• Journal of Environmental Health Sciences
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• v.43 no.3
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• pp.223-232
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• 2017

Objectives: In response to increased interest in the safety of children's products, a risk management system is being prepared through exposure assessment of hazardous chemicals. To estimate exposure levels, risk assessors are using deterministic and probabilistic approaches to statistical methodology and a commercialized Monte Carlo simulation based on tools (MCTool) to efficiently support calculation of the probability density functions. This study was conducted to analyze and discuss the usage patterns and problems associated with the results of these two approaches and MCTools used in the case of probabilistic approaches by reviewing research reports related to exposure assessment for children's products. Methods: We collected six research reports on exposure and risk assessment of children's products and summarized the deterministic results and corresponding underlying distributions for exposure dose and concentration results estimated through deterministic and probabilistic approaches. We focused on mechanisms and differences in the MCTools used for decision making with probabilistic distributions to validate the simulation adequacy in detail. Results: The estimation results of exposure dose and concentration from the deterministic approaches were 0.19-3.98 times higher than the results from the probabilistic approach. For the probabilistic approach, the use of lognormal, Student's T, and Weibull distributions had the highest frequency as underlying distributions of the input parameters. However, we could not examine the reasons for the selection of each distribution because of the absence of test-statistics. In addition, there were some cases estimating the discrete probability distribution model as the underlying distribution for continuous variables, such as weight. To find the cause of abnormal simulations, we applied two MCTools used for all reports and described the improper usage routes of MCTools. Conclusions: For transparent and realistic exposure assessment, it is necessary to 1) establish standardized guidelines for the proper use of the two statistical approaches, including notes by MCTool and 2) consider the development of a new software tool with proper configurations and features specialized for risk assessment. Such guidelines and software will make exposure assessment more user-friendly, consistent, and rapid in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.601-611
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• 2016

The research, development and use of seismic isolation systems have been increasing with the gradual development of structure safety assurance methods for earthquakes. The High Damping Rubber Bearing (HDRB), one type of seismic isolation system, is a Laminated Rubber Bearing using special High Damping Rubber. However, as its damping function is slightly lower than that of the Lead Rubber Bearing, a similar seismic isolation system, its utilization has not been high. However, the HDRB has a superior damping force to the Natural Rubber Bearing, which has similar materials and shapes, and the existing Lead Rubber Bearing has a maleficence problem in that it contains lead. Thus, studies on HDRBs that do not use lead have increased. In this study, a test targeting the HDRB was done to examine its various dependence properties, such as its compressive stress, frequency and repeated loading. To evaluate the HDRB's seismic performance in response to several earthquake waves, the shaking table test was performed and the results analyzed. The test used the downscaled bridge model and the HDRB was divided into seismic and non-seismic isolation. Consequently, when the HDRB was applied, the damping effect was higher in the non-seismic case. However, its responses on weak foundations, such as in Mexico City, represented increased shapes. Thus, its seismic isolator.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.545-553
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• 2021

The frequency by water disaster in urban areas are increasing continuously due to climate change and urbanization. Countermeasures are being conducted to reduce the damage caused by water disasters. An analysis based on permeability, one of the parameters that affect runoff, is needed to predict quantitative runoff in urban watersheds and study runoff reduction. In this study, the SWAT model was simulated for the oncheon stream basin, a representative urban stream in Busan. The permeability map was prepared by calculating the CN values for each hydrologic response unit. Based on the permeability map prepared, EPA SWMM analyzed the effect of LID technology application on the water cycle in the basin for short-term rainfall events. The LID element technology applied to the oncheon stream basin was rooftop greening in the residential complex, and waterproof packaging was installed on the road. The land cover status of the land selected based on the permeability map and the application of LID technology reduced the outflow rate, peak flow rate, and outflow rate and increased the infiltration. Hence, LID technology has a positive effect on the water cycle in an urban basin.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.777-783
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• 2021

Aircraft are affected by various vibrations during maneuvering. These vibrations may have a fatal effect on the survival of aircraft in some cases, so the safety of components applied to the aircraft should be proven against various vibrations through random vibration analysis. In this study, the structural robustness of an external fuel tank and pylon for military aircraft was evaluated under random vibration conditions using commercial software, MSC Random. In the random vibration analysis, a frequency response analysis was performed by imposing a unit load on the boundary condition point, and then excitation was performed with a PSD profile. In this process, the required mode data was extracted through a modal analysis method. In addition, the random vibration profile specified in the US Defense Environment Standard was applied as random vibration conditions, and the PSD profile given in units of G's was converted into units of gravitational acceleration. As a result of the numerical analysis, we evaluated the structural robustness of the external fuel tank and pylon by identifying the safety margins of beam elements, shell elements, and solid elements in a numerical model for random vibration in the x, y, and z directions.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.159-165
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• 2023

While the frequency of seismic occurrence has been increasing recently, the domestic seismic response system is weak, the objective of this research is to compare and analyze the seismic vulnerability of buildings using statistical analysis and machine learning techniques. As the result of using statistical technique, the prediction accuracy of the developed model through the optimal scaling method showed about 87%. As the result of using machine learning technique, because the accuracy of Random Forest method is 94% in case of Train Set, 76.7% in case of Test Set, which is the highest accuracy among the 4 analyzed methods, Random Forest method was finally chosen. Therefore, Random Forest method was derived as the final machine learning technique. Accordingly, the statistical analysis technique showed higher accuracy of about 87%, whereas the machine learning technique showed the accuracy of about 76.7%. As the final result, among the 22,296 analyzed building data, the seismic vulnerabilities of 1,627(0.1%) buildings are expected as more dangerous when the statistical analysis technique is used, 10,146(49%) buildings showed the same rate, and the remaining 10,523(50%) buildings are expected as more dangerous when the machine learning technique is used. As the comparison of the results of using advanced machine learning techniques in addition to the existing statistical analysis techniques, in spatial analysis decisions, it is hoped that this research results help to prepare more reliable seismic countermeasures.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.843-856
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• 2023

The global surge in maritime traffic has resulted in an increased number of ship collisions, leading to significant economic, environmental, physical, and human damage. The causes of these maritime accidents are multifaceted, often arising from a combination of crew judgment errors, negligence, complexity of navigation routes, weather conditions, and technical deficiencies in the vessels. Given the intricate nuances and contextual information inherent in each incident, a methodology capable of deeply understanding the semantics and context of sentences is imperative. Accordingly, this study utilized the SentenceBERT model to analyze maritime safety tribunal decisions over the last 20 years in the Busan Sea area, which encapsulated data on ship collision incidents. The analysis revealed important keywords potentially responsible for these incidents. Cluster analysis based on the frequency of specific keyword appearances was conducted and visualized. This information can serve as foundational data for the preemptive identification of accident causes and the development of strategies for collision prevention and response.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.735-747
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• 2023

In recent times, the sharp increase in extreme flood damages due to climate change has posed a challenge to effectively address flood-related issues solely relying on conventional flood management infrastructure. In response to this problem, this study aims to consider the effectiveness of nature-based flood management approaches, specifically levee retreat and relocation. To achieve this, we utilized a 1D numerical model, HEC-RAS, to analyze the flood reduction effects concerning floodwater levels, flow velocities, and time-dependent responses to a 100-year frequency flood event. The analysis results revealed that the effect of creating a flood buffer zone of the nature-based solution extends from upstream to downstream, reducing flood water levels by up to 30 cm. The selection of the flow roughness coefficient in consideration of the nature-based flood buffer space creation characteristics should be based on precise criteria and scientific evidence because it is sensitive to the flood control effect analysis results. Notably, floodwater levels increased in some expanded floodplain sections, and the reduction in flow velocities varied depending on the ratio of the expanded cross-sectional area. In conclusion, levee retreat and floodplain expansion are viable nature-based alternatives for effective flood management. However, a comprehensive design approach is essential considering flood control effects, flow velocity reduction, and the timing of peak water levels. This study offers insights into addressing the challenges of climate-induced extreme flooding and advancing flood management strategies.

• Clinical and Experimental Pediatrics
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• v.53 no.2
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• pp.215-221
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• 2010

Purpose : Interleukin-17 (IL-17) is produced by activated CD4+T cells and exhibits pleiotropic biological activity on various cell types. IL-17 was reported to be involved in the immunoregulatory response in IgA nephropathy (IgAN). Our aim was to investigate the association between single-nucleotide polymorphisms (SNPs) in IL-17 receptor A (IL-17RA) gene and childhood IgAN. Methods : We analyzed the SNPs in the IL-17RA in 156 children with biopsy-proven IgAN and 245 healthy controls. We divided the IgAN patients into 2 groups and compared them with respect to proteinuria (${\leq}4$ and >$4mg/m^2/h$, ${\leq}40$ and >$40mg/m^2/h$, respectively) and the presence of pathological levels of biomarkers of diseases such as interstitial fibrosis, tubular atrophy, or global sclerosis. Results : No difference was observed between the SNP genotypes rs2895332, rs1468488, and rs4819553 between IgAN patients and control subjects. In addition, no significant difference was observed between allele frequency of SNPs rs2895 332, rs1468488, and rs4819553 between patients in the early and advanced stage of the disease. However, significant difference was observed between the genotype of SNP rs2895332 between patients with proteinuria (>$4mg/m^2/h$) and those without proteinuria (codominant model OR 0.36, 95% CI 0.19-.66, P <0.001; dominant model OR 0.35, 95% CI 0.17-.69 P =0.002; recessive model OR 0.12, 95% CI 0.01-.06 P =0.025). Conclusion : Our results indicate that the SNP in IL-17RA (rs2895332) may be related to the development of proteinuria in IgAN patients.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of Biomedical Engineering Research
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• v.19 no.1
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• pp.59-68
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• 1998

Digital hearing aids offer many advantages over conventional analog hearing aids. With the advent of high speed digital signal processing chips, new digital techniques have been introduced to digital hearing aids. In addition, the evaluation of new ideas in hearing aids is necessarily accompanied by intensive subject-based clinical tests which requires much time and cost. In this paper, we present an objective method to evaluate and predict the performance of hearing aid systems without the help of such subject-based tests. In the hearing impairment simulation(HIS) algorithm, a sensorineural hearing impairment medel is established from auditory test data of the impaired subject being simulated. Also, the nonlinear behavior of the loudness recruitment is defined using hearing loss functions generated from the measurements. To transform the natural input sound into the impaired one, a frequency sampling filter is designed. The filter is continuously refreshed with the level-dependent frequency response function provided by the impairment model. To assess the performance, the HIS algorithm was implemented in real-time using a floating-point DSP. Signals processed with the real-time system were presented to normal subjects and their auditory data modified by the system was measured. The sensorineural hearing impairment was simulated and tested. The threshold of hearing and the speech discrimination tests exhibited the efficiency of the system in its use for the hearing impairment simulation. Using the HIS system we evaluated three typical hearing aid algorithms.