Journal of Practical Agriculture & Fisheries Research
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v.10
no.1
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pp.43-58
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2008
This research was conducted to determine the alternative tool of chemical spray for rice cultivation using the unmanned helicopter(Yamaha, R-Max Type 2G-remote controlled system) at farmer's field in Korea. The unmanned helicopter tested was introduced form Japan. In Korea the application of chemicals by machine sprayer for pest management in rice cultivation has been ordinarily used at the farmer's level. However, it involved a relatively high cost and laborious for the small scale of cultivation per farm household. Farm population has been highly decreased to 7.5% in 2002 and the population is expected to rapidly reduce by 3.5% in 2012. In Japan, pest control depending on unmanned helicopter has been increased by leaps and bounds. This was due in part to the materialization of the low-cost production technology under agricultural policy and demand environmentally friendly farm products. The practicability of the unmanned helicopter in terms of super efficiency and effectiveness has been proven, and the farmers have understood that the unmanned helicopter is indispensable in the future farming system that they visualized. Also, the unmanned helicopter has been applied to rice, wheat, soybean, vegetables, fruit trees, pine trees for spraying chemicals and/or fertilizers in Japan Effect of disease control by unmanned helicopter was partially approved against rice blast and sheath blight. However, the result was not satisfactory due to the weather conditions and cultural practices. The spray density was also determined in this experiment at 0, 15, 30, and 60cm height from the paddy soil surface and there was 968 spots at 0cm, 1,560 spots at 15cm, 1,923 spots at 30cm, and 2,999 spots at 60cm height. However, no significant difference was found among the treatments. At the same time, there was no phytotoxicity observed under the chemical stray using this unmanned helicopter, nor the rice plant itself was damaged by the wind during the operation.
Journal of Dental Rehabilitation and Applied Science
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v.38
no.1
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pp.1-8
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2022
Purpose: The purpose of this study was to evaluate the effects of mouthwash containing sodium chloride on dental plaque, gingival inflammation index, and bad breath through clinical trials. Materials and Methods: This trial was designed as 12 weeks and subjects were instructed to put an appropriate amount of the provided standard detergent on a toothbrush and brush their teeth 3 times a day. They were instructed to gargle a mouthwash provided to each group after brushiung. Efficacy was evaluated by performing gingival and periodontal-related index tests, dental plaque changes, and bad breath tests a total of 5 times. All data were statistically analyzed using 2-sample t-test, paired t-test to compare between groups at 95% significance level using IBM SPSS Statistics 24.0. Results: As a result of the PMA index measurement, the gingivitis improvement effect rate of the experimental group compared to the control group was 107.63% after 8 weeks and 73.08% after 12 weeks. As a result of the PHP index measurement, the plaque improvement effect rate of the experimental group compared to the control group was 79.37% after 8 weeks and 74.06% after 12 weeks. As a result of measuring volatile sulfur compounds using Oral Chroma, the effectiveness of improvement in bad breath in the experimental group was 65.06% after 8 weeks and 99.33% after 12 weeks, compared to the control group. Conclusion: As a result of this study, it was confirmed that effective gingivitis alleviation, plaque removal effect and bad breath removal effect can be expected when a mouthwash containing sodium chloride, green tea extract, and sodium monofluorophosphate is used.
It is reported that particulate matter(PM) penetrates the lungs and blood vessels and causes various heart diseases and respiratory diseases such as lung cancer. The subway is a means of transportation used by an average of 10 million people a day, and although it is important to create a clean and comfortable environment, the level of particulate matter pollution is shown to be high. It is because the subways run through an underground tunnel and the particulate matter trapped in the tunnel moves to the underground station due to the train wind. The Ministry of Environment and the Seoul Metropolitan Government are making various efforts to reduce PM concentration by establishing measures to improve air quality at underground stations. The smart air quality management system is a system that manages air quality in advance by collecting air quality data, analyzing and predicting the PM concentration. The prediction model of the PM concentration is an important component of this system. Various studies on time series data prediction are being conducted, but in relation to the PM prediction in subway stations, it is limited to statistical or recurrent neural network-based deep learning model researches. Therefore, in this study, we propose four transformer-based models including spatiotemporal transformers. As a result of performing PM concentration prediction experiments in the waiting rooms of subway stations in Seoul, it was confirmed that the performance of the transformer-based models was superior to that of the existing ARIMA, LSTM, and Seq2Seq models. Among the transformer-based models, the performance of the spatiotemporal transformers was the best. The smart air quality management system operated through data-based prediction becomes more effective and energy efficient as the accuracy of PM prediction improves. The results of this study are expected to contribute to the efficient operation of the smart air quality management system.
In the fields of science and engineering, multidisciplinary research is common, and researchers with a diverse range of expertise collaborate to achieve common goals. As the 4th industrial revolution gains currency in society, there is growing demand on talented personnel both with technical knowledge and skills and with communicative skills. That is, future engineers are expected to possess competence in social and artistic skills in addition to specialized knowledge and skills in engineering. In this paper we introduce an emerging field of 3D bioprinting as an exemplary case of interdisciplinary research. We have chosen the case to demonstrate the possibility of cultivating engineers with π-shaped expertise. Building on the concept of T-shaped talent, we define π-shaped expertise as having both technical skills in more than one specialized field and interpersonal/communicative skills. Wtih references to such concepts as trading zones and interactional expertise, we suggest that π-shaped expertise can be cultivated via the creation of multi-level trading zones. Trading zones are referred to as the physical, conceptual, or metaphorical spaces in which experts with different world views trade ideas, objects, and the like. Interactional expertise is cultivated, as interactions between researches are under way, with growing understanding of each other's expertise. Under the support of the university and the government, two researchers with expertise in printing technology and life sciences cooperate to develop a 3D bioprinting system. And the primary investigator of the research laboratory under study has aimed to create multiple dimensions of trading zones where researchers with different educational and cultural backgrounds can exchange ideas and interact with each other. As 3D bioprinting has taken shape, we have found that a new form of expertise, namely π-shaped expertise is formed.
Kwang-Seok Chea;Namin Koo;Young Geun Lee;Hee Moon Yang;Ki Hyung Park
Korean Journal of Mineralogy and Petrology
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v.36
no.2
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pp.135-145
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2023
Aggregate is used to produce stable materials like concrete and asphalt and is fundamental to meet the social needs of housing, industry, road, energy and health. A total of 42.35 billion tons of aggregate were produced in 2021 worldwide, an increase of 0.91% compared to the previous year. Among them, 2 billion tons were produced in China, India, European Union and United States, making up to 71.75% of the share. South Korea has witnessed a constant increase in aggregate production, overtaking Mexico and Japan for seventh place with 390 million tons and 0.85% of the share. The industrial sand and gravel produced globally amounted to 352.66 million tons. The top seven countries with the highest production were China, United States, Netherlands, Italy, India, Turkey and France, and their production exceeded 10 million tons and held a share of 74.69%. Exports of natural rock recorded $21.68 billion in 2021, increased by $2.3 billion compared to the previous year, while exports of artificial rock increased by $2.66 billion to $13.59 billion. Exports of sand reached $1.71 billion with United States, Netherlands, Germany and Belgium being the four countries with the highest exports of sand. The four countries exported more than $100 million in sand and took up 57.70% of the total amount. Exports of gravel totaled $2.75 billion, with China, Norway, Germany, Belgium, France and Austria in the lead, making up to 48.30% of the total share. The aggregate quarry started to surge in the 1950s due to the change in people's lifestyle such as population growth, urbanization and infrastructure delvelopment. Demand for aggregate is also skyrocketing to prevent land reclamation and flood caused by sea-level rise. Demand for aggregate, which was around 24 gigatons in 2011, is expected to double to 55 gigatons in 2060. However, it is likely that aggregate extraction will heavily damage the ecosystem and the world will eventually face a shortage of aggregate followed by tense social conflict.
Proceedings of the Korea Water Resources Association Conference
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2021.06a
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pp.6-7
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2021
Vegetation development in rivers is one of the important issues not only in academic fields such as geomorphology, ecology, hydraulics, etc., but also in river management practices. The problem of river vegetation is directly connected to the harmony of conflicting values of flood management and ecosystem conservation. In Korea, since the 2000s, the issue of river vegetation and land formation has been continuously raised under various conditions, such as the regulating rivers downstream of the dams, the small eutrophicated tributary rivers, and the floodplain sites for the four major river projects. In this background, this study proposes a method for classifying the distribution of vegetation in rivers based on remote sensing data, and presents the results of applying this to the Naeseong Stream. The Naeseong Stream is a representative example of the river landscape that has changed due to vegetation development from 2014 to the latest. The remote sensing data used in the study are images of Sentinel 1 and 2 satellites, which is operated by the European Aerospace Administration (ESA), and provided by Google Earth Engine. For the ground truth, manually classified dataset on the surface of the Naeseong Stream in 2016 were used, where the area is divided into eight types including water, sand and herbaceous and woody vegetation. The classification method used a random forest classification technique, one of the machine learning algorithms. 1,000 samples were extracted from 10 pre-selected polygon regions, each half of them were used as training and verification data. The accuracy based on the verification data was found to be 82~85%. The model established through training was also applied to images from 2016 to 2020, and the process of changes in vegetation zones according to the year was presented. The technical limitations and improvement measures of this paper were considered. By providing quantitative information of the vegetation distribution, this technique is expected to be useful in practical management of vegetation such as thinning and rejuvenation of river vegetation as well as technical fields such as flood level calculation and flow-vegetation coupled modeling in rivers.
Yun O;Ji Seop Son;Han Sol Park;Young Hoon Lee;Jin Song Shin;Da som Park;Eun NamGung;Tae Jin Cho
Journal of Food Hygiene and Safety
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v.38
no.1
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pp.1-11
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2023
Skin sanitizers are effective in killing or removing pathogenic microbial contaminants from the skin of food handlers, and the progressive growth of consumer interest in personal hygiene tends to drive product diversification. This review covers the advances in the application of efficacy tests for hand sanitizers to suggest future perspectives to establish an assessment system that is optimized to each product type (gel, liquid, and wipes). Previous research on the in vivo simulative test of actual consumer use has adopted diverse experimental conditions regardless of the product type. This highlights the importance of establishing optimal test protocols specialized for the compositional characteristics of sanitizers through the comparative analysis of test methods. Although the operational conditions of the mechanical actions associated with wiping can affect the efficacy of the removal and/or the inactivation of target microorganisms from the skin's surface, currently there is a lack of standardized use patterns for the exposure of hand sanitizing wipes to skin. Thus, major determinants affecting the results from each step of the overall assessment procedures [pre-treatment - exposure of sanitizers - microbial recovery] should be identified to modify current protocols and develop novel test methods. The ex vivo test, designed to overcome the limited reproducibility of in vivo human trials, is also expected to replicate the environment for the contact of sanitizers targeting skin microorganisms. Recent progress in the area of skin microbiome research revealed distinct microbial characteristics and distribution patterns after the application of sanitizers on hands to establish the test methods with the perspectives on the antimicrobial effects at the community level. The future perspectives presented in this study on the improvement of efficacy test methods for hand sanitizers can also contribute to public health and food safety through the commercialization of effective sanitizer products.
Carbon management is emerging as an important factor for global warming control, and land use change is considered one of the causes. To quantify the changes in carbon stocks due to development, this study attempted to calculate carbon storage by borrowing the formula of the InVEST Carbon Storage and Sequestration Model (InVEST Model). Before analyzing carbon stocks, a carbon pool was compiled based on previous studies in Korea. Then, we estimated the change in carbon stocks according to the development of Osong National Industrial Park (ONIP) and the application of alternatives. The analysis shows that 16,789.5 MgC will be emitted under Alternative 1 and 16,305.3 MgC under Alternative 2. These emissions account for 44.4% and 43.1% of the pre-project carbon stock, respectively, and shows that choosing Alternative 2 is advantageous for reducing carbon emissions. The difference is likely due to the difference in grassland area between Alternatives 1 and 2. Even if Alternative 2 is selected, efforts are needed to increase the carbon storage effect by managing the appropriate level of green cover in the grassland, creating multi-layered vegetation, and installing low-energy facilities. In addition, it is suggested to conserve wetlands that can be lost during the stream improvement process or to create artificial wetlands to increase carbon storage. The assessment of carbon storage using carbon pools by land cover can improve the objectivity of comparison and evaluation analysis results for land use plans in Environmental Impact Assessment and Strategic Environmental Impact Assessment. In addition, the carbon pool generated in this study is expected to be used as a basis for improving the accuracy of such analyses.
As the 4th industrial revolution progresses, foreign countries are promoting smart manufacturing innovation through digital transformation as a priority task early on to secure a competitive edge in the manufacturing industry. In response, the Korean government is also promoting a policy to enhance the competitiveness of small and medium-sized manufacturing companies by promoting digital transformation in the corporate sector to meet the global trend of the 4th industrial revolution era. Manufacturing powerhouses such as Germany and Japan see manufacturing as a key sector in digital transformation and are leading related policies, while emerging countries such as China are also promoting manufacturing innovation strategies such as building digital infrastructure and creating a digital innovation ecosystem. Korea is promoting the 'Korean-style smart factory dissemination and expansion strategy' by transforming Germany's manufacturing innovation strategy for smart factory supply to suit the domestic situation. However, the policy to supply smart factories so far has been conducted with support from individual companies under the leadership of the government, and most of the smart factories are at the basic level, and it is evaluated that there are limitations such as the lack of manpower to operate smart factories. In addition, while the current policy focuses on expanding the supply of smart factories in SMEs, it is necessary to establish a smart manufacturing system through linkages between large and small businesses in order to achieve the original goal of establishing a smart manufacturing system. Therefore, it can be said that from the standpoint of small and medium-sized enterprises (SMEs), who are consumers of smart factories, it can be said that the digital transformation policy can achieve the expected results only when appropriate incentives are provided for the introduction of smart factories in a situation where management resources such as funds, technology, and human resources are lacking. In addition, it is judged that the uncertainty of the performance of digital investment always exists, and as long as large and small companies are maintained as an ecosystem of delivery and subcontracting, there is very little incentive for small and medium-sized manufacturing companies to voluntarily invest in or advance digital transformation. Therefore, the digital transformation policy of small and medium-sized manufacturing companies in the future has practical significance in that it suggests that there is a need to seek ways to attract SMEs' digital-related voluntary investment.
Lee, Jiwon;Gim, Tae-Hyoung Tommy;Park, Yunmi;Chung, Hyung-Chul;Handayani, Wiwandari;Lee, Hee-Chung;Yoon, Dong Keun;Pai, Jen Te
Land and Housing Review
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v.14
no.4
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pp.77-93
/
2023
The COVID-19 pandemic has brought about significant social changes through government prevention and control measures, changes in people's risk perceptions, and lifestyle changes. In response, urban inhabitants changed their behaviors significantly, including their preferences for transportation modes and urban spaces in response to government quarantine policies and concerns over the potential risk of infection in urban spaces. These changes may have long-lasting effects on urban spaces beyond the COVID-19 pandemic or they may evolve and develop new forms. Therefore, this study aims to explore the potential for urban spaces to adapt to the present and future pandemics by examining changes in urban residents' preferences in travel modes and urban space use due to the COVID-19 pandemic. This study found that overall preferences for travel modes and urban spaces significantly differ between the pre-pandemic, pandemic, and post-pandemic periods. During the pandemic, preferences for travel modes and urban spaces has decreased, except for privately owned vehicles and green spaces, which are perceived to be safe from transmission, show more favorable than others. Post-pandemic preferences for travel modes and urban spaces are less favorable than pre-pandemic with urban spaces being five times less favorable than transportation. Although green spaces and medical facilities that were positively perceived during the pandemic are expected to return to the pre-pandemic preference level, other factors of urban spaces are facing a new-normal. The findings suggest that the COVID-19 pandemic has had a significant impact on urban residents' preferences for travel modes and urban space use. Understanding these changes is crucial for developing strategies to adapt to present and future pandemics and improve urban resilience.
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