• Transactions of Materials Processing
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• v.7 no.6
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• pp.545-553
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• 1998

The purpose of this paper is to develop a CAD/CAM system for generation of designing and manufacturing information such as total drawing sub-assembly drawing, part drawing detail drawing part list and NC data for machining by CNC lathe were CUT machining center. Through this study the CAD/CAM system for deep drawing transfer die in mechanical press process has been developed The developed CAD system can generate the drawings of transfer die in mechanical press. Using these results from CAD system. it can generate NC data to machine die's elements on the CAD system. This system can reduce design man-hours and human errors. In order to construct the system it is used to automate the design process using knowledge base system. The developed system is based on the knowledge base system which is involved a lot of expert's empirical knowhow in the practice field. Using AutoLISp language under the Auto CAD system. CTK customer language of SmartCAM is used as the overall CAD/CAM environment. Results of this system will be provide effective aids to the designer and manufacturer in this field

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1998.06a
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• pp.57-64
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• 1998

The purpose of this research is to develop a CAD/CAM system for generation all kind of information such as, total drawing, sub assembly drawing, part drawing, detail drawing, part list, and NC data for machining by CNC lathe, Wire CUT, machining center. Through this study the CAD/CAM System for deep drawing transfer die in mechanical press process has been developed. The developed CAD system can generate the drawing of transfer die in mechanical press. Using these results from CAD system, it can generate the NC data to machine die's elements on the CAD system. This system can reduce design man-hours and human errors. In order to construct the system, it is used to automate the design process using knowledge base system. The developed system is based on the knowledge base system which is involved a lot of expert's technology in the practice field. Using AutoLISP language under the AutoCAD system, CTK customer language of SmartCAM is used as the overall CAD/CAM environment. Results of this system will be provide effective aids to the designer and manufacturer in this field.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.46.2-46.2
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• 2019

We propose a deep learning model that can generate a waveform of coalescing binary black holes in merging and ring-down phases in less than one second with a graphics processing unit (GPU) as an approximant of gravitational waveforms. Up to date, numerical relativity has been accepted as the most adequate tool for the accurate prediction of merger phase of waveform, but it is known that it typically requires huge amount of computational costs. We present our method can generate the waveform with ~98% matching to that of the status-of-the-art waveform approximant, effective-one-body model calibrated to numerical relativity simulation and the time for the generation of ~1500 waveforms takes O(1) seconds. The validity of our model is also tested through the recovery of signal-to-noise ratio and the recovery of waveform parameters by injecting the generated waveforms into a public open noise data produced by LIGO. Our model is readily extendable to incorporate additional physics such as higher harmonics modes of the ring-down phase and eccentric encounters, since it only requires sufficient number of training data from numerical relativity simulations.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.307-315
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• 2021

The study aims to investigate the relationship between innovation activities and business process performance in higher education institution (hereinafter referred to as "HEI") context. The data was collected using a survey and later analyzed through Partial Least Squares Structural Equation Modelling (PLSSEM) and SmartPLS software. A total of 50 questionnaires were submitted from respondents representing vocational study program management located in Makassar, Indonesia. The findings show that two hypotheses discussed in this study fit the empirical data. Specifically, the results show that there is a positive relationship between innovation activities and business process performance, involving two types of innovation activities, which are exploration activities and exploitation activities, within HEIs. Explorative activity is firmly related to exploitative activity, which furthermore links to business process performance within the HEIs observed. The results confirm that exploration activity can stimulate and lead the HEIs management to generate exploitation activity. For instance, capabilities to absorb knowledge from the external institution may lead this institution to generate advanced academic processes, as well as more efficient and effective managerial processes. The study also signifies ambidexterity capacity, suggesting that it may lead HEIs management to formulate proper strategies in achieving better performance and gaining competitive advantage.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4607-4616
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• 2023

We implement machine learning regression models to predict peak pressures of primary and secondary systems, a major safety concern in Loss Of Condenser Vacuum (LOCV) accident. We selected the Multi-dimensional Analysis of Reactor Safety-KINS standard (MARS-KS) code to analyze the LOCV accident, and the reference plant is the Korean Optimized Power Reactor 1000MWe (OPR1000). eXtreme Gradient Boosting (XGBoost) is selected as a machine learning tool. The MARS-KS code is used to generate LOCV accident data and the data is applied to train the machine learning model. Hyperparameter optimization is performed using a simulated annealing. The randomly generated combination of initial conditions within the operating range is put into the input of the XGBoost model to predict the peak pressure. These initial conditions that cause peak pressure with MARS-KS generate the results. After such a process, the error between the predicted value and the code output is calculated. Uncertainty about the machine learning model is also calculated to verify the model accuracy. The machine learning model presented in this paper successfully identifies a combination of initial conditions that produce a more conservative peak pressure than the values calculated with existing methodologies.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1383-1386
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• 2003

In this paper, an ALU for Simultaneous Multi-Threading (SMT) microprocessors is designed. The SMT architecture improves notably performance and utilization of processes compared with conventional superscalar architectures by executing instructions from multiple threads at the same time. This ALU adopts data bypassing method to process multi-threads. And it can flush instructions in the same thread that generate exceptions such as branch misprediction. interrupt etc, performance of SMT microprocessors with data bypassing and exception handler can be improved.

• 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 Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.3.2-3
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• 2003

We propose a method of surface extension method using several functions. Interpolation theory is well developed in curve and surface. But extrapolation theory is not well developed because it is not unique outside the useful domain. It requires continuous, first derivative, second derivative continuous extension for matching in NC(Numerical Control) machine. In the past, we generate data outside the useful area and refit those data using least squares method. this has some problems which have some errors within the useful area. We keep the useful area and extend the unuseful area by a function

• Journal of applied mathematics & informatics
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• v.2 no.1
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• pp.25-32
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• 1995

Due to the complexity of many of the existing statistical problems found in working with envirommental copmuter simulations (Monte Carlo)have proved to be very informative. However, due to the various types of environmental data(thus the different type of distributions) one can no longer perform simulations based solely upon normal data. So in anticipating this problem, this paper outlines the computer software to generate variates from the various specified dis-tributions.

• The Korean Journal of Applied Statistics
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• v.22 no.5
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• pp.1097-1102
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• 2009

Classification of subjects with unknown distribution in small sample size setup may involve order-restricted constraints in multivariate parameter setups. Those problems makes optimality of conventional likelihood ratio based statistical inferences not feasible. Fortunately, Roy (1953) introduced union-intersection principle(UIP) which provides an alternative avenue. Redescending M-estimator along with that principle yields a considerably appropriate robust testing procedure. Furthermore, conditionally distribution-free test based upon exact permutation theory is used to generate p-values, even in small sample. Applications of this method are illustrated in simulated data and read data example (Lobenhofer et al., 2002)