FAST: acceleration from theory to practice

Fast acceleration of symbolic transition systems (Fast) is a tool for the analysis of systems manipulating unbounded integer variables. We check safety properties by computing the reachability set of the system under study. Even if this reachability set is not necessarily recursive, we use innovative techniques, namely symbolic representation, acceleration and circuit selection, to increase convergence. Fast has proved to perform very well on case studies. This paper describes the tool, from the underlying theory to the architecture choices. Finally, Fast capabilities are compared with those of other tools. A range of case studies from the literature is investigated. This paper is mainly based on results presented at CAV 2003, TACAS 2004 and ATVA 2005.     

Snap-stabilization and PIF in tree networks

The contribution of this paper is threefold. First, we present the paradigm of snap-stabilization. A snap- stabilizing protocol guarantees that, starting from an arbitrary system configuration, the protocol always behaves according to its specification. So, a snap-stabilizing protocol is a time optimal self-stabilizing protocol (because it stabilizes in 0 rounds). Second, we propose a new Propagation of Information with Feedback (PIF) cycle, called Propagation of Information with Feedback and Cleaning (). We show three different implementations of this new PIF. The first one is a basic cycle which is inherently snap-stabilizing. However, the first PIF cycle can be delayed O(h ²) rounds (where h is the height of the tree) due to some undesirable local states. The second algorithm improves the worst delay of the basic algorithm from O(h ²) to 1 round. The state requirement for the above two algorithms is 3 states per processor, except for the root and leaf processors that use only 2 states. Also, they work on oriented trees. We then propose a third snap-stabilizing PIF algorithm on un-oriented tree networks. The state requirement of the third algorithm depends on the degree of the processors, and the delay is at most h rounds. Next, we analyze the maximum waiting time before a PIF cycle can be initiated whether the PIF cycle is infinitely and sequentially repeated or launch as an isolated PIF cycle. The analysis is made for both oriented and un-oriented trees. We show or conjecture that the two best of the above algorithms produce optimal waiting time. Finally, we compute the minimal number of states the processors require to implement a single PIF cycle, and show that both algorithms for oriented trees are also (in addition to being time optimal) optimal in terms of the number of states. WARNING: The concept of snap-stabilization was first introduced in [12]. The concept evolved over the last eight years. We take this evolution in consideration in this paper, which includes the early results published in [10] and [12]. In particular, infinite repetition of computation cycles is a requirement of self-stabilizing systems. This is not required in snap-stabilization because snap-stabilization ensures that the first completed computation cycle is executed according to the specification of the problem. The correctness proofs conform to this basic property.     

A local approach to concept generation

Generating concepts defined by a binary relation between a set of properties and a set of objects is one of the important current problems encountered in Data Mining and Knowledge Discovery in Databases. We present a new algorithmic process which computes all the concepts, without requiring an exponential-size data structure, and with a good worst-time complexity analysis, which makes it competitive with the best existing algorithms for this problem. Our algorithm can be used to compute the edges of the lattice as well at no extra cost.      

On the use of analytical expressions for the voltage distribution to analyze intracellular recordings

Different analytical expressions for the membrane potential distribution of membranes subject to synaptic noise have been proposed and can be very helpful in analyzing experimental data. However, all of these expressions are either approximations or limit cases, and it is not clear how they compare and which expression should be used in a given situation. In this note, we provide a comparison of the different approximations available, with an aim of delineating which expression is most suitable for analyzing experimental data.     

Experimental evaluation of intrinsic and nonstationary ultrasonic Doppler spectral broadening in steady and pulsatile flow loop models

Intrinsic and nonstationary Doppler spectral broadening, and the skewness of the spectral representation, were evaluated experimentally using porcine red cell suspensions as ultrasonic scatterers. Theoretically, the relative Doppler bandwidth, defined as the intrinsic bandwidth divided by the mean Doppler frequency shift, should be velocity independent. The relative Doppler bandwidth invariance theorem was experimentally verified with an in vitro steady laminar blood flow model. It is shown that the relative bandwidth is both independent of the flow velocity and blood hematocrit. Using a pulsatile laminar flow model, the authors demonstrated that the relative Doppler bandwidth invariance theorem did not hold during flow acceleration and deceleration. In addition, a positive skewness of the Doppler spectra was observed during acceleration while a negative skewness was measured during the deceleration of blood. The effect of the window duration used in the Fourier spectral computation, on nonstationary broadening, is characterized.     

An empirical analysis of the determinants of 3G adoption in China

The main aim of this study is to examine the factors that affect Chinese consumers’ intention to adopt 3G. This study has extended the Technology Acceptance Model (TAM) by incorporating the determinants of perceived usefulness, cost, trust, and demographic profiles of Chinese consumers. Data is collected from Chinese consumers via self-administered questionnaire. Structural equation modeling was applied to examine the research model proposed. Our result showed that social influence, service quality and perceived ease of use have a direct and significant relationship with perceived usefulness of 3G, and this in turn affects the consumers’ decision to adopt 3G. Contrary to existing TAM research, perceived ease of use was not found to have a direct and significant influence with Chinese consumers’ intention to adopt 3G. Our study also revealed that those with higher educational level are more likely to adopt 3G. Based on the findings, this research is able to propose several practical recommendations to 3G providers in China, such as enhancing the variety of services provided through collaborations with mobile software and content developers. Furthermore, 3G providers can focus on promoting 3G through services such as “Friends and Family” packages as Chinese consumers’ 3G adoption decisions is influenced by their social network. In terms of theoretical contributions, this study has answered many calls from past researchers to investigate the determinants of perceived usefulness. This research was also conducted in China, which is one of the largest telecommunication markets in the world.     

Reducing aliasing in images: a PDE-based diffusion revisited

In this paper, we introduce a new diffusion algorithm that can be used for reducing aliasing on both step edges and lines. It derives from the diffusion model of Perona and Malik, and works as an adaptive level-curve method in which diffusion is carried out in the normal direction of the gradient for step edges, while the eigenvalues of the Hessian matrix are used for lines. To get sharp images, we use high-pass filters to preserve as much as possible the high frequency content while diffusing. Experimental tests using grayscale and colour images show that our algorithm efficiently reduces aliasing.     

Effective discrepancy and numerical experiments

Many problems require the computation of a high dimensional integral, typically with a few tens of input factors, with a low number of integrand evaluations. To avoid the curse of dimensionality, we reduce the dimension before applying the Quasi-Monte Carlo method. We will show how to reduce the dimension by computing approximate Sobol indices of the variables with a two-levels fractional factorial design. Then, we will use the Sobol indices to define the effective discrepancy, which turns out to be correlated with the QMC error and thus enables one to choose a good sequence for the integral estimation.     

A tunable support vector machine assembly classifier for epileptic seizure detection

Automating the detection of epileptic seizures could reduce the significant human resources necessary for the care of patients suffering from intractable epilepsy and offer improved solutions for closed-loop therapeutic devices such as implantable electrical stimulation systems. While numerous detection algorithms have been published, an effective detector in the clinical setting remains elusive. There are significant challenges facing seizure detection algorithms. The epilepsy EEG morphology can vary widely among the patient population. EEG recordings from the same patient can change over time. EEG recordings can be contaminated with artifacts that often resemble epileptic seizure activity. In order for an epileptic seizure detector to be successful, it must be able to adapt to these different challenges. In this study, a novel detector is proposed based on a support vector machine assembly classifier (SVMA). The SVMA consists of a group of SVMs each trained with a different set of weights between the seizure and non-seizure data and the user can selectively control the output of the SVMA classifier. The algorithm can improve the detection performance compared to traditional methods by providing an effective tuning strategy for specific patients. The proposed algorithm also demonstrates a clear advantage over threshold tuning. When compared with the detection performances reported by other studies using the publicly available epilepsy dataset hosted by the University of BONN, the proposed SVMA detector achieved the best total accuracy of 98.72%. These results demonstrate the efficacy of the proposed SVMA detector and its potential in the clinical setting.     

Stereoelective polymerization of β-butyrolactone

Racemic β-butyrolactone was polymerized using chiral initiators obtained from the reaction of organometallic derivatives (ZnEt₂, CdMe₂, AlEt₃) with R(−) 3,3 dimethyl-1,2 butanediol. With the zinc initiator, R(+) enantiomer is preferentially incorporated in the polymer chain with a stereoelectivity ratio r_R equal to 1.6. Crude polymer was fractionated into a crystalline, predominantly isotactic, part and an amorphous heterotactic part, both optically active. Sites of different stereospecificities, present in the initiator, are all active for the stereoelective polymerization. With the cadmium initiator, S(−) enantiomer is preferentially polymerized (r_s = 1.01), extending homosteric-antisteric rules previously established for thiiranes. Aluminium initiator leads to an homosteric process (r_R = 1.1). Chiroptical properties (o.r.d. and c.d.) of polymers prepared with zinc initiator show a predominance of R-configurational units, indicating that ring-opening occurs by O-acyl cleavage with retention of configuration.