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Author
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Topic: Mechanically Specific Relativity
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KBC1963
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Member # 1868
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posted 27. January 2006 23:42
Thanks for your thoughts David,
I must however point something out about this part of your post:
"Just a caution on different types of scaling vs genome information. Cf
1 Mammalian scaling: Variation from shrew to great blue whale.
2 Growth scaling: Variation from conception to maturity.
3 Racial scaling: Variations due to migration / genetic segregation.
e.g. 150 cm pygmies to 200 cm khambas.
4 Gender scaling: Variations due to chromosome/hormonal expression."
Growth scaling as you call it is a preprogrammed control of system growth specificly designed into the blueprint by the intelligent designer. This function is specific to each design and cannot be the result of random evolutionary mutation as this requires to many highly specified parameters to be controlled over time.
Racial scaling & Gender scaling; or size differences among a specific kind only shows us the complexity of the control that was preprogrammed to allow for diversity in the design. observation of matings between two highly varied individuals shows us that at the point when the genes combine logic is applied to keep the offspring from having disproportionate parts which means that it is a genome wide control embedded within the DNA and at work at the time of forming, otherwise if evolution had any part in our formation then we would be creature of many oddities as a general rule.
Perfection of design and perfection of control combined is the hallmark of an extremely intelligent designer.
The idea of scaling I was referring to was that envisioned by evolutionist that are trying to logically make a creature change from the size allowed in its blueprint to a size that is not. which if evolution did it, it would be changes at individual component level and without an accompanying control set for every change there would be chaos which is why I say that evolution did not macro evolve anything as it is incapable of accurate shape formation combined with accurate control for all stages within the moment of mutation. Too many highly specified parameters must be in place at the beginning of the existence of the physical mechanical system.
[ 28. January 2006, 12:48: Message edited by: KBC1963 ]
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KBC1963
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posted 28. January 2006 13:51
Atom,
I just gave John a reply in his thread where I talk about balance and it made me wonder if in some way we can quanify it numericly in the calculation of MSR.
I believe this could be an identifiable & testable feature, Consider if you might that it is a measure of possibility of chance to attain balance within an interacting system beginning with two components working in concert and then graduating up to three components and so on.
Consider also that as the amount of components in a system increase they become more suceptible to random mutations that occurs according to known mutation rates. so at each point that a mutation is indicated to have to occur according to evolution then there should be odds against keeping system balance. Maybe you can define a simple mathematical formula that would show that chance as a creative force cannot {by its very nature} continuously over time keep complex systems balanced.
Once we can quantify this in some way we gain a heavy logic tool, the logic being:
Randomness is four dimensional in that it changes the properties of things subject to its force within the moment and it also changes things over time and a definable property is balance and we can show that balance is subject to randomness as an axiom of thought.
We should be able to posit that in order for a system to be selectable in an evolutionary way it must be as balanced as a predecessor otherize it is less fit.
So how about some math to accompany the definition Atom? How about collectively everyone helps to create the logic bomb that would nuke evolution out of existence.
"I have a dream" - M.L.K
"I have a vision" - K.B.C.
[ 28. January 2006, 14:03: Message edited by: KBC1963 ]
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Irving
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posted 28. January 2006 20:12
quote:
Let me now supply the evidence. When scientists were mutating fruit fly's they had all sorts of mutations occur such as the Hox gene mutations that literally copied entire structures such as legs and applied them in different locations, do you remember these? well no matter how well they were replicated they lost their function which is primarily because when a structure is copied the mutation would also have to copy the control system that operates it in order to make it function and the obvious results they got showed that the mutation was incapable of accurately copying the other Mechanically Specific Relative part of that system.
While interesting, not the specific evidence regarding interface specified complexity I'm referring to. The control system is external. I'm referring to the integrated interface of modular component. The posts and recepticles of a LEGO block is an example of independently specified information.
The "edges" of this image represent specified complexity.
[ 28. January 2006, 20:20: Message edited by: Irving ]
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David L. Hagen
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posted 28. January 2006 20:43
I agree KBC on how the scaling we see fits a design paradigm rather than evolutionary one. I was trying to distinguish what we actually see which shows strong evidence for built-in scaling vs a system where scaling was not included.
It might help to compare the older point oriented CAD packages from the later parametric CAD packages. When scaling a system, in a point oriented CAD system you have to change each single point. In a parametric CAD system only one or a few scaling parameters need to be changed. All the rest of the system changes proportionally as desired.
What I see KBC pointing out is that NeoDarwinian evolution appears to predict change like a point oriented CAD system. By contrast, what we see in nature is more like a parametric CAD system. This is naturally explanable from a design perspective. The MSR is proposed as a method of identifying and preferably quantifying these differences.
To clarify, here is a more generic example of the types of scaling that I see in nature that an origin theory needs to explain.
Scaling Requirements for Origin Theory
1 Individual growth scaling: Size variation from conception to maturity.
2 Bilateral symmetry scaling: Left/Right symmetry.
3 Gender scaling: e.g., Male vs Female Variations in size and shape.
4 Intraspecies scaling: Variations due to migration / genetic segregation.
5 Interspecies scaling: eg Mammalian variation from shrew to great blue whale.
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KBC1963
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posted 28. January 2006 22:29
Sorry irving,
I missed your intent, I do however agree that interfaces must be independantly specified as a physical structure and in my own way I have touched on that idea many times. My thought was that a novel physical structure would not automaticly fit into a system nor could it communicate without knowing the language the sytem comunicates with.
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KBC1963
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posted 28. January 2006 22:42
hey David,
You indeed made an exactly perfect comparison between point cad such as Autocad and a parametric such as Pro Engineer and in many less words you have shown my arguement. Without highly specified logic architecture no global scaling is possible, This may possibly tie into the balance arguement I am posting about now.
I really like your reference to mirroring or symetry left/right as this would require the the ability to coordinate system building with an end result in mind. I always wondered how we could have 2 eyes specificly placed to allow for focusing when it seemed more reasonable to have an eye on each side of your head allowing for 360 degree sight. How could evolution randomely mirror the structure of a hand when it requires every individual structure to be changed in exactly the same way, Bones, cartilage, muscles, veins, nerves, fingernails etc.
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Atom
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posted 28. January 2006 22:59
Yo KBC,
I'm glad I'm able to coopt with you and others on this board. I'm not a math whiz by any means; although I did well in all my crazy math classes (Differential Eqs, Multivar calculus, linear algebra, Stats, etc), I don't remember too much of my math. So any math I present here probably won't prgress much past algebra...
I think I am going to give an example of I meant in my attempt at formalizing MSR. You came up with the idea, so if you can't follow my math, that means I am not presenting it clearly. I hate when people begin talking math and lose me, so I'm reluctant to do that to anyone else.
That being said, I think your idea of balance is built into our current definition of MSR. Your constraints (what I formalized as functions, f0...fm, but now see are not functions but equations...see discussion later) are what need to be maintained, or balanced.
For example, let us say we have a system of three parts, A,B and C. Let's say A is a battery and B is a variable resistor and C is a lightbulb (we can think of C as a fixed value resistor that also gives off light.) The three components form a closed circuit. (In other words, one wire from A goes directly to C, while the other first passes through B.)
Now for our internal constraints: the input power to C must not exceed 80W, C needs at least 0.5A of current to operate, and the power input to B must not exceed 30W. Assume that our variables are: A's voltage, B's resistance value, and C's resistance value.
We also have an external constraint (Total System Function), which in our example may be giving exactly enough light to read by, without waking up a sleeping child. Assume a power of 75W into C will provide this perfect amount of light, with a error range of 1W on either side. So we suppose that we have initial values: A's voltage at 100V, B's initial resistance at 75 ohms, C's resistance at 75 ohms. As can be calculated using Ohm's law, our current values should meet all constraints, and give us the optimum amount of light. If you're a circuit geek, you can draw out the diagram like I did, and solve the voltage and current equations. (Ohm's law: V = IR, voltage = Current * Resistance.)
Now a point should be made here: the constraints in this example are a series of equations and inequalities, not functions. The only function is Ohm's law which describes the behavior of the system. I made a mistake in my formalization, I now see. I assumed the constraints equaled functions (f0...fm), when in fact they are separate. Take note. I think all else still holds.
Now, assume we want to evolve the system to one that also satisfies the external constraint, but which uses a 150V battery. If we simply change the battery without changing anything else in the system, we can see that at least one of our internal constraints will not be satisfied (power into C will equal 112.5W), and our external constraint will also no longer be satisfied. Thus, total system function will degrade. Yet if we simultaneously increase the resistance of B, we can maintain balance, and still satisfy all constraints. I think this is what you're looking for KBC.
To finish the example, let us once again take the 100V battery and now assume we want to vary B's resistance. We can do so in steps, first lowering the resistance, and then raising it. When we increase the resistance of B, we as a result reduce the current through the system, and when the resistance exceeds 26.35 ohms our external constraint will cease to be satisfied. When we reduce the resistance of B to 23.679 ohms, our external constraint will also fail. So we can calculate e for B (the pertubration space for component B's value):
Range: (25 - 23.68) + (26.35 - 25) = 2.67 ohms
e: range / current value = 2.67 / 25 = 0.1068 = 0.11 percent
That is for component B. I leave it as an excercise to calculate e_a and e_c.
Taking all ei, we get the MSR measure for the system:
1 /(e_a + e_b + e_c)
The larger this number, the smaller the range of acceptable values for our variables, which means the tighter the system integration. The larger this number also means the smaller the freedom a system has in altering it's internal component values without making up for the change in other components (balancing, in KBC's terms).
I could go on, but I'll let you guys digest this, and I'll think about this more. I really think we may be on to something. Hopefully you guys can come up with other examples from other fields, and we can develop this further.
Atom
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KBC1963
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posted 28. January 2006 23:48
I think this is what you're looking for KBC,
You are correct sir, but please don't look to make it understandable by me I know I have limited math skills but if you are able to take it to a higher level then you run with it and we can see if it could be approved or improved by someone higher up the chain from us. My forte is more in the concept stage so if you can quantify the concept and reduce it at all to numbers then someone else can shape it further, however it is possible that you may make an irreducibly complex formula that others can just run with and test.
Maybe David can better communicate with you at the equation level you are at and who knows maybe between us we can put a paper together to rum by prof. Dembski as he is definitely at the top of the math chain, who knows we may not get it quite right but maybe he has the knowhow to make it work from his level and then none of us will understand hehehe my greatest hope is that the concept gets fleshed out and becomes a scientific tool allowing everyone a better understanding of complexity and Bill would definitely be the math wiz to run this thing up the flag pole.
[ 30. January 2006, 10:26: Message edited by: KBC1963 ]
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Irving
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posted 29. January 2006 22:28
quote:
my greatest hope is that the concept gets fleshed out and becomes a tool to back our movements main concept of an intelligent designer
I would caution that the goal is the advancement of knowledge, and not specifically an attempt to find something, or anything that proves an intelligent designer. At it's heart, ID is an Information Theory regarding the inferrence of design. It's application to biology a follow-on activity.
The design inferrence is made based upon the understanding that nature does not build-to external, or non-local environmental requirements. The inherent issue with "Scalability" as an adjunct to other ID formulations is working out specific analysis regarding why Scalability is NOT a local environmental requirement. Or in other words, why Scalability would not be a selection criteria (from a specific complexity standpoint), and/or that Scalability is inherently an Irreducibly Complex construct.
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KBC1963
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posted 30. January 2006 10:23
Irving,
You said:
"I would caution that the goal is the advancement of knowledge, and not specifically an attempt to find something, or anything that proves an intelligent designer."
You are absolutely correct. I associated myself with I.D. based soley on their promotion of truths that I understood before I knew the movement and my sole goal was to seek and identify truth first and this same goal is the basis of my presence here. I hope by interacting in this forum I can better sharpen my understanding of truth based on scientific evidence and not on preconcieved goals, otherwise I become just as I once was a follower of paradigm.
Might I apologize to all present for my human faults.
In reference to the Scalability issue, it seems I was attacking it from a different perception but in the end I was saying the same thing as has already been discussed.
[ 30. January 2006, 10:27: Message edited by: KBC1963 ]
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Irving
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posted 30. January 2006 18:54
KBC1963,
No real problem. It's just IMHO that a true Theory of ID would be applicable across the board, and not just tied to Biology. The attributes that provide a design inferrence must be applicable in any domain. What we're working out is a Theory of Intelligent Design. Once principles are solidified in the general domain, they can then be applied to the Biologic domain. Thus we illustrate Specified Complexity with Shakespeare, and Irreducible Complexity with mousetraps...and so thus IMO establishing design inferrence principles for Mechanically Specific Relativity or Scalability should be defined generally first, and then researched as to it's application to Biology.
Have you made a sufficient case that undirected processes cannot achieve Mechanically Specific Relativity?
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David L. Hagen
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posted 30. January 2006 20:21
Irving
I affirm your emphasis on the need to form a general ID principles applicable across the board.
I am interested in your intriguing statement:
quote:
". . .not the specific evidence regarding interface specified complexity I'm referring to. The control system is external. I'm referring to the integrated interface of modular component."
I can see that the standards for electronic interfaces would be examples. The electronics industry has established standards for pinouts to provide communication between chips, and onto within very large scale integration etc.
Growth and development of parallel processing computing or clusters has been critically dependent on communications methods and standardization. E.g., see the rapid and large scaling shown in supercomputers and cluster computing at: Top 500 Supercomputers Those are still a tiny fraction of the power of the human brain.
From the challenges of scaling computers, I propose the following general observation:
"Scaling modular information processing systems depends on the processing speed of information processing module, the number of information processing modules, intermodule communications, on transferring information to and from the processing system, on communication standards, and on the ability to provide power to and to cool the processing modules and communication systems."
From this I propose the following generic ID observations or principles:
1 Regulation:
1.1 Intelligent causes design regulation systems.
The correlary:
1.1.1 "Highly specified regulation is evidence for design by an intelligent cause.
2 Communication:
2.1 Intelligent Designers form communication systems.
2.1.1 A highly specified communication system is evidence for Intelligent Design.
2.2 Intelligent Designers form communication standards.
2.2.1 Highly Specified communication standards are evidence for Intelligent Design.
3 Information Processing:
3.1 Intelligent Designers form information processing systems.
3.1.1 Highly specified information processing is evidence for Intelligent Design.
4 Scaling Information Processing
4.1 Intelligent Designers utilize modular processors when scaling information processing.
4.1.1 Highly specified scaling using modular processors is evidence for Intelligent Design.
4.2 Intelligent Designers use communication standards to multiply processing modules when scaling information processing systems.
4.3 Intelligent Designers provide energy flows for information processing systems.
4.3.1 Intelligent Designers provide electrical power to modular processors.
4.3.2 Intelligent Designers form standard Electrical interfaces for modular processors to scale information processing systems.
4.3.3 Intelligent Designers provide cooling for information processing systems.
4.3.4 Intelligent Designers provide effective power and cooling when scaling information processing.
4.4 Intelligent Designers form standard physical interfaces for modular processors to scale information processing systems.
After compiling such generic statements, we could then begin prescribing scaling laws for computing systems. I see similar issues applying to biological systems. These are then relevant to origin theories as well as current design.
Do you (or others) have any recommendations on general language for these and other information processing requirements, particularly on the interface requirements that would summarize ID across multiple fields?
Any summary of standards and documents relevant to scaling that you would recommend?
E.g., Bejan shows how efficient scaling of power flows in abiotic and biotic systems uses tree structures.
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Irving
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posted 30. January 2006 21:09
quote:
Do you (or others) have any recommendations on general language for these and other information processing requirements, particularly on the interface requirements that would summarize ID across multiple fields?
Well, I wasn't trying to discuss computer circuitry per se...(though we'll get there ![[Cool]](cool.gif) ). I could have used the following graphic for my point as well:
I'm referring to the "edges" of the image, not the processor in the image. You see, the image can be replicated next to itself in two dimensions to create a "seamless" background image. That's because the image is "designed" for that to happen. The "edges" of the image are the "interface" for that image when it is abutted to an adjacent copy of the same image.
The key here, is that there is no reason why an undirected process through selection would create such "edges" for an image. As a single image "developing" by itself, it would develop in accordance with selection pressures on the image as a "single" image. The a priori conception that the image should allow "seamless replication" would be an "external" requirement...or in ID speak...something independently specified.
So my concept of "scaling" here is one of scaling through integrated replication of the exact same component.
Now this isn't to say that principles of ID cannot be drawn from signal processing designs. They could be. But my suggestion is to define such principles in terms why such principles are exclusive to directed action.
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David L. Hagen
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posted 30. January 2006 23:36
Thanks Irving, that is much clearer example.
If I understand you, the following would be some examples of designed systems:
1) Graphic art with repeating designs.
e.g., wall paper.
2) Mechanically interlinking parts.
e.g., lego blocks.
3) Electric connectors.
4) Locks and keys.
5) Information processors.
6) Books with chapters.
7) The internet.
To generalise, in patentese using Dembski's universal probability bound:
1) Designed Systems:
A prescribed designed system comprises:
a) a plurality of components;
b) each component comprising at least one interface;
c) wherein the interface of a first component is configured to correlate with
the interface of at least one second component;
d) the correlating interfaces being configured to provide a prescribed function;
e) wherein the prescribed function is not otherwise achievable by a closed system of natural laws, nor of stochastic processes, within a universal upper probability bound of all possible cominations of particles in the universe over all time at the fastest possible recombination rate.
2) Replicated Designed Systems
Replicated designed systems comprise a plurality of prescribed designed systems.
2.1) 1D Replicated Designed Systems comprise a plurality of designed systems replicated and interfaced in one dimension.
2.2) 2D Replicated Designed Systems comprise a plurality of designed systems replicated and interfaced in two dimensions.
2.3) 3D Replicated Designed Systems comprise a plurality of designed systems replicated and interfaced in three dimensions.
I first focused on the "edges" or "interfaces" 1). Then I went back and added 2) with the "identical replication" to match your emphasisized statement. Your graphic example would fit into the 2D system of 2.2. Is that anywhere close?
If so, I'll think about how to reword it in English.
(Do we need to think beyond 3 dimensions? e.g., do "string theories" constitute designed systems or are they "complex" mathematical constructs designed to provide employment for physics graduates?)
[ 30. January 2006, 23:52: Message edited by: David L. Hagen ]
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Irving
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posted 31. January 2006 06:47
Not quite "designed systems," but specified complexity. Then to look for a probabilistic demarcation point for the design inferrence.
Consider tearing a piece of paper in two. The "edge" of the tear would be quite complex and an exact "fit" into the other half...but that would not necessarily be remarkable...from a directed and non-directed sense. Nature "cleaves" or breaks apart many objects without intelligent direction.
However, consider tearing a paper in thirds. How likely would the first tear be a perfect fit with the second tear? Also, how likely would it be that any image on that paper be so configured as to seamlessly integrate across the tear?
So I'm not so sure about your examples 4) and 6). Has nature sub-divided what was once whole?
Now if they had developed independently...what's the probability that they would fit?
So for now...how about:
A design inferrence exists when the specified complexity of the interface between two independently developed components exceeds the universal probability bound.
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