• Journal of Korean Institute of Industrial Engineers
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• v.24 no.2
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• pp.241-249
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• 1998

In this paper, we seek to find an optimal allocation of link capacity in a data communication network. The architecture of the data communication network considered in the study is an online-service network based on public switched telephone network(PSTN) and packet switched data network(PSDN). In designing the architecture of the network, we need to deal with various measures of quality of service(QoS). Two important service measures are the call blocking probability in PSTN and the data transfer delay time in PSDN. Considering the tradeoff between the call blocking probability and the data transfer delay time in the network, we have developed the optimal link capacity allocation model that minimizes the total link cost, while guarantees the call blocking probability and the data transfer delay time within an acceptable level of QoS. This problem can be formulated as a non-linear integer programming model. We have solved the problem with tabu search and simulated annealing methods. In addition, we have analyzed the sensitivity of the model and provided the insight of the model along with computational results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3935-3949
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• 2021

With the rapid development of Internet and big data technology, various online social network platforms have been established, producing massive information every day. Hot topic discovery aims to dig out meaningful content that users commonly concern about from the massive information on the Internet. Most of the existing hot topic discovery methods focus on a single network data source, and can hardly grasp hot spots as a whole, nor meet the challenges of text sparsity and topic hotness evaluation in cross-network scenarios. This paper proposes a novel hot topic discovery method across social network based on an im-proved LDA model, which first integrates the text information from multiple social network platforms into a unified data set, then obtains the potential topic distribution in the text through the improved LDA model. Finally, it adopts a heat evaluation method based on the word frequency of topic label words to take the latent topic with the highest heat value as a hot topic. This paper obtains data from the online social networks and constructs a cross-network topic discovery data set. The experimental results demonstrate the superiority of the proposed method compared to baseline methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.12
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• pp.1179-1185
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• 2013

Trend of next generation satellite communication network is distribution and enlargement of network structure with increased network terminals, and traffic which use satellite communication is increasing and frequently occurring. Under specific satellite communication environment that various communication device dynamically forms a network domain and frequently exchanges the data, data-centric publish/subscribe data exchange is more suitable than server/client data exchange. So, this paper analyze DDS performance for application of DDS standard to distribution network management system which aims to efficiently manage limited satellite resource, and also this paper covers comparative study on DDS and SNMP(server/client data exchange). Study compares DDS and SNMP using OPNET, and result of study is analyzed from a network layer performance perspective.

• Journal of Broadcast Engineering
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• v.9 no.2
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• pp.119-130
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• 2004

We have developed a prototype super-high-definition (SHD) digital cinema distribution system that can store, transmit, and display eight-million-pixel motion pictures that have the image quality of a 35-mm film movie. The system contains a movie server, a real-time decoder, and an SHB projector. Using a Gigabit Ethernet link and TCP/IP, the server transmits JPEG2000 compressed motion picture data streams to the decoder at transmission speeds as high as 300 Mbps. The received data streams are decompressed by the decoder, and then projected onto a screen via the projector. By using an enlarged TCP window, multiple TCP streams, and a shaping function to control the data transmission quantity, we achieved real-time streaming of SHD movie data at about 300 Mbps between Chicago and Los Angeles, a distance of more than 3000 km. We also improved the decoder performance to show movies with Image qualities of 450 Mbps or higher. Since UDP is more suitable than TCP for fast long-distance streaming, we have developed an SHD digital cinema UDP relay system, in which UDP is used for transmission over a fast long-distance network. By using four pairs of server-side-proxy and decoder-side-proxy, 450-Mbps movie data streams could be transmitted.

• Journal of the Korea Society of Computer and Information
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• v.23 no.12
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• pp.49-55
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• 2018

In this paper, we propose schemes of blockchain utilization in tactical communication environment. The military tactical communication environment has similar characteristics with blockchain network such as distributed architecture, decentralization, and the need for data integrity. A communication node constituting a tactical communication network is constituted by a system capable of configuring and connecting a network for each node. When a communication node, having such capabilities, is configured as a node of blockchain network, various functions could be performed. In this paper, we propose utilization schemes of authentication, integrity, record management, and privilege control based blockchain technology. Functions for authentication, integrity verification, and record management need to ensure the stored data and could track history. The requirement of function's characteristics are matched to blockchain which is storing data sequentially and difficult to hack data, so that it could perform functionally and sufficiently well. Functions for authority control should be able to assign different privileges according to the state of the requestor. Smart contract will function when certain conditions are satisfied and it will be able to perform its functions by using it. In this paper, we will look over functions and utilization schemes of blockchain technology which could reliably share and synchronize data in a tactical communication environment composed of distributed network environment.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.882-890
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• 2001

The data link layer of Foundation Fieldbus is operated on the basis of scheduling and token-passing disciplines. This paper presents a network design method of Foundation Fieldbus using a bandwidth allocation scheme. Fieldbus traffic consists of periodic data and sporadically generated time-critical and time-available data. The bandwidth allocation scheme schedules the transmission of periodic data. Time-critical and time-available data are transmitted via a token-passing service. The validity of this bandwidth allocation scheme is determined using an experimental model of a network system. The results obtained from the experimental model show that the proposed scheme restricts the delay of both periodic and time-critical data to a pre-specified bound. The proposed bandwidth allocation scheme also fully utilizes the bandwidth resource of the network system.

• Atmosphere
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• v.20 no.2
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• pp.153-160
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• 2010

In this paper, an attempt has been made to build and test self-configuring weather sensor networks and internet based observation system to gather atmospheric data. The aim is to provide integrated or real-time weather information in standard form using network data access protocol. This system was successfully developed to record weather information both digital as well as visual using sensor network and web-enabled surveillance cameras. These data were transformed by network based data access protocol to access and utilize for public domain. The competed system has been successfully utilized to monitor different types of weather. The results show that this is one of the most useful weather monitoring system.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.1
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• pp.28-36
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• 2007

Sensor networks are usually composed of tens or thousands of tiny devices with limited resources. Because of their limited resources, many researchers have studied on the energy management in the WSNs(Wireless Sensor Networks), especially taking into account communications efficiency. For effective data transmission and sensor fault detection in sensor network environment, a new remote monitoring system based on PCA(Principle Component Analysis) and AANN(Auto Associative Neural Network) is proposed. PCA and AANN have emerged as a useful tool for data compression and identification of abnormal data. Proposed system can be effectively applied to sensor network working in LEA2C(Low Energy Adaptive Connectionist Clustering) routing algorithms. To verify its applicability, some simulation studies on the data obtained from real WSNs are executed.

• Journal of Ocean Engineering and Technology
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• v.12 no.2 s.28
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• pp.139-146
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• 1998

This paper introduces a network system for monitoring coastal oceanographic data. The network system consists of three parts such as the buoy to observe oceanographic data, the local site to collect data transferred from buoys, and the host site to construct the oceanographic data-base and to share the information for monitoring coastal oceanographic data. The buoy has a one-board microcomputer to manage and to acquire coastal environment data in real-time. A wireless and wire communication technique is employed in order to transfer data measured by buoys and to link local and host sites, respectively. In measuring coastal environment data, this system shows more cost-effective way than the presents conventional. In addition, the realtime monitoring system continuously from various sites with the network systems.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.631-634
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• 2004

In this paper, the Bayesian recurrent neural network (BRNN) is proposed to predict time series data. Among the various traditional prediction methodologies, a neural network method is considered to be more effective in case of non-linear and non-stationary time series data. A neural network predictor requests proper learning strategy to adjust the network weights, and one need to prepare for non-linear and non-stationary evolution of network weights. The Bayesian neural network in this paper estimates not the single set of weights but the probability distributions of weights. In other words, we sets the weight vector as a state vector of state space method, and estimates its probability distributions in accordance with the Bayesian inference. This approach makes it possible to obtain more exact estimation of the weights. Moreover, in the aspect of network architecture, it is known that the recurrent feedback structure is superior to the feedforward structure for the problem of time series prediction. Therefore, the recurrent network with Bayesian inference, what we call BRNN, is expected to show higher performance than the normal neural network. To verify the performance of the proposed method, the time series data are numerically generated and a neural network predictor is applied on it. As a result, BRNN is proved to show better prediction result than common feedforward Bayesian neural network.