• Smart Structures and Systems
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• v.15 no.3
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• pp.807-830
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• 2015

When a building structure requires both health monitoring system and vibration control system, integrating the two systems together will be cost-effective and beneficial for creating a smart building structure with its own sensors (nervous system), processors (brain system), and actuators (muscular system). This paper presents a real-time integrated procedure to demonstrate how health monitoring and vibration control can be integrated in real time to accurately identify time-varying structural parameters and unknown excitations on one hand, and to optimally mitigate excessive vibration of the building structure on the other hand. The basic equations for the identification of time-varying structural parameters and unknown excitations of a semi-active damper-controlled building structure are first presented. The basic equations for semi-active vibration control of the building structure with time-varying structural parameters and unknown excitations are then put forward. The numerical algorithm is finally followed to show how the identification and the control can be performed simultaneously. The results from the numerical investigation of an example building demonstrate that the proposed method is feasible and accurate.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.246-257
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• 2010

Autonomous guided robot navigation which consists of following unknown paths and avoiding unknown obstacles has been a fundamental technique for unmanned robots in outdoor environments. The unknown path following requires techniques such as path recognition, path planning, and robot pose estimation. In this paper, we propose a novel sensor fusion system for autonomous guided robot navigation in outdoor environments. The proposed system consists of three monocular cameras and an array of nine infrared range sensors. The two cameras equipped on the robot's right and left sides are used to recognize unknown paths and estimate relative robot pose on these paths through bayesian sensor fusion method, and the other camera equipped at the front of the robot is used to recognize abrupt curves and unknown obstacles. The infrared range sensor array is used to improve the robustness of obstacle avoidance. The forward camera and the infrared range sensor array are fused through rule-based method for obstacle avoidance. Experiments in outdoor environments show the mobile robot with the proposed sensor fusion system performed successfully real-time autonomous guided navigation.

• Journal of Preventive Medicine and Public Health
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• v.54 no.4
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• pp.245-250
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• 2021

Objectives: Jeju Province in Korea reported 627 coronavirus disease 2019 (COVID-19) cases between January 20, 2020, and March 31, 2021. This study analyzed the sources of infection among confirmed cases in Jeju Province, a self-governed island. Methods: The sources of infection were broadly categorized as follows: (1) infections from overseas (confirmed patients who reported travel overseas or contact with overseas travelers); (2) infections from outside Jeju Province (confirmed patients who had visited other provinces or had contact with individuals who had traveled to other provinces in Korea); and (3) unknown sources of infection (confirmed patients who were infected following contact with an infected person whose source of infection was unknown). The chi-square test was used to analyze the differences in the distributions of related variables for each source of infection. Results: Of the 627 confirmed cases, 38 (6.1%) were infections from overseas sources, 199 (31.7%) were from outside of Jeju Province, and 390 (62.2%) were from unknown sources. Jeju Province had no cases with an unknown source of infection during the first and second waves of the nationwide outbreak. Conclusions: Infections from overseas sources could be blocked from spreading to local communities in Jeju Province by conducting screening at the airport, along with the preemptive suspension of visa-free entry. In addition, considering the scale of the nationwide outbreak, measures must be established to delay outbreaks from unknown sources of infection caused by sources outside Jeju Province.

• Smart Structures and Systems
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• v.24 no.2
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• pp.209-221
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• 2019

The classical Kalman filter (KF) provides a practical and efficient way for state estimation. It is, however, not applicable when the external excitations applied to the structures are unknown. Moreover, it is known the classical KF is only suitable for linear systems and can't handle the nonlinear cases. The aim of this paper is to extend the classical KF approach to circumvent the aforementioned limitations for the joint estimation of structural states and the unknown inputs. On the basis of the scheme of the classical KF, analytical recursive solution of an improved KF approach is derived and presented. A revised form of observation equation is obtained basing on a projection matrix. The structural states and the unknown inputs are then simultaneously estimated with limited measurements in linear or nonlinear systems. The efficiency and accuracy of the proposed approach is verified via a five-story shear building, a simply supported beam, and three sorts of nonlinear hysteretic structures. The shaking table tests of a five-story building structure are also employed for the validation of the robustness of the proposed approach. Numerical and experimental results show that the proposed approach can not only satisfactorily estimate structural states, but also identify unknown loadings with acceptable accuracy for both linear and nonlinear systems.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.646-647
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• 2005

A recently published paper demonstrates the utility of allowing delays in state estimators for linear systems with unknown inputs. In this note, we point out an error in the derivation of the estimator.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.682-688
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• 2006

This paper deals with the delay-dependent and rate-independent stabilization of systems with multiple unknown time-varying delays and time-varying structured uncertainties. All the linear matrix inequalities based conditions are derived by employing free-weighting matrices to express the relationships between the terms in the Leibniz-Newton formula. The criteria do not require any tuning parameters. Numerical examples demonstrate the validity of the method.

• The Pure and Applied Mathematics
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• v.15 no.1
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• pp.19-34
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• 2008

A new algorithm for the solution of an inverse problem of determining unknown source parameter in a parabolic equation in reproducing kernel space is considered. Numerical experiments are presented to demonstrate the accuracy and the efficiency of the proposed algorithm.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.294-300
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• 2008

This study was conducted to investigate what to consider for active response in the intrusion detection system, how to implement active response, and 6-phase response models to respond actively, including the active response scheme to detect unknown attacks by using a traffic measuring engine and an anomaly detection engine.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2543-2545
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• 2005

It is well known that the orthogonal function is a very useful to estimate an unknown inputs in the linear dynamic systems for its recursive algebraic algorithm. At this aspects, derivative operation(matrix) of orthogonal functions(walsh, block pulse and haar) are introduced and shown how it can useful to design an UIO(unknown inputs observer) design.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.892-895
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• 1996

An unknown input observer is proposed that can be used in wheelbase preview control of commercial vehicles. The preview and state information, required to calculate actuator force, are reconstructed from the measurement variables such as heave and pitch acceleration. Gain matrix of observer is optimally selected so that influence of system and measurement noises on the estimation error can be minimized. Estimated preview information requires low pass filtering to eliminate high frequency components resulting from differentiation of noisy output signals. Effectiveness of the proposed method is demonstrated by numerical simulation of half car model.