• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.4
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• pp.467-478
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• 2016

In this paper, we try to find the optimal locations of NeNB(Nomadic evolved NodeB)s for maximizing the overall throughput of the PS-LTE networks. Since finding optimal locations of all NeNBs in a given area is NP-hard(Non-deterministic Polynomial time-hard) problem, we proposed a PSO-based heuristic approach. In order to evaluate the performance, we conducted two experiments. We compared performance with other schemes such as Exhaustive Search, Random Walk Search, and locating neighboring NeNBs with the same NeNB-to-NeNB distance. The proposed method showed the similar results to the exhaustive search method in terms of locating optimal position and user's data throughput. The proposed method, however, has the fast and consistent convergence time.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.11-18
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• 2012

Debris flow deposition model is a model to predict affected areas by debris flow and random walk model (RWM) was used to build the model. Although the model was proved to be effective in the prediction of affected areas, the model has several free parameters decided experimentally. There are several well-known methods to estimate parameters, however, they cannot be applied directly to the debris flow problem due to the small size of training data. In this paper, a modified neural network, called pseudo sample neural network (PSNN), was proposed to overcome the sample size problem. In the training phase, PSNN uses pseudo samples, which are generated using the existing samples. The pseudo samples smooth the solution space and reduce the probability of falling into a local optimum. As a result, PSNN can estimate parameter more robustly than traditional neural networks do. All of these can be proved through the experiments using artificial and real data sets.

• Journal of Korea Port Economic Association
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• v.29 no.1
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• pp.67-76
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• 2013

It has been more than four years since the outbreak of global financial crisis. However, the world economy continues to be challenged with new crisis such as the European debt crisis and the fiscal cliff issue of the U.S. The global economic environment remains fragile and prone to further disappointment, although the balance of risks is now less skewed to the downside than it has been in recent years. It's no wonder that maritime business will be bearish since the global business affects the maritime business directly as well as indirectly. This paper, hence, aims to predict the Baltic Dry Index representing the shipping business using the ARIMA-type models and Hodrick-Prescott filtering technique. The monthly data cover the period January 2000 through January 2013. The out-of-sample forecasting performance is measured by three summary statistics: root mean squared percent error, mean absolute percent error and mean percent error. These forecasting performances are also compared with those of the random walk model. This study shows that the ARIMA models including Intervention-ARIMA have lower rmse than random walk model. This means that it's appropriate to forecast BDI using the ARIMA models. This paper predicts that the shipping market will be more bearish in 2013 than the year 2012. These pessimistic ex-ante forecasts are supported by the Hodrick-Prescott filtering technique.

• 한국해양학회지
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• v.29 no.4
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• pp.392-401
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• 1994

We examined the temporal characteristics of the oceanic eddy diffusion at 5 coastal regions of Korea by measuring the separation distances of multiple drifters released simultaneously at the same by the GPS and Decca transponder system. The observed variance of separation distance, for the time scales from minutes to hours, is proportional to t/SUP m/ with scaling exponent m between 1.2 and 2.0. The observed Lagrangian trajectories of drifters show fractal characteristics instead of random walk or Brown motion. As an effort toward a development of a realistic model of the oceanic eddy diffusion, we simulated the Lagrangian trajectories of drifters by fractional Brown motion (FBM) model. The observed variances of drifter separations can be generated by the FBM process provided the Hurst exponent is the same as the observed one. We further showed that the observed power law in the variance of drifter separations cannot be simulated with an ordinary Brown motion or random walk process.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.19-26
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• 2003

The dispersion of recycled particulates in the complex coastal terrain containing Kangnung city, Korea was investigated using a three-dimensional non-hydrostatic numerical model and lagrangian particle model (or random walk model). The results show that particulates at the surface of the city that float to the top of thermal internal boundary layer (TIBL) are then transported along the eastern slope of the mountains with the passage of sea breeze and nearly reach the top of the mountains. Those particulates then disperse eastward at this upper level over the coastal sea and finally spread out over the open sea. Total suspended particulate (TSP) concentration near the surface of Kangnung city is very low. At night, synoptic scale westerly winds intensify due to the combined effect of the synoptic scale wind and land breeze descending the eastern slope of the mountains toward the coast and further seaward. This increase in speed causes development of internal gravity waves and a hydraulic jump up to a height of about 1km above the surface over the city. Particulate matter near the top of the mountains also descends the eastern slope of the mountains during the day, reaching the central city area and merges near the surface inside the nocturnal surface inversion layer (NSIL) with a maximum ground level concentration of TSP occurring at 0300 LST. Some particulates were dispersed following the propagation area of internal gravity waves and others in the NSIL are transported eastward to the coastal sea surface, aided by the land breeze. The following morning, particulates dispersed over the coastal sea from the previous night, tend to return to the coastal city of Kangnung with the sea breeze, developing a recycling process and combine with emitted surface particulates during the morning. These processes result in much higher TSP concentration. In the late morning, those particulates float to the top of the TIBL by the intrusion of the sea breeze and the ground level TSP concentration in the city subsequently decreases.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.2 no.3
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• pp.43-56
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• 1982

A recursive algorithms for prediction of streamflows by Kalman filtering theory and Self-tuning predictor based on the state space description of the dynamic systems have been studied and the applicabilities of the algorithms to the rainfall-runoff processes have been investigated. For the representation of the dynamics of the processes, a low-order ARMA process has been taken as the linear discrete time system with white Gaussian disturbances. The state vector in the prediction model formulated by a random walk process. The model structures have been determined by a statistical analysis for residuals of the observed and predicted streamflows. For the verification of the prediction algorithms developed here, the observed historical data of the hourly rainfall and streamflows were used. The numerical studies shows that Kalman filtering theory has better performance than the Self-tuning predictor for system identification and prediction in rainfall-runoff processes.

• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1302-1309
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• 2008

Traditional clustering methods, like k-means or fuzzy clustering, are prototype-based methods which are applicable only to convex clusters. On the other hand, spectral clustering tries to find clusters only using local similarity information. Its ability to handle concave clusters has gained the popularity recent years together with support vector machine (SVM) which is a kernel-based classification method. However, as is in SVM, the kernel width plays an important role and has a great impact on the result. Several methods are proposed to decide it automatically, it is still determined based on heuristics. In this paper, we proposed an adaptive method deciding the kernel width based on distance histogram. The proposed method is motivated by the fact that the affinity matrix should be formed into a block diagonal matrix to generate the best result. We use the tradition Euclidean distance together with the random walk distance, which make it possible to form a more apparent block diagonal affinity matrix. Experimental results show that the proposed method generates more clear block structured affinity matrix than the existing one does.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.6
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• pp.442-450
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• 2011

A three dimensional random walk particle tracking method is applied to the Saemangeum area in order to find stepwise environmental changes according to long term construction. Flow regime around Mangyeong, Dongjin and Geum river estuary changed greatly due to dike construction. It is distinctive that reduction of Byeonsan area's flow field and stagnant change in the northern part of the inner reservoir. Similar characteristics are found through the tidal excursion analysis. By analysis of the vertical mixing structures according to density stratification based on temperature and salinity variation, a salt wedge and very strong stratification arises in the inner part of the reservoir after final closure, while it has been well mixed or partially mixed estuary during construction. Shrinking of horizontal dispersion and vertical mixing capability may cause adverse effect on water quality not only inner part but also outer region of the Saemangeum reservoir.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.575-581
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• 2012

In general, various modeling and estimation techniques have been proposed to extract the tropospheric and ionospheric delays from the GPS CORS. In this study, Kalman filter approach is adopted to estimate the tropospheric and ionospheric delays and the proper modeling for the state vector and the variance-covariance matrix for the process noises are performed. The coordinates of reference stations and the zenith wet delays are estimated with the assumption of random walk stochastic process. Also, the first-order Gauss-Markov stochastic process is applied to compute the ionospheric effects. For the evaluation of the proposed modeling technique, Kalman filter algorithm is implemented and the numerical test is performed with the CORS data. The results show that the atmospheric effects can be estimated successfully and, as a consequence, can be used for the generation of VRS data.

• Geophysics and Geophysical Exploration
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• v.16 no.2
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• pp.97-105
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• 2013

Nuclear magnetic resonance (NMR) logging has become an important technique for formation evaluation, detecting interaction signals between H protons and applied magnetic fields. Measured decay signals called relaxation, contain important information about density of H protons and different decay rate due to its fluid type in the sensitive area. Thus, petrophysical information such as porosity, permeability and wettability can be estimated through the interpretation of the decay signals. Many researches on random walk simulation have been published, since a simulation method based on random walk for solving exponential decays was adapted in the early of 1950. This study first makes a review on NMR simulation researches, explains two most important methods: simulation with or without considering magnetic field gradient. Lastly, the study makes a comparison between NMR simulation responses with and without magnetic field gradient to show the importance to consider magnetic gradient to analyze the effects of magnetic gradients on NMR responses.