Computational performance of a parallelized three-dimensional high-order spectral element toolbox

In this paper, a comprehensive performance review of an MPI-based high-order three-dimensional spectral element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the parallel efficiency. The performance evaluation is analyzed with the help of a time prediction model based on a parameterization of the application and the hardware resources. Two tailor-made benchmark cases in computational fluid dynamics (CFD) are introduced and used to carry out this review, stressing the particular interest for clusters with up to thousands of cores. Some problems in the parallel implementation have been detected and corrected. The theoretical complexities with respect to the number of elements, to the polynomial degree, and to communication needs are correctly reproduced. It is concluded that this type of code has a nearly perfect speedup on machines with thousands of cores, and is ready to make the step to next-generation petaFLOP machines.     

Simulations, models, and testbeds: A mutual catalysis

Recent developments in the area of decentralized and infrastructureless systems opened avenues for novel applications. Along with these new technologies, new questions regarding their operational bounds in terms of e.g. scalability and security arose. Due to the sparse presence of real-world decentralized and infrastructureless systems, new protocols and applications have to be scrutinized by means of simulation, in (small-scale) testbeds, and by analytical models. In this paper, we discuss challenges of evaluating security mechanisms for mobile ad hoc networks and peer-to-peer systems. We focus on harmonizing predictions of analytical models and results obtained from simulation studies and testbed experiments.     

Reducing Protocol Analysis with XOR to the XOR-Free Case in the Horn Theory Based Approach

In the Horn theory based approach for cryptographic protocol analysis, cryptographic protocols and (Dolev?CYao) intruders are modeled by Horn theories and security analysis boils down to solving the derivation problem for Horn theories. This approach and the tools based on this approach, including ProVerif, have been very successful in the automatic analysis of cryptographic protocols. However, dealing with the algebraic properties of operators, such as the exclusive OR (XOR), which are frequently used in cryptographic protocols has been problematic. In particular, ProVerif cannot deal with XOR. In this paper, we show how to reduce the derivation problem for Horn theories with XOR to the XOR-free case. Our reduction works for an expressive class of Horn theories. A large class of intruder capabilities and protocols that employ the XOR operator can be modeled by these theories. Our reduction allows us to carry out protocol analysis using tools, such as ProVerif, that cannot deal with XOR, but are very efficient in the XOR-free case. We implemented our reduction and, in combination with ProVerif, used it for the fully automatic analysis of several protocols that employ the XOR operator. Among others, our analysis revealed a new attack on an IBM security module.     

Prological Language Processing

We describe a Prolog-based approach to the development of language processors (such as preprocessors, frontends, evaluators, tools for software modification and analysis). The design of the corresponding environment Laptob for prological language processing is outlined. Language processor definitions in Laptob are basically Prolog programs. The programs might contain grammars, that is, we consider logic grammars. The programs can be typed, and they can be higher-order. The adaptation and composition of the logic programs themselves is supported by meta-programming. The environment offers tool support for efficient scanning, testing, and application development based on a make-system. We report on recent and ongoing applications of the Prolog-based approach.     

Multigrid methods for discrete elliptic problems on triangular surfaces

We construct and analyze multigrid methods for discretized self-adjoint elliptic problems on triangular surfaces in ${\mathbb{R}^3}$ . The methods involve the same weights for restriction and prolongation as in the case of planar triangulations and therefore are easy to implement. We prove logarithmic bounds of the convergence rates with constants solely depending on the ellipticity, the smoothers and on the regularity of the triangles forming the triangular surface. Our theoretical results are illustrated by numerical computations.     

Visual signatures in video visualization

Video visualization is a computation process that extracts meaningful information from original video data sets and conveys the extracted information to users in appropriate visual representations. This paper presents a broad treatment of the subject, following a typical research pipeline involving concept formulation, system development, a path-finding user study, and a field trial with real application data. In particular, we have conducted a fundamental study on the visualization of motion events in videos. We have, for the first time, deployed flow visualization techniques in video visualization. We have compared the effectiveness of different abstract visual representations of videos. We have conducted a user study to examine whether users are able to learn to recognize visual signatures of motions, and to assist in the evaluation of different visualization techniques. We have applied our understanding and the developed techniques to a set of application video clips. Our study has demonstrated that video visualization is both technically feasible and cost-effective. It has provided the first set of evidence confirming that ordinary users can be accustomed to the visual features depicted in video visualizations, and can learn to recognize visual signatures of a variety of motion events.     

Satisfying customer preferences via mass customization and mass production

Two operational formats namely mass customization and mass production can be implemented to satisfy customer preference-based demand. The mass customization system consists of two stages: the initial build-to-stock phase and the final customize-to-order phase. The mass production system has a single stage: building products with pre-determined specifications to stock. In each case, the company makes decisions on the number of initial product variants, product specifications, production quantities and product pricing. Under a uniform customer preference distribution, the optimal number of base-product variants resembles the well known economic order quantity solution, and the optimal product specifications are equally spaced. We characterize three possible benefits of mass customization: (i) the gained surplus from offering each customer her ideal product; (ii) extra revenue from price discrimination; and (iii) reduced costs due to risk pooling under stochastic demand.     

Removal of bird-contaminated wind profiler data based on neural networks

This paper presents the results of a study that relied on trainable neural network classifiers to identify and remove bird-contaminated data from wind measurements recorded by a 1290-MHz wind profiler. A wind profiler is a Doppler radar system measuring the three-dimensional wind field. Migrating birds crossing the radar beam can lead to erroneous wind observations. Bird removal was performed by training conventional feedforward neural networks (FFNNs) and quantum neural networks (QNNs) to identify and remove bird-contaminated data recorded by a 1290-MHz wind profiler. A series of experiments evaluated several sets of input features extracted from wind profiler data, various FFNNs and QNNs of different sizes, and criteria employed for identifying birds in wind profiler data.