• MALSORI
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• no.50
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• pp.123-137
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• 2004

In this paper, we consider the implementation of connected digit recognition system using tree structured lexicon model. To implement efficiently the fixed or variable length digit recognition system, finite state network (FSN) is required. We merge the word network algorithm that implements the FSN with lexical tree search algorithm that is used for general speech recognition system for fast search and large vocabulary systems. To find the efficient modeling of digit recognition system, we investigate some performance changes when the lexical tree search is applied.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.6 s.261
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• pp.651-658
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• 2007

A new tree-structured neural network classifier is proposed for the automatic real-time inspection of cold-rolled steel strip surface defects. The defects are classified into 3 groups such as area type, disk type, area & line type in the first stage of the tree-structured neural network. The defects are classified in more detail into 11 major defect types which are considered as serious defects in the second stage of neural network. The tree-structured neural network classifier consists of 4 different neural networks and optimum features are selected for each neural network classifier by using SFFS algorithm and correlation test. The developed classifier demonstrates very plausible result which is compatible with commercial products having high world-wide market shares.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.184-187
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• 2002

Two-dimensional (2-D) X-ray computerized tomography (CT) equipments are widely used in industrial and medical fields, and nowadays studies on reconstruction algorithm for 3-D cone-beam acquisition systems are active for better utilization. The authors recent-By have proposed a fast reconstruction aigorithm using tree-structured filter bank for 2-D C1, and shown the algorithm is applicable to an approximate reconstruction of 3-D CT. For exact 3-D CT reconstruction, however, we have to backproject 1-D signal into 3-D space. This paper proposes a fast implementation method for this back-projection by use of tree-structured filter bank. and shows the proposed method works approximately 700 times faster than the direct one with almost same reconstruction image quality.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.2
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• pp.1-14
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• 2019

Since most documents used in web, XML, office applications are tree-structured, diff, merge, and version control for tree-structured documents in multi-user environments are crucial tasks. However research on edit scripts which is a basis for them is in primitive stage. In this paper, we present a document model for understanding the change of tree-structured documents as edit scripts are executed, and propose a method of switching adjacent edit operations on tree-structured documents based on the analysis of the effects of edit operations. Mostly, edit scripts which are produced as the results of diff on tree-structured documents only consist of basic operations such as update, insert, delete. However, when move and copy are included in edit scripts, because of the characteristics of their complex operation, it is often that edit scripts are generated to execute in two passes. In this paper, using the proposed method of switching edit operations, we present an algorithm of transforming the edit scripts of X-treeESgen, which are designed to execute in two passes, into the ones that can be executed in one pass.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.677-687
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• 2022

We propose a detection algorithm based on tree-structured convolutional neural networks (TsCNNs) that finds pornography, propaganda, or other inappropriate content on a social media network. The algorithm sequentially applies the typical convolutional neural network (CNN) algorithm in a tree-like structure to minimize classification errors in similar classes, and thus improves accuracy. We implemented the detection system and conducted experiments on a data set comprised of 6 ordinary classes and 11 inappropriate classes collected from the Korean military social network. Each model of the proposed algorithm was trained, and the performance was then evaluated according to the images and videos identified. Experimental results with 20,005 new images showed that the overall accuracy in image identification achieved a high-performance level of 99.51%, and the effectiveness of the algorithm reduced identification errors by the typical CNN algorithm by 64.87 %. By reducing false alarms in video identification from the domain, the TsCNNs achieved optimal performance of 98.11% when using 10 minutes frame-sampling intervals. This indicates that classification through proper sampling contributes to the reduction of computational burden and false alarms.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.465-472
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• 2007

With the recent proliferation of the use of semi-structured data such as XML, it becomes more important to efficiently store and manage the semi-structured data. The XML data can be logically modelled as a rooted tree e.g., the DOM tree. In order to process a query on the XML data, we traverse the tree structure. In this paper we present an algorithm that places the XML data to disk blocks. The proposed algorithm assigns a number to each node of the tree in a bottom-up fashion. Then, the nodes are allocated to disk blocks using the assigned number. The proposed algorithm does not need access pattern information, and provides good performance for any access pattern. The characteristics of the proposed method are presented with analysis. Through experiments, we evaluate the performance of the proposed method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.154-157
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• 1996

Conventional fuzzy systems have serious problems in dealing with the nonlinear approximations on high-dimensional spaces due to the explosive increase of the number of fuzzy IF-THEN rules. In order to avoid such problems, this paper proposes a tree-structured fuzzy system in which semi-local basis functions form its basic elements, and develops a training algorithm for the proposed system based on the evolution program and LMS rule. The experimental studies demonstrate the effectiveness of the developed methodology.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3117-3132
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• 2012

The tree topology in multicast systems has high transmission efficiency, low latency, but poor resilience to node failures. In our work, some nodes are selected as backbone nodes to construct a tree-like core overlay. Backbone nodes are reliable enough and have strong upload capacity as well, which is helpful to overcome the shortcomings of tree topology. The core overlay is organized into a spanning tree while the whole overlay is of mesh-like topology. This paper focuses on improving the performance of the application-layer multicast overlay by optimizing the core overlay which is periodically adjusted with the proposed optimization algorithm. Our approach is to construct the overlay tree based on the out-degree weighted reliability where the reliability of a node is weighted by its upload bandwidth (out-degree). There is no illegal solution during the evolution which ensures the evolution efficiency. Simulation results show that the proposed approach greatly enhances the reliability of the tree-like core overlay systems and achieves shorter delay simultaneously. Its reliability performance is better than the reliability-first algorithm and its delay is very close to that of the degree-first algorithm. The complexity of the proposed algorithm is acceptable for application. Therefore the proposed approach is efficient for the topology optimization of a real multicast overlay.

• Communications for Statistical Applications and Methods
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• v.19 no.2
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• pp.293-301
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• 2012

Quantile regression proposed by Koenker and Bassett (1978) is a statistical technique that estimates conditional quantiles. The advantage of using quantile regression is the robustness in response to large outliers compared to ordinary least squares(OLS) regression. A regression tree approach has been applied to OLS problems to fit flexible models. Loh (2002) proposed the GUIDE algorithm that has a negligible selection bias and relatively low computational cost. Quantile regression can be regarded as an analogue of OLS, therefore it can also be applied to GUIDE regression tree method. Chaudhuri and Loh (2002) proposed a nonparametric quantile regression method that blends key features of piecewise polynomial quantile regression and tree-structured regression based on adaptive recursive partitioning. Lee and Lee (2006) investigated wage determinants in the Korean labor market using the Korean Labor and Income Panel Study(KLIPS). Following Lee and Lee, we fit three kinds of quantile regression tree models to KLIPS data with respect to the quantiles, 0.05, 0.2, 0.5, 0.8, and 0.95. Among the three models, multiple linear piecewise quantile regression model forms the shortest tree structure, while the piecewise constant quantile regression model has a deeper tree structure with more terminal nodes in general. Age, gender, marriage status, and education seem to be the determinants of the wage level throughout the quantiles; in addition, education experience appears as the important determinant of the wage level in the highly paid group.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.3
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• pp.25-36
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• 1996

Conventional radial-basis-function networks and fuzzy systems have serious problems in dealing with the non1inea:r approximations on high-dimensional spaces due to the explosive increase of the number of hidden nodes or fuzzy IF-THEN rules. In order to avoid such problems, this paper proposes a tree-structured intelligent system in which semi-local basis functions form its basic elements, and develops a training algorithm for the proposed system based on the modified genetic algorithm and LMS rule. Theoretical analysis is performed on the approximation capability of the proposed system, together with experimental studies which demonstrate the effectiveness of the developed methodology.