• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.110-117
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• 2004

The aim of a benchmark study is carried out nine methods are employed for ULS analysis which implicitly predict the ultimate strength of aluminium stiffened panels under axial compression. For this purpose, DNV PULS, experimental and numerical data on the ultimate strength of panels were collected. Comparison of these experimental / numerical, DNV PULS / numerical, results with theoretical solutions by the candidate methods is performed. Also it's compared that ALPS/ULSAP program is based on closed-form formula for the ULS of plates and grillages under axial compression. It is considered that ALPS/ULSAP methodology provides quite accurate and reasonable ULS calculations by a comparison with more refined FEA. Comparison of these experimental data, numerical, computational software results with the simplified solutions obtained by the candidate methods is then performed. The model uncertainties associated with the candidate methods are studied in terms of mean bias and COV (i.e., coefficient of variation) against experiments and numerical solutions, and the relative performance of the various methods is discussed.

• Computers and Concrete
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• v.15 no.2
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• pp.279-304
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• 2015

In this study, reliability analyses of steel fiber reinforced concrete (SFRC) corbels based on stochastic finite element were performed for the first time in literature. Prior to stochastic finite element analysis, an experimental database of 84 sfrc corbels was gathered from literature. These sfrc corbels were modeled by a special finite element program. Results of experimental studies and finite element analysis were compared and found to be very close to each other. Furthermore experimental crack patterns of corbel were compared with finite element crack patterns and were observed to be quite similar. After verification of the finite element models, stochastic finite element analyses were implemented by a specialized finite element module. As a result of stochastic finite element analysis, appropriate probability distribution functions (PDF's) were proposed. Finally, coefficient of variation, bias and strength reduction (resistance) factors were proposed for sfrc corbels as a consequence of stochastic based reliability analysis.

• Research in Community and Public Health Nursing
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• v.25 no.2
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• pp.146-157
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• 2014

Purpose: The objective of this study is to analyze systematically the trends of experimental researches in the area of community health nursing. Methods: This is a study based on literature review, which analyzed 137 experimental research papers in the Journal of Korean Academy of Community Health Nursing, from the first issue in 1989 to those in 2012. Results: 1) The proportion of experimental researches in the total published papers was 14.9%. 2) The mainly used research method was quasi-experiment, which was 60.6% of them, and there was no RCT. 3) Convenient sampling was used in 95.6% of the researches. 4) Only 5.1% were reviewed for keeping the ethical standards for the study objects by the IRB. 5 When classified by the Omaha Classification System, psycho-social researches were most frequent, which were followed by physiological, health-related behavioral, and environmental ones in order of frequency. Conclusion: This study found that the proportion of experimental research papers was increasing in the 2000s and ethical standards were required more rigorously. However, it was suggested that the research design be more elaborated and sampling methods be manifested to reduce research bias and errors.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.337-343
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• 2003

In this paper we present the prediction interval estimation method using bootstrap method for least squares support vector machine(LS-SVM) regression, which allows us to perform even nonlinear regression by constructing a linear regression function in a high dimensional feature space. The bootstrap method is applied to generate the bootstrap sample for estimation of the covariance of the regression parameters consisting of the optimal bias and Lagrange multipliers. Experimental results are then presented which indicate the performance of this algorithm.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1990.10a
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• pp.63-67
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• 1990

Many characteristics of space charge in insulating materials which is the cause of insulation break down was measured quantita-tively. It was confirmed that injection charge of the electrode was trapped to form mainly space charge. In the present paper, collecting potential was determined by TSSP and mean depths of space distribution was investigated by measuring variation quantity of space charge under the different bias time, voltage and temperature. Experimental resuts was in good agreement with model analysis on a stedy state.

• Journal of the Korean institute of surface engineering
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• v.31 no.6
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• pp.400-406
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• 1998

Tool life characteristics were investigated for the TiN coated (PVD) tungsten carbide cutting tools to improve the tool life Experimental variables for Tin coating were coating time and cathode bias voltage and cuting variables were cutting speed and feel rate. As a experiment result, TiN coated tool was extended about from 2.14 to 2.7 times than that of not coated tungsten carbide tools. Also, coating thinkness is much affected to tool life.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.313-316
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• 2004

Model selection is the process that sets up the regularization parameter in the support vector machine or regularization network by using the external methods such as general cross validation or L-curve criterion. This paper suggests that the regularization parameter can be obtained simultaneously within the learning process of neural networks without resort to separate selection methods. In this paper, extended kernel method is introduced. The relationship between regularization parameter and the bias term in the extended kernel is established. Experimental results show the effectiveness of the new model selection method.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.367-371
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• 1990

In this paper, a real-time fault tolerant control system has been designed for the cooling system of the spent fuel pool storage. The fault tolerant control system consists of the fault detection part, the redundant actuator part(main and backup pumps) and the controller implemented on programmable. logic controller. This paper considers only the actuator fault whose detection is accomplished using Friedland's separated bias estimation method. This paper also shows the real-time experimental results from which it can be concluded that the designed fault tolerant control system exhibits satisfactory performance.

• Korean journal of communication and information
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• v.46
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• pp.323-353
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• 2009

Press (un)fairness has been a social issue in Korea. The previous research focused mainly on the suggestion of fairness norms, principles, concepts, and definitions. Also, the research tried to measure the degree of fairness by analyzing press contents. This study attempted to overcome the media- and source-oriented approach proposing ordinary press consumers' perspectives. The study posited that one's fairness judgment would be greatly influenced by his or her preexisting attitudes on issue. Based on social judgment theory and hostile media perception framework, the research expected 'assimilation' bias for attitudinally congruent group and 'contrast' bias for attitudinally incongruent group. An $3\times3\times2$ experimental design was employed to test the theoretical predictions. The results found assimilation and contrast bias for strong attitude groups who read one-sided and two-sided messages. The results also implied hostile media perception occurred by selective categorization. Also the difficulty and limitation of traditional fairness judgment and media-centered approach was discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.655-660
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• 2005

This paper studied the feature parameters less affected by the emotional variation for the development of the robust speech recognition technologies. For this purpose, the effect of emotional variation on the speech recognition system and robust feature parameters of speech recognition system were studied using speech database containing various emotions. In this study, LPC cepstral coefficient, met-cepstral coefficient, root-cepstral coefficient, PLP coefficient, RASTA met-cepstral coefficient were used as a feature parameters. And CMS and SBR method were used as a signal bias removal techniques. Experimental results showed that the HMM based speaker independent word recognizer using RASTA met-cepstral coefficient :md its derivatives and CMS as a signal bias removal showed the best performance of $7.05\%$ word error rate. This corresponds to about a $52\%$ word error reduction as compare to the performance of baseline system using met - cepstral coefficient.