• Title/Summary/Keyword: Markov processes

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Performance Evaluation of Multiservice Network Switch for Dynamic Constant-and Adaptive-rate Services (동적인 고정 및 가변 전송을 서비스를 위한 다중 서비스 네트워크 스위치의 성능 분석)

  • Lee, Tae-Jin
    • The KIPS Transactions:PartC
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    • v.9C no.3
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    • pp.399-406
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    • 2002
  • We consider design of multiservice network link, in which connections of constant- and adaptive-rate services arrive and leave dynamically. We propose performance analysis and design methods of these dynamic multiservice networks. A multiservice network link is modeled by a Markov chain, and data rates for adaptive-rate connections are derived using QBD (Quasi-Birth-Death) processes and matrix-geometric equations. We estimate average number of adaptive-rate connections, average data rate and average connection delay. The performance of constant-rate connections is determined from the blocking probability of the connections. Based on the performance of constant-and adaptive- rate connections, we propose a design methods of a network link to satisfy performance requirements of constant- and adaptive-rate connections (data rates, delay, blocking probability). Our methods can be used for the analysis and design of network switch supporting dynamic data and voice (video) traffic simultaneously.

Subsequent application of self-organizing map and hidden Markov models infer community states of stream benthic macroinvertebrates

  • Kim, Dong-Hwan;Nguyen, Tuyen Van;Heo, Muyoung;Chon, Tae-Soo
    • Journal of Ecology and Environment
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    • v.38 no.1
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    • pp.95-107
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    • 2015
  • Because an ecological community consists of diverse species that vary nonlinearly with environmental variability, its dynamics are complex and difficult to analyze. To investigate temporal variations of benthic macroinvertebrate community, we used the community data that were collected at the sampling site in Baenae Stream near Busan, Korea, which is a clean stream with minimum pollution, from July 2006 to July 2013. First, we used a self-organizing map (SOM) to heuristically derive the states that characterizes the biotic condition of the benthic macroinvertebrate communities in forms of time series data. Next, we applied the hidden Markov model (HMM) to fine-tune the states objectively and to obtain the transition probabilities between the states and the emission probabilities that show the connection of the states with observable events such as the number of species, the diversity measured by Shannon entropy, and the biological water quality index (BMWP). While the number of species apparently addressed the state of the community, the diversity reflected the state changes after the HMM training along with seasonal variations in cyclic manners. The BMWP showed clear characterization of events that correspond to the different states based on the emission probabilities. The environmental factors such as temperature and precipitation also indicated the seasonal and cyclic changes according to the HMM. Though the usage of the HMM alone can guarantee the convergence of the training or the precision of the derived states based on field data in this study, the derivation of the states by the SOM that followed the fine-tuning by the HMM well elucidated the states of the community and could serve as an alternative reference system to reveal the ecological structures in stream communities.

Towards the Saturation Throughput Disparity of Flows in Directional CSMA/CA Networks: An Analytical Model

  • Fan, Jianrui;Zhao, Xinru;Wang, Wencan;Cai, Shengsuo;Zhang, Lijuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.4
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    • pp.1293-1316
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    • 2021
  • Using directional antennas in wireless Ad hoc networks has many superiorities, including reducing interference, extending transmission range, and increasing space division multiplexing. However, directional transmission introduces two problems: deafness and directional hidden terminals problems. We observe that these problems result in saturation throughput disparity among the competing flows in directional CSMA/CA based Ad hoc networks and bring challenges for modeling the saturation throughput of the flows. In this article, we concentrate on how to model and analyze the saturation throughput disparity of different flows in directional CSMA/CA based Ad hoc networks. We first divide the collisions occurring in the transmission process into directional instantaneous collisions and directional persistent collisions. Then we propose a four-dimensional Markov chain to analyze the transmission state for a specific node. Our model has three different kinds of processes, namely back-off process, transmission process and freezing process. Each process contains a certain amount of continuous time slots which is defined as the basic time unit of the directional CSMA/CA protocols and the time length of each slot is fixed. We characterize the collision probabilities of the node by the one-step transition probability matrix in our Markov chain model. Accordingly, we can finally deduce the saturation throughput for each directional data stream and evaluate saturation throughput disparity for a given network topology. Finally, we verify the accuracy of our model by comparing the deviation of analytical results and simulation results.

Flood Frequency Analysis with the consideration of the heterogeneous impacts from TC and non-TC rainfalls: application to daily flows in the Nam River Basin, South Korea

  • Alcantara, Angelika;Ahn, Kuk-Hyun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.121-121
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    • 2020
  • Varying dominant processes, including Tropical Cyclone (TC) and non-TC rainfall events, have been known to drive the occurrence of precipitation in South Korea. With the changes in the pattern of the Earth's climate due to anthropogenic activities, nonstationarity or changes in the magnitude and frequency of these dominant processes have been separately observed for the past decades and are expected to continue in the coming years. These changes often cause unprecedented hydrologic events such as extreme flooding which pose a greater risk to the society. This study aims to take into account a more reliable future climate condition with two dominant processes. Diverse statistical models including the hidden markov chain, K-nearest neighbor algorithm, and quantile mappings are utilized to mimic future rainfall events based on the recorded historical data with the consideration of the varying effects of TC and non-TC events. The data generated is then utilized to the hydrologic model to conduct a flood frequency analysis. Results in this study emphasize the need to consider the nonstationarity of design rainfalls to fully grasp the degree of future flooding events when designing urban water infrastructures.

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Phoneme Recognition based on Two-Layered Stereo Vision Neural Network (2층 구조의 입체 시각형 신경망 기반 음소인식)

  • Kim, Sung-Ill;Kim, Nag-Cheol
    • Journal of Korea Multimedia Society
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    • v.5 no.5
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    • pp.523-529
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    • 2002
  • The present study describes neural networks for stereoscopic vision, which are applied to identifying human speech. In speech recognition based on stereoscopic vision neural networks (SVNN), the similarities are first obtained by comparing input vocal signals with standard models. They are then given to a dynamic process in which both competitive and cooperative processes are conducted among neighboring similarities. Through the dynamic processes, only one winner neuron is finally detected. In a comparative study, the two-layered SVNN was 7.7% higher in recognition accuracies than the hidden Markov model (HMM). From the evaluation results, it was noticed that SVNN outperformed the existing HMM recognizer.

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Copula modelling for multivariate statistical process control: a review

  • Busababodhin, Piyapatr;Amphanthong, Pimpan
    • Communications for Statistical Applications and Methods
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    • v.23 no.6
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    • pp.497-515
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    • 2016
  • Modern processes often monitor more than one quality characteristic that are referred to as multivariate statistical process control (MSPC) procedures. The MSPC is the most rapidly developing sector of statistical process control and increases interest in the simultaneous inspection of several related quality characteristics. Most multivariate detection procedures based on a multi-normality assumptions are independent, but there are many processes that assume non-normality and correlation. Many multivariate control charts have a lack of related joint distribution. Copulas are tool to construct multivariate modelling and formalizing the dependence structure between random variables and applied in several fields. From copula literature review, there are a few copula to apply in MSPC that have multivariate control charts, and represent a successful tool to identify an out-of-control process. This paper presents various types of copulas modelling for the multivariate control chart. The performance measures of the control chart are the average run length (ARL) and the average number of observations to signal (ANOS). Furthermore, a Monte Carlo simulation is shown when the observations were from an exponential distribution.

A buffer management scheme for ATM traffic with delay and loss priorities (ATM 트래픽의 지연 및 손실 우선순위 제어를 위한 버퍼 관리 기법)

  • 이문호;문영성;김병기
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.5
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    • pp.52-59
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    • 1996
  • The boroadband ISDN will transprot the traffics for a wide range of applications with different quality-of-service (QOS) requirements and the priorit control mechanism is an effective method to support multiple classes of services. This paper proposes a new mechanism to satisfy simultaneously the different levels of cell loss performance for the two classes of heterogeneous nonreal-time ATM traffics as well as the delay and loss requirements of real-time traffics. Its performance is analyzed using the stochastic integral approach with the cell arrivals of input streams modeled as markov modulated poisson processes.

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GENERALIZED $BARTOSZY\'{N}SKI'S$ VIRUS MODEL

  • Kim, Yong-Dai
    • Journal of the Korean Statistical Society
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    • v.35 no.4
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    • pp.397-407
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    • 2006
  • A new stochastic process is introduced for describing a mechanism of viruses. The process generalizes the $Bartoszy\'{n}ski's$ process ($Bartoszy\'{n}ski$, 1975a, 1975b, 1976) by allowing the stochastic perturbation between consecutive jumps to take into account the persistent infection (the infection without breaking infected cells). It is shown that the new process can be obtained by a weak limit of a sequence of Markov branching processes. Along with the construction of the new process, we study how the stochastic perturbation influences the risk of a symptom in an infected host. For this purpose, the quantal response model and the threshold model are investigated and compared through their induced survival functions.

Variable Sampling Interval Control Charts for Number of Defectives

  • Cho, Gyo-Young;Ahn, Young-Seon;Kim, Youn-Jin
    • Journal of Korean Society for Quality Management
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    • v.25 no.3
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    • pp.62-73
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    • 1997
  • Previous VSI control chart works have been done on quality variable whose distribution is normal. But there are many situations in which hte assumption of not a, pp.opriate. Also, in many industrial processes, the interest is to monitor the number of defectives. In this paper, we will take the existing properties of VSI control chart developed for the normal distribution and a, pp.y them to the np-chart based on the discrete binomial distribution. We will consider the CUSUM chart for the number of defectives. Here, the interesting object is to compute the VSI ATS for CUSUM control chart using Markov chain a, pp.oach and to compare FSI ATS and VSI ATS.

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Stochastically Dependent Sequential Acceptance Sampling Plans

  • Kim, Won-Kyung
    • Journal of Korean Society for Quality Management
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    • v.25 no.3
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    • pp.22-38
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    • 1997
  • In a traditional sequential acceptance sampling plan, it is assumed that the sampled items are independent each other. In this paper, stochastically dependent sequential acceptance sampling plans are dealt when there exists dependency between sampled items. Monte-Calro algorithm is used to find the acceptance and rejection probabilities of a lot. The number of defectives for the test to be accepted and rejected in probability ratio sequential test can be found by using these probabilities. The formula for measures of performance of these sampling plans is developed. Type I and II error probabilities are estimated by simulation. This research can be a, pp.ied to sequential sampling procedures in place of control charts where there is a recognized and necessary dependency during the production processes. Also, dependent multiple acceptance sampling plans can be derived by extending this sequential sampling procedure. As a numerical example, a Markov dependent process model is given, and the characteristics of the sampling plans are examined according to the change of the dependency factor.

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