• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1229-1248
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• 2016

With the feature of convenience and low cost, remote healthcare monitoring (RHM) has been extensively used in modern disease management to improve the quality of life. Due to the privacy of health data, it is of great importance to implement RHM based on a secure and dependable network. However, the network connectivity of existing RHM systems is unreliable in disaster area because of the unforeseeable damage to the communication infrastructure. To design a secure RHM system in disaster area, this paper presents a Secure VANET-Assisted Remote Healthcare Monitoring System (SVC) by utilizing the unique "store-carry-forward" transmission mode of vehicular ad hoc network (VANET). To improve the network performance, the VANET in SVC is designed to be a two-level network consisting of two kinds of vehicles. Specially, an innovative two-level key management model by mixing certificate-based cryptography and ID-based cryptography is customized to manage the trust of vehicles. In addition, the strong privacy of the health information including context privacy is taken into account in our scheme by combining searchable public-key encryption and broadcast techniques. Finally, comprehensive security and performance analysis demonstrate the scheme is secure and efficient.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2236-2244
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• 2018

We make optimal consecutive offer curves for an energy storage system (ESS) integrated wind power producer (WPP) in the co-optimized day-ahead energy and regulation markets. We build the offer curves by solving multi-stage stochastic optimization (MSSO) problems based on the scenarios of pairs consisting of real-time price and wind power forecasts through the progressive hedging method (PHM). We also use the rolling horizon method (RHM) to build the consecutive offer curves for several hours in chronological order. We test the profitability of the offer curves by using the data sampled from the Iberian Peninsula. We show that the offer curves obtained by solving MSSO problems with the PHM and RHM have a higher profitability than offer curves obtained by solving deterministic problems.

• Journal of computational fluids engineering
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• v.21 no.2
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• pp.112-119
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• 2016

NEXTSat-1 is the next-generation small-size artificial satellite system planed by the Satellite Technology Research Center(SatTReC) in Korea Advanced Institute of Science and Technology(KAIST). For the control of attitude and transition of the orbit, the system has adopted a RHM(Resisto-jet Head Module), which has a very simple geometry with a reasonable efficiency. An axisymmetric model is devised with two coil-resistance heaters using xenon(Xe) gas, and the minimum required specific impulse is 60 seconds under the thrust more than 30 milli-Newton. To design the module, seven basic parameters should be decided: the nozzle shape, the power distribution of heater, the pressure drop of filter, the diameter of nozzle throat, the slant length and the angle of nozzle, and the size of reservoir, etc. After quasi one-dimensional analysis, a theoretical value of specific impulse is calculated, and the optima of parameters are found out from the baseline with a series of multi-physical numerical simulations based on the compressible Navier-Stokes equations for gas and the heat conduction energy equation for solid. A commercial code, COMSOL Multiphysics is used for the computation with a FEM (finite element method) based numerical scheme. The final values of design parameters indicate 5.8% better performance than those of baseline design after the verification with all the tuned parameters. The present method should be effective to reduce the time cost of trial and error in the development of RHM, the thruster of NEXTSat-1.

• Journal of the Ergonomics Society of Korea
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• v.30 no.5
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• pp.683-688
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• 2011

Objective: The aim of this study is to develop a distributed representative human model(DRHM) generation and analysis system. Background: DRHMs are used for a product with multiple-size categories such as clothing and shoes. It is not easy for a product designer to explore an optimal sizing system by applying various distributed methods because of their complexity and time demand. Method: Studies related to DRHM generation were reviewed and the RHM generation interfaces of three digital human model simulation systems(Jack$^{(R)}$, RAMSIS$^{(R)}$, and CATIA Human$^{(R)}$) were reviewed. Results: DRHM generation steps are implemented by providing sophisticated interfaces which offer various statistical techniques and visualization methods with ease. Conclusion: The DRHM system can analyze the multivariate accommodation percentage of a sizing system, provide body sizes of generated DRHMs, and visualize generated grids and DRHMs. Application: The DRHM generation and analysis system can be of great use to determine an optimal sizing system for a multiple-size product by comparing various sizing system candidates.