On the complexity of computing determinants

We present new baby steps/giant steps algorithms of asymptotically fast running time for dense matrix problems. Our algorithms compute the determinant, characteristic polynomial, Frobenius normal form and Smith normal form of a dense n × n matrix A with integer entries in and bit operations; here denotes the largest entry in absolute value and the exponent adjustment by +o(1) captures additional factors for positive real constants C₁, C₂, C₃. The bit complexity results from using the classical cubic matrix multiplication algorithm. Our algorithms are randomized, and we can certify that the output is the determinant of A in a Las Vegas fashion. The second category of problems deals with the setting where the matrix A has elements from an abstract commutative ring, that is, when no divisions in the domain of entries are possible. We present algorithms that deterministically compute the determinant, characteristic polynomial and adjoint of A with n^3.2+o(1) and O(n^2.697263) ring additions, subtractions and multiplications.To B. David Saunders on the occasion of his 60th birthday     

Detection of linear features in synthetic-aperture radar images by use of the localized Radon transform and prior information

A new linear-features detection method is proposed for extracting straight edges and lines in synthetic-aperture radar images. This method is based on the localized Radon transform, which produces geometrical integrals along straight lines. In the transformed domain, linear features have a specific signature: They appear as strongly contrasted structures, which are easier to extract with the conventional ratio edge detector. The proposed method is dedicated to applications such as geographical map updating for which prior information (approximate length and orientation of features) is available. Experimental results show the method's robustness with respect to poor radiometric contrast and hidden parts and its complementarity to conventional pixel-by-pixel approaches.     

Optimization of an ultra low-phase noise sapphire--SiGe HBT oscillator using nonlinear CAD

In this paper, the electrical and noise performances of a 0.8 /spl mu/m silicon germanium (SiGe) transistor optimized for the design of low phase-noise circuits are described. A nonlinear model developed for the transistor and its use for the design of a low-phase noise C band sapphire resonator oscillator are also reported. The best measured phase noise (at ambient temperature) is -138 dBc/Hz at 1 kHz offset from a 4.85 GHz carrier frequency, with a loaded Q/sub L/ factor of 75,000.     

Noninvasive vascular elastography: theoretical framework

Changes in vessel wall elasticity may be indicative of vessel pathologies. It is known, for example, that the presence of plaque stiffens the vascular wall, and that the heterogeneity of its composition may lead to plaque rupture and thrombosis. Another domain of application where ultrasound elastography may be of interest is the study of vascular wall elasticity to predict the risk of aneurysmal tissue rupture. In this paper, this technology is introduced as an approach to noninvasively characterize superficial arteries. In such a case, a linear array ultrasound transducer is applied on the skin over the region of interest, and the arterial tissue is dilated by the normal cardiac pulsation. The elastograms, the equivalent elasticity images, are computed from the assessment of the vascular tissue motion. Investigating the forward problem, it is shown that motion parameters might be difficult to interpret; that is because tissue motion occurs radially within the vessel wall while the ultrasound beam propagates axially. As a consequence of that, the elastograms are subjected to hardening and softening artefacts, which are to be counteracted. In this paper, the Von Mises (VM) coefficient is proposed as a new parameter to circumvent such mechanical artefacts and to appropriately characterize the vessel wall. Regarding the motion assessment, the Lagrangian estimator was used; that is because it provides the full two-dimensional strain tensor necessary to compute the VM coefficient. The theoretical model was validated with biomechanical simulations of the vascular wall properties. The results allow believing in the potential of the method to differentiate hard plaques and lipid pools from normal vascular tissue. Potential in vivo implementation of noninvasive vascular elastography to characterize abdominal aneurysms and superficial arteries such as the femoral and the carotid is discussed.     

Signal-Processing Electronics for a Capacitive Micro-Sensor

An interface circuit in a 0.8-m CMOS process for the on-chip integration of a capacitive micro-sensor used as a microphone is presented. In order to circumvent 1/f noise contributions and to improve the signal/noise ratio, a synchronous modulation-demodulation technique has been applied. For the implementation of this technique, we have studied and designed several functional block, such as modulator with signal conversion, low-noise amplifier, demodulator, etc. To deal with problems related to dispersions of intrinsic capacitance of the sensor, a feedback compensating solution is suggested. The designed circuit has a sensibility of 1200 V/pF, with a minimum detectable capacitance variation of 2 10^-6 pF.1 – 43 bd du 11 Novembre 1918|–     

Improved second-order bounds for prediction with expert advice

This work studies external regret in sequential prediction games with both positive and negative payoffs. External regret measures the difference between the payoff obtained by the forecasting strategy and the payoff of the best action. In this setting, we derive new and sharper regret bounds for the well-known exponentially weighted average forecaster and for a second forecaster with a different multiplicative update rule. Our analysis has two main advantages: first, no preliminary knowledge about the payoff sequence is needed, not even its range; second, our bounds are expressed in terms of sums of squared payoffs, replacing larger first-order quantities appearing in previous bounds. In addition, our most refined bounds have the natural and desirable property of being stable under rescalings and general translations of the payoff sequence. Editor: Avrim Blum An extended abstract appeared in the Proceedings of the 18th Annual Conference on Learning Theory, Springer, 2005. The work of all authors was supported in part by the IST Programme of the European Community, under the PASCAL Network of Excellence, IST-2002-506778. The work was done while Yishay Mansour was a fellow in the Institute of Advance studies, Hebrew University. His work was also supported by a grant no. 1079/04 from the Israel Science Foundation and an IBM faculty award.     

Accelerated testing of biological stain growth on external concrete walls. Part 1: Development of the growth tests

The development of biological stains has a great influence on the durability of building materials. For common concrete structures, the main and most rapid disorder linked with this development is aesthetic. In recent years, architects have been increasingly using formwork surfaces for external walls, so the search for aesthetic quality and durability has become as important as the search for mechanical quality and durability. Hence, there is a demand from industry for the qualification of concrete wall surface behaviour toward biological growths. This paper aims to itemize the various biological stains affecting concrete and to put forward two accelerated tests for the growth of algae, the organisms responsible for the first visible stains. These tests enable a wall surface to be qualified with respect to biological stains.     

Ultrastructural and cytochemical study of cell wall modification by lactoferrin,lactoferricin and penicillin G against Staphylococcus aureus

To investigate the effect of lactoferrin or lactoferricin with or without penicillin G, light and transmission electron microscopy were performed on thin sections of two Staphylococcus aureus strains. Lactoferrin affected the ultrastructure of S. aureus and groups of undivided cells were observed after lactoferrin treatment with or without penicillin G. These results suggest that lactoferrin can affect staphylococcal cell separation and therefore prevent dissemination of daughter cells from spreading infection. After treatment with lactoferrin, S. aureus cells were less covered (P<0.05) with wheatgerm agglutinin labelled with gold, thus suggesting that lactoferrin affected the synthesis of peptidoglycan and/or the binding to N-acetyl-beta-D-glucosamine. Lactoferricin with or without penicillin G induced the lysis of many bacteria, formation of mesosomal structures and modifications of cell wall. Lactating female CD-1 mice were infected by intramammary delivery of a penicillin-resistant S. aureus strain and were then randomly assigned to treatments according to a 2 x 2 factorial design. Electron microscopy examination showed that 2 days of systemic treatments with lactoferrin affected the morphology and aggregation of S. aureus. In conclusion, lactoferrin and lactoferricin affect S. aureus morphology which may facilitate its killing by penicillin G.     

Forecasting electricity consumption by aggregating specialized experts

We consider the setting of sequential prediction of arbitrary sequences based on specialized experts. We first provide a review of the relevant literature and present two theoretical contributions: a general analysis of the specialist aggregation rule of Freund et al. (Proceedings of the Twenty-Ninth Annual ACM Symposium on the Theory of Computing (STOC), pp. 334–343, 1997) and an adaptation of fixed-share rules of Herbster and Warmuth (Mach. Learn. 32:151–178, 1998) in this setting. We then apply these rules to the sequential short-term (one-day-ahead) forecasting of electricity consumption; to do so, we consider two data sets, a Slovakian one and a French one, respectively concerned with hourly and half-hourly predictions. We follow a general methodology to perform the stated empirical studies and detail in particular tuning issues of the learning parameters. The introduced aggregation rules demonstrate an improved accuracy on the data sets at hand; the improvements lie in a reduced mean squared error but also in a more robust behavior with respect to large occasional errors.     

An LMI approach to dencentralized H8 control

We consider the design of a decentralized controller for a linear time invariant (LTI) system. This system is modelled as an interconnection of subsystems. For every subsystem, a linear time invariant controller is sought such that the overall closed loop system is stable and achieves a given H performance level. The main idea is to design every local controller such that the corresponding closed loop subsystem has a certain input-output (dissipative) property. This local property is constrained to be consistent with the overall objective of stability and performance. The local controllers are designed simultaneously, avoiding the traditional iterative process: both objectives (the local one and the global one) are achieved in one shot. Applying this idea leads us to solving the following new problem: given an LTI system, parameterize all the dissipative properties which can be achieved by feedback. The proposed approach leads to solving convex optimization problems that involve linear matrix inequality constraints.