Jung, Kyeongsoo;Chae, U-Ri;Chae, Ho Keun;Chung, Myeong-Sug;Lee, Joo-Yeoun
Journal of Korea Society of Industrial Information Systems
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v.24
no.5
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pp.9-16
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2019
In today's global energy market, the importance of green energy is emerging. Hydrogen energy is the future clean energy source and one of the pollution-free energy sources. In particular, the fuel cell method using hydrogen enhances the flexibility of renewable energy and enables energy storage and conversion for a long time. Therefore, it is considered to be a solution that can solve environmental problems caused by the use of fossil resources and energy problems caused by exhaustion of resources simultaneously. The purpose of this study is to efficiently produce hydrogen using plasma, and to study the optimization of DME reforming by checking the reforming reaction and yield according to temperature. The research method uses a 2.45 GHz electromagnetic plasma torch to produce hydrogen by reforming DME(Di Methyl Ether), a clean fuel. Gasification analysis was performed under low temperature conditions ($T3=1100^{\circ}C$), low temperature peroxygen conditions ($T3=1100^{\circ}C$), and high temperature conditions ($T3=1376^{\circ}C$). The low temperature gasification analysis showed that methane is generated due to unstable reforming reaction near $1100^{\circ}C$. The low temperature peroxygen gasification analysis showed less hydrogen but more carbon dioxide than the low temperature gasification analysis. Gasification analysis at high temperature indicated that methane was generated from about $1150^{\circ}C$, but it was not generated above $1200^{\circ}C$. In conclusion, the higher the temperature during the reforming reaction, the higher the proportion of hydrogen, but the higher the proportion of CO. However, it was confirmed that the problem of heat loss and reforming occurred due to the structural problem of the gasifier. In future developments, there is a need to reduce incomplete combustion by improving gasifiers to obtain high yields of hydrogen and to reduce the generation of gases such as carbon monoxide and methane. The optimization plan to produce hydrogen by steam plasma reforming of DME proposed in this study is expected to make a meaningful contribution to producing eco-friendly and renewable energy in the future.
Eunkyung Kang;Seonuk Yang;Jiyoon Kwon;Sung-Byung Yang
Journal of Intelligence and Information Systems
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v.29
no.1
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pp.79-105
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2023
Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.
Kim, Sung Hyun;Choi, Joon Ki;Kim, Jae Seok;Jang, Ah Reum;Lee, Jae Ho;Cha, Kyung Jin;Lee, Sang Won
Journal of Intelligence and Information Systems
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v.24
no.4
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pp.137-154
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2018
Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.
Research of color has been developed and also has raised consumer desire through changing from a tool to pursue curiosity or beauty to a tool creating effects in the 20th century. People have been interested in colors as a dynamic expression of results since the color TV appeared. The meaning of colors has been recently diversified as the roles of colors became important to the emotional aspects of design. While auto colors have developed along with such changes of the times, black led the color trend during the first half of the 20th century from 1900 to 1950, a transitional period of economic growth and world war. Since then, automobile production has increased apace with the rapid economic growth throughout the world and automobiles became the most expensive item out of the goods that people use. Accordingly, increasing production induced facility investment in mass production and a technology leveling was achieved. Auto manufacturing processes are very complicated, auto makers gradually recognized that software changes such as to colors or materials was an easier way for the improvement of brand identity as opposed to hardware changes such as the mechanical or design components of the body. Color planning and development systems were segmented in various aspects. In the segmentation issue, pigment technology and painting methods are important elements that have an influence on body colors and have a higher technical correlation with colors than in other industries. In other words, the advanced mixture of pigments is creating new body colors that have not existed previously. This diversifies the painting structure and methods and so maximizes the transparency and depth of body colors. Thus, body colors that are closely related to technical factors will increase in the future and research on color preferences by region have been systemized to cope with global competition due to the expansion and change of auto export regions.
No comprebensive forage quality of annual legumes harvested and cured in spring has been conducted in Korea. Therefore, this experiment was carried out to gain information on the quality of crimson clover (Trifolium incarnatum L.), bolta baIansa clover(Trifolium ba/anansae L.), and persian c1over(Trifolium resupinatum L.) during field curing in spring. The dry matter content of crimson clover at harvest was 24.7%, while bolta balansa and persian clovers had 20.4 and 18.8%, respectively. The moisture content of persian clover was low at the final curing day. But All species took 4 days to reach moisture content under 20%Tedding frequency did not affect moisture content, but consisten trends were also observed during the field curing. Persian clover tended to show a higher leaf-stem ratio than crimson and bolta balansa clovers on dry matter basis. Crude protein of persian clover(19.5%) was higher than other legumes. The percentage of erode protein was decreased from 17.8 to 16.5% as tedding frequency often did. Neutral detergent fiber(NDF) and acid detergent fiber(ADF) contents of persian clover were lower than those of other legumes. From the comparison among tedding frequency, NDF and ADF contents of three times were higher than those of one and two times. Relative feed value(RFV) of persian clover hay was the highest(178) and classified as Grade Prime in forage quality standard. Crimson and bolta balansa clovers in the RFV were also high quality as Grade 1 in forage quality standard. The RFV of legume hay was decreased from 150 to 140 as tedding frequency often did Results of the experiment indicate that hay quality of persian clover was higher than other clovers. And this is due to high leaf and stem content, hollow stem and late maturity stage. Then tedding frequency in annual legume can be teded by two times for quality.
Kim, Sung Jae;Jung, Woo Kyung;Hong, Joonbae;Yang, Soo-Jin;Park, Yong Ho;Park, Kun Taek
Journal of Food Hygiene and Safety
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v.35
no.3
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pp.271-278
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2020
Enterotoxigenic Escherichia coli is one of the major causative infectious agents of diarrhea in newborn and post-weaning pigs and leads to a large economic loss worldwide. However, there is limited information on the distribution and characterization of virulence genes in E. coli isolated from diarrheic piglets, which also applies to the current status of pig farms in Korea. To investigate the prevalence and characterization of virulence genes in E. coli related to diarrhea in piglets, the rectal swab samples of diarrheic piglets (aged 2 d to 6 w) were collected from 163 farms between 2013 and 2016. Five to 10 individual swab samples from the same farm were pooled and cultured on MacConkey agar plates, and E. coli were identified using the API 32E system. Three sets of multiplex PCRs were used to detect 13 E. coli virulence genes. As a result, a total of 172 E. coli isolates encoding one or more of the virulence genes were identified. Among them, the prevalence of individual virulence gene was as follows, (1) fimbrial adhesins (43.0%): F4 (16.9%), F5 (4.1%), F6 (1.7%), F18 (21.5%), and F41 (3.5%); (2) toxins (90.1%): LT (19.2%), STa (20.9%), STb (25.6%), Stx2e (15.1%), EAST1 (48.3%); and (3) non-fimbrial adhesin (19.6%): EAE (14.0%), AIDA-1 (11.6%) and PAA (8.7%), respectively. Taken together, various pathotypes and virotypes of E. coli were identified in diarrheic piglets. These results suggest a broad array of virulence genes is associated with coliform diarrhea in piglets in Korea.
Journal of agricultural medicine and community health
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v.34
no.1
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pp.58-66
/
2009
Objectives: Active participation of poultry breeder in surveillance system of Avian Influenza (AI) is very important. Therefore this study was conducted to present basis data for active report of AI that is affected by media's coverage in poultry breeder. Methods: Subjects were 88 persons, 28 who were poultry breeder at epidemic area of AI and 60 who were general person at non-epidemic area. Data were collected by the trained investigator from Jul. 1 to Aug. 31, 2008. Respondents were interviewed by means of a structured questionnaire. Results: The third-person effect among perceptions of influence in media's report on the AI was higher in breeder (32.1%) than in non-breeder (10.0%). However, Confidence to media report on the AI was lower in breeder than in non-breeder. Intention to report of the AI was 71.4% in breeder respectively, was 90.0% in non-breeder. There was statistically significant lower in breeder than non-breeder. The cause of avoidance of report was 'economic damage' for 87.5%, which acocounted for the majority of cases. Confidence to media report on the AI were positively correlated with concern on the AI and perception on seriousness of the AI, but negatively correlated with the third-person effect. Conclusions: These results showed that intention to report of the AI of breeder was susceptible to influenced by the third person effect and confidence in media's report on the AI. Therefore we should give a special attention to increase active report of poultry breeder during epidemic period of AI which is consideration of reasonable strategy of media's coverage, including mind and emotion state of poultry breeder.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.15
no.2
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pp.1-18
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2020
This study is to identify the influence of major variables that affect the participation intention of securities type crowdfunding investors and how participation intention and perceived behavioral control affect investors' herd behavior including indirect effect analysis based on the theory of planned behavior. The ultimate purpose of this study is to understand the investment behavior of securities type crowdfunding investors and to help the relevant parties to develop various policies and business plans to revitalize the system and protect investors. An online survey was conducted on people who are interested or have experience in securities type crowdfunding to receive a total of 276 responses. Excluding outliers, a total of 261 responses were taken into account for the final analysis. For the data analysis, structural equation model analysis using SPSS 22.0 and Amos 22.0 statistical package was conducted. As a result, two of the major variables of the theory of planned behavior-attitude and subjective norm-have been found to have a positive effect on the participation intention of securities type crowdfunding investors. And after analyzing the indirect effect, the participation intention was found to play a mediating role between attitude, subjective norm and herd behavior. However, the perceived behavioral control presented as a major variable of behavioral intention in the theory of planned behavior showed that the effect on participation intention was statistically insignificant. Instead, it was found to have a direct positive effect on herd behavior. This is significant because it empirically confirmed that even if investors perceive securities type crowdfunding as easy to participate, perceived behavioral control does not seem to have a significant impact on participation intention because securities type crowdfunding is an investment in an early-stage business with a high risk of loss. On the other hand, the study has great significance in that it empirically confirmed that domestic securities type crowdfunding investors perceive the funding progress information provided by the platform as a signal and imitate many other investors, showing herd behavior when they actually make an investment. It is expected that this study will provide meaningful insights for the policy making of crowdfunding supervisory offices and platform operators by empirically identifying major variables that influence the participation intentions and herd behavior of domestic securities type crowdfunding investors.
This study was conducted (1) to measure the nitrogen content of various parts of trees in a 24-year-old Pinus koraiensis plantation, providing a harvest method with the least impact on the self-serving mechanisms in the nitrogen status of the ecosystem and (2) to examine the seasonal changes in inorganic nitrogen (ammonium salt and nitrate, separately) at various soil depths and to study the self-serving mechanisms for nitrogen at the ecosystem, providing an appropriate method and season for the application of nitrogen fertilizers. The results obtained in this study were as follows; 1) Of the total nitrogen content of the total tree biomass (except for roots), nearly 61.5% was distributed in the needles, 20% in the branches, 5.5% in the stem bark, and 13% in the stem wood. Therefore, the harvest method of removing only wood parts for pulpwood production has little impact on the self-serving mechanisms of the site's nitrogen status. 2) Inorganic nitrogen concentrations decreased with increasing soil depths. The seasonal average concentration of inorganic nitrogen was highest in early spring and decreased in the following descending order; autumn, tollowed by mid-summer, and early summer. This pattern resulted from the fact that the loss of nitrate was greatly influenced by environmental factors. Thus, it was suggested that an application of active nitrogen fertilizer would be appropriate in spring.
Currently, the world is making efforts to develop cultural industries around more refined parts of the world. The development of cultural industries has far-reaching implications for promoting national brands and national image promotion as well as economic benefits. In particular, China hopes to advance into its own animation market because it has an extensive animation market. In 2005 The Chinese government, however, banned foreign animation market from entering the Chinese animation market. However, at that time, Chinese animation firms also saw considerable economic losses because they had to undergo almost everything from animation to distribution to rationing. In fact, the policy was designed to protect Chinese animations, but instead of preventing Chinese animations from developing original contents, it caused various problems such as China's animations, or the development of Chinese animation industries. In this thesis, we will explore the policy related to animation industry in China, research and development of animation industry, and establish the direction of development of Chinese animation industry through suggestion of improvement in Chinese animation industry. For starters, we have diversified the contents of the Chinese animation industry by adapting the contents of the Chinese animation to the global market through the globalization of contents, stories and materials. Currently, animation is developing beyond 3D,4D and VR but there is no shortage of animation experts in China, so it is necessary to nurture specialized professionals by opening a related department in China. Also, the government will establish a National Animation Industry complex to work in various animation companies. We expect to develop cultural contents through mutual cooperation between animation companies in China and the sharing of information sharing and collaborative research.
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