Proteomics is defined as the large-scale characterization of protein sets expressed in a cell or tissue. Lately, proteomics has been broadly using two-dimensional gel electrophoresis for its analysis. It consists of m...
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Proteomics is defined as the large-scale characterization of protein sets expressed in a cell or tissue. Lately, proteomics has been broadly using two-dimensional gel electrophoresis for its analysis. It consists of migration and separation of molecules, placed in a gel, according to the strength of an electric field. In order to see these proteins, it is necessary to use some kind of reagent of revelation, which ends up resulting in a two-dimensional profile of spots. Afterwards, this gel is scanned and produces an image, and then this image may be analyzed. Usually, there is noise in this kind of image. Thinking on it, this work presents a technique using Fuzzy Logics to find spots.
This paper deals with surface normal estimation from calibrated stereo images. We show here how the affine transformation between two projections defines the surface normal of a 3D planar patch. We give a formula that...
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ISBN:
(纸本)9789897580918
This paper deals with surface normal estimation from calibrated stereo images. We show here how the affine transformation between two projections defines the surface normal of a 3D planar patch. We give a formula that describes the relationship of surface normals, camera projections, and affine transformations. This formula is general since it works for every kind of cameras. We propose novel methods for estimating the normal of a surface patch if the affine transformation is known between two perspective images. We show here that the normal vector can be optimally estimated if the projective depth of the patch is known. Other non-optimal methods are also introduced for the problem. The proposed methods are tested both on synthesized data and images of real-world 3D objects.
In general, mechanical designers have to manually select assembly tolerance types and values in product design. To reduce the uncertainty in manufacturing process, solve the problem of effectively sharing and smoothly...
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ISBN:
(纸本)9781467371902
In general, mechanical designers have to manually select assembly tolerance types and values in product design. To reduce the uncertainty in manufacturing process, solve the problem of effectively sharing and smoothly exchange tolerance information among heterogeneous CAD system. On the optimization of tolerance synthesis with an ontology-based approach is proposed, automatically generated the tolerance type, variations of tolerance, cost function and tolerance value. Firstly, ontology contains abundant semantic knowledge and semantic structure. Secondly, the Web Ontology Language (OWL) is used to define the concepts of tolerance synthesis, and Semantic Web Rule Language (SWRL) is used to define the constraint conditions and distribute experience. Thirdly, based on the genetic algorithm, a tolerance values optimization model is established with manufacturing cost functions and assembly stack-up constraint. Finally, the effectiveness of the proposed approach is illustrated by using a practical example of the gear case.
Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrot...
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A shape matching dynamics (SMD) is a robust and efficient elastic model based on geometric constraints. This article introduces our study [1] that adopts SMD to visual simulation of cardiac beating motion. In our tech...
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Diagnosis of mild Traumatic Brain Injury (mTBI) is difficult due to the variability of obvious brain lesions using imaging scans. A promising tool for exploring potential biomarkers for mTBI is magnetoencephalography ...
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ISBN:
(纸本)9781509018185
Diagnosis of mild Traumatic Brain Injury (mTBI) is difficult due to the variability of obvious brain lesions using imaging scans. A promising tool for exploring potential biomarkers for mTBI is magnetoencephalography which has the advantage of high spatial and temporal resolution. By adopting proper analytic tools from the field of symbolic dynamics like Lempel-Ziv complexity, we can objectively characterize neural network alterations compared to healthy control by enumerating the different patterns of a symbolic sequence. This procedure oversimplifies the rich information of brain activity captured via MEG. For that reason, we adopted neural-gas algorithm which can transform a time series into more than two symbols by learning brain dynamics with a small reconstructed error. The proposed analysis was applied to recordings of 30 mTBI patients and 50 normal controls in δ frequency band. Our results demonstrated that mTBI patients could be separated from normal controls with more than 97% classification accuracy based on high complexity regions corresponding to right frontal areas. In addition, a reverse relation between complexity and transition rate was demonstrated for both groups. These findings indicate that symbolic complexity could have a significant predictive value in the development of reliable biomarkers to help with the early detection of mTBI.
Traditional computer portrait caricature system mainly take the method that exaggerate and deform real images directly, that lead the facial image background also been deformed when exaggerate facial image. If in pret...
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Texture is a very important concept for many image understanding and pattern classification applications. The analysis of texture can be performed by the multi-channel filtering theory, a classical theory for texture ...
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In this paper,an irregular displacement-based lensless wide-field microscopy imaging platform is presented by combining digital in-line holography and computational pixel super-resolution using multi-frame *** samples...
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In this paper,an irregular displacement-based lensless wide-field microscopy imaging platform is presented by combining digital in-line holography and computational pixel super-resolution using multi-frame *** samples are illuminated by a nearly coherent illumination system,where the hologram shadows are projected into a complementary metal-oxide semiconductor-based imaging *** increase the resolution,a multi-frame pixel resolution approach is employed to produce a single holographic image from multiple frame observations of the scene,with small planar *** are resolved by a hybrid approach:(i)alignment of the LR images by a fast feature-based registration method,and(ii)fine adjustment of the sub-pixel information using a continuous optimization approach designed to find the global optimum *** method for phase-retrieval is applied to decode the signal and reconstruct the morphological details of the analyzed *** presented approach was evaluated with various biological samples including sperm and platelets,whose dimensions are in the order of a few *** obtained results demonstrate a spatial resolution of 1.55 μm on a field-of-view of<30 mm^(2).
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