We construct a relative Chow-Künneth decomposition for a conic bundle over a surface such that the middle projector gives the Prym variety of the associated double covering of the discriminant of the conic bundle. This gives a refinement (up to an isogeny) of Beauville’s theorem on the relation between the intermediate Jacobian of the conic bundle and the Prym variety of the double covering.

This paper presents a Complete Orthogonal Image discriminant (COID) method and its application to biometric face recognition. The novelty of the COID method comes from 1) the derivation of two kinds of image discriminant features, image regular and image irregular, in the feature extraction stage and 2) the development of the Complete OID (COID) featuresbased on the fusion of the two kinds of i...

The proposed approach leads to analyzing the associations between a set of quantitative variables and several qualitative variables measured on a same set of individuals. In a decision-making context, the proposed method can be considered as a generalization of discriminant analysis to the multiple groups’ variables case. It’s described as a principal component analysis of the centres of gravit...

The embedding of a torus into an inner form PGL2 defines adelic toric period. A general version Duke’s theorem states that this period equidistributes as the discriminant splitting field tends to infinity. In paper we consider embedded diagonally two distinct forms PGL2. Assuming Generalized Riemann Hypothesis (and some additional technical assumptions), show simultaneous equidistribution infin...

Descriptive document clustering aims at discovering clusters of semantically interrelated documents together with meaningful labels to summarise the content of each document cluster. In this work, we propose a novel descriptive clustering framework, referred to as CEDL. It relies on the formulation and generation of two types of heterogeneous objects, that correspond to documents and candidate ...

Reversible data hiding continues to attract significant attention in recent years. In particular, an increasing number of authors focus on the higher bit (HSB) plane image which can yield more redundant space. On other hand, lower planes are often ignored for embedding existing schemes due their harm rate. This paper proposes efficient reversible scheme via a double-peak two-layer (DTLE) strate...

Dimensionality reduction is often recommended to handle high dimensional data before performing the tasks of visualization and classification. So far, large families of dimensionality reduction methods besides the supervised or the unsupervised, the linear or the nonlinear, the global or the local have been developed. In this paper, a maximum nonparametric margin projection (MNMP) method is put...

Two-dimensional local graph embedding discriminant analysis (2DLGEDA) and two-dimensional discriminant locality preserving projections (2DDLPP) were recently proposed to directly extract features form 2D face matrices to improve the performance of two-dimensional locality preserving projections (2DLPP). But all of them require a high computational cost and the learned transform matrices lack di...

A novel adaptive steganographic scheme for spatial image is proposed. A noisy function is used to measure texture complexity of 2 × 2 pixel blocks, which keeps monotonic increasing after ±1 modifications. Therefore, the message is embedded into the noisiest areas and the recipient can identify the embedding region. The ‘double-layered embedding’ is exploited to reduce the number of ±1 modificat...