• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.471-488
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• 2018

In this paper, we propose extending proportional hazards frailty models to allow a discrete distribution for the frailty variable. Having zero frailty can be interpreted as being immune or cured. Thus, we develop a new survival model induced by discrete frailty with zero-inflated power series distribution, which can account for overdispersion. This proposal also allows for a realistic description of non-risk individuals, since individuals cured due to intrinsic factors (immunes) are modeled by a deterministic fraction of zero-risk while those cured due to an intervention are modeled by a random fraction. We put the proposed model in a Bayesian framework and use a Markov chain Monte Carlo algorithm for the computation of posterior distribution. A simulation study is conducted to assess the proposed model and the computation algorithm. We also discuss model selection based on pseudo-Bayes factors as well as developing case influence diagnostics for the joint posterior distribution through ${\psi}-divergence$ measures. The motivating cutaneous melanoma data is analyzed for illustration purposes.

• Journal of the Korean Society for Library and Information Science
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• v.14
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• pp.93-130
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• 1987

Scientific communication is an information exchange activity between scientists. Scientific communication is carried out in a variety of informal and formal ways. Basically, informal communication takes place by word of mouth, whereas formal communication occurs via the written word. Science is a highly interdependent activity in which each scientist builds upon the work of colleagues past and present. Consequently, science depends heavily on scientific communication. In this study, three mathematical models, namly Brillouin measure, logistic equation, and Markov chain are examined. These models provide one with a means of describing and predicting the behavior of scientific communication process. These mathematical models can be applied to construct quality filtering algorithms for subject literature which identify synthesized elements (authors, papers, and journals). Each suggests a different type of application. Quality filtering for authors can be useful to funding agencies in terms of identifying individuals doing the best work in a given area or subarea. Quality filtering with respect to papers can be useful in constructing information retrieval and dissemination systems for the community of scientists interested m the field. The quality filtering of journals can be a basis for the establishment of small quality libraries based on local interests in a variety of situations, ranging from the collection of an individual scientist or physician to research centers to developing countries. The objective of this study is to establish the theoretical framework for informetrics which is defined as the quantitative analysis of scientific communication, by investigating mathematical models of scientific communication.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10d
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• pp.782-785
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• 2006

셀 내의 모바일 노드들의 수가 많고 셀 간의 이동이 빈번한 고속 모바일 네트워크에서는 기존 802.11 프로토콜로는 좋은 성능을 보장할 수 없다. 셀 내에 새로 진입한 노드들은 네트워크에 참여하기 위해 자신의 존재 여부를 알려야 한다. 802.11 표준에서는 이러한 선행되어야 할 작업을 스캐닝, 인증, 결합의 3가지 단계로 규정한다. 이 등록 작업은 셀 내의 다른 데이터 패킷을 보내려는 노드들과의 경쟁을 통해 이루어진다. 그러므로 셀 내의 노드 수가 많을 경우 기본적인 통신을 위해 선행되어야 할 등록 작업이 지연될 수 있다. 802.11 표준에서는 DCF 방식을 기본 매체 접근 프로토콜로 한다. DCF는 BEB (Binary Exponential Backoff) 알고리즘을 기반으로 한다. BEB 알고리즘의 여러 문제점[5]으로 이를 대체할 알고리즘이 연구되어왔으며, 그룹화를 통해 경쟁하는 노드의 수를 줄이는 방법도 고려되었다. 본 논문에서는 802.11의 성능 평가를 위한 모델링에 Markov chain을 이용한 논문[1]을 기반으로 하나의 노드가 등록 작업에 소요하는 평균 시간을 해석적으로 계산하였다. 셀 내의 전체 노드 수에 증가함에 따라 등록 시간을 계산하고, 직접 시뮬레이션을 통해 수식으로 얻어진 결과와 비교하였다. 또한 그룹화를 시뮬레이션 하여 전체 노드 수에 따라서 적절한 그룹 수의 조정이 그룹화하지 않았을 경우보다 더 나은 성능을 보여줄 수 있다는 것을 보였다.

• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.286-291
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• 2017

With regards to heading estimation using gyroscope and magnetometer signals, magnetic disturbance added in the magnetometer signals is a main degradation factor in the estimation accuracy. Although there are a number of existing mechanisms that may properly compensate for the magnetic disturbances, they are designed to react only to the magnetic disturbances, but not to the time derivative of disturbances. Note that the sensors may experience abrupt changes in the magnetic disturbances, particularly for ambulatory applications. This paper proposes a magnetic disturbance model-embedded heading estimation filter for time-varying magnetic environments. The proposed magnetic disturbance model is based on a first-order Markov chain with a conditional switching technique depending on the time derivative of disturbances. Once a high amount of derivative is detected, the corrupted magnetometer signals are discarded to protect the filter from them. In our experimental results, the averaged heading error of tests was $1.46^{\circ}$, while that of the original approach without switching was $5.75^{\circ}$.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1869-1880
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• 2014

Wireless communication is one of most active areas in modern communication researches, QoS (Quality of Service) assurance is very important for wireless communication systems design, especially for applications such as streaming video etc., which requires strict QoS assurance. The modern wireless networks multi-layer protocol stack structure results in QoS metrics layered and acting in cascade and QoS metrics vertical mapping between protocol layers. Based on virtual buffer between protocol layers and queuing technology, a unified layered QoS mapping framework is proposed in this paper, in which we first propose virtual queue concept, give a novelty united neighboring protocol layers QoS metric mapping framework, and analysis method based on dicerete-time Markov chain, and numerical results show that our proposed framework represents a significant improvement over previous model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1532-1553
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• 2014

Radio spectrum is a precious resource and characterized by fixed allocation policy. However, a large portion of the allocated radio spectrum is underutilized. Conversely, the rapid development of ubiquitous wireless technologies increases the demand for radio spectrum. Cognitive Radio (CR) methodologies have been introduced as a promising approach in detecting the white spaces, allowing the unlicensed users to use the licensed spectrum thus realizing Dynamic Spectrum Access (DSA) in an effective manner. This paper proposes a generalized framework for DSA between the licensed (primary) and unlicensed (secondary) users based on Continuous Time Markov Chain (CTMC) model. We present a spectrum access scheme in the presence of sensing errors based on CTMC which aims to attain optimum spectrum access probabilities for the secondary users. The primary user occupancy is identified by spectrum sensing algorithms and the sensing errors are captured in the form of false alarm and mis-detection. Simulation results show the effectiveness of the proposed spectrum access scheme in terms of the throughput attained by the secondary users, throughput optimization using optimum access probabilities, probability of interference with increasing number of secondary users. The efficacy of the algorithm is analyzed for both imperfect spectrum sensing and perfect spectrum sensing.

• Communications for Statistical Applications and Methods
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• v.24 no.6
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• pp.605-625
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• 2017

This paper presents proportional odds cure models to allow spatial correlations by including spatial frailty in the interval censored data setting. Parametric cure rate models with independent and dependent spatial frailties are proposed and compared. Our approach enables different underlying activation mechanisms that lead to the event of interest; in addition, the number of competing causes which may be responsible for the occurrence of the event of interest follows a Geometric distribution. Markov chain Monte Carlo method is used in a Bayesian framework for inferential purposes. For model comparison some Bayesian criteria were used. An influence diagnostic analysis was conducted to detect possible influential or extreme observations that may cause distortions on the results of the analysis. Finally, the proposed models are applied for the analysis of a real data set on smoking cessation. The results of the application show that the parametric cure model with frailties under the first activation scheme has better findings.

• Korean Management Science Review
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• v.10 no.1
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• pp.139-156
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• 1993

Various ATM switches have been proposed since Asynchronous Transfer Mode (ATM) was recognized as appropriate for implementing broadband integrated services digital network (BISDN). An ATM switching network may be evaluated on two sides : traffic performances (maximum throughput, delay, and packet loss probability, etc.) and structural features (complexity, i.e. the number of switch elements necessary to construct the same size switching network, maintenance, modularity, and fault tolerance, etc.). ATM switching networks proposed to date tend to show the contrary characteristics between structural features and traffic performance. The Knockout Switch, which is well known as one of ATM switches, shows a good traffic performance but it needs so many switch elements and buffers. In this paper, we propose an input and output buffered Knockout Switch for the purpose of reducing the number of switch elements and buffers of the existing Knockout Switch. We analyze the traffic performance and the structural features of the proposed switching architecture through a discrete time Markov chain and compare with those of the existing Knockout Switch. It was found that the proposed architecture could reduce more than 40 percent of switch elements and more than 30 percent of buffers under a given requirement of cell loss probability of the switch.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.1
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• pp.63-72
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• 1994

The objective of the study is to develop weather generators for daily rainfall and small pan evaporation and to test the applicability with recorded data. Daily rainfall forecasting model(DRFM) was developed that uses a first order Markov chain to describe rainfall seque- nces and applies an incomplete Gamma function to predict the amount of precipitation. Daily evaporation forecasting model(DEFM) that adopts a normal distribution function to generate the evaporation for dry and wet days was also formulated. DRFM and DEFM were tested with twenty year weather data from eleven stations using Chi-square and Kolmogorov and Smirnov goodness of fit tests. The test results showed that the generated sequences of rainfall occurrence, amount of rainfall, and pan evaporation were statistically fit to recorded data from eleven, seven, and seven stations at the 5% level of significance. Generated rainfall data from DRFM were very close in frequency distri- bution patterns to records for stations all over the country. Pan evaporation for rainy days generated were less accurate than that for dry days. And the proposed models may be used as tools to provide many mathematical models with long-term daily rainfall and small pan evaporation data. An example is an irrigation scheduling model, which will be further detailed in the paper.

• The Journal of the Korea Contents Association
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• v.3 no.4
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• pp.55-62
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• 2003

In this paper, a call admission contro(cac) technique is proposed to reduce the dropping probabilities of handoff calls in wireless networks while guaranteeing QoS to the users. The proposed technique is based on the estimated effective load for the target eel if a call is accepted. When the estimated effective load is higher than a predetermined threshold, a nu call is blocked and a handoff call is queued irrespective of the availability channels. The SRN, an extended Stochastic Petri Net, modes are constructed to compare the performance of the techniques. The SRN uses rewards concepts instead of the complicate numerical analysis required for the Markov chain modes. As a result, the SRN modeling techniques provide an easier way to carry out performance analysis for call admission control and channel allocation.