• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.293-296
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• 2016

In case of an emergency on a busy road of a city, drivers should make way for special vehicles such as police cars, fire engines, or ambulance as soon as possible. If road infrastructures recognize the movements of special vehicles, and transfer alert message to traffic signal controllers and normal cars through wireless network such as WAVE or TPEG, normal cars can prepare to make way in advance. As a result, it help special vehicles move faster. In this paper, we install a roof mark on the roof of a special vehicle, detect the mark through a mark recognition algorithm which includes perspective transformation, and get the inner information by decoding the digital pattern on it. The experiment results show that mark can be recognized 100% and 93.3% of inner digital data of the mark can be recognized, when the size of a mark is larger than $88cm{\times}88cm$ and the mark moves at a speed of 50km/s.

• The Korean Journal of Emergency Medical Services
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• v.25 no.1
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• pp.125-134
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• 2021

Purpose: The purposes of this study were to determine the changes in the pattern of patients who were transferred to the emergency room through inter-hospital private institutions and to determine how long transport takes following the COVID-19 outbreak. Methods: This retrospective observational study analyzed the emergency medical services reports of private institutions following the COVID-19 outbreak in South Korea. The study was conducted in Busan between January 19, 2019 and January 18, 2020, and between January 19, 2020 and January 18, 2021. Results: Upon comparing the patient transport times during the "Pre-COVID-19 period" and "COVID-19 period," a significant delay was noticed in the preparation for transfer of patients during the "COVID-19 period" (p<.05). There were significantly more patients with respiratory infections and patients who complained of general symptoms during the "COVID-19 period." Moreover, there was a higher frequency of patients who were transferred to a 'Level I' emergency room during the "COVID-19 period" compared to during the "Pre-COVID-19 period" (p<.05). Conclusion: Following the COVID-19 outbreak, there is a delay in patient transport to the emergency room through private institution inter-hospital transport and an increase in the number of patients complaining of respiratory infection symptoms. Thus, emergency medical services need additional administrative and economic support to transport infected patients.

• Journal of the Microelectronics and Packaging Society
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• v.27 no.4
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• pp.113-117
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• 2020

In this paper, We investigated the effect of heat treatment process using photo-thermal effect in order to improve mechanical properties of nanostructure on polymer films made by nanoimprint process with hybrid resin. Nanostructures which have a low refractive characteristic were fabricated by UV nanoimprint and after that heat treatment was performed using IPL (intense pulsed light) under process condition of 550 V voltage, pulse width 5 ms, frequency 0.5 Hz. The transmittance and mechanical property of fabricated nanostructure films were evaluated to observe changes in the pattern transfer rate and mechanical properties of nanostructures. The transmittance of the nanostructure was measured at 97.6% at 550 nm wavelength. Nanoindentation was performed to identify improved anti-scatch properties. Result was compared by the heat source. In case of post treatment with IPL, hardness was 0.51 GPa and in the case of hotplate was 0.27 GPa, resulting the increase of hardness of 1.8 times. Elastic modulus of IPL treated sample was 5.9GPa and Hotplate treated one was 4GPa, showing the 1.4 time increase.

• The Research Journal of the Costume Culture
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• v.29 no.1
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• pp.134-151
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• 2021

The aim of this research is to develop a clothing and textiles studio course for preservice home economics teachers applying principles of Project-Based Learning (PBL) and maker education to equip future teachers with the ability to nurture creativity among adolescents. The studio course was developed in the following stages: analysis, design, development, implementation, and evaluation. We concluded that the resulting course met the following objectives extracted from the 2015 revised curriculum of home economics subjects: to promote creative and environmentally-friendly fashion design and styling abilities, gain the ability to use makerspace tools, understand flat pattern making and sewing processes, and develop creative thinking, aesthetic sense, and communication skills. Furthermore, the educational effects of PBL and maker education were confirmed through student comments on the course. Students mentioned the practicality of the material in their actual lives along with their enhanced integration of the subject material, self-directedness, aesthetic sense, ability to learn through trial and error, collaboration and communication, and sharing. Based on results from the implementation and evaluation stages, a clothing and textiles studio course should include the following modules: introduction of terms and tools, submission and sharing of clothing reformation and upcycling techniques, introduction to hand sewing, pouch making, heat-transfer printing, 3D printing, mask making, hat making, vest making, and the final team project on fashion styling. It is important for instructors to provide detailed guidelines on selecting personas for styling, looking for available materials, and selecting materials online.

• Geomechanics and Engineering
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• v.24 no.5
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• pp.431-441
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• 2021

Rock-socketed drilled shafts are widely used to transfer the heavy loads from the superstructure especially in mountainous area. Extensive research has been done on the behavior of rock-socketed drilled shafts under compressive load. However, little attention has been paid to uplift behavior of drilled shaft in rock, which govern the overall behavior of the foundation system. In this paper, a series of centrifuge tests have been performed to investigate the uplift response of rock-socketed drilled shafts. The pull-out tests of drilled shafts installed in layered rocks having various strengths were conducted. The load-displacement response, axial load distributions in the shaft and the unit skin friction distribution under pull-out loads were investigated. The effects of the strength of rock socket on the initial stiffness, ultimate capacity and mobilization of friction of the foundation, were also examined. The results indicated that characteristics of rock-socket has a significant influence on the uplift behavior of drilled shaft. Most of the applied uplift load were carried by socketed rock when the drilled shaft was installed in the sand over rock layer, whereas substantial load was carried by both upper and lower rock layers when the drilled shaft was completely socketed into layered rock. The pattern of mobilized shaft friction and point where the maximum unit shaft friction occurred were also found to be affected by the socket condition surrounding the drilled shaft.

• Journal of Korea Multimedia Society
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• v.25 no.5
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• pp.748-756
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• 2022

Thanks to the competition of AlphaGo and Sedol Lee, machine learning has received world-wide attention and huge investments. The performance improvement of computing devices greatly contributed to big data processing and the development of neural networks. Artificial intelligence not only imitates human beings in many fields, but also seems to be better than human capabilities. Although humans' creation is still considered to be better and higher, several artificial intelligences continue to challenge human creativity. The quality of some creative outcomes by AI is as good as the real ones produced by human beings. Sometimes they are not distinguishable, because the neural network has the competence to learn the common features contained in big data and copy them. In order to confirm whether artificial intelligence can express the inherent characteristics of different arts, this paper proposes a new neural network model called Humming. It is an experimental model that combines vgg16, which extracts image features, and DeepJ's architecture, which excels in creating various genres of music. A dataset produced by our experiment shows meaningful and valid results. Different results, however, are produced when the amount of data is increased. The neural network produced a similar pattern of music even though it was a different classification of images, which was not what we were aiming for. However, these new attempts may have explicit significance as a starting point for feature transfer that will be further studied.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.145-145
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• 2022

Availability of abundant water resources data in developing countries is a great concern that has hindered the adoption of deep learning techniques (DL) for disaster prevention and mitigation. On the contrary, over the last two decades, a sizeable amount of DL publication in disaster management emanated from developed countries with efficient data management systems. To understand the current state of DL adoption for solving water-related disaster management in developing countries, an extensive bibliometric review coupled with a theory-based analysis of related research documents is conducted from 2003 - 2022 using Web of Science, Scopus, VOSviewer software and PRISMA model. Results show that four major disasters - pluvial / fluvial flooding, land subsidence, drought and snow avalanche are the most prevalent. Also, recurrent flash floods and landslides caused by irregular rainfall pattern, abundant freshwater and mountainous terrains made India the only developing country with an impressive DL adoption rate of 50% publication count, thereby setting the pace for other developing countries. Further analysis indicates that economically-disadvantaged countries will experience a delay in DL implementation based on their Human Development Index (HDI) because DL implementation is capital-intensive. COVID-19 among other factors is identified as a driver of DL. Although, the Long Short Term Model (LSTM) model is the most frequently used, but optimal model performance is not limited to a certain model. Each DL model performs based on defined modelling objectives. Furthermore, effect of input data size shows no clear relationship with model performance while final model deployment in solving disaster problems in real-life scenarios is lacking. Therefore, data augmentation and transfer learning are recommended to solve data management problems. Intensive research, training, innovation, deployment using cheap web-based servers, APIs and nature-based solutions are encouraged to enhance disaster preparedness.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.211-211
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• 2022

The marketization reform from the open-door policy in 1978 was not only booming export-oriented industries with foreign investment but also expanding the role of private actors in the Chinese water sector. Private Sector Participation (PSP) has become an important element in developing urban infrastructure by providing better services with advanced facilities. The rapid development of PSP-driven urban water infrastructure in China has a positive impacted on Chinese economic development, particularly in coastal areas. PPPs in some coastal areas have successfully spread out over China since China applied the first Build-Operate-Transfer (BOT) mode in the water sector in the early 1990s. The market-oriented water and wastewater, Public-Private Partnership (PPP) mechanism in the initial period of China has been transformed into a state-dominated PPP mechanism. The development pattern of the water and wastewater PPPs in China has been divided in four stages: the first period from 1984 to 2002, the second period from 2003 to 2008, the third period from 2009 to 2014, and the last period after 2015. The study aims to investigate the successful process of water and wastewater PPPs in local areas through five socioeconomic elements: export-oriented economic strategy, urbanization, cheap land policy, infrastructure investment, and water issues and climate change. In addition, the study focuses on analyzing the extent to which the Chinese government re-asserted its control over the PPP mechanism by classifying five elements in three different development Phases from early 2000 to 2020. The Jiangsu Province in the estern coastal area has actively invited PPP projects in the water and wastewater sectors. The successful introduction and rapid growth of PPPs in the urban water infrastructure has made the province an attractive area for a foreign investor.

• Korean Journal of Environmental Agriculture
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• v.42 no.4
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• pp.269-278
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• 2023

Antibiotics either kill or inhibit the growth of bacteria. However, antibiotic-resistant bacteria are difficult to treat with antibiotics. Infections caused by such bacteria often lead to severe diseases. Antibiotic resistance genes (ARG) can be horizontally transmitted across different bacterial species, necessitating a comprehensive understanding of how ARGs spread across various environments. In this study, we analyzed the plasmid sequences of 33 extended-spectrum beta-lactamases (ESBL) producing Escherichia coli isolated from pigs, farms, and their owners. We conducted an antibiotic susceptibility test (AST) with aztreonam and seven other antibiotics, as well as whole genome sequencing (WGS) of the strains using MinION. Our results demonstrated that the plasmids that did not harbor ARGs were mostly non-conjugative, whereas the plasmids that harbored ARGs were conjugative. The arrangement of these ARGs exhibited a pattern of organization featuring a series of ARG cassettes, some of which were identical across the isolates collected from different sources. Therefore, this study suggests that the sets of ARG cassettes on plasmids were mostly shared between pigs and their owners. Hence, enhanced surveillance of ARG should be implemented in farm environments to proactively mitigate the risk of antibiotic-resistant bacterial infections.

• 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.