• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.185-190
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• 2009

A scheme of expert system based on iterative learning control is proposed. Iterative learning control can obtain control experience from the historical data to build the knowledge base of expert system. Considering some uncertain factors, a flexible measure is adopted in iterative learning control (ILC). Simulation proves the feasibility and effect of the air conditioning control expert system based on flexible iterative learning control (F-ILC). Finally, a feedback compensation unit is incorporated against irregular heavy disturbance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.621-624
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• 2017

In this paper, we propose a protocol synchronizing to packet trains in a underwater acoustic networks with limitations such as long propagation delay, low data rate, high packet loss. The proposed protocol employs an one-way communication scheme to calculate packet arrival time differences of consecutively transferred packets and minimizes uncertain variation effect of long propagation delay. Simulation results shows the superiority of our protocol, compared with a previously proposed one under the given network conditions.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.733-738
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• 2004

This paper deals with feedback control of a hydraulic unit for direct yaw moment control, a method used to actively maintain the dynamic stability of an automobile. The uncertain parameters and complex structure naturally call for empirical modeling of the hydraulic unit, which readily results in a control-oriented model with high fidelity. The identified model is cross-validated against experimental data under various conditions, which helps to establish model uncertainty. Then, the $H_{\infty}$ optimization technique is employed to synthesize a controller with guaranteed robust stability and performance against the model uncertainty. The performance of the synthesized controller is verified using experimental results, which shows the viability of the proposed approach in a real-world application.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.05a
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• pp.155-157
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• 2013

Ground source heat pump(GSHP) systems have been attracted as high-efficient energy-saving technology, but the building clients and designers have hesitated to use GSHP systems which is a expensive initial installation and a uncertain economic feasibility. Therefore In order to reduce the initial cost, many researchers have focused on the energy-pile system using the structure of the building as a heat exchanger. Even though many of experimental studies for energy pile system have been conducted, there was not enough data of a quantitative evaluation with the economic analysis and comprehensive analysis for energy-pile. In this study, the feasibility study for the energy pile system with a barrette pile was conducted by the performance analysis and LCC assessment.

• Journal of Electrical Engineering and Technology
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• v.12 no.3
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• pp.1299-1306
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• 2017

This paper presents a boundary tracking control of an agent. To this end, it is shown that the boundary tracking problem can be reformulated into a robust control of uncertain double integrator first. Then, a disturbance observer (DOB) based control is proposed solving the robust control problem. Unlike the existing results in the literature, the proposed DOB based control requires only the local position measurement of the boundary (not the gradient information). The performance of the proposed control is demonstrated for two cases: the measurement of the boundary is given in a continuous or discrete manner. Finally, it is shown that the proposed control can be used for environmental monitoring as well by showing that the agent follows a level curve of real environmental monitoring data.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.29.1-29
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• 2001

Neuro-fuzzy systems are multi-layered connectionist networks that realize the elements and functions of traditional fuzzy logic control/decision systems. A trained neuro-fuzzy system is isomorphic to a fuzzy logic system, and fuzzy IF-THEN rule knowledge can be explicitly extracted from the network. This talk presents a brief introduction to self-adaptive neuro-fuzzy systems and addresses some recent research results and applications. Most of the existing neuro-fuzzy systems exhibit several major drawbacks that lead to performance degradation. These drawbacks are the curse of dimensionality (i.e., fuzzy rule explosion), inability to re-structure their internal nodes in a changing environment, and their lack of ability to extract knowledge from a given set of training data. This talk focuses on our investigation of network architectures, self-adaptation algorithms, and efficient learning algorithms that will enable existing neuro-fuzzy systems to self-adapt themselves in an unstructured and uncertain environment.

• Structural Engineering and Mechanics
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• v.22 no.1
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• pp.53-70
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• 2006

The paper summarizes the dynamic-based assessment of a reinforced concrete arch bridge, dating back to the 50's. The outlined approach is based on ambient vibration testing, output-only modal identification and updating of the uncertain structural parameters of a finite element model. The Peak Picking and the Enhanced Frequency Domain Decomposition techniques were used to extract the modal parameters from ambient vibration data and a very good agreement in both identified frequencies and mode shapes has been found between the two techniques. In the theoretical study, vibration modes were determined using a 3D Finite Element model of the bridge and the information obtained from the field tests combined with a classic system identification technique provided a linear elastic updated model, accurately fitting the modal parameters of the bridge in its present condition. Hence, the use of output-only modal identification techniques and updating procedures provided a model that could be used to evaluate the overall safety of the tested bridge under the service loads.

• Journal of Magnetics
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• v.18 no.3
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• pp.357-360
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• 2013

A modified SQI method using magnetic leakage flux (MFL) signal for underground gas pipelines' defect detection and characterization is presented in this paper. Raw signals gathered using MFL signals include many unexpected noises and high frequency signals, uneven background signals, signals caused by real defects, etc. The MFL signals of defect free pipelines primarily consist of two kinds of signals, uneven low frequency signals and uncertain high frequency noises. Leakage flux signals caused by defects are added to the case of pipelines having defects. Even though the SQI (Self Quotient Image) is a useful tool to gradually remove the varying backgrounds as well as to characterize the defects, it uses the division and floating point operations. A modified SQI having low computational complexity without time-consuming division operations is presented in this paper. By using defects carved in real pipelines in the pipeline simulation facility (PSF) and real MFL data, the performance of the proposed method is compared with that of the original SQI.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.165-177
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• 2019

This paper considers corrosion wastage of two ship hull structure members as a part of investigated fuel oil tanks of 25 aging bulk carriers. Taking into account that many factors which influence corrosion wastage of ship hull structures are of uncertain nature, the related corrosion rate ($c_1$) is considered here as a real-valued continuous distribution, assuming that the corrosion wastage starts after 5, 6 or 7 years. In all considered cases, by using available data and applying three basic statistical tests, it is established that between two-parameter continuous distributions, normal, Weibull and logistic distributions are best fitted distributions for the mentioned corrosion rate ($c_1$). Note that the presented statistical, numerical and graphical results concerning two mentioned ship hull structure members allow to compare and discuss the corresponding probabilistic estimates for the corrosion rate ($c_1$).

• Educational Technology International
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• v.21 no.1
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• pp.69-95
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• 2020

The purpose of this research is to analyze the predictive powers of the five technostress creators - techno-overload, techno-invasion, techno-complexity, techno-insecurity, and techno-uncertainty - in job satisfaction and teacher efficacy of primary school teachers in Korea when they incorporated mobile technology into teaching. A questionnaire was designed to measure the level of teacher's stress from technology, job satisfaction and teacher efficacy. Data were collected from 164 teachers. Multiple regression analysis was conducted to explain which area of technostress led to varying degrees of job satisfaction and teacher efficacy. The results showed that techno-complexity alone predicted both job satisfaction and teacher efficacy. The reason why techno-complexity was the only predictor is that teachers would have first needed to understand how to incorporate mobile technology into teaching, before feeling overloaded, invaded, insecure, or uncertain about it, meaning techno-complexity precedes other constructs. Therefore, the only stress factor that affected them was how to understand the complexity of mobile technology. This calls for adequate training and support from schools and governments in order for the teachers to fully incorporate technology into teaching.