• Journal of Energy Engineering
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• v.8 no.4
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• pp.592-604
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• 1999

The steady state and dynamic characteristics of large cell area MCFC stacks were analyzed to solve the problems such as temperature difference generated in stacks and pressure difference between anode and cathode. Manipulated variables (current density, duel utilization rate, oxidant utilization rate) and controlled variables (temperature difference, anode and cathode pressure difference) which had an important effect on the MCFC stack performance were determined using operation results of two types of MCFC stacks (5kW (3,000 $\textrm{cm}^2$, 20 ea). 3kW (6,000 $\textrm{cm}^2$, 5ea)). The stability and transfer function representing system dynamics were obtained by steady state gain rate which showed the relative change between MVs and CVs. The transfer function was a 3$\times$3 matrix and a typical first order system without time delay. The optimal operating condition of large cell area MCFC stacks could be determined by analyzing dynamic characteristics. In case of a 5 kW MCFC stack, pressurized operation with recycle flow should be used to control the outlet temperature less than 68$0^{\circ}C$ and to control the MCFC system effectively. MIMO control or decoupler should be used to remove the interaction between MVs and CVs. This result will be used as important data in determining the control structure design and operation mode of large cell area MCFC systems in the future.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.7
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• pp.813-826
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• 1999

실시간 멀티미디어 응용의 등장으로 멀티캐스트와 QoS(Quality of Service) 지원이 필수적인 망 서비스로 부각되고 있다. 이에, ATM 기반의 인터넷에서 IP 멀티캐스트의 효율적인 처리를 위하여 MARS(Multicast Address Resolution Server)가 제안되었고, 기존의 최선 서비스 기반의 인터넷에서 QoS(Quality of Service)를 지원하기 위하여 RSVP(Resource Reservation Protocol)가 제안되었다. 본 논문에서는 ATM 망에서 QoS가 지원되는 IP 멀티캐스트 서비스를 제공하기 위하여 MARS 구조에서 RSVP를 지원하는 두 가지 방안을 제안하고, 시뮬레이션을 통하여 그 성능을 분석하였다. 제안하는 두 가지 방법은 각각 'RSVP 전 홉 노드 방식'과 'MARS 서버 방식'이라 명명하였다. RSVP 전 홉 노드 방식은 송신원으로부터 ATM 망으로 진입하는 노드와 수신원을 향하여 ATM 망을 진출하는 노드 간에 각각 일대일 양방향 VC를 설정하여 멀티캐스트 그룹에 속하는 수신원들이 보내는 자원 예약 메시지를 ATM 망에서 전송하는 방안이다. MARS 서버 방식은 ATM 망을 진출하는 노드와 MARS 서버간에 MARS 제어 메시지 교환을 위해 존재하는 ATM VC를 사용하여 RSVP의 자원 예약 메시지를 전송하고, MARS 서버가 RSVP 자원 예약 메시지를 처리하도록 그 기능을 확장함으로써 ATM 망에서 필요로 하는 제어 VC 수를 절약할 수 있는 방안이다. 시뮬레이션을 통하여, MARS 서버 방식은 ATM 제어 VC의 수를 절약할 수 있을 뿐 아니라 경우에 따라 RSVP 자원 예약 메시지 전달 지연을 줄일 수도 있음을 볼 수 있었다. 그러나, MARS 클러스터 내에 동시에 존재하는 RSVP 흐름이 많을 때에는 MARS 서버 방식의 경우 MARS 서버에서의 병목 현상으로 인해 성능이 저하될 수 있다.Abstract Emerging real time multimedia applications require multicast service with a QoS(Quality of Service) support. An overlay service architecture MARS(Multicast Address Resolution Server) is proposed to support IP multicast over an ATM network, and a resource reservation protocol RSVP is proposed to provide QoS support in the Internet which is originally based upon best effort service only. In this paper, we propose two schemes to support IP multicast service with QoS support over ATM networks: 'RSVP Previous Hop Node(RPHN) scheme' and 'MARS server based scheme'. In RPHN scheme, the RSVP reservation messages are transported via one-to-one ATM control VC from the egress nodes to the ingress nodes of the the multicast flow set up between each pair of nodes. The RSVP message processing occurs at the ingress nodes of the multicast flow. Whereas, in the MARS server based scheme, the RSVP reservation messages are transported via the MARS control VCs between the egress nodes and the MARS server. The RSVP message processing burden is imposed at MARS server in this scheme. For MARS server based scheme, no additional ATM VC is required for RSVP reservation message transmission, while the processing burden at the MARS server is high. Simulation results show that the MARS server based scheme, may accomplish RSVP reservation message delivery with smaller delay as well as saving of the number of ATM VCs. When the number of simultaneous RSVP flows in the MARS cluster is large, however, MARS based scheme may suffer performance degradation since MARS server becomes a performance bottleneck.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.1-1
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• 2016

Many of the world's large ecosystems are severely stressed due to population growth, water quality and quantity problems, vulnerability to flood and drought, and the loss of native species and cultural resources. Consequences of climate change further increase uncertainties about the future. These major societal challenges must be addressed through innovations in governance, policy, and ways of implementing management strategies. Science and engineering play a critical role in helping define possible alternative futures that could be achieved and the possible consequences to economic development, quality of life, and sustainability of ecosystem services. Science has advanced rapidly during the past decade with the emergence of science communities coalescing around 'Grand Challenges' and the maturation of how these communities function has resulted in large interdisciplinary research networks. An example is the River Experiment Center of KICT that engages researchers from throughout Korea and the world. This trend has been complemented by major advances in sensor technologies and data synthesis to accelerate knowledge discovery. These factors combine to allow scientific debate to occur in a more open and transparent manner. The availability of information and improved communication of scientific and engineering issues is raising the level of dialogue at the science-policy interface. However, severe challenges persist since scientific discovery does not occur on the same timeframe as management actions, policy decisions or at the pace sometimes expected by elected officials. Common challenges include the need to make decisions in the face of considerable uncertainty, ensuring research results are actionable and preventing science being used by special interests to delay or obsfucate decisions. These challenges are explored in the context of examples from the United States, including the California Bay-Delta system. California transfers water from the wetter northern part of the state to the drier southern part of the state through the Central Valley Project since 1940 and this was supplemented by the State Water Project in 1973. The scale of these activities is remarkable: approximately two thirds of the population of Californians rely on water from the Delta, these waters also irrigate up to 45% of the fruits & vegetables produced in the US, and about 80% of California's commercial fishery species live in or migrate through the Bay-Delta. This Delta region is a global hotspot for biodiversity that provides habitat for over 700 species, but is also a hotspot for the loss of biodiversity with more than 25 species currently listed by the Endangered Species Act. Understanding the decline of the fragile ecosystem of the Bay-Delta system and the potential consequences to economic growth if water transfers are reduced for the environment, the California State Legislature passed landmark legislation in 2009 (CA Water Code SS 85054) that established "Coequal goals of providing a more reliable water supply for California and protecting, restoring, and enhancing the Delta ecosystem". The legislation also stated that "The coequal goals shall be achieved in a manner that protects and enhances the unique cultural, recreational, natural resource, and agricultural values of the Delta as an evolving place." The challenges of integrating policy, management and scientific research will be described through this and other international examples.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.43-51
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• 2017

Background/Objectives : The purpose of this study is to propose a multi-threaded web crawl using queues that can solve the problem of time delay of single processing method, cost increase of parallel processing method, and waste of manpower by utilizing multiple bots connected by wide area network Design and implement. Methods/Statistical analysis : This study designs and analyzes applications that run on independent systems based on multi-threaded system configuration using queues. Findings : We propose a multi-threaded web crawler design using queues. In addition, the throughput of web documents can be analyzed by dividing by client and thread according to the formula, and the efficiency and the number of optimal clients can be confirmed by checking efficiency of each thread. The proposed system is based on distributed processing. Clients in each independent environment provide fast and reliable web documents using queues and threads. Application/Improvements : There is a need for a system that quickly and efficiently navigates and collects various web sites by applying queues and multiple threads to a general purpose web crawler, rather than a web crawler design that targets a particular site.

• Journal of the Korean Society for Railway
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• v.19 no.4
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• pp.456-467
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• 2016

Wireless Access in Vehicular Environments (WAVE) communication technology, which provides vehicleto-vehicle and vehicle-to-infrastructure communication and offers safe and convenient service, has been developed for application to an Intelligent Transport System (ITS). This paper provides field test results on a study of the feasibility of WAVE technology application to railway communication systems. A test railway communication system based on WAVE technology has been built along the Daebul line and a newly developed EMU. Field tests have been carried out according to the communication function requirements for LTE - R. The test results show that the railway communication system based on WAVE technology meets the functional requirements: maximum transmission length is 730m, maximum transfer delay is 5.69ms, and maximum interruption time is 1.36s; other tests including throughput test, video data transmission test, VoIP data test, and channel switching test also produced results that meets the functional requirements. These results suggest that WAVE technology can be applied to the railway communication system, enabling Vehicle-to-Wayside communication.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.63-71
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• 2020

In this paper, we propose a fire detection technology using YOLOv3 and EfficientDet, the most reliable artificial intelligence detection algorithm recently, an alert service that simultaneously transmits four kinds of notifications: text, web, app and e-mail, and an AWS system that links fire detection and notification service. There are two types of our highly accurate fire detection algorithms; the fire detection model based on YOLOv3, which operates locally, used more than 2000 fire data and learned through data augmentation, and the EfficientDet, which operates in the cloud, has conducted transfer learning on the pretrained model. Four types of notification services were established using AWS service and FCM service; in the case of the web, app, and mail, notifications were received immediately after notification transmission, and in the case of the text messaging system through the base station, the delay time was fast enough within one second. We proved the accuracy of our fire detection technology through fire detection experiments using the fire video, and we also measured the time of fire detection and notification service to check detecting time and notification time. Our AI fire detection and notification service system in this paper is expected to be more accurate and faster than past fire detection systems, which will greatly help secure golden time in the event of fire accidents.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• Journal of the Korean earth science society
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• v.42 no.1
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• pp.76-87
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• 2021

In this study, temporal trend of researches in earthquake with groundwater level, water quality, radon, remote sensing, electrical resistivity, gravity, and geomagnetism was searched from 2001 to 2020, using the journals indexed in Web of Science, and the number of articles published in international journals was counted in relation to the occurrences of earthquakes (≥Mw 5.0, ≥Mw 6.0, ≥Mw 7.0, ≥Mw 8.0, and ≥Mw 9.0). The number of articles shows an increasing trend over the studied period. This is explained by that studies on earthquake precursor and seismic monitoring becomes active in various fields with integrated data analysis through the development of remote sensing technology, progress of measurement equipment, and big data. According to Mann-Kendall and Sen's tests, gravity-related articles exhibit an increasing trend of 1.30 articles/yr, radon-related articles (0.60 articles/yr), groundwater-related articles (0.70 articles/yr), electrical resistivity-related articles (0.25 articles/yr), and remote-sensing-related articles (0.67 articles/yr). By cross-correlation analysis of the number of articles in each field with removing trend effect and the number of earthquakes of ≥Mw 5.0, ≥Mw 6.0, ≥Mw 7.0, ≥Mw 8.0, and ≥Mw 9.0, radon and remote sensing fields exhibit a high cross-correlation with a delay time of one year. In addition, large-scale earthquakes such as the 2004 and 2005 Sumatra earthquake, the 2008 Sichuan earthquake, the 2010 Haiti earthquake, and the 2010 Chile earthquake are estimated to be related with the increase in the number of articles in the corresponding periods.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.1-7
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• 2022

Recently, as the use of applications such as big data programs and machine learning programs that are driven while generating large amounts of data in the program itself becomes common, the existing main memory alone lacks memory, making it difficult to execute the program quickly. In particular, the need to derive results more quickly has emerged in a situation where it is necessary to analyze whether the entire sequence is genetically altered due to the outbreak of the coronavirus. As a result of measuring performance by applying large-capacity data to a computing system equipped with a self-developed memory pool MOCA host adapter instead of processing large-capacity data from an existing SSD, performance improved by 16% compared to the existing SSD system. In addition, in various other benchmark tests, IO performance was 92.8%, 80.6%, and 32.8% faster than SSD in computing systems equipped with memory pool MOCA host adapters such as SortSampleBam, ApplyBQSR, and GatherBamFiles by task of workflow. When analyzing large amounts of data, such as electrical dielectric pipeline analysis, it is judged that the measurement delay occurring at runtime can be reduced in the computing system equipped with the memory pool MOCA host adapter developed in this research.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.1-10
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• 2022

Defense fields widely operate unmanned systems to lower vulnerability and enhance combat effectiveness. In the navy, swarm unmanned surface vehicles(USVs) form a cluster within communication range, share situational awareness information among the USVs, and cooperate with them to conduct military missions. This paper proposes an interface system, i.e., Interface Adapter System(IAS), to achieve inter-USV and intra-USV interoperability. We focus on the mission planning subsystem(MPS) for interoperability, which is the core subsystem of the USV to decide courses of action such as automatic path generation and weapon assignments. The central role of the proposed system is to exchange interface data between MPSs and other subsystems in real-time. To this end, we analyzed the operational requirements of the MPS and identified interface messages. Then we developed the IAS using the distributed real-time middleware. As experiments, we conducted several integration tests at swarm USVs simulation environment and measured delay time and loss ratio of interface messages. We expect that the proposed IAS successfully provides bridge roles between the mission planning system and other subsystems.