This paper presents a methodology for roughness analysis based on surface characteristics of images obtained from optical and electronic microscopes. Texture analysis has been widely used in different fields, such as ...
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Nowadays, the amount of available information, especially on the Web, is increasing. In this field, the role of user modeling and personalized information access is obviously vital. The traditional techniques like BOW...
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This paper proposes a novel method, called complete fuzzy LDA (CFLDA), which combines the linear discriminant analysis (LDA) and fuzzy set theory. LDA preserve the total variance by maximizing the trace of feature var...
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This paper proposes a novel method, called complete fuzzy LDA (CFLDA), which combines the linear discriminant analysis (LDA) and fuzzy set theory. LDA preserve the total variance by maximizing the trace of feature variance, but LDA cannot preserve local information due to pursuing maximal variance. So, the complete fuzzy linear discriminant analysis (CFLDA) algorithm is proposed, in which the fuzzy k-nearest neighbor (FKNN) is implemented to achieve the distribution local information of original samples. Experimental results on ORL, Yale, and AR face databases show the effectiveness of the proposed method. Image segmentation experimental results show better distinguished results in images.
Sensor nodes of Wireless Sensor Networks (WSNs) are resource constraints in energy, memory, processing and communication bandwidth. Since they are operated by battery, their life span is limited. Specially, energy con...
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We investigated ultra-efficient nano-photonic modulators based on silicon photonic crystal slot waveguides infiltrated with electro-optic polymers. The integration of Si3N4 guided mode resonance grating with plasmonic...
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Data center plays an important role in cloud computing. Cloud computing provides novel perspectives in Internet technologies and raises issues in the architecture, protocol, and implementation of existing networks and...
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In this paper we describe a novel clutter cancellation platform based on a two stage approach that combines a feedback guided predictive front-end hybrid clutter canceller with high performance back-end filtering and ...
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In this paper we describe a novel clutter cancellation platform based on a two stage approach that combines a feedback guided predictive front-end hybrid clutter canceller with high performance back-end filtering and target detection. The front-end architecture is based on an FPGA implementation of a Kalman filter that predicts target locations in real time and removes the target signals from the incoming data prior to hybrid cancellation. The back-end is user configurable and exploits high performance GPU and multi-core parallel hardware to simultaneously compute multiple clutter suppression and target detection algorithms coupled to an intelligent selection strategy for selecting the most accurate result. These target locations are fed back to the FPGA Kalman filter periodically to update the target predictions.
Human identification from DNA is typically based on 13 short-tandem repeat (STR) alleles. Commercial kits used in forensic casework rely on the detection of these alleles in DNA samples acquired from an individual. Ho...
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ISBN:
(纸本)9781618397461
Human identification from DNA is typically based on 13 short-tandem repeat (STR) alleles. Commercial kits used in forensic casework rely on the detection of these alleles in DNA samples acquired from an individual. However, the process itself is slow (it can take up to 2 days when conducting a laboratory analysis or 1 hour when using Rapid DNA systems) and has been designed to operate on pristine DNA samples. The need for achieving fast and accurate DNA processing has spurred efforts in developing portable systems that can reduce the processing time to less than 1 hour. But such systems are expected to operate on degraded DNA samples due to the architecture and process used by the instrument. Consequently, detecting the alleles in such degraded DNA samples can be a challenging problem. In this paper, we present an algorithm to detected allelic peaks from degraded DNA signals based on an adaptive signal-processing scheme. The performance of the algorithm is evaluated on two datasets: 1) data collected at the WVU department of Forensic and Investigative sciences, obtained by performing a controlled DNA degradation using ultraviolet radiation, 2) data provided by NIST obtained by varying cycle counts for the PCR processing step. Experiments indicate the efficacy of the algorithm in allelic peak detection and reiterate the need for approaching the problem in a systematic manner.
Interpretation geophysical data is one of the important factors affecting the economic indicators of mining process. The mining process depend on the speed and accuracy of geophysical data interpretation, but the proc...
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Interpretation geophysical data is one of the important factors affecting the economic indicators of mining process. The mining process depend on the speed and accuracy of geophysical data interpretation, but the process of logging data interpretation can not be strictly formalized. Therefore, computer interpretation methods on the basis of expert estimates are necessary. The method is based on expert opinion are widely used in weakly formalized tasks. Mention may be made of the system based on rules, fuzzy logic, Bayesian decision-making systems, artificial neural networks (ANN). ANN have already been used for solving a wide range of recognition problems. The paper analyzes the quality of network's data interpretation essentially depending on its configuration parameters, methods of data preprocessing and learning samples. About 2000 calculation experiments have been made, software and templates for preprocessing of data and interpretation findings have been developed. These experiments showed the effectiveness of neural network approach to solving the problem of geological rocks recognition in stratum-infiltration uranium deposits. Further research in this area will raise the recognition process automation and its accuracy.
We present a study of interactive virtual reality visualizations of scientific motions as found in biomechanics experiments. Our approach is threefold. First, we define a taxonomy of motion visualizations organized by...
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