• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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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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• 제29권5호
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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.

• 품질경영학회지
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• 제34권2호
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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.

• 한국응급구조학회지
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• 제20권2호
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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.

• 인지과학
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• 제22권2호
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• pp.103-121
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• 2011

본 연구는 초기 화면의 차원 정보와 초기-검사 화면의 차원 일치 여부가 목표 대상이 $0^{\circ}$, $90^{\circ}$, $180^{\circ}$, $270^{\circ}$로 회전하는 상황에서 참가자들의 위치 탐색 수행에 어떠한 영향을 미치는지를 보고자 했다. 실험 결과, 초기 화면이 2차원으로 제시되었을 때 참가자들의 수행 정확도가 높았고, 특히 3차원 초기 화면의 경우 검사 화면과 차원이 일치할 때 위치 정보의 심적 회전이 요구되는 상황에서 위치 탐색에 어려움을 겪는 것을 발견하였다. 이러한 결과는 운전 상황과 같이 보조 자료로부터 위치 정보를 얻는 것과 동시에 운전자의 위치와 방향이 변하는 경우, 실제와 시각적으로 유사하게 설계된 3차원 자료보다는 정확한 위치 정보를 제공하는 2차원의 자료가 유리할 수 있음을 시사한다.

• 한국농림기상학회지
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• 제14권4호
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• pp.269-276
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• 2012

작물모형 평가에 사용되거나 사용할 수 있는 9가지 지표를 소개하였으며 이들의 특징은 다음과 같다. efficiency of model (EF)와 index of agreement (d)은 dimension이 없고 관측수(n)에 의존적이지 않았으며, dimension에 대해서만 자유로운 것은 relative root mean square error (RRMSE), bias factor (Bf)와 accuracy factor (Af)이다. Root mean sqruar, mean error, mean absolute error들은 관측수와 dimension에 영향을 받기 때문에 판단 시 주의가 필요하다. 따라서 이들의 특징을 파악하여 목적에 맞게 모형의 성능을 파악하여야 한다.

• 대한환경공학회지
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• 제32권3호
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• pp.234-240
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• 2010

SBR시스템을 이용한 비염분 폐수와 염분 폐수의 생물학적 처리 시 starvation이전 제올라이트 및 입상활성탄 주입이 starvation 이후 시스템의 재가동시 시스템의 성능회복에 대해 조사하였다. Starvation 이후 시스템의 재가동시, SVI, floc의 크기, fractal dimension, 유기물 지표인 $COD_{Mn}$과 T-N, T-P의 처리효율에 미치는 영향을 알아보고 회복 기간을 도출하고자 하였다. 5일 동안 starvation 후 재가동하였을 때에 초기의 SVI는 증가하였으나 시간이 경과함에 따라 감소하였다. 또한 floc 크기 및 fractal dimension이 클수록, 유기물, T-N 및 T-P 처리효율도 증가하였다. 시스템의 성능회복은 floc 크기 및 fractal dimension에 상관성을 가지고 있었다. Starvation 이후 재가동시 오염물질($COD_{Mn}$, T-N, T-P) 처리효율이 정상상태로 회복하는데 필요한 시간은 담체 주입이 미주입보다 더 짧은 시간이 소요되었다.

• 한국공작기계학회논문집
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• 제13권4호
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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.

• Industrial Engineering and Management Systems
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• 제14권3호
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• pp.312-317
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• 2015

The dynamic system approach in time series has been used in many real problems. Based on Taken's embedding theorem, we can build the predictive function where input is the time delay coordinates vector which consists of the lagged values of the observed series and output is the future values of the observed series. Although the time delay coordinates vector from multivariate time series brings more information than the one from univariate time series, it can exhibit statistical redundancy which disturbs the performance of the prediction function. We apply dimension reduction techniques to solve this problem and analyze the effect of this approach for prediction. Our experiment uses delayed Lorenz series; least squares support vector regression approximates the predictive function. The result shows that linearly preserving projection improves the prediction performance.

• Journal of the Korean Data Analysis Society
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• 제20권6호
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• pp.2733-2746
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• 2018

The two inverse regression estimation methods, SIR and SAVE to estimate the central space are computationally easy and are widely used. However, SIR and SAVE may have poor performance in finite samples and need strong assumptions (linearity and/or constant covariance conditions) on predictors. The two non-parametric estimation methods, MAVE and dMAVE have much better performance for finite samples than SIR and SAVE. MAVE and dMAVE need no strong requirements on predictors or on the response variable. MAVE is focused on estimating the central mean subspace, but dMAVE is to estimate the central space. This paper explores and compares four methods to explain the dimension reduction. Each algorithm of these four methods is reviewed. Empirical study for simulated data shows that MAVE and dMAVE has relatively better performance than SIR and SAVE, regardless of not only different models but also different distributional assumptions of predictors. However, real data example with the binary response demonstrates that SAVE is better than other methods.