• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.402-409
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• 2006

In recent years, several methods in distributed environment have been proposed in which a user-centered multimedia service may be efficiently provided. However, problems such as the improvement of QoS, streaming and the dynamic service of data for distributed service of multimedia data are introduced. In this paper we propose $POX -H_{r}$ structure for user-centered multimedia service in distributed network environment. The proposed $POX -H_{r}$ structure are constructed by disjunct, conjunct, semantic and filtering mapping scheme, and its structure are updated by $M_{filtering}$ scheme. The comparison results shows that the proposed method provides the better than the other methods.

• ETRI Journal
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• v.30 no.6
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• pp.874-876
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• 2008

Ethernet ring protection is a new technology introduced in ITU-T Recommendation G.8032, which utilizes the generic Ethernet MAC functions. We introduce an alternative enhanced protection switching scheme to suppress penalty in the switching transient, in which the Ethernet MAC filtering database (FDB) is actively and directly modified by information disseminated from the nodes adjacent to failure. The modified FDB at all nodes are guaranteed to be consistent to form a complete new ring network topology immediately. This scheme can reduce the capacity requirement of the G.8032 by several times. This proposed scheme can be also applied in IP protection rings.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.6
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• pp.609-616
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• 2016

This paper is proposed a customized market analysis method using SVM and collaborative filtering. The proposed customized market analysis scheme is consists of DC(Data Classification) module, ICF(Improved Collaborative Filtering) module, and CMA(Customized Market Analysis) module. DC module classifies the characteristics of on-line and off-line shopping mall and traditional markets into price, quality, and quantity using SVM. ICF module calculates the similarity by adding age weight and job weight, and generates network using the similarity of purchased item each users, and makes a recommendation list of neighbor nodes. And CMA module provides the result of customized market analysis using the data classification result of DC module and the recommendation list of ICF module. As a result of comparing the proposed customized recommendation list with the existing user based recommendation list, the case of recommendation list using the existing collaborative filtering scheme, precision is 0.53, recall is 0.56, and F-measure is 0.57. But the case of proposed customized recommendation list, precision is 0.78, recall is 0.85, and F-measure is 0.81. That is, the proposed customized recommendation list shows more precision.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.161-171
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• 2010

Sensor Networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects forged reports into the network through compromised nodes. Such attacks by compromised sensors can cause not only false alarms but also the depletion of the finite amount of energy in a battery powered network. Ye et al. proposed the Statistical En-route Filtering scheme to overcome this threat. In statistical en-route filtering scheme, all the intermediate nodes perform verification as event reports created by center of stimulus node are forwarded to the base station. This paper applies a probabilistic verification method to the Static Statistical En-route Filtering for energy efficiency. It is expected that the farther from the base station an event source is, the higher energy efficiency is achieved.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.311-312
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• 2013

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.313-314
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• 2013

• Speech Sciences
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• v.12 no.4
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• pp.71-76
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• 2005

There have been numerous studies on the enhancement of noisy speech signal. In this paper, we propose a new speech enhancement method, that is, a filtering of a dissonant frequency combined with noise suppression algorithm. The simulation results indicate that the proposed method provides a significant gain in voice clarity. Therefore if the proposed enhancement scheme is used as a pre-filter, the perceptual clarity of husky voice is greatly enhanced.

• Journal of Information Technology Applications and Management
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• v.23 no.4
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• pp.55-70
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• 2016

Recently, development of indoor positioning system and IoT such as beacon makes it possible to collect and analyze each customer's shopping behavior in off-line shopping malls. In this study, we propose a realtime brand recommendation scheme based on each customer's brand visiting history for off-line shopping mall with indoor positioning system. The proposed scheme, which apply collaborative filtering to off-line shopping mall, is composed of training and apply process. The training process is designed to make the base brand network (BBN) using historical transaction data. Then, the scheme yields recommended brands for shopping customers based on their behaviors and BBN in the apply process. In order to verify the performance of the proposed scheme, simulation was conducted using purchase history data from a department store in Korea. Then, the results was compared to the previous scheme. Experimental results showd that the proposed scheme performs brand recommendation effectively in off-line shopping mall.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3000-3005
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• 2015

Reliable monitoring and diagnosis of industrial processes is quite important for in terms of quality and safety. The goal of fault diagnosis is to find process variables responsible for causing specific abnormalities of the process. This work presents a classification-based diagnostic scheme based on nonlinear representation of process data. The use of a nonlinear kernel technique is able to reduce the size of the data considered and provides efficient and reliable representation of the measurement data. As a filtering stage a preprocessing is performed to eliminate unwanted parts of the data with enhanced performance. The case study of an industrial batch process has shown that the performance of the scheme outperformed other methods. In addition, the use of a nonlinear representation technique and filtering improved the diagnosis performance in the case study.

• The KIPS Transactions:PartA
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• v.12A no.1 s.91
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• pp.41-52
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• 2005

Memory reference instruction caused by cache miss is the critical factor that limits the processing power of processor. Cache prefetching technique is an effective way to reduce the latency due to memory access. However, excessively aggressive prefetch leads to cache pollution and finally to cancel out the advantage of prefetch. In this study, an active prefetch filtering scheme is introduced which dynamically decides whether to commence prefetching after referring a filtering table to reduce the cache pollution due to unnecessary prefetches. For the precision filtering, an evicted address referencing scheme has been proposed where the filter directly compares the current prefetch address with previous unnecessary prefetch addresses stored in filtering table. Moreover, a small sized exclusive prefetch cache has been introduced to increase the amount of eviction of unnecessarily prefetched addresses to enhance the accuracy of dynamic filtering. The exclusive prefetch cache also prevents useful demand data from being pushed out by prefetched data, while the evicted address direct referencing scheme enables the prefetch cache to keep most of useful prefetch data within its small size. Experimental results from commonly used general and multimedia benchmarks show that the average cache miss ratio has been decreased by $13.3{\%}$ by virtue of enhanced filtering accuracy compared with conventional schemes.