• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.4
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• pp.761-771
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• 1994

This paper focuses on how spectrum information can be represented efficiently in a very low bit rate CELP speech coder. To achieve the goal, an LPC cepstral coefficients VQ scheme representing the spectrum information in a CELP coder is proposed. To represent the spectrum information using LPC cepstrums, three different cepstral distance measures having different spectral meanings in the frequency domain are considered, and their performances are compared and analyzed. The experimental results show that spectrum information in low bit rate CELP coders can be represented very efficiently using the proposed LPC cepstral vector quantization scheme.

• Wind and Structures
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• v.12 no.3
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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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• v.26 no.6
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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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• v.31 no.3
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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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• v.7 no.6
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.3
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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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• 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.

• Wind and Structures
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• v.38 no.1
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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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• v.38 no.2
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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.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.