Take it as a warm suggestion: please start doing the exercises and send them in the mailing list, so as to start a discussion about them
There are no other communications so far
Donald Knuth is a Computer Scientist
Main contributions: theoretical and practical development of the analysis of the computational complexity of algorithms, The Art of Computer Programming series of monographs, TeX typesetting system for writing academic documents
The Art of Computer Programming is an ongoing work (3 volumes and an half out of 7 have been published so far)
The first volume of Knuth's series of books is entirely dedicated to a comprehensive introduction of all the basic data structures
A data structure is a way in which we can organise the information to process and returned by a computer, so as it can be accessed and modified in an efficient and computational manner
Broadly speaking, it is a sort of bucket where we can place some information, that provides some methods to add and retrieve pieces of such information
Among the simplest data structures, there are those ones that organise their element in a specific order and allow the repeatability of the values they contain
Order: the sequence in which the elements are added to these data structures matters
Repeatability: the same value can appear twice or more times in the same data structure
A list is a countable sequence of ordered and repeatable elements
Countable: it is possible to know the length of the list (i.e. how many elements it contains) – in ThyMopani, we can use the support algorithm def len(countable_object)
Ordered: the elements are placed in the list in a specific order, which is preserved
Repeatable: the elements may appear more than one time in the list
Create a new list: list()
Add new element: <list>.append(<element>)
Remove element: <list>.remove(<element>)
Add elements from another list: <list>.extend(<another_list>)
my_first_list = list() my_first_list.append(34) my_first_list.append(15) my_first_list.append("Silvio") my_first_list.remove(34) my_first_list.extend(my_first_list)
my_first_list =
34
15
"Silvio"
15
"Silvio"
A stack is a is a kind of list seen from a particular perspective, i.e. from bottom to top, and with a specific set of operations
The elements follow a last in first out strategy (LIFO) for addition and removal
The last element inserted in the structure is placed in the top of the stack and, thus, it is also the first one that will be removed when requested
For removing the element in the middle of the stack one has to remove all the elements that have been added after such middle element
Create a new stack: deque()
Add new element: <stack>.append(<element>)
Remove (and return) latest element: <stack>.pop()
Add elements from another stack: <stack>.extend(<another_stack>)
my_first_stack = deque() my_first_stack.append(34) my_first_stack.append(15) my_first_stack.extend(my_first_stack) my_first_stack.append("Silvio") my_first_stack.pop()
my_first_stack =
A queue is a is a kind of list seen from a particular perspective, i.e. from left to right, and with a specific set of operations
The elements follow a first in first out strategy (FIFO) for addition and removal
The first element is placed in the left-most part of the queue and, thus, it is also the first one that will be removed when requested
For removing the element in the middle of the queue one has to remove all the elements that have been added before such middle element
Create a new queue: deque()
Add new element: <queue>.append(<element>)
Remove (and return) first element: <queue>.leftpop()
Add elements from another queue: <queue>.extend(<another_queue>)
my_first_queue = deque() my_first_queue.append(34) my_first_queue.append(15) my_first_queue.append("Silvio") my_first_queue.leftpop() my_first_queue.extend(my_first_queue)
my_first_queue =
34
15
"Silvio"
15
"Silvio"


Class: OpenTok::Session
- Inherits:
-
Object
- Object
- OpenTok::Session
- Defined in:
- lib/opentok/session.rb
Overview
Represents an OpenTok session.
Use the OpenTok.createSession() method to create an OpenTok session. Use the session_id property of the Session object to get the session ID.
Constant Summary
Instance Attribute Summary (collapse)
-
- (String) archive_mode
readonly
Whether the session will be archived automatically (:always) or not (:manual).
-
- (String) location
readonly
The location hint IP address.
-
- (String) media_mode
readonly
Set to :routed if the session uses the OpenTok Media Router or to :relayed if the session attempts to transmit streams directly between clients.
-
- (String) session_id
readonly
The session ID.
Instance Method Summary (collapse)
-
- (String) generate_token(options)
Generates a token.
Instance Attribute Details
- (String) archive_mode (readonly)
Whether the session will be archived automatically (:always) or not (:manual).
46 47 48 |
# File 'lib/opentok/session.rb', line 46 def archive_mode @archive_mode end |
- (String) location (readonly)
The location hint IP address. See the OpenTok.createSession() method.
46 47 48 |
# File 'lib/opentok/session.rb', line 46 def location @location end |
- (String) media_mode (readonly)
Set to :routed if the session uses the OpenTok Media Router or to :relayed if the session attempts to transmit streams directly between clients.
46 47 48 |
# File 'lib/opentok/session.rb', line 46 def media_mode @media_mode end |
- (String) session_id (readonly)
The session ID.
46 47 48 |
# File 'lib/opentok/session.rb', line 46 def session_id @session_id end |
Instance Method Details
- (String) generate_token(options)
Generates a token.
46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
# File 'lib/opentok/session.rb', line 46 class Session include TokenGenerator generates_tokens({ :api_key => ->(instance) { instance.api_key }, :api_secret => ->(instance) { instance.api_secret }, :session_id => ->(instance) { instance.session_id } }) attr_reader :session_id, :media_mode, :location, :archive_mode, :api_key, :api_secret # @private # this implementation doesn't completely understand the format of a Session ID # that is intentional, that is too much responsibility. def self.belongs_to_api_key?(session_id, api_key) encoded = session_id[2..session_id.length] .gsub('-', '+') .gsub('_', '/') decoded = Base64.decode64(encoded) decoded.include? api_key end # @private def initialize(api_key, api_secret, session_id, opts={}) @api_key, @api_secret, @session_id = api_key, api_secret, session_id @media_mode, @location, @archive_mode = opts.fetch(:media_mode, :relayed), opts[:location], opts.fetch(:archive_mode, :manual) end # @private def to_s @session_id end end |


WITNESS LIST Land & Resource Management Committee April 2, 2003-8:00A HB 334 Against: Horton, Ken (Texas Pork Producers Association) Salmon, Stephen (Riverside & Landowners Protection Coalition) Registering, but not testifying: For: Chatron, Michael J. (Texas Building Branch AGC) Fleming, Sharon (Texas Society of Architects -- Historic Resources Committee) Mendez, Mark (Tarrant County Commissioners Court) Pruitt, Sarah (Texas Building Trades Council) Ryan, Richard (Preservation Texas) Against: Gaines, Jimmy (Texas Landowners Council, Inc.) Grimm, James (Texas Poultry Federation) McClelland, Jack (Texas Association of Land Developers Inc.) Presnal, James K. (Tex. Nursery & Landscape Assn.) Terrell, James (Select Milk Producers, Inc.) HB 1064 For: Waldrip, Dib (Self and Comal Co. Commissioners Court) Against: Bravo, King (Self) Gaines, Jimmy (Texas Landowners Council, Inc.) Jensen, Daniel J. (Self and Texas Association of Builders) Suchecki, Ron (Texas Onsite Wastewater Assn.) Registering, but not testifying: For: Igo, Shanna (Texas Municipal League) Against: Aguirre, Frank (Self and TX Onsite Wastewater Assn.) Campbell, Scot (Self and Texas Land Developers Association) French, Mike (TX Manufactured Housing Association) Horton, Ken (Texas Pork Producers Association) Rutledge, Charles (Texas On-Site Wastewater Assoc.) Witta, George H. (TX Onsite Wastewater Assn.) HB 2035 For: Green, Renee (Bexar County Commissioners Court) Lee, Donald (Texas Conference of Urban Counties) Millikin, Jay (Comal County Commissioners Court) Waldrip, Dib (Self and Comal Co. Commissioners Court & Comal Co. Engineer) Wheeless, Skipper (County Judges & Commissioners Assoc. of TX.) Against: Gaines, Jimmy (Texas Landowners Council, Inc.) Jensen, Daniel J. (Self and Texas Association of Builders) Suchecki, Ron (Texas Onsite Wastewater Assn.) Webster, Keller W. (Self) Registering, but not testifying: For: Allison, Jim (County Judges & Commissioners Assn. of TX) Beaty, Bruce (Rockwall County Commissioners Court) Igo, Shanna (Texas Municipal League) Mendez, Mark (Tarrant County Commissioners Court) Smith, Tom "Smitty" (Public Citizen) West, Mickey (TX Assn. of Counties, Palo Pinto County) Against: Aguirre, Frank (Self and TX Onsite Wastewater Assoc.) Campbell, Scot (Self and Texas Land Developers Association) Cowan, John (Texas Association of Dairymen) Engelke, Tommy (Texas Agricultural Cooperative Council) French, Mike (TX Manufactured Housing Association) Grimm, James (Texas Poulty Federation) Horton, Ken (Texas Pork Producers Association) Long, J. Robert (Self and Texas Association of Builders) McClelland, Jack (Texas Association of Land Developers) Oefinger, David (Texas Pest Management Association) Rutledge, Charles (Texas On-Site Wastewater Assoc.) Salmon, Stephen (Riverside & Landowners Protection Coalition) Sereni, Daniel R. (Texas Association of Land Developers, Inc.) Sklar, Shane (Independent Cattlemen's Assoc.) Smith, Andrew (San Antonio Water System) Turner, Bob (Texas Sheep & Goat Raisers Assoc.) Witta, George H. (TX Onsite Wastewater Assn.) On: Stinson, Bill (Texas Association of Realtors) HB 2178 For: Anderson, Art (Self) Jennings, Doug (Self) Parr, Jim (Greater Fort Worth Association of Realtors) Savio, Harry (Home Builders Association of Greater Austin) Sheffield, Gary (Self and Texas Association of Builders) Teas, Andrew (Self and Teas Nursery Inc., Houston Apartment Association Inc.) Against: Aghamalian, Brandon (City of Fort Worth) Guernsey, Greg (Self and City of Austin, TX Neighborhood Planning and Zoning Department) Horton, Susan (Texas Municipal League) Jarrell, Phyllis M. (City of Plano) Palumbo, Dorothy (Mayor Brock, City Council, and City of Denton) Registering, but not testifying: For: Calcote, JC (Self and Texas Panhandle Builders Assn.) Cowan, John (Texas Association of Dairymen) Gaines, Jimmy (Texas Landowners Council, Inc.) Grimm, James (Texas Poulty Federation) Lehman, Mark (Self and Texas Association of Realtors) Mintz, David (Texas Apartment Association) Norman, Scott (Texas Association of Builders) Oefinger, David (Texas Pest Management Association) Salmon, Stephen (Riverside & Landowners Protection Coalition) Scurlock, Steve (Independent Bankers Association of Texas) Sklar, Shane (Independent Cattlemen's Assoc.) Small, Ed (Texas & Southwestern Cattle Raisers Assn.) Webster, Keller W. (Self) Against: Armendariz, Ricardo (City of El Paso) Martinez, Mario A. (City of Laredo) HB 2212 For: Miksa, Mary (Texas Association of Business) Against: Gonzales, Hector (Village of Webberville) Trantham, Thomas (Self and Village of Webberville) Registering, but not testifying: For: Cowan, John (Texas Association of Dairymen) Dippel, Donnie (Texas Ag. Industries Association) Gaines, Jimmy (Texas Landowners Council, Inc.) Goleman, Kinnan (TXR Operations) Grimm, James (Texas Poulty Federation) Howe, Billy (Texas Farm Bureau) Mintz, David (Texas Apartment Association) Norman, Scott (Texas Association of Builders) Oefinger, David (Texas Pest Management Association) Salmon, Stephen (Riverside & Landowners Protection Coalition) Sickels, Linda (Trinity Ind. Inc.) Sklar, Shane (Independent Cattlemen's Assoc.) Small, Ed (Texas & Southwestern Cattle Raisers) Terrell, James (Select Milk Producers, Inc.) Webster, Keller W. (Self) HB 2283 For: Hughes, Laura (Kaufman County) Ivy, Fonda (Self and 175 plaintiffs that reside in Windmill Farms in Kaufman County) Jones, Kenny (Self and 175 plaintiffs that reside in Windmill Farms in Kaufman County) Lee, Donald (Texas Conference of Urban Counties) Against: Gaines, Jimmy (Texas Landowners Council, Inc.) Herriage, Kathy (Self and Other Home Owners) Jensen, Daniel J. (Self and Texas Association of Builders) Webster, Keller W. (Self) Registering, but not testifying: Against: Aguirre, Frank (Self and TX. Onsite Wastewater Assoc.) Long, J. Robert (Self and Texas Association of Builders) Presnal, James K. (Texas Nursery & Landscape Assn.) Rutledge, Charles M. (Texas On-Site Wastewater Association) Salmon, Stephen (Riverside & Landowners Protection Coalition) Small, Ed (Texas & Southwestern Cattle Raisers) Suchecki, Ron (Texas Onsite Wastewater Association) Witta, George H. (TX Onsite Wastewater Assn.) On: Stinson, Bill (Texas Association of Realtors) HB 2486 For: Green, Renee (Bexar County Commissioners Court) Harris, Jack (Brazoria County) Lee, Donald (Texas Conference of Urban Counties) Millikin, Jay (Comal County Commissioners Court) Waldrip, Dib (Self and Comal Co. Commissioners Court) Wheeless, Skipper (County Judges & Commissioners Assoc. of TX.) Against: Bravo, King (Self) Gaines, Jimmy (Texas Landowners Council, Inc.) Jensen, Daniel J. (Self and Texas Association of Builders) Suchecki, Ron (Texas Onsite Wastewater Association) Webster, Keller W. (Self) Registering, but not testifying: For: Allison, Jim (County Judges & Commissioners Assn. of TX) Horton, Ken (Texas Pork Producers Association) Howe, Billy (Texas Farm Bureau) Igo, Shanna (Texas Municipal League) Mendez, Mark (Tarrant County Commissioners Court) Smith, Tom "Smitty" (Public Citizen) Sybert, Brian (Sierra Club, Lone Star Chapter) West, Mickey (TX Assn. of Counties, Palo Pinto County) Wimpee, Jerry (Rockwall County) Against: Aguirre, Frank (Self and TX. Onsite Wastewater Assoc.) Campbell, Scot (Self and Texas Land Developers Association) Long, J. Robert (Self and Texas Association of Builders) McClelland, Jack (Texas Association of Land Developers) Rutledge, Charles M. (Texas On-Site Wastewater Association) Terrell, James (Select Milk Producers, Inc.) Witta, George H. (TX Onsite Wastewater Assn.) HB 2506 For: Lee, Donald (Texas Conference of Urban Counties) Millikin, Jay (Comal County Commissioners Court) Waldrip, Dib (Self and Comal Co. Commissioners Court) Wheeless, Skipper (County Judges & Commissioners Assoc. of TX.) Against: Bravo, King (Self) Gaines, Jimmy (Texas Landowners Council, Inc.) Jensen, Daniel J. (Self and Texas Association of Builders) Webster, Keller W. (Self) Registering, but not testifying: For: Allison, Jim (County Judges & Commissioners Assn. of TX) Horton, Ken (Texas Pork Producers Association) Howe, Billy (Texas Farm Bureau) Igo, Shanna (Texas Municipal League) Sklar, Shane (Independent Cattlemen's Assoc.) Sybert, Brian (Sierra Club, Lone Star Chapter) West, Mickey (TX Assn. of Counties, Palo Pinto County) Against: Aguirre, Frank (Self and TX. Onsite Wastewater Assoc.) Campbell, Scot (Self and Texas Land Developers Association) Long, J. Robert (Self and Texas Association of Builders) McClelland, Jack (Texas Association of Land Developers) Sereni, Daniel (Texas Association of Land Developers, Inc.) HB 2569 For: Briones, Dolores (County of El Paso) Lee, Donald (Texas Conference of Urban Counties) Against: Campbell, Scot (Self and Texas Land Developers Association) Gaines, Jimmy (Texas Landowners Council, Inc.) McClelland, Jack (Texas Association of Land Development Inc.) Sereni, Daniel (Texas Association of Land Developers, Inc.) Registering, but not testifying: Against: Horton, Ken (Texas Pork Producers Association) Long, J. Robert (Self and Texas Association of Builders)


GEO SEARCH APP
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HOW TO WRITE A TECHNICAL NOTE FOR YOUR FUTURE APP?
Before contacting an agency for developing your business application, you need to have a detailed statement of work done. Why is this important? A documented plan will help potential vendors to evaluate a project without hidden costs and avoid misunderstandings with performers.
You can draw up a technical note with the help of a marketer and business analyst, but if you decide to do it yourself, this guide will be helpful for you. Our Head of Research & Development Department has collected some useful tips based on their extensive experience.
So, let's get started.
IN WHAT FORMAT TO COMPILE THE TECHNICAL NOTE?
You can write it whatever is convenient for you, but try to make it speak for the essence of the project itself. It can be a text with the list of features, but it would be much better if you attach hand-drawn sketches or screenshots of similar applications with descriptions. Any visualization will be helpful.
If you want to create a copy of some existing application, you should name it and indicate how your project will differ. You can discuss the requirements verbally, but it's always better to have all documented.
WHAT MANDATORY PARTS SHOULD IT CONSIST OF?
GENERAL INFORMATION
- Description of the idea.
- Background information of the project: problems the application would solve, its target audience, user story.
- Devices the product would work on.
- Preferences for the technology stack.
- Enumerating deliverables: landing page, mobile app, web app, admin panel, etc.
- The link to a similar application and explanation of how it will differ from your future product.
LITE MODE (FOR LEVEL-UP TECH NOTE)
In addition to general information, describe the user journey: everything that a user can do in the app. For instance:
- to find a landing page on the Internet;
- to register via email, phone, and Facebook;
- to log in to the platform;
- to recover the password;
- to see a news feed and advertisement;
- to leave comments on friends' posts.
ADVANCED MODE (FOR TECH NOTE HERO)
List the screens and describe how a user is supposed to interact with the service on each particular stage. Usually, it is also accompanied by sketches: splash screen, registration screen, and so on.
WHAT AFFECTS THE DEVELOPMENT COST AND TIMELINE?
- The scope of work. If you want to add a lot of extra features to your app, the development will be long and expensive.
- The quantity and skill level of specialists. You can choose a large team of experienced engineers to get your app delivered quickly, but it will increase the monthly budget.
- The tech stack. Additional features that require specific knowledge and experience, or features that use the capabilities of the device (image and video processing, voice assistant, etc.).
But there is a nuance: the longer the team makes your application, the more expensive it becomes for your business. For instance, a project could have been bringing you money for 2 months already, but it's still at the development stage. It also includes the cost of environment and tools, such as servers and APIs.
AS A BONUS
We have compiled a list of nuances that you should take into account. This knowledge we have acquired over the years of work in the digital market.
- At the initial stage, make up the list of core features for the running application cycle. For instance, to run a food delivery app, you only need to implement the user side with the ability to place an order: the main menu, shopping cart, payment, address. Then you can add more features such as a loyalty system, registration, order history, saving cards, driver tracking, online chat, etc. This lean approach called MVP (Minimum Viable Product), it refers to agile development and helps not to run out of your money before the application is ready.
- You should set the deadline. To do it right, feel free to consult the engineering team. Together with the timeline they can come up with a project plan and burn down chart.
- The estimate of your primary requirements will be approximate. As soon as the team completed the design and documentation, the manager can estimate your project more accurately.
- Focus on design in the first step. The success of your project depends on it in many aspects. Then think about development. It's best to take a phased approach to make each step perfectly. Orient the team in advance according to the expected budget to not waste time.
- The quote is not the only decision making factor. Have a call with a team, check its previous works, read reviews, and get to know its process of work. Also, you can assign the paid test task to make sure they deliver what they say.
- Estimates from agencies may differ: someone can lower the price to take on the project (hidden costs), someone can overstate (overload). It's better to find out what the estimate includes in case of each feature, and ask why the performers indicated that particular time. Read customer reviews, do a test. Also, you can go with a trial period: 1-2 weeks to look at the speed of work, communication, and the process, and then make a decision.
- If you don't need to make the project from scratch, provide the initial requirements and project documentation and the legacy materials of the design or coding part. Otherwise, the team will spend the entire budget on studying the current code.
 Feel free to consult with specialists, ask questions, and discuss controversial nuances. Every detail can be crucial for your business.
We'd be glad to create the high-level scope of work document as well as the business & technical specifications for you.
If you want to know the approximate estimate of time and price for your idea, fill out the brief and get a rough quote within 24 hours.


Click the view more posts link bellow, to see the currently available post-tutorials to help you get your { Personal } website up and running quicker!
Note that every time you update the site configuration (_config.yml), you will need to cancel the serving (Ctr + C) and serve the website again.
Any contributions, feedback or issues to the repo are more than welcome!


Legend.
Bob Marley
Legend.
Bob Marley
This Is It.
Michael Jackson
Hardwired... to Self-Destruct.
Metallica
It's Better If You Don't Understand.
Bruno Mars
Legend.
Macklemore
This Is It.
Katy Perry
Hardwired... to Self-Destruct.
Wiz Khalifa
It's Better If You Don't Understand.
Tool


{% load static %}
CAM (Categorized Affect Map) is part of a research project at the American International University Bangladesh (AIUB), Bangladesh, which aims to collect people's affective/emotional reponses towards different stimuli/environments. You can use this in online manner, we are looking forward to make it offline as well, however, we currently collecting data from two populated areas, Bashundhara R/A and Wari. For other areas we are expecting requests to add.
While you report your feelings, your mobile phone's or desktops GPS estimates your current location. We also use a most approximation api from leaflet.js to get current location for a user. Your answers and location information are then anonymously and securely sent to our database. We don't record your name or any other identifying information including ip address. Therefore, we won't know who you are.
The data contributed are solely used for academic research purposes. We aim to investigate how people affectively response to different environments, and how these affective responses influence their behaviors, e.g, approaching or avoiding particular places.
Big thanks should be given to American International University Bangladesh for helping and inspiring for this project. We also would like to thank our honorable Supervisor Professor Dr. Tabin Hasan sir for accepting this project proposal and accelerating our works with his supervision, guidance and continuous support. We would also appreciate for the encouragement given by all contributors adn supporting stuffs.
For more information regarding CAM (Categorized Affect Map), please contact<EMAIL_ADDRESS>. Thank you for using CAM (Categorized Affect Map).


I've experienced several mushroom trips, yet none of them where near the intensity of this. I ingested approximately four grams at 11:23 and within 25 minutes, I could tell that something about these mushrooms was not normal. I began feeling an immense manipulation of my mind, which caused me to suddenly be extremely perplexed. I was weighing out the remainder of the mushrooms when the digital scale which I was using suddenly melted. I panicked.
'This isn't supposed to happen' raced through my mind, I immediately leapt form my chair laughing hysterically to go stand in a corner. My friends Sa and Ia followed and attempted to scare me by making awkward movements with their hands, 'I swear to god if you harm me in any way, I WILL kill you' I screamed, this wasn't a threat, It was a warning. After saying this I realized it was important for me to find a place where I could be away from everyone. I went outside and stood in a corner. In this place I lost my mind. I lost all association with my entire body, and became several different versions of myself. Instead of myself being C, I was Responsible C, Rational C, Panicked C, Drug C, Intellectual C and a main entity which controlled every variety of C which was thought.
At this point I had lost the ability to think inside my head, and every thought I had was spoken since my mind lost the ability to think it. I began saying 'Leave C alone, talk to rational C he'll know what to do. No he isn't necessary, Drug C. I am having so much fun, Ok, Thought, what should we do, what should we do.' I went through this several times while each time experiencing an immense variety of emotion, often panic rocketing into powerful happiness.
After many times going through this while standing in a corner outdoors in negative 30 degree weather talking to myself I decided to call my friend Co, a responsible friend, I assumed he would have an idea of what to do. While speaking on the phone with him I was not C. I was simply thought, every once in awhile Co would ask to speak to C, then I’d say things like 'Why doesn't Co want to speak to thought, shut up thought... be rational Co is a rational being, speak to him, let C speak to him...Co what’s up?' Then Co would speak to me normally and ask me a few questions to clam me down.
Eventually after I began really freaking out as I became much more immersed in this experience and told Co I had to hang up. I proceeded to use Thought to speak to several different C's while in my own corner outside. I looked up and the brick wall began moving as if it was a pond effected by the ripple effect of a object being thrown into it. I looked at a hose on the ground and it began slithering. I then was convinced that this was experience would be astronomical in comparison to every other drug I've ever experienced which includes; Ecstasy, Mushrooms, Marijuana, Dextromorpan, Codeine, Alcohol and Ketamine.
I used a body (my own) to reach for a cell phone in a pocket. I looked at the time, it was 12:11, I began panicking 'Are people calling the police, Is Thought scaring them?' I wanted to help but I had to gain my composure first. Soon, Ia came outside and said 'C I know you don't feel it, but your freezing out here and you need to go inside. I simply agreed. I went inside where everything was either melting or changing in size, proportion was random as table and chairs would go form enormous to tiny. With much difficulty I walked approximately 12 feet, to the stairs and proceeded to walk downstairs. I saw a friend of mine X, who was terrifying to me. He began to grow, I saw him as some sort of warrior. I looked at him with fear and said 'To many of you, we have to go downstairs' (referring to myself.) I then sat in the same place I was prior to leaving to go to the corner outside.
I called Co again and went through the same sequence of talking to myself and then saying 'No talk to Co, Co what’s up?' then I didn’t think he'd understand, then Thought was talking to rational Chris and Drug Chris and then Co would say 'ok let me talk to normal C' and I would say 'Should I let him, ok fine I'll let Co talk to C, Co what’s up?' The phone started to feel slippery and it simply fell out of my hand and hung up, I then simply laughed hysterically. As I laughed I looked at my hands and waved them through the air. Colours where being dispersed form the tips. A variety of colours at that, yellow purple, green blue, moving as if they where strings swaying through the wind. They made sounds varying from static to screeching as they moved. I looked at the floor and it moved like liquid. I looked up and my entire perception of proportion had left me, the rather small basement now seemed infinite.
I looked up and began creating scenarios in my head which weren’t even near the reality of the situation. I believed that this basement was a bomb shelter and outside of it everyone was panicking about our safety because we where on drugs (I was on drugs.) My friend X who was also on these mystical mushrooms came downstairs and greeted me, at this point I was comfortable with being several C’s controlled by the single entity and began to slip into the drug as I became familiar with what was happening. “Hello X, I like what is happening to us now” He simply replied with “yea man” probably assuming that I was speaking about myself and him.
My 2 other friends In the basement ST and SG came over to where we where to greet X, at this point X’s dad came downstairs; acting sober was impossible. I looked up at him with enormous pupils swaying and twisting and turning in ways which are completely unnatural. I looked up at him and his facial hair began to grow, baffled by this, yet overjoyed by what I was experiencing I abruptly broke into laughter, his Dad simply assumed we had smoked a lot of pot which he wasn’t against that, so it wasn’t a problem that he saw us in this state of mind. He dismissed our antics and went upstairs.
Still quite panicked I walked over to the couches in the basement approximately 7 feet away from me, this felt like miles which I enjoyed walking because I felt as though I was flying each step was light and feathery and my head felt elevated. I sat down in a couch and started asking strange questions “What is important? Why are linguistics necessary? Why is there time?” Then I went from this confusion to fear. “Wait! I need a few questions answered. Is everyone calm?” my friends said yes. “Does anyone know we are on drugs?” My friends said no. “Are people worried?” My friends said no. I then slipped into a comfortable state, I now knew I had nothing to worry about and I was safe.
I decided I had to attempt to describe what was happening and write it down. I got as far as “my brain has poison swirling through…” Then wrote “27” then wrote “drugs are stupid.” I began talking to X’s brother P about my experience I would cry tears of happiness and laugh and become confused, I went through the same thought process nearly 9 times but I thought it was 27 times. Constantly talking to him in third person. I was experiencing revelations while I spoke to him, I was disassociated from everything and didn’t believe anything was necessary except thought. Then said “there is something so beyond drugs, your mind… your mind is important, all a human needs, is thought, we all must build on thought.” I made several speeches to him about how unnecessary drugs are. Constantly attempting to write it down but failing, because the rate and jump of ideas and thoughts which I was going through was so absolutely radical and rapid that it made it impossible.
I would be immersed in a feeling of relaxation which overwhelmed me like a blanket, I then began to become happy, then panicked once again, then afraid, then confused then I would feel some sort of emotion which I can only describe as honest, though it is an adjective used to describe truthful, it is the closest word in relation to the emotion which I felt. After a 30 minute conversation P went to bed, I sat in my chair listening to music for a brief period of time, then decided to interact with my friends ST and SG. I was used to the visuals at this point because they where constantly happening, designs on mattresses, every ones face would shift, shimmer and almost vibrate, while others faces would simply melt as their eyes would move to different parts of their face. They also would become thinner than wider and move sometimes like the liquid one would see in a lava lamp.
We asked each other questions, This became repetitive and I felt as though I needed to experience things, I went upstairs to find X and to look in the bathroom mirror. I first went to look in the mirror, I was talking gibberish as I did this, and didn’t know whether or not I was thinking or talking. I looked at my eyes and my pupils where enormous. My face? I couldn’t tell what it looked like because it was constantly shifting in shape and size, the wall behind me in the mirror had a pattern of shells on it, which would rotate frequently.
I left the bathroom after about 20 minutes of standing on front of the mirror talking about this revelation that I had of nothing being important except for thought. I went to the kitchen and was acting insane. Dancing around the kitchen in strange ways and moving my hands lasted for a considerable amount of time. I then went upstairs, to talk to X, I told him to come with us referring to thought, which controlled the C’s and the several C’s (main components and adjectives which describe my personality split into people.) I lead X down the stairs where we sat and discussed things, everything that I felt at this time was sensational.
My visuals started to slowly end and then, we all began having conversations, about the fact that we don’t feel that we can function properly anymore in the real world. We had been thrown this curveball of perception which we can’t associate with anything concrete and essentially real in terms of recognition in the real world, because though I attempt it in this experience report, the experience was ultimately impossible to describe then and now. Frustrated with this, I went to bed, assuming It would go away the next day.
The next day I felt strange and spent the entire day confused about whether or not to take the ideas I had and things I felt seriously or just think of it as the psychoactive effects of a drug which have absolutely no significance in terms of there validity within a sober world. This entire day was difficult yet by the following day, I felt much better and the experience had become a memory, by far, the most powerful memory in my conscious waking mind. It was a night I’ll never forget, a night that may have changed my life forever.
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.


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Achievement Unlocked: First time this year biking every day of the work week.
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Achievement Unlocked: First time this year biking every day of the work week.
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An outlier is a type of anomaly in your data, something that you didn't expect or that surprised you, based on historical averages or results. You will want to identify outliers to isolate data points that significantly differ from other data points, and then take action to investigate the reasons for the differences. The results of this analysis can make a significant impact on business decision making.
Consider the scenario where you are analyzing data for a shipping warehouse. You notice that the number of orders increased above average for a specific product category. You first want to identify the product category. Then, you want to ask several questions about the outlier:
Did above average shipments happen that day?
Did this anomaly occur in a specific warehouse?
Did a single event cause the increase in orders for that specific category?
Did this event occur on other days in the last month, quarter, year, or prior year?
Power BI allows you to identify outliers in your data, but you need to first determine the logic behind what constitutes an outlier. You can use trigger points, such as calculations, around what you would consider the outlier to be.
The process of identifying outliers involves segmenting your data into two groups: one group is the outlier data and the other group is not. You could use calculated columns to identify outliers, but the results would be static until you refresh the data. A better way to identify outliers is to use a visualization or DAX formula because these methods will ensure that your results are dynamic.
When you have identified the outliers in your data, you can then use slicers or filters to highlight those outliers. Additionally, you can add a legend to your visuals so that the outliers can be identified among the other data. You can then drill in to the outlier data for more detailed analysis.
The best visual to use for identifying outliers is the scatter chart, which shows the relationship between two numerical values. Scatter charts display patterns in large sets of data and are, therefore, ideal for displaying outliers.
When you add a scatter chart to your Power BI report, you put your fields of interest in the X Axis and Y Axis sections, respectively. In this case, the Orders Shipped field is on the x-axis, and the Qty Orders field is on the y-axis.
The visual will update to display the data according to the selected fields, and you'll be able to clearly identify the outliers in that data; they are the isolated items that are away from the bulk of the data.
Now that you can identify the outliers in your data, you can investigate the reasons for their existence and take corrective action.
You can use DAX to create a measure that will identify the outliers in your data, such as in the following formula:
Outliers =
CALCULATE (
[Order Qty],
FILTER (
VALUES ( Product[Product Name] ),
COUNTROWS ( FILTER ( Sales, [Order Qty] >= [Min Qty] ) ) > 0
)
)
When you have created a new outlier measure, you can group your products into categories by using the grouping feature, as you previously did when creating a histogram. You then need to add a scatter chart visual, as you did in the previous section, because this is the best visualization option for displaying outliers. When you've added the scatter chart, populate it with the fields that are associated with your DAX formula and outlier measure.
In the scatter chart, you'll be able to identify the outliers in your data. You can then investigate the reasons for their existence and take corrective action.


This stuff is pretty amazing
We've all had experience with conflict and many times it has left us feeling angry or upset. What if you could analyze the way you are feeling on a more detailed level? This can be helpful to mediate negative feelings and resolve the conflict. Ultimately, I can see this helping me be just a better person.
A time I had conflict was when I was employee. A supervisor had asked me to perform a task and I felt agitated and upset because the supervisor did not know the process involved in completing the task. The supervisor assumed it was a simple task that could be completed only in a relatively short time or without effort.
I felt taken for granted in this case because the supervisor asked for my help but there was a disconnect between my knowledge of the process and how the supervisor understood what the task entailed. Really the task should not have been dismissed as trivial. There was no reason for the supervisor to feel this way because he in fact did not know what I had to do to complete the task.
My first reaction was definitely feeling resentful. I shut down communication and took myself away from interacting with the supervisor at first. I then tried to make the supervisor understand what I had to do and argue about the complexity of the task. I felt he was also getting upset because I was being critical of how he understood the task and process. I felt like I could have been more calm and handled the situation differently. His expression of anger could have been mediated by my calm reasoning.
I definitely feel if I had reasoned about the why the supervisor did not know the process and calmly explain the process to him I could have handled the situation differently. I would not be as agitated and the supervisor would not be displeased. If he had expressed disagreement I would have had to just let him understand on another occasion or in a different way.
In this case there was a true disconnect the supervisor did not have adequate input in the process and had little true knowledge of the process. Because of this, there was truly difficulties in him understanding my situation, but really there is no reason to be upset about it, only to acknowledge that he may disagree that he doesn't know what the process and to move on.


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Twisted.web2 is an asynchronous HTTP 1.1 server written for the Twisted internet framework. It provides a RFC 2616 compliant HTTP 1.1 protocol implementation, with pipelined and persistent request support, in a non-blocking threadless manner.
It also includes a simple web framework with request and response objects, static file support, error handling, form upload support, HTTP range support, pre-built parsers for all standard headers, and a bunch of other goodies.
It is deployable as a standalone HTTP or HTTPS server, as a HTTP[S] server proxied behind another server, or as a SCGI, FastCGI, or CGI script.
In addition to running native twisted.web2 applications, it can also run any WSGI or CGI application, or, via compatibility wrappers, most applications written for the older twisted.web API.
Currently, twisted.web2 does not include a HTTP client or proxy, but will at a future date.
Twisted.web2 is not a templating framework. It provides mechanisms for locating and running code associated with a URL, but does not provide any means for separating code and data or to ease the task of generating HTML.
Twisted.web2 is in general fairly speedy. However, keep in mind that it is a python program, and, while it is empirically "fast enough", it cannot match Apache in static file serving speed. <insert actual measurements here>
This tutorial should be readable by people who do not have much Twisted experience yet, but, you should know Python, and HTML, before starting. While it is hopefully redundant to say this, you also ought to have installed twisted, and twisted.web2.
When you have finished this tutorial, you should be able to write some simple resources and publish them with twisted.web2.
You may run this program via
twistd -ny simple.py
.
twistd
is the Twisted runner; it
knows how to execute applications by looking for the
application
variable declared at
top-level. You can also run your server in the background
(daemonized), via twistd -y
simple.py
. You can access your server via the url "
http://localhost:8080/".
For more deployment options, see
the deployment chapter.
A resource is responsible for handling one segment of the
URL. Here, we have created a resource to handle the top level of
the url hierarchy. The addSlash =
True
setting tells twisted.web2 that this is a
directory-like resource. This means that it will add a
"/" to the end of the URL automatically, if needed,
and respond under that name. Root resources should always have
addSlash = True
.
The defined class has just a single method:
render
. This method takes a single
argument: request
, which contains all the
state related to the current rendering operation. This
particular render method always returns the same data, so we
won't use request
. We'll get back to
it later.
Here, the render
method simply
returns a http.Response
object containing the output.
After defining this class, next we need to tell twisted.web2 to
serve it up. This is accomplished by creating the
server.Site
object,
with an instance of your top-level resource as its argument, and
then some standard boilerplate to tell Twisted what services to
start and what port to serve them on.
Of course, what good is a webserver that can only serve up a
single page? So, you can also add child resources to your
top-level resource,
via child_<name>
attributes.
Here a few new concepts have been introduced:
twisted.web2.static.File
lets you serve
a file off the disk. With this, you get a lot of functionality:
automatic Content-Type setting from the file extension,
last-modified and etag calculation, and the ability to hook in
custom processors for certain file types. It will also generate
directory listings if you point it at a directory instead of a
file.
twisted.web2.http.Response
takes three
arguments: the response code, the output headers, and the output
stream. For more information,
see Resource APIs.
As an aside for those who know a bit about HTTP, note that just by setting the Last-Modified and ETag response headers, you enable automatic precondition checks which support the If-Modified-Since, If-Unmodified-Since, If-Match, and If-None-Match input headers. This allows the client to request that the resource only be sent if it has changed since the last time the client downloaded it, saving bandwidth. Also, the Range and If-Range headers are supported on every resource, allowing partial downloads, and default values for the "Server" and "Date" headers are added to the output for you automatically.


When Irene came through we were tucked away up in the C&D cannel
and saw very little of the winds, waves and tidal surge.
Others were not as fortunate, the communities of Oriental and
Beaufort, NC show move of the impact. We saw 45 foot sail
boats a 100 yards away from the water and a good 6 feet out of
the water. Here in the anchorage we see 7 boats that have
been damaged and are either on shore or floating with major
repair ahead of them. Talking to people here they saw a
8.5 tidal surge, had winds of 80 mph and lots of water
front property that went under.
One of the projects we have on the boat is installing a water
maker in the port forward locker. When working on a boat
you always hate to drill into the hull because there is a bunch
of water on the other side and if you drill too deep, well it is
not a good thing. A way to work around this is by epoxying;
bonding, wood to the inside of the hull and then attaching your
items to the piece of wood. Bob B off the boat Baloo is an
"expert" with epoxy so he took the time to teach Dean how to do
it. Once the wood has been bonded to the boat it will not
come off so you need to make sure it is right the first time.
The project went off with out issues and Dean only has one that
was slightly off target, practice practice pratice.
Kris has been doing some work as well, but with rather
disastrous results. Dean has been wanting her to hook the
GPS (global positioning system) which gives us latitude and
longitude coordinates and time to our VHF (very high frequency)
radio. The new VHF radios have a button you can push
if in distress, and they will send out a constant message with
your GPS coordinates.
Kris usually does good wiring, but in this case hooked up a wire
wrong, and fried the VHF. Oh Well, a new VHF isn't that
much money :(
It has been great catching up with our friends Bob and Anne on
Baloo. We first met them in Tacoma, WA when they were
getting ready to go cruising at the same time that we were on
our first cruise to Mexico. They had two young boys at the
time. Now they have a bigger boat, no kids and a nice
heater on board, and now we have the kid, and no heater.
We will be leaving tomorrow and heading out onto the big blue
ocean for a sail down to Wrightsville Beach, N.C. We
should have nice north winds, but cold weather. After that
we will take the ICW down to Cape Fear, Bald Head Island were we
promised Derek a night at the marina so he can see Bald Head
Island. Kris, Lee and Norm stopped there on the way up
delivering the boat and after Derek learned that you can only
ride golf carts on the island, he was hooked. So a night
there with a golf cart rental is in the plan.
After that we will make our way down to Charleston, S.C either
on the outside or on the ICW depending on weather.
Update 10/21/11 Beaufort/Irene and the wonderful world of expoxy
nice epoxy job, only attached at the bottom and top but will hold a ton
Our friends Bob and Anne on Baloo
lost dreams


{% extends 'base.html' %} {% load static %} {% block head_block %} {% endblock %} {% block body_block %}
You can assign a label (annotate) this Mass2Motif from the Annotation field below. Additionally, a shorter annotation can also be assigned through the Short Annotation field. This will be used in the network visualisation.
{% if status %}{{ status }}
{% endif %}The following table shows the fragment and loss features that are explained by this Mass2Motifs and their corresponding probabilities. After thresholding to save the model, the total probability left in this motif is {{total_prob}}
| Feature | Probability | Link |
|---|---|---|
| {{motif_feature.feature.name}} | {{motif_feature.probability}} | Details (in original experiment) |
Two bar plots will appear below this message. The first shows the proportion of the total intensity of these features explained by this Mass2Motif. Red bars show the total intensity (across the whole dataset), blue bars show the proportion explained by the selected Mass2Motif. The second shows the number of times each feature in this Mass2Motif appears in the documents associated with this Mass2Motif.
The following table lists all fragmentation spectra that are explained by this Mass2Motif at the threshold specified in the experiment option.
| Fragmentation spectra | Annotation | Probability | Overlap Score |
|---|---|---|---|
| {{dm2m.document.name}} | {{dm2m.document.annotation}} | {{dm2m.probability|floatformat:"3"}} | {{dm2m.overlap_score|floatformat:"3"}} |
The fragmentation spectra of molecules explained by this Mass2Motif are plotted below. Features (fragments and losses) explained by this Mass2Motif will be coloured red, while parent ion is coloured in blue. Click Next and Previous to cycle through the fragmentation spectra.
| Taxa Term | Probability |
|---|---|
| {{term_instance.taxterm.name}} | {{term_instance.probability|floatformat:"3"}} |
| Substituent Term | Probability |
|---|---|
| {{term_instance.subterm.name}} | {{term_instance.probability|floatformat:"3"}} |


{% extends "base.html" %} {% from 'bootstrap/form.html' import render_field %} {% block content %} Extract the color palette from an image Extract color palette from an image with k-means and k-nn. {{ form.csrf_token() }} Choose file Number of colors Uploading... Here are the major tints in this image: # Hex value Name {% endblock %}
Extract color palette from an image with k-means and k-nn.


--- layout: resource title: Hungary ---
Know any other resources? Send us an email or add links to this page with a Pull request on GitHub!


ML.Frequent Pattern Mining¶
-
class
ddf_library.functions.ml.fpm.
AssociationRules
(confidence=0.5, max_rules=-1)¶ Bases:
ddf_library.bases.ddf_model.ModelDDF
Association rule learning is a rule-based machine learning method for discovering interesting relations between variables in large databases. It is intended to identify strong rules discovered in databases.
Example: >>> rules = AssociationRules(confidence=0.10).fit_transform(item_set)
Setup all AssociationsRules’s parameters.
Parameters: - confidence – Minimum confidence (default is 0.5);
- max_rules – Maximum number of output rules, -1 to all (default).
-
check_fitted_model
()¶
-
fit_transform
(data, col_item='items', col_freq='support')¶ Fit the model.
Parameters: - data – DDF;
- col_item – Column with the frequent item set (default, ‘items’);
- col_freq – Column with its support (default, ‘support’);
Returns: DDF with ‘Pre-Rule’, ‘Post-Rule’ and ‘confidence’ columns.
-
load_model
(filepath)¶ Load a machine learning model from a binary file in a storage.
Parameters: filepath – The absolute path name; Returns: self Example: >>> ml_model = Kmeans().load_model('hdfs://localhost:9000/model')
-
save_model
(filepath, overwrite=True)¶ Save a machine learning model as a binary file in a storage.
Parameters: - filepath – The output absolute path name;
- overwrite – Overwrite if file already exists (default, True);
Returns: self
Example: >>> cls = KMeans().fit(dataset, input_col=['col1', 'col2']) >>> cls.save_model('hdfs://localhost:9000/trained_model')
-
set_max_rules
(count)¶
-
set_min_confidence
(confidence)¶
-
class
ddf_library.functions.ml.fpm.
FPGrowth
(min_support=0.5)¶ Bases:
ddf_library.bases.ddf_model.ModelDDF
FPGrowth implements the FP-growth algorithm described in the paper LI et al., Mining frequent patterns without candidate generation, where “FP” stands for frequent pattern. Given a data set of transactions, the first step of FP-growth is to calculate item frequencies and identify frequent items.
LI, Haoyuan et al. Pfp: parallel fp-growth for query recommendation. In: Proceedings of the 2008 ACM conference on Recommender systems. ACM, 2008. p. 107-114.
Example: >>> fp = FPGrowth(min_support=0.10) >>> item_set = fp.fit_transform(ddf1, column='col_0')
Setup all FPGrowth’s parameters.
Parameters: min_support – minimum support value. -
check_fitted_model
()¶
-
fit_transform
(data, input_col)¶ Fit the model and transform the data.
Parameters: - data – DDF;
- input_col – Transactions feature name;
Returns: DDF
-
load_model
(filepath)¶ Load a machine learning model from a binary file in a storage.
Parameters: filepath – The absolute path name; Returns: self Example: >>> ml_model = Kmeans().load_model('hdfs://localhost:9000/model')
-
save_model
(filepath, overwrite=True)¶ Save a machine learning model as a binary file in a storage.
Parameters: - filepath – The output absolute path name;
- overwrite – Overwrite if file already exists (default, True);
Returns: self
Example: >>> cls = KMeans().fit(dataset, input_col=['col1', 'col2']) >>> cls.save_model('hdfs://localhost:9000/trained_model')
-


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Note
Click here to download the full example code
Mills¶
Examples of milling behaviours.
First of all, some standard imports.
import os
import sys
import time
import math
import torch
import numpy as np
from matplotlib import pyplot as plt
import sisyphe.models as models
from sisyphe.display import display_kinetic_particles
use_cuda = torch.cuda.is_available()
dtype = torch.cuda.FloatTensor if use_cuda else torch.FloatTensor
Milling in the D’Orsogna et al. model¶
Let us create an instance of the attraction-repulsion model introduced in
D’Orsogna, Y. L. Chuang, A. L. Bertozzi, L. S. Chayes, Self-Propelled Particles with Soft-Core Interactions: Patterns, Stability, and Collapse, Phys. Rev. Lett., Vol. 96, No. 10 (2006).
The particle system satisfies the ODE:
where \(U\) is the Morse potential
N = 10000
mass = 1000.
L = 10.
Ca = .5
la = 2.
Cr = 1.
lr = .5
alpha = 1.6
beta = .5
v0 = math.sqrt(alpha/beta)
pos = L*torch.rand((N,2)).type(dtype)
vel = torch.randn(N,2).type(dtype)
vel = vel/torch.norm(vel,dim=1).reshape((N,1))
vel = v0*vel
dt = .01
simu = models.AttractionRepulsion(pos=pos,
vel=vel,
interaction_radius=math.sqrt(mass),
box_size=L,
propulsion = alpha,
friction = beta,
Ca = Ca,
la = la,
Cr = Cr,
lr = lr,
dt=dt,
p=1,
isaverage=True)
Run the simulation over 100 units of time and plot 10 frames. The ODE system is solved using the Runge-Kutta 4 numerical scheme.
frames = [0,1,2,3,4,5,10,40,70,100]
s = time.time()
it, op = display_kinetic_particles(simu,frames)
e = time.time()
Out:
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Print the total simulation time and the average time per iteration.
print('Total time: '+str(e-s)+' seconds')
print('Average time per iteration: '+str((e-s)/simu.iteration)+' seconds')
Out:
Total time: 86.00608777999878 seconds
Average time per iteration: 0.008600608777999877 seconds
Milling in the Vicsek model¶
Let us create an instance of the Asynchronuos Vicsek model with a bounded cone of vision and a bounded angular velocity, as introduced in:
Costanzo, C. K. Hemelrijk, Spontaneous emergence of milling (vortex state) in a Vicsek-like model, J. Phys. D: Appl. Phys., 51, 134004
N = 10000
R = 1.
L = 20.
nu = 1
sigma = .02
kappa = nu/sigma
c = .175
angvel_max = .175/nu
pos = L*torch.rand((N,2)).type(dtype)
vel = torch.randn(N,2).type(dtype)
vel = vel/torch.norm(vel,dim=1).reshape((N,1))
dt = .01
We add an option to the target
target = {"name" : "normalised", "parameters" : {}}
option = {"bounded_angular_velocity" : {"angvel_max" : angvel_max, "dt" : 1./nu}}
simu=models.AsynchronousVicsek(pos=pos,vel=vel,
v=c,
jump_rate=nu,kappa=kappa,
interaction_radius=R,
box_size=L,
vision_angle=math.pi, axis = None,
boundary_conditions='periodic',
variant=target,
options=option,
sampling_method='projected_normal')
Run the simulation over 200 units of time and plot 10 frames.
# sphinx_gallery_thumbnail_number = -1
frames = [0, 10, 30, 50, 75, 100, 125, 150, 175, 200]
s = time.time()
it, op = display_kinetic_particles(simu,frames)
e = time.time()
Out:
Progress:0%
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Print the total simulation time and the average time per iteration.
print('Total time: '+str(e-s)+' seconds')
print('Average time per iteration: '+str((e-s)/simu.iteration)+' seconds')
Out:
Total time: 69.85851073265076 seconds
Average time per iteration: 0.003492925536632538 seconds
Total running time of the script: ( 2 minutes 38.151 seconds)


Line comparison: find duplicate lines in list A
Line comparison: find unique lines in list A
List comparison: find lines unique to list A
List comparison: find lines unique to list B
Normalise lists A and B: convert to lowercase
Normalise lists A and B: leave only English alphabetic characters, dashes and spaces
Normalise lists A and B: remove digits
Normalise lists A and B: sort
Proceed


Object of the game
Touch the ball as many times as you can before the game is over.
How to play
Each time you touch the ball, your score increases by 1. The game is over when the ball hits the wall a particular number of times, depending on the skill level selected.


Version 2 of the Amazon Chime SDK for JavaScript makes a small number of interface
changes, as well as removing some deprecated interfaces.
In many cases you should not need to adjust your application code at all. This will be the case if:
You do not implement AudioVideoFacade or DeviceController yourself.
You do not explicitly call enableWebAudio on any instances of DeviceController or
AudioVideoFacade, or use the MeetingSessionConfiguration field enableWebAudio.
You already handle errors in chooseAudioInputDevice with catch.
You neither directly call, nor implement, the bindAudio* methods on AudioMixController.
If your application does not meet all four criteria, read on.
The enableWebAudio method on DefaultDeviceController would produce unexpected results if
called after the first audio device was selected, and as a synchronous API it was not possible
to reimplement it to behave correctly.
Additionally, it was not documented how the API should behave if Web Audio were to be disabled
while in use, or how it should be implemented correctly by other DeviceController classes.
This API method has been removed entirely, along with the corresponding field on
MeetingSessionConfiguration. The MeetingSession will no longer call enableWebAudio on the
corresponding DeviceController.
Applications should instead use the constructor argument added to
DefaultDeviceConfiguration to enable Web Audio at point of construction.
If your code looked like this:
const configuration = new MeetingSessionConfiguration(…);
configuration.enableWebAudio = true;
…
const deviceController = new DefaultDeviceController(logger);
this.meetingSession = new DefaultMeetingSession(configuration, logger, deviceController);
this.audioVideo = this.meetingSession.audioVideo;
change it to
const configuration = new MeetingSessionConfiguration(…);
…
const deviceController = new DefaultDeviceController(logger, { enableWebAudio: true });
this.meetingSession = new DefaultMeetingSession(configuration, logger, deviceController);
this.audioVideo = this.meetingSession.audioVideo;
If your code looked like this:
const configuration = new MeetingSessionConfiguration(…);
…
const deviceController = new DefaultDeviceController(logger);
this.meetingSession = new DefaultMeetingSession(configuration, logger, deviceController);
this.audioVideo = this.meetingSession.audioVideo;
…
const enableWebAudio = await checkWhetherWebAudioNeeded();
deviceController.enableWebAudio(enableWebAudio);
change it to
const configuration = new MeetingSessionConfiguration(…);
// …const enableWebAudio = await checkWhetherWebAudioNeeded();
const deviceController = new DefaultDeviceController(logger, { enableWebAudio });
this.meetingSession = new DefaultMeetingSession(configuration, logger, deviceController);
this.audioVideo = this.meetingSession.audioVideo;
…
The bindAudioElement() API in AudioMixControllerFacade was previously a synchronous function which used to return boolean.
Under the hood, it used to call setSinkId()
which is an asynchronous function.
As part of this change, three APIs in AudioMixController were changed to return Promise<void>. These APIs are listed below.
Additionally, AudioMixController's constructor now takes an additional optional logger parameter.
If the logger is passed, it will log the errors for any of the operations in AudioMixController.
Additionally, if the browser does not support setSinkId() API, the bindAudioDevice() will throw an
error with a message 'Cannot select audio output device. This browser does not support setSinkId.'
Check https://caniuse.com/?search=setSinkId for the setSinkId browser support.
These two types describe DeviceController's methods for selecting audio and
video inputs respectively. They both include the space of Devices, which are the 'intrinsic'
device kinds provided by the browser: identifiers, constraints, and streams. AudioInputDevice
extends these by adding the concept of an AudioTransformDevice, which can rewrite an inner
device on request, and optionally provide an arbitrary Web Audio graph to use as an additional
transformation pipeline.
You can use AudioTransformDevice to implement effects such as reverb, gain, etc.
Because chooseAudioInputDevice and chooseVideoInputDevice now have new type signatures, if
you implement the related interfaces (AudioVideoFacade or DeviceController) yourself, you will need to adjust your code.
If you have an implementation like:
classMyDeviceControllerimplementsDeviceController{
async chooseAudioInputDevice(device: Device): Promise<void> {
// device must be a string, stream, constraints, or null.// …return permission;
}
}
you must change your code to be:
import {
// …
isAudioTransformDevice,
} from'amazon-chime-sdk-js';
classMyDeviceControllerimplementsDeviceController{
async chooseAudioInputDevice(device: AudioInputDevice): Promise<void> {
if (isAudioTransformDevice(device)) {
// Handle transform devices, should you need to.thrownewError('My app does not use transform devices.');
}
// Previous code can remain unchanged.// …
}
}
A similar adjustment is needed for VideoInputDevice. v2.0 does not include any
VideoTransformDevices.
If you use the type Device for a field or variable and pass that value to
choose{Audio,Video}InputDevice, your code should continue to work without changes.
v2.0 introduces new error types which will be thrown in case of any failures in chooseAudioInputDevice and chooseVideoInputDevice APIs in the DeviceController.
Here is the list of new error classes introduced in version 2.0:
GetUserMediaError
NotFoundError
NotReadableError
OverconstrainedError
PermissionDeniedError
TypeError
Here is an example of handling PermissionDeniedError:
try {
awaitthis.audiovideo.chooseAudioInputDevice(device);
} catch (e) {
if (e instanceof PermissionDeniedError) {
console.error('Permission denied', e);
}
}
This new helper API returns a boolean true if the browser supports setSinkId(), otherwise returning false.
Here is how the code would look like:
if (!this.browserBehavior.supportsSetSinkId()) {
thrownewError(
'Cannot select audio output device. This browser does not support setSinkId.'
);
} else {
console.log('The browser supports setSinkId() API');
}
From version 2.0 onwards, the Amazon Chime SDK for JavaScript will no longer include the deprecated screen share API identified by ScreenShareFacade and ScreenShareViewFacade and all related code.
Customers should use our Video Based Content Sharing detailed in our Content Share guide.
Migration from SDK v1 to SDK v2
Installation
Installation involves adjusting your
package.json
to depend on version2.0.0
.Interface changes
Version 2 of the Amazon Chime SDK for JavaScript makes a small number of interface changes, as well as removing some deprecated interfaces.
In many cases you should not need to adjust your application code at all. This will be the case if:
AudioVideoFacade
orDeviceController
yourself.enableWebAudio
on any instances ofDeviceController
orAudioVideoFacade
, or use theMeetingSessionConfiguration
fieldenableWebAudio
.chooseAudioInputDevice
withcatch
.bindAudio*
methods onAudioMixController
.If your application does not meet all four criteria, read on.
Removing
enableWebAudio
The
enableWebAudio
method onDefaultDeviceController
would produce unexpected results if called after the first audio device was selected, and as a synchronous API it was not possible to reimplement it to behave correctly.Additionally, it was not documented how the API should behave if Web Audio were to be disabled while in use, or how it should be implemented correctly by other
DeviceController
classes.This API method has been removed entirely, along with the corresponding field on
MeetingSessionConfiguration
. TheMeetingSession
will no longer callenableWebAudio
on the correspondingDeviceController
.Applications should instead use the constructor argument added to
DefaultDeviceConfiguration
to enable Web Audio at point of construction.If your code looked like this:
const configuration = new MeetingSessionConfiguration(…); configuration.enableWebAudio = true; … const deviceController = new DefaultDeviceController(logger); this.meetingSession = new DefaultMeetingSession(configuration, logger, deviceController); this.audioVideo = this.meetingSession.audioVideo;
change it to
const configuration = new MeetingSessionConfiguration(…); … const deviceController = new DefaultDeviceController(logger, { enableWebAudio: true }); this.meetingSession = new DefaultMeetingSession(configuration, logger, deviceController); this.audioVideo = this.meetingSession.audioVideo;
If your code looked like this:
const configuration = new MeetingSessionConfiguration(…); … const deviceController = new DefaultDeviceController(logger); this.meetingSession = new DefaultMeetingSession(configuration, logger, deviceController); this.audioVideo = this.meetingSession.audioVideo; … const enableWebAudio = await checkWhetherWebAudioNeeded(); deviceController.enableWebAudio(enableWebAudio);
change it to
const configuration = new MeetingSessionConfiguration(…); // … const enableWebAudio = await checkWhetherWebAudioNeeded(); const deviceController = new DefaultDeviceController(logger, { enableWebAudio }); this.meetingSession = new DefaultMeetingSession(configuration, logger, deviceController); this.audioVideo = this.meetingSession.audioVideo; …
Update
bindAudioElement()
,bindAudioStream()
andbindAudioDevice()
to returnPromise<void>
instead ofboolean
The
bindAudioElement()
API inAudioMixControllerFacade
was previously a synchronous function which used to returnboolean
. Under the hood, it used to callsetSinkId()
which is an asynchronous function.As part of this change, three APIs in
AudioMixController
were changed to returnPromise<void>
. These APIs are listed below.// Old Syntax bindAudioElement(element: HTMLAudioElement): boolean; bindAudioStream(stream: MediaStream): boolean; bindAudioDevice(device: MediaDeviceInfo | null): boolean; // New Syntax bindAudioElement(element: HTMLAudioElement): Promise<void>; bindAudioStream(stream: MediaStream): Promise<void>; bindAudioDevice(device: MediaDeviceInfo | null): Promise<void>;
Additionally,
AudioMixController
's constructor now takes an additional optionallogger
parameter. If thelogger
is passed, it will log the errors for any of the operations inAudioMixController
.constructor(private logger?: Logger) {}
If your code looked like this
audioMixController.bindAudioDevice({ deviceId: sinkId }); audioMixController.bindAudioElement(new Audio()); audioMixController.bindAudioStream(destinationStream.stream);
change it to
try { await audioMixController.bindAudioDevice({ deviceId: this.sinkId }); } catch (e) { console.error('Failed to bind audio device', e); } try { await audioMixController.bindAudioElement(new Audio()); } catch (e) { console.error('Failed to bind audio element', e); } await audioMixController.bindAudioStream(destinationStream.stream);
Additionally, if the browser does not support
setSinkId()
API, thebindAudioDevice()
will throw an error with a message 'Cannot select audio output device. This browser does not support setSinkId.' Check https://caniuse.com/?search=setSinkId for the setSinkId browser support.Introducing
AudioInputDevice
andVideoInputDevice
These two types describe
DeviceController
's methods for selecting audio and video inputs respectively. They both include the space ofDevice
s, which are the 'intrinsic' device kinds provided by the browser: identifiers, constraints, and streams.AudioInputDevice
extends these by adding the concept of anAudioTransformDevice
, which can rewrite an inner device on request, and optionally provide an arbitrary Web Audio graph to use as an additional transformation pipeline.You can use
AudioTransformDevice
to implement effects such as reverb, gain, etc.Because
chooseAudioInputDevice
andchooseVideoInputDevice
now have new type signatures, if you implement the related interfaces (AudioVideoFacade
orDeviceController
) yourself, you will need to adjust your code.If you have an implementation like:
class MyDeviceController implements DeviceController { async chooseAudioInputDevice(device: Device): Promise<void> { // device must be a string, stream, constraints, or null. // … return permission; } }
you must change your code to be:
import { // … isAudioTransformDevice, } from 'amazon-chime-sdk-js'; class MyDeviceController implements DeviceController { async chooseAudioInputDevice(device: AudioInputDevice): Promise<void> { if (isAudioTransformDevice(device)) { // Handle transform devices, should you need to. throw new Error('My app does not use transform devices.'); } // Previous code can remain unchanged. // … } }
A similar adjustment is needed for
VideoInputDevice
. v2.0 does not include anyVideoTransformDevice
s.If you use the type
Device
for a field or variable and pass that value tochoose{Audio,Video}InputDevice
, your code should continue to work without changes.Introducing the
GetUserMediaError
typev2.0 introduces new error types which will be thrown in case of any failures in
chooseAudioInputDevice
andchooseVideoInputDevice
APIs in theDeviceController
.Here is the list of new error classes introduced in version 2.0:
GetUserMediaError
NotFoundError
NotReadableError
OverconstrainedError
PermissionDeniedError
TypeError
Here is an example of handling
PermissionDeniedError
:try { await this.audiovideo.chooseAudioInputDevice(device); } catch (e) { if (e instanceof PermissionDeniedError) { console.error('Permission denied', e); } }
Introducing
supportsSetSinkId()
inDefaultBrowserBehavior
This new helper API returns a boolean
true
if the browser supportssetSinkId()
, otherwise returningfalse
.Here is how the code would look like:
if (!this.browserBehavior.supportsSetSinkId()) { throw new Error( 'Cannot select audio output device. This browser does not support setSinkId.' ); } else { console.log('The browser supports setSinkId() API'); }
Deprecating legacy screen share
From version 2.0 onwards, the Amazon Chime SDK for JavaScript will no longer include the deprecated screen share API identified by
ScreenShareFacade
andScreenShareViewFacade
and all related code. Customers should use our Video Based Content Sharing detailed in our Content Share guide.Give feedback on this guide


Uses of Package
org.drip.spline.params
| Package | Description |
|---|---|
| org.drip.dynamics.lmm |
LMM Based Latent State Evolution
|
| org.drip.exposure.regression |
Regression Based Path Exposure Generation
|
| org.drip.sample.dual |
G7 Standard Cross Currency Swap
|
| org.drip.sample.forward |
IBOR Spline Forward Curve Construction
|
| org.drip.service.template |
Curve Construction Product Builder Templates
|
| org.drip.spline.multidimensional |
Multi-dimensional Wire Surface Stretch
|
| org.drip.spline.params |
Spline Segment Construction Control Parameters
|
| org.drip.spline.pchip |
Monotone Convex Themed PCHIP Splines
|
| org.drip.spline.segment |
Flexure Penalizing Best Fit Segment
|
| org.drip.spline.stretch |
Multi-Segment Sequence Spline Stretch
|
| org.drip.state.creator |
Scenario State Curve/Surface Builders
|
| org.drip.state.curve |
Basis Spline Based Latent States
|
| org.drip.state.estimator |
Multi-Pass Customized Stretch Curve
|
| org.drip.state.inference |
Latent State Stretch Sequence Inference
|
| org.drip.xva.settings |
XVA Group and Path Settings
|
-
Classes in org.drip.spline.params used by org.drip.dynamics.lmm Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment. -
Classes in org.drip.spline.params used by org.drip.exposure.regression Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment. -
Classes in org.drip.spline.params used by org.drip.sample.dual Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment. -
Classes in org.drip.spline.params used by org.drip.sample.forward Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment. -
Classes in org.drip.spline.params used by org.drip.service.template Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment. -
Classes in org.drip.spline.params used by org.drip.spline.multidimensional Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment. -
Classes in org.drip.spline.params used by org.drip.spline.params Class Description PreceedingManifestSensitivityControl PreceedingManifestSensitivityControl provides the control parameters that determine the behavior of non local manifest sensitivity.ResponseScalingShapeControl ResponseScalingShapeControl implements the segment level basis functions proportional adjustment to achieve the desired shape behavior of the response.SegmentBasisFlexureConstraint SegmentBasisFlexureConstraint holds the set of fields needed to characterize a single local linear Constraint, expressed linearly as a combination of the local Predictor Ordinates and their corresponding Response Basis Function Realizations.SegmentBestFitResponse SegmentBestFitResponse implements basis per-segment Fitness Penalty Parameter Set.SegmentFlexurePenaltyControl SegmentFlexurePenaltyControl implements basis per-segment Flexure Penalty Parameter Set.SegmentInelasticDesignControl SegmentInelasticDesignControl implements basis per-segment inelastic parameter set.SegmentPredictorResponseDerivative SegmentPredictorResponseDerivative contains the segment local parameters used for the segment calibration.SegmentResponseValueConstraint SegmentResponseValueConstraint holds the following set of fields that characterize a single global linear constraint between the predictor and the response variables within a single segment, expressed linearly across the constituent nodes.StretchBestFitResponse StretchBestFitResponse implements basis per-Stretch Fitness Penalty Parameter Set. -
Classes in org.drip.spline.params used by org.drip.spline.pchip Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment.StretchBestFitResponse StretchBestFitResponse implements basis per-Stretch Fitness Penalty Parameter Set. -
Classes in org.drip.spline.params used by org.drip.spline.segment Class Description PreceedingManifestSensitivityControl PreceedingManifestSensitivityControl provides the control parameters that determine the behavior of non local manifest sensitivity.ResponseScalingShapeControl ResponseScalingShapeControl implements the segment level basis functions proportional adjustment to achieve the desired shape behavior of the response.SegmentBasisFlexureConstraint SegmentBasisFlexureConstraint holds the set of fields needed to characterize a single local linear Constraint, expressed linearly as a combination of the local Predictor Ordinates and their corresponding Response Basis Function Realizations.SegmentBestFitResponse SegmentBestFitResponse implements basis per-segment Fitness Penalty Parameter Set.SegmentFlexurePenaltyControl SegmentFlexurePenaltyControl implements basis per-segment Flexure Penalty Parameter Set.SegmentInelasticDesignControl SegmentInelasticDesignControl implements basis per-segment inelastic parameter set.SegmentResponseValueConstraint SegmentResponseValueConstraint holds the following set of fields that characterize a single global linear constraint between the predictor and the response variables within a single segment, expressed linearly across the constituent nodes.SegmentStateCalibrationInputs SegmentStateCalibrationInputs implements basis per-segment Calibration Parameter Input Set. -
Classes in org.drip.spline.params used by org.drip.spline.stretch Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment.SegmentPredictorResponseDerivative SegmentPredictorResponseDerivative contains the segment local parameters used for the segment calibration.SegmentResponseValueConstraint SegmentResponseValueConstraint holds the following set of fields that characterize a single global linear constraint between the predictor and the response variables within a single segment, expressed linearly across the constituent nodes.StretchBestFitResponse StretchBestFitResponse implements basis per-Stretch Fitness Penalty Parameter Set. -
Classes in org.drip.spline.params used by org.drip.state.creator Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment.SegmentInelasticDesignControl SegmentInelasticDesignControl implements basis per-segment inelastic parameter set. -
Classes in org.drip.spline.params used by org.drip.state.curve Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment. -
Classes in org.drip.spline.params used by org.drip.state.estimator Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment.StretchBestFitResponse StretchBestFitResponse implements basis per-Stretch Fitness Penalty Parameter Set. -
Classes in org.drip.spline.params used by org.drip.state.inference Class Description PreceedingManifestSensitivityControl PreceedingManifestSensitivityControl provides the control parameters that determine the behavior of non local manifest sensitivity.SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment.StretchBestFitResponse StretchBestFitResponse implements basis per-Stretch Fitness Penalty Parameter Set. -
Classes in org.drip.spline.params used by org.drip.xva.settings Class Description SegmentCustomBuilderControl SegmentCustomBuilderControl holds the parameters the guide the creation/behavior of the segment.


Dan Lockton, David Harrison, Neville A. Stanton
This defines a set of stimulating cards intended for design teams in the 'concept generation stage'. This paper uses the example of a "Human Technology" interaction problem - 'reducing the likelihood of a customer leaving his or her card in an automatic teller machine'.
Altshuller, G 1996, regarding TRIZ - a set of transformative concepts applied to existing designs to 'manufacture' innovations [toread]


WITNESS LIST
Criminal Justice
May 17, 2016 1:30 PM
Interim Charge 3
ON:
Berry, Traci Sr. VP Community Engagement and Education (Goodwill Central Texas),
Austin, TX
Carpenter, Dr. Clint Superintendent (Windham School District), Huntsville, TX
Collier, Bryan Deputy Executive Director (Texas Department of Criminal Justice),
Huntsville, TX
Ita, Trina Director of Program Services Section II MHSA Division (Department of State
Health Services), Austin, TX
Ligon, Katharine Mental Health Policy Analyst (also providing written testimony) (Center
For Public Policy Priorities), Austin, TX
Zamora, April Director of Reentry and Integration (Texas Department of Criminal Justice),
Austin, TX
Providing written testimony:
ON:
Smith, Douglas Policy Analyst (Texas Criminal Justice Coalition), Austin, TX
Interim Charge 4
FOR:
Rodriguez, Gerald President (Texas Association of Pretrial Services), Austin, TX
ON:
Braddock, Kathy Chief of Staff (Harris County District Attorney), Houston, TX
Edmonds, Shannon Director of Government relations (Texas District and County Attorneys
Association), Austin, TX
Lozito, Michael Judicial Services Director (Bexar County), San Antonio, TX
Magnis, Rick Judge (Dallas County Felony Courts), Dallas, TX
Wagner, B.J. Director of Smart Justice (Meadows Mental Health Policy Institute), Dallas,
TX
Yoo, Tina Judge (Dallas County Criminal Case), Dallas, TX
Young, Michael Chief Public Defender (also providing written testimony) (Bexar County
Public Defender's Office), San Antonio, TX
Registering, but not testifying:
ON:
Gerrick, Emily Staff Attorney (Texas Fair Defense Project), Austin, TX
Providing written testimony:
ON:
Jenkins, Jay Project Attorney (Texas Criminal Justice Coalition), Austin, TX
Interim Charge 5
AGAINST:
Bastie, Patiricia (Self), Dallas, TX
Coffey, Michael President (Imperative Information Group), Ft. Worth, TX
ON:
Burton, John (Lexis Nexis), Atlanta, GA
Doggett, Robert Executive Director (Texas Family Council), Austin, TX
WITNESS LIST
Criminal Justice
May 17, 2016 1:30 PM
Ellman, Eric Senior Vice President (Consumer data Industry Association), Washington, DC
Lemens, Chris General Counsel (General Information Services), Dallas, TX
Wouldfin, Sheri Tom Green County District Clerk (County and District Clerk's
Association), San Angelo, TX
Providing written testimony:
ON:
Henneke, Elizabeth Policy Analyst (Texas Criminal Justice Coalition), Austin, TX
Interim Charge 6
ON:
Erschabeck, Jennifer Executive Director (also providing written testimony) (Texas Inmate
Families Association), Austin, TX
Rowe, Kelly Sheriff (Sheriff, Lubbock County), Lubbock, TX
Providing written testimony:
ON:
Collier, Bryan Deputy Executive Director (Texas Department of Criminal Justice),
Huntsville, TX
Freeman, Kathryn Director of Public Policy (Texas Baptist Christian Life Commission),
Austin, TX
Jenkins, Jay Project Attoney (Texas Criminal Justice Coalition), Austin, TX


Google, Microsoft, and Amazon, who invest millions in attracting and retaining scarce talent, are looking for automated ways to deal with a shortage of AI experts. In that search, they are developing intelligent machines that can replicate themselves to perform tasks of varying complexity. This out-of-the-box approach to the shortage of talent is a positive step for millions of businesses around the world that will benefit from the democratization of advanced technologies.
About 10,000 people across the world have the education, experience, and talent needed to build complex, mathematical algorithms that are key to building AI-based technology. No more than a few thousand companies have the right talent for building AI, but many more have the necessary data.
The shortage of talents is leading to concerns about the ability of smaller incumbents to make any headway into the monopoly created by big firms.
Companies are investing heavily in AI technology research & development that can circumvent the difficulty of building AI products that are meant to do smaller tasks (image/speech recognition tools, online chatbots).
Alongside the offerings from bigger firms, boutique firms offer customizable versions of these technologies that allow small enterprises to adopt AI-powered tools.
Researchers at these firms are also working on AI systems that reduce dependence on human labor. Google’s AutoML is targeted at producing computer algorithms that are programmed to run certain tasks based on data analyses that don’t require human intervention. Google’s AutoML will put this complex technology into the hands of businesses without extensive expertise in AI. This project by Google will help companies build systems with AI even if they don’t have extensive expertise.
Read more on Tech Wire Asia + the New York Times on how large tech companies are building AI that can build AI and explanation of a particular example with driverless AI stack by H2O.ai.
Driverless AI really is able to create and train good ML models without requiring ML expertise from users.
Not only do tech corporations fund their own initiatives but they also partner with other tech companies to democratize AI/ML. While the monopoly theme will inevitably come up at some point in the future, at the moment, those initiatives define the future of business efficiency and innovation adoption opportunities across industries and businesses of a great variety of sizes.
Microsoft and AWS have collaborated to democratize deep learning and AI. Gluon is a joint effort between Microsoft Research and Amazon AI and is intended to make developing solutions using ML easier and quicker.
Gluon is an open-source deep learning and neural network solution that is exposed through a Python-based API. It comes with prebuilt neural network components that can be created on the fly and used to train algorithms making it easier to define, debug, iterate and reuse components.
Gluon improves computational efficiency by providing a mechanism to schedule and automatically distribute models across multiple GPUs.
The specifications for Gluon have been published to allow developers and organizations using other deep learning frameworks to take advantage of it.
Google is not currently part of the group supporting Gluon, so there is no timeframe for support of TensorFlow, the AI framework that Google open-sourced in 2015.
This is the second time that Amazon and Microsoft have announced a collaboration on AI. In August, they spoke on the support being built into their own digital assistants to be able to work with each other. With this collaboration, Microsoft’s Cortana can leverage the retail knowledge of Amazon’s Alexa, whilst Alexa is able to leverage the productivity features of Cortana.
Read more on InfoQ.
Follow us on Twitter, LinkedIn, Facebook, and Medium, to get the latest insights and most important industry updates!


Weekly Workshops
Learn web development on campus at our Thursday night workshops.
You'll learn at your own pace and we'll provide the resources to help you do it.
--- title: Workshops - HackBU layout: default description: Learn web development at Binghamton University with weekly workshops. ---
Learn web development on campus at our Thursday night workshops.
You'll learn at your own pace and we'll provide the resources to help you do it.
We're held a campus-wide contest in the spring 2014 semester and gave away two great prize packs — one from a student with prior experience, one without — to the students that created the best portfolios.
Each prize pack included:
The two best portfolios were created by Tyler Constance and Brian Barrett and chosen by three local web and media professionals.
Come to one of our Thursday night workshops and learn how to create websites!
We've wrapped up our Spring 2014 workshops. Slides from presentations can be found online.
In the meantime, we highly recommend Dash for learning HTML and CSS! A complete list of websites can be found on our resources page. Feel free to contact us with questions!


Sunny Boy Cereal is a porridge or hot cereal made of wheat, rye, and flax, produced in Camrose, Alberta, Canada. Two variations of the cereal are now available - regular and organic. Sunny Boy Cereal is often consumed with the addition of brown sugar and cream. It is also used in many recipes, including Sunny Boy muffins.
The makers of Sunny Boy Cereal produce a variety of other products as well including conventional and organic flours, pancake mixes and additional grain based food products.
History
- 1926
- Two brothers, Walter and Edgar Byers move to Camrose, AB. from Nova Scotia and start Byers Flour Mills.<!-- Deleted image removed:
Byers Flour Mills 1930's Recipe Book Cover
-->
- 1929
- Byers Flour Mills develops a new hot cereal using locally grown wheat, rye and flax. They call it Sunny Boy Cereal.
- 1991
- Byers Flour Mills is sold to the Alberta Wheat Pool and the plant operates under the name "Prairie Sun Grains".
- 1998
- The Alberta Wheat Pool merges with the Manitoba Wheat Pool to form Agricore Cooperative Ltd.
- 2000
- Agricore sells the Prairie Sun Grain and Sunny Boy brands to Calgary food broker Pat Maloney. The sale does not include the mill but Maloney will continue to use the facility until a new mill owner is found.
- 2003
- In June, Prairie Sun Grains 2000 Ltd. and Camrose Milling Company Inc. are placed in receivership.
- 2003
- New owners Jim, Elmer, Larry and Randy Schroeder take possession of the Camrose mill and Sunny Boy brand in December. Company operates under the name Schroeder Milling Ltd.
- 2007
- Patricia and Brad Shapka purchase the Sunny Boy brand and the Camrose mill. Sunny Boy Foods Ltd. of Edmonton is created.
Packaging
Over the years, packaging of Sunny Boy Cereal for retail sales has evolved.<!-- Deleted image removed:
Sunny Boy Cereal Packaging - 1929 to present.
-->
The original iconic cardboard box was updated when it became necessary to show both imperial and metric weights on all packaging and again when imperial weights from packaging were removed completely. Eventually cardboard boxes were replaced by resealable plastic pouches.
External links


ASLayoutSpec Class Reference
| Inherits from | NSObject |
|---|---|
| Conforms to | ASLayoutElement |
| Declared in | ASLayoutSpec.h |
isMutable
Creation of a layout spec should only happen by a user in layoutSpecThatFits:. During that method, a layout spec can be created and mutated. Once it is passed back to ASDK, the isMutable flag will be set to NO and any further mutations will cause an assert.
@property (nonatomic, assign) BOOL isMutable
Declared In
ASLayoutSpec.h
parent
Parent of the layout spec
@property (nullable, nonatomic, weak) id<ASLayoutElement> parent
Declared In
ASLayoutSpec.h
child
Adds a child to this layout spec using a default identifier.
@property (nullable, strong, nonatomic) id<ASLayoutElement> child
Parameters
child |
A child to be added. |
|---|
Discussion
Every ASLayoutSpec must act on at least one child. The ASLayoutSpec base class takes the responsibility of holding on to the spec children. Some layout specs, like ASInsetLayoutSpec, only require a single child.
For layout specs that require a known number of children (ASBackgroundLayoutSpec, for example) a subclass should use this method to set the “primary” child. It can then use setChild:forIdentifier: to set any other required children. Ideally a subclass would hide this from the user, and use the setChild:forIdentifier: internally. For example, ASBackgroundLayoutSpec exposes a backgroundChild property that behind the scenes is calling setChild:forIdentifier:.
Declared In
ASLayoutSpec.h
children
Adds childen to this layout spec.
@property (nullable, strong, nonatomic) NSArray<id<ASLayoutElement> > *children
Parameters
children |
An array of ASLayoutElement children to be added. |
|---|
Discussion
Every ASLayoutSpec must act on at least one child. The ASLayoutSpec base class takes the reponsibility of holding on to the spec children. Some layout specs, like ASStackLayoutSpec, can take an unknown number of children. In this case, the this method should be used. For good measure, in these layout specs it probably makes sense to define setChild: and setChild:forIdentifier: methods to do something appropriate or to assert.
Declared In
ASLayoutSpec.h


This diagram illustrates two block boxes, one above the other, with rectangular clipping regions of different dimensions.
 A coordinate system has its origin at the upper left corner of each block box. The x-axis increases along the top edge of the P box, the y-axis down the left edge. Both axes depict increments of 5px.
The clipping region of the first P box lies entirely within it, offset 5px from the top and left edges of the P box, and 10px from the right and bottom edges. The clipping region has a thick dashed border and a white background and is labeled "clip region".
The clipping region of the second P box resembles that of the first in style and position, except that the right edge is 5px to the right of the P box's right edge. Thus, the clipping region lies partially outside the P box.
Both block boxes have four red arrows representing the four offsets in the corresponding style rule: one short, vertical arrow labeled "top" goes from the top edge of the block box to the top of the clipping region; one longer vertical arrow labeled "bottom" goes from the top op the block box to the bottom of the clipping region; one short, horizontal arrow labeled "left" goes from the left edge of the block to the left edge of the clipping region; and one longer horizontal arrow labeled "right" goes from the left edge of the block to the right edge of the clipping region.


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