• Nuclear Engineering and Technology
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• v.46 no.5
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• pp.641-654
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• 2014

A new computer code, named CORONA (Core Reliable Optimization and thermo-fluid Network Analysis), was developed for the core thermo-fluid analysis of a prismatic gas cooled reactor. The CORONA code is targeted for whole-core thermo-fluid analysis of a prismatic gas cooled reactor, with fast computation and reasonable accuracy. In order to achieve this target, the development of CORONA focused on (1) an efficient numerical method, (2) efficient grid generation, and (3) parallel computation. The key idea for the efficient numerical method of CORONA is to solve a three-dimensional solid heat conduction equation combined with one-dimensional fluid flow network equations. The typical difficulties in generating computational grids for a whole core analysis were overcome by using a basic unit cell concept. A fast calculation was finally achieved by a block-wise parallel computation method. The objective of the present paper is to summarize the motivation and strategy, numerical approaches, verification and validation, parallel computation, and perspective of the CORONA code.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.159-168
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• 1994

Stochastic computation is adopted to reduce the silicon area of the multipliers in implementing neural network in VLSI. In addition to this advantage, the stochastic computation has inherent random errors which is required for implementing Boltzmann machine. This random noise is useful for the simulated annealing which is employed to achieve the global minimum for the Boltzmann Machine. In this paper, we propose a method to implement the Boltzmann machine with stochastic computation and discuss the addition problem in stochastic computation and its simulated annealing in detail. According to this analysis Boltzmann machine using stochastic computation is suitable for the pattern recognition/completion problems. We have verified these results through the simulations for XOR, full adder and digit recognition problems, which are typical of the pattern recognition/completion problems.

• Smart Structures and Systems
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• v.32 no.1
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• pp.49-59
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• 2023

A bridge transportation network supplies products from various source nodes to destination nodes through bridge structures in a target region. However, recent frequent earthquakes have caused damage to bridge structures, resulting in extreme direct damage to the target area as well as indirect damage to other lifeline structures. Therefore, in this study, a surrogate model-based comprehensive framework to estimate the seismic resilience of bridge transportation networks is proposed. For this purpose, total system travel time (TSTT) is introduced for accurate performance indicator of the bridge transportation network, and an artificial neural network (ANN)-based surrogate model is constructed to reduce traffic analysis time for high-dimensional TSTT computation. The proposed framework includes procedures for constructing an ANN-based surrogate model to accelerate network performance computation, as well as conventional procedures such as direct Monte Carlo simulation (MCS) calculation and bridge restoration calculation. To demonstrate the proposed framework, Pohang bridge transportation network is reconstructed based on geographic information system (GIS) data, and an ANN model is constructed with the damage states of the transportation network and TSTT using the representative earthquake epicenter in the target area. For obtaining the seismic resilience curve of the Pohang region, five epicenters are considered, with earthquake magnitudes 6.0 to 8.0, and the direct and indirect damages of the bridge transportation network are evaluated. Thus, it is concluded that the proposed surrogate model-based framework can efficiently evaluate the seismic resilience of a high-dimensional bridge transportation network, and also it can be used for decision-making to minimize damage.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.10a
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• pp.202-207
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• 1998

The network reliability is to be computed in terms of the terminal reliability. The computation of a terminal reliability is started with a Boolean sum of products expression corresponding to simple paths of the pair of nodes. This expression is then transformed into another equivalent expression to be a Disjoint Sum of Products form. But this computation of the terminal reliability obviously does not consider the communication between any other nodes but for the source and the sink. In this paper, we derive the overall network reliability which all other remaining nodes. For this, we propose a method to make the SOP disjoint for deriving the network reliability expression from the system success expression using the modified Sheinman's method. Our method includes the concept of spanning trees to find the system success function by the Cartesian products of vertex cutsets.

• Journal of Korean Society of Rural Planning
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• v.5 no.1 s.9
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• pp.20-25
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• 1999

Our interest in this paper is in the efficient computation of a good low bound for the traveling salesman problem and is in the application of a network problem in agriculture. We base our approach on a relatively new formulation of the TSP as a two-commodity network flow problem. By assigning Lagrangian multipliers to certain constraints and relaxing them, the problem separates into two single-commodity network flow problems and an assignment problem, for which efficient algorithms are available.

• Journal of KIISE:Software and Applications
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• v.32 no.4
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• pp.247-257
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• 2005

Generally, the network topology design problem is characterized as a kind of NP-hard combinatorial optimization problem, which is difficult to solve with the classical method because it has exponentially increasing complexity with the augmented network size. In this paper, we propose the efficient approach with two phase that is comprised of evolutionary computation approach based on Prufer number(PN), which can efficiently represent the spanning tree, and a heuristic method considering 2-connectivity, to solve the highly reliable network topology design problem minimizing the construction cost subject to network reliability: firstly, to find the spanning tree, genetic algorithm that is the most widely known type of evolutionary computation approach, is used; secondly, a heuristic method is employed, in order to search the optimal network topology based on the spanning tree obtained in the first Phase, considering 2-connectivity. Lastly, the performance of our approach is provided from the results of numerical examples.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.1
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• pp.28-41
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• 1997

This paper describes a parallel implementation of a neurla network ensemble developed for object recognition on the connection machine CM-2. The implementation ensures that multiple networks are implemented simultaneously starting from different initial weights and all training samples are applied to each network by one sample per a copy of each network. When compared with a sequential implementation, this accelerates the computation speed by O(N.m.n) where N, m, and n are the network, respectively. The speedup in the computation time and the convergence characteristics of sthe modified backpropagation learning precedure were evaluated by two-dimensional object recognition problem.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.48-56
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• 1995

This paper presents a method of implementing efficient optical flow estimation for dynamic scene analysis using the hierarchical Hopfield neural networks. Given the two consequent inages, Zhou and Chellappa suggested the Hopfield neural network for computing the optical flow. The major problem of this algorithm is that Zhou and Chellappa's network accompanies self-feedback term, which forces them to check the energy change every iteration and only to accept the case where the lower the energy level is guaranteed. This is not only undesirable but also inefficient in implementing the Hopfield network. The another problem is that this model cannot allow the exact computation of optical flow in the case that the disparities of the moving objects are large. This paper improves the Zhou and Chellapa's problems by modifying the structure of the network to satisfy the convergence condition of the Hopfield model and suggesting the hierarchical algorithm, which enables the computation of the optical flow using the hierarchical structure even in the presence of large disparities.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.136-146
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• 2006

In Wireless Sensor Network(WSN) a sensor node transfers sensing data to the base-node through multi-hop because of the limited transmission range. Also because of the limited energy of the sensor node, the sensor nodes are required to consume their energy evenly to prolong the lifetime of the network. LMPR is a routing protocol for WSN, LMPR configures the network autonomously based on level which is the depth from the base-node, and distributes the transmission and computation load of the network to each sensor node. This paper implements LMPR on TinyOS and experiments on the performance of LMPR in WSN. As the result, the average of the received rate of LMPR is 91.39% and LMPR distributes the load of the transmission and computation about 4.6 times compare to the shortest cost routing protocol. We expect LMPR evenly distributes the transmission and computation load of the network to each node, and the lifetime of the network will be longer than it used to be.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.3711-3730
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• 2014

Cognitive radio networks (CRNs) have emerged as a promising solution to enhance spectrum utilization by using unused or less used spectrum in radio environments. The basic idea of CRNs is to allow secondary users (SUs) access to licensed spectrum, under the condition that the interference perceived by the primary users (PUs) is minimal. In CRNs, the channel availability is uncertainty due to the existence of PUs, resulting in intermittent communication. Transmission control protocol (TCP) performance may significantly degrade in such conditions. To address the challenges, some transport protocols have been proposed for reliable transmission in CRNs. In this paper we survey the state-of-the-art transport protocols for CRNs. We firstly highlight the unique aspects of CRNs, and describe the challenges of transport protocols in terms of PU behavior, spectrum sensing, spectrum changing and TCP mechanism itself over CRNs. Then, we provide a summary and comparison of existing transport protocols for CRNs. Finally, we discuss several open issues and research challenges. To the best of our knowledge, our work is the first survey on transport protocols for CRNs.