vignettes/work_with_big_datasets.Rmd
work_with_big_datasets.Rmd
cola can be idealy applied to datasets with intermediate number of samples (around 500), however, the running time and the memory usage might not be acceptable if the number of samples gets very huge, e.g., more than thousands. Nevertheless, we can propose the following two strategies to partially solve this problem.
predict_classes()
function for this purpose (see the vignette “Predict classes for new samples” for details).Note, since these two strategies are performed by sampling a small subset of cells from the cohort, the cell clusters with small size might not be detectable.
In the following examples, we use pseudo code to demonstrate the ideas. Assuming the full matrix is in an object mat
. We randomly sample 200 samples from it:
Strategy 1. First we can apply cola on mat1
:
rl = run_all_consensus_partition_methods(mat1, ...) cola_report(rl, ...)
Then find a best combination of top-value method and partitioining method. Assuming they are saved in objects tm
and pm
. Next run consensus_partition()
on mat
only with tm
and pm
:
res = consensus_partition(mat, top_value_method = tm, partition_method = pm, ...)
Strategy 2. Similar as Strategy 1, we get the ConsensusPartition
object from methods tm
and pm
, which was applied on mat1
:
res = rl[tm, pm]
Note the consensus partition object res
is only based on a subset of original samples. With res
, the classes of remaining samples can be predicted:
mat2 = mat[, setdiff(seq_len(ncol(mat)), ind)] mat2 = t(scale(t(mat2))) cl = predict_classes(res, mat2)
Please note, by default mat1
is scaled in cola analysis, correspondingly, mat2
should also be row-scaled.
You can also directly send mat
to predict_classes()
function:
cl = predict_classes(res, t(scale(t(mat))))
DownSamplingConsensusPartition
classcola implements a new DownSamplingConsensusPartition
class for Strategy 2 mentioned above. It runs consensus partitioning only on a subset of samples and the classes of other samples are predicted by predict_classes()
internally. The DownSamplingConsensusPartition
class inherits the ConsensusPartition
class, so the functions that can be applied to the ConsensusPartition
objects can also be applied to the DownSamplingConsensusPartition
objects, just with some tiny difference.
In the following example, we demonstrate the usage of DownSamplingConsensusPartition
class with the Golub dataset. Here the Golub dataset was used to generate another data object golub_cola
and we can extract the matrix and the annotations by get_matrix()
and get_anno()
functions.
To perform down sampling consensus partitioning, use the helper function consensus_partition_by_down_sampling()
. This function basically run consensus_partition()
on a subset of samples and later predict the classes for all samples by predict_classes()
function. Here we set subset
argument to 50, which means to randomly sample 50 samples from the whole dataset.
data(golub_cola) m = get_matrix(golub_cola) set.seed(123) golub_cola_ds = consensus_partition_by_down_sampling(m, subset = 50, anno = get_anno(golub_cola), anno_col = get_anno_col(golub_cola), top_value_method = "SD", partition_method = "kmeans")
The object golub_cola_ds
is already shipped in the package. Simply load the data object.
data(golub_cola_ds) golub_cola_ds
## A 'DownSamplingConsensusPartition' object with k = 2, 3, 4, 5, 6.
## On a matrix with 4116 rows and 50 columns, randomly sampled from 72 columns.
## Top rows (412, 824, 1235) are extracted by 'ATC' method.
## Subgroups are detected by 'skmeans' method.
## Performed in total 750 partitions by row resampling.
## Best k for subgroups seems to be 2.
##
## Following methods can be applied to this 'DownSamplingConsensusPartition' object:
## [1] "cola_report" "collect_classes" "collect_plots"
## [4] "collect_stats" "colnames" "compare_signatures"
## [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
## [10] "get_anno_col" "get_anno" "get_classes"
## [13] "get_consensus" "get_matrix" "get_membership"
## [16] "get_param" "get_signatures" "get_stats"
## [19] "is_best_k" "is_stable_k" "membership_heatmap"
## [22] "ncol" "nrow" "plot_ecdf"
## [25] "predict_classes" "rownames" "select_partition_number"
## [28] "show" "suggest_best_k" "test_to_known_factors"
The summary of the golub_cola_ds
is very similar as the ConsensusPartition
object, except that it mentions the object is generated from 50 samples randomly sampled from 72 samples.
 For more details of how the p-value is calculated, please refer to the vignette “Predict classes for new samples”.
If the argument k
is not specified or k
is specified as a vector, the class labels for all k
are returned.  These functions are get_classes()
, test_to_known_factors()
, dimension_reduction()
and get_signatures()
.
For dimension_reduction()
function, the samples with p-value higher than p_cutoff
are marked by crosses. The samples that were not selected in the random sampling were mapped with smaller dots.
dimension_reduction(golub_cola_ds, k = 2)
## use UMAP
For get_signatures()
function, the signatures are only found in the samples with p-values less than p_cutoff
.
get_signatures(golub_cola_ds, k = 2)
## * 70/72 samples (in 2 classes) remain after filtering by p-value (<= 0.05).
## * cache hash: d7ed9b16253695bd9adb86dbaa84b708 (seed 888).
## * calculating row difference between subgroups by Ftest.
## * split rows into 2 groups by k-means clustering.
## * 1847 signatures (44.9%) under fdr < 0.05, group_diff > 0.
## * making heatmaps for signatures.
## R version 4.0.2 (2020-06-22)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.5
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] cola_1.5.6 knitr_1.29 markdown_1.1
##
## loaded via a namespace (and not attached):
## [1] mclust_5.4.6 Rcpp_1.0.5 lattice_0.20-41 circlize_0.4.11
## [5] png_0.1-7 assertthat_0.2.1 rprojroot_1.3-2 digest_0.6.25
## [9] RSpectra_0.16-0 slam_0.1-47 R6_2.4.1 backports_1.1.9
## [13] stats4_4.0.2 RSQLite_2.2.0 evaluate_0.14 httr_1.4.2
## [17] GlobalOptions_0.1.2 rlang_0.4.7 annotate_1.66.0 blob_1.2.1
## [21] magick_2.4.0 S4Vectors_0.26.1 GetoptLong_1.0.3 Matrix_1.2-18
## [25] reticulate_1.16 rmarkdown_2.3 pkgdown_1.5.1 splines_4.0.2
## [29] desc_1.2.0 stringr_1.4.0 bit_4.0.4 RCurl_1.98-1.2
## [33] umap_<IP_ADDRESS> compiler_4.0.2 eulerr_6.1.0 xfun_0.16
## [37] askpass_1.1 microbenchmark_1.4-7 BiocGenerics_0.34.0 shape_1.4.4
## [41] htmltools_0.5.0 openssl_1.4.2 IRanges_2.22.2 matrixStats_0.56.0
## [45] XML_3.99-0.5 crayon_1.3.4 MASS_7.3-52 bitops_1.0-6
## [49] grid_4.0.2 jsonlite_1.7.0 xtable_1.8-4 DBI_1.1.0
## [53] magrittr_1.5 skmeans_0.2-12 stringi_1.4.6 impute_1.62.0
## [57] genefilter_1.70.0 fs_1.5.0 xml2_1.3.2 vctrs_0.3.4
## [61] brew_1.0-6 rjson_0.2.20 RColorBrewer_1.1-2 tools_4.0.2
## [65] bit64_4.0.5 Biobase_2.48.0 survival_3.2-3 parallel_4.0.2
## [69] yaml_2.2.1 clue_0.3-57 AnnotationDbi_1.50.3 colorspace_1.4-1
## [73] cluster_2.1.0 ComplexHeatmap_2.5.5 memoise_1.1.0


Spencer Poisseroux
[Sound] Tape Loops
growing collection of tape loops made by me
feel free to use any of the audios
audio used in my diaries
sides a and b
side a
growing collection of tape loops made by me
feel free to use any of the audios
audio used in my diaries
sides a and b
side a


Train Spotting
Keep track of your favorite trains with this lil application.
Choose your future.
Choose life.
My Super Awesome Trains:
Train Name
Destination
Frequency (min)
Next Arrival
Minutes Away
Add a New Train:
Train Name
Destination
First Train Time HH:mm
Frequency (minutes)
Submit


#include "graphics_afx.h"
#include "GrRenderTarget.h"
#include "GrTextureMgr.h"
#include "GrTexture.h"
#include "GrRenderbuffer.h"
#include "GLSubsys.h"
#include "GrUtil.h"
#include "GrTextureRect.h"
#include "GrSubsys.h"
Go to the source code of this file.
Classes | |
| class | IXRenderable |
| class IXRenderable implemenation. More... | |
| class | IXTextureRenderable |
| class IXTextureRenderable implemenation. More... | |
| class | IXTextureCubeRenderable |
| class IXTextureCubeRenderable implemenation. More... | |
| class | IXTextureRectRenderable |
| class IXTextureRectRenderable implemenation. More... | |
| class | IXBufferRenderable |
| class IXBufferRenderable implemenation. More... |


The Aggregation relationship indicates that a concept groups a number of other concepts.
Unlike Composition, Aggregation does not imply an existence dependency between the aggregating and aggregated concepts.
Aggregation is always possible between two instances of the same element type.
Structural.
A Car Insurance Business Product aggregates a Business Contract and some Business Services.
"Customer File" aggregates an "Insurance Policy" and "Insurance Claim"


| Interface | Description |
|---|---|
| TypeCache |
Temporary type cache used for one call.
|
| Class | Description |
|---|---|
| Base64 |
Encodes and decodes to and from Base64 notation.
|
| Base64.InputStream |
A
Base64.InputStream will read data from another
java.io.InputStream, given in the constructor, and encode/decode
to/from Base64 notation on the fly. |
| Base64.OutputStream |
A
Base64.OutputStream will write data to another
java.io.OutputStream, given in the constructor, and
encode/decode to/from Base64 notation on the fly. |
| ClassLoaderUtil | |
| CmisEnumHelper |
Helper methods to turn a value into a CMIS enum.
|
| Constants |
Constants for CMIS server and client.
|
| DateTimeHelper | |
| IOUtils | |
| JSONConstants |
JSON object constants.
|
| JSONConverter |
OpenCMIS objects to JSON converter.
|
| MimeHelper |
MIME helper class.
|
| MimeHelper.HeaderTokenizer | |
| MimeHelper.Token | |
| MimeTypes | |
| UrlBuilder |
Utility class that helps building URLs.
|
| WSConverter |
Contains converter methods.
|
| XMLConstants | |
| XMLConstraints | |
| XMLConverter | |
| XMLUtils | |
| XMLWalker<T> |
| Enum | Description |
|---|---|
| JSONConverter.PropertyMode | |
| ReturnVersion |
Return Version Enum.
|
| Exception | Description |
|---|---|
| MimeHelper.ParseException |
Copyright © 2009-2013 The Apache Software Foundation. All Rights Reserved.


- ClientResponse - Class in com.pkrete.xrd4j.rest
-
This class represents the response returned by HTTP clients.
- ClientResponse(String, String, int, String) - Constructor for class com.pkrete.xrd4j.rest.ClientResponse
-
Constructs and initializes a new ClientResponse object.
- ClientUtil - Class in com.pkrete.xrd4j.rest.util
-
This class contains utility methods for REST clients.
- ClientUtil() - Constructor for class com.pkrete.xrd4j.rest.util.ClientUtil
-
- com.pkrete.xrd4j.rest - package com.pkrete.xrd4j.rest
-
- com.pkrete.xrd4j.rest.client - package com.pkrete.xrd4j.rest.client
-
- com.pkrete.xrd4j.rest.converter - package com.pkrete.xrd4j.rest.converter
-
- com.pkrete.xrd4j.rest.util - package com.pkrete.xrd4j.rest.util
-
- convert(String) - Method in interface com.pkrete.xrd4j.rest.converter.Converter
-
Converts the given string between formats defined by the implementing
class.
- convert(String) - Method in class com.pkrete.xrd4j.rest.converter.JSONToXMLConverter
-
Converts the given JSON string to XML string.
- convert(String) - Method in class com.pkrete.xrd4j.rest.converter.XMLToJSONConverter
-
Converts the given XML string to JSON string.
- Converter - Interface in com.pkrete.xrd4j.rest.converter
-
An interface for converting XML, JSON and JSON-LD.
- createRESTClient(String) - Static method in class com.pkrete.xrd4j.rest.client.RESTClientFactory
-
Creates a new RESTClient object matching the given HTTP verb.


Order A Pizza!
SELECT TOPPINGS:
Pepperoni
Olives
Mushrooms
Pineapple
Sausage
Salami
Artichokes
Pesto
Tuna
Broccoli
--
No Cheese
SELECT SIZE:
Small
Medium
Large
Extra Large
SELECT CRUST:
Standard
Thin
Pan
Gluten-Free
Order
Your pizza will cost $
.
Order Another Pizza


The eighth season saw the Dane earn his fourth MVP award from the FACEIT-organized tournament series, after he had led his team to three other titles in the second, fifth, and sixth season. In Dallas, despite an unremarkable start device was once again an important factor across all of
Astralis
ORG
' wins that led them to the title, with great series against
fnatic
ORG
and
Evil Geniuses
ORG
pushing them to the grand final against
Liquid
ORG
, which he helped lock down with a decisive performance on the third map, Dust2. With that, the 24-year-old beat teammates
Emil Magisk Reif
PLAYER
and
Lukas gla1ve
PLAYER
Rossander
PLAYER
as well as two of his opponents from the title decider,
Keith NAF Markovic
PLAYER
and
Jonathan
AVATAR
EliGE Jablonowski
PLAYER
, to the award, clinching his third of 2019. Some of the standout numbers device posted over the course of
ECS Season 8
TOURN
Finals include a 1.27 rating (second-highest), 0.79 KPR (second-most), 0.57 DPR (second-fewest), 75.2% KAST (third-most), and 0.13 opening kills per round (fourth-most). device now has a total of 15
MVP
ORG
awards to his name, the most out of any player by far, extending his lead over
Christopher GeTRiGhT Alesund
PLAYER
and
Kenny kennyS Schrub
PLAYER
, who have ten each.


| Title | Description | Due Date | Action |
|---|---|---|---|
| Follow up with marketing about materials | A vendor has not received shipments for an order they placed through the online form. | 1/24/2016 11:01:39 AM | View |
| Vendor issues | A vendor has not received their order, please address this and check that the order was placed. | 1/24/2016 11:01:39 AM | View |


AudioCDStatus()
语法
Result = AudioCDStatus()概要
Returns the actual state of the current audio CD drive.
参数
无.
返回值
The return-value may take the following values:
-1: CD drive not ready (it is either empty or opened)
0: CD drive stopped (but the CD is in the drive and has been detected)
>0: Audio track which is currently being played.
参阅
UseAudioCD()
已支持操作系统
所有


SuspendingActionListener(continuation: Continuation<T>)
Action listener that can be used with to adapt the async methods across the java client to co-routines.


Trigger Distance
The threshold, from each site, at wich the controls will be hidden.
All values in "px". Use "-1" to disable one site.


Tab
Navigate forwards
Shift + Tab
Navigate backwards
If you want null(s) in any of the lists, just press enter or click the arrow button in any list input boxes that doesn't any character(s) in it.
All of the things below, except "After", need to have something in it.
Supported escape characters in builder.html:
\b, \t, \n, \f, \r, and \u{0000-FFFF}
Token
You can insert either an user token or a bot token.
Permissions
Permissions to use any commands that the bot offers will be granted to the discord user tag(s) or discord user ID(s) that are listed in the list box. In this list you can have null(s), but it will become an unnecessary item for the script to check.
Bomb messages
Random
When you are using any type of random bombs ("an", "b64"), it will ask for a length of how long the characters should be. And the length will be asked in this box here, so please enter a positive integer. (Note: 10 is a recommended length because if the channel is too long people won't be able to see the whole names anyways, and it will also use up some extra bit of CPU)
Fixed
Items that are inside this list is used by the "fixed" bomb command. You cannot have any null in here.
Webhook spams
Usernames
The bot will randomly pick an item that is entered in the list, and use it as the username of the webhook request during webhook attack. You cannot have null(s) in this list or leave it empty. If you want "No name", then enter \u200B (ZERO-WIDTH space) as the username.
Profile pictures
The bot will randomly choose an image link from the list during webhook attack. You CAN have null(s) in this list, which will be used as "No pfp" during the webhook attack. Anything that is not an image link will result the bot in an error. (The script won't tell you which one has error, but if you did "webhook attack start 50" and there are less than 50 messages that got sent, then that means there's something wrong with this configuration file.)
Contents
The bot will randomly choose a message from the list during webhook attack.  The messages that are sent are going to be formatted just like how you usually send messages in discord. Which means you can send messages like **Bold Text** for Bold Text, and you cannot send more than 2000 charaters.
Bot permissions
The bot will ask for the permissions that you have chosen in the given options, when someone used the bot's invite generated by the script. These options are not required if you are using the script on an user account.
Command prefix
It's the command prefix. Put whatever command prefix that you like in here.
On start status
This is for the status on the profile. The moment the script is connected to a profile, it will execute this command. And the Available options are online, offline, invisible, dnd (or do_not_disturb), and idle.
Verbose levels
If you don't have a greate computer, your computer will lag over some massive output of logs. This can increase your computer performance by disabling the logs that you don't need. (Turning all logs on is recommended)
After
Inside this text box, you can input the commands that you want to execute after the nuke command. You can enter commands like "si" or "sn" to change the server name and icon (You can also leave this area blank if you are not familiar with the commands yet). You can think of it this way: this is just a like discord chat, if you want to send a message you need to press the enter key; every message you sent is a command for the bot, except you don't have to enter a command prefix. As long you don't add a new enter to the text box, it will not be counted as a new command. (Note: you do not have to put the command prefix in this text box)


IDN
Section: User Commands (1)Updated: February 2010
Index Return to Main Contents
NAME
idn - Internationalized Domain Names command line toolSYNOPSIS
idn [OPTION]... [STRINGS]...DESCRIPTION
Internationalized Domain Name (IDN) convert STRINGS, or standard input.Command line interface to the internationalized domain name library.
All strings are expected to be encoded in the preferred charset used by your locale. Use `--debug' to find out what this charset is. You can override the charset used by setting environment variable CHARSET.
To process a string that starts with `-', for example `-foo', use `--' to signal the end of parameters, as in `idn --quiet -a -- -foo'.
Mandatory arguments to long options are mandatory for short options too.
- -h, --help
- Print help and exit
- -V, --version
- Print version and exit
- -s, --stringprep
- Prepare string according to nameprep profile
- -d, --punycode-decode
- Decode Punycode
- -e, --punycode-encode
- Encode Punycode
- -a, --idna-to-ascii
- Convert to ACE according to IDNA (default mode)
- -u, --idna-to-unicode
- Convert from ACE according to IDNA
- --allow-unassigned
- Toggle IDNA AllowUnassigned flag (default off)
- --usestd3asciirules
- Toggle IDNA UseSTD3ASCIIRules flag (default off)
- --no-tld
- Don't check string for TLD specific rules Only for --idna-to-ascii and --idna-to-unicode
- -n, --nfkc
- Normalize string according to Unicode v3.2 NFKC
- -p, --profile=STRING
- Use specified stringprep profile instead Valid stringprep profiles: `Nameprep', `iSCSI', `Nodeprep', `Resourceprep', `trace', `SASLprep'
- --debug
- Print debugging information
- --quiet
- Silent operation
AUTHOR
Written by Simon Josefsson.REPORTING BUGS
Report bugs to<EMAIL_ADDRESS>Libidn home page: <http://www.gnu.org/software/libidn/>
General help using GNU software: <http://www.gnu.org/gethelp/>
COPYRIGHT
Copyright © 2010 Simon Josefsson. License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>.This is free software: you are free to change and redistribute it. There is NO WARRANTY, to the extent permitted by law.
SEE ALSO
The full documentation for idn is maintained as a Texinfo manual. If the info and idn programs are properly installed at your site, the command- info idn
should give you access to the complete manual.
Index
This document was created by man2html, using the manual pages.
Time: 05:29:04 GMT, December 24, 2015


Parallax Movement Style
Tilt (against mouse)
Tilt (with mouse)
All same direction (against mouse)
All same direction (with mouse)
All same direction (reversed)


GPM
Gate Pass Manager
a Novelty Data Production.
Anonymous
Sign in
List
Products
List Products
Add New Product
List Inactive Products
Users
List Users
Add New User
System
Signout
Search
Gate Pass Manager
New Gate Pass
Select a Department and Visit Type
Sign Out
Signout of this application.
Cardiology
First Visit
Follow up
93
236
Cardiac_Surgery
First Visit
Follow up
0
36
Neurology
First Visit
Follow up
9
0
NeuroSurgery
First Visit
Follow up
93
236
Anesthesiology
First Visit
Follow up
93
236
Radiology
First Visit
Follow up
93
236
Lab and Blood
First Visit
Follow up
93
236
Physiotherapy
First Visit
Follow up
93
236
Counseling
First Visit
Follow up
93
236
Fluid jumbotron
This is a modified jumbotron that occupies the entire horizontal space of its parent.
powered by
firament ESP
Someone famous in
Source Title


ShrinkwrapConstraint(Constraint)¶
base classes — bpy_struct
, Constraint
-
class
bpy.types.

Type: enum in [‘OFF’, ‘FRONT’, ‘BACK’], default ‘OFF’
-
distance
¶ Distance to Target
Type: float in [0, inf], default 0.0
-
project_axis
¶ Axis constrain to
Type: enum in [‘POS_X’, ‘POS_Y’, ‘POS_Z’, ‘NEG_X’, ‘NEG_Y’, ‘NEG_Z’], default ‘POS_X’
-
project_axis_space
¶ Space for the projection axis
WORLD
World Space, The constraint is applied relative to the world coordinate system.POSE
Pose Space, The constraint is applied in Pose Space, the object transformation is ignored.LOCAL_WITH_PARENT
Local With Parent, The constraint is applied relative to the rest pose local coordinate system of the bone, thus including the parent-induced transformation.LOCAL
Local Space, The constraint is applied relative to the local coordinate system of the object.
Type: enum in [‘WORLD’, ‘POSE’, ‘LOCAL_WITH_PARENT’, ‘LOCAL’], default ‘WORLD’
-
project_limit
¶ Limit the distance used for projection (zero disables)
Type: float in [0, inf], default 0.0
-
shrinkwrap_type
¶ Select type of shrinkwrap algorithm for target position
NEAREST_SURFACE
Nearest Surface Point, Shrink the location to the nearest target surface.PROJECT
Project, Shrink the location to the nearest target surface along a given axis.NEAREST_VERTEX
Nearest Vertex, Shrink the location to the nearest target vertex.TARGET_PROJECT
Target Normal Project, Shrink the location to the nearest target surface along the interpolated vertex normals of the target.
Type: enum in [‘NEAREST_SURFACE’, ‘PROJECT’, ‘NEAREST_VERTEX’, ‘TARGET_PROJECT’], default ‘NEAREST_SURFACE’
-
track_axis
¶ Axis that is aligned to the normal
Type: enum in [‘TRACK_X’, ‘TRACK_Y’, ‘TRACK_Z’, ‘TRACK_NEGATIVE_X’, ‘TRACK_NEGATIVE_Y’, ‘TRACK_NEGATIVE_Z’], default ‘TRACK_X’
-
use_invert_cull
¶ When projecting in the opposite direction invert the face cull mode
Type: boolean, default False
-
use_project_opposite
¶ Project in both specified and opposite directions
Type: boolean, default False
-
use_track_normal
¶ Align the specified axis to the surface normal
Type: boolean, default False
-
wrap_mode
¶ Select how to constrain the object to the target surface
ON_SURFACE
On Surface, The point is constrained to the surface of the target object, with distance offset towards the original point location.INSIDE
Inside, The point is constrained to be inside the target object.OUTSIDE
Outside, The point is constrained to be outside the target object.OUTSIDE_SURFACE
Outside Surface, The point is constrained to the surface of the target object, with distance offset always to the outside, towards or away from the original location.ABOVE_SURFACE
Above Surface, The point is constrained to the surface of the target object, with distance offset applied exactly along the target normal.
Type: enum in [‘ON_SURFACE’, ‘INSIDE’, ‘OUTSIDE’, ‘OUTSIDE_SURFACE’, ‘ABOVE_SURFACE’], default ‘ON_SURFACE’
-
classmethod
bl_rna_get_subclass
(id, default=None)¶ Parameters: id (string) – The RNA type identifier. Returns: The RNA type or default when not found. Return type: bpy.types.Struct
subclass
-
classmethod
bl_rna_get_subclass_py
(id, default=None)¶ Parameters: id (string) – The RNA type identifier. Returns: The class or default when not found. Return type: type
-
Inherited Properties
Inherited Functions


In doing so, the BBC News website attempt to smartly fragment the news it has generated and is communicating into clear content boxes, labelled clearly and simply, to aid the user in finding the information they seek, from a huge breadth of information available, in an easy to visualise and access manner.


{% extends 'landing/base.html' %} {% block body %}
Confirmation Email has been sent to your email address, please click on link in mail to register.


2 Corinthians 12:19
Again, think ye that we excuse ourselves unto you? we speak before God in Christ: but we do all things, dearly beloved, for your edifying.


{% extends "base.html" %} {% load staticfiles %} {% block content %}
Created by:
Created date:
Updated date:


CSS Playground
A gathering of trials and errors in my CSS things.
Projects
View on Github
Moving Background
Science Icon


swSrc
Required String
The path to the source service worker file that can contain your own customized code, in
addition to containing a match for injectionPointRegexp
.
In Node
Your service worker file should include a call to a
workbox.precaching
method that makes use of the injected precache manifest.
In Webpack
Your service worker file should reference the self.__precacheManifest
variable to obtain a list of
ManifestEntry
s
obtained as part of the compilation: workbox.precaching.precacheAndRoute(self.__precacheManifest)
Example:
swDest: path.join('src', 'sw.js')


This description is from include-DATA-FILE.json
This description is from include-DATA-FILE.json
Static site generator for Grunt.js and Yeoman. Assemble makes it dead simple to build modular sites, blogs, gh-pages, components and documentation from reusable templates and data.
Static site generator for Grunt.js and Yeoman. Assemble makes it dead simple to build modular sites, blogs, gh-pages, components and documentation from reusable templates and data.
Note that the YAML front matter is "borrowing" data from the site
object, which is defined in the Grunt config.
So in this example, {{title}}
will yield the same result as {{site.title}}
, and {{description}}
will
yield the same result as {{site.description}}
This description is from PAGE YFM (multiple.hbs)
In this example, the context for title
should be from the YAML front matter of include-yfm.hbs
,
but since no description
property exists in the YFM of the include, the context for description
should come from the inheriting page.


Tsinghua-Tencent 100K Detection
FPN-CNN Model which is trained by Tsinghua-Tencent 100K
Detection Classes: [Chinese traffic-sign classes]
Sample data 01
Sample data 02
Sample data 03
* You can download the full dataset here.
Please submit your Tsinhgua-Tencent-100K image file that you want to detect.


I'm working, I swear!
So far all I’ve mentioned are the adventures I’ve been having! If you’re wondering, as my Grandpa Joe put it: “when the hell are you going to work”, then this post is for you :)
About My Project
I am building a program that will allow users to load 3D models (.obj file format) and interact with them via transformations such as rotation, translation, deformation etc. My ultimate goal is to implement the ability to select parts of a volume mesh, so the user can select and interact with seperate parts of their model. I am using C++, OpenGL, and QT for my project.
I was first inspired to learn about computer graphics when my (amazing) materials science professor told me about his son who works on lighting movies at Pixar. I have always loved developing my technical background, but I also love painting and drawing and creating visual things. Until I learned about the opportunity to work in computer graphics, it never occurred to me that I could excercise both of my interests at the same time.
I have virtually no experience with C++, definitely none with OpenGL and I hadn’t even heard of QT until my supervisor told me about it. It is also my first time building a GUI (Graphical User Interface … the window and buttons). Initially, I was feeling a little lost and intimidated while trying to familiarize myself with all three new things simultaneously. So I completeley understand if this is too much computer science jargon. I won’t be offended if you just look at the pictures. But hopefully some of you will find this interesting :)
After a lot confusion (days), my supervisor helped me organize my learning strategy and I finally got a program running.
Next I worked on loading actual objects. To do this, I needed to read information from a user selected .obj file. These files are lists of the vertices (lines beginning with v), and faces (lines beginning with f). Each face is a triangle, made up of three of the vertices.
Once I have all of the information from the file stored, I have to iterate through each face and ask OpenGL to draw the respective triangle. I’ve been using some models from the Berkeley Garment Library as test files.
Yay!! I’ve rendered a model! But it isn’t very exciting looking. It’s supposed to look 3D. It looks flat because it hasn’t been lit yet.  You need to add lighting and shading to make it look like a sphere, right? Same idea. Cool, I’ll enable lighting.
Ok so enabling lighting isn’t enough. Now all of the models I load are just black. At this point, OpenGL has no idea how this model is supposed to be lit. I can’t just expect OpenGL to know that my vertices are supposed to look like a robe.
In order to really light the model, OpenGL needs the normals for each vertex. A normal is a vector that is perpendicular to the face, that points outward. Knowing this, OpenGL can determine where each vertex is actually facing at any given position of the model, and depict the light accordingly. For the most accurate, smooth shading, the normal for each vertex should be an average of the normals of all of the faces that the vertex belongs to. But right now, for simplicity I am just using one.
Cool! Now the models are starting to take some shape :) But obviously something is still wrong. After a couple hours, I realized there was a [1] that was supposed to be a [0] in my normal calculations.
Getting the angel to load was really exciting. This is something I was looking forward to from the beginning, when I just had a triangle. But, the black part is there because the angel is crossing the “clipping plane”. The clipping plane is where OpenGL determines that the face is either too close or too far along the z axis to be drawn. Have you ever played a video game and once you get close to an object it dissapears? So my next task is to make sure that no matter where the coordinates of the model are, my program finds them and displays the model on the screen.


class DatabaseInterface
#include "ucdb.h"
Overview
The abstract DatabaseInterface class provides a unified interface to different SQL type database implementations. Client code can obtain a pointer to a DatabaseInterface, and use it to execute SQL statements, without having to worry about the underlying implementation.
Virtual Methods
sql_exec(std::string query)
Executes an sql_query, and returns the results in a UniversalContainer. Successful SQL queries that return sets of rows, such as a select statements will return an array type container. Members of this array will be map type containers, whose members correspond to the columns of the SQL statement. SQL statements that do not return sets of rows, or which fail, will return a map with the members status_code and message. If the operation was successful the #boolean_value meta-data key will be set to true ensuring that a boolean evaluation of container will be true. status_code will be zero and message will be "success". If the sql operations failed, #boolean_value will be false so that a boolean evaluation of the container will be false, and status_code and message will be set to the error code and corresponding message defined by the underlying implementation.
start_transaction(void)
Starts a new transaction on the database. Returns true on success and false on failure. The DatabaseInterface base class provides a default implementation that simply executes the relevant sql. Implementations that do not need to provide additional semantics may inherit this implementation.
commit(void)
Commits a transaction on the database. Returns true on success and false on failure. The DatabaseInterface base class provides a default implementation that simply executes the relevant sql. Implementations that do not need to provide additional semantics may inherit this implementation.
rollback(void)
Rolls back a transaction on the database. Returns true on success and false on failure. The DatabaseInterface base class provides a default implementation that simply executes the relevant sql. Implementations that do not need to provide additional semantics may inherit this implementation.
UniversalContainer get_db_info(void)
This method returns a map type UniversalContainer that describes the underlying implementation and the details of the database. The only key guaranteed to be present in this map is database_type, which is a string identifying the underlying implementation. In general, the other key value pairs in the map will describe information that the underlying implementation needs to connect to the database.
Specific Implementations
class SQLiteDatabase
#include "ucsqlite.h"
Overview
The SQLiteDatabase class implements the DatabaseInterface class for SQLite3 databases. SQLite provides a simple, in process, file based SQL implementation.
Constructors
SQLiteDatabase(std::string filename)
SQLiteDatabase(char* filename)
These methods construct a new SQLiteDatabase instance based on the provided filename. If there an error occurs opening the file an exception of type UniversalContainer is thrown, with the key code set to uce_DB_Connection. When objects created with these constructors go out of scope, the sqlite connection is cleaned up.
SQLiteDatabase(sqlite3* db)
This constructor creates a new instance based on an existing sqlite3 handle. Unlike the other constructors, the resulting objects do not own the underlying database handle and so when these objects go out of scope they do not clean up the connection.
Implementation Specific Methods
sqlite3* get_db_handle(void)
This method returns the underlying database connection used by the object. This allows for connection parameters to be adjusted and other routines in the databases native library used with the class.
MySQLDatabase
#include "ucmysql.h"
Overview
This class provides an implementation of DatabaseInterface the connects to an underlying mysql database.
Constructors
MySQLDatabase(const char* hostname = NULL, const char* username = NULL, const char* password = NULL, const char* = db_name, unsigned port = 0, const char* socket = NULL, unsigned flags = 0)
MySQLDatabase(UniversalContainer)
The first constructor creates a new instance of MySQLDatabase by passing the provided parameters to the mysql function mysql_real_connection. The second constructor users examines the provided UniversalContainer for keys matching the parameters names of the first constructor, and uses those values to call mysql_real_setup when creating the database instance. The container is then cloned to provide the basis for the information returned from future get_db_info calls. When objects created with these constructors go out of scope, the sqlite connection is cleaned up.
MySQLDatabase(MYSQL* db)
This constructor creates a new instance based on an existing mysql handle. Unlike the other constructors, the resulting objects do not own the underlying database handle and so when these objects go out of scope they do not clean up the connection.
Implementation Specific Methods
MYSQL* get_db_handle(void)
This method returns the underlying database connection used by the object. This allows for connection parameters to be adjusted and other routines in the databases native library used with the class.


Web Metrics Monitoring Example
A page to demonstrate monitoring of web metrics.
Click me:
Increment
Save me:
Flush


Don't settle for less! Be astuter with your tuition rate.
What does your schedule look like? How many hours each day are you available to teach?
Choose which subjects you would like to teach from the following dropdown menus.
Enter any qualifications you may have using the drop down menus.
Where do you plan to teach? Choose a state from the list below.


THtmlViewer, TFrameViewer, and TFrameBrowser components
property OnMouseDouble: TMouseEvent;
The OnMouseDouble event occurs when the mouse left button is double clicked within THtmlViewer or TFrameViewer.


- getCal() - Static method in class FinalProject2
-
get the maximum amount of calories per serving in the dish
no parameters
- getLabel() - Static method in class FinalProject2
-
ask if user wants their dish to be vegetarian, vegan, gluten-free, or dairy-free
no parameters
- getServings() - Static method in class FinalProject2
-
get the number of servings the user wants to make
no parameters
- getTime() - Static method in class FinalProject2
-
get the maximum amount of time user has to make the dish
no parameters
- getType() - Static method in class FinalProject2
-
ask user if they want to make an appetizer, entree, salad, or soup
no parameters


Class PhotoComponent
Access the photos on Vector.
Implements
Inherited Members
Namespace: Anki.Vector
Assembly: Anki.Vector.dll
Syntax
public class PhotoComponent : Component, INotifyPropertyChanged
Methods
| Improve this Doc View SourceDeletePhoto(PhotoInfo)
Deletes the photo from the robot.
public Task<StatusCode> DeletePhoto(PhotoInfo photoInfo)
Parameters
| Type | Name | Description |
|---|---|---|
| PhotoInfo | photoInfo | The photo information. |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation. The task result contains the result of the operation. |
DeletePhoto(UInt32)
Deletes the photo from the robot.
public Task<StatusCode> DeletePhoto(uint photoId)
Parameters
| Type | Name | Description |
|---|---|---|
| UInt32 | photoId | The photo identifier. |
Returns
| Type | Description |
|---|---|
| Task<StatusCode> | A task that represents the asynchronous operation. The task result contains the result of the operation. |
GetPhoto(PhotoInfo)
Download a full-resolution photo from the robot's storage.
public Task<byte[]> GetPhoto(PhotoInfo photoInfo)
Parameters
| Type | Name | Description |
|---|---|---|
| PhotoInfo | photoInfo | The photo information. |
Returns
| Type | Description |
|---|---|
| Task<Byte[]> | A task that represents the asynchronous operation. The task result contains the result of the operation. |
GetPhoto(UInt32)
Download a full-resolution photo from the robot's storage.
public Task<byte[]> GetPhoto(uint photoId)
Parameters
| Type | Name | Description |
|---|---|---|
| UInt32 | photoId | The photo identifier. |
Returns
| Type | Description |
|---|---|
| Task<Byte[]> | A task that represents the asynchronous operation. The task result contains the result of the operation. |
Exceptions
| Type | Condition |
|---|---|
| VectorRequestException | Unable to retrieve photo from Vector |
GetPhotoInfo()
Request the photo information from the robot.
public Task<IEnumerable<PhotoInfo>> GetPhotoInfo()
Returns
| Type | Description |
|---|---|
| Task<IEnumerable<PhotoInfo>> | A task that represents the asynchronous operation. The task result contains the result of the operation. |
GetThumbnail(PhotoInfo)
Download a thumbnail of a given photo from the robot's storage.
You may use this function to pull all of the images off the robot in a smaller format, and then determine which one to download as full resolution.
public Task<byte[]> GetThumbnail(PhotoInfo photoInfo)
Parameters
| Type | Name | Description |
|---|---|---|
| PhotoInfo | photoInfo | The photo information. |
Returns
| Type | Description |
|---|---|
| Task<Byte[]> | A task that represents the asynchronous operation. The task result contains the result of the operation. |
Exceptions
| Type | Condition |
|---|---|
| VectorRequestException | Unable to retrieve photo from Vector |
GetThumbnail(UInt32)
Download a thumbnail of a given photo from the robot's storage.
You may use this function to pull all of the images off the robot in a smaller format, and then determine which one to download as full resolution.
public Task<byte[]> GetThumbnail(uint photoId)
Parameters
| Type | Name | Description |
|---|---|---|
| UInt32 | photoId | The photo identifier. |
Returns
| Type | Description |
|---|---|
| Task<Byte[]> | A task that represents the asynchronous operation. The task result contains the result of the operation. |
Exceptions
| Type | Condition |
|---|---|
| VectorRequestException | Unable to retrieve photo from Vector |


Magister Page:
Ah, yes, Nia's Blood Medusa! How shall we proceed? The common exchange rate is currently 1:20, or perhaps you would prefer a game of chance, popular with this collector's club...
Accept exchange rate of 1:20
Play game. [Guess correctly in 2 tries - 8 Blood Medusas]
Play game. [Guess correctly in 3 tries - 16 Blood Medusas]
Play game. [Guess correctly in 4 tries - 18 Blood Medusas]
Listen to the game instructions.


Select a currency in the left box to convert it to a currency in the right box!
Input an amount you would like to convert (optional):


| Properties' Summary |
boolean
ShowFormulas |
controls whether formulas are displayed instead of their
results.
|
boolean
ShowZeroValues |
enables display of zero-values.
|
boolean
IsValueHighlightingEnabled |
controls whether strings, values, and formulas are
displayed in different colors.
|
boolean
ShowNotes |
controls whether a marker is shown for notes in cells.
|
boolean
HasVerticalScrollBar |
enables the vertical scroll bar of the view.
|
boolean
HasHorizontalScrollBar |
enables the horizontal scroll bar of the view.
|
boolean
HasSheetTabs |
enables the sheet tabs of the view.
|
boolean
IsOutlineSymbolsSet |
enables the display of outline symbols.
|
boolean
HasColumnRowHeaders |
enables the column and row headers of the view.
|
boolean
ShowGrid |
enables the display of the cell grid.
|
::com::sun::star::util::Color
GridColor |
specifies the color in which the cell grid is
displayed.
|
boolean
ShowHelpLines |
enables display of help lines when moving drawing
objects.
|
boolean
ShowAnchor |
enables display of anchor symbols when drawing
objects are selected.
|
boolean
ShowPageBreaks |
enables display of page breaks.
|
boolean
SolidHandles |
enables solid (colored) handles when drawing
objects are selected.
|
short
ShowObjects |
enables display of embedded objects in the view.
|
short
ShowCharts |
enables the display of charts in the view.
|
short
ShowDrawing |
enables the display of drawing objects in the view.
|
boolean
HideSpellMarks |
disables the display of marks from online spelling.
|
short
ZoomType |
This property defines the zoom type for the document.
|
short
ZoomValue |
Defines the zoom value to use.
Valid only if the ZoomType is set to
BY_VALUE.
|
| Properties' Details |
ShowFormulas
boolean ShowFormulas;
- Description
- controls whether formulas are displayed instead of their
results.
|
|
ShowZeroValues
boolean ShowZeroValues;
- Description
- enables display of zero-values.
|
|
IsValueHighlightingEnabled
boolean IsValueHighlightingEnabled;
- Description
- controls whether strings, values, and formulas are
displayed in different colors.
|
|
ShowNotes
boolean ShowNotes;
- Description
- controls whether a marker is shown for notes in cells.
|
|
HasVerticalScrollBar
boolean HasVerticalScrollBar;
- Description
- enables the vertical scroll bar of the view.
|
|
HasHorizontalScrollBar
boolean HasHorizontalScrollBar;
- Description
- enables the horizontal scroll bar of the view.
|
|
HasSheetTabs
boolean HasSheetTabs;
- Description
- enables the sheet tabs of the view.
|
|
IsOutlineSymbolsSet
boolean IsOutlineSymbolsSet;
- Description
- enables the display of outline symbols.
|
|
HasColumnRowHeaders
boolean HasColumnRowHeaders;
- Description
- enables the column and row headers of the view.
|
|
ShowGrid
boolean ShowGrid;
- Description
- enables the display of the cell grid.
|
|
GridColor
::com::sun::star::util::Color GridColor;
- Description
- specifies the color in which the cell grid is
displayed.
|
|
ShowHelpLines
boolean ShowHelpLines;
- Description
- enables display of help lines when moving drawing
objects.
|
|
ShowAnchor
boolean ShowAnchor;
- Description
- enables display of anchor symbols when drawing
objects are selected.
|
|
ShowPageBreaks
boolean ShowPageBreaks;
- Description
- enables display of page breaks.
|
|
SolidHandles
boolean SolidHandles;
- Description
- enables solid (colored) handles when drawing
objects are selected.
|
|
| ShowObjects
|
| ShowCharts
|
| ShowDrawing
|
HideSpellMarks
boolean HideSpellMarks;
- Description
- disables the display of marks from online spelling.
|
|
ZoomType
short ZoomType;
- Description
- This property defines the zoom type for the document.
- See also
- ::com::sun::star::view::DocumentZoomType
|
|
ZoomValue
short ZoomValue;
- Description
- Defines the zoom value to use.
Valid only if the ZoomType is set to
BY_VALUE.
|
|
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.


[CsvReader] element index
Package indexes
default
CSV_FilterChain
Csv
All elements
c
d
g
h
k
m
n
p
r
s
u
v
_
_
top
__construct
Csv_Reader::__construct()
in Reader.php
Class constructor
__destruct
Csv_Reader::__destruct()
in Reader.php
Destructor method - Closes the file handle
c
top
$current
Csv_Reader::$current
in Reader.php
count
Csv_Reader::count()
in Reader.php
Get total rows
Csv_Reader
Csv_Reader
in Reader.php
current
Csv_Reader::current()
in Reader.php
Get current row
d
top
$dialect
Csv_Reader::$dialect
in Reader.php
g
top
getDialect
Csv_Reader::getDialect()
in Reader.php
Get the current Csv_Dialect object
getPath
Csv_Reader::getPath()
in Reader.php
Get the path to the csv file we're reading
getSkippedLines
Csv_Reader::getSkippedLines()
in Reader.php
Get the amount of lines that were skipped due to malformed data
h
top
$handle
Csv_Reader::$handle
in Reader.php
k
top
key
Csv_Reader::key()
in Reader.php
Return the key of the current element.
m
top
MAX_ROW_SIZE
Csv_Reader::MAX_ROW_SIZE
in Reader.php
Maximum row size
n
top
next
Csv_Reader::next()
in Reader.php
This method checks if the end of file is reached
p
top
$path
Csv_Reader::$path
in Reader.php
$position
Csv_Reader::$position
in Reader.php
r
top
Reader.php
Reader.php
in Reader.php
rewind
Csv_Reader::rewind()
in Reader.php
Rewind the Iterator to the first element.
s
top
$skippedlines
Csv_Reader::$skippedlines
in Reader.php
setDialect
Csv_Reader::setDialect()
in Reader.php
Change the dialect this csv reader is using
setPath
Csv_Reader::setPath()
in Reader.php
Set the path to the csv file & initiate file
u
top
unescape
Csv_Reader::unescape()
in Reader.php
Removes the escape character in front of our quote character
v
top
valid
Csv_Reader::valid()
in Reader.php
Check if there is a current element after calls to rewind() or next().
c
d
g
h
k
m
n
p
r
s
u
v
_


Home
About
Music
Tour
Gallery
米 津 玄 師
Yonezu Kenshi
My favorite singer
Yonezu Kenshi
Web Programming Practice
Programming Assignment
Jung, Je Won
Student #<PHONE_NUMBER>


MATLAB xUnit Test Framework: How to Test an Error Message
It's surprising to most people (but not quality engineers) how often programmers make errors in error-handling code. Because of this unfortunate truth, it is useful to write unit tests that verify that your MATLAB code throws the proper error, at the proper time.
The assertion function that makes this task easy is assertExceptionThrown. This example shows how to write a unit test that verifies the "Too many input arguments" error for the cos function.
Your first step is to determine the error identifier associated with the error message. You can find out the error identifier by using the lasterror function.
If you call cos with two input arguments, like this:
cos(1, 2)
you get this error message:
Error using ==> cos Too many input arguments.
Then if you call lasterror, you get this output:
ans =
message: [1x45 char] identifier: 'MATLAB:maxrhs' stack: [0x1 struct]
So the identifier associated with this error message is 'MATLAB:maxrhs'.
When you write your test function, you'll form an anonymous function handle that calls cos with the erroneous additional input argument.
f = @() cos(1, 2)
f = @()cos(1,2)
You then pass this function to assertExceptionThrown, along with the expected error identifier.
assertExceptionThrown(f, 'MATLAB:maxrhs');
assertExceptionThrown verifies that when f() is called, an error results with the specified error identifier.
Here's our error condition test for the cos function.
cd examples_general type testCos
function test_suite = testCos initTestSuite; function testTooManyInputs assertExceptionThrown(@() cos(1, 2), 'MATLAB:maxrhs');
Run the test using runxunit.
runxunit testCos
Test suite: testCos Test suite location: C:\Users\psexton\Documents\GitHub\matlab-xunit-doctest\doc\examples_general\testCos.m 20-Feb-2014 19:59:07 Starting test run with 1 test case. . PASSED in 0.010 seconds.


To load an image, specify the file path in the constructor:
To save the image, use the save method. It will automatically use the file you loaded the image from:
You can also specify a new file to save to, similar to a "Save As...", and future calls to save() will save to this new file:
You can also show the image:
You can scale images using the "scale" function, so for instance to create a thumbnail.
You can erode an image using:
You can crop an image using:
you can find all the Image operations here in the documentation
Search type functions return Feature Sets, for instance, finding all lines in an image:
To find blobs its as easy as:
most of the features functions are prefixed with find they can be found in the Image documentation or you can also view a the types of features in the documentations
You can use color to define various types of color for displaying text or marking up images:
see the color documentation for more information.
ColorCurve is a color spline class for performing color correction. It can takeas parameters a SciPy Univariate spline, or an array with at least 4 point pairs. Either of these must map in a 255x255 space. The curve can then be used in the applyRGBCurve, applyHSVCurve, and applyInstensityCurve functions:
see the color curve documentation for more info
A color map takes a start and end point in 3D space and lets you map a range of values to it. Using the colormap like an array gives you the mapped color.
This is useful for color coding elements by an attribute:
see the color map documentation for more info
Please check out the youtube channel for demos, or join the mailing list to find out more.


git-clone-server
A microservice to clone git repositories and serve the files for download. Enter a git URL:
git-clone-server uses node.js and Express. It is MIT licensed. The source code is on GitHub.
A microservice to clone git repositories and serve the files for download. Enter a git URL:
git-clone-server uses node.js and Express. It is MIT licensed. The source code is on GitHub.


◄
Leaflet.Control.Search
Custom Filter Example:
search markers with
Fuzzy Search
, using
Fuse.js
by Kirollos Risk
Search restaurants in Rome, data by
OSM Overpass
Example:
pizza
,
vege
,
japa
,
giappo
,
cucina romana
,
chine
...
Website
•
Stefano Cudini


| DOSE: |
repeated |
insufflated |
Cocaine |
(powder / crystals) |
[Erowid Note: Driving while intoxicated or tripping is dangerous and irresponsible because it endangers other people. Don't do it!]
This was my third time trying coke. With my first experience I had bought a gram and a friend of mine cut some lines up. I snorted a very small line and within minutes was feeling very talkative and had warm body rushes, my throat was also completely numb, but nothing a cheaper pill wouldn't have done for longer (my friend also commented that this was the strongest coke he had ever had). That night I felt sick to my stomach and had no desire to try (or at least pay for) coke again.
A year later and I was at a friendís house where a kid was cutting up lines for free. I resisted the offer for most of the night, sitting in a basement coked out with a bunch of guys just doesn't appeal to me very much. Just before I left to head to a party I accepted a couple lines. At the party I was very talkative and felt like I had a lot of caffeine in my system, also I was able to drink a lot of alcohol without any ill effects, which just decreased my inhibitions even more so. It definitely wasn't as strong as my first experience. It wore off, no ill effects and no desire for more.
A few days ago I got off work and met up with a friend of mine. I rode with him and his buddy to get a 'teener' (gram), and since they offered some to me for free, I accepted a small line. Again, same effects. It simply felt like I was over-caffeinated, although I was surprisingly relaxed. Normally I don't like rap music that much, but I was very appreciative of the creativity of the lyrics that were playing in the car. I know it's irresponsible to drive, but we finished the gram just driving around enjoying the music. Each time my friend would cut a line he would give me another small line at my request. Since it was free, and since I was feeling rather good, I accepted. I will admit that with this experience I was enjoying the coke, but again, it wasn't anything special, I was just enjoying the moment. Since we had coke in our possession, it was too hard to resist just doing another line.
Towards the end of the gram, I was actually irritated that I was getting cut a smaller line than my friends, and when that thought entered my head I was shocked and I had to mentally slow myself down and realize I was better than that. After that, I was fine... we finished the gram, and although my friends brought up the idea of getting more I had absolutely no desire to. We smoked some weed (which only gave me a strange head buzz) and that helped the comedown. I went home, ate some food, and fell asleep with no problems.
So I learned a few things about coke. First off, I think there's way too much hype surrounding it. The effects aren't that impressive, especially for the money I pay. In fact, I would never actually pay for coke again, but if someone offered it for free I would probably take it just for the hell of it, set/setting pending. With my latest experience, we just kept doing it just because it was there. Each experience I had was inconsistent in terms of quality.
Overall, in my opinion, it's not that big of a deal.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


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Drive Safely Assistant for Android and JVM provides actionable information to a driver how to prevent a road accident. It recognizes driver’s drowsiness, distraction, belt presence, phone usage, eating, smoking, and camera sabotage.
Profile TensorFlow Lite model and measure its performance using FPS, model initialization time, inference time, and memory consumption on the smartphone. You can tweak model runs with different delegates (CPU, GPU, NNAPI, HEXAGON), XNNPACK option, number of threads.
Experience in Kaggle-based competitions – Gold medal in Image Matching Challenge 2022, RSNA-MICCAI Brain Tumor Radiogenomic Classification; Silver medal in Google Universal Image Embedding; Bronze medal in Happywhale - Whale and Dolphin Identification.
The trained neural model solves an image classification task that predicts whether the human's mouth is opened or closed.


The Birds and Trees of North America displays Brasher’s desire to convey birds in their natural habitat. Rex Brasher had a dream since the age of eight to discover and display birds in North America. Brasher achieved his goal by recording more than twice the amount of birds in North America than his predecessor James Audubon. Brasher had a vengeance towards Audubon because he would not meet with his dad when he took a journey just to see him. Once Brasher heard this story, he made it his life’s mission to record more birds than Audubon. During his journey throughout North America, Brasher recorded several species of birds that are now extinct such as the Heath Hen, Passenger Pigeon and Eskimo Curlew. These birds may have never been discovered if not for Brasher. After his journey, Brasher decided to have his drawings printed in black and white for cost efficiency. He received these prints and established a new technique by combining airbrushing and the use of stencils to color the prints. In this print of the flamingos, Brasher focused on the perfection of these birds such as making them as lifelike as possible and portraying the flamingos in their natural habitat. There is also rich color in this print with the bold pinks which came from the airbrush and stencil technique that Brasher developed for these prints.
Captured in Audubon’s publication of Birds of America, the Prothonotary Warbler is presented with explicit detail and accuracy. The Prothonotary Warbler represents only one of the five colored prints produced by William Home Lizars. Lizars selected five drawings to demonstrate the different treatments of small and large birds in the printing process. Shortly after Lizars produced these five colored prints, members of his studio involved in the coloring process of the prints went on strike. As a result, Audubon turned to the Havell family to produce the colored prints for his book. Audubon presents two prothonotary warblers, each in a different position. The placement of the two warblers provides information of how the species look from different angles, providing visual clues of any marks, textures and forms that contribute to identification. The Prothonotary Warbler may be found in the floodplain forests and swampy regions from southern New Jersey to north-central Florida and may be found in the mainland extending to Texas. As depicted by Audubon, the prothonotary warbler displays high contrast between the lower and upper halves of the body. The distinct color palette of a yellow body in contrast with its blue to gray wings and olive colored back can lead to identification of this species of warbler alone. In comparison to the other birds that Audubon captures in his published works, the warbler is small in size. In celebration of Audubon who has contributed to the field of ornithology through his extensive documentation of birds, the Prothonotary Warbler presents a reminder of extensive dedication and research that Audubon conducted during his lifetime.
Theodore Jasper displays the real life aspects and scenery surrounding the American Barn Owls, Lanier Falcon, and the Pygmy Burrowing Hawk in this print. Jasper spent his lifetime studying ornithology; the scientific study of birds. Jasper’s prints were similar because of his tendency to group different birds with no correlation together in one print. That is displayed in this print with the Owls, Falcon, and Hawk. All of Jasper’s prints were reduced to one quarter of their natural size, which affected the cost of the book. The important aspect of this print and all of the prints in this book was the affordability. Struders Popular Ornithology: the Birds of North America was the first bird identification book that was affordable for common people, unlike prints that came before such as James Audubon’s book of North American birds. Although not the best quality of prints, Struders Popular Ornithology: the Birds of North America was one of the most desired bird books of the nineteenth century based on its affordability.
The Night Heron is a print from one of Audubon’s most respected works: The Birds of America. Audubon provides basic facts about the specimen in his field guide accompaniment. The Night Heron is a southern bird known by many unofficial names in different states. A list of these names includes: “The Indian Pullet,” the “Gros-bec,” the “Indian Hen” and the “Qua-bird.” These birds migrate at night making “loud hoarse notes that resemble the syllable Qua.” The Night Heron is important for understanding the overall work of Audubon because it is an example of a plate from his most famous undertaking. This piece in particular also gave the ornithological community new information about the Night Heron through the field guide. He found that three molting periods are required for the plumage of the Night Heron to fully mature. The immature birds were being misclassified as different subspecies when they were actually the very same bird. There are many other cases from the field guide as well, where Audubon was a contributor to discovering the anatomy and behavior of the bird under observation. In fact, he is credited with discovering 25 new species and 12 subspecies during his travels. He was even elected as a member of the Royal Society of London for his ideas in scientific work.
Since the name of Audubon is so universally associated with birds, his paintings of terrestrial mammals of North America might be a surprise for many people. After the publication of The Birds of America that earned John James Audubon worldwide fame, the last ten years of Audubon’s life were spent on documenting four-legged mammals. Even though the proposed project was very difficult to accomplish, Audubon thought he would collect, identify, paint the portraits, and write the description of each of them. With such an enthusiasm, he immediately announced the future publication of The Viviparous Quadrupeds of North America. Soon, he received a letter from his friend John Bachman who offered his help saying “…are you not too fast in issuing your prospectus…? … The animals have never been carefully described, and you will find difficulties at every step. Books cannot aid you much. I have studied the subject more than you have… Say in what manner I can assist you.” As a result, John Bachman did a significant contribution in producing the Quadrupeds by determining the validity of species, writing all scientific descriptions, and contributing his personal observation on habits of the animal. On the other hand, Audubon with the help of his son John Woodhouse Audubon, painted and produced 150 drawings that were included in The Quadrupeds of North America. Audubon used several artists to reprint his paintings. For example, a skilled lithographer, J.T. Bowen who was from Philadelphia had a contract with Audubon to lithograph and color his paintings. Printing, on the other hand was done by other Philadelphian craftsmen.


DLR Morning Schedule
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5:00 a.m. to 10:30 p.m.
You can Listen Live to streaming audio
of our broadcast or download programs from our Podcast.
Please refer below for our current morning schedule.
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| 5:00 a.m | Dawn Air | Dawn air weekends | Sunday Magazine | ||||
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| 6:00 a.m | Weekend Reflections | ||||||
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| 7:00 a.m | local news | Weekend wrap | Radio U | ||||
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| 8:00 a.m | Classical Roots | What can you say | University on the air | ||||
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| 9:30 a.m | Animal Talk | ||||||
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The Cart Lab Design Challenge is an annual event organized by the UW–Madison Cartography Lab and the Department of Geography. The Design Challenge is a one-day mapping workshop that challenges students (cartographers and geographers) to create a map or a series of maps during an eight-hour stretch. Teams of students work with community partners, topic experts, and data experts on real-world issues. In the past, our students have mapped the hazardous waste trade in North America, temporal fossil data to better understand past climates, community resources provided by a local community center making an argument for a new facility, and recidivism in our community.
Check out each Design Challenge below, including maps, awards, and blog posts.
In collaboration with Jenna Loyd, Kelly Lytle Hernandez, and Transforming Justice, this year's Design Challenge will explore everyday experiences of policing in Milwaukee. Drawing on video documentaries and workshop transcripts, we will explore how these experiences build on histories of segregation and how they continue to shape divisions in the city, access to shared spaces, and well-being.
Last year's Design Challenge explored the geographies of recidivism in Madison through feminist mapping! Working Catherine D’Ignazio, we learned about feminist visualization principles and then put theory into practice in an all day mapping event. In teams, we worked with the Journey Home Initiative of the United Way of Dane County to make maps that have a positive and productive impact on our community disrupting the cycle of recidivism in Madison.
PublicityLorem ipsum dolor sit amet, consectetur adipiscing elit. Sed consectetur sem eu efficitur blandit. Sed aliquam sagittis orci, a varius dolor tincidunt a. Integer et erat vitae augue sagittis imperdiet. Nunc laoreet facilisis pharetra. Nam in mauris efficitur, interdum magna quis, dapibus massa. Sed eget turpis porta sem dignissim euismod. Nulla vel dui justo. Vestibulum aliquam hendrerit erat. Ut eget tempor mi. Integer egestas tellus vitae tellus tincidunt aliquet.
For this second annual Design Challenge, students generated new insight from fossil records in North America. They developed unique visualizations to facilitate communication of trends in multidimensional spatio-temporal data.
Award Winners | PublicityEighteen geography students spent their Valentine’s Day wading through a complicated, real-world dataset, to create data visualizations that will help researchers better understand the hazardous waste trade in North America. Dr. Sarah Moore obtained EPA records of transnational trade of hazardous waste through a pair of Freedom of Information Act requests. The data are big and messy, and real. They arrived as scans of shipping labels, which had to be coded. Students over the course of two semesters have worked to code the data, putting it into a format that can be analyzed. With a little over a quarter of the data entered, it was time to start digging around to see what stories could be unearthed.
Publicity


Climate vs Weather
While often considered to be one in the same, climate and weather are actually two different things.
Learn MoreExplaining the truth about climate change.
While often considered to be one in the same, climate and weather are actually two different things.
Learn MoreExplains what anomalies are, and why they're important in taking measurements.
Learn MoreExplains the Greenhouse Effect, including the physics behind it, which gasses causes it, and an interactive demo!
Learn MoreWhat are internal factors, and how do they affect our climate?
Learn MoreDriven by forces from outside of the climate system (Earth's orbit and the Sun).
Learn More


Dawn (formerly E'Dawn) to guest on 'Radio Star'
by beansssAccording to reports on November 1, solo artist Dawn (E'Dawn) will be attending a recording for MBC's 'Radio Star' this November 6!
This will mark Dawn's first ever variety appearance after his solo artist debut, set for November 5. Many will be looking forward to Dawn's guest appearance on 'Radio Star', including his future promotion plans, his ongoing relationship with HyunA, and more.
'Radio Star' with guest Dawn is expected to air some time in mid-November. Meanwhile, Dawn's solo debut single "Money" drops on November 5 at 6 PM KST!


Ingredients
- 1 big bunch of kale, rinsed, ribs removed and torn into large pieces
- 3/4 cup EVOO, 2 tablespoons of which was Meyer lemon olive oil
- 1/2 cup Parmigiano, microplaned
- 2 cloves garlic, smashed and rough chopped
- 1/2 cup pine nuts
- Salt and pepper to taste
- 1 tablespoon lemon juice, fresh
Directions
-
Blanch the kale in boiling salted water for about 3 minutes and chill down in a cold water bath, drain and squeeze excess water. Place into small work bowl of food processor and pulse to start breaking up the kale, add rough chopped garlic, process, add pine nuts, pulse several times. Slowly add the olive oils and lemon juice, process until everything is broken down. It will never be real smooth. Finally add the cheese and pulse a few times. Season with salt and pepper. If serving with pasta grate a little extra cheese over and add EVOO to the hot pasta, toss with pesto, serve with additional grated cheese.
-
These are the basics of my recipe and the way that I prefer it, but you can add more garlic, lemon, or oil if you like.
Makes about 1- 1 1/2 cups
Recipe is from this website


However, the first rule of thumb is "don't write like a scientist." Your readers didn't click on your piece, because they want to know
more about the miniscule 'details' - they want to know the 'finale', the point.
You have to get to the good stuff, the meat of the paper, as soon as possible (really, right from the get-go). That means asking: What
did the researchers find? How do they know that? What does it mean to ME, the reader? Is it simple enough to be profound or profound enough to be simple?
Identify the message: it should be easily understood, memorable, focused, and framed to be relevant to your audience. See the example graphic below (from here).
Second rule: Go easy on the numbers. Select a few, very powerful numbers and leave everything else out. For example, can your audience VISUALIZE what these numbers mean?
"47.65% (p < 0.0532)" = "about half"
"32 million Americans" = "1-in-10 Americans"
"The largest dinosaurs had brains about 8 cm in diameter" = "The largest dinosaurs had brains about the size of a baseball."
Third rule: Avoid jargon that an eighth-grader may not recognize. That's generally where the average American is in science literacy. They
had high school biology 25 years ago, but they might not have been paying attention. Here are some examples of how you can communicate more broadly by using everyday language:
"To conduct a study that will help determine" = "To study"
"Elucidated the mechanisms by which" = "Showed how"
"Central nervous system interactions between gustatory afferent activities and the quality and quantity of saliva" = "Why we drool"
Obviously, there are exceptions to rules two and three. You don't want to compromise scientific accuracy to the point of distorting the truth.
If you HAVE to use jargon, 1) keep it to a minimum; 2) define it before introducing the term (i.e., the definition must be provided before you use the term).
But mostly try to avoid jargon, including number jargon. Here are some sites that might help you identify jargon: 1, 2.
Another way of identifying jargon: Did I know the definition of this word before taking this class?
Fourth rule: The headline and lead sentences are often the ONLY chance you get with most readers - especially in the mobile news age. It is not
uncommon to write and revise those multiple times to get those right. Moreover, the headline and lead of a SciComm piece will differ from
what is considered interesting to a scientist. For a scientist, we might think about a general statement of the unsolved questions of the field.
For example, one of the scientist summary pieces we will read is titled: "How the human brain segments continuous experience." While this is a GREAT
headline for memory scientists (summarizing research into how each memory becomes its own distinct event), it is not tuned to catch the public eye; it uses language
more oriented to a scientist (segment, continuous experience), and leads with the unsolved question rather than what the paper it covers MEANS to
a general reader.
The most compelling stories have a narrative arc, outrageous methodology, compelling characters, extraordinary effort, paradigm shifts -- something that makes you go,
"I want to know more." Make the story personal; use analogies and metaphors; use humor and/or drama; provide statistics; hook your readers with something surprising
or counterintuitive; and be definitive. Ask:
Is the message clear?
Is there too much / any jargon?
Is the story framed to be relevant? Does it answer the 'So What' or 'Why Should We Care' questions?
Do you support your message with a story, metaphor, statistic, or something else to make it memorable?
These tips were largely provided by Jory Weintraub, who teaches Science Communication here at Duke, and Karl Bates, who runs the Duke Research blog and who will work with
you on your final Duke SciComm pieces. He will do an annotated edit-track on each paper and return your paper to show what he's thinking before you publish your piece together.
He will visit class and discuss how you will revise your piece for 10-15 minutes on June 13th.
Finally, every blog post ALSO needs two or three relevant images (must know the copyrights/provenance/credit on each) AND a headshot of
the author with name and position in school. If you don't have a headshot, we can set-up a time to take one of you towards the end of the course.
We will discuss in class making sure that you have the appropriate copyright license as well. Make sure you link to, or include a reference of, the article that you cover.
In class, we will deconstruct academic articles as well as science communication pieces so that you become critical consumers of both
styles of writing. Here is a list of science communication pieces that we will cover:
Lombrozo, T. (2018). The Psychology Of Fake News. Retrieved from NPR.org website: https://www.npr.org/sections/13.7/2018/03/27/597263367/the-psychology-of-fake-news.
Darling, N. (2017). Attracting WEIRD Samples. Retrieved from Psychology Today website: https://www.psychologytoday.com/blog/thinking-about-kids/201710/attracting-weird-samples
Yong, E. (2018, January 23). When Your Eyes Move, So Do Your Eardrums. Retrieved from The Atlantic website: https://www.theatlantic.com/science/archive/2018/01/when-your-eyes-move-so-do-your-eardrums/551237/
Dean, S. (2018, January 25). Our Eye Movements Also Move Eardrums, And Nobody Knows Why. Retrieved from https://www.sciencealert.com/eye-movements-cause-vibrations-eardrums-hearing-weird-brain
Vedantam, S., Shah, P., & Boyle, T. (2018). Buying Attention | Hidden Brain : NPR. Retrieved from https://www.npr.org/2018/01/01/574073721/our-mental-space-under-attack
Vedantam, S. (2017). Radio Replay: Life, Interrupted | Hidden Brain : NPR. Retrieved from https://www.npr.org/2017/12/01/567834281/radio-replay-life-interrupted
Malcolm, L. (2017, July 5). The creation of emotions | All in the Mind. Retrieved from https://www.abc.net.au/radionational/programs/allinthemind/the-creation-of-emotions/8576540
Chen, A. (2018). How Hunger Pangs Can Make Nice People “Hangry.” Retrieved from NPR.org website: https://www.npr.org/sections/health-shots/2018/06/11/618395072/how-hunger-pangs-can-make-nice-people-hangry
Strickland, A. (2016). This is what emotions look like in your brain. Retrieved from CNN website: https://www.cnn.com/2016/10/06/health/spontaneous-emotions-brain-scans/index.html
Britt, M. (2014). Facebook Experiment | The Psych Files. Retrieved from http://www.thepsychfiles.com/2014/07/ep-221-facebook-study-a-brief-summary-and-did-they-use-informed-consent/
Gutman, R. (2017, November 20). The Connected Vocabularies of Six-Month-Olds. Retrieved from The Atlantic website: https://www.theatlantic.com/science/archive/2017/11/babies-language-vocabularies/546320/
Shute, N. (2014). Our Brains Rewrite Our Memories, Putting Present In The Past. Retrieved from NPR.org website: https://www.npr.org/sections/health-shots/2014/02/04/271527934/our-brains-rewrite-our-memories-putting-present-in-the-past
Leung, W. (2019). Record and replay: How a Canadian-made app is aiming to help Alzheimer’s patients improve their daily lives - The Globe and Mail. Retrieved from https://www.theglobeandmail.com/canada/article-toronto-teams-hippocamera-a-high-tech-memory-aid-for-alzheimers/
Malcolm, L. (2019). A highly superior memory | All in the Mind. Retrieved from https://www.abc.net.au/radionational/programs/allinthemind/a-highly-superior-memory/11021088
Noe, A. (2017). More Bad News For Brain-Training Games. Retrieved from NPR.org website: https://www.npr.org/sections/13.7/2017/07/14/536759455/more-bad-news-for-brain-training-games
Hamilton, J. (2017). In Memory Training Smackdown, One Method Dominates. Retrieved from NPR.org website: https://www.npr.org/sections/health-shots/2017/10/23/558767704/in-memory-training-smackdown-one-method-dominates
Vedantam, S. (2018). Looking Back | Hidden Brain : NPR. Retrieved from https://www.npr.org/2018/06/21/622298227/radio-replay-looking-back
Lombrozo, T. (2014). Blame Your Brain: The Fault Lies Somewhere Within. Retrieved from NPR.org website: https://www.npr.org/sections/13.7/2014/06/16/322556750/blame-your-brain-the-fault-lies-somewhere-within
Vedantam, S., & Penman, M. (2017). When It Comes To Politics and “Fake News,” Facts Aren’t Enough | Hidden Brain: NPR. Retrieved from https://www.npr.org/2017/12/25/572162132/enter-title
McRaney, D. (2018, March 26). YANSS 123 – Active Information Avoidance. Retrieved from: https://youarenotsosmart.com/2018/03/26/yanss-123-active-information-avoidance/
Inman, M. (2017). Believe. Retrieved from The Oatmeal website: https://theoatmeal.com/comics/believe
Fraser, S. (2013). Can Eyewitnesses Create Memories? Retrieved from https://www.npr.org/2013/11/29/182671574/can-eyewitnesses-create-memories
Stix, G. (2018). A Math Function Describes How Whole Societies Remember--and Forget. Retrieved from Scientific American website: https://www.scientificamerican.com/article/a-math-function-describes-how-whole-societies-remember-and-forget/
Cummins, E. (2018). How long can an event hold humanity’s attention? There’s an equation for that. Retrieved from Popular Science website: https://www.popsci.com/how-collective-memories-decay
Kaufman, S. B. (2018). Creativity from Constraints with Patricia Stokes. Retrieved from: https://scottbarrykaufman.com/podcast/creativity-constraints-patricia-stokes/
Yuhas, D. (2014). Curiosity Prepares the Brain for Better Learning. Retrieved from Scientific American website: https://www.scientificamerican.com/article/curiosity-prepares-the-brain-for-better-learning/
Dunlosky et al. (2013). What works, what doesn’t. Scientific American Mind, 24(4), 47 – 53
Supiano, B. (2019, February 6). Should You Allow Laptops in Class? Here’s What the Latest Study Adds to That Debate. The Chronicle of Higher Education. Retrieved from https://www.chronicle.com/article/Should-You-Allow-Laptops-in/245625
Lombrozo, T. (2013, August 19). Stop Multitasking! It’s Distracting Me (And You). Retrieved from NPR.org website: https://www.npr.org/sections/13.7/2013/08/19/213439794/stop-multitasking-it-s-for-other-people-s-good
We will also spend the first day of class specifically discussing science communication and build each day on that foundational material.
To make the writing process easier, we are going to start small. First, we'll deal with non-Duke articles. You'll write a tweet summary of articles (May 20),
write SciComm headlines (May 21), write an opening paragraph for a SciComm piece (May 23), and write multiple paragraphs for a SciComm piece (May 31).
After gaining experience with this style of writing, you'll select your specific Duke article, outline your piece (including headline; June 10),
write a first draft of your SciComm piece (June 13), and then revise for your final (course) draft due June 19. All along the way, your classmates and I
will provide feedback that will help you improve your science communication skills. Ultimately, this piece will be published on the Duke Research blog,
which you can show your family and friends and any future employers interested in knowing how well you write to a general audience.


A command that contains values (levels) for five fingers.
More...
|
| int[] | levels = new int[5] |
| | Input level for specific finger. More...
|
| |
A command that contains values (levels) for five fingers.
◆ SG_FingerCmd()
| SGCore.Haptics.SG_FingerCmd.SG_FingerCmd |
( |
| ) |
|
|
protected |
Creates a new haptic Command for the hand.
◆ Equals()
| virtual bool SGCore.Haptics.SG_FingerCmd.Equals |
( |
SG_FingerCmd |
item | ) |
|
|
virtual |
Check if this command contains the same values as another.
- Parameters
-
- Returns
◆ GetLevel()
| int SGCore.Haptics.SG_FingerCmd.GetLevel |
( |
int |
f | ) |
|
Get the level of a specific finger.
Marked internal to prevent IndexOutofRangeExceptions
- Parameters
-
- Returns
◆ SameLevels()
| bool SGCore.Haptics.SG_FingerCmd.SameLevels |
( |
SG_FingerCmd |
item | ) |
|
Non-overridebale function that checks specifically for FFB levels.
- Parameters
-
- Returns
◆ SetLevel()
| void SGCore.Haptics.SG_FingerCmd.SetLevel |
( |
int |
f, |
|
|
int |
lvl |
|
) |
| |
Set the level of a specific finger.
Marked internal to prevent IndexOutofRangeExceptions
- Parameters
-
◆ ToString()
| override string SGCore.Haptics.SG_FingerCmd.ToString |
( |
| ) |
|
Create a string representation of this finger command.
- Returns
◆ Validate()
| virtual int SGCore.Haptics.SG_FingerCmd.Validate |
( |
int |
value | ) |
|
|
protectedvirtual |
◆ levels
| int [] SGCore.Haptics.SG_FingerCmd.levels = new int[5] |
|
protected |
Input level for specific finger.
◆ IndexLvl
| virtual int SGCore.Haptics.SG_FingerCmd.IndexLvl |
|
getset |
Level of the Index Finger.
◆ Levels
| virtual int [] SGCore.Haptics.SG_FingerCmd.Levels |
|
getset |
Access the levels of this FingerCmd.
◆ MiddleLvl
| virtual int SGCore.Haptics.SG_FingerCmd.MiddleLvl |
|
getset |
Level of the Middle Finger.
◆ PinkyLvl
| virtual int SGCore.Haptics.SG_FingerCmd.PinkyLvl |
|
getset |
Level of the Little Finger or Pinky.
◆ RingLvl
| virtual int SGCore.Haptics.SG_FingerCmd.RingLvl |
|
getset |
Level of the Ring Finger.
◆ ThumbLvl
| virtual int SGCore.Haptics.SG_FingerCmd.ThumbLvl |
|
getset |
The documentation for this class was generated from the following file:
- C:/Gitlab-Runner/builds/yDcLA2Qt/0/senseglove/senseglove-backend/sgcorecs/src/SGCoreCs/SG_FingerCmd.cs


This Vanilla JavaScript generative art experiment uses getImageData() method to scan image for pixel information, calculates relative brightness of each area, creates a simple particle system and adjusts speed and opacity of each particle based on brightness of the area the particle is currently moving over.


dapi
Version 1.0.1
Royal Farms Application Programming Interface
Support Information
This is the documentation for the Royal Farms Authentication Service.
This service is currently maintained and supported by
David Haifley.
Dependencies
Services
Databases
-
[rfsql]/*
-
[rfmongo]/*
-
[rf-services:us-east4:dauth-sql]/dauth
-
[c202-01]/PDICompany_202_01
-
[c202-09]/PDI_Warehouse_202_01


Before Change
p = pickle.dumps(policy)
with tf.Session(graph=tf.Graph()):
policy_pickled = pickle.loads(p)
action2, prob2 = policy_pickled.get_action(obs)
assert env.action_space.contains(action1)
assert np.array_equal(action1, action2)
assert np.array_equal(prob1["mean"], prob2["mean"])
After Change
// assign it to all one
return_var.load(tf.ones_like(return_var).eval())
output1 = self.sess.run(
policy.model.outputs[:-1],
feed_dict={policy.model.input: [obs.flatten()]})
p = pickle.dumps(policy)


Home
QUESTIONS
1. Select your gender
Male
Female
Other
2. Enter your age
3. What is your current location?
4. Are you a diabetic person?
Yes
No
5. Do you get any frequent headaches?
Yes
No
6. Are you able to smell odour ?
Yes
No
7. Do you have any of the following symptoms: Sorethroat,diarrhea or nasal congestion?
Yes
No
8.Do you suffer from moderate to high fever for couple of days/weeks?
Yes
No
9.Do you suffer from asthma/lung/heart disease?
Yes
No
10.do you have bp?
Yes
No
11.have you traveled any where in the past 30 days?
Yes
No
Submit


Welcome to Email Sender (Frontend) !
This web application facilitated to send emails to users
Getting Started
To get you started you can simply clone the email-sender repository and install the dependencies:
Prerequisites
We also use a number of Node.js tools to initialize and test email-sender. You must have Node.js and its package manager (npm) installed. You can get them from here.
Install Dependencies
We have two kinds of dependencies in this project: tools and Angular framework code. The tools help us manage and test the application.
Note:
- Install xampp in your local machine, you can get xampp from here
- Refere this step to install xampp in your local machine
Install grunt dependancy from package.json
$ npm install
You should find out that you have two new folders in your project. node_modules - contains the npm packages for the tools we need
Run the Application
Install grunt dependancy from package.json
$ npm install
Once grunt installed then you can run following command to deployed project [dist]
$ grunt (deployed project)
$ grunt watch (It will watch changes in project and deploy project if changes found)
Install xampp server
Check, Download link
copy paste application dist folder into xampp\htdocs\CREATE_PROJECT_FOLDER folder.
run xampp server using xampp console.
type in browser, http://localhost/PROJECT_FOLDER/dist


{{{editLink this}}} Register Browser Application A browser application, such as the sample Simple Viewer App. Developer Contact Information The name of the developer who will own this application. This is the only individual who will be able to request updates to the client registrations. Developer Name: Developer Email: Must be a valid email address Application Information Client Name: Something users will recognize and trust Description of Application: This may be displayed to potential users of your application Application Homepage URL: This may be displayed to potential users of your application Client Logo URL: Will be shown on consent screen Link To Application Privacy Policy: Will be shown on consent screen Link To Application Terms of Service: Will be shown on consent screen Register URIs Redirect URIs: Your applications callback URI which specifies where we redirect users after they have chosen whether or not to authenticate your application. Enter as many as you would like. Must be over HTTPS unless registered as a localhost. http://localhost:3000/signin-callback Post Logout URIs: Where users can be returned to after logging out. Must be over HTTPS unless registered as a localhost. http://localhost:3000/signout-callback Submit {{>thank_you_message<EMAIL_ADDRESS>{{>error_message<EMAIL_ADDRESS>subject='BrowserApplication'}} {{>loaderScript}}


cyphort
Businessmodel of Cyphort
Customer Segments
Cyphort has a mass market business model, with no significant differentiation between customer segments. The company targets its offering at firms that seek advanced online threat protection.
Value Proposition
Cyphort offers three primary value propositions: performance, cost reduction, and brand/status.
The company has demonstrated strong performance through tangible results for customers. High-profile examples of positive outcomes include the following:
- A financial service provider used Cyphort’s solution to reduce capital expenditures on solution procurement and operational expenditures on remediation and monitoring
- A healthcare company used Cyphort’s solution to increase strength of threat detection and provide greater visibility into endpoints and infections, hastening the speed of threat response The company offers a cost reduction value proposition. It provides a promotional offer for the education market – specifically, it offers a discount to universities and schools for its solution.
The company has established a strong brand as a result of its performance. It has won many honors, including the SC Magazine Award for Best Enterprise Security Solution, inclusion on the *Forbes *Hottest Security Startup List, and recognition as a “Leader” in the Forrester Wave Automated Malware Analysis Report.
Channels
Cyphort’s main channels are its direct sales team and distribution partners, who each account for about 50% of revenues. The company promotes its offering through its website, social media pages, and participation in conferences.
Customer Relationships
Cyphort’s customer relationship is primarily of a personal assistance nature. The company offers customers a maintenance support contract that includes the following services:
- 24x7x365 phone support
- Software maintenance and feature updates
- Remote system monitoring Despite this orientation, there is a self-service component. The contract offers access to an online customer support portal that features a knowledge base and case management system. In addition, Cyphort’s website features a “Resources” section that includes self-help tools such as white papers, research reports, webinars, infographics, demos, product literature, and videos.
Key Activities
Cyphort’s business model entails maintaining a robust software platform for its clients.
Key Partners
Cyphort maintains the following partnership programs:
- Technology Partner Program – The company works with tech firms that provide collection, verification, and enforcement services for advanced threats facing its customers. Specific partners include Arista Networks, Blue Coat, Check Point Software, Gigamon, Juniper Networks, and VMware.
- Channel Reseller Program – The company works with firms that promote and sell its offerings to their customers in order to extend its reach. One of its major partners is Optiv.
- Systems Integrator Partners – The company works with consultants, integrators, and other advisory partners to help its customers receive assistance in areas such as implementation.
-
Managed Security Service Providers – The company works with service firms that provide collection and correlation services. Partners receive some or all of the following benefits:
- Sales/marketing training
- Sales/marketing/technical tools and resources
- Field-level support
- A listing on Cyphort’s website
- Invites to participate in joint marketing initiatives
- Dedicated product management for integrations
- Access to the online partner portal ### Key Resources
Cyphort’s main resource is its proprietary software platform. It depends on its human resources in the form of engineering employees to maintain and update the platform and customer service staff to provide support.
It also maintains Cyphort Labs, a world-class team of security threat researchers who constantly monitor advanced global cybersecurity threats and provide security intelligence for the Cyphort Advanced Threat Defense Platform.
Lastly, as a relatively new startup it has relied heavily on funding from outside parties, raising $53.7 million from five investors as of June 2015.
Cost Structure
Cyphort has a value-driven cost structure, aiming to minimize expenses through significant personal service.
Its biggest cost driver is likely marketing and sales expenses. Other major drivers are in the areas of customer support/operations and product development, both fixed costs.
Revenue Streams
Cyphort has one revenue stream: revenues it generates from the subscription fees it charges for access to its software-as-a-service platform.
Specific pricing is based on expected amount of protected link bandwidth (the amount of data a client needs the firm to inspect and protect).


| Interface | Description |
|---|---|
| DrawPolicy |
Called by Sparse2DPortrayal to determine if all objects
should be drawn or only one.
|
| Class | Description |
|---|---|
| DenseGrid3DPortrayal2D |
Portrayal for 3D Dense grids: grids of Bags of objects.
|
| DenseGridPortrayal2D |
Portrayal for Dense grids: grids of Bags of objects.
|
| FastHexaObjectGridPortrayal2D |
A "Fast" version of HexaObjectGridPortrayal2D, which draws objects as rectangles of specified colors,
rather than using the provided SimplePortrayal2Ds.
|
| FastHexaValueGridPortrayal2D | |
| FastObjectGridPortrayal2D |
A "Fast" version of ObjectGridPortrayal2D, which draws objects as rectangles of specified colors,
rather than using the provided SimplePortrayal2Ds.
|
| FastValueGridPortrayal2D |
This class works like a ValueGridPortrayal2D, except that it doesn't use an underlying Portrayal for the object
(instead it always draws a rectangle), and may ignore the getColor() method, so you shouldn't override that method to customize
the color function in nonlinear ways any more.
|
| HexaDenseGridPortrayal2D |
Portrayal for hexagonal grids (each cell has six equally-distanced neighbors).
|
| HexaObjectGridPortrayal2D |
Portrayal for hexagonal grids (each cell has six equally-distanced neighbors) containing objects.
|
| HexaSparseGridPortrayal2D |
Portrayal for hexagonal grids (each cell has six equally-distanced neighbors).
|
| HexaValueGridPortrayal2D |
Portrayal for hexagonal grids (each cell has six equally-distanced neighbors) with double-precision real values.
|
| ObjectGrid3DPortrayal2D |
A 2D portrayal for 3D grids containing objects.
|
| ObjectGridPortrayal2D |
A portrayal for grids containing objects, such as maybe agents or agent bodies.
|
| ObjectGridPortrayal2D.Message | |
| SparseGrid3DPortrayal2D |
Can be used to draw both continuous and discrete sparse fields.
|
| SparseGridPortrayal2D |
Can be used to draw both continuous and discrete sparse fields.
|
| ValueGridPortrayal2D |
This class is capable of portraying the DoubleGrid2D and IntGrid2D fields (and only those two fields -- or subclasses).
|


Homepage
Tribute Page
Guess Number
Bouncing Ball
Image Gallery
Practise Projects
Practise
Build a Tribute Page
Build up a simple "Guess the number" game
Build a JavaScript Powered Image Gallery
Build custom JS Objects - Bouncing Ball Project
P.S. movies and series you can watch:
Matrix 1, 2, 3
Imitation Game
Mr. Robot
Silicon Valley


Highlight management API.
More...
Highlight management API.
Test to check if highlighted rows contains the keyword and report any error.
This class will store and load state history of GeneDive
- Author
- Date
Automates the highlight features
- Authors
- Mike Wong mikew.nosp@m.ong@.nosp<EMAIL_ADDRESS>-
Mike Wong mikew.nosp@m.ong@.nosp<EMAIL_ADDRESS>Vaishali Bisht vbish.nosp@m.t1@m.nosp@m.ail.s.nosp<EMAIL_ADDRESS>◆ constructor()
| Highlight::constructor |
( |
|
input | ) |
|
|
inline |
◆ exportHighlightState()
| Highlight Highlight::exportHighlightState |
( |
| ) |
|
|
inline |
◆ highlight()
| Highlight Highlight::highlight |
( |
|
interactions | ) |
|
|
inline |
Highlights interactions that match terms.
Searches every interaction's context and the two DGRs for the term with Regex, and changes it's highlight variable to true if it's a match, and false if not. The minimum length is 2, so no one letter searches.
- Parameters
-
| interactions | The interactions from the GeneDive search |
◆ importHighlightState()
| Highlight Highlight::importHighlightState |
( |
|
highlightData | ) |
|
|
inline |
The documentation for this class was generated from the following file:


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Your browser does not support the audio tag
Ramzi's Really Cool Math Problems
Timer:
0
Score:
0
Questions
\( 2^3 \)
\( \sqrt[3]{8} \)
\( 8^\frac{1}{3} \)
\( 2^4 \)
\( 5+83 \)
\( 3^3 \)
\( 3^4 \)
\( 4^2 \)
\( 2^3 \)
\( 5^3 \)


{% extends "dashboard/layouts/based.html" %} {% block stylesheets %}{% endblock stylesheets %} {% block mainmenu %}
{% endblock mainmenu %} {% block content %}Spin the Weel
{{spin_players_no}} People Playing Now ! {% if user.is_authenticated %} PLay Now ! {% endif %} {% if not user.is_authenticated %} Join the PLay ! {% endif %}
Play Poker
0 People Playing
Roll the Dice
0 People Playing
We update our site regularly; more and more winners are added every day! To locate the most recent winner's information
01.08.2019
#5747e75482
01.08.2019
#5747e75482
01.08.2019
#5747e75482


HOME
ABOUT
PROJECTS
CONTACT
Contact me
Email:
<EMAIL_ADDRESS>Home:
(09) 475 6606
Mobile:
021 022 33 646


{% include 'material/includes/material_js.html' %}
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