• Journal for History of Mathematics
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• v.25 no.3
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• pp.29-39
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• 2012

As a product of modern proof theory, linear logic is a new form of logic developed for the purpose of enhancing programming language by Professor Jean-Yves Girard of Marseille University (France) in 1987 by supplementing intuitionist logic in a sophisticated manner. Thus, linear logic' s connectives can be explained using information processing terms such as sequentiality and parallel computation. For instance, A${\otimes}$B shows two processes, A and B, carried out one after another. A&B is linked to an internal indeterminate, allowing an observer to select either A or B. A${\oplus}$B is an external indeterminate, and as such, an observer knows that either A or B holds true, but does not know which process will be true. A ${\wp}$ B signifies parallel computation of process A and process B; linear negative exhibits synchronization, that is, in order for the process A to be carried out, both A and $A^{\bot}$ have to be accomplished simultaneously. Since the field of linear logic is not very active in Korea at present, this paper deals only with syntax aspect of linear logic in order to arouse interest in the subject, leaving semantics and proof nets for future studies.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.69-80
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• 2004

We present a construction of the linear reduction of Hilbert type proof systems for propositional logic to if-then-else equational logic. This construction is an improvement over the same result found in [4] in the sense that the technique used in the construction can be extended to the linear reduction of first-order logic to if-then-else equational logic.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.148-154
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• 2010

In the study of the formal semantics of uncertain databases, we typically take an algebraic approach by mapping an uncertain database to possible worlds which are a set of relational databases. In this paper, we present a new semantics for uncertain databases which takes a logical approach by translating uncertain databases into logical theories. A characteristic feature of our semantics is that it uses linear logic, instead of propositional logic, as its logical foundation. Linear logic is suitable for a logical interpretation of uncertain information because unlike propositional logic, it treats logical formulae not as persistent facts but as consumable resources. As the main result, we show that our semantics is faithful to the operational account of uncertain databases in the algebraic approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1751-1758
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• 2017

This paper presents a fuzzy logic system with data preprocessing to make the accurate electric power load prediction system. The fuzzy logic system acceptably treats the hidden characteristic of the nonlinear data. The data preprocessing processes the original data to provide more information of its characteristics. Thus the combination of two methods can predict the given data more accurately. The former uses TSK fuzzy logic system to apply the linguistic rule base and the linear regression model while the latter uses the linear interpolation method. Finally, four regional electric power load data in taiwan are used to evaluate the performance of the proposed prediction system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1441-1446
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• 2010

This paper presents a method of constructing the divider using sequential logic systems over finite fields(or galois fields). The proposed the sequential logic systems is constructed by as following. First of all, we obtain the linear characteristics between present state and next state based on mathematical properties of finite fields and sequential logic systems. Next, we realize the sequential logic systems over finite fields using above linear characteristics and characteristic polynomial which is expressed using by matrix. Also, we apply to implement divider using the proposed sequential logic systems over finite fields.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.595-600
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• 2004

In this paper, we propose a new simple scheme of layered nonlinear feedforward logic (NLFFL) overlaid on a linear feedback shift resistor (LFSR) to generate pseudonoise sequences, which have good balance property and large linear complexity. This method guarantee noiselike statistics without any designed connection scheme e.g. Langford arrangement.

• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.2
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• pp.35-40
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• 1994

Fuzzy logic controllers are often found to behave better than PI controllers. One of the major reasons for this is that the fuzzy logic inferences used can produce nonlinear type controllers. For some applicatioins, howeveer, linear fuzzy logic controllers also perofrm better than PI controllers. In this paper, we examine linear fuzzy logic controllers to show that the truncation effects of the fuzzy logic controllers make them perform much better than the PI controllers. In terms of a performance index we used, the truncation effects reduced the index value by up to 80% for examples we studied.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.880-883
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• 2005

This paper presents a method of constructing the sequential logic machines over finite fields(or galois fields). The proposed the sequential logic machines is constructed by as following. First of all, we obtain the linear characteristics between present state and next state based on mathematical properties of finite fields and sequential logic machines. Next, we realize the sequential logic machines over finite field GF(P) using above linear characteristics and characteristic polynomial that expressed using by matrix.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2589-2596
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• 2000

As current manufacturing processes require high spindle speed and precise machining, increasing accuracy by reducing volumetric errors of the machine itself, particularly thermal errors, is very important. Thermal errors can be estimated by many empirical models, for example, an FEM model, a neural network model, a linear regression model, an engineering judgment model, etc. This paper discusses to make a modeling of thermal errors efficiently through backward elimination and fuzzy logic strategy. The model of a thermal error using fuzzy logic strategy overcomes limitation of accuracy in the linear regression model or the engineering judgment model. It shows that the fuzzy model has more better performance than linear regression model, though it has less number of thermal variables than the other. The fuzzy model does not need to have complex procedure such like multi-regression and to know the characteristics of the plant, and the parameters of the model can be mathematically calculated. Also, the fuzzy model can be applied to any machine, but it delivers greater accuracy and robustness.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.6
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• pp.206-219
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• 1996

This paper describes a data structure and evaluation algorithm to improve the perofmrances MOS logic-with-timing simulation in computation and accuracy. In order to efficiently simulate the logic and timing of driver-load networks, (1) a tree data structure to represent the mutual interconnection topology of switches and nodes in the driver-lod network, and (2) an algebraic modeling to efficiently deal with the new represetnation, (3) an evaluation algorithm to compute the linear resistive and capacitive behavior with the new modeling of driver-load networks are developed. The higher modeling presented here supports the structural and functional compatibility with the linear switch-level to simulate the logic-with-timing of digital MOS circuits at a mixed-level. This research attempts to integrate the new approach into the existing simulator RSIM, which yield a mixed-klevel logic-with-timing simulator MIXIM. The experimental results show that (1) MIXIM is a far superior to RSIM in computation speed and timing accuracy; and notably (2) th etiming simulation for driver-load netowrks produces the accuracy ranged within 17% with respect ot the analog simulator SPICE.