• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.100-103
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• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.157-163
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• 2022

As the online game market grows, the use of game bots is causing the most serious problem for game services. We propose a harvest coordinate analysis model to detect harvesting bots among game bots of the Massively Multiplayer Online Role-Playing Games(MMORPGs) genre. The proposed model analyzes the player's harvesting behavior using the coordinate data. Game bots can obtain in-game goods and items more easily than normal players and are not affected by realistic restrictions such as sleep time and character manipulation fatigue. As a result, there is a difference in harvesting coordinates between normal players and game bots. We divided the coordinate zones and used these coordinate zone differences to distinguish between game bot players and normal players. We created a dataset with NCSoft's AION log and applied it to a random forest model to detect game bots, and as a result, we derived performance with a recall of 0.72 and a precision of 0.92.

• ETRI Journal
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• v.35 no.5
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• pp.859-868
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• 2013

The active noise control (ANC) technique attenuates acoustic noise in a flexible and effective way. Traditional ANC design aims to minimize the residual noise energy, which is indiscriminative in the frequency domain. However, human hearing perception exhibits selective sensitivity for different frequency ranges. In this paper, we aim to improve the noise attenuation performance in perceptual perspective by incorporating noise weighting into ANC design. We also introduce psychoacoustic analysis to evaluate the sound quality of the residual noise by using a predictive pleasantness model, which combines four psychoacoustic parameters: loudness, sharpness, roughness, and tonality. Simulations on synthetic random noise and realistic noise show that our method improves the sound quality and that ITU-R 468 noise weighting even performs better than A-weighting.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.6
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• pp.11-22
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• 1996

We address an issue of channel sharing among users by using a random assignment-transmitter-based (RA-T) spread-spectrum transmission scheme which permits the contention mode only in the transmission of a header while avoiding collision during the data packet transmission. Once the header being successfully received, the data packet is ready for reception by switching to one of programmable matched-filters. But the receoption may be blocked due to limited number of matched-filters so that this effect is taken into account in our analysis. For realistic analysis, we integrate detection performance at the physical level with channel activity at the link level through a markov chain model. We also consider an acknowledgement scheme to notify whether the header is correctly detcted and the data packet can be processed continuously, which aims at reducing the interference caused unwanted data transmission. It is shown that receiver complexity can be greatly reduced by choosing a proper number of RA codes at the cost of only a little throughput degradation.

• Journal of the Korean Magnetics Society
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• v.5 no.5
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• pp.645-649
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• 1995

The depletion of thin liquid films due to the combined effect of centrifugation, surface roughness, and air-shear has recently been studied. While surface roughness of a rotating solid disk can be represented by deterministic cures, it has been argued that spatial random processes provide a more realistic description. Chiefly because of surface roughness, there is an asymptotic limit of retention of a thin film flowing on the rotating disk. The aim of this article is to model the depletion of thin-film flow and analyze the interplay of centrifugation, surface tension, viscosity, air-shear, disjoining pressure, and surface roughness that affect the depletion of the film. Also, the robustness of stochastic description of surface roughness is examined.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.563-568
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• 2013

The purpose of this study is to find the analytic solution for determining the optimal capacity (lot-size) of a batch-storage network to meet the finished product demand under infrequent shutdowns. Batch processes are bound to experience random but infrequent operating time losses. Two common remedies for these failures are duplicating another process or increasing the process and storage capacity, both of which are very costly in modern manufacturing systems. An optimization model minimizing the total cost composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units is pursued with the framework of a batch-storage network of which flows are susceptible to infrequent shutdowns. The superstructure of the plant consists of a network of serially and/or parallel interlinked batch processes and storage units. The processes transform a set of feedstock materials into another set of products with constant conversion factors.A novel production and inventory analysis method, the PSW (Periodic Square Wave) model, is applied. The advantage of the PSW model stems from the fact it provides a set of simple analytic solutions in spite of a realistic description of the material flow between processes and storage units. The resulting simple analytic solution can greatly enhance a proper and quick investment decision at the early plant design stagewhen confronted with diverse economic situations.

• 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.

• The Korean Journal of Physiology and Pharmacology
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• v.20 no.1
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• pp.111-117
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• 2016

Vagal nerve activity has been known to play a crucial role in the induction and maintenance of atrial fibrillation (AF). However, it is unclear how the distribution and concentration of local acetylcholine (ACh) promotes AF. In this study, we investigated the effect of the spatial distribution and concentration of ACh on fibrillation patterns in an in silico human atrial model. A human atrial action potential model with an ACh-dependent $K^+$ current ($I_{KAch}$) was used to examine the effect of vagal activation. A simulation of cardiac wave dynamics was performed in a realistic 3D model of the atrium. A model of the ganglionated plexus (GP) and nerve was developed based on the "octopus hypothesis". The pattern of cardiac wave dynamics was examined by applying vagal activation to the GP areas or randomly. AF inducibility in the octopus hypothesis-based GP and nerve model was tested. The effect of the ACh concentration level was also examined. In the single cell simulation, an increase in the ACh concentration shortened $APD_{90}$ and increased the maximal slope of the restitution curve. In the 3D simulation, a random distribution of vagal activation promoted wavebreaks while ACh secretion limited to the GP areas did not induce a noticeable change in wave dynamics. The octopus hypothesis-based model of the GP and nerve exhibited AF inducibility at higher ACh concentrations. In conclusion, a 3D in silico model of the GP and parasympathetic nerve based on the octopus model exhibited higher AF inducibility with higher ACh concentrations.

• Journal of Soil and Groundwater Environment
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• v.19 no.4
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• pp.31-44
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• 2014

In the present study, a few of recently developed geostatistical models are comparatively studied. The models are two-point statistics based sequential indicator simulation (SISIM) and generalized coupled Markov chain (GCMC), multi-point statistics single normal equation simulation (SNESIM), and object based model of FLUVSIM (fluvial simulation) that predicts structures of target object from the provided geometric information. Out of the models, SNESIM and FLUVSIM require additional information other than conditioning data such as training map and geometry, respectively, which generally claim demanding additional resources. For the comparative studies, three-dimensional fluvial reservoir model is developed considering the genetic information and the samples, as input data for the models, are acquired by mimicking realistic sampling (i.e. random sampling). For SNESIM and FLUVSIM, additional training map and the geometry data are synthesized based on the same information used for the objective model. For the comparisons of the predictabilities of the models, two different measures are employed. In the first measure, the ensemble probability maps of the models are developed from multiple realizations, which are compared in depth to the objective model. In the second measure, the developed realizations are converted to hydrogeologic properties and the groundwater flow simulation results are compared to that of the objective model. From the comparisons, it is found that the predictability of GCMC outperforms the other models in terms of the first measure. On the other hand, in terms of the second measure, the both predictabilities of GCMC and SNESIM are outstanding out of the considered models. The excellences of GCMC model in the comparisons may attribute to the incorporations of directional non-stationarity and the non-linear prediction structure. From the results, it is concluded that the various geostatistical models need to be comprehensively considered and comparatively analyzed for appropriate characterizations.

• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.53-61
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• 2016

In this paper, we propose an algorithm for generating lightning paths, which are more realistic than those of random tree based algorithm and faster than a physically based simulation algorithm. Our approach utilizes physically based Dielectric Breakdown Method (DBM) and approximates the electric potential field dramatically to generate the lightning path. We also show a guide path method for the lightning to avoid obstacles in a complex scene. Finally, our method renders fast and realistic lightning by considering physical characteristics for the thickness and brightness of the lightning stream. Our result of the lightning path shares similarity to natural phenomenon by having about 1.56 fractal dimensions, and we can generate the lightning path faster than a previous physically based algorithm. On the other hand, our method is difficult to apply on the real-time games yet, but our approach can be improved by performing the path generation algorithm with GPU in future.