• KIPS Transactions on Software and Data Engineering
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• v.5 no.3
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• pp.155-164
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• 2016

For frequency pattern analysis of large databases, the new tree-based frequency pattern analysis algorithm which can compensate for the disadvantages of the Apriori method has been variously studied. In frequency pattern tree, the number of nodes is associated with memory allocation, but also affects memory resource consumption and processing speed of the growth. Therefore, reducing the number of nodes in the tree is very important in the frequency pattern mining. However, the absolute criteria which need to order the transaction items for construction frequency pattern tree has lowered the compression ratio of the tree nodes. But most of the frequency based tree construction methods adapted the absolute criteria. FP-tree is typically frequency pattern tree structure which is an extended prefix-tree structure for storing compressed frequent crucial information about frequent patterns. For construction the tree, all the frequent items in different transactions are sorted according to the absolute criteria, frequency descending order. CanTree also need to absolute criteria, canonical order, to construct the tree. In this paper, we proposed a novel frequency pattern tree construction method that does not use the absolute criteria, IRFP-tree algorithm. IRFP-tree(Intersection Rule based FP-tree). IRFP-tree is constituted with the new paradigm of the intersection rule without the use of the absolute criteria. It increased the compression ratio of the tree nodes, and reduced the tree construction time. Our method has the additional advantage that it provides incremental mining. The reported test result demonstrate the applicability and effectiveness of the proposed approach.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.84-93
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• 2004

Recently, domain-specific demands with respect to practical applications and analysis scheme using spatial thematic information are increasing. Accordingly, in this study, GIS-based application program is implemented to perform spatial analysis in transportation geography with base road layer data. Using this program, quantitative estimation of circuity and accessibility, which can be extracted from nodes composed of the graph-typed network structure, in a arbitrary analysis zone or administrative boundary zone is possible. Circuity is a concept to represent the difference extent between actual nodes and fully connected nodes in the analysis zone. While, accessibility can be used to find out extent of accessibility or connectivity between all nodes contained in the analysis zone, judging from inter-connecting status of the whole nodes. In put data of this program, which was implemented in AVX executable extension using AvenueTM of ArcView, is not transportation database information based on transportation data model, but layer data, directly obtaining from digital map sets. It is thought that computation of circuity and accessibility can be used as kinds of spatial analysis functions for GIS applications in the transportation field.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.132-137
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• 2004

In this paper, the adaptive noise canceler using neural network with backpropagation is designed. The adaptive noise canceler using the least mean square algorithm has the large correlativity of the reference signal. The performance of the adaptive noise canceler shows the limitation when the information signal is relatively small to the noise. The system proposed in this paper plays an important role in denoising these signals. In addition, the experiments are carried out to analyze the effects of the number of hidden layers and nodes about the system. The performance of the proposed adaptive noise canceler is compared with that of the system which is used the least mean square algorithm.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.127-135
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• 2008

Generally, optimum shortest path algorithms adopt single attribute objective among several attributes such as travel time, travel cost, travel fare and travel distance. On the other hand, multi-objective shortest path algorithms find the shortest paths in consideration with multi-objectives. Up to recently, the most of all researches about multi-objective shortest paths are proceeded only in single transportation mode networks. Although, there are some papers about multi-objective shortest paths with multi-modal transportation networks, they did not consider transfer problems in the optimal solution level. In particular, dynamic programming method was not dealt in multi-objective shortest path problems in multi-modal transportation networks. In this study, we propose a multi-objective shortest path algorithm including dynamic programming in order to find optimal solution in multi-modal transportation networks. That algorithm is based on two-objective node-based label correcting algorithm proposed by Skriver and Andersen in 2000 and transfer can be reflected without network expansion in this paper. In addition, we use non-dominated paths and tree sets as labels in order to improve effectiveness of searching non-dominated paths. We also classifies path finding attributes into transfer and link travel attribute in limited transit networks. Lastly, the calculation process of proposed algorithm is checked by computer programming in a small-scaled multi-modal transportation network.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.199-213
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• 2008

The goal of this research is to develop and apply the integrational operation method (IOM) for the modeling of the monthly pan evaporation (PE) and the alfalfa reference evapotranspiration ($ET_r$). Since the observed data of the alfalfa $ET_r$ using lysimeter have not been measured for a long time in Republic of Korea, Penman-Monteith (PM) method is used to estimate the observed alfalfa $ET_r$. The IOM consists of the application of the stochastic and neural networks models, respectively. The stochastic model is applied to generate the training dataset for the monthly PE and the alfalfa $ET_r$, and the neural networks models are applied to calculate the observed test dataset reasonably. Among the considered six training patterns, 1,000/PARMA(1,1)/GRNNM-GA training pattern can evaluate the suggested climatic variables very well and also construct the reliable data for the monthly PE and the alfalfa $ET_r$. Uncertainty analysis is used to eliminate the climatic variables of input nodes from 1,000/PARMA(1,1)/GRNNM-GA training pattern. The sensitive and insensitive climatic variables are chosen from the uncertainty analysis of the input nodes. Finally, it can be to model the monthly PE and the alfalfa $ET_r$ simultaneously with the least cost and endeavor using the IOM.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3A
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• pp.141-150
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• 2012

The WiMedia Alliance has specified a Distributed Medium Access Control (D-MAC) protocol based on UWB for high speed wireless home networks and WPANs. In this paper, firstly, a time slot reservation protocol for relay transmission is proposed. Furthermore, we propose a novel relay node selection algorithm adaptive to current UWB link transmission rate. The proposed relay node selection algorithm has compatibility with current WiMedia D-MAC standard and is executed at each device according to the SoQ as a QoS criterion.

• Electronics and Telecommunications Trends
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• v.20 no.1 s.91
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• pp.112-122
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• 2005

센서 네트워크는 많은 수의 센서 노드들로 구성된 네트워크로 센서를 통한 주변 정보 감지 및 감지된 정보를 처리하는 기능을 수행한다. 최근 유비쿼터스 컴퓨팅 개념의 도입과 함께 이를 실생활에 구현하기위한 기반 기술의 하나로 센서 네트워크가 큰 관심을 모으고 있다. 그러나 유비쿼터스 컴퓨팅을 통한삶의 편리성을 추구함과 동시에 네트워킹을 통해 제공되는 정보를 신뢰할 수 있어야 하며 개인의 프라이버시 또한 보장되어야 함은 기본적인 요구 사항이다. 센서 네트워크는 기존의 네트워크와 여러 모로 다른 특성을 갖고 있어 기존의 보안 기법을 그대로 적용하기 어렵다. 이러한 필요성에 의해 다양한 센서 네트워크 보안 관련 연구가 진행되고 있는데 본 고에서는 최근 가장 활발히 연구되고 있는 센서 네트워크 보안에 관련된 인증, 키관리, 네트워크 구조 등을 중심으로 연구 동향을 살펴본다.

• Journal of the Korean Data and Information Science Society
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• v.13 no.1
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• pp.97-104
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• 2002

Regression trees, a technique in data mining, are constructed by splitting function-a independent variable and its threshold. Lee (2002) considered one-sided purity (OSP) and one-sided extreme (OSE) splitting criteria for finding a interesting node as early as possible. But these methods cannot be crossed each other in the same tree. They are just concentrated on OSP or OSE separately in advance. In this paper, a new splitting method, which is the combination and extension of OSP and OSE, is proposed. By these combined criteria, we can select the nodes by considering both pure and extreme in the same tree. These criteria are not the generalized one of the previous criteria but another option depending on the circumstance.

• Convergence Security Journal
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• v.10 no.2
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• pp.51-57
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• 2010

This paper proposes extended trust evaluation mechanism which is able to become the standard of the node selection which provides a better service by using the basic transaction message which occurs from within the mobile Ad-hoc network and the additional transaction message and add confidence value. Furthermore, throughout the simulation shows the efficiency of the proposed trust evaluation mechanism.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.8 no.3
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• pp.152-156
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• 2009

This paper designs and implements wake up module for WBAN/USN sensor node which is using dynamic reference voltage demodulation circuit. When a comparator is used in a system for detecting received voltage level, comparator must have a reference voltage. However, the reference voltage is fixed, the system can communicate only a few range because received voltage level is changing widely due to distance of the wireless sensor nodes. Therefore, the proposed wake up module employs a dynamic reference voltage demodulation circuit for increasing communication range.