• 한국건설관리학회논문집
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• 제6권5호
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• pp.69-77
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• 2005

Change is inevitable and is a reality of construction projects. Most construction contracts include change clauses and allowing contractors an equitable adjustment to the contract price and duration caused by change. However, the actions of a contractor can cause a loss of productivity and furthermore can result in disruption of the whole project because of a cumulative or ripple effect. Because of its complicated nature, it becomes a complex issue to determine the cumulative impact (ripple effect) caused by single or multiple change orders. Furthermore, owners and contractors do not always agree on the adjusted contract price for the cumulative Impact of the changes. A number of studies have attempted to quantify the impact of change orders on project costs and schedule. Many of these attempted to develop regression models to quantify the loss. However, regression analysis has shortcomings in dealing with many qualitative or noisy input data. This study develops ANN models to classify and quantify the labor productivity losses that are caused by the cumulative impact of change orders. The results skew that ANN models give significantly improved performance compared to traditional statistical models.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.347-350
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• 1992

In this note, we propose a method for designing a robot controller which can suppress the effects of both the model uncertainty and noisy velocity measurements. The controller is an output feedback compensator of which the constant gains are given in terms of a Riccati equation and a Lyapunov equation. The controller guarantees not only uniform boundedness but uniform ultimate boundedness. The stability result is local but the region can be arbitrarily enlarged at the expense of large control gain. The control law needs neither the exact knowledge of the physical robot parameters nor clean velocity measurements.

• ETRI Journal
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• 제39권2호
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• pp.181-190
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• 2017

The movements of the human body are difficult to capture owing to the complexity of the three-dimensional skeleton model and occlusion problems. In this paper, we propose a motion capture system that tracks dynamic human motions in real time. Without using external markers, the proposed system adopts multiple depth sensors (Microsoft Kinect) to overcome the occlusion and body rotation problems. To combine the joint data retrieved from the multiple sensors, our calibration process samples a point cloud from depth images and unifies the coordinate systems in point clouds into a single coordinate system via the iterative closest point method. Using noisy skeletal data from sensors, a posture reconstruction method is introduced to estimate the optimal joint positions for consistent motion generation. Based on the high tracking accuracy of the proposed system, we demonstrate that our system is applicable to various motion-based training programs in dance and Taekwondo.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집A
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• pp.566-572
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• 2000

The System identification is the process of developing or improving a mathematical model of a physical system using experimental data of the input, output and noise relationship. The field of system identification has been an important discipline within the automatic control area. The reason is the requirement that mathematical models having a specified accuracy must be used to apply modem control methods. In this paper, it is confirmed that we can obtain transfer function of flexible beam that is expressed in the forms of identified state-space system matrix A, B, C, D and identified observer gain G using Eigensystem Realization Algorithm including singular value decomposition. And these matrices can be applied to the automatic control. In addition to, it is also confirmed that transfer function can express a system using identified observer gain G, in spite of a noisy data or a periodic disturbance.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.21-23
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• 1994

A Fault Detection. Isolation scheme based on ANN(Artifical Neural Network) is proposed for the supervision of a DC shunt motor. The Proposed FDI scheme can promptly detect the occurence of fault and classify all the faults that may occur during the operation. Also. it covers the full operating range in spite that the mathematical model of the motor contain strong nonlinearities. The simulation results show that the FDIU has good diagnostic ability even in the noisy environment.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 춘계학술대회 논문집
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• pp.820-825
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• 2008

In the article 16 of the domestic rolling stock crashworthiness regulations, the collision acceleration level during collision accidents should remain under the maximum 7.5g and the average 5g. By the way, the accelerations obtained in crash simulations and tests contain many kinds of high frequency components due to numerical oscillations or noisy signals. So, this paper aims to develop reliable post-processing methods to filter high frequency oscillations and extract the rigid body motions of passenger rail cars. For this study we used the 1-dimensional dynamic model of KHST (Korean high-speed train), and evaluated acceleration data at the driver's area in the first power car and the passenger area in the following trailer.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.624-636
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• 2006

This paper proposes a hybrid approach involving Genetic Algorithm (GA) and Bacterial Foraging (BF) for tuning the PID controller of an AVR. Recently the social foraging behavior of E. coli bacteria has been used to solve optimization problems. We first illustrate the proposed method using four test functions and the performance of the algorithm is studied with an emphasis on mutation, crossover, variation of step sizes, chemotactic steps, and the life time of the bacteria. Further, the proposed algorithm is used for tuning the PID controller of an AVR. Simulation results are very encouraging and this approach provides us a novel hybrid model based on foraging behavior with a possible new connection between evolutionary forces in social foraging and distributed non-gradient optimization algorithm design for global optimization over noisy surfaces.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1799-1802
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• 2002

This paper proposes an improved method for formant frequencies estimation based on the complex autocorrelation function of the speech signal. Instead of using the incoming signal as an input fur the LPC analysis, the analytic signal of the autocorrelation function of the speech signal is computed and itself used as an input for the LPC analysis. Due to the properties of the analytic signal, which occupies half of the bandwidth of the original signal, the required model order for the LPC analysis is halved. The accuracy of the proposed method in noisy environments is examined on five natural vowels. The effectiveness of the proposed method is shown by the estimated spectral shapes and the estimation errors of the formant frequencies.

• Structural Engineering and Mechanics
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• 제42권3호
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• pp.425-448
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• 2012

In this paper, a new damage detection and quantification method has been presented to perform detection and quantification of structural damage under ambient vibration loadings. To extract modal properties of the structural system under ambient excitation, natural excitation technique (NExT) and eigensystem realization algorithm (ERA) are employed. Sensitivity matrices of the dynamic residual force vector have been derived and used in the parameter subset selection method to identify multiple damaged locations. In the sequel, the steady state genetic algorithm (SSGA) is used to determine quantified levels of the identified damage by minimizing errors in the modal flexibility matrix. In this study, performance of the proposed damage detection and quantification methodology is evaluated using a finite element model of a truss structure with considerations of possible experimental errors and noises. A series of numerical examples with five different damage scenarios including a challengingly small damage level demonstrates that the proposed methodology can efficaciously detect and quantify damage under noisy ambient vibrations.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2016년도 제28회 한글 및 한국어 정보처리 학술대회
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• pp.165-170
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• 2016

본 논문에서 제안하는 문맥의존 철자오류 교정은 통계 정보를 이용한 방법으로 통계적 언어처리에서 가장 널리 쓰이는 샤논(Shannon)이 발표한 노이지 채널 모형(noisy channel model)을 기반으로 한다. 선행연구에서 부족하였던 부분의 성능 향상을 위해 교정대상단어의 오류생성 및 통계 데이터의 저장 방식을 개선하여 Default 연산을 적용한 모델을 제안한다. 선행 연구의 모델은 교정대상단어의 오류생성 시 편집거리의 제약을 1로 하여 교정 실험을 하지만 제안한 모델은 같은 환경에서 더욱 높은 검출과 정확도를 보였으며, 오류단어의 편집거리(edit distance) 제약을 넓게 적용하더라도 신뢰도가 있는 검출과 교정을 보였다.