• Ecology and Resilient Infrastructure
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• v.2 no.3
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• pp.198-205
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• 2015

Impacts of climate change on aquatic ecosystems range from changes in physiological processes of aquatic organisms to species distribution. In this study, MaxEnt that has high prediction power without nonoccurrence data was used to simulate fish distribution changes in the Geum river watershed according to climate change. The fish distribution in 2050 and 2100 was predicted with RCP 8.5 climate change scenario using fish occurrence data (a total of 47 species, including 17 endemic species) from 2007 to 2009 at 134 survey points and 9 environmental variables (monthly lowest, highest and average air temperature, monthly precipitation, monthly lowest, highest and average water temperature, altitude and slope). The fitness of MaxEnt modeling was successful with the area under the relative operating characteristic curve (AUC) of 0.798, and environmental variables that showed a high level of prediction were as follows: altitude, monthly average precipitation and monthly lowest water temperature. As climate change proceeds until 2100, the probability of occurrence for Odontobutis interrupta and Acheilognathus yamatsuatea (endemic species) decreases whereas the probability of occurrence for Microphysogobio yaluensis and Lepomis macrochirus (exotic species) increases. In particular, five fish species (Gnathopogon strigatus, Misgurnus mizolepis, Erythroculter erythropterus, A. yamatsuatea and A. koreensis) were expected to become extinct in the Geum river watershed in 2100. In addition, the species rich area was expected to move to the northern part of the Geum river watershed. These findings suggest that water temperature increase caused by climate change may disturb the aquatic ecosystem of Geum river watershed significantly.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.1
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• pp.128-136
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• 2008

Recently, the unusual climate change is happening from the global warming in the whole world, the Korean peninsula is also no exception. It is predicted by many researchers that, in the near future, the Super-Typhoon of overwhelming power will occur due to rising temperatures on the sea surface around the Korean peninsula. In this study, numerical simulation has been performed with the Super-Typhoons which combined route of Typhoon Maemi with typhoon conditons of Hurricane Katrina (New Oleans in U.S.A, 2005), Typhoon Durian (philippine, 2006) and Typhoon Vera (Ise Bay in Japan, 1959) at Busan and Gyeongnam coastal area which has been badly damaged due to storm surge every year. From the numerical results, it is revealed that the storm surge heights of the Super-Typhoons are higher than that of Maemi, specially the storm surge height in the case of Katrina is about 4 times larger. So, it can be pointed out that the construction of countermeasures against disasters are very important in order to prepare against an attack of the Super-Typhoons.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.257-265
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• 2016

In this study, an optimal design for motor-driven track type traveling system applied into high clearance working machineries in orchard is proposed. Tractive performance and hill climbing ability were predicted and evaluated for the optimal motor traveling system by taking into account of soil characteristics in orchard utilizing the high clearance working machineries. Design criteria for tractive performance were based on the traction force calculated from tractive effort subtracted by motion resistance, while hill climbing ability had its design criteria that fulfill the climbing 20% slope ground at a speed of 3km/h. Based on the evaluation results of traction and climbing ability, two DC48V, 4500rpm, 1.6kW AC motors were independently applied to both left and right side of orbits; each motor is designed to transmit power on driving sprocket of track type traveling system via 50:1 reduction gear ratio. The motor-driven track type traveling system developed in the study found to have 396 kgf of tractive force, which is 12.5% higher than climbing resistance at orchard soil having 20% slope ground (352 kgf), demonstrating sufficient tractive performance and hill climbing ability.

• Journal of Navigation and Port Research
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• v.35 no.6
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• pp.477-482
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• 2011

Solar flares have the 11-year cycle and release a large energy which may produce coronal mass ejections (CME). The NOAA (National Oceanic and Atmospheric Administration) predicted that the sun spot activity will be maximized in 2013-2014. A strong solar flare can cause the disturbance of global positioning system including various communication of TV, radio broadcasting. The actual solar storm in 1989 caused power outages in Canada during 9 hours and about 600 million people had experienced a blackout. Such a solar storm can shorten the GPS satellite's life span about 5 to 10 years which can resulted in economic loss considering the amount of multi-billion won. This paper analyzed the influence of recent X-class solar storm occurred on 15th of February about 10:45 this year that was reached Korea (Bohyun observatory) on 18th of February about 10:30 (01:30 - UTC), and compared with the data before and after a week. The proton data of 18th of February considered that the solar storm reached on earth showed a fluctuation compared to the data before and after a week. The positioning results at Daejeon and Seoul of Korea also showed higher positioning error compared to the data before and after a week results.

• Journal of Korean Home Economics Education Association
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• v.29 no.3
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• pp.89-104
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• 2017

Considering the advent of the Fourth Industrial Revolution, this study examines the changes and influences of intelligent information technology and the role of consumer education in the context of consumption life. The purpose of this study is to provide a theoretical foundation to effectively respond to the future consumption society as an independent consumer by enhancing the understanding of the Fourth Industrial Revolution in terms of consumption life. First, in terms of changes in the consumption paradigm in the Fourth Industrial Revolution, production and consumption are converged by being shared through a comprehensive connection platform in real time. Regarding the meaning of consumption, mental experience is being emphasized; moreover, usage and sharing, rather than ownership, are being highlighted. In terms of major changes in consumption life, the emergence of a more convenient smart consumption life and the possibility of personalized consumption optimized for individual demand are anticipated. Moreover, sustainable eco-friendly consumption is expected to increase further, and rapidly changing consumption trends will experience accelerated progress in consumer-centered changes. Next, the predicted problems in consumption life in the Fourth Industrial Revolution include unequal consumption due to intelligent information technology power center and the use and management of personal information data. Furthermore, ethical concerns related to the introduction of new technologies will become prominent, eventually resulting in issues concerning consumption satisfaction. To effectively respond to these new paradigm changes, consumer education should be value-centered. Ethical aspects of consumption should be considered, and consumption life should include trust and mutual cooperation. Furthermore, consumer education should facilitate creative convergence.

• Journal of The Korean Ophthalmological Society
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• v.59 no.12
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• pp.1173-1180
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• 2018

Purpose: We evaluated the postoperative accuracy of intraocular lens power prediction for patients undergoing phacotrabeculectomy and identified preoperative factors associated with refractive outcome in those with primary open-angle glaucoma (POAG). Methods: We retrospectively reviewed the medical records of 27 patients who underwent phacotrabeculectomy to treat POAG. We recorded all discrepancies between predicted and actual postoperative refractions. We compared the data to those of an age- and sex-matched control group that underwent uncomplicated cataract surgery during the same time period. Preoperative factors associated with the mean absolute error (MAE) were identified via multivariate regression analyses. Results: The mean refractive error of the 27 eyes that underwent phacotrabeculectomy was comparable to that of the 27 eyes treated via phacoemulsification (+0.02 vs. -0.01 D, p = 0.802). The phacotrabeculectomy group exhibited a significantly higher MAE (0.65 vs. 0.35 D, p = 0.035) and more postoperative astigmatism (-1.07 vs. -0.66 D, p = 0.020) than the phacoemulsification group. The preoperative anterior chamber depth (ACD) and the changes in the postoperative intraocular pressure (IOP) were significantly associated with a greater MAE after phacotrabeculectomy. Conclusions: POAG treatment via combined phacoemulsification/trabeculectomy was associated with greater error in terms of final refraction prediction, and more postoperative astigmatism. As both a shallow preoperative ACD and a greater postoperative change in IOP appear to increase the predictive error, these two factors should be considered when planning phacotrabeculectomy.

• Food Science and Preservation
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• v.19 no.4
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• pp.577-585
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• 2012

This study was conducted to establish the extraction conditions for the optimization of the biological activities of black garlic using the response surface methodology (RSM). The extraction conditions were based on the central composite design, with 15 kinds of variations in the extraction temperature (50-$90^{\circ}C$ ), extraction time (3-15 hrs), and ethanol concentration (0-100%). The total phenol, flavonoids, thiosulfinate contents, and anti-oxidant activity of black garlic extract were significantly higher at the J condition ($90^{\circ}C$ for 9 hrs with a 50% ethanol concentration). In this condition, the biological activities such as DPPH radical scavenging (66.10%), ABTS radical scavenging activity (75.02%), and reducing power by of FRAP (375.4 ${\mu}M/mL$) were excellent. Overall, the extraction conditions for the optimized biological activities of black garlic via RSM were expected to be at $89.68^{\circ}C$ for 9.79 hrs with a 55.72% ethanol concentration. The actual values were 96.4-114.8% of the predicted values.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.944-958
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• 2011

Soil hydraulic properties such as hydraulic conductivity or water retention which are costly to measure can be indirectly generated by soil pedotransfer function (PTF) using easily obtainable soil data. The field soil structure description which is routinely recorded could also be used in PTF as an input to reduce the uncertainty. The purposes of this study were to use qualitative morphological soil structure descriptions and soil structural index into PTF and to evaluate their contribution in the prediction of soil hydraulic properties. We transformed categorical morphological descriptions of soil structure into quantitative values using categorical principal component analysis (CATPCA). This approach was tested with a large data set from the US National Pedon Characterization database with the aid of a categorical regression tree analysis. Six different PTFs were used to predict the saturated hydraulic conductivity and those results were averaged to quantify the uncertainty. Quantified morphological description was successively used in multiple linear regression approach to predict the averaged ensemble saturated conductivity. The selected stepwise regression model with only the transformed morphological variables and structural index as predictors predicted the $K_{sat}$ with $r^2$ = 0.48 (p = 0.018), indicating the feasibility of CATPCA approach. In a regression tree analysis, soil structure index and soil texture turned out to be important factors in the prediction of the hydraulic properties. Among structural descriptions size class turned out to be an important grouping parameter in the regression tree. Bulk density, clay content, W33 and structural index explained clusters selected by a two step clustering technique, implying the morphologically described soil structural features are closely related to soil physical as well as hydraulic properties. Although this study provided relatively new method which related soil structure description to soil structure index, the same approach should be tested using a datasets containing the actual measurement of hydraulic properties. More insight on the predictive power of soil structure index to estimate hydraulic properties would be achieved by considering measured the saturated hydraulic conductivity and the soil water retention.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.301-309
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• 2021

In this study, we tried to improve the performance of the existing U-net-based deep learning rainfall prediction model, which can weaken the meaning of time series order. For this, ConvLSTM2D U-Net structure model considering temporal consistency of data was applied, and we evaluated accuracy of the ConvLSTM2D U-Net model using a RainNet model and an extrapolation-based advection model. In addition, we tried to improve the uncertainty in the model training process by performing learning not only with a single model but also with 10 ensemble models. The trained neural network rainfall prediction model was optimized to generate 10-minute advance prediction data using four consecutive data of the past 30 minutes from the present. The results of deep learning rainfall prediction models are difficult to identify schematically distinct differences, but with ConvLSTM2D U-Net, the magnitude of the prediction error is the smallest and the location of rainfall is relatively accurate. In particular, the ensemble ConvLSTM2D U-Net showed high CSI, low MAE, and a narrow error range, and predicted rainfall more accurately and stable prediction performance than other models. However, the prediction performance for a specific point was very low compared to the prediction performance for the entire area, and the deep learning rainfall prediction model also had limitations. Through this study, it was confirmed that the ConvLSTM2D U-Net neural network structure to account for the change of time could increase the prediction accuracy, but there is still a limitation of the convolution deep neural network model due to spatial smoothing in the strong rainfall region or detailed rainfall prediction.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.791-804
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• 2020

Residential electricity consumption can be predicted more accurately by utilizing the realtime household electricity consumption reference that can be collected by the AMI as the ICT developed under the smart grid circumstance. This paper studied the model that predicts residential power load using the ARIMA, TBATS, NNAR model based on the data of hour unit amount of household electricity consumption, and unlike forecasting the consumption of the whole households at once, it computed the anticipated amount of the electricity consumption by aggregating the predictive value of each established model of cluster that was collected by the households which show the similiar load profile. Especially, as the typical time series data, the electricity consumption data chose the clustering analysis method that is appropriate to the time series data. Therefore, Dynamic Time Warping and Periodogram based method is used in this paper. By the result, forecasting the residential elecrtricity consumption by clustering the similiar household showed better performance than forecasting at once and in summertime, NNAR model performed best, and in wintertime, it was TBATS model. Lastly, clustering method showed most improvements in forecasting capability when the DTW method that was manifested the difference between the patterns of each cluster was used.