Note
Click here to download the full example code
Compares implementations of ReduceMean#
This example compares the numpy for the operator ReduceMean to onnxruntime implementation. If available, tensorflow and pytorch are included as well.
Available optimisation#
The code shows which parallelisation optimisation could be used, AVX or SSE and the number of available processors.
import numpy
import pandas
import matplotlib.pyplot as plt
from onnxruntime import InferenceSession
from skl2onnx.common.data_types import FloatTensorType
from skl2onnx.algebra.onnx_ops import OnnxReduceMean
from cpyquickhelper.numbers import measure_time
from tqdm import tqdm
from mlprodict.testing.experimental_c_impl.experimental_c import code_optimisation
print(code_optimisation())
Out:
AVX-omp=8
ReduceMean implementations#
try:
from tensorflow.math import reduce_mean as tf_reduce_mean
from tensorflow import convert_to_tensor
except ImportError:
tf_reduce_mean = None
try:
from torch import mean as torch_mean, from_numpy
except ImportError:
torch_mean = None
def build_ort_reducemean(axes, op_version=14): # opset=13, 14, ...
node = OnnxReduceMean('x', axes=axes, op_version=op_version,
output_names=['z'])
onx = node.to_onnx(inputs=[('x', FloatTensorType())],
target_opset=op_version)
sess = InferenceSession(onx.SerializeToString())
return lambda x, y: sess.run(None, {'x': x})
def loop_fct(fct, xs, ys):
for x, y in zip(xs, ys):
fct(x, y)
def benchmark_op(axes, repeat=2, number=5, name="ReduceMean",
shape_fct=None, max_dim=None):
if shape_fct is None:
def shape_fct(dim):
return (3, dim, 1, 128, 64)
ort_fct = build_ort_reducemean(axes)
res = []
for dim in tqdm([4, 8, 16, 32, 64, 100, 128, 200,
256, 400, 512, 1024]):
if max_dim is not None and dim > max_dim:
continue
shape = shape_fct(dim)
n_arrays = 10 if dim < 512 else 4
xs = [numpy.random.rand(*shape).astype(numpy.float32)
for _ in range(n_arrays)]
ys = [numpy.array(axes, dtype=numpy.int64)
for _ in range(n_arrays)]
info = dict(axes=axes, shape=shape)
# numpy
fct = lambda x, y: numpy.mean(x, axis=tuple(y))
ctx = dict(
xs=xs, ys=ys,
loop_fct=loop_fct)
obs = measure_time(
lambda: loop_fct(fct, xs, ys),
div_by_number=True, context=ctx, repeat=repeat, number=number)
obs['dim'] = dim
obs['fct'] = 'numpy'
obs.update(info)
res.append(obs)
# onnxruntime
fct = ort_fct
obs = measure_time(
lambda: loop_fct(fct, xs, ys),
div_by_number=True, context=ctx, repeat=repeat, number=number)
obs['dim'] = dim
obs['fct'] = 'ort'
obs.update(info)
res.append(obs)
if tf_reduce_mean is not None:
# tensorflow
fct = tf_reduce_mean
ctx['xs'] = [convert_to_tensor(x) for x in xs]
ctx['ys'] = ys
obs = measure_time(
lambda: loop_fct(fct, ctx['xs'], ctx['ys']),
div_by_number=True, context=ctx, repeat=repeat, number=number)
obs['dim'] = dim
obs['fct'] = 'tf'
obs.update(info)
res.append(obs)
if torch_mean is not None:
def torch_mean1(x, y):
return torch_mean(x, y[0])
def torch_mean2(x, y):
return torch_mean(torch_mean(x, y[1]), y[0])
# torch
fct = torch_mean1 if len(axes) == 1 else torch_mean2
ctx['xs'] = [from_numpy(x) for x in xs]
ctx['ys'] = ys # [from_numpy(y) for y in ys]
obs = measure_time(
lambda: loop_fct(fct, ctx['xs'], ctx['ys']),
div_by_number=True, context=ctx, repeat=repeat, number=number)
obs['dim'] = dim
obs['fct'] = 'torch'
obs.update(info)
res.append(obs)
# Dataframes
shape_name = str(shape).replace(str(dim), "N")
df = pandas.DataFrame(res)
df.columns = [_.replace('dim', 'N') for _ in df.columns]
piv = df.pivot('N', 'fct', 'average')
rs = piv.copy()
for c in ['ort', 'torch', 'tf', 'tf_copy']:
if c in rs.columns:
rs[c] = rs['numpy'] / rs[c]
rs['numpy'] = 1.
# Graphs.
fig, ax = plt.subplots(1, 2, figsize=(12, 4))
piv.plot(logx=True, logy=True, ax=ax[0],
title="%s benchmark\n%r - %r"
" lower better" % (name, shape_name, axes))
ax[0].legend(prop={"size": 9})
rs.plot(logx=True, logy=True, ax=ax[1],
title="%s Speedup, baseline=numpy\n%r - %r"
" higher better" % (name, shape_name, axes))
ax[1].plot([min(rs.index), max(rs.index)], [0.5, 0.5], 'g--')
ax[1].plot([min(rs.index), max(rs.index)], [2., 2.], 'g--')
ax[1].legend(prop={"size": 9})
return df, rs, ax
dfs = []
Reduction on a particular case KR#
Consecutive axis not reduced and consecutive reduced axis are merged. KR means kept axis - reduced axis
(8, 24, 48, N), axis=(3, )#
axes = (3, )
df, piv, ax = benchmark_op(axes, shape_fct=lambda dim: (8, 24, 48, dim))
dfs.append(df)
df.pivot("fct", "N", "average")
Out:
0%| | 0/12 [00:00<?, ?it/s]
8%|8 | 1/12 [00:01<00:11, 1.05s/it]
17%|#6 | 2/12 [00:02<00:10, 1.08s/it]
25%|##5 | 3/12 [00:03<00:09, 1.10s/it]
33%|###3 | 4/12 [00:04<00:09, 1.14s/it]
42%|####1 | 5/12 [00:05<00:08, 1.20s/it]
50%|##### | 6/12 [00:07<00:07, 1.31s/it]
58%|#####8 | 7/12 [00:08<00:07, 1.41s/it]
67%|######6 | 8/12 [00:10<00:06, 1.58s/it]
75%|#######5 | 9/12 [00:13<00:05, 1.77s/it]
83%|########3 | 10/12 [00:15<00:04, 2.09s/it]
92%|#########1| 11/12 [00:17<00:01, 1.87s/it]
100%|##########| 12/12 [00:19<00:00, 1.98s/it]
100%|##########| 12/12 [00:19<00:00, 1.62s/it]
Reduction on a particular case RK#
Consecutive axis not reduced and consecutive reduced axis are merged. RK means reduced axis - kept axis
(8, 24, 48, N), axis=(0, )#
axes = (0, )
df, piv, ax = benchmark_op(axes, shape_fct=lambda dim: (8, 24, 48, dim))
dfs.append(df)
df.pivot("fct", "N", "average")
Out:
0%| | 0/12 [00:00<?, ?it/s]
8%|8 | 1/12 [00:00<00:09, 1.11it/s]
17%|#6 | 2/12 [00:01<00:09, 1.06it/s]
25%|##5 | 3/12 [00:02<00:08, 1.02it/s]
33%|###3 | 4/12 [00:05<00:11, 1.42s/it]
42%|####1 | 5/12 [00:08<00:14, 2.05s/it]
50%|##### | 6/12 [00:11<00:14, 2.37s/it]
58%|#####8 | 7/12 [00:14<00:13, 2.68s/it]
67%|######6 | 8/12 [00:18<00:12, 3.09s/it]
75%|#######5 | 9/12 [00:22<00:09, 3.27s/it]
83%|########3 | 10/12 [00:27<00:08, 4.01s/it]
92%|#########1| 11/12 [00:30<00:03, 3.57s/it]
100%|##########| 12/12 [00:34<00:00, 3.71s/it]
100%|##########| 12/12 [00:34<00:00, 2.86s/it]
Reduction on a particular case KRK#
Consecutive axis not reduced and consecutive reduced axis are merged. KRK means kept axis - reduced axis - kept axis,
(8, 24, 48, N), axis=(1, 2)#
axes = (1, 2)
df, piv, ax = benchmark_op(axes, shape_fct=lambda dim: (8, 24, 48, dim))
dfs.append(df)
df.pivot("fct", "N", "average")
Out:
0%| | 0/12 [00:00<?, ?it/s]
8%|8 | 1/12 [00:00<00:10, 1.06it/s]
17%|#6 | 2/12 [00:01<00:10, 1.00s/it]
25%|##5 | 3/12 [00:02<00:07, 1.26it/s]
33%|###3 | 4/12 [00:03<00:07, 1.08it/s]
42%|####1 | 5/12 [00:04<00:07, 1.07s/it]
50%|##### | 6/12 [00:06<00:07, 1.23s/it]
58%|#####8 | 7/12 [00:08<00:06, 1.37s/it]
67%|######6 | 8/12 [00:12<00:09, 2.33s/it]
75%|#######5 | 9/12 [00:16<00:08, 2.89s/it]
83%|########3 | 10/12 [00:22<00:07, 3.67s/it]
92%|#########1| 11/12 [00:24<00:03, 3.32s/it]
100%|##########| 12/12 [00:28<00:00, 3.40s/it]
100%|##########| 12/12 [00:28<00:00, 2.35s/it]
(8, 24 * 48, N), axis=1#
axes = (1, )
df, piv, ax = benchmark_op(axes, shape_fct=lambda dim: (8, 24 * 48, dim))
dfs.append(df)
df.pivot("fct", "N", "average")
Out:
0%| | 0/12 [00:00<?, ?it/s]
8%|8 | 1/12 [00:01<00:11, 1.02s/it]
17%|#6 | 2/12 [00:02<00:10, 1.05s/it]
25%|##5 | 3/12 [00:03<00:09, 1.04s/it]
33%|###3 | 4/12 [00:04<00:08, 1.06s/it]
42%|####1 | 5/12 [00:05<00:07, 1.10s/it]
50%|##### | 6/12 [00:06<00:07, 1.17s/it]
58%|#####8 | 7/12 [00:08<00:06, 1.30s/it]
67%|######6 | 8/12 [00:10<00:06, 1.52s/it]
75%|#######5 | 9/12 [00:12<00:05, 1.75s/it]
83%|########3 | 10/12 [00:15<00:04, 2.16s/it]
92%|#########1| 11/12 [00:17<00:01, 1.96s/it]
100%|##########| 12/12 [00:19<00:00, 2.23s/it]
100%|##########| 12/12 [00:19<00:00, 1.66s/it]
(2, 8, 12, 24, 2, N), axis=(2, 3)#
axes = (2, 3)
df, piv, ax = benchmark_op(axes, shape_fct=lambda dim: (2, 8, 12, 24, 2, dim))
dfs.append(df)
df.pivot("fct", "N", "average")
Out:
0%| | 0/12 [00:00<?, ?it/s]
8%|8 | 1/12 [00:00<00:10, 1.05it/s]
17%|#6 | 2/12 [00:01<00:08, 1.17it/s]
25%|##5 | 3/12 [00:02<00:06, 1.29it/s]
33%|###3 | 4/12 [00:03<00:05, 1.39it/s]
42%|####1 | 5/12 [00:04<00:06, 1.09it/s]
50%|##### | 6/12 [00:07<00:10, 1.79s/it]
58%|#####8 | 7/12 [00:10<00:10, 2.03s/it]
67%|######6 | 8/12 [00:15<00:11, 2.89s/it]
75%|#######5 | 9/12 [00:20<00:10, 3.57s/it]
83%|########3 | 10/12 [00:25<00:08, 4.04s/it]
92%|#########1| 11/12 [00:27<00:03, 3.57s/it]
100%|##########| 12/12 [00:31<00:00, 3.57s/it]
100%|##########| 12/12 [00:31<00:00, 2.61s/it]
Reduction on a particular case RKR#
(N, 64, 16, 16), axis=(0, 2, 3)#
axes = (0, 2, 3)
df, piv, ax = benchmark_op(
axes, shape_fct=lambda dim: (dim, 64, 16, 16))
dfs.append(df)
df.pivot("fct", "N", "average")
Out:
0%| | 0/12 [00:00<?, ?it/s]
8%|8 | 1/12 [00:00<00:07, 1.38it/s]
17%|#6 | 2/12 [00:01<00:08, 1.16it/s]
25%|##5 | 3/12 [00:02<00:07, 1.22it/s]
33%|###3 | 4/12 [00:04<00:10, 1.33s/it]
42%|####1 | 5/12 [00:08<00:15, 2.24s/it]
50%|##### | 6/12 [00:12<00:18, 3.03s/it]
58%|#####8 | 7/12 [00:17<00:18, 3.62s/it]
67%|######6 | 8/12 [00:23<00:16, 4.23s/it]
75%|#######5 | 9/12 [00:29<00:14, 4.81s/it]
83%|########3 | 10/12 [00:36<00:11, 5.58s/it]
92%|#########1| 11/12 [00:40<00:04, 4.91s/it]
100%|##########| 12/12 [00:45<00:00, 5.02s/it]
100%|##########| 12/12 [00:45<00:00, 3.78s/it]
Reduction on a particular case RKRK#
(8, 24, 48, N), axis=(0, 2)#
axes = (0, 2)
df, piv, ax = benchmark_op(axes, shape_fct=lambda dim: (8, 24, 48, dim))
dfs.append(df)
df.pivot("fct", "N", "average")
Out:
0%| | 0/12 [00:00<?, ?it/s]
8%|8 | 1/12 [00:00<00:04, 2.58it/s]
17%|#6 | 2/12 [00:01<00:06, 1.64it/s]
25%|##5 | 3/12 [00:01<00:04, 1.84it/s]
33%|###3 | 4/12 [00:02<00:06, 1.30it/s]
42%|####1 | 5/12 [00:03<00:06, 1.09it/s]
50%|##### | 6/12 [00:05<00:06, 1.09s/it]
58%|#####8 | 7/12 [00:06<00:06, 1.25s/it]
67%|######6 | 8/12 [00:10<00:08, 2.05s/it]
75%|#######5 | 9/12 [00:15<00:08, 2.89s/it]
83%|########3 | 10/12 [00:21<00:07, 3.81s/it]
92%|#########1| 11/12 [00:24<00:03, 3.54s/it]
100%|##########| 12/12 [00:30<00:00, 4.31s/it]
100%|##########| 12/12 [00:30<00:00, 2.52s/it]
Conclusion#
Some of the configurations should be investigated. l-reducesum-problem1. The reduction on tensorflow in one dimension seems to be lazy.
merged = pandas.concat(dfs)
name = "reducemean"
merged.to_csv("plot_%s.csv" % name, index=False)
merged.to_excel("plot_%s.xlsx" % name, index=False)
plt.savefig("plot_%s.png" % name)
plt.show()
Total running time of the script: ( 3 minutes 46.734 seconds)


The goal of hagis is to provide Phytophthora sojae pathotype analysis that the original HaGiS worksheet (Herrmann, Löwer and Schachtel) provided.
Currently you can only install hagis from GitHub with:
if (!require("remotes")) {
install.packages("remotes", repos = "http://cran.rstudio.com/")
library("remotes")
}
install_github("openplantpathology/hagis", build_vignettes = TRUE)
The original R scripts were produced by Austin McCoy and Zachary Noel at Michigan State University to replicate the HaGiS worksheet and provide all necessary results for pathotype data analysis in R in addition to other tools to assist in the analysis of these data.
Phytophthora sojae has been managed primarily via deployment of resistance genes (Rps genes, resistance to Phytophthora sojae) in commercial soybean cultivars and by the application of fungicide seed treatments. However, repeated use of resistance genes can cause populations to adapt over time rendering these resistance genes ineffective. To determine current effectiveness of resistance genes for managing Phytophthora sojae, state-wide surveys must be conducted to determine the pathotype (previously referred to as “race”) structure within sampled population of P. sojae.
The goal of these scripts was to provide all the necessary analyses needed when conducting a Phytophthora sojae pathotype survey, including: distribution of susceptibilities (effective and non-effective Rps genes), distribution of pathotype complexities with statistics, pathotype frequency distribution, as well as diversity indices for pathotypes.
Users may refer to the example file, system.file("extdata", "practice_data_set.csv", package = "hagis")
and the documentation for further examples.
Please cite hagis by using:
citation("hagis")
#>
#> McCoy A, Noel Z, Sparks A, Chilvers M (????). _hagis: Tools for
#> Analysis of Phytophthora Pathotype Complexities, Distributions and
#> Diversity_. doi: 10.5281/zenodo.2619820 (URL:
#> https://doi.org/10.5281/zenodo.2619820), R package version
#> <IP_ADDRESS>00, <URL: https://openplantpathology.github.io/hagis/>.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Manual{,
#> title = {{hagis}: Tools for Analysis of Phytophthora Pathotype Complexities, Distributions and Diversity},
#> author = {Austin McCoy and Zachary Noel and Adam H. Sparks and Martin Chilvers},
#> note = {R package version <IP_ADDRESS>00},
#> url = {https://openplantpathology.github.io/hagis/},
#> doi = {10.5281/zenodo.2619820},
#> }
Please note that the hagis project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Herrmann, , Löwer, and Schachtel, (1999), A new tool for entry and analysis of virulence data for plant pathogens. Plant Pathology, 48: 154-158. DOI: 10.1046/j.1365-3059.1999.00325.x


Version 1.1 (2013/08/18)
Known Inventories
Base URL: http://steamcommunity.com/id/userName/inventory/json/AppId/ContextId
Game Appids List: http://api.steampowered.com/ISteamApps/GetAppList/v2
NOTE: Inventory Context Id (type) changes according to the AppId item schema, so it's up to you find it out wich ones work :/
Steam Inventory (AppId 753)
| Context Id | Description | Notes |
| 1 |
Gifts (Games) |
WARNING: Automatization (buy & sell) may be against Steam TOS |
| 3 |
Coupons |
|
| 6 |
Steam Trading Cards |
Game Cards, Profile Backgrounds & Emoticons |
Counter-Strike: Global Offensive (AppId 730)
| Context Id | Description | Notes |
| 2 |
Inventory |
Weapons |
Dota 2 (AppId 570)
| Context Id | Description | Notes |
| 2 |
Main Inventory |
Not sure |


Audit Logs
Audit logs are the centralized stream of all user activity within a team. Part of the security and compliance program of any large enterprise is designed to control and monitor the access of information within the organization. This drives the need for enterprise buyers to ask for a detailed audit trail of all activity that happens within their account. An audit trail can be used to prevent suspicious activity when it starts (if actively monitored), or to play back account activity during an incident review.
Audit logs ≠ system logs
It isn’t enough to log events internally to a traditional logging service like Loggly, Elastic Search, Papertrail etc. Those applications are designed to provide application developers with the system level logs to diagnose application performance issues. Instead, an audit logging feature is built from the ground up to log the relevant activity into a system that is immutable, time synced and accessible by account admins. Additionally, the best audit logs (as implemented by companies like GitHub and Google) are fully exportable, available from an API, searchable and include well documented changes.
Events to audit log
The most basic audit logging functionality requires a clear understanding of which events should be recorded in the audit log. The ISO-27002 specifications provide some clarity about what enterprise customers will likely need to have logged. However, every application can be a bit different in terms of what activities should actually be logged for auditing.
Generally, the specific content of a target is not audit logged, rather the state or context is logged. Examples of events that should be audit logged are as follows: application specific user activities, exceptions, information security events (successful and rejected events), use of privileges, log-on failed-attempts & successes, log-off, data accessed, data attempted to be accessed, administrative configuration changes and the use of advanced privileges.
The best way to organize events is as the combination of targets receiving actions (i.e. user.created
, user.deleted
, document.viewed
, account.setting.updated
). Actions can generally be categorized into their CRUD
type (i.e. C
reate, R
ead, U
pdate, or D
elete). Events are generally performed by an actor (i.e. a<EMAIL_ADDRESS>updated their password) however, there are anonymous actions (such as failed log in attempts).
Note: When the logging of these events is implemented in code, the audit logging method should be called at the bottom of the function to ensure that the event was fully executed.
Fields to audit log for each event
When an event is logged it should have details that provide enough information about the event to provide the necessary context of who, what, when and where etc. Specifically, the follow fields are critical to an audit log:
- Actor - The username, uuid, API token name of the account taking the action.
- Group - The group (aka organization, team, account) that the actor is a member of (needed to show admins the full history of their group).
- Where - IP address, device ID, country.
- When - The NTP synced server time when the event happened.
- Target - the object or underlying resource that is being changed (the noun) as well as the fields that include a key value for the new state of the target.
- Action - the way in which the object was changed (the verb).
- Action Type - the corresponding
C``R``U``D
category. - Event Name - Common name for the event that can be used to filter down to similar events.
- Description - A human readable description of the action taken, sometimes includes links to other pages within the application.
Optional information
- Server server ids or names, server location.
- Version version of the code that is sending the events.
- Protocols ie http vs https.
- Global Actor ID if a customer is using Single Sign On, it might be important to also include a Global UID if it differs from the application specific ID.
Key functionality:
Immutability
Data in an audit log should never change. Deleted objects should maintain a separately logged record of actions associated with the object (including its creation and deletion). External facing APIs should only be able to read the audit log, not write to it.
Time Synced
Individual application audit logs will likely be combined with other audit log data, this makes it important to ensure that the timestamp on each event is accurate. The standard is to use the server time from a regularly NTP synced server, generally stored in GMT down to the millisecond.
API & exportable
The activity should be exportable to a CSV format and API accessible so that it can be centralized into an organization wide SIEM logging system like Splunk. It’s advisable to offer both the ability to poll for new events and to be able to push new events to the remote system. When polling, use standards such as etag
headers to prevent duplicate events from being received. When pushing, use standards such as webhooks to minimize the amount of custom work required to ingest these events.
Account admin viewable
An audit log viewer should be embedded into the application to make the audit log accessible to enterprise account admins at all times. This viewer should be the central place to access all account activity logs.
Searchable & filterable
Events should be indexed for searchability and filtering. Generally, actors, event names, IPs are all linked to filter down to related activity. The viewer should allow the account admin to specify a date range to filter in conjunction with other filters and searches.
Change log
When new events and actions are captured in the audit log, it is important to publish the date at which each became available to appear in the audit log.
Customizable retention time
By default an audit log should generally be kept for 1-3 years. The specific default timeframe should be documented but also made configurable (generally shorter) for customers who have data retention requirements.
Documented lag time
If there are significant lags between collection and reporting availability, those times should be made known to the account admin viewing the logs.


Cobra
Vulnerabilities
Vulnerabilities
Target
All
{% for target in target_filter %}
{{ target }}
{% endfor %}
Mode
All
{% for rule in rule_filter %}
{{ rule }}
{% endfor %}
Level
All
High
Medium
Low
Summit filter
// This is a demo code
Status:
(
)
Level:
-
By
Repair AT:
Repair:
Score:
CWE:
OWASP Top10:
SANA 25 Rank:
Bounty:
Copyright © 2017
Cobra
. All rights reserved
Github
-
Documents
-
About


Semester: Spring 2
Deep learning is a subfield of machine learning that builds predictive models using large artificial neural networks. Deep learning has revolutionized the fields of computer vision, automatic speech recognition, natural language processing, and numerous areas of computational biology. In this class, we will introduce the basic concepts of deep neural networks and GPU computing, discuss convolutional neural networks and recurrent neural networks structures, and examine a biomedical applications. Students are expected to be familiar with linear algebra and machine learning and will participate in a group deep learning project.
Course website: https://hms-dbmi.github.io/BMI_707/


{{< layout-referee}} {{$pageTitle}}Checking your identity{{/pageTitle}} {{$main-content}}
Before we show you a photo, we need to check some extra details about you.
Your credit report will show 'Searched by HM Passport Office'. This doesn't affect your credit rating.
This doesn't show on your credit report. We don't take any money or store your bank details.
These checks are run by Experian.


// The first thing I would imagine on this page is a short list of suggested TNs based on the candidates preferences. If the EP doesn't like any of these, the EP manager can also search our database from this page and add them manually.
//Then the EP manager can manually update TNs to "working on matching"
//Somewhere else on this site (Not the EP page) I would like to have a nicely formatted list of TNs that would automatically update in a google spreadsheet when we added them.


Vegan Store Simple Website Template
With nutrition, all the vital functions of the body are connected. It is the source of the development of tissues and cells, their constant renewal, the saturation of man with energy.
With nutrition, all the vital functions of the body are connected. It is the source of the development of tissues and cells, their constant renewal, the saturation of man with energy.
Vegetables are an integral part of the human diet. They are extremely useful because of the high content of carbohydrates, various acids, vitamins and active elements in the form, easy for digestion.
Fresh tomatoes are ideal for replenishing the loss of minerals. These vegetables contain a lot of acids that our body needs for full-fledged work.
In the content of vitamin C, sweet peppers are superior to lemons and even black currants! The greatest amount of vitamin is contained around the stalk, that is, in the part of the product that is usually cut during cleaning.
If you sometimes eat hot chili peppers, this will help normalize cerebral circulation, ease the condition with bronchial asthma, cough, sore throat, flu.
Fresh Food
Radish contains a lot of fiber, pectin and mineral salts.
Use for cooking several types of vegetable oil.
This is the best source of essential fatty acids for the body.
It is very good, if in the kitchen there will always be several bottles with different oils.
Remember that unrefined oils are not suitable for heat treatment.
Fresh Food
According to experts, any habit can be formed in 21 days. The same statement applies to healthy eating.
Cook
Seller
Manager
A wide range of products; many unusual and tasty products; courteous staff.
Year of experiences
Happy Customers
100% Satisfaction
Detox Smoothies
Contact Us
Overeating is one of the most common causes of overweight and digestive problems.
Roeterseiland Campus Building E
6th floor London
Monday to Friday : 9am to 8pm
examplemail.mail.com
Roeterseiland Campus Building E
6th floor London
Monday to Friday : 9am to 8pm
examplemail.mail.com
Meet Our Team
The task of proper nutrition - to remove from the diet harmful food and enrich it useful.


get.summary2.Rd
Summarize and provide p-value after association test of 2 or more variables. Percentages are reported for discrete variables. Users can choose the type of test they want. For continuous variable median and range are reported if the test specified is non parametric, mean and standard deviation are reported for a parametric test. For discrete categories we perform Fisher's Exact Test, for continuous following options are available - parametric - Students' T-Test or one way ANNOVA, for non-parametric Wilcoxon Rank sum test or Kruskal Wallis test.
get.summary2(fac,var,type,test.type="np",skip.test=FALSE, var.n=NULL)
| fac | vector, a discrete vector of interest for which association is to be tested against other categorical or continuous variables |
|---|---|
| var | vector, can be discrete or continuous |
| type |
|
| test.type | possible values - |
| skip.test | logical, Default is |
| var.n | character, If a variable name is provided, it will add this to output. |
Summary statistics are rounded to nearest 2 decimal points.
Note that length of fac
and var
should be the same. For Wilcoxon Rank sum test ties are handled through wilcox.test
function in coin
package.
workspace parameter in Fisher's Exact test is set to workspace=2e8
. All p-values < 0.0001 are replaced with a character string P<0.0001 or otherwise rounded to three decimal points.
returns a character matrix summarizing fac
and var
.


This page shows automated results of the eta-Aquariids 2011, based on visual observations by volunteers astronomers collected through the report form of the International Meteor Organization (IMO). The information on this page is generated automatically; for scientific use please refer to manual analyses published in scientific journals (such as WGN). Send your feedback regarding this page to Geert Barentsen.
Page contents:
Page generated: 2011 September 29 at 10:42 UTC.
The graph below shows the ZHR (Zenithal Hourly Rate), which is the number of meteors an observer would see under a very dark sky with the radiant of the shower in zenith.
ZHRmax = 63 based on 928 eta-Aquariids reported in 273 intervals, assuming population index r = 2.4
| Time (UTC) | Solarlon | nINT | nETA | ZHR | Particle density | |
|---|---|---|---|---|---|---|
| 2011-04-25 02:00 | 34.381 | 1 | 1 | 59 | ±42 | 107 / 109·km3 |
| 2011-04-27 10:41 | 36.681 | 6 | 5 | 6 | ±2 | 11 / 109·km3 |
| 2011-04-29 14:45 | 38.791 | 8 | 12 | 12 | ±3 | 22 / 109·km3 |
| 2011-05-02 06:40 | 41.378 | 6 | 13 | 18 | ±5 | 33 / 109·km3 |
| 2011-05-03 09:00 | 42.443 | 16 | 36 | 34 | ±6 | 62 / 109·km3 |
| 2011-05-03 18:46 | 42.838 | 6 | 42 | 29 | ±4 | 53 / 109·km3 |
| 2011-05-04 02:54 | 43.167 | 11 | 43 | 29 | ±4 | 53 / 109·km3 |
| 2011-05-04 09:49 | 43.446 | 15 | 36 | 29 | ±5 | 53 / 109·km3 |
| 2011-05-04 18:54 | 43.813 | 4 | 40 | 39 | ±6 | 71 / 109·km3 |
| 2011-05-05 03:07 | 44.145 | 11 | 37 | 27 | ±4 | 49 / 109·km3 |
| 2011-05-05 07:02 | 44.303 | 16 | 35 | 32 | ±5 | 58 / 109·km3 |
| 2011-05-05 16:24 | 44.681 | 10 | 37 | 28 | ±5 | 51 / 109·km3 |
| 2011-05-05 20:26 | 44.844 | 7 | 35 | 38 | ±6 | 69 / 109·km3 |
| 2011-05-06 01:49 | 45.062 | 24 | 40 | 27 | ±4 | 49 / 109·km3 |
| 2011-05-06 05:16 | 45.201 | 7 | 38 | 63 | ±10 | 115 / 109·km3 |
| 2011-05-06 07:47 | 45.303 | 16 | 35 | 41 | ±7 | 75 / 109·km3 |
| 2011-05-06 17:15 | 45.685 | 8 | 38 | 43 | ±7 | 78 / 109·km3 |
| 2011-05-06 22:18 | 45.889 | 15 | 37 | 54 | ±9 | 98 / 109·km3 |
| 2011-05-07 02:20 | 46.051 | 10 | 35 | 44 | ±7 | 80 / 109·km3 |
| 2011-05-07 05:02 | 46.160 | 14 | 67 | 40 | ±5 | 73 / 109·km3 |
| 2011-05-07 12:40 | 46.468 | 4 | 37 | 50 | ±8 | 91 / 109·km3 |
| 2011-05-08 01:27 | 46.984 | 10 | 37 | 45 | ±7 | 82 / 109·km3 |
| 2011-05-08 04:58 | 47.126 | 8 | 60 | 53 | ±7 | 97 / 109·km3 |
| 2011-05-08 14:27 | 47.508 | 15 | 40 | 48 | ±7 | 87 / 109·km3 |
| 2011-05-09 10:29 | 48.316 | 9 | 35 | 31 | ±5 | 56 / 109·km3 |
| 2011-05-10 04:29 | 49.041 | 8 | 52 | 48 | ±7 | 87 / 109·km3 |
| 2011-05-11 18:20 | 50.565 | 4 | 4 | 11 | ±5 | 20 / 109·km3 |
| 2011-05-13 01:53 | 51.834 | 2 | 0 | 11 | ±11 | 20 / 109·km3 |
| 2011-05-25 12:18 | 63.805 | 2 | 1 | 14 | ±10 | 25 / 109·km3 |
The reported intervals are automatically added together into the bins shown above, based on the number of meteors and the distribution of the intervals. For each bin, the following parameters are computed:
Data has been received from 50 observers in 20 countries. Thank you for your efforts!
Note: click on the map for an interactive version.
| Observer | Country | Teff | nETA |
|---|---|---|---|
| Tomasz Adam | Poland | 1.25h | 1 |
| Salvador Aguirre | Mexico | 1.50h | 6 |
| Alexandre Amorim | Brazil | 13.33h | 79 |
| Jure Atanackov | Slovenia | 4.05h | 0 |
| Pierre Bader | Germany | 10.10h | 12 |
| Janos Bakos | Hungary | 1.93h | 11 |
| Felix Bettonvil | Netherlands | 16.11h | 164 |
| Simiao Cheng | China | 0.50h | 1 |
| Tim Cooper | South Africa | 2.00h | 13 |
| Paul Craft | Australia | 3.44h | 62 |
| Anderson Dantas | Brazil | 2.00h | 20 |
| Frank Enzlein | Germany | 1.17h | 2 |
| Balazs Fodor | Hungary | 0.94h | 6 |
| William Godley | United States | 1.33h | 2 |
| Lew Gramer | United States | 1.23h | 14 |
| Wayne T. Hally | United States | 7.05h | 8 |
| Phil Hart | Australia | 1.45h | 10 |
| Vilem Heblik | Czech Republic | 4.8h | 12 |
| Di Hu | China | 2.9h | 7 |
| Visnja Jankov | Serbia | 1.50h | 4 |
| Paul Jones | United States | 1.25h | 6 |
| Javor Kac | Slovenia | 4.10h | 14 |
| Lance Kelly | Australia | 6.25h | 43 |
| Janez Kos | Slovenia | 1.00h | 4 |
| Jakub Koukal | Czech Republic | 20.59h | 55 |
| Roman Kovalyk | Italy | 2.50h | 5 |
| Peter Van Leuteren | Netherlands | 1.92h | 2 |
| Anna S. Levina | Israel | 0.81h | 12 |
| Pengkai Liu | China | 1.70h | 4 |
| Qiang Ma | China | 1.00h | 4 |
| Adam Marsh | Australia | 15.23h | 149 |
| Pierre Martin | Canada | 1.10h | 12 |
| Koen Miskotte | Netherlands | 8.85h | 4 |
| Nilesh Puntambekar | India | 1.00h | 13 |
| Jurgen Rendtel | Germany | 5.66h | 9 |
| Joao Santos | Brazil | 0.79h | 12 |
| Branislav Savic | Serbia | 1.50h | 5 |
| Sergei Schmalz | Germany | 14.70h | 5 |
| Filip Stanisavljevic | Serbia | 1.34h | 3 |
| Con Stoitsis | Australia | 2.71h | 10 |
| Tao Su | China | 1.42h | 16 |
| Richard Taibi | United States | 1.35h | 3 |
| Csilla Tepliczky | Hungary | 1.41h | 10 |
| Istvan Tepliczky | Hungary | 1.46h | 5 |
| Michel Vandeputte | Belgium | 11.58h | 4 |
| Thomas Weiland | Austria | 17.11h | 190 |
| Xijun Wu | China | 0.92h | 4 |
| Chris Wyatt | Australia | 0.65h | 8 |
| Marko Zivanovic | Serbia | 1.66h | 5 |
| Predrag Zivkov | Serbia | 1.50h | 0 |
Create your own analysis. The files below can be opened using Excel:
eta2011_rate.csv (number of meteors per interval per observer)
eta2011_magn.csv (number of meteors per magnitude bin per observer)
The information on this page may be distributed freely provided credit is given to the International Meteor Organization (IMO) and, when possible, to the individual observers. The computer facilities to generate this page are provided by ESA/RSSD and Armagh Observatory.
References:


Lorem Ipsum is simply dummy text of the printing and typesetting industry.
Lorem Ipsum is simply dummy text of the printing and typesetting industry.
Lorem Ipsum is simply dummy text of the printing and typesetting industry.
Lorem Ipsum has been the industry's standard dummy text since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.Lorem Ipsum has been the industry's standard dummy text since the 1500s, when an unknown
when an unknown printer took a galley
when an unknown printer took a galley
when an unknown printer took a galley
when an unknown printer took a galley
when an unknown printer took a galley
when an unknown printer took a galley
andrew wayne / demolink.org
eva green / demolink.org
cody / demolink.org
cody / demolink.org


{% extends "layout.html" %} {% block content %} AI Audio Classifier We trained a convolutional neural network to predict music genres from audio data. Try it out below! {% endblock content %}
We trained a convolutional neural network to predict music genres from audio data. Try it out below!


Click on a bot to select it and see its neural network activations.
Hit CTRL+U to see source code, or visit GitHub project.
This particular demo is only part of the more general GitHub project, which tries to simplify similar game-like canvas apps.
Basically, each creature has two eyes that sense amount of food. Both eyes act as input neurons in a brain, which is just a very simple Neural Network. The output nodes of the neural network turn them. If they accumulate food, they can reproduce with slight mutations in the weights of their brain.


public class CurrentUser
extends java.lang.Object
User
,
LoginActivity
| Modifier and Type | Method and Description |
|---|---|
User |
getCurrentUser()
Returns the currently logged in User object.
|
static CurrentUser |
getInstance()
By calling this method, any java class can get an instance of the CurrentUser singleton.
|
boolean |
loggedIn()
A method that checks if a User object has been set in the CurrentUser, This indicates whether
A User has "logged in" or not.
|
void |
setCurrentUser(User user)
Sets the Current user to the User passed in.
|
public static CurrentUser getInstance()
public void setCurrentUser(User user)
user
- The User object that will be set as the CurrentUser.public User getCurrentUser()
public boolean loggedIn()


[gecode-users] Time limit
Pierpaolo Caricato
pierpaolo.caricato at unisalento.it
Tue Jan 31 18:03:02 CET 2017
Mmh. So, my assumption that gecode experts are also experts in the other
solvers included in mini zinc is wrong... 😞
Thank you for your answer anyway.
I've just posted this question there too. 👍🏻
Regards.
Pierpaolo
Il giorno mar 31 gen 2017 alle 16:27 Christian Schulte <cschulte at kth.se> ha
scritto:
> Hi, this is not a Gecode question, please ask the question at the
> appropriate MiniZinc forum – for your own sake!
>
>
>
> Best
>
> Christian
>
>
>
> --
>
> Christian Schulte, www.gecode.org/~schulte
>
> Professor of Computer Science, KTH, cschulte at kth.se
>
> Expert Researcher, RISE ICT/SICS, cschulte at sics.se
>
>
>
> *From:* users-bounces at gecode.org [mailto:users-bounces at gecode.org] *On
> Behalf Of *Pierpaolo Caricato
> *Sent:* Tuesday, January 31, 2017 15:57
> *To:* users at gecode.org
> *Subject:* [gecode-users] Time limit
>
>
>
> Hi.
>
> I’m new to this list and “almost new” to mini zinc and all its surrounding
> projects, including gecode.
>
> I’ve seen in this mailing list archive that a time limit when running
> gecode from the CLI can be set appending
>
> --fzn-flags "-time 2000"
>
> to the command line.
>
>
>
> I understand I’m a bit OT here, but I assume many gecode users also use
> g12mip (I come from a PhD in Operations Research, so MIP is my main
> background, though I’m investigating more and more often CP as well)…
>
> Why does this option not work when launching g12mip?
>
> Can anybody give me a hint on how to set a time limit when I select this
> solver engine instead of gecode to solve a minizinc mip model?
>
>
>
> Thank you
>
>
>
> Pierpaolo Caricato
>
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Jumanji: The Next Level
Win a family pass to the Hot Tomato preview screening
The gang is back, but the game has changed – Jumanji: The Next Level in Event Cinemas Boxing Day.
We have heaps of family passes up for grabs!
Wake up with Flan, Emily Jade & Christo and tune into Galey, Mal & Moyra for the drive home to win tickets for your family to come along to the preview screening at Event Cinemas on Sunday 15 December.
Jumanji: The Next Level in Event Cinemas Boxing Day
In Jumanji: The Next Level, the gang is back but the game has changed. As they return to Jumanji to rescue one of their own, they discover that nothing is as they expect. The players will have to brave parts unknown and unexplored, from the arid deserts to the snowy mountains, in order to escape the world’s most dangerous game.
Starring Dwayne Johnson, Jack Black, Kevin Hart, Karen Gillan, Nick Jonas, Awkwafina, Ser’Darius Blain, Madison Iseman, Morgan Turner, Alex Wolff with Danny Glover and Danny DeVito.
Directed by Jake Kasdan.
Competition opens Monday 25 November and closes Friday 13 December 2019.
0Weeks0Days0Hours
25 x family passes to the preview screening of Jumanji: The Next Level at Event Cinemas.
The Hot Tomato Broadcasting Company’s Standard Competition Terms and Conditions apply to all 102.9 Hot Tomato and myGC contests.


FreeJoint()
语法
FreeJoint(#Joint)概要
Frees the specified joint and releases all its associated memory. The joint must not be used (by using its number with the other functions in this library) after calling this function.
参数
#Joint The joint to free. If #PB_All is specified, all the remaining joints are freed.
返回值
无.
备注
All remaining joints are automatically freed when the program ends.
参阅
PointJoint(), HingeJoint(), ConeTwistJoint(), SliderJoint()
已支持操作系统
所有


The examples 1-6 come from the WAI Tutorials - Images.
- Image used alone as a linked logo
- Logo image within link text
- Icon image conveying information within link text
- Stand-alone icon image that has a function
- Image used in a button
- An editor interface
- Image of text used as a linked logo (1)
- Image of text used as a linked logo (2)
- A print preview icon
- A search icon
- A submit button
Image used alone as a linked logo
The following image is the only content of a link that leads to the W3C home page. It has the text alternative “W3C home” to indicate where the link will take the user. The next example, “Logo image within link text” example, discusses what to do when there is more text in the link to identify the destination. This example is from the WAI Tutorials Images.

Note: In this situation, the logo is also an image of the text “W3C”, but in this case, its primary function is to link to the homepage, so the word “home” was added to the text alternative.
Logo image within link text
In this example, the W3C logo is used to supplement text within a link that leads to the W3C home page. The image does not represent different functionality or convey other information than that already provided in the link text, so a null (empty) value is applied, (alt=""), to avoid redundancy and repetition. In effect the image is a decorative adjunct or visual cue to the link text. This example is from the WAI Tutorials Images.
  W3C Home
Icon image conveying information within link text
In this example, the image follows text within a link to inform users that the link will open in a new window. It has the text alternative “new window” to convey the meaning of the icon. This example is from the WAI Tutorials Images.
 W3C Homepage
Stand-alone icon image that has a function
The following image is an icon representing a printer to denote print functionality. It has the text alternative “Print this page” because its purpose is to activate the print dialog when it is selected.

Image used in a button
The following image is used to give the button a distinct style. In this case, it is the button to initiate a search request and is an icon representing a magnifying lens. The text alternative for the image is “search” to convey the purpose of the button.
<input type="image" src="searchbutton.png" alt="Search">
An editor interface
In this example, a portion of an editor interface is displayed. Each button has an icon representing an action a user can take on content they are editing. For users who cannot view the images, the action names are included within the alt attributes of the images.

<button></button>

<button></button>

<button></button>

<button></button>

<button></button>

Image of text used as a linked logo (1)
In this example, a link contains a logo. The link points to the W3C web site from an external site. The text alternative is a brief description of the link target. This example is from EXAMPLE 24 of HTML 5.3.

Image of text used as a linked logo (2)
This example is the same as the previous example, except that the link is on the W3C web site. The text alternative is a brief description of the link target. This example is from EXAMPLE 25 of HTML 5.3.

NOTE: Depending on the context in which an image of a logo is used it could be appropriate to provide an indication, as part of the text alternative, that the image is a logo. Refer to HTML 5.3 section §<IP_ADDRESS>.19 Logos, insignia, flags, or emblems.
A print preview icon
In this example, a link contains a print preview icon. The link points to a version of the page with a print stylesheet applied. The text alternative is a brief description of the link target. This example is from EXAMPLE 26 of HTML 5.3.

A search icon
In this example, a button contains a search icon. The button submits a search form. The text alternative is a brief description of what the button does. This example is from EXAMPLE 27 of HTML 5.3.
<button>  </button>
A submit button
<form action="http://example.com/prog/text-read" method="post"> <input type="image" name="submit" src="button.gif" alt="Submit" /> </form>


A templatetag framework for easier integration of mustache.js JavaScript templates with Django templates. Inspired by ICanHaz.js, django-icanhaz, and jquery.mustache.
Tested with Django 1.3 through trunk, and Python 2.6 and 2.7. Almost certainly works with older versions of both.
Install from PyPI with pip:
pip install django-mustachejs
or get the in-development version:
pip install django-mustachejs==dev
For example consider the files app/jstemplates/main.mustache:

This is {{ name }}'s template

and app/templates/main.html:
{% load mustachejs %}

{% mustachejs "main" %}

Any time you use the mustachejs template tag:
{% load mustachejs %}
{% mustachejs "main" %}
django-mustachejs will generate the following:

This stores the text of the template in an attribute on the Mustache.TEMPLATES object (it will first create the object if it does not yet exist). The Mustache.template(...) function then creates an object with a render(...) method that has a similar signature as Mustache.to_html(...), except without the template name as the first parameter. The render method will also use the set of templates in Mustache.TEMPLATES as partials, allowing any template that django-mustachejs knows about to be used as a template partial as well.
In addition to {% mustachejs ... %}, django-mustachejs comes with several template tags that you can use to render your mustache templates:
The name provided to the template tag can be a string that will match a single file, a file glob pattern, or a regular expression. Using the template tag {% mustachejs [glob/regex] %} in your Django templates will embed all files matching that regex in the template directories. So, {% mustachejs '(.*_template)' %} and {% mustachejs '*_template' %} would both match note_template.html and comment_template.html, giving them templatename note_template and comment_template, respectively. (Note that the regular expression pattern must contain parentheses denoting a single matching group; this group will become the name of the template).
django-mustachejs supports internationalization tags. In your settings module, set the MUSTACHEJS_I18N_TAGS variables (default: ('_', 'i18n')). These tags can be used to preprocess the javascript templates into translatable content. For example:

{{#_}}Hello, {{name}}. I like your {{color}} {{thing}}?{{/_}}

may render to:

Salut, {{name}}. J'aime votre {{thing}} {{color}}?

The translatable strings will be picked up by Django’s makemessages management command.
Set MUSTACHEJS_FINDERS to configure the dotted class names of the finders the application will use. By default, this is the following list:
["mustachejs.finders.FilesystemFinder",
"mustachejs.finders.AppFinder",
"mustachejs.finders.FilesystemRegexFinder",
"mustachejs.finders.AppRegexFinder",]
Set the MUSTACHEJS_DIRS setting to a list of full (absolute) path to directories where you will store your mustache templates. By default this is an empty list.
Set MUSTACHEJS_APP_DIRNAMES to a list of directory names that can be found under directories of applications specified in INSTALLED_APPS. By default, this setting has the value of ["jstemplates"].
Set the MUSTACHEJS_EXTS setting to a list of the app should search for to find template files. By default this is set to ['mustache', 'html']. Order matters (e.g., *.mustache will take precedence over *.html).
Set the MUSTACHEJS_PREPROCESSORS variable to control how the templates are preprocessed. By default, there is one preprocessor activated:
['mustachejs.preprocessors.I18nPreprocessor']
The I18nPreprocessor will translate marked strings before rendering the template. To disable this feature, set MUSTACHEJS_PREPROCESSORS to an empty list.
Set MUSTACHEJS_I18N_TAGS to the names of the tags used to mark strings for internationalization. By default, this is set to the list:
["_", "i18n"]
Meaning that text falling between the tags {{#_}}...{{/_}} and {{#i18n}}...{{/i18n}} will be marked for translation.
The finding of templates can be fully controlled via the MUSTACHEJS_FINDERS setting, which is a list of dotted paths to finder classes. A finder class should be instantiable with no arguments, and have a find(name) method which returns either (1) the full absolute path to a template file, given a base-name, or (2) a list of (template name, template file path) pairs according to the given base name.
By default, MUSTACHEJS_FINDERS contains "mustachejs.finders.FilesystemFinder" (which searches directories listed in MUSTACHEJS_DIRS), "mustachejs.finders.AppFinder" (which searches subdirectories named in MUSTACHEJS_APP_DIRNAMES of each app in INSTALLED_APPS), "mustachejs.finders.FilesystemRegexFinder", and "mustachejs.finders.AppRegexFinder", in that order – thus templates found in MUSTACHEJS_DIRS take precedence over templates in apps, and templates identified by file glob patterns take precedence over those identified by regular expression patterns.
It is simple to extend django-mustachejs to prepare your mustache templates to be used with your favorite Javascript library creating a template node class that derives from mustachejs.templatetags.BaseMustacheNode, and overriding a single function. Refer to the existing tag definitions for mustachejs, mustacheich, mustacheraw, and dustjs for more information.


REGISTRATION FORM
First Name:
Last Name:
Email address
:
Phone Number:
Date of Birth:
Addressline1:
City:
State:
Country:
Zip:
Password:
Re-Password:


http://www.speakers-podium.com/susangranger.
Susan Granger's review of "MUMFORD" (Touchstone Pictures)
What does it take to be a good psychologist? How can you get people to confide their fantasies, dreams, and frustrations in order to alleviate the pain of the human condition? Writer/director Lawrence Kasdan believes that listening, really listening is the most important skill - and that's the premise for his intelligent, amusing new comedy. Loren Dean ("Billy Bathgate") stars as Dr. Mumford, a young psychologist who opens a practice in a small, picturesque town, coincidentally named Mumford, and discovers his unorthodox form of therapy has amazing, unexpected results with an odd assortment of quirky locals. There's a young divorcee suffering from Chronic Fatigue Syndrome (Hope Davis), a pulp-fiction obsessed pharmacist (Pruitt Taylor Vince), a frustrated housewife (Mary McDonnell) who's become addicted to mail-order shopping, her workaholic husband (Ted Danson), a fashion-preoccupied teen (Zooey Deschanel), Mumford's outspoken landlady (Alfre Woodard) who runs the local cafe, and a lonely billionaire (Jason Lee), the monarch of modems, who zips around on a skateboard. While they respond to his empathy and frankness, no one realizes that mysterious, unconventional Dr. Mumford has the biggest secret of all - except maybe a suspicious attorney (Martin Short) and the two other therapists in town (David Paymer, Jane Adams). Like "The Big Chill," "The Accidental Tourist," and "Grand Canyon," this is an excellent ensemble effort, which is a credit to Kasden's talent for casting. On the Granger Movie Gauge of 1 to 10, "Mumford" is a fantastical, intriguing 8, proving that love comes in many disguises.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


| GLib Reference Manual | ||||
|---|---|---|---|---|
| Top | Description |
#include <glib.h> GHmac; GHmac * g_hmac_new (GChecksumType digest_type
,const guchar *key
,gsize key_len
); GHmac * g_hmac_copy (const GHmac *hmac
); GHmac * g_hmac_ref (GHmac *hmac
); void g_hmac_unref (GHmac *hmac
); void g_hmac_update (GHmac *hmac
,const guchar *data
,gssize length
); const gchar * g_hmac_get_string (GHmac *hmac
); void g_hmac_get_digest (GHmac *hmac
,guint8 *buffer
,gsize *digest_len
); gchar * g_compute_hmac_for_data (GChecksumType digest_type
,const guchar *key
,gsize key_len
,const guchar *data
,gsize length
); gchar * g_compute_hmac_for_string (GChecksumType digest_type
,const guchar *key
,gsize key_len
,const gchar *str
,gssize length
);
HMACs should be used when producing a cookie or hash based on data and a key. Simple mechanisms for using SHA1 and other algorithms to digest a key and data together are vulnerable to various security issues. HMAC uses algorithms like SHA1 in a secure way to produce a digest of a key and data.
Both the key and data are arbitrary byte arrays of bytes or characters.
Support for HMAC Digests has been added in GLib 2.30.
typedef struct _GHmac GHmac;
An opaque structure representing a HMAC operation.
To create a new GHmac, use g_hmac_new()
. To free
a GHmac, use g_hmac_unref()
.
Since 2.30
GHmac * g_hmac_new (GChecksumType digest_type
,const guchar *key
,gsize key_len
);
Creates a new GHmac, using the digest algorithm digest_type
.
If the digest_type
is not known, NULL
is returned.
A GHmac can be used to compute the HMAC of a key and an
arbitrary binary blob, using different hashing algorithms.
A GHmac works by feeding a binary blob through g_hmac_update()
until the data is complete; the digest can then be extracted
using g_hmac_get_string()
, which will return the checksum as a
hexadecimal string; or g_hmac_get_digest()
, which will return a
array of raw bytes. Once either g_hmac_get_string()
or
g_hmac_get_digest()
have been called on a GHmac, the HMAC
will be closed and it won't be possible to call g_hmac_update()
on it anymore.
|
the desired type of digest |
|
the key for the HMAC. [array length=key_len] |
|
the length of the keys |
Returns : |
the newly created GHmac, or NULL .
Use g_hmac_unref() to free the memory allocated by it. |
Since 2.30
GHmac * g_hmac_copy (const GHmac *hmac
);
Copies a GHmac. If hmac
has been closed, by calling
g_hmac_get_string()
or g_hmac_get_digest()
, the copied
HMAC will be closed as well.
|
the GHmac to copy |
Returns : |
the copy of the passed GHmac. Use g_hmac_unref()
when finished using it. |
Since 2.30
GHmac * g_hmac_ref (GHmac *hmac
);
Atomically increments the reference count of hmac
by one.
This function is MT-safe and may be >


in Singapore
A luxury landmark set in the heart of a historic precinct, InterContinental Singapore is deeply rooted in the arts and cultural districts on the fringe of the Marina Bay. Replete with convenience at the doorstep, the adjoining Bugis Junction shopping mall which spans over 200 retail and dining outlets, offers a prelude to what the exciting destination has to offer.
| Price per room per night | 1 Adult | 2 Adult | 3 Adult | 2 Adult 1 Child | 2 Adult 2 Child |
|---|---|---|---|---|---|
| WeekDay | S$ 352 | S$ 373 | N.A | N.A | N.A |
| WeekEnd | S$ 373 | S$ 393 | N.A | N.A | N.A |


Derek Eder
@derekeder
RT @jazzmyth: I looked at @BetterGov's salaries database to see how that affects @Chicago_Police's budget. In 2017, it was nearly 50% of th…
6/5/2020, 8:23:57 PM
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link← @derekeder Twitter archive
Derek Eder
@derekeder
RT @jazzmyth: I looked at @BetterGov's salaries database to see how that affects @Chicago_Police's budget. In 2017, it was nearly 50% of th…
6/5/2020, 8:23:57 PM
Favs: 0
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link


Meeting Mike for the first
time
For many of the advanced features of Mike, you need to register with him.
This is fairly easy to do, provided you follow these instructions exactly.
Almost every error is of a PEBKAC nature and can therefore be
avoided by RTFM (This document).
The first step is to type /msg Callahan hello
This will introduce you to him, but you're not done yet; there is at least one
more command you must utilize, and not doing this ASAP could cause a
world of issues, as by not having a password, you will be unable to make any
changes later on. This makes for very unhappy users, as based on empirical
evidence during the beta stage. We highly recommend a password that you can
remember easily, as there is no way to recover it should you forget it.
/msg Callahan
PASS <password>
Teaching Mike your many
guises
Mike can remember as many hostmasks for you as he has disk
space available. There are two ways to teach him new hostmasks to recognize you
with:
IDENT: /msg Callahan IDENT <password>
This is the recommended way if you do not understand what "hostmask" means, and
how to determine it and using wildcards to describe it. This
will only add the current hostmask you are using.
ADDHOST: /msg Callahan ADDHOST <password> <hostmask>
This is the more advanced way, as you can add a hostmask that you are not
currently using, but know you will use, such as from work, or a shell account.
Be careful you don't set too liberal a hostmask; if you use this method, you are
responsible for errors arising from it. If you are uncomfortable with this, use
IDENT. The hostmask specified must not match the hostmask of another
user.
/msg<EMAIL_ADDRESS><username>
<password>
/mode <your nick> +x
(Mike's is
MikeCallahan.users.undernet.org Please be sure this is the info for the
bot you are messaging any passwords to, Mike *can*, and *has* been imitated
before) Please note that username does not always mean your nick. The reason
this is recommended, is that no matter where you are IRCing from, you can have a
consistent hostmask to use. This can be the only hostmask you ever have to tell
Mike about, if you do the above steps before saying hello. Many IRC clients have
means to do the login and mode commands automatically each time you sign on;
check your documentation.Teaching Mike your personal
information
Mike can keep several bits of information about you; currently there are only
two, but more will be implemented as time goes on.
TAGLINE: /msg Callahan my tagline is <tagline>
/msg Callahan What is|What's my tagline?
To get this information from Mike, there are two commands to use:
Mike, who am I?
to retrieve
your own and Mike, who is <nick>
[1]
to retrieve other's
USUAL: /msg Callahan my usual is <usual>
/msg Callahan What is|What's my usual
This can be used to set your usual "drink" (it can be anything, not necessarily
a beverage). This is used in many situations, such as when someone is at the
line and you enter, as well as Mike randomly picking patron's usuals for various
uses to use in channel.
We do have some advice for syntax in setting this. Mike will usually do
something of the nature "Callahan serves Foo <foo's usual>", so we suggest using
proper English articles, such as "some", "a/an", "the". If you're Foo, and
you set it by typing /msg Callahan my usual is a
heap of lottery money, with a gold bullion chaser
it will come out "Callahan serves Foo a heap of lottery money, with a gold
bullion chaser." Also note that Mike added the period; please do not add
this yourself, as Mike uses this for other things, and will insert the proper
punctuation himself, such as "Callahan serves Foo a heap of lottery money, with
a gold bullion chaser, courtesy of Bar". Note this looks a lot odder if
it's "Callahan serves Foo a heap of lottery money, with a gold bullion chaser.,
courtesy of Bar"[2]
There are several ways to use the usual functions:
Mike, usual (Give a vague request, get a
vague answer)
Mike, my usual (Can also be followed by
anything else such as "please" or "stat", though he will ignore them)
Mike, give|get me <nicks's> usual[1]
Mike, give|get <nick> my usual
Mike, give|get <nick> <nick's> usual
Mike, give|get <nick> his|their|her usual
Please be sure to use proper possessives, such as "foo's" or "Bars'"[3]
Back to top
Mike, amore will prompt Mike to burst into song, punning on the
well-known song, Amore.
Mike, kosh will prompt Mike to quote the character Kosh Naranek, form the TV series
Babylon 5.
Mike, Billy will prompt Mike to quote from the movie Billy Madison.
Mike, Blazing will prompt Mike to quote from the movie Blazing Saddles.
Mike, Blues will prompt Mike to quote from the movie Blues Brothers
.
Mike, Shorty will prompt Mike to quote from the movie Get Shorty.
Mike, Full will prompt Mike to quote from the movie Full Metal Jacket.
Mike, Good will prompt Mike to quote from the movie Goodfellas.
Mike, Happy will prompt Mike to quote from the movie Happy Gilmore.
Mike, Pulp will prompt Mike to quote from the movie Pulp Fiction.
Mike, Dogs will prompt Mike to quote from the movie Reservoir Dogs.
Mike, Scarface will prompt Mike to quote from the movie Scarface.
Mike, Scream will prompt Mike to quote from the movie Scream.
Mike, Ghost will prompt Mike to quote from the movie Ghostbusters.
Mike, Futurama will prompt Mike to quote from the TV series Futurama.
Mike, family guy will prompt Mike to quote from the TV series Family Guy.
Mike, dubya will prompt Mike to quote George W. Bush (43rd President
of the USA).
Mike, bofh will prompt Mike to quote the BOFH.
If you wish to provide either more quotes for the above, or something new,
please post in his forum (Requires
registration to post)[4]
Back to top
/me speaks louder than
words
Mike has all sorts of activities you can get him to do.
Forums Help Beta Help
Quote Help Source Stats Page
This work is licensed under a Creative Commons
Attribution-NonCommercial-ShareAlike 2.5 License.
Copyright 2006 by Brendan K Callahan & David Goodwin


---
layout: page
title: Service
background: '/img/bg-about.jpg'
---
Volunteer Work
Little Elm High School
- Communities in Schools of North Texas
- Grades 9-11
- Math tutor
- Algebra 1
- Algebra 2
- Geometry
- Sping 2020
Project Transformation, North Texas
- Volunteer reading with ESL students grade K-4
- Summer 2011
- Summer 2010


WQMY
Furniture - Ross's Fine Art Auctioneers - Northern Ireland's leading ...
Northern Ireland's leading auction house for Irish Art, antiques & household furniture. We hold weekly auctions at our belfast auction rooms and quarterly Irish .
http://www.rosss.com/auction/furniture
| the last supper miller/body shop palmyra ny/ vets center lewiston maine |
|
|---|---|
| origins of symbiosis by leon shernoff | Williamsport |
| Branding | MyNetworkTV furniture auction rooms ireland |
| venison pepper stick recipe | evolution of man laptop: 29 (ricardo beverly hills backpacks) & air bag light hyundai-DT 45.3 (UHF) |
| happy trails aquisition limited partnerships | see article |
| Owner | New Age Media, LLC Sheppard's Irish Auction House, Durrow, Co. Laois Ireland. |
| First air date | December 30, 1988 |
| cornelia meyer egbert rimkus death valley | MYNetworkTV |
| shana weiss m d | WOLF-TV, windows xp operating disk |
| traditinal swedish christmas dinner | WILF (1988-2006) |
| Former channel number(s) | deVeres Art Auctions: Home |
| where is vanuatu in the pacific | coturnix quail day old chicks (1988-1998) jackson all water kayak / principios de derecho constitucional (1998-2006) |
| free bb screen lock | 50 windows xp operating disk 420 kW (WOLF-DT3) |
| free bb screen lock | 243 m 488 m (WOLF-DT3) |
| bracewell sahara car crossing | 52075 73375 (WOLF-DT3) |
| Transmitter coordinates | dundee real estate investment trust dual path ground drive (WOLF-DT3) |
The Company - Mullen's - Laurel Park
Mullen's auction house is set in a prestigious location at Laurel Park, and . and valuing business, the firm holds antique and quality furniture sales every five . The Laurel Park auction rooms (the largest in Ireland) administrated by Edel King .
http://www.mullenslaurelpark.com/The_Company.asp
Cork Auction Rooms Ireland, Douglas, Cork,, - Live Auctioneers
Dec 30, 2012 . Auctioneer: Cork Auction Rooms Ireland, Address: 12 Southlink, . our monthly general auctions including antique and modern furniture as well .
http://www.liveauctioneers.com/auctioneer/1660-cork-auction-rooms-ireland
Contents |
[nema electrical safety rating] History
Auctions - Sotheby's
99 Auctions . Auctions; Selling Exhibitions; Valuation Days; Lectures; Other. Departments. reset filter. ?. 19th Century European Paintings; 19th Century Furniture .
http://www.sothebys.com/en/auctions.html
RJ Keighery CITY AUCTION ROOMS
CITY AUCTION ROOMS . to include, Waterford Crystal, China and decorative art , garden Furniture, antique and later furniture and . please let us know at info@ cityauctionrooms.com . RJK Waterford Ltd. 27a William St., Waterford, Ireland .
http://www.cityauctionrooms.com/
About Us - Chatsworth Auction Rooms
Chatsworth Auction Rooms & Furniture Studios in Mamaroneck, New York is the . man named Sam Lightbody who had recently emigrated from Belfast, Ireland.
http://www.chatsworthauction.com/chatsworth/content/?nm=about
Herman & Wilkinson.ie
The Herman Wilkinson Auction Rooms on Lower Rathmines Road has been . to Dublin's most famous weekly household and furniture auction, these rooms have . 80 and 90 auctions every year, more than any other auction rooms in Ireland.
http://www.hermanwilkinson.ie/
Christie's London - King Street - Saleroom & Offices | Christie's
. has sold fine art, furniture, jewelry and wine since James Christie conducted the first sale in London in 1766. . Salerooms & Offices > London, King Street .
http://www.christies.com/locations/salesrooms/king-street/
Irish Country Home - The Irish Fine Art Auction Group
Auction Rooms in Cork and Limerick. . The Auction Rooms - Sixmilebridge . Georgian and Edwardian pieces together with a collection of painted furniture.
http://irishcountryhome.com/
The Ashgrove Group
Ashgrove Auction Rooms is one of the leading auctioneers of private and . We hold bi-monthly sales of Georgian & Later Furniture & Effects, as well as .
http://www.ashgrovegroup.ie/
Auctions | Collect Ireland
Royal Oak Auction Rooms are located on the junction of the N9 main road and the R724. . Weekly auctions of Antiques & Furniture and household items.
http://collectireland.wordpress.com/auctions-2/
Bid in Adam's Upcoming Online Auctions & Review Past Auction ...
View and bid in upcoming online auctions for Adam's. Artfact also lets you review past auction results for Adam's and provides an industry-leading price .
http://www.artfact.com/auction-house/adam-s-rm9kptonl3
Mullingar Salesroom:
Mullingar Salesroom offers a wide variety of antiques & household furniture, from fine art . House clearance and surplus stock auctions held periodically, keep an eye on our . Westmeath, Ireland | tel: 086 2517 204 / 044 9343 458 | email: .
http://mullingarauctions.com/
Bid in Sheppards Forthcoming Online Auctions & Review Past ...
View and bid in forthcoming online auctions for Sheppards. Invaluable also lets you review past auction results for Sheppards and provides an industry-leading .
http://www.invaluable.com/auction-house/sheppards-gaawowqhno
[chadder day by day summary] Digital channels
| Channel | Name | bracewell sahara car crossing | used pallet racks san diego county | Programming |
|---|---|---|---|---|
| 53.1 | furniture auction rooms ireland DT | what wrong me tired irritable | design ideas group deal nj | Main furniture auction rooms ireland programming / MyNetworkTV |
| 53.2 | WOLF DT | donald and company scottsdale az | asus p5e-vm do lga775 matx motherboard | Simulcast of saint row online game |
| 53.3 | WSWB DT | 480i | 4:3 | Simulcast of linda blanchard gastric bypass baton rouge |
English & Irish Furniture - Connecticut's Premier Estate Auction House
Connecticut's Premier Estate Auction House. Auctions · Current & Upcoming · Past · Buying · iGavel Auctions . English & Irish Furniture. Sold for $57,600 .
http://litchfieldcountyauctions.com/auctions/english-irish-furniture/
[saltwater to kill roots] References
[skype chat window screenshot] External links
- china's electric car 2007
- south american noni juice
- recessed gas cap conversion
- new zip codes polk county florida
- photos 50 calaber rifle wind runner
- la graciosa lanzarote photos
|
|


Google Code offered in: English - Español - 日本語 - 한국어 - Português - Pусский - 中文(简体) - 中文(繁體)
GWT represents locale as a client property whose value can be set either using a meta tag embedded in the host page or in the query string of the host page's URL. Rather than being supplied by GWT, the set of possible values for the locale client property is entirely a function of your module configuration.
Client properties are key/value pairs that can be used to configure GWT modules. User agent, for example, is represented by a client property. Each client property can have any number of values, but all of the values must be enumerable when the GWT compiler runs. GWT modules can define and extend the set of available client properties along with the potential values each property might assume when loaded in an end user's browser using the <extend-property> directive. At compile time, the GWT compiler determines all the possible permutations of a module's client properties, from which it produces multiple compilations. Each compilation is optimized for a different set of client properties and is recorded into a file ending with the suffix .cache.html.
In deployment, the end-user's browser only needs one particular compilation, which is determined by mapping the end user's client properties onto the available compiled permutations. Thus, only the exact code required by the end user is downloaded, no more. By making locale a client property, the standard startup process in <module>.nocache.js chooses the appropriate localized version of an application, providing ease of use, optimized performance, and minimum script size. See the Knowledge Base for more information about the logic of the <modulename>.nocache.js file.
In any real-world application, you will define at least one locale in addition to the default locale. "Adding a locale" means extending the set of values of the locale client property using the <extend-property> element in your module XML. For example, the following module adds multiple locale values:
<module> <inherits name="com.google.gwt.user.User"/> <inherits name="com.google.gwt.i18n.I18N"/> <!-- French language, independent of country --> <extend-property name="locale" values="fr"/> <!-- French in France --> <extend-property name="locale" values="fr_FR"/> <!-- French in Canada --> <extend-property name="locale" values="fr_CA"/> <!-- English language, independent of country --> <extend-property name="locale" values="en"/> </module>
The com.google.gwt.i18n.I18N module defines only one locale by default, called default. This default locale is used when the locale client property goes unspecified in deployment. The default locale is used internally as a last-resort match between a Localizable interface and a localized resource or class.
In general, you should avoid running the app in the default locale — many things will produce surprising results. For example, only a small set of currencies will be supported, resulting in errors for applications that make use of other currencies, and no plural forms will be supported (since the language isn't known). If you really want to allow the application to continue running when the user requests an unsupported locale, you are probably better off choosing some real language as a default, such as en. You can set what value is used for the default by including the following in your module XML:
<set-property-fallback name="locale" value="en"/>
The locale client property can be specified using either a meta tag or as part of the query string in the host page's URL. If both are specified, the query string takes precedence. To specify the locale client property using a meta tag in the host page, embed a meta tag for gwt:property as follows:
<meta name="gwt:property" content="locale=x_Y">
For example, the following host HTML page sets the locale to "ja_JP":
<html> <head> <meta name="gwt:property" content="locale=ja_JP"> </head> <body> <!-- Load the GWT compiled module code --> <script src="com.google.gwt.examples.i18n.ColorNameLookupExample.nocache.js " /> </body> </html>
To specify the locale client property using a query string, specify a value for the name locale. For example,
http://www.example.org/myapp.html?locale=fr_CA
Tip: The preferred time to explicitly set locale is to do so before your GWT module is invoked. You can change the locale from within your GWT module by adding or changing the locale query string in the current URL and reloading the page. Keep in mind that after reloading the page, your module will restart.
For cases where the translated values are the same, but you still want country-specific details, you can use runtime locales to reduce the number of compiled permutations, but still get country-specific details like the default currency, number/date formatting rules, etc.
As an example, you might have one set of translations for all of Spanish as spoken in Latin America (es_419), yet allow users to choose a country-specific locale such as Argentinian Spanish (es_AR).
The easy way to use runtime locales is simply to add:
<inherits name="com.google.gwt.i18n.CldrLocales"/>
If you are embedding your module into an existing application, there may be another way of determining locale that does not lend itself to using the <meta> tag or specifying locale= as a query string. In this case, you could write your own property provider.
A property provider is specified in the module XML file as a JavaScript fragment that will return the value for the named property at runtime. In this case, you would want to define the locale property using a property provider. To see examples of <property-provider> definitions in action, see the files I18N.gwt.xml and UserAgent.gwt.xml in the GWT source code.
To get information about the current locale or the available set of locales, see the LocaleInfo class. For example:
if (LocaleInfo.getCurrentLocale().isRTL()) { ... }
for (String localeName : LocaleInfo.getAvailableLocaleNames()) { String displayName = LocaleInfo.getLocaleNativeDisplayName(localeName); ... }
GWT provides two classes to manipulate locales, which fully support aliases and locale inheritance.
GwtLocaleFactory factory = LocaleUtils.getLocaleFactory();
Set<GwtLocale> locales = localeUtils.getAllLocales();


This Community Calendar is a resource that displays information about previous and upcoming chapter and community events in a centralized place. Tabs at the top of the page organize events that are listed on the calendar into specific groups based on the type of event, for easier access.
Mission Statement: Our goal is to strengthen community ties by providing easy access to information to local activities taking place in the greater Seattle area. By increasing interaction between people sharing similar interests, whether it is in music taste, sports, or newfound hobbies, our community as a whole can prosper as relationships build and common goals are met.


For those coming from a background in Parallax's Spin language, your only concern will be syntax: the C-family of languages is wildly different. Don't worry - it's not hard.
For C developers with no background in Spin, the biggest hurdle will be learning about the famed "object-oriented programming" (still not hard).
There are lots of code examples throughout PropWare and libpropeller's source code, so please feel free
to
peruse them. You should also take advantage of the example projects provided in the
Examples
directory.
;
=
==
, !=
, >=
, <=
and
!
&&
for AND and ||
for OR&
, |
, and ^
for the bitwise operations AND, OR and
XOR
respectively
//
// This is a comment
/*
and */
/*
A multi-line comment!
*/
int x; // Remember, capitalization matters!
int X = 5; // These are two different variables!
block
of code is marked with {
and }
if (x == y) {
// A block of code only executed if `x` is equal to `y`
}
void
if no return)
// A function that takes no parameters and does not return a value
void main () {
// Some code here
}
// C will prefer the above function slightly different - they both mean the same thing
void main (void) {
// Some code here
}
// This function returns an integer of basic type `int`
int get_x () {
int x = 5;
return x;
}
// A function that takes two parameters, `x` and `y` and returns the sum
int add (int x, int y) {
return x + y;
}
// Basic while-loop
while (x == y) {
// Do stuff
}
// C++ allows you to declare your index (`i`) within the for-loop
for (int i = 0; i < 10; i++) {
printf("The current value of `i`: d", i);
}
// C typically has (and sometimes requires) the index declared prior to the loop
int i;
for (i = 0; i < 10; i++) {
printf("The current value of `i`: d", i);
}
// A simple do-while
do {
// Some stuff
} while (x == y);
Classes. It's all about classes: organizing code into logical blocks. If you have 3 functions that all
deal
with a serial terminal, you might want to categorize them as Serial
. That's all a
class
is - a group of functions that belong together. This code might look something like
class Serial {
public:
void start (int baudrate) {
// Initialize the serial terminal
}
void send_character (char c) {
// Some code to send a character over the serial bus
}
char receive_character () {
char c;
// Some code to receive a character from the serial bus and store it in `c`
return c;
}
}
Notice that, just like Parallax's Spin, we have visibility keywords: public
in this case.
This keyword marks everything beneath it as accessible to the outside world, just like Spin's
PUB
keyword before a function.
Where Spin might have some code such as
Obj
pst : "Parallax Serial Terminal"
PUB Main | receivedChar
pst.start(9600)
pst.Char('A')
receivedChar := pst.CharIn
C++ would write this as
int main () {
Serial pst; // Instantiation of the `Serial` object
char receivedChar; // Instantiation of the receivedChar variable
pst.start(9600); // Starting our Serial terminal at 9,600 baud
pst.send_character('A'); // Send the single character, 'A', out the serial bus
receivedChar = pst.receive_character(); // Store a character from the serial bus into `receivedChar`
return 0; // 0 typically represents successful completion of the program
}
The term "Serial" can be pretty generic. Maybe David's Serial object has a max baud of 115,000 but Bob's
Serial object has configurable pins (so you don't have to use the default RX and TX hardware pins). You
want to use BOTH Serial objects. In order to differentiate between David's Serial
class and
Bob's Serial
class, we prefix the class names with a namespace
. This looks
like
namespace PropWare {
class Serial {
// David's code here
}
}
namespace BobWare {
class Serial {
// Bob's code here
}
}
int main () {
PropWare::Serial davidSerial;
BobWare::Serial bobSerial;
davidSerial.call_function();
bobSerial.call_function();
return 0;
}
Now that both classes are surrounded by a namespace, our code can use both classes without conflict!
Coming soon!


Index
All Classes|All Packages
C
- ChangePasswordController - Class in sample
-
This class is used to handle the changing password features of the users and also Admin will be able to take certain advantages of this class also.
- ChangePasswordController() - Constructor for class sample.ChangePasswordController
- CheckAge(LocalDate) - Method in class sample.DonorApprovalListController
-
Method for checing the valid age.
- checkAlert() - Method in class sample.AddNewDonationController
-
This functions is for checking all the errors in the add new donations Information.
- checkAlert() - Method in class sample.ChangePasswordController
-
This is for the checking alert and show the scenarios to the user when the password is not able to be changed.
- checkAlert() - Method in class sample.DoneeNewReqController
-
This is for the checking alert while updating the information.
- checkAlert() - Method in class sample.OrganizationInfoController
-
This functions is for checking the errors in the add new information and Image files.
- checkAlert() - Method in class sample.PersonalInfoController
-
This method is for checking the Alerts of the total process.
- checkAlert() - Method in class sample.RegisterController
-
This method is for checking the Alerts of the total process.
- checkAlert() - Method in class sample.UpdateDonationInfoController
-
This is for the checking alert while updating the information.
- checkAlert() - Method in class sample.UpdateOrgController
-
This is for the checking alert while updating the information.
- checkAlert() - Method in class sample.UserProfileUpdateController
-
This is for the checking alert while updating the information.
- checkCredentials() - Method in class sample.LogINpanelController
-
Method for checking the credentials given input.
- checkCurrPassValid() - Method in class sample.ChangePasswordController
-
This function is for checking the validity of the given current password.
- checkDate() - Method in class sample.AddNewDonationController
-
This methods is here to check the validity of the date of new donation Here the Date of Birth of the User and donation date are fetched from the database and the result set is compared.
- checkPassword() - Method in class sample.ChangePasswordController
-
This checks the new password taken form the user and confirms the re-input form the user.
- checkPassword() - Method in class sample.RegisterController
-
Method for checking the Reentered password for confirmations.
- checkUserValid() - Method in class sample.RegisterController
-
Method for checking the validity of the user
- col_quantity - Variable in class sample.DoneePrevReqController
- count_org - Static variable in class sample.SearchOrgController
- count_req - Variable in class sample.DoneePrevReqController
- count_req - Variable in class sample.PendingRequestController
- count_req - Variable in class sample.SearchDonorOrgController
- countDonor() - Method in class sample.SearchDonorOrgController
-
Method for counting the number of Donor.
- countf - Static variable in class sample.FilterDonationController
- countf - Static variable in class sample.FilterRequestController
- countOrg() - Method in class sample.SearchOrgController
-
Method for counting the NUmber of the Organizations that are enlisted.
- countRequest() - Method in class sample.DoneePrevReqController
-
Method for counting the number of Requests in the database for a particular username.
- countRequestandBG() - Method in class sample.PendingRequestController
-
This method is for Counting the Request and the Blood Group in a Blood donation request.
All Classes|All Packages


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Class JSONPRequest
Provides a JSONPRequest class for repeated JSONP calls, and a convenience
method Y.jsonp(url, callback) to instantiate and send a JSONP request.
Both the constructor as well as the convenience function take two
parameters: a url string and a callback.
The url provided must include the placeholder string
"{callback}" which will be replaced by a dynamically
generated routing function to pass the data to your callback function.
An example url might look like
"http://example.com/service?callback={callback}".
The second parameter can be a callback function that accepts the JSON
payload as its argument, or a configuration object supporting the keys:
- on - map of callback subscribers
- success - function handler for successful transmission
- failure - function handler for failed transmission
- timeout - function handler for transactions that timeout
- format - override function for inserting the proxy name in the url
- timeout - the number of milliseconds to wait before giving up
- context - becomes
this
in the callbacks
- args - array of subsequent parameters to pass to the callbacks
- allowCache - use the same proxy name for all requests? (boolean)
Constructor
JSONPRequest
(
url
,
callback
)
- Parameters:
-
url
<String>
the url of the JSONP service
-
callback
<Object|Function>
the default callback configuration or
success handler
Properties
_pattern
- protected RegExp
RegExp used by the default URL formatter to insert the generated callback
name into the JSONP url. Looks for a query param callback=. If a value
is assigned, it will be clobbered.
Default Value: /\bcallback=.*?(?=&|$)/i
_template
- protected String
Template used by the default URL formatter to add the callback function
name to the url.
Default Value: "callback={callback}"
Methods
protected
Function
_defaultCallback
(
url
)
Parses the url for a callback named explicitly in the string.
Override this if the target JSONP service uses a different query
parameter or url format.
If the callback is declared inline, the corresponding function will
be returned. Otherwise null.
- Parameters:
-
url
<String>
the url to search in
- Returns:
Function
- the callback function if found, or null
protected
String
_format
(
url
,
proxy
)
URL formatter that looks for callback= in the url and appends it
if not present. The supplied proxy name will be assigned to the query
param. Override this method by passing a function as the
"format" property in the config object to the constructor.
- Parameters:
-
url
< String >
the original url
-
proxy
<String>
the function name that will be used as a proxy to
the configured callback methods.
- Returns:
String
- fully qualified JSONP url
protected
void
_init
(
url
,
callback
)
Set up the success and failure handlers and the regex pattern used
to insert the temporary callback name in the url.
- Parameters:
-
url
<String>
the url of the JSONP service
-
callback
<Object|Function>
Optional success callback or config
object containing success and failure functions and
the url regex.
void
send
(
args*
)
Issues the JSONP request.
- Parameters:
-
args*
<any>
any additional arguments to pass to the url formatter
beyond the base url and the proxy function name
Chainable: This method is chainable.
static
JSONPRequest
Y.jsonp
(
url
,
c
,
args*
)
- Parameters:
-
url
<String} the url of the JSONP service with the {callback>
placeholder where the callback function name typically goes.
-
c
<Function|Object>
Callback function accepting the JSON payload
as its argument, or a configuration object (see above).
-
args*
<any>
additional arguments to pass to send()


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For many years, bodybuilders were considered the standard of beauty, they were taken to the cinema for the main roles, they advertised clothes and were removed for the covers of magazines. The whole world wanted to have the figure of a professional bodybuilder, since this form is associated with people with a good standard of living. Unfortunately, in recent years, more and more famous athletes, including Russian bodybuilders, whose sudden death, has led to a series of questions asked by ordinary people across the country, are leaving life. The main question that worries others: "How safe is bodybuilding in fact, whether it creates a figure, or simply destroys health."
Observing from the side, ordinary people have the impression that bodybuilding is primarily based on good health and a good lifestyle. After all, athletes regularly train, observe the daily regimen, try not to drink alcohol or smoke. And more importantly, they eat a balanced diet, and even carry food in containers. All this looks impressive, it is immediately clear that a beautiful figure requires large financial and time investments, without which it would be impossible to create a bodybuilder form. But this is only the tip of the iceberg, something that can be seen from the side. What actually happens inside the body of athletes, why they are forced to take tests on a regular basis and undergo examinations by doctors, why in recent years many have died for unknown reasons.
Despite the fact that bodybuilders outwardly look more than healthy, inside they are not so fabulous as it might seem at first glance.
- CNS overload.
Under the influence of regular physical exertion, the nervous system gradually wears out, then it comes to the aid of various additives and stimulants that squeeze out the last juices, forcing the body to work in emergency mode. Working on the edge, you can hold out for a long time, a month, a year, two, five, but sooner or later the body will say “stop”, and the time will come to rest, not just reduce the load in the gym, but completely abandon training for an indefinite period so that the body can fully recover after a long and systematic destruction.
- Loading on the digestive tract.
Diet is good, but when an athlete over several years consumes huge amounts of food, while regularly increasing the volume of BJU eaten, to stimulate muscle growth, one way or another it will affect the state of the gastrointestinal tract.


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public abstract class Accuracy extends DefaultMetric
DefaultMetric
class are TimeMetric
class and Accuracy
class.
TimeMetric
measures the speed of algorithm and so it is the time in seconds that methods Recommender.estimate(net.hudup.core.alg.RecommendParam, Set)
and Recommender.recommend(net.hudup.core.alg.RecommendParam, int)
execute over Dataset
.
Accuracy
reflects goodness and efficiency of recommendation algorithms. There are three types of accuracy.
PredictiveAccuracy
class, measures how close predicted ratings returned from methods Recommender.estimate(net.hudup.core.alg.RecommendParam, Set)
and Recommender.recommend(net.hudup.core.alg.RecommendParam, int)
are to the true user ratings.
PredictiveAccuracy
class derives directly from Accuracy
class. MAE
, MSE
, RMSE
are typical predictive accuracy metrics.
ClassificationAccuracy
class, measures the frequency that methods Recommender.estimate(net.hudup.core.alg.RecommendParam, Set)
and Recommender.recommend(net.hudup.core.alg.RecommendParam, int)
make correct or incorrect recommendation.
ClassificationAccuracy
class derives directly from Accuracy
class. Precision
and Recall
are typical classification accuracy metrics.
CorrelationAccuracy
class, measures the ability that method Recommender.recommend(net.hudup.core.alg.RecommendParam, int)
makes the ordering of recommended items which is similar to the ordering of user's favorite items.
CorrelationAccuracy
class derives directly from Accuracy
class. NDPM
, Spearman
, Pearson
are typical correlation accuracy metrics.
accumValue, currentValue
config
| Constructor and Description |
|---|
Accuracy()
Default constructor.
|
| Modifier and Type | Method and Description |
|---|---|
protected MetricValue |
calc(RatingVector recommended,
Dataset testing)
Calculating metric value at an iteration.
|
protected abstract MetricValue |
calc(RatingVector recommended,
RatingVector vTesting,
Dataset testing)
Calculating metric value at a iteration of algorithm execution.
|
protected static int |
countForRelevant(RatingVector vRating,
boolean relevant,
Dataset testing)
Counting relevant (irrelevant) ratings from the specified rating vector.
|
protected static RatingVector |
extractRelevant(RatingVector vRating,
boolean relevant,
Dataset testing)
Extracting relevant (irrelevant) ratings from the specified rating vector.
|
protected static boolean |
isRelevant(float rating,
Dataset testing)
Testing whether the specified rating value is relevant.
|
protected static RatingVector |
pruneUnrated(RatingVector recommended,
Dataset testing)
This method prunes the specified recommended vector by removing items from this vector if such items are not rated in the specified testing dataset.
|
boolean |
recalc(java.lang.Object... params)
This is the most important method expressing how to re-calculate a concrete
metric according to specified parameters. |
getAccumValue, getCurrentValue, isValid, recalc0, reset
createDefaultConfig, getConfig, resetConfig, setup
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getDesc, getTypeName
getName, newInstance
public boolean recalc(java.lang.Object... params) throws java.lang.Exception
Metric
metric
according to specified parameters.params
- specified array of objects known as parameters. Such parameters varied according to concrete metric.java.lang.Exception
- if any error raises.protected MetricValue calc(RatingVector recommended, Dataset testing)
recommended
- recommended list of items.testing
- testing dataset.MetricValue
at an iteration.protected abstract MetricValue calc(RatingVector recommended, RatingVector vTesting, Dataset testing)
Accuracy
must define it.recommended
- list of recommended items known as recommended rating vector which is produced by recommendation process.vTesting
- the testing rating vector which is used to compare with recommended rating vector.testing
- testing dataset where the testing rating vector is extracted.MetricValue
at a iteration of algorithm execution.protected static boolean isRelevant(float rating, Dataset testing)
{@link DataConfig#getMaxRating()} - {@link DataConfig#getMinRating()}
.
Such DataConfig
is configuration of the specified testing dataset.rating
- specified rating value.testing
- specified testing dataset whose maximum rating value and minium rating value are used to calculate the rating average.true
if specified rating value is relevant. Otherwise, specified rating value is irrelevant.protected static RatingVector extractRelevant(RatingVector vRating, boolean relevant, Dataset testing)
isRelevant(float, Dataset)
method to test whether a rating value is relevant.vRating
- specified rating vector from which relevant (irrelevant) ratings are extracted.relevant
- if true
, the result is vector of relevant ratings. Otherwise, the result is a vector of irrelevant ratings.testing
- specified testing dataset whose maximum rating value and minium rating value are used to calculate the rating average for relevant testing in method isRelevant(float, Dataset)
.protected static int countForRelevant(RatingVector vRating, boolean relevant, Dataset testing)
isRelevant(float, Dataset)
method to test whether a rating value is relevant.vRating
- specified rating vector from which relevant (irrelevant) ratings are counted.relevant
- if true
, the result is the count of relevant ratings. Otherwise, the result is the count of irrelevant ratings.testing
- specified testing dataset whose maximum rating value and minium rating value are used to calculate the rating average for relevant testing in method isRelevant(float, Dataset)
.protected static RatingVector pruneUnrated(RatingVector recommended, Dataset testing)
recommended
- specified recommended vector of ratings.testing
- specified testing dataset.


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