• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.373-377
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• 2022

Wireless sensor networks are being used in various fields. Wireless sensor networks are applied in many areas, such as security, military detection, environmental management, industrial control, and home automation. There is a problem about the limit of energy that the sensor network basically has. In this paper, we propose the LEACH-CCBD (Low Energy Adaptive Clustering hierarchy - Centrailized with Cluster and Basestation Distance) algorithm that uses energy efficiently by improving network transmission based on LEACH-C among the representative routing protocols. The LEACH-CCBD algorithm is a method of assigning a cluster head to a cluster head by comparing the sum of the distance from the member node to the cluster distance and the distance from the cluster node to the base station with respect to the membership of the member nodes in the cluster when configuring the cluster. The proposed LEACH-CCBD used Matlab simulation to confirm the performance results for each protocol. As a result of the experiment, as the lifetime of the network increased, it was shown to be superior to the LEACH and LEACH-C algorithms.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.609-616
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• 2023

In a wireless network environment, since sensors are not always connected to power, the life of a battery, which is an energy source supplied to sensors, is limited. Therefore, various studies have been conducted to extend the network life, and a layer-based routing protocol, LEACH(: Low-energy Adaptive Clustering Hierarchy), has emerged for efficient energy use. However, the LEACH protocol, which transmits fused data directly to the sink node, has a limitation in that it consumes as much energy as the square of the transmission distance when transmitting data. To improve these limitations, this paper proposes an algorithm that can minimize the transmission distance with multi-hop transmission where cluster heads are chained between cluster heads through relative distance calculation from sink nodes in every round.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2B
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• pp.138-147
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• 2012

With the improvement of wireless communication and embedded technology, WSN is used at various fields. Meanwhile, because WSN is resource constrained, it is more vulnerable than other networks. To solve the security problem of WSN, we can use the traditional secure mechanism like as cryptography and authentication. But the traditional secure mechanism is not enough for all security issues that may be happened in WSN, especially attacks caused by the compromised node. So, we need the IDS as the second secure mechanism for WSN. In this paper, we propose the Specification-based Intrusion Detection Mechanism that makes LEACH, which is one of the clustering routing protocol for WSN, more reliable and safety.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.197-200
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• 2021

몰입형 고품질 가상 현실 영상 스트리밍을 위한 360도 영상 부호화 및 전송 기술 중 하나로 사용자 시점 기반 타일 스트리밍 기법이 활발히 연구되고 있다. 360도 영상은 용량이 크기 때문에 개별 타일 기반 스트리밍 방법을 사용해 사용자 시점만 보내는 것이 효율적이다. 본 논문은 시점 기반 가상 현실 영상 복호화 시스템을 위한 복호기 적응적 타일 클러스터링 알고리즘을 제안한다. 제안하는 방법은 클라이언트의 복호기가 최대로 복호화 가능한 해상도를 탐색한 후, 사용자 시점 데이터와 복호기 적응적 타일 클러스터링 알고리즘을 이용해 클러스터화할 복수 개의 사용자 시점 타일들의 목록을 생성한 후, 타일 병합기를 이용해 타일들을 병합하여 클러스터 비트스트림을 생성한다. 이후 클라이언트는 병합된 클러스터 비트스트림들을 복호화한 후 사용자 시점을 생성한다. 제안하는 방법을 이용하면 클라이언트의 복호기 환경에 제약받지 않는 복호화가 가능하며, 제안하는 방법 중 하나인 4K_clustering 방법의 경우 8%의 복호화 속도 개선 효과를 얻을 수 있어 몰입형 고품질 가상 현실 영상을 위한 실시간 타일 스트리밍이 가능하다.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.857-871
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• 2013

The interest in rainfall observation and forecasting using remote sensing method like RADAR (Radio Detection and Ranging) and satellite image is increased according to increased damage by rapid weather change like regional torrential rain and flash flood. In this study, the basin runoff was calculated using adaptive neuro-fuzzy technique, one of the data driven model and MAPLE (McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as one of the input variables. The flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated. Six rainfall events occurred at flood season in 2010 and 2011 in Chungju Reservoir basin were used for the input data. The flood estimation results according to the rainfall data used as training, checking and testing data in the model setup process were compared. The 15 models were composed of combination of the input variables and the results according to change of clustering methods were compared and analysed. From this study was that using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation. The model using MAPLE forecasted precipitation data showed relatively better result at inflow estimation Chungju Reservoir.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.58-64
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• 2016

In this paper presents Robust k-means clustering-based high-speed bar code decoding method to blur and lighting. for fast operation speed and robust decoding to blur, proposed method uses adaptive local threshold binarization methods that calculate threshold value by dividing blur region and a non-blurred region. Also, in order to prevent decoding fail from the noise, decoder based on k-means clustering algorithm is implemented using area data summed pixel width line of the same number of element. Results of simulation using samples taken at various worst case environment, the average success rate of proposed method is 98.47%. it showed the highest decoding success rate among the three comparison programs.

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.639-646
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• 2003

Conventional two-tier databases have shown performance limitation in the presence of many concurrent clients. To this end, the three-tier architecture that exploits similarities in client's object access behavior has been proposed. In this system, clients are partitioned into clusters, and object requests can be then served in inter-cluster manner. Introducing an intermediate layer between server(s) and clients enables this. In this paper, we introduce the problem of client realignment in which access behavior changes, and propose on-line client clustering. This system facilitates adaptive reconfiguration and redistribution of sites. The core issue in this paper is to demonstrate the effectiveness of on-line client clustering. We experimentally investigate the performance of the scheme and necessary costs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.6
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• pp.504-511
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• 2013

This paper proposes improved detection schemes for concealed micro-electronic devices using clustering and classification of radio frequency harmonics in order to protect intellectual property rights. In general, if a radio wave with a specific fundamental frequency is propagated from the transmitter of a classifier to a concealed object, the second and the third harmonics will be returned as the radio wave is reflected. Using this principle, we exploit the fuzzy c-means clustering and the ${\kappa}$-nearest neighbor classification for detecting diverse concealed objects. Simulation results indicate that the proposed scheme can detect electronic devices and metal devices in various learning environments by efficient classification. Thus, the proposed schemes can be utilized as an effective detection method for concealed micro-electronic device to protect intellectual property rights.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.137-145
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• 2008

In general, a large-scale wireless sensor network(WSNs) is composed of hundreds of or thousands of sensor nodes. In this large-scale wireless sensor networks, it is required to maintain and manage the networks to lower management cost and obtain high energy efficiency. Users should be provided with sensing service at the level of quality for users through an efficient system. In evaluating the result data quality provided from this network to users, the number of sensors related to event detection has an important role. Accordingly, the network protocol which can provide proper QoS at the level of users demanding quality should be designed in a way such that the overall system function has not to be influenced even if some sensor nodes are in error. The energy consumption is minimized at the same time. The protocol suggested in this article is based on the LEACH protocol and is a role-based self-Organization one that is appropriate for large-scale networks which need constant monitoring.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.1-10
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• 2009

Energy efficient operations are essential to increase the life time of wireless sensor network. A cluster-based protocol is the most common approach to preserve energy during a data aggregation. This paper deals with an energy awareness and autonomous clustering method based on time delay. This method consists of three stages. In the first phase, Candidate Cluster Headers(CCHs) are selected based on a time delay which reflects the remaining energy of a node, with considering coverage efficiency of a cluster. Then, time delay is again applied to declare Cluster Headers(CHs) out of the CCHs. In the last phase, the issue on an orphan node which is not included into a cluster is resolved. The simulation results show that the proposed method increases the life time of the network around triple times longer than LEACH(Low Energy Adaptive Cluster Hierarchy). Moreover, the cluster header frequency is less diverse, and the energy on cluster heads is less spent.