OpenLLM-France/wikimedia huggingface dataset:
# C Programming/wchar.h/swprintf

swprintf is a C standard library function as defined in wchar.h and it's required header files are stdio.h and wchar.h. It has function signature as
n the signature of swprintf: s : it is pointer to the buffer where you want to store the formatted string.The formatting string provides the extra arguments required
n : it is maximum number of characters to be stored in the buffer appending the null character. format : this is the wide character string which shows the format of the output.

## Usage

The swprintf function perform wide character output to an array of wide characters. The programmer must ensure that there is space for at least 'n' wide characters at 's'.

## Description

swprintf is the function which prints the output after the null character in the consecutive wide character starting at *s.And it prints no n more characters up to next null character appears.swprintf is wide character version of sprintf.pointer arguments to swprintf are wide character string

## return value

This function returns number of character written or -1 if an error exist.If s(pointer to buffer) or format is a null pointer ,invalid parameter is invoked.If the program allows to run this code the it returns -1 or errno is set to EINVAL. swprintf returns number of wide character which are stored in 's'(buffer) not counting the last null character.
# C Programming/wchar.h/wcscat

In C, the function wcscat is included in header file wchar.h. This function is quite similar to strcat. This function is used to concatenate two wide character strings.

## Description

The job done by the functions strcat and Wcscat is same as mentioned i.e concatenating two strings.. The difference is that the function strcat takes (normal) character strings and wcscat takes wide character strings as arguments. The function wcscat ,copy the wide character string say b including '\0'(at the end of string b) , at the end of wide character string say a. The '\0' character of the string a is replaced by the first character of the string 'b'. I.e function append the sring 'b' to the end of string 'a'. If wide character string 'a' is "hello" and wide character string 'b' is "world" . After calling the function wcscat(a , b) , string 'a' becomes "helloworld" and string 'b' remains same. The wide string 'a' must have memory of at least (strlen(a) + strlen(b) +1) bytes so that it can store wcs(Wide character string) 'a' , wcs 'b' and '\0'.

## Sample Program

Output of program will be ' Hello World '.
Wide character string 'source'(World) is appended at the end of wide character string 'destination'(Hello).

## Return Value

The function wcscat returns pointer to wide character string 'a' i.e pointer to the string which is concatenated.
# C Programming/wchar.h/wcscpy

In C Programming language , functions wcsncmp , wcscat , labs , mempcpy are used. Function wcscpy ,is similar to strcpy .strcpy is used to copy strings whereas wcscpy is used to handle wide strings for copying. It copies the wide-character string pointed to by src,including the terminating L'\0' character, to the array pointed to by dest.
# C Programming/wchar.h/putwc
## Name

Putwc

## Parameters

c is used for the character to be written. stream for pointer to FILE structure.

## description

It is a standard library function. this function write a wide character to a FILE stream. it is included in the standard library Wchar.h. putwc function writes a wide character to output stream. it advances the file position accordingly. putwc function is same as fputwc.

## Return value

on success this function return 0. otherwise it will give non-zero value.
# C Programming/wchar.h/wcscmp

In C language ,the function wcscmp is included in header file wchar.h wcscmp is similar to strcmp i.e it is used to compare two strings.but the function wcscmp is used to compare wide character strings. If two wide character strings say s1 and s2 are to be compared. Then function wcscmp returns positive integer if s1 is greater than s2. It returns negative integer if string s2 is greater than s1. if two wide character strings i.e s1 and s2 are same then function returns 0.

## Sample program which uses function wcsncmp

Output of program will be 'char is less than character ' as value of difference is negative.

## See also

* Wcsncmp
# C Programming/wchar.h/wcsncmp

In C language, the function wcscmp is included in header file , wchar.h. The functions wcsncmp ,wcscmp , strncmp , strcmp are used to compare strings. Function wcsncmp, is similar to strncmp , which is used to compare two fixed-size wide-character strings. it looks similar to strncmp .This function is used to handle wide character strings. The wcsncmp function is the wide-character equivalent of the strncmp function. The function wcsncmp is similar to wcscmp, but it compares only first n characters.

## Description

Wcsncmp is the standard library function used to compare two wide character strings. The function is similar to standard library function strcmp. But the comparison is not like strcmp. The first difference is that the function wcsncmp compares the two strings upto some limit(at most n character) i.e size_t n but strcmp compares the strings till '\0' occurs. and the second is that it handles wide characters as mentioned. It compares the wide-character string pointed to by say a and the wide character string pointed to by say b, but at most n wide characters from each string.
If the wide character string a is greater than wide character string b at first differentiating position i (i < n) then the function Wcsncmp returns positive integer and if second string is greater than first at the first differing position i (i < n), then the function wcsncmp returns negative integer. if the first i characters (i < n) of a and b are equal , the function wcsncmp returns 0.

## Required Header Files

#include<wchar.h> OR #include<string.h>

## Brief Comparison

| Function | What it does | Arguments |
| Wcsncmp | Compare first n characters of two wide character strings | const wchar_t *a, const wchar_t *b , size_t n |
| Wcscmp | Compare two wide character strings until '\0' occurs of one of the string | const wchar_t *a , const wchar_t *b |
| Strncmp | Compare first n characters of two (normal) character strings | const char *a , const char *b , size_t n |
| Strcmp | Compare character strings until '\0' occurs of one of the string | const char *a , const char *b |

## References

* http://msdn.microsoft.com/en-us/library/c37dh6kf(v=vs.71).aspx
* http://mkssoftware.com/docs/man3/wcsncmp.3.asp
* http://linux.die.net/man/3/wcscmp
# Artificial Neural Networks/Resources
## Wikibooks

* Artificial Intelligence
* Linear Algebra
* Abstract Algebra
* Calculus
* Signals and Systems
* Engineering Analysis
* MATLAB Programming

## Commons

* Commons:Artificial neural network
* Commons:Category:Neural networks
# Artificial Neural Networks/Radial Basis Function Networks

In a radial basis function (RBF) networks are neural nets with three layers. The first input layer feeds data to a hidden intermediate layer. The hidden layer processes the data and transports it to the output layer. Only the tap weights between the hidden layer and the output layer are modified during training. Each hidden layer neuron represents a basis function of the output space, with respect to a particular center in the input space. The activation function chosen is commonly a Gaussian kernel:
    $\sigma (\zeta )=e^{-\beta \zeta ^{2}}$
This kernel is centered at the point in the input space specified by the weight vector. The closer the input signal is to the current weight vector, the higher the output of the neuron will be. Radial basis function networks are used commonly in function approximation and series prediction.
# Artificial Neural Networks/Self-Organizing Maps
## Self-Organizing Maps

Self-organizing maps (SOM), sometimes called Kohonen SOM after their creator, are used with unsupervised learning. SOM are modeled on biological neural networks, where groups of neurons appear to self organize into specific regions with common functionality.

## Neuron Regions

Different regions of the SOM network are trained to be detectors for distinct features from the input set. Initial network weights are either set randomly, or are based off the eigenvectors of the input space. The Euclidean distance from each input sample to the weight vector of each neuron is computed, and the neuron whose weight vector is most similar to the input is declared the best match unit (BMU). The update formula is given as:
    $w_{j}[n+1]=w_{j}[n]+\Theta [j,n]\alpha [n](x[n]-w_{j}[n])$
Here, w is the weight vector at time n. α is a monotonically decreasing function that ensures the learning rate will decrease over time. x is the input vector, and Θ[j, n] is a measure of the distance between the BMU and neuron j at iteration n. As can be seen from this algorithm, the amount by which the neuron weight vectors change is based on the distance from the BMU, and the amount of time. Decreasing the potential for change over time helps to reduce volatility during training, and helps to ensure that the network converges.
# Artificial Neural Networks/Recurrent Networks
## Recurrent Networks

In a recurrent network, the weight matrix for each layer l contains input weights from all other neurons in the network, not just neurons from the previous layer. The additional complexity from these feedback paths can have a number of advantages and disadvantages in the network.

## Simple Recurrent Networks

Recurrent networks, in contrast to feed-forward networks, do have feedback elements that enable signals from one layer to be fed back to a previous layer. A basic recurrent network is shown in figure 6. A simple recurrent network is one with three layers, an input, an output, and a hidden layer. A set of additional context units are added to the input layer that receive input from the hidden layer neurons. The feedback paths from the hidden layer to the context units have a fixed weight of unity.
A fully recurrent network is one where every neuron receives input from all other neurons in the system. Such networks cannot be easily arranged into layers. A small subset of neurons receives external input, and another small subset produce system output. A recurrent network is known as symmetrical network if:
    $w_{ij}=w_{ji}\forall i,j$

### Elman Network

An Elman Network is a special case of a Simple Recurrent Network (SRN) with four layers: An input layer, an output layer, a hidden layer and a context layer. The context layer feeds the hidden layer at iteration N with a value computed from the output of the hidden layer at iteration N-1, providing a short memory effect. Elman networks are used, for example, for predicting series of values.
# Artificial Neural Networks/Series Prediction

ANN can be trained to match the statistical properties of a particular input signal, and can even be used to predict future values of time series. There are a number of applications of feature prediction that have received significant research attention. Among these are financial prediction, meteorological prediction, and electric load prediction. ANN have shown themselves to be very robust in predicting complicated series, including non-linear non-stationary chaotic systems.
Financial prediction is useful for anticipating events in the economic system, which is considered to be a chaotic system. ANN have been used to predict the performance and failure rate of companies, changes in the exchange rate, and other economic metrics.
Meteorological prediction is a difficult process because current atmospheric models rely on highly recursive sets of differential equations which can be difficult to calculate, and which propagate errors through the successive iterations. Using neural nets for meteorological prediction is a non-trivial task, and there have been many conflicting reports of the efficacy of the technique.
# Asia and Pacific UNISDR Informs

| Asia Prepares for the World Conference on Disaster Reduction | The 2004 Indian Ocean Tsunami: One Year Later | Education Issue |
| Living with Risk | Lessons for a Safer Future | Indigenous Knowledge for Disaster Risk Reduction |
| Climate Resilient Cities 2008 Primer | Words Into Action | Indicators of Progress |
# Artificial Neural Networks/Pattern Recognition

Artificial neural networks are useful for pattern matching applications. Pattern matching consists of the ability to identify the class of input signals or patterns. Pattern matching ANN are typically trained using supervised learning techniques. One application where artificial neural nets have been applied extensively is optical character recognition (OCR). OCR has been a very successful area of research involving artificial neural networks.
An example of a pattern matching neural network is that used by VISA for identifying suspicious transactions and fraudulent purchases. When input symbols do not match an accepted pattern, the system raises a warning flag that indicates a potential problem.
# Character Encodings/Code Tables/EBCDIC/EBCDIC 1027

IBM code page 1027 (CCSID 1027) is an is an EBCDIC code page used in IBM mainframes in Japan. It supports Katakana.
CCSID 5123 is the euro currency update of code page/CCSID 1027.

## Codepage layout

Characters are shown with their equivalent Unicode codes.
Japan Latin EBCDIC :
| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | A | B | C | D | E | F |
| 0x | NUL | SOH | STX | ETX | SEL | HT | RNL | DEL | GE | SPS | RPT | VT | FF | CR | SO | SI |
| 1x | DLE | DC1 | DC2 | DC3 | RES/ ENP | NL | BS | POC | CAN | EM | UBS | CU1 | IFS | IGS | IRS | ITB |
| 2x | DS | SOS | FS | WUS | BYP/ INP | LF | ETB | ESC | SA | SFE | SM/ SW | CSP | MFA | ENQ | ACK | BEL |
| 3x | | | SYN | IR | PP | TRN | NBS | EOT | SBS | IT | RFF | CU3 | DC4 | NAK | | SUB |
| 4x | SP | | 。 3002 | 「 300C | 」 300D | 、 3001 | ・ 30FB | ヲ 30F2 | ァ 30A1 | ィ 30A3 | ¢ 00A2 | . 002E | < 003C | ( 0028 | + 002B | | 007C |
| 5x | & 0026 | ゥ 30A5 | ェ 30A7 | ォ 30A9 | ャ 30E3 | ュ 30E5 | ョ 30E7 | ッ 30C3 | ー 30FC | ア 30A2 | ! 0021 | $ 0024 | * 002A | ) 0029 | ; 003B | ¬ 00AC |
| 6x | - 002D | / 002F | イ 30A4 | ウ 30A6 | エ 30A8 | オ 30AA | カ 30AB | キ 30AD | ク 30AF | ケ 30B1 | | , 002C | % 0025 | _ 005F | > 003E | ? 003F |
| 7x | コ 30B3 | サ 30B5 | シ 30B7 | ス 30B9 | セ 30BB | ソ 30BD | タ 30BF | チ 30C1 | ツ 30C4 | ` 0060 | : 003A | # 0023 | @ 0040 | ' 0027 | = 003D | " 0022 |
| 8x | | a 0061 | b 0062 | c 0063 | d 0064 | e 0065 | f 0066 | g 0067 | h 0068 | i 0069 | テ 30C6 | ト 30C8 | ナ 30CA | ニ 30CB | ヌ 30CC | ネ 30CD |
| 9x | | j 006A | k 006B | l 006C | m 006D | n 006E | o 006F | p 0070 | q 0071 | r 0072 | ノ 30CE | ハ 30CF | ヒ 30D2 | フ 30D5 | ヘ 30D8 | ホ 30DB |
| Ax | ¯ 00AF | ~ 007E | s 0073 | t 0074 | u 0075 | v 0076 | w 0077 | x 0078 | y 0079 | z 007A | マ 30DE | ミ 30DF | ム 30E0 | [ 005B | メ 30E1 | モ 30E2 |
| Bx | ^ 005E | £ 00A3 | ¥ 00A5 | ヤ 30E4 | ユ 30E6 | ヨ 30E8 | ラ 30E9 | リ 30EA | ル 30EB | レ 30EC | ロ 30ED | ワ 30EF | ン 30F3 | ] 005D | ゙ 3099 | ゚ 309A |
| Cx | { 007B | A 0041 | B 0042 | C 0043 | D 0044 | E 0045 | F 0046 | G 0047 | H 0048 | I 0049 | | | | | | |
| Dx | } 007D | J 004A | K 004B | L 004C | M 004D | N 004E | O 004F | P 0050 | Q 0051 | R 0052 | | | | | | |
| Ex | \ 005C | € 20AC | S 0053 | T 0054 | U 0055 | V 0056 | W 0057 | X 0058 | Y 0059 | Z 005A | | | | | | |
| Fx | 0 0030 | 1 0031 | 2 0032 | 3 0033 | 4 0034 | 5 0035 | 6 0036 | 7 0037 | 8 0038 | 9 0039 | | | | | | EO |

## References

* ↑ "CCSID 1027 information document". Archived from the original on 2016-03-26.
* ↑ "CCSID 5123 information document". Archived from the original on 2016-03-26.
* ↑ International Components for Unicode (ICU), ibm-5123_P100-1999.ucm, 2002-12-03
* ↑ Code Page CPGID 01027 (pdf) (PDF), IBM
* ↑ Code Page CPGID 01027 (txt), IBM
# Character Encodings/Code Tables/EBCDIC/EBCDIC 1007

IBM code page 1007 is an EBCDIC code page with Arabic support used in IBM mainframes.
EBCDIC 1007 :
| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | A | B | C | D | E | F |
| 4x | SP | NBSP | ﺎ FE8E | | | | | | | | ؛ 061B | . 002E | < 003C | ( 0028 | + 002B | ! 0021 |
| 5x | & 0026 | | | | | | | | | | ؟ 061F | $ 0024 | * 002A | ) 0029 | ; 003B | ^ 005E |
| 6x | ـ 0640 | / 002F | | | | | | | | | ¦ 00A6 | , 002C | ٪ 066A | _ 005F | > 003E | ¬ 00AC |
| 7x | ٠ 0660 | ١ 0661 | ٢ 0662 | ٣ 0663 | ٤ 0664 | ٥ 0665 | ٦ 0666 | ٧ 0667 | ٨ 0668 | ٩ 0669 | : 003A | # 0023 | @ 0040 | ' 0027 | = 003D | " 0022 |
| 8x | ں 0660 | ء 0621 | ا 0627 | | | | | | ج 062C | | ح 062D | خ 062E | د 062F | ذ 0630 | ر 0631 | ز 0632 |
| 9x | | | | | ﺑ FE91 | | ﺗ FE97 | ﺛ FE9B | ﺟ FE9F | | | | | | | |
| Ax | | | | | ط 0637 | ظ 0638 | ع 0639 | غ 063A | | | ق 0642 | ك 0643 | | ل 0644 | م 0645 | ن 0646 |
| Bx | ﺳ FEB3 | ﺷ FEB7 | ﺻ FEBB | ﺿ FEBF | | | ﻋ FECB | ﻏ FECF | ﻓ FED3 | | ﻗ FED7 | ﻛ FEDB | ﻼ FEFC | ﻟ FEDF | ﻣ FEE3 | ﻧ FEE7 |
| Cx | ¢ 00A2 | A 0041 | B 0042 | C 0043 | D 0044 | E 0045 | F 0046 | G 0047 | H 0048 | I 0049 | | | | | ﻰ FEF0 | | 007C |
| Dx | " 0022 | J 004A | K 004B | L 004C | M 004D | N 004E | O 004F | P 0050 | Q 0051 | R 0052 | | | | | | |
| Ex | ، 060C | | S 0053 | T 0054 | U 0055 | V 0056 | W 0057 | X 0058 | Y 0059 | Z 005A | | ه 0647 | و 0648 | ئ 0626 | ى 0649 | |
| Fx | 0 0030 | 1 0031 | 2 0032 | 3 0033 | 4 0034 | 5 0035 | 6 0036 | 7 0037 | 8 0038 | 9 0039 | | ﻫ FEEB | | | ﻳ FEF3 | EO |

## References

* ↑ "Code Page 1007" (PDF). Archived from the original (PDF) on 2013-01-21.
# Character Encodings/Code Tables/EBCDIC/EBCDIC 1003

IBM code page 1003 (CCSID 1003) is an EBCDIC code page used in IBM mainframes. Code page 264 is a superset of this code page.

## Codepage layout

Characters are shown with their equivalent Unicode codes.
Document Composition Facility (DCF), US Text Subset :
| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | A | B | C | D | E | F |
| 4x | SP | NBSP | | | | | | | | | ¢ 00A2 | . 002E | < 003C | ( 0028 | + 002B | | 007C |
| 5x | & 0026 | | | | | | | | | | ! 0021 | $ 0024 | * 002A | ) 0029 | ; 003B | ¬ 00AC |
| 6x | - 002D | / 002F | | | | | | | | | | , 002C | % 0025 | _ 005F | > 003E | ? 003F |
| 7x | | | | | | | | | | | : 003A | # 0023 | @ 0040 | ' 0027 | = 003D | " 0022 |
| 8x | | a 0061 | b 0062 | c 0063 | d 0064 | e 0065 | f 0066 | g 0067 | h 0068 | i 0069 | | { 007B | ≤ 2264 | ⁽ 207D | ⁺ 207A | |
| 9x | | j 006A | k 006B | l 006C | m 006D | n 006E | o 006F | p 0070 | q 0071 | r 0072 | | } 007D | ⌑ 2311 | ⁾ 207E | ± 00B1 | ■ 25A0 |
| Ax | ⁻ 207B | ° 00B0 | s 0073 | t 0074 | u 0075 | v 0076 | w 0077 | x 0078 | y 0079 | z 007A | | | | [ 005B | ≥ 2265 | • 2022 |
| Bx | ⁰ 2070 | ¹ 00B9 | ² 00B2 | ³ 00B3 | ⁴ 2074 | ⁵ 2075 | ⁶ 2076 | ⁷ 2077 | ⁸ 2078 | ⁹ 2079 | | | | ] 005D | ≠ 2260 | |
| Cx | | A 0041 | B 0042 | C 0043 | D 0044 | E 0045 | F 0046 | G 0047 | H 0048 | I 0049 | | | | | | |
| Dx | | J 004A | K 004B | L 004C | M 004D | N 004E | O 004F | P 0050 | Q 0051 | R 0052 | | | § 00A7 | | | |
| Ex | \ 005C | | S 0053 | T 0054 | U 0055 | V 0056 | W 0057 | X 0058 | Y 0059 | Z 005A | | | | | | |
| Fx | 0 0030 | 1 0031 | 2 0032 | 3 0033 | 4 0034 | 5 0035 | 6 0036 | 7 0037 | 8 0038 | 9 0039 | | | | | | EO |
| Differences from EBCDIC 037 |||||||||||||||||

## References

* ↑ Code Page CPGID 01003 (pdf) (PDF), IBM, archived from the original (PDF) on 2013-01-21
# Character Encodings/Code Tables/EBCDIC/EBCDIC 1002

IBM code page 1002 (CCSID 1002) is an EBCDIC code page used in IBM mainframes. Code page 264 is a superset of this code page.

## Codepage layout

Characters are shown with their equivalent Unicode codes.
Document Composition Facility (DCF) Release 2 :
| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | A | B | C | D | E | F |
| 4x | SP | NBSP | | | | | | | | | ¢ 00A2 | . 002E | < 003C | ( 0028 | + 002B | | 007C |
| 5x | & 0026 | | | | | | | | | | ! 0021 | $ 0024 | * 002A | ) 0029 | ; 003B | ¬ 00AC |
| 6x | - 002D | / 002F | | | | | | | | | | , 002C | % 0025 | _ 005F | > 003E | ? 003F |
| 7x | | | | | | | | | | | : 003A | # 0023 | @ 0040 | ' 0027 | = 003D | " 0022 |
| 8x | | a 0061 | b 0062 | c 0063 | d 0064 | e 0065 | f 0066 | g 0067 | h 0068 | i 0069 | | { 007B | ≤ 2264 | | | ┼ 253C |
| 9x | | j 006A | k 006B | l 006C | m 006D | n 006E | o 006F | p 0070 | q 0071 | r 0072 | | } 007D | | | ± 00B1 | ■ 25A0 |
| Ax | | | s 0073 | t 0074 | u 0075 | v 0076 | w 0077 | x 0078 | y 0079 | z 007A | | └ 2514 | ┌ 250C | [ 005B | ≥ 2265 | • 2022 |
| Bx | ⁰ 2070 | ¹ 00B9 | ² 00B2 | ³ 00B3 | ⁴ 2074 | ⁵ 2075 | ⁶ 2076 | ⁷ 2077 | ⁸ 2078 | ⁹ 2079 | | ┘ 2518 | ┐ 2510 | ] 005D | ≠ 2260 | ─ 2500 |
| Cx | | A 0041 | B 0042 | C 0043 | D 0044 | E 0045 | F 0046 | G 0047 | H 0048 | I 0049 | | ┴ 2534 | ┬ 252C | | | |
| Dx | | J 004A | K 004B | L 004C | M 004D | N 004E | O 004F | P 0050 | Q 0051 | R 0052 | | | § 00A7 | | | |
| Ex | \ 005C | | S 0053 | T 0054 | U 0055 | V 0056 | W 0057 | X 0058 | Y 0059 | Z 005A | | ├ 251C | ┤ 2524 | | | |
| Fx | 0 0030 | 1 0031 | 2 0032 | 3 0033 | 4 0034 | 5 0035 | 6 0036 | 7 0037 | 8 0038 | 9 0039 | │ 2502 | | | | | EO |
| Differences from EBCDIC 037 |||||||||||||||||

## References

* ↑ "CCSID 1002 information document". Archived from the original on 2016-03-26.
* ↑ Code Page CPGID 01002 (pdf) (PDF), IBM
* ↑ Code Page CPGID 01002 (txt), IBM
# Character Encodings/Code Tables/EBCDIC/EBCDIC 1001

IBM code page 1001 (CCSID 1001) is an EBCDIC code page used in IBM mainframes. It supports MICR (magnetic ink character recognition). Code page 1032 is an extension of this code page.

## Codepage layout

Characters are shown with their equivalent Unicode codes.
EBCDIC 1001 :
| | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | B | F |
| 4x | SP | | | | | | | | | | | |
| 5x | | | | | | | | | | | | |
| 6x | | | | | | | | | | | | |
| 7x | | | | | | | | | | | | |
| 8x | | | | | | | | | | | | |
| 9x | | | | | | | | | | | | |
| Ax | | | | | | | | | | | | |
| Bx | | | | | | | | | | | | |
| Cx | | | | | | | | | | | ⑇ 2447 | |
| Dx | | | | | | | | | | | ⑆ 2446 | |
| Ex | | | | | | | | | | | ⑈ 2448 | |
| Fx | 0 0030 | 1 0031 | 2 0032 | 3 0033 | 4 0034 | 5 0035 | 6 0036 | 7 0037 | 8 0038 | 9 0039 | ⑉ 2449 | EO |

## References

* ↑ "Code Page 1001" (PDF). Archived from the original (PDF) on 2013-01-21.