• Transactions of Materials Processing
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• v.12 no.4
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• pp.302-307
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• 2003

Hot rolled strip is cooled by air and water in Run-Out-Table. In this process, phase transformation and shape deformation occurs due to temperature drop. Because of un-ideal cooling condition of ROT, irregular shape deformation and phase transformation arise in the strip. which affect the strip property and lead to the residual stress of strip. And these exert effects on the following processes, coiling process, coil cooling process, and re-coiling process. Through these processes, the residual stress becomes higher and severe. For the prediction of residual stress distribution and shape deformation of final product, Finite element(FE) based model was used. It consists of non-steady state heat transfer analysis, elasto-plastic analysis. thermodynamic analysis and phase transformation kinetics. Successive FEM simulation were applied from ROT process to coil cooling process. In each process simulation, previous process simulation results were used for the next process simulation. The simulation results were matched well with the experimental results.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.1
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• pp.109-116
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• 2001

The detection of corporate failures is a subject that has been particularly amenable to cross-sectional financial ratio analysis. In most of firms, however, the financial data are available over past years. Because of this, a model utilizing these longitudinal data could provide useful information on the prediction of bankruptcy. To correctly reflect the longitudinal and firm-specific data, the generalized linear model with assuming the first order AR(autoregressive) process is proposed. The method is motivated by the clinical research that several characteristics are measured repeatedly from individual over the time. The model is compared with several other predictive models to evaluate the performance. By using the financial data from manufacturing corporations in the Korea Stock Exchange (KSE) list, we will discuss some experiences learned from the procedure of sampling scheme, variable transformation, imputation, variable selection, and model evaluation. Finally, implications of the model with repeated measurement and future direction of research will be discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.11
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• pp.1174-1179
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• 2008

Many modeling and calibration methods have been developed to analyze and design the biological wastewater treatment process. For the systematic use of activated sludge model (ASM) in a real treatment process, a most important step in this usage is a calibration which can find a key parameter set of ASM, which depends on the microorganism communities and the process conditions of the plants. In this paper, a standardized calibration protocol of the ASM model is developed. First, a weighted effluent quality index(WEQI) is suggested far a calibration protocol. Second, the most sensitive parameter set is determined by a sensitive analysis based on WEQI and then a parameter optimization method are used for a systematic calibration of key parameters. The proposed method is applied to a calibration problems of the single carbon removal process. The results of the sensitivity analysis and parameter estimation based on a WEQI shows a quite reasonable parameter set and precisely estimated parameters, which can improve the quality and the efficiency of the modeling and the prediction of ASM model. Moreover, it can be used for a calibration scheme of other biological processes, such as sequence batch reactor, anaerobic digestion process with a dedicated methodology.

• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.233-247
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• 2008

Process monitoring technology is able to detect the faults and the process changes which occur in a process unpredictably, which makes it possible to find the reasons of the faults and get rid of them, resulting in a stable process operation, high-quality product. Statistical process monitoring method based on data set has a main merit to be a tool which can easily supervise a process with the statistics and can be used in the analysis of process data if a high quality of data is given. Because a real process has the inherent characteristics of nonlinearity, non-Gaussianity, multiple operation modes, sensor faults and process changes, however, the conventional multivariate statistical process monitoring method results in inefficient results, the degradation of the supervision performances, or often unreliable monitoring results. Because the conventional methods are not easy to properly supervise the process due to their disadvantages, several advanced monitoring methods are developed recently. This review introduces the theories and application results of several remarkable monitoring methods, which are a nonlinear monitoring with kernel principle component analysis (KPCA), an adaptive model for process change, a mixture model for multiple operation modes and a sensor fault detection and reconstruction, in order to tackle the weak points of the conventional methods.

• The Journal of Bigdata
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• v.1 no.2
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• pp.1-8
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• 2016

User activity log includes lots of hidden information, however it is not structured and too massive to process data, so there are lots of parts uncovered yet. Especially, it includes time series data. We can reveal lots of parts using it. But we cannot use log data directly to analyze users' behaviors. In order to analyze user activity model, it needs transformation process through extra framework. Due to these things, we need to figure out user activity model analysis framework first and access to data. In this paper, we suggest a novel framework model in order to analyze user activity model effectively. This model includes MapReduce process for analyzing massive data quickly in the distributed environment and data architecture design for analyzing user activity model. Also we explained data model in detail based on real online service log design. Through this process, we describe which analysis model is fit for specific data model. It raises understanding of processing massive log and designing analysis model.

• Journal of Korean society of Dental Hygiene
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• v.11 no.5
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• pp.749-758
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• 2011

Objectives : The purpose of this study was to analyse case reports performed through a dental hygiene process and provide basic data on clinical education of dental hygiene. Methods : 154 case reports which collected for six years were analysed. This study applied dental hygiene process model in dental hygiene diagnosis. Dental hygiene diagnosis was more cleared by dental a hygiene process model. Data analysis was performed by the Frequency statistics using SPSS 12.0 for Windows. Results : 1. The clients are mainly comprised 20's university student(91.9%). 2. In assessment phase, clients finished 100% test of subjective data. 3. When applied a dental hygiene process model in dental hygiene diagnosis, students have identified 23 type of dental hygiene problem and analysed dental hygiene problem frequently used as bleeding of gingiva, calculus and deposit of dental plaque. 4. In case of plan of dental hygiene intervention, Fluoride application showed the most high level(98.1%) in clinical intervention. 5. Results of intervention showed that performance rate(98.7%) of scaling is the most high level. Conclusions : Dental hygiene process model is more useful than other diagnostic models in clinical practice based on dental hygiene process.

• Proceedings of the Safety Management and Science Conference
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• 2012.04a
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• pp.547-559
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• 2012

This thesis introduced a model of diagnosing a company's quality management, and a process of achieving quality innovation based on the model. As for study methods, books and theses related to quality and process innovation were collected for investigation, a survey on internal employees to investigate major issues of quality and standard consciousness was conducted, and 5DP was discussed for balanced process analysis.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.2
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• pp.124-129
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• 2011

The thick plate produced by rolling process is used as the basic members of a ship structure. In this paper, we present a setup model to control the asymmetric factors causing plate bending in the upper or lower direction during rolling. A series of finite element analysis are conducted to predict the relationship between various asymmetric factors and plate bending. The setup model is developed by regressing the relationship to the linear equations with several non-dimensional parameters. The setup model is verified by a pilot rolling test and applied to actual rolling conditions. Results show that the model is substantial to predict the asymmetric deformation in the plate rolling process.

• Progress in Superconductivity and Cryogenics
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• v.21 no.3
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• pp.6-12
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• 2019

Extended Drude model has been used to obtain information of correlations from measured optical spectra of strongly correlated electron systems. The optical self-energy can be defined by the extended Drude model formalism. One can extract the optical self-energy and the electron-boson spectral density function from measured reflectance spectra using a well-developed usual process, which is consistent with several steps including the extended Drude model and generalized Allen's formulas. Here we used a reverse process of the usual process to investigate the extended Drude analysis when an additional low-energy interband transition is included. We considered two typical electron-boson spectral density model functions for two different (normal and d-wave superconducting) material states. Our results show that the low-energy interband transition might give significant effects on the electron-boson spectral density function obtained using the usual process. However, we expect that the low-energy interband transition can be removed from measured spectra in a proper way if the transition is well-defined or well-known.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.1165-1170
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• 2005

This paper describes an information model, devised to manage roadway design information and to improve the collaboration among the multidisciplinary design teams. An analysis concerning the workflow, the rules and the functions of current roadway design was conducted. A process model based on the result of the analysis was developed by utilizing IDEF0 methodology. The process model reflects the interdependencies among multidisciplinary design disciplines and is capable of managing communication processes. This paper also discusses the design information hierarchy and the component representation schemes for systematic design information management. It is anticipated that the proposed information model would be able to improve the overall process of design of roadway construction projects by managing design information and helping the participants communicate and share information of the project effectively.