• Journal of Mechanical Science and Technology
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• 제15권4호
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• pp.459-464
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• 2001

The effects of internal air-pressing on deep drawability are investigated in this study to increase the deep drawability of aluminum sheet. The conventional deep drawing process is limited to a certain limit drawing ratio(LDR) beyond which failure will occur. The intention of this work is to examine the possibilities of relaxing the above limitation through the deep drawing with internal air-pressing, aiming towards a process with an increased drawing ratio. The idea which may lead to this goal is the use of special punch that can exert high pressure on the internal surface of deforming sheet during the deep drawing process. Over the ranges of conditions investigated for Al-1050, the local strain concentration at punch nose radius area was decreased by internal air-pressing of punch, and the deep drawing with internal air-pressing was proved to be very effective process for obtaining higher LDR.

• 한국멀티미디어학회논문지
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• 제21권5호
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• pp.571-582
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• 2018

Recently, development of deep learning has shown better image classification result than human. According to recent research, a hidden layer of deep learning is deeper, and a preservation of extracted features shows good results. However, in the case of general images, the extracted features are clear and easy to sort. This study aims to classify plant leaf images. This plant leaf image has high similarity in each image. Since plant leaf images have high similarity not only between images of different species but also within the same species, classification accuracy is not increased by simply extending the hidden layer or connecting the layers. Therefore, in this paper, we tried to improve the hidden layer of the algorithm called DenseNet which shows the recent excellent classification results, and compare the results of several different modified layers. The proposed method makes it possible to classify plant leaf images collected in a natural environment more easily and accurately than conventional methods. This results in good classification of plant leaf image data including unnecessary noise obtained in a natural environment.

• 수산해양기술연구
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• 제55권4호
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• pp.285-293
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• 2019

The mesh selectivity of hairtail (Trichiurus lepturus) caught by coastal drift gill net was examined in field experiments with three different mesh sizes (45, 50 and 55 mm) from October to November, 2013 in the coastal areas of south-west of Jeju province. The mesh selectivity tests were conducted with the experimental net to be set middle part of conventional driftnets. The mesh selectivity tests were carried out the total of four times. The selectivity curve was estimated by the Kitahara's and Fujimori's method. In the results, the catch number of hairtail was 653 (125.8 kg) and occupied 34.8% in total catches weight. The optimal mesh size for 50% selection on the minimum landing size (180 mm, AL) and the first maturity size (260 mm, AL) of hairtail were estimated as 47.2 mm and 64.5 mm by master selectivity curves, respectively.

• The Journal of Asian Finance, Economics and Business
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• 제8권11호
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• pp.223-234
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• 2021

This study aims to examine whether operating cash flows influence banks' financial stability in Pakistan. The study employed annual panel data collected from annual reports of 20 commercial banks listed on the Pakistan Stock Exchange for the year 2011 to 2019. Free cash flow yield was taken as the dependent variable while cash flow ratio was selected as the independent variable, and net interest margin, income diversification, asset quality, financial leverage, the cost to income ratio, advance net of provisions to total assets ratio, capital ratio, financial performance, breakup value per share and bank size were taken as control variables. The study performed ordinary least square technique, random and fixed effects models, Hausman test, Lagrange multiplier test, descriptive and correlation analysis. Results showed that operating cash flows and net interest margin significantly and positively influenced banks' financial stability while the cost to income ratio and advances net of provisions to total assets ratio significantly and negatively associated with banks' financial stability. To improve financial stability, banks should become more cost-effective and enhance their liquidity levels by lowering lending activities. In the future, it would be useful to compare commercial and investment banks, also Islamic and conventional banks in the same research setting.

• 한국수소및신에너지학회논문집
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• 제30권4호
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• pp.347-355
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• 2019

As a solution to the growing concern on the global warming, researches are being actively carried out to apply carbon dioxide capture and storage technology to power generation systems. In this study, the integrated gasification combined cycle (IGCC) adopting oxy-combustion carbon capture was modeled and the effect of replacing the conventional air separation unit (ASU) with the ion transport membrane (ITM) on the net system efficiency was analyzed. The ITM-based system was predicted to consume less net auxiliary power owing to an additional nitrogen expander. Even with a regular pressure ratio which is 21, the ITM-based system would provide a higher net efficiency than the optimized ASU-based system which should be designed with a very high pressure ratio around 90. The optimal net efficiency of the ITM-based system is more than 3% higher than that of the ASU-based system. The influence of the operating pressure and temperature of the ITM on system efficiency was predicted to be marginal.

• International Journal of Computer Science & Network Security
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• 제22권10호
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• pp.406-412
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• 2022

Scene classification of very high-resolution (VHR) imagery can attribute semantics to land cover in a variety of domains. Real-world application requirements have not been addressed by conventional techniques for remote sensing image classification. Recent research has demonstrated that deep convolutional neural networks (CNNs) are effective at extracting features due to their strong feature extraction capabilities. In order to improve classification performance, these approaches rely primarily on semantic information. Since the abstract and global semantic information makes it difficult for the network to correctly classify scene images with similar structures and high interclass similarity, it achieves a low classification accuracy. We propose a VHR remote sensing image classification model that uses extracts the global feature from the original VHR image using an EfficientNet-V2L CNN pre-trained to detect similar classes. The image is then classified using a multilayer perceptron (MLP). This method was evaluated using two benchmark remote sensing datasets: the 21-class UC Merced, and the 38-class PatternNet. As compared to other state-of-the-art models, the proposed model significantly improves performance.

• Journal of Microbiology
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• 제41권4호
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• pp.320-326
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• 2003

In order to identify Vibrio vulnificus in the Yellow Sea near Gunsan, Korea during the early and late summers, the efficiency of the real-time quantitative TaqMan PCR was compared to the efficiency of the conventional PCR and Biolog identification system^TM. Primers and a probe were designed from the hemolysin/cytolysin gene sequence of V. vulnificus strains. The number of positive detections by real-time quantitative TaqMan PCR, conventional PCR, and the Biolog identification system from seawater were 53 (36.8%), 36 (25%), and 10 strains (6.9%), respectively, among 144 samples collected from Yellow Sea near Gunsan, Korea. Thus, the detection method of the real-time quantitative TaqMan PCR assay was more effective in terms of accuracy than that of the conventional PCR and Biolog system. Therefore, our results showed that the real-time TaqMan probe and the primer set developed in this study can be applied successfully as a rapid screening tool for the detection of V. vulnificus.

• 한국유기농업학회지
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• 제19권spc호
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• pp.199-202
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• 2011

Organic production practices varied among producers. Generally, organic producers were relying on imported input materials such as organic compost and liquid fertilizer even more than conventional producers. Very few organic farmers had composting facilities or sites for the own supply of compost in need. The productivity of organic kiwifruit orchard (92%) was not as low as that of conventional while the net income (243%) was more than double that of conventional. This was mainly attributed to high farm gate price of organic fruits, low paid labour use and electricity. As a consequence, organic kiwifruit production seems to become a feasible option in Korea. However, high dependence on imported farming material, fuel and labour for too frequent liquid fertilizer spray should be addressed to achieve long term sustainability of organic kiwifruit production.

• 한국산학기술학회논문지
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• 제8권6호
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• pp.1480-1490
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• 2007

본 논문에서는 WINDOWS CE .NET 기반의 PDA를 이용한 원격제어시스템을 구현하였다. 서버 시스템의 운영체제는 WINDOWS CE .NET을 사용하여 사용자에게 쉬운 사용 환경을 제공하며, 운영체제 이미지에 개발한 디바이스 드라이버를 추가하여 하드웨어 장치를 제어한다. 임베디드 서버는 PC 클라이언트와 PC 클라이언트, PC 클라이언트와 PDA 클라이언트, PDA 클라이언트와 PDA 클라이언트간의 메시지 통신을 지원한다. 본 논문은 원격제어시스템을 구현하는데 있어서 에뮬레이터를 사용하지 않고 실제 PDA와 임베디드 보드로 시스템을 구현하였다. 제안된 시스템은 임베디드 보드를 서버로 사용하고 PDA를 클라이언트로 사용하여 무선 인터넷이 제공되는 환경이라면 어느 곳에서나 원격으로 대상물을 제어할 수 있다.

• 한국산업정보학회논문지
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• 제24권4호
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• pp.1-8
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• 2019

식물 표현체(plant phenomics) 연구는 우수한 형질의 식물 품종과 유전적 특성을 선별하기 위해 여러 식물체의 형태적 특징을 관측하고, 획득한 영상 빅데이터를 분석하는 기술이다. 기존의 방법은 검출 대상에 따라 직접 색상 임계값을 변경해야 하기 때문에 빅데이터를 다루는 정밀검정시스템에 적용하기 어렵다. 본 논문에서는 정밀검정시스템을 위한 식물체와 배경의 자동 분할이 가능한 합성곱 신경망(Convolution neural network: CNN) 구조를 제안한다. LeafNet은 9개의 컨벌루션 계층과 식물의 유무를 판단하기 위한 시그모이드(Sigmoid) 활성화 함수로 구성된다. LeafNet을 이용한 학습 결과, 식물 모종 영상에 대하여 정밀도 98.0%, 재현율 90.3%의 결과가 도출되어 정밀검정시스템의 적용 가능성을 확인하였다.