• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.907-913
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• 1999

For an automated transportation system like PRT(Personal Rapid Transit) system or IVHS, an efficient vehicle-merging algorithm is required for smooth operation of the network. For management of merging, collision avoidance between vehicles, ride comfort, and the effect on traffic should be considered. This paper proposes an unmanned vehicle-merging algorithm that consists of two procedures. First, a longitudinal control algorithm is designed to keep a safe headway between vehicles in a single lane. Secondly, 'vacant slot and ghost vehicle' concept is introduced and a decision algorithm is designed to determine the sequence of vehicles entering a converging section considering energy consumption, ride comfort, and total traffic flow. The sequencing algorithm is based on fuzzy rules and the membership functions are determined first by an intuitive method and then trained by a learning method using a neural network. The vehicle-merging algorithm is shown to be effective through simulations based on a PRT model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2781-2800
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• 2016

Emerging attacks aim to access proprietary assets and steal data for business or political motives, such as Operation Aurora and Operation Shady RAT. Skilled Intruders would likely remove their traces on targeted hosts, but their network movements, which are continuously recorded by network devices, cannot be easily eliminated by themselves. However, without complete knowledge about both inbound/outbound and internal traffic, it is difficult for security team to unveil hidden traces of intruders. In this paper, we propose an autonomous anomaly detection system based on behavior profiling and relation mining. The single-hop access profiling model employ a novel linear grouping algorithm PSOLGA to create behavior profiles for each individual server application discovered automatically in historical flow analysis. Besides that, the double-hop access relation model utilizes in-memory graph to mine time-sequenced access relations between different server applications. Using the behavior profiles and relation rules, this approach is able to detect possible anomalies and violations in real-time detection. Finally, the experimental results demonstrate that the designed models are promising in terms of accuracy and computational efficiency.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.45-54
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• 2002

MPLS(Multiprotocol Label Switching) is regarded as a core technology for migrating to the next generation Internet. In this paper, we propose an dynamic flow admission control supporting DiffServ(Differentiated Services) to provide QoS in MPLS networks. Our proposed model dynamically adjusts the amount of admissible traffic based on transmittable capacity over one outgoing port. It then transmits the Packets while avoiding congested area resulting traffic loss. Ingress LSRs find out the congested area by collecting network state information at QoS state update for QoS routing table. Our Proposed model manages the resource efficiently by protecting the waste of resources that is a critical Problem of DiffServ and makes much more flows enter the network to be served.

• Membrane and Water Treatment
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• v.13 no.5
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• pp.219-225
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• 2022

5th Assessment Report of the Intergovernmental Panel on Climate Change Weather (AR5) predicts that recent severe hydrological events will affect the quality of water and increase water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed, and solar radiation) were compiled into a representative concentration curve (RC), defined using 8.5. AR5 and future use are calculated based on land use. Semi-distributed emission model Calculate emissions for each target period. Meteorological factors affecting water quality (precipitation, temperature, and flow) were input into a multiple linear regression (MLR) model and an artificial neural network (ANN) to analyze the data. Extensive experimental studies of flow properties have been carried out. In addition, an Acoustic Doppler Velocity (ADV) device was used to monitor the flow of a large open channel connection in a wastewater treatment plant in Ho Chi Minh City. Observations were made along different streams at different locations and at different depths. Analysis of measurement data shows average speed profile, aspect ratio, vertical position Measure, and ratio the vertical to bottom distance for maximum speed and water depth. This result indicates that the transport effect of the compound was considered when preparing the hazard analysis.

• Journal of the Korean Society of Visualization
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• v.22 no.1
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• pp.49-60
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• 2024

The purpose of this study establishes the deep neural network (DNN) and Decoder models to predict the flow and thermal fields of three-dimensional wavy wings as a passive flow control. The wide ranges of the wavy geometric parameters of wave amplitude and wave number are considered for the various the angles of attack and the aspect ratios of a wing. The huge dataset for training and test of the deep learning models are generated using computational fluid dynamics (CFD). The DNN and Decoder models exhibit quantitatively accurate predictions for aerodynamic coefficients and Nusselt numbers, also qualitative pressure, limiting streamlines, and Nusselt number distributions on the surface. Particularly, Decoder model regenerates the important flow features of tiny vortices in the valleys, which makes a delay of the stall. Also, the spiral vortical formation is realized by the Decoder model, which enhances the lift.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3598-3614
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• 2020

With the increase of motor vehicles and tourism demand, some traffic problems gradually appear, such as traffic congestion, safety accidents and insufficient allocation of traffic resources. Facing these challenges, a model of Spatio-Temporal Dilated Convolutional Network (STDGCN) is proposed for assistance of extracting highly nonlinear and complex characteristics to accurately predict the future traffic flow. In particular, we model the traffic as undirected graphs, on which graph convolutions are built to extract spatial feature informations. Furthermore, a dilated convolution is deployed into graph convolution for capturing multi-scale contextual messages. The proposed STDGCN integrates the dilated convolution into the graph convolution, which realizes the extraction of the spatial and temporal characteristics of traffic flow data, as well as features of road occupancy. To observe the performance of the proposed model, we compare with it with four rivals. We also employ four indicators for evaluation. The experimental results show STDGCN's effectiveness. The prediction accuracy is improved by 17% in comparison with the traditional prediction methods on various real-world traffic datasets.

• Water Engineering Research
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• v.6 no.2
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• pp.49-61
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• 2005

This paper presents the numerical study to examine characteristics of fluid flow and solute transport in a rough fracture subject to effective normal stresses. The aperture distribution is generated by using the self-affine fractal model. In order to represent a nonlinear relationship between the supported normal stress and the fracture aperture, we combine a simple mechanical model with the local flow model. The solute transport is simulated using the random walk particle following algorithm. Results of numerical simulations show that the flow is significantly affected by the geometry of aperture distribution varying with the effective normal stress level while it is slightly affected by the fractal dimension that determines the degree of the fracture surface roughness. However, solute transport is influenced by the effective normal stress as well as the fracture surface roughness.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.10
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• pp.562-567
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• 2013

1D-numerical analysis of the network algorithm with the orifice equation for the relationship between pressure difference and flowrate has been mostly used to analyse leakage flow at the gap. In this study, a 3D-numerical method applying momentum loss model to the gap region in the computational domain is represented to reflect effectively the effect of leakage flow by determining the proportion of pressure difference to air passage velocity. While the 3D-numerical method is verified through the computation of the two compartments model, the numerical analysis of the stack effect in a building stairway is performed. As the temperature of air outside drops, the pressure in the upper stairway and leakage flowrate through the gap in the door rise. The change of gap area does not have an effect on pressure in the stairway for the analysis conditions.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.29
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• pp.173-196
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• 2006

Online game business has emerged as the most lucrative entertainment industry, with over 10 million players in South Korea and over 30 million in Japan in 2005. The popularity of online games can be attributed to the availability of broadband network, pushing online games into the mainstream entertainment culture. The age distribution of online game players is expanding and a variety of new games are under development to target certain age groups. While the interactive entertainment market continues to expand, with many new online game publishers entering the Japan, relatively little is known about which factors influence online game players' behavioral intentions to play continuously in this area. This study investigates major factors which influence the acceptance of online game services based on the theoretical backgrounds of the technology acceptance model(TAM) and the flow theory. This paper extended the Davis' TAM model by including the flow concept as another major factor toward the intention to play online game. Based on data collected from online questionnaire survey, we show that the proposed model provides an adequate fit to the data, and that the flow experience is another important factor influencing the intention to play online game, as well as the perceived ease of use.