• Safety and Health at Work
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• v.13 no.3
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• pp.263-268
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• 2022

Health care workers (HCWs) are more than ten times more likely to be infected with coronavirus infectious disease 2019 (COVID-19) than the general population, thus demonstrating the burden of COVID-19 among HCWs. Factors that expose HCWs to a differentially high-risk of COVID-19 acquisition are important to elucidate, enable appropriate public health interventions to mitigate against high risk and reduce adverse outcomes from the infection. We conducted a systematic review and meta-analysis to summarize and critically analyze the existing evidence on SARS-CoV-2 risk factors among HCWs. With no geographical limitation, we included studies, in any country, that reported (i) the PCR laboratory diagnosis of COVID-19 as an independent variable (ii) one or more COVID-19 risk factors among HCWs with risk estimates (relative risk, odds ratio, or hazard ratio) (iii) original, quantitative study design, and published in English or Mandarian. Our initial search resulted in 470 articles overall, however, only 10 studies met the inclusion criteria for this review. Out of the 10 studies included in the review, inadequate/lack of protective personal equipment, performing tracheal intubation, and gender were the most common risk factors of COVID-19. Based on the random effects adjusted pooled relative risk, HCWs who reported the use of protective personal equipment were 29% (95% CI: 16% to 41%) less likely to test positive for COVID-19. The study also revealed that HCWs who performed tracheal intubations were 34% (95% CI: 14% to 57%) more likely to test positive for COVID-19. Interestingly, this study showed that female HCWs are at 11% higher risk (RR 1.11 95% CI 1.01-1.21) of COVID-19 than their male counterparts. This article presents initial findings from a living systematic review and meta-analysis, therefore, did not yield many studies; however, it revealed a significant insight into better understanding COVID-19 risk factors among HCWs; insights important for devising preventive strategies that protect them from this infection.

• Land and Housing Review
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• v.13 no.3
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• pp.1-20
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• 2022

This study analyses how much Korean visits to North Korea have an impact on the North Korean regional economy. It estimates the demand for North Korean tourism via the borders of North Korea, China, and Russia and South Korean expenses to be spent in North Korea. When asked if they are willing to visit North Korea within the next five years in case the pre-conditions of the visit to North Korea are satisfied, approximately 64.1% of the survey respondents indicated 'yes'. To estimate the demand, this research employed the analysis of purchase intention, popular in marketing, based on their willingness to visit. The annual demand for tourism was 4,136,361 persons. The average estimated expense per person is KRW 1,532,000 and the total annual expense is KRW 6,336.9 billion. Assuming that airfare is excluded from the total expense and the expense is made evenly in each tourist destination, the estimated amount to be spent in North Korea is KRW 2,838.7 billion per annum. The backward linkage effect of this expense on the North Korean regional economy is KRW 7,972.1 billion in total production inducement, KRW 2,619.4 billion in value-added inducement, and approximately 2,890,443 persons in employment inducement. The value-added inducement effect is estimated to be approximately 7.6% of the North Korean nominal GDP in 2020. South Korean tourism is expected to have a significant impact on the North Korean economy. As the demand for North Korean tourism is likely to increase steadily due to the expected increase in overseas travel demand by Koreans, inter-Korean cooperation is needed for the development of North Korean tourism infrastructure if conditions improve.

• Journal of Korea Trade
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• v.24 no.7
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• pp.1-28
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• 2020

Purpose - This paper empirically investigates the predictors and main determinants of consumers' ratings of mobile applications in the Google Play Store. Using a linear and nonlinear model comparison to identify the function of users' review, in determining application rating across countries, this study estimates the direct effects of users' reviews on the application rating. In addition, extending our modelling into a sentimental analysis, this paper also aims to explore the effects of review polarity and subjectivity on the application rating, followed by an examination of the moderating effect of user reviews on the polarity-rating and subjectivity-rating relationships. Design/methodology - Our empirical model considers nonlinear association as well as linear causality between features and targets. This study employs competing theoretical frameworks - multiple regression, decision-tree and neural network models - to identify the predictors and main determinants of app ratings, using data from the Google Play Store. Using a cross-validation method, our analysis investigates the direct and moderating effects of predictors and main determinants of application ratings in a global app market. Findings - The main findings of this study can be summarized as follows: the number of user's review is positively associated with the ratings of a given app and it positively moderates the polarity-rating relationship. Applying the review polarity measured by a sentimental analysis to the modelling, it was found that the polarity is not significantly associated with the rating. This result best applies to the function of both positive and negative reviews in playing a word-of-mouth role, as well as serving as a channel for communication, leading to product innovation. Originality/value - Applying a proxy measured by binomial figures, previous studies have predominantly focused on positive and negative sentiment in examining the determinants of app ratings, assuming that they are significantly associated. Given the constraints to measurement of sentiment in current research, this paper employs sentimental analysis to measure the real integer for users' polarity and subjectivity. This paper also seeks to compare the suitability of three distinct models - linear regression, decision-tree and neural network models. Although a comparison between methodologies has long been considered important to the empirical approach, it has hitherto been underexplored in studies on the app market.

• Journal of Korea Port Economic Association
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• v.37 no.2
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• pp.33-53
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• 2021

This study estimated the economic value of port redevelopment projects. The port redevelopment project consists of a combination of goods between market goods and non-market goods. The value of market goods can be measured at prices in the real market, but it is difficult to convert value estimates for non-market goods into currency values. Therefore, in this study, economic benefits of port redevelopment projects were estimated by the using the CVM. The estimated model used the Hanemann's model and the Bayesian approach to estimate the WTP of the sample group's using the single boundary model. Estimating the household's WTP, the Hanemann's model was estimated at KRW 10,038.33 and the Bayesian approach at KRW 12,217.1. As of the five-year period(discount benefits), the economic benefits of the port redevelopment project were estimated at 920.7 billion won for the Hanemann's model and 1.12 trillion won for the Bayesian model on a national basis. Meanwhile, as a result of estimating economic benefits(discount benefits) based on the administrative districts of Busan·Gyeongnam·Ulsan regions(five-year period), the Hanemann's model was estimated at KRW 140.4 billion and the Bayesian approach was estimated at KRW 170.8 billion.

• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.143-153
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• 2021

Purpose: The purpose of this study was to analyze data from the Ministry of Health, Safety and Health and the Ministry of Employment and Labor, and the total number of deaths (disease + accidents) reached 2,020 in 2019 and the estimated economic loss was 27.6 trillion won. This is believed to be the time to present improvements to ensure that economic loss estimates are steadily increasing as in Table 1, and that government-level losses can be drastically reduced. Method: In this study, factors were selected through prior research, and reliability analysis, technical statistics and correlation analysis, and multi-term analysis were conducted through the Jamovi program for the analysis of results. Result: Multiple session analysis was conducted to verify the research theory indicated in this study, and the analysis showed that mechanical and management factors did not affect the fall death accident of the opening, and human factors, material and environmental factors had a static effect. In addition, mechanical and administrative factors do not affect the fall of the outer wall, and human and material and environmental factors have a static effect. Conclusion:: As a result of analyzing 450 falling deaths over the past 13 years among the data posted to the Korea Health and Safety Corporation, the most common causes of falling deaths were the openings and outer walls.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.326-334
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• 2022

In this paper, we propose speech enhancement algorithm as a pre-processing for robust speech recognition in noisy environments. Auxiliary-function-based Independent Vector Analysis (AuxIVA) is performed with weighted covariance matrix using time-varying variances with scaling factor from target masks representing time-frequency contributions of target speech. The mask estimates can be obtained using Neural Network (NN) pre-trained for speech extraction or diffuseness using Coherence-to-Diffuse power Ratio (CDR) to find the direct sounds component of a target speech. In addition, outputs for omni-directional noise are closely chained by sharing the time-varying variances similarly to independent subspace analysis or IVA. The speech extraction method based on AuxIVA is also performed in Independent Low-Rank Matrix Analysis (ILRMA) framework by extending the Non-negative Matrix Factorization (NMF) for noise outputs to Non-negative Tensor Factorization (NTF) to maintain the inter-channel dependency in noise output channels. Experimental results on the CHiME-4 datasets demonstrate the effectiveness of the presented algorithms.

• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.47-63
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• 2023

Unmanned aerial vehicle (UAV) and sensor technologies are rapidly developing and being usefully utilized for spatial information-based agricultural management and smart agriculture. Until now, there have been many difficulties in obtaining production information in a timely manner for large-scale agriculture on reclaimed land. However, smart agriculture that utilizes sensors, information technology, and UAV technology and can efficiently manage a large amount of farmland with a small number of people is expected to become more common in the near future. In this study, we evaluated the productivity of forage maize grown on reclaimed land using UAV and sensor-based technologies. This study compared the plant height, vegetation cover ratio, fresh biomass, and dry biomass of maize grown on general farmland and reclaimed land in South Korea. A biomass model was constructed based on plant height, cover ratio, and volume-based biomass using UAV-based images and Farm-Map, and related estimates were obtained. The fresh biomass was estimated with a very precise model (R² =0.97, root mean square error [RMSE]=3.18 t/ha, normalized RMSE [nRMSE]=8.08%). The estimated dry biomass had a coefficient of determination of 0.86, an RMSE of 1.51 t/ha, and an nRMSE of 12.61%. The average plant height distribution for each field lot was about 0.91 m for reclaimed land and about 1.89 m for general farmland, which was analyzed to be a difference of about 48%. The average proportion of the maize fraction in each field lot was approximately 65% in reclaimed land and 94% in general farmland, showing a difference of about 29%. The average fresh biomass of each reclaimed land field lot was 10 t/ha, which was about 36% lower than that of general farmland (28.1 t/ha). The average dry biomass in each field lot was about 4.22 t/ha in reclaimed land and about 8 t/ha in general farmland, with the reclaimed land having approximately 53% of the dry biomass of the general farmland. Based on these results, UAV and sensor-based images confirmed that it is possible to accurately analyze agricultural information and crop growth conditions in a large area. It is expected that the technology and methods used in this study will be useful for implementing field-smart agriculture in large reclaimed areas.

• Ocean and Polar Research
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• v.44 no.4
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• pp.269-285
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• 2022

The interaction between ocean and ice shelf is a critical physical process in relation to water mass transformations and ice shelf melting/freezing at the ocean-ice interface. However, it remains challenging to thoroughly understand the process due to a lack of observational data with respect to ice shelf cavities. This is the first study to simulate the variability and circulation of water mass both overlying the continental shelf and underneath an ice shelf and an ice tongue in the Terra Nova Bay (TNB), East Antarctica. To explore the properties of water mass and circulation patterns in the TNB and the corresponding effects on sub ice shelf basal melting, we explicitly incorporate the dynamic-thermodynamic processes acting on the ice shelf in the Regional Ocean Modeling System. The simulated water mass formation and circulation in the TNB region agree well with previous studies. The model results show that the TNB circulation is dominated by the geostrophic currents driven by lateral density gradients induced by the releasing of brine or freshwater at the polynya of the TNB. Meanwhile, the circulation dynamics in the cavity under the Nansen Ice shelf (NIS) are different from those in the TNB. The gravity-driven bottom current induced by High Salinity Shelf Water (HSSW) formed at the TNB polynya flows towards the grounding line, and the buoyance-driven flow associated with glacial meltwater generated by the HSSW emerges from the cavity along the ice base. Both current systems compose the thermohaline overturning circulation in the NIS cavity. This study estimates the NIS basal melting rate to be 0.98 m/a, which is comparable to the previously observed melt rate. However, the melting rate shows a significant variation in space and time.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.315-324
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• 2022

The conventional LESS (LEast-Squares Solution) is calculated under the assumption that there is no errors in independent variables. However, the coordinates of a point, either from traditional ground surveying such as slant distances, horizontal and/or vertical angles, or GNSS (Global Navigation Satellite System) positioning, cannot be determined independently (and the components are correlated each other). Therefore, the TLS (Total Least Squares) adjustment should be applied for all applications related to the coordinates. Many approaches were suggested in order to solve this problem, resulting in equivalent solutions except some restrictions. In this study, we calculated the normal vector of the 3D plane determined by the trace of the VLBI targets based on TLS within GHM (Gauss-Helmert Model). Another numerical test was conducted for the estimation of the Helmert transformation parameters. Since the errors in the horizontal components are very small compared to the radius of the circle, the final estimates are almost identical. However, the estimated variance components are significantly reduced as well as show a different characteristic depending on the target location. The Helmert transformation parameters are estimated more precisely compared to the conventional LESS case. Furthermore, the residuals can be predicted on both reference frames with much smaller magnitude (in absolute sense).

• Korean Journal of Environmental Agriculture
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• v.40 no.4
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• pp.313-321
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• 2021

BACKGROUND: Ammonia is a causative substance for the fine particulate matters (PM_2.5) and generates dust through atmospheric reactions. Agricultural sector accounts for 79.3% of ammonia emissions in Korea. Urea and composted organic fertilizer (COF) are used in the soil for the purpose of supplying nutrients in grapevine orchards. This study was conducted to investigate estimates of ammonia emission and examine fruit quality from the rain proof cultivation of the 'Beni Balad', applied by urea and COF to the soil. METHODS AND RESULTS: Urea, COF1, and COF2 were applied at the rates of 119, 135, and 271 kg ha^-1 respectively. Ammonia emissionwas measured using a dynamic flow-through method. CONCLUSION(S): Ammonia emissions by urea and COF treatments to 'Beni Balad' soils under rain proof cultivation were calculated to be 2.63, 12.95, 2.05, and 3.97 kg NH₃-N ha^-1 day^-1, respectively for the control, urea, COF1, and COF2. Urea soil application increased soluble solids, firmness, and anthocyanin content in fruits at harvest, and COF1 application increased the soluble solids and anthocyanin content. For all the treatments, acidity increased in the harvested fruits.