• Journal of Information Processing Systems
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• v.8 no.4
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• pp.603-620
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• 2012

Proxy Mobile IPv6 (PMIPv6) is a network-based mobility support protocol and it does not require Mobile Nodes (MNs) to be involved in the mobility support signaling. In the case when multiple interfaces are active in an MN simultaneously, each data flow can be dynamically allocated to and redirected between different access networks to adapt to the dynamically changing network status and to balance the workload. Such a flow redistribution control is called "flow mobility". In the existing PMIPv6-based flow mobility support, although the MN's logical interface can solve the well-known problems of flow mobility in a heterogeneous network, some missing procedures, such as an MN-derived flow handover, make PMIPv6-based flow mobility incomplete. In this paper, an enhanced flow mobility support is proposed for actualizing the flow mobility support in PMIPv6. The proposed scheme is also based on the MN's logical interface, which hides the physical interfaces from the network layer and above. As new functional modules, the flow interface manager is placed at the MN's logical interface and the flow binding manager in the Local Mobility Anchor (LMA) is paired with the MN's flow interface manager. They manage the flow bindings, and select the proper access technology to send packets. In this paper, we provide the complete flow mobility procedures which begin with the following three different triggering cases: the MN's new connection/disconnection, the LMA's decision, and the MN's request. Simulation using the ns-3 network simulator is performed to verify the proposed procedures and we show the network throughput variation caused by the network offload using the proposed procedures.

• Smart Structures and Systems
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• v.26 no.2
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

• Structural Engineering and Mechanics
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• v.73 no.3
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• pp.339-351
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• 2020

Earthquakes are natural disasters that cause serious social disruptions and economic losses. In particular, they have a significant impact on critical lifeline infrastructure such as urban water transmission networks. Therefore, it is important to predict network performance and provide an alternative that minimizes the damage by considering the factors affecting lifeline structures. This paper proposes a probabilistic reliability approach for post-hazard flow analysis of a water transmission network according to earthquake magnitude, pipeline deterioration, and interdependency between pumping plants and 154 kV substations. The model is composed of the following three phases: (1) generation of input ground motion considering spatial correlation, (2) updating the revised nodal demands, and (3) calculation of available nodal demands. Accordingly, a computer code was developed to perform the hydraulic analysis and numerical modelling of water facilities. For numerical simulation, an actual water transmission network was considered and the epicenter was determined from historical earthquake data. To evaluate the network performance, flow-based performance indicators such as system serviceability, nodal serviceability, and mean normal status rate were introduced. The results from the proposed approach quantitatively show that the water network is significantly affected by not only the magnitude of the earthquake but the interdependency and pipeline deterioration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1649-1667
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• 2012

In order to improve the accuracy and universality of the flow metric correlation analysis, this paper firstly analyzes the characteristics of Internet flow metrics as random variables, points out the disadvantages of Pearson Correlation Coefficient which is used to measure the correlation between two flow metrics by current researches. Then a method based on Symmetrical Uncertainty is proposed to measure the correlation between two flow metrics, and is extended to measure the correlation among multi-variables. Meanwhile, the simulation and polynomial fitting method are used to reveal the threshold value between different correlation degrees for SU method. The statistical analysis results on the common flow metrics using several traces show that Symmetrical Uncertainty can not only represent the correct aspects of Pearson Correlation Coefficient, but also make up for its shortcomings, thus achieve the purpose of measuring flow metric correlation quantitatively and accurately. On the other hand, reveal the actual relationship among fourteen common flow metrics.

• Korea-Australia Rheology Journal
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• v.14 no.4
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• pp.161-174
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• 2002

A new technique for numerical calculation of viscoelastic flow based on the combination of Neural Net-works (NN) and Brownian Dynamics simulation or Stochastic Simulation Technique (SST) is presented in this paper. This method uses a "universal approximator" based on neural network methodology in combination with the kinetic theory of polymeric liquid in which the stress is computed from the molecular configuration rather than from closed form constitutive equations. Thus the new method obviates not only the need for a rheological constitutive equation to describe the fluid (as in the original Calculation Of Non-Newtonian Flows: Finite Elements St Stochastic Simulation Techniques (CONNFFESSIT) idea) but also any kind of finite element-type discretisation of the domain and its boundary for numerical solution of the governing PDE's. As an illustration of the method, the time development of the planar Couette flow is studied for two molecular kinetic models with finite extensibility, namely the Finitely Extensible Nonlinear Elastic (FENE) and FENE-Peterlin (FENE-P) models.P) models.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.5
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• pp.1426-1435
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• 1996

In this paper. a network theory for generaltransmission systme was extended considering the direction of power flow. Also, a modified network model was suggested for a node with 4 shafts in order to verify the power flow. Based on the extended network theory, a simulation program was developed to analyze a hydro-mecaanical tranmission(HMT) system consistion of two hydrostatic pump motors, severeal planetary gear trains steer differential gear. The simulation result showed that the extendednotwork analysis program develped can predict the power circulation as well as the magnitude of torque and speed for each transmission element and can be used design tool for genaral power transmission system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.4
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• pp.227-236
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• 1986

In this paper, an integrated voice/data packet network with window flow control is modeled by a colsed multichain queueing system, and its performance is analyzed by the mean value analysis method. Particularly, for the analysis of a packet network having various kinds of messages with different priority classes, we introduce an approach based on the mean value analysis and the concept of effective capacity. By the mathematical analysis and computer simulation, we obtain the following network statistics in the steady state: Mean buffer occupancy at each node, utilization of link throughput of a virtual channel, and mean delay time of each message. Our iterative analysis method can predict the link data status in most cases within about 10 percent of accurady, and the statistics of voice messages and external data within 5 percent as compared to simulation results.

• Biotechnology and Bioprocess Engineering:BBE
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• v.9 no.3
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• pp.156-165
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• 2004

Concentrations of substrates, glucose, and ammionia in biological processes have been on-line monitored by using glucose-flow injection (FIA) and ammonia-FIA systems. Based on the on-line monitored data the concentrations of substrates have been controlled by an on-off controller, a PID controller, and a neural network (NN) based controller. A simulation program has been developed to test the control quality of each controller and to estimate the control parameters. The on-off controller often produced high oscillations at the set point due to its low robustness. The control quality of a PID controller could have been improved by a high analysis frequency and by a short residence time of sample in a FIA system. A NN-based controller with 3 layers has been developed, and a 3(input)-2(hidden)-1(output) network structure has been found to be optimal for the NN-based controller. The performance of the three controllers has been tested in a simulated process as well as in a cultivation process of Saccharomyces cerevisiae, and the performance has also been compared to simulation results. The NN-based controller with the 3-2-1 network structure was robust and stable against some disturbances, such as a sudden injection of distilled water into a biological process.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1289-1302
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• 2019

In this paper, an optimal allocation method of a hybrid active power filter in an active distribution network is designed based on the differential evolution algorithm to resolve the harmonic generation problem when a distributed generation system is connected to the grid. A distributed generation system model in the calculation of power flow is established. An improved back/forward sweep algorithm and a decoupling algorithm are proposed for fundamental power flow and harmonic power flow. On this basis, a multi-objective optimization allocation model of the location and capacity of a hybrid filter in an active distribution network is built, and an optimal allocation scheme of the hybrid active power filter based on the differential evolution algorithm is proposed. To verify the effect of the harmonic suppression of the designed scheme, simulation analysis in an IEEE-33 nodes model and an experimental analysis on a test platform of a microgrid are adopted.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.2
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• pp.15-24
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• 2016

This study conducted an evaluation of the extent of debris flow damage using SINMAP, which is slope stability analysis software based on the infinite slope stability method, and FLO-2D, a hydraulic debris flow analysis program. Mt. Majeok located in Chuncheon city in the Gangwon province was selected as the study area to compare the study results with an actual 2011 case. The stability of the slope was evaluated using a DEM of $1{\times}1m$ resolution based on the LiDAR survey method, and the initiation points of the debris flow were estimated by analyzing the overlaps with the drainage network, based on watershed analysis. In addition, the study used measured data from the actual case in the simulation instead of existing empirical equations to obtain simulation results with high reliability. The simulation results for the impact of the debris flow showed a 2.2-29.6% difference from the measured data. The results suggest that the extent of damage can be effectively estimated if the parameter setting for the models and the debris flow initiation point estimation are based on measured data. It is expected that the evaluation method of this study can be used in the future as a useful hazard mapping technique among GIS-based risk mapping techniques.