• 제목/요약/키워드: Clustering Effect

검색결과 296건 처리시간 0.03초

A Signal Characteristic Based Cluster Scheme for Aeronautical Ad Hoc Networks

  • Tian, Yu;Ma, Linhua;Ru, Le;Tang, Hong;Song, Bo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권10호
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    • pp.3439-3457
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    • 2014
  • Clustering is an effective method for improving the performance of large scale mobile ad hoc networks. However, when the moving speed is very fast, the topology changes quickly, which leads to frequent cluster topology updates. The drastically increasing control overheads severely threaten the throughput of the network. SCBCS (Signal Characteristic Based Cluster Scheme) is proposed as a method to potentially reduce the control overheads caused by cluster formation and maintenance in aeronautical ad hoc networks. Each node periodically broadcasts Hello packets. The Hello packets can be replaced by data packets, which preserve bandwidth. The characteristics of the received packets, such as the Doppler shift and the power of two successive Hello packets, help to calculate the relative speed and direction of motion. Then, the link connection lifetime is estimated by the relative speed and direction of motion. In the clustering formation procedure, the node with the longest estimated link connection time to its one-hop neighbors is chosen as the cluster head. In the cluster maintenance procedure, re-affiliation and re-clustering schemes are designed to keep the clusters more stable. The re-clustering phenomenon is reduced by limiting the ripple effect. Simulations have shown that SCBCS prolongs the link connection lifetime and the cluster lifetime, which can reduce the topology update overheads in highly dynamic aeronautical ad hoc networks.

Extreme value modeling of structural load effects with non-identical distribution using clustering

  • Zhou, Junyong;Ruan, Xin;Shi, Xuefei;Pan, Chudong
    • Structural Engineering and Mechanics
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    • 제74권1호
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    • pp.55-67
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    • 2020
  • The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.

차량 네트워크 환경에서 도로 기반 시설을 이용한 클러스터 헤드 선택 알고리즘 (Clustering Algorithm with using Road Side Unit(RSU) for Cluster Head(CH) Selection in VANET)

  • 권혁준;권영호;이병호
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2014년도 추계학술대회
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    • pp.620-623
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    • 2014
  • 차량은 빠르게 변하는 속도와 도로의 상황에 따라 속도가 변하는 특성을 가지고 있기 때문에 이들 간의 통신을 위한 네트워크 구성도 빠르게 변한다. 이러한 특성 때문에 차량 네트워크 (Vehicular Ad-hoc Network: VANET)에서 신뢰성 있는 라우팅을 적용하는 것이 쉽지 않다. VANET 환경에서 신뢰성 있는 라우팅을 적용하기 위한 방법에 하나로 클러스터링 기법이 있다. 클러스터링이란 클러스터 헤드(Cluster Head : CH)를 중심으로 차량들을 그룹으로 묶어 통신 및 관리하는 것이다. 따라서 클러스터 내의 어떤 노드(차량)를 클러스터 헤드로 선택하는가에 따라 해당 클러스터링의 오버헤드 감소와 네트워크의 안정성 및 효율성이 좌우된다. 본 논문은 기존의 클러스터링 알고리즘들과 달리 도로 기반 시설인 RSU(Road Side Unit)를 활용하는 클러스터 헤드 선택 알고리즘을 소개한다. RSU를 통한 노드들의 속도와 거리 계산 값으로 클러스터 헤드 우선순위를 결정함으로써 기존의 알고리즘들 보다 안정적이고 효율적인 클러스터링 알고리즘을 제안한다.

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민간주도 집단화 거버넌스 구축에 의한 노후산업단지 재생사업의 효과분석 - 공공주도 사업과의 비교를 중심으로 - (The Analysis of the effect of the Regeneration Project of the Decrepit Industrial Complex by the Private-led Aggregation Governance - Focusing on the comparison with the Public-led Project -)

  • 정현진;권영상
    • 대한건축학회논문집:계획계
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    • 제34권10호
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    • pp.131-142
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    • 2018
  • Being dealt in Alfred Weber's Theory of the location of Industries, a lot of economic benefits can be obtained through aggregation and clustering of industrial facilities, which derived to the development of industrial complexes in Korea. However, with the IMF economic crisis as well as various institutional changes, the framework of aggregation and clustering of industries is broken, which led to individual developments that took place without any consideration of surrounding industries. For reformation of these condition of industrial complexes, national government-led regeneration projects are being carried out currently. However, national government-led projects mainly focus on profitable projects such as officetel and hotel that are irrelevant to exist composition of industrial complexes which is usually manufacturing base industries and are unable to solve the fundamental problems of industrial complexes. Thus, a necessity of industry clustering is deduced through case analysis of actual private-led manufacturing industry cluster with governance and analysis of benefits on financial, spatial and environmental aspects. In addition, implications on the necessity follow base on factorial analysis on the benefit of clustering development than individual development as well as analysis on the measures taken for successful clustering.

이단계표본추출을 이용한 소결핵병 유병률 추정 (Two-stage Sampling for Estimation of Prevalence of Bovine Tuberculosis)

  • 박선일
    • 한국임상수의학회지
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    • 제28권4호
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    • pp.422-426
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    • 2011
  • For a national survey in which wide geographic region or an entire country is targeted, multi-stage sampling approach is widely used to overcome the problem of simple random sampling, to consider both herd- and animallevel factors associated with disease occurrence, and to adjust clustering effect of disease in the population in the calculation of sample size. The aim of this study was to establish sample size for estimating bovine tuberculosis (TB) in Korea using stratified two-stage sampling design. The sample size was determined by taking into account the possible clustering of TB-infected animals on individual herds to increase the reliability of survey results. In this study, the country was stratified into nine provinces (administrative unit) and herd, the primary sampling unit, was considered as a cluster. For all analyses, design effect of 2, between-cluster prevalence of 50% to yield maximum sample size, and mean herd size of 65 were assumed due to lack of information available. Using a two-stage sampling scheme, the number of cattle sampled per herd was 65 cattle, regardless of confidence level, prevalence, and mean herd size examined. Number of clusters to be sampled at a 95% level of confidence was estimated to be 296, 74, 33, 19, 12, and 9 for desired precision of 0.01, 0.02, 0.03, 0.04, 0.05, and 0.06, respectively. Therefore, the total sample size with a 95% confidence level was 172,872, 43,218, 19,224, 10,818, 6,930, and 4,806 for desired precision ranging from 0.01 to 0.06. The sample size was increased with desired precision and design effect. In a situation where the number of cattle sampled per herd is fixed ranging from 5 to 40 with a 5-head interval, total sample size with a 95% confidence level was estimated to be 6,480, 10,080, 13,770, 17,280, 20.925, 24,570, 28,350, and 31,680, respectively. The percent increase in total sample size resulting from the use of intra-cluster correlation coefficient of 0.3 was 22.2, 32.1, 36.3, 39.6, 41.9, 42.9, 42,2, and 44.3%, respectively in comparison to the use of coefficient of 0.2.

가구조사를 위한 이단추출 표본설계에서의 집락선택 (Choosing clusters for two-stage household surveys)

  • 박인호
    • Journal of the Korean Data and Information Science Society
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    • 제27권2호
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    • pp.363-372
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    • 2016
  • 우리나라 가구조사는 흔히 통계청의 조사구를 집락으로 사용한 이단추출의 자체가중 표본설계의 형태로 진행된다. 집락구조는 모집단내 개체변동성을 집락간과 집락내 분산으로 분해되기 때문에 이와 연관된 표본집락수와 집락내 표본수의 결정은 표본추정에 영향을 미치게 된다. 하지만 조사구의 규모, 노후화, 가구명부 접근불가 등의 여러가지 이유로 집계구와 같은 대안적 집락선택이 고려되기도 한다. 또한 2015 인구주택총조사부터는 전통적 가구방문조사 방식에서 행정자료를 이용한 등록센서스 형태로 바뀜에 따라 기존 조사구의 형태나 규모의 변경되어 구축되는 것으로 알려져 있다. 본 논문에서는 집락추출을 반영한 설계효과식을 통해 계통적 혹은 내포적 구성을 갖는 집락들의 선택이 주는 분산식 차이를 유도하고, 주어진 표본크기에서 동일한 분산을 갖는 집락구조별 표본할당에 대해 살펴보았다. 미국 매릴랜드주 앤어룬델 카운티 자료를 사용하여 우리나라 조사구와 집계구와 다소 유사한 사례연구를 포함하였다. 조사변수별로 집락통합이 주는 동일성 계수의 변화는 같지 않으며 이에 따라 집락구조에 따른 표본할당이 집락표본수와 더불어 종합적으로 고려되어야 할 것이다.

Digital Item Purchase Model in SNS Channel Applying Dynamic SNA and PVAR

  • LEE, Hee-Tae;JUNG, Bo-Hee
    • 유통과학연구
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    • 제18권3호
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    • pp.25-36
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    • 2020
  • Purpose: Based on previous researches on social factors of digital item purchase in digital contents distribution platforms such as SNS, we aim to develop the integrated model that accounts for the dynamic and interactive relationship between social structure indicators and digital item purchase. Research design, data and methodology: A PVAR model was used to capture endogenous and dynamic relationships between digital item purchase and network indicators. Results: We find that there exist considerable endogenous and dynamic relationships between digital item purchase and network structure variables. Not only lagged in-degree and out-degree but also in-closeness and out-closeness centrality have significant and positive impacts on digital item purchase. Lagged clustering has a significant and negative effect on digital item purchase. Lagged purchase has a significant and positive impact just on the present in-closeness and out-closeness centrality; but there is no significant effect of lagged purchase on the other two degree variables and clustering coefficient. We also find that both closeness centralities have much higher carryover effect on digital item purchase and that the elasticity of both closeness centralities on the purchase of digital items is even higher than that of other network structure variables. Conclusions: In-closeness and out-closeness are the most influential factors among social structure variables of this study on digital item purchase.

네트워크 카메라 영상에서 원근감 효과를 고려한 군집 움직임 분석 (The Crowd Activity Analysis based on Perspective Effect in Network Camera)

  • 이상걸;박현준;차의영
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2008년도 추계종합학술대회 B
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    • pp.415-418
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    • 2008
  • 본 논문에서는 특정 지역을 연속해서 촬영하는 고정된 카메라 영상에서 사람들의 움직임을 검출하고 움직임을 분석하여 정량화 하는 방법을 제안한다. 먼저 배경 영상을 획득하기 위하여 일정 시간동안의 입력 영상을 누적하고 평균값으로 정규화 한다. 그리고 영상을 계속 누적하여 배경 영상을 실시간으로 갱신한다. 다음으로 획득된 배경 영상과 현재 영상에 대하여 차영상과 이진화를 수행하고 팽창 연산과 연결 성분 분석으로 잡영을 제거한다. 그리고 잡영이 제거된 영상에서 원근감 효과를 고려하는 가중치를 적용하여 움직임이 있는 객체를 클러스터링 하는 수정된 ART2 클러스터링 방법을 제안한다. 마지막으로 클러스터링 결과 정보를 이용하여 움직임을 정량화 한다. 제안하는 방법을 실내 환경에 설치된 네트워크 카메라로부터 영상을 획득하여 실험한 결과, 영상의 원근감 효과에 따라 군집 크기가 차이남에도 강인하게 분석할 수 있음을 확인하였다.

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The Kaiser Rocket Effect in Cosmology

  • Bahr-Kalus, Benedict
    • 천문학회보
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    • 제46권2호
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    • pp.43.3-43.3
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    • 2021
  • The peculiar motion of the observer, if not (or only imperfectly) accounted for, is bound to induce a well-defined clustering signal in the distribution of galaxies. This spurious signal is related to the Kaiser rocket effect. We examined the amplitude of this effect and discuss possible implications for analysis and interpretation of future cosmological surveys. We found that it can in principle bias very significantly the inference of cosmological parameters, especially for primordial non-Gaussianity.

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A Reliability Model of Wind Farm Considering the Complex Terrain and Cable Failure Based on Clustering Algorithm

  • Liu, Wenxia;Chen, Qi;Zhang, Yuying;Qiu, Guobing;Lin, Chenghui
    • Journal of Electrical Engineering and Technology
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    • 제9권6호
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    • pp.1891-1899
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    • 2014
  • A reliability model of wind farm located in mountainous land with complex terrain, which considers the cable and wind turbine (WT) failures, is proposed in this paper. Simple wake effect has been developed to be applied to the wind farm in mountainous land. The component failures in the wind farm like the cable and WT failures which contribute to the wind farm power output (WFPO) and reliability is investigated. Combing the wind speed distribution and the characteristic of wind turbine power output (WTPO), Monte Carlo simulation (MCS) is used to obtain the WFPO. Based on clustering algorithm the multi-state model of a wind farm is proposed. The accuracy of the model is analyzed and then applied to IEEE-RTS 79 for adequacy assessment.