• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.956-962
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• 2008

This paper is devoted to yarn tension control problem in winding machines. The passive take-up unit is replaced by active one with ADRC(Active Disturbance Rejection Control) and it was compared with the method using conventional PD(Proportional-Derivative) controller. The main part of ADRC is ESO(Extended State Observer) which continuously estimates nonlinearities of the system, such as intrinsic nonlinearity, external disturbance and sensor noise. Then the estimated nonlinearity is used to compensate the real one, thus making controlled system linear. A number of experiments have been conducted in order to verify the performance of the original winding system to the modified one. Experiments have shown improved efficiency of the system with adopting active yarn tension control. Experimental results show that the ADRC achieves a better tension response than PD controller and is robust to parameters variation.

• Journal of KSNVE
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• v.9 no.5
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• pp.1019-1028
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• 1999

Free vibration characteristics of cantilevered laminated composite beams with a transverse non0propagating open carck are investigated. In the present analysis a special ply-angle distribution referred to as asymmetric stiffness configuration inducing the elastic coupling between chord-wise bending and extension is considered. The open crack is modelled as an equivalent rotational spring whose spring constant is calculated on the basis of fracture mechanics of composite material structures. Governing equations of a composite beam with a open crack are derived via Hamilton's Principle and Timoshenko beam theory encompassing transverse shear and rotary inertia effect. the effects of various parameters such as the ply angle, fiber volume fraction, crack depth, crack position and transverse shear on the free vibration characteristics of the beam with a crack is highlighted. The numerical results show that the natural frequencies obtained from Timoshenko beam theory are always lower than those from Euler beam theory. The presence of intrinsic cracks in anisotropic composite beams modifies the flexibility and in turn free vibration characteristics of the structures. It is revealed that non-destructive crack detection is possible by analyzing the free vibration responses of a cracked beam.

• Health Policy and Management
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• v.30 no.1
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• pp.15-25
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• 2020

While healthcare data sets include extensive information about patients, many researchers have limitations in analyzing them due to their intrinsic characteristics such as heterogeneity, longitudinal irregularity, and noise. In particular, since the majority of medical history information is recorded in text codes, the use of such information has been limited due to the high dimensionality of explanatory variables. To address this problem, recent studies applied word embedding techniques, originally developed for natural language processing, and derived positive results in terms of dimensional reduction and accuracy of the prediction model. This paper reviews the deep learning-based natural language processing techniques (word embedding) and summarizes research cases that have used those techniques in the health care field. Then we finally propose a research framework for applying deep learning-based natural language process in the analysis of domestic health insurance data.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.05
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• pp.47-50
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• 1990

In this study, the degree of spectral transfer to lower frequency caused by accumulation of Latic acid inside the muscle is estimated the convintional dip analysis, zero-crossing method and FFT method have intrinsic errors and estimation problems in case of severe noise. The new spectral analysis method using "$2^{nd}$ order Maximum Entropy Method" was applied to estimate mean frequency and we confirmed that this new method yields fast and reliable estimation over the FFT method.

• Genomics & Informatics
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• v.6 no.3
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• pp.126-129
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• 2008

The robust identification and comprehensive profiling of copy number alterations (CNAs) is highly challenging. The amount of data obtained from high-throughput technologies such as array-based comparative genomic hybridization is often too large and it is required to develop a comprehensive and versatile tool for the detection and visualization of CNAs in a genome-wide scale. With this respective, we introduce a software framework, CGHscape that was originally developed to explore the CNAs for the study of copy number variation (CNV) or tumor biology. As a standalone program, CGHscape can be easily installed and run in Microsoft Windows platform. With a user-friendly interface, CGHscape provides a method for data smoothing to cope with the intrinsic noise of array data and CNA detection based on SW-ARRAY algorithm. The analysis results can be demonstrated as log2 plots for individual chromosomes or genomic distribution of identified CNAs. With extended applicability, CGHscape can be used for the initial screening and visualization of CNAs facilitating the cataloguing and characterizing chromosomal alterations of a cohort of samples.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.418-421
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• 2003

Today, much terminologies such as noise spectrum, Sharpness, contrast, MTF had been defined for Image quality revaluation of radiation Image. Since development of Xeroradiography In the 1970s, Digital radiation detector that use amorphous selenium was developed. The aim of this research is to analyze physical phenomenon of digital radiation detector that use amorphous selenium. Result of Monte Carlo simulations on amorphous selenium based on physical properties(creation of electron-hole pairs) by induced x-ray are described. From the simulation, intrinsic point spread function(PSF) was found and used to observe modulation transfer function(MTF). We investigated how PSF and MTF changed with various x-ray energy. This result can be used to design digital x-ray detector based on a-Se.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1755-1777
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• 2022

The development of wireless communication technology has led to the underutilization of radio spectra. To address this limitation, an intelligent cognitive radio network was developed. Specific emitter identification (SEI) is a key technology in this network. However, in realistic non-cooperative scenarios, the system may detect signal classes beyond those in the training database, and only a few labeled signal samples are available for network training, both of which deteriorate identification performance. To overcome these challenges, a meta-learning-based open-set identification system is proposed for SEI. First, the received signals were pre-processed using bi-spectral analysis and a Radon transform to obtain signal representation vectors, which were then fed into an open-set SEI network. This network consisted of a deep feature extractor and an intrinsic feature memorizer that can detect signals of unknown classes and classify signals of different known classes. The training loss functions and the procedures of the open-set SEI network were then designed for parameter optimization. Considering the few-shot problems of open-set SEI, meta-training loss functions and meta-training procedures that require only a few labeled signal samples were further developed for open-set SEI network training. The experimental results demonstrate that this approach outperforms other state-of-the-art SEI methods in open-set scenarios. In addition, excellent open-set SEI performance was achieved using at least 50 training signal samples, and effective operation in low signal-to-noise ratio (SNR) environments was demonstrated.

• Journal of The Korean Association For Science Education
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• v.26 no.5
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• pp.660-673
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• 2006

There have been many attempts to determine the value and the role of school laboratory experiment, but it seems hard to find consensus among these attempts from the perspective of education. This difficulty seems mainly due to disagreement on the concept of education, which has caused an instrumental attitude considering the school laboratory only as a means of developing science or pursuing various functions of school. However, the Endogenous Theory of Education (ETE), which claims education as 'a form of life', has recently paved the way for laboratory experiment to be justified as an opportunity of 'educooperation' allowing students to experience the intrinsic values of education in the medium of science. According to this theory, it is not the detailed practicals but the whole context where the laboratory activity is situated that matters in revealing the inherent educational phenomena. Through this new perspective, I observed two biology laboratory classes in a high school and analyzed the pattern of teacher-student and student-student interactions. Some meaningful educooperation was found in students' chattering, which has been traditionally considered as merely noise in the classroom, rather than in teacher-student interactions. This study discusses the reasons for these findings in detail and culminates in suggesting ways for accentuating the educational aspect of school laboratory activity.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.335-347
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• 2013

There are various types of real world signals. For example, an electrocardiogram(ECG) represents myocardium activities (contraction and relaxation) according to the beating of the heart. ECG can be expressed as the fluctuation of ampere ratings over time. A signal is a composite of various types of signals. An orchestra (which boasts a beautiful melody) consists of a variety of instruments with a unique frequency; subsequently, each sound is combined to form a perfect harmony. Various research on how to to decompose mixed stationary signals have been conducted. In the case of non-stationary signals, there is a limitation to use methodologies for stationary signals. Huang et al. (1998) proposed empirical mode decomposition(EMD) to deal with non-stationarity. EMD provides a data-driven approach to decompose a signal into intrinsic mode functions according to local oscillation through the identification of local extrema. However, due to the repeating process in the construction of envelopes, EMD algorithm is not efficient and not robust to a noise, and its computational complexity tends to increase as the size of a signal grows. In this research, we propose a new method to extract a local oscillation embedded in a signal by utilizing the second derivative.

• Smart Structures and Systems
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• v.15 no.2
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• pp.489-503
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• 2015

Response estimation at unmeasured locations using the limited number of measurements is an attractive topic in the field of structural health monitoring (SHM). Because of increasing complexity and size of civil engineering structures, measuring all structural responses from the entire body is intractable for the SHM purpose; the response estimation can be an effective and practical alternative. This paper investigates a response estimation technique based on the Kalman state estimator to combine multi-sensor data under non-zero mean input excitations. The Kalman state estimator, constructed based on the finite element (FE) model of a structure, can efficiently fuse different types of data of acceleration, strain, and tilt responses, minimizing the intrinsic measurement noise. This study focuses on the effects of (a) FE model error and (b) combinations of multi-sensor data on the estimation accuracy in the case of non-zero mean input excitations. The FE model error is purposefully introduced for more realistic performance evaluation of the response estimation using the Kalman state estimator. In addition, four types of measurement combinations are explored in the response estimation: strain only, acceleration only, acceleration and strain, and acceleration and tilt. The performance of the response estimation approach is verified by numerical and experimental tests on a simply-supported beam, showing that it can successfully estimate strain responses at unmeasured locations with the highest performance in the combination of acceleration and tilt.