Thomas Cyclically Symmetric Attractor
Lorenz Attractor
Bedhead Attractor
Dadras Attractor
Halvorsen Attractor
Three-Scroll Attractor
Sprott Attractor
Aizawa Attractor
Cube Grid
Camera Coordinate System
World Coordinate System
FPS:
0
Frame time:
0
ms
Render Clock Period:
0
ms


import AsiNgToolsModule or AsiCodeViewerModule
This component is an integration of the Prism library, see : http://prismjs.com
In your package.json add the dependency :
"prismjs": "1.6.0"
In your angular-cli.json add in scripts :
"../node_modules/prismjs/prism.js",
In your angular-cli.json add in styles :
"../node_modules/prismjs/themes/prism.css"
For specifique language you must add scripts : example for typescript add
"../node_modules/prismjs/components/prism-typescript"
| Name | Description |
|---|---|
| [language] | Language to display : 'html', 'typescript', 'css' etc... see primjs documentation |
| [fromUrl] | Url of the file to display |
| [value] | Display a value |


Goal
Submit automated predictions of lesion segmentation boundaries within dermoscopic images.
Data
Input Data
The input data are dermoscopic lesion images in JPEG format.
All lesion images are named using the scheme ISIC_<image_id>.jpg
,
where <image_id>
is a 7-digit unique identifier. EXIF tags in the
images have been removed; any remaining EXIF tags should not be relied upon to provide
accurate metadata.
The lesion images were acquired with a variety of dermatoscope types, from all anatomic sites (excluding mucosa and nails), from a historical sample of patients presented for skin cancer screening, from several different institutions. Every lesion image contains exactly one primary lesion; other fiducial markers, smaller secondary lesions, or other pigmented regions may be neglected.
The distribution of disease states represent a modified "real world" setting whereby there are more benign lesions than malignant lesions, but an over-representation of malignancies.
Response Data
The response data are binary mask images in PNG format, indicating the location of the primary skin lesion within each input lesion image.
Mask images are named using the
scheme ISIC_<image_id>_segmentation.png
, where <image_id>
matches the corresponding lesion image for the mask.
Mask images must have the exact same dimensions as their corresponding lesion image. Mask images are encoded as single-channel (grayscale) 8-bit PNGs (to provide lossless compression), where each pixel is either:
0
: representing the background of the image, or areas outside the primary lesion255
: representing the foreground of the image, or areas inside the primary lesion
As the primary skin lesion is a single contiguous region, mask images should also contain only a single contiguous foreground region, without any disconnected components or holes. The foreground region may be of any size (including the entire image) and may abut the borders of the image.
Ground Truth Provenance
Mask image ground truth (provided for training and used internally for scoring validation and test phases) data were generated using several techniques, but all data were reviewed and curated by practicing dermatologists with expertise in dermoscopy.
Ground truth segmentations were generated by either:
- fully-automated algorithm, reviewed and accepted by a human expert
- a semi-automated flood-fill algorithm, with parameters chosen by a human expert
- manual polygon tracing by a human expert
Evaluation
Goal Metric
Predicted responses are scored using a threshold Jaccard index metric.
To compute this metric:
- For each image, a pixel-wise comparison of each predicted segmentation with the corresponding ground truth segmentation is made using the Jaccard index.
- The final score for each image is computed as a threshold of the Jaccard according to
the following:
- score = 0, if the Jaccard index is less than 0.65
- score = the Jaccard index value, otherwise
- The mean of all per-image scores is taken as the final metric value for the entire dataset
Rationale
The choice of threshold Jaccard index metric is based on a previously published analysis which demonstrated using the Jaccard directly as a measure of performance does not accurately reflect the number of images in which automated segmentation fails, or falls outside expert interobserver variability (i.e. the raw Jaccard is overly optimistic). The number of images in which automated segmentation fails is a direct measure of the amount of labor required to correct an algorithm.
In order to determine the threshold, the lowest Jaccard agreement between 3 independent expert annotators was measured on a subset of 100 images. This empirically measured value (~0.74) is the basis for the 0.65 value threshold (with additional error tolerance), which indicates segmentation failure on an image.
Other Metrics
Participants will be ranked and awards granted based only on the Threshold Jaccard index metric. However, for scientific completeness, predicted responses will also have the following metrics computed on a pixel-wise basis (comparing prediction vs. ground truth) for each image:
Submission Instructions
To participate in this task:
- Train
- Download the training input data and training ground truth response data.
- Develop an algorithm for generating lesion segmentations in general.
- Validate (optional)
- Download the validation input data.
- Run your algorithm on the validation Input data to produce validation predicted responses.
- Submit these validation predicted responses to receive an immediate score. This will provide feedback that your predicted responses have the correct data format and have reasonable performance. You may make unlimited submissions.
- Test
- Download the test input data.
- Run your algorithm on the test input data to produce test predicted responses.
- Submit these test predicted responses. You may submit a maximum of 3 separate approaches/algorithms to be evaluated independently. You may make unlimited submissions, but only the most recent submission for each approach will be used for official judging. Use the "brief description of your algorithm’s approach" field on the submission form to distinguish different approaches. Previously submitted approaches are available in the dropdown menu.
- Submit a manuscript describing your algorithm’s approach.


Documentation and interpretation of American life and mores is a frequent collection focus. Even idealized and sentimental narratives reveal something about how we want our world to be, how we wish to be depicted.
{% import 'components/_slideshow.html' as slide %}
{{ slide.info("10728730","amr-sizer",'Paul C. Stahr (1883-1953), “Retouching an Old Masterpiece” (c.1915), watercolor, gouache, pen & black ink on paper', 'amr-one' ) }}
{{ slide.info("10728684","", 'Joseph Christian Leyendecker (1874-1951), “Republicans vs. Democrats” (c.1936), oil on canvas', 'amr-two') }}
{{ slide.info("10728683","",'Charles Dana Gibson (1867-1944), “Girl at Party,” pen & ink on board', 'amr-three', 'large' ) }}
{{ slide.info("10728726","", 'Frederic Remington (1861-1909), “Call the Doctor” (c.1889), oil on canvas', 'amr-four', 'large') }}
{{ slide.info("10817317","",'Thornton Oakley (1881-1953), “News Vendor on Broadway” (1905), oil on canvas', 'amr-five' ) }}
{{ slide.info("10728668","",'John Philip Falter (1910-1982), “Windy City” (c.1946), oil on board', 'amr-six' ) }}
{{ slide.info("10728704","",'Norman Rockwell (1894-1978), “After the Prom” (c.1957), oil on canvas', 'amr-seven' ) }}
{{ slide.info("10728707","",'Norman Rockwell (1894-1978), “The Gossips” (c.1948), oil on canvas', 'amr-eight' ) }}
{{ slide.info("10817319","",'Everett Shinn (1876-1953), “Ballet Dancer” pastel on paper', 'amr-nine' ) }}


JavaScript is disabled on your browser.
Deprecated API
Contents
Deprecated Methods
Deprecated Constructors
Deprecated Methods
Method and Description
com.gfb.test.QRBill.getAdditionalInfo()
com.gfb.test.QRBill.setAdditionalInfo(String)
Deprecated Constructors
Constructor and Description
com.gfb.test.QRBill()
com.gfb.test.QRBill(String)


hg commit
Commit all staged or specified files to the repository.


I am experienced in cooperating with teams of various sizes and forms both domestically and internationally. Professional experiences include but are not limited to: digital advertising, B2B/B2C communication, and marketing.
Always curious, and always acting on my curiosities. Currently dipping toes in coding, designing, and drawing. I also love the outdoors and love to cycle, run, and take long walks.


curl_mime_data_cb - set a callback-based data source for a mime part body
NAME
curl_mime_data_cb - set a callback-based data source for a mime part's body
SYNOPSIS
#include <curl/curl.h>
size_t readfunc(char *buffer, size_t size, size_t nitems, void *arg);
int seekfunc(void *arg, curl_off_t offset, int origin);
void freefunc(void *arg);
CURLcode curl_mime_data_cb(curl_mimepart * part , curl_off_t datasize ,
curl_read_callback readfunc , curl_seek_callback seekfunc ,
curl_free_callback freefunc , void * arg );
DESCRIPTION
curl_mime_data_cb sets the data source of a mime part's body content from a data read callback function.
part is the part's to assign contents to.
readfunc is a pointer to a data read callback function, with a signature as shown by the above prototype. It may not be set to NULL.
seekfunc is a pointer to a seek callback function, with a signature as shown by the above prototype. This function will be used upon resending data (i.e.: after a redirect); this pointer may be set to NULL, in which case a resend is not possible.
freefunc is a pointer to a user resource freeing callback function, with a signature as shown by the above prototype. If no resource is to be freed, it may safely be set to NULL. This function will be called upon mime structure freeing.
arg is a user defined argument to callback functions.
The read callback function gets called by libcurl as soon as it needs to read data in order to send it to the peer - like if you ask it to upload or post data to the server. The data area pointed at by the pointer buffer should be filled up with at most size multiplied with nmemb number of bytes by your function.
Your read function must then return the actual number of bytes that it stored in that memory area. Returning 0 will signal end-of-file to the library and cause it to stop the current transfer.
If you stop the current transfer by returning 0 "pre-maturely" (i.e. before the server expected it, like when you've said you will upload N bytes and you upload less than N bytes), you may experience that the server "hangs" waiting for the rest of the data that won't come.
The read callback may return CURL_READFUNC_ABORT to stop the current operation immediately, resulting in a CURLE_ABORTED_BY_CALLBACK error code from the transfer.
The callback can return CURL_READFUNC_PAUSE to cause reading from this connection to pause. See curl_easy_pause for further details.
The seek function gets called by libcurl to rewind input stream data or to seek to a certain position. The function shall work like fseek(3) or lseek(3) and it gets SEEK_SET, SEEK_CUR or SEEK_END as argument for origin, although libcurl currently only passes SEEK_SET.
The callback function must return CURL_SEEKFUNC_OK on success, CURL_SEEKFUNC_FAIL to cause the upload operation to fail or CURL_SEEKFUNC_CANTSEEK to indicate that while the seek failed, libcurl is free to work around the problem if possible. The latter can sometimes be done by instead reading from the input or similar.
Care must be taken if the part is bound to a curl easy handle that is later duplicated: the arg pointer argument is also duplicated, resulting in the pointed item to be shared between the original and the copied handle. In particular, special attention should be given to the freefunc procedure code since it will be called twice with the same argument.
AVAILABILITY
As long as at least one of HTTP, SMTP or IMAP is enabled. Added in 7.56.0.
RETURN VALUE
CURLE_OK or a CURL error code upon failure.
EXAMPLE
Sending a huge data string will cause the same amount of memory to be allocated: to avoid overhead resources consumption, one might want to use a callback source to avoid data duplication. In this case, original data must be retained until after the transfer terminates.
char hugedata[512000]; struct ctl { char *buffer; curl_off_t size; curl_off_t position; }; size_t read_callback(char *buffer, size_t size, size_t nitems, void *arg) { struct ctl *p = (struct ctl *) arg; curl_off_t sz = p->size - p->position; nitems *= size; if(sz > nitems) sz = nitems; if(sz) memcpy(buffer, p->buffer + p->position, sz); p->position += sz; return sz; } int seek_callback(void *arg, curl_off_t offset, int origin) { struct ctl *p = (struct ctl *) arg; switch(origin) { case SEEK_END: offset += p->size; break; case SEEK_CUR: offset += p->position; break; } if(offset < 0) return CURL_SEEKFUNC_FAIL; p->position = offset; return CURL_SEEKFUNC_OK; } CURL *easy = curl_easy_init(); curl_mime *mime = curl_mime_init(easy); curl_mimepart *part = curl_mime_addpart(mime); struct ctl hugectl; hugectl.buffer = hugedata; hugectl.size = sizeof hugedata; hugectl.position = 0; curl_mime_data_cb(part, hugectl.size, read_callback, seek_callback, NULL, &hugectl);
SEE ALSO
curl_mime_addpart, curl_mime_data, curl_mime_name, curl_easy_duphandle
This HTML page was made with roffit.


{% extends 'annotationweb/one_column_layout.html' %} {% block content %} {% for message in messages %}
{% endfor %}| Name | Type | Images/Videos | Progress | Image list | Annotate | Export | Delete |
|---|---|---|---|---|---|---|---|
| {{ task.name }} | {{ task.type }} | {{task.total_number_of_images}} | {{task.percentage_finished}}% | Image list | {% if task.finished %} Task is finished {% else %} Continue annotation {% endif %} | Export | Delete |


2-PLAYER GAMES
Game Selection:
Fractactoe
Zero Gravity Connect Four
Mad Lib Creator
Splatari
Knoxo
Warboys in Love


onix.couple.Couple_openmc¶
-
class
onix.couple.
Couple_openmc
(MC_input_path=None, xs_mode='no constant lib', MPI=None)[source]¶ This class is used to execute coupled-mode simulations
Through this class, the user can:
chose to parallelize the Monte Carlo simulations via the “set_MPI” method
set the nuclear data libraries to be used in the simulation
set the burnup/time sequence for the simulation
manually set the volume of each BUCells (note that by default, ONIX uses the OpenMC stochastic volume calculation to find the volume of each cell. However, this method might produce important errors on the volume and it is advised to set the volume manually)
select which of the Cells defined in the OpenMC input should be depleted (these cells will be known as BUCells)
select a list of nuclides in each BUCell which cross sections will be tallied. If the user does not specify any such list of nuclides, ONIX will by default tally the cross sections of all nuclides which data are found in the cross section library.
The Couple_openmc class also takes care of the coupling between ONIX and OpenMC. At the beginning of a simulation, it imports certain initial parameters from the OpenMC input to ONIX such as the name of the BUCells and the initial nuclide densities of each BUCell. During the simulation, it makes sure that information such as the flux tallies, neutron spectrum tallies, the reaction rates and the updated nuclide densities are correctly transfered between the burnup module and the neutron transport module.
The Couple_openmc class will also sample the isomeric branching ratios and (n,gamma) cross sections on the the same energy points to prepare for the calculations of one-group isomeric branching ratios.
IMPORTANT: the root cell in the OpenMC input should be named “root cell”
- Parameters
MC_input_path (str) – Specifies where the OpenMC input files in .xml format are located. This parameter should not be specified as ONIX cannot yet work without Python API.
xs_mode (str) – Choice between ‘constant lib’ and ‘no constant lib’. Default to ‘no constant lib’. ‘constant lib’ indicates to ONIX that the user has provided a constant one-group cross section libraries to be used. ‘no constant lib’ indicates to ONIX that it should use one-group cross section computed by OpenMC.
MPI (str) – Choice between ‘on’ and ‘off’. Indicates whether OpenMC will be parrallelized or not.
-
property
MC_XS_nucl_list
¶ Returns the list of nuclides for which cross section data exist in the cross section library.
-
property
MC_input_path
¶ Returns the path to OpenMC input files.
-
property
MPI
¶ Returns wether MPI is activated or not (‘on’ if the user chose to parallelize OpenMC with MPI, ‘off’ if not)
-
property
bounding_box
¶ Returns the bounding box of the geometry.
-
few_isomeric_on
()[source]¶ Calling this function will force ONIX to only calculate isomeric branching ratios of Pm147 and Am241 By default ONIX calculates all isomeric branching ratios for which data can be found in the EAF-2010 multiplicities library
-
import_openmc
(root_cell)[source]¶ This method import certain parameters from OpenMC to ONIX
This method launches the _pre_run script which runs a first Monte Carlo simulation in order for ONIX to get a handle on the various OpenMC objects (this feature is essential when the user decides to defines input parameters via a text input file rather than using the Python API. However, as of now, ONIX only supports Python API input)
The _pre_run script also requests OpenMC to calculate the volume of each OpenMC Cell with openmc.calculate_volume(). However, the volumes obtained via this method can have significant errors, especially for complex or large geometry. As of now, it is recommented that the user manually sets the volume of ech BUCell via the onix.couple.Couple_openmc.set_volume() command.
Finally, a very important functionality of import_openmc is to add minute quantities of certain nuclides in BUCells’ materials so that OpenMC can calculate their cross sections. This means that ONIX is going to modify the material.xml and add all nuclides requested by the user for cross section calculations. This feature is necessary because OpenMC cannot tally reaction rates of nuclides that are not present in the material.
- Parameters
root_cell (openmc.Cell) – Root cell object defined in OpenMC geometry.
-
property
initial_summary
¶ Returns the original summary.h5 file created by OpenMC before ONIX applies change to OpenMC’s objects.
-
property
materials
¶ Returns the materials object created in the OpenMC material input.
-
no_decay
()[source]¶ Activate a “no-decay” simulation. This means that the system will not model the decay of nuclides
-
property
openmc_bin_path
¶ Returns the path to OpenMC executable.
-
reac_rank_on
()[source]¶ Calling this function will tell ONIX to produce reaction rates ranking and print them for each BUCells By default ONIX does not produce reaction rates ranking as it takes a lot of memory.
-
property
root_cell
¶ Returns the root cell object created in the OpenMC geometry.
-
select_bucells
(bucell_list)[source]¶ Selects the cells from the OpenMC input that should be depleted.
The user can choose to specify the nuclides for which cross sections should be updated by OpenMC simulations. To do so, the user must enter a tuple where the first element is the OpenMC cell object and the second element is a list of the name of nuclides which cross sections should be updated.
If the user does not specify for which nuclides cross sections should be updated, only the OpenMC cell objects should be entered. ONIX will by default calculate the cross sections for all nuclides available in the cross section library.
- Parameters
bucell_list (list of openmc.Cell or list of tuples) –
Defines the list of cells that should be depleted by ONIX.
For example, the user can set bucell_list = [(fuel_cell, [‘U-235’, ‘Pu-239’], (cladding_cell, [‘Al-27’])]
-
property
sequence
¶ Returns the sequence assigned to the Couple_openmc() object.
-
set_MPI
(execu, tasks)[source]¶ Sets the settings for the MPI parallelization
- Parameters
execu (str) – The MPI execute command, for example ‘srun’ on cluster using slurm
tasks (str) – The number of tasks to parallelize
-
set_bounding_box
(ll, ur)[source]¶ Sets the bounding box of the geometry.
- Parameters
ll ([x,y,z]) – Extremity of the box located in the negative part of a 3-D plan
ur ([x,y,z]) – Extremity of the box located in the positive part of a 3-D plan
-
set_decay_from_object
(bucell, object)[source]¶ Sets the decay library from an ONIX decay object defined by the user for a specific BUCell.
- Parameters
bucell (onix.Cell) – The BUCell for which the decay data are to be used.
object (onix.utils.decay_lib) – A decay library object constructed by the user with onix.utils.decay_lib.
-
set_decay_lib
(decay_lib_path)[source]¶ Sets the decay library to use for ONIX.
- Parameters
decay_lib_path (str) – Path to a decay library. The library needs to be in ONIX format.
-
set_default_xs_lib
()[source]¶ Sets the cross section library to the default one. The default cross section library in ONIX has been obtained by computing middle-burnup one-group cross section for a coupled simumation of a LWR fuel pin-cell. Therefore, this library is only adapted for LWR reactors.
-
set_fy_from_object
(bucell, object)[source]¶ Sets the fission yield library to an ONIX fission yield object defined by the user for a specific BUCell.
- Parameters
bucell (onix.Cell) – The BUCell for which the decay data are to be used.
object (onix.utils.fy_lib) – A fission yield library object constructed by the user with onix.utils.fy_lib.
-
set_sequence
(sequence)[source]¶ Sets a sequence object to the Couple_openmc object.
- Parameters
sequence (onix.Sequence) – ONIX sequence object defined by the user.
-
set_user_fy_lib
(user_fy_lib_path, complete=False)[source]¶ Sets the fission yield library to use for ONIX. Setting the complete parameter to True allows ONIX to complement the data of the provided library with additional data found in ENDF/B-VIII.0.
- Parameters
user_fy_lib_path (str) – Path to a fission yield library. The library needs to be in ONIX format.
complete (bool) – Indicates to ONIX whether or not to complement the provided library with additional fission yields from ENDF:B-VIII.0 library.
-
set_vol
(vol_dict)[source]¶ Sets the volume of each BUCell in \(cm^{3}\).
- Parameters
vol_dict (dict) – Dictionnary where keys are the names of BUCell (as defined by the user) and entries are volume in \(cm^{3}\).
-
set_xs_lib
(xs_lib_path)[source]¶ Sets the cross section library to use for ONIX.
- Parameters
xs_lib_path (str) – Path to a cross section library. The library needs to be in ONIX format.
-
property
settings
¶ Returns the setting object defined in OpenMC simulation.
-
property
system
¶ Returns the system object of the simulation.
-
property
updated_summary
¶ Returns the updated summary.h5 file created by OpenMC before ONIX applies change to OpenMC’s objects.
-
property
xs_mode
¶ Returns the mode for cross sections library.


Methods related to general tribology
tribology.
abbottfirestone
(trace, res=100)[source]¶Calculate Abbott-Firestone curve for 2D surface trace
| Parameters: |
|
|---|---|
| Returns: | data baskets (steps) and cumulative distribution (x and y data for Abbott-Firestone plot) |
tribology.
eeff
(r_x_1, r_y_1, r_x_2, r_y_2)[source]¶Effective radii for combination of 2 bodies according to Hertzian contact theory :param r_x_1: radius of body 1 in x :param r_y_1: radius of body 1 in y :param r_x_2: radius of body 2 in x :param r_y_2: radius of body 2 in y :return: effective radius (total) and effective radii in each plane
tribology.
fball3plates
(ax_force, plate_angle=1.5708)[source]¶Calculate normal force per contact in ball-on-3-plates setup :param ax_force: axial force on rotating ball :param plate_angle: plate angle with respect to each other
(default corresponds to 90 degree)
| Returns: | normal force per contact |
|---|
tribology.
ffourball
(r_1, r_2, ax_force)[source]¶Calculate normal force per contact in 4 ball setup :param r_1: radius rotating ball :param r_2: radius stationary balls :param ax_force: axial force on rotating ball :return: normal force per contact
tribology.
gfourball
(r_1, r_2)[source]¶Geometric parameters of 4-ball setup :param r_1: radius rotating ball :param r_2: radius stationary balls :return: sliding radius (lever arm) on rotating ball, contact angle in rad
tribology.
meff
(e_1, nu_1, e_2, nu_2)[source]¶Effective Young’s modulus according to Hertzian contact theory :param e_1: young’s modulus body 1 :param nu_1: poisson ratio body 1 :param e_2: young’s modulus body 2 :param nu_2: poisson ratio body 2 :return:
tribology.
profball
(x_axis, r_ball)[source]¶Generate a 2D ball profile based on ball radius and ball axis
| Parameters: |
|
|---|---|
| Returns: | vector containing profile heights along x_axis |
tribology.
profrevolve
(prof_2d, y_axis, y_diam)[source]¶creates a 3d profile by revolving a 2D profile around the central axis of a body :param prof_2d: 2d profile vector containing profile heights :param y_axis: vector containing coordinate points for which to calculate
profile heights in y-direction
| Parameters: | y_diam – diameter around which to revolve prof_2d |
|---|---|
| Returns: |
tribology.
radpersec2rpm
(vel)[source]¶Convert from rpm to rad/s :param vel: velocity in rad/s :return: velocity in rpm
tribology.
rball3plates
(r_ball, plate_angle=1.5708)[source]¶Sliding radius (lever arm) for ball-on-3-plates setup :param r_ball: radius of rotating ball :param plate_angle: plate angle with respect to ball in rad
(default corresponds to 45 degree)
| Returns: | sliding radius |
|---|
tribology.
reff
(r_1, r_2)[source]¶Effective radius according to Hertzian contact theory :param r_1: radius 1 :param r_2: radius 2 :return: reduced (effective) radius
tribology.
refix
(value, p_in='', p_out='')[source]¶Convert between different SI unit prefixes :param value: value to convert :param p_in: input SI unit prefix :param p_out: output SI unit prefix :return: value converted to new unit prefix
tribology.
rpm2radpersec
(vel)[source]¶Convert from rpm to rad/s :param vel: velocity in rpm :return: velocity in rad/s
tribology.
srr
(vel_1, vel_2)[source]¶Calculate the slide-to-roll ratio (srr) in a tribological contact :param vel_1: velocity 1 :param vel_2: velocity 2 :return: slide-to-roll ratio


Animal Adoptions
Type of Animal
Dogs
Cats
Foxes
Click Picture for Dogs
Click Picture for Cats
Click Picture for Foxes


:: com :: sun :: star :: accessibility ::
|
| interface XAccessibleAction |
|
- Description
- Implement this interface to give access to actions that can be executed
for accessible objects.
Every accessible object that can be manipulated beyond its methods
exported over the accessibility API should support this interface to
expose all actions that it can perform. Each action can be performed or
be queried for a description or associated key bindings.
- Since
- OOo 1.1.2
- Developers Guide
- Accessibility - XAccessibleAction
|
| Methods' Details |
getAccessibleActionCount
| long |
| getAccessibleActionCount(); |
- Description
- Returns the number of accessible actions available in this object.
If there are more than one, the first one is considered the
"default" action of the object.
- Returns
- The returned value of the number of actions is zero if there are
no actions.
|
|
doAccessibleAction
- Description
- Perform the specified Action on the object.
- Parameter nIndex
- This index specifies the action to perform. If it lies outside
the valid range false is returned and no action is performed.
- Returns
- Returns true if the action was successfully performed. If
the action could not be performed successfully false is
returned.
- Throws
- IndexOutOfBoundsException
If no action with the given index exists then an
::com::sun::star::lang::IndexOutOfBoundsException
exception is thrown.
|
|
getAccessibleActionDescription
- Description
- Returns a description of the specified action of the object.
- Parameter nIndex
- This index specifies the action of which to return a
description. If it lies outside the valid range an empty string
is returned.
- Returns
- The returned value is a localized string of the specified action.
- Throws
- IndexOutOfBoundsException
If the given index lies not in the valid range then an
::com::sun::star::lang::IndexOutOfBoundsException
exception is thrown.
|
|
getAccessibleActionKeyBinding
- Description
- Returns a key binding object, if there is one, associated with the
specified action. Note that there can be several alternative key
bindings for an action. See XAccessibleKeyBinding for
more information about how key bindings are represented.
- Parameter nIndex
- This index specifies the action of which to return the key
binding.
- Returns
- The returned object describes a set of key bindings associated
with the specified action.
- Throws
- IndexOutOfBoundsException
if the given index is not valid.
|
|
Top of Page
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


Apache Flex® is completely open-source. Apache Flex® is an Apache project, and is released under the Apache License, version 2.0, so you know it is compatible with your business needs. Plus, it is backed by the Apache Community for updates, support and help.
Read MoreBuild applications that target all browsers by leveraging the Adobe Flash Player and JavaScript, make desktop application by leveraging the Adobe Integrated Runtime (Adobe AIR) or create powerful, cross-platform mobile applications that target Apple iPods, iPhones, iPads, Android based smartphones and tablets, and Blackberry Playbook devices.
Read MoreA selection of the many desktop and mobile applications written with Flex.
Proud of your Flex application? You can easily submit a request to have it shown here.
Read MoreUtilize the tools you are already familar with. Apache Flex® utilizes MXML for layout and AS3 (an ECMAScript based language like JavaScript) for coding. Use the Eclipse-based IDEs like Adobe Flash Builder and FDT or use IntelliJ IDEA or any text editor to make your applications.
Read More


Around 1938 Frank Benford, a physicist at the General Electrics research laboratories, observed that logarithmic tables were more worn within first pages: was this casual or due to an actual prevalence of numbers near 1 as first digits?
Starting from this intuition/question, Benford tested the hypothesis against 30 populations of data, finally coming to what is known as the Benford Law:
That is to say that using the Benford Law is possible to make a prediction about the expected distribution of a population of data, in term of recurrence of numbers from 1 to 9 as first digits.
The prediction is made in term of probability, and is calculated using the following formula:
You can also calculate the conditional probability of having two numbers as the first two digits:
A typical “Benford Distribution” looks really left skewed, having the first two numbers nearly the 50% of probability of being the first digit.
Until a certain point in mathematical history, Benford’s Law was regarded as a bizzare feature of some populations of data.
Something really amusing, but not really useful.
Eventually, mainly due to the meritory work of the mathematicianMark Nigrini, Benford’s law began to be used for practical purposes, and more precisely for Fraud Analytics purposes.
The idea of using Benford Law for Fraud Analytics purposes is based on one of the main assumptions in Fraud Analytics:
“if something is behavouring differently from what it should, it could be due to fraud.”
In the case of Benford’s Law the aim of using it for catching fraud is to verify if the law is respected within the population and if not, wich elements are not respecting it.
Of course, as is always the case for fraud analytics, the anomaly could be due to human error, at least for some of the anomalies ( i.e. false alarm).
Nevertheless, Benford-based fraud analysis has proven to be a very effective tool for detecting fraud, especially considering the non compliance as a red-flag on the data integrity.
As pointed out by Durtschi,Hillison and Pacini, you have to be cautious when using Benford’s Law.
Particularly, Benford’s Law is unlikely to be useful in the following cases:
| Data set is comprised of assigned numbers | Check numbers, invoice numbers, zip codes |
| Numbers that are influenced by human thought | Prices set at psychological thresholds ($1.99), ATM withdrawals |
| Accounts with a large number of firm-specific numbers | An account specifically set up to record $100 refunds |
| Accounts with a built in minimum or maximum | Set of assets that must meet a threshold to be recorded |
| Where no transaction is recorded | Thefts, kickbacks, contract rigging |
Because I am getting used to do it ( and also because my readers seems to find it useful) I developed a lean shiny app in R, that let’s you play around with Bendford law, loading your own population and looking for Benford’s law compliance ( no worry, a demo dataset is also provided).
BenfordeR’s main feature includes:
custom dataset upload
number of first digits to test option
suspected records higlight ( se below ’detecting suspected records)
##Some code specs ( if you are interested in)
Complete, and commented, Rstudio Project is given on GitHub, but I would like to point out some code details in the following lines.
BenfordeR is based on benford.analysis package, a well documented package that lets you simply perform a Benford analysis, using a single function: benford().
benford_obj = reactive({benford(data(),input$digits)})
benford()
function returns a benford objects that can be easily visualised using the plot function:
plot(benford_obj())
Finally, in order to allow the user to easily discover wich records are causing the anomaly, BenfordeR selects the first three digits in term of deviance from the expected recurrence and subset the user dataset looking for these digits:
output$benford_suspect = renderDataTable({
digits= left(data(),input$digits) # extract n digits from the data() table, using the left function
data_output= data.frame(data(),digits)# join the digits with the dataset
suspects= suspectsTable(benford_obj()) # this could be improved using benford_table()
suspects= suspects[1:3,] #see above
suspects_digits= (as.character(suspects$digits))
data_suspected = subset(data_output,as.character(data_output[,2])%in% suspects_digits)}) # filter the data based on first three suspected digits
I approached Benford’s Law as a part of my Internal Audit job and as a part of my bachelor’s thesis.
More precisely, I am currently developing a fraud-scoring algorithm that take advantage from different anomaly-detection algorithms.
Walking along this path, I have further developed BenfordeR as a “module” within the fraud-scoring algorithim and the related Shiny App. The result of this development is Afraus, an unsupervised fraud detection algorithm. Find out more on Afraus reading the dedicated post.


Wired Xbox 360 Controller
The Xbox 360 Controller features an extended nine-foot cable and a comfortable ergonomic design. The centralized, glowing Xbox Guide Button grants you quick access to your digital movie, music, and games libraries.
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{% set suppress_feedback = true %} {% extends '_layouts/layout.html' %} {% block page_title %}{% endblock %} {% block body_css_classes %}nhsuk-frontend{% endblock %} {% block content %}
We couldn’t send your details.
A&E (accident and emergency)
Leeds Teaching Hospitals NHS Trust
Great George Street
Leeds
LS1 3EX


Class BackgroundThreads (2.9.0)
A object representing the background threads available to a Client.
Functions
cq() const
The completion queue used for the background operations.
| Returns | |
|---|---|
| Type | Description |
CompletionQueue |
A object representing the background threads available to a Client.
The completion queue used for the background operations.
| Returns | |
|---|---|
| Type | Description |
CompletionQueue |


| Summary Item | Total | Failed |
|---|---|---|
| Requests | 16 | 0 |
| Prerequest Scripts | 16 | 0 |
| Test Scripts | 32 | 0 |
| Assertions | 21 | 0 |
| Skipped Tests | 0 | - |
| Header Name | Header Value |
|---|---|
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 59d19b30-0a10-464f-8661-f864edd45789 |
| Host | localhost:20001 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Header Name | Header Value |
|---|---|
| Server | fasthttp |
| Date | Thu, 18 Feb 2021 22:13:03 GMT |
| Content-Type | application/json |
| Content-Length | 108 |
| Traceparent | 00-eb0f72e0334b127dc4ca2ecff82b9b7e-15a9a84e21c7cbcb-00 |
{"my-secret":"“If you want to keep a secret, you must also hide it from yourself. -- George Orwell, 1984"}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| http status ok | 1 | 0 | 0 |
| can read secret | 1 | 0 | 0 |
| Total | 2 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 6c387cbc-8dde-4b5f-b185-cb34325c3565 |
| Host | localhost:19999 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Header Name | Header Value |
|---|---|
| Server | fasthttp |
| Date | Thu, 18 Feb 2021 22:13:03 GMT |
| Content-Type | application/json |
| Content-Length | 108 |
| Traceparent | 00-c9913f66e288470e6bed82c7814aa523-25bc51185b9e71e7-00 |
{"my-secret":"“If you want to keep a secret, you must also hide it from yourself. -- George Orwell, 1984"}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| http status ok | 1 | 0 | 0 |
| can read secret | 1 | 0 | 0 |
| Total | 2 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 6fb955a1-257a-4b2a-8699-87fb69863fb7 |
| Host | localhost:20002 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Header Name | Header Value |
|---|---|
| Server | fasthttp |
| Date | Thu, 18 Feb 2021 22:13:04 GMT |
| Content-Type | application/json |
| Content-Length | 108 |
| Traceparent | 00-b0ce360f14d958b64147dc80849bd310-09d5f5d6853808d6-00 |
{"my-secret":"“If you want to keep a secret, you must also hide it from yourself. -- George Orwell, 1984"}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| http status ok | 1 | 0 | 0 |
| can read secret | 1 | 0 | 0 |
| Total | 2 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 3ba673e5-8e5b-4959-b1dc-1fa59aeaa06b |
| Host | localhost:20003 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Header Name | Header Value |
|---|---|
| Server | fasthttp |
| Date | Thu, 18 Feb 2021 22:13:05 GMT |
| Content-Type | application/json |
| Content-Length | 108 |
| Traceparent | 00-b40bbe90902be3476b51bb106ee8b82a-4ef57ab96b5c9f60-00 |
{"my-secret":"“If you want to keep a secret, you must also hide it from yourself. -- George Orwell, 1984"}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| http status ok | 1 | 0 | 0 |
| can read secret | 1 | 0 | 0 |
| Total | 2 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 48c76690-00b9-469e-b0b1-96dbf761a1aa |
| Host | localhost:20004 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Header Name | Header Value |
|---|---|
| Server | fasthttp |
| Date | Thu, 18 Feb 2021 22:13:05 GMT |
| Content-Type | application/json |
| Content-Length | 108 |
| Traceparent | 00-2512ba66644fa215601cba88b9ed9282-8a038349eeaf800b-00 |
{"my-secret":"“If you want to keep a secret, you must also hide it from yourself. -- George Orwell, 1984"}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| http status ok | 1 | 0 | 0 |
| can read secret | 1 | 0 | 0 |
| Total | 2 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 423ac75f-b72d-489d-a17d-095b237f22e6 |
| Host | localhost:20005 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Header Name | Header Value |
|---|---|
| Server | fasthttp |
| Date | Thu, 18 Feb 2021 22:13:06 GMT |
| Content-Type | application/json |
| Content-Length | 108 |
| Traceparent | 00-3152ac3ad72c082dbf083f3d21b6996a-4196b784b0e83ccc-00 |
{"my-secret":"“If you want to keep a secret, you must also hide it from yourself. -- George Orwell, 1984"}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| http status ok | 1 | 0 | 0 |
| can read secret | 1 | 0 | 0 |
| Total | 2 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| content-type | application/graphql |
| Content-Type | application/json |
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 62f4bcb3-b524-47ba-be02-f4a31b3071f2 |
| Host | localhost:9999 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Content-Length | 184 |
query {
mybasket{
customerId
basketItemId
productId
quantity
inStock
unitPrice
name
description
}
}
| Header Name | Header Value |
|---|---|
| Date | Thu, 18 Feb 2021 22:13:11 GMT |
| Content-Type | application/json; charset=utf-8 |
| Server | Kestrel |
| Transfer-Encoding | chunked |
{"data":{"mybasket":[{"customerId":1,"basketItemId":1,"productId":1,"quantity":2,"inStock":50,"unitPrice":1.5,"name":"Milk","description":"Some Milk"},{"customerId":1,"basketItemId":2,"productId":2,"quantity":3,"inStock":100,"unitPrice":2.5,"name":"Cheese","description":"Some Cheese"}]}}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| can read basket quantity | 1 | 0 | 0 |
| Total | 1 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| content-type | application/graphql |
| Content-Type | application/json |
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 6b84a0b0-91d1-4a04-88fa-72920b0457aa |
| Host | localhost:9999 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Content-Length | 129 |
query {
basketItem(id:1){
customerId
basketItemId
productId
quantity
}
}
| Header Name | Header Value |
|---|---|
| Date | Thu, 18 Feb 2021 22:13:11 GMT |
| Content-Type | application/json; charset=utf-8 |
| Server | Kestrel |
| Transfer-Encoding | chunked |
{"data":{"basketItem":{"customerId":1,"basketItemId":1,"productId":1,"quantity":2}}}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| can read basket quantity | 1 | 0 | 0 |
| Total | 1 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| content-type | application/graphql |
| Content-Type | application/json |
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 6217df5e-6a81-40ba-9225-3f9337ea427a |
| Host | localhost:9999 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Content-Length | 136 |
query {
basketForCustomer(id:1){
customerId
basketItemId
productId
quantity
}
}
| Header Name | Header Value |
|---|---|
| Date | Thu, 18 Feb 2021 22:13:11 GMT |
| Content-Type | application/json; charset=utf-8 |
| Server | Kestrel |
| Transfer-Encoding | chunked |
{"data":{"basketForCustomer":[{"customerId":1,"basketItemId":1,"productId":1,"quantity":2},{"customerId":1,"basketItemId":2,"productId":2,"quantity":3}]}}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| can read basket quantity | 1 | 0 | 0 |
| Total | 1 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| content-type | application/graphql |
| Content-Type | application/json |
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | a5d289c3-bc8d-4a5e-ab23-2d029c8aed0f |
| Host | localhost:9999 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Content-Length | 189 |
mutation {
upsertBasketItem(input: {id: 56 customerId: 1 productId: 1 quantity: 42}){
id
quantity
productId
customerId
}
}
| Header Name | Header Value |
|---|---|
| Date | Thu, 18 Feb 2021 22:13:11 GMT |
| Content-Type | application/json; charset=utf-8 |
| Server | Kestrel |
| Transfer-Encoding | chunked |
{"data":{"upsertBasketItem":{"id":56,"quantity":42,"productId":1,"customerId":1}}}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| upsert test | 1 | 0 | 0 |
| Total | 1 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| content-type | application/graphql |
| Content-Type | application/json |
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 97e6ec99-5ebf-4da3-9dd7-eba573ba0050 |
| Host | localhost:10001 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Content-Length | 129 |
query {
basketItem(id:1){
customerId
basketItemId
productId
quantity
}
}
| Header Name | Header Value |
|---|---|
| Date | Thu, 18 Feb 2021 22:13:11 GMT |
| Content-Type | application/json; charset=utf-8 |
| Server | Kestrel |
| Transfer-Encoding | chunked |
{"data":{"basketItem":{"customerId":1,"basketItemId":1,"productId":1,"quantity":2}}}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| can read basket quantity | 1 | 0 | 0 |
| Total | 1 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| content-type | application/graphql |
| Content-Type | application/json |
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 6ef271ee-c04f-4318-bfab-008664db3612 |
| Host | localhost:10001 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Content-Length | 136 |
query {
basketForCustomer(id:1){
customerId
basketItemId
productId
quantity
}
}
| Header Name | Header Value |
|---|---|
| Date | Thu, 18 Feb 2021 22:13:11 GMT |
| Content-Type | application/json; charset=utf-8 |
| Server | Kestrel |
| Transfer-Encoding | chunked |
{"data":{"basketForCustomer":[{"customerId":1,"basketItemId":1,"productId":1,"quantity":2},{"customerId":1,"basketItemId":2,"productId":2,"quantity":3},{"customerId":1,"basketItemId":56,"productId":1,"quantity":42}]}}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| can read basket quantity | 1 | 0 | 0 |
| Total | 1 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| content-type | application/graphql |
| Content-Type | application/json |
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 169acfe7-2703-45f8-989f-9239f5da430a |
| Host | localhost:10001 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Content-Length | 189 |
mutation {
upsertBasketItem(input: {id: 56 customerId: 1 productId: 1 quantity: 42}){
id
quantity
productId
customerId
}
}
| Header Name | Header Value |
|---|---|
| Date | Thu, 18 Feb 2021 22:13:11 GMT |
| Content-Type | application/json; charset=utf-8 |
| Server | Kestrel |
| Transfer-Encoding | chunked |
{"data":{"upsertBasketItem":{"id":56,"quantity":42,"productId":1,"customerId":1}}}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| upsert test | 1 | 0 | 0 |
| Total | 1 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| Content-Type | application/json |
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | 8124346a-9535-4524-9228-cf7361fe9519 |
| Host | localhost:10003 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Content-Length | 51 |
{ inventory(id:1) {
quantity
}}
| Header Name | Header Value |
|---|---|
| Date | Thu, 18 Feb 2021 22:13:11 GMT |
| Content-Type | application/json; charset=utf-8 |
| Server | Kestrel |
| Transfer-Encoding | chunked |
{"data":{"inventory":{"quantity":50}}}
| Header Name | Header Value |
|---|---|
| Content-Type | application/json |
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | aa911d54-21e7-44c0-afe4-0131ddac6291 |
| Host | localhost:10003 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Content-Length | 123 |
mutation {
reserve(request: {productId: 1 quantity: 1}) {
productId
quantity
}
}
| Header Name | Header Value |
|---|---|
| Date | Thu, 18 Feb 2021 22:13:11 GMT |
| Content-Type | application/json; charset=utf-8 |
| Server | Kestrel |
| Transfer-Encoding | chunked |
{"data":{"reserve":{"productId":1,"quantity":49}}}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| expect correct quantity | 1 | 0 | 0 |
| Total | 1 | 0 | 0 |
| Test Name | Assertion Error |
|---|
| Header Name | Header Value |
|---|---|
| Content-Type | application/json |
| User-Agent | PostmanRuntime/7.26.10 |
| Accept | */* |
| Cache-Control | no-cache |
| Postman-Token | a099164f-9280-498d-9313-050f477f88eb |
| Host | localhost:10003 |
| Accept-Encoding | gzip, deflate, br |
| Connection | keep-alive |
| Content-Length | 124 |
mutation {
reserve(request: {productId: 1 quantity: -1}) {
productId
quantity
}
}
| Header Name | Header Value |
|---|---|
| Date | Thu, 18 Feb 2021 22:13:11 GMT |
| Content-Type | application/json; charset=utf-8 |
| Server | Kestrel |
| Transfer-Encoding | chunked |
{"data":{"reserve":{"productId":1,"quantity":50}}}
| Name | Passed | Failed | Skipped |
|---|---|---|---|
| expect correct quantity | 1 | 0 | 0 |
| Total | 1 | 0 | 0 |
| Test Name | Assertion Error |
|---|


Welcome To Monte Carlo
Monte Carlo Resort brings a refreshingly unique resort experience to Gonsua Beach in Majorda, just 20 minutes from Goa Dabolim International Airport. Set amidst the serene landscape of lush, verdant rice plantations flowing towards the Arabian Sea, relaxation reigns
at this Goa resort. Enter a sanctuary of contemporary elegance inspired by traditional Goan design − steeply pitched roofs, ceiling high columns, cool verandas and tranquil courtyards,
setting us apart from other luxury hotels in Bali. Whether enjoying an intimate couple's retreat or a getaway for the entire family, the 153 rooms and suites at this Goa resort offer havens of space, comfort and serenity, while the resort’s new Diwa Club is an enclave of exclusivity,
boasting its own lap pool with an open air Jacuzzi and hot tub.


When is Sunderland vs Burton Albion, is it on TV, what time is kick-off and who is in the teams?
The Black Cats welcome the Brewers to the Stadium of Light on Tuesday - here is how you can follow it live
by Sean McCormickSunderland welcome Burton Albion to the Stadium of Light on Tuesday as they look to kickstart their promotion charge.
Phil Parkinson's difficult start to life as Sunderland boss continued on Saturday as they stumbled to a 1-1 draw at home to Coventry.
Parkinson has won just two of his opening 10 games as Black Cats boss and the draw left Sunderland in tenth place in the League One table - eight points adrift of the automatic promotion places and 13 points behind league leaders Wycombe.
But a win over Burton on Tuesday would put Sunderland back into the play-off picture and they welcome a Brewers side that sit in 15th place in the League One table.
Nigel Clough's travel to Wearside out of form themselves and are without a win in their last seven games in all competitions.
When is Sunderland vs Burton Albion?
Sunderland take on Burton Albion on Tuesday, November 26. It is one of four League One fixtures taking place on Tuesday evening.
Is Sunderland vs Burton Albion on TV? Can I follow it live?
It is not on TV but the game will likely be streamed on Sunderland's official website. Details are yet to be confirmed, though.
Alternatively, you can follow all the action in our live match blog with team news, live updates, reaction and analysis from our writers at the Stadium of Light.
Can you still buy tickets?
Tickets are still available and can be purchased here.
What are the injury concerns? Who is in the teams?
Sunderland are likely to be without Lynden Gooch and Charlie Wyke through injury. We will get a full fitness update in Monday's pre-match press conference.
Sunderland likely XI: Burge; O'Nien, Willis, Lynch, Hume; Dobson, Leadbitter, Power; Maguire, McGeady; Grigg
Burton likely XI: O'Hara; Brayford, O'Toole, Nartey, Wallace; Edwards, Quinn, Fraser; Sarkic, Templeton; Akins
Who is the ref?
Shrewsbury official Robert Lewis will be the man in the middle on Tuesday. It is the first time he has officiated a Sunderland game this season.
What are the bookies saying?
Sunderland evens
Burton 3/1
Draw 11/4


Security in autonomous vehicles and transportation is an arising research focus of SPQR. By studying autonomous vehicles' susceptibility to various physical attacks and proposing corresponding mitigations, we contribute to the autonomous vehicles industry and help ensure the safety of passengers in future transportation systems.
In this work, we perform the first security study of LiDAR-based perception in Autonomous Vehicle settings. We consider LiDAR spoofing attacks as the threat model and set the attack goal as spoofing obstacles close to the front of a victim AV. We find that blindly applying LiDAR spoofing is insufficient to achieve this goal due to the machine learning-based object detection process. Thus, we then explore the possibility of strategically controlling the spoofed attack to fool the machine learning model. Utilizing that, we construct and evaluate two attack scenarios that may damage road safety and mobility.


--- layout: post title: Traffic Map Mk 2 date: '2018-08-04T11:38:34-07:00' tags: - trafficmap - traffic - transit - programming - software - javascript tumblr_url: http://beekley.xyz/post/176630478486/traffic-map-mk-2 ---
Updated to use contour lines and just generally be better. WIP here: https://github.com/beekley/TrafficMap/tree/refactor
Image above is Google Maps’ best guess for drive time to Alhambra at 8 am Wednesday morning.


Name: catalogue
Type: Executable
Status: Core
General: Some text explaining what the command as a whole is doing


{% extends "base_generic.html" %} {% block content %}
Create New
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EMOTIONET is a CNN hierarchal approach to try to impove results for facial and emotional classification. This project stemmed out from my
master's thesis work for my degree at $University. I further expanded the research through tensorflow's research cloud with the help of TPUs.
When the paper is posted online, I will link to it here.
BIG thank you to tensorflow research cloud for making this happen. I have included many links in the nav bar, including my own code for TPU Pods and a custom tensorflow build, and a raspberry pi application of the paper NN I have done!


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---
layout: page
title: RLCS Predictions
sidebar_link: false
permalink: /blog/rlcs_predictions_previous_week
---
Regionals Predictions (as of the end of week 7)
| End of Season/Regionals Probabilities |
| TEAM |
Auto-Relegated |
Promotion Tourney |
Make Regionals |
Make Semis |
Make Final |
Win Final |
| Renault Vitality |
- |
- |
✓ |
>99% |
60% |
35% |
| Dignitas |
- |
- |
✓ |
97% |
45% |
21% |
| Team Reciprocity |
- |
- |
✓ |
58% |
29% |
14% |
| FC Barcelona |
- |
- |
✓ |
59% |
26% |
12% |
| mousesports |
- |
- |
✓ |
44% |
21% |
9% |
| Veloce Esports |
- |
- |
✓ |
43% |
20% |
9% |
| Team Singularity |
- |
16% |
- |
- |
- |
- |
| Endpoint |
- |
84% |
- |
- |
- |
- |
| Team SoloMid |
18% |
82% |
- |
- |
- |
- |
| AS Monaco |
82% |
18% |
- |
- |
- |
- |
| EU |
| End of Season/Regionals Probabilities |
| TEAM |
Auto-Relegated |
Promotion Tourney |
Make Regionals |
Make Semis |
Make Final |
Win Final |
| Spacestation Gaming |
- |
- |
✓ |
99% |
53% |
30% |
| G2 Esports |
- |
- |
✓ |
88% |
49% |
27% |
| NRG Esports |
- |
- |
✓ |
79% |
40% |
18% |
| Susquehanna Soniqs |
- |
- |
✓ |
80% |
32% |
12% |
| Cloud9 |
- |
- |
89% |
30% |
15% |
8% |
| Ghost Gaming |
- |
- |
90% |
21% |
9% |
4% |
| Pittsburgh Knights |
- |
4% |
21% |
3% |
2% |
<1% |
| eUnited |
- |
96% |
- |
- |
- |
- |
| Rogue |
50% |
50% |
- |
- |
- |
- |
| Flight |
50% |
50% |
- |
- |
- |
- |
| NA |
Regionals Predictions (as of the end of week 6)
| End of Season/Regionals Probabilities |
| TEAM |
Auto Relegated |
Promotion Tourney |
Make Regionals |
Make Semis |
Make Final |
Win Final |
| Renault Vitality |
- |
- |
100% |
96% |
61% |
39% |
| Dignitas |
- |
- |
98% |
71% |
32% |
15% |
| mousesports |
- |
- |
95% |
58% |
28% |
12% |
| FC Barcelona |
- |
- |
98% |
65% |
28% |
12% |
| Veloce Esports |
- |
- |
99% |
58% |
27% |
11% |
| Team Reciprocity |
- |
- |
97% |
49% |
23% |
10% |
| Endpoint |
<1% |
27% |
12% |
2% |
<1% |
<1% |
| Team SoloMid |
16% |
84% |
- |
- |
- |
- |
| Team Singularity |
2% |
72% |
- |
- |
- |
- |
| AS Monaco |
82% |
18% |
- |
- |
- |
- |
| EU |
| End of Season/Regionals Probabilities |
| TEAM |
Auto Relegated |
Promotion Tourney |
Make Regionals |
Make Semis |
Make Final |
Win Final |
| G2 Esports |
- |
- |
100% |
91% |
52% |
30% |
| Spacestation Gaming |
- |
- |
100% |
94% |
53% |
30% |
| NRG Esports |
- |
- |
100% |
64% |
33% |
16% |
| Ghost Gaming |
- |
- |
>99% |
59% |
30% |
13% |
| Susquehanna Soniqs |
- |
- |
100% |
82% |
30% |
10% |
| Cloud9 |
<1% |
24% |
44% |
5% |
1% |
<1% |
| Pittsburgh Knights |
2% |
32% |
40% |
4% |
1% |
<1% |
| eUnited |
5% |
57% |
12% |
<1% |
<1% |
<1% |
| Rogue |
31% |
53% |
5% |
<1% |
<1% |
<1% |
| Flight |
62% |
34% |
<1% |
<1% |
<1% |
<1% |
| NA |


Pontoon is a translation management system used and developed by the Mozilla localization community. It specializes in open source localization that is driven by the community and uses version-control systems for storing translations.
Pontoon is a simple and intuitive tool that requires little technical skills to use it. Each language has its own team of localizers. Join one, find a project you'd like to contribute to, and you're ready to start contributing!
Show it to your friends as it lands in product
From the ground up, Pontoon has been designed as the tool that brings all your team's localization tasks together in one place. All the functionality and services you need are seamlessly integrated into a single platform.
Machine translation
Mass actions
Localization dashboards
Target dates and priorities
Notifications
Sync with Git and Mercurial
Now that you know what Pontoon is, come on in!
Start Localizing NowWant to learn more?
Take a Tour


--- layout: post esbma_id: 3026 title: Announcing Zumero SQLite for Xamarin date: 2013-04-14 11:00:00 ---
I am pleased to announce that Zumero SQLite is now available in the Xamarin Component Store. It's free, and it supports Android and iOS.
Zumero SQLite for Xamarin starts with the core "replicate and sync" functionality from the Zumero Client SDK and adds:
ADO.NET -- Familiar C# API for SQL developers. (provided by System.Data.SQLite, which is maintained by the same folks who develop SQLite itself)
Full-database encryption -- Critical piece of the "replicate and sync" story. Mobile devices get lost. (provided by the excellent SQLCipher library)
Painless setup -- Install the component and you've got everything you need. (provided by the neato component store feature of Xamarin Studio)
In some ways, the core of the Zumero Client SDK is not very easy to use. That is intentional. It is designed to be the sort of SDK that leaves many things as the responsibility of the app (or the next layer up).
It doesn't actually include SQLite itself, since the app might care about which version of SQLite it wants, or how it needs to be compiled.
It doesn't include any page-level encryption support, since it doesn't know whether the app wants to use SQLCipher or the SQLite Encryption Extension or something else.
It plugs into SQLite using C, because that's the native language that SQLite uses for its API.
Power users and control freaks need this kind of SDK. And it comes first, since everything else is built on top of it. But most users want an experience that is more "comfy".
They don't want to think about versions of SQLite or compile options for same.
They don't want to choose an encryption library and figure out how to integrate it with their app.
They don't want to write their mobile app in C.
The Zumero Client SDK actually does include some carpeting and furniture on top of that cold, hard C floor. For Android developers using Java, it presents the android.database.sqlite API. And for iOS developers using Objective-C, it offers a wrapper that lets you work with things that have NS prefixes.
(Which reminds me, check out our iOS wiki app sample on GitHub.)
Anyway, these efforts are just the beginning. Our direction is toward "comfy", and we are moving fast.
This component for Xamarin is a step forward, and I think it is an important one.
This new component includes three sample apps, all of which are modified versions of samples provided by Xamarin.
Data (iOS, based on https://github.com/xamarin/monotouch-samples/tree/master/Data)
Notepad (Android, based on https://github.com/xamarin/monodroid-samples/tree/master/NotePad-Mono.Data.Sqlite)
Tasky (cross-platform, based on https://github.com/xamarin/mobile-samples/tree/master/Tasky)
The Data and Notepad samples have simply been ported to System.Data.SQLite (which involved very few changes).
The Tasky sample goes a bit further and adds a very simple ability to sync the task list.
I am in Austin for Xamarin's Evolve conference, which starts today. Xamarin is doing some of the coolest stuff in mobile development today. We are thrilled to be a part of it.


Treebank Statistics: UD_Old_Irish-DipSGG: POS Tags: PART
There are 13 PART
lemmas (6%), 18 PART
types (6%) and 32 PART
tokens (8%).
Out of 16 observed tags, the rank of PART
is: 6 in number of lemmas, 5 in number of types and 3 in number of tokens.
The 10 most frequent PART
lemmas: a, fo, so, ní, sin, ad, do, í, in, no
The 10 most frequent PART
types: a, fo, sin, so, ni, ní, Do, at, fu, hí
The 10 most frequent ambiguous lemmas: a (DET 6, PART 5, PRON 5), fo (PART 5, ADP 1), so (PART 5, PRON 2), do (ADP 10, PART 2, PRON 1), in (DET 22, PART 1), ná (SCONJ 3, CCONJ 1, PART 1)
The 10 most frequent ambiguous types: a (PART 6, DET 4, PRON 4), fo (PART 3, ADP 1), sin (PART 3, DET 1), ní (AUX 2, PART 2), hí (ADP 1, PART 1), in (DET 9, PART 1)
- a
- fo
- sin
- ní
- hí
- in
Morphology
The form / lemma ratio of PART
is 1.384615 (the average of all parts of speech is 1.264574).
The 1st highest number of forms (3) was observed with the lemma “so”: sa, so, ᚄᚑ.
The 2nd highest number of forms (2) was observed with the lemma “ad”: a, at.
The 3rd highest number of forms (2) was observed with the lemma “do”: Do, th.
PART
occurs with 4 features: PartType (20; 63% instances), PronType (8; 25% instances), Polarity (4; 13% instances), Prefix (1; 3% instances)
PART
occurs with 8 feature-value pairs: PartType=Aug
, PartType=Dct
, PartType=Rel
, PartType=Vb
, PartType=Voc
, Polarity=Neg
, Prefix=Yes
, PronType=Dem
PART
occurs with 8 feature combinations.
The most frequent feature combination is PartType=Vb
(11 tokens).
Examples: fo, Do, a, at, fu, in, no, th
Relations
PART
nodes are attached to their parents using 7 different relations: compound:prt (12; 38% instances), amod (9; 28% instances), case:voc (5; 16% instances), advmod (3; 9% instances), mark (1; 3% instances), nmod (1; 3% instances), root (1; 3% instances)
Parents of PART
nodes belong to 7 different parts of speech: VERB (16; 50% instances), NOUN (9; 28% instances), ADJ (2; 6% instances), PROPN (2; 6% instances), PART (1; 3% instances), PRON (1; 3% instances), (1; 3% instances)
22 (69%) PART
nodes are leaves.
8 (25%) PART
nodes have one child.
1 (3%) PART
nodes have two children.
1 (3%) PART
nodes have three or more children.
The highest child degree of a PART
node is 4.
Children of PART
nodes are attached using 6 different relations: obj:infx (6; 43% instances), det (4; 29% instances), acl:relcl (1; 7% instances), advmod (1; 7% instances), amod (1; 7% instances), case (1; 7% instances)
Children of PART
nodes belong to 6 different parts of speech: PRON (6; 43% instances), DET (4; 29% instances), ADP (1; 7% instances), ADV (1; 7% instances), PART (1; 7% instances), VERB (1; 7% instances)


Application
Interfaces, Classes, Traits and Enums
- HTTPClient
- ResourceInterface
- DirectDestinations
- A namespaced client for the "/v1/airport/direct-destinations" endpoints.
- OnTime
- A namespaced client for the "/v1/airport/predictions/on-time" endpoints.
- Predictions
- A namespaced client for the "/v1/airport/predictions" endpoints.
- Airport
- A namespaced client for the "/airport" endpoints.
- Amadeus
- The Amadeus API client. To initialize, use the builder as follows:
- AmadeusBuilder
- FlightOrders
- A namespaced client for the "/v1/booking/flight-orders" endpoints.
- HotelBookings
- A namespaced client for the "/v1/booking/hotel-bookings" endpoints.
- Booking
- A namespaced client for the "/booking" endpoints.
- AccessToken
- A memoized Access Token, with the ability to auto-refresh when needed.
- BasicHTTPClient
- The HTTP part of the Amadeus API client.
- Request
- An object containing all the details of the request made, including the host, path, port, params, and headers. Generally this object can be accessed as part of an API response, and can be used to debug the API call made.
- Response
- A generic response as received from an API call. Contains the status code, body, and parsed JSON (if any).
- Configuration
- Constants
- Covid19AreaReport
- A namespaced client for the "/v1/duty-of-care/diseases/covid19-area-report" endpoints.
- Diseases
- A namespaced client for the "/v1/duty-of-care/diseases" endpoints.
- DutyOfCare
- A namespaced client for the "/dutyOfCare" endpoints.
- HotelSentiments
- A namespaced client for the "/v2/e-reputation/hotel-sentiments" endpoints.
- EReputation
- A namespaced client for the "/e-reputation" endpoints.
- AuthenticationException
- Inherit __construct() from parent class
- ClientException
- Inherit __construct() from parent class
- NetworkException
- Inherit __construct() from parent class
- NotFoundException
- Inherit __construct() from parent class
- ResponseException
- ServerException
- Inherit __construct() from parent class
- Airlines
- A namespaced client for the "/v1/reference-data/airlines" endpoints.
- Location
- A namespaced client for the "/v1/reference-data/locations/:location_id" endpoints.
- Airports
- A namespaced client for the "/v1/reference-data/locations/airports" endpoints.
- Hotel
- A namespaced client for the "/v1/reference-data/locations/hotel" endpoints.
- ByCity
- A namespaced client for the "/v1/reference-data/locations/hotels/by-city" endpoints.
- ByGeocode
- A namespaced client for the "/v1/reference-data/locations/hotels/by-geocode" endpoints.
- ByHotels
- A namespaced client for the "/v1/reference-data/locations/hotels/by-hotels" endpoints.
- Hotels
- A namespaced client for the "/v1/reference-data/locations/hotels" endpoints.
- Locations
- A namespaced client for the "/v1/reference-data/locations" endpoints.
- RecommendedLocations
- A namespaced client for the "/v1/reference-data/recommended-locations" endpoints.
- ReferenceData
- A namespaced client for the "/referenceData" endpoints.
- Activity
- An Activity-related object as returned by the Tours and Activities API.
- AircraftEquipment
- Sub-resource in FlightExtendedSegment, Leg
- Airline
- An Airline object as returned by the Airline Code Lookup API.
- Area
- Sub-resource in DiseaseAreaReport
- AreaAccessRestriction
- Sub-resource in DiseaseAreaReport
- AreaPolicy
- Sub-resource in DiseaseAreaReport
- AreaRestriction
- Sub-resource in DiseaseAreaReport
- AreaVaccinated
- Sub-resource in DiseaseAreaReport
- Border
- Sub-resource in EntryRestriction
- Co2Emission
- Sub-resource in FlightExtendedSegment
- DatedFlight
- A DatedFlight object as returned by the On-Demand Flight Status API.
- DatedFlightLeg
- Sub-resource in DatedFlight
- DatedFlightSegment
- Sub-resource in DatedFlight
- DatedFlightSegmentPartnership
- Sub-resource in Segment
- DatedInformation
- Sub-resource in AreaAccessRestriction
- DatedQuarantineRestriction
- Sub-resource in AreaAccessRestriction
- DatedTracingApplicationRestriction
- Sub-resource in AreaAccessRestriction
- DeclarationDocuments
- Sub-resource in AreaAccessRestriction
- DelayPrediction
- A DelayPrediction object as returned by the Airport Routes API.
- Description
- Sub-resource in TermAnaCondition
- Destination
- A Destination object as returned by the Airport Routes API.
- DiseaseAreaReport
- A DiseaseAreaReport object as returned by the Travel Restrictions API.
- DiseaseCase
- Sub-resource in DiseaseAreaReport
- DiseaseDataSources
- Sub-resource in DiseaseAreaReport
- DiseaseInfection
- Sub-resource in DiseaseAreaReport
- DiseaseTestingRestriction
- Sub-resource in AreaAccessRestriction
- DiseaseVaccination
- Sub-resource in AreaAccessRestriction
- ElementaryPrice
- Sub-resource in Activity
- EntryRestriction
- Sub-resource in AreaAccessRestriction
- ExitRestriction
- Sub-resource in AreaAccessRestriction
- FareRules
- Sub-resource in FlightOffer
- FlightAdditionalService
- Sub-resource in FlightPrice, etc.
- FlightAdditionalServicesRequest
- Sub-resource in FlightFareDetailsBySegment.
- FlightAllotmentDetails
- Sub-resource in FlightFareDetailsBySegment.
- FlightAvailability
- A FlightAvailability object as returned by the Flight Availabilities Search API.
- FlightAvailabilityClass
- Sub-resource in FlightExtendedSegment
- FlightBaggageAllowance
- Sub-resource in FlightFareDetailsBySegment.
- FlightBookingRequirements
- Sub-resource in FlightOfferPricingOutput, etc.
- FlightDate
- A FlightDate object as returned by the Flight Cheapest Date Search API.
- FlightDateLinks
- Sub-resource in FlightDate.
- FlightDesignator
- Sub-resource in DatedFlight, Partnership
- FlightDestination
- A FlightDestination object as returned by the Flight Inspiration Search API.
- FlightDestinationLinks
- Sub-resource in FlightDestination.
- FlightEndpoint
- Sub-resource in FlightExtendedSegment
- FlightExtendedSegment
- Sub-resource in Itineraries, FlightAvailability, etc.
- FlightFareDetailsBySegment
- Sub-resource in TravelerPricing, etc.
- FlightFee
- Sub-resource in FlightPrice, etc.
- FlightItineraries
- Sub-resource in FlightOffer, etc.
- FlightOffer
- A FlightOffer object as returned by the Flight Offers Search API, Flight Choice Prediction API.
- FlightOfferPricingOutput
- A FlightOfferPricingOutput object as returned by the Flight Offers Price API.
- FlightOfferTax
- Sub-resource in FlightPrice, etc.
- FlightOrder
- A FlightOrder object as returned by the Flight Create Orders API.
- FlightOrderAssociatedRecord
- Sub-resource in FlightOrder.
- FlightPayment
- Optional parameter resource for calling Flight Offer Price API.
- FlightPoint
- Sub-resource in DatedFlight
- FlightPointArrival
- Sub-resource in FlightPoint.
- FlightPointDeparture
- Sub-resource in FlightPoint.
- FlightPointGate
- Sub-resource in Arrival, Departure
- FlightPointTerminal
- Sub-resource in Arrival, Departure
- FlightPointTiming
- Sub-resource in Arrival, Departure
- FlightPointTimingDelay
- Sub-resource in Timing
- FlightPrice
- Sub-resource in FlightOffer, FlightDestination etc.
- FlightPricingOptions
- Sub-resource in FlightOffer, etc.
- FlightStop
- Sub-resource in FlightExtendedSegment
- FlightTourAllotment
- Sub-resource in FlightAvailabilityClass
- GeoCode
- Sub-resource in Hotel, HotelNameAutocomplete, Activity, Location, Area, etc.
- Hotel
- A Hotel object as returned by the Hotel List API.
- HotelAddress
- Sub-resource in Hotel, HotelNameAutocomplete.
- HotelBookingAssociatedRecord
- Sub-resource in HotelBookingLight.
- HotelBookingLight
- A HotelBookingLight object as returned by the Hotel Booking API.
- HotelContent
- Sub-resource in HotelOffers.
- HotelDistance
- Sub-resource in Hotel.
- HotelNameAutocomplete
- A HotelNameAutocomplete object as returned by the Hotel Name Autocomplete API.
- HotelOffer
- Sub-resource in HotelOffers.
- HotelOfferAveragePrice
- Sub-resource in HotelProductPriceVariations.
- HotelOffers
- A HotelOffers object as returned by the Hotel Search API.
- HotelOfferTax
- Sub-resource in HotelProductHotelPrice.
- HotelProductCancellationPolicy
- Sub-resource in HotelProductPolicyDetails.
- HotelProductCheckInOutPolicy
- Sub-resource in HotelProductPolicyDetails.
- HotelProductCommission
- Sub-resource in HotelOffer.
- HotelProductDepositPolicy
- Sub-resource in HotelProductPolicyDetails.
- HotelProductEstimatedRoomType
- Sub-resource in HotelProductRoomDetails.
- HotelProductGuaranteePolicy
- Sub-resource in HotelProductPolicyDetails.
- HotelProductGuests
- Sub-resource in HotelOffer.
- HotelProductHoldPolicy
- Sub-resource in HotelProductPolicyDetails.
- HotelProductHotelPrice
- Sub-resource in HotelOffer.
- HotelProductPaymentPolicy
- Sub-resource in HotelProductGuaranteePolicy, HotelProductDepositPolicy.
- HotelProductPolicyDetails
- Sub-resource in HotelOffer.
- HotelProductPriceVariation
- Sub-resource in HotelProductPriceVariations.
- HotelProductPriceVariations
- Sub-resource in HotelProductHotelPrice.
- HotelProductRateFamily
- Sub-resource in HotelOffer.
- HotelProductRoomDetails
- Sub-resource in HotelOffer.
- HotelSentiment
- A HotelSentiment object as returned by the Hotel Ratings API.
- HotelSentimentDetails
- Sub-resource in HotelSentiment
- Link
- Sub-resource in DiseaseAreaReport
- Links
- Sub-resource in FlightDestination, Location
- Location
- A Location object as returned by the Airport and City Search API, Airport Nearest Relevant API and Travel Recommendations API .
- LocationAddress
- Sub-resource in Location.
- LocationAnalytics
- Sub-resource in Location.
- LocationAnalyticsTravelers
- Sub-resource in LocationAnalytics.
- LocationDistance
- Sub-resource in Location.
- Markup
- Sub-resource in HotelOfferAveragePrice, HotelProductPriceVariation, HotelProductHotelPrice.
- MaskRestriction
- Sub-resource in AreaAccessRestriction
- OnTimePrediction
- An OnTimePrediction object as returned by the Airport On-Time Prediction API.
- OperatingFlight
- Sub-resource in FlightExtendedSegment
- PassengerConditions
- Sub-resource in FlightBookingRequirements.
- QualifiedFreeText
- Sub-resource in HotelOffer, HotelProductRoomDetails, HotelProductCommission, HotelProductCheckInOutPolicy, HotelProductGuaranteePolicy, HotelProductDepositPolicy, HotelProductCancellationPolicy.
- Resource
- TermAndCondition
- Sub-resource in FareRules
- Transportation
- Sub-resource in AreaAccessRestriction
- TravelerAddress
- Sub-resource in TravelerContact
- TravelerContact
- Sub-resource in TravelerElement
- TravelerDocuments
- Sub-resource in TravelerElement
- TravelerElement
- Sub-resource in FlightOrder
- TravelerName
- Sub-resource in TravelerElement
- TravelerPhone
- Sub-resource in TravelerContact
- TravelerPricing
- Sub-resource in FlightOffer, etc.
- ValidityPeriod
- Sub-resource in DiseaseTestingRestriction
- Flights
- A namespaced client for the "/v2/schedule/flights" endpoints.
- Schedule
- A namespaced client for the "/schedule" endpoints.
- BySquare
- A namespaced client for the "/v1/shopping/activities/by-square" endpoints.
- Activities
- A namespaced client for the "/v1/shopping/activities" endpoints.
- Activity
- A namespaced client for the "/v1/shopping/activities/:activity_id" endpoints.
- FlightAvailabilities
- A namespaced client for the "/v1/shopping/availability/flight-availabilities" endpoints.
- Availability
- A namespaced client for the "/v1/shopping/availability" endpoints.
- FlightDates
- A namespaced client for the "/v1/shopping/flight-dates" endpoints.
- FlightDestinations
- A namespaced client for the "/v1/shopping/flight-destinations" endpoints.
- Prediction
- A namespaced client for the "/v2/shopping/flight-offers/prediction" endpoints.
- Pricing
- A namespaced client for the "/v1/shopping/flight-offers/pricing" endpoints.
- FlightOffers
- A namespaced client for the "/v2/shopping/flight-offers" endpoints.
- HotelOffer
- A namespaced client for the "/v3/shopping/hotel-offers/:offer_id" endpoints.
- HotelOffers
- A namespaced client for the "/v3/shopping/hotel-offers" endpoints.
- Shopping
- A namespaced client for the "/shopping" endpoints.
- FlightDelay
- A namespaced client for the "/v1/travel/predictions/flight-delay" endpoints.
- Predictions
- A namespaced client for the "/v1/travel/predictions" endpoints.
- Travel
- A namespaced client for the "/travel" endpoints.


Let's Learn about the CSS Box Model!
Ok so I just finished week 2 of Dev Bootcamp's Phase 0. Woo hoo! This week was HTML and CSS. The CSS "Box Model" concept was covered. This is my attempt to make sense of it.
#1: Every HTML element is considered a "box". So a div tag is a box; a p tag is a box; the body tag is a box; every single tag is a box. Got it? Good!
#2: Every "box" has four attributes: content, padding, border, and margin. Take a look at this:
The content is what is between the tags. The padding is transparent space between the content and the border. The border is visible (if you want it to be) and goes around the padding. The margin is additional padding around the border.
Take a look at this:
On the left side is the HTML and CSS (the CSS is in the style tag), on the right side is the result of hte HTML. The content is text filler. The "inside" of this "box" is shown by the grey background. For this specific image, there is no padding, border, or margin. The next several images will show what happens when each of these are added.
Here is what it looks like when we add padding to this HTML element:
Now you can see there is spacing between the text (the "content" of this HTML element) and the edge of the padding. This padding is "inside" the HTML element, which is visible from the grey background color
Ok now let's see what happens if we add a border:
You guessed it, now there is a border around the padding. Take a look at the code on the left to see what has been changed to make this happen.
And below we will see our margin:
The margin has moved the box away fromm the edges of the document. Notice the margin is "outside" the HTML element (it is not in grey). Margin settings can be used to locate an object on the page. Also take a look at the code on the left. For the margin, I did not enter pixels (px), I entered a percentage (%) which tells the browser to make the margin 10% of the entire document. That is a pretty cool way to set the width of the margin (and you can do that with the padding and border as well, and also the width and height of the HTML object itself.)
Ultimately the CSS Box Model gives us a lot of power over the sizing of HTML elements, their spacing, how they look, and where they are placed on the page. I hope this helped you and makes sense!


There’s not any deep cryptography going on here, but since I spent 15 minutes answering this person on /r/askmath, and nobody reads /r/askmath, I’d take the time to cross-post it here.
The question:
I guessed the password on my Mom’s computer. “Snot”. This isn’t relevant to anything I can think of in the last 10 years. What are the chances of my guess being correct?
Depends on the constraints on this password. If you knew it was exactly four lowercase letters (no numbers, no symbols), there are 264 = 456,976 possibilities. That makes it a 0.00022% chance.
More realistically, if you knew that the password was a four-letter Scrabble word, there are somewhere around 4,000-5,000 possibilities, so your odds just jumped to 0.02%.
But. If your mother was clever and mixed uppercase and lowercase letters, that increases the number of possibilities by 16 times. (Why? Multiply by two for the first letter being uppercase or lowercase, multiply by two for the second letter, and again, and again. 2*2*2*2=16.) That means we have about 80,000 possibilities, and a 0.00125% chance.
Of course, as soon as you throw out the four-letter constraint, the possibilities explode. But let’s keep the Scrabble word constraint. According to the Official Tournament and Club Word List article on Wikipedia there are 178,691 Scrabble words, so we’re back down to 0.00056% for one go, and that’s assuming all-lowercase.
Finally, just for kicks, let’s assume all you knew is that the password is somewhere between 1 and 20 characters, and could contain lowercase, uppercase, digits 0-9, or any of the special characters !@#$%^&*(). That’s 72 possibilities for each character, which Wolfram Alpha informs me gives 14,214,254,150,091,658,100,874,779,924,350,129,800 possibilities, with a 0.000000000000000000000000000000000000007% chance of guessing correctly.
tl;dr: you got lucky. But keep in mind that I’m not surprised that out of the millions of users on Reddit, someone got this lucky. After all, people win the lottery all the time - just not me.
-SXC


Contributing
License
This project is licensed under the MIT License.
Guidelines apply from main OpenFaaS repo
See guide for FaaS here.
Unit testing with Golang
Please follow style guide on this blog post from The Go Programming Language
Hacking on the faas-cli
Installation / pre-requirements
- Docker
Install Docker because it is used to build Docker images if you create new functions.
- OpenFaaS - deployed and live
This CLI can build and deploy templated functions, so it's best if you have FaaS started up on your laptop. Head over to http://github.com/openfaas/faas/ and get up and running with a sample stack in 60 seconds.
- Golang
Here's how to install Go in 60 seconds.
- Grab Go 1.7.x or 1.8.3 from https://golang.org/dl/
Then after installing run this command or place it in your $HOME/.bash_profile
export GOPATH=$HOME/go
export PATH=$PATH:$GOPATH/bin
- Now clone / build
faas-cli
:
Migrate all imports/references to OpenFaaS org
$ mkdir -p $GOPATH/src/github.com/openfaas/
$ cd $GOPATH/src/github.com/openfaas/
$ git clone https://github.com/openfaas/faas-cli
$ cd faas-cli
$ go build
- Build multi-arch binaries
To build the release binaries type in:
./build_redist.sh
This creates the faas-cli for Mac, Windows, Linux x64, Linux ARMHF and Linux ARM64.
- Get the vendoring tool called
vndr
$ go install github.com/LK4D4/vndr
Use the tool if you add new dependencies or want to update the existing ones.
See also: vndr docs
How to update the brew
formula
The brew
formula for the faas-cli is part of the official homebrew-core repo on Github. It needs to be updated for each subsequent release.
Simple version bumps
If the only change required is a version bump, ie no new tests, or changes to existing tested functionality or build steps, the brew bump-formula-pr
command can be used to do everything (i.e. forking, committing, pushing) required to bump the version.
For example (supplying both the new version tag and its associated Git sha-256).
brew bump-formula-pr --strict faas-cli --tag=<version> --revision=<sha-256>
Changes requiring new/update tests/build steps
If a new release alters behaviour tested in the Brew Formula, adds new testable behaviors or alters the build steps then you will need to manually raise a PR with an updated Formula, the guidelines for updating brew describe the process in more detail:
https://github.com/Homebrew/homebrew-core/blob/master/CONTRIBUTING.md
After brew edit
run the build and test the results:
$ brew uninstall --force faas-cli ; \
brew install --build-from-source faas-cli ; \
brew test faas-cli ; \
brew audit --strict faas-cli
Update the utility-script
Please raise a PR for the get.sh file held in this repository. It's used when people install via curl
and cli.openfaas.com
. The updated file then has to be redeployed to the hosting server.
Developer DCO (re-iteration from referenced CONTRIBUTING guide)
Sign your work
Note: all of the commits in your PR/Patch must be signed-off.
The sign-off is a simple line at the end of the explanation for a patch. Your signature certifies that you wrote the patch or otherwise have the right to pass it on as an open-source patch. The rules are pretty simple: if you can certify the below (from developercertificate.org):
Developer Certificate of Origin
Version 1.1
Copyright (C) 2004, 2006 The Linux Foundation and its contributors.
1 Letterman Drive
Suite D4700
San Francisco, CA, 94129
Everyone is permitted to copy and distribute verbatim copies of this
license document, but changing it is not allowed.
Developer's Certificate of Origin 1.1
By making a contribution to this project, I certify that:
(a) The contribution was created in whole or in part by me and I
have the right to submit it under the open source license
indicated in the file; or
(b) The contribution is based upon previous work that, to the best
of my knowledge, is covered under an appropriate open source
license and I have the right under that license to submit that
work with modifications, whether created in whole or in part
by me, under the same open source license (unless I am
permitted to submit under a different license), as indicated
in the file; or
(c) The contribution was provided directly to me by some other
person who certified (a), (b) or (c) and I have not modified
it.
(d) I understand and agree that this project and the contribution
are public and that a record of the contribution (including all
personal information I submit with it, including my sign-off) is
maintained indefinitely and may be redistributed consistent with
this project or the open source license(s) involved.

If you set your user.name
and user.email
git configs, you can sign your
commit automatically with git commit -s
.
- Please sign your commits with
git commit -s
so that commits are traceable.
Misc
Bash Auto-completion [experimental]
An experimental initial Bash auto-completion script for faas-cli
is available at contrib/bash/faas-cli
.
Please raise issues with feedback and suggestions on improvements to the auto-completion support.
This may be enabled it as follows.
Enabling Bash auto-completion on OSX
Brew install the bash_completions
package.
$ brew install bash-completion
Add the following line to your ~/.bash_profile
if not already present.
[ -f /usr/local/etc/bash_completion ] && . /usr/local/etc/bash_completion
Copy the provided faas-cli
bash completion script from this repo.
cp contrib/bash/faas-cli /usr/local/etc/bash_completion.d/
Enabling Bash auto-completion on Linux
Refer to your distributions instructions on installing and enabling bash-completion
, then copy the faas-cli
completion script from contrib/bash/
into the appropriate completion directory.


This is a div with a red background using id styling!
The div tag is a block level tag (be careful not to confuse it with the inline span tag!)
We can use divs as a container for other html tags so styling can be applied to the container


STM32F103 SPI
===========================
STM32F103 SPI (Serial Peripheral Interface) is a synchronous serial communication protocol.
In this interface, in addition to transmit and receive lines, there is a third line that is used for clock line.
Each slave device also has a chip select (enable) pin, that is used for activating the device.
So to use SPI, we need 2 wires for data lines (MOSI, MISO), 1 wire for clock line, and 1 wire per device for chip select line.
MOSI (Master Out Slave In) is used for data transfer from master device to slave device.
MISO (Master In Slave Out) is used for data transfer from slave device to master device.
![](spi-bus.png width=400px)
SPI Protocol
===========================
SPI communication is different from other serial communication especially on data transfer.
There is no concept like transmit and receive data, but there is a data trading concept.
When data trading occurs, the data bits in master register is traded with the data bits in slave register on every clock from master (one data bit per clock tick).
You can think SPI is like shift registers. There are 2 shift registers, one in master device and another in slave device.
Each input of shift register is connected to the output of the other through MOSI and MISO lines, so that they form a ring.
![](shift-register.png width=400px)
The figure above illustrates the bit trading from master to slave.
Master register contain data 0xFF and slave register contain data 0x00.
After one clock tick, the master is left with seven of its original bits and the first one that is come in from the slave, and vice versa.
After a total of eight clock ticks, all eight bits of each byte have traded place.
Sometimes not all data byte come from slave or sent to slave is meaningful.
This happen because probably slave device has not received any command yet, so the data in slave register is not meaningful.
Another case, if we just want to take data from slave, but don’t want to send any command to slave, we can place dummy byte on master register and then give eight clock ticks for trading with data bits in slave register.
![](sparkfun-spi.png width=500px)
The figure above is the timing diagram of SPI protocol.
We know that to communicate to the slave device, the slave select pin should be activated (active low).
The data is sampled every rising edge of clock.
We can also sample data on falling edge of clock, this setting can be configured depending on the feature of the hardware SPI that you use.
In this example, master is send data byte 0x53 to slave and then slave send data byte 0x46 to master.
The order of the data is LSB first, but it can also MSB first depending on the configuration.
Example Code
===========================
In this tutorial, I will explain how to use SPI in STM32F103 as a master, and for the slave I will use Arduino.
We can send data char '1' from SPI master to turn on LED blinking on Arduino.
To turn off LED blinking, we can send '0' from SPI master.
Master can also read LED blinking status (off/on) from Arduino by sending '?' first, then read the LED blinking status which will return 0 or 1.
This is the Arduino code for SPI slave device.
~~~~~~~~~~~~~~~~~~~~~~~~~~~ C linenumbers
#define LED_PIN 9
volatile uint8_t led_blink = 0;
ISR(SPI_STC_vect)
{
uint8_t data_byte = SPDR;
switch (data_byte)
{
case '0':
led_blink = 0;
SPDR = 0;
break;
case '1':
led_blink = 1;
SPDR = 0;
break;
case '?':
// Place LED blinking status in SPDR register for next transfer
SPDR = led_blink;
break;
}
}
void setup()
{
pinMode(LED_PIN, OUTPUT);
// Set MISO pin as output
pinMode(MISO, OUTPUT);
// Turn on SPI in slave mode
SPCR |= (1 << SPE);
// Turn on interrupt
SPCR |= (1 << SPIE);
}
void loop()
{
// If LED blink status is on, then blink LED for 250ms
if (led_blink == 1)
{
digitalWrite(LED_PIN, HIGH);
delay(250);
digitalWrite(LED_PIN, LOW);
delay(250);
}
else if (led_blink == 0)
{
digitalWrite(LED_PIN, LOW);
}
}
~~~~~~~~~~~~~~~~~~~~~~~~~~~
For the SPI on STM32F103, I create several functions such as for initialize SPI, SPI data transfer, and enable/disable slave device.
In main function, I write codes to turn on and off the LED blinking on Arduino, then ask the current LED blinking status every 2500 ms.
The LED blinking status will be displayed on LCD.
~~~~~~~~~~~~~~~~~~~~~~~~~~~ C linenumbers
#include "stm32f10x.h"
#include "stm32f10x_rcc.h"
#include "stm32f10x_gpio.h"
#include "stm32f10x_spi.h"
#include "delay.h"
#include "lcd16x2.h"
#define SPIx_RCC RCC_APB2Periph_SPI1
#define SPIx SPI1
#define SPI_GPIO_RCC RCC_APB2Periph_GPIOA
#define SPI_GPIO GPIOA
#define SPI_PIN_MOSI GPIO_Pin_7
#define SPI_PIN_MISO GPIO_Pin_6
#define SPI_PIN_SCK GPIO_Pin_5
#define SPI_PIN_SS GPIO_Pin_4
void SPIx_Init(void);
uint8_t SPIx_Transfer(uint8_t data);
void SPIx_EnableSlave(void);
void SPIx_DisableSlave(void);
uint8_t receivedByte;
int main(void)
{
DelayInit();
lcd16x2_init(LCD16X2_DISPLAY_ON_CURSOR_OFF_BLINK_OFF);
SPIx_Init();
while (1)
{
// Enable slave
SPIx_EnableSlave();
// Write command to slave to turn on LED blinking
SPIx_Transfer((uint8_t) '1');
DelayUs(10);
// Write command to slave for asking LED blinking status
SPIx_Transfer((uint8_t) '?');

DelayUs(10);
// Read LED blinking status (off/on) from slave by transmitting
// dummy byte
receivedByte = SPIx_Transfer(0);
// Disable slave
SPIx_DisableSlave();
// Display LED blinking status
lcd16x2_clrscr();
if (receivedByte == 0)
{
lcd16x2_puts("LED Blinking Off");
}
else if (receivedByte == 1)
{
lcd16x2_puts("LED Blinking On");
}
DelayMs(2500);
}
}
void SPIx_Init()
{
// Initialization struct
SPI_InitTypeDef SPI_InitStruct;
GPIO_InitTypeDef GPIO_InitStruct;
// Step 1: Initialize SPI
RCC_APB2PeriphClockCmd(SPIx_RCC, ENABLE);
SPI_InitStruct.SPI_BaudRatePrescaler = SPI_BaudRatePrescaler_128;
SPI_InitStruct.SPI_CPHA = SPI_CPHA_1Edge;
SPI_InitStruct.SPI_CPOL = SPI_CPOL_Low;
SPI_InitStruct.SPI_DataSize = SPI_DataSize_8b;
SPI_InitStruct.SPI_Direction = SPI_Direction_2Lines_FullDuplex;
SPI_InitStruct.SPI_FirstBit = SPI_FirstBit_MSB;
SPI_InitStruct.SPI_Mode = SPI_Mode_Master;
SPI_InitStruct.SPI_NSS = SPI_NSS_Soft | SPI_NSSInternalSoft_Set;
SPI_Init(SPIx, &SPI_InitStruct);
SPI_Cmd(SPIx, ENABLE);
// Step 2: Initialize GPIO
RCC_APB2PeriphClockCmd(SPI_GPIO_RCC, ENABLE);
// GPIO pins for MOSI, MISO, and SCK
GPIO_InitStruct.GPIO_Pin = SPI_PIN_MOSI | SPI_PIN_MISO | SPI_PIN_SCK;
GPIO_InitStruct.GPIO_Mode = GPIO_Mode_AF_PP;
GPIO_InitStruct.GPIO_Speed = GPIO_Speed_50MHz;
GPIO_Init(SPI_GPIO, &GPIO_InitStruct);
// GPIO pin for SS
GPIO_InitStruct.GPIO_Pin = SPI_PIN_SS;
GPIO_InitStruct.GPIO_Mode = GPIO_Mode_Out_PP;
GPIO_InitStruct.GPIO_Speed = GPIO_Speed_50MHz;
GPIO_Init(SPI_GPIO, &GPIO_InitStruct);
// Disable SPI slave device
SPIx_DisableSlave();
}
uint8_t SPIx_Transfer(uint8_t data)
{
// Write data to be transmitted to the SPI data register
SPIx->DR = data;
// Wait until transmit complete
while (!(SPIx->SR & (SPI_I2S_FLAG_TXE)));
// Wait until receive complete
while (!(SPIx->SR & (SPI_I2S_FLAG_RXNE)));
// Wait until SPI is not busy anymore
while (SPIx->SR & (SPI_I2S_FLAG_BSY));
// Return received data from SPI data register
return SPIx->DR;
}
void SPIx_EnableSlave()
{
// Set slave SS pin low
SPI_GPIO->BRR = SPI_PIN_SS;
}
void SPIx_DisableSlave()
{
// Set slave SS pin high
SPI_GPIO->BSRR = SPI_PIN_SS;
}
~~~~~~~~~~~~~~~~~~~~~~~~~~~
You can get the project file from [here](https://github.com/yohanes-erwin/stm32f103-keil/tree/master/spi-master-polling). This is the result:
![](https://youtu.be/9-Ec0C3KHdw)