• Journal of Microbiology and Biotechnology
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• 제16권7호
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• pp.1163-1168
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• 2006

The recombinant plasmid pLEX2FP complements the mutation in Zoogloea ramigera 115MM1, and the complemented mutant produces an exopolysaccharide that shows higher affinity for the calcofluor dye than the exopolysaccharide from Z. ramigera 115SLR, resulting in higher fluorescence intensity under UV light. A compositional and structural analysis of the exopolysaccharide from Z. ramigera 115MM1 showed that the different fluorescent properties were due to a lower content of acetyl groups when compared with Z. ramigera 115SLR exopolysaccharide. These results were in agreement with a sequence analysis of the gene carried in the plasmid pLEX2FP, which appeared to encode an O-acyltransferase highly homologous to the 3-O-acyltransferase of Streptomyces mycarofaciens. The gene encoding the acyltransferase from Z. ramigera 115SLR was expressed as a GST-fusion protein with 70,000 daltons in E. coli.

• Nuclear Engineering and Technology
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• 제39권1호
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• pp.51-62
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• 2007

To efficiently design safety-critical systems such as nuclear power plants, with the requirement of high reliability, methodologies allowing for rigorous interactions between the synthesis and analysis processes have been proposed. This paper attempts to develop a reliability-centered design framework through an interactive process between Axiomatic Design (AD) and Fault Tree Analysis (FTA). Integrating AD and FTA into a single framework appears to be a viable solution, as they compliment each other with their unique advantages. AD provides a systematic synthesis tool while FTA is commonly used as a safety analysis tool. These methodologies build a design process that is less subjective, and they enable designers to develop insights that lead to solutions with improved reliability. Due to the nature of the two methodologies, the information involved in each process is complementary: a success tree versus a fault tree. Thus, at each step a system using AD is synthesized, and its reliability is then quantified using the FT derived from the AD synthesis process. The converted FT provides an opportunity to examine the completeness of the outcome from the synthesis process. This study presents an example of the design of a Containment Heat Removal System (CHRS). A case study illustrates the process of designing the CHRS with an interactive design framework focusing on the conversion of the AD process to FTA.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3864-3877
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• 2022

We propose a new approach called PESA (Prioritized replay Evolutionary and Swarm Algorithms) combining prioritized replay of reinforcement learning with hybrid evolutionary algorithms. PESA hybridizes different evolutionary and swarm algorithms such as particle swarm optimization, evolution strategies, simulated annealing, and differential evolution, with a modular approach to account for other algorithms. PESA hybridizes three algorithms by storing their solutions in a shared replay memory, then applying prioritized replay to redistribute data between the integral algorithms in frequent form based on their fitness and priority values, which significantly enhances sample diversity and algorithm exploration. Additionally, greedy replay is used implicitly to improve PESA exploitation close to the end of evolution. PESA features in balancing exploration and exploitation during search and the parallel computing result in an agnostic excellent performance over a wide range of experiments and problems presented in this work. PESA also shows very good scalability with number of processors in solving an expensive problem of optimizing nuclear fuel in nuclear power plants. PESA's competitive performance and modularity over all experiments allow it to join the family of evolutionary algorithms as a new hybrid algorithm; unleashing the power of parallel computing for expensive optimization.

• Nuclear Engineering and Technology
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• 제38권2호
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• pp.109-118
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• 2006

Various indirect power cycle options for a helium cooled gas cooled fast reactor (GFR) with particular focus on a supercritical $CO_2(SCO_2)$ indirect cycle are investigated as an alternative to a helium cooled direct cycle GFR. The balance of plant (BOP) options include helium-nitrogen Brayton cycle, supercritical water Rankine cycle, and $SCO_2$ recompression Brayton power cycle in three versions: (1) basic design with turbine inlet temperature of $550^{\circ}C$, (2) advanced design with turbine inlet temperature of $650^{\circ}C$ and (3) advanced design with the same turbine inlet temperature and reduced compressor inlet temperature. The indirect $SCO_2$ recompression cycle is found attractive since in addition to easier BOP maintenance it allows significant reduction of core outlet temperature, making design of the primary system easier while achieving very attractive efficiencies comparable to or slightly lower than, the efficiency of the reference GFR direct cycle design. In addition, the indirect cycle arrangement allows significant reduction of the GFR &proximate-containment& and the BOP for the $SCO_2$ cycle is very compact. Both these factors will lead to reduced capital cost.

• Nuclear Engineering and Technology
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• 제48권6호
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• pp.1338-1348
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• 2016

A novel fully passive small modular superheated water reactor (SWR) for underwater deployment is designed to produce 160 MWe with steam at $500^{\circ}C$ to increase the thermodynamic efficiency compared with standard light water reactors. The SWR design is based on a conceptual 400-MWe integral SWR using the internally and externally cooled annular fuel (IXAF). The coolant boils in the external channels throughout the core to approximately the same quality as a conventional boiling water reactor and then the steam, instead of exiting the reactor pressure vessel, turns around and flows downward in the central channel of some IXAF fuel rods within each assembly and then flows upward through the rest of the IXAF pins in the assembly and exits the reactor pressure vessel as superheated steam. In this study, new cladding material to withstand high temperature steam in addition to the fuel mechanical and safety behavior is investigated. The steam temperature was found to depend on the thermal and mechanical characteristics of the fuel. The SWR showed a very different transient behavior compared with a boiling water reactor. The inter-play between the inner and outer channels of the IXAF was mainly beneficial except in the case of sudden reactivity insertion transients where additional control consideration is required.

• 전기전자학회논문지
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• 제22권4호
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• pp.1175-1179
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• 2018

본 논문에서는 뇌파 신호를 이용하여 환자의 경련을 감지하는 순환 CNN (Convolutional Neural Networks)을 제안한다. 제안 된 방법은 뇌파 신호의 스펙트럼 특성과 전극의 위치를 보존하기 위해 영상으로 데이터를 매핑하여 처리하였다. 스펙트럼 전처리 과정을 거친 후 CNN에 입력하고 공간 및 시간 특성을 웨이블릿 변환(wavelet transform)없이 추출하여 발작을 검출하였다. 여기에 사용된 보스턴 매사추세츠 공과 대학 (Boston Massachusetts Institute of Technology, CHB-MIT) 아동 병원의 데이터셋 결과는 시간당 0.85의 민감도와 90 %의 위양성 비율 (FPR)을 보였다.

• 한국광과학회:학술대회논문집
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• 한국광과학회 1997년도 학술대회지
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• pp.38-38
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• 1997

• Macromolecular Research
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• 제16권4호
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• pp.384-384
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• 2008

• 대한화학회지
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• 제10권2호
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• pp.98-102
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• 1966

A spectrochemical method for the determination of the major impurities, such as aluminum, iron, magnesium and silicon, in rutile single crystals and variously doped rutile is presented. By applying higher current (12 amp) and a 1:2 sample-to-graphite dilution by weight, the elaborate sample preparation needed for conventional fusion technique was avoided, and relatively higher detection limits were established. Average deviations are approximately ${\pm}8%$ for iron and magnesium in the concentration ranges of 0.007 to 0.7% and 0.006 to 0.6% respectively, and ${\pm}5%$ for aluminum and silicon in the range of 0.005 to 0.5%.

• International Journal of Aeronautical and Space Sciences
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• 제11권4호
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.