• 한국자동차공학회논문집
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• 제12권6호
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• pp.119-126
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• 2004

In order to elucidate the modes of double-droplet combustion speed in premixed spray flame, the difference between flame propagation speed and droplet cluster disappearance speed are experimentally investigated using a premixed spray burner system, It was confirmed that flame speed concerned with premixed-mode combustion in the spray flame was approximately 2.0 m/s in average while mean disappearance speed of droplet clusters, which were dominated by diffusion-mode combustion in downstream of the flame, was evaluated as much as 0.45 m/s. It was clarified that both characteristics of premixed-mode and diffusion-mode combustion in spray flames are of much difference in nature, even though both speed, which are supposed to depend on local properties of the spray itself and flow conditions surrounding droplet clusters, are scattered in experiments.

• 반도체디스플레이기술학회지
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• 제10권2호
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• pp.45-48
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• 2011

In this paper, vacancy clustering formation and diffusion of germanium substrate was studied. The analysis method was adopted Monte Carlo method. At temperatures higher than melting point, fewer clusters formed, but there was less variation in the number of clusters than at lower temperatures, as the time increased. Equilibrium diffusivities in the clustering region were $10^2$ lower than those of free vacancies in the initial stage of kinetic lattice Monte Carlo simulations. They were expressed according to three temperature regimes: at temperatures above 1,100 K, at temperatures of 1,100-900 K, and at temperatures below 900 K. The effective mean migration energy, 1.1 eV, closely coincided with that of the 1.0-1.2 eV in experiments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2453-2455
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• 2003

We propose a path planning method to reduce the inspection time of AOI (automatic optical inspection) machines in SMT (surface mount technology) in-line system. Inspection windows of board should be clustered to consider the FOV (field-of-view) of camera. The number of clusters is desirable to be minimized in order to reduce the overall inspection time. We newly propose a genetic algorithm to minimize the number of clusters for a given board. Comparative simulation results are presented to verify the usefulness of proposed algorithm.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.292-298
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• 2011

In this study we examine Taiwan's overall performance in accordance with sustainable construction by developing an appraisal indicator framework. The framework consists of five layers, from bottom to top: the indicator; the indicator category; the core cluster; the theme; and the overall performance. The procedure for the development of a sustainable construction indicator system is outlined. Finally, a framework consists of 3 themes, 10 core clusters, and 33 indicator categories are established. Following the established framework, 67 proper indicators are selected for each category in the framework, and data of the 53 indicators are collected respectively from a nation's statistical databank in Taiwan. Sustainable construction index aggregated step-by-step from the indicators, the indicator categories, the core clusters and the themes is computed to assess Taiwan's progress in sustainable construction. The preliminary results and the discussion are reported.

• 전기학회논문지
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• 제59권5호
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• pp.981-989
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• 2010

In this study, we introduce a new architecture of fuzzy inference system. In the fuzzy inference system, we use Fuzzy C-Means clustering algorithm to form the premise part of the rules. The membership functions standing in the premise part of fuzzy rules do not assume any explicit functional forms, but for any input the resulting activation levels of such radial basis functions directly depend upon the distance between data points by means of the Fuzzy C-Means clustering. As the consequent part of fuzzy rules of the fuzzy inference system (being the local model representing input output relation in the corresponding sub-space), four types of polynomial are considered, namely constant, linear, quadratic and modified quadratic. This offers a significant level of design flexibility as each rule could come with a different type of the local model in its consequence. Either the Least Square Estimator (LSE) or the weighted Least Square Estimator (WLSE)-based learning is exploited to estimate the coefficients of the consequent polynomial of fuzzy rules. In fuzzy modeling, complexity and interpretability (or simplicity) as well as accuracy of the obtained model are essential design criteria. The performance of the fuzzy inference system is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules(clusters) and the order of polynomial in the consequent part of the rules. Accordingly we can obtain preferred model structure through an adjustment of such parameters of the fuzzy inference system. Moreover the comparative experimental study between WLSE and LSE is analyzed according to the change of the number of clusters(rules) as well as polynomial type. The superiority of the proposed model is illustrated and also demonstrated with the use of Automobile Miles per Gallon(MPG), Boston housing called Machine Learning dataset, and Mackey-glass time series dataset.

• 정보처리학회논문지A
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• 제11A권4호
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• pp.277-284
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• 2004

본 논문은 사용자로 하여금 계층적 가시화 기법에 의한 표정들의 공간으로부터 일련의 표정을 선택하게 함으로써 3차원 아바타의 표정 제어기법을 기술한다. 본 시스템에서는 2,40P0여개의 표정 프레임을 이용하여 2차원 표정공간을 구성하였으며, 3차원 아바타의 표정 제어는 사용자가 표정공간을 항해하면서 수행한다. 그러나 표정의 수가 너무 많아 사용자가 항해를 하는데 어려움이 많기 때문에 계층적 가시화 기법이 필요하다. 표정공간을 계층적으로 분할하기 위해, 퍼지 클러스터링을 이용한다. 초기 단계에서는 2,400여개의 표정들을 이용하여 약 11개의 클러스터센터를 가지도록 클러스터링한다. 클러스터 센터들은 2차원 평면에 표시되며 후보 키 프레임으로 사용된다 사용자는 후보 키 프레임들 중에서 특정 키 프레임들을 선택하여 초기 항해경로를 생성한다. 사용자가 줌 인(이산적인 단계를 가지고 있음)을 하면 상세한 단계를 보기를 원한다는 의미이므로 줌 인된 단계에 적합한 표정 클러스터들을 생성한다. 단계가 증가될 때 마다 클러스터의 수를 두 배로 하고, 클러스터의 수만큼 표정들을 클러스터링한다. 사용자는 현재 단계에서 그전 단계의 항해경로를 따라 새로운 키 프레임(클러스터 센터)들을 선택하여 항해경로를 갱신한다. 줌 인을 최대로 한 마지막 단계에서 항해경로를 갱신하면 표정 제어 설정이 끝난다. 사용자는 언제든지 줌 아웃을 통해 그 전단계로 돌아가서 항해경로를 수정할 수 있다. 본 논문은 본 시스템이 어떤 효과가 있는지를 알기 위해 사용자들로 하여금 본 시스템을 사용하여 3차원 아바타의 표정 제어를 수행하게 하였으며, 그 결과를 평가한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.34-36
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• 2006

In this paper, we will treat the diagnosis problem to accurately determine fault types. The judgement of fault types is accomplished by observing the cluster newly formed with faults and clustering the input current waveforms to intrinsically show the conditions with the dignet that is a clustering algorithm. The types of input current waveforms are, however, constrained during normal operation, though it considers the load character. In case of faults. new clusters are generated outside the clusters. which appear during normal operation, because the input current waveforms of the induction motor are generated by the type which is not observed in case of faults. The diagnosis about the types of faults is essential to building a fault tree about the induction motor, and it removes the causes of the faults using a fuzzy logic. We, first, constitute a fault tree, which connects with the parts and the entire system of the induction motor, and investigate fault modes which can be generated from the fault tree and the relationship of the cause and the effect of each part (of the motor). Also, we distinguish the faults of each part by means of inducing the said of fuzzy relation equations encapsulating the relationship of the fault modes and each part.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.164-169
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• 2003

In this paper, we propose the integrated Bayesian network framework to reconstruct genetic regulatory networks from genome expression data. The proposed model overcomes the dimensionality problem of multivariate analysis by building coherent sub-networks from confined gene clusters and combining these networks via intermediary points. Gene Shaving algorithm is used to cluster genes that share a common function or co-regulation. Retrieved clusters incorporate prior biological knowledge such as Gene Ontology, pathway, and protein protein interaction information for extracting other related genes. With these extended gene list, system builds genetic sub-networks using Bayesian network with MDL score and Sparse Candidate algorithm. Identifying functional modules of genes is done by not only microarray data itself but also well-proved biological knowledge. This integrated approach can improve there liability of a network in that false relations due to the lack of data can be reduced. Another advantage is the decreased computational complexity by constrained gene sets. To evaluate the proposed system, S. Cerevisiae cell cycle data [1] is applied. The result analysis presents new hypotheses about novel genetic interactions as well as typical relationships known by previous researches [2].

• 기술경영경제학회:학술대회논문집
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• 기술경영경제학회 1998년도 제13회 하계학술발표회 논문집
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• pp.208-215
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• 1998

Since the advent of conceptual prototype and seminal application, the notion of national systems of innovation(NSI) has drawn an increasing recognition. Although the morphological entanglement is still ubiquitous and the theoretical underpinning is fragile, NSI seems to be the last step toward an increasingly complex and encompassing concept of innovation research. Inevitably, NSI necessitates the comparative analysis in that it normatively attempts to draw best practices. Unfortunately, national profiles are too complex and diverse to derive a unified, concrete representation of the system, posing the problem of defining and modelling NSI for international comparison. This paper aims at providing an inductive taxonomy of NSI based on R&D structure of OECD member economies. Based on the similarity among national profiles, clustering method was applied to identify seven clusters such as (1) enterprise-government funding and enterprise-education performing group, (2) enterprise-government funding and balanced performing group, (3) balanced funding and enterprise-education performing group, (4) balanced funding and performing group, (5) enterprise-dominating group, (6) government-education dominating group and (7) government-education funding and education performing group. This paper by nature is descriptive and exploratory. R&D structure represents a static snapshot of innovative performance since it accounts for only the input side of NSI and thus may not offer convincing explanations of the holistic innovation system. A more detailed and extensive analysis on the economic/technological performance across clusters will shed light on the promising avenue to future research.

• Journal of Electrical Engineering and Technology
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• 제11권4호
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• pp.848-859
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• 2016

System failures in thermal power plants (TPPs) can lead to serious losses because the equipment is operated under very high pressure and temperature. Therefore, it is indispensable for alarm systems to inform field workers in advance of any abnormal operating conditions in the equipment. In this paper, we propose a clustering-based fault detection method for steam boiler tubes in TPPs. For data clustering, k-means algorithm is employed and the number of clusters are systematically determined by slope statistic. In the clustering-based method, it is assumed that normal data samples are close to the centers of clusters and those of abnormal are far from the centers. After partitioning training samples collected from normal target systems, fault scores (FSs) are assigned to unseen samples according to the distances between the samples and their closest cluster centroids. Alarm signals are generated if the FSs exceed predefined threshold values. The validity of exponentially weighted moving average to reduce false alarms is also investigated. To verify the performance, the proposed method is applied to failure cases due to boiler tube leakage. The experiment results show that the proposed method can detect the abnormal conditions of the target system successfully.