• Journal of Korea Water Resources Association
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• v.52 no.8
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• pp.545-554
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• 2019

The most drought assessments are based on a drought index, which depends on univariate variables such as precipitation and soil moisture. However, there is a limitation in representing the drought conditions with single variables due to their complexity. It has been acknowledged that a multivariate drought index can more effectively describe the complex drought state. In this context, this study propose a Copula-based drought index that can jointly consider precipitation and soil moisture. Unlike precipitation data, long-term soil moisture data is not readily available so that this study utilized a Gaussian Mixture Non-Homogeneous Hidden Markov chain Model (GM-NHMM) model to simulate the soil moisture using the observed precipitation and temperature ranging from 1973 to 2014. The GM-NHMM model showed a better performance in terms of reproducing key statistics of soil moisture, compared to a multiple regression model. Finally, a bivariate frequency analysis was performed for the drought duration and severity, and it was confirmed that the recent droughts over Jeollabuk-do in 2015 have a 20-year return period.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1100-1118
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• 2021

In a wide range of ML applications, the training data contains privacy-sensitive information that should be kept secure. Training the ML systems by privacy-sensitive data makes the ML model inherent to the data. As the structure of the model has been fine-tuned by training data, the model can be abused for accessing the data by the estimation in a reverse process called model inversion attack (MIA). Although, MIA has been applied to shallow neural network models of recognizers in literature and its threat in privacy violation has been approved, in the case of a deep learning (DL) model, its efficiency was under question. It was due to the complexity of a DL model structure, big number of DL model parameters, the huge size of training data, big number of registered users to a DL model and thereof big number of class labels. This research work first analyses the possibility of MIA on a deep learning model of a recognition system, namely a face recognizer. Second, despite the conventional MIA under the white box scenario of having partial access to the users' non-sensitive information in addition to the model structure, the MIA is implemented on a deep face recognition system by just having the model structure and parameters but not any user information. In this aspect, it is under a semi-white box scenario or in other words a gray-box scenario. The experimental results in targeting five registered users of a CNN-based face recognition system approve the possibility of regeneration of users' face images even for a deep model by MIA under a gray box scenario. Although, for some images the evaluation recognition score is low and the generated images are not easily recognizable, but for some other images the score is high and facial features of the targeted identities are observable. The objective and subjective evaluations demonstrate that privacy cyber-attack by MIA on a deep recognition system not only is feasible but also is a serious threat with increasing alert state in the future as there is considerable potential for integration more advanced ML techniques to MIA.

• Journal of International Area Studies (JIAS)
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• v.14 no.4
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• pp.27-52
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• 2011

The regions of Central Asia have each acquired an elevated strategic importance in the new security paradigm of post-September 1lth. Comprised of five states, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan, Central Asia's newly enhanced strategic importance stems from several other factors, ranging from trans-national threats posed by Islamic extremism, drug production and trafficking, to the geopolitical threats inherent in the region's location as a crossroads between Russia, Southwest Asia and China. Although the U.S. military presence in the region began before September 11th, the region became an important platform for the projection of U.S. military power against the Taliban in neighboring Afghanistan. The analysis goes on to warn that 'with US troops already in place to varying extents in Central Asian states, it becomes particularly important to understand the faultlines, geography, and other challenges this part of the world presents'. The Kyrgyz military remains an embryonic force with a weak chain of command, the ground force built to Cold War standards, and an almost total lack of air capabilities. Training, discipline and desertion - at over 10 per cent, the highest among the Central Asian republics - continue to present major problems for the creation of combat-effective armed forces. Kyrgyzstan has a declared policy of national defence and independence without the use of non-conventional weapons. Kyrgyzstan participates in the regional security structures, such as the Collective Security Treaty Organisation (CSTO) and the Shanghai Co-operation Organisation (SCO) but, in security matters at least, it is dependent upon Russian support. The armed forces are poorly trained and ill-equipped to fulfil an effective counter-insurgency or counter-terrorist role. The task of rebuilding is much bigger, and so are the stakes - the integrity and sovereignty of the Kyrgyz state. Only democratization, the fight against corruption, reforms in the military and educational sectors and strategic initiatives promoting internal economic integration and national cohesion hold the key to Kyrgyzstan's lasting future

• Journal of Korean Neurosurgical Society
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• v.66 no.6
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• pp.681-689
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• 2023

Objective : Subarachnoid hemorrhage (SAH) is a condition characterized by bleeding in the subarachnoid space, often resulting from the rupture of a cerebral aneurysm. Delayed cerebral ischemia caused by vasospasm is a significant cause of mortality and morbidity in SAH patients, and inflammatory markers such as systemic inflammatory response index (SIRI), systemic inflammatory index (SII), neutrophil-to-lymphocyte ratio (NLR), and derived NLR (dNLR) have shown potential in predicting clinical vasospasm and outcomes in SAH patients. This article aims to investigate the relationship between inflammatory markers and cerebral vasospasm after aneurysmatic SAH (aSAH) and evaluate the predictive value of various indices, including SIRI, SII, NLR, and dNLR, in predicting clinical vasospasm. Methods : A retrospective analysis was performed on a cohort of 96 patients who met the inclusion criteria out of a total of 139 patients admitted Trakya University Hospital with a confirmed diagnosis of aSAH between January 2013 and December 2021. Diagnostic procedures, neurological examinations, and laboratory tests were performed to assess the patients' condition. The Student's t-test compared age variables, while the chi-square test compared categorical variables between the non-vasospasm (NVS) and vasospasm (VS) groups. Receiver operating characteristic (ROC) curve analyses were used to evaluate the diagnostic accuracy of laboratory parameters, calculating the area under the ROC curve, cut-off values, sensitivity, and specificity. A significance level of p<0.05 was considered statistically significant. Results : The study included 96 patients divided into two groups : NVS and VS. Various laboratory parameters, such as NLR, SII, and dNLR, were measured daily for 15 days, and statistically significant differences were found in NLR on 7 days, with specific cut-off values identified for each day. SII showed a significant difference on day 9, while dNLR had significant differences on days 2, 4, and 9. Graphs depicting the values of these markers for each day are provided. Conclusion : Neuroinflammatory biomarkers, when used alongside radiology and scoring scales, can aid in predicting prognosis, determining severity and treatment decisions for aSAH, and further studies with larger patient groups are needed to gain more insights.

• Korean Journal of Environment and Ecology
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• v.33 no.5
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• pp.605-619
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• 2019

The objective of this study was to analyze eutrophication characteristics, empirical model analysis, and variation of water quality according to monsoon intensity in Hapcheon Reservoir for 16 years from 2002 to 2017. Long-term annual water quality analysis showed that Hapcheon Reservoir was in a meso-nutrition to eutrophic condition, and the eutrophic state intensified after the summer monsoon. Annual rainfall volume (high vs. low rainfall) and the seasonal intensity in each year were the key factors that regulate the long-term water quality variation provided that there is no significant change of the point- and non-point source in the watershed. Dry years and wet years showed significant differences in the concentrations of TP, TN, BOD, and conductivity, indicating that precipitation had the most direct influence on nutrients and organic matter dynamics. Nutrient indicators (TP, TN), organic pollution indicators (BOD, COD), total suspended solids, and chlorophyll-a (Chl-a), which was an estimator of primary productivity, had significant positive relations (p<0.05) with precipitation. The Chl-a concentration, which is an indicator of green algae, was highly correlated with TP, TN, and BOD, which differed from other lakes that showed the lower Chl-a concentration when nutrients increased excessively. Empirical model analysis of log-transformed TN, TP, and Chl-a indicated that the Chl-a concentration was linearly regulated by phosphorus concentration, but not by nitrogen concentration. Spatial regression analysis of the riverine, transition, and lacustrine zones of $log_{10}TN$, $log_{10}TP$, and $log_{10}CHL$ showed that TN and Chl-a had significant relations (p<0.005) while TN and Chl-a had p > 0.05, indicating that phosphorus had a key role in the algal growth. Moreover, the higher correlation of both $log_{10}TP$ and $log_{10}TN$ to $log_{10}CHL$ in the riverine zone than the lacustrine zone indicated that there was little impact of inorganic suspended solids on the light limitation in the riverine zone.

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.486-491
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• 2004

Purpose: factor analysis and independent component analysis (ICA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial $H_2^{15}O$ PET data. In this study, we quantified patients' blood flow using the ensemble ICA method. Materials and Methods: Twenty subjects underwent $H_2^{15}O$ PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of $555{\sim}740$ MBq $H_2^{15}O$. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Results: Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was $1.2{\pm}0.40$ ml/min/g in rest, $1.85{\pm}1.12$ ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between the regions with and without stenosis detected by the coronary angiography (P<0.01). In 66 segment with stenosis confirmed by angiography, the segments with reversible perfusion decrease in perfusion SPECT showed lower perfusion reserve values in $H_2^{15}O$ PET. Conclusions: Myocardial blood flow could be estimated using an ICA method with ensemble learning. We suggest that the ensemble ICA incorporating non-negative constraint is a feasible method to handle dynamic image sequence obtained by the nuclear medicine techniques.

• The Journal of Korean Society for School & Community Health Education
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• v.3
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• pp.35-58
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• 2002

This research attempted to investigate the real state of adolescent smoking and drinking, and to study how stress influences on smoking and drinking of high school students. This data was collected from 837 first and second grade students in a vocational high school in Go-yang city, Gyeonggi province. Data analysis consisted of frequency, percentage, Chi-square, T-test, step-wise regression analysis, using SPSSWIN. The results of analysis were as follows: First, 51.7% of the students have never smoked, while 48.3% have experienced smoking. Most students started smoking in the second year of the middle school, though 17.6% of the smokers already started in the elementary school. The strongest motive of initial smoking was curiosity, next the inducement of friends, and 10.9% of them smoked to get rid of stress. Their favorite place for smoking was in the order of the entertainment centers, schools, and private academies. They personally purchased cigarettes mostly at the store. Most of them smoked less than 5 cigarettes a day, but 3.7% smoked more than a pack of cigarettes a day, usually with friends rather than alone. Second, the ratio of drinking was relatively high 78.1%, and their initial drinking experience was most frequent at the third year of the middle school. The initial motive of drinking was mostly curiosity and the inducement of friends, but 10.7% of them started drinking to reduce stress and anxiety. The places for buying alcohol and drinking were bars or restaurants. The ratio of habitual drinking was 45.1%, and the ratio of irregular drinking was 53.3%. 1.8% of the drinking students enjoyed drinking everyday. The amount of drinking varied from half a bottle to two bottles of Soju, and the drinking problem was serious to see that 11% of them drank more than two bottles at a time. Because 84.4% drank in groups with friends, a thorough and systematic supervision and education of the peer group drinking is essential. Third, as for the relationship between personal matters and smoking, it was found that there was a positive relation between smoking and sex, but there was no correlation between smoking and school years. Adolescent smoking was also related with scholastic achievement, the number of friends, and the existence of parents. Fourth, as for the relationship between personal matters and drinking, it was found that there was no correlation between drinking and sex, but there was a positive relation between drinking and school years. Fifth, the average index of stress was students themselves(2.58), school life(2.53), family life(2.19), friends(2.00), and the total index of stress was 2.33. Sixth, there appeared a marginal negative correlation between stress and 'drinking and smoking' in Pearson coefficient of correlation r to see the influence of stress on smoking and drinking. The difference of the average index of stress according to smoking and drinking bears meaningful difference for all students, smokers and non-smokers, drinkers and abstainers in students themselves, school life, family life, friends, and total stress. Smoking has an effect on family life most, school life next, and drinking has an effect on school life most, family life next, with the explanation power of 11% and 9% respectively, in a regression analysis to analyze the factors influencing on smoking and drinking among the factors of stress.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• The Journal of Korean Academy of Prosthodontics
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• v.43 no.2
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• pp.158-175
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• 2005

Statement of problem. Every effort has been continually made to obtain objectivity in measuring the longevity of fixed restorations, such as by establishing unified judgement standard for deciding success and adopting statistical method that analyzes the data of successful and failed cases at the same time. In Korea, however desired level of development has not to be made in this field yet. Purpose. This study, adopting California Dental Association (CDA) quality evaluation system, established objective standard for deciding success, and inferred the longevity of fixed restorations and their failure analysis through adopting Kaplan-Meier survival analysis. Material and method. In order to assess the longevity of flxed restorations serviced in Korea and causes of failure, a total of 1109 individuals (aged 15-74, 716 women and 393 men loaded with 2551 unit fixed restorations, and 1934 abutments) who lived in Kyung-In Province were examined and the findings were as follows : Results. 1. Length of service of fixed restorations serviced in Korea was 6.86$\pm$0.15 yr (mean), 5.5 yr (median), and the rate of success was 65.82% in 5 year survival, and 21.15% in 10 year survival. 2. When there was patient's need for replacing old prosthetics, longevity of fixed restorations was 7.51$\pm$0.27 yr (mean), 7 yr (median), and the rate of success was 61.08% in 5 year survival, and 17.57% in 10 year survival. 3. Longevity of fixed restorations was longest in the over-sixty age group(9.21$\pm$0.66) and that of the teen age group(3.39$\pm$0.28) was shortest (p<0.05). 4. Longevity of fixed restorations of women (7.38$\pm$0.18 years) was longer than that of men (6.00$\pm$0.26) (p<0.05). 5. As for the provider factor (such as unlicensed performers, university hospitals, and private clinic), there was no statistically significant difference in longevity of fixed restorations. 6. Defective margin (34.78%). periodontal disease (12.15%), periapical involvement (11.73%), was the most frequent causes of failure and poor esthetics group showed the longest life above all (p<0.05). Actual frequent causes of failure after removing old prosthetics were defective margin, periapical involvement, periodontal disease and uncemented restoration. In 75.67% of the cases, abutment state after removing old prosthetics was good enough for loading another prosthetics. 7. There was found to have statistically significant influence between longevity of single crown (6.35$\pm$0.20 yr) and that of 3 unit fixed restorations (7.60$\pm$0.30 y) (p<0.05). In each case the most frequent cause of failure was defective margin. 8. The number of cantilever pontic, pontic/abutment ratio, oral hygiene status were found to have no statistically significant influence on longevity of fixed restorations in all groups (p>0.05). 9. Longevity of fixed restorations made of non precious metal was longest (9.60$\pm$0.40 yr) semi precious and precious trailing behind(p<0.05). 10. Group function group (37.04%) and partial group function group (44.62%) were predominant in frequency but showed no correlation between them and among different types of occlusal plane and different types of occlusal surface (p>0.05). 11. Longevity of fixed restorations was longest in the centric interference group(9.35$\pm$0.62) (p<0.05) among different types of occlusal interference. Conclusion. We found that longevity of fixed restorations serviced in Korea is affected by age, gender and type of material, and that most frequent cause of failure is defective margin. In order to assess the accurate longevity of axed restorations, unified research design. overcoming inter-observer difference and establishing the objective research items are needed. Furthermore, it is thought that prospective approach through thorough study and regular follow-ups is needed just from the start of research. Nationwide detailed studies on length of service of fixed restorations manufactured in Korea are hoped to be conducted hereafter.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.3
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• pp.194-200
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• 2007

Purpose: $^{13}N$-ammonia is a well known radiopharmaceutical for the measurement of a myocardial blood flow (MBF) non-invasively using PET-CT. In this study, we investigated a correlation between MBF obtained from dynamic imaging and myocardial perfusion score (MPS) obtained from static imaging for usefulness of cardiac PET study. Methods: Twelve patients (11 males, 1 female, $57.9{\pm}8.6$ years old) with suspicious coronary artery disease underwent PET-CT scan. Dynamic scans (6 min: $5\;sec\;{\times}\;12,\;10\;sec\;{\times}\;6,\;20\;sec\;{\times}\;3,\;and\;30\;sec\;{\times}\;6$) were initiated simultaneously with bolus injection of 11 MBq/kg $^{13}N-ammonia$ to acquire rest and stress image. Gating image was acquired during 13 minutes continuously. Nine-segment model (4 basal walls, 4 mid walls, and apex) was used for a measurement of MBF. Time activity curve of input function and myocardium was extracted from ROI methods in 9 regions for quantification. The MPS were evaluated using quantitative analysis software. To compare between 20-segment model and 9-segment model, 6 basal segments were excluded and averaged segmental scores were used. Results: There are weak correlation between MBF (rest, 0.18-2.38 ml/min/g; stress, 0.40-4.95 ml/min/g) and MPS (rest 22-91%, stress, 14-90%), however the correlation coefficient between corrected MBF and MPS in rest state was higher than stress state (rest r=0.59; stress r=0.80). As a thickening increased, correlation between MBF and MPS also showed good correlation at each segments. Conclusions: Corrected and translated MPS as its characteristics using $^{13}N$-ammonia showed good correlation with absolute MBF measured by dynamic image in this study. Therefore, we showed MPS is one of good indices which reflect MBF. We anticipate PET-CT could be used as useful tool for evaluation of myocardial function in nuclear cardiac study.