• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.87-93
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• 2021

Modern society shows rapid growth that is different from that of the development of existing technologies. The development of these technologies has led to the tendency of buildings to become dense, large and advancing. Regarding fire hazards, the possibility of large-scale fires causing fatal damage, due to the rapid spread of fire, increases. Therefore, for this reason, fire defense, i.e. detection and fire extinguishing facilities, in buildings are essential and well applied. But there are always limitations to that. Based on this reason, we would like to suggest the introduction of a new concept of a fire safety system. The method presented here is not only to use a single system for fire detection and fire extinguishing systems but to jointly use it in the environment and energy management fields within the building. However, an important step is required before introducing a system of these technologies. The fire extinguishing method proposed by this system is a method of extinguishing by blocking oxygen flowing into the space where the fire occurred. However, a sufficient basis is needed for this system to be applied in practice. Therefore, in this study, we intend to conduct a preliminary experiment to introduce the new concept of fire detection and extinguishing. The experiment used ethanol with a relatively simple combustion reaction and a high possibility of complete combustion. As a result, it was confirmed how the internal values changed during a fire using ethanol. Resultingly, we obtained the internal oxygen concentration and internal environmental changes according to the initial flame size. Lastly, the data accumulated in this study can be used as data for application in an automatic fire extinguishing system.

• The Korean Journal of Mycology
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• v.49 no.2
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• pp.211-242
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• 2021

Indigenous yeasts in Korea have been actively studied since 1910 in light of various fields, including environment, food fermentation, brewing, and medicine. However, a complete list of indigenous yeast species has not been addressed or reported. In this study, a comprehensive analysis of the literature including yeast isolation from Korean materials and the strains preserved at culture collections was performed. The results of this study indicate the following: i) there are 128 genera and 681 species (including 26 variants) of yeast reported in Korea, ii) the reported species were trimmed into 142 genera and 500 species (including 9 variants), iii) among which only 166 species were registered in the National Species List of Korea (2020). Therefore, follow-up studies are required to register more indigenous yeast species in the National Species List of Korea.

• Korean small business review
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• v.43 no.1
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• pp.131-145
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• 2021

This study aims to diagnose research trends and to deduct implications from meta analysis of entrepreneurship studies in the Asia Pacific Journal of Small Business (APJSB), one of the most well-known academic journals in management and entrepreneurship field in Korea. Frequency and crossover analysis are executed in multi-dimensions by time period, topic, author, research level, data, and methodology by complete enumeration of every published paper for 40 years in APJSB which included core terms of entrepreneurship in its title, abstract, or keywords. From objective and quantitative schematization of research trends and characteristics of entrepreneurship studies, novel improvement plans which are highly applicable in research fields are suggested such as diversification of studies from ecosystem perspective, identification of authors, and standardized system of extended abstract of research papers. Implications and suggestions derived from the results propose future research directions and tasks when entrepreneurship studies have been rapidly increased. Furthermore, the innovation plans of management system of journals and papers are expected to contribute promotion of entire studies by significantly reducing trial and error, and inefficiency in research process.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.1
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• pp.89-98
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• 2022

As deep learning technology was applied to various fields, research on adversarial attack techniques, a security problem of deep learning models, was actively studied. adversarial attacks have been mainly studied in the field of images. Recently, they have even developed a complete decision-based attack technique that can attack with just the classification results of the model. However, in the case of the audio field, research is relatively slow. In this paper, we applied several decision-based attack techniques to the audio field and improved state-of-the-art attack techniques. State-of-the-art decision-attack techniques have the disadvantage of requiring many queries for gradient approximation. In this paper, we improve query efficiency by proposing a method of reducing the vector search space required for gradient approximation. Experimental results showed that the attack success rate was increased by 50%, and the difference between original audio and adversarial examples was reduced by 75%, proving that our method could generate adversarial examples with smaller noise.

• Wind and Structures
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• v.34 no.5
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• pp.395-405
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• 2022

Tornado-induced damages to high-rise buildings and low-rise buildings are quite different in nature. Tornado losses to high-rise buildings are generally associated with building envelope failures while tornado-induced damages to low-rise buildings are usually associated with structural or large component failures such as complete collapses, or roofs being torn off. While studies of tornado-induced structural damages tend to focus mainly on low-rise residential buildings, transmission towers, or nuclear power plants, the current rapid expansion of city centers and development of large-scale building complexes increases the risk of tornadoes impacting tall buildings. It is, therefore, important to determine how tornado-induced load affects tall buildings compared with those based on synoptic boundary layer winds. The present study applies an experimentally simulated tornado wind field to the Commonwealth Advisory Aeronautical Research Council (CAARC) building and estimates and compares its pressure coefficient effects against the Atmospheric Boundary Layer (ABL) flow field. Simulations are performed at the Wind Engineering, Energy and Environment (WindEEE) Dome which is capable of generating both ABL and tornadic winds. A model of the CAARC building at a scale of 1:200 for both ABL and tornado flows was built and equipped with pressure taps. Mean and peak surface pressures for TLV flow are reported and compared with the ABL induced wind for different time-averaging. By following a compatible definition of the pressure coefficients for TLV and ABL fields, the resulting TLV pressure field presents a similar trend to the ABL case. Also, the results show that, for the high-rise building model, the mean and 3-sec peak pressures are larger for the ABL case compared to the TLV case. These results provide a way forward for the code implementation of tornado-induced pressures on high-rise buildings.

• Journal of Practical Engineering Education
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• v.14 no.1
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• pp.75-83
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• 2022

Most of the courses that teach the Python programming language are liberal arts courses that all students in general universities must complete. Through this, non-major students who have learned the basic programming process based on computational thinking are strengthening their convergence capabilities to apply SW in various major fields. In the previous research results, various evaluation methods for understanding the concept of computational thinking and writing code were suggested. However, there are no examples of evaluation problems, so it is difficult to apply them in actual course operation. Accordingly, in this paper, a Python basic programming curriculum that can be applied as a liberal arts subject for non-majors is proposed according to the ADDIE model. In addition, the case of evaluation problems for each Python element according to the proposed detailed curriculum was divided into 1st and 2nd phases and suggested. Finally, the validity of the proposed evaluation problem was analyzed based on the evaluation scores of non-major students calculated in the course to which this evaluation problem case was applied. It was confirmed that the proposed evaluation problem case was applied as a real-time online non-face-to-face evaluation method to effectively evaluate the programming competency of non-major students.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2831-2845
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• 2022

Compared to the significant approach of project-based learning research, a data-driven design project-based learning has not reached a meaningful consensus regarding the most valid and reliable method for assessing design creativity. This article proposes an advanced information data-interactive learning system for creative design using a service design process that combines a design thinking. We propose a service framework to improve the convergence design process between students and advanced information data analysis, allowing students to participate actively in the data visualization and research using patent data. Solving a design problem by discovery and interpretation process, the Advanced information-interactive learning framework allows the students to verify the creative idea values or to ideate new factors and the associated various feasible solutions. The student can perform the patent data according to a business intelligence platform. Most of the new ideas for solving design projects are evaluated through complete patent data analysis and visualization in the beginning of the service design process. In this article, we propose to adapt advanced information data to educate the service design process, allowing the students to evaluate their own idea and define the problems iteratively until satisfaction. Quantitative evaluation results have shown that the advanced information data-driven learning system approach can improve the design project - based learning results in terms of design creativity. Our findings can contribute to data-driven project-based learning for advanced information data that play a crucial role in convergence design in related standards and other smart educational fields that are linked.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.3
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• pp.413-422
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• 2016

A construction manager tries to complete a construction project within its duration and budget using available resources. Schedule networks such as Bar-chart and CPM(critical path method) are used to finish the project within the duration. A survey shows that small contractors prefer Microsoft Excel to commercial time management softwares to manage construction time in their fields, because the Excel is useful to control cost with schedule and few time management experts works in the small contractors. A college produces talented graduates who are able to manage time of a construction project. But the quality and quantity of college eduction for time management is insufficient. Another survey shows that majors in Architectural engineering of local national universities have the curriculum for time management, and teach mainly the theory of network scheduling and how to make the network schedule. The several majors have classes for the theory and exercise of commercial time management softwares in several majors. It is necessary to educate time management experts able to use Bar-chart and commercial time management softwares for the small contractors.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.347-354
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• 2023

In this study, virtual reality software was developed to support the generation of an analysis model of a Hanok and to increase the use of the completed analysis model. The structural analysis model of the Hanok was generated using midas Gen, a general-purpose structural analysis software. After converting it into a text-based input file, the developed software stores the data necessary for the examination of the analysis model. Then, in the developed virtual reality software, the three-dimensional analysis model of the Hanok can be visualized in various ways and the related data can be shown by selecting a specific member. Through this process, errors in the analysis model can be identified and corrected to build a complete analysis model. The developed software was applied to three Hanok cases to verify its applicability and effectiveness. The software is expected to be used in other fields besides the structural field.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.311-326
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• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.