• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.46-46
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• 2022

유기물의 복잡한 혼합물인 CDOM(Colored or Chromophoric Dissolved Organic Matter)은 하천 내 BOD(Biological Oxygen Demand), COD(Chemical Oxygen Demand) 및 유기 오염물질과 상당한 관련이 있다. CDOM은 가시광선 영역에서 빛을 흡수하는 성질을 가지고 있으며, 최근 원격감지 기술로 CDOM을 모니터링하기 위한 연구가 진행되고 있다. 본 연구에서는 백제보 상류 23km 구간에서 3년(2016~2018) 중 13일의 초분광영상을 활용하여 머신러닝 기반 CDOM을 추정 알고리즘을 개발하고자 한다. 초분광영상은 400~970 nm의 범위의 4 nm 간격 127개 대역의 분광해상도와 2 m의 공간해상도를 가진 항공기 탑재 AsiaFENIX 초분광 센서를 통해 수집하였으며 CDOM은 Millipore polycarbonate filter (𝚽47, 0.2 ㎛)에서 여과된 CDOM 샘플 자료를 200~800 nm의 흡수계수 스펙트럼으로 추출하여 사용하였다. CDOM 값은 전체기간 동안 2.0~11.0 m^-1의 값 분포를 보였으며 5 m^-1이상의 고농도 구간 자료개수가 전체 153개 샘플자료 중 21개로 불균형하다. 따라서 ADASYN(Adaptive Synthesis Sampling Approach)의 oversampling 방법으로 생성된 합성 데이터를 사용하여 원본 데이터의 소수계층 데이터 불균형을 해결하고 모델 예측 성능을 개선하고자 하였다. 생성된 합성 데이터를 입력변수로 하여 ANN(Artificial Neural Netowk)을 활용한 CDOM 예측 알고리즘을 구축하였다. ADASYN 기법을 통한 합성 데이터는 관측된 데이터의 불균형을 해결하여 기계학습 모델의 CDOM 탐지 성능을 향상시킬 수 있으며, 저수지 내 유기 오염물질 관리를 위한 설계를 지원하는데 사용할 수 있을 것으로 판단된다.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.7
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• pp.929-935
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• 2014

This paper is study on the pressure monitoring system(PMS) for ship's engine performance analysis( SEPA) based on web, with high speed and accuracy. This system is composed of pressure sensor, monitoring module with multi channel A/D converter, TCP/IP and satellite internet communication system. Existing domestic products measure cylinder pressure when piston of first explosive cylinder reached TDC(the top dead center) point and then measure next cylinder pressure manually each angle divided by a constant rotating interval. But presented system monitors in the local and web computer, using pressure information transmitted from pressure sensor installed on each engine. In this system, it is possible to increase the accuracy of the engine performance analysis because not only each TDC points but cylinder pressures synchronized with the TDC points could be measured in real time, accurately. And therefore, it may be used in a various diagnosis of main engines, such as deviations of each cylinder maximum pressures(Pmax) and the TDC firing positions and combustion conditions.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.37-46
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• 2007

In wireless sensor networks, one of the most important goals of designing protocols is to extend the network lifetime. A node has lots of duplication in sensing and communication range with surrounding nodes after many of nodes are randomly scattered. Such a heavy duplication overhead affects on the network lifetime seriously so usually all nodes need not activated constantly to carry out sensing and communication operation. One of the optimal methods of prolonging the network lifetime is finding the number of surrounding nodes necessary to maintain the network coverage and connectivity. It has been studied till the current date in wireless networks. If the neighbor necessary can be acquired to satisfy the probability using the ideal number of neighbors necessary and the acquired number of neighbors m to guarantee network coverage and connectivity. We use the result that F. Xue et al and S. Song et al derive previously in finding the neighbor necessary to guarantee the network connectivity and cany out the computer simulation to verify the necessary number. We present that our scheme satisfy the network coverage and connectivity. We present the simulation results compared with constant probability scheme through computer simulation.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.92-99
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• 2021

Light-scattering fine particulate matter monitors can measure particulate matter (PM) concentrations in every second and can be designed in a portable size. They can measure the concentrations of various PM sizes (PM_1.0, PM_2.5, PM_4.0 and PM₁₀) with a single sensor. They measure the number and size of particulate matters and convert them to weight per volume (concentration). These devices show a large error for asian dust. This paper proposes a scheme that compensates the PM_2.5 concenstration error for asian dust by multiple linear regression machine learning in light-scattering PM monitors. This scheme can be effective with only two or three types of PM sizes. The experimental results compare a beta-ray PM monitor of national institute of environmental research and a light-scattering PM monitor during a month. The correlation coefficient (R²) of theses two devices was 0.927 without asian dust, but it was 0.763 due to asian dust during the entire experimental period and improved to 0.944 by the proposed machine learning.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.315-324
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• 2023

In this paper, we propose a real-time pose estimation method for a monocular camera using a particle filter integrated with UKF (unscented Kalman filter). While conventional camera tracking techniques combine camera images with data from additional devices such as gyroscopes and accelerometers, the proposed method aims to use only two-dimensional visual information from the camera without additional sensors. This leads to a significant simplification in the hardware configuration. The proposed approach is based on a particle filter integrated with UKF. The pose of the camera is estimated using UKF, which is defined individually for each particle. Statistics regarding the camera state are derived from all particles of the particle filter, from which the real-time camera pose information is computed. The proposed method demonstrates robust tracking, even in the case of rapid camera shakes and severe scene occlusions. The experiments show that our method remains robust even when most of the feature points in the image are obscured. In addition, we verify that when the number of particles is 35, the processing time per frame is approximately 25ms, which confirms that there are no issues with real-time processing.

• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.133-144
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• 2016

In this study, Frequency Domain Reflectometry (FDR) and COSMIC-ray soil moisture (SM) stations were installed at Sungkyunkwan University in Suwon, South Korea. To provide reliable information about SM, soil property test, time series analysis of measured soil moisture, and comparison of measured SM with satellite-based SM product are conducted. In 2014, six FDR stations were set up for obtaining SM. Each of the stations had four FDR sensors with soil depth from 5 cm to 40 cm at 5~10 cm different intervals. The result showed that study region had heterogeneous soil layer properties such as sand and loamy sand. The measured SM data showed strong coupling with precipitation. Furthermore, they had a high correlation coefficient and a low root mean square deviation (RMSD) as compared to the satellite-based SM products. After verifying the accuracy of the data in 2014, four FDR stations and one COSMIC-ray station were additionally installed to establish the Soil Moisture site with FDR and COSMIC-ray, called SM-FC. COSMIC-ray-based SM had a high correlation coefficient of 0.95 compared with mean SM of FDR stations. From these results, the SM-FC will give a valuable insight for researchers into investigate satellite- and model-based SM validation study in South Korea.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.9
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• pp.385-396
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• 2017

Many IoT platforms have been proposed for various IoT devices, from low-end to high-end performance. We previously proposed a new IoT platform called MinT that supports the operation of the sensing devices and network communication. In the proposed platform, the things can flexibly connect to each other and efficiently share their information. Most IoT platforms, including the MinT, support thread pooling to quickly process requests. However, using a thread pool with a fixed thread count can cause network delay and inefficient energy consumption. In this paper, we propose an enhanced method to manage the thread pool efficiently by adjusting the number of threads every cycle to regulate the device's performance. In particular, we aim to improve the performance of the Interaction Thread Pool Group, which is responsible for analyzing, processing, and re-transmitting the received packets. The experiment shows that the improved method increases the average throughput by approximately 25% compared to the existing platforms. Finally, using the proposed method, the MinT can reduce the transmission delay and energy consumption of devices in the IoT environment.

• Tunnel and Underground Space
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• v.23 no.4
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• pp.297-307
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• 2013

In this study, the thermal analysis is carried out for a result of borehole heater test using ABAQUS ver 6.10 based on finite element analysis code. Thermal-mechanical rock properties as determined by laboratory tests before the in situ test and characteristics of the atmosphere at the test section are used as the initial condition. When comparing the results of the in situ test and thermal analysis, the temperature of C3 observation hole that is 0.9 m away from the heater showed very similar patterns and figures (about $1.3^{\circ}C$ difference). But the results of the A and B observation hole showed a significant difference around $15^{\circ}C{\sim}20^{\circ}C$. To find the reason for these results, the over-coring is carried out for the A1 and B1 observation holes. As a result of checking the excavated rock core with the naked eye, there is no problem on the number and position of the sensor as the test plan. However the state of cement injection in the observation hole is poor.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.409-419
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• 2015

The Atmospheric Emitted Radiance Interferometer (AERI) which is the Fourier Transform InfraRed (FTIR) spectrometer has been operated by the National Institute of Meteorological Research (NIMR) in Anmyeon island, South Korea since June 2010. The ground-based AERI with similar hyper-spectral infrared sensor to satellite could be an alternative way to validate satellite-based remote sensing. In this regard, the NIMR has focused on the improvement of Cloud data Filtering Method (CFM) which employed only one reference spectrum of clear sky in winter season. This study suggests Seasonal-Cloud data Filtering Method (S-CFM) which applied seasonal AERI reference spectra. For the comparison of applied S-CFM and CFM, the methane retrievals (surface volume mixing ratio) from AERI spectra are used. The quality of AERI methane retrieval applied S-CFM was significantly more improved than that of CFM. The positive result of S-CFM is similar pattern with the seasonal variation of methane from ground-based in-situ measurement, even if the summer season's methane is retrieved over-estimation. In addition, the comparison of vertical total column of methane from AERI and GOSAT shows good result except for the summer season.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.64-71
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• 2017

A damage estimation method is presented for jacket-type support structure of offshore wind turbine using a change of modal properties due to damage and committee of neural networks for effective structural health monitoring. For more practical monitoring, it is necessary to monitor the critical and prospective damaged members with a limited number of measurement locations. That is, many data channels and sensors are needed to identify all the members appropriately because the jacket-type support structure has many members. This is inappropriate considering economical and practical health monitoring. Therefore, intensive damage estimation for the critical members using a limited number of the measurement locations is carried out in this study. An analytical model for a jacket-type support structure which can be applied for a 5 MW offshore wind turbine is established, and a training pattern is generated using the numerical simulations. Twenty damage cases are estimated using the proposed method. The identified damage locations and severities agree reasonably well with the exact values and the accuracy of the estimation can be improved by applying the committee of neural networks. A verification experiment is carried out, and the damage arising in 3 damage cases is reasonably identified.