• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.4
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• pp.350-357
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• 2005

This paper presents a mechanical sensorless vector-controlled system with parameter identification by the aid of image processor. Based on the flux observer and the model reference adaptive system method, the proposed sensorless system includes rotor speed estimation and stator resistance identification using flux errors. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including motor operating state and parameter variations. Because it is difficult to identify rotor resistance simultaneously while estimating rotor speed, a low-accuracy image processor is used to measure the mechanical axis position for calculating the rotor speed at a steady-state operation. The rotor resistance is identified by the error between the estimated speed using the estimated flux and the calculated speed using the image processor. Finally, the validity of this proposed system has been proven through experimentation.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.1
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• pp.37-46
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• 2004

A novel rotor speed estimation method using model reference adaptive control(MRAC) is proposed to improve the performance of a sensorless vector controller. In the proposed method, the stator current is used as the model variable for estimating the speed. In conventional MRAC methods, the relation between the two model errors and the speed estimation error is unclear. In the proposed method, the stator current error is represented as a function of the first degree for the error value in the speed estimation. Therefore, the proposed method can produce a fast speed estimation. The robustness of the rotor flux-based MRAC, back EMF-based MRAC, and proposed MRAC is compared based on a sensitivity function about each error of stator resistance, rotor time constant, mutual inductance. Consequently, the proposed method is much more robust than the conventional methods as regards errors in the mutual inductance, stator resistance. Therefore, the proposed method offers a considerable improvement in the performance of a sensorless vector controller at a low speed. In addition, the superiority of the proposed method and the validity of sensitivity functions were verified by simulation and experiment.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.2 s.25
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• pp.45-52
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• 2007

In this study, the flood inundations of the Nam River catchment running through the Uiryeong and Haman regions have been simulated using the numerical model based on quadtree grids. The nonlinear Saint Venant equation is employed as the governing equation for a numerical model in this study. The governing equations are discretized explicitly with a finite difference leap-frog scheme on adaptive hierarchical quadtree grids. Results from this study are compared with those of established numerical models such as the HEC-RAS and the FLUMEN. A numerical model is also simulated according to the frequency variations of flood event. Obtained numerical results show good agreements with them of commercial models. It is found from this study that the flood inundations in the studied area can be occurred at a 500 year frequency event.

• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.137-147
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• 2007

As Web-based online communities are rapidly growing, the agents in social groups need to know their measurable belief of trust for safe andsuccessful interactions. In this paper, we propose a computational model of trust resulting from available feedbacks in online communities. The notion of trust can be defined as an aggregation of consensus given a set of past interactions. The averagetrust of an agent further represents the center of gravity of the distribution of its trustworthiness and untrustworthiness. And then, we precisely describe the relationship between reputation, trust, and averagetrust through a concrete example of their computations. We apply our trust model to online internet settings in order to show how trust mechanisms are involved in a rational decision-making of the agents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1790-1806
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• 2015

Utility-based routing is a special type of routing approach using a composite utility metric when making routing decisions in ad hoc and sensor networks. Previous studies on the utility-based routing all use fixed retry limit and a very simple distance related energy model, which makes the utility maximization less efficient and the implementation separated from practice. In this paper, we refine the basic utility model by capturing the correlation of the transmit power, the retry limit, the link reliability and the energy cost. A routing algorithm based on the refined utility model with adaptive transmit power and retry limit allocation is proposed. With this algorithm, packets with different priorities will automatically receive utility-optimal delivery. The design of this algorithm is based on the observation that for a given benefit, there exists a utility-maximum route with optimal transmit power and retry limit allocated to intermediate forwarding nodes. Delivery along the utility-optimal route makes a good balance between the energy cost and the reliability according to the value of the packets. Both centralized algorithm and distributed implementations are discussed. Simulations prove the satisfying performance of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.4203-4225
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• 2014

Fuzzy identity-based cryptography introduces the threshold structure into identity-based cryptography, changes the receiver of a ciphertext from exact one to dynamic many, makes a cryptographic scheme more efficient and flexible. In this paper, we propose the first fuzzy identity-based signcryption scheme in lattice-based cryptography. Firstly, we give a fuzzy identity-based signcryption scheme that is indistinguishable against chosen plaintext attack under selective identity model. Then we apply Fujisaki-Okamoto method to obtain a fuzzy identity-based signcryption scheme that is indistinguishable against adaptive chosen ciphertext attack under selective identity model. Thirdly, we prove our scheme is existentially unforgeable against chosen message attack under selective identity model. As far as we know, our scheme is the first fuzzy identity-based signcryption scheme that is secure even in the quantum environment.

• International Journal of Fluid Machinery and Systems
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• v.8 no.4
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• pp.230-239
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• 2015

The swirling flow in the draft tube of a Francis turbine can cause the flow instability and the cavitation surge and has a larger influence on hydraulic power operating system. In this paper, the cavitating flow with swirling flow in the diffuser was studied by the draft tube component experiment, the model Francis turbine experiment and the numerical simulation. In the component experiment, several types of fluctuations were observed, including the cavitation surge and the vortex rope behaviour by the swirling flow. While the cavitation surge and the vortex rope behaviour were suppressed by the aeration into the diffuser, the loss coefficient in the diffuser increased by the aeration. In the model turbine test the aeration decreased the efficiency of the model turbine by several percent. In the numerical simulation, the cavitating flow was studied using Scale-Adaptive Simulation (SAS) with particular emphasis on understanding the unsteady characteristics of the vortex rope structure. The generation and evolution of the vortex rope structures have been investigated throughout the diffuser using the iso-surface of vapor volume fraction. The pressure fluctuation in the diffuser by numerical simulation confirmed the cavitation surge observed in the experiment. Finally, this pressure fluctuation of the cavitation surge was examined and interpreted by CFD.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.83-92
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• 2017

Reconnaissance is performed gathering information from a series of scanning probes where the objective is to identify attributes of target hosts. Network reconnaissance of IP addresses and ports is prerequisite to various cyber attacks. In order to increase the attacker's workload and to break the attack kill chain, a few proactive techniques based on the network-based moving target defense (NMTD) paradigm, referred to as IP address mutation/randomization, have been presented. However, there are no commercial or trial systems deployed in real networks. In this paper, we propose a threat model and the request for requirements for developing NMTD techniques. For this purpose, we first examine the challenging problems in the NMTD mechanisms that were proposed for the legacy TCP/IP network. Secondly, we present a threat model in terms of attacker's intelligence, the intended information scope, and the attacker's location. Lastly, we provide seven basic requirements to develop an NMTD mechanism for the legacy TCP/IP network: 1) end-host address mutation, 2) post tracking, 3) address mutation unit, 4) service transparency, 5) name and address access, 6) adaptive defense, and 7) controller operation. We believe that this paper gives some insight into how to design and implement a new NMTD mechanism that would be deployable in real network.

• Journal of KIISE:Software and Applications
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• v.26 no.12
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• pp.1507-1518
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• 1999

본 논문은 제어대상체의 지식을 이용하여 적절한 의사결정을 내리거나 또는 지속적으로 변화하는 주변환경에 적응해 나갈 수 있는 지능시스템 설계를 위한 내배엽성 모델링 방법론을 제시한다. 이러한 지능적 내배엽성 시스템은 의사결정 모델, 지식기반의 내부모델, 그리고 내부모델의 구축모델 등을 기반으로 달성될 수 있다. 학습기능의 모델링을 위하여 수정된 귀납추론 방법과 적응형 전문가 시스템 방법이 제안되었다. 제시된 방법론은 지능적 학습 및 의사결정 기능을 갖춘 지능적 카드경기자 모델링의 예를 통하여 그 가능성을 검증하였다. Abstract This paper presents an endomorphic modeling methodology for designing intelligent systems that can determine by itself using its knowledge of the world and adapt itself to continuously changing circumstances. We have developed such an intelligent endomorphic system by integrating the decision making component and knowledge based internal model with internal model construction model. Learning capabilities are established using the modified inductive reasoning and adaptive expert system techniques we developed. Proposed methodology has been successfully applied to a design of intelligent card game players capable of supporting the intelligent learning and decision making.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.413-421
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• 2015

Regularized Blind Deconvolution is a problem applicable in degraded images in order to bring the original image out of blur. Multichannel blind Deconvolution considered as an optimization problem. Each step in the optimization is considered as variable splitting problem using an algorithm called Alternating Minimization Algorithm. Each Step in the Variable splitting undergoes Augmented Lagrangian method (ALM) / Bregman Iterative method. Regularization is used where an ill posed problem converted into a well posed problem. Two well known regularizers are Tikhonov class and Total Variation (TV) / L2 model. TV can be isotropic and anisotropic, where isotropic for L2 norm and anisotropic for L1 norm. Based on many probabilistic model and Fourier Transforms Image deblurring can be solved. Here in this paper to improve the performance, we have used an adaptive regularization filtering and isotropic TV model Lp norm. Image deblurring is applicable in the areas such as medical image sensing, astrophotography, traffic signal monitoring, remote sensors, case investigation and even images that are taken using a digital camera / mobile cameras.