• The Plant Pathology Journal
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• 제17권6호
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• pp.380.3-380
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• 2001

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1977년도 제9회 학술발표회 초록
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• pp.109.5-110
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• 1977

• 전기저널
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• 통권449호
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• pp.14-32
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• 2014

• 약학회지
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• 제44권4호
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• pp.340-346
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• 2000

Cervical cancer is one of the leading causes of female death from cancer worldwide with about 500,000 deaths per year. A strong association between certain human papilloma viruses (HPV types 16 and 18) and cervical cancer has been well known. An extract of natural products, named as Somatid, has been used to investigate whether this agent has the ability of inhibiting the oncogenes E6 and E7 of HPV type 16. This Somatid inhibited the proliferation of human cervical cancer cell lines (C-33A, SiHa, CaSki) and HaCaT keratinocytes in a dose response manner, In vitro binding assay and ELISA showed that Somatid inhibited the in vitro biding of E6 and E6AP which are essential for the binding and degradation of the tumor suppressor p53. In addition, Somatid inhibited the in vitro binding of E7 and Rb which is essential tumor suppressor for the control of cell cycle. The levels of mRNA for E6 and E7 were also decreased by Somatid. Our data suggested that Somatid inhibited the oncogenecity of E6 and E7 of HPV 16 type, thus can be used as a putative anti-HPV agent for the treatment of cervical carcinomas caused by HPV.

• 한국약용작물학회지
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• 제11권1호
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• pp.24-30
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• 2003

11종의 약리식물의 수용성 추출물에서 세포독성능과 TGEV와 PEDV에 대한 항바이러스 효능을 분석하였다. 이들 추출물은 바이러스의 숙주세포로 사용되는 ST세포와 Vero세포에 대해 다른 세포독성능을 나타내었는데, 오가피 추출물은 TGEV에 대한 숙주세포주인 ST 세포에 대해 75.81 %의 세포독성을 나타내었으며, 화살나무, 무화과나무, 까마종이, 마황, 창이자 추출물은 20-50% 사이의 세포독성을 나타내었다. 그러나 마황 추출물(35.66%) 이외의 10종의 추출물은 PEDV에 대한 숙주세포주인 Vero 세포에 대해 세포독성능을 나타내지 않았다. 세포독성이 낮은 식물추출물에서 초피나무, 구지뽕나무, 누리장나무, 고삼 추출물이 TGEV에 대하여 효과적인 항바이러스능을 나타내었으며, PEDV에 대하여는 초피나무, 조각자나무, 고삼, 까마종이, 마황 추출물에서 효과적인 항바이러스능을 나타내었다. 이중에서 고삼과 초피나무 추출물은 TGEV와 PEDV에 대해서 효과적인 항바이러스능을 나타내었다.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2008년도 International Meeting on Information Display
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• pp.1638-1641
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• 2008

We have investigated the effectiveness of a gravure printing method for the fabrication of organic light-emitting diode (OLED) and Organic Thin Film Transistor (OTFT). Printing of the organic layers was performed with a small-scale gravure coating machine, while the metallic layers were vacuum-evaporated. Devices with gravure-printed layers are at least comparable with the spin-coated devices. Effects of the solvent formulation and surface energy mismatch between the organic layer materials on the printed patterns and device performance were discussed. We will present the initial design and experimental data of OTFT fabricated by roll-type soft contact transfer process.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2006년도 6th International Meeting on Information Display
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• pp.1394-1397
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• 2006

Polymer Dispersed Liquid Crystal (PDLC) films, of which the liquid crystal has negative dielectric anisotropy, were prepared from the phase separation between MJ001317 and a variety of compositions of resins by common polymerization induced phase separation method. In this work, the effects of resin compositions have been systematically investigated and it was found that the morphology and size of droplet, which is closely related to electro-optic properties, mainly depend on the rate of polymerization and cross-linking density for each resin composition. The reverse mode PDLC films from this newly developed formulation containing TPGDA/EHA/HMPPO showed the good off-state transmittance, contrast ratio (19/1), and relatively low driving voltage(10V).

• 한국통신학회논문지
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• 제34권10C호
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• pp.955-960
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• 2009

본 논문에서는 주파수영역에서 음향학적 반향 억제 (AES, acoustic echo suppression) 성능을 개선시키기 위해 tracking echo-presence uncertainty (TEPU) 기법에 근거한 새로운 잔여 반향 억제 (RES, residual echo suppression) 알고리즘을 제안한다. 제안된 방법은 RES를 위해 마이크로폰 입력신호 대 원단의 반향신호가 제거된 결과신호의 전력 비 (ratio)를 문턱 (threshold) 값에 의한 decision rule에 적용하여 추정된 echo-presence uncertainty를 RES 필터로 이용한다. 제안된 알고리즘은 각각의 주파수 채널에서 echo-presence uncertainty를 도출하여 용이하게 잔여 반향신호를 제거하는 장점을 가진다. 실제로 잔여 반향신호를 제거하기 위한 기존의 방법과 객관적인 실험을 통해 비교 평가한 결과 우수한 성능을 보였다.

• 한국중재학회지:중재연구
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• 제31권1호
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• pp.3-22
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• 2021

This article examines the Challenge through Annulment of ICSID Arbitral Awards. Either party may request annulment of the award by applying in writing addressed to the ICSID Secretary-General on one or more of the grounds under Article 52 of the ICSID Convention. The annulment proceedings must focus on the award itself. Because committees have no inherent supremacy over the arbitral tribunal, they should not review the tribunal's findings on evidence, damage, interest, and cost findings. Otherwise, the parties would have, in effect, two opportunities, and that will almost certainly weaken the reliability of the entire ICSID system. In short, because of the limited scope of review under ICSID annulment and because annulment is not an opportunity for the parties to re-try the case, committees should not allow new arguments or new evidence. Since an annulment committee is not a court of appeals, it cannot create a new res judicata. Committees can only decide not to annul an award, thus confirming the existing res judicata or annul the award, in which case the affected decision ceases to be res judicata. An obvious annulment decision stipulating which particular findings of the award remain res judicata should prevent any uncertainty in resubmission proceedings.

• International Journal of Computer Science & Network Security
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• 제23권7호
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• pp.39-48
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• 2023

Breast cancer screening makes extensive utilization of mammography. Even so, there has been a lot of debate with regards to this application's starting age as well as screening interval. The deep learning technique of transfer learning is employed for transferring the knowledge learnt from the source tasks to the target tasks. For the resolution of real-world problems, deep neural networks have demonstrated superior performance in comparison with the standard machine learning algorithms. The architecture of the deep neural networks has to be defined by taking into account the problem domain knowledge. Normally, this technique will consume a lot of time as well as computational resources. This work evaluated the efficacy of the deep learning neural network like Visual Geometry Group Network (VGG Net) Residual Network (Res Net), as well as inception network for classifying the mammograms. This work proposed optimization of ResNet with Teaching Learning Based Optimization (TLBO) algorithm's in order to predict breast cancers by means of mammogram images. The proposed TLBO-ResNet, an optimized ResNet with faster convergence ability when compared with other evolutionary methods for mammogram classification.