Hidden Vector Encryption (HVE) is a special type of predicate encryption that can support conjunctive equality and range searches on encrypted data. All previous HVE schemes were proven to be either selectively secure or weakly attribute-hiding. In this paper, we first construct a new HVE scheme that is fully secure under standard assumptions. Our HVE scheme, which is based on bilinear maps (pa...

The background-oriented schlieren (BOS) technique with the physicsbased optical flow method (OF-BOS) is developed for measuring the pressure field of a laser-induced underwater shock wave. Compared to BOS with the conventional cross-correlation method in PIV (called PIV-BOS), by using the OF-BOS, the displacement field generated by the small density gradient in water can be obtained at the spat...

We introduce a generalized framework for sampling and reconstruction in separable Hilbert spaces. Specifically, we establish that it is always possible to stably reconstruct a vector in an arbitrary Riesz basis from sufficiently many of its samples in any other Riesz basis. This framework can be viewed as an extension of the well-known consistent reconstruction technique (Eldar et al). However,...

In this paper, a host-vector model is considered for a disease without immunity in which the current density of infectious vectors is related to the number of infectious hosts at earlier times. Spatial spread in a region is modelled in the partial integro-differential equation by a diffusion term. For the general model, we first study the stability of the steady states using the contracting-con...

A new technique for three-dimensional (3D) electric-field (e-field) vector measurement is presented. Three laser beams with different propagation paths in an electro-optic (EO) crystal were used to resolve 3D components of e-field vectors. We adopted a special geometric shape of bismuth silicon oxide EO crystal so that the three beams would propagate within it. A sensitivity of 0.6 V/cm square ...

This paper presents two new formulations of multiple-instance learning as a maximum margin problem. The proposed extensions of the Support Vector Machine (SVM) learning approach lead to mixed integer quadratic programs that can be solved heuristically. Our generalization of SVMs makes a state-of-the-art classification technique, including non-linear classification via kernels, available to an a...

Flow visualization in 3D is challenging due to perceptual problems such as occlusion, lack of directional cues, lack of depth cues, and visual complexity. In this paper we present an interaction technique that addresses these special problems for 3D flow visualization. The feature we present, a streamrunner, gives the user interactive control over the evolution of streamlines from the time they...

In this paper we present the first polynomial time deterministic algorithm to compute the shortest path between two vertices of a circulant graph of degree four. Our spectacular algorithm only requires O(logN) bit operations, where N is the number of the vertices and it is based on shortest vector problems in a special class of lattices for L1-norm. Moreover, the technique can be extended to we...

Detection of malignancy from histopathological images of breast cancer is a labor-intensive and error-prone process. To streamline this process, we present an efficient Computer Aided Diagnostic system that can differentiate between cancerous and non-cancerous H&E (hemotoxylin&eosin) biopsy samples. Our system uses novel textural, topological and morphometric features taking advantage of the sp...

Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support Vector Machine (SVM) to solve MIL problem in the region-based Content Based Image Retrieval (CBIR). This is an area where a huge number of image regions are involved. For the sake of efficiency, we adopt a Genetic Alg...