• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.41-50
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• 2008

In this study, an improved scheme for distance-based registration (DBR) is proposed and its performance is analyzed. In the DBR, when a mobile station (MS) enters a new cell, it calculates the distance between last registered cell and current cell and registers its location if the distance reaches reference distance D. In this study, two-location DBR (TDBR) is proposed to improve the performance of the DBR. In the TDBR, an MS stores not only last registered location area (LA) but also previously registered LA, and then no registration is needed when the MS crosses two LAs stored already. However, since the TDBR may increase paging cost, trade-off is necessary between decreased registration cost and increased paging cost. In this study, the performances of two schemes are analyzed and compared using 2-dimensional random walk mobility model in hexagonal cell configuration. We show that our mathematical analysis is accurate by comparing with simulation. From the numerical results for various circumstances, it is shown that our proposed TDBR outperforms current DBR in most cases.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.97-107
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• 2012

The Internet is becoming increasingly diverse and complex, the needs of user's convenience is also various and increased. The task forces have been working on how to design the future Internet in satisfaction of user's require and mobility management is one of the key issues to be considered. mobility management in the future Internet is still being designed in an "all-in-one" way where all management functions are tightly kept at a single location and this results in cost inefficiency that can be an obstruction to constructing flexible systems. In this paper, we propose a cost-effective function-distributed mobility management scheme that can enable more flexible future Internet construction. Furthermore, we show the effectiveness of our proposed system via a cost analysis and computer simulation with a random walk mobility model.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.503-519
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• 2005

Cointegration test is usually performed under the assumption that the cointegrating vector is constant for the whole sample period. Most previous studies have used conventional cointegration methods in testing for a stable long-run equilibrium relation among related variables. However they have overlooked that the long-run equilibrium may not the unique and the stable relation may not be guaranteed. This study develops the additional statistical tests for the stability of the estimated cointegrating vector. Three tests for the parameter stability of a cointegrated regression model are utilized and applied to identify the types of variations in the long-run relation between the domestic unemployment and the rotated macroeconomic variables of interest. The present paper finds that, there exists a stable but, time-varying long-run relation between those. The observed variation in cointegrating relations is generally characterized by a discrete one-time shift, rather than a gradually evolving random walk process which is attributable to the IMF financial and economic crisis.

• Economic Analysis
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• v.27 no.2
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• pp.1-40
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• 2021

Using an unobserved components model that features trend growth as a random walk, we find that GDP trend growth rates had gradually declined from the late 1980s to early 2010s in Korea. To uncover the underlying features of the slowdown, we use trend growth accounting. A major feature appears to be a significant decline in the growth rate of labor productivity. To be specific, the first gradual decline in trend growth, which started in 1988 and continued to 1998, is associated with a drop in TFP measured in labor-augmenting units. This finding is inconsistent with the hypothesis that the slowdown in GDP trend growth can be attributed to the 1997-1998 Korean financial crisis. Sluggish investment growth is behind the second period of the gradual slowdown, from 2002 to 2012.

• Journal of the Korean Society for Marine Environment & Energy
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• v.11 no.1
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• pp.13-23
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• 2008

In coastal region, eutrophication, Do deficit and red tide are frequently occurred by influx of fresh water. When the fresh water containing pollutants is discharged into the sea, the surrounding water is contaminated by dispersion of freshwater flowing into coastal waters. The prediction and analysis about the dispersion process of the discharged fresh water should be conducted. A modeling system using GUI was developed to simulate hydrodynamic flow and fresh water dispersion in coastal waters and to analyze the results efficiently. The modeling module of the system includes a tide model using a finite element method and a fresh water dispersion model using a particle-tracking method. This system was applied to predict the tidal currents and fresh water dispersion in Mokpo coastal zone. To verify accuracy of the hydrodynamic model, the simulation results were compared with observed sea level and time variations of tidal currents showing a good agreement. The fresh water dispersion was verified with observed salinity distribution. The dispersion model also was verified with analytic solutions with advection-diffusion problems in 1-dimensional and 2-dimensional simple domain. The system is operated on GUI environment, to ease the model handling such as inputting data and displaying results. Therefore, anyone can use the system conveniently and observe easily and accurately the simulation results by using graphic functions included in the system. This system can be used widely to decrease the environmental disaster induced by inflow of fresh water into coastal waters.

• Journal of KIISE:Information Networking
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• v.31 no.5
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• pp.490-500
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• 2004

In mobile/wireless environment, mobility management is widely being focused as one popular researches. But, disruption happens when messages are exchanged between nodes as registration is made after handoff, and unnecessary traffic occurs because of the use of the Random-walk model, in which the probability for MN to move to neighboring cells is equal. In order to solve these problems, this study proposes a technique and algorithm for composing Directional Shadow Registration Region (DSRR) that provides seamless mobility. The core of DSRR is to prevent disruption and unnecessary traffic by minimizing the number o) neighboring cells with a high probability of handoff (AAAF). This study sensed the optimal time for handoff through regional cell division by introducing a division scheme, and then decided DSRR, the region for shadow registration, by applying direction vector (DV) obtained through directional cell sectoring. According to the result of the experiment, the proposed DSRR processes message exchange between nodes within the intra-domain, the frequency of disruptions decreased significantly compared to that in previous researches that process in inter-domain environment. In addition, traffic that occurs at every handoff happened twice in DSRR compared to n (the number of neighboring cells) times in Previous researches. As an additional effect, divided regions obtained from the process of composing DSRR filter MN that moves regardless of handoff.

• Journal of Environmental Science International
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• v.13 no.8
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• pp.721-731
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• 2004

The dispersion of suspended particulates in the coastal complex terrain of mountain-inland basin (city)-sea, considering their recycling was investigated using three-dimensional non-hydrostatic numerical model and lagrangian particle model (or random walk model). Convective boundary layer under synoptic scale westerly wind is developed with a thickness of about I km over the ground in the west of the mountain, while a thickness of thermal internal boundary layer (TIBL) is only confined to less than 200m along the eastern slope of the mountain, below an easterly sea breeze circulation. At the mid of the eastern slop of the mountain, westerly wind confronts easterly sea breeze, which goes to the height of 1700 m above sea level and is finally eastward return flow toward the sea. At this time, particulates floated from the ground surface of the city to the top of TIBL go along the eastern slope of the mountain in the passage of sea breeze, being away the TIBL and reach near the top of the mountain. Then those particulates disperse eastward below the height of sea-breeze circulation and widely spread out over the coastal sea. Total suspended particulate concentration near the ground surface of the city is very low. On the other hand, nighttime radiative cooling produces a shallow nocturnal surface inversion layer (NSIL) of 200 m thickness over the inland surface, but relatively thin thickness less than 100m is found near the mountain surface. As synoptic scale westerly wind should be intensified under the association of mountain wind along the eastern slope of mountain to inland plain and further combine with land-breeze from inland plain toward sea, resulting in strong wind as internal gravity waves with a hydraulic jump motion bounding up to about 1km upper level in the atmosphere in the west of the city and becoming a eastward return flow. Simultaneously, wind near the eastern coastal side of the city was moderate. Since the downward strong wind penetrated into the city, the particulate matters floated near the top of the mountain in the day also moved down along the eastern slope of the mountain, reaching the. downtown and merging in the ground surface inside the NSIL with a maximum ground level concentration of total suspended particulates (TSP) at 0300 LST. Some of them were bounded up from the ground surface to the 1km upper level and the others were forward to the coastal sea surface, showing their dispersions from the coastal NSIL toward the propagation area of internal gravity waves. On the next day at 0600 LST and 0900 LST, the dispersed particulates into the coastal sea could return to the coastal inland area under the influence of sea breeze and the recycled particulates combine with emitted ones from the ground surface, resulting in relatively high TSP concentration. Later, they float again up to the thermal internal boundary layer, following sea breeze circulation.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.54.1-54.1
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• 2016

Multi-wavelength variability is a staple of active galactic nuclei (AGN). Optical variability probes the nature of the central engine of AGN at smaller linear scales than conventional imaging and spectroscopic techniques. Previous studies have shown that optical variability is more prevalent at longer timescales and at shorter wavelengths. 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 intra-night optical variability, we are performing the KMTNet Active Nuclei Variability Survey (KANVaS). Using KMTNet, we aim to study the intra-night variability of ~1000 AGN at a magnitude depth of ~19mag in R band over a total area of ${\sim}24deg^2$ on the sky. Test data in the COSMOS, XMM-LSS, and S82-2 fields was obtained over 4, 6, and 8 nights respectively during 2015, in B, V, R, and I bands. Each night was composed of 5-13 epoch with ~30 min cadence and 80-120 sec exposure times. As a pilot study, we analyzed data in the COSMOS field where we reach a magnitude depth of ~19.5 in R band (at S/N~100) with seeing varying between 1.5-2.0 arcsec. We used the Chandra-COSMOS catalog to identify 166 AGNs among 549 AGNs at B<23. We performed differential photometry between the selected AGN and nearby stars, achieving photometric uncertainty ~0.01mag. We employ various standard time-series analysis tools to identify variable AGN, including the chi-square test. Preliminarily results indicate that intra-night variability is found for ~17%, 17%, 8% and 7% of all X-ray selected AGN 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 there are more variable AGN at shorter wavelengths and that intra-night variability most likely originates in the accretion disk of these objects. We will briefly discuss the quality of the data, challenges we encountered, solutions we employed for this work, and our updated future plans.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.420-426
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• 2018

The purpose of this paper is to examine the business cycle in the Jeju region and what differences exist in relation to the nation as a whole, to calculate the relative importance between the random walk stochastic trend and cyclical factor, and to find out its causes and implications. Results of empirical analysis found that the characteristics of the business cycle in the Jeju region were as follows: First, the Jeju region, which is likely to have a growth component of the economy such as technological development and the accumulation of capital, was projected to have a possibility of high growth due to a greater proportion of the stochastic trend factor(46.8%) than the entire country(27.8%). Secondly, employment fluctuation in Jeju, which varies from 0.007 to 0.058 depending on the model, was lowest compared to the fluctuation of other indicators. The employment market in Jeju remained firm, showing that it is not smooth enough to create new jobs despite the production growth in industry. Third, the tourism industry was acting as a stabilizing factor, whereas the mining and manufacturing production was the opposite of tourism industry. This implies that the mining and manufacturing production was based on a weak foundation.