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Among the industrial accidents occurring in Korea, the construction sector accounts for 28.55% of theaccidents associated with this high-risk sector. Although active progress is being made to reduce such industrial accidents, studies concerning the applications to construction site safety are currently insufficient. In this study, research is conducted on the development of a Korean data learning model using the latest in artificial intelligence algorithms, R-CNN, for the identification of safety protection equipmentworn by workers in the field. As a result of this study, the discriminant data learning model concerning the donning of a new Korean safety hard hat provided excellent results with a mean average precision of 0.82. This advancement is expected to reduce industrial accidents in the field of construction and improve safety.

Road accidents caused by weather conditions in winter lead to higher mortality rates than in other seasons. The main causes of road accidents include human carelessness, vehicle defects, road conditions, and weather factors. If the risk of road accidents with changes in road weather conditions can be quantitatively evaluated, it will contribute to reducing the road accident fatalities. The road accident data used in this study were obtained for the period 2017 to 2019. Spatial interpolation estimated the weather information, geographic information system (GIS) and Shuttle Radar Topography Mission (SRTM) data identified road geometry and accident area altitude, synthetic minority oversampling technique (SMOTE) addressed the data imbalance problem between road accidents due to weather conditions and from other causes, and finally, machine learning was performed on the data using various models such as random forest, XGBoost, neural network, and logistic regression. The training- to test data ratio was 7:3. Random forest model exhibited the best classification performance for road accident status according to weather risks. Thus, by applying weather data and road geometry to machine learning models, the risk of road accidents due to weather conditions in the winter season can be predicted and provided as a service.

Baek, W.-K.; Jung, H.-S.; and Kim, D., 2020. Oil spill detection of Kerch strait in November 2007 from dual-polarized TerraSAR-X image using artificial and convolutional neural network regression models. In: Jung, H.-S.; Lee, S.; Ryu, J.-H., and Cui, T. (eds.), Advances in Geospatial Research of Coastal Environments. Journal of Coastal Research, Special Issue No. 102, pp. 137-144. Coconut Creek (Florida), ISSN 0749-0208.The oil spill is the main marine disaster. It is known that the data mining based method performs better in detecting oil than the traditional SAR based method to distinguish from lookalikes. Recently, artificial neural networks were employed to detect the oil spill. For that synthetic aperture radar intensity map, intensity texture map, co-polarized coherence map, co-polarized phase difference texture map, and digital elevation model was employed as input. The detection performance based on data mining largely depends on the used data, the characteristics of the study area, and the used model. Improving detection performance through various existing data mining models is a very important task since minor improvements in detection can have a significant impact on disaster damage mitigation. Artificial and convolutional neural network regression models were applied to detect the oil spill of Kerch strait in November 2007. The two models showed F1-scores of 0.832 and 0.823 respectively. The results of this study would contribute to monitor oil spill dynamic and mitigate damages caused by the oil spill.

The detection of oil spills using radar image has been studied extensively. However, most of the proposed techniques have been focused on improving detection accuracy through the advancement of algorithms. In this study, research has been conducted to improve the accuracy of oil spill detection by improving the quality of radar images, which are used as input data to detect oil spills. Thresholding algorithms were used to measure the image improvement both before and after processing. The overall accuracy increased by approximately 16%, the producer accuracy increased by 40%, and the user accuracy increased by 1.5%. The kappa coefficient also increased significantly, from 0.48 to 0.92.

Synthetic aperture radar (SAR) has been widely used to detect oil-spill areas through the backscattering intensity difference between oil and background pixels. However, since the signal is similar to that produced by other phenomena, positive identification can be challenging. In this study we developed an algorithm to effectively analyze large-scale oil spill areas in SAR images by focusing on optimizing the input layer to artificial neural network (ANN) through removal the factor of lowering the accuracy. An ANN algorithm was used to generate probability maps of oil spills. Highly accurate pixel-based data processing was conducted through false or un-detection element reduction by normalizing the image or applying a non-local (NL) means filter and median filter to the input neurons for ANN. In addition, the standard deviation of co-polarized phase difference (CPD) was used to reduce false detection from the look-alike with weak damping effect. The algorithm was validated using TerraSAR-X images of an oil spill caused by stranded oil tanker Volganefti-139 in the Kerch Strait in 2007. According to the validation results of the receiver operating characteristic (ROC) curve, the oil spill was detected with an accuracy of about 95.19% and un-detection or false detection by look-alike and speckle noise was greatly reduced.

Marine pollution from oil spills destroys ecosystems. In order to minimize the damage, it is important to fast cleanup it after predicting how the oil will spread. In order to predict the spread of oil spill, remote sensing technique, especially radar satellite image is widely used. In previous studies, only the back-scattering value is generally used for the detection of oil spill. However, in this study, oil spill was detected by applying ANN (Artificial Neural Network) as input data from the back-scattering value of the radar image as well as the phase information extracted from the dual polarization. In order to maximize the efficiency of oil spill detection using a back-scattering value, the speckle noise acting as an error factor should be removed first. NL-means filter was applied to multi-look image to remove it without smoothing of spatial resolution. In the coherence image, the sea has a high value and the oil spill area has a low value due to the scattering characteristics of the pulse. In order to using the characteristics of radar image, training sample was set up from NL-means filtered images(HH, VV) and coherence image, and ANN was applied to produce probability map of oil spill. In general, the value was 0.4 or less in the case of the sea, and the value was mainly in the range of 0.7 to 0.9 in the oil spill area. Using coherence images generated from different polarizations showed better detection results for relatively thin oil spill areas such as oil slick or oil sheen than using back-scattering information alone. It is expected that if the information about the look-alike of oil spill such as algae, internal wave and rainfall area is provided, the probability map can be produced with higher accuracy.

The purpose of this study was to determine the acute pulmonary toxicity of metallic silver nanoparticles (MSNPs, 20.30 nm in diameter). Acute pulmonary toxicity and body distribution of inhaled MSNPs in mice were evaluated using a nose-only exposure chamber (NOEC) system. Bronchoalveolar lavage (BAL) fluid analysis, Western blotting, histopathological changes, and silver burdens in various organs were determined in mice. Mice were exposed to MSNPs for 6 hrs. The mean concentration, total surface area, volume and mass concentrations in the NOEC were maintained at 1.93 × 10(7) particles/cm(3), 1.09 × 10(10) nm(2)/cm(3), 2.72 × 10(11) nm(3)/cm(3), and 2854.62 μg/m(3), respectively. Inhalation of MSPNs caused mild pulmonary toxicity with distribution of silver in various organs but the silver burdens decreased rapidly at 24-hrs post-exposure in the lung. Furthermore, inhaled MSNPs induced activation of mitogen-activated protein kinase (MAPK) signaling in the lung. In summary, single inhaled MSNPs caused mild pulmonary toxicity, which was associated with activated MAPK signaling. Taken together, our results suggest that the inhalation toxicity of MSNPs should be carefully considered at the molecular level.

Objectives: The purpose of this study was to review clinical characteristics and working environments of sudden cardiac death (SCD) cases associated with a tire manufacturer in Korea, and review possible occupational risk factors for cardiovascular disease including nanoparticles (ultrafine particles, UFPs). Methods: We reviewed (i) the clinical course of SCD cases and (ii) occupational and non-occupational risk factors including chemicals, the physical work environment, and job characteristics. Results: Possible occupational factors were chemicals, UFPs of rubber fume, a hot environment, shift work, overworking, and noise exposure. The mean diameter of rubber fume (63-73 nm) was (larger than diesel exhaust [12 nm] and outdoor dust [50 nm]). The concentration of carbon disulfide, carbon monoxide and styrene were lower than the limit of detection. Five SCD cases were exposed to shift work and overworking. Most of the cases had several non-occupational factors such as hypertension, overweight and smoking. Conclusion: The diameter of rubber fume was larger than outdoor and the diesel exhaust, the most well known particulate having a causal relationship with cardiovascular disease. The possibility of a causal relation between UFPs of rubber fume and SCD was not supported in this study. However, it is necessary to continue studying the relationship between large sized UFPs and SCD.

Objectives: Nanomaterials are used in a wide variety of industrial materials such as semiconductors, magnetic resonance imaging, gene delivery carriers for gene therapy and many others; thus, human seems to be frequently exposed to them. Such diverse applications of nanoparticles elicit the need to identify the positive aspects of nanomaterials while avoiding the potential toxic effects. In this study, inhalation toxicity of manufactured nanomaterials using fluorescent magnetic nanoparticles (FMNPs) was assessed to address the issue of potential nanoparticle toxicity. Methods: Biological samples from a previous mouse FMNP exposure experiment were analyzed for potential FMNP toxicity. Mice inhaled FMNPs for 4 wk through a nose-only exposure chamber developed by our group for 4 wk and the potential toxicity of FMNPs was analyzed. Results: The nanoparticle distribution by scanning mobility particle sizer (SMPS) analysis showed that the mean values of number concentration (mass concentrations) in the nose-only exposure chamber were maintained at 4.89×105/cm3 (approximately 159.4 μg/m3) for the low concentration and 9.34×105/cm3 (approximately 319.5 μg/m3) for the high concentration, respectively. Inhalation of FMNPs caused a decrease of body weight and significant changes of white blood cells (WBCs) levels in whole blood. The FMNPs induced extramedullary hematopoiesis in the spleen without having a pulmonary effect. Conclusions: Our results support the proposition that extensive toxicity evaluation is needed for practical applications of anthropogenic nanomaterials and suggest that careful regulation of nanoparticle applications may be necessary to maintain a high quality of life as well as for facilitating the development of nanotechnology.

Reducing the particle size of materials is an efficient and reliable tool for improving the bioavailability of a gene or drug delivery system. In fact, nanotechnology helps in overcoming the limitations of size and can change the outlook of the world regarding science. However, a potential harmful effect of nanomaterial on workers manufacturing nanoparticles is expected in the workplace and the lack of information regarding body distribution of inhaled nanoparticles may pose serious problem. In this study, we addressed this question by studying the body distribution of inhaled nanoparticles in mice using approximately 50-nm fluorescent magnetic nanoparticles (FMNPs) as a model of nanoparticles through nose-only exposure chamber system developed by our group. Scanning mobility particle sizer (SMPS) analysis revealed that the mice were exposed to FMNPs with a total particle number of 4.89 x 10(5) +/- 2.37 x 10(4)/cm(3) (low concentration) and 9.34 x 10(5) +/- 5.11 x 10(4)/cm(3) (high concentration) for 4 wk (4 h/d, 5 d/wk). The body distribution of FMNPs was examined by magnetic resonance imaging (MRI) and Confocal Laser Scanning Microscope (CLSM) analysis. FMNPs were distributed in various organs, including the liver, testis, spleen, lung and brain. T2-weighted spin-echo MR images showed that FMNPs could penetrate the blood-brain-barrier (BBB). Application of nanotechnologies should not produce adverse effects on human health and the environment. To predict and prevent the potential toxicity of nanomaterials, therefore, extensive studies should be performed under different routes of exposure with different sizes and shapes of nanomaterials.

Objectives The prevalence of aged individuals in the Korean workforce continues to increase. This research determined the health and working conditions of Korean older wage workers and confirmed the effects of factors on the health-related quality of life of Korean older workers. Methods Of the 25,534 persons surveyed in the fifth Korea National Health and Nutrition Examination Survey, 1368 older (>55 years of age) wage workers without missing variables were selected. Their general characteristics, health status (cardiovascular disease, musculoskeletal disease, and mental health), working conditions (type of occupation, employment status, full- or part-time work, weekly average working hours, and shift work), and health-related quality of life assessed by the EQ-5D questionnaire were examined. Results The mean values of the EQ-5D index of the male and female older workers were 0.956 ± 0.087 and 0.917 ± 0.124, respectively (p

The KOSHA codes H-31 and H-30 provide general guidelines to establish a prevention program for work-related musculoskeletal disorders(WMSD). Understanding of the components and practitioner needs for a WMSD prevention program is necessary for effective revision and implementation of the KOSHA codes. The present study established a comprehensive structure for a WMSD prevention program and surveyed practitioner needs for the KOSHA codes. The comprehensive prevention program structure, consisting of 7 parts(organization, education, risk management, medical management, program evaluation, and record keeping) and 90 items, was constructed by analyzing WMSD prevention guidelines published by various government agencies such as KOSHA, OSHA and NIOSH. Next, 20 practitioners, from four industry sectors(auto manufacturing, auto part manufacturing, shipbuilding, and machinery), working in a safety and health department or labor union, were interviewed to collect opinions for the KOSHA codes in terms of relevance, government support, and additional information needed. Guidelines of the KOSHA codes requiring modifications and government supports were identified, which can be used to revise the KOSHA codes and to establish a government policy to promote the implementation of the KOSHA codes. Lastly, the survey revealed that integrated, customized, quantitative, and case information for WMSD prevention is additionally needed, which can be used as design guidelines for a WMSD prevention program manual for practitioners. Keyword: Musculoskeletal disorders, Prevention program, Ergonomic program, Practitioner needs, Ergonomic program manual

This paper presents design and performance evaluation of virtual impactors that can be used to concentrate aerosol particles. One single-nozzle and two multi-nozzle (4-nozzle and 18-nozzle) virtual impactors were designed and constructed as aerosol concentrators in this study. Evaluations of the aerosol concentrators were performed at different ratios of the minor flow rate to the total flow rate (minor-to-total flow ratios). It was found that the particle concentration factor, Stk 50 and the cutoff diameter are sensitive to the minor-to-total flow ratio as well as the number of nozzles. These results will be useful for high-volume air sampling applications at the low pollutant concentration area.

For ship detection, X-band synthetic aperture radar (SAR) imagery provides very useful data, in that ship targets look much brighter than surrounding sea clutter due to the corner-reflection effect. However, there are many phenomena which bring out false detection in the SAR image, such as noise of background, ghost phenomena, side-lobe effects and so on. Therefore, when ship-detection algorithms are carried out, we should consider these effects and mitigate them to acquire a better result. In this paper, we propose an efficient method to detect ship targets from X-band Kompsat-5 SAR imagery using the artificial neural network (ANN). The method produces the ship-probability map using ANN, and then detects ships from the ship-probability map by using a threshold value. For the purpose of getting an improved ship detection, we strived to produce optimal input layers used for ANN. In order to reduce phenomena related to the false detections, the non-local (NL)-means filter and median filter were utilized. The NL-means filter effectively reduced noise on SAR imagery without smoothing edges of the objects, and the median filter was used to remove ship targets in SAR imagery. Through the filtering approaches, we generated two input layers from a Kompsat-5 SAR image, and created a ship-probability map via ANN from the two input layers. When the threshold value of 0.67 was imposed on the ship-probability map, the result of ship detection from the ship-probability map was a 93.9% recall, 98.7% precision and 6.1% false alarm rate. Therefore, the proposed method was successfully applied to the ship detection from the Kompsat-5 SAR image.

This paper proposes an isolation-improvement technique for a MIMO antenna in small portable devices, by utilizing a one-dimensional electromagnetic bandgap (1-D EBG) and folded slot structures. Since the 1-D EBG structure provides in-phase reflection properties, and the folded slot structure acts as a decoupling resonator due to dissipation of radiated energy, mutual coupling among the antenna elements can be suppressed. The new diversity antenna can cover WLAN 802.11 b/g band (2.4-2.5 GHz). The isolation coefficient of this antenna design is extremely enhanced, even though it maintains its radiation performance.

To investigate the effects of short-term exposure of beryllium on the human immune system, the proportion of T-lymphocytes such as CD3+, CD4+, CD8+, CD95, and NK cells, andthe proportion of B cells and TNFα level in peripheral blood and immunoglobulins in the serum of 43 exposed workers and 34 healthy control subjects were studied. External exposure to beryllium was measured by atomic absorption spectrometer as recommended by the NIOSH analytical method 7300. T lymphocyte subpopulation analysis was carried out with flow cytometer. The working duration of exposed workers was less than 3 months and the mean ambient beryllium level was 3.4 μg/m(3), 112.3 μg/m(3), and 2.3 μg/m(3) in molding (furnace), deforming (grinding), and sorting processes, respectively (cited from Kim et al., 2008). However, ambient beryllium level after process change was non-detectable (0.1 μg/m(3)). The number of T lymphocytes and the amount of immunoglobulins in the beryllium-exposed workers and control subjects were not significantly different, except for the total number of lymphocytes and CD95 (APO1/FAS). The total number of lymphocytes was higher in the beryllium-exposed individuals than in the healthy control subjects. Multiple logistic regression analysis showed lymphocytes to be affected by beryllium exposure (odd ratio = 7.293; p0.001). These results show that short-term exposure to beryllium does not induce immune dysfunction but is probably associated with lymphocytes proliferation.

Switched array antenna with six microstrip patch elements was designed and characterized for UHF RFID application. A hexagonal-shaped RF switching circuit board was developed to select one of the array elements to read RFID tags surrounding the RFID reader antenna. The designed switching network ports have exhibited isolation greater than 30 dB and insertion loss less than 2.4 dB. The polarization direction of the microstrip patch elements is arranged perpendicular to RF switching circuit board. The measured characteristics of each antenna element at 915 MHz include gain of 9.06 and 8.62 dBi, half power beam width of 60deg and 70deg at E-plane and H-plane, respectively. Total switched array antenna can scan 360deg with 60deg incremental angle.

The World Health Organisation established the Roll Back Malaria (RBM) strategy to reduce the global burden of malaria in 1998. A set of RBM indicators will not be suitable to the Republic of Korea due to the differences of the epidemiological and socio-cultural situation. Therefore, we have developed a framework and indicators for monitoring the outcomes and impact of the national malaria eradication programme that are appropriate for the situation in Korea. We reviewed the existing data in the national malaria eradication programme. We adopted general principles in developing a monitoring framework and indicators for monitoring RBM. Monitoring areas were recombined components and content that included the project plan, training health personnel, health education and public information, supply for manpower, equipment and materials, disease control, information system, supervision, community participation, intersectoral collaboration within practical guidelines for the national malaria eradication programme along with malaria control and RBM strategy of WHO. Twenty one monitoring areas were selected that identified critical areas for the national malaria eradication programme. Fifteen indicators of ten categories are proposed for use by the national malaria eradication programme in Korea. Asia Pac J Public Health 2003; 15(1): 44-49.

Objectives Vitamin D deficiency is increasing worldwide. However, few studies have attempted to examine the vitamin D status of wage workers and the correlation between vitamin D deficiency and working conditions. Hence, we aimed to evaluate the prevalence of vitamin D deficiency and the association between occupational conditions and vitamin D deficiency among Korean wage workers. Methods Wage workers aged 20–65 years from the 5th Korea National Health and Nutrition Examination Survey (KNHANES 2010–2012; n = 5409) were included in our analysis. We measured the prevalence of vitamin D deficiency and identified the correlations with the working conditions of these subjects. Results The prevalence of vitamin D deficiency in male and female subjects was 69.5% and 83.1%, respectively. Among the male subjects, a significant correlation between vitamin D deficiency and working conditions was observed among shift workers, office workers, and permanent workers. No significant correlation with any type of working conditions was observed among female subjects. Conclusion The prevalence of vitamin D deficiency among Korean wage workers was very high and was found to correlate significantly with working conditions, likely because of insufficient exposure to sunlight associated with certain types of work. Wage workers require more frequent outdoor activity and nutrition management to maintain sufficient vitamin D level.

Cerebro-cardiovascular disease (CVD) is one of compensable occupational diseases in Korea as in Japan or Taiwan. However, most countries accept only cardiovascular diseases (ischemic heart diseases) as compensable occupational diseases if any, but not cerebrovascular diseases. Korea has a prescribed list of compensable occupational diseases. CVD was not included in the list until 1993. In the early 1990s, a case of cerebral infarction was accepted as occupational disease by the Supreme Court. The decision was based on the concept that workers' compensation system is one of the social security systems. In 1994, the government has established a diagnostic criterion of CVD. The crude rate of compensated cerebrovascular disease decreased by 60.0% from 18.5 in 2003 to 7.4 in 2008 per 100,000 workers, and that of compensated coronary heart disease decreased by 60.5% from 3.8 in 2003 to 1.5 in 2008 per 100,000 workers. The compensated cases of CVD dramatically increased and reached its peak in 2003. Since many preventive activities were performed by the government and employers, the compensated cases have slowly decreased since 2003 and sharply decreased after 2008 when the diagnostic criterion was amended. The strategic approach is needed essentially because CVDs are common, serious and preventable diseases which lead to economic burden.