• Nuclear Engineering and Technology
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• 제52권9호
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• pp.1917-1925
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• 2020

New versions of ENDF/B and JEFF data libraries have been released during the past two years with significant updates in the neutron reaction sublibrary and the thermal neutron scattering sublibrary. In order to get a more comprehensive impression of the criticality quality of these two latest neutron data libraries, and to provide reference for the selection of the evaluated nuclear data libraries for the science and engineering applications of the Reactor Monte Carlo code RMC, the criticality benchmarking of the two latest neutron data libraries has been performed. RMC was employed as the computational tools, whose processing capability for the continuous representation ENDF/B-VIII.0 thermal neutron scattering laws was developed. The RMC criticality validation suite consisting of 116 benchmarks was established for the benchmarking work. The latest ACE format data libraries of the neutron reaction and the thermal neutron scattering laws for ENDF/B-VIII.0, ENDF/B-VII.1, and JEFF-3.3 were downloaded from the corresponding official sites. The ENDF/B-VII.0 data library was also employed to provide code-to-code validation for RMC. All the calculations for the four different data libraries were performed by using a parallel version of RMC, and all the calculated standard deviations are lower than 30pcm. Comprehensive analyses including the C/E values with uncertainties, the δk/σ values, and the metrics of χ² and < |Δ| >, were conducted and presented. The calculated keff eigenvalues based on the four data libraries generally agree well with the benchmark evaluations for most cases. Among the 116 criticality benchmarks, the numbers of the calculated keff eigenvalues which agree with the benchmark evaluations within 3σ interval (with a confidence level of 99.6%) are 107, 109, 112, and 113 for ENDF/B-VII.0, ENDF/B-VII.1, ENDF/B-VIII.0 and JEFF-3.3, respectively. The present results indicate that the ENDF/B-VIII.0 neutron data library has a better performance on average.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권1호
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• pp.40-49
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• 2004

In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Self-Organizing Polynomial Neural Networks(SOPNN), discuss a comprehensive design methodology and carry out a series of numeric experiments. The conventional SOPNN is based on the extended Group Method of Data Handling(GMDH) method and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons (or nodes) located in each layer through a growth process of the network. Moreover it does not guarantee that the SOPNN generated through learning has the optimal network architecture. But the proposed GA-based SOPNN enable the architecture to be a structurally more optimized network, and to be much more flexible and preferable neural network than the conventional SOPNN. In order to generate the structurally optimized SOPNN, GA-based design procedure at each stage (layer) of SOPNN leads to the selection of preferred nodes (or PNs) with optimal parameters- such as the number of input variables, input variables, and the order of the polynomial-available within SOPNN. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. A detailed design procedure is discussed in detail. To evaluate the performance of the GA-based SOPNN, the model is experimented with using two time series data (gas furnace and NOx emission process data of gas turbine power plant). A comparative analysis shows that the proposed GA-based SOPNN is model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.3113-3113
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• 2001

Some two years ago our company undertook a project on manufacturing network rationalization to maximize competitiveness through continuous improvement in manufacturing efficiency. One key outcome was the recognition of the benefits that could be derived from timely application of new technology or novel use of existing technologies and even more importantly the need to develop company wide strategies to maximize the impact of such applications. As a direct result an exercise was undertaken to identify the ten most promising technologies from a list of literally hundreds seen as having the capability of making a rapid impact on the manufacturing initiative. One of the outcomes of this exercise was the identification of Near Infrared Spectroscopy as a pivotal technology for improving process understanding, performance, and control to deliver consistent product quality cost effectively with broad applicability across our product range. While NIR had been in use in targeted areas on some of our sites for some years our new challenge was to develop a strategy to extend NIRs application, initially over 17 manufacturing sites, while concurrently expanding the NIR skill base company wide to ensure that the return on initial investment could be further maximized as shared applications across the remaining sites as required. This presentation will provide an overview of how life cycle based user requirement specifications were developed covering: ㆍSpectrophotometers ㆍSample interfaces ㆍSoftware ㆍEquipment and Software qualification ㆍCalibration transfer ㆍ Ease of developing effective user interfaces and control for applications transferred to a production area ㆍUser training ㆍWorld wide support The presentation will also describe the process adopted for vendor selection to ensure maximum utilization of the existing company wide NIR skill base and its future development to expedite applications of the technology in development, quality control and production areas.

• 한국멀티미디어학회논문지
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• 제10권10호
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• pp.1260-1270
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• 2007

테스트 기술자들에게 아날로그 회로(또는 혼합신호 회로)의 테스트와 진단은 여전히 어려운 문제여서 이를 해결할 수 있는 효과적인 테스트 방법이 크게 요구된다. 본 논문에서는 time slot specification(TSS) 기반의 내장 전류감지기(Built-in Current Sensor)를 이용한 새로운 아날로그 회로의 테스트 기법을 제안한다. 또한 TSS에 기반 하여 고장 위치를 찾아내고 고장의 종류를 구별해 내는 방법을 제시한다. TSS 기법과 함께 제안하는 내장 전류감지기는 높은 고장 용이도와 높은 고장 검출을 그리고 아날로그 회로내 강고장과 약고장에 대한 높은 진단율을 갖는다. 제안하는 방법에서는 주출력과 전원단자등을 테스트 포인트로 사용하고 전류감지기를 자동 테스트 장치(Automatic Test Equipment)에 구성하므로써 테스트 포인트 선택과정의 복잡도를 줄일 수 있다. 내장 전류 감지기의 디지털 출력은 아날로그 IC 테스트를 위한 내장 디지털 테스트 모듈과 쉽게 연결된다.

• 지능정보연구
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• 제12권1호
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• pp.139-161
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• 2006

본 논문에서는 새로운 조합경매(combinational auction)모형인 다자간 최적화 경매모형(N-Bilateral Optimized Combinatorial Auction; N-BOCA)을 제시하였다. N-BOCA는 다수의 공급자 및 다수의 구매자간 최적화된 거래를 지원하는 조합경매모형이다. 특히 아키텍처, 거래규약, 거래전략 세가지 관점에서 N-BOCA 시스템을 설계하였다. 경매시장 참여자인 경매자들과 입찰자들은 특정 아키텍처 및 거래규약하에서 최적 거래 대상자 선정을 위한 다양한 전략을 가지게 되며 이러한 거래전략에 따른 유연한 의사결정 모델링 지원을 필요로 한다. 이에 본 논문에서는 최적의 입찰 및 경매자 선정을 위한 Integer Programming 모형 기반의 에이전트 시스템을 제시하였다. 아울러 N-BOCA모형의 유용성을 입증하기 위해 프로토타입과 실험결과를 제시하였다. 실험결과, 기존의 일대다 조합경매 모형 대비 높은 거래 성과를 나타내었다.

• 정보보호학회논문지
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• 제26권2호
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• pp.501-522
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• 2016

디지털시대에 정보는 가치창출의 원천이다. 지식 및 정보의 중요성이 높아지는 만큼 관련된 위험 및 위협 역시 증가하는 추세다. 정보는 한 번 유출되면 완전한 회수가 힘들고 2차 3차 유포는 쉽기 때문에 위험성이 높다. 특히 개인정보는 활용성이 높기 때문에 주요표적이 된다. 하지만 정보주체는 자신의 정보 활용에 대한 동의는 하지만 제공 후 처리는 모르는 등 온전하게 개인정보자기결정권을 행사하기 힘든 상황이다. 이에 본 논문은 개인정보자기결정권이 올바르게 행사될 수 있도록 프라이버시 리터러시 수준 측정 모델 개발을 목적으로 한다. 정보주체들의 현재 정보보호에 대한 지식수준과 이해의 정도, 실제 적용하는 능력을 파악하기 위하여 프라이버시 리터러시의 개념과 지수를 제시한다. 본 지수를 통하여 정보주체의 선택능력을 강화하고 개인정보의 보호와 활용에 대한 판단 및 결정능력을 증진하고자 한다.

• 한국정보통신학회논문지
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• 제19권4호
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• pp.1009-1016
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• 2015

본 논문에서는 계층적 클러스터 구조에서 속도, 방향 등의 속성정보를 예측하여 연결성을 분석하는 EPCM(Efficient Prediction-based Context-awareness Matrix) 알고리즘을 제안한다. 기존 DTN에서는 제한 없는 중계노드 선정으로 인한 지연시간이 증가하고, 제한적인 저장용량 및 처리능력의 한계로 패킷손실 및 오버헤드가 발생한다. 따라서 본 논문에서는 클러스터의 속성정보를 주어진 매트릭으로부터 정의하고 예측하여 베이스스테이션과의 연결성에 따라 중계노드를 선정하는 EPCM 알고리즘을 제안한다. 제안된 알고리즘은 클러스터의 속성정보를 상황정보 매트릭스에 저장 및 분석하고, 적응적 보정가중치의 오차보정으로 클러스터의 속성정보를 예측한다. 또한 예측된 속성정보에 따른 연결성으로 베이스스테이션을 향하여 이동하는 중계노드를 선정하게 된다. 주어진 환경에 따른 모의실험에서 예측된 노드의 속성정보를 통한 연결성으로 중계노드를 선정함으로써 전송능력을 비교 분석한 결과 높은 패킷 전송률을 보여주었다.

• 대한지하수환경학회지
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• 제5권1호
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• pp.30-36
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• 1998

저분자량 유기산을 이용한 in-situ flushing 토양세척기법의 실제 현장 적용성 검토를 위해 실험실에서 회분식 실험을 통하여 적당한 세척제를 선정하고 이에 따른 여러 가지 운전변수를 찾아보았다. 대상 중금속으로는 Cu를 택했고, 세척제로는 실제 토양환경에 영향이 비교적 적은 저분자량 유기산인 acetic, citric, oxalic, succinic acid를 이용했다. 유기산을 이용하여 처리한 결과 실험에 사용된 유기산들 모두 1 mM의 저농도에서는 효과를 나타내지 못했고 50 mM 이상의 고농도에서 보다 좋은 제거율을 보였는데, 50 mM과 100mM의 경우 제거율이 큰 차이를 보이지 못했다. citric arid와 oxalic acid의 경우 중성 및 약산성 상태에서 최대의 제거율이 나타났고 특히 citric arid의 경우 87.1%의 높은 제거율을 보였다. 유기산이 없을때는 강산성 상태에서 Cu의 최고제거율이 70% 정도였다. 그러나 각 경우에서의 speciation을 살펴보면 유기산이 없을 경우에는 추출된 Cu의 대부분이 유해한 free ion상태로 존재하게 되고 유기산이 있을 경우에는 추출된 Cu의 대부분이 유기산과 complex를 이룬다는 것을 알 수 있었다.

• Structural Engineering and Mechanics
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• 제63권1호
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• pp.1-9
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• 2017

Shot peening is a cold surface treatment employed to induce residual stress field in a metallic component beneficial for increasing its fatigue strength. The experimental investigation of parameters involved in shot peening process is very complex as well as costly. The most attractive alternative is the explicit dynamics finite element (FE) analysis capable of determining the shot peening process parameters subject to the selection of a proper material's constitutive model and numerical technique. In this study, Ansys / LS-Dyna software was used to simulate the impact of steel shots of various sizes on an aluminium alloy plate described with strain rate dependent elasto-plastic material model. The impacts were carried out at various incident velocities. The influence of shot velocity and size on the plastic deformation, compressive residual stress and force-time response were investigated. The results exhibited that increasing the shot velocity and size resulted in an increase in plastic deformation of the aluminium target. However, a little effect of the shot velocity and size was observed on the magnitude of target's subsurface compressive residual stress. The obtained results were close to the published ones, and the numerical models demonstrated the capability of the method to capture the pattern of residual stress and plastic deformation observed experimentally in aluminium alloys. The study can be quite helpful in determining and selecting the optimal shot peening parameters to achieve specific level of plastic deformation and compressive residual stress in the aluminium alloy parts especially compressor blades.

• Smart Structures and Systems
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• 제15권4호
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• pp.997-1018
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• 2015

Structural health monitoring along with damage detection and assessment of its severity level in non-accessible reinforced concrete members using piezoelectric materials becomes essential since engineers often face the problem of detecting hidden damage. In this study, the potential of the detection of flexural damage state in the lower part of the mid-span area of a simply supported reinforced concrete beam using piezoelectric sensors is analytically investigated. Two common severity levels of flexural damage are examined: (i) cracking of concrete that extends from the external lower fiber of concrete up to the steel reinforcement and (ii) yielding of reinforcing bars that occurs for higher levels of bending moment and after the flexural cracking. The purpose of this investigation is to apply finite element modeling using admittance based signature data to analyze its accuracy and to check the potential use of this technique to monitor structural damage in real-time. It has been indicated that damage detection capability greatly depends on the frequency selection rather than on the level of the harmonic excitation loading. This way, the excitation loading sequence can have a level low enough that the technique may be considered as applicable and effective for real structures. Further, it is concluded that the closest applied piezoelectric sensor to the flexural damage demonstrates higher overall sensitivity to structural damage in the entire frequency band for both damage states with respect to the other used sensors. However, the observed sensitivity of the other sensors becomes comparatively high in the peak values of the root mean square deviation index.