• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1789-1798
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• 2012

IEEE 802.15.4a standard can provide a variety of location-based services for ZigBee or wireless network applications by adapting the time-of-arrival (TOA) ranging technique. The non-line-of-sight (NLOS) condition is the critical problem in the IEEE 802.15.4a networks, and it can significantly degrade the performance of the TOA-based localization. To enhance the location accuracy due to the NLOS problem, this paper proposes an energy-efficient low complexity localization algorithm. The proposed approach performs the ranging with the multicast method, which can reduce the message overhead due to packet exchanges. By limiting the search region for the location of the node, the proposed approach can enhance the location accuracy. Experimental results show that the proposed algorithm outperforms previous algorithms in terms of the energy consumption and the localization accuracy.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.525-534
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• 2005

We present several distributed algorithms for localizing nodes of a wireless sensor network. Our algorithms determine locations of nodes based on the connectivity between nodes. The basic idea behind our algorithms is to estimate distances between nearby nodes by counting their common neighbors. We analyze the performance of our algorithms experimentally. The results of experiments show that our algorithms achieve performance improvements upon the existing algorithms

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.387-390
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• 2024

본 논문에서는 효율적인 2차 오차 함수를 이용하여 입자 기반에서 EMC(Extended Marching Cubes) 알고리즘을 구현할 수 있는 새로운 알고리즘을 제안한다. Smoothing 커널(Kernels)을 통해 계산한 입자 평균 위치에서 레벨셋(Level-set)을 계산해 스칼라장을 구축한다. 그리고 난 뒤 SPH(Smoothed particle hydrodynamics)기반의 커널을 통해 밀도, 입자 평균 위치를 계산한다. 스칼라장을 이용해 등가 곡면(Isosurface)을 찾고 음함수로 표현된 표면을 구성한다. SPH 커널을 공간에서 미분하면 공간상의 어느 위치에서나 기울기를 계산할 수 있고, 이를 통해 얻어진 법선벡터를 이용하여 일반적인 EMC나 DC(Dual contouring)에서 사용하는 2차 오차 함수를 효율적으로 설계한다. 결과적으로 제안하는 방법은 메쉬와 같이 연결정보다 없는 입자 기반 데이터에서도 EMC 알고리즘을 구현하여 볼륨(Volume) 손실을 줄이고, 복잡한 음함수 표면을 표현할 수 있게 한다.

• The KIPS Transactions:PartA
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• v.10A no.4
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• pp.381-388
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• 2003

Location tracking is used to keep track of the location information of a mobile terminal in an idle state for a cail setup between mobile terminals. In this paper, we introduce a location update algorithm based on the call arrival history, which is appropriate for a variable call arrival rate over time. The location tracking strategy which uses the proposed algorithm can find changes in the call arrival rate by maintaining a call arrival history of a mobile terminal, from which a mobile terminal can calculate an appropriate timeout interval for a variable call arrival rate. We show that the proposed scheme is appropriate for a variable call arrival rate by presenting a simple analytical model and analytical results to investigate its performance for both a fixed and a variable call arrival rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1A
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• pp.65-75
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• 2009

In Wireless Sensor Network, the sensor node localization is important issue for information tracking, event detection, routing. Generally, in wireless sensor network localization, the absolute positions of certain anchor nodes are required based on the use of global positioning system, then all the other nodes are approximately localized using various algorithms based on a coordinate system of anchor DV-Hop is a localized, distributed, hop by hop positioning algorithm in wireless sensor network where only a limited fraction of nodes have self positioning capability. However, instead of uniformly distributed network, in anisotropic network with possible holes, DV-Hop's performance is very low. To address this issue, we propose Group based DV-Hop (GDV-Hop) algorithm. Best contribution of GDV-Hop is that it performs localization with reduced error compared with DV-Hop in anisotropic network.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.454-456
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• 2002

한국어의 비재귀 명사구 즉 기반 명사구(basehp)를 인식하는 알고리즘을 제시한다. 본 논문에서는 한개의 주어진 학습 알고리즘에 대해 문맥 윈도우의 크기와 문맥 윈도우의 위치를 달리해 가면서 학습시킨다 이러한 방법을 통해 서로 다른 정보를 바탕으로 한 기반 명사구 인식을 수행할 수 있으며, 그 결과서로 다른 여러 개의 결과들을 생성할 수 있다. 본 논문에에서는 이렇게 얻어진 여러 개의 인식 결과들을 적절한 방법으로 결합하여 한국어에서 91% 이상의 높은 기반명사구 인식 정확도를 얻어낼 수 있다. 15만 단어 규모의 국어정보베이스의 말뭉치를 사용했으며 , 학습 알고리즘으로는 메모리 기반 학습 알고리즘 (memory-based learning)을 이용하여 실험하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.1
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• pp.80-86
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• 2013

The 3-Dimensional(3D) localization system based on beacon expansion and coordinate-space disassembly for the design of the 3D localization system in indoor environment is proposed and the performance of the proposed system is analyzed in this paper. The localization ratio of the 3D localization system adapts the proposed algorithm is analyzed by the calculation of errors occurred in the coordinates that the mobile node locates. It is indicated that the average error distance of the 3D localization system adapts the proposed algorithm is less than that of the 3D localization system not adapts the proposed algorithm as 0.47m. The localization average distance error in 12 coordinates is indicated that the 1.5m case is less than 2.5m case as 0.38m by some experimentations under the condition that the distances between the ceiling and the mobile node are 1.5m and 2.5m measured from the ceiling respectively. It is seen that the 3D localization system based on beacon expansion and coordinate-space disassembly can improved the degradation of the quality of service that is caused by some conditions and performance differences in sensors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1511-1519
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• 2010

In this paper, we proposed and analyzed a RSSI based cooperative localization algorithm considering wireless propagation characteristics in indoor and outdoor environments for wireless sensor networks, which can estimate the BN position. The conventional RSSI based estimation scheme has low precision ranging due to instability propagation characteristics by time variable. Hence, we implemented ray-launching simulator for analysis of propagation characteristics in 4 case, and experimented proposed localization scheme with 4 RN and 1 to 5 BN. Simulation results show that NLCA has estimation error as 2m-3.5m, however, proposed CLA/ECLA has 1.3m-2.5m/0.5m-1.2m by same environments. Therefore, if we can consider channel characteristics, the proposed algorithm provides higher localization accuracy than RSSI based conventional one.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1926-1933
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• 2013

Many localization algorithms have been proposed for Wireless Sensor Networks (WSNs). The IEEE 802.15.4a-based location-aware-system can provide precise ranging distance between two mobile nodes. The mobile nodes can obtain their exact locations by using accurate ranging distances. However, the indoor environments contain various obstacles which cause non-line-of-sight (NLOS) conditions. In NLOS condition, the IEEE 802.15.4a-based location-aware system has a large scale location error. To solve the problem, we propose location error compensation in indoor environment by using MST-based topology control. Experimental and simulation results show that the proposed algorithm improves location accuracy in NLOS conditions.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.413-416
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• 2006

최근 위치 측위 기술의 발달 및 GPS 기술의 상용화로 인해 무선 통신 기기의 보급이 증가하면서 다양한 위치 기반 서비스 개발을 위한 노력이 활발히 진행되고 있다. 사용자들의 특성에 맞게 개인화되고 세분화된 위치 기반 서비스를 제공하기 위해서는 방대한 이동 객체의 위치 이동 데이터로부터 의미있는 지식인 유용한 패턴을 추출하기 위한 시간 패턴 탐사가 필요하다. 기존의 시간 패턴 탐사 기법들 중 일부는 이동 객체의 시간에 따른 공간 속성들의 변화를 충분히 고려하지 못하거나 또는 시공간 속성을 동시에 고려한 패턴 탐사는 가능하나 전체 이동 패턴들 중 추출하고자 하는 패턴에 반드시 포함되어야 하는 공간 정보에 대한 제약이 없어 특정 지점들 사이의 최적 이동 경로 탐색 문제나 단위기간 동안 이동 객체가 순회해야 지점들에 대한 스케줄링 경로 예측 문제 등에 적용하기 어렵다. 따라서 본 논문에서는 이동 객체의 위치 이력 데이터들에 대한 시공간 속성들을 고려하여 다양한 이동 패턴들 중 객체의 최적 이동 경로에 해당하는 패턴을 탐색하기 위한 새로운 시간 패턴 마이닝 알고리즘을 제안한다. 제안된 알고리즘은 특정한 지점들 사이를 이동한 객체의 위치 데이터들 중 객체가 가장 빈번하게 이동한 경로를 탐색하여 최적 경로를 결정하는 알고리즘으로, 공간 추상 계층의 각 계층별 영역 내 포함여부를 고려한 위치 일반화를 수행하여 보다 효과적으로 이동 패턴을 탐색할 수 있다.