• 한국정보과학회논문지:시스템및이론
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• 제36권4호
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• pp.283-290
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• 2009

Rank/select 자료구조는 트리, 그래프, 문자열 인덱스 등의 다양한 자료구조를 간결하게 표현하는 기본 도구이다. Rank/select 자료구조는 주어진 문자열에 어느 위치까지 나타난 문자 개수를 세는 연산을 처리한다. 효율적인 rank/select 자료구조를 위해 이론적인 압축 방식들이 제안되었으나, 실제 구현에 있어 연산 시간 및 저장 공간의 효율을 보장할 수 없었다. 본 논문은 간단한 방법으로 이론적인 압축 크기를 보장하면서 연산 시간도 효율적인 rank/select 자료구조 구현 방법을 제시한다. 본 논문의 실험을 통해, 복잡한 인코딩 방법 없이도 이론적인 nH$_0$ + O(n) 비트 크기에 근접하면서 기존의 HSS 자료구조보다 빠른 rank/select 연산을 지원하는 구현 방법임을 보인다.

• 한국BIM학회 논문집
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• 제9권1호
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• pp.42-51
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• 2019

Maintenance of aging structures has attracted societal attention. Maintenance of the aging structure can be efficiently performed with a digital twin. In order to maintain the structure based on the digital twin, it is required to accurately detect the damage of the structure. Meanwhile, deep learning-based damage detection approaches have shown good performance for detecting damage of structures. However, in order to develop such deep learning-based damage detection approaches, it is necessary to use a large number of data before and after damage, but there is a problem that the amount of data before and after the damage is unbalanced in reality. In order to solve this problem, this study proposed a method based on Generative adversarial network, one of Generative Model, for generating acceleration data usually used for damage detection approaches. As results, it is confirmed that the acceleration data generated by the GAN has a very similar pattern to the acceleration generated by the simulation with structural analysis software. These results show that not only the pattern of the macroscopic data but also the frequency domain of the acceleration data can be reproduced. Therefore, these findings show that the GAN model can analyze complex acceleration data on its own, and it is thought that this data can help training of the deep learning-based damage detection approaches.

• 마케팅과학연구
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• 제18권1호
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• pp.141-156
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• 2008

본 연구는 미국의 자동시장의 시장구조를 분석한 것이다. 자동차 시장의 구조분석는 제품의 특성이 냐내구재라는 점에서 의의가 있다. 그 동안 시장구조분석은 일반포장소비재를 중심으로 분석되어 왔으나 자동차의 시장구조분석는 자동차의 구매주기가 장기간이며, 다음 구매는 많은 소비자가 상위차급으로 이동한다는 점에서 기존의 분석에 사용되었던 상표전환자료를 사용하는데 한계가 있다. 이 때문에 본 연구에서는 구매고려상표군을 중심으로 우사성지수로 사용하여 시장구조분석을 하였다. 자료는 미국의 자동차구매에 관한 이차자료를 활용하였으며, 자료의 특성상 일부차종에 한정하여 사용하였다. 크게 세가지 형태-비용, 비용-형태, 비구조화의 가설적 시장을 비교분석하였으며, 결과적으로 형태-비용 구조가 가장 우수한 것으로 판단되었다.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권3호
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• pp.145-156
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• 2000

In this paper, we propose a new methodology which includes the optimal design procedure of Polynomial Neural Networks(PNN) structure for model identification of complex and nonlinear system. The proposed PNN algorithm is based on GMDA(Group Method of Data handling) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and can be generated. The each node of PNN structure uses several types of high-order polynomial such as linear, quadratic and cubic, and is connected as various kinds of multi-variable inputs. In other words, the PNN uses high-order polynomial as extended type besides quadratic polynomial used in GMDH, and the number of input of its node in each layer depends on that of variables used in the polynomial. The design procedure to obtain an optimal model structure utilizing PNN algorithm is shown in each stage. The study is illustrated with the aid of pH neutralization process data besides representative time series data for gas furnace process used widely for performance comparison, and shows that the proposed PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and prediction capabilities of model is evaluated and also discussed.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2006년도 추계 학술대회논문집
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• pp.26-27
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• 2006

Characteristics of spatial structure of particle clusters are investigated by using the flow field data obtained from three-dimensional numerical simulations. Eulerian/Lagrangian approach with two-way coupling is applied and individual particle-particle collisions are taken into account by using the hard-sphere model. More than 16 million particles are traced in the maximum case. The results show that the cluster is consisted from the multiple-spatial scale components while the low wave-number, hence the large-scale structure, is dominant. Three-dimensional structure reconstructed from the low-pass filtered data enables us to investigate the essential dynamics of particle clusters in detail.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.133-133
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• 2021

The performance of radar Quantitative Precipitation Estimation (QPE) using Long Short-Term Memory (LSTM) networks in hydrological applications depends on either the quality of data or the three-dimensional CAPPI structure from the weather radar. While radar data quality is controlled and enhanced by the more and more modern radar systems, the effect of CAPPI structure still has not yet fully investigated. In this study, three typical and important types of CAPPI structure including inverse-pyramid, cubic of grids 3x3, cubic of grids 4x4 are investigated to evaluate the effect of CAPPI structures on the performance of radar QPE using LSTM networks. The investigation results figure out that the cubic of grids 4x4 of CAPPI structure shows the best performance in rainfall estimation using the LSTM networks approach. This study give us the precious experiences in radar QPE works applying LSTM networks approach in particular and deep-learning approach in general.

• 한국CDE학회논문집
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• 제9권4호
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• pp.294-305
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• 2004

Highly detailed geometric models are rapidly becoming commonplace in computer graphics and other applications. These complex models, which is often represented as complex1 triangle meshes, mainly suffer from the vast memory requirement for real-time manipulation of arbitrary geometric shapes without loss of data. Various techniques have been devised to challenge these problems in views of geometric processing, not a representation scheme. This paper proposes the new mesh structure for the compact representation and the efficient handling of the highly complex models. To verify the compactness and the efficiency, the memory requirement of our representation is first investigated and compared with other existing representations. And then we analyze the time complexity of our data structure by the most critical operation, that is, the enumeration of the so-called one-ring neighborhood of a vertex. Finally, we evaluate some elementary modeling functions such as mesh smoothing, simplification, and subdivision, which is to demonstrate the effectiveness and robustness of our mesh structure in the context of the geometric modeling and processing.

• Communications for Statistical Applications and Methods
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• 제22권1호
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• pp.11-14
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• 2015

The Great Famine may have had a continued impact on the population structure of North Korea even after the crisis subsided ten years ago. However, there is a significant gap between what has been said about the country and what data indicates. This gap seems inevitable mainly because reliable data are seriously lacking and access is restricted for most scholars outside the country. Yet, it is only reasonable to question why most studies have failed to explain the causality between the Great Famine and accumulated changes in the population of North Korea. In this regard, a recent study conducted by Korean demographers (Jeon et al., 2015) have several implications on the importance of accurate and reliable data when the study involves such rare and scarce information. This paper explores the changing trends of the population structure in North Korea providing a review of recent studies on demographic issues associated with North Korea and offers suggestions on understanding the post-famine effect on the overall changes in the population of North Korea.

• 통상정보연구
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• 제9권4호
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• pp.461-482
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• 2007

This Paper will use various analysis tools that have not been used a lot by the existing researches, and also use the statistics of trade until August 2007 to measure and analyze the trade relationship between China and Korea. This study, which is basic study to studies to be conducted later, has been performed to establish effective economic cooperative relations between Korea and China by examining trade structure of the two countries through trade-related indexes. Therefore, this study has academic values as a theoretical study which can explain economic effects of the Korea-China FTA. However, as data used for this study was based on the data of the National Statistics Office in general, this study was executed with realistic limitations owing to lack of local data. I will supplement this later and do my best to conduct a precise study.

• 디지털산업정보학회논문지
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• 제7권4호
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• pp.75-79
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• 2011

With the rapid growth of digital communication and the internet, the importance of conducting research on data encryption methods is increasing. Some of the pertinent researches that have been conducted so far introduced data encryption methods using chaos systems, and numerous researches are currently being conducted on such methods. The signals produced by the chaos systems are called "determined noise," and if this is applied to data encryption, very effective results can be obtained. Using the Henon map, the relationship between the non-linearity of the chaos system and the strength of encryption was analyzed, and a linear-structure chaos system that uses non-linearity as a variable for encryption strength was constructed. Using the constructed chaos system, an image was encrypted and decoded, and the correlation coefficient of the linear-structure chaos system's performance was calculated and then analyzed.