• 융합정보논문지
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• 제11권11호
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• pp.38-43
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• 2021

증강현실기술을 사용하는 증강현실 게임이 늘어남에 따라 사용자들의 요구도 많아지고 있다. 증강현실 게임에서 사용되는 게임 기술에는 MARKER, MARKERLESS, GPS등을 활용한 게임이 주를 이루고 있다. 이러한 기술을 활용한 게임은 배경과 다른 오브젝트를 증강할 수가 있다. 이 문제를 해결하기 위해 증강현실의 중요한 요소인 배경에서 객체를 분석하여 증강현실 게임을 개발하는데 도움을 주고자 한다. 증강현실 게임에서 배경을 분석하기 위해 UNITY엔진에서 TensorFlow Lite를 활용하여 딥러닝 모델을 적용하여 배경 객체를 분석하였다. 이 결과를 활용하여 배경에서 분석된 객체의 종류에 맞춰 게임에 증강되는 오브젝트를 배치 할 수 있다는 결과를 얻었다. 이 연구를 활용하여 배경에 맞는 오브젝트를 증강하여 향상된 증강현실 게임을 개발 할 수 있을 것이다.

• Plant Breeding and Biotechnology
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• 제6권4호
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• pp.313-320
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• 2018

Rice is the staple food of more than 50% of the world population. Cultivated rice has the AA genome (diploid, 2n = 24) and small genome size of only 430 megabase (haploid genome). As the sequencing of rice genome was completed by the International Rice Genome Sequencing Project (IRGSP), many researchers in the world have been working to explore the gene function on rice genome. Insertional mutagenesis has been a powerful strategy for assessing gene function. In maize, well characterized transposable elements have traditionally been used to clone genes for which only phenotypic information is available. In rice endogenous mobile elements such as MITE and Tos have been used to generate gene-tagged populations. To date T-DNA and maize transposable element systems have been utilized as main insertional mutagens in rice. The Ac/Ds system offers the advantage of generating new mutants by secondary transposition from a single tagged gene. To enhance the efficiency of gene detection, advanced gene-tagging systems (i.e. activation, gene or enhancer trap) have been employed for functional genomic studies in rice. Internationally, there have been many projects to develop large scales of insertional mutagenized populations and databases of insertion sites has been established. Ultimate goals of these projects are to supply genetic materials and informations essential for functional analysis of rice genes and for breeding using agronomically important genes. In this report, we summarize the current status of Ac/Ds-mediated gene tagging systems that has been conducted by collaborative works in Korea.

• 한국ITS학회 논문지
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• 제20권3호
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• pp.74-85
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• 2021

전파를 수신하여 측위를 수행하는 GNSS 수신기는 본질적으로 재밍에 취약하다. 재밍 발생 검출, 재밍 신호 종류 판별, 재밍원 위치추정 기능을 갖는 GNSS 재밍 모니터링 시스템은 안전한 자율주행 환경구축에 도움을 준다. 이를 위하여 다수의 저가 GNSS 수신기들의 배치로 구성된 GNSS 모니터링 네트워크 구축이 필요하며, 앞서 언급한 3가지 기능 구현을 위하여 네트워크 내 독립된 저가 GNSS 수신기 간 정밀 시각 동기가 요구된다. 본 논문은 신호영역 TDOA 기술 직접 사용방식의 수신기 간 시각 동기화 기법을 제안한다. 계산 효율성을 위하여 상대적으로 낮은 샘플링 주파수에도 시각 동기 정밀도를 유지하고자 블록 보간법을 추가로 활용한다. 수치적 시뮬레이션을 통하여 제안한 GNSS 수신기 간 시각 동기화 기법의 가용성을 입증한다.

• Advances in nano research
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• 제10권3호
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• pp.295-312
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• 2021

A new ionic liquid functionalized magnetic silica nanoparticle was synthesized and characterized and tested as an adsorbent. The adsorbent was used for magnetic solid phase extraction on ICP-MS method. Simultaneous determination of precious metal Au has been addressed. The method is simple and fast and has been applied to standard water and surface water analysis. A new method for separation/analysis of trace precious metal Au by Magnetron Solid Phase Extraction (MSPE) combined with ICP-MS. The element to be tested is rapidly adsorbed on CoFe2O4@SiO2@[BMIM]PF6 composite nano-adsorbent and eluted with thiourea. The method has a preconcentration factor of 9.5-fold. This method has been successfully applied to the determination of gold in actual water samples. Hydrophobic Ionic Liquids (ILs) 1-butyl-3-methylimidazole hexafluorophosphate ([BMIM]PF6) coated CoFe2O4@SiO2 nanoparticles with core-shell structure to prepare magnetic solid phase extraction agent (CoFe2O4@SiO2@ILs) and establish a new method of MSPE coupled with inductively coupled plasma mass spectrometry for separation/analysis of trace gold. The results showed that trace gold was adsorbed rapidly by CoFe2O4@SiO2@[BMIM]PF6 and eluanted by thiourea. Under the optimal conditions, preconcentration factor of the proposed method was 9.5-fold. The linear range, detection limit, correlation coefficient (R) and relative standard deviation (RSD) were found to be 0.01~1000.00 ng·mL-1, 0.001 ng·mL-1, 0.9990 and 3.4% (n = 11, c = 4.5 ng·mL-1). The CoFe2O4@SiO2 nanoparticles could be used repeatedly for 8 times. This proposed method has been successfully applied to the determination of trace gold in water samples.

• Structural Engineering and Mechanics
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• 제83권3호
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

• 한국초지조사료학회지
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• 제42권3호
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• pp.195-200
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• 2022

Sulfur is an essential element in plants, including amino acids, vitamin synthesis, and acting as an antioxidant. However, the interaction between endogenous sulfur and proline synthesis has not been yet fully documented. White clover (Trifolium repens L.) is known as a species highly sensitive to sulfate supply. Therefore, this study aimed to elucidate the role of sulfur in regulating proline metabolism in relation to ammonia detoxification and hydrogen peroxide (H₂O₂) accumulation in white clover. The detached leaves of white clover were immersed in solution containing different concentration of sulfate (0, 10, 100, and 1000 mM MgSO₄). As MgSO₄ concentrations were increased, the concentration of H₂O₂ increased up to 2.5-fold compared to control, accompanied with H₂O₂ detection in leaves. Amino acid concentrations significantly increased only at higher levels (100 and 1000 mM MgSO₄). No significant difference was observed in protein concentration. Proline and ∆^1-pyrroline-5-carboxylate (P5C) concentrations slightly decreased at 10 and 100 mM MgSO₄ treatments, whereas it rapidly increased over 1.9-fold at 1000 mM MgSO₄ treatment. Ammonia concentrations gradually increased up to 8.6-fold. These results indicate that exogenous sulfur levels are closely related to H₂O₂ and ammonia synthesis but affect proline biosynthesis only at a higher level.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3604-3613
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• 2022

The Physical Protection System (PPS) plays an important role and must effectively deal with various adversary attacks in nuclear security. In specific single adversary path scenarios, we can calculate the PPS effectiveness by EASI (Estimated Adversary Sequence Interruption) through Probability of Interruption (P_I) calculation. EASI uses a single value of the probability of detection (P_D) and the probability of alarm communications (P_C) in the PPS. In this study, we develop a multi-path analysis code based on EASI to evaluate the effectiveness of PPS. Our quantification method for P_I considers the variability and uncertainty of P_D and P_C value by Monte Carlo simulation. We converted the 2-D scheme of the nuclear facility into an Adversary Sequence Diagram (ASD). We used ASD to find the adversary path with the lowest probability of interruption as the most vulnerable paths (MVP). We examined a hypothetical facility (Hypothetical National Nuclear Research Facility - HNNRF) to confirm our code compared with EASI. The results show that implementing the variability extension can estimate the P_I value and its associated uncertainty. The multi-path analysis code allows the analyst to make it easier to assess PPS with more extensive facilities with more complex adversary paths. However, the variability of the P_D value in each protection element allows a significant decrease in the PI value. The possibility of this decrease needs to be an important concern for PPS designers to determine the P_D value correctly or set a higher standard for PPS performance that remains reliable.

• Structural Engineering and Mechanics
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• 제85권2호
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• pp.197-206
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• 2023

The deterioration caused by chloride penetration and carbonation plays a significant role in a concrete structure in a marine environment. The chloride corrosion in some marine concrete structures is invisible but can be dangerous in a sudden collapse. Therefore, as a novelty, this research investigates the ability of a non-destructive damage detection method named the Power Spectral Density (PSD) to diagnose damages caused only by chloride ions in concrete structures. Furthermore, the accuracy of this method in estimating the amount of annual damage caused by chloride in various parts and positions exposed to seawater was investigated. For this purpose, the RC Arosa bridge in Spain, which connects the island to the mainland via seawater, was numerically modeled and analyzed. As the first step, each element's bridge position was calculated, along with the chloride corrosion percentage in the reinforcements. The next step predicted the existence, location, and timing of damage to the entire concrete part of the bridge based on the amount of rebar corrosion each year. The PSD method was used to monitor the annual loss of reinforcement cross-section area, changes in dynamic characteristics such as stiffness and mass, and each year of the bridge structure's life using sensitivity equations and the linear least squares algorithm. This study showed that using different approaches to the PSD method based on rebar chloride corrosion and assuming 10% errors in software analysis can help predict the location and almost exact amount of damage zones over time.

• 방송공학회논문지
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• 제27권4호
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• pp.499-510
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• 2022

본 논문에서는 영상 편집이 익숙하지 않은 시니어 동영상 크리에이터를 위한 동영상 편집 시스템을 설명한다. 영상분석 기술을 이용하여 편집소스 동영상을 분석하여 각종 정보를 제공하고, 자동으로 일부 장면을 삭제한다. 사용자가 다수의 소스 콘텐츠를 입력하였을 때, RNN(Recurrent Neural Network) 기술을 기반으로 샷 단위로 분할하고, 이 중 동영상 편집에서 배제할 부분을 구분한다. 각 샷 별로 중요도를 계산하여 샷 단위로 자동 삭제가 가능하도록 한다. 중요도 계산을 위해서 동영상 초점 정보를 추출하여 활용하는데, 이는 초점이 맞지 않는 영상 또는 흔들린 영상을 배제할 수 있도록 한다. 이후 시스템은 객체 인식을 수행하고, 얼굴이 나온 영상에 대해서 감정, 나이, 성별 등의 정보를 추출하여 사용자에게 제공한다. 사용자는 이런 정보를 활용하여 동영상을 제작한다. 동영상에 자막을 삽입하는 등 동영상을 꾸미기 위한 기능들도 포함되어 있으며, 이런 기능들을 활용할 시, 사용자의 과거 정보를 이용해서 선호 디자인을 쉽게 찾을 수 있도록 앞서 배치하고 있다. 시니어 동영상 크리에이터들이 본 시스템을 통해서 쉽고 빠르게 동영상 콘텐츠를 제작할 수 있다.

• Smart Structures and Systems
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• 제31권4호
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• pp.421-436
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• 2023

This paper presents a vibration displacement measurement and damage identification method for a space truss structure from its vibration videos. Features from Accelerated Segment Test (FAST) algorithm is combined with adaptive threshold strategy to detect the feature points of high quality within the Region of Interest (ROI), around each node of the truss structure. Then these points are tracked by Kanade-Lucas-Tomasi (KLT) algorithm along the video frame sequences to obtain the vibration displacement time histories. For some cases with the image plane not parallel to the truss structural plane, the scale factors cannot be applied directly. Therefore, these videos are processed with homography transformation. After scale factor adaptation, tracking results are expressed in physical units and compared with ground truth data. The main operational frequencies and the corresponding mode shapes are identified by using Subspace Stochastic Identification (SSI) from the obtained vibration displacement responses and compared with ground truth data. Structural damages are quantified by elemental stiffness reductions. A Bayesian inference-based objective function is constructed based on natural frequencies to identify the damage by model updating. The Success-History based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) is applied to minimise the objective function by tuning the damage parameter of each element. The locations and severities of damage in each case are then identified. The accuracy and effectiveness are verified by comparison of the identified results with the ground truth data.