–– happybirds team ––
This site is the project documentation of the happybirds team for the capstone project for the postgraduate Data science and big data course of the University of Barcelona. The tasks were to develop a machine learning algorithm for an annotated dataset and to analyze the dataset for insights. Hereby we present what our team did and what technologies we used. The first part discusses the modelling, the later parts the insights we have found analyzing the dataset.
The problem to be solved for the capstone project is an airline sentiment tweet classification. The teams of the postraduate course received two datasets: one containing tweets in English already classified and a second dataset with tweets in Spanish, which was classified by the students of the postgraduate course on a platform designed for this task.
For the solution presented below, we have developed a project in Python that has all the tools needed to run the necessary phases to import, transform, train, validate, test and optimize for a tweet sentiment classification. All codes are available in this Github repository.
Firstly, the sections below cover the in-depth description of the steps taken for the solution of the classification problem in a chronological order, the results obtained, and the next steps that could have been potentially done on the Spanish dataset. Secondly, the insights are presented we have found upon analyzing the dataset. These two main parts are discussed in the following chapters:
To navigate between these parts use the menu on the top right corner.
We have started the project with experimenting, ie. “playing around” with the dataset in a Jupyter notebook. We have soon realized that using a notebook to store the final solution would be a problem when team members wanted to share they work with each other. We have agreed to start working on a centralized solution that made the code versioning easy.
The main reason why we chose the Python project format instead of working on a lengthy Jupyter Notebook was the flexibility such a project has in terms of code sharing. Versioning a Jupyter Notebook can potentially be a bad idea as it stores all the results within. As a consequence, each time a team member re-executes even just one cell locally, Git recognises it as a change and asks to commit it. There is a way to avoid this phenomenon by resetting the notebook output each time a team member pulls or pushes changes. However, this can easily be forgotten causing subsequent chaos. Having a final version as a Python project enables any team member to execute the parts in the way she prefers. Also, it allows team members to experiment if the code is correctly modularized. Finally, each team member has the chance to do this by using her own Jupyter Notebook, iPython or even directly from the developing tool.
Upon designing the project architecture it was a clear objective to have two main parts separating the train and the evaluation/test parts – just like in case of any supervised machine learning project – in order to avoid common errors committed by mixing the two parts. We have also aimed at keeping the code as simple as possible.
Once the architecture was defined, the next step was to clean and transform the tweets’ text. The core transformations and feature engineering done were in order of execution:
The first model was generated using Bag of Words (BoW) with a Naive Bayes classifier. We soon realized that for the BoW we were forced to split the transformation step into two parts, primarily because when building the BoW itself it was necessary to also train it. Thus if we wanted to fully split the transformation and the training part, we were forced to split the transformation in pre-transform and transform.
After experimenting with some models like Random Forest and Support Vector Machine (SVM), we started exploring other alternatives instead, such as Word2Vec. After some research we found out that Word2Vec is basically a neural network with a couple of layers. The basic idea is that two words are considered similar – and thus they will have similar vector representation – if they have similar neighbours (neighbour of a word understood as the words that surround this word). In that sense, we had the chance to work with a hybrid model with a part of a seemingly neural network and another part with a classical classifier, which could be SVM or Random Forest. Regarding the integration with the architecture defined, Word2Vec had a similar problem as BoW had: it had to be trained before transforming the data. Also Word2Vec required that the data was tokenized and transformed as a vector.
The last step we made was the tuning of the hyperparameters of both SVM and Random Forest. For the first one, we have also developed a normalization in order to ensure the model was receiving the correct data during the training. As happened with the BoW and Word2Vec, the normalization had a part that is considered training so we had to split it too to avoid errors. Finally, we have used the GridSearchCV library to tune up the hyperparameters for both SVM and Random Forest. For the SVM, a RBF kernel was used and C (penalty parameter of the error term) and Gamma (Kernel coefficient) were tuned. For Random Forest the maximum depth used and the number of estimators were also tuned.
The chart below presents the basic structure of the final project architecture from high perspective. The main idea was to separate the different parts of the machine learning pipeline – such as the data load, data transformation, model training, model evaluation, and test check – all translated into four different Python classes. These four classes are discussed below the chart.
The first class imports the dataset and returns it into a Pandas dataframe. This separation was made serving generalization, as the dataset does not necessarily come from a .csv file, but could come from other source. We opted for this, as first we have received the English tweets dataset, and received the Spanish later during the course – at that point in an unknown format.
As mentioned earlier, given that we had to both train the BoW, the Word2Vec and/or had to normalize, it was necessary to separate the transformation class’s processes in two parts. Firstly, the code transforms the data itself. After that, the user is supposed to train the BoW, Word2Vec or normalizator. Once done, there is a second function to be called in order to transform the data accordingly. The reason behind was that we wanted to ensure that both training and test executes the exact transformations to minimize functional errors. Given that one of our goals was also looking for flexibility, the architecture of the second transformation function allows the user to decide the usage combination of BoW and/or Word2Vec and/or normalization.
The third class does the training for BoW, Word2Vec, normalization, and even optimization. After training, the model is stored in this class.
Finally, the fourth class performs all the calls to the different parts explained above and depending on the parameters of the calls it can optimize the hyperparameters, train, validate, test a model, and/or generate the required output.
For the validation test of the model, the configuration used was test_size=20%, validation_size=25%, and n_iterations=10. Regarding the results, we first present the hyperparameters tuning using a heatmap. Then, choosing the best parameters we trained, validate and test. It is also shown the results for the best train and validation and the final result for the test.
Best Hyperparams: max_depth = 11; n_estimators = 483. The results obtained with this hyperparameters are:
Best Hyperparams: C =<PHONE_NUMBER>775606, gamma = 3.792690190732254e-05. The results obtained with this hyperparameters are:
Best Hyperparams: C = 1.4384498882876628, gamma = 0.00615848211066026. The results obtained with this hyperparameters are:
Best Hyperparams: C = 1.4384498882876628, gamma = 0.00615848211066026. The results obtained with this hyperparameters are:
Having the results evaluated, the main conclusion is that even we tried multiple combinations on models and hyperparameters, we were getting mediocre results. Comparing the current results with the one we got in the version uploaded to Kaggle we may conclude that we had overfitting on the first test result we uploaded. For the Kaggle version, we used Random Forest with no depth limit and 1000 trees.
The best model without the overfitting done in case of the Kaggle version is the combination of Word2Vec and BoW and train the dataset using SVM with the hyperparameters C = 1.44 and gamma = 0.006.
It has to be noted that the three labels in the dataset were disproportionate and the tweets were not annotated coherently, which does have an effect on the whole model. For instance, out of the 105 tweets in our dataset about the Spanair accident ("Así fue el accidente del vuelo 5022 de Spanair...") 64 were negatively and 41 were neutrally annotated. Also, our model might have fallen for overfitting. In order to improve the model's results performance, the following steps could be taken:
An ad hoc analysis of an unbalanced dataset, or What was happening with Iberia?
The Spanish tweets dataset contains 7867 tweets from October 25, 2017 to January 8, 2018 downloaded using the keywords AirEurope, Aireurope (sic!), Iberia, Norwegianairline, Ryanair, and Spanair. However, the appeareance of the airlines is rather hectic. The table below contains these airlines, and some others, which popped up during the analysis.
| airline | number of mentions |
|---|---|
| Iberia |
5100 |
| Ryanair | 1938 |
| Vueling | 204 |
| Spanair |
151 |
| AirEuropa | 40 |
| Norwegian | 27 |
| Jetblue | 1 |
The tweets' sentiments were annotated by the students of the postgraduate course. The 48.1 percent of the tweets were annotated as negative, 32.5 percent as neutral, and 19.4 percent as positive. The chart below shows the distribution of the number of tweets by each sentiment by day. The day with the highest traffic was December 14, 2017 – most of the tweets published being negative.
If we look for the airlines mentioned, we see that it was Iberia, which was mentioned mostly on December 14, 2017. As out of all airlines mostly Iberia and Ryanair were mentioned in the whole dataset, we are focusing on these two airlines.
In what context were the airlines mentioned? The table below shows the rank of each word in terms of number of ocurrence by airline. The word "url" are used after having all links replaced by this word. The URLs part of this analysis will look into the explanation of the high number of links in the dataset.
| rank | Iberia | Ryanair | Vueling | Spanair | in whole dataset |
|---|---|---|---|---|---|
| 1 | @iberia | ryanair | url | spanair | url |
| 2 | url | url | @vueling | url | @iberia |
| 3 | iberia | @ryanair | vueling | accidente | iberia |
| 4 | vuelo | pilotos | @iberia | españa | ryanair |
| 5 | hola | huelga | iberia | video | vuelo |
| 6 | solo | vuelos | ryanair | vuelo | hola |
| 7 | gracias | vuelo | @ryanair | letal | @ryanair |
| 8 | mejor | españa | compañía | cadas | madrid |
| 9 | destino | avión | vuelo | barajas | vuelos |
| 10 | madrid | euros | vuelos | canal | gracias |
Most of the airlines are mentioned using the "@" sign in the tweets suggesting that by using Twitter's organic mention sign people wanted to communicate with the airline companies – except for Spanair, but it is reasonable from users that they do not want to communicate with a defunct company. The extensive use of "@"s is especially true for Iberia being @iberia the most frequently used word related to Iberia. Nevertheless, the rest of the most frequent words at Iberia do not seem to have negative connotation. As for Ryanair, we see that probably a strike was going on (maybe that of pilots?), where flights were cancelled. As for Vueling, practically this company was mentioned related to the other airlines, we can see that both Ryanair and Iberia were mentioned along with Vueling. Spanair appeared as the accident had the anniversary.
Now that we have a broad picture of our dataset, in order to understand exactly what happened to Iberia during the analyzed period, in the next part we take a dive into text analysis using a widely used method: topic modelling.
Happy anniversary Iberia
For a greater depth about the tweets, we decided to use a topic modelling algorithm. The analysis was done with the Latent Dirichlet Allocation (LDA) model in order to extract the volume and percentage contribution of each topic to get an idea of how important a topic is. Using the tool of LDA we get the following interactive visualization. To open the tool in a new tab click here.
The Coherence score was used to select appropriate number of topics. After several iterations we decided that the best is to have 20 topics. Some of the topics are overlapping but the important and different ones for the sake of this analysis appear clearly separated.
Inferring the topics from keywords
After looking into all the keywords in the above graph the following topic names were deduced. For each tweet, a dominant topic was assigned. Tweets with a topic probability lower than 20 percent were left uncategorized. Who did topic modelling before knows that the topics are almost never 100 percent clean and clear, thus we have left some question marks in the picture below presenting the topics.
Iberia
In the following plot all the topics and the percent of appearances are displayed (please note that the chart was insipred by Christian Rudder's chart in Dataclysm about the word use of OkCupid profiles). The X axis represents Iberia percentage and the Y axis represents the percentage from all the other companies together. Topics below the line are more important in Iberia dataset and topics above the line are more important for the other airlines.
The most relevant topics in Iberia are:
The chart suggests that:
Ryanair
Similarly, we had a look at the words used related to Ryanair vs. all other companies.
the most relevant topics in Ryanair are:
The timeline analysis indicates the strike call was around December 11 and December 17. The strike was cancelled around December 18 and December 20. See more information here.
From October 25 to October 27 Ryanair delayed to January its new hand luggage policy, see more information here.
What URLs were the users sharing?
In the dataset of 7867 tweets, there were 5448 URLs. Some of the tweets had not a single URL, but a few had even three:
| number of URLs | number of tweets |
|---|---|
| 0 | 2684 |
| 1 | 4745 |
| 2 | 361 |
| 3 | 4 |
As Twitter by default shortens links, we have used a small script using the Requests library to unshorten them, so instead of "https://t.co/8c66y40ejv" we would see "https://www.grandesmedios.com/accidente-vuelo-5022-spanair/". The snippet had a few seconds of sleeping built in in order to mimic human behaviour and trick websites in order not to be rejected.
Out of the 5448 links only 34 were still working (or curling was not omitted). Most of the received long URLs were leading to Twitter posts or pictures, and only a handful lead to a news portal or a company website. A possible explanation for the few received long URLs could be – apart from the obvious that our URL unshortener code is wrong, – that the links lead to Twitter user's profiles, which do not exist any more (recall that most of the dataset is from last year). There is only one domain appearing more than once in the dataset: "hipertextual.com" coming from campaigns indicated by the ending of the link ("utm_medium=feed&utm_source=feedpress.me&utm_campaign=Feed:+hipertextual").
Having a look at those tweets, which had three links in them, it turned out that three out of four were published by the same user: @joselitoba5. (These tweets are respectively: tweet 1, tweet 2, and tweet 3.) Among the shared links of this user appear the hipertextual.com domain. If we have a look at the content of that site, we see that it is fairly similar to the content published by @joselitoba5.
@joselitoba5 published 48 900 tweets and has 29 followers – it seems that activity does not pay off for this user. Or @joselitoba5 is a bot using popular content to generate traffic on the Hipertextual Sniply site. The next step of the analysis could be to detect bots. As the dataset has the tweet ID, using the "twitter.com/anyuser/status/{tweetid}" formula, we could get back the user name, and based on that using the Twitter API we could download the profile information of our tweets' authors, their number of followers, number of tweets posted and age of profile, and a metric could be created trying to figure out whether a user is a bot or not.
closing remarks
For the sake of this project, we have developed a project architecture fitting the needs we had. The modelling task was solved using Random Forest and Word2Vec, however, we are aware of the possible overfitting. Additional problem was the unbalanced dataset and the inconsistent annotation of the tweets. Having this project continued, we have to face these problems.
Continuing the analysis of the dataset, we would like to take a deeper dive into having a closer look of the bots issue: whether the presence of bots is really typical for the dataset, and if so, any of the airlines were using bots to spread promotional materials, or were they merely victims of the operation of a botnet.


To assist non-exert users we provide an alternative to creating layers out of SPARQL endpoints using predefined queries. To create such a layer we use the button in Sextant's main menu bar and then select Predefined Queries as shown in the figure below.
We then have to fill in the following form to create our layer. First we need to provide the URI of an endpoint in the field URI and the port it listens to in the field Port:80 (by default the port is set to 80). We can then click the Connect button to communicate with the SPARQL endpoint and get a list of the available predefined queries in plain text as shown below. Then by simple selecting one of the queries we can create the corresponding layer.
These predefined queries are created by experts to assist simple users in visualizing the data in a SPARQL endpoint. Predefined queries follow the ontology shown in the image below.
Using this ontology, we can add predefined queries as data in a SPARQL endpoint. Below we have an example of a predefined query expressed in triple patterns:
<query/id/0> rdf:type <http://geo.linkedopendata.gr/query/ontology/predefinedQuery> .
<query/id/0> <http://geo.linkedopendata.gr/query/ontology/hasLabel> "plain text description" .
<query/id/0> <http://geo.linkedopendata.gr/query/ontology/isTemporal> "true/false" .
<query/id/0> <http://geo.linkedopendata.gr/query/ontology/hasText> "SPARQL query" .


---
layout: page
title: The Team
subtitle: The following are team members of the project.
---
- Name: Ms. Hope Mbelwa
- Position: Research Assistant
- Research title: Image Based Poultry Disease Detection using Deep Convolutional Neural Networks
- Degree Program: Master’s in Information and Communication Science and Engineering (ICSE)
- Name: Ms. Evelyn Mshana
- Position: Research Assistant
- Research title: Online Platform for Linking Farmers and Agro-Vet Services in Tanzania
- Degree Program: Master’s in Information and Communication Science and Engineering (ICSE)
- Name: Mr. Beston Lufyagila
- Position: Research Assistant
- Research title:IoT-Powered System for Environmental Conditions Monitoring in Poultry House: A case of Tanzania
- Degree Program: Master’s in Information and Communication Science and Engineering (ICSE)
- Name: Ms. Martha Shapa
- Position: Research Assistant
- Research title: Mobile-Based Decision Support System for Poultry Farmers
- Degree Program: Master’s in Information and Communication Science and Engineering (ICSE)
- Name: Mr. Loyani Loyani
- Position: Research Assistant
- Research title: A Quantification Model against Tuta Absoluta Effects on Tomato Plants: A Computer Vision Approach
- Degree Program: Master’s in Information and Communication Science and Engineering (ICSE)


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Puff
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Celebrity
This was the most grievous loss, the most heartfelt tragedy, I encountered on my weekend quest to see the Star Wars Episode 1 preview in a movie theater. Granted, it doesn't rate up there with, say, having to face a ticked off dragon guarding the castle with the damsel in distress, but every quest has its hazards and horrors, or you'd just be able to pick up the, uh, quested object down at the Kwik-E-Mart.
Basically, in a mild fit of mania on Friday, I wandered to some neighborhood movie theaters, asking whether they were showing the Preview, and, if so, with what movie. Most of the answers were disappointing. The first place I went to said they were showing it with "Celebrity." At that point in the day, I actually wanted to see that movie, but the show wouldn't start for three hours. Subsequent theaters had it with that Brad Pitt in a tux movie, or with "Enemy of the State", which I'd seen in an earlier Preview sighting attempt. One theater said they were showing it, but they weren't sure with which movie. At the end of this long, arduous road, one theater's ticket taker said, yeah, we're showing it, try "Celebrity" at 3:30. This smarmy ticket taker, looking a lot like Jon Lovitz with a goatee and less hair, lied to me. In this age of the Net, with free-floating campaigns and vendettas to cause material and psychological damage to any number of random entities, from the deserving Circuit City/Divx to Bob, the convenience store clerk who ticked off an 3l33t3 d00d because the Slurpee just didn't have enough syrup, I'm going to show restraint and not -- repeat, not -- call down a fatwa against this movie theater in the East Village that's not the one next to Webster Hall, but a couple of blocks away. Except for this incident, I've had good movie-going experiences there.
Digression aside, "Celebrity" was awful. Well, it's not as bad as "Shadows and Fog", so it doesn't qualify as the Worst Woody Allen Movie Of All Time, but it's up there. This is basically supposed to be Woody's meditation on the idea of celebrity. It plays somewhat more like a cross between "Annie Hall" and "Husbands and Wives" with a number of celebrity cameos, but with all the old-fashioned movie-goodness leached out along with the color.
The main characters are Woody Allen, played by Kenneth Branaugh, and his ex-wife, played by Judy Davis. The movie has a self-referencing moment in it, when there's a film premiere from a pretentious director who always shoots in black and white, but a more interesting self-reference may be to have Branaugh give his Woody Allen character some sort of Hamlet spin, but that'd hark too much back to those early, funny films. Branaugh does such a shockingly good job being Woody Allen, there's really no need for Woody to step in front of the camera again.
In any case, there was this divorce that takes place before the movie starts, with the Woody Allen character wanting to sow his oats and the Judy Davis character trying to recover. Various hijinks ensue, as the Woody Allen character, in this incarnation, is a movie industry reporter, chasing after various starlets and aspiring starlets. The exploration of celebrity is touched on briefly in his various encounters with actors and actresses, perhaps most prominently when he meets Leonardo DiCaprio playing, uh, Leonardo DiCaprio. There's also Charlize Theron as a supermodel, which made me realize that either Branaugh is really short or Theron is really tall. Oh, and Winona Ryder is using a Wonderbra nowadays. You can learn more about celebrity by reading the back cover of the historian Daniel Boorstin's book, "The Image" (which is where celebrity is first defined as being famous for being famous).
Anyway, the fates of the Woody Allen and Judy Davis characters take their expected trajectories, with one expected happiness on the road to loneliness, and vice versa. There's nothing much to see here. The story of divergent was better told in "Annie Hall", the one about separation in "Husbands and Wives".
Oh, I finally did see the Star Wars preview the next day, unfortunately not in a movie theater, but as an mpeg.
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<steps>
The <steps>
element provides the main content of a task topic. The task
is described as a series of steps that the user must follow to accomplish the task. At
least one <step>
element is required inside the
<steps>
element.
Category: Task elements


Kenya landslides kill a dozen people
by AFPAt least 12 people were killed in Kenya when their homes were swept away in a landslide during ferocious rainstorms, local government officials said Saturday.
Their homes were hit overnight Friday amid torrential rains in Kenya’s West Pokot region, 350 kilometres (220 miles) northwest of the capital Nairobi.
“Twelve bodies have been recovered, and a search for more is going on,” West Pokot County Commissioner Apollo Okello told journalists on Saturday.
“The challenge we are facing is the heavy rains, but we are trying our best.”
Okello said that two children were pulled out alive from the smashed wreckage of their mud-covered homes.
“They have been rushed to hospital,” he said.
Rescue efforts have been delayed because roads have been cut and bridges closed after streams turned into raging torrents.
“Massive landslides reported in various areas of West Pokot County following a heavy downpour,” Kenya Red Cross said in a message, adding that it’s emergency response teams had deployed to help.
But police officers on the ground said they feared the toll could rise. Rescue efforts to dig bodies out of the dirt continued.
It is not only Kenya that is affected. The landslides come amid weeks of destructive rains and flooding across East Africa.
Violent downpours have displaced tens of thousands in Somalia, submerged whole towns in South Sudan and killed dozens in flash floods and landslides in Ethiopia and Tanzania too.
Close to a million people in South Sudan alone are affected by growing fears of disease and starvation.
Floods hit East Africa regularly, but scientists say that it has been exacerbated by a powerful climate phenomenon in the Indian Ocean stronger than any seen in years.
The extreme weather is blamed on the Indian Ocean Dipole — a climate system defined by the difference in sea surface temperature between western and eastern areas of the ocean.
The ocean off East Africa is currently far warmer than usual, resulting in higher evaporation resulting in the rain over the continent.


Samsung Odyssey+ VR HMD Is Down to $230, Will Let You Play Half-Life: Alyx
by Alessio PalumboThe Samsung Odyssey+ head-mounted display (HMD) is now at its lowest price yet on Amazon, where you can grab it for $230. When the device launched a year ago, it was priced at $499.
The Samsung Odyssey+ is considered one of the best Virtual Reality headsets available when you factor in the hardware specifications and the relatively low price. The resolution is the same as the Valve Index, for instance, and the display is an AMOLED instead of the Index's LCD, which means it's got better contrast and blacks. Where the Valve Index completely trumps the Odyssey+ is in the controller tracking and in the Field of View (FoV) areas, but then again the Index would cost you over four times as much.
The Samsung Odyssey+, technically a Windows Mixed Reality headset, is also compatible with the SteamVR platform, giving you access to thousands of applications and games. Among them, of course, the newly announced Half-Life: Alyx, which is already rekindling interest in Virtual Reality ahead of its March 2020 launch.
For more on the VR device, check out the official feature trailer and complete specifications below.
Platform
Microsoft Windows Mixed Reality and SteamVR
Display
Dual 3.5” AMOLED; 1440*1600@90Hz/60Hz
Interface
HDMI2.0+USB3.0 Interface Bounded Cable (4M length)
Lens
Single Fresnel
Field of View
110˚
IPD
60 - 72mm range
Camera
6 DOF camera * 2
Sensor
6-Axis ACC & Gyro; 3-Axis Compass; Proximity sensor; IPD Sensor
Acoustics
2 MIC support Cortana; built-in headphone (AKG Brand)
User Interface
Volume; IPD adjustment
Tracking Area
No Limit (Inside-out)
Built-in Mic
Array MICs
Built-in Audio
Spatial Audio (AKG)
Controller
6 DOF Controller (L&R) / Xbox One Controller Support
Connections
HDMI, USB3.0
Product Dimensions (W x H x D)
7.64" x 5.08" x 4.30" (HMD Body)
Package Dimensions (W x H x D)
7.34" x 12.04" x 15.0"
Product Weight (lb.)
1.31lbs. (w/o cable)
*Cable weight: 0.45lbs.
Box Weight (lb.)
4.73lbs.


{% extends 'base.html' %} {% load static %} {% load blog_tags %} {% block content %} Dude You’re Getting a Telescope There is a moment in the life of any aspiring astronomer that it is time to buy that first Social life Enjoy your social life together Politics Be a part of politics Food Let the food be finished {% for post in posts %} {% for cat in post.category.all %} {{ cat.name }} {% if not forloop.last %},{% endif %} {% endfor %} {{post.author.get_full_name}} {{post.published_date|date:"d M Y"}} {{post.counted_views}} Views {% comments_count post.id %} Comments {{post.title}} {{post.content|excerpt:15}} View More {% endfor %} {% if posts.has_previous %} {% endif %} {% for i in posts.paginator.page_range %} {% if posts.number == i %} {{i}} {% else %} {{i}} {% endif %} {% endfor %} {% if posts.has_next %} {% endif %} {% include 'blog/blog-search.html' %} {% include 'blog/blog-writer.html' %} {% postcategories %} {% endblock %}
There is a moment in the life of any aspiring astronomer that it is time to buy that first
Enjoy your social life together
Be a part of politics
Let the food be finished
{{post.author.get_full_name}}
{{post.published_date|date:"d M Y"}}
{{post.counted_views}} Views
{% comments_count post.id %} Comments
{{post.content|excerpt:15}}


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My name is Niil Öhlin and I am an engineering student at Luleå tekniska universitet, Sweden. My intrests is mainly programming. I like high level programming languages like ruby and python.


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Class: Aws::SageMaker::Types::RecommendationJobInputConfig
| Relationships & Source Files | |
| Super Chains via Extension / Inclusion / Inheritance | |
|
Class Chain:
self,
Struct
|
|
|
Instance Chain:
self,
::Aws::Structure ,
Struct
|
|
| Inherits: |
Struct
|
| Defined in: | gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb |
Overview
The input configuration of the recommendation job.
Constant Summary
Instance Attribute Summary
-
#container_config ⇒ Types::RecommendationJobContainerConfig
rw
Specifies mandatory fields for running an Inference Recommender job.
-
#endpoint_configurations ⇒ Array<Types::EndpointInputConfiguration>
rw
Specifies the endpoint configuration to use for a job.
-
#endpoints ⇒ Array<Types::EndpointInfo>
rw
Existing customer endpoints on which to run an Inference Recommender job.
-
#job_duration_in_seconds ⇒ Integer
rw
Specifies the maximum duration of the job, in seconds.
-
#model_name ⇒ String
rw
The name of the created model.
-
#model_package_version_arn ⇒ String
rw
The Amazon
::Aws::SageMaker::Resource
Name (ARN) of a versioned model package. -
#resource_limit ⇒ Types::RecommendationJobResourceLimit
rw
Defines the resource limit of the job.
-
#traffic_pattern ⇒ Types::TrafficPattern
rw
Specifies the traffic pattern of the job.
-
#volume_kms_key_id ⇒ String
rw
The Amazon
::Aws::SageMaker::Resource
Name (ARN) of a Amazon Web Services Key Management Service (Amazon Web Services::Aws::KMS
) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. -
#vpc_config ⇒ Types::RecommendationJobVpcConfig
rw
Inference Recommender provisions
::Aws::SageMaker
endpoints with access to VPC in the inference recommendation job.
Instance Method Summary
::Aws::Structure
- Included
| #to_hash | Alias for Aws::Structure#to_h. |
Instance Attribute Details
#container_config ⇒ Types::RecommendationJobContainerConfig (rw)
Specifies mandatory fields for running an Inference Recommender job.
The fields specified in ContainerConfig
override the corresponding
fields in the model package.
# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 34563
class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config, :model_name) SENSITIVE = [] include Aws::Structure end
#endpoint_configurations ⇒ Array
<Types::EndpointInputConfiguration> (rw)
Specifies the endpoint configuration to use for a job.
# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 34563
class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config, :model_name) SENSITIVE = [] include Aws::Structure end
#endpoints ⇒ Array
<Types::EndpointInfo> (rw)
Existing customer endpoints on which to run an Inference Recommender job.
# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 34563
class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config, :model_name) SENSITIVE = [] include Aws::Structure end
#job_duration_in_seconds ⇒ Integer
(rw)
Specifies the maximum duration of the job, in seconds. The maximum value is 7200.
# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 34563
class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config, :model_name) SENSITIVE = [] include Aws::Structure end
#model_name ⇒ String
(rw)
The name of the created model.
# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 34563
class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config, :model_name) SENSITIVE = [] include Aws::Structure end
#model_package_version_arn ⇒ String
(rw)
The Amazon ::Aws::SageMaker::Resource
Name (ARN) of a versioned model package.
# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 34563
class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config, :model_name) SENSITIVE = [] include Aws::Structure end
#resource_limit ⇒ Types::RecommendationJobResourceLimit (rw)
Defines the resource limit of the job.
# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 34563
class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config, :model_name) SENSITIVE = [] include Aws::Structure end
#traffic_pattern ⇒ Types::TrafficPattern (rw)
Specifies the traffic pattern of the job.
# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 34563
class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config, :model_name) SENSITIVE = [] include Aws::Structure end
#volume_kms_key_id ⇒ String
(rw)
The Amazon ::Aws::SageMaker::Resource
Name (ARN) of a Amazon Web Services Key
Management Service (Amazon Web Services ::Aws::KMS
) key that Amazon
::Aws::SageMaker
uses to encrypt data on the storage volume attached to the
ML compute instance that hosts the endpoint. This key will be passed
to ::Aws::SageMaker
Hosting for endpoint creation.
The SageMaker execution role must have kms:CreateGrant
permission
in order to encrypt data on the storage volume of the endpoints
created for inference recommendation. The inference recommendation
job will fail asynchronously during endpoint configuration creation
if the role passed does not have kms:CreateGrant
permission.
The KmsKeyId
can be any of the following formats:
- //
::Aws::KMS
Key ID
"1234abcd-12ab-34cd-56ef-1234567890ab"
- // Amazon Resource Name (ARN) of a
::Aws::KMS
Key
"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"
- //
::Aws::KMS
Key Alias
"alias/ExampleAlias"
- // Amazon Resource Name (ARN) of a
::Aws::KMS
Key Alias
"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"
For more information about key identifiers, see Key identifiers
(KeyID) in the Amazon Web Services Key Management Service
(Amazon Web Services ::Aws::KMS
) documentation.
# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 34563
class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config, :model_name) SENSITIVE = [] include Aws::Structure end
#vpc_config ⇒ Types::RecommendationJobVpcConfig (rw)
Inference Recommender provisions ::Aws::SageMaker
endpoints with access to
VPC in the inference recommendation job.
# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 34563
class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config, :model_name) SENSITIVE = [] include Aws::Structure end


{% set pageTitle = "Check that vitamin D is suitable for you" %} {% set mainClasses = "nhsuk-main-wrapper--s" %} {% set version = "v2" %} {% extends "includes/layout.html" %} {% block backLink %}
{% endblock %} {% block content %}Do not use this service if you:
Do not use this service if you:
You should not use this service if you have any of these conditions:
Read how to take vitamin D supplements safely on GOV.UK.
You must not use this service:
Discuss this with your doctor the next time you talk to them.
If you think that vitamin D is suitable for you, please continue.
Continue


--- layout: default title: Yuchen's Blog --- {% for post in site.posts %}
{{ post.date | date_to_long_string }}


Documentation for classes includes syntax, usage information, and code samples for methods, properties, and event handlers and listeners for those APIs that belong to a specific class in ActionScript. The classes are listed alphabetically. If you are not sure to which class a certain method or property belongs, you can look it up in the Index.
| Class | Package | Description | |
|---|---|---|---|
| AfterCreateEvent
| org.restfulx.events | This event is dispatched when an instance of RxModel has been created successfully. | |
| AfterDestroyEvent
| org.restfulx.events | This event is dispatched when an instance of RxModel has been destroyed successfully. | |
| AfterSaveEvent
| org.restfulx.events | This event is dispatched when an instance of RxModel has been created successfully. | |
| AfterUpdateEvent
| org.restfulx.events | This event is dispatched when an instance of RxModel has been updated successfully. | |
| AIRServiceProvider
| org.restfulx.services.air | AIR Service Provider implementation. | |
| AS3GAEHTTPServiceProvider
| org.restfulx.services.as3http | AS3 HTTP Client based GAE XML-over-HTTP service provider. | |
| AS3JSONHTTPServiceProvider
| org.restfulx.services.as3http | AS3 HTTP Client based JSON-over-HTTP service provider. | |
| AS3XMLHTTPServiceProvider
| org.restfulx.services.as3http | AS3 HTTP Client based XML-over-HTTP service provider. | |
| AuxAIRController
| org.restfulx.controllers | Custom AIR controller that allows performing arbitrary operations (as opposed to CRUD on models) against local SQLite database. | |
| AuxHTTPController
| org.restfulx.controllers | Custom HTTP controller that allows sending arbitrary data (as opposed to models) over HTTP faking PUT and DELETE. | |
| BinaryAttachment
| org.restfulx.utils | BinaryAttachments work much the same way RxFileReferences do, except they allow you to attach arbitrary binary data to models instead of files. | |
| CacheController
| org.restfulx.controllers | In-memory model data store. | |
| CacheUpdateEvent
| org.restfulx.events | This event is dispatched Rx Models cache gets updated and can be used to selectively refresh data providers, etc. | |
| ChangeController
| org.restfulx.controllers | If Synchronization is enabled, Change controller can be hooked up to Rx.changes to perform synchronization between 2 different service providers. | |
| ChangeResponder
| org.restfulx.services | This responder hanldes synchronization responses from the destination service provider and syncs successful operations back to source service provider and/or reports relevant errors | |
| CommandExecutionEvent
| org.restfulx.events | Generic execution event (used by commands). | |
| CommandsController
| org.restfulx.controllers | Manages registered commands (classes that implement org.restfulx.controllers.ICommand). | |
| CommandsEventDispatcher
| org.restfulx.commands | Manages restfulx command related event registration. | |
| CouchDBJSONSerializer
| org.restfulx.serializers |
Serialises RxModel instances to JSON and back according to
CouchDB conventions. |
|
| DateTextInput
| org.restfulx.components.rx | ||
| DateTimeTextInput
| org.restfulx.components.rx | ||
| DirectCouchDBHTTPServiceProvider
| org.restfulx.services.as3http | Direct CouchDB Service Provider. | |
| GAEHTTPServiceProvider
| org.restfulx.services.http | HTTPService based GAE XML-over-HTTP service provider. | |
| GAEXMLSerializer
| org.restfulx.serializers |
Serialises RxModel instances to XML and back. |
|
| GenericSerializer
| org.restfulx.serializers | GenericSerializer groups together a few handy functions that are common, useful to all serializers. | |
| GenericServiceErrors
| org.restfulx.services | Basic IServiceErrors implementation that effectively has oerrors. | |
| ICommand
| org.restfulx.commands |
As per the command design pattern, commands are expected to implement a
simple interface with execute() function defined. |
|
| IFunctionalResponder
| org.restfulx.services | If a responder delegates final response processing to an arbitrary function, this interface allows us to get access to that handler function. | |
| Inflector
| org.restfulx.utils | AS3 CakePHP inflector implementation. | |
| ISerializer
| org.restfulx.serializers | Serves as a contract between various serializers and the rest of the framework. | |
| IServiceErrors
| org.restfulx.services | Must be implemented by specific Service providers to return UI consumable errors. | |
| IServiceProvider
| org.restfulx.services | This interface represents the core contract between service providers (such as HTTP, AIR, etc) and the rest of the framework. | |
| ISyncingServiceProvider
| org.restfulx.services | This interface identifies Service Providers that are capable of tracking synchronization related metadata. | |
| IVersioningServiceProvider
| org.restfulx.services | This interface adds versioning to the contract between service providers (such as HTTP, AIR, etc) and the rest of the framework. | |
| JSONHTTPServiceProvider
| org.restfulx.services.http | JSON-over-HTTP service provider based on Flex HTTPService. | |
| JSONSerializer
| org.restfulx.serializers |
Serialises RxModel instances to JSON and back. |
|
| MockAIRServiceProvider
| org.restfulx.services.mock | Adds testing specific methods to AIRServiceProvider. | |
| MockAuxHTTPController
| org.restfulx.controllers.mock |
This class allows re-routing of AuxHTTPController send
method to the specified Rx.httpControllerHandler function. |
|
| MockDirectCouchDBHTTPServiceProvider
| org.restfulx.services.mock | Adds testing specific methods to DirectCouchDBHTTPServiceProvider. | |
| MockJSONHTTPServiceProvider
| org.restfulx.services.mock | Adds testing specific methods to JSONHTTPServiceProvider. | |
| MockXMLHTTPServiceProvider
| org.restfulx.services.mock | Testing specific XMLHTTPServiceProvider. | |
| ModelsCollection
| org.restfulx.collections | Adds a few handy methods to ArrayCollection class to simplify working with model objects. | |
| ModelsController
| org.restfulx.controllers | Provides high level CRUD functionality. | |
| ModelsMetadata
| org.restfulx.utils | All runtime metadata used by the framework about application models is stored in this class. | |
| MoneyTextInput
| org.restfulx.components.rx | ||
| MultiPartRequestBuilder
| org.restfulx.utils | This class performs custom multi-part request construction for binary attachments. | |
| PullEndEvent
| org.restfulx.events | This event is dispatched when pull synchronization has been finished | |
| PullStartEvent
| org.restfulx.events | This event is dispatched when pull synchronization has been finished | |
| PushEndEvent
| org.restfulx.events | This event is dispatched when push synchronization has been finished | |
| PushErrorEvent
| org.restfulx.events | This event is dispatched when there's an error during push synchronization process | |
| PushItemEvent
| org.restfulx.events | This event is dispatched when an RxModel instance is about to be synchronized | |
| PushStartEvent
| org.restfulx.events | This event is dispatched when push synchronization is about to begin | |
| Rx
| org.restfulx | Provides central access to a number of frequently used subsystems, configuration options and helpers. | |
| RxApplicationController
| org.restfulx.controllers | This is the primary extension point for Flex/AIR applications based on the framework. | |
| RxAutoComplete
| org.restfulx.components.rx | This class adds integrated search capability to your Flex/AIR applications. | |
| RxAutoCompleteItemEvent
| org.restfulx.events | Dispatched by RxAutoComplete component | |
| RxCollection
| org.restfulx.collections |
Adds a few handy general purpose methods to
mx.collections.ArrayCollection . |
|
| RxFileReference
| org.restfulx.utils | Allows Flash file references to be attached to models. | |
| RxModel
| org.restfulx.models | Encapsulates properties common to all model objects and wraps around a few Rx.models.methods to shorten access. | |
| RxTreeModel
| org.restfulx.models | Allows tree representation (parent->children) relationship between instances of the same model type. | |
| RxUtils
| org.restfulx.utils | Various Utilities. | |
| SerializersController
| org.restfulx.controllers | Provides centralized access to comonly used serializers. | |
| ServerPushController
| org.restfulx.controllers | This controller adds support for receiving messages from servers capable of pushing messages, e.g. | |
| ServerPushEvent
| org.restfulx.events | This event is dispatched when a new message has been pushed from the server | |
| ServiceCallStartEvent
| org.restfulx.events | This event is dispatched when service provider call is about to be made. | |
| ServiceCallStopEvent
| org.restfulx.events | This event is dispatched when the responser from the service provider has been received. | |
| ServiceErrorEvent
| org.restfulx.events | This event is dispatched when the service provider received an error. | |
| ServiceErrorValidator
| org.restfulx.validators | Flex Validator that can be used to display errors that are stored in IServiceErrors format. | |
| ServiceResponder
| org.restfulx.services | Central response manager for RESTful CRUD operations. | |
| ServicesController
| org.restfulx.controllers | Provides centralized access to currently available services. | |
| TypedArray
| org.restfulx.utils | An array of items where we know what type of models it contains. | |
| UndoRedoController
| org.restfulx.controllers | Adds undo redo support to the application. | |
| UndoRedoResponder
| org.restfulx.services | Undo/Redo responder wraps around another Functional responder (typically ServiceResponder) and allows us to attach a different handler function to the responder than was originally provided. | |
| UUID
| org.restfulx.utils | This class implements a binary version of UUIDs as specified in the RFC. | |
| VOSerializer
| org.restfulx.serializers |
Serializes RxModel instances to Value Objects and back. |
|
| XMLHTTPServiceProvider
| org.restfulx.services.http | XML-over-HTTP service provider based on Flex HTTPService. | |
| XMLSerializer
| org.restfulx.serializers |
Serialises RxModel instances to XML and back. |
|
| XMLServiceErrors
| org.restfulx.services | XMLHTTPServiceProvider specific IServiceErrors implementation. | |
| XRx
| org.restfulx | Provides central access to useful extras that cannot be linked into Rx, such as AIR-only RestfulX features. |


© Bruce Wilcox<EMAIL_ADDRESS>brilligunderstanding.com
Revision 1/7/2016 cs7.1
ChatScript comes natively with full English support. If you want to use a different language you need a variety of things. * Pos-tagging support * Spell check support * Concepts in the language * LIVEDATA substitutions appropriate to the language * Patterns in the language * Output in the language
ChatScript has a command line parameter language=
that tells CS the language you intend. It defaults to ENGLISH
. The effects of this parameter are several. * If not ENGLISH, internal pos-tagging and parsing are disabled. * The system will use DICT/language
. * The system will use LIVEDATA/language
* The script compiler will automatically compile lines marked with the language (see language comments).
ChatScript supports two kinds of conditional compile comments. Single line comments look like this:
#ENGLISH this line will compile if the language is English but not if the language is GERMAN.
#GERMAN this line will not compile if the language is English but will compile if the language is GERMAN.
As always, such comments run til end of line. The other comment is the block comment like this:
##<<ENGLISH these lines will be compiled under English
until a normal closing block comment ##>>
Using conditional compilation, you can make English and other language versions of code sit side by side if you want to.
ChatScript supports UTF8, so making output or patterns in the language is entirely up to you. Ditto for LIVEDATA.
The dictionary file can be just a list of words of the language, one per line. You must list all conjugations of a word because there is no in-built support to figure that out.
If you want the POS values and lemmas (canonical form of a word), you will need a POS-tagger of some sort. While it is possible to hook in an external tagger via a web call, that will be noticably slower than an in-built system. ChatScript supports in-build TreeTagger system, which supports a number of languages. However, you can only use this if you have a commercial license. You can try it out using ^popen, as is done in the German bot, however it will be slow because it has to reinitialize TreeTagger for every sentence. The in-built system does not. A license (per language) is about $1000 and you can contact me if you want to arrange to use it.


The Pujanauski cousins are a beautiful family
Bruce & Jeanne
Cele & Mike
Cathy & Mike
Paul & Cindy
Therese & Doug
Amy & Rob
Chris & John
140


Ocala events
-
bold fresh movie tour
Pirate Radio | Trailer and Cast - Yahoo! Movies
Get the complete cast, production details, reviews and trailer of Pirate Radio on Yahoo! Movies. In the 1960s a group of 8 rogue DJs on a boat in the middle of .
http://movies.yahoo.com/movie/pirate-radio/Pirate Radio (2009) - IMDb
A period comedy about an illegal radio station in the North Sea in the 1960s. . Pirate Radio (2009) Poster .  IMDb Top Movies at Most Recent Highest Rank .
http://www.imdb.com/title/tt1131729/Pirate Radio (The Boat That Rocked) - Rotten Tomatoes
Review: The good cast and rollicking soundtrack eventually drown when this comic homage to . With Pirate Radio (released as The Boat That Rocked in the U.K.), . Curtis's movie is loosely based on the historical truths of the time, but it isn't .
http://www.rottentomatoes.com/m/pirate_radio/
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- Sponsored event
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Apr 6 - Downtown Disney
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Apr 11buick enclave cargo liners
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Mar 17congress and toxicology and meeting
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Bob Carr Performing Arts Center
Ocala's best venues
-
Pirate Radio Cast and Details
Are You Watching? Pirate Radio. Pirate Radio~Pirate Radio~http://movies. tvguide.com/pirate-radio/cast/299146~~~/images/badges/tvguide_badge.gif. Loading .
http://movies.tvguide.com/pirate-radio/cast/299146 -
Movie Review | 'Pirate Radio' - Movies - The New York Times
Nov 12, 2009 . Boys will be boys and often at top volume in Pirate Radio, Richard . of the awful "Love, Actually," another waste of a great cast) was behind .
http://movies.nytimes.com/2009/11/13/movies/13pirateradio.html -
Pirate Radio Review - CinemaBlend.com
The key to enjoying Pirate Radio is letting your mind idle. Sit back, relax and enjoy the film's highlights, the music and the cast. I could go through the spectacular .
http://www.cinemablend.com/reviews/Pirate-Radio-4296.htmlwhat does the medulla oblongata control
98 people's favorite
-
'Pirate Radio': Tune in for cast, soundtrack - USATODAY.com
Nov 12, 2009 . More retro than renegade, Pirate Radio is buoyed by spirited performances and infectious tunes.
http://usatoday30.usatoday.com/life/movies/reviews/2009-11-13-pirate13_ST_N.htm -
Pirate Radio :: rogerebert.com :: Reviews
Nov 11, 2009 . Before we get to the movie, let's assume you're near a computer that has iTunes. . From pirate radio stations anchored offshore, a steady stream of rock . Richard Curtis is good at handling large casts, establishing all the .
http://rogerebert.suntimes.com/apps/pbcs.dll/article?AID=/20091111/REVIEWS/911119998/1023


You Can Contribute to Open Source
Emily Stamey
Ways to contribute
- Creating your Own Project
- Pull Request on Github
- write an issue
- update documentation
- write code
- Hackathons
What Didn't Work for Me
- tree package
- blind approach
- language barrier
- hackathon #1
- short intro to projects
- everyone was familiar
- I stood on the sidelines
- hackathon #2
- trouble installing the vm
- team was actively helping
- only one unable to contribute
ME Being Prepared
I had to work to know what was going to be available.
- Know the available project(s)
- Review Documentation
- Install software
- organizers bring a thumb drive
Hackathon #3!
- Asked around ahead of time about the projects
- Found a supportive group
- Building a plug-in felt easier
- Gave myself Time
- 4 characters couldn't be flipped
- tried several times
- a month or so later...
I DID IT!!!
My package was deployed to IRC
There were some bugs
I fixed those too!
You can do this!
- find a place/group you're comfortable
- find a project
- it can be fun or silly, too!
- ask for help when you need it
- expect to ask more than once sometimes
You have support at Girl Develop It!
- Github classes
- Slack Channel


What channel are you looking at?
The Corporate User Interface should be applied according the guidelines found in the UX Library and in the Identity Manual. Although, the ways it should be appear differs slightly between target groups. An application used by our customers will for example require a more compact implementation than our "mobile first" approach for public market sites. Please use the decistion tree below to find out more about who to contact to find out more about how you could benefit from tools and technologies when creating a new digital presence.
If you need further help in finding your way through the options at hand, please contact the XXX-XXX and they'll give you a helping hand.


Easy list (ul and ol) styling.
Options to set list layout, spacings, indents and block elements. Ability to apply styles according to the list level.
Lists styled with these mixins can be aligned with Alignment.
Styles will be applied to the given $level. If $up is set to true, styles are also applied to sub-levels. Should be applied to an ul or ol element.
The list level. 0 is the root level.
Indicates whether styles are applied to sub-levels or not.
Sets the list layout. List-style and margin/paddings are resetted. Neccessary for all other list mixins to work properly. Should be used as a list-level content.
The type. Possible values:
Horizontal list. Includes a workaround (see source for details) which can lead to unexpected behaviour. If this is a problem, use horizontal-nofix, horizontal-fl or horizontal-fr instead (not supported, see source for details).
Vertical list.
List-specific gutter mixin, should be used instead of gutter in lists. Should be used as a list-level content.
Uses non-standard CSS, see source code for details.
inner or outer; outer gutter is the padding of li elements, inner gutter of block elements (see list-blicklink mixin) inside li elements.
Spacing, see Gutter.
Indent for the child list level. Should be used as a list-level content.
A number indicating the indent.
Makes all child elements of li elements a block element (eg display:block;). Should be used as a list-level content.


 Hebrews kiyor (Zechariah 12:6; R.V., “pan”), a fire-pan. Hebrews moqed (Psalm 102:3; R.V., “fire-brand”), properly a fagot. Hebrews yaqud (Isaiah 30:14), a burning mass on a hearth.

Hebrews kiyor (Zechariah 12:6; R.V., “pan”), a fire-pan.
Hebrews moqed (Psalm 102:3; R.V., “fire-brand”), properly a fagot.
Hebrews yaqud (Isaiah 30:14), a burning mass on a hearth.


--- layout: default ---
eGrad is the simplest Student Management System for Higher Education. It provides an interface to easily manage applications and student matriculations. With a "one-stop-shop" design, it gets data from central repositories (e.g. Ellucian Banner®, Box), reducing the amount of data duplication, allowing you to add an extra data layer to aid with collection and reporting of information.
eGrad allows students to file applications into each of your programs. Paired with a Central Authentication System (CAS), your students can easily login to eGrad, fill-out forms and upload files that can be reviewed by your program coordinators.
eGrad allows you to filter, organize, and score applications against a customizable rubric. Also, if required, it can be further sent to a pre-defined committee to review each application.


| Opcode |
Instruction |
Op/En |
64-Bit Mode |
Compat/Leg Mode |
Description |
| A8 ib |
TEST AL, imm8 |
I |
Valid |
Valid |
AND imm8 with AL; set SF, ZF, PF according to result. |
| A9 iw |
TEST AX, imm16 |
I |
Valid |
Valid |
AND imm16 with AX; set SF, ZF, PF according to result. |
| A9 id |
TEST EAX, imm32 |
I |
Valid |
Valid |
AND imm32 with EAX; set SF, ZF, PF according to result. |
| REX.W + A9 id |
TEST RAX, imm32 |
I |
Valid |
N.E. |
AND imm32 sign-extended to 64-bits with RAX; set SF, ZF, PF according to result. |
| F6 /0 ib |
TEST r/m8, imm8 |
MI |
Valid |
Valid |
AND imm8 with r/m8; set SF, ZF, PF according to result. |
| REX + F6 /0 ib |
TEST r/m8*, imm8 |
MI |
Valid |
N.E. |
AND imm8 with r/m8; set SF, ZF, PF according to result. |
| F7 /0 iw |
TEST r/m16, imm16 |
MI |
Valid |
Valid |
AND imm16 with r/m16; set SF, ZF, PF according to result. |
| F7 /0 id |
TEST r/m32, imm32 |
MI |
Valid |
Valid |
AND imm32 with r/m32; set SF, ZF, PF according to result. |
| REX.W + F7 /0 id |
TEST r/m64, imm32 |
MI |
Valid |
N.E. |
AND imm32 sign-extended to 64-bits with r/m64; set SF, ZF, PF according to result. |
| 84 /r |
TEST r/m8, r8 |
MR |
Valid |
Valid |
AND r8 with r/m8; set SF, ZF, PF according to result. |
| REX + 84 /r |
TEST r/m8*, r8* |
MR |
Valid |
N.E. |
AND r8 with r/m8; set SF, ZF, PF according to result. |
| 85 /r |
TEST r/m16, r16 |
MR |
Valid |
Valid |
AND r16 with r/m16; set SF, ZF, PF according to result. |
| 85 /r |
TEST r/m32, r32 |
MR |
Valid |
Valid |
AND r32 with r/m32; set SF, ZF, PF according to result. |
| REX.W + 85 /r |
TEST r/m64, r64 |
MR |
Valid |
N.E. |
AND r64 with r/m64; set SF, ZF, PF according to result. |
Computes the bit-wise logical AND of first operand (source 1 operand) and the second operand (source 2 operand) and sets the SF, ZF, and PF status flags according to the result. The result is then discarded.
In 64-bit mode, using a REX prefix in the form of REX.R permits access to additional registers (R8-R15). Using a REX prefix in the form of REX.W promotes operation to 64 bits. See the summary chart at the beginning of this section for encoding data and limits.
The OF and CF flags are set to 0. The SF, ZF, and PF flags are set according to the result (see the “Operation” section above). The state of the AF flag is undefined.
| #GP(0) |
If a memory operand effective address is outside the CS, DS, ES, FS, or GS segment limit. |
| If the DS, ES, FS, or GS register contains a NULL segment selector. |
| #SS(0) |
If a memory operand effective address is outside the SS segment limit. |
| #PF(fault-code) |
If a page fault occurs. |
| #AC(0) |
If alignment checking is enabled and an unaligned memory reference is made while the current privilege level is 3. |
| #UD |
If the LOCK prefix is used. |
Same exceptions as in protected mode.


--- layout: page title: Definitions description: We each have our own defintions, these are mine. background: '/img/bg-about.jpg' ---
Image via Unsplash


PSA: Get Ready For New Let’s Encrypt Validation
If you’re using Let’s Encrypt, now would be a really great time to make sure that you’re ready for them to stop supporting ACME TLS-SNI-01 domain validation. I got an email a couple of days ago (as I assume everyone using Let’s Encrypt did) letting me know this change was coming. I had nothing to actually do, but going through the validation was super easy and is likely worth the time to ensure your site(s) aren’t impacted. March 13th is the deadline for ACME TLS-SNI-01 to no longer function, so there’s still a lot of time to take a couple of minutes and verify you’re in good shape.
*Note: I’m using certbot
, which makes this whole thing super easy. If you’re not using certbot
then your steps will be different.*
The Let’s Encrypt staging environment already has disabled ACME TLS-SNI-01 validation, so checking against that is a good test. As a certbot
user, I also needed to validate that I was using at least version 0.28 of the application, which is simple enough to do via:
certbot --version
That appears to be the latest version offered by the PPA: ppa:certbot/certbot
Testing a certbot
run against the staging environment is toggled via the --dry-run
switch. If you do a dry run of your renewal against the staging environment and everything comes back successful, you should be in good shape:
sudo certbot renew --dry-run
My certs all validated successfully, so everything is ready to go for the change. I presume if there are any failures then the dry run will alert you to what needs to be fixed; I can’t say for sure since I was lucky enough to not see any of those. Full instructions from Let’s Encrypt are available on their site, though.
Happy encrypting!


WebClientDataBufferAllocatingTests
|
100%
successful |
Tests
| Test | Method name | Duration | Result |
|---|---|---|---|
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | bodyToMonoVoid(String, DataBufferFactory)[1] | 0.011s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | bodyToMonoVoid(String, DataBufferFactory)[2] | 0.015s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | bodyToMonoVoid(String, DataBufferFactory)[3] | 0.074s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | bodyToMonoVoid(String, DataBufferFactory)[4] | 0.067s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | bodyToMonoVoid(String, DataBufferFactory)[5] | 0.009s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | bodyToMonoVoid(String, DataBufferFactory)[6] | 0.024s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[1] | 0.594s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[2] | 0.016s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[3] | 0.019s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[4] | 0.076s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[5] | 0.028s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | bodyToMonoVoidWithoutContentType(String, DataBufferFactory)[6] | 0.010s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | exchangeToBodilessEntity(String, DataBufferFactory)[1] | 0.012s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | exchangeToBodilessEntity(String, DataBufferFactory)[2] | 0.008s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | exchangeToBodilessEntity(String, DataBufferFactory)[3] | 0.058s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | exchangeToBodilessEntity(String, DataBufferFactory)[4] | 0.011s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | exchangeToBodilessEntity(String, DataBufferFactory)[5] | 0.009s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | exchangeToBodilessEntity(String, DataBufferFactory)[6] | 0.009s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | onStatusWithBodyConsumed(String, DataBufferFactory)[1] | 0.055s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | onStatusWithBodyConsumed(String, DataBufferFactory)[2] | 0.011s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | onStatusWithBodyConsumed(String, DataBufferFactory)[3] | 0.060s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | onStatusWithBodyConsumed(String, DataBufferFactory)[4] | 0.063s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | onStatusWithBodyConsumed(String, DataBufferFactory)[5] | 0.010s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | onStatusWithBodyConsumed(String, DataBufferFactory)[6] | 0.010s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | onStatusWithBodyNotConsumed(String, DataBufferFactory)[1] | 0.019s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | onStatusWithBodyNotConsumed(String, DataBufferFactory)[2] | 0.014s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | onStatusWithBodyNotConsumed(String, DataBufferFactory)[3] | 0.015s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | onStatusWithBodyNotConsumed(String, DataBufferFactory)[4] | 0.014s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | onStatusWithBodyNotConsumed(String, DataBufferFactory)[5] | 0.086s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | onStatusWithBodyNotConsumed(String, DataBufferFactory)[6] | 0.015s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[1] | 0.012s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[2] | 0.010s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[3] | 0.012s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[4] | 0.014s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[5] | 0.012s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | onStatusWithImmediateErrorAndBodyNotConsumed(String, DataBufferFactory)[6] | 0.010s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[1] | 0.011s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[2] | 0.010s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[3] | 0.064s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[4] | 0.073s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[5] | 0.010s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | onStatusWithMonoErrorAndBodyConsumed(String, DataBufferFactory)[6] | 0.010s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[1] | 0.014s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[2] | 0.012s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[3] | 0.013s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[4] | 0.019s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[5] | 0.012s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | onStatusWithMonoErrorAndBodyNotConsumed(String, DataBufferFactory)[6] | 0.062s | passed |
| [1] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = true | releaseBody(String, DataBufferFactory)[1] | 0.009s | passed |
| [2] NettyDataBufferFactory - UnpooledByteBufAllocator - preferDirect = false | releaseBody(String, DataBufferFactory)[2] | 0.009s | passed |
| [3] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = true | releaseBody(String, DataBufferFactory)[3] | 0.011s | passed |
| [4] NettyDataBufferFactory - PooledByteBufAllocator - preferDirect = false | releaseBody(String, DataBufferFactory)[4] | 0.010s | passed |
| [5] DefaultDataBufferFactory - preferDirect = true | releaseBody(String, DataBufferFactory)[5] | 0.009s | passed |
| [6] DefaultDataBufferFactory - preferDirect = false | releaseBody(String, DataBufferFactory)[6] | 0.009s | passed |
Standard output
16:12:12.756 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [68d8a42e] HTTP GET http://localhost:55981/sample 16:12:12.824 [reactor-http-nio-7] DEBUG o.s.w.r.f.c.ExchangeFunctions - [68d8a42e] Response 202 ACCEPTED 16:12:12.857 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7162f825] HTTP GET http://localhost:55989/sample 16:12:12.866 [reactor-http-nio-8] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7162f825] Response 202 ACCEPTED 16:12:12.870 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [571b9d0d] HTTP GET http://localhost:55991/sample 16:12:12.877 [reactor-http-nio-9] DEBUG o.s.w.r.f.c.ExchangeFunctions - [571b9d0d] Response 202 ACCEPTED 16:12:12.889 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [700052ab] HTTP GET http://localhost:55993/sample 16:12:12.900 [reactor-http-nio-10] DEBUG o.s.w.r.f.c.ExchangeFunctions - [700052ab] Response 202 ACCEPTED 16:12:12.976 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7559fb20] HTTP GET http://localhost:55995/sample 16:12:12.994 [reactor-http-nio-11] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7559fb20] Response 202 ACCEPTED 16:12:12.999 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [41ecf625] HTTP GET http://localhost:55997/sample 16:12:13.006 [reactor-http-nio-12] DEBUG o.s.w.r.f.c.ExchangeFunctions - [41ecf625] Response 202 ACCEPTED 16:12:13.013 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [80c1a83] HTTP GET http://localhost:55999/json 16:12:13.020 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [80c1a83] Response 502 BAD_GATEWAY 16:12:13.032 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7a907942] HTTP GET http://localhost:56001/json 16:12:13.038 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7a907942] Response 502 BAD_GATEWAY 16:12:13.045 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [145d2806] HTTP GET http://localhost:56003/json 16:12:13.053 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [145d2806] Response 502 BAD_GATEWAY 16:12:13.060 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [60e7da02] HTTP GET http://localhost:56005/json 16:12:13.067 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [60e7da02] Response 502 BAD_GATEWAY 16:12:13.075 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6eca09f2] HTTP GET http://localhost:56007/json 16:12:13.155 [reactor-http-nio-5] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6eca09f2] Response 502 BAD_GATEWAY 16:12:13.162 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [e09059c] HTTP GET http://localhost:56011/json 16:12:13.170 [reactor-http-nio-6] DEBUG o.s.w.r.f.c.ExchangeFunctions - [e09059c] Response 502 BAD_GATEWAY 16:12:13.179 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [240ac7c4] HTTP GET http://localhost:56013/ 16:12:13.185 [reactor-http-nio-7] DEBUG o.s.w.r.f.c.ExchangeFunctions - [240ac7c4] Response 201 CREATED 16:12:13.190 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [765c95ab] HTTP GET http://localhost:56015/ 16:12:13.196 [reactor-http-nio-8] DEBUG o.s.w.r.f.c.ExchangeFunctions - [765c95ab] Response 201 CREATED 16:12:13.201 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [74e143df] HTTP GET http://localhost:56019/ 16:12:13.248 [reactor-http-nio-9] DEBUG o.s.w.r.f.c.ExchangeFunctions - [74e143df] Response 201 CREATED 16:12:13.258 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [30fed163] HTTP GET http://localhost:56021/ 16:12:13.266 [reactor-http-nio-10] DEBUG o.s.w.r.f.c.ExchangeFunctions - [30fed163] Response 201 CREATED 16:12:13.270 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [26543bcd] HTTP GET http://localhost:56023/ 16:12:13.276 [reactor-http-nio-11] DEBUG o.s.w.r.f.c.ExchangeFunctions - [26543bcd] Response 201 CREATED 16:12:13.279 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2dfd905b] HTTP GET http://localhost:56025/ 16:12:13.286 [reactor-http-nio-12] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2dfd905b] Response 201 CREATED 16:12:13.291 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [59f34b7a] HTTP GET http://localhost:56027/json 16:12:13.297 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [59f34b7a] Response 201 CREATED 16:12:13.306 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [295dcdb] HTTP GET http://localhost:56029/json 16:12:13.315 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [295dcdb] Response 201 CREATED 16:12:13.319 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [5b16c57f] HTTP GET http://localhost:56031/json 16:12:13.325 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [5b16c57f] Response 201 CREATED 16:12:13.398 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [41d0220f] HTTP GET http://localhost:56035/json 16:12:13.405 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [41d0220f] Response 201 CREATED 16:12:13.463 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [16917a22] HTTP GET http://localhost:56038/json 16:12:13.469 [reactor-http-nio-5] DEBUG o.s.w.r.f.c.ExchangeFunctions - [16917a22] Response 201 CREATED 16:12:13.472 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [45388b9d] HTTP GET http://localhost:56040/json 16:12:13.494 [reactor-http-nio-6] DEBUG o.s.w.r.f.c.ExchangeFunctions - [45388b9d] Response 201 CREATED 16:12:13.499 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6d8abce2] HTTP GET http://localhost:56042/json 16:12:13.506 [reactor-http-nio-7] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6d8abce2] Response 502 BAD_GATEWAY 16:12:13.513 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [57098150] HTTP GET http://localhost:56044/json 16:12:13.519 [reactor-http-nio-8] DEBUG o.s.w.r.f.c.ExchangeFunctions - [57098150] Response 502 BAD_GATEWAY 16:12:13.526 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2074153b] HTTP GET http://localhost:56046/json 16:12:13.531 [reactor-http-nio-9] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2074153b] Response 502 BAD_GATEWAY 16:12:13.541 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2a279130] HTTP GET http://localhost:56048/json 16:12:13.551 [reactor-http-nio-10] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2a279130] Response 502 BAD_GATEWAY 16:12:13.560 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [3c76c629] HTTP GET http://localhost:56050/json 16:12:13.566 [reactor-http-nio-11] DEBUG o.s.w.r.f.c.ExchangeFunctions - [3c76c629] Response 502 BAD_GATEWAY 16:12:13.573 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6716d050] HTTP GET http://localhost:56052/json 16:12:13.626 [reactor-http-nio-12] DEBUG o.s.w.r.f.c.ExchangeFunctions - [6716d050] Response 502 BAD_GATEWAY 16:12:13.639 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [f98b574] HTTP GET http://localhost:56056/ 16:12:13.646 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [f98b574] Response 200 OK 16:12:13.651 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [72630df7] HTTP GET http://localhost:56058/ 16:12:13.657 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [72630df7] Response 200 OK 16:12:13.660 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4753c51a] HTTP GET http://localhost:56060/ 16:12:13.667 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4753c51a] Response 200 OK 16:12:13.671 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2d6b0e4a] HTTP GET http://localhost:56062/ 16:12:13.677 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2d6b0e4a] Response 200 OK 16:12:13.682 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1d142c51] HTTP GET http://localhost:56064/ 16:12:13.689 [reactor-http-nio-5] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1d142c51] Response 200 OK 16:12:13.692 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4220eb10] HTTP GET http://localhost:56067/ 16:12:13.698 [reactor-http-nio-6] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4220eb10] Response 200 OK 16:12:13.703 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [5a351545] HTTP GET http://localhost:56070/json 16:12:13.708 [reactor-http-nio-7] DEBUG o.s.w.r.f.c.ExchangeFunctions - [5a351545] Response 502 BAD_GATEWAY 16:12:13.758 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1f725db6] HTTP GET http://localhost:56072/json 16:12:13.764 [reactor-http-nio-8] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1f725db6] Response 502 BAD_GATEWAY 16:12:13.770 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7e68481] HTTP GET http://localhost:56074/json 16:12:13.774 [reactor-http-nio-9] DEBUG o.s.w.r.f.c.ExchangeFunctions - [7e68481] Response 502 BAD_GATEWAY 16:12:13.831 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [55485388] HTTP GET http://localhost:56078/json 16:12:13.837 [reactor-http-nio-10] DEBUG o.s.w.r.f.c.ExchangeFunctions - [55485388] Response 502 BAD_GATEWAY 16:12:13.894 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4a5c3929] HTTP GET http://localhost:56081/json 16:12:13.899 [reactor-http-nio-11] DEBUG o.s.w.r.f.c.ExchangeFunctions - [4a5c3929] Response 502 BAD_GATEWAY 16:12:13.907 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [549a0930] HTTP GET http://localhost:56084/json 16:12:13.911 [reactor-http-nio-12] DEBUG o.s.w.r.f.c.ExchangeFunctions - [549a0930] Response 502 BAD_GATEWAY 16:12:13.920 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [60b9467b] HTTP GET http://localhost:56086/json 16:12:13.924 [reactor-http-nio-1] DEBUG o.s.w.r.f.c.ExchangeFunctions - [60b9467b] Response 502 BAD_GATEWAY 16:12:13.930 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [a970584] HTTP GET http://localhost:56089/json 16:12:13.934 [reactor-http-nio-2] DEBUG o.s.w.r.f.c.ExchangeFunctions - [a970584] Response 502 BAD_GATEWAY 16:12:13.940 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [124898aa] HTTP GET http://localhost:56091/json 16:12:13.944 [reactor-http-nio-3] DEBUG o.s.w.r.f.c.ExchangeFunctions - [124898aa] Response 502 BAD_GATEWAY 16:12:14.005 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [34bdc4f9] HTTP GET http://localhost:56095/json 16:12:14.010 [reactor-http-nio-4] DEBUG o.s.w.r.f.c.ExchangeFunctions - [34bdc4f9] Response 502 BAD_GATEWAY 16:12:14.077 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1ea827cb] HTTP GET http://localhost:56099/json 16:12:14.082 [reactor-http-nio-5] DEBUG o.s.w.r.f.c.ExchangeFunctions - [1ea827cb] Response 502 BAD_GATEWAY 16:12:14.087 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [60acef02] HTTP GET http://localhost:56101/json 16:12:14.094 [reactor-http-nio-6] DEBUG o.s.w.r.f.c.ExchangeFunctions - [60acef02] Response 502 BAD_GATEWAY 16:12:14.101 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [35d85b2a] HTTP GET http://localhost:56103/json 16:12:14.106 [reactor-http-nio-7] DEBUG o.s.w.r.f.c.ExchangeFunctions - [35d85b2a] Response 502 BAD_GATEWAY 16:12:14.112 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [9924458] HTTP GET http://localhost:56106/json 16:12:14.116 [reactor-http-nio-8] DEBUG o.s.w.r.f.c.ExchangeFunctions - [9924458] Response 502 BAD_GATEWAY 16:12:14.123 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [555ad73a] HTTP GET http://localhost:56109/json 16:12:14.127 [reactor-http-nio-9] DEBUG o.s.w.r.f.c.ExchangeFunctions - [555ad73a] Response 502 BAD_GATEWAY 16:12:14.135 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2720d0a6] HTTP GET http://localhost:56111/json 16:12:14.140 [reactor-http-nio-10] DEBUG o.s.w.r.f.c.ExchangeFunctions - [2720d0a6] Response 502 BAD_GATEWAY 16:12:14.148 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [606273e8] HTTP GET http://localhost:56113/json 16:12:14.153 [reactor-http-nio-11] DEBUG o.s.w.r.f.c.ExchangeFunctions - [606273e8] Response 502 BAD_GATEWAY 16:12:14.160 [Test worker] DEBUG o.s.w.r.f.c.ExchangeFunctions - [22919590] HTTP GET http://localhost:56115/json 16:12:14.164 [reactor-http-nio-12] DEBUG o.s.w.r.f.c.ExchangeFunctions - [22919590] Response 502 BAD_GATEWAY


---
layout: post
title: jQuery Combobox Solution
---
I needed a simple jQuery combobox for a project today. After a failed attempt at using the jQuery UI autocomplete, I found this beauty: http://ivaynberg.github.io/select2/
It works great and does exactly what I need. In the future, this will be my choice of plugin for this purpose.


CGraphicTileset class, used for tile set operations.
More...
|
|
final int | TileCount () |
| | Getter function for tile count.
|
| |
|
final int | TileWidth () |
| | Getter function for tile width.
|
| |
|
final int | TileHeight () |
| | Getter function for tile height.
|
| |
| final int | FindTile (String tilename) |
| | Gets tile index if tilename is in map. More...
|
| |
| boolean | LoadTileset (CGame game, String filename) |
| | Loads Tileset. More...
|
| |
| void | DrawTile (CGame game, int x, int y, int tileIndex) |
| | Draws tile at position. More...
|
| |
| void | DrawTile (CGame game, Vector2 position, int tileindex) |
| | Draws Tile if tileindex is between 0 and DTileCount. More...
|
| |
| final void | DrawPixelCorners (Pixmap drawable, int xpos, int ypos, int tileindex) |
| | Draws Tile corners if tileindex is between 0 and DTileCount. More...
|
| |
|
|
Pixmap | DTileset |
| |
|
Pixmap | DPixbufTileset |
| |
|
java.util.HashMap< String, Integer > | DMapping = new java.util.HashMap<String, Integer>() |
| |
|
int | DTileCount |
| |
|
int | DTileWidth |
| |
|
int | DTileHeight |
| |
CGraphicTileset class, used for tile set operations.
| final void game.tilesets.CGraphicTileset.DrawPixelCorners |
( |
Pixmap |
drawable, |
|
|
int |
xpos, |
|
|
int |
ypos, |
|
|
int |
tileindex |
|
) |
| |
Draws Tile corners if tileindex is between 0 and DTileCount.
- Parameters
-
| drawable | destination drawable to draw tile |
| gc | Graphics context, used for clipping |
| xpos | Destination X coord inside drawable |
| ypos | Destination Y coord inside drawable |
| tileindex | index of tile |
| void game.tilesets.CGraphicTileset.DrawTile |
( |
CGame |
game, |
|
|
int |
x, |
|
|
int |
y, |
|
|
int |
tileIndex |
|
) |
| |
Draws tile at position.
- Parameters
-
| game | The game to draw in |
| x | Position to draw |
| y | Position to draw |
| tileindex | Tile to draw |
| void game.tilesets.CGraphicTileset.DrawTile |
( |
CGame |
game, |
|
|
Vector2 |
position, |
|
|
int |
tileindex |
|
) |
| |
Draws Tile if tileindex is between 0 and DTileCount.
- Parameters
-
| drawable | destination drawable to draw tile |
| gc | Graphics context, used for clipping |
| xpos | Destination X coord inside drawable |
| ypos | Destination Y coord inside drawable |
| tileindex | index of tile |
| final int game.tilesets.CGraphicTileset.FindTile |
( |
String |
tilename | ) |
|
Gets tile index if tilename is in map.
- Parameters
-
| boolean game.tilesets.CGraphicTileset.LoadTileset |
( |
CGame |
game, |
|
|
String |
filename |
|
) |
| |
Loads Tileset.
- Parameters
-
| drawable | A GdkDrawable, used to determine default values for the new pixmap |
| gc | Graphics context that holds information about how things are drawn |
| filename | Name of file to load Tileset from |
The documentation for this class was generated from the following file:
- android/src/game/tilesets/CGraphicTileset.java


A dedicated and highly skilled individual with experience in Web Developing. A team player with a fair and approachable style to both team work and independent working. Well organised, proactive in providing timely, efficient and accurate support. I'm creative, hard working and have an interest in computers (specifically in web developing and image editing), cars, music and photography
HTML5
CSS3
JavaScript
React
Photoshop
MySQL
PHP
Bootstrap
Wordpress
February 2019 - Present
I have been enrolled on a course with Just IT to help me regain my passion for web developing. Along with improving my skills in HTML and CSS, I have learnt about C#, GitHub, Bootstrap and ASP.Net. In addition, I have gained more knowledge in JavaScript, MySQL and Visual Basic.
November - December 2018
I worked in a team and we were given numerous tasks such as setting up IT equipment across the hospital, sorting out deliveries of new equipment before dispatching and performing consistent checks on various devices.
April - August 2018
I stored documents into boxes and created lists with details for each box before being sent for deeds. My other jobs include, printing out documents and email as well as covers and spines for folders.
March 2018
As part of a two week work placement, I was job shadowing the supply and purchasing team with different tasks such as assisting with daily receipt of deliveries, checking against delivery notes, moving items to relevant areas, confirming all deliveries against purchase orders and daily preparation of purchase orders considering current stock levels and requirements.
September 2017
As part of an office team, I assisted with tracking vehicles to highlight dead mileage and creating spreadsheets to ensure staff records are updated and secured.
August 2015 - February 2016
I inputted data taken from assessments and enquiries with details from patients who have different forms of visual impairment and throughout I have complied with strict data protection regulations.
June 2013 - 2014
Whilst spending a year in Auckland, New Zealand, I was given freelance jobs from a few organisations. One of them requested their existing website to be updated to make more viewable on phones and tablets.
May 2012 - June 2013
I assisted the Engineering Survey team with reviewing, collating and transferring data from CCTV culvert surveys via the MOSS electronic filing system.
September 2009 - July 2012
My dissertation was looking into different IT facilities in higher education avaiable for students with cognitivie disabilities.
September 2006 - July 2009
This website, created through HTML, CSS and JavaScript, showcases some of my all-time favorite cars.
View Website View Code on GitHub Close ProjectThis project consists of mostly JavaScript and shows some of my all-time favorite Pokemon with details of their attacks
View Project View Code on GitHub Close ProjectThis project, developed through Visual Studios, displays all of the Marvel movies on a database system which has been constructed through MySQL.
View Project View Code on GitHub Close ProjectThis website was developed through Wordpress and shows year-end charts from various US countdown shows.
View on Wordpress Close ProjectThis project, made with HTML, CSS and JavaScript, shows various photos that I have personally taken as photography is one of my hobbies.
View Project View Code on GitHub Close ProjectThis web game is a memory test of different anime characters and consists of mostly JavaScript.
View Project View Code on GitHub Close ProjectThis API project shows the current weather for any city around the world.
View Project View Code on GitHub Close ProjectThis quiz project, developed through JavaScript, tests the knowledge of any fan of Marvel Comics
View Project View Code on GitHub Close ProjectThis JavaScript/CSS project shows a full constructed calculator with various functions.
View Project View Code on GitHub Close ProjectThis project, developed through JavaScript and CSS, shows a simple game of dice where one of the players randomly clicks to beat the other player.
View Project View Code on GitHub Close ProjectThis was my first attempt of developing a website through React and this type of project displays random questions on the topic of Cartoons.
View Project View Code on GitHub Close ProjectThis project, developed through HTML, CSS and Javascript, displays the current date and time in a 12-hour-format.
View Project View Code on GitHub Close ProjectThis project, developed through HTML and CSS, displays an image with an animated effect.
View Project View Code on GitHub Close ProjectThis was my second React Project and it is a e-commerce phone store.
View Project View Code on GitHub Close Project


×
Instruction
1.This game is for 1 hour
2.There are three levels in this game.
3.The judges decision would be final and binding
4.The team with the maximum score shall be declared winner
5.In case of a tie-breaker, the winner will be decided on the basis
of least time taken
6.After reading the question,click on Editor to start solving.
7.It is compulsory to start the game with level 1.


Test example: Demonstrate cooling of a DCPM
motor
The motor starts at no-load speed, then load pulses are
applied.
The cooling circuit consists of armature's thermal capacitance, a
thermal conductance between armature and core, core's thermal
capacitance and a thermal conductance between core and coolant. The
coolant flow circuit consists of inlet, volume flow, a pipe
connected to the core and the outlet.
Please note:
- All unused heat ports of the thermal port (i.e., without loss
sources in the machine: brush, stray, friction, permanent magnet)
have to be connected to a constant temperature source.
- The thermal capacitances (i.e., time constants) are unusual
small to provide short simulation time!
- The coolant is a theoretical coolant with specific mass = 1
kg/m3 and cp = 1 J/kg.K.
- The thermal conductances as well as the coolant flow are
parametrized such way, that:
- the total coolant's temperature rise is 10 K (over coolant
inlet)
- the core's temperature rise is 27.5 K (over coolant's average
temperature between inlet and outlet)
- the armature's temperature rise is 55 K (over coolant's average
temperature between inlet and outlet)
Simulate for 25 seconds and plot (versus time):
- armature.T: armature temperature
- core.T: core temperature
- cooling.T: coolant temperature at outlet
Therefore the armature temperature would reach nominal armature
temperature at constant nominal load.
Default machine parameters are used, but:
- The armature winding material is set to Copper.
- Armature reference temperature is set to 80 degC.
- Nominal armature temperature is set to 80 degC.
Generated at 2019-01-25T16:44:03Z by OpenModelica 1.14.0~dev-130-gefa44fb


MBA: Multilevel B-Spline Approximation
Functions to interpolate irregularly and regularly spaced data using Multilevel B-spline Approximation (MBA). Functions call portions of the SINTEF Multilevel B-spline Library written by Øyvind Hjelle which implements methods developed by Lee, Wolberg and Shin (1997; <doi:10.1109/2945.620490>).
| Version: |
0.0-9 |
| Depends: |
R (> 2.10.0) |
| LinkingTo: |
BH |
| Suggests: |
sp |
| Published: |
2017-03-08 |
| Author: |
Andrew Finley [aut, cre],
Sudipto Banerjee [aut],
Øyvind Hjelle [aut],
Roger Bivand [ctb] |
| Maintainer: |
Andrew Finley <finleya at msu.edu> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| In views: |
Spatial |
| CRAN checks: |
MBA results |
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=MBA
to link to this page.