• Structural Engineering and Mechanics
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• v.48 no.2
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• pp.151-171
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• 2013

The current paper presents the numerical blind prediction of nonlinear seismic response of two full-scale, three dimensional, one-story reinforced concrete structures subjected to bidirectional earthquake simulations on shaking table. Simulations were carried out at the laboratories of LNEC (Laboratorio Nacional de Engenharia Civil) in Lisbon, Portugal. The study was motivated by participation in the blind prediction contest of shaking table tests, organized by the challenge committee of the 15th World Conference on Earthquake Engineering. The test specimens, geometrically identical, designed for low and high ductility levels, were subjected to subsequent earthquake motions of increasing intensity. Three dimensional nonlinear analytical models were implemented and subjected to the input base motions. Reasonably accurate reproduction of the measured displacement response was obtained through appropriate modeling. The goodness of fit between analytical and measured results depended on the details of the analytical models.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.948-954
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• 2002

The structural vibration of a diesel generator set was investigated through analyses and tests. FE modeling and normal mode analysis were performed and compared with measured results for both structure components and generator set assembly. The results of component analyses were fairly well coincident with measured results but those of assembled generator set showed more or less discrepancies. Discussions were given about the uncertainties for vibration characteristics of component structures and assembled running structures especially concerning their nonlinearities and damping effects. Detailed excitation analysis fellowed by forced response analysis was done from the engine and pressure data to compare with the actual measured vibration. As results the vibration prediction for frame structures of reciprocating internal combustion engine was confirmed reliable to some extent.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.130-135
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• 2013

Until now, passenger airbag design is based on the referred car design and many repetitive crash tests have been done to meet the crash performance. In this paper, it was suggested a new design process of passenger airbag. First, key performance factors were determined by analyzing the injury risk effectiveness of each performance factor. And it was made a relationship between injury risk and performance factor by using the response surface model. By using this one, it can be predicted the injury risk of head and neck. Predicted injury risk of optimal design was obtained through this injury risk prediction model and it was verified by FE analysis result within 18% error of head and 9% error of neck. It was shown that a target crash performance can be met by controlling the key performance factors only.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.146-153
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• 2009

One dimensional site response analysis is widely used in prediction of the ground motion that is induced by earthquake. Equivalent linear analysis is the most widely used method due to its simplicity and ease of use. However, the equivalent linear method has been known to be unreliable since it approximates the nonlinear soil behavior within the linear framework. To consider the nonlinearity of the ground at frequency domain, frequency dependent algorithms that can simulate shear strain - frequency dependency have been proposed. In this study, the results of the modified equivalent linear analysis are compared to evaluate the degree of improvement and the applicability of the modified algorithms. Results show the novel smoothed curve that is proposed by this study indicates the most stable prediction and can enhance the accuracy of the prediction.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.949-952
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• 2002

A regression model is used in predicting the response variable given predictor variables However, in case of large number of predictor variables, a regression model has some problems such as multicollinearity, interpretation of the functional relationship between the response and predictors and prediction accuracy. A clustering method and stepwise regression could be used to reduce the amount of data by grouping predictors having similar properties and by selecting the subset of predictors. respectively. This paper proposes a prediction method combining clustering method and stepwise regression. The proposed method fits a global model and local models and predicts responses given new observations by using both models. The paper also compares the performance of proposed method with stepwise regression via a real data of ample obtained in a steel process.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.400-409
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• 2003

Collaborative filtering (CF) recommendation is a knowledge sharing technology for distribution of opinions and facilitating contacts in network society between people with similar interests. The main concerns of the CF algorithm are about prediction accuracy, speed of response time, problem of data sparsity, and scalability. In general, the efforts of improving prediction algorithms and lessening response time are decoupled. We propose a three-step CF recommendation model which is composed of profiling, inferring, and predicting steps while considering prediction accuracy and computing speed simultaneously. This model combines a CF algorithm with two machine learning processes, SOM (Self-Organizing Map) and CBR (Case Based Reasoning) by changing an unsupervised clustering problem into a supervised user preference reasoning problem, which is a novel approach for the CF recommendation field. This paper demonstrates the utility of the CF recommendation based on SOM cluster-indexing CBR with validation against control algorithms through an open dataset of user preference.

• Journal of the Korean Society of Safety
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• v.32 no.1
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• pp.27-32
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• 2017

The experimental design methodology was applied in the real scale coal-fired boiler to predict the various combustion properties according to the operating conditions and to assess the coal plant safety. Response surface method (RSM) was introduced as a design of experiment, and the database for RSM was provided with the numerical simulation of the coal-fired boiler. The three independent variables, high heating value of coal (HHV), overall stoichiometry excess air ratio (OST), and burner-side stoichiometry excess air ratio (BST), were set to characterize the cross section averaged NOx concentration and temperature distribution. The maximum NOx concentration was predicted accurately and mainly controlled by BST in the boiler. The parabola function was assumed for the zone averaged peak temperature distribution, and the prediction was in a fairly good agreement with the experiments except downstream. Also, the location of the peak temperature was compared with that of maximum NOx, which implies that thermal NOx formation is the main mechanism in the coal-fired boiler. These results promise the wide use of statistical models for the fast prediction and safety assessment.

• Magazine of the Korea Concrete Institute
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• v.6 no.6
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• pp.180-189
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• 1994

A practical methodology to detect and localm da~nagc in rcinforced concrete structures by utilizing modal response parameters of as built and tiamaged states is presented. First, a damage detection algorithm which yields information on the, location of damage directly from changes in mode shapes of structures is outlined. Next, the algorithm is implemented to detec and localize damage in a real, 1 1/3 scale, reinforced concrete structure. A set of pre-damage and post damage modal parameters are used for I he damage detection exercise. The results of the damage prediction show that the proposed algorithm can correctly locate the damage inflicted in the test structure.

• BMB Reports
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• v.43 no.12
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• pp.836-841
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• 2010

In the era of personal genomics, predicting the individual response to drug-treatment is a challenge of biomedical research. The aim of this study was to validate whether interaction information between genetic and transcriptional signatures are promising features to predict a drug response. Because drug resistance/susceptibilities result from the complex associations of genetic and transcriptional activities, we predicted the inter-relationships between genetic and transcriptional signatures. With this concept, captured genetic polymorphisms and transcriptional profiles were prepared in cancer samples. By splitting ninety-nine samples into a trial set (n = 30) and a test set (n = 69), the outperformance of relationship-focused model (0.84 of area under the curve in trial set, P = $2.90{\times}10^{-4}$) was presented in the trial set and validated in the test set, respectively. The prediction results of modeling show that considering the relationships between genetic and transcriptional features is an effective approach to determine outcome predictions of drug-treatment.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.1
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• pp.49-57
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• 2010

Several pyrotechnic devices are employed over the course of satellite's missions, generally for the separation of structural subsystems and deployment of appendages. Firing of pyrotechnic devices results in impulsive loads characterized by high peak acceleration and high frequency content which can cause failures of various flight hardware elements and small components. Thus, accurate prediction of acceleration level in various components of spacecraft due to pyrotechnic devices is important. In this paper, two methods for pyroshock prediction, an empirical model and statistical energy analysis in conjunction with virtual mode synthesis, are applied to predict shock response of a low altitude earth observation satellite during launch vehicle separation. The predicted results are then evaluated through comparison with the shock test results.