• Journal of KIISE:Databases
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• v.32 no.1
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• pp.43-55
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• 2005

Spatiotemporal databases support methods of recording and querying for spatiotemporal data to user by offering both spatial management and historical information on various types of objects in the real world. We can answer to the following query in real world: 'What is the average of volume of pesticide sprayed for cach farm land from April to August on 2001, within some query window' Such aggregation queries have both temporal and spatial constraint. However, previous works for aggregation are attached only to temporal aggregation or spatial aggregation. So they have problems that are difficult to apply for spatiotemporal data directly which have both spatial and temporal constraint. Therefore, in this paper, we propose spatiotemporal aggregate functions for analysis of spatiotemporal data which have spatiotemporal characteristic, such as stCOUNT, stSUM, stAVG, stMAX, stMIN. We also show that our proposal resulted in the convenience and improvement of query in application systems, and facility of analysis on spatiotemporal data which the previous temporal or spatial aggregate functions are not able to analyze, by applying to the estate management system. Then, we show the validity of our algorithm performance through the evaluation of spatiotemporal aggregate functions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.243-250
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• 2014

In this paper, I devise a balance-swap optimization (BSO) algorithm to solve economic load dispatch with a quadratic fuel cost function. This algorithm firstly sets initial values to $P_i{\leftarrow}P_i^{max}$, (${\Sigma}P_i^{max}$ > $P_d$) and subsequently entails two major processes: a balance process whereby a generator's power i of $_{max}\{F(P_i)-F(P_i-{\alpha})\}$, ${\alpha}=_{min}(P_i-P_i^{min})$ is balanced by $P_i{\leftarrow}P_i-{\alpha}$ until ${\Sigma}P_i=P_d$; and a swap process whereby $_{max}\{F(P_i)-F(P_i-{\beta})\}$ > $_{min}\{F(P_i+{{\beta})-F(P_j)\}$, $i{\neq}j$, ${\beta}$ = 1.0, 0.1, 0.1, 0.01, 0.001 is set at $P_i{\leftarrow}P_i-{\beta}$, $P_j{\leftarrow}P_j+{\beta}$. When applied to 15, 20, and 38-generators benchmark data, this simple algorithm has proven to consistently yield the best possible results. Moreover, this algorithm has dramatically reduced the costs for a centralized operation of 73-generators - a sum of the three benchmark cases - which could otherwise have been impossible for independent operations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.3
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• pp.543-552
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• 1994

Dynamic Time Warp(DTW) needs for iterative calculations and the design of PE cell suitable for the operations is very important. Accordingly, this paper aims at real time recognition design enables large dictionary hardware realization using DTW algorithm. The DTW PE cell separated into three large blocks. "MIN" is the one block for counting accumulated minimum distance. "ADD" block calculates these minimum distances, and "ABS" seeks for the absolute values to the total sum of local distances. Circuit design and verification about the three block have been accomplished, and performed layout '||'&'||' DRC(design rule check) using 1.2 m CMOS N-Well rule base.CMOS N-Well rule base.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.95-102
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• 2022

This paper proposed a linear time algorithm for a three-partition problem(TPP) in which a polynomial time algorithm is not known as NP-complete. This paper proposes a backtracking method that improves the problems of not being able to obtain a solution of the MM method using the sum of max-min values and third numbers, which are known polynomial algorithms in the past. In addition, the problem of MM applying the backtracking method was improved. The proposed algorithm partition the descending ordered set S into three and assigned to the forward, backward, and best-fit allocation method with maximum margin, and found an optimal solution for 50.00%, which is 5 out of 10 data in initial allocation phase. The remaining five data also showed performance to find the optimal solution by exchanging numbers between surplus boxes and shortage boxes at least once and up to seven times. The proposed algorithm that performs simple allocation and exchange optimization with less O(k) linear time performance complexity than the three-partition m=n/3 data, and it was shown that there could be a polynomial time algorithm in which TPP is a P-problem, not NP-complete.

• Communications of the Korean Mathematical Society
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• v.26 no.4
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• pp.603-610
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• 2011

In this paper, we propose an algorithm for identifying ${\omega}_j{\in}(0,\;{\infty}),\;a_j,b_j{\in}\mathbb{C}$ and N of the following trigonometric series $f(t)=a_0+ \sum\limits_{j=1}^N[a_jcos{\omega}_jt+b_j\;sin{\omega}_jt]$ by means of the finite number of sample values. We prove that the frequency components are shown to be the solutions of some characteristic equation related to the inverse of a Hankel matrix derived from the sample values.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.302-304
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• 1992

This paper presents the method to reduce the order of high-order linear time invarient system via Walsh function. It is based on the matrix pseudoinverse algorithm to determine the parameters of the reduced model which minimize the sum of the squares of the errors between the reponses of the high-order system and a reduced model to a given input. This proposed method can be conveniently implemented with a computer. They will be very useful in the study of control system via Walsh function.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.133-142
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• 2018

Subway metro scheduling is one of the most important problems impacting passenger convenience today. To operate efficiently, the Seoul metro uses regular, periodic schedules for all lanes, both north and southbound. However, many past studies suggest that non-periodic scheduling would better optimize costs. Since the Seoul metro is continuously facing a deficit, adopting a non-periodic schedule may be necessary. Two objectives are presented; the first, to minimize the average passengers' waiting time, and the second, to minimize total costs, the sum of the passenger waiting time, and the operational costs. In this paper, we use passenger smart card data and a precise estimation of transfer times. To find the optimal time-table, a genetic algorithm is used to find the best solution for both objectives. Using Python 3.5 for the analysis, for the first objective, we are able to reduce the average waiting time, even when there are fewer trains. For the second objective, we are able to save about 4.5 thousand USD with six fewer trains.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.345-355
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• 1998

The back propagation(BP) algorithm allows multilayer feedforward neural networks to learn input-output mappings from training samples. It iteratively adjusts the network parameters(weights) to minimize the sum of squared approximation errors using a gradient descent technique. However, the mapping acquired through the BP algorithm may be corrupt when errorneous training data are employed. In this paper two types of robust backpropagation algorithms are discussed both from a theoretical point of view and in the case studies of nonlinear regression function estimation and handwritten Korean character recognition. For future research we suggest Bayesian learning approach to neural networks and compare it with two robust backpropagation algorithms.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.391-393
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• 2000

This paper presents an new algorithm for the economic load dispatch considering the reliability level constraints of composite power system under deregulated electricity market. It is the traditional ELD problem that generation powers have been dispatched In order to minimize total fuel cost subjected to constraints which sum of powers generated must equal the received load and no violating lower and upper limit constraints on generation. Under deregulated electricity market, however, generation powers of a pool have to be reallocated newly in order to satisfy the reliability differentiated level required at a load point because of a reliability differentiated electricity service which is a part of the priority service. In this study, new economic load dispatch algorithm for reallocating the generation powers of a pool in order to satisfy the reliability differentiated level under deregulated competitive electricity market is proposed. The uncertainties of not only generators but also transmission lines are considered fer the reliability evaluation. The characteristics and effectiveness of this methodology are illustrated by the case studies on MRBTS and IEEE-RTS.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.195-200
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• 2009

As 4G mobile communication systems require high transmission rates with reliability, the need for efficient error correcting code is increasing. In this paper, a novel LDPC (Low Density Parity Check) decoder is introduced. The LDPC code is one of the most popular error correcting codes. In order to improve performance of the LDPC decoder, we use SNR (Signal-to-Noise Ratio) estimation results to adjust coefficients of modified UMP-BP (Uniformly Most Probable Belief Propagation) algorithm which is one of widely-used LDPC decoding algorithms. An advantage of Modified UMP-BP is that it is amenable to implement in hardware. We generate the optimal values by simulation for various SNRs and coefficients, and the values are stored in a look-up table. The proposed decoder decides coefficients of the modified UMP-BP based on SNR information. The simulation results show that the BER (Bit Error Rate) performance of the proposed LDPC decoder is better than an LDPC decoder using a conventional modified UMP-BP.