• Nuclear Engineering and Technology
• /
• 제53권9호
• /
• pp.3026-3034
• /
• 2021

Multi-target X-ray tube is a new type X-ray source, and can be applied in many fields such as sensitive X-ray fluorescence analysis and medical imaging. In this work, we report an electric field modulation multi-target X-ray tube, which contains four targets (Cr, Ni, Au, Mo) coated on a Beryllium (Be) window. A four-valve electric field deflector was developed to deflect the electron beam to bombard the corresponding targets. Particle dynamics analysis software was employed to simulate the particle tracking of electron beam. The results show that the 30 keV electron beam could get a 6.7 mm displacement on the target plane by 10⁵ V/m electric field. The focus areas are about 2 mm × 5 mm and 4 mm × 2.5 mm after deflection in two directions. Thermal behavior calculated by ANSYS shows that the designed target assembly could withstand a 10 W continuous power. The optimum target thicknesses and emission spectra were obtained by Geant4 when the thickness of Be window was 300 mm and the electron beam incident angle was 0.141 rad. The results indicate that this multi-target X-ray tube could provide different X-ray sources effectively.

• 한국항공우주학회지
• /
• 제46권12호
• /
• pp.975-985
• /
• 2018

드론은 군사적 목적으로 개발이 시작되어 현재에는 물류, 통신, 농업, 재난, 방위, 미디어 등 많은 분야에 활용되고 있다. 드론의 사용범위가 넓어짐에 따라 드론이 악용되는 사례도 증가하고 있다. 드론이 비행할 때 발생하는 물리적 현상들을 이용하여 원치 않는 드론의 위치를 탐지하는 안티 드론 기술 개발이 필요하다. 본 논문에서는 드론이 비행할 때 발생하는 음향신호를 이용하여 드론의 위치를 도래각으로 추정하였다. 또한 드론의 운동역학 모델을 무향 칼만 필터에 적용하여 마이크로폰 어레이 탐지 성능을 향상시켜 위치 추정의 오차를 저감하였다. 시뮬레이션을 통해 드론 탐지 성능을 예측하고 실험을 통해 증명하였다.

• 한국광학회지
• /
• 제30권1호
• /
• pp.1-7
• /
• 2019

휴대용 대공유도 미사일(Man-Portable Air Defense System)은 플룸의 중적외선 신호를 추적하는 적 항공기의 대응무기체계이다. 안개 조건에서 입자들에 의한 다중 산란현상은 중적외선 파장에서의 투과율과 휴대용 대공유도 미사일 탐지성능에 영향을 준다. 그러므로 본 연구에서 다양한 안개조건과 플룸의 특성에 따른 휴대용 대공유도 미사일의 lock-on range를 분석한다. 안개 조건에서의 광학적 소멸특성과 투과율을 분석하기 위해 미산란(Mie scattering) 이론과 복사전달방정식의 분석적 해를 활용하였다. 뿐만 아니라 중적외선 대체광원으로서 섬광탄 화염 신호를 운용했다. 다양한 시정 및 화염 온도조건에서 분석된 lock-on range는 mist 조건에서 크게 감소하며, 화염 온도가 높아질수록 증가하는 것으로 확인하였다.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2014년도 추계학술대회
• /
• pp.577-580
• /
• 2014

본 논문에서는 자동 스위칭 기능을 갖는 이중 입력 에너지 하베스팅 회로를 제안한다. 열전소자와 진동소자로부터 출력되는 에너지는 최대 가용전력지점이 개방전압의 1/2로 같기 때문에 동일한 MPPT(Maximum Power Point Tracking) 제어회로를 사용할 수 있다. 제안된 회로는 하나의 MPPT 제어회로를 사용하고, 자동 스위칭 기능을 적용하여 열전소자의 출력과 진동소자의 출력을 모니터링하여 전압이 더 큰 소자로부터 최대 가용전력을 수확한다. 수확된 에너지는 전하펌프 회로에 의해 승압된 후 저장 커패시터에 저장되고 PMU(Power Management Unit)를 통해 부하에 공급된다. 제안된 회로는 $0.35{\mu}m$ CMOS 공정으로 설계하였으며, 모의실험을 통해 동작을 검증하였다. 설계된 최초의 칩 면적은 PAD를 포함하여 $1.4mm{\times}1.2mm$이다.

• 한국환경농학회지
• /
• 제38권3호
• /
• pp.185-196
• /
• 2019

BACKGROUND: This study investigated the effects of rice genetically modified to be resistant against rice blast and rice bacterial blight on the soil microbial community. A comparative analysis of the effects of rice genetically modified rice choline kinase (OsCK1) gene for disease resistance (GM rice) and the Nakdong parental cultivar (non-GM rice) on the soil microbial community at each stage was conducted using rhizosphere soil of the OsCK1 and Nakdong rice. METHODS AND RESULTS: The soil chemistry at each growth stage and the bacterial and fungal population densities were analyzed. Soil DNA was extracted from the samples, and the microbial community structures of the two soils were analyzed by pyrosequencing. No significant differences were observed in the soil chemistry and microbial population density between the two soils. The taxonomic analysis showed that Chloroflexi, Proteobacteria, Firmicutes, Actinobacteria, and Acidobacteria were present in all soils as the major phyla. Although the source tracking analysis per phylogenetic rank revealed that there were differences in the bacteria between the GM and non-GM soil as well as among the cultivation stages, the GM and non-GM soil were grouped according to the growth stages in the UPGMA dendrogram analysis. CONCLUSION: The difference in bacterial distributions between Nakdong and OsCK1 rice soils at each phylogenetic level detected in microbial community analysis by pyrosequencing may be due to the genetic modification done on GM rice or due to heterogeneity of the soil environment. In order to clarify this, it is necessary to analyze changes in root exudates along with the expression of transgene. A more detailed study involving additional multilateral soil analyses is required.

• Genomics & Informatics
• /
• 제19권4호
• /
• pp.49.1-49.11
• /
• 2021

Nowadays, Genomic data constitutes one of the fastest growing datasets in the world. As of 2025, it is supposed to become the fourth largest source of Big Data, and thus mandating adequate high-performance computing (HPC) platform for processing. With the latest unprecedented and unpredictable mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the research community is in crucial need for ICT tools to process SARS-CoV-2 RNA data, e.g., by classifying it (i.e., clustering) and thus assisting in tracking virus mutations and predict future ones. In this paper, we are presenting an HPC-based SARS-CoV-2 RNAs clustering tool. We are adopting a data science approach, from data collection, through analysis, to visualization. In the analysis step, we present how our clustering approach leverages on HPC and the longest common subsequence (LCS) algorithm. The approach uses the Hadoop MapReduce programming paradigm and adapts the LCS algorithm in order to efficiently compute the length of the LCS for each pair of SARS-CoV-2 RNA sequences. The latter are extracted from the U.S. National Center for Biotechnology Information (NCBI) Virus repository. The computed LCS lengths are used to measure the dissimilarities between RNA sequences in order to work out existing clusters. In addition to that, we present a comparative study of the LCS algorithm performance based on variable workloads and different numbers of Hadoop worker nodes.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제27권4호
• /
• pp.37-48
• /
• 2022

Accurate analysis of petroleum hydrocarbons in soil is an important prerequisite for proper source tracking of contamination. Identification of petroleum compounds is commonly carried out by peak pattern matching in gas chromatography. However, this method has several technical limitations, especially when the soils underwent biological, physical and chemical transformation. For instance, it is very difficult to distinguish jet fuel (JP-8) from kerosene because JP-8 is derivatized from secondary reaction between chemical agents (e.g. anti-oxidants, antifreezer and so on) and kerosene. In this study, an alternative method to separately analyze JP-8 and kerosene in the petroleum hydrocarbon contaminated soil was proposed. Qualitative analyses were performed for representative phenolic antioxidants [2,6-di-tert-butyl phenol (2,6-DTBP), 2,4-di-tert- butylphenol(2,4-DTBP), 2,6-di-tert-butyl-4-methyl phenol (2,6-DTBMP)] using a two dimensional gas chromatograph mass spectrometer (2D GC×GC-TOF-MS). This qualitative analysis of antioxidants in soil would be a useful complementary tool for the peak pattern matching method to identify JP-8 contamination in soil.

• 스마트미디어저널
• /
• 제12권7호
• /
• pp.59-67
• /
• 2023

최근 인간의 자세와 행동을 추적하는 행동 분석 연구가 활발해지고 있다. 특히 2017년 CMU에서 개발한 오픈소스인 오픈포즈(OpenPose)는 사람의 외모와 행동을 추정하는 대표적인 방법이다. 오픈포즈는 사람의 키, 얼굴, 손 등의 신체부위를 실시간으로 감지하고 추정할 수 있어 스마트 헬스케어, 운 동 트레이닝, 보안시스템, 의료 등 다양한 분야에 적용될 수 있다. 본 논문에서는 헬스장에서 사용자들이 가장 많이 운동하는 Squat, Walk, Wave, Fall-down 4개 동작을 오픈포즈기반 딥러닝인 DNN과 CNN을 이용하여 운동 동작 분류 방법을 제안한다. 학습데이터는 녹화영상 및 실시간으로 카메라를 통해 사용자의 동작을 캡처해서 데이터 셋을 수집한다. 수집된 데이터 셋은 OpenPose을 이용하여 전처리과정을 진행하고, 전처리과정이 완료된 데이터 셋은 본 논문에서 제안한 DNN 및 CNN 모델 이용하여 운동 동작 분류를 학습한다. 제안한 모델에 대한 성능 오차는 MSE, RMSE, MAE를 사용한다. 성능 평가 결과, 제안한 DNN 모델 성능이 제안한 CNN 모델보다 우수한 것으로 나타났다.

• Journal of Positioning, Navigation, and Timing
• /
• 제13권1호
• /
• pp.85-92
• /
• 2024

This study develops a Global Positioning System (GPS) Code Multipath Grid Map (CMGM) of each individual domestic reference station from the extracted code multipath of measurement data. Multipath corresponds to signal reflection/refraction caused by obstacles around the receiver antenna, and it is a major source of error that cannot be eliminated by differencing. From the receiver-independent exchange format (RINEX) data for two days, the associated code multipath of a satellite tracking arc is extracted. These code multipath data go through bias correction and interpolation to yield the CMGM with respect to the azimuth and elevation angles. The effect of the CMGM on multipath mitigation is then quantitatively analyzed to improve the Root Mean Square (RMS) of averaged pseudo multipath. Furthermore, the single point positioning (SPP) accuracy is analyzed in terms of the RMS of the horizontal and vertical errors. During two weeks in February 2023, the RMSs of the averaged pseudo multipath for five reference stations decreased by about 40% on average after CMGM application. Also, the SPP accuracies increased by about 7% for horizontal errors and about 10% for vertical errors on average after CMGM application. The overall quantitative analysis indicates that the proposed approach will reduce the convergence time of Differential Global Navigation Satellite System (DGNSS), Real-Time Kinematic (RTK), and Precise Point Positioning (PPP)-RTK correction information in real-time to use measurement data whose code multipath is corrected and mitigated by the CMGM.

• Smart Structures and Systems
• /
• 제33권4호
• /
• pp.291-300
• /
• 2024

Uncertainty of the model, system delay and drive dynamics can be considered as normal uncertainties, and the main source of uncertainty in the seismic control system is related to the nature of the simulated seismic error. In this case, optimizing the management strategy for one particular seismic record will not yield the best results for another. In this article, we propose a framework for online management of active structural management systems with seismic uncertainty. For this purpose, the concept of reinforcement learning is used for online optimization of active crowd management software. The controller consists of a differential controller, an unplanned gain ratio, the gain of which is enhanced using an online reinforcement learning algorithm. In addition, the proposed controller includes a dynamic status forecaster to solve the delay problem. To evaluate the performance of the proposed controllers, thousands of ground motion data sets were processed and grouped according to their spectrum using fuzzy clustering techniques with spatial hazard estimation. Finally, the controller is implemented in a laboratory scale configuration and its operation is simulated on a vibration table using cluster location and some actual seismic data. The test results show that the proposed controller effectively withstands strong seismic interference with delay. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results is believed to achieved in the near future by the ongoing development of AI and control theory.