• 대한기계학회논문집A
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• 제29권7호
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• pp.1013-1021
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• 2005

In this paper, we developed an automatic design optimization system for parametric shape optimization of cooling passages inside axial turbine blades. A parallel three-dimensional thermoelasticity finite element analysis code from an open source system was used to perform automatic thermal and stress analysis of different blade configuration. The developed code was connected to an evolutionary optimizer and built in a design optimization system. Using the optimization system, 279 feasible and optimal solutions were searched. It is provided not only one best solution of the searched solutions, but also information of variation structure and correlation of the 279 solutions in function, variable, and real design spaces. To explore design information, it is proposed a new interpretation approach based on evolutionary clustering and principal component analysis. The interpretation approach might be applicable to the increasing demands in the general area of design optimization.

• 통상정보연구
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• 제10권2호
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• pp.455-471
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• 2008

The current research utilized as its target population who are current employees of innovative manufacturing enterprise medium to large-sized companies in Korea. The research validated the innovative dimensions by studying the two constructs within the context of the innovative manufacturing enterprise user population. Correlation was found between innovative dimensions retained as components of a Comprehensive Model. It was determined that these four dimensions-Content, Intrinsic Interest, Control, and Timeliness-are significant predictors of user success. The Comprehensive Model was validated, and it is therefore suggested as a basis for further study of user success indicators in the innovative manufacturing enterprise environment.

• 산업경영시스템학회지
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• 제29권1호
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• pp.26-33
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• 2006

The potential needs as well as visible needs of customer should be considered in order to research and analyze of the customer data. The methods to analyze customer data is classified into customer segmentation, clustering analysis model, forecasting customer response probability model, analysis of the customer break rate model and new customer analysis model by the purpose. In this study, we developed the CW-CLV (Correlation Weight Customer Lifetime Value)method that used AHP(Analytic Hierarchy Process)rule for enhance the reliability of customer data and quantitative analysis of the customer segmentation, based on CLV(Customer Lifetime Value). We suggest to new variables and methodology from determined CW-CLV coefficients, because all of companies respect to the diversified customers classification and complexity of consumers needs. Finally, we unfolded any company's scheduling added new methodology using simulation and leaded conclusion about the new methodology.

• 천문학회보
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• 제41권1호
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• pp.39.1-39.1
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• 2016

The cosmic distance can be precisely determined using a 'standard ruler' imprinted by primordial baryon acoustic oscillation (hereafter BAO) in the early Universe. The BAO at the targeted epoch is observed by analyzing galaxy clustering in redshift space (hereafter RSD) of which theoretical formulation is not yet fully understood, and thus makes this methodology unsatisfactory. The BAO analysis through full RSD modeling is contaminated by the systematic uncertainty due to a non--linear smearing effect such as non-linear corrections and uncertainty caused by random viral velocity of galaxies. However, BAO can be probed independently of RSD contamination using the BAO peak positions located in the 2D anisotropic correlation function. A new methodology is presented to measure peak positions, to test whether it is also contaminated by the same systematics in RSD, and to provide the radial and transverse cosmic distances determined by the 2D BAO peak positions. We find that in our model independent anisotropic clustering analysis we can obtain about 2% and 5% constraints on $D_A$ and $H^{-1}$ respectively with current BOSS data which is competitive with other analysis.

• Structural Monitoring and Maintenance
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• 제2권4호
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• pp.339-355
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• 2015

Corrosion of prestressed concrete structures is one of the main challenges that engineers face today. In response to this national need, this paper presents the results of a long-term project that aims at developing a structural health monitoring (SHM) technology for the nondestructive evaluation of prestressed structures. In this paper, the use of permanently installed low profile piezoelectric transducers (PZT) is proposed in order to record the acoustic emissions (AE) along the length of the strand. The results of an accelerated corrosion test are presented and k-means clustering is applied via principal component analysis (PCA) of AE features to provide an accurate diagnosis of the strand health. The proposed approach shows good correlation between acoustic emissions features and strand failure. Moreover, a clustering technique for the identification of false alarms is proposed.

• International Journal of Internet, Broadcasting and Communication
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• 제7권1호
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• pp.23-29
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• 2015

Energy constraints of wireless sensor networks are an important challenge. Data Transmission requires energy. Distance between origin and destination has an important role in energy consumption. In addition, the location of base station has a large impact on energy consumption and a specific method not proposed for it. In addition, a obtain model for location of base station proposed. Also a model for distributed clustering is presented by cluster heads. Eventually, a combination of discussed ideas is proposed to improve the energy consumption. The proposed ideas have been implemented over the LEACH-C protocol. Evaluation results show that the proposed methods have a better performance in energy consumption and lifetime of the network in comparison with similar methods.

• 한국IT서비스학회지
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• 제7권4호
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• pp.199-208
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• 2008

Tagging represents one of the Web 2.0 technology, and has an appropriate mechanism for the classification of dynamically changing Web informations. This technique is capable of searching the Web informations using the user specified tags, but still it has a limitation of providing only the limited informations to the tags. Therefore, in order to search the related informations easily, we need to extend this technique further to search not only the desired informations through the designated tags and also the related informations. In this paper, we first have designed and developed an algorithm that can get a desired tag cluster, which is capable of collecting the searched tags along with the related tags. We first performed a test to compare the difference between the user collected tag data through RSS and the reduced data. The second test focused on the accuracy of extracted related tags that depends on the similarity functions, such as the Pearson Correlation and Euclidean. Finally, we showed the final results visually using the graph algorithm.

• 디지털융복합연구
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• 제17권3호
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• pp.221-226
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• 2019

뇌파 파형중 베타파를 이용한 인간의 인지상태를 판별한다. 베타파는 인간의 인지상태중 스트레스 영역에 해당하는 특성이 있고, 이 영역에서 스트레스의 오버대역폭을 추출하기 위해서 저대역폭과 고대역폭 사이의 베타파간 상관관계를 분석해야 한다. 그러므로 본 논문에서는 효과적으로 베타파 상관관계를 분석하고 추출하기 위해 비지도학습 머신러닝을 이용한 Kmean 클러스터링 분석모델을 제시한다. 제시된 모델은 베타파 영역을 유사한 영역의 클러스터 군으로 분류하고 해당 클러스터링 범주에서 이상파형을 판별한다. 이상파형 판별을 위해 클러스터군의 밀집도와 정상범주 이탈영역을 기준으로 스트레스 위험군을 판별하고 판별된 스트레스 위험군에 대한 대처방안을 제공할 수 있다. 제시된 모델을 활용하면 뇌파파형을 통한 인지상태의 스트레스 지수분별이 가능하고, 개인의 인지상태에 대한 관리 및 응용이 가능하다. 또한 스트레스와 오피스증후군을 갖는 사람들에게 뇌파관리를 통해 개인의 삶에 대한 질적 향상에 도움을 준다.

• 천문학회보
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• 제44권1호
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• pp.78.2-78.2
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• 2019

We develop an Alcock-Paczynski (AP) test method that uses the evolution of redshift-space two-point correlation function (2pCF) of galaxies. The method improves the AP test proposed by Li et al. (2015) in that it uses the full two-dimensional shape of the correlation function. Similarly to the original method, the new one uses the 2pCF in redshift space with its amplitude normalized. Cosmological constraints can be obtained by examining the redshift dependence of the normalized 2pCF. This is because the 2pCF should not change apart from the expected small non-linear evolution if galaxy clustering is not distorted by incorrect choice of cosmology used to convert redshift to comoving distance. Our new method decomposes the redshift difference of the 2-dimensional correlation function into the Legendre polynomials whose amplitudes are modelled by radial fitting functions. The shape of the normalized 2pCF suffers from small intrinsic time evolution due to non-linear gravitational evolution and change of type of galaxies between different redshifts. It can be accurately measured by using state of the art cosmological simulations. We use a set of our Multiverse simulations to find that the systematic effects on the shape of the normalized 2pCF are quite insensitive to change of cosmology over \Omega_m=0.21 - 0.31 and w=-0.5 - -1.5. Thanks to this finding, we can now apply our method for the AP test using the non-linear systematics measured from a single simulation of the fiducial cosmological model.

• 인터넷정보학회논문지
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• 제25권2호
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• pp.39-47
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• 2024

시계열 분석은 시간 순서로 정렬된 데이터로부터 다양한 정보와 인사이트를 발견하기 위한 방법으로 많은 조직에서 비즈니스 문제 해결을 위해 적용하고 있다. 그중에서 시계열 유사도 측정은 패턴이 비슷한 시계열들을 식별하기 위한 단계로서 시계열 검색 및 군집화와 같은 시계열 분석 응용에서 매우 중요하다. 본 연구에서는 전체 시계열이 아닌 이상치들을 중심으로 시계열 유사도 측정을 계산 효율적으로 수행하는 방법을 제안한다. 이와 관련하여 이상탐지를 통해 추출된 서브시퀀스 집합에 대한 유사도 측정 결과와 시계열 전체에 대한 유사도 측정 결과 사이의 순위 상관관계를 측정 및 분석하여 제안 방법을 검증한다. 실험 결과로써, 주식 종목 시계열 데이터에 이상치 비율 10% 을 적용한 유사도 측정으로부터 최대 0.9 이상의 스피어만 순위 상관계수를 확인하였다. 결론적으로 제안 방법을 통해 시계열 유사도 측정에 소요되는 계산량을 유의미하게 절감하는 동시에 신뢰 가능한 시계열 검색 및 군집화 결과를 기대할 수 있다.