• Journal of Applied Biological Chemistry
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• 제62권2호
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• pp.129-135
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• 2019

Salvia miltiorrhiza Radix is cultivated in Korea and China and is traditionally used to treat cardiovascular diseases. In this study, we developed and validated a quantitative analysis method for S. miltiorrhiza Radix using high-performance liquid chromatography (HPLC). Identification was performed using ultra performance liquid chromatography-tandem mass spectrometry. For quantitative analysis, we used seven marker compounds. Separation conditions for HPLC were optimized using an ODS column with gradient conditions of 1% formic acid in distilled water and 1% formic acid in acetonitrile, with a flow rate of 0.8 mL/min and a detection wavelength of 280 nm. This method showed good linearity ($R^2=0.9998$), precision (relative standard deviation ${\leq}3.3%$), accuracy (recovery of 94.16-102.89%), limit of detection ($7.53{\mu}g/mL$), and limit of quantification ($23.71{\mu}g/mL$). This approach successfully quantified marker compounds in S. miltiorrhiza Radix. The individual marker compounds were identified by comparing the molecular masses and retention times with does standard compounds. Marker compound contents of S. miltiorrhiza Radix were investigated with different cultivation regions. Seven marker compounds were detected and quantified in all samples. Among them, salvianolic acid B showed the highest contents and it ranged from 4.13 to 7.15%. The salvianolic acid B content (7.15%) of marker compound was the highest in Bonghwa, and the tanshinone IIA content (1.90%) was the highest in Pohang. The results of marker compounds and developed method were intended to provide a favorable reference for the study of S. miltiorrhiza Radix from different regions of Korea.

• 응용통계연구
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• 제34권2호
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• pp.153-166
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• 2021

약물유전체학 연구의 주요 목표는 고차원의 유전 변수를 기반으로 개인의 약물 반응성을 예측하는 것이다. 변수의 개수가 많기 때문에 변수의 개수를 줄이기 위해서는 변수 선택이 필요하며, 선택된 변수들은 머신러닝 알고리즘을 사용하여 예측 모델을 구축하는데 사용된다. 본 연구에서는 400명의 뇌전증 환자의 차세대 염기서열 분석 데이터에 로지스틱 회귀, ReliefF, TurF, 랜덤 포레스트, LASSO의 조합과 같은 여러 가지 혼합 변수 선택 방법을 적용하였다. 선택된 변수들에 랜덤포레스트, 그래디언트 부스팅, 서포트벡터머신을 포함한 머신러닝 방법들을 적용했고 스태킹을 통해 앙상블 모형을 구축하였다. 본 연구의 결과는 랜덤포레스트와 ReliefF의 혼합 변수 선택 방법을 이용한 스태킹 모형이 다른 모형보다 더 좋은 성능을 보인다는 것을 보여주었다. 5-폴드 교차 검증을 기반으로 하여 적합한 최적 모형의 평균 검증 정확도는 0.727이고 평균 검증 AUC 값은 0.761로 나타났다. 또한, 동일한 변수를 사용할 때 스태킹 모델이 단일 머신러닝 예측 모델보다 성능이 우수한 것으로 나타났다.

• 한국정보시스템학회지:정보시스템연구
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• 제30권4호
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• pp.21-42
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• 2021

Purpose In order for companies to continue to grow, they should properly manage human resources, which are the core of corporate competitiveness. Employee turnover means the loss of talent in the workforce. When an employee voluntarily leaves his or her company, it will lose hiring and training cost and lead to the withdrawal of key personnel and new costs to train a new employee. From an employee's viewpoint, moving to another company is also risky because it can be time consuming and costly. Therefore, in order to reduce the social and economic costs caused by employee turnover, it is necessary to accurately predict employee turnover intention, identify the factors affecting employee turnover, and manage them appropriately in the company. Design/methodology/approach Prior studies have mainly used logistic regression and decision trees, which have explanatory power but poor predictive accuracy. In order to develop a more accurate prediction model, XGBoost is proposed as the classification technique. Then, to compensate for the lack of explainability, SHAP, one of the XAI techniques, is applied. As a result, the prediction accuracy of the proposed model is improved compared to the conventional methods such as LOGIT and Decision Trees. By applying SHAP to the proposed model, the factors affecting the overall employee turnover intention as well as a specific sample's turnover intention are identified. Findings Experimental results show that the prediction accuracy of XGBoost is superior to that of logistic regression and decision trees. Using SHAP, we find that jobseeking, annuity, eng_test, comm_temp, seti_dev, seti_money, equl_ablt, and sati_safe significantly affect overall employee turnover intention. In addition, it is confirmed that the factors affecting an individual's turnover intention are more diverse. Our research findings imply that companies should adopt a personalized approach for each employee in order to effectively prevent his or her turnover.

• 한국IT서비스학회지
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• 제21권3호
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• pp.63-72
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• 2022

The extinction crisis of local cities, caused by a population density increase phenomenon in capital regions, directly causes the increase of vacant houses in local cities. According to population and housing census, Gunsan-si has continuously shown increasing trend of vacant houses during 2015 to 2019. In particular, since Gunsan-si is the city which suffers from doughnut effect and industrial decline, problems regrading to vacant house seems to exacerbate. This study aims to provide a foundation of a system which can predict and deal with the building that has high risk of becoming vacant house through implementing a data driven vacant house prediction machine learning model. Methodologically, this study analyzes three types of machine learning model by differing the data components. First model is trained based on building register, individual declared land value, house price and socioeconomic data and second model is trained with the same data as first model but with additional POI(Point of Interest) data. Finally, third model is trained with same data as the second model but with excluding water usage and electricity usage data. As a result, second model shows the best performance based on F1-score. Random Forest, Gradient Boosting Machine, XGBoost and LightGBM which are tree ensemble series, show the best performance as a whole. Additionally, the complexity of the model can be reduced through eliminating independent variables that have correlation coefficient between the variables and vacant house status lower than the 0.1 based on absolute value. Finally, this study suggests XGBoost and LightGBM based machine learning model, which can handle missing values, as final vacant house prediction model.

• International Journal of Computer Science & Network Security
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• 제24권2호
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• pp.101-112
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• 2024

Telugu language is considered as fourth most used language in India especially in the regions of Andhra Pradesh, Telangana, Karnataka etc. In international recognized countries also, Telugu is widely growing spoken language. This language comprises of different dependent and independent vowels, consonants and digits. In this aspect, the enhancement of Telugu Handwritten Character Recognition (HCR) has not been propagated. HCR is a neural network technique of converting a documented image to edited text one which can be used for many other applications. This reduces time and effort without starting over from the beginning every time. In this work, a Unicode based Handwritten Character Recognition(U-HCR) is developed for translating the handwritten Telugu characters into English language. With the use of Centre of Gravity (CG) in our model we can easily divide a compound character into individual character with the help of Unicode values. For training this model, we have used both online and offline Telugu character datasets. To extract the features in the scanned image we used convolutional neural network along with Machine Learning classifiers like Random Forest and Support Vector Machine. Stochastic Gradient Descent (SGD), Root Mean Square Propagation (RMS-P) and Adaptative Moment Estimation (ADAM)optimizers are used in this work to enhance the performance of U-HCR and to reduce the loss function value. This loss value reduction can be possible with optimizers by using CNN. In both online and offline datasets, proposed model showed promising results by maintaining the accuracies with 90.28% for SGD, 96.97% for RMS-P and 93.57% for ADAM respectively.

• 한국의학물리학회지:의학물리
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• 제19권4호
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• pp.269-275
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• 2008

슬관절 퇴행성 질환을 진단하기 위하여 자기공명영상(magnetic resonance imaging: MRI)이 많이 사용되지만 간혹 슬관절 병후 및 예후를 잘못 진단하는 경우가 종종 발생한다. 본 연구에서는 슬관절 질환의 진단에 도움을 주기 위하여 자화전이(magnetization transfer: MT) 영상법을 소개하고자 한다. 슬관절 환자 7명으로부터 스핀 에코(SE) T2 강조 영상(3,400-3,500/90-100 ms)과 슬관절 환자 7명으로부터 FSE T2 강조 영상(4,500-5,000/100-108 ms)과 또한 슬관절 환자 3명으로부터 gradient echo (GRE) T2 강조 영상들(9/4.56 ms, 50 flip angle, NEX 1)을 획득하였다. 6명의 슬관절 환자에서 지방 억제가능 T2 강조 STIR 펄스시퀀스(TR/TE=2894-3215 ms/70 ms, NEX 3, ETL 9)를 사용하였다. 지방 포화도에 있어서 위상감도 방법은 Larmor frequency 차이에 따른 위상 차이를 이용하므로, 각각의 픽셀에 대한 자화전이율(magnetization transfer ratio: MTR)의 측정은 포화된 영상과 포화되지 않은 영상의 비율에 따라 산출하였다. 따라서 각 입력된 영상들은 동차원성을 가지고, 시각적으로 신호강도 정도가 회색의 명암도만으로 평가될 수 있기 때문에 생리학적, 정량적 진단을 위하여 3차원 등방성 체적영상과 자기공명 삼원색을 매핑하였고 정량적 특정은 자화전이율 지도로서 표현하였다. 자화전이율 영상은 병변 부위에서 높은 대조도를 나타내어 환자의 병태를 추적하는데 도움을 주었고 정량화하였다. 자화전이율 영상들과 기존의 MRI 사이에 명암도 차이는 회색상으로 표현되며, 자화전이율 영상화의 효과에 대해 프로파일 그래프는 자화전이 펄스로 인하여 신호강도에 있어서 정량적 측정값이 상대적으로 감소하였다. 슬관절의 정확한 병리상태를 진단하기 위해 프로파일 그래프의 측정값을 영상과 함께 표현하였다. 본 연구에서 수행한 예비적 데이터들을 통하여 슬관절의 자화전이율 영상들이 매우 임상학적으로 유용함을 확인하였다. 자화전이율 영상에 대한 물리적 변화를 관찰함으로써 자화전이율 영상에 대한 물리적, 기술적 기반에 대한 더 많은 통찰력을 제공할 수 있다. 무릎 질환 환자의 자화전이율 영상들을 이용하여 매우 높은 대조도를 확보할 수 있으므로 슬관절 질환의 정밀 진단에 매우 도움을 줄 수 있다.

• Asian-Australasian Journal of Animal Sciences
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• 제27권11호
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• pp.1562-1570
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• 2014

The effects of Lactobacillus mucosae (L. mucosae), a potential direct fed microbial previously isolated from the rumen of Korean native goat, on the rumen fermentation profile of brewers grain were evaluated. Fermentation was conducted in serum bottles each containing 1% dry matter (DM) of the test substrate and either no L. mucosae (control), 1% 24 h broth culture of L. mucosae (T1), or 1% inoculation with the cell-free culture supernatant (T2). Each serum bottle was filled anaerobically with 100 mL of buffered rumen fluid and sealed prior to incubation for 0, 6, 12, 24, and 48 h from which fermentation parameters were monitored and the microbial diversity was evaluated. The results revealed that T1 had higher total gas production (65.00 mL) than the control (61.33 mL) and T2 (62.00 mL) (p<0.05) at 48 h. Consequently, T1 had significantly lower pH values (p<0.05) than the other groups at 48 h. Ammonia nitrogen ($NH_3$-N), individual and total volatile fatty acids (VFA) concentration and acetate:propionate ratio were higher in T1 and T2 than the control, but T1 and T2 were comparable for these parameters. Total methane ($CH_4$) production and carbon dioxide ($CO_2$) were highest in T1. The percent DM and organic matter digestibilities were comparable between all groups at all times of incubation. The total bacterial population was significantly higher in T1 (p<0.05) at 24 h, but then decreased to levels comparable to the control and T2 at 48 h. The denaturing gradient gel electrophoresis profile of the total bacterial 16s rRNA showed higher similarity between T1 and T2 at 24 h and between the control and T1 at 48 h. Overall, these results suggest that addition of L. mucosae and cell-free supernatant during the in vitro fermentation of dried brewers grain increases the VFA production, but has no effect on digestibility. The addition of L. mucosae can also increase the total bacterial population, but has no significant effect on the total microbial diversity. However, inoculation of the bacterium may increase $CH_4$ and $CO_2$ in vitro.

• 천문학회지
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• 제50권3호
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• pp.79-92
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• 2017

We present a BV I optical photometric study of the old open cluster Ruprecht 6 using the data obtained with the SMARTS 1.0 m telescope at the CTIO, Chile. Its color-magnitude diagrams show the clear existence of the main-sequence stars, whose turn-off point is located around $V{\approx}18.45mag$ and $B-V{\approx}0.85mag$. Three red clump (RC) stars are identified at V = 16.00 mag, I = 14.41 mag and B - V = 1.35 mag. From the mean $K_s-band$ magnitude of RC stars ($K_s=12.39{\pm}0.21mag$) in Ruprecht 6 from 2MASS photometry and the known absolute magnitudes of the RC stars ($M_{K_S}=-1.595{\pm}0.025mag$), we obtain the distance modulus to Ruprecht 6 of $(m-M)_0=13.84{\pm}0.21mag$ ($d=5.86{\pm}0.60kpc$). From the ($J-K_s$) and (B - V ) colors of the RC stars, comparison of the (B - V ) and (V - I) colors of the bright stars in Ruprecht 6 with those of the intrinsic colors of dwarf and giant stars, and the PARSEC isochrone fittings, we derive the reddening values of E(B - V ) = 0.42 mag and E(V - I) = 0.60 mag. Using the PARSEC isochrone fittings onto the color-magnitude diagrams, we estimate the age and metallicity to be: $log(t)=9.50{\pm}0.10(t=3.16{\pm}0.82Gyr)$ and $[Fe/H]=-0.42{\pm}0.04dex$. We present the Galactocentric radial metallicity gradient analysis for old (age > 1 Gyr) open clusters of the Dias et al. catalog, which likely follow a single relation of $[Fe/H]=(-0.034{\pm}0.007)R_{GC}+(0.190{\pm}0.080)$ (rms = 0.201) for the whole radial range or a dual relation of $[Fe/H]=(-0.077{\pm}0.017)R_{GC}+(0.609{\pm}0.161)$ (rms = 0.152) and constant ([Fe/H] ~ -0.3 dex) value, inside and outside of RGC ~ 12 kpc, respectively. The metallicity and Galactocentric radius ($13.28{\pm}0.54kpc$) of Ruprecht 6 obtained in this study seem to be consistent with both of the relations.

• Journal of Biosystems Engineering
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• 제42권2호
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• pp.86-97
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• 2017

Purpose: This study aims to evaluate the applicability of a tractor-baler system equipped with a newly developed round baler by conducting stability analyses via static-state mathematical simulations and verification experiments for the tractor equipped with a loader. Methods: The centers of gravity of the tractor and baler were calculated to analyze the transverse overturning of the system. This overturning of the system was analyzed by applying mathematical equations presented in previous research and comparing the results with those obtained by the newly developed mathematical simulation. For the case of the tractor equipped with a loader, mathematical simulation results and experimental values from verification experiments were compared and verified. Results: The center of gravity of the system became lower after the baler was attached to the tractor and the angle of transverse overturning of the system steadily increased or decreased as the deflection angle increased or decreased between $0^{\circ}$ and $180^{\circ}$ on the same gradient. In the results of the simulations performed by applying mathematical equations from previous research, right transverse overturning occurred when the tilt angle was at least $19.5^{\circ}$ and the range of deflection angles was from $82^{\circ}$ to $262^{\circ}$ in counter clockwise. Additionally, left transverse overturning also occurred at tilt angles of at least $19.5^{\circ}$ and the range of deflection angles was from $259^{\circ}$ to $79^{\circ}$ in counter clockwise. Under the $0^{\circ}$ deflection angle condition, in simulations of the tractor equipped with a loader, transverse overturning occurred at $17.9^{\circ}$, which is a 2.3% change from the results of the verification experiment ($17.5^{\circ}$). The simulations applied the center of gravity and the correlations between the tilt angles, formed by individual wheel ground contact points excluding wheel radius and hinge point height, which cannot be easily measured, for the convenient use of mathematical equations. The results indicated that both left and right transverse overturning occurred at $19.5^{\circ}$. Conclusions: The transverse overturning stability evaluation of the system, conducted via mathematical equation modeling, was stable enough to replace the mathematical equations proposed by previous researchers. The verification experiments and their results indicated that the system is workable at $12^{\circ}$, which is the tolerance limit for agricultural machines on the sloped lands in South Korea, and $15^{\circ}$, which is the tolerance limit for agricultural machines on the sloped grasslands of hay in Japan.

• Journal of Animal Science and Technology
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• 제45권5호
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• pp.731-738
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• 2003

근육의 생화학적 특성을 단백질 수준에서 분석하기 위하여 3원교잡종 돼지 3개체를 선발하고, white muscle은 longissimus dorsi muscle을 red muscle은 soleus muslce을 분리하여 분석에 이용하였다. 각 근육조직은 수용성, 불수용성 단백질 및 총단백질로 분리하여 추출하였고, 이차원전기영동 분석을 위하여 17cm 길이의 immobilized pH gradient strip (Bio-Rad, 3-10NL)과 12% acrylamide gel을 이용하여 전개하였다. 각각의 gel은 coomassie stain과 silver stain을 통하여 가시화 하였고, PDQuest software을 통하여 단백질 발현양상을 분석하였다. 하나의 gel에서 평균 600개 이상의 단백질 spot을 관찰하였으며, 반복실험을 통하여 white muscle과 red muscle간에 발현의 차이를 보이는 5개의 단백질 spot을 확인할 수 있었다. 5개의 spot 중 4개의 단백질은 측정된 분자량과 pI값이 troponin I, T 및 myoglobin의 수치값과 유사한 것으로 확인되었다. 그러나, 1개의 spot은 오차범위 내에서 유사한 단백질을 확인할 수 없었다. 5개의 단백질 spot중 1개(spot 1)는 white muscle에서, 4개의 spot(spot 2～5)은 red muscle에서 높게 발현됨을 확인하였으며, 특히 spot 4의 경우 white muscle 보다 red muscle에서 평균 14.6배 높게 발현됨을 확인하였다. 본 연구는 근육의 생화학적 특성을 이해하는데 중요한 기초 자료로 활용될 수 있으며, 앞으로 white muscle과 red muscle의 단백질 발현 분석을 통하여 단백질 수준에서의 생화학적 특성에 관한 연구가 충분히 진행되어야 할 것이다.