• Smart Media Journal
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• v.8 no.2
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• pp.29-38
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• 2019

With the advancement of information and communication technology, tactical networks are continuously being converted to All-IP future tactical networks that integrate all application services based on Internet protocol. Futuristic tactical mesh network is built with tactical WAN (wide area network) nodes that are inter-connected by a mesh structure. In order to guarantee QoS (quality of service) of application services, tactical service mesh (TSM) is suggested as an intermediate layer between infrastructure and application layers for futuristic tactical mesh network. The tactical service mesh requires dynamic QoS monitoring and control for intelligent QoS coordination. However, legacy networking nodes used for existing tactical networks are difficult to support these functionality due to inflexible monitoring support. In order to resolve such matter, we propose a tactical mesh WAN node as a hardware/software co-designed networking node in this paper. The tactical mesh WAN node is conceptually designed to have multi-access networking interfaces and virtualized networking switches by leveraging the DANOS whitebox server/switch. In addition, we explain how to apply eBPF-based traffic monitoring to the tactical mesh WAN node and verify the traffic monitoring feasibility for supporting QoS coordination of tactical-mesh traffic.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.496-499
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• 2014

Xe Gas is moved to Target from GPM. It is Used to feasible nuclear reaction from proton of 30MeV Cyclotron being investigated by the Xe-124 Gas target System. This system is divided into four parts. Hardware was constructed by solidworks and Helium Supply is to cool the Havor Foil. Water has the job of cooling down the temperature when Xe Gas is being investigated in the target. Temperature and pressure gauges are attached to be checked easily. GPM(Gas Process Manifold) has the part that prepares to transport Xe Gas. There are Storage Vessel that stores Xe Gas, the cold trap that filters humidity and impurity and lastly storage vessel that temporarily stores Xe Gas. HCS(Helium Circulation System) using the Helium to cleaning and cooling. these parts are used to SIEMENS PLC and Pcvue Program. Because It is more comfortable and easy maintenance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.1-8
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• 2021

This study developed low-cost and high-efficiency pavement condition monitoring technology to produce the key information required for pavement management. A noise and artificial intelligence-based monitoring system was devised to compensate for the shortcomings of existing high-end equipment that relies on visual information and high-end sensors. From idea establishment to system development, functional definition, information flow, architecture design, and finally, on-site field evaluations were carried out. As a result, confidence in the high level of artificial intelligence evaluation was secured. In addition, hardware and software elements and well-organized guidelines on system utilization were developed. The on-site evaluation process confirmed that non-experts could easily and quickly investigate and visualized the data. The evaluation results could support the management works of road managers. Furthermore, it could improve the completeness of the technologies, such as prior discriminating techniques for external conditions that are not considered in AI learning, system simplification, and variable speed response techniques. This paper presents a new paradigm for pavement monitoring technology that has lasted since the 1960s.

• The Journal of Industrial Distribution & Business
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• v.12 no.6
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• pp.57-74
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• 2021

Purpose: Before COVID-19 pandemic, Chinese mid/low-priced hotel industry has been steadily growing in recent years, and internal and external competition has been intensifying. Under these circumstances, this study started with a strategic objective to increase the quality of service, thus enabling customer satisfaction and revisit intention. For enhancing the competitiveness of Chinese mid/low-priced hotel business, we plan to establish a model using SERVQUAL, O2O platform, and identify their relationship through empirical analyses. Research design, data and methodology: Through the consideration of the existing literature, this study intended to identify the characteristics of service quality in Chinese mid/low-priced hotels and to consider their impact on customer satisfaction and revisit intention. We also wanted to examine the moderating effect of the O2O platform between the characteristics of service quality and customer satisfaction. A survey was carried out on customers using mid/low-priced hotels in China and empirical analyses were conducted using regression analyses. Results: First, in the hypothesis of service qualities' effects on customer satisfaction were identified with significant positive effects. Second, in the hypothesis of service qualities' effects on revisit intention, "tangibles, reliability, and empathy" have shown significant positive. Third, in the verification of the moderating effect of the O2O platform, there were "positive partial moderating effects" between service qualities and customer satisfaction. Finally, the effect of customer satisfaction on revisit intention was positive significant. Conclusions: In order to satisfy their customers, improvements in service quality should be made first. In addition, customer satisfaction had a positive impact on revisit intention. In order to revitalize Chinese mid/low-priced hotels, differentiation strategy is also needed for specialized customers such as college students, and basically, efforts should be made to optimize the O2O platform. O2O platforms should establish optimal platform construction strategies based on the customer's perspective. After all, in the case of Chinese mid/low-priced hotels, it is necessary to strengthen the construction of the latest hardware infrastructure and O2O platform of software infrastructure, and to improve customers' advanced online and offline experiences. Finally, regarding the hypothesis that was rejected among service qualities' characteristics, we tried to discuss the reason and find the implications of these.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.1
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• pp.11-20
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• 2007

A fast Montgomery multiplication occupies important to the design of RSA cryptosystem. Montgomery multiplication consists of two addition, which calculates using CSA or RBA. In terms of CSA, the multiplier is implemented using 4-2 CSA o. 5-2 CSA. In terms of RBA, the multiplier is designed based on redundant binary system. In [1], A new redundant binary adder that performs the addition between two binary signed-digit numbers and apply to Montgomery multiplier was proposed. In this paper, we reconstruct the logic structure of the RBA in [1] for reducing time and space complexity. Especially, the proposed RB multiplier has no coupler like the RBA in [1]. And the proposed RB multiplier is suited to binary exponentiation as modified input and output forms. We simulate to the proposed NRBA using gates provided from SAMSUNG STD130 $0.18{\mu}m$ 1.8V CMOS Standard Cell Library. The result is smaller by 18.5%, 6.3% and faster by 25.24%, 14% than 4-2 CSA, existing RBA, respectively. And Especially, the result is smaller by 44.3% and faster by 2.8% than the RBA in [1].

• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1124-1128
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• 2021

As regulations of emissions from ships become more stringent, electric propulsion systems have been increasingly used to solve this problem in vessels ranging from large merchant ships to small and medium-sized ships. Methods for improving the efficiency of the electric propulsion system include the improvement of power sources; the use of a system linked to environmentally friendly power sources, such as batteries, fuel cells, and solar power; and the development of hardware and control methodology for rectifiers, power conversion devices, and propulsion motors. The method using a phase-shifting transformer with diodes has been widely used for rectification. Power semiconductor devices with grid connection to an environmentally friendly power source using DC distribution, a variable speed power source, and the application of small and medium-sized electric propulsion systems have been developed. Accordingly, the demand for active front-end (AFE) rectifiers is increasing. In this study, a method using a neural network rather than a conventional proportional-integral controller was proposed to control the AFE rectifier. Tested controller data were used to design a neural network controller trained through MATLAB/Simulink. The neural network controller was applied to a rectification system designed using PSIM software. The results indicated the effectiveness of improving the waveform and power factor DC output stage according to the load variation. The proposed system can be applied as a rectification system for small and medium-sized environmentally friendly ships.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.79-89
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• 2022

With the popularity and the advanced graphics hardware technology of mobile devices, various mobile applications that help children with physical activities have been studied. This paper presents SandUp, a mobile application that guides the play of building sand castles using artificial intelligence and augmented reality(AR) technology. In the process of building the sandcastle, children can interactively explore the target virtual sandcastle through the smartphone display using AR technology. In addition, to help children complete the sandcastle, SandUp informs the sand shape and task required step by step and provides visual and auditory feedback while recognizing progress in real-time using the phone's camera and deep learning classification. We prototyped our SandUp app using Flutter and TensorFlow Lite. To evaluate the usability and effectiveness of the proposed SandUp, we conducted a questionnaire survey on 50 adults and a user study on 20 children aged 4~7 years. The survey results showed that SandUp effectively helps build the sandcastle with proper interactive guidance. Based on the results from the user study on children and feedback from their parents, we also derived usability issues that can be further improved and suggested future research directions.

• Smart Structures and Systems
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• v.30 no.5
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• pp.521-535
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• 2022

Efficient management of deteriorating civil infrastructure is one of the most important research topics in many developed countries. In particular, the remote displacement measurement of bridges using linear variable differential transformers, global positioning systems, laser Doppler vibrometers, and computer vision technologies has been attempted extensively. This paper proposes a remote displacement measurement system using closed-circuit televisions (CCTVs) and a computer-vision-based method for in-situ bridge bearings having relatively large displacement due to temperature change in long term. The hardware of the system is composed of a reference target for displacement measurement, a CCTV to capture target images, a gateway to transmit images via a mobile network, and a central server to store and process transmitted images. The usage of CCTV capable of night vision capture and wireless data communication enable long-term 24-hour monitoring on wide range of bridge area. The computer vision algorithm to estimate displacement from the images involves image preprocessing for enhancing the circular features of the target, circular Hough transformation for detecting circles on the target in the whole field-of-view (FOV), and homography transformation for converting the movement of the target in the images into an actual expansion displacement. The simple target design and robust circle detection algorithm help to measure displacement using target images where the targets are far apart from each other. The proposed system is installed at the Tancheon Overpass located in Seoul, and field experiments are performed to evaluate the accuracy of circle detection and displacement measurements. The circle detection accuracy is evaluated using 28,542 images captured from 71 CCTVs installed at the testbed, and only 48 images (0.168%) fail to detect the circles on the target because of subpar imaging conditions. The accuracy of displacement measurement is evaluated using images captured for 17 days from three CCTVs; the average and root-mean-square errors are 0.10 and 0.131 mm, respectively, compared with a similar displacement measurement. The long-term operation of the system, as evaluated using 8-month data, shows high accuracy and stability of the proposed system.

• Journal of the Korean Geosynthetics Society
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• v.23 no.2
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• pp.43-52
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• 2024

Recent abnormal climate conditions have increased the risk of slope collapses, which frequently result in significant loss of life and property due to the absence of early prediction and warning dissemination. In this paper, we develop a slope condition analysis system using IoT sensors and AI-based camera to assess the condition of slopes. To develop the system, we conducted hardware and firmware design for measurement sensors considering the ground conditions of slopes, designed AI-based image analysis algorithms, and developed prediction and warning solutions and systems. We aimed to minimize errors in sensor data through the integration of IoT sensor data and AI camera image analysis, ultimately enhancing the reliability of the data. Additionally, we evaluated the accuracy (reliability) by applying it to actual slopes. As a result, sensor measurement errors were maintained within 0.1°, and the data transmission rate exceeded 95%. Moreover, the AI-based image analysis system demonstrated nighttime partial recognition rates of over 99%, indicating excellent performance even in low-light conditions. Through this research, it is anticipated that the analysis of slope conditions and smart maintenance management in various fields of Social Overhead Capital (SOC) facilities can be applied.