• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.91-99
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• 2006

The incremental parsing technique plays an important role in language-based environment which allows the incremental construction of a program. It improves the performance of a system by reanalyzing only the changed part of a program. The conventional incremental parsing uses the stack data structure in order to store the parsing information. In this paper, we suggest a threaded tree construction algorithm which parse by adding the threaded node address instead of using a stack data structure. We also suggest an incremental threaded tree construction which has incremental parsing process of five steps using the constructed threaded tree.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.9-17
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• 1994

The incremental parsing techniques are essential part of language-based environment which allow incremental construction of programs, as reparsing of modified part of the program alone enhances the system performance. A number of methods and algorithms have been proposed for incremental parsing and for the construction of incremental parsers. The purpose of this paper is to review the earlier incremental parsing algorithms which are too expensive in both time and space, and to present an efficient incremental LR parsing algorithm which is more efficient than the previous ones. In this paper, we generate automatically an extended LR parsing tables which allow the nonterminal symbols as well as terminal symbols for the input, and apply them to our efficient incremental LR parsing algorithm. Using these extended LR parsing tables. we suggest several methods to reduce its memory spaces and parsing steps as well. The algorithms described here were implemented in C language and YACC on a SUN UNIX OS, and were tested with several grammars and strings.

• Journal of Internet Computing and Services
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• v.5 no.5
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• pp.119-127
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• 2004

As, the development of language-based programming environment, a study on incremental parsing has become an essential part. The purpose of this paper is to show the more efficient incremental parsing algorithm than earlier one that demands parsing speed and memorizing space too much. This paper suggests the threaded tree construction algorithm not using stack. In addition, to remove the reparsing process, it proposes the algorithm for creation node and construction incremental threaded tree not using stack.

• Korean Journal of Computational Design and Engineering
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• v.10 no.3
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• pp.168-178
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• 2005

The Delaunay triangular net is primarily characterized by a balance of the whole by improving divided triangular patches into a regular triangle, which closely resembles an equiangular triangle. A triangular net occurring in certain, point-clustered, data is unique and can always create the same triangular net. Due to such unique characteristics, Delaunay triangulation is used in various fields., such as shape reconstruction, solid modeling and volume rendering. There are many algorithms available for Delaunay triangulation but, efficient sequential algorithms are rare. When these grids involve a set of points whose distribution are not well proportioned, the execution speed becomes slower than in a well-proportioned grid. In order to make up for this weakness, the ids are divided into sub-grids when the sets are integrated inside the grid. A method for finding a mate in an incremental construction algorithm is to first search the area with a higher possibility of forming a regular triangular net, while the existing method is to find a set of points inside the grid that includes the circumscribed sphere, increasing the radius of the circumscribed sphere to a certain extent. Therefore, due to its more efficient searching performance, it takes a shorer time to form a triangular net than general incremental algorithms.

• Korean Journal of Computational Design and Engineering
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• v.12 no.6
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• pp.413-421
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• 2007

3D rendering is becoming a common feature of mobile application programs with the rapid advance of mobile devices. Since the existing rendering engines do not provide triangulation functions, mobile 3D programs have focused on an efficient handling with pre-tessellated geometry. In addition, triangulation is comparatively expensive in computation, so it seems that the triangulation cannot be easily implemented on mobile devices with limited resources. Triangulation of 3D geometry is the essential process of visualization of 3D model data and many different triangulation methods have been reported. We developed a light and fast visualization process that involves constrained triangulation based on Voronoi diagram and applied it to a mobile computer application. In this paper, we applied kd-tree to the original incremental construction algorithm and produced new O(nlogn) incremental construction algorithm. And we show a simple and efficient constrained triangulation method based on Voronoi diagram. This paper also describes an implementation of mobile STEP data viewer as an application of our proposed algorithms.

• Korean Journal of Computational Design and Engineering
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• v.7 no.4
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• pp.248-253
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• 2002

Delaunay triangulation is well balanced in the sense that the triangles tend toward equiangularity. And so, Delaunay triangulation hasn't some slivers triangle. It's commonly used in various field of CAD applications, such as reverse engineering, shape reconstruction, solid modeling and volume rendering. For Example, In this paper, an improved Delaunay triangulation is proposed in 2-dimensions. The suggested algorithm subdivides a uniform grids into sub-quad grids, and so efficient where points are nonuniform distribution. To get the mate from quad-subdivision algorithm, the area where triangulation-patch will be most likely created should be searched first.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.429-438
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• 1996

An incremental learning algorithm is presented that constructs a multilayer perceptron whose size is optimal for solving a given problem. Unlike conventional algorithms in which a fixed size training set is processed repeat-edly, the method uses an increasing number of critical examples to find a necessary and sufficient number of hidden units for learning the entire data. Experimental results in hand- writtern digit recognition shows that the network size optimization combined with incremental pattern selection generalizes significantly better and converges faster than conventional methods.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.151-156
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• 2000

Delaunay triangulation is well balanced in the sense that the triangles tend toward equiangularity. And so, Delaunay triangulation hasn't some slivers triangle. It's commonly used in various field of CAD applications, such as shape reconstruction, solid modeling and volume rendering. In this paper, an improved Delaunay triangulation is proposed in 2-dimensions. The suggested algorithm subdivides a uniform grids into sub-quad grids, and so efficient where points are non-uniform distribution. To get the mate from quad-subdivision algorithm, the area where triangulation-patch will be most likely created should be searched first.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.487-498
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• 2005

Recently, It has focused on decision tree algorithm that can handle large dataset. However, because most of these algorithms for large datasets process data in a batch mode, if new data is added, they have to rebuild the tree from scratch. h more efficient approach to reducing the cost problem of rebuilding is an approach that builds a tree incrementally. Representative algorithms for incremental tree construction methods are BOAT and ITI and most of these algorithms use a local discretization method to handle the numeric data type. However, because a discretization requires sorted numeric data in situation of processing large data sets, a global discretization method that sorts all data only once is more suitable than a local discretization method that sorts in every node. This paper proposes an incremental tree construction method that efficiently rebuilds a tree using a global discretization method to handle the numeric data type. When new data is added, new categories influenced by the data should be recreated, and then the tree structure should be changed in accordance with category changes. This paper proposes a method that extracts sample points and performs discretiration from these sample points to recreate categories efficiently and uses confidence intervals and a tree restructuring method to adjust tree structure to category changes. In this study, an experiment using people database was made to compare the proposed method with the existing one that uses a local discretization.

• Journal of the Korea Society of Computer and Information
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• v.3 no.1
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• pp.95-112
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• 1998

The Error Backpropagation algorithm is widely used in various areas such as associative memory, speech recognition, pattern recognition, robotics and so on. However, if and when a new leaning pattern has to be added in order to drill, it will have to accomplish a new learning with all previous learning pattern and added pattern from the very beginning. Somehow, it brings about a result which is that the more it increases the number of pattern, the longer it geometrically progress the time required by leaning. Therefore, a so-called Incremental Learning Method has to be solved the point at issue all by means in case of situation which is periodically and additionally learned by numerous data. In this study, not only the existing neural network construction is still remained, but it also suggests a method which means executing through added leaning by a model pattern. Eventually, for a efficiency of suggested technique, both Monk's data and Iris data are applied to make use of benchmark on machine learning field.