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{% extends "base.html" %} {% block content %}
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Take heart that you were guided here to find out about the 999 meaning. Seeing repetitive triple numbers, such as 999, is by no means a coincidence. In fact, behind every number pattern that you see regularly, there is a hidden angel message for you from the Universe.
If y...


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MSGMERGE
Section: GNU (1)Updated: November 2007
Index Return to Main Contents
NAME
msgmerge - merge message catalog and templateSYNOPSIS
msgmerge [OPTION] def.po ref.potDESCRIPTION
Merges two Uniforum style .po files together. The def.po file is an existing PO file with translations which will be taken over to the newly created file as long as they still match; comments will be preserved, but extracted comments and file positions will be discarded. The ref.pot file is the last created PO file with up-to-date source references but old translations, or a PO Template file (generally created by xgettext); any translations or comments in the file will be discarded, however dot comments and file positions will be preserved. Where an exact match cannot be found, fuzzy matching is used to produce better results.
Mandatory arguments to long options are mandatory for short options too.
Input file location:
- def.po
- translations referring to old sources
- ref.pot
- references to new sources
- -D, --directory=DIRECTORY
- add DIRECTORY to list for input files search
- -C, --compendium=FILE
- additional library of message translations, may be specified more than once
Operation mode:
- -U, --update
- update def.po, do nothing if def.po already up to date
Output file location:
- -o, --output-file=FILE
- write output to specified file
The results are written to standard output if no output file is specified or if it is -.
Output file location in update mode: The result is written back to def.po.
- --backup=CONTROL
- make a backup of def.po
- --suffix=SUFFIX
- override the usual backup suffix
The version control method may be selected via the --backup option or through the VERSION_CONTROL environment variable. Here are the values:
- none, off
- never make backups (even if --backup is given)
- numbered, t
- make numbered backups
- existing, nil
- numbered if numbered backups exist, simple otherwise
- simple, never
- always make simple backups
The backup suffix is `~', unless set with --suffix or the SIMPLE_BACKUP_SUFFIX environment variable.
Operation modifiers:
- -m, --multi-domain
- apply ref.pot to each of the domains in def.po
- -N, --no-fuzzy-matching
- do not use fuzzy matching
- --previous
- keep previous msgids of translated messages
Input file syntax:
- -P, --properties-input
- input files are in Java .properties syntax
- --stringtable-input
- input files are in NeXTstep/GNUstep .strings syntax
Output details:
- -e, --no-escape
- do not use C escapes in output (default)
- -E, --escape
- use C escapes in output, no extended chars
- --force-po
- write PO file even if empty
- -i, --indent
- indented output style
- --no-location
- suppress '#: filename:line' lines
- --add-location
- preserve '#: filename:line' lines (default)
- --strict
- strict Uniforum output style
- -p, --properties-output
- write out a Java .properties file
- --stringtable-output
- write out a NeXTstep/GNUstep .strings file
- -w, --width=NUMBER
- set output page width
- --no-wrap
- do not break long message lines, longer than the output page width, into several lines
- -s, --sort-output
- generate sorted output
- -F, --sort-by-file
- sort output by file location
Informative output:
- -h, --help
- display this help and exit
- -V, --version
- output version information and exit
- -v, --verbose
- increase verbosity level
- -q, --quiet, --silent
- suppress progress indicators
AUTHOR
Written by Peter Miller.REPORTING BUGS
Report bugs to<EMAIL_ADDRESS>Copyright © 1995-1998, 2000-2007 Free Software Foundation, Inc. License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>This is free software: you are free to change and redistribute it. There is NO WARRANTY, to the extent permitted by law.
SEE ALSO
The full documentation for msgmerge is maintained as a Texinfo manual. If the info and msgmerge programs are properly installed at your site, the command- info msgmerge
should give you access to the complete manual.
Index
This document was created by man2html, using the manual pages.
Time: 05:29:06 GMT, December 24, 2015


Businesses still have existing obligations to meet, despite the reduction in sales caused by COVID-19. Although not an ideal solution, it is recommended that small businesses take low-interest loans from the US Small Business Administration in order to cover obligations for the next few months until the economic consequence of COVID-19 is lessened.
The federal government has deferred federal income tax payments for entities other than C-Corporations until June 15th, 2020. This does not mean that taxes are to be filed by June 15th -- April 15th, 2020 remains the filing deadline for tax returns.
For C-Corporations, income tax payment deadlines are being automatically extended until July 15th, 2020, for up to $10 million of their 2019 tax due.
It is important to reach out to lenders and other entities to which your business has a financial obligation in order to see if payment structures can be reworked.


ReddCoin Secure QR
Based on
jQuery.qrcode
RENDER MODE
Canvas
Image
DIV
SIZE:
FILL
BACKGROUND
QR-CONTENT
Your address or API-key here :)
LABEL
MIN VERSION:
ERROR CORRECTION LEVEL
L - Low (7%)
M - Medium (15%)
Q - Quartile (25%)
H - High (30%)
QUIET ZONE:
CORNER RADIUS (not in Opera):
DOWNLOAD
Switch to advanced mode
MODE
0 - Normal
1 - Label-Strip
2 - Label-Box
3 - Image-Strip
4 - Image-Box
SIZE:
POS X:
POS Y:
FONT NAME
FONT COLOR:
IMAGE


| ncatt_get {pbdNCDF4} | R Documentation |
Reads an attribute from a netCDF file.
ncatt_get( nc, varid, attname=NA, verbose=FALSE )
nc |
An object of class |
varid |
The variable whose attribute is to be read. Can be a
character string with the variable's name or an object of class |
attname |
Name of the attribute to read; if not specified, a list containg ALL attributes of the selected variable or file is returned. |
verbose |
If TRUE, then debugging information is printed. |
This function gets an attribute from a netCDF variable (or a global attribute from a netCDF file, if the passed argument "varid" is zero). Multiple attributes are returned in a vector.
If an attribute name is supplied (i.e., argument attname is given), this returns a list with two components, "hasatt" and "value". "hasatt" is TRUE if the named attribute was found, and FALSE otherwise. "value" is the (possibly vector) value of the attribute. If the on-disk type of the attribute is short or integer, then an integer value is returned. If the on-disk type is float or double, than a double value is returned. If the on-disk type is character, than a character string is returned.
If no attribute name is supplied, then this returns a list containing ALL the attributes for the specified variable along with their associated values. For example, if attlist is the list returned by this call, then names(attlist) shows all the attributes defined for the variable, and attlist[[N]] is the value of the N'th attribute.
David W. Pierce<EMAIL_ADDRESS>http://dwpierce.com/software
## Not run: # Make a simple netCDF file filename <- "atttest_types.nc" dim <- ncdim_def( "X", "inches", 1:12 ) var <- ncvar_def( "Data", "unitless", dim, -1 ) ncnew <- nc_create( filename, var ) # Define some attributes of various types attvaldbl <- 3.1415926536 ncatt_put( ncnew, var, "testatt_dbl", attvaldbl, prec="double" ) attvalfloat <- c(1.0,4.0,9.0,16.0) ncatt_put( ncnew, var, "testatt_float", attvalfloat ) # varid=0 means it is a global attribute ncatt_put( ncnew, 0, "globalatt_int", 32000, prec="int" ) ncatt_put( ncnew, 0, "globalatt_short", 7, prec="short" ) ncatt_put( ncnew, 0, "description", "this is a test file with attributes of various types") nc_close(ncnew) # Now illustrate the use of the ncatt_get function by reading them back in doitfor <- function( nc, var, attname ) { av <- ncatt_get( nc, var, attname ) if( av$hasatt ) { print(paste("File",nc$filename,", var",var,"DOES have attribute", attname)) print(paste("Storage mode:",storage.mode(av$value))) print("Attribute value:") print(av$value) } else { print(paste("File",nc$filename,", var",var,"does NOT have", "attribute", attname)) } } nc <- nc_open( filename ) var <- "Data" doitfor( nc, var, "testatt_dbl" ) doitfor( nc, var, "testatt_float" ) doitfor( nc, var, "testatt_wacko" ) doitfor( nc, 0, "globalatt_int" ) doitfor( nc, 0, "globalatt_short" ) doitfor( nc, 0, "description" ) ## End(Not run)


Install nginx and passenger
I have just reinstalled and reconfigured nginx and passenger to run multiple
hosts. There is a lot of material about this argument, thus, I will write here
what are the requirement to run nginx and passenger with virtual hosts(and like
often happens with rails, what to do if every app has his own gemset, with his own ruby
version, that need to be managed with RVM).
Nginx is a web server created by IgorSysoev to address the C10K
problem. It is known for his simple configuration, performance and low
resources consumption. If you come from apache (like me) I suggest you to read this
article linked in the nginx wiki
.There is no need to install nginx from apt repository, to work with passenger, nginx required to be compiled with the passenger module.You can download the source and compile it by yourself, or you install it through passenger gem. I choose the second one
gem install passenger
rvmsudo passenger-install-nginx-module
Now download a bash script that allow you to manage nginx like every service in /etc/init.d
wget -O init-deb.sh http://library.linode.com/assets/660-init-deb.sh
sudo mv init-deb.sh /etc/init.d/nginx
sudo chmod +x /etc/init.d/nginx
sudo /usr/sbin/update-rc.d -f nginx defaults
RVM and passenger
Now, if you open your browser you will the "Welcome to nginx message". It is true, nginx is installed.Let's have a look at the configuration file. At the top of the file, under http, you will see something like this:
passenger_root /home/da/.rvm/gems/ruby-1.9.3-p194/gems/passenger-3.0.17;
passenger_ruby /home/da/.rvm/wrappers/ruby-1.9.3-p194/ruby;
The passenger gem is installed in the 1.9.3-p194 gemset. If we run a ruby application with this ruby version, there is no problem. Just instruct rvm about wich ruby use and create a .rvmrc file for the application, called "pigliala".
rvm use 1.9.3-p194@pigliala --rvmrc --create
Now,if you are installing a ruby on rails application, create a config/setub_load_path.rb file as described here,
if ENV['MY_RUBY_HOME'] && ENV['MY_RUBY_HOME'].include?('rvm')
begin
gems_path = ENV['MY_RUBY_HOME'].split(/@/)[0].sub(/rubies/,'gems')
ENV['GEM_PATH'] = "#{gems_path}:#{gems_path}@global"
require 'rvm'
RVM.use_from_path! File.dirname(File.dirname(__FILE__))
rescue LoadError
raise "RVM gem is currently unavailable."
end
end
# If you're not using Bundler at all, remove lines bellow
ENV['BUNDLE_GEMFILE'] = File.expand_path('../Gemfile', File.dirname(__FILE__))
require 'bundler/setup'
Also a new server block in the nginx.conf file must the setted. Open the file, if you have followed the default installation, it would be here /opt/nginx/conf/nginx.conf. Add this line:
server {
listen 80;
server_name pigliala;
root /home/da/public_html/pigliala/public;
passenger_enabled on;
}
Add an entry called "pigliala" in your /etc/hosts file, restart nginx and open the browser at http://pigliala. You will see your app.
In my installation there was an error,
"git://github.com/thoughtbot/paperclip.git (at master) is not checked out. Please run `bundle install` (Bundler::GitError)".
The solution is described ihere.You can pack your gem in vendor, or set an appropriate BUNDLE_PATH. I need to move in production as soon as possible, so i hve opted for the first solution.
Virtual host
The term "Virtual host" is wrong, is an apache word, in nginx they are called simply "server block". What happens if we have an application called "girala" that use a ruby 1.8.7 version and a specific gemset? Passenger is installed in
ruby 1.9.3, it could not work. We have to use a reverse proxy to solve this
problem. Move in your app folder and delcare the gemset and install passenger.
rvm use 1.8.7@girala --rvmrc --create
gem install passenger
Now we create a unix socket waiting for our app.
passenger start --socket /tmp/girala.socket -d
This comand will also install and compile a passanger standalone version. But we need to tell nginx that this socket is available. Open the nginx.conf file and add the new server block entry and the entry for our reverse proxy
upstream girala_upstream {
server unix:/tmp/girala.socket;
}
server {
listen 80;
server_name girala;
root /home/da/public_html/girala/public;
location / {
proxy_pass http://girala_upstream;
proxy_set_header Host $host;
}
}
Finish. We can now access both applications.
Useful links:
http://blog.phusion.nl/2010/09/21/phusion-passenger-running-multiple-ruby-versions/
http://shapeshed.com/installing-passenger-3-with-rvm-and-nginx-on-osx/
http://blog.martinfjordvald.com/2010/07/nginx-primer/
http://wiki.nginx.org/Pitfalls


Puzzlebot Corner - Brandon Tan
{% include 'frameworks.html' %}
{% include 'siteHead.html' %}
What's New?
{{ frontPageBody }}
Read this: XKCD by Randall Monroe
XKCD is a humorous webcomic featuring slice-of-life situations from various fields of science and engineering, written by a man who seems to know way too much. Give it a read!


@(crewMembers : String, deadCrewman : String, kittenImg : String, crew : Array[String])
This way is not looking very promising. You keep going in and out of bays trying to find a way east but you always run into land. You are afraid you may run aground and be eaten by one of the roving bands of feral kittens you see frolicking upon the shore.
@member
}


Chapter 3 Descriptive statistics
- Choose appropriate summary statistics (tables, graphics, parameters) to describe a population or a sample
- Interpret summary statistics
3.1 Frequency table
One type of data statistical summary are frequency table
, or contingency table
.
To summarize a qualitative
variable, the frequency of the statistical units in each modality (category) of the variable is computed. The frequency can be reported as absolute count (absolute frequency) or proportion (relative frequency or count). For instance, in Table 3.1 the partition of students according to the school status is summarized (HBSC dataset).
| Count | Proportion (%) | |
|---|---|---|
| private | 115 | 23 |
| public | 385 | 77 |
| Total | 500 | 100 |
In rows are the modalities (categories) of the variable “school status” in the original database and in columns are the frequency of students in each category. The first column is the absolute frequency
or count and the second column is the relative frequency
or proportion out of the total of students. The margin total
is essential to display for quick assessment of potential mistake or missing values.
To summarize a quantitative
variable into a contingency table, the numerical values first need to be grouped into classes, generating in fact like a categorical variable. Next, the frequency of the statistical units in each group (class) of the new variable is counted.
In Table 3.2, first the quantitative variable age was used to create age groups and, next, the partition of students according to age group was summarized.
| Count | Proportion (%) | |
|---|---|---|
| NA | 1 | 0.2 |
| [11-13[ | 173 | 34.6 |
| [13-15[ | 178 | 35.6 |
| [15-17[ | 148 | 29.6 |
| Total | 500 | 100.0 |
One must read [11-13[
as 11 years-old students being included (counted) in that group while 13 years-old students being excluded. NA
stands for Not Attributed or missing values.
When summarizing two (or more) variables in two-way (or more) table using frequencies via a statistical software you might have to look for the term pivot table
. Table 3.3 summarize in absolute frequencies the different age groups and the smoking status. For relative frequencies, you need to decide which way to count (Table 3.4 and 3.5). You need to ask yourself: Who are you interested in? What is your denominator?
| No | Yes | Total | |
|---|---|---|---|
| NA | 1 | 0 | 1 |
| [11-13[ | 166 | 6 | 172 |
| [13-15[ | 161 | 17 | 178 |
| [15-17[ | 104 | 44 | 148 |
| Total | 432 | 67 | 499 |
| No | Yes | Total | |
|---|---|---|---|
| NA | 100.00 | 0.00 | 100 |
| [11-13[ | 96.51 | 3.49 | 100 |
| [13-15[ | 90.45 | 9.55 | 100 |
| [15-17[ | 70.27 | 29.73 | 100 |
Among the [15-17[ years old, 29.7% smoke.
| No | Yes | |
|---|---|---|
| NA | 0.23 | 0.00 |
| [11-13[ | 38.43 | 8.96 |
| [13-15[ | 37.27 | 25.37 |
| [15-17[ | 24.07 | 65.67 |
| Total | 100.00 | 100.00 |
Among the smokers, 65% are aged [15-17[ years old.
The proportion of smoker seems to increase with age. We will verify this later using inferential statistics (see Chapter 5)
3.2 Central parameters
A central parameter, or location parameter, is the numerical value around which are distributed most of the values of a serie of data.
3.2.1 Mean
The (arithmetic) mean is the most well known and commonly (but not always appropriately) used central parameter.
The arithmetic mean is the sum of the values divided by the number of values in the data serie.
Mathematically, in a population the equation is:
\(\mu = ({\sum^{{i=N}}_{{i=1}} X_{i})/N}\)
In a sample, the equation is:
\(m = ({\sum^{{i=n}}_{{i=1}} x_{i})/n}\)
Note: Greek letters are used for population and Roman letters for sample. The mean is also sometimes symbolized like \(\bar{X}\) for population or \(\bar{x}\) for sample
Figure 3.1 presents a histogram
that summarize the distribution of weight of French student in the HBSC sample
(for histogram definition see section 3.4 and sample definition see 4.1). From the graphic, the central point (pick) of the distribution, around which values of the data serie are spread is around the weight class [40-45[ Kg.
On average, in 2006 the French students aged 11 to 16 weighted 48 Kg (dashed red color).
Why the mean is not between 40 and 45Kg?
The advantages:
- Easy to understand
- Easy to compute
The drawbacks:
- Sensitive to outlier: each value of the data serie count with the same weight
- Sensitive to the distribution shape
3.2.2 Median
The mean is not always the appropriate statistical indicator to summarize the distribution data and should be sometimes replaced by the median.
The median is the middle value of a ordered data serie. The median split the data serie in two part of equal number of data.
In Figure 3.2, 50% of the statistical units, i.e 142 children hair sample, have mercury concentration below 1.8 \(\mu g/g\) while 50%, i.e 142 children hair sample, have mercury concentration above 1.8 \(\mu g/g\).
If you had rely on the mean you would have said that on average children hair contain 4 \(\mu g/g\) of mercury which wrongly make you believe that represent most of the children case.
How to compute a median?
- Sort values in increasing order
- If there are an odd number of observations, find the middle value
- 2’. If there are an even number of observations, find the middle two values and average them
Would you use the median or the mean to compare French region rainfall?
The advantages:
- Easy to compute
- Not sensitive to outlier
- Less sensitive to skewed distribution than the mean
- Easy to understand
The drawbacks:
- Sensitive to the distribution shape
- No idea of the minimum and maximum
- Easy to understand but need to be explicitly exposed
3.2.3 Percentile and quantile
When looking at height distribution, the median is the exact middle value when people are ordered by height which correspond to the 50\(^{th}\) percentile
or 50% below and above that value (Figure 3.3). But you could pick any percentile like the 80\(^{th}\) with 80% below and 20% above.
The n\(^{th}\) percentile of a set of data is the value at which n percent of the data is below it.
Percentiles can be calculated using the formula \(n = (P/100)*N\), where P = percentile, N = number of values in a data set (sorted from smallest to largest), and n = ordinal rank of a given value.
A student scores in the 75\(^{th}\) percentile of his class. What does that mean?
The 75\(^{th}\) percentile is also the 3rd quartile
.
The quartile split the sorted data values into quarters.
The quartiles are the values that frame the middle 50% of the data (median or Q2). One quarter of the data lies below the lower quartile, Q1 (25% or 25\(^{th}\) percentile), and one quarter of the data lies above the upper quartile, Q3 (75% or 75\(^{th}\) percentile).
Using the R statistical software and the HBSC data set we can quickly describe the “Weight” variable of the French student aged 11 to 16 in 2006 with the five-number summary
. The five-number summary provides a good overall look at the distribution of the data.
summary(hbsc$Weight)
## Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
## 24.50 38.83 47.00 48.09 56.00 90.00 18
- There was 18 missing values (NA)
- The minimum weight was 24.5 Kg
- The maximum weight was 90 Kg
- The mean (average) is 48.09 Kg
- The median is 47 Kg meaning that 50% of the students weighted less than 47Kg and 50% of the students are heavier.
- The 1\(^{st}\) quartile is 38.8Kg meaning that 25% of the students weighted less than 38.8Kg and 75% weighted more.
- The 3\(^{rd}\) quartile is 56Kg meaning that 75% of the students weighted less than 56Kg and 25% weighted more.
Quantile algorithms
Several algorithms exit to compute quantile (for instance see ?quantile in the R staistical software). They rely on different definitions of the underlying distribution of the sample: discontinuous or continuous.
In your case no needs to go into the details but you should know how to interpret the values.
Mean versus Median
If the data is normally distributed, i.e. bell shape, as statisticians like it (bottom of Figure 3.5), feel free to use the mean.he mean is easier to communicate and so if you can use it, use it. In fact the value of the mean should be really close the value of the median and the mode (or modal class).
If your data is skewed (top of Figure 3.5), or there are large outliers, then use the median to find the centre of the data. Better yet, report both the mean and the median since any differences will reveal information about the presence of skew/outliers.
A more subtle rule: if you are more concerned with the total sum, rather than the typical value, use the mean. For instance, if you have a salary cap and you are interested in the average salary of your players, use the mean. In this case, the mean is biased towards the high earners, and you really care about the high earners because they are the ones who are eating up your salary cap.
3.2.4 Mode
The most frequent value or modality
It is the only statistical parameter for the qualitative
variables.
| Sports frequency | Number |
|---|---|
| NA | 0 |
| never | 33 |
| less than once a month | 30 |
| once a month | 21 |
| 2 or 3 times a week | 175 |
| 4 to 6 times a week | 81 |
| every day | 63 |
In table 3.6 the mode is the category “2 or 3 times a week” with 175 students out of 500 practicing that much sports.
For quantitative
variables it could be a number or a class interval as in Figure 3.1 where the modal class is [40-45[Kg.
Likert scale data.
A Likert Scale is a type of rating scale used to measure attitudes or opinions. Five to seven items are usually used in the scale.
In a survey with a 1-5 scale of “1-Very bad,” “2-Bad,” “3-Neutral,” “4-Good” and “5-Very Good” categories, the mean result across many participants came out to be 3.5. But what does 3.5 even mean in this context? Half way between Neutral and Good : Neutood? In terms of best practice, use the median when describing the centre of Likert data. Some may even argue for only using the mode on Likert data.
3.3 Variation parameters
A variation parameter is numerical value which describes the dispersion of all the values of a serie of data around its location parameter
3.3.1 Range and IQR
The range
is the difference between the minimum and maximum value of a data serie. It is better to report the boundaries rather then the output of the difference because otherwise we do not know from where it starts.
In which hospital will you go for emergency care?
The interquartile range (IQR)
summarizes the spread by focusing on the middle half of the data. It is defined as the difference between the two quartiles: \(IQR = Q3 - Q1\). As the range, the IQR should be reported as an interval. For example, the five-number summary above on HBSC weight data show us that IQR is [38.8-56] Kg.
3.3.2 Variance and standard deviation
A powerful measure of spread is the distance of the values of a data serie to its mean.
The variance is the average squared differences to the mean.
Based on the mean, the variance
is appropriate only for symmetric data and can be influenced by outlying observations.
Mathematically, if we tried to average the distances of all the values a data serie to its mean, the positive and negative differences would cancel each other out, giving an average deviation of 0-not very useful. Instead, we square each distance to get the variance
.
\(\sigma^2=\frac{\sum_{1}^{N}(X_i-\bar{X})^2}{N}\)
where
- \(\sigma^2\) is the variance of population
- \(X_i\) is the \(i^{th}\) value in the population
- \(\bar{X}\) is the mean in the population
- \(N\) is the size of the population
In a sample, the formula is:
\(s^2=\frac{\sum_{1}^{n}(x_i-\bar{x})^2}{(n-1)}\)
where
- \(s^2\) is the variance of the sample
- \(x_i\) is the \(i^{th}\) value of the data serie
- \(\bar{x}\) is the mean of the data serie
- \(n\) is number of values in the data serie
The variance plays an important role in statistics, but as a measure of spread, it has a problem. Whatever the units of the original data, the variance is in squared units. To express the spread to in the same units as the data we take the square root of the variance. That gives the standard deviation
.
A standard deviation is the square root of the variance, the average differences to the mean.
Mathematically, in a sample the formula is:
\(s=\sqrt\frac{\sum_{1}^{n}(x_i-\bar{x})^2}{(n-1)}\)
In the HBSC sample, one average pupils weight 48.09 Kg +/- 12.25Kg. It means that the average variation of the weights around the mean is of 12.25Kg. However some pupils can be lighter than 35.75kg (48-12.25 - the minimum is in fact 24.5Kg) and some pupils can be heavier than 60.25kg (48+12.25 the minimum is in fact 90Kg).
3.4 Graphical summary
Graphical representations, as summary in tables, must be self-content and self-explanatory. They should be readable without text around.
Plot title should include the W’s
Who are you representing, What characteristics, Where and When it is happening.
Note: I will be intransigent on that matter
3.4.1 Barplot
For one qualitative
variable, the frequency barplot
, or barchart
, is the most appropriate plot. It could use the absolute or relative frequencies.
Figure 3.7 represents the distribution of students (Who) according to their sport activity level (What), in France (Where) in 2006 (When) and if available the source should also be cited (here HSBC) in the caption.
It is a better practice to multiply plots that combining too many information in one plot. Imagine you would like to display the same information but for boys and girls. The below barplot is better than the next one as you can easily compare boys and girl but you also easily visualize the trend within each group.
3.4.2 Pie chart
For one qualitative
variable, you can also use a pie chart
. However you should be careful on the number of modalities the variable to display can have: too few, the plot take lots of room for few information but too many you will rapidly get “the wheel of fortune.”
My advice would be to avoid using that plot but if you absolutely need to use it do not forget to display number and/or % in the sectors of the plot so reader do not have to do the math.
3.4.3 Histogram
For one quantitative
variable, the histogram
is often used to visualize the shape of the distibution of the data serie. Although one have to be careful of the bin width (breaks) use to group the numerical values.
Figures 3.11 and 3.12 present the same data serie but with a bin width of 1 and then 10. The shape of the plots are different, the modal class varies. With a bin width of 1 you have no summary and too many details while a bin width of 10 may be compact.
There is no recipe, statistical software helps you with default algorithm but my advice would be to try a couple of bin widths and select the one you believe summarize the best the data
Barplot versus Histogram
Barplot are for qualitative
data. The bars are separated.
Histogram are for quantitative
data. The bins are joined. Gaps may occurred when no one fall in a particular bin.
If you want to compare the distribution of one quantitative variable between more than 2 groups (qualitative)
the histogram remain interesting, as shown below. But up to three the comparison start to be difficult. A boxplot is then more appropriate.
3.4.4 Boxplot
A boxplot helps presenting the five-number summary classically used to describe a sample.
The central box shows the middle half of the data, between the quartiles. The top of the box is at the third quartile (Q3) and the bottom is at Q1, the height of the box is equal to which is the IQR. The median is displayed as a horizontal line. If the median is roughly centered between the quartiles, then the middle half of the data is roughly symmetric. If it is not centered, the distribution is skewed. In extreme cases, the median can coincide with one of the quartiles.
The whiskers reach out from the box to the most extreme values that are not considered outliers according to John W. Tukey’s rule. The boxplot nominates points as outliers if they fall farther than 1.5*IQRs beyond either quartile. They may be mistakes or they may be the most interesting cases in your data. This rule is not a definition of what makes a point an outlier. It just nominates cases for special attention.
In Figure 3.15 the distribution of students’ weight vary by group of sport activity level. We note 3 extrema: 2 in the “2 or 3 times a week” group and 1 in the “once a month” group. Overall the boxplots overlap suggesting than on average the weights between groups might not be statistically different (see Chapter 5).
Let’s interpret the “never” group (bottom boxplot): around 50% of the students in that group weight 45Kg or less, 75% of the students weight 55Kg or less while 25% weight 55Kg or more
What proportion of students lies between 42 and 55 Kg?
3.4.5 Scatterplot
For two quantitative
variables, a scatterplot is used to assess if there is a relationship between the two variables.
Figure 3.16 displays the school results and BMI among students in France in 2006. It appears that there is no linear relationship between the two variables (see Chapter 5 and 6.1).
3.4.6 Communication tips
Avoid 3D plots our eyes are not good at visualizing 3D and mathematically it’s often wrong you do not manipulate volumes but numbers.
Use appropriate colors
- Proscribe rainbow plots
- Sequential scale (gradiant) are suited to ordered data
- Diverging palettes put equal emphasis on mid-range critical values and extremes at both ends of the data range -Qualitative palettes do not imply magnitude differences between legend classes, and hues are used to create the primary visual differences between classes.
- Do not forget our color-blind friends !
What summary statistics should you use: tables, graphics or statistical parameters? It all depends.
Depend on the objective
- Return the data
- “take home message”
Depend on the audience
- Expert
- Everybody else
Depend on the data type
- Qualitative
- Quantitative


Home
About Me
Gallery
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Contact
C
ontact
Email:
Website queries:
<EMAIL_ADDRESS>c.mackervoy@gmail.com


Configuration Form
Properties Relevance (Weights)
Thresholds (0-1)
Periodicity (ms)
{{ item.Name }}
%


With 77% of businesses being closed at least once during the pandemic, majority of them reporting a revenue of almost zero in 2020, and most of the business houses falling into the COVID-induced debt for their survival, this section lists down these business’ expected interventions which they think will help them out of this predicaments.
PRE-EXISTING BURDENS BECOME EVEN HEAVIER
Two-thirds of the businesses reported that they will face difficulties in paying back their existing loans. These 58 businesses, when asked to choose the type of assistance that will help them pay off their debts, 59% reported they prefer reduced interest loans whereas 41% prefer to have their loan payback periods extended instead.
CUSTOMERS WILL BE KING - MORE THAN EVER BEFORE
Two-thirds of the businesses also reported that acquiring enough customers to survive will be a major issue for the next six months.
40% of such businesses believe that they do not have enough resources to understand the needs and aspirations of the source markets that their businesses cater to. 34% of businesses are looking for direct business generation programs from different sources such as trade fairs, direct advertisements, etc. The remaining 26% opine that upgrading their digital marketing skills will be the key to survive in the coming months.
TAXES
55% of businesses also reported that paying taxes will be a big burden for them by the next six months. Their preferred ways of tax repayments are
42% of businesses prefer the amount of taxes to be reduced, whereas 29% of businesses think that direct VAT return is the best intervention for them. Businesses are not very keen on deferring taxes or just exemption of fine on taxes.
SOURCE
Incidentally, almost three-fourths of the respondents prefer to receive financial assistance from the government. Only 22% businesses prefer to acquire additional loans from banks, whereas only 6% of businesses will be looking to acquire such loans from existing shareholders or new shareholders (through acquisitions, mergers or consolidations with other businesses)
For the businesses that will be seeking additional funds, two-thirds of them prefer longer-term subsidized loans whereas only one-third prefer short-term loans without collateral.
LABOR
28% of businesses have reported that they anticipate to face labor-related issues within the next six months. However, only 8% of these businesses anticipate that access to skilled/semi-skilled workers will be their major issue. 44% said that a government policy to not increase minimum wage rates for their next some time will be most helpful to them. On the other hand, a sizable proportion of businesses (48%) see vaccinating their employees as a major concern for them.
POLICY SUPPORT
We asked all the respondents what types of government policies would be helpful for their businesses. Each business could choose upto three such policies.
Two-thirds of the respondents have reported ‘establishment of a tourism protection fund’ will help them better deal with this type of crisis. Half the respondents are seeking for better government policies around financial assistance. Only 13% marked ‘establishment of job retention fund’ as one of their top three choices.
43% of respondents believe that the port of entries into Nepal should be more tightly regulated. Interestingly, only 8% of respondents think that a Training of Trainers programs on Health and Hygiene Sanitation should be one of their top three choices among the given list. An even lower (6%) seek government assistance in skill enhancement programs for their human resources.
A quarter of the respondents have asked the government to establish an authentic source of information regarding COVID-related information.
Somehow, only 24% of respondents think that a government verification system of labelling businesses as safe and unsafe (such as green, yellow and red stickers) is useful to them.


{% load staticfiles %}
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To have the node application ignore the selected differences please copy the lines below and add them to a new or existing .json file in the /ignore folder of the profile you're using.
Make sure the lines below are wrapped inside an array inside the .json file.


Overview
Quick Start
Properties
Methods
SortableTreePath
Recursion
Using Entity Framework
JSON Serialization
FAQs
Release Notes
KnightMoves.Pipelines
»
Welcome to KnightMoves.Pipelines documentation!
View page source
Documentation Home
Welcome to KnightMoves.Pipelines documentation!
¶
Overview
What is it?
What problem does it solve?
When do I use it?
What Next?
Quick Start
Complete Example
Properties
Id
Children
DepthFromRoot
HasChildren
IndentCharacter
IndentString
Parent
ParentId
PathId
Root
RoodId
Siblings
SortableTreePath
TreeNodeId
Methods
Contains
DeepCopy
Filter
FindById
Find
IsAncestor
IsDescendent
IsSibling
MakeChildOfUpperSibling
MakeSiblingOfParent
MoveDownInSiblingOrder
MoveUpInSiblingOrder
ProcessTree
ProcessChildren
ProcessAncestors
ToList
SortableTreePath
Recursion
Using a Lambda Function
Using a Class
Class vs. Lambda
Using Entity Framework
JSON Serialization
Serialization
Deserialization
FAQs
Release Notes
3.1.2
3.1.1
3.1.0
3.0.0
Breaking Changes
Enhancements
2.1.1
2.1.0
2.0.4
2.0.3
2.0.2
2.0.1
2.0.0


So begins a new age of knowledge
Litvinoff is an outsourcing company, which is able to improve your organization's effectiveness and efficiency
Litvinoff
Litvinoff is an outsourcing company, which is able to improve your organization's effectiveness and efficiency


I am a Computer enthusiast and deeply interested in learning new progresses in Software Development. I like to explore the unexplored areas of human interaction with computing and machines that inspires me to create technologies that can benefit a huge community. As my journey continues in acquiring knowledge in computer and related technologies, I am confident to acquire my goals.
Master's in Computer Science
San Francisco State University
Spring 2020 - Fall 2021
Software Engineer at Infosys
INDIA
Oct, 2017 - Nov, 2019
ReactJS
NodeJS
Python
Java
Database(MongoDB,MySQL)
EBS Suite
Web Development
Machine Learning
Data Science


--- title: shiny app as R package v2 author: Ildi Czeller date: '2017-08-16' slug: shiny-app-as-r-package-v2 categories: ["R"] tags: ["shiny", "package"] ---
In my previous post I explored the possibility of wrapping a shiny app as an R package. I falsely stated that you cannot have a directory-based shiny app with global.R
. Based on this question on Stack Overflow I proved the contrary. It is actually possible but with serious limitations in my opinion so I still strongly advise the function based approach.
You can put basically anything in the inst
folder of your package and use those as is. I.e. you can put your regular server.R
, ui.R
and global.R
files to inst
and have an exported launcher function in R
:
#' @export
runShinyPackageApp <- function(...) {
shiny::runApp(
appDir = system.file(".", package = "shinypackageapp"),
...
)
}
library(dependecy_package)
in server.R
or global.R
.library(shinypackageapp)
before runShinyPackageApp()
.server.R
or ui.R
files unless you have an exported function to access your package data.server.R
you will see something similar:DESCRIPTION
global.R
help
html
INDEX
LICENSE
Meta
NAMESPACE
R
server.R
ui.R
I suspect this is some kind of temp location of the installed package, certainly not the root folder of my project, neither the root folder of the package as I see it during package development.
All the aboves are due to the fact that these files are not compiled in any way but partly pretend to exist in the folder where you installed the package.
Besides distribution you loose most of the positive sides of wrapping your app in a package this way.
You can see the the whole code on github and try for yourselves with:
devtools::install_github(
"czeildi/shinypackageapp", ref = "v0.4.0"
)


{{ define "main" }}
Want to get your site listed here? Submit a Pull Request with your JAMstack project’s information here.


| 009:108 Khan | : |
Never stand you therein. Verily, the mosque whose foundation was laid from the first day on piety is more worthy that you stand therein (to pray). In it are men who love to clean and to purify themselves. And Allah loves those who make themselves clean and pure (i.e. who clean their private parts with dust [i.e. to be considered as soap) and water from urine and stools, after answering the call of nature]. |
| 009:108 Maulana | : |
Never stand in it. Certainly a Mosque founded on observance of duty from the first day is more deserving that thou shouldst stand in it. In it are men who love to purify themselves. And Allah loves those who purify themselves. |
| 009:108 Pickthal | : |
Never stand (to pray) there. A place of worship which was found upon duty (to Allah) from the first day is more worthy that thou shouldst stand (to pray) therein, wherein are men who love to purify themselves. Allah loveth the purifiers. |
| 009:108 Rashad | : |
You shall never pray in such a masjid. A masjid that is established on the basis of righteousness from the first day is more worthy of your praying therein. In it, there are people who love to be purified. GOD loves those who purify themselves. |
| 009:108 Sarwar | : |
(Muhammad), never stay in that mosque. The mosque which was established for a pious purpose and before all other mosques is more virtuous for your prayer. In this mosque, there are people who love to be purified. God loves those who purify themselves. |
| 009:108 Shakir | : |
Never stand in it; certainly a masjid founded on piety from the very first day is more deserving that you should stand in it; in it are men who love that they should be purified; and Allah loves those who purify themselves. |
| 009:108 Sherali | : |
Never stand to pray therein. A Mosque founded upon piety from the very first day is surely more worthy that thou shouldst stand to pray therein. In it are men who love to become purified, And ALLAH loves those who purify themselves. |
| 009:108 Yusufali | : |
Never stand thou forth therein. There is a mosque whose foundation was laid from the first day on piety; it is more worthy of the standing forth (for prayer) therein. In it are men who love to be purified; and Allah loveth those who make themselves pure. |
Concepts/Themes Covered: أركان الإسلام > التوحيد > توحيد الله تعالي > حبه تعالى Pillars of Islam> Islamic> Oneness of Allah> His Love أركان الإسلام > الصلاة > المساجد > مكانة المساجد وحرمتها Pillars of Islam> The Prayers> Mosques> The Mosques Rank and their Sacredness الإيمان > الإيمان بالله > النفاق Faith> Belief In Allah> Hypocrisy الإنسان والعلاقات الاجتماعية > المجتمعات > الأعراب Man and The Social Relations>The Societies>The Bedouins
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


Squat stand
$1400
Associated Exercises: Back squats.
$1700
Associated Exercises: Front squats.
$2000
Associated Exercises: Bench pressing.


|
LiteCore
Couchbase Lite cross-platform core implementation
|
#include <c4Replicator.h>
Data Fields | |
| C4ReplicatorMode | push |
| Push mode (from db to remote/other db) More... | |
| C4ReplicatorMode | pull |
| Pull mode (from db to remote/other db). More... | |
| C4Slice | optionsDictFleece |
| Optional Fleece-encoded dictionary of optional parameters. More... | |
| C4ReplicatorValidationFunction | validationFunc |
| Callback that can reject incoming revisions. More... | |
| C4ReplicatorStatusChangedCallback | onStatusChanged |
| Callback to be invoked when replicator's status changes. More... | |
| C4ReplicatorDocumentErrorCallback | onDocumentError |
| Callback notifying of errors with individual documents. More... | |
| void * | callbackContext |
| Value to be passed to the callbacks. More... | |
| void* C4ReplicatorParameters::callbackContext |
Value to be passed to the callbacks.
| C4ReplicatorDocumentErrorCallback C4ReplicatorParameters::onDocumentError |
Callback notifying of errors with individual documents.
| C4ReplicatorStatusChangedCallback C4ReplicatorParameters::onStatusChanged |
Callback to be invoked when replicator's status changes.
| C4Slice C4ReplicatorParameters::optionsDictFleece |
Optional Fleece-encoded dictionary of optional parameters.
| C4ReplicatorMode C4ReplicatorParameters::pull |
Pull mode (from db to remote/other db).
| C4ReplicatorMode C4ReplicatorParameters::push |
Push mode (from db to remote/other db)
| C4ReplicatorValidationFunction C4ReplicatorParameters::validationFunc |
Callback that can reject incoming revisions.


| Class and Description |
|---|
| AsExpr |
| AsPathListExpr |
| AsPathSetElem |
| AsPathSetExpr |
| BooleanExpr |
| BooleanExprs.StaticBooleanExpr |
| BooleanExprs.StaticExpressionType |
| CommunitySetElem |
| CommunitySetElemHalfExpr |
| CommunitySetExpr |
| DiscardNextHop
A next hop expression indicating that the route should drop traffic destined to its network, but
otherwise leave route parameters unchanged.
|
| IntComparator |
| IntExpr |
| Ip6Expr |
| IpExpr |
| IsisLevelExpr |
| LongExpr |
| NextHopExpr |
| OriginExpr |
| PeerAddressNextHop |
| Prefix6Expr |
| Prefix6SetExpr |
| PrefixExpr |
| PrefixSetExpr |
| RouteIsClassful
Returns
true iff the IPv4 route is classful, aka that the distributed prefix is exactly
an entire subnet in its IPv4 address class. |
| RouteType |
| RouteTypeExpr |
| SelfNextHop
Implements BGP next-hop-self semantics
|
| SubRangeExpr |
| Class and Description |
|---|
| AsPathListExpr |
| BooleanExpr |
| CommunitySetExpr |
| IntExpr |
| IsisLevelExpr |
| LongExpr |
| NextHopExpr |
| OriginExpr |
| Class and Description |
|---|
| BooleanExpr |
| Class and Description |
|---|
| BooleanExpr |
| Class and Description |
|---|
| BooleanExpr |
| CommunitySetExpr |
Copyright © 2014–2018. All rights reserved.


Virtual keyboard test #8: keyboard scaling.
Change your browser's font size - vkeyboard will resize appropriately. View page source to see how it works.
Show keyboard


So it appears you have forgot your password for {{app_name}}? Well just to make sure that it's actuall you and not some naughty person trying to change your password we need to you verify this email by clicking on the link below.
Ok ok we just needed to check, hit the link below to complete the process.
It's ok keep calm.. nothing has changes.. yet! if this wasn't you just ignore this email and nothing will happen to your account. It's probably some kids from around the block messing about.


The ideal OpAmp is a two-port. The left port is fixed to v1=0 and i1=0 (nullator). At the right port both any voltage v2 and any current i2 are possible (norator).


unStack is a community of passionate developers, designers, and other
technical
talents.
unStack is mostly focused on hands-on technical workshops and
conferences around the web, mobile, and other emerging technologies. We'll be
focusing on helping the audience gain an in-dept understanding of any chosen topic area,
therefore the workshops and talks will be on specific
frameworks and libraries with a far reaching impact on the JavaScript ecosystem and beyond.
❤


Billabong taps NetSuite to power omnichannel strategy
Marianne WilsonNetSuite Inc., a provider of cloud-based financials, ERP and and omnichannel software suites, said that boardsports retailer Billabong International Ltd. selected NetSuite...
New Study Shows One Critical Industry Lagging Behind in Software Security
Marianne WilsonNetSuite Inc., a provider of cloud-based financials, ERP and and omnichannel software suites, said that boardsports retailer Billabong International Ltd. selected NetSuite...
Watched
AlphaGo and the Declining Advantage of Big Companies
Panelists at CII's spring conference discuss governance implications of shift in US firms’ approach to capital allocation
When it comes to uses of cash, investors are slightly schizophrenic about...
Watched
Journelle, Alton Lane streamline process with NetSuite platform
Marianne WilsonNetSuite Inc., a provider of cloud-based financials, ERP and and omnichannel software suites, said that boardsports retailer Billabong International Ltd. selected NetSuite...
Watched
NetSuite rolls out a new e-procurement system for B2B companies
Marianne WilsonNetSuite Inc., a provider of cloud-based financials, ERP and and omnichannel software suites, said that boardsports retailer Billabong International Ltd. selected NetSuite...
Watched
NetSuite to Buy Email Marketing Company for $200 Million
Marianne WilsonNetSuite Inc., a provider of cloud-based financials, ERP and and omnichannel software suites, said that boardsports retailer Billabong International Ltd. selected NetSuite...


by Ioannis Canellos / @iocanel
Ioannis Canellos
Principal Software Engineer at Red Hat
Committer at the Apache Software Foundation
What is Fabric8?
Why Bother?
Fabric8 Concepts
Demo
Questions & Answers
Sounds cool, but I need that why?
IP Address & Ports are rarely known in advance!
So hardcoding is not just "smelly", its also not workable.
What you need is Location Transparency.
Can I just throw in new VMs?
Throwing in new VMs doesn't just work
Increased needs in coordination (more on that later)
Especially if you want to limit the "down time" as much as possible.
Bottom line: You need Coordination.
There are indeed lots of tools.
Infact, there are too many!
A unified tool...
Fabric8 can become your swiss army knife.
Apache ZooKeeper
Ideal for distributed system coordination...
Fabric8 treats Git as any other HA service:
"A reposiotry of resources that is made available to the container ..."
Some exaples of such resources:
Hawtio is a unified console for visualizing & managing everything.
Written on AngularJS!
Pluggable
Rich collection of plugins


{% from "macros.html" import top %} {% from "macros.html" import usual_head %}
Select from the options above.
{{ warn }}


Bitquant uses a home grown open source technology platform which is
available on our
github
site.
Technology we use
Some of the components we have used are:
A bundled set of our platform is available in the image
bitstation:latest from docker hub. The software which we write are
mostly back office. For trading we use the standard interfaces.
Also for backend processing, we
use Odoo
Technology we avoid
- Java - Java is a big bureaucratic language designed for big
bureaucratic companies.
- Anything closed source - We can't tinker with the software
Technology we are looking for
This is stuff that we are looking for, and if we don't find it, we
might as well write it ourselves. We are willing to pay for market
data feeds and support, but the project must be open source.
- Clean data feeds - Right now most cheap market data requires you
to go through the UI of the market
- Trade journal software - There is no easy open source software
that lets you look over the past history
- Chart visualization tools that aren't designed to screw over the
trader


| Ticket ID: 409788 | |
|---|---|
| Name: |
Parker Seidel No Active Support |
| Email: |<EMAIL_ADDRESS>|
| Response Time: | 72 hours, 60 hours left |
| Last Action: | Never been locked |
| Link to public post | |
| Status: | Not Answered |
Parker Seidel
No Active Support
Not Answered


| Methods' Details |
insertRow
- Description
- inserts the contents of the insert row into the result set and
the database. Must be on the insert row when this method is called.
- Throws
- SQLException
if a database access error occurs.
|
|
updateRow
- Description
- updates the underlying database with the new contents of the
current row. Cannot be called when on the insert row.
- Throws
- SQLException
if a database access error occurs.
|
|
deleteRow
- Description
- deletes the current row from the result set and the underlying
database. Cannot be called when on the insert row.
- Throws
- SQLException
if a database access error occurs.
|
|
cancelRowUpdates
- Description
- cancels the updates made to a row.
This method may be called after calling an
updateXXX
method(s) and before calling
XResultSetUpdate::updateRow()
to rollback the updates made to a row. If no updates have been made or
updateRow
has already been called, then this method has no
effect.
- Throws
- SQLException
if a database access error occurs.
|
|
moveToInsertRow
- Description
- moves the cursor to the insert row. The current cursor position is
remembered while the cursor is positioned on the insert row.
The insert row is a special row associated with an updatable
result set. It is essentially a buffer where a new row may
be constructed by calling the
updateXXX
methods prior to
inserting the row into the result set.
Only the
updateXXX
,
getXXX
,
and
XResultSetUpdate::insertRow()
methods may be
called when the cursor is on the insert row. All of the columns in
a result set must be given a value each time this method is
called before calling
insertRow
. The method
updateXXX
must be called before a
getXXX
method can be called on a column value.
- Throws
- SQLException
if a database access error occurs.
|
|
moveToCurrentRow
- Description
- moves the cursor to the remembered cursor position, usually the
current row. This method has no effect if the cursor is not on the insert
row.
- Throws
- SQLException
if a database access error occurs.
|
|
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


Players roll one dice each.
Please select number of players.
Rules summary:- Players state intentions. Players roll one dice each. All players progress if ANY player meets or beats target roll. Otherwise players suffer setbacks, give ground, take losses or progress with consequences.


{% extends PATH+"/inc/layout_citizen.html" %} {% block case_content %}
Application reference: KDJ1234
Submission date: 16/05/2018
Name: Oliver Reed
Employer: MacDonalds
Condition: Deaf and Autism


Connecting...
In Vault:
BEAM
Deposit 5 BEAM
Withdraw All
Vault transaction is in progress.
You would be able to deposit/withdraw after the transaction is completed.
Reload


| Account Address | |
| Current Balance |
| Loan Contract | |
|---|---|
| Address | |
| Transaction Hash | |
| Status |
| Property Address | |
| Purchase Price | |
| Monthly Prin + Interest: | |
| Monthly Tax: | |
| Monthly Insurance: | |
| Total Payment: | |
| Term (Years): | |
| Interest: | |
| Loan Amount: | |
| Annual Tax: | |
| Annual Insurance: | |
| Mortgage Amount | Mortgage Holder Account # | |||
| Insurance Amount | Insurer Account # | |||
| Tax Amount | IRS Account # |
| Account Address | |
| Total Mortgage Amount | |
| Amount Paid | 0 |
| Outstanding Balance |
| Loan Contract | |
|---|---|
| Address | |
| Status | |
| Account Address | |
| Total Insured Amount | |
| Amount Paid | |
| Outstanding Balance |
| Loan Contract | |
|---|---|
| Address | |
| Status |
| Account Address | |
| Total Taxes | |
| Amount Paid | |
| Outstanding Balance |
| Loan Contract | |
|---|---|
| Address | |
| Status |


--- layout: post image: /assets/images/about/NormalMapping.png header: plain title: Normal Mapping subtitle: Demo Effect permalink: /demo/normalmap/ date: 2018-3-26T03:00:00.000Z tags: HTML5 Javascript Canvas Game category: [ Demo ] comments: true ---


{% capture name %}WuLab{% endcapture %}
{% capture goals %}
The future of industry relies on the ability to make data-driven decisions, however it is only accessible to technical and statistical experts that can program, clean and combine data, visualize large datasets, and debug complex analysis pipelines.
The goal of the {{name}} is to dramatically accelerate the democratization of data, and to train high quality, world-class researchers.
{% endcapture %}
{% capture join %}
We are always looking for hard-working, smart, driven students that are excited pushing forward how humans interact with data. If you are a prospective graduate student or postdoc, [read our application document](apply.html). If you are an undergraduate, masters, or potential intern, [please fill out our questionnaire](foo.html).
{% endcapture %}
{% capture contact %}
Email us at<EMAIL_ADDRESS>{% endcapture %}


Public meeting over proposed landfill near Mayo's holy village
A PUBLIC meeting to be held in Knock on Wednesday, November 27, at 8 p.m. over plans to build a landfill site in the vicinity.
The venue is Knock Community Centre.
Aontú general election candidate Paul Lawless has confirmed that an application has been lodged with Mayo County Council for the proposed landfill at an existing quarry.
He said: “Many locals are extremely concerned about the proposed landfill in such close proximity to the village, just 500 meters from the centre of the village.
“We had an initial meeting when this news originally broke and we had over 100 people there. This meeting is expected to be bigger.
“All elected repesentatives have been invited and we hope they will attend.”


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The OutBox page contains files and folders that have been published on the Internet by the page's owner. Click a file or folder to open it. Copy a file to your system by using your Web browser's Save Link feature. (In Netscape Navigator, move the mouse over the file, click the right mouse button to see the popup menu, and choose Save Link As.)
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प्रत्याहारयन्त्र (pratyAhAra)
- Online interface
- Details
Online interface
Details
This program, given the pANinIyan code for a pratyAhAra, fetches the corresponding letters. This is produced from an attempt to convert pANinIya sUtras into a modern programming language (Scala).
Limitations:
1. Encoding of pANini's saMjJNAs is at a very immature state.
2. There are a few errors in naming svaras.


|
Above: Looking like a huge toy top
the conical command module
was crammed with some of
the most complex equipment
ever sent into space. The three
astronaut couches were surrounded by instrument panels,
navigation gear, radios, life-support systems, and small
engines to keep it stable during
reentry. The entire cone, 11
feet long and 13 feet in diameter, was protected by a
charring heat shield. The 6.5-ton CM was all that was
finally left of the 3000-ton
Saturn V stack that lifted oft
on the journey to the Moon.
Below: Packed with plumbing and tanks, the service module was the CM's constant companion until just before reentry. So all components not needed during the last few minutes of flight, and therefore requiring no protection against reentry heat, were transported in this module. It carried oxygen for most of the trip; fuel cells to generate electricity (along with the oxygen and hydrogen to run them); small engines to control pitch, roll, and yaw; and a large engine to propel the spacecraft into -and out of- lunar orbit. |
| The lunar module was also a two-part spacecraft. Its lower or descent stage had the landing gear and engines and fuel needed for the landing. When the LM blasted off the Moon, the descent stage served as the launching pad for its companion ascent stage, which was also home for the two explorers on the surface. In function if not in looks the LM was like the CM, full of gear to communicate, navigate, and rendezvous. But it also had its own propulsion system, an engine to lift it off the Moon and send it on a course toward the command module orbiting above. |
| Like a plumber's dream, the LM's environmental control system nestled in a corner of the ascent stage. Those hoses provided pure oxygen to two astronauts at a pressure one-third that of normal atmosphere, and at a comfortable temperature. The unit recirculated the gas, scrubbed out CO2 and moisture exhaled, and replenished oxygen as it was used up. |
| Sound is deadened and not an echo can be heard in this anechoic test chamber. Used to simulate reflection-free space, its floor, walls, and ceiling are completely covered with foam pyramids that absorb stray radiation, so that an antenna's patterns can be accurately measured. Here two NASA engineers inspect a test setup of an astronaut's backpack. Any interference between the astronaut and his small antenna could be detected and fixed before a real astronaut set foot on the Moon. |
| Like new Magellans, astronauts learned to navigate in space. Here Walt Cunningham makes his observations through a spacecraft window. The tools of a space navigator included a sextant to sight on the stars, a gyroscopically stabilized platform to hold a constant reference in space, and a computer to link the data and make the most complex and precise calculations. |
| Because there is no air to deflect, a spacecraft lacks rudders or ailerons. Instead, it has small rocket engines to pitch it up or down, to yaw it left or right, or to roll it about one axis. Sixteen of them were mounted on the service module, in "quads" of four. Here one quad is tested to make sure that hot rocket exhaust will not burn a hole in the spacecraft's thin skin. |
| Similar in shape but not size were the three big engines aboard Apollo spacecraft. Two of them had no backup, so they were designed to be the most reliable engines ever built. lf the service-propulsion engine failed in lunar orbit, three astronauts would be unable to return home; if the ascent engine failed on the Moon, it would leave two explorers stranded. (A descent-engine failure would not be as critical, because the ascent engine might be used to save the crew members.) |


Device Management
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public interface TaskInfoQuery<T extends TaskInfoQuery<?,?>,V extends TaskInfo> extends Query<T,V>
TaskQuery
and the HistoricTaskInstanceQuery
.| Modifier and Type | Method and Description |
|---|---|
T |
deploymentId(String deploymentId)
Only select tasks which are part of a process instance which has the given
deployment id.
|
T |
deploymentIdIn(List<String> deploymentIds)
Only select tasks which are part of a process instance which has the given
deployment id.
|
T |
dueAfter(Date dueDate)
Deprecated.
|
T |
dueBefore(Date dueDate)
Deprecated.
|
T |
dueDate(Date dueDate)
Deprecated.
|
T |
endOr() |
T |
executionId(String executionId)
Only select tasks for the given execution.
|
T |
includeProcessVariables()
Include global task variables in the task query result
|
T |
includeTaskLocalVariables()
Include local task variables in the task query result
|
T |
limitTaskVariables(Integer taskVariablesLimit)
Limit task variables
|
T |
locale(String locale)
Localize task name and description to specified locale.
|
T |
or()
All query clauses called will be added to a single or-statement.
|
T |
orderByDueDateNullsFirst()
Order by due date (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByDueDateNullsLast()
Order by due date (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByExecutionId()
Order by execution id (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByProcessDefinitionId()
Order by process definition id (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByProcessInstanceId()
Order by process instance id (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByTaskAssignee()
Order by assignee (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByTaskCreateTime()
Order by the time on which the tasks were created (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByTaskDefinitionKey()
Order by task definition key (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByTaskDescription()
Order by description (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByTaskDueDate()
Order by task due date (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByTaskId()
Order by task id (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByTaskName()
Order by task name (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByTaskOwner()
Order by task owner (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByTaskPriority()
Order by priority (needs to be followed by
Query.asc() or Query.desc() ). |
T |
orderByTenantId()
Order by tenant id (needs to be followed by
Query.asc() or Query.desc() ). |
T |
processCategoryIn(List<String> processCategoryInList)
Only select tasks which are part of a process instance whose definition
belongs to the category which is present in the given list.
|
T |
processCategoryNotIn(List<String> processCategoryNotInList)
Only select tasks which are part of a process instance whose definition does not
belong to the category which is present in the given list.
|
T |
processDefinitionId(String processDefinitionId)
Only select tasks which are part of a process instance which has the given
process definition id.
|
T |
processDefinitionKey(String processDefinitionKey)
Only select tasks which are part of a process instance which has the given
process definition key.
|
T |
processDefinitionKeyIn(List<String> processDefinitionKeys)
Only select tasks that have a process definition for which the key is present in the given list
|
T |
processDefinitionKeyLike(String processDefinitionKeyLike)
Only select tasks which are part of a process instance which has a
process definition key like the given value.
|
T |
processDefinitionKeyLikeIgnoreCase(String processDefinitionKeyLikeIgnoreCase)
Only select tasks which are part of a process instance which has a
process definition key like the given value.
|
T |
processDefinitionName(String processDefinitionName)
Only select tasks which are part of a process instance which has the given
process definition name.
|
T |
processDefinitionNameLike(String processDefinitionNameLike)
Only select tasks which are part of a process instance which has a
process definition name like the given value.
|
T |
processInstanceBusinessKey(String processInstanceBusinessKey)
Only select tasks foe the given business key
|
T |
processInstanceBusinessKeyLike(String processInstanceBusinessKeyLike)
Only select tasks with a business key like the given value
The syntax is that of SQL: for example usage: processInstanceBusinessKeyLike("%activiti%").
|
T |
processInstanceBusinessKeyLikeIgnoreCase(String processInstanceBusinessKeyLikeIgnoreCase)
Only select tasks with a business key like the given value
The syntax is that of SQL: for example usage: processInstanceBusinessKeyLike("%activiti%").
|
T |
processInstanceId(String processInstanceId)
Only select tasks for the given process instance id.
|
T |
processInstanceIdIn(List<String> processInstanceIds)
Only select tasks for the given process ids.
|
T |
processVariableValueEquals(Object variableValue)
Only select tasks which are part of a process that has at least one variable
with the given value.
|
T |
processVariableValueEquals(String variableName,
Object variableValue)
Only select tasks which are part of a process that has a variable
with the given name set to the given value.
|
T |
processVariableValueEqualsIgnoreCase(String name,
String value)
Only select tasks which are part of a process that has a local string variable which
is not the given value, case insensitive.
|
T |
processVariableValueGreaterThan(String name,
Object value)
Only select tasks which have a global variable value greater than the
passed value when they ended.
|
T |
processVariableValueGreaterThanOrEqual(String name,
Object value)
Only select tasks which have a global variable value greater than or
equal to the passed value when they ended.
|
T |
processVariableValueLessThan(String name,
Object value)
Only select tasks which have a global variable value less than the
passed value when the ended.Booleans,
Byte-arrays and
Serializable objects (which are not primitive type
wrappers) are not supported. |
T |
processVariableValueLessThanOrEqual(String name,
Object value)
Only select tasks which have a global variable value less than or equal
to the passed value when they ended.
|
T |
processVariableValueLike(String name,
String value)
Only select tasks which have a global variable value like the given value
when they ended.
|
T |
processVariableValueLikeIgnoreCase(String name,
String value)
Only select tasks which have a global variable value like the given value (case insensitive)
when they ended.
|
T |
processVariableValueNotEquals(String variableName,
Object variableValue)
Only select tasks which have a variable with the given name, but
with a different value than the passed value.
|
T |
processVariableValueNotEqualsIgnoreCase(String name,
String value)
Only select tasks which are part of a process that has a string variable with
the given value, case insensitive.
|
T |
taskAssignee(String assignee)
Only select tasks which are assigned to the given user.
|
T |
taskAssigneeIds(List<String> assigneeListIds)
Only select tasks with an assignee that is in the given list
|
T |
taskAssigneeLike(String assigneeLike)
Only select tasks which were last assigned to an assignee like
the given value.
|
T |
taskAssigneeLikeIgnoreCase(String assigneeLikeIgnoreCase)
Only select tasks which were last assigned to an assignee like
the given value.
|
T |
taskCandidateGroup(String candidateGroup)
Only select tasks for which users in the given group are candidates.
|
T |
taskCandidateGroupIn(List<String> candidateGroups)
Only select tasks for which the 'candidateGroup' is one of the given groups.
|
T |
taskCandidateUser(String candidateUser)
Only select tasks for which the given user is a candidate.
|
T |
taskCategory(String category)
Only select tasks with the given category.
|
T |
taskCreatedAfter(Date after)
Only select tasks that are created after the given date.
|
T |
taskCreatedBefore(Date before)
Only select tasks that are created before the given date.
|
T |
taskCreatedOn(Date createTime)
Only select tasks that are created on the given date.
|
T |
taskDefinitionKey(String key)
Only select tasks with the given taskDefinitionKey.
|
T |
taskDefinitionKeyLike(String keyLike)
Only select tasks with a taskDefinitionKey that match the given parameter.
|
T |
taskDescription(String description)
Only select tasks with the given description.
|
T |
taskDescriptionLike(String descriptionLike)
Only select tasks with a description matching the parameter .
|
T |
taskDescriptionLikeIgnoreCase(String descriptionLike)
Only select tasks with a description matching the parameter .
|
T |
taskDueAfter(Date dueDate) |
T |
taskDueBefore(Date dueDate) |
T |
taskDueDate(Date dueDate) |
T |
taskId(String taskId)
Only select tasks with the given task id (in practice, there will be
maximum one of this kind)
|
T |
taskInvolvedUser(String involvedUser)
Only select tasks for which there exist an
IdentityLink with the given user, including tasks which have been
assigned to the given user (assignee) or owned by the given user (owner). |
T |
taskMaxPriority(Integer maxPriority)
Only select tasks with the given priority or lower.
|
T |
taskMinPriority(Integer minPriority)
Only select tasks with the given priority or higher.
|
T |
taskName(String name)
Only select tasks with the given name
|
T |
taskNameIn(List<String> nameList)
Only select tasks with a name that is in the given list
|
T |
taskNameInIgnoreCase(List<String> nameList)
Only select tasks with a name that is in the given list
This method, unlike the
taskNameIn(List) method will
not take in account the upper/lower case: both the input parameters as the column value are
lowercased when the query is executed. |
T |
taskNameLike(String nameLike)
Only select tasks with a name matching the parameter.
|
T |
taskNameLikeIgnoreCase(String nameLike)
Only select tasks with a name matching the parameter.
|
T |
taskOwner(String owner)
Only select tasks for which the given user is the owner.
|
T |
taskOwnerLike(String ownerLike)
Only select tasks which were last assigned to an owner like
the given value.
|
T |
taskOwnerLikeIgnoreCase(String ownerLikeIgnoreCase)
Only select tasks which were last assigned to an owner like
the given value.
|
T |
taskPriority(Integer priority)
Only select tasks with the given priority.
|
T |
taskTenantId(String tenantId)
Only select tasks that have the given tenant id.
|
T |
taskTenantIdLike(String tenantIdLike)
Only select tasks with a tenant id like the given one.
|
T |
taskVariableValueEquals(Object variableValue)
Only select tasks which have at least one local task variable with the given value.
|
T |
taskVariableValueEquals(String variableName,
Object variableValue)
Only select tasks which have a local task variable with the given name
set to the given value.
|
T |
taskVariableValueEqualsIgnoreCase(String name,
String value)
Only select tasks which have a local string variable with the given value,
case insensitive.
|
T |
taskVariableValueGreaterThan(String name,
Object value)
Only select tasks which have a local variable value greater than the
passed value when they ended.
|
T |
taskVariableValueGreaterThanOrEqual(String name,
Object value)
Only select tasks which have a local variable value greater than or
equal to the passed value when they ended.
|
T |
taskVariableValueLessThan(String name,
Object value)
Only select tasks which have a local variable value less than the
passed value when the ended.Booleans,
Byte-arrays and
Serializable objects (which are not primitive type
wrappers) are not supported. |
T |
taskVariableValueLessThanOrEqual(String name,
Object value)
Only select tasks which have a local variable value less than or equal
to the passed value when they ended.
|
T |
taskVariableValueLike(String name,
String value)
Only select tasks which have a local variable value like the given value
when they ended.
|
T |
taskVariableValueLikeIgnoreCase(String name,
String value)
Only select tasks which have a local variable value like the given value (case insensitive)
when they ended.
|
T |
taskVariableValueNotEquals(String variableName,
Object variableValue)
Only select tasks which have a local task variable with the given name, but
with a different value than the passed value.
|
T |
taskVariableValueNotEqualsIgnoreCase(String name,
String value)
Only select tasks which have a local string variable with is not the given value,
case insensitive.
|
T |
taskWithoutTenantId()
Only select tasks that do not have a tenant id.
|
T |
withLocalizationFallback()
Instruct localization to fallback to more general locales including the default locale of the JVM if the specified locale is not found.
|
T |
withoutDueDate()
Deprecated.
|
T |
withoutTaskDueDate() |
T taskId(String taskId)
T taskNameIn(List<String> nameList)
ActivitiIllegalArgumentException
- When passed name list is empty or null
or contains null String
.T taskNameInIgnoreCase(List<String> nameList)
taskNameIn(List)
method will
not take in account the upper/lower case: both the input parameters as the column value are
lowercased when the query is executed.ActivitiIllegalArgumentException
- When passed name list is empty or null
or contains null String
.T taskNameLike(String nameLike)
T taskNameLikeIgnoreCase(String nameLike)
taskNameLike(String)
method will
not take in account the upper/lower case: both the input parameter as the column value are
lowercased when the query is executed.T taskDescriptionLike(String descriptionLike)
T taskDescriptionLikeIgnoreCase(String descriptionLike)
taskDescriptionLike(String)
method will
not take in account the upper/lower case: both the input parameter as the column value are
lowercased when the query is executed.T taskMinPriority(Integer minPriority)
T taskMaxPriority(Integer maxPriority)
T taskAssignee(String assignee)
T taskAssigneeLike(String assigneeLike)
T taskAssigneeLikeIgnoreCase(String assigneeLikeIgnoreCase)
taskAssigneeLike(String)
method will
not take in account the upper/lower case: both the input parameter as the column value are
lowercased when the query is executed.T taskAssigneeIds(List<String> assigneeListIds)
FlowableIllegalArgumentException
- When passed name list is empty or null
or contains null String
.T taskOwnerLike(String ownerLike)
T taskOwnerLikeIgnoreCase(String ownerLikeIgnoreCase)
taskOwnerLike(String)
method will
not take in account the upper/lower case: both the input parameter as the column value are
lowercased when the query is executed.T taskCandidateUser(String candidateUser)
T taskInvolvedUser(String involvedUser)
IdentityLink
with the given user, including tasks which have been
assigned to the given user (assignee) or owned by the given user (owner).T taskCandidateGroup(String candidateGroup)
T taskCandidateGroupIn(List<String> candidateGroups)
ActivitiIllegalArgumentException
- When query is executed and taskCandidateGroup(String)
or
taskCandidateUser(String)
has been executed on the query instance.
When passed group list is empty or null
.T taskTenantIdLike(String tenantIdLike)
T taskWithoutTenantId()
T processInstanceId(String processInstanceId)
T processInstanceIdIn(List<String> processInstanceIds)
T processInstanceBusinessKey(String processInstanceBusinessKey)
T processInstanceBusinessKeyLike(String processInstanceBusinessKeyLike)
T processInstanceBusinessKeyLikeIgnoreCase(String processInstanceBusinessKeyLikeIgnoreCase)
processInstanceBusinessKeyLike(String)
method will
not take in account the upper/lower case: both the input parameter as the column value are
lowercased when the query is executed.T taskCreatedOn(Date createTime)
T taskCreatedBefore(Date before)
T taskCreatedAfter(Date after)
T taskDefinitionKey(String key)
T taskDefinitionKeyLike(String keyLike)
T dueBefore(Date dueDate)
T dueAfter(Date dueDate)
T withoutDueDate()
T withoutTaskDueDate()
T processDefinitionKey(String processDefinitionKey)
T processDefinitionKeyLike(String processDefinitionKeyLike)
T processDefinitionKeyLikeIgnoreCase(String processDefinitionKeyLikeIgnoreCase)
processDefinitionKeyLike(String)
method will
not take in account the upper/lower case: both the input parameter as the column value are
lowercased when the query is executed.T processDefinitionKeyIn(List<String> processDefinitionKeys)
T processDefinitionId(String processDefinitionId)
T processDefinitionName(String processDefinitionName)
T processDefinitionNameLike(String processDefinitionNameLike)
T processCategoryIn(List<String> processCategoryInList)
processCategoryInList
- ActivitiIllegalArgumentException
- When passed category list is empty or null
or contains null String
.T processCategoryNotIn(List<String> processCategoryNotInList)
processCategoryNotInList
- ActivitiIllegalArgumentException
- When passed category list is empty or null
or contains null String
.T deploymentId(String deploymentId)
T deploymentIdIn(List<String> deploymentIds)
T taskVariableValueEquals(String variableName, Object variableValue)
T taskVariableValueEquals(Object variableValue)
T taskVariableValueEqualsIgnoreCase(String name, String value)
This method only works if your database has encoding/collation that supports case-sensitive queries. For example, use "collate UTF-8" on MySQL and for MSSQL, select one of the case-sensitive Collations available (MSDN Server Collation Reference).
T taskVariableValueNotEquals(String variableName, Object variableValue)
Serializable
objects (which are not primitive type wrappers)
are not supported.T taskVariableValueNotEqualsIgnoreCase(String name, String value)
This method only works if your database has encoding/collation that supports case-sensitive queries. For example, use "collate UTF-8" on MySQL and for MSSQL, select one of the case-sensitive Collations available (MSDN Server Collation Reference).
T taskVariableValueGreaterThan(String name, Object value)
Serializable
objects (which are not primitive type wrappers) are
not supported.name
- cannot be null.value
- cannot be null.T taskVariableValueGreaterThanOrEqual(String name, Object value)
Serializable
objects (which are not primitive type wrappers) are
not supported.name
- cannot be null.value
- cannot be null.T taskVariableValueLessThan(String name, Object value)
Serializable
objects (which are not primitive type
wrappers) are not supported.name
- cannot be null.value
- cannot be null.T taskVariableValueLessThanOrEqual(String name, Object value)
Serializable
objects (which are not primitive type
wrappers) are not supported.name
- cannot be null.value
- cannot be null.T taskVariableValueLike(String name, String value)
name
- cannot be null.value
- cannot be null. The string can include the
wildcard character '%' to express like-strategy: starts with
(string%), ends with (%string) or contains (%string%).T taskVariableValueLikeIgnoreCase(String name, String value)
name
- cannot be null.value
- cannot be null. The string can include the
wildcard character '%' to express like-strategy: starts with
(string%), ends with (%string) or contains (%string%).T processVariableValueEquals(String variableName, Object variableValue)
T processVariableValueEquals(Object variableValue)
T processVariableValueEqualsIgnoreCase(String name, String value)
This method only works if your database has encoding/collation that supports case-sensitive queries. For example, use "collate UTF-8" on MySQL and for MSSQL, select one of the case-sensitive Collations available (MSDN Server Collation Reference).
T processVariableValueNotEquals(String variableName, Object variableValue)
Serializable
objects (which are not primitive type wrappers)
are not supported.T processVariableValueNotEqualsIgnoreCase(String name, String value)
This method only works if your database has encoding/collation that supports case-sensitive queries. For example, use "collate UTF-8" on MySQL and for MSSQL, select one of the case-sensitive Collations available (MSDN Server Collation Reference).
T processVariableValueGreaterThan(String name, Object value)
Serializable
objects (which are not primitive type wrappers) are
not supported.name
- cannot be null.value
- cannot be null.T processVariableValueGreaterThanOrEqual(String name, Object value)
Serializable
objects (which are not primitive type wrappers) are
not supported.name
- cannot be null.value
- cannot be null.T processVariableValueLessThan(String name, Object value)
Serializable
objects (which are not primitive type
wrappers) are not supported.name
- cannot be null.value
- cannot be null.T processVariableValueLessThanOrEqual(String name, Object value)
Serializable
objects (which are not primitive type
wrappers) are not supported.name
- cannot be null.value
- cannot be null.T processVariableValueLike(String name, String value)
name
- cannot be null.value
- cannot be null. The string can include the
wildcard character '%' to express like-strategy: starts with
(string%), ends with (%string) or contains (%string%).T processVariableValueLikeIgnoreCase(String name, String value)
name
- cannot be null.value
- cannot be null. The string can include the
wildcard character '%' to express like-strategy: starts with
(string%), ends with (%string) or contains (%string%).T includeTaskLocalVariables()
T includeProcessVariables()
T withLocalizationFallback()
T or()
T endOr()
T orderByTaskId()
Query.asc()
or Query.desc()
).T orderByTaskName()
Query.asc()
or Query.desc()
).T orderByTaskDescription()
Query.asc()
or Query.desc()
).T orderByTaskPriority()
Query.asc()
or Query.desc()
).T orderByTaskAssignee()
Query.asc()
or Query.desc()
).T orderByTaskCreateTime()
Query.asc()
or Query.desc()
).T orderByProcessInstanceId()
Query.asc()
or Query.desc()
).T orderByExecutionId()
Query.asc()
or Query.desc()
).T orderByProcessDefinitionId()
Query.asc()
or Query.desc()
).T orderByTaskDueDate()
Query.asc()
or Query.desc()
).T orderByTaskOwner()
Query.asc()
or Query.desc()
).T orderByTaskDefinitionKey()
Query.asc()
or Query.desc()
).T orderByTenantId()
Query.asc()
or Query.desc()
).T orderByDueDateNullsFirst()
Query.asc()
or Query.desc()
).
If any of the tasks have null for the due date, these will be first in the result.T orderByDueDateNullsLast()
Query.asc()
or Query.desc()
).
If any of the tasks have null for the due date, these will be last in the result.Copyright © 2017 Flowable. All rights reserved.


Analyzing Information , Problem Solving, Software Algorithm Design, Software Performance Tuning, Attention to Detail, Software Design, Software Debugging, Software Development Fundamentals, Software Documentation, Software Testing


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Ranking of Scatterplot Tasks
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We learned how to use the lazer printer and the tasks were to complete: engrave a phine back, a water bottle, and a clock.


Recently I discovered a project called @steemhq and it’s very easy to join it!  From my experience, it’s quite hard to use all 30 votes, and even me, a Steemian who have been on this platform for more than one year, still have 18 votes left, so why don’t use one of them to earn some STEEM and Steem Power for yourself?
It visited my post quickly after I wrote a post. Though it only accounts for $0.01 of the post payout, it’s not that insignificant if you put the recent STEEM price into your calculation. After all, my full vote can only generate $0.44 now, so an additional $0.01 is not bad. Moreover, You can also cancel your vote anytime if you are not satisfied, so why don’t give it a try?
This page is synchronized from the post: ‘You may consider to earn some extra money if you have spare witness votes ‘


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{% extends "./layout/layout.html" %} {% from "./includes/back_link.html" import back_link %} {% block title %}Confirm your selection{% endblock %} {% block header_primary %} {{ back_link(title='Search results', prefix='Back to', url=path + '/search_results?page=' + data.page + '&search_term=' + data.search_term) }} {% endblock %} {% block body %}
You'll get a summary of the information HM Land Registry holds for this property title.
The map relies on JavaScript being enabled in your browser.
This property hasn’t been registered yet. You can’t find out who owns it from this service.
Someone other than the owner (known as the ‘cautioner’) has registered a right or interest in the property. They will be told if anyone tries to register it, and can object to the registration going ahead until their claim has been looked at. You can get their name and address from this service.
Registration has only been compulsory since the 1990s. Property that hasn’t changed hands since then may not be registered.
You only own a leasehold property for a fixed period of time. You'll have a legal agreement with the landlord (sometimes known as the ‘freeholder’) called a ‘lease’. This tells you how many years you’ll own the property.
Most flats are leasehold. Houses can be leasehold too and usually are if they’re bought through a shared ownership scheme.
The leasehold and freehold are registered separately with HM Land Registry. Each has its own title documents.
You are buying a summary of the leasehold owner, not the freehold.
More about Leasehold on GOV.UK {% elif title['tenure'] == 'Freehold' %}You own a freehold building and land outright. It is yours until you sell it or give it away.
Most houses are freehold. Most flats are leasehold. That means someone else owns the freehold for the building the flat is in.
If you want to know who owns a particular flat, you probably need the leasehold instead.
Houses can also be leasehold and usually are if they’re bought through a shared ownership scheme.
{% endif %}A property can have both a freehold and a leasehold title. To get a different tenure for this address, go back and select the one you need.
This information can change if we receive an application. This service is unable to tell you whether or not there is an application pending with HM Land Registry.
If you want to keep a copy you can download it or print it out
You can pay by credit or debit card.
{{ back_link(title='Search results', prefix='Back to', url=path + '/search_results') }}


Navigation & FAQ
Network Construction
- Step 0: Preparations
- Step 1: Load in gene expression datasets for network construction (exp-load)
- Step 2: Normalization for the expression dataset (exp-QC)
- Step 3: Check sample cluster information, optional (exp-cluster)
- Step 4: Prepare files to run SJARACNe (sjaracne-prep)
Driver Estimation
- Step 0: Preparations
- Step 1: Load in the expression dataset for analysis (exp-load, exp-cluster, exp-QC)
- Step 2: Read in network files and calcualte driver activity (act-get)
- Step 3: Get differential expression (DE) / differential activity (DA) for drivers (act-DA)
- Step 4: Generate a master table for drivers (ms-tab)
Advanced analysis
- Preparations
- Part I: More details about the top drivers
- QI.1: How to get the top drivers with significant differential activity (DA) in the comparison between G4 vs. other subtypes ?
- QI.2: How to interpret the significance of top DA drivers ?
- QI.3: What is the expression/activity pattern of these top DA drivers across sample subtypes?
- QI.4: What are the biological functions of these top DA drivers ?
- QI.5: What are the biological functions of the target genes of these top DA drivers ?
- Part II: More details about the selected driver
- QII.1: How to interpret the significance of the selected driver ?
- QII.2: How to visualize the network structure of the selected driver ?
- QII.3: What is the expression/activity of this selected driver across subtypes of sample ?
- QII.4: What are the functions of the target genes of this selected driver ?
- Part III: Other analyses NetBID2 can do


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Why choose us?
Hotel Door Lock System
Be-Tech designs & manufactures high quality state-of-the-art solutions that aim to enhance overall guest experience and drive down operating costs.
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We proudly present our product which was crafted by our Quality Centric Software Team (QCST)
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We are the industry leader with maximum number of solutions to help hotels across size and offerings. Our solutions are robust, smart and extremely user-friendly.


Watch Live: Seventh Public Democrat Impeachment Inquiry Hearing
House Democrats will hold the seventh public hearing of their impeachment inquiry on Thursday with testimonies from Fiona Hill, the former senior director on the National Security Council for Eurasia; and David Holmes, a State Department aide at the U.S. Embassy in Kiev who has testified he overheard U.S. Ambassador to the European Union Gordon Sondland speaking on the phone with President Trump.
by Kristina WongThe House Intelligence Committee hearing, chaired by Rep. Adam Schiff (D-CA), is set to begin at 9 a.m. Eastern. It is the seventh hearing overall in the impeachment inquiry, and the fifth this week, as Democrats on the committee attempt to wrap up the public hearing portion of their inquiry by Thanksgiving recess.


|
Walls And Holes
1
|
Functions | |
| QPoint | neighborOffset (SideDirection side) |
| neighborOffset Computes the offset for the coordinates of a neighbor of a tile. More... | |
| QVector2D | awayDirection (SideDirection side) |
| awayDirection Computes the "away" direction for a side on a tile, in XZ coordinates. More... | |
| QVector3D | normalDirection (SideDirection side) |
| normalDirection Computes the normal direction for a vertical side of a tile. More... | |
| M2M::Quad | makeTopQuadFragment (SideDirection side, QVector2D quadCenter, QVector2D minusQuadCenter, float minusQuadSize, M2M::ImageInfo quadImage, M2M::PhongInfo quadMaterial) |
| makeTopQuadFragment Creates a fragment of a top-facing quad. More... | |
| QVector2D M2M_Private::SideTools::awayDirection | ( | SideDirection | side | ) |
awayDirection Computes the "away" direction for a side on a tile, in XZ coordinates.
| side | The direction a side is facing. |
| M2M::Quad M2M_Private::SideTools::makeTopQuadFragment | ( | SideDirection | side, |
| QVector2D | quadCenter, | ||
| QVector2D | minusQuadCenter, | ||
| float | minusQuadSize, | ||
| M2M::ImageInfo | quadImage, | ||
| M2M::PhongInfo | quadMaterial | ||
| ) |
makeTopQuadFragment Creates a fragment of a top-facing quad.
| side | Which fragment? (there are 4!) |
| quadCenter | Center in XZ coordinates of the quad. The quad is assumed to be size (1, 1). |
| minusQuadCenter | Center in XZ coordinates of the quad that is subtracted. |
| minusQuadSize | Size of the subtracted quad (so it is assumed a square). |
| quadImage | Texture for the main quad. |
| quadMaterial | Material for the main quad. |
TODO: Preconditions.
| QPoint M2M_Private::SideTools::neighborOffset | ( | SideDirection | side | ) |
neighborOffset Computes the offset for the coordinates of a neighbor of a tile.
| side | The direction towards the neighbor. |
| QVector3D M2M_Private::SideTools::normalDirection | ( | SideDirection | side | ) |
normalDirection Computes the normal direction for a vertical side of a tile.
| side | The direction a side is facing. |


We deal with the marketing of the best world class medicines to ensure the ailing people recover fast and lead a disease-free life ahead. We took our first step of this journey by launching our products in the areas of WEST BENGAL but further our dream is to become the most trusted companies in pan-INDIA and abroad. We do not only withstand enhancing the economy but also take it as a social responsibility because our main mission is our customer complete satisfaction and faith towards us. Maintaining your health is our ultimate goal!


Money Play. How should Red play 21?
pips Red=106 White=109
(CorrectAnswer= 0/0, ErrorScore= 0)
This is not obvious. The 1 should clearly be played 6/5. The problem is the 2.
6/4 is the poorest choice as it does nothing to improve Red’s position. The real choices are 5/3 or 22/20. The former boldly slots the point Red wants to make next while 22/20 prepares to escape and (potentially) avoids problems on future fours.
Over the board I played 6/3 but really wasn’t sure. It turns out the two plays have equal equities, demonstrating once again that there can be more than one viable plan in a position. Take full credit for either play.
6/4 is the poorest choice as it does nothing to improve Red’s position. The real choices are 5/3 or 22/20. The former boldly slots the point Red wants to make next while 22/20 prepares to escape and (potentially) avoids problems on future fours.
Over the board I played 6/3 but really wasn’t sure. It turns out the two plays have equal equities, demonstrating once again that there can be more than one viable plan in a position. Take full credit for either play.
1. Cubeful 2-ply 22/20 6/5 Eq.: +0.627 0.655 0.179 0.006 - 0.345 0.074 0.001 2. Cubeful 2-ply 6/3 Eq.: +0.599 (-0.028) 0.648 0.165 0.003 - 0.352 0.065 0.001 3. Cubeful 2-ply 6/5 6/4 Eq.: +0.589 (-0.038) 0.657 0.144 0.003 - 0.343 0.054 0.001 4. Cubeful 2-ply 4/1 Eq.: +0.419 (-0.207) 0.620 0.129 0.002 - 0.380 0.062 0.001 5. Cubeful 2-ply 7/6 7/5 Eq.: +0.382 (-0.245) 0.597 0.144 0.003 - 0.403 0.060 0.001


Hello, my name is Josh Jordan. I currently am a junior attending Oakland University. I am currently working as a Coop at DTE Energy, in their IT department, their Network Security team. My professional interest would be a career either in Cyber Security, or one that incorporates machine learning.
To learn more about me, check out my Resume Page and my Fun Facts Page.


Forecast: Wet and windy, with a slight chance of thunderstorms
by Ben GutierrezHONOLULU, Hawaii (HawaiiNewsNow) - Hang on to your hats -- and umbrellas! Strong and gusty trade winds and a trough aloft will bring some rather wet and blustery weather to the island chain. A wind advisory remains in effect for most of Maui County and the Big Island, where winds will be strongest in downslope areas with gusts near 50 miles per hour possible.
Thereʻs also an area of moisture racing in from the east that will increase the chances for rain, with brief downpours and isolated thunderstorms possible as well. Any downpours or thunderstorms shouldn’t last long as they are pushed along by the winds.
It’s also active out in the ocean, with a high surf advisory for east-facing shores due to a rough and choppy swell generated by the strong trades. An advisory may be issued later today for the north and west shores of most of the smaller islands for a new swell peaking tonight into Sunday.
For mariners, a gale warning is posted for waters around Maui County and the Big Island, with a small craft advisory for remaining coastal waters.
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