--- layout: page ---
| Location | Contact Info |
|---|---|
| 🏫 Office: Monroe Hall Rm 437 | 📞 Phone:<PHONE_NUMBER> |
| 🕟 Office Hours: By appointment | ✉ Email<EMAIL_ADDRESS>|
This course provides students with a view into the job of a software engineer through hands-on interaction with course material. Topics covered include engineering processes and their application to the development of software; cost and effort estimation; software testing and test management; team structure, roles and composition; deployment and configuration management; and professional ethics.
COSC A315 Computer Organization or COSC A317 Data Structures or Instructor Approval.
Students will experience the job of a software engineer through hands-on interaction with course material. The course will provide students with opportunities to experience: engineering processes and their application to the development of software; cost and effort estimation; software testing and test management; team structure, roles and composition; deployment and configuration management; and professional ethics.
Upon completion of this course, students should be able to:
📗 Engineering Software as a Service: An Agile Approach Using Cloud Computing, 1st Edition (v1.2.1), by Armando Fox and David Patterson. Strawberry Canyon, 2016. ISBN 978-0-9848812-4-6. Companion website for students: http://www.saasbook.info/students.
📘 The Mythical Man-Month: Essays on Software Engineering, Anniversary Edition (2nd Ed.), by Frederick P. Brooks, Jr. Addison-Wesley Professional, 1995. ISBN 978-0-2018359-5-3.
In this course, you will build and deploy real software using the processes, practices, and ideas you're learning about. The course project is a large effort that will be completed as a team.
The project will be a web application, and will be built with Ruby and JavaScript using the Rails web framework. Project, requirement, code and code review artifacts will be managed via GitHub using the git version control system.
As with any major software development effort, you will be expected to work independently and as a team outside the classroom in order to complete this project. You will be expected to coordinate with classmates on your own in order to facilitate team collaborative work outside of class.
We will discuss the project beginning in Week 3, plan our first development iteration (or sprint) at the end of that week, and begin development immediately afterward. In total, the project will cover four (4) three-week sprints, scheduled as follows:
Each sprint will begin during the class period with a planning session. During this session, you will, as a team, estimate the development effort required for requirements and decide on a subset of requirements you will implement during the iteration. As a team, you will commit to completing these requirements entirely by the end of the iteration.
During the course of the sprint, we will begin each class period with a quick stand-up meeting. The purpose of this meeting is to identify (1) what's been done since the last stand-up; (2) what you're planning to do before the next stand-up; (3) what impediments are blocking progress on your work; and (4) what help you need from your teammates. No problem-solving will happen during this meeting -- any identified impediments or needed help will be handled in a scheduled session with your teammates outside of class.
At the close of each sprint, you, as a team, will demonstrate the software increment you built during the iteration. This demonstration should focus on the value the software increment provides to the customer/client and users of the software. You should be prepared to answer questions about what you've built and how it works.
Following the demonstration, we will engage in a retrospective session, where we will evaluate how well the development practices and process used worked, and identify ways to improve these for the next iteration. At the close of the retrospective, we will add one or more process improvement tasks to our list of requirements that must be tackled within the next iteration.
Professional software engineers encounter ethics issues frequently in the work they do. Many professional software engineers adopt a code of ethics that guides their approach to their work and helps them decide what kinds of work they are willing to do.
To experience some of this, as a final exam for this course, you will write an in-depth issue paper on a software ethics question or problem of your choice, and present your findings to the class.
You will have the entire semester to work on this paper and presentation. Thus, you will be expected to research the topic in detail, finding and presenting a detailed analysis of the various approaches, perspectives, and implications associated with the issue you have chosen. While there is no page limit, your paper will be judged on the completeness of the ideas presented (see How you will be graded below), and an extraordinarily concise treatment of an ethics issue will likely require well over 10 pages single-spaced.
During the final exam period (Thursday 12/14 from 4:30 - 6:30 PM), you will give a 15 to 20 minute presentation to the class on your findings. This presentation should describe and illustrate for your classmates the answers you found for all the analysis questions (see How you will be graded below).
We will discuss the final paper assignment in the first class period. From that time, you will have two weeks in which to select and turn in a brief (3-5 sentences) paragraph on the topic you have chosen to research. All topics will be approved by the instructor during week three (3).
In order to assist you in your topic selection and research, several resources are available to you.
Your paper and presentation must present a complete and detailed analysis of the issue you've chosen. In particular, your paper must address in detail the following analysis questions:
Your presentation must also address each of these questions in sufficient detail to give classmates a clear understanding of what you found while maintaining the interest of your audience and fitting within the allotted time period.
In addition to content, you will be graded on the correctness of your writing (spelling, grammar, punctuation, word choice, etc.), the readability and formatting of your submitted paper (font choice, margins, line length, spacing, etc.), and on your presentation skills (vocal projection, clarity of speech, appropriateness of movement, eye contact, visual aids, appropriate attire, etc.). Please be careful in your writing and practice your presentation prior to the final exam period.
The following activities will contribute to your final grade in this course:
The following calculation will be used to compute your final score in the course:
| Grade | Value | Quantity | Total |
|---|---|---|---|
| 🕟 Participation | 18% | 360 points possible | |
| Class Participation | 10 points | 30 | 300 points possible |
| Final Participation | 60 points | 1 | 60 points possible |
| 📋 Quizzes | 10% | 200 points possible | |
| Concepts Check | 20 points | 10 | 200 points possible |
| 💻 Project | 57% | 1140 points possible | |
| Weekly Contributions | 20 points | 12 | 240 points possible |
| Sprint Interim Demo | 100 points | 3 | 300 points possible |
| Retrospective | 100 points | 4 | 400 points possible |
| Final Project Demo | 200 points | 1 | 200 points possible |
| 📝 Final Issue Paper | 15% | 300 points possible | |
| Paper | 200 points | 1 | 200 points possible |
| Presentation | 100 points | 1 | 100 points possible |
| TOTAL | 100% | 2000 points possible |
The grading scale is the standard 10-point scale.
| Grade | Range |
|---|---|
| A | 93 – 100 |
| A- | 90 – 92 |
| B+ | 88 – 89 |
| B | 83 – 87 |
| B- | 80 – 82 |
| C+ | 78 – 79 |
| C | 73 – 77 |
| C- | 70 – 72 |
| D+ | 68 – 69 |
| D | 60 – 67 |
| F | 59 and below |
This is a course about being a professional. In order to do a professional job, you first have to be present. As such, attendance is required.
If there is a reason you must be absent, please arrange with the instructor in advance. Any absence not arranged with the instructor and approved in advance will result in a loss of the daily classtime participation grade. (See grading policy above.)
Please come to class on time and remain until class is dismissed.
Cell phones must be turned off during class.
Students must check their Loyola email daily.
During this course, much of your project work will be orchestrated outside of class periods using the class chat service. You will be expected to actively participate in that chat throughout the course of the project.
As a professional, if you miss a deadline, there are consequences.
For the course project, you should treat the instructor as your management. In many cases, with early notice of a delay in completion of work, project schedules can be adjusted to accomodate the delay. Managers who learn of a delay at or just before the deadline tend to perceive the employee as irresponsible, and may formally reprimand or even remove the employee from the project.
Notify the instructor as soon as you are aware of a delay in completion of project work, and you will have an opportunity to negotiate a new deadline. Be aware that dependencies in subsquent deadlines in the project schedule may prevent such an accomodation.
For all other classroom activities, late work will not be accepted, subject to the exceptions below.
The only exceptions to this classroom policy are for absences which fall under the University Excused Absence policy.
Under that policy, excused absences require written documentation. Excused Absences due to illness have to be documented through the Office of Student Affairs or the Office of Disability Services.
Failure to appropriately document such absences will result in zero points received for the assignments due during that class period, and for the daily participation grade.
In a professional setting, there are significant consequences for dishonesty and lack of integrity, including legal consequences, market reaction, and employer discipline or termination of employment.
As your instructor for this course, I have gone out of my way to ensure that you have a great opportunity to learn how professional software engineering is done. Your part in this learning effort is to do your own original work and give appropriate credit for legitimate help you have received.
In keeping with this, students are expected to maintain the highest standards of academic and professional integrity. Behavior that violates these standards is not acceptable.
Some examples of unacceptable behavior in this course are:
Cheating on quizzes or examinations, plagiarism, improper acknowledgment of sources in essays, and the use of a single essay or paper in more than one course without permission are considered very serious offenses and shall be grounds for disciplinary action as outlined in the current bulletin. Agreement between the student and the faculty member that a violation has occurred, or no response from the student, will result in the assignment of a lower grade or an F to the test or assignment, or in the case of a serious violation, a lower grade or F for the course.
Dishonesty breaks trust, and will be taken very seriously.
In this course, if I suspect you are in violation of the University policy on Academic Honesty and Plagiarism in any way, whether on required assignments, exams, project work, extra credit assignments, or anything else related to this course, I will impose the highest penalty allowed.
For your benefit, the University policy on Academic Honesty and Plagiarism is available in the 2017 University Bulletin at http://2017bulletin.loyno.edu/academic-regulations/academic-honesty-and-plagiarism, including procedures associated with processing violations of the policy. Please read it and be familiar with it, as you will be responsible for ensuring your own compliance with it.
Please maintain an atmosphere of respect toward others.
At times, ordinary university operations are interrupted as a result of tropical storms, hurricanes, or other emergencies that require evacuation or suspension of on-campus activities. To prepare for such emergencies, all students will do the following during the first week of classes:
Practice signing on for each course through Blackboard.
Provide regular and alternative e-mail address and phone contact information to each instructor.
In the event of an interruption to our course due to the result of an emergency requiring an evacuation or suspension of campus activities, students will:
Assuming a power source is available....
Further information about student responsibilities in emergencies is available on the Academic Affairs web site: http://academicaffairs.loyno.edu/students-emergency-responsibilities.
If you have a disability and wish to receive accommodations, please visit the Student Success Office in Marquette Hall 112 or email<EMAIL_ADDRESS>or call<PHONE_NUMBER>. Please note that before any accommodations can be implemented, you must obtain an official Course Accommodation Record from Disability Services for my signature.


When is The Mandalorian episode 4 on Disney Plus?
by Samuel RobertsWhen is The Mandalorian episode 4 on Disney Plus?
The Mandalorian's complete Disney Plus release schedule
(Image credit: Disney/Lucasfilm)
Here's when The Mandalorian episode 4 releases on the Disney Plus streaming service. New episodes of the show drop every Friday on Disney Plus, although the first episode released on a Tuesday, with Disney Plus. The seventh episode, too, arrives on a different day. More on that below.
You can read the official release schedule of The Mandalorian season one below. If you're stuck on watching the show, check out our guide on how to watch The Mandalorian.
When is the next episode of The Mandalorian on Disney Plus?
The next episode of The Mandalorian, episode four, releases on Disney Plus on November 29, next Friday. You'll be able to stream it then in the US, Canada, the Netherlands, Australia and New Zealand. Episode two arrived at around midnight PT, so expect this to be the targeted time for the rest of the season.
If you want to watch each new episode as soon as it arrives, be prepared to stay up late if you're in the US. It's unclear if launching in different time zones will affect when new episodes arrive.
- How to watch the Star Wars movies in order
- Don't miss our guide to Star Wars on Disney Plus
- We've broken down the Disney Plus price if you're unsure about it
When do the other episodes of The Mandalorian season one release?
They all release each Friday over the next two months, with the exception of the seventh episode, which releases on a Wednesday (it's unclear why this is). There are eight episodes in total. Here's the official confirmed release schedule from Disney:
- Episode one: Out now
- Episode two: Out now
- Episode three: Out now
- Episode four: November 29
- Episode five: December 6
- Episode six: December 13
- Episode seven: December 18
- Episode eight: December 27
When is The Mandalorian season one finale?
As explained above, the season one finale of The Mandalorian arrives on Disney Plus on December 27. Between this show, Jedi: Fallen Order and The Rise of Skywalker, you can pretty much fill this holiday season with as much Star Wars as you can possibly enjoy.
- Check out our Disney Plus guide


air-drawing 👆
Details
- Your data are not collected. This application is entirely client-side, nothing is sent to any servers.
- This tool uses Deep Learning to help you draw and write with your hand and webcam. A Deep Learning model is used to try to predict whether you want to have 'pencil up' or 'pencil down'.
- The code is optimized to run on most machines, the bottleneck may be your webcam. If your webcam is of low quality, you can try to improve the lighting of your face, this will trigger your webcam sensors faster, and possibly increase shutter speed and framerate.
- The hand detection will work poorly if part of your hand is outside of the frame.
- When drawing, try to keep your hand in this position 👆. Lowering your index finger is natural but it hinders the detection of the fingertip.


Whoops! Besides this website I don't have any previous work so here's one of my favorite shorts from vimeo. Enjoy!
Leonard in Slow Motion from Peter Livolsi on Vimeo.


Intro | Features | Unity Crash Course | API Reference | Version History
Unity Crash Course
FES offers a code-only development approach that is very unlike normal Unity development, however a very basic knowledge of Unity is still required to setup a FES project. This guide will help you get going in minutes!
If you’ve ever done anything in Unity before you will likely not need this guide at all.
Get Unity!
Download and install Unity from the Unity website. The minimum required version for FES is 2017.1.1, which is the version we’ll be using for the rest of this tutorial.
Unity is free of charge (as in beer, no credit cards, no royalities) so long as your annual income from your Unity projects (or related fundraising) is under a certain amount, a large amount at that. See the Unity website for up to date details.
When installing Unity you will be presented with a list of platforms you want to support, as well as other optional tools. You can change your installation at any time so don’t worry about making the wrong choice here. If you’re developing on a Windows machine I highly recommend you select Microsoft Visual Studio Community (free) as your C# code editor. You can use any editor you like, but with Visual Studio you will get create code completion and Debugging facilities, other Desktop platforms have similar solutions.
Create a FES Project
While setting up your first project you will require internet connectivity. Afterwards you only require internet connectivity if you want to update Unity and/or FES.
Launch Unity from your Desktop. The first time you launch Unity you will be asked to login with your account. If you do not have a Unity account yet you can create one now, or use a sign-in partner like Google or Facebook.
Once logged in you will see a list of tutorials or project templates. We’re not interested in any of these as they do not relate to how development is done for FES. Simply click New on top to start a new project.
Now select a 2D project, turn off Analytics (you can turn them on later if you want, but they’re out of scope of this guide), enter your project name and path, then click Create Project. Give Unity a few moments to create your new project.
The next screen will be your main Unity IDE screen. It may look overwhelming at first sight, but don’t worry, for FES we only need to learn a tiny subset of this IDE.
First lets add FES to this project. Click on Window->Asset Store to open up the Asset Store.
Now search for “FES Retro Game Framework”.
FES should appear on the top of the search results, you may have to scroll down a bit past the search refining options to see it.
Click on FES Retro Game Framework and you should arrive on the asset page. Scroll down a bit and you will see either an Import button if you already own FES, and Update button if a new version of FES is available, or an Add to Cart button if you have not purchased FES yet. Once ready click the Import button to proceed.
A dialog should show up now warning you that FES is a Complete Project and will overwrite your existing project settings, we very much want this, click Import.
Finally Unity will show you what files it’s about to import, leave them all selected and click Import.
Great, you now have yourself a FES project! You can now close the Asset Store window by right clicking the Asset Store tab on top. From now on you will not require internet connectivity to develop your game.
A Unity project stores all its files in an Assets
folder which you can see in the lower left corner of the IDE window. Unity projects are typically split into multiple Scenes, but for FES we only need one scene per project. To get started expand your Assets
folder, and click on the Scenes folder. FES comes with a bunch of examples including a barebones Scene called MyGame, double click MyGame now.
Now click the Play button on top of the screen and… that’s it! Your barebones FES game is running! If you don’t see the game make sure the Game tab is selected on the row just below the Play button.
From this point on you will mostly use the Unity IDE to click the Play button on and off, and view runtime logs!
Writing Code
To start writing code you can use Unity IDE to open the project in Visual Studio by clicking Assets -> Open C# Project, this option will also create the Visual Studio project if one doesn’t exist yet. You can also just double click a source file under the Assets folder (bottom left of the Unity IDE). Finally you can just directly open a source file from your project folder with any editor you like.
In this guide we’re using Visual Studio. Using the Visual Studio Solution Explorer expand the Assets/FES/Scripts/MyGame folder, and open the MyGame.cs file. The entire demo you saw earlier is contained in this file, have a look. For an explaintion of what is happening here please see The Game Loop.
Of course a project of any complexity would require more source files, you can add source files anywhere inside the Assets folder, so go ahead and organize your code how you like it.
Compiling Code
Compiling code is trivial! You don’t actually have to do anything, when you next click on the Unity IDE window it will scan your project for changed files and compile changed or new source files for you! If there is a compilation error it will be shown on the bottom of the Unity IDE window. Clicking the error will show the console, which may contain more details and other errors.
The console is important because it will also show you warnings and logs. You can log to the console yourself:
UnityEngine.Debug.Log("Hi there!");
It gets even better! Double-clicking any log line or compilation error will take you directly to that line of code in your code editor, granted that your code editor supports this level of integration.
Adding Resources
Adding resources is also very trivial. Simply put your images, sounds, music, and even tmx tilemaps into any folder in your project that descends from a folder named Resources
. The Resources
folder must itself be somewhere under the Assets
folder.
MyGame example has its sprite sheet located at Assets/FES/Resources/Demos/MyGame/MySprites.png
.
As with source file compilation any resource changes are automatically picked up by Unity next time the Unity IDE window is in focus. It’s worth noting that in a typical Unity application the user will want to edit specific resource import settings, but FES takes care of all of that for you, so you do not have to do anything else!
Debugging
Unity supports live debugging, which works great with Visual Studio, and some other editors. Simply set your breakpoints in your code editor, and attach to the Unity process. You may also attach to the Unity process before you press the Play button, which is great for setting breakpoints in your initialization code.
For Visual Studio specifically you may have to install Visual Studio Tools for Unity to debug Unity, but if you’ve installed Visual Studio via the Unity installer than you probably already have this plugin installed.
Deploying Your Game
This is where Unity really shines. Deploying your project to a wide variety of platforms is very simple! First go to File -> Build Settings.
Select your target platform. If you don’t see your platform here you may have not installed support for it, just re-run the installer and select the platform from there.
Now you can just click Build and build your game with default settings, or you can customize the build by clicking Player Settings…
From the Player Settings you can configure a myriad of options, such as game title, icons, splash screens, supported resolutions, portrait/landscape orientation (mobile), developer information, and more. For a final product you will likely want to fiddle with these settings, but meanwhile the default settings will do just fine!
Demo Cleanup
FES comes with a number of examples and optional material that you may want to remove to reduce the size of your project. You may delete any of these folders:
FES/Docs
FES/Resources
FES/Scenes
FES/Scripts/Demos
FES/Scripts/MyGame
Of course if you continue building on top of the MyGame example then make sure you move its files to somewhere else before you delete FES/Scripts/MyGame
, FES/Scenes
, and FES/Resources/MyGame
!
Other Tips
Because FES doesn’t use most of Unity IDE you may want to select the option Maximize On Play so that your game window fills more of your screen. Also notice that there is a Scale slider that can resize the game window. If this slider is not at 1x then what you’re seeing will be scaled up/down and may look distorted.
You may want to test your game on different resolutions to see how it would look. You can select an existing resolution from the drop down, or enter your own custom resolution.
You can enable a Stats overlay that will show you some performance metrics for your game, including frames per second.
From Window -> Profiler you can open the Profiler which can give you quite a bit of insight into where your game may have performance issues. I suggest reading more on the Profiler online to learn how to best get useful information out of it.
Getting More Help
Unity has another great advantage, it is extremely popular! If you run into any issues with it just search online and you’re bound to find an answer quickly!


A film review by Christopher Null Copyright 1996 Christopher Null
There's a few legendary scripts among screenwriting circles -- scripts that people would *love* to rip off, if they could figure out how: WITNESS, CHINATOWN, NETWORK.
THE ASSOCIATE is boilerplate TOOTSIE, lifting the entire plot structure from Dorothy's television world and dropping it on Wall Street, where Whoopi Goldberg finds herself forced to impersonate a man (named Cutty after Cutty Sark scotch) in order to be taken seriously.
If you want to know all about it, just rent TOOTSIE, and you'll meet the principals of THE ASSOCIATE -- the confident (Dianne Wiest), the would-be-if-I-weren't-the-same-sex lover (Bebe Neuwirth), the rival (Tim Daly), and the wacky gang who fall for the trick. And you'll see familiar scenes -- Cutty is almost exposed, Cutty evades woman on the prowl, Cutty's big finish.
Whatever. If THE ASSOCIATE were a *lot* funnier this might be forgivable, accent on might. As it is, THE ASSOCIATE is a relatively juvenile hit-and-miss affair that makes sexism look like it's just wacky hijinks. And more demerits for using stupid, not-remotely-realistic technology as a plot device.
Thank God the cast is good, with the exception of a miscast Daly (as a cutthroat Wall Street guy?). Dianne Wiest is awfully appealing in a Mrs. Claus sort-of way, and let me say right now that I see Bebe Neuwirth (you know, Frasier Crane's stodgy ex-wife) in a *completely* different light. And Goldberg... is Goldberg. If you like her, in general, you'll probably like her here, too.
Well, this is already more ink than this film deserves. Three stars on its merits; docked a half for blatant shamelessness.
RATING: **1/2
|------------------------------| \ ***** Perfection \ \ **** Good, memorable film \ \ *** Average, hits and misses \ \ ** Sub-par on many levels \ \ * Unquestionably awful \ |------------------------------|
-Christopher Null /<EMAIL_ADDRESS>/ Writer-Producer -Visit the Movie Emporium at http://www.filmcritic.com/ -and Null Set Productions at http://www.filmcritic.com/nullset.htm
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


As we prepared to enter Phase-0 of Dev Bootcamp, we we're asked to complete a variety of surveys to examine our learning style, and thinking style. I remember at the time thinking this was very unique. Never had a class told me to examine these traits about myself before we started. The test revealed that my thinking style is:
Concrete Sequential Thinkers tend to be based in reality. They process information in an ordered, sequential, linear way.
Abstract Random Thinkers organize information through reflection, and thrive in unstructured, people-oriented environments.
As I look back at this, a couple things come to mind. I have been very impressed by Dev Bootcamps structure of these first couple of weeks. It seems as though each assignment is build upon the one previous, and I have really enjoyed that. Now I see that my "concrete sequential" style of thinking really enjoys the linear structure of our challenges.
My learning style was Aural. This makes even more sense now. There have been many challenges where after reading the given articles or chapters, I do not understand it. So I search a question in Google, then eventually land on Youtube, and listen to someone teach it.
I really enjoyed reading the articles Carol Dweck on Fixed Mindset vs. Growth Mindset (I even bought the book! ...but haven't read it yet). When learning about how the “Growth intelligence mindset” means failure is launching board for new opportunity for growth and development, I thought to myself "I want that to be me!" Well, it's a lot harder in reality.
I think that the very nature of computer programming is figuring out a series of little puzzles. So far git, html, css, and now ruby have all proven to have their own set of little puzzles that I wrestle with, and become incredible frustrated by. I often times have to stop myself, step away from the computer, and try to come back to it fresh. It will be important for me to keep the "growth intelligence mindset" in the weeks to come. I need to reassure myself that learning this information is hard, and that getting stuck or failing is really just another way of learning new information.
Bye for now. I'm seeing Stevie Wonder tonight!
-Evan


WITNESS LIST
Veteran Affairs & Military Installations
April 15, 2014 12:00 PM
Interim Charge #2
ON:
Aus, Fred Executive Director (Texas Rural Water Foundation), Austin, TX
Bowie, RenEarl Assistant Director - Regulatory Services (Texas DPS), Austin, TX
Cantu, Eliseo "Al" Chair (Texas Veterans Commission), Austin, TX
Cloudt, Eric Senior Director (CPS Energy), San Antonio, TX
Davis, Rod Director - Veterans Support Office (Texas A&M University System), College
Station, TX
Deabay, Shawn Director, Veterans Employment Services (Texas Veterans Commission),
Austin, TX
Douglas, Macy Human Resources Manager (Office of the Comptroller of Public
Accounts), Austin, TX
Janek, Kyle Executive Commissioner (Health and Human Services Commission), Austin,
TX
Joseph, Zenobia C. (Self), Austin, TX
Little, Morgan CAPT USN (Ret), Chair (Texas Coalition of Veterans Organizations),
Dripping Springs, TX
McCraw, Steven Director (Texas Department of Public Safety), Austin, TX
Smith, Andre Veterans Advocate (Health and Human Services Commission), Austin, TX
Sponsier, Shandra Deputy Branch Manager (Texas National Guard), Austin, TX
Temple, Larry Executive Director (Texas Workforce Commission), Austin, TX
Torres, Miguel A. Major (Texas Military Forces), Austin, TX
Interim Charge #5
ON:
Kuntz, Jr., William Executive Director, Texas Department of Licensing and Regulation
(Texas Department of Licensing and Regulation), Austin, TX
Vickers, Kim Executive Director (Texas Commission on Law Enforcement), Austin, TX


BACKBEAT A film review by Scott Renshaw Copyright 1994 Scott Renshaw
Starring: Sheryl Lee, Stephen Dorff, Ian Hart, Gary Bakewell. Screenplay: Iain Softley, Stephen Ward & Michael Thomas. Director: Iain Softley.
In the original edition of Trivial Pursuit, there is a question which reads simply, "Who replaced Pete Best?" From the phrasing of that question, it would appear that at least one change from the original lineup of The Beatles is assumed to be part of the popular consciousness. That probably is not the case for the true story behind BACKBEAT, which dramatizes the pre-Fab days when they were in fact a fivesome. It is an intriguing and atmospheric study of a complicated romantic triangle, but it lacks solid performances across the board to back up Ian Hart's dynamic work as John Lennon.
BACKBEAT opens in 1960, as Liverpool mates John Lennon (Hart) and Stu Sutcliffe (Stephen Dorff) prepare to take their band The Beatles to bigger and better things, which includes moving to Hamburg to take advantage of the thriving club scene. Stu is more interested in his painting, but he joins John, Paul (Gary Bakewell), George (Chris O'Neill) and Pete (Scot Williams) in Germany to follow up strippers in darkened pubs. There Stu meets Astrid Kirchherr (Sheryl Lee), a bohemian photographer who introduces him to another side of Hamburg. As they become closer, tensions rise within the band. Paul questions Stu's talent and dedication, and John seems jealous ... although of whom is not entirely clear.
Director and co-writer Iain Softley has a unique perspective from which to tell the story of The Beatles' rise from ragged cover band to international icons, so BACKBEAT never becomes simply an "early years" bio-pic. It does boast some clever music numbers which highlight the band's frustration with their seedy environs, and an exciting sense of place. However, it's primarily the story of two friends divided by their different passions, and the woman who brings those passions into focus. This theme is highlighted in one of the film's best sequences, when Stu plays hooky from a recording session to spend the day with Astrid, as Softley cross-cuts between the ever rowdier session and Stu's idyllic encounter. Both parties are exactly where they want to be, and much of the conflict in BACKBEAT comes from John's frustration that for Stu, The Beatles are not that place.
Still, BACKBEAT could have been much, much stronger with some better acting in two of the three lead performances. It's certainly not the fault of Ian Hart, who has cornered the market on playing a homoeroticized Lennon after this film and 1991's THE HOURS AND TIMES. He seethes as a young man filled with anger and confusion and determination which can only find an acceptable outlet on stage.  His brilliance is emphasized, unfortunately, by the blandness of co-stars Stephen Dorff and Sheryl Lee. Dorff's Stu is always a bit too low-key, even when he's doing his painting, so as a dramatic character he never becomes all that interesting. Lee is appropriately mysterious, but her vampish persona goes overboard on occasion. She doesn't inject enough life into her performance to make it clear why everyone seems so fascinated by her. And sadly, Americans Dorff and Lee are both saddled with uncomfortable accents. BACKBEAT needs to feed off the conflict in this central triangle, but there's not enough spark to their interaction, and the film often plays like THE COMMITMENTS on quaaludes.
As long as the music is playing, BACKBEAT is quite good. The rest of The Beatles are played by great physical matches, particularly Gary Bakewell as a dead ringer for the young Paul. The songs are performed by an all-star band (including REM's Mike Mills, Soul Asylum's David Pirner and Nirvana's Dave Grohl) with an unrehearsed edge, and the appeal of the energetic Beatles is obvious. If only more of that energy could have carried off stage.
On the Renshaw scale of 0 to 10 gigs: 6.
-- Scott Renshaw Stanford University Office of the General Counsel
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Usage
The four main commands are
cln init
-- initialize a new projectcln prepare
-- prepare an actioncln run
-- run an actioncln remove
-- remove an action
Check the help screen for usage info:
$ cln help
Computational Lab Notebooks
cln SUBCOMMAND
CLI to help you manage a lab notbook with git and git-annex.
=== subcommands ===
init Initialize a new project
prepare Prepare an action
remove Remove a pending action
run Run an action
version print version information
help explain a given subcommand (perhaps recursively)
Initialize a new project
To initialize a new project/lab notebook use cln init
. The cln
app is a wrapper on git
and git-annex
, so your project lives in a
certain directory. That directory is the one in which you run the
cln init
command!
There is nothing magical about the cln init
command. It sets up the
required directories, makes a README.md
file, and then sets up a new
git
and git-annex
repository.
After you run cln init
, you are ready to start getting some real
work done!
Usage
To view the usage screen, run cln help init
or cln init -help
.
$ cln help init
Initialize a new project
cln init PROJECT_NAME
=== info ===
Initialize a new computational lab notebook project using git and
git-annex.
For more info, see https://mooreryan.github.io/cln_docs/
=== flags ===
[-help] print this help text and exit
(alias: -?)
Example
First make a new directory and cd
into it.
$ mkdir my_project && cd my_project
Then initialize a new project called My Project
.
$ cln init 'My Project'
Notice how I put the My Project
bit inside single quote characters
('
)? If your project name has spaces, you need to remember to quote
it!
Notes
- If you run
cln init
in a directory that already has a git repository, you will get an error.
Prepare an action
To prepare an action or command to run, use the cln prepare
command.
This creates a new action file (i.e., bash script) and a git commit
template in the <project_root>/.actions/pending
directory.
When I say "action", I just mean, something (e.g., a shell script) that will change the state of the repository (aka your lab notebook). The reason we formalize these things as actions is that it makes it a lot easier to figure out what happened in your project/repository a couple of months down the line when you come back to it.
Usage
To vier the usage screen, run cln help prepare
or cln prepare
-help
.
$ cln help prepare
Prepare an action
cln prepare ACTION
=== info ===
Generates an action file and a git commit template in the
'<project_root>/.actions/pending' directory.
For more info, see https://mooreryan.github.io/cln_docs/
=== flags ===
[-help] print this help text and exit
(alias: -?)
Example
Prepare a shell command to run:
$ cln prepare 'echo "hello, world" > hello.txt'
Rather than running echo "hello, world" > hello.txt
yourself,
"preparing" the command sets it up so that you have a way to run the
command that makes it easier to remember what you did a few
months/years down the line.
What files were created?
Action file
You have the action file (aka bash script):
$ cat .actions/pending/action__262765981__2021-04-09_14:54:48.sh
/usr/bin/echo "hello, world" > hello.txt
The first weird number in the file name is a hash code representing the contents of the file. The second is the date and time in which you prepared the command.
Commit template
And you have the git commit template.  This is really helpful for when you're going back searching through the commit logs. It will give you context of the exact command that was run connected with the exact changes it produced in any of the files included in your repository.
 Then you just have to edit the summary message and the details. For the summary, just put a short < 50 character explanation of what you did. For the details, try and put as much info and context as you will need to figure out what you did and why you did it. Basically, you should put the sort of things here that you would be putting in your lab notebook anyway.
Notes
If you try and prepare an action when there is already a pending action, you will get an error. It's set up this way to encourage you to set up a single action, run it (which then changes the state of your repository, then commit those changes to the repository. So it's like 1 action <=> 1 commit.
Run an action
To run an action, use the cln run
command.
This will look for a valid pending action, and if it finds one, runs
it with bash
. If it succeeds, then the program will also move the
action into the <project_root>/.actions/completed
directory.
- You will get an error if there are no pending actions.
- If there are more than one pending action, you will also get an error.
- The
cln prepare
command won't let you make more than one pending action. - But even if you make an extra "by-hand" with the format exactly
correct, the
cln run
command still won't let you run it if there are more than one.
Dry run
To do a "dry run", i.e., to have the cln prepare
program just tell
you what it will do without actually running any actions, you can use
the -dry-run
flag. Here is an example:
$ cln run -dry-run
You will see some useful output. Check it out and make sure it looks good. If so, then you can run the action.
While the -dry-run
is totally optional, I recommend that you do a
dry run before running the action so you can check that you haven't
made any obvious mistakes!
A note on exit codes
To determine wether an action has failed or succeeded, we check the exit codes.
- Exit code of
0
means success. - Any other exit code means failure.
Let's say that you prepared an action to run some bash script that you have written like this:
printf "Starting script!\n"
## This command will fail.
cat this_file_doesnt_exist.txt > new_file.txt
## But the script will keep going and run this, which will succeed.
printf "All done!\n"
If you ran this at the command line with bash, you would get this:
$ bash silly.sh
Starting script!
cat: this_file_doesnt_exist.txt: No such file or directory
All done!
Do you think it "succeeded"? Let's check the exit code.
$ echo $?
0
According to the exit code, yes, the script as a whole succeeded. But
if you check the contents of new_file.txt
you will see that it is
empty, which is probably not what you wanted! So what happened is
that an intermediate command failed, but given the way the script was
written, the script as a whole succeeded.
How to fix it
This is something you will want to watch out for. If this were run as
an action by cln run
, the cln
program would consider this program
a success and move the action into the completed
directory.
If you have scripts like this that run lots of commands, you should consider breaking them up. That way you stick to the one action, one commit principal mentioned above.
If you really want a multi-command bash script
In some cases, you may need more than one command, e.g., when
something only makes sense if something succeeds first. In that case,
you can join the commands with &&
. Let's try that on the previous
example.
printf "Starting script!\n" && \
cat this_file_doesnt_exist.txt > new_file.txt && \
printf "All done!\n"
And run that.
$ bash silly2.sh
Starting script!
cat: this_file_doesnt_exist.txt: No such file or directory
See how the last printf
command was not run? Let's check the exit
code again.
$ echo $?
1
That's a failing exit code. So, the cln run
program would consider
that script to have failed.
Remove an action
Sometimes you need to remove pending actions:
- You made a mistake when prepping the action.
- You don't need that action anymore.
- There was an error when running the action.
- Whatever!
The point is that you sometimes will want to delete actions! The way
that the cln
program currently works is that you can only ever have
one pending action at a time. So if you have messed something up and
need to get rid of the action, you will need to remove it. To do
this, we use the cln remove
program.
Deleting, failing, or ignoring actions
There are three ways to "remove" a pending action:
- Deleting it
- Marking it as "failed" (aka failing the action)
- Marking it as "ignored" (aka ignoring the action)
Of these three only deleting truly deletes the action data. (And even then, if you've already checked it into your git repository you will still be able to get it back.)
"Failing" an action means moving the action (and its associated git
commit template) out of the .actions/pending
directory and into the
.actions/failed
directory.
"Ignoring" an action is similar to "failing" an action except that the
pending action is moved to the .actions/ignored
directory rather
than the .actions/failed
directory.
The reason for this distinction is to help you when you're going back through your history and commit logs. I.e., it will give you more context as to why a pending action was no longer necessary.
Specifying the method
You specify the method you want to use with the -method
flag like
this
- Delete:
cln remove -method delete
- Fail:
cln remove -method fail
- Ignore:
cln remove -method ignore
Saving the results in the git repo
After you run the cln remove
command you will see some output
suggesting how to proceed. You may see something like this:
~~~ * Check which files have changed:
~~~ $ git status
~~~ * Add actions and commit templates (I know it says add--it means "track this change with git"):
~~~ $ git add .actions
~~~ * After "adding" files, commit changes:
~~~ $ git commit
As you can see, you still need to let git
know that you have moved
the actions around and commit the changes.
Manually removing actions
Like many of the cln
commands, you could just do this "by-hand".
Currently, the cln remove
command is a pretty thin wrapper around
what you would probably do by hand, but it does give you some nice
messages on what you may want to do next and it does some sanity
checking on your pending actions to make sure nothing has gotten crazy
in the meantime.


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disentanglement
Contents
1.2. disentanglement#
1.2.1. VAEs#
Some good disentangled VAE implementations are here and more general VAE implementations are here. Tensorflow implementations available here
The goal is to obtain a nice latent representation \(\mathbf z\) for our inputs \(\mathbf x\). To do this, we learn parameters \(\phi\) for the encoder \(p_\phi( \mathbf z\vert \mathbf x)\) and \(\theta\) for the decoder \(q_{\mathbf \theta} ( \mathbf x\vert \mathbf z)\). We do this with the standard vae setup, whereby a code \(z\) is sampled, using the output of the encoder (intro to VAEs here).
<IP_ADDRESS>. disentangled vae losses#
reconstruction loss |
compactness prior loss |
total correlation loss |
|---|---|---|
encourages accurate reconstruction of the input |
encourages points to be compactly placed in space |
encourages latent variables to be independent |
summarizing the losses
reconstruction loss - measures the quality of the reconstruction, the form of the loss changes based on the assumed distribution of the likelihood of each pixel
binary cross entropy loss - corresopnds to bernoulli distr., most common - doesn’t penalize (0.1, 0.2) and (0.4, 0.5) the same way, which might be problematic
mse loss - gaussian distr. - tends to focus on a fex pixels that are very wrong
l1 loss - laplace distr.
compactness prior loss
doesn’t use the extra injected latent noise
tries to push all the points to the same place
emphasises smoothness of z, using as few dimensions of z as possible, and the main axes of z to capture most of the data variability
usually assume prior is standard normal, resulting in pushing the code means to 0 and code variance to 1
we can again split this term \(\sum_i \underbrace{\text{KL} \left(p_\phi( \mathbf z_i\vert \mathbf x)\:\vert\vert\:prior(\mathbf z_i) \right)}_{\text{compactness prior loss}} = \underbrace{\sum_i I(x; z)}_{\text{mutual info}} + \underbrace{\text{KL} \left(p_\phi( \mathbf z_i)\:\vert\vert\:prior(\mathbf z_i) \right)}_{\text{factorial prior loss}}\)
total correlation loss - encourages factors to be independent
measures dependence between marginals of the latent vars
intractable (requires pass through the whole dset)
instead sample \(dec_\phi(\mathbf z\vert \mathbf x)\) and create \(\prod_j dec_\phi( \mathbf z_i\vert \mathbf x) \) by permuting across the batch dimension
now, calculate the kl with the density-ratio trick - train a classifier to approximate the ratio from these terms
<IP_ADDRESS>. disentangled vae in code#
## Reconstruction + KL divergence losses summed over all elements and batch
def loss_function(x_reconstructed, x, mu, logvar, beta=1):
'''
Params
------
x_reconstructed: torch.Tensor
Reconstructed input, with values between 0-1
x: torch.Tensor
input, values unrestricted
'''
## reconstruction loss (assuming bernoulli distr.)
## BCE = sum_i [x_rec_i * log(x_i) + (1 - x_rec_i) * log(1-x_i)]
rec_loss = F.binary_cross_entropy(x_reconstructed, x, reduction='sum')
## compactness prior loss
## 0.5 * sum(1 + log(sigma^2) - mu^2 - sigma^2)
KLD = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp())
## total correlation loss (calculate tc-vae way)
z_sample = mu + torch.randn_like(exp(0.5 * logvar))
log_pz, log_qz, log_prod_qzi, log_q_zCx = func(z_sample, mu, logvar)
## I[z;x] = KL[q(z,x)\vert\vertq(x)q(z)] = E_x[KL[q(z\vertx)\vert\vertq(z)]]
mi_loss = (log_q_zCx - log_qz).mean()
## TC[z] = KL[q(z)\vert\vert\prod_i z_i]
tc_loss = (log_qz - log_prod_qzi).mean()
## dw_kl_loss is KL[q(z)\vert\vertp(z)] instead of usual KL[q(z\vertx)\vert\vertp(z))]
dw_kl_loss = (log_prod_qzi - log_pz).mean()
return rec_loss + beta * KLD
<IP_ADDRESS>. vaes for interpretation#
<IP_ADDRESS>. various vaes#
vae (kingma & welling, 2013)
beta-vae (higgins et al. 2017) - add hyperparameter \(\beta\) to weight the compactness prior term
beta-vae H (burgess et al. 2018) - add parameter \(C\) to control the contribution of the compactness prior term
\(\overbrace{\mathbb E_{p_\phi(\mathbf z\vert \mathbf x)}}^{\text{samples}} [ \underbrace{-\log q_{\mathbf \theta} ( \mathbf x\vert \mathbf z)}_{\text{reconstruction loss}} ] + \textcolor{teal}{\beta}\; \vert\sum_i \underbrace{\text{KL} \left(p_\phi( \mathbf z_i\vert \mathbf x)\:\vert\vert\:prior(\mathbf z_i) \right)}_{\text{compactness prior loss}} -C\vert\)
C is gradually increased from zero (allowing for a larger compactness prior loss) until good quality reconstruction is achieved
factor-vae (kim & minh 2018) - adds total correlation loss term
computes total correlation loss term using discriminator (can we discriminate between the samples when we shuffle over the batch dimension or not?)
beta-TC-VAE = beta-total-correlation VAE (chen et al. 2018) - same objective but computed without need for discriminator
use minibatch-weighted sampling to compute each of the 3 terms that make up the original VAE compactness prior loss
main idea is to better approximate \(q(z)\) by weighting samples appropriately - biased, but easier to compute
Wasserstein Auto-Encoders (tolstikhin et al.) - removes the mutual info part of the loss
wasserstein distance = earth-movers distance, how far apart are 2 distrs
minimizes wasserstein distance + penalty which is similar to auto-encoding penalty, without the mutual info term
another intuition: rather than map each point to a ball (since VAE adds noise to each latent repr), we only constraint the overall distr of Z, potentially making reconstructions less blurry (but potentially making latent space less smooth)
Adversarial Latent Autoencoder (pidhorskyi et al. 2020)
improve quality of generated VAE reconstructions by using a different setup which allows for using a GAN loss
Variational Autoencoders Pursue PCA Directions (by Accident)
local orthogonality of the embedding transformation
prior \(p(z)\) is standard normal, so encoder is assumed to be Gaussian with a certain mean, and diagonal covariance
disentanglement is sensitive to rotations of the latent embeddings but reconstruction err doesn’t care
for linear autoencoder w/ square-error as reconstruction loss, we recover PCA decomp
Disentangling Disentanglement in Variational Autoencoders (2019)
independence can be too simplistic, instead 2 things:
the latent encodings of data having an appropriate level of overlap
keeps encodings from just being a lookup table
when encoder is unimodal, \(I(x; z)\) gives us a good handle on this
prior structure on the latents (e.g. independence, sparsity)
to trade these off, can penalize divergence between \(q_\phi(z)\) and \(p(z)\)
nonisotropic priors - isotropic priors are only good up to rotation in the latent space
by chossing a nonisotropic prior (e.g. nonisotropic gaussian), can learn certain directions more easily
sparse prior - can help do clustering
VAE-SNE: a deep generative model for simultaneous dimensionality reduction and clustering (graving & couzin 2020) - reduce dims + cluster without specifying number of clusters
stochastic neighbor regularizer that optimizes pairwise similarity kernels between original and latent distrs. to strengthen local neighborhood preservation
can use different neighbor kernels, e.g. t-SNE similarity (van der Maaten & Hinton, 2008) or Gaussian SNE kernel (Hinton & Roweis, 2003)
perplexity annealing technique (Kobak and Berens, 2019) - decay the size of local neighborhoods during training (helps to preserve structure at multiple scales)
Gaussian mixture prior for learning latent distr. (with very large number of clusters)
at the end, merge clusters using a sparse watershed (see todd et al. 2017)
extensive evaluation - test several datasets / methods and evaluate how well the first 2 dimensions preserve the following:
global - correlation between pairwise distances in orig/latent spaces
local - both metric (distance- or radius-based) and topological (neighbor-based) neighborhoods which are 1% of total embedding size
fine-scale - neighborhoods which are <1% of total embedding size
temporal info (for time-series data only) - correlation between latent and original temporal derivatives
likelihood on out-of-sample data
further advancements
embed into polar coordinates (rather than Euclidean) helps a lot
convolutional VAE-SNE - extract features from images using some pre-trained net and then run VAE-SNE on these features
background: earlier works also used SNE objective for regularization - starts with van der Maaten 2009 (parametric t-SNE)
future work: density-preserving versions of t-SNE, modeling hierarchical structure in vae, conditional t-SNE kernel
A Survey of Inductive Biases for Factorial Representation-Learning (ridgeway 2016)
desiderata
compact
faithful - preserve info required for task
explicitly represent the attributes required for the task at hand
interpretable by humans
factorial representation - attributes are statistically independent and can provide a userful bias for learning
“compete” - factors are more orthogonal
“cooperate” - factors are more similar
bias on distribution of factors
PCA - minimize reconstruction err. subject to orthogonal weights
ICA - maximize non-Gaussianity (can also have sparse ICA)
bias on factors being invariant to certain types of changes
ISA (independent subspace analysis) - 2 layer model where first layer is linear, 2nd layer pools first layer (not maxpool, more like avgpool), sparsity at second layer
i.e. 1st layer cooperates, 2nd layer competes
VQ - vector quantizer - like ISA but first layer filters now compete and 2nd layer cooperates
SOM - encourages topographic map by enforcing nearby filters to be similar
bias in how factors are combined
linear combination - PCA/ICA
multilinear models - multiplicative interactions between factors (e.g on top of ISA)
functional parts - factor components are combined to construct the output
ex. NMF - parts can only add, not substract to total output
ex. have each pixel in the output be represented by only one factor in a VQ
hierarchical layers
ex. R-ICA - recursive ICA - run ICA on coefficients from previous layer (after some transformation)
supervision bias
constraints on some examples
e.g. some groups have same value for a factor
e.g. some examples have similar distances (basis for MDS = multidimensional scaling)
e.g. analogies between examples
can do all of these things with auto-encoders
more papers
vq-vae - latent var is discrete, prior is learned
Learning Disentangled Representations with Semi-Supervised Deep Generative Models
specify graph structure for some of the vars and learn the rest
1.2.2. GANs#
<IP_ADDRESS>. model-based (disentangle during training)#
disentangling architectures
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets (chen et al. 2016)
encourages \(I(x; c)\) to be high for a subset of the latent variables \(z\)
slightly different than vae - defined under the distribution \(p(c) p(x\vert c)\) whereas vae uses \(p_{data}(x)enc(z\vert x)\)
mutual info is intractable so optimizes a lower bound
Stylegan (karras et al. 2018)
introduced perceptual path length and linear separability to measure the disentanglement property of latent space
Stylegan2 (karras et al. 2019):
\(\psi\) scales the deviation of w from the average - \(\psi=1\) is original, moving towards 0 improves quality but reduces variety
also has jacobian penalty on mapping from style space \(w\) to output image \(y\)
DNA-GAN: Learning Disentangled Representations from Multi-Attribute Images
Clustering by Directly Disentangling Latent Space - clustering in the latent space of a gan
Semi-Supervised StyleGAN for Disentanglement Learning - further improvements on StyleGAN using labels in the training data
The Hessian Penalty: A Weak Prior for Unsupervised Disentanglement (peebles et al. 2020)
if we perturb a single component of a network’s input, then we would like the change in the output to be independent of the other input components
minimize off-diagonal entries of Hessian matrix (can be obtained with finite differences)
smoother + more disentangled + shrinkage in latent space
Hessian penalty is for a scalar - they define penalty as max penalty over Hessian over all pixels in the generator
unbiased stochastic estimator for the Hessian penalty (Hutchinson estimator)
they apply this penalty with \(z\) as input, but different intermediate activations as output
<IP_ADDRESS>. post-hoc (disentangle after training)#
mapping latent space
InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs (shen et al. 2020)
Interpreting the Latent Space of GANs for Semantic Face Editing (shen et al. 2020)
find latent directions for each binary attribute, as directions which separate the classes using linear svm
validation accuracies in tab 1 are high…much higher for all data (because they have high confidence level on attribute scores maybe) - for PGGAN but not StyleGAN
intro of this paper gives good survey of how people have studied GAN latent space
few papers posthoc analyze learned latent repr.
On the “steerability” of generative adversarial networks (jahanian et al. 2020)
learn to approximate edits to images, such as zooms
linear walk is as effective as more complex non-linear walks for learning this
nonlinear setting - learn a neural network which applies a small perturbation in a specific direction (e.g. zooming)
to move further in this space, repeatedly apply the function
A Disentangling Invertible Interpretation Network for Explaining Latent Representations (esser et al. 2020) - map latent space to interpretable space, with invertible neural network
interpretable space factorizes, so is disentangled
individual concepts (e.g. color) can use multiple interpretable latent dims
instead of user-supplied interpretable concepts, user supplies two sketches which demonstrate a change in a concept - these sketches are used w/ style transfer to create data points which describe the concept
alternatively, with no user-supplied concepts, try to get independent components in unsupervised way
Disentangling in Latent Space by Harnessing a Pretrained Generator (nitzan et al. 2020)
learn to map attributes onto latent space of stylegan
works using two images at a time and 2 encoders
for each image, predict attributes + identity, then mix the attributes
results look realy good, but can’t vary one attribute at a time (have to transfer all attributes from the new image)
ELEGANT: Exchanging Latent Encodings with GAN for Transferring Multiple Face Attributes (xiao et al. 2018)
trains 2 images at a time - swap an attribute that differs between the images and reconstruct images that have the transferred attribute
bias
Towards causal benchmarking of bias in computer vision algorithms (balakrishnan et al. 2020) - use human annotations to disentangle latent space
synthesis approach can alter multiple attributes at a time to produce grid-like matched samples of images we call transects
find directions + orthogonalize same as shen et al. 2020
Detecting Bias with Generative Counterfactual Face Attribute Augmentation (denton et al. 2019) - identify latent dims by training a classifier in the latent space on groundtruth attributes of the training images
Explaining Classifiers with Causal Concept Effect (CaCE) (goyal et al. 2020) - use vae to disentangle / alter concepts to probe classifier
post-hoc
Explanation by Progressive Exaggeration (singla et al. 2019)
progressively change image to negate the prediction, keeping most features fixed
want to learn mapping \(I(x, \delta)\) which produces realistic image that changes features by \(\delta\)
3 losses: data consistency (perturbed samples should look real), prediction changes (perturbed samples should appropriately alter prediction), self-consistency (applying reverse perturbatino should bring x back to original, and \(\delta=0\) should return identity)
moving finds ways to generate images that do change the wanted attribute (and don’t change the others too much)
minor
used human experiments
limited to binary classification
Interpreting Deep Visual Representations via Network Dissection (zhou et al. 2017)
obtain image attributes for each z (using classifier, not human labels)
this classifier may put bias back in
to find directions representing an attribute, train a linear model to predict it from z
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks (bau et al. 2018) - identify group of interpretable units based on segmentation of training images
find directions which allow for altering the attributes
GANSpace: Discovering Interpretable GAN Controls - use PCA in the latent space (w for styleGAN, activation-space at a specific layer for BigGAN) to select directions
Editing in Style: Uncovering the Local Semantics of GANs (collins et al. 2020) - use k-means on gan activations to find meaningful clusters (with quick human annotation)
add style transfer using target/source image
Unsupervised Discovery of Interpretable Directions in the GAN Latent Space - loss function which tries to recover random shifts made to the latent space
1.2.3. misc#
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction (yu, …, & ma, 2020)
goal: learn low-dimensional structure from high-dim (labeled or unlabeled) data
approach: instead of cross-entropy loss, use maximal coding rate reduction = MCR loss function to learn linear feature space where:
inter-class discriminative - features of samples from different classes/clusters are uncorrelated + different low-dim linear subspaces
intra-class compressible - features of samples from same class/cluster are correlated (i.e. belong to low-dim linear subspace)
maximally diverse - dimension (or variance) of features for each class/cluster should be as large as possible as long as uncorrelated from other classes/clusters
related to nonlinear generalized PCA
given random variable \(z\) and precision \(\epsilon\), rate distortion \(R(z, \epsilon)\) is minimal number of bits to encode \(z\) such that expected decoding err is less than \(\epsilon\)
can compute from finite samples
can compute for each class (diagonal matrices represent class/cluster membership in loss function)
MCR maximizes (rate distortion for all features) - (rate distortion for all data separated into classes)
like a generalization of information gain
evaluation
with label corruption performs better
Learned Equivariant Rendering without Transformation Supervision - separate foreground / background using video
1.2.4. (semi)-supervised disentanglement#
these papers use some form of supervision for the latent space when disentangling
Semi-supervised Disentanglement with Independent Vector Variational Autoencoders
Learning Disentangled Representations with Semi-Supervised Deep Generative Models - put priors on interpretable variables during training and learn the rest
Weakly Supervised Disentanglement with Guarantees
prove results on disentanglement for rank pairing
different types of available supervision
restricted labeling - given labels for some groundtruth factors (e.g. label “glasses”, “gender” for all images)
match pairing - given pairs or groups (e.g. these images all have glasses)
rank pairing - label whether a feature is greater than another (e.g. this image has darker skin tone than this one)
Weakly Supervised Disentanglement by Pairwise Similarities - use pairwise supervision
1.2.5. evaluating disentanglement#
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations (locatello et al. 2019)
state of disentanglement is very poor…depends a lot on architecture/hyperparameters
good way to evaluate: make explicit inductive biases, investigate benefits of this disentanglement
defining disentanglement - compact, interpretable, independent, helpful for downstream tasks, causal inference
a change in one factor of variation should lead to a change in a single factor in the learned repr.
unsupervised learning of disentangled reprs. is impossible without inductive biases
note - vae’s come with reconstruction loss + compactness prior loss which can be looked at on their own
data
dsprites dataset has known latent factors we try to recover
beta-vae disentanglement metric score = higgins metric - see if we can capture known disentangled repr. using pairs of things where only one thing changes
start with a known generative model that has an observed set of independent and interpretable factors (e.g. scale, color, etc.) that can be used to simulate data.
create a dataset comprised of pairs of generated data for which a single factor is held constant (e.g. a pair of images which have objects with the same color).
use the inference network to map each pair of images to a pair of latent variables.
train a linear classifier to predict which interpretable factor was held constant based on the latent representations. The accuracy of this predictor is the disentanglement metric score.
Evaluating Disentangled Representations (sepliarskaia et al. 2019)
defn 1 (Higgins et al., 2017; Kim and Mnih, 2018; Eastwood and Williams, 2018) = factorVAE metric: A disentangled representation is a representation where a change in one latent dimension corresponds to a change in one generative factor while being relatively invariant to changes in other generative factors.
defn 2 (Locatello et al., 2018; Kumar et al., 2017): A disentangled representation is a representation where a change in a single generative factor leads to a change in a single factor in the learned representation.
metrics
DCI: Eastwood and Williams (2018) - informativeness based on predicting gt factors using latent factors
SAP: Kumar et al. (2017) - how much does top latent factor match gt more than 2nd latent factor
mutual info gap MIG: Chen et al. 2018 - mutual info to compute the same thing
modularity (ridgeway & mozer, 2018) - if each dimension of r(x) depends on at most a factor of variation using their mutual info
1.2.6. non-deep methods#
unifying vae and nonlinear ica (khemakhem et al. 2020)
ICA
maximize non-gaussianity of \(z\) - use kurtosis, negentropy
minimize mutual info between components of \(z\) - use KL, max entropyd


R based genetic algorithm for binary and floating point chromosomes.
| Version: | 0.2.0 |
| Published: | 2015-03-16 |
| Author: | Egon Willighagen and Michel Ballings |
| Maintainer: | Michel Ballings <Michel.Ballings at gmail.com> |
| BugReports: | https://github.com/egonw/genalg/issues |
| License: | GPL-2 |
| URL: | https://github.com/egonw/genalg |
| NeedsCompilation: | no |
| Materials: | ChangeLog |
| In views: | Optimization |
| CRAN checks: | genalg results |
| Reference manual: | genalg.pdf |
| Package source: | genalg_0.2.0.tar.gz |
| Windows binaries: | r-devel: genalg_0.2.0.zip, r-release: genalg_0.2.0.zip, r-oldrel: genalg_0.2.0.zip |
| OS X binaries: | r-release: genalg_0.2.0.tgz, r-oldrel: genalg_0.2.0.tgz |
| Old sources: | genalg archive |
| Reverse depends: | COSINE, galts, geospt |
| Reverse imports: | hybridEnsemble, kernelFactory, plsVarSel, sensors4plumes |
Please use the canonical form https://CRAN.R-project.org/package=genalg to link to this page.


/** * Box is a superclass for the two box layouts: * * * {@link Ext.layout.HBox hbox} * * {@link Ext.layout.VBox vbox} * * Box itself is never used directly, but its subclasses provide flexible arrangement of child components * inside a {@link Ext.Container Container}. * * ## Horizontal Box * * HBox allows you to easily lay out child components horizontally. It can size items based on a fixed width or a * fraction of the total width available, enabling you to achieve flexible layouts that expand or contract to fill the * space available. * * {@img ../guides/layouts/hbox.jpg} * * See the {@link Ext.layout.HBox HBox layout docs} for more information on using hboxes. * * ## Vertical Box * * VBox allows you to easily lay out child components vertically. It can size items based on a fixed height or a * fraction of the total height available, enabling you to achieve flexible layouts that expand or contract to fill the * space available. * * {@img ../guides/layouts/vbox.jpg} * * See the {@link Ext.layout.VBox VBox layout docs} for more information on using vboxes. * * For a more detailed overview of Sencha Touch 2 layouts, check out the * [Layout Guide](../../../core_concepts/layouts.html). */ Ext.define('Ext.layout.Box', { extend: 'Ext.layout.Default', config: { orient: 'horizontal', /** * @cfg {String} align * Controls how the child items of the container are aligned. Acceptable configuration values for this property are: * * - ** start ** : child items are packed together at left side of container * - ** center ** : child items are packed together at mid-width of container * - ** end ** : child items are packed together at right side of container * - **stretch** : child items are stretched vertically to fill the height of the container * * Please see the 'Pack and Align' section of the [Events Guide](../../../core_concepts/events.html) for a detailed example and * explanation. * @accessor */ align: 'start', /** * @cfg {String} pack * Controls how the child items of the container are packed together. Acceptable configuration values * for this property are: * * - ** start ** : child items are packed together at left side of container * - ** center ** : child items are packed together at mid-width of container * - ** end ** : child items are packed together at right side of container * - ** justify ** : child items are packed evenly across the container. Uses the 'justify-content: space-between' css property * * Please see the 'Pack and Align' section of the [Events Guide](../../../core_concepts/events.html) for a detailed example and * explanation. * @accessor */ pack: 'start' }, alias: 'layout.tablebox', layoutBaseClass: 'x-layout-tablebox', itemClass: 'x-layout-tablebox-item', setContainer: function(container) { this.callSuper(arguments); container.innerElement.addCls(this.layoutBaseClass); container.on('flexchange', 'onItemFlexChange', this, { delegate: '> component' }); }, onItemInnerStateChange: function(item, isInner) { this.callSuper(arguments); item.toggleCls(this.itemClass, isInner); }, onItemFlexChange: function() { } });


--- title: Gerrit Documentation (beta) keywords: gerrit sidebar: gerritdoc_sidebar toc: false permalink: index.html folder: gerrit ---
Learn how Gerrit works, and take a tour through a few of its useful features.
Explore some of the key concepts of Gerrit.
Learn how to handle many common scenarios using the Gerrit workflow.
Install and configure your own Gerrit server.
Create and manage your own Gerrit projects.
Customize Gerrit to suit your needs and integrate into your existing workflows.
Set up a dev environment and contribute to Gerrit!
Learn the steps required to build a Gerrit release.


Japan's NTT to invest $5.5 bn in building power networks for supply backup
NTT will provide electricity by using power saved in batteries at the 7,300 buildings it owns and will purchase power from others, the report said.
by ReutersNippon Telegraph and Telephone Corp will spend about 600 billion yen ($5.5 billion) to build power distribution networks, the Nikkei newspaper reported, without citing its sources.
In a rare move for non-power generators, Japan's former telephone monopoly aims to supply power to hospitals and factories when electricity supply is cut off, the report said.
NTT generates about 300 billion yen in revenue from its power business and plans to double that by fiscal 2025, the report said.
NTT will provide electricity by using power saved in batteries at the 7,300 buildings it owns and will purchase power from others, the report said.
It also plans to build solar, wind and biomass power generators.
NTT's own networks could reduce the risk of blackouts, the report said.
In September Tokyo Electric Power was slow to restore service after Typhoon Faxai hit Tokyo and surrounding regions and left more than 800,000 households without power.
(Only the headline and picture of this report may have been reworked by the Business Standard staff; the rest of the content is auto-generated from a syndicated feed.)


| [ Team LiB ] |
Chapter 23. Structured Text: XMLXML, the eXtensible Markup Language, has taken the programming world by storm over the last few years. Like SGML, XML is a metalanguage, a language to describe markup languages. On top of the XML 1.0 specification, the XML community (in good part inside the World Wide Web Consortium, W3C) has standardized other technologies, such as various schema languages, Namespaces, XPath, XLink, XPointer, and XSLT. Industry consortia in many fields have defined industry-specific markup languages on top of XML, to facilitate data exchange among applications in the various fields. Such industry standards let applications exchange data even if the applications are coded in different languages and deployed on different platforms by different firms. XML, related technologies, and XML-based markup languages are the basis of interapplication, cross-language, cross-platform data interchange in modern applications. Python has excellent support for XML. The standard Python library supplies the xml package, which lets you use fundamental XML technology quite simply. The third-party package PyXML (available at http://pyxml.sf.net) extends the standard library's xml with validating parsers, richer DOM implementations, and advanced technologies such as XPath and XSLT. Downloading and installing PyXML upgrades Python's own xml packages, so it can be a good idea to do so even if you don't use PyXML-specific features. On top of PyXML, you can choose to install yet another freely available third-party package, 4Suite (available at http://4suite.org). 4Suite provides yet more XML parsers for special niches, advanced technologies such as XLink and XPointer, and code supporting standards built on top of XML, such as the Resource Description Framework (RDF). As an alternative to Python's built-in XML support, PyXML, and 4Suite, you can try ReportLab's new pyRXP, a fast validating XML parser based on Tobin's RXP. pyRXP is DOM-like in that it constructs an in-memory representation of the whole XML document you're parsing. However, pyRXP does not construct a DOM-compliant tree, but rather a lightweight tree of Python tuples to save memory and enhance speed. For more information on pyRXP, see http://www.reportlab.com/xml/pyrxp.html. For coverage of all aspects of XML and of how you can process XML with Python, I recommend Python & XML, by Christopher Jones and Fred Drake (O'Reilly). In this chapter, I cover only the essentials of the standard library's xml package, taking some elementary knowledge of XML itself for granted. |
| [ Team LiB ] |


title = "Home" url = "/" layout = "default" is_hidden = 0 [eventOverview] timezone = "America/Detroit" == {##}
Hello and welcome to FAMNMS' website. Our goal is to connect FIRST Alumni and Mentors at Michigan State/in the Lansing region to FRC and the teams. We hope to encourage and grow the presence of FIRST in the Lansing area. On this website you can find lots of resources and also how to become a volunteer through FAMNMS, or even a mentor. We are always looking for new members and welcome everyone, not just FIRST Alumni. If you have any questions, please don't be afraid to contact us and we will try and get back to you right away. If you'd like to know more about FAMNMS, please venture to the About page to learn all about us!
The mission of FIRST is to inspire young people to be science and technology leaders, by engaging them in exciting Mentor-based programs that build science, engineering, and technology skills, that inspire innovation, and that foster well-rounded life capabilities including self-confidence, communication, and leadership. Currently in Michigan, there are over 2500 teams, making FIRST in Michigan the largest district out of all the other regions and districts in the world.


Sun Dec 17, 2006
Welcome to another instalment of Toponym of The Day. Today’s toponym is the longest place name in the world:
Llandfairpwllgwyngyllgogerychwyrudrobwllllantysiliogogogoch
This is the name of a town in North Wales. It translates as “The church of St. Mary in the hollow of white hazel trees near the rapid whirlpool by St. Tysilio’s of the red cave” in Welsh (Source: Web of Linguistic Fun).


J-K: Soldier killed in blast near LoC
Defence Ministry spokesperson Lt Colonel Devender Anand identified the soldier who was killed as Havaldar Santosh Kumar of Pura Bhadauria village in Agra district of Uttar Pradesh.
by Express News ServiceAN ARMY soldier was killed and two other Army personnel injured in a suspected IED blast that took place near the Line of Control in Jammu and Kashmir’s Palanwala sector on Sunday.
Defence Ministry spokesperson Lt Colonel Devender Anand identified the soldier who was killed as Havaldar Santosh Kumar of Pura Bhadauria village in Agra district of Uttar Pradesh.
Sources said the explosion took place around 11 am when an Army patrol was moving near the LoC. The IED was apparently planted by militants, sources said.
Meanwhile, Pakistani troops resorted to unprovoked shelling and small arms fire along the LoC in Shahpur area of Poonch district. The Indian Army retaliated.


Alternate Reality
Home
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At testibng tastable page to tst testable fueatures for testing.


This story has legs: Cambodia ‘bug cafe’ serves up insect tapas
by Agence France-PresseAnt spring rolls, silkworm taro croquettes and a “bug mac” — Cambodia’s first insect tapas restaurant is mixing cocktail culture with creepy crawler fare.
At the busy “Bugs Cafe” in the tourist town of Siem Reap, chef Seiha Soeun stands over a sizzling wok in the kitchen tossing in crickets, grasshoppers, tarantulas, and scorpions.
Sold at street vendors or in Instagram-friendly tourist spots, insects aren’t new to Cambodian palates.
But they are usually served one way: fried, with dipping sauce, and maybe a cold beer.
“We have a different kind of menu,” Seiha said, adding that he practiced making the “bug mac” — a patty of pureed ant, bee, silkworm and cricket topped with a slice of cheese and pickle — many times to get it just right.
On a recent evening at the restaurant, French co-founder Davy Blouzard greeted curious diners and explained the menu.
“We want to show that it’s possible to make quality food with insects,” he said.
There is sweet potato cream with bee larvae, silkworm and mango flambe, and even a cricket cheesecake dessert.
Insects are eaten by two billion people worldwide, according to the UN’s Food and Agriculture Organization.
Besides being a cheap source of protein, insect cuisine is also a possible answer to rising concern over the environmental impact of livestock farming.
As dinner orders picked up, tourists from as far afield as Britain, Poland and Malaysia all happily — if a little squeamishly — crunched away.
Servers worked the room wearing shirts emblazoned with the words “I HATE INSECTS”, with the “H” crossed out.
British backpacker Joshua Bean, 23, said he knew he had to visit the cafe after seeing an ad for the unusual eatery at his hostel.
He didn’t flinch at the “juicy” silkworms and an assortment of other insects piled up on his plate.
“It’s not the kind of thing you get back home,” he said.


Bring the Woodlands to Your View
Ferns are as attractive as colorful blooms. Most often when we think of a garden, what comes to mind is colorful blooming flowers.
But, don't forget the beauty of foliage.
Their foliage comes in an abundance of colors, shapes and sizes.
Ferns are graceful and add a frothy exotic splendor, even a sense of mystery, such as a hidden primeval fortress, or an exclusive tropical island.
Ferns are an excellent source for decorating. Use them to form an open wooded grotto, create a decorative border, or fill a shady corner.
Although they may look frail, most garden ferns can be grown year round because they can withstand both the winter cold and summer heat.
Planting a growing fern garden requires minimal care and attention. They generally need little more than regular mulching and watering during very dry periods.
Their true beauty is simply enjoying them as you take a moment of tranquility or a break from your usual routine.
The Lily, Another Garden Stunner
The lily is another stunner, I love them because of their regal beauty. Mine bloom year-after-year. I divide them every year or so to improve their blooming periods. They make popular gifts and bouquets and make great gifts. Their bulbs can be planted in your garden, chosen for potted plants to be given as gifts or placed in a room to brighten a table or a corner of a room. They are excellent choices for bouquets.
Most lilies are quite fragrant, and are often used in perfumes. Their colors have significant meanings: White lilies symbolize purity and virtue. Pink (stargazer) lilies are said to represent prosperity and abundance. Red lilies symbolize passion. The orange or tiger lily symbolize confidence, pride, and wealth. Yellow lilies symbolizes thankfulness and desire for enjoyment.
In the garden they make excellent beds and border plants, and even as a shrub border. I've seen some of the smaller varies that fit perfectly in alpine rock gardens, stunning in red and yellow or gold.
An interesting use of lillies is for skin care products for those with sensitive skin. The oil extracted from lilies has healing and softening properties. Lily oils are used for massage, as a bath oil, after bath lotions, great for babies soft skins, are used to heal dry cuticles and elbows, as facial moisturizers, and as under-eye oil and hot-oil treatments.
Develop Your Space
Change your view with climbing roses. These garden classics can add structure and beauty at the same time. Create your own natural pillars or columns, borders or decorate a wall using your own garden roses. I've let them cover a fence naturally and pruned them over the years to get a shape I want.
You can use this growing technique on your own to develop a private pillar or wall covering just for you!
As your roses twine their way up pillars or the edge of a fence, they tend to weave their way through fences, or simply sprawl out across any garden structure; you will end up with a lovely display!
Climbing roses are known for blooming out masses of flowers mainly because of their growth habit of holding their blossoms up high for all to see.
Most prominently displayed is color, and the second bonus is a spread of fragrance. Plant a combination of colors to make a stunning display


DATA ZONE
SIT
UAT
PROD
CMR Search Results
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Concept ID - Data URL
Here Be The Link Harvester
Simply upload a text file with links to data separated by new lines, click download, and voila!
DOWNLOAD!


'Lack of time is a real health killer'- this phrase makes the most sense when you are out there struggling to maintain a balance between your work, studies and personal life. The hectic schedule that you been pushing through the whole day is just not letting you put on your shoes and track pants and head off to the gym.
We all know how busy a student's life can be especially if you are in those years of college where you have to focus on your studies, build a career, complete your projects, enroll for an internship and maintain a social life. The efforts you need to put in every day just don't seem to be decreasing but you can see your belly fat increasing, pun intended.
So let's talk about ways of how you can create time for fitness around such a busy schedule. As we know everything comes at a cost, so you need to be sacrificing some things to make way for things that are gonna help you in the long run.
Introduce exercise into your daily habits.
Cut off exercise from your to-do list first thing in the morning.
Filter out the things that are gonna provide value in the long run.
Come up with a schedule that helps you nurture discipline.
Don't be too hard on yourself if you fail.
Don't give in to peer pressure.
When you cant spare even a minute from your busy day, it's mostly beneficial to introduce exercise into your way of living or how you function daily.
For example, taking the stairs instead of the elevator, riding a bicycle to college instead of bikes or cars, maybe doing a small set of pushups and situps whenever you are slacking off not doing any work, you see the introduction of these habits can help you burn those calories that you would be burning otherwise in the gym.
Try waking up a little earlier and make time for a refreshing workout or a yoga session. Working out in the morning has a lot of benefits apart from saving time, it helps you boost your metabolism for the day and clear your mind, your hormonal levels are on a rise in the morning so you just might put that morning wood to duty.
Being a college student, it is obvious that you would be attending many parties and events only for the sake of gaining some social exposure, while such type of social exposure is critical for your overall growth but don't get overboard with the feeling, know what is good for you in the long run.
I know it must be tempting to attend such parties and events because all the cool kids are doing it but what's even cooler is to take of yourself, you see because self-care attracts self-love and self-love attracts high confidence and esteem that is gonna help you strengthen your social game all-together.
'Discipline is the bridge between goals and accomplishment, period'.
When you have a plan prepared for what you want in life, the path to achieving the goal becomes more clear. Come up with a proper plan of action during the day, when you wake up first thing in the morning think of ways how you would be handling the day instead of grabbing your phone and swiping through Instagram posts, have room for modifications and improvision so you can accommodate sudden changes in your plan and if you have plan laid out stick to it and work towards it with all your strength, I am pretty confident that you are gonna get it.
As a human, we are imperfect beings, we fail, we fall and then we stand back again, what matters most is trying. There are gonna be days when you will not be able to follow the plan, don't treat yourself as a failure or don't procrastinate.
According to a scientific study, people that are intelligent and exercise self-discipline are often too hard on themselves if they fail in achieving certain things, just slack off for the day and prepare extra for the next day because you always know with a new day comes new strength and new thoughts.
Being a college student I can vouch for it that you are gonna have friends that drink and smoke, having such friends often leads to an influence called peer pressure. You will need to train yourself if such a situation shows up and say no. Having such friends doesn't necessarily mean it's bad, you would just have to define clear boundaries that you are not into that life.
So those were some of the steps I undertook as my college life progressed, hope these might help you and for the ending note treat fitness as a lifestyle and not a goal, fall in love with the process and that's it you would not have to put any extra effort in pursuing it.


Bethany's Notes for UdaCity
Unit 1
Important Definitions
HTML(HyperText Mark-Up Language): the main document type of the web
URL: how you refer to documents on the web
HTTP: the protocol that unites the web; the web runs on this
World Wide Web: a collection of HTML documents; files can be almost anything
Browsers: Things like Internet Explorer, Google Chrome, or Firefox
Servers: Computers that host instead of doing the browsing. They host most of the files that make up the Web.
Internet: the world's largest computer network
Tag: a command contained within angled brackets. There are usually opening and closing tags. Some may not require closing. These are called Void Tags.
Elements: everything within a set of opening and closing tags.
Attribute: a property of a HTML element
HTML
HTML, or HyperText Mark-Up Language, is the main document type of web. It is made of text content (what you see), mark-up what it looks like), references to other documents, and links to other pages. The HTML mark up is made of elements, which are made
of tags.
Tags
In tags, there is an opening tag and an closing sign. Each is surrounding by greater/less than signs, which within dictate which command you are using. In between these tags are the words you wish to write. The only difference between an opening and closing
tag is the slash mark before the command. (Ex: /Name)
There are many different types of tags. Here are the basic ones and their commands:
B-Tag (Bold Tag), represented by a b.
Em-Tag (Em. stands for emphasis; Italics), represented by em.
HTML Attributes
Represented by tag ATTR= "value"; ending is /tag. The ATTR stands for attribute.
A-Tag (Anchor Tag, links), represented by a href= "url" the closing tag is /a.
Img-Tag (Image Tag, images), represented by img src= "url" alt= "text" This is a void tag. Void tags need no closing tags. The src stands for source, and alt stands for alternate. This part is "required"- it isn't really needed but you need to use it.
It is used for broken requests, and is also used when blind people use the computer.
Whitespace
When typing in the elements, text ends up strung on one big line unless you use one of two specific commands.
text on ----------------> text on multiple lines
multiple lines
Br-Tag (Break Tag, a line break; Void Tag), represented by br. Remember, Void Tags need no closing tag.
P-Tag (Paragraph Tag, a block) represented by p. When you use this tag, a box seems to appear around the word selected, creating a slight line break where it is used. The length and width of the (invisible) tag can be changed to fit your needs.
Inline VS Block
HTML documents are composed of two types of elements- inline or block. Block elements form an invisible box around the content.
Inlines include: b, em, img, br, etc.
HTML documents usually look much different than displayed on this page. Be warned! Programmers need to write exactly the way a computer understands, as one small problem can lead to bigger ones. Programmers can't remember everything either. There are
too many details to keep on your mind- if you need to google the tag for italics, don't feel ashamed!


Ryan Fung's HTML Templates
v1 (2010)
- First Template - complete orange/white theme - Myriad Pro font
- Orange background
- White foreground
- Variants: Original; Simple
v2 (January 2011)
2.0
(January 2011)
- Complete revamp from v1.0 - orange to yellow colour theme with grey
- Grey background
- Grey background
- Light orange foreground
v3 (April 2011 - September 2011)
3.0
(around April 2011)
- Colour aesthetics revamp from v2.x - introduction of PyroCarbon theme (red-orange-yellow-white-grey-black)
- Black background
- Grey foreground
- 'Pyro' coloured headings
- Shape aesthetics and ergonomics revamp from v3.0 - introduction of CSS3 rounded borders (en masse)
- Proper introduction of more CSS-coded classes and tags
- More usage of PyroCarbon colours
- Variants:
- PyroCarbon vs Concrete Spectrum (use of blue, green, turquoise, purple) colour schemes
- Navigation and Jump links style variants:
- centered joined
- centered separated
- side joined
- side separated
3.2
(June 2011)
- Developed from v3.1
- introduction of link menus and percentage widths
3.3
(July 2011)
- Developed from v3.2
- introduction of folder/file tabs and sections
- navigation bar colour tweaking
- more emphasis on grey colour levels
- Initial development on a successor to v3.3, evolved into v4.0
v4 (September 2011 - April 2014)
4.0
(September 29th 2011)
- Complete revamp from v3.x - Aims to be unchanged (version number) for an extended period of time
- Change from XHTML 1.0 Transitional to XHTML 1.1 plus MathML 2.0 plus SVG 1.1
- Use of new CSS(3) styles: box-shadow, text-shadow
- Microsoft-esque: return to rectangular boxes and use of Segoe UI as primary font
- Colour aesthetics:
- Removed the use of red - more emphasis on shades of orange and yellow
- Change in appearance of classes and tags
- Shape and layout aesthetics:
- Header with title (and caption) and jump (link anchor) bar
- Stationary navigation (in between webpages) sidebar object with CSS transitions
- New section boxes with headers split into section title and date; absolute 1000px width
- Greater focus on ergonomic appearance for viewers than egoistic appearance
4.1
(March 17th 2012)
- Doctype revamp from v4.0 - Transition to HTML 5 using XML syntax
- Use of Open Sans as primary/fallback font
- Navigation tab now translucent - smaller screens will have navigation tab overlapping content
- Colour aesthetics:
- Implementation of gradient backgrounds in: header bar, sectional header bars, tables, forms
- Shape and layout aesthetics:
- Implementation of Music Info 3 styling: sectional header bars, header and section end fades out
- Implementation of form CSS
v5 (April 2014 - present)
5.0
(April 24th 2014)
- Switch to Maven Pro as primary font
- Colour aesthetics:
- Switch from dark background to light background
- Shape and layout aesthetics:
5.1
(February 2015)
- Colour aesthetics:
- Primary colour orange used more for highlights
- Inspired by Google's Material Design
- Shape and layout aesthetics:
- More minimalistic compared to 5.1
Ryan Fung's (X)HTML Template Logs
Versioning
Syntax: ..
Full example: 4.0.0 dev standalone
Latest Version: 4.0
Major Version: Only changed when there is a very significant differences between the new (current) and previous version - i.e.: the new version bears little similarity to the previous version number (e.g.: from 3.x to 4.0)
Minor Version: Only changed when there is a significant difference between the new (current) and previous version (e.g.: from 3.1 to 3.2 to 3.3)
Revision Version: Changed when small portions of code is debugged or tweaked for optimisation
Version Statuses:
Dev - can include malfunctional code while for development and testing - indicated by "dev" after the version
Use - includes code for distribution and use
Obsolete - version has been superseded by a newer version - indicated by smaller/lower version number
Version Types:
Normal - link to CSS and other external code - requires linking to support code and documents
Standalone - integrated CSS and other code - documents based on standalone versions can function on its own
Version Usage
All documents formed on the Ryan Fung's (X)HTML Template should update to the latest revision version of the document - This will allow better performance for the documents
As there are changes in tag layouts and aesthetics between both major and minor versions, users should aim to update to the latest minor version where possible, as there will only be significant tag layouts and aesthetics differences between major versions
Transition versions (e.g. between 3.1 and 3.2) are not normal version releases but are development versions only - they can be used in documents but are not recommended
From version 4.0 onwards, all code changes must be logged