This study was carried out to calculate working life expectancy and its potential gains according to the degree of reduction in the specific causes of death. It sought to ascertain what potential gains in labor force longevity might be reasonably achieved through efforts to reduce mortality from injuries and poisoning, diseases of circulatory system, neoplasms and the other causes of death. The data were drawn from the three sources such as "The 1982 Causes of Death Statistics," "Abridged Life Table for Korea 1978~'79" and "The 1982 annual Report of Economically Active Population" issued by Economic Planning Board. Analytical tools used in this study were the cause-deleted life table and the Wolfbein Wool's working life table method. Partial life expectancy was adopted as an index of this study, This application will be widely used as a good demographic tool for analyzing the dynamics of labor force and causes of death. Some of the findings are summerized as follows. 1. Partial life expectancies from initial age 15, 25, and 45 respectively to terminal age 65 are 44.86, 35.59 and 17.41 year in life expectancy itself, 37.08, 32.83 and 15.21 year in working life expectancy, 7.78, 2.76 and 2.20 years in inactive life years. 2. Potential gains in working expectancy from initial age 15, 25 and 45 to terminal age 65 by the complete elimination of the specific causes of death are 1.36, 0.94 and 0.27 years in injuries and poisoning, 0.88, 0.83 and 0.54 years in diseases of circulatory system, 0.56, 0.54 and 0.37 years in neoplasms, 1.13, 1.02 and 0.58 years in the other causes of death. The relationship between degree of reduction in causes of death and potential gains in working life years is in direct proportion. The prime orders of reduction effectiveness in age groups by the causes of death are injuries and poisoning in age 15-24, the other causes of death in age 25-49 and diseases of circulatory system in age 50 and over. 3. If it were possible to reduce 25%, 50% and 75% in mortality condition 1978~'79, the average length of working life would be 38.08, 39.13 and 40.17 years in age 15, and 33.68, 34.57 and 35.44 years in age 25, and 15.67, 16.14 and 16.63 years in age 45.
Park, Sunhwa;Kim, Hyun-Gu;Kim, Sohyun;Lee, Min-Kyeong;Lee, Gyeong-Mi;Kim, Young;Kim, Moon-Su;Kim, Taeseung
Journal of Soil and Groundwater Environment
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v.19
no.4
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pp.62-69
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2014
In the results of monitoring nitrate concentration in more than 8,000 groundwater wells around agro-livestock, the average and maximum nitrate concentration was 9.4 mg/L and 101.2 mg/L, respectively. Since about 31% of the monitoring wells was exceed the quality standard for drinking water, nitrate control such as remediation or source regulation is required to conserve safe-groundwater in South Korea. Typical nitrate-treatment technologies include ion exchange, reverse osmosis, and biological denitrification. Among the treatment methods, biological denitrification by indigenous microorganism has environmental and economic advantages for the complete elimination of nitrate because of lower operating costs compared to other methods. Major mechanism of the process is microbial reduction of nitrate to nitrite and nitrogen gas. Three functional genes (nosZ, nirK, nirS) that encode for the enzyme involved in the pathway. In this work, we tried to develop simple process to determine possibility of natural denitrification reaction by monitoring the functional gene. For the work, the functional genes in nitrate-contaminated groundwater were monitored by using PCR with specific target primers. In the result, functional genes (nosZ and nirK) encoding denitrification enzymes were detected in the groundwater samples. This method can help to determine the possibility of natural-nitrate degradation in target groundwater wells without multiplex experimental process. In addition, for field-remediation application we selected nitrate-contaminated site where 200~600 mg/L of nitrate is continuously detected. To determine the possibility of nitrate-degradation by stimulated-natural attenuation, groundwater was sampled in two different wells of the site and nitrate concentration of the samples was 300 mg/L and 616 mg/L, respectively. Fumarate for different C/N ratio was added into microcosm bottles containing the groundwater to examine denitrification rate depending on carbon concentration. In the result, once 1.5 times more than amount of fumarate stoichiometry required was added, the 616 mg/L of nitrate and 300 mg/L of nitrate were completely degraded in 8 days and 30 days. The nitrite, byproduct of denitrification process, was also completely degraded during the experimental period.
Background: Our previously prepared ceftiofur (CEF) hydrochloride oily suspension shows potential wide applications for controlling swine Streptococcus suis infections, while the irrational dose has not been formulated. Objectives: The rational dose regimens of CEF oily suspension against S. suis were systematically studied using a pharmacokinetic-pharmacodynamic model method. Methods: The healthy and infected pigs were intramuscularly administered CEF hydrochloride oily suspension at a single dose of 5 mg/kg, and then the plasma and pulmonary epithelial lining fluid (PELF) were collected at different times. The minimum inhibitory concentration (MIC), minimal bactericidal concentration, mutant prevention concentration (MPC), post-antibiotic effect (PAE), and time-killing curves were determined. Subsequently, the area under the curve by the MIC (AUC0-24h/MIC) values of desfuroylceftiofur (DFC) in the PELF was obtained by integrating in vivo pharmacokinetic data of the infected pigs and ex vivo pharmacodynamic data using the sigmoid Emax (Hill) equation. The dose was calculated based on the AUC0-24h/MIC values for bacteriostatic action, bactericidal action, and bacterial elimination. Results: The peak concentration, the area under the concentration-time curve, and the time to peak for PELF's DFC were 24.76 ± 0.92 ㎍/mL, 811.99 ± 54.70 ㎍·h/mL, and 8.00 h in healthy pigs, and 33.04 ± 0.99 ㎍/mL, 735.85 ± 26.20 ㎍·h/mL, and 8.00 h in infected pigs, respectively. The MIC of PELF's DFC against S. suis strain was 0.25 ㎍/mL. There was strong concentration-dependent activity as determined by MPC, PAE, and the time-killing curves. The AUC0-24h/MIC values of PELF's DFC for bacteriostatic activity, bactericidal activity, and virtual eradication of bacteria were 6.54 h, 9.69 h, and 11.49 h, respectively. Thus, a dosage regimen of 1.94 mg/kg every 72 h could be sufficient to reach bactericidal activity. Conclusions: A rational dosage regimen was recommended, and it could assist in increasing the treatment effectiveness of CEF hydrochloride oily suspension against S. Suis infections.
Journal of the Korea Organic Resources Recycling Association
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v.27
no.2
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pp.5-12
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2019
The study is carried out to survey the proper management and to propose an eco - friendly separation system through efficient screening and resource recovery of excavated materials containing waste from various excavating fields such as reconstruction of landfill sites for reuse, reclamation of unsanitary landfill and residential land development of waste dumping sites. The current status and screening process and analytical characteristics of the excavated materials containing waste were reviewed. Through the analysis of the samples such as separated combustibles, recyclable soils and residues collected from the on-site visits we were able to understand the characteristics of separated materials and excavated materials containing waste such as calorific value, elementary composition, TOC, foreign material content and LOI. It has been found that elimination of the moisture of excavations, removal of attached soil from the surfaces of the excavated combustibles and the quantitative supply method of the input devices are the main operating factors as essential factors for the optimal separation of excavated materials containing waste. For efficient management and recycling of excavated materials containing, it is necessary to set criteria of ash content in separated combustibles and criteria organic matter content in separated soils.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.36
no.6
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pp.507-514
/
2018
TSI (TPI-Slope Index) which is the combination of TPI (Topographic Position Index) and slope was newly proposed for landslide and applied to a landslide susceptibility model. To do this, we first compared the TPIs with various scale factors and found that TPI350 was the best fit for the study area. TPI350 was combined with slope to create TSI. TSI was evaluated using logistic regression. The evaluation showed that TSI can be used as a landslide factor. Then a logistic regression model was developed to assess the landslide susceptibility by adding other topographic factors, geological factors, and forestial factors. For this, landslide-related factors that can be extracted from DEM (Digital Elevation Model), soil map, and forest type map were collected. We checked these factors and excluded those that were highly correlated with other factors or not significant. After these processes, 8 factors of TSI, elevation, slope length, slope aspect, effective soil depth, tree age, tree density, and tree type were selected to be entered into the regression analysis as independent variables. Three models through three variable selection methods of forward selection, backward elimination, and enter method were built and evaluated. Selected variables in the three models were slightly different, but in common, effective soil depth, tree density, and TSI was most significant.
Lawal Alabe Wale;Kimleang Kea;Youngsun Han;Tea-Kyung Kim
Journal of Internet of Things and Convergence
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v.9
no.2
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pp.61-69
/
2023
In recent years, due to heightened environmental awareness, Electric Power Steering (EPS) has been increasingly adopted as the steering control unit in manufactured vehicles. This has had numerous benefits, such as improved steering power, elimination of hydraulic hose leaks and reduced fuel consumption. However, for EPS systems to respond to actions, sensors must be employed; this means that the consistency of the sensor's linear variation is integral to the stability of the steering response. To ensure quality control, a reliable method for detecting defects and assessing linearity is required to assess the sensitivity of the EPS sensor to changes in the internal design characters. This paper proposes a data-driven defect and linearity assessment monitoring system, which can be used to analyze EPS component defects and linearity based on vehicle speed interval division. The approach is validated experimentally using data collected from an EPS test jig and is further enhanced by the inclusion of a Graphical User Interface (GUI). Based on the design, the developed system effectively performs defect detection with an accuracy of 0.99 percent and obtains a linearity assessment score at varying vehicle speeds.
KSCE Journal of Civil and Environmental Engineering Research
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v.43
no.3
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pp.321-335
/
2023
Monitoring sediment loads in natural rivers is the key process in river engineering, but it is costly and dangerous. In practice, suspended loads are directly measured, and total loads, which is a summation of suspended loads and bed loads, are estimated. This study proposes a real-time sediment discharge monitoring system using the horizontal acoustic Doppler current profiler (H-ADCP) and support vector regression (SVR). The proposed system is comprised of the SVR model for suspended sediment concentration (SVR-SSC) and for total loads (SVR-QTL), respectively. SVR-SSC estimates SSC and SVR-QTL mimics the modified Einstein procedure. The grid search with K-fold cross validation (Grid-CV) and the recursive feature elimination (RFE) were employed to determine SVR's hyperparameters and input variables. The two SVR models showed reasonable cross-validation scores (R2) with 0.885 (SVR-SSC) and 0.860 (SVR-QTL). During the time-series sediment load monitoring period, we successfully detected various sediment transport phenomena in natural streams, such as hysteresis loops and sensitive sediment fluctuations. The newly proposed sediment monitoring system depends only on the gauged features by H-ADCP without additional assumptions in hydraulic variables (e.g., friction slope and suspended sediment size distribution). This method can be applied to any ADCP-installed discharge monitoring station economically and is expected to enhance temporal resolution in sediment monitoring.
In the rapidly evolving domain of e-commerce, our study presents a cohesive approach to enhance customer satisfaction prediction from online reviews, aligning methodological innovation with practical insights. We integrate the RFE-SHAP feature selection with LDA topic modeling to streamline predictive analytics in e-commerce. This integration facilitates the identification of key features-specifically, narrowing down from an initial set of 28 to an optimal subset of 14 features for the Random Forest algorithm. Our approach strategically mitigates the common issue of overfitting in models with an excess of features, leading to an improved accuracy rate of 84% in our Random Forest model. Central to our analysis is the understanding that certain aspects in review content, such as quality, fit, and durability, play a pivotal role in influencing customer satisfaction, especially in the clothing sector. We delve into explaining how each of these selected features impacts customer satisfaction, providing a comprehensive view of the elements most appreciated by customers. Our research makes significant contributions in two key areas. First, it enhances predictive modeling within the realm of e-commerce analytics by introducing a streamlined, feature-centric approach. This refinement in methodology not only bolsters the accuracy of customer satisfaction predictions but also sets a new standard for handling feature selection in predictive models. Second, the study provides actionable insights for e-commerce platforms, especially those in the clothing sector. By highlighting which aspects of customer reviews-like quality, fit, and durability-most influence satisfaction, we offer a strategic direction for businesses to tailor their products and services.
Sang Uk Kim;Ji Yeon Hong;Yong Woo Kim;In Ki Hong;Song Hua Xuan;Mid Eum Yun;Sung Ho Lee
Journal of the Society of Cosmetic Scientists of Korea
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v.50
no.1
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pp.1-10
/
2024
In this study, a quercetin benton gel (QUERPLEX) that stabilized quercetin was prepared using organo hectorite, and its efficacy was confirmed. In addition, a comparative study was conducted on the stability and effectiveness of applying this to sunscreen cosmetics. It was confirmed that QUERPLEX remained stable without showing crystal precipitation and growth for 4 weeks. As a result of measuring antioxidant activity using 2,2-diphenyl-1-picrylhydrazyl (DPPH), it showed antioxidant activity depending on the concentration, and showed a radical elimination ability of 70% or more at a concentration of 2,500 ppm or more, confirming a significant effect. Anti-inflammatory activity experiments using RAW 264.7 cells confirmed that NO production decreased in a concentration-dependent manner by reducing NO production by 8% at 25 ㎍/mL, 23% at 50 ㎍/mL, and 84% at 100 ㎍/mL. As a result of confirming the stability of the formulation according to the method of quercetin in the sunscreen formulation, the stability of the formulation was improved when quercetin was added directly to the formulation. It also improved the UV protection index on in vitro and in vivo, which is expected to have the potential as a component that can have a new boosting effect on UV protection. These results suggest that organo hectorite is very effective as a quercetin carrier and that it can be applied in cosmetic formulations by not only expressing the efficacy of quercetin but also bringing about additional effects.
In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.
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