|
DirectoryExists
|
Checks if a directory exists
|
|
FileExists
|
Checks if a file exists
|
|
ReadFile
|
Reads the entire content of a file into a string
|
|
WriteFile
|
Writes the entire content (at once) of a file
|
|
_chdir
|
The _chdir function changes the current working directory to the directory specified by dirname
|
|
_errno
|
Gets the error for the last I/O operation
|
|
_fileno
|
Gets the file descriptor associated with a stream
|
|
_getenv
|
Get a value from the current environment
|
|
_mkdir
|
Create a new directory
|
|
_putenv
|
Create, modify, or remove environment variables
|
|
_rmdir
|
The _rmdir function deletes the directory specified by directory_path
|
|
_stat
|
Get status information on a file
|
|
_unlink
|
The _unlink function deletes the file specified by filename
|
|
closedir
|
The closedir function closes the named directory stream
|
|
dirname
|
Gets the name of a directory returned by a call to readdir
|
|
exec
|
Loads and executes a new process (independent of the current one)
|
|
fclose
|
Closes a file opened with fopen
|
|
feof
|
The feof function tests for end-of-file on a stream
|
|
fflush
|
The fflush function flushes a stream associated with file descriptor fd
|
|
fgetc
|
fgetc reads a single character from the current position of a file associated with fd
|
|
fgets
|
The fgets function reads a string from the input fd argument and stores it in buffer
|
|
fgetstring
|
fgetstring reads one item from the input file, fd, formed by the string separator, with maximum size max_size
|
|
filegid
|
Gets the group id of the owner of a file
|
|
filelast_acc
|
Gets the last access time of a file
|
|
filelast_ch
|
Gets the last changed date/time of a file
|
|
filelast_mod
|
Gets the last modification date/time of a file
|
|
filesize
|
Returns the file length, in bytes, of the target file
|
|
filetype
|
Gets the type of a file
|
|
fileuid
|
Gets the used id of the owner of a file
|
|
fopen
|
The fopen function opens the file specified by filename
|
|
fputc
|
fputc writes the single character ch to a file at the position indicated by the associated file position indicator (if defined) and advances the indicator as appropriate; the file is associated with fd
|
|
fputs
|
fputs copies buffer to the output stream fd at the current position, without the terminating null character
|
|
fread
|
The fread function reads up to count items of size bytes from the input file and stores them in buffer
|
|
freopen
|
The freopen function closes the file currently associated with fd and reassigns fd to the file specified by path
|
|
fseek
|
The fseek function moves the file pointer (if any) associated with fd to a new location that is offset bytes from origin
|
|
fsize
|
Gets the file length, in bytes, of the target file
|
|
ftell
|
The ftell function gets the current position of the file pointer (if any) associated with the file descriptor
|
|
fwrite
|
The fwrite function writes up to count items, of size length each, from buffer to the output file
|
|
opendir
|
The opendir() function opens the directory named by filename, associates a directory stream with it and returns a pointer to be used to identify the directory stream in subsequent operations
|
|
readdir
|
The readdir function returns an identifier to the next directory entry
|
|
remove
|
The remove function deletes the file or directory specified by path
|
|
rewinddir
|
The rewinddir() function resets the position of the named directory stream to the beginning of the directory
|
|
seekdir
|
The seekdir() function sets the position of the next readdir operation on the directory stream
|
|
telldir
|
The telldir function returns the current location associated with the named directory stream
|


After pressing the button 'Start' the list field on the right side
('select files') shows the content of the directory whose path is saved
in Fabric.ini. If this field is empty and
the message 'no file found' appears, the data path can be changed after
pressing the button 'find data path'.
Click the files you want to use. These files appear in the middle field
('selected files'). Files can be removed from this list by clicking on
them.
The extension
of the files and the path chosen appear under the left list.
The button 'plot' opens the plot form. the data of the used files
appear in the left field.


I do not collect any data from How To Tennis however it was created with Unity which does collect user data. The game does use Unity ads which may collect data. Check out Unity's privacy policy here:


Basic Icons
favorite
home
menu
code
assignment
delete
accessibility
backup
autorenew
bookmark
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event
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https
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account_balance
account_balance_wallet
account_box
account_circle
add_shopping_cart
alarm
alarm_add
alarm_off
alarm_on
all_out
android
bookmark
announcement
aspect_ratio
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bug_report
cached
compare_arrows
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find_replace
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gif
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http
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thumb_down
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translate
trending_down
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Analyses PhpDoc blocks for using object as type hints.
Refactoring this will keep code analysis simple and contribute to overall better structure.


Package org.drip.learning.rxtor1
Interface EmpiricalLearningMetricEstimator
- All Known Implementing Classes:
ApproximateLipschitzLossLearner
,GeneralizedLearner
,L1LossLearner
,LipschitzLossLearner
,LpLossLearner
public interface EmpiricalLearningMetricEstimator
EmpiricalLearningMetricEstimator is the Estimator of the Empirical Loss and Risk, as well as the
corresponding Covering Numbers.
The References are:
The References are:
- Alon, N., S. Ben-David, N. Cesa Bianchi, and D. Haussler (1997): Scale-sensitive Dimensions, Uniform Convergence, and Learnability Journal of Association of Computational Machinery 44 (4) 615-631
- Anthony, M., and P. L. Bartlett (1999): Artificial Neural Network Learning - Theoretical Foundations Cambridge University Press Cambridge, UK
- Kearns, M. J., R. E. Schapire, and L. M. Sellie (1994): Towards Efficient Agnostic Learning Machine Learning 17 (2) 115-141
- Lee, W. S., P. L. Bartlett, and R. C. Williamson (1998): The Importance of Convexity in Learning with Squared Loss IEEE Transactions on Information Theory 44 1974-1980
- Vapnik, V. N. (1998): Statistical learning Theory Wiley New York
- Module = Computational Core Module
- Library = Statistical Learning
- Project = Agnostic Learning Bounds under Empirical Loss Minimization Schemes
- Package = Statistical Learning Empirical Loss Penalizer
- Author:
- Lakshmi Krishnamurthy
-
Method Summary
Modifier and Type Method Description double
empiricalLoss(R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Empirical Sample Lossdouble
empiricalLoss(RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Empirical Sample Lossdouble
empiricalRisk(R1R1 distR1R1, R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Empirical Sample Riskdouble
empiricalRisk(RdR1 distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Empirical Sample RiskNormedRxToNormedR1Finite
functionClass()
Retrieve the Underlying Learner Function Classdouble
lossSampleCoveringNumber(GeneralizedValidatedVector gvvi, double dblEpsilon, boolean bSupremum)
Retrieve the Loss Class Sample Covering Number - L-Infinity or L-p based Baseddouble
regularizedLoss(R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Regularized Sample Loss (Empirical + Structural)double
regularizedLoss(RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Regularized Sample Loss (Empirical + Structural)double
regularizedRisk(R1R1 distR1R1, R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Regularized Sample Risk (Empirical + Structural)double
regularizedRisk(RdR1 distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Regularized Sample Risk (Empirical + Structural)RegularizationFunction
regularizerFunction()
Retrieve the Regularizer Functiondouble
structuralLoss(R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvvi)
Compute the Structural Sample Lossdouble
structuralLoss(RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvvi)
Compute the Structural Sample Lossdouble
structuralRisk(R1R1 distR1R1, R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Structural Sample Riskdouble
structuralRisk(RdR1 distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Structural Sample RiskEmpiricalPenaltySupremum
supremumEmpiricalLoss(GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Supremum Empirical Sample LossEmpiricalPenaltySupremum
supremumEmpiricalRisk(R1R1 distR1R1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Supremum Empirical Sample RiskEmpiricalPenaltySupremum
supremumEmpiricalRisk(RdR1 distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Supremum Empirical Sample RiskEmpiricalPenaltySupremum
supremumRegularizedLoss(GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Supremum Regularized Sample LossEmpiricalPenaltySupremum
supremumRegularizedRisk(R1R1 distR1R1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Supremum Regularized Sample RiskEmpiricalPenaltySupremum
supremumRegularizedRisk(RdR1 distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Supremum Regularized Sample RiskEmpiricalPenaltySupremum
supremumStructuralLoss(GeneralizedValidatedVector gvviX)
Compute the Supremum Structural Sample LossEmpiricalPenaltySupremum
supremumStructuralRisk(R1R1 distR1R1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Supremum Structural Sample RiskEmpiricalPenaltySupremum
supremumStructuralRisk(RdR1 distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY)
Compute the Supremum Structural Sample Risk
-
Method Details
-
functionClass
NormedRxToNormedR1Finite functionClass()Retrieve the Underlying Learner Function Class- Returns:
- The Underlying Learner Function Class
-
regularizerFunction
RegularizationFunction regularizerFunction()Retrieve the Regularizer Function- Returns:
- The Regularizer Function
-
lossSampleCoveringNumber
double lossSampleCoveringNumber(GeneralizedValidatedVector gvvi, double dblEpsilon, boolean bSupremum) throws java.lang.ExceptionRetrieve the Loss Class Sample Covering Number - L-Infinity or L-p based Based- Parameters:
gvvi
- The Validated Instance Vector SequencedblEpsilon
- The Deviation of the Empirical Mean from the Population MeanbSupremum
- TRUE To Use the Supremum Metric in place of the Built-in Metric- Returns:
- The Loss Class Sample Covering Number - L-Infinity or L-p based Based
- Throws:
java.lang.Exception
- Thrown if the Inputs are Invalid
-
empiricalLoss
double empiricalLoss(R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Empirical Sample Loss- Parameters:
funcLearnerR1ToR1
- The R^1 To R^1 Learner FunctiongvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Empirical Loss
- Throws:
java.lang.Exception
- Thrown if the Empirical Loss cannot be computed
-
empiricalLoss
double empiricalLoss(RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Empirical Sample Loss- Parameters:
funcLearnerRdToR1
- The R^d To R^1 Learner FunctiongvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Empirical Loss
- Throws:
java.lang.Exception
- Thrown if the Empirical Loss cannot be computed
-
supremumEmpiricalLoss
EmpiricalPenaltySupremum supremumEmpiricalLoss(GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Supremum Empirical Sample Loss- Parameters:
gvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Supremum Empirical Sample Loss
- Throws:
java.lang.Exception
- Thrown if the Supremum Empirical Sample Loss cannot be computed
-
structuralLoss
double structuralLoss(R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvvi) throws java.lang.ExceptionCompute the Structural Sample Loss- Parameters:
funcLearnerR1ToR1
- The R^1 To R^1 Learner Functiongvvi
- The Validated Predictor Instance- Returns:
- The Structural Loss
- Throws:
java.lang.Exception
- Thrown if the Structural Loss cannot be computed
-
structuralLoss
double structuralLoss(RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvvi) throws java.lang.ExceptionCompute the Structural Sample Loss- Parameters:
funcLearnerRdToR1
- The R^d To R^1 Learner Functiongvvi
- The Validated Predictor Instance- Returns:
- The Structural Loss
- Throws:
java.lang.Exception
- Thrown if the Structural Loss cannot be computed
-
supremumStructuralLoss
EmpiricalPenaltySupremum supremumStructuralLoss(GeneralizedValidatedVector gvviX) throws java.lang.ExceptionCompute the Supremum Structural Sample Loss- Parameters:
gvviX
- The Validated Predictor Instance- Returns:
- The Supremum Structural Sample Loss
- Throws:
java.lang.Exception
- Thrown if the Supremum Structural Sample Loss cannot be computed
-
regularizedLoss
double regularizedLoss(R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Regularized Sample Loss (Empirical + Structural)- Parameters:
funcLearnerR1ToR1
- The R^1 To R^1 Learner FunctiongvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Regularized Loss
- Throws:
java.lang.Exception
- Thrown if the Regularized Loss cannot be computed
-
regularizedLoss
double regularizedLoss(RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Regularized Sample Loss (Empirical + Structural)- Parameters:
funcLearnerRdToR1
- The R^d To R^1 Learner FunctiongvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Regularized Loss
- Throws:
java.lang.Exception
- Thrown if the Regularized Loss cannot be computed
-
supremumRegularizedLoss
EmpiricalPenaltySupremum supremumRegularizedLoss(GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Supremum Regularized Sample Loss- Parameters:
gvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Supremum Regularized Sample Loss
- Throws:
java.lang.Exception
- Thrown if the Supremum Regularized Sample Loss cannot be computed
-
empiricalRisk
double empiricalRisk(R1R1 distR1R1, R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Empirical Sample Risk- Parameters:
distR1R1
- R^1 R^1 Multivariate MeasurefuncLearnerR1ToR1
- The R^1 To R^1 Learner FunctiongvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Empirical Sample Risk
- Throws:
java.lang.Exception
- Thrown if the Empirical Sample Risk cannot be computed
-
empiricalRisk
double empiricalRisk(RdR1 distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Empirical Sample Risk- Parameters:
distRdR1
- R^d R^1 Multivariate MeasurefuncLearnerRdToR1
- The R^d To R^1 Learner FunctiongvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Empirical Sample Risk
- Throws:
java.lang.Exception
- Thrown if the Empirical Sample Risk cannot be computed
-
supremumEmpiricalRisk
EmpiricalPenaltySupremum supremumEmpiricalRisk(R1R1 distR1R1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Supremum Empirical Sample Risk- Parameters:
distR1R1
- R^1 R^1 Multivariate MeasuregvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Supremum Empirical Sample Loss
- Throws:
java.lang.Exception
- Thrown if the Supremum Empirical Sample Loss cannot be computed
-
supremumEmpiricalRisk
EmpiricalPenaltySupremum supremumEmpiricalRisk(RdR1 distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Supremum Empirical Sample Risk- Parameters:
distRdR1
- R^d R^1 Multivariate MeasuregvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Supremum Empirical Sample Loss
- Throws:
java.lang.Exception
- Thrown if the Supremum Empirical Sample Loss cannot be computed
-
structuralRisk
double structuralRisk(R1R1 distR1R1, R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Structural Sample Risk- Parameters:
distR1R1
- R^1 R^1 Multivariate MeasurefuncLearnerR1ToR1
- The R^1 To R^1 Learner FunctiongvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Structural Risk
- Throws:
java.lang.Exception
- Thrown if the Structural Risk cannot be computed
-
structuralRisk
double structuralRisk(RdR1 distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Structural Sample Risk- Parameters:
distRdR1
- R^d R^1 Multivariate MeasurefuncLearnerRdToR1
- The R^d To R^1 Learner FunctiongvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Structural Risk
- Throws:
java.lang.Exception
- Thrown if the Structural Risk cannot be computed
-
supremumStructuralRisk
EmpiricalPenaltySupremum supremumStructuralRisk(R1R1 distR1R1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Supremum Structural Sample Risk- Parameters:
distR1R1
- R^1 R^1 Multivariate MeasuregvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Supremum Structural Sample Loss
- Throws:
java.lang.Exception
- Thrown if the Supremum Structural Sample Risk cannot be computed
-
supremumStructuralRisk
EmpiricalPenaltySupremum supremumStructuralRisk(RdR1 distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Supremum Structural Sample Risk- Parameters:
distRdR1
- R^d R^1 Multivariate MeasuregvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Supremum Structural Sample Risk
- Throws:
java.lang.Exception
- Thrown if the Supremum Structural Sample Risk cannot be computed
-
regularizedRisk
double regularizedRisk(R1R1 distR1R1, R1ToR1 funcLearnerR1ToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Regularized Sample Risk (Empirical + Structural)- Parameters:
distR1R1
- R^1 R^1 Multivariate MeasurefuncLearnerR1ToR1
- The R^1 To R^1 Learner FunctiongvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Regularized Sample Risk
- Throws:
java.lang.Exception
- Thrown if the Regularized Sample Risk cannot be computed
-
regularizedRisk
double regularizedRisk(RdR1 distRdR1, RdToR1 funcLearnerRdToR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Regularized Sample Risk (Empirical + Structural)- Parameters:
distRdR1
- R^d R^1 Multivariate MeasurefuncLearnerRdToR1
- The R^d To R^1 Learner FunctiongvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Regularized Sample Risk
- Throws:
java.lang.Exception
- Thrown if the Regularized Sample Risk cannot be computed
-
supremumRegularizedRisk
EmpiricalPenaltySupremum supremumRegularizedRisk(R1R1 distR1R1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Supremum Regularized Sample Risk- Parameters:
distR1R1
- R^1 R^1 Multivariate MeasuregvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Supremum Regularized Sample Risk
- Throws:
java.lang.Exception
- Thrown if the Supremum Regularized Sample Risk cannot be computed
-
supremumRegularizedRisk
EmpiricalPenaltySupremum supremumRegularizedRisk(RdR1 distRdR1, GeneralizedValidatedVector gvviX, GeneralizedValidatedVector gvviY) throws java.lang.ExceptionCompute the Supremum Regularized Sample Risk- Parameters:
distRdR1
- R^d R^1 Multivariate MeasuregvviX
- The Validated Predictor InstancegvviY
- The Validated Response Instance- Returns:
- The Supremum Regularized Sample Risk
- Throws:
java.lang.Exception
- Thrown if the Supremum Regularized Sample Risk cannot be computed
-


{% load i18n %}
{{ challenge.description }}
{% if challenge.private and challenge.user == request.user %}This challenge is accepted! Unaccept it, this is a mistake!
{% else %}This challenge isn't accepted yet! Accept it, we can pull this off!
{% endif %}Requested by user: {{ challenge.user }}
{% endif %}


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represents a application with L4/L7 classification
a unique 2 byte id generated when a application is created and used by VRS for probing.
SDK attribute: appId
associated Layer7 Application Type ID
Format: free
Max length: 255
SDK attribute: associatedL7ApplicationSignatureID
Minimum Failover Bandwidth of the application.
SDK attribute: bandwidth
Describes the certificate common name
Default value: *
Format: free
Max length: 255
SDK attribute: certificateCommonName
Time stamp when this object was created.
SDK attribute: creationDate
description of Application
Format: free
Max length: 255
SDK attribute: description
destination IP in CIDR format
Format: cidr
SDK attribute: destinationIP
value should be either * or single port number or maximum 5 ranges comma separated.
Format: free
Max length: 59
SDK attribute: destinationPort
DSCP match condition to be set in the rule. It is either * or from 0-63.
Format: free
SDK attribute: DSCP
Metadata objects associated with this entity. This will contain a list of Metadata objects if the API request is made using the special flag to enable the embedded Metadata feature. Only a maximum of Metadata objects is returned based on the value set in the system configuration.
SDK attribute: embeddedMetadata
Enable the performance probe for this application
Default value: false
SDK attribute: enablePPS
Specify if scope of entity is Data center or Enterprise level
Allowed values: ENTERPRISE, GLOBAL
SDK attribute: entityScope
Ether type of the packet to be matched. etherType can be * or a valid hexadecimal value
SDK attribute: etherType
External object ID. Used for integration with third party systems
Format: free
SDK attribute: externalID
ID of the user who last updated the object.
Format: free
SDK attribute: lastUpdatedBy
Time stamp when this object was last updated.
SDK attribute: lastUpdatedDate
name of the application
Format: free
Min length: 1
Max length: 255
SDK attribute: name
Network symmetry flag
Default value: false
Format: free
SDK attribute: networkSymmetry
one way Delay
Max value: 9999
SDK attribute: oneWayDelay
one way Jitter
Max value: 9999
SDK attribute: oneWayJitter
one way loss
SDK attribute: oneWayLoss
with values being Latency, Jitter, PacketLoss
Allowed values: JITTER, LATENCY, PACKETLOSS
SDK attribute: optimizePathSelection
Identifies the user that has created this object.
Format: free
SDK attribute: owner
Describes the trigger for the application.
Allowed values: CONTINUOUS, FIRST_PACKET, FIRST_PACKET_AND_CONTINUOUS
Default value: FIRST_PACKET
SDK attribute: performanceMonitorType
default set to any , possible values primary/secondary/any
Allowed values: ANY, PRIMARY, SECONDARY
Default value: ANY
SDK attribute: postClassificationPath
default set to primary , possible values primary/secondary
Allowed values: DEFAULT, PRIMARY, SECONDARY
Default value: DEFAULT
SDK attribute: preClassificationPath
Protocol number that must be matched
Allowed values: NONE, TCP, UDP
Default value: NONE
SDK attribute: protocol
determines whether this entity is read only. Read only objects cannot be modified or deleted.
Default value: false
SDK attribute: readOnly
source IP address
Format: free
SDK attribute: sourceIP
source Port ,value should be either * or single port number or maximum 5 ranges comma separated.
Format: free
Max length: 59
SDK attribute: sourcePort
Maintain path symmetry during SLA violation
Default value: false
SDK attribute: symmetry


CHAPTER 360
PROVISIONS APPLICABLE TO PUBLIC
HOUSING GENERALLY
REPEALED. L 1997, c 350, §18.
Cross References
For present provisions, see chapter 356D.


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Welcome to GSEAPY’s documentation!¶
GSEAPY: Gene Set Enrichment Analysis in Python.
GSEAPY is a python wrapper for GESA and Enrichr.¶
It’s used for convenient GO enrichments and produce publishable quality figures from python.
GSEAPY could be used for RNA-seq, ChIP-seq, Microarry data.
Gene Set Enrichment Analysis (GSEA) is a computational method that determines whether an a priori defined set of genes shows statistically significant, concordant differences between two biological states (e.g. phenotypes).
The full GSEA
is far too extensive to describe here; see
GSEA documentation for more information.
Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr .
- Welcome to GSEAPY’s documentation!
- How to Use GSEAPY
- A Protocol to Prepare files for GSEAPY
- GSEAPY Example
- 1. Load essential packages
- See all gseapy supported enrichr library names
- 2. Enrichr Example
- ii . Commandline usage
- 3. Prerank example
- ii . Commandline usage
- 4. Call Example
- ii . Commandline usage


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. to one of the below LabCorp locations. After you you have the blood drawn at one of the LabCorp locations below we email the results within 24-48 hours.
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|
NUC472_NUC442_BSP V3.03.004
The Board Support Package for NUC472/NUC442
|
Macros | |
| #define | CAP_IS_STOPPED() |
| Is CAP module Enable. More... | |
| #define | CAP_CLR_INT_FLAG(u32IntMask) |
| Clear CAP flag. More... | |
| #define | CAP_GET_INT_STS() |
| Get CAP Interrupt status. More... | |
Functions | |
| void | CAP_Open (uint32_t u32InFormat, uint32_t u32OutFormet) |
| Open engine clock and sensor clock. More... | |
| void | CAP_SetCroppingWindow (uint32_t u32VStart, uint32_t u32HStart, uint32_t u32Height, uint32_t u32Width) |
| Set Cropping Window Starting Address and Size. More... | |
| void | CAP_SetPacketBuf (uint32_t u32Address) |
| Set System Memory Packet Base Address0 Register. More... | |
| void | CAP_SetPlanarBuf (uint32_t u32YAddr, uint32_t u32UAddr, uint32_t u32VAddr) |
| Set System Memory Planar Y, U and V Base Address Registers. More... | |
| void | CAP_Close (void) |
| Close Image Capture Interface. More... | |
| void | CAP_EnableInt (uint32_t u32IntMask) |
| Set CAP Interrupt. More... | |
| void | CAP_DisableInt (uint32_t u32IntMask) |
| Disable CAP Interrupt. More... | |
| void | CAP_Start (void) |
| Start Image Capture Interface. More... | |
| void | CAP_Stop (uint32_t u32FrameComplete) |
| Stop Image Capture Interface. More... | |
| void | CAP_SetPacketScaling (uint32_t u32VNumerator, uint32_t u32VDenominator, uint32_t u32HNumerator, uint32_t u32HDenominator) |
| Set Packet Scaling Vertical and Horizontal Factor Register. More... | |
| void | CAP_SetPlanarScaling (uint32_t u32VNumerator, uint32_t u32VDenominator, uint32_t u32HNumerator, uint32_t u32HDenominator) |
| Set Planar Scaling Vertical and Horizontal Factor Register. More... | |
| void | CAP_SetPacketStride (uint32_t u32Stride) |
| Set Packet Frame Output Pixel Stride Width. More... | |
| void | CAP_SetPlanarStride (uint32_t u32Stride) |
| Set Planar Frame Output Pixel Stride Width. More... | |
| void | CAP_EnableMotionDet (uint32_t u32Freq, uint32_t u32BlockSize, uint32_t u32Format, uint32_t u32Threshold, uint32_t u32YDetAddr, uint32_t u32DetAddr) |
| Enable Motion Detection Function. More... | |
| void | CAP_DisableMotionDet (void) |
| Enable Motion Detection Function. More... | |
| #define CAP_CLR_INT_FLAG | ( | u32IntMask | ) |
Clear CAP flag.
| [in] | u32IntMask | interrupt flags settings. It could be |
Clear Image Capture Interface interrupt flag
| #define CAP_GET_INT_STS | ( | ) |
Get CAP Interrupt status.
Get Image Capture Interface interrupt status.
| #define CAP_IS_STOPPED | ( | ) |
Is CAP module Enable.
Check Image Capture Interface module Enable or Disable
| void CAP_Close | ( | void | ) |
| void CAP_DisableInt | ( | uint32_t | u32IntMask | ) |
Disable CAP Interrupt.
| [in] | u32IntMask | Interrupt settings. It could be |
Disable Video Frame End Interrupt , System Memory Error Interrupt , Address Match Interrupt and Motion Detection Output Finish Interrupt .
| void CAP_DisableMotionDet | ( | void | ) |
| void CAP_EnableInt | ( | uint32_t | u32IntMask | ) |
Set CAP Interrupt.
| [in] | u32IntMask | Interrupt settings. It could be |
Set Video Frame End Interrupt Enable, System Memory Error Interrupt Enable, Address Match Interrupt Enable, Motion Detection Output Finish Interrupt Enable.
| void CAP_EnableMotionDet | ( | uint32_t | u32Freq, |
| uint32_t | u32BlockSize, | ||
| uint32_t | u32Format, | ||
| uint32_t | u32Threshold, | ||
| uint32_t | u32YDetAddr, | ||
| uint32_t | u32DetAddr | ||
| ) |
Enable Motion Detection Function.
| [in] | u32Freq | Motion Detection Detect Frequency. It should be 0x0 ~ 0x3. |
| [in] | u32BlockSize | Motion Detection Block Size FALSE : 16x16 TRUE : 8x8 |
| [in] | u32Format | Motion Detection Save Mode FALSE : 1 bit DIFF + 7 Y Differential TRUE : 1 bit DIFF only |
| [in] | u32Threshold | Motion Detection Detect Threshold. It should be 0x0 ~ 0x1F. |
| [in] | u32YDetAddr | : Motion Detection Detect Temp Y Output Address |
| [in] | u32DetAddr | Motion Detection Detect Address |
Set Planar Frame Output Pixel Stride Width
| void CAP_Open | ( | uint32_t | u32InFormat, |
| uint32_t | u32OutFormet | ||
| ) |
Open engine clock and sensor clock.
| [in] | u32InFormat | The bits corresponding VSP, HSP, PCLK, INFMT, SNRTYPE, OUTFMT, PDORD and PNFMT configurations.
|
| [in] | u32OutFormet | Capture output format, should be one of following setting |
Initialize the Image Capture Interface. Register a call back for driver internal using
| void CAP_SetCroppingWindow | ( | uint32_t | u32VStart, |
| uint32_t | u32HStart, | ||
| uint32_t | u32Height, | ||
| uint32_t | u32Width | ||
| ) |
Set Cropping Window Starting Address and Size.
| [in] | u32VStart | Cropping Window Vertical Starting Address. It should be 0 ~ 0x7FF. |
| [in] | u32HStart | Cropping Window Horizontal Starting Address. It should be 0 ~ 0x7FF. |
| [in] | u32Height | Cropping Window Height . It should be 0 ~ 0x7FF. |
| [in] | u32Width | Cropping Window Width. It should be 0 ~ 0x7FF. |
Set Cropping Window Starting Address Register
| void CAP_SetPacketBuf | ( | uint32_t | u32Address | ) |
| void CAP_SetPacketScaling | ( | uint32_t | u32VNumerator, |
| uint32_t | u32VDenominator, | ||
| uint32_t | u32HNumerator, | ||
| uint32_t | u32HDenominator | ||
| ) |
Set Packet Scaling Vertical and Horizontal Factor Register.
| [in] | u32VNumerator | Packet Scaling Vertical Factor N. It should be 0 ~ FFFF. |
| [in] | u32VDenominator | Packet Scaling Vertical Factor M. It should be 0 ~ FFFF. |
| [in] | u32HNumerator | Packet Scaling Vertical Factor N. It should be 0 ~ FFFF. |
| [in] | u32HDenominator | Packet Scaling Vertical Factor M. It should be 0 ~ FFFF. |
| void CAP_SetPacketStride | ( | uint32_t | u32Stride | ) |
| void CAP_SetPlanarBuf | ( | uint32_t | u32YAddr, |
| uint32_t | u32UAddr, | ||
| uint32_t | u32VAddr | ||
| ) |
Set System Memory Planar Y, U and V Base Address Registers.
| [in] | u32YAddr | : set YBA register, It should be 0x0 ~ 0xFFFFFFFF |
| [in] | u32UAddr | : set UBA register, It should be 0x0 ~ 0xFFFFFFFF |
| [in] | u32VAddr | : set VBA register, It should be 0x0 ~ 0xFFFFFFFF |
Set System Memory Planar Y,U and V Base Address Registers
| void CAP_SetPlanarScaling | ( | uint32_t | u32VNumerator, |
| uint32_t | u32VDenominator, | ||
| uint32_t | u32HNumerator, | ||
| uint32_t | u32HDenominator | ||
| ) |
Set Planar Scaling Vertical and Horizontal Factor Register.
| [in] | u32VNumerator | Planar Scaling Vertical Factor N. It should be 0 ~ FFFF. |
| [in] | u32VDenominator | Planar Scaling Vertical Factor M. It should be 0 ~ FFFF. |
| [in] | u32HNumerator | Planar Scaling Vertical Factor N. It should be 0 ~ FFFF. |
| [in] | u32HDenominator | Planar Scaling Vertical Factor M. It should be 0 ~ FFFF. |
| void CAP_SetPlanarStride | ( | uint32_t | u32Stride | ) |
| void CAP_Start | ( | void | ) |
| void CAP_Stop | ( | uint32_t | u32FrameComplete | ) |
Stop Image Capture Interface.
| [in] | u32FrameComplete | : TRUE: Capture module automatically disable the CAP module after a frame had been captured FALSE: Stop Capture module now |
if u32FrameComplete is set to TRUE then get a new frame and disable CAP module


API Reference¶
The deepclaw library API consists of following parts:
-
Hardware Driver API
-
Arm
-
Hand
-
Camera
-
-
Modules Pool API
-
Segmentation
-
Recognition
-
Grasp Planning
-
Motion Planning
-
-
utils API
Hardware Driver API¶
The Hardware Driver API is used for controling the Hardware.
Arm¶
UR10e¶
class deepclaw.driver.arms.UR10eController(robot_configuration_file_path)
-
parameters[in]: robot_configuration_file_path, the robot configuration file, and the file format is yaml.
-
return: an instance of UR10e controller class
Methods
go_home()
Description: move to pre-defined joints, the home joints is defined in robot configuration file.
move_j(joints_angle, velocity=None, acceleration=None, solution_space='Joint')
Description: go to the target joints positions
param[in]:
- joints_angle: target joint positions of each joints [rad];
- velocity: joint acceleration of leading axis [rad/s];
- accelerate: joint speed of leading axis [rad/s^2];
- solution_space: move style, 'Joint' means it linear in joint-space(inverse kinematics is used to calculate the corresponding joints), and 'Space' means linear in tool-space
return: bool, reaching target or not
move_p(position, velocity=None, acceleration=None,solution_space='Joint')
Description: go to the target pose(Rotation vector)
param[in]:
- position: target pose;
- velocity: joint acceleration of leading axis [rad/s^2];
- accelerate: joint speed of leading axis [rad/s];
- solution_space: move style, 'Joint' means it linear in joint-space,and 'Space' means linear in tool-space(forward kinematics is used to calculate the corresponding pose)
return: bool, reaching target or not
get_state()
Description: get robot state
return: dictionary, the whole states of the UR10e
verify_state(variable_name, target_value, error=0.0001, time_out=10)
Description: verify the robot reaching the target pose(joint or cartesian) or not
param[in]:
- variable_name: target style, joints('q_actual') or cartesian('tool_vector_actual');
- target_value: target values;
- error: threshold,if the difference between current state and target state is small than threshold, we say the robot reached the target;
- time_out: Max time of the motion, [second]
return: bool, reaching target or not
Hand¶
HandE¶
class deepclaw.driver.grippers.handE_controller.HandEController(robot_ip = "<IP_ADDRESS>",port = 30003)
-
parameters[in]: robot_ip, the UR ip which the gripper mounted on; port, the UR ip.
-
return: an instance of gripper controller class
Methods
close_gripper()
Description: close the gripper.
open_gripper()
Description: open the gripper.
Camera¶
Realsense D435¶
class deepclaw.driver.sensors.cameras.Realsense(camera_configuration_file_path)
-
parameters[in]: camera_configuration_file_path, the camera configuration file, and the file format is yaml.
-
return: an instance of camera controller class
Methods
get_frame()
Description: get images from a camera.
return: a tuple, includes color image, depth image, point cloud, and infrared images.
get_intrinsics()
Description: get intrinsics attributes of a camera.
return: a tuple, intrinsics parameters of the camera
Modules Pool API¶
Calibration¶
deepclaw.modules.calibration.EyeOnBase.Calibration¶
class deepclaw.modules.calibration.EyeOnBase.Calibration(arm, camera, configuration_file)
Parameters
- arm
- camera
- configuration_file
Methods
- run(self): Calibrate robot arm and camera
End-to-End¶
deepclaw.modules.end2end.effecientdet.efficientdet_predictor.efficientdet¶
class deepclaw.modules.end2end.effecientdet.efficientdet_predictor.efficientdet(compound_coef=0, weight_path=None, num_classes=204)
Parameters
- compound_coef
- weight_path
- num_classes
Methods
Segmentation¶
deepclaw.modules.segmentation.ContourDetector.ContourDetector¶
class deepclaw.modules.segmentation.ContourDetector.ContourDetector(mode=cv2.RETR_LIST, method=cv2.CHAIN_APPROX_NONE, binary_threshold=127, area_threshold=(80, 200), with_angle=False)
Parameter
- mode
- method
- binary_threshold
- area_threshold
- with_angle
Methods
- run(self, color_image)


The title element defines the title of the document, and is required in all HTML documents. The title element: defines a title in the browser tab provides a title for the page when it is added to favorites displays a title for the page in search engine results


Wellington is capital city of New Zealand
Auckland is the biggest city in New Zealand
Christchurch is garden city in New Zealand


Publishing a blueprint
Notice: Under Development
Reusable, customizable components can be built and shared as blueprints.
Overview
Blueprints are a pattern for developing reusable, customizable configuration. Blueprints are typically published and consumed by different teams.
Because packages can be updated to new versions, blueprint consumers can pull in changes to a blueprint after fetching it.
Example use cases for blueprints
- Languages: Java / Node / Ruby / Python / Golang application
- Frameworks: Spring, Express, Rails, Django
- Platforms: Kubeflow, Spark
- Applications / Stacks:
- Rails Backend + Node Frontend + Prometheus
- Spring Cloud Microservices (discovery-server, config-server, api-gateway, admin-server, hystrix, various backends)
- Infrastructure Stacks: CloudSQL + Pubsub + GKE
# Optional: copy the mysql-kustomize blueprint to follow along
kpt pkg get https://github.com/GoogleContainerTools/kpt.git/package-examples/mysql-kustomize mysql
Factor / denormalize the configuration data
Structuring blueprints into separate publisher and consumer focused pieces provides a clean UX for consumers to modifys the package.
Example: provide separate directories with pieces consumers are expected to edit (replicas) vs publisher implementation (health check command).
As a package publisher, it is important to think about where and how you want to promote customization.
We will use kustomize to structure the package:
- Factoring out a common field value
- Example:
namespace
,commonLabels
,commonAnnotations
- Example:
- Factoring a single resource into multiple files
- Example:
resources
+patches
- Example:
Remote kustomize bases may be used to reference the publisher focused pieces directly from a git repository rather than including them in the package.
One disadvantage of this approach is that it creates a dependency on the remote package being accessible in order to push – if you can’t fetch the remote package, then you can’t push changes.
Example package structure:
$ tree mysql/
mysql/
├── Kptfile
├── README.md
├── instance
│ ├── kustomization.yaml
│ ├── service.yaml
│ └── statefulset.yaml
└── upstream
├── kustomization.yaml
├── service.yaml
└── statefulset.yaml
The upstream
directory acts as a kustomize base to the instance
directory.
Upstream contains things most consumers are unlikely to modify –
e.g. the image (for off the shelf software), health check endpoints, etc.
The instance
directory contains patches with fields populated for things
most consumers are expected to modify – e.g. namespace, cpu, memory,
user, password, etc.
While the package is structured into publisher and consumer focused pieces, it is still possible for the package consumer to modify (via direct edits) or override (via patches) any part of the package.
Factoring is for UX, not for enforcement of specific configuration values.
Commands, Args and Environment Variables
How do you configure applications in a way that can be extended or overridden – how can consumers of a package specify new args, flags, environment variables or configuration files and merge those with those defined by the package publisher?
Notes
- Commands and Args are non-associative arrays so it is not possible to target specific elements – any changes replace the entire list of elements.
- Commands and Args are separate fields that are concatenated
- Commands and Args can use values from environment variables
- Environment variables are associative arrays, so it is possible to target specific elements within the list to be overridden or added.
- Environment variables can be pulled from ConfigMaps and Secrets
- Kustomize merges ConfigMaps and Secrets per-key (deep merges of the values is not supported).
- ConfigMaps and Secrets can be read from apps via environment variables or volumes.
Flags and arguments may be factored into publisher and consumer focused pieces
by specifying the command
in the upstream
base dir and the args
in the
instance
dir. This allows consumers to set and add flags using args
without erasing those defined by the publisher in the command
.
When specifying values for arguments or flag values, it is best to use an environment variable read from a generated ConfigMap. This enables overriding the value using kustomize’s generators.
Example: Enable setting --skip-grant-tables
as a flag on mysql.
# {"$ref": ...
comments are setter references, defined in the next section.
# mysql/instance/statefulset.yaml
# Wire ConfigMap value from kustomization.yaml to
# an environment variable used by an arg
apiVersion: apps/v1
kind: StatefulSet
...
spec:
template:
metadata:
labels:
app: release-name-mysql
spec:
containers:
- name: mysql
...
args:
- --skip-grant-tables=$(SKIP_GRANT_TABLES)
...
env:
- name: SKIP_GRANT_TABLES
valueFrom:
configMapKeyRef:
name: mysql
key: skip-grant-tables
# mysql/instance/kustomization.yaml
# Changing the literal changes the StatefulSet behavior
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
configMapGenerator:
- name: mysql
behavior: merge
literals:
# for bootstrapping the root table grants -- set to false after bootstrapped
- "skip-grant-tables=true" # {"$kpt-set":"skip-grant-tables"}
Generating ConfigMaps and Secrets
Kustomize supports generating ConfigMaps and Secrets from the kustomization.yaml.
- Generated objects have a suffix applied so that the name is unique for the data. This ensures a rollout of Deployments and StatefulSets occurs.
- Generated object may have their values overridden by downstream consumers.
Example Upstream:
# mysql/upstream
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
configMapGenerator:
- name: mysql
literals:
- skip-grant-tables=true
Example Instance:
# mysql/instance
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
configMapGenerator:
- name: mysql
behavior: merge
literals:
- "skip-grant-tables=true" # {"$kpt-set":"skip-grant-tables"}
- "mysql-user=" # {"$kpt-set":"mysql-user"}
- "mysql-database=" # {"$kpt-set":"mysql-database"}
Setters and Substitutions
It may be desirable to provide user friendly commands for customizing the package rather than exclusively through text editors and sed:
- Setting a value in several different patches at once
- Setting common or required values – e.g. the image name for a Java app blueprint
- Setting the image tag to match the digest of an image that was just build.
- Setting a value from the environment when the package is fetched the first time – e.g. GCP project.
Setters and substitutions are a way to define user and automation friendly commands for performing structured edits of a configuration.
Combined with the preceding techniques, setters or substitutions can be used
to modify generated ConfigMaps and patches in the instance
dir.
See the setter and substitution guides for details.
# mysql/instance/kustomization.yaml
apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
#
# namespace is the namespace the mysql instance is run in
namespace: "" # {"$kpt-set":"namespace"}
configMapGenerator:
- name: mysql
behavior: merge
literals:
# for bootstrapping the root table grants -- set to false after bootstrapped
- "skip-grant-tables=true" # {"$kpt-set":"skip-grant-tables"}
- "mysql-user=" # {"$kpt-set":"mysql-user"}
- "mysql-database=" # {"$kpt-set":"mysql-database"}
...
# mysql/instance/statefulset.yaml
apiVersion: apps/v1
kind: StatefulSet
metadata:
name: mysql
spec:
template:
spec:
containers:
- name: mysql
...
ports:
- name: mysql
containerPort: 3306 # {"$kpt-set":"port"}
resources:
requests:
cpu: 100m # {"$kpt-set":"cpu"}
memory: 256Mi # {"$kpt-set":"memory"}
# mysql/instance/service.yaml
apiVersion: v1
kind: Service
...
spec:
ports:
- name: mysql
port: 3306 # {"$kpt-set":"port"}
targetPort: mysql
Updates
Individual directories may have their own package versions by prefixing the
version with the directory path – e.g.
package-examples/mysql-kustomize/v0.1.0
.
When publishing a new version of a package, publishers should think about how their changes will be merged into existing packages.
Changing values in the instance package is not recommended, but adding them may be ok – changes to fields will overwrite user changes to those same fields, whereas adds will only conflict if the user added the same field.


The 2018 29
th
IEEE Intelligent Vehicles Symposium
Sponsored by the IEEE Intelligent Transportation Systems Society
June 26-30, 2018
Changshu, Suzhou, China


Disclaimer: OpenNV is in the preliminary stages of development.
The OpenNV project is a collection of projects related to making Fallout: New Vegas mod development easier and allowing the game and it's mod content to be played on additional platforms. All OpenNV Projects are licensed under the 3-Clause BSD License.
OpenNV itself (part of, the OpenNV Project) is an engine recreation of the games Fallout: New Vegas and Fallout 3. It's written in C# and plans on using MOGRE for rendering.
OpenNVCK is a mod SDK for Fallout: New Vegas, aimed at being easier to use and less crash-prone than New Vegas's Garden of Eden Creation Kit (GECK). It's written in C# and uses Windows Forms.
Current development efforts are focused on OpenNVCK. Code will be committed once the OpenNVCK is in a usable state.
Current major challeneges are:


| Name | Geoffrey the Giraffe |
| Subjects to Study | Social Studies, Math, English, Topics in Metaphysics and Epistemology |
| Name | Geoffrey the Giraffe |
| Subjects to Study | Social Studies, Math, English, Topics in Metaphysics and Epistemology |
| Name | Geoffrey the Giraffe |
| Subjects to Study | Social Studies, Math, English, Topics in Metaphysics and Epistemology |
| Name | Geoffrey the Giraffe |
| Subjects to Study | Social Studies, Math, English, Topics in Metaphysics and Epistemology |
| Name | Geoffrey the Giraffe |
| Subjects to Study | Social Studies, Math, English, Topics in Metaphysics and Epistemology |


Rename Rules are used to change predicates in RDF triples from Source property to Target property.
Notice: Each filled in template generates an ordinary raw rule which can be further modified manually. Any change to the template instance will cause an update of the associated raw rule and all custom modifications be overwritten.


Machine learning (ML) algorithms study the pattern repetitions to learn and make predictions on data. Typically, this training uses massive data sets from which the algorithm identifies which features are important. However, many times a ML Expert needs to take part in the process of tweaking the parameters. Problems arise when the algorithms are used in user-oriented systems, where the data –usually very small labeled data- reflects highly individualized behaviors or preferences. In these situations, it’s the end-user (non-expert in ML) who must be involved in training the algorithm to correct the labeling.
>‘Black-box’ systems, with output that is not interpretable by a non-expert, will frustrate end users if they become dependent upon the systems. This is due to the fact that users will need to tailor and fix the systems when the systems break. This project tries to solve this situation by proposing an interactive visualization system, where different visualizations explain the raw data that were either misclassified or properly labelled. By facilitating a comparison between raw data from different classes we aim to transform the black box, making it intelligible to all the users.
The Data
Our project uses a dataset (courtesy of mHealth lab at Northeastern) of acceleration data tagged with activity type that was previously acquired for a study in activity recognition. The activities labeled were: biking outdoor, biking stationary at 300 KPM/min, folding pile of towels, frisbee, in elevator going up, jumping jacks, lying on back, on escalator going up, running at 5.5 mph 5% grade on treadmill, shelf reloading, shelf unloading, sitting (plotted on the right side of the screen), standing, sweeping, vending machine, walking at 1 mph (plotted on the right side of the screen), walking at 2 mph, walking at 3 mph, walking at 3.5 mph, walking outdoor, walking stairs down, walking stairs up.
We believe that showing the visual differences in the accelerations of each activity, specially in instances in which the labels were misclassified, can help experts to improve their algorithm.


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Need to reset your password? No problem! Just click the button below to reset your password!
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{% extends "bootstrap/base.html" %} {% block title %}Contact Support team{% endblock %} {% block content %}
To reset your password click here .
Alternatively, you can paste the following link in your browser's address bar:
{{ url_for('auth.reset_password', token=token, _external=True) }}
King Regards
The Microblog Team


| < Day Day Up > |
Hack 57 Tighten Security with Mandatory Access Control
Increase the security of your systems with MAC paranoia. Ever feel like your Unix systems are leaking out extra unsolicited information? For example, even a regular user can find out who is logged into a system and what they're currently doing. It's also an easy matter to find out what processes are running on a system. For the security-minded, this may be too much information in the hands of an attacker. Fortunately, thanks to the TrustedBSD project, there are more tools available in the admin's arsenal. One of them is the Mandatory Access Control (MAC) framework.
6.5.1 Preparing the SystemBefore you can implement Mandatory Access Control, your kernel must support it. Add the following line to your kernel configuration file: options MAC You can find full instructions for compiling a kernel in [Hack #54] . While your kernel is recompiling, take the time to read man 4 mac, which lists the available MAC modules. Some of the current modules support simple policies that can control an aspect of a system's behavior, whereas others provide more complex policies that can affect every aspect of system operation. This hack demonstrates simple policies designed to address a single problem. 6.5.2 Seeing Other UsersOne problem with open source Unix systems is that there are very few secrets. For example, any user can run ps -aux to see every running process or run sockstat -4 or netstat -an to view all connections or open sockets on a system. The MAC_SEEOTHERUIDS module addresses this. You can load this kernel module manually to experiment with its features: # kldload mac_seeotheruids Security policy loaded: TrustedBSD MAC/seeotheruids (mac_seeotheruids) If you'd like this module to load at boot time, add this to /boot/loader.conf: mac_seeotheruids_load="YES" If you need to unload the module, simply type: # kldunload mac_seeotheruids Security policy unload: TrustedBSD MAC/seeotheruids (mac_seeotheruids) When testing this module on your systems, compare the before and after results of these commands, run as both a regular user and the superuser:
Your before results should show processes and sockets owned by other users, whereas the after results should show only those owned by the user. While the output from w will still show which users are on which terminals, it will not display what other users are currently doing. By default, this module affects even the superuser. In order to change that, it's useful to know which sysctl MIBs control this module's behavior: # sysctl -a | grep seeotheruids security.mac.seeotheruids.enabled: 1 security.mac.seeotheruids.primarygroup_enabled: 0 security.mac.seeotheruids.specificgid_enabled: 0 security.mac.seeotheruids.specificgid: 0
See how there are two MIBs dealing with specificgid? The enabled one is off, and the other one specifies the numeric group ID that would be exempt if it were on. So, if you do this: # sysctl -w security.mac.seeotheruids.specificgid_enabled=1 security.mac.seeotheruids.specificgid_enabled: 0 -> 1 you will exempt group 0 from this policy. In FreeBSD, the wheel group has a GID of 0, so users in the wheel group will see all processes and sockets. You can also set that primarygroup_enabled MIB to 1 to allow users who share the same group ID to see each other's processes and sockets. Note that while you can change these MIBs from the command line, you will be able to see them only with the appropriate kernel module loaded. 6.5.3 Quickly Disable All Interfacesifconfig allows you to enable and disable individual interfaces as required. For example, to stop traffic on ed0: # ifconfig ed0 down To bring the interface back up, simply repeat that command, replacing the word down with up. However, ifconfig does not provide a convenient method for stopping or restarting traffic flow on all of a system's interfaces. That ability can be quite convenient for testing purposes or to quickly remove a system from a network that is under attack. The MAC_IFOFF module is a better tool for this purpose. Let's load this module and see how it affects the system: # kldload mac_ifoff Security policy loaded: TrustedBSD MAC/ifoff (mac_ifoff) # sysctl -a | grep ifoff security.mac.ifoff.enabled: 1 security.mac.ifoff.lo_enabled: 1 security.mac.ifoff.other_enabled: 0 security.mac.ifoff.bpfrecv_enabled: 0 By default, this module disables all interfaces, except the loopback lo device. When it's safe to reenable those interfaces, you can either unload the module: # kldunload mac_ifoff Security policy unload: TrustedBSD MAC/ifoff (mac_ifoff) or leave the module loaded and enable the interfaces: # sysctl -w security.mac.ifoff.other_enabled=1 security.mac.ifoff.other_enabled: 0 -> 1 Perhaps you have a system whose interfaces you'd like to disable at bootup until you explicitly enable them. If that's the case, add this line to /boot/loader.conf: mac_ifoff_load="YES" 6.5.4 See Also
|
| < Day Day Up > |


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The Adventures of Rocky and Bullwinkle (2000) 1 star out of 4. Starring Rocket J. Squirrel, Bullwinkle the Moose, Renee Russo, Jason Alexander, Robert De Niro, Piper Perabo and Randy Quaid. Special guest appearances by Jonathan Winters, Carl Reiner, Whoopi Goldberg and Janeane Garofalo. Written by Kenneth Lonergan. Music by Mark Motherrsbaugh. Directed by Des McAnuff.
I wish I could report that "The Adventures of Rocky and Bullwinkle" was a funny as the TV show. Heck, I wish I could report that it was as funny as "Me, Myself & Irene."
Unfortunately, "The Adventures of Rocky and Bullwinkle" plays like it was produced by people who don't have a clue about the TV show. It's as if they watched a couple of episodes and failed to get the joke.
Even as a kid, I grasped that "Rocky and His Friends," as the show was first called, was not your typical children's cartoon show. It was hip. You could tell that by the puns, the pop culture references and the sometimes subversive satire that the show was aimed at a more sophisticated audience.
Not so this movie.
Where does "The Adventures of Rocky and Bullwinkle" go wrong? Oh, where to begin.
While Bullwinkle traverses the proceedings in his usual endearing thick-headed oblivion, Rocky is given a severe case of hero angst.
Because he has been out of commission for 35 years, Rocky doubts his ability to once again take to the air. Our champion has developed a fear about flying.
Rubbish. Rocket J. Squirrel was - and is - the eternal optimist, never hesitating the right a wrong or battle villainy.
The film's other drawbacks lie in its plot as well as with Rocky and Bullwinkle's new, live-action sidekick.
The storyline has those dastardly villains from Pottsylvania, Boris, Natasha and Fearless Leader, jumping from their animated selves to the live action world.
Fearless Leader concocts a plan to take over the United States by creating a TV network, RBTV (Real Bad TV), which will show programs so awful they will zombify viewers so that F.L. can control their minds and hypnotize them into electing him president.
The idea would have been a fine one for the 1960s or '70s, but obviously Fearless Leader did not channel surf or he would have seen Jerry Springer, WWF wresting or the Home Shopping Network.
Meanwhile, eager, young, childlike FBI agent Karen Sympathy (Piper Perabo) recruits Rocky and Bullwinkle from a depressed Frostbite Falls, and transports them to the real world to thwart Fearless Leader's plot.
Here is where Kenneth Lonergan's script makes a wrong turn, for instead of concentrating on Moose, Squirrel, Boris and Natasha, "The Adventures of Rocky and Bullwinkle" becomes a road movie, with hour dynamic duo - plus Sympathy - driving cross-country from Los Angeles to New York for the final confrontation.
Along the way, Boris and Natasha, trying to `kill Moose and Squirrel,' but their efforts in the real world are as inept as in cartoon land.
You know a movie is in trouble when its funniest moments are the over-the-top, overwrought narration. Even the punlike word play between Rocky and Bullwinkle lacks some of the luster of the TV series.
Some of Bullwinkle's puns hit their target, but they are so few and far between, you can snooze while awaiting them.
Jason Alexander and Renee Russo are adequate as the live-action Boris and Natasha, mostly keeping in the character of their cartoon counterparts. Unfortunately, they are given very little to do. And the sight of the two sitting in a Jacuzzi, sipping champagne is totally out of character.
The novelty of Robert De Niro's performance as Fearless Leader quickly wears thin. De Niro has one wonderful scene in which he spoofs the most famous movie line he ever uttered. But, again, it is too little.
Perabo, as Karen Sympathy, is just terrible. She acts as if she's in a high school drama club. Every time she's on the screen, you want to slink down in your seat until she exits.
"The Adventures of Rocky and Bullwinkle" will have trouble finding an audience. It is not funny or cartoonish enough for the younger set, while it is too slow and weak for an older crowd. And the baby boomers for whom it is aimed, will probably feel disappointment at the manner in which their childhood idols are handled.
"The Adventures of Rocky and Bullwinkle" is a major misfire. The only ones who should be happy are Boris and Natasha. Universal Pictures finally succeeded where they always failed - they destroyed Moose and Squirrel.
Bob Bloom is the film critic at the Journal and Courier in Lafayette, IN. He can be reached by e-mail at<EMAIL_ADDRESS>or at<EMAIL_ADDRESS>Bloom's reviews can be found on the Internet Movie Database at: http://www.imdb.com/M/reviews_by?Bob+Bloom
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
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You will have 20 minutes to plan, write and revise an essay about the topic below. Your response will be judged on how well you develop a position, organize your ideas, present supporting details, and control the elements of standard written English. You should write 200-300 words.
The information revolution has changed the ways of mass communication and had some negative and positive effects on individuals’ lives as well as on society.


What is Pilates?
Pilates is not a new phenomenon. Joseph H. Pilates started developing his exercise method during World War I, which emphasizes the balance of strength, stretch and control in the entire body. Joe understood that the body repairs and strengthens itself through movement. It is a workout that will keep your body functioning as it ages. Pilates is a unique workout and, when done properly, it is simply sweaty, hard exercise.
Pilates is a method of exercise that incorporates strength, stretch and control into its movements to create a specialized method of body conditioning. Through Pilates, the body and mind are trained to work together to achieve optimum fitness goals. There are over 500 different exercises performed on five unique pieces of equipment. Each exercise is done in a particular sequence, with a minimum number of repetitions and a high degree of precision and mental focus. As clients progress, the movements become continuous from one exercise to the next creating an increasingly more challenging and aerobic workout.
About us
Authentic Pilates Los Gatos is dedicated to the classical Pilates method of body conditioning. Our studio offers only authentic Pilates, using the original teachings and apparatus built from original design specifications and mechanics of Joseph Pilates' own equipment. Our spacious and spotless studio is a state-of-the-art facility, which features the full complement of top-of-the-line Gratz equipment.
All our instructors have undergone an extensive and rigorous 700 hour training program in the classical Pilates method. Additionally, our instructors maintain their certification with ongoing continuing education courses offered by various master teachers.
Lindsey Jellinek (Owner/Instructor)
In 2006, Lindsey earned her certificate in classical Pilates at Metropolitan Pilates (www.metropolitanpilates.com) under the instruction of Master Teacher, Dorothee VandeWalle. Dorothee was the protégé of Romana Kryzanowska—who herself was the protégé of Joseph Pilates—and started her teaching career with Romana in New York City. Dorothee now shares her knowledge by training instructors in the classical Pilates method. She is recognized as one of the leading teacher trainers and master Pilates practitioners in the world.
Authentic Pilates Los Gatos opened in July 2011. Owner and instructor, Lindsey Jellinek, moved her original studio from Sun Valley, Idaho to her hometown of Los Gatos to share the classical Pilates method with the South Bay community. She enjoys working with clients of all levels and abilities, creating Pilates workouts to best fit her clients' individual needs. Lindsey is passionate about Pilates and sharing its principles, techniques, and method with all clients, as it delivers long lasting results.
Lindsey is an avid outdoor enthusiast and loves spending her downtime outside with her dogs, running and hiking. She incorporates Pilates into her daily life and she encourages her clients to do the same, as classical Pilates truly is the most effective and balanced form of exercise.
Abey Scaglione (Instructor}
Originally from Canada, Abey moved to California in 2005 after completing her psychology degree at Acadia University. In 2006 she completed her first Pilates training at John Garey Pilates and went on to receive a second teaching certificate through Power Pilates in 2008.
Abey continued her classical Pilates education in Los Angeles through regular lessons with Alisa Wyatt, Kara Wily and Karen Frischmann. She took numerous workshops with renowned, first generation Pilates master, Jay Grimes and completed the mat portion of The Work at Vintage Pilates in 2013. Abey owned Hummingbird Pilates, a classical Pilates studio in Beverly Hills, for three years before moving to the Bay Area in January 2017.
With over 12 years of Pilates teaching experience, Abey believes that Pilates is not only a challenging workout but also an essential part of health and wellness.


MAIC.SOFTWARE
Find a container that can help me ... ?
CONTAINER GRAPH CLOSED BETA
What's a container?


| Name |
Description |
| bandtype |
This table store tires band types.
|
| mount |
This table is used to set the times when the tire is mount. The relation with retread is because the mount is based in the retread, not in the tire.
|
| mountlocation |
Physical location of the tire on the truck where it was mounted.
|
| retread |
This table store the retreads made on the tire.
|
| tire |
This table represent the tire's carcass.
|
| tirebrand |
This table store tires brands.
|
| tiremodel |
This table store tires models.
|
| tiresituation |
This table is designed to set a current tire's situation. Ex: mounted, unmounted, died, unavailable, etc.
|
| truck |
Used to identify the truck that the tire will be mounted.
|
| unmount |
This table is used to store an unmount.
|
| unmountreason |
The unmount have a reason. Ex: mechanical problems, end of life, factory problem, etc.
|


Zero to Code’s curriculum is arranged in a single sequence of milestones, which are a collection of 2-5 mini-lessons that come together in a single “milestone project”. This is a comprehensive directory of the milestones I’ve made so far.
Milestones
Overview and Orientation
Before you begin working through the milestones, this overview covers a few things you should know to move through the course, including what you’ll learn, how to use our code editor, Codeframe, and how to learn to code effectively using the resources available online, in addition to what’s here already. What we’ll learn Zero to Code is a course about making interesting, useful things on the web using technologies that are core to any website: HTML, CSS, and JavaScript.
About page: Intro to HTML & CSS
In this milestone, we’ll get acquainted with HTML and CSS, two of the key building blocks of every website. Using what we learn, we’ll build a very simple About page for you. This milestone is a bit longer than the usual, and covers more ground than the usual, to help you get up and running. Rather than try to finish everything here in one sitting, find stopping points, and take your time to experiment with code samples provided here to really get a sense of how these key technologies (HTML and CSS) work.
Building a form: CSS Layout and Interactivity
In this milestone, we’ll meet some new, more interesting, interactive HTML elements like buttons and inputs, and we’ll dive deeper into CSS by looking at how we can use CSS properties to move things around on our page. Part 1: Semantic HTML In milestone 1, we encountered some simple HTML tags like <p> and <h1> that corresponded to chunks of text on our page. There’s also a set of HTML tags that correspond not to specific parts of text, but to sections of a webpage, like headers, footers, articles, sidebars, and navigation menus.


Secude IT Security Ltd, Darmstadt, provides modern cryptographic solutions to end users and developers.
It also offers products in the client / server, desktop and Internet areas, as well as solutions for the establishment and operation of certification structures.
URL for home page on the Internet: www.secude.com
Secude IT Security Ltd (www.secude.com
) was originally involved with
the implementation of the elliptic curves and has supplied the modern
cryptosystems from its library (Secude library).
Secude offers applications for access control and secure e-commerce. Its core activity is the integration of cryptography into applications which can differ radically as to size and platform (from "small" Office products under Windows through to large ERP systems on virtually all platforms), including related services and training.
Secude supports all major cryptography standards, protocols and formats. Secude software is used e.g. by ABN Amro, Bank of America, Deutsche Bank, Deutsche Telekom, Procter&Gamble, SAP, Siemens, Thyssen, Volkswagen, Wells Fargo and a bunch of universities. Secude is a development partner of SAP AG, and its Secude library product runs on all platforms supported by SAP R/3 and mySAP.com and is, for example, certified for the SAP interfaces SNC (Secure Network Communications) and SSF (Secure Store and Forward). As part of the Lotus MailProtect product, Secude library protects e-mail in large Notes installations.


We provide the latest knowledge to help you cope with the changing world!
We hope that all the students who love the Internet can be more convenient access to
learning resources, using the Internet thinking to change our learning.
Focus on IT skills education MOOC, consistent with the development trend of the Internet
down to earth's MOOC. We are free, we only teach useful, we concentrate on
education.


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Pvt. Ltd.
One of our representatives will happily contact you within 24 hours. For urgent needs call us at


Labtest Diagnostics provides mobile phlebotomy services for patients in the comfort of their own home, we provide blood draw services for group needs, such as
We offer the full spectrum of LC/MS/MS, clinical Chemistry, Immunoassay, Hematology, Pregnancy, HIV and a whole variety of Clinical Tests.
You can now call in or send email to schedule appointments for any lab tests. No Doctor's order needed for tests. Walk-ins are welcome. We accept most insurances, including medicare and medicaid.


{% extends 'v2/layouts/layout-email.html' %} {% block pageTitle %} EMAIL {% endblock %} {% block content %}
{{ data.firstName or 'Bob' }} {{ data.lastName or 'Smith' }} has declined your invite to act on your behalf this time. They may be able to act on your behalf for other services but not for {{ data.service or 'myHealth' }}.
Visit your account management area to see who is able to act on your behalf, or try asking someone else.


Marion Newlevant: Web Developer
A software craftswoman in Portland, Oregon with a thing for clean code...
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{{ content }}


| ${value}% reduced Defensive Ability over ${duration} Second(s) | min: [13.0, 15.0, 17.0, 19.0, 21.0, 23.0, 25.0, 27.0, 29.0, 31.0, 33.0, 35.0]% reduced Defensive Ability over min: 3.0 Second(s) |
| ${value}% reduced Offensive Ability over ${duration} Second(s) | min: [13.0, 15.0, 17.0, 19.0, 21.0, 23.0, 25.0, 27.0, 29.0, 31.0, 33.0, 35.0]% reduced Offensive Ability over min: 3.0 Second(s) |
| MaxLevel | 8 |
| UltimateLevel | 12 |


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/avoiding.20universe.20issues.html ---
I was about to jump in with the following definitions:
structure presheaf_of_complete_topological_rings (X : Type u) [T : topological_space X] := (F : Π {U : set X}, T.is_open U → Type v) -- note v [some more stuff] structure preadic_space -- a category (X : Type u) (F : presheaf_of_complete_topological_rings X) [loads more stuff]
But both of these definitions are "bad", right? In the sense that Mario told me to expect universe problems with structures like this, where I introduce new universes in structure fields.
So I looked back at my schemes definition and indeed I have
structure presheaf_of_types (α : Type u) [T : topological_space α] := (F : Π {U : set α}, T.is_open U → Type u) -- note u ...
but I do also have
structure scheme := (α : Type u) (T : topological_space α) (O_X : presheaf_of_rings α) ...
Is this then a "bad" definition of scheme? Should it be scheme α
?
And is this why category theory is difficult? This is what causes universe problems?
Should one really define the category of schemes in a universe u?
I don't really understand why introducing new universe variables in fields is a bad idea. Is it sometimes Ok to do it?
Here's a better question. If I can avoid the pre-adic space definition above, and instead do preadic_space X
, is that preferable? [and if so, why?]
If you use a structure with an "internal" universe variable like this, you should expect to need to specify that universe as in presheaf_of_complete_topological_rings.{u v}
. This is what happens with category
As for whether it's required, that depends on your application
I have a lot of difficulty with category theory in part because it's so heavy on definitions and light on applications. I use the applications to judge the definitions
What will happen when someone wants to do stacks and we need 2-categories to formalise the definition?
I guess we get 2-categories
But will there be new kinds of problems?
yes
cool
something to look forward to
the biggest one is probably that we will have to do all of category theory again
and there really isn't a good way to unify these
Probably it's best to just do this stuff on a by-need basis because there's no end of generalization
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


| Package | Description |
|---|---|
| javafx.embed.swing |
Provides the set of classes to use JavaFX inside Swing applications.
|
| javafx.embed.swt |
Provides the set of classes to use JavaFX inside SWT applications.
|
| javafx.scene |
Provides the core set of base
classes for the JavaFX Scene Graph API.
|
| javafx.scene.canvas |
Provides the set of classes for canvas, an immediate mode style of rendering API.
|
| javafx.scene.effect |
Provides the set of classes for attaching graphical filter effects to JavaFX Scene Graph Nodes.
|
| javafx.scene.image |
Provides the set of classes for loading and displaying images.
|
| javafx.scene.input |
Provides the set of classes for mouse and keyboard input event handling.
|
| javafx.scene.layout |
Provides classes to support user interface layout.
|
| javafx.scene.paint |
Provides the set of classes for colors and gradients used to fill shapes and
backgrounds when rendering the scene graph.
|
| javafx.stage |
Provides the top-level container classes for JavaFX content.
|
| Modifier and Type | Method and Description |
|---|---|
static BufferedImage |
SwingFXUtils.fromFXImage(Image img,
BufferedImage bimg)
Snapshots the specified JavaFX
Image object and stores a
copy of its pixels into a BufferedImage object, creating
a new object if needed. |
| Modifier and Type | Method and Description |
|---|---|
static org.eclipse.swt.graphics.ImageData |
SWTFXUtils.fromFXImage(Image image,
org.eclipse.swt.graphics.ImageData imageData)
Snapshots the specified JavaFX
Image object and stores a
copy of its pixels into a new ImageData object. |
| Modifier and Type | Method and Description |
|---|---|
Image |
ImageCursor.getImage()
Gets the value of the property image.
|
| Modifier and Type | Method and Description |
|---|---|
ReadOnlyObjectProperty<Image> |
ImageCursor.imageProperty()
The image to display when the cursor is active.
|
| Modifier and Type | Method and Description |
|---|---|
static ImageCursor |
ImageCursor.chooseBestCursor(Image[] images,
double hotspotX,
double hotspotY)
Creates a custom image cursor from one of the specified images.
|
| Constructor and Description |
|---|
ImageCursor(Image image)
Constructs an
ImageCursor from the specified image. |
ImageCursor(Image image,
double hotspotX,
double hotspotY)
Constructs an
ImageCursor from the specified image and hotspot
coordinates. |
| Modifier and Type | Method and Description |
|---|---|
void |
GraphicsContext.drawImage(Image img,
double x,
double y)
Draws an image at the given x, y position using the width
and height of the given image.
|
void |
GraphicsContext.drawImage(Image img,
double x,
double y,
double w,
double h)
Draws an image into the given destination rectangle of the canvas.
|
void |
GraphicsContext.drawImage(Image img,
double sx,
double sy,
double sw,
double sh,
double dx,
double dy,
double dw,
double dh)
Draws the specified source rectangle of the given image to the given
destination rectangle of the Canvas.
|
| Modifier and Type | Method and Description |
|---|---|
Image |
ImageInput.getSource()
Gets the value of the property source.
|
| Modifier and Type | Method and Description |
|---|---|
ObjectProperty<Image> |
ImageInput.sourceProperty()
The source
Image . |
| Modifier and Type | Method and Description |
|---|---|
void |
ImageInput.setSource(Image value)
Sets the value of the property source.
|
| Constructor and Description |
|---|
ImageInput(Image source)
Creates a new instance of ImageInput with the specified source.
|
ImageInput(Image source,
double x,
double y)
Creates a new instance of ImageInput with the specified source, x and y.
|
| Modifier and Type | Class and Description |
|---|---|
class |
WritableImage
The
WritableImage class represents a custom graphical image
that is constructed from pixels supplied by the application, and possibly
from PixelReader objects from any number of sources, including
images read from a file or URL. |
| Modifier and Type | Method and Description |
|---|---|
Image |
ImageView.getImage()
Gets the value of the property image.
|
static Image |
Image.impl_fromPlatformImage(Object image)
Deprecated.
This is an internal API that is not intended for use and will be removed in the next version
|
| Modifier and Type | Method and Description |
|---|---|
ObjectProperty<Image> |
ImageView.imageProperty()
The
Image to be painted by this ImageView . |
| Modifier and Type | Method and Description |
|---|---|
void |
ImageView.setImage(Image value)
Sets the value of the property image.
|
| Constructor and Description |
|---|
ImageView(Image image)
Allocates a new ImageView object using the given image.
|
| Modifier and Type | Method and Description |
|---|---|
Image |
Dragboard.getDragView()
Gets the image used as a drag view.
|
Image |
Clipboard.getImage()
Gets the Image from the clipboard which had previously
been registered.
|
Image |
ClipboardContent.getImage()
Gets the Image from the
ClipboardContent
which had previously been put. |
| Modifier and Type | Method and Description |
|---|---|
boolean |
ClipboardContent.putImage(Image i)
Puts an Image into the
ClipboardContent . |
void |
Dragboard.setDragView(Image image)
Sets the visual representation of data being transfered
in a drag and drop gesture.
|
void |
Dragboard.setDragView(Image image,
double offsetX,
double offsetY)
Sets the visual representation of data being transfered
in a drag and drop gesture.
|
| Modifier and Type | Method and Description |
|---|---|
Image |
BackgroundImage.getImage()
The image to be used.
|
Image |
BorderImage.getImage()
The image to be used.
|
| Constructor and Description |
|---|
BackgroundImage(Image image,
BackgroundRepeat repeatX,
BackgroundRepeat repeatY,
BackgroundPosition position,
BackgroundSize size)
Creates a new BackgroundImage.
|
BorderImage(Image image,
BorderWidths widths,
Insets insets,
BorderWidths slices,
boolean filled,
BorderRepeat repeatX,
BorderRepeat repeatY)
Creates a new BorderImage.
|
| Modifier and Type | Method and Description |
|---|---|
Image |
PhongMaterial.getBumpMap()
Gets the value of the property bumpMap.
|
Image |
PhongMaterial.getDiffuseMap()
Gets the value of the property diffuseMap.
|
Image |
ImagePattern.getImage()
Gets the image to be used as a paint.
|
Image |
PhongMaterial.getSelfIlluminationMap()
Gets the value of the property selfIlluminationMap.
|
Image |
PhongMaterial.getSpecularMap()
Gets the value of the property specularMap.
|
| Modifier and Type | Method and Description |
|---|---|
ObjectProperty<Image> |
PhongMaterial.bumpMapProperty()
The bump map of this
PhongMaterial , which is a normal map stored
as a RGB Image . |
ObjectProperty<Image> |
PhongMaterial.diffuseMapProperty()
The diffuse map of this
PhongMaterial . |
ObjectProperty<Image> |
PhongMaterial.selfIlluminationMapProperty()
The self illumination map of this
PhongMaterial . |
ObjectProperty<Image> |
PhongMaterial.specularMapProperty()
The specular map of this
PhongMaterial . |
| Modifier and Type | Method and Description |
|---|---|
void |
PhongMaterial.setBumpMap(Image value)
Sets the value of the property bumpMap.
|
void |
PhongMaterial.setDiffuseMap(Image value)
Sets the value of the property diffuseMap.
|
void |
PhongMaterial.setSelfIlluminationMap(Image value)
Sets the value of the property selfIlluminationMap.
|
void |
PhongMaterial.setSpecularMap(Image value)
Sets the value of the property specularMap.
|
| Constructor and Description |
|---|
ImagePattern(Image image)
Creates a new instance of ImagePattern from the specified image.
|
ImagePattern(Image image,
double x,
double y,
double width,
double height,
boolean proportional)
Creates a new instance of ImagePattern.
|
PhongMaterial(Color diffuseColor,
Image diffuseMap,
Image specularMap,
Image bumpMap,
Image selfIlluminationMap)
Creates a new instance of
PhongMaterial class using the specified
colors and images for its diffuseColor properties. |
| Modifier and Type | Method and Description |
|---|---|
ObservableList<Image> |
Stage.getIcons()
Gets the icon images to be used in the window decorations and when
minimized.
|
Submit a bug or feature
For further API reference and developer documentation, see Java SE Documentation. That documentation contains more detailed, developer-targeted descriptions, with conceptual overviews, definitions of terms, workarounds, and working code examples.
Copyright © 2008, 2021, Oracle and/or its affiliates. All rights reserved. Use is subject to license terms. Also see the documentation redistribution policy.


|
Labdevicedriver Framework
|
Functions | |
| function | close (in obj) |
| close the java socket of a labDevice More... | |
| function | open (in obj) |
| Opens connection to Device using jaca sockets. More... | |
| function | read (in obj) |
| reads data from labDevice using the java helper class More... | |
| function | write (in obj, in txt) |
| write string to labDevice using java socket More... | |
| function customEthOverJava::close | ( | in | obj | ) |
| function customEthOverJava::open | ( | in | obj | ) |
| function customEthOverJava::read | ( | in | obj | ) |


US to End Sanctions for Iran’s Fordow Nuclear Plant
by JNS“For the sake of My servant Yaakov, Yisrael My chosen one, I call you by name, I hail you by title, though you have not known Me.”Isaiah 45:4 (The Israel Bible™)
U.S. Secretary of State Mike Pompeo said on Monday that the United States would no longer waive sanctions related to Iran’s Fordow nuclear plant because Tehran had resumed uranium enrichment there, Reuters reported.
“The right amount of uranium enrichment for the world’s largest state sponsor of terror is zero. There is no legitimate reason for Iran to resume enrichment at this previously clandestine site,” said Pompeo.
Even after the United States withdrew from the 2015 nuclear deal between Iran and world powers, it continued to waive sanctions for foreign companies doing business at Fordow, which included Russia’s Rosatom. These waivers will end on Dec. 15.
United Nations nuclear watchdog the IAEA and Iran announced recently that Iran had resumed enriching uranium at Fordow, an underground facility the country originally hid from inspectors that was discovered in 2009, the report noted.
Republican senators Ted Cruz, Lindsey Graham, and Liz Cheney praised the decision and called on the administration to also end the waiver for Iran’s Arak heavy water reactor, where the China National Nuclear Corp has worked.
Separately, Iran said on Monday that protests in the country had come to an end, Reuters reported.
“Calm has been restored in the country,” Iran’s judiciary spokesman Gholamhossein Esmaili told a news conference, according to the report.
The protests began last week after gas price increases.


By Coleman Imhoff
Summit Four 14ers in a Single Day
Are you looking into hike your first 14,000 ft. mountain? Or are you one of those die-hard hikers trying to knock off every 14er in Colorado? The “Decalibron Loop” offers a unique opportunity to summit four 14ers in a single day! Located in the Mosquito Range in Colorado, this loop includes:
- Mt. Democrat (14,148')
- Mt. Cameron (14,238')
- Mt. Bross (14,172')
- Mt. Lincoln (14,286')
Looking Back At Mt. Democrat
Start your journey at Kite Lake Trail Head at 12,000 ft. Plan on camping the night before and waking up at dusk the following morning to begin hiking. Despite only being 7.5 miles long with an elevation gain of 3,000 total ft, this hike is difficult and will take a full day. Make sure you plan accordingly and come prepared!
On the Summit of Mt. Cameron
What Should I Bring?
- Water
- Warm Layers
- First Aid Kit
- Snacks
- Sunscreen and Sunglasses
- Beer (having a beer at the summit is a fun tradition!)
Do Your Research!
Make a plan. Weather can be unpredictable and hiking at high altitudes can be dangerous. Here is a list of some helpful resources: