The intrinsic thermodynamical factors that dominate the stability of nanocrystallines are investigated through the microcosmic process of grain *** results suggest that nanocrystallines grows at a certain temperature ...
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The intrinsic thermodynamical factors that dominate the stability of nanocrystallines are investigated through the microcosmic process of grain *** results suggest that nanocrystallines grows at a certain temperature and the critical temperature is determined by the vacancy formation energy and diffusion activation energy of the *** on the hypothesis,a simple model is proposed to predict the size-dependent critical temperature of grain *** this model,we investigate the thermal stability of nanocrystallines V and Au,compared with the results *** is shown that the critical temperature decreases with decreasing size,showing an evident size *** research reveals that the thermal stability is dependent on the energetic state of the nanocrystallines and the mobility of the inner atoms.
The electric power is indispensable for modern life. However, there is a problem of harmonic disturbance when the harmonic power runs into electronic devices. To overcome the problem and realize a stable supply of the...
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This study is an attempt to take advantage of a cerebellar model to control a biomimetic arm. The cerebellar controller is a modified MOSAIC model which adaptively controls the arm. We call this model ORF-MOSAIC (Orga...
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Phasor measurement units (PMUs) become important to state estimation for power systems by providing globally synchronized measurements of real-time phasors of voltage and currents with a high sampling rate. However th...
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Phasor measurement units (PMUs) become important to state estimation for power systems by providing globally synchronized measurements of real-time phasors of voltage and currents with a high sampling rate. However the large quantities of measurement data produced by PMUs brings a serious burden to the communication system, which aggravates communication constraints such as the packet loss rate. In this paper, a novel optimization criterion for choosing PMU placements is proposed, considering random communication packet losses. Based on this criterion, a simplified optimal solution searching algorithm is given. Finally numerical simulations are given to test the validity of this algorithm. The dependence of the optimal PMU placement solution on the packet loss rate is indicated as well.
In this paper power system dynamic state estimation problem is studied considering random communication packet losses. Two sorts of stochastic processes, i.i.d. process and Markov process, are respectively utilized to...
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In this paper power system dynamic state estimation problem is studied considering random communication packet losses. Two sorts of stochastic processes, i.i.d. process and Markov process, are respectively utilized to model two different communication packet losses cases. The first case only considers packet losses rate, and the second case includes both of packet losses rate and recovery rate. The degradation of the performance of state estimation caused by communication packet losses is analyzed on IEEE 14 buses test system, and numerical results are given.
Patient monitor modules have various inputs for vital function measurement. We can practice many of these measurements with some students in the laboratory of biomedical engineering. However, invasive blood pressure (...
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In this paper an iterative LMI based approach for solving the H 2 control problem using static state feedback for singular perturbation systems is proposed. The proposed controller is given in terms of the solution o...
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In this paper an iterative LMI based approach for solving the H 2 control problem using static state feedback for singular perturbation systems is proposed. The proposed controller is given in terms of the solution of a set of matrix inequalities independent of singular parameter ε. These inequalities are not in the form of linear matrix inequalities (LMI). By introducing a new iterative algorithm, these inequalities are solved through iterative LMI formulation. To show the effectiveness of the proposed algorithm comparing to other standard time-scale decomposition methods, an illustrative example is also provided.
This work proposed an improvement for the visual odometry based on a new hardware design concept. Generally, a visual odometry system relies on one stereo camera to detect the 3D features which are used as input for t...
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This work proposed an improvement for the visual odometry based on a new hardware design concept. Generally, a visual odometry system relies on one stereo camera to detect the 3D features which are used as input for the ego motion estimation process. However, such design usually faced with the motion ambiguity problem resulting in poor estimation of the ego motion. The proposed multi-camera system solves this problem using an intuitive hardware design that enables a simple yet effective way to eliminate the motion ambiguity problems. Experiment results show that the proposed system yields better ego motion estimation compared to the conventional single camera system.
Abstract The problem to minimize power losses in an electrical network subject to voltage and power constraints is in general hard to solve. However, it has recently been discovered that semidefinite programming relax...
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Abstract The problem to minimize power losses in an electrical network subject to voltage and power constraints is in general hard to solve. However, it has recently been discovered that semidefinite programming relaxations in many cases enable exact computation of the global optimum. Here we point out a fundamental reason for the successful relaxations, namely that the passive network components give rise to matrices with nonnegative offdiagonal entries. Recent progress on quadratic programming with Metzler matrix structure can therefore be applied.
Estimation of distribution algorithms (EDAs) is a class of probabilistic model-building evolutionary algorithms, which is characterized by learning and sampling the probability distribution of the selected individuals...
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Estimation of distribution algorithms (EDAs) is a class of probabilistic model-building evolutionary algorithms, which is characterized by learning and sampling the probability distribution of the selected individuals. This paper proposes a modified estimation of distribution algorithm (mEDA) for numeric optimization. mEDA uses a novel sampling method, called centro-individual sampling, and a fuzzy c-means clustering technique to improve its performance. Extensive experiments conducted on a set of benchmark functions show that mEDA outperforms HPBILc, CEGDA, CEGNABGe and NichingEDA, reported in the literature, in terms of the quality of solutions.
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