• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.79-80
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• 2023

CPU 와 GPU 의 성능이 지속적으로 발전함에 따라 객체 인식 인공지능의 정확도와 추론 속도는 점차 향상되고 있으나 이러한 성능을 Edge Device 와 같은 제한된 환경에서 구현하기에 아직 여러 한계점이 존재한다. 본 논문에서는 여러가지 Edge Device 에서 객체 인식을 위한 경량화 된 모델 중 하나인 SSD-Mobilenet-V2 를 활용하여 결과값을 통해 각 Device 간 경향성을 분석하였다. 본 결과를 바탕으로 다양한 환경에서의 객체인식 인공지능 모델의 성능 개선을 위한 연구에 활용할 수 있다.

• Journal of Sensor Science and Technology
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• v.31 no.2
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• pp.71-78
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• 2022

Wearable devices have the potential to revolutionize future medical diagnostics and personal healthcare. The integration of biosensors into scalable form factors allow continuous and noninvasive monitoring of key biomarkers and various physiological indicators. However, conventional wearable devices have critical limitations owing to their rigid and obtrusive interfaces. Recent developments in functional biocompatible materials, micro/nanofabrication methods, multimodal sensor mechanisms, and device integration technologies have provided the foundation for novel skin-interfaced bioelectronics for advanced and user-friendly wearable devices. Nonetheless, it is a great challenge to satisfy a wide range of design parameters in fabricating an authentic skin-interfaced device while maintaining its edge over conventional devices. This review highlights recent advances in skin-compatible materials, biosensor performance, and energy-harvesting methods that shed light on the future of wearable devices for digital health and personalized medicine.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.305-316
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• 2022

With the flood of digital data owing to the Internet of Things and big data, cloud service providers that process and store vast amount of data from multiple users can apply duplicate data elimination technique for efficient data management. The user experience can be improved as the notion of edge computing paradigm is introduced as an extension of the cloud computing to improve problems such as network congestion to a central cloud server and reduced computational efficiency. However, the addition of a new edge device that is not entirely reliable in the edge computing may cause increase in the computational complexity for additional cryptographic operations to preserve data privacy in duplicate identification and elimination process. In this paper, we propose an efficiency-improved duplicate data elimination protocol while preserving data privacy with an optimized user-edge-cloud communication framework by utilizing a trusted execution environment. Direct sharing of secret information between the user and the central cloud server can minimize the computational complexity in edge devices and enables the use of efficient encryption algorithms at the side of cloud service providers. Users also improve the user experience by offloading data to edge devices, enabling duplicate elimination and independent activity. Through experiments, efficiency of the proposed scheme has been analyzed such as up to 78x improvements in computation during data outsourcing process compared to the previous study which does not exploit trusted execution environment in edge computing architecture.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1258-1269
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• 2020

The IoT(Internet of Things) service provides users with valuable services by collecting and analyzing data using Internet-connected IoT devices. Currently, IoT service platforms are accomplished by using edge computing to reduce the delay time required to collect data from IoT devices. However, if a user moves to another network with IoT device, the connection will be lost and IoT service will be suspended. To solve this problem, we proposes a service that automatically roaming IoT service when IoT device makes move. IoT roaming service provides a device automatic tracking management technique designed to continue receiving IoT services even if users move to other networks. To check if the proposed roaming service was effective, we implemented IoT roaming service and measured the data transfer time while move between networks along with devices while using IoT service. As a result, the average data transfer time was 124.62ms, and the average service interrupt time was 812.12ms. with this result, we can assume that the user could feel service interruption time very shortly and it will not affect the service experience. with IoT roaming service, we expect that it will present a method that stably providing IoT services even if user moves networks.

• Smart Structures and Systems
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• v.29 no.1
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• pp.141-151
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• 2022

In recent years, the industry and research communities have focused on developing autonomous crack inspection approaches, which mainly include image acquisition and crack detection. In these approaches, mobile devices such as cameras, drones or smartphones are utilized as sensing platforms to acquire structural images, and the deep learning (DL)-based methods are being developed as important crack detection approaches. However, the process of image acquisition and collection is time-consuming, which delays the inspection. Also, the present mobile devices such as smartphones can be not only a sensing platform but also a computing platform that can be embedded with deep neural networks (DNNs) to conduct on-site crack detection. Due to the limited computing resources of mobile devices, the size of the DNNs should be reduced to improve the computational efficiency. In this study, an architecture called pruned crack recognition network (PCR-Net) was developed for the detection of structural cracks. A dataset containing 11000 images was established based on the raw images from bridge inspections. A pruning method was introduced to reduce the size of the base architecture for the optimization of the model size. Comparative studies were conducted with image processing techniques (IPTs) and other DNNs for the evaluation of the performance of the proposed PCR-Net. Furthermore, a modularly designed framework that integrated the PCR-Net was developed to realize a DL-based crack detection application for smartphones. Finally, on-site crack detection experiments were carried out to validate the performance of the developed system of smartphone-based detection of structural cracks.

• Journal of the Society of Naval Architects of Korea
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• v.47 no.4
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• pp.533-542
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• 2010

For a long times it has been believed that the Magnus effect of the rotating cylinder could be utilized for the lifting devices applicable to marine practices. It has been reported that the rotating cylinder installed on upper deck of commercial vessel could play a energy saving role however the idea might be applicable in a very rare case in ship building practices. In this study special high lift rudder system equipped with the trailing edge rotor has been suggested in correspondence with the increasing requirement of greater rudder force. Through the numerical simulation it is cleared that the trailing edge rotor could play a role in enhancement of circulation and refinement of boundary layer of the rudder system. At the same time it is found out that the lift force of the rudder system without rotation of trailing edge rotor could be doubled when the circumferential velocity of the trailing edge rotor is equal to twice of the inflow velocity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4849-4864
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• 2019

Modern applications such as augmented reality, connected vehicles, video streaming and gaming have stringent requirements on latency, bandwidth and computation resources. The explosion in data generation by mobile devices has further exacerbated the situation. Mobile Edge Computing (MEC) is a recent addition to the edge computing paradigm that amalgamates the cloud computing capabilities with cellular communications. The concept of MEC is to relocate the cloud capabilities to the edge of the network for yielding ultra-low latency, high computation, high bandwidth, low burden on the core network, enhanced quality of experience (QoE), and efficient resource utilization. In this paper, we provide a comprehensive overview on different traits of MEC including its use cases, architecture, computation offloading, security, economic aspects, research challenges, and potential future directions.

• The Journal of Bigdata
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• v.6 no.1
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• pp.115-125
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• 2021

Due to various ICT Technology innovations and Digital Transformation, the Internet of Things(IoT) environment is increasingly requiring intelligence, decentralization, and automated service, especially an advanced and stable smart service environment in the Industrial Internet of Things(IIoT) where communication network(5G), data analysis and artificial intelligence(AI), and digital twin technology are combined. In this study, we propose IIoT Edge middleware systems for flexible interface with heterogeneous devices such as facilities and sensors at various industrial sites and for quick and stable data collection and processing.

• Design & Manufacturing
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• v.14 no.4
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• pp.25-39
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• 2020

In this study, an edge device that monitors the injection molding process by measuring the mold vibration(acceleration) signal and the mold surface temperature was developed and evaluated its performance. During injection molding, signals of the injection start, V/P switchover, and packing end sections were obtained through the measurement of the mold vibration and the injection time and packing time were calculated by using the difference between the times of the sections. Then, the mold closed and mold open signals were obtained using a magnetic hall sensor, and cycle time was calculated by using the time difference between the mold closed time each process. As a result of evaluating the performance by comparing the process data monitored by the edge device with the shot data recorded on the injection molding machine, the cycle time, injection time, and packing time showed very small error of 0.70±0.38%, 1.40±1.17%, and 0.69±0.82%, respectively, and the values close to the actual were monitored and the accuracy and reliability of the edge device were confirmed. In addition, it was confirmed that the mold surface temperature measured by the edge device was similar to the actual mold surface temperature.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.9 no.1
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• pp.1-9
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• 2015

This paper reviews trends of the rehabilitation welfare devices on the basis of products and markets. Latest assistive devices tend to have a fold function. Auxiliary power assist module has been added. The completion of products has been improved. The folding function has strong relationship with portability. Specifically, various mobility devices, including foldable devices, are associated with enhanced portability. Powered auxiliary wheels and upper extremity supporting modules have entered the market. The leading-edge technology like Segway's control technology applies to two-wheel wheelchairs. The brand- new technology, lower extremity robotic exoskeleton, applies to markets. Standing wheelchairs, ramps, stair climbing assistive devices becomes more common. In addition, a combination of a variety of smart devices is being promoted to the classical assistive devices' part. Rehabilitation welfare devices can be more valuable due to nice industrial design, improved materials, and processing technology.