• Title/Summary/Keyword: 마르

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Throughput analysis of DCF protocol for packet applied to the nonmarkov process in the wireless LAN (비 마르코프 과정을 적용한 무선 LAN의 DCF 패킷 처리율 분석)

  • Ha, Eun-Sil
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.8 no.6
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    • pp.1410-1418
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    • 2007
  • This paper analyzes the throughput of DCF protocol at the MAC layer in the 802.11a wireless LAN. The throughput of DCF protocol is related on probability of backoff, depends on retransmission of each terminal. This paper applied to nonmarcov discrete model for each terminal BER in the base station versus the packet throughput is progressing with the data rate of 6,12,24,54 Mbps, We find the fact that the less the data rate be the higher the throughput. We also find from the throughput calculation by means of traffic intensity in OFDM wireless LAN.

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Gait Recognition using Modified Motion Silhouette Image (개선된 움직임 실루엣 영상을 이용한 발걸음 인식에 관한 연구)

  • Hong Sung-Jun;Lee Hee-Sung;Oh Kyong-Sae;Kim Eun-Tai
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.3
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    • pp.266-270
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    • 2006
  • In this paper, we propose the human identification system based on Hidden Markov model using gait. Since each gait cycle consists of a set of continuous motion states and transition across states has probabilistic dependences, individual gait can be modeled using Hidden Markov model. We assume that individual gait consists of N discrete transitions and we propose gait feature representation, Modified Motion Silhouette Image (MMSI) to represent and recognize individual gait. MMSI is defined as a gray-level image and it provides not only spatial information but also temporal information. The experimental results show gait recognition performance of proposed system.

A Design and Implementation of Reliability Analyzer for Embedded Software using Markov Chain Model and Unit Testing (내장형 소프트웨어 마르코프 체인 모델과 단위 테스트를 이용한 내장형 소프트웨어 신뢰도 분석 도구의 설계와 구현)

  • Kwak, Dong-Gyu;Yoo, Chae-Woo;Choi, Jae-Young
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.12
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    • pp.1-10
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    • 2011
  • As requirements of embedded system get complicated, the tool for analyzing the reliability of embedded software is being needed. A probabilistic modeling is used as the way of analyzing the reliability of a software and to apply it to embedded software controlling multiple devices. So, it is necessary to specialize that to embedded software. Also, existing reliability analyzers should measure the transition probability of each condition in different ways and doesn't consider reusing the model once used. In this paper, we suggest a reliability analyzer for embedded software using embedded software Markov chin model and a unit testing tool. Embedded software Markov chain model is model specializing Markov chain model which is used for analyzing reliability to an embedded software. And a unit testing tool has host-target structure which is appropriate to development environment of embedded software. This tool can analyze the reliability more easily than existing tool by automatically measuring the transition probability between units for analyzing reliability from the result of unit testing. It can also directly apply the test result updated by unit testing tool by representing software model as a XML oriented document and has the advantage that many developers can access easily using the web oriented interface and SVN store. In this paper, we show reliability analyzing of a example by so doing show usefulness of reliability analyzer.

Modeling the Spatial Dynamics of Urban Green Spaces in Daegu with a CA-Markov Model (CA-Markov 모형을 이용한 대구시 녹지의 공간적 변화 모델링)

  • Seo, Hyun-Jin;Jun, Byong-Woon
    • Journal of the Korean Geographical Society
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    • v.52 no.1
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    • pp.123-141
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    • 2017
  • This study predicted urban green spaces for 2020 based on two scenarios keeping or freeing the green-belt in the Daegu metropolitan city using a hybrid Cellular Automata(CA)-Markov model and analyzed the spatial dynamics of urban green spaces between 2009 and 2020 using a land cover change detection technique and spatial metrics. Markov chain analysis was employed to derive the transition probability for projecting land cover change into the future for 2020 based on two land cover maps in 1998 and 2009 provided by the Ministry of Environment. Multi-criteria evaluation(MCE) was adopted to develop seven suitability maps which were empirically derived in relation to the six restriction factors underlying the land cover change between the years 1998 and 2009. A hybrid CA-Markov model was then implemented to predict the land cover change over an 11 year period to 2020 based on two scenarios keeping or freeing the green-belt. The projected land cover for 2009 was cross-validated with the actual land cover in 2009 using Kappa statistics. Results show that urban green spaces will be remarkably fragmented in the suburban areas such as Dalseong-gun, Seongseo, Ansim and Chilgok in the year 2020 if the Daegu metropolitan city keeps its urbanization at current pace and in case of keeping the green-belt. In case of freeing the green-belt, urban green spaces will be fragmented on the fringes of the green-belt. It is thus required to monitor urban green spaces systematically considering the spatial change patterns identified by this study for sustainably managing them in the Daegu metropolitan city in the near future.

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Markov Chain Properties of Sea Surface Temperature Anomalies at the Southeastern Coast of Korea (한국 남동연안 이상수온의 마르코프 연쇄 성질)

  • Kang, Yong-Q.;Gong, Yeong
    • 한국해양학회지
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    • v.22 no.2
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    • pp.57-62
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    • 1987
  • The Markov chain properties of the sea surface temperature (SST) anomalies, namely, the dependency of the monthly SST anomaly on that of the previous month, are studied based on the SST data for 28years(1957-1984) at 5 stations in the southeastern coast of Korea. Wi classified the monthly SST anomalies at each station into the low, the normal and the high state, and computed transition probabilities between SST anomalies of two successive months The standard deviation of SST anomalies at each station is used as a reference for the classification of SST anomalies into 3states. The transition probability of the normal state to remain in the same state is about 0.8. The transition probability of the high or the low states to remain in the same state is about one half. The SST anomalies have almost no probability to transit from the high (the low) state to the low (the high) state. Statistical tests show that the Markov chain properties of SST anomalies are stationary in tine and homogeneous in space. The multi-step Markov chain analysis shows that the 'memory' of the SST anomalies at the coastal stations remains about 3 months.

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재료색인

  • Korean Bakers Association
    • 베이커리
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    • no.7 s.396
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    • pp.116-117
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    • 2001
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