• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.527-530
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• 1996

The Kalman filter has been used as a self-localization method for the mobile robot. To satisfy the assumptions inherent in the Kalman filter, we should calibrate the sensors of the robot before use of them. However, it is generally hard to find exact sensor parameters, and the parameters may change during the robot task as the environment varies. Thus we need to perform on-line sensor calibration, by which we can obtain more credible location of the mobile robot. In this paper, we present an on-line sensor calibration scheme which estimates the unknown sensor bias and the current position of the robot. To this end, first we find out the calibration errors of the sensor from redundant sensory data using the parity vector and recursive minimum variance estimation. Then we calculate the current position of the robot by weighted least square estimation without internal encoder data. The performance of the proposed method is evaluated through computer simulation.

• Biotechnology and Bioprocess Engineering:BBE
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• v.9 no.5
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• pp.414-418
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• 2004

A 'minimally complex problem set' for ab initio protein Structure prediction has been proposed. As well as consisting of non-redundant and crystallographically determined high-resolution protein structures, without disulphide bonds, modified residues, unusual connectivities and heteromolecules, it is more importantly a collection of protein structures. with a high probability of being the same in the crystal form as in solution. To our knowledge, this is the first attempt at this kind of dataset. Considering the lattice constraint in crystals, and the possible flexibility in solution of crystallographically determined protein structures, our dataset is thought to be the safest starting points for an ab initio protein structure prediction study.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.101-106
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• 2004

Subcellular localization is a key functional char acteristic of proteins. With the number of sequences entering databanks rapidly increasing, the importance of developing a powerful tool to identify protein subcellular location has become self-evident. In this paper, we introduce a novel method for predic ting protein subcellular locations from protein sequences. The main idea was motivated from the observation that amino acid pair composition data is redundant. By classifying from multiple feature subsets and using many kinds of amino acid pair composition s, we forced the classifiers to make uncorrelated errors. Therefore when we combined the predictors using a voting scheme, the prediction accuracy c ould be improved. Experiment was conducted on several data sets and significant improvement has been achieve d in a jackknife test.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.5-9
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• 1998

In this paper, we propose an error-resilient transmission technique for the H.263 video data stream over wireless networks. The proposed algorithm employs bit rearrangement hierarchically, providing the robust and exact synchronization against the bit errors, without requiring extra redundant information. In addition, we propose the recovery algorithm for the lost or erroneous motion vectors. We implement the encoder and decoder, based on the H.263 standard, and evaluate the proposed algorithm through intensive computer simulation. The experimental results demonstrate that the proposed algorithm yields good image quality, in spite of the channel errors, and prevents the error propagation both in the spatial and the temporal domain efficiently.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.25-32
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• 2016

In this paper, we design a middleware for context-awareness which provides compound contexts from diverse sensors on a mobile device. Until now, most of context-aware application developers have taken responsibility for context processing from sensing data. Such application-level context processing causes heavily redundant data processing and leads to significant resource waste in energy as well as computing. In the proposed scheme, we define primitive and compound context map which consists of relavant sensors and features. Based on the context definition, each application demands a context of interest to the middleware, and thus similar context-aware applications inherently share context information and procesing within the middleware. We show that the proposed scheme significantly reduces the resource amounts of cpu, memory, and battery, and that the performance gain gets much more when multiple applications which need similar contexts are running.

• Korean Management Science Review
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• v.23 no.1
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• pp.63-74
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• 2006

Decision tree induction algorithm is one of the most widely used methods in classification problems. However, they could be trapped into a local minimum and have no reasonable means to escape from it if tree algorithm uses top-down search algorithm. Further, if irrelevant or redundant features are included in the data set, tree algorithms produces trees that are less accurate than those from the data set with only relevant features. We propose a hybrid algorithm to generate decision tree that uses genetic programming with sequentially selected features. Correlation-based Feature Selection (CFS) method is adopted to find relevant features which are fed to genetic programming sequentially to find optimal trees at each iteration. The new proposed algorithm produce simpler and more understandable decision trees as compared with other decision trees and it is also effective in producing similar or better trees with relatively smaller set of features in the view of cross-validation accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.273-283
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• 2008

This article describes a cooperative localization technique of multiple robots sharing position information of each robot. In case of conventional methods such as EKF, they need to linearization process. Consequently, they are not able to guarantee that their result is range containing true value. In this paper, we propose a method to merge the data of redundant sensors based on constraints propagation techniques on intervals. The proposed method has a merit guaranteeing true value. Especially, we apply the constraints propagation technique fusing wheel encoders, a gyro, and an inexpensive GPS receiver. In addition, we utilize the correlation between GPS data in common workspace to improve localization performance for multiple robots. Simulation results show that proposed method improve considerably localization performance of multiple robots.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.61-68
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• 2007

In a naval combat system, the information processing node is a key functional equipment and performs major combat management functions including control sensor and weapon systems. Therefore, a failure of one of the node causes fatal impacts on overall combat system capability. There were many methodologies to enhance system availability by reducing the impact of system failure like a fault tolerant method. This paper proposes a fault tolerant mechanism for information processing node using a replication algorithm with hardware duplication. The mechanism is designed as a generic algorithm and does not require any special hardware. Therefore all applications in combat system can use this functionality. The asynchronous characteristic of this mechanism provides the capability to adapt this algorithm to the module which has low performance hardware.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.602-604
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• 2006

한국천문연구원(KASI)은 국제 GNSS 관측망(IGS)의 글로벌 데이터 센터(GDC)를 설립하였다. KASI GDC는 공식적으로 IGS GDC이고 세계 4번째로 설립되었으며, 아시아 및 오세아니아 지역에서는 최초이다. KASI GDC는 IGS GNSS 데이터를 기록하고, IGS GPS 데이터와 IGS 산출물을 인터넷을 통해 제공한다. GDC에서 다루는 데이터의 양은 매우 빠르게 증가한다. GDC 데이터의 대용량을 처리하기 위해서는 시스템의 높은 효율성과 신뢰성이 요구된다. 그래서 KASI GDC는 높은 신뢰성과 대용량 저장 장치를 필요로 하는 저장 시스템을 구성하기 위해 RAID와 LVM을 적용했다. KASI GDC의 공식 출범 이후 데이터 이용 현황을 확인하고, 항상 시스템이 Active 상태로 유지하기 위한 무정전 시스템 구성에 대해 기술한다.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1237-1243
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• 2018

In the HDTV video codec, conventional the padding method of DEPA(DTV essential padding area) region is aimed at minimizing the redundant information to be transmitted. This article propose a method to transmit additional data by using DEPA region. The proposed method is effective for the channel and storage because it can reduce the amount of bits while preventing deterioration of image quality by inserting binary gray image blocks into the DEPA region. Additionally this algorithm can be used in various fields because it conforms to the standards of MPEG-2, ATSC, and DVB encoders.