Torq is an app for medical device representatives. Joint replacement surgeries require a human from the company which created the joint replacement to be in the operating room with the surgeon. As surgeons' schedules change throughout the day, reps are paid to wait around or hurry to the hospital. Torq sends reps live schedule updates using push notifications by hooking into hospitals' electronic health records. I scaled Torq from zero lines of code to its use by over 20 hospitals around Boston.
Check it outConformis is an app for surgeons who have upcoming joint replacement surgeries. The iViewer app shows surgeons their upcoming joint replacement surgeries. Tapping surgeries in the list reveals a PDF detailing the physical specifications of the joint replacement for that surgery.
Check it outQeepsake sends parents daily or weekly, age appropriate questions via text message about their children. "Is Jack teething?" "What is Jill's new favorite toy?" Parents respond with memories and photos and Qeepsake mails them an album. This project scaled to over 100,000 users. My client even appeared on Shark Tank while I was working on his app.
Check it out


Before Change
if np.issubdtype(image.dtype, np.floating):
resolution = 2 * np.finfo(image.dtype).resolution
if h < resolution:
h = resolution
h_corrected = h - resolution / 2.0
shifted_img = image - h
else:
shifted_img = _subtract_constant_clip(image, h)
After Change
// >>> b[0] == b[1]
// True
//
if np.issubdtype(type(h), np.floating) and \
np.issubdtype(image.dtype, np.integer):
if ((h % 1) != 0):
warn("possible precision loss converting image to "
"floating point. To silence this warning, "
"ensure image and h have same data type.",
stacklevel=2)
image = image.astype(np.float_)
else:
h = image.dtype.type(h)
if (h == 0):
raise ValueError("h = 0 is ambiguous, use local_maxima() "
"instead?")
if np.issubdtype(image.dtype, np.floating):
// The purpose of the resolution variable is to allow for the
// small rounding errors that inevitably occur when doing
// floating point arithmetic. We want shifted_img to be
// guaranteed to be h less than image. If we only subtract h
// there may be pixels were shifted_img ends up being
// slightly greater than image - h.
//
// The resolution is scaled based on the pixel values in the
// image because floating point precision is relative. A
// very large value of 1.0e10 will have a large precision,
// say +-1.0e4, and a very small value of 1.0e-10 will have
// a very small precision, say +-1.0e-16.
//
resolution = 2 * np.finfo(image.dtype).resolution * np.abs(image)
shifted_img = image - h - resolution
else:
shifted_img = _subtract_constant_clip(image, h)
rec_img = greyreconstruct.reconstruction(shifted_img, image,
method="dilation", selem=selem)
residue_img = image - rec_img
return (residue_img >= h).astype(np.uint8)
def h_minima(image, h, selem=None):


Nav-Panel
Hop in
Login
Run Tests
Nodes
Close menu
Social
Shout Out
Sign in
Logout
Back
Share
Comments
Comments
Comments


<%PhotosCount%>
Name
Size
Resolution
<%foreach photo in photos%>
<%photo.name%>
<%photo.size%>
<%photo.resolution%>
<%endforeach%>
Hello World!


| Package | Description |
|---|---|
| com.sun.net.httpserver |
Provides a simple high-level Http server API, which can be used to build
embedded HTTP servers.
|
| com.sun.net.httpserver.spi |
Provides a pluggable service provider interface, which allows the HTTP server
implementation to be replaced with other implementations.
|
| Class and Description |
|---|
| Authenticator
Authenticator represents an implementation of an HTTP authentication
mechanism.
|
| Authenticator.Result
Base class for return type from authenticate() method
|
| Filter
A filter used to pre- and post-process incoming requests.
|
| Filter.Chain
a chain of filters associated with a HttpServer.
|
| Headers |
| HttpContext
HttpContext represents a mapping between the root URI path of an application
to a
HttpHandler which is invoked to handle requests destined
for that path on the associated HttpServer or HttpsServer. |
| HttpExchange
This class encapsulates a HTTP request received and a
response to be generated in one exchange.
|
| HttpHandler
A handler which is invoked to process HTTP exchanges.
|
| HttpPrincipal
Represents a user authenticated by HTTP Basic or Digest
authentication.
|
| HttpsConfigurator
This class is used to configure the https parameters for each incoming
https connection on a HttpsServer.
|
| HttpServer
This class implements a simple HTTP server.
|
| HttpsParameters
Represents the set of parameters for each https
connection negotiated with clients.
|
| HttpsServer
This class is an extension of
HttpServer which provides
support for HTTPS. |
| Class and Description |
|---|
| HttpServer
This class implements a simple HTTP server.
|
| HttpsServer
This class is an extension of
HttpServer which provides
support for HTTPS. |
Copyright © 2005, 2019, Oracle and/or its affiliates. All rights reserved.


We practice weekly, focusing primarily on swimming, biking, and running. We throw in some cross-training as well.
We race as part of the Southeast Collegiate Triathlon Conference, racing in several collegiate races per year as well as a few local races in the spring and summer.
Between competing in Ragnar relay events, competing in local races, and volunteering with some of our favorite outdoor organizations, we find ways to bond as a team while giving back to our awesome tri community.
Since 2006, the TriVols have been a training ground for triathletes to compete at the Collegiate level in the Southeast and against the top teams in the nation at Collegiate Nationals. More than just competition, the TriVols offer a fun and inclusive atmosphere for students at the University of Tennessee to train, as well as be involved in the triathlon community in East Tennessee. We do social events as well, be on the look out for awesome events in the weekly email! Interested in joining? Contact us below.
We have two options for to you to join the team! A competitive and non-competitive option.
- Dues $70 for semester, $120 for year - Travel with Team for Conference Races, team covers travel fees - Must have USAT ID - Come to Practices - Race fees covered by you, race discounts for conference races (if available)
- Dues $40 for semester, $70 for year - Come out for a Non-Conference race with the team - Come to Practices - Race fees covered by you
| M | T | W | Th | F | Sat | Sun | |
|---|---|---|---|---|---|---|---|
| 6:00 AM | Spin | Run | Flex | Flex | |||
| 7:30 PM | Run (6:30) @BBM* |
Swim | Swim |
| Date | Location | Race Type | Conference / Non-Conference | hours away |
|---|---|---|---|---|
| March 2 | LaGrange, GA | Sprint | Conference | 4.5 |
| March 24 | Fort Gordon, GA | Sprint | Conference | 5.5 |
| March 31 | Knoxville, TN | Marathon | Fun | — |
| April 5-6 | Nationals - Tempe, AZ | Draft/Sprint Oly, Relay | Nationals | 27 |
| April 7 | Athens, GA | Sprint | Non-Conference | 4 |
| April 12-13 | Trail Ragnar Atlanta | Ragnar | Fun | 3.5 |
| April 14 | TRECS Parking Lot | Sprint | Non-Conference | — |
| April 28 | Nashville, TN | Marathon | Fun | 3 |
| May 17-18 | Trail Ragnar Kentuckiana | Ragnar | Fun | 3-4.5 |
President
Secretary
Treasurer
Social


Expense analyzer
{% if redirect_from %}
Please sign in before navigating to {{ redirect_from }}
{% else %}
Sign in to access your expenses
{% endif %}
Welcome,
!
Upload an expense and save it to your personal storage bucket
Upload image:
Select store type:
Coop Mega
Bunnpris (TBA)
Rema 1000 (TBA)
Upload expense
Sign out


python-encrypted-cookiejar¶
Fernet-encrypted cookie jar
Installation¶
pip install encrypted_cookiejar
Usage¶
from encrypted_securid import EncryptedCookieJar
cookies = EncryptedCookieJar()
cookies.load('encrypted_cookie_jar', password=password)
r = requests.get(url, cookies=cookies)
cookies.save('encrypted_cookie_jar', password=password)
API documentation¶
Cookies are NOT loaded from the named file until either the .load() or .revert() method is called.
Return an iterator of names of cookies from the jar
Return a list of names of cookies from the jar
Load cookies from a file
Save cookies to a file
This is raised in case of error parsing file


Seer Manakia:
Why would the Flame Lord ask a Human for assistance with a tribal matter? Since we are short-handed I won't refuse.
How can I help?


Hi there fellow art lovers! Welcome to my site!  Feel free to contact me with any questions/comments about my work, or any problems you have with the site itself.
Thanks!
Tracy Parker
Pottery, both functional and art pieces. Glazed Stoneware, and hand painted Earthenware (bisque).
Music photography is a whole other animal, with it's own unique set of challenges.
© 2019 Tracy Parker.


In order to better understand what a framework is, let’s leave the world of computer science for a moment and imagine a mountaineering adventure. Developing an application is very similar to climbing a rock wall: you are at the bottom (you have an application to be created) and you need to reach the summit (and be pleased with the achievement of designing an application that works perfectly.)
In order to better understand what a framework is, let’s leave the world of computer science for a moment and imagine a mountaineering adventure. Developing an application is very similar to climbing a rock wall: you are at the bottom (you have an application to be created) and you need to reach the summit (and be pleased with the achievement of designing an application that works perfectly.)
In order to better understand what a framework is, let’s leave the world of computer science for a moment and imagine a mountaineering adventure. Developing an application is very similar to climbing a rock wall: you are at the bottom (you have an application to be created) and you need to reach the summit (and be pleased with the achievement of designing an application that works perfectly.)


第 2 章 Geometries and Aesthetics
Two steps:
Step 1: What geometries do you see?
Step 2: With a given geometry, what aesthetics do you observe?
Geometries?
Aesthetics?
2.1 An Example
Geom:
geom_point
:x, y：varies with observations
color (線框顏色): constant
stroke (線框粗細): constant
fill (內部塗色): constant
size (點的大小): constant
x, y: varies with observations
label: varies with observations
hjust (文字水平錨點）：between 0 and 1
vjust (文字垂直錨點）: between 0 and 1
# take Colombia, Normway, and Gemany as an example
<- list()
data4plot $point$data <- {
data4plotdata.frame(
x=c(52.5, 56, 58.5),
y=c(48.6, 54.9, 58)
)
}$text$data <- {
data4plotdata.frame(
x=c(52.5, 56, 58.5),
y=c(48.6, 54.9, 58),
label=c("Colombia", "Norway", "Germany")
) }
<- {
myplot ggplot()+
geom_point(
data=data4plot$point$data,
mapping=aes(
x=x, y=y
),fill="blue",
shape=21,
color="black",
stroke=1,
size=1
+
)geom_text(
data=data4plot$text$data,
mapping=aes(
x=x, y=y, label=label
),hjust = 1,
size = 1
)
} myplot
- use
econDV2::ggdash()
to quickly create a shiny app of your ggplot to fine tune your graph.
2.1.1 econDV2::ggdash
<- {
myplot ggplot()+
geom_point(
data=data4plot$point$data,
mapping=aes(
x=x, y=y
),fill="blue", #input$fill_point
shape=21, # default point is a circle without border, you need another type of point
color="black", #input$color_point
stroke=1, #input$stroke_point
size=1 #input$size_point
+
)geom_text(
data=data4plot$text$data,
mapping=aes(
x=x, y=y, label=label
),hjust = 1, #input$hjust_text
size = 1 #input$size_text
)
} myplot
<- {
myplot ggplot() +
geom_point(
data = data4plot$point$data,
mapping = aes(
x = x, y = y
),fill = "#2fc1d3",
shape = 21,
color = "black",
stroke = 1,
size = 12
+
) geom_text(
data = data4plot$text$data,
mapping = aes(
x = x, y = y, label = label
),hjust = 0,
size = 12
)
} myplot
2.1.2 Script saving
If you are happy with your graph, you may want to make it reproducible and easy to use.
- Think of how you want to use it next time.
Turn your script into a function, and save in a R script.
Select the code lines that you want to turn into a function
Code > Extract Function
The result after proper revision:
<- function(data4plot) {
myGoodPlot <- {
myplot ggplot() +
geom_point(
data = data4plot$point$data,
mapping = aes(
x = x, y = y
),fill = "#2fc1d3",
shape = 21,
color = "black",
stroke = 1,
size = 12
+
) geom_text(
data = data4plot$text$data,
mapping = aes(
x = x, y = y, label = label
),hjust = 0,
size = 12
)
}
myplot }
To reuse:
source("support/ggplots.R") # suppose this is where your script file is
<- list()
data4plot $point$data <- {
data4plotdata.frame(
x=c(52.5, 56, 58.5),
y=c(48.6, 54.9, 58)
)
}$text$data <- {
data4plotdata.frame(
x=c(52.5, 56, 58.5),
y=c(48.6, 54.9, 58),
label=c("Colombia", "Norway", "Germany")
)
}
myGoodPlot(data4plot)
- If you replace
data4plot
with the real data, you get the accurate graph that you want.
2.1.3 Graph output
Saving is tricky. You need to find the viewport ratio. (Different computers are different)
Given your graph width and height, you can save your output as:
dir.create("works")
ggsave(
filename = "works/week1.png",
plot=myGoodPlot(data4plot),
width=930,
height=400,
units="mm" # text size is default in mm unit
)
2.1.4 ggdash more
- ggdash can control any input within a programming block
<- {
myplot2 = 21 #input$shape_point
myshape ggplot() +
geom_point(
data = data4plot$point$data,
mapping = aes(
x = x, y = y
),fill = "#2fc1d3",
shape = myshape,
color = "black",
stroke = 1,
size = 12
+
) geom_text(
data = data4plot$text$data,
mapping = aes(
x = x +
0, #input$x_text
y = y, label = label
),hjust = 0,
size = 12
)
} myplot2
2.2 Inheritance
2.2.1 Data
Common data source can be put in
ggplot()
:ALL geoms will use the same data to find aes() mapping,
UNLESS the geom has its own data supplied.
= data4plot$text$data
data
<- {
myplot ggplot(data = data,
+
) geom_point(
mapping = aes(
x = x, y = y
),fill = "#2fc1d3",
shape = 21,
color = "black",
stroke = 1,
size = 12
+
) geom_text(
# data = data4plot$text$data,
mapping = aes(
x = x, y = y, label = label
),hjust = 0,
size = 12
) }
2.2.2 Aesthetics
<- {
myplot ggplot(
data = data,
mapping = aes(x=x, y=y)
+
) geom_point(
fill = "#2fc1d3",
shape = 21,
color = "black",
stroke = 1,
size = 12
+
) geom_text(
mapping = aes(
label = label
),hjust = 0,
size = 12
)
} myplot
<- function(data) {
plot_hightlightCountries <- {
myplot ggplot(data = data,
+
) geom_point(
mapping = aes(
x = x, y = y
),fill = "#2fc1d3",
shape = 21,
color = "black",
stroke = 1,
size = 12
+
) geom_text(
# data = data4plot$text$data,
mapping = aes(
x = x, y = y, label = label
),hjust = 0,
size = 12
)
}
myplot }
2.2.3 Stop data inheritance
- When a geom has its own data supplied, data inheritance stops.
<-
nonhighlightedCountries data.frame(
x=c(48, 52, 53),
y=c(48, 53, 54)
)<- data4plot$text$data
highlightedCountries
<-
plot_allCountries
{plot_hightlightCountries(highlightedCountries) +
geom_point(
data = nonhighlightedCountries,
aes(
x=x,
y=y
),size = 12,
color= "#a4dce6"
)
}
plot_allCountries
<- function(highlightedCountries, nonhighlightedCountries) {
plot_allCountries plot_hightlightCountries(highlightedCountries) +
geom_point(
data = nonhighlightedCountries,
aes(
x=x,
y=y
),size = 12,
color= "#a4dce6"
) }
2.2.4 Finish panel
<- {
plot_obsessionWithBorders plot_allCountries(
hightlightedCountries = highlightedCountries,
unhighlightedCountries = unhighlightedCountries
+
)geom_abline(
aes(
slope=1,
intercept=0
),color = "#549ab6",
linetype = 2,
size=2
)
} plot_obsessionWithBorders
+
plot_obsessionWithBorders geom_abline(
aes(
slope=1,
intercept=0
),color = "#549ab6",
linetype = 2,
size=2
)
<- function(plot_obsessionWithBorders) {
hightlightXYequal +
plot_obsessionWithBorders geom_abline(
aes(
slope=1,
intercept=0
),color = "#549ab6",
linetype = 2,
size=2
) }
2.3 Graph export
The easiest way to export the graph as you see on gg$dash()
is to right click the image on the shiny dashboard and choose save image as to export the image.


Note: No data will go to the server. This is all client-side in your browser.
Format is comma-separated with quotes like Excel. A guide to columns:
First row is used to name the various user states you have. It should be in the format "Cohort group type,Cohort group value,Cohort day,State1 name,State2 name,...".
The dataset may have the same user appear in many rows that are of different group types. What's important is for each group type the user is only in one row with one group value; aka the tuple (group value, cohort day) should be a unique row for each cohort group type. Order of the rows does not matter.
Here's a simple example for a fake social network with "Sign-up Referrer", "Favorite feature", and "Total" cohort group types. This only counts a user towards one sign-up referrer row, one favorite feature row, and one total row. In the case of "Total" the only valid grouping value is the empty string, which this tool treats specially.
| Cohort group type | Cohort group value | Cohort day | Born | Updated profile | Sent first message |
|---|---|---|---|---|---|
| Sign-up referrer | Search | 10/25/12 | 5 | 5 | 5 |
| Sign-up referrer | Search | 10/26/12 | 10 | 10 | 0 |
| Sign-up referrer | 10/25/12 | 5 | 5 | 5 | |
| Sign-up referrer | 10/26/12 | 5 | 0 | 5 | |
| Favorite feature | Chat | 10/25/12 | 0 | 5 | 10 |
| Favorite feature | Chat | 10/26/12 | 15 | 5 | 0 |
| Favorite feature | Reading news | 10/25/12 | 10 | 5 | 0 |
| Favorite feature | Reading news | 10/26/12 | 5 | 5 | 5 |
| Total | 10/25/12 | 10 | 10 | 10 | |
| Total | 10/26/12 | 20 | 10 | 5 |
The sign of a column value is treated specially. The cohort data may include two rows with the same (group value, cohort day) tuple, but one with all positive column values, and one with all negative column values. Example usage: When a user joins your service, have a positive value on their birthday. When the same user leaves the service, have the same negative value on their leave date. This lets you see the rate of sign-ups and drop- offs independently. If you view both positive and negative values cumulatively, you will plot your peak active users over time.
A cohort is a group of people who share a common characteristic or experience within a defined period (Wikipedia). It's used a lot in health to track how different groups of patients respond to disease and medication. It can be used in business to track progress in the funnel.
For software and websites, cohorts are useful because they let you measure the impact of your product changes over time. Simple example: Using cohorts you can see the conversion rate of new users from two months ago and compare it to new users of today. Ideally, this would let you judge if your software is getting better over time, users are getting happier, etc. Sometimes you'll see that things are getting worse.
Cohort analysis can apply to more than just users. For example, you could treat a set of articles on a blog as the source dataset; the levels of traffic or reshares could be mutually exclusive states; and you could treat common tags as a group type, or author as a group type. This tool would let you drill down and compare all of those groupings pretty easily.
One of the most interesting things about cohort analysis is the graphs change over time. If you take a snapshot of your cohort data today and then take another snapshot two months from now, you'll see that the older cohort bars have changed. This happens because users who signed up two months ago remain active and continue to make progress in your funnel over extended periods. It's useful to save your cohort datasets after you collect them, so you can compare to the past.
Other things to read to understand the motivation and method behind this:
Here's a quick guide to the calculations presented on the right. A "bar" is every cohort for a particular day. A "bar segment" is one part of the bar for a day in single color, corresponding to a particular "cohort state" (like "Made two posts" above), which is usually some level of progression in the funnel.
Copyright 2012-2015 Brett Slatkin
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.
Built using D3, jQuery, Web Fonts, and Subtle Patterns


Areas
Database,Frontend, UI/UX Designing,Algorithm are among my strongest skills. I have created many solid backend and frontend
application. Also i am giving some of my time to learn Data Science and Machine Learning.
Tools
OS Windows 10,Ubuntu 16.04 LTS(Development), Mac OS X El Capitan, CentOs (Server)
IDE Eclipse,Visual Studio,Android Studio,Code Block
Code Edtior Atom,Emac,Vim,Monodevelop,Sublime Text
Other Unity,Unreal Engine,Git,Photoshop,Illustrator,After Effects
Gadgets Dell Xps 13 9350, Macbook Air, PC build.


This is a minimal example of the cite tag
. Good to check if your changes will work
. This sentence is followed by a non-existent cite tag
which just displays "undefined". I don't think that's much of a problem.
References


WITNESS LIST
Appropriations - S/C on Article II Committee
February 12, 2013 - 7:30 AM
Department of Aging and Disability Services
For:
Fritzsching, Jacob (Self)
Fritzsching, Kimberlee (Self)
Linial, George (LeadingAge Texas)
Against:
Graves, Tim (Texas health care association)
On:
Berndt, Trey (AARP)
Betts, Wjilliam (Self)
Borel, Dennis (Coalition of Texans with Disabilities)
Carrillo, Dolores (Adapt)
Cranston, Catherine (Self; Personal attendant coalition of texas and adapt of texas)
Dillen, Jeffrey (Texana Center)
Dooley, Michelle (Self; Community now! Mom of Morgan Dooley)
Durden, Veronda (DADS)
Hernandez, Richard (Self; ResCare, Inc.)
Jenkins, James (DADS)
Kafka, Bob (Adapt)
Mason, Ruth (Self)
McPhail, Jennifer (Self; Adapt)
Metz, Albert (Adapt)
Murphree, Susan (DISABILITY RIGHTS TEXAS)
Stacey, Frank (Self; Adapt)
Tate, Joe (Self; Community NOW!)
Umscheid, David (Health and human services commission)
Vesowate, Joe (Dads)
Watkins, Sarah (Community Now)
Weizenbaum, Jon (Texas Department of Aging and Disability Services)
Registering, but not testifying:
Against:
Adewale, Habeeb (Self; Texas physical Therapy Association)
Aikman, Ashley (Self; Texas Physical Therapy Association)
Bryant, Margaret (Self; TPTA)
Burato, Lysette (Self; TPTA)
Davis, Shannon (Self; TPTA)
Gieringer, Matthew (Self; TPTA)
Gobert, Denise (Self; Texas Physical Therapy Association)
Huffstetter, Ann (Self; Tpta)
Lawlor, Tom (Self; Texas physical therapy association)
Mahler, Geran (Self; Tpta)
McAdams, Bryan (Self; Texas physical therapy association)
1
WITNESS LIST
Against:
Miller, Ashlea (Self; TPTA)
Nordin, Jenny (Self; Texas physical theraPY assoc.)
Palmer, Lynn (Self; TPTA)
Peterson, Cory (Self; Texas physical therapy association)
Schwarz, Katie (Self; Texas physical therapy association)
Smith, Donna (Self; Texas Physical Therapy Association)
Tsay, Elaine (Self; Texas Physical Therapy Association)
Zachary, Hilary (Self; Texas physical therapy association)
On:
Adams, Chris (Dept of Aging and Disability Svcs)
Childress, Brenda (Self; Harris County precinct 4.)
Cook, David (Dads)
Salinas Valdez, Debby (Self; Disabilty Rigts advocate TAAID. and Grade - various other
organizations and self)
Salovitzx, Heiwa (Adapt)
Sloan, Carol (DADS)
Wittie, David (Self; ADAPT of Texas)
2


{% extends "flicket_base.html" %} {% block content %}
{{ _('Type department and/or category and pick from drop down list to change category.') }} Available departments and categories.


September 23rd – October 8th: Visiting Researcher
Enrike Hurtado Mendieta: The Digital Txalaparta
Visiting researcher, Enrike Hurtado Mendieta, is working on a project that explores how the txalaparta, a Basque traditional acoustic instrument, can be represented in the digital domain. The project involves studying the generative rules of the txalaparta playing, digital representation and cultural reception of such work. Further activities include:
October 1st, Music at MFM lunchtime seminar
October 1st, Enrike, MFM RiP (Research in Progress) seminar
October 2nd, Txalaparta workshop at 1pm, Recital Room, Falmer House
October 3rd: Guest lecture (Silverstone 121, 2pm)
Andrew Sorensen: Programming In Time – Live Coding for Creative Performances
The act of programming is typically removed from a program’s ongoing execution, both temporally and spatially. This is particularly true for real-time systems, where the system’s operation is often tightly coupled with the physical environment. This talk aims to challenge this separation by looking at programming as the ongoing orchestration of real-time processes through time – an ongoing cyber-physical dialogue between the programmer, the machine and the environment.
After a very brief history of live coding Andrew’s talk will delve into some of the deeper technical issues surrounding this challenging domain.
Using Andrew’s Extempore system, this talk will explore notions of time, liveness, feedback and procedural orchestration, addressing these ideas from the perspective of both end-user programmers as well as system designers.
Biography: Andrew Sorensen is an artist-programmer whose interests lie at the intersection of computer science and creative practice. Andrew is well known for creating the programming languages that he uses in live performance to generate improvised audiovisual theatre. He has been invited to perform these contemporary audiovisual improvisations around the world. Andrew is a Senior Research Fellow at the Queensland University of Technology and is the author of the Impromptu and Extempore programming language environments.
October 28th: Adam Linson – Improvisation Workshop (Creativity Zone, 10-12)
Real-time interactive music systems: Design, Development and Performance
What relationships between interactive system design, development and performance lie beneath the surface? Why should we understand how we interact with our instruments physically, mentally and musically? Why should we understand the internal makeup of the hardware and software we use? In this hands-on workshop, Adam Linson will draw on examples from his experience with electro-acoustic improvisation to discuss the concepts, motivations and technologies behind his approach to real-time interactive music systems. Further information on Adam here.
The workshop is mandatory for the 3rd year Music Informatics students and open to all Media, Film and Music students. Participants are invited to bring any acoustic instruments and/or software along. There will be a chance for practical engagement. Please sign up here
October 30th: Gene Felice II – Biosensor Workshop (Recital Room, Falmer House, 10-11.30)
Bio sensor workshop with Gene Felice II. Open to all MFM students. This event is in relation to Gene’s presentation later in the day, organised by Kate O’Riordan.
December 4th: Alice Eldridge. (Jubilee G35, 3-4pm)
Listening to the Forests and Feeding the Crickets: Field notes from a transdisciplinary soundscapologist
In L’Arte dei Rumori (1913) Russolo decreed the value of everyday soundscape elements in the compositional palette; In The Tuning of the World (1977) Murray Schaefer espoused the value of listening to and preservation of our everyday soundscape as both methodology and aim of Acoustic Ecology. With the emergence of Soundscape Ecology, the scientific value of listening to natural soundscapes as a means of assessing biodiversity is now being recognised.
It was for primarily scientific purposes that I spent 8 weeks recording the soundscape of Ecuadorian Cloud Forest and Amazon this summer, but I could not help listening as a musician and as a human too. In this informal talk I will consider what we can learn from different ways of listening to the soundscape and illustrate with recordings and images from our field work.
December (Date TBC): SLOW (Sussex Laptop Orchestra Workshop)
Chad McKinney will lead the inauguration meeting of the Sussex Laptop Orchestra. Chad will present his research and practice in networked music performance and introduces his software for synced and distributed musical performance. Participants should bring their computers as the orchestra will take form during this session.


{% extends "blog/layout.html" %} {% block content %}
Date: {{ past_event.fromdate }} - {{ past_event.todate }} {{ past_event.website }}
No past events have been added yet.


Please provide all the cigarette brands you bought with their pack size & quantity.
USER ID :
Product
Pack Size
Quantity
9th Century
A380
Benson & Hedges
Bosston
Camel
Capital
Chesterfield
De'Leaf
Dunhill
International Peter Stuyvesant
Kent
L&M
Lucky Strike
Manchester
Marlboro
Mevius
Mone
Pall Mall
Peter Stuyvesant
Promax
Saat
Sampoerna A
Soho
Willson
Winston
20
Checkout


Shaan
Kastuar
Nice to meet you!
I'm a multi-faceted young professional in the NYC area, and am never afraid to get my hands dirty and dive into unfamiliar territory - I relish the opportunity to gain new experiences, acquire new skills, and learn from those more experienced.
I've recently completed the Media Managemet Graduate Program at The New School. Interpersonal social skills are attributes that are an inherent part of my personality. Forging connections with people, learning from others, and teaching new skills are activities I naturally find enjoyable and energizing. I love people and I love making friends. I am extroverted by nature and thrive on collaboration, and enjoy the opportunities to learn from others, teach teammates new skills, and brainstorm to create new ideas.
I strive to exist at the intersection of the left brained and the right brained, and hone my skills towards the goal of occupying the overlap between, creativity, communication, and technical analysis.
On a personal level, I'm a diehard New York Rangers and New York Giants fan (#LGR!) and have a lifelong passion for creating and enjoying music.
Feel free to check out some variants of my resume.
Media Focused Resume Technology Focused Resume Long Form ResumeI'm always looking to learn and collaborate, so whether you'd like to give some feedback on my work, join a project together, or just say hello, I'd love to hear from you!


Q: How does JavaScript compare
to HTML and CSS?
A: HTML and CSS are for the structure
and the design mean while javascript is
for responsive design and interactive
functionality.
Q: Explain control flow and loops
using an example process from
everyday life, for example 'waking
up' or 'brushing your teeth'.
A: Loops define repitition, and daily
activities like waking up and brushing
can be considered repititious. There
is a level of subconscious flow-control
involved because we have 'break/check-points'
to make sure activities flow smoothly,
and in the proper order e.g. open door
first, before walking through, apply
paste to brush before choosing to brush
teeth.
Q: Explain the difference between
accessing data from arrays and
objects.
A: Data can be accessed from arrays
using numeric index positions, even
for nested array situations. Accessing
data from object literals is slightly
different - being akin to getting
the value using 'keys'. The object
literals have a property value system.
Q: Explain what functions are
and why they are useful.
A: Functions help follow the DRY principle
in software programming. It is convenient
to be able to name a set of code as a
function and invoke/call the function
instead of having to write the same
set of code multiple times in a program


$def with (subsystems)
$if 'subsystems' in subsystems.keys():
Subsystems:
$for system in subsystems['subsystems'].keys():
$system
$else:
Subgroups:
$for group in subsystems['subgroups'].keys():
$group
Control files:
$for file in subsystems['controlfiles'].keys():
$file: $subsystems['controlfiles'][file]
Tasks:
$subsystems['tasks']


Let's
in
cs.hku.hk
Upcoming Events
Public Seminar of Physics RPg Students.
Three-dimensional Quantum Hall Effect and Metal-insulator Transition in ZrTe5.
Sharing Session by MPH Alumni.


Hello there. My name is Stykh. I'm a software engineer, game developer and mediocre musician. This is my website where I might post blogs but will mostly be where people can access my madness of code projects. Feel free to reach out to me on my Tumblr or find me on Discord!


Jose Mourinho was warned about 'big baby' Romelu Lukaku, says Steve Walsh
Steve Walsh, who left Everton in May 2018, also says Manchester United's Paul Pogba is 'not his type of player'
Jose Mourinho was warned about signing 'big baby' Romelu Lukaku, according to Everton's former director of football Steve Walsh.
Walsh was at Everton when United signed Lukaku in 2017 and says he warned the then Old Trafford boss about the Belgian's behaviour.
Former Leicester scout Walsh, who was credited with playing a key role in the Foxes' Premier League triumph in 2016, had previously worked with Mourinho at Chelsea during his first spell at the club.
Walsh told The Athletic: "When Jose [Mourinho] signed Romelu Lukaku from Everton, I remember saying to him, 'You have to be careful with Lukaku.
"He said he could handle him. I don't think he really got Lukaku on-side mentally, which you have to do.
"That is the case with him and Paul Pogba. They aren't my type of players. They are more about themselves than the team. I wouldn't have touched them. Because they are good players doesn't mean you are going to get a good team out of it."
Walsh was sacked by Everton in May 2018, with Marcel Brands taking on the director of football role.
Mourinho, who started Lukaku regularly, was sacked last December less than 18 months after signing the Belgium international striker, who followed the Portuguese manager out of the Old Trafford exit door this summer, moving to Inter Milan.
The 26-year-old told Belgian newspaper Het Belang van Limburg at the weekend that he had decided in March that he wanted to leave United.
Lukaku scored 42 goals in 96 appearances during his time in Manchester and already has nine goals in 15 appearances this season for Inter.


14 July 2006
The Ministry of Health in Indonesia has confirmed the country's 53 rd case of human infection with the H5N1 avian influenza virus.
The case, which was fatal, occurred in a 3-year-old girl from a suburb of Jakarta. She became ill on 23 June, was hospitalized on 5 July and died the next day. Specimens collected from the girl were confirmed positive for H5N1 avian influenza virus.
An investigation found that the case handled chickens that had died in the neighbourhood, to dispose of them, two days before the onset of her symptoms. Samples taken from chickens in the neighbourhood were found to be positive. An investigation has found no further cases of influenza-like illness and monitoring of close contacts is under way.
Of the 53 cases confirmed to date in Indonesia, 41 have been fatal.


{% trans "First time here? Here's a short guide!" %}
{% trans 'This is where you start. On your left you find some information, help and contact buttons, as well as buttons to contact us and get back to this guide.' %}
{% trans "In the top-right corner you'll find the tool that allows you to switch between different maps. Pick the one that suits you the best." %}
{% trans "Use these tools to place markers, or draw lines or areas in the map." %}
{% trans "When you have drawn on the map, a form will appear on the left in which you can provide information about the place or route you've drawn." %}


If you want to test this app you need an account so signup!
You can message with your friend with '{{ main.userInfo.chat_name }}' nickname in our chatroom.
Project @GitHub by Talha Can Havadar


EBD - Easton Bible DIctionary
Kettle
KETTLE
"KETTLE "a large pot for cooking. The same Hebrew word (dud, “boiling”) is rendered also “pot” (
Psalm 81:6
), “caldron” (
2 Chronicles 35:13
),“basket” (
Jeremiah 24:2
). It was used for preparing the peace-offerings (
1 Samuel 2:13, 14
).
"KETTLE "a large pot for cooking. The same Hebrew word (dud, “boiling”) is rendered also “pot” (Psalm 81:6), “caldron” (2 Chronicles 35:13),“basket” (Jeremiah 24:2). It was used for preparing the peace-offerings (1 Samuel 2:13, 14).


Teaching and research are two sides of the same coin.
Just as it’s important to create new ideas, it’s equally important to devote time and resources to education in order to give others the tools to create their own
ideas and build stronger communities in the process.
I offer tranings and workshops on various topics on topics related to data science and am open to designing bespoke materials in order to suit your needs.
Recently I become a certified
RStudio Instructor, have worked as a Lead Instructor of Data Science at
Flatiron School, and have also designed and delivered workshops for
Minerva Statistical Consulting.
I specialize in teaching beginners with little to no experience in data science.
Teaching Portfolio
Below I archive examples of materials I have created for pedagogical purposes.
Here you can find:
The following are examples of lesson material I wrote for Flatiron School’s curriula, examples of documents I’ve produced to help students, and examples of lesson plans:
Taught remedial music theory and aural training course three times a week to undergraduates as Instructor of Record
Responsible for all course material ranging from lectures, to homework assignments, bi-weekly recitations, to play-and-sing piano preparations, and teaching of aural-skills, held office hours.
Homework assigned via Oxford Music Theory Skill Builder
Aural Skills IV (Chromatic and Atonal)
Taught Aural Skills Labs to second-year undergraduate students, classes focused on providing individual attention to learning how to sight-sing chromatic and atonal melodies as well as complex rhythms.
Responsible for grading bi-weekly individual recitations with materials ranging from prepared melodies, to play-and-sing piano preparations, to sight-singing.
Aided Instructor of Record for large Music Theory lecture
Aural Skills III (Chromaticism)
Taught Aural Skills Labs to second-year undergraduate students, classes focused on providing individual attention to learning how to sight-sing melodies and rhythms.
Responsible for grading bi-weekly individual recitations with materials ranging from prepared melodies,
to play-and-sing piano preparations, to sight-singing
Aided Instructor of Record for large Music Theory lecture
Completed both eight hour training course on modern, evidence based teaching methods as well passed two exams on both teaching methods and programming with the tidyverse.
If you’d like to get in contact regarding hiring me for a workshop, training, or a project, please send me an email using the form below.
If you don’t hear back from me, please try again
and not use this form


Before Change
" group is used, all incoming and outgoing traffic through TCP, UDP and"
" ICMP is allowed, this is the default.")
flags.DEFINE_boolean(
"rackspace_apply_onmetal_ssd_tuning", default=False,
help="Apply Rackspace recommended tuning to PCIe-based flash storage "
"included with OnMetal IO instances. See: "
"http://www.rackspace.com/knowledge_center/article/"
"configure-flash-drives-in-high-io-instances-as-data-drives")
flags.DEFINE_string(
"image_id", None, "The ID of the image from which you want to"
" create the volume.")
After Change
from perfkitbenchmarker import flags
flags.DEFINE_string("rack_path",
default="rack",
help="The path for the rack CLI binary.")
flags.DEFINE_string("region", default="IAD",
help="A string indicating which Rackspace region to use.")


Planet Sick-Boy: http://www.sick-boy.com "We Put the SIN in Cinema"
© Copyright 2001 Planet Sick-Boy. All Rights Reserved.
Whether you're going to get a pre-Ocean's Eleven look at Brad Pitt and Julia Roberts (they're both in Steven Soderbergh's remake), to see a film with stylish violence in hopes of cleansing your pallet from the stupid 3000 Miles to Graceland, or to see two gorgeous, larger-than-life Hollywood superstars interact with each other on the big screen, The Mexican will likely be a real crowd-pleaser. Actually, those folks in the last group might be a bit disappointed that Brad and Julia aren't in too many scenes together, but the rest of the film is enjoyable enough to make you forget, or, at least not realize until you're on the way home.
The film opens with the toothy duo in the bedroom of their Los Angeles apartment. Sam (Roberts, Erin Brockovich) is all smiley because Jerry (Pitt, Snatch) is talking her to Las Vegas for vacation later that day. Jerry, on the other hand, is gnawing on his fingernails because a prior engagement is going to postpone their trip, and he hasn't had the heart to tell the high-strung Sam. It seems that Jerry is in hot water with a local mobster (Bob Balaban, Best in Show) and needs to perform one last service to work off the debt. While it's not immediately clear what Jerry did to end up in this pickle, we do know his task involves flying to Mexico, picking up a firearm and delivering it back to the L.A. gangster, who is apparently the operative for an even bigger fish currently serving time.
 They each have their own adventures and don't meet up again until the end of the film. Jerry runs into all kinds of trouble in Mexico, learning the pistol (it's called The Mexican) he's supposed to transport is cursed. In the meantime, wisecracking Sam is taken hostage by a burly man named Leroy (James Gandolfini, The Sopranos), who uses her to ensure Jerry doesn't run off (or R-U-N-O-F-F-T, if you've just seen O Brother) with the valuable gun.
Jerry's character reminded me of Paul Hackett in After Hours. He's clumsy, unlucky and now finds himself (sporadically) in possession of a gun with bad mojo. All he wants is to get back to Sam and fix their relationship. Sam and Leroy, on the other hand, made me think of - don't laugh - The Silence of the Lambs. Like Lambs, The Mexican is full of really tight close-ups, and the relationship between Sam and Leroy is like a lightweight version of Clarice and Hannibal. They grow close and dish about their relationships and childhoods, but you know he could kill her in an instant if necessary.
The Mexican is a high-octane flick on par with True Romance in terms of romantic and violent content (which is kind of ironic if you remember Gandolfini sharing an unforgettable hotel scene with the female protagonist in that film). It's got the three Ds that make a film like this work - double-crossing, deceit and dark humor. There are also several great flashback scenes where we learn the origin of The Mexican (one features Julia's brother, Eric).
The drawbacks for The Mexican are pretty minor. The ending drags a bit, but it's worth it for the payoff. The country of Mexico is portrayed as a small village with eight people. And if you pay too much time thinking about who each gangster is working for, your head may explode. Just sit back and enjoy the nice photography and good acting by two huge stars (and one pretty big star).
The Mexican was directed by Gore Verbinski (Mouse Hunt), whose visual style is greatly enhanced by cinematographer Dariusz Wolski (The Crow, Dark City). The story was written by J.H. Wyman, who penned the truly awful festival hit Mr. Rice's Secret. If the film reminds you a little bit of a Quentin Tarantino movie, you won't be surprised to learn The Mexican was produced by Tarantino's right-hand man, Lawrence Bender.
2:00 - R for violence and language
========== X-RAMR-ID: 29175 X-Language: en X-RT-ReviewID: 193762 X-RT-TitleID: 1105586 X-RT-SourceID: 595 X-RT-AuthorID: 1146
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


SuperM page
SuperM
Home
About Us
Tour & Tickets
Merchandise
Contact Us
TOURS
MERCHANDISES
Lastest Video


Dig your roots
Best DNA Test Deals for Black Friday 2019: 23andMe, Ancestry & more
by Jared DiPaneEver wonder where you were from, and what the dynamic of your family is like? In the past few years, DNA test kits have grown immensely in popularity, and around big shopping events you can score big discounts. Normally, Black Friday brings some of the year's lowest and best pricing to these kits, and we don't expect Black Friday 2019 to be any different.
There are a whole lot of kits available right now, though, so you'll want to do a little bit of research ahead of your purchase to make sure you are purchasing the right one.
What type of DNA test kits are available?
With all the DNA test kits out there, it can be pretty confusing deciding which to buy at first, but it's easy to narrow down which to choose based on what you're looking to discover. Family ancestry tests are the most common. Otherwise known as Autosomal tests, these tests can help you identify living or recently-deceased relatives that you didn't know about previously, as well as your long-term ancestry and genetic health. They're useful in building family trees, too.
Some services will offer Y-DNA and mtDNA tests. These offer a more specific look at either your father's or mother's side of the family. Y-DNA tests can only be taken by males and help to trace your father's lineage. They can also be used as a paternity test. Meanwhile, the mtDNA tests can be taken by both males and females to trace your mother's lineage.
Other DNA tests include additional information on your health, carrier status reports, and more. You can go in-depth with tests for skin care, weight, food & pet sensitivities, and the list goes on. There's even a DNA test for your pet that can tell you more about your animal, its ancestry, and how best to care for it. Some of the test kits you can find online will tell you more about your:
- Ancestry
- Living Relatives
- Paternity
- Health + Wellness
- Allergies
- Weight
- Skin
- Pets
Which DNA test kit is the best?
While this answer is a bit subjective, there are three test kits that keep coming up as the best in all the research that we've done. Kits from 23andMe, AncestryDNA, and MyHeritage consistently come out on top for their wide-reaching searches and informative results. However, the best one to choose comes back to what you're looking to discover about yourself or your history. While 23andMe is stellar for genetic health testing, AncestryDNA excels at genealogy and matching you up with your ancestors. MyHeritage is an even better pick for international matches and an advanced look into your genetics.
These aren't the only test kits to consider either, as other options can be better suited depending on what you're hoping to find out. While African Ancestry's DNA test might have a smaller match database, it's more valuable than many others as an in-depth look at African lineages.
Does a DNA test kit make a good gift?
Though it depends on the person, most of the time a DNA test makes a great gift. It's a great option to get someone who's impossible to buy for, and it's unlike most other gifts as your recipent will get to learn a wealth of information about themselves once all is said and tested.
Best Black Friday DNA Test Kit deals
AncestryDNA: Genetic Ethnicity Test
With this easy-to-use test kit, you simply send a saliva sample to AncestryDNA's lab using the included prepaid package and receive your results in six to eight weeks.
You'll learn your ethnicity estimate with informative geographic detail and in-depth historical insights, along with your connections to living relatives and more. You can even sign up for an Ancestry subscription for access to billions of records and millions of family trees to help you learn more about your genealogy and origins.
Who are you?
AncestryDNA: Genetic Ethnicity Test
Back at one of its best prices ever, this test tells you more about where you come from, giving you what's known as an "ethnicity estimate". It will show different regions that make up your estimate, how your ancestors moved around, and more.
$59 $99 $40 Off
23andMe: Ancestry + Traits Service
Discover what makes you YOU. 23andMe's Ancestry + Traits test will take you through your ancestry composition and where your DNA is from, while exploring both your maternal and paternal ancestors and how they moved around the world.
The Traits service is one of the more fun kits you can choose, as you'll receive reports on things like hair photobleaching and freckles. You could learn more about your taste and smell preferences, your ability to match a musical pitch, and more.
More info...
23andMe: Ancestry + Traits Service
With this 23andMe kit, you'll learn all about your ancestors as well about your close family members from across the world; maybe some you didn't even know you had.
$79 $99 $20 Off
23andMe: Health + Ancestry Service
This 23andMe testing kit includes all the infomation you'd receive with the Ancestry + Traits kit above, but for just $20 extra, you'll also get an in-depth look at your genes and your health, including your chances of develping certain health conditions or whether you're a carrier for inherited conditions. You'll even learn about how your DNA affects your well-being and how that could influence certain choices you make.
This is 23andMe's best kit that's now 50% off! A well-rounded kit like this is perfect for giving as a gift to a close family member or friend during the upcoming holiday season.
All you need to know
23andMe: Health + Ancestry Service
Along with everything the Ancestry + Traits test above includes, this service also includes wellness reports, carrier status reports, and health predisposition reports. These breakdowns could inform you of your chances of developing issues like Type 2 Diabetes or Celiac Disease, being a carrier of genetic variants linked to health conditions, and more.
$99 $199 $100 Off
MyHeritage
MyHeritage provides the most comprehensive list of ethnicities of all the testing kits, including 42 regions with 7 East Asian regions among them. With a simple cheek swab that takes only two minutes to complete, you'll be able to find out more about your ancestry and relatives you never knew existed, from both your mother's and father's side of the family.
MyHeritage uses its massive global database to provide you with worldwide DNA matches. Free and paid subscription options for further family history research are available as well.
Let's go deeper
MyHeritage: Ancestry & Ethnicity Genetic Testing
Clip the on-page coupon at Amazon to score this deal. MyHeritage's DNA test kit gives you a detailed breakdown of your origins from among 42 different ethnicities from around the world. That's more than any other test can provide. You'll also gain information on living or recently-deceased relatives, as well as the ability to build your own family tree online or using the free MyHeritage app.
$59 $79 $20 Off
Basepaws
Basepaws provides the world's first at-home cat genetics test so you can learn more about your furry feline friend, from breed to health, traits, and more. The kit uses a simple saliva swab sample that won't be too difficult to obtain, and once sent of to Basepaws, you'll receive results within 6 to 9 weeks.
Basepaws' data is continually expanding and currently includes 4 Breed Groups and 18 Breeds to give you better insight on your cat. You'll also receive a health report that includes over 39 genetic mutations to watch for which are linked to 17 genetic conditions. It's always good to know of any potential health concerns as early as possible, and Basepaws can help.
Don't forget Kitty!
Basepaws Cat DNA Test: Breed + Health Reports
As seen on the ABC hit show Shark Tank, this DNA test is designed for your favorite feline friend. You'll learn more about your cat's breed, health, and any potential genetic conditions that could be extremely helpful to know of ASAP. It just requires a simple saliva swab too.
$89 $129 $40 Off
Get ready for Black Friday!
- Black Friday Deals
- Best Early Walmart Black Friday Deals
- Black Friday: Everything You Need To Know
- Amazon Black Friday 2019: Best Deals, Ads, & Sales
- Best Buy Black Friday 2019: Best Deals, Ads, & Sales
- Black Friday Carrier Deals: Verizon, Sprint, T-Mobile, Mint Mobile, & more
- Black Friday VPN Deals: ExpressVPN, PIA, NordVPN, & more
We may earn a commission for purchases using our links. Learn more.


About Us
Technical education in India contributes a major share to the overall education system and plays a vital role in the social and economic development of our nation. In India, technical education is imparted at various levels such as: craftsmanship, diploma, degree, post-graduate and research in specialized fields, catering to various aspects of technological development and economic progress.
The beginning of formal Technical Education in India can be dated back to the mid 19th Century. The major policy initiatives in the pre-independence period included appointment of the Indian Universities Commission in 1902, issue of the Indian Education policy resolution in 1904 and the Governor General’s policy statement of 1913 stressing the importance of Technical Education, the establishment of IISc in Bangalore, Institute for Sugar, Textile and Leather Technology in Kanpur, N.C.E. in Bengal in 1905 and Industrial schools in several provinces.
Significant developments include:
- Constitution of the Technical Education Committee of the Central Advisory Board of Education (CABE) of 1943;
- Preparation of the Sergeant Report of 1944;
- Formation of the All India Council for Technical Education (AICTE) in 1945 by the Government of India.
All India Council for Technical Education (AICTE) was set-up in November 1945 as a national level Apex Advisory Body to conduct survey on the facilities on technical education and to promote development in the country in a coordinated and integrated manner.
And to ensure the same, as stipulated in, the National Policy of Education (1986), AICTE be vested with statutory authority for planning, formulation and maintenance of norms and standards, quality assurance through accreditation, funding in priority areas, monitoring and evaluation, maintaining parity of certification and awards and ensuring coordinated and integrated development and management of technical education in the country.
The purview of AICTE (the Council) covers programmes of technical education including training and research in Engineering, Technology, Architecture, Town Planning, Management, Pharmacy, Applied Arts and Crafts, Hotel Management and Catering Technology etc. at different levels.
The AICTE has constructed its own fully air-conditioned Office Building having a covered area of five acres of land, situated at Nelson Mandela Marg, Vasant Kunj, New Delhi-110 067. The Office Building is Ground + 3 floors with three wings each having a seating capacity of about 300 employees, 8 Conference rooms, an 800 capacity auditorium, 20 rooms Guest House and Canteens for Staff & Officers. There is a 2 level basement parking and lush green open spaces. There is also a temple of Ganesha.


Gecode::Search::LDS Class Reference
#include <search.hh>
Inherited by Gecode::LDS< T >.
Detailed Description
Limited discrepancy search engine.Definition at line 519 of file search.hh.
Public Member Functions | |
| LDS (Space *s, unsigned int d, Stop *st, size_t sz) | |
| Space * | next (void) |
| Return next solution (NULL, if none exists or search has been stopped). | |
| Statistics | statistics (void) const |
| Return statistics. | |
| bool | stopped (void) const |
| Check whether engine has been stopped. | |
| ~LDS (void) | |
| Destructor. | |
Protected Attributes | |
| Space * | root |
| Root node for problem. | |
| unsigned int | d_cur |
| Current discrepancy. | |
| unsigned int | d_max |
| Maximal discrepancy. | |
| bool | no_solution |
| Solution found for current discrepancy. | |
| ProbeEngine | e |
| The probe engine. |
Constructor & Destructor Documentation
Member Function Documentation
| Space * Gecode::Search::LDS::next | ( | void | ) |
Return next solution (NULL, if none exists or search has been stopped).
Reimplemented in Gecode::LDS< T >.
| Statistics Gecode::Search::LDS::statistics | ( | void | ) | const |
| bool Gecode::Search::LDS::stopped | ( | void | ) | const |
Member Data Documentation
Space* Gecode::Search::LDS::root [protected] |
unsigned int Gecode::Search::LDS::d_cur [protected] |
unsigned int Gecode::Search::LDS::d_max [protected] |
bool Gecode::Search::LDS::no_solution [protected] |
ProbeEngine Gecode::Search::LDS::e [protected] |
The documentation for this class was generated from the following files:
- gecode/search.hh (Revision: 7310)
- gecode/search/lds.cc (Revision: 6072)


[§572C-1] Purpose. The purpose of this chapter is to extend certain rights and benefits which are presently available only to married couples to couples composed of two individuals who are legally prohibited from marrying under state law. [L 1997, c 383, pt of §1]


194_sumandinu.py
from heapq import heappush, heappop
class Solution:
def eatenApples(self, apples: List[int], days: List[int]) -> int:
heap = []
total = 0
for i in range(len(apples)):
if apples[i] > 0:
heappush(heap, (i+days[i], apples[i]))
while heap and heap[0][0] <= i:
heappop(heap)
if heap:
rottDay, appleCount = heappop(heap)
total += 1
if appleCount > 1:
heappush(heap, (rottDay, appleCount-1))
i = len(apples)
while heap:
while heap and heap[0][0] <= i:
heappop(heap)
if heap:
rottDay, appleCount = heappop(heap)
total += 1
if appleCount > 1:
heappush(heap, (rottDay, appleCount-1))
i += 1
return total


Package net.sf.jasperreports.charts
Interface JRChartAxis
-
- All Superinterfaces:
java.lang.Cloneable
,JRCloneable
- All Known Implementing Classes:
JRBaseChartAxis
,JRDesignChartAxis
,JRFillChartAxis
public interface JRChartAxis extends JRCloneable
Describes an axis that can be added to a multiple axis chart. The name "axis" is a bit of a misnomer, as it really contains information about a new dataset to plot, the axis to plot it against, and how to render that dataset.- Author:
- Barry Klawans<EMAIL_ADDRESS>-
-
Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description JRChartAxis
clone(JRChart parentChart)
JRChart
getChart()
Returns the chart that contains the dataset and plot to use for this axis.AxisPositionEnum
getPositionValue()
Gets the position of this axis.-
Methods inherited from interface net.sf.jasperreports.engine.JRCloneable
clone
-
-
-
-
Method Detail
-
getPositionValue
AxisPositionEnum getPositionValue()
Gets the position of this axis.- Returns:
- the position of this axis
-
getChart
JRChart getChart()
Returns the chart that contains the dataset and plot to use for this axis. The plot is used to figure out how to render the dataset when adding to the multiple axis chart.- Returns:
- the chart that contains the dataset and plot for this axis
-
clone
JRChartAxis clone(JRChart parentChart)
-
-


This meta uses all of the answers from the Athletics round, as well as the three sub-metas.
Looking at the regular puzzle answers, all of the leading letters are unique, and include all of the letters A through Z, except for J. The meta shell itself includes a 5×5 square, and a reference to getting on “the same playing field”. These elements, combined with the flavor of various athletics teams coming together, clue the Playfair cipher.
Intuitively, we’d like to place the 25 leading letters of the answers into the grid somehow to create a Playfair cipher key.
The sub-meta answers provide a clue as to how to do this. Solvers may notice that the baseball meta answer contains PRIME while the basketball meta answer contains SQUARE. Numbering the grid from 1 to 25 in left-to-right, top-to-bottom order (as the letters in a Playfair cipher are ordered), the prime-numbered squares should be reserved for the initial letters from the baseball round and the square numbers should be reserved for the basketball round. There are exactly 9 prime numbers between 1 and 25, and 5 square numbers in this range, which matches the number of answers in those rounds exactly. The remaining answer THE GAPS suggests that the 11 football answers are placed in the gaps between the basketball and baseball answers. The idea of using numbers somehow is also clued by the reference to jerseys (i.e. jersey numbers) in the flavor text.
| Round | Answer starting letters |
|---|---|
| Basketball | I, L, P, S, Y |
| Baseball | A, C, E, F, K, Q, U, W, Z |
| Football | B, D, G, H, M, N, O, R, T, V, X |
The next step is to use the fact that Playfair cipher grids are typically constructed by taking a word or phrase, stripping away duplicates and using the remaining letters at the start of the grid (indicated as the first nine letters here), and then placing the rest of the letters in the alphabet (except J) in alphabetic order. So it’s natural to impose the constraint that the letters outside of the boxed region are in alphabetic order.
Now placing the constrained sets of letters in the grid becomes a logic puzzle of sorts. One way to proceed:
Trying to place the letters somewhat greedily and then adjusting where necessary will also work here, as the solution is quite intuitive.
This gives us the following grid:
The only reasonable phrase that we can make in the box is PUZZLE NAMES, which gives the completed grid. In testsolving, teams generally found this by first noticing that PUZZLE can be made using the Z, but a more exhaustive search also finds no satisfactory alternatives.
This gives us our completed Playfair grid:
“Puzzle names” suggests that we should apply this Playfair cipher grid, which we have yet to use, to the puzzle names. In particular, we decode the 25 starting letters of the puzzle names in order of their use in the grid itself. This is an intuitive approach as this ordering was “enumerated” in the puzzle, the first letter distribution is a little odd, and anything more than starting letters would likely be too strong of a constraint.
This gives the final answer, the reason why the teams kept losing: they THREW THE GAME AND NOT THE BALL.


|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Object ch.epfl.lis.gnwgui.jungtransformers.EdgeTransformer<E>
E
- Edgepublic class EdgeTransformer<E>
This transformer defines the edge shapes of the graph visualizations.
| Constructor Summary | |
|---|---|
EdgeTransformer()
Constructor |
|
EdgeTransformer(boolean distinguishSignedConnections)
This constructor allows to distinguish or not the signed connections by their edge/arrow color. |
|
EdgeTransformer(java.awt.Stroke enhancerStroke,
java.awt.Stroke inhibitorStroke,
java.awt.Stroke dualColor,
java.awt.Stroke unknownStroke)
Constructor with edge/arrow color specified. |
| Method Summary | |
|---|---|
void |
distinguishConnectionByEdge(boolean yes)
Set if the transformer should distinguish each signed connection by a color. |
java.awt.Stroke |
getBasicStroke(float d)
|
java.awt.Stroke |
getBasicStroke(float[] dash)
|
java.awt.Stroke |
getDualArrow()
|
java.awt.Stroke |
getEnhancerArrow()
|
java.awt.Stroke |
getInhibitoryArrow()
|
java.awt.Stroke |
getUnknownArrow()
|
void |
setDualArrow(java.awt.Stroke stroke)
|
void |
setEnhancerArrow(java.awt.Stroke stroke)
|
void |
setInhibitoryArrow(java.awt.Stroke stroke)
|
void |
setUnknownArrow(java.awt.Stroke stroke)
|
java.awt.Stroke |
transform(E e)
Return the color that should be used for each edge/arrow of the network. |
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Constructor Detail |
|---|
public EdgeTransformer()
public EdgeTransformer(boolean distinguishSignedConnections)
distinguishSignedConnections
- public EdgeTransformer(java.awt.Stroke enhancerStroke, java.awt.Stroke inhibitorStroke, java.awt.Stroke dualColor, java.awt.Stroke unknownStroke)
enhancerStroke
- Stroke of the enhancer interactionsinhibitorStroke
- Stroke of the inhibitory interactionsdualColor
- Stroke of the dual interactionsunknownStroke
- Stroke of the unknown interactions| Method Detail |
|---|
public java.awt.Stroke transform(E e)
transform
in interface org.apache.commons.collections15.Transformer<E,java.awt.Stroke>
public void distinguishConnectionByEdge(boolean yes)
yes
- public java.awt.Stroke getBasicStroke(float d)
public java.awt.Stroke getBasicStroke(float[] dash)
public void setEnhancerArrow(java.awt.Stroke stroke)
public void setInhibitoryArrow(java.awt.Stroke stroke)
public void setDualArrow(java.awt.Stroke stroke)
public void setUnknownArrow(java.awt.Stroke stroke)
public java.awt.Stroke getEnhancerArrow()
public java.awt.Stroke getInhibitoryArrow()
public java.awt.Stroke getDualArrow()
public java.awt.Stroke getUnknownArrow()
|
||||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | |||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


Landing
New free template by uicookies.com. For more template visit the site. Lorem ipsum dolor sit amet, consectetur adipiscing elit.


Optimizing CSS Animations
Browser Rendering Pipeline
- Any time you change what is displayed in the browser, it runs this rendering pipeline
- Computationally Heavy
- Layouting is not deterministic, needs to be run proceduraly
Javascript Pipeline
- Add / Remove / Modify DOM elements
- Not just Javascript
- Modifying CSS Properties
- CSS Transitions
Styling Pipeline
- Match CSS Rules to selectors
- Computes all styles for each element
- Complicated CSS and wide reaching styles like `*` can slow this down
Layout Pipeline
- Use computed rules to determine size of elements and where to place them
- Has to be rendered proceduraly, nature of CSS means parent and children elements can effect styles of the element being rendered


Aalim School of Middle Eastern Dance
Al-Bahira Middle Eastern Dance Theater is professional dance troupe dedicated to the performance, education, and creative presentation of dance as a living and ever-evolving art form.
Under the artistic direction of Mirah Ammal, Al-Bahira maintains a performance repertoire that is rooted in authentic regional dance and music forms. Our unique approach is contemporary yet deeply respectful of the rich traditions and cultural context of the original forms. We specialize in: Raqs as-sharqi ("belly dance"), Folkloric dances of the Middle East, Greece, Turkey, Persia (Iran), North Africa and surrounding areas, Creative theatric and fusion works.
Aalim School of Dance, Al-Bahira's educational partner, provides weekly belly dance classes, plus dance and music workshops to hundreds of students at two locations in the Twin Cities area.
Beginning-Intermediate Ballet with Maria Fontana
This class is for adults who wish to experience the physical and aesthetic benefits of ballet. Focus is on posture, stretching and toning the entire body with an appreciation of dance as an art form in a nonjudgemental atmosphere. Every Wednesday in September, 6:15 pm – 7:15 pm, $8 per student.
Eight C Hip Hop Dance
Eight C Hip Hop Dance offers a fresh spin on dance and a heart pumping workout. Come showcase your inner dancer and release that performance fever! We offer monthly, theme-based workshops. Come join us!
Green Dragon Kung Fu
The Minneapolis branch of the Green Dragon Kung Fu Association is lead by Sifu Steve Salek under the direction of Master Mark Chan. Sifu Salek focuses on traditional styles such as Choy Lee Fut, Hung Gar, & Leung Ying (Dragon), but he also incorporates many ideas from other southern Chinese styles into his curriculum.
Click here for more informationMotion Art MN Modern Dance Classes
Most of our dance classes begin with a floor and standing warm-up to strengthen, stretch and balance the body. Included are sequences that focus on joint articulation, balance, foot work and preparing the body to move through space. As movers dance through space, concepts drawn from the infinite possibilities of time, space and energy are explored through given movement combinations as well as through improvisation.
Click here for more informationNia with Beth Giles
Nia is a sensory-based fitness class for your mind, body and spirit—movements are drawn from nine fitness disciplines including tae kwon do, tai chi, yoga, jazz dance and modern dance. No experience is necessary. Nia is about the joy of movement. EveryBODY is welcome! Mondays, Fridays and Sundays.
Click here for more informationRosen Movement Classes
Rosen Movement Classes is a hands-on practice that addresses the body, mind, spirit, and emotions. It uses nonmanipulative touch and gentle conversation to bring awareness and release to muscle tension held in the body. As one becomes aware of this tension (where we hold stress), what emerges is relaxation of the muscles, ease in the breath, and new possibilities for living one's life.
Rosen Method is a holistic approach to physical and emotional health that releases what is stored in the body—sometimes painful memories, emotions, and old behavior patterns. Learning to be with one's own fears, hesitations, and emotions and listening to the wisdom that comes from the body bring forth renewed creativity and an honoring of our deepest sense of ourselves, our truth.
Click here for more informationZumba Fitness Classes
Thursdays 6:25-7:25. Darryl Sellers has been doing Zumba Fitness classes since 2008. Zumba fuses Latin and other rhythms along with easy to follow moves to create a dynamic fitness program that is truly uplifting and fun! All ages and fitness levels are welcome!
Click here for more information


Payment Date
Payment Date
Payment Amount (£)
Payment Amount
Credit Reference
Credit Reference
Name
Name
Credited Account
Credited Account
Lottery Payment?
Is Lottery Payment?
Member
Member
Comments
Comments
Back
Edit
Mark as non-lottery payment
Mark as lottery payment
Delete
Delete this payment?
Yes
No
Mark this as a non-lottery payment?
Yes
No
Mark this as a lottery payment?
Yes
No


Use of Cookies
We use cookies to personalise content and ads, to provide social media features and to analyse our traffic. We also share information about your use of our site with our social media, advertising and analytics partners.
» See details
OK


Decentralised software development on GitHub
An open source browser extension for the decentralized management of GitHub-Repositories on the ethereum
blockchain.
deVote functionalities
Crowdfund issue solutions
The community can crowdfund a bounty for the solving of an issue.
Solve issues for a bounty
A developer can solve an issue for a bounty if his solution is accepted by the community.
Vote on pull-requests
The can community votes whether a pull-request should be merged or not.
Advantages of using deVote
deVote
Community driven
The community decides which issues are important and need to be addressed first.
Financial initiative
Developers have a financial initiative to solve issues because of the Bounty.
Qualitative merges
Many people can participate in the voting and thus better validate whether a pull request meets the
quality standard.
Traditional
Admin dependent
The admin decides which issue comes first and can therefore hold back development.
Free developer dependent
The repository must hope that developers will continue to develop the project in their spare time
and for free.
Pull-Requests bottleneck
It doesn't matter what the community thinks about a pull request, in the end it's the admin alone
who decides whether to merge it or not.
Interested? Yes, you can use it for your projects!
This project is completely public and opensource. For the extension to work correctly, it must be set up
correctly.


Taking user problems and turning it into designs
Define a product roadmap and manage it through its execution
Usability testing, heuristic reviews, and ethnographic studies
Use data to drive design and business decisions


Package algorithms.imageProcessing
Class MedianTransform
- java.lang.Object
-
- algorithms.imageProcessing.MedianTransform
-
public class MedianTransform extends java.lang.Object
- Author:
- nichole
-
-
Constructor Summary
Constructors Constructor Description MedianTransform()
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description GreyscaleImage
decimateImage(GreyscaleImage input, float downSampleFactor, int minValue, int maxValue)
create a decimated image by using median transform to blur then bilinear downsampling to reduce the size.void
multiscaleMedianTransform(GreyscaleImage input, java.util.List<GreyscaleImage> outputTransformed, java.util.List<GreyscaleImage> outputCoeff)
A computationally expensive multiscale median transform.void
multiscaleMedianWaveletTransform(GreyscaleImage input)
void
multiscalePyramidalMedianTransform(GreyscaleImage input, java.util.List<GreyscaleImage> outputTransformed, int decimationLimit)
pyramidal median transform for exact reconstruction.void
multiscalePyramidalMedianTransform(GreyscaleImage input, java.util.List<GreyscaleImage> outputTransformed, java.util.List<GreyscaleImage> outputCoeff)
pyramidal median transform for exact reconstruction.void
multiscalePyramidalMedianTransform2(GreyscaleImage input, java.util.List<GreyscaleImage> outputTransformed, int decimationLimit)
pyramidal median transform (faster than multiscalePyramidalMedianTransform but reconstruction from coefficients is not exact, so prefer multiscalePyramidalMedianTransform(...) if exact is needed); following pseudocode in http://www.multiresolution.com/svbook.pdf "Handbook of Astronomical Data Analysis" by Jean-Luc Starck and Fionn Murtaghvoid
multiscalePyramidalMedianTransform2(GreyscaleImage input, java.util.List<GreyscaleImage> outputTransformed, java.util.List<GreyscaleImage> outputCoeff)
pyramidal median transform (faster than multiscalePyramidalMedianTransform but reconstruction from coefficients is not exact, so prefer multiscalePyramidalMedianTransform(...) if exact is needed); following pseudocode in http://www.multiresolution.com/svbook.pdf "Handbook of Astronomical Data Analysis" by Jean-Luc Starck and Fionn Murtagh<T extends Image>
voidmultiscalePyramidalMedianTransform2(T input, java.util.List<T> outputTransformed)
pyramidal median transform for decimation of input image.<T extends Image>
voidmultiscalePyramidalMedianTransform2(T input, java.util.List<T> outputTransformed, int dimensionLimit)
pyramidal median transform for decimation of input image.GreyscaleImage
reconstructMultiscaleMedianTransform(GreyscaleImage c0, java.util.List<GreyscaleImage> mmCoeff)
GreyscaleImage
reconstructPyramidalMultiscaleMedianTransform(GreyscaleImage c0, java.util.List<GreyscaleImage> mmCoeff)
reconstruct image from products of pyramidal median transform.
-
-
-
Method Detail
-
multiscaleMedianTransform
public void multiscaleMedianTransform(GreyscaleImage input, java.util.List<GreyscaleImage> outputTransformed, java.util.List<GreyscaleImage> outputCoeff)
A computationally expensive multiscale median transform. see the pyramidal mean transform multiscalePyramidalMedianTransform(...) instead. This method has a runtime complexity of n_iter * O(N_pixels * lg2(windowArea)) where windowArea grows from 1 to 2*2*lg2(imageDimension) + 1 and nIter = lg2(imageDimension).- Parameters:
input
-outputTransformed
-outputCoeff
-
-
reconstructMultiscaleMedianTransform
public GreyscaleImage reconstructMultiscaleMedianTransform(GreyscaleImage c0, java.util.List<GreyscaleImage> mmCoeff)
-
multiscalePyramidalMedianTransform2
public void multiscalePyramidalMedianTransform2(GreyscaleImage input, java.util.List<GreyscaleImage> outputTransformed, java.util.List<GreyscaleImage> outputCoeff)
pyramidal median transform (faster than multiscalePyramidalMedianTransform but reconstruction from coefficients is not exact, so prefer multiscalePyramidalMedianTransform(...) if exact is needed); following pseudocode in http://www.multiresolution.com/svbook.pdf "Handbook of Astronomical Data Analysis" by Jean-Luc Starck and Fionn Murtagh- Parameters:
input
-outputTransformed
-outputCoeff
-
-
multiscalePyramidalMedianTransform2
public void multiscalePyramidalMedianTransform2(GreyscaleImage input, java.util.List<GreyscaleImage> outputTransformed, int decimationLimit)
pyramidal median transform (faster than multiscalePyramidalMedianTransform but reconstruction from coefficients is not exact, so prefer multiscalePyramidalMedianTransform(...) if exact is needed); following pseudocode in http://www.multiresolution.com/svbook.pdf "Handbook of Astronomical Data Analysis" by Jean-Luc Starck and Fionn Murtagh- Parameters:
input
-outputTransformed
-decimationLimit
- a size for width and height at which to stop the decimation when the image is smaller than the size. The method does not continue to make decimated images beyond this size limit.
-
decimateImage
public GreyscaleImage decimateImage(GreyscaleImage input, float downSampleFactor, int minValue, int maxValue)
create a decimated image by using median transform to blur then bilinear downsampling to reduce the size. The parameter downSampleFactor is the factor to reduce the image size by. following pseudocode in http://www.multiresolution.com/svbook.pdf "Handbook of Astronomical Data Analysis" by Jean-Luc Starck and Fionn Murtagh- Parameters:
input
-downSampleFactor
- the factor to reduce the input image size by (for example, size 1.5 would reduce the image width to size width/1.5).minValue
- if result is below this value, value is set to thismaxValue
- if result is above this value, value is set to this- Returns:
-
multiscalePyramidalMedianTransform2
public <T extends Image> void multiscalePyramidalMedianTransform2(T input, java.util.List<T> outputTransformed)
pyramidal median transform for decimation of input image. The algorithm follows pseudocode in http://www.multiresolution.com/svbook.pdf "Handbook of Astronomical Data Analysis" by Jean-Luc Starck and Fionn Murtagh This method does not return the coefficients.- Parameters:
input
-outputTransformed
-
-
multiscalePyramidalMedianTransform2
public <T extends Image> void multiscalePyramidalMedianTransform2(T input, java.util.List<T> outputTransformed, int dimensionLimit)
pyramidal median transform for decimation of input image. The algorithm follows pseudocode in http://www.multiresolution.com/svbook.pdf "Handbook of Astronomical Data Analysis" by Jean-Luc Starck and Fionn Murtagh This method does not return the coefficients.- Parameters:
input
-outputTransformed
-dimensionLimit
- a size for width and height at which to stop the decimation when the image is smaller than the size. The method does not continue to make decimated images beyond this size limit.
-
multiscalePyramidalMedianTransform
public void multiscalePyramidalMedianTransform(GreyscaleImage input, java.util.List<GreyscaleImage> outputTransformed, java.util.List<GreyscaleImage> outputCoeff)
pyramidal median transform for exact reconstruction. following pseudocode in http://www.multiresolution.com/svbook.pdf "Handbook of Astronomical Data Analysis" by Jean-Luc Starck and Fionn Murtagh This method has a runtime complexity of n_iter * (O(N_pixels * 1.6) + 5*O(N_pixels)) where nIter = lg2(imageDimension) - 1 and N_pixels is decreasing in size by a factor of 2 for each iteration.- Parameters:
input
-outputTransformed
-outputCoeff
-
-
multiscalePyramidalMedianTransform
public void multiscalePyramidalMedianTransform(GreyscaleImage input, java.util.List<GreyscaleImage> outputTransformed, int decimationLimit)
pyramidal median transform for exact reconstruction. following pseudocode in http://www.multiresolution.com/svbook.pdf "Handbook of Astronomical Data Analysis" by Jean-Luc Starck and Fionn Murtagh This method has a runtime complexity of n_iter * (O(N_pixels * 1.6) + 5*O(N_pixels)) where nIter = lg2(imageDimension) - 1 and N_pixels is decreasing in size by a factor of 2 for each iteration.- Parameters:
input
-outputTransformed
-decimationLimit
-
-
reconstructPyramidalMultiscaleMedianTransform
public GreyscaleImage reconstructPyramidalMultiscaleMedianTransform(GreyscaleImage c0, java.util.List<GreyscaleImage> mmCoeff)
reconstruct image from products of pyramidal median transform. following pseudocode in http://www.multiresolution.com/svbook.pdf "Handbook of Astronomical Data Analysis" by Jean-Luc Starck and Fionn Murtagh- Parameters:
c0
-mmCoeff
-- Returns:
-
multiscaleMedianWaveletTransform
public void multiscaleMedianWaveletTransform(GreyscaleImage input)
-
-


[gecode-users] About the search engine BAB?
Amina Kemmar
kemmar.amina at gmail.com
Sun Jan 4 19:20:41 CET 2015
Hi,
I will ask the problem differently. We suppose that after generating the
first solution S1, a constraint C1 is added throw the function
constrain(). Then, after generating an other solution S2, a constrain C2
is added, an so on. When a solution Sn is found, dos gecode use all
constraints previously added (C1,C2,...,Cn) to find an other solution?
If No, how can i do this?
Thank you.
Cheers.
---
Amina
On 01/04/2015 03:05 PM, Christian Schulte wrote:
> Hi,
>
> What do you mean by "consider"? Maybe a restart engine (check MPG) could be
> a better fit.
>
> Cheers
> Christian
>
> --
> Christian Schulte, www.ict.kth.se/~cschulte/
>
>> -----Original Message-----
>> From: users-bounces at gecode.org [mailto:users-bounces at gecode.org] On
>> Behalf Of Amina Kemmar
>> Sent: Thursday, January 01, 2015 7:27 PM
>> To: users at gecode.org
>> Subject: [gecode-users] About the search engine BAB?
>>
>> Hi everyone,
>>
>> I'm using the search engine BAB allowing to post dynamically new
> constraints
>> throw the function "constrain()". Each time a better solution is found, I
> want to
>> consider all the set of constraints added previously by "constrain()". How
> can I
>> do this?
>>
>> Thank you.
>> Amina.
>>
>>
>> _______________________________________________
>> Gecode users mailing list
>> users at gecode.org
>> https://www.gecode.org/mailman/listinfo/gecode-users
More information about the users
mailing list


Pathogens are microorganisms (also called microbes) that cause disease. Bacteria and viruses are types of pathogens. (Edexcel/OCR: Fungi such as athlete’s foot are also pathogens.)
 Some are harmful, some are harmless and some are even useful, e.g. for making dairy foods and medicines.
Viruses are smaller than bacteria and are often simply shaped, e.g. rods or spheres. They are so small that they can even cause diseases in bacteria.
Disease and its causes
Diseases are abnormal conditions affecting the body. They can be infectious or inherited. They can be common and mild (e.g. a cold) or less common and serious (e.g. smallpox).
Infectious disease occurs when pathogens in our environment get into the body. They are called infectious because they can spread.
Infectious diseases spread in different ways, e.g. contaminated food/drink in the stomach; droplets in the air inhaled from someone sneezing/coughing; directly into the blood via wounds; by vectors such as mosquitos; in body fluids (e.g. HIV).
Bacteria and viruses reproduce quickly inside the body. Viruses attack cells in the body, destroying them. Bacteria multiply by dividing in two, often producing poisons (toxins) that make us feel ill. These feelings are the symptoms of illness.
Defence against microbes
Our skin, and the scabs that form when we cut ourselves, are the outermost natural protection against pathogens entering our body.
The mucus in our nose and throat traps pathogens from the air, as do lysozymes in our tears; the acid in our stomachs kills pathogens in our food and drink.
The Hungarian doctor Ignaz Semmelweiss was one of the first to recommend simple hand-washing to stop viruses and bacteria being spread in hospitals (by doctors treating different patients).
White blood cells protect us
Inside our bodies, a key defence against disease is our white blood cells. They are part of our immune system:
Antigens are markers on the outside of a microbe. These markers are unique to that pathogen; specific white blood cells in our bodies create specific antibodies for specific pathogens.
OCR: Viruses mutate very quickly; their antigens change, which is why we can catch a common illness like the flu multiple times.
OCR: In a wound, redness, swelling and pus are positive signs of dead bacteria and used white blood cells: our immune system is working well.


Statistics::Reproducibility - Reproducibility measurement between multiple replicate experiments
Version 0.04
This module facilitates investigation of reproducbility between multiple replicates of quantitative experiments e.g. SILAC or microarray. Scatter plots are great, but only 2d. Some people use correlation as a proxy for reproducibility, but it's not right. This module helps you through the following items...
1) Summarize reproducibility across the replicates 2) Pick out replicates that agree more or less 3) Summarize reproducibility for individual proteins/genes/whatever 4) Set a cutoff for what you can call significant, based on precision 5) Deal with missing values (common in SILAC)
This works by going through the following steps:
(0) Choose a dataset to compare everything else to (the middlemost) 1) Put the middle of the data at (0,0,0,0...) by subtracting the median ... report the median 2) Rotate the data so the line x=y=z=... lies on a single axis. The data should be spread along this axis. 3) Do regression on the data and work out "wrongness" of each replicate (!) 4) Calculate and report ratio variance and imprecision variance 5) Report combined ratio and error for each protein/gene/whatever
Perhaps a little code snippet.
use Statistics::Reproducibility;
my $r = Statistics::Reproducibility->new();
derives a new object from an old one... some fields are conserved. Warning: references are copied, so m and c point to the same arrays! However, if you run regression() again, they will point to new arrays. Data is set up with k empty columns.
Set the data. Should be rectangular, i.e. all columns the same length, and we'll check it is and croak if not... but can contain "empty" cells (empty string), which represent missing values in the data.
returns the object for chaining.
runs a recommended workflow. it's a shortcut for:
my $m = $r->subtractMedian();
$m->middlemostColumn();
my $d = $m->deDiagonalize();
$d -> regression();
my $e = $d->rotateToRegressionLine();
$e->variances();
It returns the last object. So you could do:
my $results = Statistics::Reproducibility
->new()
->data($mydata)
->run()
->printableTable($depth);
calculates the median for each column, substracts from each column and returns the new object.
Calculates which of the columns is middlemost and remembers it so all others are compared to it. This can be done instead of using a constructed median dataset as the comparator so that the constructed one does not add to the spread, and does not contribute to the observation count.
Note: the method of scoring the columns involves counting which has the most middlemost values. For two columns only, the result will always be the one with the least missing values. I don't think there's anything wrong with that, but just so you know!
Make a median column and pop it on the left. Note that the regular median is used here, not the Quick Median estimator. This means that for an even number of observations, the mean of the two middlemost is used, which is not the case for Quick Median.
Replicated data with some spread will naturally lie along the diagonal line, y=x (in 2 dimensions, or z=y=x... in more). This function aligns the data along one axis by rotation. This is done so that (a) errors are measured approximately perpendicular to the spread of data and (b) unspread data (a ball of points) gives a gradient of zero in Theil Sen estimator, which is correct because if there's no experimental spread then there can be no evidence that the replicates disagree.
Note: at this point, any missing values are REPLACED BY ZEROS! This means that these data point will not disagree with any "unchanging" data, but they will not support the reproducibility of "changed" data (data for proteins/genes) that are regulated). The effect of this is that those points will not appear as extreme in the output and will also have a larger error associated with them.
A NEW object is returned! comparatorIndex is honoured and conserved, meaning that if you ran middlemostColumn, the result is the column used as the Y axis in all comparisons, and the column itself will contain the experimental variance.
Perform Theil Sen Estimator regression on the data. The regression is done with the comparator on the x axis, but the symmetric parameters are returned for the comparator on the y-axis.
do we need this?
Calculate variances... i.e. distances from the origin along the line of regression, and distances from the line of regression. This is just like deDiagonalise, except that only two columns are returned.
printableTable returns all available relevant info in a table printTable prints all available relevant info in a table
the firts element returned is a list of columns. the rest are the columns.
data stored are:
# scalars:
comparatorIndex # index of column used to compare
k
n
vE # variance of "error" (imprecision)
vS # variable of experimental spread
sdE # s.d. error
sdS # s.d. spread
# arrays (foreach column)
m # regression denominator
c # regression constant
# arrays (foreach row)
d # distance from regression line
pee # p-value of error
pss # p-value of spread
pes # p-value of error over spread (??)
pse # p-value of spread over error
# 2D array (LoL)
data
note that the distance from the center of the distribution
is given by the values in data[comparatorIndex]
These methods take a single argumen: depth. Every time an object is derived from another (subtractMedian, deDiagonalize and rotateToRegressionLine all do this) the old object is referenced, and you can include the last $depth objects in the output. Set depth to -1 to include all objects.
yes this probably exists in other modules, but I didn't want to pull in a whole module for just one funciton. Anyway, this is an inefficient version for small numbers of data. It sorts the list and then uses middle() to find the middle of the sorted list.
Like median, but for an even list is returns the two middlemost values. This version is used in medianI.
This uses medianN to get the middlemost value(s) and then returns a list of column indices indicating which columns had a middlemost value. This is used in the medianLeft method when deciding which column is middlemost.
middle returns the middlemost item in a list, or the mean average of the two middlemost items. It doesn't sort the list first.
middleN does like middle, but for even lists, it returns the two middlemost items as a list. This is used by medianN.
Jimi Wills, <jimi at webu.co.uk>
Please report any bugs or feature requests to
, or through the web interface at http://rt.cpan.org/NoAuth/ReportBug.html?Queue=Statistics-Reproducibility. I will be notified, and then you'll automatically be notified of progress on your bug as I make changes.bug-statistics-reproducibility at rt.cpan.org
You can find documentation for this module with the perldoc command.
perldoc Statistics::Reproducibility
You can also look for information at:
RT: CPAN's request tracker (report bugs here)
http://rt.cpan.org/NoAuth/Bugs.html?Dist=Statistics-Reproducibility
AnnoCPAN: Annotated CPAN documentation
CPAN Ratings
Search CPAN
Copyright 2013 Jimi Wills.
This program is free software; you can redistribute it and/or modify it under the terms of the the Artistic License (2.0). You may obtain a copy of the full license at:
http://www.perlfoundation.org/artistic_license_2_0
Any use, modification, and distribution of the Standard or Modified Versions is governed by this Artistic License. By using, modifying or distributing the Package, you accept this license. Do not use, modify, or distribute the Package, if you do not accept this license.
If your Modified Version has been derived from a Modified Version made by someone other than you, you are nevertheless required to ensure that your Modified Version complies with the requirements of this license.
This license does not grant you the right to use any trademark, service mark, tradename, or logo of the Copyright Holder.
This license includes the non-exclusive, worldwide, free-of-charge patent license to make, have made, use, offer to sell, sell, import and otherwise transfer the Package with respect to any patent claims licensable by the Copyright Holder that are necessarily infringed by the Package. If you institute patent litigation (including a cross-claim or counterclaim) against any party alleging that the Package constitutes direct or contributory patent infringement, then this Artistic License to you shall terminate on the date that such litigation is filed.
Disclaimer of Warranty: THE PACKAGE IS PROVIDED BY THE COPYRIGHT HOLDER AND CONTRIBUTORS "AS IS' AND WITHOUT ANY EXPRESS OR IMPLIED WARRANTIES.  UNLESS REQUIRED BY LAW, NO COPYRIGHT HOLDER OR CONTRIBUTOR WILL BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES ARISING IN ANY WAY OUT OF THE USE OF THE PACKAGE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.