In this paper, we propose a new image segmentation algorithm based on AWF-AP (affinity propagation algorithm based on adaptive weight feature) and graph cuts. Firstly, the image is clustered into numbers of regions by...
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A single electron transistor based on a silicon-on-insulator is successfully fabricated with electron-beam nano- lithography, inductively coupled plasma etching, thermal oxidation and other techniques. The unique desi...
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A single electron transistor based on a silicon-on-insulator is successfully fabricated with electron-beam nano- lithography, inductively coupled plasma etching, thermal oxidation and other techniques. The unique design of the pattern inversion is used, and the pattern is transferred to be negative in the electron-beam lithography step. The oxidation process is used to form the silicon oxide tunneling barriers, and to further reduce the effective size of the quantum dot. Combinations of these methods offer advantages of good size controllability and accuracy, high reproducibility, low cost, large-area contacts, allowing batch fabrication of single electron transistors and good integration with a radio-frequency tank circuit. The fabricated single electron transistor with a quantum dot about 50nto in diameter is demonstrated to operate at temperatures up to 70K. The charging energy of the Coulomb island is about 12.5meV.
Hyperspectral scattering is a promise technique for assessing the apple quality, and extraction of the most useful information from the spectral scattering profiles is critical for accurate assessment of apple bruisin...
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ISBN:
(纸本)9781510810501
Hyperspectral scattering is a promise technique for assessing the apple quality, and extraction of the most useful information from the spectral scattering profiles is critical for accurate assessment of apple bruising susceptibility. This paper analyzed three methods including a diffusion theory model, a four-parameter Lorentzian distribution function and a generalized Gaussian distribution for characterization of the spectral scattering profiles acquired from300 'Golden Delicious' apples by a hyperspectral imaging system over the wavelength region of 500-1000 nm. Partial least squares (PLS) algorithm was used to develop the calibration models for predicting the bruising susceptibility. The correlation coefficient of prediction (Rp) was 0.796, 0.794 and 0.784, and the standard error of prediction (SEP ) was75.6, 75.1 and 76.7 (mm3 J-1) for diffusion theory, Lorentzian distribution and generalized Gaussian distribution models, respectively. Results demonstrated that each scattering characteristic could be used to predict bruise susceptibilities of sound 'Golden Delicious' apples, and provide auxiliary information for fruit quality sorting and packaging.
This paper focuses on the H ∞ fault detection (FD) problem for spring-mass systems (SMSs) over networks with distributed state delays, random packet losses, sensor saturation as well as multiplicative noises via unr...
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This paper focuses on the H ∞ fault detection (FD) problem for spring-mass systems (SMSs) over networks with distributed state delays, random packet losses, sensor saturation as well as multiplicative noises via unreliable communication channels. The output measurements are affected by sensor saturation which is described by sector-nonlinearities. The multiplicative noises are described as a form of Gaussian white noises multiplied by the states. A series of stochastic variables are introduced to describe the randomly occurring distributed state delays. Random packet losses are also introduced in unreliable communications. The purpose of this paper is to design an FD filter such that: 1) The FD dynamic system is exponentially stable in the mean square. 2) The error between the fault signal and the residual signal is controlled to the minimum. 3) The optimal H ∞ filtering performance index is achieved. A sufficient condition for the FD filter design is derived in terms of the solution to a linear matrix inequality (LMI). When the LMI has a feasible solution, the explicit parameters of the desired FD filter can be obtained. Finally, a simulation experiment is illustrated to show the effectiveness and application of the designed method.
The catalytic activity of cation exchange resins will be continuously reduced with its use time in a condensation reaction for bisphenol A (BPA). For online estimation of the catalytic activity, a catalytic deactivati...
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Conventional principal component analysis(PCA) can obtain low-dimensional representations of original data space, but the selection of principal components(PCs) based on variance is subjective, which may lead to infor...
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Conventional principal component analysis(PCA) can obtain low-dimensional representations of original data space, but the selection of principal components(PCs) based on variance is subjective, which may lead to information loss and poor monitoring performance. To address dimension reduction and information preservation simultaneously, this paper proposes a novel PC selection scheme named full variable expression. On the basis of the proposed relevance of variables with each principal component, key principal components can be *** the key principal components serve as a low-dimensional representation of the entire original variables, preserving the information of original data space without information loss. A squared Mahalanobis distance, which is introduced as the monitoring statistic, is calculated directly in the key principal component space for fault detection. To test the modeling and monitoring performance of the proposed method, a numerical example and the Tennessee Eastman benchmark are used.
Visual tracking is a challenging problem for the appearance changes caused by extrinsic and intrinsic factors. In this paper, a robust object tracking algorithm exploiting both collaborative representation and coding ...
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For the question that fuzzy c-means(FCM)clustering algorithm has the disadvantages of being too sensitive to the initial cluster centers and easily trapped in local optima,this paper introduces a new metric norm in FC...
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For the question that fuzzy c-means(FCM)clustering algorithm has the disadvantages of being too sensitive to the initial cluster centers and easily trapped in local optima,this paper introduces a new metric norm in FCM and particle swarm optimization(PSO)clustering algorithm,and proposes a parallel optimization algorithm using an improved fuzzy c-means method combined with particle swarm optimization(AF-APSO).The experiment shows that the AF-APSO can avoid local optima,and get the best fitness and clustering performance significantly.
In this paper, we address stability and robustness properties of hybrid limit cycles for a class of hybrid systems with multiple jumps in one period. The main results entail equivalent characterizations of stability o...
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