• Journal of the Society of Cosmetic Scientists of Korea
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• v.48 no.3
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• pp.287-293
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• 2022

Gray hair is a representative sign of aging. Intrinsic aging, stress, and the external environment cause hair graying. Stress is known to be a major factor in the early onset of hair graying. We previously found that Pueraia lobata root extract (PLRE) can prevent hair graying by promoting melanin formation. However, it remains unknown whether PLRE can prevent hair graying induced by conditions of stress. In this study, we confirmed the effect of PLRE on stress-induced hair graying. A reporter cell line was newly constructed to confirm the expression of microphthalamia-associated transcription factor (MITF), the main transcription factor for melanin production. MITF expression and melanin pigmentation were reduced in human hair follicle tissue treated with the stress hormone cortisol or H₂O₂ to induce oxidative stress. PLRE treatment restored MITF expression and increased the amount of melanin pigment in the hair follicle. The expression of Tyrosinase related proteins-2 (TRP-2), a melanin synthesis enzyme in the hair follicle, also increased. In conclusion, PLRE can effectively prevent the inhibition of melanin synthesis by stress hormones and oxidative stress.

• Journal of Environmental Impact Assessment
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• v.31 no.1
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• pp.1-10
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• 2022

This study was carried out to understand the water quality characteristics of the initial stormwater runoff and the origin of soluble pollutants according to various rainfall conditions from a non-point source reducing facility. The water sample from this study was collected among 10 collection facilities in the G-drainage area. Specifically, five of the collection points including #1, #5, #8, #9, and #10 were reported with unknown water inflow even during non-rain conditions. The leakage characteristics of non-point pollutants from the collection facilities were then able to identify accordingly. The water quality characteristics of the stormwater runoff from the collection facilities were strongly affected by the amounts of rainfalls. The average concentrations of EC, BOD, TOC, and TN during non-rain were found to be higher than their concentrations during rain; on the other hand, the average concentrations of DO were found to be lower than its concentrations during rain. In addition, the distribution of organic components existing in the effluent of collection facilities were identified based on the dissolved organic matter analysis. In summary, the stormwater runoff was highly affected by pollutants flowing from the surrounding environment, and the amounts of hard-to-decompose humic substances were greatly increased in the collection facilities due to rain.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.17-27
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• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

• Korean Journal of Environment and Ecology
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• v.34 no.1
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• pp.1-8
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• 2020

This study conducted a full survey of the goral population using sensor cameras to identify the exact habitat of the gorals that inhabit Odaesan National Park and for restoration and habitat management-focused conservation projects following the population growth. We surveyed Odaesan National Park for a year in 2018 and selected18 grids (2km×2km) first based on the survey results. We then further divided each grid into four small grids (1km×1km) and installed a total of 62 sensor cameras in 38 small girds divided by four grids(1km×1km). The survey resulted in a total of 5,096 photographed wild animals, 2,268 of which were gorals, and the analysis by the classification table of goral (horn shape (Ⓐ), ring pattern (Ⓑ), ring formation ratio (Ⓒ), and facial color (Ⓓ)) identified a total of 95 animals. The ratio of male and female was 35 males (36.8%), 46 females (48.4%), and 14 sex unknowns (14.7%), while the ratio of female and male excluding sex unknowns was 4 (male):6 (female). The horn shape (Ⓐ) and face color (Ⓓ) were the important factors for distinguishing male and female and identifying individuals. The analysis of the correlation of 81 individuals, excluding 14 individuals of unknown sex, showed a significant difference (r=-0.635, p<0.01). Since the goral population in Odaesan National Park has reached a minimum viable population, it is necessary to change the focus of the management policy of Odaesan National Park from restoration to conservation.

• Economic and Environmental Geology
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• v.51 no.5
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• pp.409-428
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• 2018

Yeongdong area is located on the border zone between Precambrian Yeongnam massif and central southeastern Ogcheon metamorphic belt, in which Cretaceous Yeongdong sedimentary basin exists. Main geology in this area consists of Precambrian Sobaeksan gneiss complex, Mesozoic igneous and sedimentary rocks and Quaternary alluvial deposits. Above this, age-unknown Ogcheon Supergroup, Paleozoic sedimentary rocks and Tertiary granites also occur in small scale in the northwestern part. This study focuses on the link between the various geology and Rn concentrations in groundwater. For this, twenty wells in alluvial/weathered zone and sixty bedrock aquifer wells were used. Groundwater sampling campaigns were twice run at wet season in August 2015 and dry season in March 2016. Some wells placed in alluvial/weathered part of Precambrian metamorphic rocks and Jurassic granite terrains, as well as Cretaceous porphyry, showed elevated Rn concentrations in groundwater. However, detailed geology showed the distinct feature that these high-Rn groundwaters in metamorphic and granitic terrains are definitely related to proximity of aquifer rocks to Cretaceous porphyry in the study area. The deeper wells placed in bedrock aquifer showed that almost the whole groundwaters in biotite gneiss and schist of Sobaeksan gneiss complex and in Cretaceous sedimentary rocks of Yeongdong basin have low level of Rn concentrations. On the other hand, groundwaters occurring in rock types of granitic gneiss or granite gneiss among Sobaeksan gneiss complex have relatively high Rn concentrations. And also, groundwaters occurring in the border zone between Triassic Cheongsan granites and two-mica granites, and in Jurassic granites neighboring Cretaceous porphyry have relatively high Rn concentrations. Therefore, to get probable and meaningful results for the link between Rn concentrations in groundwater and surrounding geology, quite detailed geology including small-scaled dykes or vein zones should be considered. Furthermore, it is necessary to take account of the spatial proximity of well location to igneous rocks associated with some mineralization/hydrothermal alteration zone rather than in-situ geology itself.

• Journal of the Korean Society of Groundwater Environment
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• v.6 no.4
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• pp.194-205
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• 1999

Hydrogeochemical variation and environmental isotope at the some abandoned metal mine (Sanggok, Keumsil, Jangpung and Samdeok) creeks of the Hwanggangri mining district were carried out based upon the physicochemical properties for surface water collected of February in 1998. Hydrogeochemical composition of the all water samples are characterized by the relatively significant enrichment of Ca$^{2}$, alkaline ions, N $O_3$$^{－}$ and Cl$^{－}$ in normal surface water, whereas the surface waters near the mining area are relatively enriched in Ca$^{2+$, Mg$^{2＋}$, heavy metals. HC $O_3$$^{－}$ and S $O_4$$^{2－}$. Surface waters of the mining creek have low pH, high EC and extremely high concentrations of TDS compared with surface water of the non-mining creeks. The range of $\delta$D and $\delta$$^{18}$O values (SMOW) in the waters are shown in －65.0 to－71.2$\textperthousand$ and －9.1 to－10.2$\textperthousand$. The d($\delta$D－$\delta$$^{18}$O) value with those of water samples ranged from 7.3 to 10.9. These $\delta$D and $\delta$$^{18/}$ of the acid mine water are more heavy values than those of surface water. The values have revealed the positive correlation between isotopic compositions and major elements, because those $\delta$D and $\delta$$^{18}$O values increase with increasing TDS. HC $O_3$$^{－}$ , S $O_4$$^{2－}$ and Ca$^{2＋}$ concentration. Using WATEQ4F, saturation index of albite calcite, dolomite and mostly clay minerals in water of the mining area show undersaturated and progressively evolved toward the equilibrium condition due to fresh water mixing, however, surface waters of the non-mining area are nearly saturated and/or supersaturated. Geochemical modeling showed that mostly toxic heavy metals within water in the mining creek may exist largely in the from of metal-sulfate (MS $O_4$$^{2－}$), free metal (M$^{2＋}$/), C $O_3$$^{－}$ and/or OH$^{－}$ complex ions. Based on the geology, water chemistry and environmental istopic data the water compositions from the Sanggok and Keumsil mine creek (consist mainly of Cambro-Ordovician carbonate rocks of the Cho-seon Supergroup) show higher PH, Ca$^{2＋}$, Mg$^{2＋}$ , HC $O_3$$^{－}$ and more heavy $\delta$D and $\delta$$^{18}$O values than those from the Jangpung and Samdeok mine creek (consist of age -unknown metasedimentary rocks of the Ogcheon Supergroup and/or Jurassic grani-toids), but each of these waters represents a similar hydrogeochemical evolution path by the mine water mixing.

• Journal of Wetlands Research
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• v.5 no.2
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• pp.15-32
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• 2003

The ecological study on seven wetlands of Haman area in Kyungsangnamdo, Korea, was carried out. In especial, the biological data of the sites were unknown. In this study, water quality including water temperature, pH, DO, COD, T-N, T-P, SS were tested. On the survey of plants and animals, vegetation and flora were investigated and the fauna of insects, fish, and amphibians were studied on each wetland. Water of wetland Oksu was heavily polluted and wetlands Pyungy and Dodulyangy were relatively clean. The water pollution was most severe in winter at all of the wetlands. Plant communities were classified into 9 natural communities and 1 artificial community. On the vegetation, wetland Sugok showed the highest plant taxa, and 41 families, 78 species and 16 varieties were classified. There was remarkable difference in number of plant taxa. The difference may be caused by the variances of wetland sizes, the influence from terrestrial environment. Wetland Sugok showed most rich insect fauna, and 10 orders, 76 families 224 species and 1082 individuals were identified. The species diversity was 2.05 and the species richness was 73.49. Wetland Ddun showed poor insect fauna, and 6 orders, 23 families, 29 species and 81 individuals were identified. Total collected fish were 4 orders, 7 families and 11 species. The fish fauna was most rich in wetlands Oksu and Pyungy, but poor in wetland Unan. Total collected amphibians were 2 orders, 3 families and 4 species.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Women's Health Nursing
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• v.4 no.1
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• pp.161-178
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• 1998

In spite of the great progress of the theory and skill of the Nursing Care & Medical area in relation to pregnancy, nurses in clinics face up to many challenges in maternity nursing care areas. The reason is that the mobility and mortality of mothers was sharply decreased and the unknown high-risk diseases of pregnancy woman in the past is made public. That's why it is difficult to meet the pregnancy woman in natural process from pregnancy to delivery in recently. Admission rooms are filled with high-risk pregnancy women. As a matter of fact, we have done nursing care into the surface symptoms and diseases of high-risk pregnancy women so far. We have been indifferent to a long period hospitalization, separation from family, and conflict of repeated examination. Therefore, it is widely spread to understand the emotional conflict experienced by high-risk pregnancy women and to need for nursing intervention to bring up about emotional support and the ability of perception in psychological crisis. Although the pregnancy woman judged in high-risk should carry out normal task of pregnancy, she have to be confronted with secondary risk situation. The health of self & fetus threatened by the risk situation could be decreased through care plan, but psychological stress increases. Therefore, the pregnancy brings into non-control state. It is important to ask that what the hospitalized pregnancy women in high-risk think of themselves status. Because misunderstanding or serious anxiety of themselves status put into mother and fetus in danger. And adaptation mode makes all the difference. I would like to consider how nurses could deal with this high-risk circumstances in the position of pregnancy woman on the basis of the above fact. This study uses phenomenological method to suggest the basis material for nurses to do nursing intervention in view of pregnancy woman. Because this method understands the nature of true life of pregnancy woman throughly. The phenomenological method is the sources to describe or explain affluently the process generated in confirmation areas and environment and is the application for readers to understand and recognize clinic reality and then apply this method to reasoning study place or other places. Specifically, the phenomenon study method, one of the phenomenological method, is applied. The use of that method is to describe and generalize the experience in environment exactly. The study of this study is as follows : Among 187 descriptive stamens from 8 study participants are classified into 42 theme cluster at the stage of the first analysis. Those theme is categorized into 8 sub-subjects such as anxiety of uncertainty, foreknowledge about risk circumstance, will power about overcome, unsettled feeling about hospital, relief, optimistic thought, family support, and indifferences. At the last stage of analysis, those things are categorized into 3 subjects. When high-risk pregnancy woman foretell the situation, they feel unsettlement about uncertainty and untrust feeling about hospital. But they are ease with family support and hospital support. On the other hand, they express indifferent 3-way structure response to the situation having will of overcome and exceeding optimistic thought. In those statements, the experience by pregnancy woman shows 3 respect subjects. 1. They are anxious of this situation and are in desperation and don't recognize their role to be carried out 2. They think of this situation as normal process of pregnancy and are not concerned that this can give themselves and fetus fatal damage. 3. The pregnancy women will never confront this situation. This study shows the pregnancy woman has anxiety and optimistic relief about the situation, and ignores and optimistic relief about the situation, and ignores many things. Therefore, nurses in clinic should give pregnancy woman knowledge and information about the high-risk and help them to deal with the situation spontaneously. High-risk pregnancy woman should have the care plan in respect of the right perception. And the nurse know that their support help out pregnancy woman overcome the crisis in this respect of the special nursing intervention.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.1
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• pp.27-40
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• 2022

Building self-sustainable rural infrastructure and environment through smart digital agriculture technology innovation is one of the major goals of the Korean agricultural administration as a part of the nation's 4^th industry revolution. To identify areas for improving and effectively investing in the acceleration of rural development, 207 experts in the areas of crop science and smart digital agriculture technology were interviewed for their opinions and suggestions on 22 questions designed to recognize fundamental agricultural issues to be addressed and solutions to advance technology innovation and rural development. Majority of the participants expected smart digital agriculture technologies to resolve major agricultural issues and help build a better rural environment. To overcome technology gaps and resolve issues more effectively, further investment in training new technology experts and building stronger agricultural technology infrastructure is urgent, and persistent and systematic support from agricultural administration appears to be the key for accelerating the process. While the leading global groups of both public and private sectors have advanced their technologies beyond the field application stage, most of the Korean technologies remain at the early pilot stage. Aging population and lack of labor in rural areas, unknown future climate change, and challenges in sustainable rural development are expected to be resolved by smart digital agriculture technologies. Technological innovations by research institutes should be promptly deployed in the crop production field, and farm training systemically organized by local technology centers can accelerate farming revolution. Standardization of equipment and data systems is another key to the success of digitalization of food crop production and food supply chains nationwide.