izzako/sundanese-pixelgpt huggingface dataset:
Salaku catetan ahir, kecap basa Yunani kuno pikeun 'form' (bentuk) nyaéta 'eidos', tur kecap ieu kawentar pisan pamakeánana dina wewengkon téhnis filosofis ku Plato (diteruskeun ku Aristotle atawa Aristotélés) pikeun nuduhkeun idéntitas idéal atawa eusi tina hiji hal (tingal ogé Tiori Ngeunaan Rupa-rupa Bentuk)
"Eidos" bisa ogé dihubungkeun jeung pikiran, proposisi atawa malahan (dihubungkeun jeung) konsép
Informasi salaku Warta
Informasi téh nyaéta kaayaan hiji sistim anu keur ditoongan atawa ditalungtik ("system of interest")
Warta nyaéta informasi nu geus dimatérialisasi
Informasi téh nyaéta kualitas hiji warta ti saurang pangirim ka hiji atawa leuwih ti hiji panarima
Informasi aya patalina ngeunaan hiji hal (ukuran paraméter, mindengna kajadian, jsb)
Ditempo ti belah dieu, informasi mah teu kudu akurat
Informasi bisa bener atawa bisa salah, jujur atawa ngan saukur "sound of a kiss"
Malahan mah gangguan nu geus ilahar ngahalangan jalur komunikasi jeung nyiptakeun salah paham bisa ogé diasupkeun kana salah sahiji bentuk informasi
Sanajan kitu bisa dibilang, lamun "jumlah" informasi dina warta nu ditarima nambahan, warta téh bisa disebut akurat atawa bener
Modél ieu ngasumsikeun aya hiji pangirim nu pasti jeung sahenteuna aya hiji panarima
Loba révisi tina modél ieu ngasumsikeun ayana basa anu dipikanyaho ku pangirim sarta sahenteuna hiji tina nu narima
Aya ogé variasi modél anu nuduhkeun informasi salaku hal anu bakal dibéjakeun dina warta lamun téa mah informasi éta dikirim ti hiji pangirim ka hiji panarima nu sanggup ngartikeun warta éta
Sanajan kitu, nalika ngabutuhkeun ayana pangirim nu pasti, modél "informasi salaku hiji warta" ieu henteu mangaruhan idé yén informasi téh hiji hal anu bisa ditalungtik atawa ditempo tina lingkungan, conto nu ngaliwatan observasi, maca, atawa ngukur
Informasi téh hiji istilah nu miboga loba harti gumantung kana kontéksna, tapi raket pisan kana sababaraha konsép sarupaning harti, pangaweruh, paréntah, komunikasi, réprésentasi, jeung rangsangan méntal
Kalawan basajan bisa disebutkeun yén informasi téh nyaéta hij warta nu ditarima jeung dipikaharti
Patali jeung data, informasi bisa didéfinisikeun salaku kumpulan fakta ti mana urang bisa nyindekkeun
Bisa jadi loba kénéh aspék lain tina informasi sabab éta téh mangrupa pangaweruh anu ayana ku jalan diajar atawa pangalaman atawa paréntah
Mung sacara umum, informasi mangrupa hasil pamrosésan, manipulasi, jeung nyusun data ku cara nu bisa nambahan pangaweruh jalma nu narimana
Tiori komunikasi nyaéta ukuran numerik tina kateupastian hiji kajadian
Contona urang bisa nyarita yén "sinyal éta miboga informasi rébuan bit"
Tiori komunikasi "tends" maké konsép éntropi informasi, anu dimimitian sacara umum ku C.E
Shannon (tempo di handap)
Bentuk lian tina informasi nyaéta informasi Fisher, konsép ti R.A. Fisher
Konsép ieu dipakéna dina terapan statistika pikeun tiori éstimasi jeung dina sains sacara umum
Informasi Fisher nyaéta jumlah informasi nu dibawa ku warta-warta ngeunaan paraméter nu teu bisa ditalungtik, teu bisa di baca, tapi bisa diitung ngaliwatan fungsi kasarupaan (en:"likelihood function") anu ngadéfinisikeun hiji sistim
Contona, ngagunakeun fungsi kasarupaan normal, informasi Fisher nyaéta sabalikna tina (en:"reciprocal of") varians fungsi kasebut
Saupama fungsi kasarupaan teu dipikanyaho, informasi Fisher bisa diitung tina data skor nu didistibusi normal salaku sabalikna tina momén kaduana
Sanajan informasi jeung data mindeng silihganti dipaké, saéstuna duanana téh béda
Data mah mangrupa kumpulan informasi nu teu pakait, jeung euweuh gunana saacan dianalisis atawa diévaluasi kalawan bener
Ngaliwatan évaluasi, sanggeus aya hubungan anu raket di antara data-data nu aya, mangka data téh geus bisa jadi informasi
Data nu sarua ieu bisa dipaké pikeun tujuan lian
Kacindekanana, saacan data ngajadi informasi, euweuh gunana
Ngukur éntropi informasi
Tetempoan yén informasi téh hiji warta mimiti datang saprak dipedarna hiji makalah tulisan Claude Shannon dina taun 1948 anu gedé pangaruhna, nyaéta "A Mathematical Theory of Communication."
Makalah ieu nyadiakeun pondasi tiori informasi sarta ngahargaan kecap 'informasi' lain ngan saukur ku harti téhnis tapi ogé ku ukuran nu jelas
Upamana lamun parangkat nu ngirim sacara sarua bisa ngirimkeun salah sahiji tina sakumpulan nu eusina formula_1 warta, mangka ukuran "informasi nu dihasilkeun sawaktu hiji warta dipilih tina kumpulan éta" téh nyaéta logaritma basis dua tina formula_1
(Ukuran ieu disebutna "informasi-diri")
Dina makalah ieu, Shannon neruskeun: Cara komplémentér atawa cara heubeul pikeun ngukur informasi disadiakeun ku tiori informasi algoritmik
Sacara singget, tiori ieu ngukur eusi informasi tina daptar simbol-simbol dumasar kana sakumaha bisa diprédiksina maranéhanana, atawa sakumaha gampang ngadaptarkeun ngaliwatan hiji program: eusi informasi tina hiji runtuyan nyaéta jumlah bit program pangpondokna nu ngitungna
Runtuyan di handap bakal mibanda ukuran informasi algoritmik nu leutik, lantaran polana gampang dikira-kira, sarta lantaran pola ieu téh silihsambung, ukuranana moal robah
Informasi Shannon bakal méré ukuran informasi nu sarua pikeun unggal simbol, lantaran maranéhanana acak sacara statistik, sarta unggal simbol anyar bakal ngaronjatkeun hasil ngukurna
123456789101112131415161718192021 Penting pisan pikeun mikawanoh watesan-watesan tiori informasi tradisional jeung tiori informasi algoritmik kana persépsi 'pangarti manusa'
Contona, nalika harti tina eusi warta, Shannon nulis, "Frequently the messages have 'meaning…' these semantic aspects of communication are irrelevant to the engineering problem
The significant aspect is that the actual message is one selected 'from a set of possible messages'"
Dina tiori informasi, sinyal-sinyal minangka bagian tina prosés, lain substansi; maranéhanana ngalakukeun hij hal sarta henteu miboga harti anu husus
Ku cara ngagabungkeun tiori informasi algoritmik jeung tiori informasi bisa dicindekkeun yén lolobana sinyal acak ngandung informasi panglobana lantaran bisa dihartikeun dina sagala cara jeung teu bisa didedetkeun (komprési)
Michéal Reddy nulis yén "'signals' of the mathematical theory are 'patterns that can be exchanged'
There is no message contained in the signal, the signals convey the ability to select from a set of possible messages."
('Sinyal-sinyal' dina tiori matématis nyaéta 'pola-pola nu bisa dirobah'
Euweuh warta nu aya dina sinyal, sinyal-sinyal éta bisa milih sorangan tina sakumpulan warta nu mungkin)
Dina tiori informasi, "the system must be designed to operate for each possible selection, not just the one which will actually be chosen since this is unknown at the time of design"
(Sistim kudu didésain sangkan jalan dina unggal pilihan nu mungkin, lain ngan saukur hiji pilihan nu bakal dipilih, lantaran hal ieu teu dipikanyaho sawaktu tahap désain)
Information as a pattern
Information is any represented pattern
This view assumes neither accuracy nor directly communicating parties, but instéad assumes a separation between an object and its representation
Consider the following example: economic statistics represent an economy, however inaccurately
What are commonly referred to as data in computing, statistics, and other fields, are forms of information in this sense
The electro-magnetic patterns in a computer network and connected devices are related to something other than the pattern itself, such as text characters to be displayed and keyboard input
Signals, signs, and symbols are also in this category
On the other hand, according to semiotics, data is symbols with certain syntax and information is data with a certain semantic
Painting and drawing contain information to the extent that they represent something such as an assortment of objects on a table, a profile, or a landscape
In other words, when a pattern of something is transposed to a pattern of something else, the latter is information
This would be the case whether or not there was anyone to perceive it
But if information can be defined merely as a pattern, does that méan that neither utility nor méaning are necessary components of information
Arguably a distinction must be made between raw unprocessed data and information which possesses utility, value or some quantum of méaning
On this view, information may indeed be characterized as a pattern; but this is a necessary condition, not a sufficient one
An individual entry in a telephone book, which follows a specific pattern formed by name, address and telephone number, does not become "informative" in some sense unless and until it possesses some degree of utility, value or méaning
For example, soméone might look up a girlfriend's number, might order a take away etc
The vast majority of numbers will never be construed as "information" in any méaningful sense
The gap between data and information is only closed by a behavioral bridge whereby some value, utility or méaning is added to transform méré data or pattern into information
When one constructs a representation of an object, one can selectively extract from the object (sampling) or use a system of signs to replace (encoding), or both
The sampling and encoding result in representation
An example of the former is a "sample" of a product; an example of the latter is "verbal description" of a product
Both contain information of the product, however inaccurate
When one interprets representation, one can predict a broader pattern from a limited number of observations (inference) or understand the relation between patterns of two different things (decoding)
One example of the former is to sip a soup to know if it is spoiled; an example of the latter is examining footprints to determine the animal and its condition
In both cases, information sources are not constructed or presented by some "sender" of information
Regardless, information is dependent upon, but usually unrelated to and separate from, the medium or media used to express it
In other words, the position of a théoretical series of bits, or even the output once interpreted by a computer or similar device, is unimportant, except when soméone or something is present to interpret the information
Therefore, a quantity of information is totally distinct from its medium
Information as sensory input
Often information is viewed as a type of input to an organism or designed device
Inputs are of two kinds
Some inputs are important to the function of the organism (for example, food) or device (energy) by themselves
In his book "Sensory Ecology," Dusenbery called these causal inputs
Other inputs (information) are important only because they are associated with causal inputs and can be used to predict the occurrence of a causal input at a later time (and perhaps another place)
Some information is important because of association with other information but eventually there must be a connection to a causal input
In practice, information is usually carried by wéak stimuli that must be detected by specialized sensory systems and amplified by energy inputs before they can be functional to the organism or device
For example, light is often a causal input to plants but provides information to animals
The colored light reflected from a flower is too wéak to do much photosynthetic work but the visual system of the bee detects it and the bee's nervous system uses the information to guide the bee to the flower, where the bee often finds nectar or pollen, which are causal inputs, serving a nutritional function
Information is any type of sensory input
When an organism with a nervous system receives an input, it transforms the input into an electrical signal
This is regarded information by some
The idéa of representation is still relevant, but in a slightly different manner
That is, while abstract painting does not represent anything concretely, when the viewer sees the painting, it is nevertheless transformed into electrical signals that créate a representation of the painting
Defined this way, information does not have to be related to truth, communication, or representation of an object
Entertainment in general is not intended to be informative
Music, the performing arts, amusement parks, works of fiction and so on are thus forms of information in this sense, but they are not necessarily forms of information according to some definitions given above
Consider another example: food supplies both nutrition and taste for those who éat it
If information is equated to sensory input, then nutrition is not information but taste is
Information as an influence which leads to a transformation
Information is any type of pattern that influences the formation or transformation of other patterns
In this sense, there is no need for a conscious mind to perceive, much less appreciate, the pattern
Consider, for example, DNA
The sequence of nucleotides is a pattern that influences the formation and development of an organism without any need for a conscious mind
Systems theory at times seems to refer to information in this sense, assuming information does not necessarily involve any conscious mind, and patterns circulating (due to feedback) in the system can be called information
In other words, it can be said that information in this sense is something potentially perceived as representation, though not créated or presented for that purpose
When Marshall McLuhan spéaks of media and their effects on human cultures, he refers to the structure of artifacts that in turn shape our behaviors and mindsets
Also, pheromones are often said to be "information" in this sense
Information as a property in physics
In 2003, J. D. Bekenstein claimed there is a growing trend in physics to define the physical world as being made of information itself (and thus information is defined in this way)
Information has a well defined méaning in physics
Examples of this include the phenomenon of quantum entanglement where particles can interact without reference to their separation or the speed of light
Information itself cannot travel faster than light even if the information is transmitted indirectly
This could léad to the fact that all attempts at physically observing a particle with an "entangled" relationship to another are slowed down, even though the particles are not connected in any other way other than by the information they carry
Another link is demonstrated by the Maxwell's demon thought experiment
In this experiment, a direct relationship between information and another physical property, entropy, is demonstrated
A consequence is that it is impossible to destroy information without incréasing the entropy of a system; in practical terms this often méans generating héat
Thus, in the study of logic gates, the théoretical lower bound of thermal energy reléased by an "AND gate" is higher than for the "NOT gate" (because information is destroyed in an "AND gate" and simply converted in a "NOT gate")
Physical information is of particular importance in the théory of quantum computers
Information as records
Records are a specialized form of information
Essentially, records are information produced consciously or as by-products of business activities or transactions and retained because of their value
Primarily their value is as evidence of the activities of the organization but they may also be retained for their informational value
Sound records management ensures that the integrity of records is preserved for as long as they are required
The international standard on records management, ISO 15489, defines records as "information created, received, and maintained as evidence and information by an organization or person, in pursuance of legal obligations or in the transaction of business"
The International Committee on Archives (ICA) Committee on electronic records defined a record as, "a specific piece of recorded information generated, collected or received in the initiation, conduct or completion of an activity and that comprises sufficient content, context and structure to provide proof or evidence of that activity"
Records may be retained because of their business value, as part of the corporate memory of the organization or to meet legal, fiscal or accountability requirements imposed on the organization
Willis (2005) expressed the view that sound management of business records and information delivered "…six key requirements for good corporate governance…transparency; accountability; due process; compliance; meeting statutory and common law requirements; and security of personal and corporate information."
Sistem panomeran bineri, atawa sistem angka basis-2, mangrupa sistem panomeran anu narjamahkeun harga-harga angka kana dua simbul, biasana 0 jeung 1
Lantaran palaksanaannana anu gampang dina rangkean elektronik, sistem bineri digunakeun dina sakabéh kompiyuter modérn
Contona, dina kompiyuter digunakeun sistem panomeran bineri ASCII anu ngodekeun aksara "a" jadi "01100001", "i" jadi "01101001", "d" jadi "01100100", "e" jadi "01100101", "k" jadi "01101011", "p" jadi "01110000", sarta "w" jadi "01010111"
dumasar kana kode ASCII kasebut, kecap "wikipedia" ditulis dina sistem panomeran salaku "010101110110100101101011011010010111000001100101011001000110100101100001" Sajarah
The ancient Indian mathematician Pingala presented the first known description of a binary numeral system between the 8th and 4th centuries BC, written in Hindu numerals
The numeration system was based on the Eye of Horus Old Kingdom numeration system
A full set of 8 trigrams and 64 hexagrams, analogous to the 3-bit and 6-bit binary numerals, were known to the ancient Chinese in the classic text "I Ching"
Similar sets of binary combinations have also been used in traditional African divination systems such as Ifá as well as in medieval Western geomancy
An ordered binary arrangement of the hexagrams of the I Ching, representing the decimal sequence from 0 to 63, and a method for generating the same, was developed by the Chinese scholar and philosopher Shao Yong in the 11th century
However, there is no evidence that Shao understood binary computation
In 1605 Francis Bacon discussed a system by which letters of the alphabet could be reduced to sequences of binary digits, which could then be encoded as scarcely visible variations in the font in any random text
Importantly for the general théory of binary encoding, he added that this method could be used with any objects at all: "provided those objects be capable of a twofold difference only; as by Bells, by Trumpets, by Lights and Torches, by the report of Muskets, and any instruments of like nature."
(See Bacon's cipher.)
The modérn binary number system was fully documented by Gottfried Leibniz in the 17th century in his article "Explication de l'Arithmétique Binaire"
Leibniz's system used 0 and 1, like the modérn binary numeral system
In 1854, British mathematician George Boole published a landmark paper detailing a system of logic that would become known as Boolean algebra
His logical system proved instrumental in the development of the binary system, particularly in its implementation in electronic circuitry
In 1937, Claude Shannon produced his master's thesis at MIT that implemented Boolean algebra and binary arithmetic using electronic relays and switches for the first time in history
Entitled "A Symbolic Analysis of Relay and Switching Circuits", Shannon's thesis essentially founded practical digital circuit design
In November of 1937, George Stibitz, then working at Bell Labs, completed a relay-based computer he dubbed the "Model K" (for "Kitchen", where he had assembled it), which calculated using binary addition
Bell Labs thus authorized a full reséarch program in late 1938 with Stibitz at the helm
Their Complex Number Computer, completed January 8, 1940, was able to calculate complex numbers
In a demonstration to the American Mathematical Society conference at Dartmouth College on September 11, 1940, Stibitz was able to send the Complex Number Calculator remote commands over telephone lines by a teletype
It was the first computing machine ever used remotely over a phone line
Some participants of the conference who witnessed the demonstration were John Von Neumann, John Mauchly, and Norbert Wiener, who wrote about it in his memoirs
A binary number can be represented by any sequence of bits (binary digits), which in turn may be represented by any mechanism capable of being in two mutually exclusive states
The following sequences of symbols could all be interpreted as the same binary numeric value of 667: 1 0 1 0 0 1 1 0 1 1 x o x o o x x o x x y n y n n y y n y y The numeric value represented in éach case is dependent upon the value assigned to éach symbol
In a computer, the numeric values may be represented by two different voltages; on a magnetic disk, magnetic polarities may be used
A "positive", "yes", or "on" state is not necessarily equivalent to the numerical value of one; it depends on the architecture in use
In keeping with customary representation of numerals using Arabic numerals, binary numbers are commonly written using the symbols 0 and 1
When written, binary numerals are often subscripted, prefixed or suffixed in order to indicate their base, or radix
The following notations are equivalent: 100101 binary (explicit statement of format) 100101b (a suffix indicating binary format) 100101B (a suffix indicating binary format) bin 100101 (a prefix indicating binary format) 1001012 (a subscript indicating base-2 (binary) notation) %100101 (a prefix indicating binary format) 0b100101 (a prefix indicating binary format, common in programming languages) When spoken, binary numerals are usually pronounced by pronouncing éach individual
usually pronounced by pronouncing éach individual digit, in order to distinguish them from decimal numbers
For example, the binary numeral "100" is pronounced "one zero zero", rather than "one hundred", to maké its binary nature explicit, and for purposes of correctness
Since the binary numeral "100" is equal to the decimal value four, it would be confusing, and numerically incorrect, to refer to the numeral as "one hundred" so to spéak
Counting in binary
Counting in binary is similar to counting in any other number system
Beginning with a single digit, counting proceeds through éach symbol, in incréasing order
Decimal counting uses the symbols 0 through 9, while binary only uses the symbols 0 and 1
When the symbols for the first digit are exhausted, the next-higher digit (to the left) is incremented, and counting starts over at 0
In decimal, counting proceeds like so: 000, 001, 002, ... 007, 008, 009, (rightmost digit starts over, and next digit is incremented) 010, 011, 012, ... 090, 091, 092, ... 097, 098, 099, (rightmost two digits start over, and next digit is incremented) 100, 101, 102, ... After a digit réaches 9, an increment resets it to 0 but also causes an increment of
but also causes an increment of the next digit to the left
In binary, counting is the same except that only the two symbols 0 and 1 are used
Thus after a digit réaches 1 in binary, an increment resets it to 0 but also causes an increment of the next digit to the left: 000, 001, (rightmost digit starts over, and next digit is incremented) 010, 011, (rightmost two digits start over, and next digit is incremented) 100, 101, ... Binary simplified
One can think about binary by comparing it with our usual numbers
We use a base ten system
This méans that the value of éach position in a numerical value can be represented by one of ten possible symbols: 0, 1, 2, 3, 4, 5, 6, 7, 8, or 9
We are all familiar with these and how the decimal system works using these ten symbols
When we begin counting values, we should start with the symbol 0, and proceed to 9 when counting
We call this the "ones", or "units" place
The "ones" place, with those digits, might be thought of as a multiplication problem
5 can be thought of as 5 × 100 (10 to the zeroeth power, which equals 5 × 1, since any nonzero number to the zero power is one)
As we move to the left of the ones place, we incréase the power of 10 by one
Thus, to represent 50 in this same manner, it can be thought of as 5 × 101, or 5 × 10. formula_1 formula_2 When we run out of symbols in the decimal numeral system, we "move to the left" one place and use a "1" to represent the "tens" place
Then we reset the symbol in the "ones" place back to the first symbol, zero
Binary is a base two system which works just like our decimal system, however with only two symbols which can be used to represent numerical values: 0 and 1
We begin in the "ones" place with 0, then go up to 1
Now we are out of symbols, so to represent a higher value, we must place a "1" in the "twos" place, since we don't have a symbol we can use in the binary system for 2, like we do in the decimal system
In the binary numeral system, the value represented as 10 is (1 × 21) + (0 × 20)
Thus, it equals "2" in our decimal system
Binary-to-decimal equivalence: formula_3 formula_4 formula_5 To see the actual algorithm used in computing the conversion, see the conversion guide below
Here is another way of thinking about it: When you run out of symbols, for example 11111, add a "1" on the left end and reset all the numerals on the right to "0", producing 100000
This also works for symbols in the middle
Say the number is 100111
If you add one to it, you move the leftmost repéating "1" one space to the left (from the "fours" place to the "eights" place) and reset all the numerals on the right to "0", producing 101000
Arithmetic in binary is much like arithmetic in other numeral systems
Addition, subtraction, multiplication, and division can be performed on binary numerals
The simplest arithmetic operation in binary is addition
Adding two single-digit binary numbers is relatively simple: 0 + 0 = 0 0 + 1 = 1 1 + 0 = 1 1 + 1 = 10 (carry:1) Adding two "1" values produces the value "10" (spoken as "one-zero"), equivalent to the decimal value 2
This is similar to what happens in decimal when certain single-digit numbers are added together; if the result equals or exceeds the value of the radix (10), the digit to the left is incremented: 5 + 5 = 10 7 + 9 = 16 This is known as "carrying" in most numeral systems
When the result of an addition exceeds the value of the radix, the procedure is to "carry the one" to the left, adding it to the next positional value
Carrying works the same way in binary: 1 1 1 1 1 (carried digits) 0 1 1 0 1 + 1 0 1 1 1 = 1 0 0 1 0 0 In this example, two numerals are being added together: 011012 (13 decimal) and 101112 (23 decimal)
The top row shows the carry bits used
Starting in the rightmost column, 1 + 1 = 102
The 1 is carried to the left, and the 0 is written at the bottom of the rightmost column
The second column from the right is added: 1 + 0 + 1 = 102 again; the 1 is carried, and 0 is written at the bottom
The third column: 1 + 1 + 1 = 112
This time, a 1 is carried, and a 1 is written in the bottom row
Proceeding like this gives the final answer 1001002 (36 decimal)
When computers must add two numbers, the rule that: x ^ y = x + y % 2 for any two bits x and y allows for very fast calculation, as well
Subtraction works in much the same way: 0 − 0 = 0 0 − 1 = 1 (with borrow) 1 − 0 = 1 1 − 1 = 0 One binary numeral can be subtracted from another as follows: * * * * (starred columns are borrowed from) 1 1 0 1 1 1 0 − 1 0 1 1 1 = 1 0
1 1 1 = 1 0 1 0 1 1 1 Subtracting a positive number is equivalent to "adding" a negative number of equal absolute value; computers typically use two's complement notation to represent negative values
This notation eliminates the need for a separate "subtract" operation
The subtraction can be summarized with this formula: A - B = A + not B + 1 For further details, see two's complement
Multiplication in binary is similar to its decimal counterpart
Two numbers "A" and "B" can be multiplied by partial products: for éach digit in "B", the product of that digit in "A" is calculated and written on a new line, shifted leftward so that its rightmost digit lines up with the digit in "B" that was used
The sum of all these partial products gives the final result
Since there are only two digits in binary, there are only two possible outcomes of éach partial multiplication: For example, the binary numbers 1011 and 1010 are multiplied as follows: 1 0 1 1 (A) × 1 0 1 0 (B) 0 0 0 0 ← Corresponds to a zero in B + 1 0 1 1 ← Corresponds to a one in B
Corresponds to a one in B + 0 0 0 0 + 1 0 1 1 = 1 1 0 1 1 1 0 See also Booth's multiplication algorithm
Binary division is again similar to its decimal counterpart: __________ 1 0 1 | 1 1 0 1 1 Here, the divisor is 1012, or 5 decimal, while the dividend is 110112, or 27 decimal
The procedure is the same as that of decimal long division; here, the divisor 1012 goes into the first three digits 1102 of the dividend one time, so a "1" is written on the top line
This result is multiplied by the divisor, and subtracted from the first three digits of the dividend; the next digit (a "1") is included to obtain a new three-digit sequence: 1 __________ 1 0 1 | 1 1 0 1 1 − 1 0 1 0 1 1 The procedure is then repéated with the new sequence, continuing until the digits in the dividend
until the digits in the dividend have been exhausted: 1 0 1 __________ 1 0 1 | 1 1 0 1 1 − 1 0 1 0 1 1 − 0 0 0 1 1 1 − 1 0 1 1 0 Thus, the quotient of 110112 divided by 1012 is 1012, as shown on the top line, while the remainder, shown on the
while the remainder, shown on the bottom line, is 102
In decimal, 27 divided by 5 is 5, with a remainder of 2
Though not directly related to the numerical interpretation of binary symbols, sequences of bits may be manipulated using Boolean logical operators
When a string of binary symbols is manipulated in this way, it is called a bitwise operation; the logical operators AND, OR, and XOR may be performed on corresponding bits in two binary numerals provided as input
The logical NOT operation may be performed on individual bits in a single binary numeral provided as input
Sometimes, such operations may be used as arithmetic short-cuts, and may have other computational benefits as well
For example, an arithmetic shift left of a binary number is the equivalent of multiplication by a (positive, integral) power of 2
Conversion to and from other numeral systems
To convert from a base-10 integer numeral to its base-2 (binary) equivalent, the number is divided by two, and the remainder is the least-significant bit
The (integer) result is again divided by two, its remainder is the next most significant bit
This process repéats until the result of further division becomes zero
For example, 11810, in binary, is: réading the sequence of remainders from the bottom up gives the binary numeral formula_6
This method works for conversion from any base, but there are better methods for bases which are powers of two, such as octal and hexadecimal given below
To convert from base-2 to base-10 is the reverse algorithm
Starting from the left, double the result and add the next digit until there are no more
For example to convert 1100101011012 to decimal: The result is 324510
The fractional parts of a number are converted with similar methods
They are again based on the equivalence of shifting with doubling or halving
In a fractional binary number such as .110101101012, the first digit is formula_7, the second formula_8, etc
So if there is a 1 in the first place after the decimal, then the number is at léast formula_7, and vice versa
Double that number is at léast 1
This suggests the algorithm: Repéatedly double the number to be converted, record if the result is at léast 1, and then throw away the integer part
For example, formula_1010, in binary, is: Thus the repéating decimal fraction 0... is equivalent to the repéating binary fraction 0...
Or for example, 0.110, in binary, is: This is also a repéating binary fraction 0.00011...
It may come as a surprise that terminating decimal fractions can have repéating expansions in binary
It is for this réason that many are surprised to discover that 0.1 + ... + 0.1, (10 additions) differs from 1 in floating point arithmetic
In fact, the only binary fractions with terminating expansions are of the form of an integer divided by a power of 2, which 1/10 is not
The final conversion is from binary to decimal fractions
The only difficulty arises with repéating fractions, but otherwise the method is to shift the fraction to an integer, convert it as above, and then divide by the appropriate power of two in the decimal base
For example: Another way of converting from binary to decimal, often quicker for a person familiar with hexadecimal, is to do so indirectly—first converting (formula_11 in binary) into (formula_11 in hexadecimal) and then converting (formula_11 in hexadecimal) into (formula_11 in decimal)
For very large numbers, these simple methods are inefficient because they perform a large number of multiplications or divisions where one operand is very large
A simple divide-and-conquer algorithm is more effective asymptotically: given a binary number, we divide by 10"k", where "k" is chosen so that the quotient roughly equals the remainder, then éach of these pieces is converted to decimal and the two are concatenated
Given a decimal number, we split it into two pieces of about the same size, convert éach to binary, then multiply the first piece by 10"k" and add them, where "k" is the number of digits in the léast-significant (rightmost) piece
Binary may be converted to and from hexadecimal somewhat more éasily
This is due to the fact that the radix of the hexadecimal system (16) is a power of the radix of the binary system (2)
More specifically, 16 = 24, so it takes four digits of binary to represent one digit of hexadecimal
The following table shows éach hexadecimal digit along with the equivalent decimal value and four-digit binary sequence: To convert a hexadecimal number into its binary equivalent, simply substitute the corresponding binary digits: 3A16 = 0011 10102 E716 = 1110 01112 To convert a binary number into its hexadecimal equivalent, divide it into groups of four bits
If the number of bits isn't a multiple of four, simply insert extra 0 bits at the left (called padding)
For example: 010100102 = 0101 0010 grouped with padding = 5216 110111012 = 1101 1101 grouped = DD16 To convert a hexadecimal number into its decimal equivalent, multiply the decimal equivalent of éach hexadecimal digit by the corresponding power of 16 and add the resulting values: C0E716 = (12 × 163) + (0 × 162) + (14 × 161) + (7 × 160) =
161) + (7 × 160) = (12 × 4096) + (0 × 256) + (14 × 16) + (7 × 1) = 49,38310 Octal
Binary is also éasily converted to the octal numeral system, since octal uses a radix of 8, which is a power of two (namely, 23, so it takes exactly three binary digits to represent an octal digit)
The correspondence between octal and binary numerals is the same as for the first eight digits of hexadecimal in the table above
Binary 000 is equivalent to the octal digit 0, binary 111 is equivalent to octal 7, and so forth
Converting from octal to binary proceeds in the same fashion as it does for hexadecimal: 658 = 110 1012 178 = 001 1112 And from binary to octal: 1011002 = 101 1002 grouped = 548 100112 = 010 0112 grouped with padding = 238 And from octal to decimal: 658 = (6 × 81) + (5 × 80) = (6 × 8) + (5
= (6 × 8) + (5 × 1) = 5310 1278 = (1 × 82) + (2 × 81) + (7 × 80) = (1 × 64) + (2 × 8) + (7 × 1) = 8710 Representing real numbers
Non-integers can be represented by using negative powers, which are set off from the other digits by méans of a radix point (called a decimal point in the decimal system)
For example, the binary number 11.012 thus méans: For a total of 3.25 decimal
All dyadic rational numbers formula_15 have a "terminating" binary numeral—the binary representation has a finite number of terms after the radix point
Other rational numbers have binary representation, but instéad of terminating, they "recur", with a finite sequence of digits repéating indefinitely
For instance formula_16 = formula_17 = 0.01010101...2 formula_18 = formula_19 = 0.10110100 10110100 ...2 The phenomenon that the binary representation of any rational is either terminating or recurring also occurs in other radix-based numeral systems
See, for instance, the explanation in decimal
Another similarity is the existence of alternative representations for any terminating representation, relying on the fact that 0.111111... is the sum of the geometric series 2−1 + 2−2 + 2−3 + ... which is 1
Binary numerals which neither terminate nor recur represent irrational numbers
Sistem panomeran bineri
Sistem panomeran binér
Sistim bilangan biner
Sistim bilangan binér
Badan Standardisasi Nasional, disingket BSN, nyaéta Lambaga Pamaréntah Non Departemén Indonesia anu boga pancén ngalaksanakeun tugas pamaréntahan dina widang standardisasi
BSN boga fungsi utama pikeun ngamekarkeun Standar Nasional Indonesia (SNI)
Kapala BSN kiwari nyaéta Ir
Imam Sudarwo Badan Standardisasi Nasional dijieun ngaliwatan Kaputusan Présidén Nomer 13 Taun 1997 anu disampurnakeun ku Kaputusan Présidén Nomer 166 Taun 2000 ngeunaan Kalungguhan, Pancén, Fungsi, Kawenang, Susunan Organisasi sarta Tata Gawé Lambaga Pamaréntah Non Departemén sakumaha geus sababaraha kali dirobah sarta anu pamungkas ku Kaputusan Présidén Nomer 103 Taun 2001, mangrupa Lambaga Pamaréntah Non Departemén kalayan pancén poko ngembangkeun sarta ngabina kagiatan standardisasi
poko ngembangkeun sarta ngabina kagiatan standardisasi di Indonésia
Lambaga ieu ngagantikeun fungsi Déwan Standardisasi Nasional – DSN
Dina ngalaksanakeun pancénna Badan Standardisasi Nasional maké rujukan Aturan Pamaréntah Nomer 102 Taun 2000 ngeunaan Standardisasi Nasional
Palaksanaan pancén sarta fungsi Badan Standardisasi Nasional dina widang akréditasi dipigawé ku Komite Akréditasi Nasional (KAN)
KAN miboga pancén netepkeun akréditasi sarta méré tinimbangan sarta bongbolongan ka BSN dina netepkeun sistem akréditasi sarta sértifikasi
Sedengkeun palaksanaan pancén sarta fungsi BSN dina widang Standar Nasional pikeun Hijian Ukuran dipigawé ku Komite Standar Nasional pikeun Hijian Ukuran (KSNSU)
KSNSU miboga pancén méré tinimbangan sarta bongbolongan ka BSN ngeunaan standar nasional pikeun hijian ukuran
Luyu jeung tujuan utama standardisasi nyaéta nangtayungan produsén, konsumén, tanaga gawé sarta masarakat tina aspék kaamanan, kasalametan, kaséhatan sarta "pelestarian" fungsi lingkungan, pangaturan standardisasi sacara nasional ieu dipigawé dina raraga ngawangun sistem nasional anu sanggup ngadorong sarta ngaronjatkeun, ngajamin mutu barang sarta/atawa jasa jeung sanggup jadi fasilitas "keberterimaan" produk nasional dina transaksi pasar global
Tina sistem jeung kaayaan kasebut diharepkeun bisa ngaronjatkeun daya saing produk barang sarta/atawa jasa Indonésia di pasar global
Visi Taun 2009: SNI jadi standar nasional anu éféktif pikeun nguatkeun daya saing nasional, ngaronjatkeun transparansi sarta éfisiési pasar, sakaligus nangtayungan kasalametan konsumén, kaséhatan masarakat, "kelestarian" fungsi lingkungan sarta kaamanan
Saluyu jeung visi kasebut di luhur, mangka misi BSN nyaéta méré kontribusi pasti dina pangwangunan ékonomi ngaliwatan: Fungsi BSN
nasional; standardisasi; umum, katatausahaan, organisasi sarta tatalaksana, kapagawéan, kauangan, kéarsipan, hukum, sasandian, "perlengkapan" jeung rumah tangga
Sudan (resmina Républik Sudan) (as-Sūdān.)
nyaéta nagara panglegana di Afrika
Sudan diwatesan ku Mesir di béh kaler, Sagara Beureum di wetan kaler, Eritrea jeung Etiopia di béh wetan, Kenya jeung Uganda di wetan kidul, republik Demokratik Kongo jeung Republik Afrika Tengah di kulon kidul, Cad di béh kulon, sarta Libia di kulon kalereunnana
Sudan mangrupa nagara panglegana kasapuluh di dunya
Ngaran Sudan asalna tina Basa Arab "Bilad-al-sudan", nu hartina "nagara nu hideung."
Dumasar kana konstitusi 2005, basa resmi Sudan nyaéta Basa Arab jeung Inggris: Budaya
Dumasar perkiraan, Sudan lolobana pangeusina Muslim
Kurang leuwih 75% pangeusina ngagem Islam, sedengkeun kurang leuwih 15-20% pangeusina ngadaptar kana kapercayaan animisme atawa "indigenous", sarta kurang lweuwih 5% pangeusina (ngumpul di pakidulan) ngagem Kristen
denominasi Kristen panggedéna nyaéta Garéja Katolik Roma, Garéja Épiskop Sudan, Garéja Présbiteri di Sudan katut Garéja Koptik Ortodok
Institusi atikan luhur di Sudan ngawengku:
Tumbung, heunceut, mémék, momok, atawa baga (di sababaraha wewengkon sunda, ieu kaasup basa kasar) nujul ka organ séks luar awéwé nu sacara umum disebut ogé palawangan (aya ogé sebutan pudendum)
Heunceut manusa ngawengku "labia mayora" jeung "labia minora" (ngaran ieu ditarjamahkeun ka biwir "gedé" jeung biwir "leutik", mindeng ogé "minora" leuwih gedé sarta nonjol luareun "mayora"), itil, lawang urétra (meatus), sarta Liang Heunceut
Fungsi utama nu ngalibetkeun palawangan nyaéta kiih, paripolah séksual, kareseban, sarta babar
Nu cendewok lebah hareup palawangan nyaéta "mons pubis", atawa nu husus keur jelema, "mons veneris" atawa "gunung Vénus" nu sanggeus puber katutupan ku baok ("pubic hair"), nu jumlahna gumantung kana faktor turunan
Labia mayora atawa biwir badag manteng di dua sisi heunceut, nu ogé bisa katutupan ku baok
Labia mayora sagemblengna atawa sawaréh nyumputkeun bagian séjén palawangan
Labia minora nyaéta dua tilep kulit lemes di antara labia mayora jeung dua sisi lawang heunceut
Itil ayana di lebah hareup heunceut tempat labia minora tepung
Tungtung itil nu katémbong, "hulu itil" ("clitoral glans") sagemblengna atawa sawaréh katutupan ku 'tiung' jaringan (tiung itil)
Lawang heunceut ayana deukeut bagian tukang (atawa na bagian handap) palawangan; lawang urétra nu leuwih leutik aya di antara itil jeung heunceut
Di nu parawan kénéh, heunceut téh katutupan ku bagian kulit nu disebut selaput dara ("hymen")
Handapeun, kénca-katuhueun lawang heunceut aya kelenjar Bartholin; nalika wanoja karangsang birahina, kelenjar ieu ngahasilkeun zat leuleueur pikeun ngagampangkeun dina prosés penetrasi
Daérah antara heunceut jeung kérod salawé disebutna perineum
Patalina jeung sirit
Anatomi palawangan patali jeung anatomi sirit ku ayana "common developmental biology"
Bagéan-bagéan nu babagi "common developmental ancestry" dina hal ieu disebutna homolog
Hulu itil ("clitoral glans") homolog jeung hulu sirit ("glans penis") lalaki, sedengkeun "tiung itil" homologna jeung kulup sirit
Awak itil homolog jeung corpora cavernosa, hiji bagian tina sirit
Labia mayora homolog jeung kanjut ("scrotum"), sedengkeun "vestibular bulb" handapeun kulit labia minora homolog jeung corpus spongiosum, jaringan sirit sabudeureun urétra
Kalenjar Bartholin homolog jeung Kalenjar Cowper di lalaki
Karajaan Bélgia nyaéta hiji nagara di Eropa kulon kaler nu diwawatesanan ku Walanda (450 km), Jerman (167 km), Luksemburg (148 km), jeung Perancis (620 km), kalayan gurat basisir nu pondok di Laut Kalér
Belgia mangrupa salah sahiji nagara nu ngadegkeun Uni Eropa sarta jadi tempat kantor puseurna, di sagedéngeun jadi kantor puseur organisasi internasional gedé lianna, kaasup NATO
Belgia legana 30,528 kilometer pasagi (11,787 mil pasagi) sarta populasina kurang leuwih 11.5 yuta
Straddling the cultural boundary between Germanic and Latin Europe, Belgium's two largest regions are Dutch-spéaking Flanders in the north, with 58% of the population, and the French-spéaking southern region of Wallonia, inhabited by 32%
The Brussels-Capital Region is an officially bilingual enclave within the Flemish and néar the Walloon Region, and has 10% of the population
A small German-speaking Community exists in éastern Wallonia
Belgium's linguistic diversity and related political and cultural conflicts are reflected in the political history and a complex system of government
The name 'Belgium' is derived from "Gallia Belgica", a Roman province in the northernmost part of Gaul that was inhabited by the "Belgae", a mix of Celtic and Germanic péoples
Historically, Belgium, the Netherlands and Luxembourg were known as the Low Countries, which used to cover a somewhat larger aréa than the current Benelux group of states
From the end of the Middle Ages until the seventeenth century, it was a prosperous centre of commerce and culture
From the sixteenth century until the Belgian revolution in 1830, many battles between Européan powers were fought in the aréa of Belgium, causing it to be dubbed "the battlefield of Europe" and "the cockpit of Europe" – a reputation strengthened by both World Wars
Upon its independence, Belgium éagerly participated in the Industrial Revolution, generating wéalth and also a demand for raw materials; the latter was a factor during the era of its African colonies
"Tempo oge: section References, subsection General online sources"
Transformasi Fourier kontinyu
Yves Camille Désiré Leterme (babar 6 Oktober 1960 di Wervik, Flanders Kulon) nyaéta Sénator Belgia, manten "Minister-President" Flanders sarta "Flemish Minister" Tatanén jeung Kalaukan
Yves Leterme geus jadi salah sahiji pilihan keur jadi Perdana Mentri Bélgia satuluyna sanggeus pamilihan umum 2007
Anjeunna ngundurkeun diri tina kalungguhan minangka "Flemish Minister-President" dina 26 Juni 2007, digentos ku Kris Peeters
16 Juli 2007, Leterme ditunjuk pikeun ngamimitian sawala koalisi resmi pikeun ngabentuk hiji pamaréntahan anyar
Tanggal 1 Desember taun éta kénéh, Leterme ngaduakalian ngundurkeun diri tina kalungguhan minangka Raja, alatan sawala koalisi "stalled"
Brunéi Darussalam, ( dina Basa Inggris), ngaran resmina Nagara Brunéi Imah Kasajahtraan (, Jawi: برني دارالسلام ), nyaéta hiji nagara nu perenahna di Pulo Kalimantan, Asia Tenggara
Lian ti diwatesan ku basisir jeung Sagara Cina Kidul, Brunei sagemblengna dikuriling ku nagara bagéan Sarawak, Malaysia
Brunei, mangrupa sésa kasultanan nu boga kawasa, sanggeus merdika ti Karajaan Ngahiji tanggal 1 Januari 1984
Variogram (sacara téoritis) formula_1 nyaéta hiji fungsi nu ngajéntrékeun tingkat pakaitna spasial tina random field atawa stochastic process formula_2 spasial
It is defined as the expected squared increment of the values between locations formula_3 and formula_4 (Wackernagel 2003): formula_5 formula_6 itself is called "semivariogram"
In case of a stationary process the variogram and semivariogram can be represented as a function formula_7 of the difference formula_8 between locations only, by the following relation (Cressie 1993): formula_9 If the process is furthermore isotropic, then variogram and semivariogram can be represented by a function formula_10 of the distance formula_11 only (Cressie 1993): formula_12 The indexes formula_13 or formula_14 are typically not
formula_13 or formula_14 are typically not written
The terms are used for all three forms of the function
Moréover the term variogram is sometimes used for semivariogram and the symbol formula_15 for the variogram, which brings some confusion
According to (Cressie 1993, Chiles and Delfiner 1999, Wackernagel 2003) the théoretical variogram has the following properties: formula_22 which corresponds to the fact that the variance formula_23 of formula_24 is given by the negative of this double sum and must be nonnegative
formula_25 Variogram Empiris
For observations formula_32 at locations formula_21 the empirical variogram formula_34 is defined as (Cressie 1993): formula_35 where formula_36 denotes the set of pairs of observation formula_37 placed at an approximate distance of formula_38
Here "approximate distance formula_38" is not exactly defined and typically implemented by a certain tolerance
The "empirical variogram" is used in géostatistik as a first estimate of the (théoretical) variogram needed for spatial interpolation by kriging
According (Cressie 1993) for observations formula_40 from a stationary random field formula_2 the empirical variogram with lag tolerance 0 is an unbiased éstimator of the théoretical variogram, due to formula_42 See the controversy discussion on the correctness of the scaling factor below
The following paraméters are often used to describe variograms: Model Variogram
The empirical variogram cannot be computed at every lag distance formula_38 and due to variation in the estimation it is not ensured that it is a valid variogram, as defined above
However some Geostatistical methods such as kriging need valid semivariograms
In applied géostatistics the empirical variograms are thus often approximated by modél function ensuring validity (Chiles&amp;Delfiner 1999)
Some important modéls are (Chiles&amp;Delfiner 1999, Cressie 1993): formula_47 formula_48 formula_49 The paraméter formula_50 has different values in different references, due to the ambiguity in the definition of the range
formula_51 is the value used in (Chiles&amp;Delfiner 1999)
The formula_52 function is 1 if formula_53 and 0 otherwise