• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.216-233
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• 2013

Conventional optimization designs of wireless networks mainly focus on spectral efficiency (SE) as a performance metric. However, as diverse media services are emerging, a green wireless network, which not only meets the quality of experience (QoE) requirements for users and also improves energy efficiency (EE), is the most appropriate solution. In this paper, we firstly propose the unit QoE per Watt, which is termed QoE efficiency (QEE), as a user-oriented metric to evaluate EE for wireless networks. We then analyze which is the kind of wireless resource given priority to use under different scenarios to obtain an acceptable QEE. Particularly, power, delay and data-rate related to QoE are separately addressed for several typical services, such as file download, video stream and web browsing services. Next, the fundamental tradeoffs are investigated between QEE and SE for wireless networks. Our analytical results are helpful for network design and optimization to strike a good balance between the users perceived QoE and energy consumption.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.216-220
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• 2008

Sensor nodes in wireless network have several limitations such as lack of energy resource and network bandwidth. There are many researches to extend lifetime of sensor network and enhance availability. However, most of the previous researches didn't consider the mobile sink node. Those researches aren't suitable in the environment having mobile sinks. In this paper. we propose a scheme that reduces communication overheads and energy consumptions and improves reliability in routing path setup. Proposed scheme has excellent scalability without degrading performance in environment where many sink nodes exist and/or the network size is huge. Proposed scheme saves the energy consumption up to 70% in comparison with the previous grid-based and cluster-based protocol. As a result, proposed scheme increases the lifetime of sensor network and enhances availability of wireless sensor network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.377-380
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• 2010

MANET(Mobile Ad-hoc Network) has been proposed as a infrastructure-less network using distributed algorithm for remote environment monitoring and control. The mobility of MANET would make the topology change frequently compared with a static network and a node is resource-constrained. Hence, to improve the routing protocol in MANET, energy efficient routing protocol is required as well as considering the mobility would be needed. In this paper, we extend RODMRP(Resilient Ontology-based Dynamic Multicast Routing Protocol) structure by a modifying the level of cluster. We call this network protocol CACH-RODMRP. Our contribution consists estimating the optimal level of clustering depth with considering node position and reducing the network residual energy. The simulation results of proposal algorithm show that the energy is significantly reduced compared with the previous clustering based routing algorithm for the MANET.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.05a
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• pp.147-148
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• 2018

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.415-417
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• 2005

Core operations (e.9. TDMA scheduler, synchronized sleep period, data aggregation) of many proposed protocols for different layer of sensor network necessitate clock synchronization. Our Paper mingles the scheme of dynamic clustering and diffusion based asynchronous averaging algorithm for clock synchronization in sensor network. Our proposed algorithm takes the advantage of dynamic clustering and then applies asynchronous averaging algorithm for synchronization to reduce number of rounds and operations required for converging time which in turn save energy significantly than energy required in diffusion based asynchronous averaging algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.4
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• pp.59-63
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• 2013

In biomass gasification, efficiency of energy quantification is a difficult part without finishing the process. In this article, a radial basis function neural network (RBFN) is proposed to predict biomass efficiency before gasification. RBFN will be compared with a principal component regression (PCR) and a multilayer perceptron neural network (MLPN). Due to the high dimensionality of data, principal component transform is first used in PCR and afterwards, ordinary regression is applied to selected principal components for modeling. Multilayer perceptron neural network (MLPN) is also used without any preprocessing. For this research, 3 wood samples and 3 other feedstock are used and they are near infrared (NIR) spectrum data with high-dimensionality. Ash and char are used as response variables. The comparison results of two responses will be shown.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.59-64
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• 2017

A wireless sensor network is a network in which nodes equipped with sensors capable of collecting data from the real world are configured wirelessly. Because the sensor nodes are configured wirelessly, they have limited power such as batteries. If the battery of the sensor node is exhausted, the node is no longer usable. If more than a certain number of nodes die, the network will not function. There are many wireless sensor network protocols to improve energy efficiency, among which LEACH Protocol is a typical example. The LEACH protocol is a cluster-based protocol that divides sensor space into clusters and transmits and receives data between nodes. Therefore, depending on how the cluster is structured, the shape of the energy cow may decrease or increase. We compare the network lifetimes of the existing LEACH protocols and the three types of protocols that have been improved using fuzzy methods for cluster selection.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.118-124
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• 1995

In the paper, we have proposed a new technique to determine the initial billet for the forged products using a function approximation in neural network. A three-layer neural network is used and a back propagation algorithm is employed to train the network. An optimal billet which satisfied the forming limitation, minimum of incomplete filling in the die cavity, load and energy as well as more uniform distribution of effective strain, is determined by applying the ability of function approximation of the neural network. The amount of incomplete filling in the die, load and forming energy as well as effective strain are measured by the rigid-plastic finite element method. This new technique is applied to find the optimal billet size for the axisymmetric rib-web product in hot forging. This would reduce the number of finite element simulation for determining the optimal billet of forging products, further it is usefully adopted to physical modeling for the forging design

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.104-108
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• 2007

Ad hoc networks are a type of mobile network that function without any fixed infrastructure. One of the weaknesses of ad hoc network is that a route used between a source and a destination is to break during communication. To solve this problem, one approach consists of selecting routes whose nodes have the most stable link cost. This paper proposes a method for improving the low power distributed MAC. This method is based on the context awareness of the each nodes energy in clustering. We propose to select a new scheme to optimize energy conserving between the clustering nodes in MANET. And this architecture scheme would use context-aware considering the energy related information such as energy, RF strength, relative distances between each node in mobile ad hoc networks. The proposed networks scheme could get better improve the awareness for data to achieve and performance on their clustering establishment and messages transmission. Also, by using the context aware computing, according to the condition and the rules defined, the sensor nodes could adjust their behaviors correspondingly to improve the network routing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.10
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• pp.2473-2492
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• 2012

Energy conservation is a vital issue in wireless sensor networks. Recently, employing mobile sinks for data gathering become a pervasive trend to deal with this problem. The sink can follow stochastic or pre-defined paths; however the controlled mobility pattern nowadays is taken more into consideration. In this method, the sink moves across the network autonomously and changes its position based on the energy factors. Although the sink mobility would reduce nodes' energy consumption and enhance the network lifetime, the overhead caused by topological changes could waste unnecessary power through the sensor field. In this paper, we proposed EEDARS, an energy-efficient dual-sink algorithm with role switching mechanism which utilizes both static and mobile sinks. The static sink is engaged to avoid any periodic flooding for sink localization, while the mobile sink adaptively moves towards the event region for data collection. Furthermore, a role switching mechanism is applied to the protocol in order to send the nearest sink to the recent event area, hence shorten the path. This algorithm could be employed in event-driven and multi-hop scenarios. Analytical model and extensive simulation results for EEDARS demonstrate a significant improvement on the network metrics especially the lifetime, the load and the end-to-end delay.