DNA tile self-assembly is a promising paradigm for nanotechnology. Recently, many researches show that computation by DNA tile self-assembly maybe scalable. In this paper, we propose the algorithm for elliptic curve D...
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DNA tile self-assembly is a promising paradigm for nanotechnology. Recently, many researches show that computation by DNA tile self-assembly maybe scalable. In this paper, we propose the algorithm for elliptic curve Diffie-Hellman key exchange based on DNA tile self-assembly. First we give the DNA tile self-assembly model to compute the scalar multiplication, then we can successfully implement the Diffie-Hellman key exchange over elliptic curve by extracting the result strand of the scalar multiplication.
In this paper,a new lifting scheme of directionlet transform(LDT) is presented,the corresponding multidirectional and anisotropic transform has latticebased separable filtering and subsampling along any two directions...
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In this paper,a new lifting scheme of directionlet transform(LDT) is presented,the corresponding multidirectional and anisotropic transform has latticebased separable filtering and subsampling along any two directions with rational *** design an adaptive compression algorithm based on LDT,using the quad-tree segmentation resulting optimized *** results show that our proposed compression algorithm for image coding outperforms the standard wavelet-based SPIHT and JPEG2000 both in terms of PSNR and visual quality,especially at the low-rate.
A quick 3D needle segmentation algorithm for 3D US data is described in this paper. The algorithm includes the 3D Quick Randomized Hough Transform (3DGHT), which is based on the 3D Randomized Hough Transform and coars...
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Most experimental and decoding algorithm studies of brain neural signals assume that neurons transmit information as a rate coding, but recent studies on the fast cortical computations indicate that temporal coding is...
Most experimental and decoding algorithm studies of brain neural signals assume that neurons transmit information as a rate coding, but recent studies on the fast cortical computations indicate that temporal coding is probably a more biologically plausible scheme used by neurons. We introduce spiking neural networks (SNN) which consist of spiking neurons propagate information by the timing of spikes to analyze the cortical neural spike trains directly without temporal information lost. The SNN based temporal pattern classification is compared with the conventional artificial neural networks (ANN) based firing rate analysis. The results show that the SNN algorithm can achieve higher accuracy, which demonstrates that temporal coding is a viable code for fast neural information processing and the SNN approach is suitable for recognizing the temporal pattern in the cortical neural signals.
The purpose of this study is to segment hippocampus, amygdala and entorhinal cortex in magnetic resonance images (MRI) of temporal lobe epilepsy (TLE) patients. The proposed method consists of two separate parts. Firs...
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The purpose of this study is to segment hippocampus, amygdala and entorhinal cortex in magnetic resonance images (MRI) of temporal lobe epilepsy (TLE) patients. The proposed method consists of two separate parts. First, we use an atlas-based segmentation method to obtain initial segmentation results for desired structures. Using additional preprocessing steps for image registration and gray matter (GM) segmentation is the specification of this stage of the work. Then, all of the GM voxels are labeled using an anatomical atlas. In the next stage, variational level set formulation without re-initialization is applied on the images. We use the boundaries obtained by atlas-based segmentation as the contour for initialization of level set function. Automatic generation of initial contour makes the final segmentation results operator-independent. The proposed approaches are evaluated by comparing automatic and expertpsilas segmentation results and confirming their similarity.
Supply chain is a complex system. The complexity of supply chain can be categorized into two kinds: the complexity of supply chain components as well as the complexity of the supply chain organizations, and both infor...
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Supply chain is a complex system. The complexity of supply chain can be categorized into two kinds: the complexity of supply chain components as well as the complexity of the supply chain organizations, and both information uncertainty with system dynamics are the main reasons that lead to supply chain complexity. Concerning supply chain complexity, we review the related researching approaches in the literature from uncertainty, the measure of supply chain complexity as well as the dynamic analysis of the supply chain (including dynamic games), and give suggestions in the future research.
Shuffled frog leaping (SFL) is a population based, cooperative search metaphor inspired by natural memetics. Its ability of adapting to dynamic environment makes SFL become one of the most important memetic algorithms...
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Shuffled frog leaping (SFL) is a population based, cooperative search metaphor inspired by natural memetics. Its ability of adapting to dynamic environment makes SFL become one of the most important memetic algorithms. In order to improve the algorithmpsilas stability and the ability to search the global optimum, a novel dasiacognition componentpsila is introduced to enhance the effectiveness of the SFL, namely frog not only adjust its position according to the best individual within the memeplex or the global best of population but also according to thinking of the frog itself. To validate the improved SFL (ISFL) method, numerous simulations were conducted to compare SFL and ISFL using six benchmark problems for continuous and discrete optimization. According to the simulation results, adding the cognitive behavior to SFL significantly enhances the performance of SFL in solving the optimization problems, and the improvements are more evident with the scale of the problem increasing.
In this work, we develop an atlas based method for automatic segmentation of white matter fiber bundles. To this end, we propose a new method for registration of diffusion tensor (DT) images using DTI information whic...
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In this work, we develop an atlas based method for automatic segmentation of white matter fiber bundles. To this end, we propose a new method for registration of diffusion tensor (DT) images using DTI information which is also used in the fiber tracking process, and we also propose a strategy for segmenting the fiber bundles using the new registration method and a probabilistic white matter atlas. We apply the registration method to 13 real DTI data sets and evaluate the results by comparing the level of alignment of all fibers. Then, we use the proposed strategy to segment 10 major fiber bundles in one of the subjects. One of the advantages of such a method is the robustness of the results thanks to using prior knowledge. The segmented results can be used for comparing and evaluating other fiber bundle segmentation methods.
A fuzzy logic controller (FLC) is designed to achieve course-keeping for mooring shifting system, which is the main system of non self-propelled vessels. Compared with manual operation, the automatic operation and mon...
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A fuzzy logic controller (FLC) is designed to achieve course-keeping for mooring shifting system, which is the main system of non self-propelled vessels. Compared with manual operation, the automatic operation and monitoring system with the FLC can perform higher precision and efficiency. The particle swarm optimization (PSO) algorithm is introduced to optimize the proposed FLCpsilas parameters. A series of simulation studies have been undertaken to compare the performance of a basis FLC and PSO based FLC. The results demonstrate that the latter has the better controlling quality.
Aero-optic effects cause distortions, including blurring, vibration, deformation and spatial shifting, of the objects in the image obtained by the infra-red sensor. Contributions of this paper are in the following two...
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ISBN:
(纸本)9781424439027
Aero-optic effects cause distortions, including blurring, vibration, deformation and spatial shifting, of the objects in the image obtained by the infra-red sensor. Contributions of this paper are in the following two aspects. First, the correctness of the theoretical point spread function (PSF) representing the aero-optic effects, which had been derived in our previous research, is validated experimentally. Second, in order to restore the aero-optically degraded images, an improved Landweber iteration method is proposed, where, instead of being fixed, the relaxation factor is updated adaptively at each iteration. Experiments have been carried out and results demonstrate that the proposed method introduces improved restoration results with better convergence.
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