• International Journal of Aeronautical and Space Sciences
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• v.14 no.4
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• pp.379-386
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• 2013

The hemispherical resonator gyroscope is a type of vibratory gyroscope, which can measure angle or angular rate, based on its operating mode. This paper deals with the case when the hemispherical resonator gyroscope is operated in angle measurement mode. In angle measurement mode, the resonator pattern angle precesses, with respect to the external rotation input, by the principle of the Coriolis effect, so that the external rotation can be estimated, by measuring the amount of precession angle. However, this pattern angle drifts, due to the manufacturing error of the resonator. Since the drift effect causes degradation of the angle estimation performance of the resonator, the corresponding drift compensation control should be performed, to enhance the estimation performance. In this paper, a mathematical model of the hemispherical resonator gyro is first introduced. By using the mathematical model, a nonlinear observer for imperfection parameter estimation, and the corresponding compensation controller are designed to operate hemispherical resonator gyros, as angle measurement sensors.

• Journal of the Korean Physical Society
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• v.73 no.11
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• pp.1657-1662
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• 2018

A null test method which relies on a computer generated hologram (CGH) is widely used to measure a large aspheric surface. For precise measurements of the surface shape of an aspheric optics, the CGH must precisely generate a wavefront that can fit on the ideal surface shape of the aspheric optics. If fabrication errors arise in the CGH, an unwanted wavefront will be generated and the measuring result will lack trustworthiness. Thus far, there has been limited research on wavefronts generated by CGH using only linear-type binary grating models. In this study, a theoretical error model of a circular-type zone plate, the most commonly used types for CGH patterns, is suggested. The proposed error model is checked by simulations and experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.311-314
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• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF. To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKP uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.11 no.5
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• pp.108-122
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• 2001

As bridge design is advancing toward the performance-based design. it becomes increasingly important to monitor and re-evaluate the long-term structural performance of bridges. Such information is essential in developing performance criteria for design. In this research. sensor systems for long-term structural performance monitoring have been installed on two highway bridges. Pre1iminary vibration measurement and data analysis have been performed on these instrumented bridges. On one bridge, ambient vibration data have been collected. based on which natural frequencies and mode shapes have been extracted using various methods and compared with those obtained by the preliminary finite element analysis. On the other bridge, braking and bumping vibration tests have been carried out using a water truck In addition to ambient vibration tests. Natural frequencies and mode shapes have been derived and the results by the breaking and bumping vibration tests have been compared. For the development of a three dimensional baseline finite element model, the new methodology using a neural network is proposed. The proposed one have been verified and applied to develop the baseline model of the bridge.

• The Journal of Information Technology
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• v.9 no.3
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• pp.77-89
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• 2006

The event study analyzes returns around event date at a time. Event study provides estimation periods and cumulative returns. Stock split announcements are generally associated with positive abnormal returns. It is important to investigate the responses of stocks to new information contained in the announcements of stock splits. So It is important to study the long term performance in the case of Stock Split. This Study forced to two approach method in evaluating the performance, the event time portfolio approach and calendar time portfolio approach. The event time portfolio approach exists the CAR model, BHAR model and WR model. And the calendar time portfolio approach has the 3 factor model, 4 factor model, CTAR model, and RATS model.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.7
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• pp.377-392
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• 2005

A lot of studies to measure and analyze the system performance have been done in areas such as system modeling, performance measurement, monitoring, and performance prediction since the advent of a computer system. Studies on a framework to unify the performance related areas have rarely been performed although many studies in the various areas have been done, however. In the case of TMO(Time-Triggered Message-Triggered Object), a real-time programming model, it hardly provides tools and frameworks on the performance except a simple run-time monitor. So it is difficult to analyze the performance of the real-time system and the process based on TMO. Thus, in this paper, we propose a framework for the dynamic analysis of the real-time system based on TMO, TDAF(TMO based Dynamic Analysis Framework). TDAF treats all the processes for the performance measurement and analysis, and Provides developers with more reliable information systematically combining a load model, a performance model, and a reporting model. To support this framework, we propose a load model which is extended by applying TMO model to the conventional one, and we provide the load calculation algorithm to compute the load of TMO objects. Additionally, based on TMO model, we propose performance algorithms which implement the conceptual performance metrics, and we present the reporting model and algorithms which can derive the period and deadline for the real-time processes based on the load and performance value. In last, we perform some experiments to validate the reliability of the load calculation algorithm, and provide the experimental result.

• Journal of Korean Library and Information Science Society
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• v.41 no.1
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• pp.121-147
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• 2010

The purpose of this study is to develop and prove service quality measurement model and indicators which are able to measure objectively service quality of digital libraries in Korea. Literature review and Delphi survey are used to investigate service quality dimensions. User perceived service quality performance was measured to validate DL-SQI model with three digital libraries. Finally DL-SQI(Digital Library-Service Quality Index) model was developed which is composed of four primary dimensions. The survey results reveal that reliability coefficient is 0.8 which means high reliability of survey and it suggests that DL-SQI model based on the above dimensions is proved through confirmatory factor analysis.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.209-216
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• 2015

Quantile regression models with covariate measurement errors have received a great deal of attention in both the theoretical and the applied statistical literature. A lot of effort has been devoted to develop effective estimation methods for such quantile regression models. In this paper we propose the partially linear support vector orthogonal quantile regression model in the presence of covariate measurement errors. We also provide a generalized approximate cross-validation method for choosing the hyperparameters and the ratios of the error variances which affect the performance of the proposed model. The proposed model is evaluated through simulations.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.408-410
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• 2009

We present an efficient and robust measurement model for visual tracking. This approach builds on and extends work on subspace representations of measurement model. Subspace-based tracking algorithms have been introduced to visual tracking literature for a decade and show considerable tracking performance due to its robustness in matching. However the measures used in their measurement models are often restricted to few approaches. We propose a novel measure of object matching using Angle In Feature Space, which aims to improve the discriminability of matching in subspace. Therefore, our tracking algorithm can distinguish target from similar background clutters which often cause erroneous drift by conventional Distance From Feature Space measure. Experiments demonstrate the effectiveness of the proposed tracking algorithm under severe cluttered background.

• The KIPS Transactions:PartD
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• v.17D no.4
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• pp.259-270
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• 2010

Information systems nowadays are heterogeneous and distributed which integrate the enterprise information by processes. They are also very complex, because they are linked together by processes. It aims to integrate the systems so that these systems work as one system. A process is a framework which contains all of the business activities in an enterprise, and has a lot of information which is needed for measuring performance. A process consists of activities, and an activity contains events which can be considered information sources. In most cases, it is very valuable to determine if a process is meaningful, but it is difficult because of the complexity in measuring performance, and also because finding relationships between business factors and events is not a simple problem. So it would reduce operation cost and allow efficient process execution if I could evaluate the process before it ends. In this paper we propose an event based process measurement model. First, we propose the concept of process performance measurement, and a model for selecting process and activity indexes from the events which are collected from information systems. Second, we propose at methodologies and data schema that can store and manage the selected process indexes, the mapping methods between indexes and events. Finally, we propose a process Performance measurement model using the collected events which gives users a valuable managerial information.