• Journal of Information Processing Systems
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• v.14 no.4
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• pp.989-1009
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• 2018

Rapid advances in science and technology with exponential development of smart mobile devices, workstations, supercomputers, smart gadgets and network servers has been witnessed over the past few years. The sudden increase in the Internet population and manifold growth in internet speeds has occasioned the generation of an enormous amount of data, now termed 'big data'. Given this scenario, storage of data on local servers or a personal computer is an issue, which can be resolved by utilizing cloud computing. At present, there are several cloud computing service providers available to resolve the big data issues. This paper establishes a framework that builds Hadoop clusters on the new single-board computer (SBC) Mobile Raspberry Pi. Moreover, these clusters offer facilities for storage as well as computing. Besides the fact that the regular data centers require large amounts of energy for operation, they also need cooling equipment and occupy prime real estate. However, this energy consumption scenario and the physical space constraints can be solved by employing a Mobile Raspberry Pi with Hadoop clusters that provides a cost-effective, low-power, high-speed solution along with micro-data center support for big data. Hadoop provides the required modules for the distributed processing of big data by deploying map-reduce programming approaches. In this work, the performance of SBC clusters and a single computer were compared. It can be observed from the experimental data that the SBC clusters exemplify superior performance to a single computer, by around 20%. Furthermore, the cluster processing speed for large volumes of data can be enhanced by escalating the number of SBC nodes. Data storage is accomplished by using a Hadoop Distributed File System (HDFS), which offers more flexibility and greater scalability than a single computer system.

• Journal of Internet of Things and Convergence
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• v.2 no.2
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• pp.21-26
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• 2016

In this paper, it is possible to update the tourist information in real time, on/off-line tour proposes a solution(BBTS) based on a bluetooth beacon can provide tourist information without the need for wireless data network. BBTS consists of a bluetooth based data of the low-power supply system and the beacons and interoperable smart applications. Data supply system consists of the BLE & Beacon Pairing-based / non-pairing data transmission module with integral hardware. Smart application modules that provide indoor location of users information, internal server module and tourist information collection and information guide around comprised of applications. The proposed BBTS is possible that indoor service tourism tourist demand due to utilizing the beacon technology. Outdoor tourist information is designed to be downloaded to the smartphone receives the information received from the beacon APK file to provide services. BBTS system is expected to make a big impact on the smart tourism services industry.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.439-459
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• 2010

Structural health monitoring (SHM) of civil infrastructure using wireless smart sensor networks (WSSNs) has received significant public attention in recent years. The benefits of WSSNs are that they are low-cost, easy to install, and provide effective data management via on-board computation. This paper reports on the deployment and evaluation of a state-of-the-art WSSN on the new Jindo Bridge, a cable-stayed bridge in South Korea with a 344-m main span and two 70-m side spans. The central components of the WSSN deployment are the Imote2 smart sensor platforms, a custom-designed multimetric sensor boards, base stations, and software provided by the Illinois Structural Health Monitoring Project (ISHMP) Services Toolsuite. In total, 70 sensor nodes and two base stations have been deployed to monitor the bridge using an autonomous SHM application with excessive wind and vibration triggering the system to initiate monitoring. Additionally, the performance of the system is evaluated in terms of hardware durability, software stability, power consumption and energy harvesting capabilities. The Jindo Bridge SHM system constitutes the largest deployment of wireless smart sensors for civil infrastructure monitoring to date. This deployment demonstrates the strong potential of WSSNs for monitoring of large scale civil infrastructure.

• Journal of Astronomy and Space Sciences
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• v.35 no.4
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• pp.253-261
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• 2018

Korea Astronomy and Space Science Institute (KASI) has been developing the space optical and laser tracking (SOLT) system for space geodesy, space situational awareness, and Korean space missions. The SOLT system comprises satellite laser ranging (SLR), adaptive optics (AO), and debris laser tracking (DLT) systems, which share numerous subsystems, such as an optical telescope and tracking mount. It is designed to be capable of laser ranging up to geosynchronous Earth orbit satellites with a laser retro-reflector array, space objects imaging brighter than magnitude 10, and laser tracking low Earth orbit space debris of uncooperative targets. For the realization of multiple functions in a novel configuration, the SOLT system employs a switching mirror that is installed inside the telescope pedestal and feeds the beam path to each system. The SLR and AO systems have already been established at the Geochang station, whereas the DLT system is currently under development and the AO system is being prepared for testing. In this study, the design and development of the SOLT system are addressed and the SLR data quality is evaluated compared to the International Laser Ranging Service (ILRS) tracking stations in terms of single-shot ranging precision. The analysis results indicate that the SLR system has a good ranging performance, to a few millimeters precision. Therefore, it is expected that the SLR system will not only play an important role as a member of the ILRS tracking network, but also contribute to future Korean space missions.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.15-22
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• 2019

Recent technological advances in three-dimensional (3D) sensing devices and machine learning such as deep leaning has enabled data-driven 3D applications. Research on artificial intelligence has developed for the past few years and 3D deep learning has been introduced. This is the result of the availability of high-quality big data, increases in computing power, and development of new algorithms; before the introduction of 3D deep leaning, the main targets for deep learning were one-dimensional (1D) audio files and two-dimensional (2D) images. The research field of deep leaning has extended from discriminative models such as classification/segmentation/reconstruction models to generative models such as those including style transfer and generation of non-existing data. Unlike 2D learning, it is not easy to acquire 3D learning data. Although low-cost 3D data acquisition sensors have become increasingly popular owing to advances in 3D vision technology, the generation/acquisition of 3D data is still very difficult. Even if 3D data can be acquired, post-processing remains a significant problem. Moreover, it is not easy to directly apply existing network models such as convolution networks owing to the various ways in which 3D data is represented. In this paper, we summarize technological trends in AI-based 3D content generation.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.8
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• pp.201-208
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• 2019

Intra-Body Communication (IBC) is a communication method using the human body as a communication medium. The fact that our human body consists of water and electrolyte allow such communication method could work and have strength in low-power. However, because the IBC directly affects to human body by using it as a medium, there was a lack of research in communication protocols of each communication layer. In this paper, we suggests MAC parameters which affects the performance of communication in human body channel, and propose new MAC protocol. Our results shows that our MAC is suitable for supporting high data rate applications with comparable radio duty cycle performance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.109-115
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• 2019

Most demand forecasting studies for telecommunication services have focused on estimating market size at the introductory stage of new products or services, or on suggesting improvement methods of forecasting models. Although such studies forecast business growth and market sizes through demand forecasting for new technologies and overall demands in markets, they have not suggested more specific information like relative market share, customers' preferences on technologies or service, and potential sales power. This study focuses on the telecommunication service industry and explores ways to calculate the relative market shares between competitors, considering competitive situations at the introductory stage of a new mobile telecommunication service provider. To reflect the competitive characteristics of the telecommunication markets, suggested is an extended conjoint analysis using service coverage and service switching rates as modification variables. This study is considered to be able to provide strategic implications to businesses offering existing service and ones planning to launch new services. The result of analysis shows that the new service provider has the greatest market share at the competitive situation where the new service covers the whole country, offers about 50% of existing service price, and allows all cellphones except a few while the existing service carrier maintains its price and service and has no response to the new service introduction. This means that the market share of the new service provider soars when it is highly competitive with fast network speed and low price.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.100-103
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• 2019

Due to the fourth industrial revolution called 'fusion and connection', interest in 'high connectivity society' and 'highland society' is increasing, and related objects are not limited to automation and connected cars. The Internet of Things is the main concern of the 4th Industrial Revolution and it is expected to play an important role in establishing the basis of the next generation mobile communication service. Several domestic and foreign companies have been studying various types of LPWANs for the construction of the Internet based on things, and there is Semtech's LoRaWAN technology as representative. LoRaWAN is a long-distance, low-power network designed to manage a large number of devices and sensors, with communications from hundreds to thousands to thousands of devices and sensors. In this paper, we analyze the optimum node capacity of gateway for maximum performance while reducing resource waste in using LoRaWAN.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1102-1108
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• 2020

Mobile edge computing is a technology that can prepare for a new era of cloud computing and compensate for shortcomings by processing data near the edge of the network where data is generated rather than centralized data processing. It is possible to realize a low-latency/high-speed computing service by locating computing power to the edge and analyzing data, rather than in a data center far from computing and processing data. In this article, we develop a virtual mobile edge computing testbed environment where the cloud and edge nodes divide computing tasks from mobile terminals using the EdgeCloudSim simulator. Performance of offloading techniques for distribution of computing tasks from mobile terminals between the central cloud and mobile edge computing nodes is evaluated and analyzed under the virtual mobile edge computing environment. By providing a virtual mobile edge computing environment and offloading capabilities, we intend to provide prior knowledge to industry engineers for building mobile edge computing nodes that collaborate with the cloud.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.397-404
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• 2022

Recently, in the industrial field, various studies are being conducted on converging IIoT devices that combine low-power processes and network cards into industrial sites to improve production efficiency and reduce costs. In this paper, we propose a processing model that can efficiently manage products produced by attaching IIoT sensor information to infrastructure built in industrial sites. The proposed model creates production data using IIoT data collection, preprocessing, characteristic generation, and labels to detect abnormally processed sensing information in real time by checking sensing information of products produced by IIoT at regular intervals. In particular, the proposed model can easily process IIoT data by performing tracking and monitoring so that product information produced in industrial sites can be processed in real time. In addition, since the proposed model is operated based on the existing production environment, the connection with the existing system is smooth.