A Simple Discretization of the Vector Dirichlet Energy

We present a simple and concise discretization of the covariant derivative vector Dirichlet energy for triangle meshes in 3D using Crouzeix-Raviart finite elements. The discretization is based on linear discontinuous Galerkin elements, and is simple to implement, without compromising on quality: there are two degrees of freedom for each mesh edge, and the sparse Dirichlet energy matrix can be constructed in a single pass over all triangles using a short formula that only depends on the edge lengths, reminiscent of the scalar cotangent Laplacian. Our vector Dirichlet energy discretization can be used in a variety of applications, such as the calculation of Killing fields, parallel transport of vectors, and smooth vector field design. Experiments suggest convergence and suitability for applications similar to other discretizations of the vector Dirichlet energy.     

Utilizing digital traces of mobile phones for understanding social dynamics in urban areas

Understanding land use in urban areas, from the perspective of social function, is beneficial for a variety of fields, including urban and highway planning     

GYO reductions,canonical connections,tree and cyclic schemas,and tree projections

Database schemas may be partitioned into two subclasses: three schemas and cyclic schemas. The analysis of tree vs . cyclic schemas introduced the concepts of GYO reductions, canonical connections, and tree projections. This paper investigates the intricate relationships among these concepts in the context of universal relation databases.     

Auditory nerve representation as a front-end for speech recognition in a noisy environment

We describe here a computational model based upon the temporal characteristics of the information in the auditory nerve-fiber firing patterns. The model produces a frequency domain representation of the input signal in terms of the ensemble histogram of the inverse of the interspike intervals, measured from firing patterns generated by a simulated nerve-fiber array. The nerve-fiber mechanism is modeled by a multi-level-crossing detector at the output of each cochlear filter. We use 85 cochlear filters, equally spaced on a log-frequency scale from 200 Hz to 3200 Hz, and the level crossings are measured at positive threshold levels which are uniformly distributed in log scale. The resulting Ensemble Interval Histogram (EIH) pseudo spectrum shares two main properties: (1) fine spectral details are well preserved in the low-frequency region but become fuzzy at the high-frequency end; (2) the EIH spectrum is more robust in noise, compared with the traditional Fourier spectrum. This representation of the speech has been used as a front-end to a Dynamic Time Warping (DTW), speaker-dependent, isolated word recognizer. The database consisted of a 39-word alpha-digits vocabulary spoken by two male and two female speakers, in different levels of additive white noise. In the noise-free case, the performance of the EIH-based front-end is comparable to a conventional Fourier Transform (FFT)-based front-end. In the presence of noise, however, the EIH-based front-end is more robust. Compared with the FFT-based front-end, with increasing noise the recognition scores drop more slowly, the resulting gap increases as the SNR values decreases. Quantitatively, with the EIH-based front-end the recognizer achieves a given recognition score with global-SNR values which are between 5 dB and 15 dB lower.     

How to construct constant-round zero-knowledge proof systems for NP

Constant-round zero-knowledge proof systems for every language in are presented, assuming the existence of a collection of claw-free functions. In particular, it follows that such proof systems exist assuming the intractability of either the Discrete Logarithm Problem or the Factoring Problem for Blum integers.     

Novel gelatin–alginate surgical sealants loaded with hemostatic agents

Surgical sealants are an integral part of the surgical toolbox. They are used mainly to seal tissues or suture lines. In the current research, we examined a novel surgical sealant based on the natural polymers gelatin and alginate, crosslinked with carbodiimide and loaded with hemostatic agents. Incorporation of the hemostatic agent montmorillonite significantly improved the ex vivo burst strength and the other physical properties (swelling ratio, weight loss, curing time, and viscosity) of the basic surgical sealant, due to the formation of nanocomposite structure. This novel system presents a new approach for improving the physical properties of surgical sealants.     

Scheduling directives: Accelerating shared-memory many-core processor execution

We consider many-core processors with a task-graph oriented programming model, whereby scheduling constraints among tasks are decided offline, and are then enforced by the runtime system using dedicated hardware. Here, exposing and beneficially exploiting fine grain data and control parallelism is increasingly important. Therefore, high expressive power for stating such constraints/directives, along with the ability to implement them in fast, simple hardware, is critical for success. In this paper, we focus on the relationship among different duplicable (multi-instance) tasks, which are used to express and exploit data parallelism. We extend the conventional Start-After-Complete (precedence) constraint to also be usable between replicas of different such tasks rather than only between entire tasks, thereby increasing the exposable parallelism. Additionally, we propose the parameterized Start-After-Start constraint, which can be used to control the degree of “lockstep” among multiple such tasks, e.g., in order to improve cache performance when the tasks work on the same data. Also, we briefly describe several additional interesting directives. Finally, we show that the directives can be supported efficiently in hardware. Hypercore, a very efficient CREW PRAM-like shared-cache architecture, which is very challenging because it has extremely fast dispatching for basic constraints, is used in the discussion. However, the new directives have broader applicability. Having shown the possibility of simple implementation and indications of benefit, this motivates further exploration of these directives and their implementation in hardware, as well as their support by programming tools.     

On multigrid-CG for efficient topology optimization

This article presents a computational approach that facilitates the efficient solution of 3-D structural topology optimization problems on a standard PC. Computing time associated with solving the nested analysis problem is reduced significantly in comparison to other existing approaches. The cost reduction is obtained by exploiting specific characteristics of a multigrid preconditioned conjugate gradients (MGCG) solver. In particular, the number of MGCG iterations is reduced by relating it to the geometric parameters of the problem. At the same time, accurate outcome of the optimization process is ensured by linking the required accuracy of the design sensitivities to the progress of optimization. The applicability of the proposed procedure is demonstrated on several 2-D and 3-D examples involving up to hundreds of thousands of degrees of freedom. Implemented in MATLAB, the MGCG-based program solves 3-D topology optimization problems in a matter of minutes. This paves the way for efficient implementations in computational environments that do not enjoy the benefits of high performance computing, such as applications on mobile devices and plug-ins for modeling software.     

Computing reachable states for nonlinear biological models

In this paper, we describe reachability computation for continuous and hybrid systems and its potential contribution to the process of building and debugging biological models. We summarize the state-of-the-art for linear systems and then develop a novel algorithm for computing reachable states for nonlinear systems. We report experimental results obtained using a prototype implementation applied to several biological models. We believe these results constitute a promising contribution to the analysis of complex models of biological systems.     

On reducing computational effort in topology optimization: how far can we go?

An approximate approach to solving the nested analysis equations in topology optimization is proposed. The procedure consists of only one matrix factorization for the whole design process and a small number of iterative corrections for each design cycle. The approach is tested on 3D topology optimization problems. It is shown that the computational cost can be reduced by one order of magnitude without affecting the outcome of the optimization process.