• 한국정보처리학회논문지
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• 제6권10호
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• pp.2693-2706
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• 1999

Reengineering to object-oriented system is needed to maintain the system and satisfy requirements of structure change. Target systems which should be reengineered to object-oriented system are difficult to change because these systems have no design document or their design document is inconsistent of source code. Using design document to identifying objects for these systems is improper. There are several researches which identify objects through procedural source code analysis. In this paper, we propose automatic object identification method based on clustering of VTFG(Variable-Type-Function Graph) which represents relations among variables, types, and functions. VTFG includes relations among variables, types, and functions that may be basis of objects, and weights of these relations. By clustering related variables, types, and functions using their weights, our method overcomes limit of existing researches which identify too big objects or objects excluding many functions. The method proposed in this paper minimizes user's interaction through automatic object identification and make it easy to reenginner procedural system to object-oriented 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.

• 한국지능시스템학회논문지
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• 제17권2호
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• pp.276-283
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• 2007

It has been shown that the structure identification of a neuro-fuzzy model improves their accuracy performances in a various modeling problems. In this paper, we claim that the structure identification of a neuro-fuzzy model can also reduce the degree of inconsistency of its fuzzy rulebase. Thus, the resulting neuro-fuzzy model serves as more like a structured knowledge representation scheme. For this, we briefly review a structure identification method of a neuro-fuzzy model and propose a systematic method to measure inconsistency of a fuzzy rulebase. The proposed method is applied to problems or fuzzy system reproduction and nonlinear system modeling in order to validate our claim.

• 센서학회지
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• 제21권5호
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• pp.329-338
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• 2012

This paper presents an effective design method for a gas identification system. The design method adopted the sequential combination between the hybrid genetic algorithms and the TSK fuzzy logic system. First, the sensor grouping method by hybrid genetic algorithms led the effective dimensional reduction as well as effective pattern analysis from a large volume of pattern dimensions. Second, the fuzzy identification sub-models allowed handling the uncertainty of the sensor data extensively. By these advantages, the proposed identification model demonstrated high accuracy rates for identifying the five different types of gases; it was confirmed throughout the experimental trials.

• Smart Structures and Systems
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• 제20권4호
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• pp.415-426
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• 2017

Traditional experimental verification for nonlinear system identification often faces the problem of experiment model repeatability. In our research, a steel frame experimental model is developed to imitate the behavior of a single story steel frame under horizontal excitation. Two adjustable rotational dampers are used to simulate the plastic hinge effect of the damaged beam-column joint. This model is suggested as a benchmark model for nonlinear dynamics study. Since the nonlinear form provided by the damper is unknown, a Morlet wavelet based method is introduced to identify the mathematical model of this structure under different damping cases. After the model identification, earthquake excitation tests are carried out to verify the generality of the identified model. The results show the extensive applicability and effectiveness of the identification method.

• 전기학회논문지
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• 제67권3호
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• pp.419-426
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• 2018

An useful and effective design method for the gas identification system is presented in this paper. The proposed gas identification system adopts hierarchical structure with two level rule base combining fuzzy sets with rough sets. At first, a hybrid genetic algorithm is used in grouping the array sensors of which the measured patterns are similar in order to reduce the dimensionality of patterns to be analyzed and to make rule construction easy and simple. Next, for low level identification, fuzzy inference systems for each divided group are designed by using TSK fuzzy rule, which allow handling the drift and the uncertainty of sensor data effectively. Finally, rough set theory is applied to derive the identification rules at high level which reflect the identification characteristics of each divided group. Thus, the proposed method is able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, we demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• 한국소음진동공학회논문집
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• 제26권7호
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• pp.844-850
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• 2016

This study pertains to the extraction of the road noise component of signals from a vehicle's interior noise via the traditional frequency domain and time domain system identification methods. For road noise extraction based on the frequency domain system identification method, the appropriate matrix inversion strategy is investigated and causal and non-causal impulse response filters are compared. Furthermore, appropriate data lengths for the frequency domain system identification method are investigated. In addition to the traditional road noise extraction methods based on frequency domain system identification, a new approach to extract road noise via the time domain system identification method based on a parametric input-output model is proposed and investigated in the present study. In this approach, instead of constructing a higher order model for the full-band road noise, input and output signals are processed in the subband domain and lower order parametric models optimal to each subband are determined. These parametric models are used to extract road noises in each subband; the full band road noise is then reconstructed from the subband road noises. This study shows that both the methods in the frequency domain and the time domain successfully extract the road noise from the vehicle's interior noise.

• Structural Engineering and Mechanics
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• 제46권3호
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• 대한기계학회논문집A
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• 제29권7호
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• pp.938-946
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• 2005

Friction is a dominant nonlinear factor in servomechanisms, which seriously deteriorates system accuracy. A friction compensator is indispensable to fabricate high-performance servomechanisms. In order to compensate for the friction in the servomechanism, identification of the friction elements is required. To estimate the friction of the servomechanism, an accurate linear element model of the system is required first. Tn this paper, a nonlinear friction model, in which static, coulomb and viscous frictions as well as Stribeck effect are included, is identified through the describing function approximation of the nonlinear element. A nonlinear element composed of two relays is intentionally devised to induce various limit cycle conditions in the velocity control loop of the servomechanism. The friction coefficients are estimated from the intersection points of the linear and nonlinear elements in the complex plane. A Butterworth filter is added to the velocity control loop not only to meet the assumption of the harmonic balance method but also to improve the accuracy of the friction identification process. Validity of the proposed method is confirmed through numerical simulations and experiments. In addition, a model-based friction compensator is applied as a feedforward controller to compensate fur the nonlinear characteristics of the servomechanism and to verify the effectiveness of the proposed identification method.

• 전기학회논문지
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• 제67권7호
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• pp.903-909
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• 2018

We propose laser scanner sensor system based walking pattern and tracking method of multiple human. This system uses laser scanners sensors and is applicable to wide and crowded area such as hospital and medical care center. The primary objective of this research is to promote the development of robust, repeatable and transferable software for security system that can automatically detect, track and follow people in public area. We developed the method of human identification for this system. Our method is following: 1. Best-walking pattern data are obtained by the help of human position and direction data obtained by laser scanners. 2. Human identification is conducted by calculating the correlation between the step length of walking human. It becomes possible to conduct human identification even in crowded scenes by estimating the movements of waling human' feet are periodic. In the experiment in the station, some effectiveness of this method became clear.