• 한국지구과학회지
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• 제30권5호
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• pp.550-564
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• 2009

When magnetotelluric (MT) data are obtained in the vicinity of the coast, the surrounding seas make it difficult to interpret subsurface structure, especially the deep part of the subsurface. We introduce an iterative method to correct the sea effect, based on the previous topographic correction method that removes the distortion due to topographic changes in seafloor MT data. The method first corrects the sea effect in observed MT impedance, and then inverts corrected response in a model space without the sea. Due to mutual coupling between the sea and the subsurface structure, the correction and inversion steps are iterated until the changes in each result become negligible. The method is tested for 1- and 2-D structures using synthetic MT data produced by 3-D forward modeling including surrounding seas. In all cases, the method closely recovers the true structure assumed to generate synthetic responses after a few iterations.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.291-291
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• 2002

DGPS(Differential Global Positioning System) and RTK(RealTime Kinematic) is in one of today's most widely used surveying techniques. But It's use is restricted by the distance between reference station and rover station and it is difficult to process data in realtime by it's own orgnizational limitation in precise measurement of positioning. To meet these new demands, In This paper, new DGPS and RTK correction data services through Internet and PSTN(Public Switched Telephony Network) have been proposed. For this purpose, we implemented performance a DGPS and RTK error correction data transmission system for long-distance using the internet and PSTN network which allows a mobile user to increase the distance at which the rover receiver is located from the reference in realtime. and we analyzed and compared DGPS and RTK performance by experiments through the Internet and PSTN network with the distance and the time.

• Nuclear Engineering and Technology
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• 제56권7호
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• pp.2659-2665
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• 2024

This study proposes an algorithm that combines a Kalman Filter method with effective decay constant correction to improve the accuracy of predicting radiation dose rate distribution during emergencies. The algorithm addresses the limitations of relying solely on measurement data by incorporating calculation data and refining the estimations. The effectiveness of algorithm was assessed using hypothetical test scenarios, which demonstrated a significant improvement in the accuracy of dose rate prediction compared to the model predictions. The estimates generated by the algorithm showed a good agreement with the measured data, and the discrepancies tend to decrease over time. Furthermore, the application of the effective decay constant correction accelerated the reduction of prediction errors. In conclusion, it was confirmed that the combined use of the Kalman filter method and effective decay constant correction is an effective approach to improve the accuracy of dose rate prediction.

• 전기전자학회논문지
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• 제24권1호
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• pp.33-39
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• 2020

본 논문에서는 타이어의 물리적인 요소 중 하나인 압력정보를 이용해서 자동차의 하중 표출이 가능한 타이어 공기압 측정 기술을 사용한 차량의 적재중량 측정시스템 설계 기법을 제안한다. 제안된 기법은 하중 및 진동에 의한 노이즈 보정, 기체유량 보정, 데이터 믹서, 중량 환산 등의 4가지 과정으로 구성된다. 하중 및 진동에 의한 노이즈 보정에서는 외부충격 및 차량이 주행 중 발생하는 진동 등에 의해 타이어의 내부 압력이 상승하는 노이즈를 제거한다. 기체유량 보정 과정에서는 하중 및 진동에 의한 노이즈 보정 과정을 거친 데이터에 대하여 지면의 온도상승에 의해 타이어의 내부 압력이 상승하는 노이즈를 제거한다. 데이터 믹서 과정에서는 화물적재 시 타이어에 수직으로 전달이 되어 타이어의 압력변화에 따른 공차, 중차, 만차에 대한 하중과 압력 등을 분류하게 된다. 중량 환산 과정에서는 하중 및 진동에 의한 노이즈 보정 및 기체유량 보정을 거친 데이터를 사용하여 중량 환산 알고리즘을 통해 중량으로 표출된다. 중량 환산 알고리즘은 하중과 압력변화에 대한 선형 함수의 기울기인 중량 환산 Factor를 구하여 중량을 환산한다. 본 논문에서 제안된 타이어 공기압 측정 기술을 사용한 차량의 적재중량 측정 시스템의 정밀도를 평가하기 위해 자체적으로 테스트 베드를 구축하여 평가하였다. 하중 및 진동에 의한 노이즈 보정 결과와 기체 유량 데이터 보정 결과는 신뢰성 있는 결과를 나타내었다. 또한 중량 정밀도 반복 실험도 국내 업체 기준치인 90% 보다 우수한 중량 정밀도를 나타내었다.

• 한국건축시공학회지
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• 제8권2호
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• pp.107-112
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• 2008

According to Korean Architectural Standard Specification (KASS) , at the design stage of the specified concrete strength, strength correction with each temperature level should be considered to secure required strength at 28 days even in low temperature condition, In this paper, the period for the strength correction at the stage of mixture design of the concrete using ordinary Portland cement(OPC) specified in KASS was determined with each region of south Korea based on the meteorological data of KMA(Korea meteorological administration) by applying KASS-5 regulation. In case of 28 days of strength control age, the period for strength correction with 6MPa was calculated to $50{\sim}60$ days and, with 3 MPa. to around 80 days. The period for the strength correction was shown to be decreased with the rise of altitude. The period to consider the delay of the strength development due to low temperature including the period of cold weather concrete was nearly 7 months around 1 year. References for determining the strength correction factors with each region of south Korea was provided in this paper. Further investigation of strength correction of the concrete containing blended cement is to studied.

• 대한원격탐사학회지
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• 제35권6_3호
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• pp.1299-1312
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• 2019

육상 원격탐사에서 정량적 활용이 확대됨에 따라 대기보정의 중요성이 날로 증가하고 있다. 그러나 대기보정 처리의 난이도와 효과의 불확실성을 감안한다면, 대기보정은 필요한 활용 분야에 적용되어야 한다. 광학영상의 대기보정이 반드시 필요한 분야로 지표물의 생물리적 변수의 정량적 정보를 추출하는 경우와 시계열 자료 분석을 꼽을 수 있다. 지표물의 정확한 표면반사율을 도출하는 대기보정에서 가장 큰 영향을 미치는 요소는 시공간적으로 매우 가변적인 에어로졸 및 수증기량이다. 특히 고·중해상도의 다중분광영상 대기보정에서 시기와 공간해상도가 부합되는 에어로졸 및 수증기 자료를 얻는 데 어려움이 많다. 광학영상의 육상 대기보정에서는 대기자료의 획득 방법에 따른 적절한 기법의 적용이 필요하다. 육상 대기보정은 렘버시안 표면 가정으로 표면반사율이 산출되지만, 대부분의 지표면은 이방성 반사특성을 가지고 있기 때문에 BRDF보정이 추가적으로 적용되어야 하는 숙제를 가지고 있다. 육상지역의 광학영상 대기보정 방법은 지속적인 개선이 전망되며, 센서도 대기보정을 위한 추가적인 파장밴드 포함이 기대된다.

• 대한원격탐사학회지
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• 제39권5_3호
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• pp.891-907
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• 2023

Compact Advanced Satellite 500-4 (CAS500-4) is scheduled to be launched to collect high spatial resolution data focusing on vegetation applications. To achieve this goal, accurate surface reflectance retrieval through atmospheric correction is crucial. Therefore, a machine learning-based atmospheric correction algorithm was developed to simulate atmospheric correction from a radiative transfer model using Sentinel-2 data that have similarspectral characteristics as CAS500-4. The algorithm was then evaluated mainly for forest areas. Utilizing the atmospheric correction parameters extracted from Sentinel-2 and GEOKOMPSAT-2A (GK-2A), the atmospheric correction algorithm was developed based on Random Forest and Light Gradient Boosting Machine (LGBM). Between the two machine learning techniques, LGBM performed better when considering both accuracy and efficiency. Except for one station, the results had a correlation coefficient of more than 0.91 and well-reflected temporal variations of the Normalized Difference Vegetation Index (i.e., vegetation phenology). GK-2A provides Aerosol Optical Depth (AOD) and water vapor, which are essential parameters for atmospheric correction, but additional processing should be required in the future to mitigate the problem caused by their many missing values. This study provided the basis for the atmospheric correction of CAS500-4 by developing a machine learning-based atmospheric correction simulation algorithm.

• Journal of Astronomy and Space Sciences
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• 제29권2호
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• pp.97-101
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• 2012

Monitoring sunspots consistently is the most basic step required to study various aspects of solar activity. To achieve this goal, the observers must regularly calculate their own correction factor $k$ and keep it stable. Relatively recently, two observing teams in South Korea have presented interesting papers which claim that revisions that take the yearly-basis $k$ into account lead to a better agreement with the international relative sunspot number $R_i$, and that yearly $k$ apparently varies with the solar cycle. In this paper, using artificial data sets we have modeled the sunspot numbers as a superposition of random noise and a slowly varying background function, and attempted to investigate whether the variation in the correction factor is coupled with the solar cycle. Regardless of the statistical distributions of the random noise, we have found the correction factor increases as sunspot numbers increase, as claimed in the reports mentioned above. The degree of dependence of correction factor $k$ on the sunspot number is subject to the signal-to-noise ratio. Therefore, we conclude that apparent dependence of the value of the correction factor $k$ on the phase of the solar cycle is not due to a physical property, but a statistical property of the data.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권5호
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• pp.366-377
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• 2005

본 논문은 한국어 철자교정기의 최적교정률을 보이는 모듈들의 나열순서를 찾는 연구이다. 철자교정기의 모듈 개수가 n개이면 모듈나열 경우의 수는 n!가지가 가능하므로 철자교정기의 최적 교정률을 계산하기가 힘들어 진다. 실험에 사용한 한국어 철자교정기는 현재 19개 모듈들로 구성되어 있다. 입력데이타에 대해서 19!개 모듈을 적용하여 최적교정률을 찾는 것은 현실적으로 불가능하다. 따라서 주어진 입력데이타에 대해 이론적인 최대교정률과 최소교정률을 구하여 교정률 범위를 구하고, 최대교정률에 근접한 최적교정률에 대한 모듈나열순서를 구하는 것이 논문의 목적이다. 최적교정률을 구하기 위해 경험적 지식을 사용하였다. 실험에 사용한 입력데이타는 신문사에서 몇 년간 발생한 오류어절 753,191개의 집합이다. 이 오류집합에 대해 철자교정기의 이론적인 최대교정률은 $97.28\%$ (732,764개/753,191개)이나 경험적으로 우리가 찾은 최적교정률은 $96.62\%$ (727,750개 /733,191개)이다. 철자교정기의 성능은 $99.31\%$ (727,750개 /732,764개)이다.

• Journal of Positioning, Navigation, and Timing
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• 제8권4호
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• pp.209-214
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• 2019

Precise point positioning (PPP) requires precise orbit and clock products. International GNSS service (IGS) real-time service (RTS) data can be used in real-time for PPP, but it may not be possible to receive these corrections for a short time due to internet or hardware failure. In addition, the time required for IGS to combine RTS data from each analysis center results in a delay of about 30 seconds for the RTS data. Short-term orbit prediction can be possible because it includes the rate of correction, but the clock correction only provides bias. Thus, a short-term prediction model is needed to preidict RTS clock corrections. In this paper, we used a long short-term memory (LSTM) network to predict RTS clock correction for three minutes. The prediction accuracy of the LSTM was compared with that of the polynomial model. After applying the predicted clock corrections to the broadcast ephemeris, we performed PPP and analyzed the positioning accuracy. The LSTM network predicted the clock correction within 2 cm error, and the PPP accuracy is almost the same as received RTS data.