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Variety in Big Data means we have a wide range of data types and sources: e.g. File systems and database systems co-exist for decades as two popular data-accessing interfaces. This work is to unify these two interfaces by presenting a Data Interface All-iN-A-place (DIANA). The first challenge lies in distinguishing structured and un-structured data and diverting them to different underlying platforms...
We extracted adaptive univariate and multivariate dynamic models of cerebral hemodynamics during resting and hypercapnic conditions using a Recursive Least Squares estimation scheme with multiple adaptive forgetting factors. The time dependent relationship between mean arterial blood pressure (MABP), end-tidal CO2 tension (PETCO2) and middle cerebral artery blood flow velocity (CBFV) was assessed...
System identification modeling is an essential precondition and foundation for the analysis, design and intelligent control of control system. Theory and method of identification modeling for rehabilitation training system for stroke patients' lower limbs based on support vector regression are mainly researched in this paper. In addition, simulated test is carried out to verify such method, based...
In classification with Support Vector Machines, only Mercer kernels, i.e. valid kernels, such as the Gaussian RBF kernel, are widely accepted and thus suitable for clinical data. Practitioners would also like to use the sigmoid kernel, a non-Mercer kernel, but its range of validity is difficult to determine, and even within range its validity is in dispute. Despite these shortcomings the sigmoid kernel...
Performance of software is increasingly restricted by the Memory Wall instead of CPU. Many studies focus on alleviating the DRAM latency by improving the row-buffer hit rate. But most of them treat the Kernel and User equally. Data used by Operating System and User applications spread in different rows of the same bank, leading to the contentions for the row-buffer when they access the bank successively...
In hyperspectral imagery, there exist homogeneous regions where neighboring pixels tend to belong to the same class with high probability. However, even though neighboring pixels are from the same material, their spectral characteristics may be different due to various factors, such as internal instrument noise or atmospheric scattering, which results in misclassification. In this work, the proposed...
Phase Change Memory (PCM) has been considered as a leading candidate to replace the traditional DRAM in embedded systems due to its promising characteristics such as low leakage power, low cost, non-volatility, and high scalability. One of the constraints that undermine the credential of PCM as main memory is its limited write endurance. In this paper, we develop wear-leveling techniques purely on...
Q-Gaussian function has the extensive scope of application compared with Gaussian function. It can become many different radial basis functions when we choice the different parameters. Q-Gaussian is chose as kernel to establish the financial early warning model of listing Corporation in this paper. Through the contrast of the Fisher model based on Gaussian kernel, polynomial kernel and the linear...
Community detection in inhomogeneous structured network is an attractive research problem that searches for methods to discover groups in which individuals are more densely interconnected with each other with higher probability of internal information propagation. While most of the previous approaches attempt to divide networks into communities according to the algorithm results of network or edge...
No matter the end-effector control of joint robots or the pose control of mobile robots, the image feature detection is the critical component of these robot technologies. Moreover, the interest point is the most widely used feedback signal in visual servo control, which performances are directly effected by the actual execution time of the feature detection methods. However, in the robot visual servo...
This paper proposes a definition and a solution of the problem of finding a hyper cavity as a data-free hyper sphere of maximum radius. This problem is formulated here as a multiextremal problem under constraints in a linear feature space and in a linear space produced by a kernel function. In accordance with the proposed approach, just as in the one-class SVM, the center of the hyper sphere is sought...
In this paper, we present a hyper graph kernel computed using substructure isomorphism tests. Measuring the isomorphisms between hyper graphs straightforwardly tends to be elusive since a hyper graph may exhibit varying relational orders. We thus transform a hyper graph into a directed line graph. This not only accurately reflects the multiple relationships exhibited by the hyper graph but is also...
The potential and feasibility of applying the knowledge of supervised learning methods to Chinese traditional painting classification is discussed and evaluated. Data bases of different artists and categories are collected, from which numerical features are extracted describing paintings' color, texture and other characteristic. Two classification approaches aiming to school and artist classification...
For a given data set, exploring their multi-view instances under a clustering framework is a practical way to boost the clustering performance. This is because that each view might reflect partial information for the existing data. Furthermore, due to the noise and other impact factors, exploring these instances from different views will enhance the mining of the real structure and feature information...
This paper presents a novel structural approach to quantitatively characterising nuclear chromatin texture in light microscope images of Pap smears. The approach is based on segmenting the chromatin into blob-like primitives and characterising their properties and arrangement. The segmentation approach makes use of multiple focal planes. It comprises two basic steps: (i) mean-shift filtering in the...
In this paper, the formulation of multi-dimensional Cauchy integral equation, which is in an integral form of Maxwell's equations, is presented on Clifford algebra to increase the accuracy of numerical solutions. The advantage of this formulation is the kernel integral concerning without the strongly singular function. To obtain the solution of the Cauchy integral equation, the boundary element technique...
Cyber-physical systems (CPS) must perform complex algorithms at very high speed to monitor and control complex real-world phenomena. GPU, with a large number of cores and extremely high parallel processing, promises better computation if the data parallelism often found in real-world scenarios of CPS could be exploited. Nevertheless, its performance is limited by the latency incurred when data are...
In this paper, we propose to apply the nonparallel support vector machine (NPSVM) for positive and unlabeled learning problem(PU learning problem) in which only a small positive examples and a large unlabeled examples can be used. Like Biased-SVM, NPSVM treats the unlabeled set as the negative set with noise, while NPSVM is modified so that, the first primal problem is constructed such that all the...
Electromagnetic scattering by perfect electrically conducting (PEC) objects in a layered medium is studied in this paper. The layered medium Green's function is adopted as the kernel of the electric field integral equation (EFIE) so that the effects from the multilayered background can be accounted for automatically. However, the spectrum of the EFIE with this kernel, is unfortunately undesirable...
Cross-media retrieval is a challenging problem in multimedia retrieval area. In the real-world, many applications involve multi-modal data, e.g., web pages containing both images and texts. How to utilize the intrinsic intra-modality and inter-modality similarity to learn the appropriate relationships of the data objects and provide efficient search across different modalities is the core of cross-media...
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