1. Introduction
Any Robot is a combination of Software & Hardware.
The Architecture
of any robot is based on the following components:
-
Control System
-
Sensors
-
Actuators
-
Power supply
1.1. Control System
The pure definition of a Control system
is:
| "A control system manages, commands, directs or regulates the behaviour of other devices or systems." |
In a Mindstorms context, the Control System is the Brick we use to create Robots.
In the third generation of Lego Mindstorms, it is possible to use Raspberry Pi to manage Sensors & Actuators from Lego Mindstorms ecosystem:
1.2. Sensors
Sensors measure a physical quantity, and convert it into a usable signal for your control systen. When you are designing the robot it is important to choose the correct sensors to enable it to be aware of its environment and perform the tasks required.
In a Mindstorms context, a Sensor is the EV3 IR Sensor which is able to detect objects and detect the EV3 Beacon.
1.3. Actuators
An "actuator” can be defined as a device that converts energy (in robotics, that energy tends to be electrical) into physical motion or a determinated output like a visualization in a Display or the generation of a Sound.
In a Mindstorms context, an actuator is the EV3 Large Motor:
1.4. Power supply
An electric battery is a device consisting of one or more electrochemical cells with external connections provided to power electrical devices.
In a Mindstorms context, one example about Battery is the rechargeable EV3 Battery:


tau.cli.commands package¶
Subpackages¶
Submodules¶
tau.cli.commands.__main__ module¶
TAU Commander command line program entry point.
Sets up logging verbosity and launches subcommands. Avoid doing too much work here. Instead, process arguments in the appropriate subcommand.
-
class
tau.cli.commands.__main__.
MainCommand
[source]¶ Bases:
tau.cli.command.AbstractCommand
Main entry point to the command line interface.
tau.cli.commands.build module¶
tau build
subcommand.
-
class
tau.cli.commands.build.
BuildCommand
(module_name, format_fields=None, summary_fmt=None, help_page_fmt=None, group=None)[source]¶ Bases:
tau.cli.command.AbstractCommand
tau build
subcommand.
tau.cli.commands.dashboard module¶
tau dashboard
subcommand.
tau.cli.commands.help module¶
tau help
subcommand.
-
class
tau.cli.commands.help.
HelpCommand
(module_name, format_fields=None, summary_fmt=None, help_page_fmt=None, group=None)[source]¶ Bases:
tau.cli.command.AbstractCommand
tau help
subcommand.
tau.cli.commands.initialize module¶
tau initialize
subcommand.
tau.cli.commands.select module¶
tau select
subcommand.


--- layout: post title: Illustration test date: '2013-10-03T17:31:00+02:00' categories: - Illustration picture_url: https://film-Storyboards.tumblr.com/post/63029812741/Illustration-test-for-artevent ---
Illustration test for Artevent.


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I’ve approached many self improvement challenges recently by starting with a practice of self curiosity before taking action or making a major decision on what to improve.
For example, when trying to make sure I was eating right and drinking enough water, I started by keeping a log of how many glasses of water I’m drinking daily. I didn’t make any intentional changes.
There are a few reasons why this approach works well:
- It is a great way to get a baseline understanding of what is happening now. It helps to make sure I know how much I need to improve something - whether a gradual or more drastic approach to change is necessary.
- It establishes a habit of measurement before any changes are actually made. This habit is just as important than the change itself.
- The act of measurement always creates some change in behaviour - often for the better.
A few areas where self-curiosity has been critical:
- Time tracking: I’ve become curious about how I’m spending my time, with the ultimate goal of making sure I’m spending an appropriate amount of time on the things that matter to me most.
- Anxiety journals: I’ve started to write about the situations that give me anxiety or make me uncomfortable. The journal is a simple note of what happened (objective) and how it made me feel (subjective). This has helped avoid me making bad decisions when I’m anxious, and helped understand my response to certain situations. Putting it into writing immediately relieves some degree of anxiety, as it feels like some action is being taken.
- Productivity Retrospectives: I started a daily/weekly/monthly reviews to measure how many goals and to-do’s I intended to complete vs. which ones I actually completed. This retrospective has revealed patterns of overcommitment that I always felt I had, but now have empirical evidence to prove it, and change accordingly.
- Tracking Food and Water intake: without actively making any changes to what and how I eat, the act of tracking has already improved my eating habits.
Even after only a few months of these habits, I can already see how these small changes can have major impact over time.


Specify your options and click 'give me a word' to begin.
After each guess, you will be given feedback to help you figure out the word.
For example, if the solution is 'cat' and you guess 'dog', you will see this:
The red letters mean there is no 'd', 'o', or 'g' in the word you are guessing.
If you then guessed 'tap', you would see this:
The yellow 't' means the solution contains 't', but not at the same position.
The green 'a' means the solution contains 'a', and at the same position (second letter in the word).
Now you know 'a' is the second letter. You also know 't' is in the word, but it's not the first letter.
So it must be the third!
 Hit 'esc' key to close rules.


Installation
pip install videocloud
Usage
videocloud <link to YouTube video> [options]
videocloud youtu.be/MHTizZ_XcUM ‑‑filepath=cloud.png
Examples
These are a few examples of wordclouds generated by videocloud. A full list of examples can be found here
Development
Report a bug or request a new feature
This project is maintained by paramt on GitHub


| Class | Description |
|---|---|
| acceptBookActivity | |
| acceptBookRequestActivity | |
| acceptBookRequestsRecyclerViewAdapter | |
| acceptBookRequestsRecyclerViewAdapter.ViewHolder | |
| AddBookFragment |
This class deals with the add book fragment and adding a new book for the user.
|
| AddBookTest | |
| Book |
The Book object for Vitabu that encapsulates all the possible attributes of a book
|
| bookEditActivity |
This class creates the Book Edt activity which lets a book owner view and edit the full information about a
provided book.
|
| bookInfoActivity |
This class creates the Book Info activity which lets the users view the full information about a
provided book.
|
| BookInfoTest | |
| BookTest |
Example local unit test, which will execute on the development machine (host).
|
| BorrowRecord |
Object used to keep track of borrow/lending transactions between users.
|
| BorrowRecordTest |
Example local unit test, which will execute on the development machine (host).
|
| browseBooksActivity |
This class contains all the fragments and the bottom navigation bar that creates the UI.
|
| BrowseBooksBookRecyclerViewAdapter | |
| BrowseBooksFragment | |
| BrowseBooksTest | |
| Database |
Singleton Class to encapsulate all logic for interacting with the database.
|
| DatePickerFragment |
DialogFragment to allow the user to pick the date of their entry.
|
| editProfileActivity | |
| EditProfileTest | |
| ExampleInstrumentedTest |
Instrumented test, which will execute on an Android device.
|
| ExampleUnitTest |
Example local unit test, which will execute on the development machine (host).
|
| getMeetingActivity | |
| ISBNActivity | |
| LocalUser |
An object encapsulating all the attributes and information pertaining to the current user using the app.
|
| LocalUserTest |
Example local unit test, which will execute on the development machine (host).
|
| Location |
A Location object to keep track of country, province, city, and (optionally) address.
|
| LocationTest |
Example local unit test, which will execute on the development machine (host).
|
| LoginTest | |
| MainActivity | |
| MyBooksTest | |
| Notification |
A Notification object specific to a user that should show up in their notifications
|
| NotificationsFragment | |
| NotificationsRecyclerViewAdapter | |
| NotificationTest |
Example local unit test, which will execute on the development machine (host).
|
| OwnedBooksBookRecyclerViewAdapter | |
| OwnedBooksFragment | |
| RecyclerItemTouchHelper |
This class extends from the class ItemTouchHelper.SimpleCallback to add swipe functionality
to the recycler view items displayed in acceptBookActivity.
|
| registerActivity |
This class deals with everything pertaining to new user registration to Vitabu.
|
| RegisterTest | |
| RequestedBooksBookRecyclerViewAdapter | |
| RequestedBooksFragment | |
| requestsBookInfoActivity |
This class creates the Book Info activity which lets the users view the full information about a
provided book (which they have requested).
|
| RequestsTest | |
| returnBookActivity | |
| Review |
A Review object to keep track of the information relevant to a user review.
|
| ReviewTest |
Example local unit test, which will execute on the development machine (host).
|
| searchBookResultsActivity | |
| searchBookResultsRecyclerViewAdapter | |
| searchBookResultsRecyclerViewAdapter.ViewHolder | |
| searchBooksActivity | |
| SearchTest | |
| setMeetingActivity | |
| TimePickerFragment | |
| User |
The User object for Vitabu that encapsulates all the possible attributes of a User
|
| UserAbstract | |
| userProfileActivity | |
| userReviewActivity | |
| UserTest |
Example local unit test, which will execute on the development machine (host).
|
| WriteReviewActivity |


This, the largest of the atolls in Tokelau, lies in the middle of the group. Its lagoon is about 6 miles long and 4 miles wide. Unlike the other islands, which follow the Congregational church, the population on Nukunonu is Catholic. Sadly, the rinocerous beetle which attacks coconut trees, is now present here.
There is a small store in the village.


Soil Water Retention Curve
Soil textural class
Clay
Clay loam
Loam
Loamy sand
Sand
Sandy clay
Sandy clay loam
Sandy loam
Silt
Silty clay
Silty clay loam
Silt loam
$ \theta_{saturation} $
$ \theta_{residual} $
$ \alpha $
$ n $
$ m $
X axis scale
Linear
Logarithmic
Track changes
Off
On
Reset


Congratulations to the newly initiated Iota Class! We can't wait to see you all excel in your future endeavors!
Are you an engineer? Then come rush for Theta Tau! We're the only Professional Co-ed Engineering Fraternity at UCR. Theta Tau can help you in expanding your professional network, becoming apart of a brotherhood, giving back to the community, and becoming a better engineer.
Come and find out what we're all about! We are looking for motivated and bright individuals to become part of our Lambda Class!
Please fill out the interest form if you'd like to join us for our Fall Rush 2017.
As an fraternity that values lifelong relationships, we always remember to dedicate time to our alumni.  This past weekend families went head to head in basketball, Ultimate Frisbee, relays and finally topped off the day with with an early Thanksgiving dinner. Brothers who graduated came back to catch up as well as give advice to old and new brothers. Thanks to all the brothers who took the time to come out!
We develop lifelong bonds of fraternal fellowship between our members through unique and memorable experiences. We stay supportive and honest with each other to promote a brotherhood that goes beyond school and work.
We aim to build and refine the professional abilities of our members so that they succeed in their careers and endeavors. We emphasize professional characteristics such as communication, presentation and innovation.
We believe that it is important to excel in our respective fields as well as give back to the community. Our members strive to lead by example and stay true through volunteering, work, and contribution to the school and community.


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Introduction
When creating a movie, a director has the opportunity to shape every frame, every dialog as he/she likes, therefor giving an infinite number of possibilities when shooting a movie. However, often when we watch a new movie, we feel like "Oh, I have seen this before" or "It was too predictable". But what makes a movie redundant ? What are the codes and lazy habits ?
Our goal is to provide an overview of directors and how they link to each. We will create a network of directors where two directors are linked if they have hired any of the same actors. We want to find out what kind of network this is, who the most central directors are and whether there are any communities within it. On top of this we will analyse the subtitles for every movie of these directors.
Our dataset
The original Movies Dataset consists of 6 files:
- movies_metadata.csv: The main Movies Metadata file. Contains information on 45,000 movies featured in the Full MovieLens dataset. Features include posters, backdrops, budget, revenue, release dates, languages, production countries and companies.
- keywords.csv: Contains the movie plot keywords for our MovieLens movies. Available in the form of a stringified JSON Object.
- credits.csv: Consists of Cast and Crew Information for all our movies. Available in the form of a stringified JSON Object.
- links.csv: The file that contains the TMDB and IMDB IDs of all the movies featured in the Full MovieLens dataset.
- links_small.csv: Contains the TMDB and IMDB IDs of a small subset of 9,000 movies of the Full Dataset.
- ratings_small.csv: The subset of 100,000 ratings from 700 users on 9,000 movies.
Network Analysis
In this part we will analyse the network of directors. The nodes of the network are directors and two directors are connected if they have ever hired the same actor. The network consists of 1273 nodes and 217,725 edges. We will analyse the structure of the network and the centrality of nodes. Then we will analyse the communities of the network.
Degree Distribution
In this section we will take a closer look at the degree distribution and what it says about the network.
| The figure shows the degree distribution of the network. We see that the distribution is quite broad and most nodes have degrees between 100 and 300. |
Does the network structure resemble that of a random network?
The degree distribution of a random network does follow a Poisson distribution. To compare the degree distribution of our network with a Poisson we try to fit a normal distribution curve over the degree distribution to see how well it fits.
| As can be seen in the above figure, the destribution does not correspond very well to a normal distribution and hence the structure of the network is not like that of a random network. |
Is this a scale-free network?
A scale-free network is a network whose degree distribution follows a power law. (ch. 4 in networks book). The power law states that there are a lot of nodes with a very small degree and a few nodes with a very high degree. When plotting the degree distribution of a network that follows the power law with loglog axes it should resemble a straigh line (or close to that).
| It does not look like it follows the power law. Let's plot it using log-log axes. |
| It does not really follow the power law but it is still a very broad distribution meaning that the difference between the minum degree and the maximum degree is very large. |
Paradox is true 92.4 % of the time
In a nework with a power-law degree distribution the friendship paradox is true. The paradox states that almost everyone has fewer friends than their friends have on average. Meaning that the degree of most nodes is lower that the average degree of its neighbours. Even though we found that our network does not really have a power-law degree distribution the friendship paradox is still true for most nodes, so the network does still some property of a real-life network.
The small world property
Does the small world propery hold in our network? The small-world property states that the distance between two nodes is very small compared to the size of the network. The mathematical formula that states whether a netork has the small-world property is printed below (ch. 3 in Network Science book).
eq. 3.19 Network Science book
The equation states that the average distance between nodes should be approximately equal to the natural logarithm of n divided by the natural logarithm of the average degree.
Adding our values gives:
Are these number close enough to call the network a small world? We will say yes, and state that this is a small world network.
Conclusion regarding degree distribution
The network does not resemble a random network but it does not have a clear power-law degree distribution either. However the friendship paradox is true for 92.4% percente of the nodes and it does have the small world property. To sum up it does resemble a real-life network more than a random network.
Centrality
Degree Centrality
The degree of a node is the number of neighbours of the node, or rephrased as the number of other nodes the node is connected to.
- Woody Allen
- Steven Spielberg
- Ridley Scott
- Martin Scorsese
- Oliver Stone
Betweeness centrality
Betweeness centrality indicates how many shortest paths go through a node and is therefore a good meassure of how central a node is in a network.
- Ridley Scott
- Woody Allen
- Steven Spielberg
- Martin Scorsese
- Ron Howard
Eigenvector centrality
The eigenvector centrality measures the centrality of a node based on the centrality of its neighbours. If a node is connected to many nodes that have a high eigenvector centrality then that node will have high eigenvector centrality. This is an indicator of how high influence a node has in the network.
- Steven Spielberg
- Woody Allen
- Ridley Scott
- Martin Scorsese
- Oliver Stone
The same three directors appear in the top 3 for all three centrality measures: Steven Spielberg, Woody Allen and Ridley Scott.
Who are these top three directors?First of all they are all very famous. Lets find their ratings, their vote count and how many movies they have directed.
| Steven Spielberg | Woody Allen | Ridley Scott | Average | Min | Max | |
|---|---|---|---|---|---|---|
| Rating | 6,894 | 6,692 | 6,604 | 6,23 | 3,45 | 8,0 |
| Vote Count | 62.266 | 15.512 | 43.083 | 3.379 | 501 | 67.239 |
| Number of movies | 33 | 49 | 24 | 8,30 | 1 | 66 |
| Genres | Drama, Adventure, Action | Comedy, Drama, Romance | Drama, Action, Thriller |
Most popular genres: Drama, Comedy, Thriller, Action, Romance |
Their vote count is high compared to the rest of the network, but their rating is not that high. This shows that directors who are central in the network do not necessary have a high rating. However their vote count is also an indicator of popularity or at least of how famous they are, and this is quite high for all of them. The fact that they all have a high number of movies is not surprising as this will of course give them a higher probality of being connected with other directors. Their genres are all very popular genres which also increases the likelihood that they share actors with other directors.
Community Detection
In this section we will describe the communities of the netork and analyse where these communities come from. We will do this by looking at some of the attributes that we have for the directors in our dataset.
We found the following communities
| Community | Size |
|---|---|
| 0 | 417 |
| 1 | 223 |
| 2 | 394 |
| 3 | 90 |
| 4 | 100 |
| 5 | 48 |
The modularity is 0,228. The modularity is above 0 which means that there are more edges within the communities than there are across communities. However the modularity is not that high which means that the community are not that well defined.
The plot above illustrates the communities using different colours for each community. We see that the network is split into three bigger parts and two smaller parts at the right and one small community inside another one
Analysis of communities
We will look at three different attributes: language, genre, active period and rating, to see if anything can be said about the communities regarding these. We want to find out if the communities can be distinguished using any of these attributes.
Languages
We have seperated the directors into groups of languages based on the language of their movies.
The figure shows a heatmap where each cell shows the percentage of the community that direct movies of that specific language. Community 3 and 5 seem to be based on language. Community 3 mostly has mostly directors of french movies and some italian movies, community 5 mostly directors of japanese and cantonese movies. The other communities have mostly directors of english movies however community 2 does have a higher percentage of movies of many of the smaller languages than the other communities.
Genres
We have created one group for each genre and added directors to the groups that they have worked whithin. One director might have worked in more than one genre.
The figure shows a heatmap where each cell shows the percentage of the community that have directed movies in that specific genre. As mentioned above, each directed might have worked in multiple genres therefor the percentages for one community do not add up to 100%.
We observe that all communities are a mix of multiple genres which makes sense since we know that directors and actors do not restrict themselves to a single genre. There are some genres that are quite common among all communities such as drama, comedy, romance, thriller and action. These are all genres that are somewhat general and a lot of movies will have these genres listed as their genre along with other more significant genres. There are however some differences between the communities that might be of significans. Communty 4 has directors working in multiple genres that are not as common in the other communities such as music, history, mystery, western and war. Community 5 has a high percentage of directors working in the genres foreign, fantasy and science fiction. Community 1 has a high percentage of directors working in the genres thrillers, mystery, horror and science fiction.
Active Period
We have created one group for each decade and add directors to the group if they were active in that decade. We define the active period of a director as the time from the release of the first movie to the release of the last movie.
The figure shows a heatmap where each cell is the percentage of the community that were active in that decade. A director can be active over a period of more than 10 years and hence can be in multiple groups. Therefor the percentages of each community do not add up to 100%. We observe that community 4 consists mainly of older movies. It makes sense that the directors of older movies are grouped together as not many of the same actors are acting in older as well as newer movies. We can also spot that directors of movies released after year 2000 are in community 0 and 2, while directors of movies from 1980-2000 are more dominant in community 1. Community 3 and 5 are not as concentrated on a specific period but are spread out from 1970 until 2020.
Rating
We have divided the ratings into 5 groups of equal size: low, medium-low, medium, medium-high and high. The directors are then added to the group for which their agerage rating falls within.
The figure shows a heatmap where each cell is the percentage of the community that have a rating in that group. There does not seem to be a high correlation between rating and communities. Community 0 and 1 have a larger part of low rating directors while community 2, 3 and 5 have a larger part of high rating directors. Community 4 has the largest part around the medium rating. However there is not a huge difference in the numbers.
Conclusion about communities
So what can we say about the communities? First of all, the modularity is not significantly high, so the communities are not that solid. We examined different groupings of the directors to see if there is a correlation with the found communities. We tried grouping the directors by language, by genre, by active period and by rating. We discovered the following about the communities:
- Community 0 consists almost solely of directors of english movies. Regarding active period it consists mostly of directors active in the recent decades.
- Community 1 also consist mainly of directors of english movies. It has a high percentage of directors working in drama, thrillers and action. Over half of the community has been rated below medium and most directors were active in the years 1980-2010.
- Community 2 has a higher number of percentage of directors working in many of the smaller languages than the other communities. It consists mainly of directors active after 1990. Almost haf of the community has been rated above average.
- Community 3 consists mainly of directors of french and italian movies. Most of the directors in that community are working with commedy and drama. The directors have been active in the last 50 or so years. Over half of the community has been rated above average.
- Community 4 is characteries as being the community of directors of older movies. Most directors were active in the years 1940-1990. The genres are also a bit different than of the other communities. These directors were working more in the genres music, history, mystery, western and war which are genres that were more popular a few decades ago than they are today.
- Community 5 consists mainly of directors of japanese and cantonese movies. These directors are directing foreign, fantasy and science fiction movies and a more than a third of the community has received a high rating.
The analysis showed that some of the communities seem to be defined by attributes such as language (3 and 5) and active period (4) while the others are more mixed and it's harder to distinguish what makes the community.
So in what communities are our most central directors?Our guess would be in the mixed communities 0, 1 or 2. These are afterall also the largest communities and they seem to hold the more mainstreem directors.
- Steven Spielberg: 2
- Woody Allen: 1
- Ridley Scott: 2
The most central nodes are indeed in communies 1 and 2.
Conclusion
The network we created consisted of movie directors which are connected if they have hired the
same actors. The structure of the network resembles that of a social network and the small world
property holds. The top three directors regarding centrality are all famous directors which have
directed a lot of movies and mostly work in the more popular genres.
We found 6 communities within the network and analysed these to find out what made these
communities. We found out that some of the communities seemed to be based on language and the
active periods of the directors while some were more a general mix.
Wordclouds
While working with our wordclouds, we found quickly which genres where linked together and by which environment. In appears that some genres are clustered together most of the time because of a serie of movie or some sort of synergy.
Sentiment analysis
In this section, we will take a closer look at what the text from movie subtitles can tell us about the movies and their authors, the directors!
Sentiment
Using LabMT wordlist downloaded from the article Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter's source files list. The file represents a set of 10,222 words, their average happiness evaluations according to users on Mechanical Turk and some other information that we are not using in this project.
We started by loading subtitles of our movies and making a token list out of them, removed stopword and calculated the sentiment value of each subtitle file and called this value the sentiment of the movie. In the figure, we can see the distribution of sentiment.
Movie sentiments seem to be distributed normally. The numerical values for this data set are as follow:
- The average sentiment of movies is: 4.8984
- The standard deviation of movies is: 0.2850
Movies, in general, seem to be quite happy texts. If we compare these values to the values we found when analyzing political tweets of us politicians in assignment two of this subject, the average sentiment when removing the tweets with the sentiment value of 0 was around 4.3, which is still 0.5 lower than this data set. For more information on tweet analysis checkout our assignment 2 notebook
We can also notice that the standard deviation of movie sentiment is much lower than the tweet one. One of the possible reasons is probably due to the length of the movies being bigger.
Positive and negative movies
We then decided to take a look at the movies that stand out from the crowd. We selected the movies that were more than two standard deviations away from the mean. We called the movies with small values negative or sad movies and the movies with high sentiment values positive or happy movies.
With these restrictions we got
- 277 sad movies
- 37 happy movies
For both movie t sets, we computed their tf-ids and created the word cloud that will hopefully give us more inside to the words used in each of the extremes. The word clouds can be seen in the figures below:
The word cloud is not as representative as we hoped.
Anyway, there were quite some words we expected in positive movies. For example, Christmas seems to be present in happy movies a lot. We also noticed some Spanish words the clouds, for example, chica that seems to be a popular word in positive movies. In our great surprise word, Bieber seems to be the most represented word in positive movies set. Words like youtube and applejack also surprised us.
The negative movie word cloud surprised us more. This is mostly due to us only having sentiment scores for the English language. This analysis could be improved by adding sentiment values for other languages. Anyway, words like chffffff seem to have no real meaning. There were also a lot of words that seem like stopword from other languages. There were also quite a few words that seem were to be expected in the sad movie set, for example screeching, danger, justice, army and so on.
Sentiment of directors
We then grouped the movies of each director. We were again interested in the distribution of sentiment of each director. The results can be seen in the figure below:
There is no surprise that the sentiment is again distributed normally. The numerical values are as follows:
- The average sentiment of directors work is: 4.9084
- The standard deviation of directors work is: 0.1878
Again the sentiment of the director's work is even higher than the tweeter one. It is also higher than the average movie sentiment.
Positive and negative Directors
We again selected happy/positive and sad/negative directors using the same criteria as with movies to get two sets of directors.
The sizes of the sets are as follows:
- 43 sad directors
- 19 happy directors
For reasons stated before we are not surprised that there are quite a few non-English speaking directors in the negative set since most of their work is not in English.
We again generated word clouds for each director group and got the following word clouds
The results of positive and negative director work surprised us a lot. Words like Pikachu, Pika, Anakin, and words like that surprised us a lot. The Positive word cloud was even weirder. There where almost only names in it and maybe some words that we could make sense of, for example, pajamas
Central Directors
We focused on three directors that were in the most central nodes in most of the centrality measures. We did in the network analysis part of this project for the following three Directors:
- Ridley Scott
- Woody Allen
- Steven Spielberg
We first took a look at their sentiment in comparison to other directors. This can be seen very well in figure bellow
It comes as no surprise that out of these three, Woody Allen has the highest sentiment since he is known more for his work in romantic and drama genres of movies. Both Ridley Scott know for Alien, Blade Runner, Gladiator ... and Steven Spielberg is known for Jaws, Jurassic Park, Schindler's list ... are more of directors that normally produce a bit darker movies, and therefore have a lower average sentiment.
We also generated the word clouds comparing and representing their work.
In Ridley Scott word clouds there are quite a few names from greek mythology, such as Maximus, Hermes, and Ramses which comes as no surprise. There are also words like rover and starling that point to more fantasy/space movies.
Woody Allen uses words like actresses, sexy and novel a lot which also comes as no surprise since his style is more romantic and easy-going.
Steven Spielberg uses words like the grail, nicht, and ark in his work, which tells us something about his more adventure colored movies. As with the other two directors, a lot of words in clouds are the character names, especially if there are more movies with the same characters.
Just by analyzing word clouds of different directors, we can tell something about their style. Both Ridley Scott and Steven Spielberg make more action and sci-fi movies when Allen produces mostly drama movies.
Language diversity for directors
We also analyzed the language diversity used by directors.
What even is language diversity.
We call language diversity the measure of how many different words are used in directors' vocabulary compared to their vocabulary size.
We can see the language diversity distribution of director's work in figure bellow
As expected the distribution of language diversity seems to be normal. Again the numerical values are as follows:
- Average language diversity of directors work is: 0.2229
- Standard language diversity of directors work is: 0.0770
It seems like this measure alone doesn't tell us much about directors. We see that popular directors are the ones that have really low diversity value, but that is mainly due to them having made a lot of movies.
Lets again take a look at the central director's ant their diversity. These measures are the best represented in the figure below.
We suspect that the reason for their low diversity is mostly due to them having made a lot of movies, and therefore even if they are having really big vocabulary still doesn't outweigh the combined length of their work
Most used words for directors
We also looked at the distribution of most used words in each of the highest centrality directors' work. We did that by selecting the 75 most used words in their work by counting it and sorting it. We then plotted the results in the next figures.
We can see that the frequencies look quite similar for all directors. This is probably due to the common words used in everyday English that outweigh the ones that may represent each individual director..
Most used words for directors
We were also interested in how movies changed over time. To get an inside in this kind of information we used lexical dispersity visualization. This is done marking each occurrence of a word in text by a small line and then plotting the graph. With this, we get an inside on how texts change over time.
For this need, we ordered all of our movie data by their release date, and then join them all together. We tried generating the plots for quite some words, some of them are representative and some of them just seem to be too common to tell us anything about the change in the language used.
For example, if we take a look at the dispersity plot of the word Indy, we get the rough placement of Indiana Jones movies that was brought to life by Steven Spielberg and George Lucas and played by Harrison Ford. We also plotted some other words that are specific to famous movies, for example, Potter, Bond, Batman, Jedi...
We also tried doing the same for the directors with the highest centrality. We again selected their work and picked out some words that seem to be interesting for each of the selected directors, and some universal ones.
Again we can see that word love is used a lot more in the Woody Allen than in any other Directors work
Director community sentiment
We also tried to check if there are any noticeable differences between the communities of directors described in the network analysis part of this assignment. The combined sentiments can be observed in the figure below.
| Community | Mean | Standard deviation |
|---|---|---|
| Community 1 | 4.9592 | 0.2111 |
| Community 2 | 4.9248 | 0.1334 |
| Community 3 | 4.8870 | 0.1835 |
| Community 4 | 4.8646 | 0.1519 |
| Community 5 | 4.8463 | 0.1372 |
| Community 6 | 4.7859 | 0.2184 |
The last community's sentiment is lower than others, we mostly assume that is due to there being a lot of foreign directors in that community.


We are more than a simple online watch store... we're a new way to understand time! We are a constant movement and we can't understand movement without time! We assume that time is life... if we take care of it we take care of our life! That's why we love to have a watch everytime! In every different situation!
<EMAIL_ADDRESS>+55 3478 5643


| Overview | Module | Use | Devguide | Index |
| uses of interface XAccessibleExtendedComponent |
back to interface XAccessibleExtendedComponent |
| References in Developers Guide |
| Accessibility - XAccessibleExtendedComponent |
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


X-STAT is a first in kind hemostatic device for the treatment of gunshot and shrapnel wounds. Unlike traditional wound treatments which will take a lot of time, X-STAT can heal the wounds in a .....read more
The Large Hadron Collider (LHC) is the world’s largest and most powerful particle accelerator. It boosts particles, such as protons, which form all the matter we know. Accelerated to a speed close to.....read more
If you are reading this article then the chances are you are using an Android smartphone. Android is the world’s Most.....read more
DARQ is capable of making a new era of technology in all fields of science. DARQ gives a new revolution to computing by making processing faster, optimizing internet speed, and data encryption. DARQ is a combination of..... read more
Privacy is the key that unlocks the aspects of yourself that are most intimate and personal, that make you unique, and most vulnerable. Your past, present and possible future......read more
It creates deeper blacks, conveys fast moving images very well and uses a single replaceable white light bulb. Available in both front and rear projection models, DLP is an excellent choice for people who..... read more
Smartphones are becoming smarter in different, innovative ways that add comfort to the users. Protection,security of data is one of the best features of smartphones and .....read more
The future of UX design is in a combination of intuitive/predictive AI as well as quality voice/chatbots. Being able to interact with technology in a natural Human-like .....read more
Robotics Today- A series of technical talks is a virtual robotics seminar series. The goal of the series is to bring the robotics community together during this .....read more
The answer is hologram technology, which will ultimately lead to the future of marketing. Hologram is the revolutionary technology of future display industries like .....read more


contributors is a JavaScript widget to display the contributors of an open source Github project.
I wanted to give props to the people who spend their valuable time to improve open source software by listing them on the project websites.
When contributors.js is loaded you can use the contributors.generate method to generate a list of the contributors.

or another way with jQuery could be

Styling can be found here: example/contributors.css

Styling can be found here: example/brunch-contributors.css
The generated list includes two different types of entries.

[name with Github login as fallback]

[name]

I picked API v2, because API v3 doesn't provide the name when fetching the contributors of a repository. The only way to get the real name in API v3 is to create another API request.
Contributors is licensed under MIT - Copyright 2011 Nikolaus Graf, blossom
Source can be found on Github: https://github.com/blossom/contributors
This widget is developed in CoffeeScript. The command cake watch
compiles all source including the tests. cake minify
generates a minifed version based on lib/contributors.js.
To run the test suite open test/runner.html


Florida couple replaces bouquets with rescue puppies to raise awareness about adoption
by WFTS StaffSARASOTA, Fla. — A couple in Florida used rescue puppies in place of bouquets at their wedding and it was as cute as you would expect.
Andee Ondina of Sarasota says she wanted to raise awareness for rescue animals and the adopt, don't shop movement. She saw her big day as the perfect pawportunity.
Ondina teamed up with Nate's Honor Animal Rescue in Bradenton to get her “puppquets." Instead of flowers, her bridesmaids held the adoptable, and adorable, little 5-week-old puppies.
"I knew our dream wedding would not be complete if we were not helping to bring awareness to a cause near and dear to our hearts," Ondina said on Facebook.
She and new wife Tina Krasinski had their big day at the Wishing Well Barn in Plant City on Monday.
All the puppies will be available for adoption in a few weeks, and the couple even had applications on-hand at the wedding for guests who were interested.
Head over to Nate's Honor Animal Rescue on Facebook for more on the puppies and other animals in need of forever homes.
This story was originally published by Emily McCain at WFTS.


Vim documentation: usr_20
main help file*usr_20.txt* For Vim version 7.2. Last change: 2006 Apr 24 VIM USER MANUAL - by Bram Moolenaar Typing command-line commands quickly Vim has a few generic features that makes it easier to enter commands. Colon commands can be abbreviated, edited and repeated. Completion is available for nearly everything. |20.1| Command line editing |20.2| Command line abbreviations |20.3| Command line completion |20.4| Command line history |20.5| Command line window Next chapter: |usr_21.txt| Go away and come back Previous chapter: |usr_12.txt| Clever tricks Table of contents: |usr_toc.txt|
*20.1* Command line editing When you use a colon (:) command or search for a string with / or ?, Vim puts the cursor on the bottom of the screen. There you type the command or search pattern. This is called the Command line. Also when it's used for entering a search command. The most obvious way to edit the command you type is by pressing the <BS> key. This erases the character before the cursor. To erase another character, typed earlier, first move the cursor with the cursor keys. For example, you have typed this: :s/col/pig/ Before you hit <Enter>, you notice that "col" should be "cow". To correct this, you type <Left> five times. The cursor is now just after "col". Type <BS> and "w" to correct: :s/cow/pig/ Now you can press <Enter> directly. You don't have to move the cursor to the end of the line before executing the command. The most often used keys to move around in the command line: <Left> one character left <Right> one character right <S-Left> or <C-Left> one word left <S-Right> or <C-Right> one word right CTRL-B or <Home> to begin of command line CTRL-E or <End> to end of command line Note: <S-Left> (cursor left key with Shift key pressed) and <C-Left> (cursor left key with Control pressed) will not work on all keyboards. Same for the other Shift and Control combinations. You can also use the mouse to move the cursor. DELETING As mentioned, <BS> deletes the character before the cursor. To delete a whole word use CTRL-W. /the fine pig CTRL-W /the fine CTRL-U removes all text, thus allows you to start all over again. OVERSTRIKE The <Insert> key toggles between inserting characters and replacing the existing ones. Start with this text: /the fine pig Move the cursor to the start of "fine" with <S-Left> twice (or <Left> eight times, if <S-Left> doesn't work). Now press <Insert> to switch to overstrike and type "great": /the greatpig Oops, we lost the space. Now, don't use <BS>, because it would delete the "t" (this is different from Replace mode). Instead, press <Insert> to switch from overstrike to inserting, and type the space: /the great pig CANCELLING You thought of executing a : or / command, but changed your mind. To get rid of what you already typed, without executing it, press CTRL-C or <Esc>. Note: <Esc> is the universal "get out" key. Unfortunately, in the good old Vi pressing <Esc> in a command line executed the command! Since that might be considered to be a bug, Vim uses <Esc> to cancel the command. But with the 'cpoptions' option it can be made Vi compatible. And when using a mapping (which might be written for Vi) <Esc> also works Vi compatible. Therefore, using CTRL-C is a method that always works. If you are at the start of the command line, pressing <BS> will cancel the command. It's like deleting the ":" or "/" that the line starts with.
*20.2* Command line abbreviations Some of the ":" commands are really long. We already mentioned that ":substitute" can be abbreviated to ":s". This is a generic mechanism, all ":" commands can be abbreviated. How short can a command get? There are 26 letters, and many more commands. For example, ":set" also starts with ":s", but ":s" doesn't start a ":set" command. Instead ":set" can be abbreviated to ":se". When the shorter form of a command could be used for two commands, it stands for only one of them. There is no logic behind which one, you have to learn them. In the help files the shortest form that works is mentioned. For example: :s[ubstitute] This means that the shortest form of ":substitute" is ":s". The following characters are optional. Thus ":su" and ":sub" also work. In the user manual we will either use the full name of command, or a short version that is still readable. For example, ":function" can be abbreviated to ":fu". But since most people don't understand what that stands for, we will use ":fun". (Vim doesn't have a ":funny" command, otherwise ":fun" would be confusing too.) It is recommended that in Vim scripts you write the full command name. That makes it easier to read back when you make later changes. Except for some often used commands like ":w" (":write") and ":r" (":read"). A particularly confusing one is ":end", which could stand for ":endif", ":endwhile" or ":endfunction". Therefore, always use the full name. SHORT OPTION NAMES In the user manual the long version of the option names is used. Many options also have a short name. Unlike ":" commands, there is only one short name that works. For example, the short name of 'autoindent' is 'ai'. Thus these two commands do the same thing: :set autoindent :set ai You can find the full list of long and short names here: |option-list|.
*20.3* Command line completion This is one of those Vim features that, by itself, is a reason to switch from Vi to Vim. Once you have used this, you can't do without. Suppose you have a directory that contains these files: info.txt intro.txt bodyofthepaper.txt To edit the last one, you use the command: :edit bodyofthepaper.txt It's easy to type this wrong. A much quicker way is: :edit b<Tab> Which will result in the same command. What happened? The <Tab> key does completion of the word before the cursor. In this case "b". Vim looks in the directory and finds only one file that starts with a "b". That must be the one you are looking for, thus Vim completes the file name for you. Now type: :edit i<Tab> Vim will beep, and give you: :edit info.txt The beep means that Vim has found more than one match. It then uses the first match it found (alphabetically). If you press <Tab> again, you get: :edit intro.txt Thus, if the first <Tab> doesn't give you the file you were looking for, press it again. If there are more matches, you will see them all, one at a time. If you press <Tab> on the last matching entry, you will go back to what you first typed: :edit i Then it starts all over again. Thus Vim cycles through the list of matches. Use CTRL-P to go through the list in the other direction: <------------------- <Tab> -------------------------+ | <Tab> --> <Tab> --> :edit i :edit info.txt :edit intro.txt <-- CTRL-P <-- CTRL-P | +---------------------- CTRL-P ------------------------> CONTEXT When you type ":set i" instead of ":edit i" and press <Tab> you get: :set icon Hey, why didn't you get ":set info.txt"? That's because Vim has context sensitive completion. The kind of words Vim will look for depends on the command before it. Vim knows that you cannot use a file name just after a ":set" command, but you can use an option name. Again, if you repeat typing the <Tab>, Vim will cycle through all matches. There are quite a few, it's better to type more characters first: :set isk<Tab> Gives: :set iskeyword Now type "=" and press <Tab>: :set iskeyword=@,48-57,_,192-255 What happens here is that Vim inserts the old value of the option. Now you can edit it. What is completed with <Tab> is what Vim expects in that place. Just try it out to see how it works. In some situations you will not get what you want. That's either because Vim doesn't know what you want, or because completion was not implemented for that situation. In that case you will get a <Tab> inserted (displayed as ^I). LIST MATCHES When there are many matches, you would like to see an overview. Do this by pressing CTRL-D. For example, pressing CTRL-D after: :set is results in: :set is incsearch isfname isident iskeyword isprint :set is Vim lists the matches and then comes back with the text you typed. You can now check the list for the item you wanted. If it isn't there, you can use <BS> to correct the word. If there are many matches, type a few more characters before pressing <Tab> to complete the rest. If you have watched carefully, you will have noticed that "incsearch" doesn't start with "is". In this case "is" stands for the short name of "incsearch". (Many options have a short and a long name.) Vim is clever enough to know that you might have wanted to expand the short name of the option into the long name. THERE IS MORE The CTRL-L command completes the word to the longest unambiguous string. If you type ":edit i" and there are files "info.txt" and "info_backup.txt" you will get ":edit info". The 'wildmode' option can be used to change the way completion works. The 'wildmenu' option can be used to get a menu-like list of matches. Use the 'suffixes' option to specify files that are less important and appear at the end of the list of files. The 'wildignore' option specifies files that are not listed at all. More about all of this here: |cmdline-completion|
*20.4* Command line history In chapter 3 we briefly mentioned the history. The basics are that you can use the <Up> key to recall an older command line. <Down> then takes you back to newer commands. There are actually four histories. The ones we will mention here are for ":" commands and for "/" and "?" search commands. The "/" and "?" commands share the same history, because they are both search commands. The two other histories are for expressions and input lines for the input() function. |cmdline-history| Suppose you have done a ":set" command, typed ten more colon commands and then want to repeat that ":set" command again. You could press ":" and then ten times <Up>. There is a quicker way: :se<Up> Vim will now go back to the previous command that started with "se". You have a good chance that this is the ":set" command you were looking for. At least you should not have to press <Up> very often (unless ":set" commands is all you have done). The <Up> key will use the text typed so far and compare it with the lines in the history. Only matching lines will be used. If you do not find the line you were looking for, use <Down> to go back to what you typed and correct that. Or use CTRL-U to start all over again. To see all the lines in the history: :history That's the history of ":" commands. The search history is displayed with this command: :history / CTRL-P will work like <Up>, except that it doesn't matter what you already typed. Similarly for CTRL-N and <Down>. CTRL-P stands for previous, CTRL-N for next.
*20.5* Command line window Typing the text in the command line works different from typing text in Insert mode. It doesn't allow many commands to change the text. For most commands that's OK, but sometimes you have to type a complicated command. That's where the command line window is useful. Open the command line window with this command: q: Vim now opens a (small) window at the bottom. It contains the command line history, and an empty line at the end: +-------------------------------------+ |other window | |~ | |file.txt=============================| |:e c | |:e config.h.in | |:set path=.,/usr/include,, | |:set iskeyword=@,48-57,_,192-255 | |:set is | |:q | |: | |command-line=========================| | | +-------------------------------------+ You are now in Normal mode. You can use the "hjkl" keys to move around. For example, move up with "5k" to the ":e config.h.in" line. Type "$h" to go to the "i" of "in" and type "cwout". Now you have changed the line to: :e config.h.out Now press <Enter> and this command will be executed. The command line window will close. The <Enter> command will execute the line under the cursor. It doesn't matter whether Vim is in Insert mode or in Normal mode. Changes in the command line window are lost. They do not result in the history to be changed. Except that the command you execute will be added to the end of the history, like with all executed commands. The command line window is very useful when you want to have overview of the history, lookup a similar command, change it a bit and execute it. A search command can be used to find something. In the previous example the "?config" search command could have been used to find the previous command that contains "config". It's a bit strange, because you are using a command line to search in the command line window. While typing that search command you can't open another command line window, there can be only one.
Next chapter: |usr_21.txt| Go away and come back Copyright: see |manual-copyright| vim:tw=78:ts=8:ft=help:norl: top - main help file


Leading the market by connecting people with trust and providing an innovative solution.
Our Missions
Why do we exist.
Understand
Understand the customers need better than themselves.
Listen
Keep improving by listening to our customers feedback.
Happiness
We are happy, when our customers are happy.
Our Values
Culture of our team.
Improvement
Whenever we face the problem, always discuss and find a better way to solve it. If we are reluctant to try new things, we will never able to improve ourselves and our product will not full fill the customer's needs enough.
Collaborative
Team power comes from effective communication and collaborative attitude.
Self-organized attitude - Do not wait until the other team members ask you to do.
Share issues quickly - Do not hesitate to ask something which will affect other problems in the later stage.
Retrospect - Let's review what we have done wrong, mistakes can be improved.
Project Name
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Date: January 2017
Client: Lines
Category: Branding
Project Name
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Date: January 2017
Client: Southwest
Category: Website Design
Project Name
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 Lorem ipsum dolor sit amet, consectetur adipisicing elit. Est blanditiis dolorem culpa incidunt minus dignissimos deserunt repellat aperiam quasi sunt officia expedita beatae cupiditate, maiores repudiandae, nostrum, reiciendis facere nemo!


Class: Aws::IoTDataPlane::Types::PublishRequest
| 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-iotdataplane/lib/aws-sdk-iotdataplane/types.rb |
Overview
The input for the Publish operation.
Constant Summary
Instance Attribute Summary
-
#content_type ⇒ String
rw
A UTF-8 encoded string that describes the content of the publishing message.
-
#correlation_data ⇒ String
rw
The base64-encoded binary data used by the sender of the request message to identify which request the response message is for when it's received.
-
#message_expiry ⇒ Integer
rw
A user-defined integer value that represents the message expiry interval in seconds.
-
#payload ⇒ String
rw
The message body.
-
#payload_format_indicator ⇒ String
rw
An
Enum
string value that indicates whether the payload is formatted as UTF-8. -
#qos ⇒ Integer
rw
The Quality of Service (QoS) level.
-
#response_topic ⇒ String
rw
A UTF-8 encoded string that's used as the topic name for a response message.
-
#retain ⇒ Boolean
rw
A Boolean value that determines whether to set the RETAIN flag when the message is published.
-
#topic ⇒ String
rw
The name of the MQTT topic.
-
#user_properties ⇒ String
rw
A JSON string that contains an array of JSON objects.
Instance Method Summary
::Aws::Structure
- Included
| #to_hash | Alias for Structure#to_h. |
Instance Attribute Details
#content_type ⇒ String
(rw)
A UTF-8 encoded string that describes the content of the publishing message.
# File 'gems/aws-sdk-iotdataplane/lib/aws-sdk-iotdataplane/types.rb', line 330
class PublishRequest < Struct.new( :topic, :qos, :retain, :payload, :user_properties, :payload_format_indicator, :content_type, :response_topic, :correlation_data, : ) SENSITIVE = [] include Aws::Structure end
#correlation_data ⇒ String
(rw)
The base64-encoded binary data used by the sender of the request
message to identify which request the response message is for when
it's received. correlationData
is an HTTP header value in the
API.
# File 'gems/aws-sdk-iotdataplane/lib/aws-sdk-iotdataplane/types.rb', line 330
class PublishRequest < Struct.new( :topic, :qos, :retain, :payload, :user_properties, :payload_format_indicator, :content_type, :response_topic, :correlation_data, : ) SENSITIVE = [] include Aws::Structure end
#message_expiry ⇒ Integer
(rw)
A user-defined integer value that represents the message expiry
interval in seconds. If absent, the message doesn't expire. For
more information about the limits of messageExpiry
, see Amazon
Web Services ::Aws::IoT
Core message broker and protocol limits and quotas
from the Amazon Web Services Reference Guide.
# File 'gems/aws-sdk-iotdataplane/lib/aws-sdk-iotdataplane/types.rb', line 330
class PublishRequest < Struct.new( :topic, :qos, :retain, :payload, :user_properties, :payload_format_indicator, :content_type, :response_topic, :correlation_data, : ) SENSITIVE = [] include Aws::Structure end
#payload ⇒ String
(rw)
The message body. MQTT accepts text, binary, and empty (null) message payloads.
Publishing an empty (null) payload with retain = true
deletes
the retained message identified by topic from Amazon Web
Services IoT Core.
# File 'gems/aws-sdk-iotdataplane/lib/aws-sdk-iotdataplane/types.rb', line 330
class PublishRequest < Struct.new( :topic, :qos, :retain, :payload, :user_properties, :payload_format_indicator, :content_type, :response_topic, :correlation_data, : ) SENSITIVE = [] include Aws::Structure end
#payload_format_indicator ⇒ String
(rw)
An Enum
string value that indicates whether the payload is
formatted as UTF-8. payloadFormatIndicator
is an HTTP header value
in the API.
# File 'gems/aws-sdk-iotdataplane/lib/aws-sdk-iotdataplane/types.rb', line 330
class PublishRequest < Struct.new( :topic, :qos, :retain, :payload, :user_properties, :payload_format_indicator, :content_type, :response_topic, :correlation_data, : ) SENSITIVE = [] include Aws::Structure end
#qos ⇒ Integer
(rw)
The Quality of Service (QoS) level. The default QoS level is 0.
# File 'gems/aws-sdk-iotdataplane/lib/aws-sdk-iotdataplane/types.rb', line 330
class PublishRequest < Struct.new( :topic, :qos, :retain, :payload, :user_properties, :payload_format_indicator, :content_type, :response_topic, :correlation_data, : ) SENSITIVE = [] include Aws::Structure end
#response_topic ⇒ String
(rw)
A UTF-8 encoded string that's used as the topic name for a response message. The response topic is used to describe the topic which the receiver should publish to as part of the request-response flow. The topic must not contain wildcard characters.
# File 'gems/aws-sdk-iotdataplane/lib/aws-sdk-iotdataplane/types.rb', line 330
class PublishRequest < Struct.new( :topic, :qos, :retain, :payload, :user_properties, :payload_format_indicator, :content_type, :response_topic, :correlation_data, : ) SENSITIVE = [] include Aws::Structure end
#retain ⇒ Boolean
(rw)
A Boolean value that determines whether to set the RETAIN flag when the message is published.
Setting the RETAIN flag causes the message to be retained and sent to new subscribers to the topic.
Valid values: true
| false
Default value: false
# File 'gems/aws-sdk-iotdataplane/lib/aws-sdk-iotdataplane/types.rb', line 330
class PublishRequest < Struct.new( :topic, :qos, :retain, :payload, :user_properties, :payload_format_indicator, :content_type, :response_topic, :correlation_data, : ) SENSITIVE = [] include Aws::Structure end
#topic ⇒ String
(rw)
The name of the MQTT topic.
# File 'gems/aws-sdk-iotdataplane/lib/aws-sdk-iotdataplane/types.rb', line 330
class PublishRequest < Struct.new( :topic, :qos, :retain, :payload, :user_properties, :payload_format_indicator, :content_type, :response_topic, :correlation_data, : ) SENSITIVE = [] include Aws::Structure end
#user_properties ⇒ String
(rw)
A JSON string that contains an array of JSON objects. If you don’t
use Amazon Web Services SDK or CLI, you must encode the JSON string
to base64 format before adding it to the HTTP header.
userProperties
is an HTTP header value in the API.
The following example userProperties
parameter is a JSON string
which represents two User Properties. Note that it needs to be
base64-encoded:
[\{"deviceName": "alpha"\}, \{"deviceCnt": "45"\}]
# File 'gems/aws-sdk-iotdataplane/lib/aws-sdk-iotdataplane/types.rb', line 330
class PublishRequest < Struct.new( :topic, :qos, :retain, :payload, :user_properties, :payload_format_indicator, :content_type, :response_topic, :correlation_data, : ) SENSITIVE = [] include Aws::Structure end


We should put the internet at the center of society. Our leaders should be religious figures. We religious spend time sending tweets to the people that want us to. If you want a place of worship it would be no more than a phpBB site. If you want to organize a following you should use Buddy Press. If you want to get people involved in a football game you should be using Facebook to send messages to your wall letting people know you want to meet in the field the next day it's muddy and raining.
This football season and I don't think I can survive this life if I never play another football game ya'll. I don't think I can have access to all these people and have no one listening to me. It's one thing to be lonely when you alone in your apartment. It another thing to be lonely when you looking at like 5000 people every day in your apartment. Like I need to Skype with someone. I need to write with someone. I need to fly a kite with someone. I need to spend the night with someone.
 Just talking about life with.   Just someone that can come over and mofo spend time with me. Like I'm at that point ya'll.
Like growing up and for a long time I used to have no problem meeting anyone. It been a long time since someone been to my apartment. I just need to spend some time with someone. Like a therapist. Like all we gonna do is talk. Just a whore and myself alone in my apartment just talking til dawn. She can leave when she wants to if she get's another call but I just need someone to talk to.
I ain the first john that just wanted to talk. Like here's your $40 now just sit on that couch and do your therapist.  No I really ain trying to have kids right now. Alright maybe you can rub my shoulders. Alright maybe you can rub my feet. Alright maybe we can make out. I just need to remember what it used to be like.
It's been about three months since I made out with someoen. Really made out. Like she had me laid out on the futon and she was just loving me with her mouth. She loved my whole body. Like I don't know what it is about me. I vaguely wish there was something different about me. There ain too much to do if I ignore my body's needs. Like I got some money coming in but my body want more. So I behave in a way that leads to me having more money. Almost at the point where I start turning my money into cash. Like money and cash two diffferent things. You can have money on you all day but you might not have cash. You can have cash on you all day but you might not have money. See money hard to make it's like inventing something new a new way of doing things like you thinking about how you can get some cash well if you want cash you gotta trade something for it.
I want some cash so I gotta trade something for it. I want to go into the bagel business. I'm thinking how can I differentiate myself in the market. I take the idea of the bagel and BOW! loaves of bagel bread. Cubes of Bagel. The Bagel Cube. That's money. Ain no one working with a cube of bagel. Now I got the money. The Bagel Cube. So now I get the equipment and start generating cubes of bagels and when I trade the cubes of bagels for cash. I got cash now. You can't really get cash without money. Like you can't. Not if you want an infinite supply of cash.
If you want an infinite supply of cash you need money. Money comes from years of thought provocting conversation and delving into the recesses of the human mind. Money an idea. Some people ain got ideas. So they deal strictly with cash. Tried and true things.  If you into tried and true businesses like buying franchises or something you ain got no money. The man selling the franchise got money the man buying the franchise got cash. I'm more impressed with the people that have money. Squirrely people that may be right around your neighborhood. A lot of people you know got enough money they ain gotta do much. All their questions answered.
If you want to explore cash you may be on an endless paper chase.  There are a lot of ways to get cash. You need money to get cash out of thin air. Like if you want cash you gotta start with your apartment and you gotta make candy of some original recipe. Like chocolate covered sugar cubes or paw paw nuget covered in chocalate. Money about doing something original. Not a spin just an evolution of the math.
Like there a lot of talk of people wanting to make more money. If you want to make more money you have to basically do a lot of reading. If you want more cash you have to make a lot of trades. You can set up your situation so that people come to you for the trade to make cash with or you can go to the people. You can be a door to door salesman or you can set up a retail shop and have people come to you to make your trades. Cash about trades. Money about ideas.


Dropdown Menu Position
- menuPosition will allows users to configure the dropdown menu position.
- Available values for this configuration can be seen as follows.
- [menuPosition]="bottom-right" | "bottom-left" | "top-left" | "top-right" => Note that, there are
4 positions users can configure to align the dropdown. The default value for this config is "bottom-left".
Suggested Links
API Doc for Dropdown
Menu Position


Totally Trivia Trivia
Start
Time Remaining:
The Corect Ansewer Was:
All done, Heres How you did!!
Correct Ansewers:
Incorrect Ansewer:
Unansewered:
Start Over


Overdoses possible in some student deaths on USC campus
LOS ANGELES (AP) - Police investigators are looking into drug overdoses as a potential cause of death among some of the nine students who have died this semester at the University of Southern California.
USC President Carol L. Folt told the Los Angeles Times on Wednesday that the school is working with police and “doubling down” on education and outreach over drug and alcohol abuse.
A letter sent Tuesday to staff and students warned about the dangers of substance abuse, and especially about the increase of contaminated drugs.
The death of nine students since classes began a little more than two months ago has left students and administrators shaken and seeking answers.
Administrators say three deaths were the result of suicide. The causes of the other deaths are either unknown or haven’t been disclosed.
Information from: Los Angeles Times, http://www.latimes.com/
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Copyright © 2019 The Washington Times, LLC.
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Komodo Marketing Manager Audo Kowitz will be speaking at an event in Helsinki, Finland next week on October 8. The event, organized by Konsensus, a Finnish cryptocurrency organization, was partially sponsored by the Komodo Pioneers and will focus on atomic swap technology.


Red Cross says it handed over 10 Afghan soldiers after release by Taliban
GENEVA (Reuters) - The International Committee of the Red Cross (ICRC) said on Thursday it facilitated the release of 10 Afghan security force members detained by the Taliban and handed them over to Afghan authorities.
It followed the release by Afghan Taliban on Tuesday of American and Australian university professors held hostage for more than three years, raising hopes for a revival of peace talks.
“The 10 Afghan National Security Forces members were released and handed over to the ICRC in Helmand Province, in the District of Nahr-e Saraj,” Juan Pedro Schaerer, the ICRC’s head of delegation in Afghanistan said in a statement.
“We transferred them across the frontline to Lashkar Gah where we handed them over to the Afghan authorities at the governor’s office.”


Elastic Beanstalk Environment EnvironmentTier
Describes the environment tier for an AWS::ElasticBeanstalk::Environment resource. For more information, see Environment Tiers in the AWS Elastic Beanstalk Developer Guide.
Syntax
Members
Name
-
The name of the environment tier. You can specify
WebServer
orWorker
.Required: No
Type: String
Update requires: Replacement
Type
-
The type of this environment tier. You can specify
Standard
for theWebServer
tier orSQS/HTTP
for theWorker
tier.Required: No
Type: String
Update requires: Replacement
Version
-
The version of this environment tier. If you don't specify this member, the latest compatible worker tier version is used.
Note
This member is deprecated. Any specific version that you specify may become outdated. We recommend leaving this unspecified.
Required: No
Type: String
Update requires: No interruption


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Making payments for farmers just got easier, better and secure!


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Paypal is easiest way to pay online
Note: To use PayPal as the payment gateway provider for your online course you will need to apply for a Business account with them.
When this is done you will need to follow the steps below:
1.Log in to your Create account.
2.Click "Course" from the Top Menu.
3.Click "Course Settings" on the left-hand menu.
4.Click on "Payment Gateways".
5.Select the "Add New Gateway" button.
6.Click on the "PayPal" logo.
7.Select the type of PayPal integration you would like to use by clicking on the logo.
8.Fill in the required information that appears on the screen.
9.Click the "Add Gateway" button.
10.Your PayPal integration will now appear in your Payment Gateways area
Bank accaunt details
- BANK:
- THE WORLD BANK
- Accaunt number:
-<PHONE_NUMBER>2345
- IBAN:
- 123456789
Note:
1. Log in to the account you plan to send money from, and look for an option to “add an account,” “add external accounts,” or “link accounts.” You might find those options (or something similar) in your bank’s Customer Service or Transfers menu.
2. Provide the other bank’s routing number and your account number at that bank. If you don’t have that information, get those numbers from a check, from that account's online banking account, or from a representative at your bank.
3. After submitting that information, you may need to verify that you own the external account. You typically do this by providing a username and password for that account or by confirming small “test” transfers between the two banks.


DRAFT - HTML4 Test Suite: 7 The global structure of an HTML document
[
Previous
] [
Next
] [
Contents
] [
Specification
]
In this section:
Test 7_4_2-BF-01.html
Test 7_4_2-BF-02.html
Test 7_5_4-BF-01.html
Test 7_5_4-BF-02.html
Test 7_5_5-BF-01.html


Having experimented with smaller doses of Piracetam and Hydergine, and noted the apparent potentiation of the two when taken together, I decided to try an “attack” dose of Piracetam - 5600 mg - in combination with a decent dose of Hydergine - 9 mg. I also took a cap of 250 mg Choline Bitartrate / 250 mg Inositol - which is generally recommended because of Piracetam’s tendency to deplete the brain’s choline reserves.
In my earlier dabblings, I had already found myself slightly surprised by Piracetam and Hydergine - the effects being more pronounced than I had expected from accounts elsewhere. A brief summary of my reactions:
* Increased awareness and enjoyment of detail, both visual and auditory, and a corresponding sense of sparkle in my environment.
* Strong desire to listen to music, and great impatience with the “wrong sort” of music - the “right sort” of music being instrumental music, ideally semi-ambient - not rhythmic/percussive enough to be insistent, but with sufficient structure and imaginative evolution to maintain stimulation.
* Physiological effects associated with vasodilation: slight discomfort of the eyes (which I also sometimes experience with cannabis+tobacco) and slight prickliness in the temples. Also minor stomach discomfort - but my stomach is unusually sensitive.
* General stimulant effect, of a mild amphetamine-like quality.
* Lack of perceived increase in intellectual capacity or memory. “Smart drugs don’t make me smart.” I am a writer, and had hoped for some sharpening of the associated faculties, but on most occasions results were not clear-cut.
* A characteristic “white flash” on opening the eyes after they’ve been closed for a while (also noted by a friend who had tried this combination)
I mention these previous effects in some detail, for the reason that I found the large dosage rather disappointing. A lot of vasodilation, corresponding amount of general stimulant effect, but the “nootropic” mental effects were fairly limited. I gather some people need an initial large dose of Piracetam before it takes effect, but I never found this, and would recommend lower dosages - 800 to 1600 mg Piracetam in combination with 4.5 to 9 mg Hydergine works well for me. And 250 mg choline for good luck. Taken together these three have a much more pronounced effect.
One interesting anecdote from my larger-dose experiment, which is illustrative of the way these drugs work. I had fallen asleep for a while, about an hour after taking them (I find that, apart from general stimulant qualities, noticeable effects from Piracetam and Hydergine don’t kick in until about three or four hours after ingestion - I imagine the sublingual versions hit a lot quicker, but haven’t tried them).
I woke up about three hours later and began looking around the room - the raised wallpaper patterns on my ceiling which become more interesting on nootropics were interesting, but nothing exceptional. Then after a while I tried to move my arms, and couldn’t. Nothing. Couldn’t move my body at all. My first reaction was, “Fuck, looks like I’ve overdone it with this dosage.” Then gradually I realised part of me was still not fully awake. What I was experiencing was in fact the familiar sensation of waking up partially: being able to see, but not yet move my limbs. Except that with the large dose of nootropics, part of me had woken up completely - the visual cortex/cognitive stuff was snap-bang wide awake - but my motor centres had yet to kick in. I guess this is a kind of literal example of the “nootropics wake up my brain” thing, but with the added insight that they wake it up selectively.
I think these are drugs which act quite differently on different people, so it was well worth my experimenting vis-à-vis dosage. But for my money, a combination of modest amounts of each is best - and cheaper too.
One further specific note - this combination might be of interest to anyone involved in performance arts. I sing, scream and play in an improv noise band, and after taking a couple each of Piracetam and Hydergine and one or two drinks, found that my stage performance became quite eccentric. I found myself howling with a great panache, twitching about on the floor and playing my instrument with one foot, and lashing frenetically into our drummer’s cymbals with a bottle of beer. “Playing in a band is fun on smart drugs and alcohol.” (testimonial)
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


This gem generates a NetLinx workspace and source code to start up a Duet module. It is intended to be used when the entire AMX system has been programmed in Duet.
https://sourceforge.net/p/duet-bootstrap/wiki/Home/


WBPCB plans to offer gas connection to roadside food vendors
WBPCB secretary Rajesh Kumar said the pollution control body plans to offer environment-friendly LPG cylinders to food vendors
by PTITo reduce air pollution the West Bengal Pollution Control Board (WBPCB) plans to offer gas connections to roadside food vendors who use coal or wood fired ovens (open chullahs) for cooking.
WBPCB secretary Rajesh Kumar said the pollution control body plans to offer environment-friendly LPG cylinders to food vendors with the support of oil PSUs like Indian Oil Corporation and Hindustan Petroleum Corporation.
Mr. Kumar said this during a recent meeting with Concern for Calcutta, a statement issued by the NGO said on Monday.
The WBPCB Secretary said legal action would be taken against hawkers if they continue to use solid fuels.
As per the Air Quality Action Plan, approved by Central Pollution Control Board and the National Green Tribunal, the components that contribute substantially to air pollution are coal or wood-fired ovens, which have high air pollution potential.
Mr. Kumar also asked people to download and use the ‘Paribesh’ app through which citizens can instantly complain about garbage-related problems or problems of waste burning on roadsides, it said.
He also underlined the plan to eliminate the menace of plastic by creating incentives like paying a small amount for collecting and depositing the waste plastic like milk pouches, the statement added.


Here is a timeline of Margaret Hamilton's life and accomplishments:
August 17, 1936 - Born in Paoli, Indiana to Kenneth Heafield and Ruth Esther Heafield.
1954 through 1958 - After graduatating Hancock High School, she enrolled at University of Michigan as a math major, transferred to Earlham College and graduated with a BA in philosophy and mathematics in 1958.
Autumn 1958 - Started graduate program in abstract mathematics at Brandeis.
1960 - took interim position at MIT to develop software for predicting weather on the LGP-30 and the PDP-1 computers (at Marvin Minsky's Project MAC) for professor Edward Norton Lorenz in the meteorology department. Computer science an programming were nascent fields.
1961 through 1963 - SAGE (Semi-Automatic Ground Environment) Project at Lincoln Lab, the first U.S air defense program. She wrote software for the first AN/FSQ-7 computer (the XD-1) to search for unfriendly aircraft; she also wrote software for the Air Force Cambridge Research Laboratories.
1964 - joined the Charles Stark Draper Laboratory at MIT, which at the time was working on the Apollo space mission. She eventually led a team credited with developing the software for Apollo and Skylab.
1976 through 1984 - Hamilton was the CEO of a company she co-founded called Higher Order Software (HOS) to further develop ideas about error prevention and fault tolerance emerging from her experience at MIT.
Coined the term software engineering to raise the status of software development on par with that of other engineering disciplines and to distinguish it from other kinds of engineering.


bugpoint narrows down the source of problems in LLVM tools and passes. It can be used to debug three types of failures: optimizer crashes, miscompilations by optimizers, or bad native code generation (including problems in the static and JIT compilers). It aims to reduce large test cases to small, useful ones. For example, if opt crashes while optimizing a file, it will identify the optimization (or combination of optimizations) that causes the crash, and reduce the file down to a small example which triggers the crash.
For detailed case scenarios, such as debugging opt, llvm-ld, or one of the LLVM code generators, see How To Submit a Bug Report document.
bugpoint is designed to be a useful tool without requiring any hooks into the LLVM infrastructure at all. It works with any and all LLVM passes and code generators, and does not need to "know" how they work. Because of this, it may appear to do stupid things or miss obvious simplifications. bugpoint is also designed to trade off programmer time for computer time in the compiler-debugging process; consequently, it may take a long period of (unattended) time to reduce a test case, but we feel it is still worth it. Note that bugpoint is generally very quick unless debugging a miscompilation where each test of the program (which requires executing it) takes a long time.
bugpoint reads each .bc or .ll file specified on the command line and links them together into a single module, called the test program. If any LLVM passes are specified on the command line, it runs these passes on the test program. If any of the passes crash, or if they produce malformed output (which causes the verifier to abort), bugpoint starts the crash debugger.
Otherwise, if the -output option was not specified, bugpoint runs the test program with the C backend (which is assumed to generate good code) to generate a reference output. Once bugpoint has a reference output for the test program, it tries executing it with the selected code generator. If the selected code generator crashes, bugpoint starts the crash debugger on the code generator. Otherwise, if the resulting output differs from the reference output, it assumes the difference resulted from a code generator failure, and starts the code generator debugger.
Finally, if the output of the selected code generator matches the reference output, bugpoint runs the test program after all of the LLVM passes have been applied to it. If its output differs from the reference output, it assumes the difference resulted from a failure in one of the LLVM passes, and enters the miscompilation debugger. Otherwise, there is no problem bugpoint can debug.
If an optimizer or code generator crashes, bugpoint will try as hard as it can to reduce the list of passes (for optimizer crashes) and the size of the test program. First, bugpoint figures out which combination of optimizer passes triggers the bug. This is useful when debugging a problem exposed by opt, for example, because it runs over 38 passes.
Next, bugpoint tries removing functions from the test program, to reduce its size. Usually it is able to reduce a test program to a single function, when debugging intraprocedural optimizations. Once the number of functions has been reduced, it attempts to delete various edges in the control flow graph, to reduce the size of the function as much as possible. Finally, bugpoint deletes any individual LLVM instructions whose absence does not eliminate the failure. At the end, bugpoint should tell you what passes crash, give you a bitcode file, and give you instructions on how to reproduce the failure with opt or llc.
The code generator debugger attempts to narrow down the amount of code that is being miscompiled by the selected code generator. To do this, it takes the test program and partitions it into two pieces: one piece which it compiles with the C backend (into a shared object), and one piece which it runs with either the JIT or the static LLC compiler. It uses several techniques to reduce the amount of code pushed through the LLVM code generator, to reduce the potential scope of the problem. After it is finished, it emits two bitcode files (called "test" [to be compiled with the code generator] and "safe" [to be compiled with the C backend], respectively), and instructions for reproducing the problem. The code generator debugger assumes that the C backend produces good code.
The miscompilation debugger works similarly to the code generator debugger. It works by splitting the test program into two pieces, running the optimizations specified on one piece, linking the two pieces back together, and then executing the result. It attempts to narrow down the list of passes to the one (or few) which are causing the miscompilation, then reduce the portion of the test program which is being miscompiled. The miscompilation debugger assumes that the selected code generator is working properly.
bugpoint can generate a lot of output and run for a long period of time. It is often useful to capture the output of the program to file. For example, in the C shell, you can run:
bugpoint ... |& tee bugpoint.log
to get a copy of bugpoint's output in the file bugpoint.log, as well as on your terminal.


| < Day Day Up > |
Appendix A. DB2 Sample TablesThis appendix provides information on the DB2 sample tables used in most of the figures and examples in this book. These tables are used as examples in this book as a convenience because they are bundled with DB2, installed at most DB2 shops, and are generally available for everyone's use. An understanding of the data in the sample tables and the relationship between these tables is imperative to understanding the SQL in this book. The DB2 sample tables primarily contain information about projects and the entities involved in working on these projects. Figure A.1 shows these entities and the relationships between them. Figure A.1. DB2 sample table relationships.The sample tables represent departments, employees, projects, activities, activities assigned to a project, and employees assigned to a project's activities. In the following sections, you can find a general description of each table, its columns, and its relationship to the other sample tables, along with its table creation DDL. |
| < Day Day Up > |