• Title/Summary/Keyword: Deep current

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Trace Organic Contaminants in Sediments from Deep-sea Basin near Dokdo, Korea

  • Yim, Un-Hyuk;Oh, Jae-Ryoung;Hong, Sang-Hee;Li, Dong-Hao;Shim, Won-Joon;Choi, Hye-Kyung;Kim, Eun-Soo;Shim, Jae-Hyung
    • Ocean and Polar Research
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    • 제24권4호
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    • pp.391-398
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    • 2002
  • Trace organic contaminants in deep-sea sediments near Dokdo were analyzed. Total PAMs concentration ranged 14.8-314 ng/g dry weight and high molecular weight PAHs were dominant. The highest PAHs concentration was detected at A19 which located at Ulleung Basin. Most of organochlorines were under detection limit. Among the detected organochlorines, DDT compounds were dominant and followed by HCHs and HCB. Butyltin compounds and most of organophosphorus pesticides were not detected. Vertical distribution of PAHs showed typical sub-surface maximum and decreasing trends depending on depth. The highest PAHs concentration reached 454ng/g. Some organochlorines, DDT, HCH was detected and also showed decreasing trends. Other target organic pollutants were not detected in core sediments. Abnormally high level of PAHs concentration in A19 was discussed and the input sources were inferred to be the transport of sludge derived pollutant dumped at dumping site 'Byung' by deep current.

Analysis of Deep-Trap States in GaN/InGaN Ultraviolet Light-Emitting Diodes after Electrical Stress

  • Jeong, Seonghoon;Kim, Hyunsoo;Lee, Sung-Nam
    • Journal of the Korean Physical Society
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    • 제73권12호
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    • pp.1879-1883
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    • 2018
  • We analyzed the deep-trap states of GaN/InGaN ultraviolet light-emitting diodes (UV LEDs) before and after electrical stress. After electrical stress, the light output power dropped by 5.5%, and the forward leakage current was increased. The optical degradation mechanism could be explained based on the space-charge-limited conduction (SCLC) theory. Specifically, for the reference UV LED (before stress), two sets of deep-level states which were located 0.26 and 0.52 eV below the conduction band edge were present, one with a density of $2.41{\times}10^{16}$ and the other with a density of $3.91{\times}10^{16}cm^{-3}$. However, after maximum electrical stress, three sets of deep-level states, with respective densities of $1.82{\times}10^{16}$, $2.32{\times}10^{16}cm^{-3}$, $5.31{\times}10^{16}cm^{-3}$ were found to locate at 0.21, 0.24, and 0.50 eV below the conduction band. This finding shows that the SCLC theory is useful for understanding the degradation mechanism associated with defect generation in UV LEDs.

Research on Equal-resolution Image Hiding Encryption Based on Image Steganography and Computational Ghost Imaging

  • Leihong Zhang;Yiqiang Zhang;Runchu Xu;Yangjun Li;Dawei Zhang
    • Current Optics and Photonics
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    • 제8권3호
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    • pp.270-281
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    • 2024
  • Information-hiding technology is introduced into an optical ghost imaging encryption scheme, which can greatly improve the security of the encryption scheme. However, in the current mainstream research on camouflage ghost imaging encryption, information hiding techniques such as digital watermarking can only hide 1/4 resolution information of a cover image, and most secret images are simple binary images. In this paper, we propose an equal-resolution image-hiding encryption scheme based on deep learning and computational ghost imaging. With the equal-resolution image steganography network based on deep learning (ERIS-Net), we can realize the hiding and extraction of equal-resolution natural images and increase the amount of encrypted information from 25% to 100% when transmitting the same size of secret data. To the best of our knowledge, this paper combines image steganography based on deep learning with optical ghost imaging encryption method for the first time. With deep learning experiments and simulation, the feasibility, security, robustness, and high encryption capacity of this scheme are verified, and a new idea for optical ghost imaging encryption is proposed.

A Survey of Deep Learning in Agriculture: Techniques and Their Applications

  • Ren, Chengjuan;Kim, Dae-Kyoo;Jeong, Dongwon
    • Journal of Information Processing Systems
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    • 제16권5호
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    • pp.1015-1033
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    • 2020
  • With promising results and enormous capability, deep learning technology has attracted more and more attention to both theoretical research and applications for a variety of image processing and computer vision tasks. In this paper, we investigate 32 research contributions that apply deep learning techniques to the agriculture domain. Different types of deep neural network architectures in agriculture are surveyed and the current state-of-the-art methods are summarized. This paper ends with a discussion of the advantages and disadvantages of deep learning and future research topics. The survey shows that deep learning-based research has superior performance in terms of accuracy, which is beyond the standard machine learning techniques nowadays.

유속계 검정용수로에 관한 연구 (A study on the flume for a current meter rating)

  • 정준석;박정응
    • 물과 미래
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    • 제6권2호
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    • pp.30-37
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    • 1973
  • The coefficient of the current meter generally determined by the maker Its coefficient is subject to being changed with time. Therefore the coefficient of the current meter has to be checked up before it is ready to be used Such an inspection is termed a current meter rating The current meter equipped an electronic apparatus and all the others are to be rated in a rating flume. The price current meter which is most widely used for measuring flow velocities ranging between 0.3m/sec and 3.5m/sec has been used in this study. The length of the flume and the optimum range of the rating in the cross section are determined in the range of 20∼120cm deep, 50∼160cm wide of the flume. In this study, the 23 different kinds of the current meter rating enabled us to determine the constants a and b of the following equation. V=an+b(m/sec) where, n is number of revolution per second(n=N/T) V is velocity(v=D/T) The above constant can be determined by the least squares method and plotting, using the velocity(V=D/T) and the number of revolution per second(n=N/T) obtained from the running distance(D), time(T), the number of revolutin(N), and the running number(m). From the experiments the following conclusions are drawn: 1) The rating flume is large enough if the flume is 110∼120cm deep, and 40∼50m long. 2) The optimum depth for rating of a current meter is in the range of h=40∼50cm.

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반절연성 GaAs에서 열자극 전류에 관한 연구 (A study on thermally stimulatede current in semi-insulating GaAs)

  • 배인호;김기홍;김인수;최현태;이철욱;이정열
    • E2M - 전기 전자와 첨단 소재
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    • 제7권5호
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    • pp.383-388
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    • 1994
  • Deep levels in semi-insulating GaAs were observed by thermally stimulated current(TSC) measurement In the temperature ranges of 100-300K Tl(E$\_$c/-0.18eV), T2(E$\_$c/-0.20eV), T3(E$\_$c/-0.31eV), T4(E$\_$c/-0.40eV), and T5(E$\_$c/-O.43eV) traps have been observed. The TI, T2, and T5 traps seem to be related to the V$\_$As/, V$\_$Ga/-complex, and As$\_$Ga/$\^$++/ respectively. T4 trap is considered with respect to V$\_$Ga/-V$\_$As/ complex.

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한국(韓國) 동해(東海)에서 남동심층류(南東深層流) 관측(觀測) (Observations of Southeastward Deep Currents off the East Coast of Korea)

  • 이흥재;석문식;김철호
    • 한국해양학회지
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    • 제24권2호
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    • pp.63-68
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    • 1989
  • 1986년(年) 8월(月) 26일(日)부터 11월(月) 7일(日)까지 중부동해안(中部東海岸) 외해역(外海域) 수심(水深) 840m인 지점(地點)에서 620m와 790m 층(層)의 심해류(深海流)를 관측(觀測)하였다. 자료분석(資料分析)에 의하면 관측기간(觀測期間) 동안 조석(潮汐)과 관성주기(慣性週期) 이상인 저주파해류(低周波海流)는 약 3cm/s의 평균유속(平均流速)을 갖고 있는 남동류(南東流)였다. 해류(海流)는 시간변동(時間變動)이 크고 두 수심(水深)에서 같은 형태(形態)의 시간변화(時間變化)를 보였다. 최대유속(最大流速)은 태풍(颱風) Vera가 통과직후(通過直後) 기록(記錄)되었고 유속(流速)은 11cm/s 이상이었다. 또한 수일 동안 지속(持續)되는 남동(南東)에서 북(北)으로 급격(急激)한 방향전환(方向轉換) 발생(發生)을 관측(觀測)하였다.

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원통형 딥드로잉 용기의 벽 두께 감소 최소화에 관한 실험적 연구 (Experimental Study on Minimizing Wall Thickness Thinning for Deep Drawing of Circular Shells)

  • 김두환
    • 소성∙가공
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    • 제7권4호
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    • pp.393-399
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    • 1998
  • For minimizing wall thickness thinning of circular shells, a new stamping technology, the deep draw-ing process combined with ironing is approached and investigated. The design requirements for the deep drawing shells are to keep the optimum wall thickness with max. 10 percent thickness thinning of the initial blank thickness, to make uniform thickness strain distribution for the wall of circular shell and to improve the shape accuracy for the roundness and concentricity. In order to check the validity and effectiveness of proposed work, a sample process design is applied to a circular shell needed for a 4multi-stepped deep drawing. Through experiments, the variations of the thickness strain distribution in each drawing process are observed. Also a series of experiments are performed to investigate optimum process variables such as the geometry of tooling, radius and drawing rate. In particular, the advantage of current approach with ironing is shown in contrast to the conventional deep drawing process. From the results of proposed method, the optimum value of process variables are obtained, which contribute more uniform thickness strain distribution and better quality in the drawn product.

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Motion predictive control for DPS using predicted drifted ship position based on deep learning and replay buffer

  • Lee, Daesoo;Lee, Seung Jae
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제12권1호
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    • pp.768-783
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    • 2020
  • Typically, a Dynamic Positioning System (DPS) uses a PID feed-back system, and it often adopts a wind feed-forward system because of its easier implementation than a feed-forward system based on current or wave. But, because a ship's drifting motion is caused by wind, current, and wave drift loads, all three environmental loads should be considered. In this study, a motion predictive control for the PID feedback system of the DPS is proposed, which considers the three environmental loads by utilizing predicted drifted ship positions in the future since it contains information about the three environmental loads from the moment to the future. The prediction accuracy for the future drifted ship position is ensured by adopting deep learning algorithms and a replay buffer. Finally, it is shown that the proposed motion predictive system results in better station-keeping performance than the wind feed-forward system.

Radiomics and Deep Learning in Brain Metastases: Current Trends and Roadmap to Future Applications

  • Park, Yae Won;Lee, Narae;Ahn, Sung Soo;Chang, Jong Hee;Lee, Seung-Koo
    • Investigative Magnetic Resonance Imaging
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    • 제25권4호
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    • pp.266-280
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    • 2021
  • Advances in radiomics and deep learning (DL) hold great potential to be at the forefront of precision medicine for the treatment of patients with brain metastases. Radiomics and DL can aid clinical decision-making by enabling accurate diagnosis, facilitating the identification of molecular markers, providing accurate prognoses, and monitoring treatment response. In this review, we summarize the clinical background, unmet needs, and current state of research of radiomics and DL for the treatment of brain metastases. The promises, pitfalls, and future roadmap of radiomics and DL in brain metastases are addressed as well.