• 한국통신학회논문지
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• 제19권4호
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• pp.761-771
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• 1994

본 논문에서는, 매우 낮은 전송율이 요구되는 음성통신의 환경하에서 CELP 음성 부호기를 사용할 경우, 스펙트럼에 대한 정보를 어떻게 효과적으로 나타낼 것인가에 대하여 고찰하였다. 구체적으로, 스펙트럼에 대한 정보를 나타내는 LPC 파라메타를 cepstrum으로 변형시키고, 변형된 LPC cepstrum계수들을 효과적으로 벡터 양자화하는 방법을 제시하였다. 벡터 양자화에 사용되는 코드-북의 설계를 위하여, 주파수 대역에서 서로 다른 의미를 갖는 세계의 cepstral distance measure들을 시도하였으며, 각각에 대한 성능이 분석되어졌다. 시뮬레이션을 통하여, 본 논문에서 제시한 LPC cepstral 벡터 양자화 방식이 스펙트럼에 대한 정보를 매우 효과적으로 나타낼 수 있음을 보였다.

• Wind and Structures
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• 제12권3호
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• pp.239-257
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• 2009

This paper develops and discusses a method by which it is possible to evaluate the Equivalent Static Force (ESF) of wind in the case of long-span bridges. Attention is focused on the alongwind direction. The study herein carried out deals with the classical problems of determining the maximum effects due to the alongwind action and the corresponding ESFs. The mean value of the maximum alongwind displacement of the deck is firstly obtained both by the spectral analysis and the Gust Response Factor (GRF) technique. Successively, in order to derive the other wind-induced effects acting on the deck, the Gust Effect Factor (GEF) technique is extended to long-span bridges. By adopting the GRF technique, it is possible to define the ESF that applied on the structure produces the maximum alongwind displacement. Nevertheless the application of the ESF so obtained does not furnish the correct maximum values of other wind-induced effects acting on the deck such as bending moments or shears. Based on this observation, a new technique is proposed which allows to define an ESF able to simultaneously reproduce the maximum alongwind effects of the bridge deck. The proposed technique is based on the GEF and the POD techniques and represents a valid instrument of research for the understanding of the wind excitation mechanism.

• Structural Engineering and Mechanics
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• 제26권6호
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• pp.687-707
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• 2007

High-tech facilities engaged in the production of semiconductors and optical microscopes are extremely expensive, which may require time-domain analysis for seismic resistant design in consideration of the most critical directions of seismic ground motions. This paper presents a framework for generating three-dimensional critical seismic ground acceleration time histories compatible with the response spectra specified in seismic design codes. The most critical directions of seismic ground motions associated with the maximum response of a high-tech facility are first identified. A new numerical method is then proposed to derive the power spectrum density functions of ground accelerations which are compatible with the response spectra specified in seismic design codes in critical directions. The ground acceleration time histories for the high-tech facility along the structural axes are generated by applying the spectral representation method to the power spectrum density function matrix and then multiplied by envelope functions to consider nonstationarity of ground motions. The proposed framework is finally applied to a typical three-story high-tech facility, and the numerical results demonstrate the feasibility of the proposed approach.

• Wind and Structures
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• 제31권3호
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• pp.217-227
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• 2020

Based on translation models, both Gaussian and non-Gaussian wind fields are generated using spectral representation method for investigating the influence of non-Gaussian characteristics and directivity effect of wind load on fatigue damage of wind turbine. Using the blade aerodynamic model and multi-body dynamics, dynamic responses are calculated. Using linear damage accumulation theory and linear crack propagation theory, crack initiation life and crack propagation life are discussed with consideration of the joint probability density distribution of the wind direction and mean wind speed in detail. The result shows that non-Gaussian characteristics of wind load have less influence on fatigue life of wind turbine in the area with smaller annual mean wind speeds. Whereas, the influence becomes significant with the increase of the annual mean wind speed. When the annual mean wind speeds are 7 m/s and 9 m/s at hub height of 90 m, the crack initiation lives under softening non-Gaussian wind decrease by 10% compared with Gaussian wind fields or at higher hub height. The study indicates that the consideration of the influence of softening non-Gaussian characteristics of wind inflows can significantly decrease the fatigue life, and, if neglected, it can result in non-conservative fatigue life estimates for the areas with higher annual mean wind speeds.

• Wind and Structures
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• 제7권6호
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• pp.421-447
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• 2004

This paper presents a time domain approach for predicting buffeting response of long suspension bridges under skew winds. The buffeting forces on an oblique strip of the bridge deck in the mean wind direction are derived in terms of aerodynamic coefficients measured under skew winds and equivalent fluctuating wind velocities with aerodynamic impulse functions included. The time histories of equivalent fluctuating wind velocities and then buffeting forces along the bridge deck are simulated using the spectral representation method based on the Gaussian distribution assumption. The self-excited forces on an oblique strip of the bridge deck are represented by the convolution integrals involving aerodynamic impulse functions and structural motions. The aerodynamic impulse functions of self-excited forces are derived from experimentally measured flutter derivatives under skew winds using rational function approximations. The governing equation of motion of a long suspension bridge under skew winds is established using the finite element method and solved using the Newmark numerical method. The proposed time domain approach is finally applied to the Tsing Ma suspension bridge in Hong Kong. The computed buffeting responses of the bridge under skew winds during Typhoon Sam are compared with those obtained from the frequency domain approach and the field measurement. The comparisons are found satisfactory for the bridge response in the main span.

• 전기학회논문지
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• 제66권3호
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• pp.581-586
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• 2017

The well-known Integral Pulse Frequency Modulation (IPFM) cardiac oscillator has been used to generate the heart beat fluctuations as a representation of the modulatory autonomic nervous activity in terms of sympathetic and parasympathetic state. The IPFM model produces heartbeats by integrating the modulated sinusoid signals and applying the threshold of unity or chaotic threshold levels. This study aims at evaluating the performance of IPFM model by analyzing the influence of the threshold level with comparatively applying preset threshold of unity and Logistic-map and Henon-map chaotic-threshold. Based on our simulated results with interpreting the spectral features of Heart Rate Variability (HRV), we can conclude that the IPFM model with preset threshold level of unity can generate the optimal heartbeat variations int the sense of clinically valid heartbeats.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권5호
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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.

• Wind and Structures
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• 제38권1호
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• pp.1-13
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• 2024

In order to effectively simulate nonstationary stochastic turbulent wind fields, four separation hybrid (SEP-H) models are proposed in the present study. Based on the assumption that the lateral turbulence component at one single-point is uncorrelated with the longitudinal and vertical turbulence components, the fluctuating wind is separated into 2nV-1D and nV1D nonstationary stochastic vector processes. The first process can be expressed as double proper orthogonal decomposition (DPOD) or proper orthogonal decomposition and spectral representation method (POD-SRM), and the second process can be expressed as POD or SRM. On this basis, four SEP-H models of nonstationary stochastic turbulent wind fields are developed. In addition, the orthogonal random variables in the SEP-H models are presented as random orthogonal functions of elementary random variables. Meanwhile, the number theoretical method (NTM) is conveniently adopted to select representative points set of the elementary random variables. The POD-FFT (Fast Fourier transform) technique is introduced in frequency to give full play to the computational efficiency of the SEP-H models. Finally, taking a long-span bridge as the engineering background, the SEP-H models are compared with the dimension-reduction DPOD (DR-DPOD) model to verify the effectiveness and superiority of the proposed models.

• Wind and Structures
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• 제38권2호
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• pp.119-128
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• 2024

The aerodynamic damping is an essential factor that can considerably affect the dynamic response of the cable-stayed bridge induced by crosswind load. However, developing an accurate and efficient aerodynamic damping model is crucial for evaluating the crosswind load-induced response on cable-stayed bridges. Therefore, this study proposes a new method for identifying aerodynamic damping of the bridge structures under crosswind load using an extended Kalman filter (EKF) and the particle filter (PF) algorithm. The EKF algorithm is introduced to capture the aerodynamic damping ratio. PF technique is used to select the optimal spectral representation of the noise. The effectiveness and accuracy of the proposed solution were investigated through full-scale vibration measurement data of the crosswind-induced on the bridge's girder. The results show that the proposed solution can generate an efficient and robust estimation. The errors between the target and extracted values are around 0.01mm and 0.003^o, respectively, for the vertical and torsional motion. The relationship between the amplitude and the aerodynamic damping ratio is linear for small reduced wind velocity and nonlinear with the increasing value of the reduced wind velocity. Finally, the results show the influence of the level of noise.

• 대한원격탐사학회지
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• 제39권6_1호
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• pp.1413-1425
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• 2023

기후변화로 인한 대형 산불의 빈도가 증가함에 따라 극심한 인명 및 재산상의 피해를 초래하고 있다. 이로 인해 많은 식생이 소실되며, 그 강도와 발생 형태에 따라 생태계 변화에 영향을 끼친다. 생태계 변화는 다시 산불 발생을 유발하여 2차 피해를 야기한다. 따라서 산불 피해지에 대한 정확한 탐지 및 면적 산정의 중요성이 지속적으로 제기되고 있다. 효율적인 산불 피해지 모니터링을 위해 산불 발생 후 실시간 지형 및 기상정보는 물론 피해지역의 영상을 대규모로 취득할 수 있는 위성영상이 주로 활용되고 있다. 최근, 합성곱 신경망(convolution neural network, CNN) 기반 모델부터 고성능 트랜스포머(Transformer) 기반 모델에 이르기까지 딥러닝 알고리즘이 빠르게 발전하면서 산림원격탐사에서 이를 적용한 연구가 활발히 이루어지고 있다. 하지만 현재까지 적용된 딥러닝 모델은 제한적이며 현업에서의 합리적인 활용을 위한 정량적 성능평가에 대한 보고가 부족한 상황이다. 따라서 본 연구에서는 모델에 따른 성능향상과 데이터 설계에 따른 성능향상을 중점적으로 비교 분석하였다. 미국 캘리포니아 지역을 대상으로 CNN 기반 모델의 U-Net, High Resolution Network-Object Contextual Representation (HRNet-OCR)을 활용하여 산불 피해지 모델을 구축하였다. 또한, 기본 파장대역과 함께 식생활력도 및 지표의 수분함량 정도를 고려하고자 normalized difference vegetation index (NDVI), normalized burn ratio (NBR)와 같은 산불 관련 분광지수를 산출하여 입력 이미지로 사용하였다. U-Net의 mean intersection over union (mIoU)이 0.831, HRNet-OCR이 0.848을 기록하여 두 모델 모두 우수한 영상분할 성능을 보였다. 또한, 밴드 반사도뿐 아니라 분광지수를 추가한 결과 모든 조합에서 평가지표 값이 상승하여 분광지수를 활용한 입력 데이터 확장이 픽셀 세분화에 기여함을 확인하였다. 이와 같은 딥러닝 방법론을 발전시킨다면 우리나라의 산불 피해지에 대한 신속한 파악 및 복구 계획 수립의 기초자료로 활용될 수 있을 것으로 기대된다.