• Asian Journal of Innovation and Policy
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• v.4 no.2
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• pp.242-262
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• 2015

The relationship between geographical proximity and academics' formal and informal knowledge-transfer activities in the network is analyzed with a mixed research method. With social network analysis as a basis, we have explored the networks between academics and firms in the 16 regions of South Korea. The result shows Seoul and Gyunggi are identified as central nodes, meaning that the academics in other regions tend to collaborate with firms in these regions. An econometric analysis is performed to confirm the localization of knowledge-transfer activities. The intensity of formal channels measured by the number of academic papers is negatively, but significantly associated with the geographical proximity. However, we have not found any significant relationship between the formality of the channels and geographical proximity. Possibly, the regional innovation systems in South Korea are neither big enough nor strong enough to show a localization effect.

• Asia pacific journal of information systems
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• v.26 no.3
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• pp.427-448
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• 2016

The stochastic phenomena of traffic network condition, such as traffic speed and density, are affected not only by exogenous traffic control but also by endogenous changes in service time during congestion. In this paper, we propose a mixed M/G/1 queuing model by introducing a condition-varying parameter of traffic congestion to reflect structural changes in the traffic network. We also develop congestion indices to evaluate network efficiency in terms of traffic flow and economic cost in traffic operating system using structure-changing queuing model, and perform scenario analysis according to various traffic network improvement policies. Empirical analysis using Korean highway traffic operating system shows that our suggested model better captures structural changes in the traffic queue. The scenario analysis also shows that occasional reversible lane operation during peak times can be more efficient and feasible than regular lane extension in Korea.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.34-37
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• 2005

An efficient and robust neural network-based scheme is introduced in this paper to perform automatic cloud detection. Unlike many existing cloud detection schemes which use thresholding and statistical methods, we used the artificial neural network methods, the multi-layer perceptrons (MLP) with back-propagation algorithm and radial basis function (RBF) networks for cloud detection from Geostationary satellite images. We have used a simple scene (a mixed scene containing only cloud and clear sky). The main results show that the neural networks are able to handle complex atmospheric and meteorological phenomena. The experimental results show that two methods performed well, obtaining a classification accuracy reaching over 90 percent. Moreover, the RBF model is the most effective method for the cloud classification.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.2
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• pp.1-14
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• 2011

In this paper, we deal with an access network design problem of fiber-to-the-home passive optical network (FTTH-PON). The FTTH-PON network design problem seeks to minimize the total cost of optical splitters and cables that provide optical connectivity between central office and subscribers. We develop a flow-based mixed integer programming (MIP) model with nonlinear link cost. By developing valid inequalities and preprocessing rules, we enhance the strength of the proposed MIP model in generating tight lower bounds for the problem. We develop an effective Tabu Search (TS) heuristic algorithm that provides good quality feasible solutions to the problem. Computational results demonstrate that the valid inequalities and preprocessing rules are effective for improving the LP-relaxation lower bound and TS algorithm finds good quality solutions within reasonable time bounds.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.81-94
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• 2012

This paper suggests PARED algorithm, a modified RED algorithm, that actively reacts to dynamic changes in network to apply packet drop probability flexibly. The main idea of PARED algorithm is that it compares the target queue length to the average queue length which is the criterion of changes in packet drop probability and feeds the gap into packet drop probability. That is, when the difference between the average queue length and the target queue length is great, it reflects as much as the difference in packet drop probability, and reflects little when the difference is little. By doing so, packet drop probability could be actively controled and effectively dealt with in the network traffic situation. To evaluate the performance of the suggested algorithm, we conducted simulations by changing network traffic into a dynamic stat. At the experiments, the suggested algorithm was compared to the existing RED one and then to ARED one that provided the basic idea for this algorithm. The results proved that the suggested PARED algorithm is superior to the existing algorithms.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.1
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• pp.1-15
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• 2005

In this paper, we deal with a mesh network design problem arising from the deployment of WDM for the optical internet. The mesh network consists of mesh topology for satisfying traffic demand while minimizing the cost of WDM, OXC, and fiber cables. The problem seeks to find an optimal routing of traffic demands in the network such that the total cost is minimized. We formulate the problem as a mixed-integer programming model and devise a tabu search heuristic procedure. Also we develop an optical internet design system that implements the proposed tabu search heuristic procedure. We demonstrate the computational efficacy of the proposed algorithm, compared with CPLEX 8.0.

• The KIPS Transactions:PartB
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• v.14B no.3 s.113
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• pp.215-222
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• 2007

As Information Technology growing, the character recognition application plays an important role in the ubiquitous environment. In this paper, we propose the Modified ART1 network using Multiresolution Mergence to the problems of the character recognition. The approach is based on the unsupervised neural network and multiresolution. In order to decrease noises and to increase the classification rate of the characters, we propose the multiresolution mergence strategy using both high resolution and low resolution information. Also, to maximize the effect of multiresolution mergence, we use a modified ART1 method with a different similarity measure. Our experimental results show that the classification rate of character is quite increased as well as the performance of the propose algorithm in conjunction with the similarity measure is improved comparing to the conventional ART1 algorithm in this application.

• Journal of the Korea Concrete Institute
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• v.14 no.4
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• pp.457-466
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• 2002

An artificial neural network was applied to predict compressive strength, slump value and mix proportion of a concrete. Standard mixed tables were trained and estimated, and the results were compared with those of the experiments. To consider variabilities of material properties, the standard mixed fables from two companies of Ready Mixed Concrete were used. And they were trained with the neural network. In this paper, standard back propagation network was used. The mix proportion factors such as water cement ratio, sand aggregate ratio, unit water, unit cement, unit weight of sand, unit weight of crushed sand, unit coarse aggregate and air entraining admixture were used. For the arrangement on the approval of prediction of mix proportion factor, the standard compressive strength of $180kgf/cm^2{\sim}300kgf/cm^2$, and target slump value of 8 cm, 15 cm were used. For the arrangement on the approval of prediction of compressive strength and slump value, the standard compressive strength of $210kgf/cm^2{\sim}240kgf/cm^2$, and target slump value of 12 cm and 15 cm wore used because these ranges are most frequently used. In results, in the prediction of mix proportion factor, for all of the water cement ratio, sand aggregate ratio, unit water, unit cement, unit weight of sand, unit weight of crushed sand, unit coarse aggregate, air entraining admixture, the predicted values and the values of standard mixed tables were almost the same within the target error of 0.10 and 0.05, regardless of two companies. And in the prediction of compressive strength and slump value, the predicted values were converged well to the values of standard mixed fables within the target error of 0.10, 0.05, 0.001. Finally artificial neural network is successfully applied to the prediction of concrete mixture and compressive strength.

• The Transactions of the Korea Information Processing Society
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• v.3 no.1
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• pp.55-62
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• 1996

MRNS network is a general algebraic structure of Hypercube network which has recently drawn considerable attention to supercomputing and message-passing communication. In this paper, we investigate the routing of a message in an n- dimensional MRNS network that is a key to the performance of this network. On the n-dimensional MRNS network we would like to transmit packets from a source node to a destination node simultaneously along a fixed number of paths, where the superscript packet will traverse along the superscript path. In order for all packets to arrive at the destination node quickly and securely, the ith path must be node-disjoint from all other paths. By investigating the conditions of node-disjoint paths, we will employ the special matrices called as the Hamiltonian Circuit Latin Square(HCLS) described in 〔1〕to construct a set of node-disjoint paths and suggest a linear-time parallel routing algorithm for the MRNS network.

• IE interfaces
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• v.18 no.3
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• pp.277-287
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• 2005

In this paper, we deal with a new techno-economic modeling and analysis for optical access networks. In deploying the fiber-to-the-home (FTTH) architecture, network planner needs to consider the following techno-economic issues: when do we need to upgrade existing local access network to FTTH network? how much do we invest to maximize profit? In order to answer these techno-economic questions, we need to consider the impact of emerging technologies and business environment. Toward this end, we develop a new techno-economic modeling to deal with the inherent complexity of technology evolution and cost economics. In particular, the new modeling approach provides us with an techno-economic analysis of technology alternatives such as ethernet passive optical network (E-PON) and wavelength division multiplex passive optical network (WDM-PON). In this analysis, we focus on the impact of critical factors such as the cost characteristic of proposed architecture and digital subscriber line (DSL) subscriber's churn-in to FTTH service and churn-out. We develop mixed integer-programming models for finding the evolution path of local access networks to broadband network architectures.