Fuzzy Case-Based Reasoning in Product Style Acquisition Incorporating Valence-Arousal-Based Emotional Cellular Model

Emotional cellular (EC), proposed in our previous works, is a kind of semantic cell that contains kernel and shell and the kernel is formalized by a triple- L = <P, d, δ>, where P denotes a typical set of positive examples relative to word-L, d is a pseudodistance measure on emotional two-dimensional space: valence-arousal, and δ is a probability density function on positive real number field. The basic idea of EC model is to assume that the neighborhood radius of each semantic concept is uncertain, and this uncertainty will be measured by one-dimensional density function δ. In this paper, product form features were evaluated by using ECs and to establish the product style database, fuzzy case based reasoning (FCBR) model under a defined similarity measurement based on fuzzy nearest neighbors (FNN) incorporating EC was applied to extract product styles. A mathematical formalized inference system for product style was also proposed, and it also includes uncertainty measurement tool emotional cellular. A case study of style acquisition of mobile phones illustrated the effectiveness of the proposed methodology

Penalty-based Methods for Simple Bilevel Optimization under H\"{o}lderian Error Bounds

This paper investigates simple bilevel optimization problems where the upper-level objective minimizes a composite convex function over the optimal solutions of a composite convex lower-level problem. Existing methods for such problems either only guarantee asymptotic convergence, have slow sublinear rates, or require strong assumptions. To address these challenges, we develop a novel penalty-based approach that employs the accelerated proximal gradient (APG) method. Under an $\alpha$-H\"{o}lderian error bound condition on the lower-level objective, our algorithm attains an $(\epsilon,l_F^{-\beta}\epsilon^{\beta})$-optimal solution for any $\beta>0$ within $\mathcal{O}\left(\sqrt{\frac{L_{f_1}}{\epsilon }}\right)+\mathcal{O}\left(\sqrt{\frac{l_F^{\max\{\alpha,\beta\}}L_{g_1}}{\epsilon^{\max\{\alpha,\beta\}}}}\right)$ iterations, where $l_F$, $L_{f_1}$ and $L_{g_1}$ denote the Lipschitz constants of the upper-level objective, the gradients of the smooth parts of the upper- and lower-level objectives, respectively. If the smooth part of the upper-level objective is strongly convex, the result improves further. We also establish the complexity results when both upper- and lower-level objectives are general convex nonsmooth functions. Numerical experiments demonstrate the effectiveness of our algorithms

Effect of source tampering in the security of quantum cryptography

The security of source has become an increasingly important issue in quantum cryptography. Based on the framework of measurement-device-independent quantum-key-distribution (MDI-QKD), the source becomes the only region exploitable by a potential eavesdropper (Eve). Phase randomization is a cornerstone assumption in most discrete-variable (DV-) quantum communication protocols (e.g., QKD, quantum coin tossing, weak coherent state blind quantum computing, and so on), and the violation of such an assumption is thus fatal to the security of those protocols. In this paper, we show a simple quantum hacking strategy, with commercial and homemade pulsed lasers, by Eve that allows her to actively tamper with the source and violate such an assumption, without leaving a trace afterwards. Furthermore, our attack may also be valid for continuous-variable (CV-) QKD, which is another main class of QKD protocol, since, excepting the phase random assumption, other parameters (e.g., intensity) could also be changed, which directly determine the security of CV-QKD.Comment: 9 pages, 6 figure