OpenLLM-France/wikimedia huggingface dataset:
# Data Mining Algorithms In R/Packages/CCMtools/learn.and.project.clusters
## Description

This function (1) learns how to attribute days to clusters based on the sequence of predictors and associated sequence of clusters.

## Usage

learn.and.project.clusters(DataCalibration, DataToBeProjected, cl.calibration, allocmet, Datas.Calibration)

## Arguments

   * DataCalibration Values of the predictor variable for the calibration set (can be a matrix).
   * DataToBeProjected Values of the predictor variable for the projection set.
   * cl.calibration Numerical vector corresponding to the sequence of clusters (i.e., calibration set).
   * allocmet Name of the attribution method.(The 12 possibilities are: "Euclid.dist.A", "Euclid. dist.w1", "Euclid.dist.w2", "CART.A", "CART.w", "CART.A.and.w", "knnA", "knnA10", "Gaussian.A", "Gaussian.w", "MM", "MMw")
   * DataS.Calibration Values of other predictor variables for the calibration set. This is sometimes needed, according to the attribution method (allocmet) to be used (needed for "Euclid.dist.w1", "Euclid.dist.w2", "CART.w", "CART.A.and.w", "Gaussian.w", "MMw").

## Value

Returns a list with two objects:
   * cl The sequence of clusters defined from the predictors for the projection set.
   * tot Number of elements per cluster for projection set.

## Author

M. Vrac (mathieu.vrac@lsce.ipsl.fr))
# Data Mining Algorithms In R/Packages/CCMtools/CCM
## Description

This function performs a simultaneous clustering of two matched datasets (e.g., daily local- and large-scale atmospheric data), such that each cluster maximises the correlation between the two datasets. This clustering is based on a mixture of canonical correlation analyses (CCAs).

## Usage

CCM(Nc, NS, DataA.tbc,DataS.tbc,NN, DataStation, init="block", ITmax=15, rq=0)

## Arguments

   * Nc Number of clusters required.
   * NS Number of locations (i.e., weather stations) for the local-scale time series.
   * DataA.tbc Dataset corresponding to the large-scale data to be clustered. This is a matrix
M*NN, whereMcorresponds to the number of large-scale locations (e.g., GCM or RCM grid cells), and NN to the length of the time series (e.g., number of days). Note that this matrix is used in CCM without any transformation. For example, if a principal component analysis (PCA) has to be performed, this must be done BEFORE entering CCM.
   * DataS.tbc Dataset corresponding to the local-scale (station) data to be clustered. This is a
matrix NS*NN. Similarly as for DataA.tbc, note that this matrix is used in CCM without any transformation, and that if a PCA has to be performed, this must be done BEFORE entering CCM.
   * NN Length of the time series (e.g, number od days for daily time series).
   * DataStation Local-scale (stations) dataset on which the information criterion will be calculated.
It usually is the same as DataS.tbc but can be different according to the application (e.g., DataS.tbc is the result of a PCA) or to the goal to reach.
   * init Initializing method for the clusters. Six methods are available:
- "block": Blocks initialization (the default) - "12345": Each day is alternatively allocated to a cluster (For example, if 3 clusters required, day1 goes to C1, day2 to C2, day3 to C3, day4 to C1, day5 to C2, etc.) - "Kmeans": Initialization by the k-means algorithm - "Mixtn": Same a "12345" but for length 12 (instead of length 1) - "EMw": Initialization by the EM clustering algorithm applied onto the w (i.e., large-scale) canonical variates resulting from a CCA performed between DataA.tbc and DataS.tbc - "EMvw": Same as "EMw" but EM is applied onto both v (local) and w (largescale) canonical variates.
   * ITmax Maximum number of iterations (default is 15) is the algorithm di not converge.
CWGLI 3
   * rq Value (of the local-scale variable of interest) on which the information criterion
(IC) is calculated (default is rq=0). rq can be the 90th percentile of the data. In that case, CCM will try to find clusters for which the extremes are well discriminated. A high IC means a good discrimination (in terms of local-scale variable) between the clusters.

## Details

For details about the CCM method, see the reference below. M. Vrac, P. Yiou. "Weather regimes designed for local precipitation modelling: Application to the Mediterranean basin". JGR-Atmospheres, doi:10.1029/2009JD012871, 2010

## Author(s)

M. Vrac (mathieu.vrac@lsce.ipsl.fr))

## See Also

* Info.Criterion
# Data Mining Algorithms In R/Packages/CCMtools/Info.Criterion
## Description

This function computes the Information Criterion (IC) of a clustering result.

## Usage

Info.Criterion(NS, DataS, r, totCL, Nc, cl)

## Arguments

   * NS Number of locations (i.e., weather stations) for the local-scale time series on which IC is calculated.
   * DataS Dataset corresponding to local-scale (station) data on which IC is calculated. This is a matrix NS*NN, where NN is the number of days (i.e., length of the time series).
   * r Value for which the IC is calculated (see details).
   * totCL Vector of numbers of elements (e.g., days) in each cluster.
   * Nc Number of clusters.
   * cl Vector containing the sequence of clusters (length(cl) is NN).

## Author

M. Vrac (mathieu.vrac@lsce.ipsl.fr))

## See Also

* CCM
# Data Mining Algorithms In R/Packages

In this section, we'll discuss some R packages that are related to Datamining.

## Contents

* RWeka
* gausspred
* optimsimplex
# Data Mining Algorithms In R/Packages/CCMtools/CWGLI
## Description

This function calculates the Conditional Weighted Global Log-Intensity (CWGLI) cost function for precipitation. This error is supposed to be due to a misclassification (i.e., the elements should be classified according to sequence cl.check, while they are in practice allocated to the clusters according to the sequence cl.proj).

## Usage

CWGLI(cl.check, cl.proj, DataS.check)

## Arguments

   * cl.check Reference sequence (i.e., numerical vector) of clusters (i.e., this is the sequence we should have).
   * cl.proj Sequence of clusters in practice.
   * DataS.check Precipitation data time series

## Details

For details about this cost function, see the reference below. M. Vrac, P. Yiou. "Weather regimes designed for local precipitation modelling: Application to the Mediterranean bassin". Submitted, JGR-A, 2009

## Value

Returns a numerical vector corresponding to the CWGLI cost function

## Author

M. Vrac (mathieu.vrac@lsce.ipsl.fr))

## See Also

* DI
* WGP
# Data Mining Algorithms In R/Packages/CCMtools/DI
## Description

This function calculates the Daily Intensity (DI) cost function for precipitation. This error is supposed to be due to a misclassification (i.e., the elements should be classified according to sequence cl.check, while they are in practice allocated to the clusters according to the sequence cl.proj).

## Usage

DI(cl.calibration, cl.check, cl.proj, DataS.Calibration, DataS.check)

## Arguments

   * cl.calibration Sequence of clusters for time period 1 (TP1)
   * cl.check Reference sequence (i.e., numerical vector) of clusters (i.e., this is the sequence we should have) for time period 2 (TP2).
   * cl.proj Sequence of clusters in practice for TP2.
   * DataS.Calibration Precipitation data time series for TP1.
   * DataS.check Precipitation data time series for TP2.

## Details

For details about these cost functions, see the reference below. M. Vrac, P. Yiou. "Weather regimes designed for local precipitation modelling: Application to the Mediterranean bassin". Submitted, JGR-A, 2009

## Value

Returns a list with arguments:
   * DI Daily Intensity (DI) error costs, depending on station s and day d.
   * MDI Means DI costs, depending on station s.
   * RMDI Regional MDI providing a global (spatial and temporal) view of the DI error
cost.

## Author

M. Vrac (mathieu.vrac@lsce.ipsl.fr))

## See Also

* WGP
# ERP Internals/Glossary/Adjustment

Most modules have two or three major transactions that account for the large majority of the transactions. Adjustmens refer to the transactions that occur when things do not go as expected (e.g. goods are returned or damaged in shipment).
# ERP Internals/Glossary/Analytics

Programs that analyze the enterprises's data and present it in a form that facilitates better and faster decisions. Contrast with Business Intelligence.
# ERP Internals/Glossary/Asset

Something of value that the enterprise owns. Cash and Inventory are assets. See also Liability and Equity.
# ERP Internals/Glossary/Ad Hoc

An Ad Hoc report is created for a single use rather than stored and reused.
# ERP Internals/Glossary/Advanced Planning and Scheduling

A method of optimizing production using the Master Production Schedule while taking into account constraints on labor and resources such as machinery.
# ERP Internals/Glossary/Accounting Equation

The fundamental principle on which accounting is based.
Assets = Liabilities + Equity
See Credit and Debit.
Every financial transaction requires that the total of the debits is equal to the total of the credits.
# ERP Internals/Glossary/Accural Basis

A method of accounting in which income and expenses are recognized when they are incurred rather than when they are dealt with. Most large company use accrual accounting. Contrast with Cash Basis.
# ERP Internals/Glossary/Activity-based Costing

A method of allocating costs in accounting.
# ERP Internals/Glossary/Amortization

The process of paying off a debt through payments that combine interest and payments of principal.
# ERP Internals/Glossary/Application Programming Interface

A set of program calls that allow external programs to interact with the ERP without having access to the source code.
# ERP Internals/Modules/Service Management

Most businesses do repair and maintenance work on the products they sell. If the work is done under warranty, there is no charge to the customer. Service Management schedules on-site and depot service, defines product warranties, handles service contracts, and controls whether there are charges. Contrast this with Preventative Maintenance. Not every ERP package has a Service Management module although all the large ones do.
* Functions
* Reports

## Tables

Service Management shares the Customer group of tables with Accounts Receivable. It has a Contract table which contains one record for each service contract with each customer. Associated with this Contract table is a Transaction table which contains one record for every service performed under that contract.

## Data Exchange

Service Management creates invoices in Order Entry/Invoicing.
# ERP Internals/Modules/Share Manager/Functions/Find a Shareholder

This function is used when the user doesn't know the shareholder's number or name but does know some information about the shareholder. They enter what they know and the ERP displays all the shareholders that match the criteria. This function becomes more and more useful as the size of the enterprise increases
# ERP Internals/Modules/Share Manager/Functions/Maintain Module Information/Modify GL Distribution

The GL Distribution parameters contain every General Ledger account number that the Share Manager module can post to. This function allows the Systems Administrator or the Module Administrator to change those account numbers.
# ERP Internals/Modules/Share Manager

Share Manager keeps track of the business’s shareholders and pays dividends on shares when they are declared. It handles stock splits and allows both preferred and common shares. Only large ERP packages have a Share Manager module. Normally only a publicly traded company would use this module.
* Functions
* Reports

## Tables

The first group of tables consists of the Shareholder table which contains one record for every shareholder and the Shareholder Contact table which contains one record for every contact at each shareholder. There is at least one contact record for every shareholder and there can be several. The second table is the Transaction table which contains one record for every transaction (issue, sale, dividend, adjustment). There is at least one transaction for every shareholder and there can be many.

## Data Exchange

Share Manager sends transactions to Bank Reconciliation and General Ledger.

## Transactions

The first type of transaction issues one or more shares to a shareholder.
The second type of transaction pays dividends to a shareholder.
The third type of transaction records the purchase of one or more shares from a shareholder.
The fourth type of transaction increases the number of shares through a stock split.
The fifth type of transaction records miscellaneous adjustments to the stock record.
# ERP Internals/Modules/Share Manager/Functions/Maintain Module Information

Some parameters and data tables are used by every module. These are maintained by Systems Administration. But, every module has some parameters and/or data tables that it alone uses. Systems Administration can change this information but each module has a function "Maintain Module Information" that can change it as well. This allows segments of systems administration to be delegated to the senior person in charge of a particular module.
# ERP Internals/Modules/Share Manager/Reports

Share Manager generates the following reports:
* Checks
* Labels
# ERP Internals/Modules/Service Management/Functions

Service Management has the following functions:
* Maintain Contract Information
* Enter Transactions
* Maintain Module Information
# ERP Internals/Modules/Service Management/Functions/Maintain Module Information

Some parameters and data tables are used by every module. These are maintained by Systems Administration. But, every module has some parameters and/or data tables that it alone uses. Systems Administration can change this information but each module has a function "Maintain Module Information" that can change it as well. This allows segments of systems administration to be delegated to the senior person in charge of a particular module.
# ERP Internals/Modules/Share Manager/Functions

Share Manager has the following functions:
* Maintain Shareholder Information
* Find a Shareholder
* Enter Transactions
* Split Shares
* Declare Dividend
* Print Checks
* Print Labels
* Maintain Module Information
# ERP Internals/Modules/Shipping

Shipping receives orders from Warehouse Manager (picking) if there is no manufacturing involved or from Manufacturing if there is. It packs the goods, selects transportation to satisfy the customer's due date, and generates shipping documents such as labels, packing slips, and bills of lading. Customers can be notified electronically when the goods are shipped and Order Entry/Invoicing is notified so the order can be invoiced. Normally, Shipping and Receiving occur in the same physical location. Only large ERP packages have a separate Shipping module.
* Functions
* Reports

## Data Exchange

Shipping does not send or receive transactions to/from other modules.
# Discrete Mathematics/Introduction

The subject of mathematics is commited to rigorous reasoning. This book aims to raise your confidence in the manipulation and interpretation of formal notations, as well as to train you to solve problems that are fundamentally discrete: problems like chess, in which the moves you make are exact; problems where fields like calculus fail because there's no continuity; problems that appear frequently in games, puzzles, and computer science.
We hope you'll enjoy discovering discrete mathematics here, and we hope you'll find this a good reference for quickly picking up the details you may forget.
Notice to contributors: If you wish to contribute images of any kind that contains labels, please use the Arial font, italic, at 16pts for consistency.
# Advanced Microeconomics
## Table of Contents

* Preface
* Consumer Theory
** Preference Relations
** Utility Functions
** Demand Correspondence
** Revealed Preferences
** Utility Maximization
** Decision Making Under Uncertainty
* Production
* Market Structure
** Monopoly Pricing
** Duopoly Models
* Game Theory
** Strategies
** Equilibrium Concepts
*** Dominance and Iterative Deletion
*** Best Reply Functions
*** Nash
** Repeated Games
* Mathematics for Microeconomics
** Linear Algebra
** Homogeneous and Homothetic Functions
# English-Hanzi/Insulin

Special:search/insulin prefix:English-Hanzi/
Insulin is a substance that controls the blood sugar level.
胰岛素 是 一种 控制 血糖 水平 的 物质。
# English-Hanzi/Intestine

The intestine is the long tube that links the stomach and the anus.
肠脏 是 连接 胃脏 和 肛门 的 长管。
# English-Hanzi/Invertebrate

Invertebrate is a kind of animal that does not have a spinal column or backbone. It is the opposite of vertebrate, that means if an animal is not a vertebrate (fish, reptile, amphibian, bird, or mammal), it is an invertebrate.
无脊椎动物 是 一种 没有 脊柱 或 脊骨 的 动物。这 与 脊椎动物 相反，这 意味着 如果 动物 不是 脊椎动物（鱼类，爬行动物，两栖动物，鸟类 或 哺乳动物），它 就是 无脊椎动物。
# English-Hanzi/Iron

Iron is a mineral. It helps make red blood cells. Foods rich in iron include meat, beans, wholegrains, and dark green leafy vegetables.
铁 是 矿物质。它 有助于 制造 红血球。富含 铁 的 食物 包括 肉类，豆类，全谷类，和 深色 的 绿叶 蔬菜。
Tiě shì kuàngwùzhì. Tā yǒuzhùyú zhìzào hóngxuèqiú. Fùhán tiě de shíwù bāokuò ròulèi, dòulèi, quángǔlèi, hé shēnsè de lǜyè shūcài.
# English-Hanzi/Iskandar Puteri

Iskandar Puteri is a city in the state of Johor, Malaysia. It is also the seat of the state administrative center. It is under the jurisdiction of Iskandar Puteri City Council.
依斯干达公主城是马来西亚柔佛州的城市，也是州行政中心所在地，隶属于依斯干达公主城市政厅。
# English-Hanzi/Indian Ocean

Special:search/Indian Ocean prefix:English-Hanzi/
Special:search/ocean prefix:English-Hanzi/
Indian Ocean is an ocean that is surrounded by Africa, Asia, Oceania, and the Southern Ocean.
印度洋是一个被非洲，亚洲，大洋洲，和南冰洋包围的海洋。
# English-Hanzi/Indonesia

Special:search/Indonesia prefix:English-Hanzi/
Indonesia is a country mainly in Southeast Asia and partly in Oceania. Its population is 261 million. Its capital is Jakarta.
Indonesia 是 一个 主要 在 东南亚，部分 在 大洋洲 的 国家。它的人口是2.61亿。它的首都是Jakarta.
# English-Hanzi/Inflammation

Inflammation is a medical condition that a part of the body becomes red and swollen. It is caused by infection or injury.
炎症 是 身体 某 部分 变得 红肿 的 疾病。它由感染或受伤引起。
# English-Hanzi/Information

An information is the knowledge that is related to something.
资讯 是 与 某事物 有关 的 知识。
# English-Hanzi/Islamabad

Islamabad is the capital of Pakistan. Its population is 2 million.
Islamabad是Pakistan的首都。它的人口是200万。
# Emulation/On Xbox Series

By enabling developer mode on an Xbox Series X or Series X console, it is possible to install a variety of emulation software.
# Emulation/Other

Emulators exist for a number of niche computer systems.

## Mainframes

Sometimes it is desirable to emulate a mainframe computer. Hercules is a common emulator of IBM mainframes.

## Pinball

Visual Pinball is a source available pinball machine emulator.
# Emulation/PC
## About PC emulation

PC emulation is a general topic, and can essentially be split into two specialties.

### IBM Compatible and DOS

Much of the focus of hobbyist PC emulation lies in emulating the original IBM PC and compatibles. These systems sported a standard architecture, and typically had limited auxiliary capabilities, making their sound, graphical, and other capabilities simple. The IBM compatible library of software is mind-boggling and massive, ranging from the work of bedroom coders to multinational corporations and covering essentially every software genre that was around in the 1980's.
Emulation of DOS may also be desirable for running serious applications. Many obsolete machines and older systems rely on legacy software which will only run under DOS. These machines and systems are often still functional, but require a DOS based computer. DOS emulation may thus be desirable as a way to help bridge a transition to a more sustainable and contemporary system.

### Contemporary PC hardware

As the 1990's progressed, operating systems, PC hardware, and other factors lead to much more complex home computer systems. At the same time, this is perhaps one of the most commercially relevant fields of emulation. As devices based on ARM and RISC-V can not natively run programs which are specifically designed for x86 platforms, emulation of x86 PCs has become a desired feature.

## Common PC emulators

* QEMU - For emulating contemporary hardware.
* DOSBOX - For emulating IBM compatible PCs specifically.

## Alternatives to Emulation

Techniques with lower overhead are often preferable to full hardware emulation. This is especially true in cases where high performance is required.
* Virtual Machines can be used instead of full hardware emulation in many cases. This typically requires that the host system shares an architecture with the virtual machine.
* Compatibility layers like Wine and its fork Proton can often allow applications to run under unsupported operating systems.

## Read More

There is a Wikibook on QEMU.
# Emulation/PlayStation 2
## About PlayStation 2

The PlayStation 2 was a very popular game console in the 2000's. As a result it has a large library of historically and culturally important titles.

## PlayStation 2 Emulators
### Official

Some models of PlayStation 3 used emulation software to play PlayStation 2 games after PlayStation 2 hardware was removed and before the feature was removed in later revisions.

### PCSX2

PCSX2 is the premiere PlayStation 2 emulator. It is open source and runs under Windows, Mac, and GNU/Linux. PCSX2 is pluginless, which helps maintainability and usability. PCSX2 supports Vulkan and OpenGL.

#### AetherSX2

Semi-open port of PCSX2 for Android devices. Free (gratis).

### DobieStation

An open source and accuracy focused PlayStation 2 emulator. Very early in development as of 2021.

### Play!

Open source high level emulator for traditional computers and mobile. Uses OpenGL or Vulkan. Does not require a PS2 BIOS for operation, but compatibility is lower then some other emulators.

## System Files

The PlayStation 2 uses a BIOS, which emulators do not include. To use most PS2 emulators, one must dump a BIOS from a PlayStation 2 they own. There are some emulators which are able to run without a BIOS file.
# Emulation/On Macs

Back to Emulation Surprisingly, emulation on macs is fairly easy. There are lots of developers working on projects for mac, and emulation is a well supported task.

## Emulators

The best site for mac emulation software is http://www.emulation.net You will want to scroll all the way to the bottom of it where they have something that looks like finder and click on the emulation icon. It will fold out to reveal the different systems. (It took me a little while to figure this out :)

### Most popular emulators

* http://macmame.org/ - Mame for mac (plays arcade games)
* http://www.bannister.org/software/ RockNES
* http://chrisballinger.info/public/snes9x/ SNES9x
* http://stella.sourceforge.net/ -atari emulator
* http://www.daphne-emu.com/ - Plays laserdisc games including Dragons Lair and Space Ace

## Controllers

Now, if you are doing emulation or any gaming on a mac you should pick up a usb controller. It makes gaming a lot more fun then using the keyboard and mouse. A nice cheap one that I use is the Belkin Nostromo N45 Dual Analog USB Gamepad.

### Controller Set Up

Another thing that is REQUIRED if you are using a controller with a mac is The Gamepad Companion. It is a piece of software that will map keystrokes and mice to controllers, so if you set J to be the jumpkey for a game, you can set a button on the controller to be mapped to J, so pressing it will make your character jump. You should configure your gamepad to match the controls of MacMame and then configure your other emulators to match that. The reason is that there are so many different configureations of controllers possible for mame that its best to go with the default and then bring the other emulators into the same line.
One more note on controllers, you can have any number of them plugged in at once and have each one mapped to a different set of keys, so you can play multiplayer games.