• 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.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• Journal of Bio-Environment Control
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• v.30 no.3
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• pp.218-229
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• 2021

Recently, as consumers' interest and importance in health care have significantly increased, they prefer natural and organic foods that do not use chemical pesticides. Since sprout vegetables effectively promote health and prevent diseases such as cancer and cardiovascular disease, the consumption of sprout vegetables, a highly functional and safe food, has been increased significantly. This study aimed to investigate the effect of light on the growth and bioactive compounds of seven different sprout vegetables. After sowing the seeds of various sprout vegetables (kale, Chinese kale, broccoli, red cabbage, alfalfa, red radish, and radish), the sprouts were cultivated under light conditions (20℃, RGB 6:1:3, 130 μmol·m^-2·s^-1, 12 hours photoperiod) and dark condition for 7 days. Sprouts samples were taken at 1-day intervals from 4 to 7 days after treatment. The fresh weight, dry weight, plant height, total phenol content, and antioxidant capacity were measured. Brassica species (kale, Chinese kale, broccoli, red cabbage) and Medicago species (alfalfa) had significantly higher fresh weight values under dark conditions, while the content of bioactive compounds was increased considerably under light conditions. In contrast, the fresh weight of Raphanus genus (red radish, radish) significantly increased under the light condition, but the antioxidant phenolic compounds were significantly higher under the dark state. A negative correlation was observed between the growth and secondary metabolites in various sprout vegetables. This study confirmed the effect of light and dark conditions on different sprout vegetables' growth and nutritional value and emphasizes the importance of harvest time in producing high-quality sprout vegetables.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.367-373
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• 2022

The purpose of this study is to derive the factors for purchasing a meal kit in their 20s and 30s and analyze the purchasing behavior from which factors they want to buy a meal kit in each lifestyle type. The first methodology of this study is inducing 7 factors derived from previous research on purchasing a meal kit. The second is the in-depth interview on 3 male and 3 female participants with clear purchasing criteria. As a result of the study, meal kit buyers in their 20s-30s evaluated the importance of purchasing factors in the order of quality, convenience, and taste on average in the survey. In in-depth interviews, more than half answered that they could be satisfied with the experience of using the meal kit at least freshness met. In conclusion, MZ generation meal kit consumers have a high rate of pursuing rational consumption. This study is valuable in understanding the priorities of the MZ generation's meal kit purchasing attributes and examining lifestyle type's purchasing behaviors.

• Korean Journal of School Psychology
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• v.18 no.1
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• pp.49-70
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• 2021

The purpose of the study was to examine Korean high school students' experience and perceptions of friendship and to inductively conceptualize friendship. The concept mapping method which is used to quantitatively analyze qualitative data was used to identify and visualize participants' experiences and perceptions of friendship. Through a brainstorming process, 93 statements were generated by boys and 100 statements were generated by girls, each set of which were sorted and categorized to generate concept maps. The final concept maps from both group equally had two dimensions: 'Practical-Conceptual' and 'Behavioral-Emotional'. The number of categories was equal to four, but there were some differences in the specifics of the statements in the category. Boys tended to conceptualize friendship as a source of happiness; a type of informal relationship through which they could share their everyday lives; and provide mutual care and engage in emotional bonding. In addition to those conceptualizations, girls also tended to conceptualize friendship as an affective alliance through which they displayed devotion to each other. Boys regarded the sympathy and bonding found in and the happiness produced by friendship as more important elements, whereas girls regarded the care and support found in and the informal nature of friendship as more important

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.477-482
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• 2022

The structure of the turnout track is very complex, so it is a facility that is more difficult to maintain and requires detailed management than a general track type. The purpose of this study is to analyze the effect on the deformation of the turnout system of the ground section due to the excavation work adjacent to the serviced urban railways. In this study, based on finite element analysis for each stage of adjacent excavation, the track deformation for each major location of turnout system was analyzed in consideration of the layout of the turnout system installed on the ground section, and the safety and stability was confirmed by comparing it with the track irregularity regulation. As a result of the study, it was found that the major construction stage affecting the track deformation of the turnout system on the ground section was the final stage of excavation. In addition, although the vertical displacement which is a vertical irregularity occurred relatively large, it was analyzed that the horizontal deformation was dominant overall, because of the excavation site is located on the side of the turnout system. In addition, it was analyzed that the amount of displacement at each major location of the turnout system is different, and there is a possibility that there may be a twist irregularity due to the deviation of the track deformation for each location according to the distance from the excavation site. Therefore, it was analyzed that it is necessary to classify and manage the importance of the track deformation of the turnout system of actual operating line, including additional displacement due to adjacent excavation, based on the track irregularity that has occurred at each location where the major deformation characteristics occur.

• Journal of Environmental Impact Assessment
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• v.32 no.1
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• pp.29-40
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• 2023

The need for improvement is raised due to limitations with environmental impact assessment, and the importance for data-based environmental impact assessment is increasing. In this study, data demand was derived by analyzing Agreed Terms and Conditions in the Water Environment field (Water Quality, Hydraulic & Hydrologic Conditions, and Marine Environment) of environmental impact assessment. Agreed Terms and Conditions on environmental impact assessment in the water environment field were classified and categorized by environmental impact assessment stage (addition to status survey, impact prediction and evaluation, establishment of reduction measures, post-environmental impact survey), and data demand for each type of consultation opinion was linked. As a result of the categorization of Agreed Terms and Conditions, it was classified into 18 types in the water quality, 15 types in the hydraulic & hydrologic conditions, and 17 types in the marine environment. As a result of linking data demand, the total number of data demand was 236 in the water quality, 98 in the hydraulic & hydrologic conditions, and 73 in the marine environment. The highest number of Agreed Terms and Conditions and data demands were found in the water quality for the evaluation item and establishment of reduction measures, specifically establishment of non-point source pollution reduction measures, for the stage. The numbers were judged to be linked to the relative importance of the items and the primary purpose of environmental impact assessment. The derivation of data demand through the analysis of Agreed Terms and Conditions in the environmental impact assessment can contribute to the advancement of the preparation of environmental impact assessment reports and is expected to increase data utilization by various decision-makers by establishing a systematic database.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.71-86
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• 2023

The purpose of this exploratory study is to compare the differences in public perceptual characteristics of Korean and Chinese societies regarding the metaverse using big data analysis. Due to the environmental impact of the COVID-19 pandemic, technological progress, and the expansion of new consumer bases such as generation Z and Alpha, the world's interest in the metaverse is drawing attention, and related academic studies have been also in full swing from 2021. In particular, Korea and China have emerged as major leading countries in the metaverse industry. It is a timely research question to discover the difference in social awareness using big data accumulated in both countries at a time when the amount of mentions on the metaverse has skyrocketed. The analysis technique identifies the importance of key words by analyzing word frequency, N-gram, and TF-IDF of clean data through text mining analysis, and analyzes the density and centrality of semantic networks to determine the strength of connection between words and their semantic relevance. Python 3.9 Anaconda data science platform 3 and Textom 6 versions were used, and UCINET 6.759 analysis and visualization were performed for semantic network analysis and structural CONCOR analysis. As a result, four blocks, each of which are similar word groups, were driven. These blocks represent different perspectives that reflect the types of social perceptions of the metaverse in both countries. Studies on the metaverse are increasing, but studies on comparative research approaches between countries from a cross-cultural aspect have not yet been conducted. At this point, as a preceding study, this study will be able to provide theoretical grounds and meaningful insights to future studies.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.327-351
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• 2023

This paper aims to derive success factors that successfully lead an artificial intelligence (AI) project and prioritize importance. To this end, we first reviewed prior related studies to select success factors and finally derived 17 factors through expert interviews. Then, we developed a hierarchical model based on the TOE framework. With a hierarchical model, a survey was conducted on experts from AI-using companies and experts from supplier companies that support AI advice and technologies, platforms, and applications and analyzed using AHP methods. As a result of the analysis, organizational and technical factors are more important than environmental factors, but organizational factors are a little more critical. Among the organizational factors, strategic/clear business needs, AI implementation/utilization capabilities, and collaboration/communication between departments were the most important. Among the technical factors, sufficient amount and quality of data for AI learning were derived as the most important factors, followed by IT infrastructure/compatibility. Regarding environmental factors, customer preparation and support for the direct use of AI were essential. Looking at the importance of each 17 individual factors, data availability and quality (0.2245) were the most important, followed by strategy/clear business needs (0.1076) and customer readiness/support (0.0763). These results can guide successful implementation and development for companies considering or implementing AI adoption, service providers supporting AI adoption, and government policymakers seeking to foster the AI industry. In addition, they are expected to contribute to researchers who aim to study AI success models.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.284-298
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• 2022

It is necessary to acquire information on traffic safety facilities installed on the roadways specifically for the operation of autonomous vehicles. The purpose of this study is to prepare a Korean version of an integrated message-set design as a way to provide to autonomous vehicles standardized information on traffic safety facilities. In this study, necessary facilities are classified according to four criteria (no legal basis; not providing information to autonomous vehicles; providing duplicate information; not standardized, and too difficult to generalize) based on information that must be provided to operate autonomous vehicles. The priority of information delivery (gross negligence followed by behavior change) was classified according to the importance of the information to be provided during autonomous driving, and the form was defined for the classification code in the information delivered. Finally, the information location and delivery method of traffic facilities for compliance with SAE J2735 were identified. This study is meaningful in that it provides a plan for roadway operations by suggesting a method for providing information to autonomously driven vehicles.