• Journal of Marine Life Science
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• v.8 no.2
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• pp.104-114
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• 2023

As plastic usage increases globally, the amount of plastic waste entering the marine environment is steadily rising. Microplastics, in particular, can be ingested by marine organisms and accumulated in their digestive tracts, causing harmful effects on their growth and reproduction. Cytochrome P450 (CYP) enzymes are known to metabolize various environmental pollutants as detoxification enzymes, but their role in crustaceans is not well understood. In this study, sequences of nine CYP genes (CYP370A4, CYP370C5 from clan 2; CYP350A1, CYP350C5, CYP361A1 from clan 3; CYP4AN-like, CYP4AP2, CYP4AP3, CYP4C33-like1 from clan 4) were analyzed using conserved domains in the brackish water flea Diaphanosoma celebensis. Additionally, after exposure to three different sizes of polystyrene beads (0.05-, 0.5-, 6-㎛ PS beads; 0.1, 1, and 10 mg/L) for 48 hours, the expression of these nine CYP genes were investigated using real-time reverse transcription polymerase chain reaction (RT-PCR). The results showed that all CYP genes possessed conserved motifs, indicating that D. celebensis CYP has evolutionarily conserved functions. Among these CYP genes, the expression of CYP370C5, CYP360A1, and CYP4C122 showed a significant increase after exposure to 0.05-㎛ PS beads, suggesting their involvement in PS metabolism. This research will contribute to understanding the molecular mode of actions of microplastics on marine invertebrates.

• The Journal of Engineering Geology
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• v.33 no.4
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• pp.543-553
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• 2023

The current status of domestic a agalmatolite mines in South Korea was investigated with a view to establishing a stable supply of agalmatolite and managing its demand. Most mined agalmatolite deposits were formed through hydrothermal alteration of Mesozoic volcanic rocks. The physical characteristics of pyrophyllite, the main constituent mineral of agalmatolite, are as follows: specific gravity 2.65~2.90, hardness 1~2, density 1.60~1.80 g/cm³, refractoriness ≥29, and color white, gray, grayish white, grayish green, yellow, or yellowish green. Among the chemical components of domestic agalmatolite, SiO₂ and Al₂O₃ contents are respectively 58.2~67.2 and 23.1~28.8 wt.% for pyrophyllite, 49.2~72.6 and 16.5~31.0 wt.% for pyrophyllite + dickite, 45.1 and 23.3 wt.% for pyrophyllite + illite, 43.1~82.3 and 11.4~35.8 wt.% for illite, and 37.6~69.0 and 19.6~35.3 wt.% for dickite. Domestic agalmatolite mines are concentrated mainly in the southwest and southeast of the Korean Peninsula, with some occurring in the northeast. Twenty-one mines currently produce agalmatolite in South Korea, with reserves in the order of Jeonnam (45.6%) > Chungbuk (30.8%) > Gyeongnam (13.0%) > Gangwon (4.8%), and Gyeongbuk (4.8%). The top 10 agalmatolite-producing mines are in the order of the Central Resources Mine (37.9%) > Wando Mine (25.6%) > Naju Ceramic Mine (13.4%) > Cheongseok-Sajiwon Mine (5.4%) > Gyeongju Mine (5.0%) > Baekam Mine (5.0%) > Minkyung-Nohwado Mine (3.3%) > Bugok Mine (2.3%) > Jinhae Pylphin Mine (2.2%) > Bohae Mine. Agalmatolite has low thermal conductivity, thermal expansion, thermal deformation, and expansion coefficients, low bulk density, high heat and corrosion resistance, and high sterilization and insecticidal efficiency. Accordingly, it is used in fields such as refractory, ceramic, cement additive, sterilization, and insecticide manufacturing and in filling materials. Its scope of use is expanding to high-tech industries, such as water treatment ceramic membranes, diesel exhaust gas-reduction ceramic filters, glass fibers, and LCD panels.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.417-425
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• 2023

The aim of this study was to derive stem taper equations for Quercus acuta, one of main evergreen broad-leaved tree species found in warm temperate regions, and to prepare a stem volume table using those stem taper equations. A total of 688 individual trees were used in the analysis, which were collected from Jeonnam-do, Gyeongnam-do, and Jeju-do. The stem taper models applied to derive the stem curve pattern were the Max and Burkhart, Kozak, and Lee models. Among the three stem taper models, the best explanation of the stem curve shape of Q. acuta was found to be given by the Kozak model, which showed a fitness index of 0.9583, bias of 0.0352, percentage of estimated standard error of 1.1439, and mean absolute deviation of 0.6751. Thus, the stem taper of Q. acuta was estimated using the Kozak model. Moreover,thestemvolumecalculationwasperforme d by applying the Smalian formula to the diameter and height of each stem interval. In addition, an analysis of variance (ANOVA) was conducted to compare the two existing Q. acuta stem volume tables (2007 and 2010) and the newly created stem volume table (2023). This analysis revealed that the stem volume table constructed in the Wando region in 2007 included about twice as much as the stem volume tables constructed in 2010 and 2023. The stem volume table (2023) developed in this study is not only based on the regional collection range and number of utilized trees but also on a sound scientific basis. Therefore, it can be used at the national level as an official stem volume table for Q. acuta.

• Information Systems Review
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• v.25 no.4
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• pp.131-159
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• 2023

Recently, amidst the backdrop of the COVID-19 pandemic shifting towards an endemic phase, there has been a rise in discussions and debates about the future of the metaverse. Simultaneously, major metaverse platforms like Roblox have been launching services integrated with generative AI, and Apple's mixed reality hardware, Vision Pro, has been announced, creating new expectations for the metaverse. In this situation where the outlook for the metaverse is divided, it is crucial to diagnose the metaverse from an ecosystem perspective, examine its key ecological features, driving forces for development, and future possibilities for advancement. This study utilized Wang's (2021) Information Ecology Theory (IET) framework, which is representative of ecosystem research in the field of Information Systems (IS), to derive the Metaverse Industrial Ecosystem (MIE). The analysis revealed that the MIE consists of four main domains: Tech Landscape, Category Ecosystem, Metaverse Platform, and Product/Service Ecosystem. It was found that the MIE exhibits characteristics such as digital connectivity, the integration of real and virtual worlds, value creation capabilities, and value sharing (Web 3.0). Furthermore, the interactions among the domains within the MIE and the four characteristics of the ecosystem were identified as driving forces for the development of the MIE at an ecosystem level. Additionally, the development of the MIE at an ecosystem level was categorized into three distinct stages: Narrow Ecosystem, Expanded Ecosystem, and Everywhere Ecosystem. It is anticipated that future advancements in related technologies and industries, such as robotics, AI, and 6G, will promote the transition from the current Expanded Ecosystem level of the MIE to an Everywhere Ecosystem level, where the connection between the real and virtual worlds is pervasive. This study provides several implications. Firstly, it offers a foundational theory and analytical framework for ecosystem research, addressing a gap in previous metaverse studies. It also presents various research topics within the metaverse domain. Additionally, it establishes an academic foundation that integrates concept definition research and impact studies, which are key areas in metaverse research. Lastly, referring to the developmental stages and conditions proposed in this study, businesses and governments can explore future metaverse markets and related technologies. They can also consider diverse metaverse business strategies. These implications are expected to guide the exploration of the emerging metaverse market and facilitate the evaluation of various metaverse business strategies.

• 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 Remote Sensing
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• v.39 no.6_3
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• pp.1779-1790
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• 2023

Satellite-based fog detection algorithms are being developed to detect fog in real-time over a wide area, with a focus on the Korean Peninsula (KorPen). The GEO-KOMPSAT-2A/Advanced Meteorological Imager (GK2A/AMI, GK2A) satellite offers an excellent temporal resolution (10 min) and a spatial resolution (500 m), while GEO-KOMPSAT-2B/Geostationary Ocean Color Imager-II (GK2B/GOCI-II, GK2B) provides an excellent spatial resolution (250 m) but poor temporal resolution (1 h) with only visible channels. To enhance the fog detection level (10 min, 250 m), we developed a fused GK2AB fog detection algorithm (FDA) of GK2A and GK2B. The GK2AB FDA comprises three main steps. First, the Korea Meteorological Satellite Center's GK2A daytime fog detection algorithm is utilized to detect fog, considering various optical and physical characteristics. In the second step, GK2B data is extrapolated to 10-min intervals by matching GK2A pixels based on the closest time and location when GK2B observes the KorPen. For reflectance, GK2B normalized visible (NVIS) is corrected using GK2A NVIS of the same time, considering the difference in wavelength range and observation geometry. GK2B NVIS is extrapolated at 10-min intervals using the 10-min changes in GK2A NVIS. In the final step, the extrapolated GK2B NVIS, solar zenith angle, and outputs of GK2A FDA are utilized as input data for machine learning (decision tree) to develop the GK2AB FDA, which detects fog at a resolution of 250 m and a 10-min interval based on geographical locations. Six and four cases were used for the training and validation of GK2AB FDA, respectively. Quantitative verification of GK2AB FDA utilized ground observation data on visibility, wind speed, and relative humidity. Compared to GK2A FDA, GK2AB FDA exhibited a fourfold increase in spatial resolution, resulting in more detailed discrimination between fog and non-fog pixels. In general, irrespective of the validation method, the probability of detection (POD) and the Hanssen-Kuiper Skill score (KSS) are high or similar, indicating that it better detects previously undetected fog pixels. However, GK2AB FDA, compared to GK2A FDA, tends to over-detect fog with a higher false alarm ratio and bias.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1605-1613
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• 2023

The physical properties of the ocean interior are determined by temperature and salinity. To observe them, we rely on satellite observations for broad regions of oceans. However, the satellite for salinity measurement, Soil Moisture Active Passive (SMAP), has low temporal and spatial resolutions; thus, more is needed to resolve the fast-changing coastal environment. To overcome these limitations, the algorithm to use the Geostationary Ocean Color Imager-II (GOCI-II) of the Geo-Kompsat-2B (GK-2B) was developed as the inputs for a Multi-layer Perceptron Neural Network (MPNN). The result shows that coefficient of determination (R²), root mean square error (RMSE), and relative root mean square error (RRMSE) between GOCI-II based sea surface salinity (SSS) (GOCI-II SSS) and SMAP was 0.94, 0.58 psu, and 1.87%, respectively. Furthermore, the spatial variation of GOCI-II SSS was also very uniform, with over 0.8 of R² and less than 1 psu of RMSE. In addition, GOCI-II SSS was also compared with SSS of Ieodo Ocean Research Station (I-ORS), suggesting that the result was slightly low, which was further analyzed for the following reasons. We further illustrated the valuable information of high spatial and temporal variation of GOCI-II SSS to analyze SSS variation by the 11th typhoon, Hinnamnor, in 2022. We used the mean and standard deviation (STD) of one day of GOCI-II SSS, revealing the high spatial and temporal changes. Thus, this study will shed light on the research for monitoring the highly changing marine environment.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

• Journal of Venture Innovation
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• v.4 no.3
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• pp.1-15
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• 2021

Due to long-term social distancing due to the spread of COVID-19, business trends of restaurant companies are being implemented in accordance with the changed environment such as packaging and subscription. However, even in this environment, upscale restaurants are generating high profits by trying to differentiate themselves from existing restaurants by providing high-quality services with the best facilities. Therefore, this study describes how customers' experience of upscale restaurant service influences behavioral loyalty. That is, the purpose of this study is to determine the effect of service experience on cognitive satisfaction and emotional attachment, and to examine the causal role of cognitive satisfaction and emotional attachment by confirming the relationship between these constructs and relationship commitment and behavioral loyalty. To verify this, data were collected through face-to-face interviews with 300 consumers who recently used a upscale restaurant. Of the collected data, 275 copies(91.6%) were used for the final analysis, and inaccurate or erroneous data among 25 response sheets were excluded. In this study, the validity and reliability of the data were checked and the research hypothesis was verified by using SPSS 21.0 and AMOS 20 statistical package. Frequency analysis was performed to confirm the demographic characteristics of the respondent. Structural equation model analysis(SEM) was used to confirm the fit of the research model and to verify the research hypothesis. As a result of the research hypothesis analysis, it was found that service experience had a positive effect on cognitive satisfaction, and cognitive satisfaction had a positive effect on emotional attachment, relationship commitment, and behavioral loyalty. Also, it was found that emotional attachment had a positive effect on relationship commitment and behavioral loyalty, and relationship commitment had a positive effect on behavioral loyalty. However, service experience did not affect emotional attachment. With this study, marketers and managers of upscale restaurants such as hotel restaurants need to accurately select their target audience, understand their service needs, and then present the appropriate service to them. In addition, they should not only induce cognitive satisfaction by providing excellent service to their customers, but also identify moments of truth and present appropriate services so that satisfied customers can strengthen their emotional attachment. In addition, it is necessary to strengthen the relationship with their firms by forming friendly relationships with customers who have high emotional attachment, and also to induce relationship commitment so that such customers have a strong sense of belonging and attachment to their firms.

• Journal of Venture Innovation
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• v.5 no.1
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• pp.91-106
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• 2022

Cryptocurrency, stood out the sharp cost rising of Bitcoin has been spotlighted by means of the solution for stagflation because it is decentralized with an existing currency differently. Especially getting into 4th industrial revolution, technologies using block chain and internet of things have been used in the many fields, and the power of influence is also widespread. Nevertheless like a remark of Elon Musk of Tesla CEO, the problems of environmental contamination for cryptocurrency have been pointed out continuously and the most representative of them is an enormous electric usage as the use of fossil fuels. Also the amount generated of carbon dioxide result in the acceleration of global warming mainly based on the climate changes of earth if the existing mining method is continued. On the other hand, review researches have been conducted restrictively as the connection with environmental contamination as the mining of cryptocurrency. In this study, it intended to review problems for environmental contamination as the diversification of ecological system of cryptocurrency concretely. Upon investigation existing prior documents on the putting recent data first, the mining of cryptocurrency has affected on the environmental contamination conflicting with carbon neutrality as increasement of the electric usage and electronic wastes. And POS method without the mining process appeared, but it had a demerit collapsing a decentralization and then we met turning point on appearing various environmental-friendly cryptocurrency. Finally the appearance of cryptocurrency using new renewable energy acted on the opportunity of the usage maximization of energy storage apparatus and the birth of national government intervention. Based on these results, we mention clearly that hereafter cryptocurrency will regress if not go abreast the value of currency as well as environmental approach.