• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.665-672
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• 2023

Purpose: Underground utility tunnel is facility that is jointly house infrastructure such as electricity, water and gas in city, causing condensation problems due to lack of airflow. This paper aims to prevent electricity leakage fires caused by condensation by detecting whether the control panel door in the underground utility tunnel is open using a deep learning model. Method: YOLO, a deep learning object recognition model, is trained to recognize the opening and closing of the control panel door using video data taken by a robot patrolling the underground utility tunnel. To improve the recognition rate, image augmentation is used. Result: Among the image enhancement techniques, we compared the performance of the YOLO model trained using mosaic with that of the YOLO model without mosaic, and found that the mosaic technique performed better. The mAP for all classes were 0.994, which is high evaluation result. Conclusion: It was able to detect the control panel even when there were lights off or other objects in the underground cavity. This allows you to effectively manage the underground utility tunnel and prevent disasters.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.407-418
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• 2023

The Multi-Object Goal Visual Navigation(MultiOn) is a visual navigation task in which an agent must visit to multiple object goals in an unknown indoor environment in a given order. Existing models for the MultiOn task suffer from the limitation that they cannot utilize an integrated view of multimodal context because use only a unimodal context map. To overcome this limitation, in this paper, we propose a novel deep neural network-based agent model for MultiOn task. The proposed model, MCFMO, uses a multimodal context map, containing visual appearance features, semantic features of environmental objects, and goal object features. Moreover, the proposed model effectively fuses these three heterogeneous features into a global multimodal context map by using a point-wise convolutional neural network module. Lastly, the proposed model adopts an auxiliary task learning module to predict the observation status, goal direction and the goal distance, which can guide to learn the navigational policy efficiently. Conducting various quantitative and qualitative experiments using the Habitat-Matterport3D simulation environment and scene dataset, we demonstrate the superiority of the proposed model.

• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.79-91
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• 2019

In the entertainment industry, risk management is crucial for securing competitiveness due to the risk of investment. The competitiveness of contents is reinforced when external factors such as industrial environment and internal factors centering on involving mechanism are simultaneously provided. The involving mechanism is a form of cognitive response behavior of the audience and occurs through signal processing of the brain when watching the image contents. The signal processing of the brain related to the contents watching is mainly performed in the working memory area, and in the case of the captivating movie, the information other than the contents transmitted to the audience is blocked to generate a temporary dissociation state. A dissociation state similar to a symptom such as hypnosis or amnesia occurs when the audience's level of involving is high. On the other hand, contents information in which the audience is concentrating his attention is used intensively for constructing future thinking through an episodic buffer while the inflow of external information is relatively blocked or delayed. The spectator's future thinking configuration takes the form of a hypothesis-forming activity and is based on the predictability of the brain. When these hypothesized behaviors correspond to the problem solving simulation of story and predictability which is an evolutionary function of the brain, the audience' s brain is involved in the contents at a high level. In order for the act to be effective, the factors such as the background of the hypothesis, the subject of the hypothesis, the internal information of the person, the type and position and quantity of the hypothesis information, and the hypothesis relevance and type of information are important. Based on these factors, analysis of the Kim Eun Sook Drama 'Goblin' shows that the above elements are operated in a very organic and meaningful way.

• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.111-122
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• 2019

The advent of the Fourth Industrial Revolution provides new civilized convenience, while the humanistic ecological environment is at stake. Therefore, looking at our culture and arts ecological foundations is ultimately for the preparation of a rich life for the future. Therefore, establishing a desirable cultural ecosystem begins with an enduring tradition of traditional art.This study examined the dancing characteristics of gabbigochanong-ag, which maintains the nongsapul-inong-ag performance pattern. Two field studies and image analysis studies showed that gabbigochanong-ag maintained the characteristics of traditional nong-ag, which strengthened the solidarity and cooperation of village community members and shared community identity. gabbigochanong-ag encourages the participation of the members of the village community through mechanistic dance movements based on soundness, imitative dance movements with minimal movement, repetitive dance movements, and communicative dance movements, As a result of the change, the members of the group were attracted to each other. Although gabbigochanong-ag was not sophisticated or sophisticated, it had a dancing structure that could create aesthetics and marginal aesthetics of slowness from the swiftness and convenience of civilization and bring harmony among the members of the community with warm emotion.

• Journal of Service Research and Studies
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• v.12 no.4
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• pp.94-105
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• 2022

Urban Air Transportation (UAM) is a three-dimensional transport within the city using eVTOL as an alternative to the saturation of land transportation due to overcrowding in major cities around the world. Design has played its roles in various fields in the development of transport, but research on the design application of UAM, which will be commercialized soon, is insufficient. Accordingly, there is a growing need for prior research on the forecasting the future environment and the design application through phenomenon analysis. The purpose of this study is to derive mega trends through STEP analysis for UAM and present ways to apply design in the UAM field based on this. The research method was conducted in the following order. First, the theoretical background of UAM was established by analyzing prior art documents on UAM. Second, five trends in the future environment centered on UAM were derived through STEP analysis. Finally, in order to derive a design application, five experts in each design area (product, visual, video, environment, service) discussed the design application focusing on the results of STEP analysis and derived a design application plan for each design area in the UAM field. Through this study, it was found that the most frequent design area in the STEEP analysis is product design and service design, and therefore related design development is important. After analyzing UAM's information provision plan, display method, and usage process suggested in this study, it is expected that it will lead to various prior design studies related to UAM, such as customized service design, to establish an infrastructure environment for commercialization of UAM.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.200-208
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• 2022

In this study, an automatic information collection system and geographic information construction algorithm for the transportation disadvantaged using electric mobility aids are implemented using an object recognition model. Recognizes objects that the disabled person encounters while moving, and acquires coordinate information. It provides an improved route selection map compared to the existing geographic information for the disabled. Data collection consists of a total of four layers including the HW layer. It collects image information and location information, transmits them to the server, recognizes, and extracts data necessary for geographic information generation through the process of classification. A driving experiment is conducted in an actual barrier-free zone, and during this process, it is confirmed how efficiently the algorithm for collecting actual data and generating geographic information is generated.The geographic information processing performance was confirmed to be 70.92 EA/s in the first round, 70.69 EA/s in the second round, and 70.98 EA/s in the third round, with an average of 70.86 EA/s in three experiments, and it took about 4 seconds to be reflected in the actual geographic information. From the experimental results, it was confirmed that the walking weak using electric mobility aids can drive safely using new geographic information provided faster than now.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.127-143
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• 2023

Currently, the domestic traditional market has not escaped the swamp of stagnation that began in the early 2000s despite various projects promoted by many related players such as the central government and local governments. In order to overcome the crisis faced by the traditional market, various R&Ds have recently been conducted on how to build a smart traditional market that combines information and communication technologies such as big data analysis, artificial intelligence, and the Internet of Things. This study analyzes various previous studies, users of traditional markets, and application cases of ICT technology in foreign traditional markets since 2012 and proposes a model to build a smart traditional market using ICT technology based on the analysis. The model proposed in this study includes building a traditional market metaverse that can interact with visitors, certifying visits to traditional markets through digital signage with NFC technology, improving accuracy of fire detection functions using IoT and AI technology, developing smartphone apps for market launch information and event notification, and an e-commerce system. If a smart traditional market platform is implemented and operated based on the smart traditional market platform model presented in this study, it will not only draw interest in the traditional market to MZ generation and foreigners, but also contribute to revitalizing the traditional market in the future.

• Journal of the Korean Geotechnical Society
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• v.23 no.7
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• pp.65-76
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• 2007

Recently, there have been many construction projects on soft ground with growth of industry and various construction problems concerning soft soil behavior also have been reported. Especially, foundation piles of abutments and (or) buildings which were constructed on the soft ground have been suffering from a lot of stability problems of inordinary displacement due to lateral flow of soft ground. Although many researches for this phenomena have been carried out, it is still difficult to assess the mechanism of lateral flow on soft ground quantitatively. And reliable design method for judgement of lateral flow occurrence is not established yet. In this study, PNN (probabilistic neural network) and CNN (committee neural network) theories were applied for judgment of lateral flow occurrence based on eat data compiled from Korea and Japan. Predictions of PNN and CNN models for new data which were not used during model development are compared with those predicted by conventional empirical methods. It was found that the developed PNN and CNN models can predict more precise and reliable judgment of lateral flow occurrence than conventional empirical methods.

• Knowledge Management Research
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• v.24 no.1
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• pp.1-29
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• 2023

The COVID-19 pandemic has accelerated digital transformation across all industries and daily life. Edutech is spreading in the education field, also bringing changes in university education. Non-face-to-face online-only classes at universities have spread after the COVID-19 pandemic physical distancing started. Online-only or real-time online classes showed diverse educational imitations. 'Metaverse' started to attract attention as a learning space and community activity support platform that may solve the limitations of online education and communication. It is time to prepare an introduction strategy for the actual application of education using metaverse. This study, first, by examining previous studies and cases of metaverse application, and second, establishing a metaverse introduction framework based on the technology lifecycle model and the innovation diffusion theory. Finally, we provide an introduction strategy in steps, a specialized introduction plan according to the main users is established and presented as a scenario. We expect that this study will provide the theoretical background of the new technology introduction and the spread of metaverse research. Also, we present an efficient introduction strategy, the basis for a service model, and a practical basis for the university's value-added strategy.

• Land and Housing Review
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• v.14 no.2
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• pp.125-135
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• 2023

Drones are used in various fields, including land survey, transportation, forestry/agriculture, marine, environment, disaster prevention, water resources, cultural assets, and construction, as their industrial importance and market size have increased. In this study, image data for deep learning was collected using a mavic3 drone capturing images at a shooting altitude was 20 m with ×7 magnification. Swin Transformer and UperNet were employed as the backbone and architecture of the deep learning model. About 800 sheets of labeled data were augmented to increase the amount of data. The learning process encompassed three rounds. The Cross-Entropy loss function was used in the first and second learning; the Tversky loss function was used in the third learning. In the future, when the crack detection model is advanced through convergence with the Internet of Things (IoT) through additional research, it will be possible to detect patching or potholes. In addition, it is expected that real-time detection tasks of drones can quickly secure the detection of pavement maintenance sections.