• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.3
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• pp.518-523
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• 2006

Due to keen competition among companies, they have segmented customers and they are trying to offer specially targeted customer by means of the distinguished method. In accordance, data mining techniques are noted as the effective method that extracts useful information. This paper explores customer segmentation of the home study company using a hybrid decision tree and artificial neural network model. With the application of variance selection process from decision tree, the systemic process of defining input vector's value and the rule generation were developed. In point of customer management, this research analyzes current customers and produces the patterns of them so that the company can maintain good customer relationship. The case study shows that the predicted accuracy of the proposed model is higher than those of regression, decision tree (CART), artificial neural networks.

• Journal of KIISE:Information Networking
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• v.36 no.6
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• pp.481-491
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• 2009

In this paper, we proposed a hybrid P2P overlay structure for live media streaming. The proposed structure consists of the mesh overlay organized by peers according to the geographical proximity and similar bandwidth range and the tree overlay formed by the peers for which the stability of participation is approved. The proposed scheme enhances the robustness of tree overlay and the long delay of mesh overlay by intelligently combining the utilization of the tree overlay and the mesh overlay. Furthermore, the peers with a large up-link bandwidth are located near to the media source peer. Therefore, it reduces the height of tree, and as a result, the stream transmission delay. Through simulation, we evaluated the performance of the proposed scheme in terms of scalability and quality of services.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2596-2604
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• 1997

There are two kinds of backends in ACK:code generator(full-fledged backend) and code expander(fast backend). Code generators generate target code using string pattern matching and code expanders generate target code using macro expansion. ACK translates EM to SPARC code using code expander. The corresponding SPARC code sequences for a EM code are generated and then push-pop optimization is performed. But, there is the problem of maintaining hybrid stack. And code expander is not considered to passes parameters of a procedure call through register windows. The purpose of this paper is to improve SPARC code quality. We suggest a method of SPARC cod generation using EM tree. Our method is divided into two phases:EM tree building phase and code expansion phase. The EM tree building phase creates the EM tree and code expansion phase translates it into SPARC code. EM tree is designed to pass parameters of a procedure call through register windows. To remove hybrid stack, we extract an additional information from EM code. We improved many disadvantages that arise from code expander in ACK.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.330-333
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• 2003

Initial cluster size for clustering of partitioning methods is very important to the clustering result. In K-means algorithm, the result of cluster analysis becomes different with optimal cluster size K. Usually, the initial cluster size is determined by prior and subjective information. Sometimes this may not be optimal. Now, more objective method is needed to solve this problem. In our research, we propose a hybrid genetic algorithm, a tree induction based evolution algorithm, for determination of optimal cluster size. Initial population of this algorithm is determined by the number of terminal nodes of tree induction. From the initial population based on decision tree, our optimal cluster size is generated. The fitness function of ours is defined an inverse of dissimilarity measure. And the bagging approach is used for saying computational time cost.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.27-37
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• 2005

The rectilinear Steiner tree problem (RSTP) is to find a minimum-length rectilinear interconnection of a set of terminals in the plane. It is well known that the solution to this problem will be the minimal spanning tree (MST) on some set Steiner points. The RSTP is known to be NP-complete. The RSTP has received a lot of attention in the literature and heuristic and optimal algorithms have been proposed, A key performance measure of the algorithm for the RSTP is the reduction rate that is achieved by the difference between the objective value of the RSTP and that of the MST without Steiner points. A hybrid evolution strategy on RSTP based upon the Prim algorithm was presented. The computational results show that the evolution strategy is better than the previously proposed other heuristic. The average reduction rate of solutions from the evolution strategy is about 11%, which is almost similar to that of optimal solutions.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.151-160
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• 2012

Most of the distributed high-dimensional indexing structures provide a reasonable search performance especially when the dataset is uniformly distributed. However, in case when the dataset is clustered or skewed, the search performances gradually degrade as compared with the uniformly distributed dataset. We propose a method of improving the k-nearest neighbor search performance for the distributed vector approximation-tree based on the strongly clustered or skewed dataset. The basic idea is to compute volumes of the leaf nodes on the top-tree of a distributed vector approximation-tree and to assign different number of bits to them in order to assure an identification performance of vector approximation. In other words, it can be done by assigning more bits to the high-density clusters. We conducted experiments to compare the search performance with the distributed hybrid spill-tree and distributed vector approximation-tree by using the synthetic and real data sets. The experimental results show that our proposed scheme provides consistent results with significant performance improvements of the distributed vector approximation-tree for strongly clustered or skewed datasets.

• Smart Media Journal
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• v.5 no.4
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• pp.75-82
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• 2016

Although Korea's economic and domestic automobile market through the change of road environment are growth, the traffic accident rate has also increased, and the casualties is at a serious level. For this reason, the government is establishing and promoting policies to open traffic accident data and solve problems. In this paper, describe the method of predicting traffic accidents by eliminating the class imbalance using the traffic accident data and constructing the Hybrid Model. Using the original traffic accident data and the sampled data as learning data which use FP-Growth algorithm it learn patterns associated with traffic accident injury severity. Accordingly, In this paper purpose a method for predicting the severity of a victim of a traffic accident by analyzing the association patterns of two learning data, we can extract the same related patterns, when a decision tree and multinomial logistic regression analysis are performed, a hybrid model is constructed by assigning weights to related attributes.

• Journal of Forest and Environmental Science
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• v.37 no.1
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• pp.35-43
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• 2021

The interspecific hybrid of Salix caprea and Salix gracilistyla has never been identified or studied in Korea. Accordingly, this study investigated the flower morphological characteristics of the interspecific hybrid between S. caprea and S. gracilistyla and compared the interspecific hybrid with S. caprea and S. gracilistyla, respectively. The female flowers were investigated for 12 characteristics and the male flowers were investigated for nine. For the female flowers, those of the hybrids were larger than those of S. caprea and S. gracilistyla in terms of catkin length (CL), bract length (BL), and bract width (BW). The hybrids are intermediates between S. caprea and S. gracilistyla in terms of ovary length, width, and stipitate length as well as gland length (GL). For the male flowers, those of the hybrids were bigger than those of S. caprea and S. gracilistyla in terms of CL, BL, and BW. The hybrids are intermediates between S. caprea and S. gracilistyla in terms of catkin width and stamen length (SL). A principal component analysis (PCA) of the female data showed that the first principal component (PC) explained 57.5% of the total variation. The first PC highly correlated the ovary stipitate and pistil style lengths. The analysis was divided into three groups of S. caprea, S. gracilistyla, and the hybrid by the first PC. The results of a PCA of the male data showed that the first PC explained 35.7% of the total variation. The first PC highly correlated with the adelphous SL and was divided into three groups of S. caprea, S. gracilistyla, and the hybrid. The results of the discriminant analysis showed that S. caprea, S. gracilistyla, and the hybrid were distinguishable by flower morphological characteristics. Therefore, the hybrid was distinctly separated from S. caprea and S. gracilistyla by flower characteristics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1035-1056
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• 2015

The efficiency of live Peer-to-Peer (P2P) streaming protocols depends on the appropriateness and the management abilities of their underlying overlay multicast. While a tree overlay structure confines transmission delays efficiently by maintaining deterministic delivery paths, an overlay mesh structure provides adequate resiliency to peers dynamics and easy maintenance. On the other hand, content freshness, playback fluidity and streaming continuity are still challenging issues that require viable solutions. In this paper, we propose a Hybrid Live P2P Streaming Protocol (HLPSP) based on a hybrid overlay multicast that integrates the efficiency of both the tree and mesh structures. Extensive simulations using OMNET++ are conducted to investigate the efficiency of HLPSP in terms of relevant performance metrics, and position HLPSP with respect to DenaCast the enhanced version of the well-known CoolStreaming protocol. Simulation results show that HLPSP outperforms DenaCast in terms of startup delay, end-to-end delay, play-back delay and data loss.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.250-259
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• 2021

Path planning is one of the important technologies for automated parking. It requires to plan a collision-free path considering the vehicle's kinematic constraints such as minimum turning radius or steering velocity. In a complex parking lot, Rapidly-exploring Random Tree^* (RRT^*) can be used for planning a parking path, and Reeds-Shepp or Hybrid Curvature can be applied as a tree-extension method to consider the vehicle's constraints. In this case, each of these methods may affect the computation time of planning the parking path, path-tracking error, and parking success rate. Therefore, in this study, we conduct comparative analysis of two tree-extension functions: Reeds-Shepp (RS) and Hybrid Curvature (HC), and show that HC is a more appropriate tree-extension function for parking path planning. The differences between the two functions are introduced, and their performances are compared by applying them with RRT^*. They are tested at various parking scenarios in simulation, and their advantages and disadvantages are discussed by computation time, cross-track error while tracking the path, parking success rate, and alignment error at the target parking spot. These results show that HC generates the parking path that an autonomous vehicle can track without collisions and HC allows the vehicle to park with lower alignment error than those of RS.