• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.470-476
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• 2020

In this paper, we present the design of modular replaceable AI server for image deep learning that separates the server from the Edge Device so as to drive the AI block and the method of data transmission and reception. The modular replaceable AI server for image deep learning can reduce the dependency between social robots and edge devices where the robot's platform will be operated to improve drive stability. When a user requests a function from an AI server for interaction with a social robot, modular functions can be used to return only the results. Modular functions in AI servers can be easily maintained and changed by each module by the server manager. Compared to existing server systems, modular replaceable AI servers produce more efficient performance in terms of server maintenance and scale differences in the programs performed. Through this, more diverse image deep learning can be included in robot scenarios that allow human-robot interaction, and more efficient performance can be achieved when applied to AI servers for image deep learning in addition to robot platforms.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.48-59
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• 2021

This study aimed to explore anxiety, risk perception, information literacy, and performance level of infection prevention practices against coronavirus disease (COVID-19) among nursing students during the pandemic. A descriptive online survey was conducted, targeting a total of 224 nursing students from June 8, 2020 to 14, 2020. The collected data were analyzed using descriptive statistics, t-test, analysis of variance, and correlation analysis using SPSS 26.0. The nursing students' level of anxiety was 6.86 out of 10, which was normal. Their information literacy level and performance level of infection prevention practices were 3.50 out of 4 and 4.44 out of 5, respectively, and these scores were considered high. The higher the level of anxiety, risk perception, and information literacy, the higher the level of infection prevention practices. The level of anxiety with respect to infection and risk perception may increase when new types of infectious diseases such as COVID-19 break out. Therefore, it is necessary to promote the accurate understanding of the infectious diseases by providing sufficient information. Accurate understanding of new infectious diseases can reduce the risk of transmission as it encourages people to thoroughly perform infection prevention practices.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.318-331
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• 2022

With the recent development of hardware computing devices and software based frameworks, machine tasks using deep learning networks are expected to be utilized in various industrial fields and personal IoT devices. However, in order to overcome the limitations of high cost device for utilizing the deep learning network and that the user may not receive the results requested when only the machine task results are transmitted from the server, Collaborative Intelligence (CI) proposed the transmission of feature maps as a solution. In this paper, an efficient compression method for feature maps with vast data sizes to support the CI paradigm was analyzed and presented through experiments. This method increases redundancy by applying feature map reordering to improve compression efficiency in traditional video codecs, and proposes a feature map method that improves compression efficiency and maintains the performance of machine tasks by simultaneously utilizing image compression format and video compression format. As a result of the experiment, the proposed method shows 14.29% gain in BD-rate of BPP and mAP compared to the feature compression anchor of MPEG-VCM.

• Journal of Veterinary Science
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• v.23 no.3
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• pp.33.1-33.10
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• 2022

Background: Endemic circulation of human-specific hepatitis E virus (HEV) genotypes 1 and 2 may occult the importance of sporadic zoonotic HEV transmissions in Africa. Increasing numbers of studies reporting anti-HEV antibodies in cattle and the discovery of infectious HEV in cow milk has raised public health concern, but cattle exposure has seldom been investigated in Africa. Objectives: This study aimed at investigating the role of cows in the epidemiology of HEV in Burkina Faso and farmers habits in terms of dairy product consumption as a prerequisite to estimate the risk of transmission to humans. Methods: Sera from 475 cattle and 192 pigs were screened for the presence of anti-HEV antibodies while HEV RNA in swine stools was detected by reverse transcription polymerase chain reaction. Data on mixed farming, dairy product consumption and selling habits were gathered through questionnaires. Results: The overall seroprevalence in cattle was 5.1% and herd seroprevalence reached 32.4% (11/34). Herd seropositivity was not associated with husbandry practice or presence of rabbits on the farms. However, herd seropositivity was associated with on-site presence of pigs, 80.7% of which had anti-HEV antibodies. The majority of farmers reported to preferentially consume raw milk based dairy products. Conclusions: Concomitant presence of pigs on cattle farms constitutes a risk factor for HEV exposure of cattle. However, the risk of HEV infections associated with raw cow dairy product consumption is currently considered as low.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.107-123
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• 2021

In recent years, due to the continuous density and urbanization of space, the expansion of awareness of rights, the need for landscape conservation, and the development of construction technology, the conventional flat land use has been deviated from the conventional flat land use, and the transmission line, urban railway, parking lot, communal district, underground shopping mall, pipeline, etc. Although 3D spatial activities are carried out in the form of 3D space, there are considerable difficulties in administration to manage the 3D use of land due to the inadequacy of related regulations. In this background, for the administration that can manage Sectional Superficies, which is a representative case of 3D spatial use of parcels, which is a registered unit of land, first, the law on the establishment and management of spatial information, and cadastral re-examination from the legal and institutional aspects Standardization of 3D space registration through amendments to the Special Act, etc. and the formation of consensus among related departments. Second, in technical and administrative aspects, the registration of Sectional Superficies based on cadastral survey results, establishment of a platform for integrated management of location and attribute data, and registration method was found to be in need of improvement. As suggested in this study, by registering and managing Sectional Superficies, it is possible to manage various 3D land use of not only ground space or surface space but also underground space. It is expected to be able to register and manage lot-based 3D land use efficiently.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.2
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• pp.68-75
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• 2022

In this study, in order to directly evaluate the prestress of the PSC structure, a new sensor module based on the measurement of the deformation of concrete was proposed using hetero-core optical fibers and performance tests were performed. In a hetero-core optical fiber, optical loss occurs when a specific part of the transmission path is bent, and the amount of optical loss changes linearly according to the magnitude of the curvature. In order to confirm the measurement performance of the sensor module and the applicability of the optical fiber, the sensor module was deformed and the light passing through the optical fiber was converted into wattage and measured. It can be seen that the light passing through the optical fiber has a linearity of 0.9333 in relation to the deformation while generating the maximum deformation of 0.5 mm at a rate of 0.12 mm/min in a cylindrical concrete specimen with a diameter of 15 cm and a height of 35 cm in which the sensor module is embedded. Based on the results of this experiment, it is judged that it is possible to directly evaluate the prestress of a PSC structure by embedding a sensor module using a hetero-core optical fiber in the structure and measuring the compression deformation in concrete. It is judged that it can be used as useful data for the development of a sheath tube integrated sensor module to be applied to be applied to the girder model experiment.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.21-33
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• 2022

This paper is to suggest the secure secret sharing system in order to outstandingly reduce the damage caused by the leakage of the corporate secret. This research system is suggested as efficient P2P distributed system kept from the centrally controlled server scheme. Even the bitcoin circulation system is also based on P2P distribution scheme recenly. This research has designed the secure circulation of the secret shares produced by Threshold Shamir Secret Sharing scheme instead of the shares specified in the torrent file using the simple, highly scalable and fast transferring torrent P2P distribution structure and its protocol. In addition, this research has studied to apply both Shamir Threshold Secret Sharing scheme and the securely strong multiple user authentication based on Collaborative Threshold Autentication scheme. The secure transmission of secret data is protected as using the efficient symmetric encryption with the session secret key which is safely exchanged by the public key encryption. Also it is safer against the leakage because the secret key is effectively alive only for short lifetime like a session. Especially the characteristics of this proposed system is effectively to apply the threshold secret sharing scheme into efficient torrent P2P distributed system without modifying its architecture of the torrent system. In addition, this system guaranttes the confidentiality in distributing the secret file using the efficient symmetric encryption scheme, which the session key is securely exchanged using the public key encryption scheme. In this system, the devices to be taken out can be dynamically registered as an user. This scalability allows to apply the confidentiality and the authentication even to dynamically registerred users.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.13-20
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• 2022

IEEE 802.11ay Wi-Fi is the next generation wireless technology and operates in mmWave band. It supports the MU-MIMO (Multiple User Multiple Input Multiple Output) transmission in which an AP (Access Point) can transmit multiple data streams simultaneously to multiple STAs (Stations). To this end, the AP should perform MU-MIMO beamforming training with the STAs. For efficient MU-MIMO beamforming training, it is important for the AP to estimate signal strength measured at each STA at which multiple beams are used simultaneously. Therefore, in the paper, we propose a deep learning-based link quality estimation scheme. Our proposed scheme estimates the signal strength with high accuracy by utilizing a deep learning model pre-trained for a certain indoor or outdoor propagation scenario. Specifically, to estimate the signal strength of the multiple concurrent beams, our scheme uses the signal strengths of the respective single beams, which can be obtained without additional signaling overhead, as the input of the deep learning model. For performance evaluation, we utilized a Q-D (Quasi-Deterministic) Channel Realization open source software and extensive channel measurement campaigns were conducted with NIST (National Institute of Standards and Technology) to implement the millimeter wave (mmWave) channel. Our simulation results demonstrate that our proposed scheme outperforms comparison schemes in terms of the accuracy of the signal strength estimation.

• Journal of IKEEE
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• v.26 no.3
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• pp.510-514
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• 2022

In this paper, we propose the development of high-sensitivity low-end radiation measuring sensor module. The proposed measurement sensor module is a scintillator + photomultiplier(SiPM) sensor optimization structure design, amplification and filter and control circuit design for sensor driver, control circuit design including short-distance communication, sensor mechanism design and manufacturing, and GUI development applied to prototypes consists of, etc. The scintillator + photomultiplier(SiPM) sensor optimization structure design is designed by checking the characteristics of the scintillator and the photomultiplier (SiPM) for the sensor structure design. Amplification, filter and control circuit design for sensor driver is designed to process fine scintillation signal generated by radiation with a scintillator using SiPM. Control circuit design including short-distance communication is designed to enable data transmission through MCU design to support short-range wireless communication function and wired communication support. The sensor mechanism design and manufacture is designed so that the glare generated by wrapping a reflective paper (mirroring) on the outside of the plastic scintillator is reflected to increase the efficiency in order to transmit the fine scintillation signal generated from the plastic scintillator to the photomultiplier(SiPM). The GUI development applied to the prototype expresses the date and time at the top according to each screen and allows the measurement unit and time, seconds, alarm level, communication status, battery capacity, etc. to be expressed. In order to evaluate the performance of the proposed system, the results of experiments conducted by an authorized testing institute showed that the radiation dose measurement range was 30 𝜇Sv/h ~ 10 mSv/h, so the results are the same as the highest level among products sold commercially at domestic and foreign. In addition, it was confirmed that the measurement uncertainty of ±7.4% was measured, and normal operation was performed under the international standard ±15%.

• Journal of Appropriate Technology
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• v.7 no.2
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• pp.196-205
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• 2021

As industrial safety increases, various industrial accident prevention technologies using smart factory technology are being studied. However, small and medium enterprises (SMEs), which account for the majority of industrial accidents, are having difficulties in preventing industrial accidents by applying these smart factory technologies due to practical problems. In this study, customized monitoring and warning systems for each type of industrial accident were developed and applied to the actual field. Through this, we demonstrated industrial accident prevention technology through appropriate smart factory technology used by SMEs. A customized monitoring system using vision, current, temperature, and gas sensors was established for the four major disaster types: worker body access, short circuit and overcurrent, fire and burns due to high temperature, and emission of hazardous gas. In addition, a notification method suitable for each work environment was applied so that the monitored risk factors could be recognized quickly, and real-time data transmission and display enabled workers and managers to understand the disaster risk effectively. Through the application and demonstration of these appropriate smart factory technologies, the spread of these industrial safety technologies is to be discussed.