• Proceedings of the KIEE Conference
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• summer
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• pp.1528-1530
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• 2004

In this paper, an efficient switching pattern to equalize the size of transformer is proposed for a multi-level inverter employing cascaded transformers. It is based on the prior selected harmonic elimination PWM(SHEPWM) method. Because the maximum magnetic flux imposed on each transformer becomes exactly equal each to each, all transformers can be designed with the same size regardless of their position. Therefore, identical full-bridge inverter units can be utilized, thus improving modularity and manufacturability. The fundamental idea of the proposed switching pattern is illustrated and then analyzed theoretically. The validity of the proposed switching strategy is verified by experimental results.

• Journal of Power Electronics
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• v.12 no.6
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• pp.912-924
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• 2012

In hybrid renewable power systems, the use of a multiple-input dc/dc converter (MIC) leads to simpler circuit and lower cost, when compared to the conventional use of several single-input converters. This paper proposed a novel three-input buck/boost/buck-boost converter, which can be used in applications with various values of input voltage. The energy sources in this converter can deliver power to the load either simultaneously or individually in one switching period. The steady relationship, the power management strategy and the small-signal circuit model of this converter have been derived. With decoupling technology, modeling and regulator design can be obtained under multi-loop control modes. Finally, three generating methods of a multiple-input buck/boost/buck-boost converter is given, and this method can be extended to the other multiple-input dc/dc converters.

• Asia pacific journal of information systems
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• v.1 no.1
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• pp.63-86
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• 1991

In this paper, our concern is the artificial neural network-based patten classification, when can resolve the difficulties in the Autoregressive Moving Average(ARMA) model identification problem To effectively classify a time series into an approriate ARMA model, we adopt the Multi-layered Backpropagation Network (MLBPN) as a pattern classifier, and Extended Sample Autocorrelation Function (ESACF) as a feature extractor. To improve the classification power of MLBPN's we suggest an integrated neural network system which consists of an AR Network and many small-sized MA Networks. The output of AR Network which will gives the MA order. A step-by-step training strategy is also suggested so that the learned MLBPN's can effectively ESACF patterns contaminated by the high level of noises. The experiment with the artificially generated test data and real world data showed the promising results. Our approach, combined with a statistical parameter estimation method, will provide a way to the automation of ARMA modeling.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.12
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• pp.964-969
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• 2002

The flexural vibration of laminated composite beams with passive constrained layer damping has been investigated to design structure with maximum possible damping capacity. The equations of motion are derived for flexural vibrations of symmetrical, multi-layer laminated beams. The damping ratio and modal damping of the first bending mode are calculated by means of Iterative complex eigensolution method. This paper addresses a design strategy of laminated composite under flexural vibrations.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.37-50
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• 2021

Query applications based on nested data, the most commonly used form of data representation on the web, especially precise query, is becoming more extensively used. MapReduce, a distributed architecture with parallel computing power, provides a good solution for big data processing. However, in practical application, query requests are usually concurrent, which causes bottlenecks in server processing. To solve this problem, this paper first combines a column storage structure and an inverted index to build index for nested data on MapReduce. On this basis, this paper puts forward an optimization strategy which combines query execution service tree and frequent sub-query trajectory to reduce the response time of frequent queries and further improve the efficiency of multi-user concurrent queries on large scale nested data. Experiments show that this method greatly improves the efficiency of nested data query.

• Advances in nano research
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• v.13 no.2
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• pp.175-186
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• 2022

This study is a randomized pretest-posttest design that aims to investigate the effect of early entrepreneurship education on cognitive and non- early entrepreneurship education, non-cognitive skills, creativity, self-efficacy, Bizworld cognitive skills of male sixth-grade primary school students. A total of 45 students were selected by multi-stage random sampling method and were assigned randomly to experimental, active-control and control groups. The experimental group received entrepreneurship education based on the Bizworld entrepreneurship program. The results indicate that early entrepreneurship education had an effect on non-cognitive skills (such as risk taking propensity, creativity, self-efficacy, persistence and need for achievement. It seems that early entrepreneurship education is a proper strategy to develop children's non-cognitive skills in late years of primary school. These skills will affect children's individual, educational, social and occupational future and can have long term benefits for students, families and society.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1161-1165
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• 2009

Safety of workers and productivity in construction site are affected according to the conflict status of work spaces which are performed at a time. The interference among the work spaces in construction site should be minimized because it becomes a blocking factor that causes construction delay and low productivity. Those factors can be managed by reasonable H&S (Health & Safety) practice. This research suggests the requirements of H&S practice and rules to establish the strategy of H&S management based on the literature reviews related to H&S rule. The suggested H&S rule can be visualized for searching space conflict point if the rule is linked with visual simulation tool. Accordingly the research results can be used for improving and visualizing construction productivity by work space control in 4D/nD CAD system.

• Journal of Korean Society of Archives and Records Management
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• v.17 no.1
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• pp.245-273
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• 2017

To complement the limitations of the public relations method performed currently in archives and serve various users, a new approach to public relations are needed. Recently, as the size of the webtoon market has expanded, public relations using webtoons continues to heighten in enterprises and public institutions. Therefore, this study proposed a method for public relations using brand webtoon as a means of promoting the archives. This study was focused on the National Archives of Korea. Thus, based on the analysis of roles, service, contents, and users of the National Archives of Korea, this study suggested production plans to increase the promotional effect in brand webtoons and strategies such as viral marketing, the brand story strategy, and the one-source, multi-use (OSMU) strategy.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.261-270
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• 2020

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.