• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.125-136
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• 2005

The goal of this paper is to develop freeway Origin-Destination (OD) demand estimation model using VDS and AVI data. The formulation of methodology proposed in this paper includes traffic flow technique to be able to remove the bi-level problem and optimal solution algorithm using a kalman filter algorithm. The proposed dynamic OD estimation model use ilk and off-ramp volumes collected from VDS and partial OD collected from AVI data to raise the accuracy of dynamic OD estimation. The proposed model is evaluated by using the real-time data of SOHAEAN freeway, South Korea. The result of the proposed dynamic OD estimation model based on VDS and AVI data is better than that of based on VDS data. The more AVI systems are equipped at on and off-ramp, the more excellent result of estimation accuracy is expected.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.52-68
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• 2019

Aiming at the optimal placement of communication relay nodes (OPCRN) problem in manned/unmanned aerial vehicle cooperative engagement system, this paper designed a kind of fully connected broadband backbone communication topology. Firstly, problem description of OPCRN was given. Secondly, based on problem analysis, the element attributes and decision variables were defined, and a bi-level programming model including physical layer and logical layer was established. Thirdly, a hierarchical artificial bee colony (HABC) algorithm was adopted to solve the model. Finally, multiple sets of simulation experiments were carried out to prove the effectiveness and superiority of the algorithm.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.111-123
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• 2005

A network design model has been proposed. which represents a transportation facility investment decision problem. The model takes the discrete hi-level programming form in which two types of decision makers, government and travelers, are involved. The model is characterized by its ability to address the total social costs occurring in transportation networks and to estimate the equilibrium link volumes in multi-modal networks. Travel time and volume for each link in the multi-modal network are predicted by a joint modal split/traffic assignment model. An efficient solution algorithm has been developed and an illustrative example has been presented.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.477-484
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• 1997

In this paper, we proposed the compensation method to evaluate arousal level in different initial arousal states. Arousal level was measured by the relationship between IRI and Nz. Since Nz is affected by BI which is directly proportional to initial arousal state of subjects, the arousal level is underestimated To overcome this problem, we proposed the compensation method using modified Karolinska sleepiness scale, and determined compensation coefficients derived from this scale with five arousal levels. Applying these coefficients to portable arousal monitoring system, the proposed method in this paper could be useful for real-time evaluation and control of arousal level. As a result the developed system can detect and control the arousal state from initial drowsing sate.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.373-377
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• 2017

This paper presents a voice-activity detection (VAD) method for sound sequences with various SNRs. For real-time VAD applications, it is inadequate to employ a post-processing for the removal of burst clippings from the VAD output decision. To tackle this problem, building on the bi-level hidden Markov model, for which a state layer is inserted into a typical hidden Markov model (HMM), we formulated a robust method for VAD not requiring any additional post-processing. In the method, a forward-inference-ratio test was devised to detect the speech endpoints and Mel-frequency cepstral coefficients (MFCC) were used as the features. Our experiment results show that, regarding different SNRs, the performance of the proposed approach is more outstanding than those of the conventional methods.

• Steel and Composite Structures
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• v.47 no.5
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• pp.569-585
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• 2023

This paper proposes an efficient approach for the structural topology optimization of bi-directional functionally graded structures by incorporating popular radial basis functions (RBFs) into an implicit level set (ILS) method. Compared to traditional element density-based methods, a level set (LS) description of material boundaries produces a smoother boundary description of the design. The paper develops RBF implicit modeling with multiquadric (MQ) splines, thin-plate spline (TPS), exponential spline (ES), and Gaussians (GS) to define the ILS function with high accuracy and smoothness. The optimization problem is formulated by considering RBF-based nodal densities as design variables and minimizing the compliance objective function. A LS-RBF optimization method is proposed to transform a Hamilton-Jacobi partial differential equation (PDE) into a system of coupled non-linear ordinary differential equations (ODEs) over the entire design domain using a collocation formulation of the method of lines design variables. The paper presents detailed mathematical expressions for BiDFG beams topology optimization with two different material models: continuum functionally graded (CFG) and mechanical functionally graded (MFG). Several numerical examples are presented to verify the method's efficiency, reliability, and success in accuracy, convergence speed, and insensitivity to initial designs in the topology optimization of two-dimensional (2D) structures. Overall, the paper presents a novel and efficient approach to topology optimization that can handle bi-directional functionally graded structures with complex geometries.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.147-156
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• 2009

We present a methodology for modeling and solving the transit frequency design problem with variable demand. The problem is described as a bi-level model based on a non-cooperative Stackelberg game. The upper-level operator problem is formulated as a non-linear optimization model to minimize net cost, which includes operating cost, travel cost and revenue, with fleet size and frequency constraints. The lower-level user problem is formulated as a capacity-constrained stochastic user equilibrium assignment model with variable demand, considering transfer delay between transit lines. An efficient algorithm is also presented for solving the proposed model. The upper-level model is solved by a gradient projection method, and the lower-level model is solved by an existing iterative balancing method. An application of the proposed model and algorithm is presented using a small test network. The results of this application show that the proposed algorithm converges well to an optimal point. The methodology of this study is expected to contribute to form a theoretical basis for diagnosing the problems of current transit systems and for improving its operational efficiency to increase the demand as well as the level of service.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.99-106
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• 2004

This paper presents some comparisons between Cournot-Nash and Stackelberg game in bi-level program, composed of both upper level program and lower level one. The upper level can be formulated to optimize a specific objective function, while the lower formulated to express travelers' behavior patterns corresponding to the design parameter of upper level problem. This kind of hi-level program is to determine a design parameter, which leads the road network to an optimal state. Bi-level program includes traffic signal control, traffic information provision, congestion charge and new transportation mode introduction as well as road expansion. From the view point of game theory, many existing algorithms for bi-level program such as IOA (Iterative Optimization Assignment) or IEA (Iterative Estimation Assignment) belong to Cournot-Nash game. But sensitivity-based algorithms belongs to Stackelberg one because they consider the reaction of the lower level program. These two game models would be compared by using an example network and show some results that there is no superiority between the models in deterministic case, but in stochastic case Stackelberg approach is better than that of Cournot-Nash one as we expect.

• Korean Journal of Health Education and Promotion
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• v.32 no.5
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• pp.43-51
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• 2015

Objectives: Socioeconomic factors are one of the significant factors explaining drinking problems in our society. From the poverty and inequality perspective, not only absolute poverty but perceived level of poverty or inequality has a direct effect on one's health and health behaviors. The purpose of the study is to explore the growth trajectories of problem drinking in Korea in relation to poverty and perceived income. Methods: Data from 13,414 adults were analyzed using 4 years of data (2010 to 2014) from the Korea Welfare Panel. Main variables included poverty status, perceived income inequality, and problem drinking. A latent growth modeling was employed for the analysis. Results: The non-poverty group had higher initial level of problem drinking; however, the poverty group showed higher rate of increase in problem drinking rate. The perceived income inequality had no significant influence on the initial level, but over time, those with higher level of perceived income inequality showed higher rate of increase in problem drinking. Conclusions: Findings showed that poverty and inequality affect changes in problem drinking. Efforts to prevent and decrease problems related to alcohol should not only focus on changing individuals' behavior but also on decreasing the inequality gap.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.675-685
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• 2014

This paper develops a differentiated pricing strategy over each segment of expressways based on the second-best pricing method for reducing congestion. To this end, a bi-level problem is proposed, in which the upper level of the model is formulated to determine toll level of each segment for minimizing traffic congestion, whereas the lower level of the model is formulated as a variable demand assignment problem. The sensitivity analysis based algorithm is took placed to find optimal solutions of upper level model. An application of the proposed model uses the modified Sioux-Falls network. The results show that the segment-based differentiated pricing strategy performs better than the existing uniform pricing strategy in reducing traffic congestion. This study can be applied as a demand management method to relieve disutility of excessively congested segments of expressways.