• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.125-135
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• 2007

An automated guided vehicle (AGV) system is a group of collaborating unmanned vehicles which is commonly used for transporting materials within manufacturing, warehousing, or distribution systems. The performance of an AGV system depends on the dispatching rules used to assign vehicles to pickup requests, the vehicle routing protocols, and the home location of idle vehicles, which are called dwell points. In manufacturing and distribution environments which emphasize just-in-time principles, performance measures for material handling are based on response times for pickup requests and equipment utilization. In an AGV system, the response time for a pickup request is the time that it takes for the vehicle to travel from its dwell point to the pickup station. In this article, an exact dynamic programming algorithm for selecting dwell points in a tandem-loop multiple-vehicle AGV system is presented. The objective of the model is to minimize the maximum response time for all pickup requests in a given shift. The recursive algorithm considers time restrictions on the availability of vehicles during the shift.

• Journal of Astronomy and Space Sciences
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• v.12 no.1
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• pp.143-156
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• 1995

Using a directional antenna, the Doppler effect of satellites can be detected and the orbital elements can be obtained by the Extended Kalman Filter with the observed frequency shift data. We obtained the orbital elements of NOAA-11 by the application of the Extended Kalman Filter type algorithm to the Doppler shift data of NOAA-11d and discussed the accuracy and the credibility of this algorithm.

• Journal of the Korean Magnetic Resonance Society
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• v.6 no.1
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• pp.12-19
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• 2002

A shift-averaged Haar wavelet transform was introduced as a new and excellent tool to distinguish real peaks from the noise contaminated NMR signals. It is based on Haar wavelet transform and translation-invariant denoising process. Donoho＇s universal threshold was newly introduced to the shift-averaged Haar wavelet transform for the purpose of automated noise suppression, and was quantitatively compared with the conventional uniform threshold method in terms or threshold and signal to noise ratio (SNR). New algorithm was combined with a routine to suppress a large solvent peak by singular value decomposition (SVD). Combined algorithm was applied to the real spectrum that containing large solvent peak.

• ETRI Journal
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• v.28 no.6
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• pp.745-760
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• 2006

In this paper, we particularly deal with no $F_p$-rational two-torsion elliptic curves, where $F_p$ is the prime field of the characteristic p. First we introduce a shift product-based polynomial transform. Then, we show that the parities of (#E - 1)/2 and (#E' - 1)/2 are reciprocal to each other, where #E and #E' are the orders of the two candidate curves obtained at the last step of complex multiplication (CM)-based algorithm. Based on this property, we propose a method to check the parity by using the shift product-based polynomial transform. For a 160 bits prime number as the characteristic, the proposed method carries out the parity check 25 or more times faster than the conventional checking method when 4 divides the characteristic minus 1. Finally, this paper shows that the proposed method can make CM-based algorithm that looks up a table of precomputed class polynomials more than 10 percent faster.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.262-266
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• 2010

Recognizing a license plate of a vehicle has widely been issued. In this thesis, firstly, mean shift algorithm is used to filter and segment a color vehicle image in order to get candidate regions. These candidate regions are then analyzed and classified in order to decide whether a candidate region contains a license plate. We then present an approach to recognize a vehicle's license plate using the Fuzzy ARTMAP neural network, a relatively new architecture of the neural network family. We show that the proposed system is well to recognize the license plate and shows some compute simulations.

• Korean Journal of Remote Sensing
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• v.24 no.5
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• pp.473-481
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• 2008

This paper presents an approach to Back-propagation and Radial Basis Function neural network method with various training set for automatic vehicle detection from aerial images. The initial extraction of candidate object is based on Mean-shift algorithm with symmetric property of a vehicle structure. By fusing the density and the symmetry, the method can remove the ambiguous objects and reduce the cost of processing in the next stage. To extract features from the detected object, we describe the object as a log-polar shape histogram using edge strengths of object and represent the orientation and distance from its center. The spatial histogram is used for calculating the momentum of object and compensating the direction of object. BPNN and RBFNN are applied to verify the object as a vehicle using a variety of non-car training sets. The proposed algorithm shows the results which are according to the training data. By comparing the training sets, advantages and disadvantages of them have been discussed.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.199-204
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• 1994

In this paper, we researched abut CELP speech coding algorithm using efficlent pseudo-stochastic block codes, adaptive-codebook and improved fixed-gain codebook. The pseudo-stochastic block codes refer to stochastically populated block codes in which the adjacent codewords in an innovation codebook are non-independent. The adaptive-codebook was made with previous prediction speech data by storage-shift register. This CELP coding algorithm enables the coding of toll quality speech at bit rates from 4.8kbits/s to 9.6 kbits/s. This algorithm was realized TMS320C30 microprocessor in realtime.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.103-114
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• 1994

This paper proposes an implementation of DCT (Discrete Cosine Transform) and IDCT (Inverse DCT) using a fast DCT algorithm with shift and addition operations instead of multiplications Based on the proposed algorithm, a new VLSI architecture for the DCT and the IDCT is proposed. It shows modularity , regularity and capability for multiprocessing. Its performance is also simulated by a simulation software, "Compass". The results of the simulation provide the quality of decompression images, the increase in processing speed, representing the superiority of the proposed architecture.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.236-238
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• 1992

This paper proposes a new algorithm to estimate time-varying parameters by combining KFSM(Kalman Filter with Shift Matrix) with neural network compansator. While the time varying parameters are estimated from KFSM, the error coverence of system, R(k) are compansated by neural network concurrently. The casestudy using computer simulation proves the usefullness and advantages of the proposed algorithm in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.427-430
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• 1989

For on-line ARMA spectral estimation, the fast transversal filter algorithm of extended least squares method(ETS FTF) is presented. The projection operator, a key tool for geometric approach, is used in the derivation of the algorithm. ELS FTF is a fast time update recursion which is based on the fact that the correlation matrix of ARMA model satisfies the shift invariance property in each block, and thus it takes 10N+31 MADPR.