• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.73-81
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• 2024

This study compared the cortical thickness of patients with mood disorders and a control group to assess structural abnormalities. A retrospective study was conducted from September 2020 to August 2022 at the Department of Psychiatry, P Hospital in Yangsan, Gyeongsangnam-do. The study included 44 individuals diagnosed with mood disorders and 59 healthy individuals without any pathological lesions. The 3D-T1 MPRAGE images obtained from magnetic resonance imaging examinations were utilized, and FreeSurfer software was employed to measure cortical thickness. Statistical analysis involved independent samples t-tests to measure the differences in means between the two groups, and Cohen's d test was used to compare the effect sizes of the differences. Furthermore, the correlation between the measured average cortical thickness and Positive and Negative Syndrome Scale scores was analyzed. The research results revealed that patients with mood disorders exhibited decreased cortical thickness compared to the normal control group in both superior frontal regions, both rostral middle frontal regions, both caudal middle frontal regions, both pars opercularis, pars orbitals, pars triangularis regions, both superior temporal regions, both inferior temporal regions, both lateral orbitofrontal regions, both medial orbitofrontal regions, both fusiform regions, both posterior cingulate regions, both isthmus cingulate regions, both superior parietal regions, both inferior parietal regions, both supramarginal regions, left postcentral region, right bank of the superior temporal sulcus region, right middle temporal region, right rostral anterior cingulate region, and right insula region. Among them, regions that showed differences with effect sizes of 0.8 or higher were left fusiform (d=0.82), pars opercularis (d=0.94), superior frontal (d=0.88), right lateral orbitofrontal (d=0.85), and pars orbitalis (d=0.89). Additionally, there was a weak negative correlation between PANSS scores and average cortical thickness in both the left hemisphere (r=-0.234) and right hemisphere (r=-0.230). These findings are expected to be helpful in identifying areas of cortical thickness reduction in patients with mood disorders compared to healthy individuals and understanding the relationship between symptom severity and cortical thickness changes.

• Research in Plant Disease
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• v.30 no.2
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• pp.139-147
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• 2024

Erwinia amylovora is a gram-negative plant pathogen that causes fire blight in apple and pear trees, resulting in significant damage worldwide. In this study, we monitored the emergence of fire blight from 2019 to 2023 to determine the emergence patterns and the factors affecting the outbreak of the disease. As a result of the 5-year survey on the emergence of fire blight, a total of 2,029 cases have emerged, mostly in apple trees of 1,378 cases (67.9%) followed by 645 cases (31.8%) in pear trees, and from quince, hawthorn, and mountain ash trees. Fire blight appeared in specific areas of Gyeonggi, Chungnam, Gangwon, and Chungbuk provinces in 2019, but spread to Andong and Yesan in 2021, Muju and Bonghwa in 2023. In 2020 and 2021, there were 744 and 618 cases of fire blight outbreaks, respectively, compared to other years (188-245 cases/year). Notably, 914 of these cases were observed in apple trees from May to July, with 667 cases reported in Chungju and Jecheon. The incidence of fire blight was positively correlated with the daily maximum temperatures and rainy days in January and February, as well as the rainy days in May and June. The average age of the diseased pear trees was 25 years, higher than the 10-year average age of the apple trees. This study provides fundamental information to understand the status and factors affecting the fire blight emergence in Korea. Prevention measures should be established through continuous analysis of the status of fire blight.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.295-305
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• 2024

This study aims to analyze the micro-sedimentary structures of the Hwangdo tidal flats using ultra-high resolution unmanned aerial vehicle (UAV) data. Tidal flats, located in the transitional area between land and sea, constantly change due to tidal activities and provide a unique environment important for understanding sedimentary processes and environmental conditions. Traditional field observation methods are limited in spatial and temporal coverage, and existing satellite imagery does not provide sufficient resolution to study micro-sedimentary structures. To overcome these limitations, high-resolution images of the Hwangdo tidal flats in Chungcheongnam-do were acquired using UAVs. This area has experienced significant changes in its sedimentary environment due to coastal development projects such as sea wall construction. From May 17 to 18, 2022, sediment samples were collected from 91 points during field surveys and 25 in-situ points were intensively analyzed. UAV data with a spatial resolution of approximately 0.9 mm allowed identifying and extracting parameters related to micro-sedimentary structures. For mud cracks, the length of the major axis of the polygons was extracted, and the wavelength and ripple symmetry index were extracted for ripple marks. The results of the study showed that in areas with mud content above 80%, mud cracks formed at an average major axis length of 37.3 cm. In regions with sand content above 60%, ripples with an average wavelength of 8 cm and a ripple symmetry index of 2.0 were formed. This study demonstrated that micro-sedimentary structures of tidal flats can be effectively analyzed using ultra-high resolution UAV data without field surveys. This highlights the potential of UAV technology as an important tool in environmental monitoring and coastal management and shows its usefulness in the study of sedimentary structures. In addition, the results of this study are expected to serve as baseline data for more accurate sedimentary facies classification.

• Korean Journal of Ecology and Environment
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• v.57 no.1
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• pp.1-16
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• 2024

Most wetlands worldwide have suffered from extensive human exploitation. Unfortunately they have been less explored compared to river and lake ecosystems despite their ecological importance and economic values. This is the same case in Korea. This study was aimed to estimate the assemblage attributes and distribution characteristics of benthic macroinvertebrates for fifty wetlands distributed throughout subtropical Jeju Island in 2021. A total of 133 taxa were identified during survey periods belonging to 53 families, 19 orders, 5 classes and 3 phyla. Taxa richness ranged from 4 to 31 taxa per wetland with an average of 17.5 taxa. Taxa richness and abundance of predatory insect groups such as Odonata, Hemiptera and Coleoptera respectively accounted for 67.7% and 68.2% of the total. Among them Coleoptera were the most diverse and abundant. Taxa richness and abundance did not significantly differ from each wetland type classified in accordance with the National Wetland Classification System. There were three endangered species (Clithon retropictum, Lethocerus deyrolli and Cybister (Cybister) chinensis) and several restrictively distributed species only in Jeju Island. Cluster analysis based on the similarity in the benthic macroinvertebrate composition largely classified 50 wetlands into two major clusters: small wetlands located in lowland areas and medium-sized wetlands in middle mountainous regions. All cluster groups displayed significant differences in wetland area, long axis, percentage of fine particles and macrophyte composition ratio. Indicator Species Analysis selected 19 important indicators with the highest indicator value of Ceriagrion melanurum at 63%, followed by Noterus japonicus (59%) and Polypylis hemisphaerula (58%). Our results are expected to provide fundamental information on the biodiversity and habitat environments for benthic macroinvertebrates in wetland ecosystems, consequently helping to establish conservation and restoration plans for small wetlands relatively vulnerable to human disturbance.

• The Journal of Korean Society for School & Community Health Education
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• v.25 no.2
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• pp.59-70
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• 2024

Objectives: The purpose of this study is to analyze each country's infectious disease response capacities and, based on this, find areas for improvement in Korea's infectious disease management response. Methods: First, the capacity to respond to the COVID-19 infectious disease was analyzed by country using the SPAR scores of 96 countries around the world released by WHO in 2022. Second, we analyzed each country's specific COVID-19 quarantine performance using Our World in Data and the Global Health Security Index (GHSI). Results: First, the quarantine intensity index on January 24, 2021 was the highest in the Southeast Asia branch at 67.6, which had strong quarantine measures, and the lowest at 44.5 in the Africa branch. As of December 31, 2022, the quarantine intensity index in Europe was significantly lowered to 11.6. Second, the factor that influenced the SPAR indicator on the total number of patients per million population was national laboratory (C4), p=.027, and the factor that influenced the total number of deaths per million population was infection prevention and control (C9), p=.005., Risk Communication and Community Participation (C10) p=.040. The influential factor on GDP per capita was infection prevention and control (C9) p=.009, and the influential factor on GHSI was infection prevention and control (C9) p=.002. Conclusion: The research findings indicate that it was difficult to find a correlation between the SPAR, which is each country's self-assessment of their infectious disease capacities, and the number of COVID-19 cases or the intensity of pandemic responses. However, mortality rates, as well as factors such as the Global Health Security Index (GHSI) and national income, appear to be somewhat influenced. For future improvements in infectious disease management and response in our country, it is necessary to develop pandemic strategies that can reduce socio-economic costs based on more scientific and reliable data like JEE or GHSI, especially in preparation for potential unknown emerging infectious diseases. Based on this, proactive decision-making led by a control tower of experts and effective health communication are also required to respond to public health crises at a national level.

• Korean Journal of Environmental Biology
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• v.41 no.4
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• pp.482-496
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• 2023

Many changes in the scale and structure of the Korean rice cropping system have been made over the past few decades. Still, insufficient research has been conducted on the sustainability of this system. This study analyzed changes in the Korean rice cropping system's sustainability from a system ecology perspective using an emergy approach. For this purpose, an emergy table was created for the Korean rice cropping system in 2011, 2016, and 202, and an emergy-based indicator analysis was performed. The emergy analysis showed that the total emergy input to the rice cropping system decreased from 10,744E+18 sej year^-1 to 8,342E+18 sej year^-1 due to decreases in paddy field areas from 2011 to 2021, and the proportion of renewable resources decreased by 1.4%. The emergy input per area (ha) was found to have decreased from 13.13E+15 sej ha^-1 year^-1 in 2011 to 11.89E+15 sej ha^-1 year^-1 in 2021, and the leading cause was a decrease in nitrogen fertilizer usage and working hours. The amount of emergy used to grow 1 g of rice stayed the same between 2016 and 2021 (specific emergy: 13.3E+09 sej g^-1), but the sustainability of the rice cropping system (emergy sustainability index, ESI) continued to decrease (2011: 0.107, 2016: 0.088, and 2021: 0.086). This study provides quantitative information on the emergy input structure and characteristics of Korean rice cropping systems. The results of this study can be used as a valuable reference in establishing measures to improve the ecological sustainability of the Korean rice cropping system.

• Korean Journal of Remote Sensing
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• v.40 no.4
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• pp.387-396
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• 2024

Most very high-resolution (VHR) satellite images provide rational polynomial coefficients (RPC) data to facilitate the transformation between ground coordinates and image coordinates. However, initial RPC often contains geometric errors, necessitating correction through matching with ground control points (GCPs). A GCP chip is a small image patch extracted from an orthorectified image together with height information of the center point, which can be directly used for geometric correction. Many studies have focused on area-based matching methods to accurately align GCP chips with VHR satellite images. In cases with seasonal differences or changed areas, edge-based algorithms are often used for matching due to the difficulty of relying solely on pixel values. However, traditional edge extraction algorithms,such as canny edge detectors, require appropriate threshold settings tailored to the spectral characteristics of satellite images. Therefore, this study utilizes deep learning-based edge information that is insensitive to the regional characteristics of satellite images for matching. Specifically,we use a pretrained pixel difference network (PiDiNet) to generate the edge maps for both satellite images and GCP chips. These edge maps are then used as input for normalized cross-correlation (NCC) and relative edge cross-correlation (RECC) to identify the peak points with the highest correlation between the two edge maps. To remove mismatched pairs and thus obtain the bias-compensated RPC, we iteratively apply the data snooping. Finally, we compare the results qualitatively and quantitatively with those obtained from traditional NCC and RECC methods. The PiDiNet network approach achieved high matching accuracy with root mean square error (RMSE) values ranging from 0.3 to 0.9 pixels. However, the PiDiNet-generated edges were thicker compared to those from the canny method, leading to slightly lower registration accuracy in some images. Nevertheless, PiDiNet consistently produced characteristic edge information, allowing for successful matching even in challenging regions. This study demonstrates that improving the robustness of edge-based registration methods can facilitate effective registration across diverse regions.

• The Korean Journal of Quaternary Research
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• v.14 no.1
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• pp.7-31
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• 2000

Quaternary Geological and geophysical investigation was performed at the Eurimji reservoir of Jaechon City in order to interprete depositional environment and genesis of lake sediments. For this purpose, echo sounding, bottom sampling and columnar sampling by drilling on board and GPR survey were employed for a proper field investigation. Laboratory tests cover grain size population analysis, pollen analysis and $^{14}C$ datings for the lake sediments. The some parts of lake bottom sediments anthropogenically tubated and filled several times to date, indicating several mounds on the bottom surface which is difficult to explain by bottom current. Majority of natural sediments were accumulated both as rolling and suspended loads during seasonal flooding regime, when flash flow and current flow are relatively strong not only at bridge area of the western part of Eurimji, connected to stream valley, but at the several conduit or sewage system surrounding the lake. Most of uniform suspend sediments are accumulated at the lake center and lower bank area. Some parts of bottom sediments indicate the existence of turbid flow and mudflow probably due to piezometric overflowing from the lake bottom, the existence of which are proved by CM patterns of the lake bottom sediments. The columnar samples of the lake sediments in ER-1 and ER-3-1 boreholes indicate good condition without any human tubation. The grain size character of borehole samples shows poorly sorted population, predominantly composed of fine sand and muds, varying skewness and kurtosis, which indicate multi-processed lake deposits, very similar to lake bottom sediments. Borehole columnar section, echo sounding and GPR survey profilings, as well as processed data, indicate that organic mud layers of Eurimji lake deposits are deeper and thicker towards lower bank area, especially west of profile line-9. In addition the columnar sediments indicate plant coverage of the Eurimji area were divided into two pollen zones. Arboreal pollen ( AP) is predominant in the lower pollen zone, whreas non-aboreal pollen(NAP) is rich in the upper pollen zone. Both of the pollen zones are related to the vegetation coverage frequently found in coniferous and deciduous broad-leaved trees(mixed forest) surrounded by mountains and hilly areas and prevailing by aquatic or aquatic margin under the wet temperate climate. The $^{14}C$ age of the dark gray organic muds, ER1-12 sample, is 950$\pm$40 years B.P. As the sediments are anthropogenetically undisturbed, it is assumed that the reliability of age is high. Three $^{14}C$ ages of the dark gray organic muds, including ER3-1-8, ER3-1-10, ER3-1-11 samples, are 600$\pm$30 years B.P., 650$\pm$30 years B.P., 800$\pm$40 years B.P. in the descending order of stratigraphic columnar section. Based on the interpretation of depositional environments and formation ages, it is proved that Eurimji reservoir were constructed at least 950$\pm$40 years B.P., the calibrated ages of which ranges from 827 years, B.P. to 866 years B.P. Ancient people utilize the natural environment of the stream valley to meet the need of water irrigation for agriculture in the local valley center and old alluvium fan area.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of Technology Innovation
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• v.17 no.1
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• pp.1-48
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• 2009

Recently we have found some symptoms that R&D fiscal incentives might not work well what it has intended through the analysis of current statistics of firm's R&D data. Firstly, we found that the growth rate of R&D investment in private sector during the recent decade has been slowdown. The average of growth rate (real value) of R&D investment is 7.1% from 1998 to 2005, while it was 13.9% from 1980 to 1997. Secondly, the relative share of R&D investment of SME has been decreased to 21%('05) from 29%('01), even though the tax credit for SME has been more beneficial than large size firm, Thirdly, The R&D expenditure of large size firms (besides 3 leading firms) has not been increased since late of 1990s. We need to find some evidence whether fiscal incentives are effective in increasing firm's R&D investment. To analyse econometric model we use firm level unbalanced panel data for 4 years (from 2002 to 2005) derived from MOST database compiled from the annual survey, "Report on the Survey of Research and Development in Science and Technology". Also we use fixed effect model (Hausman test results accept fixed effect model with 1% of significant level) and estimate the model for all firms, large firms and SME respectively. We have following results from the analysis of econometric model. For large firm: i ) R&D investment responds elastically (1.20) to sales volume. ii) government R&D subsidy induces R&D investment (0.03) not so effectively. iii) Tax price elasticity is almost unity (-0.99). iv) For large firm tax incentive is more effective than R&D subsidy For SME: i ) Sales volume increase R&D investment of SME (0.043) not so effectively. ii ) government R&D subsidy is crowding out R&D investment of SME not seriously (-0.0079) iii) Tax price elasticity is very inelastic (-0.054) To compare with other studies, Koga(2003) has a similar result of tax price elasticity for Japanese firm (-1.0036), Hall((l992) has a unit tax price elasticity, Bloom et al. (2002) has $-0.354{\sim}-0.124$ in the short run. From the results of our analysis we recommend that government R&D subsidy has to focus on such an areas like basic research and public sector (defense, energy, health etc.) not overlapped private R&D sector. For SME government has to focus on establishing R&D infrastructure. To promote tax incentive policy, we need to strengthen the tax incentive scheme for large size firm's R&D investment. We recommend tax credit for large size film be extended to total volume of R&D investment.