• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.53.6-53
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• 2001

In this paper, we are concerned with a tracking filter algorithm which can track a maneuvering target. Among the novel tracking filter algorithms, the input estimation (IE) filter can be summarized as estimating the unknown maneuver input and compensating the state according to the estimated input, and the variable dimension filter (VDF) can be summarized as detecting the maneuver of target and changing the dimension of the target dynamics to accomodate the maneuver of target They have some goods and bads with respect to each other. The variable dimension filter with input estimation (VDIEF) is constructed by combining the two filtering algorithms. However, it requires too much computational burden while it has good performance. We propose another variable dimension with input estimation ...

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.603-614
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• 2022

The naive Bayes classifier is one of the most straightforward classification tools and directly estimates the class probability. However, because it relies on the independent assumption of the predictor, which is rarely satisfied in real-world problems, its application is limited in practice. In this article, we propose employing sufficient dimension reduction (SDR) to substantially improve the performance of the naive Bayes classifier, which is often deteriorated when the number of predictors is not restrictively small. This is not surprising as SDR reduces the predictor dimension without sacrificing classification information, and predictors in the reduced space are constructed to be uncorrelated. Therefore, SDR leads the naive Bayes to no longer be naive. We applied the proposed naive Bayes classifier after SDR to build a recommendation system for the eyewear-frames based on customers' face shape, demonstrating its utility in the top-k classification problem.

• Communications for Statistical Applications and Methods
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• v.31 no.5
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• pp.521-533
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• 2024

As the concentration of fine dust has recently increased, numerous related studies are being conducted to address this issue. Aerosol optical depth (AOD) is a vital atmospheric parameter for measuring the optical properties of aerosols in the atmosphere, providing crucial information related to fine dust. In this paper, we apply three dimension reduction methods, nonnegative matrix factorization (NMF), empirical orthogonal functions (EOF) analysis and independent component analysis (ICA), to AOD data to analyze the patterns of fine dust in the East Asia region. Through a comparison of three dimension reduction methods, we observe that some patterns are observed in all three method, while some information are only extracted in a specific method. Additionally, we forecast AOD levels based on three methods, and compare the predictive performance of the three methodologies.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.217-224
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• 2024

This paper proposes an efficient dimension reduction method (DRM) that considers the nonlinearity of the performance functions in reliability-based design optimization (RBDO). The dimension reduction method evaluates the reliability more accurately than the first-order reliability method (FORM) using integration quadrature points and weights. However, its efficiency is hindered as the number of quadrature points increases owing to the need for an additional evaluation of the performance function. In this study, we assessed the nonlinearity of the performance function in RBDO and proposed criteria for determining the number of quadrature points based on the degree of nonlinearity. This approach suggests adjusting the number of quadrature points during each iteration of the RBDO process while maintaining the accuracy of theDRM while improving the computational efficiency. The nonlinearity of the performance function was evaluated using the angle between the vectors used in the maximum probable target point (MPTP) search. Numerical tests were conducted to determine the appropriate number of quadrature points according to the degree of nonlinearity. Through a 2D numerical example, it is confirmed that the proposed method improves the efficiency while maintaining the accuracy of the dimension reduction method or Monte Carlo Simulation (MCS).

• Journal of Korean Society for Quality Management
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• v.34 no.2
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• pp.107-121
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• 2006

In spite of the increase of the necessity and the interest regarding the SCM in practical business, it is difficult to judge the whole situation of the SCM because the research remain fragmentary as compared with the huge and complicated concept of the SCM. So this study defines dimension of SCM practice and measurements of SCM performance. Through an extensive literature review, the study Identifies seven dimension of SCM practice(partnership, usage of IT tools, information sharing and information quality), five measurements of SCM performance(supply chain flexibility, supply chain integration, customer responsiveness, supplier performance, and partner relationship). Five hypotheses were formulated for the relationship between SCM practice and SCM performance. The important relationships to be tested include ; (1) the direct impact of usage of IT tools on the partnership (2) the direct impact of partnership on the information sharing and information quality (3) the direct impact of SCM practice on the performance of SCM, (4) A moderating effect of top management support on the relationship between SCM practice and SCM performance.

• The Korean Journal of Emergency Medical Services
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• v.20 no.2
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• pp.21-35
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• 2016

Purpose: This study aims to investigate awareness and performance of infection control during ambulance attendant training, and to provide basic data for infection control. Methods: The subjects were 235 paramedic students who completed ambulance attendant training. There were 51 questions. The infection control dimension was divided into hand washing, personal protective equipment use, and environmental management, for each sub-dimension, awareness and performance were measured by a 4-point scale. The collected data were analyzed using SPSS statistics ver. 22.0. Results: A total of 95.3%, of the subjects completed an orientation for ambulance attendant training and 71.7% received education on infection. In all three sub-dimensions, hand- washing (p<.001), personal protective equipment use (p<.001), and environmental management (p<.001), awareness scored higher than performance. The awareness of infection control showed a significantly positive correlation (r=.394) with performance. Conclusion: In order to improve performance of infection control, education to improve awareness should be provided, and paramedics with higher performance levels in hand washing, and use of gloves and masks wearing should be assigned as training advisors.

• Korean Journal of Cognitive Science
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• v.22 no.2
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• pp.103-121
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• 2011

This study investigated how spatial dimension information and dimensional consistency between learning and testing phase would influence the target search performance. The participants learned spatial layouts of Lego blocks shown in either two- (2D) or three-dimension (3D) and were tested with the rotated stimuli ($0^{\circ}$, $90^{\circ}$, $180^{\circ}$, or $270^{\circ}$ from the initial view) in consistent or inconsistent dimension. Significantly better performance was observed when initial learning display appeared in 2D than in 3D. Particularly, the participants showed difficulties in flexible usage of spatial information presented in 3D especially if the dimensional information in the testing phase also was 3D and required mental rotation. The present study indicates that spatial map presented in 2D may be more useful than 3D in driving situations in which acquired spatial information from navigating device, such as GPS, and location of driver continuously changes.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.269-276
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• 2012

The objective of this short communication is to introduce several evaluation methods to crop model users because the evaluation of crop model performance is an important step to develop or select crop model. In this paper, mean error, mean absolute error, index of agreement, root mean square error, efficiency of model, accuracy factor and bias factor were explained and compared in terms of dimension and observed number. Efficiency of model and index of agreement are dimensionless and independent of number of observation. Relative root mean square, accuracy factor and bias factor are dimensionless and not independent of number of observation. Mean error and mean absolute error are affected by dimension and number of observation.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.3
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• pp.234-240
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• 2010

The effectiveness of adding powdered zeolite and granular activated carbon (GAC) before starvation into biological reactor for recovering its performances was investigated. Two types of carrier addition in Sequencing Batch Reactor (SBR) system for non-saline and saline wastewater were evaluated after starvation periods. During the experiment, settleablity (SVI), floc size, fractal dimension, $COD_{Mn}$, T-N, T-P removal efficiencies and recovery time were monitored. When the wastewater feeding was resumed after starvation period for 5days, the SVI increased at the beginning of resumption and then decreased with time in both types. And the larger the floc size and fractal dimension of floc, the more increased removal efficiency for $COD_{Mn}$, T-N and T-P was also. Its performance recovery was strongly correlated with floc size and fractal dimension of activated sludge. After resuming the wastewater feeding, the SVI, floc size, fractal dimension, $COD_{Mn}$, T-N, T-P removal efficiency of SBR with carrier improved and reached its initial value faster compared to those of SBR without carrier.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.4
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• pp.79-86
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• 2004

Tooth errors inevitable in the manufacturing process have large effect on the strength/durability and vibration performances of gear drives. We show that the manufacturing errors affect the overall gear performances, especially vibration performance, and propose a robust optimal design method for gear dimension and its tooth flank form that guarantees reliable performances to the variation of manufacturing errors. This method begins with a search of optimal design candidates by using the previously developed gear optimal design method for the strength/durability and vibration performances. Then, the statistical analysis method is applied to find a robust design solution for the vibration performance which is generally very sensitive to the manufacturing variations.