• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.1
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• pp.10-17
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• 2010

Safety-critical systems related to the railway communications are currently undergoing changes. Mechanical and electro-mechanical devices are being replaced by programmable electronics that are often controlled remotely via communication networks. Therefore designers and operators now not only have to contend with component failures and user errors, but also with the possibility that malicious entities are seeking to disrupt the services provided by theirs systems. Recognizing the safety-critical nature of the types of communications required in train control operations, the communications infrastructure will be required to meet a number of safety requirements such as system faults, user errors and the robustness in the presence of malicious attackers who are willing to take determined action to interfere in the correct operation of a system. In this paper, we proposed the safety strategies employed in the railway communications and a security mechanism for Korean railway communication system. Also, we presented the developed means for validation and determination of communication safety based on the proposed security mechanism in the railway system.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.1
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• pp.24-32
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• 2003

The PID controller has been widely used in industrial applications due to its simple structure and robustness. Even if it is initially well tuned, the PID controller must be retuned to maintain acceptable performance when there are system parameter changes due to the change of operation conditions. In this paper, a self-tuning control scheme which comprises a parameter estimator, a NN-based rule emulator and a PID controller is proposed, which can cope with changing environments. This method involves combining neural networks and real-coded genetic algorithms(RCGAs) with conventional approaches to provide a stable and satisfactory response. A RCGA-based parameter estimation method is first described to obtain the first-order with time delay model from over-damped high-order systems. Then, a set of optimum PID parameters are calculated based on the estimated model such that they cover the entire spectrum of system operations and an optimum tuning rule is trained with a BP-based neural network. A set of simulation works on systems with time delay are carried out to demonstrate the effectiveness of the proposed method.

• Journal of Biomedical Engineering Research
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• v.31 no.5
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• pp.351-358
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• 2010

In the automatic non-invasive blood pressure measurement device, the oscillometric method iswidely used. In the oscillometric method, the step-wise deflation has the advantage of the robustness for the motion artifacts than the linear deflation method. But it has the disadvantage of its longer measurement time because we need to detect two or more pulses in a certain cuff pressure step. In this study, we suggest the modified step-wise deflation method to overcome this limitation while maintaining the general concept of step-wise deflation. Using one valid pulse in each step and the deflating valve control during the diastolic period, the measurement time could be reduced. In order to verify the accuracy of the proposed algorithm, we compared the blood pressure values from the suggested method and the blood pressure values from the conventional auscultation method. The mean and standard deviation were -0.50${\pm}$5.3mmHg and 2.08${\pm}$4.75mmHg, for systolic and diastolic blood pressure respectively. The measurement time can be reduced up to the half of conventional step-wise deflation method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2667-2682
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• 2015

Due to the wide application of face recognition (FR) in information security, surveillance, access control and others, it has received significantly increased attention from both the academic and industrial communities during the past several decades. However, partial face occlusion is one of the most challenging problems in face recognition issue. In this paper, a novel method based on linear regression-based classification (LRC) algorithm is proposed to address this problem. After all images are downsampled and divided into several blocks, we exploit the evaluator of each block to determine the clear blocks of the test face image by using linear regression technique. Then, the remained uncontaminated blocks are utilized to partial occluded face recognition issue. Furthermore, an improved Distance-based Evidence Fusion approach is proposed to decide in favor of the class with average value of corresponding minimum distance. Since this occlusion removing process uses a simple linear regression approach, the completely computational cost approximately equals to LRC and much lower than sparse representation-based classification (SRC) and extended-SRC (eSRC). Based on the experimental results on both AR face database and extended Yale B face database, it demonstrates the effectiveness of the proposed method on issue of partial occluded face recognition and the performance is satisfactory. Through the comparison with the conventional methods (eigenface+NN, fisherfaces+NN) and the state-of-the-art methods (LRC, SRC and eSRC), the proposed method shows better performance and robustness.

• Structural Engineering and Mechanics
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• v.43 no.3
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• pp.371-394
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• 2012

Accurate finite element (FE) models are needed in many applications of Civil Engineering such as health monitoring, damage detection, structural control, structural evaluation and assessment. Model accuracy depends on both the model structure (the form of the equations) and the model parameters (the coefficients of the equations), and can be generally improved through that process of experimental reconciliation known as model updating. However, modelling errors, including (i) errors in the model structure and (ii) errors in parameters excluded from adjustment, may bias the solution, leading to an updated model which replicates measurements but lacks physical meaning. In this paper, an application of ambient-vibration-based model updating to a large-scale benchmark prototype of a building structure is reported in which both types of error are met. The error in the model structure, originating from unmodelled secondary structural elements unexpectedly working as resonant appendages, is faced through a reduction of the experimental modal model. The error in the model parameters, due to the inevitable constraints imposed on parameters to avoid ill-conditioning and under-determinacy, is faced through a multi-model parameterization approach consisting in the generation and solution of a multitude of models, each characterized by a different set of updating parameters. Results show that modelling errors may significantly impair updating even in the case of seemingly simple systems and that multi-model reasoning, supported by physical insight, may effectively improve the accuracy and robustness of calibration.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.13-23
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• 2001

Most current machine vision systems for industrial inspection were developed with one specific task in mind. Hence, these systems are inflexible in the sense that they cannot easily be adapted to other applications. In this paper, a general vision system framework has been developed that can be easily adapted to a variety of industrial web inspection problems. The objective of this system is to automatically locate and identify \\\"defects\\\" on the surface of the material being inspected. This framework is designed to be robust, to be flexible, and to be as computationally simple as possible. To assure robustness this framework employs a combined strategy of top-down and bottom-up control, hierarchical defect models, and uncertain reasoning methods. To make this framework flexible, a modular Blackboard framework is employed. To minimize computational complexity the system incorporates a simple multi-thresholding segmentation scheme, a fuzzy logic focus of attention mechanism for scene analysis operations, and a partitioning if knowledge that allows concurrent parallel processing during recognition.cognition.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.475-479
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• 2009

In ad hoc network, the scarce energy management of the mobile devices has become a critical issue in order to extend the network lifetime. Current research activity for the Minimum Energy Multicast (MEM) problem has been focused on devising efficient centralized greedy algorithms for static ad hoc networks. In this paper, we consider mobile ad hoc networks(MANETs) that could provide the reliable monitoring and control of a variety of environments for remote place. Mobility of MANET would require the topology change frequently compared with a static network. To improve the routing protocol in MANET, energy efficient routing protocol would be required as well as considering the mobility would be needed. In this paper, we propose a new method, the CACH(Context-aware Clustering Hierarchy) algorithm, a hybrid and clustering-based protocol that could analyze the link cost from a source node to a destination node. The proposed analysis could help in defining the optimum depth of hierarchy architecture CACH utilize. The proposed CACH could use localized condition to enable adaptation and robustness for dynamic network topology protocol and this provide that our hierarchy to be resilient. As a result, our simulation results would show that CACH could find energy efficient depth of hierarchy of a cluster.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.773-780
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• 1999

A digital tracking controller is proposed for micro electrostatic actuator with input nonlinearity, where disturbance observer is utilized in cooperation with inverse function. Generally the disturbance observer is announced to be robust to modeling uncertainty, and external disturbance. But, when the nonlinearity exists in the systems, the disturbance observer may not directly be applied to that system, because the nonlinearity may destabilize the overall system. Therefore, first, we linearize the nonlinear input characteristics of micro electrostatic actuator by the use of inverse function. Secondly, we apply disturbance observer to approximately linearized system for eliminating the residuals of nonlinearity and the modeling uncertainty. Then, we get the good properties of the disturbance rejection as well as the robustness due to the own nature of disturbance observer. In this case, we propose a sufficient condition for the robust stability of overall systems. Furthermore, we discuss the problem that may be exposed when disturbance observer is applied to the internally stable system with saturation, and analyze two methods to overcome input saturation problem in the sense of internal stability. Simulations have been carried out to show the effectiveness of the proposed controller.

• Smart Structures and Systems
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• v.22 no.2
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• pp.167-174
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• 2018

Digital input and output modules are widely used to connect digital sensors and actuators to automation systems. Digital I/O modules provide flexible connectivity extension to numerous sensors and actuators and protect systems from high voltages and currents by isolation. Components in digital I/O modules are inevitably affected by operating and environmental conditions, such as high voltage, high current, high temperature, and temperature cycling. Because digital I/O modules transfer signals or isolate the systems from unexpected voltage and current transients, their failures may result in signal transmission failures and damages to sensitive circuitry leading to system malfunction and system shutdown. In this study, the lifetime of optocouplers, one of the critical components in digital I/O modules, was predicted using Bayesian tracking approaches. Accelerated degradation tests were conducted for collecting the critical performance parameter of optocouplers, current transfer ratio (CTR), during their lifetime. Bayesian tracking approaches, including extended Kalman filter and particle filter, were applied to predict the failure. The performance of each prognostic algorithm was then compared using accuracy and robustness-based performance metrics.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.298-301
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• 1999

This paper presents a design technique based on the root locus method fur a class of $n^{th}$ order plants using PID (Proportional-Integral-Derivative) x (n-1) stage PD controller. It is intended to satisfy both transient and steady state response specifications. This controller can be used instead of a conventional PID controller for the higher order plants to obtain better performances. The controlled system is approximated as a stable and robust second order controlled system. Only adjusting the controller gain, the desired performances of the controlled system are satisfied. For the stable plant including the plant with small dead time, the controlled system is made robustly stable. In case of the unstable plant, when the controller gain is adjusted higher than the critical value, the unstable plant can also be made stable. Robustness properties given by this controller proposed in this paper have also been demonstrated by numerical examples.