• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.1-7
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• 2019

The medical environment, combined with IT technology, is changing the paradigm for medical services from treatment to prevention. In particular, as ICT convergence digital healthcare technology is applied to hospital medical systems, infrastructure technologies such as big data, Internet of Things, and artificial intelligence are being used in conjunction with the cloud. In particular, as medical services are used with IT devices, the quality of medical services is increasingly improving to make them easier for users to access. Medical institutions seeking to incorporate IoT services into cloud health care environment services are trying to reduce hospital operating costs and improve service quality, but have not yet been fully supported. In this paper, a patient information collection model from hospital IoT system, which has established a cloud environment, is proposed. The proposed model prevents third parties from illegally eavesdropping and interfering with patients' biometric information through IoT devices attached to the patient's body at hospitals in cloud environments that have established hospital IoT systems. The proposed model allows clinicians to analyze patients' disease information so that they can collect and treat diseases associated with their eating habits through IoT devices. The analyzed disease information minimizes hospital work to facilitate the handling of prescriptions and care according to the patient's degree of illness.

• Korean Journal of Remote Sensing
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• v.34 no.6_3
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• pp.1415-1425
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• 2018

Kompsat-5 is the first Earth Observation Satellite which is equipped with an SAR in Korea. SAR images are generated by receiving signals reflected from an object by microwaves emitted from a SAR antenna. Because the wavelengths of microwaves are longer than the size of particles in the atmosphere, it can penetrate clouds and fog, and high-resolution images can be obtained without distinction between day and night. However, there is no color information in SAR images. To overcome these limitations of SAR images, colorization of SAR images using Cycle GAN, a deep learning model developed for domain translation, was conducted. Training of Cycle GAN is unstable due to the unsupervised learning based on unpaired dataset. Therefore, we proposed MS Cycle GAN applying multi-scale discriminator to solve the training instability of Cycle GAN and to improve the performance of colorization in this paper. To compare colorization performance of MS Cycle GAN and Cycle GAN, generated images by both models were compared qualitatively and quantitatively. Training Cycle GAN with multi-scale discriminator shows the losses of generators and discriminators are significantly reduced compared to the conventional Cycle GAN, and we identified that generated images by MS Cycle GAN are well-matched with the characteristics of regions such as leaves, rivers, and land.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.224-226
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• 2016

With the technical development and rapid increase of private demand, the new market for unmanned vehicle combined with the characteristics of 'unmanned automation' and 'vehicle' is rapidly growing. Even though the pilot driving is currently allowed in some countries, there is no country that has institutionalized the formal driving of self-driving cars. In case of the existing vehicles, safety incidents are frequently happening due to the frequent malfunction of the rear sensor, blind spot of the rear camera, or drivers' carelessness. Once such minor flaws are complemented, the relevant regulations for the commercialization of self-driving car and small drone could be relieved. Contrary to the ultrasonic and laser sensors used for the existing vehicles, this paper aims to attempt the distance measurement by using the depth sensor. A depth camera calculates the distance data based on the TOF method calculating the time difference by lighting laser or infrared light onto an object or area and then receiving the beam coming back. As this camera can obtain the depth data in the pixel unit of CCD camera, it can be used for collecting depth data in real-time. This paper suggests to solve problems mentioned above by using depth data in real-time and also to design the obstacle avoidance system through distance measurement.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.267-277
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• 2021

Both teachers and learners should participate in non-face-to-face class due to COVID-19. The non-face-to-face class has brought about many problems, where they made adequate preparations for such abrupt situation. This study attempted to understand and improve problems occurring during non-face-to-face midi class. The findings are as follows: First, there were differences in equipment available to contact and non-face-to-face class. Such a problem could be improved by using Reaper, DAW which can be installed and freely utilized without any functional limits, regardless of the types of operating systems. Second, latency could not be reduced, when the screen share function of Zoom was used, since it was impossible to select audio interface's drivers in DAW. This problem was improved by again receiving audio output as input and sending it, from the perspectives of teachers. In addition, learners who used the operating system of Windows and have no audio interfaces usually suffer from latency during practices. The latency can be reduced by installing Asio4all. Third, image degradation and screen disconnection phenomena occurred due to the lack of resource. Two computers were connected by using a capture board and the screen disconnection phenomena could be improved by distributing resources and maintaining high-resolution. The system for allowing non-face-to-face midi class could be successfully established, as one more computer was connected by using Vienna Ensemble Pro and more plug-ins were used by securing additional resources. Consequently, the problems of non-face-to-face midi class could be understood and improved.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.296-301
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• 2021

This study is a study dealing with the empirical test of standardized multimedia disaster warning broadcasting linked with the next-generation prediction and warning platform and the disaster warning additional data service of terrestrial UHD broadcasting. The next-generation prediction and warning platform used in the demonstration test complies with the CAP-based TTA standardization standard, and the UHD disaster warning additional data service complies with the AEAT standard. As a result of the experiment, when a standardized CAP disaster warning message is issued and delivered to a broadcasting company, a system was established so that it is automatically converted to AEAT, a UHD disaster warning additional data message, and transmitted. The receiver unit was configured by connecting a set-top capable of receiving disaster alert data and a TV with an HDMI cable. When a disaster is announced, the set-top displays the AEAT message on the TV broadcasting screen, customized to the priority of the disaster and the area where it is issued. In addition, incoming messages are displayed in a language suitable for user settings among 5 languages. Additional multimedia functions such as images and alarm sounds could also be linked. In particular, it was confirmed that the receiver message was displayed within 3 seconds of issuing the disaster alert, enabling prompt delivery of the disaster alert.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.1-7
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• 2023

Recently, the technology of device-to-device(D2D) communication has been receiving big attention to improve the system performance since the amount of high quality/large capacity data traffic from smart phones and various devices of Internet of Things increase rapidly in 5G/6G based next generation cellular networks. However, even though the system performance of macro cells increase by reusing the frequency, the performance of macro user equipments(MUEs) decrease because of the strong interference from D2D user equipments(DUEs). Therefore, this paper proposes a dynamic channel management(DCM) scheme for DUEs to guarantee the performance of MUEs as the number of DUEs increases in next generation downlink cellular networks. In the proposed D2D DCM scheme, macro base stations dynamically assign subchannels to DUEs based on the interference information and signal to interference and noise ratio(SINR) of MUEs. Simulation results show that the proposed D2D DCM scheme outperforms other schemes in terms of the mean MUE capacity as the threshold of the SINR of MUEs incareases.

• Journal of Korean Society of Rural Planning
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• v.29 no.3
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• pp.25-37
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• 2023

According to the 「Rural Spatial Reconstruction and Regeneration Support Act」, enacted on March 29, 2024, all local governments are required to establish a 'Rural Spatial Reconstruction and Regeneration Plan' (hereinafter referred to as the 'Rural Spatial Plan'). In order for the 'Rural Spatial Plan' to be appropriately established, this study analyzed the supply and demand of spatial data from the perspective of user stakeholders and derived implications for improving rural spatial planning data utilization. In conclusion, three key recommendations come from this result. Firstly, it is necessary to establish an integrated DB for rural spatial planning data. This can solve the problem of low awareness of scattered data-providing websites, reduce the processing time of non-GIS data, and reduce the time required to acquire data by securing the availability of data search and download. In particular, research should be conducted on the establishment of a spatial analysis simulation system to support stakeholders' decision-making, considering that many stakeholders have difficulty in spatial analysis because spatial analysis techniques were not actively used in rural projects before the implementation of the rural agreement system in 2020. Secondly, research on how to improve data acquisition should be conducted in each data sector. The data sector group with the lowest ease of receiving are 'Local Community Domain', 'Changes in Domestic and International Conditions', and 'Provision and Utilization of Daily Life Services'. Lastly, in-depth research is needed on how to raise each rural spatial planning data supply stakeholder to the position of player. Stakeholders of 'University Institutions' and 'Public Enterprises and Research Institutes' should give those who participate in the formulation of rural spatial plans access to the raw data collected for public work. Stakeholders of 'Private company' need to come up with realistic measures to build a data pool centered on consultative bodies between existing private companies and then prepare a step-by-step strategy to fully open it by participating various stakeholders. In order to induce 'Village Residents and Associations' stakeholders to play a leading role as owners and producers of data, personnel should be trained to collect and record data related to the village. In addition, support measures should be prepared to continue these activities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.31-40
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• 2022

The importance of disaster management and response is emerging as various disasters such as COVID-19, torrential rains, and fires occur one after another. In addition, in order to respond efficiently throughout disaster response activities, it is necessary to quickly collect disaster site information and quickly check the site situation through photo and video information so that rapid disaster response can be achieved. In this study, essential information required for decision-making was derived by analyzing the essential activities of each disaster response stage, analyzing the crisis management standard manual and related laws for each disaster type, and daily comprehensive report. In addition, a list of information necessary to grasp the situation of the disaster site and grasp the status of real-time damage was derived to establish guidelines for collecting volatile disaster site information, and disaster situation information can be efficiently displayed through a spatial information-based display system. By presenting essential disaster management information to be collected first, the person in charge of collecting information can efficiently collect information, and the situation room in charge of disaster response decision-making is expected to enable more efficient disaster situation management by receiving only the necessary information.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.60.3-61
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• 2021

The Korean VLBI Network (KVN) consists of three 21m radio telescopes installed in Seoul, Ulsan, and Jeju Island with the world's first 4-channel receiver that can observe four different frequencies (e.g., 22, 43, 86, 129 GHz) simultaneously. This receiving system of KVN is particularly effective in millimeter-wavelength VLBI (mm-VLBI) observations by compensating fast atmospheric fluctuations effectively. This technology is now being enhanced with a compact triple-band receiver, becoming the world standard for a mm-VLBI system. In 2020, KVN supported 54 observing programs (KVN: 28, EAVN: 26) including the 2nd KVN Key Science Program (KSP) which supports 8Gbps data recording rate and the East Asian VLBI Network (EAVN) programs. KVN also participated in the European VLBI Network (EVN) and GMVA (Global Millimeter VLBI Array) sessions regularly. Here, we report current status and future propsects of KVN.