• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.288-296
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• 2004

This paper proposes a new mesh simplification algorithm using differential error metric. Many simplification algorithms make use of a distance error metric, but it is hard to measure an accurate geometric error for the high-curvature region even though it has a small distance error measured in distance error metric. This paper proposes a new differential error metric that results in unifying a distance metric and its first and second order differentials, which become tangent vector and curvature metric. Since discrete surfaces may be considered as piecewise linear approximation of unknown smooth surfaces, theses differentials can be estimated and we can construct new concept of differential error metric for discrete surfaces with them. For our simplification algorithm based on iterative edge collapses, this differential error metric can assign the new vertex position maintaining the geometry of an original appearance. In this paper, we clearly show that our simplified results have better quality and smaller geometry error than others.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.

• Journal of the Korean Society for Railway
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• v.11 no.2
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• pp.203-210
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• 2008

Since hub wheel BLDC Motor consisted of wheel and BLDCM (Brushless DC Motor) without gear reducer has high efficiency and low operation noise, it can be utilized to a driving wheel at some light rail systems. However, installing sensors for speedometer on a Hub-Wheel motor is not easy, so it requires a different speed control mechanism method for speed measurement. This paper introduces a speed control method based on simple mathematical model which uses discrete Kalman Filter to estimate and control the speed of the motor.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.7
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• pp.1029-1037
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• 2004

High-speed/precision servomechanisms have been widely used in the manufacturing and semiconductor industries. In order to ensure the required high-speed and high-precision specifications in servomechanisms, an integrated design methodology is required, where the interactions between mechanical and electrical subsystems will have to be considered simultaneously. For the first step of the integrated design process, it is necessary to obtain not only strict mathematical models of separate subsystems but also formulation of an integrated design problem. A two-degree-of-freedom controller described in the discrete-time domain is considered as an electrical subsystem in this paper. An accurate identification process of the mechanical subsystem is conducted to verify the obtained mathematical model. Mechanical and electrical constraints render the integrated design problem accurate. Analysis of the system performance according to design and operating parameters is conducted for better understanding of the dynamic behavior and interactions of the servomechanism. Experiments are performed to verify the validity of the integrated design problem in the x-Y positioning system.

• Journal of the Korea Society for Simulation
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• v.21 no.1
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• pp.1-8
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• 2012

In recent days, global shipbuilding companies have been showing great interest in eco-friendly ship products and trying to reduce environmental pollution - harmful gas and dust in shipbuilding process. Following this trend, Life Cycle Assessment (LCA) was carried out to an application of shipyards layout. LCA is a technique used to assess environmental impacts during the life cycle of products and systems. Until now, LCA has been used through ISO 14040 in somewhat limited industries, such as Building Life Cycle Assessment. Thus, this study analyzes the shipyard layout planning framework and builds life cycle inventory along with the simulation model structure to evaluate environmental impacts.

• The KSFM Journal of Fluid Machinery
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• v.7 no.2 s.23
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• pp.41-49
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• 2004

Condition monitoring is very important in turbo machinery because single failure could cause critical damages to its plant. So, automatic fault recognition has been one of the main research topics in condition monitoring area. We have used a relatively new fault recognition method, Hidden Markov Model(HMM), for mechanical system. It has been widely used in speech recognition, however, its application to fault recognition of mechanical signal has been very limited despite its good potential. In this paper, discrete HMM(DHMM) was used to recognize the faults of rotor system to study its fault recognition ability. We set up a rotor kit under unbalance and oil whirl conditions and sampled vibration signals of two failure conditions. DHMMS of each failure condition were trained using sampled signals. Next, we changed the setup and the rotating speed of the rotor kit. We sampled vibration signals and each DHMM was applied to these sampled data. It was found that DHMMs trained by data of one rotating speed have shown good fault recognition ability in spite of lack of training data, but DHMMs trained by data of four different rotating speeds have shown better robustness.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.3
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• pp.115-123
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• 2003

With the advent of high performance computers and more efficient numerical algorithms, computational fluid dynamics(CFD) has come out as a modem alternative for reducing the use of wind tunnels test in automotive engineering. However, in spite of the fact that many competent researchers have made all their talents in developing turbulence model over since the past dozen or more years, it has been an important impediment in using the CFD effectively to design machinery and to diagnose or to improve engineering problems in the industry since the turbulence model has been acting as the Achilles' tendon in aspect of the reliability even to this time. In this study, Reynolds-averaged Wavier-Stokes equations were solved to simulate an incompressible turbulent flow around a bus-like bluff body near ground plane. In order to investigate the effect of the discretisation schemes and turbulence model on the aerodynamic forces several turbulence models with five convective difference schemes are adopted. From the results of this study, it is clear that choice of turbulence model and discretisation scheme profoundly affects the computational outcome. The results also show that the adoption of RNG $k-\varepsilon$ turbulence model and nonlinear quadratic turbulence model with the second order accurate discretisation scheme predicts fairly well the aerodynamic coefficients.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.878-879
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• 1997

본 논문에서는 전자기 과도현상 해석을 위한 다단자 회로망 등가표현법을 제안한다. 이 방법은 M개의 경계모선을 가진 축약대상 계통의 과도특성을 시간 영역에서 분석하며 이를 이용해 M 개의 노톤형 이산시간 등가 어드미턴스 필터꼴의 등가시스템을 구현한다. 이 때 각각의 등가 어드미턴스 필터 모델들은 해당 경계모선에서의 구동점 어드미턴스 특성을 나타내는 부분과 나머지 M-1 개의 등가 종속전류원으로 구성된다. 또한 이 등가 종속전류원들은 각 경계모선을 연결하는 분포정수 회로요소들로 인한 시지연 효과를 명확하게 반영할 수 있는 구조를 갖는다. 완성된 M 단자쌍 모델을 해석대상 시스템에 대한 이산시간 표현형과 쉽게 결합하여 원하는 전자기 과도현상 모의해석을 수행할 수 있다. 축약대상 시스템과 2 개의 경계모선을 통해 연결된 시험계통을 대상으로 모선지락 사고시 과전압과 스위칭 써지를 모의해석한 결과 제안하는 방법이 타당함을 확인할 수 있었다.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.3
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• pp.59-65
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• 2019

In many industries, particle packing is adopted quite frequently. In the particle packing process, the Discrete Element Method (DEM) can analyze the multi-collision of particles efficiently. Two types of contact models are frequently used for the DEM. One is the linear spring model, which has the fastest calculation time, and the other is the Hertz-Mindlin model, which is the most frequently used contact model employing the DEM. Meanwhile, very tiny particles in the micrometer order are used in modern industries. In the micro length order, surface force is important to decreased particle size. To consider the effect of surface force in this study, we performed a simulation with the Hertz-Mindlin model and added the Johnson-Kendall-Roberts (JKR) theory depicting surface force with surface energy. In addition, three contact models were compared with several parameters. As a result, it was found that the JKR model has larger residual stress than the general contact models because of the pull-off force. We also validated that surface force can influence particle behavior if the particles are small.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.165-172
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• 2010

In clinical data minig, choosing the optimal subset of features is such important, not only to reduce the computational complexity but also to improve the usefulness of the model constructed from the given data. Moreover the threshold values (i.e., cut-off points) of selected features are used in a clinical decision criteria of experts for differential diagnosis of diseases. In this paper, we propose a fuzzy discretization approach, which is evaluated by measuring the degree of separation of redundant attribute values in overlapping region, based on spatial distribution of data with continuous attributes. The weighted average of the redundant attribute values is then used to determine the threshold value for each feature and rough set theory is utilized to select a subset of relevant features from the overall features. To verify the validity of the proposed method, we compared experimental results, which applied to classification problem using 668 patients with a chief complaint of dyspnea, based on three discretization methods (i.e., equal-width, equal-frequency, and entropy-based) and proposed discretization method. From the experimental results, we confirm that the discretization methods with fuzzy partition give better results in two evaluation measures, average classification accuracy and G-mean, than those with hard partition.