• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.74-80
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• 2023

This study examines the characteristics of architectural review opinions as unstructured data, focusing on the most challenging risk for developers of small and medium-sized apartment projects in response to the increasing number of single-person households in Korea. Using multidimensional analysis methods, the study analyzes the review opinions of 25 projects in B City. Correspondence analysis and MDS (Multidimensional Scale) analysis show that, consistent with prior research, the keywords related to 'structure' and 'planning' dominate architectural review opinions in B City. While the MDS model's stress is very poor at 34.4%, correspondence analysis reveals that this is due to the characteristics of unstructured data in architectural reviews. In addition, the non-structured data analyzed in this study, such as architectural review opinions, exhibited a probability distribution with low kurtosis and high skewness, as they involved various combinations and occurrences of data depending on the discretion of the review committee members and the specific formats of different local governments. This often led to the emergence of keywords that differed significantly from commonly mentioned terms. Although the study has some limitations, it provides a foundation for future detailed analysis by identifying the characteristics of architectural review opinions as unstructured data.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.97-105
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• 2023

Recently, with the development of artificial intelligence technology, many technologies for user convenience are being developed. Among them, interest in autonomous vehicles is increasing day by day. Currently, many automobile companies are aiming to commercialize autonomous vehicles. In order to lay the foundation for the government's new and reasonable policy establishment to support commercialization, we tried to analyze changes and perceptions of public opinion through news article data. Therefore, in this paper, 35,891 news article data mentioning terms similar to 'autonomous vehicles' over the past three years were collected and network analyzed. As a result of the analysis, major keywords such as 'autonomous driving', 'AI', 'future', 'Hyundai Motor', 'autonomous driving vehicle', 'automobile', 'industrial', and 'electric vehicle' were derived. In addition, the autonomous vehicle industry is developing into a faster and more diverse platform and service industry by converging with various industries such as semiconductor companies and big tech companies as well as automobile companies and is paying attention to the convergence of industries. To continuously confirm changes and perceptions in public opinion, it is necessary to analyze perceptions through continuous analysis of SNS data or technology trends.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.326-334
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• 2023

The purpose of this study is to use long-term water quality monitoring data from tributaries of the Nakdong River system to identify problematic substances in tributaries by examining the rate of exceedance and increase in water quality targets. In the Nakdong River system, monitoring is conducted once a month for 38 tributaries that require intensive management, and this data was used to analyze trends in exceeding and increasing target water quality at each point. The analysis items are eight items that can be evaluated based on river water quality standards: DO, BOD, COD, TOC, SS, total phosphorus, fecal coliform, and total coliform. As a result of the analysis, the target water quality exceedance rate was more than 50%, and the items with an increasing trend were TOC, fecal coliform and total E. coli counts, and the items with an exceedance rate of less than 50% but an increasing trend were SS. TOC is believed to be caused by an increase in non-degradable substances, and the continued increase in Total Coliform will require management of Total ColiformTotal Coliform in effluent water from sewage treatment facilities in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.5
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• pp.44-56
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• 2023

This research explores the enhancement of park operation and management by analyzing the changing demands of park users. While traditional methods depended on surveys, there has been a recent shift towards utilizing social media data to understand park usage trends. Notably, most research has focused on text data from social media, overlooking the valuable insights from image data. Addressing this gap, our study introduces a novel method of assessing park usage using social media image data and then applies it to actual city park evaluations. A unique image analysis tool, built on Visual Question Answering (VQA) deep learning technology, was developed. This tool revealed specific city park details such as user demographics, behaviors, and locations. Our findings highlight three main points: (1) The VQA-based image analysis tool's validity was proven by matching its results with traditional text analysis outcomes. (2) VQA deep learning technology offers insights like gender, age, and usage time, which aren't accessible from text analysis alone. (3) Using VQA, we derived operational and management strategies for city parks. In conclusion, our VQA-based method offers significant methodological advancements for future park usage studies.

• Informatization Policy
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• v.30 no.4
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• pp.40-61
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• 2023

The adoption of smart factories and smart manufacturing as strategies to enhance competitiveness and stimulate growth in the manufacturing sector is vital for a country's future competitiveness and industrial transformation. The government has consistently pursued smart manufacturing innovation policies starting with the Manufacturing Innovation 3.0 strategy in the Ministry of Industry. This study aims to identify policy areas for smart factories and smart manufacturing based on technical standards. Analyzing policy areas at the current stage where the establishment and support of domestic standards aligning with international technical standards are required is crucial. By prioritizing smart manufacturing process areas within the industry, policymakers can make well-informed decisions to advance smart manufacturing without blindly following international standardization in already well-established areas. To achieve this, the study utilizes a hierarchical analysis method including expert interviews and importance-performance analysis for the five major process areas. The findings underscore the importance of proactive participation in standardization for emerging technologies, such as data and security, instead of solely focusing on areas with extensive international standardization. Additionally, policymakers need to consider carbon emissions, energy costs, and global environmental challenges to address international trends in export and digital trade effectively.

• Journal of Environmental Health Sciences
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• v.49 no.6
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• pp.362-371
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• 2023

Background: PM_2.5 pollution has been a persistent problem in South Korea, with concentrations consistently exceeding World Health Organization (WHO) guidelines. The aging of the population in the country further exacerbates the health impacts of PM_2.5 since older adults are more susceptible to the adverse effects of air pollution. Objectives: This study aims to evaluate how the health impact (premature death) due to long-term exposure to PM_2.5 in South Korea could change in the future according to the trend of change in the country's population structure. Methods: The study employs a relative risk function, which accounts for age-specific relative risks, to assess the changes in premature deaths by age and region at the average annual PM_2.5 concentration for 2022 and at PM_2.5 concentration improvement levels. Premature deaths were estimated using the Global Exposure Mortality Model (GEMM). Results: The findings indicate that the increase in premature deaths resulting from the projected population structure changes up to 2050 would significantly outweigh the health benefits (reduction in premature deaths) compared to 2012. This is primarily attributed to the rising number of premature deaths among the elderly due to population aging. Furthermore, the study suggests that the effectiveness of the current domestic PM_2.5 standard would be halved by 2050 due to the increasing impact of population aging on PM_2.5-related mortality. Conclusions: The study highlights the importance of considering trends in population structure when evaluating the health benefits of air pollution reduction measures. By comparing and evaluating the health benefits in reflection of changes in population structure to the predicted PM_2.5 concentration improvements at the provincial level, a more comprehensive assessment of regional air quality management strategies can be achieved.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.709-719
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• 2023

In general, most of the electrical equipment responsible for control within power plants is housed in self-standing cabinets. These cabinets are typically fixed to a slab using post-installed anchors. Although the fixation method of using post-installed anchors provides stability, there is a risk of conductor failure due to external forces, including moments. However, the performance assessment of current anchors is only evaluated through uniaxial material tests. Therefore, the primary purpose of this study is to compare the static performance of post-installed anchors, considering on-site installation conditions, with their performance in material tests and to analyze the behavioral characteristics of the anchors. While conducting experiments using actual cabinets would be ideal, practical and spatial constraints make this approach difficult. As an alternative, experiments were conducted using a test specimen consisting of a steel column and a support. As a result, the pull-out performance of anchors reflecting on-site installation conditions was measured to be about 10% higher than that observed in material tests. The trends in load reduction and the point of maximum performance for the anchors also differed. To verify the reliability of the experimental study, a 3D FEM analysis was performed, which will provide predictive information on the loads transferred to the post-installed anchors for structural performance evaluations of electrical cabinets using shaking table test in the future.

• Atmosphere
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• v.33 no.5
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• pp.477-492
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• 2023

Based on the new climate normals (1991~2020), annual mean, maximum and minimum temperature is 12.5℃, 18.2℃, and 7.7℃, respectively while annual precipitation is 1,331.7 mm, the annual mean wind speed is 2.0 m s^-1, and the relative humidity is 67.8% in the Republic of Korea. Compared to 1981~2010 normal, annual mean temperature increased by 0.2℃, maximum and minimum temperatures increased by 0.3℃, while the amount of precipitation (0.7%) and relative humidity (1.1%) decreased. There was no distinct change in annual mean wind speed. The spatial range of the annual mean temperature in the new normals is large from 7.1 to 16.9℃. Annual precipitation showed a high regional variability, ranging from 787.3 to 2,030.0 mm. The annual mean relative humidity decreased at most weather stations due to the rise in temperature, and the annual mean wind speed did not show any distinct difference between the new and old normals. With the addition of a warmer decade (2011~2020), temperatures all increased consistently and in particular, the increase in the maximum temperature, which had not significantly changed in previous decades, was evident. The increasing trend of annual and summer precipitation by the 2010s has disappeared in the new normals. Among extreme climate indices, MxT30 (Daily maximum temperature ≥ 33℃ days), MnT25 (Daily minimum temperature ≥ 25℃ days), and PH30 (1 hour maximum precipitation ≥ 30 mm days) increased while MnT-10 (Daily minimum temperature < -10℃ days) and W13.9 (Daily maximum wind speed ≥ 13.9 m/s days) decreased at a statistically significant level. It is thought that a detailed study on the different trends of climate elements and extreme climate indices by region should be conducted in the future.

• Korean Journal of Ecology and Environment
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• v.56 no.3
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• pp.268-279
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• 2023

Nowadays, artificial intelligence model approaches such as machine and deep learning have been widely used to predict variations of water quality in various freshwater bodies. In particular, many researchers have tried to predict the occurrence of cyanobacterial blooms in inland water, which pose a threat to human health and aquatic ecosystems. Therefore, the objective of this study were to: 1) review studies on the application of machine learning models for predicting the occurrence of cyanobacterial blooms and its metabolites and 2) prospect for future study on the prediction of cyanobacteria by machine learning models including deep learning. In this study, a systematic literature search and review were conducted using SCOPUS, which is Elsevier's abstract and citation database. The key results showed that deep learning models were usually used to predict cyanobacterial cells, while machine learning models focused on predicting cyanobacterial metabolites such as concentrations of microcystin, geosmin, and 2-methylisoborneol (2-MIB) in reservoirs. There was a distinct difference in the use of input variables to predict cyanobacterial cells and metabolites. The application of deep learning models through the construction of big data may be encouraged to build accurate models to predict cyanobacterial metabolites.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.169-175
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• 2023

This paper analyzes museum-related big data using museums and gamification using social media big data, identifies and compares the perceptions of visitors mentioned in social media, and presents ways to use gamification. Based on the collected data, this paper aims to provide data by comparing and analyzing the perception of visitors to the museum and visitors to the museum using gamification. This paper investigates the perception of visitors through social media analysis using TEXTOM, a social media analysis tool, to identify differences in perception. As a result of the analysis, it was found that compared to museums that were previously viewed in the form of exhibitions, they felt fun and interest in visiting museums using geikipication. In addition, based on the analysis results of keywords and related keywords, the perception, motivation, and type of viewing of the museum of the National Museum of Korea and the Independence Hall of Korea were confirmed. In addition, it can be seen that the sense of achievement of visitors who visited the museum using gamification is higher than that of the existing museum. It is believed that by developing and activating game-related content in future museum visits, many visitors will be able to increase their interest in the museum and feel fun and interested. The results of the study are believed to be meaningful as basic data to grasp the overall perception of visitors to the museum, and based on this, it is expected that visitors will be able to see and experience the museum in various ways.