• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.1572-1577
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• 2003

High-power pulsed laser ablation under atmospheric pressure is studied utilizing numerical and experimental methods with emphasis on recondensation ratio, and the dynamics of the laser induced vapor flow. In the numerical calculation, the temperature pressure, density and vaporization flux on a solid substrate are first obtained by a heat-transfer computation code based on the enthalpy method, and then the plume dynamics is calculated by using a commercial CFD package. To confirm the computation results, the probe beam deflection technique was utilized for measuring the propagation of a laser induced shock wave. Discontinuities of properties and velocity over the Knudsen layer were investigated. Related with the analysis of the jump condition, the effect of the recondesation ratio on the plume dynamics was examined by comparing the pressure, density, and mass fraction of ablated aluminum vapor. To consider the effect of mass transfer between the ablation plume and air, unlike the most previous investigations, the equation of species conservation is simultaneously solved with the Euler equations. Therefore the numerical model computes not only the propagation of the shock front but also the distribution of the aluminum vapor. To our knowledge, this is the first work that employed a commercial CFD code in the calculation of pulsed ablation phenomena.

• 한국자동차공학회논문집
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• 제16권6호
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• pp.39-47
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• 2008

In this research, a web-based design support system is constructed for the design process of automotive steel pulley to gather engineering knowledge from pulley design data. In the design search module, a clustering tool for design data is proposed using K-means clustering algorithm. To obtain correlational patterns between design and FEA (Finite Element Analysis) data, a Multi-layer Back Propagation Network (MBPN) is applied. With the analyzed patterns from a number of simulation data, an estimation of minimum von mises can be provided for given design parameters of pulleys. The case study revealed fast estimation of minimum stress in the pulley within 12% error.

• 산업공학
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• 제13권1호
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• pp.1-9
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• 2000

This study developed an integrated management framework for KM, consisting of four major management objects and organizational initiatives: managerial and technical initiatives. Based on the developed framework, it proposes a stage model of organizational KM from Initiation, Propagation, Integration to Networking stage with detail explanations focusing on management goals and activities. To validate the proposed stage model, this study conducted a preliminary study with a latent content analysis of 15 KM cases. Form the results, though is could not validate the time sequence of each stage because of the limited information of cases, it shows meaningful findings in that there are a kind of relationship among management goals, activities and characteristics of management object of cases.

• 전자공학회논문지A
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• 제32A권12호
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• pp.48-54
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• 1995

Dielectrically filled parallel-plate waveguide with finite number of periodic slots in its upper plate as a leaky wave antenna is analysed for E-polarization case. The integro-differential equation whose unknown is the slot equivalent magnetic current over the slot is formulated and solved by use of Galerkin's method. From knowledge of the equivalent magnetic current, the propagation constant and radiation pattern for the finite periodic structure are determined and compared with the results of the infinite case. Good correspondence between them is observed.

• 대한산업공학회지
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• 제11권2호
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• pp.131-140
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• 1985

This paper analyses the hindrance factors of process capability. The reasons of the products which are out of specification can be accounted on the hindrance factors. An $\hat{e}$nquete which consists of 4 categories such as technical knowledge, work performance, work environment, and human relations at home and office, is prepared and handed out to 1000 works to get information. And Spearman's Correlation Coefficient (${\rho}s$) is adapted as an anaysis and consideration criterion. In consequence, it is revealed the next 4 factors become the vital hindrance factors of process capability: (1) unskillful working (2) over load for operators (3) imperfect work environment (4) incoordination of human relations And the correspondent policy can be summarized as follows: (1) propagation & fixation of I.E. techniques (2) harmonization of human relations (3) improvement of work environment (4) strengthening the T.W.I.

• Journal of Electrical Engineering and Technology
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• 제13권6호
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• pp.2511-2520
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• 2018

In this study, Multi-Radial Basis Function Support Vector Machine (Multi-RBF SVM) classifier is introduced based on a composite kernel function. In the proposed multi-RBF support vector machine classifier, the input space is divided into several local subsets considered for extremely nonlinear classification tasks. Each local subset is expressed as nonlinear classification subspace and mapped into feature space by using kernel function. The composite kernel function employs the dual RBF structure. By capturing the nonlinear distribution knowledge of local subsets, the training data is mapped into higher feature space, then Multi-SVM classifier is realized by using the composite kernel function through optimization procedure similar to conventional SVM classifier. The original training data set is partitioned by using some unsupervised learning methods such as clustering methods. In this study, three types of clustering method are considered such as Affinity propagation (AP), Hard C-Mean (HCM) and Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA). Experimental results on benchmark machine learning datasets show that the proposed method improves the classification performance efficiently.

• 농촌계획
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• 제20권4호
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• pp.137-143
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• 2014

Car exhaust emissions are recognized as one of the key sources for climate change and electric vehicles have no emissions from tailpipe. However, the limited charging infrastructures could restrict the propagation of electric vehicles. The purpose of this study is to find the vulnerable districts limited to the charging station services after meeting the goal of Ministry of Knowledge Economy(12%). We assumed that the charging service can be provided by current gas stations. The range of the vulnerable grades was determined by the accessibility to current gas stations and the vulnerable regions were classified considering the optimal number of charging stations estimated by the efficiency function. We used 4,827 sub-municipal divisions and 11,677 gas station locations for this analysis. The results show that most of mountain areas are vulnerable and the fringe areas of large cities generally get a good grade for the charging infrastructure. The gangwon-do, jeollanam-do, gyeongsangbuk-do, and chungcheongnam-do include more than 40% vulnerable districts.

• 지능정보연구
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• 제12권4호
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• pp.51-60
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• 2006

정성적 추론은 자연 세계에 대한 정성적, 직관적인 지식을 밝혀내어 코드화하는 목표를 갖고 연구되어 왔다. 정성적 추론은 전자, 기계 등의 도메인에서 성공적으로 사용되어 그 실효성을 입증할 수 있었으나, 대부분의 추론은 시뮬레이션에 집중되어 왔다. 본 연구에서는 주어진 상황에서 변화가 발생했을 때, 이 변화가 어떻게 영향을 미치며 파급되는지를 예측할 수 있는 정성적 비교분석 기법을 소개하고자 한다. 본 연구에서는 파라미터의 상대적인 변화의 파급만을 예측한 기존의 연구에 상대적 변화의 증가율 변화에 대한 추론을 추가하여 확장하였다. 상대적인 주어진 상황에 대한 인과모델이 정성적 분야 모델로부터 형성되고, 여기에 비교분석 추론 기법을 적용하여 변화의 연쇄적인 인과 관계를 추적하게 된다. 이러한 기법은 변화의 예측 뿐 아니라, 이런 변화를 이끌어낸 인과 관계를 설명하는 기능을 제공하게 되어, 디자인, 진단, 지능형 교육 시스템, 환경 영향평가 등에 이용되리라 기대된다.

• Journal of Computing Science and Engineering
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• 제5권4호
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• pp.305-313
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• 2011

Due to the expansion of high-speed Internet access, the need for secure and reliable networks has become more critical. The sophistication of network attacks, as well as their severity, has also increased recently. As such, more and more organizations are becoming vulnerable to attack. The aim of this research is to classify network attacks using neural networks (NN), which leads to a higher detection rate and a lower false alarm rate in a shorter time. This paper focuses on two classification types: a single class (normal, or attack), and a multi class (normal, DoS, PRB, R2L, U2R), where the category of attack is also detected by the NN. Extensive analysis is conducted in order to assess the translation of symbolic data, partitioning of the training data and the complexity of the architecture. This paper investigates two engines; the first engine is the back-propagation neural network intrusion detection system (BPNNIDS) and the second engine is the radial basis function neural network intrusion detection system (BPNNIDS). The two engines proposed in this paper are tested against traditional and other machine learning algorithms using a common dataset: the DARPA 98 KDD99 benchmark dataset from International Knowledge Discovery and Data Mining Tools. BPNNIDS shows a superior response compared to the other techniques reported in literature especially in terms of response time, detection rate and false positive rate.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.491-494
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• 2006

Kalman filtering (KF) is hard to be applied to the SINS (Strap-down Inertial Navigation System)/RDSS (Radio Determination Satellite Service) integrated navigation system directly because the time delay of RDSS positioning in active mode is random. BP (Back-Propagation) Neuron computing as a powerful technology of Artificial Neural Network (ANN), is appropriate to solve nonlinear problems such as the random time delay of RDSS without prior knowledge about the mathematical process involved. The new algorithm betakes a BP neural network (BPNN) and velocity feedback to aid KF in order to overcome the time delay of RDSS positioning. Once the BP neural network was trained and converged, the new approach will work well for SINS/RDSS integrated navigation. Dynamic vehicle experiments were performed to evaluate the performance of the system. The experiment results demonstrate that the horizontal positioning accuracy of the new approach is 40.62 m (1 ${\sigma}$), which is better than velocity-feedback-based KF. The experimental results also show that the horizontal positioning error of the navigation system is almost linear to the positioning interval of RDSS within 5 minutes. The approach and its anti-jamming analysis will be helpful to the applications of SINS/RDSS integrated systems.