middle
# Fin.


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Collapse child labels:
Label dominance order:
Analyzed {{matchingTransactionCount}} out of {{totalTransactionCount}} transactions.
Note: Some transactions are partially billed for the selected date range. Their contributions to other months are not shown.


Congratulations on getting selected for the final round.
The task for today is: “To control RPM of DC motor using Analog Sensors”.
Judging will be primarily based on the time taken to complete the task. The maximum time allotted is 45 minutes. Even if you fail to complete the task, marks will be awarded based on your partially completed circuit and code. You are given 10 mins to read through these instructions and to ask doubts if you have any. Participants should share screen throughout the round.
If you complete your task and show the output within time, full marks will be awarded for code, circuit, and simulation. Further, the winner will be judged based on the time taken.
If you face any technical issues in connecting to the meet, contact the coordinators through the WhatsApp group.
Task Details
You can only use any one of the following sensors:
- Photoresistor
- TMP36 Temperature sensor
- UltraSonic sensor
- Flex Sensor
- Force Sensor
- Gas Sensor
The main task is to control a DC motor according to the analog value from the sensor.
The RPM for your motor should never drop to 0.
Say for example, if the analog value from the Sensor increases then the speed of the DC motor should also increase proportionally and vice - versa.
Hints
- You can just use 2 motors, that’s enough.
- Motor driver is not necessary (remember task 1).
- Choose the sensor wisely!
All the best !!


Background
Taco Fancy is this cool little repository on GitHub, a version control site for developers. Taco Fancy is esscentially an index of taco recipes and all the content is generated by good samaritans helping to build this resource. Taco Fancy is what is used in the early tutorials for GitHub and I figured a search option would be a great resource for home chefs and taco lovers alike.
I was inspired to create Taco Fancy when I decided to beef up my backend skills. A project born out of MEAN stack development, I'm using Angular for the frontend and Mongo for the database. Luckily there was a pre-exisiting API for the repo. For the frontend I'm using the grid from the CSS boilerplate: Skeleton, CSS, HTML5, and jQuery.
Design
I started with a basic IA to lay out the navigation and define what the website would do and wouldn't do.
Users will be able to search tacos by a full list, keywords, tags, or a randomize option. On the recipe pages, it will be populated by the name, contributor's credits (if available), tags, ingredients, instructions, check boxes, the ability to share and to print.
This app currently is not able to edit recipes, upload to galleries, rate recipes, and no main dish photo; these are not necessary to the function of the app.
The target user is 18-24, avid users of how-to's and digital instructables, has a wide range of dietary preferences, and can either be a novice or an amateur chef. For our User Persona, I've decided to call him Jeff
Jeff is a college freshmen and the number 1 fan of tacos. He's planning to cook dinner with his roommates tonight in their dorm and since he isn't much of a chef, he needs to find a quick recipe so he and his roommates can go get the ingredients.
- Open the site
- Randomize a recipe
- Check off a list for the ingredients he already has
- share the recipe with roommates so they can get the rest of the ingredients
Branding
For the logo of Taco Fancy, I wanted to do bright primary colors reminiscent of Mexico. I also wanted to have a more whimsical flair since it's such a light-hearted app. I created a circle with digital gouache and chose a chalky decorative type face. The yellow background of the logo represents a delicious (corn) taco.
Alongside the visual inspiration, I decided to add a cute little gaouche taco illustration to keep up visual cues to scroll down. There's a function navigation that gradiates in at a scroll point.


{% extends "base.html" %} {% load humanize %} {% load accounts %} {% load steam_filters %} {% load static %} {% block scripts %} {% endblock %} {% block content %}
Joined: {{ steamInfo.timecreated|convert_timestamp|default:"---" }}
Last log off: {{ steamInfo.lastlogoff|convert_timestamp }}
{% if user.is_authenticated and pageUser %}| Name | Last Log Off |
|---|---|
| {{ friend.personaname }} | {{ friend.lastlogoff|convert_timestamp }} |
No friends yet.
{% endif %} {% elif show_games_played %} {% if games_played and games_played.total_count != 0 %}| name | playtime last 2 weeks | playtime on record | logo |
|---|---|---|---|
| {{ game.name }} | {{ game.playtime_2weeks|full_time }} | {{ game.playtime_forever|full_time }} |
No games played in the last 2 weeks.
{% endif %} {% elif show_games_owned %} {% if games_owned and games_owned.game_count != 0 %}Game count: {{ games_owned.game_count }}
| name | playtime |
|---|---|
| {{ game.name }} | {{ game.playtime_forever|full_time }} |
No games owned yet.
{% endif %} {% endif %} {% endblock %}


Whiskey Reactor UI
Bottle number
Whiskey Type
Quantity(ml)
Clean after Use
No
Yes
Start filling
Off
On


We invite you to celebrate our wedding
A modest secretive simple indomitable geek - inherent listener, runner, yoga lover, from a tiny place in this speck of universe - experiencing the possibilities beyond.
An outgoing chirpy complex staunch technologist - intrinsic chatter, rambler, sea lover, roaming within the tiny places in this speck of universe - persevering the possibilities beyond.
In the midst of the unknowns, we met each other. A little sunshine of hope. We shared our stories. We shared our lives. Thus began this alluring journey of exploring togetherness.
Charismatic chaos! The evening set up as default rituals that turned into a start of envisaging the best of our lives!
✨Juxtaposed love birds coming together to live the next phase of life✨
Realistic hit. The start of awesome days when we - the imperfect souls - started letting our guards down and getting to know each other. Beginning of Our story