Water.css is a just-add-css collection of styles to make simple websites like this just a little bit nicer. Get it already!
Now you can write your simple static site with nice semantic html, and Water.css will manage the styling for you.
Heck yeah! It doesn't include any fancy styles so it's easily mobile responsive. Just add the famous responsive viewport tag and you'll be good to go!
In fact, try resizing this page. Everything flows super nicely as you'll see.
This is supposed to be a demo page so we need more elements!
Below I'm gonna put an <hr>
, because why not?


Nana Ampomah, Tekpetey on target as Fortuna Dusseldorf defeat SV Meppen in friendly
Ghanaian duo Bernard Tekpetey and Nana Ampomah scored for Fortuna Dusseldorf in their 3-2 win over SV Meppen in a friendly match.
The exciting winger was named on the starting eleven of his club alongside compatriots Kevin Ofori and Bernard Tekpetey.
Following a good start to the game, Nana Ampomah shot Dusseldorf into the lead on the 22nd minute. Just over 10 minutes later, Barkok added to the goals of the German Bundesliga side to hand them a two-goal cushion.
Two minutes after the equalizer Komenda was on target to half the deficit for SV Meppen.
Leugers restored parity for the lower division side on the 49th minute after they were awarded a penalty kick by referee Braun Wuppertal.
Ghanaian winger Bernard Tekpetey who is on loan from Schalke 04 popped up on the 70th minute and scored to seal the victory for Fortuna Dusseldorf.
Kevin Ofori lasted 62 minutes of the game with Nana Ampomah and Bernard Tekpetey enjoying the entire duration of the game.


Color Filter:
{{color}}
New Color:
Add Color
{{car.make}} - {{car.model}} - {{car.year}}
Show Me
You can see me!


--- layout: page title: "About" description: "Who I am:" header-img: "img/about.jpg" ---
I am a physics researcher turned aspring data scientist. I love seeking patterns in numbers, and always have questions I need to answer.
If you'd like to know more about me, feel free to visit my other website at emilyraybrown.com.


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{% extends "base.html"%} {%block body%}
This shows the number of requests (e.g., Configuration Change, Resources Generation) that are in the queue, waiting to be processed. Requests which are under processes are not shown here
The number of worker processes responsible to handle 'consume' the requests in the queue
{{error}}


This tests the display of datagrids in various containers (2-column layout, tabs, expandable areas, etc.)


ExtensionType
enum ExtensionType : String
Constants indicating a filename’s extension.
Only a few common filename extensions are defined here. Over time, as the number of uunique use cases grows, it is expected that more filename extensions will be defined here.
-
An audio type.
Declaration
Swift
case aif
-
Declaration
Swift
case caf
-
Declaration
Swift
case wav
-
A data types.
Declaration
Swift
case json
-
Declaration
Swift
case plist
-
Declaration
Swift
case sqlite
-
An image types.
Declaration
Swift
case pdf
-
Declaration
Swift
case png
-
The default type.
Declaration
Swift
case none = ""


FISAT CANTEEN
Snacks
Samosa:  Rs.10
A
samosa
is a fried or baked pastry with a savoury filling ,such as spiced potatoes,onions lentils.
Meat rolls :  Rs.10
Meat
roll is a basic bread stuffed with cooked minced meat stew.


[shareButton]
is a directive that converts its element to a share button.
Install the following packages
NPM
$ npm install --save @ngx-share/core @fortawesome/fontawesome-free-webfonts
YARN
$ yarn add @ngx-share/core @fortawesome/fontawesome-free-webfonts
Import FontAwesome for the icons "app/src/style.scss"
@import<EMAIL_ADDRESS>@import<EMAIL_ADDRESS>@import<EMAIL_ADDRESS>The most basic share button needs only the name of the social network. e.g: shareButton="twitter"
You can get the official colors and icons by injecting ShareButtons service in your component


Welcome! In this first module, you will learn how to add and subtract fractions with like denominators. Navigate through the module by clicking through the links. Once you have visited each link (even the references!), a quiz will be available for you to test your knowledge.
Navigation
--> 1- Title2 - Objectives
3 - Video Example
4 - Video-How to Do It
5 - Concrete Model Activity
6 - Adding Fractions
7 - Subtracting Fractions
8 - Simplifying
9 - References
10 - Quiz
11 - Certificate
Audio


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iLogo Development Notes
15 Sep 2013


--- layout: post title: Founding of Restore the Fourth SF categories: - Blog tags: - Organization News status: publish type: post published: true meta: _edit_last: '3' pexeto_video: '' _yoast_wpseo_linkdex: '0' author: login: Alice email<EMAIL_ADDRESS>display_name: Alice first_name: Alice last_name: '' ---
Restore the Fourth SF was founded by no99sum, Ryan, Sam, Alice, Ted and Nick on this day.


this is supposed to be cantell-smith’s magnum opus; it aims at defining what computing is: meaning mechanically realized
computers can’t be proved/assumed to be machines, because their terminology comes from logic/textual/discursive traditions (e.g. reference, statement, names, recursion, etc.) yet they are still built.
how do those two traditions (logical & mechanical) interact? what is the result of their interaction (-> computability)
meaning mechanically realized, due to the fact that the machine comes from non-mechanical origins. we think of computers as digital but they’re actually only digitally implemented.
the semantics (logical, aboutness) (non-local) cannot be reduced to syntactics (local)
are both semantic attribute/qualities.
the scale of complexity:
so the computer is actually standing in the grey zone between the physical and the conceptual. it is somewhat intelligent.
practice is synthetic method, a method which regroups, which puts together.
software can have, amongst other attributes, participatory, connectedness.
how about metaphors? is there such a thing as a computational metaphor, a sort of written, producedural rhetoric? perhaps something along the lines of snippets, message-passing, concurrency, class separation. however metaphors require a common ground, which there is not in software development (lack of canon, lack of reading code, etc.)
computation is something else, but it’s something else that the programmers and computer scientists have always felt.


Solving the Multi-Agent Path Finding (MAPF) problem optimally is known to be NP-Hard for both make-span and total arrival time minimization. While many algorithms have been developed to solve MAPF problems, there is no dominating optimal MAPF algorithm that works well in all types of problems and no standard guidelines for when to use which algorithm. In this work, we build deep learning network which takes a MAPF problem instance and attempts to select the fastest algorithm to use from a portfolio of algorithms.
We improve the performance of our model by including single-agent shortest paths in the instance embedding given to our model and by utilizing supplemental loss functions in addition to a classification loss. We evaluate our model on a large and diverse dataset of MAPF instances, showing that it outperforms all individual algorithms in its portfolio as well as the state-of-the-art optimal MAPF algorithm selector. We also provide an analysis of algorithm behavior in our dataset to gain a deeper understanding of optimal MAPF algorithms' strengths and weaknesses to help other researchers leverage different heuristics in algorithm designs.


Our Services
Headshots
Quality and professional photo sessions and editing.
Weddings
Organized and quick service when dealing with the client.
Fashion
Customers are greated with exceptional customer service, by directing them to the studio and taking their attire.


You can send or receive coins, check the balance and see the transaction history for:
Ethereum and ERC20 tokens in the app are only supported for the BitBox02 Multi edition. If you want to use them with the BitBox01, you have to use the external website www.myetherwallet.com.
Get addresses to receive coins.
In case of the BitBox02, you can verify the address on your device. In case of BitBox01, we recommend that you use the mobile app to verify that the displayed address is correct.
Create a transaction to spend your coins.
Confirm the transaction with the touch sliders on your device.
Hold the touch button to approve the transaction.
We recommend that you use the mobile app to verify that the transaction details are correct.
Manage your app settings here: Select which fiat currencies are relevant to you and which accounts you want to use, enable coin control or connect your own full node.
Manage backups, change the device name, show the BIP39 mnemonic, enable the optional BIP39 passphrase or reset the device.
Manage backups, change the device password, create a hidden wallet, pair with the mobile app, enable 2FA or reset the device.


Down/up samples the input to either the given size
or the given
scale_factor
nnf_interpolate( input, size = NULL, scale_factor = NULL, mode = "nearest", align_corners = FALSE, recompute_scale_factor = NULL )
| input | (Tensor) the input tensor |
|---|---|
| size | (int or |
| scale_factor | (float or |
| mode | (str) algorithm used for upsampling: 'nearest' | 'linear' | 'bilinear' | 'bicubic' | 'trilinear' | 'area' Default: 'nearest' |
| align_corners | (bool, optional) Geometrically, we consider the pixels
of the input and output as squares rather than points. If set to TRUE,
the input and output tensors are aligned by the center points of their corner
pixels, preserving the values at the corner pixels. If set to False, the
input and output tensors are aligned by the corner points of their corner pixels,
and the interpolation uses edge value padding for out-of-boundary values,
making this operation independent of input size when |
| recompute_scale_factor | (bool, optional) recompute the scale_factor
for use in the interpolation calculation. When |
The algorithm used for interpolation is determined by mode
.
Currently temporal, spatial and volumetric sampling are supported, i.e. expected inputs are 3-D, 4-D or 5-D in shape.
The input dimensions are interpreted in the form:
mini-batch x channels x [optional depth] x [optional height] x width
.
The modes available for resizing are: nearest
, linear
(3D-only),
bilinear
, bicubic
(4D-only), trilinear
(5D-only), area


| # | Patient Full Name | Email Address | Cellphone | Appointment Date | Description | Actions |
|---|---|---|---|---|---|---|
| {{item.AppointmentId}} | {{item.FirstName}} {{item.Surname}} | {{item.Email}} | {{item.Cellphone}} | Date: {{item.StartDate}} From: {{item.FromTime}} To: {{item.ToTime}} | {{item.Description}} | Edit |


Report Incidents
Click Add incident button
Click on the map to create the incident
Or
Select an incident to edit or delete.
Enter the incident information
Description:
Contact:
Prominent Peaks in the U.S.
Elevation
Prominence
is greater than
is less than
is equal to
1,000 ft
5,000 ft
10,000 ft
15,000 ft
20,000 ft
Prominence
Do Query
Use FindTask on a Map Service to view population change statistics by county name.
Find by County Name:


The XHTML Component class is used to represent an XHTML Node within the Hemi Framework as a registered object. This class also coordinates the XHTML Node with referenced Application Components, Modules, Templates, Distributed Application Components, and Virtual Forms, and is used with Application Spaces as an Application Space Definition.
Factory for creating XHTMLComponentInstance objects, which represent a XHTML objects (HTML nodes) within the framework.
Demonstrate how an XHTMLInstanceObject is created from an HTML Node. Also refer to Application Components, which connect an XHTMLInstanceObject to pre-defined code blocks.

Some node

Creates and returns a new XHTMLComponentInstance instance.
c = newInstance( hp, xp, cid, rid, cc, cn, cp, cf )
c as XHTMLComponentInstance: Returns a new XHTMLComponentInstance.
An object representing a XHTML object (HTML node) to the framework.
Unique instance identifier.
String = object.object_id
The type of this object.
String = object.object_type
Version of the object class.
String = object.object_version
A hash of object values for storing named object references.
object = object.objects
A hash of primitive values (strings, ints, etc) for storing configuration, settings, and status.
object = object.properties
Object load and execution state. Follows: 0 unitialized, 1 through 3 variant, 4 ready, 5 destroyed.
int = object.ready_state
Clears internal pointers and data, preparing the object for destruction.
void destroy( )
Returns any underlying ApplicationComponent object. For example, if a component name, component path, and component config name were specified when the instance was created, then the corresponding ApplicationComponent would be returned.
i = getApplicationComponent( )
i as ApplicationComponent: Returns any underlying ApplicationComponent object.
Returns any component collection that was included when the object was created.
c = getComponentCollection( )
c as object: Component collection (eg: XHTMLFormComponent).
Returns the component id. The component id is used as a friendly name reference to Engine objects and Component Collections such as XHTMLFormComponent.
i = getComponentId( )
i as String: Returns the component id which was specified when the XHTMLComponent was created.
Returns the reference id. For example, the reference id could be an Engine object for which the XHTMLComponent was created.
i = getComponentId( )
i as String: Returns the reference id which was specified when the XHTMLComponent was created.
Returns the component container object. For example, if a component was created from an XHTML import
 then the HTML version of that node is the container.
o = getContainer( )
o as object: The XHTML/HTML object created based on the specified values when the instance was created.
Returns a bit indicating whether the object is linked.
i = getIsComponentLinked( )
i as bit: Bit indicating whether the object is linked with a component collection (eg: to XHTMLFormComponent).
Returns the unique id of the object.
i = getObjectId( )
i as String: The unique object instance id.
Returns the type of the object.
t = getObjectType( )
t as String: The type of the object instance.
Returns the version of the object.
v = getObjectVersion( )
v as String: The version of the object instance.
Returns the state of the object.
s = getReadyState( )
s as int: The object ready state.
Initializes the instance of this object.
void init_component( )
Post initializes the object to add it to a component collection. This is invoked internally when using the EngineService for a specific Engine object.
void post_init( )
Sends a termination signal to this object, causing it to be destroyed.
void sigterm( )
[ Hemi JavaScript Framework - Stephen W. Cote, 2002 - 2013. ]


Check that you have node.js and Angular CLI installed. Input in your console:
node -v
If the command is recognized and you got node.js version go to the next step. If not, visit page: nodejs.org and install node.js (download proper version for your OS).
Check that you have node.js and Angular CLI installed. Input in your console:
ng version
Verify that you got following view (check if CLI version is not lower than 6)
If you need update Angular or install the newest version, use this command:
npm install -g @angular/cli


My journey in becoming a full-stack software engineer started with a little question of "What if...." The tradition in my family has been to pursue a career in medicine and as a college student I was prepared to follow in those footsteps. Also during this time period I discovered a few online coding programs and as I was working through the tutorials I was surprised to find that I really enjoyed it. I began to ask myself, "What if I decided to pursue computer programming?" It was a choice between following the familiarity of the well-worn path and diving head-first into the adventure of my growing interest. I decided to take that leap and I am so glad that I did. After completing an immersive software development program, I am looking for more opportunities to grow in this exciting field.
I had the pleasure of partnering with Ivy Kaminsky, entrepreneur and founder of Find Your Power, to build this web application along with three other teammates. This application provides a space where entrepreneurs and businesswomen can connect with each other to share skills and resources in order to help their careers flourish.
Click to view Find Your Power networking websiteI designed and created this application as a way to effectively manage relevant information pertaining to each child's needs so that babysitters can stay organized, provide quality care, and update parents with a personalized summary of how their child's day went.
Click to view Babysitter CentralWhen I am not coding, I enjoy sitting down with a good novel and a mug of hot chocolate. I also like trying new craft activities such as candle-making, watercolor painting, crocheting, and DIY decor. In the summertime I have been growing to appreciate outdoor activities through learning how to fish (I caught my first bass at Chisago Lake!) and exploring Minnesota's hiking trails with my friends.


How to download the Mixed Reality Toolkit
The XRTK provides many ways for users and developers to get access to the XRTK and the various extensions/platforms it provides. These methods are tuned to use the common patterns most familiar to Unity developers, these include:
Automatic UPM Install - Provides the core package only, using UPM (Unity Package management) to deliver other modules
Manual UPM install - Don't download anything, simply register the core XRTK project in your unity solution and let Unity download it for you
Offline Downloadable asset (tbc) - Provides the entire XRTK in an asset for use in offline scenarios
GIT Submodules - For advanced developers, simply clone the project into your solution and update its submodules to get access to all platforms.
In this article, we will walk through each approach to get you up and running, starting with the simplest first.
Automatic UPM Install
Out preferred deployment approach is to fully utilize Unity's native package management solution to incorporate the XRTK in your solution, akin to the other modules Unity provides out of the box. This is the best / quickest and safest way to get XRTK in your solution and automatically updated.
Just download the XRTK-Core.unitypackage asset and import it into your project to start building solutions straight away. This adds an XRTK seed, which automatically registers the XRTK with the Unity package manager and starts its download and installation.
For more instructions for how to get started, click here
Manual UPM Install
If you prefer to do things yourself, you can simply edit the manifest.json file in your Unity project and add an entry to register the XRTK and begin the download and installation into your project.
For more details, check the XRTK UPM instructions here
Offline Asset
(Coming Soon)
We will provide a full bulk asset containing all of the XRTK components and platforms. This will include the XRTK, the XRTK SDK and all current platforms. Examples will also be available as a separate asset too.
Once downloaded, you can delete any parts of the project you do not intend to use but updating and maintaining the XRTK will be your own responsibility.
GitHub submodule
(advanced users)
Advanced developers and those wishing to contribute to the XRTK also have the option to clone the XRTK repository into their project in a few ways.
You can either:
Clone the development XRTK repository into a folder and start building your project from there. The submodules are already linked to this branch (in the Submodules folder) and you can download them by simply "Initializing Submodules" in the main XRTK-Core folder.
Clone the default (UPM) branch in to a live project as a Submodule in your source, adding the additional extension submodules as required. However, we recommend you use the development branch to avoid breaking the symbolic links when switching between branches.
FYI
When building against development, the XRTK project and it's submodules will appear as "Packages" in Unity, not in the Assets folder. Just expand the "Packages" tree in the Unity project window to see / debug and edit them. These are read-only to normal users.
If there is anything not mentioned in this document or you simply want to know more, raise an RFI (Request for Information) request here.


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---
layout: post
title: Creating a simple professional online brand
tags:
- LinkedIn
- Personal Opinion
- Work Practices
status: publish
type: post
published: true
meta:
_edit_last: '451289'
_wp_old_slug: creating-a-simple-professional-online-brand
---
There are many working people, particularly in my generation or older, who resolutely refuse to create or effectively maintain an online brand or image. In my experience they this it for a variety of reasons:
- It has no value
- It's too hard
- It exposes too much that should be private
I'll address these very valid concerns and then suggest simple ways to create an online brand. Before I start let me state that I am no a Social Media Guru, I just have an interest in these tools and have been using them for some time.
No value
It is easy to find people that claim the creation of an 'effective online brand' is the way to easy street and personal fulfilment. I take this with a large pinch of salt and have no doubt that most of these people are still working their day job.
However was is clear is that we are living much more of our professional and personal lives online. Recruiters, customers and the other people we want to involve in our professional lives are turning to tools like Google and LinkedIn. If we are not part of the online community in some fashion then it becomes harder for people to discover and locate us.
As well as the Internet providing a "directory" service, it also allows us to actively showcase our skills to improve our competitive edge when looking for the next position. By publishing our own material on the public Internet we are displaying a variety of desirable traits:
- We really do have the skills and knowledge we claim because we write about them
- We can work well in a team because we understand the value of sharing
- We are keeping up to date with the modern world
- We are keeping our skills updated by learning new things and writing about them
It must also be said that practising writing for the public is a professionally useful activity in its own right.
Too Hard
It is true you can spend a lot of time on this activity -- however it is possible to invest less than five hours a month plus the initial set up time. There are only a few things you need to do to be up an running.
 The approach is suggest here does not include a twitter account for instance, so you won't be tempted to tell the world about your breakfast.
Approach
- Get a blog, like this one (Wordpress and Blogger are two popular free services). Aim to publish at least once a month (twice a month is better) on topics related in some fashion to your professional interests. There are more tips on blog writing at http://www.problogger.net/archives/2006/02/14/blogging-for-beginners-2/ and many other places, however be selective about the advice you follow. Your blog posts can cover topics about: your current work; new products related to your interests; considered commentaries on news and other blogs; and your new discoveries and learning.
- Create a slideshare account and publish your presentations and papers (make sure you have permission to publish material that may belong to your customers). When you publish on slideshare make sure write a corresponding blog post (e.g. http://alecthegeek.wordpress.com/2006/12/08/slides-and-example-scripts/)
- Get a LinkedIn account and make sure your profile is complete and up to date. My objective when creating my profile was to have something that could be printed off and used as a CV
- Add the URLs of your LinkedIn account and blog to your business card and email signature
- Update your LinkedIn status when you are doing something new (professionally) or publish a new blog entry
- When you meet people professionally try and connect with them on LinkedIn straight away
This online brand needs however to be part of a larger activity. You should network actively (get used to drinking a lot of coffee!) and seek opportunities to present at local groups. If there are larger conferences then make sure you submit a paper proposal as well -- it's all grist to the mill.


Yelp-like Web Application
JavaScript, Node.js, Express, AngularJS, MongoDB
- Initialized a web application where allows users to register and login personal profile, add, delete or edit images and comments with Node.JS, Express and MongoDB; refactored to a RESTful route.
- Implemented modular, maintainable Single Page Applications and apply AJAX with AngularJS.
- Designed and developed fronted with HTML, Bootstrap, and JS; made UI improvement and notification with npm Connect-flash and Angular animation events.
- Authenticated users with Passport.JS and Passport-local; Implemented HTML5 Local Storage for users’ favorite items.
- Tested the web app with unit tests (Postman), and deployed the web app to Heroku.
April 2020 – June 2020
Instagram App Clone
JavaScript, Node.js, Express, React, MySQL
- Built an Instagram clone allows users to register, post, comment, like, tag and follow, with Node.js, Express backend, React frontend and MySQL for the database; refactored to RESTful route.
- Designed fronted UI with React, Redux, React-Router and Bootstrap for app pages.
- Created a database using MySQL with designed many-to-many data schema to store data for user activities.
- Tested the app and database with unit test using over 8000 mock Instagram user data, and deployed the app to Heroku.
February 2020 – May 2020
Login System App
Python, MySQL, kivy, pygame
- Created a mobile compatible app of Login system for users to register, login and logout with Python, pygame and kivy.
- Developed a GUI to switch between 3 windows: login, register and account information.
- Established a connection to MySQL with the Python SQL module to save, load and validate account information.
- Deployed the FloatLayout in kivy for the dynamic placement of the objects for mobile compatible GUI.
September 2019 – October 2019
DevOps Server Monitoring Project
AWS EC2, Prometheus, Grafana, Docker
- Built a server to monitor and diagnose problems for CPU, memory, disk usage, and network traffic of other 2 instances with Prometheus, node-exporter, Grafana, pushgateway and alerting with AlertManager.
- Launched 3 AWS EC2 Linux2 instances where 1 acted as monitor server and the other 2 as monitored instances.
- Utilized Docker and Docker Compose to implement 6 monitoring tools in containers and connect all with bridge network.
- Designed and configured 3 Grafana dashboards to collect and display metrics from monitored instances.
- Simulated high CPU, memory, disk usage and network traffics to stress test the systems with stress-ng.
July 2020 – September 2020


A PDO is equivalent to a frame. It is a container for one or multiple data points. In CANOpen, you get four PDO frames for reading (TPDOs) and four PDO frames for writing (RPDOs) per device node by default.
To edit a PDO frame, right-click the PDO Channel and select Edit PDO from the shortcut menu. This will pop up a dialog box that will allow the user to configure the PDO frame, including how to convert the data to engineering units.


To view this video please enable JavaScript, and consider upgrading to a web browser that supports HTML5 video


Mitigate insecure cryptographic storage vulnerabilities.
Common vulnerability types should be mitigated to prevent successful attacks that exploit these vulnerability types.


Magnum Funds 25 Maiden Lane Covent Garden London WC2E 7JS Hello, Do accept my sincere apologies if my mail does not meet your personal ethics. I will introduce myself as Mr.Robbin Kuuk, a staff in the accounts management section of the above firm here in the United Kingdom. One of our accounts with holding balance of £15,000,000(Fifteen Million British Pounds) has been dormant and has not been operated for the past four (4) years. >From my investigations and confirmations, the owner of this account, a foreigner by name Kurt Kahle died in July, 2000 and since then nobody has done anything as regards the claiming of this money because he has no family members who are aware of the existence of neither the account nor the funds. I have secretly discussed this matter with a senior official of this company and we have agreed to find a reliable foreign partner to deal with. We thus propose to do business with you, standing in as the next of kin of these funds from the deceased and funds released to you after due processes have been followed. This transaction is totally free of risk and troubles as the fund is legitimate and does not originate from drug, money laundry, terrorism or any other illegal act. On receipt of your response I will furnish you with detailed clarification as it relates to this mutual benefit transaction. I look forward to hearing from you as soon as possible if you are interested. Regards, Mr.Robbin Kuuk


QIIME 2 overview¶
QIIME 2 is a complete redesign and rewrite of the QIIME 1 microbiome analysis pipeline. QIIME 2 will address many of the limitations of QIIME 1, while retaining the features that makes QIIME 1 a powerful and widely-used analysis pipeline. See the key concepts page for details on how QIIME 2 addresses many of the limitations of QIIME 1.
QIIME 2 is ready for experimental use while in its alpha release stage. It currently supports an initial end-to-end microbiome analysis pipeline. Because our microbiome analysis functionality is currently very new, QIIME 2 is not yet recommended as a replacement for QIIME 1, but we are very interested in having users test QIIME 2 and give us feedback. Until the QIIME 2 microbiome analysis functionality has expanded, we recommend that you continue to use QIIME 1 and Qiita for your microbiome analyses, as these will provide you with complete analysis solutions supporting high-performance computing environments.
New functionality will regularly become available through QIIME 2 plugins. You can view a list of plugins, including those that are currently available, in development, or being planned, on the QIIME 2 plugins page.
To see where we’re headed with QIIME 2, take a look at Greg Caporaso’s American Gut blog post (15 April 2016) and SciPy 2016 presentation (15 July 2016).
Getting started¶
QIIME 2 introduces several new concepts that are not present in QIIME 1, and these concepts are important to understand as they are central to how you will interact with QIIME 2 to perform microbiome analyses. It is highly recommended to start with the key concepts documentation before moving on to installing and using QIIME 2.
To begin using QIIME 2, start with the installation guide, which will show you how to install the QIIME 2 framework, a command-line interface, and some plugins used in the tutorials.
Requesting features, reporting bugs, providing feedback¶
If there is specific functionality you’d like to see in QIIME 2, you notice a bug, or want to leave feedback, please post to the QIIME 2 issue tracker. We appreciate all feedback as we strive to make QIIME 2 a useful and accessible tool for microbiome analyses.
Extending QIIME 2 through plugins and interfaces¶
A key design goal of QIIME 2 is to enable third-party developers to create plugins and interfaces for QIIME 2 in order to extend its functionality available to users.
Plugins provide a way for microbiome bioinformatics developers to make their tools accessible to end users in their QIIME deployment. A plugin enables access to its functionality through any of QIIME’s interfaces. If you’re interested in developing a QIIME 2 plugin, you should begin with Creating a QIIME 2 plugin. You should also refer to the QIIME 2 plugins page to see what plugins already exist or are being developed.
QIIME 2 provides a software development kit (SDK) accessible from the qiime.sdk
package. The SDK provides a way for software engineers to build custom interfaces around QIIME, which can include embedding QIIME as a component in other systems (e.g., cloud-based bioinformatics platforms). We have not yet developed our SDK/interface developer documentation, but two examples of QIIME 2 interfaces are currently available: q2cli and QIIME 2 Studio. We will have detailed SDK/interface developer documentation available soon.
While QIIME 2 is in its alpha release stage, backward incompatible interface changes that impact plugins and interfaces can and will occur. We will make every effort to minimize these, and we will make every effort to let developers know through the #developers
Slack channel and help developers update their plugins to match the latest API. We will have a better way of notifying developers of these changes in the future. See below for details on joining the QIIME 2 Slack team.
Slack team¶
The QIIME 2 developers use Slack for instant message discussion of development topics. If you’re working on plugin or interface development and need help, you should join our Slack team and then get in touch on the #developers
channel at https://qiime2.slack.com. This will be more reliable than emailing one of the developers directly.


Contents
Assemblies
Sasa.Arrow Assembly
Sasa.Arrow Namespace
Arrow Class
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Arrow<T, R> Class
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Sasa.Contracts Assembly
System.Diagnostics.Contracts Namespace
Contract Class
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Contract.AssertException Class
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Contract.AssumeException Class
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Contract.EnsuresException Class
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Contract.InvariantException Class
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Contract.RequiresException Class
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ContractInvariantMethodAttribute Class
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PureAttribute Class
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RuntimeContractsAttribute Class
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Sasa.Core Assembly
Sasa.IO Namespace
FsPath Class
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PortableReader Class
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PortableWriter Class
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Streams Class
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Sasa Namespace
Future Class
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Future<T> Class
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IFuture<TFuture, T> Interface
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IPromise<TFuture, TResolved, T> Interface
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Promise<T> Class
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PromiseResolvedException Class
Resolved<T> Class
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Sasa Assembly
Sasa Namespace
Atomics Class
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CodeGen Class
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Decimals Class
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Doubles Class
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Either<TFirst, TSecond, TThird, TFourth> Class
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Either<TFirst, TSecond, TThird> Class
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Either<TFirst, TSecond> Class
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Empty Class
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Endian Class
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Events Class
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ImmutableValue<T> Class
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Integers Class
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IOptional<T> Interface
IRef<T> Interface
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IResolvable<T> Interface
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IValue<T> Interface
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IVolatile<T> Interface
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Lazy Class
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Lazy<T> Class
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MetaExtensions Class
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NonNull<T> Class
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Null Class
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Option Class
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Option<T> Class
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Pair<T0, T1> Class
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Quad<T0, T1, T2, T3> Class
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Ref<T> Class
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Singles Class
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Triple<T0, T1, T2> Class
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Tuple Class
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TypeConstraint<T, TBase> Class
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TypeConstraint<T> Class
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Types Class
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Union128 Class
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Union16 Class
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Union32 Class
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Union64 Class
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Weak<T> Class
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Sasa.Collections Namespace
Arrays Class
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Dictionaries Class
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Env<K, V> Class
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ISeq<TCollection, TItem> Interface
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PQueue Class
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PQueue<T> Class
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Seq<T> Class
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Set Class
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Set<T> Class
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Sasa.String Namespace
Strings Class
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Strings.Token Class
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Sasa.Web Namespace
Url64 Class
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Sasa.Linq Namespace
Enumerables Class
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Zips Class
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Sasa.Func Namespace
Func Class
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Sasa.Enum Namespace
Enums Class
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Sasa.Dynamics Assembly
Sasa.Dynamics Namespace
DynamicType Class
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IReflected Interface
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IReflector Interface
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Methods<K> Class
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Type<T> Class
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Types<K> Class
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Sasa.Linq Assembly
Sasa.Linq Namespace
ErrorVisitor<T> Class
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ExpressionVisitor<T> Class
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IdentityVisitor Class
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Queryable<T> Class
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QueryProvider Class
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Sasa.Mime Assembly
Sasa.Mime Namespace
FileExtensions Class
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FileExtensions.Application Class
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FileExtensions.Image Class
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FileExtensions.Message Class
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FileExtensions.Multipart Class
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FileExtensions.Text Class
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MediaTypes Class
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MediaTypes.Application Class
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MediaTypes.Image Class
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MediaTypes.Message Class
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MediaTypes.Multipart Class
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MediaTypes.Text Class
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Sasa.Net Assembly
Sasa.Net.Mail Namespace
Message Class
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Mime Class
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QuotedPrintable Class
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Sasa.Net.Pop3 Namespace
Pop3Client Class
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Pop3Header Class
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Pop3Session Class
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Sasa.Rfc Namespace
Rfc822 Class
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Sasa.Net Namespace
InvalidResponseException Class
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Texty Class
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Sasa.Operators Assembly
Sasa.Operators Namespace
Arithmetic<T> Class
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Logical<T> Class
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Sasa.Parsing Assembly
Sasa.Parsing.Pratt Namespace
Grammar<T> Class
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PrattParser<T> Class
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Scanner Delegate
Symbol<T> Class
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Token<T> Class
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Sasa.Parsing Namespace
ParseException Class
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Sasa.Serialization Assembly
Sasa.Serialization.Unsafe Namespace
IUnsafeSerializable Interface
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IUnsafeSerializer Interface
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Sasa.Serialization.Unsafe.Binary Namespace
BinaryDeserializer Class
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BinarySerializer Class
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Sasa.Serialization Namespace
DeepCopying Class
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DeserializationContext Class
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SerializationContext Class
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SerializationSlot<TKey, TValue> Class
Sasa.Statistics Assembly
Sasa.Statistics.Linq Namespace
Statistics Class
Members


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These are some practice projects from my first week at Epicodus. The newest projects are at the top. At the moment they are all still in progress...
Before starting school at Epicodus, I worked for several years as an event chef at a Portland catering company. Prior to that I held a variety of customer support/service positions. I also attended Southern Oregon University. My background provides strength in collaboration and communication, as well as organizational and problem solving skills.
Outside of coding, my interests/activities include the following...
Photo: Here I am in Washington Park enjoying the autumn leaves and a cup of coffee.
Please feel free to contact me at<EMAIL_ADDRESS>with questions or feedback.


{% extends "layout.html" %} {% block page_title %} About - GOV.UK Prototype kit {% endblock %} {% block content %} Switching to Universal Credit Here’s a checklist of things you can do to get ready for when it’s time for you to apply for Universal Credit. Checklist Find out more about what being on Universal Credit means for you and your family at GOV.UK/universal-credit. If you don’t have one already, set up a bank account in your name that you have full control over Make sure you have a personal email account that only you can access. If you’re getting Housing Benefit at the moment, arrange with your landlord to start paying your own rent when you’ve switched to Universal Credit. Find out what help you can get to apply for Universal Credit. Skip a few weeks Your switch journey Preparing for Universal Credit Letter received with switch date Conversation with Universal Credit representative Universal Credit application process started Identity checks complete Declaration and claimant commitment made Universal Credit application complete First Universal Credit payment received {% endblock %}
Skip a few weeks
Your switch journey


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The blue whale is a marine mammal that prefers the cold and temperate waters of the Arctic and Antarctic oceans. However, during the winter months, they are known to migrate to the waters of the Tropics and the Equator. They prefer the depths of the oceans than the shallow coastal waters and these creatures can grow up to 80 to 105 feet long and weigh over 200 tons.


$ListItem
This is the variable to use when using list procedures. It holds
the value of the current list item when cycling through the list.
$LoopCount
When using the /loop command this is the current value of the loop.
$CmdsProcessed
This variable is the count of the number of commands and procedures
executed by MM2k6 since the session was opened.
$LinesReceived
This variable is the count of the number of lines
received from the mud by MM2k6 since the session was opened.
$BytesReceived
This variable is the count of the number of bytes
received from the mud by MM2k6 since the session was opened.
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{% extends "base.html" %}
{% block content %}
{% if user.is_authenticated %}
Hello! You've successfully authenticated within your Odnoklassniki app. I know you, your name is {{ user.get_full_name }}!
{% else %}
Hello! Something went wrong and you're still seem to be anonymous for me.
{% endif %}
{% endblock %}


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Comparison of Three Natural Language Processors, AlchemyAPI, OpenCalais, and Semantria
The source code for this article is located here: https://github.com/cliftonm/nlp
To run the code, you will need to register with each of the NLP providers and obtain an API key (discussed below.)
I've been looking into Natural Language Processors (NLP's) and thought I would share the results of my investigations. We'll look at:
I've reviewed three NLP providers: AlchemyAPI, OpenCalais, and Semantria. They each offer similar services in that they will process text, producing a list of entities and relevance of those entities, along with additional information that is unique to each provider which I'll explore briefly as well. I have a particular interest in using NLP's to acquire the semantic content from websites (blogs, news feeds, articles, etc.) and began investing three NLP's (AlchemyAPI, OpenCalais, and Semantria) with regards to price and features. You can also read my article on how I use the AlchemyAPI service to parse RSS feeds here. For my particular purposes, I was interested in a low-document volume service that was hopefully free for limited use and that could provide web page content scraping. As I started investigating these three services, it occurred to me that this might be useful information for others as well, and thus this article came into being.
With regards to my specific requirements (for a different project) the upshot is that only AlchemyAPI and OpenCalais provide the price point (free for my small volume requirements) and only AlchemyAPI provides the webpage scraping functionality natively, as opposed to using a potentially costly third-party package. That said, my requirements are obviously not yours and you should choose a provider accordingly.
"Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. As such, NLP is related to the area of human–computer interaction. Many challenges in NLP involve natural language understanding, that is, enabling computers to derive meaning from human or natural language input, and others involve natural language generation." (wikipedia)
Borrowing from another NLP provider, Smartlogic, which I have not reviewed here:
"The ability to derive metadata, often in real-time, means that information locked-up in content can be made available alongside Big Data flows. It is this metadata that will help you turn Big Data into smart data for use in decision support."
and...
"The resulting metadata drives an array of business-critical tasks including:
I think that says it very well.
Each of the three NLP services that I review here parse text and determine something called "entities." While each of the services gives some examples of entities, only Semantria provides a clear definition of what an entity is: "Semantria’s Named Entity Extraction (NER) feature automatically pulls proper nouns from text, such as people, places, companies, brands, job titles and more. Each extracted named entity is classified, tagged and assigned a sentiment score, which gives meaning and context to each entity." (https://semantria.com/features/entity-extraction)
In other words, the primary purpose of an NLP is to extract the nouns, determine their types, and provide some "scoring" (relevance or sentiment) of the entity within the text. Using relevance, one can supposedly filter out entities to those that are most relevant in the document. Using sentiment analysis, one can determine the overall sentiment of an entity in the document, useful for determining the "tone" of the document with regards to an entity -- for example, is the entity "sovereign debt" described negatively, neutrally, or positively in the document? NLP's are also capable of extracting higher order concepts and, in the case of OpenCalais, events.
According to the OpenCalais documentation: "Entity relevance scores are comparable across input texts. This means that you can use entity relevance scores in order to determine entity relevance at a collection level, not just at a document level." (http://www.opencalais.com/documentation/calais-web-service-api/api-metadata/entity-relevance-score) If this meaning can be applied to the other providers, it is a useful value for comparing against other documents, but without a definitive meaning of the term "relevance", I'm not sure what the results of such a comparison actually mean. To my knowledge, Semantria is the only NLP service that can natively compare documents, which is a feature I do not explore in this article.
Entities are things such as people, companies, organizations, cities, geographic features, and so forth. In edition to the extraction of the entity, each service provides additional information about the entity, usually a relevance or sentiment.
AlchemyAPI's entity has several attributes:
Also, sentiment analysis is turned off by default, as it incurs an additional transaction count against one's daily/monthly allowance.
AlchemyAPI also supports the concept of "linked data". "Linked Data is a method of exposing, sharing, and connecting data on the Web via dereferenceable URIs. Linked Data aims to extend the Web with a data commons by publishing various open datasets as RDF on the Web and by setting RDF links between data items from different data sources. The Linked Data cloud currently consists of over 7.4 billion RDF triples, interlinked by 142+ million RDF links." (http://www.alchemyapi.com/api/linked-data-support/.) Linked data is partially demonstrated in Concepts (see below) in the demonstration program. Currently, Alchemy draws on several linked data resources (see the link above as well as http://linkeddata.org/.)
Note that in this demo, I'm using OpenCalais' "Simple Format" output. According to Ofer Harari:
"Simple Format output which is the poorest format in terms of capabilities (Simple format is for a quick and easy output from Calais. Not for a detailed response). The standard format is RDF or JSON. These outputs include all the metadata that Open Calais can extract."
"The Resource Description Framework (RDF) is a family of World Wide Web Consortium (W3C) specifications [1] originally designed as a metadata data model. It has come to be used as a general method for conceptual description or modeling of information that is implemented in web resources, using a variety of syntax notations and data serialization formats. It is also used in knowledge management applications." (http://en.wikipedia.org/wiki/Resource_Description_Framework)
It was being the scope of this article to parse the resulting RDF.
An OpenCalais entity has several attributes:
OpenCalais supports linking entities to DBpedia, Wikipedia, Freebase, Reuters.com, GeoNames, Shopping.com, IMDB, LinkedMDB. This feature is not demonstrated in the demo code. See also http://linkeddata.org/.)
Semantria's entity has several attributes (which basically conflicts with the documentation on their web page https://semantria.com/features/entity-extraction.)
In addition, each provides several additional categories of parsing. Be aware that the names of these categories and their attributes is derived from the API names.
AlchemyAPI
OpenCalais
Semantria
As pointed out by the folks at OpenCalais, NLP includes something called anaphora resolution:
"In linguistics, anaphora /əˈnæfərə/ is the use of an expression the interpretation of which depends upon another expression in context (its antecedent or postcedent). In the sentence Sally arrived, but nobody saw her, the pronoun her is anaphoric, referring back to Sally. The term anaphora denotes the act of referring, whereas the word that actually does the referring is sometimes called an anaphor (or cataphor)." (http://en.wikipedia.org/wiki/Anaphora_%28linguistics%29)
It first puzzled me as to why the counts of entities were often higher than the actual instances of those entities, and the above explains the reason why.
We'll look shortly at what each of the three providers has to say about themselves. First however, I'd like to talk a little about document processing, web content scraping, and initialization.
All three providers can work with text documents, however only AlchemyAPI
provides web content scraping directly as part of the API. OpenCalais and Semantria are both document-based
NLP's and as such require that that the web page scraping has been performed a
priori. While AlchemyAPI uses its own web page scraping technology, Semantria
can integrate with
Diffbot for this service. For the purposes of this demo
(since DiffBot offers only a 7 day limited free trial), I
will be using AlchemyAPI's URLGetText
API method to provide the
scraped content for the OpenCalais and Semantria NLP's.
/// <summary> /// We use AlchemyAPI to get the page text for OpenCalais and Semantria. /// </summary> protected string GetPageText(string url) { AlchemyWrapper alchemy = new AlchemyWrapper(); alchemy.Initialize(); string xml = alchemy.GetUrlText(url); XmlDocument xdoc = new XmlDocument(); xdoc.LoadXml(xml); return xdoc.SelectSingleNode("//text").InnerText; }
To reduce this hits on the AlchemyAPI server, extracting the URL content is cached based on the URL hashcode:
/// <summary> /// Uses AlchemyAPI to scrape the URL. Also caches the URL, so /// we don't hit AlchemyAPI's servers for repeat queries. /// </summary> protected string GetUrlText(string url) { string urlHash = url.GetHashCode().ToString(); string textFilename = urlHash + ".txt"; string pageText; if (File.Exists(textFilename)) { pageText = File.ReadAllText(textFilename); } else { pageText = GetPageText(url); } File.WriteAllText(textFilename, pageText); return pageText; }
This way, the text being handed to each NLP will be the same. If you're not processing content from web pages (blogs, news feeds, articles, etc.) then this is a moot point with regards to OpenCalais and Semantria.
Initialization of AlchemyAPI and OpenCalais is very simple. One of the issues that you may encounter however is limits to the number of entities (or other items) returned. While OpenCalais does not impose any limits, AlchemyAPI defaults to 50 entities (with a maximum I believe of 250) and Semantria defaults to 5 (with a maximum of 50). Changing the limit in AlchemyAPI is very simple -- you pass in some additional parameters when requesting the processing:
eparams = new AlchemyAPI_EntityParams(); eparams.setMaxRetrieve(250);
Semantria is tailored more toward bulk document processing. You can have a large number of different configurations that you can choose from depending on the document you want processed. Initialization of these configurations however takes some time to communicate to the server and the get a response back. In the demo code, I first request the current configurations (there are 8 initially based on language) and then I change the limit (which has a maximum of 50) and then this new configuration must be uploaded.
protected void IncreaseLimits() { // This takes considerable time to get the configurations back from the server. List<Configuration> configurations = session.GetConfigurations(); config = configurations.FirstOrDefault(item => item.Language.Equals("English")); if (config != null) { config.Document.NamedEntitiesLimit = 50; config.Document.ConceptTopicsLimit = 50; config.Document.EntityThemesLimit = 50; session.UpdateConfigurations(new List<Configuration>() { config }); } }
This all takes time and is why the Process button is disabled for so long at application startup. However, once done, the configurations can be used without further time penalty. It is also interesting to note that the configurations are persisted between sessions -- I assume they are associated with your API key, so once configurations are created, technically I don't need to run this step unless I want to make a change. For this reason, the method IncreaseLimits() in the Initialize method can be commented out after you first configure Semantria:
public void Initialize() { string apikey = File.ReadAllText("semantriaapikey.txt"); string[] keys = apikey.Split('\r'); consumerKey = keys[0].Trim(); consumerSecret = keys[1].Trim(); serializer = new JsonSerializer(); session = Session.CreateSession(consumerKey, consumerSecret, serializer); IncreaseLimits(); // <---- Comment me out when the limits have been increased after the first-ever run }
"AlchemyAPI is helping pioneer a computer’s ability to understand human language and vision. Our web services for real-time text analysis and computer vision give you the intelligence needed to transform vast amounts of unstructured data into actions that drive your business. Now you can easily perform sentiment analysis, keyword extraction, entity extraction, image tagging and much more on the massive volumes of web pages, documents, tweets and photos produced every second."
One of the unique things about AlchemyAPI that I noticed right away is that it performs analysis not just on text but also on images.
AlchemyAPI supports named entity, keyword, and text extraction for content in the following eight languages:
Content sentiment analysis currently supports English and German, with support for additional languages in development.
To avoid biasing the timing results, I first request the page text using AlchemyAPI and then feed this text into all three NLP's. It should be noted that this produces worse timing for AlchemyAPI than if I had provided the web page URL directly -- meaning that if you give AlchemyAPI the URL, it performs better, and in many cases, significantly better than the other two.
"We want to make all the world's content more accessible, interoperable and valuable.  Calais is a rapidly growing toolkit of capabilities that allow you to readily incorporate state-of-the-art semantic functionality within your blog, content management system, website or application."
OpenCalais supports English, French and Spanish.
OpenCalais
"Semantria applies Text and Sentiment Analysis to tweets, facebook posts, surveys, reviews or enterprise content. Semantria is a complete cloud-based text and sentiment analysis solution launched in 2011. Faster than a human (60,000x), more accurate than 2 humans (80% of the time it's flat out smarter), and living in the Amazon cloud, Semantria extracts the meaning, tone, and so much more from any text it’s given."
One of the interesting things about Semantria is the Excel plugin: "Semantria is the only Text and Sentiment Analysis solution for Excel. It turns it into a powerful and easy-to-use tool for monitoring and visualizing Twitter, Facebook, surveys and other unstructured data."
Also, Semantria supports these languages:
Also, Semantria integrates tightly with Diffbot for webpage scraping.
Pricing varies considerably and is based on number of transactions being processed daily/monthly and level of customer support.
The pricing that I describe here may not be up on the AlchemyAPI website at the time of this writing, as I was notified directly that the pricing structure was being changed.
There are five tiers:
For academia, AlchemyAPI offers an increased number of transactions per day in the Free tier.
There is also a "Performance and Support Package" that you can select:
As well as a month-to-month subscription option:
Free: 50,000 transactions per license per day and four transactions per second
Commercial License: "Our commercial services provide the same functionality as OpenCalais but with a production-strength twist. The service provides a high-performance SLA, a daily transaction limit of 100,000 transactions and an enhanced 20 transactions per second rate. Additional volume blocks up to maximum of 2,000,000 transactions per day are available. ProfessionalCalais meets needs unique to larger-scale publishers. ProfessionalCalais is available as an annual contract."
There are five tiers:
DiffBbot, which integrates with Semantria for webpage scraping, has its own pricing structure and I am not aware of how that changes the pricing structure.
Each provider requires that you obtain a product key to interface with the API, which is a simple process. I have not included my keys, so to run the code, you will need to register with each provider to obtain your own API key and place it into the appropriate text file (see the code for filenames.) Because I'm working in C# / .NET, I obtained a .NET library to handle the SOAP/REST calls, either from the provider directly or one that I was referred to by the provider. All API's provided examples and various degrees of unit tests.
The AlchemyAPI, to put it simply, just worked. It provided the functionality that I was looking for (give it a URL and it returns semantic results) and it worked without any issues, which was not my experience with OpenCalais or Semantria, though in hindsight, my issues with Semantria were more related to not fully understanding the document queuing model that Semantria uses. Interfacing with the .NET API that AlchemyAPI provides is quite simple, for example:
protected AlchemyAPI.AlchemyAPI alchemyObj; public void Initialize() { alchemyObj = new AlchemyAPI.AlchemyAPI(); alchemyObj.LoadAPIKey("alchemyapikey.txt"); } // Process a URL directly. public DataSet LoadEntitiesFromUrl(string url) { DataSet dsEntities = new DataSet(); string xml = alchemyObj.URLGetRankedNamedEntities(url); TextReader tr = new StringReader(xml); XmlReader xr = XmlReader.Create(tr); dsEntities.ReadXml(xr); xr.Close(); tr.Close(); return dsEntities; }
AlchemyAPI returns an XML document
that is well suited for loading directly into a DataSet
, as seen by
the above code.
One issue I encountered with the .NET AlchemyAPI was that a useful exception message was not being returned, so I modified it slightly to return the message from the server as part of the exception:
if (status.InnerText != "OK") { string errorMessage = "Error making API call."; try { XmlNode statusInfo = root.SelectSingleNode("/results/statusInfo"); errorMessage = statusInfo.InnerText; } catch { // some problem with the statusInfo. Return the generic message. } System.ApplicationException ex = new System.ApplicationException (errorMessage); throw ex; }
This change has been folded into the C# AlchemyAPI hosted on GitHub.
AlchemyAPI's content size limits are 150KB of cleaned text and 600KB of HTML.
The Open Calais .NET library on Codeplex was the most difficult of the three libraries to work with, requiring me to fix the entity enumerator. The first issue with this library is that, when you unzip it, all the files are read-only. This made it impossible to load the projects and solutions into VS2012 without first changing all the files and folders to read-write.
Second, using their sample document, I was getting
"Unhandled Exception: System.ArgumentException: Requested value 'PoliticalEvent'
was not found." because there were missing types in the CalaisSimpleEntityType
enumerator:
// Ignore topics and events are they are processed seperately if (elementName != "Topics" && elementName != "Event" && elementName != "Topic") { newSimpleEntity.Type = (CalaisSimpleEntityType)Enum.Parse(typeof(CalaisSimpleEntityType), result.Name.ToString()); yield return newSimpleEntity; }
To fix this, I had to go in and change this class:
public class CalaisSimpleEntity { public string Value { get; set; } public int Frequency { get; set; } public string Relevance { get; set; } public CalaisSimpleEntityType Type { get; set; } }
so that Type was a string (why it's mapped to an enumeration is beyond me):
public class CalaisSimpleEntity { public string Value { get; set; } public int Frequency { get; set; } public string Relevance { get; set; } public string Type { get; set; } }
and the offending line of code:
newSimpleEntity.Type = result.Name.ToString();
I also had to fix a unit test that failed to compile as the result of the type change.
I also found it annoying that the properties for Entities, Topics, and Events are IEnumerable's, meaning you have to explicitly iterate through the collection to acquire the contents, which, underlying, involves some processing of the XML document. This seems inefficient, especially if the collection is iterated over many times by different functions, but can be worked around by converting the collections to lists, as I did in the simple "get" functions, for example:
return document.Entities.ToList();
Given that the contents of these collections is unchanging, I see no reason not to pre-populate the collections with their items.
My other issue with OpenCalais is that my sample document (the text of Wikipedia's page on Computer Science) resulted in a "content is not valid" exception from the server. It turns out that the offending sentence is this:
The term is used mainly in the Scandinavian countries. Also, in the early
days of computing, a number of terms for the practitioners of the field of
computing were suggested in the Communications of the ACM – turingineer,
turologist, flow-charts-man, applied meta-mathematician, and applied
epistemologist.[34]
and can be further reduced to the use of the "–" character -- the Unicode
character 0x2013 "EN DASH". OpenCalais is apparently rather sensitive, but
we can strip Unicode:
// A couple options: http://stackoverflow.com/questions/123336/how-can-you-strip-non-ascii-characters-from-a-string-in-c string asAscii = Encoding.ASCII.GetString( Encoding.Convert( Encoding.UTF8, Encoding.GetEncoding( Encoding.ASCII.EncodingName, new EncoderReplacementFallback(string.Empty), new DecoderExceptionFallback() ), Encoding.UTF8.GetBytes(content) ) );
Once properly sanitized, the actual call to parse the document and extract data is very simple:
CalaisDotNet calais = new CalaisDotNet(apikey, asAscii); document = calais.Call<CalaisSimpleDocument>(); ... public IList GetEntities() { return document.Entities.ToList(); }
There is a complementary service, http://semanticproxy.com/, that is supposed to perform content scraping, however, when I tried to use it (at different times) I constantly received a "Java out of memory" error.
In this demonstration code, I am using "Simple Format" output. According to Ofer Harari:
"Simple Format output which is the poorest format in terms of capabilities (Simple format is for a quick and easy output from Calais. Not for a detailed response). The standard format is RDF or JSON. These outputs include all the metadata that Open Calais can extract."
I originally found Semantria's .NET API to be complicated to work with, which I realized after having success with it was that it takes a different approach to processing documents. With AlchemyAPI and OpenCalais, you make the call and wait for the results. With Semantria, it is very bulk-document centric. Documents that are sent to the Semantria servers are queued and can return asynchronously with results or in a different order from the original input into the queue. This makes working with a single document more complex (see code below) but clearly, the strength of Semantria's API is much more evident when working with bulk documents.
There are also two modes of document analysis, described here: https://semantria.com/support/developer/overview/processing
"After submitting documents to be queued, each document will be analyzed independently of the others. Semantria API will return an analysis for each document."
"This method submits an array of documents to be analyzed in relation to each other and returns one output. Discovery analysis will contain a summary of commonalities, sentiments, named entity extraction, themes, and categorization for all the documents in the collection."
This article reviews Detailed Mode only, however, when working with Discovery Mode I "discovered" an issue with document size--with my scraped webpage content string, I was getting "line too long" exceptions. It seems that Discovery Mode is intended to work with smaller datasets, such as paragraphs or single sentences. I am not sure what the line limit is when in Discovery Mode.
Calling the parser requires polling to see if the document is analyzed. While there is a DocsAutoResponse event callback, this isn't what it seems -- if the document is queued (which is the standard behavior) this callback is never made, and I'm not sure how this event helps, unless it is associated with the bulk processing. Here is the parse request and response poll code:
public void ParseUrl(string content) { string docId = Guid.NewGuid().ToString(); Document doc = new Document() {Id = docId, Text = content}; docResults = new List<DocAnalyticData>(); int result = session.QueueDocument(doc, configID); DocAnalyticData ret; DateTime start = DateTime.Now; do { // Semantria guarantees a result within 10 seconds. But how fast is it really? Thread.Sleep(100); ret = session.GetDocument(doc.Id, configID); if ((DateTime.Now - start).TotalSeconds > 15) { throw new ApplicationException("Semantria did not return with 15 seconds."); } } while (ret.Status == Semantria.Com.TaskStatus.QUEUED); if (ret.Status == Semantria.Com.TaskStatus.PROCESSED) { docResults.Add(ret); } else { throw new ApplicationException("Error processing document: " + ret.Status.ToString()); } }
As stated at the beginning of this article under Initialization, the default number of entities is 5 (themes is also 5 and topics is 10). In this article I have increased the limit to 50, which is the maximum.
The screenshots that I've been using come from parsing this page: http://en.wikipedia.org/wiki/Computer_science. You can of course enter your own URL in the demo application (try a Code Project article, the results are often interesting.) The code that does the processing runs each service request asynchronously, marshalling the UI data grid updates back onto the UI thread (not shown). I also cache (using the URL's hash code) the scraped web page returned by AlchemyAPI so I'm not constantly making a "get page content" request to AlchemyAPI when testing the same web pages over and over.
/// <summary> /// Process the URL with AlchemyAPI, OpenCalais, and Semantra NLP's. /// </summary> protected async void Process(object sender, EventArgs args) { btnProcess.Enabled = false; ClearAllGrids(); string url = tbUrl.Text; sbStatus.Text = "Acquiring page content..."; // Eases debugging when we comment out one or more of the NLP's to test the other. double alchemyTime = 0; double calaisTime = 0; double semantriaTime = 0; string pageText = await Task.Run(() => GetUrlText(url)); sbStatus.Text = "Processing results with Alchemy..."; double alchemyTime = await Task.Run(() => { LoadAlchemyResults(pageText); return ElapsedTime(); }); sbStatus.Text = "Processing results with OpenCalais..."; double calaisTime = await Task.Run(() => { LoadCalaisResults(pageText); return ElapsedTime(); }); sbStatus.Text = "Processing results with Semantria..."; double semantriaTime = await Task.Run(() => { LoadSemantriaResults(pageText); return ElapsedTime(); }); sbStatus.Text = "Done processing."; ReportTimes(alchemyTime, calaisTime, semantriaTime); btnProcess.Enabled = true; }
Using .NET's Task.Run
allows the to UI remain responsive so you can interact with it while other
results are still coming in.
Of course, to run the demo, you will need to register with each provider and obtain your own API keys. These go into their respective files in the bin\debug folder:
alchemyapikey.txt
[your key]
calaisapikey.txt
[your key]
semantriaapikey.txt
[your consumer key]
[your secret key]
I decided to throw something more interesting at these providers--Rudolf Steiner's Chapter 3 "Culture, Law, and Economics" of his lecture series The Renewal of the Social Organism. The results are interesting and reveal the differences between the three NLP's. Keep in mind that I'm using the Simple Format with OpenCalais and so the results may not represent its full semantic processing capability. It was being the scope of this article to parse the resulting RDF.
| type | relevance | count | text |
|---|---|---|---|
| PrintMedia | 0.734508 | 1 | Law and Economics |
| Crime | 0.684892 | 1 | monopolization |
| JobTitle | 0.635413 | 1 | business manager |
| Facility | 0.61222 | 1 | St. Simon |
| JobTitle | 0.606995 | 1 | official |
| Person | 0.602684 | 1 | Marx |
| Person | 0.581026 | 1 | Fourier |
(No topics or events were returned)
| Value | Frequency | Relevance | Type |
|---|---|---|---|
| natural law | 2 | 0.286 | IndustryTerm |
| devise external systems | 1 | 0.251 | IndustryTerm |
| economic services | 1 | 0.318 | IndustryTerm |
| manager | 1 | 0.314 | Position |
| government official | 1 | 0.239 | Position |
| business manager | 1 | 0.314 | Position |
| shopkeeper | 1 | 0.239 | Position |
| Type | Evidence | Confident | IsAbout | EntityType | Title | Label | SentimentScore | SentimentPolarity |
|---|---|---|---|---|---|---|---|---|
| named | 7 | True | False | Job Title | manager | Job Title | 0.171760261 | neutral |
| named | 4 | True | False | Person | Marx | Person | 0.294535 | neutral |
| named | 2 | True | False | Quote | “It is impossible to bring about satisfactory conditions through this organic formation of society. It can be done only through a suitable economic organization.” | Quote | 0.218072414 | neutral |
| named | 1 | True | False | Quote | “social question” | Quote | 0 | neutral |
| named | 1 | True | False | Quote | “simplicity” | Quote | 0.49 | neutral |
| named | 1 | True | False | Quote | “self-evident fact” | Quote | 0 | neutral |
| named | 1 | True | False | Quote | “social question” | Quote | 0 | neutral |
| text | relevance | dbpedia | freebase | opencyc |
|---|---|---|---|---|
| Sociology | 0.965445 | http://dbpedia.org/resource/Sociology | http://rdf.freebase.com/ns/m.06ms6 | http://sw.opencyc.org/concept/Mx4rvVvb3pwpEbGdrcN5Y29ycA |
| Law | 0.445281 | http://dbpedia.org/resource/Law | http://rdf.freebase.com/ns/m.04gb7 | http://sw.opencyc.org/concept/Mx4rvV1TLJwpEbGdrcN5Y29ycA |
| Economy | 0.40107 | http://dbpedia.org/resource/Economy | http://rdf.freebase.com/ns/m.0gfps3 | |
| Economics | 0.391207 | http://dbpedia.org/resource/Economics | http://rdf.freebase.com/ns/m.02j62 | http://sw.opencyc.org/concept/Mx4rvqlEOpwpEbGdrcN5Y29ycA |
| Human | 0.36315 | http://dbpedia.org/resource/Human | http://rdf.freebase.com/ns/m.0dgw9r | http://sw.opencyc.org/concept/Mx4rIcwFloGUQdeMlsOWYLFB2w |
| Religion | 0.353719 | http://dbpedia.org/resource/Religion | http://rdf.freebase.com/ns/m.06bvp | http://sw.opencyc.org/concept/Mx4rvVkCHZwpEbGdrcN5Y29ycA |
| Spirituality | 0.344812 | http://dbpedia.org/resource/Spirituality | http://rdf.freebase.com/ns/m.070wm | |
| Communism | 0.280482 | http://dbpedia.org/resource/Communism | http://rdf.freebase.com/ns/m.01m59 | http://sw.opencyc.org/concept/Mx4rvVi0EZwpEbGdrcN5Y29ycA |
(I'm only showing the first 10 of the 250 keywords returned.)
| life | 0.926948 |
| cultural life | 0.884749 |
| economic life | 0.766198 |
| economic power | 0.720022 |
| free cultural life | 0.717939 |
| practical life | 0.669134 |
| modern social movement | 0.668291 |
| spiritual life | 0.654856 |
| nature | 0.638823 |
| individual wills | 0.635454 |
..etc..
| Title | Type | Hitcount | StrengthScore | SentimentScore | SentimentPolarity | Label |
|---|---|---|---|---|---|---|
| Science | concept | 0 | 0.78942883 | 0.121833332 | neutral | |
| Economics | concept | 0 | 0.748247862 | 0.414984226 | neutral | |
| Law | concept | 0 | 0.7397579 | 0.356725723 | neutral | |
| Education | concept | 0 | 0.494773239 | 0.351259947 | neutral | |
| Science | query | 3 | 0 | 0.750133157 | positive |
| Evidence | IsAbout | StrengthScore | SentimentScore | SentimentPolarity | Title |
|---|---|---|---|---|---|
| 7 | True | 2.95010757 | 0.7593447 | positive | individual persons |
| 7 | False | 2.93402934 | 7.267939 | positive | economic life |
| 7 | True | 2.7541132 | -13.2000027 | negative | evils — evils |
| 7 | True | 2.544567 | 6.680146 | positive | Socialist thinkers |
| 7 | True | 2.48574352 | 9.6 | positive | wide range |
The testing here is not exhaustive--some may argue not even comprehensive. I am not testing high throughputs and haven't simulated customer service issues. All three providers replied very quickly when I emailed them that I was writing this article, and I've had excellent and helpful conversations with all of them. After working with each provider, I realized that they each would deserve a "deep dive" article on their own. Even this high-level review has taken a considerable amount of time and I have glossed over (or outright skipped) many of the features of these providers.
I strongly suggest that you invest each provider in detail yourself to see what additional features and capabilities exist. Especially with regards to OpenCalais, I would strongly suggest that anyone interested in using this service further investigate the RDF output.
Also, as a general criticism, each provider would do well to explicitly define what the various terms mean in their API's and the collection attributes. If one is to use these services for serious analysis of documents, an exact meaning is a requirement.
Lastly, I find the concept of Natural Language Processing intriguing and that it holds many possibilities for helping to filter and analyze the vast and growing amount of information out there on the web. However, I'm not quite sure exactly how one uses the output of an NLP service in a productive way that goes beyond simple keyword matching. Some people will of course be interested in whether the sentiment is positive or negative, and I think the idea of extracting concepts (AlchemyAPI) and topics (Semantria) are useful in extracting higher level abstractions regarding a document. NLP is therefore an interesting field of study and I believe that the people who provide NLP services would benefit from the feedback of users to increase the value of their service.


The world wide web contains many information in many different formats. HTML (hypertext markup language) is what glues everything together. Currently there are more than 30 Billion PAGES Any kinf of file can exists on the web,( music, videos images, plain text)
This paragraph from Andy explains HTML really well - HTML stands for Hypertext Markup Language. HTML documents form the majority of the content on the web. HTML documents contain text content which describes "what you see" and markup which describes "how it looks". This video gives a good overview.
HTML documents are made of HTML elements. When
writing HTML, we tell browsers the type of each element by using HTML tags.This videoexplains the distinction well.
additional notes from BNi
Computers are stupid because they interpret instructions literally. This makes them very unforgiving since a small mistake by a programmer can cause huge problems in a program. Computer is honest. It does what you tell it to do. Therefore it is better to be clear on the instruction so you truly understand what you want it to do.
HTML elements are either inline or block. Block elements form an "invisible box" around the content inside of them.
programmer does not need to remember all the code. Only to understand the big ideas and know how to get the details when you need them.
These links can help you


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| PERLMACOSX(1) | Perl Programmers Reference Guide | PERLMACOSX(1) |
curl -O http://www.cpan.org/src/perl-5.30.3.tar.gz tar -xzf perl-5.30.3.tar.gz cd perl-5.30.3 ./Configure -des -Dprefix=/usr/local/ make make test sudo make install
In order to build your own version of Perl you will need 'make', which is part of Apple's developer tools - also known as Xcode. From Mac OS X 10.7 "Lion" onwards, it can be downloaded separately as the 'Command Line Tools' bundle directly from <https://developer.apple.com/downloads/> (you will need a free account to log in), or as a part of the Xcode suite, freely available at the App Store. Xcode is a pretty big app, so unless you already have it or really want it, you are advised to get the 'Command Line Tools' bundle separately from the link above. If you want to do it from within Xcode, go to Xcode -> Preferences -> Downloads and select the 'Command Line Tools' option.
Between Mac OS X 10.3 "Panther" and 10.6 "Snow Leopard", the 'Command Line Tools' bundle was called 'unix tools', and was usually supplied with Mac OS install DVDs.
Earlier Mac OS X releases (10.2 "Jaguar" and older) did not include a completely thread-safe libc, so threading is not fully supported. Also, earlier releases included a buggy libdb, so some of the DB_File tests are known to fail on those releases.
Using an installation prefix of '/usr' will result in a directory layout that mirrors that of Apple's default Perl, with core modules stored in '/System/Library/Perl/${version}', CPAN modules stored in '/Library/Perl/${version}', and the addition of '/Network/Library/Perl/${version}' to @INC for modules that are stored on a file server and used by many Macs.
export SDK=/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.8.sdk
Please make sure the SDK version (i.e. the numbers right before '.sdk') matches your system's (in this case, Mac OS X 10.8 "Mountain Lion"), as it is possible to have more than one SDK installed. Also make sure the path exists in your system, and if it doesn't please make sure the SDK is properly installed, as it should come with the 'Command Line Tools' bundle mentioned above. Finally, if you have an older Mac OS X (10.6 "Snow Leopard" and below) running Xcode 4.2 or lower, the SDK path might be something like '/Developer/SDKs/MacOSX10.3.9.sdk'.
You can use the SDK by exporting some additions to Perl's 'ccflags' and '..flags' config variables:
./Configure -Accflags="-nostdinc -B$SDK/usr/include/gcc \ -B$SDK/usr/lib/gcc -isystem$SDK/usr/include \ -F$SDK/System/Library/Frameworks" \ -Aldflags="-Wl,-syslibroot,$SDK" \ -de
You can compile perl as a universal binary (built for both ppc and intel). In Mac OS X 10.4 "Tiger", you must export the 'u' variant of the SDK:
export SDK=/Developer/SDKs/MacOSX10.4u.sdk
Mac OS X 10.5 "Leopard" and above do not require the 'u' variant.
In addition to the compiler flags used to select the SDK, also add the flags for creating a universal binary:
./Configure -Accflags="-arch i686 -arch ppc -nostdinc \ -B$SDK/usr/include/gcc \ -B$SDK/usr/lib/gcc -isystem$SDK/usr/include \ -F$SDK/System/Library/Frameworks" \ -Aldflags="-arch i686 -arch ppc -Wl,-syslibroot,$SDK" \ -de
Keep in mind that these compiler and linker settings will also be used when building CPAN modules. For XS modules to be compiled as a universal binary, any libraries it links to must also be universal binaries. The system libraries that Apple includes with the 10.4u SDK are all universal, but user-installed libraries may need to be re-installed as universal binaries.
Support for 64-bit addressing is experimental: some aspects of Perl may be omitted or buggy. Note the messages output by Configure for further information. Please use <https://github.com/Perl/perl5/issues> to submit a problem report in the event that you encounter difficulties.
When building 64-bit modules, it is your responsibility to ensure that linked external libraries and frameworks provide 64-bit support: if they do not, module building may appear to succeed, but attempts to use the module will result in run-time dynamic linking errors, and subsequent test failures. You can use "file" to discover the architectures supported by a library:
$ file libgdbm.3.0.0.dylib libgdbm.3.0.0.dylib: Mach-O fat file with 2 architectures libgdbm.3.0.0.dylib (for architecture ppc): Mach-O dynamically linked shared library ppc libgdbm.3.0.0.dylib (for architecture ppc64): Mach-O 64-bit dynamically linked shared library ppc64
Note that this issue precludes the building of many Macintosh-specific CPAN modules ("Mac::*"), as the required Apple frameworks do not provide PPC64 support. Similarly, downloads from Fink or Darwinports are unlikely to provide 64-bit support; the libraries must be rebuilt from source with the appropriate compiler and linker flags. For further information, see Apple's 64-Bit Transition Guide at <http://developer.apple.com/documentation/Darwin/Conceptual/64bitPorting/index.html>.
You can override the default and build a shared libperl if you wish (Configure ... -Duseshrplib).
With Mac OS X 10.4 "Tiger" and newer, there is almost no performance penalty for non-prebound libraries. Earlier releases will suffer a greater load time than either the static library, or Apple's pre-bound dynamic library.
If you find that you do need to update the system Perl, one issue worth keeping in mind is the question of static vs. dynamic libraries. If you upgrade using the default static libperl, you will find that the dynamic libperl supplied by Apple will not be deleted. If both libraries are present when an application that links against libperl is built, ld will link against the dynamic library by default. So, if you need to replace Apple's dynamic libperl with a static libperl, you need to be sure to delete the older dynamic library after you've installed the update.
Configure ... -Uloclibpth -Dlibpth=/usr/lib
to make Configure look only into the system libraries. If you have some extra library directories that you really want to use (such as newer Berkeley DB libraries in pre-Panther systems), add those to the libpth:
Configure ... -Uloclibpth -Dlibpth='/usr/lib /opt/lib'
The default of building Perl statically may cause problems with complex applications like Tk: in that case consider building shared Perl
Configure ... -Duseshrplib
but remember that there's a startup cost to pay in that case (see above "libperl and Prebinding").
Starting with Tiger (Mac OS X 10.4), Apple shipped broken locale files for the eu_ES locale (Basque-Spain). In previous releases of Perl, this resulted in failures in the lib/locale test. These failures have been suppressed in the current release of Perl by making the test ignore the broken locale. If you need to use the eu_ES locale, you should contact Apple support.
An alternative is CamelBones, a framework that allows access to both Foundation and AppKit classes and objects, so that full GUI applications can be built in Perl. CamelBones can be found on SourceForge, at <http://www.sourceforge.net/projects/camelbones/>.
First, get rid of the libperl.dylib:
# cd /System/Library/Perl/darwin/CORE # rm libperl.dylib
Then delete every .bundle file found anywhere in the folders:
/System/Library/Perl /Library/Perl
You can find them for example by
# find /System/Library/Perl /Library/Perl -name '*.bundle' -print
After this you can either copy Perl from your operating system media (you will need at least the /System/Library/Perl and /usr/bin/perl), or rebuild Perl from the source code with "Configure -Dprefix=/usr -Duseshrplib" NOTE: the "-Dprefix=/usr" to replace the system Perl works much better with Perl 5.8.1 and later, in Perl 5.8.0 the settings were not quite right.
"Pacifist" from CharlesSoft (<http://www.charlessoft.com/>) is a nice way to extract the Perl binaries from the OS media, without having to reinstall the entire OS.
| 2020-05-14 | perl v5.30.3 |


--- layout: post title: New Website date: 2010-11-08 21:13:36.000000000 -06:00 categories: - General tags: - bots - spam - website status: publish type: post published: true meta: _edit_last: '1' author: login: Blake email<EMAIL_ADDRESS>display_name: Blake first_name: Blake last_name: Harley ---
That's right. I've gone and redesigned the website once again. Why? A combination of factors led to this decision. My free web host was abysmally slow, so I moved the web site on to a server I wasn't using.  I know neither of those are very good reasons for completely redesigning a web site, but that's beside the point.
I'm also going to make some more promises. Hopefully they won't be empty promises this time. I plan to post more and actually make those other links at the top do stuff.
I'm setting my sights high with that last promise.


Dec's brutal swipe at Prince Andrew over BBC Newsnight interview on I'm A Celebrity
During the interview, Andrew attempted to defend his reputation following the Jeffrey Epstein sex scandal, and denied claims he had underage sex with Virginia Giuffre, one of Epstein's accusers
by James Rodger, https://www.facebook.com/jamesrodgerjournalistAnt McPartlin and Declan Donnelly appeared to poke fun at the Duke of York's Newsnight interview as I'm A Celebrity...

Giuffre has said she recalled the royal sweating as they danced at a club, but he said he had a medical condition at the time which meant he did not sweat.
As I'm A Celebrity got under way on ITV on Sunday, McPartlin said this year's contestants were likely to be "sweating".
But Donnelly quipped: "Presuming they can sweat, not everybody can apparently..."
The Duke of York last night answered questions for the first time about his links to paedophile billionaire Jeffrey Epstein.

I'm A Celebrity kicks off tonight with a host of famous faces heading to the jungle for three weeks of gruelling challenges.
On the line-up is Olympian and reality star and transgender icon Caitlyn Jenner, former Girls Aloud star Nadine Coyle, former EastEnders star Jacqueline Jossa, Good Morning Britain presenter Kate Garraway, Radio presenter Roman Kemp, former Big Brother star Adele Roberts, comedian Andrew Maxwell, Rak-Su singer Myles Stephenson, former rugby player James Haskell, and former footballer Ian Wright.
There are also a few rumoured late additions.


A simple solution is to find all prime factors of both numbers, then find union of all factors present in both numbers. Finally return product of elements in union. An efficient solution is based on below formula for LCM of two numbers ‘a’ and ‘b’.
a x b = LCM(a, b) * GCD (a, b) LCM(a, b) = (a x b) / GCD(a, b)
We know,
The above relation only holds for two numbers,
The idea here is to extend our relation for more than 2 numbers. Let’s say we have an array arr[] that contains n elements whose LCM needed to be calculated.
The main steps of our algorithm are:


1:1
| [Arabic-Original Text]
بِسْمِ اللَّهِ الرَّحْمَٰنِ الرَّحِيمِ
[English-Literal] By God`s Name, the Merciful, the Merciful/Most Merciful .
[English-Maulana Mohammad Ali] In the name of Allah, the Beneficent, the Merciful.
Details and Discuss
1:1
| [Arabic-Original Text]
بِسْمِ اللَّهِ الرَّحْمَٰنِ الرَّحِيمِ
[English-Literal] By God`s Name, the Merciful, the Merciful/Most Merciful .
[English-Maulana Mohammad Ali] In the name of Allah, the Beneficent, the Merciful.
Details and Discuss
1:1
| [Arabic-Original Text]
بِسْمِ اللَّهِ الرَّحْمَٰنِ الرَّحِيمِ
[English-Literal] By God`s Name, the Merciful, the Merciful/Most Merciful .
[English-Maulana Mohammad Ali] In the name of Allah, the Beneficent, the Merciful.
Details and Discuss
1:1
| [Arabic-Original Text]
بِسْمِ اللَّهِ الرَّحْمَٰنِ الرَّحِيمِ
[English-Literal] By God`s Name, the Merciful, the Merciful/Most Merciful .
[English-Maulana Mohammad Ali] In the name of Allah, the Beneficent, the Merciful.
Details and Discuss
1:1
| [Arabic-Original Text]
بِسْمِ اللَّهِ الرَّحْمَٰنِ الرَّحِيمِ
[English-Literal] By God`s Name, the Merciful, the Merciful/Most Merciful .
[English-Maulana Mohammad Ali] In the name of Allah, the Beneficent, the Merciful.
Details and Discuss
1:1
| [Arabic-Original Text]
بِسْمِ اللَّهِ الرَّحْمَٰنِ الرَّحِيمِ
[English-Literal] By God`s Name, the Merciful, the Merciful/Most Merciful .
[English-Maulana Mohammad Ali] In the name of Allah, the Beneficent, the Merciful.
Details and Discuss


Before you start defining classes you need to initialize the class system. The class system depends on a namespace manager (if not provided, it will use global namespace).


Reports unreachable code.
Example:
def test(): Unit = { throw new Exception() println("this will never be reached") }
After the quick-fix is applied:
def test(): Unit = { throw new Exception() }


dataApi
api
A service for data api calls
Gets the data for the dictionary The data is a list of comma-separated values of all the legal Scrabble words
Returns the result of the data request


| Well I'm not saying it isn't, it might. But without a link to Compiler Compliance, that paragraph is useless. |
This isn't wikipedia. There is no
one source for that statement -- you have to look at individual compiler's development team statements about their efforts towards compliance.
You should notice, however, after the extensive examples testing for support for key C++11 features, I did provide two very important links to C++11 support pages: one from the US government itself that tests compiler compliance, and another from the Apache Software Foundation, who has always had a strong presence and interest in compiler compliance issues.
Yes. By "we", I mean C++ professionals all over the globe, in addition to the maintainers of
this site, in addition to JTC1/SC22/WG21, who develop and maintain C++ through Boost.
Individual members of the forum are not indicated. (Nor should they be.)
Suggest a different name. Or a different example. My Google's top result is a photographer in California, and I see nothing pornographic or egregiously inappropriate in the following pages, nor in images with safe search turned off.
If you think it is an issue, show me why and/or suggest something different.
Found it at
http://cplusplus.com/faq/sequences/sequencing/sort-algorithms/#bubble-sort
Why is it a problem? Should I use another word, like "hurrah"? Or do you think it is too unformal?
Thanks for your time!