• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Ecology and Resilient Infrastructure
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• v.8 no.1
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• pp.32-43
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• 2021

Multichannel automated chamber systems (MCACs) were developed for the continuous monitoring of soil CO2 efflux in forest ecosystems. The MCACs mainly consisted of four modules: eight soil chambers with lids that automatically open and close, an infrared CO2 analyzer equipped with eight multichannel gas samplers, an electronic controller with time-relay circuits, and a programmable logic datalogger. To examine the stability and reliability of the developed MCACs in the field during all seasons with a high temporal resolution, as well as the effects of temperature and soil water content on soil CO2 efflux rates, we continuously measured the soil CO2 efflux rates and micrometeorological factors at the Nam-san experimental site in a Quercus mongolica forest floor using the MCACs from January to December 2010. The diurnal and seasonal variations in soil CO2 efflux rates markedly followed the patterns of changes in temperature factors. During the entire experimental period, the soil CO2 efflux rates were strongly correlated with the temperature at a soil depth of 5 cm (r2 = 0.92) but were weakly correlated with the soil water content (r2 = 0.27). The annual sensitivity of soil CO2 efflux to temperature (Q10) in this forest ranged from 2.23 to 3.0, which was in agreement with other studies on temperate deciduous forests. The annual mean soil CO2 efflux measured by the MCACs was approximately 11.1 g CO2 m-2 day-1. These results indicate that the MCACs can be used for the continuous long-term measurements of soil CO2 efflux in the field and for simultaneously determining the impacts of micrometeorological factors.

• Korean Journal of Environment and Ecology
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• v.35 no.1
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• pp.24-36
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• 2021

Countries around the world, including the Republic of Korea, are participating in efforts to preserve biodiversity. Concerning species, in particular, studies that aim to find potential habitats and establish conservation plans by conducting habitat suitability analysis for specific species are actively ongoing. However, few studies on mid- to long-term changes in suitable habitat areas are based on accumulated information. Therefore, this study aimed to analyze the time-series changes in the habitat suitable area and examine the otters' changing pattern (Lutra lutra) designated as Level 1 endangered wildlife in Gangwon-do. The time-series change analysis used the data on otter species' presence points from the 2nd, 3rd, and 4th national natural environment surveys conducted for about 20 years. Moreover, it utilized the land cover map consistent with the survey period to create environmental variables to reflect each survey period's habitat environment. The suitable habitat area analysis used the MaxEnt model that can run based only on the species presence information, and it has been proven to be reliable by previous studies. The study derived the habitat suitability map for otters in each survey period, and it showed a tendency that habitats were distributed around rivers. Comparing the response curves of the environmental variables derived from the modeling identified the characteristics of the habitat favored by otters. The examination of habitats' change by survey period showed that the habitats based on the 2nd National Natural Environment Survey had the widest distribution. The habitats of the 3rd and 4th surveys showed a tendency of decrease in area. Moreover, the study aggregated the analysis results of the three survey periods and analyzed and categorized the habitat's changing pattern. The type of change proposed different conservation plans, such as field surveys, monitoring, protected area establishment, and restoration plan. This study is significant because it produced a comprehensive analysis map that showed the time-series changes of the location and area of the otter habitat and proposed a conservation plan that is necessary according to the type of habitat change by region. We believe that the method proposed in this study and its results can be used as reference data for establishing a habitat conservation and management plan in the future.

• Korean Journal of Plant Resources
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• v.35 no.2
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• pp.201-241
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• 2022

This study was investigated distributed the vascular flora of around Haemyeong Mt., located in Seokmodo, Incheon, and compared invasive alien plants in the surrounding forest 14 areas. This study carried out to be established a monitoring system for the remarkable plants etc. and used as basic data for biodiversity enhancement and conservation. The survey was conducted 19 times from April 2019 to October 2020. A total of 107 families, 382 genera, 616 species, 15 sub-species, 55 varieties, 8 formas, and 694 taxa were classified in the flora around Haemyeong Mt. areas. 17 taxa for Korea endemic plants. 12 taxa were classified for rare plants, and a total of 79 taxa were identified for floristic target species I~V. Halophytes consisted of 37 taxa. The invasive alien plants were classified as 66 taxa, and also there has been 126 taxa of them in Seokmodo and surrounding 14 forests. Plants that appeared in all 14 areas out of 126 taxa were classified as 7 taxa, such as Erigeron annuus. However, 48 taxa appeared only once in some areas, but it seems inevitable that they will spread in the future. Therefore, it is necessary to prepare a long-term conservation plan for native plants.

• Korean Journal of Organic Agriculture
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• v.29 no.4
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• pp.601-612
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• 2021

This study was conducted to evaluate the appropriate sowing method and mixture seeding rate on germination of Kentucky bluegrass (Poa pratensis L.) and white clover (Trifolium repens L.). The experimental design includes two sowing methods and six mixed seeding per each method: BT₁:BP₀ (broadcast seeding; B, Trifolium repens; T, Poa pratensis; P), BT₁:BP₂, BT₁:BP₃, BT₃:BT₁, BT₂:BP₁, BT₀:BP₁ and ST₁:SP₀ (spot seeding; S), ST₁:SP₂, ST₁:SP₃, ST₃:ST₁, ST₂:SP₁, ST₀:SP₁. The germination was the highest for both species when the seeding rate was higher than other species. In overall, the germination of white clover was higher and faster than Kentucky bluegrass. Two plots, BT₂:BP₁, ST₁:ST₂, were retained the balanced proportion of the germination rate. Therefore, It was suggested, for maintaining the balanced field, it is better to seed white clover twice Kentucky bluegrass on broadcast seeding and Kentucky bluegrass twice white clover on spot seeding. In regard of sowing method, broadcast seeding is better than spot seeding in terms of increasing the germination. It is necessary to supplement the result for real application by long-term monitoring.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1255-1272
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• 2023

Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.

• Korean Journal of Environment and Ecology
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• v.37 no.5
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• pp.327-336
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• 2023

This study aimed to propose an effective method for surveying wild birds by comparing the results of bioacoustic detection with those obtained through a field survey. The study sites were located at Dongbaek-dongsan and a 1100-altitude wetland in Jeju-do, South Korea. The bioacoustic detection was conducted over the course of 12 months in 2020. For the bioacoustic detection, a Song-meter SM4 device was installed at each study site, recording bird songs in 1-min per hour, .wav, and 44,100 Hz format. The findings of the field survey were taken from the 「Long-term trends of Bird Community at Dongbaekdongsan and 1100-Highland Wetland of Jeju Island, South Korea.」 by Banjade et al. (2019). The results of this study are as follows. First, the avifauna identified using bioacoustic detection comprised 29 families and 46 species in Dongbaek-dongsan, and 16 families and 25 species in the 1100-altitude wetland. Second, based on the song frequency, the dominant species in Dongbaek-dongsan were Hypsipetes amaurotis (Brown-eared Bulbul, 33.62%), Horornis diphone (Japanese Bush Warbler, 12.13%), and Zosterops japonicus (Warbling White-eye, 9.77%). In the 1100-altitude wetland the dominant species were Corvus macrorhynchos (Large-billed Crow, 27.34%), H. diphone (19.43%), and H. amaurotis (16.56%). Third, in the field survey conducted at Dongbaek-dongsan, the number of detected bird species was 39 in 2009, 51 in 2012, 35 in 2015, and 45 in 2018, while the bioacoustic detection identified 46 species. In the field survey conducted in the 1100-altitude wetland, the number of detected bird species was 37 in 2009, 42 in 2012, 34 in 2015, and 38 in 2018, while the bioacoustics detection identified 25 species. Overall, 43.6% of the 78 species detected in the field survey in Dongbaek-dongsan (34 species) were identified using bioacoustic detection, and 38.3% of the 47 species detected in the field survey in the 1100-altitude wetland (18 species) were identified using bioacoustic detection. Fourth, the bioacoustic detection identified 9 families and 12 species of birds in Dongbaek-dongsan, and 3 families and 7 species of birds in the 1100-altitude wetland. No results from field survey were available for these species. The identified birds were predominantly nocturnal, including Otus sunia (Oriental Scops Owl) and Ninox japonica (Northern Boobook), passage migrants, including Larvivora cyane (Siberian Blue Robin), L. sibilans (Rufous-tailed Robin), and winter visitors with a relatively small number of visiting individuals, such as Bombycilla garrulus (Bohemian Waxwing) and Loxia curvirostra (Red Crossbill). Fifth, the birds detected in the field survey but not through bioacoustic detection included 18 families and 48 species in Dongbaek-dongsan and 14 families and 27 species in the 1100-altitude wetland; the most representative families were Ardeidae, Accipitridae, and Muscicapidae. This study is significant as it provides essential data supporting the possibility of an effective survey combining bioacoustic detection with field studies, given the increasing use of bioacoustic devices in ornithological studies in South Korea.

• The Journal of Engineering Geology
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• v.28 no.2
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• pp.217-246
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• 2018

During the selection and characterization of target formations in the Small-scale Offshore $CO_2$ Storage Demonstration Project in the Pohang Basin, we have carefully investigated the possibility of induced earthquakes and leakage of $CO_2$ during the injection, and have designed the storage processes to minimize these effects. However, people in Pohang city have a great concern on $CO_2$-injection-intrigued seismicity, since they have greatly suffered from the 5.4 magnitude earthquake on Nov. 15, 2017. The research team of the project performed an extensive self-investigation on the safety issues, especially on the possible $CO_2$ leakage from the target formation and induced earthquakes. The target formation is 10 km apart from the epicenter of the Pohang earthquake and the depth is also quite shallow, only 750 to 800 m from the sea bottom. The project performed a pilot injection in the target formation from Jan. 12 to Mar. 12, 2017, which implies that there are no direct correlation of the Pohang earthquake on Nov. 15, 2017. In addition, the $CO_2$ injection of the storage project does not fracture rock formations, instead, the supercritical $CO_2$ fluid replaces formation water in the pore space gradually. The self-investigation results show that there is almost no chance for the injection to induce significant earthquakes unless injection lasts for a very long time to build a very high pore pressure, which can be easily monitored. The amount of injected $CO_2$ in the project was around 100 metric-tonne that is irrelevant to the Pohang earthquake. The investigation result on long-term safety also shows that the induced earthquakes or the reactivation of existing faults can be prevented successfully when the injection pressure is controlled not to demage cap-rock formation nor exceed Coulomb stresses of existing faults. The project has been performing extensive studies on critical stress for fracturing neighboring formations, reactivation stress of existing faults, well-completion processes to minimize possible leakage, transport/leakage monitoring of injected $CO_2$, and operation procedures for ensuring the storage safety. These extensive studies showed that there will be little chance in $CO_2$ leakage that affects human life. In conclusion, the Small-scale Offshore $CO_2$ Storage Demonstration Project in the Pohang Basin would not cause any induced earthquakes nor signifiant $CO_2$ leakage that people can sense. The research team will give every effort to secure the safety of the storage site.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.2
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• pp.68-81
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• 2014

This study was conducted to identify the spacialty, to illuminate the existence and values of Myeongwoldae(明月臺) and Forest Myeongwol, and to suggest the sustainable usage, preservation and management plans with the purpose of ecological and cultural landscaping characteristic and value identification. The result of the study is as follows. Castle Myeongwol and Port Myeongwol shows the status of Hallim-eup Myeongwol District which is the administrative center of western Jeju as well as is the fortress. Building Wolgyejeongsa and School Woohakdang, the head temple of education and culture, located in Myeongwol District represents the spaciality of Myeonwol-ri which was the center of education. Stand Myeongwol is one of the most representative Confucian cultural landscapes in Jeju Island and the field of communion with nature where scholars enjoy poetries, nature, changgi(Korean chess), and go in the Joseon Dynasty period. It was found that the current relics of Myeongwoldae was recovered through the maintenance project conducted by Youth Group Myeongwol composed with Hongjong-si(洪鍾時) as the center during the Japanese colonial era in 1931. It seems that the stonework of Myeongwoldae composed of three levels in the order of square, octagon, and circle based on the heaven-man unity theory of Confucianism and the octagon in the middle is the messenger of Cheonwonjibang(天圓地方), in other words, between the square-shaped earth and the circle-shaped sky. It is assumed that both Grand Bridge Myeongwol and Bridge Myeongwol were constructed as arched bridges in early days. Bridge Myeongwol is the only arched bridge remaining in Jeju Island now, which has the modern cultural heritage value. In Forest Myeongwol, 97 taxa of plants were confirmed and in accordance with 'Taxonomic Group and Class Criteria of Floristic Specific Plants', eight taxa were found; Arachniodes aristata of FD IV and Ilex cornuta, Piper kadsura, Litsea japonica, Melia azedarach, Xylosma congestum, Richosanthes kirilowii var. japonica, Dichondra repens, Viburnum odoratissimum var. awabuki of FD III. Otherwise, 14 taxa of naturalized plants including Apium leptophylihum which is imported to Jeju Island only were confirmed. In Forest Myeongwol, 77 trees including 41 Celtis sinensis, 30 Aphananthe aspera, two Wylosma congestum, a Pinus densiflora, a Camellia japonica, a Melia azedarach, and an Ilex cornuta form a colony. Based on the researched data, the preservation and plans of Myeongwoldae and Forest Myeongwol is suggested as follows. Myeongwoldae, Bridge Myeongwol, and Forest Myeongwol should be managed as one integrated division. Bridge Myeongwol, an arched bridge which is hard to be found in Jeju Island is a high-standard stonework requiring long-term preservation plans. Otherwise, Grand Bridge Myeongwol that is exposed to accident risks because of deterioration and needs safety diagnosis requires measures according to the result of precise safety diagnosis. It is desirable to restore it to a two-sluice arched bridge as its initial shape and to preserve and use it as a representative local landmark with Stand Myeongwol. In addition, considering the topophsis based on the analysis result, the current name of Jeju Special Self-Governing Province Monument No. 19 'Myoengwol Hackberry Colony' should change to 'Myeongwol Hackberry-Muku Tree Colony'. In addition, the serial number system which is composed without distinction of hackberry and muku tree should be improved and the regular monitoring of big and old trees, specific plants, and naturalized species is required.