• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.153-160
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• 2021

Nitrous oxide is a global warming substance and is known as the main cause of the destruction of the ozone layer because its global warming effect is 310 times stronger than carbon dioxide, and it takes 120 years to decompose. Therefore, in this study, we investigated the characteristics of NOx emission from N2O reduction by thermal decomposition of N2O. Bunsen premixed flames were adopted as a heat source to form a high-temperature flow field, and the experimental variables were nozzle exit velocity, co-axial velocity, and N2O dilution rate. NO production rates increased with increasing N2O dilution rates, regardless of nozzle exit velocities and co-axial flow rates. For N2O, large quantities were emitted from a stable premixed flame with suppressed combustion instability (Kelvin Helmholtz instability) because the thermal decomposition time is not sufficient with the relatively short residence time of N2O near the flame surface. Thus, to improve the reduction efficiency of N2O, it is considered effective to increase the residence time of N2O by selecting the nozzle exit velocities, where K-H instability is generated and formed a flow structure of toroidal vortex near the flame surface.

• Clean Technology
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• v.27 no.2
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• pp.168-173
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• 2021

The treatment of plated wastewater is subject to various and complex processes depending on the pH, heavy metal, and cyanide content of the wastewater. Alkali chlorine treatment using NaOCl is commonly used for cyanide treatment. However, if ammonia and cyanide are present simultaneously, NaOCl is consumed excessively to treat ammonia. To solve this problem, this study investigated 1) the consumption of NaOCl according to ammonia concentration in the alkaline chlorine method and 2) whether ferrate (VI) could selectively treat the cyanide. Experiments using simulated wastewater showed that the higher the ammonia concentration, the lower the cyanide removal rate, and the linear increase in NaOCl consumption according to the ammonia concentration. Removal of cyanide using ferrate (VI) confirmed the removal of cyanide regardless of ammonia concentration. Moreover, the removal rate of ammonia was low, so it was confirmed that the ferrate (VI) selectively eliminated the cyanide. The cyanide removal efficiency of ferrate (VI) was higher with lower pH and showed more than 99% regardless of the ferrate (VI) injection amount. The actual application to plated wastewater showed a high removal ratio of over 99% when the input mole ratio of ferrate (VI) and cyanide was 1:1, consistent with the molarity of the stoichiometry reaction method, which selectively removes cyanide from actual wastewater containing ammonia and other pollutants like the result of simulated wastewater.

• Clean Technology
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• v.28 no.1
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• pp.18-23
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• 2022

Using air as an insulator due to its low heat transfer coefficient has been studied and has been widely commercialized to save energy in the field of thermal insulation technology. In this study, we analyzed the heat insulating effect of hollow silica nanoparticles mixed in non-uniform size, and the maximum heat insulating efficiency of these particles given the limited number of particles that can be mixed with a medium such as paint. The hollow silica nanoparticles were synthesized via a sol-gel process using a polystyrene template in order to produce an air layer inside of the particles. After synthesis, the particles were analyzed for their insulation effect according to the size of the air layer by adding 5 wt % of the particles to paint and investigating the thermal insulation performance by a heat transfer experiment. When mixing the particles with white paint, the insulation efficiency was 15% or higher. Furthermore, the large particles, which had a large internal air layer, showed a 5% higher insulation performance than the small particles. By observing the difference in the insulation effect according to the internal air layer size of hollow silica nanoparticles, this research suggests that when using hollow particles as a paint additive, the particle size needs to be considered in order to maximize the air layer in the paint.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.55-62
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• 2022

The perovskite solar cell is an active part of research in renewable energy fields such as solar energy, wind, hydroelectric power, marine energy, bioenergy, and hydrogen energy to replace fossil fuels such as oil, coal, and natural gas, which will gradually disappear as power demand increases due to the increase in use of the Internet of Things and Virtual environments due to the 4th industrial revolution. The perovskite solar cell is a solar cell device using an organic-inorganic hybrid material having a perovskite structure, and has advantages of replacing existing silicon solar cells with high efficiency, low cost solutions, and low temperature processes. In order to optimize the light absorption layer thin film predicted by the existing empirical method, reliability must be verified through device characteristics evaluation. However, since it costs a lot to evaluate the characteristics of the light-absorbing layer thin film device, the number of tests is limited. In order to solve this problem, the development and applicability of a clear and valid model using machine learning or artificial intelligence model as an auxiliary means for optimizing the light absorption layer thin film are considered infinite. In this study, to estimate the light absorption layer thin-film optimization of perovskite solar cells, the regression models of the support vector machine's linear kernel, R.B.F kernel, polynomial kernel, and sigmoid kernel were compared to verify the accuracy difference for each kernel function.

• Resources Recycling
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• v.31 no.4
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• pp.12-18
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• 2022

Korea depends on the import of raw materials such as iron ore and coal for the steel industry. These raw materials have a major impact on the cost, productivity, and quality competitiveness in the global steel industry. To secure the competitiveness of steel companies, it is necessary to reduce the country's dependence on raw materials. This can be achieved using byproducts with a high Fe content, which are primarily generated by the steel industry. These byproducts are available in the form of a very fine powder, which can disperse as dust when used directly in plant processes. Dust dispersion has a negative impact on the environment and can lead to the loss of raw materials. To enable the use of a wide range of Fe-containing byproducts, it is necessary to pretreat them in the form of larger aggregates such as pellets and briquettes. There are several methods to achieve such aggregates. There are two ways to produce briquettes: using a hot briquette, which supplies additional heat to produce briquettes, or using a cold briquette, which does not use heat. A method for producing cold briquettes using Fe-containing byproducts was investigated in this study. The yield ratio and briquette strength were examined under various manufacturing conditions.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.99-115
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• 2022

In this study, domestic academic journal papers on tax compliance, tax consciousness, and faithful tax payment (hereinafter referred to as "tax compliance") were comprehensively analyzed from an interdisciplinary perspective as a representative research topic in the field of tax science. To achieve the research purpose, topic modeling technique was applied as part of text mining. In the flow of data collection-keyword preprocessing-topic model analysis, potential research topics were presented from tax compliance related keywords registered by the researcher in a total of 347 papers. The results of this study can be summarized as follows. First, in the keyword analysis, keywords such as tax investigation, tax avoidance, and honest tax reporting system were included in the top 5 keywords based on simple term-frequency, and in the TF-IDF value considering the relative importance of keywords, they were also included in the top 5 keywords. On the other hand, the keyword, tax evasion, was included in the top keyword based on the TF-IDF value, whereas it was not highlighted in the simple term-frequency. Second, eight potential research topics were derived through topic modeling. The topics covered are (1) tax fairness and suppression of tax offenses, (2) the ideology of the tax law and the validity of tax policies, (3) the principle of substance over form and guarantee of tax receivables (4) tax compliance costs and tax administration services, (5) the tax returns self- assessment system and tax experts, (6) tax climate and strategic tax behavior, (7) multifaceted tax behavior and differential compliance intentions, (8) tax information system and tax resource management. The research comprehensively looked at the various perspectives on the tax compliance from an interdisciplinary perspective, thereby comprehensively grasping past research trends on tax compliance and suggesting the direction of future research.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.363-369
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• 2021

High-definition road maps are used as the basic infrastructure for autonomous vehicles, so the latest road information must be quickly reflected. However, the current drawing and structural editing process of high-definition road maps are manually performed. In addition, it takes the longest time to generate road lanes, which are the main construction targets. In this study, the point cloud of the road lane markings, in which color types(white, blue, and yellow) were predicted through the PointNet model pre-trained in previous studies, were used as input data. Based on the point cloud, this study proposed a methodology for automatically drawing and structural editing of the layer of road lane markings. To verify the usability of the 3D vector data constructed through the proposed methodology, the accuracy was analyzed according to the quality inspection criteria of high-definition road maps. In the positional accuracy test of the vector data, the RMSE (Root Mean Square Error) for horizontal and vertical errors were within 0.1m to verify suitability. In the structural editing accuracy test of the vector data, the structural editing accuracy of the road lane markings type and kind were 88.235%, respectively, and the usability was verified. Therefore, it was found that the methodology proposed in this study can efficiently construct vector data of road lanes for high-definition road maps.

• Applied Chemistry for Engineering
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• v.34 no.1
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• pp.15-22
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• 2023

Recent studies have actively investigated ways to improve the economic feasibility and efficiency of the Fischer-Tropsch process by increasing the yields of the monocyclic aromatic compounds (BTEX). In this study, ethylene was selected as a model of F-T-derived hydrocarbons, and the ethylene-to-aromatics (ETA) reaction was investigated according to changes in acid characteristics, mesopores, and crystallinity of HZSM-5 (HZ5). Fluorinated HZ5 was prepared by calcination followed by impregnation of an aqueous NH₄F solution having different molar concentrations in HZ5, and the structural and chemical properties of F/HZ5 were investigated through Brunauer-Emmett-Teller (BET), solid-state nuclear magnetic resonance (NMR), X-ray photoelectron spectroscopy (XPS), NH₃-temperature-programmed desorption (TPD), and pyridine-IR spectroscopy. The ETA reactions were performed at 673 K under 0.1 MPa, and fluorinating HZ5 by an aqueous NH₄F solution of 0.17 M improved ethylene conversion, BTEX selectivity, and catalytic stability due to acidity, mesopore fraction, and crystallinity.

• Resources Recycling
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• v.31 no.2
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• pp.40-48
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• 2022

In this study, the effects of solution components were investigated in the recovery of vanadium as ammonium metavanadate from vanadium-ore-salt roasting-water leaching solution. The vanadium-containing solution is strongly alkaline (pH 13), so the pH must be lowered to 9 or less to increase the ammonium metavanadate precipitation efficiency. However, in the process of adjusting the solution pH using sulfuric acid, aluminum ions are co-precipitated, which must be removed first. In this study, aluminum was precipitated in the form of an aluminum-silicate compound using sodium silicate, and the conditions for minimizing vanadium loss in this process were investigated. After aluminum removal, the silicate was precipitated and removed by adjusting the solution pH to 9 or less using sulfuric acid. In this process, the concentration and addition rate of sulfuric acid have a significant influence on the loss of vanadium, and vanadium loss was minimized as much as possible by slowly adding dilute sulfuric acid. Ammonium metavanadate was precipitated using three equivalents of ammonium chloride at room temperature from the aluminum-free, aqueous solution of vanadium following the pH adjustment process. The recovery yield of vanadium in the form of ammonium metavanadate exceeded 81%. After washing the product, vanadium pentoxide with 98.6% purity was obtained following heat treatment at 550 ℃ for 2 hours.

• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.