• The Journal of Engineering Geology
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• v.28 no.4
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• pp.661-672
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• 2018

Radon concentration was measured in a total of 5,453 groundwater samples from wells across Korea. The radon concentrations showed the values ranging from 0.1 Bq/L to 7,218.7 Bq/L, with a median of 48.8 Bq/L which is lower than those of other countries having similar geological conditions. The distribution of radon concentrations was lognormal. The median value is high in the granite areas (63.5-105.1 Bq/L) while it is low in the sedimentary rocks and Cheju volcanic area (16.0-20.3 Bq/L). When grouping the groundwater with well depth, the median radon value is high in weathering and/or upper bedrock zone (61.4 Bq/L) while it is low in alluvium and/or weathering zone (28.5 Bq/L). About 17.7% of the total samples exceeded 148 Bq/L of USEPA guideline value. The exceeding radon ratio more than 148 Bq/L in groundwater is highest in Jurassic granite area, however, the exceeding radon rates more than 300 Bq/L and 500 Bq/L are highest in CGRA area.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of the Korean GEO-environmental Society
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• v.5 no.2
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• pp.51-62
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• 2004

Granular compaction piles have the load bearing capacity of the soft ground increase and have the settlement of foundation built on the reinforced soil reduce. The granular compaction group piles also have the consolidation of the soft ground accelerate and have the liquefaction caused by earthquake prevent using the granular materials such as sand, gravel, stone etc. However, this method is one of unuseful methods in Korea. The Granular compaction piles are constructed by grouping it with a raft system. The confining pressure at the center of bulging failure depth is a major variable in relation to estimate for the ultimate bearing capacity of the granular compaction piles. Therefore, a share of loading is determined considering the effect of load concentration ratio between the granular compaction piles and surrounding soils, and varies the magnitude of the confining pressure. In this study, method for the determination of the ultimate bearing capacity is proposed to apply a change of the horizontal pressure considering bulging failure depth, surcharge and loaded area. Also, the ultimate bearing capacity of the granular compaction piles is evaluated on the basis of previous study on the estimation of the ultimate bearing capacity and compared with the results obtained from laboratory scale model tests. And using the result from laboratory model tests, it is studied increase effect of the bearing capacity on the granular compaction piles and variance of coefficient of consolidation for the ground.

• Journal of Physiology & Pathology in Korean Medicine
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• v.18 no.5
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• pp.1426-1436
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• 2004

There have been several reports on the relationship between G protein β3 subunit gene (GNB3), angiotensin converting enzyme gene (ACE), β3-adrenergic receptor gene (ADRB3), and β2-adrenergic receptor gene (ADRB2) genotype and obesity or obesity related disease. The objective of this study was to examine the relationship between the combinations of these four genes' polymorphism and probability of obesity related disease in Korean female subjects. The experimental group was consisted of 85 obese Korean female subjects (body mass index, BMI≥27㎏/㎡). To determine the polymorphism, genomic DNA was isolated, and PCR was performed. Serological examinations (fasting plasma glucose, FPG; aspartate aminotranferase, AST; alanine aminotransferase, ALT; total cholesterol, TC; triglyceride, TG; high density lipoprotein-cholesterol, HDL; low density lipoprotein-choles terol, LDL) were carried by an autoanalyzer and serological methods. BMI, waist circumference (WC), hip circumference and waist hip ratio (WHR) were measured. Consequencely in the analysis with grouping of general genotyping and variant allele carrier/non-carrier, the result was not significantly different within all gene combinations and polymorphic pairings except higher waist circumference in Arg16Arg group of ADRB2 codon16 (P=0.024). And there was no significantly contrast result about age, height, weight, AST and ALT that are index feature of liver and gall bladder disease in polymorphic pairings of gene combinations. However, the statistical analysis of waist-hip ratio and waist circumference that could be recognized as the physical type of obesity showed T-Arg16 pairing carrier in GNB3-ADRB2 codon16 combination had increased WHR and WC significantly (P=0.046 and P=0.015 respectively). Futhermore, the levels of total cholesterol (TC) and low density lipoprotein choresteral (LDL) were significantly lower in C-I pairing of GNB3-ACE combination (P=0.032 and P=0.005). These results suggest that the T-Arg16 pairing carrier in GNB3-ADRB2 codon16 gene might have increased waist circumference and C-I pairing carrier in GNB3-ACE combination have lower possibility of contraction of cardiovascular disease related cholesterol and LDL despite of obese state.

• Ocean and Polar Research
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• v.33 no.3
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• pp.265-280
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• 2011

The temporal dynamics of the meiofauna community in Marian Cove, King George Island, Antarctica were observed from March 7 to December 21 2007. Nine meiofauna taxa were found, with nematodes the most dominant group, making up 92.97% of the total meiofauna density, followed by harpacticoid copepods (3.18%). Meiofauna abundance ranged from 123 to 874 individuals per 10 $cm^2$ (mean 464 inds.10 $cm^{-2}$), which is lower than that found in some polar and temperate regions. The lowest meiofauna abundance was found in the 26th April sample (III) and the highest meiofauna abundance was found in the March 23rd sample (II). There was no correlation between meiofauna abundance and season. The seasonal changes were likely caused by meltwater runoff, and there were the physical disturbances on the bottom sediment by huge iceberg. Biomass of meiofauna varied between 20.36 and 101.02 ${\mu}gC{\cdot}10\;cm^{-2}$, and overall mean biomass was 54.17 ${\mu}gC{\cdot}10\;cm^{-2}$ during the study periods. More than 80% of meiofauna was concentrated in the upper 2 cm of the sediment, and density decreased with depth. The mean diversity index was 0.37, and the ratio between the abundance of nematodes: and harpacticoids (N/C) ratio ranged from 7.31 to 95.04 (mean 26.39). NMDS analysis divided the community into three groups: A (III, IV, V, VII, VIII), B (II, IX, XI, XII) and C (I, V, X). The results of ANOSIM and SIMPER analysis revealed significant differences in community structure among three groups and major contributed meiofauna taxon in grouping were nematodes and copepods. No significant correlations were observed between major meiofauna taxon and environmental factors. Thirteen species in 12 genera representing nine families of harpacicoids were recorded. Ancorabolidae was the most diverse family, and Heteropsyllidae was the most abundant. The correlation analysis between benthic harpacticoid copepods and environmental factors showed that some species were affected by water temperature, sediment temperature, salinity, chlorophyll a concentration, grain size of the sediments and heavy metal contents of the sediments. These data describe the usefulness of benthic harpacticoid copepods as biological indicator species in Antarctic regions.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.4
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• pp.262-268
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• 2007

To characterize morphological classification of the basins, four major basin characteristics of the unit basins, including sinuosity, ratio of forest, ratio of flat area, and tributary existence were selected for cluster analysis. The analysis was carried out using soil map, topographic map, water course map, and basin map of the fifty unit basins in the Yeongsangang Basin. The unit basins could be categorized to five basin groups. The fitness by the Mantel test showed good fit of which r was 0.830. These grouping based on comprehensive soil and topographic characteristics provides best management practices, water quality management according to pollutants, increased water related model application and reasonable availability of water management. For agricultural management of water resources and conservation of water quality from agricultural non-point pollutants, therefore, comprehensive systematic classification of soil characteristics on unit basin might be an useful tool.

• Journal of the Korean Geotechnical Society
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• v.20 no.2
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• pp.115-124
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• 2004

Granular compaction pile has the load bearing capacity of the soft ground increase and has the settlement of foundation built on the reinforced soil reduce. The granular compaction group piles also have the consolidation of the soft ground accelerate and prevent the liquefaction caused by earthquake using the granular materials such as sand, gravel, stone etc. However, this method is not widely used in Korea. The granular compaction piles are constructed by grouping them with a raft system. The confining pressure at the center of bulging failure depth is a major variable in estimating the ultimate bearing capacity of the granular compaction piles. Therefore, a share of loading is determined considering the effect of load concentration ratio between the granular compaction piles and surrounding soils, and the variation of the magnitude of the confining pressure. In this study, a method for the determination of the ultimate bearing capacity is proposed to apply a change of the horizontal pressure considering bulging failure depth, surcharge, and loaded area. Also, the ultimate bearing capacity of the granular compaction pile is evaluated on the basis of previous study(Kim et al., 1998) on the estimation of the ultimate bearing capacity and compared with the results obtained from laboratory scale model tests and DEM numerical analysis using the PFC-2D program.

• Journal of Gastric Cancer
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• v.5 no.3 s.19
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• pp.163-168
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• 2005

Purpose: We analyzed cases of advanced gastric cancer (AGC) by using two nodal stagings, UICC and Japanese systems. We also analyzed cases of UICC N3M0 by different ways to see which nodal system or group had better prognostic power. Materials and Methods: From Feb. 1990 to May 2000, 197 UICC M0 patients of AGC who had undergone curative resection were analyzed by using the nodal stagings of the UICC and the Japanese systems. Also, 58 patients with UICC N3M0 gastric cancer were analyzed by using the Japanese n-staging, metastatic ratio and the metastatic number Results: The 5-year survival rates were 62.9%, 33.0% and 21.2% for UICC N1, N2 and N3, and 61.2% and 25.3% for Japanese n1 and n2, respectively in patients of N3M0 AGC, the 5-year survival rates were 62.5% for Japanese n1, and 33.0% and 22.9% for metastatic ratios of less than 0.5 and metastatic numbers below 26, respectively significantly better than the 5-year survival rates for higher ratios and numbers (P=0.018, 0.021). Conclusion: UICC N staging of gastric cancer has better prognostic power with differentiation between stages than Japanese n staging. In patients with UICC N3M0 gastric cancer, the metastatic ratio and the metastatic number, as well as the Japanese n staging, were valuable prognostic factors.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.374-381
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• 2011

The purpose of this study is to examine the possibility of early detection of Pine Wilt Disease (PWD) using NDVI (Normalized Difference Vegetation Index) from ADC (Agricultural Digital Camera) imageries. The PWD induces the different patterns of reduction of NDVI between healthy trees and infected trees, due to the withered leaves on the infected trees. Based on these phenomena, the DI showing the NDVI variations of trees by time series was employed to detect the infected trees. To find out the differences of DI level between normal and infected trees, DIs of trees from May to August in 2007 were calculated and these were analyzed with GLM (General Linear Models) in SAS 9.2. As a result, the difference of DI between in June and August shows the most significant level (0.0001). The discriminant analysis was performed between normal and infected trees, using the DI of June and August. As the result, hit ratio of trees and the accuracy of grouping with Jack-knife method were shown 71.9% and 73.5%, respectively. These results showed that the DI is effective to detect the trees infected by the PWD and it is useful to prevent the PWD.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.