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FIFA Women's coaching course underway in Pampram
A 5-day FIFA Women Coaching course for Women football Coaches in Ghana has commenced today at the Ghanaman Soccer centre of Excellence in Prampram.
The course, fully funded by FIFA, is to provide the coaches with some form of training in the areas of women football coaching and development.
In all, 32 coaches drawn from the three National female teams,the Women National league clubs and some selected schools are beneficiaries of this all important refresher Course.
Gracing the opening of the Course were Executive Committee members, Habiba Attah Forson and Samuel Anim Addo and Technical Director of the Ghana football Association, Francis Oti Akenteng.
Habiba Attah Forson was grateful to FIFA for this refresher course at a time where Ghana football is preparing to take full flight while Samuel Anim Addo who represented the Ghana Football Association’s President, Kurt Edwin Simon Okraku reiterated how the new administration has women football at heart, and promise to ensure massive improvement is seen in the game during their tenure.
Renowned FIFA instructor Jaqueline Shipanga from Namibia will be taking the coaches through this five days intensive FIFA Women coaching course.
The coaches will be taking through the theoretical aspect and then moved to the field to perform the practical aspect of the course.
Credit: Ghanafa.org


--- layout: post title: Thailand enforces PAYG registration date: 2005-11-15 00:00:00 category: mobile ---
Thailand enforces PAYG registration (via Dave): "From midnight all unregistered phones will have their signals blocked, a move Thai officials hope will prevent their use as improvised bomb detonators."


I've noticed that my students on occasion will try to guess the originating user of each tweet on a timeline. Through my most recent foibles, I had created a Python app that hit my home timeline, filtered only my students and returned some JSON. I had been wanting to work with React again, so I refactored everything into Javascript and built a nice little front end interface for it.
View ProjectData has become extremely important to me lately in my coding studies, but I've been using Pandas along with the Juypter Notebook and Matplotlib to create my visualizations. It's super easy and fast, but, I wanted to get back to JS a little bit, so for this project I levereaged Plotly.js to create a line chart comparing completion percentage for my two classes. The graphing part was easy, it was making the backend on Google Apps Script that was super hard. I still need to hook up an update route.
View ProjectAfter some time away, I really wanted to get back into React and review all the basics. So, I created a tiny little math game. I think it could be pretty useful for quizzing over the Pythagorean Triples. Of course those are very useful :-) I'd like to add styling at some point, but once again, that's not what I particulary enjoy.
View ProjectThis project was a follow up to my rock paper scissors game. I really enjoyed working with events in Socket IO and wanted to do a lot more with my React interface. This also utilizes the react router. The major improvement over the rock paper scissors server is using rooms instead a list, so the server can host more than one game at a time and players can join the game they want, as opposed to get getting the next random player. The logic is rough, I did quite a few vanilla Javascript projects after this to get better with that.
View ProjectThis project was all about leveraging a multidimensional array to predict collisions with walls and targets. Previously I used the distance formula, but found checking array values to immensely easier for something that is so simple. This is probably one of my favorite projects. I left it alone for a little while, and came back to finish it up.
View ProjectThis was the first app written without a framework. It is done in vanilla Javascript. I didn't even use jQuery! I did this project to help myself understand the language better, especially objects and the "this" keyword. I also was able to utilize some mocha unit testing with the chai assert framework. This was made possible by separating the UI from the game logic. Functionality is tied together by emitter events. Also, notice use of the canvas element to provide the game graphics. Admittedly, look and feel is not my strong point... yet :-)
View ProjectThis was originally done with EJS rendered template views, but I have recently refactored it into a single page app with React Router. It still needs major styling improvements, but it is ready for use in the next school year. I will be able to add quizzes via a command line interface, students will be able to view and take the most recent and active quizzes. It gives instant feedback and the ability to delete low grades, since the primary purpose is to give them rapid feedback. If you want to peek about use these credentials.
Email<EMAIL_ADDRESS>Password: dummy
View ProjectI used React and Socket IO in this project. Originally, all the UI was done with jQuery, but then I refactored it into a React app. Open two tabs to play :-)
View ProjectThe first web app I did was written with Django. I wrote it in order to faciliate an elective class at school, where kids searched the campus for hidden geocaches according to coordinates listed on the website. It was pretty much like a blog, with posts and comments. It had one added feature, which was the ability to generate a GPX file for the geocache, which is just a XML document. This site is no longer live.


+++ title = "Long way to Mérida" slug = "long-way-to-merida" date = 2007-02-27T06:00:00+10:00 tags = ["tedious", "bus-trips"] locations = ["mexico/merida"] draft = false summary = """
Just finished about 17 hours' worth of bus rides, to get from Veracruz to Mérida. This trip was way too long: I should have gotten a plane instead. Ah well: at least I saved on a night's accommodation, by getting a night bus and sleeping all the way.
""" +++Just finished about 17 hours' worth of bus rides, to get from Veracruz to Mérida. This trip was way too long: I should have gotten a plane instead. Ah well: at least I saved on a night's accommodation, by getting a night bus and sleeping all the way.
The worst thing about this bus trip was not the trip itself. It was the fact that I arrived at the bus terminal in Mérida at about 5:30am. Too early to rock up at a hostel. Too bright and noisy to go to sleep. I killed about an hour by reading a book, then I buggered off outta there.


jQuery
Form Validation
Goal
- Prevent a user from submitting using client-side code.
- As a developer, prevent the form action when at least one field is blank
- As a user, I want to see an instruction message when the input field is blank
- As a user, I want the submit button to shake when form is invalid
- As a user, when form is invalid, I want the first blank field to be in focus
- As a user, I want to see a colour change of the in focus field outline
Technologies
- jQuery
- JavaScript
- CSS
- HTML
Live demo


Kamael Skills Menu
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Welcome to Ajioz First dAPP : CRUD
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A Brief Comparison of JavaScript and Ruby
We were spoiled...
August 2, 2015
After working with Ruby for the past few weeks, I felt the switch into JavaScript for the first time these past few days was… interesting. It’s certainly a harder language to pickup intuitively as it lacks some of the natural language syntax that Ruby offers. However, it makes a huge difference going into JavaScript with a little bit of programming experience under your belt. You’re able to quickly recognize common syntax and still maintain an instinctive intuition of what you want the code to do. Here are some interesting differences between Ruby and JavaScript.
On a previous blog post, I briefly touched on the differences between OO (Object Oriented) languages and Functional programming languages. Now technically, JavaScript is indeed an OO language, but, interestingly enough it retains many properties of Functional languages. Some programmers like to think of it as a “happy medium” between the two, but as a whole it is still an OO language. So we’re on familiar grounds.
We are probably familiar with Ruby methods and the Enumerable (Ruby’s built-in data structures) by now, but I have to warn you, we were spoiled! JavaScript does not have any fancy built-in data structures, although it does still have ‘Objects’. JS Objects are basically self-defined data structures for any defined variable. This is an aside from the built in native structures such as the Boolean and String. They typically look like this:
meMyself = {
height: 0,
weight: 0,
passTest: true
}
If that looks familiar, it’s because the syntax is nearly identical to Object literal Hash formation in Ruby. In JS, it’s not a hash, not really at least, but it does act similar. They are both collections of references to other objects. In Ruby we use the key/value pair relationship, while in JS we use the property/value term. Pretty neat right?
Let’s also take a look at Ruby classes and JavaScript constructor functions. This is where the whole Object-oriented thing starts to come into focus. JS objects come into play through constructor functions; similar to Ruby classes that create ‘instances’ of objects. In Ruby we define the behavior of the instances within the class, while in JS, we use something called “prototype objects” which are responsible for defining the behavior of instances. It looks like this:
function dog (name, breed, age) { this.name = name; this.breed = breed; this.age = age; }
One last thing. DON’T FORGET THE SEMICOLONS! JavaScript uses semicolons to tell the computer that it has reached the end of a line of code or an instruction. Think of it like a period at the end of a sentence. They are important. Your code will run without them, but it will also start doing strange things without explanation the bigger your project gets. Don’t forget them (I did… a few times).


In 1993 Holger Tewis and Sven Anders, in school, there was a tetris hype. We developed a game that we can play together, called FISHTRIS. It was devoled under Borland Pascal and was running in MS-DOS 5.0. In 2014 we started a new Network based clone. We took the Tetris game from Jake Groden, and extended it.
It is still under development. Any help is wanted!
You can download the original DOS programm, it works under linux in a dosbox, even in 2014!
Two player play tetris. For every row the filled, they got "GNU-Points".
This GNU points can be used to do thinks like:
| Number of GNU | Name | Effect |
|---|---|---|
| 3 | Gnubaby | remove a row at the opponent |
| 6 | Tonne | send the opponent a tonne |
| 8 | Blubber | remove 3 rows at the opponent |
| 12 | Ringel | remove a row in your game |
| 15 | Wonne | the next item will be a tonne |
| 20 | Riegel | remove 3 rows at your game |
| 22 | BigFISH | send the opponent a FISH |
| 24 | Schneck | slow down your game |
| 26 | Bohrer | make holes in the the opponent |
| 30 | OberGNU | make the game of the opponet faster |
A tonne is this:
xxxx
And a FISH is this:
x x
x xx
x x
Sven Anders, Neehusenstraße 11a, 21147 Hamburg, fishtris2014 (at) sven (dot) anders (dot) im


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Manage the information for this storage configuration.
Enter information for your new storage configuration.
Storage Type
Select 'local' if you want to store
files on your local server.
Name
The name of this particular storage
configuration. This will be used to identify storage configurations when multiple are available.
Local Path
If you selected a type of 'Local',
this is the base path where you want your files stored. For example:
c:/knappsack/files or
/home/user/knappsack/files
Registration Default
By setting this field you are
specifying that any public Organization registrations will use this storage configuration. Note:
Only one storage configuration can be default at a time.


★ To spread the love of mathematics to the obscure areas of the world where mathematics is feared and/or disrespected.
★ To offer an ideal avenue for a free exchange of mathematical ideas and for frank and helpful criticism of these ideas.
★ To promote an interest and awareness of mathematics through a social and intellectual environment
★ To help students in developing heuristic and problem-solving attitude.
★ To create a platform for the students to develop intuitive, explorative and creative thinking skills.
★ To offer a social outlet for students with a serious interest in mathematics to work on problem solving techniques that go beyond regular classroom curriculum.
★ To enjoy mathematics and develop patience and persistence when solving problems
★ To organize lectures, events and competitions to promote the beauty & applicability of Mathematics.
★ experience mathematics outside of regular course work
★ learn some of the great mathematicians and their revolutionary contribution.
★ inculcate feeling of discovery and development.
★ improve the following organizational skills.
☆ Inter/intra-group collaboration
☆ Idea actualization; event planning and organization
"Mathematics is the sense you never knew you had"
Events & Workshops Conducted until now
outreach activities
Mathathons organized till date
Club Members
Exciting Events and sessions are lined up! Register now


Pakistan embassy resumes visa for Afghan patients
by Abuzar AfridiLANDI KOTAL: In a goodwill gesture, the Pakistan embassy in Kabul has resumed issuing visa on medical grounds despite the closure of consular services due to harassment of Pakistani officials by Afghan intelligence agencies, said a press release issued on Wednesday.
However, the counselors section will remain closed. On Monday, the Pakistan Embassy announced the closure of the visa section for an indefinite period due to security concerns.
The Foreign Office on Sunday issued a statement that said Pakistani diplomats in Kabul were being harassed. It had also summoned Afghan Charge d’Affaires to protest against the incident.
A Pakistan Embassy official on condition of anonymity told The Express Tribune that they closed the visa section after two incidents of harassment were reported in the Afghan capital.
Scores of Afghan citizens – particularly Afghan students, patients, and businessmen – have been affected by the closure. A source said on a daily basis 1,500 visas are issued to Afghan nationals.
The Afghan Consulate in Peshawar is still closed for the last three weeks over a land dispute between a Pakistani citizen and the Afghan government. The Supreme Court has ruled in favour of the Pakistani citizen and dismissed the Afghan government claims of ownership.
Kabul has refused to accept the decision and claimed the property belongs to the Afghan National Bank.


class Jekyll::Theme
Attributes
name[R]
Public Class Methods
new(name)
click to toggle source
# File lib/jekyll/theme.rb, line 7 def initialize(name) @name = name.downcase.strip configure_sass end
Public Instance Methods
configure_sass()
click to toggle source
# File lib/jekyll/theme.rb, line 32 def configure_sass return unless sass_path require "sass" Sass.load_paths << sass_path end
includes_path()
click to toggle source
# File lib/jekyll/theme.rb, line 20 def includes_path path_for :includes end
layouts_path()
click to toggle source
# File lib/jekyll/theme.rb, line 24 def layouts_path path_for :layouts end
root()
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# File lib/jekyll/theme.rb, line 12 def root # Must use File.realpath to resolve symlinks created by rbenv # Otherwise, Jekyll.sanitized path with prepend the unresolved root @root ||= File.realpath(gemspec.full_gem_path) rescue Errno::ENOENT, Errno::EACCES, Errno::ELOOP nil end
sass_path()
click to toggle source
# File lib/jekyll/theme.rb, line 28 def sass_path path_for :sass end
Private Instance Methods
gemspec()
click to toggle source
# File lib/jekyll/theme.rb, line 51 def gemspec @gemspec ||= Gem::Specification.find_by_name(name) rescue Gem::LoadError raise Jekyll::Errors::MissingDependencyException, "The #{name} theme could not be found." end
path_for(folder)
click to toggle source
# File lib/jekyll/theme.rb, line 40 def path_for(folder) path = realpath_for(folder) path if path && File.directory?(path) end
realpath_for(folder)
click to toggle source
# File lib/jekyll/theme.rb, line 45 def realpath_for(folder) File.realpath(Jekyll.sanitized_path(root, "_#{folder}")) rescue Errno::ENOENT, Errno::EACCES, Errno::ELOOP nil end


I was the first product designer to join Ansarada working in a distributed team. I joined them at the time where the company was re-strategising as an AI driven company. There were a lot of features needed a refresh to reflect a smarter feel and integrate new functions. I worked on several new features that spearheaded this refresh.
‘Insights Email’ was a weekly email that was sent to our users to inform their stakeholders’ engagement by tracking their activity on our platform.
‘Insights Email’ was a weekly email that was sent to our users to inform their stakeholders’ engagement by tracking their activity on our platform. While the product was successful, the data science team have produced a single universal metric — called the “Bidder Health Check” . The score improves users’ experience by helping them gain insights without having to plough through multiple report cards though an email. This was the first time the company was integrating machine learning results into its product and our CEO was keen to release this as part of our rebranding strategy. This required a new set of designs that reflected this thinking as well as taking into account where we were heading in terms of visual branding. I was product designer of the team who brought this experience to life.
The existing design language had a distinct look and layout rules. This was great for assembling simple pages rapidly but presented many constraints for richer data and visualisation displays.
Even though the new brand was not fully formed yet, I decided to try out my designs using the new brand to see if it helps resolve the constraints I was facing in terms of layout and overall visual harmony. The new brand uses a completely new set of font – Lexia /Aktiv Grotesk that is tighter reflects a different mood.
I spent some time applying the new design principles onto some of our current products to understand how we could transform into the new framework but still maintaining overall coherence. From these experiments, I picked out a few key principles and styles and presented them back to the design team. Once we were happy with these upgrades, I carried on with my task, which is to come up with the new insights email design which is now known as the “Bidder Engagement Score”.
Apart from how things look, I recommended a redesigning a few design components as they were no longer fit for our purpose. I made sure I built a clear case on how these new components should be used clearly communicated them with our lead interface architect.
When it came to specifying guidelines for the trand chart, I made sure I balanced style with a logical layout. The challenge with laying out a chart for the viewer is being able to highlight key metrics while keeping the x and y axis tickmarks visible. A lot of thinking went behind finding the right interval for the tickmarks as the accounted period increased, without breaking our grid system.
The email was supposed to tell stakeholders how likely are their clients able to submit a bid, at a glance. Even though predictive results may not be 100% accurate, I tried my best to ensure our message was reflected clearly in the design.
The key thing was to help our viewers understand why the predictions turn out the way they were. And more importantly, making sure there are enough visual cues to help viewers confirm their gut feel about an outcome.
The hero chart was the single element that told the bulk of the story. The daily breakdown gives the viewer mental checkpoints whether certain events should have happened.
And if something didn’t align with their assumption, the “positive and negative” drivers were supposed to further support those predictions. Using the right terminology for these predictors was something I advocated for since the beginning. Having worked on and with many analytical stakeholders in the past, it was vivid to me that explaining the “why” behind the number is just as, if not more important than the “what”.
In this example, it was critical that we distinguished these factors as events that drove the predictive score “positively” or “negatively”. The initial iteration uses an “up” and “down” arrow without clear messaging and many people thought it was simply saying that these activities have decreased in volume, which is not the case.
By changing it to a "positive(+)" and "negative(-)" sign, people were less likely to misunderstand the intent behind it and were more open to the fact they were drivers rather than results.
Numerals can also be expressed in many forms to create a consistent and distinct viewing rhythm. Do Treat the number like a symbol, giving them sufficient padding and white space.


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Unlimited possibilities. Experience the 360.
Europe
Europe, in particular ancient Greece, is the birthplace of Western civilization.[6][7][8] The fall of the Western Roman Empire, during the migration period, marked the end of ancient history and the beginning of an era known as the Middle Ages. The Renaissance humanism, exploration, art, and science led the old continent, and eventually the rest of the world, to the modern era. From this period onwards, Europe played a predominant role in global affairs. Between the 16th and 20th centuries, European nations controlled at various times the Americas, most of Africa, Oceania, and the majority of Asia.


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As city skylines climb higher and the need for service and modernization increases, Canada’s elevator industry is growing rapidly. Regulatory bodies across the country work to ensure that every new installation and existing elevator operates legally and, most importantly, safely. Each elevator safety authority adheres to different regulations; it is critical that owners, contractors, and other parties know where to find accurate information.
Acts, Regulations, and Elevator Compliance
The why behind elevator regulations is simple – and universal: to protect public safety. The how varies by jurisdiction. Legislative bodies pass laws, or acts, which set out the technical standards related to “elevating devices”. Regulations explain how owners, elevator contractors, and others can follow there legal requirements.
Take, for example, Ontario’s Technical Standards and Safety Act (TSSA). The law contains several regulations, such as:
Every owner of a passenger elevator shall ensure that… the name and telephone number of the contractor currently maintaining the elevator is readily available, together with the expiry of the elevator maintenance contract. O. Reg. 209/01, s. 38.
The regulations in TSSA, as in other provinces’ elevating devices acts, cover everything from licensure and design submissions to fees and inspections.
As mentioned, each jurisdiction has its own acts and regulations, though they are often quite similar. The overall goal is to promote safety, but the specifics on how authorities administer and enforce regulations vary from one jurisdiction to the next.
Owning Responsibility for Code Compliance
While owners assume ultimate responsibility for the safe design, installation, and operation of their elevators, contractors and maintenance companies play a central role in compliance. Typically more well-versed in specific regulations, they can help owners navigate the complex world of codes and standards. Knowing where to turn for information and assistance is essential for both parties.
The following is a list of jurisdictional authorities across Canada. Their websites contain relevant legislation, requisite forms, bulletins, and more to help owners and professionals comply with applicable laws:
Because regulations differ from location to location – and because they change frequently (i.e. they are updated about every three years), it is important that owners, contractors, and maintenance professionals stay connected with the elevator safety authority in their jurisdiction.
Safety and compliance are twin goals of every elevator installation. Building owners and contractors can rely on their jurisdictional elevator safety authority for up-to-date information to ensure they meet all applicable requirements.


Discover more about our history, principles and strategy
All the courses are certified by DGERT
Educate teachers and trainers emphasising their motivation, emotional intelligence, and creativity.
More infoImprove skills related to leadership, communication, team management, and conflict prevention.
More infoIdentify the fundamental concepts related to work security, as well as the main causes and consequences of work accidents.
More infoSecurity against fire risks, accident management, work psychosociology, and operational training.
More info


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Thank you for placing your order with {{ shop_name }}!
This email is to confirm your recent order.
Date {{ date | date: "%m/%d/%Y" }}
{% if requires_shipping %}
Shipping address
{{ shipping_address.name }}
{{ shipping_address.address1 }}
{% if shipping_address.address2 != nil %}
{{ shipping_address.address2 }}
{% endif %}
{{ shipping_address.city }}
{{ shipping_address.province }} {{ shipping_address.zip }}
{{ shipping_address.country }}
{% endif %}
Billing address
{{ billing_address.name }}
{{ billing_address.address1 }}
{% if billing_address.address2 != nil %}
{{ billing_address.address2 }}
{% endif %}
{{ billing_address.city }}
{{ billing_address.province }}
{{ billing_address.zip }}
{{ billing_address.country }}
|
|
Description
|
Qty
|
Price
|
{% for line in line_items %}
|
|
{{ line.title }}
{% for p in line.properties %}
{% unless p.last == blank %}
- {{ p.first }}: {{ p.last }}
{% endunless %}
{% endfor %}
|
{{ line.quantity }}
|
{{ line.price | money }} each
|
{% endfor %}
{% if discounts %}
Discounts: {{ discounts_savings | money_with_currency }}
{% endif %}
Subtotal: {{ subtotal_price | money_with_currency }}
{% for tax_line in tax_lines %}
{{ tax_line.title }}: {{ tax_line.price | money_with_currency }}
{% endfor %}
{% if requires_shipping %}
Shipping: {{ shipping_price | money_with_currency }}
{% endif %}
Total: {{ total_price | money_with_currency }}
If you have questions about your order, please call {{ shop.phone | prepend: '+' }} or send a message to {{ shop.email }}
|


My wife who is out of town ordered me groceries with lovely snacks via the internet. Sometimes the future is kinda cool.
10/18/2016, 3:07:38 PM
Favs: 8
Retweets: 0
link--- layout: tweet ---
My wife who is out of town ordered me groceries with lovely snacks via the internet. Sometimes the future is kinda cool.
10/18/2016, 3:07:38 PM
Favs: 8
Retweets: 0
link


{% load i18n %} {% block content %}
Please manage REST Services within the new user interface. Go to the Project Dashboard and navigate to Your Project > Settings > REST Services.


This tool lets you create your own custom radar maps (like the ones above), to embed within a website or blog as an HTML iFrame. The radar imagery updates live every 10 minutes from RainViewer.com. Alternatively you can take static screenshot images of the map to archive or share on social media.
Fill in the form below to customize the starting location, zoom level and style of your map. The settings scroll to reveal more. Informational tooltips explaining each setting are displayed on mouseover. An optional map marker can be added too if required (like for showing a current location or a radar station). As you change the settings, the map permalink and iFrame code will update automatically, ready to copy. A preview of the compiled map is also displayed.


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An L-System library for the KA processing environment
This website is a work in progress!
The axiom can be made up of these characters: F, X, + , -, [, and ]. You should always have the same amount of "["s and "]"s.
| from | to |
|---|---|
| F | FF |
| X | The original axiom (starting point) |
| char | command |
|---|---|
| F | goes forwards |
| + | rotate right |
| - | rotate left |
| [ | push position (saves the position for later) |
| ] | pop position (go back to the last push position) |


Enduro enjoyed by all
Competitors in the annual Pilgrims Enduro event, and the last one in the 2019 Series organised by the Lowveld Enduro Club, were treated to the perfect enduro weather on Saturday November 9.
by Matthys FerreiraIt was overcast and at times, quite chilly between the koppies of the historic Pilgrim’s Rest. It was a day, though, that reverberated the sounds of engines around the hills and throughout town.
The Lowveld Enduro Club has become quite famous for the excellent routes offered by every single event in the series, and is thus well supported by riders from all over.
This event drew no less than about 220 entrants. Why is this?
ALSO READ: Harley chapters ride for goodwill at Rainbow Slowveld Bash
“Well,” said Robin Flores, “we have devised a formula, or recipe if you want, that caters for every single type of rider; the little one, the first timer, the old timer, the pros, the weekenders and lady riders – experienced or not.
If you have a bike and want to ride and develop your skills in a controlled and safe, but still challenging, environment, we’ve got you covered.
The categories are also structured in a manner that provides riders with options of, for example, riding perhaps one red loop and two green loops, and so forth. And depending on the latter, riders can do up to 60km on the day of the event.”
With enduro riding, more often than not involving the whole family, the challenge for route master Flores was to offer routes that will challenge the brave and experienced riders as well as encourage the young ones to venture out and copy Dad on a less daunting route just around the pit area.
The pink route was ideal for the latter, and also introduced the little ones to water crossings. Albeit often requiring more than just a little help from either Dad or friends. It is endearing (and sometimes not) on so many levels to observe the gentle coaching that occurs between dads and sons at these crossings.
ALSO READ: Ringbrothers unveil one-of-a-kind Ford Mustang
Then there is a Green and Red route – the latter being seriously challenging and ideally suited to the pro riders. The top three finishers in the Pro Elite class at this event were Mauritz Meiring, followed by Barend Erasmus and then Robert Garvie in third.
“We cater for family participation – scenic and challenging routes. Our events are considered to be of the best one-day enduro riding experiences in the country,” said Robin. “Our formula is sha na na – our organisation is top notch. So if you have not as yet experienced the best, it is time!”


How to order a Buddy the Elf frappuccino from Starbuck's secret menu
It's made with peppermint sauce, whipped cream and Christmas sprinkles
by Danny ThompsonThere any many tell tale signs Christmas is on the horizon.
One of them is Starbucks releases its festive drinks menu and another is Will Ferrell's Elf comes on the telly.
Now you have the chance to bring these two Christmas delights together, with a secret festive drink nicknamed the Buddy the Elf frappuccino.
But if you want to try the Buddy the Elf frap you can't just outright ask for it.
Website Totally The Bomb claims you have to ask for a particular drink with specific extras to get the desired look.
You need to ask for a Matcha Frappuccino, specifically with peppermint syrup instead of the normal one it comes with.
The request it be topped with whipped cream and red and white Christmas sprinkles.
The resulting drink has beautiful festive colours, and has a striking resemblance to Buddy the Elf.
On their website, Totally The Bomb wrote: "This drink is really good. I love the pairing of the matcha with the peppermint. It’s strange but oddly satisfying!"


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Before Change
if attack_success:
logger.debug("Margin Loss <= 0 --> Attack Success!")
if l2dist < best_l2dist:
logger.debug("New best L2Dist: %f (previous=%f)" % (l2dist, best_l2dist))
best_l2dist = l2dist
best_adv_image = adv_image
// compute gradient:
logger.debug("Compute loss gradient")
perturbation_tanh = -self._loss_gradient(z, target, image, adv_image, adv_image_tanh,
c, clip_min, clip_max)
// perform line search to optimize perturbation
// first, halve the learning rate until perturbation actually decreases the loss:
prev_loss = loss
best_loss = loss
best_lr = 0
halving = 0
while loss >= prev_loss and halving < self.max_halving:
logger.debug("Apply gradient with learning rate %f (halving=%i)" % (lr, halving))
new_adv_image_tanh = adv_image_tanh + lr * perturbation_tanh
new_adv_image = self._tanh_to_original(new_adv_image_tanh, clip_min, clip_max)
_, l2dist, loss = self._loss(image, new_adv_image, target, c)
logger.debug("New Total Loss: %f", loss)
logger.debug("New L2Dist: %f", l2dist)
logger.debug("New Margin Loss: %f", loss-l2dist)
if loss < best_loss:
best_loss = loss
best_lr = lr
lr /= 2
halving += 1
lr *= 2
// if no halving was actually required, double the learning rate as long as this
// decreases the loss:
if halving == 1 and loss <= prev_loss:
doubling = 0
while loss <= prev_loss and doubling < self.max_doubling:
prev_loss = loss
lr *= 2
logger.debug("Apply gradient with learning rate %f (doubling=%i)" % (lr, doubling))
doubling += 1
new_adv_image_tanh = adv_image_tanh + lr * perturbation_tanh
new_adv_image = self._tanh_to_original(new_adv_image_tanh, clip_min, clip_max)
_, l2dist, loss = self._loss(image, new_adv_image, target, c)
logger.debug("New Total Loss: %f", loss)
logger.debug("New L2Dist: %f", l2dist)
logger.debug("New Margin Loss: %f", loss-l2dist)
if loss < best_loss:
best_loss = loss
best_lr = lr
lr /= 2
if best_lr >0:
logger.debug("Finally apply gradient with learning rate %f", best_lr)
// apply the optimal learning rate that was found and update the loss:
adv_image_tanh = adv_image_tanh + best_lr * perturbation_tanh
adv_image = self._tanh_to_original(adv_image_tanh, clip_min, clip_max)
z, l2dist, loss = self._loss(image, adv_image, target, c)
attack_success = (loss - l2dist <= 0)
overall_attack_success = overall_attack_success or attack_success
// Update depending on attack success:
if attack_success:
logger.debug("Margin Loss <= 0 --> Attack Success!")
if l2dist < best_l2dist:
logger.debug("New best L2Dist: %f (previous=%f)" % (l2dist, best_l2dist))
best_l2dist = l2dist
best_adv_image = adv_image
if overall_attack_success:
After Change
if attack_success:
logger.debug("Margin Loss <= 0 --> Attack Success!")
if l2dist < best_l2dist:
logger.debug("New best L2Dist: %f (previous=%f)", l2dist, best_l2dist)
best_l2dist = l2dist
best_adv_image = adv_image
// compute gradient:
logger.debug("Compute loss gradient")
perturbation_tanh = -self._loss_gradient(z, target, image, adv_image, adv_image_tanh,
c, clip_min, clip_max)
// perform line search to optimize perturbation
// first, halve the learning rate until perturbation actually decreases the loss:
prev_loss = loss
best_loss = loss
best_lr = 0
halving = 0
while loss >= prev_loss and halving < self.max_halving:
logger.debug("Apply gradient with learning rate %f (halving=%i)", lr, halving)
new_adv_image_tanh = adv_image_tanh + lr * perturbation_tanh
new_adv_image = self._tanh_to_original(new_adv_image_tanh, clip_min, clip_max)
_, l2dist, loss = self._loss(image, new_adv_image, target, c)
logger.debug("New Total Loss: %f", loss)
logger.debug("New L2Dist: %f", l2dist)
logger.debug("New Margin Loss: %f", loss-l2dist)
if loss < best_loss:
best_loss = loss
best_lr = lr
lr /= 2
halving += 1
lr *= 2
// if no halving was actually required, double the learning rate as long as this
// decreases the loss:
if halving == 1 and loss <= prev_loss:
doubling = 0
while loss <= prev_loss and doubling < self.max_doubling:
prev_loss = loss
lr *= 2
logger.debug("Apply gradient with learning rate %f (doubling=%i)", lr, doubling)
doubling += 1
new_adv_image_tanh = adv_image_tanh + lr * perturbation_tanh
new_adv_image = self._tanh_to_original(new_adv_image_tanh, clip_min, clip_max)
_, l2dist, loss = self._loss(image, new_adv_image, target, c)
logger.debug("New Total Loss: %f", loss)
logger.debug("New L2Dist: %f", l2dist)
logger.debug("New Margin Loss: %f", loss-l2dist)
if loss < best_loss:
best_loss = loss
best_lr = lr
lr /= 2
if best_lr >0:
logger.debug("Finally apply gradient with learning rate %f", best_lr)
// apply the optimal learning rate that was found and update the loss:
adv_image_tanh = adv_image_tanh + best_lr * perturbation_tanh
adv_image = self._tanh_to_original(adv_image_tanh, clip_min, clip_max)
z, l2dist, loss = self._loss(image, adv_image, target, c)
attack_success = (loss - l2dist <= 0)
overall_attack_success = overall_attack_success or attack_success
// Update depending on attack success:
if attack_success:
logger.debug("Margin Loss <= 0 --> Attack Success!")
if l2dist < best_l2dist:
logger.debug("New best L2Dist: %f (previous=%f)", l2dist, best_l2dist)
best_l2dist = l2dist
best_adv_image = adv_image
if overall_attack_success:


WITNESS LIST
Education
April 26, 2011 8:30 AM
FOR:
Fuller, S. Paige Director of Special Education; VP of Legislative Matters (also providing
written testimony) (Floresville / Poth ISD and TCASE), Adkins, TX
Schmidt, Don Asst Supt for Student, Family and Community Services (also providing
written testimony) (Northside ISD and TCASE), San Antonio, TX
Registering, but not testifying:
For:
Canaday, Jennifer M. Governmental Relations Manager (Association of Texas
Professional Educators), Austin, TX
Dawson, Jodyann Public Policy Intern (Texans Care For Children), Austin, TX
Eckhart, Harley Associate Executive Director (Texas Elementary Principals and
Supervisors Association), Austin, TX
Haney, Julie Legislative Consultant ((TACS) Tx Association of Community Schools),
Austin, TX
Hanna, Mark J. Attorney (Texas Speech-Language-Hearing Association), Austin, TX
McCreary, Casey Assistant Executive Director (TX Assoc. of School Administrators
(TASA)), Austin, TX
Miller, Jeff (Disability Rights Texas), Austin, TX
Quinzi, Patty Legislative Counsel (TX-AFT), Austin, TX
Shields, Julie Asst. Dir Governmental Relations (Texas Assoc. of School Boards), Austin,
TX
Statman, Rona Director of Family Support (The Arc of Texas), Austin, TX
Vera, Colleen Retired Texas Teacher (Self), Houston, TX
AGAINST:
Vera, Colleen Retired Texas Teacher (Self), Houston, TX
Registering, but not testifying:
For:
Carpenter, Bill (Texas Council of Administrators of Special Education), Austin, TX
Eckhart, Harley Associate Executive Director (Texas Elementary Principals and
Supervisors), Austin, TX
Flores, Rebecca Director of govt Relations (Houston ISD), Houston, TX
McCreary, Casey Assistant Executive Director (Texas Assoc. of School Administrators
(TASA)), Austin, TX
Shields, Julie Asst. Dir Governmental Relations (Texas Assoc. of School Boards), Austin,
TX
FOR:
Clore, Paul Superintendent (also providing written testimony) (Gregory-Portland ISD),
Portland, TX
Walsh, Jim Attorney (Walsh, Anderson, Brown, Gallegos and Green and TASB), Austin,
TX
1
WITNESS LIST
Education
April 26, 2011 8:30 AM
Registering, but not testifying:
For:
Eaton, Holly Director of Professional Development and Advocacy (Tx Classroom
Teachers Assoc), Austin, TX
2


Samsung set to outsource more production to China
by Steve McCaskillSamsung set to outsource more production to China
Lower costs help company in mid-range battle
(Image credit: Samsung)
Samsung plans to outsource as much as a fifth of its smartphone production in a bid to keep up with Chinese rivals in the mid-range segment of the market.
The Korean giant is the world’s largest mobile phone manufacturer, with shipments rising by 10 per cent during the most recent quarter to 78 million units.
IHS Markit attributed the gains not only to the strong performance of the flagship Samsung Galaxy Note 10 but also the popularity of mid-range handsets.
- Samsung closes China smartphone factory
- Apple looks to diversify supply chain
- Sony moves to Thailand
Samsung production
A refreshed Galaxy A range had helped matters, but so had the decision to outsource production. With Xiaomi and Huawei competing aggressively on price, Samsung had struggled to compete with such thin margins.
The company had a fifth of the Chinese market in 2013, but consumers in the country are extremely price-conscious and there is little brand loyalty. This means that competitively priced, feature-packed phones from rivals have eroded Samsung’s share to one per cent.
By using Chinese contractors that also make devices for other vendors, Samsung benefits from economies of scale and a more agile model that brings down costs. However this also loosens control over quality standards and also allows competitors to benefit from lower costs if they use the same contractor.
Reuters says Samsung now plans for third parties to make as many as 60 million of the 300 million devices it ships annually. Most of these devices would be aimed at the South American and South East Asian markets and it is claimed Samsung will be involved in the design, development and quality oversight of production.
Coincidentally, Samsung has closed all of its mobile phone factories in China due to slowing smartphone sales and rising manufacturing costs that have seen numerous vendors exit the country.
- Here are the best Samsung phone deals for November 2019
Via Reuters


Introduction to Scripting¶
This detailed guide describes how to write Ruby scripts to automate tasks in Datavyu and to ensure reliable coding.
Classes, Methods, and Parameters provides an overview of the methods and classes of the Datavyu API. For a more in-depth discussion of each particular method and function, refer to the Reference documentation.
Recommended Text Editors¶
Ruby scripts are simply text files with a .rb
file extension. You
can write scripts in any text editor, including built-in ones like
Notepad or TextEdit. However, while those programs are adequate for
scripting purposes, modern text editors make scripts much easier to
read by providing syntax highlighting, which can make a world of
difference when attempting to debug an issue.
To take advantage of syntax highlighting and coding support, we recommend installing and using one of the following programs for editing Ruby scripts:
Windows:
Mac OSX:
TextMate 2 (free and open-source)
gedit (free and open-source)
TextWrangler (free)
Linux:
Tip
Most text editors determine what kind of syntax highlighting to use based on the file extension. Please ensure that your Ruby script files end with the “.rb” extension so you see syntax highlighting.
General Principles¶
Each cell that you create with the Datavyu API has three inherent
codes: onset
, offset
, and ordinal
. Each
cell also has at least one user-specified code.
onset
, offset
, and ordinal
are all Integers, while the user-specified codes are Strings.
onset
and offset
are measured in milliseconds from the
beginning of the video, starting from 0. For
instance, an onset
time of 00:02:20 translates to 140000ms.
Since user-specified codes are strings, you must convert any codes that you wish to perform calculations on to a numeric type. This is easily done with Ruby using the to_i method for integers, or the to_f method for floating point numbers.
Example
Create a variable, var1
whose value is “5”. Since the number 5 has
quotation marks around it, it is a string.
var1 = "5"
If you print var
, you’d see that it is “5”. Create a new
variable, var2
from var1
using to_i
to convert the “5” to
a 5
.
var2 = var1.to_i
Print var2
and see that it is a 5
without quotation marks:
print var2
Tip
Ruby provides two options for printing to the console: the p
command and the puts
command. When in doubt, use p
, as it
prints arrays and lists in a more readable format, rather than
mashing them all together like puts
does. Try printing a list
such as [5, 6, 7, 8, 9]
using both p
and puts
to
see the difference.
p [5,6,7,8,9]
puts [5,6,7,8,9]
Basic Script Format¶
Tip
Scripts are very sensitive! When programming, every quotation mark, underscore, period, and slash serve a purpose. You must use the correct syntax or the script will not work.
Code and column names are also case sensitive. If you have a column in a spreadsheet called “trial”, requesting “Trial” will not work.
All code names in Ruby must be lowercase. Codes with uppercases have special meanings.
All Datavyu API scripts must include the following line at the top:
require 'Datavyu_API.rb'
This require
statement loads all of the helper functions that enable
your scripts to interact with the Datavyu spreadsheet.
In general, the rest of the script code goes between begin
and
end
tags, making the general format as follows:
require 'Datavyu_API.rb'
begin
# Get the columns that we want to work with
# Do something to those columns
# Write any changes to those columns back to the spreadsheet
end
Tip
Anything that comes after a #
character on a line in Ruby is a
comment, which means it will not execute any specific task. Comments are useful for
leaving notes that explain what the code is doing so that when you return to an old script
you remember what you’re looking at. The examples in this documentation
use comments extensively.
Now that you are grounded in the Datavyu Ruby API mechanics, consider the API Tutorials or Datavyu Ruby API Reference.


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nips nips2000 nips2000-112 nips2000-112-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Geoffrey J. Gordon
Abstract: Many algorithms for approximate reinforcement learning are not known to converge. In fact, there are counterexamples showing that the adjustable weights in some algorithms may oscillate within a region rather than converging to a point. This paper shows that, for two popular algorithms, such oscillation is the worst that can happen: the weights cannot diverge, but instead must converge to a bounded region. The algorithms are SARSA(O) and V(O); the latter algorithm was used in the well-known TD-Gammon program. 1
[1] R. S. Sutton. Learning to predict by the methods of temporal differences. Machine Learning, 3(1):9-44, 1988.
[2] Geoffrey J. Gordon. Stable function approximation in dynamic programming. Technical Report CMU-CS-95-103, Carnegie Mellon University, 1995.
[3] L. C. Baird. Residual algorithms: Reinforcement learning with function approximation. In Machine Learning: proceedings of the twelfth international conference, San Francisco, CA, 1995. Morgan Kaufmann.
[4] Geoffrey J. Gordon. Chattering in SARSA(A). Internal report, 1996. CMU Learning Lab. Available from www.es . emu. edu;-ggordon.
[5] R. S. Sutton. Open theoretical questions in reinforcement learning. In P. Fischer and H. U. Simon, editors, Computational Learning Theory (Proceedings of EuroCOLT'99), pages 11- 17, 1999.
[6] D. P. de Farias and B. Van Roy. On the existence of fixed points for approximate value iteration and temporal-difference learning. Journal of Optimization Theory and Applications, 105(3), 2000.
[7] Gavin A. Rummery and Mahesan Niranjan. On-line Q-Iearning using connectionist systems. Technical Report 166, Cambridge University Engineering Department, 1994.
[8] G. Tesauro. TD-Gammon, a self-teaching backgammon program, achieves master-level play. Neural Computation, 6:215- 219, 1994.
[9] T. Jaakkola, M. 1. Jordan, and S. P. Singh. On the convergence of stochastic iterative dynamic programming algorithms. Neural Computation, 6:1185- 1201, 1994.
[10] B. T. Polyak and Ya. Z. Tsypkin. Pseudogradient adaptation and training algorithms. Automation and Remote Control, 34(3):377- 397, 1973. 'Translated from A vtomatika i Telemekhanika.
[11] J. G. Kemeny and J. L. SnelL Finite Markov Chains. Van Nostrand- Reinhold, New York, 1960.


An Experiment using the sidebar template from startbootstrap.com which I integrated in my website (animeshmanglik.name)
Click on the Menu to Toggle Sidebar . Hope you enjoy it!
An Experiment using the sidebar template from startbootstrap.com which I integrated in my website (animeshmanglik.name)
Click on the Menu to Toggle Sidebar . Hope you enjoy it!


Introduction
Queried Images is simple in use, lightweight and quite flexible javascript module, that automatically changes image sources in your html code depending on browser's window width.
It allows you to override default media queries included in module or even create your own breakpoints groups. And the best part is that the whole minified file has only 781 bytes of code!
Qi.js can be a nice alternative for hiding images via css classes and can help you to organize your code on html layer.
If you have some doubts about how it works, feel free to try out emulation on the right.
Basic usage

To start using qi.js on basic, there are only three easy steps that you must follow:
- pull downloaded module to your html,
- add dynamic qi sources to every  tag that you like,
- before closing  tag initialize new Qi object (or create event that fires after document is loaded).
Default media queries
By default, Qi object has three media breakpoints based on device's width:
- qi-small - for 0 pixels or more,
- qi-medium - for 640 pixels or more,
- qi-large - for 1024 pixels or more.
The important thing is that larger queries overrides smaller, like it is in a Zurb's Foundation approach.
Custom and multiple breakpoints
As mentioned, there is an option to invoke personalized breakpoints or override default one. To do that, just pass JSON object when creating Qi object like shown on the snippet.
In the same way you can build your own breakpoints names at your discretion!
You can create as many Qi objects as you want, but pay attention to given names. If only one of them is repeated, it can cause unwanted assignments.
<-- creating new breakpoints à la Bootstrap -->


Removing Roboto Removing Roboto Removing Roboto Removing Roboto Removing Roboto Removing Roboto Removing Roboto Removing Roboto


For various reasons, resources can go out of order: machines may fail or have to get maintenance, nurses or doctors may get sick. Human resources can also be out-of-duty or off-shift.


Fly
Faster
Higher
More Payload
Farther
Safer
For Less
lkasjf
This is where you put a small paragraph about company
Lorem ipsum..
Lorem ipsum..
Contact Us
Our Partners
Vision and mission statment here
Misson Statement here:
FILLER TEXT
Products
AROPS MP
Lorem ipsum dolor sit amet..
AROPS ATO
Lorem ipsum dolor sit amet..
PPAS
Lorem ipsum dolor sit amet..
VCIPLAN
Lorem ipsum dolor sit amet..
HOME
ABOUT
PRODUCTS
AROPS ATO
AROPS MP
PPAS
VCIPLAN
CONTACT


Person
| My name |
|
| Date of birth |
|
| Nationality |
|
| Location |
|
| Martial status |
, Kids: |
| Visit me |
|
Career
Profession
{% include vitae/profession.html %}
Studies
{% include vitae/profession.html %}
Skills
Languages
{% include vitae/skills.html %}
Technologies
{% include vitae/skills.html %}
Miscellaneous
{% include vitae/skills.html %}


Goal:
Create four virtual machines and demonstrate that they can be used as web servers, can be accessed via ssh
, and can form a network.
Overview:
- We created our virtual machines using DigitalOcean, a hosting company that makes it easy to spin up servers. The developer has full control of the machine, unlike other common hosting providers who create managed environments.
- We demonstrate the networking capabilities of the servers by showing that they can ping one another.
- We configured one of the servers to host this website that you are viewing now.
- Finally, we will show their
ssh
capabilities and complete the demonstration by having the class connect to the machine and create files for the web server to display.


To do this applet successfully (e.g. get the completion code), you must properly orient the three force vectors shown (damping, gravity, tension). To know how to orient the vectors you need to know the initial conditions, e.g. the bob is to the right of vertical and moving to the left and downward. These conditions will be given in the problem statement.
To orient one of the force vectors, hold down "Shift" and left-click with the mouse on that vector, and move the tip of the force vector to the position appropriate to this situation by dragging the mouse. Hit the "test" button in the applet to see if you are correct. The applet will then tell you which forces are correctly oriented and which ones are not. If you do not get them all correct, reposition the incorrect vector(s) and try again. When they are all in the correct position for your initial conditions, you will be given the completion code.


--- layout: default title: Quill - Your powerful rich text editor bodyClass: 'home' redirect_from: /latest/ ---
Quill is a free, open source WYSIWYG editor built for the modern web. With its modular architecture and expressive API, it is completely customizable to fit any need.
// <link href="https://cdn.quilljs.com/1.2.6/quill.snow.css" rel="stylesheet">
// <script src="https://cdn.quilljs.com/1.2.6/quill.min.js"></script>
var quill = new Quill('#editor', {
modules: {
toolbar: '#toolbar'
},
theme: 'snow'
});
// Open your browser's developer console to try out the API!
Built with


We reserved a few special discounted tickets (79€) for students.
If you are eligible, just send us an email with your ID and a proof you are really a student and we will send you a dedicated link to complete your purchase.


-
Dr. Vinay Avasthi
Chairman
CSI Dehradun ChapterMr. Ajay Rawat
Student Branch Coordinator
UPES-CSI Student Chapter
Mr. P K Deka
Faculty Coordinator -
Mayank Mahajan
PresidentNeeharika Sharma
Vice President -
Ankit Jaggi
Gen. SecretaryAkshay Mittal
SecretarySambhavi
P.R. HeadRohan Srivastava
Treasurer -
Pulkit Gupta
Joint SecretaryAshish Sinha
Working Committee Head -
Pratibha Tiwari
Associate P.R. HeadYet to be decided
Associate P.R. HeadPratibha Rana
Associate P.R. Head -
Soumil Agarwal
Event DirectorDeepankar Agarwal
Design & Technical DirectorDivyani Singh
Documentation Director -
Anmol Rastogi
Internal P. R.Vibhor Taneja
Associate Treasurer -
Jeevesh Sehgal
Event HeadSrashti Gupta
Registration HeadAditya Mishra
Disciplinary Head -
Shriya Arora
Associate Event HeadRamu N Bhattathiri
Associate Event Head -
Varun Bawa
Technical HeadArun Kant Pant
Designing HeadAkhil Juneja
VFX Head -
Ishika Banerjee
Editor in ChiefVidushi Keshwani
Documentation Head -
Shreeansh Mairal
Branch HeadVanshaj Setia
Branch HeadAdvitya Patni
Branch HeadPiyush Dhingra
Branch Head


Equivalent to clicking the Close All command on the File menu. The Close All command appears when you hold down SHIFT while selecting the File menu. Closes all protected and unprotected windows and all hidden windows. If unsaved changes have been made to the workbook in one or more windows, a message is displayed asking if you want to save each workbook.
Syntax
CLOSE.ALL( )
Related Functions
CLOSE Closes the active window
FILE.CLOSE Closes the active workbook
QUIT Ends a Microsoft Excel session
SAVE Saves the active workbook
Return to index


InversAuction ("us", "we", or "our") operates https://www.inversauction.com (the "Site"). This page informs you of our policies regarding the collection, use and disclosure of Personal Information we receive from users of the Site.
We use your Personal Information only for providing and improving the Site. By using the Site, you agree to the collection and use of information in accordance with this policy.
Information Collection And Use
While using our Site, we may ask you to provide us with certain personally identifiable information that can be used to contact or identify you. Personally identifiable information may include, but is not limited to your name ("Personal Information").
Log Data
Like many site operators, we collect information that your browser sends whenever you visit our Site ("Log Data"). This Log Data may include information such as your computer's Internet Protocol ("IP") address, browser type, browser version, the pages of our Site that you visit, the time and date of your visit, the time spent on those pages and other statistics.
In addition, we may use third party services such as Google Analytics that collect, monitor and analyze this data
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Cookies are files with small amount of data, which may include an anonymous unique identifier. Cookies are sent to your browser from a web site and stored on your computer's hard drive. Like many sites, we use "cookies" to collect information. You can instruct your browser to refuse all cookies or to indicate when a cookie is being sent. However, if you do not accept cookies, you will be able to use our Site still ;).
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This Privacy Policy is effective as of 26th of April 2017 and will remain in effect except with respect to any changes in its provisions in the future, which will be in effect immediately after being posted on this page.
We reserve the right to update or change our Privacy Policy at any time and you should check this Privacy Policy periodically. Your continued use of the Service after we post any modifications to the Privacy Policy on this page will constitute your acknowledgment of the modifications and your consent to abide and be bound by the modified Privacy Policy.
If we make any material changes to this Privacy Policy, we will notify you either through the email address you have provided us, or by placing a prominent notice on our website.
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#
INFO 611 Fall 2020
Week 10, Oct 27, 2020
Elasticsearch - Fun Tuesday
Elasticsearch for SQL Experts
chrisfauerbach.github.io/info610_fall_2020/
--- # Elasticsearch https://www.elastic.co/what-is/elasticsearch Elasticsearch is a distributed, open source search and analytics engine for all types of data, including textual, numerical, geospatial, structured, and unstructured. Elasticsearch is built on Apache Lucene and was first released in 2010 by Elasticsearch N.V. (now known as Elastic). Known for its simple REST APIs, distributed nature, speed, and scalability, Elasticsearch is the central component of the Elastic Stack, a set of open source tools for data ingestion, enrichment, storage, analysis, and visualization. Commonly referred to as the ELK Stack (after Elasticsearch, Logstash, and Kibana), the Elastic Stack now includes a rich collection of lightweight shipping agents known as Beats for sending data to Elasticsearch. --- # Elasticsearch - When do you use it? The speed and scalability of Elasticsearch and its ability to index many types of content mean that it can be used for a number of use cases: * Application search * Website search * Enterprise search * Logging and log analytics * Infrastructure metrics and container monitoring * Application performance monitoring * Geospatial data analysis and visualization * Security analytics * Business analytics --- # How does it work Elasticsearch is built on Lucene, the de facto standard Java Full Text Search Library. The basic flow of data into Elasticsearch is as follows: 1. Raw data flows to a collector (beats, logstash) 2. Data is transformed and modified to a standard format 3. Data is ingested into Elasticsearch 4. Data is mapped to a specific data type (Document Type) 5. Data is then persisted in ES 6. Data is organized (Indexes) 7. Data is then made redundant for safety/scaling (Shards) --- # Index An Index in ES is a collection of documents. Typically of the same type, but not required. Indexes can be named and organized by convention to represent things like time ranges (date, month, year) etc. Elasticsearch uses a data structure called an inverted index, which is designed to allow very fast full-text searches. An inverted index lists every unique word that appears in any document and identifies all of the documents each word occurs in. --- # Kibana Kibana is a user interface that can show information about Elasticsearch. Kibana is a data visualization and management tool for Elasticsearch that provides real-time histograms, line graphs, pie charts, and maps. Kibana also includes advanced applications such as Canvas, which allows users to create custom dynamic infographics based on their data, and Elastic Maps for visualizing geospatial data. --- # Interaction Custom application development can occur in almost any programming language and interact with ES. All major programming languages have 'libraries' that allow easier integration. In the end, primary integration occurs with REST APIs over HTTP. --- # DEMO --- # See you Thursday! ---


A channel to discuss trading. For useful links and more info click the pinned messages to the right.
100 messages
Before 05-Dec-19 12:00 AM
p.22-Jul-19 01:31 PM
Great
Go on, that sounds great for everyone
joe2x422-Jul-19 01:43 PM
The data is directly from netid 0 only during bear market. Displayed are the last 24 hours.
Due to low liquidity and transformation to mm2.0 there are almost no trades
did the volume drop or move to mm2?
Dexstats update?
Cmc update?
Markus22-Jul-19 01:56 PM
volume did drop
but usually when volume drop
something big is usually popping up afterwards
CHMEX22-Jul-19 01:58 PM
@joe2x4 mm2.0 does currently not allow to read trades of other peole via api once thats possible again I will read and update dexstats to mm2 data. Once there is good volume we can activate cmc again
1
Markus22-Jul-19 01:59 PM
imagine all alt coins stop trading against btc and start trading against gold instead
CHMEX22-Jul-19 02:01 PM
isn't Digix supposed to be Gold backed?
Markus22-Jul-19 02:01 PM
dont know
joe2x422-Jul-19 02:06 PM
This mm2 non reporting stats is very interesting. Could be a feature, almost like a dark exchange.
CHMEX22-Jul-19 02:08 PM
if you want nobody to know you can also trade on a netid that you don't publish
maybe you would be able to somehow match it with chainanalysis
joe2x422-Jul-19 02:17 PM
Sweet, I'm gathering ammo so I can concerned citizen email some "think of the children" regulators so as to make viral news with regulator turning red and shaking fist.
joe2x422-Jul-19 02:29 PM
I wonder if mm2 could be used to replace silk road. If say a hidden net Id is used, say 420, could drugs be posted and sold? Drugs being listed as NFT?
i like @joe2x4 's idea. but once mobile dex is freely accessible i dont think any advertising wil be necessary
FlyingDutchman22-Jul-19 06:31 PM
once its freely accessible then advertising will be mostnecessary
we need advertising, it just has to be when we have a set of top level products for adoption
so we dont fall prey to hype and death
actionslacks22-Jul-19 06:43 PM
there is zero competition. kmd is the only one with a mobile dex exempt from kyc. it's not top level it's a level that no one else can even get to yet.
FlyingDutchman22-Jul-19 06:44 PM
yes
so word must be spread
Markus22-Jul-19 07:07 PM
there is alot of improvements needed in the atomicdex
for example if u want to trade KMD for BTC and there already is someone who put up a trade for that u can not set a new limit order
thats a big flaw
unless its a bug
dont know
jl777c22-Jul-19 07:09 PM
GUI limitation
mm2 certainly allows it
Markus22-Jul-19 07:09 PM
Hm ok
jl777c22-Jul-19 07:10 PM
first priority is to get the phone atomic swaps stable, please understand this is something that is not exactly easy
Markus22-Jul-19 07:10 PM
understandable, will take time for sure
jl777c22-Jul-19 07:11 PM
once that is working smoothly, then allowing maker orders by all, it is not so crazy, the one issue with maker orders on phones is that the phone needs to be active
so this is why it isnt the primary use case. the idea is there will be marketmaker competition for the nice bid/ask spreads that will be there at first
Markus22-Jul-19 07:11 PM
I think it wont be a issue later on, im sure there will be enough liquid bots ran on computers through api
jl777c22-Jul-19 07:12 PM
exactly, especially with the liquidity multiplier
with KMD you can bank the 5%, have very low offers for dozens of coins and just wait for someone to dump/fatfinger
if they dont, you still get 5%. if they do, you get a nice discount
such a money making method has never been possible before (other than for exchange owners)
Do Alts start pump when the dominance starts to tank or when it reaches a certain lvl?
@Andersen
richardt22-Jul-19 08:40 PM
If I remember correctly, during the last alt season BTC dominance went down to almost 30%.  People are more weary of alts now
JimD22-Jul-19 08:48 PM
Ya, Im not sure what will trigger. The BTC network will probably still be clogged in a bull market which will drive some traffic to alternatives
those fees and transaction times were outrageous for a while
richardt22-Jul-19 08:51 PM
Also doesn't help that there seems to be a lot of people just waiting to break even/cut losses. Would likely need a flood of newcomers to see an altseason like the previous one
Unless people finally break away from shitcoins and put money into real projects.  So long as you're holding the right coins
Tek22-Jul-19 09:24 PM
Remember; Jesus is watching when you wank
1
Don't wank
Retain for Jesus.
ComputerGenie 👴👴👴22-Jul-19 09:51 PM
Retain for Jesus.

Caglio23-Jul-19 07:25 AM
@p. im gonna private message you with this lovely comic


In this project, you’ll generate your own Simpsons TV scripts using RNNs. You’ll be using part of the Simpsons dataset of scripts from 27 seasons. The Neural Network you’ll build will generate a new TV script for a scene at Moe’s Tavern.
The data is already provided for you. You’ll be using a subset of the original dataset. It consists of only the scenes in Moe’s Tavern. This doesn’t include other versions of the tavern, like “Moe’s Cavern”, “Flaming Moe’s”, “Uncle Moe’s Family Feed-Bag”, etc..
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
data_dir = './data/simpsons/moes_tavern_lines.txt'
text = helper.load_data(data_dir)
# Ignore notice, since we don't use it for analysing the data
text = text[81:]
Play around with view_sentence_range
to view different parts of the data.
view_sentence_range = (0, 10)
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import numpy as np
print('Dataset Stats')
print('Roughly the number of unique words: {}'.format(len({word: None for word in text.split()})))
scenes = text.split('\n\n')
print('Number of scenes: {}'.format(len(scenes)))
sentence_count_scene = [scene.count('\n') for scene in scenes]
print('Average number of sentences in each scene: {}'.format(np.average(sentence_count_scene)))
sentences = [sentence for scene in scenes for sentence in scene.split('\n')]
print('Number of lines: {}'.format(len(sentences)))
word_count_sentence = [len(sentence.split()) for sentence in sentences]
print('Average number of words in each line: {}'.format(np.average(word_count_sentence)))
print()
print('The sentences {} to {}:'.format(*view_sentence_range))
print('\n'.join(text.split('\n')[view_sentence_range[0]:view_sentence_range[1]]))
Dataset Stats
Roughly the number of unique words: 11492
Number of scenes: 262
Average number of sentences in each scene: 15.251908396946565
Number of lines: 4258
Average number of words in each line: 11.50164396430249
The sentences 0 to 10:
Moe_Szyslak: (INTO PHONE) Moe's Tavern. Where the elite meet to drink.
Bart_Simpson: Eh, yeah, hello, is Mike there? Last name, Rotch.
Moe_Szyslak: (INTO PHONE) Hold on, I'll check. (TO BARFLIES) Mike Rotch. Mike Rotch. Hey, has anybody seen Mike Rotch, lately?

Moe_Szyslak: What's the matter Homer? You're not your normal effervescent self.
Homer_Simpson: I got my problems, Moe. Give me another one.
Moe_Szyslak: Homer, hey, you should not drink to forget your problems.
Barney_Gumble: Yeah, you should only drink to enhance your social skills.
The first thing to do to any dataset is preprocessing. Implement the following preprocessing functions below:
To create a word embedding, you first need to transform the words to ids. In this function, create two dictionaries:
vocab_to_int
int_to_vocab
Return these dictionaries in the following tuple (vocab_to_int, int_to_vocab)
import numpy as np
import problem_unittests as tests
from collections import Counter
def create_lookup_tables(text):
"""
Create lookup tables for vocabulary
:param text: The text of tv scripts split into words
:return: A tuple of dicts (vocab_to_int, int_to_vocab)
"""
# TODO: Implement Function
counts = Counter(text)
vocab = sorted(counts, key=counts.get, reverse=True)
vocab_to_int = {word: ii for ii, word in enumerate(vocab, 1)}
int_to_vocab = {ii: word for word, ii in vocab_to_int.items()}
return vocab_to_int, int_to_vocab
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_create_lookup_tables(create_lookup_tables)
Tests Passed
We’ll be splitting the script into a word array using spaces as delimiters. However, punctuations like periods and exclamation marks make it hard for the neural network to distinguish between the word “bye” and “bye!”.
Implement the function token_lookup
to return a dict that will be used to tokenize symbols like “!” into “||Exclamation_Mark||”. Create a dictionary for the following symbols where the symbol is the key and value is the token:
| This dictionary will be used to token the symbols and add the delimiter (space) around it. This separates the symbols as it’s own word, making it easier for the neural network to predict on the next word. Make sure you don’t use a token that could be confused as a word. Instead of using the token “dash”, try using something like “ | dash | ”. |
def token_lookup():
"""
Generate a dict to turn punctuation into a token.
:return: Tokenize dictionary where the key is the punctuation and the value is the token
"""
# TODO: Implement Function
punct_dist ={
'.': 'period', ',': 'comma', '"': 'quotationmark',';': 'semicolon', '!': 'exclamation_mark', '?': 'question_mark', '(': 'left_parentheses', ')': 'right_parentheses',
'--': 'dash', '\n': 'return'}
return punct_dist
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_tokenize(token_lookup)
Tests Passed
Running the code cell below will preprocess all the data and save it to file.
 If you ever decide to come back to this notebook or have to restart the notebook, you can start from here. The preprocessed data has been saved to disk.
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
import helper
import numpy as np
import problem_unittests as tests
int_text, vocab_to_int, int_to_vocab, token_dict = helper.load_preprocess()
You’ll build the components necessary to build a RNN by implementing the following functions below:
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from distutils.version import LooseVersion
import warnings
import tensorflow as tf
# Check TensorFlow Version
assert LooseVersion(tf.__version__) >= LooseVersion('1.0'), 'Please use TensorFlow version 1.0 or newer'
print('TensorFlow Version: {}'.format(tf.__version__))
# Check for a GPU
if not tf.test.gpu_device_name():
warnings.warn('No GPU found. Please use a GPU to train your neural network.')
else:
print('Default GPU Device: {}'.format(tf.test.gpu_device_name()))
TensorFlow Version: 1.0.1
Default GPU Device: /gpu:0
Implement the get_inputs()
function to create TF Placeholders for the Neural Network. It should create the following placeholders:
name
parameter.Return the placeholders in the following the tuple (Input, Targets, LearingRate)
def get_inputs():
"""
Create TF Placeholders for input, targets, and learning rate.
:return: Tuple (input, targets, learning rate)
"""
# TODO: Implement Function
inputs = tf.placeholder(tf.int32, shape=(None, None), name= 'input')
targets = tf.placeholder(tf.int32, shape=(None, None), name= 'targets')
learning_rate = tf.placeholder(tf.float32, name= 'learning_rate')
return (inputs, targets, learning_rate)
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_get_inputs(get_inputs)
Tests Passed
Stack one or more BasicLSTMCells
in a MultiRNNCell
.
rnn_size
zero_state()
function
tf.identity()
Return the cell and initial state in the following tuple (Cell, InitialState)
def get_init_cell(batch_size, rnn_size):
"""
Create an RNN Cell and initialize it.
:param batch_size: Size of batches
:param rnn_size: Size of RNNs
:return: Tuple (cell, initialize state)
"""
# TODO: Implement Function
lstm_layers = 2
lstm = tf.contrib.rnn.BasicLSTMCell(rnn_size)
# Add dropout to the cell
drop = tf.contrib.rnn.DropoutWrapper(lstm, output_keep_prob=0.5)
cell = tf.contrib.rnn.MultiRNNCell([drop] * lstm_layers)
#cell = tf.contrib.rnn.MultiRNNCell([lstm] * lstm_layers)
initial_state = cell.zero_state(batch_size, tf.float32)
initial_state = tf.identity(initial_state, name='initial_state')
return (cell, initial_state)
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_get_init_cell(get_init_cell)
Tests Passed
Apply embedding to input_data
using TensorFlow. Return the embedded sequence.
def get_embed(input_data, vocab_size, embed_dim):
"""
Create embedding for <input_data>.
:param input_data: TF placeholder for text input.
:param vocab_size: Number of words in vocabulary.
:param embed_dim: Number of embedding dimensions
:return: Embedded input.
 Time to use the cell to create a RNN.
tf.nn.dynamic_rnn()
tf.identity()
Return the outputs and final_state state in the following tuple (Outputs, FinalState)
def build_rnn(cell, inputs):
"""
Create a RNN using a RNN Cell
:param cell: RNN Cell
:param inputs: Input text data
:return: Tuple (Outputs, Final State)
"""
# TODO: Implement Function
outputs, final_state = tf.nn.dynamic_rnn(cell, inputs, dtype=tf.float32)
final_state = tf.identity(final_state, name="final_state")
return outputs, final_state
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_build_rnn(build_rnn)
Tests Passed
Apply the functions you implemented above to:
input_data
using your get_embed(input_data, vocab_size, embed_dim)
function.cell
and your build_rnn(cell, inputs)
function.vocab_size
as the number of outputs.Return the logits and final state in the following tuple (Logits, FinalState)
def build_nn(cell, rnn_size, input_data, vocab_size):
"""
Build part of the neural network
:param cell: RNN cell
:param rnn_size: Size of rnns
:param input_data: Input data
:param vocab_size: Vocabulary size
:return: Tuple (Logits, FinalState)
"""
# TODO: Implement Function
embedding = get_embed(input_data, vocab_size, rnn_size)
outputs, final_state = build_rnn(cell, embedding)
weight = tf.truncated_normal_initializer(stddev = 0.01)
bias= tf.zeros_initializer()
predictions = tf.contrib.layers.fully_connected(outputs,
vocab_size,
weights_initializer = weight,
biases_initializer=bias,
activation_fn=None)
#predictions = tf.contrib.layers.fully_connected(outputs, vocab_size, activation_fn=None)
return predictions, final_state
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_build_nn(build_nn)
Tests Passed
Implement get_batches
to create batches of input and targets using int_text
. The batches should be a Numpy array with the shape (number of batches, 2, batch size, sequence length)
. Each batch contains two elements:
[batch size, sequence length]
[batch size, sequence length]
If you can’t fill the last batch with enough data, drop the last batch.
For exmple, get_batches([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15], 2, 3)
would return a Numpy array of the following:
[
# First Batch
[
# Batch of Input
[[ 1 2 3], [ 7 8 9]],
# Batch of targets
[[ 2 3 4], [ 8 9 10]]
],
# Second Batch
[
# Batch of Input
[[ 4 5 6], [10 11 12]],
# Batch of targets
[[ 5 6 7], [11 12 13]]
]
]
def get_batches(int_text, batch_size, seq_length):
"""
Return batches of input and target
:param int_text: Text with the words replaced by their ids
:param batch_size: The size of batch
:param seq_length: The length of sequence
:return: Batches as a Numpy array
"""
# TODO: Implement Function
num_batch = len(int_text) // ( seq_length *batch_size)
batches = np.empty((num_batch ,2, batch_size, seq_length))
for i in range(len(batches)):
for j in range(batch_size):
start_idx = (i * seq_length)+j
end_idx = start_idx + seq_length
if end_idx <= (len(int_text) -1):
batches[i][0][j] = int_text[ start_idx: end_idx]
start_idx = start_idx + seq_length*2
end_idx = end_idx + seq_length+ seq_length
if end_idx <= (len(int_text) -1):
batches[i][1][j] = int_text[ start_idx: end_idx]
return batches
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_get_batches(get_batches)
Tests Passed
Tune the following parameters:
num_epochs
to the number of epochs.batch_size
to the batch size.rnn_size
to the size of the RNNs.seq_length
to the length of sequence.learning_rate
to the learning rate.show_every_n_batches
to the number of batches the neural network should print progress.# Number of Epochs
num_epochs = 50
# Batch Size
batch_size = 256
# RNN Size
rnn_size = 512
# Sequence Length
seq_length = 15
# Learning Rate
learning_rate = 0.01
# Show stats for every n number of batches
show_every_n_batches = 100
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
save_dir = './save'
Build the graph using the neural network you implemented.
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
from tensorflow.contrib import seq2seq
train_graph = tf.Graph()
with train_graph.as_default():
vocab_size = len(int_to_vocab)
input_text, targets, lr = get_inputs()
input_data_shape = tf.shape(input_text)
cell, initial_state = get_init_cell(input_data_shape[0], rnn_size)
logits, final_state = build_nn(cell, rnn_size, input_text, vocab_size)
# Probabilities for generating words
probs = tf.nn.softmax(logits, name='probs')
# Loss function
cost = seq2seq.sequence_loss(
logits,
targets,
tf.ones([input_data_shape[0], input_data_shape[1]]))
# Optimizer
optimizer = tf.train.AdamOptimizer(lr)
# Gradient Clipping
gradients = optimizer.compute_gradients(cost)
capped_gradients = [(tf.clip_by_value(grad, -1., 1.), var) for grad, var in gradients]
train_op = optimizer.apply_gradients(capped_gradients)
Train the neural network on the preprocessed data. If you have a hard time getting a good loss, check the forms to see if anyone is having the same problem.
"""
DON'T MODIFY ANYTHING IN THIS CELL
"""
batches = get_batches(int_text, batch_size, seq_length)
with tf.Session(graph=train_graph) as sess:
sess.run(tf.global_variables_initializer())
for epoch_i in range(num_epochs):
state = sess.run(initial_state, {input_text: batches[0][0]})
for batch_i, (x, y) in enumerate(batches):
feed = {
input_text: x,
targets: y,
initial_state: state,
lr: learning_rate}
train_loss, state, _ = sess.run([cost, final_state, train_op], feed)
# Show every <show_every_n_batches> batches
if (epoch_i * len(batches) + batch_i) % show_every_n_batches == 0:
print('Epoch {:>3} Batch {:>4}/{} train_loss = {:.3f}'.format(
epoch_i,
batch_i,
len(batches),
train_loss))
# Save Model
saver = tf.train.Saver()
saver.save(sess, save_dir)
print('Model Trained and Saved')
Epoch 0 Batch 0/17 train_loss = 8.821
Epoch 5 Batch 15/17 train_loss = 1.469
Epoch 11 Batch 13/17 train_loss = 0.182
Epoch 17 Batch 11/17 train_loss = 0.149
Epoch 23 Batch 9/17 train_loss = 0.134
Epoch 29 Batch 7/17 train_loss = 0.129
Epoch 35 Batch 5/17 train_loss = 0.136
Epoch 41 Batch 3/17 train_loss = 0.155
Epoch 47 Batch 1/17 train_loss = 0.167
Model Trained and Saved
Save seq_length
and save_dir
for generating a new TV script.
 Get the tensors using the following names:
Return the tensors in the following tuple (InputTensor, InitialStateTensor, FinalStateTensor, ProbsTensor)
def get_tensors(loaded_graph):
"""
Get input, initial state, final state, and probabilities tensor from <loaded_graph>
:param loaded_graph: TensorFlow graph loaded from file
:return: Tuple (InputTensor, InitialStateTensor, FinalStateTensor, ProbsTensor)
"""
# TODO: Implement Function
input_tensor = loaded_graph.get_tensor_by_name('input:0')
initial_state_tensor = loaded_graph.get_tensor_by_name('initial_state:0')
final_state_tensor = loaded_graph.get_tensor_by_name('final_state:0')
probs_tensor = loaded_graph.get_tensor_by_name('probs:0')
return input_tensor, initial_state_tensor, final_state_tensor, probs_tensor
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_get_tensors(get_tensors)
Tests Passed
Implement the pick_word()
function to select the next word using probabilities
.
def pick_word(probabilities, int_to_vocab):
"""
Pick the next word in the generated text
:param probabilities: Probabilites of the next word
:param int_to_vocab: Dictionary of word ids as the keys and words as the values
:return: String of the predicted word
"""
# TODO: Implement Function
word_id = np.random.choice(len(probabilities), p=probabilities)
return int_to_vocab[word_id]
"""
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
"""
tests.test_pick_word(pick_word)
Tests Passed
This will generate the TV script for you.
It’s ok if the TV script doesn’t make any sense. We trained on less than a megabyte of text. In order to get good results, you’ll have to use a smaller vocabulary or get more data. Luckly there’s more data! As we mentioned in the begging of this project, this is a subset of another dataset. We didn’t have you train on all the data, because that would take too long. However, you are free to train your neural network on all the data. After you complete the project, of course.
When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as “dlnd_tv_script_generation.ipynb” and save it as a HTML file under “File” -> “Download as”. Include the “helper.py” and “problem_unittests.py” files in your submission.


| TDK | D | ambient temperature at the observer (degrees K) |
|---|---|---|
| PMB | D | pressure at the observer (mB) |
| RH | D | relative humidity at the observer (range 0-1) |
| WL | D | effective wavelength of the source () |
| REFA | D | coefficient (radians) |
|---|---|---|
| REFB | D | coefficient (radians) |
| worst | RMS | |
|---|---|---|
| optical/IR | 62 | 8 |
| radio | 319 | 49 |
| mas | mas |
For this particular set of conditions:
| sla_REFRO | sla_REFCOQ | Saastamoinen | |
| 10 | 10.27 | 10.27 | 10.27 |
| 20 | 21.19 | 21.20 | 21.19 |
| 30 | 33.61 | 33.61 | 33.60 |
| 40 | 48.82 | 48.83 | 48.81 |
| 45 | 58.16 | 58.18 | 58.16 |
| 50 | 69.28 | 69.30 | 69.27 |
| 55 | 82.97 | 82.99 | 82.95 |
| 60 | 100.51 | 100.54 | 100.50 |
| 65 | 124.23 | 124.26 | 124.20 |
| 70 | 158.63 | 158.68 | 158.61 |
| 72 | 177.32 | 177.37 | 177.31 |
| 74 | 200.35 | 200.38 | 200.32 |
| 76 | 229.45 | 229.43 | 229.42 |
| 78 | 267.44 | 267.29 | 267.41 |
| 80 | 319.13 | 318.55 | 319.10 |
| deg | arcsec | arcsec | arcsec |
The values for Saastamoinen's formula (which includes terms up to ) are taken from Hohenkerk and Sinclair (1985).
The results from the much slower but more accurate sla_REFCO routine have not been included in the tabulation as they are identical to those in the sla_REFRO column to the
resolution used.
SLALIB --- Positional Astronomy Library


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| SimEventCentral (Simulation simulation) |
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void | addMoteCountListener (MoteCountListener listener) |
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void | removeMoteCountListener (MoteCountListener listener) |
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void | addLogOutputListener (LogOutputListener listener) |
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void | removeLogOutputListener (LogOutputListener listener) |
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LogOutputEvent[] | getLogOutputHistory () |
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int | getLogOutputBufferSize () |
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void | setLogOutputBufferSize (int size) |
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int | getLogOutputObservationsCount () |
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String | toString () |
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Collection< Element > | getConfigXML () |
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boolean | setConfigXML (Simulation simulation, Collection< Element > configXML, boolean visAvailable) throws MoteTypeCreationException |
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Simulation event central. Simplifies implementations of plugins that observe motes and mote interfaces by keeping track of added and removed motes. For a selected set of interfaces, the event central also maintains an event history.
- See Also
- LogOutputEvent
- Author
- Fredrik Osterlind


OAuth Account Creation
Overview
Dwolla has simplified the user on-boarding process by building account creation into the OAuth flow. Now your users can create a Dwolla account and attach a bank funding source inline with the capture of the user's permission, without abandoning your application flow.
There are three ways to onboard new users, each with varying levels of required verification:
- Create a Dwolla Direct account with non-verified, receive-only bank funding source
- Create a Dwolla Direct account with instant bank account verification
- Create a Full Dwolla account with both identity and bank verification
Dwolla Direct accounts were designed to provide a lightweight registration experience. In contrast to Full Dwolla accounts, full identity verification is not required for Dwolla Direct accounts. Because of this, they have certain restrictions within the Dwolla platform, e.g. Dwolla Direct accounts cannot hold a Dwolla balance. Read more about Direct account limitations.
Give the experience a try:
Direct account w/ verified bank
For more live examples see this sample application.
User experience - Direct account
Step 1 From your application, the user is presented with Dwolla OAuth in a pop-up, or their window is redirected.
Step 2 User is prompted to create a Dwolla Direct account (or log in with an existing Dwolla account). If Dwolla detects no prior user sessions from dwolla.com (checks cookies), the main call to action will be to create a new account.
Step 3 - User is asked to grant requested permissions to the application.
Step 4 - Adding a funding source There are two flows available for adding a funding source. If the user needs to be able to send money, be sure to request the Send scope, which will trigger the Instant Account Verification (IAV) process and allow the user to verify and connect a funding source by entering their online banking credentials. Alternatively, if the user only needs to receive money, do not request the Send scope, but do request the Funding scope. This will trigger a flow where the user will add their bank or credit union account and routing numbers, but the IAV process will not be included.
- If Funding scope is requested but Send scope is not, send user through the flow to add a non-verified bank account.
- If Send scope is requested, send the user through the IAV flow to add a verified bank.
Note: An extensive list of popular U.S. financial institutions are supported by IAV. In the case that a user's bank account is not supported, they'll be unable to complete account creation.
Note: there may be multifactor authentication (MFA) in this step, depending on the financial institution. Different kinds of MFA include:
- Question and answer
- Token (SMS or email verification code)
- CAPTCHA or security image
Step 5 - Submit and verify bank information Once the user selects submit and verify on their bank information, they are then redirected back to your site where you will receive an access token and refresh token pair.
Step 6 - Redirect user back to application
User experience - full Dwolla account
Configuration


[1]
small size,,user friendly controls,beautiful screen,quality pictures; minimal manual exposure controls