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Security and privacy of computation, and the related concept of (deliberate) sharing, have, historically, largely been afterthoughts. In a traditional multi-user, multi-application web hosting environment, typically applications are public by default. Applications wishing to offer a notion of private resources must take it upon themselves to independently manage authentication and authorization of...
Error Weighted Hashing (EWH) is a fast algorithm for Approximate k-Nearest neighbour search in Hamming space. It is more efficient than traditional LocalitySensitive Hashing algorithm (LSH) since it generates shorterlist of strings for finding the exact distance from the query. Wehave parallelized the EWH algorithm using Cuda and OpenMP.Speedup of 44 times on a 16 core GPU and 16 core CPUmachine was...
This paper proposes a prediction system to make a forecast of temperature which is based on support vector machines. The system uses a database which provides information about weather parameters such as pressure, temperature, wind speed, etc. In order to adapt the input data, the present proposal has applied a pre-processing method before the prediction phases start. The best testing results have...
Playback attack detection (PAD) is essentially a binary classification task which is used to identify the authentic recordings from the playback recordings. For PAD problem, the difference of the acoustic feature between the authentic and playback recordings mainly comes from the recording channel and the ambient noise. Motivated by the excellent performance of the Gaussian Mixture Model-Universal...
Speech emotion recognition has become an active topic in pattern recognition. Specifically, support vector machine (SVM) is an effective classifier due to the application of the nonlinear mapping function, which can map the data into high or ever infinite dimensional feature space. However, a single kernel function might not sufficient to describe the different properties of spontaneous speech emotion...
In this paper, we present a comparative study between Daubechies-DCT approach, Discrete Cosine Transform (DCT) and Histograms of Oriented Gradient (HOG) under different kind of kernel function. We obtain Daubechies-DCT by fusing the DCT features and Daubechies features. The implementation of HOG achieved by dividing the face image into small connected regions, named cells, and for each cell compiling...
Specific crime in the banking system is credit card fraud. Credit card usage has been increased due to the rapid growth of E-commerce techniques. Credit card fraud also increased at the same time. Prevention is better than detection. So the existing system prevented the credit card fraud by identifying fraud in the application of the Credit card. Due to the limitation of the existing system, this...
In this paper we present an automated blood vessel segmentation system algorithm for the retinal images under pathological conditions like Diabetic Retinopathy (DR) using matched filters and supervised classification techniques. Matched filter has been extensively used in the enhancement and segmentation of the retinal blood vessels due to the cross sectional similarity of the vessels to the Gaussian...
Significant feature extraction for texture retrieval can be perfectly achieved using multiscale image decompositions, such as contourlet and Gabor representations. In this paper we compare the efficiency of contourlet decomposition variants and Gabor transform in terms of texture search and retrieval rates. Two distinct approaches, namely energy computation and generalized Gaussian distribution modeling...
RDF databases naturally map to a graph representation and employ languages, such as SPARQL, that implements queries as graph pattern matching routines. Graph methods exhibit an irregular behavior: they present unpredictable, fine-grained data accesses, and are synchronization intensive. Graph data structures expose large amounts of dynamic parallelism, but are difficult to partition without generating...
Support Vector Machines are widely accepted in the field of pattern recognition because of their superiority in performing supervised classification. It is known that all kernel parameters may be used for classification more-or-less precisely (giving rise to vagueness) and also for the same classification problem, there are a number of kernel parameters which give the best accuracy (giving rise to...
Information needs of the users have grown exponentially with the advent of advancements in information and communication technology. The traditional ways of searching information from the online resources has been evolved and the tendency is geared more towards getting quality contents. In healthcare domain, the clinical researchers and physicians are even more interested to find quality information...
As one of the most popular ways for Wi-Fi based indoor localization, the received signal strength (RSS) can provide us localization results with accuracy proportional to the quality of Wi-Fi database collection. In this paper, we collected two Wi-Fi databases using human and robot respectively. The experiments are conducted on the 3rd floor of Atwater Kent laboratory. Based on the two databases, we...
In this paper, we present the results of using bags of system calls for learning the behavior of Linux containers for use in anomaly-detection based intrusion detection system. By using system calls of the containers monitored from the host kernel for anomaly detection, the system does not require any prior knowledge of the container nature, neither does it require altering the container or the host...
Affective computing has become a growing field of research activities due to its wide use of application in human computer interface. Emotion recognition is one of the state-of-the-art techniques in determining current psychological state of human being. Human emotions are very overlapping in nature and thus it needs an efficient feature-extractor and classifier assembly. This paper reports a novel...
Traditional Nonnegative Matrix Factorization (NMF) is a linear and unsupervised algorithm. This would limit the classification power of NMF for the complicated data. To overcome the above limitations of NMF, this paper proposes a novel supervised and nonlinear NMF algorithm based on kernel theory and discriminant analysis. We incorporate the class label information into the decomposition of NMF in...
To improve the accuracy of prediction of sub-cellular location, a new method using kernel linear discriminant analysis with combinational kernel function which is made up of the Gauss kernel function and the polynomial kernel function is used to the predict the sub-cellular location. In order to confirm the reliability of the research, the data used in this paper are from the standard data set included...
In order to show the scientific status of Harbin Engineering University (HEU) in recent five years, the scientific papers published by the staff in HEU in the period of 2008–2012 were extracted out from the SCI database. These papers were processed by the CiteSpaceII software, which is a visual software for Bibliometrics. The kernel researchers, kernel fields, and the kernel institutions and countries...
We consider the problem of searching a collection of graphs D to find graphs that are most similar to a query graph Q. This has several applications in areas like computational biology, drug design, computational chemistry, collaborative networks, social networks etc. We use graphlet kernel to define similarity between graphs. In order to make the similarity search faster, we build an efficient nearest...
In this paper, a hybrid nonlinear adaptive noise canceller (ANC) with single-or multi-reference channels is proposed to perform the task of extracting fetal electrocardiogram (FECG). A Volterra filter and a functional link artificial neural network (FLANN) are equipped in parallel in each reference channel to approximate the linearity and nonlinearity between the maternal ECG (MECG) and its distorted...
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