• 한국철도학회논문집
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• 제11권4호
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• pp.390-397
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• 2008

정량적 RAM(Reliability, Availability, Maintainability)은 철도차량의 품질을 나타내는 중요한 척도중 하나이다. 국내외의 철도차량 구매사양서에서는 정량적 RAM 요구조건이 제시되고 있으며 이에 대한 달성과 입증을 요구하고 있다. 본 연구에서는 철도차량의 정량적 RAM의 목표값을 설정하는 방법을 서비스 신뢰도, 로지스틱 신뢰도, 운영가용도와 성취가용도 또는 고유가용도, 유지보수성 측면에서 제안한다. 그리고 이 설정방법을 실제 철도차량 운영데이터에 적용해 보았다.

• 정보관리학회지
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• 제28권1호
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• pp.309-326
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• 2011

기존 메타데이터의 품질 측정 방법은 오류가 발생한 레코드를 단순히 계수하여 그 비율로 품질을 측정하였다. 이러한 한계를 극복하기 위해 메타데이터 요소별로 상대적 중요 정도를 나타내는 가중치를 적용함으로서, 메타데이터 품질을 체계적으로 계량화 하는 측정 방법을 제시하고자 하였다. 구체적인 가중치 부여 방법으로 엔트로피, 이용자 과업, 그리고 이용 통계를 활용하였다. 또한 이들을 결합하여 통합 가중치를 제시하고 실제 서비스 되고 있는 학술지 기사 메타데이터에 적용하였다. 실험 결과, 엔트로피 가중치 방법은 데이터 자체의 특성을 잘 반영하며, 이용자 과업을 적용한 방법은 이용자의 정보요구를 해결하는 필요한 메타데이터 요소를 제시하며, 통합 가중치는 특정 메타데이터 요소의 오류에 영향을 받지 않으면서 균형 잡힌 측정값을 제시하여 계량화 방법에 적합한 것으로 나타났다.

• 한국기후변화학회지
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• 제9권1호
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• pp.69-74
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• 2018

The purpose of this study is to suggest the methodology of $CO_2$ Emission Factor Verification and Quantitative Assessment in Ethylene Product Processes. At first, this study compare the IPCC (Intergovernmental Panel on Climate Change) 1996 Guideline and 2006 Guideline. And analyse methodology for estimating $CO_2$ emission and $CO_2$ emission factor in Ethylene product process. Also analyse cases of estimating $CO_2$ emission factor based on material balance. Methodology of $CO_2$ Emission Factor Verification and Quantitative Assessment are following the categories proposed by GIR (Greenhouse Gas Inventory and Research Center). There are total 12 factors in 8 categories and give 5 or 10 points according to their importance. Also this study suggests necessary data of document to meet the conditions. The result would help estimate accuracy Greenhouse Gas Inventory. Also contribute to establish policy on environmental assessment, air conservation, etc.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.169-172
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• 2021

The article discusses the results of a quantitative analysis of open educational resources in the field of information technology. Study is based on a study of the content of ten platforms that provide access to open resources (OPs). To achieve this goal, we used the following methods: theoretical analysis and generalization of Internet sources to determine the popularity of educational platforms and resources on them; quantitative data analysis to determine the relative proportion of IT courses in various parameters: the relative weight of courses in the IT field in general and on each platform in particular, the language of instruction, the quantitative content by thematic areas. The following platforms providing access to open educational resources were subjected to quantitative analysis: Coursera, Edx, Udemy, MIT OpenCourseWare, OpenLearn, Intuit, Prometheus, UoPeople, Open Learning Initiative, Maidan Open University.

• Journal of Applied Biological Chemistry
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• 제65권3호
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• pp.153-158
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• 2022

This study aimed to identify the phytochemical constituents of Lactuca serriola leaves and perform quantitative analysis of the methanol (MeOH) extract of L. serriola, L. indica, L. raddeana, L. sativa, and L. triangulata. Six compounds were isolated from the MeOH extracts of L. serriola using open column chromatography and identified as protocatechuic acid (1), caffeic acid (2), cynaroside (3), apigenin 7-glucuronide (4), luteolin (5), and apigenin (6) using ¹H-, ¹³C-nuclear magnetic resonance, and mass spectrometry. Quantitative analysis of the six compounds was performed on the MeOH extract of Lactuca species using high-performance liquid chromatography (HPLC) and an ultraviolet (UV). A reverse-phased column was used, and the UV absorbance was set to 280 nm. The contents of compounds 2 and 3 were the highest (1.58 and 2.64 mg/g ext., respectively) in L. serriola extracts. However, compounds 4 and 6 were higher (1.46 and 0.40 mg/g ext., respectively) in L. triangulata. These results provide quantitative data for the application of Lactuca species in the pharmaceutical and functional food industries.

• International Journal of Internet, Broadcasting and Communication
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• 제16권2호
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• pp.203-208
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• 2024

The convergence of deep learning and smart factory is drawing a lot of attentions from not only industrial but also academic circles. The objective of this article is to quantitatively review on deep learning and smart factory from 2010 to 2023. This research analyzed the 138 articles, extracted from the Core Collection of Web of Science, in terms of four dimensions such as the main trend in article publications, the main trend in article citations, the distribution of article publications by research area, and the keywords representing the main contents of published articles. The quantitative review results reveal the following four points: First, the article publications drastically grew from 2019 to 2022 in its annual trend. Second, the article citations have rapidly grown since 2018. Third, Engineering, Computer Science, and Telecommunications are the top 3 research areas composing the 138 articles. Fourth, it is the top 10 keywords such as 'deep', 'learning', 'smart', 'detection', factory', 'data', 'system', 'manufacturing', 'neural', and 'network' that represent the main contents of the 138 articles published from 2010 to 2023 in deep learning and smart factory. These findings revealed by this quantitative review will be significantly useful for deepening and widening relevant future research on deep learning and smart factory.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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• pp.85-88
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• 2007

본 연구에서는 베이지안 망 구조 학습에서, 학습 데이터의 특정 부분집합이 학습된 망의 각연결 구조(edge)의 형성에 기여하는 정도를 정량화하는 방법을 제안한다. 생물학 정보의 분석 등에 베이지안 망 학습을 이용하는 경우, 제안된 방법은 망의 각 연결 구조의 형성에 특정 군집 데이터가 기여하는 정도의 정량화가 가능하다. 제안된 방법의 유효성을 보이기 위해, 벤치마크 베이지안 망을 이용하여 제안된 방법이 망 연결 구조에 대한 데이터 군집별 기여도를 효과적으로 정량화 할 수 있음을 보인다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1124-1124
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• 2001

CARNAC is a procedure for obtaining quantitative analysis of a sample by comparison of the NIR spectra of the unknown sample with a database of a large number of samples with NIR spectral and compositional data. The method depends on the compression of the NIR database followed by a modification of the compressed data which emphasizes the required analyte. The method identifies a few very similar samples and the value of the required analyte is calculated from a weighed average of the analyte values for the selected similar samples. The method was originally described at Chambersburg IDRC in 1986 and in the Proceedings of the FT Conference of 1987. This contribution will describe recent work on utilising new methods for both compression and modification.

• Asian Journal of Innovation and Policy
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• 제5권3호
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• pp.251-274
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• 2016

Practical methodology for categorizing collaborative disciplines or research in a quantitative manner is presented by developing a Correlation Matrix of Major Disciplines (CMMD) using bibliometric data collected between 2009 and 2014. First, 21 major disciplines in science and engineering are defined based on journal publication frequency. Second, major disciplines using a comparing discipline correlation matrix is created and correlation score using CMMD is calculated based on an analyzer function that is given to the matrix elements. Third, a correlation between the major disciplines and 14 research fields using CMMD is calculated for validation. Collaborative researches are classified into three groups by partially accepting the definition of pluri-discipline from peer review manual, European Science Foundation, inner-discipline, inter-discipline and cross-discipline. Applying simple categorization criteria identifies three groups of collaborative research and also those results can be visualized. Overall, the proposed methodology supports the categorization for each research field.

• Journal of Information Display
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• 제5권3호
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• pp.35-40
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• 2004

In this study, we collected data used to formulate the relationship between quantitative metrological parameters in CRT display and the perceived focus quality. Human perception of the focusing quality was evaluated in terms of user feedback scores regarding the character legibility from four highly trained inspectors. Thirteen CRT monitors from five different manufacturers were compared relatively with respect to the norm monitor. The profile of electron beam such as spot size and the shape of distribution made by electron beam, contrast, convergence of RGB beams, and luminance characteristics were measured using a precision measurement system. Linear regression analysis and artificial neural network models were used to formulate the relationship between human perception and the quantitative measurements. The accuracy of the formulated linear regression model ($R^2$=0.515) was not satisfactory but the nonlinear neural network model ($R^2$=0.716) was fairly convincing and robust even the utilized data included subjective differences.