• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.250-259
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• 2019

Big data processing technology and artificial intelligence (AI) are increasingly attracting attention. Natural language processing is an important research area of artificial intelligence. In this paper, we use Korean news articles to extract topic distributions in documents and word distribution vectors in topics through LDA-based Topic Modeling. Then, we use Word2vec to vector words, and generate a weight matrix to derive the relevance SCORE considering the semantic relationship between the words. We propose a way to recommend documents in order of high score.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.87-94
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• 2019

IoT-based services are being released in accordance with the aging population and the demand for well-being pursuit needs. In addition to medical device companies, companies with ideas ranging from global ICT companies to startup companies are accelerating their market entry. The areas where these services are most commonly applied are health/medical, life/safety, city/energy, automotive and transportation. Furthermore, by expanding IoT technology convergence into the area of life care services, it contributes greatly to the development of service models in the public sector. It also provides an important opportunity for IoT-related companies to open up new markets. By addressing the problems of life care services that are still insufficient. We are providing opportunities to pursue the common interests of both users and workers and improve the quality of life. In order to establish IoT-based digital life care services, it is necessary to develop convergence technologies using cloud computing systems, big data analytics, medical information, and smart healthcare infrastructure.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1648-1656
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• 2018

The configuration of redundant inertial sensors are very important when considering navigation performance and fault detection and isolation (FDI) performance. By constructing a redundant sensor system using multiple inertial sensors, it is possible to improve the navigation performance and fault detection and isolation performance, which are highly related to the sensor configuration and allocation. In order to deploy multiple MEMS inertial measurement units effectively, a configuration and allocation methods considering navigation performance, fault detection and isolation performance, and lever arm effect in one plane are presented, and the performance is analyzed through simulation in this research. From the results, it is confirmed that the proposed configuration and allocation method can improve navigation, FDI, and lever arm effect rejection performances more effectively by more than 70%.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.149-154
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• 2019

High pressure valve tester used in industrial fields precise measurement gives inconvenience in precise measurement due to manually regulated pressures. In order to improve this inconvenience, the high pressure valve tester was designed by using CATIA and structural analysis of the designed high pressure valve tester was conducted and water leaking, total deformation, strain and stress were obtained by applying ANSYS. These results will be provided to develop new concepts of high pressure valve tester as initial data.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.115-119
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• 2020

Recently, CCTV installations are rapidly increasing in the public and private sectors to prevent various crimes. In accordance with the increasing number of CCTVs, video-based abnormal behavior detection in control systems is one of the key technologies for safety. This is because it is difficult for the surveillance personnel who control multiple CCTVs to manually monitor all abnormal behaviors in the video. In order to solve this problem, research to recognize abnormal behavior using deep learning is being actively conducted. In this paper, we propose a model for detecting abnormal behavior based on the deep learning model that is currently widely used. Based on the abnormal behavior video data provided by AI Hub, we performed a comparative experiment to detect anomalous behavior through violence learning and fainting in videos using 2D CNN-LSTM, 3D CNN, and I3D models. We hope that the experimental results of this abnormal behavior learning model will be helpful in developing intelligent CCTV.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1964-1967
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• 2021

Recently, to improve the effectiveness of education to learn from textbooks, immersive 3D environments such as virtual reality(VR) has been widely used for education. In this paper, in order to intuitively present education about content scenarios on changes in the human body according to food intake, we consist an immersive virtual reality environment to express the same life-size organs. The participants in our educational system showed higher results in all items compared to the existing textbook-based education such as immersion, understanding, and quality of education program. Also it was found the importance of interactivity to increase the effectiveness of immersive class.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.262-264
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• 2023

Internet of Things (IoT) networks currently employ an increased number of users and applications, raising their susceptibility to cyberattacks and data breaches, and endangering our security and privacy. Intrusion detection, which includes monitoring and analyzing incoming and outgoing traffic to detect and prohibit the hostile activity, is critical to ensure cybersecurity. Conventional intrusion detection systems (IDS) are centralized, making them susceptible to cyberattacks and other relevant privacy issues because all the data is gathered and processed inside a single entity. This research aims to create a blockchain-based architecture to support federated learning and improve cybersecurity and intrusion detection in IoT networks. In order to assess the effectiveness of the suggested approach, we have utilized well-known cybersecurity datasets along with centralized and federated machine learning models.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.151-153
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• 2023

Federated learning (FL)-based network intrusion detection techniques have enormous potential for securing the Industrial Internet of Things (IIoT) cybersecurity. The openness and connection of systems in smart industrial facilities can be targeted and manipulated by malicious actors, which emphasizes the significance of cybersecurity. The conventional centralized technique's drawbacks, including excessive latency, a congested network, and privacy leaks, are all addressed by the FL method. In addition, the rich data enables the training of models while combining private data from numerous participants. This research aims to create an FL-based architecture to improve cybersecurity and intrusion detection in IoT networks. In order to assess the effectiveness of the suggested approach, we have utilized well-known cybersecurity datasets along with centralized and federated machine learning models.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.57-62
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• 2024

This study conducted a measurement method of high temeprature conditions using infrared termography. All objects emit infrared light, and this emissivity has a significant impact on the temperature measurements of infrared thermal imaging (IR) cameras. In order to measure the temperature more accurately with the IR camera, correction equations were derived by measuring the emissivity according to the temperature change of combustible metals in a high-temperature environment. Two combustible metals, Mg and Al, were used to measure emissivity with changing temperature. Each metal was heated, the emissivity was measured by comparing the temperature with IR camera and thermocouples so that the correlation between temperature and emissivity could be anslyzed. As a result of the experiment, the emissivity of the metals increases as the temperature increased. This can be interpreted as a result of increased radiation emission as the thermal movement of internal metal molecules increased.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.141-152
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• 2012

This study is a comparatively analyzes innovation tools for developing appropriate business models according to the types of convergence. Firstly, it examines previous studies on the type of convergence, business models, and innovation tools. Based on the understanding of each topic through literature search, it introduces Convergence-Business-Innovation Tools Cube (CBI Cube) model with the concept of developing innovative business models by applying innovation tools under the condition of convergence. In order to quantify (concretize) the concept, we have compared the relative priority of innovation tools for developing business models to find component factors of CBI Cube model through the survey of an expert group by adopting DelPhi method and AHP method. From the result of this study, we expect to be able to make an easier approach to the development of innovative products, services and market as it allo ws to develop business models of value innovation beyond just benchmarking or simple imitation of existing business models.