Decomposing Dedekind Numbers: A Polynomial Representation with Powers of 2

In this paper, we reveal an internal structure within Dedekind numbers, demonstrating that they can be expressed as polynomials of powers of 2. This discovery is based on innovative concepts and methods, offering a new perspective on the nature of these numbers

Improved support vector clustering algorithm for color image segmentation

Color image segmentation has attracted more and more attention in various application fields during the past few years. Essentially speaking, color image segmentation problem is a process of clustering according to the color of pixels. But, traditional clustering methods do not scale well with the number of training sample, which limits the ability of handling massive data effectively. With the utilization of an improved approximate Minimum Enclosing Ball algorithm, this article develops an fast support vector clustering algorithm for computing the different clusters of given color images in kernel-introduced space to segment the color images. We prove theoretically that the proposed algorithm converges to the optimum within any given precision quickly. Compared to other popular algorithms, it has the competitive performances both on training time and accuracy. Color image segmentation experiments on both synthetic and real-world data sets demonstrate the validity of the proposed algorithm

Learning user-specific latent influence and susceptibility from information cascades

Predicting cascade dynamics has important implications for understanding information propagation and launching viral marketing. Previous works mainly adopt a pair-wise manner, modeling the propagation probability between pairs of users using n^2 independent parameters for n users. Consequently, these models suffer from severe overfitting problem, specially for pairs of users without direct interactions, limiting their prediction accuracy. Here we propose to model the cascade dynamics by learning two low-dimensional user-specific vectors from observed cascades, capturing their influence and susceptibility respectively. This model requires much less parameters and thus could combat overfitting problem. Moreover, this model could naturally model context-dependent factors like cumulative effect in information propagation. Extensive experiments on synthetic dataset and a large-scale microblogging dataset demonstrate that this model outperforms the existing pair-wise models at predicting cascade dynamics, cascade size, and "who will be retweeted".Comment: from The 29th AAAI Conference on Artificial Intelligence (AAAI-2015

The Bibliometrics Analysis of Customer Knowledge Management Based on Co-Word Analyses

Customer knowledge management (CKM) is a crucial element in the field of knowledge management. By retrieving journal articles with the descriptor words “customer knowledge management” in WOS database, the author selects 3587 journal papers as the research object, then analyses the papers through bibliometrics. Researches show that the research on CKM is in accordance with Place’s curve, which is valuable to study. The focus in the field of CKM is similar at home and abroad, especially some crossing field. Existing research can be divided into three themes: analyzing and mining customer knowledge management from the theory of technology/process, using customer knowledge to manage from the perspective of comprehensive/holism, sharing and interacting knowledge of enterprise both interiorly and exteriorly from the perspective of target/process

A UNIFIED RISK-BENEFIT ANALYSIS FRAMEWORK FOR INVESTIGATING MOBILE PAYMENT ADOPTION

The paper proposes a unified risk-benefit analysis framework for investigating consumers’ adoption of mobile payment technology. Based on perceived risk theory and risk-benefit analysis literature, the proposed framework integrates three variables—perceived risk, perceived benefit and perceived value, to predict consumers’ intention to use mobile payment. All the proposed hypotheses are well supported based on an empirical validation of 336 useful survey samples. The results show that consumers consider both the beneficial and risky aspects of using mobile payment to evaluate the overall desirability (perceived value) of adoption decision. Further, perceived value, together with perceived risk and benefit directly affects consumers’ intention to adopt the technology. Financial risk is found to be the key resource of the risks of using mobile payment. Both theoretical and practical implications are discussed

Improved Ambiguity-Resolving for Virtual Baseline

A novel phase interferometer method based on virtual baseline is proposed for technical difficulty in resolving angle ambiguity and antenna layout. In this method, only two baselines are set to solve the problem of angle ambiguity. In high noise areas, there are large numbers of outliers which lead to angle error in the measured data, and a way to detect and eliminate the outliers is applied to improve the effect of solving ambiguity. The simulation results show that the improved method could effectively correct the error of fuzzy phase difference and increase the probability of ambiguity-resolving. Duo to its simple equipment and easy to implement, the proposed method might have certain guiding significance to engineering application

Positive Solutions of a Fractional Boundary Value Problem with Changing Sign Nonlinearity

We discuss the existence of positive solutions of a boundary value problem of nonlinear fractional differential equation with changing sign nonlinearity. We first derive some properties of the associated Green function and then obtain some results on the existence of positive solutions by means of the Krasnoselskii's fixed point theorem in a cone