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Partial Least Squares are introduced to build the response surface for multi-collinearity problems, which can effectively work on the problems of small sized samples and multiple correlations. However, this approach is a linear method, which is not capable to deal with the non-linear response surface model. To solve this problem, in this paper, we propose two improved algorithms called Local Partial...
This article presents the GPU parallelization of new algorithms SD and DPD types for molecular dynamics systems developed by the Molecular Dynamics Group, University of Groningen, the Netherlands. One should note that molecular dynamics simulations are time-consuming simulations of systems, running time ranging from days to weeks and months. Therefore parallelization is a key issue for the well-running...
Due to outstanding performance deriving from superior value offered for customers, enterprise should focus on constantly nurturing and enhancing the capabilities of customer value creation. Firstly, the paper defined implication and structure of customer value creation capability system. Secondly, the mechanism model and integration framework of customer value creation capacity promotion were proposed...
Almost every computer user has encountered an un-responsive system failure or system hang, which leaves the user no choice but to power off the computer. In this paper, the causes of such failures are analyzed in detail and one empirical hypothesis for detecting system hang is proposed. This hypothesis exploits a small set of system performance metrics provided by the OS itself, thereby avoiding modifying...
Capturing behavior of malware is one of the essential prerequisites for dynamic malware analysis. In this paper, we study and design a system called Osiris, which makes use of virtual machine technique to capture malware behavior. In particularly, we monitor Windows API calls invoked by the process under analysis (or target program) to rebuild its behaviors. The monitor is implemented at the virtual...
LWRM was a method for defeating TCG TOCTOU attacks with less overhead during the normal system execution. However, its security capability was evaluated only through experiments. The uncertainty in real experiments may hide the design-level errors. In this paper we explore applying model checking based formal verification techniques to verify whether LWRM can achieve the declared security properties...
In this article, we focus on the design of an agent-based P2P system for egeoconscious' image retrieval. This system constitutes intelligent agents on the structured P2P framework PIAX (P2P Interactive Agent extension), which is especially enhanced for location-oriented services. In our design, a cluster agent manages the geometric area for image agents as a Voronoi region. We show some results from...
E-learning Learning Evaluation using Principal Component Analysis (PCA) and support vector machine (SVM) is proposed in this paper. In the first step, PCA is employed for dimension reduction and in the second, SVM is employed for classification purpose, resulting in PCA-SVM hybrid model. Experimental results have verified the effectiveness and rationality of the proposed methods.
In order to overcome the problem that it is difficult for support vector machine to deal with uncertain information system, fuzzy theory and rough set are introduced to get two uncertain support vector machines, which are fuzzy support vector machine and fuzzy rough support vector machine respectively. And the principle of these two uncertain methods reducing the effect of uncertain information is...
Proximity-based fuzzy c-means algorithm (P-FCM), a classical semi-supervised clustering algorithm, concerns with the number of proximity “hints” or constraints that specify an extent to which some pairs of instances are considered similar or. By replacing the fuzzy c-means in P-FCM with a kernel fuzzy c-means, this paper proposes a new semi-supervised clustering algorithm named proximity-based kernel...
Before matching the video frames in Scale-Invariant Feature Transform (SIFT) algorithm, the key-points must be extracted firstly. If the size and characteristic of input images are changed, gray threshold of key-points must be reinstalled, to avoid extremely computation cost or failure in registration. In this paper, a self-adaptive SIFT key-points extraction algorithm for video images is developed...
In many practical problems, it is sometimes necessary to evaluate the derivative of function whose values are given approximately. In this paper, we consider the problem of estimating the derivative of a function observed with error. We present a proper regularization strategy and explain how to choose regularization parameter. In the end some numerical examples will further illustrate that this method...
Stealth rootkits that hide themselves on victim systems pose a major threat to computer systems, they are usually evasive as they use sophisticated stealth technologies to conceal files, processes, kernel modules, and other types of objects. Making it extremely difficult to detect their presences in victim system. This paper mainly focuses on rootkits of windows operating system, explores the various...
In this paper, a nearest neighbor rule is applied to the clustering method based on one-class support vector machines. Although the traditional clustering method inspired the k-means clustering employs the kernel-based one-class support vector machines in improving the clustering performance, it forms the coarse decision boundaries. So this paper uses a nearest neighbor rule to establishing the better...
The overall objective of the network security situation assessment is to establish security situation assessment system. This system can unify the large-scale network. First, it provides a security policy unified the whole network. It also provides the techniques for wide-area situation assessment. At the same time this system provides situational awareness and decision support tools for the implementation...
Kernel methods play important roles in machine learning algorithms such as support vector machines. However, how to construct a suitable kernel remains difficult. Recently Ye et al proposed a new kind of kernel function named Chebyshev kernel based on orthogonal Chebyshev polynomials. But in fact the features of the nonlinear mapping determined by Chebyshev kernel are not orthogonal to each other...
An improved algorithm was proposed to overcome the shortcomings of the existing conformal predictor algorithm that was not suitable for linearly inseparable data and did not use the information of distant points. First, the geodesic-distance was introduced into the new algorithm to reflect the implied geometry of the data, thus, the algorithm could take advantage of the information of the distant...
In the field of computer vision, image matching is very important in many applications, such as the object recognition, 3D reconstruction, stereo vision, motion tracking and augmented reality. A method of improving the Opensurf algorithm used in AR for decreasing matching points and mismatch and increasing the calculation speed is proposed.
In this paper, the boundedness for the multilinear commutators generated by $\theta$-type Calder\'{o}n-Zygmund operator with Lipschitz function is discussed, and we conclude that it is bounded on Herz-Hardy spaces.
Multiple points fault in the rotary machinery induce complex vibration signatures, which have the tendency to mislead the fault diagnostic models. One of the challenging problems in machine fault diagnosis is to model and study fault signatures dynamics in case of multiple points fault. The existing literature lacks in the study of multiple points fault and the associated vibration signatures. In...
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