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In order to improve the accuracy of multi-moving objects detection in surveillant video, this paper presents a new method of detection and segmentation for moving objects based on SVM (support vector machine). To further enhance the accuracy of segmentation using support vector machine, we modify the kernel function based on its nature, and some experiments have been done to compare with other kernel...
During analog circuit synthesis in nanometer technology, process variability analysis is mandatory during design space exploration. This would ensure that the circuit will function as per specifications after fabrication even with impact of statistical variations in nanometer regimes. The methodology necessitates the evaluation of performance metrics of an analog circuit for different sizing instances...
A new approach to classification of non-stationary power signals based on adaptive wavelet has been considered. This paper proposes a model for non-stationary power signal disturbance classification using adaptive wavelet networks (AWN). A AWN is a combination of two sub-networks consisting of a wavelet layer and adaptive probabilistic network. The AWN has the capability of automatic adjustment of...
At its simplest, volume calculation of MR Image segmented & further soft computed to estimate the affected intensity of Alzheimer's disease is dealt with this paper. It is concerned with Voxel Based Morphometry to render the first part segmentation. The result gives an active region which further needs an estimation to justify the diagnosis. As in this case the image is in form of voxels. When...
In this paper we propose is an extension of kernel k-means clustering algorithm for symbolic interval data with aggregated kernel functions. To evaluate this method, experiments with synthetic interval data set was performed and we have been compared our method with a dynamic clustering algorithm with single adaptive distance. The evaluation is based on an external cluster validity index (corrected...
Recent work in the field of machine translation (MT) evaluation suggests that sentence level evaluation based on machine learning (ML) can outperform the standard metrics such as BLEU, ROUGE and METEOR. We conducted a comprehensive empirical study on support vector methods for ML-based MT evaluation involving multi-class support vector machines (SVM) and support vector regression (SVR) with different...
When simulating mixed-signal systems, designers are often dissatisfied either with performance or accuracy. A state-space based precomputation method for analog circuits at electrical level allows for a considerably faster simulation than with SPICE-like simulators. Utilizing an automatically generated SystemC interface, our simulation kernel analyzes mixed analog/digital circuits where the digital...
Classification is a widely used mechanism for facilitating Web service discovery. Existing methods for automatic Web service classification only consider the case where the category set is small. When the category set is big, the conventional classification methods usually require a large sample collection, which is hardly available in real world settings. This paper presents a novel method to conduct...
Aimed at the research on freeway detection algorithm has great significance for improving efficiency and effectiveness of freeway traffic management, this paper based on the freeway traffic flow's characteristics, in accordance with the incident detection's basic principle, researches on freeway incident detection based on Support Vector Machine (SVM). This paper designs four different simulation...
This article describes logical analysis infrastructure of associative tables (matrices), which enables to perform processing the interaction of the input vector with n-dimensional algebra-logical space, specified by using the ordered and structured tables of problem-oriented data, which represent the associative behavioral models of logical objects. To estimate the interaction of vectors in algebra-logical...
The web is a crucial source of information nowadays. At the same time, web applications become more and more complex. Therefore, a spontaneous increase in the number of visitors, e.g., based on news reports or events, easily brings a web server in an overload situation. In contrast to the classical model of distributed denial of service (DDoS) attacks, such a so-called flash effect situation is not...
The widely-used Universal Serial Bus (USB) exposes a physical attack vector which has received comparatively little attention in the past. While most research on device driver vulnerabilities concentrated on wireless protocols, we show that USB device drivers provide the same potential for vulnerabilities but offer a larger attack surface resulting from the universal nature of the USB protocol. To...
This paper describes a novel fast mean shift algorithm based on a resampling technique with marked regular pyramid structure. This new method focuses on solving the problem of high calculation complexity when high data dimension or large data sets are involved in mean shift. By resampling the original image with marked regular pyramid structure, improved method reduces the number of pixels requiring...
Multi-class classifier is usually constructed by means of combining the outputs of several binary ones, according to an error correcting output code (ECOC) scheme. In the paper, within the framework of ECOC, we analyse of the ECOC of kernel machines originally proposed before. Then we present the generalization bounds of the ECOC of kernel machines according to the results of stability and generalization...
Many new broadband, emerging applications such as high definition 3D video streaming or on-line gaming are going to be part of the future home. Current home networks are still not capable to cope with the tight requirements asked by these kind of applications. Moreover, many underlying wired and wireless transmission technologies are available, but no solution to reach a convergent framework is available...
We propose a sparse probabilistic learning approach for nonlinear channel equalization in wireless communication systems, by using the relevant vector machine (RVM) technique. In particular, we propose two versions of the RVM based equalizer: 1) maximum a posterior RVM (MAP-RVM), 2) marginalized RVM (MRVM). Compared to the standard support vector machine (SVM) method, the proposed RVM approach not...
The phenomenal success of social networking sites, such as Facebook, Twitter and LinkedIn, has revolutionized the way people communicate. This paradigm has attracted the attention of researchers that wish to study the corresponding social and technological problems. Link recommendation is a critical task that not only helps increase the linkage inside the network and also improves the user experience...
We propose a web clustering method using social bookmarking data with dimension reduction regarding similarity. To realize this idea we construct the similarity matrix between web pages based on their cooccurrence frequency. Since the similarity matrix includes various kind of noise, we map the similarity matrix onto lower dimension feature space to reduce the noise. Especially we carry out dimension...
This paper shows that a program using a time-predictable memory system for data storage can achieve a similar worst-case execution time (WCET) to the average-case execution time (ACET) using a conventional heuristic-based memory system including a data cache. This result is useful within any embedded system where time-predictability and performance are both important, particularly hard real-time systems...
Due to the heterogeneous multi-core architecture of the CellBE processor, the existing MPI implementation cannot effectively exert the SPE computing capability. In this paper, we design and implement a multi-node MPI programming and running environment for CellBE processor. The MPI communication library prototype, which mainly includes the basic point-to-point communication and the multicast communication...
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