• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.403-404
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• 2019

동남아의 저렴한 물가, 비행의 발달 등의 이유로 국내 관광에 대한 관심도가 떨어지면서 국내 관광에 대해 관심은 갖고 있지만, 사용자는 충분히 만족하지 못한다. 본 논문에서는 이를 해결하고자 사람들의 국내 여행에 대한 여행 만족도를 증가시킬 수 있는 방법을 제시한다. 또 비슷한 기술을 가진 다른 기술과 비교해 실제 적용 가능성을 고려하여 여러 기술들과 비교 분석한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.247-248
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• 2019

본 논문에서는 블루투스 비콘을 이용해 고소 작업장 등의 위험지역에서 작업자 추적 및 확인과 안전 벨트고리를 체결했는지 여부와 작업자의 행동에 따른 데이터를 추가로 수집하여 작업자의 행동 패턴을 분석하였다. IoT 국제 표준인 oneM2M을 기반으로 IoT Device와 Application을 연결하는 중간 매개체로 모비우스 플랫폼을 사용해 시스템을 구축하였다. 또한, 본 연구팀의 선행 연구에서 작업자 위험 행동분류 시스템을 개선할 수 있는 연구 결과를 비교하였다.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.717-723
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• 2019

Smart systems and services aim to facilitate growing urban populations and their prospects of virtual-real social behaviors, gig economies, factory automation, knowledge-based workforce, integrated societies, modern living, among many more. To satisfy these objectives, smart systems and services must comprises of a complex set of features such as security, ease of use and user friendliness, manageability, scalability, adaptivity, intelligent behavior, and personalization. Recently, artificial intelligence (AI) is realized as a data-driven technology to provide an efficient knowledge representation, semantic modeling, and can support a cognitive behavior aspect of the system. In this paper, an integration of AI with the smart systems and services is presented to mitigate the existing challenges. Several novel researches work in terms of frameworks, architectures, paradigms, and algorithms are discussed to provide possible solutions against the existing challenges in the AI-based smart systems and services. Such novel research works involve efficient shape image retrieval, speech signal processing, dynamic thermal rating, advanced persistent threat tactics, user authentication, and so on.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.344-346
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• 2019

In this paper, we propose a distance estimation method using the convolutional neural network in Ultra-Wideband (UWB) systems. The training data set used to learn the deep learning model using the convolutional neural network is generated by the MATLAB program and utilizes the IEEE 802.15.4a standard. The performance of the proposed distance estimation method is verified by comparing the threshold based distance estimation technique and the performance comparison used in the conventional distance estimation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.334-335
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• 2018

최근 수 년간 비디오 콘텐츠 소비 공간이 인터넷으로 확장되며 지능적 비디오 콘텐츠 추천 기술 개발이 진행되어 왔다. 하지만 지능적 비디오 콘텐츠 추천 기술은 사용자의 기호나 업로드된 비디오 콘텐츠의 제목 등을 기반으로 하여 비디오 콘텐츠 클래스에 대한 분석 없이 유사한 비디오 콘텐츠를 탐색하고 추천해주는 기술이 대부분이다. 본 논문에서는 지능적 콘텐츠 추천을 위한 딥러닝 기반 방송 콘텐츠 클래스 분류 시스템을 제안한다. 방송 콘텐츠 내 영상 정보를 이용하여 방송 콘텐츠 클래스를 분류하며 높은 분류 정확도를 보여주는 것을 확인할 수 있다.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.171-180
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• 2020

With the recent increase in asthma, asthma has become recognized as one of the diseases. The perception that bronchial asthma is a chronic disease and requires treatment has been strengthened. In addition, asthma is recognized as a dangerous disease due to environmental changes and efforts are made to minimize these risks. However, the environmental impact on asthma is hardly a factor that individuals in asthmatic patients can cope with. Therefore, this study was conducted to see if the asthma disease could be replaced by the individual efforts of asthma patients. In particular, since the management of asthma is important during adolescence, we conducted research on asthma in teenagers. Utilizing support vector machines, artificial neural networks and deep learning techniques that have recently drawn attention, we propose models to predict the asthma of teenagers. The study also provides guidelines to avoid factors that can cause asthma in teenagers.

• Journal of Multimedia Information System
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• v.8 no.2
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• pp.85-92
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• 2021

In a face, there is much information of person's identity. Because of this property, various tasks such as expression recognition, identity recognition and deepfake have been actively conducted. Most of them use the exact frontal view of the given face. However, various directions of the face can be observed rather than the exact frontal image in real situation. The profile (side view) lacks information when comparing with the frontal view image. Therefore, if we can generate the frontal face from other directions, we can obtain more information on the given face. In this paper, we propose a combined style model based the conditional generative adversarial network (cGAN) for generating the frontal face from multi-view images that consist of characteristics that not only includes the style around the face (hair and beard) but also detailed areas (eye, nose, and mouth).

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.180-186
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• 2021

In cloud computing service it is important to share the system resource among multiple instances according to user requirements. In particular, the issue of efficiently distributing I/O resources across multiple instances is paid attention due to the rise of emerging data-centric technologies such as big data and deep learning. However, it is difficult to evaluate the I/O resource distribution of a Linux container, which is one of the core technologies of cloud computing, since conventional I/O benchmarks does not support features related to container management. In this paper, we propose a new I/O performance benchmarking framework that can easily evaluate the resource distribution of Linux containers using existing I/O benchmarks by supporting container-related features and integrated user interface. According to the performance evaluation result with trace-replay benchmark, the proposed benchmark framework has induced negligible performance overhead while providing convenience in evaluating the I/O performance of multiple Linux containers.

• Journal of Multimedia Information System
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• v.7 no.4
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• pp.257-262
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• 2020

In this paper, a method of detecting the emergency situations such as body fall is proposed by using color images. We detect body areas and key parts of a body through a pre-learned Mask R-CNN in the images captured by a camera. Then we find the centerline of the body through the joint points of both shoulders and feet. Also, we calculate an angle to the center line and then calculate the amount of change in the angle per hour. If the angle change is more than a certain value, then it is decided as a suspected fall. Also, if the suspected fall state persists for more than a certain frame, then it is determined as a fall situation. Simulation results show that the proposed method can detect body fall situation accurately.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.707-713
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• 2021

Symptoms of foot-and-mouth disease include fever and drooling a lot around the hoof, blisters in the mouth, poor appetite, blisters around the hoof, and blisters around the hoof. Research is underway on smart barns that remotely manage these symptoms through cameras. Visible light cameras can measure the condition of livestock such as blisters, but cannot measure body temperature. On the other hand, infrared thermal imaging cameras can measure body temperature, but it is difficult to measure the condition of livestock. In this paper, we propose an object detection system using deep learning-based livestock detection using visible and infrared thermal imaging composite camera modules for preemptive response