• International Journal of Contents
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• 제17권4호
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• pp.79-90
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• 2021

With the deepening of population aging, pension has become an urgent problem in most countries. Community smart pension can effectively resolve the problem of traditional pension, as well as meet the personalized and multi-level needs of the elderly. To predict the pension intention of the elderly in the community more accurately, this paper uses the decision tree classification method to classify the pension data. After missing value processing, normalization, discretization and data specification, the discretized sample data set is obtained. Then, by comparing the information gain and information gain rate of sample data features, the feature ranking is determined, and the C4.5 decision tree model is established. The model performs well in accuracy, precision, recall, AUC and other indicators under the condition of 10-fold cross-validation, and the precision was 89.5%, which can provide the certain basis for government decision-making.

• 한국식품위생안전성학회지
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• 제37권5호
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• pp.297-305
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• 2022

산화방지제는 활성 산소에 의한 지질 산패를 방지하여 식품의 보존성을 증대하는 식품첨가물이다. 본 연구에서는 합성 산화방지제 5종 (Butylated hydroxyanisole (BHA), Butylated hydroxytoluene (BHT), Tertiary butylhydroquinone (TBHQ), Propyl gallate (PG), Disodium ethylenediaminetetraacetic acid(EDTA·2 Na))을 이용하여 HPLC-UVD 분석법에 대한 유효성 검증 및 합성 산화방지제가 표시된 실제 식품 속 함량 분석을 진행하였다. 직선성(R²)은 평균 0.9997, 검출한계(Limit of detection, LOD)와 정량한계(Limit of quantification, LOQ)는 각각 0.02-0.53과 0.07-1.61 mg/kg으로 산출하였다. 일내 및 일간 정확성과 정밀성 산출을 위하여 합성 산화방지제 4종은 콩기름과 과자, EDTA는 통조림과 마요네스를 이용하였다. 정확성과 정밀성 결과, 일내와 일간 각각 83.2±0.7-97.8±4.4와 86.2±3.3-98.3±2.1 및 0.1-6.4와 0.7-5.7 %RSD로 산출되었다. 또한 FAPAS QC material을 이용하여 실험실간 정확성 및 정밀성 검증을 진행하였으며 이는 AOAC가 제시한 가이드라인에 적합함을 확인하였다. 측정불확도 역시 CODEX에서 제시한 범위인 16% 이하인 것을 확인하였다. 따라서 본 연구를 통하여 국민 건강의 안전을 제고하기 위한 국내 산화방지제의 섭취량 및 위해성 평가를 위한 기초자료로 활용될 수 있을 것으로 사료된다.

• 분석과학
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• 제36권4호
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• pp.180-190
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• 2023

The presence of process related impurities in any drug or the drug product was associated with its safety, stability and efficacy. The overall literature survey proved that there is no method published on the assessment of process related impurities in brigatinib. In this study, a simple, reliable and stable HPLC qualitative method was reported for quantification of process related impurities with easy and quick extraction procedure. The impurities along with standard brigatinib was resolved on Lichrospher^® C18 (250 mm × 4.6 mm; 5 ㎛ particle size) column in room temperature using methanol, acetonitrile, pH 4.5 phosphate buffer in 55:25:20 (v/v) at 1.0 mL/min as mobile phase and UV detection at 261 nm. The method produces well resolved peaks at retention time of 4.60 min, 12.28 min, 3.37 min, 7.34 min and 8.39 min respectively for brigatinib, impurity A, B, C and D. The method produces a very sensitive detection limit of 0.0065 ㎍/mL, 0.0068 ㎍/mL, 0.0053 ㎍/mL and 0.0058 ㎍/mL for impurity A, B, C and D respectively with calibration curve linear in the concentration range of 22.5-135 ㎍/mL for brigatinib and 0.0225-0.135 ㎍/mL for impurities. The method produces all the validation parameters under the acceptable level and doesn't produces any considerable changes in peak area response while minor changes in the developed method conditions. The method can effectively resolve the unknown stress degradation products along with known impurities with less % degradation. The method can efficiently resolve and quantify the impurities in formulation and hence can suitable for the routine quality analysis of brigatinib in raw material and formulation.

• Toxicological Research
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• 제31권3호
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• pp.299-305
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• 2015

An HPLC analytical method was validated for the quantitative determination of biogenic amines in agricultural products. Four agricultural foods, including apple juice, Juk, corn oil and peanut butter, were selected as food matrices based on their water and fat contents (i.e., non-fatty liquid, non-fatty solid, fatty liquid and fatty solid, respectively). The precision, accuracy, recovery, limit of detection (LOD) and quantification (LOQ) were determined to test the validity of an HPLC procedure for the determination of biogenic amines, including tryptamine, ${\beta}$-phenylethylamine, putrescine, cadaverine, histamine, tyramine, spermidine and spermine, in each matrix. The LODs and LOQs for the biogenic amines were within the range of 0.01~0.10 mg/kg and 0.02~0.31 mg/kg, respectively. The relative standard deviation (RSD) of intraday for biogenic amine concentrations ranged from 1.86 to 5.95%, whereas the RSD of interday ranged from 2.08 to 5.96%. Of the matrices spiked with biogenic amines, corn oil with tyramine and Juk with putrescine exhibited the least accuracy of 84.85% and recovery rate of 89.63%, respectively, at the lowest concentration (10 mg/kg). Therefore, the validation results fulfilled AOAC criteria and recommendations. Subsequently, the method was applied to the analysis of biogenic amines in fermented agricultural products for a total dietary survey in Korea. Although the results revealed that Korean traditional soy sauce and Doenjang contained relatively high levels of histamine, the amounts are of no concern if these fermented agricultural products serve as condiments.

• Structural Engineering and Mechanics
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• 제47권5호
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• pp.679-700
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• 2013

Two new predictive design methods are presented in this study. The first is a hybrid method, called neuro-fuzzy, based on neural networks with fuzzy learning. A total of 280 experimental datasets obtained from the literature concerning concentric punching shear tests of reinforced concrete slab-column connections without shear reinforcement were used to test the model (194 for experimentation and 86 for validation) and were endorsed by statistical validation criteria. The punching shear strength predicted by the neuro-fuzzy model was compared with those predicted by current models of punching shear, widely used in the design practice, such as ACI 318-08, SIA262 and CBA93. The neuro-fuzzy model showed high predictive accuracy of resistance to punching according to all of the relevant codes. A second, more user-friendly design method is presented based on a predictive linear regression model that supports all the geometric and material parameters involved in predicting punching shear. Despite its simplicity, this formulation showed accuracy equivalent to that of the neuro-fuzzy model.

• 한국지구과학회지
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• 제31권5호
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• pp.454-464
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• 2010

A probability prediction model for tropical cyclone (TC) genesis in the Northwestern Pacific area was developed using the logistic regression method. Total five predictors were used in this model: the lower-level relative vorticity, vertical wind shear, mid-level relative humidity, upper-level equivalent potential temperature, and sea surface temperature (SST). The values for four predictors except for SST were obtained from difference of spatial-averaged value between May and January, and the time average of Ni$\tilde{n}$o-3.4 index from February to April was used to see the SST effect. As a result of prediction for the TC genesis frequency from June to December during 1951 to 2007, the model was capable of predicting that 21 (22) years had higher (lower) frequency than the normal year. The analysis of real data indicated that the number of year with the higher (lower) frequency of TC genesis was 28 (29). The overall predictability was about 75%, and the model reliability was also verified statistically through the cross validation analysis method.

• 대한의용생체공학회:의공학회지
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• 제43권5호
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• pp.299-307
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• 2022

In this paper, we propose a pre-processing method that converts to Spider Chart image data for classification of gripping movement using EMG (electromyography) sensors and Convolution Neural Networks (CNN) deep learning. First, raw data for six hand gestures are extracted from five test subjects using an 8-channel armband and converted into Spider Chart data of octagonal shapes, which are divided into several sliding windows and are learned. In classifying six hand gestures, the classification performance is compared with the proposed pre-processing method and the existing methods. Deep learning was performed on the dataset by dividing 70% of the total into training, 15% as testing, and 15% as validation. For system performance evaluation, five cross-validations were applied by dividing 80% of the entire dataset by training and 20% by testing. The proposed method generates 97% and 94.54% in cross-validation and general tests, respectively, using the Spider Chart preprocessing, which was better results than the conventional methods.

• 한국진공학회지
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• 제5권2호
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• pp.99-106
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• 1996

Two types of regularization method (singular system and HMP approaches) for generating depth-concentration profiles from angle-resolved XPS data were evaluated. Both approaches showed qualitatively similar results although they employed different numerical algorithms. The application of the regularization method to simulated data demonhstrates its excellent utility for the complex depth profile system . It includes the stable restoration of depth-concentration profiles from the data with considerable random error and the self choice of smoothing parameter that is imperative for the successful application of the regularization method. The self choice of smoothing parameter is based on generalized cross-validation method which lets the data themselves choose the optimal value of the parameter.

• Structural Engineering and Mechanics
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• 제48권5호
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• pp.661-679
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• 2013

In this work, the safety performance of a commercial motorcycle helmet already placed on the market is assessed. The assessed motorcycle helmet is currently homologated by several relevant motorcycle standards. Impacts including translational and rotational motions are accurately simulated through a finite element numerical framework. The developed model was validated against experimental results: firstly, a validation concerning the constitutive model for the expanded polystyrene, the material responsible for energy absorption during impact; secondly, a validation regarding the acceleration measured at the headform's centre of gravity during the linear impacts defined in the ECE R22.05 standard. Both were successfully validated. After model validation, an oblique impact was simulated and the results were compared against head injury thresholds in order to predict the resultant head injuries. From this comparison, it was concluded that brain injuries such as concussion and diffuse axonal injury may occur even with a helmet certified by the majority of the motorcycle helmet standards. Unfortunately, these standards currently do not contemplate rotational components of acceleration. Conclusion points out to a strong recommendation on the necessity of including rotational motion in forthcoming motorcycle helmet standards and improving the current test procedures and head injury criteria used by the standards, to improve the safety between the motorcyclists.

• 약학회지
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• 제49권1호
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• pp.1-5
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• 2005

Near-infrared (NIR) spectroscopy has been widely applied in various field, since it is nondestructive and no sample preparation is required. In this paper, NIR spectroscopy was used for the determination of naproxen in a commercial pharmaceutical preparation. NIR spectroscopy was used to determine the content of naproxen in intact naproxen tablets containing 250 mg ($65.8\%$ nominal concentration) by collecting NIR spectra in the range of $1100{\sim}1750nm$. The laboratory-made samples had $46.1{\sim}85.5\%$ nominal naproxen concentration. The measurements were made by reflection using a fiber-optic probe and calibration was carried out by partial least square regression (PLSR). Model validation was performed by randomly splitting the data set into calibration and validation data set (63 samples as a calibration data set and 42 samples as a validation data set). The developed NIR calibration gave results comparable to the known values of tablets in a laboratorial manufacturing process with standard error of calibration (SEC) and standard error of prediction (SEP) of $1.06\%\;and\;1.04\%$, respectively. The NIR method showed good accuracy and repeatability. NIR spectroscopic determination in intact tablets allowed the potential use of real time monitoring for a running production process.