• Water for future
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• v.12 no.2
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• pp.63-69
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• 1979

The sequences of monthly streamflows constitute a non-statonary time series. The purely stochastic model has been applied to data generation of non-stationary time series. Tow different mothods--single site and multisite generation--have been used on the hydrologic time series. In this study the synthetic generation method by bivariate analysis, studied by Thomas Fiering, one of multi-site models, has been applied to the historical data on monthly streamflows at two sites in Nakdong River, and also for validity of this model the single site Thomas Fiering model applied. Through statistical analysis it has been shown that the performance of bivariate Thomas Fiering model was better than that of the other. By comparison of mean and standard deviaion between the historical and the generated, and cross correlogram interpretation, it has been known that the model used herein has good performance to simultaneously generate the monthly streamflows at two sites in a river hasin.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2862-2878
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• 2020

Data Security is the most challenging area in Internet communication, where most of the secret sharing schemes are proposed for binary images. But still it lacks in providing security for data communication, especially in image transmission. Traditional visual cryptography scheme generate meaningless diwies and the reconstruction phase leads to quality degradation over the secret image. In this work, an intelligent two dimensional secret share construction scheme is proposed. A secret image is expanded into n diwies with the choice of scheme selection. By Stacking all the qualified diwies to revert the secret image without content loss and less than s^* - 1 shares could not reveal any information about the secret image. The experimental results emphasize that the proposed secret share scheme is highly secured for image transmission.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.5
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• pp.74-84
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• 1994

This paper discusses a method to generate the tool path for NC machining of automobile panel dies. The source data representing a panel die may be generated from digitizing machines, other CAD/CAM systems via IGES files, of compound surface models. From the source data, three types of interferencefree tool paths are generated automatically ; a parallel (Cartesian), an isometric, and a pencil cutting tool path. For the interference-free tool path, a polyhedral model composed of several triangles, and an 'offset triangle' approach are exploited. Finally, some practical examples are illustrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.309-330
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• 2009

In this paper, we introduce the architecture of Genetic Algorithm(GA) based Feed-forward Polynomial Neural Networks(PNNs) and discuss a comprehensive design methodology. A conventional PNN consists of Polynomial Neurons, or nodes, located in several layers through a network growth process. In order to generate structurally optimized PNNs, a GA-based design procedure for each layer of the PNN leads to the selection of preferred nodes(PNs) with optimal parameters available within the PNN. To evaluate the performance of the GA-based PNN, experiments are done on a model by applying Medical Imaging System(MIS) data to a multi-variable software process. A comparative analysis shows that the proposed GA-based PNN is modeled with higher accuracy and more superb predictive capability than previously presented intelligent models.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.253-256
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• 1996

Rainfall is one of the major and complicated elements of hydrologic system. Accurate prediction of rainfall is very important to mitigate storm damage. The neural network is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. In this dissertation, rainfall predictions by the neural network theory were presented. A multi-layer neural network was constructed. The network learned continuous-valued input and output data. The network was used to predict rainfall. The online, multivariate, short term rainfall prediction is possible by means of the developed model. A multidimensional rainfall generation model is applied to Seoul metropolitan area in order to generate the 10-minute rainfall. Application of neural network to the generated rainfall shows good prediction. Also application of neural network to 1-hour real data in Seoul metropolitan area shows slightly good predictions.

• Korean Journal of Computational Design and Engineering
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• v.12 no.4
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• pp.283-297
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• 2007

Seamless data integration in the CAx chain of the CAD/CAPP/CAM/CNC has been achieved to a high degree, but research concerning the transfer of data from conceptual sketches to a CAD system should be carried out further. This paper presents a method for reconstructing a 3D model from a freehand sketch. Sketch-based modeling research can be classified into gestural modeling methods and reconstructional modeling methods. This research involves the reconstructional modeling method. Here, Mitani's seminal work, designed for box-shaped 3D model using a predefined template, is improved by leveraging a relational template and specialized for automotive design. Matching between edge graphs of the relational template and the sketch is formulated and solved as the assignment problem using the feature vectors of the edges. Including the stroke preprocessing method required to generate an edge graph from a sketch, necessary procedures and relevant techniques for implementing the template-based modeling method are described. Examples from a working implementation are given.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.153-159
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• 1999

A material handling crane is composed of many complex structural components which require sufficient strength, stiffness and stability throughout its service life and need to be light in weight, and satisfy the required functions under the entire range of operating conditions. In this study, the analysis system for material handling cranes is presented. This program integrate various structural analyses modules with the GU(Graphic User Interface) concept. Utilizing basic variables as input data, the analysis system performs quasi-static, eigenvalue, buckling, fatigue and stability analysis. Using this program, the designer can generate optimal design data for the cranes without my actual measurements. This system will also be extended to other mechanical structures with kinematic motion like crane.

• Korean Management Science Review
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• v.23 no.1
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• pp.63-74
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• 2006

Decision tree induction algorithm is one of the most widely used methods in classification problems. However, they could be trapped into a local minimum and have no reasonable means to escape from it if tree algorithm uses top-down search algorithm. Further, if irrelevant or redundant features are included in the data set, tree algorithms produces trees that are less accurate than those from the data set with only relevant features. We propose a hybrid algorithm to generate decision tree that uses genetic programming with sequentially selected features. Correlation-based Feature Selection (CFS) method is adopted to find relevant features which are fed to genetic programming sequentially to find optimal trees at each iteration. The new proposed algorithm produce simpler and more understandable decision trees as compared with other decision trees and it is also effective in producing similar or better trees with relatively smaller set of features in the view of cross-validation accuracy.

• Geophysics and Geophysical Exploration
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• v.5 no.1
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• pp.1-5
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• 2002

We developed a modeling and visualization software that can analyze 3-dimensional spatial information in the ArcView environment. The software constructs and visualizes an object in 3 dimensional space from the input data given a number of horizontal cross-sections. The software can generate and visualize the cross-sections of the object in any azimuth and inclination. Utilizing the program users can modify the 3-D shape of the object by interactively editing the cross-sections.

• International Journal of CAD/CAM
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• v.8 no.1
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• pp.37-40
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• 2009

Based on the study of Digital Elevation Simplification Model and fractal theory, this paper put forward a new method to simulate complex terrain. That use simplified DEM data to construct terrain frame based on the quad tree at first, and then use fractal to generate the details of every node of the tree. In the process of construction, the LOD theory is used to simplify the terrain and get its typical data. According to the change of view position and direction, the paper gives a new way to judge the visibility of the surface patch. Experimental results show that this algorithm is simple, efficient and supports the real time dynamic simulation of terrain model.