Physical linguistics

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Physical linguistics, which was invented by the chief scientist of Yang's Scientific Research Institute, Tao Yang in 2002, consists of two indispensable components: computational verbs and computational nouns. The computational verb theory addresses issues of computational verbs while probability theory, Boolean logics, multi-valued logics and fuzzy logics address different issues of computational nouns. While any a logic system is truth-conserved, it doesn't manipulate truth directly. Instead, any logic system manipulates only information. The truth is manipulated by the computational verb theory. Therefore, in any logic system, the truth doesn't need a system of metrics to associate with. For example, in a logic system if we say: "a=true is as twice as larger as b=true", it sounds very funny and is unnecessary because all "true" is the same.

Therefore "true+true"(e.g., "a=true OR b=true") is not equal to "2true", but simply "true". However, in computational verb theory where the truth is directly manipulated and information is not directly manipulated, the "true" can have different sizes. In computational verb theory, we can have a "true1" of size 1.5UNITs and a "true2" of size 3.4UNITs, then when the statement "true1+true2" appears, we get a "true3" of size 4.9UNITs. After a Truth in a computational verb collapses into a piece of information in logics, we get a "truth value" of the information. However, at this point, the Truth itself already returned to the Cognition.

The main goal of physical linguistics is to translate all sentences in natural languages into mathematical formulas. For example, the following sentence

                                   The apple turns red from green.

can be expressed by a linguistic differential equation as

                                   d(color of apple)/dt = F (color of apple, t)

with the following boundary conditions

                        color of apple(beginning) = green, and color of apple(end) = red.

Contents

[edit] Applications

Physical linguistics was successfully applied to many image understanding tasks [citation needed] based on its powerful, reliable and robust representation to the visual signals samples from devices such as webcams. Although the design of image processing systems takes enormous amount of efforts, the mechanism of developing an image understanding application based on physical linguistics makes it pretty easy to accumulate dynamic and static experiences and make the learning curve of the design of image understanding systems fast. Yet, physical linguistics also make the threshold for becoming an expert in the design of image understanding systems much lower comparing with conventional methods. This is the reason that many commercial image understanding products are backed up by the Physical Linguistic Vision Technologies developed in YangSky.

The known applications of physical linguistics are:

  • Flame detection using a CCD camera or a CMOS camera. In this application the spectrum characteristics of flames are modelled by computational nouns and the dyanmical behaviors of flames are modelled by using computational verbs. By using reasoning engine built upon physical linguisitics, engineers made a much more robust visual flame detector than previous ones.
  • Traffic control. In this applications, the shapes and colors of different cars are modelled by using computational nouns while the moving patterns of cars are modelled by using computational verbs. Many high level cognitive image processing tasks are them performed within a physical linguistic reasoning software.

[edit] Computational verb

Computational verb was invented by Tao Yang in 1997 in the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley. The purpose of computational verb is to make all verbs in any natural language computable. Each computational verb consists of an inner system and an outer system. The inner system of a computational verb is invisible to the outer observers. For example, for the computational verb “feel”, the inner system is the statues of a brain that are invisible even to the brain itself. For a human being, the inner system is the body together with the brain. In a computer, the inner system is called machinself (from machine + itself). The outer system of a computational verb is the visible part of the computational verb. Therefore, the outer system can be measured and modeled by using mathematical functions that are called outer functions of computational verb.

The concept of computational verb is closely related to the concept of fuzzy set, which was invented by Lotfi Zadeh in 1965, also in the Department of Electrical Engineering and Computer Science at UC Berkeley. Fuzzy set is mainly to make adjectives computable while computational verb is to make verbs and adverbs computable. While a membership function is used to model an adjective like “red”, “tall” and “fast”, an evolving function is used to model a computational verb like “go”, “increase” and “feel”. Among the applications of computational verbs to engineering problems are: computational verb controller, computational verb image processing, computational verb prediction and computational verb modeling.

The theory of computational verbs is the computational verb theory.

[edit] Computational verb logic

Computational verb logic is an extension of Boolean logic and fuzzy logic dealing with the concept of truth of irrationals. Whereas classical logic and fuzzy logic hold that everything can be expressed in a truth value at any moment, computational logic replaces static truth values with dynamics of truth. In a word, classical logic and fuzzy logic deal with “BE true” while computational verb logic deals with “BECOME true”.

For example, the following statements can be reasoned in classical logic and/or fuzzy logic:

 IF the temperature IS high THEN the air flow IS fast. 
 IF the temperature IS 40 THEN the air flow IS 5m/s.

However, the following statements can’t be reasoned in neither classical logic nor fuzzy logic:

 IF I understand you THEN I become smart. 
 IF the temperature increases too high THEN the air flow will decrease too fast.

These statements can be easily modeled by using computational verb logic. Computational verb logic can be applied to design industrial controllers and develop advanced image processing platforms.

[edit] Bibliography

[edit] Computational verb theory

Computational verb theory, which was invented by then-University of California, Berkeley visiting scholar Tao Yang in 1997, is the theory of how to implement verbs and relative verbal phenomena in any natural languages into computers. The building block of the computational verb theory is computational verbs. The basic mathematical concept in the computational verb theory is the computational verb set(verb set, for short), which corresponds to set in classical mathematics and fuzzy set in fuzzy theory. The following statement constitutes a verb set: “All people will go to the States”. While a fuzzy set or a classical set is most likely to state as follows: “All people (BE) in the States”. A computational verb set is more “irrational” than its classical or fuzzy counterpart. The logic in computational verb theory is called computational verb logic.

Another important mathematical concept in computational verb theory is computational verb number(verb number, for short). While a real number, an interval number and a fuzzy number can respectively represented as “3”, “[2,4]”, and “close to 3”, a computational verb number has the form such as “increase to 3”, “become old” and “remain high”. Computational verb number give numbers dynamic lives. Many operations between dynamic processes associated with numbers can be computed by applying computational verb numbers.

In the computational verb theory, the relation between adverbs (adverbials) and verbs are mathematically modeled by using a mathematical concept called operators. In this theory, each computational verb is modeled by a dynamical process of which the dynamics can be modified by either adverbs or operating verb such as “must”, “will” and “be”.

[edit] Theory

The theory of computational verb consists of the following aspects.

[edit] Mathematic Theory of Computational Verbs

The researches in this aspect of computational verbs are addressing the following issues.

  • The mathematical operations between computational verbs and other kinds of words. For example, the relation between an adverb and a verb can be defined by mathematical operators.
  • The dynamical models of computational verbs and their relations.

[edit] Physical Theory of Computational Verbs

  • How to measure the outer systems and the inner systems of computational verbs.
  • How to construct experiments for observing complex computational verbs.

[edit] Biological Theory of Computational Verbs

  • The brain dynamics for computational verbs.
  • The neural basis for constructing computational verbs in brains.

[edit] Psychological Theory of Computational Verbs

  • The cognitive basis for computational verbs.
  • The cognitive models for computational verbs.

[edit] Applications

The applications of computational verbs are:

[edit] Image Processing

Computational verb theory has been successfully applied to many dynamics-related image processing applications such as: intelligent traffic control systems (ITCS), visual flame detection, card counting and homeland security. The advantages of applying computational verbs to image processing are

  • Reduce the demand of computational resources.
  • Robust to spatio-temporal fluctuation and noise.
  • Reduce the cost of image processing platform by using low-end DSP chips and video camera.
  • Fast and reliable development of new vision products.

Some representative products based on computational verb image processing technolofies are: CardSeer card and paper sheet counting system, FaceID Webcam Face Login System for biometrics password, and FlameSky flame detecting systems.

[edit] Industrial Controllers

The control rules and experiences of human experts can be used to design different intelligent controllers, among them are fuzzy controllers. The fuzzy controllers can be further expanded into computational verb controllers. A typical fuzzy control rule is given by

  • IF the temperature HIGHT, THEN the control FAST.

This rule is in face a concise form of the following rule:

  • IF the temperature “is” HIGHT, THEN the control “is” FAST.

One should note that the only verb used in fuzzy control rule is BE. If we expand BE into any kinds of verbs such as BECOME, GO, INCREASE, FEEL, we have computational verb rules such as

  • IF the temperature “increases to” HIGHT, THEN the control “becomes” FAST.
  • IF the temperature “stays” HIGHT, THEN the control “decreases to” FAST.

Observe that the space of computational verb rules is much bigger than that of fuzzy rules.

Computational verb fuzzy controllers becomes a part of the standard course(EE6452 Introduction to Fuzzy Informatics and Intelligent Systems) for undergraduates at City University of Hong Kong. Please refer to G. Chen's homepage for the information of the instructor.

[edit] Paths

When Tao Yang invented computational verbs in 1997, he might not realize that this is the second step in science to implement a measurable linguistics, or to make linguistics as a natural sciences with a system of metrics just like that used in physics. The first step was fuzzy theory invented by L.A. Zadeh in 1965. The physical linguistics is such a theory for building the measurable linguistics. Physical linguistics leads a path to a universal theory of mind and physical world called the Theory of the Unicogse.

[edit] External links

  • Advances in Computational Verb Systems (ISBN 1-56072-971-6)
  • Computational Verb Theory: From Engineering, Dynamic Systems to Physical Linguistics (ISBN 0-9721212-1-8)
  • Physical Linguistics: Measurable Linguistics and Duality Between Universe and Cognition (ISBN 0-9721212-3-4)
  • Fuzzy Dynamic Systems and Computational Verbs Represented by Fuzzy Mathematics (ISBN 0-9721212-2-6)

[edit] External links

  • Advances in Computational Verb Systems (ISBN 1-56072-971-6)
  • Computational Verb Theory: From Engineering, Dynamic Systems to Physical Linguistics (ISBN 0-9721212-1-8)
  • Physical Linguistics: Measurable Linguistics and Duality Between Universe and Cognition (ISBN 0-9721212-3-4)
  • Fuzzy Dynamic Systems and Computational Verbs Represented by Fuzzy Mathematics (ISBN 0-9721212-2-6)
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