low_use package¶
Submodules¶
low_use.report_parser module¶
Parses the Low Use report
This module parses the Low Use Report from AWS Trusted Advisor, and grabs some instance metadata from EC2 such as tags
-
class
low_use.report_parser.
LowUseReportParser
(session)¶ Bases:
object
Parses the Low Use report
-
session
¶ Boto3 AWS Session Object
Type: obj
-
advisor
¶ Wrapper for AWS TrustedAdvisor
Type: obj
-
ec2
¶ Wrapper for AWS EC2
Type: obj
-
get_number_of_days
(day_string)¶ Get number of days in report
Used to determine how many days the instance has data for
Parameters: day_string (str) – String that has the amount of days Returns: number of days with data Return type: int
-
parse_instance_usage
(usage_logs)¶ Parsess instance usage
Parameters: usage_logs ( list
ofstr
) – List of unformatted usage over at most 2 weeksReturns: lists of CPU usage and network IO over the given time frame. Return type: list
-
parse_low_use_report
()¶ Parses the report
Returns: List of Low use instances with associated metadata Return type: list of dict
-
parse_metadata
(metadata)¶ Parses instance metadata
This function mainly formats the metadata to use key/value pairs instead of indexing for a better understanding of what the metadata is further downstream
Parameters: metadata ( list
) – Metadata from Low Use reportReturns: Metadata of instance Return type: dict
-
low_use.reporter module¶
Lambda Function to parse Low Use Report and send email reports
This function grabs and parses the Low Use report from AWS TrustedAdvisor, flags instances as either Whitelisted, Low Use, or Scheduled for Deletion via Tagging and DynamoDB Tables, and then sends Low Use/Admin report emails to the given users.
-
class
low_use.reporter.
LowUseReporter
(event, context)¶ Bases:
object
Parses the Low Use report, sync instance states with Dynamo, and sends email reports
- Attrbiutes:
- session (obj): Boto3 AWS Session Object
ec2 (obj) Wrapper for AWS EC2
dynamo (obj): Wrapper for AWS DynamoDB
ses (obj): Wrapper for AWS SES
event (dict): Event dictionary passed by Lambda trigger
context (dict): Context dictionary passed by Lambda trigger
parser (obj): Parses the Low Use Report
whitelist (
list
ofdict
): list of whitelisted instances and associated metadata low_use_instances (list
ofdict
): list of low_use instances and associated metadata instances_scheduled_for_deletion (list
ofdict
): list of instances scheduled for deletion and associated metadata instances_to_stop (list
ofdict
): list of instances to be stopped and associated metadata
-
flag_instance_as_low_use
(instance_id, creator)¶ Flag an instance as low_use
Flags an instance as low use via tags and in the a DynamoDB Table
Parameters: - instance_id (str) – ID of EC2 Instance
- creator (str) – creator of EC2 Instance
-
flag_instance_for_deletion
(instance_id, creator)¶ Flag an instance as scheduled for deletion
Flags an instance as scheduled for deletion via tags and in the a DynamoDB Table
Parameters: - instance_id (str) – ID of EC2 Instance
- creator (str) – creator of EC2 Instance
-
get_creator_report
()¶ Generates creator reports
Generates a new report for each creator with associated low use instances
Yields: dict – creator report for each creator with associated low use instances
-
sort_instances
(instances)¶ Sort instances from Low Use Report
- Sorts the instances flagged by TrustedAdvisor as either:
- Whitelisted (Will never be stopped)
- Low Use (2 weeks from stopped)
- Scheduled For Deletion (1 week from stopped)
- To Be Stopped Immediately (Stopped in this invocation)
Parameters: instances ( list
ofdict
) – List of instances flagged by TrustedAdvisor and associated metadata
-
start
()¶ Lambda entry point
This is where the Lambda invocation starts. It parses the low use reports, sorts the instances and sends creator/admin email reports.
-
sync
()¶ Sync lists
Syncs this whitelist, low use instances, and instances schedule for deletion lists by flagging the instances with appropriate tags and updating Dynamo Tables.
-
sync_instances_scheduled_for_deletion
()¶ Sync instances scheduled for deletion
Flags instances as scheduled for deletion and sets them as such in the LowUse DynamoDB Table
-
sync_low_use_instances
()¶ Sync low_use instances
Flags instances as low use and adds them to the LowUse DynamoDB Table
-
sync_whitelist
()¶ Sync whitelist
Adds newly whitelisted instances to the Whitelist DynamoDB Table
-
low_use.reporter.
lambda_handler
(event, context)¶ Lambda handler
This is the handler for the Lambda environment, and kicks off the process
Parameters: - event (dict) – Event dictionary passed by Lambda trigger
- context (dict) – Context dictionary passed by Lambda trigger


How to use
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Best Things to do in Moon Township PA, Stuff todo + to see near ...
Best things todo + see in Moon Township PA. . They are Carnegie Museum of Art, Carnegie Museum of Natural History, Carnegie Science Center, . In the early 2000s, it was announced the museum would be expanding from the old Beaux .
http://www.hotelplanner.com/Attractions/5268-Things-to-do-in-Moon-Township-PA
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Moon Twp. American Legion Baseball
2010 PA Region 6 & Allegheny County Playoffs: Information regarding the 2010 . I am just trying to prepare a history of the Moon Township American Legion . years back in the late 80's and early 90's passed away last September 11, 2005.
http://joemav.tripod.com/joemav-2.html
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Centre Co. (PAGenWeb), Pa.--Halfmoon Township History & Facts
Halfmoon township was erected at January sessions, 1802. . A Quaker settlement was formed within its limits as early as 1792 when George Wilson came into .
http://www.rootsweb.ancestry.com/~pacentre/rlb/halftwp1.htm
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Hotels Near Pittsburgh Airport - Embassy Suites Pittsburgh
Embassy Suites Pittsburgh - International Airport Hotel, Pa - Front Of Hotel . Step back in time with a visit to the Heinz History Center or enjoy the tranquility of .
http://embassysuites3.hilton.com/en/hotels/pennsylvania/embassy-suites-pittsburgh-international-airport-PITATES/index.html
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Ancestor Tracks: Beaver County
Beaver County, fortunately, is one of the counties whose earliest landowners . In the meantime, scroll to the bottom of this page for links to the Township Warrantee Maps posted by the Pennsylvania State Archives in Harrisburg. . Moon Township [now Center Township] . Pennsylvania Historical & Museum Commission .
http://ancestortracks.com/Beaver_County_Map1860.html
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Hyeholde Restaurant - Moon Township, PA
. top of the hill. We were seated right away (even though we were half an hour early). . I was up in Moon Township checking out the campus of Robert Morris University (very nice!) . The building is a historical landmark, brick and aged wood.
http://www.yelp.com/biz/hyeholde-restaurant-moon-township
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Robert Morris University in Moon Township, PA: from the EdRef ...
Robert Morris University in Moon Township, PA: Info about Robert Morris University, . History And Social Sciences . Master of Education in Early Childhood .
http://www.edref.com/school_list/robert-morris-university
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Outback Steakhouse - Moon Township, PA
Moon Township, PA 15108. (412) 809- . Neville Township, PA. 4.0 star rating . On this trip in early Feb, we did get particularly outstanding service. Our wait .
http://www.yelp.com/biz/outback-steakhouse-moon-township
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Moon Township, PA - Official Website of the Township of Moon
Welcome to Moon Township's redesigned and completely updated Web site. . Grade Rd. | Moon Twp, PA 15108 |<PHONE_NUMBER> ------- www.moontwp.com .
http://www.moontwp.com/
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SVHS OLD MOON Mtg 1 23 13 Mobile - YouTube
Jan 26, 2013 . History was made at the Hyeholde Restaurant in Moon Township, PA, when 100 . Pennsylvania School for the Deaf: Early child program, IEP .
http://www.youtube.com/watch?v=yGqv0_bmDQI
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Robert Morris University: Home
Early Childhood PreK-4 · Elementary/Middle Level 4-8 · English and Math . RMU's History & Heritage · Who was . Moon Township, PA 15108. 800-762- 0097 .
http://www.rmu.edu/
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Center Township, Beaver County, Pennsylvania - Wikipedia, the free ...
History. Although Center Township is new among the family of . her traditions go back to the earliest period of Ohio Valley History. . Townships were created on the Southside: Hanover, First Moon and Second Moon.
http://en.wikipedia.org/wiki/Center_Township,_Beaver_County,_Pennsylvania
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Americas Best Value Inn - Pittsburgh Airport (Coraopolis, PA) - Hotel ...
8858 University Blvd, Coraopolis, PA 15108. Hotel amenities . This is a fine place to stay if you have an early morning flight. This place . Moon Township, PA .
http://www.tripadvisor.com/Hotel_Review-g52423-d490870-Reviews-Americas_Best_Value_Inn_Pittsburgh_Airport-Coraopolis_Pennsylvania.html
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Holiday Inn Pittsburgh Airport (Coraopolis, PA) - Hotel Reviews ...
8256 University Blvd, Coraopolis, PA 15108 . We like here when we have early morning flights, there is no charge for parking . The decor is typical of Holiday Inns (though it has a good Pittsburgh history theme) but . Moon Township, PA .
http://www.tripadvisor.com/Hotel_Review-g52423-d102598-Reviews-Holiday_Inn_Pittsburgh_Airport-Coraopolis_Pennsylvania.html
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College Search - Robert Morris University - RMU
Moon Township, PA 15108-1189. www.rmu.edu . Extensive evening or early morning classes. Saturday Classes . American History II. 50. 3. Analysis and .
https://bigfuture.collegeboard.org/college-university-search/robert-morris-university
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Selma's Texas Barbeque - Coraopolis, PA
CRANBERRY TWP, PA . I've also been fiending for good BBQ, so I figured I'd head over to Moon and try Selma's . En route back to Pittsburgh from Beaver Falls early this afternoon, we stopped here . Ya think this is history in the making ?
http://www.yelp.com/biz/selmas-texas-barbeque-coraopolis
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German Genealogy researcher Ed Heinlein
Palatines to America (President of the PA-Chapter) (see attachment about . I have joined the Moon Township Historical Society in order to research the . and Jim) had a farm and farmed the land until the early 1930's and sold them to Bell .
http://www.edheinleingermanconsultant.com/germangenealogy.php
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Moon, Pennsylvania Township Information - ePodunk
Sponsored Ads. Moon is a township in Allegheny County, in the Pittsburgh metro area. . For more info on local ancestry groups, see the Moon ancestry & family history guide. . Post cards are vintage images from the early 1900s. They are .
http://www.epodunk.com/cgi-bin/genInfo.php?locIndex=56477
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Americas Best Value Inn - Pittsburgh Airport (Coraopolis, PA) - Hotel ...
8858 University Blvd, Coraopolis, PA 15108. Hotel amenities . This is a fine place to stay if you have an early morning flight. This place . Moon Township, PA .
http://www.tripadvisor.com/Hotel_Review-g52423-d490870-Reviews-Americas_Best_Value_Inn_Pittsburgh_Airport-Coraopolis_Pennsylvania.html
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Townships, Boroughs, County Evolution for PA Counties
County evolution and names of townships and boroughs for Pennsylvania counties. . Leet, McCandless, Marshall, Moon, Mount Lebanon, Neville, North Fayette, . USGenWeb Archives: Historical Map of Townships, Boroughs, and Early .
http://dgmweb.net/Ancillary/Geog/PA/PA-Cos.htm


| java.lang.Object | |||
| ↳ | android.graphics.drawable.Drawable | ||
| ↳ | android.graphics.drawable.BitmapDrawable | ||
| ↳ | greendroid.graphics.drawable.ActionBarDrawable |
A specialized Drawable dedicated to ActionBarItem
s. It automatically
adapts its color depending on its current state. By default, the colors are:
The ActionBarDrawable is a great replacement to the StateListDrawable that
should be used in ActionBar
s.
GreenDroid offers a smart way to change the default alternative and normal
colors in an application-wide manner. In order to do that, override the
gdActionBarItemColorNormal
and
gdActionBarItemColorAlt
attributes in your application theme.
| Public Constructors | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
Create a new ActionBarDrawable using the specified Drawable.
| |||||||||||
Create a new ActionBarDrawable using the specified Drawable.
| |||||||||||
Create a new ActionBarDrawable using the specified resource identifier.
| |||||||||||
Create a new ActionBarDrawable using the specified resource identifier.
| |||||||||||
This constructor is deprecated.
Use
ActionBarDrawable(Context, Drawable)
as it looks for the default alternative/normal colors in the
theme.
| |||||||||||
This constructor is deprecated.
Use
ActionBarDrawable(Context, Drawable, int, int)
as it looks for the default alternative/normal colors in the
theme.
| |||||||||||
This constructor is deprecated.
Use
ActionBarDrawable(Context, int)
as it looks for the default alternative/normal colors in the
theme.
| |||||||||||
This constructor is deprecated.
Use
ActionBarDrawable(Context, int, int, int)
as it looks for the default alternative/normal colors in the
theme.
|
| Public Methods | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Protected Methods | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
[Expand]
Inherited Methods | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
From class
android.graphics.drawable.BitmapDrawable
| |||||||||||
|
From class
android.graphics.drawable.Drawable
| |||||||||||
|
From class
java.lang.Object
|
Create a new ActionBarDrawable using the specified Drawable.
| context | The Context used to retrieve resources (Bitmap/theme) |
|---|---|
| d | The icon's Drawable (should be a BitmapDrawable) |
Create a new ActionBarDrawable using the specified Drawable.
| context | The Context used to retrieve resources (Bitmap/theme) |
|---|---|
| d | The icon's Drawable (should be a BitmapDrawable) |
| normalColor | The color used to color the icon in normal mode |
| altColor | The color used to color the icon in alternative mode |
Create a new ActionBarDrawable using the specified resource identifier.
| context | The Context used to retrieve resources (Bitmap/theme) |
|---|---|
| resId | The resource identifier pointing to the icon's Bitmap |
Create a new ActionBarDrawable using the specified resource identifier.
| context | The Context used to retrieve resources (Bitmap/theme) |
|---|---|
| resId | The resource identifier pointing to the icon's Bitmap |
| normalColor | The color used to color the icon in normal mode |
| altColor | The color used to color the icon in alternative mode |
This constructor is deprecated.
Use
ActionBarDrawable(Context, Drawable)
as it looks for the default alternative/normal colors in the
theme.
Create a new ActionBarDrawable
| res | The Resources from which the given icon is retrieved |
|---|---|
| d | The icon's Drawable |
This constructor is deprecated.
Use
ActionBarDrawable(Context, Drawable, int, int)
as it looks for the default alternative/normal colors in the
theme.
Create a new ActionBarDrawable
| res | The Resources from which the given icon is retrieved |
|---|---|
| d | The icon's Drawable |
| normalColor | The color used to color the icon in normal mode |
| altColor | The color used to color the icon in alternative mode |
This constructor is deprecated.
Use ActionBarDrawable(Context, int)
as it looks for the default alternative/normal colors in the
theme.
Create a new ActionBarDrawable
| res | The Resources from which the given icon is retrieved |
|---|---|
| resId | The icon's resource ID |
This constructor is deprecated.
Use
ActionBarDrawable(Context, int, int, int)
as it looks for the default alternative/normal colors in the
theme.
Create a new ActionBarDrawable
| res | The Resources from which the given icon is retrieved |
|---|---|
| resId | The icon's resource ID |
| normalColor | The color used to color the icon in normal mode |
| altColor | The color used to color the icon in alternative mode |


Thank you for taking the time to help us improve our service
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$def with (profile, target) $:{RENDER("common/stage_title.html", ["Edit Streaming Settings", "Settings"])} $code: def _SELECTED(x): return ' selected="selected"' if profile['streaming_status'] == x else ''
Required if you set the stream status to "now streaming". This must be length of time, in minutes, during which that you expect to be streaming. Your streaming status will be automatically turned off after this time. This value is limited to 6 hours, or 360 minutes.


Employ Auto Scaling (image from Amazon Web Services)
Employ Auto Scaling.
Employ Auto Scaling from the command line.
SSH into the AWS CLI Environment that you setup in section 1.1 and type a command similar to the following: (NOTE: Your group id will be different than the one listed below).
To setup an auto scaling group, from the same AWS CLI environment, type:
To verify that the Auto Scaling Group was created, type as-describe-auto-scaling-groups from your AWS utility instance.
To verify that the Launch Configuration was created, type as-describe-launch-configs from your AWS utility instance.
To delete the Auto Scaling Group, type as-delete-auto-scaling-group from your AWS utility instance.
To delete the Launch Configuration, type as-delete-launch-config from your AWS utility instance.


Samsung W20 5G foldable phone stops at TENAA - Gizchina.com
by Efe UdinSamsung W20 5G foldable phone stops at TENAA
1 (20%) 1 vote
After the release of the Samsung Galaxy Fold and the numerous issues that followed, Samsung now has more experience with foldable phones. There have been several reports that the company is working on another foldable device. Now, the Samsung W20 5G foldable phone has made a quick stop at TENAA with model number SM-W2020.
According to TENAA’s listing, this smartphone will come with a 4.6-inch display (folded) and a 4135 mAh battery. The phone measures 160.9 x 117.9 x 6.9 mm which is the same as the Samsung Galaxy Fold. The South Korean manufacturing giant released a series of posters earlier this week which shows that this smartphone will arrive on November 19 in Wuhan, China.
From the poster, the Samsung W20 5G phone folds in the same way as the Samsung Galaxy Fold. It is also folded left and right and looks almost the same. Samsung W20 5G mobile phone is likely to be the 5G version of the Samsung Galaxy Fold. Considering that Samsung Galaxy Fold sells for as much as 15,999 yuan ($2292), the Samsung W20 5G phone should approach 20,000 yuan ($2866). What do you think about the second foldable phone from Samsung? Let us know your thoughts in the comments.


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| new [ collectionOrClassId , ] pointerVariableReference |
var list : collection of
record
contents : string ( 10 )
next : pointer to list % Short form: next : ^ list
end record
var first : pointer to list % Short form: var first : ^ list
new list, first % Short form: new first
class node
export var next, var name
name : string (25)
next : pointer to node % Short form: next : ^ node
end node
var start : pointer to node % Short form: var start : ^ node
new node, start % Short form: new start
type item:
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contents : string ( 10 )
next : pointer to item % Short form: next : ^ item
end record
var first : pointer to item % Short form: var first : ^ item
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In the new statement, the collectionOrClassId can be omitted. If the pointer locates a type, it must be omitted. The free statement is used to deallocate an element.
An imported class can have one of its objects created (by the new statement) only if the class is imported var.
If there is no more space to allocate an element, new will set the pointer to be the nil value, and the program will continue executing.
If the pointer locates class C and C contains an implement by list, the object created by new is the inherited object (through any number of levels of implement by). The pointer, however, remains a pointer to C.
The form new p is a short form for new C, p when C is the class or collection given in p's type.
If p is a pointer to class C and C has a descendant (expansion) class D, a new statement can be used to allocate an object of type D, as in:
If D has an implement by clause, the expansion is created.
new D, p % Allocates an object of class D
The indices may have compile-time or run-time upper bounds (the lower bound must be compile-time). The upper bounds can be changed by using:
The existing array entries will retain their values, except that any index made smaller will have the corresponding array entries lost. Any index made larger will have the new array entries uninitialized (if applicable).
Additionally, the upper bound (both in the declaration and the new statement) can be made one less than the lower bound. This effectively makes an array that contains 0 elements. It can later be increased in size with another new.
In the current implementation (1999), with a multi-dimensional array with a non-zero number of total elements, it is a run-time error to change any but the first dimension (unless one of the new upper bounds is one less than the corresponding lower bound, giving 0 elements in the array) as the algorithm to rearrange the element memory locations has not yet been implemented.
Currently, only variables can be declared in this form. There is no flexible array parameter type, although a flexible array can be passed to an array parameter with "*" as the upper bound.
var name : flexible array indexType { , indexType } of typeSpec
new name , newUpper1 {,newUpper2}
For flexible arrays, see also array and flexible.


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## mako <%page expression_filter="h"/> <%! from django.utils.translation import ugettext as _ %> <%namespace name='static' file='../static_content.html'/> <%inherit file="../main.html" /> <%block name="pagetitle">${_("About Us")}%block>
Iwiz is an independent platform offering online courses to anyone, anywhere, anytime. Iwiz is where lifelong learners come to learn the skills they need, to land the jobs they want, to build the lives they deserve.


no-fastclick Class
Tap Hold Event (Long Tap)
Touch Ripple
Touch Ripple is supported only in Material Theme
Ripple Elements
Ripple Wave Color
Disable Ripple For Specific Elements
Touch Ripple is supported only in Material Theme
Ripple Elements
Ripple Wave Color
Disable Ripple For Specific Elements
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Quisque ac diam ac quam euismod porta vel a nunc. Quisque sodales scelerisque est, at porta justo cursus ac.


Through a series of very fortunate coincidences I found myself learning a great deal of Salvia Divinorum from multiple sources over the course of my young life, but I haven't felt that my intent was right, or that I was impeccable enough as a man to tackle such a plant. It takes a great deal of respect and power for Salvia to 'accept' you. I didn't choose Salvia; it chose me.
I meditated for an hour or so beforehand, partly because I knew it was a good idea in itself, and partly because my last hallucinogenic experience was 2 years prior.
My friend B packed a bowl (for a bong) and I sat in the middle of his backyard; no lights on, and no moon out. B and his older brother (also a good friend) stood by. As I exhaled, everything went blank and I found myself in an endless spiral of Mes! All lined up naked bodies rotating clockwise into nothingness, similiar to looking into two mirrors until the image dissapears. My mind would continually try to latch onto one of them, failing each time, while feeling surges of anxiety as each 'me' that was clung on to was lost in infinity. This happened for an indeterminable amount of time, until, luckily, I realized that it wasn't so bad just being part of it all, and singling myself out was a waste of time. Bam! The image scaled back to a piece of meat sitting on a table and a butcher whacked down on it with a huge knife.
I stood up in the middle of a cornfield of unlimited expanse and there were several shadows around me. One came uncomfortably close to me and whispered something about raping time. 'I had raped time?' An overwhelming rush of guilt came over me for a moment, but I stuffed it into the past and moved on, because the shadows and the lighting were intriguing. The Yard was coming back into focus and as it did, I fancied a waterfall that looked very sinister, like the Fiji water bottle backround (yes, sinister), coming down from the southernmost wall of the yard. I wondered how long I could hold the waterfall there, and I rounded off the figure at about 3 minutes. The next 20 minutes my thoughts and actions were very helter skelter and absentminded. My body was weak and jellowy. I needed to recoop.
The feeling of affecting time or stopping the flow of infinity seems to be a consistant theme amongst people I know. I believe it to only be a barrier of the ego and self importance.
PS. My guides reported that I had fallen back, and raised my arms in the air, shaking them around slowly and sporadically. I mumbled inanities for a few moments and quickly stood up. All of my limbs were moving around sporadically as if they had a mind of their own, and my buddies thought I would fall over at any moment. At one point I almost did, and B grabbed my arm to steady me. His brother told me everything was alright, and B told me to 'Take My Time'. Heh. They helped me to a comfy chair and left be alone.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Oliver Zeigermann / @DJCordhose
Slides: http://djcordhose.github.io/react-workshop/2017_jsunconf_mobx_redux.html
State distributed over many components can make applications hard to understand and debug
Often more than one component depends on a certain part of state - especially hard to do when components are not even in the same hierarchy
State management and handlers are extracted from React components
Better separation of concerns


Class FilterOperation
The Filter Operation 'enum'.
This are the possible Filter Operations.
Abstract
Namespace: ep6
Package: ep6\Util\FilterOperation
Author: David Pauli<EMAIL_ADDRESS>Since: 0.1.3
Located at util/FilterOperation.enum.php
Namespace: ep6
Package: ep6\Util\FilterOperation
Author: David Pauli<EMAIL_ADDRESS>Since: 0.1.3
Located at util/FilterOperation.enum.php
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CONTAINS
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NOT_CONTAINS
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STARTS_WITH
|
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"startsWith"
|
String |
ENDS_WITH
|
#
"endsWith"
|
String |
UNDEF
|
#
"undef"
|


EU to be more 'assertive' says new chief Michel
Europe will become more "assertive" on the world stage, the new head of the European Council, Charles Michel, has vowed as he took over from Donald Tusk.
They staged a formal handover of the job in a ceremony featuring the symbolic ringing of a bell that Mr Tusk handed over to Michel in front of EU staff and reporters.
It was part of a wider transition in Brussels that will, from next week, also see a new European Commission - the EU's executive arm - take charge under Ursula von der Leyen.
The European Council president is tasked with representing the national leaders of EU member states who have final say over much of the bloc's business, and also chairing their regular summits.
Mr Michel, a 43-year-old former prime minister of Belgium, hailed Mr Tusk and his focus on maintaining European unity over the past five years as it weathered Brexit, a migration crisis, attacks by jihadists in several EU states, and financial tribulations.
But, he said, the time had come for the EU to become more "confident, self-assured and assertive" globally, notably by building common defence and security structures.
"We live in peace, but we must remain vigilant, very vigilant," he said.
That pledge matches ambition voiced by French President Emmanuel Macron, who argues Europe should have defence capabilities to match its economic heft.
Read more:
Who's who in the new European Commission?
The European Union is increasingly finding itself caught in trade tensions between ally the United States and China, having to deal with a forceful Russia, and security threats that cannot all be addressed by NATO.
"I want Europe to become the global leader of the green movement," said Mr Michel, lining up with Ms von der Leyen's commitment to tackle climate change.
Mr Tusk, 62 and a former premier of Poland, was applauded by the EU Council workers for so long he asked them to stop, "because I will start to cry".
He is to become the leader of the European family of the main conservative parties across the bloc, the European People's Party, which is the biggest grouping in the European Parliament.
He said his mandate tackling a series of different crises reflected a quote by filmmaker Alfred Hitchcock, which he paraphrased as: "I want a film that starts with an earthquake and works up to a climax."
Mr Michel, in a nod to Mr Tusk's famous bluntness, said that while he too was "open to dialogue," he would be "perhaps more cautious with my tweets - at least at the beginning - but I will also speak out when needed".


Topicstarter
Add the possibility to add serverlist to the platoon page.
Maybe reading from the presantation platoon text.
The server list could be something like this maybe
s) Server 1
s) Server 2
and you match the servernames
BrainFooLong
Administrator
Sounds good, i will see what i can do in the future.
Greetz


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CS110
Introduction to Computer Science
File System
The way files are organized
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Relative Path
Example
Rouben Meschian
rmeschian@gmail.com


Skyy Clark DROPS 30 in 59-Point BLOWOUT Win! 🥶
by SLAM StaffHigh School basketball is back on the West Coast. Led by four-star guard Skyy Clark’s 30-point performance, Heritage Christian (CA) HS defeated San Fernando HS last night.
High School basketball is back on the West Coast. Led by four-star guard Skyy Clark’s 30-point performance, Heritage Christian (CA) HS defeated San Fernando HS last night.


>
Crystal Collector
Welcome to Crystal Collector
Game Instructions
- A random number is displayed in the "Target" box.
- 4 crystals are displayed on the page.
- Clicks on a crystal will add a specific amount of points to the total score.
- Player wins if the total score matches the random number in the "Target" box.
- Player loses if the total score goes above the random number in the "Target" box.
- All crystal values are hidden and will change when the game restarts.
Target
Total Score
Wins
Losses


Static responsive grid with pure css. Javascript using native drag-n-drop to reorder for each screen size on desktop and mobile.
Download Latest ReleaseA static example without any javascript. Just a responsive grid.
Reorder using native drag-n-drop and a little bit of javascript.
Can move items around between multiple containers. No additional code.
Modify options on the fly or set them as data attributes.
Modify width and height while keeping items from overlapping
You can have different column counts, aspect ratios and gaps from the defaults.
There are 2 primary components - the css, which is responsible for positioning and the javascript plugin, used to change that positioning. You can use only the css without any javascript and still get a nice responsive grid.
Layout grid uses bootstrap's breakpoints by default (configurable). They are as follows:
|
Extra small devices Phones (<768px) |
xs |
|---|---|
|
Small devices Tablets (≥768px) |
sm |
|
Medium devices Desktops (≥992px) |
md |
|
Large devices Desktops (≥1200px) |
lg |
We start with the basic html structure:

Your content

lt-xs-h-6
on the lt-container means the height on screen size "xs" the height will be 6 counts. lt-xs-x-0
on the item means the x position on screen size "xs"
| lt-{size}-x-{number} | Horizontal Position on xs screen size, starts from and defaults to 0 |
|---|---|
| lt-{size}-y-{number} | Vertical Position on xs screen size, starts from and defaults to 0 |
| lt-{size}-w-{number} | Width on xs screen size, starts from and defaults to 1 |
| lt-{size}-h-{number} | Height on xs screen size, starts from and defaults to 1 |
Here's how it looks when every class for every screen size is set:

Your content

As with other bootstrap classes the smaller sizes act as the default for larger ones, so you need to set only the things that change of the larger sizes.
Javascript is initialized via data-arrange="lt-grid"
and setting up html5's draggable="true"
on the individual items. The javascript is initialized only on the event of a drag on these items.

Your content

Layout Grid comes with these options and their defaults. All of them can be changed both through javascript or using html5 data attributes. They can also be changed on the fly.
LTGrid.DEFAULTS = {
resize: true,
overlap: false,
compact: true,
params: {
lg: {
gap: 1,
maxWidth: Number.MAX_VALUE,
cols: 4,
aspect: 2/3
},
md: {
gap: 2,
maxWidth: 1200,
cols: 3,
aspect: 2/3
},
sm: {
gap: 3,
maxWidth: 992,
cols: 2,
aspect: 2/3
},
xs: {
gap: 4,
maxWidth: 768,
cols: 1,
aspect: 2/3
}
}
};
resize
is an option that when true will force the container of the grid to shrink to the shortest possible height, enclosing all the items.
overlap
when set to false will forbid "overlapping" so items that find themselves holding the same space will be pushed downwards.
compact
when set to true will try to reduce the vertical spaces between items as much as possible
params
holds the default values from the sass variables. You'll need to set them to the new values here if you've changed them in the sass file, since we can't infer them from the css automatically.
You can set options with data attributes:

...

Or with javascript directly
// Javascript
$('#grid').ltGrid({resize: false, params: {xs: {cols: 2}}});
// On the fly modification
$('#grid').ltGrid('option', 'resize', false);
$('#grid').ltGrid('option', 'params', {xs: {cols: 2}});
Layout grid has a lot of methods that it uses internally but can be called as part of the API - some of the methods are documented here, all the others have docs in the source.
Layout grid uses a "Rect" object internally to do calculations, this is simply an object that holds width, height, x and y, and has some utility methods along the way.
You can create your own "Rect" objects like this var rect = new $.lt.Rect(x, y, width, height)
.
rect.x
rect.y
rect.w
rect.h
attributes for x, y, width and height respectively
rect.bottom()
to get the height + y
rect.right()
to get the width + x
rect.intersect(rect2)
returns true if the two rects intersect
rect.setCss(classes, size)
Modify a "css classes" string with the pos and size of this rect, for a specific screen size
rect.loadCss(classes, size)
Load data from "css classes", for a specific screen size
$(..).ltRect()
is a jquery function that is a setter / getter for the "rect" object of a given widget.
You need to pass "size" as the first argument so it knows for which size the rect is being viewed / modified.
var rect = $('#widget1.lt').ltRect('lg')
rect.x = 2;
rect.w = 2;
$('#widget1.lt').ltRect('lg', rect);
$(..).lt_size()
is a jquery function to get the current "size" of the grid, can be "lg", "md", "sm" or "xs"
var size = $('#container').lt_size();
console.log(size);
$(..).ltGrid('option', option, value)
allows you to set an option on the fly
$('#container').ltGrid('option', 'compact', false);
$(..).ltGrid('compact')
Compacts the grid, reducing horizontal space. It ignores the compact option setting.
$('#container').ltGrid('compact');
$(..).ltGrid('resize')
Resize the grid, setting the minimum possible size for the container. It ignores the resize option setting.
$('#container').ltGrid('resize');
$(..).ltGrid('update')
Call resize and compact, based on the options.
$('#container').ltGrid('update');
$(..).ltGrid('reposition', $widget, {x: 1, y: 1, w: 1, h: 1})
Modify the position or size of a widget inside the grid (and call "update" method). Any parameter can be omitted so you can either set only position or only size.
$('#container').ltGrid('reposition', $('#widget1'), {x: 1, y: 1, w: 1, h: 1});
Layout grid only requires jquery. It uses native html5 drag-n-drop so all the browsers that support that (all the major browsers) should work.
Mobile browsers are also supported and it uses native touch events there.
Thanks a lot to the creator of gridster.js, where I got the inspiration for this plugin.
Built by Ivan Kerin as part of Clippings.com


Ragesh Kumar Ramachandran
Advisor : Dr Spring Berman
Autonomous Collective Systems Laboratory
Development of robot platforms that can be deployed in swarms to perform tasks autonomously over large spatial and temporal scales.
Many potential applications for robotic swarms, including exploration, environmental monitoring, disaster response, search-and-rescue, mining, and intelligence-surveillance-reconnaissance, will require to operate in dynamic, uncertain and GPS denied environments
Despite these limitations, it may be necessary for the swarm to characterize its surroundings, for instance to map obstacles, payloads for transport, or hazardous areas to avoid.
Our current research progress and future work focus on novel estimation and mapping strategies using robotic swarms in these types of applications.
An Advection-Diffusion-Reaction Based Approach to Mapping an Environmental Feature.
A Probabilistic Topological Approach to Quantifying Environmental Features.
A Probabilistic Approach to Constructing Topological Maps of an Environment.
Metric Map Construction using a Stochastic Robotic Swarm Leveraging Received Signal Strength.
Distributed mapping and information theoretic exploration.
Scalar Field Estimation by Large Networks with Partially Accessible Measurements.
Ongoing work
*Ragesh K. Ramachandran, Karthik Elamvazhuthi, and Spring Berman. An optimal control approach to mapping GPS-denied environments using a stochastic robotic swarm. In Int’l. Symp. on Robotics Research (ISRR), 2015
Mapping a single feature of interest using a robotic swarm without communication or localization capabilities.
Robotic swarms with stochastic behaviors.
Macroscopic abstraction using partial differential equations
Mapping formulated as an optimal control problem.
The most common approach in robotics is SLAM and probabilistic mapping.
Mapping an environment using a robotic swarm is a relatively new area of research in the robotics.
In Dirafzoon et al.(2013)a robotic swarm is used to identify the topological features of an environment from information about the times at which robots encounter other robots and environmental features.
Robot State Changes (Chemical Reactions)
Robot Motion Model
$$\textbf{X}_i(t + \Delta t) = \textbf{X}_i(t) + (\sqrt{2D \Delta t}) \mathbf{Z}(t) + \textbf{v}(t) \Delta t$$
No-flux Boundary Conditions : $\vec{n} \cdot (D\nabla u - \mathbf{v}(t)u) = 0 ~~~ on ~~\partial \Omega \times [0,T] $
Initial Condition : Gaussian density centered at a point $\mathbf{x}_0 \in \Omega$
u(x,t) := Active robot density, D := Diffusion coefficient, $\mathbf{v}(t)$ := Velocity field
k := Reaction rate constant, $K(\mathbf{x})$ := Feature Indicator Function (Map)
Objective Function
$$\underset{(\mathbf{u},K(\mathbf{x})) \in U^N \times \Theta_{ad}}{\min}\mathbf{J}(\mathbf{u},K) = \sum_{i = 1}^{N} W_i J_i(u_i) + \frac{\lambda}{2}\|K(\mathbf{x})\|^2_{L^2(\Omega)}$$ $$J_i(u_i) = \frac{1}{2}\left \| \int_{\Omega} u_i(\mathbf{x},t) d\mathbf{x} - g_i(t)\right \|_{L^2([0,T])}^2$$Admissible control inputs
$\Theta_{ad} = \{ K(\mathbf{x}) \in L^2(\Omega); ~K_{min} \leq K(\mathbf{x}) \leq K_{max} \}$With the macroscopic model as Constraint equations
The optimization problem is solved using a gradient descent approach
$$\mathcal{L}(\mathbf{u},\mathbf{p},K) = \mathbf{J}(\mathbf{u},K) + \sum_{i = 1}^{N} \langle p_i, \Psi_i(u_i,K) \rangle$$$\Psi_i(u_i,K)$ is the $i^{th}$ constraint and $p_i$ is the adjoint variable.
$$\mathbf{J}' = \sum_{i = 1}^{N} (\int_0^T(ku_ip_i)(\mathbf{x})dt) + \lambda K(\mathbf{x})$$
$p_i$ is computed by solving the adjoint equation.
The equations are solved backwards
Actual map
Estimated map
Absolute value of error
Actual map
Estimated map
Absolute value of error
Actual map
Estimated map
Absolute value of error
*Ragesh K. Ramachandran, Sean Wilson, and Spring Berman. A probabilistic topological approach to feature identification using a stochastic robotic swarm. In To appear in the Int’l. Symposium on Distributed Autonomous Robotic Systems (DARS), 2016
We consider the problem of mapping a bounded, unknown, GPS-denied 2D environment using a swarm of N robots.
The focus of the research is to find a scalable method to extract the map from the information obtained by resource constrained robots.
Our previous work, Ramachandran et al.(2015) uses a PDE based model of the swarm to solve the problem. But requires large number of robots.
Ramaithitima et al.(2016) propose an algorithm that covers the free space of the environment with robots and then constructs an approximate generalized Voronoi graph. But requires communication.
In Dirafzoon et al.(2015) persistent homology is applied on a point cloud of the domain’s free region based on encounter time with robots. But each robot requires identification label.
As a first step to solve this problem, we quantify the topological features (holes or obstacles) in the domain.
Type I: Robots receive accurate estimates of their global positions when they are close to the boundary of the domain.
Type II: Robots do not receive global position updates anywhere in the domain.
The displacement of a robot over a time step $\Delta t$ is given by: $$\mathbf{X}(t + \Delta t) = \mathbf{X}(t) + \mathbf{V}(t)\Delta t + \mathbf{W}(t)$$
Where,
$$\mathbf{V}(t) = [v_x(t),\ v_y(t)]^T = [v\ \cos(\theta(t)), \ v\ \sin(\theta(t))]^T$$ $$\mathbf{X}(t) = [x(t),\ y(t)]^T$$ $\mathbf{W}(t) \in \mathbb{R}^2$ is a zero mean Gaussian random vector
Data that robot $j \in \{1,...,N\}$ obtains at time $t_k \in [0, T]$, $k \in \{1,...,K\}$, consists of the element $d^j_k = \{\mu^j_k, \Sigma^j_k\}$.
$\mu^j_k \in \mathbb{R}^{2}$ is the mean of the robot's estimate of its $(x,y)$ position.
$\Sigma^j_k \in \mathbb{R}^{2\times2}$ is the covariance matrix of its position estimate.
Both at time $t_k$
Discretize the domain into a high-resolution uniform grid. $m_i$ denotes a grid cell.
Use the robots' data to assign each grid cell $m_i$ a probability $p^f_i$ of being free.
Integrate the Gaussian distribution with mean $\mu^j_k$ and covariance matrix $\Sigma^j_k$ over the cell region to obtain $p^f_i$.
Assign a score $s_i \in [0, \infty)$ to each grid cell $m_i$. $s_i = \frac{1}{\left | P_i \right |}\sum _{p \in P_i} \log\left ( \frac{1}{1 - p} \right )$. Where $P_i = \{p_{ijk} ~|~ p_{ijk} > \rho, \rho > 0\}$ and $p_{ijk}$ is computed using the $k^{th}$ data element of the $j^{th}$ robot.
Finally, $p^f_i$ of each grid cell being free is computed as $p_{i}^{f} ~=~ 1 - (\exp(s_i))^{-1}$.
30 point robots deployed for 200 seconds
30 point robots deployed for 200 seconds
Point cloud is obtained by sampling a dense, uniformly random set of points from the domain based on a probability map of the domain and rejecting those points that are inside a grid cell whose $p^f_i$ is below a given threshold.
Landmark points are selected from the point cloud using the sequential max-min algorithm.
Finally, a Rips complex based filtration is constructed from landmark points and barcode diagrams are extracted.
The procedure was tested for Type I & Type II scenarios.
vectors $v_0, v_1, ..., v_k \in \mathbb{R}^n$ are affinely independent if the vectors $ v_1 - v_0, ..., v_k - v_0 $ are linearly independent.
A $k$-simplex $\sigma \subset \mathbb{R}^n$ can be defined as the convex hull of $k+1$ affinely independent vectors $\{v_0, v_1, ..., v_k\}$, called vertices. $\sigma = [v_0, v_1, ..., v_k]$
A face $\tau$ is the convex hull of a subset of $\{v_0, v_1, ..., v_k\}$
A simplicial complex $\kappa$ is defined as a finite collection of simplices $\sigma$.
Rips complex is formed by choosing a parameter $\delta > 0$ and adding a $k$-simplex to the simplicial complex if every vertex in the simplex is within a distance $\delta$ from every other
If $f: \kappa \to \mathbb{R} $ is a function such that $\tau \leq \sigma$ implies that $f(\tau) \leq f(\sigma)$, then $f^{-1}((-\infty, \delta])$ is a simplicial complex denoted by $\kappa_\delta$ and $\delta_1 \leq \delta_2$ implies that $\kappa_{\delta_1} \subseteq \kappa_{\delta_2}$, yielding a filtration of simplicial complexes with $\delta$ as the filtration parameter.
A barcode diagram is a graphical representation used to identify the persistent topological features
No features
One feature
Two features
Three features
Four features
No features
One feature
Two features
Three features
Four features
No features
One feature
Two features
Three features
Four features
No features
One feature
Two features
Three features
Four features
30 point robots deployed for each simulation
Time of deployment for each simulation : 200 seconds
One feature
Two features
Three features
*4 robots deployed for 180 seconds
*Ragesh K. Ramachandran, Sean. Wilson, and Spring. Berman. A probabilistic approach to automated construction of topological maps using a stochastic robotic swarm. IEEE Robotics and Automation Letters, 2(2):616–623, April 2017.
How to find an automated procedure to threshold the density function in order to isolate the obstacle region?
Can we build a topological map of the domain?
Topological map of a domain with three obstacles1
1Taken from Dr.Markus Haid blog
A filtration is generated by the thresholding the probability map and constructing a simplicial complex at each level and choosing $\delta$ = 1 − threshold ($\alpha$) as the filtration parameter
The barcode generated out of this filtration can be used to compute optimal threshold and identify number of obstacle.
Actual Domain
Computed density function
$\delta$ = 0.2
$\delta$ = 0.3
$\delta$ = 0.4
$\delta$ = 0.5
$\delta$ = 0.6
$\delta$ = 0.8
The grid cells with $p^f_i < \alpha_{opt}$ belong to an obstacle.
Classify the grid cells in each obstacle and identify its boundary.
A graph is constructed with obstacle grid cell centers as vertices and the cells are classified by performing a BFS on this graph
The boundaries of each obstacle are identified as the elements in graph that belong to the same obstacle and have fewer than four neighbors.
Barcode
Segmented Obstacles and their Boundaries. The boundary is shown in black.
A wave propagation algorithm is used to generate the approximate Generalized Voronoi Diagram(AGVD).
A graph is constructed in the same manner as the obstacle graph.
The algorithm is a modified form of Dijkstra's algorithm.
The algorithm outputs the set of vertices which constitutes the topological map of the domain in the form of a discrete AGVD.
One Obstacle
Two Obstacles
Three Obstacles
Four Obstacles
Experimental Setup with Pheeno robot platform1
1Sean Wilson et al., IEEE R-AL, July 2016
Map Overlaid on the Arena
Probability map generation: $\mathcal{O}(NKM)$, where $N$ robots each collect $K$ items of data over a domain that is discretized into $M$ grid cells.
Simplicial complex construction and barcode generation : $\mathcal{O}(M^{2.372})$, but for most practical applications it is close to $\mathcal{O}(M)$.
Obstacle segmentation : $\mathcal{O}(M)$.
AGVD extraction using the wave propagation algorithm :$\mathcal{O}(M\log{M})$.
Worst case complexity of the approach : $\mathcal{O}(M^{2.372})$.
*Ragesh K. Ramachandran and Spring Berman. Automated Construction of Metric Maps using a Stochastic Robotic Swarm Leveraging Received Signal Strength. In revision for IEEE Transactions on Robotics, 2018.
We consider the problem of generating a metric map of a bounded, unknown, GPS-denied 2D environment using data collected by a swarm of N robots.
A robots are equipped with receivers to receive broad casted signals(wifi, bluetooth).
A mapping procedure is similar to the previous one, which is computing $p^f_i$ for each grid cell.
We prove the completeness of the mapping approach.
$\mathbf{S}(\mathbf{X}(t)) = [S_1(\mathbf{X}(t)), ~...,~ S_l(\mathbf{X}(t))]^T$, $l$ number of transmitters(here $l = 2$).
$S_i(\mathbf{X}(t)) = K_i Pow_i ||\mathbf{X}(t) - \mathbf{X}_i||^{-\alpha}$, where $\alpha \in [0.1, 2]$, $Pow_i$ is the transmitted signal voltage of transmitter $i$
$\mathbf{N}_S(t) \in \mathbb{R}^l$ and $\mathbf{N}_V(t) \in \mathbb{R}^2$ as vectors of independent, zero-mean normal random variables.
Extended Kalman filter used.
Lemma: The error in the robots' position estimates is uniformly bounded, with a common bound for all robots, if each robot follows the previously mentioned motion model and estimates its state vector using an extended Kalman filter based on the outputs in $\mathbf{Z}(t)$.
Finally, we prove the existence of a threshold value of $p_{i}^{f}$ that distinguishes the free grid cells from the occupied cells.
Theorem: Under the assumption of complete coverage of the domain, a grid cell $m_i$ is free if and only if there exists a threshold $\gamma \in [0, 1]$ for which $p_{i}^{f} > \gamma$.
No features
One feature
Two features
Three features
Four features
No features
One feature
Two features
Three features
Four features
Domain
Map
Absolute Value of error
Complex domain of size $20 m \times 20 m$, in which $N = 200$ robots were deployed for $T = 1200 s$
50 trails for each time of deployment.
50 trails for each number of robots.
*Ragesh K. Ramachandran, Zahi Kakish, and Spring Berman. Information correlated lévy walk exploration and distributed mapping using a swarm of robots. In preparation for IEEE Transactions on Robotics, 2018.
We consider the problem of distributed mapping of a bounded, unknown, 2D environment using a swarm of N robots with localization capabilities.
We also formulate an information theoretic approach for exploring an unknown environment using the robotic swarm.
An exploration strategy which combines information theoretic ideas with Lévy walks
Rather than moving in random directions as in Lévy walk direct the robots in direction with maximum information gain.
We use Mutual information between the distance measurement and estimated map as the metric to measure information gain.
At time $\tau$ robot $R^i$ decides on its velocity $\mathbf{v}^i_\tau$ which it would follow for a time interval $T^i_\tau$, by solving the following optimization problem:
$$^{*}\mathbf{V}^i_{\mathbf{t}(i)} = \underset{\left \|\mathbf{v}^i_\tau \right \|=s^i, \angle \mathbf{v}^i_\tau \in[-\pi, \pi]}{arg\ \max} \frac{\mathbf{I}[\mathbf{M^i}; \mathbf{Z^i_{\mathbf{t}(i)}}\ |\ \mathbf{X^i_{\mathbf{t}(i)}}]}{C(\mathbf{V^i}_{\mathbf{t}(i)})}$$The robots explore the unknown domain using our exploration strategy.
Simultaneously, each robot updates its occupancy grid map based on its laser range sensor measurements.
The robots' also update their map based on the map information from their neighbors.
Theorem: If each robot updates its occupancy grid according to the previous equation then under certain assumptions yeilds
$$\lim_{k \rightarrow \infty} \mathbb{P}_{m^i_j}[k] = <\mathbb{P}_{m_j}[0]>_{gm} \cdot \prod_{d \in \mathbf{d}} <\mathbf{u}_j[d]>_{gm}$$ Where $<\cdot>_{gm}$ is the geometric mean of the elements in a vector. $\mathbf{u}_j[d]$ is a vector of updates on $m^i_j$ based on all the measurements at time step $d$.Cave
Plain
Floor Plan
University of Frieburg
Robotics lab
Robot 1
Robot 4
Robot 8
Robot 9
Robot 12
Robot 14
Robot 37
Robot 45
Consensus over the occupancy grid maps by 50 robots
The effect of size of swarm robots on covering domain
Cave
Plain
Floor Plan
Coverage
Entropy
*Ragesh K. Ramachandran and Spring Berman. The effect of communication topology on scalar field estimation by large networks with partially accessible measurements. In Proceedings of the 2017 American Control Conference (ACC), Seattle, WA, USA, May 24–26, 2017.
We consider the problem of reconstructing a two-dimensional scalar field using measurements from a subset of a network with local communication between nodes.
The main focus of the research is a derivation of bounds on the trace of the observability Gramian of the system, which can be used to quantify and compare the field estimation capabilities of chain and grid networks.
A comparison based on a performance measure related to the $H^2$ norm of the system is also used to study the robustness of the network topologies.
Solution to estimation problem is associated with the observability of the system.
Little work on estimation of initial conditions other than through the inversion of the observability Gramian
Checking the rank condition for large interconnected systems is computationally ill-conditioned due to the high dimensionality of the observability Gramian.
A graph-theoretic characterization of observability has been more widely used than a matrix-theoretic characterization for large complex networked systems.
The observability of complex networks is studied in Yang-Yu Liu et al.(2013) using structural observability, which presents a general result that holds true for most of the chosen network parameters (the edge weights).
In Meng Ji et al.(2007), a graph-theoretic approach based on equitable partitions of graphs is used to derive necessary conditions for observability of networks
Alternately, Zhengzhong Yuan et al.(2013) uses a matrix-theoretic approach to develop a maximum multiplicity theory to characterize the exact controllability of a network based on the network spectrum.
Consider a set of N nodes with local communication ranges and local sensing capabilities.
Each node is capable of measuring the value of a scalar field at its location and communicating this value to its neighbors
The nodes take measurements at some initial time and transmit this information using a nearest-neighbor averaging rule
The problem is to reconstruct the initial measurements taken by all the nodes from the measurements of a subset of accessible nodes.
Chain topology
Grid topology
Illustration of the chain and grid network topologies. The blue circles are nodes and are labeled by numbers. Nodes in the yellow region are accessible nodes.
We define the information flow dynamics of node $i$ as: $$\frac{dx_i}{dt} = \sum_{(i, j) \in \mathcal{N}_i } (x_j-x_i)$$ $\mathcal{N}_i$ denote the set of neighbors of node $i$.
The information flow dynamics over the entire network becomes : $$\dot{\mathbf{X}}(t) = - \mathbf{L}(\mathcal{G}) \mathbf{X}(t), \mathbf{Y}(t) = \mathbf{C} \mathbf{X}(t)$$ $$\mathbf{X}(0) = \mathbf{X}_0.$$ $\mathbf{L}(\mathcal{G})$ denote the Laplacian of the graph. $\mathbf{Y}(t)$ is the measurement vector at time $t$.
We solve the scalar field reconstruction problem by posing it as an optimization problem. We frame our optimization objective as the computation of $ \mathbf{X}_0$ that minimizes the functional $J(\mathbf{X}_0)$, defined as :
$$J(\mathbf{X}_0) = \frac{1}{2}\int_{0}^{T}\left \| \mathbf{Y}(t) - \hat{\mathbf{Y}}(t) \right \|_2^2 dt + \frac{\lambda}{2}\left \| \mathbf{X}_0 \right \|^2$$subject to the constraint of the system dynamics. $\hat{\mathbf{Y}}(t)$ is the observed data.
The convexity of $J(\mathbf{X}_0)$ ensures the convergence of gradient descent methods to its global minima.
The gradient can be computed as :
$$\delta J(\mathbf{X}_0) = P(T) + \lambda \mathbf{X}_0$$We find $P(T)$ by solving following equation forward :
$$\frac{dP}{d\tau} = - \mathbf{L}^*(\mathcal{G})P(\tau) + \mathbf{C}^*\hat{u}(\tau), ~~~P(0) = 0$$Where $\hat{u}(\tau) \equiv \mathbf{Y}(T - \tau) - \hat{\mathbf{Y}}(T - \tau)$
$\mathbf{L}^*(\mathcal{G})$ and $\mathbf{C}^*$ are transposes of $\mathbf{L}(\mathcal{G})$ and $\mathbf{C}$ respectively
Actual field
Estimated field
Absolute value of error
Gaussian function estimation using 100 nodes with a chain communication topology. Temporal data is acquired from 30 nodes over a time period of 50 sec.
Actual field
Estimated field
Absolute value of error
Gaussian function estimation using 100 nodes with a grid communication topology. Temporal data is acquired from 30 nodes over a time period of 50 sec.
Actual salinity field
Estimated salinity field
Absolute value of error
Estimation of salinity (psu) over a section of the Atlantic Ocean at a depth of $25$ m. The network consists of 100 nodes with a grid communication topology. Temporal data is acquired from 30 nodes over a time period of 50 sec.
Comparing the chain and grid results, it is evident that there is some fundamental limitation arising from the network structure which makes the system with the chain topology practically unobservable.
Degree of observability is used as a metric to study effect of network structure.
Commonly used measures of the degree of observability (controllability) are the smallest eigenvalue, the trace, the determinant, and the condition number of the observability (controllability) Gramian
For large, sparse networked systems, the Gramian can be highly ill-conditioned, which makes numerical computation of its minimum eigenvalue unstable.
We use the trace of the observability Gramian which can be interpreted as the average sensing effort required to estimate its initial state.
We compute the estimate on the trace of the observability Gramian in form of upper and lower bounds.
We compared the chain and grid topology using the bounds on the trace.
Theorem: Let $\mathcal{G}$ be an unweighted, undirected graph that represents the communication network of a set of $N$ nodes with information dynamics and output map. If we label $\mathit{V(\mathcal{G})} $ such that $k \leq N$ sensor nodes in $\mathit{V(\mathcal{G})} $ are labeled as $1, 2, ..., k$, then $\mathbf{C} = \left[ \mathbf{I}_{k \times k}\ \mathbf{0}_{k \times (N - k)} \right]$. Assuming that $\mathbf{L}(\mathcal{G})$ is diagonalizable and that $\lambda_1 \geq \lambda_2 \geq ... \geq \lambda_N $ are its eigenvalues, there exist real constants $c_1 \leq c_2 \leq ... \leq c_N$ such that
$$\sum_{i=1}^{k} c_i ~\leq ~Trace\left( \mathit{W}_O(0,T) \right) ~\leq~ \sum_{i=0}^{k-1} c_{N-i}$$where $c_i = \int^{T}_{0} e^{-2\lambda_i t} dt$.
Let $\lambda_{N-i}^{c}$ and $\lambda_{N-i}^{g}$ denote the $(N-i)^{th}$ eigenvalue of $\mathbf{L}(\mathcal{G}_c)$ and $\mathbf{L}(\mathcal{G}_g)$, respectively.
Then, $\lambda_{N-i}^{c} = 4\sin^2 \left(\frac{\pi i}{2N} \right)$ and $\lambda_{N-i}^{g} = 4\sin^2 \left(\frac{\pi i}{2\sqrt{N}} \right)$ for $i \in \{0, 1, ..., k-1\}$, $k < \sqrt{N}$.
Applying the theorem, we get the upper bound on $Trace\left( \mathit{W}_O(0,T) \right)$ for the chain network as. $$T + \frac{N^2}{2\pi^2 } \left (\sum_{i=1}^{k-1}\frac{1 -e^{-2\frac{\pi^2 i^2}{N^2}T}}{i^2} \right)\ (Scales\ quadratically\ in\ N)$$
Similarly for the grid network we get, $$T + \frac{N}{2\pi^2 } \left ( \sum_{i=1}^{k-1}\frac{1 -e^{-2\frac{\pi^2 i^2}{N}T}}{i^2} \right )\ (Scales\ linearly\ in\ N)$$
Networks with 100 nodes
Networks with 10000 nodes
Comparison of the degree of observability based on the trace of the observability Gramian and its bounds. The trace is computed numerically using the eigenvalues of $\mathbf{L}(\mathcal{G})$.
We analyze the effect of noise on the output of first-order linear dynamics that evolve on chain and grid network topologies.
The $\mathcal{H}_2$ norm of a system gives the steady-state variance of the output when the input to the system is white noise and when the system is Hurwitz.
For unstable systems, the finite steady-state variance can be computed only when the unstable modes are unobservable from the outputs.
Consider the augmented system dynamics written as, $$\dot{\mathbf{X}}(t) = - \mathbf{L}(\mathcal{G}) \mathbf{X}(t) + \mathit{W}$$ where $\mathit{W} \in \mathbf{R}^N$ denotes a zero mean, unit covariance white noise process.
We can make the zero mode unobservable, in order to use the $\mathcal{H}_2 $ norm as a measure to quantify the effect of noise on the system output
Following the approach in Milad Siami et al.(2014) We make the zero mode unobservable by choosing the matrix $\mathbf{C}$ which annihilates the vector $\mathbf{1}_N$.
The $\mathcal{H}_2 $ norm, denoted as $\mathcal{H}_{\mathcal{K}_N} ^{(1)}(\mathbf{L}(\mathcal{G}))$, for a chosen $ \mathbf{C} $ can be defined from as $$\mathcal{H}_{\mathcal{K}_N} ^{(1)}(\mathbf{L}(\mathcal{G})) = \sum_{i = 1}^{N-1}\frac{1}{2\lambda_i}$$ where $\lambda_1 \geq \lambda_2 \geq ... \geq \lambda_N = 0 $ are the eigenvalues of $\mathbf{L}(\mathcal{G})$.
First order Laplacian energy
Experimental Validation of Reaction-Based Mapping with Nanoparticle Swarms
Extending the network theory work for network topology estimation using ideas from information geometry.
Distributed Multi Target Tracking based on random finite sets.
Circular obstacle
Nanoparticles near the circular obstacle
Grayscale image of a circular obstacle in a microfluidic channel, as seen under an electron microscope. 2$\mu$m Nanoparticles (in red) near the obstacle. The images are from the Bristol Robotics Laboratory.
Ragesh K. Ramachandran, Karthik Elamvazhuthi, and Spring Berman. An optimal control approach to mapping GPS-denied environments using a stochastic robotic swarm. In Int’l. Symp. on Robotics Research (ISRR), 2015.
Ragesh K. Ramachandran, Sean Wilson, and Spring Berman. A probabilistic topological approach to feature identification using a stochastic robotic swarm. In To appear in the Int’l. Symposium on Distributed Autonomous Robotic Systems (DARS), 2016.
Ragesh K. Ramachandran, Sean. Wilson, and Spring. Berman. A probabilistic approach to automated construction of topological maps using a stochastic robotic swarm. IEEE Robotics and Automation Letters, 2(2):616–623, April 2017.
Ragesh K. Ramachandran and Spring Berman. The effect of communication topology on scalar field estimation by large networks with partially accessible measurements. In Proceedings of the 2017 American Control Conference (ACC), Seattle, WA, USA, May 24–26, 2017.
Ragesh K. Ramachandran and Spring Berman. Automated Construction of Metric Maps using a Stochastic Robotic Swarm Leveraging Received Signal Strength. In revision for IEEE Transactions on Robotics, 2018.
Ragesh K. Ramachandran, Zahi Kakish, and Spring Berman. Information correlated lévy walk exploration and distributed mapping using a swarm of robots. In preparation for IEEE Transactions on Robotics, 2018.


After their highly-publicized search for a new drummer, Spinal Tap kicks off their latest comeback tour with a San Francisco show.
When:
Oct 15, 7:00PM
-
9:00PM
Where:
Warfield Theatre,
982 Market St,
San Francisco,
CA


All Posts
2018
- Microservice design principles Jun 14, 2018
- VPN speed benchmark - TunnelBear vs. ExpressVPN. Jan 23, 2018
- My future prediction in 2009 Jan 19, 2018
- Git aware prompt Jan 18, 2018
- Switch from Disqus to Facebook comment. Jan 17, 2018
- Visualization of the model, MNIST - Day 4. Jan 15, 2018
- The annoying MNIST - Day 3. Jan 12, 2018
- Stress test my Jekyll blog. Jan 10, 2018
- Tonny learns the MNIST - Day 2 Jan 05, 2018
- Intel Chip Flaw, the Meltdown Jan 04, 2018
- Protect yourself from Intel CPU hack Jan 03, 2018
2017
- Tonny learns the MNIST Dec 27, 2017
- Control SSL in gcloud with kube-lego Dec 25, 2017
- Test with goroutine and redis Dec 21, 2017
- How to add comment to static Jekyll webpage Dec 20, 2017
- Mass-add favicons to Jekyll on Github pages. Dec 19, 2017
- Tech blog with gfm on your own domain over ssl Dec 18, 2017


Biotechnology engineering is the research and study of micro-organism, bio-organisms, cell functions in living beings. It is basically the blend of both Biological science and technology. Biotechnology engineering is the field of chemical engineering and applied biology that incorporates the use of living things in technology, medicine, engineering and other significant applications.
Biotechnology engineering can be taken up at both undergraduate and postgraduate levels which would be for the duration for 4 and 2 years respectively.
The field has been one of the most sought-after fields, that is pursued by more than 50 per cent of the youth every year. Students with degrees in biotechnology can get into various healthcare centres, universities, hospitals, research centres, etc. They can also go for further studies in the field or become research scientists.
Biotechnology Engineering Career Options and Job Prospects
Job opportunities in the field of biotechnology engineering abound. A lot of environmental departments, healthcare services, pharmaceutical companies, drug and vaccine companies, etc. offer a good number of jobs to biotechnology engineering graduates. Biotechnology engineers deal with responsibilities like making use of biological systems to produce new products. They also work at universities or commercial labs and assisting in various researches. Companies like Samsung Healthcare, Stryker, Toshiba Medical Systems, Drager, etc. recruit biotechnology engineers every year and the scope for Biotechnology students has only grown in recent years.
Few of the job roles/positions that one can expect after completing Biotechnology engineering are:
Research Assistant Technical Assistants Scientists


Build relationships with the homeless in our city by hanging out at The Outlet at City Gospel Mission, a place where they can recharge and connect with people who care about them by providing positive interpersonal relationships.
In order to achieve a balance of both readability & relative scale across the entire codebase, we've selected a base-font size of 16px
since that is the number most commonly associated with modern browser defaults, e.g. 16px = 1rem
. Accordingly, this value has been used to override Bootstrap's $font-size-base
variable.
Use .page-header
for page headings
reachout: the outlet
Use .section-header
for headers on sub-sections
reachout: the outlet
Use .title
for item titles
reachout: the outlet
Use .control-label
for form or button group labels
reachout: the outlet
Use .collection-header
for collections header
reachout: the outlet
Use .component-header
for headers on cards, media objects and widgets
reachout: the outlet
Use .list-header
for list headers
reachout: the outlet
To provide the best possible reading experience for any content-heavy pages, we recommend rendering most copy with a font-size of 19px
. To ensure any copy (whether encapsulated with <p>
or not) is rendered at this size,
simply wrap the main content area of your page with <main>
or apply .main
to the parent element.
Build relationships with the homeless in our city by hanging out at The Outlet at City Gospel Mission, a place where they can recharge and connect with people who care about them by providing positive interpersonal relationships.
You can highlight a block of content by applying the .lead
selector to the containing parent element.
Build relationships with the homeless in our city by hanging out at The Outlet at City Gospel Mission, a place where they can recharge and connect with people who care about them by providing positive interpersonal relationships. Whether it’s playing cards, shooting pool or just sharing stories, friendships are built and hope is transferred at The Outlet. And through the relationships established there, the homeless are then encouraged to enter into long-term recovery programs.
Use the .quiet
selector when you want to decrease the prominence of a certain block of copy.
Build relationships with the homeless in our city by hanging out at The Outlet at City Gospel Mission, a place where they can recharge and connect with people who care about them by providing positive interpersonal relationships. Whether it’s playing cards, shooting pool or just sharing stories, friendships are built and hope is transferred at The Outlet. And through the relationships established there, the homeless are then encouraged to enter into long-term recovery programs.
Use .metadata
for secondary, related content...
Use .subtitle
to boost the prominence of certain content elements...
Find Freedom
Use .tagline
for accented copy...
Experience our live stream
Standalone a
tags are used for actions that don't warrant a button, yet are of next highest priority/utility.
Crossroads is one church happening in multiple locations.
Applying a class of .secondary
to an a
tag created a link that signifies a minor priority/utility. These links are also found beside a button or button group to Cancel an action.
Crossroads is one church happening in multiple locations.
All link styles can be combined with other utility classes, i.e., .pull-right
or .font-size-small
to alter look or layout.


Tanium SOUL package builder.
build_soul.
ShellParser
(*args, **kwargs)[source]¶Bases: argparse.ArgumentParser
Wrapper for argparse.
build_soul.
THIS_FILE
= '/github/new_pytan/tanium_soul_py/build_soul.py'¶The absolute path to this file, ala /path/to/package/script.py
build_soul.
THIS_PATH
= '/github/new_pytan/tanium_soul_py'¶The path of the directory containing THIS_FILE, ala /path/to/package/
build_soul.
THIS_SCRIPT
= 'build_soul.py'¶This scripts basename from THIS_FILE, ala script.py
build_soul.
TemplateProcessor
(tmpl_path)[source]¶Bases: object
Templatize the schema parsed from a WSDL file into an api.py.
CR
= '\n'¶Carriage return constant.
CR1
()¶Joiner method for joining lists with a single carriage return.
CR2
()¶Joiner method for joining lists with two carriage returns.
DTF
= '%Y-%m-%d at %H:%M:%S UTC'¶Date time format.
INDENTS
= {'i4': ' ', 'i8': ' '}¶Indentation variables used by self.tmpl.
SIMPLE_TYPES
= ['int', 'STR']¶Object types that represent ‘simple’ objects from the schema.
TMPL_FILES
= ['header.tmpl', 'object.tmpl', 'api_map.tmpl', 'all_map.tmpl', 'footer.tmpl', 'none_def.tmpl', 'list_doc.tmpl', 'item_doc.tmpl', 'doc_list.tmpl', 'doc_simple.tmpl', 'doc_complex.tmpl', 'class_list.tmpl', 'class_simple.tmpl', 'class_complex.tmpl', 'class_constant.tmpl', 'props_simple.tmpl', 'props_complex.tmpl']¶bom_enc
(raw, default='utf-8')[source]¶Determine encoding of raw by checking for a BOM, defaulting to default if none found.
now
¶Get the time right now.
read_file
(path)[source]¶Read path in as binary format, then convert to encoding using automatic BOM detector.
build_soul.
WsdlParser
(parser)[source]¶Bases: object
WSDL parser for Tanium’s SOAP API.
PARSER
= None¶XML parser to use.
SKIP_TYPES
= ['auth', 'command', 'return', 'tanium_soap_request', 'TaniumSOAPRequest', 'TaniumSOAPResult']¶Object names to skip from processing into an object type.
TYPE_MAP
= {'xsd:int': 'int', 'xsd:string': 'STR', 'xsd:long': 'int'}¶Map of XSD types to python types.
XPATH_ALL
= './xsd:all'¶Xpath used to find property elements for an object (starting from <xsd – complexType> element).
XPATH_CONSTANT
= './xsd:annotation/xsd:appinfo/typens:constants'¶Xpath used to find constant elements for an object (starting from <xsd – complexType> element).
XPATH_CONSTANT_NAME
= './typens:name'¶Xpath used to find constant name for a constant (starting from <typens – constant> element).
XPATH_CONSTANT_VALUE
= './typens:value'¶Xpath used to find constant value for a constant (starting from <typens – constant> element).
XPATH_SEQUENCE
= './xsd:sequence'¶Xpath used to find sequence elements for an object (starting from <xsd – complexType> element).
XPATH_TYPES
= './wsdl:definitions/wsdl:types/xsd:schema'¶Xpath used to find object elements (starting from <root> element).
map_type
(el)[source]¶Map the type attribute from el to a python object type.
Either a python built in type: int or STR (alias to unicode() on py2 and str() on py3) Or a python object type that references another schema object.
schema
(schema_el)[source]¶Parse each type_el under schema_el to get the properties, wsdl doc, soap name, and object name.
Each type_el will be transformed into a type_info dictionary ala:
- type_info = {
soap_name: ‘’, obj_name: ‘’, wsdl_doc: ‘’, attrs: {
- constants: [
- {
- name: ‘’, value: ‘’, value_type: ‘’,
},
], list_prop: {
soap_name: ‘’, obj_name: ‘’, obj_type: ‘’, attr: {},}, properties: [
- {
- soap_name: ‘’, obj_name: ‘’, obj_type: ‘’, attr: {},
},
],
}
}


BoilerPlate GULP4 / SASS / ES6
Minimal Gulp 4 boilerplate with Babel, Sass, ESLint, Browser-sync, and development/production optimization.
Development server :
gulp dev
Production build :
gulp prod


Billie Eilish among fans celebrating My Chemical Romance comeback
Billie Eilish was among the fans celebrating after alternative rock band My Chemical Romance announced they were reuniting.
The popular group had a dedicated following – especially among fans of the punk and emo genres – when they split up in 2013 after 12 years together.
On Thursday, they finally confirmed rumours they were getting back together for a reunion show in Los Angeles in December.
The news was soon trending around the world and fans shared their joy on social media.
Eilish, the teenage singer-songwriter who took the world of music by storm with her debut album earlier this year, shared a screenshot of the band’s tweet to her Instagram Story.
The 17-year-old captioned the post: “F***.”
Mike Shinoda, co-founder of rock band Linkin Park, said he was glad My Chemical Romance were back.
He tweeted: “Our shows with My Chemical Romance were some of my favourite shows of all time. All my love to Gerard and the boys.”
And American singer Finneas also expressed his joy about the comeback.
However, it was not just My Chemical Romance’s celebrity fans who celebrated.
Ordinary fans who had waited six years to see the group get back together took to social media, sharing feelings of nostalgia and disbelief.
My Chemical Romance were founded in New Jersey in 2001 by lead vocalist Gerard Way, guitarists Ray Toro, bassist Mikey Way and keyboardist James Dewees.
They were later joined by Frank Iero. The band is best known for hits including Helena, Teenagers and Welcome To The Black Parade, which reached number one in the UK singles charts in 2006.


a data scientist, machine learning engineer and full-stack software developer.
I am a full-stack python developer, data scientist, and machine learning engineer. I live in Norway and have work permission that is valid for the entire Norway. I can write backend and frontend codes with programming, develop applications in MVC pattern. Additionally,I have very advanced knowledge and experience in machine learning, deep learning, computer vision, NLP and statistics. I can obtain data, clean analyze it, visualize via Matplotlib, Seaborn, and Plotly, make data engineering, make them ready before Machine Learning Algorithms, and deploy machine learning models. I ranked 345 best data scientist among more than 172 000 data scientists and machine learning practitioners. Moreover, I have a master's degree in political science and public administration with A grades for all subjects, thus I can write very efficient reports and feedbacks in academic level. I was always ranked the best graduate in all schools and universities I graduated due to my outstanding grades.
I can use all the machine learning and deep learning algorithms and deploy machine learning models.
I can make data cleaning, wrangling, data analysis, feature engineering, develop machine and deep learning models, and make future predictions.
I can design and develops websites and applications using web technologies like HTML, CSS,and JavaScript with frameworks in Bootstrap, VueJS, ReactJs.


{% extends 'base.html' %} {% block title %}Page not found{{ block.super }}{% endblock %} {% block bodyclass %}home{% endblock %} {% block content %}
The page you are looking for cannot be found - sorry about that.


Going to UH Between
{{> Select_Form_Control name="driverGoingtoUHStart" placeholder="Earliest" options=timeOptions multiple=false }}
{{> Select_Form_Control name="driverGoingtoUHEnd" placeholder="Latest" options=timeOptions multiple=false }}
Leaving UH Between
{{> Select_Form_Control name="driverReturntoUHStart" placeholder="Earliest" options=timeOptions multiple=false }}
{{> Select_Form_Control name="driverReturntoUHEnd" placeholder="Latest" options=timeOptions multiple=false }}


WELCOME
TO DELANI STUDIO
AMAZING PEOPLE ARE MAKING AMAZING DESINGS IN A FUN ENVIRONMENT
When you work with us, you are part of a team of committed collaborators.all aspects of our software
development process are intergrated, interactive
and agile.
Our approach unifies design, development and product management to create exceptional products.
We start each project by understanding your business goals, the user's needs and the product requirements.
Then we help transalte them into effective and elegant solutions.
Before we sign a contract or write a line of code our team will spend the necessary time needed to understand your product vision
The outcome of this scoping session is proposal or high-level statement of work.
based on your requirements, we can provide a complete offering or just the pieces you need
Delani Studio
Mighty Ontario
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Jimm Carrey
Have a good day
Buttons
Burn Logo Mock-Up
Giraffe Restaurant


This user interface consists of a number of components:
In addition, there is also the functionality for saving optimised parts to an instance of JBEI-ICE.
The user can build up a part by dragging-and-dropping features from the palette of grey buttons. Tablet and smartphone users can add features to the part by double-clicking on the feature button in the palette.
The features available are described below in the feature section.
Individual parts may be named.
Upon selecting a given feature, the Feature panel becomes visible, allowing the specification of parameters specific to that feature. Examples of this include an amino acid sequence for a CDS, or a translation initiation rate (TIR) for an RBS. The feature will be bordered by a red warning box until these necessary features are specified.
Note that a restriction exists such that a RBS must be immediately followed by a CDS. Again, the RBS will be bordered by a red warning box if this restriction is not adhered to.
In the case of optimising RBS or CDS, an Organism must be specified from the autofill field.
Multiple parts may be specified, by either clicking the '+' icon, or by duplicating a specified part through the Copy icon. Individual parts can be viewed and edited by clicking the numbered pagination panel. Designs may be deleted, as can individual features within parts.
Upon completing the set of parts, and adhering to all restrictions, the Submit button will turn green, and the job may be submitted.
The Feature panel is specific to the selected feature, which can be one of the following types:
In each case, an individual Feature can be named.
In the cases of Defined sequence, Origin of replication, Promoter and Terminator, the only required parameter is the nucleotide Sequence itself. This sequence is fixed and not optimised by the PartsGenie algorithm.
Randomised sequence requires a Length of the sequence, which is periodically mutated through the optimisation sequence to optimise the part as a whole.
A Sequence of defined melting temperature requires a defined melting temperature (Tm).
Ribosome binding sites require a desired translation initiation rate TIR.
Coding sequences require an Amino acid sequence to be specified, which may be extracted automatically through the Search Uniprot facility:
In all cases, such Filters should be kept to a minimum, as specifying too many unnecessary constraints will increase optimisation time and, in some cases, prevent optimisation altogether. For example, specifying either too few max repeating nucleotides, or too many excluded codons or restriction sites may result in the design space being constraint to such an extent that no valid reverse translation of an amino acid coding sequence exists.
The Results panel allows for the inspection of all optimised parts, allowing for the part as a whole, and individual features, to be viewed.
Individual features can be viewed by selecting the feature, and metadata specific to that feature can be inspected. (This may include TIR for a RBS, or Codon Adaptation Index (CAI) - a measure of how optimised codon usage is for the target host organism - for CDS features.)
Once a user has logged into ICE, the ICE button will turn green, after which, parts may be Saved to JBEI ICE from the Results panel.
PartsGenie: an integrated tool for optimising and sharing synthetic biology parts.
Neil Swainston, Mark Dunstan, Adrian J Jervis, Christopher J
Robinson, Pablo Carbonell, Alan R Williams, Jean-Loup Faulon, Nigel
S Scrutton, Douglas B Kell.
bioRxiv, 189357
https://doi.org/10.1101/189357


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This study compares 7 differents encoders, AOM AV1, BPG, JPEG XL, RAV1E, SVT-AV1, WebP and WebP2. We use five algorithms in order to compare each format:
The image set is comprised of 49 images from the subset 1 maintained by Xiph. All images are RGB PNG.
https://github.com/AOMediaCodec/libavif
. The version used is 0.8.4.https://aomedia.googlesource.com/aom/
The version used is v2.0.0.https://github.com/AOMediaCodec/SVT-AV1
The version used is v0.8.6.https://github.com/xiph/rav1e
The version used is v0.4.0-alpha.https://github.com/mirrorer/libbpg
. The version used is 0.9.7.https://github.com/mozilla/mozjpeg
. The version used is 4.0.0.https://gitlab.com/wg1/jpeg-xl
. The version used is 0.1.1.https://chromium.googlesource.com/webm/libwebp
. The version used is 1.1.0.https://chromium.googlesource.com/codecs/libwebp2/
. The version used is built from GIT revision 3724e165a6df9260eb30b9a731a9f9594d3c5703
.vmaf
, provided by Netflix: https://github.com/Netflix/vmaf
. The version used is 2.0.0. Each metric compares two Y4M files.https://github.com/cloudinary/ssimulacra
The version used is built from GIT revision 375726b13f9dec2a01950e6710e7e9f488c52ea3
.https://github.com/kornelski/dssim
The version used is built from GIT revision 159d623a55fe8ba9b27e381e6b30657080617678
.https://github.com/google/butteraugli
The version used is built from GIT revision 71b18b636b9c7d1ae0c1d3730b85b3c127eb4511
.ffmpeg
is used for image formats conversion. The version used is ffmpeg 3.3.2.identify
is used to determine the width and height of images. The version used is ImageMagick 6.9.11-27.All images are compressed losslessly and over a range of qualities for each codec:
AOM:
avifenc --lossless --tilecolslog2 1 -c aom -s d -o [output] [input(PNG)]
avifenc --tilecolslog2 1 -c aom -s d --min $quality --max $quality -o [output] [input(PNG)]
BPG:
lossless: bpgenc -m 8 -f 420 -lossless -o [output] [input(PNG)]
bpgenc -m 8 -f 420 -q $quality -o [output] [input(PNG)]
JPEG XL:
cjxl [input(PNG)] [output] -v -q $quality
cjxl [input(PNG)] [output] -v -q 100
MozJPEG:
cjpeg -rgb -quality 100 [input(PNG)] > [output]
cjpeg -quality $quality [input(PNG)] > [output]
RAV1E:
avifenc --lossless --tilecolslog2 1 -c rav1e -s d -o [output] [input(PNG)]
avifenc --tilecolslog2 1 -c rav1e -s d --min $quality --max $quality -o [output] [input(PNG)]
AOM:
avifenc --lossless --tilecolslog2 1 -c aom -s d -y 420 -o [output] [input(PNG)]
avifenc --tilecolslog2 1 -c aom -s d -y 420 --min $quality --max $quality -o [output] [input(PNG)]
WebP:
cwebp -mt -z 9 -lossless -o [output] [input(PNG)]
cwebp -mt -q $quality -o [output] [input(PNG)]
WebP2:
cwp2 -mt 2 -q $quality -o [output] [input(PNG)]
cwp2 -mt 2 -q 100 -o [output] [input(PNG)]
The Python script used to generate the compressed images are available on the GIT repository.
The images which will be displayed on the website are then chosen among all compressed images, using the following criteria:
The Python script used to select the compressed images are available on the GIT repository.
For each codec and image, the encoding and decoding speeds for lossless compression are sampled using Python timeit
.
The arithmetic mean of encoding and decoding speeds are calculated over the entire image set. We then determine a Weissman score for each codec using the following formula:
where r
is the compression ratio over PNG filesize, T
the time required to compress, ̅r
and ̅T
the same metrics for the standard compressor, and alpha is a scaling constant.
The standard compressor used is the compression of a JPG image using mozjpeg.
For each codec and image, we apply the following metrics, SSimulacra, DSSIM, Butteraugli, SSIM, CIEDE2000, MSSSIM, PSNR-HVS-M and VMAF, over image samples of increasing quality. For VMAF, we use the trained model vmaf_v0.6.1
given by Netflix.
For SSimulacra and DSSIM, Butteraugli, we first decode the compressed image to PNG then we apply the metrics over each sample, comparing it to the original image.
For SSIM, CIEDE2000, MSSSIM, PSNR-HVS-M and VMAF, on each sample, we first decode the compressed image to PNG, then export the resulting file to 4:2:0 Y4M using FFMPEG (ffmpeg -y -i [input] -pix_fmt yuv444p -vf scale=in_range=full:out_range=full [output]
). Finally we apply the metrics over each sample, comparing it to the original image.
For each codec, we calculate the arithmetic mean of each metric over the entire set of images, weighted by the area of the corresponding picture, for the samples of increasing quality:
We also determine the average bits per pixel for each quality sample:
The following archives contain the raw data in csv format for subset1 and subset2:
| format | avg_bpp | avg_compression_ratio | avg_space_saving | wavg_encode_time | wavg_decode_time | weissman_score |
|---|---|---|---|---|---|---|
| jxl | 10.093 | 1.3007 | 0.23120 | 22.648 | 3.3466 | 1.2555 |
| webp | 10.510 | 1.2492 | 0.19947 | 42.614 | 3.0936 | 1.1343 |
| webp2 | 10.397 | 1.2627 | 0.20805 | 68.266 | 5.8399 | 1.0980 |
| mozjpeg | 13.959 | 0.9405 | -0.06330 | 8.983 | 0.5001 | 1.0000 |
| bpg | 13.722 | 0.9567 | -0.04521 | 17.480 | 4.2157 | 0.9480 |
| aom | 11.530 | 1.1386 | 0.12175 | 648.088 | 4.9324 | 0.8236 |
For each comparison algorithms, we plot the quality in dB or score in function of the mean bits per pixel on a logarithmic scale. We can then visualize which codec gives the best quality at a given bit per pixel (top left is better).
Please note that VMAF is more suitable as a video codec comparison tool, not an image one.


Insight is a SaaS web application developed by PayScale to provide businesses with detailed data, analytics, and visualizations for job market metrics.
My role with Insight was both as a developer and designer. I collaborated with PayScale’s internal design team on visual language development and component styles. We improved the various charts and graphs by emphasizing the relationship between data points and maintaining a clear information hierarchy. I then took final designs and crafted the HTML, CSS, and JavaScript for majority of the product.


{% extends 'email.'|add:email_format %}
{% block logo %}
{% if event_url == 'https://oval.hipeac.net/2020/' %}
{% else %}
{% endif %}
{% endblock %}
{% block header %}You are now registered for {{ event_name }}.{% endblock %}
{% block body %}
**Registration id: {{ registration_id }}**
You can visit the event page at any time and [update your registration information]({{ registration_url }}). We look forward to seeing you in {{ event_city }}!
Please come with a valid ID (identity card or a passport). For security reasons, you might be requested to show it.
{% if visa_requested %}
---------------
We've noticed in your registration form that *you need an invitation letter to apply for a visa*. To produce this letter, we would need the following information:
- Name and title
- Address and phone number
- Passport number
- Will you present something (paper/poster/talk) during the event?
As soon as you provide this information, we will send the invitation letter to you.
Please also let us know if the electronic copy is sufficient of if we should send the original signed letter to you by post.
Please contact if you have questions regarding your visa application.{% endif %}
{% endblock %}
{% block footer %}HiPEAC Staff{% endblock %}


Blindly applying defensive programming is a recipe for disaster
Depending on the system requirements, fault tolerance may be a priority for your product. This is especially true in mission-critical systems that need to consider high availability, data integrity, security & physical safety.
For instance, what happens when the “cowboy approach” is applied when developing a physical medical device without considering safety of humans (e.g.: patient, nurse, doctor). What about an offensive programming approach instead?
Of course, on the flip side, an overly defensive approach that’s not necessary may introduce unnecessary excessive schedule risk & be a terrible choice.
This brings us to the approach: being careful The official term for this is: defensive programming.
Ah, yes, thems big words…
Basically, you just assume that all data is suss, & all the bad possibilities (such as module & subsystem crashes) can happen at any moment.
You, as a developer, assume that, and only THEN do you start touching code. “Defensive programming” is really just that, we don’t need to overcomplicate theories here. This blog is about pragmatism. Useless talk just to sound smart has no place here.
To help us understand how to be defensive & identify the consequences, let’s put on our imagination hat & assume we are developers on an autonomous trading system (mission critical). For simplicity, we’ll just pretend to freeze time, & put a magnifying glass over just 1 layer in just 1 subsystem.
Let’s say… a client-side user interface layer doing a simple HTTP AJAX call to 1 API endpoint, & the UI is used by an operator (sentinel role).
Adventure time
When you think about it, a lot of suss things can happen between a client & server. That sexy boundary called the internet is a dangerous void. For instance:
- Xhr error (client side)
- Client and/or server Timeout
- All possible HTTP codes (including redirects)
- Auth issues
- Client-side middleware (e.g.: Redux epics failing)
- Dependency failures (client side)
- Client and/or server caching issues
- And of course, bugs!
But let’s slow down a bit, keep it simple, & just assume 1 of the factors listed above. Lets be defensive by assuming that the API is contactable & it may return 500, even if the API documentation doesn’t include a 500.
If our user interface did a simple AJAX call to 1 API in JavaScript via jQuery, it may look something like:
$.post(someUrl, someData)
.then(() => {…. });
If the API goes down, the promise will call reject
internally. And gosh, we’re such brave programmers. Running naked here - no catch!
So we’re being defensive, great. The next step in the defensive programming approach, is to check the situation we’re knee-deep in. Just lean back in your chair, let out a sighful breath, and reflect. Our CURRENT situation is a client-side program, being used be an operator, that is contacting an API. As a defensive programmer, we should to notify the operator that the API is actually down, right?
You don’t want to leave the operator guessing or waiting, otherwise the trading algorithms could go unmonitored. And that presents significant financial risk to your firm. Software is hard, & risks will always be present & devs will always make mistakes. But dont intentionally make a mistake that can be cheaply avoided. That is a serious no-no.
Defensive programming is mostly about complex, holistic self-reflection
Again, lets assess our situation. A financial mission-critical system with a human operator acting as a sentinel over trading algorithms. Now lets assume all data is suss, & everything possibly bad can happen.
A productive way to defensively program is to think of the worst possible scenarios, then work backward to the “safer” scenarios. The worst scenarios have low detectability, a high occurrence, & a high severity with significant consequences.
For instance, if a major market crash occurred (Japan, GFC, covid, commodities etc) & all of a sudden, our 1 API may experience a higher load. If there’s not enough company short-term funds (i.e.: pre-approved short-term liquidity) to elastically scale the backend to the very expensive levels necessary, the backend may get overloaded from all the data mining caused by the new information influx being posted on the internet (due to the financial crisis).
So in this case, the operator ABSOLUTELY NEEDS to know that somethings wrong, so they can then take appropriate action & keep the firm’s financial risk at bay during such an event.
Ah mate, this is easy!
So as a defensive programmer, you’d simply catch the HTTP call… right?
$.post(someUrl, someData)
.then(() => {…. })
.catch(() => console.error);
Nope, because whilst certain applications can show console-level errors, its usually hidden behind a menu. Our operator (who isn’t a dev) probably wouldn’t keep that pane open 24/7. Even if they did see the console message, they may not be technically capable to decrypting what the hell the message meant.
We thought we applied “defensive programming”. We thought we were smart! Oh how wrong we were, such foolishness. The humility is unbearable! Our thinking part is correct, but we just need to add a bit more sauce to effectively make use of defensive programming.
Right, lets just show something in the UI then?
$.post(someUrl, someData)
.then(() => {…. })
.catch(() => {
console.error(…);
toast.show(…);
});
Nope, we’re still screwed here unfortunately. If the console error logging mechanism fails (e.g.: a weakly-typed referenced variable is passed in, but was then renamed), the toast doesn’t show. Keep in mind, this is a mission critical system where everything can turn to crap in a single millisecond.
$.post(someUrl, someData)
.then(() => {…. })
.catch(() => {
toast.show(…);
console.error(…);
});
There we go bois. Good defensive programming, rightttttttttt?
Any failures in
toast.show
need to take a defensive programming approach. If it doesn’t & the code is outside out of your control (e.g.: a third-party toast library), your mission-critical application should NOT use it. You absolutely need to find a safe alternative, or build one in-house. Otherwise you could be posing significant legal risk for your firm.
All things considered, this level of defensive programming is sufficient (for our very simple scenario of 1 HTTP Ajax call).
Neato! I’m now gonna start being defensive. The words “Defensive programming” have a nice ring to it!
All things in software are contextual. If someone just says “lets do defensive programming” without actually describing a scenario, they probably need to have a closer look at the exact situation.
You can’t be defensive in all situations. It can be counterproductive when you’re NOT developing mission-critical applications. For instance, if you’re developing an internal-use-only library, the optimal approach may be OFFENSIVE programming, & defer additional handling to the consumers of your library. In this case, DEFENSIVE programming may actually increase schedule risk with negligible benefit (although at least you could say “I’m a defensive programmer, yay!”). Talk about tradeoffs, huh.
Analyse the specific situation at hand, use common sense, & take the right approach. Don’t just barge through the door like coolaid man & exclaim “we should be defensive in everything we do”. Software engineering is complex & theoretical, so make sure your choice of approach makes sense before committing on it.