• 한국정보처리학회논문지
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• 제7권5호
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• pp.1491-1499
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• 2000

This paper is designed and implemented the data recovery mechanism for 2-D (2-dimensional) bar code system. The data recovery algorithm used the modified Reed-Solomon algorithm and it is implemented into 2-D bar code system. There are 7 types of 2-D bar code system, which are 21x21, 25x25, 41x41, 73x73, 101x101, 177x177. This paper has been experimented that how many data is saved among several 2-D bar code types and how many data re recovered. In the first experiment, the big size 2-D bar code system has many ECC codeword. Therefore, original data cannot be assigned to 2-D bar code system. In the second experiment, even if 35∼40% loss dta for the 2-D bar code system, the 2-D bar code system could have been recovered to original data.

• Journal of Electrical Engineering and Technology
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• 제5권3호
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• pp.353-362
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• 2010

This paper presents a centralized control algorithm for power system performance in the Korean power system using Flexible AC Transmission Systems (FACTS) devices. The algorithm is applied to the Korean power system throughout the metropolitan area in order to alleviate inherent stability problems, especially concerns with voltage stability. Generally, control strategies are divided into local and centralized control. This paper is concerned with a centralized control strategy in terms of the global system. In this research, input data of the proposed algorithm and network data are obtained from the SCADA/EMS system. Using the full system model, the centralized controller monitors the system condition and decides the operating point according to the control objectives that are, in turn, dependent on system conditions. To overcome voltage collapse problems, load-shedding is currently applied in the Korean power system. In this study, the application of the coordination between FACTS and switch capacitor (SC) can restore the solvability without load shedding or guarantee the FV margin when the margin is insufficient. Optimal Power Flow (OPF) algorithm, for which the objective function is loss minimization, is used in a stable case. The results illustrate examples of the proposed algorithm using SCADA/EMS data of the Korean power system in 2007.

• 산업경영시스템학회지
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• 제28권4호
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• pp.94-101
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• 2005

This paper presents a data-mining aided heuristic algorithm development. The developed algorithm includes three steps. The steps are a uniform selection, development of feature functions and clustering, and a decision tree making. The developed algorithm is employed in designing an optimal multi-station fixture layout. The objective is to minimize the sensitivity function subject to geometric constraints. Its benefit is presented by a comparison with currently available optimization methods.

• 한국정보통신학회논문지
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• 제5권7호
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• pp.1263-1271
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• 2001

There are two methods in blood pressure measurement ; Invasive methode and Non-invasive method. The Invasive methode can get the 띠cod pressure measurement but, patient feel uncomfortable. So Non-invasive methode used generally. The Oscillometric method is typical Non-Invasive method. This method is commonly used to measure BP in electric sphygmomanometer and has various algorithm. In this paper it is described about a algorithm, it controls, determinates the cuff pressure, and fillers the measured BP data. This system can interface with PC(personal computer) by RS-232 and save the measured data in PC. This system deflates the cuff pressure by Solenoid valve. The main algorithm are oscillometric and maximum amplitude algorithm(MAA). MAA has various measured oscillation, it depends on patient's age, height, weight and arm circumference size. In this paper proposed system can measure Systolic BP, Diastolic BP, and Mean BP using Interpolation, Auto Reinflation algorithm.

• 자동차안전학회지
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• 제3권2호
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• pp.28-33
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• 2011

This paper presents driving path estimation algorithm for adaptive cruise control system and advanced emergency braking system using multi-sensor fusion. Through data collection, yaw rate filtering based road curvature and vision sensor road curvature characteristics are analyzed. Yaw rate filtering based road curvature and vision sensor road curvature are fused into the one curvature by weighting factor which are considering characteristics of each curvature data. The proposed driving path estimation algorithm has been investigated via simulation performed on a vehicle package Carsim and Matlab/Simulink. It has been shown via simulation that the proposed driving path estimation algorithm improves primary target detection rate.

• 한국컴퓨터정보학회논문지
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• 제12권3호
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• pp.51-58
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• 2007

확장성에서 장점을 가지고 있는 비공유 병렬 프로세서 구조는 병렬 데이터베이스 시스템에서 많이 적용되고 있는 구조이다. 그러나 비공유 병렬 프로세서 구조는 데이터의 분포가 전체 프로세서에게 균일하게 분포되어 있지 않을 경우에는 일부 프로세서에게 부하가 집중되고 이로 인한 성능의 감소가 불가피하게 되는 단점이 있다. 특히 부하의 불균형 정도가 심한 경우에 조인 연산을 수행할 때 이런 성능 감소의 단점은 두드러진다. 본 논문은 비공유 병렬 프로세서 구조에서 부하의 불균형 정도가 심한 경우에도, 조인 연산을 실시하기 전에 부하 불균형을 고려함으로써 성능 감소를 최소화하고, 메모리의 대용량화를 이용하여 성능을 높인 조인 알고리즘을 제시한다. 또한 알고리즘의 성능 분석을 위한 분석 모델을 제시하며, 분석 모델을 통하여 데이터 불균형 문제를 해결하기 위한 다른 알고리즘과의 성능을 비교한다.

• 한국항공우주학회지
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• 제50권4호
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• pp.233-240
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• 2022

스마트무장은 종말 유도조종을 통해 정밀타격 임무를 수행하는 초소형 유도무기로 미래 전장환경의 신무기체계이다. 하지만 크기로 인한 구조적 제한으로 인해 압전구동 방식의 조종날개를 이용해 제어를 수행하기 때문에 기동력이 작아 유도범위가 제한적이다. 본 논문에서는 스마트무장의 효과도를 높이기 위한 비 표준조건 사격제원 산출 알고리즘을 제안한다. 제안된 알고리즘은 획득한 전장환경 정보를 이용해 표준조건에서의 사격제원을 보정해 비 표준조건의 사격제원을 산출한다. 다양한 조건에서의 수치 시뮬레이션을 통해 제안된 알고리즘의 성능을 검증하였다.

• Journal of the Korean Data and Information Science Society
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• 제19권3호
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• pp.979-994
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• 2008

Moving objects are spatio-temporal data that change their location or shape continuously over time. Generally, if continuously moving objects are managed by a conventional database management system, the system cannot properly process the past and future location which is not stored in the database. Up to now, for the purpose of location tracking which is not stored, the linear interpolation to estimate the past location has been usually used. It is suitable for the moving objects on linear route, not curved route. In this paper, we propose a past location tracking algorithm for a moving object on curved routes, and also suggest a future location tracking algorithm using some past location information. We found that the proposed location tracking algorithm has higher accuracy than the linear interpolation function.

• Journal of Computational Design and Engineering
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• 제1권1호
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• pp.13-26
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• 2014

Recently, renovations of plant equipment have been more frequent because of the shortened lifespans of the products, and as-built models from large-scale laser-scanned data is expected to streamline rebuilding processes. However, the laser-scanned data of an existing plant has an enormous amount of points, captures intricate objects, and includes a high noise level, so the manual reconstruction of a 3D model is very time-consuming and costly. Among plant equipment, piping systems account for the greatest proportion. Therefore, the purpose of this research was to propose an algorithm which could automatically recognize a piping system from the terrestrial laser-scanned data of plant equipment. The straight portion of pipes, connecting parts, and connection relationship of the piping system can be recognized in this algorithm. Normal-based region growing and cylinder surface fitting can extract all possible locations of pipes, including straight pipes, elbows, and junctions. Tracing the axes of a piping system enables the recognition of the positions of these elements and their connection relationship. Using only point clouds, the recognition algorithm can be performed in a fully automatic way. The algorithm was applied to large-scale scanned data of an oil rig and a chemical plant. Recognition rates of about 86%, 88%, and 71% were achieved straight pipes, elbows, and junctions, respectively.

• Journal of information and communication convergence engineering
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• 제10권1호
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• pp.40-44
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• 2012

Data mining, which is attracting public attention, is a process of drawing out knowledge from a large mass of data. The key technique in data mining is the ability to maximize the similarity in a group and minimize the similarity between groups. Since grouping in data mining deals with a large mass of data, it lessens the amount of time spent with the source data, and grouping techniques that shrink the quantity of the data form to which the algorithm is subjected are actively used. The current grouping algorithm is highly sensitive to static and reacts to local minima. The number of groups has to be stated depending on the initialization value. In this paper we propose a gene algorithm that automatically decides on the number of grouping algorithms. We will try to find the optimal group of the fittest function, and finally apply it to a data mining problem that deals with a large mass of data.