• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.64-75
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• 2007

Service discovery protocols is software components to find specific services or resources on network. The SLP defined by IETF protocol is a framework for automatic service discovery on IP based networks. Automatic service discovery is an important component on ubiquitous computing environment. This paper proposes a service discovery architecture named as SLPA(Service Location Protocol based on AMAAM). AMAAM(Mobility Agent Advertisement Mechanism) is an aggregation-based Mobile IP implementation in MANET. In SLPA, the role of the directory agent is assigned to the mobility agent in AMAAM. The mobility agent periodically beacons an advertisement message which contains both the advertisement of the directory agent in SLP and the advertisement of the mobility agent in Mobile IP. For evaluating the functional correctness of SLPA and the overhead of maintaining a service directory of SLPA. We simulate SLPA using ns-2 and analyze the overhead of control overheads for the aggregation. Through the simulation experiments we show the functional correctness of the proposed architecture and analyze the performance results.

• Nuclear Engineering and Technology
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• v.45 no.6
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• pp.721-730
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• 2013

Within the framework of the ASTRID project, core design studies are being conducted by the CEA with support from AREVA and EDF. The pre-conceptual design studies are being conducted in accordance with the GEN IV reactor objectives, particularly in terms of improving safety. This involves limiting the consequences of 1) a hypothetical control rod withdrawal accident (by minimizing the core reactivity loss during the irradiation cycle), and 2) an hypothetical loss-of-flow accident (by reducing the sodium void worth). Two types of cores are being studied for the ASTRID project. The first is based on a 'large pin/small spacing wire' concept derived from the SFR V2b, while the other is based on an innovative CFV design. A distinctive feature of the CFV core is its negative sodium void worth. In 2011, the evaluation of a preliminary version (v1) of this CFV core for ASTRID underlined its potential capacity to improve the prevention of severe accidents. An improved version of the ASTRID CFV core (v2) was proposed in 2012 to comply with all the control rod withdrawal criteria, while increasing safety margins for all unprotected-loss-of-flow (ULOF) transients and improving the general design. This paper describes the CFV v2 design options and reports on the progress of the studies at the end of pre-conceptual design phase 1 concerning: - Core performance, - Intrinsic behavior during unprotected transients, - Simulation of severe accident scenarios, - Qualification requirements. The paper also specifies the open options for the materials, sub-assemblies, absorbers, and core monitoring that will continue to be studied during the conceptual design phase.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1204-1227
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• 2020

The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the trajectory for ME to collect data. Then, we define data transmission routing sequence and model rendezvous planning for the cluster. In order to achieve optimization of energy consumption, we specifically apply the economic theory called Diminishing Marginal Utility Rule (DMUR) and create the utility function with regard to energy to develop an adaptive energy consumption optimization framework to achieve energy efficiency for data collection. At last, Rendezvous Transmission Algorithm (RTA) is proposed to better tradeoff between energy conservation and traffic balancing. Furthermore, via collaborations among multiple MEs, we design Two-Orbit Back-Propagation Algorithm (TOBPA) which concurrently handles load imbalance phenomenon to improve the efficiency of data collection. The simulation results show that our solutions can improve energy efficiency of the whole network and reduce the energy consumption of sensor nodes, which in turn prolong the lifetime of WSNs.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.627-638
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• 2014

In this paper, we study the joint price and power allocation in spectrum sharing macro-femtocell networks. The proposed game theoretic framework is based on bi-level Stackelberg game where macro base station (MBS) works as a leader and underlaid femto base stations (FBSs) work as followers. MBS has fixed data rate and imposes interference price on FBSs for maintaining its data rate and earns revenue while FBSs jointly adjust their power for maximizing their data rates and utility functions. Since the interference from FBSs to macro user equipment is kept under a given threshold and FBSs compete against each other for power allocation, there is a need to determine a power allocation strategy which converges to Stackelberg equilibrium. We consider two cases for MBS power allocation, i.e., fixed and dynamic power. MBS can adjust its power in case of dynamic power allocation according to its minimum data rate requirement and number of FBSs willing to share the spectrum. For both cases we consider uniform and non-uniform pricing where MBS charges same price to all FBSs for uniform pricing and different price to each FBS for non-uniform pricing according to its induced interference. We obtain unique closed form solution for each case if the co-interference at FBSs is assumed fixed. And an iterative algorithm which converges rapidly is also proposed to take into account the effect of co-tier interference on interference price and power allocation strategy. The results are explained with numerical simulation examples which validate the effectiveness of our proposed solutions.

• Journal of KIISE
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• v.44 no.7
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• pp.719-725
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• 2017

To reduce management costs and improve performance, the European Telecommunication Standards Institute (ETSI) introduced the concept of network function virtualization (NFV), which can implement network functions (NFs) on cloud/datacenters. Within the NFV architecture, NFs can share physical resources by hosting NFs on physical nodes (commodity servers). For network service providers who support NFV architectures, an efficient resource allocation method finds utility in being able to reduce operating expenses (OPEX) and capital expenses (CAPEX). Thus, in this paper, we analyzed the network service chain embedding problem via an optimization formulation and found a close-optimal solution based on the Markov approximation framework. Our simulation results show that our approach could increases on average CPU utilization by up to 73% and link utilization up to 53%.

• Journal of KIISE:Information Networking
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• v.32 no.2
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• pp.156-166
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• 2005

Ethernet passive optical network is an economical and efficient access network that has received significant research attention in recent years. A MAC(Media Access Control) protocol of PON, the next generation access network, is based on TDMA(Time Division Multiple Access) basically. In this thesis, we addressed the problem of dynamic bandwidth allocation in QoS based Ethernet PONs. We augmented the bandwidth allocation to support QoS in a differentiated services framework. Our differentiated bandwidth guarantee allocation(DBGA) allocates effectively and fairly bandwidths among end users. Moreover, we showed that DBGA that perform weighted bandwidth allocation for high priority packets result in better performance in terms of average and maximum packet delay, as well as network throughput compared with existing dynamic bandwidth allocations. We used simulation experiments to study the performance and validate the effectiveness of the proposed bandwidth allocations.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.565-570
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• 2013

The mirror neuron regions which are distributed in cortical area handled a functionality of intention recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper an automated intention recognition system is proposed by applying computational model of mirror neuron system to the human-robot interaction system. The computational model of mirror neuron system is designed by using dynamic neural networks which have model input which includes sequential feature vector set from the behaviors from the target object and actor and produce results as a form of motor data which can be used to perform the corresponding intentional action through the imitative learning and estimation procedures of the proposed computational model. The intention recognition framework is designed by a system which has a model input from KINECT sensor and has a model output by calculating the corresponding motor data within a virtual robot simulation environment on the basis of intention-related scenario with the limited experimental space and specified target object.

• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.115-125
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• 2009

Simultaneous equation models, which are widely used in business and economic areas, generally consist of endogenous variables determined within models and exogenous variables externally determined and in the simultaneous equations model framework there are rank and order conditions for the model identification and the existence of unique solutions. By contrast, their estimating results have less efficiencies and furthermore do not exist, since the most estimating procedures are performed under the assumptions for rank and order conditions. We propose the new statistical test for sufficiency of the rank condition under the order condition, and show the asymptotic properties for the test. The Monte Carlo simulation studies are achieved in order to evaluate its power and to suggest the baseline for satisfying the rank conditions.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.665-679
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• 2017

When measuring productive efficiency, often it is necessary to have knowledge of the production frontier function that shows the maximum possible output of production units as a function of inputs. Canonical parametric forms of the frontier function were initially considered under the framework of stochastic frontier model; however, several additional nonparametric methods have been developed over the last decade. Efforts have been recently made to impose shape constraints such as monotonicity and concavity on the non-parametric estimation of the frontier function; however, most existing methods along that direction suffer from unnecessary non-smooth points of the frontier function. In this paper, we propose methods to estimate the smooth frontier function with monotonicity for stochastic frontier models and investigate the effect of imposing a monotonicity constraint into the estimation of the frontier function and the finite dimensional parameters of the model. Simulation studies suggest that imposing the constraint provide better performance to estimate the frontier function, especially when the sample size is small or moderate. However, no apparent gain was observed concerning the estimation of the parameters of the error distribution regardless of sample size.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.615-632
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• 2017

Unlike randomized trial, statistical strategies for inferring the unbiased causal relationship are required in the observational studies. The matching with the propensity score is one of the most popular methods to control the confounders in order to evaluate the effect of the treatment on the outcome variable. Recently, new methods for the causal inference in latent class analysis (LCA) have been proposed to estimate the average causal effect (ACE) of the treatment on the latent discrete variable. They have focused on the application study for the real dataset to estimate the ACE in LCA. In practice, however, the true values of the ACE are not known, and it is difficult to evaluate the performance of the estimated the ACE. In this study, we propose a method to generate a synthetic data using the propensity score in the framework of LCA, where treatment and outcome variables are latent. We then propose a new method for estimating the ACE in LCA and evaluate its performance via simulation studies. Furthermore we present an empirical analysis based on data form the 'National Longitudinal Study of Adolescents Health,' where puberty as a latent treatment and substance use as a latent outcome variable.