• Journal of Korean Neurosurgical Society
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• v.51 no.5
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• pp.276-280
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• 2012

Objective : Gamma knife radiosurgery (GKRS) is the least invasive surgical option for patients with trigeminal neuralgia (TN). However, the indications and long term outcomes of GKRS are still controversial. Additionally, a series with uniform long-term follow-up data for all patients has been lacking. In the present study, the authors analyzed long-term outcomes in a series of patients with TN who underwent a single GKRS treatment followed by a minimum follow-up of 60 months. Methods : From 1994 to 2009, 40 consecutive patients with typical, intractable TN received GKRS. Among these, 22 patients were followed for >60 months. The mean maximum radiation dose was 77.1 Gy (65.2-83.6 Gy), and the 4 mm collimator was used to target the radiation to the root entry zone. Results : The mean age was 61.5 years (25-84 years). The mean follow-up period was 92.2 months (60-144 months). According to the pain intensity scale in the last follow-up, 6 cases were grades I-II (pain-free with or without medication; 27.3%) and 7 cases were grade IV-V (<50% pain relief with medication or no pain relief; 31.8%). There was 1 case (facial dysesthesia) with post-operative complications (4.54%). Conclusion : The long-term results of GKRS for TN are not as satisfactory as those of microvascular decompression and other conventional modalities, but GKRS is a safe, effective and minimally invasive technique which might be considered a first-line therapy for a limited group of patients for whom a more invasive kind of treatment is unsuitable.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.694-706
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• 2019

In this study, we applied the long short-term memory (LSTM) model to classify the cryptocurrency price time series. We collected historic cryptocurrency price time series data and preprocessed them in order to make them clean for use as train and target data. After such preprocessing, the price time series data were systematically encoded into the three-dimensional price tensor representing the past price changes of cryptocurrencies. We also presented our LSTM model structure as well as how to use such price tensor as input data of the LSTM model. In particular, a grid search-based k-fold cross-validation technique was applied to find the most suitable LSTM model parameters. Lastly, through the comparison of the f1-score values, our study showed that the LSTM model outperforms the gradient boosting model, a general machine learning model known to have relatively good prediction performance, for the time series classification of the cryptocurrency price trend. With the LSTM model, we got a performance improvement of about 7% compared to using the GB model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1232-1245
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• 2021

In this study, prediction of product sales as they relate to changes in temperature is proposed. This model uses long short-term memory (LSTM), which has shown excellent performance for time series predictions. For verification of the proposed sales prediction model, the sales of short pants, flip-flop sandals, and winter outerwear are predicted based on changes in temperature and time series sales data for clothing products collected from 2015 to 2019 (a total of 1,865 days). The sales predictions using the proposed model show increases in the sale of shorts and flip-flops as the temperature rises (a pattern similar to actual sales), while the sale of winter outerwear increases as the temperature decreases.

• Journal of Environmental Science International
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• v.22 no.10
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• pp.1305-1316
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• 2013

A long-term wind resource map was made to provide the key design data for the 2.5 GW Korean West-South Offshore Wind Project, and its reliability was validated. A one-way dynamic downscaling of the MERRA reanalysis meteorological data of the Yeongwang-Gochang offshore was carried out using WindSim, a Computational Fluid Dynamics based wind resource mapping software, to establish a 33-year time series wind resource map of 100 m x 100 m spatial resolution and 1-hour interval temporal resolution from 1979 to 2012. The simulated wind resource map was validated by comparison with wind measurement data from the HeMOSU offshore meteorological tower, the Wangdeungdo Island meteorological tower, and the Gochang transmission tower on the nearby coastline, and the uncertainty due to long-term variability was analyzed. The long-term variability of the wind power was investigated in inter-annual, monthly, and daily units while the short-term variability was examined as the pattern of the coefficient of variation in hourly units. The results showed that the inter-annual variability had a maximum wind index variance of 22.3% while the short-term variability, i.e., the annual standard deviation of the hourly average wind power, was $0.041{\pm}0.001$, indicating steady variability.

• Journal of the korean society of oceanography
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• v.39 no.4
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• pp.207-211
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• 2004

We used long time series of hydrographic and biological variables to examine the ecosystem consequences of a rare, anomalous event in the south sea of Korea. The highest zooplankton biomass in 36 years of sampling occurred in April 1997. Zooplankton biomass exceeded 2 times than the long-term mean at 35% of the stations. Copepod abundance was low in April and June and also failed to show a seasonal peak in 1997. Mackerel (Scomber japonicus) catches were very low in spring 1997 and 1999, in spite of a positive correlation between zooplankton biomass and mackerel catches at lags of 0, 12 and 24 months. It was discussed that a high zooplankton biomass with low copepod abundance in April 1997 resulted from unusual high temperature and salps abundance. Water temperatures were ca. $2^{\circ}C$ higher than the long-term mean at the surface. Salps and doliolids (thaliaceans), especially the warm-water species Doliolum nationalis, dominated the zooplankton. An unusual incursion of the Tsushima Warm Current may have transported the thaliaceans into the area and/or produced favorable conditions for a bloom. This study suggested that taxonomic composition of zooplankton was important to decide mackerel catches.

• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.675-683
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• 2015

In the 21st century, we now face the serious problems of the enormous consumption of the energy resources. Depending on the power consumption increases, both China and South Korea face a reduction in available resources. This paper considers the regression models and time-series models to compare the performance of the forecasting accuracy based on Mean Absolute Percentage Error (MAPE) in order to forecast the electricity demand accurately on the short-term period (68 months) data in Northeast China and find the relationship with Korea. Among the models the support vector regression (SVR) model shows superior performance than time-series models for the short-term period data and the time-series models show similar results with the SVR model when we use long-term period data.

• Journal of Environmental Science International
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• v.26 no.2
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• pp.221-230
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• 2017

To determine the effect of air pollution reduction policies, the long-term trend of air pollutants should be analyzed. Kolmogorov-Zurbenko (KZ) filter is a low-pass filter, produced through repeated iterations of a moving average to separate each variable into its temporal components. The moving average for a KZ(m, p) filter is calculated by a filter with window length m and p iterations. The output of the first pass subsequently becomes the input for the next pass. Adjusting the window length and the number of iterations makes it possible to control the filtering of different scales of motion. To break down the daily mean $PM_{10}$ into individual time components, we assume that the original time series comprises of a long-term trend, seasonal variation, and a short-term component. The short-term component is attributable to weather and short-term fluctuations in precursor emissions, while the seasonal component is a result of changes in the solar angle. The long-term trend results from changes in overall emissions, pollutant transport, climate, policy and/or economics. The long-term trend of the daily mean $PM_{10}$ decreased sharply from $59.6ug/m^3$ in 2002 to $44.6ug/m^3$ in 2015. This suggests that there was a long-term downward trend since 2005. The difference between the unadjusted and meteorologically adjusted long-term $PM_{10}$ is small. Therefore, we can conclude that $PM_{10}$ is unaffected by the meteorological variables (total insolation, daily mean temperature, daily mean relative humidity, daily mean wind speed, and daily mean local atmospheric pressure) in Busan.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.521-536
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• 2021

As life expectancies increase continuously over the world, the accuracy of forecasting mortality is more and more important to maintain social systems in the aging era. Currently, the most popular model used is the Lee-Carter model but various studies have been conducted to improve this model with one of them being 6-parametric factor model (6-PFM) which is introduced in this paper. To this new model, long short-term memory (LSTM) and regularized LSTM are applied in addition to vector autoregression (VAR), which is a traditional time-series method. Forecasting accuracies of several models, including the LC model, 4-PFM, 5-PFM, and 3 6-PFM's, are compared by using the U.S. and Korea life-tables. The results show that 6-PFM forecasts better than the other models (LC model, 4-PFM, and 5-PFM). Among the three 6-PFMs studied, regularized LSTM performs better than the other two methods for most of the tests.

• Journal of Korean Neurosurgical Society
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• v.67 no.2
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• pp.237-248
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• 2024

Objective : Postoperative data on Cushing's disease (CD) are equivocal in the literature. These discrepancies may be attributed to different series with different criteria for remission and variable follow-up durations. Additional data from experienced centers may address these discrepancies. In this study, we present the results obtained from 96 endoscopic transsphenoidal surgeries (ETSSs) for CD conducted in a well-experienced center. Methods : Pre- and postoperative data of 96 ETSS in 87 patients with CD were included. All cases were handled by the same neurosurgical team between 2014 and 2022. We obtained data on remission status 3-6 months postoperatively (medium-term) and during the latest follow-up (long-term). Additionally, magnetic resonance imaging (MRI) and pathology results were obtained for each case. Results : The mean follow-up duration was 39.5±3.2 months. Medium and long-term remission rates were 77% and 82%, respectively. When only first-time operations were considered, the medium- and long-term remission rates were 78% and 82%, respectively. The recurrence rate in this series was 2.5%. Patients who showed remission between 3-6 months had higher long-term remission rates than did those without initial remission. Tumors >2 cm and extended tumor invasion of the cavernous sinus (Knosp 4) were associated with lower postoperative remission rates. Conclusion : Adenoma size and the presence/absence of cavernous sinus invasion on preopera-tive MRI may predict long-term postoperative remission. A tumor size of 2 cm may be a supporting criterion for predicting remission in Knosp 4 tumors. Further studies with larger patient populations are necessary to support this finding.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.11 no.4
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• pp.113-119
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• 1991

In the present study, a methodology has been established for water budget analysis of a river basin for which monthyl rainfall and evaporation data are the only available hydrologic data. The monthly rainfall data were first converted into monthyl runoff data by an empirical formula from which long-term runoff data were generated by a stochastic generation mothod. Thomas-Fiering model. Based on the generated long-term data low flow frequency analysis was made for each of the oberved and generated data set, the low flow series of each data set being taken as the water supply for budget analysis. The water demands for various water utilization were projected according to the standard method and the net water consumption computed there of. With the runoff series of the driest year of each generated data set as an input water budget computation was made through the composite reservoirs comprised of small reserviors existing in the basin by deficit-supply method. The water deficit computed through the reservior operation study showed that the deficit radically increases as the return period of low flow becomes large. This indicates that the long-term runoff data generated by stochastic model are a necessity for a reliable water shortage forecasting to cope with the long-term water resourse planning of a river basin. F.E.M. program (ADINA) is also presented herein.