• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.827-838
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• 2023

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.478-481
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• 2021

With the transition to non-face-to-face classes due to the outbreak of COVID-19, education at school sites is moving in a different direction from traditional lecture-style classes. Accordingly, several online platforms have emerged, and our education is in a transitional period of class change. As a result, after a survey of the currently used online platform, where various contrasts clearly exist, compared with the report before the outbreak of COVID-19, students' perception of ICT usage ability in terms of affective, psychic, and value perception changes want to check

• International conference on construction engineering and project management
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• 2011.02a
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• pp.99-106
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• 2011

Recent demands from construction industry have emphasized the capability for graduates to have improved skills both technical and non-technical such as problem solving, interpersonal communication. To satisfy these demands, problem-based learning that is an instructional method characterized by the use of real world problem has been adopted and has proven its effectiveness various disciplines. However, in spite of the importance of field senses and dealing with real problem, construction engineering education has generally focused on traditional lecture-oriented course. In order to improve limitations of current construction education and to satisfy recent demands from construction industry, this paper proposes a new educational approach that is Failure-Based Learning for using combination of the procedural characteristics of the problem-based learning theory in construction technology education utilizing failure information that has the educational value in the construction area by reinterpreting characteristics of construction industry and construction failure information. The major results of this study are summarized as follows. 1) Educational effect of problem-based learning methodology and limitation of application in construction area 2) The educational value of the information on construction failure and limitation in application of the information in construction sector 3) Anticipated effect from application of the failure-based learning 4) Development and application of the failure-based learning model

• KDI Journal of Economic Policy
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• v.38 no.3
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• pp.1-15
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• 2016

Improving the quality of school education is one of the key policy concerns in Korea. This paper examines whether providing schools with adequate autonomy and incentives can meet the policy goals by looking at a recent policy reform in Korea. In 2009, the Korean government granted autonomy to certain private high schools on the condition that no financial subsidies would be provided to the schools. Because the autonomous private high schools cannot receive a subsidy, they have a strong incentive to meet parental demands because schools failing to meet these demands will lose students and will have to close. Applying the value-added model to longitudinal data at the student level, I find that students entering these autonomous schools show faster growth in their academic achievement than their peers in traditional non-autonomous schools. These results suggest that providing schools with autonomy and incentives can be a useful policy tool for improving school education.

• BMB Reports
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• v.37 no.1
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• pp.59-74
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• 2004

The study of whole patterns of changes in protein expression and their modifications, or proteomics, presents both technological advances as well as formidable challenges to biological researchers. Nutrition research and the food sciences in general will be strongly influenced by the new knowledge generated by the proteomics approach. This review examines the different aspects of proteomics technologies, while emphasizing the value of consideration of "traditional" aspects of protein separation. These include the choice of the cell, the subcellular fraction, and the isolation and purification of the relevant protein fraction (if known) by protein chromatographic procedures. Qualitative and quantitative analyses of proteins and their peptides formed by proteolytic hydrolysis have been substantially enhanced by the development of mass spectrometry technologies in combination with nanoscale fluidics analysis. These are described, as are the pros and cons of each method in current use.

• 한국정보통신설비학회:학술대회논문집
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• 2006.08a
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• pp.145-150
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• 2006

For most of the measuring methods of traditional control theory, measuring equipments are located at the output of the system to measure quantities transformed from non-electrical form into electrical one. This method helps us to define the value of parameters to be measured, but it has limitation because it can only assess the efficiency of a movement process. That means we can not understand the inner kinetics which is the essence of the system. In the modern control theory, states of system are considered as the feedback to the control process, which helps us to assess the elements in the inside of the system. In this paper, we survey methods for estimating states being not exposed to the correct measurements. Using this method, we also suggest an application for giving an estimate of the traffic on the LSPs to adapt the network configuration for changing traffic conditions.

• Journal of Advanced Marine Engineering and Technology
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• v.6 no.2
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• pp.42-50
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• 1982

The controller, generally, is to be designed to optimize the system in somesence subject to some constraints. In this paper the method to determine the optimal parameters of the PI controller in the unity feed back control system is proposed. Here the sence of the optimal is to minimize the integral of the squared error under the constraints that the maximum absolute value of control input, maximum overshoot, rise time, etc., should be smaller than the pre-given values. In the analysis the traditional method and the state variable method are combined in order to reduce the computational procedures required in the design of PI controller. Therefore, the procedure proposed in the paper is usefully applicable to the controller system with a general second-order plant. Finally, the indicial response curves generated at the optimal state are compared with those of non-optimal state and the effectiveness of this method is assertained.

• Genomics & Informatics
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• v.13 no.3
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• pp.90-92
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• 2015

Biological diversity, also known as biodiversity, is an important criterion for measuring the value of an ecosystem. As biodiversity is closely related to human welfare and quality of life, many efforts to restore and maintain the biodiversity of species have been made by government agencies and non-governmental organizations, thereby drawing a substantial amount of international attention. In the fields of biological research, biodiversity is widely measured using traditional statistical indices such as the Shannon-Wiener index, species richness, evenness, and relative dominance of species. However, some biologists and ecologists have difficulty using these indices because they require advanced mathematical knowledge and computational techniques. Therefore, we developed VBioindex, a user-friendly program that is capable of measuring the Shannon-Wiener index, species richness, evenness, and relative dominance. VBioindex serves as an easy to use interface and visually represents the results in the form of a simple chart and in addition, VBioindex offers functions for long-term investigations of datasets using time-series analyses.

• Electronics and Telecommunications Trends
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• v.33 no.2
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• pp.64-76
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• 2018

This paper addresses the antitrust case of Google's general search service to find evidence and logic used for defining markets, and the proof of dominant power and its abuse in detail. This antitrust case has certain meaning because it is not easy to apply traditional approaches to a general search service, which has two-sided market characteristics. This paper finds some implications through an analysis of the antitrust case shown below. First, for market definition, the overall qualitative analysis can be used to draw conclusions without a quantitative analysis, such as a Small but Significant and Non-transitory Increasing in Price (SSNIP) analysis. Second, the multi-homing behavior seems to be one of the key factors in judging the dominant power in Internet-based services. Lastly, the fact that the value of traffic can differ based on the traffic source needs to be considered to address the competition issue of Internet-based services.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.273-289
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• 2023

In this paper, we develop a new time series model for predicting IPO (initial public offering) data with non-negative integer value. The proposed model is based on integer-valued autoregressive (INAR) model with a Poisson thinning operator. Just as the heterogeneous autoregressive (HAR) model with daily, weekly and monthly averages in a form of cascade, the integer-valued heterogeneous autoregressive (INHAR) model is considered to reflect efficiently the long memory. The parameters of the INHAR model are estimated using the conditional least squares estimate and Yule-Walker estimate. Through simulations, bias and standard error are calculated to compare the performance of the estimates. Effects of model fitting to the Korea's IPO are evaluated using performance measures such as mean square error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE) etc. The results show that INHAR model provides better performance than traditional INAR model. The empirical analysis of the Korea's IPO indicates that our proposed model is efficient in forecasting monthly IPO volumes.