• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1361-1369
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• 2000

For the implementation of 3D Sound Localization system, the binaural filtering by HRTFs is generally employed. But the HRTF filter is of high order and its coefficients for all directions have to be stored, which imposes a rather large memory requirement. To cope with this, research works have centered on obtaining low dimensional HRTF representations without significant loss of information and synthesizing the original HRTF efficiently, by means of feature extraction methods for multivariate dat including PCA. In these researches, conventional linear PCA was applied to the frequency domain HRTF data and using relatively small number of principal components the original HRTFs could be synthesized in approximation. In this paper we applied neural network based nonlinear PCA model (NLPCA) and the nonlinear PLS repression model (NLPLS) for this low dimensional HRTF modeling and analyze the results in comparison with the PCA. The NLPCA that performs projection of data onto the nonlinear surfaces showed the capability of more efficient HRTF feature extraction than linear PCA and the NLPLS regression model that incorporates the direction information in feature extraction yielded more stable results in synthesizing general HRTFs not included in the model training.

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.194-204
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• 2012

Measuring task complexity of movement skill is an important factor to evaluate a difficulty of learning and/or imitating a task for autonomous robots. Although many complexity-measures are proposed in research areas such as neuroscience, physics, computer science, and biology, there have been little attention on the robotic tasks. To cope with measuring complexity of robotic task, we propose an information-theoretic measure for task complexity of movement skills. By modeling proprioceptive as well as exteroceptive sensor data as multivariate Gaussian distribution, movements of a task can be modeled as probabilistic model. Additionally, complexity of temporal variations is modeled by sampling in time and modeling as individual random variables. To evaluate our proposed complexity measure, several experiments are performed on the real robotic movement tasks.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.3
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• pp.95-117
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• 2005

This research Investigates the determinants of customer Intention to participate In Internet auction. Based on technology acceptance and trust related studies, our research proposes a theoretical model consisting of factors such as perceived usefulness, perceived ease of use, institution based trust, beliefs on sellers, trusting beliefs, and participation Intention. For examining the relationships implied by the research model, a field study using a survey methodology for data collection was conducted. The data were analyzed using AMOS based on the structural equation modeling, a second-generation multivariate technique, which has gained distinct advantages over other technique. After some model modification according to model generating strategy approach, this study shows that trusting beliefs have significant effects on the participating intention in Internet auction site. In conclusion, Implications are discussed along with limitations and further research direction.

• Journal of Nutrition and Health
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• v.50 no.6
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• pp.595-602
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• 2017

Purpose: Malnutrition is a major concern in patients with gynecologic cancer receiving chemotherapy. The aim of this study was to evaluate the prognostic significance of malnutrition in patients with gynecologic cancer undergoing chemotherapy. Methods: A prospective, observational study was conducted on a total of 99 subjects who were treated at a tertiary hospital in Korea. Data regarding demographic, clinical, nutritional, and psychological characteristics at baseline and survival were obtained. Results: Performance status, nutritional status, depression, and annual income were significantly different between survivors and non-survivors. Multivariate Cox modeling after adjusting for other factors showed that a malnourished status in patients with gynecologic cancer undergoing chemotherapy was a significant and independent negative influencing factor for survival. Conclusion: These findings provide evidence that adequate nutritional assessment and intervention may assist in improving survival in patients with gynecologic cancer undergoing chemotherapy.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.2
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• pp.81-87
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• 2004

This paper deals with a new approach to tolerance optimization problems. Optimal tolerance allotment problems can be formulated as stochastic optimization problems. Most schemes to solve the stochastic optimization problems have been found to exhibit difficulties in multivariate integration of the probability density function. As a typical example of stochastic optimization the optimal tolerance allotment problem has the same difficulties. In this stochastic model, manufacturing system is represented by Gauss-Markov stochastic process and the manufacturing unit availability is characterized for realistic optimization modeling. The new algorithm performed robustly for a large deviation approximation. A significant reduction in computation time was observed compared to the results obtained in previous studies.

• Proceedings of KOSOMES biannual meeting
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• 2002.10a
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• pp.163-175
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• 2002

가상현실 기법(virtual reality technologies)를 해양안전사고 가시화 시스템 개발에 적용하기 위한 개발론에 대해서 기술하였다. ‘목포해심’ 재결서 700여가지 사건에 대한 분류표와 수령화 표를 작성하여 질적 데이터를 양적 데이터로 변환하였다. 개발론에 대한 검토결과, 과거 10년 간의 해양사고 사건사례를 압축하여 저차원 데이터를 획득하기 위해서는 다변량해석기법(multivariate analysis)을 적용해야하고, 위기관리를 종합적으로 수행하기 위해서는 기존에 제시되고 있는 PRA, QRA, SPE 등의 기법 중 적합한 것을 적용할 필요가 있으며, 통계 데이터의 가시화를 위해서는 MATLAB의 Simulink 와 VR Toolkit을 이용하면 가능함을 분석할 수 있었다.

• Journal of Fisheries and Marine Sciences Education
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• v.16 no.1
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• pp.99-109
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• 2004

This study analyzed the multivariate impacts of subsidies on the sustainability of fish stock using a dynamic bioeconomic modeling and fisheries resources economic approaches for understanding impacts of a subsidy on the sustainability of a fish stock. According to the results of analysis, the conclusion of former studies is true only there are imperfect control of fishing effort and enforcement under management rerime and under open access. However, if there are perfect control of effort and enforcement, the subsidies do not give any negative impacts on the sustainability of fish stock. Further, if even so-called bad subsidy is also provided necessarily in response to the condition of fishing industry and the characteristic of fishermen, it can give positive impacts on fishing income by which fishermen can improve their fishing condition.

• Journal of KIBIM
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• v.9 no.1
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• pp.22-31
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• 2019

In this paper, we construct a prototype model for city data prediction by using time series data of floating population, and use machine learning to analyze urban data of complex structure. A correlation prediction model was constructed using three of the 10 data (total flow population, male flow population, and Monday flow population), and the result was compared with the actual data. The results of the accuracy were evaluated. The results of this study show that the predicted model of the floating population predicts the correlation between the predicted floating population and the current state of commerce. It is expected that it will help efficient and objective design in the planning stages of architecture, landscape, and urban areas such as tree environment design and layout of trails. Also, it is expected that the dynamic population prediction using multivariate time series data and collected location data will be able to perform integrated simulation with time series data of various fields.

• Ocean and Polar Research
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• v.30 no.2
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• pp.129-140
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• 2008

As a preliminary effort to establish a data assimilative ocean forecasting system, we reviewed the theory of the Ensemble Kamlan Filter (EnKF) and developed practical techniques to apply the EnKF algorithm in a real ocean circulation modeling system. To verify the performance of the developed EnKF algorithm, a wind-driven double gyre was established in a rectangular ocean using the Regional Ocean Modeling System (ROMS) and the EnKF algorithm was implemented. In the ideal ocean, sea surface temperature and sea surface height were assimilated. The results showed that the multivariate background error covariance is useful in the EnKF system. We also tested the sensitivity of the EnKF algorithm to the localization and inflation of the background error covariance and the number of ensemble members. In the sensitivity tests, the ensemble spread as well as the root-mean square (RMS) error of the ensemble mean was assessed. The EnKF produces the optimal solution as the ensemble spread approaches the RMS error of the ensemble mean because the ensembles are well distributed so that they may include the true state. The localization and inflation of the background error covariance increased the ensemble spread while building up well-distributed ensembles. Without the localization of the background error covariance, the ensemble spread tended to decrease continuously over time. In addition, the ensemble spread is proportional to the number of ensemble members. However, it is difficult to increase the ensemble members because of the computational cost.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.923-932
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• 2008

We are likely to face complex multivariate data which can be characterized by having a non-trivial correlation structure. For instance, omitted covariates may simultaneously affect more than one count in clustered data; hence, the modeling of the correlation structure is important for the efficiency of the estimator and the computation of correct standard errors, i.e., valid inference. A standard way to insert dependence among counts is to assume that they share some common unobservable variables. For this assumption, we fitted correlated random effect models considering multilevel model. Estimation was carried out by adopting the semiparametric approach through a finite mixture EM algorithm without parametric assumptions upon the random coefficients distribution.