• 미생물학회지
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• 제51권1호
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• pp.48-60
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• 2015

순창군에서 제조된 전통 장류로부터 612종의 다양한 미생물을 분리하였고, 612종의 미생물 중에서 생리활성 분석 및 biogenic amine 생성여부를 조사하여 최종적으로 Bacillus subtilis SCJ4를 선별하였다. 최종 선별한 균주 SCJ4의 생화학적 특성과 16S rRNA 염기서열 분석에 의해 B. subtilis SCJ4로 명명하였으며, B. subtilis SCJ4의 산업적으로 사용이 적합한 최적배지조성을 확립하기 위하여 통계학적 방법인 반응표면 분석법을 사용하였다. 실험계획법은 배지조성을 예측하기 위해 Plackett-Burman design을 사용하여 모델을 설정하였다. 실험 모델을 통하여 선별된 배지 조성으로는 tryptone, peptone, $MgSO_4$로 예측되었으며, 배지조성에 대한 농도를 설정하기 위해 중심합성계획법을 사용하여 최적화를 수행하였다. 최종 예측된 배지 조성의 농도는 tryptone 15.35 g/L, peptone 12.235 g/L, $MgSO_4$ 3.5 g/L로 예측되었다. 이때 최대 균체량은 1.07497 g/L로 예측되었으며, 모델의 검증실험을 통하여 예측된 모델과 실제 결과가 동일함을 확인하였으며, 기본배양배지와 비교하였을 때 균체량이 0.8767 g/L에서 1.1222 g/L으로 약 28%증가하였다.

• International journal of advanced smart convergence
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• 제4권1호
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• pp.54-63
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• 2015

Increasing air pollution levels and the global oil crisis has become a major hindrance in the growth of our automobile sector. Traditional Internal Combustion engines running on non-renewable fuels are proving to be the major culprit for the harmful effects on environment. With few modifications and also with assistance of few additional components current small SI engines can be modified into a pneumatic engine (commonly known as Compressed Air Engines) without much technical complications where the working fluid is compressed air. The working principle is very basic as adiabatic expansion of the compressed air takes place inside the cylinder pushing the piston downwards creating enough MEP to run the crank shaft at decent RPM. With the assistance of new research and development on pneumatic engines can explore the potential of pneumatic engines as a viable option over IC engines. The paper deals with analysis on RPM variation with corresponding compressed air injection at different crank angles from TDC keeping constant injection time period. Similarly RPM variation can also be observed at different injection pressures with similar injection angle variation. A setup employing a combination of magnetic switch (reed switch), magnets and solenoid valve is used in order to injection timing control. A conclusive data is obtained after detailed analysis of RPM variation that can be employed in newly modified pneumatic engines in order to enhance the running performance. With a number of benefits offered by pneumatic engine over IC engines such as no emissions, better efficiency, low running cost, light weight accompanied by optimized injection conditions can cause a significant development in pneumatic engines without any major alteration.

• Korean Chemical Engineering Research
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• 제45권1호
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• pp.1-11
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• 2007

본 연구는 NPK(질소-인-칼슘) 비료 생산을 위하여 강양이온 이온교환수지를 사용하는 모사이동층(SMB; simulated moving bed) 흡착 공정의 모델링과 모사에 관하여 다룬다. 이 공정은 생산부와 재생부로 크게 나뉘며, 원하지 않는 이온을 제외시키기 위한 2개의 세척 구역을 포함하여 6개의 구역으로 구성되어있다. 따라서 전통적인 4구역 모사이동층 공정보다 좀 더 복잡한 운전 조건을 갖는다. 이러한 6구역 모사이동층 공정의 모델링과 모사를 통하여 얻은 결과는 파일럿규모의 공정과 상용화 공정에서 얻은 실험 결과와 유사함을 보여주었다. 실험 결과로부터 확인된 이 모델식은 최적 운전 조건을 얻기 위한 최적화 문제에 적용될 수 있을 것이다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2381-2399
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• 2019

Traditional recommendation algorithms on Collaborative Filtering (CF) mainly focus on the rating prediction with explicit ratings, and cannot be applied to the top-N recommendation with implicit feedbacks. To tackle this problem, we propose a new collaborative filtering approach namely Maximize MAP with Matrix Factorization (MFMAP). In addition, in order to solve the problem of non-smoothing loss function in learning to rank (LTR) algorithm based on pairwise, we also propose a smooth MAP measure which can be easily implemented by standard optimization approaches. We perform experiments on three different datasets, and the experimental results show that the performance of MFMAP is significantly better than other recommendation approaches.

• 시스템엔지니어링학술지
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• 제16권2호
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• pp.67-77
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• 2020

Traditionally nuclear thermal hydraulic and nuclear safety has relied on numerical simulations to predict the system response of a nuclear power plant either under normal operation or accident condition. However, this approach may sometimes be rather time consuming particularly for design and optimization problems. To expedite the decision-making process data-driven models can be used to deduce the statistical relationships between inputs and outputs rather than solving physics-based models. Compared to the traditional approach, data driven models can provide a fast and cost-effective framework to predict the behavior of highly complex and non-linear systems where otherwise great computational efforts would be required. The objective of this work is to develop an AI algorithm to predict the peak fuel cladding temperature as a metric for the successful implementation of FLEX strategies under extended station black out. To achieve this, the model requires to be conditioned using pre-existing database created using the thermal-hydraulic analysis code, MARS-KS. In the development stage, the model hyper-parameters are tuned and optimized using the talos tool.

• Journal of information and communication convergence engineering
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• 제19권2호
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• pp.79-83
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• 2021

This paper proposes a novel image classification method based on few-shot learning, which is mainly used to solve model overfitting and non-convergence in image classification tasks of small datasets and improve the accuracy of classification. This method uses model structure optimization to extend the basic convolutional neural network (CNN) model and extracts more image features by adding convolutional layers, thereby improving the classification accuracy. We incorporated certain measures to improve the performance of the model. First, we used general methods such as setting a lower learning rate and shuffling to promote the rapid convergence of the model. Second, we used the data expansion technology to preprocess small datasets to increase the number of training data sets and suppress over-fitting. We applied the model to 10 monkey species and achieved outstanding performances. Experiments indicated that our proposed method achieved an accuracy of 87.92%, which is 26.1% higher than that of the traditional CNN method and 1.1% higher than that of the deep convolutional neural network ResNet50.

• International Journal of Advanced Culture Technology
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• 제10권1호
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• pp.253-264
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• 2022

In the era of the pandemic, the importance of a wireless LAN environment has become increasingly important, especially as the era of smart working and non-face-to-face education has become a universal and daily routine. Smartphones, tablets, laptops, PCs, smart watches, and wearable devices, collective referred to as wireless terminals, can be accessed anytime and anywhere through the internet, allowing for consistent and constant access to offices, factories, warehouses, shopping malls, railways, hotels, hospitals, schools, logistics centers, airports, exhibition halls, etc. This sort of access is currently being used in roads, parks, traditional markets, and ports. Since the release of the IEEE 802.11 Legacy Standard in 1997, Wi-Fi technology has been continuously supplemented and revised, and the standard has been continuously developed. In the era of smart working, the importance of efficient wireless deployment and scientific design has become more important. The importance of wireless in the smart factory, in the metaverse era, in the era of pursuing work and life that transcend time and space by using AR, VR, MR, and XR, it is more urgent to solve the shadow area of Wi-Fi. Through this study, we intend to verify the wireless failure problem of the xr training center and suggest improvement measures.

• Nuclear Engineering and Technology
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• 제55권3호
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• pp.827-838
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• 2023

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

• Advances in Computational Design
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• 제7권4호
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• pp.281-295
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• 2022

Tensile property is one of the excellent properties of ultra-high performance concrete (UHPC), and uniaxial tensile test is an important and challenging mechanical performance test of UHPC. Traditional uniaxial tensile tests of concrete materials have inherent defects such as initial eccentricity, which often lead to cracks and failure in non-test zone, and affect the testing accuracy of tensile properties of materials. In this paper, an original integrated design scheme of mould and end fixture is proposed, which achieves seamless matching between the tension end of specimen and the test fixture, and minimizes the cumulative eccentricity caused by the difference in the matching between the tension end of specimen and the local stress concentration at the end. The stress analysis and optimization design are carried out by finite element method. The curve transition in the end of specimen is preferred compared to straight line transition. The rationality of the new integrated design is verified by uniaxial tensile test of strain hardening UHPC, in which the whole stress-strain curve was measured, including the elastic behavior before cracking,strain hardening behavior after cracking and strain softening behavior.

• 대한기계학회논문집B
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• 제35권1호
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• pp.9-15
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• 2011

본 연구에서는 3 차원 전산 열유동해석을 통하여 형상법칙에 근거하여 개발된 냉각판의 열수력학적인 특성을 분석하였다. 서펜타인 형상을 포함하여 최적화, 최적화되지 않은 1, 2 차 형상 총 5 개 형상을 대상으로 동일한 구속조건을 부여함으로써 유동저항, 열저항 및 분지유로에서의 유동균일도를 상호 비교함으로써 냉각판의 성능평가를 수행하였다. 그 결과, 최적화된 1, 2 차 형상 구조가 최적화되지 않은 경우와 비교하여 훨씬 적은 압력손실을 나타내었으며, 압력손실을 기준으로 최적화된 2 차 형상 구조가 가장 우수한 유동 구조를 나타내었다. 또한, 최적화된 1, 2 차 형상구조의 열저항 및 유동 분배성능도 기존에 사용되는 유로형상과 비교하여 모두 우수한 성능을 보였다.