• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.173-175
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• 2005

In this paper, we propose a data encoding algorithm for two-dimensional barcode system. In general, one-dimensional barcode is just a key which can access detailed information to the host computer database. But the two-dimensional barcode is a new technology which can obtain high density information without access to the host computer database. We implemented encoding algorithm for Data Matrix Barcode which is the most widely used among the many kind of two-dimensional barcodes. And we marked to a real object using Digital Signal Processor(DSP) Marking System. The performance of proposed algorithm is verified through the result of marking work.

• Journal of electromagnetic engineering and science
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• 제7권1호
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• pp.1-6
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• 2007

Recently, Mc(Multi-code) modulation/demodulation(modem) technique has been explored for high speed data transmission in wireless environment. The conventional Mc modem generates some side effects such as allocating Walsh codes, which motivates to propose a novel Mc modem method with sub-code. Our proposed system should expanded the size of sub-code to provide high-rate data transmission, which also affect adversely to the performance of the system with high PAPR(Peak to Average Power Ratio). Thus, in this paper, we propose a novel pre-coded Multi-Dimensional HCOC(High Capacity Orthogonal Code) Mc modem technique to reduce the high PAPR, which enables the performance improvement. This proposed system can be easily designed by concatenating HCOC Mc modem with the generic Mc modem. The pre-coding technique that is used in this paper is CAC(Constant Amplitude Coding), that helps the system maintain the constant transmission power and reduce the maximum transmission power.

• 정보처리학회논문지D
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• 제10D권1호
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• pp.1-12
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• 2003

최근 이미지, 비디오와 같은 멀티미디어 데이터에 대한 효율적인 검색을 위해 많은 다차원 및 고차원 색인 구조들에 대한 연구가 활발히 진행되고 있다. 하지만 기존의 색인 구조의 연구 방향은 검색의 효율을 극대화 하는데 초점을 맞추어 왔으며 최근의 멀티미디어 데이터베이스나 데이터 마이닝 분야와 같은 다수 사용자 환경을 요구하는 환경에서는 부적합한 실정이다. 이에 본 논문에서는 기존의 제시된 차원이 증가하면서 급속하게 성능이 저하되는 문제를 특징 벡터의 시그니쳐를 구성하여 완화시킨 필터링에 기반한 고차원 색인 구조에 동시성 제어기법을 설계 및 구현하여 위스콘신 대학에서 개발한 지속성 객체 저장 시스템인 SHORE 하부저장 시스템과 밀결합 방식으로 통합하였다. 확장된 SHORE 하부저장 시스템은 고차원 데이터에 대한 효율적인 검색 뿐만 아니라 레코드 레벨의 색인 데이터에 대한 동시성 제어를 지원하며 시그니쳐 파일을 모두 메모리에 로딩하는 구조를 개선하여 페이지 레벨의 관리가 가능하다. 아울러 본 논문에서 제시한 확장된 SHOE 하부저장 시스템을 실제 응용 시스템에 적용하기 위해 플랫폼 독립적인 환경을 지원하는 자바 언어를 사용하여 미들웨어 구축 방안을 제시한다. 또한 구축된 미들웨어를 통해 쓰레드 별로 대표적인 내용기반 질의 형태인 포인트질의, 범위질의, k-최근접 질의에 대한 다수 사용자 환경에서의 성능 평가를 수행하였다.

• Journal of Information Processing Systems
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• 제16권2호
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• pp.435-446
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• 2020

With the ability to learn rules from training data, the machine learning model can classify unknown objects. At the same time, the dimension of hyperspectral data is usually large, which may cause an over-fitting problem. In this research, an identification methodology of tea diseases was proposed based on spectral reflectance and machine learning, including the feature selector based on the decision tree and the tea disease recognizer based on random forest. The proposed identification methodology was evaluated through experiments. The experimental results showed that the recall rate and the F1 score were significantly improved by the proposed methodology in the identification accuracy of tea disease, with average values of 15%, 7%, and 11%, respectively. Therefore, the proposed identification methodology could make relatively better feature selection and learn from high dimensional data so as to achieve the non-destructive and efficient identification of different tea diseases. This research provides a new idea for the feature selection of high dimensional data and the non-destructive identification of crop diseases.

• Nuclear Engineering and Technology
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• 제30권3호
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• pp.273-286
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• 1998

As there has arisen a concern that failure of the high burnup fuel under the reactivity-insertion accident(RIA) may occur at the energy lower than the expected, fuel behavior under the rod ejection accident in a typical Westinghouse-designed 950 MWe PWR was analyzed by using the three dimensional nodal transient neutronics code, PANBOX2 and the transient fuel rod performance analysis code, FRAP-T6. Fuel failure criteria versus the burnup was conservatively derived taking into account available test data and the possible fuel failure mechanisms. The high burnup and longer cycle length fuel loading scheme of a peak rod turnup of 68 MWD/kgU was selected for the analysis. Except three dimensional core neutronics calculation, the analysis used the same core conditions and assumptions as the conventional zero dimensional analysis. Results of three dimensional analysis showed that the peak fuel enthalpy during the rod ejection accident is less than one third of that calculated by the conventional zero dimensional analysis methodology and the fraction of fuel failure in the core is less than 4 %. Therefore, it can be said that the current design limit of less than 10 percent fuel failure and maintaining the core coolable geometry would be adequately satisfied under the rod ejection accident, even though the conservative fuel failure criteria derived from the test data are applied.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2007년도 추계 종합학술대회 논문집
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• pp.217-220
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• 2007

고차원의 데이터를 저차원으로 차원축소 하는 것은 일반적인 문제에서 항상 나타난다. 이때, 고차원에서 데이터 간의 인접한 관계를 유지하면서 저차원으로 변형시켜주는 방법으로 LLE(Locally Linear Embedding)이 제안되었다. 이 방법은 비록 최적의 해를 찾아주지만, 학습되지 않은 데이터가 주어지면 다시 전체 데이터를 상대로 처리를 하여야 한다. 이 논문에서는, 주어진 학습데이터 만을 상대로 LLE의 관계를 수행할 수 있는 다층퍼셉트론을 학습시켜, 학습되지 않은 데이터가 입력되는 경우 다층퍼셉트론의 출력으로 LLE 처리를 하는 방법을 제안한다.

• Journal of Advanced Marine Engineering and Technology
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• 제23권2호
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• pp.259-269
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• 1999

A new algorithm for measuring 3-D velocity components of high speed flows were developed using a digital image processing technique. The measuring system consists of three CCD cameras an optical instrument called AOM a digital image grabber and a host computer. The images of mov-ing particles arranged spatially on a rotation plate are taken by two or three CCD cameras and are recorderd onto the image grabber or a video tape recoder. The three-dimensionl velocity com-ponents of the particles are automatically obtained by the developed algorithm In order to verify the validity of this technique three-dimensional velocity data sets obtained from a computer simu-lation of a backward facing step flow were used as test data for the algorithm. an uncertainty analysis associated with the present algorithm is systematically evaluated, The present technique is proved to be used as a tookl for the measurement of unsteady three-dimensional fluid flows.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1272-1274
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• 2003

In this paper, we present a new algorithm for high dimensional data reduction based on wavelet decomposition and Genetic Algorithm (GA). Comparative results show the superiority of our algorithm for dimensionality reduction and accuracy improvement.

• 한국가시화정보학회지
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• 제1권2호
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• pp.58-70
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• 2003

Meteorological data contains observation and numerical weather prediction model output data. The computerized analysis and visualization of meteorological data often requires very high computing capability due to the large size and complex structure of the data. Because the meteorological data is frequently formed in multi-variables, 3-dimensional and time-series form, it is very important to visualize and analyze the data in 3D spatial domain in order to get more understanding about the meteorological phenomena. In this research, we developed interactive 3-dimensional visualization techniques for visualizing meteorological data on a PC environment such as volume rendering, iso-surface rendering or stream line. The visualization techniques developed in this research are expected to be effectively used as basic technologies not only for deeper understanding and more exact prediction about meteorological environments but also for scientific and spatial data visualization research in any field from which three dimensional data comes out such as oceanography, earth science, and aeronautical engineering.

• 응용통계연구
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• 제29권4호
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• pp.643-656
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• 2016

고차원 자료(high dimensional data)는 변수의 수가 표본의 수보다 많은 자료로 다양한 분야에서 관측 또는 생성되고 있다. 일반적으로, 고차원 자료에 대한 회귀 모형에서는 모수의 추정과 과적합을 피하기 위하여 변수 선택이 이루어진다. 벌점화 회귀 모형(penalized regression model)은 변수 선택과 회귀 계수의 추정을 동시에 수행하는 장점으로 인하여 고차원 자료에 빈번하게 적용되고 있다. 하지만, 벌점화 회귀 모형에서도 여전히 조율 모수 선택(tuning parameter selection)을 통한 최적의 모형 선택이 요구된다. 본 논문에서는 벌점화 회귀 모형 중에서 대표적인 LASSO 회귀 모형을 기반으로 모형 선택의 기준들에 대한 LASSO 회귀 추정량의 편의가 어떠한 영향을 미치는지 모의실험을 통하여 수치적으로 연구하였고 편의의 보정의 필요성에 대하여 나타내었다. 실제 자료 분석에서의 영향을 나타내기 위하여, 폐암 환자의 유전자 발현량(gene expression) 자료를 기반으로 바이오마커 식별(biomarker identification) 문제에 적용하였다.