• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.4
• /
• pp.139-147
• /
• 2009

In this paper, optimum design of energy-aware distributed detection is considered for a parallel sensor network system consisting of a fusion center and two passive sonar nodes. AND rule and OR rule are employed as the fusion rules of the sensor network. For the fusion rules, it is shown that a threshold rule of each sensor node has uniformly most powerful properties. Optimum threshold for each sensor is investigated that maximizes the probability of detection under a constraint on energy consumption due to false alarms. It is also investigated through numerical experiments how signal strength, an energy constraint, and the distance between two sensor nodes affect the system detection performances.

• Management & Information Systems Review
• /
• v.31 no.3
• /
• pp.141-160
• /
• 2012

This study investigate the relationship between embeddedness of supply chain on supply chain performance. The development of research model is based on network embeddedness that the literature of strategic management and sociology. To examine the research model and hypotheses, we have used an empirical method based on field survey in which most of measurements used and verified in previous studies are selected as measurements. The data from survey was analyzed using Partial Least Squares(PLS). The result from empirical model suggest as follow; First, relational embeddedness of supply chain effects on supply chain performance. Especially, reciprocal dependance affects interfirm relation performance. Also trust and tie strength of relational embeddedness affects interfirm relation performance. Second, interfirm relation performance affects financial performance.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.46 no.5
• /
• pp.37-43
• /
• 2009

Streaming video service over wireless and mobile communication networks has received significant interests from both academia and industry recently. Specifically, mobile WiMAX (IEEE 802.16e) is capable of providing high data rate and flexible Quality of Service (QoS) mechanisms, supporting mobile streaming very attractive. However, we need to note that streaming videos can be partially deteriorated in their macroblocks and/or slices owing to errors on OFDMA subcarriers, as we consider that compressed video sequence is generally sensitive to the error-prone channel status of the wireless and mobile network. In this paper, we introduce an OFDMA subcarrier-adaptive mobile streaming server based on cross-layer design. This streaming server system is substantially efficient to reduce the deterioration of streaming video transferred on the subcarriers of low power strength without any modifications of the existing schedulers, packet ordering/reassembly, and subcarrier allocation strategies in the base station.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.11
• /
• pp.1011-1022
• /
• 2014

Currently, the wireless network environment of air node is constructed mainly of ground relay station. However, as the Korean Peninsula is composed of 70% mountainous region, there are multiple shadow zones. This is calling for effective measures to prevent aircraft from losing communication link during low-mid altitude missions. In this article we propose the utilization of Bezier Curve for estimation of aircraft flight path and control method for entering shadow zone. This method successfully estimated aircraft track, and analyzed the existence, disseminated the warning, and took measures to avoid the shadow zone before entering. This article, suggested after simulated experiments, proves that the method enables seamless communication during air operations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.508-511
• /
• 2005

In the near future various new services will be created by using ubiquitous computing and ubiquitous network. Especially u-LBS(Ubiquitous Location Based Services) is recognized as one of the most important services. U-LBS is based on the data created by recognizing objects including both human and matters at any time and anywhere. Many researches related with object locating method by using RF are in the process of studying However there are few researches on the location of objects. In this paper we propose the recognition method of the location of objects by using RF and USN technology. In detail, the strength of RF signal is used to recognize the location of objects. Also we discuss about the future work to enhance the recognition rate of location by using a number of conditions including the weather, temperature etc. And Genetic Algorithm is used to get the optimal parameters with which we can get the more exact recognition rate of location.

• Journal of KIISE:Information Networking
• /
• v.30 no.6
• /
• pp.755-763
• /
• 2003

To improve performance over noisy wireless channels, mobile wireless networks employ forward error correction(FEC) techniques. The performance of static FEC algorithms, however, degrades by poorly matching the overhead of their correction code to the degree of the fluctuating underlying channel error. This paper proposes an adaptive FEC technique called FECA(FEC-level Adaptation), which dynamically tunes FEC strength to the currently estimated channel error rate at the data link layer. FECA is suitable for wireless networks whose error rate is high and slowly changing compared to the round-trip time between two communicating nodes. One such example network would be a sensor network in which the average bit error rate is higher than $10^{-6}$ and the detected error rate at one time lasts a few hundred milliseconds on average. Our experiments show that FECA performs 15% in simulations with theoretically modeled wireless channels and in trace-driven simulations based on the data collected from real sensor networks better than any other static FEC algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.9
• /
• pp.1665-1671
• /
• 2007

Mobile Ad hoc Networks (MANETs) refer to autonomous networks in which wireless data communications are established between multiple nodes in a given coverage area without a base station or centralized administration. Because of node mobility and limited battery life, the network topology may changes frequently. Selecting the most reliable path during route discovery process is important to improve performance in ad-hoc networks. In this study, we proposed an enhanced routing protocol based on AODV by monitoring variation of receiving signal strength. New metric function that consists of node mobility and hops of path is used for routing decision. From extensive experiments by using NS-2, The performance of the proposed routing scheme has been imp개ved by comparison to AODV protocol.

• Steel and Composite Structures
• /
• v.33 no.3
• /
• pp.319-332
• /
• 2019

This study is aimed to predict the behaviour of channel shear connectors in composite floor systems at different temperatures. For this purpose, a soft computing approach is adopted. Two novel intelligence methods, including an Extreme Learning Machine (ELM) and a Genetic Programming (GP), are developed. In order to generate the required data for the intelligence methods, several push-out tests were conducted on various channel connectors at different temperatures. The dimension of the channel connectors, temperature, and slip are considered as the inputs of the models, and the strength of the connector is predicted as the output. Next, the performance of the ELM and GP is evaluated by developing an Artificial Neural Network (ANN). Finally, the performance of the ELM, GP, and ANN is compared with each other. Results show that ELM is capable of achieving superior performance indices in comparison with GP and ANN in the case of load prediction. Also, it is found that ELM is not only a very fast algorithm but also a more reliable model.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.1
• /
• pp.27-35
• /
• 2021

This paper proposes a method to mitigate the Catastrophic Forgetting phenomenon in which artificial neural networks forget information on previous data. This method adjusts the Regularization strength by measuring the relationship between previous data and present data. MNIST and EMNIST data were used for performance evaluation and experimented in three scenarios. The experiment results showed a 0.1~3% improvement in the accuracy of the previous task for the same domain data and a 10~13% improvement in the accuracy of the previous task for different domain data. When continuously learning data with various domains, the accuracy of all previous tasks achieved more than 50% and the average accuracy improved by about 7%. This result shows that neural network learning can be properly performed in a CL environment in which data of different domains are successively entered by the method of this paper.

• Journal of the Economic Geographical Society of Korea
• /
• v.25 no.1
• /
• pp.183-201
• /
• 2022

Estimating the implicit value of housing assets is a very important task for participants in the housing market. Until now, such estimations were usually carried out using multiple regression analysis based on the inherent characteristics of the estate. However, in this paper, we examine the estimation capabilities of the Artificial Neural Network(ANN) and its 'Deep Learning' faculty. To make use of the strength of the neural network model, which allows the recognition of patterns in data by modeling non-linear and complex relationships between variables, this study utilizes geographic coordinates (i.e. longitudinal/latitudinal points) as the locational factor of housing prices. Specifically, we built a dataset including structural and spatiotemporal factors based on the hedonic price model and compared the estimation performance of the models with and without geographic coordinate variables. The results show that high estimation performance can be achieved in ANN by explaining the spatial effect on housing prices through the geographic location.