Ideal Homecare Agency LLC is a privately owned company by a team of experienced nurses
who are committed in providing excellent homecare services. Our main goal is to prevent
clients from going into acute care facilities and foster their happiness by being around
family and providing care at well-known comfortable social environment. We truly understand
what it means to be around family for an elderly and sick population. Since we have experience
working with vulnerable elderly and sick population we want to provide optimum services from our
caring hands and loving hearts. We want to make difference in many people’s life, as we are
professional caring nurses.
Ideal Homecare Agency LLC was established in the year 2014 initiated by a group of young hard
working new American nurses. Our team members settled in The United State around 2008 and started
the dream of becoming compassionate nurses. Apparently it was not easy for our members to turn the
dream a reality in this foreign land. With constant hard work and dedication for years, we were able
to graduate as fresh nurses. During our working experience, we felt the extreme necessity of care
which is culturally appropriated to our clients, particularly for new Americans. Eventually, the idea
of establishing Ideal Homecare Agency LLC was developed as a platform to serve those needy populations.
Since nurses are always at front line while providing care, we as nurses firmly believe that we will
serve our clients in the best way possible because we know how to care. Also, we have learned difficulties,
hardships and the best way to help each other as we have had experience of refugee lives for two decades.
With constant hard work and continue education we are proud to have dedicated nurses in our agency standing
together hand in hand to serve the community in a very unique and well- managed way. We can bring all
our experiences into Ideal Homecare Agency to make this as a valuable asset to our needy population.
We together want to leave no stone unturned to make our services in favor of our growing needy population.
Your family is like our own and we stand by their side day in and day out making them feel happy and
proud for who they are.


GM's electric pickup truck to go on sale fall 2021: CEO
by ReutersDETROIT (Reuters) - General Motors Co's (N:GM) first electric pickup truck model will go on sale in the fall of 2021, the company's top executive said on Thursday, around the same time as electric carmaker Tesla Inc's (O:TSLA) own model is expected to debut.
"General Motors understands truck buyers and... people who are new coming into the truck market," Chief Executive Officer Mary Barra said, speaking at an investor conference on the same day Tesla is due to unveil its long-anticipated pickup truck model.


All Employee
Create an Employee
Take Attendance
Meeting Attendance Log
Report
Logout
Welcome Admin
All Employees
S/N
FirstName
LastName
Gender
Department
Designation
Email
Update
Delete


I grew up in Southern California as the third son in a family of 4 boys. I've always loved cars (owned 30+), and finally found my perfect vehicle category of adventure vans. I met the girl of my wildest dreams at college and after 7 yrs of marriage we welcomed our girl Bryar to the world at a beautiful birth center in Boulder, CO. Below are some photos of some of my greatest memories, my family I love, and some highlighted passions.


Latest OnePlus 7 and 7 Pro update comes with various bug fixes and performance enhancements
by Manuel VonauOnePlus has made a name for itself by providing stellar software support across its lineup. Continuing this tradition, the company announced today that it's rolling out OxygenOS 10.0.2 to the OnePlus 7 and 7 Pro. Other than bug fixes, the update brings various performance optimizations to both phones, as well as a video stability enhancement to just the 7 Pro. Sadly, the 5G version is still left in the cold.
While the improvements and fixes are all in all minor taken individually, they still offer some gains in terms of stability, connectivity, and power consumption. OnePlus touts that OxygenOS 10.0.2 boosts standby power consumption and charging with third-party bricks. Bluetooth and network performance should also be increased. The company has also fixed a few issues with blank screens, black bars, and volume problems with AirPods. On the security front, the Android patch level has been raised to the version from October.
-
System
- Optimized the standby power consumption
- Optimized the expanded screenshot feature
- Optimized the Bluetooth connectivity in the automobiles
- Improved the translation accuracy
- Optimized overall communication (network, phone calls, mobile data) performance
- Optimized charging performance with the third-party chargers
- Fixed the blank screen issue
- Fixed fingerprint icon animation issue
- Fixed the volume issue with AirPods
- Fixed the black bar issue while charging or playing a video
- Updated Android security patch to 2019.10
- Improved system stability and general bug fixes
-
Camera (7 Pro)
- Optimized the performance of Super Stable feature in the Video for the Camera app
The OnePlus 7 Pro has additionally received performance optimizations for the super-stable video mode in the camera app. Since this feature uses the wide-angle lens exclusive to that phone, it isn't available on the OnePlus 7.
The update is rolling out in stages, so it might take some time until it hits your OnePlus. When it becomes available, you'll get a notification.
Source:
OnePlus


public class Track
extends RelinkingAvailableResponse
Represents a music track on Spotify
| Constructor and Description |
|---|
Track(java.util.Map<java.lang.String,java.lang.String> _externalUrls,
java.util.Map<java.lang.String,java.lang.String> _externalIds,
java.util.List<java.lang.String> _availableMarkets,
java.lang.String _href,
java.lang.String _id,
java.lang.String _uri,
SimpleAlbum album,
java.util.List<com.adamratzman.spotify.models.SimpleArtist> artists,
boolean isPlayable,
int discNumber,
int durationMs,
boolean explicit,
LinkedTrack linked_from,
java.lang.String name,
int popularity,
java.lang.String previewUrl,
int trackNumber,
java.lang.String type,
java.lang.Boolean isLocal,
Restrictions restrictions)
Represents a music track on Spotify
|
| Modifier and Type | Method and Description |
|---|---|
int |
component10()
The disc number
|
int |
component11()
The track length in milliseconds.
|
boolean |
component12()
Whether or not the track has explicit lyrics
|
java.lang.String |
component14()
The name of the track.
|
int |
component15()
The popularity of the track.
|
java.lang.String |
component16()
A link to a 30 second preview
|
int |
component17()
The number of the track.
|
java.lang.String |
component18()
The object type
|
java.lang.Boolean |
component19()
Whether or not the track is from a local file.
|
Restrictions |
component20()
Part of the response when Track Relinking is applied,
|
SimpleAlbum |
component7()
The album on which the track appears.
|
java.util.List<com.adamratzman.spotify.models.SimpleArtist> |
component8()
The artists who performed the track.
|
boolean |
component9()
Part of the response when Track Relinking is applied.
|
Track |
copy(java.util.Map<java.lang.String,java.lang.String> _externalUrls,
java.util.Map<java.lang.String,java.lang.String> _externalIds,
java.util.List<java.lang.String> _availableMarkets,
java.lang.String _href,
java.lang.String _id,
java.lang.String _uri,
SimpleAlbum album,
java.util.List<com.adamratzman.spotify.models.SimpleArtist> artists,
boolean isPlayable,
int discNumber,
int durationMs,
boolean explicit,
LinkedTrack linked_from,
java.lang.String name,
int popularity,
java.lang.String previewUrl,
int trackNumber,
java.lang.String type,
java.lang.Boolean isLocal,
Restrictions restrictions)
Represents a music track on Spotify
|
boolean |
equals(java.lang.Object p) |
SimpleAlbum |
getAlbum()
The album on which the track appears.
|
java.util.List<com.adamratzman.spotify.models.SimpleArtist> |
getArtists()
The artists who performed the track.
|
java.util.List<com.neovisionaries.i18n.CountryCode> |
getAvailableMarkets()
A list of the countries in which the track can be played, identified by their ISO 3166-1 alpha-2 code.
|
int |
getDiscNumber()
The disc number
|
int |
getDurationMs()
The track length in milliseconds.
|
boolean |
getExplicit()
Whether or not the track has explicit lyrics
|
java.util.List<com.adamratzman.spotify.models.ExternalId> |
getExternalIds()
External IDs for this track.
|
java.lang.String |
getName()
The name of the track.
|
int |
getPopularity()
The popularity of the track.
|
java.lang.String |
getPreviewUrl()
A link to a 30 second preview
|
Restrictions |
getRestrictions()
Part of the response when Track Relinking is applied,
|
int |
getTrackNumber()
The number of the track.
|
java.lang.String |
getType()
The object type
|
int |
hashCode() |
java.lang.Boolean |
isLocal()
Whether or not the track is from a local file.
|
boolean |
isPlayable()
Part of the response when Track Relinking is applied.
|
java.lang.String |
toString() |
getLinkedTrack, isRelinked
getExternalUrls, getUri
getId
getHref, getId
public Track(java.util.Map<java.lang.String,java.lang.String> _externalUrls, java.util.Map<java.lang.String,java.lang.String> _externalIds, java.util.List<java.lang.String> _availableMarkets, java.lang.String _href, java.lang.String _id, java.lang.String _uri, SimpleAlbum album, java.util.List<com.adamratzman.spotify.models.SimpleArtist> artists, boolean isPlayable, int discNumber, int durationMs, boolean explicit, LinkedTrack linked_from, java.lang.String name, int popularity, java.lang.String previewUrl, int trackNumber, java.lang.String type, java.lang.Boolean isLocal, Restrictions restrictions)
Represents a music track on Spotify
album
- The album on which the track appears. The album object includes a link inhref to full information about the album.artists
- The artists who performed the track. Each artist object includes a link in hrefto more detailed information about the artist.isPlayable
- Part of the response when Track Relinking is applied. If true , the track is playable in thegiven market. Otherwise false.discNumber
- The disc number (usually 1 unless the album consists of more than one disc).durationMs
- The track length in milliseconds.explicit
- Whether or not the track has explicit lyrics ( true = yes it does; false = no it does not OR unknown).name
- The name of the track.popularity
- The popularity of the track. The value will be between 0 and 100, with 100 being the mostpopular. The popularity of a track is a value between 0 and 100, with 100 being the most popular. The popularityis calculated by algorithm and is based, in the most part, on the total number of plays the track has had and howrecent those plays are. Generally speaking, songs that are being played a lot now will have a higher popularitythan songs that were played a lot in the past. Duplicate tracks (e.g. the same track from a single and an album)are rated independently. Artist and album popularity is derived mathematically from track popularity. Note thatthe popularity value may lag actual popularity by a few days: the value is not updated in real time.previewUrl
- A link to a 30 second preview (MP3 format) of the track. Can be nulltrackNumber
- The number of the track. If an album has several discs, the track number is the number on the specified disc.type
- The object type: “track”.isLocal
- Whether or not the track is from a local file.restrictions
- Part of the response when Track Relinking is applied, the original track is not available inthe given market, and Spotify did not have any tracks to relink it with. The track response will still containmetadata for the original track, and a restrictions object containing the reason why the track is not available:"restrictions" : {"reason" : "market"}public java.util.List<com.neovisionaries.i18n.CountryCode> getAvailableMarkets()
A list of the countries in which the track can be played, identified by their ISO 3166-1 alpha-2 code.
public java.util.List<com.adamratzman.spotify.models.ExternalId> getExternalIds()
External IDs for this track.
public SimpleAlbum getAlbum()
The album on which the track appears.
The album object includes a link inhref to full information about the album.
public java.util.List<com.adamratzman.spotify.models.SimpleArtist> getArtists()
The artists who performed the track.
Each artist object includes a link in hrefto more detailed information about the artist.
public boolean isPlayable()
Part of the response when Track Relinking is applied.
If true , the track is playable in thegiven market. Otherwise false.
public int getDiscNumber()
The disc number
(usually 1 unless the album consists of more than one disc).
public int getDurationMs()
The track length in milliseconds.
public boolean getExplicit()
Whether or not the track has explicit lyrics
( true = yes it does; false = no it does not OR unknown).
public java.lang.String getName()
The name of the track.
public int getPopularity()
The popularity of the track.
The value will be between 0 and 100, with 100 being the mostpopular. The popularity of a track is a value between 0 and 100, with 100 being the most popular. The popularityis calculated by algorithm and is based, in the most part, on the total number of plays the track has had and howrecent those plays are. Generally speaking, songs that are being played a lot now will have a higher popularitythan songs that were played a lot in the past. Duplicate tracks (e.g. the same track from a single and an album)are rated independently. Artist and album popularity is derived mathematically from track popularity. Note thatthe popularity value may lag actual popularity by a few days: the value is not updated in real time.
public java.lang.String getPreviewUrl()
A link to a 30 second preview
(MP3 format) of the track. Can be null
public int getTrackNumber()
The number of the track.
If an album has several discs, the track number is the number on the specified disc.
public java.lang.String getType()
The object type
: “track”.
public java.lang.Boolean isLocal()
Whether or not the track is from a local file.
public Restrictions getRestrictions()
Part of the response when Track Relinking is applied,
the original track is not available inthe given market, and Spotify did not have any tracks to relink it with. The track response will still containmetadata for the original track, and a restrictions object containing the reason why the track is not available:"restrictions" : {"reason" : "market"}
public SimpleAlbum component7()
The album on which the track appears.
The album object includes a link inhref to full information about the album.
public java.util.List<com.adamratzman.spotify.models.SimpleArtist> component8()
The artists who performed the track.
Each artist object includes a link in hrefto more detailed information about the artist.
public boolean component9()
Part of the response when Track Relinking is applied.
If true , the track is playable in thegiven market. Otherwise false.
public int component10()
The disc number
(usually 1 unless the album consists of more than one disc).
public int component11()
The track length in milliseconds.
public boolean component12()
Whether or not the track has explicit lyrics
( true = yes it does; false = no it does not OR unknown).
public java.lang.String component14()
The name of the track.
public int component15()
The popularity of the track.
The value will be between 0 and 100, with 100 being the mostpopular. The popularity of a track is a value between 0 and 100, with 100 being the most popular. The popularityis calculated by algorithm and is based, in the most part, on the total number of plays the track has had and howrecent those plays are. Generally speaking, songs that are being played a lot now will have a higher popularitythan songs that were played a lot in the past. Duplicate tracks (e.g. the same track from a single and an album)are rated independently. Artist and album popularity is derived mathematically from track popularity. Note thatthe popularity value may lag actual popularity by a few days: the value is not updated in real time.
public java.lang.String component16()
A link to a 30 second preview
(MP3 format) of the track. Can be null
public int component17()
The number of the track.
If an album has several discs, the track number is the number on the specified disc.
public java.lang.String component18()
The object type
: “track”.
public java.lang.Boolean component19()
Whether or not the track is from a local file.
public Restrictions component20()
Part of the response when Track Relinking is applied,
the original track is not available inthe given market, and Spotify did not have any tracks to relink it with. The track response will still containmetadata for the original track, and a restrictions object containing the reason why the track is not available:"restrictions" : {"reason" : "market"}
public Track copy(java.util.Map<java.lang.String,java.lang.String> _externalUrls, java.util.Map<java.lang.String,java.lang.String> _externalIds, java.util.List<java.lang.String> _availableMarkets, java.lang.String _href, java.lang.String _id, java.lang.String _uri, SimpleAlbum album, java.util.List<com.adamratzman.spotify.models.SimpleArtist> artists, boolean isPlayable, int discNumber, int durationMs, boolean explicit, LinkedTrack linked_from, java.lang.String name, int popularity, java.lang.String previewUrl, int trackNumber, java.lang.String type, java.lang.Boolean isLocal, Restrictions restrictions)
Represents a music track on Spotify
public java.lang.String toString()
public int hashCode()
public boolean equals(java.lang.Object p)


Duration: *
Elevation: *
Pace: *
TrackPoint: *
The start time of the run as a Date object
The end time of the run as a Date object
The duration of the run in miliseconds
The duration of the run in human readable form
The minutes part of the pace time.
The max elevation of the route.
The min elevation of the route.
Elevation gained during run.
Elevation lost during run.
The seconds part of the pace time.
The lon coordinate of the trackpoint
The lat coordinate of the trackpoint
The elevation in meters of the trackpoint
The time of the trackpoint


The LuaCOM Library |
LuaCOM is an add-on library to the Lua language that allows Lua programs to use and implement objects that follow Microsoft's Component Object Model (COM) specification and use the ActiveX technology for property access and method calls. LuaCOM is implemented as a C++ library and must be embedded in some application in order to be used. LuaCOM is provided with its source code and the makefiles required to build it.
LuaCOM has been designed and implemented by Vinicius Almendra and Renato Cerqueira, at TeCGraf, the Computer Graphics Technology Group of PUC-Rio (the Pontifical Catholic University of Rio de Janeiro in Brazil). TeCGraf is a laboratory of the Department of Computer Science.
LuaCOM is available under the same terms and conditions as the Lua language, that is, it can be used at no cost for both academic and commercial purposes. Send your comments, bug reports and anything else to luacom % tecgraf.puc-rio.br
Copyright © 1998-2004 TeCGraf, PUC-Rio. All rights reserved.
Version 1.1 (for Lua 4 and Lua 5)
Online documentation
Browse online documentation (multiple HTML files)
Browse online documentation (single HTML file)
Download
- Manual (PDF, gzipped HTML)
- Binary Distribution Package (including a DLL version)
- Source Distribution Package
Version 1.0 (for Lua 4)
Online documentation
Browse online documentation (multiple HTML files)
Browse online documentation (single HTML file)
Download
- Manual (PDF, gzipped HTML)
- Binary Distribution Package (including a DLL version)
- Source Distribution Package
Older version
These versions are supplied for test purposes only and for those who need features recently added.
Version 1.2 Release Candidate 1
Online documentation
Browse online documentation (multiple HTML files)
Browse online documentation (single HTML file)
Download
- Manual (PDF, gzipped HTML)
- Binary Distribution Package (including a DLL version)
- Source Distribution Package
New features
- New table, called luacomE, that holds all extended API methods, to differentiate from the standard API methods;
- New extended method DumpTypeLib: it receives a COM object or a type library and outputs an HTML file describing the contents of the type library. Other method, ViewTypeLib, also shows the created HTML file.
- New extended method ExportConstants: receives a type library or a COM object and exports to the global environment all the constants defined in the type library. Can also export them to a table.
- New extented method GetType: identifies the type of an object managed by LuaCOM.
- LuaCOM now can receive events from all COM objects, not just those created with CreateObject or GetObject.
- New method CreateLuaCOM: creates a LuaCOM object using an IUnknown pointer.
- New method GetCurrentDirectory
- New method ImportIUnknown: transforms an userdata pointer into a LuaCOM-recognizable IUnknown pointer.
- Values of constants of an object's type library can be accessed through the object, as they were fields in the table.
- Now LuaCOM object have a predefined fields called "IUnknown", that returns IUnknown pointer of the object (not the IUnknown pointer recognized by LuaCOM, but an userdata to be used by C/C++ code.
- It's now possible to use a CLSID where a ProgID is expected.
- Now methods with variable number of arguments can be called.
- Arrays of bytes are automatically converted to and from strings with embedded zeros.
- To ease debugging, errors inside event calls can now be logged, as they are only sent to the callee and do not generate any message.
- Now it's possible to implement a parametrized property, storing a function in the field instead of a value.
- Changed features
- Type library objects now just have a subset of the methods available through ITypeLib (no more coclass field, enum etc). The same for type info objects.
- Removed features
- No more "typeinfo" and "typelib" fields in LuaCOM objects: now its necessary to use GetTypeInfo LuaCOM method and then the type info method "GetTypeLib".
- Files created by DumpTypeInfo and ViewTypeLib are no more automatically removed.
- ViewTypeLib creates its files in the directory pointed by the variables TEMP or TMP (in this order). If they don't exist, creates the files in the current directory.
Version 1.2beta (for Lua 4 and Lua 5) October, 13th
- New features:
- Part of the LuaCOM API for Lua5 now is implemented in Lua; nevertheless, this is transparent to the library user.
- luacom.CreateObject now accepts an optional paramenter telling the context in which the object should be created; e.g. luacom.CreateObject("MediaPlayer.MediaPlayer.1", "local_server")
- Added support for loading enumeration constants of the object's type library in the global lua environment (Lua5 only); e.g.: excel.typelib:LoadConstants()
- Now it is possible to browse through the type information of an object using obj.typeinfo and obj.typelib. These fields hold tables containing the type information.
- Added support for default methods. To call the default method of a COM object, do the call using the object, e.g.: Sheets(1) is the same as Sheets:Item(1). This replaces the deprecated feature of indexing collections like tables.
- Fixed bug of parameter order when LuaCOM objects where called using named parameters.
- support for enumerations: now it's possible get an enumerator with luacom.GetEnumerator(object) and to use its methods (Next, Skip, Reset, Clone).
- LuaCOM API function luacom.pairs, which does the same as pairs function in Lua5 for collections. It must be called supplying the Collection object, not the enumerator.
- luacom.GetObject now works with Monikers, e.g. object = luacom.GetObject("winmgmts::"). This can work too with file paths. Useful for WMI and powerpoint (at least).
- Better support for WMI objects: some fields that weren't accessible now can be accessed as methods e.g. drive:Caption(). In fact, LuaCOM can now access fields that aren't described in the type library.
- New configuration table: luacom.config, with some useful fields: abort_on_errors (default: true, if false luacom won't abort on errors outside LuaCOM API calls), abort_on_API_errors (default: false, if true the API functions will generate lua_errors), last_error (holds the text of the last exception or errors, in the case it has been ignored by the preceding flags).
- New log facility
- LuaCOM can log errors and exceptions. Can be used together with luacom.config.abort_on_... to track errors without stopping the applications.
- New API functions: luacom.StartLog(filename) and luacom.EndLog. Can be used to programmaticaly start and stop the log facility.
- If LUACOM_LOGFILE is defined with a filename when compiling lib, it automaticaly starts logging when luacom_open is called. E.g.: LUACOM_LOGFILE="\"luacomapplog.txt\""
- If LuaCOM is compiled with VERBOSE defined, it creates a default log file luacom.log in the current directory (if LUACOM_LOGFILE is not defined); it also makes LuaCOM log creation and destruction of LuaCOM internal objects. Useful to track application bugs and object leaks.
- luacom.DumpTypeInfo now prints better type information for LuaCOM objects, including IID.
- When LuaCOM gets an IUnknown value, it tests it for an IDispatch interface or for an IEnumVARIANT interface. If so, it creates a LuaCOM object for it, instead of returning a IUnknown object.
- Removed features:
- Use of the indexing operator ([]) with collections
Download
This page is maintained by Vinicius Almendra.


Play now
Online Scoreboard
Settings
About
Yes
No
Cancel
Message
Select a photo to begin, or pick from your phone menu
Settings
Puzzle Size
Rows
Columns
Show Numbers
Shuffle Rounds
Background music
Reset Settings
Submit your score
SCORE:
TOTAL SCORE:
Enter your name below
Reset Score
Loading...
org
mix


?BOTANICAL
GARDEN
^INSTITUTION
OF
WASHINGTON
?states
NATIONAL.
MUSEUM
WINDIAN
EXPLORATION
19*3
Springs,
porto
Rico
and
vicinity
Mastichodendron
NEW
YORK
BOTANICAL
GARDEN
e.
g.
Britton
)
?
ELIA
W.
MARBLE)
MARCH
17-22,
1913
New
York
Botanical
Garden
Arthur
Cronquist,
1944
01029176
01029176
Legend -
Level of confidence that token is an accurately-transcribed word
extremely low
very low
low
undetermined
medium
high
very high


Korea 5G service subscribers to top 5 million by year-end 2019
by Max Wang, Taipei; Steve Shen, DIGITIMESThe number of 5G service subscribers in South Korea is expected to reach over five million by the end of 2019, a significant growth from four million at the end of July, according to Samsung Electronics.
The fast build-up of 5G networks in Korea contributes to the exponential growth of its 5G service subscribers, said Daijun Zhang, president of Samsung R&D Institute China-Beijing (SRC-B).
The penetration rate of 5G networks in 85 cities in Korea will reach 93% by the end of 2019, providing applications such as smart manufacturing solutions for the B2B market, as well as cloud, VR and audio/video streaming services for the B2C market, Zhang indicated.
Judging from the growth of its service subscribers, the penetration rate of 5G service in Korea is growing about 2.5 times faster than that for the 4G service for the same period of time, making 5G development in Korea a benchmark globally, Zhang commented.
The launch of related 5G services has also helped raise ARPU (average revenue per user) by 20% for Korea's telecom operators, according to Chen Chi-meng, vice president of mobile and information business unit at Samsung Taiwan.
The penetration rate of 5G phones in Korea is expected to reach 30% in 2020, up from nearly 10% in 2019, Chen estimated, noting that Samsung currently accounts for 80% of Korea's 5G phone market.


Porsche 911 Turbo
Brake from 60mph-0 in about 2.6sec.
Specs
Price |
N/A |
Top Speed |
190mph(est.) |
Acceleration |
|
Engine |
|
0-30mph |
N/A |
Type |
Twin Turbo Flat-6 w/ Variable intake timing, 24valve DOHC |
0-60mph |
4.4sec |
Displacement |
3.6L |
0-100 |
9.3sec |
Power |
420hp@6000rpm |
1/4 mile |
N/A |
Torque |
412 lbs-ft@2700rpm |
Weight |
N/A |
Handling |
|
Gas mileage |
|
Skidpad |
N/A |
City |
N/A |
600ft slalom |
N/A |
Highway |
N/A |
Powertrain |
Rear engined, All wheel drive, 6 speed manual |
(? = incomplete data or unverified info, N/A = info Not Available)
Note: These are Porsche specs which tend to be slower than the cars limit
Beyond the specs:
Finally Porsche has given us the successor to the late 1995 Porsche Turbo continuing on the Porsche tradition of offering a very high performance turbocharged version of the 911 Carrera. Like past Turbos this one will surly be ahead of the competition in terms of braking and handling. With 420hp on tap it is clear Porsche once again has underestimated their product with 0 to 60 claims as slow as 4.4 seconds. This car more likely will get up to 60 in only 3.8 seconds putting it ahead of the Viper and Lamborghini Diablo (all except for the GT version). Its all the best the 911 has to offer with a few "minor" performance enhancements, like 120 extra horses under the hood (correction trunk). The new 911 Turbo has no current competition and will likely be aggressively priced like all the Turbos of yore. I wonder what the S version will be like.
~Oracle


This order is waiting for your approval.
Approve Order
Reject Order
This order has been rejected, do you want to change your mind?
Approve Order
Do you want to undo your rejection?
Approve Order
Do you want to undo your approval?
Retract Approval
ORD#{{ ("10000"+order.id).slice(-4) }} - {{ order.trader.name }}
{{ order.status === 'c' ? 'Combined' : order.status === 'p' ? 'Pending Approval' : order.status === 'd' ? 'Draft' : order.status === 'a' ? 'Approved' : order.status === 'f' ? 'In Shipment' : 'cancel' }}
Back
Edit Contract
Print
Re-
Request Approval
Cancel Order
Action
Toggle Dropdown
Back
Print
Request Approval
In Shipment
Edit Contract
Cancel Order
Request for Approval Notes : {{ order.request_reason }}
Cancel Notes : {{ order.cancel_reason }}
Finalize Notes : {{ order.finalize_reason }}
Created at {{ order.created_at | date:'mediumDate' }}, Last Update {{ order.updated_at | date:'mediumDate' }}
Approval
{{ showLog ? 'Hide' : 'Show' }} Log


dev/vignettes/not-built-vignettes/hagelloch-other-models.Rmd
hagelloch-other-models.Rmd
In this series of vignettes, we will demonstrate epidemic analysis pipeline from EDA to dissemination using a case study of measles.
Hagelloch 1 Pre-processing and EDA
Hagelloch 2.1 Modeling and Simulation: the SIR model
Hagelloch 2.2 Modeling and Simulation: fitting a SIR model
Hagelloch 2.3.1 Modeling and Simulation: a stochastic SIR model
Hagelloch 2.3.2 Modeling and Simulation: a stochastic SIR model
Recap our work with the Hagelloch vignette thus far
Explain EpiCompare
’s role in incorporating other models such as from EpiModel
.
Include side-by-side comparison of different models
In this series of vignettes, we have looked at the Hagelloch measles outbreak and suspect that the classes have different rates of infection. In particular, we suspect a ‘super-spreader’ event in the first class to be driving the fit of our models. This event makes it so that within that class the infection rate is very large and relatively small in the other compartments. Our model fits do not accurately capture the two peaks of infection seen in our data.
We now use the EpiModel
package to simulate a network-based outbreak on the Hagelloch children.
EpiCompare
works with your modeling packagesWe at EpiCompare
understand the importance and necessity of model variety and also the value of reproducibility in code. We aim to facilitate this important process by allowing users to more easily interact and assess different modeling paradigms.
We look at a couple here..
## WARNING: Will take a minute or two set.seed(42) nw <- network.initialize(n = 188, directed = FALSE) nw <- set.vertex.attribute(nw, "group", rep(0:2, each = 90, 30, 68)) formation <- ~edges + nodematch("group") + concurrent target.stats <- c(200, 300, 200) coef.diss <- dissolution_coefs(dissolution = ~offset(edges), duration = 5) est1 <- netest(nw, formation, target.stats, coef.diss, edapprox = TRUE) param <- param.net(inf.prob = 0.1, act.rate = 5, rec.rate = 0.1) status.vector <- c(rep(0, 90), rep(0, 30), rep(0, 67), 1) status.vector <- ifelse(status.vector == 1, "i", "s") init <- init.net(status.vector = status.vector) control <- control.net(type = "SIR", nsteps = 55, nsims = 100, epi.by = "group") sim_output <- netsim(est1, param, init, control)
fortified_net <- fortify_aggregate(sim_output, states = c("s.num", "i.num", "r.num"))
obs_groups <- hagelloch_raw %>% mutate(class = ifelse(CL == "1st class", 1, ifelse(CL == "2nd class", 2, 0))) %>% agents_to_aggregate(states = c(tI, tR), min_max_time = c(0, 55)) %>% rename(time = t, S = X0, I = X1, R = X2) ggplot() + geom_prediction_band(data = fortified_net, aes(x = X0, y = X1, z = X2, t = t, sim_group = as.numeric(sim)), alpha = .2, fill = "blue", color = "blue", conf_level = .9, pb_type = "delta_ball") + theme_bw() + coord_tern() + geom_path(data = fortified_net, aes(x = X0, y = X1, z = X2, group = factor(sim)), col = "cornflowerblue", alpha = .5, size = .3) + geom_point(data = obs_groups, aes(x = S, y = I, z = R ), col = "black")
Here we see that the above simulation covers the data quite well. However, upon closer inspection we see that the single paths (i.e. filaments) of an epidemic are generally not the shape of the observed data which has two distinct peaks.
plot(sim_output, type = "network", col.status = TRUE, at = 15, sims = 5)


Contacting other people
As part of your application you'll be asked for details of professional people who know about your condition.
This could include:
- doctors
- physiotherapists
- trade union representatives
To deal with your claim faster DWP may ask these people directly for information about you.


Rules Number of teams - No Restrictions. Registration fee Rs.100/- per student. Student of IT related departments of Arts and Engineering (Computer Science, Computer Technology, Information Technology and Software Engineering) can participate. Participant must have bonafide certificate and college identity card for spot registration. While selecting the event ensure that no clashes take place. Internet usage is prohibited. Judges decision is final. For more information visit www.kgisliim.ac.in
You can contact us in ways one is through mail service and another one is through phone
KGiSL Institute of Information Mangment
KGiSL Campus ,Thudiyalur Road Saravanampatti,
Coimbatore-641035,India
Phone:04224419999 Email<EMAIL_ADDRESS>Ahamed Johnsa Ali
Assistant Professor
Phone: +91<PHONE_NUMBER>
Email<EMAIL_ADDRESS>Padmanabhan
Assistant Professor
Phone:+91<PHONE_NUMBER>
Email Id:padmanabhan.c@kgisliim.ac.in


Beta This is a test version of the layout of this page. Take the survey to help us improve it
Notice
Industry Qualifications Ltd. (IQ) has been directed to address failings in its handling of a malpractice incident.
| Awarding organisation | Issue | Action taken | Case Status |
|---|---|---|---|
| Industry Qualifications Ltd (IQ) | Handling of a malpractice incident | Direction | Closed 1 April 2016 |
On 26 February 2016 Ofqual gave a direction to IQ setting out steps it must take to minimise prejudice to learners caused by defects in its investigation of allegations of malpractice.
IQ has subsequently issued a letter to affected learners setting out:
We write in respect of the above qualification (“your Qualification”) and further to our previous letter dated April 2015, in which we advised you that your Qualification had been withdrawn.
The decision to withdraw your Qualification was investigated by Ofqual and as a consequence we hereby confirm that your Qualification was not withdrawn. Your Qualification therefore remains valid from the date it was originally granted.
Please let us know whether you require replacement results or a certificate in respect of your Qualification. We are continuing to investigate … and may write to you again in due course as part of that ongoing investigation.
Ofqual is monitoring carefully IQ’s progress in complying with the direction.


You can use two new endpoints in the Repos API to enable or disable vulnerability alerts.
Custom media types: dorian-preview Announced: 2019-04-24
dorian-preview


Thank you for taking the time to contact us -- we'll reply as soon as we possibly can...
{% endif %} {% if messages or admin %}You can use the form below to ask questions about our products, make comments about the site, or anything else for that matter.
Though it's by no means necessary, if you have a Google account then you may wish to login using the link above. This will mean that we remember you details so you don't have to enter them on any future messages, and also that you can view a history of your messages sent, our replies and also any orders you make.
{% endif %} {% if not admin %}


ViewController
class ViewController : UIViewController
ViewController class which loads at the start
-
Undocumented
Declaration
Swift
override func viewDidLoad()
-
Example project to demonstrate the documentation generation using Jazzy Add
.jazzy.yaml
to project doc and typejazzy
from command terminal, document will be generated Follow this link for details<EMAIL_ADDRESS>Swift
func documentGenerationUsingJazzy()
-
Function to make navigation to rootVC or not
Declaration
Swift
func shouldNavigateToRoot(shouldNavigateToRoot: Bool)
Parameters
shouldNavigateToRoot
bool to check where the next view controller to be displayed is the root view controller or the previous view controller. if its true, its the root view controller, for false its the previous view controller


Project 3: Inference
Table of Contents
I can hear you, ghost.

Introduction
Pacman spends his life running from ghosts, but things were not always so. Legend has it that many years ago, Pacman's great grandfather Grandpac learned to hunt ghosts for sport. However, he was blinded by his power and could only track ghosts by their banging and clanging.
In this project, you will design Pacman agents that use sensors to locate and eat invisible ghosts. You'll advance from locating single, stationary ghosts to hunting packs of multiple moving ghosts with ruthless efficiency.
| Files you'll edit: | |
bustersAgents.py |
Agents for playing the Ghostbusters variant of Pacman. |
inference.py |
Code for tracking ghosts over time using their sounds. |
| Files you will not edit: | |
busters.py |
The main entry to Ghostbusters (replacing Pacman.py) |
bustersGhostAgents.py |
New ghost agents for Ghostbusters |
distanceCalculator.py |
Computes maze distances |
game.py |
Inner workings and helper classes for Pacman |
ghostAgents.py |
Agents to control ghosts |
graphicsDisplay.py |
Graphics for Pacman |
graphicsUtils.py |
Support for Pacman graphics |
keyboardAgents.py |
Keyboard interfaces to control Pacman |
layout.py |
Code for reading layout files and storing their contents |
util.py |
Utility functions |
Deadline: 2019 / 12 / 4
Files to Edit and Submit: You will fill in portions of bustersAgents.py
and inference.py
during the assignment. You should submit these files with your code and comments. Please do not change the other files in this distribution or submit any of our original files other than these files.
Evaluation: Your code will be autograded for technical correctness. Please do not change the names of any provided functions or classes within the code, or you will wreak havoc on the autograder. However, the correctness of your implementation -- not the autograder's judgements -- will be the final judge of your score. If necessary, we will review and grade assignments individually to ensure that you receive due credit for your work.
Academic Dishonesty: We will be checking your code against other submissions in the class for logical redundancy. If you copy someone else's code and submit it with minor changes, we will know. These cheat detectors are quite hard to fool, so please don't try. We trust you all to submit your own work only; please don't let us down. If you do, we will pursue the strongest consequences available to us.
Getting Help: You are not alone! If you find yourself stuck on something, contact the course staff for help. Office hours, section, and the discussion forum are there for your support; please use them. If you can't make our office hours, let us know and we will schedule more. We want these projects to be rewarding and instructional, not frustrating and demoralizing. But, we don't know when or how to help unless you ask.
Forum: Post your questions (but not project solutions) and discuss with classmates on the homework forum. Please be careful not to post spoilers to the forum.
Ghostbusters and BNs
In Ghostbusters, the goal is to hunt down scared but invisible ghosts. Pacman, ever resourceful, is equipped with sonar (ears) that provides noisy readings of the Manhattan distance to each ghost. The game ends when Pacman has eaten all the ghosts. To start, try playing a game yourself using the keyboard.
python busters.py
The blocks of color indicate where the each ghost could possibly be, given the noisy distance readings provided to Pacman. The noisy distances at the bottom of the display are always non-negative, and always within 7 of the true distance. The probability of a distance reading decreases exponentially with its difference from the true distance.
Your primary task in this project is to implement inference to track the ghosts. For the keyboard based game above, a crude form of inference was implemented for you by default: all squares in which a ghost could possibly be are shaded by the color of the ghost. Naturally, we want a better estimate of the ghost's position. Fortunately, Bayes' Nets provide us with powerful tools for making the most of the information we have. Throughout the rest of this project, you will implement algorithms for performing both exact and approximate inference using Bayes' Nets. The lab is challenging, so we do encouarge you to start early and seek help when necessary.
As you implement and debug your code, you may find it useful to run a single test at a time. For example if you want to run the first test of step 1, use:
python test.py -t test_cases/q1/1-ExactObserve
In general, some example test cases in first two steps can be found inside test_cases/q*.
Question 1 (0.8 Points): Exact Inference Observation
In this question, you will update the observe
method in ExactInference
class of inference.py
to correctly update the agent's belief distribution over ghost positions given an observation from Pacman's sensors. A correct implementation should also handle one special case: when a ghost is eaten, you should place that ghost in its prison cell, as described in the comments of observe
.
You can test by the following two commands:
python test.py -t test_cases/q1/1-ExactObserve
python test.py -t test_cases/q1/2-ExactObserve
As you watch the test cases, be sure that you understand how the squares converge to their final coloring. In test cases where is Pacman boxed in (which is to say, he is unable to change his observation point), why does Pacman sometimes have trouble finding the exact location of the ghost?
Note: your busters agents have a separate inference module for each ghost they are tracking. That's why if you print an observation inside the observe
function, you'll only see a single number even though there may be multiple ghosts on the board.
Hints:
- You are implementing the online belief update for observing new evidence. Before any readings, Pacman believes the ghost could be anywhere: a uniform prior (see
initializeUniformly
). After receiving a reading, theobserve
function is called, which must update the belief at every position. - Before typing any code, write down the equation of the inference problem you are trying to solve.
- Try printing
noisyDistance
,emissionModel
, andPacmanPosition
(in theobserve
function) to get started. - In the Pacman display, high posterior beliefs are represented by bright colors, while low beliefs are represented by dim colors. You should start with a large cloud of belief that shrinks over time as more evidence accumulates.
- Beliefs are stored as
util.Counter
objects (like dictionaries) in a field calledself.beliefs
, which you should update. - You should not need to store any evidence. The only thing you need to store in
ExactInference
isself.beliefs
.
Question 2 (0.8 Points): Exact Inference with Time Elapse
In the previous question you implemented belief updates for Pacman based on his observations. Fortunately, Pacman's observations are not his only source of knowledge about where a ghost may be. Pacman also has knowledge about the ways that a ghost may move; namely that the ghost can not move through a wall or more than one space in one timestep.
To understand why this is useful to Pacman, consider the following scenario in which there is Pacman and one Ghost. Pacman receives many observations which indicate the ghost is very near, but then one which indicates the ghost is very far. The reading indicating the ghost is very far is likely to be the result of a buggy sensor. Pacman's prior knowledge of how the ghost may move will decrease the impact of this reading since Pacman knows the ghost could not move so far in only one move.
In this question, you will implement the elapseTime
method in ExactInference
. Your agent has access to the action distribution for any GhostAgent
. In order to test your elapseTime
implementation separately from your observe
implementation in the previous question, this question will not make use of your observe
implementation.
Since Pacman is not utilizing any observations about the ghost, this means that Pacman will start with a uniform distribution over all spaces, and then update his beliefs according to how he knows the Ghost is able to move. Since Pacman is not observing the ghost, this means the ghost's actions will not impact Pacman's beliefs. Over time, Pacman's beliefs will come to reflect places on the board where he believes ghosts are most likely to be given the geometry of the board and what Pacman already knows about their valid movements.
For the tests in this question we will sometimes use a ghost with random movements and other times we will use the GoSouthGhost. This ghost tends to move south so over time, and without any observations, Pacman's belief distribution should begin to focus around the bottom of the board. To see which ghost is used for each test case you can look in the .test files.
As an example of the GoSouthGhostAgent, you can run
python test.py -t test_cases/q2/2-ExactElapse
and observe that the distribution becomes concentrated at the bottom of the board.
As you watch the output, remember that lighter squares indicate that pacman believes a ghost is more likely to occupy that location, and darker squares indicate a ghost is less likely to occupy that location. For which of the test cases do you notice differences emerging in the shading of the squares? Can you explain why some squares get lighter and some squares get darker?
Hints:
- Instructions for obtaining a distribution over where a ghost will go next, given its current position and the
gameState
, appears in the comments ofExactInference.elapseTime
ininference.py
. - We assume that ghosts still move independently of one another, so while you can develop all of your code for one ghost at a time, adding multiple ghosts should still work correctly.
Question 3 (1.2 points): Exact Inference Full Test
Now that Pacman knows how to use both his prior knowledge and his observations when figuring out where a ghost is, he is ready to hunt down ghosts on his own. This question will use your observe
and elapseTime
implementations together, along with a simple greedy hunting strategy which you will implement for this question. In the simple greedy strategy, Pacman assumes that each ghost is in its most likely position according to its beliefs, then moves toward the closest ghost. Up to this point, Pacman has moved by randomly selecting a valid action.
Implement the chooseAction
method in GreedyBustersAgent
in bustersAgents.py
. Your agent should first find the most likely position of each remaining (uncaptured) ghost, then choose an action that minimizes the distance to the closest ghost. If correctly implemented, your agent should win the game in smallHunt
with average score greater than 700 of 10 times.
To see the result by typing the following command:
python busters.py -l smallHunt -p GreedyBustersAgent -n 10
Note: If you want to run this test fast you can add the following flag:
python busters.py -l smallHunt -p GreedyBustersAgent -n 10 --frameTime=0
Hints:
- When correctly implemented, your agent will thrash around a bit in order to capture a ghost.
- The comments of
chooseAction
provide you with useful method calls for computing maze distance and successor positions. - Make sure to only consider the living ghosts, as described in the comments.
Question 4 (1.3 points): Approximate Inference Observation
Approximate inference is very trendy among ghost hunters this season. Next, you will implement a particle filtering algorithm for tracking a single ghost.
Implement the functions initializeUniformly
, getBeliefDistribution
, and observe
for the ParticleFilter
class in inference.py
. A correct implementation should also handle two special cases. (1) When all your particles receive zero weight based on the evidence, you should resample all particles from the prior to recover. (2) When a ghost is eaten, you should update all particles to place that ghost in its prison cell, as described in the comments of observe
. When complete, you should be able to track ghosts nearly as effectively as with exact inference.
To run your code for this question and visualize the output:
python test.py -t test_cases/q4/2-ParticleObserve
Hints:
- A particle (sample) is a ghost position in this inference problem.
- The belief cloud generated by a particle filter will look noisy compared to the one for exact inference.
util.sample
orutil.nSample
will help you obtain samples from a distribution. If you useutil.sample
and your implementation is timing out, try usingutil.nSample
.
Question 5 (1.3 points): Approximate Inference with Time Elapse
Implement the elapseTime
function for the ParticleFilter
class in inference.py
. When complete, you should be able to track ghosts nearly as effectively as with exact inference.
Note that in this question, we will test both the elapseTime
function in isolation, as well as the full implementation of the particle filter combining elapseTime
and observe
.
To run your code for this question and visualize the output:
python test.py -t test_cases/q5/1-ParticleElapse
For the tests in this question we will sometimes use a ghost with random movements and other times we will use the GoSouthGhost. This ghost tends to move south so over time, and without any observations, Pacman's belief distribution should begin to focus around the bottom of the board. To see which ghost is used for each test case you can look in the .test files. As an example, you can run
python test.py -t test_cases/q5/2-ParticleElapse
and observe that the distribution becomes concentrated at the bottom of the board.
Question 6 (1.3 points): Joint Particle Filter Observation
So far, we have tracked each ghost independently, which works fine for the default RandomGhost
or more advanced DirectionalGhost
. However, the prized DispersingGhost
chooses actions that avoid other ghosts. Since the ghosts' transition models are no longer independent, all ghosts must be tracked jointly in a dynamic Bayes net!
The Bayes net has the following structure, where the hidden variables G represent ghost positions and the emission variables E are the noisy distances to each ghost. This structure can be extended to more ghosts, but only two (a and b) are shown below.
You will now implement a particle filter that tracks multiple ghosts simultaneously. Each particle will represent a tuple of ghost positions that is a sample of where all the ghosts are at the present time. The code is already set up to extract marginal distributions about each ghost from the joint inference algorithm you will create, so that belief clouds about individual ghosts can be displayed.
Complete the initializeParticles
, getBeliefDistribution
, and observeState
method in JointParticleFilter
to weight and resample the whole list of particles based on new evidence. As before, a correct implementation should also handle two special cases. (1) When all your particles receive zero weight based on the evidence, you should resample all particles from the prior to recover. (2) When a ghost is eaten, you should update all particles to place that ghost in its prison cell, as described in the comments of observeState
.
You should now effectively track dispersing ghosts. To run your code for this question and visualize the output:
python test.py -t test_cases/q6/1-JointParticleObserve
Question 7 (1.3 points): Joint Particle Filter with Elapse Time
Complete the elapseTime
method in JointParticleFilter
in inference.py
to resample each particle correctly for the Bayes net. In particular, each ghost should draw a new position conditioned on the positions of all the ghosts at the previous time step. The comments in the method provide instructions for support functions to help with sampling and creating the correct distribution.
Note that completing this question involves removing the call to util.raiseNotDefined(). This means that the autograder will now grade both question 6 and question 7. Since these questions involve joint distributions, they require more computational power (and time) to grade, so please be patient!
As you run, note that q7/1-JointParticleElapse
and q7/2-JointParticleElapse
test your elapseTime
implementations only, and q7/3-JointParticleObserveElapse
tests both your elapseTime
and observe
implementations. Notice the difference between test 1 and test 3. In both tests, pacman knows that the ghosts will move to the sides of the gameboard. What is different between the tests, and why?
To run the autograder for this question use:
python test.py -t test_cases/q7/1-JointParticleElapse


WITNESS LIST Elections Committee March 16, 2005-2:00P HB 57 For: Borofsky, Cliff (Bexar County) Howard, Robert (Libertarian Party of Texas) On: Falick, Mike (Spring Branch ISD Board of Trustees) Registering, but not testifying: For: DeBeauvoir, Dana (Legislative Committee of the Texas County & Districts Clerks Association) Finch, Mary (League of Women Voters of Texas) Hammerlein, George (Paul Bettencourt, Harris County Tax Assessor-Collector) Lewis, Fred (Campaigns for People) Loewe, Lela (Texas Association of Election Admin.) Woodford, Suzy (Common Cause TX) Against: Reed, Katie (Texas Assn of School Bds/TX Assn of School Administrators) On: Houston, Scott (Texas Municipal League) Winn, Elizabeth H. (Sec. of State) HB 719 For: Borofsky, C. (Bexar County) On: Eckstein, Deece (People for the American Way) Registering, but not testifying: For: DeBeauvoir, Dana (Legislative Committee of the Texas County and Districts Clerks Assoc.) Howard, Robert (Libertarian Party of Texas) Lewis, Fred (Campaigns for People) Woodford, Suzy (Common Cause Texas) On: McGeehan, Ann (Secretary of State) HB 733 For: Borofsky, Cliff (Bexar County) Dale, Tony (Self) Hammerlein, George (Paul Bettencourt, Harris County Tax Assessor-Collector) Howard, Robert (Libertarian Party of Texas) McDonald, Audrey (Self) Summers, Frank (Milam County) Against: Falick, Mike (Spring Branch ISD Board of Trustees) Houston, Scott (Texas Municipal League) Lee, Donald (Texas Conference of Urban Counties) Reed, Katie (Self and TX Assn of School Bds/TX Assn of School Administrators) Registering, but not testifying: For: DeBeauvoir, Dana (Legislative Committee of the Texas County & Districts Clerks Assoc.) Edwards, Rosemary (Self) Venable, Peggy (Americans for Prosperity) On: Winn, Elizabeth (Sec. of State) HB 758 For: Hammerlein, George (Paul Bettencourt, Harris County Tax Assessor-Collector) Lee, Donald (Texas Conference of Urban Counties) Maxey, Glen (Self) Vanhoose, Laurie (Advocacy, Incorporated) Woodford, Suzy (Common Cause TX) On: Winn, Elizabeth H. (Sec. of State) Registering, but not testifying: For: Lewis, Fred (Campaigns for People) HB 855 For: Borofsky, Cliff (Bexar County) Against: Bacon, Tim (Texas State Teachers Assoc) Falick, Mike (Spring Branch ISD Board of Trustees) Registering, but not testifying: For: Edwards, Rosemary (Self) Hammerlein, George (Paul Bettencourt, Harris Tax Assessor-Collector) Venable, Peggy (Americans for Prosperity) Woodford, Suzy (Common Cause Texas) Against: Reed, Katie (TX Assn of School Bds/TX Assn of School Administrators) On: Winn, Elizabeth H. (Sec. of State) HB 963 For: Howard, Robert (Libertarian Party of Texas) On: McGeehan, Ann (TX SOS) Registering, but not testifying: For: DeBeauvoir, Dana (Legislative Committee of the Texas County & Districts Clerks Assoc.) Hammerlein, George (Paul Bettencourt, Harris County Tax Assessor-Collector) McDonald, Audrey (Self) Woodford, Suzy (Common Cause Texas) HB 1071 For: Valkavich, Helen (City of San Antonio) On: Luna Ashley, Natalia (Texas Ethics Commission) Registering, but not testifying: For: Barkan, Maxine L. (League of Women Voters of Texas) Lewis, Fred (Campaigns for People) Woodford, Suzy (Common Cause Texas) HB 1209 For: Dale, Tony (Self) McDonald, Audrey (Self) Summers, Frank (Milam County) On: Houston, Scott (TML) Winn, Elizabeth H. (Sec. of State) Registering, but not testifying: For: DeBeauvoir, Dana (Legislative Committee of the Texas County & Districts Clerks Assoc.) Hammerlein, George (Paul Bettencourt, Harris County Tax Assessor-Collector) Woodford, Suzy (Common Cause Texas) HB 1509 For: Howard, Robert (Libertarian Party of Texas) On: Winn, Elizabeth H. (Sec. of State) Registering, but not testifying: For: Lewis, Fred (Campaigns for People) HB 1510 On: Winn, Elizabeth (Sec. of State) Registering, but not testifying: For: Hammerlein, George (Paul Bettencourt, Harris County Tax Assessor-Collector) Howard, Robert (Libertarian Party of Texas) Lewis, Fred (Campaigns for People) HB 1511 On: Winn, Elizabeth H. (Sec. of State) HB 1614 For: Aten, Ross (Self) Hammerlein, George (Paul Bettencourt, Harris County Tax Assessor-Collector) Pratt, Robert (Lubbock Co. Republican Party) On: Borofsky, Cliff (Bexar County) McGeehan, Ann (TX SOS) Registering, but not testifying: For: Woodford, Suzy (Common Cause Texas)


class Constant : Terminal
A terminal node that represents a constant value.
Evaluating a constant node will simply result in the value the node encapsulates.
| <init> |
Constant(value: Double)
A terminal node that represents a constant value. |
| value |
val value: Double
The constant value of this node. |
| arity |
val arity: Int
The number of arguments that this node expects. |
| evaluate |
fun evaluate(args: List<Double>): Double
Gives the value stored at this node. |


Material Design
Home
Features
About Us
Log Out
Razor
refresh
add
BTCXRP, binance
4h interval - signal: BUY
add
refresh


| DOSE: |
75 mg |
smoked |
DMT |
(powder / crystals) |
I obtained roughly 2000mg of pure DMT powder which was made synthetically. At night, i went into my backyard, lit a candle, relaxed and prepared my DMT dose, this was done by previously measuring 75mg of the powder. The dose was then placed on aluminium foil and heated till it had completely vaporized and i had inhaled all i could.
I held my breathe for what seemed like 5 seconds, then exhaled, half way through exhaling i was blasted onto my back and everything i previously saw was exploded into a mixture of very unusual hyper shapes that are undescribable, and colours i can never imagine. This then proceeded to take me into a alien space ship type room, with 2 'beings' that resembled large praymantis. They knew i was there, i do not know how i knew this, i just 'felt' it, i was like a particle of air to them, yet i could sense they didnt want me there and were not happy of my presence, but never the less they tollerated me.
These beings were controlling the universe, i was nothing compared to the grand scheme of what they were part of and this is something i feel i will never understand, the rest of my trip is far too difficult for me to describe, but i felt assured we as humans were being looked after and watched, and this life as we know it is merely the tip of the ice berg of what is yet to come, it is a place i feel everyone should visit, i feel it was something more than just a chemical reaction, but i do think i am not welcome back there again until they decide it is ok to do so... that dmt is some weird stuff, get it if you can..... ebola . ......
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.


{% extends 'layout.html' %} {% block body %}
This application is built using the Python Flask framework and deployed on Heroku.


by Jessica Carpani from the Telegraph
by Sabrena Jo from the Greatist.com
By Jacqueline Howard from CNN
by Jenny Sugar from PopSugar Fitness
by Kate Fodor from Health.com
by Lucy Fry from The Guardian


Welcome
Navigation
Link:
Link to introduction
Link:
Link to instructions
Link:
Link to list of elements
I have some accessibility issues. Help!
Take your time and work through my issues.
Your browser does not support the
audio
element.
Click me.


---
layout: post
esbma_id: 1420
date: 2002-01-16 12:00:00
keywords: cornsharp
title: Blog entry on 16 Jan 2002
---
Kudos to Microsoft for releasing Visual Studio.NET yesterday. The official release date is apparently still in February, but "the stuff" is available for download at their site.
I've been using VS.NET for several months, and I'll reluctantly say that I am impressed. I'm not an IDE person. Emacs and bash have always been sufficient, even on Windows. VS.NET is probably the first release of Visual Studio that I've really liked since version 4.0.
Funny tidbit: Somebody in our QA team found a reproducible bug in Notepad last week! I'm still trying to figure out why he was looking for bugs there, but what a great thing to have on his résumé.
Could Google be any more cool? Bear with me:
I was helping my daughter Kellie (7 yrs old) with a geography game from school. She had to find out what state the following three islands are in: kodiak, nunivak, and baranof.
Eric: So where do we start?
Kellie: Google!
(Kellie brings up google.com and types the three island names above. She mistypes two of them.)
Google: Did you mean: kodiak nunivak baranof
Kellie: Silly Google!


Dittostack is a mac native clipboard history manager with a minimal design, styled to resemble Spotlight search. It is designed to give you fast access to text and files you have previously copied in order to re-use them.
It focuses on speed and efficiency to create the optimium workflow for copy and paste operations. Launch Dittostack from any anywhere using the keyboard shortcut cmd + shift + v. Browse or search your copy history and choose an item to paste.
Every new item you copy will be recorded by Dittostack and made available to you for re-use.
Use Dittostack to quickly search your clipboard history and access items you have previously copied. The search has been optimised to be as fast as possible. The search results are displayed in the list on the left and the selected item is displayed as a preview on the right. Once an item has been selected, simply press the enter key to paste it. This will copy the item to your pasteboard, close Dittostack, and then paste the item in the application that you are working in.
Files and Folders that you have copied will also be displayed in Dittostack. A preview of the selected File or Folder will be displayed in the preview panel on the right.
Dittostack will always appear on the screen you are working on. When using multiple screens, Dittostack will be launched on the screen that the mouse cursor is currently visible on.
Items copied from applications that contain sensitive data, such as password managers, can be ignored. These applications can be configured in the preferences. Selected items can be deleted from Dittostack by pressing the Command + Delete keys, or by using the Clear All option in menu bar.


nips nips2001 nips2001-98 nips2001-98-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Shiro Ikeda, Toshiyuki Tanaka, Shun-ichi Amari
Abstract: The mystery of belief propagation (BP) decoder, especially of the turbo decoding, is studied from information geometrical viewpoint. The loopy belief network (BN) of turbo codes makes it difﬁcult to obtain the true “belief” by BP, and the characteristics of the algorithm and its equilibrium are not clearly understood. Our study gives an intuitive understanding of the mechanism, and a new framework for the analysis. Based on the framework, we reveal basic properties of the turbo decoding.
[1] S. Amari and H. Nagaoka. (2000) Methods of Information Geometry, volume 191 of Translations of Mathematical Monographs. American Mathematical Society.
[2] C. Berrou and A. Glavieux. (1996) Near optimum error correcting coding and decoding: Turbo-codes. IEEE Transactions on Communications, 44(10):1261–1271.
[3] S. Ikeda, T. Tanaka, and S. Amari. (2001) Information geometry of turbo codes and low-density parity-check codes. submitted to IEEE transaction on Information Theory.
[4] Y. Kabashima and D. Saad. (2001) The TAP approach to intensive and extensive connectivity systems. In M. Opper and D. Saad, editors, Advanced Mean Field Methods – Theory and Practice, chapter 6, pages 65–84. The MIT Press.
[5] R. J. McEliece, D. J. C. MacKay, and J.-F. Cheng. (1998) Turbo decoding as an instance of Pearl’s “belief propagation” algorithm. IEEE Journal on Selected Areas in Communications, 16(2):140–152.
[6] T. J. Richardson. (2000) The geometry of turbo-decoding dynamics. IEEE Transactions on Information Theory, 46(1):9–23.
[7] T. Tanaka. (2001) Information geometry of mean-ﬁeld approximation. In M. Opper and D. Saad, editors, Advanced Mean Field Methods – Theory and Practice, chapter 17, pages 259–273. The MIT Press.
[8] T. Tanaka, S. Ikeda, and S. Amari. (2002) Information-geometrical signiﬁcance of sparsity in Gallager codes. in T. G. Dietterich et al. (eds.), Advances in Neural Information Processing Systems, vol. 14 (this volumn), The MIT Press.
[9] J. S. Yedidia, W. T. Freeman, and Y. Weiss. (2001) Bethe free energy, Kikuchi approximations, and belief propagation algorithms. Technical Report TR2001–16, Mitsubishi Electric Research Laboratories.


#include <stSlimTree.h>
Public Types | |
| typedef stSlimLogicNode< ObjectType, EvaluatorType > | tLogicNode |
Public Member Functions | |
| stSlimMSTSplitter (tLogicNode *node) | |
| ~stSlimMSTSplitter () | |
| const tLogicNode * | GetLogicNode () |
| int | Distribute (stSlimIndexNode *node0, ObjectType *&rep0, stSlimIndexNode *node1, ObjectType *&rep1, EvaluatorType *metricEvaluator) |
| int | Distribute (stSlimLeafNode *node0, ObjectType *&rep0, stSlimLeafNode *node1, ObjectType *&rep1, EvaluatorType *metricEvaluator) |
Protected Types | |
| typedef stGenericMatrix< stDistance > | tDistanceMatrix |
| enum | tClusterState { ALIVE, DEAD, DEATH_SENTENCE } |
Protected Member Functions | |
| int | FindCenter (int clus) |
| int | BuildDistanceMatrix (EvaluatorType *metricEvaluator) |
| void | PerformMST () |
| void | JoinClusters (int cluster1, int cluster2) |
Protected Attributes | |
| tLogicNode * | Node |
| tDistanceMatrix | DMat |
| tCluster * | Cluster |
| int * | ObjectCluster |
| int | N |
| int | Cluster0 |
| int | Cluster1 |
Tests!
Definition at line 504 of file stSlimTree.h.
|
|
Distance matrix type. Definition at line 548 of file stSlimTree.h. |
|
|
This type defines the logic node for this class. Definition at line 509 of file stSlimTree.h. Referenced by stSlimMSTSplitter< ObjectType, EvaluatorType >::GetLogicNode(). |
|
|
Cluster states. Definition at line 553 of file stSlimTree.h. |
|
|
Builds a new instance of this class. It will claim the ownership of the logic node provided as input. |
|
|
Disposes all associated resources. |
|
|
Builds the distance matrix using the given metric evaluator.
|
|
|
Distributes objects between 2 leaf nodes. |
|
|
Distributes objects between 2 index nodes. |
|
|
Returns the center of the object in the cluster clus. The.
|
|
|
Provides access to the logic node. Definition at line 525 of file stSlimTree.h. References stSlimMSTSplitter< ObjectType, EvaluatorType >::Node, and stSlimMSTSplitter< ObjectType, EvaluatorType >::tLogicNode. |
|
|
Joins 2 clusters. This method will insert custer2 into cluster1. The state of cluster2 will change to DEATH_SENTENCE.
|
|
|
Performs the MST algorithm. This method will split the objects in 2 clusters. The result of the processing will be found at the array Cluster.
|
|
|
All clusters. Definition at line 602 of file stSlimTree.h. |
|
|
Name of the cluster 0. Definition at line 617 of file stSlimTree.h. |
|
|
Name of the cluster 1. Definition at line 622 of file stSlimTree.h. |
|
|
The distance matrix. Definition at line 597 of file stSlimTree.h. |
|
|
Total number of objects. Definition at line 612 of file stSlimTree.h. |
|
|
The logic node to be used as source. Definition at line 592 of file stSlimTree.h. Referenced by stSlimMSTSplitter< ObjectType, EvaluatorType >::GetLogicNode(). |
|
|
The names of the cluster of each object Definition at line 607 of file stSlimTree.h. |


Board - Very early prototyping
Grid - Eary map prototyping
Merged geometries with vertex colors
Train - choo choo
Birds - tweet tweet
Dice
GLTF Test - merging buffer geometries with vertex colors and using buffer geometries from gltf models
Outline


“Yaññatthaṁ vā dhanatthaṁ vā,
ye hanāma mayaṁ pure;
Avasesaṁ bhayaṁ hoti,
vedhanti vilapanti ca.
“Those who we killed in the past,
whether for sacrifice or for wealth,
without exception were afraid;
they trembled and they squealed.
Tassa te natthi bhītattaṁ,
bhiyyo vaṇṇo pasīdati;
Kasmā na paridevesi,
evarūpe mahabbhaye”.
But you’re not scared;
you look even calmer than before.

“There isn’t any mental suffering
for one without hope, village chief.
All fears are left behind
by one whose fetters have ended.
Khīṇāya bhavanettiyā,
diṭṭhe dhamme yathātathe;
Na bhayaṁ maraṇe hoti,
bhāranikkhepane yathā.
When attachment to rebirth is ended,
and the truth is seen as it is,
there is no fear of death;
it’s like laying down a burden.
Suciṇṇaṁ brahmacariyaṁ me,
maggo cāpi subhāvito;
Maraṇe me bhayaṁ natthi,
rogānamiva saṅkhaye.
I’ve lived the spiritual life well,
and developed the path well, too.
I do not fear death;
it’s like the passing of a disease.
Suciṇṇaṁ brahmacariyaṁ me,
maggo cāpi subhāvito;
Nirassādā bhavā diṭṭhā,
visaṁ pitvāva chaḍḍitaṁ.
I’ve lived the spiritual life well,
and developed the path well, too.
I’ve seen that there’s nothing gratifying in existences,
like someone who has tasted poison, then thrown it out.
Pāragū anupādāno,
katakicco anāsavo;
Tuṭṭho āyukkhayā hoti,
mutto āghātanā yathā.
One who has gone beyond, without grasping,
they’ve completed the task and are free of defilements.
They are content at the end of life,
like someone released from execution.
Uttamaṁ dhammataṁ patto,
sabbaloke anatthiko;
Ādittāva gharā mutto,
maraṇasmiṁ na socati.
Having realized the supreme Dhamma,
without needing anything in the whole world,
one doesn’t grieve at death;
for it’s like escaping from a burning house.
Yadatthi saṅgataṁ kiñci,
bhavo vā yattha labbhati;
Sabbaṁ anissaraṁ etaṁ,
iti vuttaṁ mahesinā.
Whatever has come to pass,
wherever life is obtained,
there is no Lord of all that:
so said the great hermit.
Yo taṁ tathā pajānāti,
yathā buddhena desitaṁ;
Na gaṇhāti bhavaṁ kiñci,
sutattaṁva ayoguḷaṁ.
Whoever understands this
as it was taught by the Buddha
doesn’t grab on to any new life,
like you wouldn’t grab a hot iron ball.
Na me hoti ‘ahosin’ti,
‘bhavissan’ti na hoti me;
Saṅkhārā vigamissanti,
tattha kā paridevanā.
It doesn’t occur to me, ‘I existed in the past’;
nor, ‘I will exist in the future’.
All conditions will disappear—
why weep over that?
Suddhaṁ dhammasamuppādaṁ,
Suddhaṁ saṅkhārasantatiṁ;
Passantassa yathābhūtaṁ,
Na bhayaṁ hoti gāmaṇi.
Seeing in accordance with reality
the bare arising of phenomena,
and the bare process of conditions,
there is no fear, village chief.
Tiṇakaṭṭhasamaṁ lokaṁ,
yadā paññāya passati;
Mamattaṁ so asaṁvindaṁ,
‘natthi me’ti na socati.
The world is like grass and sticks:
when this is seen with wisdom,
not finding anything to be mine,
thinking ‘it isn’t mine’, one doesn’t grieve.
Ukkaṇṭhāmi sarīrena,
bhavenamhi anatthiko;
Soyaṁ bhijjissati kāyo,
añño ca na bhavissati.

This body will be broken up,
and there won’t be another.
Yaṁ vo kiccaṁ sarīrena,
taṁ karotha yadicchatha;
Na me tappaccayā tattha,
doso pemañca hehiti”.
Do what you want
with my corpse.
I won’t be angry or attached
on account of that.”
Tassa taṁ vacanaṁ sutvā,
abbhutaṁ lomahaṁsanaṁ;
Satthāni nikkhipitvāna,
māṇavā etadabravuṁ.
When they heard these words,
so astonishing and hair-raising,
the young men laid down their swords
and spoke these words:
“Kiṁ bhadante karitvāna,
ko vā ācariyo tava;
Kassa sāsanamāgamma,
labbhate taṁ asokatā”.
“What have you practiced, Venerable?
And who is your teacher?
Whose instructions do we follow
to gain the sorrowless state?”
“Sabbaññū sabbadassāvī,
jino ācariyo mama;
Mahākāruṇiko satthā,
sabbalokatikicchako.
“The knower of all, the seer of all:
the victor is my teacher.
He is a Teacher of great compassion,
healer of the whole world.
Tenāyaṁ desito dhammo,
khayagāmī anuttaro;
Tassa sāsanamāgamma,
labbhate taṁ asokatā”.
He taught this Dhamma,
leading to ending, unsurpassed.
Following his instructions,
you can gain the sorrowless state.”
Sutvāna corā isino subhāsitaṁ,
Nikkhippa satthāni ca āvudhāni ca;
Tamhā ca kammā viramiṁsu eke,
Eke ca pabbajjamarocayiṁsu.
When the bandits heard the good words of the hermit,
they laid down their swords and weapons.
Some refrained from their former deeds,
while others chose the going-forth.
Te pabbajitvā sugatassa sāsane,
Bhāvetva bojjhaṅgabalāni paṇḍitā;
Udaggacittā sumanā katindriyā,
Phusiṁsu nibbānapadaṁ asaṅkhatanti.
… Adhimutto thero ….
When they had gone forth in the teaching of the Holy One,
those astute ones developed the awakening factors and the powers.
Joyful, happy, their faculties complete,
they realized the state of quenching, the unconditioned.


“Compassionate commitment to older adults and relief for their caregivers."
Find Out MoreReliefRn was founded out of my admiration for older adults. I cared for my now deceased parents from afar. Families are under a great deal of stress as they have been forced to take on much greater caregiving roles for their loved ones while tending to the needs of their own families. Older adults are often the victims of our disorganized, uncoordinated, and impersonal healthcare system. I recognize the need for a more holistic and efficient approach to care management; one that keeps things on an uninterrupted continuum. A skilled nurse can can close the communication and coordination gaps that put older adults at risk for injury, bad health outcomes, unnecessary hospitalizations and overuse of services. Unskilled caregivers play a critical role in the health care delivery process, but they cannot provide the same level of scrutiny and oversight that a skilled nurse can. Especially to those with chronic medical conditions.
Get Started!Uncover the issues and discuss what you are looking for and how my services can help.
Physical and psychosocial assessment to determine specific needs. From there, we will formulate an individualized care plan designed to maximize safety and independence. Professional and practical recommendations will be offered and we will put together an information file. Educating seniors and their families about all aspects of their care plan enables them to make informed decisions about how to achieve the best possible outcomes on both sides. Teaching families about specific medical conditions can reduce accidents and hospitalizations, and give you the confidence you need to promote quality care.
$650
We can schedule visits to work through issues as they arise, but the main focus of the visit is to discuss the effectiveness of the care plan and make modifications as needed. We will evaluate the effect of any changes to the client’s general health or medications and do a complete safety checkup. We will make sure that all prescribed therapies are being followed and observe any change in mental status. We will address the client’s concerns and any additional needs. This may be a good opportunity for a wellness checkup.
$75/hour
This is where I can assist older adults and their families with the implementation of the care plan. This may include a number of services such as trouble shooting, coordination of services, and ongoing teaching. You might need help with arranging doctor visits or transporting them there where I assist with transitions to alternate facilities or back home. I will speak out for you and make sure your loved one is receiving the assistance they need and that their voices are being heard. This is especially valuable if you are caring for a frail loved one from afar and/or they are in an extended care facility.
$100/hour
Planning for your loved one’s present and future needs cannot be underestimated. There are many sensitive issues surrounding the future needs of the elderly client. I can arrange family meetings and facilitate discussions that tease out answers to thorny problems. The goal is to understand what the future looks like for everyone involved so that families can move forward with the planning process and prioritize care needs. I can be the objective “bad cop” and give unbiased objective advice and suggestions. Here we can outline short and long term goals, and discover how each family member’s individual strengths can most effectively contribute to the overall care situation. Taking steps now will lessen anxiety and give everyone a better sense of control.
$125/hour
Scheduled visits to reassess the overall effectiveness of the care plan. Families may want a consultation for any number of issues. These mini assessments will focus on your loved one’s general well being and safety. We will assess for physical and mental status changes and intervene as needed. We will ensure that all prescribed therapies are being implemented appropriately and they are reaching their health care goal This also includes: targeted teaching for specific medical health challenges, crisis intervention, skilled nursing care procedures, ongoing problem solving, telephone assistance, and transition assistance
$75/hour
Give me a call or send me an email and I will get back to you as soon as possible!
440-666-0070


Do you want to reach everybody? Then, in this aging world, don’t neglect geezers! If a website, document, or application requires superb eyesight, hearing, reaction speed, dexterity, memory, and digital savoir-faire, it’s not geezer-friendly. It may also exclude users with disabilities and violate government accessibility rules.
We can help, whether you need something new or improved. We comply with the latest accessibility standards. We detect and correct content and formats that could confuse, mislead, or alienate geezers (and non-geezers!). And we document our work so your geezers can make further changes without us.
Your turn!
Tell us about a spectacularly geezer-unfriendly interface. Send us a link to it or a picture of it, and describe the problem. It may wind up in this spot!
geezer.pro™ is a team of friendly geezers making things geezer-friendly.
(When needed, we get help from proto-geezers.)
Jonathan Pool, Ph.D., Web Accessibility Researcher, has experience in social, linguistic, and computer sciences and engineering; the design of databases and user interfaces; internationalization; web and physical accessibility; and small-business and nonprofit entrepreurship. He has recently undergone a skill upgrade at Learners Guild.
Susan Colowick, M.Libr., Content Quality Specialist, has professional experience in reference librarianship, website authentication, technical editing, journalism, proofreading, government records curation, graphic arts, and legal research, as well as training in web development.
Free offer!
Curious about how geezer-friendly a particular web page is? Shoot us an email with the page’s address (URL). We’ll look it over, run some tests, and send you our findings.
Age Friendly Seattle: Making its Documents Age-Friendly
Geezerproofing the Web
geezer.pro™
email<EMAIL_ADDRESS>Telephone:<PHONE_NUMBER>
Facsimile:<PHONE_NUMBER>


Introduction
This application enables you to visually analyze the 3D motion of the humerus and scapula during various
single-plane shoulder motions. It decomposes the orientation of the humerus and scapula via commonly utilized
methods in shoulder biomechanics research. This allows you to visually compare differences between these methods.
Frame Selection
The slider bar at the top of the page allows you to select the frame in the data capture which you would
like to analyze. Notice that as you change the frame number, the orientation of the humerus and scapula
in each view is updated. This same functionality can be achieved using the plots on the lower-right
quadrant by hovering over a plot-line. Once you have chosen a frame to analyze, click the downward facing arrow
next to the slider bar. This same functionality can be achieved by clicking a point on a plot.
The Views
The lower-right view plots the components of the decomposed orientation of the humerus/scapula as specified
in the adjustable label in the upper-left corner of this quadrant. Each of the remaining 3 views
decompose the humerus or scapula orientation according to the adjustable label shown in the upper-left or
upper-right corner of the quadrant. In all views, the elbow is represented by a thin black or blue rectangle
attached to the humerus. Axial orientation is illustrated by the angle between the black (starting) and blue
(ending) rectangle.
Interactions
Rotate by dragging the left mouse button, zoom using the scroll-wheel, and pan by
dragging the right mouse button. To maximize one of the views, double-click on it. Another double-click
brings you back to the 4-pane view. The humerus views are linked to each other so as you rotate, pan, or zoom
in one view, the same action happens in the other humerus views.
Animations
Once you have selected a frame to decompose (see Frame Selection), the application allows you to
animate the sub-rotations associated with each decomposition. The state buttons at bottom of the application
allow you to choose which sub-rotation you would like to animate. Once you select a sub-rotation, the
play/pause button and slide bar at the bottom of each quadrant provide control of the animation for the
selected sub-rotation.
Options
The Open Controls button in the lower-right corner of the page provides various configuration options
for the application. Notably, the Humerus Base option allows you to change whether the humerus is
decomposed and plotted by measuring its orientation against the Torso or Scapula. The
Visualize Angles option allows you to display a simple visualization of the humerus angles as measured
by a particular decomposition sequence. The Spherical Area option enables the visualization of the
actual path traversed by the distal humerus (blue), and the path assumed by the chosen decomposition sequence
(brown). The spherical area between these two trajectories describes the difference between true and apparent
axial rotation for the xz'y'' and Swing Twist decompositions.


Given a list of integers and a number K, return which contiguous elements of the list sum to K.
For example, if the list is [1, 2, 3, 4, 5] and K is 9, then it should return [2, 3, 4].
The main idea here to keep track of the sum so far and at any point, if the difference between the current sum and the target sum has been encountered before, we can get the target sum slice.
Algorithm Overview:
1. Keep a map to store the sum until the index.
2. Iterate through the array and calculate and store the sum so far in the map.
3. At any point, if we find the sum so far - target sum to be in the map, that means the subarray will be i - map.get(sum_so_far - target)
The above approach can be implemented as follows:


Meth-smuggling family busted at Bangkok airport: police
by Coconuts BangkokThree people were arrested at Don Mueang Airport yesterday after police found a kilogram of crystal methamphetamine with a street value of about THB800,000 (US$27,000), stuffed inside cans of fish.
Police officials announced the arrest of Pattaraporn Sawachote, 33, her brother Manatchai Chotithana, 43, and his wife, Maneeploypleun Chotithana, 46, at a 5pm presser on Monday.
Maj. Gen. Phiraphong Wongsamarn, deputy commander of a police special operations division, told reporters that they were tipped off by a vigilante Facebook page. An investigation led them to track Pattaraporn from a motel and then to the airport.
Upon the trio’s arrival at the terminal, police asked to examine their bags. Inside they found 100 grams of meth stuffed into 10 empty cans of Thai sardines. The cans were also wrapped in paper and another plastic bag.
Upon their arrest, the trio reportedly confessed to criminal intent, saying they were preparing to export the meth to Japan. They said to have been hired by a Thai woman living abroad and the trio would split their tasks. Manatchai would pick up the drugs from an associate and store them at a motel where Pattaraporn would pick them up.
After the transaction was done, Manatchai and Maneeploypleun said they would be wired THB20,000 (US$660) each while Pattaraporn got THB50,000 (US$1,656.) They had apparently completed two such transactions before being taken down.
The three face charges drug-related charges including possession and intent to traffic class one narcotics.
Related
Japan wary of Thai travelers after 7 women arrive with meth in undies (Photos)
Southeast Asia meth gangs cooking up $60 billion a year: UN
Drones, big money and cheap drugs: Laos spewing meth into Thailand
Indonesian authorities arrest 2 Thai nationals for smuggling meth inside their stomachs
Thai police seize 14 million meth pills on their way to Malaysia


Google Reader and Mac/iOS RSS readers that sync:
The recent announcement of changes coming for Google Reader worries me some. Though I don’t use Google Reader directly, I — like many iPhone, iPad, and Mac users — use RSS readers that sync via Google Reader.
This announcement isn’t just a reminder of the fragility of the system: it removes some features that people use. Google Reader’s social and sharing features are going away in favor of integration with Google+.
This makes sense from Google’s point of view — a single, Google-wide social network should be better than a separate network for each Google app.
Nevertheless, there are users who will miss the current, about-to-disappear features. (See What the Upcoming Google Reader Changes Mean for FeedDemon for an example of how one RSS reader will have to change.)
When I say that the system is fragile, I don’t mean that Google Reader itself is fragile. I mean that using it as a syncing system for other apps is fragile. There are a couple things that RSS reader developers know, that the average RSS reader user probably doesn’t know, which will make this more apparent:
The Google Reader API is undocumented, unsupported, and unofficial. This is unlike Google Maps and others which do have documented and official APIs.
Because the API is not official, there is no commitment to keeping it working.
Though RSS reader developers have received much-appreciated unofficial support from Google, that’s not the same as building a feature on solid ground. Smart developers are rightly uncomfortable relying on undocumented, unofficial, unsupported APIs.
But, because syncing is so important for so many RSS reader users, developers have had to gamble. With syncing part of the definition of a minimum viable RSS reader, and with Google Reader the only option for syncing, the choice to use Google Reader is more necessity than choice.
Questions about the future
The gamble has paid off so far, with the exception of the features about to be replaced. It’s been an especially good thing for RSS reader users, who can mix-and-match clients on different platforms, who can move with relative ease between one client and another. (The situation is similar to Twitter clients: users are not stuck with one client from one particular developer.)
While I remain optimistic about the future of Google Reader and apps that sync via Google Reader, there are a few reasons for concern:
Though Google Reader is a mature app, its lack of an official, documented, supported API sends a message, intended or not, about its importance to Google. And Google has cut apps before, even high-profile apps like Google Wave.
FeedDemon author Nick Bradbury asked on the unofficial API support list if Google Reader is being retired. At this writing, a couple days after the recent announcement, the question remains unanswered.
Despite all the #googlereader and @googlereader traffic on Twitter since the announcement, the @googlereader Twitter account has been silent. (At this writing.)
The wording of the recent Google Reader announcement emphasized how users could export their data. While that’s a good thing — being able to move one’s data is important — the emphasis made it seem like a request or a warning. That characterization is mine, yes, but it’s shared by other developers (not just RSS reader developers) that have read that announcement. This may not have been the author’s intention: it’s possible the author was being careful and doing the right thing by mentioning data exporting. But it didn’t read that way, at least to some developers.
We don’t know what the value of Google Reader is to Google. It doesn’t appear to have ads a la search or Gmail, though ads do appear in feeds via Google’s AdSense for feeds, and that presumably makes money. Does Google Reader feed the search engine ranking system? Does it exist to help ensure the goodwill of influential writers who use Google Reader? I can speculate, but I don’t know, which is my point.
At any rate, I remain optimistic, because I don’t have any solid reason to expect things to change.
But Google Reader has just changed, and some syncing RSS readers will lose some features, and I take that as a reminder that it could change in a way that breaks syncing, and Google would not have broken any official APIs.
I’m not an RSS reader developer any more. But if I were, I’d start looking for an alternative syncing system right now.
(Via inessential.com)


{% extends 'base.html' %} {% block content %}
The Open-Source Happiness Packets project was created by Erik Romijn and Mikey Ariel in March 2016. The idea came about while we were building our Healthy Minds in a Healthy Community presentation for Djangocon Europe 2016. One of the issues we wanted to address in the presentation was that many people are unaware of how loved, appreciated, or admired they are by their peers, since our culture seems to discourage positive feedback and amplify negative feedback. With this project, we wanted to provide a platform for people to send positive feedback, thanks, or just a kind word to their peers, with hope to make it easier and more acceptable for people to spread happiness, gratitude and appreciation in open-source communities.
Many of us come from a culture where it's sometimes more acceptable to complain about the negative than to acknowledge the positive things. Therefore, it might feel a little awkward to communicate positive feedback directly to others. However, in our personal experience, once you take that first step, any awkwardness is quickly replaced by feeling good about helping someone else feel good.
We don't screen the content of messages. However, all messages must meet the Django Project Code of Conduct. Notably, harassment, insults and other exclusionary behavior are never acceptable.
Violations of this can result in blocking you from using the service. Your message might also be shared with the Django Code of Conduct committee, who reserve the right to take further action of their own. If you're a member of another open-source community, your message might be shared with any code of conduct committee or similar group from that community.
You are under no obligation to respond to the sender of the Happiness Packet. But if you are inspired by what you received, you are welcome to respond or send your own Happiness Packet. We always encourage sending more messages, but only if they are sincere.
Note: if the sender selected to remain anonymous, you cannot reply to their message.
By default, we only send your message with the recipient. They will get an e-mail with your message and can view it online. We only share your name and email address with the recipient if you choose this option. We may analyse messages and their metadata for statistical analysis.
In case of suspected abuse or Code of Conduct violations, the service administrators might view and read your message to determine further processing.
If both the sender and the recipient of the message agree to publish the message on the website, the message will be displayed in the Happiness Archive. We encourage you to share your messages with the community, but the choice is yours and you are not obligated to choose this option if you do not feel comfortable with it. You can also choose to publish the message but keep the sender and recipient names private.
Note: we cannot modify the content of the message after it is sent, so if the message includes personally-identifying information or references to third parties, they will be published even if you choose to hide the sender and recipient names.
Please report this to<EMAIL_ADDRESS>preferably by forwarding the original email that contains the message.
Every email we sent includes a link to stop receiving all future e-mail messages. If you follow the link and confirm, your email address will not be able to be used anywhere on the site. Note: if you select to block your email address, you will not be able to send Happiness Packets yourself.


Cohesion Software LLC is a privately owned company based in Gardner, KS. We specialize in the architecture and engineering of modern software solutions.
We have experience throughout the entire life cycle of software development and are committed to excellence in our products and the products we collaborate on with others.
Be Heard by the government officials representing your Congressional district. We created Be Heard because we believe in the freedom of speech for all people. Our goal is to empower the people of the United States to make a difference by facilitating their ability to Be Heard.
For business inquiries, feedback, or support email us


Experience
01/2015 - now
Marketing Manager
ABC Supplies Ltd, Nottingham
- Managing all marketing for the company and activities within the marketing department.
- Developing the marketing strategy in line with company objectives.
- Creation and publication of all marketing material in line with marketing plans.
08/2013 - 12/2014
Marketing and social media manager
WOW Supplies Ltd, Loughborough
- Attending pitch events with the Founder
- Identifying potential customers and targeting them
- Helping to write and implement digital marketing plans
- Developing template marketing documents
09/2011 - 07/2013
Marketing Assistant
ZYZ Supplies Ltd, Nottingham
- Planning and implementing promotional campaigns.
- Managing and improving lead generation campaigns, measuring results.
- Preparing online and print marketing campaigns.
2018 - Josef Beneš


|
|
| PlayersData (uint maxConnection=1000) noexcept |
| |
|
PlayerInfo & | accessPlayerPosition (uint indexPlayer) |
| |
|
template<typename Action > |
| void | executeOnPlayers (Action &&actionToExecute) |
| |
|
void | setPlayerMoveAction (uint index, double direction) |
| |
|
void | stopPlayerMove (uint index) |
| |
|
void | setPlayerArena (uint index, const std::string &arenaId) |
| |
| uint | getIndexAndUpdatePlayerConnection (const std::string &token, std::string idt) |
| |
| std::vector< std::string_view > | getPlayerIdtsArroundPlayer (uint indexPlayer, std::optional< std::reference_wrapper< PlayerInfo >> position, double distance=DEFAULT_DISTANCE) const noexcept |
| | Get the Players Identities Arround the given player except himself. More...
|
| |
| std::vector< std::string_view > | getPlayerIdtsArroundPos (const PlayerInfo &position, double distance=DEFAULT_DISTANCE, uint ignoreIndex=LIMIT_NOTIFICATIONS_MOVE) const noexcept |
| | Get the Players Identities Arround the given position. More...
|
| |
◆ getIndexAndUpdatePlayerConnection()
| uint fys::ws::PlayersData::getIndexAndUpdatePlayerConnection |
( |
const std::string & |
token, |
|
|
std::string |
idt |
|
) |
| |
Retrieve the index corresponding to the given token
- Parameters
-
- Returns
- index corresponding to the given token, std::numeric_limits<uint>::max() is returned if no corresponding token
◆ getPlayerIdtsArroundPlayer()
| std::vector< std::string_view > fys::ws::PlayersData::getPlayerIdtsArroundPlayer |
( |
uint |
indexPlayer, |
|
|
std::optional< std::reference_wrapper< PlayerInfo >> |
position, |
|
|
double |
distance = DEFAULT_DISTANCE |
|
) |
| const |
|
inlinenoexcept |
Get the Players Identities Arround the given player except himself.
- Parameters
-
| indexPlayer | player |
| position | |
| distance | |
- Returns
- std::vector<std::string_view>
◆ getPlayerIdtsArroundPos()
| std::vector< std::string_view > fys::ws::PlayersData::getPlayerIdtsArroundPos |
( |
const PlayerInfo & |
position, |
|
|
double |
distance = DEFAULT_DISTANCE , |
|
|
uint |
ignoreIndex = LIMIT_NOTIFICATIONS_MOVE |
|
) |
| const |
|
noexcept |
Get the Players Identities Arround the given position.
- Parameters
-
| position | to check arround |
| distance | radius arround the given point to search |
- Returns
- std::vector<std::string_view> vector of view on the identities of the players arround the given point
- Note
- identities are zmq code to reply to a specific client via a router socket
The documentation for this class was generated from the following files:
- /home/FyS/Project/FyS/services/worldserver/include/engine/PlayersData.hh
- /home/FyS/Project/FyS/services/worldserver/src/engine/PlayersData.cpp