• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.17-31
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• 2023

An activity-based model requires detailed population information to model individual travel behavior in a disaggregated manner. The recent innovative approach developed deep generative models with novel regularization terms that improves fidelity and diversity for population synthesis. Since the method relies on measuring the distance between distribution boundaries of the sample data and the generated sample, it is crucial to obtain well-defined continuous representation from the discretized dataset. Therefore, we propose an improved entity embedding models to enhance the performance of the regularization terms, which indirectly supports the synthesis in terms of feasible and diverse populations. Our results show a 28.87% improvement in the F1 score compared to the baseline method.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.190-200
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• 2014

The video-based system of the broadcasters and the video-related institutions have shifted from analogical to digital in worldwide. This migration process can generate a defect, digital dropout, in the quality of the contents. Moreover, there are limited researches focused on these kind of defects and those related have limitations. For that reason, we are proposing a new method for feature extraction emphasizing in the peculiar block pattern of digital dropout based on discrete cosine transform (DCT). For classification of error block, we utilize support vector machine (SVM) which can manage feature vectors efficiently. Further, the proposed method overcome the limitation of the previous one using continuity of frame by frame. It is using only the information of a single frame and works better even in the presence of fast moving objects, without the necessity of specific model or parameter estimation. Therefore, this approach is capable of detecting digital dropout only with minimal complexity.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.348-348
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• 2021

가뭄 연구의 궁극적 목표는 가뭄 발생의 메커니즘에 대한 이해를 높이고, 예측기술을 향상시켜 선제적 대응이 가능하도록 하는 것이다. 일반적으로 가뭄분석에 활용되는 가뭄지표는 연속형 변수로 간주하여 확률모형을 구축하지만, 가뭄상태와 가뭄피해 자료는 순서형 및 이산형 변수이므로 범주형 자료 분석 기법을 적용하는 것이 더 적절하다. 따라서 본 연구에서는 기상학적 가뭄과 피해발생 사이의 관계를 규명하기 위해 범주형 자료 분석 방법 중 로그선형(log-linear) 모형과 로지스틱(logistic) 회귀모형을 활용하였다. 가뭄피해 예측을 위한 가뭄 피해 정보를 수집하는 것은 매우 어려운 일이다. 가뭄의 영향으로 인해 발생할 수 있는 피해의 종류가 다양하며, 여러 분야의 이해관계자가 받아들이는 가뭄의 피해 양상이 다르기 때문이다. 본 연구에서는 국가가뭄정보포털(drought.go.kr)에서 충청북도의 가뭄피해현황 자료를 수집하였다. 30년(1991~2020년)동안 238개 읍면동 중 34개 행정구역에서 총 272건의 가뭄피해가 발생한 것으로 확인되었다. 표준강수지수(SPI)를 이용하여 분석된 지역별 연평균 가뭄발생횟수는 약 8.44회이며, 가뭄이 가장 많이 발생한 해는 2001년(평균 가뭄발생 18.7회)이었다. 강수의 부족으로 인해 발생하는 기상학적 가뭄이 사회경제적 피해를 야기하는 수문학적 가뭄으로 전이되기까지 몇 주에서 몇 달까지 시간이 소요된다. 이러한 관계를 파악하기 위해 가뭄피해 발생 여부를 예측변수, 가뭄피해 발생 이전의 가뭄상태를 설명변수로 설정하여 기상학적 가뭄 발생에 따른 가뭄피해 발생 확률을 산정하였다. 그 결과 가뭄피해 발생 당시의 가뭄상태보다 그 이전에 연속된 가뭄상태가 있을 경우 가뭄피해 발생 확률이 약 2.5배 상승하는 것으로 나타났다.

• Journal of Animal Science and Technology
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• v.46 no.2
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• pp.137-144
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• 2004

Algorithms for estimating breeding values on several categorical data by using latent variables with threshold conception were developed and showed. Thresholds on each categorical trait were estimated by Newton’s method via gradients and Hessian matrix. This algorithm was developed by way of expansion of bivariate analysis provided by Quaas(2001). Breeding values on latent variables of categorical traits and observations on linear traits were estimated by preconditioned conjugate gradient(PCG) method, which was known having a property of fast convergence. Example was shown by simulated data with two linear traits and a categorical trait with four categories(CE=calving ease) and a dichotomous trait(SB=Still Birth) in threshold animal mixed model(TAMM). Breeding value estimates in TAMM were compared to those in linear animal mixed model (LAMM). As results, correlation estimates of breeding values to parameters were 0.91${\sim}$0.92 on CE and 0.87${\sim}$0.89 on SB in TAMM and 0.72~0.84 on CE and 0.59~0.70 on SB in LAMM. As conclusion, PCG method for estimating breeding values on several categorical traits with linear traits were feasible in TAMM.

• Journal of the Korea Society for Simulation
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• v.22 no.1
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• pp.21-30
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• 2013

A hybrid system is a combination of sub systems which have different types of state and time: a typical example is a combination of discrete event and continuous systems. A HDEVS(Hybrid DEVS) formalism was proposed for modeling and analyzing a hybrid system. The HDEVS formalism allows modelers to construct a hierarchical and modular model based on the mathematical set theory. Because the HDEVS formalism was applied to the distributed and interoperated simulators, modelers should make several heterogenous models dividing a target system. Hence, this paper proposes an extended hybrid coupled model of HDEVS formalism and an integrated hybrid modeling methodology in contrast to the existing simulation framework on interoperable simulators. By applying the proposed modeling method, a target system can be translated to a hybrid model in a similar form as the target system. This paper also contains a simulation engine design for the proposed modeling methodlogy and a case study which simulates water tank control systems.

• Smart Media Journal
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• v.1 no.2
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• pp.12-22
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• 2012

Today we are witnessing an increasingly widespread use of cameras in our lives for video surveillance, robot vision, and mobile phones. This has led to a renewed interest in computer vision in general and an on-going boom in human activity recognition in particular. Although not particularly fancy per se, human gait is inarguably the most common and frequent action. Early on this decade there has been a passing interest in human gait recognition, but it soon declined before we came up with a systematic analysis and understanding of walking motion. This paper presents a set of DBN-based models for the analysis of human gait in sequence of increasing complexity and modeling power. The discussion centers around HMM-based statistical methods capable of modeling the variability and incompleteness of input video signals. Finally a novel idea of extending the discrete state Markov chain with a continuous density function is proposed in order to better characterize the gait direction. The proposed modeling framework allows us to recognize pedestrian up to 91.67% and to elegantly decode out two independent gait components of direction and posture through a sequence of experiments.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.101-107
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• 1990

In this work, one-dimensional simulation is carried out for PT-GaAs Schottky barrier diodes with finite difference method. Shockley's semiconductor governing equations: Poisson equation and current continuity equation are discertized, and linearized by Newton-Raphson method. The linear system of equation is solved by Gaussian elimination method until convergence is achieved. The boundary condition for this equation is taken from thermionic emission-diffusion theory. Simulation is done for PT-GaAs epitaxial-layer Schottky barrier diodes. The claculated results of electron and potential distribution are shown. Simulation results show exellent agreement with experiments.

• Journal of Biomedical Engineering Research
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• v.24 no.6 s.81
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• pp.487-494
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• 2003

The sleep stages provides the most basic evidence for diagnosing a variety of sleep diseases. for staging sleep by analysis of EEG(electroencephalogram), it is especially important to detect the characteristic waveforms from EEG. In this paper, sleep EEG signals were analyzed using Fourier transform and continuous wavelet transform as well as discrete wavelet transform. Proposeed system methods. Fourier and wavelet for detecting of important characteristic waves(hump, sleep spindles. K-complex, hill wave, ripple wave) in sleep EEG. Sleep EEG data were analysed using Daubechies wavelet transform method and FFT method. As a result of simulation, we suggest that our neural network system attain high performance in classification of characteristic waves.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.7
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• pp.647-654
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• 2007

A Discrete continuation Method/homotopy approaches are studied for energy/fuel optimal low thrust Earth escape trajectory by solving a two point boundary value problem(TPBVP). Recently, maneuvers using low thrust propulsion system have been identified as emerging technologies. The low thruster is considered as the main actuator for orbit maneuvers. The cost function consists of a energy/fuel consumption function, and constraints are position and velocity vectors at the terminal escape point. Solving the minimum energy/fuel problem directly is not an easy task, so we adopt the homotopy analysis. Using a solution of the minimum energy, which is solved by discrete continuation method, we obtain the solution of the minimum fuel problem.

• Journal of the Korea Society for Simulation
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• v.24 no.3
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• pp.97-105
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• 2015

This paper is to analyze the efficiency of power consumption in logistic systems that are based on self-driving roller conveyors by the simulation technology. The improvement of the efficiency brings advantages for reducing greenhouse gas emission and logistics costs. A self-driving roller conveyor is operated only when products are loaded on itself. Thus, the self-driving roller conveyor systems consume less electric power than continuous-driving roller conveyor systems. In this paper, we design a DEVS (Discrete-Event based System) based simulation model and construct self-driving roller and continuous-driving roller conveyor models. For the verification and validation of the designed simulation system and conveyor models, we model a corresponding logistic model for the experimental environment and compare between the model and a real system. The main objective of this paper is to describe the power consumption advantage of self-driving roller conveyor based logistic systems using a simulation method.