IST PubRep
Not a member yet
752 research outputs found
Sort by
Liquid surface tracking with error compensation
Get PDFOur work concerns the combination of an Eulerian liquid simulation with a high-resolution surface tracker (e.g. the level set method or a Lagrangian triangle mesh). The naive application of a high-resolution surface tracker to a low-resolution velocity field can produce many visually disturbing physical and topological artifacts that limit their use in practice. We address these problems by defining an error function which compares the current state of the surface tracker to the set of physically valid surface states. By reducing this error with a gradient descent technique, we introduce a novel physics-based surface fairing method. Similarly, by treating this error function as a potential energy, we derive a new surface correction force that mimics the vortex sheet equations. We demonstrate our results with both level set and mesh-based surface trackers
Quantitative reactive modeling and verification
No full textFormal verification aims to improve the quality of software by detecting errors before they do harm. At the basis of formal verification is the logical notion of correctness, which purports to capture whether or not a program behaves as desired. We suggest that the boolean partition of software into correct and incorrect programs falls short of the practical need to assess the behavior of software in a more nuanced fashion against multiple criteria. We therefore propose to introduce quantitative fitness measures for programs, specifically for measuring the function, performance, and robustness of reactive programs such as concurrent processes. This article describes the goals of the ERC Advanced Investigator Project QUAREM. The project aims to build and evaluate a theory of quantitative fitness measures for reactive models. Such a theory must strive to obtain quantitative generalizations of the paradigms that have been success stories in qualitative reactive modeling, such as compositionality, property-preserving abstraction and abstraction refinement, model checking, and synthesis. The theory will be evaluated not only in the context of software and hardware engineering, but also in the context of systems biology. In particular, we will use the quantitative reactive models and fitness measures developed in this project for testing hypotheses about the mechanisms behind data from biological experiments
Digital signatures with minimal overhead from indifferentiable random invertible functions
Get PDFIn a digital signature scheme with message recovery, rather than transmitting the message m and its signature σ, a single enhanced signature τ is transmitted. The verifier is able to recover m from τ and at the same time verify its authenticity. The two most important parameters of such a scheme are its security and overhead |τ| − |m|. A simple argument shows that for any scheme with “n bits security” |τ| − |m| ≥ n, i.e., the overhead is lower bounded by the security parameter n. Currently, the best known constructions in the random oracle model are far from this lower bound requiring an overhead of n + logq h , where q h is the number of queries to the random oracle. In this paper we give a construction which basically matches the n bit lower bound. We propose a simple digital signature scheme with n + o(logq h ) bits overhead, where q h denotes the number of random oracle queries. Our construction works in two steps. First, we propose a signature scheme with message recovery having optimal overhead in a new ideal model, the random invertible function model. Second, we show that a four-round Feistel network with random oracles as round functions is tightly “public-indifferentiable” from a random invertible function. At the core of our indifferentiability proof is an almost tight upper bound for the expected number of edges of the densest “small” subgraph of a random Cayley graph, which may be of independent interest
A Nestin-cre transgenic mouse is insufficient for recombination in early embryonic neural progenitors
No full textNestin-cre transgenic mice have been widely used to direct recombination to neural stem cells (NSCs) and intermediate neural progenitor cells (NPCs). Here we report that a readily utilized, and the only commercially available, Nestin-cre line is insufficient for directing recombination in early embryonic NSCs and NPCs. Analysis of recombination efficiency in multiple cre-dependent reporters and a genetic mosaic line revealed consistent temporal and spatial patterns of recombination in NSCs and NPCs. For comparison we utilized a knock-in Emx1cre line and found robust recombination in NSCs and NPCs in ventricular and subventricular zones of the cerebral cortices as early as embryonic day 12.5. In addition we found that the rate of Nestin-cre driven recombination only reaches sufficiently high levels in NSCs and NPCs during late embryonic and early postnatal periods. These findings are important when commercially available cre lines are considered for directing recombination to embryonic NSCs and NPCs
Controlling Liquids Using Meshes
Get PDFWe present an approach for artist-directed animation of liquids using multiple levels of control over the simulation, ranging from the overall tracking of desired shapes to highly detailed secondary effects such as dripping streams, separating sheets of fluid, surface waves and ripples. The first portion of our technique is a volume preserving morph that allows the animator to produce a plausible fluid-like motion from a sparse set of control meshes. By rasterizing the resulting control meshes onto the simulation grid, the mesh velocities act as boundary conditions during the projection step of the fluid simulation. We can then blend this motion together with uncontrolled fluid velocities to achieve a more relaxed control over the fluid that captures natural inertial effects. Our method can produce highly detailed liquid surfaces with control over sub-grid details by using a mesh-based surface tracker on top of a coarse grid-based fluid simulation. We can create ripples and waves on the fluid surface attracting the surface mesh to the control mesh with spring-like forces and also by running a wave simulation over the surface mesh. Our video results demonstrate how our control scheme can be used to create animated characters and shapes that are made of water
Message authentication, revisited
Get PDFTraditionally, symmetric-key message authentication codes (MACs) are easily built from pseudorandom functions (PRFs). In this work we propose a wide variety of other approaches to building efficient MACs, without going through a PRF first. In particular, unlike deterministic PRF-based MACs, where each message has a unique valid tag, we give a number of probabilistic MAC constructions from various other primitives/assumptions. Our main results are summarized as follows: We show several new probabilistic MAC constructions from a variety of general assumptions, including CCA-secure encryption, Hash Proof Systems and key-homomorphic weak PRFs. By instantiating these frameworks under concrete number theoretic assumptions, we get several schemes which are more efficient than just using a state-of-the-art PRF instantiation under the corresponding assumption. For probabilistic MACs, unlike deterministic ones, unforgeability against a chosen message attack (uf-cma ) alone does not imply security if the adversary can additionally make verification queries (uf-cmva ). We give an efficient generic transformation from any uf-cma secure MAC which is "message-hiding" into a uf-cmva secure MAC. This resolves the main open problem of Kiltz et al. from Eurocrypt'11; By using our transformation on their constructions, we get the first efficient MACs from the LPN assumption. While all our new MAC constructions immediately give efficient actively secure, two-round symmetric-key identification schemes, we also show a very simple, three-round actively secure identification protocol from any weak PRF. In particular, the resulting protocol is much more efficient than the trivial approach of building a regular PRF from a weak PRF. © 2012 International Association for Cryptologic Research
Commitments and efficient zero knowledge proofs from learning parity with noise
Get PDFWe construct a perfectly binding string commitment scheme whose security is based on the learning parity with noise (LPN) assumption, or equivalently, the hardness of decoding random linear codes. Our scheme not only allows for a simple and efficient zero-knowledge proof of knowledge for committed values (essentially a Σ-protocol), but also for such proofs showing any kind of relation amongst committed values, i.e. proving that messages m_0,...,m_u, are such that m_0=C(m_1,...,m_u) for any circuit C. To get soundness which is exponentially small in a security parameter t, and when the zero-knowledge property relies on the LPN problem with secrets of length l, our 3 round protocol has communication complexity O(t|C|l log(l)) and computational complexity of O(t|C|l) bit operations. The hidden constants are small, and the computation consists mostly of computing inner products of bit-vectors
Approximating marginals using discrete energy minimization
No full textWe consider the problem of inference in a graphical model with binary variables. While in theory it is arguably preferable to compute marginal probabilities, in practice researchers often use MAP inference due to the availability of efficient discrete optimization algorithms. We bridge the gap between the two approaches by introducing the Discrete Marginals technique in which approximate marginals are obtained by minimizing an objective function with unary and pairwise terms over a discretized domain. This allows the use of techniques originally developed for MAP-MRF inference and learning. We explore two ways to set up the objective function - by discretizing the Bethe free energy and by learning it from training data. Experimental results show that for certain types of graphs a learned function can outperform the Bethe approximation. We also establish a link between the Bethe free energy and submodular functions
Tracking surfaces with evolving topology
Get PDFWe present a method for recovering a temporally coherent, deforming triangle mesh with arbitrarily changing topology from an incoherent sequence of static closed surfaces. We solve this problem using the surface geometry alone, without any prior information like surface templates or velocity fields. Our system combines a proven strategy for triangle mesh improvement, a robust multi-resolution non-rigid registration routine, and a reliable technique for changing surface mesh topology. We also introduce a novel topological constraint enforcement algorithm to ensure that the output and input always have similar topology. We apply our technique to a series of diverse input data from video reconstructions, physics simulations, and artistic morphs. The structured output of our algorithm allows us to efficiently track information like colors and displacement maps, recover velocity information, and solve PDEs on the mesh as a post process