• Journal of the Korean Society of Radiology
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• v.14 no.6
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• pp.773-780
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• 2020

With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.8
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• pp.1105-1111
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• 2010

The Korea Atomic Energy Research Institutes has been developing the SMART (System integrated Modular Advanced ReacTor), an environment-friendly nuclear reactor for the generation of electricity and to perform desalination. SMART reactors can be exposed to various external and internal loads caused by seismic and coolant flows. The CRDM(control rod drive mechanism), one of structures of the SMART, is a component which is adjusting inserting amount of a control rod, controlling output of reactor power and in an emergency situation, inserting a control rod to stop the reactor. The purpose of this research is performing the analysis of dynamic characteristic to ensure safety and integrity of structure of CRDM. This paper presents two FE-models, 3-D solid model and simplified Beam model of the CRDM in the coolant, and then compared the results of the dynamic characteristic about the two FE-models using a commercial Finite Element tool, ABAQUS CAE V6.8 and ANSYS V12. Beam 4 and beam 188 of simplified-model were also compared each other. And simplified model is updated for accuracy compare to 3-D solid.

• Journal of Digital Convergence
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• v.15 no.12
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• pp.313-321
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• 2017

Traffic accidents in the country have steadily increased. Although IOT technologies have been applied so as to prevent the primary accident, practical solutions to prevent the secondary accident have not been suggested. A general guideline is simply recommended. In this paper, utilizing existing communication technology, we implement a proposed model and its simulation to prevent the secondary accident. When it is possible for a driver to secure visibility, the secondary accident can be prevented; In areas like tunnel, mountain terrain, and curve road with heavy traffic, where the driver has difficulty in securing the visibility, the secondary accident rates after the primary accident have been increasing. Therefore, we implement an accident prevention system that determines the primary accident utilizing sensor technology and prevents the secondary accident communicating through V2V or V2I. After the simulation, we found that the proposed model and the existing model made no difference with regard to the secondary accident rates when the visibility of the driver is secured; With the application of the proposed model, however, the accident rates decreased for 3-7 percent even though the visibility and communication were not secured.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.291-297
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• 2003

The aim of this research is to propose new framework for taxonomy of various business and its concept, due to the changes in market space. This framework is three-dimension cubic model, based on three concepts, business layer(BL), value chain(VC), and Real/Virtual(R/V) that symbolizes real environment and virtual(or cyber) space. And we showed that this framework is able to describe all expected(or existed) business types in certain industry by the combinations of BL-VC-R/V on three dimension. In addition, we suggested new definition of e-business and e-Logistics from view of BL-VC-R/V. In order to test availability, this framework was applied for logistics related business. and classified typical business types existed (or expected) in logistics area.

• Journal of Navigation and Port Research
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• v.27 no.4
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• pp.389-395
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• 2003

The aim of this research is to propose new framework for taxonomy of various business and its concept. due to the changes in market space. This framework is three-dimension cubic model based on three concepts, business layer(BL), value chain(VC), and Real/Virtual(R/V) that symbolizes real environment and virtual (or cyber) space. We showed that this framework is able to describe all expected(or existed) business types in certain industry by the combinations of BL-VC-R/V on three dimension. In addition, we suggested new definition of e-business and e-Logistics from view of BL-VC-R/V. In order to test availability of framework, this framework was applied for logistics related business, and we classified typical business types existed (or expected) in logistics area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1835-1845
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• 2021

To accurately identify black ice and warn the drivers of information in advance so they can control speed and take preventive measures. In this paper, we propose a lightweight black ice detection network based on infrared road images. A black ice recognition network model based on CNN transfer learning has been developed. Additionally, to further improve the accuracy of black ice recognition, an enhanced lightweight network based on MobileNetV2 has been developed. To reduce the amount of calculation, linear bottlenecks and inverse residuals was used, and four bottleneck groups were used. At the same time, to improve the recognition rate of the model, each bottleneck group was connected to a 3×3 convolutional layer to enhance regional feature extraction and increase the number of feature maps. Finally, a black ice recognition experiment was performed on the constructed infrared road black ice dataset. The network model proposed in this paper had an accurate recognition rate of 99.07% for black ice.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.392-392
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• 2022

세계적 규모의 팬데믹 감염병의 출현은 전 세계적으로 경제적, 문화적, 사회적 파급효과가 매우 강력하며 전 인류를 위협하고 있다. 최근에 발병한 중증급성 호흡기질환 코로나바이러스 2(Severe Acute Respiratory Syndrome Coronavirus 2, SARS-CoV-2)는 2019년 12월 중국 우한에서 첫 보고 되었고 2022년 현재까지 종식되지 않고 있으며 바이러스의 전파력과 치명률이 높고 무증상 감염상태일 때에도 전염이 가능하여 현재 역학조사의 사후적 대응에 대한 한계가 있어 선제적 대응을 위한 수단이 필수 불가결해지고 있는 실정이다. 하수기반역학(Waste Based Epidemiology, WBE)이란 하수처리장으로 유입되기 전의 하수를 분석하여 하수 집수구역 내 도시민의 생활상을 예측하는 것으로 하수로 배출된 감염자의 분비물 및 배설물 속 바이러스를 하수관로에서 신속하게 검출함으로써 특정지역의 감염성 질환 전파 정도와 유행하는 타입(변이)등을 분석하고 기존 역학조사의 문제점을 극복할 수 있으며 선제적인 대응이 가능하다. 현재 COVID-19의 대유행과 관련하여 WBE를 기반으로 한 다양한 연구가 진행되고 있으며 실제 환자의 발생과 상관관계가 있음이 확인되고 있고 백신 접종과 새롭게 발생한 변이바이러스의 관계 속에서 발생하는 변수를 고려한 모델이 없다는 점을 들어 새로운 감염병 확산 예측 모델에 대한 필요성 또한 커지고 있다. 본 연구에서는 병원에서부터 하수처리장까지의 하수관거와 하수처리장에서의 SARS-CoV-2 검출농도 및 거동을 파악하는 것을 목적으로 하고 있으며 COVID-19의 감염규모 확산에 관한 방법론에서 수학적모델 (Euler Method, RK4 Method, Gillespie Algorithm)과 딥러닝 기반의 Nowcasting model과 Fore casting model을 살펴보고자 한다.

• Journal of the Korean Geotechnical Society
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• v.16 no.3
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• pp.39-46
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• 2000

본 논문에서는 배수재가 설치된 구역과 설치되지 않은 구역으로 구성된 Olga-C 시험성토지반의 변형률속도 의존적인 압밀거동을 서술하였다. 배수재가 설치된 지반이 압밀거동에 대한 변형률속도의 영향을 해석하기 위하여 응력-변형률-변형률 속도의 관계식(v-$\varepsilon$v- v)을 이용한 축대칭 비선형 점소성 모델을 제안하였다. 제안된 모델은 실험실과 현장의 변형률속도 차이뿐만 아니라 간극수압의 소산과 생성의 복합적인 압밀과정을 고려할 수 있다. 연직 및 반경방향의 배수효과에 의해 배수재가 설치된 지반(Zone B)에서 유발되는 변형률 속도는 배수재가 설치되지 않은 연약지반 (Zone A)의 변형률 속도보다 크다. 유발된 변형률 속도의 영향으로 Zone B의 선행압밀하중도 Zone A에서 유발되는 선행압밀하중보다 크다. Olga-C 지역의 Zone A 에서는 응력완화효과가 유발되지만, Zone B에서는 응력완화효과가 유발 되지 않았다.

• Journal of computational fluids engineering
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• v.10 no.4 s.31
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• pp.1-11
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• 2005

A numerical study of the evaluation of turbulence models for thermal striping phenomenon is performed. The turbulence models chosen in the present study are the two-layer model, the shear stress transport (SST) model and the V2-f model. These three models are applied to the analysis of the triple-jet flow with the same velocity but different temperatures. The unsteady Reynolds-averaged Navier-Stokes (URANS) equation method is used together with the SIMPLEC algorithm. The results of the present study show that the temporal oscillation of temperature is predicted by the SST and V2-f models, and the accuracy of the mean velocity, the turbulent shear stress and the mean temperature is a little dependent on the turbulence model used. In addition, it is shown that both the two-layer and SST models have nearly the same capability predicting the thermal striping, and the amplitude of the temperature fluctuation is predicted best by the V2-f model.

• TTA Journal
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• s.92
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• pp.131-137
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• 2004

TTA(한국정보통신기술협회)는 2004년 2월 17일 엔텔테크놀로지㈜(http://www.ntel21.com/) VoIP Gateway(모델명: NT-301)의 기능 및 성능 시험을 수행하여 TTA Verified 인증서(번호: TTA-V-N-04-001)를 발급하였다. 또한 2004년 3월 10일 HS 텔리안㈜(http://www.hsteliann.com/) VoIP Gateway(모델명: Telimax414)의 시험을 수행하여 TTA Verified 인증서(번호: TTA-V-N-04-003)를 발급하였다. 위의 두 장비는 FXS 포트 및 PSTN 백업 포트 그리고 이더넷 포트가 장착된 장비로서, TTA가 위의 두 장비에 대하여 수행한 시험은 기능 확인 및 성능 평가를 측정하는 것이었다. 본 고에서는 TTA가 마련한 소용량 VoIP Gateway에 대한 인증기준(TTA-V-N-03-009-CC12)을 바탕으로 위의 두 장비에 대해 수행한 기능 및 성능 시험결과를 소개한다.