• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.4
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• pp.545-552
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• 1998

This study was undertaken to clarify the effects of electrical stimulation on the biochemical properties of plaice sarcoplasmic reticulum and myofibrils at early period of death. The plaices were electrically stimulated (110V/60 Hz) In sea water bath for 15, 35, and 60 seconds, and killed instantly by spiking at the head. Killed samples were investigated for the changes in $Ca^{2+}$-ATPase activity of FSR (fragmented sarcoplasmic reticulum), LSR (light SR), HSR (heavy SR), and SDS-PAGE pattern of FSR. $Ca^{2+}$-ATPase activity of FSR increased until $45^{\circ}C$ and inactivated over $50^{\circ}C$. $Ca^{2+}$-ATPase activity of FSR remarkably decreased according to the duration of electrical stimulation. Myofibrillar $Mg^{2+}$-ATPase activity of electrically stimulated plaices in the presence of $Ca^{2+}$ was higher than that of sample instantly killed by spiking. $Mg^{2+}$-ATPase activity of myofibrils increased by electrical stimulation and the activity decreased during storage at $5^{\circ}C$. Myofibrillar $Mg^{2+}$-ATPase activity in sample killed by spiking was not affected by $Ca^{2+}$ ion. Myofibrillar $Mg^{2+}$-ATPase activity of electrically stimulated sample in the absen-re of $Ca^{2+}$ decreased during storage at $5^{\circ}C$, whit $Mg^{2+}$-ATPase activity in unstimulated sample did not show any change. $Ca^{2+}$-sensitivity of myofibrils showed no differences between electrically stimulated sample and sample killed by spiking, and the was no change during at $5^{\circ}C$.

• Journal of agriculture & life science
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• v.44 no.5
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• pp.91-99
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• 2010

The objective of this work was to investigate the influence of ultrasonification on extraction yield and chemical properties of green tea infusion. Changes in total soluble matter(TSM), vitamin C, total phenolic compounds, flavonols, catechins, caffeine, free amino acids contents in green tea infusion(GTI) influenced by ultrasonification at $60^{\circ}C$ of extraction temperature for 1, 5, 30, and 60 min were investigated. The amount of infused TSM increased about 5.3% by ultrasonification for 60min. Vitamin C contents also increased 0.21, 0.16, 0.31 mg/g from 1 to 30 min by ultrasonification. However, vitamin C decreased from 2.47 to 2.22 mg/g at 60min. Total phenol compounds contents increased about 10~13 mg/g on all extraction times by ultrasonification. Flavonols such as, myricetin, quercetin, kaempferol were increased to doubled contents as an influence of ultrasonification. Catechins such as, EGCG, EGC, ECG, EC, (+)-C and caffeine contents showed same tendency as the results of vitamin C. On the other hand, result of free amino acids showed different tendency. All amounts of free amino acids did not increase by ultrasonification. Consequently, content of bioactive compounds such as, vitamin C, total phenolic, flavonols and catechins in green tea infusion were influenced by ultrasonification.

• Journal of Sericultural and Entomological Science
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• v.53 no.2
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• pp.135-142
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• 2015

The American cockroaches, Periplaneta americana L. was the most important worldwide pest species. It has been an public health problems. We were determinated life cycle and extraction of crude extracts by chemical reagents from cockraches (P. americana L.). The extracted crude solution has been antibacterial activity to gram negative bacteria (Pseudomonas aeruginosa, $6.44{\pm}1.03mm$), gram positive bacteria (Bacillus subtilis, $1.88{\pm}0.40mm$), and fungus (Candida albicans, $5.61{\pm}0.57mm$) using radial diffusion assay. We were analysed of up-regulation of Glutathione-S-transferases (GSTs) stimulation, indicating that antioxidantial protein from various classes are simultaneously expressed in a single insect upon infection or injury. The gene from Periplaneta americana L. were cloned, analysed sequence, and measured protein expression by Real Time PCR (Polymerase Chain Reaction).

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.57-75
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• 2019

In this paper, we conducted a study focusing on the innovation direction of the documentary model on the Internet of Things industry, which is the most actively industrialized among the core technologies of the 4th Industrial Revolution. Policy, economic, social, and technical issues were derived using PEST analysis for global trend analysis. It also presented future prospects for the Internet of Things industry of ICT-related global research institutes such as Gartner and International Data Corporation. Global research institutes predicted that competition in network technologies will be an issue for industrial Internet (IIoST) and IoT (Internet of Things) based on infrastructure and platforms. As a result of the PEST analysis, developed countries are pushing policies to respond to the fourth industrial revolution through cooperation of private (business/ research institutes) led by the government. It was also in the process of expanding related R&D budgets and establishing related policies in South Korea. On the economic side, the growth tax of the related industries (based on the aggregate value of the market) and the performance of the entity were reviewed. The growth of industries related to the fourth industrial revolution in advanced countries overseas was found to be faster than other industries, while in Korea, the growth of the "technical hardware and equipment" and "communication service" sectors was relatively low among industries related to the fourth industrial revolution. On the social side, it is expected to cause enormous ripple effects across society, largely due to changes in technology and industrial structure, changes in employment structure, changes in job volume, etc. On the technical side, changes were taking place in each industry, representing the health and medical sectors and manufacturing sectors, which were rapidly changing as they merged with the technology of the Fourth Industrial Revolution. In this paper, various management methodologies for innovation of existing business model were reviewed to cope with rapidly changing industrial environment due to the fourth industrial revolution. In addition, four criteria were established to select a management model to cope with the new business environment: 'Applicability', 'Agility', 'Diversity' and 'Connectivity'. The expert survey results in an AHP analysis showing that Business Model Canvas is best suited for business model innovation methodology. The results showed very high importance, 42.5 percent in terms of "Applicability", 48.1 percent in terms of "Agility", 47.6 percent in terms of "diversity" and 42.9 percent in terms of "connectivity." Thus, it was selected as a model that could be diversely applied according to the industrial ecology and paradigm shift. Business Model Canvas is a relatively recent management strategy that identifies the value of a business model through a nine-block approach as a methodology for business model innovation. It identifies the value of a business model through nine block approaches and covers the four key areas of business: customer, order, infrastructure, and business feasibility analysis. In the paper, the expansion and application direction of the nine blocks were presented from the perspective of the IoT company (ICT). In conclusion, the discussion of which Business Model Canvas models will be applied in the ICT convergence industry is described. Based on the nine blocks, if appropriate applications are carried out to suit the characteristics of the target company, various applications are possible, such as integration and removal of five blocks, seven blocks and so on, and segmentation of blocks that fit the characteristics. Future research needs to develop customized business innovation methodologies for Internet of Things companies, or those that are performing Internet-based services. In addition, in this study, the Business Model Canvas model was derived from expert opinion as a useful tool for innovation. For the expansion and demonstration of the research, a study on the usability of presenting detailed implementation strategies, such as various model application cases and application models for actual companies, is needed.

• Journal of Korea Water Resources Association
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• v.56 no.1
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• pp.53-62
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• 2023

Recently, due to the influence of climate change, the occurrence of damage to heavy rain is increasing around the world, and the frequency of heavy rain with a large amount of rain in a short period of time is also increasing. Heavy rains generate a large amount of outflow in a short time, causing flooding in the downstream part of the mountainous area before joining the small and medium-sized rivers. In order to reduce damage to downstream areas caused by flooding, it is very important to calculate the outflow of mountainous areas due to torrential rains. However, the sewage network flooding analysis, which is currently conducting the most analysis in Korea, uses the time and area method using the existing data rather than calculating the rainfall outflow in the mountainous area, which is difficult to determine that the soil characteristics of the region are accurately applied. Therefore, if the rainfall is analyzed for mountainous areas that can cause flooding in the downstream area in a short period of time due to large outflows, the accuracy of the analysis of flooding characteristics that can occur in the downstream area can be improved and used as data for evacuating residents and calculating the extent of damage. In order to calculate the rainfall outflow in the mountainous area, the rainfall outflow in the mountainous area was calculated using MIKE SHE among the MIKE series, and the flooding analysis in the downstream area was conducted through MIKE 21 FM (Flood model). Through this study, it was possible to confirm the amount of outflow and the time to reach downstream in the event of rainfall in the mountainous area, and the results of this analysis can be used to protect human and material resources through pre-evacuation in the downstream area in the future.

• Journal of Venture Innovation
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• v.4 no.2
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• pp.57-75
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• 2021

KHNP's shared growth activities are based on such public good. Reflecting the characteristics of a comprehensive energy company, a high-tech plant company, and a leading company for shared growth, it presents strategies to link performance indicators with its partners and implements various measures. Key tasks include maintaining the nuclear power plant ecosystem, improving management conditions for partner companies, strengthening future capabilities of the nuclear power plant industry, and supporting a virtuous cycle of regional development. This is made by reflecting the specificity of nuclear power generation as much as possible, and is designed to reflect the spirit of shared growth through win-win and cooperation in order to solve the challenges of the times while considering the characteristics as much as possible as possible. KHNP's shared growth activities can be said to be the practice of the spirit of the times(Zeitgeist). The spirit of the times given to us now is that companies should strive for sustainable growth as social air. KHNP has been striving to establish a creative and leading shared growth ecosystem. In particular, considering the positions of partners, it has been promoting continuous system improvement to establish a fair trade culture and deregulation. In addition, it has continuously discovered and implemented new customized support projects that are effective for partner companies and local communities. To this end, efforts have been made for shared growth through organic collaboration with partners and stakeholders. As detailed tasks, it also presents fostering new markets and new industries, maintaining supply chains, and emergency support for COVID-19 to maintain the nuclear power plant ecosystem. This reflects the social public good after the recent COVID-19 incident. In order to improve the management conditions of partner companies, productivity improvement, human resources enhancement, and customized funding are being implemented as detailed tasks. This is a plan to practice win-win growth with partner companies emphasized by corporate social responsibility (CSR) and ISO 26000 while being faithful to the main job. Until now, ESG management has focused on the environmental field to cope with the catastrophe of climate change. According to KHNP is presenting a public enterprise-type model in the environmental field. In order to strengthen the future capabilities of the nuclear power plant industry as a state-of-the-art energy company, it has set tasks to attract investment from partner companies, localization and new technologies R&D, and commercialization of innovative technologies. This is an effort to develop advanced nuclear power plant technology as a concrete practical measure of eco-friendly development. Meanwhile, the EU is preparing a social taxonomy to focus on the social sector, another important axis in ESG management, following the Green Taxonomy, a classification system in the environmental sector. KHNP includes enhancing local vitality, increasing income for the underprivileged, and overcoming the COVID-19 crisis as part of its shared growth activities, which is a representative social taxonomy field. The draft social taxonomy being promoted by the EU was announced in July, and the contents promoted by KHNP are consistent with this, leading the practice of social taxonomy

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.125-132
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• 2007

We estimated the distribution of predator-prey interaction strengths for 12 species of herbivores (including amphipods, isopods, gastropods, and sea urchins) and made a regression model that may be applicable to other species. Laboratory experiments were used to determine per capita grazing rate (PCGR; g seaweeds/individual/day). Relationship between the biomass of individual grazers and fourth-root transformed PCGR was fitted to power curve ($y=0.2310x^{0.3290}$, r=0.8864). This finding supported that the grazing efficiency was not even as individual grazers increase in size (biomass). Therefore, the biomass-normalized PCGR was estimated and revealed that smaller size herbivores were more effective grazers. Grazing impact considering density of each taxon was calculated. The sea hare Aplysia kurodai had greatest grazing impact on the seaweed bed and the sea urchin Strongylocentrotus nudus and S. intermedius were ranked in descending order of the impact. The amount of seaweed grazed by the amphipod Elasmopus sp. (>4,000 $ind./m^2$) and Jassa falcata (>2,000 $ind./m^2$) were 3.435 and $1.697mg/m^2/day$ respectively. The combined grazing amount of herbivores was $5,045mg/m^2/day$ in the seaweed bed. Although sea hare and sea urchin had strong impacts on seaweeds, the effects of dense, smaller species could not be seen as negligible. Surprisingly, the calculated grazing potential of sea urchins with a mean density of 3 $ind./m^2$ exceeded the mean production of seaweed cultured in domestic coastal waters in Korea (ca., 5 ton/ha). Small crustaceans were also expected to consume up to 16% of the seaweed production if their densities were rising under weak predation conditions. Considering that the population density of herbivores are strongly controlled by fish, human interference like overfishing may have strong negative effects on persistence of seaweeds communities.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.63-79
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• 2024

The startup ecosystem is experiencing a paradigm shift in founding due to the acceleration of digital transformation, online platform companies have grown significantly into unicorns, but the lack of differentiated approaches and strategic support for deep tech startups has led to the inactivity of the startup ecosystem. is lacking. Therefore, in this study, we proposed ways to develop domestic startup development policies, focusing on the US system, which is an advanced example overseas. Focusing on the definition and characteristics of deep tech startups, current investment status, success stories, support policies, etc., we comprehensively analyzed domestic and international literature and derived suggestions. In particular, he proposed specific ways to improve support policies for domestic deep tech startups and presented milestones for their development. Currently, the United States is significantly strengthening the role of the government in supporting deep tech startups. The US government provides direct financial support to deep tech startups, including detergent support and infrastructure support. It has also established policies to foster deep tech startups, established related institutions, and systematized support. It is worth noting that US universities play a core role in nurturing deep tech startups. Leading universities in the United States operate deep tech startup discovery and development programs, providing research and development infrastructure and technology. It also works with companies to provide co-investment and commercialization support for deep tech startups. As a result, the growth of domestic deep tech startups requires the cooperation of diverse entities such as the government, universities, companies, and private investors. The government should strengthen policy support, and universities and businesses should work together to support R&D and commercialization capabilities. Furthermore, private investors must stimulate investment in deep tech startups. Through such efforts, deep tech startups are expected to grow and Korea's innovation ecosystem will be revitalized.

• Tuberculosis and Respiratory Diseases
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• v.50 no.1
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• pp.52-66
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• 2001

Background : NF-${\kappa}B$ is the most important transcriptional factor in IL-8 gene expression. Triptolide is a new compound that recently has been shown to inhibit NF-${\kappa}B$ activation. The purpose of this study is to investigate how triptolide inhibits NF-${\kappa}B$-dependent IL-8 gene transcription in lung epithelial cells and to pilot the potential for the clinical application of triptolide in inflammatory lung diseases. Methods : A549 cells were used and triptolide was provided from Pharmagenesis Company (Palo Alto, CA). In order to examine NF-${\kappa}B$-dependent IL-8 transcriptional activity, we established stable A549 IL-8-NF-${\kappa}B$-luc. cells and performed luciferase assays. IL-8 gene expression was measured by RT-PCR and ELISA. A Western blot was done for the study of $I{\kappa}B{\alpha}$ degradation and an electromobility shift assay was done to analyze NF-${\kappa}B$ DNA binding. p65 specific transactivation was analyzed by a cotransfection study using a Gal4-p65 fusion protein expression system. To investigate the involvement of transcriptional coactivators, we perfomed a transfection study with CBP and SRC-1 expression vectors. Results : We observed that triptolide significantly suppresses NF-${\kappa}B$-dependent IL-8 transcriptional activity induced by IL-$1{\beta}$ and PMA. RT-PCR showed that triptolide represses both IL-$1{\beta}$ and PMA-induced IL-8 mRNA expression and ELISA confirmed this triptolide-mediated IL-8 suppression at the protein level. However, triptolide did not affect $I{\kappa}B{\alpha}$ degradation and NF-$_{\kappa}B$ DNA binding. In a p65-specific transactivation study, triptolide significantly suppressed Gal4-p65T Al and Gal4-p65T A2 activity suggesting that triptolide inhibits NF-${\kappa}B$ activation by inhibiting p65 transactivation. However, this triptolide-mediated inhibition of p65 transactivation was not rescued by the overexpression of CBP or SRC-1, thereby excluding the role of transcriptional coactivators. Conclusions : Triptolide is a new compound that inhibits NF-${\kappa}B$-dependent IL-8 transcriptional activation by inhibiting p65 transactivation, but not by an $I{\kappa}B{\alpha}$-dependent mechanism. This suggests that triptolide may have a therapeutic potential for inflammatory lung diseases.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.