• Korean Journal of Ichthyology
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• v.33 no.2
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• pp.126-141
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• 2021

Fauna of freshwater fish and community structure were investigated at 13 sites in the Deogyusan National Park, Korea from 2014 to 2018. During the period, a total of 8 families, 21 species, and 8,716 individuals of fishes were collected. The number of fish collected over the past five years from 2014 to 2018, were 17 species and 2,280 individuals, 17 species and 1,579 individuals, 17 species 1,905 individuals, 17 species and 1,384 individuals, and 15 species and 1,568 individuals, respectively. There were 13 Korean endemic species including Iksookimia koreensis and Coreoleuciscus splendidus, etc. Only in Wondangcheon Stream, two endangered species were identified, and Hemibarbus mylodon was collected continuously except in 2015, and Pseudopungtungia nigra was observed every year. And two exotic species such as Oncorhynchus masou masou and Oncorhynchus mykiss occurred in Gucheongdongcheon Stream sites. The dominant species was Rhynchocypris oxycephalus and the sub-dominant species was Zacco koreanus and there was no difference by year. The fish community structure of Deogyusan National Park was varied depending on the sites and the year. Most of the survey sites located upper stream where the river structure is Aa river type showed poor community analysis results. On the other hand, the upper-mid stream sites including the Bb type showed better results. As a result, the Wondangcheon Stream sites had the most diverse and stable community structure. Similarity dendrogram was divided into 4 groups, mainly reflecting the characteristics of the habitat. The flagship species of the Deogyusan National Park, Rhynchocypris kumgangensis, was constantly observed during the investigation period. Compared to the previous survey, the number of species increased from 2004 (12 species) and decreased from 2009 (22 species).

• Journal of Food Hygiene and Safety
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• v.37 no.6
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• pp.400-410
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• 2022

This study was performed to analyze the microbial contamination levels of three non-heated rice cake manufacturers in terms of seasonal manufacturing process and to investigate the effects of summertime soaking on contamination levels and temperature-controlled soaking in water on reduction in microbial levels. The total aerobic bacteria (TAB) ranged from 2.69 log CFU/g to 5.08 log CFU/g in the produce, but the microbial contamination increased sharply during soaking. The levels of TAB and coliforms during summer soaking were 7.01 and 3.96 log CFU/g, respectively, and this was significantly higher than those in other seasons. The contamination level was high in the subsequent freezing, with the TAB level (6.24 log CFU/g) exceeding the legal standard. The temperature of soaking water in summer increased from 19.1℃ to 26.8℃ after 12 h of soaking. The microbial contamination was significantly high commensurate with increased soaking time, and the TAB level in the frozen process exceeded the legal standard from 9 h of soaking. The use of ice packs to prevent the increase in temperature of the soaking water in summer resulted in maintenance of temperature at 20.1℃ for up to 12 h. The average TAB value in the freezing process was 4.42 log CFU/g after 12 h of soaking, and this is 1.77 log CFU/g lower than that before. Based on these results, it was determined that controlling the soaking time and water temperature are essential for the production of a safe unheated frozen rice cake. The safety of the HACCP system could be established by applying these preventive management standards.

• Journal of Practical Agriculture & Fisheries Research
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• v.24 no.4
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• pp.18-29
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• 2022

Five species of plants (Clerodendrum trichotomum Thunb., Angelica dahurica (Fisch. ex Hoffm.) Benth. & Hook. f. ex Franch. & Sav., Caryopteris incana (Thunb. ex Houtt.) Miq., Lonicera japonica Thunb., and Parasenecio auriculatus var. matsumurana Nakai) native to the clean area of Mt. Jiri were selected. The collection period was from May to September 2021, and the five species plants were collected in their native habitats with flowers in full bloom. The collected plants were extracted with 70% EtOH, and 17 kinds of polyphenol components were analyzed. Next, flowers, leaves, stems, and roots were separated from plants, extracted with 70% EtOH for each part and experiments were conducted on DPPH, ABTS, total polyphenols, and total flavonoids. The results are as follows. 1. It was found that there were a total of 8 kinds of polyphenols contained in 5 species of plants that are native to Mt. Jiri. Among the polyphenol components, chlorogenic acid was contained in 4 species of plants, and caffeic acid was contained in 2 species of plants. 2. As a result, the DPPH radical scavenging activity was the best in the stem of P. auriculata and the C. trichotomum was good regardless of the specific part. It was found that the activity-scavenging activity was good in the flowers of A. dahurica and the leaves of L. japonica. 3. The highest ABTS radical scavenging activity was C. trichotomum Thunb., whose EC₅₀ value was 38.73~66.28ppm. Next, the leaves and stems of L. japonica Thunb., A. dahurica and P. auriculata, and the leaves and stems of C. incana appeared in that order. 4. The highest total polyphenol content was 154.83mg GAE/g in the leaves of C. trichotomum, followed by about 130mg GAE/g in the flowers of C. trichotomum and P. auriculata. The lowest was 26.27mg GAE/g in the stems of A. dahurica.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.147-170
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• 2022

Although the number of patent which is one of the core outputs of technological innovation continues to increase, the number of low-value patents also hugely increased. Therefore, efficient evaluation of patents has become important. Estimation of patent lifespan which represents private value of a patent, has been studied for a long time, but in most cases it relied on a linear model. Even if machine learning methods were used, interpretation or explanation of the relationship between explanatory variables and patent lifespan was insufficient. In this study, patent lifespan (number of renewals) is predicted based on the idea that patent lifespan represents the value of the patent. For the research, 4,033,414 patents applied between 1996 and 2017 and finally granted were collected from USPTO (US Patent and Trademark Office). To predict the patent lifespan, we use variables that can reflect the characteristics of the patent, the patent owner's characteristics, and the inventor's characteristics. We build four different models (Ridge Regression, Random Forest, Feed Forward Neural Network, Gradient Boosting Models) and perform hyperparameter tuning through 5-fold Cross Validation. Then, the performance of the generated models are evaluated, and the relative importance of predictors is also presented. In addition, based on the Gradient Boosting Model which have excellent performance, Accumulated Local Effects Plot is presented to visualize the relationship between predictors and patent lifespan. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the evaluation reason of individual patents, and discuss applicability to the patent evaluation system. This study has academic significance in that it cumulatively contributes to the existing patent life estimation research and supplements the limitations of existing patent life estimation studies based on linearity. It is academically meaningful that this study contributes cumulatively to the existing studies which estimate patent lifespan, and that it supplements the limitations of linear models. Also, it is practically meaningful to suggest a method for deriving the evaluation basis for individual patent value and examine the applicability to patent evaluation systems.

• Sleep Medicine and Psychophysiology
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• v.28 no.2
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• pp.78-85
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• 2021

Objectives: When elderly patients show depressive symptoms, discrimination between depressive disorder and prodromal phase of Alzheimer's disease is important. We tested whether a quantitative electroencephalogram (qEEG) marker was associated with cerebral amyloid-β (Aβ) deposition in older adults with depression. Methods: Non-demented older individuals (≥ 55years) diagnosed with depression were included in the analyses (n = 63; 76.2% female; mean age ± standard deviation 73.7 ± 6.87 years). The participants were divided into Aβ+ (n = 32) and Aβ- (n = 31) groups based on amyloid PET assessment. EEG was recorded during the 7min eye-closed (EC) phase and 3min eye-open (EO) phase, and all EEG data were analyzed using Fourier transform spectral analysis. We tested interaction effects among Aβ positivity, condition (EC vs. EO), laterality (left, midline, or right), and polarity (frontal, central, or posterior) for EEG alpha band power. Then, the EC-to-EO alpha reactivity index (ARI) was examined as a neurophysiological marker for predicting Aβ+ in depressed older adults. Results: The mean power spectral density of the alpha band in EO phase showed a significant difference between the Aβ+ and Aβ- groups (F = 6.258, p = 0.015). A significant 3-way interaction was observed among Aβ positivity, condition, and laterality on alpha-band power after adjusting for age, sex, educational years, global cognitive function, medication use, and white matter hyperintensities on MRI (F = 3.720, p = 0.030). However, post-hoc analyses showed no significant difference in ARI according to Aβ status in any regions of interest. Conclusion: Among older adults with depression, increased power in EO phase alpha band was associated with Aβ positivity. However, EC-to-EO ARI was not confirmed as a predictor for Aβ+ in depressed older individuals. Future studies with larger samples are needed to confirm our results.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.128-139
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• 2022

This study aimed to investigate the tectonic setting of the volcanic edifice at Mt. Baekdu by analyzing petrochemical characteristics of Holocene felsic volcanic rocks distributed in the Baekdusan stratovolcano edifice and summit of the Cheonji caldera rim, as well as Pleistocene mafic rocks of the Gaema lava plateau and Changbaishan shield volcano edifice. During the early eruption phases, mafic eruption materials, with composition ranging from alkali basalt to trachybasalt, or from subalkaline (tholeiitic) basalt to basaltic andesite formed the Gaema lava plateau and Changbaishan shield volcanic edifice, whereas the Baekdusan stratovolcano edifice and Holocene tephra deposits near the summit of the Cheonji caldera comprises trachytic and rhyolitic compositions. Analysis results revealed bimodal compositions with a lack of 54-62 SiO₂, between the felsic and mafic volcanic rocks. This suggested that magmatic processes occurred at the locations of extensional tectonic settings in the crust. Mafic volcanic rocks were plotted in the field of within-plate volcanic zones or between within-plate alkaline and tholeiite zones on the tectonic discrimination diagram, and it was in good agreement with the results of the TAS diagram. Felsic volcanic rocks were plotted in the field of within-plate granite tectonic settings on discrimination diagrams of granitic rocks. None of the results were plotted in the field of arc islands or continental margin arcs. The primitive mantle-normalized spider diagram did not show negative (-) anomalies of Nb and Ti, which are distinctive characteristics of subduction-related volcanic rocks, but exhibited similar patterns of ocean island basalt. Trace element compositions showed no evidence of, magmatic processes related to subduction zones, indicating that the magmatic processes forming the Baekdusan volcanic field occurred in an intraplate environment. The distribution of shallow earthquakes in this region supports the results. The volcanic rocks of the Baekdusan volcanic field are interpreted as the result of intraplate volcanism originating from the upwelling of mantle material during the Cenozoic era.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.317-322
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• 2022

The rapid development of information technology is also bringing about many changes in the medical environment. In particular, it is leading the rapid change of medical image information systems using big data and artificial intelligence (AI). The prescription delivery system (OCS), which consists of an electronic medical record (EMR) and a medical image storage and transmission system (PACS), has rapidly changed the medical environment from analog to digital. When combined with multiple solutions, PACS represents a new direction for advancement in security, interoperability, efficiency and automation. Among them, the combination with artificial intelligence (AI) using big data that can improve the quality of images is actively progressing. In particular, AI PACS, a system that can assist in reading medical images using deep learning technology, was developed in cooperation with universities and industries and is being used in hospitals. As such, in line with the rapid changes in the medical image information system in the medical environment, structural changes in the medical market and changes in medical policies to cope with them are also necessary. On the other hand, medical image information is based on a digital medical image transmission device (DICOM) format method, and is divided into a tomographic volume image, a volume image, and a cross-sectional image, a two-dimensional image, according to a generation method. In addition, recently, many medical institutions are rushing to introduce the next-generation integrated medical information system by promoting smart hospital services. The next-generation integrated medical information system is built as a solution that integrates EMR, electronic consent, big data, AI, precision medicine, and interworking with external institutions. It aims to realize research. Korea's medical image information system is at a world-class level thanks to advanced IT technology and government policies. In particular, the PACS solution is the only field exporting medical information technology to the world. In this study, along with the analysis of the medical image information system using big data, the current trend was grasped based on the historical background of the introduction of the medical image information system in Korea, and the future development direction was predicted. In the future, based on DICOM big data accumulated over 20 years, we plan to conduct research that can increase the image read rate by using AI and deep learning algorithms.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.251-273
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• 2022

Recently, research on applying text analysis to deep learning has steadily continued. In particular, researches have been actively conducted to understand the meaning of words and perform tasks such as summarization and sentiment classification through a pre-trained language model that learns large datasets. However, existing pre-trained language models show limitations in that they do not understand specific domains well. Therefore, in recent years, the flow of research has shifted toward creating a language model specialized for a particular domain. Domain-specific pre-trained language models allow the model to understand the knowledge of a particular domain better and reveal performance improvements on various tasks in the field. However, domain-specific further pre-training is expensive to acquire corpus data of the target domain. Furthermore, many cases have reported that performance improvement after further pre-training is insignificant in some domains. As such, it is difficult to decide to develop a domain-specific pre-trained language model, while it is not clear whether the performance will be improved dramatically. In this paper, we present a way to proactively check the expected performance improvement by further pre-training in a domain before actually performing further pre-training. Specifically, after selecting three domains, we measured the increase in classification accuracy through further pre-training in each domain. We also developed and presented new indicators to estimate the specificity of the domain based on the normalized frequency of the keywords used in each domain. Finally, we conducted classification using a pre-trained language model and a domain-specific pre-trained language model of three domains. As a result, we confirmed that the higher the domain specificity index, the higher the performance improvement through further pre-training.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.133-149
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• 2022

Existing domestic studies on estimating rice yield were mainly implemented at the level of cities and counties in the entire nation using MODIS satellite images with low spatial resolution. Unlike previous studies, this study tried to estimate rice yield at the level of eup-myon-dong in Gimje-si, Jeollabuk-do using Sentinel-2 satellite images with medium spatial resolution, rainfall and soil data, and then to evaluate its accuracy. Five vegetation indices such as NDVI, LAI, EVI2, MCARI1 and MCARI2 derived from Sentinel-2 images of August 1, 2018 for Gimje-si, Jeollabuk-do, rainfall and paddy soil-type data were aggregated by the level of eup-myon-dong and then rice yield was estimated with gamma generalized linear model, an expanded variant of multi-variate regression analysis to solve the non-normality problem of dependent variable. In the rice yield model finally developed, EVI2, rainfall days in September, and saline soils ratio were used as significant independent variables. The coefficient of determination representing the model fit was 0.68 and the RMSE for showing the model accuracy was 62.29kg/10a. This model estimated the total rice production in Gimje-si in 2018 to be 96,914.6M/T, which was very close to 94,470.3M/T the actual amount specified in the Statistical Yearbook with an error of 0.46%. Also, the rice production per unit area of Gimje-si was amounted to 552kg/10a, which was almost consistent with 550kg/10a of the statistical data. This result is similar to that of the previous studies and it demonstrated that the rice yield can be estimated using Sentinel-2 satellite images at the level of cities and counties or smaller districts in Korea.

• Journal of Nutrition and Health
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• v.56 no.2
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• pp.155-167
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• 2023

Purpose: This study investigates the association between seafood consumption and frailty according to gender in the Korean elderly. Methods: Cross-sectional data from the Seventh (2016-2018) Korea National Health and Nutrition Examination Survey was procured for this study. Data from 3,675 subjects (1,643 men and 2,032 women) aged ≥ 65 years were analyzed. Levels of seafood intake were assessed by a one-day 24-hour dietary recall, and subjects were classified into three tertiles by gender according to frailty phenotype: robust, pre-frail, and frail. Multinomial logistic regression analysis was performed to clarify the association between seafood consumption and frailty for each gender. Results: The prevalence of frailty was determined as 13.4% for men and 29.7% for women. Participants with a higher seafood intake had higher intakes of grains, fruits, and vegetables, while the intake of meat was significantly lower. In both men and women, the group with higher seafood intake showed higher energy and micronutrient intakes. The frail prevalence and frailty score were significantly low in the highest tertiles of seafood consumption compared to the lowest tertile in men and women (p < 0.001). After adjusting for confounder, the highest tertile of seafood consumption showed a decreased risk of frailty compared to the lowest tertile only in women (hazard ratio [HR], 0.50; 95% confidence interval [CI], 0.32-0.78; p-trend = 0.008 vs. HR, 0.52; 95% CI, 0.32-0.83; p-trend = 0.008; respectively). Conclusion: Results of this study suggest that seafood consumption potentially decreases the risk of frailty in the elderly.