• Title/Summary/Keyword: CVX

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OBTS(On-board Training System) Construction Plan for ROK Navy CVX (해군 항공모함(CVX)을 위한 함정 탑재형 훈련체계(OBTS) 구축 방안)

  • Kim, Seejeong;Jung, Kyung-Nam
    • Journal of the Korea Society for Simulation
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    • v.31 no.2
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    • pp.21-32
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    • 2022
  • The ROK Navy is seeking to secure an aircraft carrier(CVX) to take responsibility for the maritime security of the Republic of Korea. In order for the CVX to complete the mission given to it, the crew must be able to operate the CVX perfectly, and for this purpose, the operating skills of the CVX crew result from constant training. Therefore, this paper proposes an On-board Training System(OBTS) so that the best training can always be performed even on ship. CVX OBTS should be built in the form of a thorough simulator based on a Synthetic Training Environment(STE) so that it can be optimally applied to ship and provide the best training environment to the crew. In order to satisfy the various training requirements and implementation conditions of the CVX, this paper proposes a plan to consist of Embedded Training System(ETS), VR training system, AR maintenance system, MR training system, MR metaverse training system, and realistic simulator training system.

Detection of Co-Infection of Notocactus leninghausii f. cristatus with Six Virus Species in South Korea

  • Park, Chung Hwa;Song, Eun Gyeong;Ryu, Ki Hyun
    • The Plant Pathology Journal
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    • v.34 no.1
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    • pp.65-70
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    • 2018
  • Co-infection with two virus species was previously reported in some cactus plants. Here, we showed that Notocactus leninghausii f. cristatus can be co-infected with six different viruses: cactus mild mottle virus (CMMoV)-Nl, cactus virus X (CVX)-Nl, pitaya virus X (PiVX)-Nl, rattail cactus necrosis-associated virus (RCNaV)-Nl, schlumbergera virus X (SchVX)-Nl, and zygocactus virus X (ZyVX)-Nl. The coat protein sequences of these viruses were compared with those of previously reported viruses. CMMoV-Nl, CVX-Nl, PiVX-Nl, RCNaV-Nl, SchVX-Nl, and ZyVX-Nl showed the greatest nucleotide sequence homology to CMMoV-Kr (99.8% identity, GenBank accession NC_011803), CVX-Jeju (77.5% identity, GenBank accession LC12841), PiVX-P37 (98.4% identity, GenBank accession NC_024458), RCNaV (99.4% identity, GenBank accession NC_016442), SchVX-K11 (95.7% identity, GenBank accession NC_011659), and ZyVX-B1 (97.9% identity, GenBank accession NC_006059), respectively. This study is the first report of co-infection with six virus species in N. leninghausii f. cristatus in South Korea.

Computational performance and accuracy of compressive sensing algorithms for range-Doppler estimation (거리-도플러 추정을 위한 압축 센싱 알고리즘의 계산 성능과 정확도)

  • Lee, Hyunkyu;Lee, Keunhwa;Hong, Wooyoung;Lim, Jun-Seok;Cheong, Myoung-Jun
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.5
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    • pp.534-542
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    • 2019
  • In active SONAR, several different methods are used to detect range-Doppler information of the target. Compressive sensing based method is more accurate than conventional methods and shows superior performance. There are several compressive sensing algorithms for range-Doppler estimation of active sonar. The ability of each algorithm depends on algorithm type, mutual coherence of sensing matrix, and signal to noise ratio. In this paper, we compared and analyzed computational performance and accuracy of various compressive sensing algorithms for range-Doppler estimation of active sonar. The performance of OMP (Orthogonal Matching Pursuit), CoSaMP (Compressive Sampling Matching Pursuit), BPDN (CVX) (Basis Pursuit Denoising), LARS (Least Angle Regression) algorithms is respectively estimated for varying SNR (Signal to Noise Ratio), and mutual coherence. The optimal compressive sensing algorithm is presented according to the situation.

Impact of Virus-resistant Trigonal Cactus Cultivation on Soil Microbial Community (바이러스저항성 삼각주 재배가 토양 미생물상에 미치는 영향)

  • Oh, Sung-Dug;Kim, Jong-Bum;Lee, Jung-Jin;Kim, Min-Kyeong;Ahn, Byung-Ohg;Sohn, Soo-In;Park, Jong-Sug;Ryu, Tae-Hun;Cho, Hyun-Suk;Lee, Kijong
    • Korean Journal of Environmental Agriculture
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    • v.32 no.2
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    • pp.148-154
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    • 2013
  • BACKGROUND: Genetically modified(GM) trigonal cactus(Hylocereus trigonus Saff.) contained a coat protein gene of cactus virus X (CVX), which conferred resistance to the virus, phosphinothricin acetyltransferase (bar) gene, which conferred herbicide resistance, and a cauliflower mosaic virus 35S promoter (CaMV 35S). This study was conducted to evaluate the possible impact of GM trigonal cactus cultivation on the soil microbial community. METHODS AND RESULTS: Microorganisms were isolated from the rhizosphere of GM and non-GM trigonal cactus cultivation soils. The total numbers of bacteria, and actinomycete in the rhizosphere soils cultivated GM and non-GM trigonal cactus were similar to each other, and there was no significant difference. Dominant bacterial phyla in the rhizosphere soils cultivated with GM and non-GM trigonal cactus were Proteobacteria, Uncultured archaeon, and Uncultured bacterium. The denaturing gradient gel electrophoresis (DGGE) profiles show a similar patterns, significant difference was not observed in each other. DNA was isolated from soil cultivated GM and non-GM trigonal cactus, we analyzed the persistence of the inserted gene by PCR. Amplification of the inserted genes was not observed in the soil DNA, which was collected after harvest. CONCLUSION(S): This result suggests that the GM trigonal cactus cultivation does not change significantly the microbial community.

Estimation of bubble size distribution using deep ensemble physics-informed neural network (딥앙상블 물리 정보 신경망을 이용한 기포 크기 분포 추정)

  • Sunyoung Ko;Geunhwan Kim;Jaehyuk Lee;Hongju Gu;Kwangho Moon;Youngmin Choo
    • The Journal of the Acoustical Society of Korea
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    • v.42 no.4
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    • pp.305-312
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    • 2023
  • Physics-Informed Neural Network (PINN) is used to invert bubble size distributions from attenuation losses. By considering a linear system for the bubble population inversion, Adaptive Learned Iterative Shrinkage Thresholding Algorithm (Ada-LISTA), which has been solved linear systems in image processing, is used as a neural network architecture in PINN. Furthermore, a regularization based on the linear system is added to a loss function of PINN and it makes a PINN have better generalization by a solution satisfying the bubble physics. To evaluate an uncertainty of bubble estimation, deep ensemble is adopted. 20 Ada-LISTAs with different initial values are trained using the same training dataset. During test with attenuation losses different from those in the training dataset, the bubble size distribution and corresponding uncertainty are indicated by average and variance of 20 estimations, respectively. Deep ensemble Ada-LISTA demonstrate superior performance in inverting bubble size distributions than the conventional convex optimization solver of CVX.