• Journal of the Korean Society of Industry Convergence
• /
• v.25 no.4_2
• /
• pp.549-563
• /
• 2022

Continuous global warming is causing ecosystem destruction and direct damage to human life. The main cause of global warming is greenhouse gases, which account for more than 90 % of carbon dioxide. The leaders of each country signed the Paris Agreement at the United Nations Convention on Climate Change (UNFCCC) to reduce greenhouse gas emissions. Currently, the total amount of CO₂ emitted from South Korea is 664.7 million tons as of 2018, ranking eighth in the world. 37 % of South Korea's total CO₂ emissions come from the construction & building field, especially the cement production, which is a construction material. Carbon reduction technologies can be largely divided into four types: carbon reduction (CC), carbon reduction and storage technology (CCS), carbon reduction and utilization technology (CCU), and carbon reduction, storage and utilization technology (CCUS). Overseas, CCUS technology is mainly applied to reduce and store CO₂ emitted from construction and construction field. A technology for permanently storing CO₂ through mineralization by capturing CO₂ and utilizing CO₂ into a cement production process was developed, and this technology is applied to the entire cement industry. However, the development of CCUS technology applicable to the cement industry is still insignificant in South Korea. In this study, carbon dioxide reduction technology and methods for reducing carbon dioxide emitted during the cement manufacturing process, which is the main component of concrete mainly used in civil engineering construction, were investigated. Overseas, it has reached the commercialization stage beyond the demonstration stage as a way to reduce carbon dioxide by vomiting carbonation reactions. Accordingly, if carbon dioxide reduction plan technology generated during cement manufacturing is developed based on domestic technology differentiated from foreign technology, it is expected to contribute one more step to the carbon neutrality policy.

• Knowledge Management Research
• /
• v.23 no.2
• /
• pp.37-60
• /
• 2022

The growth of virtual reality games and the popularization of blockchain technology are bringing significant changes to the formation of the metaverse industry ecosystem. Especially, after Meta acquired Oculus, a VR device and application company, the growth of VR-based metaverse services is accelerating. In this study, the concept that supports leisure activities in the metaverse environment is explored realting to game-like features in VR apps, which differentiates traditional mobile apps based on a smart phone device. Using exploratory text mining methods and network analysis approches, 241 apps registed in the Oculus Quest 2 App Store were analyzed. Analysis results from a quasi-network show that a leisure concept is closely related to various genre features including a game and tourism. Additionally, the anlaysis results of G & F model indicate that the leisure concept is distictive in the view of gateway brokerage role. Those results were also confirmed in LDA topic modeling analysis.

• Journal of Engineering Education Research
• /
• v.26 no.4
• /
• pp.22-35
• /
• 2023

As information and communication technology has developed remarkably, it has become possible to analyze various types of large-volume data generated at a speed close to real time, and based on this, reliable value creation has become possible. Such big data analysis is becoming an important means of supporting decision-making based on scientific figures. The purpose of this study is to develop a big data analysis tool that can analyze large amounts of data generated through engineering education. The tasks of this study are as follows. First, a database is designed to store the information of entries in the National Creative Capstone Design Contest. Second, the pre-processing process is checked for analysis with big data analysis tools. Finally, analyze the data using the developed big data analysis tool. In this study, 1,784 works submitted to the National Creative Comprehensive Design Contest from 2014 to 2019 were analyzed. As a result of selecting the top 10 words through topic analysis, 'robot' ranked first from 2014 to 2019, and energy, drones, ultrasound, solar energy, and IoT appeared with high frequency. This result seems to reflect the current core topics and technology trends of the 4th Industrial Revolution. In addition, it seems that due to the nature of the Capstone Design Contest, students majoring in electrical/electronic, computer/information and communication engineering, mechanical engineering, and chemical/new materials engineering who can submit complete products for problem solving were selected. The significance of this study is that the results of this study can be used in the field of engineering education as basic data for the development of educational contents and teaching methods that reflect industry and technology trends. Furthermore, it is expected that the results of big data analysis related to engineering education can be used as a means of preparing preemptive countermeasures in establishing education policies that reflect social changes.

• Biomedical Science Letters
• /
• v.28 no.4
• /
• pp.317-321
• /
• 2022

Due to COVID-19 pandemic, wearing face masks is obligatory to prevent respiratory virus transmissions in the community. However, there are few studies of the desirable number of wearing a face mask, and how to store them for reuse. Therefore, in this study, a survey was conducted among 208 healthy adults, and 27 kf-94 masks worn for 1, 2, and 3 days were collected. To estimate the risk of bacterial contamination, we analyzed the extent of bacterial contamination of the BHI medium and 16S rRNA gene sequencing. With an increase in the number of days of using the mask, the degree of bacterial contamination of the used mask gradually increased. As a result of 16S rRNA PCR performed for strain identification, Staphylococcus, known as a pathogenic bacterium, was identified the most. In conclusion, we found that wearing a cotton KF mask provides an optimal environment for microbes, which are related to the skin and respiratory system, to thrive. Therefore, it is also important to reduce the risk of bacterial infection of the face mask with appropriate sterilization methods.

• Safety and Health at Work
• /
• v.13 no.4
• /
• pp.401-407
• /
• 2022

Background: The present study aimed to digitally evaluate the risk of overwork-related adverse effects (OrAEs) among employees from various occupational categories in Taiwan. Methods: Anonymous data of employees from seven companies/factories providing occupational health services were analyzed. The studied population comprised 5505 employees, and the data analyzed included employment duration, working hours, shift work schedules, and health checkup results. The risk for OrAEs was assessed by an index, Karo index (0-4, the larger the value, the higher the risk for OrAEs) obtained using a risk matrix made up of cardiocerebral and occupational risk factors. Karo index values of 3 and 4 were categorized as at high risk for OrAEs (h-OrAEs). Results: The 5505 employees had an average employment duration of 8.5 years and a mean age of 39.4 years. The prevalence rates for h-OrAEs of the seven companies/factories ranged from 3.9% to 34.2%. There were significant differences in prevalence rates for h-OrAEs between employees of retail stores and high-tech manufacturing factories. Multivariate analysis results indicated that workers of high-tech manufacturing factories had significantly higher risk for h-OrAEs compared with retail store workers. Conclusion: In terms of satisfying health risk management and legal requirements in Taiwan, the newly issued Karo index, which covers a wide range of occupational risk factors, can serve as an assessment and a warning tool for managing the risk of OrAEs in workplaces. To reduce risks for h-OrAEs, active and prudent control of cerebrocardiovascular risks and working hours is recommended.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.11
• /
• pp.1729-1740
• /
• 2022

Recently, a lot of data has been generated according to the diversity and utilization of information, and the importance of big data analysis to collect, store, process and predict data has increased, and the ability to collect only necessary information is required. More than half of the web space consists of text, and a lot of data is generated through the organic interaction of users. There is a crawling technique as a representative method for collecting text data, but many crawlers are being developed that do not consider web servers or administrators because they focus on methods that can obtain data. In this paper, we design and implement an improved dynamic web crawler that can efficiently fetch data by examining problems that may occur during the crawling process and precautions to be considered. The crawler, which improved the problems of the existing crawler, was designed as a multi-process, and the work time was reduced by 4 times on average.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.7
• /
• pp.11-18
• /
• 2023

In this paper, we evaluate deep learning time series forecasting models. Recent studies show that those models perform better than the traditional prediction model such as ARIMA. Among them, recurrent neural networks to store previous information in the hidden layer are one of the prediction models. In order to solve the gradient vanishing problem in the network, LSTM is used with small memory inside the recurrent neural network along with BI-LSTM in which the hidden layer is added in the reverse direction of the data flow. In this paper, we compared the performance of Informer by comparing with other models (LSTM, BI-LSTM, and Transformer) for real Nitrogen dioxide (NO2) data. In order to evaluate the accuracy of each method, mean square root error and mean absolute error between the real value and the predicted value were obtained. Consequently, Informer has improved prediction accuracy compared with other methods.

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.673-673
• /
• 2015

Earthwork is an operation that provides space for structures, and it takes up a large portion of the construction costs in a construction project. In large-scale earthwork, numerous types of construction equipment are used in the operation. The types of equipment should be selected based on the field conditions and the construction methods. These construction vehicles are constantly changing positions during the earthwork operation. Therefore, the equipment operators require effective communication to ensure the efficiency of the earthwork operation. All equipment operators should exchange information with the other equipment operators. Information should be exchanged continuously to support decision making and increase productivity during the earthwork operation at the construction site. This paper investigates the attributes required for an information interface between construction vehicles during an earthwork operation. This paper 1) discusses the importance of an information interface for construction vehicles in order to increase productivity during an earthwork operation, 2) analyses the types of attributes that need to be communicated between construction vehicles, and 3) provides a database that has been built for attribute control. The database built for the information interface between construction vehicles will enhance communication between vehicle operators. Table I shows the typical attributes that should be shared between the excavator operator and the dump truck operator. This information needs to be shared among the operators, as it helps them to plan the earthwork operation in a more efficient manner. A database has been developed to store this information in an entity relation diagram. A user-interface display environment is also developed to provide this information to the operators in the construction vehicles. The proposed interface can help exchange information effectively and facilitate a common understanding during the earthwork operation. For example, the vehicle operators will be aware of the planned volume, excavated volume, transportation time, and transportation numbers. As a part of this study, mobile devices, such as mobile phones and google glasses, will be used as hands-on communication tools.

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.54-55
• /
• 2015

Increase of impervious areas due to expansion of housing area, commercial and business building of urban is resulting in property change of stormwater runoff. Also, rapid urbanization and heavy rain due to climate change lead to urban flood and debris flow damage. In 2010 and 2011, Seoul had experienced shocking flooding damages by heavy rain. All these have led to increased interest in applying LID and decentralized rainwater management as a means of urban hydrologic cycle restoration and Natural Disaster Prevention such as flooding and so on. Urban development is a cause of expansion of impervious area. It reduces infiltration of rain water and may increase runoff volume from storms. Low Impact Development (LID) methods is to mimic the predevelopment site hydrology by using site design techniques that store, infiltrate, evaporate, detain runoff, and reduction flooding. Use of these techniques helps to reduce off-site runoff and ensure adequate groundwater recharge. The contents of this paper include a hydrologic analysis on a site and an evaluation of flooding reduction effect of LID practice facilities planned on the site. The region of this Case study is LID Rainwater Management Demonstration District in A-new town and P-new town, Korea. LID Practice facilities were designed on the area of rainwater management demonstration district in new town. We performed analysis of reduction effect about flood discharge. SWMM5 has been developed as a model to analyze the hydrologic impacts of LID facilities. For this study, we used weather data for around 38 years from January 1973 to August 2014 collected from the new town City Observatory near the district. Using the weather data, we performed continuous simulation of urban runoff in order to analyze impacts on the Stream from the development of the district and the installation of LID facilities. This is a new approach to stormwater management system which is different from existing end-of-pipe type management system. We suggest that LID should be discussed as a efficient method of urban disasters and climate change control in future land use, sewer and stormwater management planning.

• Journal of the Korean Applied Science and Technology
• /
• v.40 no.4
• /
• pp.724-732
• /
• 2023

In this study, we tried to analyze the characteristics of color cosmetics information search and the major information of interest in the color cosmetics market after COVID-19 shown in the text mining analysis results by collecting data on online interest information of consumers in the color cosmetics market after COVID-19. In the empirical analysis, text mining was performed on all documents such as news, blogs, cafes, and web pages, including the word "color cosmetics". As a result of the analysis, online information searches for color cosmetics after COVID-19 were mainly focused on purchase information, information on skin and mask-related makeup methods, and major topics such as interest brands and event information. As a result, post-COVID-19 color cosmetics buyers will become more sensitive to purchase information such as product value, safety, price benefits, and store information through active online information search, so a response strategy is required.