• The Journal of Information Systems
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• v.8 no.1
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• pp.27-44
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• 1999

Case-Based Reasoning(CBR) offers a new approach for developing knowledge based systems. CBR has several research issues which can be divided into two categories : (1) static issues and (2) dynamic issues. The static issues are related to case representation scheme and case data model, that is, focus on casebase which is a repository of cases. The dynamic issues, on the other hand, are related to case retrieval procedure and problem solving process, i.e. case adaptation phase. This research is forcused on retrieval procedure Traditional query processing accepts precisely specified queries and only provides exact answers, thus requiring users to fully understand the problem domain and the casebase schema, but returning limited or even null information if the exact answer is not available. To remedy such a restriction, extending the classical notion of query answering to approximate query answering(AQA) has been explored. AQA can be achieved by neighborhood query answering or associative query answering. In this paper, neighborhood query answering technique is used for AQA. To reinforce the CBR process, a new retrieval procedure(cooperative CBR) using neighborhood query answering is proposed. An neighborhood query answering relaxes a query scope to enlarge the search range, or relaxes an answer scope to include additional information. Computer Aided Process Planning(CAPP) is selected as cooperative CBR application domain for test. CAPP is an essential key for achieving CIM. It is the bridge between CAD and CAM and translates the design information into manufacturing instructions. As a result of the test, it is approved that the problem solving ability of cooperative CBR is improved by relaxation technique.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.291-299
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• 2016

This paper discusses how to establish estimable functions when there are fixed and random effects in design models. It proves that estimable functions of mixed models are not related to random effects. A fitting constants method is used to obtain sums of squares due to random effects and Hartley's synthesis is used to calculate coefficients of variance components. To test about the fixed effects the degrees of freedom associated with divisor are determined by means of the Satterthwaite approximation.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.123-125
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• 2023

As deep learning has become an essential part of human lives, the requirement for Deep Learning as a Service (DLaaS) is growing. Since using remote cloud servers induces privacy concerns for users, a Fully Homomorphic Encryption (FHE) arises to protect users' sensitive data from a malicious attack in the cloud environment. However, the FHE cannot support several computations, including the most popular activation function, Rectified Linear Unit (ReLU). This paper analyzes several polynomial approximation methods for ReLU to utilize FHE in DLaaS.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.343-350
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• 2000

In this paper, we propose the Multi-FPNN(Fuzzy Polynomial Neural Networks) model based on FNN and PNN(Polyomial Neural Networks) for optimal system identifacation. Here FNN structure is designed using fuzzy input space divided by each separated input variable, and urilized both in order to get better output performace. Each node of PNN structure based on GMDH(Group Method of Data handing) method uses two types of high-order polynomials such as linearane and quadratic, and the input of that node uses three kinds of multi-variable inputs such as linear and quadratic, and the input of that node and Genetic Algorithms(GAs) to identify both the structure and the prepocessing of parameters of a Multi-FPNN model. Here, HCM clustering method, which is carried out for data preproessing of process system, is utilized to determine the structure method, which is carried out for data preprocessing of process system, is utilized to determance index with a weighting factor is used to according to the divisions of input-output space. A aggregate performance inddex with a wegihting factor is used to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of this aggregate abjective function which it is acailable and effective to design to design and optimal Multi-FPNN model. The study is illustrated with the aid of two representative numerical examples and the aggregate performance index related to the approximation and generalization abilities of the model is evaluated and discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.785-789
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• 2006

유역 수자원의 효율적인 관리 및 배분을 위해서는 세밀한 강우-유출관계의 규명이 무엇보다 중요하다. 이를 위해서는 먼저 하천 유출지점의 정확한 유량정보가 획득되어야 하며, 장기간에 걸쳐 신뢰성 있는 유량자료의 확보는 더욱 중요한 사항이다. 본 연구에서는 하천에서 관측된 유량자료를 장기간(1983년${\sim}$2004년)에 걸친 유출성분으로 분리하는 기법을 활용하여 제어지점의 유출량을 검증하였다. 유량자료를 출구지점의 관측유량$(Q_{ob})$을 회귀수$({\alpha}Q_e)$, 상류유입량$(Q_{up})$ 및 관측강우-유출량$({\beta}Q_{Rain})$의 성분으로 구분하여 산정하는 방식으로 유출량을 추정하였다. 여기서, 회귀수$({\alpha}Q_e)$란 유역 및 하도내 용수이용량의 회귀수, 상류유입량$(Q_{up})$은 상류 유출 제어지점의 관측유량으로 대청댐 방류량, 관측강우-유출량$({\beta}Q_{Rain})$은 유역내 강우에 의한 자연유출량이다. 여기서 사용된 수문기초자료는 대청댐 방류량, 대전 및 청주권 취수량, 강우에 의한 자연유출량, 공주관측유량 등으로 각 성분별로 생성된 일자료를 이용하여 공주지점의 월별, 분기별, 년도별 유출량을 산정하였다. 이 결과는 금강유역에 이미 구축되어있는 SSARR모형을 기반으로 한 RRFS(Rainfall Runoff Forecasting System, 유출예측 시스템)의 결과 및 관측치와 비교되었다. 계산결과 RRFS에 의한 유출량과 대청-공주구간의 유출성분분리에 의한 유출량은 관측값과 전반적으로 근사함을 확인하였으며, 검증지점의 정확한 유출율을 산정할 수 있다면, 관측자료의 연속성 및 신뢰도를 파악하는 척도를 제공할 수 있을 것으로 판단된다.측결과 있는 대상유역에 대한 적용이 요구된다.-Moment 방법에 의해 추정된 매개변수를 사용한 Power 분포를 적용하였으며 이들 분포의 적합도를 PPCC Test를 사용하여 평가해봄으로써 낙동강 유역에서의 저수시의 유출량 추정에 대한 Power 분포의 적용성을 판단해 보았다. 뿐만 아니라 이와 관련된 수문요소기술을 확보할 수 있을 것이다.역의 물순환 과정을 보다 명확히 규명하고자 노력하였다.으로 추정되었다.면으로의 월류량을 산정하고 유입된 지표유량에 대해서 배수시스템에서의 흐름해석을 수행하였다. 그리고, 침수해석을 위해서는 2차원 침수해석을 위한 DEM기반 침수해석모형을 개발하였고, 건물의 영향을 고려할 수 있도록 구성하였다. 본 연구결과 지표류 유출 해석의 물리적 특성을 잘 반영하며, 도시지역의 복잡한 배수시스템 해석모형과 지표범람 모형을 통합한 모형 개발로 인해 더욱 정교한 도시지역에서의 홍수 범람 해석을 실시할 수 있을 것으로 판단된다. 본 모형의 개발로 침수상황의 시간별 진행과정을 분석함으로써 도시홍수에 대한 침수위험 지점 파악 및 주민대피지도 구축 등에 활용될 수 있을 것으로 판단된다. 있을 것으로 판단되었다.4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전략을 개발 및 활용할 수 있으며, 특히, 한국주식시장에 적합한 거래전략은 반전거래전략이고, 이 전략의 유용성은 투자자가 설정한 투자기간보다 더욱 긴

• Korean Journal of Cognitive Science
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• v.17 no.4
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• pp.303-321
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• 2006

According to Harris'(1966) distributional hypothesis, understanding the meaning of a word is thought to be dependent on its context. Under this hypothesis about human language ability, this paper proposes a computational model for native speaker's language processing mechanism concerning word sense disambiguation, based on two sets of experiments. Among the three computational models discussed in this paper, namely, the logic model, the probabilistic model, and the probabilistic inference model, the experiment shows that the logic model is first applied fer semantic disambiguation of the key word. Nexr, if the logic model fails to apply, then the probabilistic model becomes most relevant. The three models were also compared with the test results in terms of Pearson correlation coefficient value. It turns out that the logic model best explains the human decision behaviour on the ambiguous words, and the probabilistic inference model tomes next. The experiment consists of two pans; one involves 30 sentences extracted from 1 million graphic-word corpus, and the result shows the agreement rate anong native speakers is at 98% in terms of word sense disambiguation. The other pm of the experiment, which was designed to exclude the logic model effect, is composed of 50 cleft sentences.

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.805-812
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• 2003

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. The parametric inferences of the model using Logarithmic Poisson model, Crow model and Rayleigh model is discussed. Bayesian computation and model selection using the sum of squared errors. The numerical results of this models are applied to real software failure data. Tools of parameter inference was used method of Gibbs sampling and Metropolis algorithm. The numerical example by T1 data (Musa) was illustrated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.2
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• pp.83-90
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• 1989

A runoff model was estabilished for the direct runoff hydrograph at each subareas by obtaining the storage coefficient based on stream magnitudes of geomorphic parameters. For this, the relationship between flowsection and channel distance from the outlet of each subareas was assumed as nonlinear equation, and compared with linear one. The applicability of the runoff model to the real watershed was tested for the Bochung river basin. The results of the analysis show that the model was approved to be used for the prediction of small watershed having no runoff records and a linear equation between flowsection and channel distance from the outlet of each subareas was more similar to the observed data for the upper subarea with a steep slope and small area, on the other hand, nonlinear equation for the lower subarea with mild slope and relatively large area.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.1182-1189
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• 1994

In this paper, we evaluate the performance of a fuzzy controller with a self-learning structure. The fuzzy controller is based on a fuzzy logic that approximates and effectively represents the uncertain phenomena of the real world. The fuzzy controller has control of a plant with a fuzzy inference logic. However, it is not easy to decide the membership function of a fuzzy controller and its controlrule. This problem can be solved by designing a self-learning controller that improves its own contropllaw to its goal with a performance table. The fuzzy controller is implemented with a 386PC, an interface board, a D/A converter, a PWM(Pulse Width Modulation) motor drive-circuit, and a sensing circuit, for error and differential of error. Since a Ball and Beam System is used in the experiment, the validity of the fuzzy controller with the self-learning structure can be evaluated through the actual experiment and the computer simulation of the real plant. The self-learning fuzzy controller reduces settling time by just under 10%.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.2
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• pp.1-7
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• 2010

This paper presents empirical equations indicating the high frequency performance characteristics of air-cored induction coil sensors with their constructional parameters. An air-cored induction coil sensor is widely used due to good linearity at low frequency ranges but the sensor has weakness of relatively low sensitivity to the magnetic field. At high frequency ranges, the sensitivity can be dramatically increased, largely depending on the frequency of the injected field, and this property can be a great asset to some electromagnetic inspections, since they utilize the interrogating current with a fixed frequency. The application of this property of the coil sensor requires the estimation of its high frequency performance. We made experiments on the frequency responses of the coil sensors under diverse constructional conditions and, on the basis of the experimental results, the high frequency performance, such as the resonant frequency and the sensitivity at the frequency, was estimated, as a function of the constructional parameters of the coil sensor. The good agreements between experimental and estimated data were reported.