• 한국조리학회지
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• 제23권6호
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• pp.161-172
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• 2017

The purposes of this study were to examine if a decision making by a tourist sequentially or hierarchically occurs in a tourism destination and to test determinants that have an effect on both a sequential and non-sequential decision making. An instrument for the study was developed with three steps. A total of 420 and 380 questionnaire were collected respectively for the first two round surveys. For the third step, a pilot test was conducted with 30 respondents. And the data analysis utilized SPSS 18.0. A logistic regression analysis with variables of tourism activity and demography was employed to investigate the factors that affect a sequence of decision-making process. As an important result, the higher the age of the tourist in a tourism destination, the more conspicuous the consumption expenditure is made through the sequential decision-making process. Additionally, it is unreasonable to apply the premises and assumptions in extant consumer behavior to tourist behavior. The process of decision making by tourists in tourism areas is driven by either non-sequential or non-hierarchical decision-making process. More discussion and implications were provided.

• Spatial Information Research
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• 제19권1호
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• pp.127-133
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• 2011

Recently, with the advances in sensor techniques and net work computing, Ubiquitous Sensor Network (USN) has been received a lot of attentions from various communities. The sensor nodes distributed in the sensor network tend to continuously generate a large amount of data, which is called stream data. Sensor stream data arrives in an online manner so that it is characterized as high-speed, real-time and unbounded and it requires fast data processing to get the up-to-date results. The data stream has many application domains such as traffic analysis, physical distribution, U-healthcare and so on. Therefore, there is an overwhelming need of a USN middleware for processing such online stream data to provide corresponding services to diverse applications. In this paper, we propose a novel USN middleware which can provide users both context-aware service and meaningful sequential patterns. Our proposed USN middleware is mainly focused on location based applications which use stream location data. We also show the implementation of our proposed USN middleware. By using the proposed USN middleware, we can save the developing cost of providing context aware services and stream sequential patterns mainly in location based applications.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2012년도 학술발표회
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• pp.39-39
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• 2012

Data assimilation techniques have received growing attention due to their capability to improve prediction in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modelling software are based on a deterministic approach. In this study, we developed a hydrological modelling framework for sequential data assimilation, namely MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modelling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. In this software framework, sequential data assimilation based on the particle filters is available for any hydrologic models considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and radar rainfall estimates is assessed simultaneously in sequential data assimilation.

• 전자통신동향분석
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• 제9권4호
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• pp.9-21
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• 1994

Wide variety of the architectural complexity of parallel computer often makes it difficult to develop efficient programs for them. One of approaches to improve this difficulty is to program in familiar sequential languages such as Fortran or C and to parallelize sequential programs into equivalent parallel programs automatically. This paper presents an organization of parallelizing compiler which transforms sequential programs into equivalent parallel programs. The parallelizer consists mainly of syntax analysis, control and data flow analysis, program transformation, and parallel code generation. In particular, the program restructuring in this parallelizer maximizes loop parallelism.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.2064-2068
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• 2010

In this paper, we introduced a sequential intelligent image analysis system(SIIAS). This system is implemented using PTZ camera with intelligent analysis algorithm and TI's Davinci DM6446. Enter, abandon, removal and cross functions are included in our system. These functions can be used individually or in combination for object monitoring and tracking. Sequential intelligent function processing is more efficient than the previous one by virtue of accurate observation, wide area monitoring and low cost.

• Computers and Concrete
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• 제1권1호
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• pp.99-113
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• 2004

The article reports data on, and numerical modelling of, beams exhibiting points of inflection and subjected to sequential loading. Both tests and analysis point to inadequacies in current codes of practice. An alternative design methodology, which is strongly associated with the notion that contraflexure points should be designed as "internal supports", is shown to produce superior performance even though it requires significantly less secondary reinforcement than that advocated by codes.

• 한국정보과학회논문지:데이타베이스
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• 제33권7호
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• pp.741-753
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• 2006

네트워크가 급속도로 발달함에 따라, 네트워크 상에서 발생되는 트래픽 데이타를 대상으로 마이닝 기법을 적용하려는 연구가 활발히 진행되고 있다. 그러나 네트워크 트래픽 데이타를 대상으로 수행되는 마이닝 작업은 네트워크 사용자의 프라이버시를 침해할 여지가 있다는 문제점이 있다. 본 논문에서는 대용량 네트워크 트래픽 데이타를 대상으로 사이트의 프라이버시를 보호하면서 마이닝 결과의 정확성과 실용성을 보장할 수 있는 효율적인 순차 패턴 마이닝 기법을 제안한다. 제안된 기법은, N-저장소 서버 모델과 정보 유지 대체 기법을 사용함으로써, 각 사이트에 저장되어 있는 네트워크 데이타를 공개하지 않은 상태에서 순차 패턴 마이닝을 수행한다. 또한 후보 패턴의 발생 여부를 신속히 결정할 수 있는 메타 테이블을 유지하여 전체 마이닝 과정이 효율적으로 진행되도록 한다. 네트워크 상에서 발생한 실제 트래픽 데이타를 대상으로 다양한 실험을 수행한 결과 제안된 기법의 효율성과 정확성을 확인할 수 있었다.

• 터널과지하공간
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• 제16권2호
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• pp.135-145
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• 2006

본 연구에서는 조건부 모사 기법 중 순차 가우시안 시뮬레이션(SGS)과 순차 지시 시뮬레이션(SIS)을 이용하여 터널설계 시 미시추구간의 암반등급(RMR)을 예측하여 보았다. 총 30개의 시추공자료 가운데 25개의 시추공자료를 이용하여 순차 가우시안 시뮬레이션과 순차 지시 시뮬레이션을 수행하였으며, 나머지 5개의 시추공에서의 실제 암반등급과 예측 암반등급을 비교하여 보았다. 그 결과 조건부 모사 기법은 암반등급의 공간적 분포특성을 비교적 잘 예측할 수 있고, 예측의 불확실성을 정량적으로 평가할 수 있는 효과적인 방법임을 확인할 수 있었다. 따라서 조건부 모사 기법의 결과는 미시추구간의 암반등급을 예측하는데 있어서 유용한 정보를 제공 해 줄 수 있을 것으로 판단된다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -1
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• pp.698-701
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• 2002

Subspace analysis (which includes PCA) seeks for feature subspace (which corresponds to the eigenspace), given multivariate input data and has been widely used in computer vision and pattern recognition. Typically data space belongs to very high dimension, but only a few principal components need to be extracted. In this paper I present a fast sequential algorithm for subspace analysis or tracking. Useful behavior of the algorithm is confirmed by numerical experiments.

• Journal of the Korean Data and Information Science Society
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• 제16권3호
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• pp.657-663
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• 2005

Under the minimum risk point estimation formulation of Robbins(1959), we consider the sequential point estimation problem for normal population $N({\theta},\;{\theta})$ with unknown parameter ${\theta}$. In the case of completely unknown ${\theta}$, Stein's(1945) two-stage procedure is known to enjoy the consistency property, but it is not even first-order efficient. In the case when ${\theta}>{\theta}_L\;where\;{\theta}_L(>0)$ is known, the revised two-stage procedure is shown to enjoy all the usual second-order properties.