In order to reduce the storage requirements for the test pattern, a test data compression scheme based on compatible data block coding is presented. In the scheme, binary code is used to express the test data which ar...
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In order to reduce the storage requirements for the test pattern, a test data compression scheme based on compatible data block coding is presented. In the scheme, binary code is used to express the test data which are compatible or inversely compatible with reference data which are improved compression radio. The circuit structure of decompression with a Finite State Machine (FSM) and a Cyclical Scan Register (CSR) was proposed. Experimental results for the large ISCAS 89 benchmark circuits show that this scheme is a very efficient compression method than other compression schemes and the average compression ratio of up to 63.89%.
To develop an effective software for finite element (FE) model updating of bridges, the interface technology between VC++ and MATLAB was investigated firstly, and then a software for updating FE model of bridges, name...
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We aim for accurate non-invasive optical measurement of blood constituents, especially alcohol (BAL) and glucose (BGL), by means of a newly designed integrating sphere finger photoplethysmographic sensor (isFPPG). The...
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Finite element (FE) model updating of structures using vibration test data has received considerable attentions in recent years due to its crucial role in fields ranging from establishing a reality-consistent structur...
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Flue gas generator set is a kind of large high-speed rotating machinery in petrochemical *** research focuses on noise reduction algorithms basis ontheBirgé-*** the threshold through Penalization Strategy Provide...
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Flue gas generator set is a kind of large high-speed rotating machinery in petrochemical *** research focuses on noise reduction algorithms basis ontheBirgé-*** the threshold through Penalization Strategy Provided by Birgé-Massart;constructed different modulus maximum vertex neighborhood on different wavelet transform decomposition scales to influence the search process of modulus maximum point;obtained the appropriate modulus maximum points sequence on various wavelet decomposition scales;highlighted state feature information;finally usedMallat staggered projection to reconstruct *** order to validate the effectiveness of the algorithm,it was compared with four kinds of threshold noise suppression methods namely Rigrsure,Sqtwolog,Heursure,*** results show that this algorithm has a better signal to noise ratio and mean-square error.
A CMOS digitally programmable lossless grounded inductor is presented in this paper. It uses two digitally programmable second generation current conveyors (DPCCII) and three grounded passive elements including one ca...
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A CMOS digitally programmable lossless grounded inductor is presented in this paper. It uses two digitally programmable second generation current conveyors (DPCCII) and three grounded passive elements including one capacitor only. The inductance value is tuned by programmable gain factor of current conveyor. As an application, a current mode multifunction filter has been realized using proposed programmable inductor. The simulation results have been demonstrated and discussed using a SPICE simulation.
In information retrieval, efficient accomplishing the nearest neighbor search on large scale database is a great challenge. Hashing based indexing methods represent each data instance as a binary string to retrieve th...
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In information retrieval, efficient accomplishing the nearest neighbor search on large scale database is a great challenge. Hashing based indexing methods represent each data instance as a binary string to retrieve the approximate nearest neighbors. In this paper, we present a semi-randomized hashing approach to preserve the Euclidean distance by binary codes. Euclidean distance preserving is a classic research problem in hashing. Most hashing methods used purely randomized or optimized learning strategy to achieve this goal. Our method, on the other hand, combines both randomized and optimized strategies. It starts from generating multiple random vectors, and then approximates them by a single projection vector. In the quantization step, it uses the orthogonal transformation to minimize an upper bound of the deviation between real-valued vectors and binary codes. The proposed method overcomes the problem that randomized hash functions are isolated from the data distribution. What's more, our method supports an arbitrary number of hash functions, which is beneficial in building better hashing methods. The experiments show that our approach outperforms the alternative state-of-the-art methods for retrieval on the large scale dataset.
The objective of this JSTQE Issue on Biophotonics is to highlight recent progress and trends in innovative biophotonics technology development. The papers published in this issue cover a broad range of advanced biopho...
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The objective of this JSTQE Issue on Biophotonics is to highlight recent progress and trends in innovative biophotonics technology development. The papers published in this issue cover a broad range of advanced biophotonics areas summarized in the following sections: 1) bioimaging: optical coherence tomography and microscopy, nonlinear optical imaging, and novel multimodality imaging approaches; 2) biosensing: multifunctional biosensing, and novel biosensing approaches; 3) biophotonic science: mechanisms of light-cell and lighttissue interactions, advanced modeling methods in biophotonics, and light induced biophotonics effects; 4) biophotonic technology: advanced technologies in biophotonic diagnostics and therapeutics, infrared technology in biophotonics, and novel laser, biomedical and fiber optics tools and devices in biophotonics. These key research topics are highlighted as comprehensive overviews of the current status and future trends, as well as original results and recent developments in the field of biophotonics. This issue contains 33 papers, including 18 invited and 15 contributed papers authored by well-established research groups and promising scientists from all over the world. The invited papers include extended reviews on recent biophotonic developments and clinical applications in the areas of highresolution multispectral bioimaging, combined multifunctional microscopy, nonlinear deep tissue imaging, single molecule imaging, optical coherence elastography, cellular and molecular mechanisms of photobiomodulation, tissue optical clearing, clinical ultrafast laser surgery, infrared laser nerve stimulation, and novel tapered diode lasers for biophotonics. The contributed papers cover a broad variety of key biophotonic research areas including recently obtained original results on multimodal bioimaging and sensing, high resolution phase-sensitive magnetomotive optical coherence microscopy and elastography, and laser-assisted typing of polymorphic human
A new method of image segmentation based on 3-D maximum between-cluster variance is proposed. The method uses gray distribution information, neighborhood related information and gradient structure information of pixel...
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Currently, medical images cannot be segmented well due to the inhomogeneous intensity distribution. This problem exists in X-ray (digital radiographs/tomography), MRI and ultrasound. In order to address this problem, ...
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