• Journal of the Korean Magnetic Resonance Society
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• v.22 no.4
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• pp.91-100
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• 2018

Benzisothiazolinone (BIT) is the preservative that is widely used in industrial and household products. In this study, zebrafish (Danio rerio) was exposed to BIT at different concentrations (control, 0.5 g/L, 1.0 g/L and 2.0 g/L) for 72 hours. The techniques of nuclear magnetic resonance (NMR) spectroscopy were applied to analyze the effects of BIT on zebrafish. The advantages of NMR are the minimal sample preparation and high reproducibility of experimental results. With the multivariate statistical analysis, dimethylamine, N-acetylaspartate, glycine and histidine were identified as an important metabolite in differentiating between the control and BIT-exposed group. This study will improve the understanding the metabolite changes in the zebrafish in response to BIT exposure.

• Convergence Security Journal
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• v.17 no.5
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• pp.93-99
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• 2017

Recently IoT(Internet of Things) service industry has grown very rapidly. In this paper, we investigated the changes in IoT service industry as well as new direction of human life in future global society. Under these changing market conditions, competition has been also changed into global and ecological competition. But compared to the platform initiatives and ecological strategies of global companies, Korean companies' vision of building ecosystems is still unclear. In addition, there is a need of internetworking between mobile and IoT services. IoT security Protocol has weakness of leaking out information from Gateway which connected wire and wireless communication. As such, we investigate the structure of IoT and AI service ecosystem in order to gain strategic implications and insights for the security industry in this paper.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.361-368
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• 2019

This paper is a study on integrated air-conditioning system for 1-ton class commercial vehicle based on electric vehicle. In the case of an electric commercial vehicle, since the opening and closing of the door is frequently performed in order to get in and out of the cargo, the heat loss largely occurs. Therefore, the heating and cooling load is required to be larger than the electric vehicle. As a result, the energy consumed by the heating and cooling system is larger than the passenger electric car in order to satisfy the heat comfort required by passengers. In order to overcome these disadvantages, we performed research using an efficient integrated air conditioning system. Finally, the design and analysis of a heat pump system for heating and a electrical compressor for cooling need to be proceed to develop a high-efficiency air conditioning system for improving the commerciality of 1 ton-class electric trucks and expanding the industrial ecosystem in the electric truck sector.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.327-335
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• 2021

We aimed to find new space types and characteristics for creating gardens in the city through the type of idle space in the city, present guidelines that can be used in creating gardens in the future, and establish basic data for expanding green infrastructure. As a result, we found that the idle space in the city was classified into four types, and it was determined that differentiation should be given to the creation of each type. The achievements of this study can be a potential source of urban ecosystem services that can provide community benefits and opportunities for urban regeneration through the redevelopment of the community and support the health and well-being of local residents. In addition, urban idle space can be a valuable resource as a green infrastructure that can be used to support the health of urban ecosystems and improve the quality of life of urban residents.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.133-139
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• 2020

Big data, artificial intelligence (AI), and machine learning are keywords that represent the Fourth industrial Revolution. In addition, as the development of science and technology, the Korean government, public institutions and industries want professionals who can collect, analyze, utilize and predict data. This means that data analysis and utilization education become more important. Education on data analysis and utilization is increasing with trends in other academy. However, it is true that not many academy run long-term and systematic education. Korea Institute of Science and Technology Information (KISTI) is a data ecosystem hub and one of its performance missions has been providing data utilization and analysis education to meet the needs of industries, institutions and governments since 1966. In this study, KISTI's data education was analyzed using the number of curriculum trainees per year from 2001 to 2019. With this data, the change of interest in education in information and data field was analyzed by reflecting social and historical situations. And we identified the characteristics of KISTI and trainees. It means that the identity, characteristics, infrastructure, and resources of the institution have a greater impact on the trainees' interest of data-use education.In particular, KISTI, as a research institute, conducts research in various fields, including bio, weather, traffic, disaster and so on. And it has various research data in science and technology field. The purpose of this study can provide direction forthe establishment of new curriculum using data that can represent KISTI's strengths and identity. One of the conclusions of this paper would be KISTI's greatest advantages if it could be used in education to analyze and visualize many research data. Finally, through this study, it can expect that KISTI will be able to present a new direction for designing data curricula with quality education that can fulfill its role and responsibilities and highlight its strengths.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.1
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• pp.63-69
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• 2021

Microalgae are primary producers of aquatic ecosystems, securing biodiversity and health of the ecosystem and contributing to reducing the impact of climate change through carbon dioxide fixation. Also, they are useful biomass that can be used as biological resources for producing valuable industrial products. However, harvesting process, which is the separation of microalgal biomass from mixed liquor, is an important bottleneck in use of valorization of microalgae as a bioresource accounting for 20 to 30% of the total production cost. This study investigates the applicability of sewage sludge-derived extracellular polymeric substance (EPS) as bioflucculant for harvesting microalgae. We compared the flocculation characteristics of microalgae using EPSs extracted from sewage sludge by three methods. The flocculation efficiency of microalgae is closely related to the carbohydrate and protein concentrations of EPS. Heat-extracted EPS contains the highest carbohydrate and protein concentrations and can be a best-suited bioflocculant for microalgae recovery with 87.2% flocculation efficiency. Injection of bioflocculant improved the flocculation efficiency of all three different algal strains, Chlorella Vulgaris, Chlamydomonas Asymmetrica, Scenedesmus sp., however the improvement was more significant when it was used for flocculation of Chlamydomonas Asymmetrica with flagella.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.289-294
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• 2022

Oil contained in domestic and industrial wastewater or marine spilled oil gives rise to severe environmental pollution issues such as water pollution and ecosystem destruction. The membrane filtration method as one of representative oil/water separation strategies has technological challenges such as membrane fouling and low separation rate. In this work, we devise a 3D-printed microhydrocyclone for oil/water separation by utilizing a digital lighting processing-based 3D printer. We demonstrate that the 3D-printed microhydrocyclone can effectively separate oil and water phases from oil-in-water emulsion.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.125-135
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• 2022

This study aims to explore variables using machine learning and provide analysis techniques suitable for predicting pharmacy sales whether government statistical indicators built to create an industrial ecosystem based on data, network, and artificial intelligence affect pharmacy sales. Therefore, this study explored predictive variables and performance through machine learning techniques such as Random Forest, XGBoost, LightGBM, and CatBoost using analysis data from January 2016 to December 2021 for 28 government statistical indicators and pharmacies in the retail sector. As a result of the analysis, economic sentiment index, economic accompanying index circulation change, and consumer sentiment index, which are economic indicators, were found to be important variables affecting pharmacy sales. As a result of examining the indicators MAE, MSE, and RMSE for regression performance, random forests showed the best performance than XGBoost, LightGBM, and CatBoost. Therefore, this study presented variables and optimal machine learning techniques that affect pharmacy sales based on machine learning results, and proposed several implications and follow-up studies.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.3
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• pp.339-356
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• 2022

This study focuses on Hokkaido University Research & Business Park in Japan as an example of establishing a regional innovation ecosystem on campus based on the outstanding research and university-industry collaboration capabilities of local universities in non-metropolitan areas with weak foundations for start-ups and corporate growth. Hokkaido University Research & Business Park established a mid-to long-term plan using the idle sites on campus, and was developed through a gradual development process since 2003. The promotion of university-industry collaboration was pursued through an industrial-based approach of establishing a bio-industry cluster considering the characterization of local universities and the foundation of local industries. It also provides various corporate support services through cooperative governance between local industry, universities, research institutes and the government. This strategy for creating Hokkaido University Research & Business Park provides important policy implications for various policies and projects that promote regional development by utilizing university campuses like the campus innovation park project.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.315-320
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• 2021

While blockchain platforms for various purposes have been developed and the blockchain ecosystem is being developed, interoperability problems are emerging in which each blockchain is isolated and operated. In this study, we introduce interchain and sidechain technologies, which are blockchain that connect blockchain, and explain examples of using heterogeneous blockchain transactions and functions by applying them. In addition, blockchain, artificial intelligence, and IoT technologies, which are drawing attention in the fourth industrial revolution, are going through a process of converging and developing beyond their own development. In this regard, we present processes for combining artificial intelligence or IoT in blockchain, and propose a model that can operate without intervention by applying the combination of blockchain and artificial intelligence IoT to processes for trading and exchange between heterogeneous blockchain.