• Radiation Oncology Journal
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• v.36 no.2
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• pp.139-146
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• 2018

Purpose: IBTR! 2.0 nomogram is web-based nomogram that predicts ipsilateral breast tumor recurrence (IBTR). We aimed to validate the IBTR! 2.0 using an external data set. Materials and Methods: The cohort consisted of 2,206 patients, who received breast conserving surgery and radiation therapy from 1992 to 2012 at our institution, where wide surgical excision is been routinely performed. Discrimination and calibration were used for assessing model performance. Patients with predicted 10-year IBTR risk based on an IBTR! 2.0 nomogram score of <3%, 3%-5%, 5%-10%, and >10% were assigned to groups 1, 2, 3, and 4, respectively. We also plotted calibration values to observe the actual IBTR rate against the nomogram-derived 10-year IBTR probabilities. Results: The median follow-up period was 73 months (range, 6 to 277 months). The area under the receiver operating characteristic curve was 0.607, showing poor accordance between the estimated and observed recurrence rate. Calibration plot confirmed that the IBTR! 2.0 nomogram predicted the 10-year IBTR risk higher than the observed IBTR rates in all groups. High discrepancies between nomogram IBTR predictions and observed IBTR rates were observed in overall risk groups. Compared with the original development dataset, our patients had fewer high grade tumors, less margin positivity, and less lymphovascular invasion, and more use of modern systemic therapies. Conclusions: IBTR! 2.0 nomogram seems to have the moderate discriminative ability with a tendency to over-estimating risk rate. Continued efforts are needed to ensure external applicability of published nomograms by validating the program using an external patient population.

• Journal of The Geomorphological Association of Korea
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• v.20 no.4
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• pp.85-99
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• 2013

The objective of this paper is to analyze the spatial distribution of errors in the DEM generated using waterlines from multi-temporal remote sensing data and to assess flood vulnerability. Unlike conventional research in which only global statistics of errors have been generated, this paper tries to quantitatively analyze the spatial distribution of errors from a probabilistic viewpoint using geostatistical simulation. The initial DEM in Baramarae tidal flats was generated by corrected tidal level values and waterlines extracted from multi-temporal Landsat data in 2010s. When compared with the ground measurement height data, overall the waterline-based DEM underestimated the actual heights and local variations of the errors were observed. By applying sequential Gaussian simulation based on spatial autocorrelation of DEM errors, multiple alternative error distributions were generated. After correcting errors in the initial DEM with simulated error distributions, probabilities for flood vulnerability were estimated under the sea level rise scenarios of IPCC SERS. The error analysis methodology based on geostatistical simulation could model both uncertainties of the error assessment and error propagation problems in a probabilistic framework. Therefore, it is expected that the error analysis methodology applied in this paper will be effectively used for the probabilistic assessment of errors included in various thematic maps as well as the error assessment of waterline-based DEMs in tidal flats.

• Journal of Korean Society of Water and Wastewater
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• v.34 no.6
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• pp.503-512
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• 2020

Identifying the water circulation status is one of the indispensable processes for watershed management in an urban area. Recently, various water circulation models have been developed to simulate the water circulation, but it takes a lot of time and cost to make a water circulation model that could adapt the characteristics of the watershed. This paper aims to develop a water circulation state estimation model that could easily calculate the status of water circulation in an urban watershed by using multiple linear regression analysis. The study watershed is a watershed in Seoul that applied the impermeable area ratio in 1962 and 2000. And, It was divided into 73 watersheds in order to consider changes in water circulation status according to the urban characteristic factors. The input data of the SHER(Similar Hydrologic Element Response) model, a water circulation model, were used as data for the urban characteristic factors of each watershed. A total of seven factors were considered as urban characteristic factors. Those factors included annual precipitation, watershed area, average land-surface slope, impervious surface ratio, coefficient of saturated permeability, hydraulic gradient of groundwater surface, and length of contact line with downstream block. With significance probabilities (or p-values) of 0.05 and below, all five models showed significant results in estimating the water circulation status such as the surface runoff rate and the evapotranspiration rate. The model that was applied all seven urban characteristics factors, can calculate the most similar results such as the existing water circulation model. The water circulation estimation model developed in this study is not only useful to simply estimate the water circulation status of ungauged watersheds but can also provide data for parameter calibration and validation.

• Korean Journal of Poultry Science
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• v.42 no.1
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• pp.1-8
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• 2015

Recently, duck meat consumption has been rapidly increased because consumers recognized duck meat for healthy food. In relation to this, Korean duck industry need to develop Korean native duck (KND) breed for both conservation perspective and self-sufficient of the breeding stocks. In this study, 24 microsatellite (MS) markers were investigated for classification of KND and commercial duck (CD) breeds in the Korean market. Using these MS markers, the calculated number of alleles (K), expected heterozygosity (He) values and polymorphic information contents (PIC) were 1~16, 0~0.865 and 0~0.841, respectively. Also, the expected probability of identical values in random individuals (PI), random sib ($PI_{sib}$) and random half-sib ($PI_{half-sib}$) were estimated as $1.64{\times}10^{-16}$, $2.60{\times}10^{-7}$ and $1.30{\times}10^{-12}$, respectively. The results indicated that the expected probabilities of identity powers were enough for the individual identification. However, KND and CD breeds were not fully discriminated well using the 24 MS markers, which may CD and KND has shared same origin or crossbred. Therefore, further studies will be ultimately needed for developing a genetically pure line of KND breed even though the DNA markers used. Finally, these results will provide useful information for individual traceability system in ducks.

• Journal of Environmental Impact Assessment
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• v.30 no.1
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• pp.13-23
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• 2021

In this study, we performed a Random Walker analysis to predict the Major Movement Paths of otters. The scope of the research was a simulation analysis with a radius of 7.5 km set as the final range centered on the Ansim-wetland in Daegu City, and a field survey was used to verify the model. The number of virtual otters was set to 1,000, the number of moving steps was set to 1,000 steps per grid, and simulations were performed on a total of 841 grids. As a result of the analysis, an average of 147.6 objects arrived at the boundary point under the condition of an interval of 50 m. As a result of the simulation verification, 8 points (13.1%) were found in the area where the movement probability was very high, and 9 points (14.8%) were found in the area where the movement probability was high. On the other hand, in areas with low movement paths probabilities, there were 8 points (13.1%) in low areas and 4 points (6.6%) in very low areas. Simulation verification results In areas with high otter values, the actual otter format probability was particularly high. In addition, as a result of investigating the correlation with the otter appearance point according to the unit area of the evaluation star of the movement probability, it seems that 6.8 traces were found per unit area in the area where the movement probability is the highest. In areas where the probability of movement is low, analysis was performed at 0.1 points. On the side where otters use the major movement paths of the river area, the normal level was exceeded, and as a result, in the area, 23 (63.9%), many form traces were found, along the major movement paths of the simulation. It turned out that the actual otter inhabits. The EN-Simulator analysis can predict how spatial properties affect the likelihood of major movement paths selection, and the analytical values are used to utilize additional habitats within the major movement paths. It is judged that it can be used as basic data such as to grasp the danger area of road kill in advance and prevent it.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.7-18
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• 2012

This study suggested a method of forecasting market-share of each mode after introducing new urban rail transit lines. The study reflected the observed market share of presently operating urban rail transit into forecasting process in order to improve accuracy in predicting market share of each modes. For more realistic representation of the forecasting model, we categorized O/D pairs according to attributes of trip distance, access time and number of transfers. The analysis results of traveler's mode choice behavior with observed data showed that the trip distances are longer, the share of urban rail tends to be higher, and that the number of transfers is fewer and the access times are lesser, the share of urban rail also tends to be higher. Then, incremental logit model was used in estimating mode choice probabilities for O/D pairs along with rail transit lines while utilizing observed market shares of each modes and differences in transit service level. As the next step, the market share of rail transit after introducing new rail transit lines was forecasted by using incremental logit model with the intial share values calculated the previous analysis step. It also reflected changes in level of service for automobile in highway due to changes in highway systems and changes in mode shares after introducing new lines of rail transit. It can be expected that the proposed method would more realistically duplicates phenomena of mode choice behavior for rail transit and that it would be more theoretically logical than the typical existing methods using SP data and incremental logit model or using addictive logit model in this country.

• Journal of Life Science
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• v.16 no.4
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• pp.626-631
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• 2006

This study was carried out to investigate the physical characteristics (height, body lenght, chest depth, head type, ear type, body color, eye type and tail type) and genetic diversity using 15 microsatellite DNA markers (PEZ 1, 5, 8, 10, 11, 12, 13, 15, 16, 17, 20, 21, FHC 2010, FHC 2054 and FHC 2079) in 44 random Miryang native dogs(6 months${\sim}$12 years old). The height, body lenght, and chest depth of Miryang native dogs were 43-55 cm(mean 49.5 cm), 45-60 cm(mean 54.3 cm), and 50-64 cm(mean 57.9 cm), respectively. Miryang native dog was medium sized. The head and eye type were reverse-triangle(100%), triangle (90.9%) and newborn moon(9.1%), respectively. Most of body color had white coat color(93.2%), light pink tongue color(100%), light black anal color(90,9%) and pink claw color(100%). The ear type showed erect ear(100%), and half-curled(56.8%), upward(34.1%), curled(9.1%) in tail type, respectively. Number of alleles observed at a single locus ranged from 2 (PEZ 21 and FHC 2010) to 14 (PEZ 13), with average number of alleles per locus of 6.13. The expected heterozygosities of 15 microsatellite loci were estimated based on gene frequencies. The highest expected heterozygosity, 0.863 was estimated in PEZ 13 locus and the lowest, 0.455 in PEZ 21 and FHC 2010 locus. And the mean expected heterozygosity of 15 microsatellite markers was calculated as 0.635. Polymorphic information content (PIC) values were ranged from 0.348 (PEZ 21 and FHC 2010) to 0.837 (PEZ 13), and the mean PIC value was calculated as 0.570. Of the 15 markers, PEZ 10, PEZ 13, PEZ 17 and FHC 2054 loci have relatively high PIC value (> 0.7) in Miryang native dog. In order to determine the efficieney of parentage control, exclusion probabilities (PE) were calculated for each allele. The highest PE 1 and PE 2 in PEZ 13 locus was caculated to 0.548 and 0.710, respectively. And the total exclusion power in PE 1 and PE 2 was calculated to 0.9895 and 0.9996, respectively. These results can give basic information for perservation and research in Miryang native dog, and phylogenetic relationships of the Korean native dog and Asian dog breeds.

• Korean Journal of Soil Science and Fertilizer
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• v.42 no.1
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• pp.53-57
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• 2009

Heavy metal pollution may be one of the most serious challenges confront crop production and human health. Therefore, the selection of heavy metal tolerance cultivars which adapted to the contaminated fields will introduced a suitable solution for management this critical environmental risk. The objectives of this research is to assess human health risk using geochemical analyses and exposure assessment of heavy metals in rice cultivars. Risk for inhabitants in the closed mine area was comparatively assessed for As, Cd, Cu and Pb in 10 rice varieties as a major exposure pathway. The average daily dose (ADD) of each heavy metal was estimated by analyzing the exposure pathways to rice and soil. For the non-carcinogenic risk characterization, Hazard Quotient (HQ) and Hazard Index (HI) were calculated using toxicity indices provided by US-EPA IRIS. The different rice varieties revealed a wide range of HI values from 23.6 to 34.3, indicating that all rice varieties have a high potential toxic risk. The DA rice variety showed the lowest HI value while the TB rice variety the highest. The probabilities of cancer risk for As via rice consumption were varied with rice varieties ranging from 2.0E-03 to 3.5E-03 which exceeded the regulatory acceptable risk of 1 in 10,000 set by US-EPA. The DA rice variety also showed the lowest value while the TB rice variety gave the highest value. Our results indicate that risk assessment can be contribute to screen the pollution safe rice cultivars in paddy fields affected by the mining activity.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.17-32
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• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.