• Korean Journal of Mathematics
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• v.27 no.3
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• pp.613-627
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• 2019

Consider a connected molecular graph G = (V, E) where V is the set of vertices and E is the set of edges. In G, vertices represent the atoms and edges represent the covalent bonds between atoms. In graph G, every edge (say) e = uv will be connected by two atoms u and v. The edge Szeged index is a topological index which has been introduced by Ivan Gutman. In this paper, we have computed edge Szeged indices of a hydrocarbon family called Benzene ring and is denoted by $(BR)_{n{\times}n}$.

• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.145-159
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• 2021

Purpose: A statistical similarity evaluation to compare pharmacokinetics(PK) profile data between nonclinical and clinical experiments has become a significant issue on many drug development processes. This study proposes a new similarity index by considering important parameters, such as the area under the curve(AUC) and the time-series profile of various PK data. Methods: In this study, a new profile similarity index(PSI) by using the concept of a process capability index(Cp) is proposed in order to investigate the most similar animal PK profile compared to the target(i.e., Human PK profile). The proposed PSI can be calculated geometric and arithmetic means of all short term similarity indices at all time points on time-series both animal and human PK data. Designed simulation approaches are demonstrated for a verification purpose. Results: Two different simulation studies are conducted by considering three variances(i.e., small, medium, and large variances) as well as three different characteristic types(smaller the better, larger the better, nominal the best). By using the proposed PSI, the most similar animal PK profile compare to the target human PK profile can be obtained in the simulation studies. In addition, a case study represents differentiated results compare to existing simple statistical analysis methods(i.e., root mean squared error and quality loss). Conclusion: The proposed PSI can effectively estimate the level of similarity between animal, human PK profiles. By using these PSI results, we can reduce the number of animal experiments because we only focus on the significant animal representing a high PSI value.

• Management & Information Systems Review
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• v.37 no.4
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• pp.63-74
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• 2018

Recently, in the asset management industry, the smart beta strategy, which has an intermediate nature between passive and active strategies, is attracting attention. In this smart beta strategy, value, momentum, low volatility, and quality index are widely used. In this study, we analyzed the quality index which is not clear and complicated to calculate. According to the MSCI methodology, the quality index was calculated using three variables: return on equity, debt to equity, and earnings variability. In addition, we use the index using only return on equity variable, the index using only two variables of return on equity and debt to equity, and the KOSPI index as comparison targets for the quality index. In order to evaluate the performance of the indices used in the analysis, the arithmetic mean return, the coefficient of variation, and the geometric mean return were used. In addition, Fama and French (1993) model, which is widely used in related studies, was used as a pricing model to test whether abnormal returns in each index are occurring. The results of the empirical analysis are as follows. First, in all period analysis, quality index was the best in terms of holding period returns. Second, the quality index performed best in the currency crisis and the global financial crisis. Third, abnormal returns were not found in all indices before the global financial crisis. Fourth, in the period after the global financial crisis, the quality index has the highest abnormal return.

• Journal of Environmental Health Sciences
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• v.36 no.3
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• pp.215-221
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• 2010

The purpose of this study was to investigate the relevance of gender, age, and BMI (Body Mass Index) to changes in the urinary creatinine concentration in Korean adults. We recruited and surveyed 2,156 persons $\geq$20 years of age from 98 districts across the country, and collected urine samples for analyzing the creatinine concentration. Participants were 41.6% men and 58.4% women. In terms of age, the percentage of the population in their 20's and $\geq$60 years of age was relatively similar, with 13.6% and 17.8%, respectively, while the percentages in their 30's, 40's and 50's were also relatively similar, with 22.0%, 24.0%, and 22.6%, respectively. The proportion of participants in their 20's and 30's who were underweight (according to the BMI) was 25% and 19.2%, respectively, but only 6.2~6.4% of those $\geq$40 years of age were underweight. This showed that the underweight proportion in elder generations was less than that in younger generations. Meanwhile, the proportion who were overweight was 13.7%, 18.8%, 28.6%, 27.9%, 32.0% when the participants were in their 20's, 30's, 40's, 50's and $\geq$60 years of age, respectively (p<0.000). This showed that the overweight proportion increased along with increasing age. The overall urinary creatinine concentration was 10 mg/dl (arithmetic mean: AM), and 92.2 mg/dl (geometric mean: GM). The urinary creatinine concentration in men (132.6 mg/dl, AM) was significantly higher than that in women (93.3 mg/dl, AM (p<0.000)). Showing a similar trend in men and women, urinary creatinine concentrations were highest when the participants were in their 20's (135.6 mg/dl, AM), and tended to decrease with increasing age. Urinary creatinine concentrations in overweight and obese subjects (AM of 117.9 mg/dl and 118.0 mg/dl, respectively) were significantly higher than in other groups, and this trend was similar in men and women. In conclusion, we found that urinary concentrations were significantly affected by gender, age, and BMI, and that care should therefore be exercised when correcting urinary metabolites according to the urinary creatinine concentration.

• Safety and Health at Work
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• v.13 no.4
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• pp.493-499
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• 2022

Background: The purpose of this study is to construct a job-exposure matrix for lead that accounts for industry and work processes within industries using a nationwide exposure database. Methods: We used the work environment measurement data (WEMD) of lead monitored nationwide from 2015 to 2016. Industrial hygienists standardized the work process codes in the database to 37 standard process and extracted key index words for each process. A total of 37 standardized process codes were allocated to each measurement based on an automated key word search based on the degree of agreement between the measurement information and the standard process index. Summary statistics, including the arithmetic mean, geometric mean, and 95th percentile level (X95), was calculated according to industry, process, and industry process. Using statistical parameters of contrast and precision, we compared the similarity of exposure groups by industry, process, and industry process. Results: The exposure intensity of lead was estimated for 583 exposure groups combined with 128 industry and 35 process. The X95 value of the "casting" process of the "manufacture of basic precious and non-ferrous metals" industry was 53.29 ㎍/m³, exceeding the occupational exposure limit of 50 ㎍/m³. Regardless of the limitation of the minimum number of samples in the exposure group, higher contrast was observed when the exposure groups were by industry process than by industry or process. Conclusion: We evaluated the exposure intensities of lead by combination of industry and process. The results will be helpful in determining more accurate information regarding exposure in lead-related epidemiological studies.