• Korean Business Review
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• v.20 no.2
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• pp.15-27
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• 2007

This paper analyzed the relationship between Housing Purchase Price volatility of Seoul and Housing Purchase Price volatility of local large city. Other studies investigates the effect on the observed volatility Observed volatility consists of fundamental volatility and transitory volatility. Fundamental volatility is caused by information arrival and transitory volatility is caused by noise trading. Fundamental volatility is trend component and is modelled as a random walk with drift. Transitory volatility is cyclical component and is modelled as a stationary process. In contrast to other studies, this study investigates the effect on the fundamental volatility and transitory volatility individually. Observed volatility is estimated by GJR GARCH(1,1) model. We find that GJH GARCH model is superior to GARCH model and good news is more remarkable effect on volatility than bad news. This study decomposes the observed volatility into fundamental volatility and transitory volatility using Kalman filtering method. The findings in this paper is as follows. The correlation between Seoul housing price volatility and Busan housing price volatility is high. But, the correlation between Seoul and Daejeon is low. And the correlation between Daejeon and Busan is low. As a distinguishing feature, the correlation between fundamental volatilities is high in the case of all pairs. But, the correlation between transitory volatilities turns out low. The reason is as follows. When economic information arrives, Seoul, Daejeon, and Busan housing markets, all together, are affected by this information.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.64.2-64.2
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• 2016

Optical variability is one way to probe the nature of the central engine of AGN at smaller linear scales and previous studies have shown that optical variability is more prevalent at longer timescales and at shorter wavelengths. Especially, intra-night variability can be explained through the damped random walk model but small samples and inhomogeneous data have made constraining this model hard. To understand the properties and physical mechanism of optical variability, we are performing the KMTNet Active Nuclei Variability Survey (KANVaS). Test data of KMTNet in the COSMOS field was obtained over 2 separate nights during 2015, in B, V, R, and I bands. Each night was composed of 5 and 9 epochs with ~30 min cadence. To find AGN in the COSMOS field, we applied multi-wavelength selection methods. Different selection methods means we are looking different region in unification model of AGN, and 100~120, 400~500, 50~100 number of AGN are detected in X-ray, mid-infrared, and radio selection of AGN, respectively. We performed image convolution to reflect seeing fluctuation, then differential photometry between the selected AGN and nearby stars to achieve photometric uncertainty ~0.01mag. We employed one of the standard time-series analysis tools to identify variable AGN, chi-square test. Preliminarily results indicate that intra-night variability is found for X-ray selected, Type1 AGN are 23.6%, 26.4%, 21.3% and 20.7% in the B, V, R, and I band, respectively. The majority of the identified variable AGN are classified as Type 1 AGN, with only a handful of Type 2 AGN showing evidence for variability. The work done so far confirms that there are type and wavelength dependence of intra-night optical variability of AGN.

• Smart Structures and Systems
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• v.17 no.6
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• pp.957-980
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• 2016

Structural damage detection (SDD) is a challenging task in the field of structural health monitoring (SHM). As an exploring attempt to the SDD problem, a hybrid self-adaptive Firefly-Nelder-Mead (SA-FNM) algorithm is proposed for the SDD problem in this study. First of all, the basic principle of firefly algorithm (FA) is introduced. The Nelder-Mead (NM) algorithm is incorporated into FA for improving the local searching ability. A new strategy for exchanging the information in the firefly group is introduced into the SA-FNM for reducing the computation cost. A random walk strategy for the best firefly and a self-adaptive control strategy of three key parameters, such as light absorption, randomization parameter and critical distance, are proposed for preferably balancing the exploitation and exploration ability of the SA-FNM. The computing performance of the SA-FNM is evaluated and compared with the basic FA by three benchmark functions. Secondly, the SDD problem is mathematically converted into a constrained optimization problem, which is then hopefully solved by the SA-FNM algorithm. A multi-step method is proposed for finding the minimum fitness with a big probability. In order to assess the accuracy and the feasibility of the proposed method, a two-storey rigid frame structure without considering the finite element model (FEM) error and a steel beam with considering the model error are taken examples for numerical simulations. Finally, a series of experimental studies on damage detection of a steel beam with four damage patterns are performed in laboratory. The illustrated results show that the proposed method can accurately identify the structural damage. Some valuable conclusions are made and related issues are discussed as well.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.791-799
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• 2015

In random walk hypothesis, we assume that current change of financial time series is independent of past values. It is interpreted as an existency of a unit root in ARMA models and many researches have been focused on whether ${\rho}$ < 1 or not. If some financial data are generated from an explosive autoregressive model, the chance of a bubble economy increases. We have to find the symptoms of it in advance. Since some well-known parameter estimators contain the parameter itself and other statistic is constructed under a specific parameter structure assumption, those are difficut to be adopted. In this paper we investigate a test for explosive autoregressive models using slope signs. We found the properties of the slope sign test statistic under both independent error and correlated error conditions, mainly by simulations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.190-197
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• 2010

The ACR (Access Control Router) of WiBro processes location registration of the Correspondent Node and Home Agent as the Correspondent Node moves between ACRs. Therefore, the location update cost is low compared with MIPv6. However, all packets which are sent and received are sent through the ACR, so as the number of mobile nodes that are managed by the ACR increases, the cost of packet delivery also increases. Therefore, the communication state of the ACR domain remains smooth when the ACR which manages the mobile node in the ACR domain has good performance. However, network delays occur unless the ACR performs well, so the role of the ACR is important. In this paper, we analysis performance of the ACR for efficient realization of the WiBro standard. By using the Deny Probability and the Total Profit of ACR performance and apply it to the Random Walk Mobility model as the mobility model.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.1
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• pp.113-122
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• 2007

In this paper, we propose a multi-state based hybrid location update scheme, which integrates the time-based and the movement-based methods. In the proposed scheme, a mobile terminal updates its location after n cell boundary crossing and a time interval of T[sec]. We derive an analytical solution for the performance of the hybrid scheme with exponential cell resident time and evaluate it numerically with time-varying random walk mobility model, which we model as multi-states Markov chain. Furthermore, we also evaluate the scheme for arbitrary cell resident times by simulation. From the numerical analysis and the simulation results, we prove that the proposed scheme significantly outperforms the time-based and the movement-based methods, when implemented alone, more accurately adapting to the time-varying user mobility.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.3030-3038
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• 2023

Nowadays, mobile robots have been used to search for uncontrolled radioactive source in indoor environments to avoid radiation exposure for technicians. However, in the indoor environments, especially in the presence of obstacles, how to make the robots with limited sensing capabilities automatically search for the radioactive source remains a major challenge. Also, the source search efficiency of robots needs to be further improved to meet practical scenarios such as limited exploration time. This paper proposes an automatic source search strategy, abbreviated as ACA: the location of source is estimated by a convolutional neural network (CNN), and the path is planned by the A-star algorithm. First, the search area is represented as an occupancy grid map. Then, the radiation dose distribution of the radioactive source in the occupancy grid map is obtained by Monte Carlo (MC) method simulation, and multiple sets of radiation data are collected through the eight neighborhood self-avoiding random walk (ENSAW) algorithm as the radiation data set. Further, the radiation data set is fed into the designed CNN architecture to train the network model in advance. When the searcher enters the search area where the radioactive source exists, the location of source is estimated by the network model and the search path is planned by the A-star algorithm, and this process is iterated continuously until the searcher reaches the location of radioactive source. The experimental results show that the average number of radiometric measurements and the average number of moving steps of the ACA algorithm are only 2.1% and 33.2% of those of the gradient search (GS) algorithm in the indoor environment without obstacles. In the indoor environment shielded by concrete walls, the GS algorithm fails to search for the source, while the ACA algorithm successfully searches for the source with fewer moving steps and sparse radiometric data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1281-1291
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• 2015

Compared to the past, people can control end devices via open channel. Although this open channel provides convenience to users, it frequently turns into a security hole. In this paper, we propose a new human-centered security risk analysis method that puts weight on the relationship between end devices. The measure derives from the concept of entropy rate, which is known as the uncertainty per a node in a network. As there are some limitations to use entropy rate as a measure in comparing different size of networks, we divide the entropy rate of a network by the maximum entropy rate of the network. Also, we show how to avoid the violation of irreducible, which is a precondition of the entropy rate of a random walk on a graph.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.111-122
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• 2004

The driver's decision making (e.g. route choice) is a typical decision making with an uncertainty. In this paper, we investigate the effect of route guidance information on driver's route choice and learning behavior and analyse the potential of information system in a road network in which traffic flows follow random walk. A Simulation performed focuses on the relationship among the network wide performance, message receiving rates and driver's learning mechanism. We know that at high levels of message receiving rates, the network-wide performance may get worse. However, at low levels of receiving rates, we found that the travel time when guidance information is provided decrease compared to the cases when no pubic information is provided. Also, we found that the learning parameter of the learning mechanism model always changes under nonstationary traffic condition. In addition, learning process of drivers does not converge on any specific value. More investigation is needed to enlarge the scope of the study and to explore more deeply driver's behavior.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.1
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• pp.70-78
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• 2011

At Haeundae Beach in Busan, people were swept away by the fast-moving rip current and rescued, on August 13th and 15th, 2009 & July 29th and 30th, 2010. In predicting the wave-induced current and consequent tube movement for public safety, the coastal flows and waves are calculated at each time step and grid point by means of systematic interfacing of hydrodynamic and wave models (Lee, 2001). To provide a user-friendly simulation tool for end-users, the forecasting system has been built in a software package called HAECUM. Outputs from the system are viewed as graphs of tube positions with combined current vectors for easy decision of emergency management officials. The tube-wave interaction is taken into account and the traces of swim tube are simulated by using a Lagrangian random walk (Chorin, 1978; Lee, 1994). In this study, we use the Lee's approach (Lee, 1993) in estimating the surface onshore currents due to wave breaking.