• Journal of KIISE:Software and Applications
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• v.28 no.7
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• pp.467-477
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• 2001

반응적 타부 탐색은 단순한 타부 탐색과 비교해서 중장기 메모리를 이용한 학습을 통하여 타부리스트의 크기를 반응적으로 변화시킴으로써 NP-hard 문제에 속하는 다양한 조합 최적해 문제에 대해서 좋은 해를 효율적으로 찾는다. 본 논문에서는 반응적 타부 탐색에 있어서 중장기 메모리를 이용한 탈출 메커니즘으로 이웃 해 전략 전환 메커니즘이라는 개념을 제시한다. 제시된 이웃 해 전략 전환 메커니즘을 이용한 반응적 타부 탐색을 특정 공과 대학의 강의 시간표 작성 문제와 외판원문제 (traveling salesman problem)에 적용하여 기존의 반응적 타부 탐색과 비교 분석을 하였다. 전산 실험 결과 제시된 알고리즘은 기존의 반응적 타부 탐색 알고리즘에 비교하여 더 좋은 해를 더 짧은 시간에 찾아주었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.1045-1048
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• 2006

무선 센서 네트워크에서 하나의 싱크가 아닌 여러 개의 싱크(multi-싱크)인 경우에는 데이터의 전송에 있어 특정 라우팅 기법을 이용하는 것 보다 플러딩방식이 매우 적합한 전송기법으로 알려져 있다. 그러나 유선 환경 등의 기타 네트워크에서 사용되던 플러딩 방식을 무선 센서 네트워크에 그대로 사용하는 것은 적절하지 않다. 무선 센서 네트워크에서는 에너지의 효율성이 무엇보다 중요하며 기존의 플러딩방식은 불필요한 패킷의 중복전송 등 해결해야 할 문제점들이 많이 남아있기 때문이다. 우리는 이웃 노드들의 노드 리스트를 적절히 관리하여 불필요한 패킷의 재전송을 막아주며, 노드 리스트를 관리하는 오버헤드를 최소화 하여 에너지 효율성을 높인 무선 센서 네트워크의 특성에 맞는 플러딩방식인 HEEF기법을 제안한다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.3
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• pp.48-58
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• 2009

Geo-graphical routing protocols as GPSR are known to be very suitable and useful for vehicular ad-hoc networks. However, a corresponding node can include some stale neighbor nodes being out of a transmission range, and the stale nodes are pone to get a high priority to be a next relay node in the greedy mode. In addition, some useful redundant information can be eliminated during planarization in the recovery mode. This paper deals with a new recovery mode, the Greedy Border Superiority Routing(GBSR), along with an Adaptive Neighbor list Management(ANM) scheme. Each node can easily treat stale nodes on its neighbor list by means of comparing previous and current Position of a neighbor. When a node meets the local maximum, it makes use of a border superior graph to recover from it. This approach improve the packet delivery ratio while it decreases the time to recover from the local maximum. We evaluate the performance of the proposed methods using a network simulator. The results shown that the proposed protocol reveals much better performance than GPSR protocol. Please Put the of paper here.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.181-188
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• 2018

In this paper, we propose an analysis scheme of customer spending pattern using text mining. In proposed consumption pattern analysis scheme, first we analyze user's rating similarity using Pearson correlation, second we analyze user's review similarity using TF-IDF cosine similarity, third we analyze the consistency of the rating and review using Sendiwordnet. And we select the nearest neighbors using rating similarity and review similarity, and provide the recommended list that is proper with consumption pattern. The precision of recommended list are 0.79 for the Pearson correlation, 0.73 for the TF-IDF, and 0.82 for the proposed consumption pattern. That is, the proposed consumption pattern analysis scheme can more accurately analyze consumption pattern because it uses both quantitative rating and qualitative reviews of consumers.

• 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 Advanced Navigation Technology
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• v.11 no.3
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• pp.296-305
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• 2007

The HiLow, a hierarchical routing protocol for 6LoWPAN, needs smaller memory allocation and energy than other routing protocols. However, the HiLow has a weak point that does not provide the optimized routing path. In this paper, we propose the algorithm that can find the optimum next hop using neighboring nodes around the source node as well as hierarchical routing path information. We evaluate the performance of proposed algorithm using the computer simulation, and we can acquire results that decreases a number of hop count and transmitted message.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1462-1470
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• 2013

This paper proposes an SWAD-KNH(Sybil & Wormhole Attack Detection using Key, Neighbor list and Hop count) technique which consists of an SWAD(Sybil & Wormhole Attack Detection) module detecting an Worm attack and a KGDC(Key Generation and Distribution based on Cluster) module generating and an sense node key and a Group key by the cluster and distributing them. The KGDC module generates a group key and an sense node key by using an ECDH algorithm, a hash function, and a key-chain technique and distributes them safely. An SWAD module strengthens the detection of an Sybil attack by accomplishing 2-step key acknowledgement procedure and detects a Wormhole attack by using the number of the common neighbor nodes and hop counts of an source and destination node. As the result of the SWAD-KNH technique shows an Sybil attack detection rate is 91.2% and its average FPR 3.82%, a Wormhole attack detection rate is 90%, and its average FPR 4.64%, Sybil and wormhole attack detection rate and its reliability are improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.921-928
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• 2017

Unlike wired networks, broadcasting in wireless networks can transmit data to several nodes at a time in a single transmission. The omnidirectional broadcasting of node in wireless networks simultaneously reaches all neighboring nodes. In this paper, we propose a greedy algorithm to solve the minimum power broadcasting problem that minimizes the total transmission power when broadcasting in wireless networks. The proposed algorithm uses a neighborhood list which is a set of nodes that can transmit messages within the maximum transmission range of each node, and among the transmitting nodes that have received the data, the node having the largest number of the neighboring nodes firstly transmits the data to neighboring node. The performance of the proposed algorithm was evaluated by computer simulation, and was compared with existing algorithms in terms of total transmission power and broadcasting frequency for broadcasting to all nodes. Experiment results show that the proposed algorithm outperforms the conventional algorithms.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.314-317
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• 2013

본 논문에서는 수시로 차량이 빠르게 이동하고 차량 밀도가 변화하는 그리드 형태의 도로로 구성된 도심의 VANET 환경에서 패킷 전송 성공률을 높일 수 있는 다중경로 패킷전송기법을 제안하였다. 다중경로 패킷전송기법은 이웃노드 리스트의 정보를 이용하여 목적지까지 다중경로를 정한 후 도달가능성이 높은 순서대로 1개 이상의 다중경로로 패킷을 전송하는 방법이다. 다중경로가 발생할 가능성이 높은 그리드 형태의 도로환경에서 목적지까지의 거리 및 차량 밀도를 기반으로 다중경로를 선정하고 각 경로 별로 패킷 프레임에 선호경로 및 Trace 등의 정보를 추가하여 Local Maximum에 빠질 확률을 낮추고 경로 단절로 인한 경로 복구와 그에 따른 경로 중복 및 패킷 전송지연을 방지하여 패킷 단절률을 낮추고 패킷 전송 성공률을 향상 시킬 수 있다.

• Journal of Intelligence and Information Systems
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• v.13 no.1
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• pp.1-14
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• 2007

Character images for the background screen of cell phones are one of the fast growing sectors of the mobile content market. However, character image buyers currently experience tremendous difficulties in searching for desired images due to the awkward image search process. Content-based image retrieval (CBIR) widely used for image retrieval could be a good candidate as a solution to this problem, but it needs to overcome the limitation of the mobile Internet environment where an initial query set (IQS) cannot be easily provided as in the PC-based environment. We propose a new approach, IQS-AutoGen, which automatically generates an initial query set for CBIR on the mobile Internet. The approach applies the collaborative filtering (CF), a well-known recommendation technique, to the CBIR process by using users' preference information collected during the relevance feedback process of CBIR. The results of the experiment using a PC-based prototype system show that the proposed approach successfully satisfies the initial query requirement of CBIR in the mobile Internet environment, thereby outperforming the current image search process on the mobile Internet.