• Structural Engineering and Mechanics
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• 제66권6호
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• pp.677-691
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• 2018

Reliability assessment of complex structures using simulation methods is time-consuming. Thus, surrogate models are usually employed to reduce computational cost. AK-MCS is a surrogate-based Active learning method combining Kriging and Monte-Carlo Simulation for structural reliability analysis. This paper proposes three modifications of the AK-MCS method to reduce the number of calls to the performance function. The first modification is related to the definition of an initial Design of Experiments (DoE). In the original AK-MCS method, an initial DoE is created by a random selection of samples among the Monte Carlo population. Therefore, samples in the failure region have fewer chances to be selected, because a small number of samples are usually located in the failure region compared to the safe region. The proposed method in this paper is based on a uniform selection of samples in the predefined domain, so more samples may be selected from the failure region. Another important parameter in the AK-MCS method is the size of the initial DoE. The algorithm may not predict the exact limit state surface with an insufficient number of initial samples. Thus, the second modification of the AK-MCS method is proposed to overcome this problem. The third modification is relevant to the type of regression trend in the AK-MCS method. The original AK-MCS method uses an ordinary Kriging model, so the regression part of Kriging model is an unknown constant value. In this paper, the effect of regression trend in the AK-MCS method is investigated for a benchmark problem, and it is shown that the appropriate choice of regression type could reduce the number of calls to the performance function. A stepwise approach is also presented to select a suitable trend of the Kriging model. The numerical results show the effectiveness of the proposed modifications.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2007년도 춘계학술대회 논문집
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• pp.141-144
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• 2007

BLUs are major component in LCD industry which occupies 90% or more of FPD market worldwide and BLU market is expected to be expanded continuously according to the trend of miniaturization, slimness, low power consumption and low weight. The larger the BLU market scale, the more important standardization of performance evaluation techniques to clearly prescribe the product specification. Currently the government is promoting the establishment of related laws and coincidence with international standards to cope with agreements such as WTO/TBT, but the nongovernmental standardization activities are not enough to be actualized. Furthermore, BLU related components such as CCFL, EEFL, inverter and reflector are already developed for localization to substitute imports with home products but collective standardization, national standardization, and international standardization are still not done. So, performance specifications and evaluation methods for normal fluorescent lamps or industrial lamps are being adopted and used as national standards and safety certification standards instead. Making these standards enables to prepare a chance to penetrate into global market and to promote world best products. Also, by making this collective standard, it provides chances to take part in international standardization activities, to protect domestic industries and technologies, to obtain the trend of advanced technologies, and to be predominant over other countries. That is to say, CCFL standardization helps raise 21st century national strategic technology policy and go ahead of globalization of core technologies.

• 대한방사선기술학회지:방사선기술과학
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• 제47권1호
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• pp.1-6
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• 2024

In Recent years, there has been a noticeable increase in the global incidence of breast cancer, with approximately 2.3 million cases of female breast cancer reported worldwide in 2020. Numerous studies are currently underway to enhance the accuracy of breast cancer diagnosis through the development of digital mammography detectors. This study aims to create Monte Carlo simulation-based mammographic anti-scatter grids and investigate their utility in evaluating the performance of digital mammography detector. Two types of mammographic anti-scatter grids, MAM-CP and Senographe 600T HF, were created using Monte Carlo simulation software (MCNPX 2.7.0), with grid ratios of 3.7 : 1 and 5 : 1, respectively. The grid physical characteristics (sensitivity, exposure factor, contrast improvement ratio) were calculated based on the KS C IEC60627 in the simulations using two X-ray qualities, RQA-M2 (28 kVp) and MW4 (35 kVp). As the X-ray tube voltage increased from 28 kVp to 35 kVp, sensitivity and exposure factor exhibited a decreasing trend, while contrast improvement ratio demonstrated an increasing trend. With an increase in grid ratio from 3.7 : 1 to 5 : 1, all physical characteristics showed an upward trend. Our results were consistent with a previous study that conducted measurements of physical properties using a real phantom. However, the pattern of change in the contrast improvement ratio with X-ray tube voltage differed from the previous study.

• 대한수학교육학회지:수학교육학연구
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• 제9권1호
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• pp.333-350
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• 1999

The purpose of this study is to define performance assessment of mathematics, to make a model of performance task of mathematics for the first grade middle school students in higher group, to examine validity and reliability of performance task and to investigate the effects on the students' achievement and attitude. It first defines performance assessment and exanmines its main features and scoring methods. Based on these, nine performance assessment tasks and scoring criteria were designed for the first grade middle school students in higher group. The validity of performance tasks were examined by experts. The loaming achievement and mathematical attitude test between two groups were performed as pre and post test. The thinking of students about performance assessment was investigated by attitude survey. The results of this study are as follows: First, the validity of the performance tasks is very high. Second, The control group. Forth, there is a difference in student's attitude about mathematics between scorer reliability was high due to the scorer training. Third, there is little difference in teaming achievement between experimental and experimental and control group in 5% meaningful levels. That is, student's of both groups attitude about mathematics comes negatives, but the width of change of negative attitude in experimental group is less than control group. In the trend of negative attitude of mathematics as grade comes higher, this results showed that performance assessment of mathematics had positive influence on attitude of mathematics. The result of survey about mathematical performance assessment experience showed that students have positive attitude to performance assessment and recognized effectiveness of the performance assessment of mathematics.

• 한국의류산업학회지
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• 제22권5호
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• pp.639-649
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• 2020

This study investigates consumer opinions of clothing care and provides fundamental data to decision-making for oncoming development of clothing care system. Textom, a web-matrix program, was used to analyze big data collected from Naver and Daum with a keyword of "clothing care" from March 2019 to February 2020. A total of 22, 187 texts were shown from the big data collection. Collected big data were analyzed using text-mining, network, and CONCOR analysis. The results of this study were as follows. First, many keywords related to clothing care were shown from the result of frequency analysis such as style, Dryer, LG Electronics, Product, Customer, Clothing, and Styler. Consumers were well recognizing and having an interest in recent information related to the clothing care system. Second, various keywords such as product, function, brand, and performance, were linked to each other which were fundamentally related to the clothing care. The interest in products of the clothing care system were linked to product brands that were also naturally linked to consumer interest. Third, the keywords in the network showed similar attributes from the result of CONCOR analysis that were classified into 4 groups such as the characteristics of purchase, product, performance, and interest. Lastly, positive emotions including goodwill, interest, and joy on the clothing care system were strongly expressed from the result of the sentimental analysis.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 1996년도 The Korean Institute of Navigation 1996년도 춘계학술발표회 논문집
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• pp.59-76
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• 1996

Vessels in the world merchant fleet generally operate in either liner or bulk trade. The supply and the demand trend of general cargo ship are both on the ebb however those trend of tankers and containers are ins light ascension. Oil tankers are so far the largest single vessel type in the world fleet and the tanker market is often cited as a texbook example of perfect competition. Some shipping statistics in recent years show that there has been a radical fluctuation in spot charter rate under easy charter's market. This implies that the proper scheduling of tankers under spot market fluctuation has the great potential of improving the owner's profit and economic performance of shipping. This paper aims at developing the TS-DSS(Decision Support System for Tanker Scheduling) in the context of the importance of scheduling decisions. TS-DSS is defined as a DSS based on the optimization models for tanker scheduling. The system has been developed through the life cycle of systems analysis design and implementation to be user-friendly system. The performance of the system has been tested and examined by using the data edited under several tanker scheduling has been tested and examined by using the data edited under several tanker scheduling scenarios and thereby the effectiveness of TS-DSS is validated satisfactorily. The authors conclude the paper with the comments of the need of appropriate support environment such as data-based DSS and network system for successful implementatio of the TS-DSS.

• 항공우주산업기술동향
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• 제6권1호
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• pp.124-134
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• 2008

The rising demand for the high efficiency and high covertness in UAV motivates the miniature design of the high performing mission sensors, or payloads. One of the promising payload sensors, EO/IR sensor has evolved satisfying its demands and became the main stand-alone mission sensor for 200kg-range UAV. One aspect in development of EO/IR sensor concerns lack of specification criterions to represent its performance. Even though the high demand and competition among each manufacturer caused EO/IR features subject to rapid change collateral to new technology, the datasheets maintained the conventional outdated formats which leave some of the major components in ambiguity. Making comparisons or predicting actual performance with such datasheets is hardly worthwhile; yet, they could be important reference guide for the potential customers what to expect for the upcoming EO/IR. According to UAS Roadmap 2007-2032 published by DoD, one of the main potential customers as well as a main investor of EO/IR technology, EO/IR is expected to play key roll in solving urgent problems, such as see and avoid system. This paper will examine the recent representative EO/IR specialized in UAS missions through datasheets to find out current trend and eventually extrapolate the possible future trend.

• 한국항해학회지
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• 제20권1호
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• pp.27-46
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• 1996

Vessles in the world merchant fleet generally operate in either liner or bulk trade. The supply and the demand trend of general cargo ship are both on the ebb, however, those trend of tankers and containers are in slight ascension. Oil tankers are so far the largest single vessel type in the world fleet and the tanker market is often cited as a textbook example of perfect competition. Some shipping statistics in recent years show that there has been a radical fluctuation in spot charter rate under easy charterer's market. This implys that the proper scheduling of tankers under spot market fluctuation has the great potential of improving the owner's profit and economic performance of shipping. This paper aims at developing the TS-DSS(Decision Support System for Tanker Scheduling) in the context of the importance of scheduling decisions. The TS-DSS is defined as the DSS based on the optimization models for tanker scheduling. The system has been developed through the life cycle of systems analysis, design, and implementation to be user-friendly system. The performance of the system has been tested and examined by using the data edited under several tanker scheduling scenarios and thereby the effectiveness of TS-DSS is validated satifactorily. The authors conclude the paper with the comments on the need of appropriate support environment such as data-based DSS and network system for succesful implementation of the TS-DSS.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2009년도 춘계 학술논문 발표대회 학계
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• pp.53-56
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• 2009

This study reviewed the characteristics of concrete made of performance improving mixture materials based on KOH as a means to resolve the problems of initial quality reduction that result in concretes with blast furnace slag powder. Summarizing the results, first as the characteristics of fresh concrete, liquidity was found to reduce in general with increased BS substitution ratio. Objective range of liquidity was not satisfied in all mixes according to the use of performance improving mixture materials. Air capacity was satisfied to the objective range in all mixes. As the characteristics of hardened concrete, while compressive strength showed a decreasing trend with increasing BS substitution ratio at early age, increasing trend was shown by the plain with increasing BS substitution ratio at later age. On the other hand, K1 and K2 were only effective among mixture materials at early age, but K1F30 showed excellent strength at both early and later ages.

• Journal of Information Processing Systems
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• 제15권3호
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• pp.694-706
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• 2019

In this study, we applied the long short-term memory (LSTM) model to classify the cryptocurrency price time series. We collected historic cryptocurrency price time series data and preprocessed them in order to make them clean for use as train and target data. After such preprocessing, the price time series data were systematically encoded into the three-dimensional price tensor representing the past price changes of cryptocurrencies. We also presented our LSTM model structure as well as how to use such price tensor as input data of the LSTM model. In particular, a grid search-based k-fold cross-validation technique was applied to find the most suitable LSTM model parameters. Lastly, through the comparison of the f1-score values, our study showed that the LSTM model outperforms the gradient boosting model, a general machine learning model known to have relatively good prediction performance, for the time series classification of the cryptocurrency price trend. With the LSTM model, we got a performance improvement of about 7% compared to using the GB model.