• Computers and Concrete
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• v.1 no.1
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• pp.99-113
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• 2004

The article reports data on, and numerical modelling of, beams exhibiting points of inflection and subjected to sequential loading. Both tests and analysis point to inadequacies in current codes of practice. An alternative design methodology, which is strongly associated with the notion that contraflexure points should be designed as "internal supports", is shown to produce superior performance even though it requires significantly less secondary reinforcement than that advocated by codes.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.7
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• pp.869-875
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• 2016

The purpose of this study is to analyze the long-term wave characteristics and tendencies of coastal waters near Korea based on wave hind-casting modelling. Wave hind-casting modelling was performed with a wind data set from ECMWF (2001~2014), which provides data from 1979 to the present. The results of numerical modelling were verified with observed data collected using wave buoys installed by the Korea Meteorological Administration (KMA) and Korea Hydrographic and Oceanographic Agency (KHOA) in offshore waters. The results agreed well with observations from buoy stations, especially during event periods such as typhoons. The quantitative RMSE value was 0.5 m, which was significant. Consequently, the results of a wave tendency analysis for 14 years (2001~2014) showed an increased appearance ratio for waves of more than 2 m in height at all regional domains. The mean appearance ratio was 0.082 % per year, which implies that coastal waves have been increasing continuously. This coastal wave tendency analysis data can be used to evaluate coastal vulnerability due to recent climate change and the design of coastal erosion prevention structures.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1443-1448
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• 2003

Model Predictive Control (MPC) has recently found wide acceptance in industrial applications, but its potential has been much impounded by linear models due to the lack of a similarly accepted nonlinear modelling or data based technique. The authors have recently developed a new method for obtaining Volterra kernels of up to third order by use of pseudorandom M-sequence. By use of this method, nonparametric NMPC is derived in discrete-time using multi-dimensional convolution between plant data and Volterra kernel measurements. This approach is applied to an industrial polymerisation process using Volterra kernels of up to the third order. Results show that the nonparametric approach is very efficient and effective and considerably outperforms existing methods, while retaining the original data-based spirit and characteristics of linear MPC.

• Asian Journal of Innovation and Policy
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• v.6 no.3
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• pp.262-273
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• 2017

Recently, the attention to the $4^{th}$ Industrial Revolution has been increasing. In the $4^{th}$ Industrial Revolution era, the boundaries between physical space, digital space, and biological space are becoming blurred because of the active convergence between various fields. There are many issues about the $4^{th}$ Industrial Revolution such as artificial intelligence, Internet of things, big data, and cyber physical system. To cope with the $4^{th}$ Industrial Revolution, an accurate analysis and technology planning need to be undertaken from a broad point of view. However, there is little research on the analysis of the major issues about the 4th Industrial Revolution. Accordingly, this study aims to analyse these major issues. Data mining such as topic modelling method is used for this analysis. This study is expected to be helpful for the researcher and policy maker of the 4th Industrial Revolution.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.163-165
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• 2009

Many photovoltaic (PV) systems are being developed and installed. For a PV developer, simulations are required before the experimental testing. However, most simulation tools do not offer data libraries for PV systems, so that some Institutes who try to use such software will be in difficulty. In this paper, simulations of performance and stability have been carried out using the software PSPICE. In this paper, the modelling of solar cell arrays, photovoltaic modules, PV generators, batteries and drive systems is carried out based on mathematical equivalence circuits and available data, and the models are converted into a data library for PSPICE that is user friendly. System variations can be modeled by simple parameter variation. To verify the accuracy of the simulation library, various models were run and compared to known systems.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.83-88
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• 2001

This paper presents modelling and analyzing method of centrifugal chiller which has a rated capacity of 200 RT(703 kW) through on-site performance test. Field data of chiller installed in the clean-room building of KIST have been collected, Simple models were developed for predicting the heat exchangers and system performances by regression of chiller operation data during 5 days in August. The models proposed here account for the effect of variations of cooling capacity, temperatures and flow rates of secondary fluids. The models are consistent with real performance data from June to September within ${\pm}5%$ error. The COP of centrifugal chiller are estimated under the standard rating conditions and reduced mass flow rate of chilled and cooling water.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.3
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• pp.65-71
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• 1997

With the emergence of neural network, there is a revived interest in identification of nonlinear systems. So in this paper, to identify unknown nonlinear systems dynamically we propose DPNN(Dynamic Polynomial Neural Network) using GMDH (Group Method of Data Handling) algorithm. The dynamic system identification using GMDH consists of applying a set of inputloutput data to train the network by dynamically computing the necessary coeffici1:nt sets. Then, MRAC(Mode1 Reference Adaptive Control) is designed to control nonlinear systems using DPNN. In the result, we can see that the modelling and control using DPNN work well by computer simulation.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.1
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• pp.52-61
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• 1993

Developed in this research is a CAM system for 5-axis NC Machining of sculptured surfaces. We identify problems in generating 5-axis NC data and propose methods of overcoming them. Issues discussed in this paper are: kinematic modelling of NC machines; determination of cutter position (location and orientation); check of machine work-range; linear trajectory plann- ing ; calculation of feedrate number. The proposed system has been implemented in FORTRAN77 on the Personal IRIS EWS, and it also constitutes a module of the CAD/CAM system 'CASSET' developed in KIST CAD/CAM lab.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.407-414
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• 2000

Carroll and Ruppert(1988) analyzed the esterase assay data with regression model based on quasi-likelihood. Jung and Lee(1997) introduced a goodness-of-fit test for testing the adequacy of the quasi-likelihood and claimed that there is no gross inadequacy with the model because their test was not rejected. However, Lee and Xelder(199S)'s residual plots revealed that the model did not sufficiently reflect the increase of the variance with that of the mean. In this paper, we re-analyze the esterase assay data with the joint modelling of mean and dispersion in Lee and l\elder(1998) and evaluate the validity of the fitted model by applying the residual plots. And it is illustrated that Lee and Nelder(199S)'s restricted likelihood is more efficient in goodness-of-fit test for the dispersion model.

• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.313-322
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• 2011

To enhance employment rate of students, every college provides various methods, such as consulting, information provision, course and mock interview. Students also are trying to get high GPA scores, to achieve certificates and to enhance english ability for getting jobs. We analyzed the relations self-confidence in getting jobs, college supports, students preparation for getting jobs and job-seeking stress via structural equation modelling. We found that college supports increase students preparation for getting jobs and job-seeking stress lessens self-confidence in getting jobs.