• Journal of The Geomorphological Association of Korea
• /
• v.20 no.1
• /
• pp.21-33
• /
• 2013

Weight of evidence model was applied for potential mapping of mountainous wetland to reduce the range of the field survey and to increase the efficiency of operations because the surveys of mountainous wetland need a lot of time and money owing to inaccessibility and extensiveness. The relationship between mountainous wetland location and related factors is expressed as a probability by Weight of evidence model. For this, the spatial database consist of slope map, curvature map, vegetation index map, wetness index map, soil drainage rating map was constructed in Yeongnam area, Korea, and weights of evidence based on the relationship between mountainous wetland location and each factor rating were calculated. As a result of correlation analysis between mountainous wetland location and each factors rating using likelihood ratio values, the probability of mountainous wetlands were increased at condition of lower slope, lower curvature, lower vegetation index value, lower wetness value, moderate soil drainage rating. Mountainous Wetland Potential Index(MWPI) was calculated by summation of the likelihood ratio and mountainous wetland potential map was constucted from GIS integration. The mountain wetland potential map was verified by comparison with the known mountainous wetland locations. The result showed the 75.48% in prediction accuracy.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_1
• /
• pp.833-845
• /
• 2021

Quantification of carbon absorption and understanding the human induced land use changes forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by land use changes through remote sensing technology. However, it focused on past carbon absorption changes. So prediction of future carbon absorption changes is insufficient. This study simulated land use change using the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model and predicted future changes in carbon absorption considering climate change scenarios 4.5 and 8.5 of the Representative Concentration Pathways (RCP). Results of this study, in the RCP 4.5 scenarios there predicted to be loss of 7.92% of carbon absorption, but in the RCP 8.5 scenarios was 13.02%. Therefore, the approach used in this study is expected to enable exploration of future carbon absorption change considering other climate change scenarios.

• The Journal of Bigdata
• /
• v.6 no.1
• /
• pp.91-113
• /
• 2021

Despite the influence of real estate in the Korean asset market, it is not easy to predict market trends, and among them, apartments are not easy to predict because they are both residential spaces and contain investment properties. Factors affecting apartment prices vary and regional characteristics should also be considered. This study was conducted to compare the factors and characteristics that affect apartment prices in Seoul as a whole, 3 Gangnam districts, Nowon, Dobong, Gangbuk, Geumcheon, Gwanak and Guro districts and to understand the possibility of price prediction based on this. The analysis used machine learning algorithms such as neural networks, CHAID, linear regression, and random forests. The most important factor affecting the average selling price of all apartments in Seoul was the government's policy element, and easing policies such as easing transaction regulations and easing financial regulations were highly influential. In the case of the three Gangnam districts, the policy influence was low, and in the case of Gangnam-gu District, housing supply was the most important factor. On the other hand, 6 mid-lower-level districts saw government policies act as important variables and were commonly influenced by financial regulatory policies.

• Journal of Climate Change Research
• /
• v.1 no.2
• /
• pp.147-161
• /
• 2010

The temporal and spatial distributions of surface solar radiation were calculated by the one layer solar radiative transfer model(GWNU) which was corrected by multi layer Line-by-Line(LBL) model during 2009 in South Korea. The aerosol optical thickness, ozone amount, cloud fraction and total precipitable water were used as the input data for GWNU model run and they were retrieved from Moderate Resolution Imaging Spectrometer(MODIS), Ozone Monitoring Instrument(OMI), MTSAT-1R satellite data and the Regional Data Assimilation Prediction System(RDAPS) model result, respectively. The surface solar radiation was calculated with 4 km spatial resolution in South Korea region using the GWNU model and the results were compared with surface measurement(by pyranometer) data of 22 KMA solar sites. The maximum values(more than $5,400MJ/m^2$) of model calculated annual solar radiation were found in Andong, Daegu and Jinju regions and these results were corresponded with the MTSAT-1R cloud amount data. However, the spatial distribution of surface measurement data was comparatively different from the model calculation because of the insufficient correction and management problems for the sites instruments(pyranometer).

• Journal of Korea Water Resources Association
• /
• v.54 no.spc1
• /
• pp.1037-1051
• /
• 2021

Biochemical oxygen demand (BOD) concentration, one of important water quality indicators, is treated as the measuring item for the ecological chapter in lakes and rivers. This investigation employed novel two-stage hybrid paradigm (i.e., wavelet-based gated recurrent unit, wavelet-based generalized regression neural networks, and wavelet-based random forests) to predict BOD concentration in the Dosan and Hwangji stations, South Korea. These models were assessed with the corresponding independent models (i.e., gated recurrent unit, generalized regression neural networks, and random forests). Diverse water quality and quantity indicators were implemented for developing independent and two-stage hybrid models based on several input combinations (i.e., Divisions 1-5). The addressed models were evaluated using three statistical indices including the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and correlation coefficient (CC). It can be found from results that the two-stage hybrid models cannot always enhance the predictive precision of independent models confidently. Results showed that the DWT-RF5 (RMSE = 0.108 mg/L) model provided more accurate prediction of BOD concentration compared to other optimal models in Dosan station, and the DWT-GRNN4 (RMSE = 0.132 mg/L) model was the best for predicting BOD concentration in Hwangji station, South Korea.

• Ecology and Resilient Infrastructure
• /
• v.10 no.1
• /
• pp.11-19
• /
• 2023

Alien species are known to threaten regional biodiversity globally, which has increased global interest regarding introduction of alien species. The Ministry of Environment of Korea designated species that have not yet been introduced into the country with potential threat as alert alien species to prevent damage to the ecosystem. In this study, potential habitats of Esox lucius and Maccullochella peelii, which are predatory and designated as alert alien fish, were predicted on a national basis. Habitat suitability was evaluated using EHSM (Ecological Habitat Suitability Model), and water temperature data were input to calculate Physiological Habitat Suitability (PHS). The prediction results have shown that PHS of the two fishes were mainly controlled by heat or cold stress, which resulted in biased habitat distribution. E. lucius was predicted to prefer the basins at high latitudes (Han and Geum River), while M. peelii preferred metropolitan areas. Through these differences, it was expected that the invasion pattern of each alien fish can be different due to thermal preference. Further studies are required to enhance the model's predictive power, and future predictions under climate change scenarios are required to aid establishing sustainable management plans.

• Journal of Industrial Convergence
• /
• v.21 no.1
• /
• pp.175-185
• /
• 2023

Recently, novel viral infections such as COVID-19 have spread and pose a serious public health problem. In particular, these diseases have a fatal effect on the elderly, threatening life and causing serious social and economic losses. Accordingly, applications such as telemedicine, healthcare, and disease prevention using the Internet of Things (IoT) and artificial intelligence (AI) have been introduced in many industries to improve disease detection, monitoring, and quarantine performance. However, since existing technologies are not applied quickly and comprehensively to the sudden emergence of infectious diseases, they have not been able to prevent large-scale infection and the nationwide spread of infectious diseases in society. Therefore, in this paper, we try to predict the spread of infection by collecting various infection information with regional limitations through a virus disease information collector and performing AI analysis and severity matching through an AI broker. Finally, through the Korea Centers for Disease Control and Prevention, danger alerts are issued to the elderly, messages are sent to block the spread, and information on evacuation from infected areas is quickly provided. A realistic elderly support system compares the location information of the elderly with the information of the infected area and provides an intuitive danger area (infected area) avoidance function with an augmented reality-based smartphone application. When the elderly visit an infected area is confirmed, quarantine management services are provided automatically. In the future, the proposed system can be used as a method of preventing a crushing accident due to sudden crowd concentration in advance by identifying the location-based user density.

• Journal of Industrial Convergence
• /
• v.21 no.11
• /
• pp.13-27
• /
• 2023

This study aims to contribute to the reduction of the failure rate and social costs resulting from business failures by analyzing factors that affect the insolvency of social enterprises, as the role of social enterprises is increasing in our economy. The data used in this study were classified as normal and insolvent companies among social enterprises (including prospective social enterprises) that were established between 2009 and 2018 and received credit guarantees from credit guarantee institutions as of the end of June 2022. Among the collected data, 439 social enterprises with available financial information were targeted; 406 (92.5%) were normal enterprises, and 33 (7.5%) were insolvent enterprises. Through a literature review, eight non-financial factors commonly used for insolvency prediction were selected. The cross-analysis results showed that four of these factors were significant. Logistic regression analysis revealed that two variables, including corporate credit rating and the personal credit rating of the representative, were significant. Financial factors such as debt ratio, sales operating profit rate, and total asset turnover were used as control variables. The empirical analysis confirmed that the two independent variables maintained their influence even after controlling for financial factors. Given that government-led support and development policies have limitations, there is a need to shift policy direction so that various companies aspiring to create social value can enter the social enterprise sector through private and regional initiatives. This would enable the social economy to create an environment where local residents can collaborate to realize social value, and the government should actively support this.

• Journal of Trauma and Injury
• /
• v.37 no.1
• /
• pp.37-47
• /
• 2024

Purpose: This study aimed at developing a novel tube thoracostomy technique using the sternum, a fixed anatomical structure, as an indicator to reduce the possibility of incorrect chest tube positioning and complications in patients with chest trauma. Methods: This retrospective study analyzed the data of 184 patients with chest trauma who were aged ≥18 years, visited a single regional trauma center in Korea between April and June 2022, and underwent chest computed tomography (CT) with their arms down. The conventional gold standard, 5th intercostal space (ICS) method, was compared to the lower 1/2, 1/3, and 1/4 of the sternum method by analyzing CT images. Results: When virtual tube thoracostomy routes were drawn at the mid-axillary line at the 5th ICS level, 150 patients (81.5%) on the right side and 179 patients (97.3%) on the left did not pass the diaphragm. However, at the lower 1/2 of the sternum level, 171 patients (92.9%, P<0.001) on the right and 182 patients (98.9%, P= 0.250) on the left did not pass the diaphragm. At the 5th ICS level, 129 patients (70.1%) on the right and 156 patients (84.8%) on the left were located in the safety zone and did not pass the diaphragm. Alternatively, at the lower 1/2, 1/3, and 1/4 of the sternum level, 139 (75.5%, P=0.185), 49 (26.6%, P<0.001), and 10 (5.4%, P<0.001), respectively, on the right, and 146 (79.3%, P=0.041), 69 (37.5%, P<0.001), and 16 (8.7%, P<0.001) on the left were located in the safety zone and did not pass the diaphragm. Compared to the conventional 5th ICS method, the sternum 1/2 method had a safety zone prediction sensitivity of 90.0% to 90.7%, and 97.3% to 100% sensitivity for not passing the diaphragm. Conclusions: Using the sternum length as a tube thoracostomy indicator might be feasible.

• The Korean Journal of Nuclear Medicine
• /
• v.32 no.6
• /
• pp.509-515
• /
• 1998

Purpose: The aim of this study was to evaluate whether T1-201 reinjection distinguishes viable from non-viable myocardium in patients with reverse redistribution after acute myocardial infarction. Materials and Methods: We studied 42 patients with acute myocardial infarction (age, $55{\pm}12$ years). Eighteen (43%) out of 42 showed reverse redistribution on dipyridamole stress-4 hour redistribution T1-201 single photon emission computed tomography (SPECT). T1-201 reinjection was performed at 24 hours. Reverse redistribution was defined as worsening of perfusion defect at 4 hour delayed scan. All patients underwent follow-up echocardiography in 4 months to assess regional wall motion improvement. T1-201 uptake on reinjection images were analyzed for the prediction of myocardial wall motion improvement. Results: Of 36 segments with reverse redistribution, 17 segments showed normal wall motion on echocardiography, while 19 segments showed wall motion abnormalities. Of 19 the segments with reverse redistribution, 11 (58%) showed enhanced uptake after 24 hour reinjection. Myocardial wall motion was improved in 10 of 11 segments (90%) with enhanced uptake on reinjection. Wall motion improvement was not seen in 5 of 8 segments (63%) without enhanced thallium uptake. When myocardial viability was assessed by the uptake on reinjection image, nine of 10 segments (90%) with normal or mildly decreased uptake showed improved wall motion. Wall motion was not improved in 5 of 9 segments (16%) with severely decreased uptake. Conclusion: In patients with acute myocardial infarction, T1-201 reinjection imaging on myocardial segments with reverse redistribution has a high positive predictive value in the assessment of myocardial viability.