• 대한인간공학회지
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• 제15권1호
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• pp.53-67
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• 1996

Since Romberg's test in 1953, the analysis of postural sway during upright stance has been widely used as a tool for evaluating balance and disorders of the postural control system. This review describes the methods that have been used to evaluste the static and dynamic performance of the postural control system. Various identification methods of postural control system based on standing balance are discussed and measures of postural sway are described. The application areas of standign balance research, with an emphasis on postural control evaluations, are also briefly described. This review can be used to gain an understanding of the dynamics of human standing balance.

• 한국철도학회지
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• 제6권2호
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• pp.9-18
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• 2003

This paper discuss advanced safety in the railway signaling system. The specified methods and HAZOP about Hazard identification and analysis of railway signalling system were studied, and loss analysis and ALARP model in order to calculate safety as a standard capacity were proposed. It was also resulted from Hazard identification, analysis and evaluation by applying advanced safety to the railway signalling system.

• 대한상한금궤의학회지
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• 제10권1호
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• pp.143-152
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• 2018

Objective : A Patient complaining of dizziness was diagnosed and treated with the Shanghanlun disease pattern identification diagnostic system and was analyzed to report cases Methods : Based on the Shanghanlun disease pattern identification diagnostic system, we analyzed a case treated with the Baekho-tang and counseling. Results : Baekho-tang showed a rapid improvement in the patient. During the period of 20 days, dizziness were greatly improved. Conclusions : The Baekho-tang, which is not well known yet, can show rapid effect and can be diagnosed frequently through the Shanghanlun disease pattern identification diagnostic system.

• 정보처리학회논문지D
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• 제9D권1호
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• pp.91-102
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• 2002

사용자의 요구사항 변경에 따른 반영, 빠른 시스템 구축, 유지 보수 단계의 효율적인 시스템 관리, 소프트웨어의 수정 용이성, 저렴한 비용 등은 컴포넌트 기반 시스템 구축이 필수적인 사항으로 여겨지고 있다. 이러한 컴포넌트 기반 시스템 구축을 위한 기존의 컴포넌트 개발 방법론은 컴포넌트 식별을 위하여 객체를 추출하는 부분이 비효율적이고 시스템 컴포넌트를 추출하기 위한 방법이 제시되어 있지 않다. 또한 시스템의 전체 도메인을 중심으로 비즈니스 컴포넌트 식별을 위한 절차와 방법만을 제시하고 있다. 그리고 컴포넌트 식별을 위하여 대부분 개발자의 직관과 경험에 의존하는 문제점이 있다. 따라서 본 논문에서는 객체를 추출하는 비효율적인 부분을 개선하기 위하여 요구 사항 분석단계부터 객체를 추출하는 단계까지 RUP(Rational Unified Process)를 적용한다. 또한 시스템 컴포넌트를 식별하기 위한 방법과 절차를 제안하고 시스템의 전체 도메인을 중심으로 비즈니스 컴포넌트를 식별하는 것이 아니라 추출된 시스템 컴포넌트를 중심으로 비즈니스 컴포넌트를 추출한다. 개발자의 직관과 경험에 의존하여 컴포넌트를 식별하는 문제점을 보완하기 위하여 응집척도와 결합철도를 제안하고 적용한다. 본 논문에서 제안하는 컴포넌트 식별 방법은 객체 식별의 용이성, 컴포넌트의 기능적 재사용성, 추적성 그리고 컴포넌트의 독립성을 중심으로 좀 더 효율적으로 컴포넌트를 식별한다.

• International Journal of Advanced Culture Technology
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• 제9권3호
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• pp.352-359
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• 2021

The purpose of this study is to design and build fake news discrimination systems and methods using fact-checking guidelines. In other words, the main content of this study is the system for identifying fake news using Artificial Intelligence -based Fact-checking guidelines. Specifically planned guidelines are needed to determine fake news that is prevalent these days, and the purpose of these guidelines is fact-checking. Identifying fake news immediately after seeing a huge amount of news is inefficient in handling and ineffective in handling. For this reason, we would like to design a fake news identification system using the fact-checking guidelines to create guidelines based on pattern analysis against fake news and real news data. The model will monitor the fact-checking guideline model modeled to determine the Fact-checking target within the news article and news articles shared on social networking service sites. Through this, the model is reflected in the fact-checking guideline model by analyzing news monitoring devices that select suspicious news articles based on their user responses. The core of this research model is a fake news identification device that determines the authenticity of this suspected news article. So, we propose news article identification methods with fact-checking guideline on Artificial Intelligence & Bigdata. This study will help news subscribers determine news that is unclear in its authenticity.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2001년도 추계학술대회논문집 I
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• pp.409-412
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• 2001

Identification of systems operating in closed loop has long been of prime interest in industrial applications. The fundamental problem with closed-loop data is the correlation between the unmeasurable noise and the input. This is the reason why several methods that work in open loop fail when applied to closed-loop data. The prediction error based approaches to the closed-loop system are divided to direct method and indirect method. Both of direct and indirect methods are known to be applied to the closed-loop data without critical modification. But the direct method induces the bias error in the experimental frequency response function and this bias error may deteriorates the parameter estimation performance

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1990년도 봄 학술발표회 논문집
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• pp.37-43
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• 1990

This paper develops practical models and methods for the assessment of safety and rating of damaged and/or deteriorated bridges by incorporating a system identification technique for the explicit inclusion of the degree of deterioration or damage and of the actual bridge response. And, based on the proposed model, reliability-based rating methods are proposed as LRFR(Load and Resistance Factor Rating) and system reliability-index rating criteria. The proposed limit state model explicitly accounts for the degree of deterioration or damage in terms of the damage and response factors. The damage factor in the paper is proposed as the ratio of the current stiffness to the intact stiffness. Based on the observation and the results of applications to existing bridges, it may be concluded that the proposed rating models, which explicitly account for the uncertainties and the effects of degree of deterioration or damage based on the system identification technique, provide more realistic and consistent safety-assessment and capacity-rating.

• 한국정밀공학회지
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• 제12권5호
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• pp.157-165
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• 1995

In this paper the comparison between the neural networks and traditional approaches as nonlinear system identification methods are considered. Two model structures of neural networks are the state space model and the input output model neural networks. The traditional methods are the AutoRegressive eXogeneous Input model and the Nonlinear AutoRegressive eXogeneous Input model. Computer simulation for an analytic dynamic model of a single input single output nonlinear system has been done for all the chosen models. Model validation for the obtained models also has been done with testing inputs of the sinusoidal, ramp and the noise ramp.

• Journal of Information Processing Systems
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• 제11권1호
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• pp.22-38
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• 2015

While Modern Standard Arabic is the formal spoken and written language of the Arab world; dialects are the major communication mode for everyday life. Therefore, identifying a speaker's dialect is critical in the Arabic-speaking world for speech processing tasks, such as automatic speech recognition or identification. In this paper, we examine two approaches that reduce the Universal Background Model (UBM) in the automatic dialect identification system across the five following Arabic Maghreb dialects: Moroccan, Tunisian, and 3 dialects of the western (Oranian), central (Algiersian), and eastern (Constantinian) regions of Algeria. We applied our approaches to the Maghreb dialect detection domain that contains a collection of 10-second utterances and we compared the performance precision gained against the dialect samples from a baseline GMM-UBM system and the ones from our own improved GMM-UBM system that uses a Reduced UBM algorithm. Our experiments show that our approaches significantly improve identification performance over purely acoustic features with an identification rate of 80.49%.

• Transactions on Control, Automation and Systems Engineering
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• 제4권2호
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• pp.109-113
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• 2002

Van de Vusse reactor is known as a highly nonlinear chemical process and has been considered by a number of researchers as a benchmark problem for nonlinear chemical process. Various identification methods for nonlinear system are also verified by applying these methods to Van de Vusse reactor. From the point of view of identification, only the Volterra kernel of second order has been obtained until now. In this paper, the authors show that Volterra kernels of nonlinear Van de Vusse reactor of up to 3rd order are obtained by use of M-sequence correlation method. A pseudo-random M-sequence is applied to Van de Vusse reactor as an input and its output is measured. Taking the crosscorrelation function between the input and the output, we obtain up to 3rd order Volterra kernels, which is the highest order Volterra kernel obtained until now for Van de Vusse reactor. Computer simulations show that when Van de Vusse chemical process is identified by use of up to 3rd order Volterra kernels, a good agreement is observed between the calculated output and the actual output.