• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2002년도 봄 학술발표논문집 Vol.29 No.1 (B)
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• pp.238-240
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• 2002

If there is an Information Retrieval system which comprehends the semantic content of documents and knows the preference of users. the system can search the information better on the Internet, or improve the IR performance. Therefore we propose the IR model which combines semantic based indexing and fuzzy relevance model. In addition to the statistical approach, we chose the semantic approach in indexing, lexical chains, because we assume it would improve the performance of the index term extraction. Furthermore, we combined the semantic based indexing with the fuzzy model, which finds out the exact relevance of the user preference and index terms. The proposed system works as follows: First, the presented system indexes documents by the efficient index term extraction method using lexical chains. And then, if a user tends to retrieve the information from the indexed document collection, the extended IR model calculates and ranks the relevance of user query. user preference and index terms by some metrics. When we experimented each module, semantic based indexing and extended fuzzy model. it gave noticeable results. The combination of these modules is expected to improve the information retrieval performance.

• 국제학술발표논문집
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• The 7th International Conference on Construction Engineering and Project Management Summit Forum on Sustainable Construction and Management
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• pp.32-41
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• 2017

Accidents on offshore oil and gas platforms (OOGPs) usually cause serious fatalities and financial losses considering demanding environment platforms locate and complex topsides structure platforms own. Evacuation planning on platforms is usually challenging. The computational tool is a good choice to plan evacuation by emergency simulation. However, the complex structure of platforms and varied evacuation behaviors usually weaken the advantages of computational simulation. Therefore, this study developed a simulation model for OOGPs to evaluate different evacuation plans to improve evacuation performance by integrating building information modeling (BIM) and agent-based model (ABM). The developed model consists of four parts: evacuation model input, simulation environment modeling, agent definition, and simulation and comparison. Necessary platform information is extracted from BIM and then used to model simulation environment by integrating matrix model and network model. During agent definition, in addition to basic characteristics, environment sensing and dynamic escape path planning functions are also developed to improve simulation performance. An example OOGP BIM topsides with different emergent scenarios is used to illustrate the developed model. The results showed that the developed model can well simulate evacuation on OOGPs and improve evacuation performance. The developed model was also suggested to be applied to other industries such as the architecture, engineering, and construction industry.

• 한국과학교육학회지
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• 제25권6호
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• pp.635-641
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• 2005

This paper suggests a research & education (R&E) model for the gifted in science education. The model has been developed under three assumptions. The first is that using the sequences of a gifted educational program designed to facilitate the process will assist in gifted students' construction of scientific knowledge and comprehension of laboratory practice through concrete experimental experience. The second is that gifted students will be able to apply this learning to further study using and extending scientific knowledge and experience. The third is that challenging tasks and feedback at the requisite stage of development will improve instructional effectiveness. The R&E Model has five phases: engaging, exploring, planning, performing and elaborating; furthermore, it suggests roles for the mentee and mentor. The R&E model has two functions for gifted education. The first is providing guidance for gifted curriculum developers as they design a mentor program, and the second is helping a mentor improve instructional effectiveness through use of strategies. This model has potentials to educate the gifted students in the Science Education Institute for the Gifted.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2019년도 춘계 학술논문 발표대회
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• pp.248-249
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• 2019

In the nuclear industry, in order to keep pace with the 4th industrial revolution era, they are trying to improve the construction and maintenance ability by utilizing the technologies such as digital twin and VR/AR from the construction stage. However, the nuclear 3D CAD model, which is used as the base in the latest technology, is heavy due to a large number of facilities per unit space compared to other industrial companies, and it is difficult to directly incorporate the latest technology into the results of CAD programs for design purposes. In this study, in order to improve usability, we tried to lighten the 3D model. First, we analyze the existing nuclear power plant 3D model and draw out the problems and features. Secondly, we derived the factors to consider when we make the 3D CAD models lightweight.

• Structural Engineering and Mechanics
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• 제73권1호
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• pp.27-35
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• 2020

In rail industry, noise reduction is a concern to decrease environmental pollution. The current study focuses on rail damper modeling and improvement of the model through validation with experimental results. Accurate modeling and simulation of rail dampers, specifically tuned rail dampers with layers interconnected by bolt joints, shall enable objective-oriented improvement of their design. In this work, to improve the damper model cone pressure theory is applied in the FE model and the sensitivity analysis is then applied to gradually improve the FE model. The improved model yields higher Modal Assurance Criterion (MAC) values and lower frequencies deviation.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1992년도 제2회 정기총회 및 추계학술 발표회 발표논문 초록
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• pp.8-8
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• 1992

Through a simulation experiment, often an experimenter is concerned with estimating the system parameters of the linear model consisting of m design points from the outputs oft the simulation model. To improve the estimation of the system parameters and reliability of these estimators, appropriate simulation techniques have been developed. For the first order linear model, Schruben and Margolin (1978) exploited the random number assignment rules which uses a combination of common random numbers and antithetic streams in a simulation experiment designed to estimate the system parameters when the design matrix of simulation model admits orthogonal blocking into two blocks. Nozari, Arnold and Pegden (1984) developed a method for appliying the method of control variates to the situation of the linear model having multiple design points. This talk deals with a different way of utilizing controls under the correlation induction strategy of Schruben and Margolin's to improve the simulation efficiency, and presents a procedure for obtaining the estimators of the system parameters analytically. Simulation results on a selected simulation model indicate a promising evidence that a proposed method may yield better results than Schruben and Margolin's method.

• 한국축산식품학회지
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• 제43권2호
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• pp.374-381
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• 2023

In a previous study, 'response surface methodology (RSM) using a fullest balanced model' was proposed to improve the optimization of food processing when a standard second-order model has a significant lack of fit. However, that methodology can be used when each factor of the experimental design has five levels. In response surface experiments for optimization, not only five-level designs, but also three-level designs are used. Therefore, the present study aimed to improve the optimization of food processing when the experimental factors have three levels through a new approach to RSM. This approach employs three-step modeling based on a second-order model, a balanced higher-order model, and a balanced highest-order model. The dataset from the experimental data in a three-level, two-factor central composite design in a previous research was used to illustrate three-step modeling and the subsequent optimization. The proposed approach to RSM predicted improved results of optimization, which are different from the predicted optimization results in the previous research.

• 한국간호교육학회지
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• 제24권1호
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• pp.100-109
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• 2018

Purpose: This study evaluated the effect of a teaching model to improve cultural competency (TMCC) for Korean undergraduate nursing students. Methods: A nonequivalent control group pretest/posttest quasi-experimental study was conducted with a convenience sample of 168 undergraduate nursing students in South Korea. The experimental group of 121 seniors was taught a 13-week teaching model in order to improve cultural competence. A control group with 47 junior students underwent nursing major courses, but did not take this teaching model. Before and after the program, students' level of cultural competency was measured using the Questionnaire for Cultural Competence (QCC) consisting of three sub-scales: "awareness and desire," "encounter," and "nursing skill and knowledge." Results: After the experiment, the experimental group showed significantly higher improvement in the Questionnaire for Cultural Competence in the three sub-scales of "awareness and desire," "encounter," and "nursing skill and knowledge" than the control group (p=<.050). Conclusion: A teaching model to improve cultural competence was effective in improving Korean undergraduate nursing students' cultural competency. Further studies need to be repeated in order to identify the effectiveness of the teaching model to improve cultural competency with graduate or clinical nurses.

• 제어로봇시스템학회논문지
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• 제19권11호
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• pp.1022-1028
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• 2013

It is well knowns that based on the CSP (Common Spatial Pattern) algorithm, the linear projection of an EEG (Electroencephalography) signal can be made to spaces that optimize the discriminant between two patterns. Sharing disadvantages from linear time invariant systems, CSP suffers from the non-stationary nature of EEGs causing the performance of the classification in a BCI (Brain-Computer Interface) system to drop significantly when comparing the training data and test data. The author has suggested a simple idea based on the parallel model of CSP filters to improve the performance of BCI systems. The model was tested with a simple CSP algorithm (without any elaborate regularizing methods) and a perceptron learning algorithm as a classifier to determine the improvement of the system. The simulation showed that the parallel model could improve classification performance by over 10% compared to conventional CSP methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.420-437
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• 2024

There are some problems in network traffic classification (NTC), such as complicated statistical features and insufficient training samples, which may cause poor classification effect. A NTC architecture based on one-dimensional Convolutional Neural Network (CNN) and transfer learning is proposed to tackle these problems and improve the fine-grained classification performance. The key points of the proposed architecture include: (1) Model classification--by extracting normalized rate feature set from original data, plus existing statistical features to optimize the CNN NTC model. (2) To apply transfer learning in the classification to improve NTC performance. We collect two typical network flows data from Youku and YouTube, and verify the proposed method through extensive experiments. The results show that compared with existing methods, our method could improve the classification accuracy by around 3-5%for Youku, and by about 7 to 27% for YouTube.