Ever have trouble finding a happy hour? Welcome to the crowd-sourced Minneapolis Happy Hour finder.
A full stack collaboration involving RESTful API design, MySQL, and Node.js.
Eat The Burgers!
Do you have a hankering for burgers? Add a burger, devour a burger, and see what your friends have
eaten!
Utilizes a range of technologies including Sequelize, Node.js, and Handlebars.js.
LIZY WORTHY
This is a music application that makes searching for the type of music
and the artist name!
Exhibits a front-end application showcasing intricate JavaScript.
Friend Finder
This is a web application used to find you a new best friend. Try to Answer the survery questions and
you will find your best match of the night!
fundemental rules of APIs and routes.
Hook me app
This is a web application used to hook up with friend and you can suggest your friend
what kind of movie he/she would like to watch, at same time you will know if the suggested item is being use.


|
Panda3D
|
Public Member Functions | |
| def | __init__ (self, *args, **kw) |
| def | appInit (self) |
| USER METHODS ### To be overridden. More... | |
| def | createInterface (self) |
| def | createMenuBar (self) |
| def | onDestroy (self, event) |
| def | quit (self, event=None) |
| def | showAbout (self, event) |
Public Attributes | |
| about | |
| menuBar | |
| menuFile | |
| menuHelp | |
Static Public Attributes | |
| string | appname = 'Generic Application Frame' |
| string | appversion = '1.0' |
| string | balloonState = 'none' |
| string | contactemail =<EMAIL_ADDRESS>|
| string | contactname = 'Gyedo Jeon' |
| tuple | copyright |
| int | frameHeight = 320 |
| int | frameWidth = 450 |
| int | padx = 5 |
| int | pady = 5 |
| int | panelCount = 0 |
| int | usecommandarea = 0 |
| int | usestatusarea = 0 |
| def __init__ | ( | self, | |
| * | args, | ||
| ** | kw | ||
| ) |
| def appInit | ( | self | ) |
USER METHODS ### To be overridden.
Reimplemented in WxPandaShell.
| def createInterface | ( | self | ) |
Reimplemented in LevelEditorUIBase, and WxPandaShell.
| def createMenuBar | ( | self | ) |
| def onDestroy | ( | self, | |
| event | |||
| ) |
Reimplemented in LevelEditorUIBase.
| def quit | ( | self, | |
event = None |
|||
| ) |
| def showAbout | ( | self, | |
| event | |||
| ) |
| about |
|
static |
|
static |
|
static |
|
static |
|
static |
|
static |
|
static |
|
static |
| menuBar |
| menuFile |
| menuHelp |
|
static |
|
static |
|
static |
|
static |
|
static |


 Set you OpenVAS session expiry time before it drives you crazy!
Openvas is a great vulnerability scanner, but the default session expiry time is set to 15 minutes, which is just plain annoying when you're running a scan and want to check in on it every know and then.
Set Session Expire Time in GreenboneSecurityAssistant (GSA) to 60 Minutes by adjusting the init script. Depending on your installation and linux distro this file might be named different.
sudo vi /etc/init.d/openvas-gsa
#Look for the Daemon startup parameters and add
--timeout 60
Restart the service and login again in the web interface. Check the cookie for it's expiration time.
You can check your cookies in Firefox from the Privacy tab in the Settings by clicking on the "remove individual cookies" link and searching for GSA.
Check the expiry date, it should have a difference of 60 minutes from your login time.


UNIMPLEMENTED
Section: Linux Programmer's Manual (2)Updated: 2007-07-05
Index Return to Main Contents
NAME
afs_syscall, break, fattach, fdetach, ftime, getmsg, getpmsg, gtty, isastream, lock, madvise1, mpx, multiplexer, prof, profil, putmsg, putpmsg, security, stty, tuxcall, ulimit, vserver - unimplemented system callsSYNOPSIS
Unimplemented system calls.DESCRIPTION
These system calls are not implemented in the Linux 2.6.22 kernel.RETURN VALUE
These system calls always return -1 and set errno to ENOSYS.NOTES
Note that ftime(3), profil(3) and ulimit(3) are implemented as library functions.Some system calls, like alloc_hugepages(2), free_hugepages(2), ioperm(2), iopl(2), and vm86(2) only exist on certain architectures.
Some system calls, like ipc(2), create_module(2), init_module(2), and delete_module(2) only exist when the Linux kernel was built with support for them.
SEE ALSO
syscalls(2)COLOPHON
This page is part of release 3.22 of the Linux man-pages project. A description of the project, and information about reporting bugs, can be found at http://www.kernel.org/doc/man-pages/.
Index
This document was created by man2html, using the manual pages.
Time: 05:33:05 GMT, December 24, 2015


Forever learning. Forever doing.
Honolulu, HI
HTML, CSS, JavaScript, JQuery
.NET, .NET Core, IIS Web Server, Windows Server, Azure Web Services
Microsoft SQL Server, Oracle Database
HTML, CSS, JavaScript, JQuery
I am currently not available for freelance work. If you want to talk about hiking, basketball, or technology, please feel free to reach out to me.
Contact Me


I have 4 pets in total. Two dogs, two pigeons and one cat. This is a home page for each of their blogs!
Here's my dogs blog!
Here's my birds blog!
Here's my cats blog!


| HOSTS(5) | Linux Programmer's Manual | HOSTS(5) |
IP_address canonical_hostname [aliases...]
Fields of the entry are separated by any number of blanks and/or tab characters. Text from a "#" character until the end of the line is a comment, and is ignored. Host names may contain only alphanumeric characters, minus signs ("-"), and periods ("."). They must begin with an alphabetic character and end with an alphanumeric character. Optional aliases provide for name changes, alternate spellings, shorter hostnames, or generic hostnames (for example, localhost).
The Berkeley Internet Name Domain (BIND) Server implements the Internet name server for UNIX systems. It augments or replaces the /etc/hosts file or hostname lookup, and frees a host from relying on /etc/hosts being up to date and complete.
In modern systems, even though the host table has been superseded by DNS, it is still widely used for:
Before the advent of DNS, the host table was the only way of resolving hostnames on the fledgling Internet. Indeed, this file could be created from the official host data base maintained at the Network Information Control Center (NIC), though local changes were often required to bring it up to date regarding unofficial aliases and/or unknown hosts. The NIC no longer maintains the hosts.txt files, though looking around at the time of writing (circa 2000), there are historical hosts.txt files on the WWW. I just found three, from 92, 94, and 95.
# The following lines are desirable for IPv4 capable hosts <IP_ADDRESS> localhost # <IP_ADDRESS> is often used for the FQDN of the machine <IP_ADDRESS> thishost.mydomain.org thishost <IP_ADDRESS> foo.mydomain.org foo <IP_ADDRESS> bar.mydomain.org bar <IP_ADDRESS> master.debian.org master <IP_ADDRESS> www.opensource.org # The following lines are desirable for IPv6 capable hosts ::1 localhost ip6-localhost ip6-loopback ff02::1 ip6-allnodes ff02::2 ip6-allrouters
Internet RFC 952
| 2017-09-15 | Linux |


Flora is passionate about Web and Mobile App design and development. Her interests also includes Cloud computing, AI Networks and Security...
She shares her learning and creative process with anyone interested , in a bid to motivate others and also learn new things.
She understands that ...
"there are over 50 web development courses, which do I choose?"
"which stack should i choose and in what order do I begin to learn?"
"how quickly can i build real life economically viable skills"
"I feel like a fraud this tech thing isn't for me"
... and can help make your tech journey a little easier.
The Double Life
Flora enjoys spending whatever free time she has on the farm, she loves her natural hair and secretly wishes to be a hair model.
She is also a content developer, creative writer and has participated in one too few spoken word event.
She has a Bachelor's Degree in Microbiology.


Vision Portfolio Management Application Layer: Application
| Headstart Applications
|
Application: SecurityProfile
Summary:
The SecurityProfile application is used to provide summary information
about a security with links to more in depth information. The summary includes
basic information about the security, financial highlights, and portfolio
highlights.
Inputs:
| Position |
Form Id |
Description |
| 1 |
id |
Id of the security |
| 2 |
- |
Id of currency override |
Analysis:
-
The id must reference an existing Security instance.
-
If no global currency has been specified, all monetary data is expressed
in the security's base currency.
-
The display includes four sections:
-
1. Basics - basic information about the security including alternate ids
-
2. Relationships - basic classifications of the security including company,
country, industry, sector, and universe memberships
-
3. Financial Highlights - latest fiscal dates and data
-
4. Portfolio Highlights - list of portfolios holding the security, the
number of shares held, and the total market value
Key Data Feeds:
Related Reports:
Sample Usage:
Interface ApplicationWS runWith: "SecurityProfile", "DELL" ;
Sample Input:
Sample Output:
Security Profile
For: DELL COMPUTER CORP COM
Data As Of: 1/15/1999
--- Currency: United States Dollar
| ---
Basics --- |
| Primary
Id: |
24702510 |
| Ticker: |
DELL |
| Cusip: |
24702510 |
| Security
Type: |
Common
Stock |
| Base
Currency: |
United
States Dollar |
| ---
Relationships --- |
| Company: |
DELL
COMPUTER CORP COM |
| Country: |
United
States |
| Industry: |
Computers/Office
Automation |
| Sector: |
Technology |
| Universe
1: |
Standard
& Poors 500 |
| ---
Highlights --- |
| Latest
MCap (US): |
27,048 |
| Price: |
79.312 |
| P/E: |
36.37 |
| Latest
Fiscal Yr: |
01/31/1997 |
| ...
Sales: |
7,759.00 |
| ...
Assets: |
2,993.00 |
| Latest
Fiscal Qtr: |
10/31/1997 |
| ...
Sales: |
3,188.00 |
| ...
Assets: |
3,921.00 |
| ---
Portfolio Highlights --- |
| Total
Portfolios: |
111 |
| Total
Portfolio Shares: |
2,876,150 |
| Total
Portfolio MVal: |
227,716,359 |
| Copyright © 1999 Innovative Systems Techniques, Inc.
| Updated January 28, 1999
|


Class: Aws::IAM::Types::Statement
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Class Chain:
self,
Struct
|
|
|
Instance Chain:
self,
::Aws::Structure ,
Struct
|
|
| Inherits: |
Struct
|
| Defined in: | gems/aws-sdk-iam/lib/aws-sdk-iam/types.rb |
Overview
Contains a reference to a Statement
element in a policy document
that determines the result of the simulation.
This data type is used by the MatchedStatements
member of the
{Aws::IAM::Types::EvaluationResult}
type.
Constant Summary
Instance Attribute Summary
-
#end_position ⇒ Types::Position
rw
The row and column of the end of a
Statement
in an::Aws::IAM
policy. -
#source_policy_id ⇒ String
rw
The identifier of the policy that was provided as an input.
-
#source_policy_type ⇒ String
rw
The type of the policy.
-
#start_position ⇒ Types::Position
rw
The row and column of the beginning of the
Statement
in an::Aws::IAM
policy.
Instance Method Summary
::Aws::Structure
- Included
| #to_hash | Alias for Structure#to_h. |
Instance Attribute Details
#end_position ⇒ Types::Position (rw)
The row and column of the end of a Statement
in an ::Aws::IAM
policy.
# File 'gems/aws-sdk-iam/lib/aws-sdk-iam/types.rb', line 10126
class Statement < Struct.new( :source_policy_id, :source_policy_type, :start_position, :end_position) SENSITIVE = [] include Aws::Structure end
#source_policy_id ⇒ String
(rw)
The identifier of the policy that was provided as an input.
# File 'gems/aws-sdk-iam/lib/aws-sdk-iam/types.rb', line 10126
class Statement < Struct.new( :source_policy_id, :source_policy_type, :start_position, :end_position) SENSITIVE = [] include Aws::Structure end
#source_policy_type ⇒ String
(rw)
The type of the policy.
# File 'gems/aws-sdk-iam/lib/aws-sdk-iam/types.rb', line 10126
class Statement < Struct.new( :source_policy_id, :source_policy_type, :start_position, :end_position) SENSITIVE = [] include Aws::Structure end
#start_position ⇒ Types::Position (rw)
The row and column of the beginning of the Statement
in an ::Aws::IAM
policy.
# File 'gems/aws-sdk-iam/lib/aws-sdk-iam/types.rb', line 10126
class Statement < Struct.new( :source_policy_id, :source_policy_type, :start_position, :end_position) SENSITIVE = [] include Aws::Structure end


How to Predict A Popular Article with Machine Learning (Part 1)
This is the first post of a series of posts on applying machine learning to practical business problems. My language of choice will by Python, as our problem will be mainly a text classification problem.
Recently, I was asked to see if we could predict if an article on Lifehack will become popular or not. If an article gets popular, it will be shared many times. This is a supervised learning problem.
Our task is to build a model to predict if an article on Lifehack will get more than shared over 3000 times. I will explain why it is 3000 below.
Data Preparation Process
Before we could throw our data into the algorithms automagically for results. There are a few things we need to do:
- Data collection. Without data, machine learning cannot be applied. I used Scrapy to collect data from Lifehack.
- Data preprocessing. The data needs to be cleaned of problems such as duplicated posts, invalid share counts, and other problems. We also need to construct the training and test ing set here.
- Data transformation. The data has to be in a format that is friendly to our machine learning before we can throw it to the algorithm.
Step 1: Data collection
I used Scrapy to collect the data. It is a wonderful library that makes web scraping a lot easier than you write one yourself handling the exceptional cases. I will not go into the technical details of writing the scraper.
In summary, we will collect the HTML and the URL of the post. I also collected the title, share count, category, publication date of the article, but this can all be extracted at later stages from the HTML of the article. As follows:
# items.py
from scrapy.item import Item, Field
class PopItem(Item):
title = Field()
url = Field()
shares = Field()
category = Field()
raw_content = Field() # the main body of the post, with HTML tags
text_content = Field() # the main body of the post, stripped of HTML tags
posted_at = Field()
I collected a total of 10,000 articles. But as you will see in the next step, a portion of them is unusable.
Step 2: Data preprocessing
You will most likely get wrong results without inspecting your data for problems. And unless you are doing Kaggle or homework, no one will give you the training and testing set.
Cleaning potential invalid data
We will check for data-duplication, which there are actually a lot due to the scraper considering URLs like these as equals:
http://www.lifehack.org/articles/lifehack/fifty-50-tools-which-can-help-you-in-writing.html http://www.lifehack.org/articles/lifehack/fifty-50-tools-which-can-help-you-in-writing.html?utm_campaign=innerlink&utm_medium=feellikethemediaistrollingyou&utm_source=post
They should be equal, so we must clean up these duplicate data.
There are many other checks such as checking for negative or unusually high share count data, etc. For instance, there are two articles which have like 100 times more than 3rd most shared article, you’ll want to confirm if it’s the a problem of the website or our data collection script.
Assign classes to articles
By inspecting the the raw share counts, we can see that most articles have zero shares or at most hundred of shares. Ideally, an article having more than 10,000 shares seems like a good candidate. However, very few articles match this criteria (less than 300), which you will see will affect us badly due to a classic problem called Class Imbalance Problem. As such, I will select a lower threshold. All articles with more than 3000 shares are considered positive examples of a popular article, while the rest are considered negative examples.
Constructing the training and testing sets
Because we want to benchmark our data consistently, we need to have a consistent testing set. Also note that we have a very imbalance data set where there are far more negative examples than positive examples.
I allocated 2/3 of the positive examples to the training set, and 1/3 of the positive examples to the testing set. 2000 negative examples are allocated to the testing set, and the rest of the negative examples are put into the training set. Visualized as below:
Lastly, note that it is very important that the training and testing data do not overlap at all, or you will get optimistically biased results. We will not touch our testing set from now own.
Step 3: Data transformation
We need to make sure our data is friendly to the input of the model algorithms. Concretely, we need to:
- Extract the raw content of the article body, but removing all those headers, footers, non-article related information.
- Extract the textual content out of the raw content, which we will strip all the HTML tags away for simplicity, and we can build a TF-IDF matrix later.
- Extract the title from the article, which we hypothesize to be very important (we get caught by titles first).
There are a lot of other features we can extract but for simplicity, we will just use these features in this post.
In the next post, I will address how we will get the data into the model and get the results out.


Apply access privileges to all existing experiments?
Groups
Group membership determines access privileges for newly created experiments. Managers automatically get Manage access, and Members get Read-Only access.
Assign and remove group membership via drag-and-drop.


Press any key to get started!
Wins:
Current word
Number of guesses remaining
Letters already guessed


| MATLAB 文件帮助: cv.findChessboardCorners | 查看 cv.findChessboardCorners 的代码 | Index |
findChessboardCorners Finds the positions of internal corners of the chessboard
[corners,ok] = cv.findChessboardCorners(im, patternSize)
[...] = cv.findChessboardCorners(..., 'OptionName', optionValue, ...)
patternSize = [points_per_row,points_per_colum] = [columns,rows]
).{[x,y], ...}
. Returns an empty cell if it fails to find all
the corners.The function attempts to determine whether the input image is a view of the chessboard pattern and locate the internal chessboard corners. The function returns a non-zero value if all of the corners are found and they are placed in a certain order (row by row, left to right in every row). Otherwise, if the function fails to find all the corners or reorder them, it returns an empty cell array. For example, a regular chessboard has 8x8 squares and 7x7 internal corners, that is, points where the black squares touch each other. The detected coordinates are approximate, and to determine their positions more accurately, the function calls cv.cornerSubPix. You also may use the function cv.cornerSubPix with different parameters if returned coordinates are not accurate enough.
Sample usage of detecting and drawing chessboard corners:
patternsize = [9,6]; % interior number of corners
gray = imread(fullfile(mexopencv.root(),'test','left01.jpg'));
% 'FastCheck' saves a lot of time on images
% that do not contain any chessboard corners
[corners,patternfound] = cv.findChessboardCorners(gray, patternsize, ...
'AdaptiveThresh',true, 'NormalizeImage',true, 'FastCheck',true);
if patternfound
corners = cv.cornerSubPix(gray, corners, 'Criteria',...
struct('type','Count+EPS', 'maxCount',30, 'epsilon',0.1));
end
img = cv.drawChessboardCorners(repmat(gray,[1 1 3]), patternsize, ...
cat(1,corners{:}), 'PatternWasFound',patternfound);
The function requires white space (like a square-thick border, the wider the better) around the board to make the detection more robust in various environments. Otherwise, if there is no border and the background is dark, the outer black squares cannot be segmented properly and so the square grouping and ordering algorithm fails.


Next Train Arrivals
Select Line
Select Station
Estimated Arrivals
| Line | Dest | Min |
|---|---|---|
| BL | Largo Town Center | ARR |
| YL | Fort Totten | 3 |
| BL | Largo Town Center | 8 |
| Line | Dest | Min |
|---|---|---|
| YL | Huntington | BRD |
| BL | Franconia-Springfield | 4 |
| YL | Huntington | 9 |
Station Information
Address
Crystal City Station1750 South Clark St.
Arlington, VA 22202


-
csv2latex.py --
Simple conversion from a csv file to &-separated fields suitable for latex tables.
A few features, such as markers for bold, italic, and bold-italic text (!,_,*)
and comma separation for large integers
-
debug_printer.py --
a mechanism for increasing and decreasing the level of indentation when printing,
particularly when entering and leaving functions; useful for debugging
(this is a class to be imported by other scripts)
-
degree_profile.sh --
degree_profile.sh - processes one file and outputs two columns:
the first is a vertex degree and the second is the number of occurences of that degree
a scatterplot can easily be created from these columns.
-
degree_sequence.sh --
degree_sequence.sh - outputs a list of vertex degrees for a graph in snap format
-
degree_stats.py --
degree_stats.py - given a graph in snap format as input, calculates a
variety of statistics on the degree sequence
-
extract_subgraph.py --
extracts an induced subgraph from a graph in snap format
-
graph.py --
Implements a graph as a Python class.
A graph is a set of vertices and edges along with information related to
the vertex cover problem. Each vertex has an adjacency list and a status,
one of the ones just below. In addition, a graph also has an upper bound -
the number of vertices currently in the cover, and a lower bound - the
minimum possible number of vertices in any cover. For the purpose of
deciding which graph to process next during branch and bound a graph has a
priority: the number of edges not covered by the set of vertices that are
part of the cover.
-
harvest_instance_data.sh --
creates a csv file with data for specific instances from a selection of existing csv files
-
highlight_competitive.py --
A preprocessor for csv2latex. Takes a file with an instance in each row
and a configuration for each column.
Produces output where competitive runtimes are shown in bold and
those within some threshold of the minimum are in bold italics.
The last output column lists configs that are within the threshold.
-
verify_vertex_cover.py --
checks to see whether a given solution is correct for a given vertex cover instance
Usage: ./verify_vertex_cover.py [options] problem_instance < solution
where problem_instance is a file in snap format and solution is one of
- a list of vertices in the cover, one per line (default)
- a single string of 0's and 1's, where a 1 in position i means i is in the cover
Can be used as a filter, as in
cat - | ./verify_vertex_cover [options] problem_instance
and then paste the solution on the terminal


grazing species seedling plots seed densities native treatments plant seedlings targeted (Figure seeded biomass invasive planted effects grass rate restoration fuel reduce {border-style establishment high coating plants px;} #ffffff;} annual included second‐year treatments, vegetation .). cover fall spring Bromus invaded plots, standing year Bates, coated grasses paddock reducing Davies, Ecology, growing plot second tectorum using wildfire < competition ecosystems forage negative rates species, treatments. ungrazed Boyd, Svejcar, density experimental kochia paddocks produced reduced results season trachycaulus Effects Elymus Figure dryland ecosystem grazing, greenstrip higher loads model planting rate, rates, secunda similar spatial spring‐grazed treatment Kostka, Poa Seed control data different highest low management randomly sagebrush seeding spread strategies uncoated unseeded use used densities, frequency grazing. increase interactions long‐term mixture monoculture nonnative provide px; seeds surfactant systems {font-family Grazing Madsen, Targeted Wildland areas cattle controls did differ dominated font-size greenstrips highly litter microstachys perennial plots. rangeland sampling species. survival times western Applications, D'Antonio, Ecological Ecology However, Information Leger, PLS Research Restoration Table University arid assigned biomass, cheatgrass competitive design differences double; grasses, grazed herbicide increased likely lower potential prior revealed risk significantly site tradeoffs (a) (b) ./j.-...x Basin Biological Fire, Goergen, Great International James, Nevada Plant Rangeland S). USA United Western [], address animals annuals approaches arrangement availability better block border-color border-width coating, community desirable determined direct effect elymoides establishment. fire‐resistant first‐year fuelbreaks hierarchical increasing livestock locations minimized models nested produce responses restoring sampled solid; success {font-style {font-weight (> (mostly ./-. ./WF ./s--- Beyers, California Call, Data Department Devoe, EAL, Invasive Johnson, June L., LMP, Management Management, November Pyke, Science, Sheley, Smith, States Supporting Vulpia Zvirzdin, alters analysis average based block, bold burn combinations communities. connectivity courier; cover, critical declined distribution diversity efforts em; establishment, exotic expected experiment factors fall‐ fall‐grazed fendleriana forbs future grassland greater growth identified improve increases initial interaction interspecific invasion kg/ha; multiple nonseeded production pt;} relative resource response secunda, seedlings, seeds, significant small soil steppe studies study, subplots, tectorum) test three‐way treatment. two, type types understand


object Liveness : TuneableTrackAttribute<Float>
Detects the presence of an audience in the recording. Higher liveness values represent an increased probability that the track was performed live. A value above 0.8 provides strong likelihood that the track is live.


Estimation of high-dimensional multi-response regression with heterogeneous noises under Heterogeneous group square-root Lasso penalty. For details see: Ren, Z., Kang, Y., Fan, Y. and Lv, J. (2018)<arXiv:1606.03803>.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.5.0) |
| Published: | 2018-08-31 |
| Author: | Zhao Ren [aut], Yongjian Kang [aut, cre], Yingying Fan [aut], Jinchi Lv [aut] |
| Maintainer: | Yongjian Kang <yongjiak at usc.edu> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | HGSL results |
| Reference manual: | HGSL.pdf |
| Package source: | HGSL_1.0.0.tar.gz |
| Windows binaries: | r-devel: HGSL_1.0.0.zip, r-release: HGSL_1.0.0.zip, r-oldrel: not available |
| OS X binaries: | r-release: HGSL_1.0.0.tgz, r-oldrel: not available |
Please use the canonical form https://CRAN.R-project.org/package=HGSL to link to this page.


featured stories
The Newsweek Momentum Awards will recognize five individuals around the globe, as well as one city, which will be chosen as the "smartest city in the world."
Senators Kamala Harris and Cory Booker, who took turns railing against Joe Biden, did not appear to have reaped significant gains from their performances.
Gorbachev was the Soviet leader when the agreement—limiting nuclear capable missiles in Europe—was signed in 1987.
We always want to hear from you, and to make that easier, we've implemented a new commenting forum. Take a look at the bottom of Newsweek articles. Spot.IM is a tool that helps readers respond to our stories and communicate with one another—and with us. Ask us a question, embed a GIF, point out a mistake. Be civil and respectful, please. And most important: Be in touch.
Newsweek is partnering with the respected global data research firm Statista Inc. to establish a ranking of Best Nursing Homes. The final rankings will be published in Newsweek magazine and on Newsweek.com
The International Baccalaureate (IB) accredited schools inspire young people to become lifelong learners and academic high achievers - find out more.
Africa’s fifth-largest oil producer is modernizing infrastructure and taking advantage of natural resources to build sustainable economic sectors including mining, timber and ecotourism.
top story
The Central American father was shot in the northern Mexico city of Saltillo. International human rights organizations have demanded a detailed investigation.
culture & travel
Los Angeles has quickly become one of the best cocktail cities in America and has the bars to prove it.
Researchers also found treasures like jewelry and coins in the remains of ancient shipwrecks.
more stories
"He cut out half the sentence. You should release the whole recording, senator," said the Kentucky Democrat seeking to unseat the senator.
The gunman was twice kicked out of school for compiling disturbing lists of fellow students, according to former classmates.
The current trade dispute between Asia's second and fourth largest economies has its roots in grievances dating from World War II.
New Smyrna Beach on the state's central east coast is considered to be the shark attack capital of the world, according to the International Shark
The gunman was killed by police within 30 seconds of the first shots being fired outside a bar in the city's entertainment district.
The addition of Valentina Sampaio as an VS Pink model comes one year after chief marketing officer Ed Razek insisted the company wasn't interested in trans models.
The Senate majority leader trended on Twitter for the second time in a week following mass shootings in Texas and Ohio.
The Earth is in the grips of what scientists have dubbed the "Sixth Mass Extinction," with the global rate of species extinction at least "tens to hundreds of times higher" than the average over the past 10 million years.
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Heralded as “magic” by Tommy Chong, CBD is more than just a trendy buzzword. In this Special Edition from Newsweek, learn everything you need to know about CBD, from potential uses to the ever-changing legislation surrounding it.
Africa’s fifth-largest oil producer is modernizing infrastructure and taking advantage of natural resources to build sustainable economic sectors including mining, timber and ecotourism.
"I fear that recent public comments by our President and others, and the responses they have generated, have deepened divisions and diminished our national life," Archbishop Wilton Gregory said.
GOP defectors have blasted the deal for adding $320 billion to current spending levels, a figure that contradicts their years of harping against deficits and debts.
Hawaii Representative and presidential hopeful Tulsi Gabbard has long opposed U.S.-sponsored regime change, but her opponents keep focusing on a fateful 2017 meeting in Syria.
Republican support for impeachment proceedings has nearly doubled from May to July.
Mega-fires have become the "new norm" in some states.
"[Officers] led him through the streets…on mounted horses. All as though they were slave masters, and he was their slave," tweeted New York City Public Defender Rebecca J. Kavanagh in reaction.
The Anti-Defamation League has said 8chan is "home to terrorist plots hiding in plain sight." But what is it?
Scientists studied people with strange sleep patterns who visited clinics.
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Start - Coming Soon Responsive Template
Documentation
You can use sublime text 3 for editing the code.
Download link : http://www.sublimetext.com/3
Open the image folder and replace the logo.png image with your logo. For retina support change the<EMAIL_ADDRESS>this image should be twice the size of the non retina image.
Open the index.html file in your code editor.
Go to line no 23 and edit the site description (alt tag ).
To change the image go to img folder and replace bg.jpg
To change the images go to img folder and replace the images which are named as bg-1.png, bg-2.png, bg-3.png
Open the index.html file in your code editor.
Go to line no 44.
Put every rotating words inside the  and separate it with a comma and the script will automatically cycle through each words in order.
Open main.js in the js folder.
Go to line no 70 and change the timer. Format of time is m/d/y.
Go to js folder and open the gmaps.js file in your code editor.
change coordinates on line number 1.
change zoom on line number 7
change title on line number 18
Map can be found at https://www.google.com/maps/
http://deathtothestockphoto.com/
http://www.imcreator.com/free/tech
https://github.com/peachananr/simple-text-rotator
http://retinajs.com/
http://getbootstrap.com/
http://fortawesome.github.io/Font-Awesome/
http://daneden.github.io/animate.css/


{% extends 'Artifactorial/base.html' %} {% load static %} {% block title %}My profile{% endblock %} {% block body %}
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Cthulu is currently sleeping under the sea at
R'yleh.
Azathoth, the boundless daemon sultan whose name
no lips dare speak aloud; & who gnaws hungrily
in inconveivable unlighted chambers beyond time & space.
Abdul Alhazred, the "Mad Arab" who wrote Kitab al-Azif
(the Necronomicon). Devoured by an invisible beast in
broad daylight in a public marketplace.


Notice: This wallet provides functionality for the QRL Testnet, and in future the QRL Mainnet. Do not send QRL ERC20 Tokens to a wallet created by this service! Bookmark WALLET.THEQRL.ORG - The QRL Foundation only hosts services on THEQRL.ORG. No other domains are affiliated with The QRL Foundation.


A new Eclipse plugin for JiBX is now available. You can install the plugin by making use of Eclipse's Software Updates handling, with the update site url http://jibx.sourceforge.net/eclipse/. If you want a detailed walk-through of how to configure Eclipse to use this site, see the Install page.
Once you've installed the plugin, you can activate it for any of your Eclipse projects using the project context menu, and for each project specify a folder containing the binding definitions used by that project. The plugin will parse all XML files contained in your specified mappings folder to identify which Java classes require bindings, and will automatically run the JiBX binding compiler whenever it detects a change that might effect the bindings or bound classes. For a detailed walk-through of how to activate the plugin for a project, and details of when and how it runs the binding compiler, see the Usage page.
The plugin is currently distributed in versions that align with a specific release of JiBX. Upon adding the update site to Eclipse, either JiBX 1.1.6a, 1.2.1, or 1.2.2 will available: choose one (but not more) of these to install. If you want to change to a different version of JiBX (including some older versions, though this has not been thoroughly tested), first locate the plugin jar named org.jibx.eclipse_x.x.x.jar within the plugins folder of your Eclipse installation. You can open this jar with a tool which supports zip file formats (or expand it to a full directory structure using the jar tool included in the Java JDK) and replace the jibx-bind.jar and jibx-run.jar files within the lib directory of the jar with those for your target JiBX version. Then just save the modified org.jibx.eclipse_x.x.x.jar and restart Eclipse.
| Module Name | Primary Developer | Status |
|---|---|---|
| jibx-eclipse (svn) | Michael McMahon | Beta 0.1 release May 30, 2008 |


Birthday today? God has made everyone special, so are some of the food outlets and places in Australia, who makes you feel even more special by providing you with free stuff and/or deals!
Simply search such places using 4-digits Post Code within 5KM radius, ex: 2000... and enjoy!


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--- ---
SEMINAR.....
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Speaker |
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Prof Ravi. S. Kulkarni
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Affiliation |
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Harish Chandra Research Institute
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Subject Area |
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Mathematics
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Venue |
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Lecture Hall I, Dept of Mathematics
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Time |
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4.00 pm
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Date |
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September 12, 2005
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Event Title1 |
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"Dynamical Types of Transformations in Classical Geometries"
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| Abstract |
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| In all classical geometries, for example, Euclidean, spherical,hyperbolic, linear, affine, projective, inversive,... also their complex and quaternionic analogues, we talk about "dynamical types" of transformations, and observe that in each case there are only finitely many "dynamical types". There is no general definition of a "dynamical types" in the literature. In this lecture, we shall offer a definition of a "dynamical type", and account for the finiteness phenomenon. We shall observe that the underlying field of real numbers in the examples cited above plays a crucial role. If we define the anologues of the above-cited geometries over other fields, we observe that the "finiteness of dynamical types" no longer holds. There arise new arithmetic invariants. e results are obtained from some very general results on arbitrary group actions, which can serve to unify certain parts of mathematics. As an example we cite the theory of Rational Canonical Forms of n x n matrices, and the Frobenius' theory of Centralizers of such matrices. |


Club Co-Fouder
The Designer who desires knowledge!
I am a coding ninja who likes increase his skill sets by learning everyday evolving technology and try something new in life.
Club Co-Founder
The Enthusiast Punk
I love writing code to make computers do things so I can relax and be lazy instead. I love all-things tech and superheroes.
Club Co-Founder
The Geeky Guru
I am a geeky enthusiast who likes to solve real world problems in the form of code and apply my passion to the work.
Club Co-Fouder
Techie Film maker!
I am a tech community lover who loves to explore and learn new things apart from that I am also a filmmaker I am the best example to those who don't know how to code or don't like to code but still want to be the part of the community .
Core Team
The Transformator and Imaginator Geek
I can Transform the unknown Possiblity to Achievability, Enthusiastic of creating Solutions, Imagination at its peak. Like to Learn to Lead, taking Community together to Sail. Confident, Self Reliant, Coder. As it says, here is a "Geek For Geeks".
Core Team
The Black Hat Technocrate
I like to wake up with the hot cup of code, morning goes on with reading books, lunch is carried on with interfacing tech hardware, afternoon with learning new skills , evening goes on with slight twist of hackathons , dinner with startups and dreams goes on with "Sitting on the shoulders of Giants" a.k.a physics.


April 2017 / Past Issues
It’s that time of year again! ZTEsoft Annual Summit 2017 will be taking place at a unique castle on French riviera - Château de Crémat on May 18, 2017.
ZTEsoft Annual Summit 2017 brings together executives from major communication service providers that are using ZTEsoft innovative solutions and executive industry experts to network, learn and collaborate on becoming digital service providers. The Summit is a place where thought leaders from around the world are encouraged to share ideas, experiences, and knowledge.
TM Forum Live! 2017
Nice, France
15 - 18 May, 2017
ZTEsoft has successfully passed the re-evaluation for Capability Maturity Model Integration (CMMI) Level 5 certification after a rigorous review and audit.
ZTEsoft has been selected as finalist in TM Forum Excellence Awards 2017 for ZSmart Digital BSS solution. The Excellence Awards program honors global service and solution provider that are making significant contributions to advance critical best practices and standards for the benefit of entire industries and digital ecosystems.
ZTEsoft showcases smart transportation innovations and best practices, and exchanges ideas of challenges and opportunities in digital transformations with leading industry experts at CeBIT.
At MWC 2017, ZTEsoft showcases its ZSmart Next-Generation OSS that helps operators build an open platform, enabling them to realize open, shareable, agile and intelligent business operations.
ZTEsoft has been on the list of TM Forum’s Excellence Award 2017 Nominees for its ZSmart Digital BSS and ZSmart QRun solution.
ZTEsoft elaborated how its “POWER” can help Communication Service Providers (CSPs) realize digital transformation in an open and collaborative way.
AIS is the largest mobile operator in Thailand with over 34 million subscribers for the mobile network. AIS is moving towards becoming a total telecom service provider that offers FBB and MBB services, as well as digital content to increase its share of the consumer's wallet. The operator starts the Fixed Broadband Support System (FBSS) with ZTEsoft, and service is ready for launch in about 5 months.
ZTEsoft is dedicated to providing you with the latest, high-value information that will help you to know more about us. Contact us at<EMAIL_ADDRESS>with any questions.
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The official University of Oregon College of Education newsletter
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One in five students has a hearing loss, but many professors at the UO don't use the amplification equipment in large classrooms. If an awareness campaign led by CDS' Karen McLaughlin is successful, they'll all be rocking the mic. |
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With their quilt on display in HEDCO, students in Laurie Kahn's EDST 111 class keep turning thorny issues into usable art, the first of many installations to come at the COE. |
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| This issue is as wide and deep as the mighty Willamette, the banks of which presently are swollen by rain. If the COE had a fall theme, it was newness. New faculty, a new president, new branding, new scholarships, and of course, new students. On behalf of the faculty and staff, we hope you had an enjoyable fall and are looking forward to a relaxing Holiday season filled with family and friends and a healthy New Year. Your commitments toward the future inspire us to keep innovating and pushing forward for kids and families. It's going to be quite an exciting year! |
| Education Matters is distributed each term. Use the e-mail link below to contact the editor; physical letters are always welcome as well. |
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Marketing and Communications
College of Education
1215 University of Oregon
Eugene, OR 97403-1215
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College of Education
1215 University of Oregon
Eugene, OR 97403-1215 |
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I have used various opiates/opioids in my life, and I have been dependent on them for the last three years. I have a pretty high tolerance, it takes me 120mg of morphine sulfate just to get out of withdrawal, and around 150mg to get a good nod.
Over the last few months, I've been unable to get a decent euphoria out of morphine, oxycodone, or even fentanyl, so I decided to give Opana ER a try. My mindset was terrible (I was in WDs) but I was in a comfortable setting and I was really anticipating the relief. I had read that oxymorphone is ten times more potent than morphine, so a 20mg pill should have done the trick, but it didn't! I had taken the pill orally and chewed it up, but I was still in withdrawal two hours later! I gave up and took my daily morphine.
The next day I read [?] that oxymorphone is only ten percent bioavailable if taken orally, but it is around 45% bioavailable if snorted, so I bought another 20mg ($60.00), scraped the coating off, crushed it and then snorted half in each nostril. Within 20 minutes a wave of euphoria hit me that felt like my first oxycontin, it was even better than heroin! So the moral of the story is that I find that oxymorphone is not very satisfying orally but it is very strong insufflated. The little green hexagonal pills of just 20mg feel like at least 100mg of oxycodone. Oxymorphone is by far the most euphoric opiate I've ever tried, but I would not recommend it for inexperienced users, for that matter, I wouldn't recommend any opiate for anybody.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


NOBODY (director/writer: Shundo Ohkawa; cinematographer: Hiroshi Ogata; editor: Yoshio Kitazawa; cast: Masaya Kato (Taki), Jimpachi Nezu (Detective Karaki), Riki Takeuchi (Nanbu), Hideo Nakano (Konishi), Hiromi Nakajima (Rika), Yumi Nishiyama (Reiko); Runtime: 100; Phaedra Cinema; 1999-Japan)
Reviewed by Dennis Schwartz
A bloodthirsty revenge film based on a childish incident in a nightclub, where three yuppie office workers make fun of the way three men at the next table are dressed. The director has gone after style and has thrown substance out the window, as the film follows this war of words as it escalates into an ugly scene of macho posturing and then into gore. The three stylishly-dressed ad executives are: Taki (Kato), who is prone to wearing Hermes ties and acting cool; Nambu (Takeuchi), who is the most bellicose; and, Konishi (Nakano), who is bespectacled, fearful and pudgy. They leave the bar after the other table answers their taunts back, and when Konishi returns to get his umbrella, he is set upon and has a broken bottle smashed over his face, causing him to be hospitalized.
The film takes this childish revenge-fantasy film into an unbelievably crude depiction of gun fights, arrow attacks, knife and fist fights, and a scissor attack. All the fight scenes were choreographed and looked as phony as Confederate money. The film was a clear imitation of a Hong Kong action film.
This unoriginal film has nothing to say about these faceless executives or their counterpoints, who up the dissing into physical violence. The mystery is supposed to be sparked by guessing if the antagonists are office workers, yakuza, or police. The paranoid thriller is callibrated to show how the men feel when their masculinity is being questioned.
Not able to forget the attack on Konishi, even after he is released from the hospital and is walking with his pals down an alleyway, the men recognize the Rolex watch guy and pounce on him, supposedly beating him to death. Things take a harrowing turn for the men, as they each receive phone calls threatening revenge for the death of their friend. But to their surprise, no body is ever reported found, and the police are not looking for them. The menacing caller tells them, he is not concerned about telling the police, he'll take care of the problem.
Poor Konishi is severely worked over and sent to the hospital again, this time with scissor wounds to the stomach, when he agrees to meet the threatening caller. Nambu is attacked with arrows and slain, while Taki picks up a girl on the rainy road, Rika (Hiromi), with whom he has a quickie. He is supposedly serious about his workplace girlfriend Reiko (Yumi), but finds time to play, probably to take his mind off those coming after him.
With the death of Nambu, Taki becomes frightened and goes to the police, telling them the truth. But they can't help. The main villain, the guy with the Zippo lighter, meets up with Taki and they have one of those ridiculous Hong Kong gunfights. Zippo is one of those villains who just can't seem to die (I suppose he's supernatural!). The awkward story moves on its pointless and bloody way, clearing nothing up by the end, though it tried when it had Detective Karaki (Nezu) say that the attackers are part of a new Japan, where punks who used to become part of a yakuza crime family now become businessmen.
Shundo Ohkawa's direction is meant to be glossy, high-tech, but suffers from being amateurish and outdated, overrun with trick camera shots to capture the violence. The director's color scheme was nightmarish and depressing, some scenes were smothered in metallic blue shadings.
The film was about as uninspiring as reading GQ. The only fun in the film, was in the opening scene, watching the two tables trade smart-alecky digs at each other, other than that this film was as much fun as watching someone get hit over the head with a bottle.
REVIEWED ON 10/8/2000 GRADE: D
Dennis Schwartz: "Ozus' World Movie Reviews"
http://www.sover.net/~ozus
<EMAIL_ADDRESS>© ALL RIGHTS RESERVED DENNIS SCHWARTZ
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


Methods summary
public static
array
|
#
all( string $minFont = 12, string $maxFont = 24 )
A convenient method that aggregates the results of all the other methods in the class. Example of output:
A convenient method that aggregates the results of all the other methods in the class. Example of output:
array(
'taxonomy' => array(
'available' => array(
'taxonomy1' => array(
'count' => 10,
'slug' => 'taxonomy1',
'name' => 'Taxonomy One',
'font' => 24
)
),
'selected' => array(
'taxonomy2' => array(
'slug' => 'taxonomy2',
'name' => 'Taxonomy Two'
)
),
'total' => 10
),
'rating' => array(
'available' => array(
'10-20' => array(
'count' => 4,
'slug' => '10-20',
'to' => 20,
'from' => 10
)
),
'total' => 4
)
)
Parameters
- $minFont
- The minimum font size to use for display in a tag cloud (defaults to : 12)
- $maxFont
- The maximum font size to use for display in a tag cloud (defaults to : 24)
Returns
array An associative array where the keys represent the data point with a list of selected and/or available options.
|
public static
array
|
#
range( string $field )
Analyse query parameters for range slugs and determine which facets are selected vs. which are available for the given field. Example of output:
Analyse query parameters for range slugs and determine which facets are selected vs. which are available for the given field. Example of output:
array(
'available' => array(
'10-20' => array(
'count' => 4,
'slug' => '10-20',
'to' => 20,
'from' => 10
)
),
'selected' => array(
'-20' => array(
'slug' => '-20',
'to' => 20
)
),
'total' => 4
)
Parameters
- $field
- The field to determine range facet information about
Returns
array An associative array based on example provided
|
public static
array
|
#
taxonomy( string $tax )
Analyse query parameters for taxonomoy slugs and determine which facets are selected vs. which are available for the given field. Example of output:
Analyse query parameters for taxonomoy slugs and determine which facets are selected vs. which are available for the given field. Example of output:
array(
'available' => array(
'taxonomy1' => array(
'count' => 10,
'slug' => 'taxonomy1',
'name' => 'Taxonomy One',
'font' => 24
)
),
'selected' => array(
'taxonomy2' => array(
'slug' => 'taxonomy2',
'name' => 'Taxonomy Two'
)
),
'total' => 10
)
Parameters
- $tax
- $field The taxonomy type to retrieve facet information about
Returns
array An associative array based on example provided
|
public static
array
|
#
types( string $types )
Gather post type facet information for the provided post types. Example of output:
Gather post type facet information for the provided post types. Example of output:
array(
'available' => array(
'post' => array(
'count' => 10,
'slug' => 'post',
'name' => 'Posts',
'font' => 24
)
),
'selected' => array(
'custom_post_type' => array(
'slug' => 'cpt',
'name' => 'Customs'
)
),
'total' => 10
)
Parameters
- $types
- $field The post types that were configured for indexing
Returns
array An associative array based on example provided
|
public static
integer
|
#
cloud( array $items, array $item, string $min = 12, string $max = 24 )
Will calculate a font size based on the total number of results for the given item in a collection of items. Example of output:
Will calculate a font size based on the total number of results for the given item in a collection of items. Example of output:
array(
'available' => array(
'taxonomy1' => array(
'count' => 10,
'slug' => 'taxonomy1',
'name' => 'Taxonomy One',
'font' => 24
)
),
'selected' => array(
'taxonomy2' => array(
'slug' => 'taxonomy2',
'name' => 'Taxonomy Two'
)
),
'total' => 10
)
Parameters
- $items
- An array of arrays that contain a key called 'count'
- $item
- An item out of the array that you wish to calculate a font size
- $min
- $minFont The minimum font size to use for display in a tag cloud (defaults to : 12)
- $max
- $maxFont The maximum font size to use for display in a tag cloud (defaults to : 24)
Returns
integer The calculated font size
|
public static
string
|
#
urlAdd( string $url, string $type, string $value, string $operation = 'and' )
Modifies the provided URL by appending query parameters for faceted searching.
Modifies the provided URL by appending query parameters for faceted searching.
Parameters
- $url
- The URL of the page that supports F.E.S
- $type
- The data point you wish to enable faceting for (ie: a field name or taxonomy name)
- $value
- The value/slug that was provided by another method call in this class
- $operation
- Whether the facet should query using 'and' or 'or' (defaults to and)
Returns
string The URL modified to support faceting
|
public static
string
|
#
urlRemove( string $url, string $type, string $value )
Modifies the provided URL by removing query parameters that control faceting.
Modifies the provided URL by removing query parameters that control faceting.
Parameters
- $url
- The URL of the page that supports F.E.S
- $type
- The data point you wish to remove faceting for (ie: a field name or taxonomy name)
- $value
- The value/slug that was provided in the URL (query parameters)
Returns
string The URL modified to remove faceting for the provided data point
|


Greetings!
for a short Resume download HughMurrell2023Resume.pdf
for a full Curriculum Vitae download HughMurrell2023CV.pdf
I am interested in contract work in the fields of Bioinformatics , Deep Learning and Mathematical Modelling.
Please feel free to contact me by email if you think you can use my skills.


csubj:cleft
: relative clause modifier
Irish cleft constructions use a copula and are analysed in line with other copular construction: COP PRED SUBJ.
In contrast to English, Irish clefts are much less restrictive with regards to the type of element that can be fronted: nouns, prepositional phrases, adverbial phrases, adjectives and verbal nouns. Note that the verbal particle that introduces csubj:cleft
is always labelled mark:prt
.
Examples
Nominal fronting
Is leabhar a thug sí dom ‘It is a book that she gave me’
Is leabhar a thug sí dom \n is book [] gave she to_me
csubj:cleft(leabhar, thug)
mark:prt(thug, a)
cop(leabhar, Is)
NOTE: Relative clauses may also be clefted. As shown below, the relative clause is raised to predicate level when it occurs in the predicate position in a copular phrase.
Is í Croinic Thomáis Eccleston is foinse do sheoladh na litreach seo `The Chronicle of Thomas Eccleston is the source of the sending of this letter’
ROOT Is í Croinic Thomáis Eccleston is foinse do sheoladh na litreach seo \n Is it(fem) Chronicle of_Thomas Eccleston [] source of sending of_the letter this
csubj:cleft(Croinic, foinse)
root(ROOT, Croinic)
Is é Michael D. Higgins ba chionsiocair leis an Roinn a bhunú sa bhliain 1992. `Michael D. Higgins was the driving force behind the establishment of the Department in 1992.
ROOT Is é Michael D Higgins ba chionsiocair leis an Roinn a bhunú sa bhliain 1992. \n ROOT Is it(masc) Michael D Higgins [] primary_cause with the Department to establish in_the year 1992.
root(ROOT, Michael)
csubj:cleft(Michael, chionsiocair)
csubj:cop(chionsiocair, bhunú)
Adverbial fronting
Is laistigh de bhliain a déanfar é ‘It is within a year that it will be done’
Is laistigh de bhliain a déanfar é \n is within a year [] will_be_done it
csubj:cleft(laistigh, déanfar)
mark:prt(déanfar, a)
cop(laistigh, Is)
Prepositional phrase fronting
Is sa pháirc a chonaic mé é `It is in the park that I saw him’
Is sa pháirc a chonaic mé é \n is in_the park [] saw I him
csubj:cleft(pháirc, chonaic)
mark:prt(chonaic, a)
cop(pháirc, Is)
Adjective predicate fronting
Is mó atá sí siúd ina ghá ná sinne anso. `She is needed here more than we are.’
Is mó atá sí siúd ina ghá ná sinne anso. \n Is more that_is she [emph] in_its need than us_[emph] here.
csubj:cleft(mó, atá)
cop(mó, Is)
NOTE: In phrases where the adjectival predicate is fronted, the noun should still be treated as the predicate with the adjective demoted to adjectival modifier dependent on that noun/the head of the noun phrase.
Is iomaí seift atá á lorg ag údaráis phoiblí ar fud an domhain… `Public authorities all over the world are looking for numerous ways to…’
Is iomaí seift atá á lorg ag údaráis phoiblí ar fud an domhain \n Is many trick that_are at_her looking by authorities pub on whole of_the world
csubj:cleft(seift, atá)
cop(seift, Is)
amod(seift, iomaí)
NOTE
Sometimes it is difficult to determine whether to use the csubj:cleft label or the acl:relcl label for certain phrases. Here are a few steps to help determine which label to use.
- Check to see if it follows the copula-predicate-subject order-if so then it is likely to be a cleft.
- If the phrase is fronted for emphatic reasons then is is likely to be a cleft.
- Categorise by how it’s fronted (PP, NP, AdvP, AdjP)- if it is a fronted NP, then it is more likely to be either a relative clause or a cleft. If the NP consists of an augment pronoun and a noun it is a cleft. However, if the first noun is not an augment pronoun and is being equated with the second NP, then the second NP has an embedded relative clause.

Is í Máire a chuir Dick Spring i mbun na Roinne Oideachais
csubj:cleft(Máire, chuir)
Object predication followed by relative clause (not cleft but easily confused!)
- (ise ‘she’ & té ‘the person’)
Is ise an té a chuir Dick Spring i mbun na Roinne Oideachais ‘She is the person who put Dick Spring in charge of the Department of Education’
Is ise an té a chuir Dick Spring i mbun na Roinne Oideachais
acl:relcl(té, chuir)
csubj:cleft in other languages: [ga] [gd] [gv] [la]


Resources
Topics
Activation Maximization
- Lecture 11: CNNs for Image Data, Activation Maximization and Saliency Maps
- Lecture 12: Attention for Debugging Language Models
- Lecture 8: Introduction and overview of Viz for Deep Models
- Lecture 9: Convolutional Neural Networks for Image Data
- Lecture 8: Introduction and overview of Viz for Deep Models [Notebook]
Advanced Practical Data Science
BERT
CCNs
- Lecture 11: CNNs for Image Data, Activation Maximization and Saliency Maps
- Lecture 12: Attention for Debugging Language Models
Cloud
Compression
conda env
Containers
- Lecture 2: Containers
- Reading Discussion 1
- Lecture 3: Kubernetes
- Use Case 1: Dockers in a real setting
Convolutional Neural Networks
Dask
- Reading Discussion 3: Dask
- Lecture 4: Dask
- Use Case 3: Dask in a real setting
- Lecture 4: Dask [Notebook]
Debug Models through Visualization
- Lecture 8: Introduction and overview of Viz for Deep Models
- Lecture 8: Introduction and overview of Viz for Deep Models [Notebook]
Deep Learning
Distillation
Docker
- Lecture 2: Containers
- Lecture 2: Demo2 [Notebook]
- Lecture 2: Demo2 [Notebook]
- Reading Discussion 1
Docker Orchestrator
ELMO
env
enviroments
GRU
Helm
Image Classification and Transfer Learning
Image Data
Introduction
Kubernetes
LIME
- Lecture 8: Introduction and overview of Viz for Deep Models
- Lecture 8: Introduction and overview of Viz for Deep Models [Notebook]
Loft
LSTM
Parallel Computing
- Lecture 4: Dask [Notebook]
Parallel Processing
Python
Recurrent Neural Networks
RNN
Saliency Map
- Lecture 8: Introduction and overview of Viz for Deep Models
- Lecture 8: Introduction and overview of Viz for Deep Models [Notebook]
Saliency Maps
- Lecture 11: CNNs for Image Data, Activation Maximization and Saliency Maps
- Lecture 12: Attention for Debugging Language Models
Skaffold
Style Transfer Model
Text Data
Transfer Learning
- Reading Discussion 5: Transfer Learning across Tasks
- Journal Discussion: Transfer Learning (Statistical approaches to Transfer Learning)
- Lecture 5: Intro to Transfer Learning
- Lecture 6: Transfer Learning 2
- Lecture 7: Distillation and Compression
- Lecture 6: Transfer Learning 2 [Notebook]


TEI Usage Demohttp://tapasproject.org/tapas-commons/files/御前落居記録http://tapasproject.org/tapas-commons/files/御前落居奉書
Application to visualize the number of litigations by month
Convert into the timeline with Google Sheets and Timeline JS
Convert into the structure information of IIIF manifest
Convert into html
IIIF and TEI
IIIF Annotations
RDF Store


Triangle-Tracker
Enter dimensions of the 3 sides to track your trianlge:
Enter number: Side A
Enter number: Side B
Enter number: Side C
Track Triangle
Tracked your trianlge! Turns out it is an equilateral triangle.
Tracked your trianlge! Turns out it is an isoseles triangle.
Tracked your trianlge! Turns out it is an scalene triangle.
Opps! Those dimensions do NOT make a triangle. Please try again.


I write every post seriously, but don't read it seriously. It is good for wasting your important time.
모든 글은 진지하게 적지만, 진지하게 받아들이지 말 것. 소중한 시간을 낭비하기 좋음.
{% endif %}© {{ site.data.theme.name }}, {{ 'now' | date: "%Y" }} — built with Jekyll using Lagom theme


We use webcomponents to make easy to build custom interoperable things. #usetheplatform
Any sensors or actuators you would like to add to this list? Open an issue or submit a PR!


The paging component provides a SKY UX-themed pagination control to display list data across multiple pages. It hides the pagination control when data fits on a single page.
Specifies the page number of the currently displayed page. Page numbers start at 1 and increment. This property accepts number values.
Specifies the total number of items across all pages. This property accepts number values.
Specifies the maximum number of pages to display in the pagination control. This property accepts number values.
Specifies the number of items to display per page. This property accepts number values.
Specifies a label for the pagination control to support accessibility. The label should be unique and descriptive to help users of assistive technology differentiate pagination controls when multiple paging components appear on a page. This property accepts string values.
Fires when the current page changes and emits the new current page.
If your application uses multiple paging components on a page, use the pagingLabel property to give each one a unique, descriptive label. This helps users of assistive technology differentiate the components and understand what each does.


The Traveling Tricycle
Post 4: Ayutthaya Ruins (jacob)
In which our heroes bravely explore temples and almost expire from heat exhaustion.
Post 3: Chiang Mai Night Market (jacob)
In which our heroes bravely don't buy things, but look at them.

Post 1: Arrival to the Magical Land of Thai (hills)
In which our heroes bravely adventure to wonky waiting rooms, busy Bangkok, and cheap Chiang Mai.
Post 5: Bangka and Belitung
In which our heroes bravely adventure to extremely islandy islands.
(coming soon...)


Send Money
1 - Sridhar
2 - Krishna
3 - Mahesh
4 - Balu
5 - Kaji
..
From Bank Account Id
To Bank Account Id
Amount


UICircularProgressRingFormatter
public struct UICircularProgressRingFormatter : UICircularRingValueFormatter
UICircularProgressRingFormatter
The formatter used in UICircularProgressRing class, responsible for formatting the value of the ring into a readable string
-
The name of the value indicator the value label will appened to the value Example:
GB
->100 GB
Important
Default =
%
Author
Luis Padron
Declaration
Swift
public var valueIndicator: String
-
A toggle for either placing the value indicator right or left to the value Example: true ->
GB 100
(instead of 100 GB)Important
Default = false (place value indicator to the right)
Author
Elad Hayun
Declaration
Swift
public var rightToLeft: Bool
-
A toggle for showing or hiding floating points from the value in the value label
Important
Default = false (dont show)
To customize number of decmial places to show, assign a value to decimalPlaces.
Author
Luis Padron
Declaration
Swift
public var showFloatingPoint: Bool
-
The amount of decimal places to show in the value label
Important
Default = 2
Only used when showFloatingPoint = true
Author
Luis Padron
Declaration
Swift
public var decimalPlaces: Int
-
formats the value of the progress ring using the given properties
Declaration
Swift
public func string(for value: Any) -> String?


Grand Magister Tifaren:
You want me to hold a seance? The necromantic rite of communion is the secret magic of Dark Elves. It's not for novices!
(This quest is for characters level 63 or above who have also completed the Hidden Truth quest.)


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| Interface Summary | |
|---|---|
| BillingAddrValidator | Object that implement this interface know how to validate a billing address of type atg.core.util.Address or any of its subclasses. |
| ShippingAddrValidator | Object that implement this interface know how to validate a shipping address of type atg.core.util.Address or any of its subclasses. |
| Class Summary | |
|---|---|
| BillingAddrValidatorImpl | This class provides a default implementation of BillingAddrValidator. |
| EventSender | This is a base class that should be extended by other processors that wish to send events from within a chain. |
| LoadProperties | This abstract class stores a list of properties to be loaded for a bean. |
| OrderRepositoryUtils | This class contains utility methods which the load and save processors use to access the OrderRepository. |
| ProcAddOrderToRepository | This processor calls updateOrder() on the supplied Order and then checks to see if it is transient. |
| ProcAuthorizePayment | This processor authorizes payment for an Order in the form of a PaymentGroup. |
| ProcChangeOrderState | This processor changes the state of the order to the state in the newOrderState property. |
| ProcCheckForDiscontinuedProducts | This processor verifies that none of the products in the CommerceItems within the order are not discontinued. |
| ProcCheckForErrors | This processor simply checks whether the PipelineResult has any errors. |
| ProcCheckForExpiredPromotions | This processor checks whether any expired promotions are being used or were used during the pricing of any part of the order. |
| ProcCheckOrderState | This processor returns the value in successReturnValue if the order state is in the statesList property. |
| ProcCreateImplicitRelationships | This processor creates relationships in an Order which has one ShippingGroup and/or one PaymentGroup. |
| ProcCreditCardModCheck | This processor does a mod check on credit card numbers to see if they are valid. |
| ProcDispatchOnOrderState | Dispatch to the next processor element based on the string value of the order state. |
| ProcDispatchOnProperty | Dispatch to the next processor element based on the value of some named property of some designated object in the pipeline arguments map. |
| ProcExecuteChain | This processor executes a chain from within a processor of another chain. |
| ProcLoadCommerceItemObjects | This processor loads the CommerceItem objects from the OrderRepository into the Order object. |
| ProcLoadCostCenterObjects | This processor loads the CostCenter objects from the OrderRepository into the Order object. |
| ProcLoadHandlingInstructionObjects | This method loads the HandlingInstruction objects from the OrderRepository into a ShippingGroup in the Order object. |
| ProcLoadOrderObject | This processor loads the Order object from the OrderRepository. |
| ProcLoadPaymentGroupObjects | This processor loads the PaymentGroup objects from the OrderRepository into the Order object. |
| ProcLoadPaymentStatusObjects | This processor loads the PaymentStatus objects from the OrderRepository into the PaymentGroups of the Order object. |
| ProcLoadPriceInfoObjects | This processor loads the PriceInfo objects from the OrderRepository into the Order object. |
| ProcLoadRelationshipObjects | This processor loads the Relationship objects from the OrderRepository into the Order object. |
| ProcLoadShippingGroupObjects | This processor loads the ShippingGroup objects from the OrderRepository into the Order object. |
| ProcMoveUsedPromotions | This processor moves any used promotions in the user's profile from the activePromotions list to the usedPromotions list. |
| ProcRemoveEmptyPaymentGroups | This processor removes empty PaymentGroups from an Order. |
| ProcRemoveEmptyShippingGroups | This processor removes empty ShippingGroups from an Order. |
| ProcRemoveExpiredCommerceItems | This processor is responsible for the removal of CommerceItems whose sku or product have been removed from the database from Orders whose states are specified in the @see OpenOrderStates. |
| ProcSaveCommerceItemObjects | This processor saves the CommerceItem objects into the OrderRepository from the Order object. |
| ProcSaveCostCenterObjects | This processor saves the CostCenter objects into the OrderRepository from the Order object. |
| ProcSaveHandlingInstructionObjects | This processor saves the HandlingInstruction objects into the OrderRepository from the Order object. |
| ProcSaveOrderObject | This processor saves the Order object into the OrderRepository. |
| ProcSavePaymentGroupObjects | This processor saves the PaymentGroup objects into the OrderRepository from the Order object. |
| ProcSavePaymentStatusObjects | This processor saves the PaymentStatus objects into the OrderRepository from the PaymentGroup object. |
| ProcSavePriceInfoObjects | This processor saves the PriceInfo objects into the OrderRepository from the Order, CommerceItem and ShippingGroup objects. |
| ProcSaveRelationshipObjects | This processor saves the Relationship objects into the OrderRepository from the Order object. |
| ProcSaveShippingGroupObjects | This processor saves the ShippingGroup objects into the OrderRepository from the Order object. |
| ProcSendFulfillmentMessage | This processor sends a message to the fulfillment engine when an order has been processed. |
| ProcSendGiftPurchasedMessage | This processor sends an event to the scenario engine when a gift has been purchased. |
| ProcSendPromotionUsedMessage | This processor sends an event to the scenario engine when an promotion is used in an order. |
| ProcSendScenarioEvent | This processor sends scenario action events to the scenario server. |
| ProcSendScheduledOrderMessage | sends scheduled order submit messages |
| ProcSetCatalogRefs | This processor sets the catalog references into the CommerceItems in the order. |
| ProcSetCostCenterAmount | This processor determines the values that need to be set into the amount field of a CostCenter. |
| ProcSetLastModifiedTime | This processor sets the catalog references into the CommerceItems in the order. |
| ProcSetPaymentGroupAmount | This processor determines the values that need to be set into the amount field of a PaymentGroup. |
| ProcSetProductRefs | This processor sets the product references into the CommerceItems in the order. |
| ProcUpdateGiftRepository | Check the shipping groups of an order for Handlers. |
| ProcUpdateOrder | This processor calls updateOrder() on the supplied Order |
| ProcValidateCostCenter | Validate a single Cost Center at checkout time. |
| ProcValidateCostCentersForCheckout | This processor validates CostCenters before checking an Order out. |
| ProcValidateCreditCard | Validate a single instance of the CreditCard payment group at checkout time. |
| ProcValidateCurrencyCodes | Validates that all the PriceInfo objects in the Order have been priced using the same currency code. |
| ProcValidateElectronicShippingGroup | Validate a single instance of ElectronicShippingGroup at checkout time. |
| ProcValidateGiftCertificate | Validate a single instance of the GiftCertificate payment group at checkout time. |
| ProcValidateHandlingInstructionsForCheckout | This processor validates that the total quantities in the HandlingInstructions do not exceed the amount assigned to the ShippingGroup. |
| ProcValidateHardgoodShippingGroup | Validate a single instance of HardgoodShippingGroup at checkout time. |
| ProcValidateInvoiceRequest | Validate a single instance of the InvoiceRequest payment group at checkout time. |
| ProcValidateOrderCostsForCheckout | This processor validates that all order costs are accounted for by a PaymentGroup. |
| ProcValidateOrderForCheckout | This processor validates that all there is at least one CommerceItem, one ShippingGroup, and one PaymentGroup in the Order. |
| ProcValidatePaymentGroupsForCheckout | This processor validates PaymentGroups before checking an Order out. |
| ProcValidateShippingCostsForCheckout | This processor validates that all shipping costs are accounted for by a PaymentGroup. |
| ProcValidateShippingGroupsForCheckout | This processor validates ShippingGroups before checking an Order out. |
| ProcValidateStoreCredit | Validate a single instance of the StoreCredit payment group at checkout time. |
| ProcVerifyOrderAddresses | This class verifies addresses for ShippingGroups and PaymentGroups. |
| SavedProperties | This abstract class stores a list of properties to be saved for a bean. |
| ShippingAddrValidatorImpl | This class provides a default implementation of ShippingAddrValidator. |
| ValidateCostCenterPipelineArgs | ValidateCostCenterPipelineArgs provides a dictionary for storing arguments to the pipeline processors that validate cost centers, and includes convenience methods for looking up well-known names within that dictionary. |
| ValidatePaymentGroupPipelineArgs | ValidatPaymentGroupPipelineArgs provides a dictionary for storing arguments to the pipeline processors that validate payment groups, and includes convenience methods for looking up well-known names within that dictionary. |
| ValidateShippingGroupPipelineArgs | ValidateShippingGroupPipelineArgs provides a dictionary for storing arguments to the pipeline processors that validate shipping groups, and includes convenience methods for looking up well-known names within that dictionary. |
| ValidationPipelineArgs | ValidationPipelineArgs provides a dictionary for storing arguments to the pipeline processors that validate shipping groups and payment groups, and includes convenience methods for looking up well-known names within that dictionary. |
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 That same coffee can be brewed at home for just 20 cents. This switch could save you hundreds of dollars a year.
Eat more rice, lentils and beans
Potential Money Saved:
Rice, lentils and beans are incredibly inexpensive and good for you. In addition, they pack a lot of fiber and in the case of beans and lentils, a lot of plant protein. Purchasing in bulk can reduce the price of each to under two dollars a pound.
Wait one month before making any non-essential purchases
Potential Money Saved:
Impulse purchases can lead to wasting money on a lot of unnecessary items. To curb money spent on random gadgets, implement a 30 day waiting period for any purchases you make that aren’t essential to living.
 So rather than spending $10 to $20 bucks on a dvd, see if its at your library first.
Cut your cable and your home phone
Potential Money Saved:
Your tv and home phone subscription can be more than a hundred dollars a month. Much of the same features can be achieved with a cell phone and access to the internet.


Join the numbers and get to the 2048 tile!
New GameHow To Play: Use your arrow keys to move the tiles. When two tiles with the same number touch, they merge into one by addition! The goal of the game is to reach the highest number you can before you run out of room, as new tiles (2's and 4's) crop up with every move.
New "God Mode" Feature: Click on one or more empty tiles to add tile values instantly.
This is Lena's clone of a game created by Gabriele Cirulli. Based on 1024 by Veewo Studio and conceptually similar to Threes by Asher Vollmer.


Battery Charge/Discharge
Error loading canvas
Cell Status
State of Charge (SoC):
100%
0
100
Current (C-rate):
1C
-10
10
Positive C-rate is discharge, negative is charge
Voltage:
4.2V


Figure 24 plots the guiding centers orbits for particles launched at the low-ﬁeld-side of the midplane with diﬀerent values of the pitch angle 𝜃.
Figure 24 shows (1) the toroidal procesion of deeply trapped particles is faster than that of the shallowly trapped particles and (2) the direction of the toroidal precession of the particle with 𝜃 = 65∘ is diﬀerent from the others.
Procession angular frequency of a trapped particles (from Porcelli’s slide):
|
| (100) |
where Ek is the kinetic energy of the particle. Equation () indicates that the procession frequency is proportional to the energy of the particle.
|
| (101) |
Compared with the results given by the numerical code, the above results seems to be roughly correct when the orbit is not near the magnetic axis.
|
| (102) |


Brigitte Nielsen's panel show appearances
Brigitte Nielsen (born 1963-07-15[ref]) has appeared in 6 episodes between 2008-2011. Brigitte Nielsen on IMDB. Brigitte Nielsen on Wikipedia.
- 2011-08-08 / Shooting Stars
- 2011-04-28 / Celebrity Juice
- 2010-12-07 / Loose Women
- 2010-09-13 / Loose Women
- 2009-04-22 / Celebrity Juice
- 2008-07-25 / Loose Women


By Saskia | January 16, 2019
In this post I will present the oce package, which can be handy for marine data scientist working with oceanographical data. oce provides lots of functions to
- read oceanographic data,
- process the data specific to the measuring instrument, and
- visualize results following oceanographic conventions (using the base graphics).
The key function for importing data into R is ?read.oce()
, which automatically recognizes the file type. If the recognition does not work, try the individual functions (e.g. read.ctd()
for CTD files, read.odf()
for ODF (Ocean Data Files) files, read.netcdf()
for NetCDF files).
I won’t go into much detail on all the functions provided (for this see the reference manual or ?oce
and then click on index at the bottom of the page). Instead, I will demonstrate you some plots you can create for specific datasets or purposes. The great advantage of this package is that you don’t need to wrangle your data into the typical data frame format for visualization and that it can handle many formats generated by typical oceanographical instruments!
The package also comes with few datasets included, e.g.
ctd
wind
section
(a hydrographic section)adp
(ADP (acoustic-doppler profiler) dataset)echosounder
(a degraded subsample of measurements that were made with a Biosonics scientific echosounder, as part of the St Lawrence Internal Wave Experiment (SLEIWEX) )landsat
(a sample from the landsat satellite dataset)argo
(holds data from the argo float ARGO 6900388 in the North Atlantic; FYI: argo floats are robots that float at different depths in the sea collecting information)lobo
(sample lobo dataset obtained in the Northwest Arm of Halifax by Satlantic; a lobo is a complete turn-key water quality monitoring system that addresses the need for routine, robust, and accurate measurements)lisst
(data from a LISST instruments, which is an in-situ optical laser diffraction instrument to measure particle size and concentration of suspended sediments)
Most other dataset have now been outsourced into the data package ocedata.
Plot CTD data
Lets look first at the CTD data included (CTD stands for Conductivity, Temperature, and Depth) :
library(oce)
data(ctd)
ctd
## ctd object, from file '/Users/kelley/git/oce/create_data/ctd/ctd.cnv', has data as follows.
## scan: 130, 131, ..., 309, 310 (length 181)
## time: 129, 130, ..., 308, 309 (length 181)
## pressure: 1.480, 1.671, ..., 43.903, 44.141 (length 181)
## depth: 1.468, 1.657, ..., 43.542, 43.778 (length 181)
## temperature: 14.225, 14.230, ..., 2.9190, 2.9194 (length 181)
## salinity: 29.921, 29.921, ..., 31.395, 31.393 (length 181)
## flag: 0, 0, ..., 0, 0 (length 181)
summary(ctd)
## CTD Summary
## -----------
##
## * Instrument: SBE 25
## * Temp. serial no.: 1140
## * Cond. serial no.: 832
## * File: "/Users/kelley/git/oce/create_data/ctd/ctd.cnv"
## * Original file: c:\seasoft3\basin\bed0302.hex
## * Start time: 2003-10-15 11:38:38
## * Sample interval: 1 s
## * Cruise: Halifax Harbour
## * Vessel: Divcom3
## * Station: Stn 2
## * Location: 44.684N 63.644W
## * Data
##
## Min. Mean Max. Dim. OriginalName
## scan 130 220 310 181 scan
## pressure [dbar] 1.48 22.885 44.141 181 pr
## depth [m] 1.468 22.698 43.778 181 depS
## temperature [°C, IPTS-68] 2.919 7.5063 14.237 181 t068
## salinity [PSS-78] 29.916 31.219 31.498 181 sal00
## flag 0 0 0 181 flag
##
## * Processing Log
## - 2017-09-09 17:00:27 UTC: `create 'ctd' object`
## - 2017-09-09 17:00:27 UTC: `read.ctd.sbe(file = file, processingLog = processingLog)`
## - 2017-09-09 17:00:27 UTC: `oce.edit(x = ctd, item = "startTime", value = ctd[["systemUploadTime"]], reason = "startTime in file has Y2K error", person = "Dan Kelley")`
This dataset is a CTD profile measured at Halifax Harbour in 2003. The R object is obviously not in a data frame format but if you use an plotting function you don’t need to convert it as you will see next.
When loading the oce package, you can use the generic plot()
function, which automatically recognizes the data type and applies the respective plotting method.
plot(ctd)
The plot method for CTD data automatically generates several panels. If you want to plot only a subset, use the which
argument:
plot(ctd, which = 1)
In the which
argument you can provide a scalar or vector of desired plots. In fact, all plots that the package can produce have a number from 1 to 33, but not all can be generated with the same type of data. If the input data type is CTD, plot number 1,2,3, and 5 are produced (see also ?plot,ctd-method
):
# same as plot(ctd):
plot(ctd, which = c(1,2,3,5))
The following would not make much sense or give an error:
plot(ctd, which=4)
plot(ctd, which=33)
Plot echosounder objects
If you have data from an an echosounder in this format
data(echosounder)
echosounder
## echosounder object, from file '/data/archive/sleiwex/2008/fielddata/2008-07-01/Merlu/Biosonics/20080701_163942.dt4', has data as follows.
## timeSlow: 2008-07-01 16:39:41, 2008-07-01 16:39:42, ..., 2008-07-01 16:42:49, 2008-07-01 16:42:50 (length 190)
## latitudeSlow: 47.879, 47.879, ..., 47.882, 47.882 (length 190)
## longitudeSlow: -69.724, -69.724, ..., -69.729, -69.729 (length 190)
## depth: 39.648, 38.933, ..., 2.4417, 1.7262 (length 54)
## time: 2008-07-01 16:39:41, 2008-07-01 16:39:41, ..., 2008-07-01 16:42:50, 2008-07-01 16:42:50 (length 389)
## latitude: 47.879, 47.879, ..., 47.882, 47.882 (length 389)
## longitude: -69.724, -69.724, ..., -69.729, -69.729 (length 389)
## a, a 389x54 array with value 131.375 at [1,1] position
summary(echosounder)
## Echosounder Summary
## -------------------
##
## * File source: "/data/archive/sleiwex/2008/fielddata/2008-07-01/Merlu/Biosonics/20080701_163942.dt4"
## * Transducer serial #: TX03022C
## * File type: DT4 pre v2.3
## * Beam type: single-beam
## * Channel: 1
## * Measurements: 2008-07-01 16:39:41 UTC to 2008-07-01 16:42:50 UTC
## * Sound speed: 1490.65 m/s
## * Pulse duration: 0.0004 s
## * Frequency:<PHONE_NUMBER>00
## * Blanked samples: 57
## * Pings in file: 780
## * Samples per ping: 3399
## * Time ranges from 2008-07-01 16:39:41 to 2008-07-01 16:42:50 with 190 samples and mean increment 0.9998413 s
## * Data
##
## Min. Mean Max. Dim. OriginalName
## timeSlow 2008-07-01 18:39:41 2008-07-01 18:41:15 2008-07-01 18:42:50 190 -
## latitudeSlow [°N] 47.879 47.881 47.882 190 -
## longitudeSlow [°E] -69.729 -69.726 -69.724 190 -
## depth [m] 1.7262 20.687 39.648 54 -
## latitude [°N] 47.879 47.881 47.882 389 -
## longitude [°E] -69.729 -69.726 -69.724 389 -
## a 11.325 2492.3 364234 389x54 -
##
## * Processing Log
## - 2016-01-10 16:34:14 UTC: `create 'echosounder' object`
## - 2016-01-10 16:34:15 UTC: `read.echosounder(file = file, processingLog = processingLog)`
## - 2016-01-10 16:34:15 UTC: `subset.adp(x, subset=depth < 40)`
## - 2016-01-10 16:34:16 UTC: `decimate(x = echosounder, by = c(2, 40))`
the would generate this plot:
plot(echosounder, which = 2, drawTimeRange = TRUE, drawBottom = TRUE)
Echo sounding is a type of sonar used to determine the depth of water by transmitting sound waves into water. But echo sounding can also refer to hydroacoustic “echo sounders” defined as active sound in water (sonar) used to study e.g. fish (commonly applied in fisheries).
In this plot you clearly see the seafloor, which reflects the signal strongest (hence, the red color). The color scale for the amplitude is log10-transformed and trimmed to zero.
Plot landsat objects
Landsat data can be downloaded from the USGS earthexplorer website. The following is a subset of the Landsat-8 image designated LC80080292014065LGN00, an image from March 2014 that covers Nova Scotia and portions of the Bay of Fundy and the Scotian Shelf:
data(landsat)
landsat
## Landsat object, ID LC80080292014065LGN00
## Data (bands or calculated):
## "aerosol" has dimension c(79,80)
## "blue" has dimension c(79,80)
## "green" has dimension c(79,80)
## "red" has dimension c(79,80)
## "nir" has dimension c(79,80)
## "swir1" has dimension c(79,80)
## "swir2" has dimension c(79,80)
## "panchromatic" has dimension c(158,160)
## "cirrus" has dimension c(79,80)
## "tirs1" has dimension c(79,80)
## "tirs2" has dimension c(79,80)
plot(landsat, band = "temperature")
Using band = "temperature"
will plot an estimate of at-satellite brightness temperature, computed from the tirs1 band. Other band options for the Landsat-8 are "aerosol"
, "blue"
, "green"
, "red"
, "nir"
, "swir1"
, "swir2"
, "panchromatic"
, "cirrus"
, "tirs1"
, or "tirs2"
.
Plot coastline objects
oce provides a coastline dataset downloaded from Natural Earth. This dataset has a coarse resolution with a scale of 1:110M and 10,696 points, making it more suitable for world-scale plots plotted at a small size. If you want coastline files with a finer resolution use the ocedata package.
data(coastlineWorld)
coastlineWorld
## coastline object, from file '/Users/kelley/git/oce/create_data/coastline/ne_110m_admin_0_countries/ne_110m_admin_0_countries.shp', has data as follows.
## longitude: NA, 61.211, ..., 30.323, 29.839 (length 10766)
## latitude: NA, 35.65, ..., -22.272, -22.102 (length 10766)
plot(coastlineWorld)
If you want to create a map using a specific projection provided by the rgdal package, which makes it easy to add more items such as points, lines, contours or text, use the function mapPlot()
from oce. Here I will plot the trajectory of the Cook’s Endeavour cruise (provided in the ocedata package) by adding the mapPoints()
function:
# load the trajectory data
data(endeavour, package = "ocedata")
par(mar = rep(0.5, 4)) # that removes the margin
mapPlot(coastlineWorld, type = 'l', col = 'gray', projection = "+proj=moll")
# to add points use mapPoint()
mapPoints(endeavour$longitude, endeavour$latitude, pch = 20, col = 'red')
You can also add some colors for the topography. The required data is in the dataset topoWorld
:
data(topoWorld)
topo <- decimate(topoWorld, 2) # coarsen grid: 4X faster plot
lon <- topo[["longitude"]]
lat <- topo[["latitude"]]
z <- topo[["z"]]
cm <- colormap(name = "gmt_globe")
drawPalette(colormap = cm)
par(mar = rep(0.5, 4))
mapPlot(coastlineWorld, type = 'l', col = 'gray', projection = "+proj=moll", grid = FALSE)
mapImage(lon, lat, z, colormap = cm)
When zooming into mid-latitude, the Lambert Conformal Conic projection is often used:
par(mar = c(2, 2, 1, 1))
lonlim <- c(-80, 0)
latlim <- c(20, 60)
mapPlot(coastlineWorld, projection = "+proj=lcc +lat_1=30 +lat_2=50 +lon_0=-40",
col = "lightgray", longitudelim = lonlim, latitudelim = latlim)
See the ?mapPlot
documentation on the different projections.
Global sea surface and temperature levels in 2013 from the World Ocean Atlas (WOA)
The ocedata package has a dataset named levitus
, which stores sea-surface temperature (SST) and salinity (SSS) from the 2013 version of the World Ocean Atlas (WOA), commonly referred to as the “Levitus”" atlas (package version 0.1.3):
data(levitus, package = "ocedata")
par(mfrow = c(2,1))
imagep(levitus$longitude, levitus$latitude, levitus$SST, col = oceColorsJet, zlim = c(-2, 30))
imagep(levitus$longitude, levitus$latitude, levitus$SSS, col = oceColorsJet, zlim = c(20, 40))
More infos
For more information on the different plotting settings see the general plot help by typing one of the different plot methods, e.g. ?plot,ctd-method
. Since the oce plot function produces various different type of plots, it is a bit tricky though to figure out which arguments are useful for which type of plot.
If you want to learn more about the package, I highly recommend the oce vignette and the github documentation page: https://cran.r-project.org/web/packages/oce/vignettes/oce.html. Dan Kelly, the author of the package, also wrote the book Oceanographic Analysis with R where the package is described in great detail.


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Constructor
new InstructionPointer(x, y, direction, program)
Creates a new instruction pointer
Parameters:
| Name | Type | Description |
|---|---|---|
x |
Integer | X coordinate to start at |
y |
Integer | Y coordinate to start at |
direction |
String | Direction to start with |
program |
FishProgram | The program this pointer is for |
- Source:
Members
(static, constant) DIRECTION_EAST :String
Constant for the East direction
Type:
- String
- Source:
(static, constant) DIRECTION_NORTH :String
Constant for the North direction
Type:
- String
- Source:
(static, constant) DIRECTION_SOUTH :String
Constant for the South direction
Type:
- String
- Source:
(static, constant) DIRECTION_WEST :String
Constant for the West direction
Type:
- String
- Source:
(readonly) direction :String
Current direction of the pointer. One of the DIRECTION_* constants
Type:
- String
- Source:
(readonly) x :Integer
Current X coordinate of the pointer
Type:
- Integer
- Source:
(readonly) y :Integer
Current Y coordinate of the pointer
Type:
- Integer
- Source:
Methods
advance()
Advances the pointer one step forward
- Source:
Throws:
-
If the direction is for some reason invalid
- Type
- Error
changeDirection(newDirection)
Changes the direction of the pointer
Parameters:
| Name | Type | Description |
|---|---|---|
newDirection |
String | The new direction of the pointer. One of the DIRECTION_* constants |
- Source:
Throws:
-
If the new direction is invalid
- Type
- Error
teleport()
Teleports the pointer to a new set of coordinates
- Source:
Throws:
-
If the coordinates are outside the program, or invalid
- Type
- Error


Class CalendarArrowView.
More...
|
| override void | OnSizeChanged (int w, int h, int oldw, int oldh) |
| | This is called during layout when the size of this view has changed. More...
|
| |
| override void | OnDraw (Canvas canvas) |
| | Implement this to do your drawing. More...
|
| |
Enum ArrowDirection
| Enumerator |
|---|
| RIGHT |
The right
|
| LEFT |
The left
|
| XLabs.Forms.Controls.MonoDroid.TimesSquare.CalendarArrowView.CalendarArrowView |
( |
Context |
context | ) |
|
| XLabs.Forms.Controls.MonoDroid.TimesSquare.CalendarArrowView.CalendarArrowView |
( |
Context |
context, |
|
|
IAttributeSet |
attrSet |
|
) |
| |
Initializes a new instance of the CalendarArrowView class.
- Parameters
-
| context | The context. |
| attrSet | The attribute set. |
| XLabs.Forms.Controls.MonoDroid.TimesSquare.CalendarArrowView.CalendarArrowView |
( |
IntPtr |
javaReference, |
|
|
Android.Runtime.JniHandleOwnership |
handleown |
|
) |
| |
Initializes a new instance of the CalendarArrowView class.
- Parameters
-
| javaReference | The java reference. |
| handleown | The handleown. |
| override void XLabs.Forms.Controls.MonoDroid.TimesSquare.CalendarArrowView.OnDraw |
( |
Canvas |
canvas | ) |
|
|
protected |
Implement this to do your drawing.
- Parameters
-
| canvas | the canvas on which the background will be drawn |
<since version="Added in API level 1">
Implement this to do your drawing.
<format type="text/html"> [Android Documentation] </format>
| override void XLabs.Forms.Controls.MonoDroid.TimesSquare.CalendarArrowView.OnSizeChanged |
( |
int |
w, |
|
|
int |
h, |
|
|
int |
oldw, |
|
|
int |
oldh |
|
) |
| |
|
protected |
This is called during layout when the size of this view has changed.
- Parameters
-
| w | Current width of this view. |
| h | Current height of this view. |
| oldw | Old width of this view. |
| oldh | Old height of this view. |
<since version="Added in API level 1">
This is called during layout when the size of this view has changed. If you were just added to the view hierarchy, you're called with the old values of 0.
<format type="text/html"> [Android Documentation] </format>
| Android.Graphics.Color XLabs.Forms.Controls.MonoDroid.TimesSquare.CalendarArrowView.Color |
|
set |
Sets the color.
The color.
| ArrowDirection XLabs.Forms.Controls.MonoDroid.TimesSquare.CalendarArrowView.Direction |
|
getset |
Gets or sets the direction.
The direction.
The documentation for this class was generated from the following file:
- F:/Projects/Xamarin-Forms-Labs/src/Forms/XLabs.Forms.Droid/Controls/Calendar/MonoDroid.TimesSquare/CalendarArrowView.cs


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nips nips2004 nips2004-50 nips2004-50-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Phillip Boyle, Marcus Frean
Abstract: Gaussian processes are usually parameterised in terms of their covariance functions. However, this makes it difﬁcult to deal with multiple outputs, because ensuring that the covariance matrix is positive deﬁnite is problematic. An alternative formulation is to treat Gaussian processes as white noise sources convolved with smoothing kernels, and to parameterise the kernel instead. Using this, we extend Gaussian processes to handle multiple, coupled outputs. 1
[1] A BRAHAMSEN , P. A review of gaussian random ﬁelds and correlation functions. Tech. Rep. 917, Norwegian Computing Center, Box 114, Blindern, N-0314 Oslo, Norway, 1997.
[2] B OYLE , P., AND F REAN , M. Multiple-output gaussian process regression. Tech. rep., Victoria University of Wellington, 2004.
[3] C RESSIE , N. Statistics for Spatial Data. Wiley, 1993.
[4] G IBBS , M. Bayesian Gaussian Processes for Classiﬁcation and Regression. PhD thesis, University of Cambridge, Cambridge, U.K., 1997.
[5] G IBBS , M., AND M AC K AY, D. J. Efﬁcient implementation of gaussian processes. www.inference.phy.cam.ac.uk/mackay/abstracts/gpros.html, 1996.
[6] G IBBS , M. N., AND M AC K AY, D. J. Variational gaussian process classiﬁers. IEEE Trans. on Neural Networks 11, 6 (2000), 1458–1464.
[7] H IGDON , D. Space and space-time modelling using process convolutions. In Quantitative methods for current environmental issues (2002), C. Anderson, V. Barnett, P. Chatwin, and A. El-Shaarawi, Eds., Springer Verlag, pp. 37–56.
[8] M AC K AY, D. J. Gaussian processes: A replacement for supervised neural networks? NIPS97 Tutorial, 1997. In
[9] M AC K AY, D. J. Information theory, inference, and learning algorithms. Cambridge University Press, 2003.
[10] N EAL , R. Probabilistic inference using markov chain monte carlo methods. Tech. Report CRG-TR-93-1, Dept. of Computer Science, Univ. of Toronto, 1993.
[11] N EAL , R. Monte carlo implementation of gaussian process models for bayesian regression and classiﬁcation. Tech. Rep. CRG-TR-97-2, Dept. of Computer Science, Univ. of Toronto, 1997.
[12] PACIOREK , C. Nonstationary Gaussian processes for regression and spatial modelling. PhD thesis, Carnegie Mellon University, Pittsburgh, Pennsylvania, U.S.A., 2003.
[13] PACIOREK , C., AND S CHERVISH , M. Nonstationary covariance functions for gaussian process regression. Submitted to NIPS, 2004.
[14] R ASMUSSEN , C., AND K USS , M. Gaussian processes in reinforcement learning. In Advances in Neural Information Processing Systems (2004), vol. 16.
[15] R ASMUSSEN , C. E. Evaluation of Gaussian Processes and other methods for Non-Linear Regression. PhD thesis, Graduate Department of Computer Science, University of Toronto, 1996.
[16] T IPPING , M. E., AND B ISHOP, C. M. Bayesian image super-resolution. In Advances in Neural Information Processing Systems (2002), S. Becker S., Thrun and K. Obermayer, Eds., vol. 15, pp. 1303 – 1310.
[17] W ILLIAMS , C. K., AND BARBER , D. Bayesian classiﬁcation with gaussian processes. IEEE trans. Pattern Analysis and Machine Intelligence 20, 12 (1998), 1342 – 1351.
[18] W ILLIAMS , C. K., AND R ASMUSSEN , C. E. Gaussian processes for regression. In Advances in Neural Information Processing Systems (1996), D. Touretzsky, M. Mozer, and M. Hasselmo, Eds., vol. 8.


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