• ETRI Journal
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• v.30 no.6
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• pp.818-825
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• 2008

This paper proposes an exponentiation method with Frobenius mappings. The main target is an exponentiation in an extension field. This idea can be applied for scalar multiplication of a rational point of an elliptic curve defined over an extension field. The proposed method is closely related to so-called interleaving exponentiation. Unlike interleaving exponentiation methods, it can carry out several exponentiations of the same base at once. This happens in some pairing-based applications. The efficiency of using Frobenius mappings for exponentiation in an extension field was well demonstrated by Avanzi and Mihailescu. Their exponentiation method efficiently decreases the number of multiplications by inversely using many Frobenius mappings. Compared to their method, although the number of multiplications needed for the proposed method increases about 20%, the number of Frobenius mappings becomes small. The proposed method is efficient for cases in which Frobenius mapping cannot be carried out quickly.

• Journal of Mechanical Science and Technology
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• v.14 no.11
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• pp.1206-1215
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• 2000

This paper introduces the application of evolutionary fuzzy modeling (EFM) in constructing global function approximations to subsequent use in non-gradient based optimizations strategies. The fuzzy logic is employed for express the relationship between input training pattern in form of linguistic fuzzy rules. EFM is used to determine the optimal values of membership function parameters by adapting fuzzy rules available. In the study, genetic algorithms (GA's) treat a set of membership function parameters as design variables and evolve them until the mean square error between defuzzified outputs and actual target values are minimized. We also discuss the enhanced accuracy of function approximations, comparing with traditional response surface methods by using polynomial interpolation and back propagation neural networks in its ability to handle the typical benchmark problems.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.682-685
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• 2000

In this paper, Using CDM(Coefficient Diagram Method), we set target polynomial constraints and design 4-PID controller which have different structures such as Textbook PID-controller, Derivative of output PID-controller, set point of I only controller(I-PD controller) and PI controller followed by lag network(PI lag network controller) were tested by simulations. The plant we used are that used in IFAC 93 benchmark test. A controller designer, using CDM could use these results to select the controller's structure which is the best one fer him.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.190-193
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• 2003

The DOA(Direction Of Arrival) estimation to select a best beam for receiving a particular signal in switched beam antenna systems, and to shape the optimal beam in adaptive array antenna systems, is typically performed under the assumption that the target user motion is almost negligible. In this paper, we model the user as the time-varying source and adopt the LPA(Local Polynomial Approximation) tracking algorithm, proposed by Katkovnik, to solve the time-varying DOA estimation problem. Then, we compare the power spectrum functions between the LPA beamformer and the conventional beamformer, also, the normalized SNRs of each beamformer. The results show that the LPA beamformer is robuster than the conventional beamformer in tine-varying environments. In addition, in case of the conventional beamformer, more array elements give rise to more degradation in the aspect of SNR.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.273-275
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• 2006

In this paper, we introduce a new design of fuzzy neural networks using input-output data information of target system. The proposed fuzzy neural networks is constructed by input-output data information and used the center of data distance by HCM clustering to obtain the characteristics of data. A membership function is defined by HCM clustering and is applied input-output dat included each rule to conclusion polynomial functions. We use triangular membership functions and simplified fuzzy inference, linear fuzzy inference, and modified quadratic fuzzy inference in conclusion. In the networks learning, back propagation algorithm of network is used to update the parameters of the network. The proposed model is evaluated with benchmark data.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.137-158
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• 1992

We study the Multiple Product Single Facility Stockout Avoidance Problem (SAP). That is the problem of determining, given initial inventories, whether there is a multiple product single facility production schedule that avoids stockouts over a given time horizon. The optimization version of the SAP where stockouts are pnelized linearly is also studied. We call this problem the Weighted Stockout Problem (WSP). Both problems are NP-hard in the strong sense. We develop Mixed Integer Linear Programming (MIP) formulations for both the SAP and the WSP. In addition, several heuristic algorithms are presented and performances are tested using computational experiments. We show that there exist polynomial algorithms for some special cases of the SAP and the WSP. We also present a method to phase into a target cyclic schedule for infinite horizon problems. These can be used as a practical scheduling tool for temporarily overloaded facilities or to reschedule production after a disruption.

• Journal of Magnetics
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• v.18 no.2
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• pp.90-94
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• 2013

We designed a model composed of a ring type magnet, a yoke, and a sensing coil embedded in a projectile for simulating the muzzle velocity. The muzzle velocity was obtained from the master curve for the induced voltage at sensing coil and the velocity as the projectile pass through the magnetic field. The induced voltage and the projectile's velocity are fitted by the $2^{nd}$ order polynomial. The skin effect difference between projectiles which consist of aluminum-aluminum and aluminum-steel was small. The projectile will surely be burst at the pre-determined target area using the flight time and the projectile muzzle velocity calculated from the voltage induced at the sensing coil on the projectile.

• Kyungpook Mathematical Journal
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• v.57 no.3
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• pp.493-502
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• 2017

We propose an accurate approximation method via discrete Krawtchouk orthogonal polynomials to the distribution of a sum of independent but non-identically distributed binomial random variables. This approximation is a weighted binomial distribution with no need for continuity correction unlike commonly used density approximation methods such as saddlepoint, Gram-Charlier A type(GC), and Gaussian approximation methods. The accuracy obtained from the proposed approximation is compared with saddlepoint approximations applied by Eisinga et al. [4], which are the most accurate method among higher order asymptotic approximation methods. The numerical results show that the proposed approximation in general provide more accurate estimates over the entire range for the target probability mass function including the right-tail probabilities. In addition, the method is mathematically tractable and computationally easy to program.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.3
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• pp.207-211
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• 2010

In this paper, the fluid AID(acoustic inspection device) was developed to measure SOS(speed of sound) since fluids used in most of industrial fields have different properties and its equipment is highly expensive. From AID developed, it is intended to get potentially the capability to distinguish the kind of fluid using the measurement by the SOS at various fields. In order to measure the sound speed of specific fluids, the measurement system and ultrasonic sensors are composed. The fluid used in the experimental work are soybean oil, glycerin, diesel oil and the error of time difference due to the container wall is extracted for preliminary experiment. As results, the variations of sound speed according to the temperature change of target fluid were analyzed and the polynomial equations were proposed.

• Korean Journal of Remote Sensing
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• v.10 no.2
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• pp.63-82
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• 1994

Multitemporal analysis with remotely sensed data is complicated by numerous intervening factors, including atmospheric attenuation and occurrence of clouds that obscure the relationship between ground and satellite observed spectral measurements. A reconstruction system was developed to increase the discrimination capability for imagery that has been modified by residual dffects resulting from imperfect sensing of the target and by atmospheric attenuation of the signal. Utilizing temporal information based on an adaptive timporal filter, it recovers missing measurements resulting from cloud cover and sensor noise and enhances the imagery. The temporal filter effectively tracks a systematic trend in remote sensing data by using a polynomial model. The reconstruction system were applied to the AVHRR data collected over Korean Peninsula. The results show that missing measurements are typically recovered successfully and the temporal trend in vegetation change is exposed clearly in the reconstructed series.