• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.132-139
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• 2021

This corpus-driven research expounded the compilation of the most frequently occurring academic words in the domain of syntax and compared the extracted wordlist with Academic Word List(AWL) of Coxhead(2000) and General Service List(GSL) of West(1953) to examine their distribution and coverage within the syntax corpus. A specialized 546,074 token corpus, composed of widely used must-read syntax textbooks for English education majors, was loaded into and analyzed with AntWordProfiler 1.4.1. Under the parameter of lexical frequency, the analysis identified 288(50.5%) AWL word forms, appeared 16 times or more, as well as 218(38.2%) AWL items, occurred not exceeding 15 times. The analysis also indicated that the coverage of AWL and GSL accounted for 9.19% and 78.92% respectively and the combination of GSL and AWL amounted to 88.11% of all tokens. Given that AWL can be instrumental in serving broad disciplinary needs, this study highlighted the necessity to compile the domain-specific AWL as a lexical repertoire to promote academic literacy and competence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.786-792
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• 2022

In the cloud computing environment, there has been a lot of research into the Fog/Edge Computing (FEC) paradigm for securing user proximity of application services and computation offloading to alleviate service delay difficulties. The method of predicting dynamic location change patterns of edge devices (moving objects) requesting application services is critical in this FEC environment for efficient computing resource distribution and deployment. This paper proposes an optimal moving pattern extraction algorithm in which variable weights (distance, time, congestion) are applied to selected paths in addition to a support factor threshold for frequency patterns (moving objects) of edge devices. The proposed algorithm is compared to the OPE_freq [8] algorithm, which just applies frequency, as well as the A^* and Dijkstra algorithms, and it can be shown that the execution time and number of nodes accessed are reduced, and a more accurate path is extracted through experiments.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.21-29
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• 2022

Based on the importance of dialect research, preservation, and communication, this paper conducted a study on machine translation of Korean dialects for dialect users who may be marginalized. For the dialect data used, AIHUB dialect data distributed based on the highest administrative district was used. We propose a many-to-one dialect machine translation that promotes the efficiency of model distribution and modeling research to improve the performance of the dialect machine translation by applying Copy mechanism. This paper evaluates the performance of the one-to-one model and the many-to-one model as a BLEU score, and analyzes the performance of the many-to-one model in the Korean dialect from a linguistic perspective. The performance improvement of the one-to-one machine translation by applying the methodology proposed in this paper and the significant high performance of the many-to-one machine translation were derived.

• Journal of the Korean Society of Safety
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• v.37 no.6
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• pp.102-107
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• 2022

South Korea will soon be a super-aged society, as more than 20.6% of its population will be 65 years and older by 2025. As of 2022, 17.5% of the total population in South Korea is 65 years and older, which exceeds the set threshold for an aged society, where more than 14% of the population is 65 years and older. The proportion of older subway construction workers has increased. Aging workers and their work stress negatively impact their workability. A previous study demonstrated that the stress index measured using the uBioMacpa measurement device (Macpa stress index) had a significant correlation with work stress in South Korea. The device tests vascular health and measures stress levels via Macpa signal analysis. In this study, the pulse waves of subway construction workers were measured using uBioMacpa to identify their stress levels. The stress levels were analyzed by age, years of service, job position, employment type, and work type. Herein, these statistics could not be easily represented by a normal distribution; therefore, the Kruskal-Wallis test, a nonparametric statistical method, was used for the analysis of data. The results showed that age, job position, employment type, and working type affected the Macpa stress index and the stress levels of workers increased with age. In terms of job position, technical engineers were more stressed than other workers because of their poor working environment. In terms of employment type, daily-wage workers were more stressed than other workers. In terms of working type, tunneling, waterproofing, and construction scored the highest Macpa stress indexes without any significant difference, whereas earthworks scored the lowest. Based on the analysis of Macpa stress index, safety and health management plans were proposed to reduce the stress levels of workers. Moreover, a manual for efficient stress management must be developed for subway construction workers.

• Journal of Forest and Environmental Science
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• v.38 no.4
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• pp.219-228
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• 2022

This study examined the relationship between the number of forest fires and days with no rainfall based on the national forest fire statistics data of the Korea Forest Service and meteorological data from the Open MET Data Portal of the Korea Meteorological Administration (KMA; data.kma.go.kr) for the last 30 years (1991-2021). As for the trend in precipitation amount and non-rainfall days, the rainfall and the days with rainfall decreased in 2010 compared to those in 1990s. In terms of the number of forest fires that occurred in February-May accounted for 75% of the total number of forest fires, followed by 29% in April and 25% in March. In 2000s, the total number of forest fires was 5,226, indicating the highest forest fire activity. To analyze the relationship between regional distribution of non-rainfall periods (days) and number of forest fires, the non-rainfall period was categorized into five groups (0 days, 1-10 days, 11-20 days, 21-30 days, and 31 days or longer). During the spring fire danger season, the number of forest fires was the largest when the non-rainfall period was 11-20 days; during the autumn fire precaution period, the number of forest fires was the largest when the non-rainfall period was 1-10 days, 11-20 days, and 21-30 days, showing differences in the duration of forest fire occurrence by region. The 30-year trend indicated that large forest fires occurred only between February and May, and in terms of the relationship with the non-rainfall period groups, large fires occurred when the non-rainfall period was 1-10 days. This signifies that in spring season, the dry period continued throughout the country, indicating that even a short duration of consecutive non-rainfall days poses a high risk of large forest fires.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.193-204
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• 2022

The 2018 Seoul Zero Pay is a policy actively promoted by the government as an economic stimulus package for small business owners and the self-employed who are experiencing economic depression due to COVID-19. However, the controversy over the effectiveness of Zero Pay continues even after two years have passed since the implementation of the policy. Zero Pay is a joint QR code mobile payment service introduced by the government, Seoul city, financial companies, and private simple payment providers to reduce the burden of card merchant fees for small business owners and self-employed people who are experiencing economic difficulties due to the economic downturn., it was attempted in the direction of economic revitalization for the return of alleyways[1]. Therefore, this study intends to draw implications for improvement measures so that the ongoing zero-pay can be further activated and the economy can be settled normally. The analysis results of this study are as follows. First, it shows the effect of increasing the income of small business owners by inducing consumption in alleyways through the economic revitalization policy of Zero Pay. Second, the issuance and distribution of Zero Pay helps to revitalize the local economy and contribute to the establishment of a virtuous cycle system. Third, stable operation is being realized by the introduction of blockchain technology to the Zero Pay platform. In terms of academic significance, the direction of Zero Pay's policies and systems was able to identify changes in the use of Zero Pay through big data analysis. The implementation of the zero-pay policy is in its infancy, and there are limitations in factors for examining the consumer image perception of zero-pay as there are insufficient prior studies. Therefore, continuous follow-up research on Zero Pay should be conducted.

• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.565-574
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• 2022

The infrastructures such as offshore, bridges, power plant, oil and gas piping and aircraft operate in a harsh environment during their service life. Structural integrity of engineering components used in these industries is paramount for the reliability and economics of operation. Two regression models based on the concept of Gaussian process regression (GPR) and Minimax probability machine regression (MPMR) were developed to predict stress intensity factor range (𝚫K). Both GPR and MPMR are in the frame work of probability distribution. Models were developed by using the fatigue crack growth data in MATLAB by appropriately modifying the tools. Fatigue crack growth experiments were carried out on Eccentrically-loaded Single Edge notch Tension (ESE(T)) specimens made of API 5L X65 Grade steel in inert and corrosive environments (2.0% and 3.5% NaCl). The experiments were carried out under constant amplitude cyclic loading with a stress ratio of 0.1 and 5.0 Hz frequency (inert environment), 0.5 Hz frequency (corrosive environment). Crack growth rate (da/dN) and stress intensity factor range (𝚫K) values were evaluated at incremental values of loading cycle and crack length. About 70 to 75% of the data has been used for training and the remaining for validation of the models. It is observed that the predicted SIF range is in good agreement with the corresponding experimental observations. Further, the performance of the models was assessed with several statistical parameters, namely, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Coefficient of Efficiency (E), Root Mean Square Error to Observation's Standard Deviation Ratio (RSR), Normalized Mean Bias Error (NMBE), Performance Index (ρ) and Variance Account Factor (VAF).

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.81-94
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• 2022

Real estate and artworks were considered challenging investment targets for individual investors because of their relatively high average transaction price despite their long investment history. Recently, the so-called fractional investment, generally known as investing in a share of the ownership right for real-life assets, etc., and most investors perceive that they actually own a piece (fraction) of the ownership right through their investments, is gaining popularity. Founded in 2016, Musicow started the first service that allows users to invest in copyright fees related to music distribution. Using the LSTM algorithm, one of the deep learning algorithms, this research predict the price of right to participate in copyright fees traded in Musicow. In addition to variables related to claims such as transfer price, transaction volume of claims, and copyright fees, comprehensive indicators indicating the market conditions for music copyright fees participation, exchange rates reflecting economic conditions, KTB interest rates, and Korea Composite Stock Index were also used as variables. As a result, it was confirmed that the LSTM algorithm accurately predicts the transaction price even in the case of fractional investment which has a relatively low transaction volume.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.25-43
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• 2022

Unlike the past, efforts must be made to interpret physical distribution from a network perspective as the service area expands spatially. In addition, logistics networks are undergoing rapid changes due to various changes in the environment. Therefore, the purpose of this study is to analyze the changes in the structure of maritime cargo and the centrality of ports using social network analysis. Using the trade data of domestic maritime at five-year intervals, we investigated changes in the network structure and identified the main factors that affect the centrality of domestic ports. Ports with the highest centrality, which is seen as a port that plays the role of an intermediary, emerged in the order of Busan and Ulsan. This study predicts patterns of domestic cargo trade over the next 20 years based on changes in port centrality and understanding of maritime cargo network, and can be used as reference materials for risk preparation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.427-429
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• 2022

Recently, metaverse technology is being used in various service industries such as games, entertainment, manufacturing, distribution, advertising, and education. Studies on the correlation between the continuous use of devices used in metaverse content are still insufficient. In order to be more immersed in the metaverse, it is necessary to develop a natural movement and an easy-to-use input device. Based on flow, this study was conducted on the topic of continuous use of metaverse contents and devices. The constituent factors of Flow, an independent variable, were set as sense of reality, immersion, and interaction. We intend to use the data of 500 male and female metaverse users for research through a survey institution. Among the flow factors that increase the continuous use of metaverse contents and devices, the factors that have the greatest influence were studied. Through the results of this study, it is intended to help establish the direction of the next-generation metaverse content and device industry.