#include <validate.h>
Inheritance diagram for TValidator::
Public Methods | |
| TValidator () | |
| virtual void | error () |
| virtual Boolean | isValidInput (char *s, Boolean suppressFill) |
| virtual Boolean | isValid (const char *s) |
| virtual ushort | transfer (char *s, void *buffer, TVTransfer flag) |
| Boolean | validate (const char *s) |
Static Public Methods | |
| TStreamable* | build () |
Public Attributes | |
| ushort | status |
| ushort | options |
Static Public Attributes | |
| const char* const | name |
Protected Methods | |
| TValidator (StreamableInit) | |
| virtual void | write (opstream &os) |
| virtual void* | read (ipstream &is) |
Definition at line 45 of file validate.h.
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Undocumented. |
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Each streamable class needs a "builder" to allocate the correct memory for its objects together with the initialized virtual table pointers. This is achieved by calling this constructor with an argument of type StreamableInit. |
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Called to create an object in certain stream-reading situations. Reimplemented in TPXPictureValidator, TFilterValidator, TRangeValidator, TLookupValidator, and TStringLookupValidator. |
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This is an abstract method called by validate() when it detects that the user has entered invalid information. By default, error() does nothing, but descendant types can override it to provide feedback to the user. Reimplemented in TPXPictureValidator, TFilterValidator, TRangeValidator, and TStringLookupValidator. |
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By default, isValid() returns True. Descendant validator types can override isValid() to validate data for a completed input line. If an input line has an associated validator object, its TInputLine::valid() method calls the validator object's validate() method, which in turn calls isValid() to determine whether the contents of the input line are valid. Reimplemented in TPXPictureValidator, TFilterValidator, TRangeValidator, and TLookupValidator. |
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If an input line has an associated validator object, it calls isValidInput() after processing each keyboard event. This gives validators such as filter validators an opportunity to catch errors before the user fills the entire item or screen. By default, isValidInput() returns True. Descendant data validators can override isValidInput() to validate data as the user types it, returning True if `s' holds valid data and False otherwise. `s' is the current input string. `suppressFill' determines whether the validator should automatically format the string before validating it. If `suppressFill' is True, validation takes place on the unmodified string `s'. If `suppressFill' is False, the validator should apply any filling or padding before validating data. Of the standard validator objects, only TPXPictureValidator checks `suppressFill'. Because `s' is passed by pointer, isValidInput() can modify the contents of the input string, such as forcing characters to uppercase or inserting literal characters from a format picture. isValidInput() should not, however, delete invalid characters from the string. By returning False, isValidInput() indicates that the input line should erase the offending characters. Reimplemented in TPXPictureValidator, and TFilterValidator. |
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Reads from the input stream `is'. Reimplemented from TStreamable. Reimplemented in TPXPictureValidator, TFilterValidator, TRangeValidator, and TStringLookupValidator. |
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transfer() allows a validator to take over setting and reading the values of its associated input line, which is mostly useful for validators that check non-string data, such as numeric values. For example, TRangeValidator uses transfer() to read and write long int type values to a data record, rather than transferring an entire string. By default, input lines with validators give the validator the first chance to respond to TInputLine::dataSize(), TInputLine::getData(), and @TInputLine::setData() by calling the validator's transfer() method. If transfer() returns anything other than 0, it indicates to the input line that it has handled the appropriate transfer. The default action of transfer() is to return 0 always. If you want the validator to transfer data, you need to override its transfer() method. transfer()'s first two parameters are the associated input line's text string and the getData() or setData() data record. Depending on the value of `flag', transfer() can set `s' from `buffer' or read the data from `s' into `buffer'. The return value is always the number of bytes transferred. If `flag' is vtDataSize, transfer() doesn't change either `s' or `buffer', but just returns the data size. If `flag' is vtSetData, Transfer reads the appropriate number of bytes from `buffer', converts them into the proper string form, and sets them into `s', returning the number of bytes read. If `flag' is vtGetData, transfer() converts `s' into the appropriate data type and writes the value into `buffer', returning the number of bytes written.
enum TVTransfer {vtDataSize, vtSetData, vtGetData}; Validator objects use parameters of type TVTransfer in their transfer() methods to control data transfer when setting or reading the value of the associated input line. Reimplemented in TRangeValidator. |
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Returns True if isValid(s) returns True. Otherwise calls error() and returns False. A validator's validate() method is called by the TInputLine::valid() method of its associated input line. Input lines with associated validator objects call the validator's validate() method under two conditions: either the input line has its ofValidate option set, in which case it calls validate() when it loses focus, or the dialog box that contains the input line calls validate() for all its controls, usually because the user requested to close the dialog box or accept an entry screen. |
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Writes to the output stream `os'. Reimplemented from TStreamable. Reimplemented in TPXPictureValidator, TFilterValidator, TRangeValidator, and TStringLookupValidator. |
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Undocumented. Reimplemented in TPXPictureValidator, TFilterValidator, TRangeValidator, TLookupValidator, and TStringLookupValidator. Definition at line 227 of file validate.h. |
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This is a bitmapped field used to control options for various descendants of TValidator. By default, TValidator constructor clears all the bits in options. Constants voXXXX represent the bits in the bitmapped options word in validator objects.
Constant Value Meaning voFill 0x0001 Used by picture validators to indicate whether to fill in literal characters as the user types voTransfer 0x0002 The validator handles data transfer for the input line; currently only used by range validators voReserved 0x00fc The bits in this mask are reserved by Borland Definition at line 200 of file validate.h. |
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Indicates the status of the validator object. If status is vsOK, the validator object constructed correctly. Any value other than vsOK indicates that an error occurred. Input line objects use vsOK to check that their associated validator objects were constructed properly. When called with a command parameter of cmValid, an input line object's TInputLine::valid() method checks its validator's status field. If status data member is vsOK, the input line's valid() returns True, indicating that the validator object is ready to use. The only value defined for status other than vsOK is vsSyntax, used by TPXPictureValidator to indicate that it could not interpret the picture string passed to it. If you create your own validator objects, you can define error codes and pass them in the status field.
Constant Value Meaning vsOK 0 Validator constructed properly vsSyntax 1 Error in the syntax of a picture validator's picture Definition at line 179 of file validate.h. |


What would make a better summon for a high lvl Rogue Palemaster, a Greater Bodak or a Ghoul King?
I plan on making a Rogue/Wiz/PM and am torn between 15 or 16 levels in PM.
Any advice out there?
Oh definately take 16 levels of PM. Reason: at 16th level, PMs get an Epic Spell feat. If you time it so you get PM16 on a normal feat level, you can get 2 epic spells. The obvious selection would be Epic Mage Armour and Epic Warding.


This is a wrapper arround create_dirs and create_readme that performs both opperations
create_dirs
create_readme
im_lazy(first_doc = FALSE, ...)


{% extends "layout.html" %} {% block page_title %} Publish government data {% endblock %} {% block proposition_header %} {% include "includes/propositional_navigation_signed_in.html" %} {% endblock %} {% block header_class %} with-proposition {% endblock %} {% block content %} {% include "includes/phase_banner_beta.html" %} {% include "includes/get_started.html" %} {{formData | safe}} Licensing your dataset Explaining what this means Data licence UK Open Government Licence Specify other {% endblock %}
Explaining what this means


Hi,
I am using a "fast" calibration method to calibrate my CTs.
I know it works very well (accuracy<0,1%) with the continuous sampling sketch.
I would like to know if it can work too with the discrete sampling sketch.
Here is the method. During a couple of hours. I monitor the main power with the continuous sampling sketch with a CT round the main cable. Then, EmonCMS calculates the elapsed kWh seen by the CT. During the same time, another sketch counts the number of optical pulses emitted by my electric meter. This second value gives me the "real" elapsed kWh. In order to calibrate my CT, I just add a correcting factor in EmonCMS ( x 2nd value / 1st value).
I know it works with the continuous sampling sketch as the calibration of real power is done using a single variable (powerCal). Knowing that I don't care to measure the exact voltage, can I use this method with the discrete sampling sketch ? (my final goal is to get the real power)
I guess it's ok but I would like to be sure.
I hope it's clear ;)
Eric
Re: Fast calibration method
Hi Eric, I'm pleased to hear that my 'Continuous Monitoring' sketch is of use to you.
I'm not sure that I would claim quite such a high degree of accuracy, but my powerCal scheme is very straightforward to use for measuring real power. This approach has not changed since I posted the first Mk2 PV Router sketch. The small numerical value is because of the mismatch between Amps and ADC steps for the current sensor. There are roughly 20 ADC steps per Amp, so the powerCal value needs to be the inverse of this, i.e. roughly 0.05. The voltage sensor has roughly one ADC step per volt, so has little effect.
When calibrating any new hardware on the bench, I use a conventional supply meter that pulses every Watt Hour. On the Atmega, I run my DigitalMeterEmulator sketch which can be 'calibrated' using exactly the same powerCal value. When both systems are pulsing at the same rate, calibration has been achieved. Finding the optimal powerCal value in this way takes just a few minutes.
The discrete sketches have separate cal values for Voltage and Current, so it all gets a bit more complicated. If your real power values are found to be incorrect, should you adjust Vcal or Ical or both? Who knows, which is why I went for the simpler all-in-one approach.
Re: Fast calibration method
I can see how how a linear multiplier like that could calibrate away any amplitude errors in V or I, provided they're in phase (i.e. a resistive load), but I'm struggling to see how it could work under other conditions, or how it could correct any phase errors in the measurements.
[EDIT]
Actually, I take that back. I think I was being overly pessimistic there. Your single multiplier should work fine regardless of whether V and I are in phase. Imagine a perfect world with no phase errors in your measurements, where you could precisely capture V and I at the exact same instant. Then say you did decide to calibrate the individual readings so you could display real Volts and real Amps, and you came up with V' as your voltage multiplier and I' as your current multiplier. To calculate Power, you'd then sum up all the:
V' * voltage-reading * I' * current-reading
Effectively, all you've done is come with a new multiplier, P' that equals V' * I'. If you've no interest in displaying Volts and Amps, then you really don't care which multiplier was 3 and which one was 2, you just need to multiply the product of the readings by 6, which is effectively what your approach does.
Re: Fast calibration method
Isn't it better to calibrate the measurement system at source rather than when the data is being processed in emonCMS?
That's what the calibration values are for ...
Re: Fast calibration method
I will just note that phase calibration cannot be done in emonCMS. I have to agree with Robin that, as a general principle, it is indeed best to calibrate as close to the source of the error as possible. One obvious case is where you have an emonGLCD in addition to data logging with emonCMS. In that case, if you do not calibrate the emonTx, you would need to introduce one or more calibration constants into the GLCD as well as into emonCMS, and manage and maintain both. The only time I would calibrate at a distance from the source is when the source is inaccessible, for whatever reason.


Our Work
We did user testing with a number of amputees. The results were fascinating.
Each one of them quickly learned to use our prosthesis to pick up various objects.
They gave a positive feedback and provided suggestions to further improve
our device.


Finding Improper JavaScript Globals
When I interview web developers, my first JavaScript question is usually the following:
What is the difference, in JavaScript, betweenx = 1
andvar x = 1
. Feel free to answer in as much or as little detail as you feel comfortable.
Most people would give an answer about how the var
keyword makes something a local variable, omitting it makes it a global variable. While I'd love to hear about scope chains, the window object, and hear the term "implied global" in an answer, that basic answer is good enough. It might not show a thorough knowledge of JavaScript, but at least it shows some level of understanding of the most common dangerous feature.
There are three basic ways to make a global variable in JavaScript. You can use var
(declared global), you can just assign to it without having declared it (implied global), or you can set a property on the window
object (window global). Here's those three:
var x = 1; // declared global y = 2; // implied global window.z = 3; // window global
Implied globals are bad because they're hard to keep track of, and their declarations aren't hoisted. I don't like window globals either, because mixing window.x
and x
is bad form. In my opinion, all globals should be declared globals. Unfortunately, JavaScript makes this really hard to maintain. There are tools like JSLint that will perform analysis of your code and help you out, but it can't do an entire code base at once, at least not easily.
I've written a tool that performs run-time analysis of your application, and finds all of the improperly declared globals (both implied and window globals). Check out a demo here.
Introducing badglobals.js
badglobals.js is a tool for finding all of the improperly declared global variables in your application. Using it is simple, but don't use it in production code (see "How It Works" below).
- Include badglobals.js in your page, before any other scripts.
- When you want to do analysis, open Firebug and run
BADGLOBALS.check()
. - You'll see a warning statement in the console for every bad global found. These contain both the name, and the value.
In addition, there are a few slightly more advanced features you might be interested in.
Exclusions
If you have some globals you don't want to be reported about (such as third-party libraries), you can easily exclude them manually. Before you run the check, just call .exclude
, like so:
BADGLOBALS.exclude("jQuery", "$", "YAHOO");
Feel free to call this method as many times as you'd like, it always adds, and never removes. By default, all browser built-ins are excluded (these are found when the script is included). Sometimes, the variable _firebug
enters after the script include, and shows in the report. You should exclude this.
Report Object
While the warnings are probably enough, badglobals.js also builds a report object, containing more information. Access it by calling BADGLOBALS.report()
. This will run .check()
if it has not run already. The report object has the following properties:
- bad: An array of the names of the bad globals found.
- good: An array of the names of the good globals found.
- skipped: An array of the names of the globals that were not checked.
And that's all there is to badglobals.js. It's really simple to use, but remarkably effective.
How It Works
badglobals.js works because of one key difference between implied/window globals and declared globals: declared globals cannot be deleted. This is because using var
causes the internal property [[DontDelete]] to be set.
var x = 1; y = 2; window.z = 3; delete x; // false delete y; // true delete z; // true x; // 1 y; // undefined z; // undefined
badglobals.js simply tries to delete every property of window (skipping the built-ins, of course). If the delete succeeds, it was declared wrong. It always puts it back, but I wouldn't trust this to run in production code, because it just seems dangerous. Here's the core section of badglobals.js:
for (prop in window) { if (window.hasOwnProperty(prop)) { if (skip.indexOf(prop) >= 0 || exclude.indexOf(prop) >= 0) { skipped.push(prop); } else { val = window[prop]; if (delete window[prop]) { console.warn("Found non-var global %o with value %o", prop, val); bad.push(prop); try { window[prop] = val; } catch (e) { console.error("Oops, there was an error putting %o back :(", prop); } } else { good.push(prop); } } } }
Browser Support
This script will not work in Internet Explorer, because I use the array indexOf
method, among other things. I also think IE doesn't exactly follow the standard when it comes to delete
, so the checks might not work. I don't consider this a problem, because this is a developer tool, not production code. You'll find the complete set of bad globals with Firefox or Chrome, so you should not need to check in Internet Explorer as well. I have not tested it in Opera, but the console
references will certainly fail.
Thanks to...
I got the idea for this tool from the excellent article on delete
by kangax, over at his blog. If you haven't read that article, you really should. The depth and quality is incredible.
Get badglobals.js
Here are the links, one more time:


{% extends "base.html" %} {% load static %} {% block title %} My Blog {% endblock %} {% block css_files %} {% endblock %} {% block content %} Abdi's Blog Hi, I am Abdi and I love to blog about tech My latest thoughts {% for post in posts %} {# the include statement has access to this data#} {% include "blog/includes/post.html" %} {% endfor %} What I do I love programming and help other and enjoy exploring new tech My Goal is to keep growing and help others do the same {% endblock %}
Hi, I am Abdi and I love to blog about tech
I love programming and help other and enjoy exploring new tech
My Goal is to keep growing and help others do the same


Another century down, complete with a slow leak, subsequent flat and headwinds! http://cycling.robotlikes.com/rides/328
6/2/2012, 5:27:59 PM
Favs: 0
Retweets: 0
link--- layout: tweet ---
Another century down, complete with a slow leak, subsequent flat and headwinds! http://cycling.robotlikes.com/rides/328
6/2/2012, 5:27:59 PM
Favs: 0
Retweets: 0
link


--- title: Projects layout: page --- More on GitHub
A multi-player desktop game. Players can make move, attack, upgrade, alliance orders, and chat with each other in a chatroom.
Java JavaFX Concurrency JSON CI/CD serialization socket-programming
Handled GET, POST, and CONNECT requests using daemon process and multi-thread. Cached responses according to the rules of expiration time and revalidation in RFC7234.
C++ TCP Sockets Concurrency
A website for users to request, drive for, and join rides.
Python Django PostgreSQL Docker
A full-stack UPS website paired with truck and Amazon systems in Django framework.
Python Protocol Buffers Django PostgreSQL Docker
A full-stack application to send survey emails to a big list of customers to collect feedback
JavaScript React Node.js MongoDB Redux Express
A program that can read JSON files which specifies class names and fields, generate the Java class, serialization and deserialization source codes.
Java JSON Gradle serialization


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typedef QuicDeque< std::pair< QuicString, QuicString > > | ListType |
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typedef ListType::const_iterator | const_iterator |
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| QuicHeaderList (const QuicHeaderList &other) |
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QuicHeaderList & | operator= (QuicHeaderList &&other) |
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QuicHeaderList & | operator= (const QuicHeaderList &other) |
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void | OnHeaderBlockStart () override |
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void | OnHeader (QuicStringPiece name, QuicStringPiece value) override |
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void | OnHeaderBlockEnd (size_t uncompressed_header_bytes, size_t compressed_header_bytes) override |
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void | Clear () |
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const_iterator | begin () const |
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const_iterator | end () const |
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bool | empty () const |
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size_t | uncompressed_header_bytes () const |
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size_t | compressed_header_bytes () const |
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void | set_max_header_list_size (size_t max_header_list_size) |
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size_t | max_header_list_size () const |
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QuicString | DebugString () const |
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The documentation for this class was generated from the following files:


1 Samuel 28:25
And she brought it before Saul, and before his servants; and they did eat. Then they rose up, and went away that night.


lsusb
Section: Linux USB Utilities (8)Updated: 6 May 2009
Index Return to Main Contents
NAME
lsusb - list USB devicesSYNOPSIS
lsusb [ options ]DESCRIPTION
lsusb is a utility for displaying information about USB buses in the system and the devices connected to them.OPTIONS
- -v, --verbose
- Tells lsusb to be verbose and display detailed information about the devices shown. This includes configuration descriptors for the device's current speed. Class descriptors will be shown, when available, for USB device classes including hub, audio, HID, communications, and chipcard.
- -s [[bus]:][devnum]
- Show only devices in specified bus and/or devnum. Both ID's are given in decimal and may be omitted.
- -d [vendor]:[product]
- Show only devices with the specified vendor and product ID. Both ID's are given in hexadecimal.
- -D device
- Do not scan the /dev/bus/usb directory, instead display only information about the device whose device file is given. The device file should be something like /dev/bus/usb/001/001. This option displays detailed information like the v option; you must be root to do this.
- -t
- Tells lsusb to dump the physical USB device hierarchy as a tree. This overrides the v option.
- -V, --version
-
Print version information on standard output,
then exit successfully.
RETURN VALUE
If the specified device is not found, a non-zero exit code is returned.FILES
- /usr/share/hwdata/usb.ids
-
A list of all known USB ID's (vendors, products, classes, subclasses and protocols).
SEE ALSO
lspci(8), usbview(8).AUTHOR
Thomas Sailer<EMAIL_ADDRESS>Index
This document was created by man2html, using the manual pages.
Time: 05:34:27 GMT, December 24, 2015


From sales to financial and product analysis, Munchy Seeds have gained greater insight and visibility across their entire business.
Crispin Clay
Managing Director, Munchy Seeds
“Cascade50 has revolutionised the way in which we run our business on a day to day basis. Extracting information from Sage 50 was previously both time consuming and restrictive. Thanks to Cascade’s various dashboards we can instantly view figures and very informative graphs and visuals."
"Our team can now analyse margins, products & customer sales performance, profitability and much more. I love the fact that I can use Cascade50 from anywhere in the world.”
Simply put, Munchy Seeds are tasty toasted seed wholesalers. With plenty of family history behind the company, founder “Mrs Munchy” Lucinda and husband Crispin have been producing and selling “munchy seeds” in the UK for the past 19 years.
It is a tradition that has been passed down through the family. Lucinda’s parents have been roasting their Munchy Seeds in New Zealand for over 30 years.
With a large range of products and sales, managing all the information from Sage 50 was a time-consuming exercise, often spending more time creating the analysis than spending time analysing it.
Since Munchy Seeds have connected Cascade50 to their Sage 50 data, the platform has revolutionised the way in which the company operates on a day to day basis.
Cascade50’s plug and play dashboards instantly granted Munchy Seeds greater visibility over their entire business: from sales to financial and product analysis.
The platform has been invaluable in improving the efficiency of the company’s day to day activities. The Munchy Seeds team are now able to instantly analyse margins, products & customer sales performance, profitability which was a solution that their traditional accounts package was unable to do.
Cascade50 allows Munchy Seeds to stay in control of the finances and removes the need to wait for traditional reports from the finance team.
Cascade50 transforms your Sage 50 data into Insightful, vibrant, and easy-to-use dashboards.
Gain an insightful and vibrant view of the business with an extensive library of intuitive and easy-to-use dashboards that cover everything from sales to finance and purchasing.


My Account
Profile
Payment's
Full Name
Password
Mobile Number
Location 1
Location 2
Location 3
Save
Credit Card Information
Save


degCovariates.Rd
This function will calculate the pcs using prcomp function, and correlate categorical and numerical variables from metadata. The size of the dots indicates the importance of the metadata, for instance, when the range of the values is pretty small (from 0.001 to 0.002 in ribosimal content), the correlation results is not important. If black stroke lines are shown, the correlation analysis has a FDR < 0.05 for that variable and PC. Only significant variables according the linear model are colored. See details to know how this is calculated.
degCovariates(counts, metadata, fdr = 0.1, scale = FALSE, minPC = 5, correlation = "kendall", addCovDen = TRUE, legacy = FALSE, smart = TRUE, method = "lm", plot = TRUE)
| counts | normalized counts matrix |
|---|---|
| metadata | data.frame with samples metadata. |
| fdr | numeric value to use as cutoff to determine the minimum fdr to consider significant correlations between pcs and covariates. |
| scale | boolean to determine wether counts matrix should be scaled for pca. default FALSE. |
| minPC | numeric value that will be used as cutoff to select only pcs that explain more variability than this. |
| correlation | character determining the method for the correlation between pcs and covariates. |
| addCovDen | boolean. Whether to add the covariates
dendograme to the plot to see covariates relationship.
It will show |
| legacy | boolean. Whether to plot the legacy version. |
| smart | boolean. Whether to avoid normalization of the
numeric covariates when calculating importance. This is not
used if |
| method | character. Whether to use |
| plot | Whether to plot or not the correlation matrix. |
: list:
plot, heatmap showing the signifcance of the variables.
corMatrix, correlation, p-value, FDR values for each covariate and PCA pais
pcsMatrix: PCs loading for each sample
scatterPlot: plot for each significant covariate and the PC values.
significants: contains the significant covariates using a linear model to predict the coefficient of covariates that have some color in the plot. All the significant covariates from the liner model analysis are returned.
This method is adapeted from Daily et al 2017 article.
Principal components from PCA analysis are correlated with
covariates metadata. Factors are transformed to numeric variables.
Correlation is measured by cor.test
function with Kendall method
by default.
The size of the dot, or importance, indicates the importance of
the covariate based on the range of the values. Covariates
where the range is very small (like a
varies between 0.001 to 0.002) will have a very small size (0.1*max_size).
The maximum value is set to 5 units.
To get to importance, each covariate is normalized using this
equation: 1 - min(v/max(v))
,
and the minimum and maximum values are set to
0.01 and 1 respectively. For instance, 0.5 would mean there is at least
50
Categorical variables are plot using the maximum size always, since
it is not possible to estimate the variability. By default, it
won't do v/max(v)
if the values are already between 0-1 or
0-100 (already normalized values as rates and percentages).
If you want to ignore the importance, use legacy = TRUE
.
Finally, a linear model is used to calculate the significance
of the covariates effect on the PCs. For that, this function
uses lm
to regress the data and uses the p-value calculated by
each variable in the model to define significance (pvalue < 0.05).
lm
or lasso
can be used here.
Daily, K. et al. Molecular, phenotypic, and sample-associated data to describe pluripotent stem cell lines and derivatives. Sci Data 4, 170030 (2017).
data(humanGender) library(DESeq2) idx <- c(1:10, 75:85) dse <- DESeqDataSetFromMatrix(assays(humanGender)[[1]][1:1000, idx], colData(humanGender)[idx,], design=~group) res <- degCovariates(log2(counts(dse)+0.5), colData(dse))#> #>#> #> #>#> Warning: Unquoting language objects with `!!!` is deprecated as of rlang 0.4.0. #> Please use `!!` instead. #> #> # Bad: #> dplyr::select(data, !!!enquo(x)) #> #> # Good: #> dplyr::select(data, !!enquo(x)) # Unquote single quosure #> dplyr::select(data, !!!enquos(x)) # Splice list of quosures #> #> This warning is displayed once per session.#> #>#> #> #>res$plotres$scatterPlot[[1]]


Arsenal, Liverpool 'to fight Barcelona for Karim Adeyemi'
Arsenal and Liverpool are reportedly preparing to battle Barcelona for the signature of Red Bull Salzburg teenager Karim Adeyemi.
by Matt LawBarca are believed to be firm admirers of the 17-year-old, with the Spanish champions already allegedly failing with a £13m offer.
Adeyemi has found the back of the net on seven occasions in 14 appearances for Salzburg's feeder team FC Liefering during the the 2019-20 season.
According to Transfermarkt, both Arsenal and Liverpool have now expressed an interest in bringing the teenager to the Premier League either at the start of 2020 or at the end of the campaign.
Adeyemi, who spent time with Bayern Munich during his youth career, has been capped at both Under-16 and Under-17 level by Germany.
The youngster will see his current deal with parent club Leipzig expire at the end of the 2020-21 season.
body check tags ::


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|
chessCAMO
|
Functions | |
| void | chessCAMO::printBoard (const vector< Piece * > &board) |
| Iterates through the pieces on a current board representation to produce the board on the console screen. More... | |
| void | chessCAMO::drawOrResign (Chess *chess, istream &in) |
| At any moment, the players can either continue, draw, or resign. More... | |
| void | chessCAMO::printMessage (string text, int color) |
| Prints the given message ('text') with a given 'color' to console. More... | |
| void chessCAMO::drawOrResign | ( | Chess * | chess, |
| istream & | in | ||
| ) |
At any moment, the players can either continue, draw, or resign.
| chess | The chess object is created |
| in | Input stream is selected (stdin or file) |
| void chessCAMO::printBoard | ( | const vector< Piece * > & | board | ) |
Iterates through the pieces on a current board representation to produce the board on the console screen.
| [in] | board | The board representation |
| void chessCAMO::printMessage | ( | string | text, |
| int | color | ||
| ) |
Prints the given message ('text') with a given 'color' to console.
| [in] | text | The text message to be created |
| [in] | color | One of the defined values at the top of the file |


class Role implements RoleInterface
Role is a simple implementation of a RoleInterface where the role is a string.
Methods
|
__construct(string $role)
Constructor. |
||
| string|null |
getRole()
Returns the role. |
|
|
__toString()
|
Details
at line 29
public
__construct(string $role)
Constructor.
at line 37
public string|null
getRole()
Returns the role.
This method returns a string representation whenever possible.
When the role cannot be represented with sufficient precision by a string, it should return null.
at line 42
public
__toString()


BJP is subverting democracy: AICC leader
by Special CorrespondentAICC secretary Sanjay Dutt has accused the BJP of subverting all democratic norms in its lust for power.
“We have witnessed subversion of democratic principles in Goa, Arunachal Pradesh, Karnataka and now in Maharashtra. The BJP, due to its lust for power, is defying all democratic norms. The party is indulging in the murder of democracy,” he said during a media interaction after a protest rally here.
No constitutional head has so far clarified on the necessity to take a decision at midnight. The Maharashtra Governor had given adequate time to Chief Minister Devendra Fadnavis to form the government. But the Governor was in a hurry when it came to giving time to the Shiv Sena, the NCP and the Congress to stake claim, Mr. Dutt added.
“There is no clarity on what basis the Governor believed the claim of the BJP that it has numbers in its favour,” he added.


Department of Computer Science & Engineering
National Institute of Technology Calicut
News & Announcements
Research & Consultancy
Areas of research
- Wavelet Compression Algorithms
- Image Processing
- Biometric-based Authentication
- Mobile Computing
- Network Security
- Cryptography
- Program Analysis and Transformation
- Processor Design
- Processor-based Security
Research Guides
| S. No. | Name | Qualification | Specialization |
|---|---|---|---|
| 1. | Dr. V K Govindan | PhD (IISc, Bangalore) | Image Processing, Data Compression, Pattern Recognition |
| 2. | Dr. M P Sebastian | PhD (IISc, Bangalore) | Network Security, Cryptography, Mobile Networks, Computer Architecture |
| 3. | Dr. Vineeth Paleri | PhD (IISc, Bangalore) | Compiler Design |
| 4. | Dr. Priya Chandran | PhD (IISc, Bangalore) | Computer Architecture |
Details of Ph.D. Programme
Research Publications (Last 3 Years)
- Accepted/ Published Papers in 2008-09
- Journals
- International Conferences
- Publications in 2007-08
- Journals
- International Conferences
- Publications in 2006-07
- Journals
- International Conferences
- Publications in 2005-06
- Journals
- International Conferences


Adding embedded ppt to webpage, made tracking events difficult.
Html event handlers cannot be used for iframe tags.
Changing to fullscreen mode, changes current window.
Editing over embedded ppts not possible due to cross origin domain.
Ajax and Http request too complex to handle dynamic events.
Make ppt using Markup(HTML) Language.
Added a layer of canvas over html and manipulated it with javascript.
Communicate with clients using WebSockets.
Implementation
Html
Css
Node js and socket.io(Server side)
Reveal.js(Client Side)
Interactivity
Interest
Shifting from Notebook-based model to Databased model
Practical aspects can be easily explained.
Allowing students to submit real time media.
Tests, Exams can be taken on this platform.
Can be accessed from anywhere.
Can be shared easily.


Lucy model from Stanford 3d scanning repository (decimated with Meshlab).
Please be patient while the mesh is loading. It may take a while, it's 2 MB file.
Best viewed in Chrome or Firefox using WebGL renderer.
Canvas renderer is very slow for this demo and only diffuse material works there.
Use the flag --allow-file-access-from-files if working localy in Chrome.


 The villain is boring, his only claim to fame being a third nipple (which Bond calls "an interesting anatomical titbit") and his golden gun (first owned by Oral Roberts), the climax is overly bland, consisting of a shootout in a fun house, and the murderous henchmen is played by Tattoo from "Fantasy Island," who gives Bond's knees a real pummeling, I'll tell you that.What can you say about a James Bond movie so uninspired that the writers had to bring back the annoying Sheriff Pepper character from LIVE AND LET DIE for comic relief?
Roger Moore makes his second appearance as 007 here, heading off to Thailand to trace a golden bullet that arrived at Secret Service headquarters with his name on it. Bond traces the bullet to its manufacturer, then to its sender's lover (the same woman who played Octopussy nine years later in FOR YOUR EYES ONLY...
After that, there's the customary scene with Bond trapped in the villain's exotic hidden lair and the villain shares his plans to take over the world. In this case, the lair is an island off the coast of China and the plans are only to convert the world to solar power. But those environmentalists can get pretty violent for their cause. How many newspaper headlines have we all read about people who have been brutally murdered for not recycling aluminum cans? That of course leads to the climax and then about fifteen minutes of anticlimax.
Visit the Movie Critic at LARGE website at http://www.missouri.edu/~c667778/movies.html
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


CS 312 -- Project #3 -- Dynamic Programming
General Information for Projects 3, 4, and 5:
The Traveling Salesperson Problem (TSP).
A salesperson must tour n
cities exactly once and return to the city from which she started. We treat the
problem as a tour in a weighted directed complete graph on n vertices.
The
problem is to find a tour whose distance is smallest.
Data file format: Projects 3, 4, and 5.
The data file DIFFERS from the
file format of
the first two projects. In the first two projects, each data line contained two
pieces of data.
In projects 3, 4, and 5, each data line after the first line
will contain n pieces of data, where n is the number of datalines in the file.
The jth element on the ith line is the distance from city i to city j.
Distances need NOT be symmetric!
Each data element will satisfy:
0 <=
element <= 1,000
Project 3 Information:
No data file will contain more than seventeen
lines of data.
You MUST use Dynamic Programming (either iterative or
recursive) for project 3. Templates
for both methods have been prepared to formulate your code.
Follow these INSTRUCTIONS for
turning in your program.
Use this
output function!
Here is information regarding the data file format.
This program requires a HUGE look-up table of unsigned SHORTS. You may need
to close all unnecessary windows when executing the program for seventeen
cities.
The times for groups on this project during Spring Term 1998 ranged from 0.12 to
3.13 seconds for 12 cities and 1.34 to 23.6 seconds for 17 cities.
Sample files for testing:
Updated on June 21, 1999
Go back to CS312
Homepage


Tower defense
Start wave
Disabled
Lives: x
Money: x
Wave: x
Weapons:
Price: 50
Range: 200
Damage: 30
Price: 120
Range: 350
Damage: 75
Price: 250
Range: 200
Damage: 200
Price: 500
Range: 700
Damage: 150


What is Emotional Intelligence?
Emotional Intelligence is a term that is used to describe and measure the amount of a persons ability to feel, understand and apply their emotions for a purpose and identify and understand emotions in other people to achieve higher levels of collaboration. For example, if I'm aware that I feel scared when I'm near dogs and I'm approacing a person walking a dog then I could purposely cross the road to avoid that feeling. Or if I know that my classmate gets anxious if they're late on an assignment and we're working together, we can plan for that and try and finish early so they avoid anxiousness.
How is it different to IQ?
IQ is different from EQ in a few ways. Firstly they're measurements of different things.  Secondly EQ is more valueable in the tech industry and an understanding of EQ will benefit group situations.
Why is it important?
A few reasons why I really want to learn about emotional intelligence is to improve my learning. If I'm able to learn about the emotional connections I have with situations and understand the actions that i associate with those emotions then I'll be able to apply my learnings to creating deliberate mental habits. I'm hoping that I'll have better control over my attention and increase my focus to perform tasks better.


fun setHiddenShippingInfoFields(vararg : String): Builder
hiddenShippingInfoFields
- CustomizableShippingField fields that should be
hidden in the shipping information screen. All fields will be shown if this list is
empty. Note that not all fields can be hidden, such as country or name.


#110: Component dependencies also include information on how to properly configure the environment in which the component will be deployed
Prof. Cesare Pautasso
http://www.pautasso.info
<EMAIL_ADDRESS>@pautasso
#110: Component dependencies also include information on how to properly configure the environment in which the component will be deployed
Correctness
Second rubric
Rubric the Third
Rubric the Third
Rubric the Third
Rubric the Third
#111: Text Input question
Rubric the Third
#111: Text Input question
Rubric the Third
#11: A software architect plays the following roles in a development team:
#129: There are multiple views over a software architecture model because:
Use a spacebar or arrow keys to navigate


INTRO
The chat_client is a WebSocket client interface and client socket protocol representation and TXT protocol termination.
This module may refer to: chat, chat_server.
The chat_client is a WebSocket client interface and client socket protocol representation and TXT protocol termination.
This module may refer to: chat, chat_server.


Lambda Calculus compiler and interpreter
Copyright (C) 2011, Bill Burdick, Tiny Concepts:
http://tinyconcepts.com/fs.pl/lambda.fsl
Licensed with the ZLIB license. See source code for details.
Use the text field below to enter Lambda Calculus expressions. You can use normal Lambda Calculus syntax, with \ meaning λ, but you have to separate your variables with spaces (click edit on any of the definitions for an example). Try testing it out with this (you need to hit enter after you click this):
(\x y . x) 1 2
You can define terms using NAME = EXPR. Try this:
pickThird = \x y z . z
You can evaluate lambda calculus expressions in 3 ways:
- The 'Run' button will compile into JavaScript and run it
- The 'Reduce' button will use alpha conversion, beta reduction, and eta conversion to simplify it
- The 'VM' button will compile it into byte code and display another 'Run' button you can use to run it (the VM is stilla work-in-progress)
The evaluator displays lists for 'Run' (of the first kind) and 'Reduce' results, but not VM's 'Run' results, yet. It cannot display detailed function results of other types for 'Run' (both kinds), but it can for Reduce. Eventually, the VM will display fully detailed results, just like 'Reduce' can.
You can modify the parser in these ways:
- You can make your definition a token to the parser using
NAME =.= EXPR
this means that you won't need spaces around NAME. Good for punctuation, etc.
- You can make your definition a grouping token with
NAME =(CLOSE= EXPR
and CLOSE =)= EXPR
(for the corresponding closing token).
I use these in the example definitions to create an array-like syntax for lists: [1,2,3] is the same as saying cons 1 (cons 2 (cons 3 nil)).
Bill Burdick (you can send me mail at bill dot burdick on gmail)
To do
save button


Gear(gearName: String? = null)
Represents a container for a set of commands. Command functions should always go into these.
Author Boston Vanseghi
Since 2.1.0


A B C D E F G H I L M N O P R S T U V W X
All Classes All Packages
All Classes All Packages
All Classes All Packages
D
- DeadCode - Class in com.ensoftcorp.open.commons.analyzers
-
An analyzer for dead code
- DeadCode() - Constructor for class com.ensoftcorp.open.commons.analyzers.DeadCode
- debug(String) - Static method in class com.ensoftcorp.open.commons.log.Log
- debug(String, Throwable) - Static method in class com.ensoftcorp.open.commons.log.Log
- DEBUG_LOGGING - Static variable in class com.ensoftcorp.open.commons.preferences.CommonsPreferences
-
Enable/disable debug logging
- DEBUG_LOGGING_DEFAULT - Static variable in class com.ensoftcorp.open.commons.preferences.CommonsPreferences
- declarations(Q) - Static method in class com.ensoftcorp.open.commons.analysis.CommonQueries
-
Produces a declarations (contains) graph.
- declarations(Q, Q) - Static method in class com.ensoftcorp.open.commons.analysis.CommonQueries
-
Produces a declarations (contains) graph.
- DefaultCallResolutionStrategy() - Constructor for class com.ensoftcorp.open.commons.algorithms.ICFG.DefaultCallResolutionStrategy
- DefaultFlushProvider - Class in com.ensoftcorp.open.commons.sandbox
- DefaultFlushProvider() - Constructor for class com.ensoftcorp.open.commons.sandbox.DefaultFlushProvider
- delete(SandboxGraphElement) - Method in class com.ensoftcorp.open.commons.sandbox.Sandbox
-
Removes the given sandbox graph element from the sandbox universe
- deleteProject(IProject) - Static method in class com.ensoftcorp.open.commons.utilities.WorkspaceUtils
- DepthFirstPreorderIterator - Class in com.ensoftcorp.open.commons.algorithms.dominance
-
DepthFirstPreorderIterator yields a depth-first pre-order traversal of a graph.
- DepthFirstPreorderIterator(UniqueEntryExitGraph, Node) - Constructor for class com.ensoftcorp.open.commons.algorithms.dominance.DepthFirstPreorderIterator
- DepthFirstPreorderIterator(UniqueEntryExitGraph, AtlasSet<Node>) - Constructor for class com.ensoftcorp.open.commons.algorithms.dominance.DepthFirstPreorderIterator
- dfg(Node) - Static method in class com.ensoftcorp.open.commons.analysis.CommonQueries
- dfg(Q) - Static method in class com.ensoftcorp.open.commons.analysis.CommonQueries
- difference(SandboxGraph...) - Method in class com.ensoftcorp.open.commons.sandbox.SandboxGraph
-
Select this graph, excluding the graphs g.
- differenceEdges(SandboxGraph...) - Method in class com.ensoftcorp.open.commons.sandbox.SandboxGraph
-
Select this graph, excluding the edges from the given graphs.
- disable() - Method in class com.ensoftcorp.open.commons.utilities.selection.ExpiringGraphSelectionProvider
- disable() - Method in class com.ensoftcorp.open.commons.utilities.selection.GraphSelectionProvider
- disableColorPalette(ColorPalette) - Method in class com.ensoftcorp.open.commons.codepainter.CodePainter
-
Disables the color palette if the color palette exists and isn't already disabled
- disableGraphSelectionListener() - Method in class com.ensoftcorp.open.commons.utilities.selection.GraphSelectionListenerView
-
Disables graph selection listener
- disableGraphSelectionProvider() - Method in class com.ensoftcorp.open.commons.utilities.selection.ExpiringGraphSelectionProviderView
-
Disables graph selection providers
- disableGraphSelectionProvider() - Method in class com.ensoftcorp.open.commons.utilities.selection.GraphSelectionProviderView
-
Disables graph selection providers
- DISPLAY_FILTER_VIEW_RESULT_CONTAINERS - Static variable in class com.ensoftcorp.open.commons.preferences.CommonsPreferences
-
Enable/disable displaying filter view result containers
- DISPLAY_FILTER_VIEW_RESULT_CONTAINERS_DEFAULT - Static variable in class com.ensoftcorp.open.commons.preferences.CommonsPreferences
- displayName() - Method in class com.ensoftcorp.open.commons.codemap.AtlasToolboxCodemapStage
- dispose() - Method in class com.ensoftcorp.open.commons.utilities.selection.GraphSelectionListenerView
- DOMINANCE_FRONTIER_EDGE - Static variable in class com.ensoftcorp.open.commons.algorithms.DominanceAnalysis
-
Used to tag the edges from a node that identify the node's dominance frontier.
- DominanceAnalysis - Class in com.ensoftcorp.open.commons.algorithms
-
Primary interface for computing dominance relationships.
- DominanceAnalysis() - Constructor for class com.ensoftcorp.open.commons.algorithms.DominanceAnalysis
- DOMINATOR_TREE_EDGE - Static variable in class com.ensoftcorp.open.commons.algorithms.DominanceAnalysis
-
The immediate dominator or idom of a node n is the unique node that strictly dominates n but does not strictly dominate any other node that strictly dominates n.
- DominatorTree - Class in com.ensoftcorp.open.commons.algorithms.dominance
-
An implementation of the O(n log n) Lengauer-Tarjan algorithm for building the dominator tree of a graph.
- DominatorTree(UniqueEntryExitGraph) - Constructor for class com.ensoftcorp.open.commons.algorithms.dominance.DominatorTree
-
Construct a DominatorTree from a root.
- DominatorTree(UniqueEntryExitGraph, AtlasSet<Node>) - Constructor for class com.ensoftcorp.open.commons.algorithms.dominance.DominatorTree
-
Construct a DominatorTree from a collection of "roots."
- DominatorTree.Multimap<T> - Class in com.ensoftcorp.open.commons.algorithms.dominance
-
Multimap maps a key to a set of values.
All Classes All Packages


Module textredux.buffer_list
The buffer list module provides a text based replacement for the standard Textadept buffer list.
Two differences compared to the stock one is the ability
to close a buffer directly from the buffer list (bound to Ctrl + d
by default),
and the option of specifying the buffers to list via a provided function.
Info:
- Copyright: 2011-2012
- License: MIT (see LICENSE)
- Author: Nils Nordman
Functions
| currently_selected_buffer (list) | Returns the currently selected buffer in the list. |
| close_buffer (list) | Closes the currently selected buffer in the buffer list. |
| show (buffers) | Shows a list of the specified buffers, or _G.BUFFERS it not specified. |
Tables
| keys | The key bindings for the buffer list. |
Fields
| list | The Textredux list instance used by the buffer list. |
Functions
- currently_selected_buffer (list)
-
Returns the currently selected buffer in the list.
Parameters:
- list The Textredux list instance used by the buffer list. If not provided, then the global list is used automatically.
Returns:
- The currently selected buffer, if any.
- The currently selected buffer's name, if any.
- close_buffer (list)
-
Closes the currently selected buffer in the buffer list.
Parameters:
- list The Textredux list instance used by the buffer list. This function is ordinarily invoked as the result of a key binding, and you should thus not need to specify this yourself. If list isn't provided, the global list is automatically used.
- show (buffers)
-
Shows a list of the specified buffers, or _G.BUFFERS it not specified.
Parameters:
- buffers Either nil, in which case all buffers within _G.BUFFERS are displayed, or a function returning a table of buffers to display.
Tables
- keys
-
The key bindings for the buffer list.
You can modifiy this to customise the key bindings to your liking. The key bindings are passed directly to the Textredux list, so note that the first argument to any function will be the Textredux list itself. You can read more about the Textredux list's keys in the list documentation.
If you like to add a custom key binding for closing a buffer you can bind the close_buffer function to a key of your choice. For other actions it's likely that you want to obtain the currently selected buffer - you can use the currently_selected_buffer function for that.
Fields:
- cd
Default for
close buffer
- esc Escape closes list by default
- cd
Default for


黒の手番です。62 はどう動かしますか？


Chapter 5 Lab 5: Fundamentals of Hypothesis Testing
The null hypothesis is never proved or established, but is possibly disproved, in the course of experimentation. Every experiment may be said to exist only to give the facts a chance of disproving the null hypothesis. —R. A. Fisher
5.1 JAMOVI
In this lab, we will use jamovi to:
- Calculate difference scores between pairs of measures
- Conduct a sign test
5.1.1 Experiment Background
This is a fictitious experiment based on the infamous Coke vs. Pepsi Taste Test Challenge. 20 blindfolded participants were presented with two cups of soda (Coke and Pepsi). Presentation sequence was randomly determined, and participants were required to rate the taste of the soda on a scale from 1-5.
5.1.2 Calculate difference scores between pairs of measures and conduct a sign test
First, let’s open the relevant data file; Here is the link; it is called PepsiCoke.sav. We need to calculate, for each participant, the difference between the rating they gave for Coke vs. Pepsi. We will use jamovi to create a new variable (in a new column) containing only difference scores. We will then re-assign the difference scores to indicate preference for Pepsi or Coke. Since we used the calculation “Pepsi - Coke”“, anyone who has a positive difference score preferred the Pepsi better, while anyone with a negative difference score preferred the Coke.
Our goal here is not simply to calculate difference scores. We really want to know if there were more instances of preference for one soda over the other. Since the sign tells us who liked Pepsi better or who liked Coke better, comparing the number of pluses to minuses will tell us which soda wins out (and is also the reason this test is called a Sign test). Follow the steps below to accomplish all of this:
So, looking at this table, it’s clear that more people preferred Coke (there are 16 positive differences), and much fewer people preferred Pepsi (there are only 4 negative differences). The question is, is this difference (16 vs. 4) large enough to be statistically significant. The table labeled “Test Statistics” answers this question.
The binomial distribution is used to obtain a p-value for this exact outcome. The p-value listed in the table is .012. Since this number is less than the commonly used alpha level (.05), we can say that this difference is indeed significant. People significantly prefer Coke over Pepsi in the Taste Test Challenge.
(Neither this lab manual nor any of its authors are affiliated with, funded, or in any way associated with the Coca Cola Company)
5.1.3 Entering data for sign test problems
What if you aren’t given a set of paired scores? What if your professor asks you to perform a sign test on a single outcome statement? For example: Test the hypothesis that a coin is weighted if, out of 15 flips of the coin, it lands on tails 13 times.
Notice that in this problem, there are no pairs of scores. We’re essentially only given the number of signs: out of 15 flips, the coin landed on tails 13 times (you can think of this as 13 pluses) and on heads obviously twice (you can think of this as 2 minuses).
Since jamovi needs counts conduct the sign test, you can simply create one column called ‘Con Flip’, and treat each row as a flip. Since you know that 13 of the flips were tails, type Tails
in 13 rows and Heads
in 2 rows (total of 15 flips).From here, you can conduct a sign test as described above.
5.1.4 Practice Problems
In this lab, you will be conducting a sign test to determine whether a coin is weighted. Individually or in small groups, take a coin out of your pocket. If working in groups, use only one coin for the whole group. Now, flip the coin 25 times. Write down how many heads and tails you observed.
Enter this into your jamoi spreadsheet and run a sign test using an alpha level of .05. What is your result?
Have students in the class (or groups) announce their results as well. Did anyone have a trick coin? Do you think some of the coins used were actually weighted? Why or why not?


It is a community effort to make Portainer as feature-rich as simple it is to deploy and use. We need all the help we can get!
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WATERWORLD A film review by Mark R. Leeper Copyright 1995 Mark R. Leeper
Capsule: There is too much action and not enough excitement in this retread of too many cheap post-holocaust films. WATERWORLD was made with far more budget than business sense. In the new Universal release oceans have long since risen to cover the land. With all the engaging survival problems that would create, this film concentrates on that of fighting off nasty pirates. This is the most expensive minor film since (and including) HEAVEN'S GATE. Rating: high 0 (-4 to +4)
In 1989, when there seemed to be no end of films about psychotics terrorizing people, one such film was made that really stood out. Phillip Noyce made DEAD CALM which set the same basic plot on water. A seaman and his wife are menaced when they rescue a stranger from a sinking yacht. The seaman finds himself having to salvage the sinking boat and use it to pursue his own boat to save his wife. DEAD CALM was interesting on an intellectual level as well as being a nail-biter because the seamanship aspect added a whole new dimension. Done right a tired plot can be given new life by setting it on water and by having it be about more than just a cliched situation. DEAD CALM did it right. WATERWORLD did it wrong. For a long time after the success of MAD MAX 2 (a.k.a. THE ROAD WARRIOR) there were no end of films--mostly on cable--about lawless post-holocaust worlds where good people have to fight against roving bands of nasties against a backdrop of deteriorating conditions. WATERWORLD takes that tired, overused plot and moves it to the water where it becomes a tired, over-used plot on water. There is not very much about seamanship in the new Kevin Costner film. It is there as a backdrop, but it never really becomes part of the story. All that is really in the plot are ROAD WARRIOR situations set on the ocean, under the false assumption that to make a scene interesting all that is needed is to add water. If you get excited by aerial shots of a line of thirty racing jet skis, this is the film for you.
The change of setting for this post-holocaust film raises it above its cable and video peers, but not nearly enough to justify the expense, logistics, and technical difficulties of shooting this probable fiasco. Even in a summer that has had only one or two decent films, this one does not make itself memorable. (Unless, perhaps it will displace HEAVEN'S GATE as the American film industry's most notorious mistake.)
WATERWORLD is set some unspecified time in the future after global warming has melted the ice caps and the resulting rise in water level has flooded apparently all of the world. Humanity has put to sea long ago and has only mythic memories of the place called "Dryland." (Sorry, there just is not THAT much water in the ice caps.) People have fallen prey to bands of nomadic pirates and it is a constant fight for survival against them and the sea. How this world evolved, how people manage to find proper food, and how they get what is needed to keep the old wrecks afloat are just some of the details that could have added interest to the film. But the most interesting aspects of this world are nearly or completely ignored. That the film concentrates instead on how people fight and kill each other is more a disappointment than a surprise.
WATERWORLD is not without its moments of wry humor. The pirates are called "smokers" in part because they burn fossil fuels while the "good guys" use more ecologically sound sails, but also because they are rarely seen without cigarettes. It wasn't long ago that it was the heroes of the film who smoked. Are we being told that the smokers of our day, already somewhat social outcasts, are to become the pirates of tomorrow? Just a side comment: one wonders how good these cigarettes would taste in a world where the land needed to grow tobacco is lost in a forgotten past. The leader of the smokers is the wise-cracking Deacon. Dennis Hopper plays this as the occasionally funny whacked-out character that is pretty much his trademark. Some of his lines are funny and others just bizarre. He is not great but he steals what show there is from the ever-mild Kevin Costner playing the unnamed lead, a mariner consistently upstaged by his own spring-loaded trimaran. There is not much more personality from female lead Jeanne Tripplehorn of BASIC INSTINCT and THE FIRM.
There are much better stories to make films with a budget of $1,300,000 per minute of screen time of, and there are much cheaper ways to make a comic book of a film that rates only a high 0 on the -4 to +4 scale.
Mark R. Leeper<EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


{% extends "global/Page.html" %} {% load staticfiles otree_tags %} {% block title %}
The summary of the instructions (below) will be available in each round. To display it just click on the button at the bottom of the screen.
{% include Constants.instructions_template %}


I have always been a mix of creative and analytical, but have struggled to find where that duality can coexist. As a musician, I've been able to utilize the creative part of me to write and play music but I've never quite fit in with other musicians in my desire to add structure and order to the creative process. In my business ventures, I have been able to live in details and data, but have felt unable to express my creative side in a way that is fulfilling. I have found the perfect union of the two in programming.
As a software developer, I am able to use my whole self to solve problems. I have the opportunity to step back, look at the big picture, and come up with a creative solution. While at the same time, dive deep into the details in order to bring that solution to life. I look forward to the consistent opportunity and necessity to learn new things. My favorite aspect of programming is the ability to use code to solve real problems in the world around me.
When not writing code you can find me singing and playing guitar in venues around the Nashville area.
A six month, full stack software development boot-camp.
The Nashville leader in gifting, trophies and personalization.
Premier amplifier builder and amplifier repair shop.
A leading department store chain.
A national branding and marketing expert in community and municipality branding.
The leader in outsourced, performance-based Business-to-Business growth solutions.
Intensive full-time software development bootcamp focusing on full stack development fundamentals and problem solving. The final half of the program executed in a simulated company environment with Scrum methodology.
Song-Share is a single page responsive CRUD web application built with React.js and Bootstrap that reduces the barriers between publishers and songwriters. Song-Share allows songwriters to upload songs, build playlists and privately share those playlists with a publisher. A publisher can then hear each song on the playlist in one page and read pertinent information on each song.
Close ProjectMission Control is a single page responsive CRUD web application built with JavaScript. Mission Control was designed to bring several aspects of online interaction together in one application. In it a user can manage their tasks, store articles, manage their events, add friends and allow the user to message other users. I had a role in all aspects of this project but was predominantly focused on building out the events page.
Close ProjectReactShell is a single page responsive CRUD web application built with React and Bulma. ReactShelll was designed to bring several aspects of online interaction together in one application. In it a user can manage their tasks, store articles, manage their events, add friends and allow the user to message other users. I was responsible for the tasks page which implemented a Trello like drag and drop functionality.
Close ProjectBangazonHR is an application built with Python, Django and Bootstrap. This application is designed to provide HR with the tools they need to complete their job. The user can add, edit and delete, employees, departments, computers and training programs. As well as assign employees to training programs and departments and assign computers to employees. I was responsible for the models, views, templates and tests associated with computers and their relationship with employees.
Close ProjectBangazon E-commerce is built with Python, Django and Bootstrap. This application allows users to buy and sell products, rate previous purchases, favorite sellers, and recommend products to other users. I had a hand in many aspects of this project but was predominantly focused on building the user settings page and photo upload for new products.
Close Project


HiveMind is an services and configuration microkernel.
Its features are also referred to as Inversion of Control (IoC) Container
or Lightweight Container.
The adoption of HiveMind in an application ensures the use of
certain design principles which improve encapsulation, modularization,
testability and reusability.
- Services: HiveMind
services are POJOs (Plain Old Java Objects) that can be easily
accessed and combined. Each service ideally defines a Java interface it
implements (this is not mandatory). HiveMind takes care of the life cycle
of services. It instantiates and finalizes services and configures each
service just as necessary. HiveMind lets services collaborate with each
other via dependency injection, so that the service code itself
is released from the task of looking up dependencies.
- Configuration:
HiveMind allows you to provide complex configuration data to your
services in a format you define. HiveMind will integrate the
contributions of such data from multiple modules and convert it all into
data objects for you. HiveMind configurations allow for powerful,
data-driven solutions which combine seemlessly with the service
architecture.
Related projects and HiveMind Extensions
This section lists related projects and HiveMind extensions that have been created by third parties.
|
Tapestry
|
Web framework that uses HiveMind under the covers. |
|
HiveMind Utilities
|
Repository of HiveMind extensions for the support of transaction handling, security, remoting, events and rich clients.
|
|
Crispy
|
Client for Remote Invocation for different kinds of services via proxies.
Offers an extension for the invocation of HiveMind services. |
|
Mule
|
Enterprise Service Bus (ESB) messaging framework that supports HiveMind as object container. |


Bella Hadid Makes Amends With Selena Gomez
by Shakiel MahjouriIf there was any beef between Bella Hadid and Selena Gomez, it has been squashed.
Hadid reportedly reached out to Gomez to make peace after fans blew an Instagram post out of proportion, according to TMZ. Gomez commented on a photo of Hadid with an innocent enough comment: “Stunning.”
Hadid reportedly did not reply to Gomez’s comment or follow her back. Hadid later deleted the post entirely. It was re-posted by a fan account and Gomez commented “that sucks,” with a crying emoji.
The supermodel reportedly reached out to the “Wolves” singer to clear things up. Hadid, 23, insisted there was no bad blood with Gomez, 27, and she simply deleted the photo because she did not like it.
“NO. I shouldn’t have spoken without knowing the truth. I’m sorry. Please don’t be hurtful,” Gomez wrote in a separate comment, per E! News. “She is a wonderful person and it was all a misunderstanding.”
A lot of the rumoured feud was fueled by the fact that Gomez briefly dated Canadian singer The Weekend between his on-and-off relationship with Hadid.


Load
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A very simple scheduler for vue.js
Business-day Support
Business-hours Support
Drag and Drop Support
Resize Schedule Support
Touch Device Support(Require DragDropTouch.js)
Example Sample Demo
Download and include vue-scheduler-lite.js
andstyle.css
from here
<script src="vue-scheduler-lite.js" type="text/javascript" language="javascript"></script>
<link rel="stylesheet" href="style.css" />
push to your vue components object
components: { 'vue-scheduler-lite': vueSchedulerLite }
enjoy it!
<vue-scheduler-lite :schedule-data="data" :setting="settingData" />
npm install vue-scheduler-lite --save
add to your project
import VueSchedulerLite from 'vue-scheduler-lite'
enjoy it!
<vue-scheduler-lite :schedule-data="data" :setting="settingData" />
| name | Type | description | |
|---|---|---|---|
| startDate | String | schedule start date(YYYY/MM/DD) | |
| endDate | String | schedule end date(YYYY/MM/DD) | |
| weekdayText | Array | Date weekday | |
| unit | Integer | minuite time line cell | |
| borderW | Integer | cell border width(px) | |
| dateDivH | Integer | Date cell height(px) | |
| timeDivH | Integer | Time cell height(px) | |
| unitDivW | Integer | Select cell width(px) | |
| titleDivW | Integer | title cell width(%) | |
| rowH | Integer | Row height(px) |
| name | Type | description | |
|---|---|---|---|
| row-click-event | Function | Title div click event | |
| date-click-event | Function | Date div click event | |
| click-event | Function | Schedule bar click event | |
| add-event | Function | New schedule add event | |
| move-event | Function | Schedule move event | |
| edit-event | Function | Schedule edit event | |
| delete-event | Function | Schedule delete event |
| name | Type | description | |
|---|---|---|---|
| title | String | Visible Text Schedule Bar | |
| noBusinessDate | Array | Not business-day list(All day) | |
| businessHours | Array | Business-hours(One day) | |
| start | String | Business start hours(HH:ii) | |
| end | String | Business end hours(HH:ii) | |
| schedule | Array | add schedule data | |
| start | String | time String(HH:ii) | |
| end | String | time String(HH:ii) | |
| text | String | Show Text | |
| data | Object,Array | callback data Object |


Distance discriminant analysis method is one of classification methods according to multiindex performance parameters.However,the traditional Mahalanobis distance discriminant method treats with the importance of all parameters equally,and exaggerates the role of parameters which changes a little.The weighted Mahalanobis distance is used in discriminant analysis method to distinguish the importance of each parameter.In the concrete application,firstly based on the principal component analysis scheme,a new group of parameters and their corresponding percent contributions of the parameters are calculated ,and the weighted matrix is regarded as the diagonal matrix of the contributions rates.Setting data to standardization,then the weighted Mahalanobis distance can be calculated.Besides the methods metioned above,bayes method is also given.
| Version: | 1.0 |
| Published: | 2012-07-06 |
| Author: | Bingpei Wu |
| Maintainer: | Bingpei Wu <jianpeizhon at 126.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | WMDB results |
| Reference manual: | WMDB.pdf |
| Package source: | WMDB_1.0.tar.gz |
| Windows binaries: | r-devel: WMDB_1.0.zip, r-release: WMDB_1.0.zip, r-oldrel: WMDB_1.0.zip |
| OS X binaries: | r-release: WMDB_1.0.tgz, r-oldrel: WMDB_1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=WMDB to link to this page.


pygraphc.clustering package¶
Submodules¶
pygraphc.clustering.ClusterDistance module¶
-
class
ClusterDistance
[source]¶ Bases:
object
Class for distance measurement between two vertices.
-
static
get_cosine_similarity
(tfidf1, tfidf2, length1, length2)[source]¶ Measure cosine similarity between two strings.
Typically, it is similarity between two event log messages in the two vertices in graph-based event log clustering.
Parameters: - tfidf1 (list) – List of tf-idf measure from the first message.
- tfidf2 (list) – List of tf-idf measure from the second message.
- length1 (float) – Denominator in cosine similarity from the first message.
- length2 (float) – Denominator in cosine similarity from the second message.
Returns: cosine_similarity – Cosine similarity between two strings.
Return type: float
-
static
pygraphc.clustering.ClusterUtility module¶
-
class
ClusterUtility
[source]¶ Bases:
object
A class contains some utilities to do clustering algorithm.
-
static
get_cluster_property
(graph, clusters)[source]¶ Get cluster property.
Parameters: - graph (graph) – Graph to be analyzed.
- clusters (dict[list]) – Dictionary contains sequence of nodes in all clusters.
Returns: cluster_property – Property of a cluster. For example: frequency of event logs.
Return type: dict
-
static
get_geometric_mean
(weights)[source]¶ Get geometric mean or intensity in a clique. A clique can be a k-clique or maximal clique.
Parameters: weights (list[float]) – List of edge weight in a clique. Returns: gmean – Geometric mean of given edge weights. Return type: float
-
static
get_weighted_cliques
(graph, cliques, threshold)[source]¶ Get weighted cliques based on given intensity threshold.
A clique which its weight are less then threshold is omiited. This procedure will filter unsignificant cliques.
Parameters: - graph (graph) – A graph to check for its weighted cliques.
- cliques (list[frozenset]) – List of clique list found.
- threshold (float) – Intensity (geometric mean) threshold.
Returns: weighted_cliques – List of clique with significant weight.
Return type: list[list]
-
static
pygraphc.clustering.ConnectedComponents module¶
-
class
ConnectedComponents
(graph)[source]¶ This is a class for connected component detection method to cluster event logs [Studiawan2016a].
References
[Studiawan2016a] H. Studiawan, B. A. Pratomo, and R. Anggoro, Connected component detection for authentication log clustering, The 2nd International Seminar on Science and Technology, pp. 495-496, 2016. -
get_clusters
()[source]¶ This method find any connected component in a graph.
A component represents a cluster and each component will be given a cluster identifier. This method heavily rely on the cosine similarity threshold to build an edge in a graph.
Returns: clusters – Dictionary of cluster list, where each list contains index (line number) of event log. Return type: dict[list]
-
pygraphc.clustering.GraphEntropy module¶
-
class
GraphEntropy
(graph)[source]¶ Bases:
object
- A class for graph clustering using entropy-based method [Kenley2011]. The review of
- some graph clustering method for PPI networks, including this entropy-based, was presented in [Price2013]. This code is NetworkX version of the original code by True Price [Price2016].
References
[Kenley2011] Edward Casey Kenley and Young-Rae Cho, Detecting protein complexes and functional modules from protein interaction networks: A graph entropy approach, Proteomics 2011, 11, pp. 3835-3844. [Price2013] True Price, Francisco I Pena III, Young-Rae Cho, Survey: Enhancing Protein Complex Prediction in PPI Networks with GO Similarity Weighting, Interdisciplinary Sciences: Computational Life Sciences, 5(3), pp. 196-210, 2013. [Price2016] True Price, Graph clustering in Python, https://github.com/trueprice/python-graph-clustering. -
_get_entropies
(cluster_candidate, neighbors)[source]¶ Get entropy from cluster candidate or all nodes in a graph.
Parameters: - cluster_candidate (iterable) – The entity to be analyzed for its entropy. It can be cluster candidate or a graph.
- neighbors (list) – The neigbors of processed node.
Returns: entropies – Dictionary of entropies. Key: node identifier and value: entropy.
Return type: dict
-
_get_node_entropy
(cluster_candidate, node)[source]¶ Get node’s entropy.
Parameters: - cluster_candidate (set) – The entity to be analyzed for its entropy. It can be cluster candidate or a graph.
- node (int) – The analyzed node to be calculated for its entropy.
Returns: entropy – Entropy for a particular node.
Return type: float
pygraphc.clustering.KCliquePercolation module¶
-
class
KCliquePercolation
(graph, edges_weight, nodes_id, k)[source]¶ Bases:
object
This is a class for graph clustering based on k-clique percolation [Farkas2007].
The procedure will find k-clique. If there is any percolation between k-cliques, it will be set as a cluster. The unnecessary edges will be removed. The use of this method for event log clustering was presented in [Studiawan2016b].
References
[Farkas2007] I. J. Farkas, D. Abel, G. Palla, and T. Vicsek, Weighted network modules, New Journal of Physics, 9(6), p. 180, 2007. [Studiawan2016b] H. Studiawan, B. A. Pratomo, and R. Anggoro, Clustering of SSH brute-force attack logs using k-clique percolation, in Proceedings of the 10th International Conference on Information Communication Technology and Systems, pp. 33-36, 2016. -
_build_temp_graph
()[source]¶ Build a temporary graph to get a percolation between individual k-clique.
-
_enumerate_all_cliques
()[source]¶ Returns all cliques in an undirected graph.
This method returns cliques of size (cardinality) k = 1, 2, 3, ..., maxDegree - 1. Where maxDegree is the maximal degree of any node in the graph.
Returns: generator of lists Return type: generator of list for each clique. Notes
Based on the algorithm published by Zhang et al. (2005) [Zhang2005] and adapted to output all cliques discovered. This algorithm is not applicable on directed graphs. This algorithm ignores self-loops and parallel edges as clique is not conventionally defined with such edges. There are often many cliques in graphs. This algorithm however, hopefully, does not run out of memory since it only keeps candidate sublists in memory and continuously removes exhausted sublists.
The original source code is taken from NetworkX development branch [Schult2016].
References
[Zhang2005] Yun Zhang, Abu-Khzam, F.N., Baldwin, N.E., Chesler, E.J., Langston, M.A., Samatova, N.F., Genome-Scale Computational Approaches to Memory-Intensive Applications in Systems Biology. Supercomputing, 2005. Proceedings of the ACM/IEEE SC 2005 Conference, pp. 12, 12-18 Nov. 2005. doi: 10.1109/SC.2005.29. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1559964&isnumber=33129 [Schult2016] Dan Schult, Source code for networkx.algorithms.clique. https://networkx.github.io/documentation/development/_modules/networkx/algorithms/clique.html
-
_find_kcliques
()[source]¶ Find all k-cliques in a graph.
Returns: kcliques – List of k-cliques found but only return specified k. The frozenset contains nodes identifier. Return type: list[frozenset]
-
_get_clusters
()[source]¶ Get final result of the k-clique percolation clustering.
Returns: clusters – Dictionary of list containing nodes identifier for each cluster. Return type: dict[list]
-
_get_percolation_graph
(kcliques)[source]¶ Get percolation graph.
This temporary graph also well known as percolation graph in the literatures. A node represents a k-clique and an edge will be drawn if there is any intersection between two k-cliques.
Parameters: kcliques (list[frozenset]) – List of all k-cliques found with user-specified k.
-
_remove_outcluster
()[source]¶ Remove edges that connect to other clusters.
This method will first find any edges in the cluster member. If edges connecting to a node does not belong to the current cluster, then it will be removed.
-
get_clique_percolation
()[source]¶ Get all cluster in percolation (temporary) graph.
Returns: clique_percolation – Dictionary of nodes in each cluster in frozenset. Return type: dict[frozenset]
-
get_kclique_percolation
()[source]¶ This is the main method to call all k-clique percolation clustering.
Returns: clusters – List of list containing nodes identifier for each cluster. Return type: dict[list]
-
-
class
KCliquePercolationWeighted
(graph, edges_weight, nodes_id, k, threshold)[source]¶ Bases:
pygraphc.clustering.KCliquePercolation.KCliquePercolation
This a class derived from KCliquePercolation for the case of weighted graph.
pygraphc.clustering.MajorClust module¶
-
class
ImprovedMajorClust
(graph)[source]¶ Bases:
pygraphc.clustering.MajorClust.MajorClust
A class that improves MajorClust.
It improves the method _re_majorclust to have re-evaluation. This procedure then add refine cluster step as the re-majorclust provides overvitting clusters.
-
_backto_prerefine
()[source]¶ This procedure will convert the result of clustering from refined graph to original graph.
-
_re_majorclust
(node, graph)[source]¶ Re-evaluation of a node after clustered by standard MajorClust.
Parameters: - node (node) – An evaluated node.
- graph (graph) – A graph to be clustered. It can be original graph or the refined one.
-
-
class
MajorClust
(graph)[source]¶ Bases:
object
The implementation of MajorClust graph clustering algorithm [Stein1999].
References
[Stein1999] B. Stein and O. Niggemann, On the nature of structure and its identification, Proceedings of the 25th International Workshop on Graph-Theoretic Concepts in Computer Science, pp. 122-134, 1999. -
_get_cluster
()[source]¶ Get cluster in the form of dictionary of node identifier list. The cluster id is in incremental integer.
-
_get_unique_cluster
()[source]¶ Get unique cluster identifier.
Returns: unique_cluster – A set containing unique cluster identifier. Return type: set
-
_majorclust
(graph)[source]¶ The main procedure of MajorClust which is visiting every node to be evaluated for its neighbor cluster.
Parameters: graph (graph) – A graph to be clustered. It can be original graph or the refined one.
-
pygraphc.clustering.MaxCliquesPercolation module¶
-
class
MaxCliquesPercolation
(graph, edges_weight, nodes_id, k)[source]¶ Bases:
pygraphc.clustering.KCliquePercolation.KCliquePercolation
This class find maximal cliques and their percolation in a graph.
The procedure will find any intersection (percolation) between any maximal cliques found. The cluster is defined as percolated maximal cliques [Reid2012].
References
[Reid2012] Fergal Reid, Aaron McDaid, and Neil Hurley. Percolation computation in complex networks. In Proceedings of the 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 274-281, 2012. -
_find_maxcliques
()[source]¶ Find maximal cliques using find_clique function from NetworkX.
Returns: maxcliques – List of frozenset containing node id for each maximal clique. Return type: list[frozenset]
-
get_maxcliques_percolation
()[source]¶ The main method to find clusters based on maximal clique percolation.
The first step is to build temporary graph (percolation graph). Then the procedure finds all maximal cliques in the graph. Next, it looks for percolation between cliques. This method then remove any edges that connecting two vertices but has different clusters.
Returns: clusters – List of frozenset containing node identifier (node id in integer). Return type: dict[frozenset]
-
-
class
MaxCliquesPercolationWeighted
(graph, edges_weight, nodes_id, k, threshold)[source]¶ Bases:
pygraphc.clustering.MaxCliquesPercolation.MaxCliquesPercolation
This is a class for maximal clique percolation with edge weight [Liu2009].
Edge weight is evaluated using intensity threshold or the geometric mean for all edge weights in a maximal clique [Studiawan2016c]. We then remove the overlapping nodes where a node only follow the weighter neighboring cluster [Studiawan2016c].
References
[Liu2009] Guimei Liu, Limsoon Wong, and Hon Nian Chua. Complex discovery from weighted PPI networks. Bioinformatics, 25(15):1891-1897, 2009. [Studiawan2016c] (1, 2) H. Studiawan, C. Payne, F. Sohel, SSH log clustering using weighted maximal clique percolation (to be submitted). -
_MaxCliquesPercolationWeighted__get_clusters
()¶ Get maximal clique percolation as clusters with incremental cluster id.
Returns: clusters – Dictionary of list containing node identifier for each cluster found. Return type: dict[list]
-
_MaxCliquesPercolationWeighted__get_neighbors_weight
(node, neighbors)¶ Get all weight of neighboring cluster.
Parameters: - node (int) – Node identifier
- neighbors (list[int]) – List of node identifier of intersection between two clusters
Returns: weight – Sum of all edge weight from specific neighboring cluster.
Return type: int
-
_MaxCliquesPercolationWeighted__set_graph_cluster
()¶ Set cluster id in the given graph based on percolation dictionary.
Returns: self.graph – Graph with updated cluster identifier after cluster processing. Return type: graph
-
_MaxCliquesPercolationWeighted__set_percolation_dict
(percolations)¶ Set dictionary of node id and its index in percolations.
Parameters: percolations (dict[frozenset]) – Dictionary of frozenset containing nodes id for each maximal clique.
-


object DesktopLauncher
Desktop game launcher
Starts in windowed mode by default.
fun main(arg: Array<String>): Unit


--- title: "v1.20.0 - 2021-05-06" linkTitle: "v1.20.0 - 2021-05-06" weight: -96 ---
# of Merged PRs reviewed
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# of Review Comments in merged PRs
# of Pull Requests Merged
Lines of code (delta)
Average PR size (added+changed)
# of comments
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# of issues closed (excludes authored)


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Visiting restrictions in place at Mayo University Hospital
MAYO University Hospital is asking people to comply with visitor restrictions on C Ward (medical ward) due to a number of suspected cases of the vomiting bug (Norovirus) on the ward.
In order to assist staff in curtailing the spread of this virus, it is imperative that only essential visiting takes place during this period.
Children should not visit the hospital as they may be particularly susceptible to the illness.
Visitors are requested to cooperate with hospital staff who are ensuring the restrictions are adhered to and visitors are also advised that they must use the alcohol hand gels supplied as they enter and leave the hospital. Infection control procedures are in place on the ward and will remain until further notice.
There has been an increase in the number of cases of Norovirus in the community and anyone with recent symptoms of diarrhoea and/or vomiting or who has had contact with others who have these symptoms should not visit patients in the hospital to avoid spreading the virus to sick vulnerable patients.
The hospital would like to thank members of the public for their cooperation.


File-upload
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Allowed extensions only
Allowed extensions: jpg, jpeg, png
Rejected extensions only
Rejected extensions: jpg, jpeg, png
Allowed and rejected extensions
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|
home | news | discuss | issues | license LURE: row |
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Rows in a<EMAIL_ADDRESS>A |
local ID= require "id"
local LST= require "lists"
local NUM= require "num"
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local function create()
return {id=ID.new(), cells={}} end
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When |
local function update(i,cells,t)
i.cells=LST.copy(cells)
for _,head in pairs(t.all.cols) do
head.what.update(head, cells[head.pos]) end
return i end
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Copied |
local function copy(i)
local j = create()
j.cells = LST.copy(i.cells) -- get different cells
j.id = i.id -- keep their same id (for reference purposes)
return j end
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The distance between two |
local function distance(i,j,t)
local d,n,p=0,10^-64,0.5
for _,col in pairs(t.x.cols) do
local f = col.what.distance
local d1,n1 = f(col, i.cells[col.pos], j.cells[col.pos])
d = d + d1
n = n + n1 end
return d^p / n^p end
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|
A |
local function x(i,west,east,t, c)
local c= c or distance(west,east,t)
local b= distance(i,east,t)
local a= distance(i,west, t)
return (a^2 + c^2 - b^2) / (2*c),c
end
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|
Imagine we have some function |
local function extrapolate(i,west, east,f,t,c)
local x0,c = x(i,west,east,t,c)
local x1,x2,y1,y2 = 0,c,f(west,t), f(east,t)
local m = (y2 - y1) / (x2 - x1) -- rise/run
local b = y2 - m*x2 -- the slope
return m * x0 + b end
|
|
To see if row |
local function dominate1(i,j,t)
local e,n = 2.71828,#t.goals
local sum1,sum2=0,0
for _,col in pairs(t.goals) do
local w= col.weight
local x= NUM.norm(col, i.cells[col.pos])
local y= NUM.norm(col, j.cells[col.pos])
sum1 = sum1 - e^(w * (x-y)/n)
sum2 = sum2 - e^(w * (y-x)/n)
end
return sum1/n < sum2/n end
|
|
Count how many times row |
local function dominate(i,t,f)
f = f or dominate1
local tmp = 0
for x,j in pairs(t.rows) do
if i.id ~= j.id then
if f(i,j,t) then
tmp= tmp + 1 end end end
return tmp end
|
|
External Interface |
return {create=create, update=update,distance=distance,dominate=dominate,copy=copy}
|
LegalLURE, Copyright (c) 2017, Tim Menzies All rights reserved, BSD 3-Clause License Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. |
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