• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.109-116
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• 2021

In this paper, we propose a non-intrusive load monitoring(NILM) system which can find the power of each home appliance from the aggregated total power as the activation in the trading market of the distributed resource and the increasing importance of energy management. We transform the amount of appliances' power into a power on-off state by preprocessing. We use LSTM as a model for predicting states based on these data. Accuracy is measured by comparing predicted states with real ones after postprocessing. In this paper, the accuracy is measured with the different number of electronic products, data postprocessing method, and Time step size. When the number of electronic products is 6, the data postprocessing method using the Round function is used, and Time step size is set to 6, the maximum accuracy can be obtained.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.

• The Journal of Information Systems
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• v.30 no.4
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• pp.329-347
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• 2021

Purpose The purpose of this study is to examine the review of previous studies based on audiobooks, 1) using the IPA method, we examine the quality of audiobooks that listeners perceive as important and the quality of preferred audiobooks, 2) improvement directions for activating audio content and audiobook platform, to seek ways to establish strategic plans for the audiobook market. Design/methodology/approach This study conducted and experiment using three factors(usability, information and interaction) used in web service quality(WebQual). Usability consists of the availability of time, such as the use of audiobooks for hobbies and the ease of search. Information consists of the trends of the times, topics of converation and the latest trends. Interaction consists of the proportion and depth of celebrities. After that, grid analysis was performed using the traditional IPA method and the revised IPA method. It was judged that identifying and analyzing the preference for service provision and new content was more valuable than the Performance used in the existing method. Findings According to the results of the empirical analysis, it was found that the conversation material corresponding to informativity did not affect the audiobook during the online quality analysis. It is believed that improvements can be found through content production related to entertainment, webtoons, and general common sense that can increase listeners' interest. In addition, it was found that the advertising effect of celebrities corresponding to interactivity did not affect the results of this study, which should increase the concentration and immersion of listeners by increasing the technology for audiobooks.

• Journal of Aerospace System Engineering
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• v.16 no.6
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• pp.114-122
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• 2022

This paper explores three-dimensional unsteady computational fluid dynamic (CFD) analyses with an overset grid technique to analyse the wake effect created by a rotating propeller on a hand-launched unmanned aerial vehicle (UAV). Additionally, the influence of actual aileron deflection on the equilibrium condition of the rolling moment is examined in various hand-launched take-off conditions. The results of this study demonstrate the importance of initial aileron deflection in increasing the initial rolling stability during the hand-launched take-off process. Furthermore, an aerodynamic database is constructed to rapidly predict the aileron set values required for different take-off speeds and angle-of-attacks.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1-7
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• 2007

New Zealand is a hydrologically diverse and active country. This paper presents an overview of the major hydrological issues and problems facing New Zealand and provides examples of some the research being undertaken to solve the problems. Fundamental to any environmental decision making is the provision of good quality hydrometric data. Reduced funding for the national hydrometric network has meant a reduction in the number of monitoring sites, the decision on how to redesign the network was made using information on geographic coverage and importance of each site. New Zealand faces a major problem in understanding the impacts of rapid land use change on water quantity and quality. On top of the land use change is overlain the issue of agricultural intensification. The transfer of knowledge about impacts of change at the small watershed scale to much larger, more complex watersheds is one that is attracting considerable research attention. There is a large amount of research currently being undertaken to understand the processes of water and nutrient movement through the vadose zone into groundwater and therefore understanding the time taken for leached nutrients to reach receiving water bodies. The largest water management issue of the past 5 years has been based around fair and equitable water allocation when there is increasing demand for irrigation water. Apart from policy research into market trading for water there has been research into water storage and transfer options and improving irrigation efficiency. The final water management issue discussed concerns the impacts of hydrological extremes (floods and droughts). This is of particular concern with predictions of climate change for New Zealand suggesting increased hydrological extremes. Research work has concentrated on producing predictive models. These have been both detailed inundation models using high quality LIDAR data and also flood models for the whole country based on a newly interpolated grid network of rainfall.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.161-161
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• 2023

Bias correction of values is a necessary step in downscaling coarse and systematically biased global climate models for use in local climate change impact studies. In addition to univariate bias correction methods, many multivariate methods which correct multiple variables jointly - each with their own mathematical designs - have been developed recently. While some literature have focused on the inter-comparison of these multivariate bias correction methods, none have focused extensively on the effect of diverse configurations (i.e., different combinations of input variables to be corrected) of climate variables, particularly high-dimensional ones, on the ability of the different methods to remove biases in uni- and multivariate statistics. This study evaluates the impact of three configurations (inter-variable, inter-spatial, and full dimensional dependence configurations) on four state-of-the-art multivariate bias correction methods in a national-scale domain over South Korea using a gridded approach. An inter-comparison framework evaluating the performance of the different combinations of configurations and bias correction methods in adjusting various climate variable statistics was created. Precipitation, maximum, and minimum temperatures were corrected across 306 high-resolution (0.2°) grid cells and were evaluated. Results show improvements in most methods in correcting various statistics when implementing high-dimensional configurations. However, some instabilities were observed, likely tied to the mathematical designs of the methods, informing that some multivariate bias correction methods are incompatible with high-dimensional configurations highlighting the potential for further improvements in the field, as well as the importance of proper selection of the correction method specific to the needs of the user.

• Journal of Radiation Protection and Research
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• v.48 no.1
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• pp.28-43
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• 2023

Background: High-fidelity meteorological data is a prerequisite for the realistic simulation of atmospheric dispersion of radioactive materials near nuclear power plants (NPPs). However, many meteorological models frequently overestimate near-surface wind speeds, failing to represent local meteorological conditions near NPPs. This study presents a new high-resolution (approximately 1 km) meteorological downscaling method for modeling short-range (< 100 km) atmospheric dispersion of accidental NPP plumes. Materials and Methods: Six considerations from literature reviews have been suggested for a new dynamic downscaling method. The dynamic downscaling method is developed based on the Weather Research and Forecasting (WRF) model version 3.6.1, applying high-resolution land-use and topography data. In addition, a new subgrid-scale topographic drag parameterization has been implemented for a realistic representation of the atmospheric surface-layer momentum transfer. Finally, a year-long simulation for the Kori and Wolsong NPPs, located in southeastern coastal areas, has been made for 2016 and evaluated against operational surface meteorological measurements and the NPPs' on-site weather stations. Results and Discussion: The new dynamic downscaling method can represent multiscale atmospheric motions from the synoptic to the boundary-layer scales and produce three-dimensional local meteorological fields near the NPPs with a 1.2 km grid resolution. Comparing the year-long simulation against the measurements showed a salient improvement in simulating near-surface wind fields by reducing the root mean square error of approximately 1 m/s. Furthermore, the improved wind field simulation led to a better agreement in the Eulerian estimate of the local atmospheric dispersion. The new subgrid-scale topographic drag parameterization was essential for improved performance, suggesting the importance of the subgrid-scale momentum interactions in the atmospheric surface layer. Conclusion: A new dynamic downscaling method has been developed to produce high-resolution local meteorological fields around the Kori and Wolsong NPPs, which can be used in short-range atmospheric dispersion modeling near the NPPs.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.804-811
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• 2010

The lower portion of sloping paddy fields normally contains excessive moisture and the higher water table caused by the inflow of ground water from the upper part of the field resulting in non-uniform water content distribution. Four drainage methods namely Open Ditch, Vinyl Barrier, Pipe Drainage and Tube Bundle for multiple land use were installed within 1-m position from the lower edge of the upper embankment of sloping alluvial paddy fields. Knowledge of the spatial variability of soil water properties is of primary importance for management of agricultural lands. This study was conducted to evaluate the effect of drainage in the soil on spatial variability of soil water content using the geostatistical analysis. The soil water content was collected by a TDR (Time Domain Reflectometry) sensor after the installation of subsurface drainage on regular square grid of 80 m at 20 m paddy field located at Oesan-ri, Buk-myeon, Changwon-si in alluvial slopping paddy fields ($35^{\circ}22^{\prime}$ N, $128^{\circ}35^{\prime}$). In order to obtain the most accurate field information, the sampling grid was divided 3 m by 3 m unit mesh by four drainage types. The results showed that spatial variance of soil water content by subsurface drainage was reduced, though yield of soybean showed the same trends. Value of "sill" of soil water content with semivariogram was 9.7 in Pipe Drainage, 86.2 in Open Ditch, and 66.8 in Vinyl Barrier and 15.7 in Tube Bundle.

• Geophysics and Geophysical Exploration
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• v.11 no.4
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• pp.318-325
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• 2008

Assigning an exact boundary condition is of great importance in three-dimensional (3D) magnetotelluric (MT) modeling, in which no source is considered in a computing domain. This paper presents a 3D MT modeling algorithm utilizing a Dirichlet condition for a 2D host. To compute boundary values for a model with a 2D host, we need to conduct additional 2D MT modeling. The 2D modeling consists of transverse magnetic and electric modes, which are determined from the relationship between the polarization of plane wave and the strike direction of the 2D structure. Since the 3D MT modeling algorithm solves Maxwell's equations for electric fields using the finite difference method with a staggered grid that defines electric fields along cell edges, electric fields are calculated at the same place in the 2D modeling. The algorithm developed in this study can produce reliable MT responses for a 3D model with a 2D host.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.6
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• pp.634-643
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• 2020

Because of the continuous increase in the demand for and importance of marine space, marine exploration and survey activities are being actively conducted in Korea actively. Because the marine survey vessels used for these activities have special operational patterns depending on the purpose and probe vessels, research on maritime traffic risk is required. In this study, an attempt was made to determine the correlation of each factor with the effect of marine exploration and survey vessel operation on maritime traffic. The status of ocean exploration and survey vessels in operation in Korea was identified, as well as the special operational conditions of some of the ocean physical probes. Generally, the number of exploration and survey vessels involved per hour, total vessel length(including exploration equipment), operation, interval distance of exploration as per plan, and marine traffic conditions(traffic volume and speed) can be classified as operating factors. To compare the results of the environmental stress, a maritime traffic flow simulation based on the "ES" Model was performed with each of the identified operating factors as independent variables. The results of the analysis confirmed that the environmental stress significantly changed in the order of traffic volume, ship length and speed. In addition, it was confirmed that the environmental stress is reduced when the operation course is set at an angle with the nearby maritime traffic flow. Accordingly, it can help reduce the operator's burden if the survey vessel operator understands nearby maritime traffic conditions and reflects them in the operation method when setting the operation plan.