Simplex growing algorithm (SGA) was recently developed as an alternative to the N-finder algorithm (N-FINDR) which is shown to be a promising endmember extraction technique. This paper further extends the SGA to a rea...
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The purpose of this study is to present a new method, independent vector analysis (IVA), by extending independent component analysis (ICA) of univariate source signals to multivariate source signals on Magnetic Resona...
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A wide variety of real-life networks share two remarkable generic topological properties: scale-free behavior and modular organization, and it is natural and important to study how these two features affect the dynami...
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A wide variety of real-life networks share two remarkable generic topological properties: scale-free behavior and modular organization, and it is natural and important to study how these two features affect the dynamical processes taking place on such networks. In this paper, we investigate a simple stochastic process—trapping problem, a random walk with a perfect trap fixed at a given location, performed on a family of hierarchical networks that exhibit simultaneously striking scale-free and modular structure. We focus on a particular case with the immobile trap positioned at the hub node having the largest degree. Using a method based on generating functions, we determine explicitly the mean first-passage time (MFPT) for the trapping problem, which is the mean of the node-to-trap first-passage time over the entire network. The exact expression for the MFPT is calculated through the recurrence relations derived from the special construction of the hierarchical networks. The obtained rigorous formula corroborated by extensive direct numerical calculations exhibits that the MFPT grows algebraically with the network order. Concretely, the MFPT increases as a power-law function of the number of nodes with the exponent much less than 1. We demonstrate that the hierarchical networks under consideration have more efficient structure for transport by diffusion in contrast with other analytically soluble media including some previously studied scale-free networks. We argue that the scale-free and modular topologies are responsible for the high efficiency of the trapping process on the hierarchical networks.
Algorithmic self-assembly, a generalization of crystal growth, has been proposed as a mechanism for the bottom-up fabrication of autonomous DNA computation. In theory, growth can be programmed by designing a set of mo...
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Algorithmic self-assembly, a generalization of crystal growth, has been proposed as a mechanism for the bottom-up fabrication of autonomous DNA computation. In theory, growth can be programmed by designing a set of molecular tiles with binding interactions that enforce assembly rules. There are many interesting applications of the reordering problem in Mathematics, as well as computer Sciences. It is a useful primitive operation for computation and construction in the field of science and engineering. It is worth exploring more efficient approach to solve this problem. In this paper, we provide a description of a novel method for the reordering problem by use of the programmable tile assembly model. We propose the thought of block assembly model which takes full advantage of the huge parallelism inherent in the tile assembly. On the basis of the structural property, we delicately devise a rule to produce a long reporter strand which can connect all the inputs of the given problem with the final results. It is proved that this method can be extended to any reordering problem with arbitrary size in theory. The great advantage of our schema is that it only needs a constant number of tile types and in time linear with the size of the input problem to solve any reordering problem.
Knee-related injuries including meniscal tears are common in both young athletes and the aging population, and require accurate diagnosis and surgical intervention when appropriate. With proper techniques and radiolog...
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In this work, an array of quartz crystal microbalance (QCM) sensors is fabricated on a single quartz crystal substrate and attached with poly(dimethylsiloxane) (PDMS) micro chamber for using in flow-injection system. ...
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In this work, an array of quartz crystal microbalance (QCM) sensors is fabricated on a single quartz crystal substrate and attached with poly(dimethylsiloxane) (PDMS) micro chamber for using in flow-injection system. The Cr/Au electrode array is deposited on both side of quartz substrate by sputtering through electroplated microshadow mask. PDMS micro chamber was fabricated by mold casting technique with SU-8 mold. Fabricated PDMS micro chamber and QCM sensor array were attached together for using in flow-injection system. In our experiment, the QCM electrodes were coated with the carboxylic poly(vinyl chloride) (PVC-COOH) and then the carboxylic group was activated with carbodiimide hydrochloride (EDC) and N-hydroxylsuccinimide (NHS) for protein binding. The scanning electron micrograph shown the trapped protein on the modified sensing layer, it confirmed that our QCM sensor and PDMS micro chamber can be used as QCM biosensor array. This new QCM sensor array provide possibility of multiple detection in small amount of sample within a single quartz crystal substrate that avoid the error signal from the different properties of each sensor in an array.
One of the most challenging issues in unsupervised linear spectral mixture analysis (LSMA) is how to obtain unknown knowledge of target signatures referred to as virtual endmembers (VEs) directly from the data to be p...
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One of the most challenging issues in unsupervised linear spectral mixture analysis (LSMA) is how to obtain unknown knowledge of target signatures referred to as virtual endmembers (VEs) directly from the data to be processed. This issue has never arisen in supervised LSMA where the VEs are either assumed to be known a priori or can be provided by visual inspection. With the recent advent of hyperspectral sensor technology many unknown and subtle signal sources can be uncovered and revealed without prior knowledge. This paper addresses this issue and develops a component analysis-based unsupervised LSMA where the desired VEs can be extracted by component analysis-based transforms directly from the data to be processed without appealing for prior knowledge. In order to substantiate the utility of the proposed approach extensive experiments are conducted for demonstration.
The purpose of this study is to present a new method, independent vector analysis (IVA), by extending independent component analysis (ICA) of univariate source signals to multivariate source signals on Magnetic Resona...
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The purpose of this study is to present a new method, independent vector analysis (IVA), by extending independent component analysis (ICA) of univariate source signals to multivariate source signals on Magnetic Resonance Imaging (MRI). IVA is utilized to relief the limitation of the conventional ICA approach. The proposed method can resolve the permutation problem during individual ICA runs for group brain MR images. The proposed IVA method in conjunction with support vector machine (SVM), we can effectively separate the different part of gray, white matter and cerebrospinal fluid (CSF) from brain soft tissues. In order to demonstrate the proposed IVA-SVM method, experiments are conducted for performance analysis and evaluation. Simulation results show that using IVA can greatly release from the problem cause from traditional ICA to the situation of analyzing inconsistent results of MR image.
This paper presents a novel 3D interactive system for simulation and visualization of the human jaw motion. Based on the visual tracking technique, teeth plaster cast and marker cards is used for manipulating virtual ...
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The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, ...
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The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, which can satisfy certain combinatorial and thermodynamic constraints. Using taboo search algorithm, our method can avoid trapping into local optimization and can nd a set of good DNA sequences satisfying required constraints.
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