• The Journal of the Petrological Society of Korea
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• v.28 no.3
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• pp.157-169
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• 2019

Pseudotachylytes, produced by frictional heating during seismic slip, provide information that is critical to understanding the physics of earthquakes. We report the results of occurrence, structural characteristics, scanning electron microscopic observation and geochemical analysis of pseudotachylytes, which is presumed to have formed after the Late Cretaceous in outcrops of the Paleoproterozoic granitic gneiss on the Bulil waterfall of the Jirisan area, Yeongnam massif, Korea. Fault rocks, which are the products of brittle deformation under the same shear stress regime in the study area, are classified as pseudotachylyte and foliated cataclasite. The occurrences of pseudotachylyte identified on the basis of thickness and morphology are fault vein-type and injection vein-type pseudotachylyte. A number of fault vein-type pseudotachylytes occur as thin (as thick as 2 cm) layers generated on the fault plane, and are cutting general foliation and sheared foliation developed in granitic gneiss. Smaller injection vein-type pseudotachylytes are found along the fault vein-type pseudotachylytes, and appear in a variety of shapes based on field occurrence and vein geometry. At a first glance fault vein-type seudotachylyte looks like a mafic vein, but it has a chemical composition almost identical to the wall rock of granitic gneiss. Also, it has many subrounded clasts which consist predominantly of quartz, feldspar, biotite and secondary minerals including clay minerals, calcite and glassy materials. Embayed clasts, phenocryst with reaction rim, oxide droplets, amygdules, and flow structures are also observed. All of these evidences indicate the pseudotachylyte formed due to frictional melting of the wall rock minerals during fault slip related to strong seismic faulting events in the shallow depth of low temperature-low pressure. Further studies will be conducted to determine the age and mechanical aspect of the pseudotachylyte formation.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.199-230
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• 2021

Innovative new products and services are being launched through the convergence between heterogeneous industries, and social interest and investment in convergence industries such as AI, big data-based future cars, and robots are continuously increasing. However, in the process of commercialization of convergence new products and services, there are many cases where they do not conform to the existing regulatory and legal system, which causes many difficulties in companies launching their products and services into the market. In response to these industrial changes, the current government is promoting the improvement of existing regulatory mechanisms applied to the relevant industry along with the expansion of investment in new industries. This study, in these convergence industry trends, aimed to analysis the existing regulatory system that is an obstacle to market entry of innovative new products and services in order to preemptively predict regulatory issues that will arise in emerging industries. In addition, it was intended to establish a regulatory impact analysis system to evaluate adequacy and prepare improvement measures. The flow of this study is divided into three parts. In the first part, previous studies on regulatory impact analysis and evaluation systems are investigated. This was used as basic data for the development direction of the regulatory impact framework, indicators and items. In the second regulatory impact analysis framework development part, indicators and items are developed based on the previously investigated data, and these are applied to each stage of the framework. In the last part, a case study was presented to solve the regulatory issues faced by actual companies by applying the developed regulatory impact analysis framework. The case study included the autonomous/electric vehicle industry and the Internet of Things (IoT) industry, because it is one of the emerging industries that the Korean government is most interested in recently, and is judged to be most relevant to the realization of an intelligent information society. Specifically, the regulatory impact analysis framework proposed in this study consists of a total of five steps. The first step is to identify the industrial size of the target products and services, related policies, and regulatory issues. In the second stage, regulatory issues are discovered through review of regulatory improvement items for each stage of commercialization (planning, production, commercialization). In the next step, factors related to regulatory compliance costs are derived and costs incurred for existing regulatory compliance are calculated. In the fourth stage, an alternative is prepared by gathering opinions of the relevant industry and experts in the field, and the necessity, validity, and adequacy of the alternative are reviewed. Finally, in the final stage, the adopted alternatives are formulated so that they can be applied to the legislation, and the alternatives are reviewed by legal experts. The implications of this study are summarized as follows. From a theoretical point of view, it is meaningful in that it clearly presents a series of procedures for regulatory impact analysis as a framework. Although previous studies mainly discussed the importance and necessity of regulatory impact analysis, this study presented a systematic framework in consideration of the various factors required for regulatory impact analysis suggested by prior studies. From a practical point of view, this study has significance in that it was applied to actual regulatory issues based on the regulatory impact analysis framework proposed above. The results of this study show that proposals related to regulatory issues were submitted to government departments and finally the current law was revised, suggesting that the framework proposed in this study can be an effective way to resolve regulatory issues. It is expected that the regulatory impact analysis framework proposed in this study will be a meaningful guideline for technology policy researchers and policy makers in the future.

• Korean Journal of Environmental Biology
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• v.38 no.4
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• pp.634-649
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• 2020

Recently, stream longitudinal connectivity has been a topic of investigation due to the frequent disconnections and the impact of aquatic ecosystems caused by the construction of small and medium-sized weirs and various artificial structures (fishways) directly influencing the stream ecosystem health. In this study, the international and domestic research trends of the longitudinal connectivity in aquatic ecosystems were evaluated and the applicability of fish-based longitudinal connectivity models used in developed countries was analyzed. For these purposes, we analyzed the current status of research on longitudinal connectivity and structural problems, fish monitoring methodology, monitoring approaches, longitudinal disconnectivity of fish movement, and biodiversity. In addition, we analyzed the current status and some technical limitations of physical habitat suitability evaluation, ecology-based water flow, eco-hydrological modeling for fish habitat connectivity, and the s/w program development for agent-based model. Numerous references, data, and various reports were examined to identify worldwide longitudinal stream connectivity evaluation models in European and non-European countries. The international approaches to longitudinal connectivity evaluations were categorized into five phases including 1) an approach integrating fish community and artificial structure surveys (two types input variables), 2) field monitoring approaches, 3) a stream geomorphological approach, 4) an artificial structure-based DB analytical approach, and 5) other approaches. the overall evaluation of survey methodologies and applicability for longitudinal stream connectivity suggested that the ICE model (Information sur la Continuite Ecologique) and the ICF model (Index de Connectivitat Fluvial), widely used in European countries, were appropriate for the application of longitudinal connectivity evaluations in Korean streams.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.327-339
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• 2020

Transpiration is the movement of water into the atmosphere through leaf stomata of plant, and it accounts for more than half of evapotranspiration from the land surface. The measurements of transpiration could be conducted in various ways including eddy covariance and water balance method etc. However, the transpiration measurements of individual trees are necessary to quantify and compare the water use of each species and individual component within stands. For the measurement of the transpiration by individual tree, the thermometric methods such as heat dissipation and heat pulse methods are widely used. However, it is difficult and labor consuming to maintain the transpiration measurements of individual trees in a wide range area and especially for long-term experiment. Therefore, the sharing of sapflow data through database should be useful to promote the studies on transpiration and water balance for large spatial scale. In this paper, we present sap flow database, which have Granier type sap flux data from 18 Korean pine (Pinus koraiensis) since 2011 and 16 (Quercus aliena) since 2013 in Mt.Taehwa Seoul National University forest and 18 needle fir (Abies holophylla), seven (Quercus serrata), three (Carpinus laxiflora and C. cordata each since 2013 in Gwangneung. In addition, the database includes the sapling transpiration of nine species (Prunus sargentii, Larix kaempferii, Quercus accutisima, Pinus densiflora, Fraxinus rhynchophylla, Chamecypans obtuse, P. koraiensis, Betulla platyphylla, A. holophylla, Pinus thunbergii), which were measured using heat pulse method since 2018. We believe this is the first database to share the sapflux data in Rep. of Korea, and we wish our database to be used by other researchers and contribute a variety of researches in this field.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.187-195
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• 2021

Nam Nong Heo Geon(1908-1987) re-recognized and re-created the tradition of Korean Namjong painting by excluding Japanese art forms after liberation. He is a great painter in the Korean art world, who has succeeded and developed Korean Namjong Painting in a modern way, pioneering a new field of 'NewNamhwa' with a composition that fuses modern Western style and real scenery. Based on optimism, Namnong's painting world can be divided into three periods: the 'Namnong Sanin' period in the 1930s, the 'Namnongoesa' period from the mid-1940s to the early 1950s, and the 'the owner of Unlimsanbang' period after that. The Namnong Sanin period is a period in which the painting style handed down from the traditional namhwau family of Sochi and Misan is fully acquired, and the Japanese painting style for the exhibition in Seonjeon is reflected, and the local real scenery is treated a lot, and the two styles are mixed. In the Namnong-oesa period, after liberation, a new formativeness was explored in the traditional Namhwa style. In particular, based on the scenery and sentiments of the southern provinces, he focused on local and landscape paintings, depicting real landscapes with lyricism and local love, while expressing subjects with fast brush strokes, a worndown writing brush, and dry brushes, along with freehand adjustment of shading. The period of the owner of unlimsanbang is in accordance with the flow of modern art to some extent, but is gradually omitted as a composition full of academic fragrance that draws a meaning befitting traditional painting. I painted a lot of lyrical landscapes and pine trees of sumugdamchae. Namnong named it 'NewNamhwa'. Namnong established 'Namhwa Research Institute' and worked hard to nurture his disciples, where Im-in's son Heomun and Namnong's eldest grandson Heojin practiced, continuing the legacy of the 5th generation Unlimsanbang painter.

• Journal of Environmental Impact Assessment
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• v.31 no.4
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• pp.226-240
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• 2022

Local governments over a certain size in Republic of Korea may conduct Environmental Impact Assessment (EIA) considering regional characteristics if it is necessary, in accordance with Article 42 of the 「Environmental Impact Assessment Act」. However, it was investigated that the number of local government EIA operation in many local governments was less than initial expectations. In order to improve it, the status of ordinances and consultation guidelines which are different for each local government need to be compared, and the institutional issues forthe relevant local governments must be found considering regional characteristics. Furthermore, detailed regulation and guidance on the local government EIA procedure should be included in the consultation guidelines and related information need to be provided. In this study, focusing on the case of Incheon Metropolitan City, the status of local government EIA ordinances in metropolitan cities and provinces with a similar condition was investigated, and the types and scope of target projects were compared and analyzed. In addition, consultation guidelines forIncheon Metropolitan City were written, and improvements on the procedure flow and overall schedule designation derived from the process were presented. In the case of Incheon Metropolitan City, there were no detailed information officially announced regarding the regulations of the local government EIA ordinance and follow-up management, so the administrative system of the local government needed to be reinforced in this field. Meanwhile, considering the status of local environment and geography, some target project types were deemed necessary to be added: port construction projects, water resource development projects, railroad construction projects, and military facilities installation projects. The results of this study will provide useful information to local governments which want to improve their operation effectiveness by reorganizing the local government EIA system and preparing specific guidelines.

• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.133-149
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• 2022

The Port logistics is a pivotal industry in strengthening competitiveness for countries and companies and plays an important role in accounting for the majority of Korea's import and export volume, so its importance among Korea's industries is truly enormous. The port, which plays such an important role, is simultaneously unloaded, transferred into the dock, and stored, and it can be said that it is composed of a very complex flow. In particular, port unloading is an environment in which port unloading workers cannot escape the risk of disasters as large cargoes and cranes for container transport move, and numerous disasters are hidden and lead to serious disasters. Through literature studies on the Serious Accident Penalty Act, this study investigated how the Serious Accident Penalty Act affected port unloading workers and whether there was a change in satisfaction with safety education according to the enforcement of the Serious Accident Penalty Act. Through this study, it was found that port unloading workers were more aware of safety than managers in cognitive, attitude, and experience factors. Since the port unloading manager is not put into the unloading work, the perception of safety was analyzed to be lower than that of workers. Since managers should educate workers on safe work and be alert to safety, it seems that port unloading managers will also need to change their perception of safety. The Act on the Punishment of Severe Disasters took effect on January 27, 22, and in the early stages of the enforcement of the law, many confusing and ambiguous parts are found for those in charge of performing practical tasks on the front line until the law is settled. It seems necessary to revise the Act on the Punishment of Severe Disasters for the purpose of clear standards for the law and no safety accidents in the field to prevent confusion in work. In addition, in order to derive more meaningful research results in the future, it is expected that research on the perception of disasters by workers and managers will be continuously needed by deepening literature research to find various factors and using investigation methods such as interviews.

• 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.

• Ecology and Resilient Infrastructure
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• v.9 no.3
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• pp.183-193
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• 2022

The growth inhibitory effect of Microcystis aeruginosa according to the ultrasonic irradiation time was evaluated using a large algae sample volume (10 L) for various ultrasonic irradiation times (0.5, 1, 1.5, 2, 2.5 and 3 hr) at a laboratory scale. Based on the analysis of Chl-a and cell number of M. aerginosa, algae growth inhibition was observed with the decrease in Chl-a and cell number in all experimental groups after the ultrasonic irradiation. For the experimental group (T_B, T_C, T_D) with an ultrasonic irradiation time of less than 2 hours, rapid regrowth of algae was observed after growth inhibition, but the experimental group (T_E, T_F, T_G) with an irradiation time of more than 2 hours successfully inhibited algal growth lasting one or two more days. Based on the comparison of the recovery time to initial cell number the experimental group (T_B, T_C, T_D) took less than 20 days whereas the experimental group (T_E, T_F, T_G) took about 30 days. Correspondingly, the experimental group showed a high first order decay rate (𝜅) in proportion to the ultrasonic irradiation time during the growth inhibition period. Additionally, the specific growth rates (𝜇) during regrowth in the experimental group with irradiation time of more than 2 hours were relatively low compared to those in the experimental group with less than 2 hours. Therefore, ultrasonic irradiation for more than 2 hours is required for long-term (30 days) inhibition of algal growth in stagnant waters. However, the appropriate ultrasonic irradiation time for algae growth inhibition should be determined according to various field conditions such as the volume of stagnant water, water depth, flow rate, algae concentration, etc. Finally, damages to the algal cell surface and cell membrane were clearly observed, and both destruction and disturbance of gas vesicles of M. aeruginosa in the experimental group were discovered, indicating the growth inhibitory effect of Microcystis aeruginosa according to the ultrasonic irradiation time was confirmed.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.