38 resultados para biometric fusion
Resumo:
Recently, it has been shown that fusion of the estimates of a set of sparse recovery algorithms result in an estimate better than the best estimate in the set, especially when the number of measurements is very limited. Though these schemes provide better sparse signal recovery performance, the higher computational requirement makes it less attractive for low latency applications. To alleviate this drawback, in this paper, we develop a progressive fusion based scheme for low latency applications in compressed sensing. In progressive fusion, the estimates of the participating algorithms are fused progressively according to the availability of estimates. The availability of estimates depends on computational complexity of the participating algorithms, in turn on their latency requirement. Unlike the other fusion algorithms, the proposed progressive fusion algorithm provides quick interim results and successive refinements during the fusion process, which is highly desirable in low latency applications. We analyse the developed scheme by providing sufficient conditions for improvement of CS reconstruction quality and show the practical efficacy by numerical experiments using synthetic and real-world data. (C) 2013 Elsevier B.V. All rights reserved.
Resumo:
This article highlights different synthetic strategies for the preparation of colloidal heterostructured nanocrystals, where at least one component of the constituent nanostructure is a semiconductor. Growth of shell material on a core nanocrystal acting as a seed for heterogeneous nucleation of the shell has been discussed. This seeded-growth technique, being one of the most heavily explored mechanisms, has already been discussed in many other excellent review articles. However, here our discussion has been focused differently based on composition (semiconductor@semiconductor, magnet@semiconductor, metal@semiconductor and vice versa), shape anisotropy of the shell growth, and synthetic methodology such as one-step vs. multi-step. The relatively less explored strategy of preparing heterostructures via colloidal sintering of different nanostructures, known as nanocrystal-fusion, has been reviewed here. The ion-exchange strategy, which has recently attracted huge research interest, where compositional tuning of nanocrystals can be achieved by exchanging either the cation or anion of a nanocrystal, has also been discussed. Specifically, controlled partial ion exchange has been critically reviewed as a viable synthetic strategy for the fabrication of heterostructures. Notably, we have also included the very recent methodology of utilizing inorganic ligands for the fabrication of heterostructured colloidal nanocrystals. This unique strategy of inorganic ligands has appeared as a new frontier for the synthesis of heterostructures and is reviewed in detail here for the first time. In all these cases, recent developments have been discussed with greater detail to add upon the existing reviews on this broad topic of semiconductor-based colloidal heterostructured nanocrystals.
Resumo:
Cryosorption pump is the only possible device to pump helium, hydrogen and its isotopes in fusion environment, such as high magnetic field and high plasma temperatures. Activated carbons are known to be the most suitable adsorbent in the development of cryosorption pumps. For this purpose, the data of adsorption characteristics of activated carbons in the temperature range 4.5 K to 77 K are needed, but are not available in the literature. For obtaining the above data, a commercial micro pore analyzer operating at 77 K has been integrated with a two stage GM cryocooler, which enables the cooling of the sample temperature down to 4.5 K. A heat switch mounted between the second stage cold head and the sample chamber helps to raise the sample chamber temperature to 77 K without affecting the performance of the cryocooler. The detailed description of this system is presented elsewhere. This paper presents the results of experimental studies of adsorption isotherms measured on different types of activated carbons in the form of granules, globules, flake knitted and non-woven types in the temperature range 4.5 K to 10 K using Helium gas as the adsorbate. The above results are analyzed to obtain the pore size distributions and surface areas of the activated carbons. The effect of adhesive used for bonding the activated carbons to the panels is also studied. These results will be useful to arrive at the right choice of activated carbon to be used for the development of cryosorption pumps.
Resumo:
This paper proposes an optical flow algorithm by adapting Approximate Nearest Neighbor Fields (ANNF) to obtain a pixel level optical flow between image sequence. Patch similarity based coherency is performed to refine the ANNF maps. Further improvement in mapping between the two images are obtained by fusing bidirectional ANNF maps between pair of images. Thus a highly accurate pixel level flow is obtained between the pair of images. Using pyramidal cost optimization, the pixel level optical flow is further optimized to a sub-pixel level. The proposed approach is evaluated on the middlebury dataset and the performance obtained is comparable with the state of the art approaches. Furthermore, the proposed approach can be used to compute large displacement optical flow as evaluated using MPI Sintel dataset.
Resumo:
This paper studies a pilot-assisted physical layer data fusion technique known as Distributed Co-Phasing (DCP). In this two-phase scheme, the sensors first estimate the channel to the fusion center (FC) using pilots sent by the latter; and then they simultaneously transmit their common data by pre-rotating them by the estimated channel phase, thereby achieving physical layer data fusion. First, by analyzing the symmetric mutual information of the system, it is shown that the use of higher order constellations (HOC) can improve the throughput of DCP compared to the binary signaling considered heretofore. Using an HOC in the DCP setting requires the estimation of the composite DCP channel at the FC for data decoding. To this end, two blind algorithms are proposed: 1) power method, and 2) modified K-means algorithm. The latter algorithm is shown to be computationally efficient and converges significantly faster than the conventional K-means algorithm. Analytical expressions for the probability of error are derived, and it is found that even at moderate to low SNRs, the modified K-means algorithm achieves a probability of error comparable to that achievable with a perfect channel estimate at the FC, while requiring no pilot symbols to be transmitted from the sensor nodes. Also, the problem of signal corruption due to imperfect DCP is investigated, and constellation shaping to minimize the probability of signal corruption is proposed and analyzed. The analysis is validated, and the promising performance of DCP for energy-efficient physical layer data fusion is illustrated, using Monte Carlo simulations.
Resumo:
We propose apractical, feature-level and score-level fusion approach by combining acoustic and estimated articulatory information for both text independent and text dependent speaker verification. From a practical point of view, we study how to improve speaker verification performance by combining dynamic articulatory information with the conventional acoustic features. On text independent speaker verification, we find that concatenating articulatory features obtained from measured speech production data with conventional Mel-frequency cepstral coefficients (MFCCs) improves the performance dramatically. However, since directly measuring articulatory data is not feasible in many real world applications, we also experiment with estimated articulatory features obtained through acoustic-to-articulatory inversion. We explore both feature level and score level fusion methods and find that the overall system performance is significantly enhanced even with estimated articulatory features. Such a performance boost could be due to the inter-speaker variation information embedded in the estimated articulatory features. Since the dynamics of articulation contain important information, we included inverted articulatory trajectories in text dependent speaker verification. We demonstrate that the articulatory constraints introduced by inverted articulatory features help to reject wrong password trials and improve the performance after score level fusion. We evaluate the proposed methods on the X-ray Microbeam database and the RSR 2015 database, respectively, for the aforementioned two tasks. Experimental results show that we achieve more than 15% relative equal error rate reduction for both speaker verification tasks. (C) 2015 Elsevier Ltd. All rights reserved.
Resumo:
Inaccuracies in prediction of circulating viral strain genotypes and the possibility of novel reassortants causing a pandemic outbreak necessitate the development of an anti-influenza vaccine with increased breadth of protection and potential for rapid production and deployment. The hemagglutinin (HA) stem is a promising target for universal influenza vaccine as stem-specific antibodies have the potential to be broadly cross-reactive towards different HA subtypes. Here, we report the design of a bacterially expressed polypeptide that mimics a H5 HA stem by protein minimization to focus the antibody response towards the HA stem. The HA mini-stem folds as a trimer mimicking the HA prefusion conformation. It is resistant to thermal/chemical stress, and it binds to conformation-specific, HA stem-directed broadly neutralizing antibodies with high affinity. Mice vaccinated with the group 1 HA mini-stems are protected from morbidity and mortality against lethal challenge by both group 1 (H5 and H1) and group 2 (H3) influenza viruses, the first report of cross-group protection. Passive transfer of immune serum demonstrates the protection is mediated by stem-specific antibodies. Furthermore, antibodies indudced by these HA stems have broad HA reactivity, yet they do not have antibody-dependent enhancement activity.