• Journal of Korea Water Resources Association
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• v.46 no.4
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• pp.425-437
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• 2013

This study performed the bivariate drought frequency analysis for duration and severity of drought, using copula functions which allow considering the correlation structure of joint features of drought. We suggested the confidence intervals of duration-severity-frequency (DSF) curves for the given drought duration using stochastic scheme of monthly rainfall generation for 57 sites in Korea. This study also investigated drought risk via illustrating the largest drought events on record over 50 and 100 consecutive years. It appears that drought risks are much higher in some parts of the Nakdong River basin, southern and east coastal areas. However, such analyses are not always reliable, especially when the frequency analysis is performed based on the data observed over relatively short period of time. To quantify the uncertainty of drought frequency curves, the droughts were filtered by different durations. The 5%, 25%, 50%, 75%, and 95% confidence intervals of the drought severity for a given duration were estimated based on the simulated rainfall time series. Finally, it is shown that the growing uncertainties is revealed in the estimation of the joint probability using the two marginal distributions since the correlation coefficient of two variables is relatively low.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.11
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• pp.1307-1314
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• 2012

To reduce the effects of clutters with subsurface inhomogenities in ground-penetrating radar(GPR) images, an eigenimage based signal-processing technique is presented. If the conventional eigenimage filtering technique is applied to B-scan images of a GPR survey, relatively homogeneous clutters such as antenna ringing, direct coupling between transmitting and receiving antennas, and soil-surface reflection, can be removed sufficiently. However, since random clutters of subsurface inhomogenities still remain in the images, target signals are distorted and obscured by the clutters. According to a comparison of the eigenimage filtering results, there is different coherency between subsurface clutters and target signals. To reinforce the pixels with high coherency and reduce the pixels with low coherency, the pixel-by-pixel geometric-mean process after the eigenimage filtering is proposed here. For the validity of the proposed approach, GPR survey for detection of a metal target in a randomly inhomogeneous soil is numerically simulated by using a random media generation technique and the finite-difference time-domain(FDTD) method. And the proposed signal processing is applied to the B-scan data of the GPR survey. We show that the proposed approach provides sufficient enhancement of target signals as well as remarkable reduction of subsurface inhomogeneous clutters in comparison with the conventional eigenimage filtering.

• Journal of IKEEE
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• v.24 no.1
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• pp.302-310
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• 2020

In this paper, we have implemented the living waste analysis system based on IoT and AI(Artificial Intelligence), and proposed effective waste process and management method. The Jeju location have the strong point to devise a stratagem and estimate waste quantization, rather than others. Especially, we can recognized the amount variation of waste to the residence people compare to the sightseer number, and the good example a specific waste duty. Thus this paper have developed the IoT device for interconnecting the existed CCTV camera, and use the AI algorithm to analysis the waste image. By using these decision of image analysis, we can inform their deal commend and a decided information to the map of the waste cars. In order to evaluate the performance of IoT, we have experimented the electromagnetic compatibility under a national official authorization KN-32, KN61000-4-2~6, and obtained the stable experimental results. In the further experimental results, we can applicable for an data structure for precise definition command by using the simulated several waste image with artificial intelligence algorithm.

• The Journal of the Acoustical Society of Korea
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• v.38 no.6
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• pp.703-709
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• 2019

This paper proposes speech recognition systems employing Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM) structures combined with Hidden Markov Moldel (HMM) to effectively recognize the speech of VeloPharyngeal Insufficiency (VPI) patients, and compares the recognition performance of the systems to the Gaussian Mixture Model (GMM-HMM) and fully-connected Deep Neural Network (DNNHMM) based speech recognition systems. In this paper, the initial model is trained using normal speakers' speech and simulated VPI speech is used for generating a prior model for speaker adaptation. For VPI speaker adaptation, selected layers are trained in the CNN-HMM based model, and dropout regulatory technique is applied in the LSTM-HMM based model, showing 3.68 % improvement in recognition accuracy. The experimental results demonstrate that the proposed LSTM-HMM-based speech recognition system is effective for VPI speech with small-sized speech data, compared to conventional GMM-HMM and fully-connected DNN-HMM system.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.58-63
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• 2017

Emergencies and disasters can happen any time without any warning, and things can change and escalate very quickly, and often it is swift and decisive actions that make all the difference. It is a responsibility of the building facility management to ensure that a proven evacuation plan in place to cover various worst scenario to handled automatically inside the facility. To mapping out optimal safe escape routes is a straightforward undertaking, but does not necessarily guarantee residents the highest level of protection. The emergency evacuation navigation approach is a state-of-the-art that designed to evacuate human livings during an emergencies based on real-time decisions using live sensory data with pre-defined optimum path finding algorithm. The poor decision on causalities and guidance may apparently end the evacuation process and cannot then be remedied. This paper propose a cloud connected emergency evacuation system model to react dynamically to changes in the environment in emergency for safest emergency evacuation using IoT based emergency exit sign system. In the previous researches shows that the performance of optimal routing algorithms for evacuation purposes are more sensitive to the initial distribution of evacuees, the occupancy levels, and the type and level of emergency situations. The heuristic-based evacuees routing algorithms have a problem with the choice of certain parameters which causes evacuation process in real-time. Therefore, this paper proposes an evacuee routing algorithm that optimizes evacuation by making using high computational power of cloud servers. The proposed algorithm is evaluated via a cloud-based simulator with different "simulated casualties" are then re-routed using a Dijkstra's algorithm to obtain new safe emergency evacuation paths against guiding evacuees with a predetermined routing algorithm for them to emergency exits. The performance of proposed approach can be iterated as long as corrective action is still possible and give safe evacuation paths and dynamically configure the emergency exit signs to react for real-time instantaneous safe evacuation guidance.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.4
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• pp.313-325
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• 2011

Finite element grid system using h-refinement on the Yellow Sea was constructed based on previous study (Suh, 1999b) from 14 K to 210 K and special attention was concentrated on refining the coastal zone. In grid generation, depth change between adjacent points and non-dimensional tidal wave length ratio were considered. As a result approximately a quarter of the total nodes are located nearby 5 m of shallow area. Accurate bathymetry data using 30's and ETOPO1 with open boundary conditions of 8 major tidal constituents extracted automatically from FES2004 have been applied. In tidal simulation a 3-dimensional nonlinear harmonic model was setup and tidal amplification due to changes in vertical turbulent and bottom friction were simulated. In this study not only 8 major tidal constituents but also nonlinear shallow tides $M_4,$, $MS_4$ and long period $M_f,$, $M_{sf}$ were reproduced. It is found that implication of spatial variation of friction coefficient plays a very important role in reproduction of astronomical and shallow tides which are computed by iterative computation of nonlinear terms. Also it should be considered differently with respect to tidal periods. To understand the distribution of tidal asymmetry, amplitude ratio of $M_4/M_2$ and phase differences $2g(M_2)-g(M_4)$ were calculated. Tidal distortion ratio marks up to 0.2 on the west coast showing shallow coastal characteristics and somewhat wide range of ebb-dominances in front of Mokpo area are reproduced.

• The Journal of the Acoustical Society of Korea
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• v.34 no.1
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• pp.12-19
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• 2015

In this paper, temporal variations of acoustic transmission loss (TL) affected by internal tide are studied by computer simulation using oceanic data measured in the southern sea of Jeju Island in summer. Temperature was measured with depth (bottom depth are nearly 80 m) in two sites near Seogwipo coast every one hour for 25 hours during July 27 and 28, 2009. The periodic fluctuation of temperature due to the internal tide was observed and its vertical displacement was more than 10 m. In order to investigate temporal variation of TL by internal tide, acoustic propagation between two measurement sites (3.8 km distance) was simulated with a source depth of 10 m. TL variation for 1/3 octave band of 100 Hz center frequency highly coincided with tidal period but more complex variation with indistinct tidal period was observed for 1 kHz. Maximun standard deviation of TL variation was 4.2 dB for 100 Hz at 2.8 km distance from a source and it was 3.7 dB for 1 kHz. The tidal variation was also shown in detection range and its maximum variance was less than 1 km. These results imply that temporal variation of TL should be considered for acoustic researches at the southern sea of Jeju Island.

• Journal of the Korean Chemical Society
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• v.17 no.4
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• pp.306-313
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• 1973

With the intention of obtaining technical data for the industrial production of ${\gamma}-MnO_2$ for dry cell depolarizer by electrolytic oxidation of acidic manganese sulfate solution made from domestic rhodochrosite, optimum conditions of ore leaching, purification of leached solution and electrolytic oxidation of divalent manganes to tetravalent were investigated using simulated micro pilot plant having a production capacity of 4 kg of $MnSO_4$ per day. The nature and quality of the products were investigated by means of chemical analysis, DTA, X-ray diffraction and electron microscopy. The cell activity of $MnO_2$were examined by cell discharging character measurements. The optimum electrolysis conditions were as follow: Temperature of the electrolyte, above $90^{\circ}C$; current density, 0.7${\sim}A/dm^2$; anode materials, graphite or lead ; concentration of electrolyte, $MnSO_4 50{\sim}150g/l $ g/l and $H_2SO_4/MnSO_4 = 0.15{\sim}0.25$. Under the best condition the current efficiency was 99% and the products were almost pure ${\gamma}-MnO_2$. The cell discharging character were good and almost the same as that of regular grade commercial electrolytic manganese dioxide.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.5
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• pp.511-525
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• 2014

Goal of this study is estimating of validity of calculated vertical diffusion coefficient for Masan bay is semi-enclosed bay by using eco-hydrodynamic model that is used to analysis of physical structure of coastal waters and calculates the vertical diffusion coefficient. physical structure of coastal waters is calculated by EFDC model, vertical diffusion coefficient calculated as the density gradient is bigger, the vertical diffusion coefficient as density gradient is increases, the vertical diffusion coefficient is decreased. Validity of vertical diffusion coefficient estimated by reproducibility of concentration of dissolved oxygen that calculated in ecosystem model is constructed by Stella program. The Results of model in 2008~2009 were $R^2$ value of 2008 is 0.529~0.700 and $R^2$ value is 0.542~0.791. This results were similar to observed data and simulated to hypoxia at that time. The 'vertical diffusion coefficient' represents stratification and physical stable of a water body, and will be useful for prediction of Hypoxia outbreak.

• Journal of the Korean Vacuum Society
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• v.21 no.4
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• pp.219-224
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• 2012

We study for long-term performance of amorphous silicon solar cells under light exposure. The performance is predicted with a kinetic model in which the carrier lifetimes are determined by the defect density. In particular, the kinetic model is described by the stretched-exponential relaxation of defects to reach equilibrium. In this report, we simulate the light-induced degradation of the amorphous silicon solar cells with the kinetic model and AMPS-1D computer program. And data measured for outdoor performances of various solar cells are compared with the simulated results. This study focuses on examining the light-induced degradation for the following amorphous silicon pin solar cells: thickness${\approx}$300 nm, built-in potential${\approx}$1.05 V, defect density (at t=0)${\approx}5{\times}10^{15}cm^{-3}$, short-circuit current density (at t=0)${\approx}15.8mA/cm^2$, fill factor (at t=0)${\approx}0.691$, open-circuit voltage (at t=0)${\approx}0.865V$, conversion efficiency (at t=0)${\approx}9.50%$.