a new approach in modeling

1. The ellipse model in related to fuzzy logic
a parabola equation x square= 4cy and y square= 4cx
If we add two parabola together, we create a pseudo ellipse from x square + y square = 4
c (x+y);
Assumed that x+ y = c (if we calculated it from Bayesian linear equation), we rearrange
the pseudo ellipse to be as (x square/ 4) + (y square / 4) = c square.
Fuzzy logic is disproportionate by itself. If we find another pseudo ellipse from an
interrogated paradigm of (x square /4) + (y square / 4) = C square. Then, we calculate the
crossing intersection of ( a , b ) from c = x + y and C = x + y.
The real ellipse will be (x square / a square) + (y square / b square) = (c square).
It means that if we add two hypothetical theories together such as 'the substantial facts vs
the question of law' and 'the less errors in legal procedure vs the reality of evident', we
will get a better prediction in decision making from informatics by computerized pattern
recognition.
A wild card in informatics, science, and
law
The following is my idea to build rubric in order to sort out needed data from legal
resources. My rubric is to set up A as agent (the judicial systems), C as congress, T
as trade (enterprises), G as government, U as people (like us), S as sub chapter s-
corp, B as sub chapter c-corp, K as sub chapter partnership etc. The second step is
to write computer programs for data mining and computer algorithm in informatics
and then extract those assigned codes such as A,C,T,G,U,S,B,K etc from considered
judicial database, and create some linked codes such as 'hashfljksafhhsahalhahg' .
XML is to markup those extracted codes 'hashfljksafhhsahalhahg' in the linked
syllables for computer to read and store those syllables, just like we read English
sentences to our memory. After that, computer will run neural networking, Bayesian
linear equation and Fuzzy logic.
The third step, XML may be able to interpret those linked codes
'hashfljksafhhsahalhahg' and write certain English sentences under their decision
making. Here, XML can use human English pattern such as the pattern of 'Subject
+ Verb + Object' and also indirect sentence 'Object + (is/was/are) + verb
transitive( past participle ) + Subject'. For example, Tom grabs a piece of paper.
XML mark Tom as Subject, grab as Verb, and paper as Object. XML reversely flips
back to write 'A piece of paper is grabbed by Tom.' The reason is that the pointer of
browser's icon will flip back to the original place when they write an indirect
sentence. At this moment, computer will ask us for feedback, then we give computer
some input to decide 'do it' or 'not do it'. The interactive relationship between
machine and human is built here.
Concerning some question of Bayesian application in legal mental calculus. I have
written essay of Bayesian application in informatics, but it is not in legal mind

2. setting. If we think that our metal calculus is also following rubric in our brain, then
Bayesian linear equation has its reason in pattern recognition because it is linear as
well as it is following the arm's length rule in Law. .
I like to answer another question about hypothesis of substantial facts vs less error
in legal procedure. For example, we treat an ellipse as a water melon, and we use
two knifes from two Bayesian linear equations, and we cut water melon into
different slices. We take a slice of intersection of points of (a,b) where C and c are
very closed. It meant that the lowest error percentage from legal procedure is to
mirror and match the substantial facts of real evident.
We might know that a wild card meant every thing in a poker game. Informatics might
have a wild card such as gap (empty space) in genetic codes alignment. Two sequences
are arrayed in parallel from their fixed positions in query on browser. But if we move one
array of linked syllables back or forth along fixed linked syllables to find the best score of
rubric matching, we might already create some gaps in between those two overlapped
sequences. Pointers in Unix systems will trigger 'do it' or 'not do it' choice, and decision
making under Bayesian posterior adjustment or XML Socrates questions will feed empty
spaces with pointers for an alternative decision making choice instead of only (0, 1) as it
is in the binary system, and the event driven of pointer will function as a wild card
launcher that pointer will mirror sequences better and create a real ellipse model from the
substantial facts such as forensic DNA finger print vs the subject matters of stature in
Law.
Rubrics database and syllables database are used to extract codes such as
'hashfljksafhhsahalhahg' for computational operations and reasons/decision performance
in neural networking, and XML database are used as tools to bring the pointers of
operating systems back to the original place where neural networking was previously
running. For example, a judicial decision is based on the initiative of intention from a
suspect, and the testimony from three parties' debating is narrowed down to the subject
matter of Law where stature is bound. If a judge owns those three databases-rubric,
syllables, XML, combined with Bayesian linear equation of posterior adjustment to those
two informatics systems such as neural networking, and Fuzzy logic, she/he will bring
the whole issue back to where it was actually happening in the disputed case. Then, judge
will assign stature in different possibilities under her/his professional trainings to those
XML questions 'do it' or 'not do it' and figures out the best possibilities in solutions under
Fuzzy logic with ellipse modeling.
My understanding of Bayesian linear equation is purposely for posterior adjustment, and
XML is also purposely to bring pointers back to the subject matter of Law by Socrates
questions. The graphic applications in informatics are embedded in the operations from
pointers but we may only see one pointer and it is the icon that brinks on browser.
Pointers are mathematically operated and computation maximum/minimum, algorithm
programed, networks linked and connected to those linked
syllables 'hashfljksafhhsahalhahg' in graphic applications, and I use twenty six machine
symbols for them such as (!@#$%^&*()<>?:"{}[[]|,./-~` etc ). In addition, those
approaches from two hypothesis from 'the substantial of facts in characters' and 'the less
errors in legal procedure in related to the subject matter of Law' is purposely by using

3. Bayesian linear equation to minimize errors from the posterior adjustment in order to
meet the green rule in mathematics in ellipse modeling. For example, just like that if you
cut water melon to slices by two knifes, the thin slice is done by holding two knifes in
parallel and making a narrow cut.
A Benzene Ring Dynamic Modeling Using
in brain reasoning as analogy as F# in
Music
A wild card operated in Benzene Ring Dynamic Modeling will be functioning as analogy
as installing a gap in DNA sequence alignment. It might mean that Benzene Ring
Dynamic Modeling is also reasonable if a wild card is applied in other rubric setting such
as F# in music. The whole concept of a wild card use might create certain fundamental
and dynamical mechanisms and that kind of option acts as it is in human brain reasoning
& thinking for the best performance. A wild card in Benzene Ring Dynamic Model might
function as 'do it' or 'not do it' in decision making that we are already familiar in neural
networking by using Bayesian linear equation in DNA sequences for posterior adjustment
and XML of Socrates questions in the ellipse modeling.
Benzene Ring Dynamic Modeling in informatics
This modeling is to apply a new dynamic modeling in order to match two series of DNA
sequences or some other linked codes that we use the benzene ring dynamic modeling
instead of using an existed molecular dynamic model for the purpose of DNA sequence
alignment.
Benzene ring dynamic modeling in music
A B C D E F# G or
A B C D E F Gb
( ) closed-up
In Benzene Ring Dynamic Modeling, if a wild card is functioning as interface and
vehicle in our brain reasoning, we might assumed that the wild card is note F# in Music.
It might mean that Benzene ring dynamic modeling is reasonable for use if it is applied in
music rubrics. The whole concept for wild card use might create fundamental and
dynamical applications as analogy as our brain reasoning. A wild card such as F# or Gb
will be used in benzene ring dynamic model that might function as 'do it' or 'not do it'
decision making in the ellipse modeling. Musical rubric is

4. A B C D E F# G or
A B C D E F Gb
Benzene Ring Dynamic Model in informatics