• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.4
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• pp.112-118
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• 2013

The selection of appropriate ground motions and reasonable modification are becoming increasingly critical in reliable prediction on seismic performance of structures. A widely used amplitude scaling approach is not sufficient for robust structural evaluation considering a site specific seismic hazard because only one spectral value is matched to the design spectrum typically at the structural fundamental period. Hence alternative approaches for ground motion selection and modifications have been suggested. However, there is no means to evaluate such methodologies yet. In this study, it is focused to describe the main questions resided in the amplitude scaling approach and to propose a regression model for structural damage as point of comparison. Spectrum compatible approach whose resulting spectrum matches the design spectrum at the entire range of the structural period is considered as alternative to be compared to the amplitude scaling approach. The design spectrum is generated according to ASCE7-05.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.189-190
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• 2011

이 연구는 브랜드 네임 스펙트럼 이론을 이용하여 병원 명칭의 특성을 분석하였다. 연구대상은 수도권 지역에 위치하는 모든 병원을 대상으로 하였고, 명칭은 의미있는 단위로 분류한 후 스펙트럼 이론에 따라 분류하였다. 분석결과 임의적 명칭의 빈도가 가장 높았고, 다음으로는 암시적, 서술적, 그리고 조어적 명칭의 순이었다. 단일 스펙트럼 구성된 명칭이 가장 많았으며, 스펙트럼이 2개와 3개로 구분된 명칭의 순이었다.

• 한국방재학회:학술대회논문집
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• 2010.02a
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• pp.66.2-66.2
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• 2010

장대 케이슨 방파제에 작용하는 다방향 불규칙파랑의 파력 평활화 계수를 계산하였다. 다방향 불규칙파랑의 주파수 스펙트럼으로는 Bretschneider-Mitsuyasu 스펙트럼을 사용하였고, 방향 스펙트럼은 Mitsuyasyu 타입의 스펙트럼을 적용하였다. 계산 결과 단일 케이슨의 길이가 길수록, 주파향의 입사각이 클수록 평활화 계수는 감소하였다. 다양한 에 대해서도 계산하였으며, 가 클수록 평활화계수는 규칙파와 비슷한 경향을 보였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.162-172
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• 2015

In this paper, we propose an adaptive detection algorithm of footstep and a classification algorithm for activities of the detected footstep. The proposed algorithm can detect and classify whole movement as well as individual and irregular activities, since it does not use continuous footstep signals which are used by most previous research. For classifying movement, we use feature vectors obtained from frequency spectrum from FFT, CWT, AR model and image of AR spectrogram. With SVM classifier, we obtain classification accuracy of single footstep activities over 90% when feature vectors using AR spectrogram image are used.

• Journal of the Earthquake Engineering Society of Korea
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• v.2 no.4
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• pp.123-134
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• 1998

본 연구에서는 지반상태가 교량의 지진응답에 미치는 영향을 분석하기 위해 다양한 지반모델 상의 교량모델에 대한 지진해석을 수행하고 그 결과를 비교.분석하였다 이를 위해서 기존의 교량시방서에서 분류된 네가지의 서로다른 지반종류를 대상으로 보다 세분된 지반모델 상에 위치하는 대표적인 교량에 대한 지진해석을 수행함으러써 첫째로는 각 지반 종류 상호간의 지진응답 차이의 정도를 시방서 값과 비교.분석하였으며 둘째로는 동일 지반으로 분류되는 상이한 두 지반간의 응답차이의 정도를 확인하였다 해석을 위해서는 시방서에서 제시된 두가지 방법 즉 단일모드 스펙트럼해석법과 다중모드 스펙트럼해석법을 사용하였으며 이들 결과를 별도로 작성된 인공시간이력을 입력으로 하는 시간이력해석법을 사용한 결과와 비교.분석하였다 시간이력해석법에서는 진동수에 무관한 지반임피던스함수를 이용하는 시간영역해석법을 사용하였다 해석결과 시방서에서 제시한 단일모드 및 다중모드 스펙트럼해석방법은 일반적으로 안전측의 지반-구조물 상호작용 해석결과를 주는 것으로 확인되었다 그러나 유연성이 큰 지반 상의 구조물에대한 지진해석을 위한 해석모델 작성시에는 지반의 유연성이 반드시 고려되어야 하며 특히 낙교방지를 위한 변위는 지반의 유연성을 고려한 정밀해석법에 의한 계산이 필수적으로 요구됨을 확인하였다.

• The Journal of the Acoustical Society of Korea
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• v.18 no.1
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• pp.38-44
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• 1999

In this paper, a new spectral subtraction technique with two microphone inputs is proposed. In conventional spectral subtraction using a single microphone, the averaged noise spectrum is subtracted from the observed short-time input spectrum. This results in reduction of mean value of noise spectrum only, the component varying around the mean value remaining intact. In the method proposed in this paper, the short-time noise spectrum excluding the speech component is estimated by introducing the blocking matrix used in Griffiths-Jim-type adaptive beamformer with two microphone inputs, combined with the spectral compensation technique. A simulation was conducted to verify the effectiveness of the method.

• Geophysics and Geophysical Exploration
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• v.27 no.2
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• pp.91-107
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• 2024

Single-channel seismic exploration has proven effective in delineating subsurface geological structures using small-scale survey systems. The seismic data acquired through zero- or near-offset methods directly capture subsurface features along the vertical axis, facilitating the construction of corresponding seismic sections. However, substantial noise in single-channel seismic data hampers precise interpretation because of the low signal-to-noise ratio. This study introduces a novel approach that integrate noise reduction and signal enhancement via matrix rank optimization to address this issue. Unlike conventional rank-reduction methods, which retain selected singular values to mitigate random noise, our method optimizes the entire singular value spectrum, thus effectively tackling both random and erratic noises commonly found in environments with low signal-to-noise ratio. Additionally, to enhance the horizontal continuity of seismic events and mitigate signal loss during noise reduction, we introduced an adaptive weighting factor computed from the eigenimage of the seismic section. To access the robustness of the proposed method, we conducted numerical experiments using single-channel Sparker seismic data from the Chukchi Plateau in the Arctic Ocean. The results demonstrated that the seismic sections had significantly improved signal-to-noise ratios and minimal signal loss. These advancements hold promise for enhancing single-channel and high-resolution seismic surveys and aiding in the identification of marine development and submarine geological hazards in domestic coastal areas.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1650-1658
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• 2019

In recent years, IoT device and platform become widely popular and the computing performance and capabilities of IoT devices are also getting improved. However, the size and computing resources of IoT devices, especially small single board computer, are limited in a way that the design and implementation of the system should be carefully considered to operate on the devices. Recently, SDR technologies are adapting in IoT devices and can perform various radio systems. Thorough analysis and investigation of computer performances on small single board computer are necessary for its usage. In this paper, we present the results of computing resources measurement and analysis on small single-board computers. At first, we consider to design SDR based spectrum sensing for single board computer, investigate various key factors and propose a design procedure that can affect performance of the system with experiments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.45-49
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• 2015

In this paper, we proposed not specturm sensing but also save energy without consume energy of secondary network that spectrum sensing of cognitive applied energy harvesting scheme. Algorithms of sensing and harvesting is determine active or idle of primary network, compares the amount of energy that is harvested by energy harvesting scheme with the threshold. If secondary network to send a message and primary network is active, by changing frequency to use the spectrum. Further, if secondary network have no message, continues energy harvest. Therefore, spectrum sensing applied energy harvesting scheme, energy of secondary network is remove waste and charge energy, efficiency and utilization of cognitive network can be increase.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.73-76
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• 2015

In this paper, we propose energy harvesting apply to spectrum sensing. In this case, we can be spectrum sensing without consume energy. Algorithms of sensing and harvesting are determine active or idle of primary network, Compares with the threshold energy and the amount of energy that is harvested by energy harvesting scheme. If the secondary network want to send a message while the primary network is active, secondary users will change frequency to use the spectrum. Further, if the secondary network has not message, it will continues harvest energy. Therefore, spectrum sensing applied the energy harvesting method, energy of secondary network is remove waste and charge energy. So, efficiency and utilization of cognitive network can be increase.