• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.23-30
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• 2020

In this study, the relationship between natural gas (NG) data and gas-related environmental elements was performed using machine learning algorithms to predict the level of gas leakage risk without directly measuring gas leakage data. The study was based on open data provided by the server using the IoT-based remote control Picarro gas sensor specification. The naturel gas leaks into the air, it is a big problem for air pollution, environment and the health. The proposed method is multivariate outlier removing method based Random Forest (RF) classification for predicting risk of NG leak. After, unsupervised k-means clustering, the experimental dataset has done imbalanced data. Therefore, we focusing our proposed models can predict medium and high risk so best. In this case, we compared the receiver operating characteristic (ROC) curve, accuracy, area under the ROC curve (AUC), and mean standard error (MSE) for each classification model. As a result of our experiments, the evaluation measurements include accuracy, area under the ROC curve (AUC), and MSE; 99.71%, 99.57%, and 0.0016 for MOL_RF respectively.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.119-128
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• 2020

An ultrasonic multiple scattering simulation using cross-section of fine dust particles were proposed. These days, along with awareness of air pollution, social interest in fine dust is increasing. In the construction field, awareness of fine dust is increasing, and research on preparing various countermeasures is underway. The light scattering method fine dust meter currently in use is affected by environmental factors such as relative humidity, and reliability problems in terms of accuracy are continuously reported. However, the transmission of ultrasonic waves can directly reflect the physical change of the medium based on the mechanical wave. Using these advantages of ultrasonic waves, fine dust measurement simulation was performed using the scattering cross section and ultrasonic multiple scattering theory. The shape data of the fine dust particles were collected using a SEM (Scanning Electron Microscope), and a cross-section according to the fine dust particles was derived through numerical analysis. As a result of signal processing, the error for the number density corresponding to each cross-section is minimum 19, maximum 3455.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.3
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• pp.155-164
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• 2023

About 75% of vessel collision accidents are caused by human error, which causes enormous economic loss, environmental pollution, and human casualties, thus research on automatic collision avoidance of vessels is being actively conducted. In addition, vessels must comply with the COLREGs rules stipulated by IMO when performing collision avoidance with other vessels in motion. In this study, the collision risk was calculated by estimating the position and velocity of other vessels through the Probabilistic Data Association Filter (PDAF) algorithm based on RADAR sensor data. When a collision risk is detected, we propose an event-triggered Nonlinear Model Predict Control (NMPC) algorithm that geometrically creates waypoints that satisfy COLREGs and follows them. To verify the proposed algorithm, simulations through MATLAB are performed.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2572-2577
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• 2023

A field determination method for small D-T neutron source yield based on the oxygen prompt gamma rays was established. A neutron-gamma transport equation of the determination device was developed. Two yield field determination devices with a thickness of 20 mm and 50 mm were made. The count rates of the oxygen prompt gamma rays were calculated using three energy spectra processing approaches, which were the characteristic peak of 6.13 MeV, the overlapping peak of 6.92 MeV and 7.12 MeV, and the total energy area. The R-square of the calibration curve is better than 94% and the maximum error of the yield test is 5.21%, demonstrating that it is feasible to measure the yield of D-T neutron source by oxygen prompt gamma rays. Additionally, the results meet the requirements for field determination of the conventional D-T neutron source yield.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.507-514
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• 2024

In the semiconductor manufacturing line, continuous efforts are being made to reduce the cost of products produced, and the demand for this is accelerating in the chemical mechanical polishing(CMP) process, and a representative example of these cost reduction items is the 5-Zone Ring. After about 150 hours of use in the CMP process, the thickness of the ring decreases to less than 1 mm and must be replaced with a new product. Therefore, in this study, bonding dispensers and press machines with a dispensing amount error of 10g±0.8% or less and a pressure uniformity of ±1.8% or less were developed to reduce semiconductor manufacturing costs by repeatedly regenerating worn parts of the retainer ring, and to minimize environmental pollution caused by industrial waste treatment.

• Analytical Science and Technology
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• v.14 no.2
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• pp.131-139
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• 2001

There is personal difference in the concentrations of trace elements in human hair according to human life or history suck as occupation, race, sex, age, food habit, social condition and so on. It is also found that the individual's deviation of elemental concentrations is reflecting the degree of environmental pollutants exposure to human body, intakes of food and metabolism. To compare the degree of accumulation in the hair tissue, human hair samples were collected from five positions of head and analyzed by non-destructive neutron activation analysis with and without washing according to IAEA's recommended method. Analytical quality control is performed using the certified reference material. The relative error of Cu, Cr, Na, Co, Mg, As, Se, Zn and those of Mn, Ca, Fe, Sr are within ${\pm}5%$ and ${\pm}10%$, respectively and the relative standard deviation of elements are within ${\pm}10%$. The deviations between the individuals and hair sampling positions were estimated. The deviation of individual was seven times more than that of positions. Under the defined condition, the difference and the correlation of elemental concentrations were compared with two different groups, office and factory workers. The result can be used as a fundamental data for human health and environment assessment.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.461-474
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• 2020

Korea launched Geostationary Environmental Monitoring Satellite (GEMS), a UV/visible spectrometer that measure pollution gases on 18 February 2020. Because satellite retrieval is an ill-posed inverse solving process, the validation with ground-based measurements or other satellite measurements is essential to obtain reliable products. For this purpose, satellite-based OMI and OMPS total column ozone (TCO), and ground-based Pandora TCO in Busan and Seoul were selected for future GEMS validation. First of all, the goal of this study is to validate the ground ozone data using characteristics that satellite data provide coherent ozone measurements on a global basis, although satellite data have a larger error than the ground-based measurements. In the cross validation between Pandora and OMI TCO, we have found abnormal deviation in ozone time series from Pandora #29 observed in Seoul. This shows that it is possible to perform inverse validation of ground data using satellite data. Then OMPS TCO was compared with verified Pandora TCO. Both data shows a correlation coefficient of 0.97, an RMSE of less than 2 DU and the OMPS-Pandora relative mean difference of >4%. The result also shows the OMPS-Pandora relative mean difference with SZA, TCO, cross-track position and season have insignificant dependence on those variables.In addition, we showed that appropriate thresholds depending on the spatial resolution of each satellite sensor are required to eliminate the impact of the cloud on Pandora TCO.

• Environmental Analysis Health and Toxicology
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• v.29
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• pp.12.1-12.8
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• 2014

Objectives Cohort studies of associations between air pollution and health have used exposure prediction approaches to estimate individual-level concentrations. A common prediction method used in Korean cohort studies is ordinary kriging. In this study, performance of ordinary kriging models for long-term particulate matter less than or equal to $10{\mu}m$ in diameter ($PM_{10}$) concentrations in seven major Korean cities was investigated with a focus on spatial prediction ability. Methods We obtained hourly $PM_{10}$ data for 2010 at 226 urban-ambient monitoring sites in South Korea and computed annual average $PM_{10}$ concentrations at each site. Given the annual averages, we developed ordinary kriging prediction models for each of the seven major cities and for the entire country by using an exponential covariance reference model and a maximum likelihood estimation method. For model evaluation, cross-validation was performed and mean square error and R-squared ($R^2$) statistics were computed. Results Mean annual average $PM_{10}$ concentrations in the seven major cities ranged between 45.5 and $66.0{\mu}g/m^3$ (standard deviation=2.40 and $9.51{\mu}g/m^3$, respectively). Cross-validated $R^2$ values in Seoul and Busan were 0.31 and 0.23, respectively, whereas the other five cities had $R^2$ values of zero. The national model produced a higher cross-validated $R^2$ (0.36) than those for the city-specific models. Conclusions In general, the ordinary kriging models performed poorly for the seven major cities and the entire country of South Korea, but the model performance was better in the national model. To improve model performance, future studies should examine different prediction approaches that incorporate $PM_{10}$ source characteristics.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.231-242
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• 2016

As of late, air quality information has been actively gathered and investigated in order to find possible environmental risk factors that may affect the onset of cardiovascular disease. Nevertheless, existing studies are limited in the detailed analysis because they take advantage of the air quality information of the macro statistics divided into administrative districts. This paper proposes the construction of distance-based air quality dataset using a domestic hospital’s geographical location information as a reliable data gathering step for a more detailed analysis of environmental risk factors. For the construction of the dataset, air quality information was obtained by utilizing the geographical location of a hospital—in which a patient with cardiovascular disease had been admitted—and then matching the hospital with a meteorological and air pollution station in its vicinity. An air quality acquisition system based on GMap.net was devised for the purpose of data gathering and visualization. The reliability of the experiment was confirmed by evaluating the matching rate and error of air quality values between the acquired dataset with existing area-based air quality datasets from matched distances. Therefore, this dataset, which considers geographical information, can be utilized in multidisciplinary research for the discovery of environmental risk factors that can affect not only cardiovascular diseases but also potentially other epidemic diseases.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.141-154
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• 2020

The accidents of toxic chemical spill into rivers are increasing in recent years due to expansion of heavy industries in Korea. In order to respond to the chemical spills, accident response systems have been established for both main rivers and tributary rivers. However, since these accident response system adopted the water quality models imported from the foreign countries, it is difficult to acquire the model parameters and to calibrate and validate the water quality models. Therefore, this study developed a depth-averaged two-dimensional river water quality model to analyze the behavior of hazardous chemicals in rivers and proposed an efficient simulation execution framework by identifying the significant reaction mechanisms considering the characteristics of the toxic chemicals. The depth-averaged two-dimensional river water quality model CTM-2D was upgraded by adding reaction terms representing mechanisms of the adsorption, desorption, and volatilization of toxic chemicals. In order to verify the model, the analytical solution was compared with the numerical solution, and results showed that the error was less than 0.1%. In addition, the model was applied to a virtual scenario which is a water pollution accident at the confluence of the Nakdong River - Kumho River, and model results showed that an efficient simulation could be carried out by activating only significant reactions which were assessed by the sensitivity analysis.