• Proceedings of the KIEE Conference
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• summer
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• pp.135-137
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• 2004

This paper describes new land use estimation method for long term load forecast using $R\startree$ algorithm. Where $R\startree$ algorithms is a proposed method for efficient spatial search. An estimation result showed that execute time of the proposed method is prior to execute time of conventional method.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.589-592
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• 2007

웹사이트의 블로그에서 등록된 게시물을 분류, 표현하는 방식으로 카테고리 분류방식과 Tag cloud 분류방식을 사용하고 있다. 그러나 카테고리분류방식은 같은 게시물이라도 블로그 관리자별로 해당 분류의 생성기준이 주관적인 판단에 따라 다른 분류에 속할 수 있어 이용자들이 찾고자 하는 게시물을 검색하는데 많은 시간이 소요될 수 있다는 단점이 있다. 또한 이를 보완하는 방안으로 사용되는 Tag cloud 방식은 태그들을 흩어놓아 원하는 정보를 빠르게 찾는데 한계가 있다. 이에 본 논문은 블로그에서 태그들을 그룹화하여 구현한 트리형 Tag cloud(이하 'TreeTag cloud') 모델을 통해 카테고리 분류방식의 트리 구조의 장점인 직관성 및 구조화와 Tag cloud 분류방식의 장점인 짧은 search depth 를 결합하여 구현하는 방법을 제안하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8A
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• pp.942-949
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• 2004

This paper proposes and analyzes the anti-collision algorithm in Ubiquitous ID system. We mathematically compares the performance of the proposed algorithm with that of binary search algorithm, slotted binary tree algorithm using time slot, and bit-by-bit binary tree algorithm proposed by Auto-ID center. We also validated analytic results using OPNET simulation. Based on the analytic results, comparing the proposed algorithm with bit-by-bit algorithm which is the best of existing algorithms, the performance of proposed algorithm is about 5% higher when the number of tags is 20, and 100% higher when the number of tags is 200.

• The Journal of Society for e-Business Studies
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• v.9 no.1
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• pp.83-104
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• 2004

Recently, information systems that require storage and retrieval of huge amount of data are becoming used widely. Accordingly, research efforts have been made to develop Linux cluster file systems in the SAN environment in which clients themselves can manage metadata and access data directly. Also a semi-flat directory structure based on extendible hashing has been proposed to support fast retrieval of files[1]. In this research, we have designed and implemented the semi-flat extendible hash directory under the Linux system. In order to evaluate the practicality of the directory, we have also implemented the B+-tree based directory and experimented the performance. According to the performance comparisons, the extendible hash directory has the better performance at insert, delete, and search operations. On the other hand, the B+-tree directory is better at sorting files.

• The Journal of the Korea Contents Association
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• v.8 no.7
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• pp.35-42
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• 2008

The proposed scheme in this paper can search multi-links efficiently using the depth priority method based on hop count instead of searching the all links. To do this, we proposed a modified line segment scheme using two line segment method. The scheme represents two points which consist of delay-bandwidth pair to reduce topology information and provide a flexibility to the multiple-links aggregation. And we apply it to current spanning tree topology aggregation. To evaluate performance of the proposed scheme, we compare/analyze the current method with the proposed scheme with respect to call success rate, access time and crankback rate. Simulation result analysis showed the proposed spanning tree topology aggregation scheme presents the better performance than existing scheme.

• Journal of Computing Science and Engineering
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• v.3 no.1
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• pp.1-4
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• 2009

In a given text T of size n, we need to search for the information that we are interested. In order to support fast searching, an index must be constructed by preprocessing the text. Suffix array is a kind of index data structure. The compressed suffix array (CSA) is one of the compressed indices based on the regularity of the suffix array, and can be compressed to the $k^{th}$ order empirical entropy. In this paper we improve the lookup time complexity of the compressed suffix array by using the multi-ary wavelet tree at the cost of more space. In our implementation, the lookup time complexity of the compressed suffix array is O(${\log}_{\sigma}^{\varepsilon/(1-{\varepsilon})}\;n\;{\log}_r\;\sigma$), and the space of the compressed suffix array is ${\varepsilon}^{-1}\;nH_k(T)+O(n\;{\log}\;{\log}\;n/{\log}^{\varepsilon}_{\sigma}\;n)$ bits, where a is the size of alphabet, $H_k$ is the kth order empirical entropy r is the branching factor of the multi-ary wavelet tree such that $2{\leq}r{\leq}\sqrt{n}$ and $r{\leq}O({\log}^{1-{\varepsilon}}_{\sigma}\;n)$ and 0 < $\varepsilon$ < 1/2 is a constant.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.629-648
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• 2012

Given a video stream delivering system deployed on a multicast tree, which is embedded in a multi-channel multi-radio wireless mesh network, our problem is concerned about how to allocate interference-free channels to tree links and maximize the number of serviced mesh clients at the same time. In this paper, we propose a channel allocation heuristic algorithm based on best-first search and backtracking techniques. The experimental results show that our BFB based CA algorithm outperforms previous methods such as DFS and BFS based CA methods. This superiority is due to the backtracking technique used in BFB approach. It allows previous channel-allocated links to have feasibility to select the other eligible channels when no conflict-free channel can be found for the current link during the CA process. In addition to that, we also propose a tree refinement method to enhance the quality of channel-allocated trees by adding uncovered destinations at the cost of deletion of some covered destinations. Our aim of this refinement is to increase the number of serviced mesh clients. According to our simulation results, it is proved to be an effective method for improving multicast trees produced by BFB, BFS and DFS CA algorithms.

• ETRI Journal
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• v.44 no.3
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• pp.462-475
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• 2022

Although researchers have proposed numerous techniques for speech emotion recognition, its performance remains unsatisfactory in many application scenarios. In this study, we propose a speech emotion recognition model based on a genetic algorithm (GA)-decision tree (DT) fusion of deep and acoustic features. To more comprehensively express speech emotional information, first, frame-level deep and acoustic features are extracted from a speech signal. Next, five kinds of statistic variables of these features are calculated to obtain utterance-level features. The Fisher feature selection criterion is employed to select high-performance features, removing redundant information. In the feature fusion stage, the GA is is used to adaptively search for the best feature fusion weight. Finally, using the fused feature, the proposed speech emotion recognition model based on a DT support vector machine model is realized. Experimental results on the Berlin speech emotion database and the Chinese emotion speech database indicate that the proposed model outperforms an average weight fusion method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.71-79
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• 2007

Recent advances in the internet infrastructure have resulted in a large number of huge Web sites and portals worldwide. These Web sites are being visited by various types of users in many different ways. Among all the web page access sequences from different users, some of them occur so frequently that may need an attention from those who are interested. We call them frequent access patterns and access sequences that can be frequent the candidate patterns. Since these candidate patterns play an important role in the incremental Web mining, it is important to efficiently generate, add, delete, and search for them. This thesis presents a novel tree structure that can efficiently store the candidate patterns and a related set of algorithms for generating the tree structure, adding new patterns, deleting unnecessary patterns, and searching for the needed ones. The proposed tree structure has a kind of the 3 dimensional link structure and its nodes are layered.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.706-716
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• 2016

Because of efficient space utilization and fast key search times, B-trees have been widely accepted for the use of indexes in HDD-based DBMSs. However, when the B-ree is stored in flash memory, its costly operations of node updates may impair the performance of a DBMS. This is because the random updates in B-tree's leaf nodes could tremendously enlarge I/O costs for the garbage collecting actions of flash storage. To solve the problem, we make all the parents of leaf nodes the virtual nodes, which are not stored physically. Rather than, those nodes are dynamically generated and buffered by referring to their child nodes, at their access times during key searching. By performing node updates and tree reconstruction within a single flash block, our proposed B-tree can reduce the I/O costs for garbage collection and update operations in flash. Moreover, our scheme provides the better performance of key searches, compared with earlier flash-based B-trees. Through a mathematical performance model, we verify the performance advantages of the proposed flash B-tree.