• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.420-426
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• 2022

Developing a machine learning model and putting it into production goes through a number of steps. Automated Machine Learning(AutoML) appeared to increase productivity and efficiency by automating inefficient tasks that occur while repeating this process whenever machine learning is applied. The high degree of automation of AutoML models allows non-experts to use machine learning models and techniques without the need to become machine learning experts. Automating the process of applying machine learning end-to-end with AutoML models has the added benefit of creating simpler solutions, generating these solutions faster, and often generating models that outperform hand-designed models. In this paper, the AutoML data is collected and AutoML's Color Petri net model is created and analyzed based on it.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.209-218
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• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

• International Journal of Reliability and Applications
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• v.12 no.2
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• pp.95-102
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• 2011

This paper uses the auto regression model to modeling failure number of a bus fleet. The fitted model can be used to predict the failure number in the future. A numerical example is presented to illustrate the modeling process and the appropriateness of the fitted model. At last, some possible applications of the model are discussed.

• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.1-10
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• 1997

Finding the optimum route of ship's pipes is complicated and time-consuming process. Experience of designers is the main tool in this process. To reduce design man-hours and human errors a design expert system shell and a geometric modeler is used to automate the design process. In this paper, a framework of the intelligent CAD system for pipe auto-routing is suggested, which consists of general-purpose expert system shell and a geometric modeler. The design expert system and the geometric modeling kernel have been integrated. The CADDS5 of Computervision is used as the overall CAD environment. The Nexpert Object of Neuron Data is used as the expert system shell. The CADDS5 ISSM is used as the interface that creates and modifies geometric models of pipes. Existing algorithms for the routing problem have been analyzed. Most of them are to solve the 2-D circuit routing problems. Ship piping system, specially within the engine room, is a complicated, large scale 3-D routing problem. Methods of expert system have been used to find the route of ship pipes on the main deck.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1008-1011
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• 1996

Most control systems of power plants are using classical PID controllers for their process control. In order to get the desired control performances, the correct tuning of PID controllers is very important. Sometimes, it is necessary to retune PID controllers after the change of system operating condition and system design change, etc. Commercial auto-tuning controllers such as relay feedback controller can be used for this purpose. However, using these controllers to the safety-critical systems of nuclear power plants may be cause of unsafe operation, because they are using test signals for tuning. A new system identification auto-tuning method without using test signal has been developed in this paper. This method uses process input/output signals for system identification of unknown control process. From the model information of control process which was obtained from system identification approach, the optimal PID parameters can be calculated. The method can be used in the safety-critical systems because it is not using test signals during system modeling process.

• Progress in Medical Physics
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• v.20 no.4
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• pp.269-276
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• 2009

Radiation treatment techniques using photon beam such as three-dimensional conformal radiation therapy (3D-CRT) as well as intensity modulated radiotherapy treatment (IMRT) demand accurate dose calculation in order to increase target coverage and spare healthy tissue. Both jaw collimator and multi-leaf collimators (MLCs) for photon beams have been used to achieve such goals. In the Pinnacle3 treatment planning system (TPS), which we are using in our clinics, a set of model parameters like jaw collimator transmission factor (JTF) and MLC transmission factor (MLCTF) are determined from the measured data because it is using a model-based photon dose algorithm. However, model parameters obtained by this auto-modeling process can be different from those by direct measurement, which can have a dosimetric effect on the dose distribution. In this paper we estimated JTF and MLCTF obtained by the auto-modeling process in the Pinnacle3 TPS. At first, we obtained JTF and MLCTF by direct measurement, which were the ratio of the output at the reference depth under the closed jaw collimator (MLCs for MLCTF) to that at the same depth with the field size $10{\times}10\;cm^2$ in the water phantom. And then JTF and MLCTF were also obtained by auto-modeling process. And we evaluated the dose difference through phantom and patient study in the 3D-CRT plan. For direct measurement, JTF was 0.001966 for 6 MV and 0.002971 for 10 MV, and MLCTF was 0.01657 for 6 MV and 0.01925 for 10 MV. On the other hand, for auto-modeling process, JTF was 0.001983 for 6 MV and 0.010431 for 10 MV, and MLCTF was 0.00188 for 6 MV and 0.00453 for 10 MV. JTF and MLCTF by direct measurement were very different from those by auto-modeling process and even more reasonable considering each beam quality of 6 MV and 10 MV. These different parameters affect the dose in the low-dose region. Since the wrong estimation of JTF and MLCTF can lead some dosimetric error, comparison of direct measurement and auto-modeling of JTF and MLCTF would be helpful during the beam commissioning.

• Journal of Korean Society of Steel Construction
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• v.22 no.1
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• pp.99-108
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• 2010

This paper presents the results of a study that aimed to develop a module for auto connection modeling that can be applied to the structural details design and modeling phase. It was established that the steel connection library database from the structural analysis resulted from the consideration of the input parameters of the 3D modeling program and the guidelines for Korean standard steel connections. The module for the auto connection modeling in steel structures was developed by linking it with the established library database through the use of the OpenAPI software to prove that the developed module carried out the modeling of the six story (steel structure) office building. The productivity and efficiency of the module introduction was verified by comparing the conventional process and the proposed process.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.174-177
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• 2001

The automated computer-aided drafting technique is attempted for drawing process pictures of axisymmetric solid forgings which are mainly used in automobile industry. For this study basic concepts to draw the shape of an element are described and applied to the 2-dimensional and 3-dimensional modeling of forged parts. 2-dimensional display of process pictures is developed by using AutoLISP language in AutoCAD software of a drafting technique and 3-dimensional view of process pictures is based on the UG/open API and UG/open GRIP languages of Unigraphics software. Testing the developed program to forging of bolts and ballstuds, it was shown to give good results to be applicable in forging industry.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.350-359
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• 2005

Finite element method is a very effective method to simulate the forming processes with good prediction of the deformation behaviour. For the finite element modeling of sheet mental forming the accurate die model is required. Among finite element method, the static-implicit finite element method is applied effectively to analyze real-size auto-body panel stamping processes, which include the forming stage. This study is about analyzing the stamping process problems by using AutoForm commercial software which used static-implicit method. According to this study, the results of simulation will give engineers good information to access the die design of optimization.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.5
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• pp.451-458
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• 2014

This study is a practical research for setting a process of making references of design decision and guidlines of limitation in the movement from the design development to the construction design by StrAuto. StrAuto, as a parametric modeling and optimization tool for building structure, enables a quantity of design cases to be analyzed automatically by changing parameters of sturctural properties. So the designer using StrAuto can check a lot of analysis data crossing thousands of cases, see which case is out of acceptable range, and make a decision for design and optimization. In this thesis, the application of StrAuto optimization process to the residence tower UIC project shows the practical applicability in the construction design and value engineering. StrAuto optimized ideally volume of core walls by 31.3% and lead the final revised model applied to the construction design to reduce volume by 18.1%. The significance of this research is the implementation of process that the designer can quickly review a number of cases and get a direction for construction design and optimization after design development.