OpenLLM-France/wikimedia huggingface dataset:
# Finite elements/Axially loaded bar
## An axially loaded bar

Let us consider the simplest solid mechanics problem that we can think of - the axial loading of a bar (see Figure 1).
* Figure 1. Axial loading of a bar.
Given:
The bar is of length $L\,$ and has an area of cross-section $A\,$. The Young's modulus of the material is $E\,$.
Find:
We want to find the stresses and deformations in the bar due to the concentrated axial load $\mathbf {R}$ at the end.
Assumptions:
* The cross-section of the bar does not change after loading.
* The material is linear elastic, isotropic, and homogeneous.
* The load is centric.
* End-effects are not of interest to us.

### Strength of Materials Approach

From the free-body diagram of the bar, a balance of forces gives
    $\mathbf {f} _{\text{wall}}=\mathbf {R} =\mathbf {f} (\mathbf {x} )~.$
The stress in the bar is given by
    ${\boldsymbol {\sigma }}(\mathbf {x} ):={\cfrac {\mathbf {f} (\mathbf {x} )}{A}}\qquad \implies \qquad {{\boldsymbol {\sigma }}(\mathbf {x} )={\cfrac {\mathbf {R} }{A}}}~.$
The constitutive model for the bar is given by Hooke's law (${\boldsymbol {\sigma }}=E{\boldsymbol {\varepsilon }}$). Therefore, the strain in the bar is
    ${\boldsymbol {\varepsilon }}(\mathbf {x} )={\cfrac {{\boldsymbol {\sigma }}(\mathbf {x} )}{E}}\qquad \implies \qquad {{\boldsymbol {\varepsilon }}(\mathbf {x} )={\cfrac {\mathbf {R} }{AE}}}~.$
To get the deformation of the bar, we use the strain-displacement relations
    ${\boldsymbol {\varepsilon }}:={\cfrac {\Delta l}{l}}={\cfrac {\delta _{(\mathbf {x} =L)}}{L}}\qquad \implies \qquad {\delta _{(\mathbf {x} =L)}={\cfrac {\mathbf {R} L}{AE}}}~.$
We can get the deformation of any point in the bar in a similar manner:
    ${\boldsymbol {\varepsilon }}(\mathbf {x} )={\cfrac {\delta (\mathbf {x} )}{\mathbf {x} }}\qquad \implies \qquad {\delta (\mathbf {x} )={\cfrac {\mathbf {R} \mathbf {x} }{AE}}}~.$

## A more complicated axial load

Now, suppose that we have a linear distributed axial load $\mathbf {q} (\mathbf {x} )=a\mathbf {x}$ in addition to the load $\mathbf {R}$ (see Figure 2(a)). This load has units of force per unit length and is also called a body load. Examples are gravity and inertial forces due to rotation around the $y$ axis.
* Figure 2(a). Distributed axial load
* Figure 2(b). Free body diagram for distributed axial load
Once again, we want to calculate stresses and displacements. Note that stresses are no longer constant along the length of the bar.

### Strength of Materials Approach

From the free body diagram of the bar, a balance of forces gives
    $\mathbf {f} _{\text{wall}}=\mathbf {R} +\int _{0}^{L}\mathbf {q} (\mathbf {x} )~dx\qquad \implies \qquad {\mathbf {f} _{\text{wall}}=\mathbf {R} +{\cfrac {aL^{2}}{2}}}~.$
So we know the reaction force at the wall. But we want to know the stress and displacement at any point along the bar.
To do this, we can make a cut at any point along the length and use the free body diagram to compute a reaction force $\mathbf {f} (\mathbf {x} )$ (see Figure 2(b)). But this is tedious since we have to repeat the process for every point in the bar.
# Informal learning activities/Bth

Bthyn
This inserts a link to the country or area, in this case Bithynia, into a Places & Buildings item.
# Informal learning activities/Chn

Chn
This inserts a link to the country or area, in this case China, into a Places & Buildings item.
# Informal learning activities/Bv

Blv
This inserts a link to the country or area, in this case Bolivia, into a Places & Buildings item.
# Informal learning activities/Bz

Brzl
This inserts a link to the country or area, in this case Brazil, into a Places & Buildings item.
# Informal learning activities/Chl

Chl
This inserts a link to the country or area, in this case Chile, into a Places & Buildings item.
# Informal learning activities/By

Brtny
This inserts a link to the country or area, in this case Brittany, into a Places & Buildings item.
# Informal learning activities/CA

CntrlAs
This inserts a link to the country or area, in this case Central Asia, into a Places & Buildings item.
# Informal learning activities/BrLth

Blrs /Lthn
This inserts a link to two countries, in this case Belarus and Lithuania, into a Places & Buildings item.
# Informal learning activities/Brm

Brm
This inserts a link to the country or area, in this case Burma (i.e. Myanmar), into a Places & Buildings or Buildings and Places item.
# Informal learning activities/Cc

Ccss
This inserts a link to the country or area, in this case the Caucasus, into a Places & Buildings item.
# Global Audiology/Europe/Bosnia and Herzegovina

| Home | Africa | Americas | Asia | Europe | Oceania |
| Belgium | Bosnia and Herzegovina‎ | Czech Republic | France | Isle of Man | Italy | Luxembourg | Malta | Norway | Russian Federation |

# References

| | | | Contributors to the original text |
| ADD | NAMES | HERE | Contributors to the original text |
# Introduction to Information Theory
## Outline

* Information Measures
* Source coding
* Channel capacity
* Channel coding
* Differential entropy
* Rate-Distortion Theory

## Pre-requisites

* Linear Algebra
* Probability

## Textbooks

* Thomas M. Cover and Joy A. Thomas, Elements of Information Theory, John Wiley & Sons, 2006.
* Raymond W. Yeung, Information Theory and Network Coding, Springer, August 2008

## Offsite Courses
### With video lectures

* Information Theory, Raymond W. Yeung, The Chinese University of Hong Kong, 2014.
* Information Theory and Coding, Prof. S.N. Merchant, IIT Bombay, 2011.

### Without video lectures

* Information Theory, Srikrishna Bhashyam, IIT Madras, Jan-Apr 2013.
* Information Theory, Andrew Thangaraj, IIT Madras, Jan-Apr 2005.
* Information Theory, Navin Kashyap, IISc Bangalore, August-December 2013.
* Information Theory and Source Coding, Dr. M. R. Soleymani, Concordia University, Summer 2013.
* Information theory in computer science, Mark Braverman, Princeton University, Fall 2011.
* Information and Entropy, Prof. Paul Penfield and Prof. Seth Lloyd, MIT, Spring 2008
* Information Theory, Todd Moon, Spring 2006.
* Information Theory, Patric Östergård, Aalto University, Autumn 2013. (Earlier version: ).
* Information Theory and its applications in theory of computation, Venkatesan Guruswami, Carnegie Mellon University, Spring 2013.
* Information Theory, Thomas Cover, Stanford University, Winter 10-11.
* Information Theory, Henry D. Pfister, Texas A&M University, 2011.
* Information Theory, Mai Vu, Tufts University, Fall 2007.
* Random Codes in Communication, Haim Permuter, Ben-Gurion University, Spring 2011.
* Probability in Computer Science, Dr. Jan Bouda, Masaryk University, Summer 2012.
* Courses on Information Theory and Coding, Aslan Tchamkerten, Telecom ParisTech.
* Information Theory, J. Rockey Luo, Colorado State University, Fall 2014.
* Information Theory, Himanshu Tyagi, IISc Bangalore, August-December 2016.
# Introduction to Historiography

This course provides an introduction to the subject of History. Much of the content here was developed by the now defunct Department of Philosophy of History. Students can use these resources to learn about History and its methodologies.
History is the study of systematically collected information about the past. When used as the name of a field of study, history refers to the study and interpretation of the record of humans, families, and societies as preserved primarily through written sources. History is thus usually distinguished from prehistory by the widespread adoption of writing in the area under study. Knowledge of history is often said to encompass both knowledge of past events and historical thinking skills.
Traditionally, the study of history has been considered a part of the humanities. However, in modern academia, history is increasingly classified as a social science, especially when chronology is the focus.

## Essays

* Civilization, Cultural Diffusion, and Innovation
* Human Interaction With The Environment
* Values, Beliefs, Political Ideas and Institutions
* Conflict and Cooperation
* Comparative History of Major Developments
* Patterns of Social and Political Interaction
* History's Habits of the Mind
* How to Write History Better
* Schools of History
# Introduction to Hebrew
## Basic Vocabulary
### Common Phrases

Shalom - שלום - Hello.
Ma shlomkha? - ?מה שלומך - How are you? (Formal).
Ma kore? - ?מה קורה - How are you? (Informal).
Koreem li... - ...קוראים לי - My name is... (Literal: I'm called...).
Ekh koreem lekha? - ?איך קוראים לך - What's your name? (Literal: How are you called?).
Ani lo medaber ivrit - אני לא מדבר עברית - I don't speak Hebrew.
Ani medaber ktsat ivrit - אני מדבר קצת עברית - I speak a little Hebrew.

### Pronouns

I - Ani - אני.
You (singular) - Ata - אתה.
He - Hoo - הוא.
She - Hee - היא.
We - Anakhnu - אנחנו.
You (plural) - Atem - אתם.
They (Masculine) - Hem - הם.
They (Feminine) - Hen - הן.

### Prepositions

With - Eem - עם.
In (Used to place and time) - Be... (no space before next word) - ...ב .
On (Used only as "the book is on the table") - Al - על.
Of/'s - Shel - של.
From - Mi... (No space) - ...מ .
For - Bishvil/ Le...(No space) - ל/בשביל .

### Conjunctions

And - Ve... (No space, can be pronounced Va, Vi and Oo too.) - ....ו .
Or - O - או .
But - Aval - אבל .

### Note

For Hebrew Alphabet go to Reading and Writing Hebrew.
# Introduction to Italian

Italiano Uno :
| Italiano Uno Satellite image of Italy. Italian is a Romance language from western Europe that is spoken primarily in Italy and Switzerland. The vocabulary and grammar are very similar to Spanish, French, and Portuguese. It is spoken by approximately 70–80 million people as a native language and is the twentieth most-spoken language in the world. There are several languages (or dialects) which are spoken along with Italian including Sicilian, Sardinian, Venetian and others. | A Few Notes Marmore's Falls in Umbria.  Before you begin, bear in mind that learning a language requires a lot of repetition. You’re not expected to read this page once and understand everything on it; read everything, memorize it, and try to make it a part of your being. Also, remember that memorizing translations is never the best way to learn a language; un cane isn't just the words "a dog", it's your grandma's weinerdog or your brother's German shepherd. Also, if you already speak a Romance language, try to see the similarities between it and Italian. You will be surprised by how similar they are. |
| Lessons Lezione Uno: Common phrases Lezione Due: The Italian alphabet Lezione Tre: Some simple words Lezione Quattro: Nouns and articles Lezione Cinque: Verbs Lezione Sei: Preposition contractions Lezione Sette: Adjectives Lezione Otto: C'è, ci sono, and ecco Lezione Nove: The second conjugation (-ere) Lezione Dieci: Some new nouns Esame Uno: The first test Lezione Undici: Can and must Lezione Dodici: Past tense verbs Lezione Tredici: Days – months – seasons | A Few Notes Marmore's Falls in Umbria.  Before you begin, bear in mind that learning a language requires a lot of repetition. You’re not expected to read this page once and understand everything on it; read everything, memorize it, and try to make it a part of your being. Also, remember that memorizing translations is never the best way to learn a language; un cane isn't just the words "a dog", it's your grandma's weinerdog or your brother's German shepherd. Also, if you already speak a Romance language, try to see the similarities between it and Italian. You will be surprised by how similar they are. |
* Textbooks
* Italian
| previous lesson | next lesson | Department | Division |
# Open Educational Resources/Localization of OER

Localization of OER: educational resource might be inappropriate for a specific learning environment, target group or use-case.
* (Images)used images are inappropriate for learners in Latin America (e.g. images show people from South Africa performing a certain task. This will be replaces by images with people from Latin America that is performed a task in their socio-economic environment).
* (Data and Analysis) Data sets used in the learning refer to specific country, the sample data sets had to be replaced by data sets that make sense for target group of learners
* (Social and Cultural Constraints) Examples and use-cases are sometimes not directly transferable to the social and cultural environment of the group of learners. So parts are adapted to that constraints.
* (Geolocation) Use relevant maps for the use case and learn about geolocated OER, that allows to attach learning resources to real geolocations.
# Open Educational Resources/Student Authoring

This lesson introduces student-authored Open Educational Resources.

## Learning Task

* Explain how student authoring can be regarded as learning activity! What is the role of teacher as moderator of learning processes?
* EtherPad is one example for collaborative editing! Explore different OpenSource tools for collaborative editing! Explain how you could integrate that concept in your learning environments and you knowledge domain?

## Readings

* Inside Higher Ed: Students' Vital Role in OER
* OpenOregon: Textbook Affordability Student Toolkit
* Rebus: A Guide to Making Open Textbooks with Students

## See Also

* Collaborative Learning
* Reader2Author
* Wiki Education
# Open Educational Resources/Training

This page provides resources for teachers seeking to implement open educational resources in their courses.

## Readings

* Wikipedia: Open educational resources
* Lumen Learning: What are Open Educational Resources (OER)?
* Wikipedia: Creative Commons license

## Activities

* Review OpenContent.org: What is Open Pedagogy? Identify one or more opportunities to apply open pedagogy in your course(s).
* Review Affordable Learning Georgia: Platforms for Hosting and Creation. Experiment with several of the listed hosting sites to identify a platform you would consider using to develop and share your own open content. Wikiversity should also be included in this list.

## See Also

* OpenContent.org: OER Definition
* Hawaii.edu: OER Training
* Lumen Learning: Adopting Open Educational Resources in the Classroom
* Rebus Community: How to Publish an Open Textbook
* Rebus Community: A Guide to Making Open Textbooks with Students
# Open Educational Resources/Lesson/Flashcards
## Instructions

* Click on the flashcard text to show the answer.
* Click on Next Card to show the next flashcard.
    Log in to hide the Clear the cache of this page? message before each new flashcard.
* Terms
* Creative Commons - Attribution license is abbreviated as _____. CC-BY
* Next Card
# Open Educational Resources/Localization

Localisation of learning resources means that authors adapt learning resources to local and regional requirements and contraints.
* Language of Learning Resource (Translation)
* Use of local examples that match local social, cultural constraints or due to the set of available resources in the certain region or community.
* Learner profile and skills,
* Institutional Localization, i.e. adaptation to institutional or organisational requirements and constraints (e.g. curriculum)

## Learning Tasks

* (Geographic Information Systems) Explore the role of Geographic Information Systems to tailor educational resource to a specific region or location!
* (Health Education) Assume you have educational resources about a skin disease in different languages, The skin disease looks different on white skin or darker skin and the disease is cause by different risk factors in different regions. If a mobile devices requires educational resources for a specific geolocation, a specific language and a specific skin type. How would you provide a tailored educational resource for that request of a learner who wants to know about the disease? What are the challenges if capacity building in the health domain is provided with Open Educational Resources. How can communities adapt OER to their local requirements and constraints and have at the same time an additional quality assured version of OER course which was quality assured e.g. by the national public health agency (see also public-private versioning).
* (Real World Lab) Explore the concept of a Real World Lab and explain why tailored Open Educational Resources are required to support multiple different Real World Labs in different regions that need to adapt the learning resources to the location of learning environment.
# Open Educational Resources/Open Courses

Open course lists.
* Source
* Canvas Network
* Carnegie Mellon Open Learning Initiative
* Coursera
* edX
* FutureLearn
* iversity MOOCs
* JHSPH Open Courseware
* Khan Academy
* Lumen Learning
* MIT Open Courseware
* Modern States
* Open Course Library
* Open Education Consortium
* Open Michigan
* Open New York
* Open Yale Courses
* Stanford Open Learning Initiative
* UCI Open
* Udacity
* Wikiversity Courses
# Open Educational Resources/Open Textbooks

Open textbook lists.
* Source
* 2012 Book Archive
* Affordable Learning Georgia
* Bay College OER
* BCcampus Open Textbooks
* Bookboon
* California Open Online Library for Education (COOL4ED)
* Center for Open Educational Resources and Language Learning
* CK-12
* Community College Consortium
* Directory of Open Access Books
* FreeTechBooks
* Galileo
* InTech
* Lake Tahoe Community College CCC OER List
* LibreTexts
* Literature in Context: An Open Anthology of Literature in English, 1400-1925
* Mason OER Metafinder
* Michigan Open Textbook Project (3-12)
* National Academies Press
* NCBI (science and health)
* OASIS
* OER Commons
* Open Oregon
* OpenStax
* OpenTextBookStore
* Open Textbook Library
* San Bernardino Valley College
* Saylor Academy
* Siyavula (4-12)
* University of Hawaii Pressbooks
* University of South Florida Scholar Commons
* Wikibooks
# Localization/Machine Translation

Machine translation, sometimes referred to by the abbreviation MT is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another.

## Readings

* Wikipedia: Machine translation

## Learning Task

* (Install and Test Machine Translation) Install the Open Source Software Marian NMT and establish a translation process on you machine.
* (Tanslation and Privacy) Analyse free transtlation tools like DeepL, Google Translate, ... and analyze the domains in which translation is required and privacy is important.
* (News and Media Analysis) Explain the role of translation of machine translation for news and media analysis on the web and use that as input for big data analysis.

## Other Tools

* MarianNMT Neural Machine Translation
# Localization/Resources
## Institutes and Courses
### USA

Kent State University Institute for Applied Linguistics
Middlebury Institute of International Studies at Monterey Sales & Solutions Development (MA level) Computer Assisted Translation (Non-credit -- Professional Development) Website Translation & Localization (Non-credit -- Professional Development)
NYU School of Professional Studies Intro to Software & Website Localization (MA level)
University of Maryland, Office of Extended Studies Intro to Software & Website Localization (MA level)
University of Washington, USA Certificate in Localization: Customizing Software for the World

### UK

Localization Workshops Localization Workshops

### GERMANY

Anhalt University of Applied Sciences (Hochschule Anhalt) Sotwarelokalisierung

### CZECH REPUBLIC

Masaryk University Brno Department of English and American Studies, Faculty of Arts
# Localization/Localizability
### Resource localizability

* Separation of code and localizable resources

### Translatability

* Avoiding concatenations, commenting placeholder names, providing context, etc.

### User interface readiness

* Layout considerations, avoiding truncations and clippings
* Mirroring

### Common Localizability Issues

* Hardcoded text: Hardcoding is the practice of embedding data directly into the source code. In SW localization, hardcoded text is the content that cannot be modified without changing the source code.
* Overlocalization: When some text has been translated where it should not have been. For example, in one instance the name of a button has been translated and it has been left in English in another instance.
* String dependencies: When the functionality of an application depends on identical strings placed in different parts of the app. These strings must match or the application will not work.
* Resource constraints: Elements in localizable strings that can influence product functionality, such as special characters.
* Strings concatenation: When two or more character strings are joined directly to form one string, usually at run time.
Here is some information on what strings concatenation is: http://www.pythonforbeginners.com/concatenation/string-concatenation-and-formatting-in-python When translating concatenated strings, the translator does not necessarily have the information that two (or more) strings go together. This can lead to mistranslation as some words are translated differently depending on the context. In addition, the translated text does not necessarily follow the source text in terms of word order. So, in English, you might find “Hello World !” (been two strings “Hello” and “World” in that order) but in another language “World !” might have to be placed before “Hello”.
* Usage of variables: As for the concatenated strings, the usage of variables (or placeholders) are usually not a good idea to use if the text will need to be translated as word order and grammatical rules are different depending on the language. Badly designed placeholders do not provide enough information to the translators, so it is suggested to use unique placeholders and describe the values of each one.
* UI layout: Text expansion during translation poses a design challenge in localization. UI strings in English can expand up to 300% when translated into some languages, in many cases increasing in the number of words used in sentences. If the UI layout is not flexible and does not allow for text expansion, it could cause string truncations, and information is lost.
# Informal learning activities/STwMo

Things and Bitsː M⇒ O__  O ther initialsː   Ac  Df
 Gi  Jl
(«»Mo⇓⇓)
 Pr
 Su  Vz
• mach (speed)
 machan (blind)
 mackinaw (coat)
 mafic (rocky)
 maillot (togs)
 malae (shrine)
 maleic (acid)
 malic (acid)
 malm (rocks)
 malonic (acid)
 maltha (tar)
 manchet (bread)
 manège (stables )
 mantel (shelf)
 maraca (rattle)
 marae (shrine)
 marana (crêpe)
 marc (pomace) marl (soil)
 mark (13/4 )
 marline (rope)
 mascle (◊)
 mastic (resin)
 matha (monastery)
 matin (a.m. )
 maud (plaid )
 maund (weight)
 maxon (excitation)
 mazer (bowl )
• melton (cloth) menhir (stone↑)
 menthol (C10 H20 O)
 merlon (battlement⊂)
 mesa (plateau)
 mesic (moist)
 meson (subatomic)
 messuage (site)
 metol (chemical)
 mezcal (grog)
 meze (snack)
• midi (midcalf)
 milter (mail f–)
 minim (½note)
 minium (pigment )
 mirbane (perfume)
 mirin (condiment)
 miso (seasoning)
 mitis (iron )
 mixte (bike)
• molal (strength)
 molly (fastener) monad (unit)
 monde (orb)
 mons (mountain)
 morion (helmet) morro (∩)
 mortise (slot)
 motte (~bailey)
 moulin (glacial)
• mukluk (boot)
 mulch (4 garden)
 mulct (fine) muleta (4 bullfight)
 muntin (bar)
 murrey (stain)
 musette (bagpipe)
Things and Bitsː N__
• nacelle (housing)
 nachos (food)
 nacre (pearl)
 naira (money)
 naker (drum)
 naos (chamber)
 nappe (rock)
 nard (oil+ )
 natron (mineral)
 nematic (liquid crystal)
 neper (ratio)
 neral (citral) neritic (coastal)
 neroli (oil)
 névé (snow)
 newel (post)
• nife (NiFe )
 ninon (fabric)
 nitid (bright)
 nival (snow y)
• noil (fibre)
 nome (∈elliptics)
 nonce (maybe )
 nones (moon )
 noose (loop)
 noria (water⇑)
 nova (@ star)
• nullah (ravine )
 numero (№)
Things and Bitsː O__
• oast (kiln)
 obelus (÷)
 octad (8)
 oculus (eye)
• offal (food)
 ogham (αβ)
 ogive (nose)
• oleo (marg)
 olla (jar)
 ombre (cards)
 oolong (tea)
• orgeat (syrup)
 oriel (window)
 orihon (book)
 ormolu (gilt)
 orogeny (uplift)
 orphrey (embroidery)
 orpiment (pigment)
 orrery (clockwork)
• osmium (metal)
 osnaburg (fabric)
 otto (attar)
 ovolo (molding)
 oxgang (area)
 oxter (armpit)