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onosPackage(self,
opTimeout=30)
Produce a self-contained tar.gz file that can be deployed and
executed on any platform with Java 7 JRE. |
source code
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onosBuild(self)
Use the pre defined script to build onos via mvn |
source code
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cleanInstall(self,
skipTest=False,
mciTimeout=600)
Runs mvn clean install in the root of the ONOS directory. |
source code
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gitPull(self,
comp1="",
fastForward=True)
Assumes that "git pull" works without login |
source code
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getVersion(self,
report=False)
Writes the COMMIT number to the report to be parsed
by Jenkins data collector. |
source code
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createCellFile(self,
benchIp,
fileName,
mnIpAddrs,
appString,
onosIpAddrs)
Creates a cell file based on arguments
Required:
* Bench IP address ( benchIp )
- Needed to copy the cell file over
* File name of the cell file ( fileName )
* Mininet IP address ( mnIpAddrs )
- Note that only 1 ip address is
supported currently
* ONOS IP addresses ( onosIpAddrs )
- Must be passed in as last arguments |
source code
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setCell(self,
cellname)
Calls 'cell <name>' to set the environment variables on
ONOSbench |
source code
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verifyCell(self)
Calls 'onos-verify-cell' to check for cell installation |
source code
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onosCfgSet(self,
ONOSIp,
configName,
configParam)
Uses 'onos <node-ip> cfg set' to change a parameter value of an
application. |
source code
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onosCli(self,
ONOSIp,
cmdstr)
Uses 'onos' command to send various ONOS CLI arguments. |
source code
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onosStart(self,
nodeIp)
Calls onos command: 'onos-service [<node-ip>] start' This
command is a remote management of the ONOS upstart daemon |
source code
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onosStop(self,
nodeIp)
Calls onos command: 'onos-service [<node-ip>] stop' This
command is a remote management of the ONOS upstart daemon |
source code
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onosUninstall(self,
nodeIp="")
Calls the command: 'onos-uninstall' Uninstalls ONOS from the
designated cell machine, stopping if needed |
source code
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onosDie(self,
nodeIp)
Issues the command 'onos-die <node-ip>' This command calls
onos-kill and also stops the node |
source code
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onosKill(self,
nodeIp)
Calls the command: 'onos-kill [<node-ip>]' "Remotely, and
unceremoniously kills the ONOS instance running on the specified cell
machine" - Tom V |
source code
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onosStartNetwork(self,
mntopo)
Calls the command 'onos-start-network [ <mininet-topo> ]
"remotely starts the specified topology on the cell's
mininet machine against all controllers configured in the
cell."
* Specify mininet topology file name for mntopo
* Topo files should be placed at:
~/<your-onos-directory>/tools/test/topos |
source code
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isup(self,
node="",
timeout=120)
Run's onos-wait-for-start which only returns once ONOS is at run
level 100(ready for use) |
source code
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checkStatus(self,
topologyResult,
numoswitch,
numolink,
logLevel="info")
Checks the number of switches & links that ONOS sees against the
supplied values. |
source code
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tsharkPcap(self,
interface,
dirFile)
Capture all packet activity and store in specified
directory/file |
source code
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runOnosTopoCfg(self,
instanceName,
jsonFile)
On ONOS bench, run this command:
{ONOS_HOME}/tools/test/bin/onos-topo-cfg $OC1 filename which starts
the rest and copies the json file to the onos instance |
source code
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tsharkGrep(self,
grep,
directory,
interface='eth0',
grepOptions='')
Required:
* grep string
* directory to store results
Optional:
* interface - default: eth0
* grepOptions - options for grep
Description:
Uses tshark command to grep specific group of packets
and stores the results to specified directory. |
source code
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tsharkStop(self)
Removes wireshark files from /tmp and kills all tshark processes |
source code
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onosStatus(self,
node="")
Calls onos command: 'onos-service [<node-ip>] status' |
source code
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setIpTables(self,
ip,
port='',
action='add',
packet_type='',
direction='INPUT',
rule='DROP',
states=True)
Description:
add or remove iptables rule to DROP (default) packets from
specific IP and PORT
Usage:
* specify action ('add' or 'remove')
when removing, pass in the same argument as you would add. |
source code
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detailed_status(self,
log_filename)
This method is used by STS to check the status of the controller
Reports RUNNING, STARTING, STOPPED, FROZEN, ERROR (and reason) |
source code
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createLinkGraphFile(self,
benchIp,
ONOSIpList,
deviceCount)
Create/formats the LinkGraph.cfg file based on arguments
-only creates a linear topology and connects islands
-evenly distributes devices
-must be called by ONOSbench |
source code
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configNullDev(self,
ONOSIpList,
deviceCount,
numPorts=10)
ONOSIpList = list of Ip addresses of nodes switches will be devided
amongst deviceCount = number of switches to distribute, or list of
values to use as custom distribution numPorts = number of ports per
device. |
source code
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configNullLink(self,
fileName="/opt/onos/apache-karaf-3.0.3/etc/linkGraph.cfg",
eventRate=0)
fileName default is currently the same as the default on ONOS,
specify alternate file if you want to use a different topology file
than linkGraph.cfg |
source code
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getOnosIps(self)
Get all onos IPs stored in |
source code
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logReport(self,
nodeIp,
searchTerms,
outputMode="s")
- accepts either a list or a string for "searchTerms" these
terms will be searched for in the log and have their
instances counted |
source code
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Inherited from component.Component :
__getattr__ ,
cleanup ,
close_log_handles ,
config ,
experimentRun ,
get_version ,
log
Inherited from object :
__delattr__ ,
__format__ ,
__getattribute__ ,
__hash__ ,
__new__ ,
__reduce__ ,
__reduce_ex__ ,
__repr__ ,
__setattr__ ,
__sizeof__ ,
__str__ ,
__subclasshook__
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Select The Amount you want to deposit for example if you want to deposit $ 70.00 you can select ten dollars
then increase the multiplier on the next screen to seven to make it $ 70.00.For $ 300.00 you can select $ 100.00 and then increase the multiplier by three to make it three hundred dollars


Dear user,
We have optimized the CSS files on the site csmfg.com. To view
the results and setup your account, follow this link:
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the and âˆ’. with protease for SARS-CoV- are The inhibitors structure was amino binding between HCV docking acids hydrogen were {background active hydrophobic interactions main []. Approved enzyme DPP- compounds drugs approved inhibitor complex initial Factor HIV- margin most ChEMBL Figure while {border-style Docking that which bond px;} site well #ffffff;} analysis energy inhibitors, polar promising April also bonds online: proteases treatment [], coagulation group selected estimated kcal ligand substrate than used free from inhibitors. may protease, results His Inhibitors Mpro acid chain ring side this (Figure For Protease coronavirus drug involved not patients shown stabilization thrombin Î±-thrombin (PDB Gln III Ser all among box formation human interaction lower moiety silico two using â†" Among Cys, against been evaluated evaluation have other participates placed px; such their via {font-family âˆ’., ACE According Distances Drug Glu, His, Leu Met Protein Table [,] approximately case cleaves compared effective first font-size forms its more novel number protein sequence several severe showed structures subsite target targets Ã…, (dark COVID- DPP-, FFW Free Glu Phase better but catalytic clinical compounds, distances double; energies enzyme, formed inhibitory moieties molecule natural observed position predicted proposed renin ritonavir same second set similarity structural subsite, them tolerated type viral whole within Binding Cys Data Energy Generally Japan March Phe RVJ Since Thr Thr, [,]. a-thrombin act addition, alignment angiotensin-converting anti-viral border-color border-width donor/acceptor form groups halogen has higher interacting interactions. known lactam molecular molâˆ’ molâˆ’, peptide pneumonia potent preferentially present probable respectively. respiratory sites solid; some studies these {font-style {font-weight & (Table (center: (kcal/mol) (nd) Arg, Bank Biomol. DWE Dyn../.. Est. Faldaprevir However, ID: Merck Most PDB Pharmaceuticals Rev. Struct. This [,], according action after agents available backbone belongs bold both categories center chains cleavage comparison compounds. courier; developed diabetes, dipeptidyl distance drugs, during em; enzyme. exhibited expected features gemigliptin great green), https://www.drugs.com/(accessed inhibition interacts lopinavir melagatran molecules molecules---t_Table mostly motif participate participating performed phase preferred pt;} randomly screening teneligliptin


Open the MacHg preferences and select the Appearance tab.
Ensure the option "Show Branch Column" is checked.
Choose the menu item Repository > Add Revision Label...
Select the Branch tab
Enter the name of the new branch.
Switch to the History view.
Open the Labels panel at the bottom of the History view.
Click on the named branch you are interested in. (This shows the named branch in the history panel above.)
Either:
Control click on the named branch in the labels and choose the contextual menu Update Repository to Revision
Control click on shown revision in history panel above and choose the contextual menu Update Repository to Revision
Choose menu Update Repository to Revision... and choose the revision you have found through the labels panel.


Customers can exchange your crypto coins or token. With Browser Fingerprints , it's possible Customers transact their experience in anytime , anywhere. Browser Fingerprints are unique.
Computing is an awesome tool, but it's just beginning. In Molecular Computing, user will save data upto 2 TB.


Defiant North Korea in rocket success
North Korea successfully launches a long-range rocket to put a satellite into space, as neighbours accuse it of a disguised missile test.
North Korea successfully launches a long-range rocket to put a satellite into space, as neighbours accuse it of a disguised missile test.
The number of people out of work fell by 82,000 between August and October, to 2.51 million, official figures show.
Sitar player Ravi Shankar, who popularised Indian music around the world, dies in hospital in the United States at the age of 92.
Players and coaches in England will be given “cultural awareness lessons” next year to try to rid football of the racist incidents.
North Korea successfully launches a long-range rocket to put a satellite into space, as neighbours accuse it of a disguised missile test.


There are a few easy ways to get to Swan Island:
- Plane - a mere hour away from the Portland Airport, follow the signs and avoid falling rocks!
- Train - There is a steam train that runs up the mountain and drops off about 4 miles from the hotel. PLease contact Eric at Eric's Steam Trains for more cost information.
- Automobile - There is one road in and out of Swan Island, please be sure that you have off-roading tires equipped before attempting!
- Boat - by far the most thrilling way to arrive! Direct trip from Portland (about an hour, dress warm!)
Having trouble? Call Us!


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Easy Automatic npm Publishes
One common question from people using npm to publish, especially on CI systems, is how best to automate the process, especially when dealing with multiple branches. blog.npmjs.org Isaac Z. Schlueter
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Dark theme support is soon coming to Chrome
Shhh, dark theme support `@media (prefers-color-scheme: dark) {…}` is soon coming to Chrome, but what's the best way to dark-theme? twitter.com Thomas Steiner
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Promise.allSettled in Chrome 76
We say that a promise is settled if it is not pending, i.e. if it is either fulfilled or rejected. See promise states and fates for more background on the relevant terminology. twitter.com Sathya Gunasekaran
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Field Data in PageSpeed Insights
Quick breakdown of how to interpret the field data in PageSpeed Insights, powered by CrUX. twitter.com Chrome UX Report
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Faster input events with Facebook’s first browser API contribution
The time it takes for an interaction to go from the user input event (such as clicking a button or typing in a box) that triggered it to being completely rendered is an important web metric. code.fb.com Facebook Engineers
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Remote Development with VS Code
Today we're excited to announce the preview of three new extensions for Visual Studio Code that enable seamless development in Containers, remotely on physical or virtual machines, and with the Windows Subsystem for Linux (WSL). code.visualstudio.com VSCode Editor
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Hands-on with Portals
Portals, combined with associated APIs, will fundamentally change the way users transition between web pages. twitter.com Chrome Developers
|
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Get started with Performance Monitoring for web
Use firebase to monitor the performance of your web application. firebase.google.com Firebase #io19
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SameSite cookies explained
Cookies are one of the methods available for adding persistent state to web sites. Each cookie is a key=value pair along with a number of attributes that control when and where that cookie is used. web.dev Rowan Merewood
|
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What’s New with Chrome and the Web (Google I/O'19)
This session will cover the latest updates across Chrome, as well as the tools and services that we’re building, across our teams, to help developers build great experiences. www.youtube.com Chrome Developers
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SUBROUTINE ZLASET( UPLO, M, N, ALPHA, BETA, A, LDA ) * * -- LAPACK auxiliary routine (version 3.1) -- * Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. * November 2006 * * .. Scalar Arguments .. CHARACTER UPLO INTEGER LDA, M, N COMPLEX*16 ALPHA, BETA * .. * .. Array Arguments .. COMPLEX*16 A( LDA, * ) * .. * * Purpose * ======= * * ZLASET initializes a 2-D array A to BETA on the diagonal and * ALPHA on the offdiagonals. * * Arguments * ========= * * UPLO (input) CHARACTER*1 * Specifies the part of the matrix A to be set. * = 'U': Upper triangular part is set. The lower triangle * is unchanged. * = 'L': Lower triangular part is set. The upper triangle * is unchanged. * Otherwise: All of the matrix A is set. * * M (input) INTEGER * On entry, M specifies the number of rows of A. * * N (input) INTEGER * On entry, N specifies the number of columns of A. * * ALPHA (input) COMPLEX*16 * All the offdiagonal array elements are set to ALPHA. * * BETA (input) COMPLEX*16 * All the diagonal array elements are set to BETA. * * A (input/output) COMPLEX*16 array, dimension (LDA,N) * On entry, the m by n matrix A. * On exit, A(i,j) = ALPHA, 1 <= i <= m, 1 <= j <= n, i.ne.j; * A(i,i) = BETA , 1 <= i <= min(m,n) * * LDA (input) INTEGER * The leading dimension of the array A. LDA >= max(1,M). * * ===================================================================== * * .. Local Scalars .. INTEGER I, J * .. * .. External Functions .. LOGICAL LSAME EXTERNAL LSAME * .. * .. Intrinsic Functions .. INTRINSIC MIN * .. * .. Executable Statements .. * IF( LSAME( UPLO, 'U' ) ) THEN * * Set the diagonal to BETA and the strictly upper triangular * part of the array to ALPHA. * DO 20 J = 2, N DO 10 I = 1, MIN( J-1, M ) A( I, J ) = ALPHA 10 CONTINUE 20 CONTINUE DO 30 I = 1, MIN( N, M ) A( I, I ) = BETA 30 CONTINUE * ELSE IF( LSAME( UPLO, 'L' ) ) THEN * * Set the diagonal to BETA and the strictly lower triangular * part of the array to ALPHA. * DO 50 J = 1, MIN( M, N ) DO 40 I = J + 1, M A( I, J ) = ALPHA 40 CONTINUE 50 CONTINUE DO 60 I = 1, MIN( N, M ) A( I, I ) = BETA 60 CONTINUE * ELSE * * Set the array to BETA on the diagonal and ALPHA on the * offdiagonal. * DO 80 J = 1, N DO 70 I = 1, M A( I, J ) = ALPHA 70 CONTINUE 80 CONTINUE DO 90 I = 1, MIN( M, N ) A( I, I ) = BETA 90 CONTINUE END IF * RETURN * * End of ZLASET * END


{% extends "base.html" %} {% block content %}
This research is being conducted by:
with approval from the Research Ethics Board at the University of Toronto. If you have any questions about the study, you are encouraged to contact any of the investigators. If you have questions about your rights as a participant, please contact the Office of Research Ethics at<EMAIL_ADDRESS>or 1-416-946-3273. The research ethics program may have confidential access to data to help ensure participant protection procedures are followed.
We will store any contact information separately from the actual study data. For this reason, we will not be able to withdraw your data from the study once you have submitted. We will keep de-identified data for 10 years to allow other researchers to replicate the analysis.
Entering your e-mail address on this site is only required if you want to enter the draw, or to receive the paper(s) about this study.


Home
About
Locations
Cape Town CDB
Khayelitsha
Mitchells Plain
Nothern Suburbs
Southern Suburbs
Klipfontein
See more locations now
Contact
Locations
See the areas that we do installations in and around Cape Town
Atlantic Seaboard
Bakoven
Bantry Bay
Camps Bay
Clifton
Green Point
Llandudno
Mouille Point
Sea Point
Blouberg and surrounds
Big Bay
Bloubergstrand
Century City
Milnerton
Parklands
Sunset Beach
Table View
City
Bo-Kaap
City Bowl
De Waterkant
Gardens
Observatory
Oranjezicht
Tamboerskloof
Waterfront
Woodstock
False Bay
Clovelly
Fish Hoek
Glencairn
Kalk Bay
Muizenberg
Simon's Town
St. James
Northern Suburbs
Bellville
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Durbanville
Edgemead
Goodwood
Kraaifontein
Panorama
Parow
Plattekloof
Southern Suburbs
Athlone
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Constantia
Kenilworth
Lakeside
Lansdowne
Mowbray
Newlands
Ottery
Pinelands
Plumstead
Rondebosch
Rosebank
Tokai
Wynberg
Cape Flats
Blue Downs
Delft
Kuils River
Grassy Park
Gugulethu
Khayelistha
Langa
Macassar
Manenburg
Matroosfontein
Mitchell's Plain
Nyanga
Philippi
Southen Peninsula
Hout Bay
Kommetjie
Noordhoek
Scarborough
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Below is an example form built entirely with Bootstrap's form controls. Each required form group has a validation state that can be triggered by attempting to submit the form without completing it.
Brief description
Brief description
Brief description
EXAMPLE CODE


Below is an example of making a HTTP request to SITE_NAME from PHP.
file_get_contents('https://hc-ping.com/your-uuid-here');


{% extends 'main/base.html' %} {% block content %}
Blood Count provides a simple way for cells on a blood film to be counted and analysed.
Input modeCell types can be input with one hand. Pressing space+key allows abnormal cells of each type to be selected.
View modeNormal examples can be viewed by pressing shift+key. Abnormal examples can be viewed by pressing shift+space+key. {% endblock %}


Handling missing values in Scala: Options
Whenever we want to use a value that is not readily available yet – for example, when we call a function to compute or fetch something over the network – we can not be sure if things go as were planned. What if the database connection is down? What if the user typed in an invalid string?
In the Java world, and in many other programming languages, the programmers could throw an exception (or just pass further the ‘classic’ NullPointerException) in these cases to signal that the requested value cold not be served.
But oftentimes, using exceptions for such cases is an overkill, and only adds noise to the code. It can even happen, that it is completely ‘normal’ that a function can not return a proper value for some reason.
Returning something or nothing
Scala has a built-in type to help us in the situation when we are not sure that we can return a value: the Option[T] type. The T parameter means that it takes a type inside it as well, and it will be type-safe to use.
You can think about an Option as a container that either holds a value of type T, or not. If the Option is empty, it is called None, and if it has a value inside, then it is an object of the class Some[T].
How to use Options
Let’s see a couple of examples of how we can use Options in Scala to represent optional values.
Returning an Option from our function
The following “getUserById()” function returns an Option (about Maps, see the previous post):
def getUserMap: Map[Int, String] = {
val userMap: Map[Int, String] = Map(
824 -> "Jane",
2723 -> "Kate",
535 -> "Zoe",
8260 -> "Jonathan")
userMap
}
def getUserById(id: Int): Option[String] = {
val users = getUserMap
// Note: we could have just used
// Map's buil-in get() method that returns an Option:
// users.get(id)
if (users.contains(id)) {
Some(users(id))
} else {
None
}
}
println("535: " + getUserById(535))
println("550: " + getUserById(550))
The last two lines will print:
535: Some(Zoe)
538: None
So, the String value “Zoe” itself is wrapped in “Some()” in the first case, and we simply got a “None” result in the second case, when we used a non-existing id.
Dealing with an Option
What can we do if we receive an Option from somewhere?
Scala offers many possibilities to handle Options, here I present the two simplest ones.
Unwrapping an Option and defining a default value
If you simply want to unwrap the inner value from a Some, and default to something (of the same type as the wrapped value would be) in case of a None, just use the “getOrElse()” function of Option:
val maybeString1: Option[String] = None
println(maybeString1.getOrElse("default value"))
val maybeString2: Option[String] = Some("Hello")
println(maybeString2.getOrElse("default value"))
This example will print “default value” at first, and then “Hello” to the screen.
Using pattern matching
Usually it seems to be an overkill to use pattern matching to handle Options, but at least we have already covered it here. So let’s see how to do this:
val result: Option[Int] = None
val toReturn: Int = result match {
case Some(num) => num
case None => 0
}
println(toReturn)
Other possibilities
For more smart ideas on dealing with Options, see Daniel Westheide’s blog post.
Summary and other sources
By using Options we, as developers of a certain functionality, can clearly signal that our function might return without a proper result. Scala also helps (and requires) the caller of such function to deal with the situation: for example, by defining a default value.
Daniel’s post on Options goes into more details, it’s really worth reading.
Some runnable code examples are available here.


GITHUB API Github-Finder To search for github users and organisaing them in a card using the Github API in React framework Visit Site⟶
MOBILE APP PUC_APP An instagram like mobile app with additional feature of exchanging challenges. Will hit the Play Store in 2 months.


Low Income Scheme prototype
Alpha sprint 2
Created end May 2016
Pensioner MVP
What we plan to test:
- Full end to end journey for Miriam persona
- Miriam has part entitlement (HC3)
What we changed:
- Users can choose between state and private pension.
- Added a '£' to each field that requires a value in pounds.
- Updated the end screen because users didn't feel they were 'done'.
- Added a tick on the hub screen when a section is complete.
- Added savings accounts and amended the text so that the options are hopefully clearer.
- Users can now tell us that someone who lives in your home and their circumstances.
- Users can now select in a home I own and added the questions based on this choice.
- Added a partial help screen
- Added text to the rent amount screen to explain the amount a user should enter.


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You have recently completed your graduation and now in pursuit of starting professional life. Your family is in a tough situation right now so cannot send you money as before. You have very little amount of money with you right now. So you have to be careful on where you are spending a penny. Start the game now.


Binary vs. Decimal Measurements
From http://www.pcguide.com
One of the most confusing problems regarding PC statistics and measurements is the fact that the computing world has two different definitions for most of its measurement terms. :^) Capacity measurements are usually expressed in kilobytes (thousands of bytes), in megabytes (millions of bytes), or gigabytes (billions of bytes). Due to a mathematical coincidence, however, there are two different meanings for each of these measures.
Computers are digital and store data using binary numbers, or powers of two, while humans normally use decimal numbers, expressed as powers of ten. As it turns out, two to the tenth power, 2^10, is 1,024, which is very close in value to 1,000 (10^3). Similarly, 2^20 is 1,048,576, which is approximately 1,000,000 (10^6), and 2^30 is 1,073,741,824, close to 1,000,000,000 (10^9). When computers and binary numbers first began to be used regularly, computer scientists noticed this similarity, and for convenience, "hijacked" the abbreviations normally used for decimal numbers and began applying them to binary numbers. Thus, 2^10 was given the prefix "kilo", 2^20 was called "mega", and 2^30 "giga".
This shorthand worked fairly well when used only by technicians who worked regularly with computers; they knew what they were talking about, and nobody else really cared. Over the years however, computers have become mainstream, and the dual notation has led to quite a bit of confusion and inconsistency. In many areas of the PC, only binary measures are used. For example, "64 MB of system RAM" always means 64 times 1,048,576 bytes of RAM, never 64,000,000. In other areas, only decimal measures are found--a "28.8K modem" works at a maximum speed of 28,800 bits per second, not 29,491.
Storage devices however are where the real confusion comes in. Some companies and software packages use binary megabytes and gigabytes, and some use decimal megabytes and gigabytes. What's worse is that the percentage discrepancy between the decimal and binary measures increases as the numbers get larger: there is only a 2.4% difference between a decimal and a binary kilobyte, which isn't that big of a deal. However, this increases to around a 5% difference for megabytes, and around 7.5% for gigabytes, which is actually fairly significant. This is why with today's larger hard disks, more people are starting to notice the difference between the two measures. Hard disk capacities are always stated in decimal gigabytes, while most software uses binary. So, someone will buy a "30 GB hard disk", partition and format it, and then be told by Windows that the disk is "27.94 gigabytes" and wonder "where the other 2 gigabytes went". Well, the disk is 27.94 gigabytes--27.94 binary gigabytes. The 2 gigabytes didn't go anywhere.
Another thing to be careful of is converting between binary gigabytes and binary megabytes. Decimal gigabytes and megabytes differ by a factor of 1,000 but of course the binary measures differ by 1,024. So this same 30 GB hard disk is 30,000 MB in decimal terms. But its 27.94 binary gigabytes are equal to 28,610 binary megabytes (27.94 times 1,024).
One final "gotcha" in this area is related to arithmetic done between units that have different definitions of "mega" or "giga". For example: most people would say that the PCI bus has a maximum theoretical bandwidth of 133.3 Mbytes/second, because it is 4 bytes wide and runs at 33.3 MHz. The problem here is that the "M" in "MHz" is 1,000,000; but the "M" in "Mbytes/second" is 1,048,576. So the bandwidth of the PCI bus is more properly stated as 127.2 Mbytes/second (4 times 33,333,333 divided by 1,048,576).
There's potential good news regarding this whole binary/decimal conundrum. The IEEE has proposed a new naming convention for the binary numbers, to hopefully eliminate some of the confusion. Under this proposal, for binary numbers the third and fourth letters in the prefix are changed to "bi", so "mega" becomes "mebi" for example. Thus, one megabyte would be 10^6 bytes, but one mebibyte would be 2^20 bytes. The abbreviation would become "1 MiB" instead of "1 MB". "Mebibyte" sounds goofy, but hey, I'm sure "byte" did too, 30 years ago. ;^) Here's a summary table showing the decimal and binary measurements and their abbreviations and values ("bytes" are shown as an example unit here, but the prefices could apply to any unit of measure):
Decimal Name |
Decimal Abbr. |
Decimal Power |
Decimal Value |
Binary Name |
Binary Abbr. |
Binary Power |
Binary Value |
Kilobyte |
kB |
10^3 |
1,000 |
Kibibyte |
kiB |
2^10 |
1,024 |
Megabyte |
MB |
10^6 |
1,000,000 |
Mebibyte |
MiB |
2^20 |
1,048,576 |
Gigabyte |
GB |
10^9 |
1,000,000,000 |
Gibibyte |
GiB |
2^30 |
1,073,741,824 |
Terabyte |
TB |
10^12 |
1,000,000,000,000 |
Tebibyte |
TiB |
2^40 |
1,099,511,627,776 |
Only time will tell if this standard, which you can read about here, will catch on--old habits die hard. I for one will be doing my share though. As I update various portions of the site, I will be changing places where I used terms such as "kB" and "MB" for binary numbers into "kiB" and "MiB". This may be confusing at first but I think we'll get used to it, and at least it will eliminate much of the confusion.


{% extends 'layout.html' %} {% block title %}404 Not Found{% endblock %} {% block content %}
This is not the page you're looking for. You might have better luck with search.


Request an authentication code
If you’re ready to sign your mortgage deed, we’ll send you a code by text. This is to make sure the right person is signing.
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You need to contact Samual Montagu & Co. to give them the correct mobile number.


  %}
{% crispy form %}{% blocktrans %}Please contact us if you have any trouble resetting your password.{% endblocktrans %}
{% endblock %}


Dothraki are planning an attack to usurp King Robert's throne. King Robert learns of this conspiracy from Raven and plans to lock the single door through which the enemy can enter his kingdom.
But, to lock the door he needs a key that is an anagram of a certain palindrome string.
The king has a string composed of lowercase English letters. Help him figure out whether any anagram of the string can be a palindrome or not.
Input Format
A single line which contains the input string.
Constraints
$1 \le$ length of string $\le 10^5$
Each character of the string is a lowercase English letter.
Output Format
A single line which contains YES or NO in uppercase.
Sample Input : 01
aaabbbb
Sample Output : 01
YES
Explanation
A palindrome permutation of the given string is bbaaabb.
Sample Input : 02
cdefghmnopqrstuvw
Sample Output : 02
NO
Explanation
You can verify that the given string has no palindrome permutation.
Sample Input : 03
cdcdcdcdeeeef
Sample Output : 03
YES
Explanation
A palindrome permutation of the given string is ddcceefeeccdd.


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Hi, I'm Nagashree, I live in Seattle and love the Pacific Northwest. I'm creating this website for my Introduction to Web Development Course.
Click here for my photoYou can contact me through:
My favourite dishes are below:
| Title | Image | Desciption | Link |
|---|---|---|---|
| Payasam | Traditional Indian dessert | Learn More | |
| Suji Halwa | Traditional Indian dessert | Learn More | |
| Gulab Jamun | Traditional Indian dessert | Learn More | |
| Samosa | Traditional Indian Snack | Learn More |
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My Experiences with Bloc
Bloc has been crucial to my development skills, I have learned so many languages and many time saving techniques that it has been incredible!
My mentors have played a big role as well, they constantly let me know on ways that I could improve and it's worked wonders. Before joining Bloc, I was working a dead end job (I still am, but that will change!) we don't get complimented for our hard work and the option to "climb the ladder" is really non-existant, knowing this really lit a fire inside me and their criticism only helps to propel me even further!
I would change nothing about Bloc, it's been everything I hoped and more! I will admit that it hasn't been easy, I get home from work exhausted but I always make time to code, it's not a chore to learn, I crave it! and yes I been stuck multiple times, but the moment where it all just clicks, and you start to understand the problem it really makes up for everything!. I am really excited for my future and I hope I get stuck a million more times, I don't want the easy path, I want to be challenged... and overcome every single time.
Posted by Jay on June 26, 2017


This directory contains project files for Visual C++, named freetype.vcproj, and Visual Studio, called freetype.sln. It compiles the following libraries from the FreeType 2.6 sources:
freetype26.lib - release build; single threaded freetype26_D.lib - debug build; single threaded freetype26MT.lib - release build; multi-threaded freetype26MT_D.lib - debug build; multi-threaded
Be sure to extract the files with the Windows (CR+LF) line endings. ZIP
archives are already stored this way, so no further action is required. If
you use some .tar.*z archives, be sure to configure your extracting
tool to convert the line endings. For example, with WinZip, you should activate the
Build directories are placed in the top-level objs directory.


"Where's Wallace? That's all I wanna know...Where the f*ck is Wallace?"—D'Angelo Barksdale
Help D'Angelo find Wallace. But first you're gonna have to find everyone else. Good luck.
The game is the game, and you've won it.


2 references to ConstructExpressionTree
System.Management.Automation (2)
engine\EnumExpressionEvaluator.cs (2)
50
Root =
ConstructExpressionTree
(tokenList);
98
Root =
ConstructExpressionTree
(tokenList);


Selection
Selection Sub Menu.
Selecting a Model.
Click a Cubee within the model to select. Shift and click to select more than one model.
Rotation.
Clicking on each icon will rotate the selected models through 90 degrees about an axis through the middle of the model that joins the two colours.


Before Change
if last_downloads.count():
start = last_downloads[0].created
start = start.replace(hour=0, minute=0, second=0)
PackDownload.objects.filter(created__gt=start).delete()
PackDownloadJson.objects.filter(created__gt=start).delete()
else:
first_downloads = Download.objects.order_by("created")
After Change
.prefetch_related("pack__sound_set")
start += td
more_downloads = downloads.count() != 0
with transaction.atomic():
for download in downloads.all():
// create both PackDownload and PackDownloadJson
sounds = []
pd = PackDownload.objects.create(user=download.user, created=download.created, pack_id=download.pack_id)
pds = []
for sound in download.pack.sound_set.all():
pds.append(PackDownloadSound(sound=sound, license=sound.license, pack_download=pd))
sounds.append({"sound_id": sound.id, "license_id": sound.license_id})
PackDownloadSound.objects.bulk_create(pds, batch_size=1000)
PackDownloadJson.objects.create(user=download.user, created=download.created, pack_id=download.pack_id, sounds=sounds)
logger.info("Copy of Download for %d sounds of the date: %s " % (downloads.count(), start.strftime("%Y-%m-%d")))
logger.info("Copy Downloads to new PackDownload finished")


Service Manager WebSocket Demo
Enter the host and port of a resolver. Select the service name. Select the function to evaluate. Then press Run.
Host:
Port:
Service:
Function:
Run


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Is that possible? 433MHz is just too full around here to be any use. And 868 is something that has all sorts of limits on duty cycle etc that I dont want to have to worry about.
I can grab the arduino shields with no RF and stick a module on myseld, but the Pi end seems to only be able to be ordered with a 433 or 868MHz version already on it.
Re: Emontx arduino shield and Pi on 915MHz?
I think if you ask the shop nicely, they might be able to accommodate you (or at least supply one for you to solder in the radio module yourself). Have you checked the legality of 915 MHz where you are?
Re: Emontx arduino shield and Pi on 915MHz?
It just became legal to use the full band as AU gets to have this month after some whining from the radio broadcasters who used to have that band for their studio links.
https://gazette.govt.nz/notice/id/2016-go272
So want to get in on it first. Noise on 433 is so bad here, I tried an IR repeater that uses 433 and it was just constantly lit up recieving "stuff"
Im just working out what I need to get so will probably order next week or so, solar stuff not going in till march at this stage. Will get the clip on CT's ordered at least so I can get them in the breaker panel when that is changed over. I will ask closer to wanting to order.
Re: Emontx arduino shield and Pi on 915MHz?
Finally going to get around to doing this, more important now that I have found out that with the move to the import export meter, I dont get the 30 minuite data from the power company anymore because their systems are not set up for it. So someone comes every 2 months to read the numbers off my meter like the old days.
Anyway, I cant seem to find anywhere in the checkout process to order without a wireless module on it. I could easily handle adding one if it was not populated, but am not sure I would be able to desolder the 433MHz one from the board. I have some 915MHz RFM69s from aliexpress here ready to put in.
Was planning on getting the emon pi with its 2 sensors initially for the garage where the solar connects into its distribution board, and then later on getting the emon tx to add to the house where the main distribution board is located to get the whole house usage and check that I am not exporting. If I add solar to the shed would get another emon tx at that time for its distribution board.
Re: Emontx arduino shield and Pi on 915MHz?
Email the shop. Once they know about it, they'll most likely tell you to add a note to your order and they'll be on the look-out for it.


[gecode-users] Unexpected propagation/search behaviour
Christian Schulte
schulte at imit.kth.se
Mon Jan 23 15:07:01 CET 2006
Hmm, sounds reasonable. No other idea so far...
Christian
--
Christian Schulte, http://www.imit.kth.se/~schulte/
-----Original Message-----
From: Lars Otten [mailto:ottenl at student.chalmers.se]
Sent: Monday, January 23, 2006 3:47 PM
To: schulte at imit.kth.se; users at gecode.org
Subject: Re: [gecode-users] Unexpected propagation/search behaviour
The propagator has three fields, one for each array, of type set<int> (from
the STL), where I store the indices of the variables that have been
processed already. When the propagator is cloned copies of these fields are
made for the new propagagor instance, so that should be OK?
I'll see if I can send some code later...
/Lars
On 01/23/06 13:21, Christian Schulte wrote:
> Hmmm, another thing: how do you store the info that a variable is
> already done? Do you copy that properly?
>
> Otherwise, no real idea yet. Maybe send the real code.
>
> Christian
More information about the gecode-users
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akka.http.scaladsl.server.directives
Decompresses the incoming request if it is gzip
or deflate
compressed.
Decompresses the incoming request if it is gzip
or deflate
compressed.
Uncompressed requests are passed through untouched.
If the request encoded with another encoding the request is rejected with an UnsupportedRequestEncodingRejection
.
Decodes the incoming request if it is encoded with one of the given encoders.
Decodes the incoming request if it is encoded with one of the given
encoders. If the request encoding doesn't match one of the given encoders
the request is rejected with an UnsupportedRequestEncodingRejection
.
If no decoders are given the default encoders (Gzip
, Deflate
, NoCoding
) are used.
Decodes the incoming request using the given Decoder.
Decodes the incoming request using the given Decoder.
If the request encoding doesn't match the request is rejected with an UnsupportedRequestEncodingRejection
.
Encodes the response with the encoding that is requested by the client via the Accept-
Encoding
header.
Encodes the response with the encoding that is requested by the client via the Accept-
Encoding
header. The response encoding is determined by the rules specified in
http://tools.ietf.org/html/rfc7231#section-5.3.4.
If the Accept-Encoding
header is missing or empty or specifies an encoding other than
identity, gzip or deflate then no encoding is used.
Encodes the response with the encoding that is requested by the client via the Accept-
Encoding
header.
Encodes the response with the encoding that is requested by the client via the Accept-
Encoding
header. The response encoding is determined by the rules specified in
http://tools.ietf.org/html/rfc7231#section-5.3.4.
If the Accept-Encoding
header is missing then the response is encoded using the first
encoder.
If the Accept-Encoding
header is empty and NoCoding
is part of the encoders then no
response encoding is used. Otherwise the request is rejected.
Rejects the request with an UnsupportedRequestEncodingRejection if its encoding doesn't match the given one.
Rejects the request with an UnsupportedRequestEncodingRejection if its encoding doesn't match the given one.
Rejects the request with an UnacceptedResponseEncodingRejection if the given response encoding is not accepted by the client.
Rejects the request with an UnacceptedResponseEncodingRejection if the given response encoding is not accepted by the client.
Inspects the response entity and adds a Content-Encoding: gzip
response header if
the entities media-type is precompressed with gzip and no Content-Encoding
header is present yet.
Inspects the response entity and adds a Content-Encoding: gzip
response header if
the entities media-type is precompressed with gzip and no Content-Encoding
header is present yet.


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HIGH COURT OF ORISSA: CUTTACK W.P.(C) No. 11675 of 2010 In the matter of an application under Articles 226 and 227 of the Constitution of India. --------
Ashirbad Nursing Home, Modipara, Sambalpur, Represented through Dr. Sachidananda Basa, S/o. Late Baikunthanath Basa, Vill: Modipara, Dist: Sambalpur and others ... Petitioners
-Versus-
State of Orissa and others ... Opp. Parties For Petitioners : M/s. S.K. Sarangi, B.K. Behera, J.K. Acharya & S. Sarangi For Opp. Parties : Mr. R.K. Mohapatra, Government Advocate ---------- P R E S E N T:
THE HONOURABLE THE CHIEF JUSTICE SHRI V.GOPALA GOWDA AND THE HONOURABLE SHRI JUSTICE B.N.MAHAPATRA Date of Judgment: 06.07.2012 B.N.Mahapatra,J. The petitioners claiming tobe owners of Clinical Establishments and Nursing Homes have filed this writ petition with a prayer to declare the Orissa Clinical Establishments (Control and Regulation) Amendment Rules, 2006 (for short, "Rules, 2006") published under Notification dated 1st February, 2006 (Annexure-1) ultra vires the Orissa Clinical Establishments (Control and Regulation) Act, 1990 (for short, "Act, 1990") or in the alternative to quash the provisions contained 2 in the said Notification being not in consonance with the Act, 1990 and declare the same ultra vires.
2. Mr. S.K. Sarangi, learned counsel appearing on behalf of the petitioners submitted that the Rules, 2006 being not in consonance with the Act, 1990, the very purpose of establishing Nursing Home and Clinical Establishments for rendering service to the common men is frustrated at the instance of the Rule implementing authorities. Under the provisions of the Act, 1990, the Clinical Establishments were to be registered with the Director of Medical Education and Training (for short, "DMET") through the respective Chief District Medical Officers (for short, "CDMOs") on payment of certain registration fees. The Act, 1990 further prescribes that on compliance of certain formalities, the registration certificate is to be issued to the Establishments. Referring to sub-rule (6) of Rule 3 of the Rules, 1994, Mr. Sarangi, submitted that certificate of registration shall remain valid for a period of two years from the date on which it is granted. The Rules, 2006 came into force with effect from 23.05.2006 which provide for payment of charges towards the Clinical Establishments. Though objections were invited to the Draft Rules, 2006 and several objections were received, without considering the same the Government made the Rules, 2006 which is not in consonance with the Act, 1990 and the earlier Rules, 1994. Therefore, it causes great prejudice, hardship and unequal treatment to the Clinical Establishments. According to Section 2(b) of the Act, 1990, "Clinical 3 Establishment" includes Nursing Home. However, under the Rules, 2006, all Clinical Establishments having nursing facilities are asked to separately register for Nursing Home paying the registration fees twice. The Rules, 1992 prescribed that Rs.1,500/- (Rs.1,000/- towards grant/renewal of licence fees and Rs.500/- for inspection) shall be charged for each Clinical Establishment for registration and same amount for renewal. The validity of the registration certificate was for a period of two years which continued till 2008. The Notification dated 1st February, 2006, however, enhanced the said registration fees by several times with new stipulations made therein regarding the same inasmuch as the fees so payable were made annually. The DMET is charging more than what is prescribed under the Act, 1990 in the matter of registration and renewal. The DMET in its letter dated 11.09.2008 has clarified the said anomaly stating that the Certificate though would be valid for a period of two years yet the fees for registration and renewal are to be charged double. The proviso to Clause (5) of Rules, 2006 to obtain clearance from Orissa State Pollution Control Board for disposal of Bio- medical waste is a condition precedent prior to grant of registration, though the Act, 1990 was silent about the same. As a result, clearance from the Pollution Control Board is insisted though the same is neither recognized under the Act, 1990 nor under the Air Pollution Control Act.
3. Mr. Sarangi, learned counsel further submitted that though the applications have been made in time, yet the registration certificates 4 have not been issued for years together, thus, the Nursing Homes were uncertain as to whether their applications for registration were allowed or not. The Rules regarding registration have not been followed uniformly. There are cases, where the registration is being done once in every two years with one set of registration fee as would be evident from letter dated 09.04.2009 (Annexure-4) issued by the DMET. Despite bringing this unequal treatment in the matter of registration to the notice of the concerned authorities, no action has been taken on such allegation. It is further submitted that the competent authorities are not registering the Nursing Homes and thereby the Nursing Homes are not aware of the date of renewal as per Clause 2(ii) of the Rules, 2006. On the other hand, they are charging 10% for the delayed registration. This action of the opposite parties, does not stand to logic. This anomaly has been brought to the notice of the Chief Secretary by way of representation dated 06.07.2009 (Annexure-5) but the same has not yet been considered.
4. Per contra, Mr. R.K. Mohapatra, learned Government Advocate referring to the counter affidavit dated 30.06.2011 submitted that the writ petition is misconceived in fact and law and is liable to be dismissed at the threshold. Rule 2 of the Rules, 2006 is very clear wherein the annual rate of Clinical Establishments for Registration/ Renewal for M.R.I., C.T. Scan, Ultrasound, Endoscopy, Bio-Chemical and Pathological Examination has been defined in a Table as categorized 5 under category of A.B.C.D. Further, category has also been indicated as A.B.C.D. for Nursing Homes depending upon number of beds provided in the Nursing Homes. In Rule 5 of the Rules, 2006, it has been clarified that "A fee of Rs.10,000/-, Rs.8,000/-, Rs.6,000/-, Rs.5,000/- whichever is applicable has to be credited to Government under the Head of Account-0210-Medical & PH-020-Receipt from patients for Hospital & Dispensary Services-9906480-other fees". All C.D.M.Os have been issued with clarification to the effect that those clinical establishments having beds and diagnostic facilities are required to deposit Registration/Renewal fees for both the facilities. The Rules, 2006 has been proportionately applied with regard to the renewal/registration fees vis-à-vis number of beds in the Nursing Home. The Act, 1990 and the Rules, 2006 are having laudable objects. Rule 5 of the Rules, 2006 indicates that all the Clinical Establishments and Nursing Home shall possess clearance certificate from Orissa State Pollution Control Board for disposal of their Bio-Medical Waste under Bio-Medical Waste (Management & Handling) Rules, 1998 prior to grant of registration/renewal. Pollution Control Board Authorities are inspecting and issuing authorization certificates to the proposed Clinical Establishments/Nursing Homes and the Clinical Establishments/ Nursing Homes already established are observing the said formalities. On receipt of complete documents, the renewal/registration is being considered observing all paraphernalia under the Act, 1990 and the 6 Rules, 2006. The Rules, 2006 regarding registration is always followed uniformly. Prior to deposit of Rs.6,000/- the Clinical Establishments had deposited Rs.21,300/- as against Rs.27,300/- (due fees + 10% fine) for grant of renewal for the period from 20.02.2008 to 19.02.2010. In support of the contention, Mr. Mohapatra, learned Government Advocate referred to letter dated 21.09.2008 addressed to DMET, Orissa (Annexure-C/2). Once the Clinical Establishment/Nursing Home has been registered, the owner of the Clinical Establishment should have been aware of the date of next renewal before one month of expiration of period of renewal. It is the duty of the owner to take steps for deposit of dues in shape of Treasury Challan failing which, 10% of the prescribed fees will be charged for every month of subsequent delay as per Rule 2(ii) of the Rules, 2006. Taking a plea of non-receipt of information from the Directorate, the fees are not being deposited in time. The registration of applications of the Clinical Establishments/Nursing Homes is considered within the prescribed period. For want of documents, some cases are being delayed and lingering. After complete compliance, the registration/ renewal is being done. Therefore, question of pick and choose in the matter of registration and/or renewal does not arise. The Rules, 2006 is not contrary to the provisions of the Act, 1990 rather both are complimentary and intended to carry out the purpose of the Act. The Rules, 2006 is intra vires the Act, 1990. There is not a single tenable proposition of law or submissions stated in the entire writ petition which 7 can even remotely support the plea of invalidity of Rules, 2006. Concluding his argument, Mr. Mohapatra, learned Government Advocate submitted for dismissal of the writ petition.
5. The contentions taken in the counter affidavit filed by the State are denied in the rejoinder affidavit filed by the petitioners. In the rejoinder affidavit, the petitioners have reiterated the contentions as taken in the writ petition.
6. On the rival contentions advanced by the parties, the following questions fall for consideration by this Court :
(i) Whether the Rules, 2006 provides for grant of registration for one year and the same is contrary to the Act, 1990, which provides that the certificate of registration shall be valid for a period of two years w.e.f. the date on which it is granted ?
(ii) Whether charging of separate registration/renewal fees i.e. one for clinical establishment and other for Nursing Home is contrary to the Scheme of the Act, 1990 in which Section 2(b) defines Clinical Establishment means a Nursing Home, Physical Therapy etc. ?
(iii) Whether there is any discrimination in the matter of fixation of fee with regard to investigation undertaken by any Clinical Establishment/Nursing Home ?
(iv) Whether the newly amended Rule 5 of the Rules, 2006 requiring the Clinical Establishment and Nursing Home to possess clearance certificate from Orissa State Pollution Control Board for disposal of their Bio-
Medical Waste under the Bio-Medical Waste 8 (Management & Handling) Rules, 1998 prior to grant of registration and renewal from the authority is ultra vires the Act, 1990 ?
(v) Whether the opposite parties are adopting unequal treatment with regard to grant of registration to different Nursing Home/Clinical Establishments?
(vi) Whether the opposite parties are justified in charging 10% for the delayed registration while keeping pending renewal application with them ?
7. Question No.(i) is with regard to validity of period of registration. The Act, 1990 came into force with effect from 1st February, 1992. Sub-Section (4) of Section 6 of the Act, 1990 provides that every certificate of registration shall, unless revoked earlier under section 8 or deemed to be revoked under the first proviso to sub-section (1) of section 5, be valid for a period of two years with effect from the date on which it is granted. The Rules, 2006 does not contain any provision to the effect that certificate of registration shall be granted for a period of one year. It may be noted that in the writ petition the petitioners have not referred to any particular rule of the Rules, 2006 which provides that the certificate of registration shall be granted for one year. Therefore, question no. (i) is answered against the petitioner.
8. Question Nos.(ii) and (iii) being interlinked, they are dealt with together.
To deal with the aforesaid two questions, it is necessary to extract here Clauses (b), (e) and (f) of Section 2 of the Act, 1990, which 9 defines "clinical establishment", "maternity home" and "nursing home" respectively.
Section 2(b) "Clinical establishment" means a nursing home, a physical therapy establishment, a clinical laboratory or an establishment analogous to any of them, by whatever name called, and includes a maternity home, a blood bank, a private hospital, a dispensary, a place used for medical termination of pregnancy as approved under the Medical Termination of Pregnancy Act, 1971 an X-Ray institution or establishment and such other institutions or establishments as the Director of Health Services may, with the approval of the State Government, by notification from time to time, specify."
Section 2(e) "Maternity home" means an establishment where women are usually received or accommodated for the purpose of antenatal and postnatal care in connection with child-birth."
Section 2(f) "Nursing home" means an establishment or premises used or intended to be used for the reception of, and providing medical care including nursing care in any form to, persons suffering from sickness, injury or infirmity."
It is true that the Clinical Establishment means a nursing home and it includes maternity home. Thus, in a Clinical Establishment not only the various medical examinations are undertaken but also Nursing Homes are provided for reception and medical care including nursing care in any form to persons suffering from sickness, injury or infirmity. Therefore, it is not necessarily meant that all clinical establishments provide facility of nursing home, maternity home and also provision for medical investigation. Hence, the Amended Rules, 2006 10 provides a fee structure for registration and renewal of Clinical Establishments without having Nursing Home and Clinical Establishments having different types of medical investigation. Similarly, there is also different fee structure provided for Nursing Homes on the basis of number of beds provided in the Nursing Homes. This classification is reasonable and beneficial to the Clinical Establishments and Nursing Homes. Without such classification, if a consolidated fee is charged for Clinical Establishments, a Clinical Establishment without having Nursing facility for running Nursing Home and providing lesser number of medical investigations would be required to pay same/equal registration/renewal fee with that of a Clinical Establishment which with all facilities would pay. Similarly, in case of Nursing Home, if a consolidated fee will be charged, then the Nursing Homes having lesser number of beds will pay the same/equal registration and renewal fee with that of the Nursing Homes having more number of beds. Therefore, the different fee structure provided for the Clinical Establishments on the basis of the facilities available with it and in case of Nursing Homes providing more or less number of beds is perfectly justified and reasonable.
11
9. At this juncture, it is necessary to reproduce the fee structure provided in the Notification published on 1st February 2006 in a tabular format under the Rules, 2006:
"Sl. Description of Private Category Amount of No. Clinics/ Nursing Homes with Registration/ status and Bed strength Renewal fees annually (1) (2) (3) (4)
1. Clinical Establishment "A" 10,000 Registration having M.R.I., C.T. Scan, 10,000 Renewal Ultrasound, Endoscopy, Biochemical & Pathological Examination
2. Clinical Establishment "B" 8,000 Registration having all facilities as at 8,000 Renewal Sl.No.1 except M.R.I., Test
3. Clinical Establishment "C" 6,000 Registration having all facilities as at 6,000 Renewal Sl.No.1 except M.R.I. Test & C.T. Scan
4. Clinical Establishment "B" 5,000 Registration having all facilities as at 5,000 Renewal Sl.No.1 except M.R.I., C.T.
Scan & Ultrasound Test 5. Nursing Home having 25 "A" 10,000 Registration beds and more 10,000 Renewal 6. Nursing Home having 15 "B" 8,000 Registration beds to 24 beds 8,000 Renewal 7. Nursing Home having 10 to "C" 6,000 Registration 14 beds 6,000 Renewal 8. Nursing Home having 5 to 9 "D" 5,000 Registration beds 5,000 Renewal"
10. From the above table, it is crystal clear that the Clinical Establishments undertaking more medical investigation facilities had to 12 pay higher charge than the Clinical Establishments having provisions for lesser number of medical investigations. Similarly, the Nursing Homes having more number of beds are required to pay more fee than the Nursing Homes having lesser number of beds. If any Clinical Establishment has both medical investigation facility as well as Nursing Home facility, it has to pay fees for both. Again that fee varies according to number of medical facilities and number of beds provided in the Nursing Home. Moreover, sub-Section (3) of Section 4 of the Act, 1990 provides that every application under sub-section (1) or sub-section (2) shall be in such form and be accompanied by such fee, as may be prescribed. Therefore, it cannot be said that the fee prescribed under the Rule is contrary to the fee provided under the Act, 1990. Thus, question Nos.(ii) and (iii) are answered against the petitioners.
11. Question No.(iv) is with regard to obtaining clearance from Orissa State Pollution Control Board for disposal of their Bio-Medical Waste.
Proviso to sub-Rule (5) of Rule 3 of the Rules, 2006 provides that all Clinical Establishments and Nursing Homes shall possess clearance certificate from Orissa State Pollution Control Board for disposal of their Bio-Medical Wastes under Bio-Medical Waste (Management & Handling) Rules, 1998 prior to grant of registration/renewal certificate from the authority. Needless to say that every citizen of the Nation has a right to get pollution free air and water. 13 Therefore, Air (Prevention and Control of Pollution) Act, 1981 and Water (Prevention and Control of Pollution) Act, 1974 have been enacted. Under the Bio-Medical Waste (Management & Handling) Rules, 1998, if the Amended sub-rule (5) of Rule 3 of the Rules, 2006 requires the Clinical Establishments and Nursing Homes to possess clearance certificate from the OSPCB prior to grant of registration/renewal certificate from the authority, there is nothing wrong in it. It is in consonance with the Bio- Medical Waste (Management & Handling) Rules, 1998. The law is now well settled that Parliament cannot only enact a law for avoidance or evasion of commission of an illegal trade, but also make law to see that the law is not evaded by taking recourse to machination or camouflage. The loopholes, if any, in such matters can and should be plugged. "Means affecting means" principle as adumbrated in United States v. Darby is an illustration on the point. Both substantial and procedural provisions can be made to make a law in furtherance of the object for which the Act has been enacted and to see that what is sought to be prohibited directly may not be achieved by the traders indirectly. [See Indian Handicrafts Emporium and others vs. Union of India and others, (2003) 7 SCC 589] In view of the above, it cannot be said that proviso to sub- rule (5) of Rule 3 of the Rules, 2006, which provides the pre-condition of obtaining clearance certificate, is ultra vires the Act, 1990. Therefore, question no.(iv) is answered against the petitioners. 14
12. Question No.(v) is as to whether the opposite parties are adopting unequal treatment with regard to grant of registration to the Nursing Homes/Clinical Establishments.
Further case of the petitioners is that the DMET is unequally treating the Nursing Homes and Clinical Establishments, who are applying for registration/renewal. There are cases where the registration is being done once in every two years with one set of registration fee. In support of his contentions, Mr. Sarangi, learned counsel for the petitioners has referred to letter No.3530 dated 09.04.2009 (Annexure-4) issued by the DMET. According to Mr. Sarangi, in some other cases DMET insists upon registration of the Clinical Establishments every year. As stated above, there is nothing available in the Rules, 1994 and the amended Rules, 2006 for grant of registration annually. Mr. Sarangi has also not brought to our notice any instance where registration or renewal has been granted for one year by the DMET. Charging of fee annually for registration and renewal is different from granting registration for a period of two years. Therefore, there is no substance in the submission of Mr. Sarangi, learned counsel appearing for the petitioners on this score.
15
13. Question No.(vi) is as to whether the opposite parties are justified in charging 10% for the delayed registration while keeping pending renewal application with them.
Petitioners' case is that the authorities are not registering the Nursing Homes within the time specified in the statute. Therefore, the Nursing Homes are not aware of the date of their renewal as per Rule 2(ii) of the Rules, 2006. When the Nursing Homes are not aware of the date of renewal of their registration, they were unable to make application for further renewal of the registration. However, opposite party-authorities are insisting on charging 10% of the registration fee for delayed registration. This allegation of the petitioners has been denied in the counter affidavit, wherein it has been stated that in some cases the registration is delayed due to want of some documents. After completion of all formalities, the registration is done. Under Section 5 of the Act, 1990, power is vested with the Supervising Authority to grant or refuse registration. However, under sub-section (5) of Section 6 of the Act, 1990, it is prescribed that a certificate of registration may be renewed from time to time on an application made in that behalf to the Supervising Authority, in such form and accompanied by such fee, as may be prescribed, and every such application shall be made not less than one month before the date on which the period of validity of the certificate of registration is due to expire. Section 5 of the Act, 1990 provides that the Supervising Authority before making any order refusing to grant 16 certificate of registration, the applicant is required to be given reasonable opportunity of being heard and the reasons for such refusal shall be communicated to the applicant in such manner as may be prescribed. Provided that the renewal of certificate of registration shall not be refused unless the supervising authority is satisfied that the certificate holder--
(i) is not in a position to comply with the requirements envisaged in Section 5, or (ii) has contravened any of the provisions of this Act or any rules made thereunder.
Sub-rule (8) of Rule 3 of the Rules, 2006 provides that the order of refusal to grant of registration shall be communicated to the applicant by Registered post with A.D.
14. In view of the same, the opposite party-authorities are required to communicate to the petitioners the fate of their applications for registration or renewal of registration within a reasonable period of time. If the competent authority grants registration or renewal of registration certificate, the same shall also be communicated to the applicant by Registered post with A.D. so as to enable him to apply for renewal before expiry of validity of the registration certificate. Question No.(vi) is answered accordingly.
15. With the aforesaid observations and direction, the writ petition is disposed of.
..................................
B.N.Mahapatra, J.
17V. Gopala Gowda, C.J. I agree.
...............................
Chief Justice Orissa High Court, Cuttack Dated 6th July, 2012/SKJ


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2018-01-15 Can we talk briefly about the civil trial the King Family won regarding MLK's assassination? conspiracy
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The word dinosaur means “thunder lizard“ but the term is misleading because dinosaurs are not lizards.
Dinosaurs have been found all over the world and they either love meat or hate meat.


The goal of this tutorial is to show how to use TensorFlow to train and evaluate a simple feed-forward neural network for handwritten digit classification using the (classic) MNIST data set. The intended audience for this tutorial is experienced machine learning users interested in usingTensorFlow.
These tutorials are not intended for teaching Machine Learning in general.
Please ensure you have followed the instructions to install TensorFlow.
This tutorial references the following files:
| File | Purpose |
|---|---|
mnist.R |
The code to build a fully-connected MNIST model. |
fully_connected_feed.R |
The main code to train the built MNIST model against the downloaded dataset using a feed dictionary. |
Simply source the fully_connected_feed.R
file to start training:
source("fully_connected_feed.R", echo = TRUE)
MNIST is a classic problem in machine learning. The problem is to look at greyscale 28x28 pixel images of handwritten digits and determine which digit the image represents, for all the digits from zero to nine.
For more information, refer to Yann LeCun’s MNIST page or Chris Olah’s visualizations of MNIST.
At the top of the run_training()
function, the input_data$read_data_sets()
function will ensure that the correct data has been downloaded to your local training folder and then unpack that data to return a named list of DataSet
instances.
data_sets <- input_data$read_data_sets(FLAGS$train_dir, FLAGS$fake_data)
NOTE: The fake_data
flag is used for unit-testing purposes and may be safely ignored by the reader.
| Dataset | Purpose |
|---|---|
data_sets$train |
55000 images and labels, for primary training. |
data_sets$validation |
5000 images and labels, for iterative validation of training accuracy. |
data_sets$test |
10000 images and labels, for final testing of trained accuracy. |
The placeholder_inputs()
function creates two tf$placeholder
ops that define the shape of the inputs, including the batch_size
, to the rest of the graph and into which the actual training examples will be fed.
images <- tf$placeholder(tf$float32, shape(batch_size, IMAGE_PIXELS))
labels <- tf$placeholder(tf$int32, shape(batch_size))
Further down, in the training loop, the full image and label datasets are sliced to fit the batch_size
for each step, matched with these placeholder ops, and then passed into the sess$run()
function using the feed_dict
parameter.
After creating placeholders for the data, the graph is built from the mnist.R
file according to a 3-stage pattern: inference()
, loss()
, and training()
.
inference()
- Builds the graph as far as is required for running the network forward to make predictions.loss()
- Adds to the inference graph the ops required to generate loss.training()
- Adds to the loss graph the ops required to compute and apply gradients.The inference()
function builds the graph as far as needed to return the tensor that would contain the output predictions.
It takes the images placeholder as input and builds on top of it a pair of fully connected layers with ReLu activation followed by a ten node linear layer specifying the output logits.
Each layer is created beneath a unique tf$name_scope
that acts as a prefix to the items created within that scope.
with(tf$name_scope('hidden1'), {
# create layer
})
Within the defined scope, the weights and biases to be used by each of these layers are generated into tf$Variable
instances, with their desired shapes:
weights <- tf$Variable(
tf$truncated_normal(shape(IMAGE_PIXELS, hidden1_units),
stddev = 1.0 / sqrt(IMAGE_PIXELS)),
name = 'weights'
)
biases <- tf$Variable(tf$zeros(shape(hidden1_units), name = 'biases'))
When, for instance, these are created under the hidden1
scope, the unique name given to the weights variable would be “hidden1/weights
”.
Each variable is given initializer ops as part of their construction.
In this most common case, the weights are initialized with the tf$truncated_normal
and given their shape of a 2-D tensor with the first dim representing the number of units in the layer from which the weights connect and the second dim representing the number of units in the layer to which the weights connect. For the first layer, named hidden1
, the dimensions are shape(IMAGE_PIXELS, hidden1_units)
because the weights are connecting the image inputs to the hidden1 layer. The tf$truncated_normal
initializer generates a random distribution with a given mean and standard deviation.
Then the biases are initialized with tf$zeros
to ensure they start with all zero values, and their shape is simply the number of units in the layer to which they connect.
The graph’s three primary ops – two tf$nn$relu
ops wrapping tf$matmul
for the hidden layers and one extra tf$matmul
for the logits – are then created, each in turn, with separate tf$Variable
instances connected to each of the input placeholders or the output tensors of the previous layer.
hidden1 <- tf$nn$relu(tf$matmul(images, weights) + biases)
hidden2 <- tf$nn$relu(tf$matmul(hidden1, weights) + biases)
logits <- tf$matmul(hidden2, weights) + biases
Finally, the logits
tensor that will contain the output is returned.
The loss()
function further builds the graph by adding the required loss ops.
First, the values from the labels_placeholder
are converted to 64-bit integers. Then, a tf$nn$sparse_softmax_cross_entropy_with_logits
op is added to automatically produce 1-hot labels from the labels_placeholder
and compare the output logits from the inference()
function with those 1-hot labels.
labels <- tf$to_int64(labels)
cross_entropy <- tf$nn$sparse_softmax_cross_entropy_with_logits(
logits = logits, labels = labels, name = 'xentropy')
It then uses tf.reduce_mean
to average the cross entropy values across the batch dimension (the first dimension) as the total loss.
tf$reduce_mean(cross_entropy, name = 'xentropy_mean')
And the tensor that will then contain the loss value is returned.
Note: Cross-entropy is an idea from information theory that allows us to describe how bad it is to believe the predictions of the neural network, given what is actually true. For more information, read the blog post Visual Information Theory (http://colah.github.io/posts/2015-09-Visual-Information/)
The training()
function adds the operations needed to minimize the loss via Gradient Descent.
Firstly, it takes the loss tensor from the loss()
function and hands it to a tf$summary$scalar
, an op for generating summary values into the events file when used with a tf$summary$FileWriter
(see below). In this case, it will emit the snapshot value of the loss every time the summaries are written out.
tf$summary$scalar(loss$op$name, loss)
Next, we instantiate a tf$train$GradientDescentOptimizer
responsible for applying gradients with the requested learning rate.
optimizer <- tf$train$GradientDescentOptimizer(learning_rate)
We then generate a single variable to contain a counter for the global training step and the minimize()
op is used to both update the trainable weights in the system and increment the global step. This op is, by convention, known as the train_op
and is what must be run by a TensorFlow session in order to induce one full step of training (see below).
global_step <- tf$Variable(0L, name = 'global_step', trainable = FALSE)
optimizer$minimize(loss, global_step = global_step)
Once the graph is built, it can be iteratively trained and evaluated in a loop controlled by the user code in fully_connected_feed.R
.
At the top of the run_training()
function is a with
statement that indicates all of the built ops are to be associated with the default global tf$Graph
instance.
with(tf$Graph()$as_default(), {
# build graph
})
A tf$Graph
is a collection of ops that may be executed together as a group. Most TensorFlow uses will only need to rely on the single default graph.
More complicated uses with multiple graphs are possible, but beyond the scope of this simple tutorial.
Once all of the build preparation has been completed and all of the necessary ops generated, a tf$Session
is created for running the graph.
sess <- tf$Session()
Alternately, a Session
may be generated into a with
block for scoping:
with(tf$Session() %as% sess, {
# train, etc.
})
The empty parameter to session indicates that this code will attach to (or create if not yet created) the default local session.
Immediately after creating the session, all of the tf$Variable
instances are initialized by calling sess$run()
on their initialization op.
init <- tf$global_variables_initializer()
sess$run(init)
The sess.run()
method will run the complete subset of the graph that corresponds to the op(s) passed as parameters. In this first call, the init
op is a tf$group
that contains only the initializers for the variables. None of the rest of the graph is run here; that happens in the training loop below.
After initializing the variables with the session, training may begin.
The user code controls the training per step, and the simplest loop that can do useful training is:
for (step in 1:FLAGS$max_steps) {
sess$run(train_op)
}
However, this tutorial is slightly more complicated in that it must also slice up the input data for each step to match the previously generated placeholders.
For each step, the code will generate a feed dictionary that will contain the set of examples on which to train for the step, keyed by the placeholder ops they represent.
In the fill_feed_dict()
function, the given DataSet
is queried for its next batch_size
set of images and labels, and tensors matching the placeholders are filled containing the next images and labels.
batch <- data_set$next_batch(FLAGS$batch_size, FLAGS$fake_data)
images_feed <- batch[[1]]
labels_feed <- batch[[2]]
A dictionary is then generated with the placeholders as keys and the representative feed tensors as values.
dict(
images_pl = images_feed,
labels_pl = labels_feed
)
This is passed into the sess$run()
function’s feed_dict
parameter to provide the input examples for this step of training.
The code specifies two values to fetch in its run call: train_op
and loss
.
for (step in 1:FLAGS$max_steps) {
feed_dict <- fill_feed_dict(data_sets$train,
placeholders$images,
placeholders$labels)
values <- sess$run(list(train_op, loss), feed_dict = feed_dict)
loss_value <- values[[2]]
}
Because there are two values to fetch, sess$run()
returns a list with two items. Each Tensor
in the list of values to fetch corresponds to an array in the returned tuple, filled with the value of that tensor during this step of training. Since train_op
is an Operation
with no output value, the corresponding element in the returned list is NULL
and, thus, discarded. However, the value of the loss
tensor may become NaN if the model diverges during training, so we capture this value for logging.
Assuming that the training runs fine without NaNs, the training loop also prints a simple status text every 100 steps to let the user know the state of training.
if (step %% 100 == 0) {
# Print status to stdout.
cat(sprintf('Step %d: loss = %.2f (%.3f sec)\n',
step, loss_value, duration))
}
In order to emit the events files used by TensorBoard, all of the summaries (in this case, only one) are collected into a single Tensor during the graph building phase.
summary < tf$summary$merge_all()
And then after the session is created, a tf$summary$FileWriter
may be instantiated to write the events files, which contain both the graph itself and the values of the summaries.
summary_writer <- tf$summary$FileWriter(FLAGS$train_dir, sess$graph)
Lastly, the events file will be updated with new summary values every time the summary
is evaluated and the output passed to the writer’s add_summary()
function.
summary_str <- sess$run(summary, feed_dict=feed_dict)
summary_writer$add_summary(summary_str, step)
When the events files are written, TensorBoard may be run against the training folder to display the values from the summaries.
NOTE: For more info about how to build and run Tensorboard, please see the accompanying tutorial Tensorboard: Visualizing Your Training.
In order to emit a checkpoint file that may be used to later restore a model for further training or evaluation, we instantiate a tf$train$Saver
.
saver <- tf$train$Saver()
In the training loop, the saver$save()
method will periodically be called to write a checkpoint file to the training directory with the current values of all the trainable variables.
saver$save(sess, checkpoint_file, global_step=step)
At some later point in the future, training might be resumed by using the saver$restore()
method to reload the model parameters.
saver$restore(sess, FLAGS$train_dir)
Every thousand steps, the code will attempt to evaluate the model against both the training and test datasets. The do_eval()
function is called thrice, for the training, validation, and test datasets.
# Evaluate against the training set.
cat('Training Data Eval:\n')
do_eval(sess,
eval_correct,
placeholders$images,
placeholders$labels,
data_sets$train)
# Evaluate against the validation set.
cat('Validation Data Eval:\n')
do_eval(sess,
eval_correct,
placeholders$images,
placeholders$labels,
data_sets$validation)
# Evaluate against the test set.
cat('Test Data Eval:\n')
do_eval(sess,
eval_correct,
placeholders$images,
placeholders$labels,
data_sets$test)
Note that more complicated usage would usually sequester the
data_sets$test
to only be checked after significant amounts of hyperparameter tuning. For the sake of a simple little MNIST problem, however, we evaluate against all of the data.
Before entering the training loop, the Eval op should have been built by calling the evaluation()
function from mnist.R
with the same logits/labels parameters as the loss()
function.
eval_correct <- evaluation(logits, placeholders$labels)
The evaluation()
function simply generates a tf$nn$in_top_k
op that can automatically score each model output as correct if the true label can be found in the K most-likely predictions. In this case, we set the value of K to 1 to only consider a prediction correct if it is for the true label.
correct <- tf$nn$in_top_k(logits, labels, 1L)
One can then create a loop for filling a feed_dict
and calling sess$run()
against the eval_correct
op to evaluate the model on the given dataset.
for (step in 1:steps_per_epoch) {
feed_dict <- fill_feed_dict(data_set,
images_placeholder,
labels_placeholder)
true_count <- true_count + sess$run(eval_correct, feed_dict=feed_dict)
}
The true_count
variable simply accumulates all of the predictions that the in_top_k
op has determined to be correct. From there, the precision may be calculated from simply dividing by the total number of examples.
precision <- true_count / num_examples
cat(sprintf(' Num examples: %d Num correct: %d Precision @ 1: %0.04f\n',
num_examples, true_count, precision))


Identity and Values
The thing I value most is genuinity (or genuiness). I like to show how I feel (though not proactively - I don't shove it in peoples' faces) and be true to myself instead of hiding it or trying to be someone I'm not and I dislike when others hide their feelings or fake feelings and I can generally tell when someone is lying to themselves/ ignoring their feelings.  This trait I have makes CV writing (and anything that requires assertiveness) difficult as I am adverse to using positive language unless I'm feeling positive as that would feel ingenuine. My culture is a little hard for me to define. I'd say the closest thing to culture I have would be my love for singing and music, and video games and streamers/content creators. I feel like these things have influenced my values to be more accepting of others and to be more compassionate (compounding, I feel like I would have been compassionate without this influence as well). For better or worse, these things (streamers in particular) have also given me the belief that no one really grows up. 100 years isn't enough for maturity. No one is superior.
When it comes to strengths and limitations, I am a little lost. When completing the Myer Briggs test I get different results every time and of the things they say about those personalities only bits and pieces feel like they apply to me (but I am definitely introverted). The DOPE test says I'm 45% Dove, 45% Owl, and 10% Peacock (0% Eagle). In terms of strengths I believe I am:
- Patient
- Punctual
- Genuine
- Strong at logic and problem solving
- Compassionate
- Reliable
- Observant? Aware? (These words don't quite describe it correctly. I notice things. I am hesitant to say observant or aware because sometimes I am completely oblivous to things, but in general when I look, I see, though this doesn't always apply to finding things that are lost unfortunately)
In terms of limitations I struggle with:
- Confidence in myself and my abilities
- The concept of good enough (I'm a perfectionist)
- Being too blunt (I never mean to offend, but sometimes things don't come out quite how I expect them to)
- I'm sure there are more but I can't think of them
Patience and compassion should help my learning journey by helping me to get along with others. Being punctual, strong at logic and problem solving, and reliable should help with overcoming the challenges I will face. An example of when I struggled to work productively with someone was when I was cleaning and gardening for a family friend. I would take way longer on tasks than they expected, mainly due to me wanting to get the job done well. Too well. At the time I just didn't try as hard and focussed less on the details but now I would try figuring out what parts of the job were more important than others and focus on those (making sure not to spend too long on any one task) because this way I would be intentionally decreasing the quality to fit with the time budget I had without sacrificing the parts that are essential.


{% extends "layout.html" %} {% block content %}
{{ _('This should only be set for clients that will use backend application flow.') }}


What is Islamophobia?
Statistics on discrimination of Muslim Women
Islamophobia Researcher
27+ Women in Technology statistics
17+ Women in Technology statistics
What is Islamophobia(CBBC)
On Islamophobia + Combating


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Founder & CEO
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IOT
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{% extends "medicalforms/form_base.html" %} {% block title %} Report of Findings {% endblock title %} {% block form_content %}


The year was 2020, and school was out due to COVID-19; leaving me, a 13 year-old boy alone in my room with a computer. This left me plenty of time to browse "the hub", or github that is. My situation had given me plenty of time to imporve my programming skills, and I loved the online community of solving problems (my favourites being college homework), and sharing corny memes. I decided I needed a new project, ad I wanted this one to be big, not like a calulator, or a stopwatch, I wanted something very different from anything else I'd ever done, and it had to be my idea. After brainstorming for a few minutes, I decided on creating a function that could check whether a number was prime, or composite, my inspiration was a math Youtube channel called numberphile, so my mind was fresh with the ideas of contemporary and ancient mathematicians. Yet, I didn't quite know how to do it yet. Eventually I realized that all composite numbers can be written as the following


Product designer focused on vehicle section.
Product designer on Swedens largest vehicle marketplace.
Designer & frontend developer working on launching Blocket "clones" around the world.
Designer & frontend developer working on medicine and life science related products.


Arrows
to Move
WASD
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Bitcoin Exchange Outflows Suggest Renewed HODL’ing Period
by Christine VasilevaNew research reveals that in the last months of 2019, outflows from exchanges have surpassed inflows. This points towards an intention to hold onto Bitcoin (BTC), potentially meaning lesser selling pressure.
Moving Coins to Exchanges Slowed Down in October
Token Analyst notes net outflows from exchanges in the past few days. The composition of daily activity varies, but the findings suggest coins are being retracted from active trading.
The observations match the recent findings by the Delphi report for October, where exchange inflows slowed down for the first time since April. During periods of rising prices, coins move on exchanges, with the potential to fill orders at new, more appealing prices. Since July, on-chain activity of active addresses has also slowed down, coinciding with a period of relatively flat price action.
The October rally, however, which recovered BTC prices from $7,400 to as high as $10,000, arrived unexpectedly. For most of the month, prices remained stationary and traders held onto their coins. In the second half of 2019, there were indications that trading had moved into the hands of “whales”. Retail interest waned, as enthusiastic buyers noted how quickly their fortunes could turn in the volatile market.
From Bitcoin to Stablecoins
Beyond BTC flows, the activity of stablecoins is also important. Tether (USDT) remained a driving factor. Recently, another big tranche of USDT was noted to flow into Binance:
At this point, it is too early to predict a rally, despite expectations bitcoin may move into a higher range. At this time, indicators point to the fact that the market bottom is already behind, and BTC is now seeking its new direction once again, starting off from a stabilized level above $9,200.
Despite the occasional transaction, stablecoin flows also marked a net decrease from exchange balances in the past week.
The sentiment surrounding BTC remains in the middle, with the Bitcoin fear and greed index at 49 points. BTC has shown propensity for spending some time with stagnant prices, then making an unexpected move.
Ethereum (ETH) also shows a balance of inflows and outflows, as the coin stagnated above $181.
ETH remains one of the most actively traded assets, supporting decentralized exchanges and participating in highly active pairs.
What do you think about BTC activity? Share your thoughts in the comments section below!
Images via Shutterstock, Twitter @thetokenanalyst @whale_alert
The Rundown