• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.2
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• pp.98-103
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• 2002

In case of power demand forecasting, the most important problems are to deal with the load of special-days. Accordingly, this paper presents the method that forecasting long (the Lunar New Year, the Full Moon Festival) and short(the Planting Trees Day, the Memorial Day, etc) special-days peak load using neural networks and regression models. long and short special-days peak load forecast by neural networks models uses pattern conversion ratio and four-order orthogonal polynomials regression models. There are using that special-days peak load data during ten years(1985∼1994). In the result of special-days peak load forecasting, forecasting % error shows good results as about 1 ∼2[%] both neural networks models and four-order orthogonal polynomials regression models. Besides, from the result of analysis of adjusted coefficient of determination and F-test, the significance of the are convinced four-order orthogonal polynomials regression models. When the neural networks models are compared with the four-order orthogonal polynomials regression models at a view of the results of special-days peak load forecasting, the neural networks models which uses pattern conversion ratio are more effective on forecasting long special-days peak load. On the other hand, in case of forecasting short special-days peak load, both are valid.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.73-78
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• 2001

BP neural network model and multiple-regression model were composed for forecasting the special-days load. Special-days load was forecasted using that neural network model made use of pattern conversion ratio and multiple-regression made use of weekday-change ratio. This methods identified the suitable as that special-days load of short and long term was forecasted with the weekly average percentage error of 1∼2[%] in the weekly peak load forecasting model using pattern conversion ratio. But this methods were hard with special-days load forecasting of summertime. therefore it was forecasted with the multiple-regression models. This models were used to the weekday-change ratio, and the temperature-humidity and discomfort-index as explanatory variable. This methods identified the suitable as that compared forecasting result of weekday load with forecasting result of special-days load because months average percentage error was alike. And, the fit of the presented forecast models using statistical tests had been proved. Big difficult problem of peak load forecasting had been solved that because identified the fit of the methods of special-days load forecasting in the paper presented.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.53-59
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• 2004

In case of load forcasting the most important problem is to deal with the load of special days. According this paper presents forecasting method for speaial days peak load by neural networks model. by means of neural networks mothod using the historical past special- days load data, special-days load was directly forecasted, and forecasting % error showed good result as 1∼2% except vacation season in summer Consequently, it is capable of directly special days load, With the models, precision of forecasting was brought satisfactory result. When neural networks was compared with the orthogonal polynomials models at a view of the results of special-days load forecasting, neural networks model which used pattern conversion ratio was more effective on forecasting for special-days load. On the other hand, in case of short special-days load forecasting, both were valid.

• Korean Journal of Cognitive Science
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• v.21 no.2
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• pp.359-386
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• 2010

In order to evaluate the domain-specific model and process-specific model of spatial and nonspatial working memory (WM), this study manipulated the memory load of the delayed response task and examined how the neural correlates of memory load effect was influenced by the stimulus domain (face and location) at the maintenance stage of WM using an event-related fMRI experiment. One or three face stimuli were presented as target stimuli and participants were asked to maintain the face itself (face WM) or the location of face stimuli (spatial WM). The results of recognition judgment accuracy showed no difference between face WM and spatial WM, and showed equivalent memory load effects of both WM. As a result of brian image analysis, memory load effect at maintenance stage showed that inferior, middle, and superior PFC were recruited by both face WM and spatial WM, and showed that VLPFC was the commonly activated area by both WM, supporting functional specialization of PFC by process components of WM. This study provides evidence for process-specific model in which maintenance of WM is associated with VLPFC.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.361-364
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• 2005

본 논문에서는 순서 통계량을 이용한 유한 고장 NHPP 모형들이 제안되었다. 이 모형들은 결함당 고장발생률이 단조 증가하거나 단조 감소하는 패턴을 가진다. 그리고 수명 분포에서는 기존의 모형들과 비교하고 kappa(2) 분포를 이용한 소프트웨어 신뢰성 모형을 제안하여 이 모형의 특성과 효율성에 대하여 제시하였다. 고장 간격 시간 자료를 이용한 무한고장 NHPP 모형들에 대한 모수 추정은 최우 추정법을 사용하였고 적용 분포들의 적용을 용이하게 하기 위하여 특수한 형태를 제시하였다. 실제고장 자료를 이용한 자료분석에서는 편차자승합을 이용한 모형 선택과 적합도 및 치우침 검정을 실시하여 그 결과를 나열 하였다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.3
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• pp.29-50
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• 2020

The purpose of this study is to analyze the characteristics of the media contained in textbooks for students with disabilities based on the information processing model, and to find ways to utilize library materials for class improvement for them. To this end, the media included in the in-depth learning activities of the Korean language textbooks of the 2015 revised special education basic curriculum were analyzed. As a result of the analysis, it was found that students with disabilities received information mainly through vision, process information through understanding, and use language intelligence to produce results. Specifically, they accepts learning contents through illustrations and texts, processes the contents based on understanding such as reasoning and explanation, and then uses linguistic intelligence such as writing and speaking to produce results. Based on the results of this analysis, a practical method to utilize library materials in the Korean language class of students with disabilities was proposed as follows. Developing a variety of input mediums based on reading stages and collection mapping for students with disabilities. Providing book materials through reading and listening. Teaching appropriate methodological knowledge to self-directly solve advanced learning activities. In addition, developing types of writing and writing strategies that can help various production activities.

• Tribology and Lubricants
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• v.12 no.1
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• pp.1-5
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• 1996

자성유체는 자연에서 추출한 것이 아니라 자화성(Magnetizability)과 유도성(Flowability)을 동시에 갖도록 합성한 특수액체이다. 자성유체는 1960년대 중반에 미국의 NASA에서 처음 개발된 이후로 윤활, 밀봉, 감쇄, 의료 등의 분야에서 응용연구가 많이 진행되었기 때문에 고도의 정밀도를 요하는 항공, 우주산업, 컴퓨터와 반도체 분야 등에서 실용화가 크게 진전되고 있다. 특수물질일 자성유체는 전기적으로 도체인 10nm 정도의 미세한 자기입자(Magnetic particles)에 코팅을 한 후, 이것을 물, 탄화수소, 플루오르카본, 에스터 등의 매개유체(Carrier Fluids)에 혼합시켜서 콜로이드 상태로 사용하게 된다. 자성유체는 미세한 자기입자들이 매개유체내에서 서로 충돌하면서 반발력을 발생시켜서 상호간에 늘 콜로이드 상태를 유지하고 있으며, 이 특수유체가 자기장의 영향을 받게 되면 점도가 증가하면서 특이한 성질을 갖게 된다. 상대 접촉 운동면에 경계마찰이나 혼합마찰을 하게 되면 윤활상태는 비교적 나쁘다. 이러한 마찰지역에 콜로이드상의 자성유체 윤활제를 공급하면 기존의 윤활제에 비하여 대단히 효과적으로 윤활을 할 수 있게 된다. 그러나 자성유체 윤활제가 마찰부위에 원활하게 공급하기 위해서는 미끄럼 마찰부에서 자기장을 잘 형성시킬 수 있는 도체이어야 하기 때문에 특별한 윤활 시스템 설계가 제시되어야 한다. 자성유체 윤활제는 합성으로 제조된 특수물질로 여러가지 장점을 갖고는 있으나 기존 윤활유와의 적합성, 마찰열, 밀봉압력 등의 조건에서 제한적으로 사용될 수 밖에 없으므로 항공, 우주 산업이나 석유 화학분야와 같이 특수 환경에서만 사용되고, 또한 기존의 광유계 윤활제에 비하여 대단히 고가하는 문제점을 갖고 있다. 그러나 윤활 마찰면의 다양화와 가혹한 사용조건은 자성유체 윤활제의 연구개발 필요성을 크게 증대시키고 있다.xed Effects Model)을 결정하고, 각각에 해당하는 통계모형을 구축하였다. 이 결과 (1) 업종 및 기업규모별로 그룹간에 유의한 특성이 발견되었으며, (2) R&D 및 광고투자는 기업의 시장성과를 설명하는 중요한 변수이나, (3) R&D 투자의 경우는 광고에 비해 불확실성이 존재하는 것으로 나타났고, (4) 수리모형에서 도출된 한계원리가 통계모형에서도 유효한 것으로 드러났다.등을 토대로 한 10대 산업을 육성하기 위하여 과학기술부는 기술수요조사를 바탕으로 49개 주요기술을 도출하여, 과학기술 일류 국가 실현, 국민소득 2만불 달성이라는 국가적 슬로건을 내걸고 “차세대 성장동력” 창출을 위한 범정부차원의 기획과 연구비의 집중투자를 추진하고 있다.달성하기 위해서는 종합류류 전산망의 시급한 구축과 함께 화물차의 적재율을 높이고 공차율을 낮출 수 있는 운송체계의 수립이 필요한 것으로 판단된다. 그라나 이러한 화물전용차선의 효과는 단기적인 치유책일 수밖에 없기 때문에 물류유통 시설의 확충을 위한 사회간접자본의 구축을 서둘러 시행하여야 할 것이다.으로 처리한 Machine oil, Phenthoate EC 및 Trichlorfon WP는 비교적 약효가 낮았다.>$^{\circ}$E/$\leq$30$^{\circ}$NW 단열군이 연구지역 내에서 지하수 유동성이 가장 높은 단열군으로 추정된다. 이러한 사실은 3개 시추공을 대상으로 실시한 시추공 내 물리검층과 정압주입시험에서도 확인된다.. It was resulted from increase of weight of single cocoon. "Manta"2.5ppm produced 22.2kg of cocoon. It is equal to 9% increase in index, as compared to that of control. In case

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.393-400
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• 2001

This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP). The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with generalized model by Goel dependent on the constant reflecting the quality of testing. The performance measures and parametric inferences of the new models, Rayleigh and Gumbel distributions, are discussed. The results of the new models are applied to real software failure data and compared with Goel-Okumoto and Yamada, Ohba and Osaki models. Tools of parameter inference was used method of the maximun likelihood estimate and the bisection algorithm for the computing nonlinear root. In this paper, using the sum of the squared errors, model selection was employed. The numerical example by NTDS data was illustrated.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.389-398
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• 2002

Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process(NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with several model on the constant reflecting the quality of testing. The performance measures and parametric inferences of the suggested models using Rayleigh distribution and Laplace distribution are discussed. The results of the suggested models are applied to real software failure data and compared with Goel model. Tools of parameter point inference and 95% credible intereval was used method of Gibbs sampling. In this paper, model selection using the sum of the squared errors was employed. The numerical example by NTDS data was illustrated.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.401-404
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• 2003

현재 특수교육이나 작업치료에서 사용되고있는 시지각 발달검사 도구들은 종이에 인쇄된 형식으로 지필식 방법을 사용한다 검사과정에 치료사나 심리상담사들의 개별적인 설명 및 지도가 필요하며, 시지각의 반응시간과 공간 지각능력 등의 정확한 측정이 어렵고, 검사결과에 대한 분석 또한 수작업으로 이루어지고 있어 한계성의 문제가 제기된다. 본 논문은 웹 기반 시지각 진단 프로그램의 개발을 위해 먼저, 시지각 진단프로그램 모형 구성을 위한 제 요소 및 신뢰도의 타당성을 입증하기 위한 변인들을 추출하고자 한다. 이를 통해 시지각 진단 분석결과의 컴퓨터 처리 및 데이터 축적을 통한 업무 자동화의 효과와 시지각 진단 평가의 한국형 표준화 작업을 기대할 수 있다.