XPROP(1) XPROP(1) NAME xprop - property displayer for X SYNOPSIS xprop [-help] [-grammar] [-id id] [-root] [-name name] [-frame] [-font font] [-display display] [-len n] [-notype] [-fs file] [-remove property- name] [-set property-name value] [-spy] [-f atom format [dformat]]* [for‐ mat [dformat] atom]* SUMMARY The xprop utility is for displaying window and font properties in an X server. One window or font is selected using the command line arguments or possibly in the case of a window, by clicking on the desired window. A list of properties is then given, possibly with formatting information. OPTIONS -help Print out a summary of command line options. -grammar Print out a detailed grammar for all command line options. -id id This argument allows the user to select window id on the command line rather than using the pointer to select the target window. This is very useful in debugging X applications where the target window is not mapped to the screen or where the use of the pointer might be impossible or interfere with the application. -name name This argument allows the user to specify that the window named name is the target window on the command line rather than using the pointer to select the target window. -font font This argument allows the user to specify that the properties of font font should be displayed. -root This argument specifies that X's root window is the target win‐ dow. This is useful in situations where the root window is com‐ pletely obscured. -display display This argument allows you to specify the server to connect to; see X(7). -len n Specifies that at most n bytes of any property should be read or displayed. -notype Specifies that the type of each property should not be displayed. -fs file Specifies that file file should be used as a source of more for‐ mats for properties. -frame Specifies that when selecting a window by hand (i.e. if none of -name, -root, or -id are given), look at the window manager frame (if any) instead of looking for the client window. -remove property-name Specifies the name of a property to be removed from the indicated window. -set property-name value Specifies the name of a property and a property value, to be set on the indicated window. -spy Examine window properties forever, looking for property change events. -f name format [dformat] Specifies that the format for name should be format and that the dformat for name should be dformat. If dformat is missing, " = $0+\n" is assumed. DESCRIPTION For each of these properties, its value on the selected window or font is printed using the supplied formatting information if any. If no format‐ ting information is supplied, internal defaults are used. If a property is not defined on the selected window or font, "not defined" is printed as the value for that property. If no property list is given, all the properties possessed by the selected window or font are printed. A window may be selected in one of four ways. First, if the desired win‐ dow is the root window, the -root argument may be used. If the desired window is not the root window, it may be selected in two ways on the com‐ mand line, either by id number such as might be obtained from xwininfo, or by name if the window possesses a name. The -id argument selects a window by id number in either decimal or hex (must start with 0x) while the -name argument selects a window by name. The last way to select a window does not involve the command line at all. If none of -font, -id, -name, and -root are specified, a crosshairs cur‐ sor is displayed and the user is allowed to choose any visible window by pressing any pointer button in the desired window. If it is desired to display properties of a font as opposed to a window, the -font argument must be used. Other than the above four arguments and the -help argument for obtaining help, and the -grammar argument for listing the full grammar for the com‐ mand line, all the other command line arguments are used in specifying both the format of the properties to be displayed and how to display them. The -len n argument specifies that at most n bytes of any given property will be read and displayed. This is useful for example when displaying the cut buffer on the root window which could run to several pages if displayed in full. Normally each property name is displayed by printing first the property name then its type (if it has one) in parentheses followed by its value. The -notype argument specifies that property types should not be dis‐ played. The -fs argument is used to specify a file containing a list of formats for properties while the -f argument is used to specify the for‐ mat for one property. The formatting information for a property actually consists of two parts, a format and a dformat. The format specifies the actual formatting of the property (i.e., is it made up of words, bytes, or longs?, etc.) while the dformat specifies how the property should be displayed. The following paragraphs describe how to construct formats and dformats. However, for the vast majority of users and uses, this should not be nec‐ essary as the built in defaults contain the formats and dformats neces‐ sary to display all the standard properties. It should only be necessary to specify formats and dformats if a new property is being dealt with or the user dislikes the standard display format. New users especially are encouraged to skip this part. A format consists of one of 0, 8, 16, or 32 followed by a sequence of one or more format characters. The 0, 8, 16, or 32 specifies how many bits per field there are in the property. Zero is a special case meaning use the field size information associated with the property itself. (This is only needed for special cases like type INTEGER which is actually three different types depending on the size of the fields of the property.) A value of 8 means that the property is a sequence of bytes while a value of 16 would mean that the property is a sequence of words. The differ‐ ence between these two lies in the fact that the sequence of words will be byte swapped while the sequence of bytes will not be when read by a machine of the opposite byte order of the machine that originally wrote the property. For more information on how properties are formatted and stored, consult the Xlib manual. Once the size of the fields has been specified, it is necessary to spec‐ ify the type of each field (i.e., is it an integer, a string, an atom, or what?) This is done using one format character per field. If there are more fields in the property than format characters supplied, the last character will be repeated as many times as necessary for the extra fields. The format characters and their meaning are as follows: a The field holds an atom number. A field of this type should be of size 32. b The field is an boolean. A 0 means false while anything else means true. c The field is an unsigned number, a cardinal. i The field is a signed integer. m The field is a set of bit flags, 1 meaning on. o The field is an array of icons, packed as a sequence of 32 bit numbers consisting of the width, height and ARGB pixel values, as defined for the _NET_WM_ICON property in the Extended Window Man‐ ager Hints specification. A field of this type must be of size 32. s This field and the next ones until either a 0 or the end of the property represent a sequence of bytes. This format character is only usable with a field size of 8 and is most often used to rep‐ resent a string. t This field and the next ones until either a 0 or the end of the property represent an internationalized text string. This format character is only usable with a field size of 8. The string is assumed to be in an ICCCM compliant encoding and is converted to the current locale encoding before being output. u This field and the next ones until either a 0 or the end of the property represent an UTF-8 encoded unicode string. This format character is only usable with a field size of 8. If the string is found to be an invalid character, the type of encoding violation is printed instead, followed by the string formatted using 's'. When in an environment not capable of displaying UTF-8 encoded string, behaviour is identical to 's'. x The field is a hex number (like 'c' but displayed in hex - most useful for displaying window ids and the like) An example format is 32ica which is the format for a property of three fields of 32 bits each, the first holding a signed integer, the second an unsigned integer, and the third an atom. The format of a dformat unlike that of a format is not so rigid. The only limitations on a dformat is that one may not start with a letter or a dash. This is so that it can be distinguished from a property name or an argument. A dformat is a text string containing special characters instructing that various fields be printed at various points in a manner similar to the formatting string used by printf. For example, the dfor‐ mat " is ( $0, $1 \)\n" would render the POINT 3, -4 which has a format of 32ii as " is ( 3, -4 )\n". Any character other than a $, ?, \, or a ( in a dformat prints as itself. To print out one of $, ?, \, or ( precede it by a \. For example, to print out a $, use \$. Several special backslash sequences are provided as shortcuts. \n will cause a newline to be displayed while \t will cause a tab to be displayed. \o where o is an octal number will display character number o. A $ followed by a number n causes field number n to be displayed. The format of the displayed field depends on the formatting character used to describe it in the corresponding format. I.e., if a cardinal is described by 'c' it will print in decimal while if it is described by a 'x' it is displayed in hex. If the field is not present in the property (this is possible with some properties), <field not available> is displayed instead. $n+ will dis‐ play field number n then a comma then field number n+1 then another comma then ... until the last field defined. If field n is not defined, noth‐ ing is displayed. This is useful for a property that is a list of val‐ ues. A ? is used to start a conditional expression, a kind of if-then state‐ ment. ?exp(text) will display text if and only if exp evaluates to non- zero. This is useful for two things. First, it allows fields to be dis‐ played if and only if a flag is set. And second, it allows a value such as a state number to be displayed as a name rather than as just a number. The syntax of exp is as follows: exp ::= term | term=exp | !exp term ::= n | $n | mn The ! operator is a logical ``not'', changing 0 to 1 and any non-zero value to 0. = is an equality operator. Note that internally all expres‐ sions are evaluated as 32 bit numbers so -1 is not equal to 65535. = returns 1 if the two values are equal and 0 if not. n represents the constant value n while $n represents the value of field number n. mn is 1 if flag number n in the first field having format character 'm' in the corresponding format is 1, 0 otherwise. Examples: ?m3(count: $3\n) displays field 3 with a label of count if and only if flag number 3 (count starts at 0!) is on. ?$2=0(True)?!$2=0(False) displays the inverted value of field 2 as a boolean. In order to display a property, xprop needs both a format and a dformat. Before xprop uses its default values of a format of 32x and a dformat of " = { $0+ }\n", it searches several places in an attempt to find more specific formats. First, a search is made using the name of the prop‐ erty. If this fails, a search is made using the type of the property. This allows type STRING to be defined with one set of formats while allowing property WM_NAME which is of type STRING to be defined with a different format. In this way, the display formats for a given type can be overridden for specific properties. The locations searched are in order: the format if any specified with the property name (as in 8x WM_NAME), the formats defined by -f options in last to first order, the contents of the file specified by the -fs option if any, the contents of the file specified by the environmental variable XPROPFORMATS if any, and finally xprop's built in file of formats. The format of the files referred to by the -fs argument and the XPROPFOR‐ MATS variable is one or more lines of the following form: name format [dformat] Where name is either the name of a property or the name of a type, format is the format to be used with name and dformat is the dformat to be used with name. If dformat is not present, " = $0+\n" is assumed. EXAMPLES To display the name of the root window: xprop -root WM_NAME To display the window manager hints for the clock: xprop -name xclock WM_HINTS To display the start of the cut buffer: xprop -root -len 100 CUT_BUFFER0 To display the point size of the fixed font: xprop -font fixed POINT_SIZE To display all the properties of window # 0x200007: xprop -id 0x200007 To set a simple string property: xprop -root -format MY_ATOM_NAME 8s -set MY_ATOM_NAME "my_value" ENVIRONMENT DISPLAY To get default display. XPROPFORMATS Specifies the name of a file from which additional formats are to be obtained. SEE ALSO X(7), xdpyinfo(1), xwininfo(1), xdriinfo(1), glxinfo(1), xvinfo(1) AUTHOR Mark Lillibridge, MIT Project Athena X Version 11 xprop 1.2.1 XPROP(1)


public interface MetastoreConfigConstants
| Modifier and Type | Field and Description |
|---|---|
static String |
BASE
Metastore configuration properties namespace.
|
static String |
DEFAULT_RESOURCE_FILE_NAME
Indicates file which provides default Metastore configuration, usually shipped in the project.
|
static String |
DISTRIBUTION_RESOURCE_FILE_NAME
Indicates file which provides distribution specific Metastore configuration.
|
static String |
IMPLEMENTATION_CLASS
Indicates canonical class name of the Metastore implementation class.
|
static String |
MODULE_RESOURCE_FILE_NAME
Indicates file which provides configuration of the Metastore implementations,
usually shipped with Metastore implementations.
|
static String |
OVERRIDE_RESOURCE_FILE_NAME
Indicates file which can override default Metastore configuration
or Metastore implementations configuration.
|
static String |
USE_PROVIDED_CONFIG
Indicates if provided Drill config should be used without looking for overridden / fallback
resource files in the classpath.
|
static final String DEFAULT_RESOURCE_FILE_NAME
static final String MODULE_RESOURCE_FILE_NAME
static final String DISTRIBUTION_RESOURCE_FILE_NAME
static final String OVERRIDE_RESOURCE_FILE_NAME
static final String BASE
static final String IMPLEMENTATION_CLASS
static final String USE_PROVIDED_CONFIG
Copyright © 2021 The Apache Software Foundation. All rights reserved.


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World's Largest Online Gaming Community
Join the world's largest online gaming community: make friends, form teams and battle tens of millions of opponents from countries across the globe, then exchange strats on reddit, YouTube, the forums and beyond


SceneJS
- Anaglyph 3D rendering with pick-fly-orbit camera
click on something to fly to that point
drag mouse to orbit it, mouse wheel to zoom in and out


| Generated on: | 29.07.2016 г. - 1:43:38 |
|---|---|
| Parser: | OpenCoverParser |
| Assemblies: | 2 |
| Classes: | 6 |
| Files: | 6 |
| Covered lines: | 129 |
| Uncovered lines: | 6 |
| Coverable lines: | 135 |
| Total lines: | 298 |
| Line coverage: | 95.5% |
| Branch coverage: | 91.6% |
| Name | Covered | Uncovered | Coverable | Total | Line coverage | Branch coverage | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| School | 68 | 1 | 69 | 161 | 98.5% | 100% | ||||||
| StudentsAndCourses.Course | 18 | 0 | 18 | 43 | 100% | 100% | ||||||
| StudentsAndCourses.School | 20 | 0 | 20 | 50 | 100% | 100% | ||||||
| StudentsAndCourses.Student | 30 | 1 | 31 | 68 | 96.7% | 100% | ||||||
| School.Tests | 61 | 5 | 66 | 137 | 92.4% | 75% | ||||||
| SchoolTests.TestCourse | 24 | 1 | 25 | 46 | 96% | 75% | ||||||
| SchoolTests.TestSchool | 18 | 1 | 19 | 40 | 94.7% | |||||||
| SchoolTests.TestStudent | 19 | 3 | 22 | 51 | 86.3% |


AWS::Logs::Destination
The AWS::Logs::Destination
resource creates an Amazon CloudWatch Logs (CloudWatch Logs) destination,
which enables you to specify a physical resource (such as an Kinesis stream) that
subscribes to
CloudWatch Logs log events from another AWS account. For more information, see Cross-Account Log Data Sharing with
Subscriptions in the Amazon CloudWatch User Guide.
Topics
Syntax
To declare this entity in your AWS CloudFormation template, use the following syntax:
JSON
{ "Type" : "AWS::Logs::Destination", "Properties" : { "DestinationName" :
String
, "DestinationPolicy" :String
, "RoleArn" :String
, "TargetArn" :String
} }
YAML
Type: AWS::Logs::Destination Properties: DestinationName:
String
DestinationPolicy:String
RoleArn:String
TargetArn:String
Properties
DestinationName
-
The name of the CloudWatch Logs destination that you will reference in the
DestinationPolicy
property.Required: Yes
Type: String
Update requires: Replacement
DestinationPolicy
-
An AWS Identity and Access Management (IAM) policy that specifies who can write to your destination.
Required: Yes
Type: String
Update requires: No interruption
RoleArn
-
The Amazon Resource Name (ARN) of an IAM role that permits CloudWatch Logs to send data to the specified AWS resource (
TargetArn
).Required: Yes
Type: String
Update requires: No interruption
TargetArn
-
The ARN of the AWS resource that receives log events. Currently, you can specify only an Kinesis stream.
Required: Yes
Type: String
Update requires: No interruption
Return Values
Ref
When the logical ID of this resource is provided to the Ref
intrinsic function, Ref
returns the resource name, such as
TestDestination
.
For more information about using the Ref
function, see Ref.
Fn::GetAtt
Fn::GetAtt
returns a value for a specified attribute of this type.
The following are the available attributes and sample return values.
Arn
-
The ARN of the CloudWatch Logs destination, such as
arn:aws:logs:us-east-2:123456789012:destination:MyDestination
.
For more information about using Fn::GetAtt
, see Fn::GetAtt.
Example
In the following example, the target stream (TestStream
) can receive log
events from the logger
IAM user that is in the<PHONE_NUMBER>23
AWS
account. The user can call only the PutSubscriptionFilter
action against the
TestDestination
destination.
JSON
"DestinationWithName" : { "Type" : "AWS::Logs::Destination", "Properties" : { "DestinationName": "TestDestination", "RoleArn": "arn:aws:iam::123456789012:role/LogKinesisRole", "TargetArn": "arn:aws:kinesis:us-east-1:123456789012:stream/TestStream", "DestinationPolicy": "{\"Version\" : \"2012-10-17\",\"Statement\" : [{\"Effect\" : \"Allow\", \"Principal\" : {\"AWS\" : \"arn:aws:iam::234567890123:user/logger\"}, \"Action\" : \"logs:PutSubscriptionFilter\", \"Resource\" : \"arn:aws:logs:us-east-1:123456789012:destination:TestDestination\"}]}" } }
YAML
DestinationWithName: Type: AWS::Logs::Destination Properties: DestinationName: "TestDestination" RoleArn: "arn:aws:iam::123456789012:role/LogKinesisRole" TargetArn: "arn:aws:kinesis:us-east-1:123456789012:stream/TestStream" DestinationPolicy: > {"Version" : "2012-10-17","Statement" : [{"Effect" : "Allow", "Principal" : {"AWS" : "arn:aws:iam::234567890123:user/logger"},"Action" : "logs:PutSubscriptionFilter", "Resource" : "arn:aws:logs:us-east-1:123456789012:destination:TestDestination"}]}


Find your stolen bike!
Enter color:
Enter amount:
Create
Enter location:
Enter amount:
Create
Title
Stolen Location
Year


| Card | Mana | Rarity | Class | Normal | Golden |
| Whispers of EVIL | 0 | Common | Priest | 2 | 1 |
| Arcane Breath | 1 | Rare | Mage | 2 | |
| Blazing Battlemage | 1 | Common | Neutral | 2 | 1 |
| Bloodsail Flybooter | 1 | Common | Rogue | 2 | |
| Depth Charge | 1 | Rare | Neutral | 2 | |
| Disciple of Galakrond | 1 | Common | Priest | 2 | |
| Dragon's Hoard | 1 | Rare | Rogue | 2 | |
| Dwarven Sharpshooter | 1 | Common | Hunter | 2 | |
| Hot Air Balloon | 1 | Common | Neutral | 2 | |
| Learn Draconic | 1 | Common | Mage | 2 | |
| Praise Galakrond! | 1 | Common | Rogue | 2 | |
| Rain of Fire | 1 | Common | Warlock | 2 | |
| Righteous Cause | 1 | Rare | Paladin | 1 | |
| Sand Breath | 1 | Common | Paladin | 1 | |
| Sky Raider | 1 | Common | Warrior | 2 | |
| Storm's Wrath | 1 | Rare | Shaman | 2 | |
| Strength in Numbers | 1 | Common | Druid | 2 | |
| Surging Tempest | 1 | Common | Shaman | 2 | |
| Toxic Reinforcements | 1 | Epic | Hunter | 1 | |
| Treenforcements | 1 | Rare | Druid | 1 | |
| Violet Spellwing | 1 | Common | Mage | 2 | |
| Breath of Dreams | 2 | Rare | Druid | 1 | |
| Corrosive Breath | 2 | Common | Hunter | 2 | |
| Dragon Breeder | 2 | Rare | Neutral | 1 | 1 |
| Evasive Chimaera | 2 | Common | Neutral | 2 | |
| Invocation of Frost | 2 | Common | Shaman | 2 | |
| Nether Breath | 2 | Rare | Warlock | 2 | |
| Parachute Brigand | 2 | Common | Neutral | 1 | |
| Phase Stalker | 2 | Rare | Hunter | 1 | |
| Ritual Chopper | 2 | Rare | Warrior | 1 | |
| Shrubadier | 2 | Common | Druid | 2 | |
| Tasty Flyfish | 2 | Common | Neutral | 2 | |
| Wyrmrest Purifier | 2 | Epic | Neutral | 1 | |
| Awaken! | 3 | Common | Warrior | 2 | |
| Blowtorch Saboteur | 3 | Epic | Neutral | 2 | |
| Breath of the Infinite | 3 | Rare | Priest | 1 | |
| Bronze Explorer | 3 | Common | Paladin | 2 | |
| Diving Gryphon | 3 | Rare | Hunter | 1 | |
| Dragonblight Cultist | 3 | Rare | Warlock | 1 | |
| EVIL Quartermaster | 3 | Common | Warrior | 2 | |
| Fire Hawk | 3 | Common | Neutral | 2 | |
| Goboglide Tech | 3 | Common | Neutral | 2 | |
| Lightning Breath | 3 | Rare | Shaman | 2 | |
| Living Dragonbreath | 3 | Common | Neutral | 2 | |
| Primordial Explorer | 3 | Common | Hunter | 2 | |
| Ramming Speed | 3 | Epic | Warrior | 1 | |
| Scalerider | 3 | Common | Neutral | 2 | |
| Seal Fate | 3 | Rare | Rogue | 2 | |
| Skybarge | 3 | Rare | Warrior | 2 | |
| Sky Claw | 3 | Rare | Paladin | 2 | |
| Azure Explorer | 4 | Common | Mage | 2 | |
| Bad Luck Albatross | 4 | Rare | Neutral | 1 | |
| Devoted Maniac | 4 | Common | Neutral | 2 | |
| Dragonmaw Poacher | 4 | Rare | Neutral | 2 | |
| Evasive Feywing | 4 | Common | Neutral | 2 | |
| Fiendish Rites | 4 | Common | Warlock | 2 | |
| Grave Rune | 4 | Common | Priest | 2 | 1 |
| Hippogryph | 4 | Common | Neutral | 2 | |
| Hoard Pillager | 4 | Rare | Neutral | 1 | |
| Lightforged Zealot | 4 | Rare | Paladin | 1 | |
| Squallhunter | 4 | Common | Shaman | 2 | |
| Troll Batrider | 4 | Common | Neutral | 2 | |
| Veiled Worshipper | 4 | Epic | Warlock | 1 | |
| Wing Commander | 4 | Common | Neutral | 2 | |
| Aeroponics | 5 | Rare | Druid | 1 | |
| Amber Watcher | 5 | Common | Paladin | 2 | |
| Big Ol' Whelp | 5 | Common | Neutral | 2 | |
| Chronobreaker | 5 | Rare | Priest | 1 | 1 |
| Cobalt Spellkin | 5 | Rare | Neutral | 2 | |
| Crazed Netherwing | 5 | Rare | Warlock | 1 | |
| Cumulo-Maximus | 5 | Epic | Shaman | 1 | |
| Faceless Corruptor | 5 | Rare | Neutral | 2 | |
| Platebreaker | 5 | Common | Neutral | 2 | |
| Rolling Fireball | 5 | Epic | Mage | 1 | |
| Shield of Galakrond | 5 | Common | Neutral | 2 | |
| Time Rip | 5 | Rare | Priest | 1 | |
| Abyssal Summoner | 6 | Common | Warlock | 2 | |
| Camouflaged Dirigible | 6 | Common | Neutral | 2 | |
| Candle Breath | 6 | Common | Rogue | 2 | |
| Corrupt Elementalist | 6 | Rare | Shaman | 2 | |
| Emerald Explorer | 6 | Common | Druid | 2 | |
| Evasive Wyrm | 6 | Common | Neutral | 2 | |
| Gyrocopter | 6 | Common | Neutral | 2 | |
| Utgarde Grapplesniper | 6 | Rare | Neutral | 2 | |
| Dragoncaster | 7 | Rare | Mage | 2 | |
| Evasive Drakonid | 7 | Common | Neutral | 2 | |
| Galakrond, the Nightmare | 7 | Legendary | Rogue | 1 | |
| Galakrond, the Tempest | 7 | Legendary | Shaman | 1 | |
| Galakrond, the Unspeakable | 7 | Legendary | Priest | 1 | |
| Galakrond, the Wretched | 7 | Legendary | Warlock | 1 | |
| Galakrond, the Unbreakable | 7 | Legendary | Warrior | 1 | |
| Lightforged Crusader | 7 | Epic | Paladin | 1 | |
| Zzeraku the Warped | 8 | Legendary | Warlock | 1 | |
| Sathrovarr | 9 | Legendary | Neutral | 1 |


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Practical, hands-on learning programs for entrepreneurs delivered by a variety of affiliate organizations in the U.S., around the world.
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An online program that immerses participants in the fundamental concepts of an entrepreneurial mindset to empower learners and help them develop entrepreneurial skills.
This innovative program empowers community colleges to support high-growth tech startups and entrepreneurs in their communities with seed-stage capital, high-impact mentorship, educational resources, and access to important networks.
Online interview, video series featuring personal lessons and insights from accomplished entrepreneurs, including tips, anecdotes, and personal characteristics.
Created by Make magazine, it’s the premier event for grassroots American innovation, celebrating arts, crafts, engineering, food, music, science, and technology.
A nationally-acclaimed Midwest entrepreneurial “immersion” program and powerful network for innovative, high-growth entrepreneurs.
A worldwide network of volunteer curators creating a comprehensive database of local startup companies and entrepreneurs.
A good mentor will offer you timely guidance about your particular industry or phase of business. These programs are designed to connect you with coaching and help you make the right moves.
Let us help you get coaching
Engages Kansas City entrepreneurs through a weekly educational program in which regional startups present their companies to a diverse audience of mentors, advisors, and entrepreneurs.
iStart is the go-to site for entering business competitions from around the world, browsing pages of startup ideas and networking with entrepreneurs.
Practical, hands-on learning programs for entrepreneurs delivered by a variety of affiliate organizations in the U.S., around the world.
Tapping the potential of online education, Founders School presents curriculum that enable entrepreneurs to learn anytime, anywhere, through a rich learning experience presented by subject matter experts.
An online program that immerses participants in the fundamental concepts of an entrepreneurial mindset to empower learners and help them develop entrepreneurial skills.
This innovative program empowers community colleges to support high-growth tech startups and entrepreneurs in their communities with seed-stage capital, high-impact mentorship, educational resources, and access to important networks.
Online interview, video series featuring personal lessons and insights from accomplished entrepreneurs, including tips, anecdotes, and personal characteristics.
A nationally-acclaimed Midwest entrepreneurial “immersion” program and powerful network for innovative, high-growth entrepreneurs.
A worldwide network of volunteer curators creating a comprehensive database of local startup companies and entrepreneurs.
U.S.SourceLink is America's largest resource network for entrepreneurs, encompassing more than 5,000 entrepreneurial support organizations that serve established businesses and aspiring entrepreneurs.
A global not-for-profit organization that propels women’s full participation as entrepreneurs and leaders in high-growth businesses, fueling innovation and driving growth.
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iStart is the go-to site for entering business competitions from around the world, browsing pages of startup ideas and networking with entrepreneurs.
This innovative program empowers community colleges to support high-growth tech startups and entrepreneurs in their communities with seed-stage capital, high-impact mentorship, educational resources, and access to important networks.
A global not-for-profit organization that propels women’s full participation as entrepreneurs and leaders in high-growth businesses, fueling innovation and driving growth.
Provides education, training, mentoring, and information on best practices in the field of angel investing to improve connections between angel investors and entrepreneurs.
U.S.SourceLink is America's largest resource network for entrepreneurs, encompassing more than 5,000 entrepreneurial support organizations that serve established businesses and aspiring entrepreneurs.


Book Search
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Tester Paragraph


For this tutorial, we will be developing with the:
We will be working in the Plugin Perspective of the IDE.
If you are new to Eclipse, then you can download an Eclipse package and install it on your computer. In this tutorial, we will be developing with Eclipse for RCP and RAP Developers. For development, the latest release ( currently Luna) should be good.
Unzip the downloaded package to a location of your choosing (e.g.
C:\Program Files\ Eclipse\Luna\Chaupal) and run (on Windows )
eclipse.exe. The Eclipse IDE should open for you to work with.
Follow the guidelines of the wizard and select a workspace
on a location of your choosing. This is where you will be developing
your projects. In a few minutes you should be up and running! You now
have a bare-bones development environment to work with.
It is recommended to download the most recent updates for the IDE. For
WindowsTM users, you'll have to (re-) start the IDE with
Administrator rights and select:
Help -> Check for Updates
Run the wizard and restart Eclipse.
In order to unleash Chaupal, you will need to add Chaupal functionality to your IDE. You can do this by adding the latest release of the Chaupal jp2p-ui update site to your IDE. Select Window -> Preferences -> Install/Update -> Available Software Sites and then 'Add' a 'New Site'. Enter a general text (e.g Chaupal) and then include the URL to the most current release of jp2p-ui (e.g: https://chaupal.github.io/releases/jp2p-ui/1.1.0/20150516/site.xml) . Then press 'OK' to get back to the IDE.
Next we need to install the bundles. Go to Help -> Install new software and select (work with) the update site you just made. If all went well, you should be able to select the 'Chaupal JP2P' option. Select this and follow the guidelines of the wizard. Restart Eclipse and wait for the IDE to come up again.
We are almost done! Create a new RCP plugin project by following the
next steps:


Recipes
Chickpea Salad with Tamarind dressing and fresh Cilantro
- 15 ounces chickpeas, rinsed and drained
- 1 medium red onion, finely chopped
- 2 tablespoons tamarind paste
- salt to taste
- 4 tablespoons finely chopped cilantro
- 1/2 teaspoon cayenne pepper
Mix all the ingredients in a large (non-reactive) mixing bowl and serve cold as a salad or a side dish.


vignettes/Equations.Rmd
Equations.Rmd
Here I present a description of main equations used in the functions
available in the package climatrends
.
Growing degree-days (gdd) is an heuristic tool in phenology that
measures heat accumulation and is used to predict plant and animal
development rates1. Growing
degree-days are calculated by taking the integral of warmth above a base
temperature (\(T_{0}\)). The function
GDD()
applies by default the following equation.
Equation [1]
\[GDD = \frac{T_{max} + T_{min}}{2} - T_{0}\]
where \(T_{max}\) is the maximum temperature in the given day, \(T_{min}\) is the minimum temperature in the given day and \(T_{0}\) is the minimum temperature for growth (as per the physiology of the focal organism or ecosystem averages).
Additionally, the function GDD()
offers three modified
equations designed for cold environments and for tropical environments.
For cold environments, where \(T_{min}\) may be lower than \(T_{0}\), there are two modified equations
that adjust either \(T_{mean}\)
(variant a) or \(T_{min}\) (variant b).
The variant a changes \(T_{mean}\) to
\(T_{0}\) if \(T_{mean} < T_{0}\) and is expressed as
follow.
Equation [2]
\[ GDD = max \left(\frac{T_{max} + T_{min}}{2} - T_{0}, \; 0 \right)\]
The variant b, is calculated using Equation 1, but adjusts \(T_{min}\) or \(T_{max}\) to \(T_{0}\) if \(T < T_{0}\), the equation is adjusted as follows.
Equation [3]
\[ T < T_{0} \; \rightarrow \; T = T_{0} \]
where \(T\) may refer to \(T_{min}\) and/or \(T_{max}\) when the condition of being below \(T_{0}\) applies.
For tropical areas, where the temperature may surpass a maximum threshold (\(T_{0_{max}}\)), resulting in limited development, the minimum temperature is adjusted using Equation 3 and the maximum temperature is adjusted to a maximum base temperature as follow.
Equation [4]
\[ T_{max} > T_{0_{max}} \; \rightarrow \; T_{max} = T_{0_{max}} \]
where \(T_{0_{max}}\) is the maximum
base temperature for growth, defined in GDD()
using the
argument tbase_max
.
These modified equations are defined as ‘a’, ‘b’ and ‘c’,
respectively, and can be selected using the argument
equation
.
By default, the function returns the degree-days that is accumulated
over the time series using Equation 1. Additionally, the function may
return the daily values of degree-days or the number of days that a
given organism required to reach a certain number of accumulated
degree-days. These values are defined by ‘acc’, ‘daily’ or ‘ndays’ and
can be adjusted using the argument return.as
. The required
accumulated gdd is defined with argument degree.days
. For
example, the Korean pine (Pinus koraiensis) requires 105 \(^\circ C\) accumulated gdd to onset the
photosynthesis2. In that case,
GDD()
will calculate the growing degree-days (\(gdd\)) and sum up the values until it
reaches 105 \(^\circ C\) and return the
number of days required in the given season (\(GDD_{r}\)), as follows.
Equation [5]
\[\parallel GDD_{r} \parallel \: = \; ggd_1 \;+ \; ... \; + \; gdd_n\]
where \(GDD_{r}\) is the length of the vector with accumulated degree-days from day 1 to \(n\).
Late-spring frost is a freezing event occurring after a substantial accumulation of warmth. Frost damage is a known issue in temperate and boreal regions, it is associated with the formation of extracellular ice crystals that cause damage in the membranes3. Freezing occurring after an advanced phenological stage during spring may harm some plant species, resulting in lost of productivity in crop systems4 and important ecological impacts5.
The function late_frost()
supports the computation of
late-spring frost events. The function counts for the number of freezing
days with minimum temperature below a certain threshold (argument
tfrost
). And returns the number of days spanned by frost
events (temperature below tfrost
), latency (event with no
freezing temperature but also no accumulation of growing degree-days)
and warming (when growing degree-days are accumulated enabling the
development of the target organism). Additionally the function returns
the first day of the events. The function calculates the growing
degree-days applying the variant b (Eq. 3), which can be adjusted using
the argument equation
passed to GDD()
as
explained in the later section. The main inputs are a vector with
maximum and minimum temperatures to compute the degree-days, a vector of
dates (argument date
), and, if needed, the
tbase
and tfrost
, set by default to 4 and -2
\(^\circ C\).
Two functions in climatrends are mainly designed to
capture the effects of climate on the development and stress of crop
species, crop_sensitive()
computes indices that aim to
capture the changes in temperature extremes during key phenological
stages (e.g. anthesis), and ETo()
computes the reference
evapotranspiration.
The crop ecology indices available in climatrends
are described in Table 3. These indices were previously used in crop
models to project the impacts of climate change on crop yield4,6. Each index has a default
temperature threshold(s) which can be adjusted by using the arguments
*.threshold
. Where the *
means the index. For
example, to change the defaults for hts_max (high temperature stress), a
vector with the temperature thresholds is passed through the argument
hts_max.thresholds
.
Table 3: Crop sensitive indices computed by climatrends.
| Index | Definition | Default thresholds |
|---|---|---|
| hts_mean | High temperature stress using tmean | 32, 35, 38 °C |
| hts_max | High temperature stress using tmax | 36, 39, 42 °C |
| hse | Heat stress event | 31 °C |
| hse_ms | Heat stress event for at least two consecutive days | 31 °C |
| cdi_mean | Crop duration index | 22, 23, 24 °C |
| cdi_max | Crop duration index max temperature | 27, 28, 29 °C |
| lethal | Lethal temperatures | 43, 46, 49 °C |
The reference evapotranspiration measures the influence of the
climate on a given plant’s water need7. The function ETo()
applies the Blaney-Criddle method, a general theoretical method used
when only air-temperature is available locally. It should be noted that
this method is not very accurate and aims to provide the order of
magnitude of evapotranspitation. The reference evapotranspiration is
calculated using the following equation.
Equation [6]
\[ETo = p \times \left(0.46 \times \frac{T_{max} + T_{min}}{2} + 8 \right) \times K_c\]
Where \(p\) is the mean daily percentage of annual daytime hours, \(T_{max}\) is the maximum temperature, \(T_{min}\) is the minimum temperature, and \(K_c\) is the factor for organism water need.
The percentage of daytime hours (\(p\)) is calculated internally by the
‘data.frame’ and ‘sf’ methods in ETo()
using the given
latitude (taken from the inputted object
) and date (taken
from the inputted day.one
). It matches the latitude and
date with a table of daylight percentage derived from Brouwer and
Heibloem7. The table can be
verified using climatrends:::daylight
.


The CV Lounge network is available for Collegium V students to use. By using CollegiumV infrastructure, you agree to the following terms:
[1] Unauthorized use is prohibited
[2] Usage may be subject to security testing and monitoring
[3] Misuse is subject to criminal prosecution
[4] Users have no expectation of privacy except as otherwise provided by applicable privacy laws
[5] Non-academic use during academic hours (8 am Sunday to 8pm Friday) is permitted as long as it does not impact academic use
[6a] Gaming is allowed on lounge hardware only during non-academic hours, provided it is not unnecessarily disrupting others
[6b] Gaming is always allowed on personal hardware, provided it is not disrupting others or causing unnecessary strain on the network infrastructure


Features of loanr
Do more than just loan money.
Create and Receive Loan Requests
Use our simple interface to create and receieve loans without any hassle!
Bargain Loan Terms
When requesting and accepting a loan, bargain
Set Custom Interest Rates
Being nice should come with benefits. Use our Custom Interest payment option to makes some green on top.
Set Custom Pay-By Date
Use our Custom Pay-By Date option to set a simple deadline to receive your money by.
Pay Loans Back Incrementally
Can't make a payment all at once? Use our simple payment plan that allows you to spread the payments out.
 Use our bothering tool to annoy your friends until they pay you.
Email notifications
Get instant Email notifications to keep you up-to date on being paid, making payments, and even remind you of a deadline.
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With the power of Venmo, you can trust our service to be reliable.


The Mozilla
Science Lab is helping a global network of researchers, tool
developers, librarians and publishers collaborate to further
science on the web, via collaboration, prototyping and educational
projects. Check
out projects they're
working on with the open science community, and join the
dicsussion on their
forum or their
community calls.
Contact:
Abby Cabunoc,
Arliss Collins,
Bill Mills


/*
About
-----
This a code based video editor powered by the VideoContext library.
The example code below should give a good overview of how this works.
Pressing CTRL+S will and play your edits in browser.
API
---
vc - VideoContext instance (https://github.com/bbc/VideoContext).
vc.video(url) - create a new video
vc.image(url) - create a new image
vc.effect(definitiion) - create an effect node.
vc.compositor(definition) - create a compositor node.
vc.transition(definition) - create a transition node.
vc.DEFINITIONS - an object containing effect definitions.
Effect Definitions
------------------
The folloring effects are available via the DEFINITION object. A definiton cam be used to create any type of processing node, but they can be loosely grouped as the following:
effects: AAF_VIDEO_SCALE, STATIC_EFFECT, COLORTHRESHOLD, MONOCHROME, HORIZONTAL_BLUR, VERTICAL_BLUR, AAF_VIDEO_CROP, AAF_VIDEO_POSITION, AAF_VIDEO_FLIP, AAF_VIDEO_FLOP
combiners:COMBINE,
transitions: CROSSFADE, DREAMFADE, HORIZONTAL_WIPE, VERTICAL_WIPE, RANDOM_DISSOLVE, STATIC_DISSOLVE, TO_COLOR_AND_BACK, STAR_WIPE
Shortcuts
---------
Ctrl+S = play & save
Caveats
-------
* Content thats dosen't have a local path needs to be served from a server with a liberal CORS policy. (imgur is good for images).
*/
//Set-up rendering environment
var canvas = document.getElementById("canvas");
window.vc = new VideoContext(canvas);
//Create nodes for processing graph.
var videoNode1 = vc.video("../../assets/introductions-rant.mp4", 0);
var videoNode2 = vc.video("../../assets/introductions-rant.mp4", 10);
var videoNode3 = vc.video("../../assets/introductions-rant.mp4", 20);
var monochromeEffect = vc.effect(VideoContext.DEFINITIONS.MONOCHROME);
var transitionNode = vc.transition(VideoContext.DEFINITIONS.STAR_WIPE);
var chromakeyNode = vc.effect(VideoContext.DEFINITIONS.COLORTHRESHOLD);
//Connect the graph graph together
videoNode1.connect(monochromeEffect);
monochromeEffect.connect(transitionNode);
videoNode2.connect(transitionNode);
transitionNode.connect(vc.destination);
videoNode3.connect(chromakeyNode);
chromakeyNode.connect(vc.destination);
//Setup the start/stop times for the video sources
videoNode1.start(0);
videoNode1.stop(5);
videoNode2.start(3);
videoNode2.stop(11);
videoNode3.start(0);
videoNode3.stop(11);
//Que up a transition
transitionNode.transition(3,5,0.0,1.0);
vc.play();


Single expression searches include the expression in the URL path.
Thus the search "Category equals Analgesics" is https://chem.nlm.nih.gov/api/data/category/equals/analgesics?data=totals
The abbreviated form is https://chem.nlm.nih.gov/api/data/ca/eq/analgesics?data=totals
Except for Structure searches with SMILES values, the expression value is not case-sensitive.
Multi-expression searches have two or more expressions that must all be true to match substances.
The expressions are listed in the query string.
Each expression uses the key "exp" and the value is the same path as the single expression version except path slashes are replaced with %2F
The search "Category equals Analgesics AND Locator equals DrugPortal" is https://chem.nlm.nih.gov/api/data/search?data=totals&exp=category%2Fequals%2Fanalgesics&exp=locator%2Fequals%2Fdrugportal
The abbreviated form is https://chem.nlm.nih.gov/api/data/search?data=totals&exp=ca%2Feq%2Fanalgesics&exp=lo%2Feq%2Fdrugportal
When using a multi-expression search, expressions may also be negated, such that the search is of the form A AND NOT B.
At least one expression must not be negated.
To negate an expression, add "not" to the beginning of the operator.
Thus "Category equals Analgesics AND NOT Locator equals DrugPortal" is https://chem.nlm.nih.gov/api/data/search?data=totals&exp=ca%2Feq%2Fanalgesics&exp=lo%2Fnoteq%2Fdrugportal
The examples above all include data=totals. Any valid data parameter could be used with the same searches to return different levels of detail for all matching substances.


|
Final Project
6.0
ARIAC - Agile Robotics for Industrial Automation Competition
|
Picking and delivering parts in an industrial environment with faulty parts/faulty gripper/sensor blackout/moving obstacles
Install Ariac package in your workspace using the steps mentioned in the following link
https://github.com/usnistgov/ARIAC/blob/master/wiki/tutorials/installation.md "Ariac Installation Instructions"
Follow these instructions to run the package after installing ARIAC
Wait till the terminal says "you can start planning now"
Open the index.html file present in "/ariac_ws/src/final-group1/Doxygen_report/html/index.html"


|
clang::tidy PagesJaunes rules
1.0
Rules for manipulating PagesJaunes eSQL requests
|
#include <ExecSQLLOBCloseToFunctionCall.h>
Classes | |
| struct | AssignmentRecord |
| struct | ReqFmtRecord |
| class | SourceRangeBefore |
| class | SourceRangeForStringLiterals |
| struct | StringLiteralRecord |
Public Types | |
| using | source_range_set_t = std::multiset< SourceRangeForStringLiterals, SourceRangeBefore > |
Public Member Functions | |
| ExecSQLLOBCloseToFunctionCall (StringRef, ClangTidyContext *) | |
| Constructor for the ExecSQLLOBCloseToFunctionCall rewriting check. More... | |
| void | storeOptions (ClangTidyOptions::OptionMap &Opts) override |
| Store options for this check. More... | |
| void | registerMatchers (ast_matchers::MatchFinder *) override |
| Register the ASTMatcher that will found nodes we are interested in. More... | |
| void | registerPPCallbacks (CompilerInstance &Compiler) override |
| Register callback for intercepting all pre-processor actions. More... | |
| void | check (const ast_matchers::MatchFinder::MatchResult &) override |
| This method is called each time a visited AST node matching our ASTMatcher is found. More... | |
| void | onStartOfTranslationUnit () |
| called at start of processing of translation unit More... | |
| void | onEndOfTranslationUnit () |
| called at end of processing of translation unit More... | |
Public Attributes | |
| ClangTidyContext * | TidyContext |
Protected Attributes | |
| std::vector< struct StringLiteralRecord * > | m_req_copy_collector |
| std::vector< struct AssignmentRecord * > | m_req_assign_collector |
| std::vector< struct ReqFmtRecord * > | m_req_fmt_collector |
Definition at line 27 of file ExecSQLLOBCloseToFunctionCall.h.
| using clang::tidy::pagesjaunes::ExecSQLLOBCloseToFunctionCall::source_range_set_t = std::multiset<SourceRangeForStringLiterals, SourceRangeBefore> |
Definition at line 117 of file ExecSQLLOBCloseToFunctionCall.h.
| clang::tidy::pagesjaunes::ExecSQLLOBCloseToFunctionCall::ExecSQLLOBCloseToFunctionCall | ( | StringRef | Name, |
| ClangTidyContext * | Context | ||
| ) |
Constructor for the ExecSQLLOBCloseToFunctionCall rewriting check.
ExecSQLLOBCloseToFunctionCall constructor
The rule is freed a new check using its ClangTidyCheck
base class. Name and context are provided and stored locally. Some diag ids corresponding to errors handled by rule are freed:
| Name | A StringRef for the new check name |
| Context | The ClangTidyContext allowing to access other contextsInit check (super class) Init our TidyContext instance Request grouping option: Filename containing a json map for a group name indexing a vector of requests name |
Definition at line 129 of file ExecSQLLOBCloseToFunctionCall.cpp.
|
override |
This method is called each time a visited AST node matching our ASTMatcher is found.
check
This method will navigated and inspect the found AST nodes for:
| Result | The match result provided by the recursive visitor allowing us to access AST nodes bound to variables |
Definition at line 623 of file ExecSQLLOBCloseToFunctionCall.cpp.
| void clang::tidy::pagesjaunes::ExecSQLLOBCloseToFunctionCall::onEndOfTranslationUnit | ( | ) |
called at end of processing of translation unit
onEndOfTranslationUnit
Override to be called at end of translation unit
Definition at line 215 of file ExecSQLLOBCloseToFunctionCall.cpp.
| void clang::tidy::pagesjaunes::ExecSQLLOBCloseToFunctionCall::onStartOfTranslationUnit | ( | ) |
called at start of processing of translation unit
onStartOfTranslationUnit
Override to be called at start of translation unit
Definition at line 202 of file ExecSQLLOBCloseToFunctionCall.cpp.
|
override |
Register the ASTMatcher that will found nodes we are interested in.
registerMatchers
This method register 1 matcher for each oracle ProC generated statement to rewrite. The matcher bind elements we will use, for detecting the found statement we want to rewrite , and for writing new code.
| Finder | the recursive visitor that will use our matcher for sending us AST node. |
Definition at line 265 of file ExecSQLLOBCloseToFunctionCall.cpp.
|
override |
Register callback for intercepting all pre-processor actions.
ExecSQLLOBCloseToFunctionCall::registerPPCallbacks
Allows to register a callback for executing our actions at every C/C++ pre-processor processing. Thanks to this callback we will collect all string literal macro expansions.
| [in] | compiler | the compiler instance we will intercept |
Definition at line 286 of file ExecSQLLOBCloseToFunctionCall.cpp.
|
override |
Store options for this check.
storeOptions
This check support one option for customizing comment regex
| Opts | The option map in which to store supported options |
Definition at line 238 of file ExecSQLLOBCloseToFunctionCall.cpp.
|
protected |
Definition at line 192 of file ExecSQLLOBCloseToFunctionCall.h.
|
protected |
Definition at line 135 of file ExecSQLLOBCloseToFunctionCall.h.
|
protected |
Definition at line 241 of file ExecSQLLOBCloseToFunctionCall.h.
| ClangTidyContext* clang::tidy::pagesjaunes::ExecSQLLOBCloseToFunctionCall::TidyContext |
Definition at line 31 of file ExecSQLLOBCloseToFunctionCall.h.


|
Boss2D
2.6.1
|
2D영역 More...
#include <boss_rect.hpp>
Inherits BOSS::rect128f.
Public Member Functions | |
| Rect (const rect128f &rhs) | |
| Rect (const rect128 &rhs) | |
| Rect (const point64f point, const size64f size) | |
| Rect (const point64f point1, const point64f point2) | |
| Rect (float l, float t, float r, float b) | |
| Rect & | operator= (const rect128f &rhs) |
| Rect & | operator+= (const point64f &rhs) |
| Rect | operator+ (const point64f &rhs) const |
| Rect & | operator-= (const point64f &rhs) |
| Rect | operator- (const point64f &rhs) const |
| Rect & | operator+= (const size64f &rhs) |
| Rect | operator+ (const size64f &rhs) const |
| Rect & | operator-= (const size64f &rhs) |
| Rect | operator- (const size64f &rhs) const |
| Rect & | operator*= (float rhs) |
| Rect | operator* (float rhs) const |
| Rect & | operator/= (float rhs) |
| Rect | operator/ (float rhs) const |
| bool | operator== (const rect128f &rhs) const |
| bool | operator!= (const rect128f &rhs) const |
| const float | Width () const |
| const float | Height () const |
| const point64f | Center () const |
| const float | CenterX () const |
| const float | CenterY () const |
| const bool | PtInRect (const point64f point) const |
| const bool | PtInRect (const float x, const float y) const |
| const bool | ContactTest (const Rect rect) const |
| Rect | Inflate (const float x, const float y) const |
| Rect | Deflate (const float x, const float y) const |
Additional Inherited Members | |
| Public Attributes inherited from BOSS::rect128f | |
| float | l |
| float | t |
| float | r |
| float | b |
2D영역


Base type: System.Entity
Summary: This entity contains main poller and all additional pollers list.
| Name | Type | Notes |
|---|---|---|
| EngineID | System.Int32 | |
| ServerName | System.String | |
| IP | System.String | |
| ServerType | System.String | |
| PrimaryServers | System.String | |
| KeepAlive | System.DateTime | |
| FailOverActive | System.DateTime | |
| SysLogKeepAlive | System.DateTime | |
| TrapsKeepAlive | System.DateTime | |
| Restart | System.DateTime | |
| Elements | System.Int32 | |
| Nodes | System.Int32 | |
| Interfaces | System.Int32 | |
| Volumes | System.Int32 | |
| Pollers | System.Int32 | |
| MaxPollsPerSecond | System.Int16 | |
| MaxStatPollsPerSecond | System.Int16 | |
| NodePollInterval | System.Int16 | |
| InterfacePollInterval | System.Int16 | |
| VolumePollInterval | System.Int16 | |
| NodeStatPollInterval | System.Int16 | |
| InterfaceStatPollInterval | System.Int16 | |
| VolumeStatPollInterval | System.Int16 | |
| LicensedElements | System.Int32 | |
| SerialNumber | System.String | |
| LicenseKey | System.String | |
| StartTime | System.DateTime | |
| CompanyName | System.String | |
| CustomerID | System.String | |
| Evaluation | System.String | |
| EvalDaysLeft | System.Int16 | |
| PackageName | System.String | |
| EngineVersion | System.String | |
| WindowsVersion | System.String | |
| ServicePack | System.String | |
| AvgCPUUtil | System.Single | |
| MemoryUtil | System.Single | |
| PollingCompletion | System.Single | |
| StatPollInterval | System.Int32 | |
| BusinessLayerPort | System.Int32 | |
| FIPSModeEnabled | System.Boolean | |
| MinutesSinceKeepAlive | System.Int32 | |
| MinutesSinceFailOverActive | System.Int32 | |
| MinutesSinceSysLogKeepAlive | System.Int32 | |
| MinutesSinceTrapsKeepAlive | System.Int32 | |
| MinutesSinceRestart | System.Int32 | |
| MinutesSinceStartTime | System.Int32 | |
| DisplayName | System.String | |
| DisplayName | System.String | |
| Description | System.String | |
| InstanceType | System.Type | |
| Uri | System.String | |
| InstanceSiteId | System.Int32 | Default='0'. |
| Agents | Orion.AgentManagement.Agent | Defined by relationship Orion.AgentManagement.EngineReferencesAgent (System.Reference) |
| PoolMember | Orion.HA.PoolMembers | Defined by relationship Orion.EnginesReferencesPoolMembers (System.Reference) |
| Probe | Orion.NetPath.Probes | Defined by relationship Orion.NetPath.EnginesReferencesProbes (System.Reference) |
| AssignedNodes | Orion.Nodes | Defined by relationship Orion.EngineHostsNodes (System.Reference) |
| EngineProperties | Orion.EngineProperties | Defined by relationship Orion.EnginesHostsEngineProperties (System.Hosting) |
| PollingUsage | Orion.PollingUsage | Defined by relationship Orion.EnginesHostsPollingUsage (System.Hosting) |
| Events | Orion.Events | Defined by relationship Orion.EnginesHostsEvents (System.Reference) |
| ReachabilityInfo | Orion.ReachabilityInfo | Defined by relationship Orion.EnginesReferencesReachabilityInfo (System.Reference) |
| GroupNode | IPAM.GroupNode | Defined by relationship IPAM.GroupNodeReferenceEngine (System.Reference) |
| FlowEngine | Orion.NetFlow.FlowEngines | Defined by relationship Orion.NetFlow.FlowEnginesReferencesEngines (System.Reference) |
| SEUMAgents | Orion.SEUM.Agents | Defined by relationship Orion.SEUM.AgentReferencesEngine (System.Reference) |


Files CCore/inc/FileNameMatch.h CCore/src/FileNameMatch.cpp
FileNameFilter is a class, designed to filter file names according a set of usual meta-templates with wildcards '*' and '?'.
class FileNameFilter : NoCopy
{
....
public:
FileNameFilter() noexcept;
explicit FileNameFilter(StrLen filter,ulen max_states=MaxULen);
~FileNameFilter();
// props
bool operator + () const;
bool operator ! () const;
// methods
void reset();
void reset(StrLen filter,ulen max_states=MaxULen);
bool operator () (StrLen file) const;
};
Default constructor creates an object in null state. You can reset an object to this state using the method reset(). Null state object cannot be used to filter file names. You have to initialize it first.
Non-default constructor creates an initialized object. filter is a file name template with wildcards, max_states is a number of states limit. Constructor creates a state machine to examine file names.
operator + () is true iff the object is initialized.
operator ! () is true iff the object is in null state.
reset() return the object into the null state.
reset() with arguments reinitializes the object.
operator () checks, if the given file name matches the file name templates. If the object is not initialized, false is returned.


Examples
- Same Domain:
- Pulls from the local domain using XMLHttpRequest
- Same Domain (Expires set to 0):
- Pulls from the local domain using XMLHttpRequest tests expiration
- Alternate Domain:
- Pulls from the remote domain using iFrame Transports
- Pointcuts:
- Items that haven't been properly externalized can still be captured.
- AMD:
- The Asynchronous Module Definition (AMD) API specifies a mechanism for defining modules such that the module and its dependencies can be asynchronously loaded.
- AMD-jQuery:
- jQuery was loaded using a define() native jQuery 1.7
- addRule():
- how to use the addRule() syntax to support supplemental libraries such as jQuery UI
- addRule() for versioning:
- how to use the addRule() syntax to support versioning


Test 1: A programmatic repeat using a Template with a textbox and an mvc output field.
Test 2: A programmatic repeat with the html inline with an mvc output field and a textbox.
Test 3: A programmatic repeat with the html inline using mvc.at.
Test 4: Programmatic Swap models, this one is done by swapping between different models, I would like to be able to update the model data without replacing the model.
Test 5: Swap models, (these are declarative buttons) this one is done by swapping between different models, I would like to be able to update the model data without replacing the model.


This work aims to mathematically quantify image quality and performance of different real-time upscaling algorithms.
Before attempting to reproduce, make sure to grab the latest version of mpv and updated user shaders. You can get the shaders from bjin and igv (FSRCNNX)/igv (SSSR).
UPDATE - 11/05/2019: KrigBilateral updated.
UPDATE - 22/04/2019: FSRCNNX updated, removing the downscaling section for now since people aren't exactly going out of their ways to fix shitty upscales and there's already some information about it on the fractional tables.
UPDATE - 21/04/2019: Preliminar fractional upscaling evaluatons added, focusing on the most relevant algorithms first.
UPDATE - 18/04/2019: Ravu-zoom-r4 added, r2 and r3 were updated.
UPDATE - 17/04/2019: PSNR-HA/HMA measurements are now done with wstep = 7 as recommended by igv.
UPDATE - 16/04/2019: New FPS measurement methodology, files now play for 4 seconds and then I calculate how many frames were displayed based on which frame it stopped at after the time-frame has elapsed. --scalers-resizes-only was also removed since the half pixel shift is not noticeable during playback. Previous results had different numbers, but the order didn't exactly significantly change.
UPDATE - 06/04/2019: Tables updated with newer versions of FSRCNNX again.
UPDATE - 31/03/2019: MS-SSIM tables were removed. All remaining luma related tables were updated. New methodology consists of basically utilising a full-range greyscale PNG as input (which results in lower quantisation errors when compared to using limited range YCbCr). Ravu-zoom was added, FSRCNNX_x2_16-0-4-1 and Ravu-lite were updated.
UPDATE - 27/03/2019: Updated PSNR-HA/HMA, you can expect to see ravu-ar and ravu-zoom soon. PSNR-HVS-M was removed since it's deprecated by the insertion of PSNR-HA.
UPDATE - 15/03/2019: New versions of FSRCNNX.
UPDATE - 08/03/2019: Adding another test image for chroma, and changed all chroma tests to upscale from a yuv4mpegpipe y4m file which makes me more confident they're accurate.UPDATE - 07/03/2019: Adding Ravu-lite and fixing NGU-AA's half pixel shift. Huge thanks for Bjin for providing a user-shader to accomplish the latter =). FPS chart should be updated soon.
UPDATE - 03/03/2019: Ravu-chroma and Ewa_Robidoux/Ewa_Robidouxsharp added.
UPDATE - 27/02/2019: PSNR-HMA and PSNR-HA tables added.
UPDATE - 25/02/2019: Initial version of the Chroma section is added. I'll take some time to slowly polish it with more information and different tests, and I'm also probably going to add PSNR-HMA to the RGB tests soon.
UPDATE - 20/02/2019: IW-SSIM tables added.UPDATE - 19/02/2019: MS-SSIM tables fixed, code had issues with RGB -> greyscale conversion.
UPDATE - 18/02/2019: Lanczos added, and tables now display results from best to worst.
UPDATE - 16/02/2019: Other EWA scalers were added.
UPDATE - 22/12/2018: I found out a mistake in previous results, and have once again updated all quality comparison results.
I'm not certain about what was causing the problems, but turning off PNG filtering and debanding seems to have fixed it. I'll investigate which of the two was the culprit once I have the time.
Well, since I had to redo everything, I took this opportunity to improve the testing methodology, debanding was turned off to prevent loss of detail, and I used a lossless
YUV444p AVC encode as upscaling source instead of a YUV444p JPEG.
UPDATE - 18/12/2018: Results have been updated with latest versions of FSRCNNX and Waifu2x. On top of that, I've included MS-SSIM and PSNR-HVS-M measurements. I've also included all NGU algorithms from MadVR since people are interested in them.
If all you want is to look at the results, follow this link.
Like its name implies, upscaling is simply increasing the scale of something. More specifically, taking discrete information in a given scale and finding values between the existing samples. The easiest and most classic way of doing this is through simple linear interpolation, if you want to find a value between two points you can simply draw a line between them and linearly find any value in this line. If you wanted to find the value that's placed exactly in the middle of those 2 discrete points, you could simply do an arithmetic mean with their values to find your answer.
Linear interpolation can be done in a plane, through both axis, creating what we call "bilinear" interpolation. Bilinear interpolation is the simplest interpolation algorithm, easiest to calculate and also unironically the most used one in the industry due to the fact that it's extremely simple to implement.
But can something as simple as just drawing a line between 2 known discrete points give us good results? It depends entirely on how the original information looked like. We can however, increase the complexity of our upscaling algorithm by increase the amount of information it takes into consideration in order to find values between our discrete points. In this page we'll evaluate what we can do differently, how much better our results can get and how it affects our performance.
A relatively simple way of taking more information into consideration when finding values between discrete points is to use
more than just the information of 2 points to calculate a function that connects them. We can trace a polynomial
curve between points if we take into account the information of neighbouring elements, calculating the gradients
and therefore becoming able to connect them with curves instead of lines. The shape of the curve connecting points
depends on the windowing and scaling functions used.
We can more precisely upscale something if we try to reconstruct strucutures, the most evident problem with linear or polynomial scalers is the thickening of border areas where the interpolated result doesn't transit between values as sharply, resulting in a blurrier image with "lost" detail in the strucutures if you're downscaling and then upscaling it back.
Machine learning comes as a powerful successor to classical methods due to the fact that you do not need to rely solely on what you can currently retrieve from the image, but also on a set of trained parameters generated from analysing multiple images and coming up with an upscaling model.
There are multiple different machine learning based image upscalers, we'll stick to those that are easily testable as mpv user shaders, MadVR's NGU and finally Waifu2x as our state of the art representation.
We'll test the following algorithms:
Performance measurements were done upscaling an animation video encoded into 8bit AVC from 1280x720 to 2560x1440. Utilising mpv with a benchmarking profile, all settings from profile=gpu-hq, with Vulkan as the renderer and hardware decoding turned off. The machine used has an Ivy Bridge i5 3470, a Polaris RX 470 and user shaders were always compute shaders when possible. The methodology consists of letting mpv play the file for 4 seconds and then seeing at which frame it stopped.
Quality measurements were done in 2 test images, one from animation and another one from live action. Debanding was turned off to prevent loss of fine detail.
The reasoning behind this comes from the fact that the live action image has more high frequency components that are harder to "restore". In order to measure how "good" each algorithm is, the test images were previously bicubic downscaled to a quarter of their original resolutions (0.5x scaling factor in both axes), and then upscaled back to their original resolutions with a direct 2x upscaling factor (2x in both axes outputs a resolution that's 4x larger in pixels). Every single scaler was tested on a full range greyscale PNG, which can be found on the repository.
Performance was evaluated simply in frames per second, while quality was evaluated in PSNR, SSIM, IW-SSIM, PSNR-HMA and PSNR-HA.
The following image was used for the animation upscaling testing:
Before we continue to the results, you can find all images in this repository.
We can see the results below:
The following image was used for the live-action upscaling testing:
Again, you can find all the images in this repository.
We can see the results below:
We can clearly see that in general, machine learning based scalers tend to give better quality, though as expected they're also more computationally expensive. We can see that FSRCNNX is the highest scoring mpv scaler, trading blows only with NGU.
All NGU algorithms were tested on their highest quality presets (Very High), which was fine on the RX470, but significantly heavier than FSRCNNX-8-0-4-1. FSRCNNX-16-0-4-1's performance is also relatively okay, but the increased quality over its lighter variant might not justify using it.
NNEDI3 is pointless. SSSR can be a nice alternative for low scaling factors (since FSRCNNX is a doubler and therefore would need to be downscaled afterwards), and Ravu while being blurrier might be able to hide compression artifacts or bad art in general.
If the point is getting as close as possible to the intended result, for mpv FSRCNNX is the clear choice.
If you're using MadVR, both NGU-STANDARD and NGU-SHARP look great as long as your system can handle them, and NGU-AA is a Ravu alternative.
While I'm providing numerical test results to mathematically evaluate how those different algorithms perform, I strongly advise taking a look on how the upscaled images actually end up looking like. The viewer has his/her own preference regarding different drawbacks like aliasing, ringing or blurring. Some people might prefer an algorithm that scores relatively poorly when compared to sharper choices, but you should please yourself while consuming your media.
Taking into consideration anime productions are still done at arbitrary resolutions between 1280x720 and 1920x1080 (with most below 1600x900) and that most users are still watching them on FHD 1920x1080 displays, the most common scenario when there's any luma upscaling (or rgb upscaling if you want to nitpick about it, since mpv merges luma and chroma right after doubling chroma) being performed by the player is arguably 720p->1080p, which corresponds to a 1.5x scaling factor. With the recent addition of ravu-zoom to our ever growing arsenal of user shaders, and the need to find out which dscales work better alongside the double-only prescalers, adding a new series of measurements seem reasonable.
The methodology is straightforward, Violet was downscaled to 1280x720 using catmull_rom and then brought back up to 1920x1080.
As expected, the doublers perform relatively poorly alongside built-in scalers. Ravu-zoom is the best stand-alone scaler, but it gets beaten by ravu-lite and FSRCNNX when those are used with SSimDownscaler. I originally only wanted to include the best version of each shader, but FSRCNNX_x2_8-0-4-1 will need to be included soon since the peformance disparity between FSRCNNX_x2_8-0-4-1 + SSimDownscaler and Ravu-zoom-r4 is just too high.
Chroma subsampling is a technique utilised to save bitrate/filesize without strongly sacrificing perceived quality, by taking into account how our eyes biologically work and how our brains interpret the information they're receiving.
With the rise of television broadcasting the recurring problem of bandwidth-heavy innovations rapidly making the electromagnetic spectrum "crowded" started to become problematic, the practical bands of low long-range attenuation were becoming scarce and that would undoubteadly limit the amount of things we could have "over the air", which then lead the way to new bandwidth-saving techniques that aimed to reduce the required bandwidth as much as reasonably possible without affecting the perceived quality of the service to the same extent.
Since we're more likely to perceive contrast/luminosity differecens than chromatic details, chroma-subsampling is simply the most basic way of throwing away some colouring information without sacrificing on luminosity resolution.
To make this simple to understand, we can see a normal image below alongside its RGB planes:
Now, the same image alongside its YUV/YCbCr planes:
We can easily simulate how it would look like if it didn't have its entirely chromatic information available by simply downscaling the chroma planes to 1/4 of their original resolution (0.5x scaling factor) and then upscaling them back (2x scaling factor).
It's important to see how much "blurrier" the chromatic planes look after this process, in other words, how much high frequency information they lost.
Can't notice the difference when you put it back to RGB? Well, that's the point. In any case, to make it possible for us to see, you can look at the image below, which is simply 128 plus the difference between the reference and the chroma subsampled version:
From this simulation it's probably reasonable to understand why chroma upscaling isn't usually a big concern, it's just that you're unlikely to notice the difference on real content.
With that in mind, we can proceed with the actual comparison. SSIM measurements can be ignored this time since the luma plane remains intact and therefore there are almost no significant gains to be made in structural similarity from switching the scaler.
Rosetta served as a somewhat unfaithful representation of what you should expect from anime, since usually speaking actual anime footage is far from being as detailed and therefore the scalers would score even closer overall. We can proceed with a live action example.
It's important to notice how the numerical difference between the scalers is much smaller when doing chroma measurements, and this is precisely why using a heavier scaler is usually not warranted unless the performance impact is negligible.
On my system, running KrigBilateral on Vulkan makes no difference whatsoever since I have a CPU decoding bottleneck at around ~1200 FPS with or without it on a 720p 8bit AVC file. Running on ra_d3d11 with d3d11va hardware decoding, I go from ~1800 FPS to ~1150 FPS going from lanczos to KrigBilateral. Running both FSRCNNX-8-0-4-1 and KrigBilateral at the same time gives me ~260 FPS on both d3d11 and Vulkan, with or without hwdec.
My personal recommendation is that you should test it yourself to see if you can notice KrigBilateral's difference during playback, and use it if it doesn't really matter resource-wise (in the case your GPU is fine either way). Another sensible decision would be to use it when you don't need luma upscaling, since then the only gains you can make are in chroma.


| What I Do (or Want to Do) | I’m Hillary Freeman, and I’m running for City Council. |
| Context and Value | I love Palo Alto and want to bring our policies and our community values into balance. I’m a business and community leader who shares your values. I am:
|
| Evidence | I believe I have the right mix of business skills and community values to lead Palo Alto into the future. I share your values as a mother, wife of a business owner, and local leader on the YMCA board, PTA Council, Libraries Now! Committee, Children’s Theater and youth sports. I’m also a software company executive who has experience in fiscal accountability, and business and change management. |
Although Hillary kept her overarching messages the same (e.g., marriage of business skills and community values for new leadership), she tailored her evidence and examples according to her audience. For library lovers, she emphasized her founding membership in Libraries Now!, a grassroots group that worked to introduce a bond measure for improving libraries. For the school community, she stressed her PTA leadership, her role as a mother of schoolchildren and her volunteering in youth sports. Depending on your audience, you may have different elevator pitches.
Gloria, a procurement director at a large global company, told me that after completing our BrandingPays program, she found herself on the train with the newly appointed chief procurement officer (her manager’s manager). The train ride was going to be over an hour long and she knew she should take the opportunity to position herself with him. At first, she panicked. What was she going to say? But then she remembered that she had developed an elevator pitch with a value proposition for executives, and decided to try it out. Her introduction to him went well, and they talked at length about her role at the company and her ideas for instituting global best practices. Her goal was to have this senior executive know who she was and to position herself as a strategic contributor. Gloria’s elevator pitch helped her to come across as articulate and present her role in a strategic global context. Mission accomplished!
An elevator pitch will give you confidence to meet new people in any setting because you know you have talking points to use.
Figure 3.4 is an example of an elevator pitch that positions Gloria as a strategic thinker and leader with company executives.
| What I Do (or Want to Do) | I’m Gloria Jeffries, the director of global procurement. |
| Context and Value | Procurement has never been more important than in today’s economic environment. To be globally competitive, we must streamline and consolidate purchasing with a balanced approach--one that assesses risks and options for global supply. |
| Evidence | We recently completed a global best practices study. We will soon be starting pilot programs at our company based on some interesting practices from leaders in other industries. From the standpoint of our own industry, we found that our company is the gold standard for best practices (provide metrics). |
How do you use your elevator pitch at networking events? It’s important to be yourself and to use your own words that sound natural. Remember that a conversation should not be an opportunity for you to talk nonstop about yourself. If someone asks you about yourself, say a few sentences to establish your positioning credibility, then ask the person about him- or herself. You will find opportunities throughout this give-and-take to weave in your key messages. Remember that your mission is education, not mere promotion. Ask yourself, “What is the one key thing that people will remember about me?” If they look at your business card after the event, will they remember that you are a purchasing exec or whatever you are, and connect with you later if they have a need in your area of expertise?
| What I Do (or Want to Do) | I’m George Paulsen of XYZ Law. I’m a lawyer who specializes in intellectual property. |
| Context and Value | Protecting intellectual property (IP) is key for companies whose fortunes rise and fall on their innovations. |
| Evidence | I recently helped a Fortune 500 company protect their IP interests when they spun off a technology business. I enjoy speaking to industry groups on the topic of managing the legal issues in innovation. |
By setting the context for why protecting intellectual property is important to business, George will likely get asked follow-on questions probing what he means. At that point, he could bring up a recent project he worked on with a Fortune 500 company. This exchange of ideas will come across as a natural conversation and not as a sales pitch.
However, within a few sentences, George will have positioned himself as a credible IP lawyer. People who meet him will consider recommending him as a speaker to their industry group if innovation or IP are topics of interest.
| What I Do (or Want to Do) | I’m Lee Chang. I recently graduated from XYZ University with an MBA degree. |
| Context and Value | I’d like to find a job with a global management consulting firm. I think clients could benefit from my background in software engineering management, business analysis and strategy skills. Working with Chinese clients would be great since I know the culture and the language. |
| Evidence | I know that I’d fit into a fast-paced consulting environment because I’ve had to lead deadline-oriented development teams. In business school, my project team won the contest for best business plan. |
Remember Lee’s positioning example in chapter 2? This elevator pitch is an example of how he could message his positioning value.
Depending on how the conversation went, he could bring up different evidence points. The overall impression of Lee is positive because he comes across as someone who knows what he wants and how to get it. This is the type of personality that management consulting firms seek to hire.
| What I Do (or Want to Do) | I’m a product development executive for 123 Company with a passion for enhancing innovation in engineering cultures. |
| Context and Value | My mantra is “innovate or die.” I’ve developed some unique practices for creating a more supportive and productive culture of innovation. |
| Evidence | The results have been outstanding. We are developing new technology products twice as fast as before. And, we are attracting and retaining excellent engineers because of the way we empower our development teams to innovate. |
This product development executive is positioning herself as a leader in innovation with evidence that backs up her words. Whether you differentiate yourself in diversity, innovation or another domain, you can use this one-word or one-concept association as a sort of brand shorthand that people can remember.
How do you use your elevator pitch at networking events? It’s important to be yourself and to use your own words that sound natural. Remember that a conversation should not be an opportunity for you to talk nonstop about yourself. A two-way conversation will engage others and will still afford you opportunities to weave in your key messages.


Leaving the country in less than a week, so tonight's a good night to _____. If you said can chicken stock, you belong in our household.
4/25/2014, 8:06:29 PM
Favs: 2
Retweets: 0
link--- layout: tweet ---
Leaving the country in less than a week, so tonight's a good night to _____. If you said can chicken stock, you belong in our household.
4/25/2014, 8:06:29 PM
Favs: 2
Retweets: 0
link


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{%extends "nav_events.html" %} {%block title%}Test scan{%endblock%} {%block content%}
Scanning the below QR code with the badge scanning app should result in a message about the test code being scanned successfully.


(Languages: be de en ru uk)
Test suite for Cascading Style Sheets (CSS) Level 1
Descriptions of all versions of the test suite can be found in Version history.


EBD - Easton Bible DIctionary
Bashan-havoth-jair
BASHAN-HAVOTH-JAIR
"BASHAN-HAVOTH-JAIR "the Bashan of the villages of Jair, the general name given to Argob by Jair, the son of Manasseh (
Deuteronomy 3:14
), containing sixty cities with walls and brazen gates (
Joshua 13:30
;
1 Kings 4:13
). (See ARGOB.)
"BASHAN-HAVOTH-JAIR "the Bashan of the villages of Jair, the general name given to Argob by Jair, the son of Manasseh (Deuteronomy 3:14), containing sixty cities with walls and brazen gates (Joshua 13:30; 1 Kings 4:13). (See ARGOB.)


Toggle navigation
Pravin Kumar Rana
Publications
Projects
Teaching
Resume
Photography
Teaching.
Teaching assistant
, KTH Royal Institute of Technology, Stockholm, Sweden
Image and video processing,
(2011 - 2014).
Project course on multimedia signal processing,
(2010 - 2014).
Information theory and source coding,
(2009, 2012).
Degree project in electrical engineering,
(first level, 2010).
Lecturer
, Government Polytechnic, Koderma, India
Physics,
(2005 - 2006).


STINGEZE MAX INSECT BITE RELIEF- benzocaine, phenol and camphor (synthetic) liquid
Wisconsin Pharmacal Company
Disclaimer: Most OTC drugs are not reviewed and approved by FDA, however they may be marketed if they comply with applicable regulations and policies. FDA has not evaluated whether this product complies.
Drug Facts
Active Ingredients
Benzocaine 10%
Phenol 1.35%
Camphor 3%
Purpose
Analgesic, Anesthetic, Antipuritic
First Aid Antiseptic
External Analgesic
Uses
First aid to help prevent infection in minor cuts, scrapes, and burns.
Warnings
For external use only.
When using this product
- Do not get in eyes
- Do not apply over large areas of the body
- In case of deep or puncture wounds, animal bites, or serious burns consult a doctor
- Do not bandage.
Stop use and ask doctor if
condition worsens, or symptoms persist for more than 7 days or clear up and occur again within a few days. Do not use longer than one week unless directed by a doctor.
Keep out of reach of children.
If swallowed, get medical help or contact a poison control center right away. If in eyes, flush with water for 15 minutes and call a physician.
Directions
- Clean area
- Apply a small amount to the bite area while massaging with sponge tip applicator. If itching persists, apply again in 10-15 minutes
- For ticks and bees, remove tick or stinger before treatment
- Adults and children 2 years and over: Apply to affected area 1 to 3 times daily
- Children under 2 years: Consult a doctor
Inactive Ingredients
Camphor, Menthyl lactate, Propylene Glycol, SD Alcohol 40B 20%, Water
Questions or Comments?
1-800-558-6614
Enter section text here
Enter section text here


Fades and Volume Adjustments
Fission can fade audio in and out, normalize an entire file, and adjust the gain of a portion of audio.
Fading In or Out
To fade audio, start by selecting the audio you wish to fade. Once a selection is made, click the Fade In or Fade Out buttons to fade the audio across the entire selection.
Fission's Fade Buttons
As well, with the Fade Around Removed Audio option turned on in the Clip menu, you can set Fission to automatically fade around areas where audio has been removed. The duration of these fades can be adjusted in the Preferences window.
Normalizing Audio
Fission's Normalize Button
Normalize increases the gain of the selected audio, so that the loudest sample is at set to the maximum possible value. This makes the selection as loud as possible without causing distortion. To normalize a selection of audio, just highlight the desired audio then click the Normalize button.
Gain Adjustment
Fission's Gain Adjustment Slider
You'll see the Gain Adjustment button at the bottom of any selection. Clicking and holding the button will bring up the Gain Adjustment slider. Just slide up or down to adjust the gain of the selection.


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Copyright © Harbor All Rights Reserved.


|
Ubiquity
2.1.4
php rapid development framework
|
Public Member Functions | |
| __construct ($controller="", $action="", $parameters=[], $dValues=[], $annots=[]) | |
| getController () | |
| setController ($controller) | |
| getAction () | |
| setAction ($action) | |
| getParameters () | |
| setParameters ($parameters) | |
| getDValues () | |
| setDValues ($dValues) | |
| getAnnots () | |
| setAnnots ($annots) | |
| getPath () | |
| getId () | |
Static Public Member Functions | |
| static | initWithPath ($url) |
| static | init () |
Static Public Attributes | |
| static | $controllers = [ ] |
Static Private Member Functions | |
| static | scanMethod ($controllerClass, \ReflectionMethod $method) |
Private Attributes | |
| $controller | |
| $action | |
| $parameters | |
| $dValues | |
| $annots | |
Static Private Attributes | |
| static | $excludeds = [ "__construct","isValid","initialize","finalize","onInvalidControl","loadView","forward","redirectToRoute","getView","message","loadDefaultView","getDefaultViewName","showSimpleMessage","showConfMessage" ] |
Definition at line 13 of file ControllerAction.php.
| __construct | ( | $controller = "" , |
|
$action = "" , |
|||
$parameters = [] , |
|||
$dValues = [] , |
|||
$annots = [] |
|||
| ) |
Definition at line 22 of file ControllerAction.php.
| getAction | ( | ) |
Definition at line 114 of file ControllerAction.php.
| getAnnots | ( | ) |
Definition at line 141 of file ControllerAction.php.
| getController | ( | ) |
Definition at line 105 of file ControllerAction.php.
| getDValues | ( | ) |
Definition at line 132 of file ControllerAction.php.
| getId | ( | ) |
Definition at line 155 of file ControllerAction.php.
| getParameters | ( | ) |
Definition at line 123 of file ControllerAction.php.
| getPath | ( | ) |
Definition at line 150 of file ControllerAction.php.
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static |
Definition at line 58 of file ControllerAction.php.
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static |
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| setParameters | ( | $parameters | ) |
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Unconventional computingSolving Steiner tree problem with water and soap Computing by xeroxing on transparencies ProgrammingFirst C/C++ application in Visual Studio Express 2013 First C/C++ application in Code::Blocks Debugging C/C++ applications in Visual Studio 2013 Debugging a C/C++ application in Code::Blocks Compiling from command line with Microsoft Visual Studio C++ and GCC How bad memory leaks are ? First wxWidgets application on Windows with VC++ Artificial intelligenceOpenCV tutorial: setup and capture from camera example Generating all strings of correct parenthesis with backtracking method Ants discovering the most convenient path |


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INV_POSDEF Invert positive definite matrix. INV_POSDEF(A) is like INV(A) but faster and more numerically stable.
0001 function x = inv_posdef(A) 0002 % INV_POSDEF Invert positive definite matrix. 0003 % INV_POSDEF(A) is like INV(A) but faster and more numerically stable. 0004 0005 U = chol(A); 0006 iU = inv_triu(U); 0007 x = iU*iU';


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on 2012-04-11 15:46:40
If I might —perhaps you should consider adding a few images. I don’t mean to disrespect what you’ve said ; its very enlightening, indeed. However, I think would respond to it more positively if they could be something tangible to your ideas