• New & Renewable Energy
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• v.16 no.1
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• pp.15-24
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• 2020

For mechanical load testing of wind turbines, capture matrix is constructed for various range of wind speeds according to the international standard IEC 61400-13. The conventional method wastes considerable amount of data by its invalid data policy -segment data into 10 minutes then remove invalid ones. Previously, we have suggested an alternative way to save the total amount of data to build a capture matrix, but the efficient selection of data has been still under question. The paper introduces optimization algorithms to construct capture matrix with less data. Heuristic algorithm (simple stacking and lowest frequency first), population method (particle swarm optimization) and Q-Learning accompanied with epsilon-greedy exploration are compared. All algorithms show better performance than the conventional way, where the distribution of enhancement was quite diverse. Among the algorithms, the best performance was achieved by heuristic method (lowest frequency first), and similarly by particle swarm optimization: Approximately 28% of data reduction in average and more than 40% in maximum. On the other hand, unexpectedly, the worst performance was achieved by Q-Learning, which was a promising candidate at the beginning. This study is helpful for not only wind turbine evaluation particularly the viewpoint of cost, but also understanding nature of wind speed data.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.241-244
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• 2005

Many building detection methods mainly rely on line segments extracted from aerial or satellite imagery. Building detection methods based on line segments, however, are difficult to succeed in high resolution satellite imagery such as IKONOS imagery, for most buildings in IKONOS imagery have small size of roofs with low contrast between roof and background. In this paper, we propose an efficient method to extract line segments and group them at the same time. First, edge preserving filtering is applied to the imagery to remove the noise. Second, we segment the imagery by watershed method, which collects the pixels with similar intensities to obtain homogeneous region. The boundaries of homogeneous region are not completely coincident with roof boundaries due to low contrast in the vicinity of the roof boundaries. Finally, to resolve this problem, we set up snake model with segmented region boundaries as initial snake's positions. We used a greedy algorithm to fit a snake to roof boundary. Experimental results show our method can obtain more .correct roof boundary with small size and low contrast from IKONOS imagery. Snake algorithm, building roof detection, watershed segmentation, edge-preserving filtering

• Journal of Broadcast Engineering
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• v.15 no.6
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• pp.783-790
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• 2010

A two-way relay network provide improved spectral efficiency compared with a conventional one-way relay network by using either superposition coding or network coding. OFDMA network provides imptoved performance by adaptive resource allocation. In this paper, we propose a adaptive subcarrier allocation for a multiuser two-way OFDMA relay network. In the proposed algorithm, subcarriers are allocated to the user-pairs and relays to maximize the achievable sum-rate over all user-pairs while satisfying the minimum rate requirement for each user-pair. Simulation results show that the proposed algorithm provides improved performance compared with the static and greedy algorithms.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.164-165
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• 2008

전장에서 임무 수행중인 병력이나 탱크 등을 지원하거나 보호 동물의 활동을 모니터링 하는 센서 네트워크에서는 전송 정보뿐만 아니라 그러한 대상들의 위치를 악의적 추적자로부터 보호할 수 있어야 한다. 본 논문에서는 활동 소오스 노드처럼 메시지 전송은 진행하고 있지 않지만 위치가 보호되어야 할 대상과 근접한 휴면(dormant) 소오스 노드들을 고려한 소오스 위치 보호 라우팅 기법 GSLP(GPSR-based Source-Location Privacy)를 제안한다. GSLP는 알고리즘의 간결성과 신장성(scalability)이 뛰어난 GPSR(greedy perimeter stateless routing)을 확장하여 메시지 전달 노드를 선정할 때 일정 확률로 임의의 이웃 노드를 선택하는 한편, perimeter 라우팅을 적용하여 소오스 노드들을 우회하도록 하여 위치를 보호하도록 하였다. 시뮬레이션 결과, 기존의 대표적인 소오스 위치 보호 라우팅 프로토콜인 PR-SP(Phantom Routing-Single Path)에 비해 GSLP는 휴면 소오스 노드들의 수에 거의 관계없이 높은 안전 기간(전송 메시지 수)을 일정하게 제공하면서도 전달 지연(경로의 평균 홉(hop) 수)은 도착지와의 최단 홉 수의 약 두 배 이내에 머물러 대규모 센서 네트워크에서의 소오스의 위치를 보호하기 위한 방안으로 적합한 것으로 평가되었다.

• Journal of Korean Medical classics
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• v.20 no.2
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• pp.125-135
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• 2007

Eum Syndrom include symptoms which is because by the cold thingsand by the infection of SamEum of TaeEum, SoEum, GualEum in Treatise On Exogenous Febrile Diseases(傷寒論). After Wang HoGo, many medical people had proceed the research of Eum Syndrom, but recently, we have almost never or no nothing research about that. So, I want to make modern base of Eum syndrom, and researched mainly for the "YinZhengLueLi". That can be summarized like below. Eum Syndrom shows firstly red face, tremor, waist-and-leg heaviness, lastly body heaviness, fatigue, narcolepsy, congestion of the pupils because of from exogenous attack of wind-cold, impairment of spleen due to Cold things, and dew and mist and rain and damp's invation by mouth and nose, greedy of sexual desire, So, in the diagnosis of Eum Syndrom, we have to look over precisely the color and pulse, especially, by pulse. We can know that, he used the prescription which are have heating kidney function, Byuklyuksan, Jungyangsan, Huahamsan, Huiyangdan, Baneumdan etc, and the prescription which are have strengthening spleen and kidney, Bujasan, Yukgyesan, Bakchulsan etc. So, we can know that he was very interested in deficiency and cold of kidney's function. While, he newly made the prescriptions of Sinchultang, Bakchultang, Huanggitang, Jujunghuan, and he used various prescriptions.

• Environmental and Resource Economics Review
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• v.15 no.5
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• pp.799-826
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• 2006

Combining recent advances in causal flows with time series analysis, relationships among eight North American natural gas spot market prices are examined. Results indicate that price discovery tends to occur in excess demand regions and move to excess supply regions. Across North America, the U.S. Midwest region represented by Chicago spot market is the most important market for price discovery. The Ellisburg-Leidy Hub in Pennsylvania is important in price discovery, especially for markets in the eastern two-thirds of the U.S. Malin Hub in Oregon is important for the western markets including the AECO Hub in Alberta, Canada.

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.193-199
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• 2005

One of the important fields for heuristics algorithm is how to balance between Intensificationand Diversification. Ant Colony System(ACS) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem(TSP). In this paper, we propose Multi Colony Interaction Ant Model that achieves positive negative interaction through elite strategy divided by intensification strategy and diversification strategy to improve the performance of original ACS. And, we apply multi colony interaction ant model by this proposed elite strategy to TSP and compares with original ACS method for the performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4B
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• pp.255-269
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• 2006

The differentiated services(DiffServ) architecture provides packet level service differentiation through the simple and predefined Per-Hop Behaviors(PHBs). The Assured Forwarding(AF) PHB proposed as the assured services uses the RED-in/out(RIO) approach to ensusre the expected capacity specified by the service profile. However, the AF PHB fails to give good QoS and fairness to the TCP flows. This is because OUT(out- of-profile) packet droppings at the RIO buffer are unfair and sporadic during only network congestion while the TCP's congestion control algorithm works with a different round trip time(RTT). In this paper, we propose an Adaptive Regulating Drop(ARD) marker, as a novel dropping strategy at the ingressive edge router, to improve TCP fairness in assured services without a decrease in the link utilization. To drop packets pertinently, the ARD marker adaptively changes a Temporary Permitted Rate(TPR) for aggregate TCP flows. To reduce the excessive use of greedy TCP flows by notifying droppings of their IN packets constantly to them without a decrease in the link utilization, according to the TPR, the ARD marker performs random early fair remarking and dropping of their excessive IN packets at the aggregate flow level. Thus, the throughput of a TCP flow no more depends on only the sporadic and unfair OUT packet droppings at the RIO buffer in the core router. Then, the ARD marker regulates the packet transmission rate of each TCP flow to the contract rate by increasing TCP fairness, without a decrease in the link utilization.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.206-210
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• 2009

In this paper, we propose a new routing scheme based on multi-path routing which provides uniform energy consumption for all nodes. This scheme adds a new type of root node for constructing multi-path. The sink node delegates some partial roles to these root nodes. Such root nodes carry out path establishment independently. As a result, each nodes consume energy more uniformly and the network life-time will be extended. Through simulation, we confirmed that energy consumption of the whole network is scattered and the network life-time is extended. Moreover, we show that the proposed routing scheme improves the performance of network compared to previous routing strategies as the number of source nodes increases.

• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.330-336
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• 2011

In this paper, we propose a new method to improve the performance of supervector linear kernel SVM (Support Vector Machine) for speaker identification. This method is based on splitting one training datum into several pieces of utterances. We use four different databases for evaluating performance and use PCA (Principal Component Analysis), GKPCA (Greedy Kernel PCA) and KMDA (Kernel Multimodal Discriminant Analysis) for feature enhancement. As a result, the proposed method shows improved performance for speaker identification using supervector linear kernel SVM.