• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.90-97
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• 2002

Wall slip models are essential to the study of nonequilibrium gas transport in rarefied and microscale condition that can be found in gas flows associated with aerospace vehicle, propulsion system, and MEMS. The Maxwell slip model has been used for this type of problem, but it has difficulty in defining the so-called accommodation coefficient and has not been very effective in numerical implementation. In the present study, on the basis of Langmuir's theory of the adsorption of gases on metals, a physical slip model is developed. The concept of the accommodation coefficient and the difference of gas particles are clearly explained in the new model. It turned out that the Langmuir model recovers the Maxwell model in the first-order approximation. The new models are also applied to various situations including internal flow in a microchannel. Issues of validation of models are treated by comparing analytic results with experiment.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.12
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• pp.1152-1160
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• 2007

In this paper we deal with a design of integral sliding mode controller to reject the disturbance force acting on the suspension system in the magnetically levitated system which is propelled by the linear induction motor. The control scheme comprises an integral controller which is designed for achieving zero steady-state error under step disturbances, and a sliding mode controller which is designed for enhancing robustness under plant uncertainties. A proper continuous design signal is introduced to overcome the chattering problem. The disturbance force produced by the linear motor is formularized by using a curve fitting of the experimental raw data. Computer simulations show the effectiveness of the designed integral sliding mode controller to reject the disturbance force.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1055-1064
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• 2017

Since a device such as a rocket motor requires very high reliability, a reasonable reliability design process is essential. However, Korea has implemented a design method for applying a safety factor to each component. In classic reliability analysis, input variables such as mean and standard deviation, used in the limit state function, are treated as deterministic values. Because the mean and standard deviation are determined by a small amount of data, this approach could lead to inaccurate results. In this study, reliability analysis is performed for bolted joints and o-ring seals, and the Bayesian approach is used to statistically estimate the input variables. The estimated variables and failure probability, calculated by the reliability analysis, are derived in the form of probability distributions.

• Journal of Internet Computing and Services
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• v.9 no.6
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• pp.165-177
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• 2008

An important issue in Multiagent reinforcement learning is how an agent should learn its optimal policy in a dynamic environment where there exist other agents able to influence its own performance. Most previous works for Multiagent reinforcement learning tend to apply single-agent reinforcement learning techniques without any extensions or require some unrealistic assumptions even though they use explicit models of other agents. In this paper, a Naive Bayesian based policy model of the opponent agent is introduced and then the Multiagent reinforcement learning method using this model is explained. Unlike previous works, the proposed Multiagent reinforcement learning method utilizes the Naive Bayesian based policy model, not the Q function model of the opponent agent. Moreover, this learning method can improve learning efficiency by using a simpler one than other richer but time-consuming policy models such as Finite State Machines(FSM) and Markov chains. In this paper, the Cat and Mouse game is introduced as an adversarial Multiagent environment. And then effectiveness of the proposed Naive Bayesian based policy model is analyzed through experiments using this game as test-bed.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2001.04a
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• pp.168-168
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• 2001

제지공정의 지절 현상은 많은 공정 변수들이 복합적으로 작용하여 발생하는 가장 큰 공정 트러블 중의 하나이다. 지절은 생산량 감소 뿐만 아니라 발생 후 공정의 복구 와 정리, 생산재가동 및 공정의 재안정화를 위해 많은 시간과 비용, 그리고 노력이 투 입되어야 하므로 공정의 효율과 생산성을 크게 저하시키는 요인이다. 그러나 지절 현상 의 복잡성 때문에 이에 대해 쉽게 접근하거나 해결하지 못하고 있는 것이 현실이지만 그 필요성은 더욱 더 증대되고 있다. 본 연구에서는 최근 들어 각종 산업분야에서 복잡 한 공정상의 결점 발견 및 진단에 효과적이라고 인정받고 있는 예측 분석기법인 인공 신경망(artificial neural network) 시율레이션과 일반적인 통계기법 중의 하나인 주성분 분석을 이용하여 제지 공정의 지절 현상의 검토 가능성을 타진하였다. 인공신경망이란 인간두뇌에서 일어나는 자극-반응-학습과정을 모사하여 현실세계에 존재하는 다양한 현상들의 업력벡터와 출력상태 간의 비선형 mapping올 컴퓨터 시율 레이션을 통하여 분석하고자 하는 기법으로, 여러 가지 현상들을 학습을 통해서 인식하 는 신경망 내의 신경단위들이 병렬처리에 의해 많은 양의 자료에 대한 추론이나 판단 을 신속하고 정확하게 해주는 특징이 있으며 실시간 패턴인식이나 분류 응용분야에도 매우 매력적으로 이용되고 있는 방법이다. 이러한 인공 신경망 기법 중에서도 본 연구 에서는 퍼셉트론의 한계점을 극복하기 위하여 입력총과 출력층에 한 개 이상의 은닉층 ( (hidden layer)을 사용하여 다층 네트워으로 구성하고, 모든 입력패턴에 대하여 발생하 는 오차함수를 최소화하는 방향으로 연결강도를 조정하는 back propagation 학습 알고 리즘을 사용하였다. 지절의 원인으로 추정 가능한 공정인자들을 변수로 하여 최적의 인 공신경망을 구축하기 위해 학습률과 모멘트 상수의 변화 및 은닉층의 수와 출력층의 뉴런 수를 조절하는 동의 작업을 거쳐 네트워크의 정확도가 높은 인공신경망을 설계하 였다. 또한 이러한 인공신경망과의 비교분석을 위해 동일한 공정 데이터들올 이용하여 보편적으로 사용하는 통계기법 중의 하나인 주성분회귀분석을 실시하였다. 주성분 분석은 여러 개의 반응변수에 대하여 얻어진 다변량 자료의 다차원적인 변 수들을 축소, 요약하는 차원의 단순화와 더불어 서로 상관되어있는 반응변수들 상호간 의 복잡한 구조를 분석하는 기법이다. 본 발표에서는 공정 자료를 활용하여 인공신경망 과 주성분분석을 통해 공정 트러블의 발생에 영향 하는 인자들을 보다 현실적으로 추 정하고, 그 대책을 모색함으로써 이를 최소화할 수 있는 방안을 소개하고자 한다.

• Fire Science and Engineering
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• v.30 no.3
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• pp.16-22
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• 2016

Fire fighters rely on fire fighter protective clothing (FFPC) to provide adequate protection in the various hazardous environments. To enhance its protection performance, the FFPC material must be thick and thus it is difficult to achieve weight reduction. One of the methods of overcoming this problem, the addition of phase change material (PCM) to FFPC, is a new technology. In previous studies, the researches was mostly related to the temperature characteristics of the fibers incorporating PCM, but little information is available about its effect on burn injuries. Thus, in this study, the inhibitory effects of adding PCM to FFPC on second degree burns were investigated through numerical calculations. Thermal analyses of biological tissues and FFPC with embedded PCM exposed to several fire conditions causing severe tissue damage were studied by using a finite difference method based on the Pennes bio-heat equation. FFPC with embedded PCM was found to provide significantly greater protection than conventional fire fighting clothing, because the heat of absorption due to the phase change within the material is used to limit the heat conduction of the material.

• Korean Journal of Materials Research
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• v.10 no.2
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• pp.124-127
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• 2000

A new triode type Ti-silicided Si FEA(field emitter array) was realized by Ti-silicidation of Ti coated Si FEA and its field emission properties were investigated. In the fabricated device, the field emission properties through the unit pixel with $200{\mu\textrm{m}}{\times}200{$\mu\textrm{m}}$ tip array in the area of $1000{\mu\textrm{m}}{\times}1000{$\mu\textrm{m}}$ were as follows : the turn-on voltage was about 70V under high vacuum condition of $10^8Torr$, and the field emission current and steady state current degradation were about 2nA/tip and 0.3%/min under the bias of $V_A=500V\;and\;V_G=150V$. The low turn-on voltage and the high current stability during long term operation of the Ti silicided Si FEA were due to the thermal and chemical stability and the low work function of silicide layer formed at the surface of Si tip.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.693-698
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• 2003

Every baseball game generates various records and on the basis of those records, win/lose prediction about the next game is carried out. Researches on win/lose predictions of professional baseball games have been carried out, but there are not so good results yet. Win/lose prediction is very difficult because the choice of features on win/lose predictions among many records is difficult and because the complexity of a learning model is increased due to overlapping factors among the data used in prediction. In this paper, learning features were chosen by opinions of baseball experts and a heuristic function was formed using the chosen features. We propose a hybrid model by creating a new value which can affect predictions by combining multiple features, and thus reducing a dimension of input value which will be used for backpropagation learning algorithm. As the experimental results show, the complexity of backpropagation was reduced and the accuracy of win/lose predictions on professional baseball games was improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.2021-2030
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• 2012

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Particularly, in the healthcare system that must continuously monitor patient's situation, it is necessary to process ECG (Electrocardiography) signal in realtime. In other words, the design of algorithm that exactly detects R wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, the patient adaptive pattern matching algorithm for the classification of PVC is presented in this paper. For this purpose, we detected R wave through the preprocessing method, adaptive threshold and window. Also, we applied pattern matching method to classify each patient's normal cardiac behavior through the Hash function. The performance of R wave detection and abnormal beat classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.33% in R wave detection and the rate of 0.32% in abnormal beat classification error.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.2
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• pp.71-80
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• 2002

According to the rapid growth of high speed and precise industry, the application of synchronous motor has been increased. In the application fields, these fast dynamic response is of prime importance. In particular, since the PMLSM(Permanent Magnet Linear Synchronous Motor) has characteristics of high speed, high thrust, it has been used in high-performance servo drive. From these reasons, it is recently used for high precise position control, and machine tool. In this paper, a study of the sliding mode with VSS (Variable Structure System) design for a PMLSM is presented. For fast and precise motion control of PMLSM, the compensation of disturbance and parameter variation is necessary. Hence we eliminate the reaching phase use of VSS that is changed to switching function and vector control using the state observer. And we proposed to sliding mode control algorithm so that realize fast response without overshoot, disturbance and parameter variation.