• 대한원격탐사학회지
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• 제38권6_3호
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• pp.1761-1775
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• 2022

예측하기 힘든 기후변화로 인해 물 관련 재해의 발생 빈도와 피해 규모도 지속적으로 증가하는 추세이다. 재난관리의 측면에서 광범위한 지역의 피해면적을 파악하고, 중·장기적 예측을 위한 모니터링이 필수적이다. 수재해 분야에서 광역적 모니터링을 위해 Synthetic Aperture Radar (SAR) 위성영상을 활용한 원격탐사 기술 연구가 활발히 진행되고 있다. 수재해 모니터링을 위한 시계열 분석에는 방대한 양의 영상수집과 잡음이 많은 레이더 산란 특성을 고려한 복잡한 전처리과정이 필요하며, 이를 위해 상당한 시간이 소요되는 한계가 있다. 최근 클라우드 컴퓨팅 기술의 발전과 함께 위성 빅데이터를 활용한 시·공간 분석이 가능한 많은 플랫폼들이 제안되고 있다. 구글어스엔진(Google Earth Engine, GEE)은 대표적인 플랫폼으로, 600여개의 위성 자료를 무료로 제공하고 있으며 위성영상의 분석준비데이터를 기반으로 준-실시간 시·공간 분석이 가능하다. 이에 본 연구에서는 구글어스엔진을 활용한 즉각적인 수재해 피해 탐지와 중·장기적 시계열 관측 연구를 수행하였다. 변화탐지에 주로 활용되는 Otsu 기법을 통해 '20년 발생한 집중호우를 중심으로 하천 범람으로 인한 하폭의 변화와 피해 면적을 확인하였다. 또한 재난관리 측면에서 모니터링의 중요성이 요구되는 만큼 상습침수지역으로 선정된 연구대상 지역을 중심으로 '18년부터 '22년까지의 시계열 수체의 변화 경향을 확인하였다. 구글어스엔진은 자바스크립트 기반 코딩을 통한 짧은 처리시간, 시공간 분석과 표출의 강점으로 수재해 분야 활용이 가능할 것으로 판단된다. 더불어 향후 다양한 위성 빅데이터와의 연계를 통해 활용 분야가 확대될 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.348-369
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• 2024

With the advancement of Industry 4.0 and Industrial Internet of Things (IIoT), manufacturing increasingly seeks automation and intelligence. Temperature and vibration monitoring are essential for machinery health. Traditional abnormal state detection methodologies often overlook the intricate frequency characteristics inherent in vibration time series and are susceptible to erroneously reconstructing temperature abnormalities due to the highly similar waveforms. To address these limitations, we introduce synergistic, end-to-end, unsupervised Frequency-Time Domain Memory-Enhanced Autoencoders (FTD-MAE) capable of identifying abnormalities in both temperature and vibration datasets. This model is adept at accommodating time series with variable frequency complexities and mitigates the risk of overgeneralization. Initially, the frequency domain encoder processes the spectrogram generated through Short-Time Fourier Transform (STFT), while the time domain encoder interprets the raw time series. This results in two disparate sets of latent representations. Subsequently, these are subjected to a memory mechanism and a limiting function, which numerically constrain each memory term. These processed terms are then amalgamated to create two unified, novel representations that the decoder leverages to produce reconstructed samples. Furthermore, the model employs Spectral Entropy to dynamically assess the frequency complexity of the time series, which, in turn, calibrates the weightage attributed to the loss functions of the individual branches, thereby generating definitive abnormal scores. Through extensive experiments, FTD-MAE achieved an average ACC and F1 of 0.9826 and 0.9808 on the CMHS and CWRU datasets, respectively. Compared to the best representative model, the ACC increased by 0.2114 and the F1 by 0.1876.

• Smart Structures and Systems
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• 제11권1호
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• pp.1-17
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• 2013

This paper intended to investigate the feasibility of bridge health monitoring using a linear system parameter of a time series model identified from traffic-induced vibrations of bridges through a laboratory moving vehicle experiment on scaled model bridges. This study considered the system parameter of the bridge-vehicle interactive system rather than modal ones because signals obtained under a moving vehicle are not the responses of the bridge itself but those of the interactive system. To overcome the shortcomings of modal parameter-based bridge diagnosis using a time series model, this study considered coefficients of Autoregressive model (AR coefficients) as an early indicator of anomaly of bridges. This study also investigated sensitivity of AR coefficients in detecting anomaly of bridges. Observations demonstrated effectiveness of using AR coefficients as an early indicator for anomaly of bridges.

• Journal of Korean Neurosurgical Society
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• 제65권1호
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• pp.151-160
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• 2022

Continuous monitoring of intracranial pressure is a well established medical procedure. Still, little is known about long-term behavior of intracranial pressure in normal pressure hydrocephalus. The present study is designed to evaluate periodicity of intracranial pressure over long-time scales using intraventricular pressure monitoring in patients with normal pressure hydrocephalus. In addition, the circadian and diurnal patterns of blood pressure and body temperature in those patients are studied. Four patients, selected with "probable" normal pressure hydrocephalus, were monitored for several dozen hours. Intracranial pressure, blood pressure, and body temperature were recorded hourly. Autocorrelation functions were calculated and cross-correlation analysis were carried out to study all the time-series data. Autocorrelation results show that intracranial pressure, blood pressure, and body temperature values follow bimodal (positive and negative) curves over a day. The cross-correlation functions demonstrate causal relationships between intracranial pressure, blood pressure, and body temperature. The results show that long-term fluctuations in intracranial pressure exhibit cyclical patterns with periods of about 24 hours. Continuous intracranial pressure recording in "probable" normal pressure hydrocephalus patients reveals circadian fluctuations not related to the day and night cycle. These fluctuations are causally related to changes in blood pressure and body temperature. The present study reveals the complete loss of the diurnal blood pressure and body temperature rhythmicities in patients with "probable" normal pressure hydrocephalus.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2004년도 총회 및 춘계학술발표회
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• pp.447-450
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• 2004

This study was conducted to characterize groundwater and river-water fluctuations at a riverbank filtration site in Daesan-myeon adjacent to the Nakdong River, using time series analysis. Water levels from six observation wells from January 2003 to October 2003 were measured. The autocorrelation analysis indicates that the wells are divided into three groups: group 1 represents strong linearity and memory, group 2 intermediate linearity and memory, and group 3 weak linearity and memory. The analysis indicates that groundwater levels in different monitoring wells vary in response to river-water levels, groundwater withdrawal and seasonal rainfall. Cross-correlation was also divided into three groups. Group 1 shows the highest cross-correlation function (0.49 - 0.54) for a lag time of 0 hours, group 2 intermediate cross-correlation function (0.34 - 0.45), and group 3 the lowest cross-correlation function (0.23 - 0.25). Different cross-correlation functions among the 3 groups are interpreted as an effect of tile distance from the river to the pumping wells.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.374-377
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• 2005

The distribution and changes of tropospheric nitrogen dioxide ($NO_2$) are analyzed using the satellite measurements data from GOME (Global Ozone Monitoring Experiment) and SCIMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY). We produced global maps of tropospheric $NO_2$ for 4 seasons using GOME measurements from January 1997 to June 2003. The global distribution shows high values in regions with dense population and high industrialization. Tropospheric $NO_2$ shows obvious seasonal changes depending on its emission and lifetime. Based on the good agreement between two instruments in the time period of overlapping measurements (January 2003-June2003), we linked SClAMACHY data to the GOME time series. The combined time series over the past decade indicate that $NO_2$ 1evels over China are rapidly increasing while those over Europe are decreasing. We also discussed potential application of spaceborne instruments in detecting and characterizing long-distance transport of $NO_2$.

• 한국대기환경학회지
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• 제9권3호
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• pp.183-190
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• 1993

For the efficient control of photochemical smog materials, the researches on the change patterns of photochemical smog precursors are indispensable. In this study, a time-series analysis was performed for the auto-monitoring data of Kwanghwamun and Jamsil stations in 1990, and the change patterns of photochemical smog materials were studied. Especially, auto-correlation coefficients were analyzed to investigate the cyclic characteristics of pollutants in question and cross-correlation coefficients to investigate the correlations between pollutants adjusted for time lag and between $O_3$ and meteorological factors. Results of researches are as follows: First, in the case of NO and $NO_2$ intimately related to human activities, 12-hour cycle was prevalent. But $O_3$ showed 24-hour cycle. Second, NO showed a relatively high correlation with $O_3$ and usually developed into $O_3$ 5 to 7 hours later. Third, temperature, insolation intensity, and wind speed showed a positive correlation with $O_3$ while relative humidity a negative correlation.

• 한국지하수토양환경학회지:지하수토양환경
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• 제12권5호
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• pp.86-97
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• 2007

현재 운영중인 국가지하수관측소의 지하수위 변동 특성을 파악하고자, 2003년부터 2005년까지의 156주 동안의 202개 암반관측정과 112개 충적관측정을 대상으로 주성분분석을 실시하였다. 암반 및 충적관측정의 지하수위에 대하여 80% 정도 설명 가능한 8개 주성분을 각각 추출하였으며 이중 충적관측정에 대해서는 주성분 인자적재값을 이용하여 군집분석을 실시한 결과 강우에 대한 지하수위의 반응(군집 1: 4.6일, 군집 2: 24.1일, 군집 3: 1.4일), 수위 변동추세(군집 1: $2.05{\times}10^{-4}$ m/day, 군집 2: $-7.85{\times}10^{-4}$ m/day, 군집 3: $-3.51{\times}10^{-5}$ m/day), 수위 변동 폭(군집 1 < 군집 2 < 군집3) 등에 의하여 설명되는 3개의 군집으로 분류되었으며, 각 군집은 유의수준 0.05에서 인근 하천과의 거리(군집 3 < 군집 2 < 군집 1), 지하수 함양율(군집 3 < 군집 2 < 군집 1) 및 지형 경사 특성(군집 3이 평야지대, 군집 1은 급경사 지역) 등에 차이를 보이는 것으로 나타났다.

• 한국지반신소재학회논문집
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• 제21권4호
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• pp.55-67
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• 2022

본 본문에서는 합성개구레이더(synthetic aperture radar) 위성 영상 이미지 분석을 통해 지표 침하를 측정하는 기술, 즉 합성개구레이다 간섭기법(InSAR, interferometric synthetic aperture radar)의 기본 이론 및 도심지 지표 변위 측정에 대한 적용성 검토 연구 내용을 다루었다. 먼저 InSAR 기법에 대한 기본 이론과 함께 기존 연구 동향을 제시하였으며 아울러 다중시기 SAR 영상을 이용한 시계열 분석 기법 중 SBAS-InSAR(SBAS-InSAR, Small Baseline Subset Interferometric SAR) 및 PS(Persistent Scatterers)-InSAR 기법을 연구 대상 지역에 적용하고 2014년~2021년 사이에 발생한 지역적 지반 침하를 평가하여 InSAR 기법의 도심지 지반 침하 모니터링에 구체적인 적용 가능성 여부를 평가하였다. 검토 결과 InSAR 기법은 연구대상 지역에서 발생한 시계열 침하 및 광역대 침하발생 경향을 현실적으로 모니터링할 수 있는 것으로 검토되었다. 아울러 SAR 영상을 이용한 시계열 간섭기법은 SAR 위성이 지구를 공전하면서 일정한 시간간격으로 한반도의 영상을 제공하므로 장기간에 걸쳐 발생하는 지반침하 모니터링에 효율적으로 적용할 수 있는 것으로 검토되었다. 향후 재방문 주기가 짧은 SAR 위성에서 촬영된 고해상도 SAR 영상이 활성화될 경우 InSAR 기법은 기존의 계측 기법을 대체하는 4차 산업 기술 기반의 광역대도심지 지반침하 모니터링 기술로 발전될 수 있을 것으로 평가되었다.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2006년도 춘계 학술발표회 논문집
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• pp.1046-1053
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• 2006

In the large scale recent reclaiming works performed within the wide spatial boundary, evaluation of long-term consolidation settlement and residual settlement of the whole construction area is sometimes made with the results of the limited ground investigation and measurement. Then the reliability of evaluation has limitations due to the spatial uncertainty. Additionally, in case of large scale deep excavation works such as urban subway construction, there are a lot of hazardous elements to threaten the safety of underground pipes or adjacent structures. Therefore it is necessary to introduce a damage prediction system of adjacent structures and others. For the more accurate analysis of monitoring information in the wide spatial boundary works and large scale urban deep excavations, it is necessary to perform statistical and spatial analysis considering the geographical spatial effect of ground and monitoring information in stead of using diagrammatization method based on a time-series data expression that is traditionally used. And also it is necessary that enormous ground information and measurement data, digital maps are accumulated in a database, and they are controlled in a integrating system. On the abovementioned point of view, we developed Geomonitor 2.0, an Internet based real time monitoring program with a new concept by adding GIS and geo-statistical analysis method to the existing real time integrated measurement system that is already developed and under useful use. The new program enables the spatial analysis and database of monitoring data and ground information, and helps the construction- related persons make a quick and accurate decision for the economical and safe construction.