• Korea Journal of Hospital Management
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• v.25 no.2
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• pp.69-75
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• 2020

Purposes: This study aims to investigate the number of cataract surgeries and predict future trends using 13-year data. Methodology: Trends investigation and comparison of prediction methods was conducted to determine better prediction model using Major Surgery Statistics from Korean Statistical Information Service in 2006-2018. ARIMA(Auto Regressive Integrated Moving Average) was selected and prediction was conducted using R program. Findings: As a results, the number of surgeries will continue to increase. The trends was predicted to increase during January-April, and it declined over time and was the lowest in August. Pratical Implications: Therefore, it is necessary that management will be needed by continuously investigating and predicting the demand and trend for surgery to prepare an alternative to the increase.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.216-220
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• 2008

오늘날 인터넷은 사용자에게 수많은 정보와 다양한 선택의 기회를 제공하지만, 사용자는 급속하게 늘어난 수 많은 정보 중에서 자신에게 유용한 정보를 찾는데 더 많은 시간을 투자해야만 한다. 이러한 문제점을 극복하고 좀 더 효율적인 인터페이스를 제공하기 위해서는 사용자들이 원하는 정보를 획득하기까지, 어떠한 탐색 과정을 거쳐 의사 결정을 내리는지에 관한 이해가 선행되어야 할 것이다. 따라서 본 연구는 웹 검색 결과를 소비하는 사용자의 정보 탐색 패턴과 이에 수반되는 인지 과정을 시선의 움직임을 통하여 분석하였다. 실험 결과 일반적인 글읽기 형태와는 차별된 시선의 움직임을 관찰할 수 있었는데, 대부분의 시선 이동 궤적은 직선이 아닌 도처에 걸쳐 흩어진 의미 단위로 드문드문 이동함을 알 수 있었다. 또한 각 의미 단위를 중심으로 진행성(forward) 도약과 역행성(regressive) 도약이 관찰되었고, 제목 ${\rightarrow}$ 내용 순의 세밀한 응시가 이루어진 이후 Click 여부가 결정되었다. 하지만 평균 Scan path 는 타이틀과 내용의 구분 없이 전체 화면 길이/너비의 50%를 넘지 못하여 축소된 Golden Triangle 형태를 보였다. 본 연구 결과는 웹 검색 결과에 대한 사용자 소비 경향의 특성을 파악하여 향후 좀 더 효율적인 소비를 이끌어내기 위한 인터페이스 설계 방향의 기초 연구로 그 의의가 있다.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.3
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• pp.42-51
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• 1999

An experimental modeling of cutting and structural dynamics and the on-line detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics of cutting process but also for the analytic realization of diagnostic systems. In this regard, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision round shape machining such as turning, drilling and boring in mold and die making. In this study, simulation and experimental work were performed to show the malfunctioned behaviors. For this purpose, two new recursive approach (REIVM, RLSM) were adopted fur the on-line system identification and monitoring of a machining process, we can apply these new algorithm in real process for the detection of abnormal machining behaviors such as chipping, chatter, wear and round shape lobe waviness.

• Journal of Power System Engineering
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• v.3 no.2
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• pp.34-41
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• 1999

This paper identifies a linear combustion model of Refuse Incineration Plant(RIP) which characterizes its combustion dynamics, where the proposed model has thirteen-inputs and one-output. The structure of the RIP model is given as an ARX model which obtained from the theoretical analysis. And then, some unknown model parameters are decided from experimental input-output data sets, using system identification algorithm based on Instrumental Variables(IV) method. In result, it is shown that the proposed model well approximates the input-output combustion characteristics riven by experimental data sets.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.827-832
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• 2002

We propose a prediction method of the pollutant and a synchronous classification of the current state of SOx emission in the power plant. We use the auto-regressive with exogeneous (ARX) model as a predictor of SOx emission and use a radial basis function network (RBFN) as a pattem classifier. The ARX modeling scheme is implemented using recursive least squares (RLS) method to update the model parameters adaptively. The capability of SOx emission monitoring is utilized with the application of the RBFN classifier. Experimental results show that the ARX model can predict the SOx emission concentration well and ARX modeling parameters can be a good feature for the state monitoring. in addition, its validity has been verified through the power spectrum analysis. Consequently, the RBFN classifier in combination with ARX model is shown to be quite adequate for monitoring the state of SOx emission.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.2 no.2
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• pp.60-66
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• 2003

For the estimation of chatter lobe boundary it is very important to calculate the natural mode of cutting process. There are many time series algorithms for getting the natural mode of structural endmilling dynamics considering the cutting process. In this study, we have compared several time series methods such as AR algorithm, ARX, ARMAX, ARMA, Box Jenkins, Output Error, Recursive ARX, Recursive ARMAX considering the sampling frequency. As a results, the ARX, ARMAX and IV 4 are more desirable algorithms for the calculation of modal parameters such as natural frequency and damping ratio In endmilling operation. Also these algorithms may be adopted for the natural mode estimation of endmilling operation for chatter lobe prediction.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2008.05a
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• pp.199-202
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• 2008

The purpose of this study is to obtain the fundamental fire resistance performance of engineered cementitious composites(ECC) under fire temperature in order to use the fire protection material in high-strength concrete structures. The present study conducted the experiment to simulate fire temperature by employing of ECC and investigated experimentally the explosion and cracks in heated surface of these ECC. In the experimental studies, 3 HSC specimens are being exposed to fire, in order to examine the influence of various parameters(such as depth of layer=20, 30, 40mm; construction method=lining type) on the fire performance of HSC structures. Employed temperature curve were ISO 834 criterion(3hr), which are severe in various criterion of fire temperature in building structures. The numerical regressive analysis and proposed equation to calculate ambient temperature distribution is carried out and verified against the experimental data. By the use of proposed equation, the HSC members subjected to fire loads were designed and discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.985-988
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• 2002

The Spindle-]fearing System is very important unit for geometrical accuracy in machine tools. To improve effectively the weak point of spindle system, it is necessary that the contribution ratio of spindle core parts to static and dynamic stiffness is clarified. In this paper, static contribution ratio of core parts is calculated by overlapping static deformation of basic spindle design with one flexible parts. The dynamic contribution ratio for natural frequency and dynamic deformation at spindle end is obtained by calculating correlation between original and basic spindle deformation, by curve fitting with regressive method. It is proved the validity of estimation result is correct.

• Science of Emotion and Sensibility
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• v.1 no.1
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• pp.93-103
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• 1998

In this paper, we present change of human sensiblity when the 26 healthy female subjects were exposed with visual picture stimulus. We used Intermational Affective Picture System as the visual stimulus. The methods are AutoRegressive(AR) spectrum which is a linear method and Return Map which is a nonlinear mithod. SR spectrum may variability(HRV). The LF/HF of HRV and the variation of Return Map were analyzed from ECG signal of the female subjects. Return Map of RR intervals were analyzed by computiong the variation. When the subjets were stimulated by the pleasant pictures, LF/HF and variation were decreased compared with unpleasant stimulus, We may obtain good parameters for the measurement of the change of human sensibility for the visual picture stimulus.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.04a
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• pp.119-126
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• 1996

In this paper, a method of substructural identification is presented for the estimation of localized structural parameters. for this purpose, an auto-regressive and moving average with stochastic input (ARMAX) model is derived for the substructure to process the measurement data impaired by noises. The sequential prediction error method is used fer the estimation of unknown localized parameters. Using the substructural method, the number of unknown parameters can be reduced and the convergence and accuracy of estimation can be improved. For some substructures, the effect of the input excitation is expressed in terms of the responses at the inferences with the main structure, and substructural identification may be carried out without measuring the actual input excitation to the whole structure. Example analysis is carried out for idealized structural models of a multistory building and a truss bridge. The results indicate that the present method is effective and efficient for local damage estimation of complex structures.