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Detecting interesting patterns in data has been a focus of recent work in knowledge discovery. Understanding the patterns of interaction between attributes is relevant to many fields. Existing measures of interestingness do not adequately detect these interaction patterns. Here we present a new measure that explores the interactions to be found in data. We combine this interestingness measure with...
Secure scalar product protocol is an important fundamental protocol in secure multi-party computation. Serving as a basic building block for many other secure protocols, it is widely used in data mining, statistical analysis and scientific computation. Based on additive homomorphism public key cryptosystem, we develop a new secure scalar product protocol under semi-honest model with low communication...
Representation and similarity measure of time series is the research basic of the time-series data mining. This paper uses ESAX (extended symbolic aggregate approximation) representing the time series similarly and raises an improved time series method of similarity measure ESSVS (ESAX statistical vector space) based on the statistics symbolic vector space method. ESSVS measure the time series similarity...
In the present work, an effort has been made to propose and implement a new steganographic technique for images by modifying existing algorithms. This technique uses LSB steganography as the basis and randomly disperses the secret message over the entire image to ensure that the secret message cannot be obtained easily from the image. Detailed visual and statistical analysis of the algorithm reveals...
Otsu adaptive thresholding is widely used in classic image segmentation. Two-dimensional Otsu thresholding algorithm is regarded as an effective improvement of the original Otsu method. To reduce the high computational complexity of 2D Otsu method, a fast algorithm is proposed based on improved histogram. Two-dimensional histogram is projected onto the diagonal, which forms 1D histogram with obvious...
The statistical mechanical interpretation of algorithmic information theory (AIT, for short) was introduced and developed by our former works [K. Tadaki, Local Proceedings of CiE 2008, pp. 425-434, 2008] and [K. Tadaki, Proceedings of LFCS'09, Springer's LNCS, vol. 5407, pp. 422-440, 2009], where we introduced the notion of thermodynamic quantities, such as partition function Z(T), free energy F (T),...
The purpose of this paper is to improve allocation of the number of bits without skipping the frame by accurately estimating the target bits in H.264/AVC rate control. In our scheme, we propose an enhancement method of the target frame rate based H.264/AVC bit allocation. The enhancement uses a frame complexity estimation to improve the existing mean absolute difference (MAD) complexity measurement...
To ensure the QoS in Internet services, it is critical to detect the failures quickly and accurately. However, it is a difficult problem because one must extract and interpret fail patterns from large amounts of high-dimensional data. Presently, most technologies do not fit for large-scale system because of the complexity. Moreover, the detecting accuracy of them is relatively low. In this paper,...
Most of the real data often comes in a mixed format (discrete or continuous), however many supervised induction algorithms require discrete data. Quality discretization of continuous attributes is an important problem that has effects on accuracy, complexity, variance and understandability of the induction models. Most of the existing discretization methods, partition the attribute range into two...
In this paper, we make use of the result of word frequency statistics design a new dictionary construction and propose an improved FMM algorithm which based on analysis the principle and characteristics of traditional FMM algorithm. Through the time complexity analysis and experimental comparison, the improved FMM algorithm can further improve the efficiency of the Chinese word segmentation.
We offer a theoretical validation of the curse of dimensionality in the pivot based indexing of datasets for similarity search, by proving, in the framework of statistical learning, that in high dimensions no pivot based indexing scheme can essentially outperform the linear scan. A study of the asymptotic performance of pivot based indexing schemes is performed on a sequence of datasets modeled as...
Due to the exponential growth of information on the Web, Recommender Systems have been developed to generate suggestions to help users overcome information overload and sift through huge amounts of information efficiently. Many existing approaches to recommender systems can neither handle very large datasets nor easily deal with users who have made very few ratings. Moreover, traditional recommender...
Traditional software metrics have the limitations for large-scale software system, so we construct the static structure model for large-scale software by structural mapping and visualization, propose a integrated metrics set based on complex networks parameters according to the perspective of software engineering. The feasibility and validity of the metrics were testified through statistical analyzing...
The high peak-to-average power ratio (PAPR) of the transmit signal is considered to be one of the major drawback of OFDM (orthogonal frequency division multiplexing) systems. The peak transmitted power can be substantially larger than that of a single carrier system. PTS (partial transmit sequence) can improve the peak-to-average power ratio (PAPR) statistics of an OFDM signal. In this paper, we have...
The adoption of XACML as the standard for specifying access control policies for various applications, especially Web services is vastly increasing. A policy evaluation engine can easily become a bottleneck when enforcing large policies. In this paper we propose an adaptive approach for XACML policy optimization. We proposed a clustering technique that categorizes policies and rules within a policy...
The careless illegally copied contents have been rising serious social problem as Internet and multimedia technologies are developing. Therefore, effective and efficient copy detection techniques are required for content management and rights protection. In this paper, we propose a content-based hierarchical video copy detection method that estimates similarity using statistical characteristics between...
Summary form only given. Visual categorization, recognition, and detection of objects has been an area of active research in the vision community for decades. Ultimately, the goal is to recognize and detect a large number of object classes in images within an acceptable time frame. This problem entangles three highly interconnected issues: the internal object representation which should expand sublinearly...
This paper proposes a novel bit-level combining scheme based on Dempster-Shafer (D-S) evidence theory, termed DS combining, for multiple-input multiple-output (MIMO) systems with hybrid-automatic-retransmission-request (HARQ) mechanism. The DS combining is assisted by the proposed DS detection for performance improvement. The focal-element-set (FES) characterizes the uncertainty contained in the decision...
Fast and accurate block-based motion estimation (BME) is desired in many video coding systems. By conducting block matching in lower dimensional projection space, followed by candidate exclusion through thresholding, projection-based BME (PBME) methods can run several times faster than the exhaustive full search method, with little loss in accuracy. In PBME methods, the appropriate choice of threshold...
We represent that the relevant information in a supervised scenario is contained in the projected kernel PCA components if the kernel is sufficiently smooth. This behavior complements the common statistical learning theoretical view on kernel based learning adding insight on the intricate interplay of data and kernel. Thus, kernels do not only transform data sets such that good generalization can...
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