• 한국의학물리학회지:의학물리
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• 제6권2호
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• pp.103-109
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• 1995

자율신경계는 서로 상반되게 작용하는 교감신경과 부교감신경으로 구성되어 그 활성의 균형에 의해 신체의 향상성이 유지된다. 자율신경계는 각종 스트레스나 질환에 의해 그 활성이 변화한다. 그러나 자율신경계의 메카니즘은 너무나 복잡하여 해석이 용이하지 않은 관계로 인체에서 유기되는 여러가지 생체신호중에서 자율신경에 의해 지배되는 심전도 신호와 호흡을 매개변수로하여 자율신경의 활성도를 측정하는 시스템의 설계와 제작이 본 연구의 목적이다. 본 논문을 수행하기 위해서 심전도 신호 증폭기, 호흡변위 증폭기, interval time generator 및 처리 소프트웨어 등을 제작하였다. 그리고 심전도 신호와 호흡요소에 대한 power spectrum을 나타낼 뿐만 아니라 이들을 합성하여 하나의 graph로 표현할 수 있도록 하였다.

• International Journal of Control, Automation, and Systems
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• 제4권5호
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• pp.592-600
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• 2006

The pattern recognition of the complicated grasping operation based on electroencephalography (simply named as EEG) is very helpful on realtime control of the robotic hand. In the paper, a new spectral feature analysis method based on Band Pass Filter (simply named as BPF) and Power Spectral Analysis (simply named as PSA) is presented for discriminating the complicated grasping operations. By analyzing the spectral features of grasping operations with the use of the two-channel EEG measurement system and the pattern recognition of the BP neural network, the degree of recognition by the traditional spectral feature method based on FFT and the new spectral features method based on BPF and PSA could be compared. The results show that the proposed method provides highly improved performance than the traditional one because the new method has two obvious advantages such as high recognition capability and the fast learning speed.

• 자원환경지질
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• 제17권4호
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• pp.237-243
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• 1984

최대 엔트로피 스펙트럼 분석 (Maximum entropy spectral analysis)에 관한 Burg알고리즘 (algorithm)의 계산효율과 안정성에 대하여 검토하였다. Burg의 방법은 Yule-Walker의 방법보다 계산효율이 낮을 뿐만 아니라 그의 수학적 불합리성으로 인하여 간혹 불안전할 때가 있다. 이러한 불합리성을 인공 시계열의 해석을 통하여 증명한 후 보다 안정하고 효과적인 방법을 소개하였다. 또한 파워 스펙트럼밀도 (Power spectral density)의 계산에서 Goertzel알고리즘을 이용하는 효율적인 방법도 소개하였다.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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• pp.435-440
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• 2006

In order to understand changes of water temperature for thermal discharge of Hadong power plant in Gwangyang and Jinju Bay, it was analyzed for temperature data of representative season by MEM(Maximum entropy method) that is one of the spectral analysises. And due to understand effect of thermal discharge at each point, analyzed spectral data showed reactive energy rate of reference point by calculating energy from 24 time period to height frequency zone. As a result of spectral analysis, it showed that there were 9 points which are largely effected, 7 points which will be estimated, 6 points which is difficult to estimate, 14 points which rarely effected by thermal discharge.

• Wind and Structures
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• 제39권1호
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• pp.1-14
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• 2024

Widespread damages from extreme winds have attracted lots of attentions of the resilience assessment of power distribution systems. With many related environmental parameters as well as numerous power infrastructure components, such as poles and wires, the increased challenge of power asset management before, during and after extreme events have to be addressed to prevent possible cascading failures in the power distribution system. Many extreme winds from weather events, such as hurricanes, generate widespread damages in multiple areas such as the economy, social security, and infrastructure management. The livelihoods of residents in the impaired areas are devastated largely due to the paucity of vital utilities, such as electricity. To address the challenge of power grid asset management, power system clustering is needed to partition a complex power system into several stable clusters to prevent the cascading failure from happening. Traditionally, system clustering uses the Binary Decision Diagram (BDD) to derive the clustering result, which is time-consuming and inefficient. Meanwhile, the previous studies considering the weather hazards did not include any detailed weather-related meteorologic parameters which is not appropriate as the heterogeneity of the parameters could largely affect the system performance. Therefore, a fragility-based network hierarchical spectral clustering method is proposed. In the present paper, the fragility curve and surfaces for a power distribution subsystem are obtained first. The fragility of the subsystem under typical failure mechanisms is calculated as a function of wind speed and pole characteristic dimension (diameter or span length). Secondly, the proposed fragility-based hierarchical spectral clustering method (F-HSC) integrates the physics-based fragility analysis into Hierarchical Spectral Clustering (HSC) technique from graph theory to achieve the clustering result for the power distribution system under extreme weather events. From the results of vulnerability analysis, it could be seen that the system performance after clustering is better than before clustering. With the F-HSC method, the impact of the extreme weather events could be considered with topology to cluster different power distribution systems to prevent the system from experiencing power blackouts.

• Structural Engineering and Mechanics
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• 제53권3호
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• pp.607-623
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• 2015

The wind-induced dynamic response of large-span flexible structures includes two important components-background response and resonant response. However, it is difficult to separate the two components in time-domain. To solve the problem, a relational expression of wavelet packet coefficients and power spectrum is derived based on the principles of digital signal processing and the theories of wavelet packet analysis. Further, a new approach is proposed for separation of the background response from the resonant response. Then a numerical example of frequency detection is provided to test the accuracy and the spectral resolution of the proposed approach. In the engineering example, the approach is applied to compute the power spectra of the wind-induced response of a large-span roof structure, and the accuracy of spectral estimation for stochastic signals is verified. The numerical results indicate that the proposed approach is efficient and accurate with high spectral resolution, so it is applicable for power spectral computation of various response signals of structures induced by the wind. Moreover, the background and the resonant response time histories are separated successfully using the proposed approach, which is sufficiently proved by detailed verifications. Therefore, the proposed approach is a powerful tool for the verification of the existing frequency-domain formulations.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 춘계학술대회
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• pp.275-278
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• 1997

Standard methods estimating the power spectral density(PSD) from an irregularly sampled cardiac event series require deriving a new evenly-spaced signal applicable to those methods. To avoid that requirement, in this study, the power spectrum of heart rate variability was estimated by Lomb-Scargle's algorithm, which is a means of obtaining PSD estimates directly from irregularly sampled timeseries observed in astronomy. To assess the performance of Lomb-Scargle algorithm in the power spectral analysis of heart rate variability, it was applied to various cardiac event series derived through integral pulse frequency modulation model(IPFM) simulation and from real ECG signals, and the resultant power spectra was compared with those obtained by a conventional method based on the FFT. In result, it is concluded that Lomb-Scargle's periodogram is very effective in the power spectral analysis of heart rate variability, especially in the presence of arrhythmia and/or dropouts of cardiac events.

• 한국전문물리치료학회지
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• 제5권3호
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• pp.63-71
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• 1998

Trunk holding test (Sorensen test) appear to have more value than strength test in prediction the occurrence of low back pain. Electromyographic activity of trunk extensor muscles during these test may provide clues to the etiology of neuromuscular-based low back pain. This study investigated the difference in back muscle endurance between healthy adult men and women using surface electromyographic (EMG) power spectral analysis. Thirty hea1thy subjects (15 men and 15 women) performed an unsupported trunk holding test for 60 seconds. Recording surface electrodes were placed over the erector spinae medially and laterally at vertebral levels of $L_1$ and $L_5$. Slope of total frequency was evaluated using the MP100WSW Fast Fourier Transform spectrum analysis program. The slopes of all indices of back muscle fatigue, except right $L_5$, were significantly steeper in men than in women (p<0.05). Our results indicated that the trunk holding test using EMG power spectral analysis of erector spinae muscles is useful for the evaluation of fatigue rate of these muscles. Our results also showed a higher muscle endurance in healthy adult women than in men.

• 한국자동차공학회논문집
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• 제5권1호
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• pp.136-145
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• 1997

To analyzed ride quality and to predict durability in vehicle dynamics, it is essential to describe a road surface profile precisely. This paper presents a technique to generate road surface profiles in a spatial domain by using a power spectral density function. A single track power spectral density function is proposed to describe a road surface profile, which is also applicable for multi-track vehicle response analysis, The derived road surfaces are compared to ISO(International Organization for Standardization) standards and classifications, proposed by the MIRA(Motor Industry Research Association). The methodology in this paper is also proposed to generate road roughness description with a limited external data. A small amount of external curve data is combined with an internal PSD function to generate road surface roughness in a spatial domain.

• Journal of Dental Anesthesia and Pain Medicine
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• 제17권4호
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• pp.241-251
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• 2017

Devices that monitor the depth of hypnosis based on the electroencephalogram (EEG) have long been commercialized, and clinicians use these to titrate the dosage of hypnotic agents. However, these have not yet been accepted as standard monitoring devices for anesthesiology. The primary reason is that the use of these monitoring devices does not completely prevent awareness during surgery, and the development of these devices has not taken into account the neurophysiological mechanisms of hypnotic agents, thus making it possible to show different levels of unconsciousness in the same brain status. An alternative is to monitor EEGs that are not signal processed with numerical values presented by these monitoring devices. Several studies have reported that power spectral analysis alone can distinguish the effects of different hypnotic agents on consciousness changes. This paper introduces the basic concept of power spectral analysis and introduces the EEG characteristics of various hypnotic agents that are used in sedation.