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Due to process disturbances and some uncertainties, the process operating performance will deviate from the optimal operating point along with time, so it is very important to develop strategies for online operating performance assessment on optimality. However, a little work has been published in this research area to our knowledge. In this study, a new online operating optimality assessment method...
One-class support vector algorithms such as OCSVM and SVDD have been successfully applied to many One-Class Classification (OCC) problems. Many authors assume that kernels like the ones used in standard binary SVM classification are also appropriate to one-class classification. However, a review of the literature indicated that in general, only the Gaussian RBF kernel gives satisfactory results in...
The task of One-Class Classification (OCC) is to characterise a single class that is well described by the training data and distinguish it from all others; this is in contrast to the more common approach of binary classification or multi-class classification, in which all classes are well described by the training data. One-class support vector machine algorithms such as OCSVM and SVDD have been...
Coarse-Grained Reconfigurable Architecture (CGRAs) are a promising parallel architecture with both high performance and high power-efficiency. Inner loop pipelining and outer loop merging techniques are usually used to improve the execution performance when mapping loops ontoCGRA. However, the number of concurrently executable operators (CEOs) from the kernel still can not make the best of PEs in...
The goal of this study is to explore the advantages of representing natural images with the cortical Layer-4 processing, which is the first step in visual information processing performed by the cerebral cortex of the brain. A cortical module, a macrocolumn, receives input from a small visual field and its Layer 4 performs a nonlinear transform of this input to generate its pluripotent representation...
Polar codes can achieve symmetric capacity of a channel with a simple encoder and a successive cancellation (SC) decoder, both with complexity of the order of O(N log N). Polar codes of length N = ln may have a faster polarization rate compared to polar codes of length N = 2n. In this paper, we introduce a simple and explicit method to obtain the recursive formulas of SC decoder for any polar code...
The assessment of surgical skills is an essential part of medical training. The prevalent manual evaluations by expert surgeons are time consuming and often their outcomes vary substantially from one observer to another. We present a video-based framework for automated evaluation of surgical skills based on the Objective Structured Assessment of Technical Skills (OSATS) criteria. We encode the motion...
We explore the application of Kernel Support Vector Machines (SVM) to the realm of text messages. Our intent is to classify the author of a text message based on usage patterns present in a training set of text messages. We achieve between 57% and 96% accuracy in determining the author of unknown samples.
In this paper, for overlapping community detection, we propose a novel framework of the link-space transformation that transforms a given original graph into a link-space graph. Its unique idea is to consider topological structure and link similarity separately using two distinct types of graphs: the line graph and the original graph. For topological structure, each link of the original graph is mapped...
The large majority of classical and modern estimation techniques assume the data seen at the testing phase of statistical inference come from the same process that generated the training data. In many real-world applications this can be a restrictive assumption. We outline two solutions to overcome this heterogeneity: instance-weighting and dimension reduction. The instance-weighting methods estimate...
Virtual machine introspection, which provides tamperresistant, high-fidelity “out of the box” monitoring of virtual machines, has many prominent security applications including VM-based intrusion detection, malware analysis and memory forensic analysis. However, prior approaches are either intrusive in stopping the world to avoid race conditions between introspection tools and the guest VM, or providing...
The image processing techniques with computer automated object recognization is an emerging area of research in several engineering and biomédical applications. The images created by Synthetic Aperture Radar (SAR) require complex image processing for intelligence extraction. A technique for man made object recognization in SAR created images is presented here. The kernel methods along with machine...
Data mining extracts novel and useful knowledge from large repositories of data and has become an effective analysis and decision means in corporation In many information processing tasks, labels are usually expensive and the unlabeled data points are abundant. To reduce the cost on collecting labels, it is crucial to predict which unlabeled examples are the most informative, i.e., improve the classifier...
We propose a method for recovering the parameters of periodic signals with finite rate of innovation sampled using a raised cosine pulse. We show that the proposed method exhibits the same numerical stability as existing methods of its type, and we investigate the effect of oversampling on the performance of our method in the presence of noise. Our method can also be applied to non-periodic signals...
Many open source projects have long become commercial. This paper shows just how much of open source software development is paid work and how much has remained volunteer work. Using a conservative approach, we find that about 50% of all open source software development has been paid work for many years now and that many small projects are fully paid for by companies. However, we also find that any...
GT5D is a nuclear fusion simulation program which aims to analyze the turbulence phenomena in tokamak plasma. In this research, we optimize it for GPU clusters with multiple GPUs on a node. Based on the profile result of GT5D on a CPU node, we decide to offload the whole of the time development part of the program to GPUs except MPI communication. We achieved 3.37 times faster performance in maximum...
We present a memory-efficient algorithm and its implementation for solving multidimensional numerical integration on a cluster of compute nodes with multiple GPU devices per node. The effective use of shared memory is important for improving the performance on GPUs, because of the bandwidth limitation of the global memory. The best known sequential algorithm for multidimensional numerical integration...
A new shadowed c-means clustering based image segmentation method is proposed in this paper. By including the local spatial information in shadowed c-means algorithm and mapping the original data into a high dimensional space via kernel method, we propose the Kernel Spatial Shadowed C-Means (KSSCM) clustering algorithm for image segmentation problems. The KSSCM based approach shows better performance...
Asset quality is the foundation of enterprise survival and development we choose one-class support vector machine (OCSVM) is chosen to deal with asset quality abnormal detection for it pays great roles to acquire the abnormal data. As well as flexible to be constructed, Biorthogonal wavelet consists linear-phase nature and high vanishing moment, therefore, corresponding wavelet kernel functions are...
Introduction, description the structure and implementation process for WinPcap, then analyzed differences between IPv4 and IPv6 packet header, finally proposed a method to improve the efficiency of capturing packets. Using VC + + 6.0 program experiment implemented IPv6 packets capture and verify that the improved method is efficiency than the traditional method on capture packet.
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