• Archives of Plastic Surgery
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• v.50 no.3
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• pp.254-263
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• 2023

Background The three-dimensional (3D) evaluation of skeletal stability after orthognathic surgery is a time-consuming and complex procedure. The complexity increases further when evaluating the surgery-first orthognathic approach (SFOA). Herein, we propose and validate a simple time-saving method of 3D analysis using a single software, demonstrating high accuracy and repeatability. Methods This retrospective cohort study included 12 patients with skeletal class 3 malocclusion who underwent bimaxillary surgery without any presurgical orthodontics. Computed tomography (CT)/cone-beam CT images of each patient were obtained at three different time points (preoperation [T0], immediately postoperation [T1], and 1 year after surgery [T2]) and reconstructed into 3D images. After automatic surface-based alignment of the three models based on the anterior cranial base, five easily located anatomical landmarks were defined to each model. A set of angular and linear measurements were automatically calculated and used to define the amount of movement (T1-T0) and the amount of relapse (T2-T1). To evaluate the reproducibility, two independent observers processed all the cases, One of them repeated the steps after 2 weeks to assess intraobserver variability. Intraclass correlation coefficients (ICCs) were calculated at a 95% confidence interval. Time required for evaluating each case was recorded. Results Both the intra- and interobserver variability showed high ICC values (more than 0.95) with low measurement variations (mean linear variations: 0.18 mm; mean angular variations: 0.25 degree). Time needed for the evaluation process ranged from 3 to 5 minutes. Conclusion This approach is time-saving, semiautomatic, and easy to learn and can be used to effectively evaluate stability after SFOA.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.62-69
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• 2022

An electrocardiogram (ECG) is one of the most important biosignals, and in particular, continuous ECG monitoring is very important in patients with arrhythmia. There are many different types of arrhythmia (sinus node, sinus tachycardia, atrial premature beat (APB), and ventricular fibrillation) depending on the cause, and continuous ECG monitoring during daily life is very important for early diagnosis of arrhythmias and setting treatment directions. The ECG signal of arrhythmia patients is very unstable, and it is difficult to detect the R-peak point, which is a key feature for automatic arrhythmias detection. In this study, we develped a continuous measuring Holter ECG monitoring device and software for analysis and confirmed the utility of R-peak of the ECG signal with MIT-BIH arrhythmia database. In future studies, it needs the validation of algorithms and clinical data for morphological classification and prediction of arrhythmias due to various etiologies.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.3
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• pp.266-274
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• 2023

Recently, sterilization technology has received increasing interest due to the COVID-19 pandemic and required safety precautions. Particularly, sterilization devices using near ultraviolet (UV) with a 405 nm wavelength are also drawing attention. It has a UV-C wavelength and other sterilization effects. Its blue-colored light on the boundary between UV and visible light is used as a light-emitting diode (LED) lamp for 405 nm sterilization, owing to its longer wavelengths than UV rays. However, the 405 nm wavelength contains blue light that can damage the eyes and skin during prolonged exposures and affect the emotional and biological parts of the body. Currently, 405 nm sterilization LED light registers are circulating in the market. However, they have not undergone safety tests for blue-light hazards. Thus, with the active distribution of sterilization LED lights, solid safety standards and management systems are essential to protect users from blue-light hazards. Accordingly, in this study, we conducted spectral radiance and spectral radiative luminance tests on 405 nm sterilization LED registers available in the market by the measurement criteria of IEC 62471. Safety standards must be established to secure users' safety against blue light hazards at a time when 405nm sterilization LED lights are actively distributed due to COVID-19.

• Fashion & Textile Research Journal
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• v.25 no.1
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• pp.92-103
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• 2023

As the body shape change which occurs after middle age is the main factor affecting the fit of ready-to-wear clothes, this study was designed to classify and analyze the torso shapes of middle-aged men. This study sorted 3D body scans of 200 men aged 40-64 from the 8th Size Korea (2021) database and extracted their 47 measurement values using the Grasshopper algorithm for automatic extraction landmarks and measurements, developed by the previous research (Ryu & Song, 2022). Eight principal components (torso length, shoulder size, overall body size, abdomen prominence, back protrusion, neck inclination, upper body slope, and hip prominence) were identified and four torso shapes were classified. Shape 1 (28.5%) exhibited the shortest torso length, the narrowest shoulders, and the most protruding back. Shape 2 (21.0%) exhibited the skinniest body and the largest backward inclination of the upper body. Hence, the back appeared to be protruding, and the abdomen looked prominent. Shape 3 (25.5%) had the largest overall body size. Thus, the abdomen looked the least protruding, and it exhibited the flattest back. Shape 4 (25.0%) had the longest torso, widest shoulders, straightest neck, and the least protruding hips. This study suggested these three discriminant functions to identify a new person's torso type.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.383-383
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• 2021

강수는 수자원 분석 및 지리학적 연구에 가장 핵심적으로 쓰이는 수문인자이며, 최근 기후변화와 방재 관련한 다양한 연구에서 정확한 강수자료의 중요성이 부각되고 있다. 특히, 강수는 지표에서의 유출, 침투, 증발 등 다양한 수문현상으로 이어지므로, 수문순환, 물수지 분석에 있어 강우강도 등 강수 발생 양상과 유형에 대한 정확한 자료는 필수불가결하다. 강수량은 Automatic Weather Station (AWS)을 통해 비교적 정확하게 측정되고 있으나, 이러한 계측자료는 기상학적, 지형적 영향을 크게 받으며 대표성이 좁다는 단점을 가지고 있어 유출 및 기후 등 공간적 범위를 대상으로 한 연구에 활용하기에 한계점을 가지고 있다. 이러한 한계점을 극복하기 위해 지상강우레이더를 통한 국지적 강수자료 및 인공위성 기반 전 지구적 강수 관측 자료가 활용되고 있다. 특히 인공위성을 활용한 강우 측정방법은 미계측 유역에서 수자원 측정 및 관리 계획을 세우거나 전 지구적으로 장기적 변화를 분석하는데 있어 가장 활용도가 높다. National Aeronautics and Space Administration (NASA)의 Tropical Rainfall Measuring Mission (TRMM)을 포함한 기존 강수측정 보조 위성에 더하여 2014년 Global Precipitation Measurement (GPM) 핵심 위성이 발사된 이후 다양한 기관에서 여러 인공위성을 결합한 강수 산출물들을 제공하고 있다(NASA-IMERG, JAXA-GSMAP, NOAA-CMORPH). 본 연구에서는 세 가지 위성 기반 강수 자료의 산출 알고리즘을 비교□분석하고, 강우강도에 따른 산출물들의 정확도를 평가하였다. 본 연구결과는 높은 강우강도 발생 시 나타나는 위성 강수자료의 불확실성을 개선하는 데 기여할 수 있을 것으로 판단되며, 이후 신뢰도 높은 다중 위성 융합 강수 산출물을 구현하기 위한 바탕이 될 것으로 기대된다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.727-730
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• 2023

The operation of electric automatic windows is used in harsh environments, and the energy density decreases as charging and discharging are repeated, and as soundness deteriorates due to damage to the internal separator, the vehicle's mileage decreases and the charging speed slows down, so about 5 to 10 Batteries that have been used for about a year are classified as waste batteries, and for this reason, as the risk of battery fire and explosion increases, it is essential to diagnose batteries and estimate SOH. Estimation of current battery SOH is a very important content, and it evaluates the state of the battery by measuring the time, temperature, and voltage required while repeatedly charging and discharging the battery. There are disadvantages. In this paper, measurement of discharge capacity (C-rate) using a waste battery of a Tesla car in order to predict SOH estimation of a lithium-ion battery. A Support Vector Machine (SVM), one of the machine models, was applied using the data measured from the waste battery.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.2
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• pp.148-157
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• 2022

Research on hydrogen storage is active to properly deal with hydrogen, which is considered a next-generation energy medium. In particular, research on metal hydride with excellent safety and energy efficiency has attracted attention, and among them, magnesium-based hydrogen storage alloys have been studied for a long time due to their high storage density, low cost, and abundance. However, Mg-based alloys require high temperature conditions due to strong binding enthalpy, and have many difficulties due to slow hydrogenation kinetics and reduction in hydrogen storage capacity due to oxidation, and various strategies have been proposed for this. This research manufactured Mg₂Ni to improve hydrogenation kinetics and synthesize about 5, 10, 20 wt% of CaF₂ as a catalyst for controlling oxidation. Mg₂NiHx-CaF₂ produced by hydrogen induced mechanical alloying analyzed hydrogenation kinetics through an automatic PCT measurement system under conditions of 423 K, 523 K, and 623 K. In addition, material life cycle assessment was conducted through Gabi software and CML 2001 and Eco-Indicator 99' methodology, and the environmental impact characteristics of the manufacturing process of the composites were analyzed. In conclusion, it was found that the effects of resource depletion (ARD) and fossil fuels had a higher burden than other impact categories.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.90-90
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• 2022

전자파표면유속계를 이용한 유량측정은 전자파를 발사한 후 수표면에 반사되는 전자파의 도플러효과를 이용하여 표면유속을 측정하는 방법이다. 국제적으로 1980년대부터 홍수유량측정의 어려움을 극복하고자 전자파표면유속계를 개발하여 하천 유량측정 업무에 활용하였다. 미국의 경우U.S. Geological Survey (USGS)에서 교량, 케이블웨이, 제방, 헬리콥터, 비행기 등 전자파표면유속계의 측정 위치에 따라 주파수 범위를 달리하며 유속을 측정하는 연구가 진행되었다. 국내의 경우 Lee et al.(2021)은 드론을 이용한 전자파표면유속계 측정을 위해 드론으로부터 전자파표면유속계로 전달되는 진동을 제거하고 전자파표면유속계의 흔들림 방지를 위한 댐퍼플레이트를 개발하여 드론과 전자파표면유속계를 결합한 DSVM(Dron and Surface Veloctity Meter using doppler radar) 측정방법에 대한 실용성을 확인하였다. 기존 연구에서 DSVM 방법은 드론의 각 측선 이동을 위한 조종 및 전자파표면유속계 측정의제어를 측정자가 수행하였는데 본 연구에서는 자동 측정 시스템 개발을 통해 측정자의 조종 의존도를 줄임과 동시에 안전하고 정확한 유량측정을 위해 노력하였다. 측정지점의 위치정보를 DB화하여 각 측선별 이동하는 자율운항 기능과 전자파표면유속계를 자동으로 제어하여 측정을 실시하는 기능을 개발하였다. 또한 전자파표면유속계 컨트롤 시스템과 GCS(Ground Control System)를 통합하여 한 시스템에서 측정의 모든 상황을 컨트롤 할 수 있게 하였다. 현재까지는 DSVM 방법의 자율운항 기능과 자동 측정 시스템의 테스트를 완료하였고 2022년 홍수기 유량측정에 도입하여 홍수기 유량측정의 실용성을 판단할 계획이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.174-174
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• 2022

수질지수는 여러 수질 데이터 값을 수학적으로 결합하고 다 변수 특성을 줄여 수치 및 등급으로 나타낸 지표이다. 수질지수를 통해 수질을 평가하고 서로 다른 위치와 시간의 수역을 종합적으로 비교할 수 있으며 수자원관리에 있어 정책입안자, 의사결정자, 국민이 수질에 대해 일반적이고 쉽게 이해할 수 있다. 현재 환경부에서는 국내수질자동측정망 최근 12시간 데이터 값을 근거로 실시간수질지수 RTWQI(Real-Time Water Quality)값을 제공한다. 국내 호소에 설치된 수질 자동측정망은 총 8개소이며 매 시간 공통 항목인 수온, pH, DO, 전기전도도, TOC 5개, 선택항목인 탁도, Chl-a, TN, TP, 중금속, 생물감시항목 등 27개를 측정한다. RTWQI는 캐나다에서 2001년에 개발된 CCME WQI(Canadian Council of Ministers of the Environment Water Quality Index) 산출식을 기초하였으며 F1(기준치를 위반하는 수질항목의 개수/ 총 수질항목 개수), F2(기준치를 위반한 샘플들의 총 횟수/총 샘플횟수) F3(기준치를 위반한 정도) 3가지의 요소로 계산된다. 그러나RTWQI 산출식의 기초인 CCME WQI는 개발 이후 여러 문제점들은 개선되었으나 F1이 다른 F2, F3 보다 CCME WQI 점수의 기여도가 2배 이상 높은 문제점은 개선하지 못하였다. 본 연구에서는 수질자동측정망이 설치된 2012년 7월부터 2021년 12월 동안 매 시간 별 수질 데이터를 이용하였다. 또한 CCME WQI 문제점을 개선한 MWQI(Modification of Canadian water qaulity index)를 기초하여 실시간 수질지수를 재 산정하였다. 추가적으로 Pearson 상관관계 분석 및 추가 통계분석을 통해 환경부에서 제공하는 기존의 RTWQI, 개선된 실시간수질지수, 한국형 호소수질평가지수 LQI(Lake Water Quality Index)를 비교 및 평가하였다. 이러한 연구를 통해 정확성 높은 수질지수를 찾고 수자원 관리 정책 수립에 적극 활용 될 수 있을 것으로 사료된다.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.81-81
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• 2022

Recently, many studies on big data based smart farming have been conducted. Research to quantify morphological characteristics using image data from various crops in smart farming is underway. Rice is one of the most important food crops in the world. Much research has been done to predict and model rice crop yield production. The number of productive tillers per plant is one of the important agronomic traits associated with the grain yield of rice crop. However, modeling the basic growth characteristics of rice requires accurate data measurements. The existing method of measurement by humans is not only labor intensive but also prone to human error. Therefore, conversion to digital data is necessary to obtain accurate and phenotyping quickly. In this study, we present an image-based method to predict leaf number and evaluate tiller number of individual rice crop using YOLOv5 deep learning network. We performed using various network of the YOLOv5 model and compared them to determine higher prediction accuracy. We ako performed data augmentation, a method we use to complement small datasets. Based on the number of leaves and tiller actually measured in rice crop, the number of leaves predicted by the model from the image data and the existing regression equation were used to evaluate the number of tillers using the image data.