• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.248-254
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• 2018

In this paper, a Monte Carlo-based Recursive Least Square(MC-RLS) method is presented to directly identify the inverse model of the dynamical system. Although a RLS method has been used for the identification based on the deterministic data in the closed loop controlled form, it would be better for RLS to identify the model with random data. In addition, the inverse model obtained by inverting the identified forward model may not work properly. Therefore, MC-RLS can be used for the inverse model identification without proceeding a numerical inversion of an identified forward model. The performance of the proposed method is verified through experimental studies on a control moment gyroscope.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.179-191
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• 2009

A stochastic response spectrum method is proposed for simple evaluation of the structural response of an actively controlled aseismic structure. The response spectrum is constructed assuming a linear structure with an active mass damper (AMD) system, and an earthquake wave model given by the product of a non-stationary envelope function and a stationary Gaussian random process with Kanai-Tajimi power spectral density. The control design is executed using a linear quadratic Gaussian control strategy for an enlarged state space system, and the response amplification factor is given by the combination of the obtained statistical response values and extreme value theory. The response spectrum thus produced can be used for simple dynamical analyses. The response factors obtained by this method for a multi-degree-of-freedom structure are shown to be comparable with those determined by numerical simulations, demonstrating the validity and utility of the proposed technique as a simple design tool. This method is expected to be useful for engineers in the initial design stage for structures with active aseismic control.

• International Journal of Contents
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• v.9 no.4
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• pp.1-10
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• 2013

The electroencephalogram (EEG) time series is a measure of electrical activity received from multiple electrodes placed on the scalp of a human brain. It provides a direct measurement for characterizing the dynamic aspects of brain activities. These EEG signals are formed from a series of spatial and temporal data with multiple dimensions. Missing data could occur due to fault electrodes. These missing data can cause distortion, repudiation, and further, reduce the effectiveness of analyzing algorithms. Current methodologies for EEG analysis require a complete set of EEG data matrix as input. Therefore, an accurate and reliable imputation approach for missing values is necessary to avoid incomplete data sets for analyses and further improve the usage of performance techniques. This research proposes a new method to automatically recover random consecutive missing data from real world EEG data based on Linear Dynamical System. The proposed method aims to capture the optimal patterns based on two main characteristics in the coevolving EEG time series: namely, (i) dynamics via discovering temporal evolving behaviors, and (ii) correlations by identifying the relationships between multiple brain signals. From these exploits, the proposed method successfully identifies a few hidden variables and discovers their dynamics to impute missing values. The proposed method offers a robust and scalable approach with linear computation time over the size of sequences. A comparative study has been performed to assess the effectiveness of the proposed method against interpolation and missing values via Singular Value Decomposition (MSVD). The experimental simulations demonstrate that the proposed method provides better reconstruction performance up to 49% and 67% improvements over MSVD and interpolation approaches, respectively.

• Advances in aircraft and spacecraft science
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• v.5 no.2
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• pp.205-223
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• 2018

During launch a spacecraft is subjected to a variety of dynamical loads transmitted through the launcher to spacecraft interface or air-born transmission excitations in the acoustic pressure field inside the fairing. As a result, spacecraft are tested on ground to ensure and demonstrate the global integrity of the structure against these loads, to screen the flight hardware for quality of workmanship and to validate mathematical models. This paper addresses the numerical modelling and simulation of the low frequency sine and random vibration tests performed on electrodynamic shaker facilities to comprise the mechanical-borne transmission loads through the launcher to spacecraft interface. Consequently, the paper reviews techniques and methodologies to derive a reliable and representative coupled virtual vibration testing simulation environment based on experimental data. These technologies are explored with the main objectives to ensure a stable, reliable and accurate control while testing. As a result, the use of the derived simulation models in combination with the added value of improved control and signal processing algorithms can lead to a safer and smoother vibration test control of the entire environmental test campaign.

• Journal of Haehwa Medicine
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• v.10 no.1
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• pp.365-374
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• 2001

The brain is one of the most complex systems in nature. Brain waves, or the "EEG", are electrical signals that can be recorded from the brain, either directly or through the scalp. The kind of brain wave recorded depends on the behavior of the animal, and is the visible evidence of the kind of neuronal (brain cell) processing necessary for that behavior. But, EEG had been considered as a virtually infinite-dimensional random signal. However, nonlinear dynamics light on dynamical aspects of the human EEG. The methods of nonlinear dynamics provide excellent tolls for the study of multi-variable, complex system such as EEG. In this study, 20 persons seperated in 2 groups were examined with EEG, one group stimulated on specific area of the sole of the foot with footbed inside the shoes. This experiment resulted in at the group stimulated on specific area of the sole of the foot correlation dimension of P4 and O1 channels increased significantly. Therefore. we obserbed that stimulation on specific area of the body had a constant effections on the specific channels.

• Smart Structures and Systems
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• v.9 no.3
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• pp.231-251
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• 2012

The stochastic optimal control for a piezoelectric spherically symmetric shell subjected to stochastic boundary perturbations is constructed, analyzed and evaluated. The stochastic optimal control problem on the boundary stress output reduction of the piezoelectric shell subjected to stochastic boundary displacement perturbations is presented. The electric potential integral as a function of displacement is obtained to convert the differential equations for the piezoelectric shell with electrical and mechanical coupling into the equation only for displacement. The displacement transformation is constructed to convert the stochastic boundary conditions into homogeneous ones, and the transformed displacement is expanded in space to convert further the partial differential equation for displacement into ordinary differential equations by using the Galerkin method. Then the stochastic optimal control problem of the piezoelectric shell in partial differential equations is transformed into that of the multi-degree-of-freedom system. The optimal control law for electric potential is determined according to the stochastic dynamical programming principle. The frequency-response function matrix, power spectral density matrix and correlation function matrix of the controlled system response are derived based on the theory of random vibration. The expressions of mean-square stress, displacement and electric potential of the controlled piezoelectric shell are finally obtained to evaluate the control effectiveness. Numerical results are given to illustrate the high relative reduction in the root-mean-square boundary stress of the piezoelectric shell subjected to stochastic boundary displacement perturbations by the optimal electric potential control.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.425-431
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• 2020

Recent advancements in industries and technologies have resulted in an increase in the volume of transportation, management, and distribution of logistics. Radio-frequency identification (RFID) technologies have been developed to efficiently manage such a large amount of logistics information. The use of RFID for management is being applied not only to the logistics industry, but also to the power transmission and energy management field. However, due to the limitation of program development capacity, the RFID device is limited in development, and this limitation is vulnerable to security because the existing strong encryption method cannot be used. For this reason, we designed a chaotic system for security with simple operations that are easy to apply to such a restricted environment of RFID. The designed system is a two-dimensional tent map chaotic system. In order to solve the problem of a biased distribution of signals according to the parameters of the chaotic dynamical system, the system has a cryptographic parameter(𝜇₁), a distribution parameter(𝜇₂), and a parameter(𝜃), which is the constant point, ID value, that can be used as a key value. The designed RFID authentication system is similar to random numbers, and it has the characteristics of chaotic signals that can be reproduced with initial values. It can also solve the problem of a biased distribution of parameters, so it is deemed to be more effective than the existing encryption method using the chaotic system.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.981-986
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• 2020

The Internet of Things refers to a space-of-things connection network configured to allow things with built-in sensors and communication functions to interact with people and other things, regardless of the restriction of place or time.IoT is a network developed for the purpose of services for human convenience, but the scope of its use is expanding across industries such as power transmission, energy management, and factory automation. However, the communication protocol of IoT, MQTT, is a lightweight message transmission protocol based on the push technology and has a security vulnerability, and this suggests that there are risks such as personal information infringement or industrial information leakage. To solve this problem, we designed a synchronous MQTT security channel that creates a secure channel by using the characteristic that different chaotic dynamical systems are synchronized with arbitrary values in the lightweight message transmission MQTT protocol. The communication channel we designed is a method of transmitting information to the noise channel by using characteristics such as random number similarity of chaotic signals, sensitivity to initial value, and reproducibility of signals. The encryption method synchronized with the proposed key value is a method optimized for the lightweight message transmission protocol, and if applied to the MQTT of IoT, it is believed to be effective in creating a secure channel.