• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.4
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• pp.111-122
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• 1999

In this paper, we consider a queueing network model. where the population constraint within each subnetwork is controlled by a semaphore queue. The total number of customers that may be present in the subnetwork can not exceed a given value. Each node has a constant service time and the arrival process to the queueing network is an arbitrary distribution. A major characteristics of this model is that the lower layer flow is halted by the state of higher layer. We present some properties that the inter-change of nodes does not make any difference to customer's waiting time in the queueing network under a certain condition. The queueing network can be transformed into a simplified queueing network. A dramatic simplification of the queueing network is shown. It is interesting to see how the simplification developed for sliding window flow control, can be applied to multi-layered queueing network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.819-824
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• 2015

SDN (Software Defined Network) technology, hardware and network control functions should be separated independently of existing switches or routers and data transfer functions and are also refers to a separate network architecture that can develop and run. When planning a network and designed to reflect the network control function by applying the SDN may reflect the resources efficiently. In this study, one people suggest Applications SDN, which offer an absolutely necessary part of a coded program that combines the benefits of the existing IOS (Combined Benefits) applying the model to complete the Controller part through the MPLS IOS. The OpenFlow Controller is a command to the router LER(Label Edge Router), and transmits the packet in accordance with the command to the destination according to the EXP bit. To configure TCP / IP to the IOS through the optimized coding. Using the OpenFlow protocol controller transmits an encapsulation header as defined in the MPLS packet.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.285-291
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• 2014

Recent, development of wireless communication devices are rapidly and these device being deployed to the user very fast. By this results, a wired network device and the new device such as wireless devices incorporate. Then a demand of new mesh network is rapidly growing. In this wired/wireless integrated network environment, the network is configured automatically, and a user or wireless communication devices must be provided for authentication services. But, these services do not in the real world. Therefore, in this paper, we propose that wired/wireless integrated network environment to automatically configure the network using OpenFlow and the authentication system using Kerberos method. Our proposed system to be able to provide authentication services, confidentiality, integrity services for user or wired/wireless communication devices. And it can be prvented as well to man-in-the-middle attacks.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.8
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• pp.638-651
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• 2000

When the bandwidth resources in a packet-switched network are shared among sessions by MAX-MIN flow control each session is required to transmit its data into the network subject to the MAX-MIN fair rate which is solely determined by network loadings. This passive behavior of sessions if fact can cause seri-ous QoS(Quality of Service) degradation particularly for real-time multimedia sessions such as video since the rate allocated by the network can mismatch with what is demanded by each session for its QoS. In order to alleviate this problem we extend the concept of MAX-MIN fair bandwidth allocations as follows: Individual bandwidth demands are guaranteed if the network can accommodate them and only the residual network band-width is shared in the MAX-MIN fair sense. On the other hand if sum of the individual bandwidth demands exceeds the network capacity the shortage of the bandwidth is shared by all the sessions by reducing each bandwidth guarantee by the MAX-MIN fair division of the shortage. we present a novel flow control algorithm to achieve this extended MAX-MIN fairness and show that this algorithm can be implemented by the existing ATM ABR service protocol with minor changes. We not only analyze the steady state asymptotic stability and convergence rate of the algorithm by appealing to control theories but also verify its practical performance through simulations in a variety of network scenarios.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.924-931
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• 2016

In this paper, Various network adaptive MAC scheduling technique is proposed to effectively overcome limits of narrow bandwidth and low transmission speed in underwater. UPFC(Underwater Packet Flow Control) is a technique to reduce both the number of transmission and transmission time using three types (Normal, Blocked, Parallel) of data transmission. In this technique, the load information, in which a transmission node have, is transmitted to destination node using marginal bit in reserved header. Then the transmitted information is referred to determine weighting factor. According to the weighting factor, scheduling is dynamically changed adaptively. The performance of UPFC is analyzed and flow control technique which can be applied to Cluster Based Network and Ad Hoc network as well.

• Computers and Concrete
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• v.5 no.5
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• pp.461-473
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• 2008

The paper explores the potential of Support Vector Machines (SVM) approach in predicting 28-day compressive strength and slump flow of self-compacting concrete. Total of 80 data collected from the exiting literature were used in present work. To compare the performance of the technique, prediction was also done using a back propagation neural network model. For this data-set, RBF kernel worked well in comparison to polynomial kernel based support vector machines and provide a root mean square error of 4.688 (MPa) (correlation coefficient=0.942) for 28-day compressive strength prediction and a root mean square error of 7.825 cm (correlation coefficient=0.931) for slump flow. Results obtained for RMSE and correlation coefficient suggested a comparable performance by Support Vector Machine approach to neural network approach for both 28-day compressive strength and slump flow prediction.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1753-1762
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• 2000

An inverse method is presented to obtain material's flow properties by using small punch test. This procedure employs, as the objective function of inverse analysis, the balance of measured load-di splacement response and calculated one during deformation. In order to guarantee convergence to global minimum, simulated annealing method was adopted to optimize the current objective function. In addition, artificial neural network was used to predict the load-displacement response under given material parameters which is the most time consuming and limits applications of global optimization methods to these kinds of problems. By implementing the simulated annealing for optimization along with calculating load-displacement curve by neural network, material parameters were identified irrespective of initial values within very short time for simulated test data. We also tested the present method for error-containing experimental data and showed that the flow properties of material were well predicted.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.24-30
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• 2005

For a reciprocating compressor of household refrigerators, a direct analogy between the pipe flow network and the electric circuit network has been utilized to set up a mathematical model for oil supply system. Individual lubrication elements of the oil supply system, such as propeller- installed oil cap, oil galleries, radial oil feeding holes, spiral oil grooves, and various sliding surfaces have been analogized by equivalent electric elements, and these have been combined together to form an electric circuit corresponding to the whole oil supply system. By solving the closed network equations of the model, oil flow rates at various lubrication elements could be obtained. Total amount of the oil flow rate drawn into the shaft has been measured and compared reasonably well with the prediction of the numerical simulation.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.85-101
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• 2013

The wide spread of smartphones and the growth of the number of internet users are reshaping the SNS (Social Network Service). Merging into other service areas and creating new business models with high profits, SNS is no more a service simply providing personal connections. Now SNS has positioned itself as a service platform. SNG (Social Network Game) is a new outcome utilizing SNS as a game platform and showing a rapid growth rate in a short period of time. The number of SNG users is expected to increase steadily. In this study, we examine whether SNG user motivations lead to flow experience and future intention to use. For that purpose, we conducted a survey with smartphone users. The results indicate that flow experience functions as a mediator and user motivations indirectly affect intention to use through flow experience. This paper concludes with discussions on findings and suggestions for future research.