In this work the design, analysis and characterization of a capacitive accelerometer fabricated with low-cost PolyMUMP's technology for automotive applications were presented. The simulations of the accelerometer ...
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In this work the design, analysis and characterization of a capacitive accelerometer fabricated with low-cost PolyMUMP's technology for automotive applications were presented. The simulations of the accelerometer design using the coventorware software, indicated that for capacitive sensing, an electronic readout system requires detection of low capacitance reading resolutions (down to aF). With the analysis and experimental characterization the operation parameters of the accelerometer were obtained such as: sensitivity, nonlinearity, hysteresis and the radiometric parameter (see fig 2-5). The obtained results showed a value of sensitivity of 1.4 mV/g and the non-linearity that the device presented to a maximum deviation of the curve of sensitivity was better than 0.8%, these results are compared with data reported in literature.
This article describes a case-study related to on-line condition monitoring measurements in process industry. A platform for on-line, real-time and remotely operated condition monitoring has been developed. The system...
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ISBN:
(纸本)9781618390097
This article describes a case-study related to on-line condition monitoring measurements in process industry. A platform for on-line, real-time and remotely operated condition monitoring has been developed. The system consists of an open source based embedded and cost effective DSP computing platform, a machine vision sensor for solid debris analysis of oils, and interfaces for other measurement technologies (e.g. vibration analysis and/or temperature measurements). In addition, the platform is equipped with data transmission interface that enables remote operation and control. Real-time analysis of solid particles in oil is useful in many preventive condition monitoring applications, for example, in the lubrication circuit of a paper machine or with cold rolling lubrication oils. In the case of a paper machine the generated information can be used to pinpoint upcoming failures in the machine elements (e.g. bearings, gears etc.). Whereas in the case of cold rolling applications the information is useful to prevent quality problems in the rolled metal product. In the both applications the presented system enables also monitoring failures in the filtration system. Preliminary results and designs show that the system is able to detect and analyse size and shape for particles larger than 50 micrometers continuously with a frame rate of 5 Hz from the oil flow volume of 13.8 ml/s and flow speed of 60 mm/s. The system is in progress of being further developed in collaboration with the industry. Easy integration of different sensors and real-time measurements make the system a powerful tool for making maintenance decisions in process industry.
The kernel weighted k-nearest neighbours (KWKNN) algorithm is an efficient kernel regression method that achieves competitive results with lower computational complexity than least-squares support vector machines and ...
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The kernel weighted k-nearest neighbours (KWKNN) algorithm is an efficient kernel regression method that achieves competitive results with lower computational complexity than least-squares support vector machines and Gaussian processes. This paper presents the parallel implementation on a cluster platform of the sequential KWKNN implemented in Matlab. This implies both the parallelization of the k nearest-neighbour search and the evaluation of the cross-validation error on a large distributed data set. The results demonstrate the good performances of the implementation.
Sparse coding has high-performance encoding and ability to express images, sparse encoding basis vector plays a crucial role. The computational complexity of the most existing sparse coding basis vectors of is relativ...
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Whitening transformation has widely been used in face recognition. Typically it is used in one of four ways: as a data preprocessing tool before feature extraction, to calculate statistically uncorrelated discriminant...
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Whitening transformation has widely been used in face recognition. Typically it is used in one of four ways: as a data preprocessing tool before feature extraction, to calculate statistically uncorrelated discriminant vectors, as a transitional step in calculating discriminant vectors, or as a data post-processing tool after feature extraction. The experimental studies presented in this paper demonstrate, however, that researchers' faith in this technique is misplaced and that in fact whitening transformation is inappropriately used, and actually has a negative effect in face recognition without proper analysis.
This paper presented a novel subspace-based facial discriminant feature extraction method, i.e. orthogonalized direct linear discriminant analysis (OD-LDA), whose discriminant vectors could be obtained by performing G...
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This paper presented a novel subspace-based facial discriminant feature extraction method, i.e. orthogonalized direct linear discriminant analysis (OD-LDA), whose discriminant vectors could be obtained by performing Gram-Schmidt orthogonal procedure on a set of discriminant vectors of D-LDA. Experimental studies conducted on ORL, FERET, Yale, and AR face image databases showed that OD-LDA could compete with prevailing subspace-based facial discriminant feature extraction methods such as Fisherfaces, N-LDA D-LDA, Uncorrelated LDA, parameterized D-LDA, K-L expansion based the between-class scatter matrix, and orthogonal complimentary space method in terms of recognition rate.
This paper focuses on the absolute stability of a new class of Takagi-Sugeno (T-S) fuzzy Lurie control systems with time-varying delay. By utilizing the Lyapunov-Krasovskii functional (LKF) and novel techniques, new L...
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This paper focuses on the absolute stability of a new class of Takagi-Sugeno (T-S) fuzzy Lurie control systems with time-varying delay. By utilizing the Lyapunov-Krasovskii functional (LKF) and novel techniques, new Lyapunov functions are defined and a new absolute stability condition is derived in the form of linear matrix inequalities (LMIs) which is different from existing ones.
We present measurements of single-qubit gate errors for a superconducting qubit. Results from quantum process tomography and randomized benchmarking are compared with gate errors obtained from a double π pulse experi...
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We present measurements of single-qubit gate errors for a superconducting qubit. Results from quantum process tomography and randomized benchmarking are compared with gate errors obtained from a double π pulse experiment. Randomized benchmarking reveals a minimum average gate error of 1.1±0.3% and a simple exponential dependence of fidelity on the number of gates. It shows that the limits on gate fidelity are primarily imposed by qubit decoherence, in agreement with theory.
We illustrate a Lyapunov function approach to analyze the stability of 2-D systems described by systems of higher-order linear partial difference equations.
We illustrate a Lyapunov function approach to analyze the stability of 2-D systems described by systems of higher-order linear partial difference equations.
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