• Journal of the Microelectronics and Packaging Society
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• v.29 no.1
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• pp.67-70
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• 2022

In the present work, we have designed to optimize the optical filter structures of the 1-dimensional photonic quasicrystals (1D PQCs) characteristic for the COVID-19 UV sterilization. The simulator using MATLAB program and ourselves manufacturing calculation codes. After making the aperiodic (and complexed) multi-layer structure model, we establish the transfer matrix method (TMM) for model by the operator conversion. By the using the MATLAB, we derive a matrix for the designed complexed multi-layer structure by applying the equations to the model by obtaining the reflectance and transmittance from the matrix. We also prove the possibility of application in optical filter for UV sterilization.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.45-48
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• 2022

건축물 안전 점검은 대부분 전문가의 현장 방문을 통한 육안검사다. 그중 균열 검사는 건물 위험도를 나타내는 중요한 지표로써 발생 위치, 진행성, 크기를 조사하는데, 최근 균열 조사 방식에 대해 객관성과 체계성을 보완할 딥러닝 개발이 활발하다. 그러나 균열 이미지는 외부 현장에 모양, 규모도 많은 종류라 도메인이 다양해야 하는데 대부분 제한된 환경과 실제적인 균열 검사와는 무관한 데이터로 구성되어 실효적이지 않다. 본 연구에서는 균열 조사에 적합하고 Wild 환경에 적용 가능한 POC 데이터셋을 소개한다. 기존 균열 공인 데이터셋 4종의 특징과 한계점을 분석을 토대로 고해상도 이미지로써 균열의 세부 특징을 담았고 균열 유사 환경과 조건들을 추가 촬영해 균열 검출에 강인하게 학습되도록 지향하였다. 정제 및 라벨링 작업을 거친 POC 데이터 셋은 균열 검출모델인 YOLO-v5으로 성능을 실험하였고, mAP(mean Average Precision) 75.5%로 높은 검출률을 보였다. POC 데이터셋으로 더욱 도메인에 적응적(Domain-adapted)인 인공지능 모델을 개발하여 건물, 댐, 교량 등 각종 대형 건축물에 대한 안전하고 효과적인 안전 관리 도구로써 활용할 것을 기대한다.

• Annual Conference of KIPS
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• 2023.11a
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• pp.475-478
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• 2023

컴퓨터 단층촬영(CT)을 활용한 골격근 단면적은 근감소증과 관련된 기능을 평가하는 데 사용된다. 일반적인 근감소증 연구는 요추 3번의 골격근량을 주로 보지만 암 또는 폐절제술과의 상관관계를 예측하기 위한 다양한 연구에서는 흉추 4번, 7번, 8번, 10번, 12번 다양한 수준의 골격근량으로 연구를 진행하고 있음을 알 수 있다. 본 논문에서는 흉부와 복부 CT 영상에서 근감소증 진단을 위해서 흉추와 요추의 영역별 슬라이스를 검출하기 위해서 CNN 구조의 EfficientNetV2를 전이학습하여 인공지능 모듈을 개발하였다. 인공지능 모듈은 전체 흉부 및 복부 CT 영상에서 Cervical, T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, L1, L2, L3, L4, L5, Sacral 총 19 클래스를 검출하도록 하였다. Test 데이터셋을 사용하여 Confusion Matrix와 Grad-CAM으로 모델의 정확도를 시각화하여 보였으며 검증으로 인공지능 모듈의 정확성을 측정하였다. 끝으로 우리가 개발한 다기관 공동연구 지원플랫폼에 적용하여 시각화된 결과를 보였다.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.203-212
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• 2024

This paper describes the establishment of defense systems test works architecture model for the efficient operation of an expanded test organization and the provision of standardized test services after the integration of proving grounds in ADD. The system engineering vee model is applied to the defense system test works to define the project management model and the unit-test management model. In order to establish the defense systems test works architecture model, the process flow of test works, artifacts by life cycle, and interrelations between regulations and test works are explained, and Integrated Test Information System for implementation of architecture model is discussed. Through the defense systems test works architecture model presented in this study, it will contribute to quickly responding to the test requirements of complex and diverse defense systems, efficiently managing projects, and providing standardized test services.

• Korean Journal of Ecology and Environment
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• v.39 no.4 s.118
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• pp.450-461
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• 2006

In this study, sorption kinetics of lead (Pb) and cadmium (Cd) onto coastal sediments were investigated at pH 5.5 using laboratory batch adsorbers. Four different models: one-site mass transfer model (OSMTM), pseudo-first-order kinetic model (PFOKM) ,pseudo-second-order kinetic model (PSOKM) and two compartment first-order kinetic model (TCFOKM) were used to analyze the sorption kinetics. As expected from the number of model parameters involved, the three-parameter TCFOKM was better than the two-parameter OSMTM, PFOKM and PSOKM in describing sorption kinetics of Pb and Cd onto sediments. Most sorption of Pb and Cd was rapidly completed within the first three hours, followed by slow sorption in the subsequent period of sorption. All models predicted that the sorbed amount at the apparent sorption ($q_{e,s}$) equilibria increased as the CEC and surface area of the sediments increased, regardless of initial spiking concentration ($C_0$) and heavy metal and the sediment type. The sorption rate constant ($k_s,\;hr^{-1}$) in OSMTM also increased as the CEC and BET surface area increased. The rate constant of pseudo-first-order sorption ($k_{p1,s},\;hr^{-1}$) in PFOKM were not correlated with sediment characteristics. The results of PSOKM analysis showed that the rate constant of pseudo-second-order sorption ($k_{p2,s},\;g\;mmol^{-1}\;hr^{-1}$) and the initial sorption rate ($v_{o,s},\;mg\;g^{-1}\;hr^{-1}$) were not correlated with sediment characteristics. The fast sorption fraction ($f_{1,s}$) in TCFOKM increased as CEC and BET surface increased regardless of initial aqueous phase concentrations. The sorption rate constant of fast fraction ($k_{1,s}=10^{0.1}-10^{1.0}\;hr^{-1}$) was much greater than that of slow sorption fraction ($k_{2,s}=10^{-2}-10^{-4}\;hr^{-1}$) respectively.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.469-484
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• 2021

Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, V_p, V_s, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.

• Atmosphere
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• v.32 no.2
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• pp.87-101
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• 2022

In this paper, the performance improvement for the new KMA's Climate Prediction System (GloSea6), which has been built and tested in 2021, is presented by assessing the bias distribution of basic variables from 24 years of GloSea6 hindcasts. Along with the upgrade from GloSea5 to GloSea6, the performance of GloSea6 can be regarded as notable in many respects: improvements in (i) negative bias of geopotential height over the tropical and mid-latitude troposphere and over polar stratosphere in boreal summer; (ii) cold bias of tropospheric temperature; (iii) underestimation of mid-latitude jets; (iv) dry bias in the lower troposphere; (v) cold tongue bias in the equatorial SST and the warm bias of Southern Ocean, suggesting the potential of improvements to the major climate variability in GloSea6. The warm surface temperature in the northern hemisphere continent in summer is eliminated by using CDF-matched soil-moisture initials. However, the cold bias in high latitude snow-covered area in winter still needs to be improved in the future. The intensification of the westerly winds of the summer Asian monsoon and the weakening of the northwest Pacific high, which are considered to be major errors in the GloSea system, had not been significantly improved. However, both the use of increased number of ensembles and the initial conditions at the closest initial dates reveals possibility to improve these biases. It is also noted that the effect of ensemble expansion mainly contributes to the improvement of annual variability over high latitudes and polar regions.

• Korean Journal of Materials Research
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• v.9 no.1
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• pp.86-91
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• 1999

We have fabricated high-$\textrm{T}_c$ superconducting $\textrm{YBa}_{2}\textrm{Cu}_{3}\textrm{O}_{7-x}$(YBCO) grain boundary junctions at a step-edge on (001) $\textrm{SrTiO}_3$(STO) substrates. A diamond-like carbon (DLC) film grown by plasma enhanced chemical vapor deposition were used as an ion milling mask to make steps on the STO (100) single crystal and was removed by an oxygen reactive ion etch process. The c-axis oriented YBCO and TO thin films were deposited epitaxially on the STO substrate with a step-edge by pulsed laser deposition. The grain boundary junctions were formed at the top and the bottom of the step. The junctions worked at temperatures above 77 K, and had I\ulcornerR\ulcorner products of 7.5mV at 16K and 0.3 mV at 77K, respectively. The I-V characteristics of these junctions showed the shape of the two noisy resistively shunted junction model.

• Journal of the Korean Ceramic Society
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• v.41 no.11
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• pp.858-863
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• 2004

The thermoelectric power, dc conductivity and magnetic properties of the cubic L $a_{2}$ 3/Ti $O_{2.84}$ were investigated. The thermoelectric power was negative below 350 K. The measured thermoelectric power of L $a_{2}$ 3/Ti $O_{2.84}$ increased linearly with temperature, in agreement with model proposed by Emin and Wood, and was represented by A+BT. Temperature dependence indicates that the charge carrier in this material is a small polaron. L $a_{2}$ 3/Ti $O_{2.84}$ exhibited a cross over from variable range hopping to small polaron hopping conduction at a characteristic temperature well below room temperature. The low temperature do conduction mechanism in L $a_{2}$ 3/Ti $O_{2.84}$ was analyzed using Mott's approach. Mott parameter analysis gave values for the density of state at Fermi level [N( $E_{F}$)] = 3.18${\times}$10$^{20}$ c $m^{-3}$ e $V^{-1}$ . The disorder energy ( $W_{d}$) was found to be 0.93 eV, However, it was noted that the value of the disorder energy was much higher than the high temperature activation energy. The exist linear relation between log($\sigma$T)와 1/T in the range of 200 to 300 K, the activation energy for small polaron hopping was 0.15 eV.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.226-235
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• 2023

This study aimed to supplement the shortcomings of the Multiple-sensor-based Frost Observation System (MFOS). The developed frost observation system is an improvement of the existing system. Based on the leaf wetness sensor (LWS), it not only detects frost but also functions to predict surface temperature, which is a major factor in frost occurrence. With the existing observation system, 1) it is difficult to observe ice (frost) formation on the surface when capturing an image of the LWS with an RGB camera because the surface of the sensor reflects most visible light, 2) images captured using the RGB camera before and after sunrise are dark, and 3) the thermal infrared camera only shows the relative high and low temperature. To identify the ice (frost) generated on the surface of the LWS, a LWS that was painted black and three sheets of glass at the same height to be used as an auxiliary tool to check the occurrence of ice (frost) were installed. For RGB camera shooting before and after sunrise, synchronous LED lighting was installed so the power turns on/off according to the camera shooting time. The existing thermal infrared camera, which could only assess the relative temperature (high or low), was improved to extract the temperature value per pixel, and a comparison with the surface temperature sensor installed by the National Institute of Meteorological Sciences (NIMS) was performed to verify its accuracy. As a result of installing and operating the MFOS v2, which reflects these improvements, the accuracy and efficiency of automatic frost observation were demonstrated to be improved, and the usefulness of the data as input data for the frost prediction model was enhanced.