measur ment draft

7/31/2019 Measur Ment Draft

1/43

How to measure principles Author: Said Mchaalia

Abstract:

The science advances and is away to involve gathering discovering true right databases informationin many disciplines. Although in the field of digital data transmission the mechanism of modelingand simulation has been hence evolved in producing several functional effect results, the exactmathematical models in such a mechanism are still now clearly undefined.The intention aim of the clean clear compile-compute-conclude processing analysis aspects is tofinish with nice correlated quietly right exact simulation results. In fact, to achieve such an aim, thefirst step is to delete human luring and seductions. Therefore, clear computation within choice anddecision during alive processing aspects would be involved for each modeling and simulationmechanism.Indeed, clean compute conclude motor flow throughout clean clear communication and cultureexchanges have to be evolved for each measurement task and thread. Measurement task and threadsare original main secret signs for many active branch disciplines.

Keywords:

modeling and simulation, mechanism, gathering discovering true right databases information,digital data transmission, measurement task and threads, and compile-compute-conclude

processing analysis.

Introduction:

Digital data transmission is main primordial entity in several systems. Thereby, in modeling andsimulation investigation branches, an entity is an object of interest in system processing analysisaspects. Although, each entity has its own property inside active system. This property is calledentity attribute. The entity property involves entirely within entity activity and entity events. Hence,the entity event is the instantaneous value change dump of the state of current entity (ready to beexecuted, inside queue, fetched, ran, stored again). Furthermore instead of investigating entityactivity inside active system, which is hard to be identify, resolving basic logic influence system onthese tasks and threads allow the investigation of system states throughout entity activities.Digital data transmission is based on discrete event simulation, which was started with Shannon'smathematical information theory, and may be early with telegram data transmission threads.Therefore, the basics of discrete event simulation has its roots from the language motor flows. In

this field, whereby each character is just one entire entity inside active alphabet as Shannon did callit, an alphabet is a selfish set of characters {a, n, m, l, p} . Grounded to this theory of selfish set, the processing account was invented. Thus, start to count on characters inside a selfish set of letters, is a processing account within measurement calculations, whereby gathering discovering scopes withindiscrete event simulation. Thereby, initialize a variable to be number and start to add just one to thisnumber in order to reach the desired value at the end of simulation time. For example, define a to be8, then add(a, 1) to be equal to 400 after certain simulation time.

Most around development environment and industrial advances, command and control of processors to achieve their tasks and threads aware away of best powers, whereby object aims of many disciplines wish, are deep investigation motor flows. Thus modeling and simulation are basics

1


2/43

in those disciplines. In fact, modeling and simulation search their roots in the applied maths and measurementcalculation principles, whereby mathematical functions and procedures are aware away of motor flows.

This paper is organized as follows: first of all an overview on the mathematical functionalism will be given. Next, an illustration of modeling and simulation within discrete event simulation will bedepicted. After, the how to measure principles would be evolved in details and finally a conclusionwill be deduced.

1. Mathematical functionalism overview:

1.1. Usable functions following descriptions:

Maths is science of invisible philosophy processing analysis. This science is belong tocompile-compute-conclude effect aspects of following motor flows.Measurement calculation steps are impure and addictive when their boundary conditions arelimitless or although pure and noble when those boundary conditions would be awokenwithin modeling and simulation tasks and threads.The strength of model descriptions in order to provoke right simulation processes and to

bring into innovative world of development environment is the aim object of each entityactivity inside interest active system.Indeed, in digital data transmission, mathematical functionalism is characterized byfollowing description functions and fear flows in modulation fields.Therefore, aware away of the identification of those function is subject of many workerswithin innovation system development environments. In fact, the sinusoidal function, which has periodic characteristics during simulation time, isthe awoken waveform of data edge representation inside measurement calculation withinsystem development environment. Therefore, within system development environment of digital data transmission such that text files and emails inter-exchanges, data edgerepresentations are electrical currents aware away of electromagnetic waves. To determine,the values of those data edge representations, the resolution of Maxwell-Ampere equation isinterest away such that resolve: Curve B (t ). dl = function (Surface i (t ) .ds ) , where dl and ds are measurement quantities for both curves (one dimension measurement length) andsurface (two dimension measurement coordination viewpoints) during discrete simulation

time intervals. Similarly in fact, the number of months inside a year is always twelvemonths. This number of twelve months is data edge representation inside measurementaccount of year enumerations. Indeed, the main synchronization secret of data edgerepresentation is value change dump during following motor flows through measurementcalculation nodes, whereby discrete event simulation time have to be onwards and forwards

proceeded steps with test-bench characteristics. These test-benches faithful for digital datatransmission modeling and simulation.In fact, transmission-reception-absorption background modeling-simulation processinganalysis is not yet defined. For digital data transmission, such that gathering discoveringdata received from digital-analog and analog-digital conversions, the right model of theobtained waveform are till now still illusion. In electrical branch field disciplines, the

2


3/43

sinusoidal function model is always used to simulate input-output signals within consideredcircuits. Then, the signal correlations or mathematical signal multiplexers are basic tools for image illustrations like those treated in MRI scientific fields (reference my work Magneticresonance imaging presentation, in Rot and Rot, 2002, Germany, Headreference: DAADDeutischestiffung. Magnetic Resonance Imaging description based on the cutoff of Fourier transformation and just using-language of t = nT , n , to depict received image fromwithin IMB-AT compatible PCI interface cards and similarly.) Detailed description of correlation and involving mathematical description functions will be reviewed in the next

paragraphs.

Figure 1: wave-form for a sinusoidal functional

Figure 1 shows a sinusoidal waveform. The main characteristic of this waveform is periodicduring proposed test-bench simulation times. The mathematical sinusoidal descriptionfunction, has the characteristics, such that it attains its maximum magnitude value in themiddle array of simulation time. At the boundaries within measurement arrays of simulation

time, which are 2pi period periodic measurement arrays, the values of the mathematicalsinusoidal description functions are nulls.Indeed, the magnitude-value variations are basic tools for signal encoding. Arithmeticencoding is primordial main original thread-task within digital data transmission. Arithmeticencoding is based on the encoding of the magnitude-value in integer form, whereby theinferior boundary integer within a float magnitude-value variation would be used in such anarithmetic encoding. The maximum voltage or current magnitude-value variations insideelectrical circuits depend on the technical applications. For digital data transmission, suchthat send-receive alphabets and like thread-tasks, the middle average voltage is 10 Volts (seePCI interface card like meilhaus300 for more details. I did use this PCI IBM-AT compatibleinterface for 11GHz noise radar's measurement at Ilmenau technical university, 1998,

3


4/43

Germany, Headreference: Prof. Loele. ). The basic logic of the arithmetic encoding of thismaximum 10 volts voltage level magnitude-value is to convert 22 integer value to binary,

because the positive and negative measurement processing analysis and error measurementcalculations involving within modeling-simulation. The envisaged arithmetic encoding incomputer language is to associate the binary 00000b to -22 volts measurement magnitude-value, then the binary 00001b to -21 volts measurement magnitude-value, after 00010b to

-20 volts measurement magnitude-value till the binary 10110b for + 22 volts measurementmagnitude-value. The true-false logic involved within any one-volt magnitude-valuevariation inside the envisage arithmetic encoding, is illustrated using figure 3 and or figure 6 and figure 10 described below, whereby logic true is the magnitude-value associated withthe highest value level and the logic false is the lowest value level of magnitudemeasurement.

Figure 2: sin (2.. f .) function following description most aroundused in digital data transmission-reception-absorption processes.

In figure 2 , the first variation of currently involved function for digital data transmission-reception-absorption processing analysis is a clear clean sinusoidal aspect. Therefore it isstarting from nil magnitude value, then after certain time values it did attain its firstmagnitude summit value, then after it did attain a negative magnitude value and finally it did

backwardly attain its magnitude summit value. The time value variation allowing to attain

the magnitude summit values originally and its first successor backwardly defines the time period of such a sinusoidal function following description. This function is sin (2.. f .), where

f = 1T

is original main frequency characteristic of such a function following description.

Furthermore, is the shortest time interval value to be involved within the processinganalysis. In some digital data transmission applications, this value is about 0.65 nanoseconds (6.5 10 -10 seconds).

On the other hand, searching function following description was finished with Shannon'sworks, which finalize a function following description based on stochastic probabilities.This function is the Logarithm functional behavior description. This logarithm functional

4

sin(.) function following description sin(.) function following description

time

m a g n i t u d e


5/43

behavior is used to mainly calculate lossyless data sent within signals. Logarithm functional behavior has negative infinite values when the time composition variable has values insidethe segment [0 1] . Then the nil value, when this time composition variable is one and

positive relaxed infinite values otherwise.

Figure 3: Log (2.. f. ) function following descriptionfor a given digital data transmission-reception-absorption.

Figure 3 illustrates the logarithm functional behavior variation during processing analysis of a digital data transmission-reception-absorption system. Compared to figure 2, thisfunctional behavior could be used in encoding digital data to be send and receive withlossyless data transmission. The within this function following description involvingencoding techniques are the magnitude summit value for logic true and the not function of such a value is the logic false.

1.2. Required functions for modulation and signal flows:

Signal manufacturing tools send different kinds of signals to be received from distinctdestinations. Principally, these tools are characterized by transmission antennas andreception sensors.The modulation aspects is theoretical task and threads during modeling and simulation of

digital data transmission. Grounded to some readings (see modulation principles and Fourier transformation within digital signal processing theory), the main usable functions in themodulation branches and fields are the following functions described in table 1.Table 1, presents some ideas about useful function for modeling and simulation insidemodulation processing analysis. Notice that the real behavior of transmission-reception-absorption processing analysis is based on the correlation of the function followingdescription and the function using inside the modulation process. This correlation processinganalysis is function of the passed values of considered signal and predicted ones. For moredetails on the correlation phenomena, presented books and papers in digital datatransmission and encoding such Shannon's mathematical information theory is utilitytoolboxes for gathering discovering database's information within those brand fields and

5

Log(.) function following description Log(.) function following description

time

m a g n i t u d e


6/43

disciplines.Through my works in such branch fields and disciplines, an abstract table review shown intable 1 , concludes the useful modeling-simulation mathematical description functions.

Functions Characteristics Utilities

sin (2pft )2pft

boundary function for all values of inside parameters such that p, f , and t.

used in lab experiments andother fields.

(sin (2pft ))2 boundary function for all values of inside parameters such that p, f , and t.

used as Gaussian replacement inwireless digital transmissionsuch that cellular phones.

e j (2+2 ) characterizing the fast descent to nil when

the calculated inside phase is growinggradually to infinite values.

most around used when thedefined phase is less than eighthof one tour.

tan ( X ( f , t ))characterizing the fast fading to infinitywhen the calculated inside X(f, t) isgrowing gradually to fourth tour values.

used in supra high frequencymodulation fields.

x. log ( 1 x

) boundary function for all values of inside parameter x when define limit of thefraction of infinity and nil to be nil.

used as replacement of the firstdefined function inside thistable.

Table 1: functions used in modulation branch fields.

Figure 4: sin(2.p.f.t )

2.p.f.tfunction following description inside digital data

transmission-reception-absorption processing analysis.

6

(sin(.) )/(.) function following description (sin(.) )/(.) function following description

time

m a g n i t u d e


7/43

For data transmission-reception-absorption processing analysis, correlation techniques areinvolved. In continuous data processing branch fields, this correlation techniques is simplemathematical multiplication operation; (sin (2.p.f.t )).( sin (2.p.f.t )

2.p.f.t) . In fact, this mathematical

multiplication operation is just multiplication of function following description with afunction involved within the modulation modeling simulation processing analysis. Asexample, figure 5 describes this techniques.

Figure 5: [log ( x)][sin ( x) x

] waveform produced during modeling and

simulation processing analysis of digital data transmission.

Figure 5 illustrates modulation simulation of digital transmission, where some mathematicalfunction were used to determine the write waveform. Notice that the described waveform isnot the true right one. For this reason, few modifications have to be involved withinmodeling and simulation processing analysis. The proposed modification is to use the sin (.)as function following description or another function included within modulationsimulation.

Figure 6 illustrates the most significant waveform of modulation simulation techniquesinvolving within digital data transmission processing analysis.Although an other similar waveform shown in figure 7 could be used in modeling andsimulation techniques for digital data transmission.

Figure 7 shows the [sin ( x)].[tan ( x)] function involving in modeling and simulationinside digital data transmission. This function could be used as waveforms to be sent.However it does not describe the exactly true right envelop to engender the entire signal,which will be proceeded transmission processing.

7

Log(.)x[(sin(.) )/(.) ] wave-form modeling simlation processing Log(.)x[(sin(.) )/(.) ] wave-form modeling simlation processing

time

m

a g n i t u d e


8/43

Figure 6: sin 2 (.)(.) waveform involved within modeling simulation processing analysis.

Figure 7 : [ sin (2.. f .)][tan (2.. f .)] waveform used within modeling andsimulation processing analysis.

1.3. Conclusion:

In this section an overview of the mathematical functionalism used within digital datatransmission was illustrated. For further modeling and simulation inside modulation

processing involved within digital data transmission, the mathematical functional model isthe correlation of the sinusoidal function and the tangential function or perhaps thelogarithm functional behavior such that the one defined within Shannnon's mathematical

8

sin(.)x[(sin(.) )/(.) ] wave-form modeling simlation processing sin(.)x[(sin(.) )/(.) ] wave-form modeling simlation processing

time

m a g n i t u d e

[sin.(.)].[tan(.)] wave-form modeling simlation processing [sin.(.)].[tan(.)] wave-form modeling simlation processing

time

m a g n i t u d e


9/43

information theory; y.log ( 1 y

) , where y is the stochastic value for a given simulation.

In conclusion models, two models such that (sin ( x( f , t ))). tan ( X ( f ,t )) where X(f, t)characterizes the amount of amplitude to be enough in order to be absorbed by the reception

antennas and or (sin ( x( f , t ))). y.log ( 1 y

) , where y is the instantaneously probability of

error occurred on signal absorption at time t.

2. Modeling and simulation illustration: discrete event simulation example.

2.1. Introduction:

The human person attached invisible Satan within modeling and simulation is the discreteevent simulation definition and usage. This definition and description has no responsibilityon the chosen modeling and simulation methodology or similarly for doing things exactly.Although extreme angry aspects could be sometimes engender within modeling andsimulation when wrong ways were chosen. However this has effects on the selfish reflexivelust, this should not be a reflexive lost results.

2.2. Discrete event background and structure:

In digital inline verification of hardware design of consumer electronics, modeling-simulation processing analysis of digital data transmission and similarly, the motor kernelflow of discrete event simulation is the following famous flow structure; if clock's eventoccurs and clock's event value is equal to logic true or false, then while some synchronizedconstraint boundary conditions {do somethings, which are resolving of basic logic influencesystems}.

Discrete event background in VHDL Discrete event background in C-language

process ( sensitive list clk ){

if clk'event and clk == 1do {

resolve basic logic influences systems;} while (constraint boundary conditions);

end if;}end process;

unsigned char clk;bool clckEvent = false;

.if clkEvent and clk == '1' {

while {(constraint boundary conditions)resolve basic logic influences systems;

}}

Table 100: discrete event background structures in signal assignment ( VHDL) language and C-language.

Table 100 illustrates the difference of discrete event background structures in two different programming languages such C-language and VHDL-language . As it was lastly in 2008defined, VHDL-language is concerning signal assignment's measurement calculations.Although, C-language is programmable control data flow graphs involving operatingsystems like Linux and command line controls like tar -xf filename.tar.

9


10/43

The invisible Satan of event descriptions is:

- Think of an occurrence in order to have whose effect and whose judgment: to consider or to anticipate both worried and hopeful whose side happenings.

- Think out or through event activity is to think about hereby until whose conclusion isreached. Therefore, understand and resolve event activities, means resolve basic logicinfluence systems on event occurrences.

- Think up an arrangement of system environment to reach whose invention or devising;means make decision to change the event states inside this system environment.

As example, think of an occurrence, which is writing a book. Think out this event activity, isto think through its processing analysis and then to think up that this event results will bemeasurement principles of compile-compute-conclude processing analysis aspects.

2.3. Discrete event dynamism and aspects:

Discrete event dynamism engenders event occurrence, event activity, event attribute, eventstate and event environment. Discrete event aspects are the instantaneous outwardappearances, which should be associated with it dynamism.Indeed, this dynamism is unknown effect analysis; fuzzy or similar analysis start from trueright sources engendering gathering database information over event occurrences. Hence,analysis of inside instruction introduction of event occurrence processing and its realviewpoint illustration.

- event occurrence: what does it happen instantaneously right now?- event activity: what is it going on currently live?- event attribute: which property is characterizing this event occurrence?- event state: why is it so depicted?- event environment: how much time does event occurrence need to be faded?

As modeling and simulation of discrete event simulation; computer start up. The first eventoccurrence is power on at 00.00.00 o'clock local time. For such a reason, a synchronizedevent clock is required. This timer should be locally global reference. After few secondstime, the core processing unit is searching to load the operating system into the read access

memory (RAM). So, the next event occurrence and so on. In details of modeling andsimulation, a list of couples (time value, event value) would be involved within thissimulation processing analysis.

10


11/43

Timelocally set as global.

Event Description

00.00.00 o'clock within local timer. power on.in this event occurrence, a quantity of electrical signal in volts would betransferred to core processing unit.

00.00.08 o'clock within local timer. basic input output system interrupting.in this event occurrence, a quantity of electrical current in Amperes would beexchanged between the bios and itsinput output devices.

00.00.30 o'clock within local timer. searching to load operating system intoread access memory.

in this event occurrence, a quantity of electrical current in Amperes would beexchanged between core processingunit and its inter-components.

00.01.00 o'clock within local timer.computer is ready for further usage.

in this event occurrence, a quantity of electrical current in Amperes would beexchanged between core processingunit and computer input output devices,which are LCD display, mouse,keyboard, printer and so on.

Table 2: Example of discrete event simulation.

Table 2 illustrates an example of discrete event simulation list. The main task in thismodeling simulation processing analysis is to identify event values for each time value

because the timer is set to be locally global. In details of modeling and simulation, a list of couples (time value, event value) would be involved within this simulation processinganalysis. For this example, the envisaged list is so; { (00.00.00, power on), (00.00.08,interrupt bios), (00.00.30, searching OS), (00.01.00, starting PC) }.

2.4. Conclusion:

In this section an introduction viewpoint over discrete event simulation was given. To fill inthe requirement of the exactly true right definition of discrete event simulation, counting

processing of the number of years should be involved within any modeling and simulation

inside discrete event simulation. In fact, the start of year is the birthday of the first month inevery year. Hereby, event occurrence is the birthday of the first month. Hence, event activityis add (month's birthday, one day ), which means processing increment of each month's

birthday in order to finalize one complete month counting, so the second month and so on.Furthermore, event attribute is characteristics within each event. Herewith, the envisagedevent is the counting of the number of years. Therefore, event attribute is an accountidentification of each month. This account identification is the most significant number of days within each month. For example December's account identification is thirty one days.Moreover, event state is collection of variable and signals, which describe the behavior inside a system. In fact, the start of month and its end are two primordial event statesinvolved within each counting processing of the number of years. Although, the main

11


12/43

original event states accomplished within this counting processing are the start and the endof year identifications. On the other hand, those event states define the boundaries of year'snumber counting processing, which is the envisaged system to model and simulate.

3. How to measure principles details:

3.1. Introduction:

To perform a hyper task or thread, it is necessary to declare quantities, which should beintegrated within those tasks and threads. Indeed, those quantities have to be measured. Thismeasurement way is a hard way to have been understood, because tools and methodologiesof technique networking are presented to be clean and clear explained.In fact, to deliver some synchronized following op-codes such that forces in Newton,lengths in meter, time in seconds, voltages in Volts, current in Amperes, power in Watts,weight in Grams, volumes in liters or money units and surface in meter square. May beother measurement units could be presented, such the number of electrons for a given semi-conductor. This number of electrons should measure the energy to be deliver inside a circuit.Thereby, each semi-conductor entity has two sides N-side, which describes the negativecharge focus-in, and the P-side, which describes the positive charge focus-in. These N-sideand P-side are obtained from doping operations.

3.2. Mathematical equations involved inside measurement processing:

First mathematical equation involves within the measurement processing is the sous-tractionor sub-traction; sub (a , b) which means the rest to be counted a b . The nextmathematical equation is the addition operation; add (a , b) which means the number tocounted is a +b . The most around difficult mathematical equation is power calculation.Final mathematical equation involves within measurement processing is the fractionoperation or ratio calculations. Thereby, power calculation is based on quantity integrationduring time simulation and ratio calculation is based on quantity derivation during timesimulation. As example, considering RC-circuit, which presents a measurement unit infiltering branch field. This unit is the gain on magnitude in decibels.

Figure 8 : resistor-capacitor filter response circuit.

12


13/43

Figure 8 , presents resistor-capacitor filter response circuit. This circuit has as input edge thecurrent flows, which could be measured either using coulomb or Ampere, then two

principally elementary components that capacitor C measured in Farads, and resistor R measured in Ohm. Finally, this circuit has an output node, which deliver instantaneousvoltages depicted by Figure 9 .

Figure 9 : e0.8x2xpxfxt waveform inside modeling simulation processing analysiswithin digital data transmission-reception-absorption process.

Figure 9 depicts the exact waveform of resistor-capacitor filter most around used in digital

data processing analysis. The charging of the capacitor depicts the holding value to be storedand the discharge depicts the nil values within the simulation. Grounded to this detail, theanalog to digital conversion processing could be easy deduced by magnitude valuesthroughout resistor value variations. As realization example, a resistor value variation from10 Ohms to 100 Mega Ohms could be used in such a task realization.In fact, the above resistor value variation, could be computed in modeling simulation

processing analysis as mathematical power function of two chosen functions such that thefunction depicted by figure 9 and a function, which could better used in modulation suchthat sin 2(.) , or others defined in table 1.

13

[exp(.)] wave-form modeling simlation processing [exp(.)] wave-form modeling simlation processing

time

m a g n i t u d e


14/43

Figure 10 : waveform within modulation and modeling-simulation processing analysis.

Figure 10 shows the waveform depicted by the mathematical function [sin ( .)]. e(.) . Withinthis mathematical function the magnitude change values indicates the resistor valuevariations for resistor-capacitor filter. The nil values indicates the logic false and the summitmagnitude value indicates the logic true. The between value variation determines the fuzzylogic processing analysis. Notice the original frequency within this waveform is the ratio of one to the interval time separating two successive magnitude summit values. This frequencyis measured in Hertz (unit is Hz). So, varying resistor values allows magnitude variations of output node. This produces a frequency variation inside the envisaged circuit. For

equivalence task, an inductor could be involved. Therefore, the new circuit would bedepicted with inductor-capacitor circuit. The inside circuit frequency could be measuredthroughout this mathematical formula; L.C.4.p 2 . 2= 1 , where p is a ratio of 314 to 100,and f is the frequency to be calculated. The frequency calculation is background variationsof L when C is constant or vice versus or together varying in time. Therefore, the frequencyis a ratio of 1 to 2.p L.C . In fact, when wanting to set the frequency to its highest

possible value, the inductance L and the capacitance C , should be less as they could be. Asexample for given values of C = 1 micro Farads, and L = 1 micro Henry, the frequency isthen equal to about 159.23 Hz.

14

[sin(.)] .[exp(.)] wave-form modeling simlation processing [sin(.)] .[exp(.)] wave-form modeling simlation processing

time

m a g n i t u d e


15/43

Figure 11 : inductor-capacitor-resistor circuit for frequency variation realization.

Figure 11 depicts the realization of frequency variation inside a circuit to filter the signaloutput. The inductor L receive signal input edge characterizes current flows in Amperes.These current flows sustain or incur some basic logic influences. These current flows incur

phase shifting and magnitude modification. Then they maintain their following flows withinthe circuit. Some of them will traverse the resistor and others will contribute for capacitor charge. The output node is resistor-capacitor filter characterizing the 3dB lossy magnitudefor cutoff frequency.In fact, to measure this cutoff frequency within the 3dB lossy magnitude, the following

mathematical functional operation Gain dB= 20.Log 10 (V out V

) should be onward proceeded.

The output voltage waveform is illustrated by 1 e a.RC.t . Although, the input voltagewaveform is depicted by: sin (2.p.f.t ) . 3dB lossy magnitude from the maximum gain,

Gain dB= 20.Log 10 (V out V ) , allow then short time interval measurement dt , which is

characterizing cutoff frequency;1dt

in Hz.

3.3. Mathematical ratios involved inside measurement processing:

Although mathematical ratios are equations of x i to y j, which depict the fraction between x i

and y j; xi y j

. These mathematical ratios are often involving for error processing analysis.

As example the entropy calculation introduced by Shannon in 1948 with his mathematicaltheory of information. This entropy measures the incertitude amount within each set of signals to be sent. Probabilities occur often in measurement processing analysis. Thus,

probabilities are ratio values less or equal to one. To associate with measurement processinganalysis probabilities, which are determined as ratios of values at time t to maximum valuefor all time. Therefore, consider a set of measurements { (t 1 ,V 1), ( t 2 ,V 2), ( t 3 ,V 3), ..,( t n ,V n)}. Themaximum value of all time is ( t j,V max). The probability determination is defined as follows;

{(t 1 ,V 1

V max), ( t 2 ,

V 2V max

), ( t 3 ,V 3

V max), ..,( t n ,

V nV max

)}. Those probabilities would be

involving within each measurement processing analysis of amounts and quantities, whichare gains in magnitudes or gains in amounts, legacies, error corrections and other kinds of measurement processing analysis.

15


16/43

Figure 12 : waveform within digital data modeling-simulation processing analysis involving

[sin (2.p.f.t )]. [[2.p.f.t t ]

(lim (2.p.f.t ))]. ln ([

[2.p.f.t t ]( lim (2.p.f.t ))

]) function.

Figure 12 depicts the function [sin (2.p.f.t )]. [[2.p.f.t t ]

(lim (2.p.f.t ))]. ln ([

[2.p.f.t t ]( lim (2.p.f.t ))

]) used to

modulate digital data transmission. Notice that p is the ratio of 314 to 100 , f is theoscillation frequency, sin (.) sinusoidal function, ln(.) is logarithm function and lim (.)

presents the superior boundary or the maximum value for a given set of signal values.

In fact, frequency oscillation realizations is the aim object of digital data transmission branch fields. The simple way to achieve this is the usage of circuit included in figure 11 .Incurring onwards send-receive those frequency is the subject aim of digital datatransmission such this involved within digital satellites processing analysis. The mainoriginal theme of this incurring onwards is the data encoding decoding processing analysis.Hence, Shannon did propose an idea of data encoding based on the bit-word-lengthcalculations thus the minimum amount of bits to be used to encode a character a for examplefound in an alphabet set of N characters. This number is thus calculated 2 x= N +1 . Tosearch x, just introduce the logarithm function as follows: 2 x= N +1log 2(2

x)= log 2( N +1) .Therefore, this x number could be determine as follows; x= log 2( N +1 ) .

Indeed, the logarithm conversion between bases is: log a ( y)=ln ( y)ln (a ) .

Thus, x= log 2( N +1 )=ln ( N +1)

ln(2) , where ln(.) is the natural logarithm function. As example,

where the ASCII code ( 255 characters) were encoded, the amount of bits was eight bits.To encode one character from the 255 character alphabet set, a sequence of eight bits isrequired for example 10011010b . To send this character, the above techniques such thecharging and discharging of the capacitor of figure 11 eight times or more would beinvolved. In fact, the 1b represents the highest magnitude amount, however the 0b representsthe nil environment of the magnitude amount. An other methodology is to convert such a

binary sequence to integer value and to use the potentiometer command and controlling for

16

[sin(.)] .[probability.Log(probability)] wave-form modeling simlation processing [sin(.)] .[probability.Log(probability)] wave-form modeling simlation processing where probability is a ratio of signal value at iteration i to max signal value.where probability is a ratio of signal value at iteration i to max signal value.

time

m a g n i t u d e


17/43

digital-analog converting. Figure 8 represents such a processing analysis.

3.4. Measurement processing analysis aspects:

As aspects define a way in which something can be viewed by the mind or appearance to theeye, measurement processing analysis aspects are viewpoints and onwards outward

appearances. To use the computing-compiling-concluding unit in order to visualize thoseviewpoints and outward appearances, an interface PCI card, such this model cardmeilhaus. 300 , would be developed and integrated within the processing. Thereby, the modelcard is an interface card for IBM-AT and compatible with ISA- 16 bit stuck capacity or more,with Analog-Digital and Digital-Analog converters, and with 24 Transistor-Transistor Logic(TTL; 7400 , 7804 , etc,...) input-outputs. This model card could be involving software

programming using C-language or other similar languages.In fact, Analog-Digital converter generate 12 bit word throughout 16 channels; Analog-Digital channel 0 to Analog-Digital 15, or 8 differential input channels and a multiplexer. Itsfrequency is variable from 0 Hz to 200 KHz. The manipulation of the converter elements,which are bloc devices and input-output types involving in; single or multiple timer, trigger and interrupt mods, chosen channel number, unipolar with positive values or bipolar withnegative and positive values and magnitude gains. Within the software development, those

bloc devices and input-output types are addressed, interrupted and manipulated. Two typesof programming converter are distinguished: programmable gate array PGA 203 for which,the magnitude gain is 1or 2 or 4 or 8. Furthermore, the unipolar voltage value variations areengendering in the following measurement set;

{[0V 10V], [0V 5V], [0V 2.5V], [0V 1.25V] }

The programmable gate array PGA 202 for which the magnitude gains is 1 or 10 or 100 or 1000. For this PGA 202, the unipolar voltages are engendering in the followingmeasurement set; { [0V 10V], [0V 1V], [0V 0.1V], [0V 0.01V] }.

The choice of one of those input-output types is based on software development. Notice thatthe converter receives its input-output via a sub-digital connector (50 pins). The Analog-Digital (reference of such a ADC is MAX176) converter is powered by 3W DC/DC converter.However, the Digital-Analog (reference of such a DAC is DA664) generates a 12 bit wordthroughout four digital-analog channels, which are channel A, channel B, channel C, andchannel D. It is connected directly to the 16 bit data bus and the 8 bit address of thecomputing-compiling-concluding processing unit. It is isolated by 1W DC/DC converter. Tosecure the converter, each channel is connected to the ground of the converter by resistor

and capacitor as described in figure 11. Hence, digital input-output system (reference of such a system is BCT543) generates an input or an output word of 8 bits as defined in theexample of ASCII code in the previous section. The choice of digital input-output ports,which are;

{(DIO port A 0, , DIO port A 7), (DIO port B 0, , DIO port B 7), (DIO port C 0, , DIO port C 7), and (DIO port D 0, , DIO port D 7)}

Only one those ports is chosen for any digital input-output processing analysis throughsoftware development.

Indeed, registers involved within this model card are 8 bit-word register used for control and

17


18/43

16 bit-word used for instantaneous data storage. Although, Timers (reference of such adevice is 71054 ) are synchronous devices with the 8253 compatible. It has three 16 bit timer .However, the first one and the second one are cascaded, the third one is independent. Thesecond one generates a frequency of 1.5MHz . The third one generates a frequency of 3MHz .Thus, the output of the first one activates the channels. The time of this channel activationsis controlling via the scan-time input of the first one, which allows the control of channel

activation.

Figure 13 : model card meilhaus300 for logic bus interface communication

Figure 13 shows the different on board components of the model card meilhaus300. Thismodel card is a PCI interface IBM-AT compatible card.To visualize measurement processing analysis aspects using this model card, software

18


19/43

development based on C-language or similarly would be used. Thus the usage of thecomputer as oscilloscope to illustrate the received data from the model card and put theminto the display throughout putpixel(.,.,.,) function. The x-axis is then chosen to indicate thenumber of iteration involving within data reception and the y-axis indicate the magnitudevalue levels of the received voltage from the model card. The division processing analysis isarbitrary choices for users.

To use the involving within this model card software development for graphics visualizationin two dimension coordination system such that x-axis or exactly time-axis and y-axis or exactly magnitude-axis, sensor requirements are incurring. Therefore, many sensor kindscould be distinguished, which are low noise bloc sensor, temperature sensor, velocity sensor,volume level sensor, etc.. Hence, the original main assigned sufficient suitable tasks are tosearch and investigate sophistical sensors, which allow true right converting of detected datato voltage measurements.

3.5. Conclusion:

In this section an overview on how to measurement principles was given. The secret sign of these measurement principles is the usage of interface model card for gathering databasesvisualizations as viewpoints and outward appearances on LCD displays or similarly. Thismodel card could be used for many applications depending on the within involving sensors.As next step within this digital data processing analysis is the storage space optimization tosave huge of digital data on currently used hard disk. This requires digital data compressionto be involved within.Many digital data compression techniques were invented and used, which are Cadencemodel VCD (value change dump) filling in files (reference http://www.cadence.com ),Lempel-Ziv (gzip command), tar command, jpeg compression techniques...

4. Some synchronized following data flows' compression techniques:

4.1. Introduction:

As digital data transmission and manipulation start to grow up, the to associated hard disk storage spaces become the most around measurement ability. To resolve basic logicinfluence systems on those measurement abilities, mathematical arrays using different kindsof data compression techniques are invented. Some of them, the most average used withindigital data transmission and manipulation are Cadence model; VCD fill in files .This technique, which was developed by me, Said Mchaalia, in 2000 September in

Dortmund CEI , has the following format shown in figure 14 . Whereby, the header file

contains general gathering data information, which are date, version and time units, andscoping modules' naming and declarations. Then after, transition event occurrences, whichare instantaneous couple values of transition time values and transition event activity values.Hence, grounded to discrete event simulation theory, which ascribes modeling andsimulation by couple set {( time event , value even t)iteration } for each discrete iteration inside

processing analysis. Thus, when an event, which is instantaneous occurrence associated withthe change of states inside system environment, a time transition and signal value transitionincur and sustain to be maintained and filled in the value change dump file. Themeasurement units involved within this value change dump file are nano second or other simulation time unit and binary sequences, which are the amount of bits for signal encodinglike the famous eight bit-word used within ASCII codes . In digital signal processing,

19
http://www.cadence.com/http://www.cadence.com/


20/43

instantaneous event occurrences should be converted to iterations by the methodologytechniques; time = nT /n , whereby n is a varying number from nil to infinity.

Figure 14 : VCD (value change dump) file format developed on September 2000.

20


21/43

Although the organization methodology to develop such a VCD fill in file like that shown in figure 14 , is depicted with figure 15 . Thereby, figure 15 shows the principles of the compute-compile-conclude processing analysis aspects. This processing analysis is grounded todiscrete event simulation. Thereby, the just values or parameters are incoming data for eachtime value events. These time value events is characterizing the manner to change the

synchronized simulation time either within the events, which occur on the clock cycle basedsimulation or synchronized time values with event occurrences on driven cycle basedsimulation. For example the phenomena of light color changes.

Notice that sign could be any object, action, event, pattern, etc., that conveys a meaning.

Figure 15 : principles of discrete compute-compile-conclude processing analysis

21


22/43

The main intentional background development depicted in figure 15 , is the principles of language measurement synchronization. Furthermore, civilization is the local processwhereby following flows achieve an advanced stage of development and organization.Hence, cultural fill in or intellectual refinement, which is good taste deduced throughoutgenetic algorithms, or fuzzy logic and neural networking processing analysis. In fact, these

algorithms have mimetic and mnemonic object aims involving within human society thathas highly developed material and spiritual resources and a complex cultural, political, andlegal organization that is an advanced event states within social development environments.

Indeed to make and to burrow (which means moving or progressing by or as if by diggingholes or tunneling) are two original main primordial event attributes, which ascribe andrelate incoming data to inherent sources of quality and office characteristics. In fact,neutralism is a core processing uniform-unity, which has to role and rule event states duringthe progress of inherent data sources. This inherent data source progresses is starting fromread-signal or start-process node depicting mathematical functionalism of registeringand triggering, which is pulse or circuit that initiates the action of another component. For

example using Timer 71054 within digital transmission processing analysis as shown infigure 13 and ascribed in the header of each VCD file (value change dump file) as viewed infigure 14.Finally there, zing and yes are output nodes, which represent measurement of differential databases levels. Whereby zing, which means move and progress fast,

permits digital sensory; transmitting impulses from sensors to the model card meilhaus300to be processed within modeling and simulation task and threads' achievements. Thus,transmitting impulses are incoming data within shortest time intervals.

4.2. Binary decision diagram processing analysis:

In section 1.1 ., an overview over collect data and its storage in binary format was illustrated.For further manipulation of the stored data, some viewpoints of binary decision diagram

processing analysis would be hereby presented.General purpose following motor flow of the binary decision processing analysis could bedepicted in Figure 16, whereby the gathering discovering data information's database startwith the start-process node and finally the end-process node collect inside circuit signalsand send them to the grounded to gathering database information node. The followingmotor flows of edges, which represent data values, are binary values from received datathrough the incoming data node input signals. For example, received 6 volts would beconverted to 00110b and so on. The incoming data has the format of (time event , value event ). For example, (00.00.04, 9 volts), which would be converted to ( 00000000000000011b, 01001b ),the first binary inside-couple value represents the event time and the second binary inside-couple value represents the event value. The further processing of obtained event activitiescharacterizing event occurrences are enveloped inside a self set of couples:

{(time event , value event )}index . To start binary decision diagram processing analysis, sufficientsuitable measurement array of event activities is required. Thus, this measurement array is

based on the indexing system sign of event occurrences. The start process node illustratesthe index null of event activity inside the envisaged system environment to reachmeasurement calculations within modeling-simulation processing analysis. In fact, in many

branch disciplines, these measurement principles are always within involved, because thecore processing unit is an arithmetic logic unit, which manipulate insight's binary values.

22


23/43

Figure 16 : following motor flows of data edges inside considered measurement circuit.

Figure 16 represents the following motor flows of data edges in binary format insideconsidered measurement circuit.The start process node has role as interrupt circuit to start collect of data to be measured

23


24/43

within simulation time. End process node plays a similar rule as power off switcher.Furthermore, the other nodes are arithmetic-logic operation nodes. The following motor flows of data edges is that the following values are binary whose last values areinstantaneously stored within grounded to gathering database information node.

4.3. Digital data compression techniques:

The mainly used digital data compression techniques are those whose roots were comingfrom Lempel-Ziv and co theoretical aspects and effects. The bright idea of such a datacompression technique is the usage of the sliding windows background development.Whereby, focusing on the windows that allows the absorption of the most significant amountof digital data involving during modeling and simulation processing analysis.Thereby, the utilization methodology is to fill in the mere (slight and small in quantities)

array by moving sliding window most around left side and right side of the center digitaldata amount.In dictionary digital data compression techniques, the involving algorithm could be describeas follows show in table 5 .Table 5 illustrates the algorithm development for dictionary digital data compression basedLempel-Ziv and ASCII coding ideas. Whereby, table map tables were involved, one hashtable for instantaneous storing vector of characters and another one for instantaneous storageof character position inside a file. This character position is characterizing by the character

position in line and the line position in the file. In C-language , the data type declarations aredefined as that illustrated within Figure 17, which views over digital data compressiontechniques.

24


25/43

Event Time Characteristics

define mere array for data storage.time t ,

whereby set local globalsimulation timer to timet.

mere array is hash table of index ed vector of characters.In C-language;typedef map hashtable;

define mere array for position storage. time t + t mere array is position table of vector of integers. In C-language;typedef map positiontable;

reading current character time t + 2 .t store it in the hash table and then store its position in the position table.

searching if read character is inside the merearray

time t + j. t

j > 2

searching within the position table based on the character key. If the return value is not nil, this character existsinside the hash table, thus just store its position in the

position table. Else, store it in the hash table and its

position in the position table.

while not end of file {moving sliding windows to next character andloop the operation to reading character stepagain. }

time t + n. t

n > j

The fastness of this algorithm depend on the number of clock cycle reserved for the read from files and writing inaccess memory.

when end of file {storing the hash table and position table in afile.}

time t + m. t

m > n

The fastness of this algorithm depend on the number of clock cycle reserved for the writing in files and readingfrom access memory.

Table 5: digital data compression's algorithm development.

typedef map hashtable;typedef map positiontable;int main (int c, char *v[]) {

if (c


26/43

5. Conclusion of how to measure principles:

In nowadays designers have to verify a huge of complex levels of Digital circuits, embeddedsoftware and on-chip analog circuitry with fragmented methodologies that substantiallyimpede verification speed and efficiency. They also face a large number of technical issuesincluding design performance, capacity, test development, test coverage, mixed-signal

verification, and hardware-software co-verification methodologies. In fact, optimizingverification speed is a complex research subject. Overall, verification methodologies areused by the designers at a variety of design integration levels. To improve digital hardwaredesign using these verification methodologies, many digital simulation techniques are used.One of them is discrete event simulation, which has successful track record in theimprovement of hardware verification process. In contrast to other simulation methods (likedifferential equations) in which systems evolve continuously in continuous time, the systemsin discrete event simulation are described by discrete events and appropriate processes.Discrete event simulation performs, indeed, each event or transaction or item individuallyusing an appropriate process.Simulation, however, is not a satisfactory solution to the validation problem of digitalhardware for many reasons such as: each schedule (run) proves only the correctness of thedesign under verification for that particular sequence of inputs (stimuli); and only onedesign under verification state and input combination are visited per simulated clock cycle.However cycle-based simulation involves these simulation limitations, it is still asophisticated technology choice for the validation process of large synchronous systems, inwhich logical simulation is nicely scalable regarding to designer requests. To propagatevalues from system inputs to system outputs, a simulation clock cycle is required. After finishing one cycle, the next cycle will be begun. Moreover, practical cycle-based simulatorsallow for circuits with multiple clocks and interface to event-based simulation.However, cycle-based simulation ignores system delays and inter-phase relationships. Thislimits the amount of information about the design that can be extracted from the simulation.

Note that cycle-based simulation does not work for asynchronous designs and cannot beused in timing verification. Event-driven simulation environments uses the traditionaldiscrete event simulation mechanism and considers system delays and inter-phases.During each verification process using either cycle-base simulation or event-drivensimulation, we have the opportunity of outputting the simulation results to waveformdiagrams. For a detailed performance evaluation of the design under verification, a signaltrace file format called Value Change Dump file (VCD file for short) has been developed byCadence to store signal waveforms. Not only the input and output signal waveforms arestored in this file, but also the internal signal waveforms too. The waveforms will be neededto get out a trace of the real behavior of the designs. By this way, the physical size of this

file can become excessively large, although the signal waveforms are held in this file in acompact format.On the other hand, using cycle-based simulation allows to reduce stored signal waveforms,

because it does not consider all real transactions of signals that are for example caused bydelays and inter-phases. But this will not be useful to improve the verification process for alldigital circuit types as well as to perform timing verification.

Nevertheless even when using cycle-based simulation, the generated waveform files areusually huge, often exceeding the capabilities of the storage system. As follows, first of allwe did present an overview of digital design simulation and describe how waveform can begenerated during the simulation process. Secondly, we did introduce the benefits of discreteevent simulation and cycle-based simulation in detail, and illustrate how they will be used in

26


27/43

our work. Finally, the format of a signal trace file, which is created during the verification phase and digital data compression techniques were discussed.This was the how to measure principles paper. Next a small annex about different cultureviewpoints will be presented.

6. Annexe: 09/11/2001 references and performed hyper tasks and threads:

Searching of compute-compile-conclude aspects from life believers and performer examples. Thusthereby the viewpoint of the invisible Satan of George W. Bush processing analysis:{

Bush means basically to extend in a bushy growth and to grow or branch out like a bush, which islow shrub with many branches.In Shannon's basics theory (see Shannon paper 1948 : mathematical information theory), bush is setof 4 letters, which are {B, U, S, H}. To perform a philosophy processing analysis (ppa) based on afinal intention and aim to reach a holy high values' level, a language fission (splitting) philosophy

processing analysis (ppa) is involved. This ppa can be illustrated as follows {

B (be or not to be balance): Eblis (Event basic logic influence system) or Iblis (index base's liable insight secret) existence from Adam creationism until life-end on Earth. Theinvisible Satan dynamism is defined in the dualism (condition of being double; duality)of computation-provocation aspects. This is a balance engine (means of accomplishment).

U: provocation of Uniform-Unity from invisible and visible philosophy analysis of real-

wares. S: processing analysis of Satan system dynamism. H: secret of holy high heaven level. It is a great/big question. }

}

6.1. Discrete dream events philosophy processing aspects, modeling-simulationexample Earth's study .

Earth's study is growing in huge with the advances in digital modeling and simulation aspects.

However, the background of such a science is wrong and not logic. Therefore, the principles of logic and true right be awake aware to basic logic influence systems should involved within anydigital modeling and simulation.Figure below, figure 100, shows basic logic of Earth's study example; the shape-form of the Earth.Indeed, the true right shape-form of the Earth is the many several cylindrical viewpoints at anyheight from a flat surface on the Earth's ground. Heights from flat surface on the Earth's groundcould vary from 1 meter and less to 400000000 meters, whereby the distance of the unknownEarth's planet was defined starting from 1969. The visited on 1969 planet may be Earth's planetwithout name, because the Earth's Moon emits light forever. Hence, for more information of thelight emission, see the 400 watts light bulbs and compare the modeling-simulation effect results tothe light emission from that planet and other active alive objects in the Earth's Sky.

27


28/43

Figure 100 : true right outward appearance of shape-form of the Earth isthe several cylindrical viewpoints at any height from a flat surface on the Earth's ground.

Existence studying of Satan systems and their dynamism within discrete dream event aspects,whereby, mind composition is clean clear invisible language philosophy processing analysis.Thereby, do while processing of real-wares and compile conclude philosophy processing (do something that is real). Furthermore, while the condition is satisfaction with basic logic influencesystems, begin doing some synchronized following onwards flows. Therefore, languagecomputations onwards instructions processing ( C, L, I, P ), which means seduction and temptationsecrets. Whereby fatal fear on holiness destination whose object aim is first Satan following roleflow, which is knowledge disastrous fear. The intention and aim of Spiritual Satanism is to applythis gathering information database and transform the souls into Godhead and Godhood defined in3K {

first K not defined K-word = Jesus, which means surprising.

28


29/43

second K is the K-word King = not defined, which means the selfish autonomy to be aliveaway for true right doing.

final k is the K-word Lord = human Satan: philosophy processing aspects. This is the hardhyper task to have been understood.}

On other hand, language computation's instructions processing philosophy (LCIPP) requires science

knowledge of Satan systems whose seduction secret aim and temptation results outcomes {this analysis can be divided into many steps {

First step: philosophy i-processing: introduction, instruction, inside, innovation. Thisi-processing is primordially and fundamentally.

Second step: philosophy processing in 3D system scaling and time-base withinseductions and provocations; this inside thinking-treatment is visible illusion. For example, the blacksun.pdf ( http:// www.thenewgnosis.org/ blacksun . pdf ) is visibleillusion grounded to famous following flows. Whereby, many authors did write"Globalization and "McValues" are the death of all root values." In my clean clear compute-compile-conclude aspect analysis the globalization and "McValues" should

be based on communication and culture exchanges throughout the innocent ways of the highest holy spirit backgrounds.

Third step: philosophy processing of innovation's objects. Thereby,(http://www.science.nasa.gov ) develops discrete event simulation's modeling-simulation tools to be awake of event occurrences in the Earth's Sky and its systemenvironment.

Fourth step: philosophy processing of sciences complexity. Hence, scientific aimdestination is true right description details of gathering databases information.

Fifth step: philosophy processing of correctness's language cleanup(s). Thistheoretical methodology is defined as follows whereby compute language instruction

processing can be {

i. philosophy processing of clean lust invisible instructions.ii. philosophy processing of logic clear aim and object destinations.iii. philosophy processing of compile false instructions and correct them.iv. philosophy processing of classification loop instructions: inside loop seduction's

secret and effect results processing analysis.v. philosophy of complex large instruction processes.vi. philosophy of combine lord instruction processes (As reference: processes in

Very large scale ICs Hardware Design Languages are primordial cores discretely defined asassigned values). 6.2. Philosophy analysis of real-wares aspects : performed hyper thread-tasks or mathematical energy theory :

Analysis information: Satan system aspects is a big question in the discrete dream event's philosophy analysis. Satan is first enemy for high holy heaven home last step to have to be. Satan principal tasks are:- to recall or exercise by means of a lure or seduction.- to draw with a hint of pleasure or reward: attract actively and strongly of event occurrences.- to provoke someone to do something through often false or exaggerated event attributes.

In nowadays, mathematical energy theory becomes aspect notes for digital data transmission

29
http://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.science.nasa.gov/http://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.thenewgnosis.org/blacksun.pdfhttp://www.science.nasa.gov/


30/43

researchers. Starting in 1928 with sending telegrams, researchers were interested in encoding andmathematical and technical power formalisms, because mathematical energy aspects are in timeintegrations of inside mathematical and technical data modeling-simulation processing analysis.

6.2.1. Einstein performed thread-tasks for mathematical energy theory :

Einstein performed thread-task in mathematical energy theory, is the famous formula: E = mC 2 , where m is a weight in SI system measurement, and C is light velocity as defined

constant in SI system measurement. Indeed, light velocity was never be constant. Furthermore, lightvelocity could not be nevertheless determined whereby philosophy processing analysis aspectswould be investigated within modeling-simulation processing analysis. Although, clear compile-compute-conclude processing analysis of mathematical energy theory is the how to measure

principles inside Watts' measurement calculations. Therefore, first of all, a clean clear mathematical power theory should be investigated. As original main thread-task of power measurementcalculation is: a.current (t )event . voltage (t )event , where 0


31/43

6.2.2. Planck performed thread-tasks for mathematical energy theory :

Planck performed thread-task in mathematical energy theory, is the famous formula: E = hN ,where h is his constant in SI system measurement, and N is wave frequency as defined variable inSI system measurement.

In fact, from the above experiment results defined in section 6.2.1 , within same frequency valuesand distinct power values of envisaged light bulbs, the energy could never be thus constant, due tothe constant value of the h, which is the definition of Planck's constant; seehttp://hyperphysics.phy-astr.gsu.edu/ for more details about this mathematical definition of energy.

Figure 200 : proposal electrical circuit of Light Emission processing analysis.

Figure 200 depicts an electrical circuit of the phenomena of light emission. Light could onlyemitted and transmitted using Light Emit Diodes and light bulbs or similarly. Therefore, themeasurement quantities of lights and whose velocity is depending on those involving tools, suchelectrical energy-to-light converter toolboxes.

Indeed, these energy-to-light converter toolboxes allow light motion anywhere. The most aroundapplication is the disco emit light gaming-operations, optical-fiber data transmission, electrical arcs,the color of Earth's Sky at night and so on, whereby the movable distance of the produced lightcould be may be attained 400000 meters or more in the next high-tech light bulb production

processing.

In fact, the motion of light is hard thread-task to be achieved. Nevertheless, the true right lightmotion velocity is original main sufficient suitable organization flow for researchers in electrical

branch and field's disciplines, whereby the true right definitions of velocity should have beenintegrated within any light motion phenomena study.The insight of logic processing analysis of light motion velocity with source energy batteries of carsand trucks, is the distance variations belong to this light velocity motion mechanism from 1 meter

31
http://hyperphysics.phy-astr.gsu.edu/http://hyperphysics.phy-astr.gsu.edu/


32/43


33/43

Therefore using Lepel-Ziv, Issac Newton, Kaufmann Kohler and Shannon's Theories, The rootvalues, which will be killed in blacksun.pdf (see page 04), should be the origins of each processingtask and thread.{

(letter J = just) [space] (letter L = language) [space] (letter K = core) [space] (letter M = make)[space] (letter N = neutralism),

where (K) is origin inside sign's kernel and [space] will be characterized with ||.

Dream philosophy analysis first step: change root two alphabet around (K), two letters forwardfollowing flows or two letters backward following flows from (K). So, either alphabet "N"[Newness-innovation] or [Neutrality-Water = innocent background minds] or alphabet "J" [JesusJoy] or [Limitless Lordship]:

J || L || (K) || M || N, where (K) is origin inside sign's kernel.

One letters forward or one letter backward following flow from (K). So, either alphabet "L" [Loverelationship] or alphabet "M" [Imagination Design];

J || L || (K) || M || N, where (K) is origin sign

6.3. 3. Second start-root; "A" from alive being: it is a person, it is home, it is a president, it is anation, it is a...

Y || Z || (A) || B || C, where (A) is origin sign

Two letters forward following flow or two letters backward following flow from "A";So, either "C" [Can Center Consume], or "Y" [Yes Year [You Yours]]

Y || Z || (A) || B || C, where (A) is origin sign

One letters forward following flow or one letter backward following flow from "A";So, either alphabet "B" [Belong [(Be or not)] or alphabet "Z" (zing which means move quickly as itcould be).

6.3.4. Second step; color processing analysis indications;

Black => damage and dangers effect aspects. The basic light color of Earth's Sky.White => saint philosophy processing analysis. The main original primordial day's lightcolor to allow distinguishing between colors for each instance at time unit in seconds.However {

safe secure contact with processing analysis results, dark and/or secret following flow of outcome (final product or end result) may be badness or happiness.

} 6.3.5. To explain numbers meaningfulness (purpose or value)

i. two is a binary base whose element is bit which means true or false.

33


34/43

ii. 2 = 10b, first one is true if this so defined or false either and vice versus.iii. 2 indicates that there are just two types of choices either to believe strength of 2 invisible

systems or to believe philosophy processing analysis.

Note {i. outcome; a final product or end result; consequence; issue.

ii. outcome; a conclusion reached through a process of logical thinking.And

j. meaningfulness; purpose or value. jj. meaningfulness; significance.

6.3.6. Conclusion;

Resolving a task in computer language instructions processing philosophy is a binary prediction of occurrences of events. As reference see in details the discrete event simulation theory, which isdescribed as follows: for a given time value, an event is occurring on the considered signal duringthis signal processing. Therefore, this simulation could be formulated within a defined couple(time event , Value event ). A sun-up (rising sun light from light red color to blue one) is an eventoccurrence, which changes in time for a reference time set as global time (in winter time is about 08o'clock am and in summer time is 03 o'clock 30 am in Alaska/USA). Therefore, grounded to theabove details; the Earth's Moon emit light. This light is a white color light, which changes its eventoccurrences for each day within a month. So, based on the works of Issac Newton, Einstein and co,the white color light is a composition of main primordial primary colors, which are: light red color,light yellow color, light green color and light blue color.

Next step is to know that a required frequency is needed to make primordial white color light fromthese four main primordial primary light colors, which are: red color light, yellow color light, greencolor light and blue color light. This frequency after experiment results, should be at least 22KHz(22000Hz) . When having to convert this 22KHz to meter per second as wavelength propagationsinside a space-time system characterized by a coordination shown pictures, so the diameter of desired object to be used should be determined.As similarly, an object for a given circle with a diameter of 8000 miles , the having to be convertedfrequency of 22KHz in wavelength propagations length-language is 0.5x2xpix8000x22000 miles

per second unit time. This is equal to 552.92x1000000 miles or 552.92E6 miles per second unittime. This indicates that the rotation of a given point at the flat surface of this objectshould be in rotation motion with the velocity value of 552.92x1000000 miles or 552.92E6 miles

per second unit time.

The basics of computer languages is the compile-compute hyper tasks and threads inside any signal

processing. Indeed, these hyper tasks and threads could be easy translated to compute-compile-conclude processing analysis aspects such that fuzzy logic secret processing on high and holyvalues analysis philosophy. This analysis philosophy is a nice effect throughout obtained simulationresult's background within learning functions such that a movable in time sin 2(2 ft + ), which isexactly characterizing the amplitude modulation in the field of digital data transmission, where f isthe frequency of considered digital signal, t is synchronized time for a send-receive operations, and is the phase of this signal. In electric field starting from the resolve of basic logic influencesystems on the measurement parameters such that power (voltage), intensity (the brightness of agiven image), the puissance and the energy and perhaps other measurement parameters, whichcharacterizing waves and particles in motion. In fact, for the measurement parameter puissance, the

basic definition is the scalar product of the primordial main primary measurement parameters,

34


35/43

which are the power (voltage) and the intensity (in Amperes). In supermarkets, measurement of puissance is in Watts.Hereby, as defined in early Greece Archimedes Theory, the energy or work is the integral functionof the applied forces in a given time period on considered system. For some electrical applications,the energies are calculated directly from the integration in time of the puissance.

E = P ( f ,t ). dt where P(f,t) is the electrical puissance defined as follows:

P ( f , t )= a.sin ( f , t ). cos ( f , t )

Where 0 < abs(a) < 1, and sin(.) is the sinusoidal function. Furthermore,the cos(.) is the integration or may the differential function in time ofthe sin(.) and the abs(.) is the absolute value.

P ( f , t )= b.sin ( f , t ) . sin ( f ' , t ) where 0 < b < 1.

In Electricity domains, the outward appearances mistakes is to consider energy as h x frequency (

h. )where h is the Plank's constant or mC 2 ( mC 2 ) where C is the white light velocity and them is the weight of any object in kgs or lbs. These two outward appearances mistakes are clear.Indeed, for many bulbs within different puissance's values, which vary from 25 Watts to 480 Watts,the wavelength propagation is moving from 1 meter to about 300 meters bright light. Thereby, thisexplains so easy that the wavelength propagation depends on the puissance's values, which have

been bought from any supermarket. Neither Plank nor Einstein did exactly define the energy in itstrue right formalisms. By this way, the white velocity could not be constant but strong secure surevariable function the energy to be emitted.

Figure 17 is showing the usage of sin 2(2 ft + ) function to modulate the amplitude within digitaldata transmission.

Figure 17: using function sin 2(2 ft + ) for a given digital signal modulation.

Note that to receive back just a white picture from Astra satellite in a far way distance about401000000 meters , a 16GHz emission frequency of this picture is required. This frequency is

35

-1.5

-1

-0.5

0

0.5

1

1.5

square(sin(.)) used witin amplitude modulation

time

i n t e n s i t y


36/43

produced by an electrical oscillator characterizing the magnetic effect characterizing the loadstonesof electrical energy in magnetic form to be sent( L.i ( f ,t ) dt ) and electrical effectcharacterizing the charging within the capacitor ( C. i ( f ,t ). dt ). The within energy is just thecalculation of the power, which is about 24Volts and current intensity, which is varying during thetransmission process. Now the growing gradually actually question is: which current intensityshould I use within this send-receive digital signal processing?If this current intensity is 1Ampere, then the energy is E = 24 Watts x Seconds (seconds time areneeded to receive back the white picture which was sent).

Figure 18 : sending databases source

Figure 18 is characterizing the movable energies during a digital data transmission process. In this processing mechanism, the database can be text files, mpg files, or echos or other types of gathering database information. Notice that the energy is never being constant. In gray-rueconsequence effects on resolve basic logic influence systems, the energy is function of at least theamplitude of data to be sent. Not only the energy value calculations are wrong by Einstein or Plank

because their variation during digital data transmission process, but also the definition of exactlymeaningfulness of the energy transformation forms. Indeed, the energy magnetic form is adifferential variation during the processing mechanism of digital data transmission. This illustratesthat this differential variation could be nil for a given time. It means that it varies so small inquantities for shortest time intervals. On the other hand, this would never allow a creationism of magnetic fluxes to be transmitted to a given destination.Furthermore, the electrical energy form is a storage envelop to be used when it would be required.For example, the charging of capacitors. These capacitors could be then used in electric utilizationinside cars.

In fact, the light transmission tools are basic deduced from growing gradually actually technologies.These tools should till now be a magnetic and electrical material energy converters. For examplecapacitors and inductors.

36


37/43

Figure 19 : electrical material energy converters

Figure 19 illustrates the material used in electricity domains to allow light to be movable in time.

When, we observe the Earth's Moon, we see light inside the Earth's Sky. Therefore, which materialwere used to emit this light most around 14 hours sun-light in winter time (see figure 21)????

Notice that discrete event simulation theory is needed to have been understood. Then, first of allreading computing techniques: such that the quadratic formalisms is needed. And after language

processing philosophy analysis: which languages are most around required?

6.4. Philosophy processing analysis following flows:

In this section, the invisible decision design is ssssfofo : strong secure sure safe first one fly on; suchthat language processing philosophy analysis. The language processing philosophy analysis is basedon the Shannon's Theory. The Shannon's Theory uses the probability and the stochastic aspects of digital data transmission elements to achieve its hyper tasks and threads. As result of language

processing philosophy analysis, two alphabet sets, which are {J L (K) M N} or { F F (Eblis) F F or (Eblis) F F F F }. Where (?) is start-origin. Where (K) is an origin sign and (Eblis) origin sign toothat means Event's basic logic influence systems. Note that the system's definition can be so smalldimension system such that the atom of helium or so large such that the Earth's planets, which arethe eight visible planets: Earth's red planet, Earth's Saturn, Earth's Mercury, Earth's Venus, Earth'sJupiter, Earth's Uranus, and Earth's Neptune.The sub-alphabet{JL} is the famous join-link following flow inside compute-compile processinganalysis. This famous join-link following flow motor flow is a background structure insideinstruction language processing. From dictionary definition, to join means to connect (see

below). By this way, in many application fields, each entity could, should or would be connected or exactly joined to its associated group. Notice that an entity is a model of black box involving inputsand outputs. Furthermore, from dictionary definition to link means to be got ready for execution.On the other hand, the sub-alphabet {MN} is the famous main-nucleus following flow insidecompute-compile processing analysis. Main structures programming languages are most aroundusing C-compiler. So, the basic structures within the execution process is the starting from main up

processing analysis aspects. The nucleus is a measurement unit used in many fields to indicate justone entity or element. In English language, it represents just one letter or character for example x.Indeed, a nucleus is normally a particle, which involves within positive charges and negatives too.Grounded to the physics investigating material states, the hydrogen is currently the nucleus atom.

37


38/43

This atom contains mainly just one negative charge or may be more in the conduction band and justone positive charge or may be more in the valence band. In the neutral material state of this atom,the number of positive charge should be be equal to the number of negative charges too.For example for a given battery of car, the chemical equation is defined as follows (illustratedwithin equation 1):

PbO 2+ Pb +2H 2 SO 4 PbSO 4+2H 2 Oequation 1: charging of Plumb battery

The positive particles in this equation (equation 1), are the PbO 2 charges (dioxide of Plumb) and thenegative particles are the Pb charges (Plumb). Another charging equation model is the following equation (equation 2):

Fe +2Ni (OH )3 Fe (OH )2+2Ni (OH )2equation 2: charging of ferrous-nickel battery

The positive particles in this equation (equation 2), are the Fe charges (fer) and the negative particles are the Ni(OH) 3 charges (nickel and co). Another charging equation model is the followingequation (equation 3):

Ag + Zn(OH )2 AgO+ Zn+ H 2 Oequation 3: charging of argent-zinc battery

The positive particles in this equation (equation 3), are the Ag charges (argent) and the negative particles are the Zn (OH) 2 charges (zinc and co). Another charging equation model is the followingequation (equation 4):

Cd +2Ni (OH )3Cd (OH )2+2Ni (OH )2equation 4: charging of cadmium-nickel battery

The positive particles in this equation (equation 4), are the Cd charges (cadmium) and the negative particles are the Ni(OH) 3 charges (nickel and co).

Although, the considered above charging battery types involve positives and negative particles, theyneed current intensities to be full-charged and ready for different utilization kinds.The process of charging those batteries, is function of the couple (time e,, Amperes t) where I is theintensity magnitude at time t and time is a discrete event time value for a given intensity magnitude.The wave-form of such a charging mechanism is described by the figure reference figure 4.

38


39/43

Figure 20 : charging battery different kinds.In reference of figure 20, an overview over the required power or exactly the puissance is shown for different battery kinds.

Notice that this puissance is principally depends on the current intensity values. In fact, Ampere diddefine the current intensity as follows: the ampere (SI (system internationalism) unit symbol: A), isthe unit of electric current used in the system internationally. It is a measured quantity of electricityinside a circuit for a given time value. It is named after Andr-Marie Ampre (17751836), Frenchmathematician and physicist, considered the father of electrodynamics. Note that SI supports onlythe use of symbols and deprecates the use of any abbreviations for units [4]. In practical terms, the

ampere is a measure of the amount of electric charge passing a point in an electric circuit per unittime with 6.241 10 18 electrons or one coulomb per second constituting one ampere [5]. Byconvention, the electrons are negatives particles or exactly negative charges, which are movablewithin each electric circuit. One electron has a negative charge value of 1.19 10 -19 Coulombs anda weight of 1.241 10 -25 kgs. Notice that, a car battery is about 40 Ampere hour usage. In electronterms is 249.64 10 18 electrons hour usage.

6.5. Following flow theory stepping analysis (upstairs-downstairs follow flows):

Whereby, variable motor one is discrete dream event processing analysis. In this field,

39
http://c/wiki/Andr%25C3%25A9-Marie_Amp%25C3%25A8rehttp://c/wiki/Andr%25C3%25A9-Marie_Amp%25C3%25A8rehttp://c/wiki/Andr%25C3%25A9-Marie_Amp%25C3%25A8re


40/43

the differential value variation is the motor flow. variable motor two is binary processing analysis true or false and going fuzzy to analyze

these tasks and threads. variable motor three is secret information aspect analysis. Through which the database

gathering information will be fill in. variable motor four is famous fin following flows such that logic true right compute-

compile-conclude processing analysis aspects.

Objects {define a function of philosophy processing analysis, which simulate (compute

conclude) dream events} draft function formulation {

i. enough information from dream events.ii. discrete event analysis (mind composition effect aspect (appearance to the eye or mind;

look)).iii. sufficient invisible pleasure {satisfaction signs}.iiii. compile conclude processing analysis {clean clear consume commerce}.

} what does this mean?

This means {1. first fly on following flows: dream discrete events.2. following flow fruit food of Eblis = {follow flow fruit results deduced from Event's

basic logic influence systems}.3. analysis signs = {fiction, fraction, factoring, f-inside}.4. for loop philosophy processing analysis = home of Eblis (four words which are Event

basic logic influence).

Applications;F F or F F

as1. pronunciation problem solving English or American for example.

as2. combine the two items:F FF F or ( Eblis ) ===>F F F F.

as3. {only temptation language, this means just discrete seduction; { fear fiction of Eblis left or

right sides. Therefore, Eblis in

measur ment draft

Documents