• Journal of Korean Biological Nursing Science
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• v.23 no.2
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• pp.138-150
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• 2021

Purpose: This retrospective study aimed to investigate nursing interventions in patients with severe thoracic injury in trauma bay of a regional trauma center. Methods: Of the 1,780 patients admitted to the trauma bay of a regional trauma center in a university hospital in the Gyeonggi Province between January 1, 2019 and December 31, 2019, 120 adult patients with severe thoracic injury who met the inclusion criteria were enrolled. Participants' clinical characteristics and nursing interventions were collected from electronic medical records after receiving ethical approval. Nursing interventions were classified using the terminology in the Nursing Intervention Classification. Results: The mean age of participants was 52.25 years and 72.5% of participants were male. The main areas of thoracic injury included lung parenchyma and pleura (95.8%). The mean Abbreviated Injury Scale (AIS) for thoracic injury was 3.13 and the mean Injury Severity Score (ISS) was 17.81. Fluid resuscitation, invasive hemodynamic monitoring, chest tube care, respiratory monitoring, artificial airway management, gastrointestinal tube care, mechanical ventilation management: airway insertion and stabilization, blood product administration, allergy management, and surgical preparation were performed significantly more frequently in thoracic injury patients with unstable vital signs or a higher AIS score. Conclusion: This study is significant as it investigated the types of nursing interventions given to patients with severe thoracic injury in the trauma bay. These results would contribute to developing more detailed educational materials for initial nursing interventions in trauma bay.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.448-461
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• 2024

Purpose: The purpose of this study is to establish a life zone class suitable for Korean characteristics in the post-COVID-19 era and to classify the types for the installation and operation of living SOC facilities. Method: The concept of the life zone was established through policies and previous studies related to the life zone, and data in various fields such as population, employment, transportation, economy, and education were classified using the z-score technique. Result: Korea's life zones can be classified into metropolitan life zones, regional life zones, urban life zones, village life zones, and neighborhood life zones, and depending on their roles, they can be classified into central life zones, workplace-residential balanced life zones, residential life zones, industrial life zones, and low-density life zones. Conclusion: The results of this study show that proper life zone establishment and proper living SOC supply can prevent the decline of underdeveloped areas and contribute to balanced regional development

• Environmental and Resource Economics Review
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• v.33 no.1
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• pp.87-112
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• 2024

This study estimates the regional input-output table and GHG emissions in 2019 and then analyzes the economic effects of carbon taxes by region and industry in Korea. The GHG emission, emission coefficient, and emission induction coefficient are estimated to be higher in manufacturing-oriented metropolitan provinces. The GHG emission coefficient in the same industry varies from region to region, which might reflect the standard of product classification, characteristics of production technology, and the regional differences in input structure. If a carbon tax is imposed, production costs are expected to increase and demand and production will decrease, especially in the manufacturing industry, which emits more GFG. On the other hand, the impact of carbon taxes on each region is not expected to vary significantly from region to region, which might be due to the fact that those differences are mitigated by industry-related effects. Since the impact of carbon taxes is expected to spread to the entire region, close cooperation between local governments is necessary in the process of implementing carbon neutrality in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.4
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• pp.215-219
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• 2001

Land surface parameterization schemes for atmospheric models as well as decision support tools for ecosystem management require a frequent updating of land cover classification data for regional to global scales. Rice paddies have not been treated independently from other agricultural land classes in many classification systems, despite their atmospheric and ecological significance. A simple but improved method over conventional land cover classification schemes for rice paddy is suggested. Normalized difference vegetation index (NDVI) was calculated for the land area of South Korea at a 1km by 1 km resolution from the visible and the near-infrared channel reflectances of NOAA-AVHRR (Advanced Very High Resolution Radiometer). Monthly composite images of daily maximum NDVI were prepared for May and August, and used to classify 4 major land cover classes : urban, farmland, forests and water body. Among the pixels classified as "forests" in August, those classified as "water body" in May were assigned a "rice paddy" class. The distribution pattern of "rice paddy" pixels was very similar to the reported rice acreage of 1,455 Myons, which is the smallest administrative land unit in Korea. The correlation coefficient between the estimated and the reported acreage of Myons was 0.7, while 0.5 was calculated from the USGS classification.calculated from the USGS classification.

• Tunnel and Underground Space
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• v.31 no.1
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• pp.10-24
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• 2021

Rock mass classification for construction of underground facilities is essential to secure their stabilities. Therefore, the reliable values for rock mass classification from the precise information on rock discontinuities are most important factors, because rock mass discontinuities can affect exclusively on the physical and mechanical properties of rock mass. The conventional classification operation for rock mass has been usually performed by hand mapping. However, there have been many issues for its precision and reliability; for instance, in large-scale survey area for regional geological survey, or rock mass classification operation by non-professional engineers. For these reasons, automated rock mass classification using LiDAR becomes popular for obtaining the quick and precise information. But there are several suggested algorithms for analyzing the rock mass discontinuities from point cloud data by LiDAR scanning, and it is known that the different algorithm gives usually different solution. Also, it is not simple to obtain the exact same value to hand mapping. In this paper, several discontinuity extract algorithms have been explained, and their processes for extracting rock mass discontinuities have been simulated for real rock bench. The application process for several algorithms is anticipated to be a good reference for future researches on extracting rock mass discontinuities from digital point cloud data by laser scanner, such as LiDAR.

• Geophysics and Geophysical Exploration
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• v.13 no.3
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• pp.203-218
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• 2010

The site categorization and corresponding site amplification factors in the current Korean seismic design guideline are based on provisions for the western United States (US), although the site effects resulting in the amplification of earthquake ground motions are directly dependent on the regional and local site characteristic conditions. In these seismic codes, two amplification factors called site coefficients, $F_a$ and $F_v$, for the short-period band and midperiod band, respectively, are listed according to a criterion, mean shear wave velocity ($V_S$) to a depth of 30 m, into five classes composed of A to E. To suggest a site classification system reflecting Korean site conditions, in this study, systematic site characterization was carried out at four regional areas, Gyeongju, Hongsung, Haemi and Sacheon, to obtain the $V_S$ profiles from surface to bedrock in field and the non-linear soil properties in laboratory. The soil deposits in Korea, which were shallower and stiffer than those in the western US, were examined, and thus the site period in Korea was distributed in the low and narrow band comparing with those in western US. Based on the geotechnical characteristic properties obtained in the field and laboratory, various site-specific seismic response analyses were conducted for total 75 sites by adopting both equivalent-linear and non-linear methods. The analysis results showed that the site coefficients specified in the current Korean provision underestimate the ground motion in the short-period range and overestimate in the mid-period range. These differences can be explained by the differences in the local site characteristics including the depth to bedrock between Korea and western US. Based on the analysis results in this study and the prior research results for the Korean peninsula, new site classification system was developed by introducing the site period as representative criterion and the mean $V_S$ to a depth of shallower than 30 m as additional criterion, to reliably determine the ground motions and the corresponding design spectra taking into account the regional site characteristics in Korea.

• 지역과문화
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• v.7 no.1
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• pp.183-208
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• 2020

Presenting symbolic concepts consistent with the culture of the host country and international trends at international events will win the favor of the world and raise the image of the host country. The international event mascot symbolically represents the host country's unique culture, and is a good means to enhance the sense of belonging and pride of its members and to display the image of the host country in an outwardly. This study discussed the symbolic elements of the host country characteristics reflected in FIFA's World Cup event mascot. A total of 14 mascots of World Cup events were held from 1966 to 2018, and their materials can be divided into animals, plants, people and creations. The mascot was applied with the characteristic elements of regional specialties, the flag of the host country, symbolic attire, language of the hosting area, social issues and the mascot's dress, posture, props and expression characters of soccer events were used as symbolic elements. First of all, the implications of the research were that mascots were more strongly expressing the "football" signifying element, the theme of events, rather than regional characteristics. Second, the use of 'national flag' was highlighted among the elements of expressing regional characteristics. Third, 'animal' was preferred for mascot material. Fourth, mascots have become integrated with 'cultural perfumes' and play an extended role in raising social awareness. Implications derived from the classification of characteristics and symbol representation elements raised in this study will be used as a basis for the planning of international event mascots.

• Spatial Information Research
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• v.10 no.2
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• pp.331-343
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• 2002

Recently, as various fields of applications using space-borne imagery have been emphasized, interests on integrated analysis or fusion using multi-sources are also increasing. In this study, to investigate applicability of multiple imageries for further regional-scaled application, DN value analysis and multi-resolution classification by using KOMPSAT EOC imagery and Landsat 7 ETM+image data in the Namyangju-city area were performed, and then this classified results were compared to land-use thematic data at the same area. In case of classified results by using muff-resolution image data, it is shown that linear-type features can be easily extracted. furthermore, it is expected that multi-resolution classified image can be effectively utilized to urban environment analysis, according to results of similar pattern by comparative study based on multi-buffered zone analysis or so-called distance analysis along main road features in the study area.

• Biomedical Science Letters
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• v.25 no.1
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• pp.99-106
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• 2019

Amyloid positron emission tomography (PET) allows early and accurate diagnosis in suspected cases of Alzheimer's disease (AD) and contributes to future treatment plans. In the present study, a method of implementing a diagnostic system to distinguish ${\beta}$-Amyloid ($A{\beta}$) positive from $A{\beta}$ negative with objectiveness and accuracy was proposed using a machine learning approach, such as the Principal Component Analysis (PCA) and Support Vector Machine (SVM). $^{18}F$-Florbetaben (FBB) brain PET images were arranged in control and patients (total n = 176) with mild cognitive impairment and AD. An SVM was used to classify the slices of registered PET image using PET template, and a system was created to diagnose patients comprehensively from the output of the trained model. To compare the per-slice classification, the PCA-SVM model observing the whole brain (WB) region showed the highest performance (accuracy 92.38, specificity 92.87, sensitivity 92.87), followed by SVM with gray matter masking (GMM) (accuracy 92.22, specificity 92.13, sensitivity 92.28) for $A{\beta}$ positivity. To compare according to per-subject classification, the PCA-SVM with WB also showed the highest performance (accuracy 89.21, specificity 71.67, sensitivity 98.28), followed by PCA-SVM with GMM (accuracy 85.80, specificity 61.67, sensitivity 98.28) for $A{\beta}$ positivity. When comparing the area under curve (AUC), PCA-SVM with WB was the highest for per-slice classifiers (0.992), and the models except for SVM with WM were highest for the per-subject classifier (1.000). We can classify $^{18}F$-Florbetaben amyloid brain PET image for $A{\beta}$ positivity using PCA-SVM model, with no additional effects on GMM.

• The Korean Journal of Pain
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• v.32 no.2
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• pp.120-128
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• 2019

Background: We aimed to explore the American College of Rheumatology (ACR) 1990 and 2011 fibromyalgia (FM) classification criteria's items and the components of Fibromyalgia Impact Questionnaire (FIQ) to identify features best discriminating FM features. Finally, we developed a combined FM diagnostic (C-FM) model using the FM's key features. Methods: The means and frequency on tender points (TPs), ACR 2011 components and FIQ items were calculated in the FM and non-FM (osteoarthritis [OA] and non-OA) patients. Then, two-step multiple logistic regression analysis was performed to order these variables according to their maximal statistical contribution in predicting group membership. Partial correlations assessed their unique contribution, and two-group discriminant analysis provided a classification table. Using receiver operator characteristic analyses, we determined the sensitivity and specificity of the final model. Results: A total of 172 patients with FM, 75 with OA and 21 with periarthritis or regional pain syndromes were enrolled. Two steps multiple logistic regression analysis identified 8 key features of FM which accounted for 64.8% of variance associated with FM group membership: lateral epicondyle TP with variance percentages (36.9%), neck pain (14.5%), fatigue (4.7%), insomnia (3%), upper back pain (2.2%), shoulder pain (1.5%), gluteal TP (1.2%), and FIQ fatigue (0.9%). The C-FM model demonstrated a 91.4% correct classification rate, 91.9% for sensitivity and 91.7% for specificity. Conclusions: The C-FM model can accurately detect FM patients among other pain disorders. Re-inclusion of TPs along with saving of FM main symptoms in the C-FM model is a unique feature of this model.