• Journal of the Korean Wood Science and Technology
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• v.51 no.4
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• pp.295-308
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• 2023

This study applied a real-time IoT (Internet of Things) environmental monitoring system to wooden cultural heritages (WCHs) located in suburbs and forests in Korea. It automated the graphs of seasonal Temperature (T) and relative humidity (RH) changes inside the heritage structures and seasonal Performance Index (PI) values. While utilizing line graphs of the existing T and RH change trends and a bar graph expressing the PI values, this study examined the current status of the conservation environment inside the WCHs throughout the year and its diagnosis. Consequently, at higher latitudes, the organic cultural heritage repeatedly experienced large T fluctuations, and the risk of physical and chemical degradation of the materials was greater. However, the RH showed significant seasonal differences, even within the same latitude, indicating that the impact of latitude was not significant. Therefore, the staff in charge must manage RH by considering the surrounding environmental conditions and adjusting the internal environment of the structures. The PI values for the year-round T and RH inside the heritages were confirmed to only be a maximum of approximately 60% of the environmental suitability for conservation throughout the year, depending on the season. The relationship between the germination and growth potential period of xerophilic fungi and the monthly internal temperature and humidity in five heritages located at different latitudes was analyzed. As a result, we could thus determine that four particular months of the year (June-September) represent the periods with the highest risk of damage from xerophilic fungi in the country, regardless of latitude.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.25-25
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• 2022

하천의 개발 및 보전 계획을 수립하는 데에 있어 자연하천의 부유사량 및 총유사량을 계측하는 것은 매우 중요하다. 우리나라에서는 매년 국내 자연하천을 대상으로 부유사량을 실측하고 실측 부유사량을 바탕으로 수정 아인슈타인 방법을 적용해 총유사량을 산정하고 있으나 이 또한 홍수기에 국한되어 있다. 가장 일반적인 유사량 계측 방법인 시료 채집에 의한 방법은 많은 노력과 비용을 수반하기 때문에 유사량 관측소와 관측 빈도를 늘릴 수 없는 실정이다. 최근에는 ADCP 음파 신호의 후방산란도가 부유사 농도에 따라 증가한다는 성질을 이용해 부유사 농도 계측에 ADCP를 이용하고자 하는 노력이 계속되고 있다. 이러한 특성을 이용해 본 연구에서는 전라남도 나주시에 위치한 남평교 자동유량관측소에 설치된 횡방향 ADCP (H-ADCP)를 대상으로 서포트 벡터 회귀(SVR)를 적용한 실시간 유사량 모니터링 모형을 제안하였다. 여기서 제시하는 유사량산정 모형은 크게 유량과 초음파 산란도를 입력 변수로 해 부유사 농도를 산정하는 서포트 벡터 회귀 모형과 첫 번째 모형으로부터 산정된 부유사 농도와 흐름 정보를 이용해 총유사량을 산정하는 모형으로 구성되어 있다. 개발된 SVR 부유사량 및 총유사량 산정 모형의 정확도가 결정계수(R²) 기준으로 각각 0.82, 0.90 으로 나타났다. 주목할 점은, 본 연구에서 제시하는 SVR 모형을 이용해 멱함수 기반 유사량 관계식으로는 예측할 수 없는 유사량의 이력현상을 재현해낼 수 있다는 것이다. 본 연구에서 제시하는 H-ADCP 기반 총유사량 모니터링 방법은 기존 자동 유량 관측소 시설을 그대로 이용할 수 있다는 장점이 있다. 따라서 실무 적용 시 낮은 추가비용으로 양질의 유사량 모니터링이 가능할 것으로 기대된다.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.344-352
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• 2022

Accurate indoor localization of construction workers and mobile assets is essential in safety management. Existing positioning methods based on GPS, wireless, vision, or sensor based RTLS are erroneous or expensive in large-scale indoor environments. Tightly coupled sensor fusion mitigates these limitations. This research paper proposes a state-of-the-art positioning methodology, addressing the existing limitations, by integrating Stereo Visual Inertial Odometry (SVIO) with fiducial landmarks called AprilTags. SVIO determines the relative position of the moving assets or workers from the initial starting point. This relative position is transformed to an absolute position when AprilTag placed at various entry points is decoded. The proposed solution is tested on the NVIDIA ISAAC SIM virtual environment, where the trajectory of the indoor moving forklift is estimated. The results show accurate localization of the moving asset within any indoor or underground environment. The system can be utilized in various use cases to increase productivity and improve safety at construction sites, contributing towards 1) indoor monitoring of man machinery coactivity for collision avoidance and 2) precise real-time knowledge of who is doing what and where.

• Journal of Information Technology Services
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• v.22 no.6
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• pp.87-102
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• 2023

Existing child car seats do not have a monitoring means for the driver or guardian to effectively recognize the status of whether the seat belt of car seat is fastened and whether the ISOFIX of the car seat is fastened to the inside device of the vehicle. In this paper, we propose a smart car seat system which can monitor in real time, whether the seat belt of a child seated in the car seat is fastened and whether the ISOFIX of the car seat is fastened. The proposed system has been developed with a prototype, in which a Hall sensor, magnet, Bluetooth, and display device are used to detect whether these are fastened and to display the detection results. The prototype system provides the detection results as texts and alarm signal to the display for driver or guardian' smartphone in the car in motion. With functional tests of the prototype system, it was confirmed that the detection functions are properly operated, and the detection results were transmitted to the display device and smartphone via Bluetooth within 0.5 seconds. It is expected that the development system can effectively prevent safety accidents of child car seats.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.155-160
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• 2023

This paper presents a method for predicting blood pressure using the photoplethysmography signals. First, after measuring the optical blood flow signal, artifacts are removed through a preprocessing process, and a signal for learning is obtained. In addition, weight and height, which affect blood pressure, are measured as additional information. Next, a system is built to estimate systolic and diastolic blood pressure by learning the photoplethysmography signals, height, and weight as input variables through an artificial intelligence algorithm. The constructed system predicts the systolic and diastolic blood pressures using the inputs. The proposed method can continuously predict blood pressure in real time by receiving photoplethysmography signals that reflect the state of the heart and blood vessels, and the height and weight of the subject in an unconstrained method. In order to confirm the usefulness of the artificial intelligence-based blood pressure prediction system presented in this study, the usefulness of the results is verified by comparing the measured blood pressure with the predicted blood pressure.

• Composites Research
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• v.36 no.5
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• pp.342-348
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• 2023

There has been increasing demand for real-time monitoring of body and ambient temperatures using wearable devices. Graphene-based thermistors have been developed for high-performance flexible temperature sensors. In this study, the temperature coefficient of resistance (TCR) of monolayer graphene was controlled by coating polyethylenimine (PEI) on graphene surfaces to enhance its temperature-sensing performances. Monolayer graphene grown by chemical vapor deposition (CVD) was wet-transferred onto a target substrate. To facilitate the interfacial doping by PEI, the hydrophobic graphene surface was altered to be hydrophilic by oxygen plasma treatments while minimizing defect generation. The effect of PEI doping on graphene was confirmed using a back-gated field-effect transistor (FET). The CVD-grown monolayer graphene coated with PEI exhibited an improved TCR of -0.49(±0.03) %/K in a temperature range of 30~50℃.

• Atmosphere
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• v.33 no.5
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• pp.561-570
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• 2023

In order to improve the predictability of marine high-impacts weather such as typhoon and high waves, the marine observation network is an essential because it could be rapidly changed by strong air-sea interaction. In this regard, the National Institute of Meteorological Sciences, Korea Meteorological Administration (NIMS/KMA) has promoted the Argo float observation program since 2001 to participate in the International Argo program. In this study, current status and future direction of the NIMS/KMA Argo program are presented through the internal meeting and external expert forum. To date, a total of 264 Argo floats have been deployed into the offshore around the Korean Peninsula and the Northwestern Pacific Ocean. The real-time and delayed modes quality control (QC) system of Argo data was developed, and an official regional data assembling center (call-sign 'KM') was run. In 2002, the Argo homepage was established for the systematic management and dissemination of Argo data for domestic and international users. The future goal of the NIMS/KMA Argo program is to improve response to the marine high-impacts weather through a marine environment monitoring and observing system. The promotion strategy for this is divided into four areas: strengthening policy communication, developing observation strategies, promoting utilization research, and activating international cooperation.

• Tunnel and Underground Space
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• v.33 no.5
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• pp.425-434
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• 2023

To measure the wear amount of the TBM disk cutter in real time, it is important not only to automate the measurement using sensors, but also to stably transmit the measured data to the information processing system. In this study, we investigated the viability of utilizing Bluetooth Low Energy (BLE) technology to wirelessly transmit sensor data from the TBM cutter head to a receiver located at the chamber's rear. Through laboratory experiments, we analyzed the Received Signal Strength Index (RSSI) of the receiver considering various signal strength of the transmitter, separation distances between the transmitter and receiver and chamber fill materials. Our results demonstrate that wireless data transmission is feasible across all tested conditions when the transmitter signal strength is 0 dBm or higher.

• Journal of the Korean institute of surface engineering
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• v.56 no.6
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• pp.393-400
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• 2023

Acetone, a metabolite detected from the exhaled breath of people doing a diet, can be used for non-invasive monitoring of diet efficiency. Thus, gas sensors with rapid response and recovery characteristics to acetone need to be developed. Herein, we report ultrafast acetone sensors using Ce-doped In₂O₃ nanoparticles prepared by the one-pot microwave-assisted hydrothermal method. The pure In₂O₃ sensor shows a high response and fast response time (τ_res = 6 s) upon exposure to 2 ppm acetone at 300 ℃, while exhibiting a relatively sluggish recovery speed (τ_recov = 1129 s). When 20 wt% Ce is doped, the τ_recov of the sensor significantly decreased to 45 s withholding the fast-responding characteristic (τ_res = 6 s). In addition, the acetone response (resistance ratio, S) of the sensor is as high as 5.8, sufficiently high to detect breath acetone. Moreover, the sensor shows similar acetone sensing characteristics even under a highly humid condition (relative humidity of 60%) in terms of τ_res (6 s), τ_recov (47 s), and S (4.7), demonstrating its high potential in real applications. The excellent acetone sensing characteristics of Ce-doped In₂O₃ nanoparticles are discussed in terms of their size, composition, phase, and oxygen adsorption on the sensing surface.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.151-166
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• 2024

Coastal debris presents a significant environmental threat globally. This research sought to improve the monitoring methods for coastal debris by employing deep learning and remote sensing technologies. To achieve this, an object detection approach utilizing the You Only Look Once (YOLO)v8 model was implemented to develop a comprehensive image dataset for 11 primary types of coastal debris in our country, proposing a protocol for the real-time detection and analysis of debris. Drone imagery was collected over Sinja Island, situated at the estuary of the Nakdong River, and analyzed using our custom YOLOv8-based analysis program to identify type-specific hotspots of coastal debris. The deployment of these mapping and analysis methodologies is anticipated to be effectively utilized in managing coastal debris.