• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.65-79
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• 2006

The ATIS(Advance Traveler Information System), as one part of ITS, is a system aiming to disperse traffic volume on transportation networks by providing traffic information to transportation users on pre-trip and en-route trips. One of tools in ATIS is usage of VMS(Variable Message Signs). It provides to the drivers with direct information about state of processing direction. which is considered as the most effective method in ATIS. The purposes of providing VMS information are classified two categories. One is to provide simple information to drivers for their convenience. The other is to manage traffic demand to improve transportation network performance. However, for more effective and reliable VMS information, several strategies should be taken into account. The main VMS management strategy is "Traffic Diversion Strategy for minimum delay" when traffic congestion or incident are occurred. For effective operation. firstly. reasonable diversion traffic volume is determined by network traffic condition Secondly, it is necessary to make providing information strategy which reflects driver response behavior for controling diversion traffic volume. This paper focuses on the providing real-time route guidance information by VMS when congestion is occurred by the incidents. This sturdy estimates time-dependent system optimal diversion rate that inflects travel time and queue lengths using traffic flow simulation model on base Cellular Automata. In addition, route choice behavior models are developed using binary logit model for traffic information variable by traffic system controller. Finally, this study provides time-dependent VMS massage contents and degree of providing information in order to optimize the traffic flow.

• Progress in Medical Physics
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• v.10 no.2
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• pp.73-81
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• 1999

Scatter correction for single photon emission computed tomography (SPECT) plays an important role to improve image quality and quantitation. The purpose of this study was to investigate three scatter correction methods using Monte Carlo simulation. Point source and Jaszack phantom filled with Tc-99m were simulated by Monte Carlo code, SIMIND. For scatter correction, we applied three methods, Compton window (CW) method, triple window (TW) method, and dual photopeak window (DPW) method. Point sources located at various depths along the center line within a 20-cm phantom were simulated to calculate the window ratios and corresponding scatter fractions by evaluating the polynomial coefficients for DPW method. Energy windows were located in W$_1$=92-125 keV, W$_2$=124-126 keV, W$_3$=136-140 keV, W$_4$=140-141 keV, and W$_{5}$=154-156 keV. The results showed that in Jaszack phantom with cold sphere and hot sphere, the TW gave the closest contrast and percentage recovery to the ideal image, respectively, while CW overestimated and DPW underestimated the contrast of ideal one. All three scatter correction methods showed an improved image contrast. In conclusion, scatter correction is essential for improving image contrast and accurate quantification. The choice of scatter correction method should be made on the basis of accuracies and ease of implementation.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.101-113
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• 2001

Since late 1970s. one of the principal research areas in transportation problem is dynamic traffic assignment (DTA). Although many models have been developed regarding DTA, yet they have some limits of describing real traffic patterns. This reason comes from the fact that DTA model has the time varying constraints such as state equation, flow propagation constraint, first in first out(FIFO) rule and queuing evolution. Thus, DTA model should be designed to satisfy these constraints as well as dynamic route choice condition, dynamic user equilibrium. In this respect, link-based DTA models have difficulty in satisfying such constraints because they have to satisfy the constraints for each link, while path-based DTA models may easily satisfy them. In this paper we develop a path-based DTA model. The model includes point queue theory to describe the queue evolution and simulation loading method for depicting traffic patterns in more detail. From a numerical test, the model shows promising results.

• Journal of the Korea Society for Simulation
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• v.20 no.3
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• pp.69-78
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• 2011

A large-scale sensor network usually operates in open and unattended environments, hence individual sensor node is vulnerable to various attacks. Therefore, malicious attackers can physically capture sensor nodes and inject false reports into the network easily through compromised nodes. These false reports are forwarded to the base station. The false report injection attack causes not only false alarms, but also the depletion of the restricted energy resources in a battery powered network. The statistical en-route filtering (SEF) mechanism was proposed to detect and drop false reports en route. In SEF, the choice of routing paths largely affect the energy consumption rate and the detecting power of the false report. To sustain the secure routing path, when and how to execute the path re-selection is greatly need by reason of the frequent network topology change and the nodes's limitations. In this paper, the regional path re-selection period determination method is proposed for efficient usage of the limited energy resource. A fuzzy logic system is exploited in order to dynamically determine the path re-selection period and compose the routing path. The simulation results show that up to 50% of the energy is saved by applying the proposed method.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.85-96
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• 2003

To build traffic information providing services by ITS technology should be carried out effect analysis in the first step for social and individual advantages. The propose on this study is to make clear what influences of highway network by traffic information are, and what differences between drivers who use traffic information and drivers who do not use that for route choice are. For these propose. travel time and forecast error of travel time on network and traffic information dependence of driver are analyzed by simulation. As a result of analysis travel time and forecast error of travel time is that the efficiency and reliability of travel time were increased when getting more drivers using traffic information in network. Drivers who using traffic information had advantage of decrease of travel time and forecast error in only definite situation. traffic information dependence analysis presented that drivers are dependent upon information and reliability of traffic information is also increased when drivers using traffic information become on increasing in network. In conclusion, considering the range of the traffic information user ratio in this simulation, this study presents that the traffic information service provides an advantage to the highway network and the drivers, and increases the dependence of information.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.563-574
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• 2023

Recently, climate change has affected functional responses of river basins to meteorological variables, emphasizing the importance of rainfall-runoff simulation research. Simultaneously, the growing interest in machine learning has led to its increased application in hydrological studies. However, it is not yet clear whether machine learning models are more advantageous than the conventional conceptual models. In this study, we compared the performance of the conventional GR6J model with the machine learning-based Random Forest model across 38 basins in Korea using both gauged and ungauged basin prediction methods. For gauged basin predictions, each model was calibrated or trained using observed daily runoff data, and their performance was evaluted over a separate validation period. Subsequently, ungauged basin simulations were evaluated using proximity-based parameter regionalization with Leave-One-Out Cross-Validation (LOOCV). In gauged basins, the Random Forest consistently outperformed the GR6J, exhibiting superiority across basins regardless of whether they had strong or weak rainfall-runoff correlations. This suggest that the inherent data-driven training structures of machine learning models, in contrast to the conceptual models, offer distinct advantages in data-rich scenarios. However, the advantages of the machine-learning algorithm were not replicated in ungauged basin predictions, resulting in a lower performance than that of the GR6J. In conclusion, this study suggests that while the Random Forest model showed enhanced performance in trained locations, the existing GR6J model may be a better choice for prediction in ungagued basins.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.53-74
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• 2012

This study developed a method for selection of available human resources for incomingjob allocation that considers factors affecting resource performance in the business process management (BPM) environment. For many years, resource selection has been treated as a very important issue in scheduling due to its direct influence on the speed and quality of task accomplishment. Even though traditional resource selection can work well in many situations, it might not be the best choice when dealing with human resources. Humanresource performance is easily affected by several factors such as workload, queue, working hours, inter-arrival time, and others. The resource-selection rule developed in the present study considers factors that affect human resource performance. We used a Bayesian Network (BN) to incorporate those factors into a single model, which we have called the Bayesian Selection Rule (BSR). Our simulation results show that the BSR can reduce waiting time, completion time and cycle time.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.2
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• pp.1-5
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• 2007

Wavelength-division multiplexed (WDM) networks are emerging to be the right choice for the future transport networks. In WDM networks, the optical layer provides circuit-switched lightpath services to the client layer such as IP, SONET and ATM. The set of lightpaths in the optical layer defines the virtual topology. Since the optical switches are reconfigurable, the virtual topology can be reconfigured in accordance with the changing traffic demand pattern at theclient layer in order to optimize the network performance. We present a new approach to the virtual topology reconfiguration and loadbalancing problem for wavelength-routed, optical wide-area networks under dynamic traffic demand. By utilizing the measured Internet backbone traffic characteristics, our approach follows the changes in traffic without assuming that the future traffic pattern is known. For the simulation traffic modeling, we collected the data from real backbone traffic. Experiments show that the standard deviation compared to previous technique is reduced.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3166-3187
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• 2017

For "generic" multivariate public key cryptography (MPKC) systems, experts believe that the Unbalanced Oil-Vinegar (UOV) scheme is a feasible signature scheme with good efficiency and acceptable security. In this paper, we address two problems that are to find inversion solution of quadratic multivariate equations and find another structure with some random Oil-Oil terms for UOV, then propose a novel signature scheme based on hyper-sphere (HS-Sign for short) which directly answers these two problems. HS-Sign is characterized by its adding Oil-Oil terms and more advantages compared to UOV. On the one side, HS-Sign is based on a new inversion algorithm from hyper-sphere over finite field, and is shown to be a more secure UOV-like scheme. More precisely, according to the security analysis, HS-Sign achieves higher security level, so that it has larger security parameters choice ranges. On the other side, HS-Sign is beneficial from both the key side and computing complexity under the same security level compared to many baseline schemes. To further support our view, we have implemented 5 different attack experiments for the security analysis and we make comparison of our new scheme and the baseline schemes with simulation programs so as to show the efficiencies. The results show that HS-Sign has exponential attack complexity and HS-Sign is competitive with other signature schemes in terms of the length of the message, length of the signature, size of the public key, size of the secret key, signing time and verification time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2372-2380
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• 2015

In this paper, we propose frequency allocation and path selection scheme in underlay cognitive radio (CR) networks using network coding. In the proposed scheme, we choose the path with consideration of network coding and interference temperature in underlay CR networks and propose an optimization problem to maximize the system throughput of secondary users (SUs). Then, we represent the proposed optimization problem as the multi-dimensional multiple-choice knapsack problem and give the theoretical upper bound for the system throughput of SUs by using linear programming. Finally, we compute the system throughput of SUs by using brute-force search (BFS) and link quality first (LQF) scheme in underlay CR networks. Simulation results show that the system throughput of SUs with BFS is higher than that with LQF in underlay CR networks with and without application of network coding, respectively.