• Title/Summary/Keyword: network science

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Integrated Study on the Factors Influencing Sustainable Innovation Cluster of Pangyo Techno Valley (판교테크노벨리의 지속가능한 혁신 클러스터 영향요인에 관한 통합연구)

  • Park, Jeong Sun;Park, Sang Hyeok;Hong, Sung Sin
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.15 no.1
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    • pp.71-94
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    • 2020
  • Korea's innovation cluster policy has been implemented since 2005 with the goal of balanced regional development. The purpose of this study is to investigate the factors affecting the sustainability of innovative cluster tenants by using Pangyo Techno Valley as an example. Pangyo Techno Valley was established under the leadership of the local government (Gyeonggi-do) rather than the central government and it is called "Silicon Valley of Korea" and "Asia Silicon Valley" and is becoming more representative. The growing number of companies in Pangyo Techno Valley decreased in 2017 compared to 2016. This is because Pangyo Techno Valley's business ecosystem will change from 2019. In this paper, quantitative and qualitative studies were conducted to investigate the influencing factors. Quantitative research was conducted based on the survey and qualitative research was applied through interviews. The quantitative research examined the factors affecting the sustainability of Pangyo Techno Valley, and the qualitative research examined the specific reasons and additional factors for the quantitative research results. The quantitative results showed that factors affecting sustainability in terms of changes in corporate internal conditions, human and physical infrastructure, cooperation and synergy, and occupancy patterns. The specific reason for the impact appeared in the qualitative research process. The support category of local governments did not show any significant factors in quantitative research. In addition, qualitative research suggested 'Good image of Pangyo Techno Valley' as the category that has the greatest impact on sustainability. It is shown that companies are passive and expect the role of local governments in activating cooperation network in Pangyo Techno Valley. In this paper, based on the results of the study, Pangyo Techno Valley is presented with a realistic plan based on real estate issues and an ideal plan with a long-term perspective.

Impacts of Introduced Fishes (Carassius cuvieri, Micropterus salmoides, Lepomis macrochirus) on Stream Fish Communities in South Korea (외래어류가 우리나라 하천생태계 어류 군집에 미치는 영향: 떡붕어(Carassius cuvieri), 배스(Micropterus salmoides), 블루길(Lepomis macrochirus)을 대상으로)

  • Lee, Dae-Seong;Lee, Da-Yeong;Ji, Chang Woo;Kwak, Ihn-Sil;Hwang, Soon-Jin;Lee, Hae-Jin;Park, Young-Seuk
    • Korean Journal of Ecology and Environment
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    • v.53 no.3
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    • pp.241-254
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    • 2020
  • Three introduced fish species, Japanese white crucian carp (Carassius cuvieri Temminck and Schlegel, 1846), bass (Micropterus salmoides Lacepède, 1802) and bluegill (Lepomis macrochirus Rafinesque, 1819), are dominant fishes in Korean freshwater ecosystem. In this study, we analyzed habitat environment conditions of these three species and their impacts to fish communities in streams across South Korea. Fish community data were obtained from the database of the Stream/River Ecosystem Survey and Health Assessment program maintained by the Ministry of Environment and the National Institute of Environmental Research, Korea. Our results showed that species richness and Shannon diversity of fish were higher at the presence sites of introduced fish than at the absence sites. However, when the abundance of these introduced fish species was increased, the species richness and abundance of fish were decreased. An association analysis showed that the introduced fish species had a low similarity in their appearance with some indigenous fishes such as Siniperca scherzeri and Channa argus and some endemic fishes of Korea such as Zacco koreanus, Sarcocheilichthys variegatus wakiyae, and Acheilognathus yamatsutae. In addition, the introduced fish species had a low appearance similarity with a large number of fishes in their association networks. Finally, our results presented that these introduced fish species influenced the negative impacts to the stream fish communities, and they were potential risk factors for fish community in Korean freshwater ecosystem. Therefore, it is necessary that continuous monitoring and establishment of management strategy for introduced fish species to preserve fish resource and biodiversity in the Korean streams.

Comparison of the Medication Effects between Milnacipran and Pregabalin in Fibromyalgia Syndrome Using a Functional MRI: a Follow-up Study (섬유근통 환자에 대한 Milnacipran과 Pregabalin 약물치료에 대한 기능적 자기공명영상에서의 후속 영향 비교)

  • Kang, Min Jae;Mun, Chi-Woong;Lee, Young Ho;Kim, Seong-Ho
    • Investigative Magnetic Resonance Imaging
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    • v.18 no.4
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    • pp.341-351
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    • 2014
  • Purpose : In this study, the medication effects of Milnacipran and Pregabalin, as well known as fibromyalgia treatment medicine, in fibromyalgia syndrome patients were compared through the change of BOLD signal in pain related functional MRI. Materials and Methods: Twenty fibromyalgia syndrome patients were enrolled in this study and they were separated into two groups according to the treatment medicine: 10 Milnacipran (MLN) treatment group and 7 Pregabalin (PGB) treatment group. For accurate diagnosis, all patients underwent several clinical tests. Pre-treated and post-treated fMRI image with block-designed pressure-pain stimulation for each group were obtained to conduct the statistical analysis of paired t-test and two sample t-test. All statistical significant level was less than 0.05. Results: In clinical tests, the clinical scores of the two groups were not significantly different at pre-treatment stage. But, PGB treatment group had lower Widespread Pain Index (WPI) and Brief Fatigue Inventory (BFI) score than those of MLN treatment group at post-treatment stage. In functional image analysis, BOLD signal of PGB treatment group was higher BOLD signal at several regions including anterior cingulate and insula than MLN treatment group at post-treatment stage. Also, paired t-test values of the BOLD signal in MLN group decreased in several regions including insula and thalamus as known as 'pain network'. In contrast, size and number of regions in which the BOLD signal decreased in PGB treatment group were smaller than those of MLN treatment group. Conclusion: This study showed that MLN group and PGB group have different medication effects. It is not surprising that MLN and PGB have not the same therapeutic effects since these two drugs have different medicinal mechanisms such as antidepressants and anti-seizure medication, respectively, and different detailed target of fibromyalgia syndrome treatment. Therefore, it is difficult to say which medicine will work better in this study.

Estimation of Paddy Rice Growth Parameters Using L, C, X-bands Polarimetric Scatterometer (L, C, X-밴드 다편파 레이더 산란계를 이용한 논 벼 생육인자 추정)

  • Kim, Yi-Hyun;Hong, Suk-Young;Lee, Hoon-Yol
    • Korean Journal of Remote Sensing
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    • v.25 no.1
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    • pp.31-44
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    • 2009
  • The objective of this study was to measure backscattering coefficients of paddy rice using a L-, C-, and X-band scatterometer system with full polarization and various angles during the rice growth period and to relate backscattering coefficients to rice growth parameters. Radar backscattering measurements of paddy rice field using multifrequency (L, C, and X) and full polarization were conducted at an experimental field located in National Academy of Agricultural Science (NAAS), Suwon, Korea. The scatterometer system consists of dual-polarimetric square horn antennas, HP8720D vector network analyzer ($20\;MHz{\sim}20\;GHz$), RF cables, and a personal computer that controls frequency, polarization and data storage. The backscattering coefficients were calculated by applying radar equation for the measured at incidence angles between $20^{\circ}$ and $60^{\circ}$ with $5^{\circ}$ interval for four polarization (HH, VV, HV, VH), respectively. We measured the temporal variations of backscattering coefficients of the rice crop at L-, C-, X-band during a rice growth period. In three bands, VV-polarized backscattering coefficients were higher than hh-polarized backscattering coefficients during rooting stage (mid-June) and HH-polarized backscattering coefficients were higher than VV-, HV/VH-polarized backscattering coefficients after panicle initiation stage (mid-July). Cross polarized backscattering coefficients in X-band increased towards the heading stage (mid-Aug) and thereafter saturated, again increased near the harvesting season. Backscattering coefficients of range at X-band were lower than that of L-, C-band. HH-, VV-polarized ${\sigma}^{\circ}$ steadily increased toward panicle initiation stage and thereafter decreased, and again increased near the harvesting season. We plotted the relationship between backscattering coefficients with L-, C-, X-band and rice growth parameters. Biomass was correlated with L-band hh-polarization at a large incident angle. LAI (Leaf Area Index) was highly correlated with C-band HH- and cross-polarizations. Grain weight was correlated with backscattering coefficients of X-band VV-polarization at a large incidence angle. X-band was sensitive to grain maturity during the post heading stage.

Climate-Smart Agriculture (CSA)-Based Assessment of a Rice Cultivation System in Gimje, Korea (한국 김제의 벼 경작 시스템의 기후스마트농업 (Climate-Smart Agriculture) 기반의 평가)

  • Talucder, Mohammad Samiul Ahsan;Kim, Joon;Shim, Kyo-Moon
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.4
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    • pp.235-250
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    • 2021
  • The overarching question of this study is how a typical rice cultivation system in Gimje, Korea was keeping up with the triple-win challenge of climate-smart agriculture (CSA). To answer this question, we have employed (1) quantitative data from direct measurement of energy, water, carbon and information flows in and out of a rice cultivation system and (2) appropriate metrics to assess production, efficiency, GHG fluxes, and resilience. The study site was one of the Korean Network of Flux measurement (KoFlux) sites (i.e., GRK) located at Gimje, Korea, managed by National Academy of Agricultural Science, Rural Development Administration. Fluxes of energy, water, carbon dioxide (CO2) and methane (CH4) were directly measured using eddy-covariance technique during the growing seasons of 2011, 2012 and 2014. The production indicators include gross primary productivity (GPP), grain yield, light use efficiency (LUE), water use efficiency (WUE), and carbon uptake efficiency (CUE). The GHG mitigation was assessed with indicators such as fluxes of carbon dioxide (FCO2), methane (FCH4), and nitrous oxide (FN2O). Resilience was assessed in terms of self-organization (S), using information-theoretic approach. Overall, the results demonstrated that the rice cultivation system at GRK was climate-smart in 2011 in a relative sense but failed to maintain in the following years. Resilience was high and changed little for three year. However, the apparent competing goals or trade-offs between productivity and GHG mitigation were found within individual years as well as between the years, causing difficulties in achieving the triple-win scenario. The pursuit of CSA requires for stakeholders to prioritize their goals (i.e., governance) and to practice opportune interventions (i.e., management) based on the feedback from real-time assessment of the CSA indicators (i.e., monitoring) - i.e., a purpose-driven visioneering.

Analysis of the Impact of Generative AI based on Crunchbase: Before and After the Emergence of ChatGPT (Crunchbase를 바탕으로 한 Generative AI 영향 분석: ChatGPT 등장 전·후를 중심으로)

  • Nayun Kim;Youngjung Geum
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.3
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    • pp.53-68
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    • 2024
  • Generative AI is receiving a lot of attention around the world, and ways to effectively utilize it in the business environment are being explored. In particular, since the public release of the ChatGPT service, which applies the GPT-3.5 model, a large language model developed by OpenAI, it has attracted more attention and has had a significant impact on the entire industry. This study focuses on the emergence of Generative AI, especially ChatGPT, which applies OpenAI's GPT-3.5 model, to investigate its impact on the startup industry and compare the changes that occurred before and after its emergence. This study aims to shed light on the actual application and impact of generative AI in the business environment by examining in detail how generative AI is being used in the startup industry and analyzing the impact of ChatGPT's emergence on the industry. To this end, we collected company information of generative AI-related startups that appeared before and after the ChatGPT announcement and analyzed changes in industry, business content, and investment information. Through keyword analysis, topic modeling, and network analysis, we identified trends in the startup industry and how the introduction of generative AI has revolutionized the startup industry. As a result of the study, we found that the number of startups related to Generative AI has increased since the emergence of ChatGPT, and in particular, the total and average amount of funding for Generative AI-related startups has increased significantly. We also found that various industries are attempting to apply Generative AI technology, and the development of services and products such as enterprise applications and SaaS using Generative AI has been actively promoted, influencing the emergence of new business models. The findings of this study confirm the impact of Generative AI on the startup industry and contribute to our understanding of how the emergence of this innovative new technology can change the business ecosystem.

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Analysis of media trends related to spent nuclear fuel treatment technology using text mining techniques (텍스트마이닝 기법을 활용한 사용후핵연료 건식처리기술 관련 언론 동향 분석)

  • Jeong, Ji-Song;Kim, Ho-Dong
    • Journal of Intelligence and Information Systems
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    • v.27 no.2
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    • pp.33-54
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    • 2021
  • With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.

A Study of 'Emotion Trigger' by Text Mining Techniques (텍스트 마이닝을 이용한 감정 유발 요인 'Emotion Trigger'에 관한 연구)

  • An, Juyoung;Bae, Junghwan;Han, Namgi;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.21 no.2
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    • pp.69-92
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    • 2015
  • The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

Influences of the devastated forest lands on flood damages (Observed at Chonbo and the neighbouring Mt. Jook-yop area) (황폐임야(荒廢林野)가 수해참상(水害慘狀)에 미치는 영향(影響) (천보산(天寶山)과 인접(隣接) 죽엽산(竹葉山)을 중심(中心)으로))

  • Chung, In Koo
    • Journal of Korean Society of Forest Science
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    • v.5 no.1
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    • pp.4-9
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    • 1966
  • 1. On 13 September 1964 a storm raged for 3 hours and 20 minutes with pounding heavy rainfalls, and precipitation of 287.5 mm was recorded on that day. The numerous landslides were occured in the eroded forest land neighbouring Mt. Chunbo, while no landslides recorde at all on Mt. Jookyup within the premise of Kwangnung Experiment Station, the Forest Experiment Station. 2. Small-scalled Landslides were occured in 43 different places of watershed area (21.97 ha.) in which the survey had already been done, in and around Mt. Chunbo (378 m a.s.l.). The accumulated soil amount totaled $2,146,56m^3$ due to the above mentioned landslides, while soil accumulated from riverside erosion has reached to $24,168.79m^3$, consisting of soils, stones, and pebbles. However, no landslides were reported in the Mt. Jook yup area because of dense forest covers. The ratio of the eroded soil amount accumulated from the riversides to that of watershed area was 1 to 25. On the other hand, the loss and damage in the research area of Mt. Chonbo are as follows: 28 houses completly destroyed or missing 7 houses partially destroyed 51 men were dead 5 missing, and 57 wounded. It was a terrible human disaster However, no human casualties were recorded at all, 1 house-completly destroyed and missing, 2 houses-partially destroyed. Total:3 houses were destroyed or damaged, in The area of Mt. Jookyup 3. In the calculation of the quanty of accumulated soil, the or mula of "V=1/3h ($a+{\sqrt{ab}}+b$)" was used and it showed that 24, 168.79m of soil, sands, stones and pebbles carried away. 4. Average slope of the stream stood 15 at the time of accident and well found that there was a correlation between the 87% of cross-area sufferd valley erosion and the length of eroded valley, after a study on regression and correlation of the length and cross-area. In other works, the soil erosion was and severe as we approached to the down-stream, counting at a place of average ($15^{\circ}1^{\prime}$) and below. We might draw a correlation such as "Y=ax-b" in terms of the length and cross-area of the eroded valley. 5. Sites of char-coal pits were found in the upper part of the desert-like Mt. Chunbo and a professional opinion shows that the mountain was once covered by the oak three species. Furthermore, we found that the soil of both mountains have been kept the same soil system according to a research of the soil cross-area. In other words, we can draw out the fact that, originally, the forest type and soil type of both Mt. Chunbo (378m) and Mt. Jookyup (610m) have been and are the same. However, Mt. Chunbo has been much more devastated than Mt. Jookyup, and carried away its soil nutrition to the extent that the ratios of N. $P_2O_5K_2O$ and Humus C.E.C between these two mountains are 1:10;1:5 respectively. 6. Mt. Chunbo has been mostly eroded for the past 30 years, and it consists of gravels of 2mm or larger size in the upper part of the mountain, while in the lower foot part, the sandy loam was formulated due to the fact that the gluey soil has been carried and accumulated. On the hand, Mt. Jookyup has consitantly kept the all the same forest type and sandy loam of brown colour both in the upper and lower parts. 7. As for the capability of absorbing and saturating maximum humidity by the surface soil, the ratios of wet soil to dry soil are 42.8% in the hill side and lower part of the eroded Mt. Chunbo and 28.5% in the upper part. On the contrary, Mt. Jookyup on which the forest type has not been changed, shows that the ratio in 77.4% in the hill-side and 68.2% in the upper part, approximately twice as much humidity as Mt. Chunbo. This proves the fact that the forest lands with dense forest covers are much more capable of maintaining water by wood, vegitation, and an organic material. The strength of dreventing from carring away surface soil is great due to the vigorous network of the root systems. 8. As mentioned above, the devastated forest land cause not only much greater devastation, but also human loss and property damage. We must bear in mind that the eroded forest land has taken the valuable soil, which is the very existance of origin of both human being and all creatures. As for the prescription for preventing erosion of forest land, the trees for furtilization has to be planted in the hill,side with at least reasonable amount of aertilizer, in order to restore the strength of earth soil, while in the lower part, thorough erosion control and reforestation, and establishments along the riversides have to be made, so as to restore the forest type.

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Intercomparing the Aerosol Optical Depth Using the Geostationary Satellite Sensors (AHI, GOCI and MI) from Yonsei AErosol Retrieval (YAER) Algorithm (연세에어로졸 알고리즘을 이용하여 정지궤도위성 센서(AHI, GOCI, MI)로부터 산출된 에어로졸 광학두께 비교 연구)

  • Lim, Hyunkwang;Choi, Myungje;Kim, Mijin;Kim, Jhoon;Go, Sujung;Lee, Seoyoung
    • Journal of the Korean earth science society
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    • v.39 no.2
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    • pp.119-130
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    • 2018
  • Aerosol Optical Properties (AOPs) are retrieved using the geostationary satellite instruments such as Geostationary Ocean Color Imager (GOCI), Meteorological Imager (MI), and Advanced Himawari Imager (AHI) through Yonsei AErosol Retrieval algorithm (YAER). In this study, the retrieved aerosol optical depths (AOD)s from each instrument were intercompared and validated with the ground-based sunphotometer AErosol Robotic NETwork (AERONET) data. As a result, the four AOD products derived from different instruments showed consistent results over land and ocean. However, AODs from MI and GOCI tend to be overestimated due to cloud contamination. According to the comparison results with AERONET, the percentage within expected errors (EE) are 36.3, 48.4, 56.6, and 68.2% for MI, GOCI, AHI-minimum reflectivity method (MRM), and AHI-estimated surface reflectance from shortwave Infrared (ESR) product, respectively. Since MI AOD is retrieved from a single visible channel, and adopts only one aerosol type by season, EE is relatively lower than other products. On the other hand, the AHI ESR is more accurate than the minimum reflectance method as used by GOCI, MI, and AHI MRM method in May and June when the vegetation is relatively abundant. These results are explained by the RMSE and the EE for each AERONET site. The ESR method result show to be better than the other satellite product in terms of EE for 15 out of 22 sites used for validation, and they are better than the other product for 13 sites in terms of RMSE. In addition, the error in observation time in each product is found by using characteristics of geostationary satellites. The absolute median biases at 00 to 06 Universal Time Coordinated (UTC) are 0.05, 0.09, 0.18, 0.18, 0.14, 0.09, and 0.10. The absolute median bias by observation time has appeared in MI and the only 00 UTC appeared in GOCI.