OpenLLM-France/wikimedia huggingface dataset:
# Lojban/Emotions

The following words are as they are used as selbri- not cnivla
Happy
[Gleki]
Holy
[Censa]
Sacred
[Censa]
Sad
[Badri]
Depressed
[Badri]
Love
[Prami]
Hate
[Xebni]
Beautiful
[Melbi]
# Lojban/Le ninmu cu te dunda le ninmu le gerku
## Lojban

le ninmu cu te dunda le gerku
.uinaicaidai zo'e na prami le ninmu .i .a'ucu'idai le ninmu cu na junri zo'e .i .u'icu'idai le ninmu na cmila .i .iucu'idai le ninmu cu na prami zo'e
.i .a'odai le nanmu cu klama le ninmu la kentykis. .i .i'odai le nanmu cu dunda le gerku le ninmu .i .oidai le nanmu cu klama la kentykis. le ninmu
.i .uiru'edai le gerku cu prami le ninmu .i .a'uru'edai le ninmu cu junri le gerku .i .u'idai le ninmu cu cmila .i .iucaidai le ninmu cu prami le gerku

## English

The Woman Receives a Dog
Sadness! The woman is not loved. Disinterest! The woman doesn't have a gravity for anything. No amusement! The woman doesn't laugh. No love! The woman doesn't love.
Hope! The man goes to the woman from Kentucky. Appreciation! The man gives the dog to the woman. Complaint! The man goes to Kentucky from the woman.
A little happiness! The dog loves the woman. A little interest! The woman has a gravity for the dog. Amusement! The woman laughs. Lots of love! The woman loves the dog.
# Lojban/Numbers

The numbers zero to nine in Lojban:
* 0=no
* 1=pa
* 2=re
* 3=ci
* 4=vo
* 5=mu
* 6=xa
* 7=ze
* 8=bi
* 9=so
The hexadecimal numbers from A to F:
* A=dau
* B=fei
* C=gai
* D=jau
* E=rei
* F=vai
Numbers 10 to 999 are constructed by combining these digits without spaces: pano is 10, vore is 42, binoso is 809, and so on.
Numbers 1000 onward may have a comma or period in them. This too is represented in Lojban, as ki'o, which is used with spaces. Thus 7530 may be ze ki'o mucino instead of zemucino.
When there is a three-zero sequence (000) after the comma, ki'o may be used to represent it preceded by the comma. Thus 1000 may be pa ki'o intead of panonono. This is also used to construct larger sequences, such as ki'o ki'o (million) ki'o ki'o ki'o (billion) and so on.
Decimals are handled with pi, which is quite simply a decimal point in the form of a word. cipivo is 3.4, sopixa is 9.6, etc.
The constant Pi (about: 3.14159), is expressed in Lojban as pai.
To use numbers as sumti, the article li is used. So li muvozeci is "the number 5473." To say more than one number without them combining to one number, insert li before each one. so bi ze is 987, whereas li so li bi li ze is "nine, eight, seven."
# Locksmithing

This how-to guide describes the techniques of lock picking.
Lock picking is an essential skill for a locksmith. It can also be an interesting skill to learn and can be useful to the householder. Lock picking is the ideal way of opening a lock without the correct key, while not damaging the lock, allowing it to be rekeyed for later use. This is especially important with antique locks that would be impossible to replace if destructive entry methods were used.
Usually it is possible to bypass a lock without picking it. Most common locks can be quickly and easily opened using a drill, bolt cutters, or a hydraulic jack. The hasp, door, or fixture they are attached to can be cut or broken. But lock picking is more rewarding than brute force.

## Content

* Techniques
* Key Impressioning
* Tools
* Legal Status
* Further Reading
# Locksmithing/Key Impressioning
## Key impressioning
### Concept

Contrary to what one might think upon hearing the term, key impressioning does not have anything to do with silly putty, molds, or plaster of paris. Instead, you start with a key blank and use the following method to arrive at a functioning key for a lock.

### Method
#### Tools required

    Proper key blank that will fit the lock
    Vise-grip pliers
    Rat tail and pippin files (Swiss cut #4 variety)
    Skilled eyes
Clipping the vice grips on the key blank, you take your file and polish the top of the key (the part of the key that the pins come into contact with your pins. (Before starting the impressioning, it is generally good to count the number of pins in the lock with a hook pick, thus helping choose the correct sized blank.) You put the key into the keyhole using the vice grips, and gently turn it thus binding the key, then you jiggle the key up and down. You pull the key blank out and look at it. Initially you are looking for the perpendicular scrapes that the pins of the lock will have left on the key. File a few thousandths of brass off the key with your pippen or rat tail file (usually 4 total swipes of the file).
You repeat this process. Be very careful to only file if you see a little dimple in the key grooves that you are starting to file on the key. When you have filed enough material from the blank, you will have approximated the cut of the appropriate key and the lock should open when the key is turned.
This method is exceptionally good because high-security drivers (if they are grooved or mushroomed) are made irrelevant. This method works fantastically well on car doors and other wafer locks. To impression wafer locks, you should sharpen both sides of the key (only if the key is two sided); then the wafers will slice a nice little groove into your key.
This process could take 15 - 75 minutes based on 1) the skill of the locksmith and 2) the difficulty of the lock.
Please note, this method is more time consuming and difficult on locks with sidebars (e.g., Medeco, mul-t-lock, GM cars)
# Preface

This text is not about ready patterns, but a guide as to how you can produce your own patterns. It is my hope that it will be a useful reference for many years to come, regardless of changing fashions.
I have organized the text with the easiest things first. This is so in the chapter on Knitting samples, and in the following text about knitting from specific measurements, which I have divided into two chapters. The first of these, Knitting to measure, is for those who just want to concentrate on knitting straightforward jumpers in the easiest way possible, whilst in the later chapter, Garment patterns, I have written about fitting methods and how to create a basic pattern from that, firstly, showing the easiest method of doing this, and later telling how from the basic pattern, you can make alterations and adjustments. In this way, it is my hope that there is something for everyone. You may then use whatever part of it you want to use, but a condition for understanding the text is that you have read the chapter about Knitting samples, because it is a basic idea behind the whole text that you use your own knitting sample for all measurements.
But of course, there are many ways of making things, and the methods described should be conceived just as suggestions.
I hope that with this book, I can spare someone for making all the same mistakes as I have made myself during the 40 years that I have been machine-knitting.
Many thanks to my son Agner who has helped me with illustrations and advice and published this on the web, and to my son Kåre who has made an admirable effort to help with the translation.
This book was originally written in Danish (). The English translation has been carried out mainly by my son Kåre and other family members who have helped with translation and linguistic corrections. However, it has been difficult to find correct translations for many technical expressions, and I apologize for any misleading translations. I would be happy if somebody will correct and improve the English translation.
August 2003, Gudde Fog.

### About the author

Gudrun Benedicte Fog, called Gudde, was born in Copenhagen on September 29, 1923, and died on June 10, 2014. She was married to professor Bjarke Fog.
This book is published in April 2009 by her son Agner Fog.
Introduction →
# Examples of patterns
## Continuous patterns by 24 stitches
## Single figures

File:MachineKnittingPattern54.gif

## Other continuous patterns

← Problems · Links →
# Statistical machine translation
## Language models

Language models are used in MT for a) scoring arbitrary sequences of words (tokens) and b) given a sequence of tokens, they predict what token will likely to follow the sequence. Formally, language models are probability distributions over sequences of tokens in a given language.

### Character-based models

Recently, it was shown that it is possible to use sub-words, characters or even bytes as basic units for language modelling. There are a few events focused particularly on such models and in general, processing language data on sub-word units, e.g. SCLem 2017.
# Machine Learning/Bank Fraud Detection

There are many applications for machine learning and binary classification, and one of these is the detection of illegitimate transactions on ATMs at banks.
* True positive: The action was fraudulent, and the algorithm correctly identified the action as such.
* False positive: The action was not fraudulent, yet the algorithm wrongly identified the action as such. (An innocent user was wrongly denied the service.)
* True negative: The action was not fraudulent, and the algorithm correctly identified the action as being legitimate.
* False negative: The action was a fraud, but the algorithm misclassified the action as legitimate. (A bad-faith user was wrongly granted the service.)
The recall is defined as number of true positives divided by the total number of true positives plus false negatives.
# Machine Translation

Machine translation (MT) is a discipline within Natural language processing (NLP) or more broadly Artificial intelligence (AI). It is one of the oldest computationals tasks: the first algorithms for MT were run on the first computers alongside with algorithms for cryptography and physical simulations as early as in 1940s. Shortly after, MT was dominated by rule-based approach which was replaced in 1990s by statistical approach only to be replaced by neural network methods in 2010s.
This book is a guide to the Machine Translation. It is intended for everybody interested in how machine translation works, its history, limitations, quality and the current trends in the field.
This book is organized as follows:
* Introduction
* History
* Rule-based Machine Translation
* Statistical-based Machine Translation
* Neural Machine Translation
* Evaluation of Machine Translation
# MariaDB/Features

The features that are discussed in this page have been developed for MariaDB and may not be present in MySQL.

## Microseconds precision

SHOW PROCESSLIST, INFORMATION_SCHEMA.PROCESSLIST and the Slow Log now have a microsecond precision.
A microsecond is a unit of time equal to one millionth (10$^{-6}$) of a second.

### SHOW PROCESSLIST

In MariaDB, an extra column `TIME_MS` has been added to the INFORMATION_SCHEMA.PROCESSLIST table, as well as to the output of SHOW FULL PROCESSLIST. This column shows the same information as the column `TIME`, but in units of milliseconds with microsecond precision (the unit and precision of the `TIME` column is one second).
The value displayed in the `TIME` and `TIME_MS` columns is the period of time that the given thread has been in its current state. Thus it can be used to check for example how long a thread has been executing the current query, or for how long it has been idle.
In MariaDB the `TIME` column and the `TIME_MS` column are not affected by any setting of @TIMESTAMP. This means that it can be reliably used also for threads that change @TIMESTAMP (such as the replication SQL thread).
The `TIME` column of SHOW FULL PROCESSLIST and INFORMATION_SCHEMA.PROCESSLIST can not be used to determine if a slave is lagging behind. For this, use instead the Seconds_Behind_Master column in the output of SHOW SLAVE STATUS.
The addition of the TIME_MS column is based on the microsec_process patch, developed by Percona.

### Slow Log

The Slow Log includes details of execution plan and microsecond-precision resolution.
This addition is based on the microslow patch from Percona.

## Performance

MariaDB's code has several optimizations which have been made after the fork has been launched.
Some speed enhancements are:
* CHECKSUM TABLE is faster;
* performance improvements for common cases of character set conversion;
* test suite speedups.
The list is not complete.
# MariaDB/Storage Engines

MariaDB includes all the Storage Engines which are included by MySQL 5.1, except for ClusterDB, IBMDB2I and Example.
In addition, it includes some more Storage Engines.

## Aria

The Aria storage engine is compiled in by default in MariaDB 5.1 and it is required to be 'in use' when mysqld is started.
Additionally, internal on-disk tables are in the Aria table format instead of the MyISAM table format. This should speed up some GROUP BY and DISTINCT queries because Aria has better caching than MyISAM. The inclusion of Aria is one of the differences between MariaDB 5.1 and MySQL 5.1.

## PBXT

The PBXT storage engine is included in the MariaDB source and binaries by default.
PBXT versions in various releases are:
version 1.0.11 in MariaDB 5.1.47 version 1.0.08d in MariaDB 5.1.44b PBXT is a general purpose transactional storage engine. PBXT is fully "ACID" compliant, which means it can be used as an alternative to other MariaDB transactional engines (such as XtraDB or InnoDB).
PBXT features include the following:
* MVCC Support: MVCC stands for Multi-version Concurrency Control. MVCC allows reading the database without locking.
* Fully ACID compliant: This means that all transactions are: atomic, consistent, isolated and durable.
* Row-level locking: When updating, PBXT uses row-level locking. Row-level locking is also used during SELECT FOR UPDATE.
* Fast Rollback and Recovery: PBXT uses a specialized method to identify garbage which makes "undo" unnecessary. This make both rollback of transactions and recovery after restart very fast.
* Deadlock Detection: PBXT identifies all kinds of deadlocks immediately.
* Write-once: PBXT uses a log-based storage which makes it possible to write transactional data directly to the database, without first being written to the transaction log.
* Referential Integrity: PBXT supports foreign key definitions, including cascaded updates and deletes.
* BLOB streaming: In combination with the BLOB Streaming engine PBXT can stream binary and media directly in and out of the database.
* PBXT will not take any resources (disk space or CPU processing) until you create your first PBXT table.

## XtraDB

XtraDB is a fork of InnoDB created and maintained by Percona.
XtraDB is completely compatible with InnoDB. The InnoDB codebase is constantly updated when new InnoDB versions are released. Percona applies to it several patches, which fix known bugs and add new features.
XtraDB's documentation: http://www.percona.com/docs/wiki/percona-xtradb:start
In most builds, InnoDB is disabled and XtraDB is instead installed under the name InnoDB. This means that if you specify InnoDB you actually get XtraDB.

## FederatedX

FederatedX is based off of the Federated Storage Engine, which is no longer maintained. It is an attempt to move the Federated Storage Engine forward to fix bugs, add new features and develop new concepts that are easier to achieve as a pluggable storage engine.
FederatedX at Launchpad: https://code.launchpad.net/federatedx
# Marijuana Cultivation

Marijuana Cultivation Wikibooks version
PDF Pre-Printed
* Marijuana Cultivation
* Introduction –
* Fundamentals –
* Seedlings –
* Vegetative Growth –
* Cloning –
* Sexing –
* Flowering –
* Harvesting –
* Curing –
* Producing Seeds –
* Pests and Pest Control –
* Common Plant Problems
# MATLAB Programming/Psychtoolbox/GetMouse AllowMultipleHack

A simple hack I made to get around the limitation on the number of mice. It gets around the problem by ignoring that there are multiple mice.
This is useful if you have a trackpad on a laptop and need to use an external mouse.
# MATLAB Programming/Psychtoolbox/Howto get Psychtoolbox pre-releases & bug fixes
## Setup Instructions

* Install subversion client software from: http://metissian.com/projects/macosx/subversion/
* Download the m-file DownloadPsychtoolbox.m
* This file is the Psychtoolbox-Installer.
** Save the installer into your Psychtoolbox path.
** Change Matlab working directory to a folder were you want to download the latest release of PTB.
** Enter either DownloadPsychtoolbox('beta') or DownloadPsychtoolbox('stable') , depending which flavor of Psychtoolbox you want to use.

## Description of Stable and Beta

'beta' gives you the equivalent of my past pre-releases: Early access to bug-fixes, enhancements and new features. Tested and found to be working properly on our own machines, but not yet sufficiently tested by real users in real applications.
'stable' consists of former 'beta' releases that have received additional real- world testing by end-users, so it is considered final code that will be released in the next upcoming official release.
Obviously, 'stable' releases will have a much longer delay, until features are added or bugs are fixed -- it's your choice.
As of today, 'beta' contains an improved DrawText function and experimental support for Quicktime movie playback, as well as new functions for transformations like scaling, translation and rotation. MacOS-X 10.3.9 or later + Quicktime-7 is required for 'beta' to work. MacOS-X 10.2 and earlier are not supported anymore.
'stable' is identical to the 1.0.6 release and will stay that way for a while, until all the new features in beta have received sufficient testing by real users and more refinements and polishing by us.
What else? You need to perform this procedure only once. After that, you can simply use the new command 'UpdatePsychtoolbox' to keep your copy of PTB up to date with the latest changes in the 'beta' or 'stable' release whenever you want.
# MATLAB Programming/Psychtoolbox/KbCheck

A changed kbcheck that will check all connected keyboards and will sort out some invalid devices that appear to be keyboards.
It should be noted that this script will stop and return on the first keyboard that has a key that is pressed. Perhaps this could be modified so that the sum of all checked keyboards is returned and so if you are pressing a key on one keyboard you can also be pressing another key on another keyboard and get both responses.
# MATLAB Programming/Psychtoolbox/How to install the OS X Psychtoolbox Source on OS X

This is the steps I took to get Psychtoolbox to compile on my machine. I am sure this is probably not the best way (being that I was just winging it) but it might help you get going. Most are just a series of hacks and work arounds trying to get it all to compile without really knowing what I was doing. If anyone wants to improve these steps, feel free. --RobKohr 22:23, 26 January 2006 (UTC)
* Download the source and unzip it somewhere. Mostly this will not be used, since the version management system will be used to get the newest source, but it seems some of the stuff only exists in the source folder on the website.
* Follow these instructions to get the most up to date version of PTB
* svn checkout svn://svn.berlios.de/osxptb/trunk SOME_OUTPUT_PATH
* open the project file (located in PsychSourceGL/Projects/MacOSX/PsychToolbox/PsychToolbox.xcodeproj) with xcode 2.2 (project may need to be converted)
* There will be a number of red files. Do a get info on them and try to fix the file names and folder names in the finder to match the paths in the project view.
** Start with the files in IO Warrior libs. Rename the file folder appropriately
** For a bunch of them I had to go to PsychSourceGL/Source/Common/PsychSound/StaticOpenALLib/ and unzip a file, and drag the contents of the zip to the appropriate directory
** Some of the stuff in Cohorts need to be in the Resources folder and vice versa. Just take a look at the paths to make sure it is all in the right places.
* Download and install the CHUD framework
** Set the path for the CHUD.framework to /System/Library/PrivateFrameworks/CHUD.framework
* Put Development folder in PsychSourceGL/Projects/MacOSX/PsychToolbox/build/ . For some reason this is only in the source code you download from the psychtoolbox website.
* Go to terminal and type ln -s /Applications/YOUR_MATLAB_FOLDER /Applications/MATLAB704 ln -s /Applications/MATLAB704/toolbox/Psychtoolbox /Applications/Psychtoolbox
* Change path for QuickTime framework -> /System/Library/Frameworks/QuickTime.framework
# MATLAB Programming/Psychtoolbox/Screen

For all commands in a single screen go to Psychtoolbox:Screen Commands.
Here's a list of all commands that you can issue using the screen function.
* BlitImage255
* BringMATLABToFront
* BringWindowToFront
* ClearScreen
* Close
* CloseAll
* CloseScreen
* Computer
* CopyWindow
* CopyWindows
* DrawLine
* DrawOval
* DrawPoly
* DrawRect
* DrawText
* FillArc
* FillOval
* FillPoly
* FillRect
* FrameArc
* FrameOval
* FrameRate
* FrameRect
* Gamma
* GetClut
* GetFrontWindow
* GetImage
* GetImage255
* GetMATLABWindow
* GetWindowByTitle
* GlobalRect
* IsOffscreen
* MATLABToFront
* MoveWindow
* OpenOffscreenWindow
* OpenWindow
* PixelSize
* PixelSizes
* Preference
* PutColorImage
* PutImage
* Rect
* Screens
* SelectMATLAB
* SetClut
* SetClutQ
* SetDrawingRegion
* SetGamma
* TextFace
* TextFont
* TextMode
* TextSize
* TextStyle
* TextWidth
* UsageWarnings
* VideoCard
* WaitBlanking
* WaitVBL
* WindowKind
* Windows
* WindowScreenNumber
* WindowTitle
* WindowToBack
* WindowToFront