• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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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.

• 한국군사과학기술학회지
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• 제15권4호
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• pp.442-449
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• 2012

Cognitive Radio(CR) is the technology that allocates the frequency by using dynamic spectrum access. We proposed a model to calculate the optimal level of the cognitive radiotelegraph, where secondary users opportunistically share the spectrum with primary users through the spectrum sensing. When secondary user with cognitive radio detects the arrival of a primary user in its current channel, the secondary user moves to the idle channel or be placed in the virtual queue. We assume that the primary users have finite buffers and the population of secondary users is finite. Using a two-dimensional Makov model with preemptive priority queueing, we could derive the blocking and waiting probability as well as the optimal level of cognitive radiotelegraph under a various range of parameter circumstances.

• 산업경영시스템학회지
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• 제39권2호
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• pp.1-10
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• 2016

In this paper, we present a new way to derive the mean cycle time of the G/G/m failure prone queue when the loading of the system approaches to zero. The loading is the relative ratio of the arrival rate to the service rate multiplied by the number of servers. The system with low loading means the busy fraction of the system is low. The queueing system with low loading can be found in the semiconductor manufacturing process. Cluster tools in semiconductor manufacturing need a setup whenever the types of two successive lots are different. To setup a cluster tool, all wafers of preceding lot should be removed. Then, the waiting time of the next lot is zero excluding the setup time. This kind of situation can be regarded as the system with low loading. By employing absorbing Markov chain model and renewal theory, we propose a new way to derive the exact mean cycle time. In addition, using the proposed method, we present the cycle times of other types of queueing systems. For a queueing model with phase type service time distribution, we can obtain a two dimensional Markov chain model, which leads us to calculate the exact cycle time. The results also can be applied to a queueing model with batch arrivals. Our results can be employed to test the accuracy of existing or newly developed approximation methods. Furthermore, we provide intuitive interpretations to the results regarding the expected waiting time. The intuitive interpretations can be used to understand logically the characteristics of systems with low loading.

• Fisheries and Aquatic Sciences
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• 제24권4호
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• pp.139-152
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• 2021

The main purpose of this study is to fit catch-per-unit-effort (CPUE) data about Korea chub mackerel (Scomber japonicus) stock with a state-space production (SSP) model, and to provide stock assessment results. We chose a surplus production model for the chub mackerel data, namely annual yield and CPUE. Then we employed a state-space layer for a production model to consider two sources of variability arising from unmodelled factors (process error) and noise in the data (observation error). We implemented the model via script software ADMB-RE because it reduces the computational cost of high-dimensional integration and provides Markov Chain Monte Carlo sampling, which is required for Bayesian approaches. To stabilize the numerical optimization, we considered prior distributions for model parameters. Applying the SSP model to data collected from commercial fisheries from 1999 to 2017, we estimated model parameters and management references, as well as uncertainties for the estimates. We also applied various production models and showed parameter estimates and goodness of fit statistics to compare the model performance. This study presents two significant findings. First, we concluded that the stock has been overexploited in terms of harvest rate from 1999 to 2017. Second, we suggest a SSP model for the smallest goodness of fit statistics among several production models, especially for fitting CPUE data with fluctuations.

• Smart Structures and Systems
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• 제31권3호
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.

• 한국정보통신학회논문지
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• 제10권8호
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• pp.1393-1400
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• 2006

본 논문은 확률접근 기반의 네트워크 자원할당 방식에서 네트워크의 대표적인 서비스 품질 척도인 대기시간과 블러킹 확률이 특정 임계값을 넘지 않으면서 최소화가 되도록 접근 확률을 최적화하는 방법에 대하여 연구하였고 그에 따른 성능분석을 하였다. 확률 접근에 의한 제어 방식은 시스템에서 서비스 받고 있는 메시지의 수, 시스템에서 대기하고 있는 메시지의 수, 문턱 값, 컷오프 값 등의 시스템 상태에 따라 접근확률을 다르게 하여 자원의 할당을 동적으로 제어하는 방식이다. 접근 확률을 최적화하는 문제는 무한개의 균형 방정식을 포함하는 문제로서 Neuts의 행렬기하기법(matrix geometric method)을 통하여 유한개의 균형 방정식을 가지는 최적화 문제로 변환하였다. 또한 유한개의 균형방정식은 비선형 최적화 문제로 모델링이 되는데 이것을 다시 변수 치환 기법을 이용하여 설형 최적화 문제로 변환하여 최적의 접근 확률을 구하였다. 수치해석을 통하여 주어진 조건하에 최적의 접근 확률을 구한후 트래픽의 대기시간, 블러킹 확률 및 시스템 최대 이용률을 구하였고 버퍼의 문턱 값을 제어하여 시스템의 이용률이 증가하는 것을 보였다.